﻿FN Clarivate Analytics Web of Science
VR 1.0
PT J
AU Gunderson, AR
   Siegel, J
   Leal, M
AF Gunderson, Alex R.
   Siegel, Jeremy
   Leal, Manuel
TI Tests of the contribution of acclimation to geographic variation in
   water loss rates of the West Indian lizard <i>Anolis cristatellus</i>
SO JOURNAL OF COMPARATIVE PHYSIOLOGY B-BIOCHEMICAL SYSTEMS AND
   ENVIRONMENTAL PHYSIOLOGY
LA English
DT Article
DE Acclimation; Climate; Desiccation; Adaptive radiation; Geographic
   variation; Anolis cristatellus; Puerto Rico
ID BRITISH-VIRGIN-ISLANDS; PHENOTYPIC PLASTICITY; INSULAR POPULATIONS;
   TEMPERATURE REGULATION; HUMIDITY ACCLIMATION; HEAT SENSITIVITY; COMMON
   GARDEN; PUERTO-RICO; EVOLUTIONARY; HINDLIMB
AB Phenotypic plasticity can contribute to the process of adaptive radiation by facilitating population persistence in novel environments. West Indian Anolis lizards provide a classic example of an adaptive radiation, in which divergence has occurred along two primary ecological axes: structural microhabitat and climate. Adaptive plasticity in limb morphology is hypothesized to have facilitated divergence along the structural niche axis in Anolis, but very little work has explored plasticity in physiological traits. Here, we experimentally ask whether Puerto Rican Anolis cristatellus from mesic and xeric habitats differ in desiccation rates, and whether these lizards exhibit an acclimation response to changes in relative humidity. We first present microclimatic data collected at lizard perch sites that demonstrate that abiotic conditions experienced by lizards differ between mesic and xeric habitat types. In Experiment 1, we measured desiccation rates of lizards from both habitats maintained under identical laboratory conditions. This experiment demonstrated that desiccation rates differ between populations; xeric lizards lose water more slowly than mesic lizards. In Experiment 2, lizards from each habitat were either maintained under the conditions of Experiment 1, or under extremely low relative humidity. Desiccation rates did not differ between lizards from the same habitat maintained under different treatments and xeric lizards maintained lower desiccation rates than mesic lizards within each treatment. Our results demonstrate that A. cristatellus does not exhibit an acclimation response to abrupt changes of hydric conditions, and suggest that tropical Anolis lizards might be unable to exhibit physiological plasticity in desiccation rates in response to varying climatic conditions.
C1 [Gunderson, Alex R.; Siegel, Jeremy; Leal, Manuel] Duke Univ, Dept Biol, Durham, NC 27708 USA.
C3 Duke University
RP Gunderson, AR (corresponding author), Duke Univ, Dept Biol, Durham, NC 27708 USA.
EM alexander.gunderson@duke.edu
RI Leal, Manuel/A-7220-2010
FU Center for Latin American and Caribbean Studies at Duke University;
   North Carolina Academy of Sciences
FX We would like to thank Ray Huey, Paul Hertz, Brian Powell, David
   Steinberg, and three anonymous reviewers for providing helpful comments
   that improved the manuscript. We would also like to thank the Mata de
   Platano (Intermerican University, Bayamon) and Isla Magueyes (University
   of Puerto Rico, Mayaguez) field stations, and Tony and Joan at T. J.
   Ranch for logistical support while in Puerto Rico. We are very grateful
   to the Departamento de Recursos Naturales y Ambientales of Puerto Rico,
   which provided all the necessary permits for conducting fieldwork. We
   followed the Recommendations for the Care of Amphibians and Reptiles
   (Pough 1991) in the treatment of all animals used in this study. The
   research presented here was approved by the Institutional Animal Care of
   Duke University. This work was supported by a Mellon Dissertation
   Research Grant from the Center for Latin American and Caribbean Studies
   at Duke University and a Bryden Graduate Student Research Grant from the
   North Carolina Academy of Sciences to ARG.
CR Agrawal AA, 2001, SCIENCE, V294, P321, DOI 10.1126/science.1060701
   [Anonymous], RECOMMENDATIONS CARE
   [Anonymous], DEV PLASTICITY EVOLU
   BENTLEY PJ, 1966, SCIENCE, V151, P1547, DOI 10.1126/science.151.3717.1547
   Calsbeek R, 2006, EVOL ECOL, V20, P377, DOI 10.1007/s10682-006-0007-y
   Daly C, 2003, INT J CLIMATOL, V23, P1359, DOI 10.1002/joc.937
   DeWitt TJ, 1998, TRENDS ECOL EVOL, V13, P77, DOI 10.1016/S0169-5347(97)01274-3
   Dmiel R, 1997, BIOTROPICA, V29, P111
   Ewel J. J., 1973, ITF18
   EYNAN M, 1993, OECOLOGIA, V95, P290, DOI 10.1007/BF00323502
   Ghalambor CK, 2007, FUNCT ECOL, V21, P394, DOI 10.1111/j.1365-2435.2007.01283.x
   Heatwole H., 1976, Occasional Papers Mus Nat Hist Univ Kans, VNo. 46, P1
   Helmer EH, 2002, CARIBB J SCI, V38, P165
   HERTZ PE, 1992, OECOLOGIA, V90, P127, DOI 10.1007/BF00317818
   HERTZ PE, 1992, ECOLOGY, V73, P1405, DOI 10.2307/1940686
   HERTZ PE, 1980, COPEIA, P440, DOI 10.2307/1444519
   HERTZ PE, 1993, AM NAT, V142, P796, DOI 10.1086/285573
   HERTZ PE, 1979, COMP BIOCHEM PHYS A, V63, P217, DOI 10.1016/0300-9629(79)90151-8
   HERTZ PE, 1979, COMP BIOCHEM PHYS A, V62, P947, DOI 10.1016/0300-9629(79)90033-1
   HILLMAN S, 1979, COMP BIOCHEM PHYS A, V62, P491, DOI 10.1016/0300-9629(79)90091-4
   HILLMAN SS, 1977, OECOLOGIA, V29, P105, DOI 10.1007/BF00345791
   HUEY RB, 1976, ECOLOGY, V57, P985, DOI 10.2307/1941063
   KATTAN GH, 1989, PHYSIOL ZOOL, V62, P593, DOI 10.1086/physzool.62.2.30156187
   KOBAYASHI D, 1983, COPEIA, P701, DOI 10.2307/1444335
   Kolbe JJ, 2005, J HERPETOL, V39, P674, DOI 10.1670/87-05N.1
   Lillywhite HB, 2006, J EXP BIOL, V209, P202, DOI 10.1242/jeb.02007
   LILLYWHITE HB, 1993, COPEIA, P99
   Losos JB, 2009, ORGANISM ENVIRON, V10, P1
   Losos JB, 2000, EVOLUTION, V54, P301, DOI 10.1111/j.0014-3820.2000.tb00032.x
   Malhotra A, 1997, HERPETOLOGICA, V53, P49
   Perry G, 1999, BIOTROPICA, V31, P337, DOI 10.1111/j.1744-7429.1999.tb00145.x
   Perry G, 2000, BIOTROPICA, V32, P722, DOI 10.1646/0006-3606(2000)032[0722:EWLIIP]2.0.CO;2
   Pfennig KS, 2009, Q REV BIOL, V84, P253, DOI 10.1086/605079
   R Development Core Team, 2009, R: a language and environment for statistical computing
   RAND AS, 1964, ECOLOGY, V45, P745, DOI 10.2307/1934922
   REYNOLDS WW, 1979, AM ZOOL, V19, P211
   Rogowitz GL, 1996, J THERM BIOL, V21, P11, DOI 10.1016/0306-4565(95)00014-3
   RUIBAL R, 1961, EVOLUTION, V15, P98, DOI 10.2307/2405846
   Sol D, 2005, EVOLUTION, V59, P2669, DOI 10.1111/j.0014-3820.2005.tb00978.x
   Spezzano LC, 2004, J EXP BIOL, V207, P2115, DOI 10.1242/jeb.00995
   Stillman JH, 2003, SCIENCE, V301, P65, DOI 10.1126/science.1083073
   Thorpe RS, 2005, AM NAT, V165, P495, DOI 10.1086/428408
   Warner DA, 2002, BIOL J LINN SOC, V76, P105, DOI 10.1111/j.1095-8312.2002.tb01718.x
   Williams E.E., 1983, P326
   Williams E.E., 1972, EVOL BIOL, V6, P47, DOI [10.1007/978-1-4684-9063-3_3, DOI 10.1007/978-1-4684-9063-3_3]
NR 45
TC 25
Z9 30
U1 0
U2 38
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 0174-1578
EI 1432-136X
J9 J COMP PHYSIOL B
JI J. Comp. Physiol. B-Biochem. Syst. Environ. Physiol.
PD OCT
PY 2011
VL 181
IS 7
BP 965
EP 972
DI 10.1007/s00360-011-0576-0
PG 8
WC Physiology; Zoology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Physiology; Zoology
GA 851EI
UT WOS:000297250800011
PM 21516326
DA 2025-01-10
ER

PT J
AU Hartmann, K
   Brunotte, E
AF Hartmann, Kerstin
   Brunotte, Ernst
TI The genesis and current reshaping of dunes at the eastern margin of the
   northern Namib Desert (Hartmann Valley, NW Namibia) Modelled wind-flow
   patterns, multi-temporal aerial photograph analysis and anthropogenic
   morphodynamics
SO ZEITSCHRIFT FUR GEOMORPHOLOGIE
LA English
DT Article
ID NEBKHA DUNES; BURKINA-FASO; DEGRADATION; INDICATORS; AFRICA
AB This research was carried out in the framework of the Collaborative Research Centre for "Arid Climate Adaptation and Cultural Innovation in Africa" (ACACIA/SFB 389) at the University of Cologne. The research centre was financed by the German Science Foundation (DFG) and included the study of landscape formation in north-western Namibia.
   One focus of our research was on the transitional area between the Namib Desert and the dry savannah in the Marienfluss Valley - Hartmann Valley region. When the research project was initiated, this region with a total area of approx. 5600 km(2) was 'terra incognita' from a geomorphological point of view. For this reason the entire recent Quaternary development of relief including current morphodynamics was studied.
   In the context of the issue of 'shifting desert margins', dune fields at the eastern margin of the Namib Desert in NW Namibia south of the Angolan border were studied during several years of field observation using geomorphological relief analysis in the field, aerial photographs and pictures taken when flying over the area. In the absence of meteorological stations, the genesis of the dunes has been inferred on the basis of calculated wind-flow patterns. In this way it was possible to show that the distribution of dunes in the study area is determined by a change in wind direction over the South Atlantic.
   The changes in dune forms since 1964 were identified by means of multi-temporal analysis of aerial photographs; reshaping by man through the beginnings of tourism in recent years could be observed directly. The transformation of dunes in heavy thunderstorms is also described.
C1 [Hartmann, Kerstin; Brunotte, Ernst] Univ Cologne, Sect Appl Geomorphol & Landscape Studies, Dept Geog, D-50923 Cologne, Germany.
C3 University of Cologne
RP Hartmann, K (corresponding author), Univ Cologne, Sect Appl Geomorphol & Landscape Studies, Dept Geog, Albertus Magnus Pl, D-50923 Cologne, Germany.
CR AlDabi H, 1997, J ARID ENVIRON, V36, P15, DOI 10.1006/jare.1996.0230
   [Anonymous], 2002, ATLAS NAMIBIA PORTRA
   ASENDORPF D, 2004, ZEIT, V38
   Besler H., 2002, Zeitschrift fur Geomorph. Suppl, V126, P59
   Besler H., 1987, GEOGR RUNDSCH, V39, P422
   BUSCHE D, 1998, OBERFLACHENFORMEN WA
   Cooke R, 1993, Desert Geomorphology
   DAVID L, 2007, IMPACTS TOURISM SPOR
   Dougill AJ, 2002, J ARID ENVIRON, V50, P413, DOI 10.1006/jare.2001.0909
   Goudie A., 2006, ENCY GEOMORPHOLOGY
   HARTMANN K, 2007, KOLNER GEOGR ARB, V87
   Jakel D., 2004, Zeitschrift fur Geomorphologie, Supplementband, VSupplement, P107
   NICKLING WG, 1994, J ARID ENVIRON, V28, P13, DOI 10.1016/S0140-1963(05)80017-5
   SANDER H, 2004, PASSAUER SCHR GEOGR, V19
   Tengberg A, 1998, GEOMORPHOLOGY, V22, P181, DOI 10.1016/S0169-555X(97)00068-8
   TENGBERG A, 1995, J ARID ENVIRON, V30, P265, DOI 10.1016/S0140-1963(05)80002-3
   WANG X, 2005, J ARID ENVIRON, P129
NR 17
TC 3
Z9 3
U1 0
U2 13
PU GEBRUDER BORNTRAEGER
PI STUTTGART
PA JOHANNESSTR 3A, D-70176 STUTTGART, GERMANY
SN 0372-8854
J9 Z GEOMORPHOL
JI Z. Geomorphol.
PD SEP
PY 2008
VL 52
SU 2
BP 1
EP 14
DI 10.1127/0372-8854/2008/0052S2-0001
PG 14
WC Geography, Physical; Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Physical Geography; Geology
GA 373VI
UT WOS:000261001200002
DA 2025-01-10
ER

PT J
AU Choi, Y
   Tang, ZQ
   Ma, YN
AF Choi, Yongrok
   Tang, Ziqian
   Ma, Yunning
TI Lessons from the Pilot Project of Korean ETS on the Local Landscape of
   Economy
SO LAND
LA English
DT Article
DE general non-radial directional distance function (GNDDF); environmental
   total factor productivity; technological efficiency; economic
   efficiency; emission trading scheme (ETS)
ID EMISSION PERFORMANCE; PRODUCTIVITY; EFFICIENCY
AB For a sustainable landscape of local economies, many researchers have emphasized the importance of field-oriented differentiation in government policies. In particular, the Paris Agreement, based on the bottom-up approach, aims to maximize the participation of all economic agents, in contrast to the top-down approach of the Tokyo Protocol. In response to these global paradigm shifts in the local landscape, local governments in Korea have made significant efforts to adapt to sustainable development during the pilot phase of emission trading scheme (ETS), during the period from 2015 to 2020. This study evaluates the performance of these local government policies in the transition to a carbon-zero economy. Using the general non-radial directional distance function (GNDDF), we found that Gyeongsang Province demonstrated enhanced environmental total factor productivity (TFP) during the pilot project, whereas the Seoul metropolitan area lagged behind due to a lack of governance. As the economic center of Korea, Seoul showed poor environmental performance because of the arbitrary elimination of green belt areas and unchecked land development, resulting in environmental degradation, a trend common in many developing countries facing climate adaptation challenges. To address these urbanization issues, this study concludes that a balanced approach combining stricter regulations with market-oriented promotional incentives is essential for optimizing the transition of local economies to a sustainable landscape.
C1 [Choi, Yongrok] Inha Univ, Dept Int Trade, Inharo 100, Incheon 22221, South Korea.
   [Tang, Ziqian; Ma, Yunning] Inha Univ, Ind Secur & Egovernance, Inharo 100, Incheon 22221, South Korea.
C3 Inha University; Inha University
RP Tang, ZQ; Ma, YN (corresponding author), Inha Univ, Ind Secur & Egovernance, Inharo 100, Incheon 22221, South Korea.
EM yrchoi@inha.ac.kr; t784949232@gmail.com; mayunning666@gmail.com
RI Choi, Yongrok/AFN-7905-2022
OI Choi, Yongrok/0000-0003-1935-2172
CR 2050cnc, Carbon Neutrality of the Republic of Korea
   Choi Y, 2024, SUSTAINABILITY-BASEL, V16, DOI 10.3390/su16114713
   Chung YH, 1997, J ENVIRON MANAGE, V51, P229, DOI 10.1006/jema.1997.0146
   Dong F, 2022, J ENVIRON MANAGE, V316, DOI 10.1016/j.jenvman.2022.115252
   FARE R, 1994, AM ECON REV, V84, P66, DOI 10.1111/j.1467-8268.2004.00089.x
   Guo BS, 2024, SUSTAIN CITIES SOC, V106, DOI 10.1016/j.scs.2024.105365
   Huang KA, 2022, ECON ANAL POLICY, V75, P362, DOI 10.1016/j.eap.2022.05.016
   Jing ZB, 2024, ENERGY, V306, DOI 10.1016/j.energy.2024.132357
   Kwak Y, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11247172
   Lee Serim, 2017, [Journal of Climate Change Research, 한국기후변화학회지], V8, P221
   Lin BQ, 2021, ENERGY, V223, DOI 10.1016/j.energy.2021.120081
   Nie X, 2021, J CLEAN PROD, V314, DOI 10.1016/j.jclepro.2021.128027
   Oesingmann K, 2022, ENERG POLICY, V160, DOI 10.1016/j.enpol.2021.112657
   Ouyang XL, 2023, ENVIRON IMPACT ASSES, V98, DOI 10.1016/j.eiar.2022.106968
   Pan YH, 2024, ENERG ECON, V130, DOI 10.1016/j.eneco.2023.107285
   Shi BB, 2022, J ENVIRON MANAGE, V319, DOI 10.1016/j.jenvman.2022.115650
   Tan XJ, 2024, UTIL POLICY, V88, DOI 10.1016/j.jup.2024.101752
   Verbruggen A, 2021, ENVIRON SCI POLICY, V119, P66, DOI 10.1016/j.envsci.2021.02.013
   Wang N, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11143895
   wmo, Climate Change Indicators Reached Record Levels in 2023: WMO
   Xie HL, 2019, J CLEAN PROD, V207, P1047, DOI 10.1016/j.jclepro.2018.10.087
   Yu Jongmin, 2017, [Journal of Environmental Policy and Administration, 환경정책], V25, P231, DOI 10.15301/jepa.2017.25.2.231
   Zhang N, 2013, ENERG ECON, V40, P549, DOI 10.1016/j.eneco.2013.08.012
   Zhao Y, 2024, ENERG J, V45, P177, DOI 10.5547/01956574.45.3.yzha
   Zhou P, 2012, EUR J OPER RES, V221, P625, DOI 10.1016/j.ejor.2012.04.022
NR 25
TC 0
Z9 0
U1 2
U2 2
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-445X
J9 LAND-BASEL
JI Land
PD OCT
PY 2024
VL 13
IS 10
AR 1603
DI 10.3390/land13101603
PG 19
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA K1X5X
UT WOS:001341881300001
OA gold
DA 2025-01-10
ER

PT J
AU Streck, C
AF Streck, Charlotte
TI Synergies between the Kunming-Montreal Global Biodiversity Framework and
   the Paris Agreement: the role of policy milestones, monitoring
   frameworks and safeguards
SO CLIMATE POLICY
LA English
DT Article; Early Access
DE Climate policy; Paris Agreement; UNFCCC; CBD; Global Biodiversity
   Framework
AB The 2022 Kunming-Montreal Global Biodiversity Framework (GBF) and Paris Agreement (PA) are highly complementary agreements where each depends on the other's success to be effective. The GBF offers a very specific framework of interim goals and targets that break down the objective of the Convention on Biodiversity (CBD) into a decade-spanning work plan. Comprised of 10 sections - including a 2050 vision and a 2030 mission, four overarching goals and 23 specific targets - the GBF is expected to guide biodiversity policy around the world in the coming years to decades. A similar set of global interim climate policy targets could translate the global temperature goal into concrete policy milestones that would provide policy makers and civil society with reference points for policy making and efforts to hold governments accountable. Beyond inspiring climate policy experts to convert temperature goals into policy milestones, GBF has the potential to strengthen the implementation of the PA at the nexus of biodiversity and climate (adaptation and mitigation) action. For example, the GBF can help to ensure that nature-based climate solutions are implemented with full consideration of biodiversity concerns, of the rights and interests of Indigenous Peoples and local communities, and with fair and transparent benefit sharing arrangements. In sum, the GBF should be mandatory reading for all climate policy makers.
C1 [Streck, Charlotte] Univ Potsdam, Potsdam, Germany.
   [Streck, Charlotte] Climate Focus, Berlin, Germany.
   [Streck, Charlotte] Univ Potsdam, Neuen Palais 10, D-14469 Potsdam, Germany.
   [Streck, Charlotte] Climate Focus, Chausseestr 84, D-10115 Berlin, Germany.
C3 University of Potsdam; University of Potsdam
RP Streck, C (corresponding author), Univ Potsdam, Neuen Palais 10, D-14469 Potsdam, Germany.; Streck, C (corresponding author), Climate Focus, Chausseestr 84, D-10115 Berlin, Germany.
EM C.Streck@climatefocus.com
OI Streck, Charlotte/0000-0001-5105-5683
CR AHTEG, 2003, INT BIOL DIV CLIM CH
   AHTEG, 2008, CONN BIOD CLIM CHANG
   AHTEG, 2006, GUID PROM SYN ACT AD
   [Anonymous], 2022, SHARM EL SHEIKH MITI
   [Anonymous], 2022, MONITORING FRAMEWORK
   [Anonymous], CLIMATE ACTION PATHW
   [Anonymous], 2018, Guidelines on transparency under Regulation
   [Anonymous], 2010, STRATEGIC PLAN BIODI
   [Anonymous], 2022, SUMMARY GLOBAL CLIMA
   Antonelli A, 2023, NATURE, V613, P239, DOI 10.1038/d41586-023-00021-4
   Baldwin-Cantello W, 2023, CLIM POLICY, V23, P782, DOI 10.1080/14693062.2023.2175637
   Bastin JF, 2019, SCIENCE, V365, P76, DOI 10.1126/science.aax0848
   Bendig D, 2023, J IND ECOL, V27, P125, DOI 10.1111/jiec.13341
   Bodansky D, 2016, REV EUR COMP INT ENV, V25, P142, DOI 10.1111/reel.12154
   Bongaarts J, 2019, POPUL DEV REV, V45, P680, DOI 10.1111/padr.12283
   Brunnee Jutta., 2002, LEIDEN J INT L, V15, P1, DOI DOI 10.1017/S0922156502000018
   Carbon Brief, 2022, COP15 KEY OUTC AGR U
   CBD, 2012, BIOD CLIM CHANG INT
   CBD, 2019, REV NEW SCI TECHN IN
   CBD, 2010, IN DEPTH REV WORK BI, V13, P245, DOI [10.1080/13880292.2010.503134, DOI 10.1080/13880292.2010.503134]
   CBD, 2012, BIOD CLIM CHANG REL
   CBD Secretariat, 2022, CBDIDOM20221INF2
   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]
   Cohen-Shacham E, 2019, ENVIRON SCI POLICY, V98, P20, DOI 10.1016/j.envsci.2019.04.014
   COP27, 2022, UN NEWS
   Díaz S, 2022, NATURE, V612, P9, DOI 10.1038/d41586-022-04154-w
   Díaz S, 2020, SCIENCE, V370, P411, DOI 10.1126/science.abe1530
   Dirnitrov R, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.583
   Esmail N, 2023, TRENDS ECOL EVOL, V38, P666, DOI 10.1016/j.tree.2023.02.008
   Fa JE, 2020, FRONT ECOL ENVIRON, V18, P135, DOI 10.1002/fee.2148
   Fabius L., 2022, COMMUNICATION
   Garnett ST, 2018, NAT SUSTAIN, V1, P369, DOI 10.1038/s41893-018-0100-6
   Glasgow Leaders' Declaration on Forests and Land Use, 2021, GLASGOW LEADERS DECL
   Greenfield P., 2022, The Guardian16 Nov.
   Grumbine RE, 2021, BIOSCIENCE, V71, P637, DOI 10.1093/biosci/biab013
   Katowice Climate Package, 2018, KATOWICE CLIMATE PAC
   Kunming-Montreal Global Biodiversity Framework, 2022, KUNMING MONTREAL GLO, DOI [10.5281/ZENODO.3831673, DOI 10.5281/ZENODO.3831673]
   Lovera S., 2022, The good, the bad and the ugly: A historical deal for biodiversity
   Maljean-Dubois S., 2017, ELGAR ENCY ENV LAW S
   Mauro F, 2000, ECOL APPL, V10, P1263, DOI 10.2307/2641281
   Nagoya Protocol, 2010, NAGOYA PROTOCOL
   Newbold T, 2018, P ROY SOC B-BIOL SCI, V285, DOI 10.1098/rspb.2018.0792
   Reed G, 2022, CLIM POLICY, V22, P514, DOI 10.1080/14693062.2022.2047585
   Resource mobilization, 2022, RESOURCE MOBILIZATIO
   Science Based Targets initiative, 2023, SCI BAS TARG
   Seddon N, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0120
   Seddon N, 2019, NAT CLIM CHANGE, V9, P84, DOI 10.1038/s41558-019-0405-0
   Sharm el-Sheikh joint work on implementation of climate action on agriculture and food security, 2022, SHARM EL SHEIKH JOIN
   Streck C, 2019, J EUR ENVIRON PLAN L, V16, P165, DOI 10.1163/18760104-01602005
   "The Paris Agreement.", 2015, PARIS AGREEMENT
   Tsioumani E., 2022, LINKAGES SYNERGIES I
   UNFCCC, 2021, 14 NAIR WORK PROGR F
   UNFCCC Secretariat, 2022, FIN NAT BAS SOL MUST
   UNFCCC Secretariat, 2020, JUST TRANS WORKF CRE
   Walker WS, 2020, P NATL ACAD SCI USA, V117, P3015, DOI 10.1073/pnas.1913321117
   World Economic Forum (WEF), 2023, The voluntary carbon market: climate finance at an inflection point
NR 56
TC 4
Z9 4
U1 11
U2 24
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 2023 JUL 8
PY 2023
DI 10.1080/14693062.2023.2230940
EA JUL 2023
PG 12
WC Environmental Studies; Public Administration
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Public Administration
GA O8GF2
UT WOS:001046130000001
OA hybrid
DA 2025-01-10
ER

PT J
AU Horne, AC
   Webb, JA
   Mussehl, M
   John, A
   Rumpff, L
   Fowler, K
   Lovell, D
   Poff, L
AF Horne, Avril C.
   Webb, J. Angus
   Mussehl, Meghan
   John, Andrew
   Rumpff, Libby
   Fowler, Keirnan
   Lovell, Daniel
   Poff, LeRoy
TI Not Just Another Assessment Method: Reimagining Environmental Flows
   Assessments in the Face of Uncertainty
SO FRONTIERS IN ENVIRONMENTAL SCIENCE
LA English
DT Article
DE environmental flows; uncertainty; adaptive management; non-stationarity;
   eflows
ID ADAPTIVE MANAGEMENT; CLIMATE-CHANGE; SCIENCE; CHALLENGES; PARTICIPATION;
   PERSPECTIVE; ECOSYSTEMS; KNOWLEDGE
AB The numerous environmental flows assessment methods that exist typically assume a stationary climate. Adaptive management is commonly put forward as the preferred approach for managing uncertainty and change in environmental flows. However, we contend that a simple adaptive management loop falls short of meeting the challenges posed by climate change. Rather, a fundamental rethink is required to ensure both the structure of environmental flows assessments, along with each individual technical element, actively acknowledges the multiple dimensions of change, variability and complexity in socio-ecological systems. This paper outlines how environmental flow assessments can explicitly address the uncertainty and change inherent in adaptively managing multiple values for management of environmental flows. While non-stationarity and uncertainty are well recognised in the climate literature, these have not been addressed within the structure of environmental flows methodologies. Here, we present an environmental flow assessment that is structured to explicitly consider future change and uncertainty in climate and socio-ecological values, by examining scenarios using ecological models. The environmental flow assessment methodology further supports adaptive management through the intentional integration of participatory approaches and the inclusion of diverse stakeholders. We present a case study to demonstrate the feasibility of this approach, highlighting how this methodology facilitates adaptive management. Rethinking our approach to environmental flows assessments is an important step in ensuring that environmental flows continue to work effectively as a management tool under climate change.
C1 [Horne, Avril C.; Webb, J. Angus; Mussehl, Meghan; John, Andrew; Rumpff, Libby; Fowler, Keirnan] Univ Melbourne, Parkville, Vic, Australia.
   [Lovell, Daniel] Goulburn Broken Catchment Management Author, Sheparton, Vic, Australia.
   [Poff, LeRoy] Univ Canberra, Canberra, ACT, Australia.
   [Poff, LeRoy] Colorado State Univ, Ft Collins, CO USA.
C3 University of Melbourne; University of Canberra; Colorado State
   University
RP Horne, AC (corresponding author), Univ Melbourne, Parkville, Vic, Australia.
EM avril.horne@unimelb.edu.au
RI Fowler, Keirnan/AAS-3461-2020; Webb, James/F-8001-2011
OI John, Andrew/0000-0002-6919-3221; Mussehl, Meghan/0000-0001-8455-7671;
   Fowler, Keirnan/0000-0002-1983-0253; Horne, Avril/0000-0001-6615-9987;
   Rumpff, Libby/0000-0001-9400-8086
CR Acreman M., 2017, WATER ENV, DOI [10.1016/B978-0-12-803907-6.00028-0, DOI 10.1016/B978-0-12-803907-6.00028-0]
   Acreman MC, 2014, HYDROLOG SCI J, V59, P433, DOI 10.1080/02626667.2014.886019
   Acreman M, 2014, FRONT ECOL ENVIRON, V12, P466, DOI 10.1890/130134
   Allan C, 2018, ENVIRON MANAGE, V61, P520, DOI 10.1007/s00267-017-0931-3
   Allen CR, 2011, J ENVIRON MANAGE, V92, P1339, DOI 10.1016/j.jenvman.2010.11.019
   Anderson EP, 2019, WIRES WATER, V6, DOI 10.1002/wat2.1381
   [Anonymous], WORLD RESOURCES REPO
   [Anonymous], 2012, STRUCTURED DECISION, DOI DOI 10.1002/9781444398557
   Arthington AH, 2018, FRONT ENV SCI-SWITZ, V6, DOI 10.3389/fenvs.2018.00045
   Bellard C, 2012, ECOL LETT, V15, P365, DOI 10.1111/j.1461-0248.2011.01736.x
   Bestgen KR, 2020, ECOL APPL, V30, DOI 10.1002/eap.2005
   Beven K, 2016, HYDROLOG SCI J, V61, P1652, DOI 10.1080/02626667.2015.1031761
   Boltz Frederick, 2019, Water Security, V8, DOI 10.1016/j.wasec.2019.100048
   Burton P, 2013, URBAN POLICY RES, V31, P399, DOI 10.1080/08111146.2013.778196
   Colloff MJ, 2019, AUSTRALAS J WAT RESO, V23, P88, DOI 10.1080/13241583.2019.1664878
   Conallin J.C., 2017, WATER ENV, DOI [10.1016/B978-0-12-803907-6.00028-0, DOI 10.1016/B978-0-12-803907-6.00028-0]
   Conallin J, 2018, ENVIRON MANAGE, V62, P955, DOI 10.1007/s00267-018-1091-9
   de Little SC, 2018, ENVIRON MODELL SOFTW, V100, P146, DOI 10.1016/j.envsoft.2017.11.020
   Doolan J., 2017, WATER ENV, DOI [10.1016/B978-0-12-803907-6.00028-0, DOI 10.1016/B978-0-12-803907-6.00028-0]
   Fowler K, 2022, ENVIRON MODELL SOFTW, V150, DOI 10.1016/j.envsoft.2022.105339
   Fujitani M, 2017, SCI ADV, V3, DOI 10.1126/sciadv.1602516
   Gawne B., 2020, FINAL REPORT PREPARE
   Gawne B., 2021, MONITORING EVALUATIO, P227, DOI 10.1016/b978-0-12-818152-2.00011-5
   Gawne B, 2020, RIVER RES APPL, V36, P630, DOI 10.1002/rra.3504
   Godden L, 2019, AUSTRALAS J WAT RESO, V23, P45, DOI 10.1080/13241583.2019.1608688
   Gregory R, 2006, ECOL APPL, V16, P2411, DOI 10.1890/1051-0761(2006)016[2411:DAMCFA]2.0.CO;2
   Grose MR, 2020, EARTHS FUTURE, V8, DOI 10.1029/2019EF001469
   Hanea AM, 2017, INT J FORECASTING, V33, P267, DOI 10.1016/j.ijforecast.2016.02.008
   HARAWAY D, 1988, FEMINIST STUD, V14, P575, DOI 10.2307/3178066
   Holling C.S., 1978, Adaptive environmental assessment and management
   Horne A.C., 2017, WATER ENV, DOI [10.1016/B978-0-12-803907-6.00028-0, DOI 10.1016/B978-0-12-803907-6.00028-0]
   Horne AC, 2019, BIOSCIENCE, V69, P789, DOI 10.1093/biosci/biz087
   Horne AC, 2017, FRONT ENV SCI-SWITZ, V5, DOI 10.3389/fenvs.2017.00089
   Horne AC, 2018, ENVIRON MANAGE, V61, P347, DOI 10.1007/s00267-017-0874-8
   Horne AC, 2017, WATER FOR THE ENVIRONMENT: FROM POLICY AND SCIENCE TO IMPLEMENTATION AND MANAGEMENT, P3, DOI 10.1016/B978-0-12-803907-6.00001-2
   John A, 2021, FRONT ENV SCI-SWITZ, V9, DOI 10.3389/fenvs.2021.789206
   John A, 2021, WIRES CLIM CHANGE, V12, DOI 10.1002/wcc.692
   Kingsford RT, 2011, BIOL CONSERV, V144, P1194, DOI 10.1016/j.biocon.2010.09.022
   Kosovac A, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11051279
   Le Quesne T., 2010, The Implementation Challenge: Taking stock of government policies to protect and restore environmental flows
   Mostert E, 2007, ECOL SOC, V12
   Murray C., 2015, Adaptive Management of Social-Ecological Systems
   Mussehl ML, 2022, FRONT ENV SCI-SWITZ, V9, DOI 10.3389/fenvs.2021.749864
   Nathan RJ, 2019, CLIMATIC CHANGE, V156, P87, DOI 10.1007/s10584-019-02497-4
   O'Donnell EL, 2019, AUSTRALAS J WAT RESO, V23, P1, DOI 10.1080/13241583.2019.1586058
   Pahl-Wostl C, 2013, CURR OPIN ENV SUST, V5, P341, DOI 10.1016/j.cosust.2013.06.009
   Poff NL, 2018, FRESHWATER BIOL, V63, P1011, DOI 10.1111/fwb.13038
   Poff NL, 2017, WATER FOR THE ENVIRONMENT: FROM POLICY AND SCIENCE TO IMPLEMENTATION AND MANAGEMENT, P203, DOI 10.1016/B978-0-12-803907-6.00011-5
   Poff NL, 2010, FRESHWATER BIOL, V55, P147, DOI 10.1111/j.1365-2427.2009.02204.x
   Poff NL, 2003, FRONT ECOL ENVIRON, V1, P298, DOI 10.1890/1540-9295(2003)001[0298:RFAWWE]2.0.CO;2
   Prosser IP, 2021, WATER-SUI, V13, DOI 10.3390/w13182504
   Raymond CM, 2010, J ENVIRON MANAGE, V91, P1766, DOI 10.1016/j.jenvman.2010.03.023
   Richter BD, 2012, RIVER RES APPL, V28, P1312, DOI 10.1002/rra.1511
   Rist L, 2013, ECOL SOC, V18, DOI 10.5751/ES-06183-180463
   Rosendahl J, 2015, FUTURES, V65, P17, DOI 10.1016/j.futures.2014.10.011
   Roux DJ, 2011, KOEDOE, V53, DOI 10.4102/koedoe.v53i2.1049
   Stein ED, 2021, FRONT ENV SCI-SWITZ, V9, DOI 10.3389/fenvs.2021.769943
   Stewardson M., 2008, River Restoration: Managing the Uncertainty in Restoring Physical Habitat, P61
   Tharme RE, 2003, RIVER RES APPL, V19, P397, DOI 10.1002/rra.736
   Tompkins EL, 2004, ECOL SOC, V9
   Tonkin JD, 2019, NATURE, V570, P301, DOI 10.1038/d41586-019-01877-1
   Treadwell S., 2021, 2019 20 GOULBURN MER
   Voinov A, 2008, ECOL MODEL, V216, P197, DOI 10.1016/j.ecolmodel.2008.03.010
   Voinov A, 2016, ENVIRON MODELL SOFTW, V77, P196, DOI 10.1016/j.envsoft.2015.11.016
   Webb A., 2019, EVALUATION RES PLAN
   Webb J.A., 2017, WATER ENV POLICY SCI, DOI [10.1016/B978-0-12-803907-6.00028-0, DOI 10.1016/B978-0-12-803907-6.00028-0]
   Webb JA, 2018, FRESHWATER BIOL, V63, P831, DOI 10.1111/fwb.13069
   Webb JA, 2010, MAR FRESHWATER RES, V61, P798, DOI 10.1071/MF09059
   Williams BK, 2014, ENVIRON MANAGE, V53, P465, DOI 10.1007/s00267-013-0205-7
   Williams BK, 2011, J ENVIRON MANAGE, V92, P1346, DOI 10.1016/j.jenvman.2010.10.041
   Williams J G., 2019, Environmental flow assessment: methods and applications
NR 71
TC 15
Z9 15
U1 6
U2 28
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 MAY 10
PY 2022
VL 10
AR 808943
DI 10.3389/fenvs.2022.808943
PG 17
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA 1M5UX
UT WOS:000800035200001
OA gold
DA 2025-01-10
ER

PT J
AU Hashida, Y
   Lewis, DJ
AF Hashida, Yukiko
   Lewis, David J.
TI Estimating welfare impacts of climate change using a discrete-choice
   model of land management: An application to western US forestry
SO RESOURCE AND ENERGY ECONOMICS
LA English
DT Article
DE Climate adaptation; Forestry; Econometric model; Land-use modeling; Land
   value
ID UNITED-STATES; AGRICULTURE; ADAPTATION; MARKET
AB This study develops a method to estimate the welfare impacts of climate change on landowners using a discrete-choice econometric model of land management. We apply the method to forest management in the Pacific states of the U.S. and estimate welfare effects on the region that holds the largest current commercial value - western Oregon and Washington. We find evidence that a warmer and drier climate will induce an approximate 39 % loss in the economic value of timberland by 2050, though there is heterogeneity across space. The discrete-choice approach allows us to determine that the welfare losses are primarily driven by estimated losses to Douglas-fir, the most commercially valuable species. An alternative approach to welfare analysis from climate change is the Ricardian method, which gives conceptually similar estimates to the discrete-choice method. While we find similar empirical findings between the discrete-choice and Ricardian approaches, the discrete-choice approach provides more heterogeneity and somewhat larger negative welfare impacts. Our analysis is notable for providing the first empirical evidence that climate change can induce welfare losses to timberland owners, even while accounting for optimal adaptation. (c) 2022 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 [Hashida, Yukiko] Univ Georgia, Athens, GA 30602 USA.
   [Lewis, David J.] Oregon State Univ, Corvallis, OR 97331 USA.
C3 University System of Georgia; University of Georgia; Oregon State
   University
RP Hashida, Y (corresponding author), Univ Georgia, Athens, GA 30602 USA.
EM yhashida@uga.edu; lewisda@oregonstate.edu
RI Hashida, Yukiko/AFK-1455-2022; Lewis, David/I-5700-2013
OI Hashida, Yukiko/0000-0001-8546-1532; Lewis, David/0000-0002-2161-4189
FU National Institute of Food and Agriculture; U.S.D.A. Forest Service
   Pacific Northwest Research Station; U.S.D.A Forest Service Southern
   Research Station; U.S.D.A. Forest Service Southern Research Station
FX We thank the National Institute of Food and Agriculture, the U.S.D.A.
   Forest Service Pacific Northwest Research Station and U.S.D.A Forest
   Service Southern Research Station for funding support. Lewis also
   acknowledges funding support from the U.S.D.A. Forest Service Southern
   Research Station. Any errors remain our own.
CR Abatzoglou JT, 2016, P NATL ACAD SCI USA, V113, P11770, DOI 10.1073/pnas.1607171113
   Amacher GS, 2005, LAND ECON, V81, P284, DOI 10.3368/le.81.2.284
   BEN-AKIVA M. E., 1985, Discrete Choice Analysis: Theory and Application to Travel Demand
   Brunette M, 2020, CLIMATIC CHANGE, V162, P2157, DOI 10.1007/s10584-020-02751-0
   Crookston NL, 2010, FOREST ECOL MANAG, V260, P1198, DOI 10.1016/j.foreco.2010.07.013
   Davis KT, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/abb9df
   Dundas SJ, 2020, J ASSOC ENVIRON RESO, V7, P209, DOI 10.1086/706343
   Fezzi C, 2015, J ASSOC ENVIRON RESO, V2, P57, DOI 10.1086/680257
   Grotta AT, 2013, J FOREST, V111, P87, DOI 10.5849/jof.12-052
   Guo C, 2013, J ENVIRON ECON MANAG, V65, P452, DOI 10.1016/j.jeem.2012.12.003
   Hanewinkel M, 2013, NAT CLIM CHANGE, V3, P203, DOI [10.1038/NCLIMATE1687, 10.1038/nclimate1687]
   Hashida Y, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0230525
   Hashida Y, 2019, J ASSOC ENVIRON RESO, V6, P893, DOI 10.1086/704517
   Jones BA, 2017, ENVIRON MANAGE, V60, P809, DOI 10.1007/s00267-017-0930-4
   Kennedy RSH, 2004, FOREST ECOL MANAG, V200, P129, DOI 10.1016/j.foreco.2003.12.022
   KRINSKY I, 1986, REV ECON STAT, V68, P715, DOI 10.2307/1924536
   Latta G, 2010, FOREST ECOL MANAG, V259, P720, DOI 10.1016/j.foreco.2009.09.003
   Lawler JJ, 2014, P NATL ACAD SCI USA, V111, P7492, DOI 10.1073/pnas.1405557111
   Lawler JJ, 2009, ECOLOGY, V90, P588, DOI 10.1890/08-0823.1
   Lee DM, 2004, SOUTH ECON J, V70, P467, DOI 10.2307/4135326
   Lubowski RN, 2008, LAND ECON, V84, P529, DOI 10.3368/le.84.4.529
   Massetti E, 2018, REV ENV ECON POLICY, V12, P324, DOI 10.1093/reep/rey007
   McKenney DW, 2015, CAN J FOREST RES, V45, P1248, DOI 10.1139/cjfr-2015-0051
   Mendelsohn RO, 2017, REV ENV ECON POLICY, V11, P280, DOI 10.1093/reep/rex017
   Mihiar C., 2021, CLIMATE ADAPTATION V
   Ortiz-Bobea A, 2020, AM J AGR ECON, V102, P934, DOI 10.1093/ajae/aaz047
   Rehfeldt GE, 2014, FOREST ECOL MANAG, V324, P126, DOI 10.1016/j.foreco.2014.02.035
   Restaino CM, 2016, P NATL ACAD SCI USA, V113, P9557, DOI 10.1073/pnas.1602384113
   Reyer CPO, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa5ef1
   Sanford T, 2014, NAT CLIM CHANGE, V4, P164, DOI 10.1038/nclimate2148
   Schick T., 2020, BIG MONEY BOUGHT ORE
   Schlenker W, 2006, REV ECON STAT, V88, P113, DOI 10.1162/rest.2006.88.1.113
   Serra-Diaz JM, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-24642-2
   Severen C, 2018, J ENVIRON ECON MANAG, V89, P235, DOI 10.1016/j.jeem.2018.03.009
   Sims C, 2021, CLIM CHANG ECON, V12, DOI 10.1142/S2010007821500123
   SMALL KA, 1981, ECONOMETRICA, V49, P105, DOI 10.2307/1911129
   Sohngen B, 1998, AM ECON REV, V88, P686
   Sohngen B, 2020, ANNU REV RESOUR ECON, V12, P23, DOI 10.1146/annurev-resource-110419-010208
   Sohngen B, 2016, FOREST POLICY ECON, V72, P18, DOI 10.1016/j.forpol.2016.06.011
   St Clair JB, 2020, J FOREST, V118, P1, DOI 10.1093/jofore/fvz064
   Swanson M, 2005, SAV WASH WORK FOR LA, V19
   Thomas J, 2022, FOREST POLICY ECON, V135, DOI 10.1016/j.forpol.2021.102662
   Train KE, 2009, DISCRETE CHOICE METHODS WITH SIMULATION, 2ND EDITION, P1, DOI 10.1017/CBO9780511805271
   Weiskittel A. R., 2012, Schweizerische Zeitschrift fur Forstwesen, V163, P70, DOI 10.3188/szf.2012.0070
   Yousefpour R, 2017, ECOL SOC, V22, DOI 10.5751/ES-09614-220440
   Yousefpour R, 2012, ANN FOREST SCI, V69, P1, DOI 10.1007/s13595-011-0153-4
NR 46
TC 1
Z9 1
U1 3
U2 16
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0928-7655
EI 1873-0221
J9 RESOUR ENERGY ECON
JI Resour. Energy Econ.
PD MAY
PY 2022
VL 68
AR 101295
DI 10.1016/j.reseneeco.2022.101295
EA FEB 2022
PG 16
WC Economics; Energy & Fuels; Environmental Sciences; Environmental Studies
WE Social Science Citation Index (SSCI)
SC Business & Economics; Energy & Fuels; Environmental Sciences & Ecology
GA ZR7VV
UT WOS:000767988200004
OA hybrid
DA 2025-01-10
ER

PT J
AU Rampini, C
AF Rampini, Costanza
TI Climate and energy justice along the Brahmaputra river in Northeast
   India
SO ENVIRONMENT AND PLANNING E-NATURE AND SPACE
LA English
DT Article
DE Brahmaputra; floods; hydropower; climate adaptation; Northeast India
ID SUSTAINABLE ADAPTATION; HYDROPOWER DEVELOPMENT; SOLAR-ENERGY;
   VULNERABILITY; MANAGEMENT; POLITICS; FLOOD; POWER; DAMS; RESILIENCE
AB Recurrent summer floods along the Brahmaputra river and its tributaries are a major challenge for the people and state governments of Northeast India. While riverine communities in the region rely upon a variety of adaptation strategies to live with these destructive floods, climate change is expected to further exacerbate this challenge, as melting Himalayan glaciers and changes in the South Asian monsoon lead to an increase in the frequency of severe floods. At the same time, a multitude of new dams are under construction in the Brahmaputra river basin, to meet India's growing energy demands. Though these dams could provide flood protection for downstream communities, political and economic factors have led dam-builders to prioritize hydroelectricity generation over flood control. Furthermore, hydroelectricity generated along the Brahmaputra is "evacuated" to distant urban centers, while rural dwellers in Northeast India suffer from high levels of energy poverty. Using the Ranganadi Hydroelectric Project in Arunachal Pradesh as a case study, this paper examines how, by changing the flood regime and undermining current adaptive strategies, large dams along the Brahmaputra are testing the capacity of downstream communities to live with summer floods. This work highlights the ways in which poor and vulnerable communities in Northeast India are forced to bear the costs of both climate change impacts and decarbonization efforts.
C1 [Rampini, Costanza] San Jose State Univ, San Jose, CA 95192 USA.
C3 California State University System; San Jose State University
RP Rampini, C (corresponding author), San Jose State Univ, Dept Environm Studies, One Washington Sq, San Jose, CA 95192 USA.
EM costanza.rampini@sjsu.edu
OI Rampini, Costanza/0000-0002-8060-4386
FU United States Environmental Protection Agency Science to Achieve Results
   [FP 91724201]; University of California, Santa Cruz
FX The author(s) disclosed receipt of the following financial support for
   the research, authorship, and/or publication of this article: This
   research was funded by the United States Environmental Protection Agency
   Science to Achieve Results (FP 91724201), and by the University of
   California, Santa Cruz.
CR Adger WN, 2005, GLOBAL ENVIRON CHANG, V15, P77, DOI [10.1016/j.gloenvcha.2005.03.001, 10.1016/j.gloenvcha.2004.12.005]
   Ahlers R, 2015, EARTH SYST DYNAM, V6, P195, DOI 10.5194/esd-6-195-2015
   Alam S, 2016, J HYDROL ENG, V21, DOI 10.1061/(ASCE)HE.1943-5584.0001435
   Allison HE, 2004, ECOL SOC, V9
   Amrith SunilS., 2018, UNRULY WATERS RAINS
   Anderson D, 2015, WATER ENVIRON J, V29, P268, DOI 10.1111/wej.12101
   [Anonymous], 2018, Energy Statistics
   [Anonymous], 2019, DataBank | World Development Indicators
   [Anonymous], 2009, Local Responses to Too Much and Too Little Water in the Greater Himalayan Region
   [Anonymous], 2014, Handbook of Climate Change Adaptation, DOI DOI 10.1007/978-3-642-40455-9_114-1
   [Anonymous], 2007, 38984NP WORLD BANK
   Ansar A, 2014, ENERG POLICY, V69, P43, DOI 10.1016/j.enpol.2013.10.069
   Apurv T, 2015, J HYDROL, V527, P281, DOI 10.1016/j.jhydrol.2015.04.056
   Baka J, 2017, ANTIPODE, V49, P977, DOI 10.1111/anti.12219
   Baruah M., 2016, THESIS SYRACUSE U
   Baruah S., 2012, Economic and Political Weekly, V47, P41
   Baruah Sanjib., 2005, DURABLE DISORDER UND
   Baruah Sanjib., 2008, ECON POLIT WEEKLY, V43, P15
   Baruah Sanjib., 1999, INDIA ITSELF ASSAM P
   Bebbington Anthony., 2013, Subterranean Struggles: New Dynamics of Oil, Mining, and Gas in Latin America
   Bernard Harvey R., 2011, Research methods in anthropology Qualitative and quantitative approaches
   Bhattacharya S., 2018, CHINAS HYDROAMBITION
   Blaikie P., 1994, At Risk: Natural hazards, people's vulnerability, and disasters
   Bora AK, 2004, WTR SCI TEC LIBR, V47, P88
   Borgohain PL, 2019, INT J RIVER BASIN MA, V17, P25, DOI 10.1080/15715124.2018.1439497
   Branche E, 2017, CR PHYS, V18, P469, DOI 10.1016/j.crhy.2017.06.001
   Brooks N, 2009, DEV POLICY REV, V27, P741, DOI 10.1111/j.1467-7679.2009.00468.x
   Brown K, 2011, CLIM DEV, V3, P21, DOI 10.3763/cdev.2010.0062
   Cannon T, 2010, NAT HAZARDS, V55, P621, DOI 10.1007/s11069-010-9499-4
   Carboncopy.info, 2021, STAT HYDR POT DEV BA
   Castells-Quintana D, 2018, WORLD DEV, V104, P183, DOI 10.1016/j.worlddev.2017.11.016
   Chakraborty R, 2021, CURR OPIN ENV SUST, V51, P42, DOI 10.1016/j.cosust.2021.02.005
   Chakravartty, 2018, WIRE ENV        0822
   Chatterjee E, 2012, CONTEMP SOUTH ASIA, V20, P91, DOI 10.1080/09584935.2011.646072
   Chaube S.K., 1975, Social Scientist, V4, P40
   Chevallier R, 2010, CLIM DEV, V2, P191, DOI 10.3763/cdev.2010.0039
   Conway D, 2011, GLOBAL ENVIRON CHANG, V21, P227, DOI 10.1016/j.gloenvcha.2010.07.013
   Crow B, 2009, INDIA REV, V8, P306, DOI 10.1080/14736480903116826
   D'Souza R., 2006, Drowned and damned: Colonial capitalism and flood control in Eastern India
   Das P., 2012, ROLE POLICY I LOCAL, P43
   Das PJ., 2009, Adjusting to Floods on the Brahmaputra Plains, Assam, India Aranayak, Assam
   Davis AE, 2021, AUST J INT AFF, V75, P15, DOI 10.1080/10357718.2020.1787333
   Dharmadhikary S., 2008, Mountains of concrete: Dam building in the Himalayas
   DHAWAN BD, 1993, ECON POLIT WEEKLY, V28, P849
   Eakin HC, 2014, GLOBAL ENVIRON CHANG, V27, P1, DOI 10.1016/j.gloenvcha.2014.04.013
   Edwards R., 2013, What is qualitative interviewing?, P43
   Eriksen SH, 2007, CLIM POLICY, V7, P337, DOI 10.1080/14693062.2007.9685660
   Erlewein A, 2011, MT RES DEV, V31, P293, DOI 10.1659/MRD-JOURNAL-D-11-00054.1
   Ete M, 2018, GEOGRAPHIES OF DIFFERENCE: EXPLORATIONS IN NORTHEAST INDIAN STUDIES, P109
   Fahey S., 2016, Journal of Education for Sustainable Development, V10, P54, DOI DOI 10.1177/0973408215625534
   Folke C, 2005, ANNU REV ENV RESOUR, V30, P441, DOI 10.1146/annurev.energy.30.050504.144511
   Folke C, 2010, ECOL SOC, V15
   Gallopin GC, 2006, GLOBAL ENVIRON CHANG, V16, P293, DOI 10.1016/j.gloenvcha.2006.02.004
   Gamble R, 2019, THESIS ELEV, V150, P42, DOI 10.1177/0725513619826204
   Gambo K., 2015, ECON POLIT WEEKLY, V50, P10
   Gergan MD, 2020, POLIT GEOGR, V80, DOI 10.1016/j.polgeo.2020.102175
   Ghosh S, 2012, J EARTH SYST SCI, V121, P637, DOI 10.1007/s12040-012-0181-y
   Grumbine RE, 2013, SCIENCE, V339, P36, DOI 10.1126/science.1227211
   Gudmundsdóttir H, 2018, ENVIRON PLAN E-NAT, V1, P579, DOI 10.1177/2514848618796829
   GUHA Amalendu., 1977, PLANTER RAJ SWARAJ F
   Hanasz P, 2017, WATER ALTERN, V10, P459
   Hanasz P, 2015, INT J WATER GOV, V3, P9
   Healy N, 2019, ENERGY RES SOC SCI, V48, P219, DOI 10.1016/j.erss.2018.09.016
   Hijioka Y, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1327
   Hiren Gohain Hiren Gohain, 2008, Economic and Political Weekly, V43, P19
   Hornborg A, 2019, ENVIRON PLAN E-NAT, V2, P989, DOI 10.1177/2514848619863607
   Howarth Candice, 2017, Climate Services, V5, P3, DOI 10.1016/j.cliser.2017.04.003
   Huber A, 2019, WATER-SUI, V11, DOI 10.3390/w11030414
   Huber Amelie., 2017, CAPITALISM NATURE SO, V28, P48, DOI DOI 10.1080/10455752.2016.1225222
   Huber M, 2015, GEOGR COMPASS, V9, P327, DOI 10.1111/gec3.12214
   Huber MT, 2017, T I BRIT GEOGR, V42, P655, DOI 10.1111/tran.12182
   Huda MS, 2018, GEOFORUM, V96, P160, DOI 10.1016/j.geoforum.2018.08.015
   Hussain A, 2019, RENEW SUST ENERG REV, V107, P446, DOI 10.1016/j.rser.2019.03.010
   India Infoline News Service, 2015, POW GRID CORP COMM P
   Indian Chamber of Commerce (ICC), 2013, IND N E DIV GROWTH O
   IPCC, 2018, GLOB WARM 1 5C SUMM
   Jain S., 2021, Economic and Political Weekly, V56, P43
   Jiang HC, 2017, WATER POLICY, V19, P496, DOI 10.2166/wp.2017.056
   Cisneros BEJ, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P229
   Jones HP, 2012, NAT CLIM CHANGE, V2, P504, DOI 10.1038/NCLIMATE1463
   Kalita J., 2010, Downstream Impact Study of the ongoing Subansiri Lower Hydroelectric Power Project at Gerukamukh of National Hydroelectric Power Corporation Limited
   Karlsson BengtG., 2011, Unruly Hills: Nature and Nation in India's Northeast
   Klein RJT, 2010, NATO SCI PEACE SECUR, P157, DOI 10.1007/978-94-007-1770-1_9
   Kohli K., 2016, BUSINESS INTERESTS E
   Kumar D, 2014, RENEW SUST ENERG REV, V35, P101, DOI 10.1016/j.rser.2014.03.048
   Kurian N., 2013, WATER CONFLICTS NE I, P58
   Lakhanpal S, 2019, ENVIRON DEV, V30, P51, DOI 10.1016/j.envdev.2019.02.002
   Lemos MC, 2007, ECOL SOC, V12
   Malakar Y, 2019, ENERGY RES SOC SCI, V49, P16, DOI 10.1016/j.erss.2018.11.002
   McCarthy J, 2015, ENVIRON PLANN A, V47, P2485, DOI 10.1177/0308518X15602491
   McDuie-Ra D., 2016, Borderland City in New India: Frontier to Gateway
   McDuie-Ra D, 2011, ASIAN ETHN, V12, P77, DOI 10.1080/14631369.2011.538220
   McDuie-Ra Duncan, 2012, NE MIGRANTS DELHI RA
   Menon M., 2019, INFRASTRUCTURE DEV N
   Mirza MMQ, 2002, GLOBAL ENVIRON CHANG, V12, P127, DOI 10.1016/S0959-3780(02)00002-X
   Mishra A, 2019, HINDU KUSH HIMALAYA ASSESSMENT: MOUNTAINS, CLIMATE CHANGE, SUSTAINABILITY AND PEOPLE, P457, DOI 10.1007/978-3-319-92288-1_13
   Mohammed K, 2017, CLIMATIC CHANGE, V145, P159, DOI 10.1007/s10584-017-2073-2
   Mulvaney D., 2019, SOLAR POWER INNOVATI
   Mulvaney D, 2014, GEOFORUM, V54, P178, DOI 10.1016/j.geoforum.2014.01.014
   Nadeem S., 2012, ROLE POLICY I LOCAL, P21
   Nayo Apum Nayo Apum, 2015, Science and Culture, V81, P200
   Newell P, 2013, GEOGR J, V179, P132, DOI 10.1111/geoj.12008
   Nishat A., 2000, INT NEGOTIAITION, V5, P289, DOI [DOI 10.1023/A:1009851418477, 10.1023/A:1009851418477]
   NRSC ISRO and ASDMA, 2016, Flood hazard atlas for Assam state (1998-2015)
   Olivier JosG. J., 2015, TRENDS GLOBAL CO2 EM
   Pahuja S., 2006, A fluvial geomorphology perspective on the knowledge base of the Brahmaputra
   Pandey R, 2017, ECOL INDIC, V79, P338, DOI 10.1016/j.ecolind.2017.03.047
   Pelling M, 2005, GLOBAL ENVIRON CHANG, V15, P308, DOI 10.1016/j.gloenvcha.2005.02.001
   Perlik M., 2015, J ALPINE RES, V103, DOI 10.4000/rga.3142
   Phadke R, 2011, ANTIPODE, V43, P754, DOI 10.1111/j.1467-8330.2011.00881.x
   Phanindra Goyari Phanindra Goyari, 2005, Economic and Political Weekly, V40, P2723
   Pielke R, 2007, NATURE, V445, P597, DOI 10.1038/445597a
   Pritchard B, 2014, AUST GEOGR, V45, P325, DOI 10.1080/00049182.2014.930001
   PTI, 2017, AD REV SHAR FORM PAY
   Rahaman Muhammad Mizanur, 2012, International Journal of Sustainable Society, V4, P131, DOI 10.1504/IJSSOC.2012.044670
   Rahaman MM, 2009, WATER POLICY, V11, P168, DOI 10.2166/wp.2009.012
   Rahaman MM, 2009, NAT RESOUR FORUM, V33, P60, DOI 10.1111/j.1477-8947.2009.01209.x
   Rahman M.M., 2010, Journal of Science Foundation, V8, P1
   Rahman MM, 2020, DELTAS IN THE ANTHROPOCENE, P23, DOI 10.1007/978-3-030-23517-8_2
   Rahman MATMT, 2015, CLIM DEV, V7, P185, DOI 10.1080/17565529.2014.910163
   Rahman Mirza Zulfiqur, 2019, PICKLED INFRASTRUCTU
   Rampini C., 2016, THESIS
   Rampini C., 2021, POLITICAL EC HYDROPO, P235, DOI DOI 10.1007/978-3-030-59361-2_12
   Ray PA, 2015, ENVIRON SCI POLICY, V54, P64, DOI [10.1016/j.envsci.2015.06.015, 10.1016/j.e]
   Rignall KE, 2016, ENVIRON PLANN A, V48, P540, DOI 10.1177/0308518X15619176
   Rotberg FJY, 2010, CLIM DEV, V2, P65, DOI 10.3763/cdev.2010.0031
   Runhaar H, 2018, REG ENVIRON CHANGE, V18, P1201, DOI 10.1007/s10113-017-1259-5
   Saikia A., 2019, The Unquiet River: A Biography of the Brahmaputra, DOI [10.1093/oso/9780199468119.001.0001, DOI 10.1093/OSO/9780199468119.001.0001]
   Saikia A., 2011, Forests and ecological history of assam, 1826-2000
   Samaranayake N., 2016, WATER RESOURCE COMPE
   Sareen S, 2018, ENERGY RES SOC SCI, V41, P270, DOI 10.1016/j.erss.2018.03.023
   Sarma Maitreyee, 2015, Journal of Human Ecology, V49, P129
   Shimrah T, 2017, INT SCHOLARLY SCI RE, V11, P671
   Siamanta ZC, 2019, ENVIRON PLAN E-NAT, V2, P274, DOI 10.1177/2514848619835156
   Sovacool BK, 2017, ENERG POLICY, V105, P677, DOI 10.1016/j.enpol.2017.03.005
   Sovacool BK, 2011, CLIM POLICY, V11, P1177, DOI 10.1080/14693062.2011.579315
   Subba T. B., 2013, The Modern Anthropology of India: Ethnography, Themes and Theory, P193
   TOBLER WR, 1970, ECON GEOGR, V46, P234, DOI 10.2307/143141
   Vagholikar N., 2010, Damming Northeast India: juggernaut of hydropower projects threatens social and environmental security of the region
   Vij S, 2020, WATER INT, V45, P254, DOI 10.1080/02508060.2018.1554767
   Water for Welfare Secretariat, 2008, HYDR POL GUID IND I
   Watts Michael., 2004, Geopolitics, V9, P50, DOI DOI 10.1080/14650040412331307832
   White GF., 2001, GLOB ENV CHANGE PART, V3, P81, DOI DOI 10.1016/S1464-2867(01)00021-3
   Yaro JA, 2015, CLIM DEV, V7, P235, DOI 10.1080/17565529.2014.951018
   Yenneti K, 2016, GEOFORUM, V76, P90, DOI 10.1016/j.geoforum.2016.09.004
   Yenneti K, 2015, ENERG POLICY, V86, P664, DOI 10.1016/j.enpol.2015.08.019
NR 146
TC 7
Z9 7
U1 3
U2 11
PU SAGE PUBLICATIONS INC
PI THOUSAND OAKS
PA 2455 TELLER RD, THOUSAND OAKS, CA 91320 USA
SN 2514-8486
EI 2514-8494
J9 ENVIRON PLAN E-NAT
JI Environ. Plan. E-Nat. Space
PD DEC
PY 2022
VL 5
IS 4
SI SI
BP 1919
EP 1946
DI 10.1177/25148486211032042
EA SEP 2021
PG 28
WC Environmental Studies; Geography
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geography
GA 6I6DZ
UT WOS:000849106000001
DA 2025-01-10
ER

PT J
AU Torabi, N
   Cooke, B
   Bekessy, SA
AF Torabi, Nooshin
   Cooke, Benjamin
   Bekessy, Sarah A.
TI The Role of Social Networks and Trusted Peers in Promoting Biodiverse
   Carbon Plantings
SO AUSTRALIAN GEOGRAPHER
LA English
DT Article
DE trust; carbon farming; private land conservation; biodiverse carbon
   plantings; social capital; social networks; Biodiversity
ID CLIMATE-CHANGE; ECOLOGICAL RESTORATION; RURAL AUSTRALIA; LOCAL
   KNOWLEDGE; CONSERVATION; FARMERS; MANAGEMENT; LANDSCAPE; COMMUNITY;
   LANDCARE
AB Social capital has the potential to influence the success of biodiverse carbon plantings in the face of uncertainty amongst rural landholders about the need or efficacy of efforts to address climate change through tree planting. We conducted 17 face-to-face semi-structured interviews with landholders in Victoria, Australia who voluntarily participate in biodiverse carbon plantings on their land, focusing in particular on the role of social capital for understanding how 'early adopters' can advocate for programs locally. The interviews revealed the importance of social networks and the profound impact of trusted peers on the diffusion of carbon planting schemes. These social capital dimensions are especially important for shaping ongoing participation and the ways in which participants become active agents in trusted relationships that influence the participation of others. Our results suggest that the positive impact of social networks can counteract doubts about the validity of climate adaptation responses such as carbon planting, and enable landholders to connect the program with their existing stewardship motivations. The ability for early adopters of the program to demonstrate the physical materialisation of their plantings to others was vital to this process. We propose that targeting champions and trusted peers in local communities could accelerate the proliferation of biodiverse carbon planting schemes.
C1 [Torabi, Nooshin; Cooke, Benjamin; Bekessy, Sarah A.] RMIT Univ Melbourne, Sch Global Urban & Social Studies, Interdisciplinary Conservat Sci Res Grp, Melbourne, Vic, Australia.
C3 Royal Melbourne Institute of Technology (RMIT)
RP Torabi, N (corresponding author), RMIT Univ Melbourne, Sch Global Urban & Social Studies, Interdisciplinary Conservat Sci Res Grp, Melbourne, Vic, Australia.
EM nooshin.torabi@rmit.edu.au
RI Torabi, Nooshin/AAD-3220-2019; Cooke, Benjamin/S-3603-2019
OI Cooke, Benjamin/0000-0002-8845-7966; Bekessy, Sarah/0000-0002-0503-1979;
   Torabi, Dr Nooshin/0000-0002-5834-4477
FU Australian government's National Environmental Science Program
   (Threatened Species Recovery Hub); Australian Research Council Centre of
   Excellence for Environmental Decisions; ARC Future Fellowship
FX This research was conducted with the support of funding from the
   Australian government's National Environmental Science Program
   (Threatened Species Recovery Hub) and the Australian Research Council
   Centre of Excellence for Environmental Decisions. Sarah Bekessy is
   supported by an ARC Future Fellowship. The authors also acknowledge
   Greenfleet's assistance in providing data on their environmental
   planting sites.
CR Abbott S, 2008, J HEALTH PSYCHOL, V13, P874, DOI 10.1177/1359105308095060
   Adger WN, 2003, ECON GEOGR, V79, P387
   Almedom AM, 2005, SOC SCI MED, V61, P943, DOI 10.1016/j.socscimed.2004.12.025
   [Anonymous], 2013, MOL CELLULAR BIOCH
   [Anonymous], 2003, POSTMODERN INTERVIEW
   Arbuckle JG, 2013, CLIMATIC CHANGE, V117, P943, DOI 10.1007/s10584-013-0707-6
   Bäckstrand K, 2006, GLOBAL ENVIRON POLIT, V6, P50
   Torres AB, 2010, ECOL ECON, V69, P469, DOI 10.1016/j.ecolecon.2009.09.007
   Barlow K, 2003, J RURAL STUD, V19, P503, DOI 10.1016/S0743-0167(03)00029-9
   Bathelt H, 2004, PROG HUM GEOG, V28, P31, DOI 10.1191/0309132504ph469oa
   Bauhus J., 2010, Ecosystem goods and services from plantation forests
   Baumgart-Getz A, 2012, J ENVIRON MANAGE, V96, P17, DOI 10.1016/j.jenvman.2011.10.006
   Bodin Ö, 2009, GLOBAL ENVIRON CHANG, V19, P366, DOI 10.1016/j.gloenvcha.2009.05.002
   Boyatzis R. E., 1998, Transforming qualitative information: Thematic analysis and code development
   Bradshaw CJA, 2013, BIOL CONSERV, V161, P71, DOI 10.1016/j.biocon.2013.02.012
   Braun V, 2021, QUAL RES PSYCHOL, V18, P328, DOI 10.1080/14780887.2020.1769238
   Breetz HL, 2005, LAND ECON, V81, P170, DOI 10.3368/le.81.2.170
   Buys L, 2012, REG ENVIRON CHANGE, V12, P237, DOI 10.1007/s10113-011-0253-6
   CAMPBELL CA, 1995, J SOIL WATER CONSERV, V50, P125
   Campos J.J., 2005, Forests in the global balance-changing paradigms, P97
   Carswell Fiona, 2006, New Zealand Journal of Forestry, V51, P31
   COLEMAN JS, 1988, AM J SOCIOL, V94, pS95, DOI 10.1086/228943
   Compton E, 2012, J RURAL STUD, V28, P149, DOI 10.1016/j.jrurstud.2011.12.004
   Connor LH, 2013, GLOBAL ENVIRON CHANG, V23, P1852, DOI 10.1016/j.gloenvcha.2013.07.002
   Cooke B, 2015, LANDSCAPE URBAN PLAN, V134, P43, DOI 10.1016/j.landurbplan.2014.10.006
   Cooper S, 2009, EMERG MED J, V26, P773, DOI 10.1136/emj.2008.071159
   Crona BI, 2006, ECOL SOC, V11
   Crossman ND, 2011, CONSERV BIOL, V25, P835, DOI 10.1111/j.1523-1739.2011.01649.x
   Curtis A, 2002, J AM WATER RESOUR AS, V38, P1207, DOI 10.1111/j.1752-1688.2002.tb04342.x
   Curtis A, 2000, AUST GEOGR, V31, P349, DOI 10.1080/713612253
   Dougill AJ, 2010, ECOL SOC, V15
   Fischer AP, 2009, SOC NATUR RESOUR, V22, P884, DOI 10.1080/08941920802314926
   Fisher R, 2013, J RURAL STUD, V31, P13, DOI 10.1016/j.jrurstud.2013.02.006
   FUKUYAMA F, 1995, FOREIGN AFF, V74, P89, DOI 10.2307/20047302
   George SJ, 2012, AGR ECOSYST ENVIRON, V163, P28, DOI 10.1016/j.agee.2012.06.022
   Gill N, 2014, T I BRIT GEOGR, V39, P265, DOI 10.1111/tran.12025
   Gill N, 2010, J ENVIRON PLANN MAN, V53, P317, DOI 10.1080/09640561003612890
   Harrington C, 2006, AUST GEOGR, V37, P187, DOI 10.1080/00049180600672342
   Hogan A., 2010, Decisions made by farmers that relate to climate change. Australian Government: Rural Industries Research and Development Corp. Report
   Hunt C, 2008, ECOL ECON, V66, P309, DOI 10.1016/j.ecolecon.2007.09.012
   Knapp CN, 2009, RANGELAND ECOL MANAG, V62, P500, DOI 10.2111/08-175.1
   Lachapelle PR, 2012, SOC NATUR RESOUR, V25, P321, DOI 10.1080/08941920.2011.569855
   Lederer M, 2011, ECOL ECON, V70, P1900, DOI 10.1016/j.ecolecon.2011.02.003
   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
   MAYER RC, 1995, ACAD MANAGE REV, V20, P709, DOI 10.2307/258792
   Meadows J, 2013, SOC NATUR RESOUR, V26, P745, DOI 10.1080/08941920.2012.719586
   Measham TG, 2007, AUST GEOGR, V38, P145, DOI 10.1080/00049180701392758
   Mills J, 2012, J RURAL STUD, V28, P612, DOI 10.1016/j.jrurstud.2012.08.001
   Moore ML, 2011, ECOL SOC, V16
   Pannell DJ, 2006, AUST J EXP AGR, V46, P1407, DOI 10.1071/EA05037
   Pearce D., 2005, World Econ, V6, P57
   Prell C, 2009, SOC NATUR RESOUR, V22, P501, DOI 10.1080/08941920802199202
   Pretty J, 2001, WORLD DEV, V29, P209, DOI 10.1016/S0305-750X(00)00098-X
   Putnam R.D., 1993, Making Democracy Work: Civic Traditions in Modern Italy
   Rejesus R. M., 2013, Journal of Agricultural and Applied Economics, V45, P701
   Rice P., 1999, QUALITATIVE RES METH
   Riley M, 2006, J RURAL STUD, V22, P337, DOI 10.1016/j.jrurstud.2005.10.005
   Robertson M, 2016, REG ENVIRON CHANGE, V16, P189, DOI 10.1007/s10113-014-0743-4
   Rochecouste JF, 2015, AGR SYST, V135, P20, DOI 10.1016/j.agsy.2014.12.002
   Sabto M., 2011, 160 ECOS
   Safi AS, 2012, RISK ANAL, V32, P1041, DOI 10.1111/j.1539-6924.2012.01836.x
   Saunders D., 1998, REFORM, V6, P11
   Sharp EA, 2013, J ENVIRON PLANN MAN, V56, P1246, DOI 10.1080/09640568.2012.717052
   Smith FP, 2008, LANDSCAPE URBAN PLAN, V86, P66, DOI 10.1016/j.landurbplan.2007.12.008
   Smith JW, 2013, SOC NATUR RESOUR, V26, P452, DOI 10.1080/08941920.2012.678465
   Sobels J, 2001, J RURAL STUD, V17, P265, DOI 10.1016/S0743-0167(01)00003-1
   SoE, 2008, STAT ENV VICT 2008 4
   SoE, 2013, VICT STAT ENV REP 20
   Stephenson G., 2003, J EXTENSION, V41, P4
   Strauss A., 1967, DISCOV GROUNDED THEO
   Sutherland LA, 2011, SOCIOL RURALIS, V51, P238, DOI 10.1111/j.1467-9523.2011.00536.x
   Tarnoczi TJ, 2010, CLIMATIC CHANGE, V98, P299, DOI 10.1007/s10584-009-9762-4
   Trigger D, 2008, GEOFORUM, V39, P1273, DOI 10.1016/j.geoforum.2007.05.010
   Trigger DS, 2010, SOC NATUR RESOUR, V23, P1060, DOI 10.1080/08941920903232902
   UPHOFF N, 1993, WORLD DEV, V21, P607, DOI 10.1016/0305-750X(93)90113-N
   van Noordwijk M., 2011, How trees and people can co-adapt to climate change: reducing vulnerability through multifunctional agroforestry landscapes
   Whitmarsh L, 2011, GLOBAL ENVIRON CHANG, V21, P690, DOI 10.1016/j.gloenvcha.2011.01.016
   Willy DK, 2013, ECOL ECON, V90, P94, DOI 10.1016/j.ecolecon.2013.03.008
NR 78
TC 11
Z9 11
U1 3
U2 28
PU ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
SN 0004-9182
EI 1465-3311
J9 AUST GEOGR
JI Aust. Geogr.
PD APR 2
PY 2016
VL 47
IS 2
BP 139
EP 156
DI 10.1080/00049182.2016.1154535
PG 18
WC Geography
WE Social Science Citation Index (SSCI)
SC Geography
GA DI0VB
UT WOS:000373214300001
OA Green Accepted
DA 2025-01-10
ER

PT J
AU Sisodia, S
   Singh, BN
AF Sisodia, Seema
   Singh, Bashisth N.
TI Influence of developmental temperature on cold shock and chill coma
   recovery in <i>Drosophila ananassae</i>: Acclimation and latitudinal
   variations among Indian populations
SO JOURNAL OF THERMAL BIOLOGY
LA English
DT Article
DE Latitudinal variations; Chill-coma recovery; Cold acclimation; Growth
   temperatures; Adaptive plasticity; Drosophila ananassae
ID LIFE-HISTORY TRAITS; NATURAL-POPULATIONS; PHENOTYPIC PLASTICITY;
   CLIMATIC ADAPTATION; STRESS RESISTANCE; ADULT DROSOPHILA; MELANOGASTER;
   TOLERANCE; GENETICS; CLINES
AB Exposure of various Drosophila species to mild increase or decrease in temperature has consistently been shown to result in increased resistance to subsequent temperature extremes. We investigated cold tolerance in 45 Indian natural populations of Drosophila ananassae collected from all over India by monitoring the time taken by adults to recover from chill-coma after a treatment for 16 h at 4 C. Significant latitudinal and altitudinal differentiation was observed for chill coma recovery in D. ananassae. Chill-coma recovery was closely associated with local climatic factors like average annual temperature and relative humidity of origin of populations.
   Role of growth temperature on chill-coma recovery was also analyzed. In all cases, recovery time decreased when growth temperature was lowered and linear reaction norms were observed. Populations from higher latitudes were more cold resistance than low latitude populations. Our results also suggest that within species cold adaptation and response may vary with latitude as a consequence of direct or indirect effects of selection. Our study extends evidence for a higher cold tolerance in north Indian populations that seems to have evolved during the colonization of D. ananassae and supports the hypothesis of an adaptive response of plasticity to the experienced environment. (C) 2010 Elsevier Ltd. All rights reserved.
C1 [Sisodia, Seema; Singh, Bashisth N.] Banaras Hindu Univ, Genet Lab, Dept Zool, Varanasi 221005, Uttar Pradesh, India.
C3 Banaras Hindu University (BHU)
RP Singh, BN (corresponding author), Banaras Hindu Univ, Genet Lab, Dept Zool, Varanasi 221005, Uttar Pradesh, India.
EM bnsingh@bhu.ac.in
RI Singh, Akanksha/AAF-6177-2021
FU Department of Science and Technology, New Delhi
FX Financial assistance in the form of Fast Track Young Scientist Research
   Project from the Department of Science and Technology, New Delhi to SS
   is gratefully acknowledged. The authors thank Prof. V. Loeschcke for his
   valuable suggestions during the course of this study, Dr. Pranveer Singh
   for his diversified collections of D. ananassae flies and two anonymous
   reviewers for their helpful comments on the original draft of the
   manuscript.
CR Addo-Bediako A, 2000, P ROY SOC B-BIOL SCI, V267, P739, DOI 10.1098/rspb.2000.1065
   Anderson AR, 2005, GENET RES, V85, P15, DOI 10.1017/S0016672304007281
   [Anonymous], 1983, The genetics and biology of Drosophila
   Ayrinhac A, 2004, FUNCT ECOL, V18, P700, DOI 10.1111/j.0269-8463.2004.00904.x
   Chown SL, 2003, ECOGRAPHY, V26, P445, DOI 10.1034/j.1600-0587.2003.03479.x
   Collinge JE, 2006, J EVOLUTION BIOL, V19, P473, DOI 10.1111/j.1420-9101.2005.01016.x
   David JR, 1997, J THERM BIOL, V22, P441, DOI 10.1016/S0306-4565(97)00063-6
   DAVID JR, 1975, NATURE, V257, P588, DOI 10.1038/257588a0
   David RJ, 1998, J THERM BIOL, V23, P291, DOI 10.1016/S0306-4565(98)00020-5
   Endler J.A., 1977, Monographs in Population Biology, pi
   Gibert P, 2001, EVOLUTION, V55, P1063, DOI 10.1554/0014-3820(2001)055[1063:CCTAMC]2.0.CO;2
   Hallas R, 2002, GENET RES, V79, P141, DOI 10.1017/S0016672301005523
   HOFFMANN AA, 1993, AM NAT, V142, pS93, DOI 10.1086/285525
   Hoffmann AA, 2003, J THERM BIOL, V28, P175, DOI 10.1016/S0306-4565(02)00057-8
   Hoffmann AA, 2002, ECOL LETT, V5, P614, DOI 10.1046/j.1461-0248.2002.00367.x
   Karan D, 1998, EVOLUTION, V52, P825, DOI 10.1111/j.1558-5646.1998.tb03706.x
   KIMURA MT, 1994, J NAT HIST, V28, P401, DOI 10.1080/00222939400770181
   KIMURA MT, 1988, EVOLUTION, V42, P1288, DOI [10.2307/2409012, 10.1111/j.1558-5646.1988.tb04188.x]
   Leather SR., 1993, ECOLOGY INSECT OVERW
   Macdonald SS, 2004, J INSECT PHYSIOL, V50, P695, DOI 10.1016/j.jinsphys.2004.05.004
   MAGLAFOLOU A, 2002, J EVOLUTION BIOL, V15, P763
   Palo JU, 2003, MOL ECOL, V12, P1963, DOI 10.1046/j.1365-294X.2003.01865.x
   Parkash R, 1999, J ZOOL SYST EVOL RES, V37, P133
   Parkash R, 2008, J INSECT PHYSIOL, V54, P1050, DOI 10.1016/j.jinsphys.2008.04.008
   Robinson SJW, 2000, EVOLUTION, V54, P1819, DOI 10.1111/j.0014-3820.2000.tb00726.x
   Sarup P, 2006, HEREDITY, V96, P479, DOI 10.1038/sj.hdy.6800828
   SCHENKER R, 1984, REV ECOL BIOL SOL, V21, P205
   SINGH BN, 1986, GENETICA, V69, P143, DOI 10.1007/BF00115134
   Singh BN, 2000, CURR SCI INDIA, V78, P391
   Singh P, 2007, GENET RES, V89, P191, DOI 10.1017/S0016672307008890
   Singh Pranveer, 2010, International Journal of Biology, V2, P19
   Singh P, 2008, GENET RES, V90, P409, DOI 10.1017/S0016672308009737
   Sisodia S, 2002, GENETICA, V114, P95, DOI 10.1023/A:1014640604740
   Sisodia S, 2006, CAN J ZOOL, V84, P895, DOI 10.1139/Z06-075
   Sisodia S, 2009, J BIOSCIENCES, V34, P263, DOI 10.1007/s12038-009-0030-6
   Sorensen JG, 2005, J EVOLUTION BIOL, V18, P829, DOI 10.1111/j.1420-9101.2004.00876.x
   STANLEY SM, 1980, AUST J ZOOL, V28, P413, DOI 10.1071/ZO9800413
   Vishalakshi C, 2008, J THERM BIOL, V33, P201, DOI 10.1016/j.jtherbio.2007.09.004
   Yadav JP, 2005, J THERM BIOL, V30, P457, DOI 10.1016/j.jtherbio.2005.05.007
   Zar JH, 2005, BIOSTATISTICAL ANAL
NR 40
TC 24
Z9 28
U1 1
U2 17
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0306-4565
EI 1879-0992
J9 J THERM BIOL
JI J. Therm. Biol.
PD APR
PY 2010
VL 35
IS 3
BP 117
EP 124
DI 10.1016/j.jtherbio.2010.01.001
PG 8
WC Biology; Zoology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Life Sciences & Biomedicine - Other Topics; Zoology
GA 579MF
UT WOS:000276374100001
DA 2025-01-10
ER

PT J
AU Dufour, P
   Carande, JG
   Renaud, J
   Renoult, JP
   Lavergne, S
   Crochet, PA
AF Dufour, Paul
   Guerra Carande, Julia
   Renaud, Julien
   Renoult, Julien P.
   Lavergne, Sebastien
   Crochet, Pierre-Andre
TI Plumage colouration in gulls responds to their non-breeding climatic
   niche
SO GLOBAL ECOLOGY AND BIOGEOGRAPHY
LA English
DT Article
DE biogeography; bird colouration; Bogert's rule; Gloger's rule; migration
   distance; photoprotection; thermoregulation
ID PHYLOGENETIC-RELATIONSHIPS; SEXUAL SELECTION; HISTORY; BIRDS; RULE
AB Aim Global variation in animal colouration has inspired ecogeographical rules that suggest common patterns of recurrent adaptations to climate. However, little attention has been paid to the relative influence of the different climatic conditions encountered by species during their annual life cycle. We explored this question by testing whether breeding or non-breeding climatic conditions most influence plumage colouration in gulls, a cosmopolitan group of birds with extensive variation in plumage darkness and seasonal migratory strategies. Location Global. Time period Contemporary. Major taxa studied All species and subspecies of gulls (Aves, Laridae). Methods We used literature data and digital images to assess two characteristics of plumage colouration in all 80 species and subspecies of gulls: the darkness of the mantle and the proportion of black on wingtips. For each species and subspecies, we collected data on migration distance and environmental variables across its breeding and non-breeding range for both breeding and non-breeding seasons. We performed a phylogenetic comparative analysis to quantify the relative influence of climatic conditions experienced during the breeding and non-breeding season on plumage colouration. Results The climatic conditions encountered during the non-breeding season explained interspecific variation in colouration better than the climate experienced during the breeding season. In accordance with hypotheses on the role of dark colouration in thermoregulation and feather protection, darker mantle colouration was positively correlated with insolation and negatively with air temperature. The proportion of black on wingtips was greater for long distance migrants wintering under insolated conditions than short distance migrants or residents occupying less insolated regions. Main conclusions In gulls, plumage colouration is predominantly shaped by selection experienced outside the breeding period, in accordance with the hypothesized photoprotective and thermoregulatory functions of avian plumage. This highlights the importance of taking into account seasonality and migration to understand global spatial patterns of avian colouration.
C1 [Dufour, Paul; Guerra Carande, Julia; Renaud, Julien; Lavergne, Sebastien] Univ Savoie Mt Blanc, Univ Grenoble Alpes, CNRS, Lab Ecol Alpine LECA, Grenoble, France.
   [Renoult, Julien P.; Crochet, Pierre-Andre] Univ Paul Valery Montpellier 3, Univ Montpellier, CEFE, CNRS,EPHE,IRD, Montpellier, France.
C3 Universite Savoie Mont Blanc; Communaute Universite Grenoble Alpes;
   Universite Grenoble Alpes (UGA); Centre National de la Recherche
   Scientifique (CNRS); Universite PSL; Ecole Pratique des Hautes Etudes
   (EPHE); Institut Agro; Montpellier SupAgro; CIRAD; Centre National de la
   Recherche Scientifique (CNRS); Institut de Recherche pour le
   Developpement (IRD); Universite Paul-Valery; Universite de Montpellier
RP Dufour, P (corresponding author), Univ Grenoble Alpes, Lab Ecol Alpine, CNRS, UMR 5553,USMB, CS 40700, F-38058 Grenoble 9, France.
EM paul.dufour80@gmail.com
OI Guerra Carande, Julia/0000-0002-7398-3402
FU LabEx OSUG@2020 (Investissements d'avenir) [ANR10LABX56]
FX We would like to thank the ornithologist and artist Lars Jonsson, who
   first suggested that climate during the non-breeding period determines
   gull colouration during a conversation with Pierre-Andre Crochet on
   Gotland in 1999. We also thank Daniele Occhiato, and all photographers
   and enthusiasts in gull identification (http://www.gull-research.org/)
   who have enriched the internet with photographs of live gulls. This work
   was supported by a PhD grant to P. D. awarded by the LabEx OSUG@2020
   (Investissements d'avenir -ANR10LABX56).
CR [Anonymous], 2006, Biogeography
   [Anonymous], 2019, HDB BIRDS WORLD ALIV
   [Anonymous], 1929, PRINZIP GEOGRAPHISCH, DOI DOI 10.1038/124753A0
   BERGMAN G, 1982, Ornis Fennica, V59, P77
   BirdLife International and Handbook of the Birds of the World, 2018, BIRD SPEC DISTR MAPS
   BOGERT CM, 1949, EVOLUTION, V3, P195, DOI 10.2307/2405558
   BONSER RHC, 1995, CONDOR, V97, P590, DOI 10.2307/1369048
   Borgudd J., 2003, TVSM5121 LUND 365 TU
   BRETAGNOLLE V, 1993, AM NAT, V142, P141, DOI 10.1086/285532
   Burger J., 2019, HDB BIRDS WORLD ALIV
   Burtt EH, 2004, CONDOR, V106, P681, DOI 10.1650/7383
   Clark PU, 2009, SCIENCE, V325, P710, DOI 10.1126/science.1172873
   Clusella Trullas S, 2007, J THERM BIOL, V32, P235, DOI 10.1016/j.jtherbio.2007.01.013
   Cuthill IC, 2017, SCIENCE, V357, DOI 10.1126/science.aan0221
   Dale J, 2015, NATURE, V527, P367, DOI 10.1038/nature15509
   Dalrymple RL, 2018, ECOL MONOGR, V88, P204, DOI 10.1002/ecm.1287
   del Hoyo J., 2014, Non-passerines, V1
   Delhey K, 2019, BIOL REV, V94, P1294, DOI 10.1111/brv.12503
   Delhey K, 2019, ECOL LETT, V22, P726, DOI 10.1111/ele.13233
   Delhey K, 2018, ECOGRAPHY, V41, P673, DOI 10.1111/ecog.03040
   Dufour P, 2020, J BIOGEOGR, V47, P155, DOI 10.1111/jbi.13700
   Eyres A, 2017, J AVIAN BIOL, V48, P1517, DOI 10.1111/jav.01308
   Friedman NR, 2017, GLOBAL ECOL BIOGEOGR, V26, P261, DOI 10.1111/geb.12522
   Galván I, 2018, FUNCT ECOL, V32, P1531, DOI 10.1111/1365-2435.13094
   Gaston KJ, 2008, J BIOGEOGR, V35, P483, DOI 10.1111/j.1365-2699.2007.01772.x
   Gay L, 2009, HEREDITY, V102, P133, DOI 10.1038/hdy.2008.99
   Gilg O, 2010, J AVIAN BIOL, V41, P532, DOI 10.1111/j.1600-048X.2010.05125.x
   Gloger CL., 1833, ABANDERN VOGEL DURCH
   Goldstein G, 2004, AUK, V121, P656, DOI 10.1642/0004-8038(2004)121[0656:BDOBAW]2.0.CO;2
   GROJEAN RE, 1980, APPL OPTICS, V19, P339, DOI 10.1364/AO.19.000339
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Hill GE, 2006, AVIAN CONSERV ECOL, V1
   Ho LST, 2014, SYST BIOL, V63, P397, DOI 10.1093/sysbio/syu005
   Howell SNG., 2007, Gulls of the Americas
   Indykiewicz P, 2017, BEHAV ECOL SOCIOBIOL, V71, DOI 10.1007/s00265-017-2411-4
   Jacobsen L.B., 2017, Animal Biotelemetry, V5, P4, DOI DOI 10.1186/S40317-017-0119-X
   Jetz W, 2012, NATURE, V491, P444, DOI 10.1038/nature11631
   Karger DN, 2017, SCI DATA, V4, DOI 10.1038/sdata.2017.122
   KETTLEWELL H D, 1961, ANNU REV ENTOMOL, V6, P245
   Lai YC, 2008, J ZOOL, V274, P270, DOI 10.1111/j.1469-7998.2007.00382.x
   Liebers D, 2004, P ROY SOC B-BIOL SCI, V271, P893, DOI 10.1098/rspb.2004.2679
   Liebers D, 2002, J EVOLUTION BIOL, V15, P1021, DOI 10.1046/j.1420-9101.2002.00454.x
   LUSTICK S, 1978, SCIENCE, V200, P81, DOI 10.1126/science.635577
   Malling Olsen K., 2018, GULLS WORLD PHOTOGRA
   Marques PAM, 2009, ACTA ETHOL, V12, P87, DOI 10.1007/s10211-009-0060-y
   McQueen A, 2019, ECOL LETT, V22, P1838, DOI 10.1111/ele.13375
   Miller ET, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-09721-w
   Minias P, 2020, J EVOLUTION BIOL, V33, P682, DOI 10.1111/jeb.13604
   Pagel M, 1999, NATURE, V401, P877, DOI 10.1038/44766
   Paradis E, 2019, BIOINFORMATICS, V35, P526, DOI 10.1093/bioinformatics/bty633
   Pons JM, 2014, HEREDITY, V112, P226, DOI 10.1038/hdy.2013.98
   Pons JM, 2005, MOL PHYLOGENET EVOL, V37, P686, DOI 10.1016/j.ympev.2005.05.011
   Rappole J. H., 2013, AVIAN MIGRANT
   Revell LJ, 2012, METHODS ECOL EVOL, V3, P217, DOI 10.1111/j.2041-210X.2011.00169.x
   REYNOLDS PS, 1981, INT J BIOMETEOROL, V25, P299, DOI 10.1007/BF02198245
   Roulin A, 2004, IBIS, V146, P509, DOI 10.1111/j.1474-919x.2004.00292.x
   Roulin A, 2009, J EVOLUTION BIOL, V22, P345, DOI 10.1111/j.1420-9101.2008.01651.x
   Schielzeth H, 2010, METHODS ECOL EVOL, V1, P103, DOI 10.1111/j.2041-210X.2010.00012.x
   Schliep KP, 2011, BIOINFORMATICS, V27, P592, DOI 10.1093/bioinformatics/btq706
   Schneider CA, 2012, NAT METHODS, V9, P671, DOI 10.1038/nmeth.2089
   Sonsthagen SA, 2016, MOL PHYLOGENET EVOL, V103, P41, DOI 10.1016/j.ympev.2016.06.008
   Stenhouse IJ, 2012, IBIS, V154, P42, DOI 10.1111/j.1474-919X.2011.01180.x
   Sternkopf V., 2010, THESIS
   Székely T, 2004, P NATL ACAD SCI USA, V101, P12224, DOI 10.1073/pnas.0404503101
   Team R. C. R., 2019, LANG ENV STAT COMP
   The GIMP Development Team, 2019, GIMP
   Voitkevitch A. A., 1966, FEATHERS PLUMAGE BIR
   Wolf BO, 2000, AM ZOOL, V40, P575, DOI 10.1668/0003-1569(2000)040[0575:TROTPI]2.0.CO;2
   Zimova M, 2018, BIOL REV, V93, P1478, DOI 10.1111/brv.12405
   Zink R.M., 1986, Current Ornithology, V4, P1
NR 70
TC 10
Z9 11
U1 0
U2 25
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1466-822X
EI 1466-8238
J9 GLOBAL ECOL BIOGEOGR
JI Glob. Ecol. Biogeogr.
PD OCT
PY 2020
VL 29
IS 10
BP 1704
EP 1715
DI 10.1111/geb.13142
EA JUL 2020
PG 12
WC Ecology; Geography, Physical
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Physical Geography
GA NT8FV
UT WOS:000548737500001
OA Green Published
DA 2025-01-10
ER

PT J
AU Seely, M
   Dirkx, E
   Hager, C
   Klintenberg, P
   Roberts, C
   von Oertzen, D
AF Seely, M.
   Dirkx, E.
   Hager, C.
   Klintenberg, P.
   Roberts, C.
   von Oertzen, D.
TI Advances in desertification and climate change research: Are they
   accessible for application to enhance adaptive capacity?
SO GLOBAL AND PLANETARY CHANGE
LA English
DT Article
DE adaptation; communication platform; decision making; local level
   monitoring; Namibia; political will
ID INFORMATION; SYSTEMS; SCIENCE
AB Sustainable living in and lands is the goal of many, including local residents, policy-makers and scientists. Research into desertification and climate change has the potential to significantly enhance livelihoods of resident people. It also has the potential to contribute to their capacity for risk reduction, improved natural resources management and adaptation to climatic and other changes in multi-stressor systems. This potential is not frequently realised. To effectively ensure that scientific insights and contemporary technologies are applied, active involvement of and feedback from those who apply and use the benefits offered by science and technology are required. Scientists and technologists have to address the diverse, mainly non-technical, aspects required to understand and cope with endemic climate variability, desertification and climate change. They need to appropriately tailor their approaches to disseminate results, and communicate their findings in a way that can be understood and readily implemented by policy-makers, politicians and communities. At the same time, they must learn from experiences gained through implementation by users at all levels.
   The challenges of making the necessary connections between the combinatory effects of desertification and climate change and their effective application are explored and tested. It was found that several key factors contribute to making the necessary connections to facilitate application on all levels of research advances. These include translation, information dissemination, communication, communication platforms, boundary organisations and leadership contributing to knowledge, motivation and capacity. The purpose of this paper is to assess research experiences from integrated land and water resource management, the application of renewable energy and energy efficiency, and local-level monitoring of natural resources and their application to the challenges of desertification and climate change. The conclusion of this assessment is the identification and description of a common framework that can be applied to address the challenges of desertification and climate change. (C) 2008 Elsevier B.V. All rights reserved.
C1 [Seely, M.; Dirkx, E.; Hager, C.; Klintenberg, P.; Roberts, C.; von Oertzen, D.] Desert Res Fdn Namibia, Windhoek, Namibia.
RP Seely, M (corresponding author), Desert Res Fdn Namibia, POB 20232, Windhoek, Namibia.
EM Mary.seely@drfn.org.na
RI Klintenberg, Patrik/AAE-4747-2020; Seely, Mary/AAI-1072-2019
OI Klintenberg, Patrik/0000-0003-2189-0105
CR [Anonymous], 2007, CLIMATE SOC
   [Anonymous], LOCAL LEVEL MONITORI
   [Anonymous], 2006, Livestock's Long Shadow: Environmental Issues and Options, DOI DOI 10.1007/S10666-008-9149-3
   Botes A, 2003, PHYS CHEM EARTH, V28, P853, DOI 10.1016/j.pce.2003.08.028
   BROWN CJ, 1992, NAMIBIAS GREEN PLAN, P174
   Cash DW, 2003, P NATL ACAD SCI USA, V100, P8086, DOI 10.1073/pnas.1231332100
   Christelis G., 2001, Report
   Christensen JH, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P847
   de Wit M, 2006, SCIENCE, V311, P1917, DOI 10.1126/science.1119929
   *DRFN, 2007, NAMB SUPP LOC DEC MA, P40
   ENNE G, 2007, AIDCCD ACTIVE EXCHAN
   Geist HJ, 2004, BIOSCIENCE, V54, P817, DOI 10.1641/0006-3568(2004)054[0817:DCPOD]2.0.CO;2
   Gillson L, 2007, SCIENCE, V315, P53, DOI 10.1126/science.1136577
   Gordon R., 2001, WALL STREET SECRETS
   HELLDEN U, 1991, AMBIO, V20, P372
   Kambatuku J.R., 2003, FIRM FORUM INTEGRATE
   KING C, 2007, UNU DESERTIFICATION, V7
   Klintenberg Patrik, 2007, Secheresse (Montrouge), V18, P336, DOI 10.1684/sec.2007.0102
   Lambin EF, 2005, GLOBAL ENVIRON CHANG, V15, P177, DOI 10.1016/j.gloenvcha.2005.06.002
   LANE A, 2003, STOCKTAKING DRYLAND
   Lepers E, 2005, BIOSCIENCE, V55, P115, DOI 10.1641/0006-3568(2005)055[0115:ASOIOR]2.0.CO;2
   Manning N, 2005, PHYS CHEM EARTH, V30, P886, DOI 10.1016/j.pce.2005.08.035
   Mendelsohn J., 2002, ATLAS NAMIBIA PORTRA
   Millennium Ecosystem Assessment, 2005, Ecosystems and human well-being: Synthesis (Millennium Ecosystem Assessment)
   *NASCO, 2006, NAM COMM CONS REV PR
   New M, 2006, J GEOPHYS RES-ATMOS, V111, DOI 10.1029/2005JD006289
   *NPC, 2006, 2003 2004 NAM HOUS E
   Oldeman L.R., 1991, GLOBAL ASSESSMENT SO
   Olsson K., 1985, REMOTE SENSING FUELW
   Olsson L., 1993, Geojournal, V31, P23, DOI 10.1007/BF00815899
   Ostrom E., 1992, CRAFTING I SELF GOVE
   PILESJO P, 1992, GIS REMOTE SENSING S
   *REP NAM, 2006, CAPR REG POV PROF BA
   *REP NAM, 2002, IN NAT COMM UN FRAM
   *REP NAM, 2004, OH REG POV PROF BAS
   *REP NAM, 2007, KAR REG POV PROF BAS
   Republic of Namibia, 1997, NAT DROUGHT POL STRA
   Reynolds JF, 2007, SCIENCE, V316, P847, DOI 10.1126/science.1131634
   Seely M, 2004, ENVIRON MONIT ASSESS, V99, P23, DOI 10.1007/s10661-004-3997-3
   SEELY M, 2007, DESERTIFICATION INT, P107
   SEELY M, 2007, AIDCCD ACTIVE EXCHAN, P13
   Seely MK, 1998, J ARID ENVIRON, V39, P267, DOI 10.1006/jare.1998.0404
   [Solomon S. IPCC IPCC], 2007, CLIMATE CHANGE 2007
   Stringer LC, 2007, NAT RESOUR FORUM, V31, P198, DOI 10.1111/j.1477-8947.2007.00154.x
NR 44
TC 14
Z9 16
U1 0
U2 19
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0921-8181
EI 1872-6364
J9 GLOBAL PLANET CHANGE
JI Glob. Planet. Change
PD DEC
PY 2008
VL 64
IS 3-4
SI SI
BP 236
EP 243
DI 10.1016/j.gloplacha.2008.07.006
PG 8
WC Geography, Physical; Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Physical Geography; Geology
GA 394EM
UT WOS:000262428500014
DA 2025-01-10
ER

PT J
AU Caleca, V
   Bella, S
   La Pergola, A
   Lombardo, A
   Lo Verde, G
   Maltese, M
   Nucifora, S
   Rizzo, R
   Suma, P
   Tortorici, F
   Rapisarda, C
AF Caleca, Virgilio
   Bella, Salvatore
   La Pergola, Alessandra
   Lombardo, Alberto
   Lo Verde, Gabriella
   Maltese, Matted
   Nucifora, Salvatore
   Rizzo, Roberto
   Suma, Pompeo
   Tortorici, Francesco
   Rapisarda, Carmelo
TI ENVIRONMENTAL FACTORS IMPACT AND INCIDENCE OF PARASITISM OF
   <i>PSYLLAEPHAGUS BLITEUS</i> RIEK (HYMENOPTERA ENCYRTIDAE) ON
   POPULATIONS OF <i>GLYCASPIS BRIMBLECOMBEI</i> MOORE (HEMIPTERA
   APHALARIDAE) IN MEDITERRANEAN CLIMATIC AREAS
SO REDIA-GIORNALE DI ZOOLOGIA
LA English
DT Article
DE Red gum lerp psyllid; Sicily; General Linear Model; Relative Humidity;
   Temperature
ID 1ST RECORD; INSECT PESTS; ASHMEAD HYMENOPTERA; ACIZZIA-JAMATONICA;
   PSYLLIDAE; EUCALYPTUS; PLANTS
AB The red gum lerp psyllid, Glycaspis brimblecombei Moore (Hemiptera, Aphalaridae), is an Australian native sap-sucking insect pest of eucalypts that has been first reported for the West Palaearctic Region in 2008 and, in 2010, it has been found also in Italy. Subsequently its primary parasitoid, Psyllaephagus bliteus Riek (Hymenoptera: Encyrtidae), was also detected within the main European and North African infested areas, where no release of the parasitoid was ever performed. This study, carried out in 30 Eucalyptus camaldulensis plantations located along the coast, on the hills and the mountains in Mediterranean climatic areas of Sicily (Italy), aimed to determine the influence of environmental parameters on the incidence of both, the psyllid infestation level and the parasitization activity. P. bliteus reached highest average levels in summer samplings and resulted widespread in Sicily at all detected altitudes without statistically significant differences. P. bliteus parasitization is the main factor lowering G. brimblecombei infestation; this result, together with the accidental and contemporaneous arrival of the host and its parasitoid, could explain the absence of high damage level on eucalypts in Sicily. The most significant metric factors positively influencing G. brimblecombei infestation are the percentage of daily hours above 80% of relative humidity and the average maximum temperature, obviously related to other, but less significant climatic factors. The altitude affects both infestation and parasitization, but single sites could explain significantly more, so that the local conditions where the samplings were carried out have to be considered as the main responsibles for the variability in the obtained results. In any sampled Sicilian site, from sea level to 540 m a.s.l., both the psyllid and its parasitoids show a good adaptation to climatic conditions, confirming that areas fitting for E. camaldulensis growth fit also for P. bliteus activity, and proving that Mediterranean climate, differently from some inland areas of California, does not obstacle its parasitic activity.
C1 [Caleca, Virgilio; Lo Verde, Gabriella; Maltese, Matted; Tortorici, Francesco] Univ Palermo, Dipartimento Sci Agr Alimentari & Forestali SAAF, Viale Sci,Edificio 5, I-90128 Palermo, Italy.
   [Bella, Salvatore] CREA OFA Consiglio Ric Agr & Anal Econ Agr, Ctr Ric Olivicoltura Frutticoltura & Agrumicoltur, Corso Savoia 190, I-95024 Catania, Italy.
   [La Pergola, Alessandra; Nucifora, Salvatore; Suma, Pompeo; Rapisarda, Carmelo] Univ Catania, Dipartimento Agr Alimentaz & Ambiente Di3A, Via Santa Sofia 100, I-95123 Catania, Italy.
   [Lombardo, Alberto] Univ Palermo, DIID, Viale Sci,Edificio 8, I-90128 Palermo, Italy.
   [Rizzo, Roberto] CREA DC Consiglio Ric Agr & Anal Econ Agr, Ctr Ric Difesa & Certificaz, Res Ctr Plant Protect & Certificat, SS-113,Km 245,5, I-90011 Bagheria, PA, Italy.
C3 University of Palermo; University of Catania; University of Palermo
RP Caleca, V (corresponding author), Univ Palermo, Dipartimento Sci Agr Alimentari & Forestali SAAF, Viale Sci,Edificio 5, I-90128 Palermo, Italy.
EM virgilio.caleca@unipa.it
RI Rizzo, Roberto/AAC-4496-2020; Suma, Pompeo/L-1952-2019; Caleca,
   Virgilio/N-4475-2018; Tortorici, Francesco/K-2587-2015
OI Tortorici, Francesco/0000-0002-0071-3292; LO VERDE,
   Gabriella/0000-0001-8207-1416; SUMA, Pompeo/0000-0001-6082-7964;
   LOMBARDO, Alberto/0000-0002-4406-9777; RIZZO,
   ROBERTO/0000-0003-1628-643X; NUCIFORA, Salvatore/0000-0002-3627-683X;
   Rapisarda, Carmelo/0000-0002-0824-9797; Bella,
   Salvatore/0000-0003-3893-6907
FU Sicilian Region Project "Studi ed indagini sulla presenza di avversita
   biotiche d'interesse forestale e sulle strategie di lotta"; project
   "Insects and globalization: sustainable control of exotic species in
   agroforestry ecosystems (GEISCA)" - Italian Ministry for Education,
   University and Research (PRIN 2010/2011) [2010CXXHJE_004]
FX This research was partially supported by the Sicilian Region Project
   "Studi ed indagini sulla presenza di avversita biotiche d'interesse
   forestale e sulle strategie di lotta" and by the project "Insects and
   globalization: sustainable control of exotic species in agroforestry
   ecosystems (GEISCA)", funded by the Italian Ministry for Education,
   University and Research (PRIN 2010/2011, project 2010CXXHJE_004).
   Climatic data have been kindly provided by the Sicilian
   Agrometeorological Information Service of the Sicilian Region (Regione
   Siciliana - SIAS - Servizio InforMativo Agrometeorologico Siciliano).
   Dr. Luigi Pasotti (SIAS) drew the map on rainfall of the sampling period
   used to realize Fig. III.
CR BALDINI A, 2006, PLAGAS ENFERMEDADES
   BAMI R, 2011, LE MATIN, P6
   Bella S., 2014, Hellenic Plant Protection Journal, V7, P53
   Bella S, 2014, REDIA, V97, P151
   Bella S, 2013, ANN SOC ENTOMOL FR, V49, P374, DOI 10.1080/00379271.2013.856210
   Bella S, 2013, REDIA, V96, P33
   Ben Attia S, 2014, PHYTOPARASITICA, V42, P535, DOI 10.1007/s12600-014-0391-8
   Berry JA, 2007, AUST J ENTOMOL, V46, P99, DOI 10.1111/j.1440-6055.2007.00575.x
   Berti Filho E., 2003, Revista de Agricultura (Piracicaba), V78, P304
   Bouvet Juan P. R., 2005, Rev. Soc. Entomol. Argent., V64, P99
   Brennan EB, 1999, PAN-PAC ENTOMOL, V75, P55
   Burckhardt Daniel, 2008, Mitteilungen der Schweizerischen Entomologischen Gesellschaft, V81, P83
   Caleca Virgilio, 2011, Naturalista Siciliano, V35, P435
   Caleca V, 2011, BIOL CONTROL, V57, P66, DOI 10.1016/j.biocontrol.2010.12.006
   CIBRIAN T. D., 2001, 36 C NAC ENT SANT QU, pE
   Cocquempot Christian, 2012, Bulletin de la Societe Entomologique de France, V117, P363
   Daane KM, 2012, BIOCONTROL SCI TECHN, V22, P1305, DOI 10.1080/09583157.2012.724383
   Daane KM, 2005, BIOL CONTROL, V32, P228, DOI 10.1016/j.biocontrol.2004.09.015
   Dahlsten D. L., 2005, California Agriculture, V59, P229, DOI 10.3733/ca.v059n04p229
   Dahlsten D. L., 2002, Proceedings of the 1st International Symposium on Biological Control of Arthropods, Honolulu, Hawaii, 14-18 January 2002, P356
   de Queiroz DL, 2012, INTEGRATED PEST MANAGEMENT AND PEST CONTROL - CURRENT AND FUTURE TACTICS, P385
   Dhahri S., 2014, Silva Lus., V22, P99
   Drago A., 2005, RIV ITALIANA AGROMET, V2, P67
   EPPO (European and Mediterranean Plant Protection Organization), 2011, EPPO REPORTING SERVI, V2011, P12
   Ferreira PJ, 2015, PHYTOPARASITICA, V43, P151, DOI [10.1007/s12600-014-044, 10.1007/s12600-014-0440-3]
   Garonna A. P., 2011, FOREST, V18, P71, DOI DOI 10.3832/EFOR0654-008
   Gill R.J., 1998, California Pest and Disease Report, V17, P7
   Halbert Susan E., 2001, Florida Department of Agriculture and Consumer Services Division of Plant Industry Entomology Circular, V407, P1
   HERTING B, 1972, COMMONWEALTH AGR BUR, V2, P27
   HOLLIS D, 2004, AUSTR BIOL RESOURCES
   Hurtado Hernandez A., 2008, Boletin de la SEA, V43, P447
   IBNELAZYZ A, 2011, B PHYTOSANITAIRE ONS, V1, P3
   Ide MES., 2006, DETECCION CONTROL BI, P32
   JIMENEZ G. E, 2013, BIOMA, V1, P45
   Julio Rosales Carlos, 2008, ENTOMOTROPICA, V23, P103
   Karaca I, 2015, PHYTOPARASITICA, V43, P171, DOI 10.1007/s12600-015-0457-2
   Laudonia S, 2014, J NAT HIST, V48, P675, DOI 10.1080/00222933.2013.825021
   Laudonia S, 2010, B INSECTOL, V63, P233
   Lo Verde Gabriella, 2011, Naturalista Siciliano, V35, P425
   Malumphy C., 2010, Entomologist's Monthly Magazine, V146, P148
   Malumphy Chris, 2013, Acta Entomologica Serbica, V18, P11
   Margiotta M, 2017, J ECON ENTOMOL, V110, P491, DOI 10.1093/jee/tow253
   Nagamine W.T., 2001, State of Hawaii Department of Agriculture, P1
   Noyes John S., 1996, Bulletin of the Natural History Museum Entomology Series, V65, P105
   Onore G., 2007, 4 EUR HEM C TUR 10 1, P41
   Paine T. D., 2000, California Agriculture, V54, P8, DOI 10.3733/ca.v054n06p8
   Perez-Otero R., 2011, Boletin de Sanidad Vegetal Plagas, V37, P37
   Peris-Felipo Francisco Javier, 2011, Biodiversity Journal, V2, P13
   PIBIRI M, 2011, LUNIONE SARDA, P33
   Plascencia-Gonzalez A., 2005, REV CHAPINGO SER CIE, V11, P11, DOI DOI 10.1111/j.1439-0418.2008.01324.x
   Reguia Kheddar, 2013, Biodiversity Journal, V4, P501
   RIEK E. F., 1962, AUSTRALIAN JOUR ZOOL, V10, P684, DOI 10.1071/ZO9620684
   Rizzo MC, 2015, PHYTOPARASITICA, V43, P407, DOI 10.1007/s12600-015-0472-3
   Rodas CA, 2014, SOUTH FORESTS, V76, P245, DOI 10.2989/20702620.2014.965983
   SANDOVAL A, 2003, DETECCION DELPSILIDO
   SANTANA D. L. Q, 2003, COMUNICACAO TECNICA, P105
   SOOKAR P, 2013, REDGUM LERP PSYLLID, P327
   Suma P., 2014, Bulletin OEPP, V44, P179, DOI 10.1111/epp.12122
   Suma P, 2018, REDIA, V101, P81, DOI 10.19263/REDIA-101.18.11
   WICKEN C. F, 2003, CIRCULAR TECNICA IPE, V201, P1
   Withers TM, 2001, AUSTRAL ECOL, V26, P467, DOI 10.1046/j.1442-9993.2001.01140.x
   World Meteorological Organisation, 2014, GUID MET INSTR METH, V8th edn
NR 62
TC 6
Z9 6
U1 0
U2 3
PU CRA-RESEARCH CENTRE AGROBIOLOGY & PEDOLOGY
PI FIRENZE
PA VIA LANCIOLA 12-A, FIRENZE, 50125, ITALY
SN 0370-4327
J9 REDIA
JI Redia
PY 2018
VL 101
BP 89
EP 100
DI 10.19263/REDIA-101.18.12
PG 12
WC Zoology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Zoology
GA HH2QE
UT WOS:000455562600012
OA gold, Green Submitted
DA 2025-01-10
ER

PT C
AU Okorie, FC
   Okeke, I
   Njoku, J
   Duru, P
AF Okorie, Fidelis Chinazor
   Okeke, Ifeyinwa
   Njoku, John
   Duru, Patricia
BE Hu, J
TI Climate Variability and Malaria Incidence: Impact and Adaptation in
   Owerri Municipal of Imo State Nigeria
SO SOCIAL SCIENCES AND SOCIETY
SE Advances in Education Research
LA English
DT Proceedings Paper
CT 2nd International Conference on Social Sciences and Society (ICSSS 2012)
CY NOV 01-02, 2012
CL San Diego, CA
DE Climate variation; malaria cases; effects; adaptation strategy; Owerri;
   Nigeria
AB It is widely accepted that the Earth's climate has become increasingly warmer, most likely due to increasing greenhouse gas emissions. The variability in climate refers to natural changes in climate that fall within the normal range of extremes for a particular region, as measured by temperature, precipitation and frequency of events. This variation is driven by the uneven distribution of solar heating, the individual responses of the atmosphere, oceans and land surface, the interactions between these and the physical characteristics of the regions. Climate change is expected to exacerbate the already serious challenges to human health, food security and economic development, especially on the African Continent where people are already struggling to meet challenges posed by existing climate variability. Although climate disasters of the past and present decades and their disastrous consequences were not limited to or peculiar to Nigeria or Africa; adaptation to climate variability and changes seems to be especially relevant for Africa, due to her low coping capacity to impacts of the changes. Climate, more especially temperature has a strong and direct influence on development, reproduction and survival of tropical insects such as mosquitoes. Since insect population growth potentials are mainly temperature driven, a rise in temperature may either increase or decrease insect development, likewise rainfall. This paper highlights malaria incidence as a consequence of climate variability and its adaptation by the urbanites within Owerri microclimate in Imo State of Nigeria. It employed the use of 20 years (1990-2000) temperature and rainfall data for Owerri from Nigerian Meteorological Agency and available 10 years (2000 - 2009) data on average malaria cases in Owerri metropolis from primary health care data center, Owerri. The results show variations in the climate of Owerri city and the resultant malaria incidence within the period under study, hence evidence of climate variability and change in Nigeria includes increasing heat waves which enhances disease vectors, communicable diseases and epidemics. However, Owerri people are adapting positively to control the spread of malaria being one of the impacts of climate variability in the metropolis but however, more adaptation strategies are needed.
C1 [Okorie, Fidelis Chinazor; Duru, Patricia] Imo State Univ, Dept Geog & Environm Management, Owerri, Nigeria.
EM chinazorfiddy@hotmail.com
CR Adefolalu D. O., 2007, INT C CLIM CHANG EC
   Intergovernmental Panel on Climate Change (IPCC), 2007, CLIM CHANG 2007 IMP, V4
   NIMET (Nigerian Meteorological Agency), 2008, CLIM WEATH WAT INF S
   Nwafor, 2007, INT C CLIM CHANG EC
   Randall, 2007, P NATL ACAD SCI USA, V103, P5635
   Snow R.W., 2005, NATURE, V420, P627
   Sumiet A., 2004, HIGH PERFORMANCE COM, P480
   Tank AMGK, 2005, INT J CLIMATOL, V25, P1, DOI 10.1002/joc.1087
   WMO, 1979, WORLD CLIM C DECL SU
   WMO, 1995, ANN TROP MED PARASIT, V100, P535
NR 10
TC 0
Z9 0
U1 1
U2 22
PU INFORMATION ENGINEERING RESEARCH INST, USA
PI NEWARK
PA 100 CONTINENTAL DR, NEWARK, DE 19713 USA
SN 2160-1070
BN 978-1-61275-048-4
J9 ADV EDUC RES
PY 2013
VL 6
BP 98
EP 104
PG 7
WC Social Sciences, Interdisciplinary
WE Conference Proceedings Citation Index - Social Science &amp; Humanities (CPCI-SSH)
SC Social Sciences - Other Topics
GA BEU41
UT WOS:000318205600018
DA 2025-01-10
ER

PT J
AU Hamza, A
   Shi, GQ
   Hossain, B
AF Hamza, Amir
   Shi, Guoqing
   Hossain, Babul
TI Migration as an Adaptation Measure to Achieve Resilient Lifestyle in the
   Face of Climate-Induced Drought: Insight from the Thar Desert in
   Pakistan
SO WATER
LA English
DT Article
DE climate change; natural hazards; drought; socio-ecological factors;
   coping strategy; sustainability; Tharparkar
ID DISPLACEMENT; RESETTLEMENT; STRATEGIES; CONTEXT; HAZARDS; SOIL
AB A significant number of people, either seasonally or permanently, migrate from the Thar Desert in Pakistan each year due to droughts caused by climate change. This study aims to investigate the determinants and consequences of these migration decisions, examine the effectiveness of migration as a climate adaptation strategy, and identify challenges in adapting to these changes. Data were gathered from 400 migrated households in the Mithi sub-district. A mixed-method approach was used, combining qualitative and quantitative methods. The findings revealed that threats to the standard of living, including lack of food and clean drinking water, unemployment, and limited educational and medical opportunities, were the primary reasons for permanent and temporary migration from ancestral locations. Migration significantly impacted the origin and destination regions, with positive or negative effects. Specifically, migrants identified various consequences for both the origin and destination communities, including population decline (63%), changes in age structure, increased demand for housing, economic fluctuations (73%), alterations in healthcare services, and increased psychological stress (77%). The study also revealed that individuals who migrated from the Thar Desert experienced improved conditions compared to their previous location, such as diversification of income sources, increased job stability, access to clean water and food, reduced health risks, and overall improvements in their living conditions. However, the destination communities faced significant challenges due to widespread resource depletion and environmental deterioration. Migrants encountered barriers to developing resilient livelihoods in destination areas, including lack of proper knowledge and information, institutional and government issues, environmental and technological challenges, and social and cultural issues. The study highlights the urgent need for comprehensive policies and sustainable solutions to address the root causes of migration and support the resilience of vulnerable populations.
C1 [Hamza, Amir] Hohai Univ, Sch Publ Adm, Dept Sociol, Nanjing 210098, Peoples R China.
   [Shi, Guoqing] Hohai Univ, Natl Res Ctr Resettlement, Nanjing 210098, Peoples R China.
   [Hossain, Babul] Univ Jinan, Sch Informat Sci & Engn, Jinan 250024, Peoples R China.
   [Hossain, Babul] Daffodil Int Univ, Dept Dev Studies, Dhaka 1216, Bangladesh.
C3 Hohai University; Hohai University; University of Jinan; Daffodil
   International University
RP Shi, GQ (corresponding author), Hohai Univ, Natl Res Ctr Resettlement, Nanjing 210098, Peoples R China.; Hossain, B (corresponding author), Univ Jinan, Sch Informat Sci & Engn, Jinan 250024, Peoples R China.; Hossain, B (corresponding author), Daffodil Int Univ, Dept Dev Studies, Dhaka 1216, Bangladesh.
EM a.hamza@hhu.edu.cn; gshi@hhu.edu.cn; babulhhu@gmail.com
RI Hossain, Babul/AAQ-4938-2021; HAMZA, AMIR/LSI-7940-2024
OI HAMZA, AMIR/0009-0004-7252-9293
FU National Foundation of Social Science of China [21, ZD 183]; Key
   Research Project of National Foundation of Social Science of China
FX Key Research Project of National Foundation of Social Science of China,
   Community Governance and Post-relocation Support in Cross District
   Resettlement (Fund no. 21 and ZD 183).
CR Afifi T., 2016, Migration and Development, V5, P254, DOI [DOI 10.1080/21632324.2015.1022974, 10.1080/21632324, DOI 10.1080/21632324]
   Ahmed Khuhro T., 2022, Sci. Int, V34, P37
   AJZEN I, 1991, ORGAN BEHAV HUM DEC, V50, P179, DOI 10.1016/0749-5978(91)90020-T
   Alam G.M. M., 2016, An Assessment of the Livelihood Vulnerability of the Riverbank Erosion Hazard and its Impact on Food Security for Rural Households in Bangladesh
   Alam GMM, 2020, INT J DISAST RISK RE, V43, DOI 10.1016/j.ijdrr.2019.101364
   Alemayehu A, 2017, LOCAL ENVIRON, V22, P825, DOI 10.1080/13549839.2017.1290058
   Atif I., 2016, Sci. Int, V28, P257
   Azhar MF, 2024, ENVIRON DEV, V50, DOI 10.1016/j.envdev.2024.100996
   Bahta YT, 2022, LAND-BASEL, V11, DOI 10.3390/land11060893
   Barua P, 2017, INT J CLIM CHANG STR, V9, P790, DOI 10.1108/IJCCSM-02-2017-0026
   Bilal M., 2018, Proceedings, V2, P179, DOI DOI 10.3390/ECWS-2-04948
   Black R, 2013, ENVIRON SCI POLICY, V27, pS32, DOI 10.1016/j.envsci.2012.09.001
   Boas I, 2022, J ETHN MIGR STUD, V48, P3365, DOI 10.1080/1369183X.2022.2066264
   Borgomeo E., 2018, The Water-Energy-Food Nexus in the Middle East and North Africa Scenarios for a Sustainable Future
   Bourdieu P., 1986, Handbook of Theory and Research for the Sociology of Education, P241
   Brzoska M., 2016, Migration and Development, V5, P190, DOI DOI 10.1080/21632324.2015.1022973
   Casson N, 2023, BMC PUBLIC HEALTH, V23, DOI 10.1186/s12889-023-15105-z
   Chambers R., 1992, Discussion Paper - Institute of Development Studies, University of Sussex
   Chen J, 2018, NAT CLIM CHANGE, V8, P981, DOI 10.1038/s41558-018-0313-8
   Dai AG, 2018, CURR CLIM CHANGE REP, V4, P301, DOI 10.1007/s40641-018-0101-6
   Ebi KL, 2020, HEALTH AFFAIR, V39, P2056, DOI 10.1377/hlthaff.2020.01125
   Haghighi AT, 2020, WATER-SUI, V12, DOI 10.3390/w12030838
   Han Q, 2024, J GEOCHEM EXPLOR, V256, DOI 10.1016/j.gexplo.2023.107352
   Harraka M., 2002, J. Cathol. Educ, V6, P266, DOI DOI 10.15365/JOCE.0602122013
   Heshmati G.A., 2013, Combating Desertii Cation in Asia, Africa and the Middle East Proven Practices
   Holling C.S., 1973, Annual Rev Ecol Syst, V4, P1, DOI 10.1146/annurev.es.04.110173.000245
   Holling C.S., 2002, Understanding Transformations in Human and Natural Systems
   Hossain B., 2020, ASIAN RES J ARTS SOC, V10, P47, DOI [10.9734/arjass/2020/v10i130140, DOI 10.9734/ARJASS/2020/V10I130140, 10.9734/ARJASS/2020/v10i130140]
   Hossain B., 2024, Living with Floods in Bangladeshs Riverine Islands: Understanding Vulnerability and Resilience
   Hossain B, 2023, BMC PUBLIC HEALTH, V23, DOI 10.1186/s12889-023-16497-8
   Hossain B, 2022, FRONT PSYCHOL, V13, DOI 10.3389/fpsyg.2022.964648
   Hussain MA, 2023, LAND-BASEL, V12, DOI 10.3390/land12010140
   Iqbal MP., 2020, Proc Pak Acad Sci B Life Environ Sci, V57, P1
   Islam MR, 2016, NAT HAZARDS, V81, P1051, DOI 10.1007/s11069-015-2119-6
   Jha CK, 2018, INT J CLIM CHANG STR, V10, P121, DOI 10.1108/IJCCSM-03-2017-0059
   Kabir ME, 2018, INT J DISAST RISK RE, V31, P617, DOI 10.1016/j.ijdrr.2018.06.010
   Khan A.H., 2014, Ph.D. Thesis
   Khan K., 2021, Impacts of climate change in vulnerable communities in Sindh
   Koubi V, 2016, WORLD DEV, V79, P197, DOI 10.1016/j.worlddev.2015.11.016
   Kpadonou RAB, 2017, LAND USE POLICY, V61, P196, DOI 10.1016/j.landusepol.2016.10.050
   Kumar A, 2023, ECOHYDROLOGY, V16, DOI 10.1002/eco.2483
   Kumar A, 2022, J SUSTAIN FOREST, V41, P642, DOI 10.1080/10549811.2020.1794907
   Kumar P, 2021, ATMOSPHERE-BASEL, V12, DOI 10.3390/atmos12101248
   LEE ES, 1966, DEMOGRAPHY, V3, P47, DOI 10.2307/2060063
   Leonardi G., 2010, Environmental Medicine, P521
   Mahmood R, 2016, WATER-SUI, V8, DOI 10.3390/w8010023
   Malhi Y, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0104
   Mazhin SA, 2020, J EDUC HEALTH PROMOT, V9, DOI 10.4103/jehp.jehp_4_20
   Memon M. H., 2018, Pakistan Development Review, V57, P307, DOI 10.30541/v57i3pp.307-321
   Moser SC, 2010, P NATL ACAD SCI USA, V107, P22026, DOI 10.1073/pnas.1007887107
   Mueller V, 2014, NAT CLIM CHANGE, V4, P182, DOI [10.1038/nclimate2103, 10.1038/NCLIMATE2103]
   Nikuze A, 2019, HABITAT INT, V86, P38, DOI 10.1016/j.habitatint.2019.02.006
   Nyamekye C, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10093182
   Paul S, 2015, HABITAT INT, V48, P113, DOI 10.1016/j.habitatint.2015.03.018
   Salik K.M., 2020, Climate-Induced Displacement and Migration in Pakistan Insights from Muzaffargarh and Tharparkar Districts
   Sarker MNI, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11061623
   Sattar A., 2014, Climate Change and Migration. Exploring the Linkage and What Needs to Be Done in the Context of Pakistan
   Scoones I., 1998, Working Paper - Institute of Development Studies, University of Sussex
   Shah Nadeem Abbas, 2020, Sarhad Journal of Agriculture, V36, P1162, DOI 10.17582/journal.sja/2020/36.4.1162.1173
   Sheikh MA, 2021, MITIG ADAPT STRAT GL, V26, DOI 10.1007/s11027-021-09941-w
   Siddiqui S., 2017, Int. J. Econ. Environ. Geol, V8, P8
   Smit B, 2006, GLOBAL ENVIRON CHANG, V16, P282, DOI 10.1016/j.gloenvcha.2006.03.008
   Solomon S., 2019, A Literature Review, 1990-2018
   STARK O, 1985, AM ECON REV, V75, P173
   Tajrin Suriya., 2017, INT J LAW HUMANITIES, V1, P60, DOI [DOI 10.3390/GEOSCIENCES9110482, 10.3390/geosciences9110482]
   Talpur M.A., 2021, Pak. J. Appl. Econ, V31, P209
   TORRES C.A.-Q., 2015, State Environ. Migr, V19, P64
   Usman M, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12030580
   Warner K, 2010, GLOBAL ENVIRON CHANG, V20, P402, DOI 10.1016/j.gloenvcha.2009.12.001
   Wiederkehr C, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aae6de
   Wilkinson E, 2016, CLIMATE CHANGE MIGRA
   World Bank, 2017, Pakistan
   ZAMAN MQ, 1989, HUM ORGAN, V48, P196, DOI 10.17730/humo.48.3.v55465j651259835
   Zickgraf C., 2020, The State of Environmental Migration 2015
NR 74
TC 0
Z9 0
U1 2
U2 2
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4441
J9 WATER-SUI
JI Water
PD SEP
PY 2024
VL 16
IS 18
AR 2692
DI 10.3390/w16182692
PG 22
WC Environmental Sciences; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Water Resources
GA H4H0E
UT WOS:001323055700001
OA gold
DA 2025-01-10
ER

PT J
AU Zhou, W
   Yu, WD
   Zhang, ZY
   Cao, W
   Wu, T
AF Zhou, Wen
   Yu, Wendong
   Zhang, Ziyi
   Cao, Wei
   Wu, Tao
TI How can urban green spaces be planned to mitigate urban heat island
   effect under different climatic backgrounds? A threshold-based
   perspective
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Urban green space; Cooling effect; Local climate zone; The absolute
   threshold of cooling; Climate adaption and mitigation
ID LAND-SURFACE TEMPERATURE; SPATIAL-PATTERN; CITIES; TECHNOLOGIES; IMPACT;
   RISK; CITY; VARIABILITY; EFFICIENCY; MORTALITY
AB Urban green space (UGS) was widely regarded as an effective nature-based solution to mitigate the urban heat island (UHI) effect, therefore, developing landscape strategies to enhance its cooling intensity (CI) is crucial. However, two main problems prevent the application of results to practical actions: one is the inconsistency of relationships between influencing factors of landscape and the thermal environment; another is the unfeasibility of some common conclusions such as simply increasing the amount of vegetation cover in highly-urbanized areas. This study compared the CIs of UGSs, investigated the influencing factors of CI and identified the absolute threshold of cooling (ToCabs) of the influencing factors in four Chinese cities with very different climatic backgrounds (Hohhot, Beijing, Shanghai and Haikou). Results demonstrate that local climate condition affects the cooling effect of UGS. The CI of UGS is weaker in cities with humid and hot summer than in cities with dry and hot summer. Patch characteristics (area and shape), the percentage of water bodies within the UGS (Pland_w) and neighboring greenspace (NGP), vegetation abundance (NDVI) and planting structure together can explain a significant proportion (R2 = 0.403-0.672, p < 0.001) of the CI variations of UGS. The inclusion of water bodies can ensure effective cooling of UGS, except in the tropical city. Besides, ToCabs of area (Hohhot, 2.6 ha; Beijing, 5.9 ha; Shanghai, 4.0 and Haikou, 5.3 ha), and NGP (Hohhot, 8.5 %; Beijing, 21.6%; and Shanghai, 23.5 %), NDVI (Hohhot, 0.31; Beijing, 0.33; and Shanghai, 0.39) were identified and related landscape strategies of cooling were proposed. The identification of ToCabs values can provide easy-to-use landscape recommendations to UHI mitigation.
C1 [Zhou, Wen; Yu, Wendong; Zhang, Ziyi; Cao, Wei; Wu, Tao] Yangzhou Univ, Coll Hort & Landscape Architecture, Yangzhou 225000, Peoples R China.
C3 Yangzhou University
RP Zhou, W (corresponding author), Yangzhou Univ, Coll Hort & Landscape Architecture, Yangzhou 225000, Peoples R China.
EM wenzhou0305@hotmail.com
RI Zhou, Wen/LTD-0998-2024; Cao, Wei/GWC-9162-2022
FU National Natural Science Foundation of China [32101577]; Scientific
   Research Foundation for Advanced Talents, Yangzhou University
   [137012167]
FX This work is supported by the National Natural Science Foundation of
   China (Grant Number: 32101577; Representative: Wen Zhou) and Scientific
   Research Foundation for Advanced Talents, Yangzhou University (Grant
   Number: 137012167; Representative: Wen Zhou) . Special thanks to two
   anonymous reviewers and the editor for their valuable comments to
   improve our manuscript.
CR Akbari H, 2016, ENERG BUILDINGS, V133, P834, DOI 10.1016/j.enbuild.2016.09.067
   Anderson GB, 2011, ENVIRON HEALTH PERSP, V119, P210, DOI 10.1289/ehp.1002313
   Beijing Municipal Bureau Statistics, 2021, BEIJ STAT YB 2021
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   Cao C, 2016, NAT COMMUN, V7, DOI 10.1038/ncomms12509
   Cao X, 2010, LANDSCAPE URBAN PLAN, V96, P224, DOI 10.1016/j.landurbplan.2010.03.008
   Chang CR, 2007, LANDSCAPE URBAN PLAN, V80, P386, DOI 10.1016/j.landurbplan.2006.09.005
   Chen AL, 2016, ECOL INDIC, V69, P828, DOI 10.1016/j.ecolind.2016.05.045
   Chen AL, 2014, URBAN FOR URBAN GREE, V13, P646, DOI 10.1016/j.ufug.2014.07.006
   Chen X, 2019, URBAN FOR URBAN GREE, V43, DOI 10.1016/j.ufug.2019.126368
   Corburn J, 2009, URBAN STUD, V46, P413, DOI 10.1177/0042098008099361
   Di Blasi C., 2023, INT J ENV RES PUB HE, V20, P2781
   Dugord PA, 2014, COMPUT ENVIRON URBAN, V48, P86, DOI 10.1016/j.compenvurbsys.2014.07.005
   Emmanuel R, 2007, INT J CLIMATOL, V27, P1995, DOI 10.1002/joc.1609
   Fan HY, 2019, AGR FOREST METEOROL, V265, P338, DOI 10.1016/j.agrformet.2018.11.027
   Feyisa GL, 2014, LANDSCAPE URBAN PLAN, V123, P87, DOI 10.1016/j.landurbplan.2013.12.008
   Foley JA, 2005, SCIENCE, V309, P570, DOI 10.1126/science.1111772
   Gilbert H, 2016, ENERG BUILDINGS, V114, P20, DOI 10.1016/j.enbuild.2015.06.023
   Gomez-Martinez F, 2021, LAND-BASEL, V10, DOI 10.3390/land10020155
   Grimm NB, 2008, SCIENCE, V319, P756, DOI 10.1126/science.1150195
   GRIMMOND CSB, 1991, WATER RESOUR RES, V27, P1739, DOI 10.1029/91WR00557
   Guerri G, 2022, SCI TOTAL ENVIRON, V806, DOI 10.1016/j.scitotenv.2021.151383
   Gunawardena KR, 2017, SCI TOTAL ENVIRON, V584, P1040, DOI 10.1016/j.scitotenv.2017.01.158
   Haikou Municipal Bureau Statistics, 2021, HAIK STAT YB 2021
   He BJ, 2020, SUSTAIN CITIES SOC, V60, DOI 10.1016/j.scs.2020.102289
   He BJ, 2019, SUSTAIN CITIES SOC, V44, P416, DOI 10.1016/j.scs.2018.10.049
   He BJ, 2018, URBAN FOR URBAN GREE, V34, P154, DOI 10.1016/j.ufug.2018.06.015
   Hoag H, 2015, NATURE, V524, P402, DOI 10.1038/524402a
   Hohhot Municipal Bureau Statistics, 2021, HOHH STAT YB 2021
   Jim CY, 2012, URBAN FOR URBAN GREE, V11, P73, DOI 10.1016/j.ufug.2011.10.001
   Jiménez-Muñoz JC, 2014, IEEE GEOSCI REMOTE S, V11, P1840, DOI 10.1109/LGRS.2014.2312032
   Jin ML, 2005, J CLIMATE, V18, P1551, DOI 10.1175/JCLI3334.1
   Kong FH, 2014, LANDSCAPE URBAN PLAN, V128, P35, DOI 10.1016/j.landurbplan.2014.04.018
   Lehmann I, 2014, ECOL INDIC, V42, P58, DOI 10.1016/j.ecolind.2014.02.036
   Li D, 2013, J APPL METEOROL CLIM, V52, P2051, DOI 10.1175/JAMC-D-13-02.1
   Li JX, 2011, REMOTE SENS ENVIRON, V115, P3249, DOI 10.1016/j.rse.2011.07.008
   Li XM, 2013, LANDSCAPE URBAN PLAN, V114, P1, DOI 10.1016/j.landurbplan.2013.02.005
   Li XM, 2012, LANDSCAPE ECOL, V27, P887, DOI 10.1007/s10980-012-9731-6
   Manteghi G., 2015, MOD APPL SCI, V9
   Marando F, 2022, SUSTAIN CITIES SOC, V77, DOI 10.1016/j.scs.2021.103564
   Masoudi M, 2019, LANDSCAPE URBAN PLAN, V184, P44, DOI 10.1016/j.landurbplan.2018.10.023
   McGeehin MA, 2001, ENVIRON HEALTH PERSP, V109, P185, DOI 10.2307/3435008
   Mora C, 2017, NAT CLIM CHANGE, V7, P501, DOI [10.1038/nclimate3322, 10.1038/NCLIMATE3322]
   Morabito M, 2021, SCI TOTAL ENVIRON, V751, DOI 10.1016/j.scitotenv.2020.142334
   Morabito M, 2017, ATMOSPHERE-BASEL, V8, DOI 10.3390/atmos8070115
   OKE TR, 1982, Q J ROY METEOR SOC, V108, P1, DOI 10.1002/qj.49710845502
   Oliveira S, 2011, BUILD ENVIRON, V46, P2186, DOI 10.1016/j.buildenv.2011.04.034
   Park J, 2017, URBAN FOR URBAN GREE, V21, P203, DOI 10.1016/j.ufug.2016.12.005
   Peng J, 2016, REMOTE SENS ENVIRON, V173, P145, DOI 10.1016/j.rse.2015.11.027
   Rizwan AM, 2008, J ENVIRON SCI, V20, P120, DOI 10.1016/S1001-0742(08)60019-4
   Rydin Y, 2012, LANCET, V379, P2079, DOI 10.1016/S0140-6736(12)60435-8
   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
   Shanghai Municipal Bureau Statistics, 2021, SHANGH STAT YB 202
   Stewart I.D., 2003, B AM METEOROL SOC, V86, P370
   Theeuwes NE, 2013, J GEOPHYS RES-ATMOS, V118, P8881, DOI 10.1002/jgrd.50704
   Ullah S, 2022, EARTHS FUTURE, V10, DOI 10.1029/2021EF002511
   UNDESA, 2018, World Urbanization Prospects: The 2018 Revision
   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
   Weng Q, 2001, INT J REMOTE SENS, V22, P1999, DOI 10.1080/713860788
   Xiao XD, 2018, SUSTAIN CITIES SOC, V40, P428, DOI 10.1016/j.scs.2018.04.002
   Xu JC, 2010, BUILD ENVIRON, V45, P1072, DOI 10.1016/j.buildenv.2009.10.025
   Yan H, 2018, SCI TOTAL ENVIRON, V622, P882, DOI 10.1016/j.scitotenv.2017.11.327
   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 X, 2009, INT J REMOTE SENS, V30, P2105, DOI 10.1080/01431160802549252
   Zhou WQ, 2017, REMOTE SENS ENVIRON, V195, P1, DOI 10.1016/j.rse.2017.03.043
   Zhou WQ, 2014, LANDSCAPE ECOL, V29, P153, DOI 10.1007/s10980-013-9950-5
   Zhou WQ, 2011, LANDSCAPE URBAN PLAN, V102, P54, DOI 10.1016/j.landurbplan.2011.03.009
   Zhou W, 2023, SCI TOTAL ENVIRON, V863, DOI 10.1016/j.scitotenv.2022.160712
   Zhou W, 2022, LANDSCAPE URBAN PLAN, V225, DOI 10.1016/j.landurbplan.2022.104449
   Zhou W, 2020, ECOL INDIC, V109, DOI 10.1016/j.ecolind.2019.105778
   Zhou W, 2019, FORESTS, V10, DOI 10.3390/f10030282
NR 74
TC 39
Z9 40
U1 42
U2 139
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 10
PY 2023
VL 890
AR 164422
DI 10.1016/j.scitotenv.2023.164422
EA MAY 2023
PG 11
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA L6ZC5
UT WOS:001024712600001
PM 37236468
OA hybrid
DA 2025-01-10
ER

PT J
AU Andree, E
   Su, J
   Larsen, MAD
   Drews, M
   Stendel, M
   Madsen, KS
AF Andree, Elin
   Su, Jian
   Dahl Larsen, Morten Andreas
   Drews, Martin
   Stendel, Martin
   Skovgaard Madsen, Kristine
TI The role of preconditioning for extreme storm surges in the western
   Baltic Sea
SO NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
LA English
DT Article
ID ANTECEDENT CONDITIONS; NATURAL HAZARDS; CLIMATE RISK; LEVEL RISE; FLOOD;
   VARIABILITY; REANALYSIS; EVENTS; DYNAMICS; BLOCKING
AB When natural hazards interact in compound events, they may reinforce each other. This is a concern today and in light of climate change. In the case of coastal flooding, sea-level variability due to tides, seasonal to inter-annual salinity and temperature variations, or larger-scale wind conditions modify the development and ramifications of extreme sea levels. Here, we explore how various prior conditions could have influenced peak water levels for the devastating coastal flooding event in the western Baltic Sea in 1872. We design numerical experiments by imposing a range of precondition circumstances as boundary conditions to numerical ocean model simulations. This allows us to quantify the changes in peak water levels that arise due to alternative preconditioning of the sea level before the storm surge. Our results show that certain preconditioning could have generated even more catastrophic impacts. As an example, a simulated increase in the water level of 36 cm compared to the 1872 event occurred in Koge just south of Copenhagen (Denmark) and surrounding areas - a region that was already severely impacted. The increased water levels caused by the alternative sea-level patterns propagate as long waves until encountering shallow and narrow straits, and after that, the effect vastly decreases. Adding artificial increases in wind speeds to each study point location reveals a near-linear relationship with peak water levels for all western Baltic locations, highlighting the need for good assessments of future wind extremes. Our research indicates that a more hybrid approach to analysing compound events and readjusting our present warning system to a more contextualised framework might provide a firmer foundation for climate adaptation and disaster risk management. In particular, accentuating the importance of compound preconditioning effects on the outcome of natural hazards may avoid under- or overestimation of the associated risks.
C1 [Andree, Elin; Su, Jian; Dahl Larsen, Morten Andreas; Stendel, Martin; Skovgaard Madsen, Kristine] Danish Meteorol Inst, Lyngbyvej 100, DK-2100 Copenhagen, Denmark.
   [Andree, Elin; Dahl Larsen, Morten Andreas; Drews, Martin] Tech Univ Denmark, Dept Technol Management & Econ Produktionstorvet, Bldg 424, DK-2800 Lyngby, Denmark.
C3 Danish Meteorological Institute DMI; Technical University of Denmark
RP Drews, M (corresponding author), Tech Univ Denmark, Dept Technol Management & Econ Produktionstorvet, Bldg 424, DK-2800 Lyngby, Denmark.
EM mard@dtu.dk
RI Larsen, Morten/HSG-6811-2023; Madsen, Kristine Skovgaard/KCL-3477-2024;
   Larsen, Morten Andreas Dahl/F-5185-2015; Drews, Martin/E-8081-2017
OI Madsen, Kristine Skovgaard/0000-0001-6371-1078; Larsen, Morten Andreas
   Dahl/0000-0002-7478-5416; Drews, Martin/0000-0002-3532-4780
FU Danish State through the Danish Climate Atlas; Swedish Research Council,
   Formas
FX Part of the funding was provided by the Danish State through the Danish
   Climate Atlas. A portion of the work was carried out within the "Extreme
   events in the coastal zone - a multidisciplinary approach for better
   preparedness" project, hosted by Uppsala University and funded by the
   Swedish Research Council, Formas.
CR AghaKouchak A, 2020, ANNU REV EARTH PL SC, V48, P519, DOI 10.1146/annurev-earth-071719-055228
   Alexandersson H., 1998, The Global atmosphere and ocean system, V6, P97
   Andree E, 2022, WEATHER CLIM EXTREME, V36, DOI 10.1016/j.wace.2022.100422
   Andrée E, 2021, OCEAN MODEL, V162, DOI 10.1016/j.ocemod.2021.101802
   Arns A, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-15752-5
   Baensch O., 1875, Z BAUWESEN BERLIN
   Barriopedro D, 2006, J CLIMATE, V19, P1042, DOI 10.1175/JCLI3678.1
   BENGTSSON L, 1985, ADV GEOPHYS, V28, P3
   Berg P., 2012, 1211 DMI, P147
   Bevacqua E, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aaw5531
   Bischiniotis K, 2018, NAT HAZARD EARTH SYS, V18, P271, DOI 10.5194/nhess-18-271-2018
   Bradstock RA, 2009, INT J WILDLAND FIRE, V18, P932, DOI 10.1071/WF08133
   Brown S, 2018, EARTHS FUTURE, V6, P583, DOI 10.1002/2017EF000738
   Buchanan MK, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa6cb3
   Bureau Veritas: 44. Jahrgang, 1872, DTSCH SCHIFFAHRTSMUS, V44
   Calafat FM, 2020, P NATL ACAD SCI USA, V117, P1877, DOI 10.1073/pnas.1913049117
   Clemmensen LB, 2014, EARTH SURF PROC LAND, V39, P499, DOI 10.1002/esp.3466
   Colding A., 1881, NOGLE UNDERSOGELSER, DOI [10.48563/dtu-0000041, DOI 10.48563/DTU-0000041]
   Coles S., 2001, An Introduction to Statistical Modeling of Extreme Values, DOI DOI 10.1007/978-1-4471-3675-0
   Compo GP, 2011, Q J ROY METEOR SOC, V137, P1, DOI 10.1002/qj.776
   Couasnon A, 2020, NAT HAZARD EARTH SYS, V20, P489, DOI 10.5194/nhess-20-489-2020
   Dangendorf S, 2021, NAT CLIM CHANGE, V11, P514, DOI 10.1038/s41558-021-01046-1
   Donnelly C, 2016, HYDROLOG SCI J, V61, P255, DOI 10.1080/02626667.2015.1027710
   Feistel R., 2008, Oceanologia, P625, DOI 10.1002/9780470283134.ch20
   Feuchter D., 2013, Geographica Bernensia, V89, P91, DOI [10.4480/GB2013.G89.10, DOI 10.4480/GB2013.G89.10]
   Frederikse T, 2020, NATURE, V584, P393, DOI 10.1038/s41586-020-2591-3
   Fu W, 2012, OCEAN SCI, V8, P827, DOI 10.5194/os-8-827-2012
   Gazzard R., 2019, Forest Fires in Europe, Middle East and North Africa 2018, DOI 10.2760/561734
   Hallegatte S, 2013, NAT CLIM CHANGE, V3, P802, DOI [10.1038/nclimate1979, 10.1038/NCLIMATE1979]
   Hallin C, 2021, WATER-SUI, V13, DOI 10.3390/w13121697
   Harjanne A, 2017, ADV SCI RES, V14, P293, DOI 10.5194/asr-14-293-2017
   Hendry A, 2019, HYDROL EARTH SYST SC, V23, P3117, DOI 10.5194/hess-23-3117-2019
   Hilker N, 2009, NAT HAZARD EARTH SYS, V9, P913, DOI 10.5194/nhess-9-913-2009
   Intergov Panel Clim Chg, 2012, MANAGING THE RISKS OF EXTREME EVENTS AND DISASTERS TO ADVANCE CLIMATE CHANGE ADAPTATION, P1, DOI 10.1017/CBO9781139177245
   Jacobsen T., 2021, DMI Report 21-28
   Johnson F, 2016, CLIMATIC CHANGE, V139, P21, DOI 10.1007/s10584-016-1689-y
   Jönsson B, 2008, J GEOPHYS RES-OCEANS, V113, DOI 10.1029/2006JC003862
   Kiecksee H., 1972, OSTSEE STURMFLUT 187
   Kleine E., 1994, Das operationelle Modell des BSH fur Nordsee und Ostsee: Konzeption und Ubersicht
   Lavaud L, 2020, OCEAN MODEL, V156, DOI 10.1016/j.ocemod.2020.101710
   Leppäranta M, 2009, SPRINGER-PRAX BOOKS, pXI
   Lillo SP, 2017, Q J ROY METEOR SOC, V143, P1211, DOI 10.1002/qj.2938
   Lin M., WATER RES
   Lisitzin E., 1974, SEA LEVEL CHANGES, P185, DOI [10.1016/S0422-9894(08)70781-5, DOI 10.1016/S0422-9894(08)70781-5]
   Madsen K.S, 2009, THESIS U COPENHAGEN
   Marcos M, 2015, J GEOPHYS RES-OCEANS, V120, P8115, DOI 10.1002/2015JC011173
   Matsueda M, 2018, Q J ROY METEOR SOC, V144, P1012, DOI 10.1002/qj.3265
   MATTHAUS W, 1992, CONT SHELF RES, V12, P1375, DOI 10.1016/0278-4343(92)90060-W
   McMillan SK, 2018, BIOGEOCHEMISTRY, V141, P487, DOI 10.1007/s10533-018-0482-6
   Modrakowski LC, 2022, FRONT CLIM, V3, DOI 10.3389/fclim.2021.772629
   Mudersbach C., 2010, KORRESPONDENZ WASSER, V3, P136
   Murawski J, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.657720
   Nabizadeh E, 2019, GEOPHYS RES LETT, V46, P13488, DOI 10.1029/2019GL084863
   Petersen M., 1977, Sturmflut: die grossen Fluten an den Kusten Schleswig-Holsteins und in der Elbe
   Poulsen J.W, 2012, Technical Report
   Pugh DT., 1987, Tides, Surges and Mean Sea-Level: A Handbook for Engineers and Scientists
   Raymond C, 2020, NAT CLIM CHANGE, V10, P611, DOI 10.1038/s41558-020-0790-4
   Ridal M., 2017, Deliverable D2.7 HARMONIE Reanalysis Report of Results and Dataset
   Rosenhagen G., 2009, Die Kuste, V75, P51
   Rutgersson A, 2022, EARTH SYST DYNAM, V13, P251, DOI 10.5194/esd-13-251-2022
   Samuelsson M, 1996, TELLUS A, V48, P672, DOI 10.1034/j.1600-0870.1996.t01-4-00006.x
   Santos VM, 2021, HYDROL EARTH SYST SC, V25, P3595, DOI 10.5194/hess-25-3595-2021
   She J, 2007, J MARINE SYST, V65, P450, DOI 10.1016/j.jmarsys.2006.01.017
   She J, 2019, J OPER OCEANOGR, V12, pS111
   Slivinski LC, 2019, Q J ROY METEOR SOC, V145, P2876, DOI 10.1002/qj.3598
   SMHI, 2021, SMHI OP DAT NAT ARCH
   Soomere T, 2016, CONT SHELF RES, V115, P53, DOI 10.1016/j.csr.2015.12.016
   Stendel M., 2021, CLIMATE CHANGE OBSER, VThird, P327, DOI [DOI 10.1016/B978-0-12-821575-3.00015-3, 10.1016/B978-0-12-821575-3.00015-3]
   Su Jian, 2022, Zenodo, DOI 10.5281/ZENODO.6769238
   Su J, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.629470
   Summary for Policymakers, 2001, CLIMATE CHANGE 2001, P2
   Talia M, 2021, INT J PUBLIC THEOL, V15, P595, DOI 10.1163/15697320-01
   Thorarinsdottir TL, 2017, WATER RESOUR RES, V53, P8147, DOI 10.1002/2016WR020354
   Tian T, 2016, CLIM DYNAM, V46, P99, DOI 10.1007/s00382-015-2571-8
   Travis WR, 2014, CLIM RISK MANAG, V1, P1, DOI 10.1016/j.crm.2014.02.003
   Vafeidis AT, 2019, NAT HAZARD EARTH SYS, V19, P973, DOI 10.5194/nhess-19-973-2019
   Vogel J, 2021, WEATHER CLIM EXTREME, V32, DOI 10.1016/j.wace.2021.100312
   Vousdoukas MI, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-15665-3
   Vousdoukas MI, 2016, NAT HAZARD EARTH SYS, V16, P1841, DOI 10.5194/nhess-16-1841-2016
   Wahl T, 2017, NAT COMMUN, V8, DOI 10.1038/ncomms16075
   Weisse R, 2021, EARTH SYST DYNAM, V12, P871, DOI 10.5194/esd-12-871-2021
   Weisse R, 2017, PROC IUTAM, V25, P65, DOI 10.1016/j.piutam.2017.09.010
   Wolski T, 2014, OCEANOLOGIA, V56, P259, DOI 10.5697/oc.56-2.259
   Woodworth PL, 2019, SURV GEOPHYS, V40, P1351, DOI 10.1007/s10712-019-09531-1
   Woollings T, 2018, CURR CLIM CHANGE REP, V4, P287, DOI 10.1007/s40641-018-0108-z
   WUBBER C, 1979, OCEANOL ACTA, V2, P435
   Zappa G, 2014, GEOPHYS RES LETT, V41, P135, DOI 10.1002/2013GL058480
   Zscheischler J, 2018, NAT CLIM CHANGE, V8, P469, DOI 10.1038/s41558-018-0156-3
NR 88
TC 9
Z9 9
U1 2
U2 7
PU COPERNICUS GESELLSCHAFT MBH
PI GOTTINGEN
PA BAHNHOFSALLEE 1E, GOTTINGEN, 37081, GERMANY
SN 1561-8633
EI 1684-9981
J9 NAT HAZARD EARTH SYS
JI Nat. Hazards Earth Syst. Sci.
PD MAY 15
PY 2023
VL 23
IS 5
BP 1817
EP 1834
DI 10.5194/nhess-23-1817-2023
PG 18
WC Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences;
   Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology; Meteorology & Atmospheric Sciences; Water Resources
GA G4HQ8
UT WOS:000988789800001
OA Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Zhao, SQ
   Nie, XH
   Liu, XQ
   Wang, BY
   Liu, S
   Qin, L
   Xing, Y
AF Zhao, Shuqing
   Nie, Xinghua
   Liu, Xueqing
   Wang, Biyao
   Liu, Song
   Qin, Ling
   Xing, Yu
TI Genome-Wide Identification of the <i>CER</i> Gene Family and Significant
   Features in Climate Adaptation of <i>Castanea mollissima</i>
SO INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
LA English
DT Article
DE Castanea mollissima; CER gene family; drought stress; epicuticular wax
   layer thickness; expression
ID CUTICULAR WAX BIOSYNTHESIS; DROUGHT; WILD; EVOLUTION; ENCODES; POLLEN;
   ORIGIN
AB The plant cuticle is the outermost layer of the aerial organs and an important barrier against biotic and abiotic stresses. The climate varies greatly between the north and south of China, with large differences in temperature and humidity, but Chinese chestnut is found in both regions. This study investigated the relationship between the wax layer of chestnut leaves and environmental adaptation. Firstly, semi-thin sections were used to verify that there is a significant difference in the thickness of the epicuticular wax layer between wild chestnut leaves in northwest and southeast China. Secondly, a whole-genome selective sweep was used to resequence wild chestnut samples from two typical regional populations, and significant genetic divergence was identified between the two populations in the CmCER1-1, CmCER1-5 and CmCER3 genes. Thirty-four CER genes were identified in the whole chestnut genome, and a series of predictive analyses were performed on the identified CmCER genes. The expression patterns of CmCER genes were classified into three trends-upregulation, upregulation followed by downregulation and continuous downregulation-when chestnut seedlings were treated with drought stress. Analysis of cultivars from two resource beds in Beijing and Liyang showed that the wax layer of the northern variety was thicker than that of the southern variety. For the Y-2 (Castanea mollissima genome sequencing material) cultivar, there were significant differences in the expression of CmCER1-1, CmCER1-5 and CmCER3 between the southern variety and the northern one-year-grafted variety. Therefore, this study suggests that the CER family genes play a role in environmental adaptations in chestnut, laying the foundation for further exploration of CmCER genes. It also demonstrates the importance of studying the adaptation of Chinese chestnut wax biosynthesis to the southern and northern environments.
C1 [Zhao, Shuqing; Nie, Xinghua; Liu, Xueqing; Wang, Biyao; Liu, Song; Qin, Ling; Xing, Yu] Beijing Univ Agr, Coll Plant Sci & Technol, Beijing Key Lab Agr Applicat & New Tech, Beijing 102206, Peoples R China.
C3 Beijing University of Agriculture
RP Qin, L; Xing, Y (corresponding author), Beijing Univ Agr, Coll Plant Sci & Technol, Beijing Key Lab Agr Applicat & New Tech, Beijing 102206, Peoples R China.
EM qinling@bua.edu.cn; xingyu@bua.edu.cn
RI Xing, Yu/HOF-0285-2023; liu, xq/JDW-2596-2023; qin, ling/KIB-1029-2024
OI zhao, shuqing/0000-0002-7359-4714; Nie, Xinghua/0000-0001-5627-6557;
   Xing, Yu/0000-0002-1647-9736
FU National Key Research & Development Program of China;  [2018YFD1000605]
FX This work was supported by the National Key Research & Development
   Program of China (2018YFD1000605).
CR Aarts MGM, 1995, PLANT CELL, V7, P2115, DOI 10.1105/tpc.7.12.2115
   Aharoni A, 2004, PLANT CELL, V16, P2463, DOI 10.1105/tpc.104.022897
   Ahmad HM, 2021, SAUDI J BIOL SCI, V28, P6884, DOI 10.1016/j.sjbs.2021.07.077
   Ai WF, 2022, MOL ECOL RESOUR, V22, P2396, DOI 10.1111/1755-0998.13616
   Arya GC, 2021, FRONT PLANT SCI, V12, DOI 10.3389/fpls.2021.663165
   Bernard A, 2013, PROG LIPID RES, V52, P110, DOI 10.1016/j.plipres.2012.10.002
   Bi HH, 2017, BMC PLANT BIOL, V17, DOI 10.1186/s12870-017-1033-3
   Bird D, 2007, PLANT J, V52, P485, DOI 10.1111/j.1365-313X.2007.03252.x
   Blair MW, 2016, PLANT SCI, V242, P250, DOI 10.1016/j.plantsci.2015.08.004
   Cortés AJ, 2012, THEOR APPL GENET, V125, P1069, DOI 10.1007/s00122-012-1896-5
   Dai AG, 2013, NAT CLIM CHANGE, V3, P52, DOI [10.1038/NCLIMATE1633, 10.1038/nclimate1633]
   Dimopoulos N, 2020, J EXP BOT, V71, P3126, DOI 10.1093/jxb/eraa046
   Fiebig A, 2000, PLANT CELL, V12, P2001, DOI 10.1105/tpc.12.10.2001
   Fischer I, 2011, NEW PHYTOL, V190, P1032, DOI 10.1111/j.1469-8137.2011.03648.x
   Fukuda N, 2022, FRONT PLANT SCI, V13, DOI 10.3389/fpls.2022.898317
   Haslam TM, 2015, PLANT PHYSIOL, V167, P682, DOI 10.1104/pp.114.253195
   Haslam TM, 2012, PLANT PHYSIOL, V160, P1164, DOI 10.1104/pp.112.201640
   Kenrick P, 1997, NATURE, V389, P33, DOI 10.1038/37918
   Lai C, 2007, PLANT J, V50, P189, DOI 10.1111/j.1365-313X.2007.03054.x
   Lee SB, 2016, PLANT CELL PHYSIOL, V57, P2300, DOI 10.1093/pcp/pcw147
   Li N, 2021, RUSS J PLANT PHYSL+, V68, P828, DOI 10.1134/S1021443721050101
   Lü SY, 2012, PLANT PHYSIOL, V159, P930, DOI 10.1104/pp.112.198697
   Lü SY, 2009, PLANT J, V59, P553, DOI 10.1111/j.1365-313X.2009.03892.x
   Pascal S, 2013, PLANT J, V73, P733, DOI 10.1111/tpj.12060
   Patwari P, 2019, PLANT J, V98, P727, DOI 10.1111/tpj.14269
   Pennisi E, 2008, SCIENCE, V320, P171, DOI 10.1126/science.320.5873.171
   Pfister B, 2016, CELL MOL LIFE SCI, V73, P2781, DOI 10.1007/s00018-016-2250-x
   Qi CH, 2019, HORTIC PLANT J, V5, P1, DOI 10.1016/j.hpj.2018.11.003
   Rizwan HM, 2022, FRONT PLANT SCI, V13, DOI 10.3389/fpls.2022.898307
   Rowland O, 2006, PLANT PHYSIOL, V142, P866, DOI 10.1104/pp.106.086785
   Samuels L, 2008, ANNU REV PLANT BIOL, V59, P683, DOI 10.1146/annurev.arplant.59.103006.093219
   Seo PJ, 2011, PLANT CELL, V23, P1138, DOI 10.1105/tpc.111.083485
   Shepherd T, 2006, NEW PHYTOL, V171, P469, DOI 10.1111/j.1469-8137.2006.01826.x
   Shi L, 2019, PLANT PHYSIOL, V181, P901, DOI 10.1104/pp.19.00722
   Tresch S, 2012, PHYTOCHEMISTRY, V76, P162, DOI 10.1016/j.phytochem.2011.12.023
   Tsuwamoto R, 2010, PLANT MOL BIOL, V73, P481, DOI 10.1007/s11103-010-9634-3
   Waters ER, 2003, MOL PHYLOGENET EVOL, V29, P456, DOI 10.1016/j.ympev.2003.07.018
   Wu HQ, 2022, HORTIC RES-ENGLAND, V9, DOI 10.1093/hr/uhac004
   Wu HQ, 2019, FRONT PLANT SCI, V10, DOI 10.3389/fpls.2019.01389
   Xia YJ, 1996, PLANT CELL, V8, P1291, DOI 10.1105/tpc.8.8.1291
   Xia YJ, 1997, PLANT PHYSIOL, V115, P925, DOI 10.1104/pp.115.3.925
   Yang XP, 2020, PLANT PHYSIOL, V182, P1211, DOI 10.1104/pp.19.01002
   Yang XP, 2017, PLANT PHYSIOL, V173, P1109, DOI 10.1104/pp.16.01956
   Yeats TH, 2013, PLANT PHYSIOL, V163, P5, DOI 10.1104/pp.113.222737
   Zhang JH, 2011, J EXP BOT, V62, P3707, DOI 10.1093/jxb/err132
   Zhang Q, 2016, THEOR APPL CLIMATOL, V125, P187, DOI 10.1007/s00704-015-1503-1
   Zhao LF, 2016, PLANT PHYSIOL, V171, P960, DOI 10.1104/pp.16.00450
   Zhao Y, 2021, HORTIC RES-ENGLAND, V8, DOI 10.1038/s41438-021-00564-5
NR 48
TC 4
Z9 4
U1 8
U2 19
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
SN 1661-6596
EI 1422-0067
J9 INT J MOL SCI
JI Int. J. Mol. Sci.
PD DEC
PY 2022
VL 23
IS 24
AR 16202
DI 10.3390/ijms232416202
PG 16
WC Biochemistry & Molecular Biology; Chemistry, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Chemistry
GA 7G6MI
UT WOS:000902635400001
PM 36555843
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Junquera, AB
AF Junquera, Adela Brianso
TI Paying lip service to health: An analysis of health in climate change
   mitigation policies in Spain
SO JOURNAL OF CLIMATE CHANGE AND HEALTH
LA English
DT Article
DE Health; Climate change; Policy; Mitigation; Discourse; Co -benefits
ID CO-BENEFITS
AB A significant body of research points to the serious health dimensions of climate change. Yet, research suggests that the health agenda has so far had a limited role in global climate change policy. This study sets out to examine if and how health is represented in climate change mitigation policies in Spain. Through an interpretive discourse analysis following the 'What's the Problem Represented to be' framework, I examine whether climate change is represented to be a health 'problem' in key national policy documents and explore the meanings that stakeholders assign to climate change and health in Spain. This analysis suggests that climate change is hardly represented to be a health 'problem' in Spanish climate change mitigation policies. Instead, climate change mitigation is represented to be an economic and labour market problem. Health is relegated to the climate adaptation agenda. In turn, the representation of health is limited to quantitative gains led by air pollution reduction associated with the implementation of policies. This finding is consistent with literature in the health and climate change field. This study identifies a discrepancy between key stakeholders' ambitions to make health an overarching priority and its limited consideration in policy documents. This article concludes that the policies pay lip service to health. The importance of health is acknowledged but the measures proposed in the policies are neither driven by nor target health goals. A discrepancy between the ambition to prioritise health and its limited consideration in policy is observed. Further research on the representation of health in climate policy elsewhere would supplement these findings. (c) 2022 The Author. Published by Elsevier Masson SAS. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
C1 [Junquera, Adela Brianso] Univ Copenhagen, Sch Global Hlth, Worked carried out, Oster Farimagsgade 5,Bldg 9, DK-1353 Copenhagen K, Denmark.
C3 University of Copenhagen
RP Junquera, AB (corresponding author), Univ Copenhagen, Sch Global Hlth, Worked carried out, Oster Farimagsgade 5,Bldg 9, DK-1353 Copenhagen K, Denmark.
EM adelabrianso@gmail.com
FX The author would like to thank Anabelle Workman, L ? eopold Sal-zenstein
   and Signild Va ? llgarda for their helpful comments in early drafts. The
   author would also like to thank the two anonymous reviewers for their
   comments and suggestions.
CR [Anonymous], 2011, Referencia:BOE-A-2011-15623
   Aydin-Düzgit S, 2019, ALL AZIMUTH, V8, P285
   Bacchi C., 2009, Analysing policy: what's the problem represented to be?
   Bäckstrand K, 2006, GLOBAL ENVIRON POLIT, V6, P50
   Bambra C, 2005, HEALTH PROMOT INT, V20, P187, DOI 10.1093/heapro/dah608
   Baum FE, 2013, SOC SCI MED, V87, P138, DOI 10.1016/j.socscimed.2013.03.033
   Braithwaite I, 2019, ENVIRON HEALTH PERSP, V127, DOI 10.1289/EHP4595
   Ciscar JC, 2020, Papeles de Economia Espanola, V163, P2
   Costello A, 2009, LANCET, V373, P1693, DOI 10.1016/S0140-6736(09)60929-6
   Field C. B, 2014, Working Group II contribution to the IPCC Fifth Assessment Report Climate Change: Impacts, Adaptation, and Vulnerability, P1
   Fox M, 2019, INT J ENV RES PUB HE, V16, DOI 10.3390/ijerph16183232
   Gao JH, 2018, SCI TOTAL ENVIRON, V627, P388, DOI 10.1016/j.scitotenv.2018.01.193
   Gobierno de Espana Boletin Del Estado (BOE), 2014, Boletin Oficial Del Estado, V226, P72336
   IPCC, 2018, GLOB WARM 1 5C SUMM
   Kampa M, 2008, ENVIRON POLLUT, V151, P362, DOI 10.1016/j.envpol.2007.06.012
   Koivusalo M, 2010, J EPIDEMIOL COMMUN H, V64, P500, DOI 10.1136/jech.2009.102020
   Kurze K, 2018, ENVIRON POLICY GOV, V28, P329, DOI 10.1002/eet.1819
   Matthews B., 2010, RES METHODS PRACTICA
   Nemet GF, 2010, ENVIRON RES LETT, V5, DOI 10.1088/1748-9326/5/1/014007
   Romanello M, 2021, LANCET, V398, P1619, DOI [10.1016/S0140-6736(21)01787-6, 10.1016/S0140-6736(23)01859-7]
   Sainz-Elipe S, 2010, MALARIA J, V9, DOI 10.1186/1475-2875-9-221
   Sampedro J, 2020, ENVIRON INT, V136, DOI 10.1016/j.envint.2020.105513
   Scovronick N, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-09499-x
   Simon F, 2005, Euro Surveill, V10, P156, DOI 10.2807/esm.10.07.00555-en
   Smith KR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P709
   UNFCCC, 2021, Introduction to mitigation
   UNFCCC, 2021, What do adaptation to climate change and climate resilience mean?
   WALT G, 1994, HEALTH POLICY PLANN, V9, P353, DOI 10.1093/heapol/9.4.353
   Watts N, 2021, LANCET, V397, P129, DOI 10.1016/S0140-6736(20)32290-X
   Watts N, 2019, LANCET, V394, P1836, DOI 10.1016/S0140-6736(19)32596-6
   Workman A, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/aba8c3
   Workman A, 2019, CLIM POLICY, V19, P585, DOI 10.1080/14693062.2018.1544541
NR 32
TC 2
Z9 2
U1 0
U2 0
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
PY 2022
VL 6
AR 100128
DI 10.1016/j.joclim.2022.100128
PG 5
WC Environmental Sciences; Public, Environmental & Occupational Health
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology; Public, Environmental & Occupational
   Health
GA YE8M3
UT WOS:001266900400020
OA gold
DA 2025-01-10
ER

PT J
AU van den Hurk, B
   Bisaro, A
   Haasnoot, M
   Nicholls, RJ
   Rehdanz, K
   Stuparu, D
AF van den Hurk, Bart
   Bisaro, Alexander
   Haasnoot, Marjolijn
   Nicholls, Robert J.
   Rehdanz, Katrin
   Stuparu, Dana
TI Living with sea-level rise in North-West Europe: Science-policy
   challenges across scales
SO CLIMATE RISK MANAGEMENT
LA English
DT Article
DE Sea Level Rise; Coastal management; Climate adaptation
ID CLIMATE; FLOOD; MANAGEMENT; ENGLAND; ADAPT
AB Sea-level rise (SLR) confronts coastal societies and stakeholders with increasing hazards and coastal risks with large uncertainties associated to these changes. Adaptation to SLR requires societal and policy decision-making to consider these changing risks, which are in turn defined by socio-economic development objectives and the local societal context. Here, we review some of the key challenges facing governments, stakeholders and scientists in adapting to SLR, and key aspects of successful adaptation, by exploring different approaches to SLR and coastal adaptation planning in three western European countries, the Netherlands, Germany and the United Kingdom. Several common challenges of SLR adaptation emerge across the different settings, including the inherent uncertainty regarding future conditions, the significant social and socioeconomic consequences, the consideration and distribution of (residual) risk over communities, and the long legacy of present-day decisions that affect future risk and management options supporting future generations. These challenges are addressed differently in the three countries, e. g. in the governance level at which adaptation is initiated, although common elements also emerge. One common emerging element is adaptive pathways planning, which entails dynamic decision-making that breaks uncertain decisions into manageable elements or steps over time, while keeping options for the future. Another common element is the development of effective local science-policy interfaces, as engagement of local decision-makers and citizens is essential to manage conflicting interests. Lastly, we find that social and communication sciences have great potential to support effective science-policy interfaces, e.g. though identifying societal tipping points. Yet, in decisions on SLR adaptation, insights from these fields are rarely used to date. We conclude that supporting science-policy interactions for adaptation decision-making at relevant (inter)national to local scales through tailored multi-disciplinary scientific assessments is an important way forward for SLR adaptation in Europe.
C1 [van den Hurk, Bart] Deltares & VU Univ Amsterdam, Amsterdam, Netherlands.
   [Bisaro, Alexander] Global Climate Forum, Berlin, Germany.
   [Haasnoot, Marjolijn] Deltares & Utrecht Univ, Utrecht, Netherlands.
   [Nicholls, Robert J.] Univ East Anglia, Tyndall Ctr Climate Change Res, Norwich, England.
   [Rehdanz, Katrin] Univ Kiel, Dept Econ, Kiel, Germany.
   [Stuparu, Dana] Deltares, Delft, Netherlands.
C3 University of East Anglia; University of Kiel; Deltares
RP van den Hurk, B (corresponding author), Deltares & VU Univ Amsterdam, Amsterdam, Netherlands.
EM Bart.vandenHurk@deltares.nl; sandy.bisaro@globalclimateforum.org;
   Marjolijn.Haasnoot@deltares.nl; Robert.Nicholls@uea.ac.uk;
   rehdanz@economics.uni-kiel.de
RI Nicholls, Robert/G-3898-2010; van den Hurk, Bart/ABI-1654-2020;
   Haasnoot, Marjolijn/H-4827-2012
OI Stuparu, Dana/0000-0001-5853-2980; van den Hurk,
   Bart/0000-0003-3726-7086
FU project RECEIPT (REmote Climate Effects and their Impact on European
   sustainability, Policy and Trade) from the European Union [820712];
   Federal Ministry of Education and Research (BMBF), Germany from the
   European Union [1LA1812A/C, 101003598]
FX The webinar "Living with sea Level Rise" at the ECCA21 conference and
   this manuscript have been supported by the conference secretariat and by
   the project RECEIPT (REmote Climate Effects and their Impact on European
   sustainability, Policy and Trade) which received funding from the
   European Union's Horizon 2020 Research and Innovation Programme under
   Grant agreement No. 820712. It was also supported by the research
   project GoCoase, funded by the Federal Ministry of Education and
   Research (BMBF), Germany, grant number 1LA1812A/C and the research
   project CoCliCo (Coastal Climate Core Service) which received funding
   from the European Union's Horizon 2020 Research and Innovation Programme
   under Grant agreement No. 101003598. We are grateful for the
   contribution of Jacobus Hofstede (Ministry of Energy, Agriculture, the
   Environment, Nature and Digitalization of Schleswig-Holstein) and
   Annemiek Roeling (manager of Dutch ministry of infrastructure Knowledge
   Program on Sea Level Rise) for their contributions to the webinar. Also
   three anonymous reviewers are acknowledged for their constructive
   comments on earlier versions of this manuscript.
CR Anderhub V., 2001, GER ECON REV, V2, P239, DOI [DOI 10.1111/1468-0475.00036, 10.1111/1468-0475.00036]
   [Anonymous], 2014, OECD Studies on Water, DOI DOI 10.1787/9789264102637-EN
   Ardeshiri A, 2019, OCEAN COAST MANAGE, V178, DOI 10.1016/j.ocecoaman.2019.05.007
   Bamber JL, 2019, P NATL ACAD SCI USA, V116, P11195, DOI 10.1073/pnas.1817205116
   Bisaro A, 2020, ENVIRON SCI POLICY, V112, P203, DOI 10.1016/j.envsci.2020.05.018
   Bloemen P.J.T.M., 2019, DECISION MAKING DEEP, DOI [10.1007/978-3-030-05252-2_14 321 351, DOI 10.1007/978-3-030-05252-2_14321351]
   Bouwer LM, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aa98a3
   Brady AF, 2017, OCEAN COAST MANAGE, V143, P164, DOI 10.1016/j.ocecoaman.2016.11.013
   Cash DW, 2003, P NATL ACAD SCI USA, V100, P8086, DOI 10.1073/pnas.1231332100
   Christel I, 2018, CLIM SERV, V9, P111, DOI 10.1016/j.cliser.2017.06.002
   Climate Change Committee (CCC), 2018, MAN COAST CHANG CLIM
   Dronkers J., 1990, Strategies for Adaption to Sea Level Rise, Report of the IPCC Coastal Zone Management Subgroup: Intergovernmental Panel on Climate Change
   Fox-Kemper B., 2021, AGU FALL M
   Gralepois M, 2016, ECOL SOC, V21, DOI 10.5751/ES-08907-210437
   Haasnoot M, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab666c
   Haasnoot M., 2019, 11203724004 DELT
   Haasnoot M, 2020, REG ENVIRON CHANGE, V20, DOI 10.1007/s10113-020-01623-8
   Haasnoot M, 2018, GLOBAL ENVIRON CHANG, V52, P273, DOI 10.1016/j.gloenvcha.2018.08.003
   Haasnoot M, 2013, GLOBAL ENVIRON CHANG, V23, P485, DOI 10.1016/j.gloenvcha.2012.12.006
   Haigh I.D., 2020, MCCIP Sci. Rev, V2020, P546, DOI DOI 10.14465/2020.ARC23.CFL
   Hinkel J, 2018, NAT CLIM CHANGE, V8, P570, DOI 10.1038/s41558-018-0176-z
   Hofstede J, 2019, Die Kuste, DOI 10.18171/1.087103
   Hutton NS, 2019, J FLOOD RISK MANAG, V12, DOI 10.1111/jfr3.12469
   Jensen J., 2008, KUSTE, V74, P92
   Johnston RJ, 2018, COAST MANAGE, V46, P259, DOI 10.1080/08920753.2018.1474067
   Kabat P., 2005, CLIMATE PROOFING NET
   Klijn F, 2012, AMBIO, V41, P180, DOI 10.1007/s13280-011-0193-x
   Lamb H. H., 1991, Historic storms of the North Sea, British Isles and northwest Europe
   Landry Craig., 2003, Marine Resource Economics, V18, P105, DOI [10.1086/mre.18.2.42629388, DOI 10.1086/mre.18.2.42629388]
   Le Cozannet G, 2017, J MAR SCI ENG, V5, DOI 10.3390/jmse5040049
   Lee M, 2001, GEOGR J, V167, P39, DOI 10.1111/1475-4959.00004
   Mach K.J., 2021, SCIENCE
   Masselink G, 2019, WATER-SUI, V11, DOI 10.3390/w11122587
   Masson-Delmotte V., 2021, Climate Change 2021: the physical science basis, P3
   Mauch F., 2012, ENV SOC PORTAL ARCAD, V6, DOI [10.5282/rcc/3733, DOI 10.5282/RCC/3733]
   McEvoy S, 2021, OCEAN COAST MANAGE, V203, DOI 10.1016/j.ocecoaman.2020.105512
   McRobie A, 2005, PHILOS T R SOC A, V363, P1263, DOI 10.1098/rsta.2005.1567
   MELUR, 2001, GEN KUST INT KUST SC
   MELUR, 2013, GEN PLAN KUST LAND S
   Meyerhoff J, 2021, J ENVIRON ECON POLIC, V10, P374, DOI 10.1080/21606544.2021.1894990
   Mullin M, 2019, CLIMATIC CHANGE, V152, P275, DOI 10.1007/s10584-018-2191-5
   Nicholls RJ, 2013, OCEAN ENG, V71, P3, DOI 10.1016/j.oceaneng.2013.01.025
   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]
   Penning-Rowsell EC, 2015, GEOFORUM, V62, P131, DOI 10.1016/j.geoforum.2015.03.019
   Po urtner H.-O., 2019, IPCC SPECIAL REPORT, P755, DOI [10.1017/9781009157964, DOI 10.1017/9781009157964]
   Pranzini E, 2015, J COAST CONSERV, V19, P445, DOI 10.1007/s11852-015-0399-3
   Ranger N, 2013, EURO J DECIS PROCESS, V1, P233, DOI 10.1007/s40070-013-0014-5
   SAATY RW, 1987, MATH MODELLING, V9, P161, DOI 10.1016/0270-0255(87)90473-8
   Saengsupavanich C, 2013, J ENVIRON MANAGE, V115, P106, DOI 10.1016/j.jenvman.2012.11.029
   Siders AR, 2019, SCIENCE, V365, P761, DOI 10.1126/science.aax8346
   Taylor BM, 2012, URBAN POLICY RES, V30, P5, DOI 10.1080/08111146.2011.639178
   Thorne C.R., 2014, FUTUR FLOODING COAST, DOI [10.1680/ffacer.34495, DOI 10.1680/FFACER.34495]
   Townend BIH, 2021, SCI TOTAL ENVIRON, V783, DOI 10.1016/j.scitotenv.2021.146880
   Van Alphen J, 2016, J FLOOD RISK MANAG, V9, P310, DOI 10.1111/jfr3.12183
   Wadey MP, 2015, FRONT MAR SCI, V2, DOI 10.3389/fmars.2015.00084
   Wang ZB, 2018, NETH J GEOSCI, V97, P183, DOI 10.1017/njg.2018.8
   Wannewitz M, 2021, NAT HAZARD EARTH SYS, V21, P3285, DOI 10.5194/nhess-21-3285-2021
   Winter R, 2008, EUR J INFORM SYST, V17, P470, DOI 10.1057/ejis.2008.44
   Wouters B, 2019, FRONT EARTH SC-SWITZ, V7, DOI 10.3389/feart.2019.00096
   Zscheischler J, 2018, NAT CLIM CHANGE, V8, P469, DOI 10.1038/s41558-018-0156-3
NR 60
TC 9
Z9 9
U1 1
U2 18
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2212-0963
J9 CLIM RISK MANAG
JI CLIM. RISK MANAG.
PY 2022
VL 35
AR 100403
DI 10.1016/j.crm.2022.100403
EA JAN 2022
PG 11
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 0G0RO
UT WOS:000777762300005
OA Green Published, gold, Green Accepted
DA 2025-01-10
ER

PT J
AU Furlan, E
   Dalla Pozza, P
   Michetti, M
   Torresan, S
   Critto, A
   Marcomini, A
AF Furlan, E.
   Dalla Pozza, P.
   Michetti, M.
   Torresan, S.
   Critto, A.
   Marcomini, A.
TI Development of a Multi-Dimensional Coastal Vulnerability Index:
   Assessing vulnerability to inundation scenarios in the Italian coast
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Coastal vulnerability assessment; Climate and socio-economic scenarios;
   Coastal adaptation; Geographic Information Systems; Italian coastal
   areas
AB Understanding how natural and human-induced drivers will contribute to rising vulnerability and risks in coastal areas requires a broader use of future projections capturing the spatio-temporal dynamics which drive changes in the different vulnerability dimensions, including the solo-demographic and economic spheres.
   To go beyond the traditional approaches for coastal vulnerability appraisal, a Multi-dimensional Coastal Vulnerability Index (MDim-CVI) - integrating a composite set of physical, environmental and socio-economic indicators - is proposed to rank Italian coastal provinces according to their relative vulnerability to extreme sea level scenarios, in 2050. Specifically, information on hazard-prone areas, potentially inundated by sea level rise and extreme water levels (under the RCP8.5 climate scenario) is combined with indicators of geomorphic vulnerability (e.g. elevation, distance from coastline, shoreline evolution trend) exposure, and adaptive capacity (e.g. sensible segments of the population, GDP, land use patterns). The methodology is applied to a reference timeframe, representing current climate and land use condition, and a future scenario for the year 2050, integrating both climate projections and data simulating potential evolution of the environmental and socio-economic systems.
   Results show that most vulnerable provinces are located in the North Adriatic, the Gargano area and other Southern parts of Italy, mostly due to the very high vulnerability scores reported by climate-related indicators (e.g. extreme sea level). The number of vulnerable provinces as well as the magnitude of vulnerability is expected to increase in the future due to the worsening of climate, environmental, and socio-economic conditions (e.g. land use variations and increase of the elderly population). These outcomes can timely inform integrated coastal zone management and support climate adaptation planning. (C) 2021 Elsevier B.V. All rights reserved.
C1 [Furlan, E.; Michetti, M.; Torresan, S.; Critto, A.; Marcomini, A.] Fdn Ctr Euromediterraneo Cambiamenti Climat, I-73100 Lecce, Italy.
   [Furlan, E.; Dalla Pozza, P.; Torresan, S.; Critto, A.; Marcomini, A.] Univ Ca Foscari Venice, Dept Environm Sci Informat & Stat, I-30170 Venice, Italy.
   [Michetti, M.] ENEA Ctr Ric Bologna, Div Models & Technol Risk Reduct, Via Martiri di Monte Sole 4, Bologna, Italy.
C3 Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC); Universita Ca
   Foscari Venezia
RP Critto, A (corresponding author), Fdn Ctr Euromediterraneo Cambiamenti Climat, I-73100 Lecce, Italy.; Critto, A (corresponding author), Univ Ca Foscari Venice, Dept Environm Sci Informat & Stat, I-30170 Venice, Italy.
EM critto@unive.it
RI Michetti, Melania/AAB-4075-2021; Furlan, Elisa/AAA-4247-2021; Marcomini,
   Antonio/JSL-7114-2023
OI michetti, melania/0000-0001-6649-1349
FU SAVEMEDCOAST project (Sea level rise scenarios along the Mediterranean
   coasts); European Union Humanitarian Aid and Civil Protection
   [ECHO/SUB/2016/742473/PREV16]
FX The research leading to these results has been funded by the
   SAVEMEDCOAST project (Sea level rise scenarios along the Mediterranean
   coasts, www.savemedcoasts.eu) funded by the European Union Humanitarian
   Aid and Civil Protection (Reference number:
   ECHO/SUB/2016/742473/PREV16). The authors gratefully acknowledge their
   colleagues Dr. Shouro Dasgupta and Dr. Mattia Amadio for their valuable
   advice on the construction of the economic and social sub-indices.
CR Abuodha P.A., 2006, ASSESSING VULNERABIL
   [Anonymous], 2012, MEET REP WORK NAT US
   [Anonymous], 1994, J. Coast Res.
   [Anonymous], 2014, Climate change 2014: synthesis report
   Antonioli F, 2017, QUATERNARY SCI REV, V158, P29, DOI 10.1016/j.quascirev.2016.12.021
   Anzidei M, 2017, TERRA NOVA, V29, P44, DOI 10.1111/ter.12246
   Anzidei Marco, 2015, FORMS T OBJECTIVE AC
   Balica SF, 2012, NAT HAZARDS, V64, P73, DOI 10.1007/s11069-012-0234-1
   Bertoni D, 2019, OCEAN COAST MANAGE, V180, DOI 10.1016/j.ocecoaman.2019.104916
   Bonaldo D., 2018, INTEGRATINGMULTIDISC
   Diaz-cuevas P., 2020, HIERARCHY PROCESS, V189, DOI [10.1016/j.ocecoaman.2020.105146, DOI 10.1016/J.OCECOAMAN.2020.105146]
   EC E.C, 2018, WILL WE BE AFFECTED
   European Commission EIB & EBRD, 2017, JASPERS Guidance Note. The Basics of Climate Change Adaptation-Vulnerability and Risk Assessment
   Frigerio I, 2016, APPL GEOGR, V74, P12, DOI 10.1016/j.apgeog.2016.06.014
   Gallina V, 2019, WATER-SUI, V11, DOI 10.3390/w11061300
   Giardino A, 2019, WATER-SUI, V11, DOI 10.3390/w11010061
   Giorgi F, 2006, GEOPHYS RES LETT, V33, DOI 10.1029/2006GL025734
   Gornitz V., 1991, Vulnerability of the US to future sea level rise
   Greco M, 2016, NAT HAZARDS, V82, pS7, DOI 10.1007/s11069-016-2293-1
   Gutierrez BT, 2011, J GEOPHYS RES-EARTH, V116, DOI [10.1029/2010JF001891, 10.1029/20101F001891]
   ISPRA, 2014, GUID ENV STUD REL CO, V20
   ISPRA, 2016, ANN DAT AMB 2016, V2016, P71
   ISTAT, 2018, Annuario Statistico Italiano 2018
   Istat, 2017, FUT DEM PAES, V2065, P1
   ISTAT,, 2008, PREV DEM, P1
   Jurgilevich A, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa5508
   Kebede AS, 2018, SCI TOTAL ENVIRON, V635, P659, DOI 10.1016/j.scitotenv.2018.03.368
   Koks EE, 2015, ENVIRON SCI POLICY, V47, P42, DOI 10.1016/j.envsci.2014.10.013
   Koroglu A, 2019, OCEAN COAST MANAGE, V178, DOI 10.1016/j.ocecoaman.2019.05.001
   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
   Marignani M, 2017, SCI TOTAL ENVIRON, V590, P566, DOI 10.1016/j.scitotenv.2017.02.221
   Marsico A, 2017, J MAPS, V13, P961, DOI 10.1080/17445647.2017.1415989
   Maselli F, 2012, CLIM RES, V54, P271, DOI 10.3354/cr01121
   Mathew MJ, 2020, SCI TOTAL ENVIRON, V706, DOI 10.1016/j.scitotenv.2019.135963
   MATTM, 2017, PIAN NAZ AD CAMB CLI
   MATTM, 2014, STRAT NAZ AS CAMB CL
   McLaughlin S, 2010, ENVIRON HAZARDS-UK, V9, P233, DOI 10.3763/ehaz.2010.0052
   Mentaschi L, 2017, GEOPHYS RES LETT, V44, P2416, DOI 10.1002/2016GL072488
   Mercogliano P., 2013, 21 CENT CLIM CHANG I
   Moss RH, 2010, NATURE, V463, P747, DOI 10.1038/nature08823
   Munafo M., 2016, CONSUMO SUOLO DINAMI
   Murakami D, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11072106
   Mysiak J, 2018, PHILOS T R SOC A, V376, DOI 10.1098/rsta.2017.0305
   Ng K, 2019, SCI TOTAL ENVIRON, V690, P1218, DOI 10.1016/j.scitotenv.2019.07.013
   Niesing H., 2005, Dunes and Estuaries 2005, P421
   Ozyurt G, 2007, Vulnerability of coastal areas to sea level rise: a case study on Goksu Delta
   Pantusa D, 2018, WATER-SUI, V10, DOI 10.3390/w10091218
   Peltier WR, 2004, ANNU REV EARTH PL SC, V32, P111, DOI 10.1146/annurev.earth.32.082503.144359
   Pendleton ElizabethA. E., 2005, COASTAL VULNERABILIT
   Pollino CA, 2007, ENVIRON MODELL SOFTW, V22, P1140, DOI 10.1016/j.envsoft.2006.03.006
   Preston B.L., 2008, PREPARED SYDNEY COAS
   Riahi K, 2011, CLIMATIC CHANGE, V109, P33, DOI 10.1007/s10584-011-0149-y
   Rizzi J., 2017, J COAST CONSERV, P1
   Ronco P, 2015, HYDROL EARTH SYST SC, V19, P1561, DOI 10.5194/hess-19-1561-2015
   Salman A., 2004, Living with coastal erosion in Europe: sediment and space for sustainability. Part I - Major findings and policy recommendations of the EUROSION project
   Santini M, 2011, REG ENVIRON CHANGE, V11, P483, DOI 10.1007/s10113-010-0157-x
   Sanuy M, 2020, COAST ENG, V157, DOI 10.1016/j.coastaleng.2019.103627
   Satta A, 2017, INT J DISAST RISK RE, V24, P284, DOI 10.1016/j.ijdrr.2017.06.018
   Satta A, 2016, ESTUAR COAST SHELF S, V175, P93, DOI 10.1016/j.ecss.2016.03.021
   Scoccimarro E, 2011, J CLIMATE, V24, P4368, DOI 10.1175/2011JCLI4104.1
   Sekovski I, 2020, OCEAN COAST MANAGE, V183, DOI 10.1016/j.ocecoaman.2019.104982
   Soldati M, 2017, WOR GEOMORPHOL LANDS, P1, DOI 10.1007/978-3-319-26194-2
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Szlafsztein Claudio, 2007, Journal of Coastal Conservation, V11, P53, DOI 10.1007/s11852-007-0003-6
   Tate E, 2010, ENVIRON PLANN B, V37, P646, DOI 10.1068/b35157
   Thieler E.R., 2000, US GEOL SURV, P99
   Torresan S, 2012, NAT HAZARD EARTH SYS, V12, P2347, DOI 10.5194/nhess-12-2347-2012
   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
   UNISDR, 2016, SEND FRAM DIS RISK R
   Verburg PH, 2008, ANN REGIONAL SCI, V42, P57, DOI 10.1007/s00168-007-0136-4
   Vousdoukas MI, 2017, EARTHS FUTURE, V5, P304, DOI 10.1002/2016EF000505
   Weiland FCS, 2010, HYDROL EARTH SYST SC, V14, P1595, DOI 10.5194/hess-14-1595-2010
   Zald A.E., 2006, A Z GIS ILLUSTRATED
NR 75
TC 45
Z9 46
U1 1
U2 45
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 10
PY 2021
VL 772
AR 144650
DI 10.1016/j.scitotenv.2020.144650
EA FEB 2021
PG 19
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA QW6JO
UT WOS:000628753700002
PM 33770878
DA 2025-01-10
ER

PT J
AU Ibrahim, S
   Ziedan, I
   Ahmed, A
AF Ibrahim, Sara
   Ziedan, Ibrahim
   Ahmed, Ayman
TI Study of Climate Change Detection in North-East Africa Using Machine
   Learning and Satellite Data
SO IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE
   SENSING
LA English
DT Article
DE Meteorology; Climate change; Terrestrial atmosphere; Atmospheric
   modeling; Ocean temperature; Greenhouse effect; Sea measurements;
   Climate change; greenhouse gases (GHGs); machine learning (ML); neural
   network; space systems
ID RETRIEVAL ALGORITHM; NEURAL-NETWORK; CNN-RNN; VALIDATION; CARBON; CO2;
   TEMPERATURE; PERFORMANCE; SCIENCE; GOSAT
AB The study of climate change has become an important topic because of its negative impact on human life. The North-East African part lacks the studies for climate change detection, despite it being one of the most affected parts worldwide. The relationship between the emission of greenhouse gases (GHGs) and climate change is an important factor to understand. To investigate this linkage, we used machine-learning (ML) models based on essential climate variables (ECVs) to investigate the relationship between the GHGs and the rhythm of climate variable change. The article investigates how ML techniques can be applied to climatic data to build an ML model that is able to predict the state of climate variables for the short and long term. By selecting a candidate model, it will help in climate adaptation and mitigation, also determine at what level GHGs should be kept and their corresponding concentrations in order to avoid climate events and crises. The used models are long short-term memory, autoencoders, and convolutional neural network (CNN). Alternatively, the dataset has been selected from U.K. National Centre for Earth Observation and Copernicus Climate Change Services. We compared the performance of these techniques and the best candidate was the Head-CNN; based on performance metrics such as root-mean-squared-error: 5.378, 2.395, and 15.923, mean-absolute-error: 4.157, 1.928, and11.672, Pearson: 0.368, 0.649, and 0.291, and R-2 coefficient: 0.607, 0.806, and 0.539 for the ECVs temperature, CO2, and CH4, respectively. We were able to link the GHG emission to ECVs with high accuracy based on the reading of this geographic area.
C1 [Ibrahim, Sara; Ziedan, Ibrahim] Zagazig Univ, Fac Engn, Dept Comp & Syst, Zagazig, Egypt.
   [Ahmed, Ayman] Egyptian Space Agcy, Cairo 1564, Egypt.
C3 Egyptian Knowledge Bank (EKB); Zagazig University
RP Ibrahim, S (corresponding author), Zagazig Univ, Fac Engn, Dept Comp & Syst, Zagazig, Egypt.
EM sara.khalil@zu.edu.eg; ieziedan@gmail.com; ayman.ahmed@egsa.gov.eg
RI Ahmed, Ayman/D-2280-2017; Ibrahim, Sara K./M-2861-2018
OI Ahmed, Ayman/0000-0002-9508-7449; Ibrahim, Sara K./0000-0002-9320-3661
FU Space Plasma Nanosatellite Experiment Mission Alliance - Academy of
   Scientific Research and Technology; Egyptian Space Agency, Egypt
   [SPNEX-2021]
FX This work was supported by the Space Plasma Nanosatellite Experiment
   Mission Alliance, funded by Academy of Scientific Research and
   Technology and the Egyptian Space Agency, Egypt under Grant SPNEX-2021.
CR Abadi M, 2016, ACM SIGPLAN NOTICES, V51, P1, DOI [10.1145/2951913.2976746, 10.1145/3022670.2976746]
   Acito N, 2020, IEEE T GEOSCI REMOTE, V58, P8163, DOI 10.1109/TGRS.2020.2987905
   Ahmed A., 2019, AEROSP CONF PROC, P1, DOI [10.1109/AERO.2019.8742023, DOI 10.1109/aero.2019.8742023, DOI 10.1109/AERO.2019.8742023]
   Albiñana AP, 2017, PROC SPIE, V10403, DOI 10.1117/12.2268875
   Amin A, 2018, ATMOS RES, V213, P422, DOI 10.1016/j.atmosres.2018.06.021
   [Anonymous], 2018, Machine Learning Algorithms: Popular Algorithms for Data Science and Machine Learning
   Bergamaschi P, 2007, J GEOPHYS RES-ATMOS, V112, DOI 10.1029/2006JD007268
   Blanco G., 2014, CLIMATECHANGE 2014 M
   Botchkarev A., 2018, Performance Metrics (Error Measures) in Machine Learning Regression, Forecasting and Prognostics: Properties and Typology"
   Buchwitz M, 2015, REMOTE SENS ENVIRON, V162, P344, DOI 10.1016/j.rse.2013.04.024
   Buchwitz M., 2015, P 36 INT S REM SENS
   Buchwitz M., 2016, SPECIAL PUBLICATION
   Buchwitz M, 2017, ATMOS CHEM PHYS, V17, P5751, DOI 10.5194/acp-17-5751-2017
   Butz A, 2011, GEOPHYS RES LETT, V38, DOI 10.1029/2011GL047888
   Caldecott B., 2018, PT1 GLOBAL PROCESSES, P3
   Canizo M, 2019, NEUROCOMPUTING, V363, P246, DOI 10.1016/j.neucom.2019.07.034
   Collier P, 2008, OXFORD REV ECON POL, V24, P337, DOI 10.1093/oxrep/grn019
   Crisp D, 2015, PROC SPIE, V9607, DOI 10.1117/12.2187291
   Crisp D, 2017, ATMOS MEAS TECH, V10, P59, DOI 10.5194/amt-10-59-2017
   Deng L, 2013, FOUND TRENDS SIGNAL, V7, pI, DOI 10.1561/2000000039
   Dils B, 2014, ATMOS MEAS TECH, V7, P1723, DOI 10.5194/amt-7-1723-2014
   Doelling DR, 2013, IEEE T GEOSCI REMOTE, V51, P1245, DOI 10.1109/TGRS.2012.2227760
   Feng J, 2019, INT GEOSCI REMOTE SE, P588, DOI [10.1109/IGARSS.2019.8897819, 10.1109/igarss.2019.8897819]
   Funk C, 2020, NATURE, V586, P645, DOI 10.1038/d41586-020-02698-3
   Gentine P, 2018, GEOPHYS RES LETT, V45, P5742, DOI 10.1029/2018GL078202
   Gettelman A., 2016, Demystifying Climate Models, V2, DOI [10.1007/978-3-662-48959-8, DOI 10.1007/978-3-662-48959-8]
   Goodfellow I, 2016, ADAPT COMPUT MACH LE, P1
   Graves A, 2012, STUD COMPUT INTELL, V385, P5
   Guo LJ, 2015, IEEE J-STARS, V8, P376, DOI 10.1109/JSTARS.2014.2363019
   Hagenlocher M, 2014, IEEE J-STARS, V7, P229, DOI 10.1109/JSTARS.2013.2259579
   Hakkarainen J, 2016, GEOPHYS RES LETT, V43, P11400, DOI 10.1002/2016GL070885
   Han ZY, 2021, IEEE SENS J, V21, P7833, DOI 10.1109/JSEN.2019.2923982
   Hastie T., 2001, Springer Series in Statistics, DOI [10.1007/978- 0-387-21606-5, DOI 10.1007/978-0-387-21606-5, DOI 10.1007/B9460815]
   He ZH, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12030576
   Hersbach H, 2020, Q J ROY METEOR SOC, V146, P1999, DOI 10.1002/qj.3803
   Hu MY, 1999, DECISION SCI, V30, P197, DOI 10.1111/j.1540-5915.1999.tb01606.x
   Huntingford C, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab4e55
   Ibrahim SK, 2020, AIN SHAMS ENG J, V11, P45, DOI 10.1016/j.asej.2019.08.006
   Ibrahim SK, 2019, IEEE T AERO ELEC SYS, V55, P1816, DOI 10.1109/TAES.2018.2876586
   IPCC, 2018, GLOBAL WARMING 15 C, V1st, DOI [10.1017/9781009157940, DOI 10.1017/9781009157940]
   Kalinicheva E, 2020, IEEE J-STARS, V13, P1450, DOI 10.1109/JSTARS.2020.2982631
   Kataoka F, 2019, IEEE T GEOSCI REMOTE, V57, P3490, DOI 10.1109/TGRS.2018.2885162
   Keppel-Aleks G, 2013, ATMOS CHEM PHYS, V13, P4349, DOI 10.5194/acp-13-4349-2013
   Kim S, 2019, IEEE WINT CONF APPL, P1761, DOI 10.1109/WACV.2019.00192
   Knüsel B, 2019, NAT CLIM CHANGE, V9, P196, DOI 10.1038/s41558-019-0404-1
   Lazar B, 2008, COLD REG SCI TECHNOL, V51, P219, DOI 10.1016/j.coldregions.2007.03.015
   LeCun Y, 2015, NATURE, V521, P436, DOI 10.1038/nature14539
   Liu Y, 2016, Application of Deep Convolutional Neural Networks for Detecting Extreme Weather in Climate Datasets
   Liu Y, 2018, SCI BULL, V63, P1200, DOI 10.1016/j.scib.2018.08.004
   Matsunaga T., 2019, AGUFM, V2019, pA52H
   Monteleoni C, 2013, COMPUT SCI ENG, V15, P32, DOI 10.1109/MCSE.2013.50
   Muthoni F, 2020, IEEE J-STARS, V13, P2960, DOI 10.1109/JSTARS.2020.2997075
   Nassar R, 2017, GEOPHYS RES LETT, V44, P10045, DOI 10.1002/2017GL074702
   Nicholson SE., 1996, LIMNOLOGY CLIMATOLOG, P25, DOI DOI 10.1201/9780203748978-2
   Olhoff A., 2018, EMISSIONS GAP REPORT
   Plummer S, 2017, REMOTE SENS ENVIRON, V203, P2, DOI 10.1016/j.rse.2017.07.014
   Poghosyan A, 2017, PROG AEROSP SCI, V88, P59, DOI 10.1016/j.paerosci.2016.11.002
   Qian YM, 2016, IEEE-ACM T AUDIO SPE, V24, P2263, DOI 10.1109/TASLP.2016.2602884
   Rapp D., 2014, ASSESSING CLIMATE CH
   Reichstein M, 2019, NATURE, V566, P195, DOI 10.1038/s41586-019-0912-1
   Reuter M, 2020, ATMOS MEAS TECH, V13, P789, DOI 10.5194/amt-13-789-2020
   Rodgers C.D., 2004, Inverse Methods for Atmospheric Sounding: Theory and Practice, DOI DOI 10.1142/3171
   RODGERS CD, 1976, REV GEOPHYS, V14, P609, DOI 10.1029/RG014i004p00609
   Rolnick D., 2019, Tackling climate change with machine learning
   Schneising O, 2018, Advances in Astronautics Science and Technology, V1, P57, DOI DOI 10.1007/S42423-018-0004-6
   Ssenyunzi RC, 2020, ADV SPACE RES, V65, P1877, DOI 10.1016/j.asr.2020.02.003
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Sutton RT, 2007, GEOPHYS RES LETT, V34, DOI 10.1029/2006GL028164
   Tanaka T, 2016, IEEE T GEOSCI REMOTE, V54, P4367, DOI 10.1109/TGRS.2016.2539973
   Tsironi E, 2017, NEUROCOMPUTING, V268, P76, DOI 10.1016/j.neucom.2016.12.088
   Vogel A., 2018, Africa climate change 2007: Impacts, adaptation and vulnerability: Contribution of working group ii to the fourth assessment report of the intergovernmental panel on climate change
   Wainwright CM, 2021, WEATHER, V76, P26, DOI 10.1002/wea.3824
   Wang TX, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0105050
   Wunch D, 2017, ATMOS MEAS TECH, V10, P2209, DOI 10.5194/amt-10-2209-2017
   Yan X, 2020, IEEE T GEOSCI REMOTE, V58, P8427, DOI 10.1109/TGRS.2020.2987896
   Yin CY, 2022, IEEE T SYST MAN CY-S, V52, P112, DOI 10.1109/TSMC.2020.2968516
   Yoshida Y, 2013, ATMOS MEAS TECH, V6, P1533, DOI 10.5194/amt-6-1533-2013
   Zhang JJ, 2019, IEEE SENS J, V19, P5256, DOI 10.1109/JSEN.2019.2900257
   Zhang M, 2014, ADV CLIM CHANG RES, V5, P131, DOI 10.1016/j.accre.2014.11.002
   Zhang ZY, 2019, IEEE SENS J, V19, P6811, DOI 10.1109/JSEN.2019.2910810
   Zhao B, 2018, NEUROCOMPUTING, V322, P47, DOI 10.1016/j.neucom.2018.09.048
NR 81
TC 5
Z9 5
U1 4
U2 16
PU IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
PI PISCATAWAY
PA 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
SN 1939-1404
EI 2151-1535
J9 IEEE J-STARS
JI IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens.
PY 2021
VL 14
BP 11080
EP 11094
DI 10.1109/JSTARS.2021.3120987
PG 15
WC Engineering, Electrical & Electronic; Geography, Physical; Remote
   Sensing; Imaging Science & Photographic Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Physical Geography; Remote Sensing; Imaging Science &
   Photographic Technology
GA WU7CJ
UT WOS:000716698800015
OA gold
DA 2025-01-10
ER

PT J
AU Wang, CJ
   Wang, F
   Huang, GZ
   Wang, Y
   Zhang, XL
   Ye, YY
   Lin, XJ
   Zhang, ZW
AF Wang, Changjian
   Wang, Fei
   Huang, Gengzhi
   Wang, Yang
   Zhang, Xinlin
   Ye, Yuyao
   Lin, Xiaojie
   Zhang, Zhongwu
TI Examining the Dynamics and Determinants of Energy Consumption in China's
   Megacity Based on Industrial and Residential Perspectives
SO SUSTAINABILITY
LA English
DT Article
DE urban energy consumption accounting; industrial energy consumption;
   residential energy consumption; LMDI
ID DECOMPOSITION ANALYSIS; CARBON EMISSIONS; SUSTAINABLE DEVELOPMENT;
   DRIVING FORCES; CO2 EMISSIONS; POLICY RECOMMENDATIONS; LMDI
   DECOMPOSITION; GHG EMISSIONS; INDEX; INTENSITY
AB Cities are regarded as the main areas for conducting strategies for energy sustainability and climate adaptation, specifically in the world's top energy consumer-China. To uncover dynamic features and main drivers for the city-level energy consumption, a comprehensive and systematic city-level total energy consumption accounting approach was established and applied in China's megacity, which has the highest industrial electricity consumption. Compared with previous studies, this study systematically analyzes drivers for energy consumption based on industrial and residential perspectives. Additionally, this study analyzes not only the mechanisms by which population size, economic growth, and energy intensity affect energy consumption but also the effects of population and industry structural factors. According to the extended Logarithmic mean Divisia index (LMDI) method, the main conclusions drawn from this research are as follows: (1) The total energy consumption of Suzhou presented an overall increasing trend, with 2006-2012 as a rapid growth stage and 2013-2016 as a moderate growth stage. (2) The energy consumption structure was mainly dominated by coal, which was followed by outsourced electricity and natural gas. (3) Scale-related factors have dominated changes in energy consumption, and structural and technological factors have had profound effects on energy consumption in different development periods. (4) Population size and economic output were the main drivers for increments in industrial energy consumption, whereas energy intensity and economic structure performed the important curbing effects. The income effect of urban residents was the biggest driver behind the increase in residential energy consumption, whereas energy intensity was the main limiter. These findings provide a scientific basis for an in-depth understanding of the determinants of the evolution of urban energy consumption in China's megacity, including similar cities or urban areas in the developing world.
C1 [Wang, Changjian; Wang, Yang; Ye, Yuyao; Lin, Xiaojie] Guangdong Acad Sci, Guangzhou Inst Geog, Guangdong Open Lab Geospatial Informat Technol &, Key Lab Guangdong Utilizat Remote Sensing & Geog, Guangzhou 510070, Peoples R China.
   [Wang, Fei] Sun Yat Sen Univ, Xinhua Coll, Dept Resources & Urban Planning, Guangzhou 510520, Peoples R China.
   [Huang, Gengzhi] Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou 510275, Peoples R China.
   [Zhang, Xinlin] Jiangsu Normal Univ, Sch Geog Geomat & Planning, Xuzhou 221116, Jiangsu, Peoples R China.
   [Lin, Xiaojie] Guangdong Univ Technol, Sch Architecture & Urban Planning, Guangzhou 510090, Peoples R China.
   [Zhang, Zhongwu] Shanxi Normal Univ, Coll Geog Sci, Linfen 041000, Shanxi, Peoples R China.
C3 Guangdong Academy of Sciences; Guangzhou Institute of Geography,
   Guangdong Academy of Sciences; Sun Yat Sen University; Sun Yat Sen
   University; Jiangsu Normal University; Guangdong University of
   Technology; Shanxi Normal University
RP Wang, CJ (corresponding author), Guangdong Acad Sci, Guangzhou Inst Geog, Guangdong Open Lab Geospatial Informat Technol &, Key Lab Guangdong Utilizat Remote Sensing & Geog, Guangzhou 510070, Peoples R China.; Wang, F (corresponding author), Sun Yat Sen Univ, Xinhua Coll, Dept Resources & Urban Planning, Guangzhou 510520, Peoples R China.; Zhang, ZW (corresponding author), Shanxi Normal Univ, Coll Geog Sci, Linfen 041000, Shanxi, Peoples R China.
EM wwwangcj@126.com; wangfei09@mails.ucas.ac.cn; hgzhi3@mail.sysu.edu.cn;
   wyxkwy@163.com; smilezhang89@163.com; yeyuyao@gdas.ac.cn;
   linxj01@126.com; zhangzhongwu69@163.com
RI Wang, Changjian/S-7317-2016; Lin, Xiaojie/G-4885-2016; zhang,
   zhongwu/G-1875-2012
FU GDAS Special Project of Science and Technology Development
   [2020GDASYL-20200301003, 2020GDASYL-20200102002]; National Natural
   Science Foundation of China [41501144]; GDAS' Project of Science and
   Technology Development [2016GDASRC0101, 2017GDASCX-0101,
   2018GDASCX-0101, 2018GDASCX-0403, 2019GDASYL-0302001]
FX This work was supported by the GDAS Special Project of Science and
   Technology Development (2020GDASYL-20200301003, 2020GDASYL-20200102002),
   the National Natural Science Foundation of China (41501144), the GDAS'
   Project of Science and Technology Development (2016GDASRC0101,
   2017GDASCX-0101, 2018GDASCX-0101, 2018GDASCX-0403, 2019GDASYL-0302001).
CR Achao C, 2009, ENERG POLICY, V37, P5208, DOI 10.1016/j.enpol.2009.07.043
   Ang BW, 2007, ENERG POLICY, V35, P1426, DOI 10.1016/j.enpol.2006.04.020
   Ang BW, 2015, ENERG POLICY, V86, P233, DOI 10.1016/j.enpol.2015.07.007
   ANG BW, 1994, ENERG ECON, V16, P83, DOI 10.1016/0140-9883(94)90001-9
   Ang BW, 2005, ENERG POLICY, V33, P867, DOI 10.1016/j.enpol.2003.10.010
   Ang BW, 2004, ENERG POLICY, V32, P1131, DOI 10.1016/S0301-4215(03)00076-4
   Ang BW, 2000, ENERGY, V25, P1149, DOI 10.1016/S0360-5442(00)00039-6
   [Anonymous], 2019, BP Statistical Review of World Energy Statistical Review of World
   Balezentis A, 2011, ENERG POLICY, V39, P7322, DOI 10.1016/j.enpol.2011.08.055
   Bi J, 2011, ENERG POLICY, V39, P4785, DOI 10.1016/j.enpol.2011.06.045
   Cansino JM, 2018, ENERG ECON, V69, P350, DOI 10.1016/j.eneco.2017.12.001
   Chen B, 2018, RENEW SUST ENERG REV, V82, P4100, DOI 10.1016/j.rser.2017.10.063
   Choi KH, 2012, ENERG ECON, V34, P171, DOI 10.1016/j.eneco.2011.04.011
   Chong CH, 2017, ENERGY, V133, P525, DOI 10.1016/j.energy.2017.05.045
   Chontanawat J, 2014, ENERGY, V77, P171, DOI 10.1016/j.energy.2014.05.111
   Chu S, 2012, NATURE, V488, P294, DOI 10.1038/nature11475
   Chung W, 2011, APPL ENERG, V88, P5180, DOI 10.1016/j.apenergy.2011.07.030
   González PF, 2015, APPL ENERG, V137, P364, DOI 10.1016/j.apenergy.2014.10.020
   Fu BJ, 2007, ENVIRON SCI TECHNOL, V41, P7597, DOI 10.1021/es072643l
   Gu S, 2019, J CLEAN PROD, V240, DOI 10.1016/j.jclepro.2019.118034
   Guan DB, 2012, NAT CLIM CHANGE, V2, P672, DOI [10.1038/NCLIMATE1560, 10.1038/nclimate1560]
   Hasanbeigi A, 2012, ENERG POLICY, V46, P234, DOI 10.1016/j.enpol.2012.03.056
   Jin T, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12208483
   Jung S, 2012, ENERGY, V46, P231, DOI 10.1016/j.energy.2012.08.028
   Kang JD, 2014, ENERGY, V68, P562, DOI 10.1016/j.energy.2014.01.023
   Kayaçetin NC, 2020, RENEW SUST ENERG REV, V117, DOI 10.1016/j.rser.2019.109470
   Keeler BL, 2019, NAT SUSTAIN, V2, P29, DOI 10.1038/s41893-018-0202-1
   Kennedy C, 2009, ENVIRON SCI TECHNOL, V43, P7297, DOI 10.1021/es900213p
   Lee J, 2019, RENEW SUST ENERG REV, V115, DOI 10.1016/j.rser.2019.109370
   Li JS, 2015, RENEW SUST ENERG REV, V41, P1167, DOI 10.1016/j.rser.2014.08.073
   Li JS, 2013, RENEW SUST ENERG REV, V22, P23, DOI 10.1016/j.rser.2012.11.072
   Liang S, 2010, ECOL ECON, V69, P1805, DOI 10.1016/j.ecolecon.2010.04.019
   Lin JY, 2013, ENERG POLICY, V58, P220, DOI 10.1016/j.enpol.2013.03.007
   Liu JG, 2005, NATURE, V435, P1179, DOI 10.1038/4351179a
   Liu Z, 2015, ECOL MODEL, V318, P118, DOI 10.1016/j.ecolmodel.2015.02.001
   Liu Z, 2012, ENERGY, V37, P245, DOI 10.1016/j.energy.2011.11.040
   Ma MD, 2019, J CLEAN PROD, V222, P193, DOI 10.1016/j.jclepro.2019.01.314
   Nerini FF, 2018, NAT ENERGY, V3, P10, DOI 10.1038/s41560-017-0036-5
   Peters GP, 2017, NAT CLIM CHANGE, V7, P118, DOI [10.1038/NCLIMATE3202, 10.1038/nclimate3202]
   Ru MY, 2015, ENVIRON SCI TECHNOL, V49, P13708, DOI 10.1021/acs.est.5b03374
   Shan YL, 2020, SCI DATA, V7, DOI 10.1038/s41597-020-0393-y
   Shan YL, 2019, SCI DATA, V6, DOI 10.1038/sdata.2019.27
   Shan YL, 2018, SCI ADV, V4, DOI 10.1126/sciadv.aaq0390
   Shao L, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/11/114028
   Shao S, 2016, RENEW SUST ENERG REV, V55, P516, DOI 10.1016/j.rser.2015.10.081
   SIEGEL IH, 1945, J AM STAT ASSOC, V40, P520, DOI 10.2307/2280220
   Su YX, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab858b
   Su YX, 2014, RENEW SUST ENERG REV, V35, P231, DOI 10.1016/j.rser.2014.04.015
   Taka GN, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12104175
   Tan XC, 2016, APPL ENERG, V162, P1345, DOI 10.1016/j.apenergy.2015.06.071
   Wang CJ, 2019, NATURE, V566, P455, DOI 10.1038/d41586-019-00670-4
   Wang CJ, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0210430
   Wang CJ, 2017, SCIENCE, V357, P764, DOI 10.1126/science.aao2785
   Wang CJ, 2015, SUSTAINABILITY-BASEL, V7, P7548, DOI 10.3390/su7067548
   Wang CJ, 2014, SUSTAINABILITY-BASEL, V6, P8164, DOI 10.3390/su6118164
   Wang CJ, 2014, ENVIRON SCI POLICY, V39, P49, DOI 10.1016/j.envsci.2014.02.007
   Wang CJ, 2013, ENVIRON SCI TECHNOL, V47, P11920, DOI 10.1021/es403642u
   Wang F, 2020, ENVIRON DEV SUSTAIN, V22, P7743, DOI 10.1007/s10668-019-00545-8
   Wang F, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9020274
   Wang H, 2017, ENERG POLICY, V107, P585, DOI 10.1016/j.enpol.2017.05.034
   Wang SJ, 2019, APPL ENERG, V235, P95, DOI 10.1016/j.apenergy.2018.10.083
   Wang SJ, 2017, APPL ENERG, V185, P189, DOI 10.1016/j.apenergy.2016.10.052
   Wang WW, 2014, ENERGY, V67, P617, DOI 10.1016/j.energy.2013.12.064
   Wang ZH, 2016, ECOL INDIC, V61, P634, DOI 10.1016/j.ecolind.2015.10.015
   Wei YX, 2018, RENEW SUST ENERG REV, V82, P1027, DOI 10.1016/j.rser.2017.09.108
   Xu Q, 2019, J CLEAN PROD, V214, P615, DOI 10.1016/j.jclepro.2018.12.280
   Xu XY, 2014, APPL ENERG, V113, P342, DOI 10.1016/j.apenergy.2013.07.052
   Yalew SG, 2020, NAT ENERGY, V5, P794, DOI 10.1038/s41560-020-0664-z
   Zeng N, 2008, SCIENCE, V319, P730, DOI 10.1126/science.1153368
   Zhang XX, 2012, RENEW SUST ENERG REV, V16, P599, DOI 10.1016/j.rser.2011.08.026
   Zhang XL, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9030459
   Zhao M, 2010, ENERGY, V35, P2505, DOI 10.1016/j.energy.2010.02.049
NR 72
TC 3
Z9 3
U1 3
U2 48
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD JAN
PY 2021
VL 13
IS 2
AR 764
DI 10.3390/su13020764
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 PY0PD
UT WOS:000611751300001
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Zampieri, M
   Weissteiner, CJ
   Grizzetti, B
   Toreti, A
   van den Berg, M
   Dentener, F
AF Zampieri, Matteo
   Weissteiner, Christof J.
   Grizzetti, Bruna
   Toreti, Andrea
   van den Berg, Maurits
   Dentener, Frank
TI Estimating resilience of crop production systems: From theory to
   practice
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Agricultural production stability; Crop yield variability; Resilience
   indicator; Climate change; Extreme events; Climate adaptation; Crop
   diversity
ID YIELD STABILITY; RESPONSE DIVERSITY; MAIZE PRODUCTION; CLIMATE-CHANGE;
   IMPACT; WHEAT; TEMPERATURE; INSIGHTS; INCREASE; DROUGHT
AB Agricultural production systems are sensitive to weather and climate anomalies and extremes as well as to other environmental and socio-economic adverse events. An adequate evaluation of the resilience of such systems helps to assess food security and the capacity of society to cope with the effects of global warming and the associated increase of climate extremes.
   Here, we propose and apply a simple indicator of resilience of annual crop production that can be estimated from crop production time series. First, we address the problem of quantifying resilience in a simplified theoretical framework, focusing on annual crops. This results in the proposal of an indicator, measured by the reciprocal of the squared coefficient of variance, which is proportional to the return period of the largest shocks that the crop production system can absorb, and which is consistent with the original ecological definition of resilience.
   Subsequently, we show the sensitivity of the crop resilience indicator to the level of management of the crop production system, to the frequency of extreme events as well as to simplified socio-economic impacts of the production losses.
   Finally, we demonstrate the practical applicability of the indicator using historical production data at national and sub-national levels for France. The results show that the value of the resilience indicator steeply increases with crop diversity until six crops are considered, and then levels off. The effect of diversity on production resilience is highest when crops are more diverse (i.e. as reflected in less well correlated production time series). In the case of France, the indicator reaches about 60% of the value that would be expected if all crop production time-series were uncorrelated.
C1 [Zampieri, Matteo; Weissteiner, Christof J.; Grizzetti, Bruna; Toreti, Andrea; van den Berg, Maurits; Dentener, Frank] European Commiss, Joint Res Ctr JRC, Ispra, Italy.
C3 European Commission Joint Research Centre; EC JRC ISPRA Site
RP Zampieri, M (corresponding author), European Commiss, Joint Res Ctr JRC, Ispra, Italy.
EM matteo.zampieri@ec.europa.eu; christof.weissteiner@ec.europa.eu;
   bruna.grizzetti@ec.europa.eu; andrea.toreti@ec.europa.eu;
   maurits.vandenberg@ec.europa.eu; frank.dentener@ec.europa.eu
RI Dentener, Frank/ABW-0482-2022; Weissteiner, Christof/G-7470-2012
OI Grizzetti, Bruna/0000-0001-5570-8581
FU MEDGOLD EU-H2020 project [776467]
FX This work has been supported by the MEDGOLD EU-H2020 project (grant
   agreement ID: 776467). We are indebted with Luigi Nisini Scacchiafichi
   for handling and providing us the AGRESTE data thatwere used in this
   paper.
CR Angeler DG, 2016, J APPL ECOL, V53, P617, DOI 10.1111/1365-2664.12649
   [Anonymous], 1996, ENG RESILIENCE VERSU
   Bahri H, 2019, SCI TOTAL ENVIRON, V692, P1223, DOI 10.1016/j.scitotenv.2019.07.307
   Barnabas B, 2008, PLANT CELL ENVIRON, V31, P11, DOI 10.1111/j.1365-3040.2007.01727.x
   Barranco D, 2005, HORTSCIENCE, V40, P558, DOI 10.21273/HORTSCI.40.3.558
   Barros VR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1133
   Ben-Ari T, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-04087-x
   Berbés-Blázquez M, 2017, CLIMATIC CHANGE, V141, P227, DOI 10.1007/s10584-017-1897-0
   Brand FS, 2007, ECOL SOC, V12
   Carr J.A., 2016, RESERVES TRADE JOINT
   Ceglar A, 2016, AGR FOREST METEOROL, V216, P58, DOI 10.1016/j.agrformet.2015.10.004
   Challinor AJ, 2014, NAT CLIM CHANGE, V4, P287, DOI [10.1038/nclimate2153, 10.1038/NCLIMATE2153]
   CLEVELAND WS, 1988, J AM STAT ASSOC, V83, P596, DOI 10.2307/2289282
   Descamps C, 2018, ECOL EVOL, V8, P3443, DOI 10.1002/ece3.3914
   Deutsch CA, 2018, SCIENCE, V361, P916, DOI 10.1126/science.aat3466
   Douxchamps Sabine, 2017, World Development Perspectives, V5, P10, DOI 10.1016/j.wdp.2017.02.001
   Downes BJ, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/1/014041
   Eccel E, 2009, INT J BIOMETEOROL, V53, P273, DOI 10.1007/s00484-009-0213-8
   Esper J, 2017, CLIM RES, V72, P39, DOI 10.3354/cr01449
   Folke C, 2006, GLOBAL ENVIRON CHANG, V16, P253, DOI 10.1016/j.gloenvcha.2006.04.002
   Gil JDB, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.461
   Gourdji SM, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/2/024041
   Holling C.S., 1973, Annual Rev Ecol Syst, V4, P1, DOI 10.1146/annurev.es.04.110173.000245
   Iizumi T, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/3/034003
   Kahiluoto H, 2019, P NATL ACAD SCI USA, V116, P10627, DOI 10.1073/pnas.1903594116
   Kahiluoto H, 2019, P NATL ACAD SCI USA, V116, P123, DOI 10.1073/pnas.1804387115
   Khumairoh U, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-32915-z
   Lamichhane JR, 2015, AGRON SUSTAIN DEV, V35, P443, DOI 10.1007/s13593-014-0275-9
   Lesk C, 2016, NATURE, V529, P84, DOI 10.1038/nature16467
   Lobell DB, 2014, SCIENCE, V344, P516, DOI 10.1126/science.1251423
   Lobell DB, 2011, SCIENCE, V333, P616, DOI [10.1126/science.1206376, 10.1126/science.1204531]
   Macholdt J, 2019, FIELD CROP RES, V238, P82, DOI 10.1016/j.fcr.2019.04.014
   Macholdt J, 2019, EUR J AGRON, V102, P14, DOI 10.1016/j.eja.2018.10.007
   Macholdt J, 2017, AGRONOMY-BASEL, V7, DOI 10.3390/agronomy7030045
   Morris EK, 2014, ECOL EVOL, V4, P3514, DOI 10.1002/ece3.1155
   Olesen JE, 2011, EUR J AGRON, V34, P96, DOI 10.1016/j.eja.2010.11.003
   Peltonen-Sainio P, 2009, FIELD CROP RES, V110, P85, DOI 10.1016/j.fcr.2008.07.007
   Piepho HP, 2019, P NATL ACAD SCI USA, V116, P10625, DOI 10.1073/pnas.1901946116
   Puma MJ, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/2/024007
   Quinlan AE, 2016, J APPL ECOL, V53, P677, DOI 10.1111/1365-2664.12550
   Rao CS, 2019, ECOL INDIC, V105, P621, DOI 10.1016/j.ecolind.2018.06.038
   Renard D, 2019, NATURE, V571, P257, DOI 10.1038/s41586-019-1316-y
   Russo L., 2016, RIMA 2 RESILIENCE 1, DOI [10.1038/s41559-018-0793-y., DOI 10.1038/S41559-018-0793-Y]
   Savary S, 2019, NAT ECOL EVOL, V3, P430, DOI 10.1038/s41559-018-0793-y
   Schlenker W, 2009, P NATL ACAD SCI USA, V106, P15594, DOI 10.1073/pnas.0906865106
   Seekell D, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa5730
   Shaw RE, 2013, CROP PASTURE SCI, V64, P549, DOI 10.1071/CP13080
   Snowdon RJ, 2019, P NATL ACAD SCI USA, V116, P10623, DOI 10.1073/pnas.1901882116
   Sweeney S, 2013, APPL GEOGR, V39, P78, DOI 10.1016/j.apgeog.2012.12.005
   Toreti A, 2019, EARTHS FUTURE, V7, P652, DOI 10.1029/2019EF001170
   Twomlow S, 2008, PHYS CHEM EARTH, V33, P780, DOI 10.1016/j.pce.2008.06.048
   Yang LN, 2019, NAT SUSTAIN, V2, P46, DOI 10.1038/s41893-018-0201-2
   Zampieri M, 2019, EARTHS FUTURE, V7, P113, DOI 10.1029/2018EF000995
   Zampieri M, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aaa00d
   Zampieri M, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa723b
   Zampieri M, 2020, REG ENVIRON CHANGE, V20, DOI 10.1007/s10113-020-01622-9
   Zampieri M, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11222708
   Zampieri M, 2019, LAND DEGRAD DEV, V30, P2033, DOI 10.1002/ldr.3402
   Zampieri M, 2018, REMOTE SENS-BASEL, V10, DOI 10.3390/rs10020244
   Zampieri M, 2015, SCI TOTAL ENVIRON, V503, P222, DOI 10.1016/j.scitotenv.2014.06.036
   Zampieri M, 2009, J CLIMATE, V22, P4747, DOI 10.1175/2009JCLI2568.1
   Zhang JT, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0137409
   Zimmerer KS, 2017, NAT PLANTS, V3, DOI 10.1038/nplants.2017.47
NR 63
TC 40
Z9 42
U1 11
U2 99
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 15
PY 2020
VL 735
AR 139378
DI 10.1016/j.scitotenv.2020.139378
PG 10
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA MB4HV
UT WOS:000542565200004
PM 32480148
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Hawchar, L
   Naughton, O
   Nolan, P
   Stewart, MG
   Ryan, PC
AF Hawchar, Lara
   Naughton, Owen
   Nolan, Paul
   Stewart, Mark G.
   Ryan, Paraic C.
TI A GIS-based framework for high-level climate change risk assessment of
   critical infrastructure
SO CLIMATE RISK MANAGEMENT
LA English
DT Article
DE Climate change; Critical infrastructure; Geographic information system;
   GIS-based analysis; Risk assessment
ID VULNERABILITY ANALYSIS; NETWORK
AB The IPCC states that climate change unequivocally impacts on various aspects of the natural and built environment, including our vital critical infrastructure systems (transport, energy, water/wastewater and communications). It is thus essential for countries to gain an understanding of critical infrastructure vulnerability to current and future climate-related threats, in order to develop effective climate adaptation strategies. The first requisite step towards implementing these strategies, before any detailed analysis can commence, is high-level vulnerability or risk assessments. The work in this paper is concerned with such high-level assessments, however the framework presented is GIS-based, facilitating modelling of geographical variability in both climate and asset vulnerability within a country. This permits the identification of potential climate change risk hotspots across a range of critical infrastructure sectors. The framework involves a number of distinct steps. Sectoral information matrices are developed to highlight the key relationships between the infrastructure and climate threats. This information is complemented with sectoral maps showing, on an asset-level, the potential geospatial impacts of climate change, facilitating initial quantification of the vulnerable portions of the infrastructure systems. Finally, the approach allows for development of multi-sectoral semi-quantitative risk ranking maps that account for the geographical proximities of various assets from different critical infrastructure sectors which are vulnerable to a specific climate threat. The framework is presented in the paper and applied as a case study in the context of Irish critical infrastructure. The case-study identified for instance, potentially substantial increases in fluvial flooding risk for Irish critical infrastructure, while the multi-sectoral risk ranking maps highlighted a number of Ireland's urban and rural areas as climate change risk hotspots. These high-level insights are likely to be useful in informing more detailed assessment, and initiating important conversations relating to a region's critical infrastructure cross-sectoral risk.
C1 [Hawchar, Lara; Ryan, Paraic C.] Univ Coll Cork, Sch Engn, Discipline Civil Struct & Environm Engn, Cork, Ireland.
   [Naughton, Owen] Inst Technol Carlow, Dept Built Environm, Carlow, Ireland.
   [Nolan, Paul] Natl Univ Ireland Galway, Irish Ctr High End Comp ICHEC, Galway, Ireland.
   [Nolan, Paul] Met Eireann, Res & Applicat Div, Dublin, Ireland.
   [Stewart, Mark G.] Univ Newcastle, Ctr Infrastruct Performance & Reliabil, Callaghan, NSW 2308, Australia.
   [Ryan, Paraic C.] Univ Coll Cork, MaREI Ctr, Environm Res Inst, Cork, Ireland.
C3 University College Cork; South East Technological University (SETU);
   Ollscoil na Gaillimhe-University of Galway; Met Eireann - Ireland;
   University of Newcastle; University College Cork
RP Ryan, PC (corresponding author), Univ Coll Cork UCC, Discipline Civil Struct & Environm Engn, Coll Rd, Cork, Ireland.
EM paraic.ryan@ucc.ie
RI Stewart, Mark/G-7415-2013
OI Stewart, Mark/0000-0001-6887-6533; Ryan, Paraic/0000-0003-3767-8096;
   Naughton, Owen/0000-0001-9616-0022; Nolan, Paul/0000-0003-0629-9771
FU Environmental Protection Agency (EPA), Ireland under the EPA Research
   Programme
FX This work was supported by the Environmental Protection Agency (EPA),
   Ireland under the EPA Research Programme 2014-2020.
CR Abebe Y, 2018, J CLEAN PROD, V174, P1629, DOI 10.1016/j.jclepro.2017.11.066
   Adger WN, 2018, PHILOS T R SOC A, V376, DOI 10.1098/rsta.2018.0106
   AFW CVC, 2017, NAT INFR BUILD CLIM
   [Anonymous], 2005, 201 FED ENV AG GERM
   [Anonymous], UCDPPRIO ARMED CONFL
   [Anonymous], 2014, 3 NATL COMMUNICATION
   [Anonymous], 2014, INDICATORS ASSESS EX
   Bababeik M, 2018, TRANSPORT RES E-LOG, V119, P110, DOI 10.1016/j.tre.2018.09.009
   Bababeik M, 2017, TRANSP RES PROC, V22, P275, DOI 10.1016/j.trpro.2017.03.034
   Bambrick E., 2017, APPL COASTAL RAILWAY
   Barros V, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, pIX
   ComReg, 2016, UN SERV OBL PROV ACC
   Dawson R.J., 2017, UK CLIMATE CHANGE RI
   Dawson RJ, 2018, PHILOS T R SOC A, V376, DOI 10.1098/rsta.2017.0298
   DCCAE, 2018, CLIM CHANG AD PLAN E
   Deng L, 2010, PRACT PERIOD STRUCT, V15, P125, DOI 10.1061/(ASCE)SC.1943-5576.0000041
   Dikanski H, 2018, STRUCT SAF, V71, P1, DOI 10.1016/j.strusafe.2017.10.008
   Dourte DR, 2015, CLIM RISK MANAG, V7, P11, DOI 10.1016/j.crm.2015.02.001
   DTTAS, 2017, AD PLANN DEV RES CLI
   DTTAS, 2013, NAT PORTS POL 2013
   DTTAS, 2019, STAT CLIM CHANG AD P
   EEA, 2017, GLOSS URB GREEN INFR
   Environmental Protection Agency (EPA), 2016, URB WAST WAT TREATM
   EPA, 2017, 430R17001 UE EPA
   EU, 2013, EU STSTRAT AD CLIM C
   Fekete A, 2011, INT J DISAST RISK SC, V2, P15, DOI 10.1007/s13753-011-0002-y
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fisk G.W., 2017, CLIMATE RISKS ADAPTA
   Fu G, 2016, INFRASTRUCT ASSET MA, V3, P42, DOI 10.1680/jinam.15.00002
   Füssel HM, 2007, GLOBAL ENVIRON CHANG, V17, P155, DOI 10.1016/j.gloenvcha.2006.05.002
   Giannopoulos G., 2012, JRC TECHNICAL NOTES
   Gibbs MT, 2015, CLIM RISK MANAG, V8, P1, DOI 10.1016/j.crm.2015.05.001
   Guerreiro SB, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aaaad3
   Hammerli B., 2009, PROTECTING CRITICAL
   Hernandez-Fajardo I, 2013, RELIAB ENG SYST SAFE, V111, P260, DOI 10.1016/j.ress.2012.10.012
   Hughes J., 2016, REV METHODS DETERMIN
   Independent, 2017, IRISH INDEPENDENT NE
   Irish Water (IW), 2015, WAT SERV STRAT PLAN
   Islam S.N., 2017, HDB DROUGHT WATER SC, P31
   Kember O., 2012, COMING READY NOT MAN
   Kingsborough A, 2017, CLIM RISK MANAG, V16, P73, DOI 10.1016/j.crm.2017.01.001
   Koks EE, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-10442-3
   Koutroulis AG, 2018, SCI TOTAL ENVIRON, V613, P271, DOI 10.1016/j.scitotenv.2017.09.074
   Mach KJ, 2017, GLOBAL ENVIRON CHANG, V44, P1, DOI 10.1016/j.gloenvcha.2017.02.005
   Martinovic K, 2018, GEOMORPHOLOGY, V306, P40, DOI 10.1016/j.geomorph.2018.01.006
   Mazumder RK, 2018, J INFRASTRUCT SYST, V24, DOI 10.1061/(ASCE)IS.1943-555X.0000426
   Mckeon C., 2016, Final Report
   Meyer M.D., 2012, Background Paper
   Munich RE, 2017, YEAR FLOODS NATURAL
   Nolan P, 2015, TECH REP
   NTA, 2018, NAT HEAV RAIL CENS R
   Open Eir, 2017, STORM OPH NETW UPD
   OPW, 2016, SHANN CATCHM BAS FLO
   OPW, 2015, DRAFT CONS CLIM CHAN
   OPW, 2010, TECHNICAL REPORT
   Ouzeau G., 2016, Climate Services, V4, P1, DOI 10.1016/j.cliser.2016.09.002
   Pregnolato M, 2017, J INFRASTRUCT SYST, V23, DOI 10.1061/(ASCE)IS.1943-555X.0000372
   Rinaldi SA, 2001, IEEE CONTR SYST MAG, V21, P11, DOI 10.1109/37.969131
   Ryan PC, 2017, CLIMATIC CHANGE, V143, P519, DOI 10.1007/s10584-017-2000-6
   Ryan PC, 2016, CONSTR BUILD MATER, V120, P504, DOI 10.1016/j.conbuildmat.2016.04.089
   Ryan PC, 2016, INT J ELEC POWER, V78, P513, DOI 10.1016/j.ijepes.2015.11.061
   Ryan PC, 2014, J BRIDGE ENG, V19, DOI 10.1061/(ASCE)BE.1943-5592.0000541
   Salman AM, 2018, NAT HAZARDS REV, V19, DOI 10.1061/(ASCE)NH.1527-6996.0000294
   Seppänen H, 2018, INT J CRIT INFR PROT, V22, P25, DOI 10.1016/j.ijcip.2018.05.002
   Stevens L., 2008, Assessment of Impacts of Climate Change on Australia's Physical Infrastructure
   Stewart MG, 2015, ASCE-ASME J RISK U A, V1, DOI 10.1061/AJRUA6.0000809
   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]
   Suh J, 2019, J INFRASTRUCT SYST, V25, DOI 10.1061/(ASCE)IS.1943-555X.0000506
   Sukhija S., 2018, IRISH SUN 1129
   Theoharidou M, 2009, IFIP ADV INF COMM TE, V311, P35
   Tsavdaroglou M, 2018, INT J CRIT INFR PROT, V21, P57, DOI 10.1016/j.ijcip.2018.04.002
   Turner BL, 2003, P NATL ACAD SCI USA, V100, P8074, DOI 10.1073/pnas.1231335100
   US Department of Energy, 2016, Climate Change and the Electricity Sector: Guide for Climate Change Resilience Planning
   Wang T, 2018, SAFETY AND RELIABILITY - SAFE SOCIETIES IN A CHANGING WORLD, P2771
   Wicht M., 2016, J CLEANER PROD, V174, P1629
   Yang GT, 2016, INT J SOLIDS STRUCT, V97-98, P637, DOI 10.1016/j.ijsolstr.2016.04.037
NR 76
TC 36
Z9 37
U1 8
U2 85
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2212-0963
J9 CLIM RISK MANAG
JI CLIM. RISK MANAG.
PY 2020
VL 29
AR 100235
DI 10.1016/j.crm.2020.100235
PG 20
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 ND4PW
UT WOS:000561885100010
OA gold
DA 2025-01-10
ER

PT J
AU Park, E
   Jo, HW
   Biging, GS
   Chun, JA
   Jeon, SW
   Son, Y
   Kraxner, F
   Lee, WK
AF Park, Eunbeen
   Jo, Hyun-Woo
   Biging, Gregory Scott
   Chun, Jong Ahn
   Jeon, Seong Woo
   Son, Yowhan
   Kraxner, Florian
   Lee, Woo-Kyun
TI Advancement of a diagnostic prediction model for spatiotemporal
   calibration of earth observation data: a case study on projecting forest
   net primary production in the mid-latitude region
SO GISCIENCE & REMOTE SENSING
LA English
DT Article
DE Diagnostic prediction model; Earth observation data; Spatiotemporal
   modeling; Net primary production; Mid latitude region
ID TOPOGRAPHIC WETNESS INDEX; DROUGHT; ECOLOGY; CLIMATE
AB Developing a precise and interpretable spatiotemporal model is need for establishing evidence-based adaptation strategies on climate change-driven disasters. This study introduced a diagnostic prediction concept as a generalized modeling framework for enhancing modeling precision and interpretability and demonstrate a case study of estimating forest net primary production (NPP) in a mid-latitude region (MLR) by developing a diagnostic NPP diagnostic prediction model (DNPM). The diagnostic prediction concept starts with modeling meteorology and static environmental data, referred as a prognostic prediction part. Then, its outcome is refined with spatiotemporal residual calibration in the diagnostic prediction part, of which result undergo spatial, temporal, and spatiotemporally explicit validation methods. For the case of DNPM, a prognostic NPP prediction model (PNPM) was set, using a multilinear regression on SPEI 3, temperature, and static environmental features extracted from topography and soil by a random forest. Subsequently, during the diagnostic process of DNPM, we calibrated the primary outcome based on the temporal pattern captured at the time-series residual of PNPM. The results highlighted the superiority of the DNPM over the PNPM. Spatiotemporal validation showed that the DNPM achieved higher accuracy, with Pearson correlation coefficients ($r$r) ranging from 0.975 to 0.992 and root mean squared error (RMSE) between 38.99 and 70.23 gC/m2/year across all climate zones. Similarly, temporal validation indicated that DNPM outperformed the PNPM, with $r$r values of 0.233 to 0.494 and RMSE of 46.01 to 70.75 gC/m2/year, compared to the PNPM's $r$r values of 0.192 to 0.406 and RMSE of 55.23 to 89.31 gC/m2/year. This study showed enhanced diagnostic prediction concept can be applied to diverse environmental modeling approaches, offering valuable insights for climate adaptation and forest policy formulation. By accurately predicting various environmental targets, including drought and forest NPP, this approach aids in making informed policy decisions across different scales.
C1 [Park, Eunbeen; Jo, Hyun-Woo; Kraxner, Florian] Int Inst Appl Syst Anal IIASA, Biodivers & Nat Resource BNR Program, Agr Forestry & Ecosyst Serv AFE Grp, Laxenburg, Austria.
   [Park, Eunbeen; Jo, Hyun-Woo] Korea Univ, OJEong Resilience Inst OJERI, Seoul, South Korea.
   [Biging, Gregory Scott] Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA USA.
   [Chun, Jong Ahn] APEC Climate Ctr, Climate Analyt Dept, Busan, South Korea.
   [Jeon, Seong Woo; Son, Yowhan; Lee, Woo-Kyun] Korea Univ, Dept Environm Sci & Ecol Engn, Seoul, South Korea.
C3 International Institute for Applied Systems Analysis (IIASA); Korea
   University; University of California System; University of California
   Berkeley; Korea University
RP Lee, WK (corresponding author), Korea Univ, Dept Environm Sci & Ecol Engn, Seoul, South Korea.
EM leewk@korea.ac.kr
RI Jeon, Seongwoo/AAU-4618-2020; Lee, Woo-Kyun/AAP-9837-2020; Jo,
   Hyun-Woo/GZK-7613-2022; Jeon, Seongwoo/M-2550-2016
OI son, yowhan/0000-0001-5621-9894; Jo, Hyun-Woo/0000-0001-6127-883X; Chun,
   Jong Ahn/0000-0001-8047-1811; Park, Eunbeen/0000-0002-0442-7621; Jeon,
   Seongwoo/0000-0001-5928-8510
FU National Research Foundation of Korea [2021K2A9A1A02101519,
   RS-2023-00270057]
FX This work was supported under the framework of international cooperation
   program managed by the National Research Foundation of Korea
   [2021K2A9A1A02101519 and RS-2023-00270057].
CR Beven K. J., 1979, HYDROL SCI B, V24, P43, DOI DOI 10.1080/02626667909491834
   Breiman L, 2001, MACH LEARN, V45, P5, DOI 10.1023/A:1010933404324
   Center for Ocean Plastic Studies, 2024, Best Practices for Microplastic Research-Webinar, DOI [10.5281/zenodo.11363671, DOI 10.5281/ZENODO.11363671]
   Chen T, 2013, HYDROL EARTH SYST SC, V17, P3885, DOI 10.5194/hess-17-3885-2013
   CISA, 2021, Drought and Infrastructure: A Planning Guide
   Easterling DavidR., 2021, FAO
   FAO, 2020, Global Forest Resources Assessment 2020: Main Report
   Fick SE, 2017, INT J CLIMATOL, V37, P4302, DOI 10.1002/joc.5086
   FIELD CB, 1995, REMOTE SENS ENVIRON, V51, P74, DOI 10.1016/0034-4257(94)00066-V
   Fischer G., 2008, Global Agro-ecological Zones Assessment for Agriculture (GAEZ 2008), P10
   Gillman LN, 2015, GLOBAL ECOL BIOGEOGR, V24, P107, DOI 10.1111/geb.12245
   Hassan Q. K., 2018, Environmental Modelling, DOI [https://doi.org/10.11575/PRISM/5245, DOI 10.11575/PRISM/5245]
   Hengl T, 2007, COMPUT GEOSCI-UK, V33, P1301, DOI 10.1016/j.cageo.2007.05.001
   Jarvis A., 2008, HOLE FILLED SRTM GLO
   Kim M, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab71a2
   Kindermann GE, 2008, SILVA FENN, V42, P387, DOI 10.14214/sf.244
   Kindermann Georg E, 2013, Carbon Balance Manag, V8, P2, DOI 10.1186/1750-0680-8-2
   Kopecky M, 2010, APPL VEG SCI, V13, P450, DOI 10.1111/j.1654-109X.2010.01083.x
   Li HT, 2022, FRONT ENV SCI-SWITZ, V10, DOI 10.3389/fenvs.2022.988362
   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]
   Mickler RA, 2002, ENVIRON POLLUT, V116, pS7, DOI 10.1016/S0269-7491(01)00241-X
   Orusa T, 2023, REMOTE SENS-BASEL, V15, DOI 10.3390/rs15010178
   Orusa T, 2021, CLIMATE, V9, DOI 10.3390/cli9030047
   Pan Y, 1996, GLOBAL CHANGE BIOL, V2, P5, DOI 10.1111/j.1365-2486.1996.tb00045.x
   Park E, 2022, GISCI REMOTE SENS, V59, P36, DOI 10.1080/15481603.2021.2012370
   Park JH, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13081441
   Piao D, 2018, FORESTS, V9, DOI 10.3390/f9030155
   Running S.W., 1993, Generalization of a Forest Ecosystem Process Model for Other Biomes, BIOME-BGC, and an Application for Global-Scale Models, Scaling Physiological Processes, DOI [10.1016/b978-0-12-233440-5.50014-2, DOI 10.1016/B978-0-12-233440-5.50014-2]
   Shahin M.A., 2014, COMPUTATIONAL INTELL, DOI [DOI 10.1007/978-94-017-8642-3_2, 10.1007/978-94-017-8642-3_2, DOI 10.1007/978-94-017-8642-32]
   Shamsnia S.A., 2011, INT C ENV IND INNOVA, V12, P282
   Shvidenko A. S., 2008, Federal Agency of Forest Management
   음성원, 2005, [Korean Journal of Agricultural and Forest Meteorology, 한국농림기상학회지], V7, P66
   Song C, 2019, FORESTS, V10, DOI 10.3390/f10060523
   Sorensen R, 2006, HYDROL EARTH SYST SC, V10, P101, DOI 10.5194/hess-10-101-2006
   Tang GP, 2010, ECOSPHERE, V1, DOI 10.1890/ES10-00087.1
   Thornthwaite CW, 1948, GEOGR REV, V38, P55, DOI 10.2307/210739
   Trabucco Antonio, 2019, Figshare
   UN/ISDR, 2008, UN/ISDR Briefing Note, V1
   United Nations Department of Economic and Social Affairs & United Nations Forum on Forests Secretariat, 2021, The Global Forest Goals Report 2021
   Vicente-Serrano SM, 2010, J CLIMATE, V23, P1696, DOI 10.1175/2009JCLI2909.1
   Xue P, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14010015
   Yang J, 2017, FORESTS, V8, DOI 10.3390/f8100361
   Yu B, 2019, J SPAT SCI, V64, P173, DOI 10.1080/14498596.2017.1367331
   Zhao MS, 2010, SCIENCE, V329, P940, DOI [10.1126/science.1192666, 10.1126/science.1189590]
NR 44
TC 0
Z9 0
U1 11
U2 11
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 1548-1603
EI 1943-7226
J9 GISCI REMOTE SENS
JI GISci. Remote Sens.
PD DEC 31
PY 2024
VL 61
IS 1
AR 2401247
DI 10.1080/15481603.2024.2401247
PG 21
WC Geography, Physical; Remote Sensing
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Physical Geography; Remote Sensing
GA F5W1V
UT WOS:001310511400001
OA gold
DA 2025-01-10
ER

PT J
AU Khikmah, F
   Sebald, C
   Metzner, M
   Schwieger, V
AF Khikmah, Fithrothul
   Sebald, Christoph
   Metzner, Martin
   Schwieger, Volker
TI Modelling Vegetation Health and Its Relation to Climate Conditions Using
   Copernicus Data in the City of Constance
SO REMOTE SENSING
LA English
DT Article
DE climate change; Copernicus; Climate Data Store; city resilience;
   vegetation health; vulnerability; bioclimate indicators; municipal;
   urban planning; remote sensing
AB Monitoring vegetation health and its response to climate conditions is critical for assessing the impact of climate change on urban environments. While many studies simulate and map the health of vegetation, there seems to be a lack of high-resolution, low-scale data and easy-to-use tools for managers in the municipal administration that they can make use of for decision-making. Data related to climate and vegetation indicators, such as those provided by the C3S Copernicus Data Store (CDS), are mostly available with a coarse resolution but readily available as freely available and open data. This study aims to develop a systematic approach and workflow to provide a simple tool for monitoring vegetation changes and health. We built a toolbox to streamline the geoprocessing workflow. The data derived from CDS included bioclimate indicators such as the annual moisture index and the minimum temperature of the coldest month (BIO06). The biophysical parameters used are leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FAPAR). We used a linear regression model to derive equations for downscaled biophysical parameters, applying vegetation indices derived from Sentinel-2, to identify the vegetation health status. We also downscaled the bioclimatic indicators using the digital elevation model (DEM) and Landsat surface temperature derived from Landsat 8 through Bayesian kriging regression. The downscaled indicators serve as a critical input for forest-based classification regression to model climate envelopes to address suitable climate conditions for vegetation growth. The results derived contribute to the overall development of a workflow and tool for and within the CoKLIMAx project to gain and deliver new insights that capture vegetation health by explicitly using data from the CDS with a focus on the City of Constance at Lake Constance in southern Germany. The results shall help gain new insights and improve urban resilient, climate-adaptive planning by providing an intuitive tool for monitoring vegetation health and its response to climate conditions.
C1 [Khikmah, Fithrothul] Monash Univ Indonesia, Fac Art Design & Architecture, Tangerang Selatan 15345, Indonesia.
   [Sebald, Christoph; Metzner, Martin; Schwieger, Volker] Univ Stuttgart, Inst Engn Geodesy IIGS, Fac Aerosp Engn & Geodesy 6, D-70174 Stuttgart, Germany.
C3 University of Stuttgart
RP Sebald, C (corresponding author), Univ Stuttgart, Inst Engn Geodesy IIGS, Fac Aerosp Engn & Geodesy 6, D-70174 Stuttgart, Germany.
EM fithrothul.khikmah@monash.edu; chr.sebald@gmail.com;
   martin.metzner@iigs.uni-stuttgart.de;
   volker.schwieger@iigs.uni-stuttgart.de
OI Schwieger, Volker/0000-0001-9055-9809; Sebald,
   Christoph/0000-0001-6597-7857
FU German Aerospace Center
FX The publication is based on a master thesis at Stuttgart University of
   Applied Sciences (HFT) and the University of Stuttgart, Institute of
   Engineering Geodesy (IIGS), that was co. supervised by C. Sebald. The
   support of M. Hahn. from the Stuttgart University of Applied Sciences
   (HFT) is gratefully acknowledged. The authors would also like to thank
   the editors and the reviewers for their help and suggestions.
CR [Anonymous], 2018, Urban Atlas Street Tree Layer, DOI [10.2909/205691b3-7ae9-41dd-abf1-1fbf60d72c8c, DOI 10.2909/205691B3-7AE9-41DD-ABF1-1FBF60D72C8C]
   Bajocco S, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14153554
   Bonafoni S, 2016, EUR J REMOTE SENS, V49, P553, DOI 10.5721/EuJRS20164929
   BOX EO, 1993, J BIOGEOGR, V20, P629, DOI 10.2307/2845519
   Breiman L., 2001, Machine Learning, V45, P5, DOI 10.1023/A:1010933404324
   Bühler MM, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13183634
   Buermann W, 2002, J GEOPHYS RES-ATMOS, V107, DOI 10.1029/2001JD000975
   Cârlan I, 2020, ECOL INFORM, V55, DOI 10.1016/j.ecoinf.2019.101032
   Chen ZT, 2021, ECOL EVOL, V11, P7335, DOI 10.1002/ece3.7564
   Copernicus Climate Change Service (C3S), 2018, Climate Data Store (CDS) Copernicus Climate Change Service Leaf Area Index and Fraction Absorbed of Photosynthetically Active Radiation 10-Daily Gridded Data from 1981 to Present, DOI [10.24381/cds.7-59b01a, DOI 10.24381/CDS.7-59B01A]
   Daly C, 2008, INT J CLIMATOL, V28, P2031, DOI 10.1002/joc.1688
   defence-industry-space.ec.europa.eu, Copernicus Copernicus History Overview
   European Environment Agency, 2016, URB AD CLIM CHANG EU
   European Environment Agency, 2020, URB AD EUR CIT TOWNS
   European Environment Agency, Extreme Weather: Floods, Droughts and Heatwaves
   Gamble J.L., 2016, The Impacts of Climate Change on Human Health in the United States: A Scientific Assessment, DOI [10.7930/J00P0WXS, DOI 10.7930/J00P0WXS]
   Heikkinen RK, 2006, PROG PHYS GEOG, V30, P751, DOI 10.1177/0309133306071957
   Heugel A., 2020, Lake Constance
   HUETE A R, 1988, Remote Sensing of Environment, V25, P295, DOI 10.1016/0034-4257(88)90106-X
   Kabisch N, 2017, THEOR PRACT URB SUST, P1, DOI 10.1007/978-3-319-56091-5
   Kamenova I, 2021, EUR J REMOTE SENS, V54, P89, DOI 10.1080/22797254.2020.1839359
   Lechterbeck J, 2021, GRANA, V60, P119, DOI 10.1080/00173134.2020.1784265
   Magness DR, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0208883
   Notaro M, 2012, ECOL APPL, V22, P1365, DOI 10.1890/11-1269.1
   Onacillová K, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14164076
   Rondeaux G, 1996, REMOTE SENS ENVIRON, V55, P95, DOI 10.1016/0034-4257(95)00186-7
   Rosch M., 1993, Vegetation History and Archaeobotany, V2, P213, DOI [DOI 10.1007/BF00198163, 10.1007/BF00198163]
   Weiss JL, 2004, J ARID ENVIRON, V58, P249, DOI 10.1016/j.jaridenv.2003.07.001
   Wu H, 2009, SENSORS-BASEL, V9, P1768, DOI 10.3390/s90301768
   Yan K., VIIRS Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation Absorbed by Vegetation (FPAR) Product Algorithm Theoretical Basis Document (ATBD)
   Zanaga Daniele, 2021, Zenodo, DOI 10.5281/ZENODO.5571935
   Zarco-Tejada P., 2007, ESTUDIOS ZONA NO SAT, P37
   Zbigniew B., 2017, Geoinf. Issues, V9, P15
NR 33
TC 0
Z9 0
U1 2
U2 4
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 2024
VL 16
IS 4
AR 691
DI 10.3390/rs16040691
PG 20
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 JJ0U8
UT WOS:001172688400001
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Maheng, D
   Bhattacharya, B
   Zevenbergen, C
   Pathirana, A
AF Maheng, Dikman
   Bhattacharya, Biswa
   Zevenbergen, Chris
   Pathirana, Assela
TI Changing Urban Temperature and Rainfall Patterns in Jakarta: A
   Comprehensive Historical Analysis
SO SUSTAINABILITY
LA English
DT Article
DE urbanization; land use land cover change; urban temperature; daily
   rainfall; flooding; Jakarta
ID EXTREME RAINFALL; CLIMATE-CHANGE; HEAT-ISLAND; ST-LOUIS; IMPACTS;
   PRECIPITATION; URBANIZATION; INDONESIA; TOKYO; CITY
AB The increasing global population and in-country migration have a significant impact on global land use land cover (LULC) change, which reduces green spaces and increases built-up areas altering the near-surface radiation and energy budgets, as well as the hydrological cycle over an urban area. The LULC change can lead to a combination of hazards such as increasing urban temperatures and intensified rainfall, ultimately resulting in increased flooding. This present study aims to discuss the changing pattern in urban temperature, daily rainfall, and flooding in Jakarta. The daily urban temperature and daily rainfall were based on a 30-year dataset from three meteorological stations of Jakarta in the period between 1987 and 2013. The changing trend was analyzed by using the Mann-Kendall and the Pettitt's tests. The relation between daily rainfall and flooding was analyzed using a 30-year flooding dataset collected from several sources including the international disaster database, research, and newspaper. The results show that there was an increasing trend in the daily temperature and the daily rainfall in Jakarta. The annual maximum daily temperature showed that an increasing trend started in 2001 at the KMY station, and in 1996 at the SHIA station. In general, the highest annual maximum daily temperature was about 37 degrees C, while the lowest was about 33 degrees C. Moreover, the maximum daily rainfall started increasing from 2001. An increase in the maximum daily rainfall was observed mainly in January and February, which coincided with the flood events recorded in these months in Jakarta. This indicates that Jakarta is not only vulnerable to high urban temperature but also to flooding. While these two hazards occur in distinct timeframes, there is potential for their convergence in the same geographical area. This study provides new and essential insights to enhance urban resilience and climate adaptation, advocating a holistic approach required to tackle these combined hazards.
C1 [Maheng, Dikman] Delft Univ Technol, Fac Civil Engn & Geosci, Stevinweg 1, NL-2628CN Delft, Netherlands.
   [Maheng, Dikman; Zevenbergen, Chris; Pathirana, Assela] Inst Water Educ, Dept Coastal & Urban Risk & Resilience, IHE Delft, WestVest 7, NL-2611AX Delft, Netherlands.
   [Maheng, Dikman] Univ Muhammadiyah Kendari, Dept Civil Engn, Jalan Ahmad Dahlan 10, Kendari 93117, Indonesia.
   [Bhattacharya, Biswa] Inst Water Educ, Dept Hydro Informat & Socio Tech Innovat, IHE Delft, WestVest 7, NL-2611AX Delft, Netherlands.
   [Zevenbergen, Chris] Delft Univ Technol, Fac Architecture & Built Environm, Dept Urbanism, Julianalaan 134, NL-2628 BL Delft, Netherlands.
C3 Delft University of Technology; IHE Delft Institute for Water Education;
   Universitas Muhammadiyah Kendari; IHE Delft Institute for Water
   Education; Delft University of Technology
RP Maheng, D (corresponding author), Delft Univ Technol, Fac Civil Engn & Geosci, Stevinweg 1, NL-2628CN Delft, Netherlands.; Maheng, D (corresponding author), Inst Water Educ, Dept Coastal & Urban Risk & Resilience, IHE Delft, WestVest 7, NL-2611AX Delft, Netherlands.; Maheng, D (corresponding author), Univ Muhammadiyah Kendari, Dept Civil Engn, Jalan Ahmad Dahlan 10, Kendari 93117, Indonesia.
EM m.d.maheng@tudelft.nl
RI PARK, DAERYONG/B-3888-2013; Pathirana, Assela/B-5189-2011; Maheng,
   Muhammad/Z-5113-2019; Maheng, Muhammad Dikman/N-4182-2017
OI Maheng, Muhammad Dikman/0000-0003-4777-2246; Zevenbergen,
   Christiaan/0000-0003-0807-5253; Pathirana, Assela/0000-0003-0907-1764
FU Indonesia Endowment Fund for Education (LPDP)
FX The authors acknowledge the use of data from Agency for Meteorology,
   Climatology and Geophysics of Republic of Indonesia (BMKG). The authors
   appreciate all anonymous reviewers who provide valuable and constructive
   comments which have improved the quality of the paper.
CR Aldrian E., 2008, J HIDROSFIR INDONESI, V3, P105
   Alvarez JAC, 2019, ENVIRON ECON POLICY, V21, P555, DOI 10.1007/s10018-019-00242-w
   Arvind G, 2017, IOP C SER EARTH ENV, V80, DOI 10.1088/1755-1315/80/1/012067
   Asseng S, 2021, LANCET PLANET HEALTH, V5, pE378, DOI 10.1016/S2542-5196(21)00079-6
   Bergeson CB, 2022, J ENVIRON MANAGE, V313, DOI 10.1016/j.jenvman.2022.115004
   bmkg, BMKG DATA ONLINE PUS
   Carolita I., 2002, LAND USE PATTERN CHA
   CEDR, INT DIS DAT
   Chow V. T., 1988, Applied hydrology
   Darmanto NS, 2019, URBAN CLIM, V29, DOI 10.1016/j.uclim.2019.100482
   De Troeyer K, 2020, ENVIRON RES, V188, DOI 10.1016/j.envres.2020.109848
   detik, DETIKNEWS BANJIR 131
   detik, DETIKNEWS KORBAN BAN
   Diposaptono S., 2004, ASIAN PACIFIC COASTS, P1, DOI [10.1142/9789812703040_0006, DOI 10.1142/9789812703040_0006]
   Doan QV, 2016, INT J CLIMATOL, V36, P3633, DOI 10.1002/joc.4582
   Duan YL, 2019, J CLIMATE, V32, P5453, DOI 10.1175/JCLI-D-18-0513.1
   Eshtawi T, 2016, HYDROLOG SCI J, V61, P826, DOI 10.1080/02626667.2014.1000916
   Fletcher TD, 2013, ADV WATER RESOUR, V51, P261, DOI 10.1016/j.advwatres.2012.09.001
   Forman R.T.T., 2013, URBAN ECOL
   Fu P, 2018, THEOR APPL CLIMATOL, V133, P123, DOI 10.1007/s00704-017-2160-3
   Gao J, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-15788-7
   Gregory JH, 2006, J SOIL WATER CONSERV, V61, P117
   Guardian T., 4 METRE FLOODWATERS
   Han JY, 2014, ASIA-PAC J ATMOS SCI, V50, P17, DOI 10.1007/s13143-014-0016-7
   Hasibuan HS, 2023, CITY ENVIRON INTERAC, V18, DOI 10.1016/j.cacint.2023.100103
   Hidalgo J, 2008, ANN NY ACAD SCI, V1146, P354, DOI 10.1196/annals.1446.015
   HUFF FA, 1978, J APPL METEOROL, V17, P565, DOI 10.1175/1520-0450(1978)017<0565:UTADEO>2.0.CO;2
   Jaiswal RK, 2015, ENVIRON PROCESS, V2, P729, DOI 10.1007/s40710-015-0105-3
   jakarta, 2020, MEDIA JAYA INFORM ME
   JBA, RETR VIEWS FLOODS JA
   Jin MLS, 2015, CLIMATE, V3, P193, DOI 10.3390/cli3010193
   Kasai M, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9081467
   Kaspersen PS, 2017, HYDROL EARTH SYST SC, V21, P4131, DOI 10.5194/hess-21-4131-2017
   Kolokotroni M, 2012, ENERG BUILDINGS, V47, P302, DOI 10.1016/j.enbuild.2011.12.019
   Kusaka H, 2014, J APPL METEOROL CLIM, V53, P824, DOI 10.1175/JAMC-D-13-065.1
   Lei CG, 2023, URBAN CLIM, V47, DOI 10.1016/j.uclim.2022.101399
   Li Y, 2005, J CLIMATE, V18, P852, DOI 10.1175/JCLI-3296.1
   Lin CY, 2011, J APPL METEOROL CLIM, V50, P339, DOI 10.1175/2010JAMC2504.1
   Luiz-Silva W, 2022, NAT HAZARDS, V114, P713, DOI 10.1007/s11069-022-05409-5
   MacDicken KG, 2015, FOREST ECOL MANAG, V352, P3, DOI 10.1016/j.foreco.2015.02.006
   Maheng D., 2023, CITY ENVIRON INTERAC
   Maheng D, 2021, LAND-BASEL, V10, DOI 10.3390/land10020218
   Maheng D, 2019, ATMOSPHERE-BASEL, V10, DOI 10.3390/atmos10030151
   Majidi AN, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11226361
   Marani M, 2015, ADV WATER RESOUR, V79, P121, DOI 10.1016/j.advwatres.2015.03.001
   Marelle L, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/abcc8f
   Matsumoto J, 2017, J ENVIRON SCI-CHINA, V59, P54, DOI 10.1016/j.jes.2017.04.012
   McCarthy MP, 2010, GEOPHYS RES LETT, V37, DOI 10.1029/2010GL042845
   Nagasawa R., 2015, Urban Plan. Des. Res, V3, P7, DOI [10.14355/updr.2015.03.002, DOI 10.14355/UPDR.2015.03.002]
   Ndoen E.M., 2013, EVOLUTION RISK VULNE
   Noorduyn J., 1972, Bijdr. Tot De Taal-Land En Volkenkd, V2, P298, DOI DOI 10.1163/22134379-90002752
   Nuryanto DE, 2018, IOP C SER EARTH ENV, V149, DOI 10.1088/1755-1315/149/1/012028
   Nuryanto DE, 2019, GEOSCI LETT, V6, DOI 10.1186/s40562-019-0131-5
   Oke T. R., 2017, Urban Climates, DOI [10.1017/9781139016476, DOI 10.1017/9781139016476]
   Oke TR, 1987, BOUNDARY LAYER CLIMA, DOI [10.4324/9780203407219, DOI 10.4324/9780203407219]
   Pathirana A, 2014, ATMOS RES, V138, P59, DOI 10.1016/j.atmosres.2013.10.005
   Potapov P, 2022, FRONT REMOTE SENS, V3, DOI 10.3389/frsen.2022.856903
   Pravitasari A.E., 2015, THESIS KYOTO U JAPAN
   Doan QV, 2021, Q J ROY METEOR SOC, V147, P1189, DOI 10.1002/qj.3966
   Ramdhoni S, 2016, PROCEDIA ENVIRON SCI, V33, P204, DOI 10.1016/j.proenv.2016.03.071
   Regoto P, 2021, INT J CLIMATOL, V41, P5125, DOI 10.1002/joc.7119
   ReliefWeb, 2013, JAKARTA FLOOD RESPON
   reliefweb, 2002, RELIEFWEB FLOODS JAK
   ReliefWeb AHA Centre, 2015, FLASH UPDATE JAKARTA
   ReliefWeb Indonesia, 4 RELIEFWEB IND
   Rozoff CM, 2003, J APPL METEOROL, V42, P716, DOI 10.1175/1520-0450(2003)042<0716:SOSLML>2.0.CO;2
   Rustiadi E., 2002, LAND COVER CHANGE JA
   Shang HX, 2020, J HYDROL, V591, DOI 10.1016/j.jhydrol.2020.125594
   Sharma R, 2019, J URBAN HEALTH, V96, P235, DOI 10.1007/s11524-018-0322-y
   Shephard JM, 2005, EARTH INTERACT, V9
   Sherwood SC, 2010, P NATL ACAD SCI USA, V107, P9552, DOI 10.1073/pnas.0913352107
   Siswanto, 2022, J METEOROL SOC JPN, V100, P475, DOI [10.2151/jmsj.2022-023475, 10.2151/jmsj.2022-023]
   Siswanto, 2017, WEATHER CLIM EXTREME, V16, P23, DOI 10.1016/j.wace.2017.03.003
   Siswanto, 2015, B AM METEOROL SOC, V96, pS131, DOI 10.1175/BAMS-D-15-00128.1
   Siswanto S, 2016, INT J CLIMATOL, V36, P3207, DOI 10.1002/joc.4548
   Sobri E., 2009, J AGROMETEOROL, V23, P169
   Song XP, 2018, NATURE, V560, P639, DOI 10.1038/s41586-018-0411-9
   Steensen BM, 2022, CLIM DYNAM, V58, P3393, DOI 10.1007/s00382-021-06105-z
   Steul K, 2018, INT J HYG ENVIR HEAL, V221, P81, DOI 10.1016/j.ijheh.2017.10.005
   Supari, 2018, CLIM DYNAM, V51, P2559, DOI 10.1007/s00382-017-4028-8
   Supari,, 2017, INT J CLIMATOL, V37, P1979, DOI 10.1002/joc.4829
   Takagi H, 2021, OCEAN COAST MANAGE, V211, DOI 10.1016/j.ocecoaman.2021.105753
   Tokairin T, 2010, INT J CLIMATOL, V30, P1931, DOI 10.1002/joc.2138
   Towler E, 2020, WEATHER CLIM EXTREME, V29, DOI 10.1016/j.wace.2020.100260
   Tsiringakis A., 2017, P EMS ANN M EUROPEAN
   Uddin ASMS, 2022, THEOR APPL CLIMATOL, V147, P891, DOI 10.1007/s00704-021-03872-x
   Umer Y, 2023, HYDROLOGY-BASEL, V10, DOI 10.3390/hydrology10010015
   UNDESA, 2018, World Urbanization Prospects: The 2018 Revision
   United Nations-DESA, 2018, REVISION WORLD URBAN
   United Nations-DESA, US
   uz Zaman Chaudhry Q., 2015, GOVT PAKISTAN MINIST
   Wicaksono A.P.A., 2021, J GLOB ENV DYN, V2, P8
   Winkler K, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-22702-2
   Yao L, 2015, URBAN FOR URBAN GREE, V14, P300, DOI 10.1016/j.ufug.2015.02.014
   Young A, 2021, J FLOOD RISK MANAG, V14, DOI 10.1111/jfr3.12702
   Zevenbergen C, 2017, NAT HAZARDS, V86, P901, DOI 10.1007/s11069-016-2724-z
   Zhong S, 2017, ATMOS CHEM PHYS, V17, P5439, DOI 10.5194/acp-17-5439-2017
NR 97
TC 0
Z9 0
U1 3
U2 8
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD JAN
PY 2024
VL 16
IS 1
AR 350
DI 10.3390/su16010350
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 ER4B6
UT WOS:001140626400001
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Nagamuthu, P
AF Nagamuthu, Piratheeparajah
TI Assessment of Projected Temperature and Precipitation in the Northern
   Province of Sri Lanka through Statistically Downscaled CMIP6 Projection
SO JOURNAL OF GEOLOGY GEOGRAPHY AND GEOECOLOGY
LA English
DT Article
DE Temperature; Rainfall; Multimodel; Ensemble; Increasing; Northern Sri
   Lanka
ID CLIMATE-CHANGE; RIVER-BASIN; IMPACT; FLOOD; RISK
AB The issue of climate change has emerged as a paramount concern for the global community, with several nations grappling with the far-reaching effects thereof on their respective territories. Among these nations, Sri Lanka is ranked as the country facing the greatest potential threat. In the Northern Province of Sri Lanka, which has experienced a rebirth after years of internal conflict with the aid of international agencies, projections regarding climate change indicate a diverse array of potential impacts. To arrive at these projections, a comprehensive analysis was conducted, which leveraged downscaled data derived from the Coupled Model Inter -comparison Projects, Phase 6 (CMIP6), obtained via the grid for the Northern Province. Various models were employed to scrutinize this data, and to validate the findings, an analysis was performed by comparing the model -simulated past climate data to observed data. Multimodal ensembles provided insights into unique temperature and precipitation patterns under varying emission scenarios, including the Shared Socioeconomic Pathways (SSP) 4.5 and 8.5, between 2020 and 2100. Under the SSP2 4.5 scenario, for instance, the temperature increase would total 1.13 degrees C, accompanied by 106.19mm of augmented rainfall. By contrast, under the SSP5-8.5 scenario, temperature would increase by 1.81 degrees C, with a projection of 159.6mm increase in rainfall. Moreover, spatially, the future changes in temperature and rainfall for the Northern Province of Sri Lanka display consequential variations. Specifically, the western part is projected to witness higher rates of temperature and rainfall increase than the eastern part. However, it should be noted that variations exist in the values of the projections of temperature and rainfall across the different models. Regardless, the region must brace itself for elevated temperatures, resulting in heatwaves and an augmented frequency of scorching days, indicating an urgent need for policymakers and communities to incorporate these findings when developing and implementing climate adaptation strategies that aim to mitigate climate change's adverse impact in the area of study.
C1 [Nagamuthu, Piratheeparajah] Univ Jaffna, Dept Geog, Jaffna, Sri Lanka.
C3 University Jaffna
RP Nagamuthu, P (corresponding author), Univ Jaffna, Dept Geog, Jaffna, Sri Lanka.
EM npiratheeparajah@gmail.com
RI PIRATHEEPARAJAH, NAGAMUTHU/AIA-0858-2022
CR Adams K, 2023, NAT HAZARDS, V116, P637, DOI 10.1007/s11069-022-05692-2
   ADB, 2022, Climate Change Risk Profile of the Mountain Region in Sri Lanka
   Alahacoon N, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13063427
   Alahacoon N, 2021, ISPRS INT J GEO-INF, V10, DOI 10.3390/ijgi10020084
   Basnayake S., 2021, APN Science Bulletin, V11, P37, DOI [DOI 10.30852/SB.2021.1499, 10.30852/sb.2021.1499]
   Bonjean Stanton M. C., 2016, Energy Policy, V1, DOI [10.1016/j. renene.2009.10.022%0A, DOI 10.1016/J.RENENE.2009.10.0"0A]
   Chandrasekara S. S. K., 2013, Experimental Climate Services for Water Management in Sri Lanka and Maldives
   De Costa WAJM, 2012, J NATL SCI FOUND SRI, V40, P281, DOI 10.4038/jnsfsr.v40i4.5041
   De Silva MMGT, 2018, ECOL ECON, V152, P131, DOI 10.1016/j.ecolecon.2018.05.010
   De Silva Shanthi, 2016, Impacts of Climate Change on Water Resources in Sri Lanka Impacts of Climate Change on Water Resources in Sri Lanka
   De Silva MT, 2019, J HYDROL-REG STUD, V25, DOI 10.1016/j.ejrh.2019.100624
   De-Silva G., 2016, HYDROLOGY CURRENT RE, V7, DOI [10.4172/2157-7587.1000228, DOI 10.4172/2157-7587.1000228]
   Eriyagama N., 2010, Impacts of climate change on water resources and agriculture in Sri Lanka: a review and preliminary vulnerability mapping
   Facts S, 2022, IPCC Climate Change technical report 2022: Impacts, Adaptation, and Level 2-Details on IPCC Climate Change technical report 2022: Impacts, P1
   Guruge A., 2017, Current Studies, V1, P40
   Hettiarachchi S., 2015, Journal of Humanities and Social Science, V3, P35
   IPCC, 2017, AR6- Synthesis Report on Climate Change
   IPCC, 2021, Eur. Univ. Inst., P2
   Iresh A. D. S., 2019, ANN SESS IESL, P571
   Kaklauskas A, 2018, PROCEDIA ENGINEER, V212, P270, DOI 10.1016/j.proeng.2018.01.035
   Kumar Guntu R., 2020, Sciforum Electronic Conference Series, V3
   Lacombe G, 2019, 1 INT WAT MAN I, DOI [10.5337/2019.202, DOI 10.5337/2019.202]
   Lee H., 2023, CLIMATE CHANGE 2023, DOI DOI 10.59327/IPCC/AR6-9789291691647
   Li JY, 2021, ECOL INDIC, V129, DOI 10.1016/j.ecolind.2021.107936
   Makubura R, 2022, FLUIDS, V7, DOI 10.3390/fluids7050147
   Nagamuthu P., 2015, J. S. Asian Stud, V03, P363
   Naveendrakumar G, 2018, ADV METEOROL, V2018, DOI 10.1155/2018/4217917
   Northern Provincial Council, 2022, Annual Report
   Piratheeparajah N., 2015, Journal of Environment and Earth Science, V5, P179
   Piratheeparajah N., 2016, The International Journal Environmental Science, V5, P63
   Piratheeparajah N., 2010, 3 NATL GEOGRAPHIC C, P35
   Praveen B, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-67228-7
   Rajendran M., 2017, Tropical Agricultural Research, V28, P375, DOI 10.4038/tar.v28i4.8239
   Ruosteenoja K., 2021, Geophysica, V56, P39
   Silva S. de, 2014, Environmental Engineering and Management Journal, V13, P881, DOI [10.30638/eemj.2014.092, DOI 10.30638/EEMJ.2014.092]
   Somasundaram D, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12223701
   Stocker, 2014, CLIMATE CHANGE 2013
   Thennakone V., 2018, International Journal of Hydraulic Engineering, V3, P38
   Umar Nura, 2023, International Journal of Environmental Studies, V80, P540, DOI 10.1080/00207233.2022.2081471
   Weerasinghe KM, 2018, PROCEDIA ENGINEER, V212, P503, DOI 10.1016/j.proeng.2018.01.065
   Withanachchi SS, 2014, CLIMATE, V2, P329, DOI 10.3390/cli2040329
   World Bank Group, 2021, User Manual Climate Change Knowledge Portal, P18
   Xiang YY, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14010115
NR 43
TC 2
Z9 2
U1 0
U2 0
PU OLES GONCHAR DNIPRO NATL UNIV
PI DNIPRO
PA GEOLOGY & GEOGRAPHY DEPT, DMYTRO YAVOMITSKYI, 36, DNIPRO, 49066, UKRAINE
SN 2617-2909
EI 2617-2119
J9 J GEOL GEOGR GEOECOL
JI J. Geol. Geogr. Geoecol.
PY 2024
VL 33
IS 1
BP 132
EP 154
DI 10.15421/112414
PG 23
WC Geosciences, Multidisciplinary
WE Emerging Sources Citation Index (ESCI)
SC Geology
GA MZ2L9
UT WOS:001197391400008
OA gold
DA 2025-01-10
ER

PT J
AU Marcos-Pérez, M
   Sánchez-Navarro, V
   Zornoza, R
AF Marcos-Perez, Mariano
   Sanchez-Navarro, Virginia
   Zornoza, Raul
TI Soil Greenhouse Gas Emissions in Intercropped Systems Between Melon and
   Cowpea
SO SPANISH JOURNAL OF SOIL SCIENCE
LA English
DT Article
DE intercropping; legumes; CO2 emissions; N2O emissions; crop
   diversification
ID ARBUSCULAR MYCORRHIZAL FUNGI; NITROUS-OXIDE EMISSIONS; CARBON-DIOXIDE;
   CO2 EMISSION; FIELD; TEMPERATURE
AB There is a need to assess alternative cropping systems for climate change mitigation. Hence, we aimed to evaluate if cowpea, a legume crop with high climate adaptability and active rhizodeposition, can reduce GHG emissions when intercropped with melon, if different intercropping patterns can affect these soil GHG emissions, and elucidate if GHG emissions are related by soil and crop properties. We compared a cowpea and melon monocultures with different melon-cowpea intercropping patterns during two crop cycles. The different melon-cowpea intercropping patterns were: row intercropping 1:1 (melon:cowpea), row intercropping 2:1 (melon:cowpea) and mixed intercropping (alternate melon/cowpea plants within the same row), receiving 30% less fertilizers than monocrops. Results showed that CO2 emission rates were higher in the row 2:1 and row 1:1 intercropping systems compared to mixed intercropping, melon monocrop and cowpea monocrop, with the lowest emissions, likely due to the highest density of both plant species, which may stimulate microbial communities. Soil N2O emission rates were not affected by crop diversification, with very low values. Soil CO(2 )and N2O emissions were not correlated with environmental factors, soil properties or crop yield and quality, suggesting that crop management and plant density and growth were the main factors controlling GHG emissions. When the GHG emissions were expressed on a crop production basis, the lowest values were observed in mixed intercropping, owing to higher crop production. However, the 1:1 and 2:1 cowpea intercropping systems, with the lowest overall crop production, showed higher values of GHG emissions per unit of product, compared to cowpea monocrop. Thus, intercropping systems, and mostly mixed intercropping, have the potential to contribute to sustainable agriculture by increasing land productivity, reducing the need for synthetic fertilizers and decreasing GHG emissions per unit of product. These results highlight the importance of considering both agricultural productivity and greenhouse gas emissions when designing and implementing intercropping systems.
C1 [Marcos-Perez, Mariano; Sanchez-Navarro, Virginia; Zornoza, Raul] Univ Politecn Cartagena, Escuela Tecn Super Ingn Agron, Sustainable Use Management & Reclamat Soil & Water, Cartagena, Spain.
C3 Universidad Politecnica de Cartagena
RP Marcos-Pérez, M (corresponding author), Univ Politecn Cartagena, Escuela Tecn Super Ingn Agron, Sustainable Use Management & Reclamat Soil & Water, Cartagena, Spain.
EM mariano.marcos@upct.es
RI Marcos-Pérez, Mariano/KUC-7455-2024; Zornoza, Raul/M-6939-2013
OI Marcos-Perez, Mariano/0000-0003-1882-0413
FU This research was funded by the Project AsociaHortus granted by the
   Spanish Ministry of Science and Innovation (AGL2017-83975-R).; Project
   AsociaHortus; Spanish Ministry of Science and Innovation; 
   [AGL2017-83975-R]
FX This research was funded by the Project AsociaHortus granted by the
   Spanish Ministry of Science and Innovation (AGL2017-83975-R).
CR Aldoshin N, 2020, ENG RUR DEVELOP, P767, DOI 10.22616/ERDev.2020.19.TF175
   Alvaro Fuentes J., 2019, HDB PLANT SOIL ANAL
   Amorim MR, 2022, APPL SOIL ECOL, V172, DOI 10.1016/j.apsoil.2021.104354
   Baggs EM, 2000, SOIL USE MANAGE, V16, P82, DOI 10.1111/j.1475-2743.2000.tb00179.x
   Bedoussac L, 2015, AGRON SUSTAIN DEV, V35, P911, DOI 10.1007/s13593-014-0277-7
   Boden T. A., 2009, CARBON DIOXIDE INF A
   Cavicchioli R, 2019, NAT REV MICROBIOL, V17, P569, DOI 10.1038/s41579-019-0222-5
   Chen WW, 2013, AGR ECOSYST ENVIRON, V178, P64, DOI 10.1016/j.agee.2013.05.008
   Cuartero J, 2022, FRONT MICROBIOL, V13, DOI 10.3389/fmicb.2022.1004593
   Cuartero J, 2022, AGR ECOSYST ENVIRON, V328, DOI 10.1016/j.agee.2022.107856
   D'Amours J, 2023, AGR ECOSYST ENVIRON, V341, DOI 10.1016/j.agee.2022.108205
   Dilekoglu MF, 2017, J ANIM PLANT SCI-PAK, V27, P1596
   Duhamel M, 2013, TRENDS PLANT SCI, V18, P597, DOI 10.1016/j.tplants.2013.08.010
   Dutaur L, 2007, GLOBAL BIOGEOCHEM CY, V21, DOI 10.1029/2006GB002734
   Fageria NK, 2011, J PLANT NUTR, V34, P945, DOI 10.1080/01904167.2011.555578
   FAO, 2017, The impact of disasters and crises on agriculture and food security: 2021, DOI DOI 10.4060/CB3673-N
   Feiglsconcelos ALSJ, 2022, BIOMASS BIOENERG, V158, DOI 10.1016/j.biombioe.2022.106342
   Gilbert Natasha., 2012, NATURE NEWS, DOI [10.1038/nature.2012.11708, DOI 10.1038/NATURE.2012.11708]
   Hijri I, 2006, MOL ECOL, V15, P2277, DOI 10.1111/j.1365-294X.2006.02921.x
   Huang JX, 2014, J INTEGR AGR, V13, P1363, DOI 10.1016/S2095-3119(13)60509-2
   Huang JX, 2019, PEDOSPHERE, V29, P764, DOI 10.1016/S1002-0160(17)60389-8
   IUSS Working Group WRB, 2015, World Soil Resources Reports, V106, DOI DOI 10.1017/S0014479706394902
   Jensen ES, 2012, AGRON SUSTAIN DEV, V32, P329, DOI 10.1007/s13593-011-0056-7
   Jiao H, 2011, MYCORRHIZA, V21, P681, DOI 10.1007/s00572-011-0377-z
   Li L, 2006, OECOLOGIA, V147, P280, DOI 10.1007/s00442-005-0256-4
   Li NH, 2020, MICROORGANISMS, V8, DOI 10.3390/microorganisms8060834
   Li YL, 2008, PEDOSPHERE, V18, P273, DOI 10.1016/S1002-0160(08)60017-X
   Lüscher A, 2014, GRASS FORAGE SCI, V69, P206, DOI 10.1111/gfs.12124
   Maitra S, 2021, AGRONOMY-BASEL, V11, DOI 10.3390/agronomy11020343
   Mao LL, 2015, J INTEGR AGR, V14, P1542, DOI 10.1016/S2095-3119(15)61039-5
   Marcos-Pérez M, 2023, SCI HORTIC-AMSTERDAM, V312, DOI 10.1016/j.scienta.2023.111834
   MurphyBokern D, 2017, LEGUMES IN CROPPING SYSTEMS, P1, DOI 10.1079/9781780644981.0000
   Oertel C, 2016, CHEM ERDE-GEOCHEM, V76, P327, DOI 10.1016/j.chemer.2016.04.002
   Panosso AR, 2009, SOIL TILL RES, V105, P275, DOI 10.1016/j.still.2009.09.008
   Paustian K, 2000, BIOGEOCHEMISTRY, V48, P147, DOI 10.1023/A:1006271331703
   Rocci KS, 2021, SCI TOTAL ENVIRON, V793, DOI 10.1016/j.scitotenv.2021.148569
   Sánchez-Navarro V, 2023, EUR J AGRON, V142, DOI 10.1016/j.eja.2022.126684
   Sanchez-Navarro V, 2022, SCI TOTAL ENVIRON, V845, DOI 10.1016/j.scitotenv.2022.157225
   Sánchez-Navarro V, 2019, EUR J AGRON, V107, P10, DOI 10.1016/j.eja.2019.03.007
   Senbayram M, 2016, ENERGY SUSTAIN SOC, V6, DOI 10.1186/s13705-015-0067-3
   Steinweg JM, 2012, SOIL BIOL BIOCHEM, V55, P85, DOI 10.1016/j.soilbio.2012.06.015
   Stuczynski TI, 2003, J ENVIRON QUAL, V32, P1346, DOI 10.2134/jeq2003.1346
   Tang XM, 2021, PEERJ, V9, DOI 10.7717/peerj.10880
   Usyskin-Tonne A, 2021, ISME J, V15, P1073, DOI 10.1038/s41396-020-00831-8
   Wang XL, 2021, J CLEAN PROD, V314, DOI 10.1016/j.jclepro.2021.127997
   Ward SE, 2013, ECOL LETT, V16, P1285, DOI 10.1111/ele.12167
   Wu HS, 2017, ATMOS ENVIRON, V158, P259, DOI 10.1016/j.atmosenv.2017.03.046
   Yerlikaya B A., 2020, Environment, Climate, Plant and Vegetation Growth, P109, DOI DOI 10.1007/978-3-030-49732-3_5
   Zhang MM, 2018, MICROBIOLOGYOPEN, V7, DOI 10.1002/mbo3.555
   Zornoza R, 2018, SCI TOTAL ENVIRON, V644, P1429, DOI 10.1016/j.scitotenv.2018.06.398
NR 50
TC 1
Z9 1
U1 3
U2 16
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
SN 2253-6574
J9 SPAN J SOIL SCI
JI Span. J. Soil Sci.
PD AUG 11
PY 2023
VL 13
AR 11368
DI 10.3389/sjss.2023.11368
PG 10
WC Soil Science
WE Emerging Sources Citation Index (ESCI)
SC Agriculture
GA Q1FY8
UT WOS:001055056600001
OA gold
DA 2025-01-10
ER

PT J
AU Machefer, M
   Perpinyà-Vallès, M
   Escorihuela, MJ
   Gustafsson, D
   Romero, L
AF Machefer, Melissande
   Perpinya-Valles, Marti
   Escorihuela, Maria Jose
   Gustafsson, David
   Romero, Laia
TI Challenges and Evolution of Water Level Monitoring towards a
   Comprehensive, World-Scale Coverage with Remote Sensing
SO REMOTE SENSING
LA English
DT Article
DE remote sensing; satellite; altimetry; water level; water inland;
   essential climate variable; database
ID TIME-SERIES; ALTIMETRY; BASIN; SURFACE; SCIENCE
AB Surface water availability is a fundamental environmental variable to implement effective climate adaptation and mitigation plans, as expressed by scientific, financial and political stakeholders. Recently published requirements urge the need for homogenised access to long historical records at a global scale, together with the standardised characterisation of the accuracy of observations. While satellite altimeters offer world coverage measurements, existing initiatives and online platforms provide derived water level data. However, these are sparse, particularly in complex topographies. This study introduces a new methodology in two steps (1) teroVIR, a virtual station extractor for a more comprehensive global and automatic monitoring of water bodies, and (2) teroWAT, a multimission, interoperable water level processor, for handling all terrain types. L2 and L1 altimetry products are used, with state-of-the-art retracker algorithms in the methodology. The work presents a benchmark between teroVIR and current platforms in West Africa, Kazakhastan and the Arctic: teroVIR shows an unprecedented increase from 55% to 99% in spatial coverage. A large-scale validation of teroWAT results in an average of unbiased root mean square error ubRMSE of 0.638 m on average for 36 locations in West Africa. Traditional metrics (ubRMSE, median, absolute deviation, Pearson coefficient) disclose significantly better values for teroWAT when compared with existing platforms, of the order of 8 cm and 5% improved respectively in error and correlation. teroWAT shows unprecedented excellent results in the Arctic, using an L1 products-based algorithm instead of L2, reducing the error by almost 4 m on average. To further compare teroWAT with existing methods, a new scoring option, teroSCO, is presented, measuring the quality of the validation of time series transversally and objectively across different strategies. Finally, teroVIR and teroWAT are implemented as platform-agnostic modules and used by flood forecasting and river discharge methods as relevant examples. A review of various applications for miscellaneous end-users is given, tackling the educational challenge raised by the community.
C1 [Machefer, Melissande; Perpinya-Valles, Marti; Romero, Laia] Lobelia Earth SL, Marie Curie 8-14,A226, Barcelona 08042, Spain.
   [Escorihuela, Maria Jose] isardSAT, Marie Curie 8-14,A219, Barcelona 08042, Spain.
   [Gustafsson, David] Sveriges Meteorol & HydrolInst SMHI, Folkborgsvagen 17, SE-60176 Norrkoping, Sweden.
RP Machefer, M (corresponding author), Lobelia Earth SL, Marie Curie 8-14,A226, Barcelona 08042, Spain.
EM melissande@lobelia.earth; marti@lobelia.earth;
   mj.escorihuela@isardsat.cat; david.gustafsson@smhi.se;
   laia@lobelia.earth
RI Escorihuela, Maria/AAB-5851-2020; Gustafsson, David/G-6729-2012
OI Machefer, Melissande/0000-0002-9359-3946; Romero,
   Laia/0000-0001-6476-0875; Escorihuela, Maria Jose/0000-0002-7780-7334;
   Perpinya-Valles, Marti/0000-0002-9886-9331; Gustafsson,
   David/0000-0002-2754-7415
CR Abdalla S, 2021, ADV SPACE RES, V68, P319, DOI 10.1016/j.asr.2021.01.022
   Abileah R., 2011, Int. Water Technol. J, V1, P6377
   Agency E.S.,, 2012, SENTINEL 3 ESAS GLOB
   Alsdorf D, 2001, GEOPHYS RES LETT, V28, P2671, DOI 10.1029/2001GL012962
   Andersson JCM, 2017, PHYS CHEM EARTH, V100, P3, DOI 10.1016/j.pce.2017.02.010
   Benveniste J., 2008, P IGARSS 2008 2008 I, VVolume 3, pII, DOI [10.1109/IGARSS.2008.4779494, DOI 10.1109/IGARSS.2008.4779494]
   Birkett C, 2011, COASTAL ALTIMETRY, P19, DOI 10.1007/978-3-642-12796-0_2
   Bogning S, 2018, REMOTE SENS-BASEL, V10, DOI 10.3390/rs10020350
   BROWN GS, 1977, IEEE T ANTENN PROPAG, V25, P67, DOI 10.1109/TAP.1977.1141536
   Buchhorn M, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12061044
   Calmant S, 2016, REMOTE SENS OBSERV C, P175
   Calmant S, 2013, ADV SPACE RES, V51, P1551, DOI 10.1016/j.asr.2012.07.033
   Chen X, 2014, HYDROL EARTH SYST SC, V18, P1539, DOI 10.5194/hess-18-1539-2014
   Coss S, 2020, EARTH SYST SCI DATA, V12, P137, DOI 10.5194/essd-12-137-2020
   Crétaux JF, 2011, ADV SPACE RES, V47, P1497, DOI 10.1016/j.asr.2011.01.004
   da Silva JS, 2010, REMOTE SENS ENVIRON, V114, P2160, DOI 10.1016/j.rse.2010.04.020
   Davis CH, 1997, IEEE T GEOSCI REMOTE, V35, P974, DOI 10.1109/36.602540
   Dekking F. M., 2005, A Modern Introduction to Probability and Statistics Understanding Why and How, P383, DOI 10.1007/1-84628-168-7
   Duan Z, 2013, REMOTE SENS ENVIRON, V134, P403, DOI 10.1016/j.rse.2013.03.010
   Gao Q, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11060718
   Garcia-Mondejar A., 2016, P DRAGON 3 FINAL RES
   Haritashya UK, 2006, HYDROL PROCESS, V20, P3147, DOI 10.1002/hyp.6397
   Huntington TG, 2006, J HYDROL, V319, P83, DOI 10.1016/j.jhydrol.2005.07.003
   Lettenmaier DP, 2015, WATER RESOUR RES, V51, P7309, DOI 10.1002/2015WR017616
   Makhoul E, 2018, ADV SPACE RES, V62, P1464, DOI 10.1016/j.asr.2018.04.004
   Markert KN, 2019, ENVIRON MODELL SOFTW, V117, P164, DOI 10.1016/j.envsoft.2019.03.021
   Normandin C, 2018, REMOTE SENS-BASEL, V10, DOI 10.3390/rs10060833
   Pekel JF, 2016, NATURE, V540, P418, DOI 10.1038/nature20584
   Qiao BJ, 2019, J HYDROL, V578, DOI 10.1016/j.jhydrol.2019.124052
   Schröder S, 2019, HYDROL EARTH SYST SC, V23, P4113, DOI 10.5194/hess-23-4113-2019
   Schwatke C, 2015, HYDROL EARTH SYST SC, V19, P4345, DOI 10.5194/hess-19-4345-2015
   Tarpanelli A, 2019, IEEE T GEOSCI REMOTE, V57, P329, DOI 10.1109/TGRS.2018.2854625
   Tong XH, 2016, REMOTE SENS ENVIRON, V187, P400, DOI 10.1016/j.rse.2016.10.012
   Van Den Hoek J, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11070827
   Vignudelli S, 2011, COASTAL ALTIMETRY, P1, DOI 10.1007/978-3-642-12796-0
   Vignudelli S, 2019, EXTREME HYDROCLIMATIC EVENTS AND MULTIVARIATE HAZARDS IN A CHANGING ENVIRONMENT: A REMOTE SENSING APPROACH, P87, DOI 10.1016/B978-0-12-814899-0.00004-3
   Zaidi AZ, 2021, ADV SPACE RES, V68, P641, DOI 10.1016/j.asr.2020.03.044
   Zhai P., 2021, CONTRIBUTION WORKING, DOI DOI 10.1007/978-94-007-4001-3_7
NR 38
TC 1
Z9 2
U1 0
U2 5
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2072-4292
J9 REMOTE SENS-BASEL
JI Remote Sens.
PD AUG
PY 2022
VL 14
IS 15
AR 3513
DI 10.3390/rs14153513
PG 16
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 3S6WV
UT WOS:000839735400001
OA Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Nyoni, NMB
   Grab, S
   Archer, E
   Malherbe, J
AF Nyoni, Njongenhle M. B.
   Grab, Stefan
   Archer, Emma
   Malherbe, Johan
TI Temperature and relative humidity trends in the northernmost region of
   South Africa, 1950-2016
SO SOUTH AFRICAN JOURNAL OF SCIENCE
LA English
DT Article
DE agriculture; climate change; temperature; humidity; northernmost; South
   Africa
ID CLIMATE-CHANGE; HEAT WAVES; IMPACTS; VARIABILITY; ADAPTATION; EXTREMES;
   PROVINCE; MAXIMUM; SEASON; RANGE
AB The northernmost Limpopo Province is located in one of the warmest regions of South Africa, where the agricultural sector is prone to heat stress. The aim of this study was to explore air temperature and relative humidity trends for the region, which have implications for agricultural adaptation and management (amongst other sectors). In particular, we investigated seasonal, annual and decadal scale air temperature and relative humidity changes for the period 1950-2016. Positive temperature trends were recorded for this period, averaging +0.02 degrees C/year, with the strongest changes observed in mean maximum summer temperatures (+0.03 degrees C/year). Interannual temperature variability also increased over time, especially for the period 2010-2016, which presents probability densities of <50% for minimum temperatures. Positive relative humidity trends (+0.06%/year) were also recorded for the period 1980- 2016, but proved to be the least predictable weather parameter, with probability densities of <0.5% across seasons for the study period. Considering the substantial interannual variability in temperature and relative humidity, there is clear increased risk for the agricultural sector, particularly for small-scale farmers who generally have limited capacity to adapt. Climate science focusing on the southern African region should continue to establish the impact of climate change and variability on specific small-scale farming systems and enterprises, with recommendations for strategic adaptation based on up-to-date evidence. Significance: center dot Heat indices have increased, and variability in temperature and relative humidity has substantially increased over recent decades. center dot Changes in air temperature and relative humidity have direct and/or indirect negative effects on sectors such as agriculture, leading to reduced productivity. center dot The small-scale farming sector, which contributes significantly to national food security in developing countries, is the production system most exposed and vulnerable to observed changes/extremes in temperature and relative humidity. center dot There is an urgent need to build capacity of small-scale farmers for appropriate adaptation to observed changes in climate based on up-to-date evidence.
C1 [Nyoni, Njongenhle M. B.; Grab, Stefan] Univ Witwatersrand, Sch Geog Archaeol & Environm Studies, Johannesburg, South Africa.
   [Nyoni, Njongenhle M. B.] Food Agr & Nat Resources Policy Anal Network FANR, Pretoria, South Africa.
   [Archer, Emma] Univ Pretoria, Dept Geog Geoinformat & Meteorol, Pretoria, South Africa.
   [Malherbe, Johan] Soil Climate & Water Agr Res Council, Pretoria, South Africa.
   [Malherbe, Johan] Council Sci & Ind Res CSIR, Smart Pl, Johannesburg, South Africa.
C3 University of Witwatersrand; University of Pretoria
RP Nyoni, NMB (corresponding author), Univ Witwatersrand, Sch Geog Archaeol & Environm Studies, Johannesburg, South Africa.; Nyoni, NMB (corresponding author), Food Agr & Nat Resources Policy Anal Network FANR, Pretoria, South Africa.
EM nmbnyoni@gmail.com
RI Archer, Emma/V-5736-2019
OI Grab, Stefan/0000-0001-7678-1526; Malherbe, Johan/0000-0003-3124-5687;
   Archer, Emma/0000-0002-5374-3866
FU Open Society Foundation
FX Open Society Foundation
CR Anderson G., 2016, Weathermetrics: Functions to Convert Between Weather Metrics (R package)
   Blunden J., 2012, Bull. Am. Meteorol. Soc, V93, pS1, DOI DOI 10.1175/2012BAMSSTATEOFTHECLIMATE.1
   Boissonnade AC, 2002, CLIMATE RISK WEATHER, P73
   Davis CL, 2016, S AFR J SCI, V112, P89, DOI 10.17159/sajs.2016/20150217
   Diallo I, 2015, THEOR APPL CLIMATOL, V121, P749, DOI 10.1007/s00704-014-1260-6
   Easterling DR, 1997, SCIENCE, V277, P364, DOI 10.1126/science.277.5324.364
   Engelbrecht F, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/8/085004
   Gbetibouo G.A., 2009, IFPRI DISCUSSION PAP, DOI DOI 10.1068/A312017
   Hachigonta S., 2013, SO AFRICAN AGR CLIMA, DOI [10.2499/9780896292086, DOI 10.2499/9780896292086]
   Huth R, 2000, CLIMATIC CHANGE, V46, P29, DOI 10.1023/A:1005633925903
   Hyndman R.J., 2020, PACKAGE FORECAST CRA
   Jury MR, 2013, S AFR J SCI, V109, P53, DOI 10.1590/sajs.2013/980
   KARL TR, 1993, B AM METEOROL SOC, V74, P1007, DOI 10.1175/1520-0477(1993)074<1007:ANPORG>2.0.CO;2
   Keggenhoff I, 2015, WEATHER CLIM EXTREME, V8, P34, DOI 10.1016/j.wace.2014.11.002
   Kruger AC, 2013, INT J CLIMATOL, V33, P661, DOI 10.1002/joc.3455
   Kruger AC, 2019, S AFR J SCI, V115, P50, DOI 10.17159/sajs.2019/4846
   Kruger AC, 2017, INT J CLIMATOL, V37, P2364, DOI 10.1002/joc.4851
   Kusangaya S, 2014, PHYS CHEM EARTH, V67-69, P47, DOI 10.1016/j.pce.2013.09.014
   Lakhraj-Govender R, 2017, INT J CLIMATOL, V37, P2337, DOI 10.1002/joc.4849
   Lefcourt AM, 1996, J ANIM SCI, V74, P2633
   Liu BH, 2004, J CLIMATE, V17, P4453, DOI 10.1175/3230.1
   MacKellar N, 2014, S AFR J SCI, V110, P51, DOI 10.1590/sajs.2014/20130353
   Makhado Rudzani, 2016, Transactions of the Royal Society of South Africa, V71, DOI 10.1080/0035919X.2015.1102174
   Mbokodo I, 2020, ATMOSPHERE-BASEL, V11, DOI 10.3390/atmos11070712
   Meehl GA, 2004, SCIENCE, V305, P994, DOI 10.1126/science.1098704
   National Weather Service Hydrometeorological Prediction Center Web Team, 2015, HEAT IND CALC
   New M, 2006, J GEOPHYS RES-ATMOS, V111, DOI 10.1029/2005JD006289
   Nyoni NMB, 2019, CLIM DEV, V11, P83, DOI 10.1080/17565529.2018.1442792
   Qu M, 2014, WEATHER CLIM EXTREME, V4, P86, DOI 10.1016/j.wace.2014.05.002
   Schlenker W, 2009, P NATL ACAD SCI USA, V106, P15594, DOI 10.1073/pnas.0906865106
   Shisanya S, 2016, FOOD SECUR, V8, P597, DOI 10.1007/s12571-016-0569-7
   South African Department of Environmental Affairs, 2013, LONG TERM ADAPTATION
   Spinu V., 2018, LUBRIDATE MAKE DEALI
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Tadross M, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL024460
   Tankson JD, 2001, POULTRY SCI, V80, P1384, DOI 10.1093/ps/80.9.1384
   Thornton PK, 2009, AGR SYST, V101, P113, DOI 10.1016/j.agsy.2009.05.002
   Thornton PK, 2014, GLOBAL CHANGE BIOL, V20, P3313, DOI 10.1111/gcb.12581
   Tshiala M.F., 2011, Journal of Geography and Geology, V3, P13, DOI [DOI 10.5539/JGG.V3N1P13, https://doi.org/10.5539/jgg.v3n1p13]
   van Aardt I., 2013, Journal of Geography and Geology, V5, P131
   van der Velde M, 2012, CLIMATIC CHANGE, V113, P751, DOI 10.1007/s10584-011-0368-2
   van Garderen ERMA, 2011, WEATHER CLIM SOC, V3, P249, DOI 10.1175/WCAS-D-11-00026.1
   van Wilgen NJ, 2016, INT J CLIMATOL, V36, P706, DOI 10.1002/joc.4377
   Vincent LA, 2012, J GEOPHYS RES-ATMOS, V117, DOI 10.1029/2012JD017859
   Wang XLL, 2014, ATMOS OCEAN, V52, P222, DOI 10.1080/07055900.2013.818526
   Wickham H, 2011, WIRES COMPUT STAT, V3, P180, DOI 10.1002/wics.147
   Zhang X., 2018, Introduction to RClimdex V1.9
   Ziervogel G, 2014, WIRES CLIM CHANGE, V5, P605, DOI 10.1002/wcc.295
NR 48
TC 2
Z9 2
U1 1
U2 4
PU ACAD SCIENCE SOUTH AFRICA A S S AF
PI LYNWOOD RIDGE
PA PO BOX 72135, LYNWOOD RIDGE 0040, SOUTH AFRICA
SN 0038-2353
EI 1996-7489
J9 S AFR J SCI
JI S. Afr. J. Sci.
PD NOV-DEC
PY 2021
VL 117
IS 11-12
AR 7852
DI 10.17159/sajs.2021/7852
PG 11
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA YB4TY
UT WOS:000739008100017
OA Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Klemm, T
   Briske, DD
AF Klemm, T.
   Briske, D. D.
TI Retrospective Assessment of Beef Cow Numbers to Climate Variability
   Throughout the US Great Plains
SO RANGELAND ECOLOGY & MANAGEMENT
LA English
DT Article
DE beef cattle climate adaptation; beef cattle production; beef production
   vulnerability; grass-fed beef; rangeland beef production
ID LIVESTOCK; ADAPTATION; NORTHERN; IMPACTS; VULNERABILITY; GRASSLANDS;
   STRATEGIES; CATTLE; RANCH
AB The Great Plains provide amajor portion of US beef cattle production, and beef cattle represent the largest sector of the regional agricultural economy. Cattle producers regularly contend with climate variability, but the consequences of this variability are less well understood than for cropping systems. A retrospective analysis of US Department of Agriculture AgCensus data was conducted to assess the extent to which climate variability (1978-2017) has affected the spatial and temporal distribution of beef cow numbers throughout the Great Plains. Cow numbers were remarkably stable, declining only 3.1% between 1978 and 2017. However, beef production increased 30% during this period, in response to a steady increase in live animal slaughter weight. Cownumbers decreased during droughts in the late 1980s and the early 2010s but recovered before the subsequent 5-yr census. Cow numbers decreased 5.1%, 8.8%, and 4.0% in the Northern, Central, and Southern Plains, respectively, between the 1982 and 1987 censuses, even though annual precipitation only decreased in the Northern Plains. The reduction in cow numbers during the 2010s drought, which is assumed to portend future extreme droughts, was greatest in the Southern Plains (- 17.6%) followed by the Central (- 11%) and Northern Plains (- 4.9%), compared with the 2007 census. The relative increase in beef cow numbers in the Northern Plains may represent an emerging signal of climate variability on rangeland beef production. This may be a consequence of weaker correlations between cow numbers and mean annual precipitation and temperature established by lower mean annual temperatures in the Northern Plains. This retrospective analysis indicates that continued climatewarming and drying will adversely affect rangeland beef production, it identifies a large knowledge gap between climate variability and sustainable rangeland beef production, and it provides a reference to begin assessing the vulnerability of rangeland beef cattle production in future climates. (C) 2019 The Society for Range Management. Published by Elsevier Inc. All rights reserved.
C1 [Klemm, T.; Briske, D. D.] Texas A&M Univ, Dept Ecosyst Sci & Management, 2138 TAMU, College Stn, TX 77843 USA.
C3 Texas A&M University System; Texas A&M University College Station
RP Briske, DD (corresponding author), Texas A&M Univ, Dept Ecosyst Sci & Management, 2138 TAMU, College Stn, TX 77843 USA.
EM dbriske@tamu.edu
RI Klemm, Toni/GVS-2040-2022
FU USDA-NIFA [2016-67003-24970]
FX This work was supported by USDA-NIFA grant 2016-67003-24970 to DDB.
CR Amundson JL, 2006, J ANIM SCI, V84, P3415, DOI 10.2527/jas.2005-611
   [Anonymous], 2011, GUID CLIM PRACT NO 1
   [Anonymous], 2018, Quick Stats
   Augustine DJ, 2018, ECOL APPL, V28, P721, DOI 10.1002/eap.1680
   Bastian C.T., 2006, W EC FORUM, V5, P8
   BLACKSHAW JK, 1994, AUST J EXP AGR, V34, P285, DOI 10.1071/EA9940285
   Briske DD, 2015, FRONT ECOL ENVIRON, V13, P249, DOI 10.1890/140266
   Campbell A, 2019, CLIMATIC CHANGE, V152, P35, DOI 10.1007/s10584-018-2344-6
   Challinor AJ, 2014, NAT CLIM CHANGE, V4, P287, DOI [10.1038/nclimate2153, 10.1038/NCLIMATE2153]
   Chen M, 2017, ECOSPHERE, V8, DOI 10.1002/ecs2.2069
   Conant R.T., 2018, IMPACTS RISKS AND AD, P941, DOI DOI 10.7930/NCA4.2018.CH22
   Cook BI, 2015, SCI ADV, V1, DOI 10.1126/sciadv.1400082
   Coppock DL, 2011, RANGELAND ECOL MANAG, V64, P607, DOI 10.2111/REM-D-10-00113.1
   Davis MS, 2003, J ANIM SCI, V81, P649
   Derner J, 2018, CLIMATIC CHANGE, V146, P19, DOI 10.1007/s10584-017-2029-6
   Drummond MA, 2012, LAND USE POLICY, V29, P710, DOI 10.1016/j.landusepol.2011.11.007
   Irisarri JG, 2019, LIVEST SCI, V220, P93, DOI 10.1016/j.livsci.2018.12.009
   Griffith G.R., 2002, AGRIBUSINESS REV, V10
   Hamilton TW, 2016, RANGELAND ECOL MANAG, V69, P465, DOI 10.1016/j.rama.2016.06.008
   Hansen J, 2010, REV GEOPHYS, V48, DOI 10.1029/2010RG000345
   Hatfield JL, 2020, CLIMATIC CHANGE, V163, P1719, DOI 10.1007/s10584-018-2222-2
   Hoerling M, 2014, B AM METEOROL SOC, V95, P269, DOI 10.1175/BAMS-D-13-00055.1
   Hu ZZ, 2009, J CLIMATE, V22, P6047, DOI 10.1175/2009JCLI2798.1
   Joyce LA, 2013, RANGELAND ECOL MANAG, V66, P512, DOI 10.2111/REM-D-12-00142.1
   Kachergis E, 2014, ECOSPHERE, V5, DOI 10.1890/ES13-00402.1
   Kloesel K., 2018, IMPACTS RISKS ADAPTA, VII, P987, DOI [DOI 10.7930/NCA4.2018.CH23, DOI 10.7930/NCA4.2018]
   MacNeil M.D., 2012, AGR SCI, V3, P7
   Marshall NA, 2018, SUSTAIN SCI, V13, P393, DOI 10.1007/s11625-017-0435-3
   Moran MS, 2014, ECOLOGY, V95, P2121, DOI 10.1890/13-1687.1
   Nardone A, 2010, LIVEST SCI, V130, P57, DOI 10.1016/j.livsci.2010.02.011
   NOAA ESRL Physical Sciences Division, 2019, MULT ENSO IND VERS 2
   NOAA NCEI, 2019, CLIM GLANC
   NRDC, 2013, REC BREAK 17 3 BILL
   Petrie MD, 2018, GLOBAL CHANGE BIOL, V24, P1935, DOI 10.1111/gcb.14024
   Polley HW, 2013, RANGELAND ECOL MANAG, V66, P493, DOI 10.2111/REM-D-12-00068.1
   Reeves JL, 2013, LIVEST SCI, V155, P355, DOI 10.1016/j.livsci.2013.04.015
   Reeves JL, 2013, RANGELAND ECOL MANAG, V66, P438, DOI 10.2111/REM-D-12-00157.1
   Ritten JP, 2010, AM J AGR ECON, V92, P1242, DOI 10.1093/ajae/aaq052
   Roche LM, 2015, RANGELAND ECOL MANAG, V68, P248, DOI 10.1016/j.rama.2015.03.011
   SALA OE, 1988, ECOLOGY, V69, P40, DOI 10.2307/1943158
   Seager R, 2018, EARTH INTERACT, V22, P1, DOI 10.1175/EI-D-17-0011.1
   Shrum TR, 2018, CLIM RISK MANAG, V20, P11, DOI 10.1016/j.crm.2018.01.002
   Steiner JL, 2018, CLIMATIC CHANGE, V146, P201, DOI 10.1007/s10584-017-1965-5
   Thamo T, 2017, AGR SYST, V150, P99, DOI 10.1016/j.agsy.2016.10.013
   Tollerud H, 2018, EARTH INTERACT, V22, P1, DOI 10.1175/EI-D-17-0025.1
   Torell LA, 2010, RANGELAND ECOL MANAG, V63, P415, DOI 10.2111/REM-D-09-00131.1
   USDA ERS, 2019, ANN CASH REC SEL COM
   USDA ERS, 2019, FARM SECT EXP DROUGH
   USDA NASS, 2016, OV US CATTL IND
   USDANASS, LIV POULTR LIV DRESS
   Vermeire LT, 2009, RANGELAND ECOL MANAG, V62, P230, DOI 10.2111/07-140R2.1
   Vose R. S., 2017, Climate Science Special Report: Fourth National Climate Assessment, VI, P185, DOI DOI 10.7930/J0N29V45
   Wehner M.F., 2017, CLIMATE SCI SPECIAL, VI., P231, DOI [DOI 10.7930/J0CJ8BNN, 10.7930/JOCJ8BNN, DOI 10.7930/JOCJ8BNN]
   Wilmer H, 2018, RANGELAND ECOL MANAG, V71, P626, DOI 10.1016/j.rama.2017.08.001
NR 54
TC 7
Z9 9
U1 0
U2 1
PU SOC RANGE MANAGEMENT
PI LAKEWOOD
PA 445 UNION BLVD, STE 230, LAKEWOOD, CO 80228-1259 USA
SN 1550-7424
EI 1551-5028
J9 RANGELAND ECOL MANAG
JI Rangel. Ecol. Manag.
PD SEP
PY 2021
VL 78
BP 273
EP 280
DI 10.1016/j.rama.2019.07.004
PG 8
WC Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA YU9RZ
UT WOS:000752373800028
OA Bronze
DA 2025-01-10
ER

PT J
AU Sun, Y
   Brönnimann, O
   Roderick, GK
   Poltavsky, A
   Lommen, STE
   Müller-Schärer, H
AF Sun, Yan
   Broennimann, Olivier
   Roderick, George K.
   Poltavsky, Alexander
   Lommen, Suzanne T. E.
   Mueller-Schaerer, Heinz
TI Climatic suitability ranking of biological control candidates: a
   biogeographic approach for ragweed management in Europe
SO ECOSPHERE
LA English
DT Article
DE Ambrosia artemisiifolia; biological invasions; climate change; niche
   overlap; species distribution model
ID OPHRAELLA-COMMUNA; AMBROSIA-ARTEMISIIFOLIA; PERFORMANCE; EVOLUTION;
   INVASIONS; MODELS
AB Biological control using natural antagonists has been a most successful management tool against alien invasive plants that threaten biodiversity. The selection of candidate agents remains a critical step in a biocontrol program before more elaborate and time-consuming experiments are conducted. Here, we propose a biogeographic approach to identify candidates and combinations of candidates to potentially cover a large range of the invader. We studied Ambrosia artemisiifolia (common ragweed), native to North America (NA) and invasive worldwide, and six NA biocontrol candidates for the introduced Europe (EU) range of ragweed, both under current and future bioclimatic conditions. For the first time, we constructed species distribution models based on worldwide occurrences and important bioclimatic variables simultaneously for a plant invader and its biocontrol candidates in view of selecting candidates that potentially cover a large range of the target invader. Ordination techniques were used to explore climatic constraints of each species and to perform niche overlap tests with ragweed. We show a large overlap in climatic space between candidates and ragweed, but a considerable discrepancy in geographic range overlap between EU (31.4%) and NA (83.3%). This might be due to niche unfilling and expansion of ragweed in EU and the fact that habitats with high ragweed occurrences in EU are rare in NA and predicted to be unsuitable for the candidates. Total geographic range of all candidates combined is expected to decrease under climate change in both ranges, but they will respond differently. The relative geographic coverage of a plant invader by biocontrol candidates at home is largely transferable to the introduced range, even when the invader shifts its niche. Our analyses also identified which combination of candidates is expected to cover the most area and for which abiotic conditions to select in order to develop climatically adapted strains for particular regions, where ragweed is currently unlikely to be controlled.
C1 [Sun, Yan; Roderick, George K.] Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA.
   [Broennimann, Olivier] Univ Lausanne, Dept Ecol & Evolut, CH-1015 Lausanne, Switzerland.
   [Poltavsky, Alexander] Southern Fed Univ, Bot Garden, Rostov Na Donu 344041, Russia.
   [Lommen, Suzanne T. E.; Mueller-Schaerer, Heinz] Univ Fribourg, Dept Biol Ecol & Evolut, CH-1700 Fribourg, Switzerland.
   [Sun, Yan] Univ Tubingen, Plant Evolutionary Ecol, Morgenstelle 5, D-72076 Tubingen, Germany.
C3 University of California System; University of California Berkeley;
   University of Lausanne; Southern Federal University; University of
   Fribourg; Eberhard Karls University of Tubingen
RP Sun, Y (corresponding author), Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA.; Sun, Y (corresponding author), Univ Tubingen, Plant Evolutionary Ecol, Morgenstelle 5, D-72076 Tubingen, Germany.
EM yansun.ecology@gmail.com
RI Mueller-Schaerer, Heinz/H-5277-2011; Sun, Yan/AFU-8985-2022;
   Broennimann, Olivier/D-3495-2011
OI Roderick, George/0000-0001-7557-2415; Bronnimann,
   Olivier/0000-0001-5394-4564
FU Early.Postdoc.Mobility fellowship from the Swiss National Science
   Foundation (SNSF) [P2FRP3_148577]; University of Fribourg, Switzerland;
   EU COST Action FA1203 "Sustainable management of A. artemisiifolia in
   Europe" (SMARTER); Swiss State Secretariat for Education, Research, and
   Innovation (SERI) [13.0146]; UC Berkeley's Geospatial Innovation
   Facility (GIF); Swiss National Science Foundation (SNF) [P2FRP3_148577]
   Funding Source: Swiss National Science Foundation (SNF)
FX Y.S. was supported by an Early.Postdoc.Mobility fellowship from the
   Swiss National Science Foundation (SNSF; Project No. P2FRP3_148577),
   with additional support from the University of California, Berkeley, and
   the University of Fribourg, Switzerland. H.M.S. acknowledges financial
   support from the EU COST Action FA1203 "Sustainable management of A.
   artemisiifolia in Europe" (SMARTER) and the Swiss State Secretariat for
   Education, Research, and Innovation (SERI, Grant Number 13.0146). This
   research benefited from the support and services of UC Berkeley's
   Geospatial Innovation Facility (GIF, gif.berkeley.edu). We thank G.
   Rapacciuolo, J. Weaver, and E. Farrer for their comments on species
   distribution models, and B. Petitpierre for his help on Exdet_function
   in R. We gratefully acknowledge the help from M.A. Fleming and A.C.
   Sanders for occurrences collection from publications. We are grateful to
   R.L. Brown (Mississippi Entomological Museum, USA), C.C. Grinter
   (Entomology Collections Manager, Illinois Natural History Survey, USA),
   M. E. Epstein (California Department of Food & Agriculture, USA), D.J.
   Futuyma and J.E. Hayden, L.A. Sommar (Florida Department of Agriculture
   and Consumer Services, Division of Plant Industry, FDACS-DPI, USA), A.Y.
   Kawahara (McGuire Center for Lepidoptera and Biodiversity, Florida
   Museum of Natural History, USA), O.V. Kovalev (Zoological Institute
   Russian Academy of Sciences, Russia), P.T. Oboyski (Essig Museum of
   Entomology, University of California, Berkeley, USA), F. Sperling and
   Mr. Danny Shpeley (Strickland Museum, University of Alberta, Canada),
   and D.V. Stojanovic (Institute of Lowland Forestry and Environment
   Protection, Serbia) for providing species occurrences or assistance
   using their databases. We also thank U. Schaffner for commenting on an
   earlier draft of this manuscript.
CR Alexander JM, 2013, P ROY SOC B-BIOL SCI, V280, DOI 10.1098/rspb.2013.1446
   [Anonymous], 2013, R PACKAGE
   [Anonymous], PACKAGE ECOSPAT SPAT
   [Anonymous], 2014, BIOL CONTROL WEEDS W
   [Anonymous], 1956, Massachusetts Institute of Technology Defense Doc. Center No. 110268
   [Anonymous], 2015, CLIMATE CHANGE INSEC
   [Anonymous], 2014, Climate Change 2013: The Physical Science Basis. Working Group I contribution to the fifth assessment report of the Intergovernmental Panel on Climate Change
   Araújo MB, 2007, TRENDS ECOL EVOL, V22, P42, DOI 10.1016/j.tree.2006.09.010
   Auguie B., 2017, Miscellaneous Functions for "Grid"Graphics
   Broennimann O, 2007, ECOL LETT, V10, P701, DOI 10.1111/j.1461-0248.2007.01060.x
   Broennimann O, 2008, BIOL LETTERS, V4, P585, DOI 10.1098/rsbl.2008.0254
   Broennimann O, 2012, GLOBAL ECOL BIOGEOGR, V21, P481, DOI 10.1111/j.1466-8238.2011.00698.x
   Burbach GJ, 2009, ALLERGY, V64, P664, DOI 10.1111/j.1398-9995.2009.01975.x
   Chapman DS, 2014, GLOBAL CHANGE BIOL, V20, P192, DOI 10.1111/gcb.12380
   Coetzee JA, 2007, ENTOMOL EXP APPL, V125, P237, DOI 10.1111/j.1570-7458.2007.00622.x
   Cunze S., 2013, Int Sch Res, P1, DOI [DOI 10.1155/2013/610126, 10.1155/2013/610126]
   Davidson AM, 2011, ECOL LETT, V14, P419, DOI 10.1111/j.1461-0248.2011.01596.x
   Elith J, 2005, ECOL MODEL, V186, P280, DOI 10.1016/j.ecolmodel.2004.12.007
   Elith J, 2006, ECOGRAPHY, V29, P129, DOI 10.1111/j.2006.0906-7590.04596.x
   Essl F, 2015, J ECOL, V103, P1069, DOI 10.1111/1365-2745.12424
   Gerber E, 2011, WEED RES, V51, P559, DOI 10.1111/j.1365-3180.2011.00879.x
   Gillson L, 2013, TRENDS ECOL EVOL, V28, P135, DOI 10.1016/j.tree.2012.10.008
   Giorgetta MA, 2013, J ADV MODEL EARTH SY, V5, P572, DOI 10.1002/jame.20038
   Graham CH, 2004, TRENDS ECOL EVOL, V19, P497, DOI 10.1016/j.tree.2004.07.006
   Guisan A, 2000, ECOL MODEL, V135, P147, DOI 10.1016/S0304-3800(00)00354-9
   Gurevitch J, 2011, ECOL LETT, V14, P407, DOI 10.1111/j.1461-0248.2011.01594.x
   Hamaoui-Laguel L, 2015, NAT CLIM CHANGE, V5, P766, DOI [10.1038/nclimate2652, 10.1038/NCLIMATE2652]
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Hoelmer KA, 2005, BIOL CONTROL, V34, P255, DOI 10.1016/j.biocontrol.2005.05.001
   Kettenring KM, 2011, J APPL ECOL, V48, P970, DOI 10.1111/j.1365-2664.2011.01979.x
   Kettunen M., 2009, Technical support to EU strategy on invasive species (IAS)-Assessment of the impacts of IAS in Europe and the EU, Final report for the European Commission
   Kovalev O. V., 1970, Entomologicheskoe Obozrenie, V49, P23
   Müller-Schärer H, 2008, BIOL INVASIONS, V10, P859, DOI 10.1007/s10530-008-9238-x
   Mukherjee A, 2011, BIOL CONTROL, V56, P254, DOI 10.1016/j.biocontrol.2010.11.006
   Palmer WA, 2010, BIOL CONTROL, V52, P271, DOI 10.1016/j.biocontrol.2009.07.011
   Pearce J, 2000, ECOL MODEL, V133, P225, DOI 10.1016/S0304-3800(00)00322-7
   Peterson AT, 2003, Q REV BIOL, V78, P419, DOI 10.1086/378926
   Petitpierre B, 2012, SCIENCE, V335, P1344, DOI 10.1126/science.1215933
   PRUESS KP, 1983, ENVIRON ENTOMOL, V12, P613, DOI 10.1093/ee/12.3.613
   Roderick GK, 2012, EVOL APPL, V5, P419, DOI 10.1111/j.1752-4571.2012.00281.x
   Savicky P., 2014, pspearman: Spearman's rank correlation test
   Seastedt TR, 2015, NEW PHYTOL, V205, P490, DOI 10.1111/nph.13065
   Szucs M, 2012, EVOL APPL, V5, P858, DOI 10.1111/j.1752-4571.2012.00264.x
   Tanaka K, 2015, ENTOMOL SCI, V18, P104, DOI 10.1111/ens.12087
   Tanaka K, 2009, ENVIRON ENTOMOL, V38, P266, DOI 10.1603/022.038.0133
   Theoharides KA, 2007, NEW PHYTOL, V176, P256, DOI 10.1111/j.1469-8137.2007.02207.x
   Van Kleunen M, 2008, AM NAT, V171, P195, DOI 10.1086/525057
   Walther GR, 2009, TRENDS ECOL EVOL, V24, P686, DOI 10.1016/j.tree.2009.06.008
   Wisz MS, 2008, DIVERS DISTRIB, V14, P763, DOI 10.1111/j.1472-4642.2008.00482.x
   Zhou ZS, 2014, BIOCONTROL SCI TECHN, V24, P950, DOI 10.1080/09583157.2014.897305
   Zhou ZS, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0074760
NR 51
TC 54
Z9 59
U1 0
U2 21
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 e01731
DI 10.1002/ecs2.1731
PG 17
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA EU4FN
UT WOS:000400985300006
OA gold, Green Published, Green Submitted
DA 2025-01-10
ER

PT J
AU Brooks, N
   Adger, WN
   Kelly, PM
AF Brooks, N
   Adger, WN
   Kelly, PM
TI The determinants of vulnerability and adaptive capacity at the national
   level and the implications for adaptation
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article
DE vulnerability; adaptive capacity; indicators; national-level; risk;
   mortality; Delphi survey; governance; literacy; health
ID CLIMATE-CHANGE; EXTREMES; GLOBALIZATION; INDEX
AB We present a set of indicators of vulnerability and capacity to adapt to climate variability, and by extension climate change, derived using a novel empirical analysis of data aggregated at the national level on a decadal timescale. The analysis is based on a conceptual framework in which risk is viewed in terms of outcome, and is a function of physically defined climate hazards and socially constructed vulnerability. Climate outcomes are represented by mortality from climate-related disasters, using the emergency events database data set, statistical relationships between mortality and a shortlist of potential proxies for vulnerability are used to identify key vulnerability indicators. We find that 11 key indicators exhibit a strong relationship with decadally aggregated mortality associated with climate-related disasters. Validation of indicators, relationships between vulnerability and adaptive capacity, and the sensitivity of subsequent vulnerability assessments to different sets of weightings are explored using expert judgement data, collected through a focus group exercise. The data are used to provide a robust assessment of vulnerability to climate-related mortality at the national level, and represent an entry point to more detailed explorations of vulnerability and adaptive capacity. They indicate that the most vulnerable nations are those situated in sub-Saharan Africa and those that have recently experienced conflict. Adaptive capacity-one element of vulnerability-is associated predominantly with governance, civil and political rights, and literacy. (C) 2005 Elsevier Ltd. All rights reserved.
C1 Univ E Anglia, Tyndall Ctr Climate Change Res, Norwich NR4 7TJ, Norfolk, England.
   Univ E Anglia, CSERGE, Norwich NR4 7TJ, Norfolk, England.
   Univ E Anglia, Climat Res Unit, Norwich NR4 7TJ, Norfolk, England.
C3 University of East Anglia; University of East Anglia; University of East
   Anglia
RP Univ E Anglia, Tyndall Ctr Climate Change Res, Norwich NR4 7TJ, Norfolk, England.
EM nick.brooks@uea.ac.uk
RI ; Adger, William Neil/F-7676-2010
OI Brooks, Nick/0000-0002-5073-9386; Adger, William
   Neil/0000-0003-4244-2854
CR Adger W. N., 1999, Mitig Adapt Strateg Glob Change, V4, P253, DOI [10.1023/A:1009601904210, DOI 10.1023/A:1009601904210]
   Adger WN, 1999, WORLD DEV, V27, P249, DOI 10.1016/S0305-750X(98)00136-3
   [Anonymous], ENV HAZARDS
   [Anonymous], 2003, 38 U E ANGL TYND CTR
   [Anonymous], NAT AD PROGR ACT NAP
   [Anonymous], UNEP POLICY SERIES
   [Anonymous], ADAPTATION CLIMATE C
   BARNETT J, 2005, IN PRESS JUSTICE VUL
   Bell S., 1999, Sustainability Indicators: Measuring the Immeasurable
   Blaikie P., 2003, At risk - Natural hazards, people's vulnerability and disasters
   Brooks N., 2004, 61 U E ANGL TYND CTR
   BROOKS N, 2003, UNPUB AMBIO
   CONWAY D, 2005, GLOBAL ENV CHANGE, V15
   Easterling DR, 2000, SCIENCE, V289, P2068, DOI 10.1126/science.289.5487.2068
   Ebisuzaki W, 1997, J CLIMATE, V10, P2147, DOI 10.1175/1520-0442(1997)010<2147:AMTETS>2.0.CO;2
   Frich P, 2002, CLIMATE RES, V19, P193, DOI 10.3354/cr019193
   Haan N., 2001, CHRONIC VULNERABILIT
   HADDAD B, 2005, GLOBAL ENV CHANGE, V15
   Jones R., 2003, ASSESSING CURRENT CL
   Kaufmann D., 1999, World Bank Working Paper 2195
   Kaufmann Daniel., 1999, Aggregating Governance Indicators, V2195
   Kelly PM, 2000, CLIMATIC CHANGE, V47, P325, DOI 10.1023/A:1005627828199
   Knack S, 1997, Q J ECON, V112, P1251, DOI 10.1162/003355300555475
   KRUGMAN P, 1995, Q J ECON, V110, P857, DOI 10.2307/2946642
   Lawn PA, 2003, ECOL ECON, V44, P105, DOI 10.1016/S0921-8009(02)00258-6
   Leichenko R. M., 2002, Mitigation and Adaptation Strategies for Global Change, V7, P1, DOI 10.1023/A:1015860421954
   McCarthy J.J., 2001, CLIMATE CHANGE IMPAC
   Morgan DL, 1996, ANNU REV SOCIOL, V22, P129, DOI 10.1146/annurev.soc.22.1.129
   Moss R.H., 1999, VULNERABILITY CLIMAT
   Neumayer E, 2001, ECOL ECON, V39, P101, DOI 10.1016/S0921-8009(01)00201-4
   NORDHAUS WD, 1994, AM SCI, V82, P45
   O'Brien K, 2004, GLOBAL ENVIRON CHANG, V14, P303, DOI 10.1016/j.gloenvcha.2004.01.001
   O'Brien KL, 2003, ANN ASSOC AM GEOGR, V93, P89, DOI 10.1111/1467-8306.93107
   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]
   Stenchion P., 1997, AUST J EMERG MANAG, V12, P40, DOI [10.3316/ielapa.397086657696665adresindenalindi, DOI 10.3316/IELAPA.397086657696665ADRESINDENALINDI]
   Stewart F, 2002, BRIT MED J, V324, P342, DOI 10.1136/bmj.324.7333.342
   UNDHA, 1992, INT AGR GLOSS BAS TE
   Vaughan DG, 2002, CLIMATIC CHANGE, V52, P65, DOI 10.1023/A:1013038920600
   Yohe G, 2002, GLOBAL ENVIRON CHANG, V12, P25, DOI 10.1016/S0959-3780(01)00026-7
NR 39
TC 1225
Z9 1437
U1 8
U2 360
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 2005
VL 15
IS 2
BP 151
EP 163
DI 10.1016/j.gloenvcha.2004.12.006
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 931VR
UT WOS:000229514100008
DA 2025-01-10
ER

PT J
AU Shi, TT
   Zhang, XX
   Hou, YK
   Jia, CF
   Dan, XM
   Zhang, YL
   Jiang, YZ
   Lai, Q
   Feng, JJ
   Feng, JJ
   Ma, T
   Wu, JL
   Liu, SY
   Zhang, L
   Long, ZQ
   Chen, LY
   Street, NR
   Ingvarsson, PK
   Liu, JQ
   Yin, TM
   Wang, J
AF Shi, Tingting
   Zhang, Xinxin
   Hou, Yukang
   Jia, Changfu
   Dan, Xuming
   Zhang, Yulin
   Jiang, Yuanzhong
   Lai, Qiang
   Feng, Jiajun
   Feng, Jianju
   Ma, Tao
   Wu, Jiali
   Liu, Shuyu
   Zhang, Lei
   Long, Zhiqin
   Chen, Liyang
   Street, Nathaniel R.
   Ingvarsson, Par K.
   Liu, Jianquan
   Yin, Tongming
   Wang, Jing
TI The super-pangenome of Populus unveils genomic facets for its adaptation
   and diversification in widespread forest trees
SO MOLECULAR PLANT
LA English
DT Article
DE Populus; pangenomes; whole-genome duplication; structural variation;
   genome evolution
ID BODY DNA METHYLATION; WHOLE-GENOME; TRANSPOSABLE ELEMENTS;
   GENE-EXPRESSION; EVOLUTION; ARABIDOPSIS; PLANT; ALIGNMENT; ANNOTATION;
   SELECTION
AB Understanding the underlying mechanisms and links between genome evolution and adaptive innovations stands as a key goal in evolutionary studies. Poplars, among the world's most widely distributed and cultivated trees, exhibit extensive phenotypic diversity and environmental adaptability. In this study, we present a genus-level super-pangenome comprising 19 Populus genomes, revealing the likely pivotal role of private genes in facilitating local environmental and climate adaptation. Through the integration of pangenomes with transcriptomes, methylomes, and chromatin accessibility mapping, we unveil that the evolutionary trajectories of pangenes and duplicated genes are closely linked to local genomic landscapes of regulatory and epigenetic architectures, notably CG methylation in gene-body regions. Further comparative genomic analyses have enabled the identification of 142 202 structural variants across species that intersect with a significant number of genes and contribute substantially to both phenotypic and adaptive divergence. We have experimentally validated a - 180-bp presence/absence variant affecting the expression of the CUC2 gene, crucial for leaf serration formation. Finally, we developed a user-friendly web-based tool encompassing the multi-omics resources associated with the Populus super-pangenome (http://www.populussuperpangenome.com). Together, the present pioneering super-pangenome resource in forest trees not only aids in the advancement of breeding efforts of this globally important tree genus but also offers valuable insights into potential avenues for comprehending tree biology.
C1 [Shi, Tingting; Zhang, Xinxin; Hou, Yukang; Jia, Changfu; Dan, Xuming; Zhang, Yulin; Jiang, Yuanzhong; Lai, Qiang; Feng, Jiajun; Ma, Tao; Wu, Jiali; Liu, Shuyu; Zhang, Lei; Long, Zhiqin; Chen, Liyang; Liu, Jianquan; Wang, Jing] Sichuan Univ, Coll Life Sci, Key Lab Bioresources & Ecoenvironm, Minist Educ, Chengdu, Sichuan, Peoples R China.
   [Feng, Jianju] Tarim Univ, Coll Hort & Forestry, Alar 843300, Peoples R China.
   [Street, Nathaniel R.] Umea Univ, Umea Plant Sci Ctr, Dept Plant Physiol, Umea, Vasterbotten, Sweden.
   [Ingvarsson, Par K.] Swedish Univ Agr Sci, Linnean Ctr Plant Biol, Dept Plant Biol, Uppsala Bioctr, Uppsala, Sweden.
   [Yin, Tongming] Nanjing Forestry Univ, Dept China, Key Lab Tree Genet & Biotechnol Jiangsu Prov & Edu, Nanjing, Jiangsu, Peoples R China.
C3 Sichuan University; Tarim University; Umea University; Swedish
   University of Agricultural Sciences; Nanjing Forestry University
RP Liu, JQ; Wang, J (corresponding author), Sichuan Univ, Coll Life Sci, Key Lab Bioresources & Ecoenvironm, Minist Educ, Chengdu, Sichuan, Peoples R China.; Yin, TM (corresponding author), Nanjing Forestry Univ, Dept China, Key Lab Tree Genet & Biotechnol Jiangsu Prov & Edu, Nanjing, Jiangsu, Peoples R China.
EM liujq@nwipb.cas.cn; tmyin@njfu.com.cn; wangjing2019@scu.edu.cn
RI Ingvarsson, Pär/G-2748-2010; long, zhiqin/HNS-7718-2023; LIU,
   JIANQUAN/B-1296-2011; Jia, Changfu/JUF-7075-2023; Street,
   Nathaniel/B-3920-2008
OI Ingvarsson, Par/0000-0001-9225-7521; Street,
   Nathaniel/0000-0001-6031-005X
FU National Key Research and Develop- ment Program of China
   [2022YFD2201200, 2021YFD2200202]; National Natural Science Foundation of
   China [32371695, 31971567]; Fundamental Research Funds for the Central
   Universities [2023SCUNL105, SCU2022D003]
FX <BOLD>Acknowledgements</BOLD> FUNDING We express our gratitude to
   Haoyang Cai and Jinjiang Liu (College of Life Sciences, Sichuan
   University) for their assistance with database construc- tion. This work
   was supported by the National Key Research and Develop- ment Program of
   China (2022YFD2201200 to J.W. and 2021YFD2200202 to T.Y. and J.L.) ,
   National Natural Science Foundation of China (32371695 and 31971567 to
   J.W.) , and Fundamental Research Funds for the Central Universities
   (2023SCUNL105 and SCU2022D003 to J.W.) .
CR Alexa A, 2006, BIOINFORMATICS, V22, P1600, DOI 10.1093/bioinformatics/btl140
   Alonge M, 2020, CELL, V182, P145, DOI 10.1016/j.cell.2020.05.021
   Armstrong J, 2020, NATURE, V587, P246, DOI 10.1038/s41586-020-2871-y
   Bastiaanse HL, 2021, PLANT CELL, V33, P940, DOI 10.1093/plcell/koaa016
   Belyeu JR, 2021, GENOME BIOL, V22, DOI 10.1186/s13059-021-02380-5
   Bennetzen JL, 2014, ANNU REV PLANT BIOL, V65, P505, DOI 10.1146/annurev-arplant-050213-035811
   Bewick AJ, 2017, CURR OPIN PLANT BIOL, V36, P103, DOI 10.1016/j.pbi.2016.12.007
   Bilsborough GD, 2011, P NATL ACAD SCI USA, V108, P3424, DOI 10.1073/pnas.1015162108
   Birney E, 2004, GENOME RES, V14, P988, DOI 10.1101/gr.1865504
   Bolger AM, 2014, BIOINFORMATICS, V30, P2114, DOI 10.1093/bioinformatics/btu170
   Borthakur D, 2022, FORESTRY RES, V2, DOI 10.48130/FR-2022-0011
   Bousios A, 2016, CURR OPIN PLANT BIOL, V30, P123, DOI 10.1016/j.pbi.2016.02.009
   Minh BQ, 2020, MOL BIOL EVOL, V37, P2727, DOI 10.1093/molbev/msaa106
   Burton JN, 2013, NAT BIOTECHNOL, V31, P1119, DOI 10.1038/nbt.2727
   Camacho C, 2009, BMC BIOINFORMATICS, V10, DOI 10.1186/1471-2105-10-421
   Capella-Gutiérrez S, 2009, BIOINFORMATICS, V25, P1972, DOI 10.1093/bioinformatics/btp348
   Chen JH, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-13128-y
   Chen J, 2017, MOL BIOL EVOL, V34, P1417, DOI 10.1093/molbev/msx088
   Chen LY, 2023, bioRxiv, DOI [10.1101/2023.07.11.548481, 10.1101/2023.07.11.548481, DOI 10.1101/2023.07.11.548481]
   Chen S, 2019, GENOME BIOL, V20, DOI 10.1186/s13059-019-1909-7
   Chen SF, 2018, BIOINFORMATICS, V34, P884, DOI 10.1093/bioinformatics/bty560
   Chen ZY, 2020, PLANT J, V103, P430, DOI 10.1111/tpj.14744
   Choi JY, 2018, MOL BIOL EVOL, V35, P365, DOI 10.1093/molbev/msx284
   Cochetel N, 2023, GENOME BIOL, V24, DOI 10.1186/s13059-023-03133-2
   Cuevas HE, 2016, MOL BIOL EVOL, V33, P2417, DOI 10.1093/molbev/msw120
   Dai XG, 2014, CELL RES, V24, P1274, DOI 10.1038/cr.2014.83
   Hoang DT, 2018, MOL BIOL EVOL, V35, P518, DOI 10.1093/molbev/msx281
   Diez CM, 2014, CURR OPIN PLANT BIOL, V18, P1, DOI 10.1016/j.pbi.2013.11.017
   Dyson CJ, 2020, MOL BIOL EVOL, V37, P2322, DOI 10.1093/molbev/msaa088
   Emms DM, 2019, GENOME BIOL, V20, DOI 10.1186/s13059-019-1832-y
   Evans LM, 2014, NAT GENET, V46, P1089, DOI 10.1038/ng.3075
   FAO, 2020, Global Forest Resources Assessment 2020: Main Report
   Goel M, 2019, GENOME BIOL, V20, DOI 10.1186/s13059-019-1911-0
   Haas BJ, 2003, NUCLEIC ACIDS RES, V31, P5654, DOI 10.1093/nar/gkg770
   Haas BJ, 2008, GENOME BIOL, V9, DOI 10.1186/gb-2008-9-1-r7
   Haas BJ, 2013, NAT PROTOC, V8, P1494, DOI 10.1038/nprot.2013.084
   Han MV, 2013, MOL BIOL EVOL, V30, P1987, DOI 10.1093/molbev/mst100
   Hellens RP, 2005, PLANT METHODS, V1, DOI 10.1186/1746-4811-1-13
   Heller D, 2019, BIOINFORMATICS, V35, P2907, DOI 10.1093/bioinformatics/btz041
   Hickey G, 2013, BIOINFORMATICS, V29, P1341, DOI 10.1093/bioinformatics/btt128
   Hu J, 2020, BIOINFORMATICS, V36, P2253, DOI 10.1093/bioinformatics/btz891
   Huang KM, 2021, EVOLUTION, V75, P706, DOI 10.1111/evo.14184
   Jansson S, 2007, ANNU REV PLANT BIOL, V58, P435, DOI 10.1146/annurev.arplant.58.032806.103956
   Jay P, 2021, NAT GENET, V53, P288, DOI 10.1038/s41588-020-00771-1
   Jeffares DC, 2017, NAT COMMUN, V8, DOI 10.1038/ncomms14061
   Jiang T, 2020, GENOME BIOL, V21, DOI 10.1186/s13059-020-02107-y
   Jiao W, 2020, NAT COMMUN, V11, DOI [10.1038/s41467-019-13825-8, 10.1038/s41467-020-14779-y]
   Jones P, 2014, BIOINFORMATICS, V30, P1236, DOI 10.1093/bioinformatics/btu031
   Kalyaanamoorthy S, 2017, NAT METHODS, V14, P587, DOI [10.1038/NMETH.4285, 10.1038/nmeth.4285]
   Kamiuchi Y, 2014, FRONT PLANT SCI, V5, DOI 10.3389/fpls.2014.00165
   Katoh K, 2013, MOL BIOL EVOL, V30, P772, DOI 10.1093/molbev/mst010
   Keller TE, 2014, P NATL ACAD SCI USA, V111, P5932, DOI 10.1073/pnas.1321420111
   Kim D, 2015, NAT METHODS, V12, P357, DOI [10.1038/NMETH.3317, 10.1038/nmeth.3317]
   Koch MA, 2000, MOL BIOL EVOL, V17, P1483, DOI 10.1093/oxfordjournals.molbev.a026248
   Kou YX, 2020, MOL BIOL EVOL, V37, P3507, DOI 10.1093/molbev/msaa185
   Krueger F, 2011, BIOINFORMATICS, V27, P1571, DOI 10.1093/bioinformatics/btr167
   Langmead B, 2012, NAT METHODS, V9, P357, DOI [10.1038/NMETH.1923, 10.1038/nmeth.1923]
   Lescot M, 2002, NUCLEIC ACIDS RES, V30, P325, DOI 10.1093/nar/30.1.325
   Li H., 2013, GENOMICS, DOI [10.48550/arXiv.1303.3997, DOI 10.48550/ARXIV.1303.3997]
   Li H, 2018, BIOINFORMATICS, V34, P3094, DOI 10.1093/bioinformatics/bty191
   Li H, 2011, NATURE, V475, P493, DOI 10.1038/nature10231
   Li H, 2009, BIOINFORMATICS, V25, P1754, DOI 10.1093/bioinformatics/btp324
   Li HB, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-28362-0
   Li R, 2023, GENOME RES, V33, P463, DOI 10.1101/gr.277372.122
   Li YL, 2023, MOL ECOL, V32, P1366, DOI 10.1111/mec.16566
   Liu SY, 2023, bioRxiv, DOI [10.1101/2023.07.11.548479, 10.1101/2023.07.11.548479, DOI 10.1101/2023.07.11.548479]
   Liu YJ, 2019, SCI CHINA LIFE SCI, V62, P609, DOI 10.1007/s11427-018-9455-2
   Liu YC, 2020, CELL, V182, P162, DOI 10.1016/j.cell.2020.05.023
   Long ZQ, 2024, bioRxiv, DOI [10.1101/2023.07.11.548483, 10.1101/2023.07.11.548483, DOI 10.1101/2023.07.11.548483]
   Ma T, 2013, NAT COMMUN, V4, DOI 10.1038/ncomms3797
   Marçais G, 2018, PLOS COMPUT BIOL, V14, DOI 10.1371/journal.pcbi.1005944
   Marcais G, 2011, BIOINFORMATICS, V27, P764, DOI 10.1093/bioinformatics/btr011
   Minh BQ, 2020, MOL BIOL EVOL, V37, P1530, DOI 10.1093/molbev/msaa015
   Muyle A, 2019, MOL BIOL EVOL, V36, P155, DOI 10.1093/molbev/msy204
   Muyle AM, 2022, GENOME BIOL EVOL, V14, DOI 10.1093/gbe/evac038
   Neale DB, 2011, NAT REV GENET, V12, P111, DOI 10.1038/nrg2931
   Nikovics K, 2006, PLANT CELL, V18, P2929, DOI 10.1105/tpc.106.045617
   Ou SJ, 2019, GENOME BIOL, V20, DOI 10.1186/s13059-019-1905-y
   Plomion C, 2016, ANN FOREST SCI, V73, P77, DOI 10.1007/s13595-015-0488-3
   Qiao X, 2019, GENOME BIOL, V20, DOI 10.1186/s13059-019-1650-2
   Qin P, 2021, CELL, V184, P3542, DOI 10.1016/j.cell.2021.04.046
   Quinlan AR, 2010, BIOINFORMATICS, V26, P841, DOI 10.1093/bioinformatics/btq033
   Ren R, 2018, MOL PLANT, V11, P414, DOI 10.1016/j.molp.2018.01.002
   Rhie A, 2020, GENOME BIOL, V21, DOI 10.1186/s13059-020-02134-9
   Ritter EJ, 2021, CURR OPIN PLANT BIOL, V61, DOI 10.1016/j.pbi.2020.101990
   Roach MJ, 2018, BMC BIOINFORMATICS, V19, DOI 10.1186/s12859-018-2485-7
   Robinson KM, 2024, bioRxiv, DOI [10.1101/805614, 10.1101/805614, DOI 10.1101/805614]
   Rodgers-Melnick E, 2012, GENOME RES, V22, P95, DOI 10.1101/gr.125146.111
   Sanderson MJ, 2003, BIOINFORMATICS, V19, P301, DOI 10.1093/bioinformatics/19.2.301
   Sang YP, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-34206-8
   Sedlazeck FJ, 2018, NAT METHODS, V15, P461, DOI 10.1038/s41592-018-0001-7
   Servant N, 2015, GENOME BIOL, V16, DOI 10.1186/s13059-015-0831-x
   Shumate A, 2021, BIOINFORMATICS, V37, P1639, DOI 10.1093/bioinformatics/btaa1016
   Simao FA, 2015, BIOINFORMATICS, V31, P3210, DOI 10.1093/bioinformatics/btv351
   Song LH, 2008, PLANT PHYSIOL, V148, P280, DOI 10.1104/pp.108.124875
   Springer NM, 2016, PLANT CELL, V28, P314, DOI 10.1105/tpc.15.00911
   Suyama M, 2006, NUCLEIC ACIDS RES, V34, pW609, DOI 10.1093/nar/gkl315
   Tang D, 2022, NATURE, V606, P535, DOI 10.1038/s41586-022-04822-x
   Tarailo-Graovac Maja, 2009, Curr Protoc Bioinformatics, VChapter 4, DOI 10.1002/0471250953.bi0410s25
   Thorvaldsdóttir H, 2013, BRIEF BIOINFORM, V14, P178, DOI 10.1093/bib/bbs017
   Trapnell C, 2012, NAT PROTOC, V7, P562, DOI 10.1038/nprot.2012.016
   Trapnell C, 2009, BIOINFORMATICS, V25, P1105, DOI 10.1093/bioinformatics/btp120
   Tuskan GA, 2006, SCIENCE, V313, P1596, DOI 10.1126/science.1128691
   Vaser R, 2017, GENOME RES, V27, P737, DOI 10.1101/gr.214270.116
   Walkowiak S, 2020, NATURE, V588, DOI 10.1038/s41586-020-2961-x
   Wang Dapeng, 2010, Genomics Proteomics & Bioinformatics, V8, P77, DOI 10.1016/S1672-0229(10)60008-3
   Wang HF, 2015, P NATL ACAD SCI USA, V112, P13729, DOI 10.1073/pnas.1519067112
   Wang J, 2018, GENOME BIOL, V19, DOI 10.1186/s13059-018-1444-y
   Wang J, 2016, GENETICS, V202, P1185, DOI 10.1534/genetics.115.183152
   Wang MC, 2020, NEW PHYTOL, V225, P1370, DOI 10.1111/nph.16215
   Wang N, 2022, NATL SCI REV, V9, DOI 10.1093/nsr/nwac114
   Wang XY, 2015, MOL PLANT, V8, P885, DOI 10.1016/j.molp.2015.04.004
   Wang XY, 2009, GENOME BIOL, V10, DOI 10.1186/gb-2009-10-6-r68
   Wang YP, 2013, NEW PHYTOL, V198, P274, DOI 10.1111/nph.12137
   Wang YP, 2012, NUCLEIC ACIDS RES, V40, DOI 10.1093/nar/gkr1293
   Wei SY, 2020, HORTIC RES-ENGLAND, V7, DOI 10.1038/s41438-020-0268-6
   Xin HY, 2020, PLANT J, V101, P253, DOI 10.1111/tpj.14536
   Yanai I, 2005, BIOINFORMATICS, V21, P650, DOI 10.1093/bioinformatics/bti042
   Yang WL, 2017, GIGASCIENCE, V6, DOI 10.1093/gigascience/gix075
   Yang ZH, 2007, MOL BIOL EVOL, V24, P1586, DOI 10.1093/molbev/msm088
   Yu GC, 2015, BIOINFORMATICS, V31, P2382, DOI 10.1093/bioinformatics/btv145
   Zhang C, 2020, MOL BIOL EVOL, V37, P3292, DOI 10.1093/molbev/msaa139
   Zhang C, 2018, BMC BIOINFORMATICS, V19, DOI 10.1186/s12859-018-2129-y
   Zhang L, 2021, HORTIC RES-ENGLAND, V8, DOI 10.1038/s41438-021-00494-2
   Zhang RG, 2022, HORTIC RES-ENGLAND, V9, DOI 10.1093/hr/uhac017
   Zhang Y, 2008, GENOME BIOL, V9, DOI 10.1186/gb-2008-9-9-r137
   Zhang ZY, 2020, MOL ECOL RESOUR, V20, DOI 10.1111/1755-0998.13142
   Zhou R, 2020, GENOME BIOL, V21, DOI 10.1186/s13059-020-1952-4
   Zhou YF, 2019, NAT PLANTS, V5, P965, DOI 10.1038/s41477-019-0507-8
   Zilberman D, 2007, NAT GENET, V39, P61, DOI 10.1038/ng1929
NR 130
TC 10
Z9 10
U1 41
U2 65
PU CELL PRESS
PI CAMBRIDGE
PA 50 HAMPSHIRE ST, FLOOR 5, CAMBRIDGE, MA 02139 USA
SN 1674-2052
EI 1752-9867
J9 MOL PLANT
JI Mol. Plant.
PD MAY 6
PY 2024
VL 17
IS 5
BP 725
EP 746
DI 10.1016/j.molp.2024.03.009
EA MAY 2024
PG 22
WC Biochemistry & Molecular Biology; Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Plant Sciences
GA TF1F4
UT WOS:001239748600001
PM 38486452
OA hybrid
HC Y
HP N
DA 2025-01-10
ER

PT J
AU Goulart, HMD
   Lazaro, IB
   van Garderen, L
   van der Wiel, K
   Le Bars, D
   Koks, E
   van den Hurk, B
AF Goulart, Henrique M. D.
   Lazaro, Irene Benito
   van Garderen, Linda
   van der Wiel, Karin
   Le Bars, Dewi
   Koks, Elco
   van den Hurk, Bart
TI Compound flood impacts from Hurricane Sandy on New York City in
   climate-driven storylines
SO NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
LA English
DT Article
ID INTERCOMPARISON PROJECT SCENARIOMIP; INTERNAL VARIABILITY; TROPICAL
   CYCLONES; WEATHER; RISK; RESILIENCE; STRATEGIES; RAINFALL; EVENTS
AB High impact events like Hurricane Sandy (2012) significantly affect society and decision-making around weather/climate adaptation. Our understanding of the potential effects of such events is limited to their rare historical occurrences. Climate change might alter these events to an extent that current adaptation responses become insufficient. Furthermore, internal climate variability in the current climate might also lead to slightly different events with possible larger societal impacts. Therefore, exploring high impact events under different conditions becomes important for (future) impact assessment. In this study, we create storylines of Sandy to assess compound coastal flooding on critical infrastructure in New York City under different scenarios, including climate change effects (on the storm and through sea level rise) and internal variability (variations in the storm's intensity and location). We find that 1 m of sea level rise increases average flood volumes by 4.2 times, while maximised precipitation scenarios (internal variability) lead to a 2.5-fold increase in flood volumes. The maximised precipitation scenarios impact inland critical infrastructure assets with low water levels, while sea level rise impacts fewer coastal assets though with high water levels. The diversity in hazards and impacts demonstrates the importance of building a set of relevant scenarios, including those representing the effects of climate change and internal variability. The integration of a modelling framework connecting meteorological conditions to local hazards and impacts provides relevant and accessible information that can directly be integrated into high impact event assessments.
C1 [Goulart, Henrique M. D.; van den Hurk, Bart] Deltares, Climate Adaptat & Disaster Risk Management, Delft, Netherlands.
   [Goulart, Henrique M. D.; Lazaro, Irene Benito; Koks, Elco; van den Hurk, Bart] Vrije Univ Amsterdam, Inst Environm Studies, Amsterdam, Netherlands.
   [van der Wiel, Karin; Le Bars, Dewi] Royal Netherlands Meteorol Inst KNMI, De Bilt, Netherlands.
   [van Garderen, Linda] Helmholtz Zentrum Hereon, Inst Coastal Res Anal & Modelling, Geesthacht, Germany.
C3 Deltares; Vrije Universiteit Amsterdam; Royal Netherlands Meteorological
   Institute; Helmholtz Association; Helmholtz-Zentrum Hereon
RP Goulart, HMD (corresponding author), Deltares, Climate Adaptat & Disaster Risk Management, Delft, Netherlands.; Goulart, HMD (corresponding author), Vrije Univ Amsterdam, Inst Environm Studies, Amsterdam, Netherlands.
EM henrique.goulart@deltares.nl
RI van der Wiel, Karin/AAJ-8827-2021; van den Hurk, Bart/ABI-1654-2020; Le
   Bars, Dewi/AAK-8631-2020; Koks, Elco/ABE-7946-2020
OI van Garderen, Linda/0000-0002-9171-8709; van den Hurk,
   Bart/0000-0003-3726-7086; Moreno Dumont Goulart,
   Henrique/0000-0002-9670-4250; van der Wiel, Karin/0000-0001-9365-5759;
   Benito Lazaro, Irene/0000-0002-1917-9173; Koks,
   Elco/0000-0002-4953-4527; Le Bars, Dewi/0000-0002-1175-4225
FU Horizon 2020 Framework Programme, H2020 Societal Challenges [820712]
FX This research has been supported by the Horizon 2020 Framework
   Programme, H2020 Societal Challenges (grant no. 820712).
CR Aerts JCJH, 2013, ANN NY ACAD SCI, V1294, P1, DOI 10.1111/nyas.12200
   Aerts JCJH, 2014, SCIENCE, V344, P472, DOI 10.1126/science.1248222
   Amante CJ, 2023, REMOTE SENS-BASEL, V15, DOI 10.3390/rs15061702
   [Anonymous], 2014, General Bathymetric Chart of the Oceans
   Baatsen M, 2015, CLIM DYNAM, V45, P949, DOI 10.1007/s00382-014-2329-8
   Bartholomeus R P., 2023, Cambridge Prisms: Water, V1, P1, DOI [10.1017/wat.2023.4, DOI 10.1017/WAT.2023.4, 10.1017/ wat.2023.4]
   Bevacqua E, 2020, COMMUN EARTH ENVIRON, V1, DOI 10.1038/s43247-020-00044-z
   Bloemendaal N, 2019, CLIM DYNAM, V52, P5031, DOI 10.1007/s00382-018-4430-x
   Bony S, 2015, NAT GEOSCI, V8, P261, DOI 10.1038/NGEO2398
   Buchhorn Marcel, 2020, Zenodo
   Chang SE, 2016, OXFORD RES ENCY NATU, DOI DOI 10.1093/ACREFORE/9780199389407.013.66
   Cooperative Institute for Research in Environmental Sciences (CIRES) at the University of Colorado Boulder, 2022, NCEI
   Deser C, 2012, NAT CLIM CHANGE, V2, P775, DOI 10.1038/NCLIMATE1562
   Done JM, 2018, CLIMATIC CHANGE, V146, P561, DOI 10.1007/s10584-015-1513-0
   Done JM, 2014, J GEOPHYS RES-ATMOS, V119, P6506, DOI 10.1002/2014JD021542
   Dullaart JCM, 2021, COMMUN EARTH ENVIRON, V2, DOI 10.1038/s43247-021-00204-9
   Eilander D., Journal of Open Source Software, V8, P4897, DOI [10.21105/joss.04897,2023a, DOI 10.21105/JOSS.04897,2023A]
   Eilander Dirk, 2023, Zenodo, DOI 10.5281/ZENODO.10143631
   Eilander D, 2023, NAT HAZARD EARTH SYS, V23, P2251, DOI 10.5194/nhess-23-2251-2023
   Feser F, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/1/014024
   Gelaro R, 2017, J CLIMATE, V30, P5419, DOI 10.1175/JCLI-D-16-0758.1
   Gerritsen H, 2005, PHILOS T R SOC A, V363, P1271, DOI 10.1098/rsta.2005.1568
   Goulart H. M. D., 2023, Zenodo [code], DOI [10.5281/zenodo.10209795, DOI 10.5281/ZENODO.10209795]
   Goulart HMD, 2023, EARTHS FUTURE, V11, DOI 10.1029/2022EF003106
   Goulart HMD, 2021, EARTH SYST DYNAM, V12, P1503, DOI 10.5194/esd-12-1503-2021
   Gutmann ED, 2018, J CLIMATE, V31, P3643, DOI 10.1175/JCLI-D-17-0391.1
   Haasnoot M., Environ. Res. Lett., V15, DOI [10.1088/1748-9326, DOI 10.1088/1748-9326]
   Haklay M, 2008, IEEE PERVAS COMPUT, V7, P12, DOI 10.1109/MPRV.2008.80
   Hall J.W., 2019, Adaptation of infrastructure systems: background paper for the global commission on adaptation
   Hall TM, 2013, GEOPHYS RES LETT, V40, P2312, DOI 10.1002/grl.50395
   Hallegatte S, 2013, NAT CLIM CHANGE, V3, P802, DOI [10.1038/nclimate1979, 10.1038/NCLIMATE1979]
   Hamed R, 2023, EARTH SYST DYNAM, V14, P255, DOI 10.5194/esd-14-255-2023
   Hawker Laurence, 2021, data.bris, DOI 10.5523/BRIS.25WFY0F9UKOGE2GS7A5MQPQ2J7
   Hawker L, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac4d4f
   Herfort B, 2023, NAT COMMUN, V14, DOI 10.1038/s41467-023-39698-6
   Hersbach H, 2020, Q J ROY METEOR SOC, V146, P1999, DOI 10.1002/qj.3803
   Hill KA, 2011, J CLIMATE, V24, P4644, DOI 10.1175/2011JCLI3761.1
   Hinkel J, 2014, P NATL ACAD SCI USA, V111, P3292, DOI 10.1073/pnas.1222469111
   Hodges K, 2017, J CLIMATE, V30, P5243, DOI [10.1175/JCLI-D-16-0557.1, 10.1175/jcli-d-16-0557.1]
   Jaafar HH, 2019, SCI DATA, V6, DOI 10.1038/s41597-019-0155-x
   Jongman B, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-04396-1
   Kalnay E, 1996, B AM METEOROL SOC, V77, P437, DOI 10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2
   Kazakov E., 2023, OSM Road Completeness
   Kernkamp HWJ, 2011, OCEAN DYNAM, V61, P1175, DOI 10.1007/s10236-011-0423-6
   Knapp KR, 2010, B AM METEOROL SOC, V91, P363, DOI 10.1175/2009BAMS2755.1
   Knutson T, 2020, B AM METEOROL SOC, V101, pE303, DOI 10.1175/BAMS-D-18-0194.1
   Koks EE, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-10442-3
   Koks EE, 2023, SUSTAIN RESIL INFRAS, V8, P237, DOI 10.1080/23789689.2022.2142741
   Kunz M., Nat. Hazards Earth Syst. Sci.
   Lackmann GM, 2015, B AM METEOROL SOC, V96, P547, DOI 10.1175/BAMS-D-14-00123.1
   Le Bars D, 2018, EARTHS FUTURE, V6, P1275, DOI 10.1029/2018EF000849
   Lehner F, 2023, ENVIRON RES-CLIM, V2, DOI 10.1088/2752-5295/accf30
   Leijnse T, 2021, COAST ENG, V163, DOI 10.1016/j.coastaleng.2020.103796
   Lin N, 2016, P NATL ACAD SCI USA, V113, P12071, DOI 10.1073/pnas.1604386113
   Liu K, 2023, NAT COMMUN, V14, DOI 10.1038/s41467-023-38203-3
   Liu MF, 2018, J CLIMATE, V31, P7269, DOI [10.1175/jcli-d-17-0747.1, 10.1175/JCLI-D-17-0747.1]
   Lockwood JW, 2022, EARTHS FUTURE, V10, DOI 10.1029/2021EF002462
   Martinez GS, 2019, ENVIRON RES, V176, DOI 10.1016/j.envres.2019.108548
   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]
   Mechler R, 2010, MITIG ADAPT STRAT GL, V15, P737, DOI 10.1007/s11027-010-9249-7
   Mei W, 2015, J CLIMATE, V28, P143, DOI 10.1175/JCLI-D-14-00164.1
   Meinshausen M, 2011, CLIMATIC CHANGE, V109, P213, DOI 10.1007/s10584-011-0156-z
   Muis S, 2020, FRONT MAR SCI, V7, DOI 10.3389/fmars.2020.00263
   Nicholls RJ, 2010, SCIENCE, V328, P1517, DOI 10.1126/science.1185782
   Nirandjan S, 2022, SCI DATA, V9, DOI 10.1038/s41597-022-01218-4
   O'Neill BC, 2016, GEOSCI MODEL DEV, V9, P3461, DOI 10.5194/gmd-9-3461-2016
   OCM Partners, 2017, NYC Topobathy Lidar DEM
   Otto FEL, 2018, CLIMATIC CHANGE, V149, P399, DOI 10.1007/s10584-018-2258-3
   Patricola CM, 2018, NATURE, V563, P339, DOI 10.1038/s41586-018-0673-2
   Prein AF, 2016, CLIM DYNAM, V46, P383, DOI 10.1007/s00382-015-2589-y
   Qiu JC, 2022, EARTHS FUTURE, V10, DOI 10.1029/2021EF002638
   Rosenzweig C, 2014, GLOBAL ENVIRON CHANG, V28, P395, DOI 10.1016/j.gloenvcha.2014.05.003
   Schubert-Frisius M, 2017, MON WEATHER REV, V145, P909, DOI 10.1175/MWR-D-16-0036.1
   Schwarzwalda K, 2022, P NATL ACAD SCI USA, V119, DOI 10.1073/pnas.2208095119
   Sebastian A, 2021, NAT HAZARDS, V109, P2343, DOI 10.1007/s11069-021-04922-3
   Shepherd TG, 2019, P ROY SOC A-MATH PHY, V475, DOI 10.1098/rspa.2019.0013
   Shepherd TG, 2018, CLIMATIC CHANGE, V151, P555, DOI 10.1007/s10584-018-2317-9
   Sillmann J, 2021, EARTHS FUTURE, V9, DOI 10.1029/2020EF001783
   Special Initiative for Rebuilding and Resiliency (SIRR), 2013, A Stronger, More Resilient New York, New York Special Initiative for Rebuilding and Resilience
   Stevens B, 2013, J ADV MODEL EARTH SY, V5, P146, DOI 10.1002/jame.20015
   Stott PA, 2016, WIRES CLIM CHANGE, V7, P23, DOI 10.1002/wcc.380
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Sutton RT, 2019, B AM METEOROL SOC, V100, P1637, DOI 10.1175/BAMS-D-18-0280.1
   Talia M, 2021, INT J PUBLIC THEOL, V15, P595, DOI 10.1163/15697320-01
   Tebaldi C, 2021, EARTH SYST DYNAM, V12, P253, DOI 10.5194/esd-12-253-2021
   Trenberth KE, 2018, EARTHS FUTURE, V6, P730, DOI 10.1029/2018EF000825
   van den Hurk BJJM, 2023, CLIM RISK MANAG, V40, DOI 10.1016/j.crm.2023.100500
   van den Hurk BJJM, 2023, ISCIENCE, V26, DOI 10.1016/j.isci.2023.106030
   van Garderen L, 2022, WEATHER, V77, P212, DOI 10.1002/wea.4185
   van Garderen L, 2021, NAT HAZARD EARTH SYS, V21, P171, DOI 10.5194/nhess-21-171-2021
   Van Ormondt Maarten, 2023, Zenodo, DOI 10.5281/ZENODO.10118583
   von Storch H, 2000, MON WEATHER REV, V128, P3664, DOI 10.1175/1520-0493(2000)128<3664:ASNTFD>2.0.CO;2
   Wahl T, 2015, NAT CLIM CHANGE, V5, P1093, DOI [10.1038/nclimate2736, 10.1038/NCLIMATE2736]
   Weisse R, 2003, COAST ENG, V48, P211, DOI 10.1016/S0378-3839(03)00027-9
   Woodruff JD, 2013, NATURE, V504, P44, DOI 10.1038/nature12855
   Yamada Y, 2019, GEOPHYS RES LETT, V46, P7592, DOI 10.1029/2019GL082086
   Yates D, 2014, IEEE POWER ENERGY M, V12, P66, DOI 10.1109/MPE.2014.2331901
   Zhou Q, 2022, INT J DIGIT EARTH, V15, P2400, DOI 10.1080/17538947.2022.2159550
   Zio E, 2016, RELIAB ENG SYST SAFE, V152, P137, DOI 10.1016/j.ress.2016.02.009
NR 99
TC 0
Z9 0
U1 4
U2 7
PU COPERNICUS GESELLSCHAFT MBH
PI GOTTINGEN
PA BAHNHOFSALLEE 1E, GOTTINGEN, 37081, GERMANY
SN 1561-8633
EI 1684-9981
J9 NAT HAZARD EARTH SYS
JI Nat. Hazards Earth Syst. Sci.
PD JAN 10
PY 2024
VL 24
IS 1
BP 29
EP 45
DI 10.5194/nhess-24-29-2024
PG 17
WC Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences;
   Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology; Meteorology & Atmospheric Sciences; Water Resources
GA IU5W6
UT WOS:001168874000001
OA gold
DA 2025-01-10
ER

PT J
AU Saravanakumar, V
   Das Lohano, H
   Balasubramanian, R
AF Saravanakumar, Venkatachalam
   Das Lohano, Heman
   Balasubramanian, Rudrasamy
TI A district-level analysis for measuring the effects of climate change on
   production of rice: evidence from Southern India
SO THEORETICAL AND APPLIED CLIMATOLOGY
LA English
DT Article
ID GRIDDED RAINFALL DATA; ADAPTATION STRATEGIES; DOWNSCALING APPROACH;
   GREENHOUSE GASES; MODEL OUTPUT; CROP YIELDS; TAMIL-NADU; DATA SET;
   IMPACT; VARIABILITY
AB Climate change may cause adverse impact on agricultural production that could jeopardize food availability and security. In this paper, we investigate how changes in mean values and variability of weather variables may affect rice yield using panel data for 30 districts of Tamil Nadu State from 1971 to 2018. We estimate a fixed-effects regression model with panel-corrected standard errors. Results show that rainfall and temperature have a statistically significant impact on rice yield. Furthermore, weather variability, measured as standard deviations of temperature and rainfall, has a negative effect on rice yields. We use the Coupled Model Inter-comparison Project-5 outputs and dynamically downscaled the weather outputs using the regional climate model. The results of the climate model showed that the rise in temperature and disruptions in rainfall patterns including both excessive and deficient rainfall events in Tamil Nadu will continue in the future under different climate scenarios. Projected changes in the weather variables are likely to decrease rice yield in Tamil Nadu from 0.7 to 6.3% under the low emission scenario and 4.1 to 20.1% in the high emission scenario during 2022-2050 (relative to 1971-2018). These projections have implications for the planning and targeting of climate adaptation technologies such as drought-tolerant and flood-tolerant varieties to lessen the adverse impact of weather variability due to climate change in the future.
C1 [Saravanakumar, Venkatachalam; Balasubramanian, Rudrasamy] Tamil Nadu Agr Univ, Dept Agr Econ, Coimbatore 641003, Tamil Nadu, India.
   [Das Lohano, Heman] Inst Business Adm IBA, Dept Econ, Main Campus,Univ Rd, Karachi 75270, Pakistan.
C3 Tamil Nadu Agricultural University; Institute of Business
   Administration, Karachi
RP Saravanakumar, V (corresponding author), Tamil Nadu Agr Univ, Dept Agr Econ, Coimbatore 641003, Tamil Nadu, India.
EM sharanu2k@gmail.com; hlohano@iba.edu.pk; rubalu@gmail.com
RI , Balasubramanian/AAP-5095-2020; Lohano, Heman Das/HGB-9502-2022
OI Venkatachalam, Saravanakumar/0000-0002-2971-3093
FU South Asian Network for Development and Environmental Economics
   (SANDEE), ICIMOD, Nepal
FX This work was financially supported by the South Asian Network for
   Development and Environmental Economics (SANDEE), ICIMOD, Nepal.
CR [Anonymous], CONTRIBUTION WORKING, DOI [DOI 10.1017/CBO9781107415324, 10.1017/CBO9781107415324]
   Ashrit RG., 2001, MAUSAM, V1, P229
   Attavanich W, 2011, AGR APPL EC ASS 2011
   Auffhammer M, 2006, P NATL ACAD SCI USA, V103, P19668, DOI 10.1073/pnas.0609584104
   Auffhammer M, 2013, REV ENV ECON POLICY, V7, P181, DOI 10.1093/reep/ret016
   Auffhammer M, 2012, CLIMATIC CHANGE, V111, P411, DOI 10.1007/s10584-011-0208-4
   Bal PK, 2016, ASIA-PAC J ATMOS SCI, V52, P353, DOI 10.1007/s13143-016-0004-1
   Barnwal P, 2013, ECOL ECON, V87, P95, DOI 10.1016/j.ecolecon.2012.11.024
   Barros VR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1133
   BECK N, 1995, AM POLIT SCI REV, V89, P634, DOI 10.2307/2082979
   Blackwell JL, 2005, STATA J, V5, P202, DOI 10.1177/1536867X0500500205
   Blanc E, 2017, REV ENV ECON POLICY, V11, P258, DOI 10.1093/reep/rex016
   Chen CC, 2005, AGR ECON-BLACKWELL, V33, P503, DOI 10.1111/j.1574-0864.2005.00097.x
   Chen CC, 2004, CLIMATIC CHANGE, V66, P239, DOI 10.1023/B:CLIM.0000043159.33816.e5
   Clarke L., 2007, SCENARIOS GREENHOUSE
   Cline WilliamR., 2007, Global Warming and Agriculture: Impact Estimates by Country
   Cuba P, 2017, J AGROMETEOROL, P32
   Dash SK, 2007, CURR SCI INDIA, V93, P782
   Silva WKD, 2019, CLIMATIC CHANGE, V154, P195, DOI 10.1007/s10584-019-02424-7
   Deschênes O, 2012, AM ECON REV, V102, P3761, DOI 10.1257/aer.102.7.3761
   Garcia-Carreras L, 2015, J APPL METEOROL CLIM, V54, P1283, DOI 10.1175/JAMC-D-14-0226.1
   Gedik MA, 2021, ACTA AGR SCAND B-S P, V71, P318, DOI 10.1080/09064710.2021.1897155
   Geethalakshmi V, 2011, CURR SCI INDIA, V101, P342
   Government of Tamil Nadu, SEAS CROP REP TAM NA
   Guang Jie, 2007, Hupo Kexue, V19, P241
   Gupta S, 2014, CLIM CHANG ECON, V5, DOI 10.1142/S2010007814500018
   Hoechle D, 2007, STATA J, V7, P281, DOI 10.1177/1536867X0700700301
   HOFSTRA N, 2008, J GEOPHYS RES, V113, P1, DOI DOI 10.1029/2008JD010100
   Im KS, 2003, J ECONOMETRICS, V115, P53, DOI 10.1016/S0304-4076(03)00092-7
   Isik M, 2006, APPL ECON, V38, P835, DOI 10.1080/00036840500193682
   Jones R.G., 2004, GENERATING HIGH RESO, P40
   Kmenta J., 1986, Elements of Econometrics, V2
   Kripalani RH, 2007, THEOR APPL CLIMATOL, V90, P133, DOI 10.1007/s00704-006-0282-0
   Kumar KSK, 2011, CAMB J REG ECON SOC, V4, P221, DOI 10.1093/cjres/rsr004
   Kumar P., 2014, ECON POLIT WEEKLY, V49, P54
   Kumar SN, 2011, CURR SCI INDIA, V101, P332
   Kurukulasuriya P, 2008, AFR J AGRIC RESOUR E, V2, P1
   Lakshmanan A, 2011, APPL ENG AGRIC, V27, P887
   Laprise R, 2008, J COMPUT PHYS, V227, P3641, DOI 10.1016/j.jcp.2006.10.024
   Lohano HD, 2018, CLIM DEV, V10, P625, DOI 10.1080/17565529.2017.1372263
   Maurer EP, 2008, HYDROL EARTH SYST SC, V12, P551
   McCarl BA, 2008, AM J AGR ECON, V90, P1241, DOI 10.1111/j.1467-8276.2008.01211.x
   Mendelsohn R, 1996, AGR FOREST METEOROL, V80, P55, DOI 10.1016/0168-1923(95)02316-X
   MENDELSOHN R, 1994, AM ECON REV, V84, P753
   Mendelsohn R., 2008, Journal of Natural Resources Policy Research, V1, P5, DOI [DOI 10.1080/19390450802495882, 10.1080/19390450802495882]
   Mohanty Abinash, 2021, Mapping India's Climate Vulnerability-A District Level Assessment
   Morita S., 2004, Japanese Journal of Crop Science, V73, P77, DOI 10.1626/jcs.73.77
   Moss Richard, 2008, Towards New Scenarios for Analysis of Emissions: Climate Change, Impacts, and Response Strategies
   Murphy J, 2007, HADLEY CTR REGIONAL, P20
   Pachauri RK, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, pVII
   Pai DS, 2014, MAUSAM, V65, P1
   Panda A, 2019, ATMOS SCI LETT, V20, DOI 10.1002/asl.932
   Panneerselvam S., 2016, Current World Environment, V11, P517, DOI 10.12944/CWE.11.2.20
   Peng SB, 2004, P NATL ACAD SCI USA, V101, P9971, DOI 10.1073/pnas.0403720101
   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]
   Rajalakshmi D., 2013, African Journal of Agricultural Research, V8, P4334
   Rajeevan M, 2006, CURR SCI INDIA, V91, P296
   Rajkumar R., 2021, RECENT PATTERNS EXTR, DOI 10.3354/cr01655
   Ramachandran A, 2017, J COAST CONSERV, V21, P731, DOI 10.1007/s11852-017-0532-6
   Ramachandran A, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0180706
   Ranganathan, 2009, WORKING PAPER SOCIAL, V9008
   Rao S, 2006, ENERG J, P177
   Reynolds M, 2018, AGRONOMY-BASEL, V8, DOI 10.3390/agronomy8120291
   Rummukainen M, 2010, WIRES CLIM CHANGE, V1, P82, DOI 10.1002/wcc.8
   San José R, 2016, J COMPUT APPL MATH, V293, P192, DOI 10.1016/j.cam.2015.04.024
   Saravanakumar V., 2015, Impact of Climate Change on Yield of Major Food Crops in Tamil Nadu, India
   Schlenker W, 2009, P NATL ACAD SCI USA, V106, P15594, DOI 10.1073/pnas.0906865106
   Srivastava AK, 2009, ATMOS SCI LETT, V10, P249, DOI 10.1002/asl.232
   Tan BT, 2021, AGRICULTURE-BASEL, V11, DOI 10.3390/agriculture11060569
   Thornton PK, 2014, GLOBAL CHANGE BIOL, V20, P3313, DOI 10.1111/gcb.12581
   van der Wiel K, 2021, COMMUN EARTH ENVIRON, V2, DOI 10.1038/s43247-020-00077-4
   Varadan RJ, 2015, CLIMATIC CHANGE, V129, P159, DOI 10.1007/s10584-015-1327-0
   Wilby RL, 1997, PROG PHYS GEOG, V21, P530, DOI 10.1177/030913339702100403
   World Bank, 2018, WORLD BANK REPORT
   Xu YF, 2021, CROP J, V9, P963, DOI 10.1016/j.cj.2021.02.011
   Xu ZF, 2015, J GEOPHYS RES-ATMOS, V120, P3063, DOI 10.1002/2014JD022958
   Yoshida S., 1981, Fundamentals of rice crop science.
NR 77
TC 9
Z9 10
U1 0
U2 6
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 2022
VL 150
IS 3-4
BP 941
EP 953
DI 10.1007/s00704-022-04198-y
EA SEP 2022
PG 13
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA 6H0IK
UT WOS:000854858500001
DA 2025-01-10
ER

PT J
AU Ajibade, I
   Sullivan, M
   Lower, C
   Yarina, L
   Reilly, A
AF Ajibade, Idowu
   Sullivan, Meghan
   Lower, Chris
   Yarina, Lizzie
   Reilly, Allie
TI Are managed retreat programs successful and just? A global mapping of
   success typologies, justice dimensions, and trade-offs
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article
DE Climate adaptation; Intersectional justice; Managed retreat; Planned
   resettlement; Success typologies
ID CLIMATE-CHANGE; ENVIRONMENTAL JUSTICE; RISK REDUCTION; RESETTLEMENT;
   RELOCATION; LESSONS; BUYOUT; GENTRIFICATION; RESTORATION; COMMUNITIES
AB As managed retreat programs expand across the globe, there is an urgent need to assess whether these programs are reducing exposure to climatic hazards, enhancing adaptive capacity, and improving the living conditions of communities in a just and equitable manner or are they exacerbating existing risks and vulnerabilities? Strictly speaking, are retreat programs successful? Using an expansive intersectional justice approach to examine 138 post-resettlement case studies published between 2000 and 2021 across the Global North and South, we identified five typologies of success - techno-managerial, eco-restorative, compensatory, reformative, and transformative - and their trade-offs and synergies. Our meta-analysis incorporated a variety of metrics: relocation types, funding, decision making, socio-economic class, land use change, livelihood options, and social impacts. We found 26% of cases failed, 43% were successful, and 30% are on-going and therefore success was undetermined. The techno-managerial cases, while successful in the limited terms of relocating residents, paid little attention to equity and justice. The eco-restorative and compensatory cases reduced hazard exposure but revealed the synergies and tensions associated with social, ecological, and intergenerational justice. The reformative and transformative cases improved community wellbeing, rootedness, and access to livelihoods while incorporating diverse justice concerns to different degrees. By intersecting these typologies with multiple dimensions of justice, this study advances a novel planning and analytical tool for assessing the potential success or failure of current and future retreat programs.
C1 [Ajibade, Idowu; Sullivan, Meghan; Lower, Chris] Portland State Univ, Dept Geog, 1721 SW Broadway, Portland, OR 97201 USA.
   [Yarina, Lizzie] MIT, Sch Architecture & Planning, Dept Urban Studies & Planning, Cambridge, MA 02139 USA.
   [Reilly, Allie] WSP, Climate Resilience & Sustainabil Team, New York, NY USA.
C3 Portland State University; Massachusetts Institute of Technology (MIT)
RP Ajibade, I (corresponding author), Portland State Univ, Dept Geog, 1721 SW Broadway, Portland, OR 97201 USA.
EM jajibade@pdx.edu
FU Portland State University
FX Funding for this research was provided by Portland State University
   (Faculty enhancement grant; Global Diversity Fund, and Vision 2025
   Grant) .
CR Ahmed I., 2014, International Journal of Disaster Resilience in the Built Environment, V5, P53, DOI DOI 10.1108/IJDRBE-08-2012-0028
   Ajibade I., 2022, GLOBAL VIEWS CLIMATE
   Ajibade I, 2022, ANN AM ASSOC GEOGR, V112, P2230, DOI 10.1080/24694452.2022.2062290
   Ajibade I, 2020, GLOBAL ENVIRON CHANG, V65, DOI 10.1016/j.gloenvcha.2020.102187
   Ajibade I, 2019, CLIMATIC CHANGE, V157, P299, DOI 10.1007/s10584-019-02535-1
   Albert S, 2018, REG ENVIRON CHANGE, V18, P2261, DOI 10.1007/s10113-017-1256-8
   Alexander KS, 2012, J ENVIRON PLANN MAN, V55, P409, DOI 10.1080/09640568.2011.604193
   Algoed L., 2019, Radical Housing Journal, V1, P29, DOI [https://doi.org/10.54825/MOVK2096, DOI 10.54825/MOVK2096]
   Alvarez MK, 2019, INT J URBAN REGIONAL, V43, P227, DOI 10.1111/1468-2427.12757
   Anguelovski I, 2019, P NATL ACAD SCI USA, V116, P26139, DOI 10.1073/pnas.1920490117
   [Anonymous], 2021, Global Report on Internal Displacement 2021
   Arnall A, 2019, CLIM DEV, V11, P253, DOI 10.1080/17565529.2018.1442799
   Baja K, 2021, GLOBAL VIEWS CLIMATE, P19
   Baker CK, 2018, RISK HAZARDS CRISIS, V9, P455, DOI 10.1002/rhc3.12144
   Bergmann J, 2021, J ENVIRON STUD SCI, V11, P365, DOI 10.1007/s13412-021-00699-w
   Bertana A, 2020, ENVIRON PLAN C-POLIT, V38, P902, DOI 10.1177/2399654420909394
   Binder SB, 2016, POLITICS GOV, V4, P97, DOI 10.17645/pag.v4i4.738
   Bisht T., 2014, LOSE GAIN IS INVOLUN, P15
   Carey J, 2020, P NATL ACAD SCI USA, V117, P13182, DOI 10.1073/pnas.2008198117
   Cernea M, 1997, WORLD DEV, V25, P1569, DOI 10.1016/S0305-750X(97)00054-5
   Chappell B., 2019, JAKARTA IS CROWDED S
   Chatterjee P., 2009, Innovative approaches for involuntary resettlement: Lunawa Environmental and Community Development Project
   Connell Raewyn, 2012, CONTEXTS, V11, P12, DOI [10.1177/1536504212436479, DOI 10.1177/1536504212436479]
   Correa E., 2011, Populations at Risk of Disaster A Resettlement Guide
   Crenshaw Kimberle, 1989, University of Chicago Legal Forum, P139, DOI DOI 10.4324/9780429500480-5
   Crenshaw Kimberle., 1991, Mapping the Margins: Intersectionality, Identity Politics, and Violence Against Women of Color, DOI [10.2307/1229039, DOI 10.2307/1229039]
   Nguyen CN, 2020, INT J DISAST RISK RE, V47, DOI 10.1016/j.ijdrr.2020.101543
   Dale L.A., 2022, CASE RWERU MODEL GRE, DOI [10.7916/dr28-0884, DOI 10.7916/DR28-0884]
   Davies R, FLOODLIST 0720
   Davis J. E., 2020, COMMON GROUND INT PE, P189
   de la Vega-Leinert AC, 2018, J COASTAL RES, V34, P586, DOI 10.2112/JCOASTRES-D-15-00217.1
   de Sherbinin A, 2011, SCIENCE, V334, P456, DOI 10.1126/science.1208821
   De Wet Chris., 2006, DEV INDUCED DISPLACE
   Dickinson D, 2007, J DEV STUD, V43, P537, DOI 10.1080/00220380701204513
   Du FC, 2012, NOMAD PEOPLES, V16, P116, DOI 10.3167/np.2012.160109
   Dundon LA, 2021, J ENVIRON STUD SCI, V11, P420, DOI 10.1007/s13412-021-00691-4
   Dyckman CS, 2014, OCEAN COAST MANAGE, V102, P212, DOI 10.1016/j.ocecoaman.2014.09.010
   Edwards JB, 2013, REFUG SURV Q, V32, P52, DOI 10.1093/rsq/hdt011
   Elliott JR, 2020, SOCIUS, V6, DOI 10.1177/2378023120905439
   Erwin A, 2021, WORLD DEV, V138, DOI 10.1016/j.worlddev.2020.105282
   Farbotko C, 2020, NAT CLIM CHANGE, V10, P702, DOI 10.1038/s41558-020-0829-6
   Fernando N, 2018, PROCEDIA ENGINEER, V212, P1026, DOI 10.1016/j.proeng.2018.01.132
   Ferris E., 2011, Planned relocations, disasters and climate change. Prepared for the Gilbert + Tobin Centre of Public Law's conference on climate change and migration in the Asia-Pacific: Legal and policy response, P1
   Ferris Elizabeth., 2015, SAIS Review of International Affairs, V35, P109, DOI DOI 10.1353/SAIS.2015.0001
   Freudenberg R., 2016, Buy-in for buyouts: the case for managed retreat from flood zones
   Funder M, 2018, J DEV STUD, V54, P30, DOI 10.1080/00220388.2016.1277021
   Gebauer C, 2015, AREA, V47, P97, DOI 10.1111/area.12168
   Gharbaoui D, 2016, GLOB MIGRAT ISS, V6, P149, DOI 10.1007/978-3-319-42922-9_8
   Gini G, 2021, GLOBAL VIEWS CLIMATE, P217
   Gini G., 2020, Forced Migr. Rev., V64, P35
   Gould KA, 2018, CITY COMMUNITY, V17, P12, DOI 10.1111/cico.12283
   Greer A, 2017, HOUS POLICY DEBATE, V27, P372, DOI 10.1080/10511482.2016.1245209
   Haasnoot M, 2021, SCIENCE, V372, P1287, DOI 10.1126/science.abi6594
   Hammond L, 2008, J REFUG STUD, V21, P517, DOI 10.1093/jrs/fen041
   Harvey F, 2021, GUARDIAN 0726
   Hazelden J, 2001, SOIL USE MANAGE, V17, P150, DOI 10.1079/SUM200166
   Hemming V, 2018, METHODS ECOL EVOL, V9, P169, DOI 10.1111/2041-210X.12857
   Hermann E, 2017, CONTEMP PACIFIC, V29, P231, DOI 10.1353/cp.2017.0030
   Hino M, 2017, NAT CLIM CHANGE, V7, P364, DOI [10.1038/NCLIMATE3252, 10.1038/nclimate3252]
   Horton RM, 2021, SCIENCE, V372, P1279, DOI 10.1126/science.abi8603
   Huang JC, 2021, J ENVIRON STUD SCI, V11, P404, DOI 10.1007/s13412-021-00687-0
   Huang SM, 2018, NAT HAZARDS REV, V19, DOI 10.1061/(ASCE)NH.1527-6996.0000308
   Hurdle J, 2019, NEW JERSEY SPOT 1007
   Intergovernmental Panel on Climate Change (IPCC), 2021, AR6 Climate Change 2021: The Physical Science Basis
   Islam Arafatul., 2021, Deutsche Welle
   Iuchi K, 2014, J AM PLANN ASSOC, V80, P413, DOI 10.1080/01944363.2014.978353
   Jessee N., 2020, Louisiana's Response to Extreme Weather, P147
   Kaijser A, 2014, ENVIRON POLIT, V23, P417, DOI 10.1080/09644016.2013.835203
   Kang D, 2021, CHINA FLOODING BROUG
   Keenan JM, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aabb32
   Kita SM, 2017, INT J DISAST RISK RE, V22, P158, DOI 10.1016/j.ijdrr.2017.03.010
   Koslov L, 2021, CLIMATIC CHANGE, V165, DOI 10.1007/s10584-021-03069-1
   Koslov L, 2016, PUBLIC CULTURE, V28, P359, DOI 10.1215/08992363-3427487
   Kothari U, 2014, GEOGR J, V180, P130, DOI 10.1111/geoj.12032
   Kulp SA, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-12808-z
   Lawrence J, 2020, CURR CLIM CHANGE REP, V6, P66, DOI 10.1007/s40641-020-00161-z
   Lei YR, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9081373
   Loughran K, 2019, SOC CURR, V6, P121, DOI 10.1177/2329496518797851
   Mach KJ, 2021, SCIENCE, V372, P1294, DOI 10.1126/science.abh1894
   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
   Marter-Kenyon J, 2020, ANTHROPOCENE REV, V7, P159, DOI 10.1177/2053019620915633
   McAdam J, 2015, CAMB INT LAW J, V4, P137, DOI 10.7574/cjicl.04.01.137
   McAdam J, 2014, J PAC HIST, V49, P301, DOI 10.1080/00223344.2014.953317
   McMichael C, 2021, INT J ENV RES PUB HE, V18, DOI 10.3390/ijerph18084355
   Miao Q, 2022, NAT HAZARDS REV, V23, DOI 10.1061/(ASCE)NH.1527-6996.0000534
   Miller F, 2020, URBAN STUD, V57, P1570, DOI 10.1177/0042098019830239
   Miller F, 2019, ASIA PAC VIEWP, V60, P132, DOI 10.1111/apv.12228
   Moher D, 2010, INT J SURG, V8, P336, DOI [10.1371/journal.pmed.1000097, 10.1136/bmj.b2700, 10.1016/j.ijsu.2010.02.007, 10.1136/bmj.i4086, 10.1136/bmj.b2535, 10.1016/j.ijsu.2010.07.299, 10.1186/2046-4053-4-1]
   Mortreux C, 2009, GLOBAL ENVIRON CHANG, V19, P105, DOI 10.1016/j.gloenvcha.2008.09.006
   Mulligan B, 2017, COMMUNITY ENGAGEMENT, P175
   Nakelevu T., 2021, POSTRELOCATION SURVE
   Natural Resources Canada, 2020, PLANN RETR APPR SUPP, DOI [10.4095/328323, DOI 10.4095/328323]
   Okada T, 2014, INT J DISAST RISK RE, V8, P20, DOI 10.1016/j.ijdrr.2014.01.001
   Ovalles L., 2021, MOVING TOGETHER PUER
   Picciotto R., 2001, Involuntary Resettlement
   Piggott-McKellar AE, 2020, AMBIO, V49, P1474, DOI 10.1007/s13280-019-01289-5
   Pinter N, 2021, ELEMENTA-SCI ANTHROP, V9, DOI 10.1525/elementa.2021.00036
   Santiago JSS, 2018, INT J DISAST RISK RE, V27, P480, DOI 10.1016/j.ijdrr.2017.11.012
   Schernewski G, 2018, J COAST CONSERV, V22, P157, DOI 10.1007/s11852-017-0496-6
   Schlosberg D, 2013, ENVIRON POLIT, V22, P37, DOI 10.1080/09644016.2013.755387
   Scudder T T., 2012, The future of large dams: Dealing with social, environmental, institutional and political costs
   See J, 2020, GLOBAL ENVIRON CHANG, V65, DOI 10.1016/j.gloenvcha.2020.102188
   Seebauer S, 2020, CLIMATIC CHANGE, V162, P2219, DOI 10.1007/s10584-020-02796-1
   Sheffield P, 2014, ANN GLOB HEALTH, V80, P296, DOI 10.1016/j.aogh.2014.07.001
   Siders AR, 2021, CURR OPIN ENV SUST, V50, P272, DOI 10.1016/j.cosust.2021.06.007
   Siders AR, 2021, J ENVIRON STUD SCI, V11, P287, DOI 10.1007/s13412-021-00700-6
   Siders AR, 2019, ONE EARTH, V1, P216, DOI 10.1016/j.oneear.2019.09.008
   Siders AR, 2020, OCEAN COAST MANAGE, V183, DOI 10.1016/j.ocecoaman.2019.105023
   Siders AR, 2019, CLIMATIC CHANGE, V152, P239, DOI 10.1007/s10584-018-2272-5
   Silva K.D, 2021, INT J MASS EMERGEN D, V39
   Smith R., 2013, Journal of New Zealand Pacific Studies, V1, P23
   Sousa CAM, 2020, LAND USE POLICY, V94, DOI 10.1016/j.landusepol.2020.104544
   Spidalieri Katie., 2020, Managing the Retreat from Rising Seas
   Stefancu O, 2021, GLOBAL VIEWS CLIMATE, P152
   Sultana F, 2021, SOC CULT GEOGR, V22, P447, DOI 10.1080/14649365.2021.1910994
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Tabucanon GMP, 2014, INT J MINOR GROUP RI, V21, P25, DOI 10.1163/15718115-02101002
   Tefera M.M., 2009, J SUSTAINABLE DEV AF, V11, P93
   Terry G., 2009, Gender and Development, V17, P5, DOI 10.1080/13552070802696839
   Thaler T, 2021, J ENVIRON STUD SCI, V11, P412, DOI 10.1007/s13412-021-00694-1
   Thomas DR, 2006, AM J EVAL, V27, P237, DOI 10.1177/1098214005283748
   Townend I, 2002, PHILOS T R SOC A, V360, P1477, DOI 10.1098/rsta.2002.1011
   Tronquet C., 2015, The State of Environmental Migration, V2015, P121
   Whyte KP, 2011, ENVIRON JUSTICE, V4, P199, DOI 10.1089/env.2011.0036
   Wilmsen B, 2015, DEV PRACT, V25, P612, DOI 10.1080/09614524.2015.1051947
   Wilmsen B, 2015, GEOFORUM, V58, P76, DOI 10.1016/j.geoforum.2014.10.016
   World Bank, 2021, MILL MOV THEIR OWN C
   Wu J., 2015, Geography Research Forum, P95
   Xiao QY, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10082913
   Yarina L, 2019, J LANDSC ARCHIT, V14, P8, DOI 10.1080/18626033.2019.1705570
   Yi S, 2015, CHINA DIALOGUE
NR 132
TC 27
Z9 32
U1 4
U2 31
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 SEP
PY 2022
VL 76
AR 102576
DI 10.1016/j.gloenvcha.2022.102576
EA AUG 2022
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 3Z4SX
UT WOS:000844408100002
DA 2025-01-10
ER

PT J
AU Marijnissen, R
   Kok, M
   Kroeze, C
   van Loon-Steensma, J
AF Marijnissen, Richard
   Kok, Matthijs
   Kroeze, Carolien
   van Loon-Steensma, Jantsje
TI The Sensitivity of a Dike-Marsh System to Sea-Level Rise-A Model-Based
   Exploration
SO JOURNAL OF MARINE SCIENCE AND ENGINEERING
LA English
DT Article
DE climate adaptation; flood protection; salt marsh
ID SALT-MARSH; TIDAL MARSH; FLOOD PROTECTION; COASTAL DEFENSE; RANDOM
   BREAKING; NORTH NORFOLK; VEGETATION; SEDIMENT; GROWTH; COLLAPSE
AB Integrating natural components in flood defence infrastructure can add resilience to sea-level rise. Natural foreshores can keep pace with sea-level rise by accumulating sediment and attenuate waves before reaching the adjacent flood defences. In this study we address how natural foreshores affect the future need for dike heightening. A simplified model of vertical marsh accretion was combined with a wave model and a probabilistic evaluation of dike failure by overtopping. The sensitivity of a marsh-dike system was evaluated in relation to a combination of processes: (1) sea-level rise, (2) changes in sediment concentration, (3) a retreat of the marsh edge, and (4) compaction of the marsh. Results indicate that foreshore processes considerably affect the need for dike heightening in the future. At a low sea-level rise rate, the marshes can accrete such that dike heightening is partially mitigated. But with sea-level rise accelerating, a threshold is reached where dike heightening needs to compensate for the loss of marshes, and for increasing water levels. The level of the threshold depends mostly on the delivery of sediment and degree of compaction on the marsh; with sufficient width of the marsh, lateral erosion only has a minor effect. The study shows how processes and practices that hamper or enhance marsh development today exacerbate or alleviate the challenge of flood protection posed by accelerated sea-level rise.
C1 [Marijnissen, Richard; Kroeze, Carolien; van Loon-Steensma, Jantsje] Wageningen Univ & Res, Water Syst & Global Change Grp, POB 47, NL-6700 AA Wageningen, Netherlands.
   [Kok, Matthijs; van Loon-Steensma, Jantsje] Delft Univ Technol, Fac Civil Engn & Geosci, POB 5048, NL-2600 GA Delft, Netherlands.
   [Kok, Matthijs] HKV Consultants, Botter 11 29, NL-8232 JN Lelystad, Netherlands.
C3 Wageningen University & Research; Delft University of Technology
RP Marijnissen, R (corresponding author), Wageningen Univ & Res, Water Syst & Global Change Grp, POB 47, NL-6700 AA Wageningen, Netherlands.
EM richard.marijnissen@wur.nl; Matthijs.Kok@tudelft.nl;
   carolien.kroeze@wur.nl; jantsje.vanloon@wur.nl
RI Kroeze, Carolien/C-6938-2014
OI Marijnissen, Richard Johannes Cornelis/0000-0002-9840-450X; van
   Loon-Steensma, Jantsje M./0000-0002-6181-7829
FU NWO Domain Applied and Engineering Sciences [P15-21]
FX This work is part of the Perspectief research programme All-Risk with
   project number P15-21, which is financed by NWO Domain Applied and
   Engineering Sciences.
CR ALLEN JRL, 1990, MAR GEOL, V95, P77, DOI 10.1016/0025-3227(90)90042-I
   Allen JRL, 2000, QUATERNARY SCI REV, V19, P1155, DOI 10.1016/S0277-3791(99)00034-7
   Atkins RJ, 2016, J COASTAL RES, P790, DOI 10.2112/SI75-159.1
   Baptist MJ, 2007, J HYDRAUL RES, V45, P435, DOI 10.1080/00221686.2007.9521778
   Baptist MJ, 2019, ECOL ENG, V127, P312, DOI 10.1016/j.ecoleng.2018.11.019
   Bass AS, 1997, J COASTAL RES, V13, P895
   BATTJES JA, 1985, J GEOPHYS RES-OCEANS, V90, P9159, DOI 10.1029/JC090iC05p09159
   Booij N, 1999, J GEOPHYS RES-OCEANS, V104, P7649, DOI 10.1029/98JC02622
   Borsje BW, 2011, ECOL ENG, V37, P113, DOI 10.1016/j.ecoleng.2010.11.027
   Bouma TJ, 2016, LIMNOL OCEANOGR, V61, P2261, DOI 10.1002/lno.10374
   Bouma TJ, 2010, ECOLOGY, V91, P2696, DOI 10.1890/09-0690.1
   Costanza R, 2008, AMBIO, V37, P241, DOI 10.1579/0044-7447(2008)37[241:TVOCWF]2.0.CO;2
   Craft C, 2009, FRONT ECOL ENVIRON, V7, P73, DOI 10.1890/070219
   Crosby SC, 2016, ESTUAR COAST SHELF S, V181, P93, DOI 10.1016/j.ecss.2016.08.018
   DALRYMPLE RA, 1984, J WATERW PORT C-ASCE, V110, P67, DOI 10.1061/(ASCE)0733-950X(1984)110:1(67)
   Duits M.T., 2018, Hydra-NL - Systeemdocumentatie - Versie 2.4
   Elschot K, 2013, ESTUAR COAST SHELF S, V133, P109, DOI 10.1016/j.ecss.2013.08.021
   Esselink P, 1998, J COASTAL RES, V14, P570
   Esselink P., 2011, 02 PUCCIMAR ALT WYM
   Esselink P., 2007, Hoogteontwikkeling verwaarloosde landaanwinningskwelder: Opslibbing van de Dollardkwelders in de periode 1991 - 2003 en een vergelijking met de periode 1984 - 1991 Report 2007-009
   Esselink P., 2000, THESIS
   Fagherazzi S, 2013, OCEANOGRAPHY, V26, P70, DOI 10.5670/oceanog.2013.47
   Fagherazzi S, 2012, REV GEOPHYS, V50, DOI 10.1029/2011RG000359
   Firth LB, 2014, COAST ENG, V87, P122, DOI 10.1016/j.coastaleng.2013.10.015
   Ford MA, 1999, ECOL ENG, V12, P189, DOI 10.1016/S0925-8574(98)00061-5
   Foster-Martinez MR, 2018, COAST ENG, V136, P26, DOI 10.1016/j.coastaleng.2018.02.001
   FRENCH JR, 1993, EARTH SURF PROC LAND, V18, P63, DOI 10.1002/esp.3290180105
   Ganju NK, 2019, ESTUAR COAST, V42, P917, DOI 10.1007/s12237-019-00531-3
   Glass EM, 2018, LIMNOL OCEANOGR, V63, P951, DOI 10.1002/lno.10682
   Kirwan M, 2009, QUATERNARY SCI REV, V28, P1801, DOI 10.1016/j.quascirev.2009.02.022
   Kirwan ML, 2016, NAT CLIM CHANGE, V6, P253, DOI 10.1038/NCLIMATE2909
   Kirwan ML, 2013, NATURE, V504, P53, DOI 10.1038/nature12856
   Kirwan ML, 2010, GEOPHYS RES LETT, V37, DOI 10.1029/2010GL045489
   Krone R.B., 1987, Coastal Sediments '87, P316
   Leo KL, 2019, OCEAN COAST MANAGE, V175, P180, DOI 10.1016/j.ocecoaman.2019.03.019
   Leonard LA, 2002, J COASTAL RES, P459
   Low BK, 2007, J ENG MECH, V133, P1378, DOI 10.1061/(ASCE)0733-9399(2007)133:12(1378)
   Marijnissen R.J.C., SCI TOTAL ENV
   Mariotti G, 2013, P NATL ACAD SCI USA, V110, P5353, DOI 10.1073/pnas.1219600110
   Mcleod E, 2011, FRONT ECOL ENVIRON, V9, P552, DOI 10.1890/110004
   Mendez FJ, 2004, COAST ENG, V51, P103, DOI 10.1016/j.coastaleng.2003.11.003
   Möller I, 2002, J COASTAL RES, P506
   Möller I, 2014, NAT GEOSCI, V7, P727, DOI [10.1038/ngeo2251, 10.1038/NGEO2251]
   Möller I, 2001, J CHART INST WATER E, V15, P109
   Möller I, 1999, ESTUAR COAST SHELF S, V49, P411, DOI 10.1006/ecss.1999.0509
   Möller I, 2019, FRONT ENV SCI-SWITZ, V7, DOI 10.3389/fenvs.2019.00049
   Nolte S, 2013, ESTUAR COAST SHELF S, V135, P296, DOI 10.1016/j.ecss.2013.10.026
   Peteet DM, 2018, P NATL ACAD SCI USA, V115, P10281, DOI 10.1073/pnas.1715392115
   Powell EJ, 2019, J COAST CONSERV, V23, P1, DOI 10.1007/s11852-018-0632-y
   Provincie Groningen Ministerie van Infrastructuur en Milieu, 2018, PROGR EEMS DOLLL 205
   Pullen T., J EUROTOP WAVE OVERT
   Rijkswaterstaat, WTI2011 WADD VOORL M
   Rijkswaterstaat, 2017, HANDR ONTW MET OV
   Rijkswaterstaat, ACT HOOGT NED 2 AHN2
   Rupp-Armstrong S, 2007, J COASTAL RES, V23, P1418, DOI 10.2112/04-0426.1
   SCHERES B, 2019, WATER-SUI, V11, DOI DOI 10.3390/W11081617
   Schoonees T, 2019, ESTUAR COAST, V42, P1709, DOI 10.1007/s12237-019-00551-z
   Schoutens K, 2019, LIMNOL OCEANOGR, V64, P1750, DOI 10.1002/lno.11149
   Schuerch M, 2018, NATURE, V561, P231, DOI 10.1038/s41586-018-0476-5
   Silliman BR, 2012, P NATL ACAD SCI USA, V109, P11234, DOI 10.1073/pnas.1204922109
   Slomp R.M., 2015, P 36 IAHR WORLD C HA, P1
   Spencer T, 2016, GLOBAL PLANET CHANGE, V139, P15, DOI 10.1016/j.gloplacha.2015.12.018
   Stark J, 2015, LIMNOL OCEANOGR, V60, P1371, DOI 10.1002/lno.10104
   Stark J, 2016, ESTUAR COAST SHELF S, V175, P34, DOI 10.1016/j.ecss.2016.03.027
   Temmerman S, 2013, NATURE, V504, P79, DOI 10.1038/nature12859
   Tempest JA, 2015, HYDROL PROCESS, V29, P2346, DOI 10.1002/hyp.10368
   van de Koppel J, 2005, AM NAT, V165, pE1
   Van Loon-Steensma JM, 2016, E3S WEB CONF, V7, DOI 10.1051/e3sconf/20160713003
   van Loon-Steensma JM, 2016, J COASTAL RES, V32, P241, DOI 10.2112/JCOASTRES-D-15-00095.1
   van Loon-Steensma JM, 2015, MITIG ADAPT STRAT GL, V20, P929, DOI 10.1007/s11027-015-9640-5
   Van Loon-Steensma JM, 2013, J COASTAL RES, V29, P783, DOI 10.2112/JCOASTRES-D-12-00123.1
   van Maren DS, 2016, MAR GEOL, V376, P147, DOI 10.1016/j.margeo.2016.03.007
   Vermeersen BLA, 2018, NETH J GEOSCI, V97, P79, DOI 10.1017/njg.2018.7
   Vuik V, 2016, COAST ENG, V116, P42, DOI 10.1016/j.coastaleng.2016.06.001
   Vuik V, 2019, OCEAN COAST MANAGE, V171, P96, DOI 10.1016/j.ocecoaman.2019.01.010
   Vuik V, 2018, COAST ENG, V139, P47, DOI 10.1016/j.coastaleng.2018.05.002
   Vuik V, 2018, ESTUAR COAST SHELF S, V200, P41, DOI 10.1016/j.ecss.2017.09.028
   Wamsley TV, 2010, OCEAN ENG, V37, P59, DOI 10.1016/j.oceaneng.2009.07.018
   Yang SL, 2006, GEOPHYS RES LETT, V33, DOI 10.1029/2005GL025507
   Yang SL, 2001, GEOMORPHOLOGY, V38, P167, DOI 10.1016/S0169-555X(00)00079-9
   Young IR, 1996, COAST ENG, V29, P47, DOI 10.1016/S0378-3839(96)00006-3
   Ysebaert T, 2011, WETLANDS, V31, P1043, DOI 10.1007/s13157-011-0240-1
NR 82
TC 5
Z9 5
U1 1
U2 14
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2077-1312
J9 J MAR SCI ENG
JI J. Mar. Sci. Eng.
PD JAN
PY 2020
VL 8
IS 1
AR 42
DI 10.3390/jmse8010042
PG 17
WC Engineering, Marine; Engineering, Ocean; Oceanography
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Oceanography
GA KL8GY
UT WOS:000513656700032
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Roggero, M
   Kähler, L
   Hagen, A
AF Roggero, Matteo
   Kaehler, Leonhard
   Hagen, Achim
TI Strategic cooperation for transnational adaptation: lessons from the
   economics of climate change mitigation
SO INTERNATIONAL ENVIRONMENTAL AGREEMENTS-POLITICS LAW AND ECONOMICS
LA English
DT Article
DE Transnational adaptation; Public goods; Climate mitigation; Governance
   arrangements; Spillovers; Baltic Sea
ID BALTIC SEA; COALITION-FORMATION; STABILITY; FINANCE; FUTURE; GOVERNANCE;
   MANAGEMENT; CAPACITY; TREATIES; LEAKAGE
AB The literature on climate adaptation has so far conceptualized it as a domestic issue, to be governed somewhere between the local and the national scale. By contrast, scholars have shown little interest in exploring the case of cross-boundary adaptation spillovers, where adaptation by one country affects other countries. Two decades of the economic literature on climate mitigation may contribute to bridge this research gap because the problem structure of climate mitigation resembles that of adaptation with cross-boundary spillovers. With this in mind, we ask the following research question: Are there lessons to be learned by applying a mitigation perspective to the governance of adaptation with cross-boundary spillovers? After reviewing the relevant adaptation and mitigation literature, the paper applies mitigation insights to an adaptation case with cross-boundary spillovers: climate change-induced eutrophication in the Baltic Sea. Insights on coalition structures, side-payments, issue-linkage, and trade sanctions provide novel perspectives on the governance structures in place. To improve cooperation on providing adaptation as a public good, smaller regional governance arrangements could be more effective, European subsidies for pollution control might be redirected, and progress on eutrophication could be made a precondition for cooperation on other areas. These perspectives depart both from the way the Baltic Sea eutrophication problem is addressed at present, and from the way public goods are addressed in the adaptation literature. They show that some lessons can indeed be learned, calling for further research.
C1 [Roggero, Matteo; Kaehler, Leonhard; Hagen, Achim] Humboldt Univ, Berlin, Germany.
C3 Humboldt University of Berlin
RP Roggero, M (corresponding author), Humboldt Univ, Berlin, Germany.
EM matteo.mancini.roggero@gmail.com
CR Ahlvik L, 2013, ENVIRON RESOUR ECON, V56, P353, DOI 10.1007/s10640-013-9651-1
   Ahtiainen H, 2014, J ENVIRON ECON POLIC, V3, P278, DOI 10.1080/21606544.2014.901923
   Andersson A, 2015, AMBIO, V44, pS345, DOI 10.1007/s13280-015-0654-8
   [Anonymous], INT ENV AGREEMENTS P
   [Anonymous], 2018, BALT SEA ENV P
   [Anonymous], INT ENV AGREEMENTS P
   [Anonymous], OECD EC DEP WORKING
   [Anonymous], 2011, Working Paper
   [Anonymous], 2002, The Institutional Dimensions of Environmental Change, DOI DOI 10.7551/MITPRESS/3807.001.0001
   [Anonymous], INT ENV AGREEMENTS P
   [Anonymous], INT ENV AGREEMENTS P
   Asheim GB, 2006, J ENVIRON ECON MANAG, V51, P93, DOI 10.1016/j.jeem.2005.04.004
   Atteridge A, 2018, WIRES CLIM CHANGE, V9, DOI 10.1002/wcc.500
   Backer H, 2011, J COAST CONSERV, V15, P279, DOI 10.1007/s11852-011-0156-1
   Backer H, 2010, MAR POLLUT BULL, V60, P642, DOI 10.1016/j.marpolbul.2009.11.016
   BARRETT S, 1994, OXFORD ECON PAP, V46, P878, DOI 10.1093/oep/46.Supplement_1.878
   Barrett S, 2001, EUR ECON REV, V45, P1835, DOI 10.1016/S0014-2921(01)00082-4
   Barrett S, 1997, RESOUR ENERGY ECON, V19, P345, DOI 10.1016/S0928-7655(97)00016-X
   Barrett S, 2013, GLOBAL ENVIRON CHANG, V23, P1819, DOI 10.1016/j.gloenvcha.2013.07.015
   Bengtsson R, 2009, European Policy Analysis, V9, P1
   Benzie M, 2019, INT ENV AGREEMENTS P
   Bisaro A, 2016, NAT CLIM CHANGE, V6, P354, DOI 10.1038/NCLIMATE2936
   Bohringer C., 2016, AM ECON J-ECON POLIC, V8, P1
   Bosello F, 2003, J EUR ECON ASSOC, V1, P601, DOI 10.1162/154247603322391233
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   CARRARO C, 1993, J PUBLIC ECON, V52, P309, DOI 10.1016/0047-2727(93)90037-T
   Carraro Carlo, 2004, GAME PRACTICE ENV, P65
   Carraro Carlo., 1997, INT ENV NEGOTIATIONS, P71
   CHANDER P., 1995, INT TAX PUBLIC FINAN, V2, P279, DOI [10.1007/bf00877502, DOI 10.1007/BF00877502]
   Chapman AD, 2016, CLIMATIC CHANGE, V137, P593, DOI 10.1007/s10584-016-1684-3
   Chong J, 2014, INT ENVIRON AGREEM-P, V14, P391, DOI 10.1007/s10784-014-9242-9
   DASPREMONT C, 1983, CAN J ECON, V16, P17, DOI 10.2307/134972
   Dellink R, 2011, CLIM CHANG ECON, V2, P105, DOI 10.1142/S2010007811000231
   Dodman D, 2008, IDS BULL-I DEV STUD, V39, P67
   Ducrotoy JP, 2008, MAR POLLUT BULL, V57, P8, DOI 10.1016/j.marpolbul.2008.04.030
   Duus-Otterström G, 2016, INT ENVIRON AGREEM-P, V16, P655, DOI 10.1007/s10784-015-9288-3
   Dzebo A, 2015, GLOBAL ENVIRON CHANG, V35, P423, DOI 10.1016/j.gloenvcha.2015.10.006
   Eisenack K, 2014, NAT CLIM CHANGE, V4, P867, DOI 10.1038/NCLIMATE2350
   Elliott M, 2015, MAR POLLUT BULL, V95, P7, DOI 10.1016/j.marpolbul.2015.03.015
   Elmgren R, 2015, AMBIO, V44, pS335, DOI 10.1007/s13280-015-0653-9
   European Court of Auditors, 2016, SPECIAL REPORT
   FELDER S, 1993, J ENVIRON ECON MANAG, V25, P162, DOI 10.1006/jeem.1993.1040
   Folmer H., 1993, Environmental and Resource Economics, V3, P313, DOI 10.1007/BF00418815
   FOLMER H, 1994, ANN OPER RES, V54, P97, DOI 10.1007/BF02031729
   Friedland R, 2012, J MARINE SYST, V105, P175, DOI 10.1016/j.jmarsys.2012.08.002
   Grasso Marco., 2006, International Environmental Agreements, V6, P249
   Gren IM, 2008, ECOL ECON, V66, P337, DOI 10.1016/j.ecolecon.2007.09.010
   HAGEN A, 2017, OLDENBURG DISCUSSION
   Hagen A, 2017, EC INT ENV AGREEMENT, P79
   Hassler B, 2017, J ENVIRON POL PLAN, V19, P408, DOI 10.1080/1523908X.2016.1233808
   Hedlund J, 2018, GLOBAL ENVIRON CHANG, V52, P75, DOI 10.1016/j.gloenvcha.2018.04.006
   HOEL M, 1991, J ENVIRON ECON MANAG, V20, P55, DOI 10.1016/0095-0696(91)90023-C
   Huttunen I, 2015, SCI TOTAL ENVIRON, V529, P168, DOI 10.1016/j.scitotenv.2015.05.055
   James P, 2009, URBAN FOR URBAN GREE, V8, P65, DOI 10.1016/j.ufug.2009.02.001
   Jim CY, 2008, J ENVIRON MANAGE, V88, P665, DOI 10.1016/j.jenvman.2007.03.035
   Johannesson K, 2011, AMBIO, V40, P179, DOI 10.1007/s13280-010-0129-x
   Jones HP, 2012, NAT CLIM CHANGE, V2, P504, DOI 10.1038/NCLIMATE1463
   Juhola S, 2016, ENVIRON SCI POLICY, V55, P135, DOI 10.1016/j.envsci.2015.09.014
   Karlsson M, 2016, MARE PUBL SER, V10, P21, DOI 10.1007/978-3-319-27006-7_2
   Kay K, 2014, GEOFORUM, V54, P80, DOI 10.1016/j.geoforum.2014.04.003
   Kistin EJ, 2008, INT J WATER RESOUR D, V24, P385, DOI 10.1080/07900620802127325
   Klein RJT, 2010, CLIM DEV, V2, P203, DOI 10.3763/cdev.2010.0049
   Kundzewicz ZW, 2009, BOREAL ENVIRON RES, V14, P193
   Lesnikowski A, 2017, CLIM POLICY, V17, P825, DOI 10.1080/14693062.2016.1248889
   Lessmann K, 2015, ENVIRON RESOUR ECON, V62, P811, DOI 10.1007/s10640-015-9886-0
   Lessmann K, 2009, ECON MODEL, V26, P641, DOI 10.1016/j.econmod.2009.01.005
   Liverman D, 2016, CLIMATIC CHANGE, V135, P173, DOI 10.1007/s10584-015-1464-5
   Magnan AK, 2016, WIRES CLIM CHANGE, V7, P646, DOI 10.1002/wcc.409
   Markowska A, 1999, ECOL ECON, V30, P301, DOI 10.1016/S0921-8009(98)00138-4
   Marrouch W, 2015, INT REV ENVIRON RESO, V9, P245, DOI 10.1561/101.00000078
   Mitchell SM, 2006, POLIT GEOGR, V25, P357, DOI 10.1016/j.polgeo.2006.05.001
   Mohr E, 1998, J DEV ECON, V55, P173, DOI 10.1016/S0304-3878(97)00061-8
   Moser SC, 2015, CLIMATIC CHANGE, V129, P13, DOI 10.1007/s10584-015-1328-z
   Moss T, 2012, ECOL SOC, V17, DOI 10.5751/ES-04821-170302
   Munang R, 2013, CURR OPIN ENV SUST, V5, P67, DOI 10.1016/j.cosust.2012.12.001
   Nordhaus W, 2015, AM ECON REV, V105, P1339, DOI 10.1257/aer.15000001
   Osmani D, 2010, COMPUT ECON, V36, P93, DOI 10.1007/s10614-010-9232-0
   Pielke R, 2007, NATURE, V445, P597, DOI 10.1038/445597a
   Piwowarczyk J, 2012, AMBIO, V41, P645, DOI 10.1007/s13280-012-0327-9
   Sælen H, 2016, INT ENVIRON AGREEM-P, V16, P909, DOI 10.1007/s10784-015-9311-8
   Sandler T., 1998, FISC STUD, V19, P221
   Sandler T, 2006, REV INT ORGAN, V1, P5, DOI 10.1007/s11558-006-6604-2
   Smit B, 2006, GLOBAL ENVIRON CHANG, V16, P282, DOI 10.1016/j.gloenvcha.2006.03.008
   Smit B, 2001, CLIMATE CHANGE 2001: IMPACTS, ADAPTATION, AND VULNERABILITY, P877
   Stern N, 2008, AM ECON REV, V98, P1, DOI 10.1257/aer.98.2.1
   Subramanian N, 2014, INT ENVIRON AGREEM-P, V14, P25, DOI 10.1007/s10784-013-9233-2
   Weikard HP, 2010, ENVIRON RESOUR ECON, V45, P573, DOI 10.1007/s10640-009-9329-x
   Wu J, 2018, INT ENVIRON AGREEM-P, V18, P573, DOI 10.1007/s10784-018-9406-0
   [No title captured]
   [No title captured]
   [No title captured]
   [No title captured]
NR 92
TC 10
Z9 11
U1 3
U2 21
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 1567-9764
EI 1573-1553
J9 INT ENVIRON AGREEM-P
JI Int. Environ. Agreem.-Polit. Law Econom.
PD OCT
PY 2019
VL 19
IS 4-5
SI SI
BP 395
EP 410
DI 10.1007/s10784-019-09442-x
PG 16
WC Economics; Environmental Studies; Law; Political Science
WE Social Science Citation Index (SSCI)
SC Business & Economics; Environmental Sciences & Ecology; Government & Law
GA IK5EN
UT WOS:000476608600003
DA 2025-01-10
ER

PT J
AU Harris, RMB
   Remenyi, T
   Fox-Hughes, P
   Love, P
   Bindoff, NL
AF Harris, Rebecca Mary Bernadette
   Remenyi, Tomas
   Fox-Hughes, Paul
   Love, Peter
   Bindoff, Nathaniel L.
TI Exploring the Future of Fuel Loads in Tasmania, Australia: Shifts in
   Vegetation in Response to Changing Fire Weather, Productivity, and Fire
   Frequency
SO FORESTS
LA English
DT Article
DE climate change; prescribed burning; vegetation change; climate
   adaptation
ID SEVERITY; FOREST; SMOKE
AB Changes to the frequency of fire due to management decisions and climate change have the potential to affect the flammability of vegetation, with long-term effects on the vegetation structure and composition. Frequent fire in some vegetation types can lead to transformational change beyond which the vegetation type is radically altered. Such feedbacks limit our ability to project fuel loads under future climatic conditions or to consider the ecological tradeoffs associated with management burns. We present a " pathway modelling" approach to consider multiple transitional pathways that may occur under different fire frequencies. The model combines spatial layers representing current and future fire danger, biomass, flammability, and sensitivity to fire to assess potential future fire activity. The layers are derived from a dynamically downscaled regional climate model, attributes from a regional vegetation map, and information about fuel characteristics. Fire frequency is demonstrated to be an important factor influencing flammability and availability to burn and therefore an important determinant of future fire activity. Regional shifts in vegetation type occur in response to frequent fire, as the rate of change differs across vegetation type. Fire-sensitive vegetation types move towards drier, more fire-adapted vegetation quickly, as they may be irreversibly impacted by even a single fire, and require very long recovery times. Understanding the interaction between climate change and fire is important to identify appropriate management regimes to sustain fire-sensitive communities and maintain the distribution of broad vegetation types across the landscape.
C1 [Harris, Rebecca Mary Bernadette; Remenyi, Tomas; Love, Peter; Bindoff, Nathaniel L.] Univ Tasmania, Antarctic Climate & Ecosyst Cooperat Res Ctr ACE, Hobart, Tas 7001, Australia.
   [Fox-Hughes, Paul] Bur Meteorol, Hobart, Tas 7001, Australia.
   [Bindoff, Nathaniel L.] Univ Tasmania, IMAS, Hobart, Tas 7001, Australia.
   [Bindoff, Nathaniel L.] Univ Tasmania, ARC Ctr Excellence Climate Syst Sci, Hobart, Tas 7001, Australia.
   [Bindoff, Nathaniel L.] Commonwealth Sci & Ind Res Org CSIRO Marine & Ato, CAWCR, Hobart, Tas 7001, Australia.
C3 University of Tasmania; Antarctic Climate & Ecosystems Cooperative
   Research Centre (ACE CRC); Bureau of Meteorology - Australia; University
   of Tasmania; ARC Centre of Excellence for Climate System Science;
   University of Tasmania; Commonwealth Scientific & Industrial Research
   Organisation (CSIRO)
RP Harris, RMB (corresponding author), Univ Tasmania, Antarctic Climate & Ecosyst Cooperat Res Ctr ACE, Hobart, Tas 7001, Australia.
EM rmharris@utas.edu.au; tom.remenyi@utas.edu.au;
   paul.fox-hughes@bom.gov.au; p.t.love@utas.edu.au; N.Bindoff@utas.edu.au
RI Fox-Hughes, Paul/G-8731-2013; Love, Peter/O-6421-2017; Harris,
   Rebecca/N-2790-2013; Bindoff, Nathaniel/C-8050-2011
OI Harris, Rebecca/0000-0002-6426-2179; Love, Peter/0000-0001-7840-0467;
   Bindoff, Nathaniel/0000-0001-5662-9519; Remenyi,
   Tomas/0000-0002-4145-9323
FU National Bushfire Mitigation-Tasmanian Grants Program (NBMP); Humboldt
   Research Fellowship
FX This work was funded by the National Bushfire Mitigation-Tasmanian
   Grants Program (NBMP). Rebecca Harris was supported in part by a
   Humboldt Research Fellowship. Jon Marsden-Smedley and Dave Taylor
   provided guidance and data for fuel accumulation curves and vegetation
   attributes. Sandra Whight and Paul Black supported the concept and gave
   valuable insights into the operational implications of prescribed
   burning regimes in Tasmania. Jayne Balmer (Department of Primary
   Industries, Parks, Water and Environment) gave ecological advice that
   helped in translating the TASVEG types into the model.
CR [Anonymous], 1972, Bulletin
   [Anonymous], 1967, Forestry and Timber Bureau No. Leaflet 107
   [Anonymous], ANUCLIM VERSION 6 1
   Bowman DMJS, 2014, GLOBAL CHANGE BIOL, V20, P1008, DOI 10.1111/gcb.12433
   Bradstock RA, 2012, J ENVIRON MANAGE, V105, P66, DOI 10.1016/j.jenvman.2012.03.050
   Bradstock RA, 2010, GLOBAL ECOL BIOGEOGR, V19, P145, DOI 10.1111/j.1466-8238.2009.00512.x
   Cary GJ, 2012, FLAMMABLE AUSTRALIA: FIRE REGIMES, BIODIVERSITY AND ECOSYSTEMS IN A CHANGING WORLD, P149
   Corney S.P., 2010, Climate futures for Tasmania technical report: Climate modelling
   di Folco MB, 2013, J BIOGEOGR, V40, P197, DOI 10.1111/j.1365-2699.2012.02779.x
   Fernandes PM, 2003, INT J WILDLAND FIRE, V12, P117, DOI 10.1071/WF02042
   Flannigan M, 2013, FOREST ECOL MANAG, V294, P54, DOI 10.1016/j.foreco.2012.10.022
   Fletcher MS, 2010, J BIOGEOGR, V37, P2183, DOI 10.1111/j.1365-2699.2010.02363.x
   Fletcher MS, 2010, HOLOCENE, V20, P351, DOI 10.1177/0959683609351903
   Fox-Hughes P., 2015, CLIMATE FUTURES TASM
   Fox-Hughes P, 2014, INT J WILDLAND FIRE, V23, P309, DOI 10.1071/WF13126
   Gill A. M., 1999, AUSTR BIODIVERSITY R, P206
   Haikerwal A, 2015, J AIR WASTE MANAGE, V65, P592, DOI 10.1080/10962247.2015.1032445
   Hammill K, 2016, PLANT ECOL, V217, P725, DOI 10.1007/s11258-016-0578-9
   Harris R. M. B., 2016, REV CLIM CHANG
   Harris R. M.B., 2018, NAT CLIM CHANGE
   Harris S., 2005, From Forest to Fjaeldmark: Descriptions of Tasmanias Vegetation
   Holz A, 2015, GLOBAL CHANGE BIOL, V21, P445, DOI 10.1111/gcb.12674
   Johnston F, 2014, GEOGR RES-AUST, V52, P45, DOI 10.1111/1745-5871.12028
   Jolly WM, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms8537
   Lindenmayer DB, 2011, P NATL ACAD SCI USA, V108, P15887, DOI 10.1073/pnas.1110245108
   Liu YQ, 2010, FOREST ECOL MANAG, V259, P685, DOI 10.1016/j.foreco.2009.09.002
   Marsden-Smedley J. B., 1999, Tasforests, V11, P87
   Marsden-Smedley JB, 2009, Planned burning in Tasmania: operational guidelines and review of current knowledge
   NOBLE IR, 1980, VEGETATIO, V43, P5, DOI 10.1007/BF00121013
   OLSON JS, 1963, ECOLOGY, V44, P322, DOI 10.2307/1932179
   Pyrke A. F., 2005, Tasforests, V16, P35
   Rumsewicz M., 2017, P BUSHF NAT HAZ CRC
   Sands PJ, 2002, FOREST ECOL MANAG, V163, P273, DOI 10.1016/S0378-1127(01)00586-2
   Tasmanian Department of Primary Industries Parks Water and Environment, 2013, TASM VEG MON MAPP PR
   Westerling AL, 2006, SCIENCE, V313, P940, DOI 10.1126/science.1128834
   Zylstra Philip, 2013, Victorian Naturalist (Blackburn), V130, P232
NR 36
TC 7
Z9 8
U1 2
U2 24
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 1999-4907
J9 FORESTS
JI Forests
PD APR
PY 2018
VL 9
IS 4
AR 210
DI 10.3390/f9040210
PG 16
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Forestry
GA GI9PH
UT WOS:000434856800054
OA gold
DA 2025-01-10
ER

PT J
AU McAfee, D
   Cumbo, VR
   Bishop, MJ
   Raftos, DA
AF McAfee, Dominic
   Cumbo, Vivian R.
   Bishop, Melanie J.
   Raftos, David A.
TI Intraspecific differences in the transcriptional stress response of two
   populations of Sydney rock oyster increase with rising temperatures
SO MARINE ECOLOGY PROGRESS SERIES
LA English
DT Article
DE Climate adaptation; Global warming; Molecular mechanisms; Saccostrea
   glomerata; Selective breeding; Thermal stress
ID CLIMATE-CHANGE; GENE-EXPRESSION; PACIFIC OYSTER; CRASSOSTREA-GIGAS;
   SACCOSTREA-GLOMERATA; OCEAN ACIDIFICATION; THERMAL TOLERANCE; PROTEIN
   RESPONSE; ADAPTATION; LIMITS
AB The vulnerability of sessile organisms to warming temperatures may depend on their capacity to adaptively alter their expression of genes associated with stress mitigation. We compared the transcriptional profile of 2 populations of Sydney rock oysters Saccostrea glomerata (one that had been selectively bred over 7 generations for fast growth and disease resistance and one wild type that had not been subjected to selection) following exposure to an artificial temperature gradient in the field. Oysters were attached to white, grey or black stone pavers that experienced mean maximum substrate temperatures of approximately 34, 37 and 40 degrees C, respectively, at low tide. Across all pavers, selectively bred oysters suffered 12% higher mortality than wild-type oysters, although this difference was not significant. Expression profiles did not differ between oyster populations on the coolest (white) pavers. However, divergent transcriptional profiles of genes associated with the key intracellular stress mechanisms of antioxidant defence, heat shock re sponse, energy metabolism and the cytoskeleton were detected in oysters on the hottest (black) pavers. Expression of these genes was upregulated at high temperatures by the selectively bred oysters but displayed little change, or was suppressed at high temperature among the non-selected wild-type oysters. One potential explanation is that the selectively bred oysters have traded off rapid growth for a lower thermal maximum. Complementary physiological and ecological studies are needed to confirm this hypothesis.
C1 [McAfee, Dominic; Cumbo, Vivian R.; Bishop, Melanie J.; Raftos, David A.] Macquarie Univ, Dept Biol Sci, N Ryde, NSW 2109, Australia.
   [McAfee, Dominic] Univ Adelaide, Sch Biol Sci, Adelaide, SA 5005, Australia.
C3 Macquarie University; University of Adelaide
RP McAfee, D (corresponding author), Macquarie Univ, Dept Biol Sci, N Ryde, NSW 2109, Australia.; McAfee, D (corresponding author), Univ Adelaide, Sch Biol Sci, Adelaide, SA 5005, Australia.
EM dominic.mcafee@adelaide.edu.au
RI Bishop, Melanie/AGA-7862-2022; McAfee, Dominic/ABD-5585-2020
OI Bishop, Melanie/0000-0001-8210-6500; McAfee,
   Dominic/0000-0001-8278-8169; Cumbo, Vivian/0000-0001-5757-8899
FU Australian Research Council Discovery Grant [DP150101363]; Australian
   Postgraduate Award; Department of Biological Sciences, Macquarie
   University
FX This research was funded by an Australian Research Council Discovery
   Grant DP150101363 to M.J.B. and D.A.R.; D.M. was supported by an
   Australian Postgraduate Award and the Department of Biological Sciences,
   Macquarie University. We are grateful to P. Goncalves for technical
   assistance. We also thank NSW Department of Primary Industries (DPI)
   personnel, A. McAfee, M. Vozzo and J. Thompson for assistance with
   fieldwork. Oysters were provided by NSW DPI.
CR Anderson K, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0118839
   [Anonymous], 2008, PERMANOVA + For Primer User Manual
   Barrett RDH, 2008, TRENDS ECOL EVOL, V23, P38, DOI 10.1016/j.tree.2007.09.008
   Bureau of Meteorology, 2017, COMM AUSTR 2017
   Crain CM, 2006, BIOSCIENCE, V56, P211
   Edwards M, 2004, NATURE, V430, P881, DOI 10.1038/nature02808
   Evans TG, 2012, PHILOS T R SOC B, V367, P1733, DOI 10.1098/rstb.2012.0019
   Fabbri E., 2008, ISJ, V5, P135
   Fangue NA, 2006, J EXP BIOL, V209, P2859, DOI 10.1242/jeb.02260
   Feder ME, 1999, ANNU REV PHYSIOL, V61, P243, DOI 10.1146/annurev.physiol.61.1.243
   Goncalves P, 2016, MOL ECOL, V25, P4836, DOI 10.1111/mec.13808
   Groh KJ, 2015, AQUAT TOXICOL, V159, P1, DOI 10.1016/j.aquatox.2014.11.013
   Hamdoun AM, 2003, BIOL BULL-US, V205, P160, DOI 10.2307/1543236
   Hand SC, 1996, ANNU REV PHYSIOL, V58, P539, DOI 10.1146/annurev.ph.58.030196.002543
   Heise K, 2006, J EXP BIOL, V209, P353, DOI 10.1242/jeb.01977
   Helmuth B, 2006, ANNU REV ECOL EVOL S, V37, P373, DOI 10.1146/annurev.ecolsys.37.091305.110149
   Huey RB, 2012, PHILOS T R SOC B, V367, P1665, DOI 10.1098/rstb.2012.0005
   Ivanina AV, 2009, AQUAT TOXICOL, V91, P245, DOI 10.1016/j.aquatox.2008.11.016
   Iwama GK, 1998, REV FISH BIOL FISHER, V8, P35, DOI 10.1023/A:1008812500650
   Jo PG, 2008, MOLLUSCAN RES, V28, P158
   Keppel G, 2012, GLOBAL CHANGE BIOL, V18, P2389, DOI 10.1111/j.1365-2486.2012.02729.x
   Krassoi FR, 2001, THESIS
   Lang RP, 2009, MAR BIOTECHNOL, V11, P650, DOI 10.1007/s10126-009-9181-6
   Livak KJ, 2001, METHODS, V25, P402, DOI 10.1006/meth.2001.1262
   Martinez E, 2016, COMP BIOCHEM PHYS A, V191, P209, DOI 10.1016/j.cbpa.2015.07.014
   McAfee D, 2017, J ANIM ECOL, V86, P1352, DOI 10.1111/1365-2656.12757
   McAfee D, 2016, ECOLOGY, V97, P929, DOI 10.1890/15-0651.1
   Ng TPT, 2017, J EXP MAR BIOL ECOL, V492, P121, DOI 10.1016/j.jembe.2017.01.023
   NSW DPI (New South Wales Department of Primary Industries, 2014, NSW OYST IND SUST AQ
   Pankhurst NW, 2011, MAR FRESHWATER RES, V62, P1015, DOI 10.1071/MF10269
   Parker LM, 2011, MAR BIOL, V158, P689, DOI 10.1007/s00227-010-1592-4
   Parker LM, 2012, GLOBAL CHANGE BIOL, V18, P82, DOI 10.1111/j.1365-2486.2011.02520.x
   Parker LM, 2009, GLOBAL CHANGE BIOL, V15, P2123, DOI 10.1111/j.1365-2486.2009.01895.x
   Parmesan C, 2003, NATURE, V421, P37, DOI 10.1038/nature01286
   Pörtner HO, 2007, PHILOS T R SOC B, V362, P2233, DOI 10.1098/rstb.2006.1947
   Pörtner HO, 2007, SCIENCE, V315, P95, DOI 10.1126/science.1135471
   Pörtner HO, 2008, SCIENCE, V322, P690, DOI 10.1126/science.1163156
   Portner HO, 2004, J OCEANOGR, V60, P705, DOI 10.1007/s10872-004-5763-0
   Rosenzweig C, 2008, NATURE, V453, P353, DOI 10.1038/nature06937
   SANDERS BM, 1991, PHYSIOL ZOOL, V64, P1471, DOI 10.1086/physzool.64.6.30158225
   Shamseldin AA, 1997, J SHELLFISH RES, V16, P487
   Sheppard Brennand H, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0011372
   Somero GN, 2010, J EXP BIOL, V213, P912, DOI 10.1242/jeb.037473
   Somero George N., 2005, Frontiers in Zoology, V2, P1, DOI 10.1186/1742-9994-2-1
   Somero GN, 2002, INTEGR COMP BIOL, V42, P780, DOI 10.1093/icb/42.4.780
   STEARNS SC, 1989, FUNCT ECOL, V3, P259, DOI 10.2307/2389364
   Stillman JH, 2003, SCIENCE, V301, P65, DOI 10.1126/science.1083073
   Storey KB, 2004, BIOL REV, V79, P207, DOI 10.1017/S1464793103006195
   Thompson EL, 2015, MOL ECOL, V24, P1248, DOI 10.1111/mec.13111
   Thompson JA, 2017, MAR ECOL PROG SER, V570, P127, DOI 10.3354/meps12109
   Tomanek L, 1999, J EXP BIOL, V202, P2925
   Tomanek L, 2014, J PROTEOMICS, V105, P92, DOI 10.1016/j.jprot.2014.04.009
   Tomanek L, 2010, J EXP BIOL, V213, P3559, DOI 10.1242/jeb.041228
   Wilkie EM, 2012, J EXP MAR BIOL ECOL, V420, P16, DOI 10.1016/j.jembe.2012.03.018
   Wolf PH, 1979, SUMMARY DAILY TEMPER
   Xie FL, 2012, PLANT MOL BIOL, V80, P75, DOI 10.1007/s11103-012-9885-2
   Zhang GF, 2016, ANNU REV ANIM BIOSCI, V4, P357, DOI 10.1146/annurev-animal-022114-110903
   Zhang GF, 2012, NATURE, V490, P49, DOI 10.1038/nature11413
   Zhong XX, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0150868
NR 59
TC 8
Z9 10
U1 1
U2 23
PU INTER-RESEARCH
PI OLDENDORF LUHE
PA NORDBUNTE 23, D-21385 OLDENDORF LUHE, GERMANY
SN 0171-8630
EI 1616-1599
J9 MAR ECOL PROG SER
JI Mar. Ecol.-Prog. Ser.
PD FEB 23
PY 2018
VL 589
BP 115
EP 127
DI 10.3354/meps12455
PG 13
WC Ecology; Marine & Freshwater Biology; Oceanography
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Marine & Freshwater Biology;
   Oceanography
GA FX7HI
UT WOS:000426258800009
DA 2025-01-10
ER

PT J
AU Roulin, AC
   Bourgeois, Y
   Stiefel, U
   Walser, JC
   Ebert, D
AF Roulin, Anne C.
   Bourgeois, Yann
   Stiefel, Urs
   Walser, Jean-Claude
   Ebert, Dieter
TI A Photoreceptor Contributes to the Natural Variation of Diapause
   Induction in <i>Daphnia magna</i>
SO MOLECULAR BIOLOGY AND EVOLUTION
LA English
DT Article
DE diapause; resting-stage; QTL mapping; association mapping; Daphnia
   magna; Rhodopsin
ID PHOTOPERIODIC INDUCTION; GEOGRAPHIC-VARIATION; SEXUAL REPRODUCTION;
   CLIMATIC ADAPTATION; EXPRESSION ANALYSIS; LATITUDINAL CLINE;
   GENETIC-VARIATION; LOCAL ADAPTATION; QTL; IDENTIFICATION
AB Diapause is an adaptation that allows organisms to survive harsh environmental conditions. In species occurring over broad habitat ranges, both the timing and the intensity of diapause induction can vary across populations, revealing patterns of local adaptation. Understanding the genetic architecture of this fitness-related trait would help clarify how populations adapt to their local environments. In the cyclical parthenogenetic crustacean Daphnia magna, diapause induction is a phenotypic plastic life history trait linked to sexual reproduction, as asexual females have the ability to switch to sexual reproduction and produce resting stages, their sole strategy for surviving habitat deterioration. We have previously shown that the induction of resting stage production correlates with changes in photoperiod that indicate the imminence of habitat deterioration and have identified a Quantitative Trait Locus (QTL) responsible for some of the variation in the induction of resting stages. Here, new data allows us to anchor the QTL to a large scaffold and then, using a combination of a new mapping panel, targeted association mapping and selection analysis in natural populations, to identify candidate genes within the QTL. Our results show that variation in a rhodopsin photoreceptor gene plays a significant role in the variation observed in resting stage induction. This finding provides a mechanistic explanation for the link between diapause and day-length perception that has been suggested in diverse arthropod taxa.
C1 [Roulin, Anne C.; Bourgeois, Yann; Stiefel, Urs; Ebert, Dieter] Univ Basel, Inst Zool, Vesalgasse 1, Basel, Switzerland.
   [Roulin, Anne C.] Univ Zurich, Inst Plant & Microbial Biol, Zollikerstr 107, Zurich, Switzerland.
   [Walser, Jean-Claude] Swiss Fed Inst Technol, Genet Divers Ctr, Univ Str 16, Zurich, Switzerland.
C3 University of Basel; University of Zurich; Swiss Federal Institutes of
   Technology Domain; ETH Zurich
RP Roulin, AC (corresponding author), Univ Basel, Inst Zool, Vesalgasse 1, Basel, Switzerland.; Roulin, AC (corresponding author), Univ Zurich, Inst Plant & Microbial Biol, Zollikerstr 107, Zurich, Switzerland.
EM anne.roulin@botinst.uzh.ch
RI ; Bourgeois, Yann/D-9938-2012; Ebert, Dieter/B-5502-2009
OI Roulin, Anne C./0000-0002-6668-3321; Walser,
   Jean-Claude/0000-0003-1513-0783; Bourgeois, Yann/0000-0002-1809-387X;
   Ebert, Dieter/0000-0003-2653-3772
FU Swiss National Science Foundation [PDFMP3_130479, 31003A_146462,
   PZ00P3_154724]; Swiss National Science Foundation (SNF) [PDFMP3_130479,
   PZ00P3_154724, 31003A_146462] Funding Source: Swiss National Science
   Foundation (SNF)
FX We would like to thank Jurgen Hottinger and Kristina Muller for
   laboratory support as well as Gilberto Bento and Elodie Burcklen for
   preparing the DNA for PacBio sequencing. We would also like to thank
   Gilberto Bento for helpful comments on the manuscript, Suzanne Zweizig
   for proofreading the manuscript and Mahendra Mariadassou for
   methodological advice. We also thank the two anonymous reviewers for
   their comments on the manuscript. The Swiss National Science Foundation
   supported this work (Grant PDFMP3_130479, 31003A_146462 and
   PZ00P3_154724).
CR Allison DB, 2002, AM J HUM GENET, V70, P575, DOI 10.1086/339273
   Altermatt F, 2008, OECOLOGIA, V157, P441, DOI 10.1007/s00442-008-1080-4
   ALTSCHUL SF, 1990, J MOL BIOL, V215, P403, DOI 10.1006/jmbi.1990.9999
   [Anonymous], SCIENCE
   [Anonymous], NATURE
   Au KF, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0046679
   Aulchenko YS, 2007, BIOINFORMATICS, V23, P1294, DOI 10.1093/bioinformatics/btm108
   Bell G, 2010, PHILOS T R SOC B, V365, P87, DOI 10.1098/rstb.2009.0150
   Bergland AO, 2014, PLOS GENET, V10, DOI 10.1371/journal.pgen.1004775
   Broman KW, 2003, BIOINFORMATICS, V19, P889, DOI 10.1093/bioinformatics/btg112
   Chen YS, 2013, J INSECT PHYSIOL, V59, P855, DOI 10.1016/j.jinsphys.2013.06.002
   Chenoweth SF, 2010, ANNU REV ECOL EVOL S, V41, P81, DOI 10.1146/annurev-ecolsys-102209-144657
   Coop G, 2010, GENETICS, V185, P1411, DOI 10.1534/genetics.110.114819
   Cooper David N, 2010, Hum Genomics, V4, P284
   Coulombe-Huntington J, 2009, PLOS GENET, V5, DOI 10.1371/journal.pgen.1000766
   Crawley J.M., 2013, The R Book
   Danecek P, 2011, BIOINFORMATICS, V27, P2156, DOI 10.1093/bioinformatics/btr330
   Deng HW, 1996, HEREDITY, V76, P449, DOI 10.1038/hdy.1996.67
   Denlinger DL, 2002, ANNU REV ENTOMOL, V47, P93, DOI 10.1146/annurev.ento.47.091201.145137
   Elshire RJ, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0019379
   Fielenbach N, 2008, GENE DEV, V22, P2149, DOI 10.1101/gad.1701508
   Frentiu FD, 2015, MOL BIOL EVOL, V32, P368, DOI 10.1093/molbev/msu304
   Fuller ZL, 2015, BMC GENOMICS, V16, DOI 10.1186/s12864-015-1712-0
   Gautier M, 2015, GENETICS, V201, P1555, DOI 10.1534/genetics.115.181453
   Gilbert JJ, 1998, ECOLOGY, V79, P1371, DOI 10.2307/176749
   Günther T, 2013, GENETICS, V195, P205, DOI 10.1534/genetics.113.152462
   Hahn DA, 2011, ANNU REV ENTOMOL, V56, P103, DOI 10.1146/annurev-ento-112408-085436
   HOULE D, 1992, GENETICS, V130, P195
   Jaquiéry J, 2014, PLOS GENET, V10, DOI 10.1371/journal.pgen.1004838
   Khan SG, 2002, NUCLEIC ACIDS RES, V30, P3624, DOI 10.1093/nar/gkf469
   Koch U, 2009, OECOLOGIA, V159, P317, DOI 10.1007/s00442-008-1216-6
   Larkin MA, 2007, BIOINFORMATICS, V23, P2947, DOI 10.1093/bioinformatics/btm404
   Le Trionnaire G, 2008, BIOL CELL, V100, P441, DOI 10.1042/BC20070135
   Lehmann P, 2014, INSECT MOL BIOL, V23, P566, DOI 10.1111/imb.12104
   McCarthy MI, 2008, HUM MOL GENET, V17, pR156, DOI 10.1093/hmg/ddn289
   Meuti ME, 2013, INTEGR COMP BIOL, V53, P131, DOI 10.1093/icb/ict023
   Montell C, 2012, TRENDS NEUROSCI, V35, P356, DOI 10.1016/j.tins.2012.03.004
   Nakanishi T, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0098363
   Palczewski K, 2006, ANNU REV BIOCHEM, V75, P743, DOI 10.1146/annurev.biochem.75.103004.142743
   Paolucci S, 2013, J EVOLUTION BIOL, V26, P705, DOI 10.1111/jeb.12113
   Parker DJ, 2016, G3-GENES GENOM GENET, V6, P1373, DOI 10.1534/g3.116.027870
   Pinheiro J., 2018, Linear and Nonlinear Mixed Effects Models
   Price AL, 2006, NAT GENET, V38, P904, DOI 10.1038/ng1847
   R Core Team R, 2013, R: A language and environment for statistical computing
   Rice P, 2000, TRENDS GENET, V16, P276, DOI 10.1016/S0168-9525(00)02024-2
   Roff Derek, 2002, pi
   Roulin AC, 2015, EVOLUTION, V69, P2747, DOI 10.1111/evo.12770
   Roulin AC, 2013, MOL ECOL, V22, P3567, DOI 10.1111/mec.12308
   Routtu J, 2014, BMC GENOMICS, V15, DOI 10.1186/1471-2164-15-1033
   Salminen TS, 2015, SCI REP-UK, V5, DOI 10.1038/srep11197
   Saunders DS, 2012, PHYSIOL ENTOMOL, V37, P207, DOI 10.1111/j.1365-3032.2012.00837.x
   Schmidt PS, 2008, P NATL ACAD SCI USA, V105, P16207, DOI 10.1073/pnas.0805485105
   Schmidt PS, 2005, EVOLUTION, V59, P1721, DOI 10.1111/j.0014-3820.2005.tb01821.x
   Seo S, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0076960
   Shepherd C, 2015, BMC MED GENET, V16, DOI 10.1186/s12881-015-0254-2
   Sim C, 2015, P NATL ACAD SCI USA, V112, P3811, DOI 10.1073/pnas.1502751112
   Sonnhammer ELL, 1995, GENE, V167, pGC1, DOI 10.1016/0378-1119(95)00714-8
   Stehlík J, 2008, J BIOL RHYTHM, V23, P129, DOI 10.1177/0748730407313364
   Stinchcombe JR, 2008, HEREDITY, V100, P158, DOI 10.1038/sj.hdy.6800937
   STROSS RG, 1965, SCIENCE, V150, P1462, DOI 10.1126/science.150.3702.1462
   STROSS RG, 1971, BIOL BULL, V140, P137, DOI 10.2307/1540033
   Syrová Z, 2003, CELL MOL LIFE SCI, V60, P2510, DOI 10.1007/s00018-003-3227-0
   Takahashi T, 2016, ZOOL SCI, V33, P106, DOI 10.2108/zs150068
   Terakita A, 2005, GENOME BIOL, V6, DOI 10.1186/gb-2005-6-3-213
   Tyukmaeva VI, 2011, ECOL EVOL, V1, P160, DOI 10.1002/ece3.14
   Vales MI, 2005, THEOR APPL GENET, V111, P1260, DOI 10.1007/s00122-005-0043-y
   van Kuilenburg ABP, 2010, HUM GENET, V128, P529, DOI 10.1007/s00439-010-0879-3
   Varela-Lasheras I, 2014, EVODEVO, V5, DOI 10.1186/2041-9139-5-16
   VEERMAN A, 1983, NATURE, V302, P248, DOI 10.1038/302248a0
   Veerman A, 2001, J INSECT PHYSIOL, V47, P1097, DOI 10.1016/S0022-1910(01)00106-8
   Visser M, 2012, GENOME RES, V22, P446, DOI 10.1101/gr.128652.111
   Wickham H, 2009, USE R, P1, DOI 10.1007/978-0-387-98141-3
   Williams KD, 2006, P NATL ACAD SCI USA, V103, P15911, DOI 10.1073/pnas.0604592103
   Winterhalter WE, 2007, EVOLUTION, V61, P1520, DOI 10.1111/j.1558-5646.2007.00127.x
   Xiong B, 2013, TRENDS NEUROSCI, V36, P652, DOI 10.1016/j.tins.2013.08.003
   Yuan HY, 2006, NUCLEIC ACIDS RES, V34, pW635, DOI 10.1093/nar/gkl236
NR 76
TC 20
Z9 21
U1 1
U2 28
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 DEC
PY 2016
VL 33
IS 12
BP 3194
EP 3204
DI 10.1093/molbev/msw200
PG 11
WC Biochemistry & Molecular Biology; Evolutionary Biology; Genetics &
   Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Evolutionary Biology; Genetics &
   Heredity
GA EC2FO
UT WOS:000387925300016
PM 27660296
OA Green Accepted, Bronze
DA 2025-01-10
ER

PT J
AU Kummu, M
   de Moel, H
   Ward, PJ
   Varis, O
AF Kummu, Matti
   de Moel, Hans
   Ward, Philip J.
   Varis, Olli
TI How Close Do We Live to Water? A Global Analysis of Population Distance
   to Freshwater Bodies
SO PLOS ONE
LA English
DT Article
ID WORLD; RESOURCES; LEVEL; MAPS
AB Traditionally, people have inhabited places with ready access to fresh water. Today, over 50% of the global population lives in urban areas, and water can be directed via tens of kilometres of pipelines. Still, however, a large part of the world's population is directly dependent on access to natural freshwater sources. So how are inhabited places related to the location of freshwater bodies today? We present a high-resolution global analysis of how close present-day populations live to surface freshwater. We aim to increase the understanding of the relationship between inhabited places, distance to surface freshwater bodies, and climatic characteristics in different climate zones and administrative regions. Our results show that over 50% of the world's population lives closer than 3 km to a surface freshwater body, and only 10% of the population lives further than 10 km away. There are, however, remarkable differences between administrative regions and climatic zones. Populations in Australia, Asia, and Europe live closest to water. Although populations in arid zones live furthest away from freshwater bodies in absolute terms, relatively speaking they live closest to water considering the limited number of freshwater bodies in those areas. Population distributions in arid zones show statistically significant relationships with a combination of climatic factors and distance to water, whilst in other zones there is no statistically significant relationship with distance to water. Global studies on development and climate adaptation can benefit from an improved understanding of these relationships between human populations and the distance to fresh water.
C1 [Kummu, Matti; Varis, Olli] Aalto Univ, Water & Dev Res Grp, Espoo, Finland.
   [de Moel, Hans; Ward, Philip J.] Vrije Univ Amsterdam, Inst Environm Studies, Amsterdam, Netherlands.
C3 Aalto University; Vrije Universiteit Amsterdam
RP Kummu, M (corresponding author), Aalto Univ, Water & Dev Res Grp, Espoo, Finland.
EM matti.kummu@iki.fi
RI de Moel, Hans/L-1311-2013; Varis, Olli/G-6506-2011; Ward,
   Philip/E-6208-2010; Kummu, Matti/C-4797-2011
OI Kummu, Matti/0000-0001-5096-0163; Ward, Philip/0000-0001-7702-7859;
   Varis, Olli/0000-0001-9231-4549; de Moel, Hans/0000-0002-6826-1974
FU Maa- ja vesitekniikan tuki ry; Aalto University; Dutch research
   programme "Climate changes Spatial Planning"; Dutch research programme
   "Knowledge for Climate."
FX This work was funded by the following research grants: Maa- ja
   vesitekniikan tuki ry, postdoctoral funds of Aalto University, Dutch
   research programme "Climate changes Spatial Planning" and Dutch research
   programme "Knowledge for Climate." The funders had no role in study
   design, data collection and analysis, decision to publish, or
   preparation of the manuscript.
CR Alcamo J, 2007, HYDROLOG SCI J, V52, P247, DOI 10.1623/hysj.52.2.247
   [Anonymous], 2010, World Urbanization Prospects: The 2009 Revision
   [Anonymous], 2008, World Population Prospects: The 2008 Revision
   [Anonymous], 2008, Climate Change and the Global Harvest: Impacts of El Nino and Other Oscillations on Agroecosystems
   [Anonymous], UN WORLD MACR REG CO
   [Anonymous], 2007, Groundwater: a global assessment of scale and significance, DOI DOI 10.1111/J.1461-9563.2008.00379.X
   [Anonymous], 2017, PROGR DRINKING WATER
   [Anonymous], 2009, World development report 2009
   BISWAS AK, 1970, HIST HYDROLOGY, pR12
   Cai XM, 2002, WATER INT, V27, P159, DOI 10.1080/02508060208686989
   *CIESIN, 2009, GLOB RUR URB MAPP PR
   *CIESIN, 2009, GRIDD POP WORLD GPW
   de Fraiture C, 2007, WATER RESOUR MANAG, V21, P185, DOI 10.1007/s11269-006-9048-9
   Dettinger MD, 2000, J HYDROMETEOROL, V1, P289, DOI 10.1175/1525-7541(2000)001<0289:GCOSFS>2.0.CO;2
   GLEICK PETER H., 2008, The World's Water 2008-2009: The Biennial Report on Freshwater Resources
   Goldewijk KK, 2010, HOLOCENE, V20, P565, DOI 10.1177/0959683609356587
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Kirshen P., 2007, ADAPTATION OPTIONS C
   Kummu M, 2011, APPL GEOGR, V31, P495, DOI 10.1016/j.apgeog.2010.10.009
   Kummu M, 2010, ENVIRON RES LETT, V5, DOI 10.1088/1748-9326/5/3/034006
   *LANDSCAN TM, 2007, GLOB POP DAT 2007
   Lehner B, 2004, J HYDROL, V296, P1, DOI 10.1016/j.jhydrol.2004.03.028
   Lehner B., 2008, EoS Transactions, V89, P93, DOI [DOI 10.1029/2008EO100001, 10.1029/2008EO100001]
   Luck GW, 2007, BIOL REV, V82, P607, DOI 10.1111/j.1469-185X.2007.00028.x
   McCool S.F., 2008, Water and People: Challenges at the Interface of Symbolic and Utilitarian Values
   MCCORRISTON J, 1991, AM ANTHROPOL, V93, P46, DOI 10.1525/aa.1991.93.1.02a00030
   Nikula J., 2008, Modern Myths of the Mekong - A Critical Review of Water and Development Concepts, Principles and Policies, P27
   Oki T, 2006, SCIENCE, V313, P1068, DOI 10.1126/science.1128845
   Potere D, 2009, INT J REMOTE SENS, V30, P6531, DOI 10.1080/01431160903121134
   Rosegrant M.W., 2002, World Water and Food to 2025: Dealing with Scarcity
   Rubel F, 2010, METEOROL Z, V19, P135, DOI 10.1127/0941-2948/2010/0430
   Schneider A, 2009, ENVIRON RES LETT, V4, DOI 10.1088/1748-9326/4/4/044003
   Siebert S, 2010, HYDROL EARTH SYST SC, V14, P1863, DOI 10.5194/hess-14-1863-2010
   Small C, 2003, J COASTAL RES, V19, P584
   SMALL C, 2002, ENV HAZARDS, V3, P93
   Trabucco A., 2009, GLOBAL ARIDITY INDEX
   *USGS, 2001, RIV WORLD PART GLOB
   *USGS, 2001, ADM BOUND PART GLOB
   Varis O, 2006, INT J WATER RESOUR D, V22, P377, DOI 10.1080/07900620600684550
   Vörösmarty CJ, 2000, SCIENCE, V289, P284, DOI 10.1126/science.289.5477.284
   Ward PJ, 2010, ENVIRON RES LETT, V5, DOI 10.1088/1748-9326/5/4/044011
   Ward PJ, 2010, GEOPHYS RES LETT, V37, DOI 10.1029/2010GL043215
   *WORLD DAT BANK 2, 1980, GLOB RIV NETW
   Zhou Y, 2005, WATER RESOUR RES, V41, DOI 10.1029/2004WR003749
   ,, 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 45
TC 209
Z9 239
U1 3
U2 89
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 JUN 8
PY 2011
VL 6
IS 6
AR e20578
DI 10.1371/journal.pone.0020578
PG 13
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA 777JJ
UT WOS:000291611500032
PM 21687675
OA Green Published, gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Teixeira, E
   Fischer, G
   van Velthuizen, H
   van Dingenen, R
   Dentener, F
   Mills, G
   Walter, C
   Ewert, F
AF Teixeira, Edmar
   Fischer, Guenther
   van Velthuizen, Harrij
   van Dingenen, Rita
   Dentener, Frank
   Mills, Gina
   Walter, Christof
   Ewert, Frank
TI Limited potential of crop management for mitigating surface ozone
   impacts on global food supply
SO ATMOSPHERIC ENVIRONMENT
LA English
DT Article
DE AEZ; Air quality; Climate adaptation; Food security; Ozone pollution;
   Mitigation
ID AGRICULTURAL CROPS; TROPOSPHERIC OZONE; MODERN WHEAT; EUROPE; CULTIVARS;
   GROWTH; YIELD; SENSITIVITY; EXPOSURE; STANDARD
AB Surface ozone (O-3) is a potent phytotoxic air pollutant that reduces the productivity of agricultural crops. Growing use of fossil fuel and climate change are increasing O-3 concentrations to levels that threaten food supply. Historically, farmers have successfully adapted agricultural practices to cope with changing environments. However, high O-3 concentrations are a new threat to food production and possibilities for adaptation are not well understood. We simulate the impact of ozone damage on four key crops (wheat, maize, rice and soybean) on a global scale and assess the effectiveness of adaptation of agricultural practices to minimize ozone damage. As O-3 concentrations have a strong seasonal and regional pattern, the adaptation options assessed refer to shifting crop calendars through changing sowing dates, applying irrigation and using crop varieties with different growth cycles. Results show that China, India and the United States are currently by far the most affected countries, bearing more than half of all global losses and threatened areas. Irrigation largely affects ozone exposure but local impacts depend on the seasonality of emissions and climate. Shifting crop calendars can reduce regional O-3 damage for specific crop-location combinations (e.g. up to 25% for rain-fed soybean in India) but has little implication at the global level. Considering the limited benefits of adaptation, mitigation of O-3 precursors remains the main option to secure regional and global food production. (C) 2011 Elsevier Ltd. All rights reserved.
C1 [Teixeira, Edmar; Fischer, Guenther; van Velthuizen, Harrij] Int Inst Appl Syst Anal, Land Use Change & Agr Program, LUC IIASA, A-2361 Laxenburg, Austria.
   [van Dingenen, Rita; Dentener, Frank] European Commiss, Joint Res Ctr, Inst Environm & Sustainabil, Ispra, Italy.
   [Mills, Gina] Ctr Ecol & Hydrol, Bangor, Gwynedd, Wales.
   [Ewert, Frank] Wageningen Univ, Dept Plant Sci, Wageningen, Netherlands.
   [Ewert, Frank] Univ Bonn, Inst Crop Sci & Resource Conservat, D-5300 Bonn, Germany.
C3 International Institute for Applied Systems Analysis (IIASA); European
   Commission Joint Research Centre; EC JRC ISPRA Site; UK Centre for
   Ecology & Hydrology (UKCEH); Wageningen University & Research;
   University of Bonn
RP Teixeira, E (corresponding author), New Zealand Inst Plant & Food Res Ltd, Christchurch Mail Ctr, Private Bag 4704, Christchurch 8140, New Zealand.
EM Edmar.Teixeira@plantandfood.co.nz
RI Ewert, Frank/AER-0007-2022; Van Dingenen, Rita/AAI-3197-2021; Dentener,
   Frank/ABW-0482-2022; Teixeira, Edmar/K-1238-2016; Mills,
   Gina/E-4540-2010
OI Van Dingenen, Rita/0000-0003-2521-4972; Ewert,
   Frank/0000-0002-4392-8154; Teixeira, Edmar/0000-0002-4835-0590; Mills,
   Gina/0000-0001-9870-2868
FU Defra [AQ0810, AQ0816]; NERC
FX The authors would like to thank Prof. Hakan Pleijel, Dr. Markus Amann,
   Dr. Chris Heyes and Dr. Lisa Emberson for invaluable discussions on
   different topics developed in this paper. Gina Mills would like to thank
   Defra (contracts AQ0810 and AQ0816) and NERC for funding. This study is
   part of the EIGER-Ag project, a collaboration between Unilever,
   Wageningen University and IIASA. We also thank two anonymous reviewers
   for their helpful comments which improved the final version of this
   manuscript.
CR Akhtar N, 2010, ENVIRON POLLUT, V158, P2970, DOI 10.1016/j.envpol.2010.05.026
   Amann Markus., 2008, GAINS ASIA TOOL COMB
   [Anonymous], 2008, DTSCH ARZTEBLATT
   [Anonymous], ATMOSPHERIC CHEM PHY
   [Anonymous], IIASAS 2007 PROBABIL
   [Anonymous], MANUAL METHODOLOGIES
   Aunan K, 2000, AMBIO, V29, P294, DOI 10.1639/0044-7447(2000)029[0294:SOICAI]2.0.CO;2
   Biswas DK, 2008, J EXP BOT, V59, P951, DOI 10.1093/jxb/ern022
   BOONSPRINS ER, 1993, CROP SPECIFIC PARAME
   Burkey KO, 2009, FIELD CROP RES, V111, P207, DOI 10.1016/j.fcr.2008.12.005
   Cofala J, 2007, ATMOS ENVIRON, V41, P8486, DOI 10.1016/j.atmosenv.2007.07.010
   Dentener F, 2005, ATMOS CHEM PHYS, V5, P1731, DOI 10.5194/acp-5-1731-2005
   Dentener F, 2006, ENVIRON SCI TECHNOL, V40, P3586, DOI 10.1021/es0523845
   Ellingsen K., 2008, Atmos. Chem. Phys. Discuss, V8, P2163, DOI DOI 10.5194/ACPD-8-2163-2008
   Emberson LD, 2009, ATMOS ENVIRON, V43, P1945, DOI 10.1016/j.atmosenv.2009.01.005
   *FAOSTAT, 2009, CONS CROP PRIM EQ
   FAOSTAT, 2009, PROD STAT
   Feng ZZ, 2009, ATMOS ENVIRON, V43, P1510, DOI 10.1016/j.atmosenv.2008.11.033
   Fischer G., 2002, RR0202 IIASA
   Fuhrer J, 2003, ENVIRON INT, V29, P141, DOI 10.1016/S0160-4120(02)00157-5
   Fuhrer J, 1997, ENVIRON POLLUT, V97, P91, DOI 10.1016/S0269-7491(97)00067-5
   Fuhrer J, 2009, NATURWISSENSCHAFTEN, V96, P173, DOI 10.1007/s00114-008-0468-7
   Heath RL, 2009, ATMOS ENVIRON, V43, P2919, DOI 10.1016/j.atmosenv.2009.03.011
   KEYZER MA, 2005, DATA SET CHINAGRO WE
   Krol M, 2005, ATMOS CHEM PHYS, V5, P417, DOI 10.5194/acp-5-417-2005
   Lelieveld J, 2000, J GEOPHYS RES-ATMOS, V105, P3531, DOI 10.1029/1999JD901011
   Long SP, 2005, PHILOS T R SOC B, V360, P2011, DOI 10.1098/rstb.2005.1749
   Mauzerall DL, 2001, ANNU REV ENERG ENV, V26, P237, DOI 10.1146/annurev.energy.26.1.237
   Mills G, 2007, ATMOS ENVIRON, V41, P2630, DOI 10.1016/j.atmosenv.2006.11.016
   Morgan PB, 2006, NEW PHYTOL, V170, P333, DOI 10.1111/j.1469-8137.2006.01679.x
   Musselman RC, 2007, THESCIENTIFICWORLDJO, V7, P15, DOI 10.1100/tsw.2007.24
   Paoletti E, 2007, ENVIRON POLLUT, V150, P85, DOI 10.1016/j.envpol.2007.06.037
   Pleijel H, 2007, ATMOS ENVIRON, V41, P3022, DOI 10.1016/j.atmosenv.2006.12.002
   Rai R, 2010, ATMOS ENVIRON, V44, P4272, DOI 10.1016/j.atmosenv.2010.06.022
   Reidsma P, 2007, CLIMATIC CHANGE, V84, P403, DOI [10.1007/s10584-007-9242-7, 10.1007/S10584-007-9242-7]
   Sarkar A, 2010, ENVIRON EXP BOT, V69, P328, DOI 10.1016/j.envexpbot.2010.04.016
   Schmidhuber J, 2007, P NATL ACAD SCI USA, V104, P19703, DOI 10.1073/pnas.0701976104
   Shetty P, 2006, P NUTR SOC, V65, P7, DOI 10.1079/PNS2005479
   Siebert S, 2005, HYDROL EARTH SYST SC, V9, P535, DOI 10.5194/hess-9-535-2005
   Slingo JM, 2005, PHILOS T R SOC B, V360, P1983, DOI 10.1098/rstb.2005.1755
   Soja G, 2000, ENVIRON POLLUT, V109, P517, DOI 10.1016/S0269-7491(00)00055-5
   Van Dingenen R, 2009, ATMOS ENVIRON, V43, P604, DOI 10.1016/j.atmosenv.2008.10.033
   Wang XK, 2007, ENVIRON POLLUT, V147, P394, DOI 10.1016/j.envpol.2006.05.006
   Wang YH, 1998, J GEOPHYS RES-ATMOS, V103, P31123, DOI 10.1029/1998JD100004
NR 44
TC 67
Z9 70
U1 1
U2 67
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 1352-2310
EI 1873-2844
J9 ATMOS ENVIRON
JI Atmos. Environ.
PD MAY
PY 2011
VL 45
IS 15
BP 2569
EP 2576
DI 10.1016/j.atmosenv.2011.02.002
PG 8
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA 757FA
UT WOS:000290069400013
DA 2025-01-10
ER

PT S
AU Sullivan, AL
AF Sullivan, A. L.
BE Sparks, DL
TI GRASSLAND FIRE MANAGEMENT IN FUTURE CLIMATE
SO ADVANCES IN AGRONOMY, VOL 106
SE Advances in Agronomy
LA English
DT Review; Book Chapter
ID BIODIVERSITY CONSERVATION; FOREST; GROWTH; BEHAVIOR; SPREAD; FUEL;
   PREDICTION; ALGORITHM; INDEX; RISK
AB A thorough understanding of the behavior of fire in grasslands is critical to the minimization of the impact of fires on agricultural and pastoral land as well as the successful management of the health, robustness, and species diversity of native grasslands. This is also necessary to understand the impact that a changing climate will have on these fires and the subsequent impacts and adaptation steps needed to protect valuable farmland and grassland ecosystems in the future, a challenge that will soon be facing all land managers. While a number of studies have investigated the impact of climate change on fire danger indices, the fire danger systems used in Australia are actually fire weather indices that provide no information about the likely impact of climate change on fire behavior.
   This chapter summarizes the state of the knowledge of fire behavior in grass fuels and discusses in detail the factors that influence the behavior of grassfires. The CSIRO Grassland Fire Spread Meter is the recommended operational system for the prediction of grassfire behavior in all Australian grass types. The system is used to assess the impact of a high-emission climate change scenario upon the likely behavior of grassfires throughout the fire season for three major pastoral and agricultural regions of eastern Australia in 2020 and 2050. It was found that mean fire rate of forward spread in ungrazed/natural pastures will increase by a maximum of 10% by 2020 and by 32% by 2050 in southeastern Australia. The implications for grassland management strategies and possible climate adaptation pathways are explored.
C1 [Sullivan, A. L.] CSIRO Sustainable Ecosyst, Canberra, ACT, Australia.
   [Sullivan, A. L.] CSIRO Climate Adaptat Flagship, Canberra, ACT, Australia.
C3 Commonwealth Scientific & Industrial Research Organisation (CSIRO);
   Commonwealth Scientific & Industrial Research Organisation (CSIRO)
RP Sullivan, AL (corresponding author), CSIRO Sustainable Ecosyst, Canberra, ACT, Australia.
RI Sullivan, Andrew/E-9427-2010
OI Sullivan, Andrew/0000-0002-8038-8724
CR *ABS, 2008, 2008 YB AUSTR ABS
   Adcock D. P., 2005, THESIS U ADELAIDE
   Andersen AN, 2005, AUSTRAL ECOL, V30, P155, DOI 10.1111/j.1442-9993.2005.01441.x
   Andrews P., 1986, INT194 USDA FOR SERV
   [Anonymous], 2006, Energy and Environment, DOI DOI 10.1260/095830506776318804
   [Anonymous], 1984, fuel subsystem
   [Anonymous], 100 COMM DEP NAT DEV
   [Anonymous], 2001, 103 BTE
   [Anonymous], DEV BUSHFIRE SPREAD
   Blong R, 2005, ISSUES RISK SCI
   Bradstock R., 2002, Flammable Australia: the fire regimes and biodiversity of a continent
   Briz S, 2003, REMOTE SENS ENVIRON, V86, P19, DOI 10.1016/S0034-4257(03)00064-6
   BURROWS N, 1991, J ARID ENVIRON, V20, P189, DOI 10.1016/S0140-1963(18)30708-0
   Burrows ND, 2001, INT J WILDLAND FIRE, V10, P137, DOI 10.1071/WF01005
   Byram G.M., 1959, Forest fire, V2nd, P90
   *CFA, 1999, CFA GRASSL CUR GUID
   Chan KY, 1996, AUST J AGR RES, V47, P479, DOI 10.1071/AR9960479
   Chandler C., 1983, FIRE FORESTRY, V1
   CHATTO K, 1997, 46 CRESW RES STAT FI
   Cheney N. P., 1995, Landscape Fires '93: Proceedings of an Australian Bushfire Conference, Perth, Western Australia, 27-29 September 1993., P3
   Cheney N.P., 1990, CSF35A RIRDC, P24
   CHENEY NP, 1993, INT J WILDLAND FIRE, V3, P31, DOI 10.1071/WF9930031
   Cheney NP, 1997, INT J WILDLAND FIRE, V7, P1, DOI 10.1071/WF9970001
   Cheney NP, 1995, INT J WILDLAND FIRE, V5, P237, DOI 10.1071/WF9950237
   Cheney NP, 1998, INT J WILDLAND FIRE, V8, P1, DOI 10.1071/WF9980001
   Cheney P, 2008, GRASSFIRES: FUEL, WEATHER AND FIRE BEHAVIOUR, 2ND EDITION, P1
   Coleman JR, 1996, SIMULATION, V67, P230, DOI 10.1177/003754979606700402
   CROOKS S, 2009, AUSTR GRAINS 09 1
   *CSIRO, 1997, CSIRO MOD MCARTH MK
   *CSIRO, 1996, CSIRO FIR SPREAD FIR
   *CSIRO, 1997, CSIRO FIR SPREAD MET
   CSIRO, 1997, CSIRO Grassland Fire Spread Meter. Cardboard meter
   Dennison PE, 2009, REMOTE SENS ENVIRON, V113, P1646, DOI 10.1016/j.rse.2009.03.010
   Dilley AC, 2004, INT J REMOTE SENS, V25, P3913, DOI 10.1080/01431160410001698889
   Dios JRMD, 2008, IMAGE VISION COMPUT, V26, P550, DOI 10.1016/j.imavis.2007.07.002
   Finnigan J, 2000, ANNU REV FLUID MECH, V32, P519, DOI 10.1146/annurev.fluid.32.1.519
   Giglio L, 2008, REMOTE SENS ENVIRON, V112, P3055, DOI 10.1016/j.rse.2008.03.003
   Gill AM., 1991, Proceedings of Conference on Bushfire Modelling and Fire Danger Rating Systems, P137
   GILL AM, 1981, FIRE AUSTR BIOTA, P244
   GRIFFIN GF, 1983, J ENVIRON MANAGE, V17, P311
   Günay O, 2009, FIRE SAFETY J, V44, P860, DOI 10.1016/j.firesaf.2009.04.003
   HENNESSY K, 2005, 1 PMB CSIRO MAR ATM
   Kant Y, 2000, INFRARED PHYS TECHN, V41, P29, DOI 10.1016/S1350-4495(99)00053-5
   Kant Y, 2002, INFRARED PHYS TECHN, V43, P383, DOI 10.1016/S1350-4495(02)00128-7
   Kemp E.M., 1981, FIRE AUSTR BIOTA, P3
   Kremens R, 2003, INT J WILDLAND FIRE, V12, P237, DOI 10.1071/WF02055
   Lucas C., 2007, BUSHFIRE WEATHER SE, DOI DOI 10.25919/5-31C82EE0A4C
   Luke R.H., 1978, Bushfires in Australia
   MarsdenSmedley JB, 1995, INT J WILDLAND FIRE, V5, P215, DOI 10.1071/WF9950215
   Matthews S, 2006, INT J WILDLAND FIRE, V15, P155, DOI 10.1071/WF05063
   MATTHEWS S, 2010, INT J WILDL IN PRESS, V19
   MCARTHUR AG, 1962, 80 COMM DEP NAT DEV
   MCARTHUR AG, 1965, P 4 C I FOR AUSTR HO
   MCINNES KL, 2004, C0919 CSIRO ATM RES
   Moore R., 1970, Australian grasslands
   MOORE RM, 1993, NATURAL GRASSLANDS E, P315
   Nicholls N, 2003, GEOPHYS RES LETT, V30, DOI 10.1029/2003GL017037
   NOBLE IR, 1980, AUST J ECOL, V5, P201, DOI 10.1111/j.1442-9993.1980.tb01243.x
   Noble J. C., 1991, International Journal of Wildland Fire, V1, P189, DOI 10.1071/WF9910189
   Noble J. C., 1993, Rangeland Journal, V15, P270, DOI 10.1071/RJ9930270
   PALTRIDGE GW, 1988, REMOTE SENS ENVIRON, V25, P381, DOI 10.1016/0034-4257(88)90110-1
   PARROTT R T, 1970, Australian Journal of Experimental Agriculture and Animal Husbandry, V10, P67, DOI 10.1071/EA9700067
   Pitman AJ, 2007, CLIMATIC CHANGE, V84, P383, DOI 10.1007/s10584-007-9243-6
   Plucinski MP, 2007, A0701 CRC
   Pozo D, 1997, REMOTE SENS ENVIRON, V60, P111, DOI 10.1016/S0034-4257(96)00117-4
   Pyne StephenJ., 1991, Burning Bush: A Fire History of Australia
   ROTHERMEL RC, 1972, INT115 UT USDA FOR S
   Russell-Smith J, 2007, INT J WILDLAND FIRE, V16, P361, DOI 10.1071/WF07018
   San-Miguel-Ayanz J, 2005, NAT HAZARDS, V35, P361, DOI 10.1007/s11069-004-1797-2
   SMITH JMB, 1979, NATURAL LEGACY ECOLO, P13
   [Solomon S. IPCC IPCC], 2007, CLIMATE CHANGE 2007
   Springett B. P, 1979, NATURAL LEGACY ECOLO, P90
   Suppiah R, 2007, AUST METEOROL MAG, V56, P131
   TOLHURST K, 2008, REV EFFECT FARMING P
   Tolhurst K, 2008, AUST J EMERG MANAG, V23, P47
   Wang LL, 2008, AGR FOREST METEOROL, V148, P1767, DOI 10.1016/j.agrformet.2008.06.005
   Wang WT, 2007, REMOTE SENS ENVIRON, V108, P163, DOI 10.1016/j.rse.2006.11.009
   Williams RJ, 2003, INT J WILDLAND FIRE, V12, P391, DOI 10.1071/WF03025
   Williams RJ, 1998, INT J WILDLAND FIRE, V8, P227, DOI 10.1071/WF9980227
   WILSON AAG, 1988, CAN J FOREST RES, V18, P682, DOI 10.1139/x88-104
NR 80
TC 20
Z9 21
U1 3
U2 41
PU ELSEVIER ACADEMIC PRESS INC
PI SAN DIEGO
PA 525 B STREET, SUITE 1900, SAN DIEGO, CA 92101-4495 USA
SN 0065-2113
BN 978-0-12-381035-9
J9 ADV AGRON
JI Adv. Agron.
PY 2010
VL 106
BP 173
EP 208
DI 10.1016/S0065-2113(10)06005-0
PG 36
WC Agronomy
WE Book Citation Index – Science (BKCI-S); Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA BOL68
UT WOS:000276955800005
DA 2025-01-10
ER

PT J
AU Neu, A
   Fischer, K
AF Neu, Anika
   Fischer, Klaus
TI Indications for rapid evolution of trait means and thermal plasticity in
   range-expanding populations of a butterfly
SO JOURNAL OF EVOLUTIONARY BIOLOGY
LA English
DT Article
DE cold tolerance; counter-gradient variation; genotype-environment
   interaction; heat tolerance; local adaptation; phenotypic plasticity;
   Pieris mannii; range expansion
ID PIERIS-MANNII MAYER; REPEATED COLD-EXPOSURE; PHENOTYPIC PLASTICITY;
   ADAPTIVE PLASTICITY; GENE-EXPRESSION; TOLERANCE; TEMPERATURE;
   DROSOPHILA; EXPANSION; RESPONSES
AB Currently, poleward range expansions are observed in many taxa, often in response to anthropogenic climate change. At the expanding front, populations likely face cooler and more variable temperature conditions, imposing thermal selection. This may result in changes in trait means or plasticity, the relative contribution of which is not well understood. We, here, investigate evolutionary change in range-expanding populations of the butterfly Pieris mannii, by comparing populations from the core and the newly established northern range under laboratory conditions. We observed both changes in trait means and in thermal reaction norms. Range-expanding populations showed a more rapid development, potentially indicative of counter-gradient variation and an increased cold tolerance compared with core populations. Genotype-environment interactions prevailed in all associated traits, such that the above differences were restricted to cooler environmental conditions. In range-expanding populations, plasticity was decreased in developmental traits enabling relatively rapid growth even under cooler conditions but increased in cold tolerance arguably promoting higher activity under thermally challenging conditions. Notably, these changes must have occurred within a time period of ca. 10 years only. Our results suggest, in line with contemporary theory, that the evolution of plasticity may play a hitherto underestimated role for adaptation to climatic variation. However, rather than generally increased or decreased levels of plasticity, our results indicate fine-tuned, trait-specific evolutionary responses to increase fitness in novel environments.
C1 [Neu, Anika; Fischer, Klaus] Univ Greifswald, Museum & Inst Zool, D-17489 Greifswald, Germany.
   [Fischer, Klaus] Univ Koblenz Landau, Inst Integrated Nat Sci, Dept Biol, Koblenz, Germany.
C3 Universitat Greifswald; University of Koblenz & Landau
RP Neu, A (corresponding author), Univ Greifswald, Museum & Inst Zool, D-17489 Greifswald, Germany.
EM anika.neu@uni-greifswald.de
OI Fischer, Klaus/0000-0002-2871-246X; Neu, Anika/0000-0002-4165-9210
CR Andersen JL, 2015, FUNCT ECOL, V29, P55, DOI 10.1111/1365-2435.12310
   Angilletta MJ, 2009, BIO HABIT, P1, DOI 10.1093/acprof:oso/9780198570875.001.1
   Angilletta MJ, 2003, TRENDS ECOL EVOL, V18, P234, DOI 10.1016/S0169-5347(03)00087-9
   [Anonymous], 2011, Distribution atlas of butterflies in Europe
   Carbonell JA, 2020, ECOLOGY, V101, DOI 10.1002/ecy.3134
   ATKINSON D, 1994, ADV ECOL RES, V25, P1, DOI 10.1016/S0065-2504(08)60212-3
   Batz ZA, 2020, EVOLUTION, V74, P1451, DOI 10.1111/evo.14029
   Bauerfeind SS, 2014, POPUL ECOL, V56, P239, DOI 10.1007/s10144-013-0409-y
   Bolker BM, 2009, TRENDS ECOL EVOL, V24, P127, DOI 10.1016/j.tree.2008.10.008
   Bowler K, 2008, BIOL REV, V83, P339, DOI 10.1111/j.1469-185X.2008.00046.x
   Bozinovic F, 2014, COMP BIOCHEM PHYS A, V178, P46, DOI 10.1016/j.cbpa.2014.08.009
   Breed GA, 2013, NAT CLIM CHANGE, V3, P142, DOI [10.1038/nclimate1663, 10.1038/NCLIMATE1663]
   BRETT JR, 1956, Q REV BIOL, V31, P75, DOI 10.1086/401257
   Bridle JR, 2007, TRENDS ECOL EVOL, V22, P140, DOI 10.1016/j.tree.2006.11.002
   Buckley LB, 2012, FUNCT ECOL, V26, P969, DOI 10.1111/j.1365-2435.2012.01969.x
   Chen IC, 2011, SCIENCE, V333, P1024, DOI 10.1126/science.1206432
   Chevin LM, 2011, J EVOLUTION BIOL, V24, P1462, DOI 10.1111/j.1420-9101.2011.02279.x
   Chevin LM, 2017, PHILOS T R SOC B, V372, DOI 10.1098/rstb.2016.0138
   Chuang A, 2016, GLOBAL CHANGE BIOL, V22, P494, DOI 10.1111/gcb.13107
   Clark MS, 2008, J COMP PHYSIOL B, V178, P917, DOI 10.1007/s00360-008-0286-4
   Davidson AM, 2011, ECOL LETT, V14, P419, DOI 10.1111/j.1461-0248.2011.01596.x
   de Jong MA, 2018, J EVOLUTION BIOL, V31, P636, DOI 10.1111/jeb.13247
   Deere JA, 2006, J INSECT PHYSIOL, V52, P693, DOI 10.1016/j.jinsphys.2006.03.009
   Diamond SE, 2017, BIOL J LINN SOC, V121, P248, DOI 10.1093/biolinnean/blw047
   Donelson JM, 2019, PHILOS T R SOC B, V374, DOI 10.1098/rstb.2018.0186
   Eierman LE, 2016, J HERED, V107, P90, DOI 10.1093/jhered/esv057
   Fischer K, 2010, CLIM RES, V43, P17, DOI 10.3354/cr00892
   Fischer K, 2021, HEREDITY, V126, P23, DOI 10.1038/s41437-020-0338-4
   Fischer K, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0015284
   Franke K, 2019, BMC EVOL BIOL, V19, DOI 10.1186/s12862-019-1362-y
   Geier Thomas, 2016, Nachrichten des Entomologischen Vereins Apollo, V37, P27
   Gerken AR, 2016, J THERM BIOL, V59, P77, DOI 10.1016/j.jtherbio.2016.04.004
   Gerken AR, 2015, P NATL ACAD SCI USA, V112, P4399, DOI 10.1073/pnas.1503456112
   Gunderson AR, 2015, P ROY SOC B-BIOL SCI, V282, DOI 10.1098/rspb.2015.0401
   Hallsson LR, 2012, J EVOLUTION BIOL, V25, P1275, DOI 10.1111/j.1420-9101.2012.02512.x
   Halsch C.A., 2021, PNAS, V118, P1, DOI [DOI 10.1101/2020.03.09, 10.1101/2020.03.09.984328, DOI 10.1101/2020.03.09.984328]
   Hardie DC, 2010, ENVIRON REV, V18, P1, DOI 10.1139/A09-014
   Hendry AP, 2016, J HERED, V107, P25, DOI 10.1093/jhered/esv060
   Hensle J., 2015, ATALANTA-REV LET BAR, V47, P1
   Hensle Juergen, 2017, Atalanta (Marktleuthen), V48, P7
   Hodgson MJ, 2019, J THERM BIOL, V83, P178, DOI 10.1016/j.jtherbio.2019.05.016
   Jones PD, 1999, REV GEOPHYS, V37, P173, DOI 10.1029/1999RG900002
   Kelly M, 2019, PHILOS T R SOC B, V374, DOI 10.1098/rstb.2018.0176
   Kingsolver JG, 2003, INTEGR COMP BIOL, V43, P470, DOI 10.1093/icb/43.3.470
   Kleckova I, 2014, J THERM BIOL, V41, P50, DOI 10.1016/j.jtherbio.2014.02.002
   Kratochwill Michael, 2011, Beitraege zur Bayerischen Entomofaunistik, V11, P9
   Lafranchis T., 2015, VIE PAPILLONS ECOLOG
   Lancaster LT, 2016, MOL ECOL, V25, P1141, DOI 10.1111/mec.13548
   Lancaster LT, 2015, J BIOGEOGR, V42, P1953, DOI 10.1111/jbi.12553
   Lande R, 2015, MOL ECOL, V24, P2038, DOI 10.1111/mec.13037
   Leonard AM, 2020, BMC EVOL BIOL, V20, DOI 10.1186/s12862-020-1589-7
   Levis NA, 2016, TRENDS ECOL EVOL, V31, P563, DOI 10.1016/j.tree.2016.03.012
   MacLean HJ, 2016, OECOLOGIA, V181, P107, DOI 10.1007/s00442-016-3561-1
   Manenti T, 2015, J EVOLUTION BIOL, V28, P2078, DOI 10.1111/jeb.12735
   Marshall KE, 2012, J EXP BIOL, V215, P1607, DOI 10.1242/jeb.059956
   Marshall KE, 2010, P ROY SOC B-BIOL SCI, V277, P963, DOI 10.1098/rspb.2009.1807
   Matesanz S, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0044955
   Merilä J, 2014, EVOL APPL, V7, P1, DOI 10.1111/eva.12137
   Murren CJ, 2015, HEREDITY, V115, P293, DOI 10.1038/hdy.2015.8
   Neu A, 2021, J BIOGEOGR, V48, P3016, DOI 10.1111/jbi.14258
   Nguyen AD, 2019, AM NAT, V194, pE151, DOI 10.1086/705939
   Nicotra AB, 2015, ECOL EVOL, V5, P634, DOI 10.1002/ece3.1329
   Nurnberger B., 2013, Encyclopedia of Biodiversity, V2, P714, DOI [10.1016/B978-0-12-384719-5.00038-1, DOI 10.1016/B978-0-12-384719-5.00038-1]
   Overgaard J, 2011, AM NAT, V178, pS80, DOI 10.1086/661780
   Paehler Rudolf, 2016, Melanargia, V28, P117
   Petavy G, 2001, J THERM BIOL, V26, P29, DOI 10.1016/S0306-4565(00)00022-X
   Phillips BL, 2010, ECOLOGY, V91, P1617, DOI 10.1890/09-0910.1
   Pinsky ML, 2020, ANNU REV MAR SCI, V12, P153, DOI 10.1146/annurev-marine-010419-010916
   Pintanel P, 2019, J BIOGEOGR, V46, P1664, DOI 10.1111/jbi.13596
   Polechov? J., 2017, INT REV FINANC ANAL, P1
   Preisser EL, 2008, ECOL ENTOMOL, V33, P709, DOI 10.1111/j.1365-2311.2008.01021.x
   Reger J, 2018, NAT ECOL EVOL, V2, P100, DOI 10.1038/s41559-017-0373-6
   Reinhardt R., 2020, VERBREITUNGSATLAS TA
   Richards CL, 2006, ECOL LETT, V9, P981, DOI 10.1111/j.1461-0248.2006.00950.x
   Rohner PT, 2020, EVOLUTION, V74, P2059, DOI 10.1111/evo.14045
   Scheiner SM, 2020, EVOL APPL, V13, P388, DOI 10.1111/eva.12876
   Scheiner SM, 2012, ECOL EVOL, V2, P751, DOI 10.1002/ece3.217
   Schmid M, 2019, AM NAT, V193, P798, DOI 10.1086/703171
   Settele J, 2015, Schmetterlinge-Die Tagfalter Deutschlands, V2nd
   Sgrò CM, 2016, ANNU REV ENTOMOL, V61, P433, DOI 10.1146/annurev-ento-010715-023859
   Shah AA, 2017, FUNCT ECOL, V31, P2118, DOI 10.1111/1365-2435.12906
   Sinclair BJ, 2016, ECOL LETT, V19, P1372, DOI 10.1111/ele.12686
   Sommer RJ, 2020, GENETICS, V215, P1, DOI 10.1534/genetics.120.303163
   Stazione L, 2020, ECOL EVOL, V10, P1998, DOI 10.1002/ece3.6032
   Sultan SE, 2002, AM NAT, V160, P271, DOI 10.1086/341015
   Sunday JM, 2012, NAT CLIM CHANGE, V2, P686, DOI 10.1038/NCLIMATE1539
   Swaegers J, 2015, MOL ECOL, V24, P6163, DOI 10.1111/mec.13462
   Teets NM, 2011, J EXP BIOL, V214, P806, DOI 10.1242/jeb.051912
   Therry L, 2014, ECOGRAPHY, V37, P1012, DOI 10.1111/ecog.00630
   Titelboim D, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-40944-5
   Tonione MA, 2020, ECOL EVOL, V10, P4749, DOI 10.1002/ece3.6229
   Turner KG, 2015, ECOL EVOL, V5, P3183, DOI 10.1002/ece3.1599
   Van Buskirk J, 2009, J EVOLUTION BIOL, V22, P852, DOI 10.1111/j.1420-9101.2009.01685.x
   Verberk WCEP, 2021, BIOL REV, V96, P247, DOI 10.1111/brv.12653
   von Schmalensee L, 2021, ECOL LETT, V24, P1633, DOI 10.1111/ele.13779
   Wiemers Martin, 2016, Oedippus, V32, P34
   Yampolsky LY, 2014, P ROY SOC B-BIOL SCI, V281, DOI 10.1098/rspb.2013.2744
   Ziegler Heiner, 1999, Neue Entomologische Nachrichten, V45, P1
NR 99
TC 6
Z9 6
U1 0
U2 23
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1010-061X
EI 1420-9101
J9 J EVOLUTION BIOL
JI J. Evol. Biol.
PD JAN
PY 2022
VL 35
IS 1
BP 124
EP 133
DI 10.1111/jeb.13969
EA DEC 2021
PG 10
WC Ecology; Evolutionary Biology; Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Evolutionary Biology; Genetics &
   Heredity
GA YL4HR
UT WOS:000730735100001
PM 34860427
OA hybrid
DA 2025-01-10
ER

PT J
AU Zhang, XC
   Kuzyakov, Y
   Zang, HD
   Dippold, MA
   Shi, LL
   Spielvogel, S
   Razavi, BS
AF Zhang, Xuechen
   Kuzyakov, Yakov
   Zang, Huadong
   Dippold, Michaela A.
   Shi, Lingling
   Spielvogel, Sandra
   Razavi, Bahar S.
TI Rhizosphere hotspots: Root hairs and warming control microbial
   efficiency, carbon utilization and energy production
SO SOIL BIOLOGY & BIOCHEMISTRY
LA English
DT Article
DE Microbial hotspots; Enzyme kinetics; Activation energy; Microbial growth
   kinetics; r and K strategists; Soil microcalorimetry
ID SUBSTRATE-USE EFFICIENCY; SOIL ORGANIC-MATTER; ENZYME-ACTIVITY;
   TEMPERATURE SENSITIVITY; BETA-GLUCOSIDASE; PLANT-GROWTH; HOT MOMENTS;
   STABILIZATION; DECOMPOSITION; OPTIMIZATION
AB Root hairs proliferation and warming strongly influence exudate release, enzyme activities and microbial substrate utilization. However, how the presence of root hairs regulates those processes in the rhizosphere under elevated temperature is poorly known. To clarify these interactions, a wild type maize (with root hairs) and its hairless mutant were grown for 3 weeks at 20 and 30 degrees C, respectively. We combined zymography (localize hotspots of beta-glucosidase) with substrate-induced respiration and microcalorimetry to monitor exudate effects on enzyme kinetics, microbial growth and heat production in the rhizosphere hotspots in response to warming.
   Root hairs effects were more pronounced at the elevated temperature: i) beta-glucosidase activity of the wild type at 30 degrees C was 21% higher than that of the hairless maize; ii) temperature shifted the microbial growth strategy, whereas root hairs promoted the fraction of growing microbial biomass; iii) K-m and the activation energy for beta-glucosidase under the hairless mutant was lower than that under wild maize. These results suggest that microorganisms inhabiting hotspots of the wild type synthesized more enzymes to fulfill their higher energy and nutrient demands than those of the hairless mutant. In contrast, at higher temperature the hairless maize produced an enzyme pool with higher efficiencies rather than higher enzyme production, enabling metabolic needs to be met at lower cost. We therefore conclude that root hairs play an important role in regulating enzyme systems and microbial growth to adapt to climate warming.
C1 [Zhang, Xuechen; Zang, Huadong] China Agr Univ, Coll Agron & Biotechnol, Beijing, Peoples R China.
   [Zhang, Xuechen; Dippold, Michaela A.; Shi, Lingling] Univ Gottingen, Dept Biogeochem Agroecosyst, Gottingen, Germany.
   [Kuzyakov, Yakov] Univ Gottingen, Dept Agr Soil Sci, Gottingen, Germany.
   [Kuzyakov, Yakov] Russian Acad Sci, Inst Physicochem & Biol Problems Soil Sci, Pushchino 142290, Russia.
   [Shi, Lingling] Chinese Acad Sci, Kunming Inst Bot, Key Lab Econ Plants & Biotechnol, 132 Lanhei Rd, Kunming 650201, Yunnan, Peoples R China.
   [Shi, Lingling] World Agroforestry Ctr, China & East Asia Off, 132 Lanhei Rd, Kunming 650201, Yunnan, Peoples R China.
   [Spielvogel, Sandra] Christian Albrecht Univ Kiel, Inst Plant Nutr & Soil Sci, Kiel, Germany.
   [Razavi, Bahar S.] Christian Albrecht Univ Kiel, Inst Phytopathol, Dept Soil & Plant Microbiome, Kiel, Germany.
C3 China Agricultural University; University of Gottingen; University of
   Gottingen; Russian Academy of Sciences; Pushchino Scientific Center for
   Biological Research (PSCBI) of the Russian Academy of Sciences;
   Institute of Physicohemical & Biological Problems of Soil Science;
   Chinese Academy of Sciences; Kunming Institute of Botany, CAS;
   University of Kiel; University of Kiel
RP Zang, HD (corresponding author), China Agr Univ, Coll Agron & Biotechnol, Beijing, Peoples R China.
EM zanghuadong@cau.edu.cn
RI Kuzyakov, Yakov/D-1605-2010; Zhang, Xuechen/AFU-9165-2022; Shi,
   Lingling/ABA-5391-2020; Razavi, Bahar/S-7262-2017; Zang,
   Huadong/T-6447-2017; Dippold, Michaela/C-1548-2017
OI Zang, Huadong/0000-0002-2008-143X; Razavi, Bahar S./0000-0002-3726-8268;
   Dippold, Michaela/0000-0002-3657-4693
FU China Scholarship Council (CSC); DFG [RA-3062/3-1, SP 943/6-1];
   Fundamental Research Funds for the Central Universities from China
   [2020TC120]; Russian Science Foundation [18-14-00362]
FX We gratefully acknowledge the China Scholarship Council (CSC) for
   financial support for Xuechen Zhang. This study was supported by the DFG
   grant RA-3062/3-1 and SP 943/6-1, as well as the Fundamental Research
   Funds for the Central Universities from China (2020TC120). We
   acknowledge Frank Hochholdinger, University of Bonn, for kindly
   providing maize seeds. The contribution of YK was supported by the
   Russian Science Foundation (project No. 18-14-00362). The authors would
   like to thank Callum C. Banfield for constructive criticism of the text.
CR Allison SD, 2010, NAT GEOSCI, V3, P336, DOI 10.1038/NGEO846
   B_olscher T., 2016, DECOMPOSITION SOIL O, P1652
   Badri DV, 2009, PLANT CELL ENVIRON, V32, P666, DOI [10.1111/j.1365-3040.2009.01926.x, 10.1111/j.1365-3040.2008.01926.x]
   Barros N, 2010, J THERM ANAL CALORIM, V99, P771, DOI 10.1007/s10973-010-0673-4
   Bates TR, 2000, AM J BOT, V87, P958, DOI 10.2307/2656994
   Bilyera N., 2019, EGU2019
   Blagodatskaya E, 2011, SOIL BIOL BIOCHEM, V43, P778, DOI 10.1016/j.soilbio.2010.12.011
   Blagodatskaya EV, 2009, EUR J SOIL SCI, V60, P186, DOI 10.1111/j.1365-2389.2008.01103.x
   Blagodatskaya E, 2016, SCI REP-UK, V6, DOI 10.1038/srep22240
   Blagodatskaya E, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0093282
   Blagodatsky SA, 2000, BIOL FERT SOILS, V32, P73, DOI 10.1007/s003740000219
   Bölscher T, 2017, SOIL BIOL BIOCHEM, V109, P59, DOI 10.1016/j.soilbio.2017.02.005
   Bölscher T, 2016, BIOL FERT SOILS, V52, P547, DOI 10.1007/s00374-016-1097-5
   Bradford MA, 2019, NAT ECOL EVOL, V3, P223, DOI 10.1038/s41559-018-0771-4
   Bradford MA, 2013, FRONT MICROBIOL, V4, DOI 10.3389/fmicb.2013.00333
   Burns RG, 2013, SOIL BIOL BIOCHEM, V58, P216, DOI 10.1016/j.soilbio.2012.11.009
   Cotrufo MF, 2013, GLOBAL CHANGE BIOL, V19, P988, DOI 10.1111/gcb.12113
   Crowther TW, 2013, ECOL LETT, V16, P469, DOI 10.1111/ele.12069
   Datta S, 2011, PLANT SOIL, V346, P1, DOI 10.1007/s11104-011-0845-4
   Davidson EA, 2006, NATURE, V440, P165, DOI 10.1038/nature04514
   Fierer N, 2007, ECOLOGY, V88, P1354, DOI 10.1890/05-1839
   Finkel SE, 2006, NAT REV MICROBIOL, V4, P113, DOI 10.1038/nrmicro1340
   Ge TD, 2017, SOIL BIOL BIOCHEM, V113, P108, DOI 10.1016/j.soilbio.2017.06.005
   German DP, 2011, SOIL BIOL BIOCHEM, V43, P1387, DOI 10.1016/j.soilbio.2011.03.017
   Hansen LD, 2004, THERMOCHIM ACTA, V422, P55, DOI 10.1016/j.tca.2004.05.033
   Harris JA, 2012, SOIL BIOL BIOCHEM, V47, P149, DOI 10.1016/j.soilbio.2011.12.017
   Hassan W, 2014, J THERM ANAL CALORIM, V116, P969, DOI 10.1007/s10973-013-3588-z
   Herrmann AM, 2014, ENVIRON SCI TECHNOL, V48, P4344, DOI 10.1021/es403941h
   Holz M, 2018, ANN BOT-LONDON, V121, P61, DOI 10.1093/aob/mcx127
   Jones DL, 2009, PLANT SOIL, V321, P5, DOI 10.1007/s11104-009-9925-0
   Keiblinger KM, 2010, FEMS MICROBIOL ECOL, V73, P430, DOI 10.1111/j.1574-6941.2010.00912.x
   Kuzyakov Y, 2019, SOIL BIOL BIOCHEM, V135, P343, DOI 10.1016/j.soilbio.2019.05.011
   Kuzyakov Y, 2015, SOIL BIOL BIOCHEM, V83, P184, DOI 10.1016/j.soilbio.2015.01.025
   Kuzyakov Y, 2010, SOIL BIOL BIOCHEM, V42, P1363, DOI 10.1016/j.soilbio.2010.04.003
   Lammirato C, 2010, SOIL BIOL BIOCHEM, V42, P2203, DOI 10.1016/j.soilbio.2010.08.018
   Ma XM, 2017, SOIL BIOL BIOCHEM, V107, P226, DOI 10.1016/j.soilbio.2017.01.009
   Marx JC, 2007, MAR BIOTECHNOL, V9, P293, DOI 10.1007/s10126-006-6103-8
   Marx MC, 2001, SOIL BIOL BIOCHEM, V33, P1633, DOI 10.1016/S0038-0717(01)00079-7
   Mishra BS, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0004502
   Moscatelli MC, 2012, ECOL INDIC, V13, P322, DOI 10.1016/j.ecolind.2011.06.031
   Panikov N.S., 1995, MICROBIAL GROWTH KIN
   Panikov NS, 1996, J MICROBIOL METH, V24, P219, DOI 10.1016/0167-7012(95)00074-7
   Paterson E, 2009, NEW PHYTOL, V184, P19, DOI 10.1111/j.1469-8137.2009.03001.x
   Pausch J, 2016, SOIL BIOL BIOCHEM, V100, P74, DOI 10.1016/j.soilbio.2016.05.009
   Poirier V, 2018, SOIL BIOL BIOCHEM, V120, P246, DOI 10.1016/j.soilbio.2018.02.016
   Razavi BS, 2019, RHIZOSPHERE-NETH, V11, DOI 10.1016/j.rhisph.2019.100161
   Razavi BS, 2017, SOIL BIOL BIOCHEM, V105, P236, DOI 10.1016/j.soilbio.2016.11.026
   Razavi BS, 2016, SOIL BIOL BIOCHEM, V96, P229, DOI 10.1016/j.soilbio.2016.02.020
   Razavi BS, 2016, SOIL BIOL BIOCHEM, V97, P15, DOI 10.1016/j.soilbio.2016.02.018
   Razavi BS, 2015, FRONT MICROBIOL, V6, DOI 10.3389/fmicb.2015.01126
   Schimel JP, 2012, FRONT MICROBIOL, V3, DOI 10.3389/fmicb.2012.00348
   Sinsabaugh RL, 2013, ECOL LETT, V16, P930, DOI 10.1111/ele.12113
   SOMERO GN, 1978, ANNU REV ECOL SYST, V9, P1, DOI 10.1146/annurev.es.09.110178.000245
   Spohn M, 2014, PLANT SOIL, V379, P67, DOI 10.1007/s11104-014-2041-9
   Steinweg JM, 2008, SOIL BIOL BIOCHEM, V40, P2722, DOI 10.1016/j.soilbio.2008.07.002
   Tian P, 2020, SOIL BIOL BIOCHEM, V141, DOI 10.1016/j.soilbio.2019.107662
   Treseder KK, 2012, BIOGEOCHEMISTRY, V109, P7, DOI 10.1007/s10533-011-9636-5
   Wadsö L, 2015, METHODS, V76, P11, DOI 10.1016/j.ymeth.2014.10.024
   Wei L, 2019, SOIL BIOL BIOCHEM, V135, P134, DOI 10.1016/j.soilbio.2019.04.016
   Wei XM, 2019, PLANT SOIL, V445, P169, DOI 10.1007/s11104-018-03902-0
   Wen Y, 2019, SOIL BIOL BIOCHEM, V139, DOI 10.1016/j.soilbio.2019.107629
   Zang HD, 2020, LAND DEGRAD DEV, V31, P683, DOI 10.1002/ldr.3496
   Zhang XC, 2019, SOIL BIOL BIOCHEM, V133, P83, DOI 10.1016/j.soilbio.2019.02.010
   Zinser ER, 1999, J BACTERIOL, V181, P5800, DOI 10.1128/JB.181.18.5800-5807.1999
NR 64
TC 55
Z9 58
U1 12
U2 131
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0038-0717
EI 1879-3428
J9 SOIL BIOL BIOCHEM
JI Soil Biol. Biochem.
PD SEP
PY 2020
VL 148
AR 107872
DI 10.1016/j.soilbio.2020.107872
PG 8
WC Soil Science
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA NK3YD
UT WOS:000566668900015
DA 2025-01-10
ER

PT J
AU Hallmark, B
   Karafet, TM
   Hsieh, P
   Osipova, LP
   Watkins, JC
   Hammer, MF
AF Hallmark, Brian
   Karafet, Tatiana M.
   Hsieh, PingHsun
   Osipova, Ludmila P.
   Watkins, Joseph C.
   Hammer, Michael F.
TI Genomic Evidence of Local Adaptation to Climate and Diet in Indigenous
   Siberians
SO MOLECULAR BIOLOGY AND EVOLUTION
LA English
DT Article
DE natural selection; Siberians; brown adipose tissue; missense variant;
   cold adaptation; diet
ID ANGIOPOIETIN-LIKE PROTEIN; SECRETORY PHOSPHOLIPASE A(2); CLASSIC
   SELECTIVE SWEEPS; BASAL METABOLIC-RATES; BROWN ADIPOSE-TISSUE; LACTASE
   PERSISTENCE; YAKUT SAKHA; POSITIVE SELECTION; NATURAL-SELECTION;
   THYROID-HORMONE
AB The indigenous inhabitants of Siberia live in some of the harshest environments on earth, experiencing extended periods of severe cold temperatures, dramatic variation in photoperiod, and limited and highly variable food resources. While the successful long-term settlement of this area by humans required multiple behavioral and cultural innovations, the nature of the underlying genetic changes has generally remained elusive. In this study, we used a three-part approach to identify putative targets of positive natural selection in Siberians. We first performed selection scans on whole exome and genome-wide single nucleotide polymorphism array data from multiple Siberian populations. We then annotated candidates in the tails of the empirical distributions, focusing on candidates with evidence linking them to biological processes and phenotypes previously identified as relevant to adaptation in circumpolar groups. The top candidates were then genotyped in additional populations to determine their spatial allele frequency distributions and associations with climate variables. Our analysis reveals missense mutations in three genes involved in lipid metabolism (PLA2G2A, PLIN1, and ANGPTL8) that exhibit genomic and spatial patterns consistent with selection for cold climate and/or diet. These variants are unified by their connection to brown adipose tissue and may help to explain previously observed physiological differences in Siberians such as low serum lipid levels and increased basal metabolic rate. These results support the hypothesis that indigenous Siberians have genetically adapted to their local environment by selection on multiple genes.
C1 [Hallmark, Brian; Watkins, Joseph C.] Univ Arizona, Interdisciplinary Program Stat, Tucson, AZ USA.
   [Karafet, Tatiana M.; Hammer, Michael F.] Univ Arizona, ARL Div Biotechnol, Tucson, AZ 85721 USA.
   [Hsieh, PingHsun; Hammer, Michael F.] Univ Washington, Dept Genome Sci, Seattle, WA 98195 USA.
   [Osipova, Ludmila P.] Russian Acad Sci, Siberian Branch, Inst Cytol & Genet, Novosibirsk, Russia.
C3 University of Arizona; University of Arizona; University of Washington;
   University of Washington Seattle; Russian Academy of Sciences; Institute
   of Cytology & Genetics ICG SB RAS
RP Hammer, MF (corresponding author), Univ Arizona, ARL Div Biotechnol, Tucson, AZ 85721 USA.; Hammer, MF (corresponding author), Univ Washington, Dept Genome Sci, Seattle, WA 98195 USA.
EM mfh@email.arizona.edu
FU National Science Foundation [PLR-1203874]; State Research Project
   [0324-2018-0016]
FX We thank all of the Siberian people who participated in this study. This
   work was supported by National Science Foundation grants to T.M.K. and
   M.F.H. (PLR-1203874) and by the State Research Project (No.
   0324-2018-0016) to L.P.O.
CR Alexander DH, 2009, GENOME RES, V19, P1655, DOI 10.1101/gr.094052.109
   Altshuler DM, 2015, NATURE, V526, P68, DOI 10.1038/nature15393
   [Anonymous], AM J HUMAN GENETICS
   Antelope CX, 2017, HUM BIOL, V89, P81, DOI 10.13110/humanbiology.89.1.05
   Blair LM, 2014, HUM GENOMICS, V8, DOI 10.1186/1479-7364-8-1
   Bolger AM, 2014, BIOINFORMATICS, V30, P2114, DOI 10.1093/bioinformatics/btu170
   Bonnefont Jean-Paul, 2004, Molecular Aspects of Medicine, V25, P495, DOI 10.1016/j.mam.2004.06.004
   Breitling LP, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0022318
   Burke JE, 2009, J LIPID RES, V50, pS237, DOI 10.1194/jlr.R800033-JLR200
   Cannon B, 2004, PHYSIOL REV, V84, P277, DOI 10.1152/physrev.00015.2003
   Cardona A, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0098076
   Chang CC, 2015, GIGASCIENCE, V4, DOI 10.1186/s13742-015-0047-8
   Clemente FJ, 2014, AM J HUM GENET, V95, P584, DOI 10.1016/j.ajhg.2014.09.016
   De Marchi U, 2011, J BIOL CHEM, V286, P32533, DOI 10.1074/jbc.M110.216044
   Dijk W, 2016, CURR OPIN LIPIDOL, V27, P249, DOI 10.1097/MOL.0000000000000290
   Exeter HJ, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0041139
   Frichot E, 2015, METHODS ECOL EVOL, V6, P925, DOI 10.1111/2041-210X.12382
   Fu ZY, 2013, BIOCHEM BIOPH RES CO, V430, P1126, DOI 10.1016/j.bbrc.2012.12.025
   Fumagalli M, 2015, SCIENCE, V349, P1343, DOI 10.1126/science.aab2319
   Fumagalli M, 2014, BIOINFORMATICS, V30, P1486, DOI 10.1093/bioinformatics/btu041
   Fumagalli M, 2011, PLOS GENET, V7, DOI 10.1371/journal.pgen.1002355
   Gautier M, 2017, MOL ECOL RESOUR, V17, P78, DOI 10.1111/1755-0998.12634
   Gburcik V, 2012, AM J PHYSIOL-ENDOC M, V303, pE1053, DOI 10.1152/ajpendo.00104.2012
   Glaser C, 2010, METABOLISM, V59, P993, DOI 10.1016/j.metabol.2009.10.022
   Granka JM, 2012, GENETICS, V192, P1049, DOI 10.1534/genetics.112.144071
   Günther T, 2013, GENETICS, V195, P205, DOI 10.1534/genetics.113.152462
   Guo T, 2015, MOL MED REP, V12, P3285, DOI 10.3892/mmr.2015.3825
   Hancock AM, 2008, PLOS GENET, V4, DOI 10.1371/journal.pgen.0040032
   Hancock AM, 2011, PLOS GENET, V7, DOI 10.1371/journal.pgen.1001375
   Hancock AM, 2011, MOL BIOL EVOL, V28, P601, DOI 10.1093/molbev/msq228
   Hancock AM, 2010, P NATL ACAD SCI USA, V107, P8924, DOI 10.1073/pnas.0914625107
   Hernandez RD, 2011, SCIENCE, V331, P920, DOI 10.1126/science.1198878
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Howie B, 2012, NAT GENET, V44, P955, DOI 10.1038/ng.2354
   Hsieh P, 2017, MOL BIOL EVOL, V34, P2913, DOI 10.1093/molbev/msx226
   Ivandic B, 1999, ARTERIOSCL THROM VAS, V19, P1284, DOI 10.1161/01.ATV.19.5.1284
   Iyer A, 2012, DIABETES, V61, P2320, DOI 10.2337/db11-1179
   Jang Y, 2006, INT J OBESITY, V30, P1601, DOI 10.1038/sj.ijo.0803312
   Karafet TM, 2002, HUM BIOL, V74, P761, DOI 10.1353/hub.2003.0006
   Kemper KE, 2014, BMC GENOMICS, V15, DOI 10.1186/1471-2164-15-246
   Konige M, 2014, BBA-MOL BASIS DIS, V1842, P393, DOI 10.1016/j.bbadis.2013.05.007
   Korneliussen TS, 2014, BMC BIOINFORMATICS, V15, DOI 10.1186/s12859-014-0356-4
   Kriticos DJ, 2012, METHODS ECOL EVOL, V3, P53, DOI 10.1111/j.2041-210X.2011.00134.x
   Kuefner MS, 2017, J LIPID RES, V58, P1822, DOI 10.1194/jlr.M076141
   Kugiyama K, 1999, CIRCULATION, V100, P1280, DOI 10.1161/01.CIR.100.12.1280
   Kuzmin YV, 2018, ARCHAEOL ANTHROP SCI, V10, P111, DOI 10.1007/s12520-016-0342-z
   Lemas DJ, 2012, J LIPID RES, V53, P175, DOI 10.1194/jlr.P018952
   Leonard WR, 2014, AM J HUM BIOL, V26, P437, DOI 10.1002/ajhb.22524
   Leonard WR, 2005, ANNU REV ANTHROPOL, V34, P451, DOI 10.1146/annurev.anthro.34.081804.120558
   Leonard WR, 2002, AM J HUM BIOL, V14, P609, DOI 10.1002/ajhb.10072
   Leppaluoto J, 1998, Int J Circumpolar Health, V57 Suppl 1, P383
   Li H, 2009, BIOINFORMATICS, V25, P1094, DOI [10.1093/bioinformatics/btp100, 10.1093/bioinformatics/btp324]
   Mayewski PA, 2004, QUATERNARY RES, V62, P243, DOI 10.1016/j.yqres.2004.07.001
   McKenna A, 2010, GENOME RES, V20, P1297, DOI 10.1101/gr.107524.110
   Monroy-Muñoz IE, 2017, IMMUNOBIOLOGY, V222, P967, DOI 10.1016/j.imbio.2016.08.014
   Nielsen R, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0037558
   Novembre J, 2009, NAT REV GENET, V10, P745, DOI 10.1038/nrg2632
   OTEVA EA, 1993, TERAPEVT ARKH, V65, P21
   Ozguven S, 2016, EUR J NUCL MED MOL I, V43, P355, DOI 10.1007/s00259-015-3166-7
   Paradis ME, 2006, INT J OBESITY, V30, P1615, DOI 10.1038/sj.ijo.0803315
   Patterson N, 2006, PLOS GENET, V2, P2074, DOI 10.1371/journal.pgen.0020190
   Peter BM, 2012, PLOS GENET, V8, DOI 10.1371/journal.pgen.1003011
   Pitulko V, 2017, QUATERNARY SCI REV, V165, P127, DOI 10.1016/j.quascirev.2017.04.004
   Pitulko VV, 2016, SCIENCE, V351, P260, DOI 10.1126/science.aad0554
   Pugach I, 2016, MOL BIOL EVOL, V33, P1777, DOI 10.1093/molbev/msw055
   Purcell S, 2007, AM J HUM GENET, V81, P559, DOI 10.1086/519795
   Quagliarini F, 2012, P NATL ACAD SCI USA, V109, P19751, DOI 10.1073/pnas.1217552109
   Racimo F, 2017, MOL BIOL EVOL, V34, P509, DOI 10.1093/molbev/msw283
   Rasmussen M, 2010, NATURE, V463, P757, DOI 10.1038/nature08835
   Rellstab C, 2015, MOL ECOL, V24, P4348, DOI 10.1111/mec.13322
   Robinson JT, 2011, NAT BIOTECHNOL, V29, P24, DOI 10.1038/nbt.1754
   Sabeti PC, 2002, NATURE, V419, P832, DOI 10.1038/nature01140
   Sawada T, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0014006
   Ségurel L, 2017, ANNU REV GENOM HUM G, V18, P297, DOI 10.1146/annurev-genom-091416-035340
   Shao XL, 2016, LIPIDS HEALTH DIS, V15, DOI 10.1186/s12944-016-0310-8
   Shuvalova YA, 2015, GENE, V564, P29, DOI 10.1016/j.gene.2015.03.030
   Siddiqa A, 2017, GENOMICS, V109, P408, DOI 10.1016/j.ygeno.2017.06.006
   Simonides WS, 2001, BIOSCIENCE REP, V21, P139, DOI 10.1023/A:1013692023449
   Smith CE, 2012, NUTR REV, V70, P611, DOI 10.1111/j.1753-4887.2012.00515.x
   Snodgrass JJ, 2006, AM J CLIN NUTR, V84, P798, DOI 10.1093/ajcn/84.4.798
   Snodgrass JJ, 2013, ANNU REV ANTHROPOL, V42, P69, DOI 10.1146/annurev-anthro-092412-155517
   Snodgrass JJ, 2005, AM J HUM BIOL, V17, P155, DOI 10.1002/ajhb.20106
   Song WH, 2015, BIOCHEM BIOPH RES CO, V456, P896, DOI 10.1016/j.bbrc.2014.12.053
   Souza SC, 2007, J LIPID RES, V48, P1273, DOI 10.1194/jlr.M700047-JLR200
   Sun ZQ, 2013, NAT COMMUN, V4, DOI 10.1038/ncomms2581
   Tansey JT, 2004, IUBMB LIFE, V56, P379, DOI 10.1080/15216540400009968
   Tishkoff SA, 2007, NAT GENET, V39, P31, DOI 10.1038/ng1946
   Tseng YH, 2014, INT J MOL SCI, V15, P23640, DOI 10.3390/ijms151223640
   Tseng YH, 2014, AUTOPHAGY, V10, P20, DOI 10.4161/auto.26126
   Vitti JJ, 2013, ANNU REV GENET, V47, P97, DOI 10.1146/annurev-genet-111212-133526
   Wang K, 2010, NUCLEIC ACIDS RES, V38, DOI 10.1093/nar/gkq603
   Wong ENM, 2017, GENOME RES, V27, P1, DOI 10.1101/gr.202945.115
   Wootton PTE, 2006, HUM MOL GENET, V15, P355, DOI 10.1093/hmg/ddi453
   Yi X, 2010, SCIENCE, V329, P75, DOI 10.1126/science.1190371
   Zhang R, 2016, OPEN BIOL, V6, DOI 10.1098/rsob.150272
NR 95
TC 33
Z9 37
U1 2
U2 27
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 FEB
PY 2019
VL 36
IS 2
BP 315
EP 327
DI 10.1093/molbev/msy211
PG 13
WC Biochemistry & Molecular Biology; Evolutionary Biology; Genetics &
   Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Evolutionary Biology; Genetics &
   Heredity
GA HM2VJ
UT WOS:000459328600008
PM 30428071
OA Bronze
DA 2025-01-10
ER

PT J
AU Seifert, LI
   Weithoff, G
   Gaedke, U
   Vos, M
AF Seifert, Linda I.
   Weithoff, Guntram
   Gaedke, Ursula
   Vos, Matthijs
TI Warming-induced changes in predation, extinction and invasion in an
   ectotherm food web
SO OECOLOGIA
LA English
DT Article
DE Community dynamics; Freshwater ecosystem; Global warming; Species range
   shift; Trophic interactions
ID CLIMATE-CHANGE; INDUCIBLE DEFENSES; TOP-DOWN; POPULATION-DYNAMICS;
   TEMPERATURE; ECOSYSTEMS; IMPACTS; EUTROPHICATION; COMMUNITIES; STABILITY
AB Climate change will alter the forces of predation and competition in temperate ectotherm food webs. This may increase local extinction rates, change the fate of invasions and impede species reintroductions into communities. Invasion success could be modulated by traits (e.g., defenses) and adaptations to climate. We studied how different temperatures affect the time until extinction of species, using bitrophic and tritrophic planktonic food webs to evaluate the relative importance of predatory overexploitation and competitive exclusion, at 15 and 25 A degrees C. In addition, we tested how inclusion of a subtropical as opposed to a temperate strain in this model food web affects times until extinction. Further, we studied the invasion success of the temperate rotifer Brachionus calyciflorus into the planktonic food web at 15 and 25 A degrees C on five consecutive introduction dates, during which the relative forces of predation and competition differed. A higher temperature dramatically shortened times until extinction of all herbivore species due to carnivorous overexploitation in tritrophic systems. Surprisingly, warming did not increase rates of competitive exclusion among the tested herbivore species in bitrophic communities. Including a subtropical herbivore strain reduced top-down control by the carnivore at high temperature. Invasion attempts of temperate B. calyciflorus into the food web always succeeded at 15 A degrees C, but consistently failed at 25 A degrees C due to voracious overexploitation by the carnivore. Pre-induction of defenses (spines) in B. calyciflorus before the invasion attempt did not change its invasion success at the high temperature. We conclude that high temperatures may promote local extinctions in temperate ectotherms and reduce their chances of successful recovery.
C1 [Seifert, Linda I.; Weithoff, Guntram; Gaedke, Ursula; Vos, Matthijs] Univ Potsdam, Dept Ecol & Ecosyst Modelling, D-14469 Potsdam, Germany.
   [Gaedke, Ursula] Berlin Brandenburg Inst Adv Biodivers Res BBIB, D-4195 Berlin, Germany.
   [Vos, Matthijs] Leiden Univ, Inst Environm Sci CML, NL-2300 RA Leiden, Netherlands.
C3 University of Potsdam; Leiden University - Excl LUMC; Leiden University
RP Seifert, LI (corresponding author), Univ Potsdam, Dept Ecol & Ecosyst Modelling, Maulbeerallee 2, D-14469 Potsdam, Germany.
EM linda.seifert@uni-potsdam.de
FU Deutsche Forschungsgemeinschaft [VO 1669/1-1]
FX We thank Sabine Donath for help with the counting. We are grateful to
   the editor and reviewers for their comments that considerably improved
   the manuscript. This work was funded through Deutsche
   Forschungsgemeinschaft grant VO 1669/1-1 to M. V.
CR Abrams PA, 2003, EVOL ECOL RES, V5, P1113
   Araújo MB, 2013, ECOL LETT, V16, P1206, DOI 10.1111/ele.12155
   Barton BT, 2009, ECOLOGY, V90, P2346, DOI 10.1890/08-2254.1
   Beisner BE, 1997, CAN J FISH AQUAT SCI, V54, P586, DOI 10.1139/cjfas-54-3-586
   Beisner BE, 1996, FRESHWATER BIOL, V35, P219, DOI 10.1046/j.1365-2427.1996.00492.x
   Beisner BE, 1997, FUNCT ECOL, V11, P112, DOI 10.1046/j.1365-2435.1997.00062.x
   Binzer A, 2012, PHILOS T R SOC B, V367, P2935, DOI 10.1098/rstb.2012.0230
   Burgmer T, 2007, OECOLOGIA, V151, P93, DOI 10.1007/s00442-006-0542-9
   Deutsch CA, 2008, P NATL ACAD SCI USA, V105, P6668, DOI 10.1073/pnas.0709472105
   Edwards M, 2004, NATURE, V430, P881, DOI 10.1038/nature02808
   Ewald NC, 2013, FRESHWATER BIOL, V58, P2481, DOI 10.1111/fwb.12224
   Gaedke U, 2010, GLOBAL CHANGE BIOL, V16, P1122, DOI 10.1111/j.1365-2486.2009.02009.x
   GILBERT JJ, 1967, ARCH HYDROBIOL, V64, P1
   GUILLARD RR, 1972, J PHYCOL, V8, P10, DOI 10.1111/j.0022-3646.1972.00010.x
   HALBACH U, 1970, OECOLOGIA, V4, P176, DOI 10.1007/BF00377100
   Hansen J, 2012, P NATL ACAD SCI USA, V109, pE2415, DOI 10.1073/pnas.1205276109
   Hoekman D, 2010, ECOLOGY, V91, P2819, DOI 10.1890/10-0260.1
   Holzapfel AM, 2005, GLOBAL CHANGE BIOL, V11, P2009, DOI 10.1111/j.365-2486.2005.01057.x
   Jankowski T, 2006, LIMNOL OCEANOGR, V51, P815, DOI 10.4319/lo.2006.51.2.0815
   Jeppesen E, 2007, HYDROBIOLOGIA, V581, P269, DOI 10.1007/s10750-006-0507-3
   Kirk KL, 1998, ECOLOGY, V79, P2456, DOI 10.2307/176835
   Kishi D, 2005, FRESHWATER BIOL, V50, P1315, DOI 10.1111/j.1365-2427.2005.01404.x
   Kratina P, 2012, ECOLOGY, V93, P1421, DOI 10.1890/11-1595.1
   Krenek S, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0030598
   Logan JD, 2007, NAT RESOUR MODEL, V20, P549
   Lundberg P, 2000, ECOL LETT, V3, P465, DOI 10.1046/j.1461-0248.2000.00170.x
   O'Gorman EJ, 2012, ADV ECOL RES, V47, P81, DOI 10.1016/B978-0-12-398315-2.00002-8
   Petchey OL, 1999, NATURE, V402, P69, DOI 10.1038/47023
   Pörtner HO, 2008, SCIENCE, V322, P690, DOI 10.1126/science.1163156
   Rall BC, 2010, GLOBAL CHANGE BIOL, V16, P2145, DOI 10.1111/j.1365-2486.2009.02124.x
   Richardson AJ, 2004, SCIENCE, V305, P1609, DOI 10.1126/science.1100958
   Seifert LI, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0095046
   Sentis A, 2013, GLOBAL CHANGE BIOL, V19, P833, DOI 10.1111/gcb.12094
   Sentis A, 2012, OECOLOGIA, V169, P1117, DOI 10.1007/s00442-012-2255-6
   Shurin JB, 2012, PHILOS T R SOC B, V367, P3008, DOI 10.1098/rstb.2012.0243
   Stachowicz JJ, 2002, P NATL ACAD SCI USA, V99, P15497, DOI 10.1073/pnas.242437499
   Suikkanen S, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0066475
   Teixeira-de Mello F, 2009, FRESHWATER BIOL, V54, P1202, DOI 10.1111/j.1365-2427.2009.02167.x
   Thompson PL, 2012, J ANIM ECOL, V81, P251, DOI 10.1111/j.1365-2656.2011.01908.x
   Tylianakis JM, 2008, ECOL LETT, V11, P1351, DOI 10.1111/j.1461-0248.2008.01250.x
   Van Der Stap I, 2006, FRESHWATER BIOL, V51, P424, DOI 10.1111/j.1365-2427.2005.01498.x
   van der Stap I, 2008, OECOLOGIA, V157, P697, DOI 10.1007/s00442-008-1111-1
   Van der Stap I, 2007, HYDROBIOLOGIA, V593, P103, DOI 10.1007/s10750-007-9051-z
   van der Stap I, 2007, ECOLOGY, V88, P2474, DOI 10.1890/07-1731.1
   van der Stap I, 2009, ECOL RES, V24, P1145, DOI 10.1007/s11284-009-0596-3
   Vandermeer J, 2006, BIOSCIENCE, V56, P967, DOI 10.1641/0006-3568(2006)56[967:OPABM]2.0.CO;2
   Vasseur DA, 2005, AM NAT, V166, P184, DOI 10.1086/431285
   Verschoor AM, 2004, ECOL LETT, V7, P1143, DOI 10.1111/j.1461-0248.2004.00675.x
   Vijverberg J, 2006, FRESHWATER BIOL, V51, P756, DOI 10.1111/j.1365-2427.2006.01528.x
   Vucic-Pestic O, 2011, GLOBAL CHANGE BIOL, V17, P1301, DOI 10.1111/j.1365-2486.2010.02329.x
   Weithoff G, 1995, HYDROBIOLOGIA, V313, P381, DOI 10.1007/BF00025974
   Wentz FJ, 2000, SCIENCE, V288, P847, DOI 10.1126/science.288.5467.847
   Winder M, 2004, GLOBAL CHANGE BIOL, V10, P1844, DOI 10.1111/j.1365-2486.2004.00849.x
   Woodward G, 2010, PHILOS T R SOC B, V365, P2093, DOI 10.1098/rstb.2010.0055
NR 54
TC 22
Z9 23
U1 3
U2 91
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 0029-8549
EI 1432-1939
J9 OECOLOGIA
JI Oecologia
PD JUN
PY 2015
VL 178
IS 2
BP 485
EP 496
DI 10.1007/s00442-014-3211-4
PG 12
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA CI6VF
UT WOS:000354900700016
PM 25564019
DA 2025-01-10
ER

PT J
AU Sikkema, R
   Wilhelmsson, E
   Ellison, D
   Petersson, H
AF Sikkema, Richard
   Wilhelmsson, Erik
   Ellison, David
   Petersson, Hans
TI Forest Owner Attitudes Toward Climate-Proof Forest Management in Sweden
   and the Netherlands-Between Forest Strategies and Practical Measures
SO SMALL-SCALE FORESTRY
LA English
DT Article
DE Climate action; Life on land; Natural disturbances; Forest owner's
   response curves; European forest strategies
ID DISTURBANCES; EUROPE; TIMBER; WOOD
AB Our research targets the role of forests under the international Paris Climate Agreement, the EU Green Deal and Forest Strategy. In line with the latter objectives, Member States are expected to encourage forest owners to contribute to international climate goals via national strategic plans and new management measures. How forest owners will respond, however, to a range of climate smart forestry (CSF) measures in the near future, is not well known. After postal and email distribution in 2020, 98 Swedish (response rate 21%) and 241 Dutch forest owners (24%) filled out a forest-climate survey. Based upon specific CSF measures, several hypothetical climate-related scenarios were incorporated into the survey. Dutch forest owners are planning to introduce new tree species, more mixed species stands (a gradual shift to broadleaved species) and additional water reservoirs in anticipation of increased drought periods, all part of a hypothetical climate adaptation package for 2030. Swedish forest owners prefer earlier thinning and salvaging activities. Zooming in on Dutch scale differences, small forest owners rely less on current public subsidy packages and show significantly less interest in committing to the adaptation package than large forest owners. In Sweden, preferences for the high forest management intensity scenario is significantly affected by size class: more intensive activities are the least popular with the smallest forest owners. The greatest difference between both countries is the way in which CSF measures should be financially supported. In general, Dutch forest owners would prefer to maintain subsidy schemes but adapt them to new circumstances, while Swedish forest owners benefit from timber and bioenergy markets.
C1 [Sikkema, Richard] Wageningen Univ & Res, Dept Forest Ecol & Forest Management, Wageningen, Netherlands.
   [Sikkema, Richard] Tall Forester Trees Advisory Serv, Heteren, Netherlands.
   [Wilhelmsson, Erik; Ellison, David; Petersson, Hans] Swedish Univ Agr Sci SLU, Forest Resource Management, Umea, Sweden.
   [Ellison, David] Swiss Fed Inst Technol, Nat Resource Policy NARP, Environm Syst Sci, Zurich, Switzerland.
   [Ellison, David] Univ Bern, Inst Geog, Land Syst & Sustainable Land Management Unit LS SL, Bern, Switzerland.
C3 Wageningen University & Research; Swedish University of Agricultural
   Sciences; Swiss Federal Institutes of Technology Domain; ETH Zurich;
   University of Bern
RP Petersson, H (corresponding author), Swedish Univ Agr Sci SLU, Forest Resource Management, Umea, Sweden.
EM RSikkema@hetnet.nl; hans.petersson@slu.se
RI Wilhelmsson, Erik/KIE-4325-2024; Ellison, David/AFK-5297-2022
OI Wilhelmsson, Erik/0000-0001-5215-7921; Petersson,
   Hans/0000-0003-3755-0041; Ellison, David/0000-0002-3755-6024
FU Nederlandse Organisatie voor Wetenschappelijk Onderzoek; WUR's
   statistical department Biometris
FX The authors wish to express their gratitude for the contributions of the
   Dutch cadastral authority (www.kadaster.nl/about-us), WUR climate
   research colleagues Etienne Thomassen, Marleen Vos, Meike Bouwman, Juul
   Limpens and WUR's statistical department Biometris. We likewise express
   our appreciation for the fruitful input provided by the European
   Alterfor 2016-2020 project (Marjanke Hoogstra-Klein; Geerten Hengeveld,
   WUR) and the US project Willingness to Harvest (Francisco Aguilar, SLU)
   during the initial survey stages. At the final stage, we were involved
   with the "Unie van Bosgroepen" (www.bosgroepen.nl) and "Federatie
   Particulier Grondbezit" (www.grondbezit.nl) in their evaluation of the
   Dutch SNL subsidy scheme. Additional thanks go to our FORCLIMIT
   2017-2020 project colleagues Gert Jan Nabuurs (Wageningen University),
   Viorel Blujdea and Ioan Dutca (Transylvania University of Brasov) for
   their involvement in the original part of the surveys and Pieter Vis
   (WUR) for data processing. We are likewise grateful to two anonymous
   reviewers for their helpful comments. Finally, our thanks go to all
   Swedish and Dutch respondents for their efforts in returning the forest
   and climate surveys during the first half of 2020.
CR Aguilar FX, 2014, BIOMASS BIOENERG, V71, P202, DOI 10.1016/j.biombioe.2014.10.006
   [Anonymous], 2020, State of Europes Forests 2020
   [Anonymous], 2014, A policy framework for climate and energy in the period from 2020 to 2030
   Bij12, 2023, GRANT APPL NATURE LA
   Bij12, 2019, DUTCH SUBSIDY SCHEME
   Blennow K, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0050182
   Bouwman M, 2021, FOREST ECOL MANAG, V481, DOI 10.1016/j.foreco.2020.118615
   Bowditch E, 2020, ECOSYST SERV, V43, DOI 10.1016/j.ecoser.2020.101113
   Caudullo G., 2016, Publications Office of the European Union, DOI [10.2760/776635, DOI 10.2760/776635]
   Compendium voor de Leefomgeving (CLO), 2023, FOREST AREA FOREST P
   Copini P., 2022, VAKBLAD NATUUR BOS L, V181, P3
   De Winter JC., 2010, PRACT ASSESS RES EVA, V15, P1, DOI [10.7275/bj1p-ts64, 10.7275/bj1pts64, 10.7275/BJ1P-TS64]
   den Ouden J., 2010, Bosecologie en Bosbeheer
   EC (European Commission), 2022, Proposal for a Regulation of the European Parliament and of the Council on Nature Restoration
   Eggers J, 2019, FOREST POLICY ECON, V103, P55, DOI 10.1016/j.forpol.2017.07.002
   Ellison D, 2014, ENVIRON SCI POLICY, V40, P1, DOI 10.1016/j.envsci.2014.03.004
   Eriksson L, 2018, SOC NATUR RESOUR, V31, P409, DOI 10.1080/08941920.2017.1382629
   European Commission, 2023, AM LULUCF REG 2023 8
   European Commission, 2021, Report from the Commision to the European Parliament, the Council, the European Economic and Social Cmmitee and the Committee of the Regions. Bruxels
   European Commission, 2018, REG 2018 841 EC LULU
   European Commission, 2013, OFF J EUR UNION, VL165, P80
   Eurostat, 2020, FOREST RESOURCES ARE
   Forest Europe, 2020, ADAPTATION CLIMATE C
   Forzieri G, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-21399-7
   Grassi G, 2019, CARBON BAL MANAGE, V14, DOI 10.1186/s13021-019-0123-y
   Haeler E, 2023, FOREST POLICY ECON, V146, DOI 10.1016/j.forpol.2022.102882
   Hallberg-Sramek I, 2022, FORESTS, V13, DOI 10.3390/f13010098
   Hengst-Ehrhart Y, 2019, ANN FOREST SCI, V76, DOI 10.1007/s13595-019-0878-z
   Hurmekoski E, 2018, CAN J FOREST RES, V48, P1417, DOI 10.1139/cjfr-2018-0116
   Iordan CM, 2018, CARBON BAL MANAGE, V13, DOI 10.1186/s13021-018-0101-9
   IPO & Ministry LNV, 2020, IPO PUBL
   Juutinen A, 2022, FOREST POLICY ECON, V144, DOI 10.1016/j.forpol.2022.102839
   Kaanin-Grubin M., 2021, CAN J FOREST RES, V51, pv, DOI [10.1139/cjfr-2021-0308, DOI 10.1139/CJFR-2021-0308]
   Kerr G, 2004, PLANTATION SILVICULT, P837
   Korosuo A, 2023, CARBON BAL MANAGE, V18, DOI 10.1186/s13021-023-00234-0
   Kronholm T, 2024, SMALL-SCALE FOR, V23, P85, DOI 10.1007/s11842-023-09555-x
   Kuneman G, 2020, VERKENNING KLIMAATBE
   Leszczyszyn E, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14074358
   Lidestav G, 2023, SMALL-SCALE FOR, V22, P435, DOI 10.1007/s11842-022-09538-4
   Linser S, 2023, IFOREST, V16, P325, DOI 10.3832/ifor4457-016
   Ministry LNV, 2020, COMMUNICATION   0203
   Mishra A, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-32244-w
   Moen J, 2014, CONSERV LETT, V7, P408, DOI 10.1111/conl.12098
   Mostegl NM, 2019, FOREST POLICY ECON, V99, P83, DOI 10.1016/j.forpol.2017.10.001
   Nabuurs G. J., 2018, From Science to Policy, V6
   Nabuurs GJ, 2023, COMMUN EARTH ENVIRON, V4, DOI 10.1038/s43247-023-01005-y
   Nabuurs GJ, 2017, FORESTS, V8, DOI 10.3390/f8120484
   Nilsson P, 2021, FOREST STAT 2021 SKO
   Paquel K, 2017, ANAL LULUCF ACTIONS
   Parliament E., 2021, LEGISLATIVE TRAIN, V5, P2021
   Penninkhof J., 2023, VAKBLAD NATUUR BOS L, V199, P27
   Petersson H, 2022, GCB BIOENERGY, V14, P793, DOI 10.1111/gcbb.12943
   Provincie Gelderland, 2020, VIT DIV BOS UITV BOM
   Provincie Noord-Brabant, 2020, BRABANT FOREST STRAT
   Quiroga S, 2019, FOREST POLICY ECON, V99, P136, DOI 10.1016/j.forpol.2018.08.008
   Ramage MH, 2017, RENEW SUST ENERG REV, V68, P333, DOI 10.1016/j.rser.2016.09.107
   Regeringskansliet, 2018, SWEDISH NATL FOREST
   RODRIGUEZ E, 2021, J CLEAN PROD, V280, DOI DOI 10.1016/J.JCLEPRO.2020.124527
   Schelhaas M, 2022, WOT RAPPORT 142
   Schelhaas MJ, 2003, GLOBAL CHANGE BIOL, V9, P1620, DOI 10.1046/j.1365-2486.2003.00684.x
   Schelhaas MJ., 2014, ALTERRA REP, V2545, P98
   Seidl R, 2014, NAT CLIM CHANGE, V4, P806, DOI [10.1038/nclimate2318, 10.1038/NCLIMATE2318]
   Short I., 2008, Silvicultural Guidelines for the Tending and Thinning of Broadleaves
   Sikkema R, 2023, SUSTAIN CITIES SOC, V90, DOI 10.1016/j.scs.2022.104370
   Sikkema R, 2020, FORCLIMIT PROJECT DE
   Sikkema R., 2020, VAKBLAD NBL, V169, P18
   Sikkema R, 2021, RENEW ENERG, V165, P758, DOI 10.1016/j.renene.2020.11.047
   Silvis HJ, 2015, 2017090 WAG EC RES
   Silvis HJ, 2022, 2022066 WAG EC RES
   Skogsstyrelsen, 2023, PROPERTY OWNERSHIP S
   Sousa-Silva R, 2018, FOREST POLICY ECON, V90, P22, DOI 10.1016/j.forpol.2018.01.004
   Sousa-Silva R, 2016, FOR ECOSYST, V3, DOI 10.1186/s40663-016-0082-7
   UNFCCC, 2015, C PART 15 PAR 12 DEC
   United Nations, 2023, The Sustainable Development Goals Report Special Edition
   Van Duinhoven G., 2023, VAKBLAD NBL, V199, P34
   Verkerk PJ, 2020, FOREST POLICY ECON, V115, DOI 10.1016/j.forpol.2020.102164
   Vos MAE, 2023, FOREST ECOL MANAG, V529, DOI 10.1016/j.foreco.2022.120731
   Vulturius G, 2018, REG ENVIRON CHANGE, V18, P511, DOI 10.1007/s10113-017-1218-1
   Westin K, 2023, FOREST POLICY ECON, V146, DOI 10.1016/j.forpol.2022.102881
   Wilhelmsson E, 2020, INTERNAL SLU REPORT
NR 80
TC 1
Z9 1
U1 3
U2 3
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 1873-7617
EI 1873-7854
J9 SMALL-SCALE FOR
JI Small-Scale For.
PD DEC
PY 2024
VL 23
IS 4
BP 693
EP 720
DI 10.1007/s11842-024-09576-0
EA OCT 2024
PG 28
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Forestry
GA O4R3Y
UT WOS:001326013800001
OA hybrid
DA 2025-01-10
ER

PT J
AU Okatch, H
   Remshifski, PA
   Fennessey, A
   Campbell, H
   Barnoy, S
   Friedman, J
   Kern, SB
   Frasso, R
   Sorensen, C
   Bar-Shalita, T
   Hunter, LN
AF Okatch, Harriet
   Remshifski, Patricia A.
   Fennessey, Anita
   Campbell, Haley
   Barnoy, Sivia
   Friedman, Jason
   Kern, Stephen B.
   Frasso, Rosemary
   Sorensen, Cecilia
   Bar-Shalita, Tami
   Hunter, Louis N.
TI Climate change and its impact on health: a global collaborative learning
   model
SO FRONTIERS IN MEDICINE
LA English
DT Article
DE climate change; interprofessional; healthcare; curriculum;
   international; course development; symposium
AB To address the health effects of climate change, leaders in healthcare have called for action to integrate climate adaptation and mitigation into training programs for health professionals. However, current educators may not possess sufficient climate literacy and the expertise to effectively include such content in their respective healthcare curricula. We, an international and interprofessional partnership, collaborated with experts to develop and deploy curriculum to increase health educators' and graduate health profession students' knowledge and competencies on climate change. In a tri-step process, the first phase included recruiting interested faculty members from two institutions and varying health professions. In phase two, faculty members collaborated to develop a faculty symposium on climate change including educational competencies required of health professions, practice standards, guidelines, and profession-specific content. Symposium outcomes included broader faculty member interest and commitment to create an interprofessional climate change course for healthcare graduate students. In phase three, course development resulted from collaboration between faculty members at the two institutions and faculty members from the Global Consortium on Climate and Health Education (GCCHE), with course objectives informed by GCCHE competencies. Climate experts and faculty members delivered the course content over a 10-week period to 30 faculty members and students representing seven health professions, who were surveyed (n = 13) for feedback. This course can serve as an example for international collaborators interested in developing climate change courses for health profession students. Lessons learned in this process include: climate change novice faculty members can develop impactful climate change courses; students and faculty members can be co-learners; diverse representation in course attendees enriches the learning experience; and collaboration is key.
C1 [Okatch, Harriet; Frasso, Rosemary] Thomas Jefferson Univ, Jefferson Coll Populat Hlth, Philadelphia, PA 19144 USA.
   [Remshifski, Patricia A.] Thomas Jefferson Univ, Jefferson Coll Rehabil Sci, Dept Speech Language Pathol, Philadelphia, PA USA.
   [Fennessey, Anita] Thomas Jefferson Univ, Jefferson Coll Nursing, Philadelphia, PA 19107 USA.
   [Campbell, Haley; Sorensen, Cecilia] Columbia Univ, Mailman Sch Publ Hlth, Dept Environm Hlth Sci, New York, NY USA.
   [Campbell, Haley; Sorensen, Cecilia] Columbia Univ, Mailman Sch Publ Hlth, Global Consortium Climate Change & Hlth Educ, New York, NY USA.
   [Barnoy, Sivia] Tel Aviv Univ, Fac Med & Hlth Sci, Sch Hlth Profess, Dept Nursing, Tel Aviv, Israel.
   [Friedman, Jason] Tel Aviv Univ, Fac Med & Hlth Sci, Sch Hlth Profess, Dept Phys Therapy, Tel Aviv, Israel.
   [Kern, Stephen B.] Thomas Jefferson Univ, Jefferson Coll Rehabil Sci, Dept Occupat Therapy, Philadelphia, PA USA.
   [Frasso, Rosemary] Thomas Jefferson Univ, Sidney Kimmel Med Coll, Asano Gonnella Ctr Res Med Educ & Hlth Care, Philadelphia, PA USA.
   [Sorensen, Cecilia] Columbia Univ, Dept Emergency Med, New York, NY USA.
   [Bar-Shalita, Tami] Tel Aviv Univ, Fac Med & Hlth Sci, Sch Hlth Profess, Dept Occupat Therapy, IL-6997801 Tel Aviv, Israel.
   [Hunter, Louis N.] Thomas Jefferson Univ, Jefferson Coll Hlth Profess, Philadelphia, PA USA.
   [Hunter, Louis N.] Thomas Jefferson Univ, Jefferson Coll Rehabil Sci, Dept Phys Therapy, Philadelphia, PA 19107 USA.
C3 Thomas Jefferson University; Thomas Jefferson University; Thomas
   Jefferson University; Columbia University; Columbia University; Tel Aviv
   University; Tel Aviv University; Thomas Jefferson University; Thomas
   Jefferson University; Columbia University; Tel Aviv University; Thomas
   Jefferson University; Thomas Jefferson University
RP Okatch, H (corresponding author), Thomas Jefferson Univ, Jefferson Coll Populat Hlth, Philadelphia, PA 19144 USA.
EM okatcharriet@gmail.com
RI Barnoy, Sivia/AAT-7275-2021; Bar-Shalita, Tami/AFU-9220-2022
OI Barnoy, Sivia/0000-0002-9358-3422
FU Tel Aviv University10.13039/501100004375
FX No Statement Available
CR Aasheim ET, 2023, LANCET PLANET HEALTH, V7, pE12, DOI 10.1016/S2542-5196(22)00304-7
   [Anonymous], 2018, Sustainability matters: guiding principles for sustainability in occupational therapy practice, education, and scholarship
   Briese P, 2020, CLIN SIMUL NURS, V48, P64, DOI 10.1016/j.ecns.2020.08.006
   Cerceo E, 2022, J CLIM CHANGE HEALTH, V5, DOI 10.1016/j.joclim.2021.100105
   Global Consortium on Climate and Health Education, 2023, Climate & Health Concepts for Health Professionals
   Hathaway J, 2018, CURR ENV HLTH REP, V5, P197, DOI 10.1007/s40572-018-0190-3
   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, V1st ed.
   Kotcher J, 2021, LANCET PLANET HEALTH, V5, pE316, DOI 10.1016/S2542-5196(21)00053-X
   Mckinnon S, 2022, J CLIM CHANGE HEALTH, V5, DOI 10.1016/j.joclim.2021.100086
   MEZIROW J, 1994, ADULT EDUC QUART, V44, P222, DOI 10.1177/074171369404400403
   Ong CCP, 2022, PERSPECT MED EDUC, V11, P86, DOI 10.1007/s40037-021-00687-4
   Rocque RJ, 2021, BMJ OPEN, V11, DOI 10.1136/bmjopen-2020-046333
   Rogers Heidi Honegger, 2023, Int J Environ Res Public Health, V20, DOI 10.3390/ijerph20105885
   Rom William N, 2023, Int J Environ Res Public Health, V21, DOI 10.3390/ijerph21010041
   Sarfaty M, 2016, J ALLER CL IMM-PRACT, V4, P333, DOI 10.1016/j.jaip.2015.09.018
   Shaw E, 2021, MED TEACH, V43, P272, DOI 10.1080/0142159X.2020.1860207
   Shea B, 2020, JAMA NETW OPEN, V3, DOI 10.1001/jamanetworkopen.2020.6609
   Sherratt S., 2022, Perspect ASHA Spec Interest Groups, V7, P245, DOI [10.1044/2021_PERSP-21-00186, DOI 10.1044/2021PERSP-21-00186, DOI 10.1044/2021_PERSP-21-00186]
   Slavich GM, 2012, EDUC PSYCHOL REV, V24, P569, DOI 10.1007/s10648-012-9199-6
   Sorensen C, 2023, FRONT PUBLIC HEALTH, V11, DOI 10.3389/fpubh.2023.1077306
   Tun S, 2020, MED TEACH, V42, P1112, DOI 10.1080/0142159X.2020.1796950
   United Nations, The 17 Goals
   Van Schalkwyk SC, 2019, MED EDUC, V53, P547, DOI 10.1111/medu.13804
   Vipler BS, 2023, MED EDUC, V57, P1184, DOI 10.1111/medu.15189
   Wellbery C, 2018, ACAD MED, V93, P1774, DOI 10.1097/ACM.0000000000002368
   World Health Organization (WHO), 2023, Climate change exacerbates nutrient
NR 26
TC 0
Z9 0
U1 2
U2 2
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2296-858X
J9 FRONT MED-LAUSANNE
JI Front. Med.
PD AUG 16
PY 2024
VL 11
AR 1438609
DI 10.3389/fmed.2024.1438609
PG 9
WC Medicine, General & Internal
WE Science Citation Index Expanded (SCI-EXPANDED)
SC General & Internal Medicine
GA E8U8E
UT WOS:001305702500001
PM 39234047
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Seibert, SL
   Greskowiak, J
   Essink, GHPO
   Massmann, G
AF Seibert, Stephan L.
   Greskowiak, Janek
   Essink, Gualbert H. P. Oude
   Massmann, Gudrun
TI Understanding Climate Change and Anthropogenic Impacts on the
   Salinization of Low-Lying Coastal Groundwater Systems
SO EARTHS FUTURE
LA English
DT Article
DE saltwater intrusion; coastal hydrogeology; numerical modeling; sea-level
   rise; land subsidence; climate adaptation
ID SEA-LEVEL RISE; SALTWATER INTRUSION; SEAWATER INTRUSION; SALINITY;
   AQUIFER; VULNERABILITY; NETWORK
AB Fresh coastal groundwater is a valuable water resource of global significance, but its quality is threatened by saltwater intrusion. Excessive groundwater abstraction, sea-level rise (SLR), land subsidence and other climate-related factors are expected to accelerate this process in the future. The objective of this study is to (a) quantify the impact of projected climate change and (b) explore the role of individual hydrogeological boundaries on groundwater salinization of low-lying coastal groundwater systems until 2100 CE. We employ numerical density-dependent groundwater flow and salt transport modeling for this purpose, using Northwestern Germany as a case. Separate model variants are constructed and forced with climate data, that is, projected SLR and groundwater recharge, as well as likely ranges of other hydrogeological boundaries, including land subsidence, abstraction rates and drain levels. We find that autonomous salinization in the marsh areas, resulting from non-equilibrium of the present-day groundwater salinity distribution with current boundary conditions, is responsible for >50% of the salinization increase until 2100 CE. Sea-level rise, land subsidence and drain levels are the other major factors controlling salinization. We further show that salinization of the water resources is a potential threat to coastal water users, including water suppliers and the agrarian sector, as well as coastal ecosystems. Regional-scale uplifting of drain levels is identified as an efficient measure to mitigate salinization of deep and shallow groundwater in the future. The presented modeling approach highlights the consequences of climate change and anthropogenic impacts for coastal salinization, supporting the timely development of mitigation strategies.
C1 [Seibert, Stephan L.; Greskowiak, Janek; Massmann, Gudrun] Carl von Ossietzky Univ Oldenburg, Inst Biol & Environm Sci, Oldenburg, Germany.
   [Seibert, Stephan L.; Greskowiak, Janek; Massmann, Gudrun] Carl von Ossietzky Univ Oldenburg, Inst Chem & Biol Marine Environm ICBM, Oldenburg, Germany.
   [Essink, Gualbert H. P. Oude] Unit Subsurface & Groundwater Syst, Utrecht, Netherlands.
   [Essink, Gualbert H. P. Oude] Univ Utrecht, Dept Phys Geog, Utrecht, Netherlands.
C3 Carl von Ossietzky Universitat Oldenburg; Carl von Ossietzky Universitat
   Oldenburg; Utrecht University
RP Seibert, SL (corresponding author), Carl von Ossietzky Univ Oldenburg, Inst Biol & Environm Sci, Oldenburg, Germany.; Seibert, SL (corresponding author), Carl von Ossietzky Univ Oldenburg, Inst Chem & Biol Marine Environm ICBM, Oldenburg, Germany.
EM stephan.seibert@uol.de
RI Massmann, Gudrun/L-8702-2014
OI Massmann, Gudrun/0000-0001-6907-7733; Oude Essink,
   Gualbert/0000-0003-0931-6944; Seibert, Stephan/0000-0002-6086-2943
FU DFG through its Major Research Instrumentation Programs [INST 184/225-1
   FUGG]; Ministry of Science and Culture (MWK) of the Lower Saxony State;
   DFG [MA 3274/9-1]; WAKOS (BMBF) [01LR2003E]; DFG research unit FOR 5094:
   The dynamic deep subsurface of high-energy beaches (DynaDeep) [GR
   4514/3-1]
FX We thank the following institutions for manifold support: Deltares
   (technical modeling support), Landesamt fuer Bergbau, Energie und
   Geologie (LBEG) and Niedersaechsisches Kompetenzzentrum Klimawandel
   (NIKO) (provision of mGROWA18/22, geologic and freshwater interface
   data), Niedersaechsischer Landesbetrieb fur Wasserwirtschaft,
   Kuesten-und Naturschutz (NLWKN) (provision of groundwater
   heads/salinities, river levels/discharges), Oldenburg-Ostfriesischer
   Wasserverband (OOWV) (provision of geologic data and abstraction rates)
   as well as regional water works (provision of abstraction rates). We
   thank L. Karrasch and B. Siebenhuener for fruitful collaboration within
   the SALTSA project. Simulations were performed at the University of
   Oldenburg HPC Cluster ROSA, located at the University of Oldenburg
   (Germany) and funded by the DFG through its Major Research
   Instrumentation Programs (INST 184/225-1 FUGG) and the Ministry of
   Science and Culture (MWK) of the Lower Saxony State. The DFG is thanked
   for SALTSA project funding (MA 3274/9-1) within the Special Priority
   Programme (SPP-1889) "Regional Sea Level Change and Society (SeaLevel)."
   Research related to this article further benefited from funding of the
   projects WAKOS (BMBF; support code 01LR2003E) and the DFG research unit
   FOR 5094: The dynamic deep subsurface of high-energy beaches (DynaDeep)
   (GR 4514/3-1).
CR Ataie-Ashtiani B, 2013, HYDROGEOL J, V21, P1673, DOI 10.1007/s10040-013-1021-0
   Bhuiyan MJAN, 2012, ESTUAR COAST SHELF S, V96, P219, DOI 10.1016/j.ecss.2011.11.005
   Böhme D, 2011, LIMNOLOGICA, V41, P80, DOI 10.1016/j.limno.2010.08.003
   Bundesamt fr Kartographie und Geodsie (BKG) Federal Agency for Cartography and Geodesy, 2013, Digitales Gelndemodell Gitterweite 200 m DGM200
   Cantelon JA, 2022, WATER RESOUR RES, V58, DOI 10.1029/2022WR032614
   Colombani N, 2015, WATER RESOUR MANAG, V29, P603, DOI 10.1007/s11269-014-0795-8
   de Louw PGB, 2010, J HYDROL, V394, P494, DOI 10.1016/j.jhydrol.2010.10.009
   Delsman JR, 2014, HYDROL EARTH SYST SC, V18, P3891, DOI 10.5194/hess-18-3891-2014
   Deltares, 2020, iMOD 5.2: IMODWQ (water quality)
   Deutscher Wetterdients (DWD) German Meteorological Service, 2021, Climate Data for the model region Dataset
   Döll P, 2009, ENVIRON RES LETT, V4, DOI 10.1088/1748-9326/4/3/035006
   Doherty J. E., 2021, PEST MODEL INDEPENDE, P274
   Doherty J. E., 2021, PEST MODEL INDEPENDE, P394
   Ertl G., 2019, GeoBerichte, V36
   Eslami S, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-55018-9
   Essink GHPO, 2010, WATER RESOUR RES, V46, DOI 10.1029/2009WR008719
   Essink GHPO, 2001, TRANSPORT POROUS MED, V43, P137, DOI 10.1023/A:1010625913251
   Ferguson G, 2012, NAT CLIM CHANGE, V2, P342, DOI [10.1038/NCLIMATE1413, 10.1038/nclimate1413]
   Feseker T, 2007, HYDROGEOL J, V15, P267, DOI 10.1007/s10040-006-0151-z
   Fox-Kemper B., 2021, Climate Change 2021: The Physical Science Basis, DOI DOI 10.1017/9781009157896.011.1212
   Garner G. G., 2021, IPCC AR6 sealevel rise projections, version 20210809
   González E, 2021, GRUNDWASSER, V26, P343, DOI 10.1007/s00767-021-00496-w
   Green NR, 2014, HYDROGEOL J, V22, P609, DOI 10.1007/s10040-013-1092-y
   Grieve Catherine M., 2012, Agricultural Salinity Assessment and Management, Second Edition, P405
   Hajati M., 2022, Dokumentation der niederschsischen Klimaprojektionsdaten AR5NI v2.1, DOI [10.48476/geofakt3912022, DOI 10.48476/GEOFAKT3912022]
   Harbaugh A.W., 2000, US GEOLOGICAL SURVEY
   Herbert ER, 2015, ECOSPHERE, V6, DOI 10.1890/ES14-00534.1
   Herrera-García G, 2021, SCIENCE, V371, P34, DOI 10.1126/science.abb8549
   Herrmann F, 2013, HYDROL WASSERBEWIRTS, V57, P206, DOI 10.5675/HyWa_2013,5_2
   Holt T, 2017, J HYDROL, V554, P666, DOI 10.1016/j.jhydrol.2017.09.014
   Horton BP, 2020, NPJ CLIM ATMOS SCI, V3, DOI 10.1038/s41612-020-0121-5
   Illangasekare T, 2006, WATER RESOUR RES, V42, DOI 10.1029/2006WR004876
   IPCC, 2019, Special Report on the Ocean and Cryosphere in a Changing Climate, P321, DOI DOI 10.1017/9781009157964.006
   Karle M, 2021, NETH J GEOSCI, V100, DOI 10.1017/njg.2021.10
   Karrasch L, 2023, EARTH SYST GOV-NETH, V17, DOI 10.1016/j.esg.2023.100179
   Kopp RE, 2023, GEOSCI MODEL DEV, V16, P7461, DOI 10.5194/gmd-16-7461-2023
   Kopp RE, 2014, EARTHS FUTURE, V2, P383, DOI 10.1002/2014EF000239
   Landesamt fr Bergbau Energie und Geologie (LBEG) State Office for Mining Energy and Geology, 2018, Geologic models for the EastFrisian regions Nordenham and Varel
   Landesamt fur Bergbau Energie und Geologie (LBEG) State Office for Mining Energy and Geology & Niedersachsisches Kompetenzzentrum Klimawandel (NIKO) Lower Saxony Competence Center for Climate Change, 2022, Grundwasserneubildung fur die Klimaszenarien-Zeitraume (Methode: mGROWA22) - NIBIS Kartenserver im Niedersachsischen Bodeninformationssystem Dataset
   Langevin C.D., 2008, US GEOLOGICAL SURVEY, P39
   Mabrouk M, 2018, WATER-SUI, V10, DOI 10.3390/w10111690
   [Masson-Delmotte V. Intergovernmental Panel on Climate Change Intergovernmental Panel on Climate Change], 2021, 6 ASSESSMENT REPORT, DOI [DOI 10.1017/9781009157896, 10.1017/9781009157896]
   Meyer R, 2019, WATER RESOUR RES, V55, P1792, DOI 10.1029/2018WR023624
   Michael HA, 2013, WATER RESOUR RES, V49, P2228, DOI 10.1002/wrcr.20213
   Minderhoud PSJ, 2020, ENVIRON RES COMMUN, V2, DOI 10.1088/2515-7620/ab5e21
   Nicholls RJ, 2021, NAT CLIM CHANGE, V11, P338, DOI 10.1038/s41558-021-00993-z
   Niederschsischer Landesbetrieb fr Wasserwirtschaft Ksten und Naturschutz (NLWKN) Lower Saxony Water Management Coastal Defence and Nature Conservation Agency, 2016, Fliegewsser (WRRL) Niedersachsen
   OldenburgOstfriesischer Wasserverband (OOWV) OldenburgEast Frisian Water Board, 2020, Geologic model for the German EastFrisian region
   Paldor A, 2021, WATER RESOUR RES, V57, DOI 10.1029/2020WR029213
   Porter-Goff ER, 2013, ECOL INDIC, V32, P97, DOI 10.1016/j.ecolind.2013.03.017
   Portmann FT, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/2/024023
   Reutter E., 2013, Geofakten, V21
   Seibert S. L., 2024, Dataset. Earth's Future. Zenodo, DOI [10.5281/zenodo.12607668, DOI 10.5281/ZENODO.12607668]
   Seibert SL, 2023, WATER RESOUR RES, V59, DOI 10.1029/2022WR033151
   Seibert SL, 2018, APPL GEOCHEM, V92, P196, DOI 10.1016/j.apgeochem.2018.03.001
   Shirzaei M, 2021, NAT REV EARTH ENV, V2, P40, DOI 10.1038/s43017-020-00115-x
   Small C, 2003, J COASTAL RES, V19, P584
   Smith AJ, 2001, HYDROL PROCESS, V15, P2595, DOI 10.1002/hyp.303
   Tiggeloven T, 2020, NAT HAZARD EARTH SYS, V20, P1025, DOI 10.5194/nhess-20-1025-2020
   van Engelen J, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/aca16c
   van Engelen J, 2019, HYDROL EARTH SYST SC, V23, P5175, DOI 10.5194/hess-23-5175-2019
   Verkaik J, 2021, ENVIRON MODELL SOFTW, V143, DOI 10.1016/j.envsoft.2021.105092
   Vineis P, 2011, J EPIDEMIOL GLOB HEA, V1, P5, DOI 10.1016/j.jegh.2011.09.001
   Visser M., 2019, iMODPython: Work with iMOD MODFLOW models in Python
   Wada Y, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/10/104003
   Werner AD, 2013, ADV WATER RESOUR, V51, P3, DOI 10.1016/j.advwatres.2012.03.004
   Zamrsky D, 2024, EARTHS FUTURE, V12, DOI 10.1029/2023EF003581
   Zheng C., 1999, Final Report, Contract Report SERDP-99-1
NR 68
TC 1
Z9 1
U1 4
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 AUG
PY 2024
VL 12
IS 8
AR e2024EF004737
DI 10.1029/2024EF004737
PG 19
WC Environmental Sciences; Geosciences, Multidisciplinary; Meteorology &
   Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Geology; Meteorology & Atmospheric
   Sciences
GA A6E5Y
UT WOS:001283447800001
OA gold
DA 2025-01-10
ER

PT J
AU Casagrande, D
   Emanuel, L
   Freitas, C
   Oliveira, F
AF Casagrande, Dieison
   Emanuel, Lucas
   Freitas, Carlos
   Oliveira, Felipe
TI Climate adaptation policies and rural income: Evidence from social
   technologies in Brazil
SO WORLD DEVELOPMENT
LA English
DT Article
DE Second water cisterns; Social technologies; Rural income; Brazil
ID SUB-SAHARAN AFRICA; FOOD SECURITY; POVERTY; WATER; IRRIGATION; FARMERS;
   GROUNDWATER; MANAGEMENT; TENURE; IMPACT
AB Several developing countries have implemented programs to support rural families, but there is still a lack of evidence on their effectiveness. This paper seeks to address the existing gap by analyzing the impact of the Second Water Cisterns Program (SWCP) on the income of Brazilian family farmers. The policy intervention consists of a social technology that harvests rainwater for use in agriculture. We combined data from family farmers with administrative data from the program, identifying the participation status of each farmer. Using the Differences in Differences strategy and exploring the time when the farms received the cistern over the period from 2007 to 2016, our results show that the SWCP has a positive impact on the income of rural farms, causing an increase of 5.9%. Heterogeneous effects indicate a greater magnitude of impact among low-income and smaller family farmers. Moreover, the effect is more pronounced for farmers in municipalities with a lower share of agriculture in the total economy as well as for farmers in municipalities with lower rainfall. Our findings highlight the importance of production and productivity as a potential mechanism for raising the income level of rural farmers, with the impact concentrating on low-income family farmers. Based on the cost-benefit analysis, each Brazilian Real invested in SWCP generates an average return of approximately BRL 0.11. These findings suggest that the provision of low-cost social technologies to families in rural areas may be an important mechanism for local economic development.
C1 [Casagrande, Dieison] Univ Fed Santa Catarina, Dept Econ & Int Relat, Florianopolis, SC, Brazil.
   [Emanuel, Lucas] Univ Fed Bahia UFBA, Fac Econ, Salvador, BA, Brazil.
   [Freitas, Carlos] Univ Fed Rondonopolis UFR, Dept Econ, Rondonopolis, Brazil.
   [Oliveira, Felipe] Univ Fed Mato Grosso UFMT, Fac Econ, Cuiaba, Brazil.
C3 Universidade Federal de Santa Catarina (UFSC); Universidade Federal da
   Bahia; Universidade Federal de Mato Grosso do Sul
RP Casagrande, D (corresponding author), Univ Fed Santa Catarina, Dept Econ & Int Relat, Florianopolis, SC, Brazil.
EM dieison.casagrande@ufsm.br; lucasemanuel@ufba.br;
   carlos.freitas@ufr.edu.br; felipe.oliveira@ufmt.br
OI Casagrande, Dieison/0000-0003-4096-3971
FU Secretariat for Evaluation and Information Management/Ministry of
   Citizenship, Brazil
FX The authors are grateful to the Editor and two anonymous referees who
   provided useful comments to improve the quality of the manuscript. This
   work was supported by the Secretariat for Evaluation and Information
   Management/Ministry of Citizenship, Brazil (SAGI/MC) . We are grateful
   to participants at the Economic and Socio-Environmental Research Center
   (Nupes/UFMT) , ANPEC 2022, UCB, UFPB, and UFPR seminars for comments and
   suggestions.
CR Ali A, 2017, CLIM RISK MANAG, V16, P183, DOI 10.1016/j.crm.2016.12.001
   Aragón FM, 2021, AM ECON J-ECON POLIC, V13, P1, DOI 10.1257/pol.20190316
   Balana BB, 2020, WATER RESOUR ECON, V29, DOI 10.1016/j.wre.2019.03.001
   Belay A, 2022, HELIYON, V8, DOI 10.1016/j.heliyon.2022.e12089
   Bertrand M, 2004, Q J ECON, V119, P249, DOI 10.1162/003355304772839588
   Biazin B, 2012, PHYS CHEM EARTH, V47-48, P139, DOI 10.1016/j.pce.2011.08.015
   Blakeslee D, 2023, J DEV ECON, V161, DOI 10.1016/j.jdeveco.2022.102997
   Blakeslee D, 2020, AM ECON REV, V110, P200, DOI 10.1257/aer.20180976
   Brasil, 2013, LEI N 12.873, DE 24 DE OUTUBRO DE 2013.
   Burney JA, 2012, WORLD DEV, V40, P110, DOI 10.1016/j.worlddev.2011.05.007
   Carter MR, 2007, WORLD DEV, V35, P835, DOI 10.1016/j.worlddev.2006.09.010
   Da Mata D, 2023, J PUBLIC ECON, V220, DOI 10.1016/j.jpubeco.2023.104835
   Da Mata D, 2020, J DEV ECON, V146, DOI 10.1016/j.jdeveco.2020.102459
   Deininger K, 2006, EUR ECON REV, V50, P1245, DOI 10.1016/j.euroecorev.2005.02.001
   Dillon A, 2011, WORLD DEV, V39, P2165, DOI 10.1016/j.worlddev.2011.04.006
   Do MH, 2024, INT J WATER RESOUR D, V40, P463, DOI 10.1080/07900627.2023.2233645
   Duflo E, 2007, Q J ECON, V122, P601, DOI 10.1162/qjec.122.2.601
   Dyer J, 2023, J DEV ECON, V163, DOI 10.1016/j.jdeveco.2022.103034
   Embaye TAG, 2020, SUST WAT RESOUR MAN, V6, DOI 10.1007/s40899-020-00435-2
   Fankhauser S, 2017, ANNU REV RESOUR ECON, V9, P209, DOI 10.1146/annurev-resource-100516-033554
   FEDER G, 1991, WORLD BANK ECON REV, V5, P135, DOI 10.1093/wber/5.1.135
   Gebrehiwot T, 2013, ENVIRON MANAGE, V52, P29, DOI 10.1007/s00267-013-0039-3
   Girma Y, 2022, J AGR FOOD RES, V7, DOI 10.1016/j.jafr.2021.100253
   Gomez M, 2019, WATER-SUI, V11, DOI 10.3390/w11020202
   Hagerty N., 2021, Adaptation to surface water scarcity in irrigated agriculture
   Hagos F, 2012, AGR ECON-BLACKWELL, V43, P99, DOI 10.1111/j.1574-0862.2012.00623.x
   Harvey C. A., 2018, Agriculture & Food Security, V7, P57, DOI 10.1186/s40066-018-0209-x
   Hornbeck R, 2014, AM ECON J-APPL ECON, V6, P190, DOI 10.1257/app.6.1.190
   Kahn ME, 2016, REV ENV ECON POLICY, V10, P166, DOI 10.1093/reep/rev023
   Kandulu JM, 2017, INT J WATER RESOUR D, V33, P270, DOI 10.1080/07900627.2016.1188060
   Lobell DB, 2010, AGR FOREST METEOROL, V150, P1443, DOI 10.1016/j.agrformet.2010.07.008
   Lowder SK, 2016, WORLD DEV, V87, P16, DOI 10.1016/j.worlddev.2015.10.041
   Maddison DavidJ., 2007, PERCEPTION ADAPTATIO, DOI 10.1596/1813-9450-4308
   Maitre N., 2018, The employment impact of climate change adaptation
   Makate C, 2019, J ENVIRON MANAGE, V231, P858, DOI 10.1016/j.jenvman.2018.10.069
   Miller DL, 2023, J ECON PERSPECT, V37, P203, DOI 10.1257/jep.37.2.203
   Mukherjee M, 2024, WORLD DEV, V179, DOI 10.1016/j.worlddev.2024.106600
   Nguyen TT, 2020, WEATHER CLIM EXTREME, V30, DOI 10.1016/j.wace.2020.100286
   Ortiz-Bobea A., 2021, HDB AGR EC, P3981, DOI DOI 10.1016/BS.HESAGR.2021.10.002
   Pachauri R.K., 2014, Intergovernmental Panel on Climate Change Report (IPCC)
   Pardey PG, 2016, FOOD POLICY, V65, P1, DOI 10.1016/j.foodpol.2016.09.009
   Passador CS, 2010, CAD GEST PUBLICA CID, V15, P65
   Rambachan A, 2023, REV ECON STUD, V90, P2555, DOI 10.1093/restud/rdad018
   Rosegrant MW, 2009, ANNU REV ENV RESOUR, V34, P205, DOI 10.1146/annurev.environ.030308.090351
   Roth J, 2023, J ECONOMETRICS, V235, P2218, DOI 10.1016/j.jeconom.2023.03.008
   Roth JONATHAN, 2022, AM ECON REV INSIGHTS, V4, P305
   Santana Vitor Leal, 2020, Investimentos Transformadores Para um Estilo de Desenvolvimento Sustentavel: Estudos de Casos de Grande Impulso (Big Push) Para a Sustentabilidade No Brasil.
   Sekhri S, 2014, AM ECON J-APPL ECON, V6, P76, DOI 10.1257/app.6.3.76
   Sun LY, 2021, J ECONOMETRICS, V225, P175, DOI 10.1016/j.jeconom.2020.09.006
   Tessema YA, 2018, ENVIRON DEV, V25, P33, DOI 10.1016/j.envdev.2017.11.001
   Thinda KT, 2020, LAND USE POLICY, V99, DOI 10.1016/j.landusepol.2020.104858
   UN-Water, 2019, UN world water development report
   UNESCO World Water Assessment P, 2023, UN WORLD WAT DEV REP
   Valencia V, 2019, AGRON SUSTAIN DEV, V39, DOI 10.1007/s13593-019-0572-4
   Yosef BA., 2015, INT J WATER RESOURCE, V7, P17
NR 55
TC 1
Z9 1
U1 11
U2 14
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 SEP
PY 2024
VL 181
AR 106683
DI 10.1016/j.worlddev.2024.106683
EA JUN 2024
PG 13
WC Development Studies; Economics
WE Social Science Citation Index (SSCI)
SC Development Studies; Business & Economics
GA UU6D6
UT WOS:001250605800001
DA 2025-01-10
ER

PT J
AU Rostam, MG
   Abbasi, A
AF Rostam, Mehdi Gholami
   Abbasi, Alireza
TI Enhancing building energy efficiency through a climate adaptive design:
   Considering upcoming extreme climate conditions
SO JOURNAL OF CLEANER PRODUCTION
LA English
DT Article
DE Climate change; Dynamic design; Energy efficiency; Morphing method;
   Synthesized weather files
ID WEATHER DATA SETS; THERMAL COMFORT; COMMERCIAL BUILDINGS; FUTURE
   CLIMATE; SIMULATION; PERFORMANCE
AB Known as one of the significant sources of impacting building energy efficiency, climate change can drastically alter the long-term energy consumption patterns of buildings. It is widely acknowledged in the literature that designs based on conventional pathways relying solely on historical weather data disregard the effects of the changing climate and lose their intended energy performance over time. Several endeavors have been made to generate weather files capable of capturing the essence of the changing climate and carrying its variability. In line with these efforts, the synthesized weather files have emerged as a promising alternative to the commonly used morphing method for incorporating climate change variability into building energy designs. However, a comprehensive framework with a potential to accommodate this variability in this context is yet to be investigated. Addressing this gap, the present study aims to propose a novel framework that can facilitate dynamic design upgrades in response to the changing climate including the extreme climate conditions. This framework has been applied to a case study building in Australia and around 31% annual thermal load reduction, on average, has been achieved. Furthermore, the results showed that conventional design pathways are likely to leave buildings inadequately prepared against the upcoming climate conditions. Therefore, the proposed framework is capable of generating a dynamic design that not only maintains the expected energy performance by incorporating the changing climate into its structure but also draws a more realistic picture of the building energy demand pattern over time.
C1 [Rostam, Mehdi Gholami; Abbasi, Alireza] Univ New South Wales, Sch Engn & Informat Technol, Canberra, ACT, Australia.
C3 University of New South Wales Sydney
RP Rostam, MG (corresponding author), Univ New South Wales, Sch Engn & Informat Technol, Canberra, ACT, Australia.
EM m.gholami_rostam@adfa.edu.au
RI Abbasi, Alireza/HLW-8556-2023; Abbasi, Alireza/K-9295-2013
OI Abbasi, Alireza/0000-0001-9136-1837
CR Abdou N, 2022, J BUILD ENG, V61, DOI 10.1016/j.jobe.2022.105332
   'Agostino D, 2024, ENERGY, V288, DOI 10.1016/j.energy.2023.129886
   American Society of Heating, 2004, ASHRAE Standard: Standards for Natural and Mechanical Ventilation
   Anandhi A, 2011, WATER RESOUR RES, V47, DOI 10.1029/2010WR009104
   Baglivo C, 2023, J CLEAN PROD, V411, DOI 10.1016/j.jclepro.2023.137345
   Baldinelli G, 2022, ENERG BUILDINGS, V268, DOI 10.1016/j.enbuild.2022.112209
   Belcher S. E., 2005, Building Services Engineering Research & Technology, V26, P49, DOI 10.1191/0143624405bt112oa
   Bre F, 2017, ENERG BUILDINGS, V154, P283, DOI 10.1016/j.enbuild.2017.08.002
   Carlucci F, 2023, ENERG BUILDINGS, V289, DOI 10.1016/j.enbuild.2023.113056
   Chan ALS, 2006, ENERG CONVERS MANAGE, V47, P87, DOI 10.1016/j.enconman.2005.02.010
   Crawley D.B., 2015, Proceedings of the 14th Conference of International Building Performance Simulation Association BS2015, P2655
   Crawley DB, 2000, ASHRAE J, V42, P49
   CSIRO, 2020, CLIM CHANG AUSTR
   CSIRO and BoM, 2015, CLIM CHANG AUSTR PRO
   Hosseini M, 2021, ENERG BUILDINGS, V230, DOI 10.1016/j.enbuild.2020.110543
   Hosseini SM, 2019, BUILD ENVIRON, V153, P186, DOI 10.1016/j.buildenv.2019.02.040
   Invidiata A, 2016, ENERG BUILDINGS, V130, P20, DOI 10.1016/j.enbuild.2016.07.067
   Kim H, 2020, ENERG BUILDINGS, V219, DOI 10.1016/j.enbuild.2020.110020
   Lapisa R, 2018, BUILD ENVIRON, V132, P83, DOI 10.1016/j.buildenv.2018.01.029
   Li HL, 2023, ENERGY, V278, DOI 10.1016/j.energy.2023.128020
   Liu XJ, 2023, RENEW SUST ENERG REV, V183, DOI 10.1016/j.rser.2023.113458
   Moazami A, 2019, ENERG BUILDINGS, V202, DOI 10.1016/j.enbuild.2019.109378
   Moazami A, 2019, APPL ENERG, V238, P696, DOI 10.1016/j.apenergy.2019.01.085
   Mousavi S, 2022, ENERG BUILDINGS, V263, DOI 10.1016/j.enbuild.2022.112053
   Murtagh N, 2020, J CLEAN PROD, V268, DOI 10.1016/j.jclepro.2020.122264
   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
   Pajek L, 2021, APPL ENERG, V297, DOI 10.1016/j.apenergy.2021.117116
   Phillips R, 2017, ENERG BUILDINGS, V146, P295, DOI 10.1016/j.enbuild.2017.04.009
   Qin YD, 2022, SUSTAIN CITIES SOC, V78, DOI 10.1016/j.scs.2021.103625
   Rey-Hernández JM, 2018, ENERG BUILDINGS, V174, P85, DOI 10.1016/j.enbuild.2018.06.006
   Rostam MG, 2023, APPL ENERG, V341, DOI 10.1016/j.apenergy.2023.121146
   Rostam MG, 2022, J CLEAN PROD, V378, DOI 10.1016/j.jclepro.2022.134543
   Sartori I, 2012, ENERG BUILDINGS, V48, P220, DOI 10.1016/j.enbuild.2012.01.032
   Shum C, 2023, ENERG BUILDINGS, V300, DOI 10.1016/j.enbuild.2023.113638
   Silva AS, 2016, BUILD ENVIRON, V102, P95, DOI 10.1016/j.buildenv.2016.03.004
   Wang SY, 2021, BUILD ENVIRON, V195, DOI 10.1016/j.buildenv.2021.107777
   Wijesuriya S, 2018, APPL ENERG, V222, P497, DOI 10.1016/j.apenergy.2018.03.119
   Xiong J, 2023, ENERGY, V269, DOI 10.1016/j.energy.2023.126789
   Yang YC, 2021, APPL ENERG, V298, DOI 10.1016/j.apenergy.2021.117246
   Zhai YN, 2019, RENEW ENERG, V134, P1190, DOI 10.1016/j.renene.2018.09.024
   Zhou YK, 2023, ENERG BUILDINGS, V279, DOI 10.1016/j.enbuild.2022.112649
NR 42
TC 1
Z9 1
U1 5
U2 7
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 APR 15
PY 2024
VL 450
AR 141747
DI 10.1016/j.jclepro.2024.141747
EA MAR 2024
PG 12
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 QD5P3
UT WOS:001218956400001
OA hybrid
DA 2025-01-10
ER

PT J
AU Ye, PY
   Liu, ZX
   Wang, XW
   Zhang, YYS
AF Ye, Peiying
   Liu, Zhixi
   Wang, Xiaowu
   Zhang, Yaoyushan
TI Barriers to green human resources management (GHRM) implementation in
   developing countries: evidence from China
SO ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
LA English
DT Article
DE Green human resource management; Green innovation; China; Barriers;
   Green policies
ID CORPORATE SOCIAL-RESPONSIBILITY; PERFORMANCE; IMPACT
AB Because of the current climate adaptation and long-term viability advancements, campaigners both locally and globally are pressuring businesses to embrace green practices. But there are challenges to putting green policies into action. The goal of this research was to analyze the most significant challenges encountered by Chinese businesses when attempting to implement environmentally responsible HR practices (GHRM). There were seventeen setbacks found, and these were sorted into five main groups. In order to pilot test the survey questions, we spoke with twenty experts in the fields of human resources and environmental management. One hundred and ninety-nine questionnaires were subsequently distributed to a random sample of company CEOs (19), HR managers (30), CFOs (30), and HR directors (40). The PSI approach was used to establish a hierarchy of the most significant obstacles and their subobstacles. Twenty-three percent of GHRM barriers in the research area were attributable to economic factors. The absence of financial resources emerged as the most crucial obstacle overall (with a score of 0.99) and among the subbarriers. The second most common barrier was found to be political and regulatory (20.1%), while the least common was found to be cultural and educational (18.2%). Government and financial institutions can help businesses overcome the most significant obstacles by offering low-interest loans for the development and implementation of sustainable business strategies and initiatives. As such, this study complements the current body of literature on green HR. Examining the challenges faced when trying to put GHRM into practice in a poor country context, this helps policymakers and practitioners in China and other similar economies understand environmental innovation barriers and develop policies to overcome them.
C1 [Ye, Peiying] South China Agr Univ, Zhujiang Coll, Business Coll, Guangzhou 510900, Peoples R China.
   [Liu, Zhixi] Huazhong Univ Sci & Technol, Nontraditonal Secur, Wuhan 430000, Peoples R China.
   [Wang, Xiaowu] Nanchang Hangkong Univ, Sch Int Educ, Nanchang 330063, Peoples R China.
   [Zhang, Yaoyushan] Shandong Inst Commerce & Technol, Informat Technol Applicat Innovat & Network Secur, Jinan 250103, Peoples R China.
C3 South China Agricultural University; Huazhong University of Science &
   Technology; Nanchang Hangkong University; Shandong Institute of Commerce
   & Technology
RP Zhang, YYS (corresponding author), Shandong Inst Commerce & Technol, Informat Technol Applicat Innovat & Network Secur, Jinan 250103, Peoples R China.
EM ypy0210lw@163.com; Liuzx0813@163.com; promethusa@163.com;
   18615313954@163.com
OI zhang, yaoyushan/0009-0005-9513-7361
CR Aboramadan M, 2021, INT J CONTEMP HOSP M, V33, P3199, DOI 10.1108/IJCHM-12-2020-1440
   Aboramadan M, 2022, PERS REV, V51, P1788, DOI 10.1108/PR-02-2021-0078
   Ahmed M, 2021, INT J HOSP MANAG, V94, DOI 10.1016/j.ijhm.2020.102852
   Ahmed RR, 2023, HELIYON, V9, DOI 10.1016/j.heliyon.2022.e12679
   Al-Shammari A., 2022, FRONT ENV SCI-SWITZ, V10, P581
   Al-Swidi AK, 2021, J CLEAN PROD, V316, DOI 10.1016/j.jclepro.2021.128112
   Alavi S, 2023, INT J PRODUCT PERFOR, V72, P599, DOI 10.1108/IJPPM-05-2020-0232
   Ali M, 2022, INT J MANPOWER, V43, P614, DOI 10.1108/IJM-04-2020-0185
   Ansari N, 2022, VISION, P78, DOI [10.1177/09722629221092133, DOI 10.1177/09722629221092133]
   Awan FH, 2023, ENVIRON SCI POLLUT R, V30, P2958, DOI 10.1007/s11356-022-22424-y
   Bahuguna PC, 2023, BENCHMARKING, V30, P585, DOI 10.1108/BIJ-10-2021-0619
   Chen LM, 2023, SUSTAIN CITIES SOC, V96, DOI 10.1016/j.scs.2023.104654
   Cheng C, 2023, MANAGE INT REV, V63, P403, DOI 10.1007/s11575-023-00502-8
   Cheng YF, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph19031807
   Jabbour CJC, 2016, J CLEAN PROD, V112, P1824, DOI 10.1016/j.jclepro.2015.01.052
   Darban G, 2022, EMPL RELAT, V44, P1092, DOI 10.1108/ER-05-2021-0215
   Du LJ, 2023, ENVIRON SCI POLLUT R, V30, P1540, DOI 10.1007/s11356-022-22221-7
   Ercantan O, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14031718
   Faisal S, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su15032259
   Farrukh M, 2022, TECHNOL FORECAST SOC, V179, DOI 10.1016/j.techfore.2022.121643
   Govindan K, 2015, EXPERT SYST APPL, V42, P7207, DOI 10.1016/j.eswa.2015.04.030
   Guo BN, 2023, ECON MODEL, V120, DOI 10.1016/j.econmod.2023.106194
   Guo Q, 2022, TECHNOL FORECAST SOC, V184, DOI 10.1016/j.techfore.2022.122003
   Haldorai K, 2022, TOURISM MANAGE, V88, DOI 10.1016/j.tourman.2021.104431
   Harvey G, 2013, INT J HUM RESOUR MAN, V24, P152, DOI 10.1080/09585192.2012.669783
   Huang X, 2021, J ECON BEHAV ORGAN, V191, P387, DOI 10.1016/j.jebo.2021.09.005
   Irani F, 2022, J HOSP MARKET MANAG, V31, P570, DOI 10.1080/19368623.2022.2022554
   Kanan M, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su15021077
   Kara K, 2023, SUPPLY CHAIN FORUM, V24, P488, DOI 10.1080/16258312.2022.2045873
   Karatepe OM, 2022, INT J HOSP MANAG, V103, DOI 10.1016/j.ijhm.2022.103202
   Kaynak H., 2009, Academy of Management Proceedings, V2009, P1, DOI [DOI 10.5465/AMBPP.2009.44256538, 10.5465/AMBPP.2009.44256538]
   Kim YJ, 2019, INT J HOSP MANAG, V76, P83, DOI 10.1016/j.ijhm.2018.04.007
   Kumar S, 2021, J CLEAN PROD, V293, DOI 10.1016/j.jclepro.2021.126023
   Latif Y, 2021, ENVIRON SCI POLLUT R, V28, P60019, DOI 10.1007/s11356-021-14792-8
   Li XT, 2023, NEURAL COMPUT APPL, V35, P2045, DOI 10.1007/s00521-022-07377-0
   Li ZP, 2021, INT J PROD ECON, V238, DOI 10.1016/j.ijpe.2021.108166
   Malesios C, 2021, SOCIO-ECON PLAN SCI, V75, DOI 10.1016/j.seps.2020.100993
   Mican D, 2020, DECIS SUPPORT SYST, V139, DOI 10.1016/j.dss.2020.113420
   Mubarik MS, 2021, TECHNOL SOC, V64, DOI 10.1016/j.techsoc.2020.101524
   Muisyo PK, 2022, J MANUF TECHNOL MANA, V33, P22, DOI 10.1108/JMTM-10-2020-0388
   Munawar S, 2022, J HOSP TOUR MANAG, V52, P141, DOI 10.1016/j.jhtm.2022.06.009
   Niazi UI, 2023, ENVIRON SCI POLLUT R, V30, P45353, DOI 10.1007/s11356-023-25442-6
   Obeidat SM, 2023, EMPL RELAT, V45, P535, DOI 10.1108/ER-01-2022-0041
   Paillé P, 2014, J BUS ETHICS, V121, P451, DOI 10.1007/s10551-013-1732-0
   Qin ZT, 2023, TRANSPORT RES D-TR E, V119, DOI 10.1016/j.trd.2023.103723
   Rajabpour E, 2022, ENVIRON SCI POLLUT R, V29, P48720, DOI 10.1007/s11356-022-19137-7
   Roscoe S, 2019, BUS STRATEG ENVIRON, V28, P737, DOI 10.1002/bse.2277
   Saeed A, 2022, BENCHMARKING, V29, P2881, DOI 10.1108/BIJ-05-2021-0297
   Shang YF, 2023, ECON CHANG RESTRUCT, V56, P2003, DOI 10.1007/s10644-023-09502-y
   Singh SK, 2020, TECHNOL FORECAST SOC, V150, DOI 10.1016/j.techfore.2019.119762
   Song XG, 2019, RESOUR CONSERV RECY, V146, P405, DOI 10.1016/j.resconrec.2019.03.050
   Sulich A, 2022, ENVIRON SCI POLLUT R, V29, P14231, DOI 10.1007/s11356-021-16562-y
   Ubeda-García M, 2021, J BUS RES, V123, P57, DOI 10.1016/j.jbusres.2020.09.055
   Wang JW, 2022, FRONT NEUROROBOTICS, V16, DOI 10.3389/fnbot.2022.877069
   Xiang H, 2022, BUSINESS ETHICS IRRA
   Xiang XW, 2022, APPL ENERG, V322, DOI 10.1016/j.apenergy.2022.119401
   Xing ZY, 2023, J CLEAN PROD, V413, DOI 10.1016/j.jclepro.2023.137552
   Yan L, 2021, IEEE ACCESS, V9, P123764, DOI 10.1109/ACCESS.2021.3108178
   Yu WT, 2020, INT J PROD ECON, V219, P224, DOI 10.1016/j.ijpe.2019.06.013
   Yusliza MY, 2019, BENCHMARKING, V26, P2051, DOI 10.1108/BIJ-09-2018-0283
   Yusoff YM, 2020, GLOB BUS REV, V21, P663, DOI 10.1177/0972150918779294
   Zaid AA, 2018, J CLEAN PROD, V204, P965, DOI 10.1016/j.jclepro.2018.09.062
   Zhang SF, 2023, APPL ENERG, V342, DOI 10.1016/j.apenergy.2023.121164
   Zheng WF, 2022, PEERJ COMPUT SCI, V8, DOI 10.7717/peerj-cs.908
   Zheng WF, 2022, APPL SCI-BASEL, V12, DOI 10.3390/app12073416
   Zou CC, 2023, ENERGY, V277, DOI 10.1016/j.energy.2023.127689
NR 66
TC 1
Z9 1
U1 4
U2 21
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 SEP
PY 2023
VL 30
IS 44
BP 99570
EP 99583
DI 10.1007/s11356-023-28697-1
EA AUG 2023
PG 14
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA W8UA1
UT WOS:001063543800019
PM 37620692
DA 2025-01-10
ER

PT J
AU Gardner, H
   Onofre, KFA
   De Wolf, ED
AF Gardner, Heather
   Onofre, Kelsey F. Andersen
   De Wolf, Erick D.
TI Characterizing the Response of <i>Puccinia striiformis</i> f. sp.
   <i>tritici</i> to Periods of Heat Stress that Are Common in Kansas and
   the Great Plains Region of North America
SO PHYTOPATHOLOGY
LA English
DT Article
DE climate adaptation; pathogen fitness; yellow rust
ID PREDICTING STRIPE RUST; WINTER-WHEAT; LOCAL ADAPTATION; TEMPERATURE;
   POPULATIONS; AGGRESSIVENESS; EPIDEMIOLOGY; GERMINATION; MECHANISMS;
   RESISTANCE
AB Stripe rust of wheat, caused by Puccinia striiformis f. sp. tritici, is considered a disease of cool environments, and it has been observed that high temperatures can suppress disease development. However, recent field observations in Kansas suggest that the pathogen may be recovering from heat stress more quickly than expected. Previous research indicates that some strains of this pathogen were adapted to warm temperature regimes but did not consider how the pathogen responds to periods of heat stress that are common in the Great Plains region of North America. Therefore, the objectives of this study were to characterize the response of contemporary isolates of P. striiformis f. sp. tritici to periods of heat stress and to look for evidence of temperature adaptations within the pathogen population. These experiments evaluated nine isolates of the pathogen: eight isolates collected in Kansas between 2010 and 2021 and a historical reference isolate. Treatments compared the latent period and colonization rate of isolates given a cool temperature regime (12 to 20 degrees C) and as they recovered from 7 days of heat stress (22 to 35 degrees C). Results documented that contemporary isolates of the pathogen had similar latent periods and colonization rates as the historical reference under the cool temperature regime. Following exposure to 7 days of heat stress, the contemporary isolates had shorter latent periods and higher colonization rates than the historical isolate. There was also variability in how the contemporary isolates recovered from heat stress, with some isolates collected during 2019 to 2021 recovering sooner than those collected just 5 to 10 years ago.
C1 [Gardner, Heather; Onofre, Kelsey F. Andersen; De Wolf, Erick D.] Kansas State Univ, Dept Plant Pathol, Manhattan, KS 66506 USA.
C3 Kansas State University
RP De Wolf, ED (corresponding author), Kansas State Univ, Dept Plant Pathol, Manhattan, KS 66506 USA.
EM dewolf1@ksu.edu
OI Andersen, Kelsey/0000-0003-1812-2009; De Wolf, Erick/0000-0002-9339-1543
FU U.S. Department of Agriculture-Agricultural Research Service through the
   National Predictive Model Tool Initiative [5800206-0-196]; Kansas State
   University; Kansas Agricultural Experiment Station [23-266-J]
FX Support was provided by the U.S. Department of Agriculture-Agricultural
   Research Service through the National Predictive Model Tool Initiative
   (agreement 5800206-0-196), the Kansas State University, and the Kansas
   Agricultural Experiment Station (contribution 23-266-J).
CR Chen XM, 2007, AUST J AGR RES, V58, P648, DOI 10.1071/AR07045
   Chen X. M., 2013, American Journal of Plant Sciences, V4, P608
   Chen XM, 2005, CAN J PLANT PATHOL, V27, P314
   Chen XM, 2002, PLANT DIS, V86, P39, DOI 10.1094/PDIS.2002.86.1.39
   COAKLEY SM, 1988, PHYTOPATHOLOGY, V78, P543, DOI 10.1094/Phyto-78-543
   COAKLEY SM, 1982, PHYTOPATHOLOGY, V72, P1539, DOI 10.1094/Phyto-72-1539
   de Vallavieille-Pope C, 2018, PLANT PATHOL, V67, P1307, DOI 10.1111/ppa.12840
   DENNIS JI, 1987, T BRIT MYCOL SOC, V88, P91, DOI 10.1016/S0007-1536(87)80189-4
   DEVALLAVIEILLEPOPE C, 1995, PHYTOPATHOLOGY, V85, P409, DOI 10.1094/Phyto-85-409
   Gao XS, 2022, J FUNGI, V8, DOI 10.3390/jof8020175
   Gladders P, 2007, ANN APPL BIOL, V150, P371, DOI 10.1111/j.1744-7348.2007.00131.x
   Hau B., 1998, The Epidemiology of Plant Diseases
   Hovmoller MS, 2008, MOL ECOL, V17, P3818, DOI 10.1111/j.1365-294X.2008.03886.x
   Hovmoller MS, 2011, ANNU REV PHYTOPATHOL, V49, P197, DOI 10.1146/annurev-phyto-072910-095230
   Kranz J., 2003, Comparative epidemiology of plant diseases, DOI DOI 10.1007/978-3-662-05261-7
   Leach MD, 2016, NAT COMMUN, V7, DOI 10.1038/ncomms11704
   Leach MD, 2014, CURR FUNGAL INFECT R, V8, P185, DOI 10.1007/s12281-014-0182-1
   Line RF, 2002, ANNU REV PHYTOPATHOL, V40, P75, DOI 10.1146/annurev.phyto.40.020102.111645
   LING L, 1945, PHYTOPATHOLOGY, V35, P885
   Loladze A, 2014, PLANT PATHOL, V63, P572, DOI 10.1111/ppa.12132
   Lollato RP, 2017, FIELD CROP RES, V203, P212, DOI 10.1016/j.fcr.2016.12.014
   Mariette N, 2016, ECOL EVOL, V6, P6320, DOI 10.1002/ece3.2282
   Markell SG, 2008, PHYTOPATHOLOGY, V98, P632, DOI 10.1094/PHYTO-98-6-0632
   Mboup M, 2012, EVOL APPL, V5, P341, DOI 10.1111/j.1752-4571.2011.00228.x
   Milus EA, 2006, PLANT DIS, V90, P847, DOI 10.1094/PD-90-0847
   Milus EA, 2009, PHYTOPATHOLOGY, V99, P89, DOI 10.1094/PHYTO-99-1-0089
   Munday PL, 2017, GLOBAL CHANGE BIOL, V23, P307, DOI 10.1111/gcb.13419
   O'Hare G., 2005, Weather, Climate and Climate Change: Human Perspectives
   Palumbi SR, 2014, SCIENCE, V344, P895, DOI 10.1126/science.1251336
   PARK RF, 1990, PLANT PATHOL, V39, P416, DOI 10.1111/j.1365-3059.1990.tb02517.x
   QAYOUM A, 1985, PHYTOPATHOLOGY, V75, P1121, DOI 10.1094/Phyto-75-1121
   RAPILLY F, 1979, ANNU REV PHYTOPATHOL, V17, P59, DOI 10.1146/annurev.py.17.090179.000423
   Roelfs AP., 1992, Cimmyt
   Sharma-Poudyal D, 2011, PHYTOPATHOLOGY, V101, P544, DOI 10.1094/PHYTO-08-10-0215
   Sully S, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-09238-2
   TOLLENAAR H, 1966, PHYTOPATHOLOGY, V56, P787
   van den Berg F, 2007, PHYTOPATHOLOGY, V97, P1512, DOI 10.1094/PHYTO-97-11-1512
   Walter S, 2016, ECOL EVOL, V6, P2790, DOI 10.1002/ece3.2069
   Xia HQ, 2021, FRONT MICROBIOL, V12, DOI 10.3389/fmicb.2021.695535
   Xiao W, 2022, APPL MICROBIOL BIOT, V106, P5415, DOI 10.1007/s00253-022-12119-2
   Zhan JS, 2011, MOL ECOL, V20, P1689, DOI 10.1111/j.1365-294X.2011.05023.x
NR 41
TC 3
Z9 3
U1 0
U2 1
PU AMER PHYTOPATHOLOGICAL SOC
PI ST PAUL
PA 3340 PILOT KNOB ROAD, ST PAUL, MN 55121 USA
SN 0031-949X
EI 1943-7684
J9 PHYTOPATHOLOGY
JI Phytopathology
PD AUG
PY 2023
VL 113
IS 8
BP 1457
EP 1464
DI 10.1094/PHYTO-12-22-0475-R
PG 8
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA LU2B2
UT WOS:001189237500011
PM 37097624
DA 2025-01-10
ER

PT J
AU Richardson, S
   Sun, Q
AF Richardson, Steven
   Sun, Qian
TI Effects of soil moisture on tunneling, survivorship, and food
   consumption of the Formosan and eastern subterranean termites
   (Blattodea: Rhinotermitidae)
SO ENVIRONMENTAL ENTOMOLOGY
LA English
DT Article
DE water availability; invasive species; climate adaptation; Coptotermes
   formosanus; Reticulitermes flavipes
ID LABIAL GLAND RESERVOIRS; ISOPTERA RHINOTERMITIDAE;
   RETICULITERMES-FLAVIPES; FUNCTIONAL-ASPECTS; INVASIVE TERMITES; WOOD
   CONSUMPTION; TEMPERATURE; IMPACTS; WATER; POPULATIONS
AB Soil moisture is a critical environmental factor for the survival and behavior of subterranean termites (family Rhinotermitidae). The invasive Formosan subterranean termite, Coptotermes formosanus Shiraki, and the native eastern subterranean termite, Reticulitermes flavipes (Kollar), co-occur in the southeastern United States, while R. flavipes is distributed in a wider geoclimatic range. Previous studies showed that subterranean termites preferred higher soil moisture levels for tunneling and feeding; however, the impacts of constant moisture remained to be characterized to understand their moisture tolerance. In this study, we hypothesized that different soil moisture regimes can alter termite foraging and survival, and that the effects differ between the two species. The tunneling activity, survivorship, and food consumption of termites were documented for 28 days with different sand moisture conditions ranging from no moisture to full saturation (0%, 1%, 5%, 15%, 25%, and 30%). We found that there were no significant differences in the responses between C. formosanus and R. flavipes. In both species, termites did not survive or tunnel with 0% moisture. Termites performed tunneling with only 1% sand moisture, although they did not survive for 28 days. A minimal of 5% sand moisture was required for survival, and there were no significant differences in survivorship, tunneling activity, or food consumption among moisture contents of 5-30%. The results suggest that subterranean termites are resilient to moisture extremes. Colonies can tolerate low moisture conditions in their foraging environment for extended times, which may allow them to tunnel and find new moisture sources for colony survival.
C1 [Richardson, Steven; Sun, Qian] Louisiana State Univ, Dept Entomol, Agr Ctr, 404 Life Sci Bldg, Baton Rouge, LA 70803 USA.
   [Richardson, Steven] Univ Florida, Dept Entomol & Nematol, Gainesville, FL 32608 USA.
C3 Louisiana State University System; Louisiana State University; State
   University System of Florida; University of Florida
RP Sun, Q (corresponding author), Louisiana State Univ, Dept Entomol, Agr Ctr, 404 Life Sci Bldg, Baton Rouge, LA 70803 USA.
EM qsun@agcenter.lsu.edu
OI Sun, Qian/0000-0001-6341-6036
FU Hatch fund from the USDA National Institute of Food and Agriculture
   [1019492, LAB94437]; Louisiana Department of Agriculture and Forestry;
   Residential Life Assistantship from the Department of Residential Life
   and College of Agriculture at Louisiana State University
FX We thank Arjun Khadka for assistance with the experiments and Joseph
   McCarthy for comments and editing of an earlier draft of the manuscript.
   This research was supported by a Hatch fund (Accession Number: 1019492;
   Project Number: LAB94437) from the USDA National Institute of Food and
   Agriculture and the Structural Pest Research Grant from the Louisiana
   Department of Agriculture and Forestry to QS. In addition, SR was
   supported by the Residential Life Assistantship from the Department of
   Residential Life and College of Agriculture at Louisiana State
   University.
CR Akinsanola AA, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab92c1
   Berg A, 2018, CURR CLIM CHANGE REP, V4, P180, DOI 10.1007/s40641-018-0095-0
   Bignell DE, 2000, TERMITES: EVOLUTION, SOCIALITY, SYMBIOSES, ECOLOGY, P363
   Blumenfeld AJ, 2021, COMMUN BIOL, V4, DOI 10.1038/s42003-021-01725-x
   Buczkowski G, 2017, ECOL EVOL, V7, P974, DOI 10.1002/ece3.2674
   Cao RX, 2016, ANN ENTOMOL SOC AM, V109, P64, DOI 10.1093/aesa/sav095
   Cao RX, 2014, ANN ENTOMOL SOC AM, V107, P696, DOI 10.1603/AN13181
   Chouvenc T, 2011, FLA ENTOMOL, V94, P817, DOI 10.1653/024.094.0413
   Cornelius ML, 2011, J ECON ENTOMOL, V104, P1024, DOI 10.1603/EC10332
   Cornelius ML, 2010, J ECON ENTOMOL, V103, P799, DOI 10.1603/EC09250
   Cottone CB, 2015, SOCIOBIOLOGY, V62, P76
   DELAPLANE KS, 1989, J ECON ENTOMOL, V82, P95, DOI 10.1093/jee/82.1.95
   Dietz HF., 1920, P INDIAN ACAD SCI, V30, P87
   Evans TA, 2019, BIOL INVASIONS, V21, P1283, DOI 10.1007/s10530-018-1899-5
   Evans TA, 2013, ANNU REV ENTOMOL, V58, P455, DOI 10.1146/annurev-ento-120811-153554
   Eyer PA, 2021, MOL ECOL, V30, P3948, DOI 10.1111/mec.16022
   Forschler BT, 1995, ENVIRON ENTOMOL, V24, P1592, DOI 10.1093/ee/24.6.1592
   FOWLER AM, 1995, NAT HAZARDS, V11, P283, DOI 10.1007/BF00613411
   Gallagher NT, 2010, SOCIOBIOLOGY, V55, P735
   Gautam BK, 2011, ENVIRON ENTOMOL, V40, P1232, DOI 10.1603/EN11062
   Gautam BK, 2011, ANN ENTOMOL SOC AM, V104, P459, DOI 10.1603/AN10190
   Gautam BK, 2011, J ENTOMOL SCI, V46, P1
   Green JM, 2005, J ECON ENTOMOL, V98, P933, DOI 10.1603/0022-0493-98.3.933
   Greening H, 2006, ESTUARIES COASTS, V29, P877, DOI 10.1007/BF02798646
   Grube S, 1997, INT J INSECT MORPHOL, V26, P49, DOI 10.1016/S0020-7322(97)00006-8
   Grube S, 1999, SOCIOBIOLOGY, V33, P307
   HIGA S Y, 1983, Proceedings of the Hawaiian Entomological Society, V24, P233
   Houseman RM, 2003, J AGR URBAN ENTOMOL, V20, P69
   Houseman RM, 2001, ENVIRON ENTOMOL, V30, P673, DOI 10.1603/0046-225X-30.4.673
   Hu XP, 2004, ENVIRON ENTOMOL, V33, P197, DOI 10.1603/0046-225X-33.2.197
   Kunkel KE, 2020, J APPL METEOROL CLIM, V59, P125, DOI 10.1175/JAMC-D-19-0185.1
   Lowe S., 2000, 100 of the Worlds' Worst Invasive Alien Species: A Selection from the Global Invasive Species Database
   Masson-Delmotte V., 2018, GLOBAL WARMING 1 5 C, V1
   Nutting W. L., 1969, P233
   Osbrink WLA, 2008, J ECON ENTOMOL, V101, P1367, DOI 10.1603/0022-0493(2008)101[1367:EOFOFP]2.0.CO;2
   Owens CB, 2012, J ECON ENTOMOL, V105, P518, DOI 10.1603/EC11150
   Scheffrahn RH, 2011, FLA ENTOMOL, V94, P57, DOI 10.1653/024.094.0108
   SPONSLER RC, 1990, ENVIRON ENTOMOL, V19, P15, DOI 10.1093/ee/19.1.15
   Su NY, 2003, SOCIOBIOLOGY, V41, P7
   Su NY, 2003, J ECON ENTOMOL, V96, P88, DOI 10.1603/0022-0493-96.1.88
   SU NY, 1991, J ECON ENTOMOL, V84, P912, DOI 10.1093/jee/84.3.912
   SU NY, 1990, SOCIOBIOLOGY, V17, P77
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Tseng SP, 2021, J ECON ENTOMOL, V114, P1264, DOI 10.1093/jee/toab077
   Woon JS, 2019, INSECT SOC, V66, P57, DOI 10.1007/s00040-018-0664-1
   Zukowski J, 2019, J INSECT SCI, V19, DOI 10.1093/jisesa/iez090
NR 46
TC 1
Z9 1
U1 0
U2 3
PU OXFORD UNIV PRESS INC
PI CARY
PA JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA
SN 0046-225X
EI 1938-2936
J9 ENVIRON ENTOMOL
JI Environ. Entomol.
PD AUG 18
PY 2023
VL 52
IS 4
BP 539
EP 545
DI 10.1093/ee/nvad049
EA JUN 2023
PG 7
WC Entomology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Entomology
GA P1SE2
UT WOS:001003999900001
PM 37300303
DA 2025-01-10
ER

PT J
AU Lie, MH
   Asplund, J
   Goehl, M
   Ohlson, M
   Nybakken, L
AF Lie, Marit H.
   Asplund, Johan
   Goehl, Matthias
   Ohlson, Mikael
   Nybakken, Line
TI Similar growth responses to climatic variations in Norway spruce
   (<i>Picea abies</i>) and European beech (<i>Fagus sylvatica</i>) at the
   northern range limit of beech
SO EUROPEAN JOURNAL OF FOREST RESEARCH
LA English
DT Article
DE Tree-rings dendrochronology; Drought; Temperature
ID TEMPERATE FOREST TREES; FUTURE DISTRIBUTION; CENTRAL APENNINES; MASTING
   BEHAVIOR; COMMON BEECH; STEM GROWTH; L. KARST; DROUGHT; VARIABILITY;
   SENSITIVITY
AB In south-east Norway, in the hemiboreal vegetation zone, beech reaches its northern distribution limit and typically occupies the same type of sites as spruce. Under future climate change, this area is projected to fall within the temperate zone and beech to increase its distribution towards the north at the expense of spruce. However, such forecasts are based on very broad scale estimates and the knowledge of climatic adaptation and the competitive potential of the beech and spruce populations at these latitudes is scarce. Here, we use a dendrochronological approach to study the growth performance of neighbouring spruce and beech trees to climate variability over a period of 70 years. The two species responded quite similarly to variations in climate in the study area. Both showed increased incremental growth in response to high precipitation both in the previous and present year June, indicating that water is a limiting resource. In addition, beech showed a negative response to high temperatures in previous July and August, which is probably connected with growth reductions due to masting. Overall, spruce and beech in the hemiboreal zone show comparable responses to climatic variations as in the temperate zone. Due to the different drought-handling strategies of the two species, we suggest that the intensity of summer droughts and the variability between years are likely factors that would be decisive for which of them that will be more successful under future climatic conditions.
C1 [Lie, Marit H.; Asplund, Johan; Goehl, Matthias; Ohlson, Mikael; Nybakken, Line] Norwegian Univ Life Sci, Fac Environm Sci & Nat Resource Management, As, Norway.
   [Lie, Marit H.] NLA Univ Coll, Oslo, Norway.
C3 Norwegian University of Life Sciences; NLA University College
RP Nybakken, L (corresponding author), Norwegian Univ Life Sci, Fac Environm Sci & Nat Resource Management, As, Norway.
EM line.nybakken@nmbu.no
FU Research Council of Norway [225018]
FX AcknowledgementsThis study was funded by the Research Council of Norway
   (Grant Number 225018).
CR Altman J, 2017, SCI TOTAL ENVIRON, V609, P506, DOI 10.1016/j.scitotenv.2017.07.134
   Andreassen K, 2006, FOREST ECOL MANAG, V222, P211, DOI 10.1016/j.foreco.2005.10.029
   [Anonymous], 2001, Tree rings and climate
   Asplund J, 2015, FUNGAL ECOL, V16, P1, DOI 10.1016/j.funeco.2015.03.006
   Backes K, 2000, CAN J FOREST RES, V30, P335, DOI 10.1139/cjfr-30-3-335
   BAKKE A, 1983, Z ANGEW ENTOMOL, V96, P118
   Basler D, 2012, AGR FOREST METEOROL, V165, P73, DOI 10.1016/j.agrformet.2012.06.001
   BIONDI F, 1993, ACTA OECOL, V14, P57
   Bjune AE, 2009, HOLOCENE, V19, P1073, DOI 10.1177/0959683609341004
   Bjune AE, 2013, VEG HIST ARCHAEOBOT, V22, P215, DOI 10.1007/s00334-012-0371-1
   Bréda N, 2006, ANN FOREST SCI, V63, P625, DOI 10.1051/forest:2006042
   Bunn A., 2020, R PACKAGE VERSION, V1, P1
   Büntgen U, 2006, TREES-STRUCT FUNCT, V20, P99, DOI 10.1007/s00468-005-0017-3
   Chen IC, 2011, SCIENCE, V333, P1024, DOI 10.1126/science.1206432
   Cook ER., 1990, Methods of Dendrochronology: Applications in the Environmental Sciences, P97, DOI 10.1007/978-94-015-7879-0
   Dittmar C, 2003, FOREST ECOL MANAG, V173, P63, DOI 10.1016/S0378-1127(01)00816-7
   Drobyshev I, 2010, FOREST ECOL MANAG, V259, P2160, DOI 10.1016/j.foreco.2010.01.037
   Ellingsen VM, 2017, SCAND J FOREST RES, V32, P105, DOI 10.1080/02827581.2016.1215523
   Grundmann BM, 2011, SCAND J FOREST RES, V26, P64, DOI 10.1080/02827581.2011.564392
   GUTIERREZ E, 1988, ACTA OECOL-OEC PLANT, V9, P301
   Hanssen-Bauer I, 2015, CLIMATE NORWAY 2100, P203
   Hickler T, 2012, GLOBAL ECOL BIOGEOGR, V21, P50, DOI 10.1111/j.1466-8238.2010.00613.x
   Kausrud K, 2022, IMPACTS CLIMATE CHAN, P15
   Klein T, 2014, FUNCT ECOL, V28, P1313, DOI 10.1111/1365-2435.12289
   Koenig WD, 1998, NATURE, V396, P225, DOI 10.1038/24293
   Kramer K, 2010, FOREST ECOL MANAG, V259, P2213, DOI 10.1016/j.foreco.2009.12.023
   Kraus C, 2016, EUR J FOREST RES, V135, P1011, DOI 10.1007/s10342-016-0990-7
   Lebourgeois F, 2010, J VEG SCI, V21, P364, DOI 10.1111/j.1654-1103.2009.01148.x
   Lloret F, 2011, OIKOS, V120, P1909, DOI 10.1111/j.1600-0706.2011.19372.x
   Löw M, 2006, TREES-STRUCT FUNCT, V20, P539, DOI 10.1007/s00468-006-0069-z
   del Castillo EM, 2016, FRONT PLANT SCI, V7, DOI 10.3389/fpls.2016.00370
   McDowell N, 2008, NEW PHYTOL, V178, P719, DOI 10.1111/j.1469-8137.2008.02436.x
   Moen A., 1999, ATLAS NORWAY
   Müller-Haubold H, 2013, ECOSYSTEMS, V16, P1498, DOI 10.1007/s10021-013-9698-4
   Mund M, 2010, TREE PHYSIOL, V30, P689, DOI 10.1093/treephys/tpq027
   Nikolova PS, 2020, FRONT PLANT SCI, V11, DOI 10.3389/fpls.2020.01211
   Obladen N, 2021, AGR FOREST METEOROL, V307, DOI 10.1016/j.agrformet.2021.108482
   Ohlson M, 2017, HOLOCENE, V27, P397, DOI 10.1177/0959683616660174
   Pflug EE, 2018, FRONT PLANT SCI, V9, DOI 10.3389/fpls.2018.00187
   Piovesan G, 2001, CAN J BOT, V79, P1039, DOI 10.1139/cjb-79-9-1039
   Piovesan G, 2008, GLOBAL CHANGE BIOL, V14, P1265, DOI 10.1111/j.1365-2486.2008.01570.x
   Pretzsch H, 2005, EUR J FOREST RES, V124, P193, DOI 10.1007/s10342-005-0068-4
   Pretzsch H, 2014, TREES-STRUCT FUNCT, V28, P1305, DOI 10.1007/s00468-014-1035-9
   Pretzsch H, 2013, PLANT BIOLOGY, V15, P483, DOI 10.1111/j.1438-8677.2012.00670.x
   Pretzsch H, 2020, CAN J FOREST RES, V50, P689, DOI 10.1139/cjfr-2019-0368
   R Core Team, 2020, R: A Language and Environment for Statistical Computing
   Rossi S, 2008, GLOBAL ECOL BIOGEOGR, V17, P696, DOI 10.1111/j.1466-8238.2008.00417.x
   Saltré F, 2015, GLOBAL CHANGE BIOL, V21, P897, DOI 10.1111/gcb.12771
   Selås V, 2002, CAN J FOREST RES, V32, P217, DOI 10.1139/X01-192
   Skomarkova MV, 2006, TREES-STRUCT FUNCT, V20, P571, DOI 10.1007/s00468-006-0072-4
   Sohn JA, 2012, TREE PHYSIOL, V32, P1199, DOI 10.1093/treephys/tps077
   Speer J.H., 2011, FUNDAMENTALS TREE RI
   Steinbauer MJ, 2018, NATURE, V556, P231, DOI 10.1038/s41586-018-0005-6
   Stokes M.A.T.L. Smiley., 1996, INTRO TREE RING DATI
   van der Werf G. W., 2007, Dendrochronologia, V25, P103, DOI 10.1016/j.dendro.2007.03.004
   Zang C, 2015, ECOGRAPHY, V38, P431, DOI 10.1111/ecog.01335
   Zang C, 2014, GLOBAL CHANGE BIOL, V20, P3767, DOI 10.1111/gcb.12637
NR 57
TC 2
Z9 2
U1 1
U2 5
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 1612-4669
EI 1612-4677
J9 EUR J FOREST RES
JI Eur. J. For. Res.
PD OCT
PY 2023
VL 142
IS 5
BP 1059
EP 1068
DI 10.1007/s10342-023-01576-7
EA MAY 2023
PG 10
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Forestry
GA GO0H1
UT WOS:000987115500001
OA Green Submitted, hybrid
DA 2025-01-10
ER

PT J
AU Reuter, L
   Graf, A
   Goergen, K
   Döscher, N
   Leuchner, M
AF Reuter, Lynn
   Graf, Alexander
   Goergen, Klaus
   Doescher, Niels
   Leuchner, Michael
TI Modelling climate analogue regions for a central European city
SO CLIMATIC CHANGE
LA English
DT Article
DE Climate analogue cities; Climate twins; Climate change; Regional climate
   models; EURO-CORDEX
ID URBAN AREAS; CORDEX; CITIES; PROJECTIONS; IMPACTS
AB In this study, we describe a methodology to derive climate analogue cities for spatially highly resolved future climate scenarios. For the computation, a reduced and in hindsight bias-adjusted EURO-CORDEX EUR-11 dataset is used based on two climate scenarios (RCP4.5 and RCP8.5). A total of 389 European cities are processed by the algorithm, which uses five statistical climate variables (2-m air temperature average and amplitude, precipitation sum and amplitude, correlation between 2-m air temperature average and precipitation sum). Additionally, extreme weather events (hot days, summer days, tropical nights, extreme precipitation events) are calculated for further comparison and validation. Finding an appropriate analogue permits a more accurate derivation and depiction of necessary climate adaptation efforts and therefore assist decision-making in city planning. As an example of our method, we searched for plausible climate twins for the mid-sized city of Aachen (Germany) at the end of the twenty-first century. Our results show that the French city of Dijon is highly likely to become Aachen's climate twin by the end of the century for RCP4.5. As for the scenario RCP8.5, no clear European analogue city could be determined, indicating that the city might enter a novel climate. The nearest match suggests the cities of Florence and Prato in Tuscany. However, considering climate indices, the encompassing region of the French-Spanish city triangle Bordeaux-Toulouse-Bilbao is a better fit. The developed algorithm can be applied to any of the cities included in the dataset.
C1 [Reuter, Lynn; Doescher, Niels; Leuchner, Michael] Rhein Westfal TH Aachen, Dept Geog, Phys Geog & Climatol, Aachen, Germany.
   [Graf, Alexander; Goergen, Klaus] Forschungszentrum Julich, Agrosphere Inst, IBG 3, Julich, Germany.
C3 RWTH Aachen University; Helmholtz Association; Research Center Julich
RP Döscher, N (corresponding author), Rhein Westfal TH Aachen, Dept Geog, Phys Geog & Climatol, Aachen, Germany.
EM lynn.reuter@rwth-aachen.de
RI Goergen, Klaus/A-4655-2017; Leuchner, Michael/U-9021-2019; Graf,
   Alexander/D-1963-2009
OI Goergen, Klaus/0000-0002-4208-3444; Doscher, Niels/0000-0002-5847-2057;
   Leuchner, Michael/0000-0002-0927-2622; Graf,
   Alexander/0000-0003-4870-7622
FU DEIMS-SDR
FX AcknowledgementsThe eLTER EURO-CORDEX regional climate projections and
   DEIMS-SDR are products of LTER-Europe. We acknowledge the World Climate
   Research Programme's Working Group on Regional Climate, and the Working
   Group on Coupled Modelling, the former coordinating body of CORDEX and
   responsible panel for CMIP5. We also thank the climate modelling groups
   for producing and making available their model output. We also
   acknowledge the Earth System Grid Federation infrastructure, an
   international effort led by the U.S. Department of Energy's Program for
   Climate Model Diagnosis and Intercomparison, the European Network for
   Earth System Modelling and other partners in the Global Organisation for
   Earth System Science Portals (GO-ESSP). We also thank Uwe Schulzweida
   for the freely available CDO tool.
CR ALEXANDER L., 2016, ClimPACT2: Indices and software
   [Anonymous], 2021, WCRP COORD REG CLIM
   Bastin JF, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0217592
   Beniston M, 2014, INT J CLIMATOL, V34, P1838, DOI 10.1002/joc.3804
   Boé J, 2020, CLIM DYNAM, V54, P2981, DOI 10.1007/s00382-020-05153-1
   Buttstädt M, 2014, METEOROL Z, V23, P63, DOI 10.1127/0941-2948/2014/0549
   Casanueva A, 2020, REG ENVIRON CHANGE, V20, DOI 10.1007/s10113-020-01625-6
   Chapagain D, 2021, CLIMATIC CHANGE, V168, DOI 10.1007/s10584-021-03216-8
   Copernicus Climate Change Service, 2023, ECMWR, DOI 10.24381/CDS.BC91EDC3
   Deutscher Wetterdienst, 2021, CDC CLIM DAT CTR
   Deutscher Wetterdienst, 2021, KLIM KENNT
   ECMWF, 2022, CORDEX REG CLIM PROJ
   EURO-CORDEX, 2022, ERR TABL
   Fernandez J, 2019, CLIM DYNAM, V52, P1139, DOI 10.1007/s00382-018-4181-8
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fitzpatrick MC, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-08540-3
   GCOS, 2003, 1143 GCOS WMOTD
   Giorgi F., 2009, Bulletin - World Meteorological Organization, V58, P175
   Giorgi F, 2016, CURR CLIM CHANGE REP, V2, P202, DOI 10.1007/s40641-016-0046-6
   Grafakos S., 2018, Climate Change and Cities eds, P101, DOI DOI 10.1017/9781316563878.011
   Grimm NB, 2008, SCIENCE, V319, P756, DOI 10.1126/science.1150195
   Gutowski WJ, 2016, GEOSCI MODEL DEV, V9, P4087, DOI 10.5194/gmd-9-4087-2016
   Hallegatte S, 2007, CLIMATIC CHANGE, V82, P47, DOI 10.1007/s10584-006-9161-z
   Herold N, 2018, WEATHER CLIM EXTREME, V20, P54, DOI 10.1016/j.wace.2018.01.001
   IPCC, 2015, INT PAN CLIM CHANG W
   Jacob D, 2020, REG ENVIRON CHANGE, V20, DOI 10.1007/s10113-020-01606-9
   Jacob D, 2014, REG ENVIRON CHANGE, V14, P563, DOI 10.1007/s10113-013-0499-2
   Junk J, 2019, INT J ENV RES PUB HE, V16, DOI 10.3390/ijerph16203959
   Kalkstein LS, 2008, B AM METEOROL SOC, V89, P75, DOI 10.1175/BAMS-89-1-75
   Karlicky J, 2020, ATMOS CHEM PHYS, V20, P15061, DOI 10.5194/acp-20-15061-2020
   Kopf S, 2008, NAT HAZARD EARTH SYS, V8, P905, DOI 10.5194/nhess-8-905-2008
   Kotlarski S, 2014, GEOSCI MODEL DEV, V7, P1297, DOI 10.5194/gmd-7-1297-2014
   Kotlarski S, 2019, INT J CLIMATOL, V39, P3730, DOI 10.1002/joc.5249
   Kottek M, 2006, METEOROL Z, V15, P259, DOI 10.1127/0941-2948/2006/0130
   Kreienkamp F., 2012, Environmental Systems Research, V1, P9, DOI DOI 10.1186/2193-2697-1-9
   Kuttler Wilhelm, 2011, Environmental Sciences Europe, V23, P11, DOI 10.1186/2190-4715-23-11
   Landeshauptstadt Dusseldorf, 2020, DUSS TOUL GEM BESS
   Langendijk GS, 2019, ATMOSPHERE-BASEL, V10, DOI 10.3390/atmos10120730
   LANUV, 2019, DAT FAKT KLIM EIF
   Maraun D, 2016, CURR CLIM CHANGE REP, V2, P211, DOI 10.1007/s40641-016-0050-x
   Muñoz-Sabater J, 2021, EARTH SYST SCI DATA, V13, P4349, DOI 10.5194/essd-13-4349-2021
   Nakaegawa T, 2022, INT J CLIMATOL, V42, P8950, DOI 10.1002/joc.7784
   Natural Earth, 2022, 1 10M PHYS VECT OC
   Oke T. R., 2017, Urban Climates, DOI [10.1017/9781139016476, DOI 10.1017/9781139016476]
   Reckien D, 2014, CLIMATIC CHANGE, V122, P331, DOI 10.1007/s10584-013-0989-8
   Rennie S, 2021, EARTH SYST SCI DATA, V13, P631, DOI 10.5194/essd-13-631-2021
   Rohat G, 2018, INT J CLIM CHANG STR, V10, P428, DOI 10.1108/IJCCSM-05-2017-0108
   Rohat G, 2017, MITIG ADAPT STRAT GL, V22, P929, DOI 10.1007/s11027-016-9708-x
   Rosenzweig C, 2010, NATURE, V467, P909, DOI 10.1038/467909a
   Schwalm CR, 2020, P NATL ACAD SCI USA, V117, P19656, DOI 10.1073/pnas.2007117117
   Stadt Aachen, 2014, ANP FOLG KLIM AACH T
   UNDESA, 2018, World Urbanization Prospects: The 2018 Revision
   Ungar J., 2011, HREBICEK J, P428
   van Vuuren DP, 2011, CLIMATIC CHANGE, V109, P5, DOI [10.1007/s10584-011-0148-z, 10.1007/s10584-011-0157-y]
   Vautard R, 2021, J GEOPHYS RES-ATMOS, V126, DOI 10.1029/2019JD032344
   Williams JW, 2007, FRONT ECOL ENVIRON, V5, P475, DOI 10.1890/070037
   Yosef Y, 2019, INT J CLIMATOL, V39, P5022, DOI 10.1002/joc.6125
NR 57
TC 2
Z9 2
U1 0
U2 6
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 MAY
PY 2023
VL 176
IS 5
AR 61
DI 10.1007/s10584-023-03531-2
PG 22
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA F7FL7
UT WOS:000983963000001
OA hybrid
DA 2025-01-10
ER

PT J
AU Bach, AJE
   Palutikof, JP
   Tonmoy, FN
   Smallcombe, JW
   Rutherford, S
   Joarder, AR
   Hossain, M
   Jay, O
AF Bach, Aaron J. E.
   Palutikof, Jean P.
   Tonmoy, Fahim N.
   Smallcombe, James W.
   Rutherford, Shannon
   Joarder, Ashikur R.
   Hossain, Monir
   Jay, Ollie
TI Retrofitting passive cooling strategies to combat heat stress in the
   face of climate change: A case study of a ready-made garment factory in
   Dhaka, Bangladesh
SO ENERGY AND BUILDINGS
LA English
DT Article
DE Building modelling; Building simulation; Occupational health and safety;
   Wet -bulb globe temperature; Climate adaptation; Sustainable cooling
ID BUILDING ENVELOPE; PRODUCTION SPACES; GREEN; PERFORMANCE; HEALTH;
   PRODUCTIVITY; EXPOSURE; WORKERS; ROOFS
AB The ready-made garment industry is critical to the Bangladesh economy. There is an urgent need to improve current working conditions and build capacity for heat mitigation as conditions worsen due to climate change. We modelled a typical, mid-sized, non-air-conditioned factory in Bangladesh and simulated how the indoor thermal environment is altered by four rooftop retrofits (1. extensive green roof, 2. rooftop shading, 3. white cool roof, 4. insulated white cool roof) on present-day and future decades under different climate scenarios. Simulations showed that all strategies reduce indoor air temperatures by around 2 degrees C on average and reduce the number of present-day annual work-hours during which wetbulb globe temperature exceeds the standardised limits for moderate work rates by up to 603 h - the equivalent of 75 (8 h) working days per year. By 2050 under a high-emissions scenario, indoor conditions with a rooftop intervention are comparable to present-day conditions. To reduce the growing need for carbon-intensive air-conditioning, sustainable heat mitigation strategies need to be incorporated into a wider range of solutions at the individual, building, and urban level. The results presented here have implications for factory planning and retrofit design, and may inform policies targeting worker health, well-being, and productivity. (c) 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).
C1 [Bach, Aaron J. E.; Palutikof, Jean P.; Tonmoy, Fahim N.] Griffith Univ, Natl Climate Change Adaptat Res Facil NCCARF, Gold Coast, Qld, Australia.
   [Bach, Aaron J. E.; Palutikof, Jean P.; Rutherford, Shannon] Griffith Univ, Cities Res Inst, Gold Coast, Qld, Australia.
   [Tonmoy, Fahim N.] BMT Grp, Brisbane, Qld, Australia.
   [Smallcombe, James W.; Jay, Ollie] Univ Sydney, Fac Med & Hlth, Sydney, NSW, Australia.
   [Smallcombe, James W.; Jay, Ollie] Univ Sydney, Heat & Hlth Res Incubator, Sydney, NSW, Australia.
   [Rutherford, Shannon] Griffith Univ, Sch Med & Dent, Gold Coast, Qld, Australia.
   [Joarder, Ashikur R.; Hossain, Monir] Bangladesh Univ Engn & Technol BUET, Dept Architecture, Dhaka, Bangladesh.
   [Bach, Aaron J. E.] Griffith Univ, N56,Off 1-37, Nathan, Qld 4111, Australia.
C3 Griffith University; Griffith University - Gold Coast Campus; Griffith
   University; Griffith University - Gold Coast Campus; University of
   Sydney; University of Sydney; Griffith University; Griffith University -
   Gold Coast Campus; Bangladesh University of Engineering & Technology
   (BUET); Griffith University
RP Bach, AJE (corresponding author), Griffith Univ, N56,Off 1-37, Nathan, Qld 4111, Australia.
EM a.bach@griffith.edu.au
RI Bach, Aaron/AAQ-2258-2020; Jay, Ollie/AAD-8009-2020; Tonmoy,
   Fahim/A-1502-2012
OI Palutikof, Jean/0000-0002-5248-6925; Tonmoy, Fahim/0000-0002-0963-112X
FU Wellcome Trust;  [216059/Z/19/Z]
FX This research was funded in whole by the Wellcome Trust [216059/Z/19/Z:
   Managing heat stress among Bangladesh ready-made clothing industry
   workers] . For the purpose of open access, we have applied a CC BY
   public copyright licence to any Author Accepted Manuscript version
   arising from this submission. The authors would like to acknowledge our
   partners on the ground Ino-vace Technologies for their help and support
   in installation and data acquisition of instrumentation during border
   closures through the COVID-19 pandemic. Thanks also to Environdata for
   construct-ing a remote, modular weather station to meet our specific
   project needs. This research was also supported by use of the Nectar
   Research Cloud, a collaborative Australian research platform sup-ported
   by the NCRIS-funded Australian Research Data Commons (ARDC) . Finally,
   thank you to both Eren Bastanoglu and David Mor-roni for their
   consultation, contributions, and expertise in the building modelling and
   simulation.
CR Adamski M, 2008, ENERG BUILDINGS, V40, P1883, DOI 10.1016/j.enbuild.2008.04.008
   Akhter S, 2019, BMC INT HEALTH HUM R, V19, DOI 10.1186/s12914-019-0188-4
   Almazroui M, 2020, EARTH SYST ENVIRON, V4, P297, DOI 10.1007/s41748-020-00157-7
   Androutsopoulos AV, 2017, PROCEDIA ENVIRON SCI, V38, P178, DOI 10.1016/j.proenv.2017.03.103
   [Anonymous], 2022, HDB 1
   ASHRAE, 2014, ASHRAE Guideline 14-2014: Measurement of Energy, Demand and Water Saving
   ASHRAE, 2019, ANSI/ASHRAE/IES Standard 90.1-2019
   Baba FM, 2022, BUILD ENVIRON, V207, DOI 10.1016/j.buildenv.2021.108518
   Belcher S. E., 2005, Building Services Engineering Research & Technology, V26, P49, DOI 10.1191/0143624405bt112oa
   BGMEA, 2022, BGMEA EXP PERF
   Biardeau LT, 2020, NAT SUSTAIN, V3, P25, DOI 10.1038/s41893-019-0441-9
   Bretz SE, 1997, ENERG BUILDINGS, V25, P159, DOI 10.1016/S0378-7788(96)01005-5
   Cascone S, 2018, BUILD ENVIRON, V136, P227, DOI 10.1016/j.buildenv.2018.03.052
   Chowdhury Sajal, 2017, International Journal of Sustainable Built Environment, V6, P449, DOI 10.1016/j.ijsbe.2017.09.001
   Chowdhury S, 2017, SUSTAIN CITIES SOC, V29, P41, DOI 10.1016/j.scs.2016.11.012
   Chowdhury S, 2015, ENERG BUILDINGS, V107, P144, DOI 10.1016/j.enbuild.2015.08.014
   Corne D., 2018, HDB HEURISTICS, DOI [10.1007/978-3-319-07153-4_27-1, DOI 10.1007/978-3-319-07153-4_27-1]
   Das S, 2015, CLIM CHANG ECON, V6, DOI 10.1142/S2010007815500074
   DesignBuilder Software Ltd, 2022, DesignBuilder
   Fahad MGR, 2018, INT J CLIMATOL, V38, P1634, DOI 10.1002/joc.5284
   Flouris AD, 2018, LANCET PLANET HEALTH, V2, pE521, DOI 10.1016/S2542-5196(18)30237-7
   Foster J, 2022, INT J BIOMETEOROL, V66, P507, DOI 10.1007/s00484-021-02212-y
   Foster J, 2021, INT J BIOMETEOROL, V65, P1215, DOI 10.1007/s00484-021-02105-0
   Garg V, 2016, ENERG BUILDINGS, V114, P156, DOI 10.1016/j.enbuild.2015.06.043
   Hossain MA, 2019, BUILDINGS-BASEL, V9, DOI 10.3390/buildings9040079
   Hossain MM, 2019, BUILD ENVIRON, V157, P319, DOI 10.1016/j.buildenv.2019.04.048
   IEA-International Energy Agency, 2021, Hydrogen
   Ioannou Leonidas G, 2022, Temperature (Austin), V9, P274, DOI 10.1080/23328940.2022.2044739
   Islam MS, 2021, GEOJOURNAL, V86, P1301, DOI 10.1007/s10708-019-10131-0
   ISO I.S.O., 2017, 72432017 ISO
   Jay O, 2021, LANCET, V398, P709, DOI 10.1016/S0140-6736(21)01209-5
   Ma R, 2019, SCI TOTAL ENVIRON, V666, P147, DOI 10.1016/j.scitotenv.2019.02.201
   Manso M, 2021, RENEW SUST ENERG REV, V135, DOI 10.1016/j.rser.2020.110111
   Matsuura A., 2020, Understanding the gender composition and experience of ready-made garment (RMG) workers in Bangladesh
   Miller V, 2011, ANN OCCUP HYG, V55, P548, DOI 10.1093/annhyg/mer012
   Morris NB, 2020, ENVIRON HEALTH-GLOB, V19, DOI 10.1186/s12940-020-00641-7
   NASA, 2022, POWER DAT ACC VIEW V
   NIOSH, 2016, CRITERIA RECOMMENDED, V2016106
   Obringer R, 2022, EARTHS FUTURE, V10, DOI 10.1029/2021EF002434
   Parsons LA, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-27328-y
   Philip S., EPPY SCRIPTING LANGU
   Pitman SD, 2015, T ROY SOC SOUTH AUST, V139, P97, DOI 10.1080/03721426.2015.1035219
   Purohit P, 2022, P NATL ACAD SCI USA, V119, DOI 10.1073/pnas.2206131119
   R Core Team, 2022, R: A Language and Environment for Statistical Computing
   Ruiz GR, 2016, APPL ENERG, V168, P691, DOI 10.1016/j.apenergy.2016.01.075
   Reback Jeff, 2020, Zenodo, DOI 10.5281/ZENODO.3715232
   RStudio Team, 2020, Integrated development for R
   Sadineni SB, 2011, RENEW SUST ENERG REV, V15, P3617, DOI 10.1016/j.rser.2011.07.014
   Shafique M, 2018, RENEW SUST ENERG REV, V90, P757, DOI 10.1016/j.rser.2018.04.006
   Shittu E, 2020, ENERG BUILDINGS, V217, DOI 10.1016/j.enbuild.2020.110007
   Smallcombe JW, 2022, INT J BIOMETEOROL, V66, P2463, DOI 10.1007/s00484-022-02370-7
   Solcast, 2022, API TOOLK TIM SER HI
   Sproul J, 2014, ENERG BUILDINGS, V71, P20, DOI 10.1016/j.enbuild.2013.11.058
   Steinisch M, 2013, HEALTH PLACE, V24, P123, DOI 10.1016/j.healthplace.2013.09.004
   Tan HC, 2023, SCI TOTAL ENVIRON, V860, DOI 10.1016/j.scitotenv.2022.160508
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   United States Department of Energy, 2020, ENERGYPLUS
   van Vuuren DP, 2011, CLIMATIC CHANGE, V109, P5, DOI [10.1007/s10584-011-0148-z, 10.1007/s10584-011-0157-y]
   Varghese BM, 2018, SAFETY SCI, V110, P380, DOI 10.1016/j.ssci.2018.04.027
   Waite M, 2017, ENERGY, V127, P786, DOI 10.1016/j.energy.2017.03.095
   Wickham H., 2016, GGPLOT2 ELEGANT GRAP, P189
   Wood Simon, 2023, CRAN
   Woods J, 2022, JOULE, V6, P726, DOI 10.1016/j.joule.2022.02.013
   Xiang JJ, 2018, J OCCUP ENVIRON MED, V60, pE463, DOI 10.1097/JOM.0000000000001395
   Zander KK, 2015, NAT CLIM CHANGE, V5, P647, DOI [10.1038/NCLIMATE2623, 10.1038/nclimate2623]
   Zhao L, 2021, NAT CLIM CHANGE, V11, DOI 10.1038/s41558-020-00958-8
   Zonato A, 2021, J GEOPHYS RES-ATMOS, V126, DOI 10.1029/2021JD035002
NR 67
TC 7
Z9 7
U1 4
U2 22
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 MAY 1
PY 2023
VL 286
AR 112954
DI 10.1016/j.enbuild.2023.112954
EA MAR 2023
PG 12
WC Construction & Building Technology; Energy & Fuels; Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Energy & Fuels; Engineering
GA E0NK1
UT WOS:000972603300001
PM 37601430
OA hybrid, Green Accepted
DA 2025-01-10
ER

PT J
AU Tribble, CM
   May, MR
   Jackson-Gain, A
   Zenil-Ferguson, R
   Specht, CD
   Rothfels, CJ
AF Tribble, Carrie M.
   May, Michael R.
   Jackson-Gain, Abigail
   Zenil-Ferguson, Rosana
   Specht, Chelsea D.
   Rothfels, Carl J.
TI Unearthing Modes of Climatic Adaptation in Underground Storage Organs
   Across Liliales
SO SYSTEMATIC BIOLOGY
LA English
DT Article
ID MULTIPLE SEQUENCE ALIGNMENT; STABILIZING SELECTION; R PACKAGE;
   EVOLUTION; CHARACTERS; ECOLOGY; INFORMATION; SPECIATION; DISCRETE;
   SOFTWARE
AB Testing adaptive hypotheses about how continuous traits evolve in association with developmentally structured discrete traits, while accounting for the confounding influence of other, hidden, evolutionary forces, remains a challenge in evolutionary biology. For example, geophytes are herbaceous plants-with underground buds-that use underground storage organs (USOs) to survive extended periods of unfavorable conditions. Such plants have evolved multiple times independently across all major vascular plant lineages. Even within closely related lineages, however, geophytes show impressive variation in the morphological modifications and structures (i.e.,"types" of USOs) that allow them to survive underground. Despite the developmental and structural complexity of USOs, the prevailing hypothesis is that they represent convergent evolutionary "solutions" to a common ecological problem, though some recent research has drawn this conclusion into question. We extend existing phylogenetic comparative methods to test for links between the hierarchical discrete morphological traits associated with USOs and adaptation to environmental variables, using a phylogeny of 621 species in Liliales. We found that plants with different USO types do not differ in climatic niche more than expected by chance, with the exception of root morphology, where modified roots are associated with lower temperature seasonality. These findings suggest that root tubers may reflect adaptations to different climatic conditions than those represented by other types of USOs. Thus, the tissue type and developmental origin of the USO structure may influence the way it mediates ecological relationships, which draws into question the appropriateness of ascribing broad ecological patterns uniformly across geophytic taxa. This work provides a new framework for testing adaptive hypotheses and for linking ecological patterns across morphologically varying taxa while accounting for developmental (non-independent) relationships in morphological data. [Climatic niche evolution; geophytes; imperfect correspondence; macroevolution.].
C1 [Tribble, Carrie M.] Univ Hawaii Manoa, Sch Life Sci, Honolulu, HI 96822 USA.
   [May, Michael R.; Jackson-Gain, Abigail; Rothfels, Carl J.] Biol Univ Calif Berkeley, Dept Integrat, Berkeley, CA 94709 USA.
   [May, Michael R.; Jackson-Gain, Abigail; Rothfels, Carl J.] Univ Calif Berkeley, Univ Herbarium, Berkeley, CA 94709 USA.
   [May, Michael R.] Univ Calif Davis, Dept Evolut & Ecol, Davis, CA 95616 USA.
   [Jackson-Gain, Abigail] Univ Chile, Fac Ciencias Fis & Matemat, Dept Geol, Santiago, Chile.
   [Zenil-Ferguson, Rosana] Univ Kentucky, Dept Biol, Lexington, KY 40506 USA.
   [Specht, Chelsea D.] Cornell Univ, Sch Integrat Plant Sci, Sect Plant Biol & LH Bailey Hortorium, Ithaca, NY 14853 USA.
   [Rothfels, Carl J.] Utah State Univ, Dept Biol, Logan, UT 84322 USA.
   [Tribble, Carrie M.] Univ Hawaii Manoa, Sch Life Sci, 2538 McCarthy Mall, Edmondson 216, Honolulu, HI 96822 USA.
C3 University of Hawaii System; University of Hawaii Manoa; University of
   California System; University of California Berkeley; University of
   California System; University of California Davis; Universidad de Chile;
   University of Kentucky; Cornell University; Utah System of Higher
   Education; Utah State University; University of Hawaii System;
   University of Hawaii Manoa
RP Tribble, CM (corresponding author), Univ Hawaii Manoa, Sch Life Sci, 2538 McCarthy Mall, Edmondson 216, Honolulu, HI 96822 USA.
EM ctribble09@gmail.com
RI Specht, Chelsea/E-8545-2010
OI Rothfels, Carl/0000-0002-6605-1770; May, Michael/0000-0002-5031-4820;
   Specht, Chelsea/0000-0001-7746-512X; Tribble, Carrie
   M./0000-0001-7263-7885
CR Adler PB, 2014, P NATL ACAD SCI USA, V111, P740, DOI 10.1073/pnas.1315179111
   [Anonymous], 2006, R News
   [Anonymous], 2016, Angiosperm phylogeny website. Version 13
   Beaulieu JM, 2016, SYST BIOL, V65, P583, DOI 10.1093/sysbio/syw022
   Beaulieu JM, 2013, SYST BIOL, V62, P725, DOI 10.1093/sysbio/syt034
   Beaulieu JM, 2012, EVOLUTION, V66, P2369, DOI 10.1111/j.1558-5646.2012.01619.x
   Benson DA, 2017, NUCLEIC ACIDS RES, V45, pD37, DOI [10.1093/nar/gkw1070, 10.1093/nar/gkp1024, 10.1093/nar/gkx1094, 10.1093/nar/gks1195, 10.1093/nar/gkl986, 10.1093/nar/gkq1079, 10.1093/nar/gkg057, 10.1093/nar/gkr1202, 10.1093/nar/gkn723]
   Butler MA, 2004, AM NAT, V164, P683, DOI 10.1086/426002
   Cuéllar-Martínez M, 2016, BOT SCI, V94, P687, DOI 10.17129/botsci.763
   de Queiroz A, 2007, TRENDS ECOL EVOL, V22, P34, DOI 10.1016/j.tree.2006.10.002
   Enquist BJ, 1999, NATURE, V401, P907, DOI 10.1038/44819
   Felsenstein J, 2012, AM NAT, V179, P145, DOI 10.1086/663681
   Feng X, 2019, ECOL EVOL, V9, P10365, DOI 10.1002/ece3.5555
   Fick SE, 2017, INT J CLIMATOL, V37, P4302, DOI 10.1002/joc.5086
   Flemons P, 2007, ECOL INFORM, V2, P49, DOI 10.1016/j.ecoinf.2007.03.004
   Freyman WA, 2015, EVOL BIOINFORM, V11, P263, DOI 10.4137/EBO.S35384
   GARLAND T, 1993, SYST BIOL, V42, P265, DOI 10.2307/2992464
   Givnish TJ, 2016, CLADISTICS, V32, P581, DOI 10.1111/cla.12153
   Green PJ, 1995, BIOMETRIKA, V82, P711, DOI 10.1093/biomet/82.4.711
   Hansen TF, 1997, EVOLUTION, V51, P1341, DOI [10.2307/2411186, 10.1111/j.1558-5646.1997.tb01457.x]
   Howard CC, 2021, AM J BOT, V108, P361, DOI 10.1002/ajb2.1622
   Howard CC, 2019, AM J BOT, V106, P850, DOI 10.1002/ajb2.1289
   Huelsenbeck JP, 2003, SYST BIOL, V52, P131, DOI 10.1080/10635150309342
   Iles WJD, 2015, BOT J LINN SOC, V178, P346, DOI 10.1111/boj.12233
   JANZEN D.H., 1975, Ecology of plants in the tropics
   Kamenetsky R, 2013, ORNAMENTAL GEOPHYTES: FROM BASIC SCIENCE TO SUSTAINABLE PRODUCTION, P1
   Katoh K, 2013, MOL BIOL EVOL, V30, P772, DOI 10.1093/molbev/mst010
   Klimesová J, 2018, FUNCT ECOL, V32, P2115, DOI 10.1111/1365-2435.13145
   Kubitzki K., 1998, FAMILIES GENERA VASC, VIII
   Lee DC, 1999, CLADISTICS, V15, P373, DOI 10.1111/j.1096-0031.1999.tb00273.x
   Leebens-Mack J., 2020, COMMUNICATION
   Maddison WP, 2007, SYST BIOL, V56, P701, DOI 10.1080/10635150701607033
   Maddison WP, 2015, SYST BIOL, V64, P127, DOI 10.1093/sysbio/syu070
   Maitner BS, 2018, METHODS ECOL EVOL, V9, P373, DOI 10.1111/2041-210X.12861
   May MR, 2020, SYST BIOL, V69, P530, DOI 10.1093/sysbio/syz069
   Miller MA, 2015, EVOL BIOINFORM, V11, P43, DOI 10.4137/EBO.S21501
   Mirarab S, 2015, J COMPUT BIOL, V22, P377, DOI 10.1089/cmb.2014.0156
   Nielsen R, 2002, SYST BIOL, V51, P729, DOI 10.1080/10635150290102393
   Paradis E, 2019, BIOINFORMATICS, V35, P526, DOI 10.1093/bioinformatics/bty633
   Parsons RF, 2003, AUST J BOT, V51, P129, DOI 10.1071/BT02067
   Pate J.S., 1982, Tuberous, cormous and bulbous plants: Biology of an adaptive strategy in Western Australia
   Patterson TB, 2002, EVOLUTION, V56, P233, DOI 10.1111/j.0014-3820.2002.tb01334.x
   Phillips SJ, 2008, ECOGRAPHY, V31, P161, DOI 10.1111/j.0906-7590.2008.5203.x
   Raats M. M., 1992, Food Quality and Preference, V3, P89, DOI 10.1016/0950-3293(91)90028-D
   Rabosky DL, 2015, SYST BIOL, V64, P340, DOI 10.1093/sysbio/syu131
   RAUNKIAER C., 1934
   Rees A., 1989, Herbertia, V45, P104
   REES AR, 1966, BOT REV, V32, P1, DOI 10.1007/BF02858583
   Revell LJ, 2012, METHODS ECOL EVOL, V3, P217, DOI 10.1111/j.2041-210X.2011.00169.x
   Ronquist F, 2012, SYST BIOL, V61, P539, DOI 10.1093/sysbio/sys029
   Sanderson MJ, 2002, MOL BIOL EVOL, V19, P101, DOI 10.1093/oxfordjournals.molbev.a003974
   Sanso AM, 2001, ANN BOT-LONDON, V88, P1057, DOI 10.1006/anbo.2001.1548
   Sosa V, 2017, PEERJ, V5, DOI 10.7717/peerj.3932
   Sosa V, 2016, TAXON, V65, P235, DOI 10.12705/652.2
   Tarasov S, 2019, INSECT SYST DIVER, V3, DOI 10.1093/isd/ixz009
   Tarasov S, 2019, SYST BIOL, V68, P698, DOI 10.1093/sysbio/syz005
   Tribble C., 2022, DRYAD DATASET, DOI [10.6078/D1BM6V, DOI 10.6078/D1BM6V]
   Tribble CM, 2021, AM J BOT, V108, P372, DOI 10.1002/ajb2.1623
   Uyeda J. C., 2019, BAYOU TUTORIAL
   Uyeda JC, 2018, SYST BIOL, V67, P1091, DOI 10.1093/sysbio/syy031
   Uyeda JC, 2014, SYST BIOL, V63, P902, DOI 10.1093/sysbio/syu057
   Vaidya G, 2011, CLADISTICS, V27, P171, DOI 10.1111/j.1096-0031.2010.00329.x
   Vasconcelos T, 2023, J BIOGEOGR, V50, P43, DOI 10.1111/jbi.14292
   WCSP, 2020, WORLD CHECKL SEL PLA
   Whigham DE, 2004, ANNU REV ECOL EVOL S, V35, P583, DOI 10.1146/annurev.ecolsys.35.021103.105708
NR 65
TC 7
Z9 7
U1 2
U2 11
PU OXFORD UNIV PRESS
PI OXFORD
PA GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND
SN 1063-5157
EI 1076-836X
J9 SYST BIOL
JI Syst. Biol.
PD MAY 19
PY 2023
VL 72
IS 1
BP 198
EP 212
DI 10.1093/sysbio/syac070
EA MAR 2023
PG 15
WC Evolutionary Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Evolutionary Biology
GA H0GQ5
UT WOS:000942794000001
PM 36380514
OA Green Submitted
DA 2025-01-10
ER

PT J
AU Zhao, QQ
   Chen, Y
   Gone, KP
   Wells, E
   Margeson, K
   Sherren, K
AF Zhao, Qiqi
   Chen, Yan
   Gone, Keshava Pallavi
   Wells, Emily
   Margeson, Keahna
   Sherren, Kate
TI Modelling cultural ecosystem services in agricultural dykelands and
   tidal wetlands to inform coastal infrastructure decisions: A social
   media data approach
SO MARINE POLICY
LA English
DT Article
DE Cultural ecosystem services; Climate adaptation; Social media data; CES
   modeling; Landscape management; Tidal wetlands; polders
ID MARINE PROTECTED AREA; VALUES; INDICATORS; ENVIRONMENT; ADAPTATION;
   LANDSCAPES; SCIENCE; BAY
AB Agricultural dykelands and tidal wetlands around Canada's Bay of Fundy are experiencing increasingly severe impacts from sea level rise and climate change, leading to management challenges. Managers will have to decide which dykes to reinforce, which to realign or remove, and where to restore wetlands. These decisions will have important impacts on the ecosystem services provided by different landscapes and the beneficiaries who use them. Cultural ecosystem services (CES) are non-material benefits that play a significant role in human-nature relationships. Previous research in the region has indicated strong local dykeland attachments and CES but provided little insight about tidal wetland uses and values. Using the Kings County region as a study area, we identify CES provided by the area through text analysis of Instagram data and map the CES using the SolVES model combined with environmental data. Revealed differences in CES delivery from agricultural dykelands and tidal wetlands provide spatial insight for coastal planning. The results show that agricultural dykelands have a higher supply capacity for cultural heritage/diversity, education and knowledge systems and social relations and relational values; tidal wetlands have a higher supply capacity for sense of place and terroir. For aesthetics, inspiration and art, and recreation and tourism, the two landscapes are comparable in delivery. In the small proportion of the two landscapes where CES are modelled as being present they often overlap, demonstrating multifunctionality, with an average of 1.4 services provided by a given area of agricultural dykelands and 2.6 services by tidal wetlands.
C1 [Zhao, Qiqi] Nanjing Univ, Sch Geog & Ocean Sci, Nanjing, Peoples R China.
   [Zhao, Qiqi; Chen, Yan; Wells, Emily; Margeson, Keahna; Sherren, Kate] Dalhousie Univ, Sch Resource & Environm Studies, Halifax, NS, Canada.
   [Chen, Yan; Gone, Keshava Pallavi] Dalhousie Univ, Sch Informat, Halifax, NS, Canada.
   [Gone, Keshava Pallavi] Dalhousie Univ, Fac Comp Sci, Halifax, NS, Canada.
   [Margeson, Keahna] Dalhousie Univ, Sch Planning, Halifax, NS, Canada.
   [Zhao, Qiqi] Nanjing Univ, Sch Geog & Oceanog Sci, 163 Xianlin Ave, Nanjing 210023, Jiangsu, Peoples R China.
C3 Nanjing University; Dalhousie University; Dalhousie University;
   Dalhousie University; Dalhousie University; Nanjing University
RP Zhao, QQ (corresponding author), Nanjing Univ, Sch Geog & Oceanog Sci, 163 Xianlin Ave, Nanjing 210023, Jiangsu, Peoples R China.
EM dg1927048@smail.nju.edu.cn
RI Margeson, Keahna/GYV-4037-2022
OI Sherren, Kate/0000-0003-1576-9878
FU China Scholarship Council (CSC) [202106190085]; program B for
   Outstanding PhD candidate of Nanjing University [202202B030]; Social
   Sciences and Humanities Research Council (SSHRC) of Canada through
   Insight Grant [435-2018-1018, 2018-2022]; NS Research and Innovation
   Graduate Scholarship; SSHRC Canada Graduate Scholarship-Masters and
   Natural Sciences and Engineering Research Council (NSERC) of Canada
   Strategic Partnership Grant for Networks ResNet [OCN-110-7]; Ocean
   Graduate Excellence Network; Ocean Frontiers Institute; National
   Research Council [435-2021-0221]; SSHRC Insight Grant;  [CRSNG NETGP
   523374-18]
FX QZ is funded by China Scholarship Council (CSC) No.202106190085.
   Supported by the program B for Outstanding PhD candidate of Nanjing
   University, No.202202B030. YC and KPG are funded by the Social Sciences
   and Humanities Research Council (SSHRC) of Canada through Insight Grant
   435-2018-1018, 2018-2022 (MS as PI, KS CI) , and YC the NS Research and
   Innovation Graduate Scholarship (2018-2023) . EW is funded by a SSHRC
   Canada Graduate Scholarship-Masters and Natural Sciences and Engineering
   Research Council (NSERC) of Canada Strategic Partnership Grant for
   Networks ResNet (CRSNG NETGP 523374-18, KS CI). KM is funded by the
   Ocean Graduate Excellence Network through a partnership with Ocean
   Frontiers Institute and the National Research Council (OCN-110-7) with
   additional funds from SSHRC Insight Grant (435-2021-0221, KS PI) . Many
   thanks to Mehrnoosh Mohammadi for early discussions of this work, and
   Robin Gerl for the bigram methodology.
CR [Anonymous], 2005, Ecosystems and Human Well-being: Desertification Synthesis, P1
   [Anonymous], 2019, DYK SYST UPGR PROT C
   Becken S, 2017, J ENVIRON MANAGE, V203, P87, DOI 10.1016/j.jenvman.2017.07.007
   Blake D, 2017, OCEAN COAST MANAGE, V148, P195, DOI 10.1016/j.ocecoaman.2017.08.010
   Blythe J, 2020, OCEAN COAST MANAGE, V185, DOI 10.1016/j.ocecoaman.2019.105028
   Boone LK, 2017, COAST RES LIBR, V21, P705, DOI 10.1007/978-3-319-56179-0_21
   Brown P. F., 1992, Computational Linguistics, V18, P467
   Butzer KW, 2002, ANN ASSOC AM GEOGR, V92, P451, DOI 10.1111/1467-8306.00299
   Calcagni F, 2019, SUSTAIN SCI, V14, P1309, DOI 10.1007/s11625-019-00672-1
   Campbell C.E., 2017, MCG QUEEN RURAL WILD
   Cao HJ, 2022, ECOL INDIC, V137, DOI 10.1016/j.ecolind.2022.108756
   Chen Y, 2020, OCEAN COAST MANAGE, V193, DOI 10.1016/j.ocecoaman.2020.105254
   Chen Y, 2019, SOC NATUR RESOUR, V32, P1114, DOI 10.1080/08941920.2019.1587128
   Clarke B, 2021, ENVIRON SCI POLICY, V116, P220, DOI 10.1016/j.envsci.2020.11.014
   Clemente P, 2019, ECOL INDIC, V96, P59, DOI 10.1016/j.ecolind.2018.08.043
   Costanza R, 1997, NATURE, V387, P253, DOI 10.1038/387253a0
   Dang H, 2021, FORESTS, V12, DOI 10.3390/f12070813
   Davey M, 2014, AUST GEOGR, V45, P131, DOI 10.1080/00049182.2014.899025
   Davidson NC, 2019, MAR FRESHWATER RES, V70, P1189, DOI 10.1071/MF18391
   Depietri Y, 2020, ECOSYST SERV, V44, DOI 10.1016/j.ecoser.2020.101108
   Desplanque C., 1982, CAN POLDERS WORLD, V1, P5
   Díaz S, 2018, SCIENCE, V359, P270, DOI 10.1126/science.aap8826
   Dou YH, 2021, ECOSYST SERV, V50, DOI 10.1016/j.ecoser.2021.101311
   Edwards A, 2013, INT J SOC RES METHOD, V16, P245, DOI 10.1080/13645579.2013.774185
   Elwell TL, 2020, ECOSYST SERV, V44, DOI 10.1016/j.ecoser.2020.101123
   Fagerholm N, 2012, ECOL INDIC, V18, P421, DOI 10.1016/j.ecolind.2011.12.004
   Fletcher R, 2014, MAR POLICY, V50, P151, DOI 10.1016/j.marpol.2014.05.001
   Fox N, 2021, ECOSYST SERV, V50, DOI 10.1016/j.ecoser.2021.101328
   Galparsoro I, 2021, MAR POLICY, V131, DOI 10.1016/j.marpol.2021.104609
   Ghermand A., 2020, Tourism Management, P77
   Hale R.L., 2019, ECOL INDIC, P107
   Heikinheimo V, 2020, LANDSCAPE URBAN PLAN, V201, DOI 10.1016/j.landurbplan.2020.103845
   Ibrohim Muhammad Okky, 2018, Procedia Computer Science, V135, P222, DOI 10.1016/j.procs.2018.08.169
   INSTAGRAM STATISTICS A.N.D, 2022, TRENDS ESS INST STAT
   Iqbal M., 2022, INSTAGRAM REVENUE US
   Johnston A., 2020, BIORXIV
   Ketonen V, 2020, INT J MED INFORM, V141, DOI 10.1016/j.ijmedinf.2020.104223
   Lee H, 2019, ECOL INDIC, V96, P505, DOI 10.1016/j.ecolind.2018.08.035
   Ma ZJ, 2014, SCIENCE, V346, P912, DOI 10.1126/science.1257258
   Malik A, 2022, TECHNOL SOC, V70, DOI 10.1016/j.techsoc.2022.102008
   Malinauskaite L, 2021, ECOL ECON, V180, DOI 10.1016/j.ecolecon.2020.106867
   Marres N, 2012, SOCIOL REV, V60, P139, DOI 10.1111/j.1467-954X.2012.02121.x
   Mitchell L, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0064417
   Mitsch William J., 2015, International Journal of Biodiversity Science Ecosystem Services & Management, V11, P1, DOI 10.1080/21513732.2015.1006250
   Munang R, 2013, CURR OPIN ENV SUST, V5, P67, DOI 10.1016/j.cosust.2012.12.001
   OECD, 2019, RESP RIS SEAS
   Oteros-Rozas E, 2018, ECOL INDIC, V94, P74, DOI 10.1016/j.ecolind.2017.02.009
   Pinto R, 2014, ECOL INDIC, V36, P644, DOI 10.1016/j.ecolind.2013.09.015
   Retka J, 2019, OCEAN COAST MANAGE, V176, P40, DOI 10.1016/j.ocecoaman.2019.04.018
   Ruiz-Frau A, 2020, ECOSYST SERV, V45, DOI 10.1016/j.ecoser.2020.101176
   Rusho M.A., 2021, WATER AIR SOIL POLL, V11
   Santos Vieira F.A., 2021, OCEAN COAST MANAGE, V214
   Schirpke U., 2021, ECOSYST SERV, P51
   Schirpke U, 2021, ECOSYST SERV, V51, DOI 10.1016/j.ecoser.2021.101354
   Schreiber L, 2023, ENVIRON RES, V216, DOI 10.1016/j.envres.2022.114456
   Shah DV, 2015, ANN AM ACAD POLIT SS, V659, P6, DOI 10.1177/0002716215572084
   Sherren K, 2021, FACETS, V6, P1446, DOI 10.1139/facets-2020-0073
   Sherren K, 2016, LAND USE POLICY, V51, P267, DOI 10.1016/j.landusepol.2015.11.018
   Sherren K, 2011, SOC NATUR RESOUR, V24, P412, DOI 10.1080/08941920.2010.488686
   Sherren Kate, 2022, CURR OPIN ENV SUST
   Sherrouse B., 2015, SOCIAL VALUES ECOSYS
   Sherrouse BC, 2017, ECOSYST SERV, V26, P431, DOI 10.1016/j.ecoser.2017.02.003
   Sherrouse BC, 2011, APPL GEOGR, V31, P748, DOI 10.1016/j.apgeog.2010.08.002
   Spanou E, 2020, ECOL ECON, V176, DOI 10.1016/j.ecolecon.2020.106757
   Tan CM, 2002, INFORM PROCESS MANAG, V38, P529, DOI 10.1016/S0306-4573(01)00045-0
   Tenerelli P, 2017, LANDSCAPE ECOL, V32, P1097, DOI 10.1007/s10980-017-0498-7
   Tenerelli P, 2016, ECOL INDIC, V64, P237, DOI 10.1016/j.ecolind.2015.12.042
   Tengberg A, 2012, ECOSYST SERV, V2, P14, DOI 10.1016/j.ecoser.2012.07.006
   Toivonen T, 2019, BIOL CONSERV, V233, P298, DOI 10.1016/j.biocon.2019.01.023
   Van Coppenolle R, 2019, ESTUAR COAST SHELF S, V226, DOI 10.1016/j.ecss.2019.106262
   van Proosdij D., 2011, DYKELANDS CLIMATE CH
   van Zanten BT, 2016, P NATL ACAD SCI USA, V113, P12974, DOI 10.1073/pnas.1614158113
   Virgin SDS, 2020, ECOL ENG, V149, DOI 10.1016/j.ecoleng.2020.105713
   Waltham NJ, 2021, ESTUAR COAST, V44, P1681, DOI 10.1007/s12237-020-00875-1
   Wang ZF, 2021, URBAN FOR URBAN GREE, V63, DOI 10.1016/j.ufug.2021.127233
   White MP, 2016, PREV MED, V91, P383, DOI 10.1016/j.ypmed.2016.08.023
   Wollenberg JT, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0193930
   Yang YY, 2019, J CLEAN PROD, V225, P11, DOI 10.1016/j.jclepro.2019.03.242
   Zhao Q., 2021, REMOTE SENS-BASEL, V13, P2
   Zhao QQ, 2019, ENVIRON SCI POLLUT R, V26, P6065, DOI 10.1007/s11356-018-3910-1
NR 80
TC 10
Z9 10
U1 17
U2 68
PU ELSEVIER SCI LTD
PI London
PA 125 London Wall, London, ENGLAND
SN 0308-597X
EI 1872-9460
J9 MAR POLICY
JI Mar. Pol.
PD APR
PY 2023
VL 150
AR 105533
DI 10.1016/j.marpol.2023.105533
EA FEB 2023
PG 10
WC Environmental Studies; International Relations
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; International Relations
GA 8X4QG
UT WOS:000931998200001
DA 2025-01-10
ER

PT J
AU Altoom, MB
   Adam, E
   Ali, KA
AF Altoom, Mohammed B. B.
   Adam, Elhadi
   Ali, Khalid Adem
TI Mapping and Monitoring Spatio-Temporal Patterns of Rainfed Agriculture
   Lands of North Darfur State, Sudan, Using Earth Observation Data
SO LAND
LA English
DT Article
DE remote sensing; Sudan; change detection; random forest classifier; land
   cover
ID DESERTIFICATION; REGION; IMPACT
AB Rainfed agriculture in Northern Darfur is influenced by erratic seasonal and decadal rainfall patterns and frequent droughts. Understanding the spatio-temporal variation in rainfed agriculture is crucial for promoting food security, socio-economic stability and protecting the vulnerable ecosystem. This study aimed to investigate the spatio-temporal dynamics of rainfed agriculture in North Darfur State from 1984-2019 using multitemporal Landsat observation data. Using the random forest technique, the multitemporal images were classified into common land use/land cover classes and rainfed agriculture on goz (sandy) and wadi (seasonal river) lands. Overall accuracies were assessed using a confusion matrix. Overall accuracies were assessed using a confusion matrix has ranging between 94.7% and 96.9%, while the kappa statistics were greater than 0.90. The results showed that the high spatial variability in goz land used for rainfed agriculture increased of (889,622.46 ha) over 1994-1999, while it decreased (658,568.61 ha) over 2004-2009 south of the 232.9 mm isohyet. Rainfed cultivation of wadi lands expanded significantly of (580,515.03 ha) over 2014-2019 and decreased (182,701.8 ha) over 1994-1999, especially in the 362.8-477.2 mm isohyets (beyond the climate-adapted 500 mm isohyet agronomic dry limit). These spatial trends need further investigation as they may exacerbate both regional land degradation and disputes among farmers over scarce wadi lands. This study provides essential spatial data which are lacking owing to ongoing conflicts; this can help decision-makers formulate sustainable land use monitoring systems.
C1 [Altoom, Mohammed B. B.; Adam, Elhadi; Ali, Khalid Adem] Univ Witwatersrand, Fac Sci, Sch Geog Archaeol & Environm Studies, ZA-2050 Johannesburg, South Africa.
   [Ali, Khalid Adem] Coll Charleston, Dept Geol & Environm Geosci, Charleston, SC 29424 USA.
C3 University of Witwatersrand; College of Charleston
RP Altoom, MB (corresponding author), Univ Witwatersrand, Fac Sci, Sch Geog Archaeol & Environm Studies, ZA-2050 Johannesburg, South Africa.
EM 2287659@students.wits.ac.za
RI Adam, Elhadi/R-2647-2016
OI Adam, Elhadi/0000-0003-3626-5839
CR Abdelaziz H. H., 2010, Journal of Applied Sciences Research, P156
   Abdul-Jalil M, 2013, WAR SOC, V32, P156, DOI 10.1179/0729247313Z.00000000022
   Ali Ahmed A., 2008, 5 POPULATION CENSUS
   Ali E.-A.D.M., 2016, INT J CURR MICROBIOL, V5, P94, DOI [10.20546/ijcmas.2016.505.011, DOI 10.20546/IJCMAS.2016.505.011]
   Biro K, 2013, LAND DEGRAD DEV, V24, P90, DOI 10.1002/ldr.1116
   Bradford JB, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-13165-x
   Branch HG, 2006, NATO SCI PEACE SECUR, V3, P11
   Breiman L, 2001, MACH LEARN, V45, P5, DOI 10.1023/A:1010933404324
   Carella E, 2022, ANIMALS-BASEL, V12, DOI 10.3390/ani12081049
   Colombo R., 2011, OPTICAL REMOTE SENSI
   CONGALTON RG, 1991, REMOTE SENS ENVIRON, V37, P35, DOI 10.1016/0034-4257(91)90048-B
   De Marinis P, 2021, LAND-BASEL, V10, DOI 10.3390/land10121368
   Elagib NA, 2021, J HYDROL, V599, DOI 10.1016/j.jhydrol.2021.126362
   Elagib NA, 2019, AGR FOREST METEOROL, V276, DOI 10.1016/j.agrformet.2019.107640
   Fadul A.A., 2004, P ENV DEGRADATION CA, P33
   FULLER TD, 1987, AGR ADMIN EXT, V25, P215, DOI 10.1016/0269-7475(87)90078-X
   Ibrahim F., 1978, GeoJournal, V2, P243, DOI 10.1007/BF00208640
   Ibrahim F. N., 1982, Geo Journal, V6, P25, DOI 10.1007/BF00446590
   Ibrahim F.N., 1984, Ecological imbalance in the Republic of the Sudan: With reference to desertification in Darfur
   Ibrahim H.H., 2015, INT J REMOTE SENS, V4, P124
   Islam K, 2018, EGYPT J REMOTE SENS, V21, P37, DOI 10.1016/j.ejrs.2016.12.005
   Kumar Saurabh, 2020, Procedia Computer Science, V171, P1184, DOI 10.1016/j.procs.2020.04.127
   Laux P, 2010, AGR FOREST METEOROL, V150, P1258, DOI 10.1016/j.agrformet.2010.05.008
   Levi P, 2010, PROGRAM-ELECTRON LIB, V44, P39, DOI 10.1108/00330331011019672
   Lossou E, 2019, REMOTE SENS APPL, V16, DOI 10.1016/j.rsase.2019.100264
   Melaas EK, 2013, REMOTE SENS ENVIRON, V132, P176, DOI 10.1016/j.rse.2013.01.011
   Mohammed A. J., 2013, Journal of Natural Resources Policy Research, V5, P49, DOI 10.1080/19390459.2013.797153
   Mohmmed N, 2018, LAND DEGRAD DEV, V29, P4424, DOI 10.1002/ldr.3180
   Nababa II, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12213619
   Nakalembe C, 2021, GLOB FOOD SECUR-AGR, V29, DOI 10.1016/j.gfs.2021.100543
   Orusa T, 2021, CLIMATE, V9, DOI 10.3390/cli9030047
   Orusa T, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12213542
   Osman A, 2012, THESIS TUFTS U BOSTO
   Osman A. K., 2007, LEISA Magazine, V23, P18
   Osman A.M.K., 2013, EXAMINATION DARFUR O
   Osman A.M.K., 2014, WE NO LONGER SHARE L
   Puissant A, 2014, INT J APPL EARTH OBS, V26, P235, DOI 10.1016/j.jag.2013.07.002
   Rembold F, 2019, AGR SYST, V168, P247, DOI 10.1016/j.agsy.2018.07.002
   Rockström J, 2010, AGR WATER MANAGE, V97, P543, DOI 10.1016/j.agwat.2009.09.009
   Sabzchi-Dehkharghani H, 2021, AGR WATER MANAGE, V245, DOI 10.1016/j.agwat.2020.106611
   Sahajpal R., 2020, P 12 CONGRESO AGROIN
   Schaefer M, 2019, HELIYON, V5, DOI 10.1016/j.heliyon.2019.e01773
   Siddig K., 2018, POSTSEPARATION SOCIA, V8
   Siddig K, 2020, ECOL ECON, V169, DOI 10.1016/j.ecolecon.2019.106566
   SINGH A, 1989, INT J REMOTE SENS, V10, P989, DOI 10.1080/01431168908903939
   Sohoulande CDD, 2019, AGR WATER MANAGE, V223, DOI 10.1016/j.agwat.2019.105728
   Thyagharajan KK, 2019, ARCH COMPUT METHOD E, V26, P275, DOI 10.1007/s11831-017-9239-y
   Tsoumakas G, 2009, STUD COMPUT INTELL, V245, P1, DOI 10.1007/978-3-642-03999-7_1
   Verikas A, 2011, PATTERN RECOGN, V44, P330, DOI 10.1016/j.patcog.2010.08.011
   Yang X, 2012, J GEOPHYS RES-BIOGEO, V117, DOI 10.1029/2012JG001977
   Young H., 2005, DARFUR 2005 LIVELIHO, V130
NR 51
TC 3
Z9 3
U1 0
U2 6
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-445X
J9 LAND-BASEL
JI Land
PD FEB
PY 2023
VL 12
IS 2
AR 307
DI 10.3390/land12020307
PG 21
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA 9J3FF
UT WOS:000940076400001
OA gold
DA 2025-01-10
ER

PT J
AU Sharif, AN
   Saleh, SK
   Afzal, S
   Razavi, NS
   Nasab, MF
   Kadaei, S
AF Sharif, Amirmasood Nakhaee
   Saleh, Sanaz Keshavarz
   Afzal, Sadegh
   Razavi, Niloofar Shoja
   Nasab, Mozhdeh Fadaei
   Kadaei, Samireh
TI Evaluating and Identifying Climatic Design Features in Traditional
   Iranian Architecture for Energy Saving (Case Study of Residential
   Architecture in Northwest of Iran)
SO COMPLEXITY
LA English
DT Article
ID ENVELOPE DESIGN; BUILDINGS; CONSTRUCTION; ENHANCEMENT; CONSUMPTION;
   EFFICIENCY; COMFORT
AB In the last decades, researchers have been considering some fundamental issues such as energy saving, global warming, greenhouse emissions, and non-renewable energy to make models of house environmental standards to achieve a suitable consumption pattern for saving energy. In architecture, using natural energy is one of the essential pillars of design because it was one of the criteria of designing, which was considered on climate and geography, and it has been a high performance of climate adaptation in the modeling of traditional houses. In this research, Azerbaijan (located in northwestern Iran) is selected to evaluate the practical features of traditional Iranian houses designed in the cold climate, and criteria for developing sensible solutions to achieve a suitable design model for energy saving are provided. The primary purpose of this paper is to evaluate and identify the features of climate design in traditional houses in a cold climate, which are suitable residential buildings for energy management, and to identify the components affecting energy saving. The data collection method is based on checklists, observation, considering the orientation, density, solar radiation angle in the region, documentary, analysis of maps, and adaptation of the architectural plan of the studied houses with the pattern of solar radiation in the area. This research discusses the design criteria for future structures and their adaptable measures based on the obtained results. Finally, it is declared that the traditional architectural design model follows the region's climatic conditions, and considering the current climate and energies, traditional houses were designed; therefore, the best model for maximum use of available energy is climatic design. As a result, suggestions are made regarding residential architecture design to save energy.
C1 [Sharif, Amirmasood Nakhaee] Islamic Azad Univ Mashhad, Fac Art & Architecture, Dept Architecture, Mashhad, Razavi Khorasan, Iran.
   [Saleh, Sanaz Keshavarz] Islamic Azad Univ, Dept Architecture, Zanjan Branch, Zanjan, Iran.
   [Afzal, Sadegh] Univ Mohaghegh Ardabili, Dept Mech Engn, Ardebil, Iran.
   [Razavi, Niloofar Shoja] Imam Khomeini Int Univ IKIU, Dept Architecture & Urbanism, MA Grad Urban Dev, Qazvin, Iran.
   [Nasab, Mozhdeh Fadaei] Fac Payame Noor Univ Sirjan, Kerman, Iran.
   [Kadaei, Samireh] Bushehr Univ, Fac Art & Architecture, Dept Architecture, Bushehr, Iran.
C3 Islamic Azad University; Islamic Azad University; University of
   Mohaghegh Ardabili; Imam Khomeini International University; Persian Gulf
   University
RP Kadaei, S (corresponding author), Bushehr Univ, Fac Art & Architecture, Dept Architecture, Bushehr, Iran.
EM samira.kadaei@gmail.com
RI kadaei, samireh/AFE-4124-2022
CR Abanda FH, 2016, ENERGY, V97, P517, DOI 10.1016/j.energy.2015.12.135
   Al-Saadi SN, 2007, BUILDING SIMULATION 2007, VOLS 1-3, PROCEEDINGS, P1726
   [Anonymous], 2015, URBAN MANAGEMENT
   Aydin YC, 2019, ENERG POLICY, V128, P593, DOI 10.1016/j.enpol.2018.12.036
   Bastide A, 2006, ENERG BUILDINGS, V38, P1093, DOI 10.1016/j.enbuild.2005.12.005
   Bathaei, 2018, ACTA TECHNICA NAPOCE, V61
   Bathaei B, 2016, REV COLII DOCTORALE, V1, P53
   Bathaei B., 2016, EDITURA UNIVERSITAR, V124
   Bathaei B, 2022, CONSTRUCTION RESEARCH CONGRESS 2022: INFRASTRUCTURE, SUSTAINABILITY, AND RESILIENCE, P627
   Biddulph Mike., 2007, Introduction to Residential Layout, DOI [DOI 10.1177/0739456X05285119, 10.4324/9780080468617]
   Binggeli C., 2003, BUILDING SYSTEMS INT, V3rd
   Bodach S, 2014, ENERG BUILDINGS, V81, P227, DOI 10.1016/j.enbuild.2014.06.022
   Chen XY, 2021, ENVIRON MODELL SOFTW, V143, DOI 10.1016/j.envsoft.2021.105116
   Cheung CK, 2005, ENERG BUILDINGS, V37, P37, DOI 10.1016/j.enbuild.2004.05.002
   Department of Housing Urban Development, 2010, EXPERIENCE DOCUMENTA
   DoE U., 2011, Buildings energy databook
   Doraj Parisa, 2022, Natural Volatiles & Essential Oils, V9, P7
   Felius LC, 2020, ENERG EFFIC, V13, P101, DOI 10.1007/s12053-019-09834-7
   Ghobadian V., 2015, TRADITIONAL BUILDING
   Guo C, 2021, IEEE T POWER DELIVER, V36, P2374, DOI 10.1109/TPWRD.2020.3043938
   Guo LB, 2021, IEEE T POWER DELIVER, V36, P3231, DOI 10.1109/TPWRD.2020.3037193
   Gurabi R., 2011, GEOGRAPHICAL Q J ENV, V4, P21
   Heidari A., 2017, IRANIAN ISLAMIC CITY, V7, P21
   Hossein Eskandani O., 2021, INT J SOCIAL HUMANIT, V8, P1114, DOI [10.26450/jshsr.2416, DOI 10.26450/JSHSR.2416]
   Huang S, 2021, ENG APPL COMP FLUID, V15, P1113, DOI 10.1080/19942060.2021.1939790
   Iran T., 2010, 19 ISSUE IRAN NATL B
   Jerusha J., 2020, INT J ENG RES TECHNO, V13, P4084
   Kadaei S., 2020, HUMAN PRESENCE ARCHI, P144
   Kadaei S, 2021, SHOCK VIB, V2021, DOI 10.1155/2021/6363571
   Keynejad M.A., 2010, HIST HOUSES TABRIZ, V1
   Khalil, 2009, P 7 INT ENERGY CONVE
   Kheyri S., 2006, ARCHITECTURE DECORAT, V1
   Kohansal ME, 2022, ARCHIT ENG DES MANAG, V18, P410, DOI 10.1080/17452007.2021.1901220
   Liu SY, 2022, IEEE T TRANSP ELECTR, V8, P1194, DOI 10.1109/TTE.2021.3104876
   Lu CJ, 2022, MEASUREMENT, V188, DOI 10.1016/j.measurement.2021.110527
   Motealleh Parinaz, 2018, HBRC Journal, V14, P215, DOI 10.1016/j.hbrcj.2016.08.001
   Nhleko M., 2020, INT J ENG RES TECHNO, V13, P4033
   Oral GK, 2004, BUILD ENVIRON, V39, P281, DOI 10.1016/S0360-1323(03)00141-0
   Pérez-Lombard L, 2008, ENERG BUILDINGS, V40, P394, DOI 10.1016/j.enbuild.2007.03.007
   Qiu LH, 2022, ENERG CONVERS MANAGE, V267, DOI 10.1016/j.enconman.2022.115879
   Qiu LH, 2022, J ENERGY STORAGE, V51, DOI 10.1016/j.est.2022.104447
   Ralegaonkar RV, 2010, RENEW SUST ENERG REV, V14, P2238, DOI 10.1016/j.rser.2010.04.016
   Rashdi WSSWM, 2016, PROCD SOC BEHV, V222, P782, DOI 10.1016/j.sbspro.2016.05.161
   Rogora A., 2021, BIOCLIMATIC APPROACH, DOI [10.1007/978-3-030-59328-5_25, DOI 10.1007/978-3-030-59328-5_25]
   Sabouri S, 2012, OPTIMIZATION ARCHITE
   Sadineni SB, 2011, RENEW SUST ENERG REV, V15, P3617, DOI 10.1016/j.rser.2011.07.014
   Saljoughinejad S, 2015, BUILD ENVIRON, V92, P475, DOI 10.1016/j.buildenv.2015.05.005
   Shams M., GEOGRAPHICAL PREPARA, V3, P91
   Shan Y, 2022, SOIL DYN EARTHQ ENG, V161, DOI 10.1016/j.soildyn.2022.107419
   Shaterian R., 2009, CLIMATE ARCHITECTURE
   Siew CC, 2011, PROCEDIA ENGINEER, V20, DOI 10.1016/j.proeng.2011.11.178
   Steemers K, 2003, ENERG BUILDINGS, V35, P3, DOI 10.1016/S0378-7788(02)00075-0
   Tian HF, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12213539
   Xu XH, 2019, PHYS REV LETT, V123, DOI 10.1103/PhysRevLett.123.233902
   Yuan J, 2022, INT J CIV ENG, V20, P763, DOI [10.1007/s40999-021-00696-8, 10.1109/IECON49645.2022.9968503]
   Zhang CW, 2022, MECH SYST SIGNAL PR, V177, DOI 10.1016/j.ymssp.2022.109175
   Ziapour BM, 2017, ENERG CONVERS MANAGE, V136, P283, DOI 10.1016/j.enconman.2017.01.031
NR 57
TC 13
Z9 13
U1 1
U2 13
PU WILEY-HINDAWI
PI LONDON
PA ADAM HOUSE, 3RD FL, 1 FITZROY SQ, LONDON, WIT 5HE, ENGLAND
SN 1076-2787
EI 1099-0526
J9 COMPLEXITY
JI Complexity
PD SEP 5
PY 2022
VL 2022
AR 3522883
DI 10.1155/2022/3522883
PG 12
WC Mathematics, Interdisciplinary Applications; Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Mathematics; Science & Technology - Other Topics
GA 5P1IN
UT WOS:000872913200001
OA gold
DA 2025-01-10
ER

PT J
AU Konsta, A
   Chatzimentor, A
   Lin, ML
   Dimitriadis, C
   Kyprioti, A
   Liu, MM
   Li, SH
   Doxa, A
   Mazaris, AD
AF Konsta, Aikaterini
   Chatzimentor, Anastasia
   Lin, Mingli
   Dimitriadis, Charalmpos
   Kyprioti, Amalia
   Liu, Mingming
   Li, Songhai
   Doxa, Aggeliki
   Mazaris, Antonios D.
TI Marine heatwaves threaten key foraging grounds of sea turtles in
   Southeast Asian Seas
SO REGIONAL ENVIRONMENTAL CHANGE
LA English
DT Article
DE Extreme events; Ocean warming; Diet; Marine turtles; Exposure; Tropical
ID SPECIES DISTRIBUTION MODELS; CLIMATE-CHANGE; GREEN TURTLES;
   CHELONIA-MYDAS; ECOSYSTEM; TEMPERATURE; PREDICTION; SEAGRASSES;
   ABUNDANCE; RESPONSES
AB Extreme regional ocean warming events, like marine heatwaves (MHWs), could have severe and long-lasting impacts on species and ecosystems. Extreme and persistent warming of the ocean could directly threaten survival of marine species, as exceeding their thermal tolerance often leads to massive mortality events. Similarly, MHWs could further threaten species persistence indirectly, by altering food webs, leading to cascading effects that are expected to be more pronounced for species at a lower trophic position. Green turtles, a representative species of the charismatic marine megafauna, are largely herbivorous; thus, their food availability is tightly linked to environmental conditions. Here, we explored the degree to which foraging areas of green turtles along the Southeast Asian region could be subjected to MHWs in the future. For this, we applied a series of climatic niche models to spatially delineate important foraging habitats for adult green turtles, Chelonia mydas, across the marine region of Southeast Asia. Our analysis revealed that marine sites, which could host foraging grounds for adult green turtles, cover around 37% of the Southeast Asian region, with high probability of experiencing prolonged and intense MHWs for the vast majority of these sites. The annual number of days subjected to MHWs could increase by 16-fold from the very recent past period, leading to even a permanent MHW state. These results offer some alarming messages for scientists and conservation planners, highlighting the need to improve our knowledge on the potential response of species to MHWs and design climate adaptation strategies.
C1 [Konsta, Aikaterini; Chatzimentor, Anastasia; Kyprioti, Amalia; Doxa, Aggeliki; Mazaris, Antonios D.] Aristotle Univ Thessaloniki, Sch Biol, Dept Ecol, Thessaloniki 54124, Greece.
   [Lin, Mingli; Liu, Mingming; Li, Songhai] Chinese Acad Sci, Inst Deep Sea Sci & Engn, Marine Mammal & Marine Bioacoust Lab, Sanya 572000, Peoples R China.
   [Dimitriadis, Charalmpos] Natl Marine Pk Zakynthos, El Venizelou 1, Zakynthos 29100, Greece.
   [Li, Songhai] Chinese Acad Sci, Ctr Ocean Megasci, Qingdao 266071, Peoples R China.
C3 Aristotle University of Thessaloniki; Chinese Academy of Sciences;
   Institute of Deep-Sea Science & Engineering, CAS; Chinese Academy of
   Sciences
RP Konsta, A (corresponding author), Aristotle Univ Thessaloniki, Sch Biol, Dept Ecol, Thessaloniki 54124, Greece.
EM aakonsta@bio.auth.gr; achatzimen@bio.auth.gr; mingli@idsse.ac.cn;
   xdimitriadis@marine.aegean.gr; kpamalia@bio.auth.gr;
   liuming@idsse.ac.cn; lish@idsse.ac.cn; angedoxa@bio.auth.gr;
   amazaris@bio.auth.gr
RI Chatzimentor, Anastasia/AAY-4664-2020; Li, Songhai/A-2652-2012;
   Dimitriadis, Charalampos/AAF-6504-2020
OI Konsta, Katerina/0000-0001-6615-4350; Chatzimentor,
   Anastasia/0000-0001-7409-8694; Doxa, Aggeliki/0000-0003-4279-1499;
   Dimitriadis, Charalampos/0000-0002-8381-4362
FU Hellenic Foundation for Research and Innovation [2340]
FX The work of AC, AK, AD, and ADM was supported by the Hellenic Foundation
   for Research and Innovation (H.F.R.I.) under the "First Call for
   H.F.R.I. Research Projects to support Faculty members and Researchers
   and the procurement of highcost research equipment grant" (Project
   Number: 2340).
CR Ali A, 2004, CONSERVATION ENHANCE, P31
   Allouche O, 2006, J APPL ECOL, V43, P1223, DOI 10.1111/j.1365-2664.2006.01214.x
   Almpanidou V, 2022, BIODIVERS CONSERV, V31, P143, DOI 10.1007/s10531-021-02326-0
   Arias-Ortiz A, 2018, NAT CLIM CHANGE, V8, P338, DOI 10.1038/s41558-018-0096-y
   Barbet-Massin M, 2012, METHODS ECOL EVOL, V3, P327, DOI 10.1111/j.2041-210X.2011.00172.x
   Bennett S, 2019, PHILOS T R SOC B, V374, DOI 10.1098/rstb.2018.0550
   Bjorndal KA, 2005, ECOL APPL, V15, P304, DOI 10.1890/04-0059
   BJORNDAL KA, 1980, MAR BIOL, V56, P147, DOI 10.1007/BF00397131
   Bjorndal KA, 2017, GLOBAL CHANGE BIOL, V23, P4556, DOI 10.1111/gcb.13712
   Broderick AC, 2001, PHYSIOL BIOCHEM ZOOL, V74, P161, DOI 10.1086/319661
   Brown CJ, 2010, GLOBAL CHANGE BIOL, V16, P1194, DOI 10.1111/j.1365-2486.2009.02046.x
   Carroll G, 2021, P ROY SOC B-BIOL SCI, V288, DOI 10.1098/rspb.2021.0671
   Chambault P, 2021, ECOGRAPHY, V44, P766, DOI 10.1111/ecog.05436
   Chan SKF, 2007, CHELONIAN CONSERV BI, V6, P185, DOI 10.2744/1071-8443(2007)6[185:ACOOTP]2.0.CO;2
   Chatzimentor A., 2021, Clim Change Ecol, V2, DOI DOI 10.1016/J.ECOCHG.2021.100038
   Comte L, 2017, NAT CLIM CHANGE, V7, P718, DOI 10.1038/NCLIMATE3382
   Davenport J, 1997, J THERM BIOL, V22, P479, DOI 10.1016/S0306-4565(97)00066-1
   Dong ZZ, 2021, EARTHS FUTURE, V9, DOI 10.1029/2021EF001992
   Elith J, 2009, ANNU REV ECOL EVOL S, V40, P677, DOI 10.1146/annurev.ecolsys.110308.120159
   Environmental Systems Research Institute (ESRI), 2012, ARCGIS REL 10 1
   Esteban N, 2020, MAR BIOL, V167, DOI 10.1007/s00227-020-03786-8
   Etten JV, 2012, **DATA OBJECT**
   Fielding AH, 1997, ENVIRON CONSERV, V24, P38, DOI 10.1017/S0376892997000088
   Freer JJ, 2018, MAR BIOL, V165, DOI 10.1007/s00227-017-3239-1
   Frölicher TL, 2018, NATURE, V560, P360, DOI 10.1038/s41586-018-0383-9
   Gaillard D, 2021, WILDLIFE RES, V48, P55, DOI 10.1071/WR19127
   Garcia RA, 2014, SCIENCE, V344, P486, DOI 10.1126/science.1247579
   George Robert H., 1997, P363
   Gissi E, 2019, ENVIRON SCI POLICY, V92, P191, DOI 10.1016/j.envsci.2018.12.002
   HAINES H, 1977, INFECT IMMUN, V15, P756, DOI 10.1128/IAI.15.3.756-759.1977
   Halim MH, 1999, REPORT SEAFDEC ASEAN, P328
   Hamann M, 2006, BIODIVERS CONSERV, V15, P3703, DOI 10.1007/s10531-005-4880-4
   Harley CDG, 2012, J PHYCOL, V48, P1064, DOI 10.1111/j.1529-8817.2012.01224.x
   Harvell CD, 1999, SCIENCE, V285, P1505, DOI 10.1126/science.285.5433.1505
   Hattam C, 2021, ECOSYST SERV, V51, DOI 10.1016/j.ecoser.2021.101346
   Hayashida H, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-18241-x
   Hays GC, 2021, BIOL LETTERS, V17, DOI 10.1098/rsbl.2021.0038
   Hijmans A.R.J., 2011, Package 'dismo'
   Hobday AJ, 2016, PROG OCEANOGR, V141, P227, DOI 10.1016/j.pocean.2015.12.014
   Huang DW, 2015, MAR BIODIVERS, V45, P157, DOI 10.1007/s12526-014-0236-1
   Hughes AR, 2009, FRONT ECOL ENVIRON, V7, P242, DOI 10.1890/080041
   Jacox MG, 2019, NATURE, V571, P485, DOI 10.1038/d41586-019-02196-1
   Joseph J, 2014, HERPETOL CONSERV BIO, V9, P516
   Lasram FB, 2010, GLOBAL CHANGE BIOL, V16, P3233, DOI 10.1111/j.1365-2486.2010.02224.x
   Montoya JM, 2010, PHILOS T R SOC B, V365, P2013, DOI 10.1098/rstb.2010.0114
   Moore JK, 2018, SCIENCE, V359, P1139, DOI 10.1126/science.aao6379
   Naimi B, 2016, ECOGRAPHY, V39, P368, DOI 10.1111/ecog.01881
   Ng CKY, 2016, CHELONIAN CONSERV BI, V15, P289, DOI 10.2744/CCB-1210.1
   Nolte CR, 2020, J MAR BIOL ASSOC UK, V100, P291, DOI 10.1017/S0025315420000107
   Oliver ECJ, 2021, ANNU REV MAR SCI, V13, P313, DOI 10.1146/annurev-marine-032720-095144
   Oliver ECJ, 2019, FRONT MAR SCI, V6, DOI 10.3389/fmars.2019.00734
   Oliver ECJ, 2019, CLIM DYNAM, V53, P1653, DOI 10.1007/s00382-019-04707-2
   Orr JA, 2021, METHODS ECOL EVOL, V12, P1521, DOI 10.1111/2041-210X.13621
   Patrício AR, 2021, ENDANGER SPECIES RES, V44, P363, DOI 10.3354/esr01110
   Payne MR, 2016, ICES J MAR SCI, V73, P1272, DOI 10.1093/icesjms/fsv231
   Penick DN, 1996, COMP BIOCHEM PHYS A, V113, P293, DOI 10.1016/0300-9629(95)02068-3
   Pierce D., 2019, Package "ncdf4."
   Pilcher NJ, 2014, J EXP MAR BIOL ECOL, V457, P190, DOI 10.1016/j.jembe.2014.04.002
   Poloczanska ES, 2016, FRONT MAR SCI, V3, DOI 10.3389/fmars.2016.00062
   Poloczanska ES, 2013, NAT CLIM CHANGE, V3, P919, DOI [10.1038/nclimate1958, 10.1038/NCLIMATE1958]
   Pulis A., 2006, JEAPM, V8, P403
   Radchuk V, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-10924-4
   Robinson Robert A., 2009, Endangered Species Research, V7, P87, DOI 10.3354/esr00095
   Schofield G, 2010, DIVERS DISTRIB, V16, P840, DOI 10.1111/j.1472-4642.2010.00694.x
   Sheppard C, 2020, MAR POLLUT BULL, V154, DOI 10.1016/j.marpolbul.2020.111075
   Short FT, 1999, AQUAT BOT, V63, P169, DOI 10.1016/S0304-3770(98)00117-X
   Sippo JZ, 2018, ESTUAR COAST SHELF S, V215, P241, DOI 10.1016/j.ecss.2018.10.011
   Smale DA, 2019, NAT CLIM CHANGE, V9, P306, DOI 10.1038/s41558-019-0412-1
   Spalding MD, 2007, BIOSCIENCE, V57, P573, DOI 10.1641/B570707
   Stillman JH, 2019, PHYSIOLOGY, V34, P86, DOI 10.1152/physiol.00040.2018
   Straub SC, 2019, FRONT MAR SCI, V6, DOI 10.3389/fmars.2019.00763
   Strydom S, 2020, GLOBAL CHANGE BIOL, V26, P3525, DOI 10.1111/gcb.15065
   Stubbs JL, 2020, ECOL MODEL, V431, DOI 10.1016/j.ecolmodel.2020.109185
   Thomson JA, 2015, GLOBAL CHANGE BIOL, V21, P1463, DOI 10.1111/gcb.12694
   Turkozan O, 2021, CLIMATIC CHANGE, V167, DOI 10.1007/s10584-021-03153-6
   Unsworth RKF, 2019, AMBIO, V48, P801, DOI 10.1007/s13280-018-1115-y
   van de Merwe JP, 2009, WILDLIFE RES, V36, P637, DOI 10.1071/WR09099
   Veron J.E.N., 2009, Galaxea - Tokyo, V11, P91
   Walther GR, 2010, PHILOS T R SOC B, V365, P2019, DOI 10.1098/rstb.2010.0021
   Waycott M, 2009, P NATL ACAD SCI USA, V106, P12377, DOI 10.1073/pnas.0905620106
   Whisnant R., 2019, J. Ocean Coast. Econ., V6, DOI [10.15351/2373-8456.1116, DOI 10.15351/2373-8456.1116]
   Yao YL, 2021, J GEOPHYS RES-OCEANS, V126, DOI 10.1029/2021JC017792
NR 82
TC 5
Z9 5
U1 1
U2 21
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 2022
VL 22
IS 3
AR 97
DI 10.1007/s10113-022-01952-w
PG 12
WC Environmental Sciences; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA 2Y6PK
UT WOS:000826016200001
DA 2025-01-10
ER

PT J
AU Fuldauer, LI
   Adshead, D
   Thacker, S
   Gall, S
   Hall, JW
AF Fuldauer, Lena I.
   Adshead, Daniel
   Thacker, Scott
   Gall, Sarah
   Hall, Jim W.
TI Evaluating the benefits of national adaptation to reduce climate risks
   and contribute to the Sustainable Development Goals
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article
DE Sustainable Development Goals (SDGs); National adaptation assessments;
   Climate risk analysis; Spatial SDG indicator translation; Participatory
   methods
ID SOCIAL VULNERABILITY; BASE-LINES; FUTURE; INFRASTRUCTURE; STRATEGIES;
   MANAGEMENT; HOTSPOTS; COSTS; GHANA
AB Scaling up national climate adaptation under the Paris Agreement is critical not only to reduce risk, but also to contribute to a nation's development. Traditional adaptation assessments are aimed at evaluating adaptation to cost-effectively reduce risk and do not capture the far-reaching benefits of adaptation in the context of devel-opment and the global Sustainable Development Goals (SDGs). By grounding adaptation planning in an SDG vision, we propose and demonstrate a methodological process that for the first time allows national decision -makers to: i) quantify the adaptation that is needed to safeguard SDG target progress, and ii) evaluate strate-gies of stakeholder-driven adaptation options to meet those needs whilst delivering additional SDG target co -benefits. This methodological process is spatially applied to a national adaptation assessment in Ghana. In the face of the country's risk from floods and landslides, this analysis identifies which energy and transport assets to prioritise in order to make the greatest contribution to safeguarding development progress. Three strategies ('built', 'nature-based', 'combined SDG strategy') were formulated through a multi-stakeholder partnership involving government, the private sector, and academia as a means to protect Ghana's prioritised assets against climate risk. Evaluating these adaptation strategies in terms of their ability to deliver on SDG targets, we find that the combined SDG strategy maximises SDG co-benefits across 116 targets. The proposed methodological process for integrating SDG targets in adaptation assessments is transferable to other climate-vulnerable nations, and can provide decision-makers with spatially-explicit evidence for implementing sustainable adaptation in alignment with the global agendas.
C1 [Fuldauer, Lena I.; Adshead, Daniel; Thacker, Scott; Gall, Sarah; Hall, Jim W.] Univ Oxford, Environm Change Inst, South Parks Rd, Oxford OX1 3QY, England.
   [Adshead, Daniel] KTH Royal Inst Technol, KTH Climate Act Ctr & KTH Div Energy Syst, SE-10044 Stockholm, Sweden.
C3 University of Oxford; Royal Institute of Technology
RP Fuldauer, LI (corresponding author), Univ Oxford, Environm Change Inst, South Parks Rd, Oxford OX1 3QY, England.
EM lenafuldauer@gmail.com
RI Hall, Jim/ABF-1407-2020; Gall, Sarah/HTQ-1249-2023
OI Adshead, Daniel/0000-0002-0829-925X
FU UK Engineering and Physical Sciences Research Council [EP/R513295/1,
   EP/N509711/1, EP/N017064/1]; United Nations Office for Project Services
   (UNOPS); Ministry for the Environment, Science, Technology and
   Innovation (MESTI); Global Centre for Adaptation; EPSRC [EP/N017064/1]
   Funding Source: UKRI
FX The transferable python code to conduct the analysis can be requested
   from the corresponding author upon reasonable request. This research was
   conducted at the Environmental Change Institute at the University of
   Oxford and was supported by the UK Engineering and Physical Sciences
   Research Council by grants EP/R513295/1, EP/N509711/1, and EP/N017064/1
   as well as the United Nations Office for Project Services (UNOPS) . We
   thank the UNOPS team, the Ministry for the Environment, Science,
   Technology and Innovation (MESTI) , the Global Centre for Adaptation,
   and the Technical Working Group in Ghana for facilitating this research
   as well as all stakeholders consulted for providing valuable insights
   and useful data. We further wish to thank colleagues at the University
   of Oxford, in particular Nicholas Chow, Dr. Raghav Pant, and Tom Russel,
   as well as the reviewers and editors for providing valuable
   contributions to this project. We acknowledge the image courtesy of the
   United Nations Sustainable Development Goals: https://
   www.un.org/sustainabledevelopment. The content of this publication has
   not been approved by the United Nations and does not reflect the views
   of the United Nations or its officials or Member States.
CR Abubakari M., 2018, J HUMAN RESOURCE SUS, V06, P24, DOI [10.4236/jhrss.2018.61024, DOI 10.4236/JHRSS.2018.61024]
   Acheampong EN, 2014, CLIMATIC CHANGE, V126, P31, DOI 10.1007/s10584-014-1195-z
   Adshead D, 2021, EARTHS FUTURE, V9, DOI 10.1029/2020EF001699
   Adshead D, 2019, GLOBAL ENVIRON CHANG, V59, DOI 10.1016/j.gloenvcha.2019.101975
   Allen C, 2021, GLOB SUSTAIN, V4, DOI 10.1017/sus.2021.13
   Allen C, 2019, NAT SUSTAIN, V2, P1041, DOI 10.1038/s41893-019-0409-9
   Allen C, 2019, SUSTAIN SCI, V14, P421, DOI 10.1007/s11625-018-0596-8
   [Anonymous], 2021, NAT CLIM CHANGE, V11, P887, DOI 10.1038/s41558-021-01213-4
   [Anonymous], 2020, Nature-Based Solutions | Environment - Research and Innovation - European Commission
   [Anonymous], 2008, OECD Key Environmental Indicators 2008
   [Anonymous], 2015, GHAN 3 NAT COMM REP
   [Anonymous], 2022, GHANA RESILIENT INFR
   Antwi-Agyei P., 2020, GHANAS ADAPTATION ST
   Antwi-Agyei P, 2018, CLIM RISK MANAG, V19, P83, DOI 10.1016/j.crm.2017.11.003
   Antwi-Agyei P, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9112130
   Antwi-Agyei P, 2012, APPL GEOGR, V32, P324, DOI 10.1016/j.apgeog.2011.06.010
   Apuri I, 2018, ENVIRON DEV, V28, P32, DOI 10.1016/j.envdev.2018.09.002
   Asante FA, 2015, CLIMATE, V3, P78, DOI 10.3390/cli3010078
   Australian Curriculum AaRA, 2015, TECHNICAL REPORT
   Barnett J, 2010, GLOBAL ENVIRON CHANG, V20, P211, DOI 10.1016/j.gloenvcha.2009.11.004
   Beck MW, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-04568-z
   Biagini B, 2014, GLOBAL ENVIRON CHANG, V25, P97, DOI 10.1016/j.gloenvcha.2014.01.003
   Blicharska M, 2019, NAT SUSTAIN, V2, P1083, DOI 10.1038/s41893-019-0417-9
   Booysen F, 2002, SOC INDIC RES, V59, P115, DOI 10.1023/A:1016275505152
   Cairns G, 2013, TECHNOL FORECAST SOC, V80, P1, DOI 10.1016/j.techfore.2012.08.005
   Chausson A, 2020, GLOBAL CHANGE BIOL, V26, P6134, DOI 10.1111/gcb.15310
   Cohen-Shacham E., 2016, NATURE BASED SOLUTIO, V97, P2016
   Conway D, 2014, NAT CLIM CHANGE, V4, P339, DOI 10.1038/NCLIMATE2199
   Cutter SL, 2013, J FLOOD RISK MANAG, V6, P332, DOI 10.1111/jfr3.12018
   Cutter SL, 2003, SOC SCI QUART, V84, P242, DOI 10.1111/1540-6237.8402002
   Dovie B., 2015, GHANAS INTENDED NATI
   Environmental Protection Agency (EPA), 2020, GHAN 4 NAT COMM UN F
   Eriksen S, 2021, WORLD DEV, V141, DOI 10.1016/j.worlddev.2020.105383
   Eriksen S, 2011, CLIM DEV, V3, P7, DOI 10.3763/cdev.2010.0060
   European Environment Agency, 2021, NAT EM RED COMM DIR
   Fuldauer LI, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-31202-w
   Fuldauer LI, 2021, GLOBAL ENVIRON CHANG, V71, DOI 10.1016/j.gloenvcha.2021.102396
   Fuldauer LI, 2019, J CLEAN PROD, V223, P147, DOI 10.1016/j.jclepro.2019.02.269
   Gao Q., 2015, PART GLOBAL SECTORAL, P1101, DOI [10.1017/CBO9781107415379.025, DOI 10.1017/CBO9781107415379.025]
   Gomez-Echeverri L, 2018, PHILOS T R SOC A, V376, DOI 10.1098/rsta.2016.0444
   Greco S, 2019, SOC INDIC RES, V141, P61, DOI 10.1007/s11205-017-1832-9
   Hall JW, 2016, The future of national infrastructure: A System-of-Systems Approach
   Hall N, 2018, EUR J INT RELAT, V24, P540, DOI 10.1177/1354066117725157
   Hanson HI, 2020, LAND USE POLICY, V90, DOI 10.1016/j.landusepol.2019.104302
   Hardee K, 2010, MITIG ADAPT STRAT GL, V15, P113, DOI 10.1007/s11027-009-9208-3
   Hellmuth M., 2017, GHANA INTEGRATED RES
   Hickford AJ, 2015, FUTURES, V66, P13, DOI 10.1016/j.futures.2014.11.009
   Huizinga J., 2017, Publications Office, DOI DOI 10.2760/16510
   IPCC, 2018, GLOB WARM 1 5C SUMM
   Jafino BA, 2021, NAT CLIM CHANGE, V11, P394, DOI 10.1038/s41558-021-01030-9
   Khan M., 2020, USE SPATIAL INFORM N
   Kheradmand S, 2018, J HYDROL-REG STUD, V19, P1, DOI 10.1016/j.ejrh.2018.07.001
   Koks EE, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-10442-3
   Koks EE, 2015, ENVIRON SCI POLICY, V47, P42, DOI 10.1016/j.envsci.2014.10.013
   Lafortune G., 2018, SDG Index and Dashboards Detailed Methodological paper
   Lawson ET, 2020, GEOJOURNAL, V85, P439, DOI 10.1007/s10708-019-09974-4
   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
   Liu JG, 2015, SCIENCE, V347, DOI 10.1126/science.1258832
   Liu ZM, 2019, NAT CLIM CHANGE, V9, P494, DOI 10.1038/s41558-019-0519-4
   Magnan AK, 2016, SCIENCE, V352, P1280, DOI 10.1126/science.aaf5002
   Malhi Y, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0104
   Martín EG, 2020, SCI TOTAL ENVIRON, V738, DOI 10.1016/j.scitotenv.2020.139693
   McSweeney C., 2012, UNDP Climate Change Country Profiles: Senegal
   Menéndez P, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-61136-6
   Meyer V, 2013, NAT HAZARD EARTH SYS, V13, P1351, DOI 10.5194/nhess-13-1351-2013
   Miola A, 2019, ECOL ECON, V164, DOI 10.1016/j.ecolecon.2019.106373
   Morgan EA, 2019, ENVIRON SCI POLICY, V93, P208, DOI 10.1016/j.envsci.2018.10.012
   Nalau J, 2021, CLIM RISK MANAG, V32, DOI 10.1016/j.crm.2021.100290
   NDPC, 2019, GHANA INFRASTRUCTURE, V1
   Nerini FF, 2019, NAT SUSTAIN, V2, P674, DOI 10.1038/s41893-019-0334-y
   Noble I. R., 2014, Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, P833, DOI 10.1017/cbo9781107415379.019
   Noble IR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P833
   OECD, 2019, MEAS DIST SDG TARG 2, DOI DOI 10.1787/A8CAF3FA-EN
   Otto A, 2016, IEEE SYST J, V10, P385, DOI 10.1109/JSYST.2014.2361157
   Owen G, 2020, GLOBAL ENVIRON CHANG, V62, DOI 10.1016/j.gloenvcha.2020.102071
   Owusu M, 2019, CLIM DEV, V11, P687, DOI 10.1080/17565529.2018.1532870
   Pant R, 2018, J FLOOD RISK MANAG, V11, P22, DOI 10.1111/jfr3.12288
   Prakash M, 2017, ACHIEVING SUSTAINABL, DOI DOI 10.13140/RG.2.2.25012.09601
   Raymond C, 2020, NAT CLIM CHANGE, V10, P611, DOI 10.1038/s41558-020-0790-4
   Reichstein M, 2021, NATURE, V592, P347, DOI 10.1038/d41586-021-00927-x
   Schipper ELF, 2020, ONE EARTH, V3, P409, DOI 10.1016/j.oneear.2020.09.014
   Schipper ELF, 2016, INT J DISASTER RESIL, V7, P216, DOI 10.1108/IJDRBE-03-2015-0014
   Schmidt-Traub G, 2017, NAT GEOSCI, V10, P547, DOI 10.1038/NGEO2985
   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
   Shukla P.R., 2019, Special Report on climate change and land
   Singh C, 2020, CLIMATIC CHANGE, V162, P255, DOI 10.1007/s10584-020-02762-x
   Termeer C, 2012, EUR POLIT SCI, V11, P41, DOI 10.1057/eps.2011.7
   Thacker S, 2019, NAT SUSTAIN, V2, P324, DOI 10.1038/s41893-019-0256-8
   Thacker S, 2018, RISK ANAL, V38, P134, DOI 10.1111/risa.12839
   Thacker S, 2017, RISK ANAL, V37, P2490, DOI 10.1111/risa.12840
   Thacker S, 2017, RELIAB ENG SYST SAFE, V167, P30, DOI 10.1016/j.ress.2017.04.023
   Tompkins EL, 2018, WIRES CLIM CHANGE, V9, DOI 10.1002/wcc.545
   Tompkins EL, 2012, GLOBAL ENVIRON CHANG, V22, P3, DOI 10.1016/j.gloenvcha.2011.09.010
   UNEP, NATURE BASED SOLUTIO
   Verschuur J, 2020, GLOBAL ENVIRON CHANG, V65, DOI 10.1016/j.gloenvcha.2020.102179
   Ward P. J, 2020, Tech. rep
   Ward PJ, 2017, NAT CLIM CHANGE, V7, P642, DOI [10.1038/nclimate3350, 10.1038/NCLIMATE3350]
   Williams PA, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/ac092d
   Winsemius HC, 2016, NAT CLIM CHANGE, V6, P381, DOI [10.1038/nclimate2893, 10.1038/NCLIMATE2893]
   Wood SLR, 2018, ECOSYST SERV, V29, P70, DOI 10.1016/j.ecoser.2017.10.010
   Xu ZC, 2020, NATURE, V577, P74, DOI 10.1038/s41586-019-1846-3
   Zscheischler J, 2018, NAT CLIM CHANGE, V8, P469, DOI 10.1038/s41558-018-0156-3
NR 103
TC 11
Z9 11
U1 4
U2 25
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 SEP
PY 2022
VL 76
AR 102575
DI 10.1016/j.gloenvcha.2022.102575
EA AUG 2022
PG 16
WC Environmental Sciences; Environmental Studies; Geography
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geography
GA 3Z4SX
UT WOS:000844408100003
OA hybrid
DA 2025-01-10
ER

PT J
AU Baumgart, L
   Wittke, M
   Morsbach, S
   Abou, B
   Menzel, F
AF Baumgart, Lucas
   Wittke, Marti
   Morsbach, Svenja
   Abou, Berengere
   Menzel, Florian
TI Why do ants differ in acclimatory ability? Biophysical mechanisms behind
   cuticular hydrocarbon acclimation across species
SO JOURNAL OF EXPERIMENTAL BIOLOGY
LA English
DT Article
DE Climate adaptation; Cuticular hydrocarbons; Ecological niche breadth;
   Phase behaviour; Microrheology; Drought tolerance
ID LIPID-COMPOSITION; EVOLUTION; INSECTS; ECOLOGY; PERMEABILITY;
   HYMENOPTERA; PATTERNS; BEETLE
AB Maintaining water balance is vital for terrestrial organisms. Insects protect themselves against desiccation via cuticular hydrocarbons (CHCs). CHC layers are complex mixtures of solid and liquid hydrocarbons, with a surprisingly diverse composition across species. This variation may translate into differential phase behaviour, and hence varying waterproofing capacity. This is especially relevant when temperatures change, which requires acclimatory CHC changes to maintain waterproofing. Nevertheless, the physical consequences of CHC variation are still little understood. We studied acclimatory responses and their consequences for CHC composition, phase behaviour and drought survival in three congeneric ant species. Colony sub-groups were kept under cool, warm and fluctuating temperature regimes. Lasius niger and Lasius platythorax, both of which are rich in methyl-branched alkanes, showed largely predictable acclimatory changes of the CHC profile. In both species, warm acclimation increased drought resistance. Warm acclimation increased the proportion of solid compounds in L. niger but not in L. platythorax. In both species, the CHC layer formed a liquid matrix of constantly low viscosity, which contained highly viscous and solid parts. This phase heterogeneity may be adaptive, increasing robustness to temperature fluctuations. In Lasius brunneus, which is rich in unsaturated hydrocarbons, acclimatory CHC changes were less predictable, and warm acclimation did not enhance drought survival. The CHC layer was more homogeneous, but matrix viscosity changed with acclimation. We showed that ant species use different physical mechanisms to enhance waterproofing during acclimation. Hence, the ability to acclimate, and thus climatic niche breadth, may strongly depend on species-specific CHC profile.
C1 [Baumgart, Lucas; Wittke, Marti; Menzel, Florian] Johannes Gutenberg Univ Mainz, Inst Organism & Mol Evolut IomE, Hanns Dieter Husch Weg 15, D-55128 Mainz, Germany.
   [Baumgart, Lucas] Rhein Westfal TH Aachen, Inst Biol 2, Worringerweg 2, D-52074 Aachen, Germany.
   [Baumgart, Lucas; Abou, Berengere] Univ Paris, Matiere & Syst Complexes MSC, UMR CNRS 7057, F-75205 Paris 13, France.
   [Morsbach, Svenja] Max Planck Inst Polymer Res, Ackermannweg 10, D-55128 Mainz, Germany.
C3 Johannes Gutenberg University of Mainz; RWTH Aachen University;
   Universite Paris Cite; Centre National de la Recherche Scientifique
   (CNRS); Max Planck Society
RP Menzel, F (corresponding author), Johannes Gutenberg Univ Mainz, Inst Organism & Mol Evolut IomE, Hanns Dieter Husch Weg 15, D-55128 Mainz, Germany.
EM menzelf@uni-mainz.de
RI Menzel, Florian/H-2436-2017; Morsbach, Svenja/O-9082-2016
OI Menzel, Florian/0000-0002-9673-3668; Morsbach,
   Svenja/0000-0001-9662-8190; Baumgart, Lucas/0000-0003-1006-0659
FU Heisenberg fellowship of the Deutsche Forschungsgemeinschaft (DFG)
   [3842/6-1]; Deutscher Akademischer Austauschdienst (DAAD) [57388961];
   Bundesministerium fur Bildung und Forschung; PHC Procope [40427NM];
   Ministe`re de l'Europe et des Affaires etrangeres (MEAE); Ministere de
   l'Enseignement Superieur, de la Recherche et de l'Innovation (MESRI)
FX This study was funded by a Heisenberg fellowship of the Deutsche
   Forschungsgemeinschaft (DFG) to F.M. (grant no. M.E. 3842/6-1).
   Furthermore, it was supported by the Deutscher Akademischer
   Austauschdienst (DAAD, PPP Procope France, project ID: 57388961, to
   F.M.) with funds from the Bundesministerium fur Bildung und Forschung.
   B.A. was supported by PHC Procope 2018 (project ID: 40427NM) with funds
   from Ministe`re de l'Europe et des Affaires etrangeres (MEAE) and
   Ministere de l'Enseignement Superieur, de la Recherche et de
   l'Innovation (MESRI).
CR Abou B, 2010, J R SOC INTERFACE, V7, P1745, DOI 10.1098/rsif.2010.0075
   Blomquist GJ, 2021, ANNU REV ENTOMOL, V66, P45, DOI 10.1146/annurev-ento-031620-071754
   Blomquist GJ, 2010, INSECT HYDROCARBONS: BIOLOGY, BIOCHEMISTRY, AND CHEMICAL ECOLOGY, P3, DOI 10.1017/CBO9780511711909.002
   Blomquist GJ, 2010, INSECT HYDROCARBONS: BIOLOGY, BIOCHEMISTRY, AND CHEMICAL ECOLOGY, P19, DOI 10.1017/CBO9780511711909.003
   Buellesbach J, 2018, J CHEM ECOL, V44, P1101, DOI 10.1007/s10886-018-1029-y
   Carlson DA, 1998, J CHEM ECOL, V24, P1845, DOI 10.1023/A:1022311701355
   Chown SL, 2007, P ROY SOC B-BIOL SCI, V274, P2531, DOI 10.1098/rspb.2007.0772
   Chown SL, 2011, J INSECT PHYSIOL, V57, P1070, DOI 10.1016/j.jinsphys.2011.05.004
   Colinet H, 2015, ANNU REV ENTOMOL, V60, P123, DOI 10.1146/annurev-ento-010814-021017
   Cooper R, 2009, J TRIBOL-T ASME, V131, DOI 10.1115/1.3002327
   De Guzman J., 1913, Anales de la Sociedad Espanola de Fisica y Quimica., V11, P353
   Drechsler P, 2006, J COMP PHYSIOL A, V192, P1213, DOI 10.1007/s00359-006-0150-5
   Einstein A, 1905, ANN PHYS-BERLIN, V17, P549, DOI 10.1002/andp.19053220806
   Eyring H, 1935, J CHEM PHYS, V3, P107, DOI 10.1063/1.1749604
   FERLONI P, 1971, Z NATURFORSCH PT A, VA 26, P1713
   Ferveur JF, 2010, INSECT HYDROCARBONS: BIOLOGY, BIOCHEMISTRY, AND CHEMICAL ECOLOGY, P325, DOI 10.1017/CBO9780511711909.016
   GIBBS A, 1991, P NATL ACAD SCI USA, V88, P7257, DOI 10.1073/pnas.88.16.7257
   GIBBS A, 1995, COMP BIOCHEM PHYS B, V112, P243, DOI 10.1016/0305-0491(95)00081-X
   GIBBS A, 1994, PHYSIOL ZOOL, V67, P1523, DOI 10.1086/physzool.67.6.30163910
   Gibbs AG, 1998, AM ZOOL, V38, P471
   Gibbs AG, 2002, J INSECT PHYSIOL, V48, P391, DOI 10.1016/S0022-1910(02)00059-8
   Gibbs AG, 1997, J EXP BIOL, V200, P1821
   Gibbs AG, 2010, INSECT HYDROCARBONS: BIOLOGY, BIOCHEMISTRY, AND CHEMICAL ECOLOGY, P100, DOI 10.1017/CBO9780511711909.007
   Gold V., 2019, Compendium of Chemical Terminology, DOI [DOI 10.1351/GOLDBOOK, 10.1351/goldbook]
   HADLEY NF, 1977, INSECT BIOCHEM, V7, P277, DOI 10.1016/0020-1790(77)90025-7
   Hartke J, 2019, ECOL EVOL, V9, P9160, DOI 10.1002/ece3.5464
   Kather R, 2015, J CHEM ECOL, V41, P871, DOI 10.1007/s10886-015-0631-5
   Kather R, 2012, PHYSIOL ENTOMOL, V37, P25, DOI 10.1111/j.1365-3032.2011.00826.x
   Kellermann V, 2012, EVOLUTION, V66, P3377, DOI 10.1111/j.1558-5646.2012.01685.x
   Krupp JJ, 2020, J INSECT PHYSIOL, V121, DOI 10.1016/j.jinsphys.2019.103990
   Leonhardt SD, 2016, CELL, V164, P1277, DOI 10.1016/j.cell.2016.01.035
   Lide D. R., 2004, Handbook of chemistry and physics, V84th
   MARONCELLI M, 1982, J AM CHEM SOC, V104, P6237, DOI 10.1021/ja00387a013
   Martin SJ, 2008, BIOL J LINN SOC, V95, P131, DOI 10.1111/j.1095-8312.2008.01038.x
   McGill BJ, 2006, TRENDS ECOL EVOL, V21, P178, DOI 10.1016/j.tree.2006.02.002
   Menzel F., 2022, **DATA OBJECT**, DOI 10.5061/dryad.k98sf7m8n
   Menzel F, 2019, J EXP BIOL, V222, DOI 10.1242/jeb.210807
   Menzel F, 2018, FUNCT ECOL, V32, P657, DOI 10.1111/1365-2435.13008
   Menzel F, 2017, P ROY SOC B-BIOL SCI, V284, DOI 10.1098/rspb.2016.1727
   Michelutti KB, 2018, J THERM BIOL, V71, P221, DOI 10.1016/j.jtherbio.2017.11.019
   Pokorny T, 2014, APIDOLOGIE, V45, P276, DOI 10.1007/s13592-013-0250-5
   Rajpurohit S, 2017, J EVOLUTION BIOL, V30, P66, DOI 10.1111/jeb.12988
   Seifert Bernhard, 2008, P157
   Spicer ME, 2017, OECOLOGIA, V183, P1007, DOI 10.1007/s00442-017-3825-4
   Sprenger PP, 2020, MYRMECOL NEWS, V30, P1, DOI 10.25849/myrmecol.news_030:001
   Sprenger PP, 2018, J EXP BIOL, V221, DOI 10.1242/jeb.171488
   Steiger Sandra, 2014, Insects, V5, P423, DOI 10.3390/insects5020423
   TOOLSON EC, 1979, J COMP PHYSIOL, V129, P319, DOI 10.1007/BF00686988
   van Wilgenburg E, 2011, J EVOLUTION BIOL, V24, P1188, DOI 10.1111/j.1420-9101.2011.02248.x
   Wang YW, 2021, BIOL REV, V96, P1421, DOI 10.1111/brv.12709
   Wittke M, 2022, FUNCT ECOL, V36, P1973, DOI 10.1111/1365-2435.14104
NR 51
TC 5
Z9 5
U1 1
U2 10
PU COMPANY BIOLOGISTS LTD
PI CAMBRIDGE
PA BIDDER BUILDING, STATION RD, HISTON, CAMBRIDGE CB24 9LF, ENGLAND
SN 0022-0949
EI 1477-9145
J9 J EXP BIOL
JI J. Exp. Biol.
PD AUG
PY 2022
VL 225
IS 16
AR jeb243847
DI 10.1242/jeb.243847
PG 15
WC Biology; Zoology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Life Sciences & Biomedicine - Other Topics; Zoology
GA 4H1JR
UT WOS:000849639200005
PM 35775442
OA Bronze
DA 2025-01-10
ER

PT J
AU Feng, X
   Prates, LL
   Espinosa, MER
   Peng, QH
   Zhang, HH
   Zhang, WX
   Yu, PQ
AF Feng, Xin
   Prates, Luciana L.
   Espinosa, Maria E. Rodriguez
   Peng, Quanhui
   Zhang, Huihua
   Zhang, Weixian
   Yu, Peiqiang
TI Dry heating, moist heating, and microwave irradiation of
   cold-climate-adapted barley grain-Effects on ruminant-relevant
   carbohydrate and molecular structural spectral profiles
SO JOURNAL OF ANIMAL PHYSIOLOGY AND ANIMAL NUTRITION
LA English
DT Article
DE molecular structure; nutrient utilization and availability; vibrational
   spectroscopy (ATR-FTIR)
ID CORNELL NET CARBOHYDRATE; PROTEIN SYSTEM; INTESTINAL DIGESTION;
   NITROGEN-METABOLISM; STARCH DEGRADATION; DAIRY-COWS; MODEL;
   DIGESTIBILITY; PERFORMANCE; SORGHUM
AB Different feed processing techniques affect barley digestibility and nutrient utilization in ruminants. To our knowledge, there are few studies on the interactive relationship between carbohydrate molecular structure profiles of cool-season-adapted barley grain and nutritional characteristics for ruminants. The objectives of this study were: (1) to investigate the effect of different technological processing methods on carbohydrate chemical profiles, Cornell Net Carbohydrate and Protein System-carbohydrate subfractions, ruminal and intestinal carbohydrate digestion of barley grain in dairy cows; (2) to study the effect of heat processing on carbohydrate molecular structure of barley grain using advanced molecular spectroscopy; and (3) to associate processing-induced changes in carbohydrate molecular structure with changes in carbohydrate metabolic profiles in dairy cows. Barley grain samples collected from Crop Research Field in Western Canada underwent four different processing treatments: control, dry heating (120 degrees C for 60 min in an air-ventilated oven), moist heating (120 degrees C for 60 min in an autoclave), and microwave irradiation (900 W and 2450 MHz for 5 min in a microwave). The heating conditions used in the current study induced some changes in rumen-degradable and -undegradable digestible fibre (CB3) fraction. Intestinally digestible CB3 was decreased after moist heating. Moist heating decreased starch digestibility compared to the other three treatments. The processing-induced carbohydrate molecular structure changes, which was revealed by advanced vibrational molecular spectroscopic technique (attenuated total reflectance-Fourier transform infrared), could be used to predict carbohydrate nutritional value.
C1 [Feng, Xin; Prates, Luciana L.; Espinosa, Maria E. Rodriguez; Yu, Peiqiang] Univ Saskatchewan, Coll Agr & Bioresources, Dept Anim & Poultry Sci, Saskatoon, SK, Canada.
   [Feng, Xin; Zhang, Huihua] Foshan Univ, Sch Life Sci & Engn, Foshan, Peoples R China.
   [Peng, Quanhui] Sichuan Agr Univ, Anim Nutr Inst, Yaan, Sichuan, Peoples R China.
   [Zhang, Weixian] Henan Univ Anim Husb & Econ, Zhengzhou, Peoples R China.
C3 University of Saskatchewan; Foshan University; Sichuan Agricultural
   University; Henan University of Animal Husbandry & Economy
RP Zhang, WX (corresponding author), Henan Univ Anim Husb & Econ, Zhengzhou, Peoples R China.; Yu, PQ (corresponding author), Univ Saskatchewan, Coll Agr & Bioresources, 6D10 Agr Bldg,51 Campus Dr, Saskatoon, SK S7N 5A8, Canada.
EM zhangwx126@126.com; peiqiang.yu@usask.ca
RI Zhang, Huihua/HJY-0843-2023
FU Ministry of Agriculture Strategic Research Chair Programme; SaskMilk;
   Natural Sciences and Engineering Research Council of Canada
FX Ministry of Agriculture Strategic Research Chair Programme; SaskMilk;
   Natural Sciences and Engineering Research Council of Canada
CR AMTS, 2010, AGR MOD TRAIN SYST
   [Anonymous], 2001, Nutrient requirements of dairy cattle, V7th, P381
   AOAC, 2016, Official Methods of Analysis of the AOAC
   Aoac, 1995, Agricultural chemicals, contaminants, drugs, Vsixteenth
   Azarfar A, 2008, J SCI FOOD AGR, V88, P1380, DOI 10.1002/jsfa.3228
   CALSAMIGLIA S, 1995, J ANIM SCI, V73, P1459
   CCAC, 2009, CANADIAN COUNCIL ANI
   Dehghan-Banadaky M, 2007, ANIM FEED SCI TECH, V137, P1, DOI 10.1016/j.anifeedsci.2006.11.021
   Espinosa MER, 2020, ANIM FEED SCI TECH, V269, DOI 10.1016/j.anifeedsci.2020.114681
   Fox DG, 2004, ANIM FEED SCI TECH, V112, P29, DOI 10.1016/j.anifeedsci.2003.10.006
   FRANCO CML, 1995, STARCH-STARKE, V47, P223, DOI 10.1002/star.19950470607
   García M, 2008, POULTRY SCI, V87, P940, DOI 10.3382/ps.2007-00266
   Gozho GN, 2008, J DAIRY SCI, V91, P247, DOI 10.3168/jds.2007-0407
   Higgs RJ, 2015, J DAIRY SCI, V98, P6340, DOI 10.3168/jds.2015-9379
   Jonker A, 2012, GRASS FORAGE SCI, V67, P369, DOI 10.1111/j.1365-2494.2012.00853.x
   Khan NA, 2015, J AGR FOOD CHEM, V63, P1057, DOI 10.1021/jf503575y
   Kiran D, 2007, J ANIM SCI, V85, P3391, DOI 10.2527/jas.2007-0081
   Lanzas C, 2008, J DAIRY SCI, V91, P4881, DOI 10.3168/jds.2008-1440
   Lazaridou A., 2014, Bioactive Carbohydrates and Dietary Fibre, V4, P58
   Ljokjel K, 2003, ANIM FEED SCI TECH, V107, P105, DOI 10.1016/S0377-8401(03)00122-6
   McCleary BV, 1997, J AOAC INT, V80, P571
   McKinnon JJ, 1995, ANIM FEED SCI TECH, V56, P243, DOI 10.1016/0377-8401(95)00828-4
   Mertens DR, 2002, J AOAC INT, V85, P1217
   Nuez-Ortín WG, 2010, J DAIRY SCI, V93, P3775, DOI 10.3168/jds.2010-3143
   Nuez-Ortín WG, 2010, J SCI FOOD AGR, V90, P2058, DOI 10.1002/jsfa.4052
   Prates LL, 2018, J CEREAL SCI, V80, P212, DOI 10.1016/j.jcs.2018.01.008
   Richards CJ, 2007, VET CLIN N AM-FOOD A, V23, P207, DOI 10.1016/j.cvfa.2007.05.006
   ROONEY LW, 1986, J ANIM SCI, V63, P1607, DOI 10.2527/jas1986.6351607x
   Sadeghi AA, 2008, ANIM FEED SCI TECH, V141, P184, DOI 10.1016/j.anifeedsci.2007.05.034
   SNIFFEN CJ, 1992, J ANIM SCI, V70, P3562, DOI 10.2527/1992.70113562x
   Sun BL, 2018, SPECTROCHIM ACTA A, V201, P8, DOI 10.1016/j.saa.2018.04.036
   Tosta MR, 2022, CRIT REV FOOD SCI, V62, P5130, DOI 10.1080/10408398.2021.1882380
   Tothi R, 2003, ANIM FEED SCI TECH, V104, P71, DOI 10.1016/S0377-8401(02)00292-4
   Tylutki TP, 2008, ANIM FEED SCI TECH, V143, P174, DOI 10.1016/j.anifeedsci.2007.05.010
   Van Amburgh ME, 2015, J DAIRY SCI, V98, P6361, DOI 10.3168/jds.2015-9378
   Walde SG, 2002, J FOOD ENG, V55, P271, DOI 10.1016/S0260-8774(02)00101-2
   WEISS WP, 1992, ANIM FEED SCI TECH, V39, P95, DOI 10.1016/0377-8401(92)90034-4
   Xin HS, 2021, ANIM FEED SCI TECH, V276, DOI 10.1016/j.anifeedsci.2021.114903
   Yang WZ, 2000, J DAIRY SCI, V83, P554, DOI 10.3168/jds.S0022-0302(00)74915-0
   Zinn RA, 2002, J ANIM SCI, V80, P1145
NR 40
TC 3
Z9 3
U1 0
U2 9
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0931-2439
EI 1439-0396
J9 J ANIM PHYSIOL AN N
JI J. Anim. Physiol. Anim. Nutr.
PD JAN
PY 2023
VL 107
IS 1
BP 113
EP 120
DI 10.1111/jpn.13708
EA MAR 2022
PG 8
WC Agriculture, Dairy & Animal Science; Veterinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Veterinary Sciences
GA 7P7GR
UT WOS:000774835200001
PM 35352398
DA 2025-01-10
ER

PT J
AU Xiao, X
   Seekamp, E
   Lu, JY
   Eaton, M
   van der Burg, MP
AF Xiao, Xiao
   Seekamp, Erin
   Lu, Junyu
   Eaton, Mitchell
   van der Burg, Max Post
TI Optimizing preservation for multiple types of historic structures under
   climate change
SO LANDSCAPE AND URBAN PLANNING
LA English
DT Article
DE Climate change; Adaptation planning; Historic preservation; National
   park; Decision support tool
ID ARCHAEOLOGICAL SITES; CULTURAL RESOURCES; CHANGE ADAPTATION; HERITAGE;
   VULNERABILITY; IMPACTS; MITIGATION; SUPPORT; MODEL; RISK
AB Cultural resources in coastal parks and recreation areas are vulnerable to climate change. The US National Park Service (NPS) is facing the challenge of insufficient budget allocations for both maintenance and climate adaptation of historic structures. Research on adaptation planning for cultural resources has predominately focused on vulnerability assessments of heritage sites; however, few studies integrate multiple factors (e.g., vulnerability, cultural significance, use potential, and costs) that managers should consider when making tradeoff decisions about which cultural resources to prioritize for adaptation. Moreover, heritage sites typically include multiple types of cultural resources, and researchers have yet to examine such complex tradeoffs. This study applies the Optimal Preservation (OptiPres) Model as a decision support framework to evaluate the tradeoffs of adaptation actions among multiple types of historic structures-wooden buildings, masonry and concrete buildings, forts, and batteries-under varying budget scenarios. Results suggest that the resource values of different types of historic structures vary greatly under a range of budget scenarios, and tradeoffs have to be made among different types of historical structures to achieve optimal planning objectives. Moreover, periodic, incremental funding and partial maintenance are identified as optimal funding strategies for preservation needs of cost-intensive historic structures. Also, adaptative use of historical buildings (e.g., building occupancy) can improve the resource values when budgets are constrained. The OptiPres Model provides managers with a unique framework to inform adaptation planning efforts for a broad range of historic structures, which is transferable across coastal parks to enhance historic preservation planning under climate change.
C1 [Xiao, Xiao; Lu, Junyu] Arizona State Univ, Sch Community Resources & Dev, 411 N Cent Ave,Suite 550, Phoenix, AZ 85004 USA.
   [Xiao, Xiao; Lu, Junyu] Hainan Univ, Hainan Univ Arizona State Univ Joint Int Tourism, 58 Remin Rd, Haikou 570004, Hainan, Peoples R China.
   [Seekamp, Erin] North Carolina State Univ, Dept Pk Recreat & Tourism Management, Box 8004,Biltmore Hall, Raleigh, NC 27695 USA.
   [Eaton, Mitchell] US Geol Survey, Southeast Climate Adaptat Sci Ctr, 127H David Clark Labs, Raleigh, NC 27695 USA.
   [van der Burg, Max Post] US Geol Survey, Northern Prairie Wildlife Res Ctr, 8711 37th St SE, Jamestown, ND 58401 USA.
C3 Arizona State University; Arizona State University-Downtown Phoenix;
   Hainan University; North Carolina State University; United States
   Department of the Interior; United States Geological Survey; United
   States Department of the Interior; United States Geological Survey
RP Xiao, X (corresponding author), Arizona State Univ, Sch Community Resources & Dev, 411 N Cent Ave,Suite 550, Phoenix, AZ 85004 USA.; Xiao, X (corresponding author), Hainan Univ, Hainan Univ Arizona State Univ Joint Int Tourism, 58 Remin Rd, Haikou 570004, Hainan, Peoples R China.
EM xiao.xiao.7@asu.edu; elseekam@ncsu.edu; junyulu@asu.edu;
   mitchell.eaton@usgs.gov; maxpostvanderburg@usgs.gov
RI Xiao, Xiao/Z-1199-2019; Eaton, Mitch/HKW-4534-2023; Lu,
   Junyu/JDC-5021-2023
OI Xiao, Xiao/0000-0001-5124-0985; Eaton, Mitchell/0000-0001-7324-6333;
   Seekamp, Erin/0000-0001-5082-1921
FU National Park Service Climate Change Response Program through U.S.
   Department of Interior Inter-Agency Agreement [P17AC00794]; U.S.
   Geological Survey through Southeast Climate Adaptation Science Center
   [G19AP00042]
FX The research presented in this paper was supported by the National Park
   Service Climate Change Response Program through U.S. Department of
   Interior Inter-Agency Agreement P17AC00794 (project title: Assessing the
   transferability of a historic resources decision support model for
   optimized budget allocation and adaptation planning). Additional funding
   for model development was provided by the U.S. Geological Survey
   (https://www.usgs.gov) through Southeast Climate Adaptation Science
   Center (https://globalchange.ncsu.edu/secsc/) through grant agreement
   G19AP00042 (project title: Enhancing cultural resource adaptation
   planning in dynamic environments and assessing sediment budget research
   and information needs at Gulf Islands National Seashore).
CR Adger WN, 2005, GLOBAL ENVIRON CHANG, V15, P77, DOI [10.1016/j.gloenvcha.2005.03.001, 10.1016/j.gloenvcha.2004.12.005]
   Andelman, 2000, MATH METHODS IDENTIF
   Anderson DG, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0188142
   [Anonymous], 2014, 1402 NPS
   Aplet GH, 2017, ECOSYST HEALTH SUST, V3, DOI 10.1002/ehs2.1261
   Arsenault R, 2014, J HYDROL ENG, V19, P1374, DOI 10.1061/(ASCE)HE.1943-5584.0000938
   Bonan GB, 2008, SCIENCE, V320, P1444, DOI 10.1126/science.1155121
   Borges P, 2014, EUR J OPER RES, V233, P700, DOI 10.1016/j.ejor.2013.08.039
   Borrelli M., 2008, SOLUTIONS COASTAL DI
   Butchart SHM, 2010, SCIENCE, V328, P1164, DOI 10.1126/science.1187512
   Caffery M. A., 2018, SEA LEVEL RISE STORM
   Carmichael B, 2015, RANGELAND J, V37, P597, DOI 10.1071/RJ15048
   Casey A, 2019, COAST MANAGE, V47, P169, DOI 10.1080/08920753.2019.1564952
   Daly C, 2014, CONSERV MANAGE ARCHA, V16, P268, DOI 10.1179/1350503315Z.00000000086
   Davis CM, 2018, ADV GLOB CHANGE RES, V63, P209, DOI 10.1007/978-3-319-56928-4_11
   Eaton MJ, 2019, ECOL APPL, V29, DOI 10.1002/eap.1962
   Fatoric S, 2018, J CULT HERIT, V30, P168, DOI 10.1016/j.culher.2017.08.006
   Fatoric S, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9112143
   Fatoric S, 2017, LAND USE POLICY, V68, P254, DOI 10.1016/j.landusepol.2017.07.052
   Fatoric S, 2017, CLIMATIC CHANGE, V142, P227, DOI 10.1007/s10584-017-1929-9
   Godschalk DR, 2003, NAT HAZARDS REV, V4, P136, DOI 10.1061/(ASCE)1527-6988(2003)4:3(136)
   Hambrecht G, 2017, AM ANTIQUITY, V82, P627, DOI 10.1017/aaq.2017.30
   Huijbregts Z, 2012, BUILD ENVIRON, V55, P43, DOI 10.1016/j.buildenv.2012.01.008
   Johnson ChristopherF., 2020, PARKS STEWARDSHIP FO, V36, P49, DOI [10.5070/p536146396, DOI 10.5070/P536146396]
   KEENEY RL, 1982, OPER RES, V30, P803, DOI 10.1287/opre.30.5.803
   Klein RJT, 2007, CLIMATIC CHANGE, V84, P23, DOI 10.1007/s10584-007-9268-x
   Laurenzi A, 2013, ADV ARCHAEOL PRACT, V1, P61, DOI 10.7183/2326-3768.1.2.61
   Laurikka H, 2003, GLOBAL ENVIRON CHANG, V13, P207, DOI 10.1016/S0959-3780(03)00048-7
   Leissner J, 2015, HERIT SCI, V3, DOI 10.1186/s40494-015-0067-9
   Lockwood M, 2010, SOC NATUR RESOUR, V23, P986, DOI 10.1080/08941920802178214
   Marzeion B, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/3/034001
   Nocca F, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9101882
   O'Brien G, 2015, J CULT HERIT MANAG S, V5, P99, DOI 10.1108/JCHMSD-06-2013-0021
   Peek K., 2017, ADAPTING CLIMATE CHA
   Peterson GD, 2003, CONSERV BIOL, V17, P358, DOI 10.1046/j.1523-1739.2003.01491.x
   Reeder-Myers LA, 2019, AM ANTIQUITY, V84, P292, DOI 10.1017/aaq.2018.85
   Reeder-Myers LA, 2015, J ISL COAST ARCHAEOL, V10, P436, DOI 10.1080/15564894.2015.1008074
   Rockman M, 2020, P NATL ACAD SCI USA, V117, P8295, DOI 10.1073/pnas.1914213117
   Rockman Marcy., 2016, CULTURAL RESOURCES C
   Rowland E.R., 2016, Considering Multiple Futures: Scenario Planning to Address Uncertainty in Natural Resource Conservation
   Runyon AN, 2020, Parks Stewardship Forum, V36, DOI [10.5070/p536146402, DOI 10.5070/P536146402]
   Sandsmark M, 2007, ENVIRON RESOUR ECON, V37, P681, DOI 10.1007/s10640-006-9049-4
   Seekamp E., 2019, OPTIMIZING HIST PRES
   Sofaer HR, 2017, GLOBAL CHANGE BIOL, V23, P2537, DOI 10.1111/gcb.13653
   St Amand A, 2020, NAT HAZARDS, V103, P1761, DOI 10.1007/s11069-020-04053-1
   Star J, 2016, CLIM RISK MANAG, V13, P88, DOI 10.1016/j.crm.2016.08.001
   Vecco M, 2010, J CULT HERIT, V11, P321, DOI 10.1016/j.culher.2010.01.006
   Vieira J, 2017, WATER RESOUR MANAG, V31, P1381, DOI 10.1007/s11269-017-1584-y
   Vörösmarty CJ, 2000, SCIENCE, V289, P284, DOI 10.1126/science.289.5477.284
   Westley K, 2019, J ISL COAST ARCHAEOL, V14, P226, DOI 10.1080/15564894.2018.1435592
   Westphal MI, 2007, LANDSCAPE URBAN PLAN, V81, P56, DOI 10.1016/j.landurbplan.2006.10.015
   Woosnam KM, 2014, TOURISM GEOGR, V16, P364, DOI 10.1080/14616688.2013.823235
   Xiao X, 2019, LAND USE POLICY, V83, P379, DOI 10.1016/j.landusepol.2019.02.011
NR 53
TC 11
Z9 11
U1 10
U2 22
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 OCT
PY 2021
VL 214
AR 104165
DI 10.1016/j.landurbplan.2021.104165
PG 14
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 TU6CS
UT WOS:000681122700007
OA Bronze
DA 2025-01-10
ER

PT J
AU Jacobs, KL
   Street, RB
AF Jacobs, Katharine L.
   Street, Roger Brian
TI The next generation of climate services
SO CLIMATE SERVICES
LA English
DT Article
DE Climate services; Climate adaptation networks; Transformational
   capability; Network capability
ID SCIENCE; ADAPTATION; INFORMATION; KNOWLEDGE; FORECASTS; COPRODUCTION;
   MANAGERS; POLICY
AB Climate services have advanced significantly, evolving from primarily supply-side, top-down, one-size-fits-all approaches to a recognition of the need to support a unique and evolving community of decision makers and decision contexts. However, investments in climate services have not kept pace with the increasing need for evidence-based actions, and the need for "trusted relationships" between consumers and producers of those services may actually be slowing progress at a time when there is an increasing need to scale up from individual decisions to system-wide adaptation and resilience. In the meantime, recognition of the linkages between adaptation actions and the broader sustainable development agenda require an expansion of the concept of climate services from its historically narrow focus on the use of climate science for impact assessments and adaptation to that required to deliver a broader set of societal benefits based on increasing capacity to manage climate and other risks. A "next generation approach" is justified by the complexity and inter-relatedness of climate issues, the broad range of societal challenges, the scope of required actions, the rate at which adaptation and resilience challenges are emerging, and the range of data, tools and methods required. An approach based on transformational relationship-and capacity-building, which is capable of drawing on and informing science, service and practice is needed. Working at the science-to-service-to-practice interfaces to enable delivery of services aimed at informing action at scale will require new ways of collecting, analysing and using information and data about the effectiveness of climate actions in particular contexts.
C1 [Jacobs, Katharine L.] Univ Arizona, ENRB2, Ctr Climate Adaptat Sci & Solut, 426N,1064 E Lowell St, Tucson, AZ 85721 USA.
   [Street, Roger Brian] Univ Oxford, Ctr Environm, Environm Change Inst, South Parks Rd, Oxford OX1 3QY, England.
C3 University of Arizona; University of Oxford
RP Jacobs, KL (corresponding author), Univ Arizona, ENRB2, Ctr Climate Adaptat Sci & Solut, 426N,1064 E Lowell St, Tucson, AZ 85721 USA.
EM jacobsk@arizona.edu; roger.street@ouce.ox.ac.uk
CR Agrawala S, 2001, SCI TECHNOL HUM VAL, V26, P454, DOI 10.1177/016224390102600404
   [Anonymous], 2019, AD NOW GLOB CALL LEA
   [Anonymous], 2007, WMO B
   [Anonymous], 2015, A European research and innovation Roadmap for Climate Services
   [Anonymous], 1999, MAKING CLIMATE FOREC
   ARGYRIS C, 1991, HARVARD BUS REV, V69, P99
   Bidwell D, 2013, NAT CLIM CHANGE, V3, P610, DOI 10.1038/nclimate1931
   Buizer J, 2016, P NATL ACAD SCI USA, V113, P4597, DOI 10.1073/pnas.0900518107
   Cash D., 2005, KNOWLEDGE ACTION SYS
   Cash DW, 2006, SCI TECHNOL HUM VAL, V31, P465, DOI 10.1177/0162243906287547
   Colloff MJ, 2017, ENVIRON SCI POLICY, V68, P87, DOI 10.1016/j.envsci.2016.11.007
   Dilling L, 2011, GLOBAL ENVIRON CHANG, V21, P680, DOI 10.1016/j.gloenvcha.2010.11.006
   Feldman DL, 2009, WEATHER CLIM SOC, V1, P9, DOI 10.1175/2009WCAS1007.1
   Gerlak A. K., 2017, MIDTERM REV GLOBAL F
   Hansen James., 2019, Scaling Climate Services to Enable Effective Adaptation Action
   Hulme M., 2009, CLIMATE PREDICTION L
   Jacobs K, 2005, ENVIRONMENT, V47, P6, DOI 10.3200/ENVT.47.9.6-21
   Jacobs K., 2015, FOREWORD CLIMATE CON
   Lemos MC, 2014, WEATHER CLIM SOC, V6, P273, DOI 10.1175/WCAS-D-13-00044.1
   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
   Lövbrand E, 2011, SCI PUBL POLICY, V38, P225, DOI 10.3152/030234211X12924093660516
   McNie EC, 2007, ENVIRON SCI POLICY, V10, P17, DOI 10.1016/j.envsci.2006.10.004
   McNie EC, 2016, RES POLICY, V45, P884, DOI 10.1016/j.respol.2016.01.004
   McNie EC, 2013, WEATHER CLIM SOC, V5, P14, DOI 10.1175/WCAS-D-11-00034.1
   Meadow AM, 2015, WEATHER CLIM SOC, V7, P179, DOI 10.1175/WCAS-D-14-00050.1
   Meinke H, 2006, CLIM RES, V33, P101, DOI 10.3354/cr033101
   MOSER S, 2011, CLIMATE CHANGE GREAT, P179
   Moser S.C., 2018, PUBLICATION CCCA4 CE
   Moser S.C., 2014, SUCCESSFUL ADAPTATIO
   Moser SC, 2015, CLIMATIC CHANGE, V129, P13, DOI 10.1007/s10584-015-1328-z
   Moss R.H., 2019, WEATHER CLIMATE SOC, V11
   Natl Acad Sci Engn Med, 2016, ATTRIBUTION OF EXTREME WEATHER EVENTS IN THE CONTEXT OF CLIMATE CHANGE, P1, DOI 10.17226/21852
   Rayner S, 2005, CLIMATIC CHANGE, V69, P197, DOI 10.1007/s10584-005-3148-z
   Romme AGL, 1999, J ORGAN CHANGE MANAG, V12, P439, DOI 10.1108/09534819910289110
   Rosenzweig C, 2014, GLOBAL ENVIRON CHANG, V28, P395, DOI 10.1016/j.gloenvcha.2014.05.003
   Smith B, 2000, CLIMATIC CHANGE, V45, P223, DOI 10.1023/A:1005661622966
   Termeer CJAM, 2017, J ENVIRON PLANN MAN, V60, P558, DOI 10.1080/09640568.2016.1168288
   USGCRP, 2018, IMPACTS RISKS ADAPTA, VII, DOI [10.7930/NCA42018, DOI 10.7930/NCA42018]
   Vaughan C, 2014, WIRES CLIM CHANGE, V5, P587, DOI 10.1002/wcc.290
   White DD, 2010, SCI PUBL POLICY, V37, P219, DOI 10.3152/030234210X497726
   Wilby RL, 2010, WEATHER, V65, P180, DOI 10.1002/wea.543
NR 42
TC 49
Z9 50
U1 0
U2 10
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2405-8807
J9 CLIM SERV
JI Clim. Serv.
PD DEC
PY 2020
VL 20
AR 100199
DI 10.1016/j.cliser.2020.100199
PG 7
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 PH1SK
UT WOS:000600201200007
OA gold
DA 2025-01-10
ER

PT J
AU Zhou, YK
   Zheng, SQ
   Zhang, GQ
AF Zhou, Yuekuan
   Zheng, Siqian
   Zhang, Guoqiang
TI Machine learning-based optimal design of a phase change material
   integrated renewable system with on-site PV, radiative cooling and
   hybrid ventilations-study of modelling and application in five climatic
   regions
SO ENERGY
LA English
DT Article
DE Phase change materials (PCMs); Latent heat storage; Optimal design;
   Robust operation; Machine learning; Climate-adaptive operation
ID PERFORMANCE ENHANCEMENT; THERMAL PERFORMANCE; ENERGY PERFORMANCE; PCM;
   OPTIMIZATION; BUILDINGS; WALL
AB The widespread application of advanced renewable systems with optimal design can promote the cleaner production, reduce the carbon dioxide emission and realise the renewable and sustainable development. In this study, a phase change material integrated hybrid system was demonstrated, involving with advanced energy conversions and multi-diversified energy forms, including solar-to-electricity conversion, active water-based and air-based cooling, and distributed storages. A generic optimization methodology was developed by integrating supervised machine learning and heuristic optimization algorithms. Multivariable optimizations were systematically conducted for widespread application purpose in five climatic regions in China. Results showed that, the energy performance is highly dependent on mass flow rate and inlet cooling water temperature with contribution ratios at around 90% and 7%. Furthermore, compared to Taguchi standard orthogonal array, the machine-learning based optimization can improve the annual equivalent overall output energy from 86934.36 to 90597.32 kWh (by 4.2%) in ShangHai, from 86335.35 to 92719.07 (by 7.4%) in KunMing, from 87445.1 to 912183 (by 4.3%) in GuangZhou, from 87278.24 to 88212.83 (by 1.1%) in HongKong, and from 87611.95 to 92376.46 (by 5.4%) in HaiKou. This study presents optimal design and operation of a renewable system in different climatic regions, which are important to realise renewable and sustainable buildings. (C) 2019 Published by Elsevier Ltd.
C1 [Zhou, Yuekuan] Hong Kong Polytech Univ, Fac Construct & Environm, Dept Bldg Serv Engn, Hong Kong, Peoples R China.
   [Zheng, Siqian] City Univ Hong Kong, Dept Architecture & Civil Engn, Hong Kong, Peoples R China.
   [Zhang, Guoqiang] Hunan Univ, Natl Ctr Int Res Collaborat Bldg Safety & Environ, Changsha 410082, Hunan, Peoples R China.
   [Zhang, Guoqiang] Hunan Univ, Coll Civil Engn, Changsha 410082, Hunan, Peoples R China.
C3 Hong Kong Polytechnic University; City University of Hong Kong; Hunan
   University; Hunan University
RP Zheng, SQ (corresponding author), City Univ Hong Kong, Dept Architecture & Civil Engn, Hong Kong, Peoples R China.
EM candyz129@sina.com
RI Zhou, Yuekuan/AAI-1054-2020
OI Zhou, Yuekuan/0000-0003-2038-0314; Zhang, Guoqiang/0000-0003-3781-6874;
   ZHENG, Siqian/0000-0002-8436-4367
FU Hong Kong Polytechnic University; City University of Hong Kong; Hunan
   University
FX This research is supported by the Hong Kong Polytechnic University, City
   University of Hong Kong, and Hunan University.
CR Ahangari M, 2019, SUSTAIN CITIES SOC, V44, P120, DOI 10.1016/j.scs.2018.09.008
   Ahmad T, 2018, ENERGY, V158, P17, DOI 10.1016/j.energy.2018.05.169
   Aldossary A, 2016, APPL THERM ENG, V100, P490, DOI 10.1016/j.applthermaleng.2016.02.023
   [Anonymous], 2011, INT J ADV THERM SCI
   [Anonymous], 2015, DSP First
   Chow TT, 2010, APPL ENERG, V87, P365, DOI 10.1016/j.apenergy.2009.06.037
   Cui TF, 2016, ENERG CONVERS MANAGE, V112, P49, DOI 10.1016/j.enconman.2016.01.008
   Elminshawy NAS, 2019, APPL THERM ENG, V148, P1, DOI 10.1016/j.applthermaleng.2018.11.027
   Gu WB, 2019, ENERG CONVERS MANAGE, V198, DOI 10.1016/j.enconman.2019.111800
   Hasan A, 2016, ENERG BUILDINGS, V130, P495, DOI 10.1016/j.enbuild.2016.08.059
   Huang MJ, 2011, SOL ENERG MAT SOL C, V95, P1598, DOI 10.1016/j.solmat.2011.01.008
   Ji J, 2009, INT J HEAT MASS TRAN, V52, P1365, DOI 10.1016/j.ijheatmasstransfer.2008.08.017
   Kuznik F, 2015, ENERG BUILDINGS, V106, P216, DOI 10.1016/j.enbuild.2015.06.021
   Li ZP, 2019, ENERGY, V178, P471, DOI 10.1016/j.energy.2019.04.166
   Lin WY, 2019, RENEW ENERG, V130, P1116, DOI 10.1016/j.renene.2018.08.071
   Lin WY, 2016, ENERGY, V106, P23, DOI 10.1016/j.energy.2016.03.013
   Liu X., 2018, Materials, V11, P1
   Liu XH, 2019, ENERGIES, V12, DOI 10.3390/en12061022
   Liu ZX, 2019, ENERGY, V172, P220, DOI 10.1016/j.energy.2019.01.098
   Liu ZX, 2019, ENERG CONVERS MANAGE, V186, P433, DOI 10.1016/j.enconman.2019.02.069
   Lu BW, 2018, ENERG CONVERS MANAGE, V175, P213, DOI 10.1016/j.enconman.2018.08.108
   Ma T, 2019, SOL ENERGY, V184, P292, DOI 10.1016/j.solener.2019.03.089
   Marin P, 2016, ENERG BUILDINGS, V129, P274, DOI 10.1016/j.enbuild.2016.08.007
   Park J, 2014, SOL ENERGY, V105, P561, DOI 10.1016/j.solener.2014.04.020
   Peng JQ, 2015, APPL ENERG, V138, P572, DOI 10.1016/j.apenergy.2014.10.003
   Plytaria MT, 2019, THERM SCI ENG PROG, V10, P59, DOI 10.1016/j.tsep.2019.01.010
   Plytaria MT, 2019, ENERG CONVERS MANAGE, V188, P40, DOI 10.1016/j.enconman.2019.03.042
   Sardarabadi M, 2017, SOL ENERG MAT SOL C, V161, P62, DOI 10.1016/j.solmat.2016.11.032
   Sharma S, 2016, SOL ENERG MAT SOL C, V149, P29, DOI 10.1016/j.solmat.2015.12.035
   Smith CJ, 2014, APPL ENERG, V126, P21, DOI 10.1016/j.apenergy.2014.03.083
   Souayfane F, 2019, ENERGY, V169, P1274, DOI 10.1016/j.energy.2018.12.116
   Su D, 2017, ENERG CONVERS MANAGE, V131, P79, DOI 10.1016/j.enconman.2016.11.002
   Sun WC, 2018, ENERG CONVERS MANAGE, V177, P306, DOI 10.1016/j.enconman.2018.09.073
   Tang L, 2020, SOL ENERGY, V195, P514, DOI 10.1016/j.solener.2019.11.067
   Wang ZX, 2019, ENERG CONVERS MANAGE, V187, P472, DOI 10.1016/j.enconman.2019.02.094
   Yan J, 2020, ENERG CONVERS MANAGE, V203, DOI 10.1016/j.enconman.2019.112261
   Zhang JY, 2019, INT C COMP SUPP COOP, P57, DOI [10.1109/CSCWD.2019.8791878, 10.1109/cscwd.2019.8791878]
   Zhao B, 2019, APPL ENERG, V252, DOI 10.1016/j.apenergy.2019.113432
   Zheng SQ, 2019, ADV THEOR SIMUL, V2, DOI 10.1002/adts.201900092
   Zhou Y, 2019, TABLE 3 IS PARTIALLY, P111
   Zhou Y, 2019, TABLE 4 IS PARTIALLY, P111
   Zhou YK, 2020, RENEW ENERG, V151, P403, DOI 10.1016/j.renene.2019.11.037
   Zhou YK, 2019, J BUILD ENG, V26, DOI 10.1016/j.jobe.2019.100845
   Zhou YK, 2019, ENERG CONVERS MANAGE, V199, DOI 10.1016/j.enconman.2019.111888
   Zhou YK, 2019, RENEW SUST ENERG REV, V114, DOI 10.1016/j.rser.2019.109337
   Zhou YK, 2019, ENERGY, V179, P111, DOI 10.1016/j.energy.2019.04.173
   Zhou YK, 2019, INDOOR BUILT ENVIRON, V28, P195, DOI 10.1177/1420326X18807451
   Zhou YK, 2018, APPL THERM ENG, V144, P1091, DOI 10.1016/j.applthermaleng.2018.04.083
   Zhou YK, 2017, PROCEDIA ENGINEER, V205, P1337, DOI 10.1016/j.proeng.2017.10.109
   Zhou YK, 2016, INDOOR BUILT ENVIRON, V25, P1279, DOI 10.1177/1420326X16671983
NR 50
TC 65
Z9 67
U1 6
U2 93
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 FEB 1
PY 2020
VL 192
AR 116608
DI 10.1016/j.energy.2019.116608
PG 21
WC Thermodynamics; Energy & Fuels
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Thermodynamics; Energy & Fuels
GA KO0CB
UT WOS:000515212800032
DA 2025-01-10
ER

PT J
AU Cernoch, V
   Kopecky, D
AF Cernoch, V.
   Kopecky, D.
TI Drought tolerance and regrowth capacity revealed in the
   <i>Festuca-Lolium</i> complex
SO BIOLOGIA PLANTARUM
LA English
DT Article
DE intergeneric hybridization; climatic adaptation; Festulolium krasanii;
   Festulolium braunii; Festulolium loliaceum
ID CLIMATE-CHANGE; PERENNE L.; STRESS TOLERANCE; GLAUCESCENS; POLYPLOIDY;
   GRASSLANDS; RESPONSES; IMPACT; GENES
AB The climate change appears to have accelerated in recent years, and more changes are envisaged in the near future. With this in mind, breeders should consider the choices of materials to be used in breeding for the future to potentially mitigate the impacts of changes. In forage grasses, a special attention has to be paid to drought and heat tolerance. Here, in a screening trial of numerous accessions, we investigated drought tolerance and after-drought recovery rates among the species of the Festuca-Lolium complex, including cultivars and breeding materials as well as various ecotypes of wild species. Experimental trials were done using rainout shelters during three successive years 2017 2019. The most drought tolerant genotypes belonged to the species F. glaucescens and F. mairei, followed by F. atlantigena, F. arundinacea, and some genotypes of F. pratensis. These genotypes should be considered as suitable candidates for intergeneric hybridization with L. multiflorum and L. perenne. Our test shows that Festulolium krasanii (L. multiflorum x F. arundinacea) is a good candidate to replace pure tall fescue (F. arundinacea) stands. It has the same or similar drought tolerance and drought recovery as tall fescue and at least some cultivars are known for their high feeding value, unlike tall fescue itself. A large variability for drought tolerance and recovery rates in Fl. braunii (the L. multiflorum x F. pratensis hybrid) and Fl. loliaceum (the L. perenne x F. pratensis hybrid) permit selection of genotypes that can outperform the original L. multiflorum and L. perenne.
C1 [Cernoch, V.] DLF Seeds, Fulnecka 95, CZ-74247 Hladke Zivotice, Czech Republic.
   [Kopecky, D.] Czech Acad Sci, Inst Expt Bot, Ctr Reg Hana Biotechnol & Agr Res, CZ-77900 Olomouc, Czech Republic.
C3 Czech Academy of Sciences; Institute of Experimental Botany of the Czech
   Academy of Sciences
RP Kopecky, D (corresponding author), Czech Acad Sci, Inst Expt Bot, Ctr Reg Hana Biotechnol & Agr Res, CZ-77900 Olomouc, Czech Republic.
EM kopecky@ueb.cas.cz
RI Kopecky, David/F-7284-2014
OI Kopecky, David/0000-0002-2834-1734
FU Czech Science Foundation [20-10019S]; European Regional Development Fund
   OPVVV project 'Plants as a tool for sustainable development'
   [CZ.02.1.01/0.0/0.0/16_019/0000827]
FX We would like to thank Prof. Adam J. Lukaszewski (University of
   California, Riverside) for his critical reading and valuable comments.
   This research was partially funded by the Czech Science Foundation
   (grant awards 20-10019S) and by the European Regional Development Fund
   OPVVV project 'Plants as a tool for sustainable development' number
   CZ.02.1.01/0.0/0.0/16_019/0000827 supporting Excellent Research at CRH.
CR Alm V, 2011, THEOR APPL GENET, V123, P369, DOI 10.1007/s00122-011-1590-z
   Bothe A, 2018, J AGRON CROP SCI, V204, P375, DOI 10.1111/jac.12269
   Cai XM, 2015, WIRES WATER, V2, P439, DOI 10.1002/wat2.1089
   Cao M, 2003, CROP SCI, V43, P1659, DOI 10.2135/cropsci2003.1659
   Catalán P, 2004, MOL PHYLOGENET EVOL, V31, P517, DOI 10.1016/j.ympev.2003.08.025
   Chaves MM, 2003, FUNCT PLANT BIOL, V30, P239, DOI 10.1071/FP02076
   Cheplick GP, 2000, FUNCT ECOL, V14, P657, DOI 10.1046/j.1365-2435.2000.00466.x
   Devesa J. A., 2013, Lagascalia, V33, P183
   Dierking R., 2015, PLANT GENOME, V8, P1
   Ebrahimiyan M, 2012, CROP PASTURE SCI, V63, P360, DOI 10.1071/CP11279
   Eitzinger J, 2013, J AGR SCI-CAMBRIDGE, V151, P787, DOI 10.1017/S0021859612000767
   Eitzinger J, 2007, MANAGING WEATHER AND CLIMATE RISKS IN AGRICULTURE, P141, DOI 10.1007/978-3-540-72746-0_10
   Ghesquiere M, 1996, PLANT BREEDING, V115, P238, DOI 10.1111/j.1439-0523.1996.tb00910.x
   Ghesquière M, 2010, HANDB PLANT BREED, V5, P293, DOI 10.1007/978-1-4419-0760-8_12
   Harle KJ, 2007, AGR SYST, V93, P61, DOI 10.1016/j.agsy.2006.04.003
   Hulke BS, 2007, CROP SCI, V47, P1596, DOI 10.2135/cropsci2006.10.0671
   Humphreys J, 2005, THEOR APPL GENET, V110, P579, DOI 10.1007/s00122-004-1879-2
   Kamau S., 2018, BREEDING GRASSES PRO, P121
   Kipling RP, 2016, SCI TOTAL ENVIRON, V566, P851, DOI 10.1016/j.scitotenv.2016.05.144
   Kopecky D, 2008, CYTOGENET GENOME RES, V120, P370, DOI 10.1159/000121086
   Kopecky D, 2006, THEOR APPL GENET, V113, P731, DOI 10.1007/s00122-006-0341-z
   Kopecky D, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11113153
   Kopecky D, 2019, EUPHYTICA, V215, DOI 10.1007/s10681-019-2419-0
   Kosmala A., 2003, Vortr Pflanzenzuchtg, V59, P225
   Lee MA, 2019, AGRONOMY-BASEL, V9, DOI 10.3390/agronomy9030159
   MacDougall AS, 2013, NATURE, V494, P86, DOI 10.1038/nature11869
   Mickelbart MV, 2015, NAT REV GENET, V16, P237, DOI 10.1038/nrg3901
   O'Mara FP, 2012, ANN BOT-LONDON, V110, P1263, DOI 10.1093/aob/mcs209
   Parisod C, 2010, NEW PHYTOL, V186, P5, DOI 10.1111/j.1469-8137.2009.03142.x
   STEBBINS GL, 1984, BOT HELV, V94, P1
   te Beest M, 2012, ANN BOT-LONDON, V109, P19, DOI 10.1093/aob/mcr277
   Trnka M, 2013, CLIMATIC CHANGE, V120, P405, DOI 10.1007/s10584-013-0786-4
   Turner LR, 2012, GRASS FORAGE SCI, V67, P507, DOI 10.1111/j.1365-2494.2012.00866.x
   Wang YF, 2007, ECOL LETT, V10, P401, DOI 10.1111/j.1461-0248.2007.01031.x
   Xu JQ, 2019, J FORESTRY RES, V30, P1267, DOI 10.1007/s11676-018-0729-z
   Zahradnícek P, 2015, INT J CLIMATOL, V35, P3335, DOI 10.1002/joc.4211
   Zhao G, 2015, GLOBAL CHANGE BIOL, V21, P4031, DOI 10.1111/gcb.13008
   Zhou K, 2019, ENVIRON EXP BOT, V159, P44, DOI 10.1016/j.envexpbot.2018.12.005
NR 38
TC 6
Z9 6
U1 0
U2 5
PU ACAD SCIENCES CZECH REPUBLIC, INST EXPERIMENTAL BOTANY
PI PRAHA 6
PA ROZVOJOVA 263, PRAHA 6, CZ-165 02, CZECH REPUBLIC
SN 0006-3134
EI 1573-8264
J9 BIOL PLANTARUM
JI Biol. Plant.
PY 2020
VL 64
BP 561
EP 568
DI 10.32615/bp.2020.093
PG 8
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA NM0PZ
UT WOS:000567808400001
OA gold
DA 2025-01-10
ER

PT J
AU Anderies, JM
   Barreteau, O
   Brady, U
AF Anderies, John M.
   Barreteau, Olivier
   Brady, Ute
TI Refining the Robustness of Social-Ecological Systems Framework for
   comparative analysis of coastal system adaptation to global change
SO REGIONAL ENVIRONMENTAL CHANGE
LA English
DT Article
DE Climate adaptation; Coupled infrastructure systems; Frameworks;
   Robustness; Coastal settlements; Comparative analysis
ID INSTITUTIONAL ANALYSIS; BIODIVERSITY LOSS; COMMONS; GOVERNANCE;
   PERFORMANCE; COMMUNITY; RESOURCE; DESIGN
AB There are numerous frameworks for studying the governance of shared resources that have been discussed extensively in the literature. Although these frameworks have been applied to multiple case studies, these applications are often idiosyncratic, subject to the interpretation of the researcher, and raise concerns regarding the operational use of frameworks for case-study comparisons. As a result, insights from these studies have not lived up to the aspirations of the frameworks to generate generalizable knowledge. Here, based on several case studies and our experience using various frameworks for analyzing social-ecological systems, we undertake the task of providing a mechanism to systematically qualify interactions among ecological, social, institutional, and built infrastructure systems that impact the governance of shared resources. Specifically, we generate a series of archetypal social-ecological systems and extract from them a verb list to represent key interactions in the Robustness of Coupled Infrastructure Systems Framework. We then extend and refine the list based on three case studies of coastal social-ecological systems. We categorize these verbs and use them to demonstrate governance patterns across the case studies. We find that governance entities predominantly seek control over paths of change directed at lower governance levels rather than acting at their own level. Governance entities shed responsibility to lower governance levels without providing necessary resources. Finally, we find high potential for the cancelation of efforts due to lack of coordination among governance entities. The set of system archetypes and associated verb list is a first step in laying the foundation for a general typology of and a standardized protocol for representing the dynamics of CIS.
C1 [Anderies, John M.; Brady, Ute] Arizona State Univ, Sch Human Evolut & Social Change, Tempe, AZ 85287 USA.
   [Anderies, John M.] Arizona State Univ, Sch Sustainabil, Tempe, AZ 85287 USA.
   [Barreteau, Olivier] Univ Montpellier, Montpellier SupAgro, AgroParisTech, UMR G EAU,Cirad,IRD,IRSTEA, Montpellier, France.
C3 Arizona State University; Arizona State University-Tempe; Arizona State
   University; Arizona State University-Tempe; AgroParisTech; CIRAD;
   Institut de Recherche pour le Developpement (IRD); Universite de
   Montpellier; INRAE; Institut Agro; Montpellier SupAgro
RP Anderies, JM (corresponding author), Arizona State Univ, Sch Human Evolut & Social Change, Tempe, AZ 85287 USA.; Anderies, JM (corresponding author), Arizona State Univ, Sch Sustainabil, Tempe, AZ 85287 USA.
EM m.anderies@asu.edu; olivier.barreteau@irstea.fr; Ute.Brady@asu.edu
RI Brady, Ute/JDW-3249-2023
OI Anderies, John/0000-0002-0138-8655; Brady, Ute/0000-0002-9350-5037
FU MAGIC project (Multi-scale Adaptations to Global changes In Coastlines)
   under the Belmont Forum [ANR-13-JCLI-0005]; MAGIC project (U.S. National
   Science Foundation) under the Belmont Forum [ICER-1342933]; G8
   International Opportunities Fund (IOF); Agence Nationale de la Recherche
   (ANR) [ANR-13-JCLI-0005] Funding Source: Agence Nationale de la
   Recherche (ANR)
FX The authors gratefully acknowledge financial support for this work
   conducted during the MAGIC project (Multi-scale Adaptations to Global
   changes In Coastlines: ANR-13-JCLI-0005 and U.S. National Science
   Foundation ICER-1342933) under the Belmont Forum and G8 International
   Opportunities Fund (IOF).
CR Agrawal A., 2002, Drama of the commons, P41
   Anderies J.M., 2006, Journal of Institutional Economics, V2, P133, DOI DOI 10.1017/S1744137406000312
   Anderies JM, 2004, ECOL SOC, V9
   Anderies JM, 2016, INT J COMMONS, V10, P495, DOI 10.18352/ijc.651
   Anderies JM, 2015, B MATH BIOL, V77, P259, DOI 10.1007/s11538-014-0030-z
   Anderies JM, 2013, POLICY STUD J, V41, P513, DOI 10.1111/psj.12027
   Anderies JM, 2013, ECOL SOC, V18, DOI 10.5751/ES-05178-180208
   [Anonymous], 1973, SMALL IS BEAUTIFUL S
   Araral E, 2014, ENVIRON SCI POLICY, V36, P11, DOI 10.1016/j.envsci.2013.07.011
   Armitage D., 2007, International Journal of the Commons, V2, P7
   Balooni K., 2007, Economic and Political Weekly, V42, P1443
   Barreteau O., 2016, Ecology and Society, V21, P42, DOI [DOI 10.5751/ES-08834-210442, 10.5751/ES-08834-210442]
   Bastakoti RC, 2012, J I ECON, V8, P225, DOI 10.1017/S1744137411000452
   Cifdaloz O, 2010, ECOL SOC, V15
   Cox M, 2010, ECOL SOC, V15
   CRAWFORD SES, 1995, AM POLIT SCI REV, V89, P582, DOI 10.2307/2082975
   Daly Herman., 1973, STEADY STATE EC
   Duit A, 2010, GLOBAL ENVIRON CHANG, V20, P363, DOI 10.1016/j.gloenvcha.2010.04.006
   Dyball R., 2014, Understanding human ecology: a systems approach to sustainability / Robert Dyball, Barry Newell. Milton Park, Abingdon
   Epstein G, 2014, INT J COMMONS, V8, P337, DOI 10.18352/ijc.407
   Epstein G, 2014, INT J COMMONS, V8, P277, DOI 10.18352/ijc.410
   Ghorbani A, 2013, JASSS-J ARTIF SOC S, V16, DOI 10.18564/jasss.2166
   Gibson ClarkC., 2005, SAMARITANS DILEMMA P
   Gordon HS, 1954, J POLIT ECON, V62, P124, DOI 10.1086/257497
   Guerbois C, 2019, REG ENVIRON CHANGE, V19, P1849, DOI 10.1007/s10113-019-01508-5
   Gutiérrez NL, 2011, NATURE, V470, P386, DOI 10.1038/nature09689
   Hinkel J, 2014, ECOL SOC, V19, DOI 10.5751/ES-06475-190351
   Hooper DU, 2012, NATURE, V486, P105, DOI 10.1038/nature11118
   INSEE, 2014, 30 ANS DEM LANG ROUS
   Kiser L., 1982, STRATEGIES POLITICAL, P179
   Klinke A, 2012, J RISK RES, V15, P273, DOI 10.1080/13669877.2011.636838
   LONG NE, 1958, AM J SOCIOL, V64, P251, DOI 10.1086/222468
   Lubell M, 2013, POLICY STUD J, V41, P537, DOI 10.1111/psj.12028
   Mazouni N, 2006, VIE MILIEU, V56, P265
   McKee R, 2017, HOMES EVACUATED CORN
   Muneepeerakul R, 2017, EARTHS FUTURE, V5, P865, DOI 10.1002/2017EF000562
   Nyoka N, 2017, SERIES EVACUATIONS F
   Ostrom E, 2005, UNDERSTANDING INSTITUTIONAL DIVERSITY, P1
   Ostrom E., 1992, CRAFTING I SELF GOVE
   Ostrom E., 1994, RULES GAMES COMMON P
   Ostrom E., 2009, PROPERTY RIGHTS LAND
   Ostrom E, 2007, P NATL ACAD SCI USA, V104, P15181, DOI 10.1073/pnas.0702288104
   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
   Poteete AR, 2010, WORKING TOGETHER: COLLECTIVE ACTION, THE COMMONS, AND MULTIPLE METHODS IN PRACTICE, P1
   Rieucau J, 2000, ANN GEOGR, V109, P631, DOI [10.3406/geo.2000.1820, DOI 10.3406/GEO.2000.1820]
   SABATIER PA, 1988, POLICY SCI, V21, P129, DOI 10.1007/BF00136406
   Savill R, 2009, GALE FORCE WINDS RAI
   Schlüter M, 2014, ECOL SOC, V19, DOI 10.5751/ES-05782-190136
   Therville C, 2018, EVIDENCE LANGUEDOC F, DOI [10.1007/s10113-018-1427-2, DOI 10.1007/S10113-018-1427-2]
   Western Cape Government, 2008, ED DISTR BE DECL LOC
   Worm B, 2006, SCIENCE, V314, P787, DOI 10.1126/science.1132294
   Yu DJ, 2015, P NATL ACAD SCI USA, V112, P13207, DOI 10.1073/pnas.1410688112
   [No title captured]
NR 54
TC 21
Z9 23
U1 5
U2 46
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 OCT
PY 2019
VL 19
IS 7
SI SI
BP 1891
EP 1908
DI 10.1007/s10113-019-01529-0
PG 18
WC Environmental Sciences; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA JB9WG
UT WOS:000488930500006
DA 2025-01-10
ER

PT J
AU Lewis, JA
   Ernstson, H
AF Lewis, Joshua A.
   Ernstson, Henrik
TI Contesting the coast: Ecosystems as infrastructure in the Mississippi
   River Delta
SO PROGRESS IN PLANNING
LA English
DT Article
DE New Orleans; Deltaic landscapes; Environmental politics; Urban ecology;
   Expertise
ID CLIMATE-CHANGE; HURRICANE-KATRINA; NEW-ORLEANS; ADAPTATION; RESILIENCE;
   ECOLOGY; WATER; RISK; VULNERABILITY; TECHNOLOGY
AB We develop an analytical repertoire for understanding historical interrelationships between water infrastructure, regional environmental politics, and large-scale coastal ecosystems. In doing so, we scrutinize how notions of urban resilience, climate adaptation, and ecosystem-based infrastructure are influencing contemporary planning practice. Our account from New Orleans and the Mississippi River Delta traces several large-scale hydrological engineering projects with origins in the early 20th century, which aimed to restructure the landscape for more effective maritime transportation, flood protection, and urban drainage. The account then turns to a discussion of a massive and ongoing planning project, which aims to restore the historical dynamics of the Mississippi River Delta, diverting the river into nearby coastal wetlands to provide storm protection for vulnerable communities, most especially New Orleans. Our analysis shows how the development of water infrastructure systems in the region produced cleavages in the region's body politic and eco-hydrology, generating disputes that threaten to slow or obstruct the plan's implementation. The study shows how the forms and discourses of political contention in the present are deeply informed by past decisions regarding the placement, operation, and maintenance of water infrastructures in the region. The conflicts that emerge from these cleavages comprise the primary obstacle facing ecosystem-based strategies aimed at securing New Orleans and other major settlements in the region from storm surges. This raises fundamental challenges for planning practice, which are explored here through a discussion of situational dissensus, conflicting rationalities, and pathways for democratic institutional innovation.
C1 [Lewis, Joshua A.] Stockholm Univ, Stockholm Resilience Ctr, SE-10691 Stockholm, Sweden.
   [Lewis, Joshua A.] Tulane Univ, Water Inst, 6823 St Charles Ave, New Orleans, LA 70118 USA.
   [Ernstson, Henrik] KTH Royal Inst Technol, Div Hist Sci Technol & Environm, KTH Environm Human Lab, Teknikringen 74D-4tr, SE-10044 Stockholm, Sweden.
   [Ernstson, Henrik] Univ Manchester, Sch Environm Educ & Dev, Dept Geog, Manchester M13 9PL, Lancs, England.
C3 Stockholm University; Tulane University; Royal Institute of Technology;
   University of Manchester
RP Lewis, JA (corresponding author), 6823 St Charles Ave,627 Lindy Boggs Ctr, New Orleans, LA 70118 USA.
EM jlewis9@tulane.edu
RI Ernstson, Henrik/LMP-6473-2024
OI Ernstson, Henrik/0000-0002-6415-4821
FU Swedish Research Council Formas [211-2011-1519]
FX We thank Sverker Sorlin and Andrew Karvonen for providing feedback on
   earlier versions of this manuscript. We also thank the editor of the
   journal and in particular two anonymous reviewers for constructive
   critique. Ashley Carse is also acknowledged for discussions that
   clarified our approach. We are of course wholly responsible for the
   final text. The Swedish Research Council Formas is further acknowledged
   for providing funding through the research grant "Socioecological
   Movements and Transformative Collective Action in Urban Ecosystems"
   (MOVE; Dnr: 211-2011-1519, which has funded interdisciplinary urban
   ecology research in Cape Town and New Orleans. For more information, see
   http://www.situatedecologies.net.
CR Aalto HE, 2017, LANDSCAPE URBAN PLAN, V157, P309, DOI 10.1016/j.landurbplan.2016.05.018
   Adger WN, 2004, ENVIRON PLANN A, V36, P1711, DOI 10.1068/a37108
   Adger WN, 2003, ECON GEOGR, V79, P387
   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
   Ahern J., 2007, Green infrastructure for cities: The spatial dimension
   Anand N, 2012, ETHNOGRAPHY, V13, P487, DOI 10.1177/1466138111435743
   [Anonymous], HYDROLOGICAL BIOL ST
   [Anonymous], IND CANAL INNNER HAR
   [Anonymous], PROGR HUMAN GEOGRAPH
   [Anonymous], TRANSFORMING NEW ORL
   [Anonymous], SEM REP SEW WAT BOAR
   [Anonymous], 1 US CES BUR
   [Anonymous], ENV PLANNING A
   [Anonymous], SEM REP SEW WAT BOAR
   [Anonymous], 2015, THESIS
   [Anonymous], T GULF COAST ASS GEO
   [Anonymous], COMBINING SOCIAL NET
   [Anonymous], PHILOS T ROYAL SOC B
   [Anonymous], PORT BUTS LAND TERMI
   [Anonymous], LAND FOREST AREA CHA
   [Anonymous], 7 SEM ANN REP SEW WA
   [Anonymous], COMMUNICATION
   [Anonymous], WORLD PORT RANK
   [Anonymous], 2017, LOUISIANAS COMPRE
   [Anonymous], SUPPL ENV IMP STAT I
   [Anonymous], FAIL IN FIN REP SEL
   [Anonymous], 2014, INFRASTRUCTURAL LIVE
   [Anonymous], CIT LOUIS DES TRUTH
   [Anonymous], EC ANAL OYSTER LEASE
   [Anonymous], 1985, DIALECTICAL BIOL
   [Anonymous], 3 CPRA
   [Anonymous], ELECT J GEOTECHNICAL
   [Anonymous], LOUIS COMPR MAST PLA
   [Anonymous], 2006, INVESTIGATION PERFOR
   [Anonymous], 2014, OFFSHORE OIL DEEPWAT
   [Anonymous], 2004, ECOLOGY SOC, DOI DOI 10.5751/ES-00650-090205
   [Anonymous], 2 SPOTS MAP HIGHLIGH
   [Anonymous], SIDES REMAIN FAR APA
   [Anonymous], 2001, SPLINTERING URBANISM
   [Anonymous], HIST 3 GREAT PUBLIC
   [Anonymous], OCEAN COASTAL LAW J
   [Anonymous], 1967, PARTY SYSTEMS VOTER
   [Anonymous], 1991, OYSTER FISHERY GULF
   [Anonymous], M MIN US ARM CORPS E
   [Anonymous], SEM REP SEW WAT BOAR
   [Anonymous], 2012, SACRED ECOLOGY
   [Anonymous], HOPE DAMMED US ARMY
   [Anonymous], GREATER BATON ROUGE
   [Anonymous], **DROPPED REF**
   [Anonymous], 2007, RISING TIDE GREAT MI
   [Anonymous], AGU FALL M
   [Anonymous], SORTING THINGS OUT C
   [Anonymous], 2004, PATHOLOGIES POWER HL
   Azcona BrianLloyd., 2006, SOCIAL THOUGHT RES, V27, P69
   Barbier EB, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0058715
   Barry Andrew., 2006, European Journal of Social Theory, V9, P239, DOI DOI 10.1177/1368431006063343
   Barthel S, 2010, GLOBAL ENVIRON CHANG, V20, P255, DOI 10.1016/j.gloenvcha.2010.01.001
   Batker D., 2014, Perspectives on the restoration of the Mississippi Delta. Estuaries of the world, P141
   Blum MD, 2009, NAT GEOSCI, V2, P488, DOI 10.1038/ngeo553
   Brenner N., 2011, Urban constellations, P11
   Breunlin R, 2006, AM ANTHROPOL, V108, P744, DOI 10.1525/aa.2006.108.4.744
   Callon M, 1998, LAWS OF THE MARKETS, P244, DOI 10.1111/j.1467-954X.1998.tb03477.x
   Campanella Richard., 2006, GEOGRAPHIES NEW ORLE
   Campanella Richard., 2002, Time and Place in New Orleans: Past Geographies in the Present Day
   Carse A, 2017, ENVIRON PLANN A, V49, P9, DOI 10.1177/0308518X16663015
   Carse A, 2012, SOC STUD SCI, V42, P539, DOI 10.1177/0306312712440166
   Carse Ashley., 2014, Beyond the Big Ditch. Politics, Ecology
   Colten CraigE., 2006, An unnatural metropolis : wresting New Orleans from nature
   Cowen D., 2014, The Deadly Life of Logistics: Mapping Violence in Global Trade, DOI DOI 10.5749/MINNESOTA/9780816680870.001.0001
   CPRA, 2012, Louisiana's Comprehensive Master Plan for a Sustainable Coast
   Crutzen P.J., 2006, The Anthropocene. Earth System Science in the Anthropocene, P13, DOI [10.1007/3-540-26590-23, DOI 10.1007/3-540-26590-23, 10.1007/3-540-26590-2_3, DOI 10.1007/3-540-26590-2_3]
   Dalbom C., 2014, Community resettlement prospects in southeast Louisiana: A multidisciplinary exploration of legal, cultural, and demographic aspects of moving individuals and communities
   Day JohnW., 2014, Perspectives on the Restoration of the Mississippi Delta: The Once and Future Delta
   De Landa Manuel., 2000, A Thousand Years of Nonlinear History
   Dokka RK, 2011, J GEOPHYS RES-SOL EA, V116, DOI 10.1029/2010JB008008
   Dougill AJ, 2010, ECOL SOC, V15
   Ernstson H, 2013, ECOL ECON, V86, P274, DOI 10.1016/j.ecolecon.2012.09.012
   Ernstson H, 2013, LANDSCAPE URBAN PLAN, V109, P7, DOI 10.1016/j.landurbplan.2012.10.005
   Ernstson H, 2010, ECOL SOC, V15
   Evans JP, 2011, T I BRIT GEOGR, V36, P223, DOI 10.1111/j.1475-5661.2010.00420.x
   Farmer P, 1996, DAEDALUS, V125, P261
   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
   Freudenburg WR, 2009, SOC SCI QUART, V90, P497, DOI 10.1111/j.1540-6237.2009.00628.x
   Freudenburg WilliamR., 2009, CATASTROPHE MAKING E
   GALTUNG J, 1969, J PEACE RES, P167
   Germany KentB., 2007, New Orleans After the Promises: Poverty, Citizenship, and the Search for the Great Society
   Giosan L, 2014, NATURE, V516, P31, DOI 10.1038/516031a
   Gramling R, 2011, SOC NATUR RESOUR, V24, P521, DOI 10.1080/08941920903311417
   Hallegatte S, 2013, NAT CLIM CHANGE, V3, P802, DOI [10.1038/nclimate1979, 10.1038/NCLIMATE1979]
   Hodson M.Marvin., 2010, World cities and climate change: Producing urban ecological security
   Holling C.S., 1973, Annual Rev Ecol Syst, V4, P1, DOI 10.1146/annurev.es.04.110173.000245
   Holling CS, 1996, CONSERV BIOL, V10, P328, DOI 10.1046/j.1523-1739.1996.10020328.x
   Hornbeck R, 2014, AM ECON REV, V104, P963, DOI 10.1257/aer.104.3.963
   Hornborg A, 2009, INT J COMP SOCIOL, V50, P237, DOI 10.1177/0020715209105141
   Howes NC, 2010, P NATL ACAD SCI USA, V107, P14014, DOI 10.1073/pnas.0914582107
   Jeansonne Glen., 2006, Leander Perez: Boss of the Delta
   Kaika M, 2017, ENVIRON URBAN, V29, P89, DOI 10.1177/0956247816684763
   Kelman Ari., 2003, A River and Its City: The Nature of Landscape in New Orleans
   Kolker AS, 2013, J HYDROL, V498, P319, DOI 10.1016/j.jhydrol.2013.06.014
   Lade SJ, 2015, P NATL ACAD SCI USA, V112, P11120, DOI 10.1073/pnas.1504954112
   Landphair J., 1999, J LOUISIANA HIST ASS, V40, P35
   Landphair J, 2007, J AM HIST, V94, P837, DOI 10.2307/25095146
   Landström C, 2011, ENVIRON PLANN A, V43, P1617, DOI 10.1068/a43482
   LEWONTIN RC, 1969, BROOKHAVEN SYM BIOL, P13
   Massey Doreen., 2008, For Space
   Massey Doreen B., 2005, For Space
   Mazmanian Daniel., 1979, Can Organizations Change?: Environmental Protection, Citizen Participation, and the Corps of Engineers
   McGranahan G, 2007, ENVIRON URBAN, V19, P17, DOI 10.1177/0956247807076960
   Melosi M.V., 2000, The Sanitary City: Urban Infrastructure in America from Colonial Times to the Present
   Monstadt J, 2009, ENVIRON PLANN A, V41, P1924, DOI 10.1068/a4145
   Murdoch Jonathan., 2006, Post-Structuralist Geography: A Guide to Relational Space
   Muth D., 2014, PERSPECTIVES RESTORA, P9
   Nadasdy Paul., 2007, ADAPTIVE COMANGAGEME, P208
   Nelson DR, 2007, ANNU REV ENV RESOUR, V32, P395, DOI 10.1146/annurev.energy.32.051807.090348
   Paavola J, 2006, ECOL ECON, V56, P594, DOI 10.1016/j.ecolecon.2005.03.015
   Pachauri R.K., 2014, CLIMATE CHANGE 2014
   Poirrier Michael A., 2013, Gulf and Caribbean Research, V25, P105
   Rabinow P, 2003, IN-FORMATION, P1
   Ramos SJ, 2014, J TRANSP GEOGR, V36, P32, DOI 10.1016/j.jtrangeo.2014.02.007
   Ranciere Jacques., 2010, DISSENSUS
   Rocha J, 2015, PHILOS T R SOC B, V370, DOI 10.1098/rstb.2013.0273
   Rodgers D, 2012, ETHNOGRAPHY, V13, P401, DOI 10.1177/1466138111435738
   Scheffer M, 2003, TRENDS ECOL EVOL, V18, P648, DOI 10.1016/j.tree.2003.09.002
   Scheffer M, 2009, NATURE, V461, P53, DOI 10.1038/nature08227
   Seed RB, 2008, J GEOTECH GEOENVIRON, V134, P718, DOI 10.1061/(ASCE)1090-0241(2008)134:5(718)
   Seto KC, 2011, GLOBAL ENVIRON CHANG, V21, pS94, DOI 10.1016/j.gloenvcha.2011.08.005
   Shaffer GP, 2009, J COASTAL RES, P206, DOI 10.2112/SI54-004.1
   Slingerland R, 2004, ANNU REV EARTH PL SC, V32, P257, DOI 10.1146/annurev.earth.32.101802.120201
   Spalding MD, 2014, CONSERV LETT, V7, P293, DOI 10.1111/conl.12074
   Star SL, 1996, INFORM SYST RES, V7, P111, DOI 10.1287/isre.7.1.111
   Steffen W, 2011, PHILOS T R SOC A, V369, P842, DOI 10.1098/rsta.2010.0327
   Stengers Isabelle., 2005, MAKING THINGS PUBLIC, P994
   Sumaila UR, 2012, CAN J FISH AQUAT SCI, V69, P499, DOI [10.1139/F2011-171, 10.1139/f2011-171]
   Teal J.M., 2012, Final Report to the State of Louisiana and the U.S. Army Corps of Engineers through the Louisiana Coastal Area Science Technology Program
   Tessler ZD, 2015, SCIENCE, V349, P638, DOI 10.1126/science.aab3574
   Thomas DSG, 2005, GLOBAL ENVIRON CHANG, V15, P115, DOI 10.1016/j.gloenvcha.2004.10.001
   Tiner R.W., 2013, TIDAL WETLANDS PRIME
   Tompkins EL, 2004, ECOL SOC, V9
   Upton HaroldF., 2011, The Deepwater Horizon Oil Spill and the Gulf of Mexico Fishing Industry
   Wamsley TV, 2010, OCEAN ENG, V37, P59, DOI 10.1016/j.oceaneng.2009.07.018
   Watson V., 2003, PLANNING THEORY PRAC, V4, P395, DOI DOI 10.1080/1464935032000146318
   Wells AE, 2004, URBAN EDUC, V39, P408, DOI 10.1177/0042085904265108
   Whatmore SJ, 2011, ECON SOC, V40, P582, DOI 10.1080/03085147.2011.602540
   WIEDER A, 1987, PHYLON, V48, P122, DOI 10.2307/274776
   Wolf J, 2010, GLOBAL ENVIRON CHANG, V20, P44, DOI 10.1016/j.gloenvcha.2009.09.004
   Zarycki Tomasz, 2007, REGIONAL LOCAL STUDI, P110
NR 148
TC 34
Z9 40
U1 6
U2 66
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0305-9006
EI 1873-4510
J9 PROG PLANN
JI Prog. Plan.
PD APR
PY 2019
VL 129
SI SI
BP 1
EP 30
DI 10.1016/j.progress.2017.10.003
PG 30
WC Environmental Studies; Regional & Urban Planning
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Public Administration
GA HT3SE
UT WOS:000464482700001
OA Green Submitted
DA 2025-01-10
ER

PT J
AU Wang, SG
   Chen, B
AF Wang, Saige
   Chen, Bin
TI Three-Tier carbon accounting model for cities
SO APPLIED ENERGY
LA English
DT Article
DE Urban carbon footprint; Supply chain; Three tiers; Life cycle analysis
ID LIFE-CYCLE ASSESSMENT; INPUT-OUTPUT-ANALYSIS; ENERGY-WATER NEXUS; CO2
   EMISSIONS; EMBODIED ENERGY; ENVIRONMENTAL IMPACTS; FOOTPRINT ESTIMATION;
   GHG EMISSIONS; SUPPLY CHAIN; TRADE
AB With the rapid population and economic growth, carbon emissions in cities have been increasing due to the accelerating urbanization, which provide great potential for global climate change mitigation. To measure the carbon emissions along the urban supply chain in terms of sectoral and urban horizons, this study tries to build a systematic carbon accounting framework to quantify sectoral indirect upstream supply chain emissions for effective urban carbon mitigation. An urban Three-Tier carbon accounting model has been established based on the Economic input-output life cycle assessment (EIO-LCA) method, concerning Tier 1: direct emissions; Tier 2: emissions from purchased secondary energy resource; and Tier 3: complete supply chain emissions. A case study of Chongqing city was conducted to identify the critical sectors of three tiers that contribute most to total carbon emissions, covering 28 economic sectors during 2002-2007. The results showed that emissions of Tier 1 and Tier 2 included in most protocols only occupy a small fraction (27.8%) of the total emissions of all 3 tiers, especially for industrial sectors. It is concluded that the existing climate-control protocols have underestimated the emissions of each sector and particularly, Tier 3 emissions have to be incorporated when formulating effective urban management strategies and climate adaptation planning. By incorporating the Three-Tier carbon footprint into sectoral input-output accounting framework, this study developed carbon sector specific categorizations to pursue emissions mitigation pathways not just within their own economic activity but also across their supply chain.
C1 [Wang, Saige; Chen, Bin] Beijing Normal Univ, Sch Environm, State Key Joint Lab Environm Simulat & Pollut Con, Beijing 100875, Peoples R China.
C3 Beijing Normal University
RP Chen, B (corresponding author), 19 Xinjiekouwai St, Beijing 100875, Peoples R China.
EM chenb@bnu.edu.cn
RI Chen, Bin/A-6951-2012
FU National Science Fund for Distinguished Young Scholars of China
   [71725005]; National Key Research & Development Program
   [2016YFA0602304]; National Natural Science Foundation of China
   [71573021, 71628301]; special fund of State Key Joint Laboratory of
   Environment Simulation and Pollution Control [18L03ESPC]
FX This work was supported by the National Science Fund for Distinguished
   Young Scholars of China (71725005), National Key Research & Development
   Program (2016YFA0602304), and National Natural Science Foundation of
   China (Nos. 71573021, 71628301), and special fund of State Key Joint
   Laboratory of Environment Simulation and Pollution Control (18L03ESPC).
CR Alcantara V, 2009, ECOL ECON, V68, P905, DOI 10.1016/j.ecolecon.2008.07.010
   [Anonymous], GREENH GAS PROT IN N
   [Anonymous], 2009, Input-Output Analysis: Foundations and Extensions
   Bi J, 2011, ENERG POLICY, V39, P4785, DOI 10.1016/j.enpol.2011.06.045
   Brizga J, 2017, APPL ENERG, V189, P780, DOI 10.1016/j.apenergy.2016.01.102
   Cai BF, 2014, ENERG POLICY, V66, P557, DOI 10.1016/j.enpol.2013.10.072
   CDRC, 2010, CHONGQ DEV REF COMM
   Chen B, 2018, APPL ENERG, V210, P98, DOI 10.1016/j.apenergy.2017.10.113
   Chen B, 2017, ENERG POLICY, V110, P69, DOI 10.1016/j.enpol.2017.08.010
   Chen B, 2017, RENEW SUST ENERG REV, V67, P662, DOI 10.1016/j.rser.2016.09.027
   Chen JX, 2017, J ENVIRON MANAGE, V188, P255, DOI 10.1016/j.jenvman.2016.12.006
   Chen JH, 2018, SCI TOTAL ENVIRON, V612, P931, DOI 10.1016/j.scitotenv.2017.08.304
   Chinese Academy for Environment Planning, 2009, ANAL FOR ENV EC KEY
   Davis SJ, 2011, P NATL ACAD SCI USA, V108, P18554, DOI 10.1073/pnas.1107409108
   Dhakal S, 2009, ENERG POLICY, V37, P4208, DOI 10.1016/j.enpol.2009.05.020
   Eggleston H.S., 2006, 2006 IPCC GUIDELINES
   Gibon T, 2015, ENVIRON SCI TECHNOL, V49, P11218, DOI 10.1021/acs.est.5b01558
   [顾朝林 Gu Chaolin], 2011, [城市环境与城市生态, Urban Environment and Urban Ecology], V24, P1
   Hendrickson C.T., 2010, ENV LIFE CYCLE ASSES, DOI DOI 10.4324/9781936331383
   Hertwich EG, 2009, ENVIRON SCI TECHNOL, V43, P6414, DOI 10.1021/es803496a
   Hillman T, 2010, ENVIRON SCI TECHNOL, V44, P1902, DOI 10.1021/es9024194
   Hu YC, 2016, ENVIRON SCI TECHNOL, V50, P6154, DOI 10.1021/acs.est.6b00985
   Huang YA, 2009, ECON SYST RES, V21, P217, DOI 10.1080/09535310903541348
   Huang YA, 2009, ENVIRON SCI TECHNOL, V43, P8509, DOI 10.1021/es901643a
   ICLEI-Local Governments for Sustainability, 2008, LOC GOV OP PROT QUAN
   Igos E, 2015, APPL ENERG, V145, P234, DOI 10.1016/j.apenergy.2015.02.007
   Joshi S., 1999, Journal of Industrial Ecology, V3, P95, DOI DOI 10.1162/108819899569449
   Larsen HN, 2010, ECOL ECON, V70, P60, DOI 10.1016/j.ecolecon.2010.05.001
   Larsen HN, 2010, J IND ECOL, V14, P965, DOI 10.1111/j.1530-9290.2010.00295.x
   Lenzen M., 2002, J. Ind. Eco, V6, P137, DOI DOI 10.1162/108819802766269575
   Leontief W, 1986, INPUT OUTPUT EC
   Li JS, 2016, RENEW SUST ENERG REV, V53, P1602, DOI 10.1016/j.rser.2015.09.090
   Lin JY, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/5/054001
   Lin JY, 2013, ENERG POLICY, V58, P220, DOI 10.1016/j.enpol.2013.03.007
   Lindner S, 2014, J IND ECOL, V18, P201, DOI 10.1111/jiec.12119
   Liu Z, 2016, APPL ENERG, V166, P239, DOI 10.1016/j.apenergy.2015.11.005
   Liu Z, 2015, ECOL MODEL, V318, P118, DOI 10.1016/j.ecolmodel.2015.02.001
   Liu Z, 2012, ENERGY, V37, P245, DOI 10.1016/j.energy.2011.11.040
   Matthews HS, 2008, ENVIRON SCI TECHNOL, V42, P5839, DOI 10.1021/es703112w
   Meng FX, 2017, J ENVIRON ACCOUNT MA, V5, P71, DOI 10.5890/JEAM.2017.03.007
   Menzies GF, 2007, PROC INST CIV ENG-CO, V160, P135, DOI 10.1680/coma.2007.160.4.135
   Minx JC, 2011, ENVIRON SCI TECHNOL, V45, P9144, DOI 10.1021/es201497m
   Munksgaard J, 2001, ENERG POLICY, V29, P327, DOI 10.1016/S0301-4215(00)00120-8
   National Bureau of Statistics of China, 2008, 2007 INP OUTP TABL C
   Onat NC, 2014, BUILD ENVIRON, V72, P53, DOI 10.1016/j.buildenv.2013.10.009
   Peters G.P., 2006, ECON SYST RES, V18, P155, DOI DOI 10.1080/09535310600653008
   Peters GP, 2006, ECOL ECON, V59, P1, DOI 10.1016/j.ecolecon.2005.08.008
   Potting J, 2006, INT J LIFE CYCLE ASS, V11, P11, DOI 10.1065/lca2006.04.005
   Ramaswami A, 2017, NAT CLIM CHANGE, V7, P736, DOI [10.1038/nclimate3373, 10.1038/NCLIMATE3373]
   Satterthwaite D, 2008, ENVIRON URBAN, V20, P539, DOI 10.1177/0956247808096127
   Su B, 2015, APPL ENERG, V154, P13, DOI 10.1016/j.apenergy.2015.04.101
   Suh S, 2005, J CLEAN PROD, V13, P687, DOI 10.1016/j.jclepro.2003.04.001
   Tan XC, 2016, APPL ENERG, V162, P1345, DOI 10.1016/j.apenergy.2015.06.071
   Tan XC, 2011, PROCEDIA ENVIRON SCI, V5, P167, DOI 10.1016/j.proenv.2011.03.063
   Wang SG, 2018, APPL ENERG, V227, P353, DOI 10.1016/j.apenergy.2017.11.093
   Wang SG, 2017, APPL ENERG, V196, P208, DOI 10.1016/j.apenergy.2017.02.011
   Wang SG, 2016, APPL ENERG, V178, P773, DOI 10.1016/j.apenergy.2016.06.112
   Wiedmann T., 2007, A Definition of Carbon Footprint
   Wiedmann TO, 2016, J IND ECOL, V20, P676, DOI 10.1111/jiec.12346
   World Resources Institute, 2004, The greenhouse gas protocol: A corporate accounting and reporting standard, Vrevised ed.
   Xu XWH, 2018, J CLEAN PROD, V172, P529, DOI 10.1016/j.jclepro.2017.10.136
   Yang J, 2014, APPL ENERG, V122, P269, DOI 10.1016/j.apenergy.2014.02.034
   Yang J, 2014, RENEW SUST ENERG REV, V29, P499, DOI 10.1016/j.rser.2013.09.013
   Yang Y, 2018, ENVIRON MODELL SOFTW, V99, P52, DOI 10.1016/j.envsoft.2017.09.017
NR 64
TC 22
Z9 23
U1 1
U2 81
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 NOV 1
PY 2018
VL 229
BP 163
EP 175
DI 10.1016/j.apenergy.2018.07.109
PG 13
WC Energy & Fuels; Engineering, Chemical
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Energy & Fuels; Engineering
GA HA0IK
UT WOS:000449891500014
DA 2025-01-10
ER

PT J
AU Hellin, J
   Ratner, BD
   Meinzen-Dick, R
   Lopez-Ridaura, S
AF Hellin, Jon
   Ratner, Blake D.
   Meinzen-Dick, Ruth
   Lopez-Ridaura, Santiago
TI Increasing social-ecological resilience within small-scale agriculture
   in conflict-affected Guatemala
SO ECOLOGY AND SOCIETY
LA English
DT Article
DE agriculture; climate change; collective action; conflict; Guatemala;
   resilience
ID CLIMATE-CHANGE; WESTERN HIGHLANDS; COLLECTIVE ACTION; AGRARIAN CONFLICT;
   MAIZE DIVERSITY; ADAPTATION; LANDRACES; LANDSCAPE; COMMUNITY; SECURITY
AB Climate change scenarios suggest largely detrimental impacts on agricultural production from a deterioration of renewable natural resources. Over the last 15 years, a new field of research has focused on the interactions between climate and conflict risk, particularly as it relates to competition over natural resources and livelihoods. Within this field, there has been less attention to the potential for resource competition to be managed in ways that yield greater cooperation, local adaptation capacity, social-ecological resilience, and conflict mitigation or prevention. The challenge of increasing social-ecological resilience in small-scale agriculture is particularly acute in the socioeconomically and agroecologically marginalized Western Highlands of Guatemala. Not only is climate change a threat to agriculture in this region, but adaptation strategies are challenged by the context of a society torn apart by decades of violent conflict. Indeed, the largely indigenous population in the Western Highlands has suffered widespread discrimination for centuries. The armed conflict has left a legacy of a deeply divided society, with communities often suspicious of outsider interventions and in many cases with neighbors pitted against each other. We use the example of the Buena Milpa agricultural development project to demonstrate how grassroots approaches to collective action, conflict prevention, and social-ecological resilience, linking local stakeholder dynamics to the broader institutional and governance context, can bear fruit amidst postconflict development challenges. Examples of microwatershed management and conservation of local maize varieties illustrate opportunities to foster community-level climate adaptation strategies within small-scale farming systems even in deeply divided societies.
C1 [Hellin, Jon; Lopez-Ridaura, Santiago] Int Maize & Wheat Improvement Ctr CIMMYT, Texcoco, Mexico.
   [Hellin, Jon] Int Rice Res Inst IRRI, Philadelphia, PA USA.
   [Ratner, Blake D.] CGIAR, WorldFish, Montpellier, France.
   [Meinzen-Dick, Ruth] IFPRI, Washington, DC USA.
C3 CGIAR; International Maize & Wheat Improvement Center (CIMMYT); CGIAR;
   Worldfish; CGIAR; International Food Policy Research Institute (IFPRI)
RP Hellin, J (corresponding author), Int Maize & Wheat Improvement Ctr CIMMYT, Texcoco, Mexico.
OI Hellin, Jon/0000-0002-2686-8065; Meinzen-Dick, Ruth/0000-0003-4782-3074
FU United States Agency for International Development (USAID); CGIAR Fund;
   CGIAR Research Programs on Policies, Institutions and Markets (PIM)
FX We would like to acknowledge support provided by United States Agency
   for International Development (USAID) through its Global Hunger and Food
   Security Initiative, Feed the Future. This work was also implemented as
   part of 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#.WxqT_4onaUk), and the CGIAR
   Research Programs on Policies, Institutions and Markets (PIM). The views
   expressed in this document cannot be taken to reflect the official
   opinions of these organizations. The authors are also very grateful for
   the invaluable comments provided by two anonymous reviewers and Eleanor
   Fisher (University of Reading, UK).
CR Adger WN, 2013, NAT CLIM CHANGE, V3, P112, DOI [10.1038/NCLIMATE1666, 10.1038/nclimate1666]
   Adger WN, 2003, ECON GEOGR, V79, P387
   [Anonymous], 2006, GLOBAL ENVIRON CHANG, DOI [DOI 10.1007/s11027-013-9475-x, DOI 10.1016/j.gloenvcha.2005.10.004]
   [Anonymous], 2014, ENCUESTA MONITOREO E
   Barnett J, 2007, POLIT GEOGR, V26, P639, DOI 10.1016/j.polgeo.2007.03.003
   Barrett CB, 2014, P NATL ACAD SCI USA, V111, P14625, DOI 10.1073/pnas.1320880111
   Brown ME, 2008, SCIENCE, V319, P580, DOI 10.1126/science.1154102
   CIMMYT (International Maize and Wheat Improvement Center), 2017, MAIZ WHEAT FUT CLIMA
   Copeland N, 2011, J LAT AM STUD, V43, P485, DOI 10.1017/S0022216X11000411
   Democracy International, 2015, LEG EXCL SOC CONFL V
   Gleditsch NP, 2006, POLIT GEOGR, V25, P361, DOI 10.1016/j.polgeo.2006.02.004
   Grandin G, 1997, LAT AM PERSPECT, V24, P7, DOI 10.1177/0094582X9702400202
   Granovsky-Larsen S, 2013, J PEASANT STUD, V40, P325, DOI 10.1080/03066150.2013.777044
   Hanjra MA, 2010, FOOD POLICY, V35, P365, DOI 10.1016/j.foodpol.2010.05.006
   Hellin J, 2017, MT RES DEV, V37, P188, DOI 10.1659/MRD-JOURNAL-D-16-00065.1
   Hendrix CS, 2007, POLIT GEOGR, V26, P695, DOI 10.1016/j.polgeo.2007.06.006
   Higbee EC, 1947, GEOGR REV, V37, P177, DOI 10.2307/210767
   HOY DR, 1984, J DEV AREAS, V18, P161
   Institute of Development Studies, 2010, CHANG CONFL MOV IMP
   International Fund for Agricultural Development, 2011, EN POOR RUR PEOPL OV
   Isakson SR, 2014, J AGRAR CHANGE, V14, P347, DOI 10.1111/joac.12023
   Isakson SR, 2009, J PEASANT STUD, V36, P725, DOI 10.1080/03066150903353876
   Klepek J, 2012, INT J AGR SUSTAIN, V10, P117, DOI 10.1080/14735903.2012.641326
   Krznaric R., 2006, J HUMAN DEV, V7, P111, DOI DOI 10.1080/14649880500502144
   LOVELL WG, 1983, J HIST GEOGR, V9, P127, DOI 10.1016/0305-7488(83)90219-0
   Mathewson K, 2006, GEOFORUM, V37, P15, DOI 10.1016/j.geoforum.2005.01.009
   McAllister C, 2009, J PEASANT STUD, V36, P645, DOI 10.1080/03066150903143038
   Mercer KL, 2012, GLOBAL ENVIRON CHANG, V22, P495, DOI 10.1016/j.gloenvcha.2012.01.003
   Mercer KL, 2010, EVOL APPL, V3, P480, DOI 10.1111/j.1752-4571.2010.00137.x
   Milen D., 2011, Vulnerability, Risk Reduction and Adaption to Climate Change Viet Nam, Climate Change and Adaption Country Profile
   Municipalidad de Todos Santos Cuchumatan, 2016, PLAN MAESTR PARQ REG
   Ortiz R, 2015, ENLACE, V28, P42
   Ostrom E, 2005, UNDERSTANDING INSTITUTIONAL DIVERSITY, P1
   Ratner BD, 2017, INT J COMMONS, V11, P877, DOI 10.18352/ijc.768
   Ratner BD, 2013, INT J COMMONS, V7, P183, DOI 10.18352/ijc.276
   Scheffran J, 2012, SCIENCE, V336, P869, DOI 10.1126/science.1221339
   Steinberg M, 2007, MT RES DEV, V27, P318, DOI 10.1659/mrd.0948
   Steinberg MK, 2002, MT RES DEV, V22, P344, DOI 10.1659/0276-4741(2002)022[0344:TIOPTO]2.0.CO;2
   Taylor MJ, 2006, GEOFORUM, V37, P41, DOI 10.1016/j.geoforum.2004.12.002
   Thornton PK, 2009, GLOBAL ENVIRON CHANG, V19, P54, DOI 10.1016/j.gloenvcha.2008.08.005
   Tyndale W, 2006, MT RES DEV, V26, P315, DOI 10.1659/0276-4741(2006)26[315:MACST]2.0.CO;2
   United States Agency for International Development (USAID), 2017, AN BRIEF EC AN DAT
   van Etten J, 2006, J HIST GEOGR, V32, P689, DOI 10.1016/j.jhg.2005.12.002
   van Leeuwen M, 2010, J LAT AM STUD, V42, P91, DOI 10.1017/S0022216X10000064
   Vermeulen SJ, 2013, P NATL ACAD SCI USA, V110, P8357, DOI 10.1073/pnas.1219441110
   Walker B, 2004, ECOL SOC, V9
   Wayland J, 2016, EXTRACT IND SOC, V3, P395, DOI 10.1016/j.exis.2016.03.001
   Wittman HK, 2008, LAND DEGRAD DEV, V19, P178, DOI 10.1002/ldr.832
NR 48
TC 39
Z9 43
U1 8
U2 43
PU RESILIENCE ALLIANCE
PI WOLFVILLE
PA ACADIA UNIV, BIOLOGY DEPT, WOLFVILLE, NS B0P 1X0, CANADA
SN 1708-3087
J9 ECOL SOC
JI Ecol. Soc.
PY 2018
VL 23
IS 3
AR 5
DI 10.5751/ES-10250-230305
PG 11
WC Ecology; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA GV7PN
UT WOS:000446321000020
OA gold
DA 2025-01-10
ER

PT J
AU Bajpai, A
   Muthukumar, M
   Singh, A
   Nath, V
   Ravishankar, H
AF Bajpai, Anju
   Muthukumar, M.
   Singh, Awtar
   Nath, Vishal
   Ravishankar, H.
TI Narrow genetic base of Indian litchi (<i>Litchi chinensis</i>) cultivars
   based on molecular markers
SO INDIAN JOURNAL OF AGRICULTURAL SCIENCES
LA English
DT Article
DE Genetic diversity; ISSR; Phylogenetic analysis; RAPD; SSR barcode
ID SSR MARKERS; IDENTIFICATION; DIVERSITY; RAPD
AB Litchi (Litchi chinensis Sonn.) is an introduced crop in India and has limited genetic variability characterized by differences in flushing pattern, leaf, panicle and fruit traits. Molecular markers were employed to expose the genetic diversity of 20 litchi cultivars from the Indian peninsula and facilitate documentation of the native germplasm diversity. Efficiency of individual primers was evaluated on the basis of average band informativeness and resolving power, where random oligonucleotide markers OPA-5 and OPA-3 scored best. Among tested microsatellite markers, ISSR 01 and 13 had high values for primer efficiency and these were found to supplement simple sequence repeats for generation of cultivar barcode and clustering analyses. Efficiency of microsatellites (Simple Sequence Repeats and Inter Simple Sequence Repeats) was established by high values for polymorphism (0.691), diversity index (0.264), effective multiplex ratio (48.8470) and marker index (12.896), thus reiterating its potential as for developing barcodes for cultivar identification and conservation. Phylogenetic analysis based on RAPD and microsatellites revealed clustering of the cultivars into four major groups, although within a very narrow range (0.63 - 0.90) of similarity, viz. Seedless (i.e. Bedana), Mandarji, Shahi and China groups. The clustering followed grouping based on fruit morphology, leaf and panicle attributes disagreeing with earlier views regarding incongruity of clustering pattern with morphological, ecological and climatic adaptations. Discrimination of cultivars like Dehrarose and Dehradun, being often labeled as synonyms, was also done. Interestingly high polymorphism and low gene diversity have been exposed by molecular markers, commenting on narrow genetic background of litchi cultivars from India.
C1 [Bajpai, Anju; Muthukumar, M.; Singh, Awtar; Nath, Vishal; Ravishankar, H.] ICAR Cent Inst Subtrop Hort, Lucknow 226101, Uttar Pradesh, India.
   [Singh, Awtar] IARI, Div Fruits & Hort Technol, New Delhi 110012, India.
   [Nath, Vishal] ICAR Natl Res Ctr Litchi, Muzaffarpur 842002, Bihar, India.
   [Ravishankar, H.] ICAR IIHR, Bengaluru 560089, Karnataka, India.
C3 Indian Council of Agricultural Research (ICAR); ICAR - Central Institute
   of Subtropical Horticulture; Indian Council of Agricultural Research
   (ICAR); Indian Council of Agricultural Research (ICAR); ICAR - National
   Research Centre for Litchi; Indian Council of Agricultural Research
   (ICAR); ICAR - Indian Institute of Horticultural Research
RP Bajpai, A (corresponding author), ICAR Cent Inst Subtrop Hort, Lucknow 226101, Uttar Pradesh, India.
EM anju.bajai@gmail.com
FU ICAR-National Research Centre for Litchi, Muzaffarpur; ICAR-Central
   Institute for Subtropical Horticulture, Lucknow
FX The authors thank the Directors of ICAR-National Research Centre for
   Litchi, Muzaffarpur, and ICAR-Central Institute for Subtropical
   Horticulture, Lucknow for supporting this collaborative research.
CR Anju Bajpai Anju Bajpai, 2008, Indian Journal of Horticulture, V65, P377
   Bajpai A, 2008, INDIAN J GENET PL BR, V68, P441
   Chen YeYuan Chen YeYuan, 2004, Acta Horticulturae Sinica, V31, P224
   Dwivedi A. K., 1995, Horticultural Journal, V8, P113
   Galbacs Z, 2009, VITIS, V48, P17
   Jones M, 2006, PLANT AN MICR GEN C, V89, P223
   KUMAR S, 2012, PLANT ARCH, V12, P1109
   Li MF, 2006, MOL ECOL NOTES, V6, P1205, DOI 10.1111/j.1471-8286.2006.01492.x
   Madhou M, 2013, TREE GENET GENOMES, V9, P387, DOI 10.1007/s11295-012-0560-1
   Madhou M, 2010, FRUITS, V65, P141, DOI 10.1051/fruits/2010009
   Milbourne D, 1997, MOL BREEDING, V3, P127, DOI 10.1023/A:1009633005390
   Pathak AK, 2014, J AM SOC HORTIC SCI, V139, P657, DOI 10.21273/JASHS.139.6.657
   Prevost A, 1999, THEOR APPL GENET, V98, P107, DOI 10.1007/s001220051046
   Sharp PJ, 2001, NUCLEIC ACIDS RES, V29, P1
   Singh H.P., 2002, Lychee Production in the Asia-Pacific Region, P55
   Sun QingMing Sun QingMing, 2011, Scientia Agricultura Sinica, V44, P4037
   Tongpamnak P., 2002, Kasetsart Journal, Natural Sciences, V36, P370
   VanBuren R., 2011, Tropical Plant Biology, V4, P228, DOI 10.1007/s12042-011-9084-3
   Viruel MA, 2004, THEOR APPL GENET, V108, P896, DOI 10.1007/s00122-003-1497-4
   Wu YL, 2007, SCI HORTIC-AMSTERDAM, V114, P143, DOI 10.1016/j.scienta.2007.07.016
   Yi GanJun Yi GanJun, 2003, Acta Horticulturae Sinica, V30, P399
   Yonemoto Y, 2006, SCI HORTIC-AMSTERDAM, V109, P147, DOI 10.1016/j.scienta.2006.04.003
   [昝逢刚 Zan Fenggang], 2009, [分子植物育种, Molecular Plant Breeding], V7, P562
NR 23
TC 3
Z9 3
U1 0
U2 4
PU INDIAN COUNC AGRICULTURAL RES
PI NEW DELHI
PA KAB-1, NEW DELHI 110012, INDIA
SN 0019-5022
EI 2394-3319
J9 INDIAN J AGR SCI
JI Indian J. Agric. Sci.
PD APR
PY 2016
VL 86
IS 4
BP 448
EP 455
PG 8
WC Agriculture, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA DK0RL
UT WOS:000374619800004
DA 2025-01-10
ER

PT S
AU Tchebakova, NM
   Parfenova, EI
   Soja, AJ
AF Tchebakova, Nadezhda M.
   Parfenova, Elena I.
   Soja, Amber J.
BE Mueller, L
   Sheudshen, AK
   Eulenstein, F
TI Significant Siberian Vegetation Change is Inevitably Brought on by the
   Changing Climate
SO NOVEL METHODS FOR MONITORING AND MANAGING LAND AND WATER RESOURCES IN
   SIBERIA
SE Springer Water
LA English
DT Article; Book Chapter
DE Vegetation; Siberia; Climate change; Scenario
ID MODEL
AB The redistribution of terrestrial ecosystems and individual species is predicted to be profound under Global Climate Model simulations. We modeled the progression of potential vegetation and forest types in Siberia by the end of the twenty-first century by coupling large-scale bioclimatic models of vegetation zones and major conifer species with climatic variables and permafrost using the B1 and A2 Hadley Centre HadCM3 climate change scenarios. In the projected warmer and dryer climate, Siberian taiga forests are predicted to dramatically decrease and shift to the northeast, and forest-steppe, steppe, and novel temperate broadleaf forests are predicted to dominate most of Siberia by 2090. The permafrost should not retreat sufficiently to provide favorable habitats for dark (Pinus sibiric, Abies sibirica, and Picea obovata) taiga, and the permafrost-tolerant L. dahurica taiga should remain the dominant forest type in many current permafrost-lain areas. Water stress and fire-tolerant tree species (Pinus sylvestris and Larix spp.) should have an increased advantage over moisture-loving tree species (P. sibirica, A. sibirica, and P. obovata) in a new climate. Accumulated surface fuel loads due to increased tree mortality from drought, insects, and other factors, especially at the southern forest border and in the Siberian interior (Yakutia), together with an increase in severe fire weather, should also lead to increases in large, high-severity fires that are expected to facilitate vegetation progression toward a new equilibrium with the climate. Adaptation of the forest types and tree species to climate change in the south may be based on the genetic means of individual species and human willingness to aid migration, perhaps by seeding. Additionally, useful and viable crops could be established in agricultural lands instead of failing forests.
C1 [Tchebakova, Nadezhda M.; Parfenova, Elena I.] Russian Acad Sci, VN Sukachev Inst Forest, Siberian Branch SIF SB RAS, Akademgorodok 50-28, Krasnoyarsk 660036, Russia.
   [Soja, Amber J.] NASA, Langley Res Ctr, 21 Langley Blvd,Mail Stop 420, Hampton, VA 23681 USA.
C3 Russian Academy of Sciences; Krasnoyarsk Science Center of the Siberian
   Branch of the Russian Academy of Sciences; Sukachev Institute of Forest,
   Siberian Branch, Russian Academy of Sciences; National Aeronautics &
   Space Administration (NASA); NASA Langley Research Center
RP Tchebakova, NM (corresponding author), Russian Acad Sci, VN Sukachev Inst Forest, Siberian Branch SIF SB RAS, Akademgorodok 50-28, Krasnoyarsk 660036, Russia.
EM ncheby@ksc.krasn.ru; lyeti@ksc.krasn.ru; Amber.J.Soja@nasa.gov
RI Parfenova, Elena/T-5101-2017; Tchebakova, Nadezhda/H-1987-2016
CR Abaimov A P, 2002, J FOREST RES, V5, P95
   [Anonymous], FOREST ECOSYSTEMS YE
   [Anonymous], RUSS J METEOROL HYDR
   [Anonymous], 1974, Climate and Life
   [Anonymous], 2014, CLIMATE CHANGE 2014, V80, P1
   [Anonymous], RUSS J METEOROL HYDR
   [Anonymous], REGIONAL ENV CHANGES
   [Anonymous], 2006, COMPUTING TECHNOLOGY
   [Anonymous], RUSS J MET HYDROL
   [Anonymous], 1981, J APPL ECOL
   Bazhenova OI, 2003, GEOGR NAT RESOUR, V4, P51
   Dokuchaev VV, 1899, STUDIES NATURAL ZONE
   DOSTAVALOV BN, 1967, BASIC PERMAFROST SCI
   Gerasimchuk IV, 2011, ASSESSMENT REPORT CL, P94
   Gruza GV., 2004, METEOROLOGY HYDROLOG, V4, P50
   Hogg EH, 1997, AGR FOREST METEOROL, V84, P115, DOI 10.1016/S0168-1923(96)02380-5
   Hutchinson M. F., 2000, ANUSPLIN VERSION 4 1
   Ivanov NN, 1954, ALL UNION GEOGR SOC, V86, P189
   Kharuk VI, 2005, RUSS J ECOL+, V36, P164, DOI 10.1007/s11184-005-0055-5
   Kirilenko AP, 1998, CLIMATIC CHANGE, V38, P15, DOI 10.1023/A:1005379630126
   Kukavskaya EA, 2013, CAN J FOREST RES, V43, P493, DOI 10.1139/cjfr-2012-0367
   Lawrence DM, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL025080
   Malevsky-Malevich SP, 2001, COLD REG SCI TECHNOL, V32, P1, DOI 10.1016/S0165-232X(01)00018-0
   Maximov T.C., 2007, THESIS
   MONSERUD RA, 1992, ECOL MODEL, V62, P275, DOI 10.1016/0304-3800(92)90003-W
   Nazimova DI, 2006, RUSSIAN J FOREST SCI, V1, P1
   Peng CH, 2000, ECOL MODEL, V135, P33, DOI 10.1016/S0304-3800(00)00348-3
   Polikarpov N. P., 1998, RUSS J FOREST SCI, V5, P3
   Polikarpov N.P., 1986, Climate and Mountain Forests of South Siberia
   Popov PP, 1980, EUROPEAN SIBERIAN SP
   Pozdnyakov LK, 1993, FOREST ON PERMAFROST
   PRENTICE IC, 1992, J BIOGEOGR, V19, P117, DOI 10.2307/2845499
   Rehfeldt GE, 2002, GLOBAL CHANGE BIOL, V8, P912, DOI 10.1046/j.1365-2486.2002.00516.x
   Rehfeldt GE, 1999, CAN J FOREST RES, V29, P1660, DOI 10.1139/cjfr-29-11-1660
   Shugart HH, 1991, SYSTEMS ANAL GLOBAL, P565
   Shumilova L.V., 1962, Botanical Geography of Siberia
   Shvidenko AZ, 2011, DOKL EARTH SCI, V441, P1678, DOI 10.1134/S1028334X11120075
   Soja AJ, 2007, GLOBAL PLANET CHANGE, V56, P274, DOI 10.1016/j.gloplacha.2006.07.028
   SOKOLOV SI, 1977, TREE SHRUB RANGES US
   [Solomon S. IPCC IPCC], 2007, CLIMATE CHANGE 2007
   Stephenson NL, 1998, J BIOGEOGR, V25, P855, DOI 10.1046/j.1365-2699.1998.00233.x
   Tchebakova NM, 2011, REG ENVIRON CHANGE, V11, P817, DOI 10.1007/s10113-011-0210-4
   Tchebakova NM, 2010, ECOL STUD-ANAL SYNTH, V209, P427, DOI 10.1007/978-1-4020-9693-8_22
   Tchebakova NM, 2009, ENVIRON RES LETT, V4, DOI 10.1088/1748-9326/4/4/045013
   Tchebakova N M., 2003, Siberian Ecol J, V6, P677
   Tchebakova NM, 2012, BOSQUE, V33, P253, DOI 10.4067/S0717-92002012000300004
   Tchebakova NM, 2016, SPRINGER WATER, P287, DOI 10.1007/978-3-319-24409-9_11
   Thornthwaite CW, 1948, GEOGR REV, V38, P55, DOI 10.2307/210739
   VELICHKO AA, 1992, DOKL AKAD NAUK+, V324, P667
   Vygodskaya NN, 2007, ENVIRON RES LETT, V2, DOI 10.1088/1748-9326/2/4/045033
   Walter H., 1985, Vegetation of the earth and ecological systems of the geobiosphere, V3rd
NR 51
TC 7
Z9 7
U1 0
U2 5
PU SPRINGER INTERNATIONAL PUBLISHING AG
PI CHAM
PA GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
SN 2364-6934
EI 2364-8198
BN 978-3-319-24409-9; 978-3-319-24407-5
J9 SPRINGER WATER
PY 2016
BP 269
EP 285
DI 10.1007/978-3-319-24409-9_10
D2 10.1007/978-3-319-24409-9
PG 17
WC Environmental Sciences; Soil Science; Water Resources
WE Book Citation Index – Science (BKCI-S)
SC Environmental Sciences & Ecology; Agriculture; Water Resources
GA BF9BQ
UT WOS:000385421600011
DA 2025-01-10
ER

PT J
AU de Abreu-Harbicha, LV
   Labakia, LC
   Matzarakis, A
AF de Abreu-Harbicha, Loyde Vieira
   Labakia, Lucila Chebel
   Matzarakis, Andreas
TI Effect of tree planting design and tree species on human thermal comfort
   in the tropics
SO LANDSCAPE AND URBAN PLANNING
LA English
DT Article
DE Human thermal comfort; Physiologically equivalent temperature; Mean
   radiant temperature; Tree planting design; Tropical climate; Brazil
   (Campinas)
ID URBAN-ENVIRONMENT; CLIMATE; CITY; VEGETATION; FOREST; STREET
AB Trees behave in different ways on microclimate due to mainly distinct features of each species and planting strategies especially in the tropics. This paper quantifies the daily and seasonal microclimate behavior of various tree species with different planting design either individual or in clusters. This specific knowledge is an important step in the development of urban design guidelines based on the shading of trees and climate adaptation in urban areas in the tropics. It focuses on human thermal comfort based on the physiologically equivalent temperature (PET) for different species. Twelve species were analyzed: Handroanthus chrysotrichus (Mart. ex A.DC.) Mattos, Jacaranda mimosaefolia D. Don., Syzygium cumini L, Mangifera indica L, Pinus palustris L, Pinus coulteri L.; Lafoensia glyptocarpa L, Caesalpinia pluviosa F., Spathodea campanulata P. Beauv., Tipuana tipu F., Delonix indica F. and Senna siamea L. The results show that shading of trees can influence significantly human thermal comfort expressed by (PET). The species C. pluviosa F. presents the best possibility in terms of PET because it can reduce between 12 and 16 C for individual trees cluster can reduce between 12.5 and 14.5 degrees C. Appropriate vegetation used for shading public and private areas is essential to mitigate heat stress and can create better human thermal comfort especially in cities. The results can be seen as a possibility of improvement of outdoor thermal comfort conditions and as an important step in order to achieve sustainability in cities. (C) 2015 Elsevier B.V. All rights reserved.
C1 [de Abreu-Harbicha, Loyde Vieira; Labakia, Lucila Chebel] Univ Estadual Campinas, Sch Civil Engn Architecture & Urban Design, BR-13083850 Campinas, Brazil.
   [Matzarakis, Andreas] Univ Freiburg, Fac Environm & Nat Resource, D-79085 Freiburg, Germany.
C3 Universidade Estadual de Campinas; University of Freiburg
RP de Abreu-Harbicha, LV (corresponding author), Univ Estadual Campinas, Sch Civil Engn Architecture & Urban Design, Rua Saturnino Brito 224, BR-13083850 Campinas, Brazil.
EM loydeabreu@gmail.com
RI Matzarakis, Andreas/AAO-2676-2021; Matzarakis, Andreas/E-4738-2012;
   Labaki, Lucila/B-8192-2012; Abreu-Harbich, Loyde Vieira de/G-9093-2012
OI Matzarakis, Andreas/0000-0003-3076-555X; Labaki,
   Lucila/0000-0002-6811-0252; Abreu-Harbich, Loyde Vieira
   de/0000-0003-0153-4509
FU Sao Paulo Research Foundation (FAPESP) [08/05870-5]; National Counsel of
   Technological and Scientific Development (CNPq) [311641/2013-0];
   Coordination for the Improvement of Higher Education Personnel (CAPES)
   [BEX 4234/10-3]; German Academic Exchange Service (DAAD) [BEX
   4234/10-3]; Fundacao de Amparo a Pesquisa do Estado de Sao Paulo
   (FAPESP) [08/05870-5] Funding Source: FAPESP
FX This research was supported by Sao Paulo Research Foundation (FAPESP)
   research grant (08/05870-5), National Counsel of Technological and
   Scientific Development (CNPq) research grant (311641/2013-0), and
   research cooperation between Coordination for the Improvement of Higher
   Education Personnel (CAPES) and German Academic Exchange Service (DAAD)
   research grant (BEX 4234/10-3).
CR Abreu-Harbich L. V., 2012, P INT C PASS LOW EN
   Abreu-Harbich L. V., 2013, URBAN ECOSYSTEMS
   Abreu-Harbich LV, 2014, THEOR APPL CLIMATOL, V115, P333, DOI 10.1007/s00704-013-0886-0
   AKBARI H, 1992, ENERGY, V17, P141, DOI 10.1016/0360-5442(92)90063-6
   Akbari H, 2002, ENVIRON POLLUT, V116, pS119, DOI 10.1016/S0269-7491(01)00264-0
   Akbari H., 1996, 76 AM MET SOC ANN M
   Akbari H., 2008, J. Hum. Environ. Syst., V11, P85, DOI DOI 10.1618/JHES.11.85
   [Anonymous], HDB UMWELTVERANDERUN
   [Anonymous], 1998, 3787 VDI  1
   Bernatzky A., 1979, DBZ FORSCHUNG PRAXIS, P1205
   Brown RD., 1995, MICROCLIMATIC LANDSC
   Bueno-Bartholomei C. L., 2003, 5 INT C URB CLIM
   CARDELINO CA, 1990, J GEOPHYS RES-ATMOS, V95, P13971, DOI 10.1029/JD095iD09p13971
   Correa E, 2012, BUILD ENVIRON, V58, P219, DOI 10.1016/j.buildenv.2012.06.007
   Dimoudi A, 2003, ENERG BUILDINGS, V35, P69, DOI 10.1016/S0378-7788(02)00081-6
   Emmanuel M. R., 2005, URBAN APPROACH CLIMA
   Emmanuel R, 2007, INT J CLIMATOL, V27, P1995, DOI 10.1002/joc.1609
   Grimmond S, 2007, GEOGR J, V173, P83, DOI 10.1111/j.1475-4959.2007.232_3.x
   Gulyás A, 2006, BUILD ENVIRON, V41, P1713, DOI 10.1016/j.buildenv.2005.07.001
   Heisler G. M., 1977, Journal of Arboriculture, V3, P201
   Herrington L. P., 1977, P SOC AM FORESTERS, P20
   Holst T, 2004, INT J BIOMETEOROL, V48, P192, DOI 10.1007/s00484-004-0201-y
   Höppe P, 1999, INT J BIOMETEOROL, V43, P71, DOI 10.1007/s004840050118
   HOPPE PR, 1993, EXPERIENTIA, V49, P741
   Kjelgren R, 1998, ATMOS ENVIRON, V32, P35, DOI 10.1016/S1352-2310(97)00177-5
   Kottek M, 2006, METEOROL Z, V15, P259, DOI 10.1127/0941-2948/2006/0130
   Lin TP, 2008, INT J BIOMETEOROL, V52, P281, DOI 10.1007/s00484-007-0122-7
   Lin TP, 2010, BUILD ENVIRON, V45, P213, DOI 10.1016/j.buildenv.2009.06.002
   Matzarakis A, 2013, GEFAHRST REINHALT L, V73, P115
   Matzarakis A., 1996, WHO NEWS, V18, P7
   Matzarakis A, 2007, INT J BIOMETEOROL, V51, P323, DOI 10.1007/s00484-009-0261-0
   Matzarakis Andreas, 2010, Int J Biometeorol, V54, P479, DOI 10.1007/s00484-009-0296-2
   MAYER H, 1993, EXPERIENTIA, V49, P957, DOI 10.1007/BF02125642
   MAYER H, 1987, THEOR APPL CLIMATOL, V38, P43, DOI 10.1007/BF00866252
   Mayer JD, 2008, AM PSYCHOL, V63, P503, DOI 10.1037/0003-066X.63.6.503
   McPherson E.G., 1994, CHICAGOS URBAN FORES
   Meyer F. H., 1982, TREES CITY BAUME STA
   Monteiro L. M., 2010, 3 PASS LOW EN COOL B
   Nackaerts K, 2000, AGR FOREST METEOROL, V101, P247, DOI 10.1016/S0168-1923(00)00090-3
   NEUMANN HH, 1989, AGR FOREST METEOROL, V45, P325, DOI 10.1016/0168-1923(89)90052-X
   Nunes L. H., 1997, THESIS U SAO PAULO
   OKE TR, 1989, PHILOS T ROY SOC B, V324, P335, DOI 10.1098/rstb.1989.0051
   Santamouris M., 2001, ENERGY CLIMATE URBAN
   Scudo G., 2002, GREEN STRUCTURES URB
   Shahidan MF, 2010, LANDSCAPE URBAN PLAN, V97, P168, DOI 10.1016/j.landurbplan.2010.05.008
   Shashua-Bar L, 2000, ENERG BUILDINGS, V31, P221, DOI 10.1016/S0378-7788(99)00018-3
   Shashua-Bar L, 2010, INT J CLIMATOL, V30, P44, DOI 10.1002/joc.1869
   Shashua-Bar L, 2009, LANDSCAPE URBAN PLAN, V92, P179, DOI 10.1016/j.landurbplan.2009.04.005
   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]
   STEVEN MD, 1986, FIELD CROP RES, V13, P75, DOI 10.1016/0378-4290(86)90012-2
   Streiling S., 2003, Journal of Arboriculture, V29, P309
   Tsutsumi J. G., 2003, 5 INT C URB CLIM LOD
   Yilmaz S, 2007, BUILD ENVIRON, V42, P1604, DOI 10.1016/j.buildenv.2006.01.017
NR 53
TC 295
Z9 310
U1 14
U2 278
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 99
EP 109
DI 10.1016/j.landurbplan.2015.02.008
PG 11
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:000355023000010
HC Y
HP N
DA 2025-01-10
ER

PT J
AU Koyama, T
   Ito, H
   Kakishima, S
   Yoshimura, J
   Cooley, JR
   Simon, C
   Sota, T
AF Koyama, T.
   Ito, H.
   Kakishima, S.
   Yoshimura, J.
   Cooley, J. R.
   Simon, C.
   Sota, T.
TI Geographic body size variation in the periodical cicadas
   <i>Magicicada</i>: implications for life cycle divergence and local
   adaptation
SO JOURNAL OF EVOLUTIONARY BIOLOGY
LA English
DT Article
DE clinal variation; converse Bergmann cline; geographic variation; sexual
   dimorphism
ID REPRODUCTIVE CHARACTER DISPLACEMENT; CLIMATIC ADAPTATION; RAPID
   EVOLUTION; 13-YEAR; SELECTION; 17-YEAR; CLINES; DIFFERENTIATION;
   SPECIATION; HEMIPTERA
AB Seven species in three species groups (Decim, Cassini and Decula) of periodical cicadas (Magicicada) occupy a wide latitudinal range in the eastern United States. To clarify how adult body size, a key trait affecting fitness, varies geographically with climate conditions and life cycle, we analysed the relationships of population mean head width to geographic variables (latitude, longitude, altitude), habitat annual mean temperature (AMT), life cycle and species differences. Within species, body size was larger in females than males and decreased with increasing latitude (and decreasing habitat AMT), following the converse Bergmann's rule. For the pair of recently diverged 13- and 17-year species in each group, 13-year cicadas were equal in size or slightly smaller on average than their 17-year counterparts despite their shorter developmental time. This fact suggests that, under the same climatic conditions, 17-year cicadas have lowered growth rates compared to their 13-years counterparts, allowing 13-year cicadas with faster growth rates to achieve body sizes equivalent to those of their 17-year counterparts at the same locations. However, in the Decim group, which includes two 13-year species, the more southerly, anciently diverged 13-year species (Magicicada tredecim) was characterized by a larger body size than the other, more northerly 13- and 17-year species, suggesting that local adaptation in warmer habitats may ultimately lead to evolution of larger body sizes. Our results demonstrate how geographic clines in body size may be maintained in sister species possessing different life cycles.
C1 [Koyama, T.; Sota, T.] Kyoto Univ, Grad Sch Sci, Dept Zool, Kyoto 6068502, Japan.
   [Ito, H.; Kakishima, S.; Yoshimura, J.] Shizuoka Univ, Grad Sch Sci & Technol, Hamamatsu, Shizuoka 4328011, Japan.
   [Yoshimura, J.] SUNY Coll Environm Sci & Forestry, Dept Environm & Forest Biol, Syracuse, NY 13210 USA.
   [Yoshimura, J.] Chiba Univ, Marine Biosyst Res Ctr, Chiba, Japan.
   [Cooley, J. R.; Simon, C.] Univ Connecticut, Dept Ecol & Evolutionary Biol, Storrs, CT USA.
C3 Kyoto University; Shizuoka University; State University of New York
   (SUNY) System; State University of New York (SUNY) College of
   Environmental Science & Forestry; Chiba University; University of
   Connecticut
RP Sota, T (corresponding author), Kyoto Univ, Grad Sch Sci, Dept Zool, Kyoto 6068502, Japan.
EM sota@terra.zool.kyoto-u.ac.jp
RI Kakishima, Satoshi/IZD-4587-2023
OI Kakishima, Satoshi/0000-0001-6000-3068; Ito, Hiromu/0000-0001-9350-0546;
   Cooley, John/0000-0002-3691-2592
FU JSPS KAKENHI [22255004, 22370010, 26257405, 15H00420]; NSF [DEB
   09-55849]; Grants-in-Aid for Scientific Research [25257406, 25440217,
   15H04420, 13J03600, 14J02983, 26257405, 26840126, 15H00420] Funding
   Source: KAKEN
FX We thank H. Ikeda and D. Suzuki for sampling and W. Blanckenhorn for
   helpful comments on our manuscript. This study was supported by JSPS
   KAKENHI (no. 22255004, 22370010, 26257405 and 15H00420 to JY) and
   grants-in-aid for JSPS Fellows to HI and SK. CS and JRC received support
   from NSF DEB 09-55849.
CR [Anonymous], U MICH MUS ZOOL MISC
   BENNETCLARK HC, 1994, J EXP BIOL, V191, P291
   Blanckenhorn WU, 2004, INTEGR COMP BIOL, V44, P413, DOI 10.1093/icb/44.6.413
   Cooley JR, 2013, GLOBAL ECOL BIOGEOGR, V22, P410, DOI 10.1111/geb.12002
   Cooley John R., 2009, American Entomologist, V55, P106
   Cooley JR, 2001, MOL ECOL, V10, P661, DOI 10.1046/j.1365-294x.2001.01210.x
   Gilchrist GW, 2001, GENETICA, V112, P273, DOI 10.1023/A:1013358931816
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Huey RB, 2000, SCIENCE, V287, P308, DOI 10.1126/science.287.5451.308
   KARBAN R, 1983, AM MIDL NAT, V109, P324, DOI 10.2307/2425413
   Karban R, 1997, AM NAT, V150, P446, DOI 10.1086/286075
   Kivelä SM, 2011, J ANIM ECOL, V80, P1184, DOI 10.1111/j.1365-2656.2011.01864.x
   LLOYD M, 1966, EVOLUTION, V20, P466, DOI 10.1111/j.1558-5646.1966.tb03381.x
   Maier C. T., 1996, Frontiers of Plant Science, V48, P4
   Marlatt C. L., 1907, U S Department of Agriculture Bureau of Entomology Bulletin, VNo. 71
   Marshall DC, 2000, EVOLUTION, V54, P1313, DOI 10.1111/j.0014-3820.2000.tb00564.x
   MARTIN AP, 1988, NATURE, V336, P237, DOI 10.1038/336237a0
   MASAKI S, 1972, EVOLUTION, V26, P587, DOI 10.1111/j.1558-5646.1972.tb01966.x
   MASAKI S, 1967, EVOLUTION, V21, P725, DOI 10.1111/j.1558-5646.1967.tb03430.x
   Oberdörster U, 2007, BIOL J LINN SOC, V90, P15, DOI 10.1111/j.1095-8312.2007.00701.x
   Okuzaki Y, 2010, J ANIM ECOL, V79, P383, DOI 10.1111/j.1365-2656.2009.01645.x
   Paradis E, 2004, BIOINFORMATICS, V20, P289, DOI [10.1093/bioinformatics/btg412, 10.1093/bioinformatics/bty633]
   R Development Core Team, 2012, R: a language and environment for statistical computing
   ROFF D, 1980, OECOLOGIA, V45, P202, DOI 10.1007/BF00346461
   Simon C, 2000, EVOLUTION, V54, P1326
   SIMON C, 1983, EVOLUTION, V37, P104, DOI [10.2307/2408179, 10.1111/j.1558-5646.1983.tb05519.x]
   Simon Chris, 1992, P309
   Sota T, 2000, POPUL ECOL, V42, P279, DOI 10.1007/PL00012006
   Sota T, 2013, P NATL ACAD SCI USA, V110, P6919, DOI 10.1073/pnas.1220060110
   Sota Teiji, 2000, Entomological Science, V3, P309
   Tanaka Y, 2009, P NATL ACAD SCI USA, V106, P8975, DOI 10.1073/pnas.0900215106
   WHITE JA, 1975, AM MIDL NAT, V94, P127, DOI 10.2307/2424544
   Yoshimura J, 2009, EVOLUTION, V63, P288, DOI 10.1111/j.1558-5646.2008.00545.x
NR 33
TC 15
Z9 16
U1 2
U2 58
PU OXFORD UNIV PRESS
PI OXFORD
PA GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND
SN 1010-061X
EI 1420-9101
J9 J EVOLUTION BIOL
JI J. Evol. Biol.
PD JUN
PY 2015
VL 28
IS 6
BP 1270
EP 1277
DI 10.1111/jeb.12653
PG 8
WC Ecology; Evolutionary Biology; Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Evolutionary Biology; Genetics &
   Heredity
GA CL0ID
UT WOS:000356624200008
PM 25975714
OA Bronze
DA 2025-01-10
ER

PT C
AU van Baaren, J
   Le Lann, C
   van Alphen, JJM
AF van Baaren, Joan
   Le Lann, Cecile
   van Alphen, Jacques J. M.
BE Kindlmann, P
   Dixon, AFG
   Michaud, JP
TI Consequences of Climate Change for Aphid-Based Multi-trophic Systems
SO APHID BIODIVERSITY UNDER ENVIRONMENTAL CHANGE: PATTERNS AND PROCESSES
LA English
DT Proceedings Paper
CT 7th International Symposium on Aphids
CY OCT 02-07, 2005
CL Freemantle, AUSTRALIA
DE Climate change; Parasitoids; Aphidiidae; Aphelinidae; Multitrophic
   interactions; Life history traits; Distribution; Phenology
ID ELEVATED CO2; CEREAL APHIDS; LIFE-HISTORY; MATRICARIAE HYMENOPTERA;
   ACYRTHOSIPHON-PISUM; HOST-PLANT; PEA APHID; PARASITOIDS; TEMPERATURE;
   GOSSYPII
AB Climatic models predict a 1.7-4.9 degrees C increase in mean global temperatures from 1990 to 2100. In ecosystems in general, multitrophic interactions often result from a long co-evolutionary process specific to a particular environment and relatively stable climatic conditions. Temperature changes may differentially affect the biology of each of the component species of a system: for example, the herbivores, their natural enemies (parasitoids, predators and pathogens), and hyperparasitoids. The endosymbionts of these different insects are also affected, and their functions can be altered by temperature increase. Such effects could destabilise system dynamics even lead to extinctions. The effects of climatic change are likely to be relatively more important in higher trophic levels that depend on the capacity of lower trophic levels to adapt to these changes. This paper addresses the effects of climate on insect communities, focusing on aphids, aphids parasitoids and predators, and hyperparasitoids. For each trophic level, the general effect of temperature change on insects is discussed, with emphasis on species belonging to aphid-based communities. The effects of climate change on communities can be short-term or long-term. Short-term consequences include the direct effects of temperature on different life history traits such as development time (which affects the annual number of generations), metabolic rate (which affects activity levels, longevity, and fecundity), and sex allocation. Potential effects on endosymbiont survival, virus transmission, geographical distribution of species and phenological synchronisation between trophic levels are also discussed. Long-term effects involve genetic changes in populations associated with climatic adaptations.
C1 [van Baaren, Joan] Univ Rennes 1, UMR CNRS ECOBIO 6553, F-35042 Rennes, France.
C3 Centre National de la Recherche Scientifique (CNRS); Universite de
   Rennes
RP van Baaren, J (corresponding author), Univ Rennes 1, UMR CNRS ECOBIO 6553, F-35042 Rennes, France.
EM joan.van-baaren@univ-rennes1.fr
RI Le Lann, Cecile/C-1005-2013
CR Bensadia F, 2006, J INSECT PHYSIOL, V52, P146, DOI 10.1016/j.jinsphys.2005.09.011
   Bernal J, 1997, ENTOMOL EXP APPL, V82, P159, DOI 10.1023/A:1002929500786
   Bezemer TM, 1998, OECOLOGIA, V116, P128, DOI 10.1007/s004420050571
   BRODEUR J, 1994, CAN ENTOMOL, V126, P1493, DOI 10.4039/Ent1261493-6
   Cannon RJC, 1998, GLOBAL CHANGE BIOL, V4, P785, DOI 10.1046/j.1365-2486.1998.00190.x
   Chen DQ, 2000, ENTOMOL EXP APPL, V95, P315, DOI 10.1023/A:1004083324807
   Chen FJ, 2007, BIOCONTROL SCI TECHN, V17, P313, DOI 10.1080/09583150701211814
   Chen FJ, 2005, ENVIRON ENTOMOL, V34, P37, DOI 10.1603/0046-225X-34.1.37
   CRAFFORD J E, 1986, South African Journal of Antarctic Research, V16, P42
   Degnan PH, 2008, MOL ECOL, V17, P916, DOI 10.1111/j.1365-294X.2007.03616.x
   Dixon A., 1998, Aphid Ecology, V2nd ed.
   Easterling DR, 2000, SCIENCE, V289, P2068, DOI 10.1126/science.289.5487.2068
   Fabre F, 2005, AGR ECOSYST ENVIRON, V106, P49, DOI 10.1016/j.agee.2004.07.004
   Foster GN, 2004, PEST MANAG SCI, V60, P113, DOI 10.1002/ps.796
   Gillespie D.R., 2002, Biological Control Programmes in Canada, 1981-2000, P44
   GODFRAY HCJ, 1994, J ANIM ECOL, V63, P1, DOI 10.2307/5577
   Hance T, 2007, ANNU REV ENTOMOL, V52, P107, DOI 10.1146/annurev.ento.52.110405.091333
   Hansen LM, 1999, ACTA AGR SCAND B-S P, V49, P117, DOI 10.1080/09064719950135632
   Harrington R, 2001, AGR FOREST ENTOMOL, V3, P233, DOI 10.1046/j.1461-9555.2001.00120.x
   HOLLER C, 1993, J INSECT PHYSIOL, V39, P649, DOI 10.1016/0022-1910(93)90070-8
   Hoover JK, 2004, GLOBAL CHANGE BIOL, V10, P1197, DOI 10.1111/j.1529-8817.2003.00796.x
   Hullé M, 2008, POLAR BIOL, V31, P1037, DOI 10.1007/s00300-008-0442-z
   Karl TR, 2003, SCIENCE, V302, P1719, DOI 10.1126/science.1090228
   Krespi L, 1997, ENVIRON ENTOMOL, V26, P545, DOI 10.1093/ee/26.3.545
   LANDSBERG J, 1992, AUST J BOT, V40, P565, DOI 10.1071/BT9920565
   Lee JE, 2007, POLAR BIOL, V30, P1195, DOI 10.1007/s00300-007-0277-z
   Li BP, 2004, ENTOMOL EXP APPL, V110, P249, DOI 10.1111/j.0013-8703.2004.00144.x
   Mason PG, 1997, ENVIRON ENTOMOL, V26, P1416, DOI 10.1093/ee/26.6.1416
   Moran NA, 2005, P NATL ACAD SCI USA, V102, P16919, DOI 10.1073/pnas.0507029102
   MUNSON MA, 1991, J BACTERIOL, V173, P6321, DOI 10.1128/jb.173.20.6321-6324.1991
   Newman JA, 2005, GLOBAL CHANGE BIOL, V11, P940, DOI 10.1111/j.1365-2486.2005.00946.x
   OHTAKA C, 1991, SYMBIOSIS, V11, P19
   Oliver KM, 2005, P NATL ACAD SCI USA, V102, P12795, DOI 10.1073/pnas.0506131102
   Parmesan C, 2006, ANNU REV ECOL EVOL S, V37, P637, DOI 10.1146/annurev.ecolsys.37.091305.110100
   Powell SJ, 2004, J INSECT PHYSIOL, V50, P277, DOI 10.1016/j.jinsphys.2004.01.003
   Pritchard SG, 1999, GLOB CHANGE BIOL, V5, P807, DOI 10.1046/j.1365-2486.1999.00268.x
   Rahbé Y, 2002, J INSECT PHYSIOL, V48, P507, DOI 10.1016/S0022-1910(02)00053-7
   Röhne O, 2002, J APPL ENTOMOL, V126, P572, DOI 10.1046/j.1439-0418.2002.00608.x
   Shigenobu S, 2000, NATURE, V407, P81, DOI 10.1038/35024074
   Sigsgaard L, 2000, ENTOMOL EXP APPL, V95, P173, DOI 10.1023/A:1003993719952
   Simon JC, 2002, TRENDS ECOL EVOL, V17, P34, DOI 10.1016/S0169-5347(01)02331-X
   Stacey DA, 2002, GLOBAL CHANGE BIOL, V8, P668, DOI 10.1046/j.1365-2486.2002.00506.x
   Sullivan DJ, 1999, ANNU REV ENTOMOL, V44, P291, DOI 10.1146/annurev.ento.44.1.291
   Terblanche JS, 2007, P ROY SOC B-BIOL SCI, V274, P2935, DOI 10.1098/rspb.2007.0985
   Thomas MB, 2003, TRENDS ECOL EVOL, V18, P344, DOI 10.1016/S0169-5347(03)00069-7
   Traugott M, 2008, MOL ECOL, V17, P3928, DOI 10.1111/j.1365-294X.2008.03878.x
   Tsuchida T, 2004, SCIENCE, V303, P1989, DOI 10.1126/science.1094611
   van der Putten WH, 2004, BASIC APPL ECOL, V5, P487, DOI 10.1016/j.baae.2004.09.003
   Van Veen FJF, 2008, J ANIM ECOL, V77, P191, DOI 10.1111/j.1365-2656.2007.01325.x
   VANSTEENIS MJ, 1995, ENTOMOL EXP APPL, V76, P121, DOI 10.1007/BF02383210
   WALTON MP, 1990, ENTOMOL EXP APPL, V54, P271, DOI 10.1007/BF00186796
   Yu D.S., 2005, World Ichneumonoidea 2004. Taxonomy, Biology
   Zamani AA, 2007, ENVIRON ENTOMOL, V36, P263, DOI 10.1603/0046-225X-36.2.263
NR 53
TC 30
Z9 34
U1 0
U2 19
PU SPRINGER-VERLAG BERLIN
PI BERLIN
PA HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
BN 978-90-481-8600-6
PY 2010
BP 55
EP 68
PG 14
WC Entomology
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Entomology
GA BH0JN
UT WOS:000395360600004
DA 2025-01-10
ER

PT J
AU Madaki, MY
   Kaechele, H
   Bavorova, M
AF Madaki, Mustapha Yakubu
   Kaechele, Harald
   Bavorova, Miroslava
TI Agricultural insurance as a climate risk adaptation strategy in
   developing countries: a case of Nigeria
SO CLIMATE POLICY
LA English
DT Article; Early Access
DE Agricultural insurance; awareness; adoption impediment; weather
   information; statutory land ownership; climate change extremes
ID WEATHER-INDEX INSURANCE; FOOD SECURITY; FARMERS; ADOPTION; IMPACT;
   MODEL; WILLINGNESS; PREFERENCES; PERCEPTION; PROTECTION
AB Despite the potential benefits of agricultural insurance in helping farmers adapt to climate risks, its uptake among smallholder farmers remains limited. This study analyses the drivers of awareness and adoption of agricultural insurance in Nigeria to better understand the adoption process. 1,080 farming households were surveyed across six agro-ecological zones in Nigeria, covering areas with different socio-economic characteristics of farmers and levels of climate risk. Data were collected through face-to-face interviews between October 2020 and February 2021. The results show that more than half of the farmers were unaware of agricultural insurance. Logit regression results show that education, herd size, access to a bank, weather information, and flood experience positively influence awareness and adoption of agricultural insurance. In addition to low awareness, the main barriers to adoption are lack of knowledge about the effectiveness of insurance, difficulty in affording insurance, and farmers' low level of trust in insurance providers. Late payment of claims and inadequate compensation were the main challenges faced by adopters of agricultural insurance. Raising awareness and helping farmers to assess the effectiveness of agricultural insurance, as well as developing a supportive institutional environment, would help to build a well-functioning insurance market.Key policy insightsTo increase the uptake of agricultural insurance, it is first necessary to raise awareness among farmers.Government agencies should consider monitoring and sanctioning insurance agencies and companies that fail to comply with contractual agreements to promote and ensure prompt payment of due compensation; to increase transparency of insurance providers' performance; and to increase confidence in insurance providers.We recommend using different premium payment methods, adjusting land policies, improving access to weather information, and increasing access to bank credit for smallholder farmers to increase farmers' motivation to use insurance.
C1 [Madaki, Mustapha Yakubu; Bavorova, Miroslava] Czech Univ Life Sci Prague, Fac Trop Agrisci, Prague, Czech Republic.
   [Madaki, Mustapha Yakubu; Kaechele, Harald] Leibniz Ctr Agr Landscape Res ZALF, Muncheberg, Germany.
   [Kaechele, Harald] Eberswalde Univ Sustainable Dev, Fac Landscape Management & Nat Conservat, Eberswalde, Germany.
   [Bavorova, Miroslava] Czech Univ Life Sci Prague, Fac Trop Agrisci, Kamycka 129, Prague 16500, Czech Republic.
C3 Czech University of Life Sciences Prague; Leibniz Association; Leibniz
   Zentrum fur Agrarlandschaftsforschung (ZALF); Eberswalde University for
   Sustainable Development; Czech University of Life Sciences Prague
RP Bavorova, M (corresponding author), Czech Univ Life Sci Prague, Fac Trop Agrisci, Kamycka 129, Prague 16500, Czech Republic.
EM bavorova@ftz.czu.cz
RI Madaki, Mustapha Yakubu/HSG-9990-2023
OI Bavorova, Miroslava/0000-0001-8102-9304; Kaechele,
   Harald/0000-0002-4146-2821; Madaki, Mustapha Yakubu/0000-0001-9693-0170
FU Ceska Zemedelska Univerzita v Praze [IGA20223113]
FX This work was supported by Ceska Zemedelska Univerzita v Praze: [Grant
   Number IGA20223113]
CR Abugri S.A., 2017, Agriculture Food Security, V6, P71, DOI DOI 10.1186/S40066-017-0152-2
   Ajieh C.P., 2010, J AGR SCI-CAMBRIDGE, V1, P43
   Akinola B.D., 2014, BRIT J POULTRY SCI, V3, P36, DOI DOI 10.5829/IDOSI.BJPS.2014.3.2.83216
   Akinwande M.O., 2015, Open J. Stat., V5, P754, DOI [10.4236/ojs.2015.57075, DOI 10.4236/OJS.2015.57075]
   Ali E, 2020, CLIM POLICY, V20, P534, DOI 10.1080/14693062.2020.1745742
   Amare A, 2019, CLIM RISK MANAG, V25, DOI 10.1016/j.crm.2019.100191
   Ankrah DA., 2021, Agriculture Food Security, V10, P1, DOI DOI 10.1186/S40066-021-00292-Y
   [Anonymous], 2001, IPCC
   [Anonymous], 2016, RISK MANAGEMENT AGR
   ARC, 2023, AFR RISK CAP STRAT F
   Arshad M, 2016, CLIM DEV, V8, P234, DOI 10.1080/17565529.2015.1034232
   Barrett CB, 2001, FOOD POLICY, V26, P315, DOI 10.1016/S0306-9192(01)00014-8
   Below TB, 2015, REG ENVIRON CHANGE, V15, P1169, DOI 10.1007/s10113-014-0620-1
   Biglari T, 2019, LAND USE POLICY, V87, DOI 10.1016/j.landusepol.2019.104043
   Bogale A, 2015, CLIM DEV, V7, P246, DOI 10.1080/17565529.2014.934769
   Britannica, 2021, CLIM NIG
   Broberg M, 2020, CLIM POLICY, V20, P693, DOI 10.1080/14693062.2019.1641461
   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
   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
   Chantarat S, 2017, WORLD DEV, V94, P119, DOI 10.1016/j.worlddev.2016.12.044
   Chavas JP, 2019, EUR REV AGRIC ECON, V46, P29, DOI 10.1093/erae/jby019
   Cole S, 2013, AM ECON J-APPL ECON, V5, P104, DOI 10.1257/app.5.1.104
   Cole SA, 2017, ANNU REV ECON, V9, P235, DOI 10.1146/annurev-economics-080315-015225
   Collier B, 2009, GENEVA PAP R I-ISS P, V34, P401, DOI 10.1057/gpp.2009.11
   Daberkow S. G., 2003, Precision Agriculture, V4, P163, DOI 10.1023/A:1024557205871
   Daron JD, 2014, CLIM RISK MANAG, V1, P76, DOI 10.1016/j.crm.2014.01.001
   De Nicola F., 2013, AM EC ASS M
   De Nicola F., 2015, World Bank Policy Research Working Paper No.7187
   Devereux S, 2016, FOOD POLICY, V60, P52, DOI 10.1016/j.foodpol.2015.03.009
   Di Falco S, 2014, J AGR ECON, V65, P485, DOI 10.1111/1477-9552.12053
   Di Falco S, 2011, AM J AGR ECON, V93, P825, DOI 10.1093/ajae/aar006
   Elabed G, 2013, AGR ECON-BLACKWELL, V44, P419, DOI 10.1111/agec.12025
   Elum ZA, 2017, CLIM RISK MANAG, V16, P246, DOI 10.1016/j.crm.2016.11.001
   Falola A., 2013, International Journal of Food and Agricultural Economics, V1, P97
   FAO, 2021, NIG DEM
   Fisher E, 2019, DEV POLICY REV, V37, P581, DOI 10.1111/dpr.12387
   Floyd DL, 2000, J APPL SOC PSYCHOL, V30, P407, DOI 10.1111/j.1559-1816.2000.tb02323.x
   Freudenreich H, 2018, J AGR ECON, V69, P96, DOI 10.1111/1477-9552.12226
   Gine X, 2008, WORLD BANK ECON REV, V22, P539, DOI 10.1093/wber/lhn015
   Gine Xavier., 2010, WORLD BANK POLICY RE
   Greene WH, 2003, TRANSPORT RES B-METH, V37, P681, DOI 10.1016/S0191-2615(02)00046-2
   Hansen J. W., 2017, 218 CCAFS
   Hansen J, 2019, AGR SYST, V172, P28, DOI 10.1016/j.agsy.2018.01.019
   Hill RV, 2013, AGR ECON-BLACKWELL, V44, P385, DOI 10.1111/agec.12023
   Hountondji R. L., 2018, INT J PROGRESSIVE SC, V12, P37
   Ibitoye S. J., 2013, INT J AGR SCI RES TE, V2, P143
   IFAD, 2010, The potential for scale and sustainability in weather index insurance for agriculture and rural livelihoods
   IFPRI, 2014, NAT CROP INS PROGR C
   IPCC, 2019, CLIMATE CHANGE LAND, P511
   IPCC, 2018, GLOB WARM 1 5C SUMM
   IWMI, 2021, BUNDL SOL SEED SYST
   Jatto Ayoyinka Nurudeen, 2019, Agricultura Tropica et Subtropica, V52, P79, DOI 10.2478/ats-2019-0009
   Jensen N, 2017, APPL ECON PERSPECT P, V39, P199, DOI 10.1093/aepp/ppw022
   Jensen ND, 2017, J DEV ECON, V129, P14, DOI 10.1016/j.jdeveco.2017.08.002
   Jin JJ, 2016, INT J DISAST RISK SC, V7, P366, DOI 10.1007/s13753-016-0108-3
   Jin JJ, 2015, LAND USE POLICY, V47, P365, DOI 10.1016/j.landusepol.2015.04.028
   Johnson L, 2019, J DEV STUD, V55, P1221, DOI 10.1080/00220388.2018.1453603
   Kong R, 2011, CHINA AGR ECON REV, V3, P423, DOI 10.1108/17561371111192293
   Marr A, 2016, AGRIC FINANCE REV, V76, P94, DOI 10.1108/AFR-11-2015-0050
   Mendelsohn R, 2000, CLIMATIC CHANGE, V45, P583, DOI 10.1023/A:1005507810350
   Ministry of Environment Lands and Parks, 1998, B.C. Presses Federal Government For Strong Action On Greenhouse Gases And Climate Change
   NAIC, 2021, NIG AGR INS CORP
   NAIC, 2017, NIG AGR INS PROF
   Nnadi F. N., 2013, Net Journal of Agricultural Science, V1, P1
   Nordlander L, 2020, CLIM POLICY, V20, P704, DOI 10.1080/14693062.2019.1671163
   Ntukamazina N., 2017, Journal of Agriculture and Rural Development in the Tropics and Subtropics, V118, P171
   Oduniyi OS, 2020, CLIMATE, V8, DOI 10.3390/cli8030047
   Olajide-Adedamola F. O., 2019, INT J AGR MANAGEMENT, V9, P285
   Olila D. O., 2014, 8 ANN EGERTON U INT
   Olubiyo S. O., 2005, Savings and Development, V29, P293
   Omerkhil N, 2020, ECOL INDIC, V110, DOI 10.1016/j.ecolind.2019.105863
   Ricome A, 2017, AGR SYST, V156, P149, DOI 10.1016/j.agsy.2017.05.015
   Rogers E.M., 2003, Diffusion of Innovations, V5th
   Sidra Ghazanfar Sidra Ghazanfar, 2015, Journal of Northeast Agricultural University (English Edition), V22, P76
   Skees J., 2001, Policy Research Working Paper Series 2577
   Skees J. R., 2008, OECD EXP WORKSH EC A
   Skees JR, 2004, RURAL FINANCE AND CREDIT INFRASTRUCTURE IN CHINA, P172
   Stoltzfus JC, 2011, ACAD EMERG MED, V18, P1099, DOI 10.1111/j.1553-2712.2011.01185.x
   Subhash Chand Subhash Chand, 2016, Indian Journal of Agricultural Economics, V71, P335
   Tadesse A.M., 2015, AGR FOOD ECON, V3, P26, DOI [10.1186/s40100-015-0044-3, DOI 10.1186/S40100-015-0044-3]
   Thornton PK, 2014, GLOB FOOD SECUR-AGR, V3, P99, DOI 10.1016/j.gfs.2014.02.002
   Turvey CG, 2006, AM J AGR ECON, V88, P696, DOI 10.1111/j.1467-8276.2006.00889.x
   *UNFCCC, 2015, NIG INT NAT DET CONT
   Woodard JD, 2016, GENEVA PAP R I-ISS P, V41, P259, DOI 10.1057/gpp.2015.31
   World Bank, 2014, RED VULN AZ AGR SYST, P94, DOI [10.1596/978-1-4648-0184-6, DOI 10.1596/978-1-4648-0184-6]
   World Bank, 2011, NIG CROP WEATH IND I
   World Climate Guide, 2019, NIG CLIM AV WEATH TE
   Zhu WJ, 2019, AGRIC FINANCE REV, V79, P2, DOI [10.1108/AFR-08-2017-0064, 10.1108/afr-08-2017-0064]
NR 90
TC 6
Z9 8
U1 11
U2 38
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 2023 JUN 9
PY 2023
DI 10.1080/14693062.2023.2220672
EA JUN 2023
PG 16
WC Environmental Studies; Public Administration
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Public Administration
GA I5NX3
UT WOS:001003257500001
OA hybrid
DA 2025-01-10
ER

PT J
AU Guan, XY
   Wen, Y
   Zhang, Y
   Chen, Z
   Cao, KF
AF Guan, Xinyi
   Wen, Yin
   Zhang, Ya
   Chen, Zhao
   Cao, Kun-Fang
TI Stem hydraulic conductivity and embolism resistance of Quercus species
   are associated with their climatic niche
SO TREE PHYSIOLOGY
LA English
DT Article
DE climatic niche; distribution range; embolism resistance; hydraulic
   conductivity; Quercus; vessel anatomy
ID CAVITATION RESISTANCE; XYLEM; TRAITS; LEAF; EVERGREEN; VULNERABILITY;
   SAFETY; DIFFERENTIATION; COORDINATION; EFFICIENCY
AB The hydraulic traits of a plant species may reflect its climate adaptations. Southwest China is considered as a biodiversity hotpot of the genus Quercus (oak). However, the hydraulic adaptations of Asian oaks to their climate niches remain unclear. Ten common garden-grown oak species with distinct natural distributions in eastern Asia were used to determine their stem xylem embolism resistance (water potential at 50% loss of hydraulic conductivity, P-50), stem hydraulic efficiency (vessel anatomy and sapwood specific hydraulic conductivity (Ks)) and leaf anatomical traits. We also compiled four key functional traits: wood density, hydraulic-weighted vessel diameter, Ks and P-50 data for 31 oak species from previous literature. We analyzed the relationship between hydraulic traits and climatic factors over the native ranges of 41 oak species. Our results revealed that the 10 Asian oak species, which are mainly distributed in humid subtropical habitats, possessed a stem xylem with low embolism resistance and moderate hydraulic efficiency. The deciduous and evergreen species of the 10 Asian oaks differed in the stem and leaf traits related to hydraulic efficiency. Ks differed significantly between the two phenological groups (deciduous and evergreens) in the 41-oak dataset. No significant difference in P-50 between the two groups was found for the 10 Asian oaks or the 41-oak dataset. The oak species that can distribute in arid habitats possessed a stem xylem with high embolism resistance. Ks negatively related to the humidity of the native range of the 10 Asian oaks, but showed no trend when assessing the entire global oak dataset. Our study suggests that stem hydraulic conductivity and embolism resistance in Quercus species are shaped by their climate niche. Our findings assist predictions of oak drought resistance with future climate changes for oak forest management.
C1 [Guan, Xinyi; Wen, Yin; Chen, Zhao; Cao, Kun-Fang] Guangxi Univ, Plant Ecophysiol & Evolut Grp, State Key Lab Conservat & Utilisat Subtrop Agrobi, Nanning 530004, Guangxi, Peoples R China.
   [Guan, Xinyi; Wen, Yin; Chen, Zhao; Cao, Kun-Fang] Guangxi Univ, Coll Forestry, Guangxi Key Lab Forest Ecol & Conservat, Nanning 530004, Guangxi, Peoples R China.
   [Zhang, Ya] Anhui Normal Univ, Coll Life Sci, Anhui Prov Key Lab Conservat & Exploitat Biol Res, Wuhu 241000, Anhui, Peoples R China.
C3 Guangxi University; Guangxi University; Anhui Normal University
RP Cao, KF (corresponding author), Guangxi Univ, Plant Ecophysiol & Evolut Grp, State Key Lab Conservat & Utilisat Subtrop Agrobi, Nanning 530004, Guangxi, Peoples R China.; Cao, KF (corresponding author), Guangxi Univ, Coll Forestry, Guangxi Key Lab Forest Ecol & Conservat, Nanning 530004, Guangxi, Peoples R China.
EM xinyi.guan@uni-ulm.de; weny@scbg.ac.cn; zhangya@ahnu.edu.cn;
   1015229017@qq.com; kunfangcao@gxu.edu.cn
RI Zhang, Ya/KFR-4664-2024; Wen, Yin/CAH-8939-2022
OI Wen, Yin/0000-0002-0262-8876
FU National Natural Science Foundation of China [31861133008, 31470469,
   32001105]; Bagui Scholarship and Innovation Project of Guangxi Graduate
   Education Grant [YCSW2017041]
FX National Natural Science Foundation of China (Nos 31861133008, 31470469,
   32001105), Bagui Scholarship (No. 2016A32) and Innovation Project of
   Guangxi Graduate Education Grant (No. YCSW2017041).
CR Aguilar-Romero R, 2017, TREE PHYSIOL, V37, P915, DOI 10.1093/treephys/tpx033
   Anderegg WRL, 2016, P NATL ACAD SCI USA, V113, P5024, DOI 10.1073/pnas.1525678113
   Bourne AE, 2017, ANN BOT-LONDON, V120, P123, DOI 10.1093/aob/mcx020
   Brodribb TJ, 2002, PLANT CELL ENVIRON, V25, P1435, DOI 10.1046/j.1365-3040.2002.00919.x
   Cardoso AA, 2020, PLANT PHYSIOL, V182, P547, DOI 10.1104/pp.19.00585
   Cavender-Bares J, 2001, PLANT CELL ENVIRON, V24, P1243, DOI 10.1046/j.1365-3040.2001.00797.x
   Chen YJ, 2021, ECOL LETT, V24, P2350, DOI 10.1111/ele.13856
   Chen YJ, 2021, NEW PHYTOL, V229, P805, DOI 10.1111/nph.16927
   de Souza BC, 2020, OECOLOGIA, V194, P221, DOI 10.1007/s00442-020-04760-3
   Deng M, 2018, MOL PHYLOGENET EVOL, V119, P170, DOI 10.1016/j.ympev.2017.11.003
   Escudero A, 2017, TREE PHYSIOL-NETH, V7, P195, DOI 10.1007/978-3-319-69099-5_6
   Fick SE, 2017, INT J CLIMATOL, V37, P4302, DOI 10.1002/joc.5086
   Fontes CG, 2022, FUNCT ECOL, V36, P326, DOI 10.1111/1365-2435.13964
   Fu PL, 2012, ANN BOT-LONDON, V110, P189, DOI 10.1093/aob/mcs092
   Gleason SM, 2016, NEW PHYTOL, V209, P123, DOI 10.1111/nph.13646
   Gleason SM, 2012, FUNCT ECOL, V26, P343, DOI 10.1111/j.1365-2435.2012.01962.x
   GREENIDGE KNH, 1952, AM J BOT, V39, P570, DOI 10.2307/2438704
   Hacke UG, 2006, TREE PHYSIOL, V26, P689, DOI 10.1093/treephys/26.6.689
   Hacke UG, 2017, PLANT CELL ENVIRON, V40, P831, DOI 10.1111/pce.12777
   Hipp AL, 2020, NEW PHYTOL, V226, P1198, DOI 10.1111/nph.16162
   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
   Kaack L, 2021, NEW PHYTOL, V230, P1829, DOI 10.1111/nph.17282
   Kaack L, 2019, IAWA J, V40, P673, DOI 10.1163/22941932-40190259
   Kröber W, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0109211
   Larter M, 2017, NEW PHYTOL, V215, P97, DOI 10.1111/nph.14545
   Lens F, 2011, NEW PHYTOL, V190, P709, DOI 10.1111/j.1469-8137.2010.03518.x
   Li XM, 2018, PLANT CELL ENVIRON, V41, P646, DOI 10.1111/pce.13129
   Liu H, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aav1332
   Liu H, 2015, SCI REP-UK, V5, DOI 10.1038/srep12246
   Liu XD, 2017, SCI REP-UK, V7, DOI 10.1038/srep40344
   Lobo A, 2018, FOREST ECOL MANAG, V424, P53, DOI 10.1016/j.foreco.2018.04.031
   Markesteijn L, 2011, PLANT CELL ENVIRON, V34, P137, DOI 10.1111/j.1365-3040.2010.02231.x
   Martin-StPaul N, 2017, ECOL LETT, V20, P1437, DOI 10.1111/ele.12851
   Meinzer FC, 2008, OECOLOGIA, V156, P31, DOI 10.1007/s00442-008-0974-5
   Méndez-Alonzo R, 2012, ECOLOGY, V93, P2397, DOI 10.1890/11-1213.1
   NIXON KC, 2006, ECOLOGY CONSERVATION, P3, DOI DOI 10.1007/3-540-28909-7_1
   Nolan RH, 2021, NEW PHYTOL, V230, P1354, DOI 10.1111/nph.17298
   Oyanoghafo OO, 2021, ANN BOT-LONDON, V127, P909, DOI 10.1093/aob/mcab020
   Pagel M, 1999, NATURE, V401, P877, DOI 10.1038/44766
   Pammenter NW, 1998, TREE PHYSIOL, V18, P589, DOI 10.1093/treephys/18.8-9.589
   Pfautsch S, 2016, ECOL LETT, V19, P240, DOI 10.1111/ele.12559
   Powers JS, 2020, GLOBAL CHANGE BIOL, V26, P3122, DOI 10.1111/gcb.15037
   Pratt RB, 2020, TREE PHYSIOL, V40, P5, DOI 10.1093/treephys/tpz092
   Robert EMR, 2017, TREE PHYSIOL-NETH, V7, P261, DOI 10.1007/978-3-319-69099-5_8
   Rosas T, 2019, NEW PHYTOL, V223, P632, DOI 10.1111/nph.15684
   Sancho-Knapik D, 2021, NEW PHYTOL, V230, P521, DOI 10.1111/nph.17151
   Schuldt B, 2016, NEW PHYTOL, V210, P443, DOI 10.1111/nph.13798
   Skelton RP, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2008987118
   Skelton RP, 2019, NEW PHYTOL, V223, P1296, DOI 10.1111/nph.15886
   Skelton RP, 2018, PLANT PHYSIOL, V177, P1066, DOI 10.1104/pp.18.00103
   SPERRY JS, 1988, PLANT CELL ENVIRON, V11, P35, DOI 10.1111/j.1365-3040.1988.tb01774.x
   Trabucco A., 2018, CGIAR Consortium for Spatial Information (CGIAR-CSI)
   TYREE MT, 1989, ANNU REV PLANT PHYS, V40, P19, DOI 10.1146/annurev.pp.40.060189.000315
   Wang AY, 2020, FORESTS, V11, DOI 10.3390/f11080844
   Wheeler JK, 2013, PLANT CELL ENVIRON, V36, P1938, DOI 10.1111/pce.12139
   Wheeler JK, 2005, PLANT CELL ENVIRON, V28, P800, DOI 10.1111/j.1365-3040.2005.01330.x
   Wolfe BT, 2016, NEW PHYTOL, V212, P1007, DOI 10.1111/nph.14087
   Xiong DL, 2020, PLANT J, V101, P800, DOI 10.1111/tpj.14595
   Xu XT, 2016, J BIOGEOGR, V43, P279, DOI 10.1111/jbi.12620
   Zhang Y, 2018, TREE PHYSIOL, V38, P1016, DOI 10.1093/treephys/tpy015
   Zhang YJ, 2013, PLANT CELL ENVIRON, V36, P149, DOI 10.1111/j.1365-3040.2012.02563.x
   Zhu SD, 2019, TREE PHYSIOL, V39, P1405, DOI 10.1093/treephys/tpz028
   Zhu SD, 2017, TREE PHYSIOL, V37, P1469, DOI 10.1093/treephys/tpx094
   Zhu SD, 2013, PLANT CELL ENVIRON, V36, P879, DOI 10.1111/pce.12024
NR 64
TC 4
Z9 5
U1 9
U2 54
PU OXFORD UNIV PRESS
PI OXFORD
PA GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND
SN 0829-318X
EI 1758-4469
J9 TREE PHYSIOL
JI Tree Physiol.
PD FEB 4
PY 2023
VL 43
IS 2
BP 234
EP 247
DI 10.1093/treephys/tpac119
EA NOV 2022
PG 14
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Forestry
GA P0KL4
UT WOS:000882083500001
PM 36209451
DA 2025-01-10
ER

PT J
AU Guo, WH
   Liang, S
   He, YW
   Li, WW
   Xiong, B
   Wen, HY
AF Guo, Weihong
   Liang, Sheng
   He, Yiwei
   Li, Weiwei
   Xiong, Bo
   Wen, Hongyan
TI Combining EnergyPlus and CFD to predict and optimize the passive
   ventilation mode of medium-sized gymnasium in subtropical regions
SO BUILDING AND ENVIRONMENT
LA English
DT Article
DE Subtropical regions; Medium-sized gymnasium; Passive ventilation mode;
   Thermal stratification; Numerical simulation
ID INDOOR THERMAL ENVIRONMENT; BUILDING ENERGY; SIMULATION; COMFORT;
   PERFORMANCE; STRATIFICATION; DRIVEN
AB Thermal stratification is considered to be common in large space buildings, which constitutes a complex indoor thermal environment of gymnasiums. In consideration of the combined effect of wind pressure and thermal buoyancy on natural ventilation efficiency, this work combining the building energy modeling (BEM) and computational fluid dynamics (CFD) to evaluate the impact of climatic conditions and building forms on natural ventilation of medium-sized gymnasiums in subtropical regions. The ventilation efficiency at peak time (13:00-15:00) is significantly higher than that at valley time (08:00), which indicates that thermal buoyancy plays a positive role in air change rate (ACH) and wind velocity conditions, and the thermal pressure form with low-inlet and high-outlet has a higher climate adaptability. Using the Adaptive Predicted Mean Vote (APMV) to evaluate the comfort of the combining results, and to effectiveness predict the passive ventilation mode in each quarter. There is a large operating time range (71.35% similar to 100%) for a medium-sized gymnasium in the subtropical regions to apply the passive ventilation mode in transition seasons of spring and autumn, and the thermal comfort condition of the sports area is better than that of the spectator area. On the other hand, the operating time range shows 36.96%-64.93% in summer as the peak time comfort exceeds the upper limit of the standard value. Since the sports crowd has stronger thermal endurance than the sitting crowd, it is possible to achieve a higher range of energy saving by effectively controlling the operation time and power consumption of air conditioning measures in non-event time (no consideration of the use in spectator area) in hot summer.
C1 [Guo, Weihong; Liang, Sheng; He, Yiwei; Li, Weiwei; Xiong, Bo; Wen, Hongyan] South China Univ Technol, Sch Architecture, Guangzhou 510640, Guangdong, Peoples R China.
   [Guo, Weihong] South China Univ Technol, State Key Lab Subtrop Bldg Sci, Guangzhou 510640, Guangdong, Peoples R China.
C3 South China University of Technology; South China University of
   Technology
RP Liang, S (corresponding author), South China Univ Technol, Sch Architecture, Guangzhou 510640, Guangdong, Peoples R China.
EM whguo@scut.edu.cn; lsh_guangzhou@126.com
RI wen, Hongyan/HTR-6460-2023
OI Hongyan, Wen/0009-0008-9795-6602; He, Yiwei/0009-0004-2754-1701
FU National Natural Science Foundation of China [51678239]; National Key
   Research and Development Program of China [2017YFC0702505]; State Key
   Laboratory of Subtropical Building Science
FX The authors thank the joint support of the National Natural Science
   Foundation of China (Project NO. 51678239) and the National Key Research
   and Development Program of China (Project NO. 2017YFC0702505) for this
   research, which allows the cooperation and technical exchange between
   the school of architecture of South China University of Technology and
   the State Key Laboratory of Subtropical Building Science, and provides
   funds for all aspects of this work.
CR [Anonymous], THERMAL COMFORT
   [Anonymous], 2009, ASHRAE 2009 FUND HDB
   [Anonymous], 2012, GBT507852012
   ASHRAE, 2019, AHSRAE 2019
   Blocken B, 2007, ATMOS ENVIRON, V41, P238, DOI 10.1016/j.atmosenv.2006.08.019
   Caciolo M, 2013, ENERG BUILDINGS, V60, P372, DOI 10.1016/j.enbuild.2013.01.024
   Calay RK, 2000, ENERG BUILDINGS, V32, P281, DOI 10.1016/S0378-7788(00)00054-2
   Chen QY, 2009, BUILD ENVIRON, V44, P848, DOI 10.1016/j.buildenv.2008.05.025
   [程征 Cheng Zheng], 2020, [建筑科学, Building Science], V36, P106
   Chenvidyakarn T, 2007, BUILD ENVIRON, V42, P99, DOI 10.1016/j.buildenv.2005.08.007
   de Dear RJ, 2002, ENERG BUILDINGS, V34, P549, DOI 10.1016/S0378-7788(02)00005-1
   Dean R.H., 1976, ASHRAE T, V82, P584
   Demuren A, 2009, NUMER HEAT TR B-FUND, V56, P1, DOI 10.1080/10407790902970080
   Fanger PO, 2002, ENERG BUILDINGS, V34, P533
   Fumo N, 2010, ENERG BUILDINGS, V42, P2331, DOI 10.1016/j.enbuild.2010.07.027
   Gil-Lopez T., 2014, ASHRAE 1 INT C EN IN
   Gil-Lopez T, 2017, ENERG BUILDINGS, V140, P371, DOI 10.1016/j.enbuild.2017.02.017
   Gilani S, 2016, BUILD ENVIRON, V95, P299, DOI 10.1016/j.buildenv.2015.09.010
   Glicksman L., 1999, RP949 ASHRAE
   Havenith G, 2002, ENERG BUILDINGS, V34, P581, DOI 10.1016/S0378-7788(02)00008-7
   Huang C, 2007, BUILD ENVIRON, V42, P1869, DOI 10.1016/j.buildenv.2006.02.016
   Lam JC, 2001, BUILD ENVIRON, V36, P351, DOI 10.1016/S0360-1323(00)00014-7
   Larsen TS, 2008, ENERG BUILDINGS, V40, P1031, DOI 10.1016/j.enbuild.2006.07.012
   Li C., 2012, BUILD SCI, V28, P84
   Li J, 2011, STUDY SYNERGISM GYMN
   Li Jin, 2013, Journal of South China University of Technology (Natural Science Edition), V41, P83, DOI 10.3969/j.issn.1000-565X.2013.03.012
   Li LS, 2020, BUILD ENVIRON, V186, DOI 10.1016/j.buildenv.2020.107391
   Li Z., 2019, BUILD ENERGY EFFIC, V47, P76
   Lin JT, 2011, BUILD ENVIRON, V46, P89, DOI 10.1016/j.buildenv.2010.07.007
   Lin K., 2018, Journal of nanjing tech university (Natural Science Edition)J, V40, P95
   LINDEN PF, 1990, J FLUID MECH, V212, P309, DOI 10.1017/S0022112090001987
   Lomas KJ, 2007, ENERG BUILDINGS, V39, P32, DOI 10.1016/j.enbuild.2006.03.032
   Losi G, 2021, J BUILD ENG, V33, DOI 10.1016/j.jobe.2020.101599
   Mei J.K., 2010, RESEARCHES SPORTS AR
   Nishioka T, 2000, ENERG BUILDINGS, V32, P217, DOI 10.1016/S0378-7788(00)00048-7
   Perén JI, 2015, BUILD ENVIRON, V92, P578, DOI 10.1016/j.buildenv.2015.05.011
   [钱锋 Qian Feng], 2017, [建筑科学, Building Science], V33, P202
   Rajagopalan P, 2013, ENERG BUILDINGS, V58, P111, DOI 10.1016/j.enbuild.2012.11.022
   Ran JD, 2018, SUSTAIN CITIES SOC, V38, P466, DOI 10.1016/j.scs.2018.01.027
   Revel GM, 2014, BUILD ENVIRON, V77, P12, DOI 10.1016/j.buildenv.2014.03.017
   Said MNA, 1996, ENERG BUILDINGS, V24, P105, DOI 10.1016/0378-7788(95)00966-3
   Shan XF, 2020, SUSTAIN CITIES SOC, V60, DOI 10.1016/j.scs.2020.102257
   SHIH TH, 1995, COMPUT FLUIDS, V24, P227, DOI 10.1016/0045-7930(94)00032-T
   Stamou AI, 2008, APPL THERM ENG, V28, P1206, DOI 10.1016/j.applthermaleng.2007.07.020
   Tang G., 2005, Hot and Humid Climate and Traditional Architecture in Lingnan
   Tian W, 2018, ENERG BUILDINGS, V165, P184, DOI 10.1016/j.enbuild.2018.01.046
   van Hooff T, 2013, BUILD ENVIRON, V61, P1, DOI 10.1016/j.buildenv.2012.11.021
   van Hooff T, 2011, BUILD ENVIRON, V46, P22, DOI 10.1016/j.buildenv.2010.06.013
   van Hooff T, 2010, ENVIRON MODELL SOFTW, V25, P51, DOI 10.1016/j.envsoft.2009.07.008
   Wang JH, 2020, BUILD ENVIRON, V172, DOI 10.1016/j.buildenv.2020.106705
   Wang LP, 2008, AUTOMAT CONSTR, V17, P386, DOI 10.1016/j.autcon.2007.06.004
   Wu Y, 2016, BUILD ENVIRON, V105, P307, DOI 10.1016/j.buildenv.2016.06.005
   Wvon D.P., 1996, INDOOR AIR, V6, P48
   [杨伟 Yang Wei], 2003, [同济大学学报. 自然科学版, Journal of Tongji University], V31, P647
   Yao RM, 2009, BUILD ENVIRON, V44, P2089, DOI 10.1016/j.buildenv.2009.02.014
   Zhai ZJ, 2006, ENERG BUILDINGS, V38, P1060, DOI 10.1016/j.enbuild.2005.12.003
   Zhai ZQ, 2002, BUILD ENVIRON, V37, P857, DOI 10.1016/S0360-1323(02)00054-9
   Zhai ZQJ, 2005, ENERG BUILDINGS, V37, P333, DOI 10.1016/j.enbuild.2004.07.001
   Zhang R, 2013, BUILD ENVIRON, V68, P100, DOI 10.1016/j.buildenv.2013.04.002
NR 59
TC 23
Z9 25
U1 11
U2 98
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 2022
VL 207
AR 108420
DI 10.1016/j.buildenv.2021.108420
EA OCT 2021
PN A
PG 24
WC Construction & Building Technology; Engineering, Environmental;
   Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Engineering
GA WN4PK
UT WOS:000711751500004
DA 2025-01-10
ER

PT J
AU Fekety, PA
   Crookston, NL
   Hudak, AT
   Filippelli, SK
   Vogeler, JC
   Falkowski, MJ
AF Fekety, Patrick A.
   Crookston, Nicholas L.
   Hudak, Andrew T.
   Filippelli, Steven K.
   Vogeler, Jody C.
   Falkowski, Michael J.
TI Hundred year projected carbon loads and species compositions for four
   National Forests in the northwestern USA
SO CARBON BALANCE AND MANAGEMENT
LA English
DT Article
DE Climate-FVS; Climate change; dClim rule; Forest carbon planning; Forest
   Inventory and Analysis (FIA); Forest Vegetation Simulator (FVS);
   Modeling
ID CLIMATE-CHANGE; TREE MORTALITY; VEGETATION SIMULATOR; TRANSFER
   GUIDELINES; MANAGEMENT; IMPACTS; WILDFIRE; DROUGHT; MODEL; CONSEQUENCES
AB Background Forests are an important component of the global carbon balance, and climate sensitive growth and yield models are an essential tool when predicting future forest conditions. In this study, we used the dynamic climate capability of the Forest Vegetation Simulator (FVS) to simulate future (100 year) forest conditions on four National Forests in the northwestern USA: Payette National Forest (NF), Ochoco NF, Gifford Pinchot NF, and Siuslaw NF. Using Forest Inventory and Analysis field plots, aboveground carbon estimates and species compositions were simulated with Climate-FVS for the period between 2016 and 2116 under a no climate change scenario and a future climate scenario. We included a sensitivity analysis that varied calculated disturbance probabilities and the dClim rule, which is one method used by Climate-FVS to introduce climate-related mortality. The dClim rule initiates mortality when the predicted climate change at a site is greater than the change in climate associated with a predetermined shift in elevation. Results Results of the simulations indicated the dClim rule influenced future carbon projections more than estimates of disturbance probability. Future aboveground carbon estimates increased and species composition remained stable under the no climate change scenario. The future climate scenario we tested resulted in less carbon at the end of the projections compared to the no climate change scenarios for all cases except when the dClim rule was disengaged on the Payette NF. Under the climate change scenario, species compositions shifted to climatically adapted species or early successional species. Conclusion This research highlights the need to consider climate projections in long-term planning or future forest conditions may be unexpected. Forest managers and planners could perform similar simulations and use the results as a planning tool when analyzing climate change effects at the National Forest level.
C1 [Fekety, Patrick A.; Filippelli, Steven K.; Vogeler, Jody C.; Falkowski, Michael J.] Colorado State Univ, Nat Resources Ecol Lab, Ft Collins, CO 80523 USA.
   [Hudak, Andrew T.] US Forest Serv, Rocky Mt Res Stn, 1221 South Main St, Moscow, ID 83843 USA.
   [Vogeler, Jody C.; Falkowski, Michael J.] Colorado State Univ, Dept Ecosyst Sci & Sustainabil, Ft Collins, CO 80523 USA.
C3 Colorado State University; United States Department of Agriculture
   (USDA); United States Forest Service; Colorado State University
RP Fekety, PA (corresponding author), Colorado State Univ, Nat Resources Ecol Lab, Ft Collins, CO 80523 USA.
EM patrick.fekety@colostate.edu
OI Vogeler, Jody/0000-0002-3639-8984
FU Carbon Monitoring System Award through USFS Rocky Mountain Research
   Station [NNH15AZ06I, 16-JV-11221633-061]; Carbon Monitoring System Award
   through Oregon State University [NNH15AZ06I, 15-JV-11221633-041]
FX This work was funded by Carbon Monitoring System Award #NNH15AZ06I
   awarded to Andrew Hudak (P.I.) through two Joint Venture Agreements from
   the USFS Rocky Mountain Research Station to Colorado State University
   (16-JV-11221633-061) and Oregon State University (15-JV-11221633-041).
CR Allen CD, 2010, FOREST ECOL MANAG, V259, P660, DOI 10.1016/j.foreco.2009.09.001
   Anderegg WRL, 2013, NAT CLIM CHANGE, V3, P30, DOI 10.1038/nclimate1635
   [Anonymous], FIA DATAMART
   [Anonymous], FOR GIFF PINCH NAT F
   [Anonymous], CLIMATE ESTIMATES PL
   [Anonymous], NEW PERSPECTIVES FOR
   [Anonymous], RMRSGTR319 USDA FOR
   [Anonymous], FOR SIUSL NAT FOR
   [Anonymous], FIRE FUELS EXTENSION
   [Anonymous], ECOTRUST
   [Anonymous], 2018, INTERNAL REPORT
   [Anonymous], PAYETT NAT FOR FOR
   [Anonymous], OCH NAT FOR FOR
   [Anonymous], SPRUC PEATL RESP CHA
   [Anonymous], VOL EST
   [Anonymous], SRSGTR80 USDA FOR SE
   [Anonymous], FS1035 USDA FOR SERV
   Bagdon B, 2014, FORESTS, V5, P620, DOI 10.3390/f5040620
   Bagdon BA, 2017, ECOL ECON, V140, P201, DOI 10.1016/j.ecolecon.2017.05.016
   Bell DM, 2014, GLOBAL ECOL BIOGEOGR, V23, P168, DOI 10.1111/geb.12109
   Berzaghi F, 2020, TRENDS ECOL EVOL, V35, P191, DOI 10.1016/j.tree.2019.11.006
   Breiman L, 2001, MACH LEARN, V45, P5, DOI 10.1023/A:1010933404324
   Bugmann H, 2019, ECOSPHERE, V10, DOI 10.1002/ecs2.2616
   Buma B, 2013, FOREST ECOL MANAG, V306, P216, DOI 10.1016/j.foreco.2013.06.044
   Case MJ, 2016, CLIMATIC CHANGE, V136, P367, DOI 10.1007/s10584-016-1608-2
   Chen HYH, 2016, ECOL LETT, V19, P1150, DOI 10.1111/ele.12653
   Chmura DJ, 2011, FOREST ECOL MANAG, V261, P1121, DOI 10.1016/j.foreco.2010.12.040
   Crookston NL, 2010, FOREST ECOL MANAG, V260, P1198, DOI 10.1016/j.foreco.2010.07.013
   Crookston NL, 2005, COMPUT ELECTRON AGR, V49, P60, DOI 10.1016/j.compag.2005.02.003
   Dale VH, 2001, BIOSCIENCE, V51, P723, DOI 10.1641/0006-3568(2001)051[0723:CCAFD]2.0.CO;2
   Dickinson RE, 2002, J CLIMATE, V15, P278, DOI 10.1175/1520-0442(2002)015<0278:NCOCME>2.0.CO;2
   Flatley WT, 2016, ECOSPHERE, V7, DOI 10.1002/ecs2.1471
   Franklin J.F., 1988, NATURAL VEGETATION O
   Galvez Fabian B, 2014, Carbon Balance Manag, V9, P1, DOI 10.1186/1750-0680-9-1
   Gray LK, 2013, CLIMATIC CHANGE, V117, P289, DOI 10.1007/s10584-012-0548-8
   Hamann A, 2011, TREE GENET GENOMES, V7, P399, DOI 10.1007/s11295-010-0341-7
   Huang SL, 2018, FOREST ECOL MANAG, V415, P26, DOI 10.1016/j.foreco.2018.02.026
   Jantarasami LC, 2010, ECOL SOC, V15
   Johnson G. R., 2004, Native Plants Journal, V5, P131, DOI 10.2979/NPJ.2004.5.2.131
   Kemp KB, 2015, ECOL SOC, V20, DOI 10.5751/ES-07522-200217
   Landsberg JJ, 1997, FOREST ECOL MANAG, V95, P209, DOI 10.1016/S0378-1127(97)00026-1
   Law BE, 2015, FOREST ECOL MANAG, V355, P4, DOI 10.1016/j.foreco.2014.11.023
   Mockta TK, 2018, FOREST ECOL MANAG, V430, P250, DOI 10.1016/j.foreco.2018.08.017
   Mote PW, 2010, CLIMATIC CHANGE, V102, P29, DOI 10.1007/s10584-010-9848-z
   Nagel LM, 2017, J FOREST, V115, P167, DOI 10.5849/jof.16-039
   O'Donnell FC, 2018, ECOL APPL, V28, P1459, DOI 10.1002/eap.1746
   Pachauri R.K., 2014, CLIMATE CHANGE 2014
   Rehfeldt GE, 2001, CLIMATIC CHANGE, V50, P355, DOI 10.1023/A:1010614216256
   Rehfeldt GE, 1994, INTERIOR CEDAR-HEMLOCK-WHITE PINE FORESTS: ECOLOGY AND MANAGEMENT, SYMPOSIUM PROCEEDINGS, P91
   Rehfeldt GE, 2006, INT J PLANT SCI, V167, P1123, DOI 10.1086/507711
   Rehfeldt GE, 2014, FOREST ECOL MANAG, V324, P147, DOI 10.1016/j.foreco.2014.02.040
   Rehfeldt GE, 2009, FOREST ECOL MANAG, V258, P2353, DOI 10.1016/j.foreco.2009.06.005
   Reilly MJ, 2016, FOREST ECOL MANAG, V374, P102, DOI 10.1016/j.foreco.2016.05.002
   Rupp DE, 2017, CLIM DYNAM, V48, P2191, DOI 10.1007/s00382-016-3200-x
   Salathé EP, 2007, INT J CLIMATOL, V27, P1611, DOI 10.1002/joc.1540
   Scheller RM, 2007, ECOL MODEL, V201, P409, DOI 10.1016/j.ecolmodel.2006.10.009
   Shive KL, 2014, INT J WILDLAND FIRE, V23, P915, DOI 10.1071/WF13184
   Sork VL, 2013, TREE GENET GENOMES, V9, P901, DOI 10.1007/s11295-013-0596-x
   St Clair JB, 2007, GLOBAL CHANGE BIOL, V13, P1441, DOI 10.1111/j.1365-2486.2007.01385.x
   Stovall AEL, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-12380-6
   Tarancón AA, 2014, ECOL APPL, V24, P1626, DOI 10.1890/13-1787.1
   USDA Forest Service, 2012, NAT FOR SYST LAND MA
   van Mantgem PJ, 2009, SCIENCE, V323, P521, DOI 10.1126/science.1165000
   Weed AS, 2013, ECOL MONOGR, V83, P441, DOI 10.1890/13-0160.1
   Westerling AL, 2006, SCIENCE, V313, P940, DOI 10.1126/science.1128834
   Williams MI, 2013, J FOREST, V111, P287, DOI 10.5849/jof.13-016
   Yazzie JO, 2019, ECOL APPL, V29, DOI 10.1002/eap.1944
   Ying CC, 2006, FOREST ECOL MANAG, V227, P1, DOI 10.1016/j.foreco.2006.02.028
NR 68
TC 3
Z9 5
U1 0
U2 10
PU BMC
PI LONDON
PA CAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND
SN 1750-0680
J9 CARBON BAL MANAGE
JI Carbon Balanc. Manag.
PD MAR 28
PY 2020
VL 15
IS 1
AR 5
DI 10.1186/s13021-020-00140-9
PG 14
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA KY3GR
UT WOS:000522459900001
PM 32222913
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Sheng, RR
   Li, CC
   Wang, Q
   Yang, LP
   Bao, JZ
   Wang, KW
   Ma, R
   Gao, CS
   Lin, S
   Zhang, Y
   Bi, P
   Fu, CD
   Huang, CR
AF Sheng, Rongrong
   Li, Changchang
   Wang, Qiong
   Yang, Lianping
   Bao, Junzhe
   Wang, Kaiwen
   Ma, Rui
   Gao, Chuansi
   Lin, Shao
   Zhang, Ying
   Bi, Peng
   Fu, Chuandong
   Huang, Cunrui
TI Does hot weather affect work-related injury? A case-crossover study in
   Guangzhou, China
SO INTERNATIONAL JOURNAL OF HYGIENE AND ENVIRONMENTAL HEALTH
LA English
DT Article
DE High temperature; Work injury; Case-crossover study; Occupational
   health; Climate change
ID CLIMATE-CHANGE; HEAT EXPOSURE; TEMPERATURE; STRESS; MODELS; HEALTH
AB Background: Despite increasing concerns about the health effects of climate change, the extent to which workers are affected by hot weather is not well documented. This study aims to investigate the association between high temperatures and work-related injuries using data from a large subtropical city in China.
   Methods: We used workers' compensation claims to identify work-related injuries in Guangzhou, China during 2011-2012. To feature the heat effect, the study period was restricted to the warm seasons in Guangzhou (1 May-31 October). We conducted a time-stratified case-crossover study to examine the association between ambient outdoor temperatures, including daily maximum and minimum temperatures, and cases of work-related injury. The relationships were assessed using conditional Poisson regression models.
   Results: Overall, a total of 5418 workers' compensation claims were included over the study period. Both maximum and minimum temperatures were significantly associated with work-related injuries, but associations varied by subgroup. One degrees C increase in maximum temperature was associated with a 1.4% (RR = 1.014, 95%CIs 1.012-1.017) increase in daily injury claims. Significant associations were seen for male and middle-aged workers, workers in small and medium-sized enterprises, and those working in manufacturing sector. And 1 degrees C increase in minimum temperature was associated with 1.7% (RR = 1.017, 95%CIs 1.012-1.021) increase in daily injury claims. Significant associations were observed for female and middle-aged workers, workers in large-sized enterprises, and those working in transport and construction sectors.
   Conclusions: We found a higher risk of work-related injuries due to hot weather in Guangzhou, China. This study provides important epidemiological evidence for policy-makers and industry that may assist in the formulation of occupational safety and climate adaptation strategies.
C1 [Sheng, Rongrong; Li, Changchang; Wang, Qiong; Yang, Lianping; Bao, Junzhe; Wang, Kaiwen; Ma, Rui; Huang, Cunrui] Sun Yat Sen Univ, Sch Publ Hlth, Zhongshan Rd 2, Guangzhou 510080, Guangdong, Peoples R China.
   [Gao, Chuansi] Lund Univ, Fac Engn, Dept Design Sci, Div Ergon & Aerosol Technol,Thermal Environm Lab, Lund, Sweden.
   [Lin, Shao] SUNY Albany, Dept Environm Hlth Sci, Rensselaer, NY USA.
   [Lin, Shao] SUNY Albany, Dept Epidemiol & Biostat, Rensselaer, NY USA.
   [Zhang, Ying] Univ Sydney, Sch Publ Hlth, Sydney, NSW, Australia.
   [Bi, Peng] Univ Adelaide, Discipline Publ Hlth, Adelaide, SA, Australia.
   [Fu, Chuandong] Guangdong Prov Work Injury Rehabil Hosp, Guangzhou, Guangdong, Peoples R China.
C3 Sun Yat Sen University; Lund University; State University of New York
   (SUNY) System; University at Albany, SUNY; State University of New York
   (SUNY) System; University at Albany, SUNY; University of Sydney;
   University of Adelaide
RP Huang, CR (corresponding author), Sun Yat Sen Univ, Sch Publ Hlth, Zhongshan Rd 2, Guangzhou 510080, Guangdong, Peoples R China.; Fu, CD (corresponding author), Guangdong Prov Work Injury Rehabil Hosp, Guangzhou, Guangdong, Peoples R China.
EM fucd168168@163.com; huangcr@mail.sysu.edu.cn
RI Bi, Peng/H-9782-2012; Zhang, Ying/ABE-2275-2021; Huang,
   Cunrui/ABI-3312-2020; Gao, Chuansi/C-6904-2011
OI Gao, Chuansi/0000-0001-7386-692X; Bi, Peng/0000-0002-3238-3427; Zhang,
   Ying/0000-0001-6214-2440; Bao, Junzhe/0000-0002-8165-1838
FU Natural Science Foundation of Guangdong Province, China
   [2016A030313216]; Asia-Pacific Network for Global Change Research
   [CRRP2016-10MY-Huang]
FX This work was supported by the Natural Science Foundation of Guangdong
   Province, China [2016A030313216] and the Asia-Pacific Network for Global
   Change Research [CRRP2016-10MY-Huang].
CR Adam-Poupart A, 2015, OCCUP ENVIRON MED, V72, P338, DOI 10.1136/oemed-2014-102428
   Armstrong BG, 2014, BMC MED RES METHODOL, V14, DOI 10.1186/1471-2288-14-122
   Barnett AG, 2017, ENVIRON RES, V154, P222, DOI 10.1016/j.envres.2017.01.007
   Bennett Charmian M, 2010, Glob Health Action, V3, DOI 10.3402/gha.v3i0.5640
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fortune M, 2014, ENVIRON RES, V132, P449, DOI 10.1016/j.envres.2014.04.022
   Gao C., 2017, INT J BIOMETEOROL, DOI [10.1007/s00484-017-1352, DOI 10.1007/S00484-017-1352]
   Garzon-Villalba XP, 2016, AM J IND MED, V59, P1169, DOI 10.1002/ajim.22650
   Hyatt Olivia M, 2010, Glob Health Action, V3, DOI 10.3402/gha.v3i0.5715
   International Labour Organization (ILO), 2012, NAT PROF REP OCC SAF
   Kampe EOI, 2016, BMJ OPEN, V6, DOI 10.1136/bmjopen-2015-010399
   Kjellstrom T., 2017, INT J BIOMETEOROL, DOI [10.1007/s00484-017-1407, DOI 10.1007/S00484-017-1407]
   Kjellstrom T, 2016, ANNU REV PUBL HEALTH, V37, P97, DOI 10.1146/annurev-publhealth-032315-021740
   Kjellstrom T, 2013, IND HEALTH, V51, P56, DOI 10.2486/indhealth.2012-0174
   Kjellstrom T, 2009, GLOBAL HEALTH ACTION, V2, P81, DOI 10.3402/gha.v2i0.2082
   Lan L, 2014, BUILD ENVIRON, V73, P24, DOI 10.1016/j.buildenv.2013.11.024
   Lundgren K, 2013, IND HEALTH, V51, P3, DOI 10.2486/indhealth.2012-0089
   Luo HM, 2014, SCI TOTAL ENVIRON, V472, P1130, DOI 10.1016/j.scitotenv.2013.11.042
   Mathee A, 2010, GLOBAL HEALTH ACTION, V3, DOI 10.3402/gha.v3i0.5612
   McInnes J. A., 2017, INT J BIOMETEOROL, DOI [10.1007/s00484-017-1435, DOI 10.1007/S00484-017-1435]
   McInnes JA, 2017, SCAND J WORK ENV HEA, V43, P86, DOI 10.5271/sjweh.3602
   Morabito M, 2006, IND HEALTH, V44, P458, DOI 10.2486/indhealth.44.458
   Pal JS, 2016, NAT CLIM CHANGE, V6, P197, DOI [10.1038/NCLIMATE2833, 10.1038/nclimate2833]
   Pilcher JJ, 2002, ERGONOMICS, V45, P682, DOI 10.1080/00140130210158419
   Roelofs C, 2014, AM J PUBLIC HEALTH, V104, P1799, DOI 10.2105/AJPH.2014.302145
   Sahu S, 2013, IND HEALTH, V51, P424, DOI 10.2486/indhealth.2013-0006
   Salminen S, 2010, J SLEEP RES, V19, P207, DOI 10.1111/j.1365-2869.2009.00780.x
   Schulte PA, 2016, J OCCUP ENVIRON HYG, V13, P847, DOI 10.1080/15459624.2016.1179388
   Sett M, 2014, GLOBAL HEALTH ACTION, V7, DOI 10.3402/gha.v7.21923
   Spector JT, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0164498
   The People's Government of Guangdong Province, 2011, HIGH TEMP LAB PROT M
   The State Administration of Work Safety, 2012, ADM MEAS HEATSTR PRE
   Uebll K, 2013, SWISS MED WKLY, V143, DOI 10.4414/smw.2013.13902
   Uehli K, 2014, SLEEP MED REV, V18, P61, DOI 10.1016/j.smrv.2013.01.004
   UNDP, 2016, CLIM CHANG LAB IMP H
   Wang HC, 2015, INT J ENV RES PUB HE, V12, P6006, DOI 10.3390/ijerph120606006
   Watts N, 2017, LANCET, V389, P1151, DOI 10.1016/S0140-6736(16)32124-9
   Xiang J., 2014, ENVIRON RES, P90
   Xiang JJ, 2014, IND HEALTH, V52, P91, DOI 10.2486/indhealth.2012-0145
   Xiang JJ, 2014, OCCUP ENVIRON MED, V71, P246, DOI 10.1136/oemed-2013-101584
   Zhao Y, 2016, P NATL ACAD SCI USA, V113, P4640, DOI 10.1073/pnas.1521828113
NR 41
TC 54
Z9 56
U1 2
U2 34
PU ELSEVIER GMBH
PI MUNICH
PA HACKERBRUCKE 6, 80335 MUNICH, GERMANY
SN 1438-4639
EI 1618-131X
J9 INT J HYG ENVIR HEAL
JI Int. J. Hyg. Environ. Health.
PD APR
PY 2018
VL 221
IS 3
BP 423
EP 428
DI 10.1016/j.ijheh.2018.01.005
PG 6
WC Public, Environmental & Occupational Health; Infectious Diseases
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Public, Environmental & Occupational Health; Infectious Diseases
GA GM6ZQ
UT WOS:000438327900006
PM 29361390
DA 2025-01-10
ER

PT J
AU Khosravi, F
   Soares, MB
   Teixeira, M
   Fontes, N
   Graca, A
AF Khosravi, Fatemeh
   Soares, Marta Bruno
   Teixeira, Marta
   Fontes, Natacha
   Graca, Antonio
TI Assessing the usability and value of a climate service in the wine
   sector
SO CLIMATE SERVICES
LA English
DT Article
DE Climate services; Usability; Assessment; Value of climate information;
   Decision-making; Wine sector
ID INFORMATION; VITICULTURE; PREDICTION; MANAGERS; SCIENCE; LEARN
AB Climate change can significantly affect and influence, both positively and negatively, the wine sector. In this context, the adoption of timely, cost-effective adaptation strategies may contribute to reduce such risks, maximise opportunities, and enhancing the sector's resilience to changing climatic conditions. Climate services involve the production and use of climate information to support decision-makers adapting to climate variability and change. Assessing the value and benefits of using climate services constitutes a critical area of research and can help climate service providers identify any barriers in their development, uptake, and use. The climate service developed in this research benefitted from a co-production approach with a Portuguese Wine company SOGRAPE. In this paper, we aim to assess the usability and value of the climate service co-developed with SOGRAPE and identify possible barriers that limited the tool's usability and value. Engagement with SOGRAPE users was pursued based on mixed methods approach throughout the various stages of co-development and testing of the tool. The results show that the data provided in the Dashboard was perceived as reliable and legitimate. However, the saliency of the Dashboard was questioned, and some recommendations proposed to increase its saliency and overall usability. More importantly, SOGRAPE users were not able to use the climate information provided in the tool due to a number of barriers which are also reported in this study. The findings and recommendations from this study will help inform the design, development and usability of other climate services within and beyond the wine sector.
C1 [Khosravi, Fatemeh] Univ East London, Sustainabil Res Inst, London, England.
   [Soares, Marta Bruno] Univ Leeds, Sustainabil Res Inst, Sch Earth & Environm, Leeds, England.
   [Teixeira, Marta; Fontes, Natacha; Graca, Antonio] Sogrape Vinhos SA, P-4430809 Avintes, Portugal.
C3 University of East London; University of Leeds
RP Khosravi, F (corresponding author), Univ East London, Sustainabil Res Inst, London, England.
RI Soares, Marta/KXR-3872-2024
OI Graca, Antonio/0000-0003-1083-4386; khosravi,
   Fatemeh/0000-0002-3453-1729
FU European Union [776467]
FX This research was funded by the MED-GOLD (Turning climate-related
   information into added value for traditional MEDiterranean Grape, Olive
   and Durum wheat food systems) project through the European Union's
   Horizon 2020 research and innovation programme under grant agreement No.
   776467. The authors wish to thank the MED- GOLD team including Sara
   Silva, Alessandro Dell'Aquila, Nube Gonzalez-Reviriego, Rauel Marcos,
   Christos Giannakopoulos, and Konstantinos V. Varotsos.
CR Adams P., 2015, WMO Bull., DOI [10.13140/RG.2.1.1029.0645, DOI 10.13140/RG.2.1.1029.0645]
   Anderson G., 2015, WMO-No. 1153
   [Anonymous], 1997, Agendas, Alternatives, and Public Agenda
   [Anonymous], 2013, Eos., DOI DOI 10.1002/2013EO110002
   Arias LA, 2022, FRONT PLANT SCI, V13, DOI 10.3389/fpls.2022.835425
   Babin N, 2021, CALIF AGR, V75, P142, DOI 10.3733/ca.2021a0019
   Bessembinder J, 2019, CLIM SERV, V16, DOI 10.1016/j.cliser.2019.100135
   Brown M, 2017, WEATHER CLIM SOC, V9, P39, DOI 10.1175/WCAS-D-16-0034.1
   Bruno Soares M., 2019, H2020 Environment & Resources
   Buontempo C, 2018, CLIM SERV, V9, P21, DOI 10.1016/j.cliser.2017.06.003
   Cash DW, 2006, SCI TECHNOL HUM VAL, V31, P465, DOI 10.1177/0162243906287547
   Cash DW, 2003, P NATL ACAD SCI USA, V100, P8086, DOI 10.1073/pnas.1231332100
   Ceglar A, 2021, NPJ CLIM ATMOS SCI, V4, DOI 10.1038/s41612-021-00198-3
   DellAquila A., 2021, Report on the climatic, bioclimatic and extreme climate indices developed in the wine pilot services. MED-GOLD Project
   Dunn MR, 2015, AUST J GRAPE WINE R, V21, P226, DOI 10.1111/ajgw.12138
   Dunn M, 2019, REG ENVIRON CHANGE, V19, P723, DOI 10.1007/s10113-017-1240-3
   Evely AC, 2010, ENVIRON CONSERV, V37, P442, DOI 10.1017/S0376892910000792
   Falloon P, 2018, CLIM SERV, V9, P86, DOI 10.1016/j.cliser.2017.08.002
   Fazey I, 2014, GLOBAL ENVIRON CHANG, V25, P204, DOI 10.1016/j.gloenvcha.2013.12.012
   Fraga H, 2017, AUST J GRAPE WINE R, V23, P296, DOI 10.1111/ajgw.12278
   Fraga H, 2012, FOOD ENERGY SECUR, V1, P94, DOI 10.1002/fes3.14
   Gettelman A, 2016, Usability of Climate Model Projections by Practitioners
   Haines S, 2019, CLIMATIC CHANGE, V157, P43, DOI 10.1007/s10584-018-2357-1
   Hewitt CD, 2018, B AM METEOROL SOC, V99, P1997, DOI 10.1175/BAMS-D-18-0022.1
   Khosravi F, 2021, SCI TOTAL ENVIRON, V750, DOI 10.1016/j.scitotenv.2020.141637
   Kushnir Y, 2019, NAT CLIM CHANGE, V9, P94, DOI 10.1038/s41558-018-0359-7
   Lemos MC, 2019, WEATHER CLIM SOC, V11, P535, DOI 10.1175/WCAS-D-18-0075.1
   Lemos MC, 2012, NAT CLIM CHANGE, V2, P789, DOI [10.1038/NCLIMATE1614, 10.1038/nclimate1614]
   Lemos MC, 2008, J AM WATER RESOUR AS, V44, P1388, DOI 10.1111/j.1752-1688.2008.00231.x
   Marcos-Matamoros R., 2020, Report on the methodology followed to implement the wine pilot services. MED-GOLD Project
   Marcos-Matamoros R., 2020, 2 FEEDBACK REPORT US
   Martins J, 2021, AGRONOMY-BASEL, V11, DOI 10.3390/agronomy11050990
   McNie EC, 2007, ENVIRON SCI POLICY, V10, P17, DOI 10.1016/j.envsci.2006.10.004
   McNie EC, 2013, WEATHER CLIM SOC, V5, P14, DOI 10.1175/WCAS-D-11-00034.1
   Met Office, 2019, Report on the assessment of quality of seasonal forecasts and climate projections
   Mihailescu E, 2020, FRONT SUSTAIN FOOD S, V4, DOI 10.3389/fsufs.2020.00064
   Nesbitt A, 2022, OENO ONE, V56, P69, DOI 10.20870/oeno-one.2022.56.3.5398
   Nicolls J., 1996, World Climate Applications and Services Programme, V38
   OIV, 2018, OIV Statistical Report On World Viti viniculture
   Ranasinghe R., 2021, IN PRESS
   Robinson J.B., 2006, Science Public Policy, V33, P151, DOI DOI 10.3152/147154306781779064
   Ruti PM, 2020, B AM METEOROL SOC, V101, pE23, DOI 10.1175/BAMS-D-17-0302.1
   Santos JA, 2020, AGR FOREST METEOROL, V291, DOI 10.1016/j.agrformet.2020.108095
   Santos JA, 2020, APPL SCI-BASEL, V10, DOI 10.3390/app10093092
   Soares MB, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.587
   Soares MB, 2017, ADV SCI RES, V14, P175, DOI 10.5194/asr-14-175-2017
   Soares MB, 2018, WIRES CLIM CHANGE, V9, DOI 10.1002/wcc.523
   Soares MB, 2018, CLIM SERV, V9, P5, DOI 10.1016/j.cliser.2017.06.001
   Tall A., 2013, DEV METHODOLOGY EVAL
   Tall A, 2018, CLIM SERV, V11, P1, DOI 10.1016/j.cliser.2018.06.001
   Tavares C, 2010, 3RD ANNUAL EUROMED CONFERENCE OF THE EUROMED ACADEMY OF BUSINESS: BUSINESS DEVELOPMENTS ACROSS COUNTRIES AND CULTURES, P1073
   Teixeira M., 2018, Report on the two case studies at seasonaland long-term timescales for the wine sector
   VanderMolen K, 2020, ENVIRON MANAGE, V65, P178, DOI 10.1007/s00267-019-01237-9
   Vaughan C, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.586
   Vaughan C, 2018, WEATHER CLIM SOC, V10, P373, DOI 10.1175/WCAS-D-17-0030.1
   Vincent K, 2020, CLIM RISK MANAG, V29, DOI 10.1016/j.crm.2020.100242
   Vincent K, 2018, CLIM SERV, V12, P48, DOI 10.1016/j.cliser.2018.11.001
   Wall TU, 2017, WEATHER CLIM SOC, V9, P95, DOI 10.1175/WCAS-D-16-0008.1
   Weisheimer A, 2014, J R SOC INTERFACE, V11, DOI 10.1098/rsif.2013.1162
   White CJ, 2017, METEOROL APPL, V24, P315, DOI 10.1002/met.1654
   Williams DS, 2020, CLIM SERV, V19, DOI 10.1016/j.cliser.2020.100180
   Wine spectator, 2019, Portugal's Largest Wine Company Bets Big on White Wine Grape Arinto
   World Meteorological Organization (WMO), 2011, Report No. WMO-No. 1065
   Zeng YJ, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11101186
NR 64
TC 0
Z9 0
U1 5
U2 5
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2405-8807
J9 CLIM SERV
JI Clim. Serv.
PD APR
PY 2024
VL 34
AR 100496
DI 10.1016/j.cliser.2024.100496
EA JUN 2024
PG 11
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 UZ7U7
UT WOS:001251960900001
OA gold
DA 2025-01-10
ER

PT J
AU Xie, L
   Macken, A
   Johnsen, B
   Norli, M
   Skogan, OAS
   Tollefsen, KE
AF Xie, Li
   Macken, Ailbhe
   Johnsen, Bjorn
   Norli, Marit
   Skogan, Odd Arne Segtnan
   Tollefsen, Knut Erik
TI The MicroClimate Screen - A microscale climate exposure system for
   assessing the effect of CO<sub>2</sub>, temperature and UV on marine
   microalgae
SO MARINE ENVIRONMENTAL RESEARCH
LA English
DT Article
DE Climatechange; Micro-scaleexposuresystem; Oceanacidification;
   Temperature; Ultravioletradiation; Diatom
ID OCEAN ACIDIFICATION; SKELETONEMA-COSTATUM; CARBON UPTAKE; GROWTH;
   RADIATION
AB Global warming and anthropogenic activities are changing the ocean, inducing profound impacts on marine life and ecosystems from changing physical and chemical factors in and above the water column. Rising surface temperatures, ocean acidification, and seasonal variations in UV radiation (UVR), modulated by water clarity and sea-ice extent, affect life cycles of the marine food-web, and directly or indirectly also the global carbon fixation. Diatoms, pelagic microalgae that are responsible for 40% of the marine productivity, have limited capability to avoid exposure to changing ocean conditions, and hence, highly relevant for model studies of the influence of climate change on growth and productivity in the marine environment. A plate-based high -throughput exposure system was constructed to assess the biological effects from relevant climate change factors on the diatom Skeletonema pseudocostatum, conducted as a chronic toxicity tests over 72 h periods. The exposure system consisted of a micro-climate unit and a light-exposure unit, enabling accurate regulation of pCO(2), temperature, UVR and photosynthetic active radiation (PAR). Changes in physical factors, including pH, dissolved inorganic carbon (DIC), total alkalinity (TA), temperature and salinity in the medium, as well as reduction in growth were characterised to demonstrate performance of the micro exposure system. The results demonstrate that the exposure system successfully simulated ocean acidification and could maintain stable temperature (CV < 3%), PAR and UVR irradiance (CV < 8%). Growth inhibition responses were typically dose-dependent and verified that the micro-exposure system could be used to assess effects and adaptions to climate-relevant stressors.
C1 [Xie, Li; Macken, Ailbhe; Norli, Marit; Skogan, Odd Arne Segtnan; Tollefsen, Knut Erik] Norwegian Inst Water Res NIVA, Okernveien 94, N-0579 Oslo, Norway.
   [Tollefsen, Knut Erik] Norwegian Univ Life Sci NMBU, Ctr Environm Radioact, Post Box 5003, N-1432 As, Norway.
   [Johnsen, Bjorn] Norwegian Radiat & Nucl Safety Author DSA, Grini Naeringspark 13, NO-1361 Osteras, Norway.
   [Tollefsen, Knut Erik] Norwegian Univ Life Sci NMBU, Fac Environm Sci & Nat Resource Management, Post Box 5003, N-1432 As, Norway.
   [Tollefsen, Knut Erik] Norwegian Inst Water Res NIVA, Sect Ecotoxicol & Risk Assessment, Okernveien 94, N-0579 Oslo, Norway.
C3 Norwegian Institute for Water Research (NIVA); Norwegian University of
   Life Sciences; Norwegian University of Life Sciences; Norwegian
   Institute for Water Research (NIVA)
RP Tollefsen, KE (corresponding author), Norwegian Inst Water Res NIVA, Sect Ecotoxicol & Risk Assessment, Okernveien 94, N-0579 Oslo, Norway.
EM knut.erik.tollefsen@niva.no
RI Xie, Li/IAR-0860-2023
OI Tollefsen, Knut Erik/0000-0002-7534-0937
FU Research Council of Norway (RCN) through the Norwegian Institute for
   Water Research basic [160016]; Centres of Excellence (CoE) funding
   scheme [223268]
FX This study was supported by the Research Council of Norway (RCN) through
   the Norwegian Institute for Water Research basic funding (SIS-program on
   Ocean Acidification, RCN contract number 160016) , the Centres of
   Excellence (CoE) funding scheme (RCN contract number 223268) , and the
   NIVA Computational Toxicology Program, NCTP ( www.niva.no/nctp) . The
   skilful assistance of Hans Christian Tollefsen in constructing the light
   controlling systems is also acknowledged.
CR Bach LT, 2019, OCEAN SCI, V15, P1159, DOI 10.5194/os-15-1159-2019
   Bernhard GH, 2020, GEOPHYS RES LETT, V47, DOI 10.1029/2020GL090844
   CHEN CY, 1994, MAR ECOL PROG SER, V109, P83, DOI 10.3354/meps109083
   DeLorenzo ME, 2001, ENVIRON TOXICOL CHEM, V20, P84, DOI 10.1002/etc.5620200108
   DICKSON AG, 1990, J CHEM THERMODYN, V22, P113, DOI 10.1016/0021-9614(90)90074-Z
   DICKSON AG, 1987, DEEP-SEA RES, V34, P1733, DOI 10.1016/0198-0149(87)90021-5
   Gao G, 2018, ENVIRON EXP BOT, V156, P96, DOI 10.1016/j.envexpbot.2018.08.031
   Gao G, 2018, ENVIRON EXP BOT, V147, P95, DOI 10.1016/j.envexpbot.2017.11.014
   Gao G, 2009, J PHYCOL, V45, P119, DOI 10.1111/j.1529-8817.2008.00616.x
   Gregg WW, 2016, FRONT MAR SCI, V3, DOI 10.3389/fmars.2016.00240
   GUILLARD RR, 1962, CAN J MICROBIOL, V8, P229, DOI 10.1139/m62-029
   Häder DP, 2007, PHOTOCH PHOTOBIO SCI, V6, P267, DOI 10.1039/b700020k
   Harley CDG, 2006, ECOL LETT, V9, P228, DOI 10.1111/j.1461-0248.2005.00871.x
   Hays GC, 2005, TRENDS ECOL EVOL, V20, P337, DOI 10.1016/j.tree.2005.03.004
   Koch M, 2013, GLOBAL CHANGE BIOL, V19, P103, DOI 10.1111/j.1365-2486.2012.02791.x
   Mackey KRM, 2015, OCEANOGRAPHY, V28, P74, DOI 10.5670/oceanog.2015.33
   Neale RE, 2021, PHOTOCH PHOTOBIO SCI, V20, P1, DOI 10.1007/s43630-020-00001-x
   Orr JC, 2005, NATURE, V437, P681, DOI 10.1038/nature04095
   Pessoa M. F., 2012, Emirates Journal of Food and Agriculture, V24, P510, DOI 10.9755/ejfa.v24i6.510526
   Petersen K, 2014, AQUAT TOXICOL, V150, P45, DOI 10.1016/j.aquatox.2014.02.013
   Pierrot D., 2006, ORNL/CDIAC-105, DOI DOI 10.3334/CDIAC/OTG.CO2SYS_XLS_CDIAC105A
   Plattner GK, 2001, TELLUS B, V53, P564, DOI 10.1034/j.1600-0889.2001.530504.x
   Rousseaux CS, 2015, GLOBAL BIOGEOCHEM CY, V29, P1674, DOI 10.1002/2015GB005139
   Roy RN, 1996, MAR CHEM, V52, P183, DOI 10.1016/0304-4203(96)83094-5
   Salarzadeh A., 2016, INT J LIFE SCI, V10, P40, DOI [10.3126/ijls.v10i1.14508, DOI 10.3126/ijls.v10i1.14508]
   SMITH RC, 1992, SCIENCE, V255, P952, DOI 10.1126/science.1546292
   von der Gathen P, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-24089-6
   Wu HY, 2009, J PHOTOCH PHOTOBIO B, V94, P82, DOI 10.1016/j.jphotobiol.2008.10.005
   Wu Y, 2010, BIOGEOSCIENCES, V7, P2915, DOI 10.5194/bg-7-2915-2010
   Wu Y, 2014, LIMNOL OCEANOGR, V59, P1027, DOI 10.4319/lo.2014.59.3.1027
   Xie L, 2020, PLANTA, V252, DOI 10.1007/s00425-020-03482-3
   Yuan WB, 2018, MAR ENVIRON RES, V135, P63, DOI 10.1016/j.marenvres.2018.01.016
NR 32
TC 1
Z9 1
U1 3
U2 13
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0141-1136
EI 1879-0291
J9 MAR ENVIRON RES
JI Mar. Environ. Res.
PD JUL
PY 2022
VL 179
AR 105670
DI 10.1016/j.marenvres.2022.105670
PG 6
WC Environmental Sciences; Marine & Freshwater Biology; Toxicology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Marine & Freshwater Biology;
   Toxicology
GA 3A4KW
UT WOS:000827231600003
PM 35728490
OA Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Nik, VM
   Moazami, A
AF Nik, Vahid M.
   Moazami, Amin
TI Using collective intelligence to enhance demand flexibility and climate
   resilience in urban areas
SO APPLIED ENERGY
LA English
DT Article
DE Collective intelligence; Demand flexibility; Climate flexibility;
   Climate resilience; Demand side management; Urban energy system
ID THERMAL-ENERGY STORAGE; WEATHER DATA SETS; EXTREME WEATHER; RENEWABLE
   ENERGY; RETROFITTING MEASURES; SELF-ORGANIZATION; SIDE MANAGEMENT;
   FUTURE CLIMATE; COMBINED HEAT; POWER
AB Collective intelligence (CI) is a form of distributed intelligence that emerges in collaborative problem solving and decision making. This work investigates the potentials of CI in demand side management (DSM) in urban areas. CI is used to control the energy performance of representative groups of buildings in Stockholm, aiming to increase the demand flexibility and climate resilience in the urban scale. CI-DSM is developed based on a simple communication strategy among buildings, using forward (1) and backward (0) signals, corresponding to applying and disapplying the adaptation measure, which is extending the indoor temperature range. A simple platform and algorithm are developed for modelling CI-DSM, considering two timescales of 15 min and 60 min. Three climate scenarios are used to represent typical, extreme cold and extreme warm years in Stockholm. Several indicators are used to assess the performance of CI-DSM, including Demand Flexibility Factor (DFF) and Agility Factor (AF), which are defined explicitly for this work. According to the results, CI increases the autonomy and agility of the system in responding to climate shocks without the need for computationally extensive central decision making systems. CI helps to gradually and effectively decrease the energy demand and absorb the shock during extreme climate events. Having a finer control timescale increases the flexibility and agility on the demand side, resulting in a faster adaptation to climate variations, shorter engagement of buildings, faster return to normal conditions and consequently a higher climate resilience.
C1 [Nik, Vahid M.] Lund Univ, Div Bldg Phys, Dept Bldg & Environm Technol, SE-22363 Lund, Sweden.
   [Nik, Vahid M.] Chalmers Univ Technol, Div Bldg Technol, Dept Architecture & Civil Engn, SE-41258 Gothenburg, Sweden.
   [Nik, Vahid M.] Queensland Univ Technol QUT, Inst Future Environm IFE, Garden Point Campus,2 George St, Brisbane, Qld 4000, Australia.
   [Moazami, Amin] NTNU Norwegian Univ Sci & Technol, Dept Ocean Operat & Civil Engn, Fac Engn, Alesund, Norway.
C3 Lund University; Chalmers University of Technology; Queensland
   University of Technology (QUT); Norwegian University of Science &
   Technology (NTNU)
RP Nik, VM (corresponding author), Lund Univ, Div Bldg Phys, Dept Bldg & Environm Technol, SE-22363 Lund, Sweden.
EM vahid.nik@byggtek.lth.se; amin.moazami@ntnu.no
RI ; Nik, Vahid M./K-2632-2016
OI Moazami, Amin/0000-0003-1622-2444; Nik, Vahid M./0000-0002-1497-4813
FU Swedish Research Council for Sustainable Development [Formas
   2016-20123]; joint programming initiative 'ERA-Net Smart Energy Systems'
   focus initiative on Integrated, Regional Energy Systems; European
   Union's Horizon 2020 research and innovation programme [775970]
FX In memory of legendary Mohammad-Reza Shajarian whose character and music
   have been always inspiring for the authors. This work was supported by
   the Swedish Research Council for Sustainable Development [Formas
   2016-20123] and the framework of the joint programming initiative
   'ERA-Net Smart Energy Systems' focus initiative on Integrated, Regional
   Energy Systems, with support from the European Union's Horizon 2020
   research and innovation programme [775970].
CR Aghaei J, 2013, RENEW SUST ENERG REV, V18, P64, DOI 10.1016/j.rser.2012.09.019
   [Anonymous], 2015, NIAC FRAMEWORK ESTAB
   [Anonymous], 2010, CLIMATE SIMULATION A
   [Anonymous], 2012, Climate change and energy systems: impacts, risks and adaptation in the Nordic and Baltic Countries
   [Anonymous], 2015, WORLD EN OUTL SPEC B
   [Anonymous], 2011, World Urbanization Prospects: The 2011 Revision
   [Anonymous], 2012, THESIS CHALMERS U TE
   [Anonymous], CONTRIBUTION WORKING, DOI [DOI 10.1017/CBO9781107415324, 10.1017/CBO9781107415324]
   Badjonski M, 1999, OBJECT ORIENTED TECH, P111, DOI [10.1533/9781782420613.111, DOI 10.1533/9781782420613.111]
   Bartusch C, 2011, ENERG POLICY, V39, P5008, DOI 10.1016/j.enpol.2011.06.013
   Boykoff MT, 2010, GLOBAL ENVIRON CHANG, V20, P53, DOI 10.1016/j.gloenvcha.2009.09.003
   Carreiro AM, 2017, RENEW SUST ENERG REV, V73, P1160, DOI 10.1016/j.rser.2017.01.179
   Charpentier A, 2011, CLIMATIC CHANGE, V109, P245, DOI 10.1007/s10584-010-9944-0
   Chaudry M., 2011, BUILDING RESILIENT U
   Chen Y, 2018, ANNU REV ENV RESOUR, V43, P35, DOI 10.1146/annurev-environ-102017-030052
   D'Oca S, 2017, ENERGY RES SOC SCI, V34, P240, DOI 10.1016/j.erss.2017.08.002
   Damper RI, 2000, INT J SYST SCI, V31, P811, DOI 10.1080/002077200406543
   De Coninck R, 2016, APPL ENERG, V162, P653, DOI 10.1016/j.apenergy.2015.10.114
   De Wolf T, 2005, LECT NOTES COMPUT SC, V3464, P1
   Dounis AI, 2009, RENEW SUST ENERG REV, V13, P1246, DOI 10.1016/j.rser.2008.09.015
   FARLEY BG, 1954, IRE T INFORM THEOR, P76, DOI 10.1109/TIT.1954.1057468
   Finck C, 2020, APPL ENERG, V263, DOI 10.1016/j.apenergy.2020.114671
   Finck C, 2018, APPL ENERG, V209, P409, DOI 10.1016/j.apenergy.2017.11.036
   Forzieri Giovanni, 2017, Lancet Planet Health, V1, pe200, DOI 10.1016/S2542-5196(17)30082-7
   Gelazanskas L, 2014, SUSTAIN CITIES SOC, V11, P22, DOI 10.1016/j.scs.2013.11.001
   Heylighen F, 2013, UNDERST COMPLEX SYST, P117
   Hong TZ, 2018, BUILD SIMUL-CHINA, V11, P1, DOI 10.1007/s12273-017-0396-6
   Intelligence Swarm, 1999, NATURAL ARTIFICIAL S
   IPCC, 2018, GLOB WARM 1 5C SUMM
   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, 2019, SUSTAIN CITIES SOC, V49, DOI 10.1016/j.scs.2019.101597
   Javanroodi K, 2018, APPL ENERG, V231, P714, DOI 10.1016/j.apenergy.2018.09.116
   Jensen SO, 2017, ENERG BUILDINGS, V155, P25, DOI 10.1016/j.enbuild.2017.08.044
   Johansson Johansson Christian Christian, INTELLIGENT DISTRICT
   Joo JY, 2013, IEEE T SMART GRID, V4, P2081, DOI 10.1109/TSG.2013.2261565
   Kaiser Reinhard, 2007, Am J Public Health, V97 Suppl 1, pS158, DOI 10.2105/AJPH.2006.100081
   Kammen DM, 2016, SCIENCE, V352, P922, DOI 10.1126/science.aad9302
   Ke XD, 2016, APPL ENERG, V183, P504, DOI 10.1016/j.apenergy.2016.08.188
   Kenward A., 2014, CLIMATE CENTRAL, V10, P1
   Kysely J, 2010, INT J CLIMATOL, V30, P89, DOI 10.1002/joc.1874
   Le Dréau J, 2016, ENERGY, V111, P991, DOI 10.1016/j.energy.2016.05.076
   Le Guen M, 2018, ENERG BUILDINGS, V158, P906, DOI 10.1016/j.enbuild.2017.10.057
   Lopes RA, 2016, ENRGY PROCED, V91, P1053, DOI 10.1016/j.egypro.2016.06.274
   Luber G, 2008, AM J PREV MED, V35, P429, DOI 10.1016/j.amepre.2008.08.021
   Lund PD, 2015, RENEW SUST ENERG REV, V45, P785, DOI 10.1016/j.rser.2015.01.057
   Magnan AK, 2016, WIRES CLIM CHANGE, V7, P646, DOI 10.1002/wcc.409
   Mainzer K, 2014, Nat. Works Complex. Interdiscip. Res. Appl, P19, DOI [10.1007/978-3-319-00254-5_2, DOI 10.1007/978-3-319-00254-5_2]
   Mauree D, 2019, RENEW SUST ENERG REV, V112, P733, DOI 10.1016/j.rser.2019.06.005
   Mavromatidis G, 2018, RENEW SUST ENERG REV, V88, P258, DOI 10.1016/j.rser.2018.02.021
   McArthur SDJ, 2007, IEEE T POWER SYST, V22, P1743, DOI 10.1109/TPWRS.2007.908471
   McIlvennie C, 2020, ENERGY RES SOC SCI, V68, DOI 10.1016/j.erss.2020.101555
   Moazami A, 2019, APPL ENERG, V238, P696, DOI 10.1016/j.apenergy.2019.01.085
   Mondada F, 2004, AUTON ROBOT, V17, P193, DOI 10.1023/B:AURO.0000033972.50769.1c
   Najjar YSH, 2001, APPL THERM ENG, V21, P407, DOI 10.1016/S1359-4311(00)00033-8
   Nik VM, 2021, NATL SCI REV, V8, DOI 10.1093/nsr/nwaa134
   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, 2016, ENERG BUILDINGS, V121, P176, DOI 10.1016/j.enbuild.2016.03.044
   Nik VM, 2015, ENRGY PROCED, V78, P955, DOI 10.1016/j.egypro.2015.11.031
   Nik VM, 2015, ENERG BUILDINGS, V88, P262, DOI 10.1016/j.enbuild.2014.11.015
   Nik VM, 2013, BUILD ENVIRON, V60, P291, DOI 10.1016/j.buildenv.2012.11.005
   Nuytten T, 2013, APPL ENERG, V104, P583, DOI 10.1016/j.apenergy.2012.11.029
   Ottesen SO, 2015, ENERGY, V88, P364, DOI 10.1016/j.energy.2015.05.049
   Ottino JM, 2004, NATURE, V427, P399, DOI 10.1038/427399a
   Panteli M, 2015, ELECTR POW SYST RES, V127, P259, DOI 10.1016/j.epsr.2015.06.012
   Perera ATD, 2020, APPL ENERG, V262, DOI 10.1016/j.apenergy.2020.114580
   Perera ATD, 2020, NAT ENERGY, V5, P150, DOI 10.1038/s41560-020-0558-0
   Perera ATD, 2019, APPL ENERG, V253, DOI 10.1016/j.apenergy.2019.113572
   Perera ATD, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-53653-w
   Perera ATD, 2019, APPL ENERG, V243, P191, DOI 10.1016/j.apenergy.2019.03.202
   Perera ATD, 2016, OPTIMUM DESIGN CONTR
   Perrone D, 2014, WIRES WATER, V1, P49, DOI 10.1002/wat2.1004
   Petersen MK, 2013, P AMER CONTR CONF, P1150
   Reynders G, 2017, APPL ENERG, V198, P192, DOI 10.1016/j.apenergy.2017.04.061
   Robine JM, 2008, CR BIOL, V331, P171, DOI 10.1016/j.crvi.2007.12.001
   Sansavini G, 2014, RENEW ENERG, V64, P71, DOI 10.1016/j.renene.2013.11.002
   Schulz N, 2010, J URBAN TECHNOL, V17, P3, DOI 10.1080/10630732.2010.553038
   Schut MC, 2010, INFORM SCIENCES, V180, P132, DOI 10.1016/j.ins.2009.08.006
   Sethi A. K., 1990, International Journal of Flexible Manufacturing Systems, V2, P289, DOI 10.1007/BF00186471
   Soroudi A, 2017, RENEW ENERG, V102, P316, DOI 10.1016/j.renene.2016.10.051
   Spiliotis K, 2016, APPL ENERG, V182, P613, DOI 10.1016/j.apenergy.2016.08.145
   Strbac G, 2008, ENERG POLICY, V36, P4419, DOI 10.1016/j.enpol.2008.09.030
   Suran S, 2020, ACM COMPUT SURV, V53, DOI 10.1145/3368986
   Vázquez-Canteli JR, 2019, APPL ENERG, V235, P1072, DOI 10.1016/j.apenergy.2018.11.002
   Wei C, 2020, COMPLEXITY, V2020, DOI 10.1155/2020/5908102
   Wong P.C., 2009, AAAI Spring Symposium: Technosocial Predictive Analytics, P148
   Wooldridge M, 1999, MULTIAGENT SYSTEMS, P27
   Wooldridge M., 2009, INTRO MULTIAGENT SYS
   Xiao P., 2018, THESIS
   Zhou KL, 2016, RENEW SUST ENERG REV, V56, P215, DOI 10.1016/j.rser.2015.11.050
NR 91
TC 28
Z9 29
U1 3
U2 22
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 JAN 1
PY 2021
VL 281
AR 116106
DI 10.1016/j.apenergy.2020.116106
PG 17
WC Energy & Fuels; Engineering, Chemical
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Energy & Fuels; Engineering
GA OU2RS
UT WOS:000591381500011
OA Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Ahrens, CW
   Byrne, M
   Rymer, PD
AF Ahrens, Collin W.
   Byrne, Margaret
   Rymer, Paul D.
TI Standing genomic variation within coding and regulatory regions
   contributes to the adaptive capacity to climate in a foundation tree
   species
SO MOLECULAR ECOLOGY
LA English
DT Article
DE Eucalyptus sensu lato; genotype environment association; landscape
   genomics; local adaptation; standing genetic variation
ID LOCAL ADAPTATION; CANDIDATE GENES; ABSCISIC-ACID; EUCALYPTUS; LANDSCAPE;
   TEMPERATURE; DIVERSITY; RESPONSES; DROUGHT; FOREST
AB Global climate is rapidly changing, and the ability for tree species to adapt is dependent on standing genomic variation; however, the distribution and abundance of functional and adaptive variants are poorly understood in natural systems. We test key hypotheses regarding the genetics of adaptive variation in a foundation tree: genomic variation is associated with climate, and genomic variation is more likely to be associated with temperature than precipitation or aridity. To test these hypotheses, we used 9,593 independent, genomic single-nucleotide polymorphisms (SNPs) from 270 individuals sampled from Corymbia calophylla's entire distribution in south-western Western Australia, spanning orthogonal temperature and precipitation gradients. Environmental association analyses returned 537 unique SNPs putatively adaptive to climate. We identified SNPs associated with climatic variation (i.e., temperature [458], precipitation [75] and aridity [78]) across the landscape. Of these, 78 SNPs were nonsynonymous (NS), while 26 SNPs were found within gene regulatory regions. The NS and regulatory candidate SNPs associated with temperature explained more deviance (27.35%) than precipitation (5.93%) and aridity (4.77%), suggesting that temperature provides stronger adaptive signals than precipitation. Genes associated with adaptive variants include functions important in stress responses to temperature and precipitation. Patterns of allelic turnover of NS and regulatory SNPs show small patterns of change through climate space with the exception of an aldehyde dehydrogenase gene variant with 80% allelic turnover with temperature. Together, these findings provide evidence for the presence of adaptive variation to climate in a foundation species and provide critical information to guide adaptive management practices.
C1 [Ahrens, Collin W.; Rymer, Paul D.] Western Sydney Univ, Hawkesbury Inst Environm, Hawkesbury Campus,Locked Bag 1797, Penrith, NSW 2751, Australia.
   [Byrne, Margaret] Dept Biodivers Conservat & Attract, Biodivers & Conservat Sci, Perth, WA, Australia.
C3 Western Sydney University
RP Rymer, PD (corresponding author), Western Sydney Univ, Hawkesbury Inst Environm, Hawkesbury Campus,Locked Bag 1797, Penrith, NSW 2751, Australia.
EM p.rymer@westernsydney.edu.au
RI Byrne, Margaret/H-8198-2015
OI Byrne, Margaret/0000-0002-7197-5409; Rymer, Paul/0000-0003-0988-4351;
   Ahrens, Collin/0000-0002-0614-9928
FU Australian Research Council [LP150100936]; Western Australia Department
   of Biodiversity, Conservation, and Attractions; Australian Research
   Council [LP150100936] Funding Source: Australian Research Council
FX We thank Bronwyn Macdonald and Richard Mazanec for the field collections
   and laboratory work, and the anonymous reviewers for their helpful
   suggestions. We thank the anonymous reviewers and Prof Victoria Sork for
   their helpful suggestions on this manuscript. Funding and/or in-kind
   support was provided by the Australian Research Council (LP150100936)
   and Western Australia Department of Biodiversity, Conservation, and
   Attractions. Permission for use of the draft Corymbia citriodora genome
   as granted by Merv Sheppard (Corymbia Genome Project: ).
CR Afzal AJ, 2008, MOL PLANT MICROBE IN, V21, P507, DOI 10.1094/MPMI-21-5-0507
   Ahrens CW, 2019, EVOL APPL, V12, P1178, DOI 10.1111/eva.12796
   Ahrens CW, 2018, MOL ECOL, V27, P1342, DOI 10.1111/mec.14549
   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
   Allen CD, 2010, FOREST ECOL MANAG, V259, P660, DOI 10.1016/j.foreco.2009.09.001
   [Anonymous], SHORT MANUAL SNMF PR
   [Anonymous], STAT ENV REP
   [Anonymous], EVOLUTIONARY IMPACTS
   [Anonymous], FOR MAN PLAN 2014 20
   Aspinwall MJ, 2017, TREE PHYSIOL, V37, P1095, DOI 10.1093/treephys/tpx047
   Assmann SM, 2016, CURR OPIN PLANT BIOL, V33, P157, DOI 10.1016/j.pbi.2016.07.003
   Bates BC, 2008, CLIMATIC CHANGE, V89, P339, DOI 10.1007/s10584-007-9390-9
   Blackman CJ, 2017, TREE PHYSIOL, V37, P583, DOI 10.1093/treephys/tpx005
   BOOTH JD, 1994, CRUSTACEANA, V66, P271, DOI 10.1163/156854094X00035
   Byrne M, 2001, BIOTECHNIQUES, V30, P742, DOI 10.2144/01304bm06
   Byrne M., 2008, Phylogeny, diversity and evolution of eucalypt, P303
   Cahill AE, 2014, J BIOGEOGR, V41, P429, DOI 10.1111/jbi.12231
   Cong L, 2013, SCIENCE, V339, P819, DOI 10.1126/science.1231143
   Coop G, 2010, GENETICS, V185, P1411, DOI 10.1534/genetics.110.114819
   De Mita S, 2013, MOL ECOL, V22, P1383, DOI 10.1111/mec.12182
   de Villemereuil P, 2014, MOL ECOL, V23, P2006, DOI 10.1111/mec.12705
   Dillon S, 2015, AUSTRAL ECOL, V40, P558, DOI 10.1111/aec.12223
   Dillon S, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0103515
   Doyle J., 1990, Focus, V12, P13
   Ehrenreich IM, 2017, GENETICS, V206, P531, DOI 10.1534/genetics.117.203059
   Elshire RJ, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0019379
   Falconer D.S., 1996, Quantitative Genetics
   Ferrier S, 2007, DIVERS DISTRIB, V13, P252, DOI 10.1111/j.1472-4642.2007.00341.x
   Fick SE, 2017, INT J CLIMATOL, V37, P4302, DOI 10.1002/joc.5086
   Fitzpatrick MC, 2015, ECOL LETT, V18, P1, DOI 10.1111/ele.12376
   Frichot E, 2015, METHODS ECOL EVOL, V6, P925, DOI 10.1111/2041-210X.12382
   Frichot E, 2013, MOL BIOL EVOL, V30, P1687, DOI 10.1093/molbev/mst063
   Fujita Y., 2013, CLIMATE CHANGE ABIOT, P521
   Futuyma D.J., 2013, Evolution, V3rd
   Gautier M., 2015, BAYPASS VERSION 2 1
   Gautier M, 2015, GENETICS, V201, P1555, DOI 10.1534/genetics.115.181453
   Gomulkiewicz R, 2010, EVOL APPL, V3, P97, DOI 10.1111/j.1752-4571.2009.00117.x
   Goudet J, 2005, MOL ECOL NOTES, V5, P184, DOI 10.1111/j.1471-8286.2004.00828.x
   Grewe PM, 2015, SCI REP-UK, V5, DOI 10.1038/srep16916
   Günther T, 2013, GENETICS, V195, P205, DOI 10.1534/genetics.113.152462
   Havens K, 2015, NAT AREA J, V35, P122, DOI 10.3375/043.035.0116
   Hendre PS, 2012, PLANT BIOTECHNOL J, V10, P646, DOI 10.1111/j.1467-7652.2012.00699.x
   Hereford J, 2009, AM NAT, V173, P579, DOI 10.1086/597611
   Hoban S, 2016, AM NAT, V188, P379, DOI 10.1086/688018
   Humplík JF, 2017, TRENDS PLANT SCI, V22, P830, DOI 10.1016/j.tplants.2017.07.009
   Hwang JU, 2016, MOL PLANT, V9, P338, DOI 10.1016/j.molp.2016.02.003
   IPCC, 2018, GLOB WARM 1 5C SUMM
   Jakobsson M, 2007, BIOINFORMATICS, V23, P1801, DOI 10.1093/bioinformatics/btm233
   Johnson DA, 1996, PHYTOPATHOLOGY, V86, P480, DOI 10.1094/Phyto-86-480
   Johnson IG, 2009, SILVAE GENET, V58, P180, DOI 10.1515/sg-2009-0024
   Jordan R, 2017, MOL ECOL, V26, P6002, DOI 10.1111/mec.14341
   Jordan R, 2016, NEW PHYTOL, V212, P992, DOI 10.1111/nph.14084
   Kalunke RM, 2015, FRONT PLANT SCI, V6, DOI 10.3389/fpls.2015.00146
   KASS RE, 1995, J AM STAT ASSOC, V90, P773, DOI 10.1080/01621459.1995.10476572
   Kawecki TJ, 2004, ECOL LETT, V7, P1225, DOI 10.1111/j.1461-0248.2004.00684.x
   Kryazhimskiy S, 2008, PLOS GENET, V4, DOI 10.1371/journal.pgen.1000304
   LANDE R, 1983, HEREDITY, V50, P47, DOI 10.1038/hdy.1983.6
   Lasky JR, 2014, MOL BIOL EVOL, V31, P2283, DOI 10.1093/molbev/msu170
   Leimu R, 2008, PLOS ONE, V3, DOI 10.1371/journal.pone.0004010
   Liu DG, 2016, CURR OPIN PLANT BIOL, V30, P70, DOI 10.1016/j.pbi.2016.01.007
   Lotterhos KE, 2015, MOL ECOL, V24, P1031, DOI 10.1111/mec.13100
   Lynch Michael, 1998
   Mackay TFC, 2009, NAT REV GENET, V10, P565, DOI 10.1038/nrg2612
   Manion G., 2018, gdm: Generalized Dissimilarity Modeling
   Mano S, 2004, PLANT J, V38, P487, DOI 10.1111/j.1365-313X.2004.02063.x
   Matesanz S, 2014, ENVIRON EXP BOT, V103, P53, DOI 10.1016/j.envexpbot.2013.09.004
   Matusick G, 2013, EUR J FOREST RES, V132, P497, DOI 10.1007/s10342-013-0690-5
   Meier IC, 2008, ECOSYSTEMS, V11, P655, DOI 10.1007/s10021-008-9135-2
   Moles AT, 2014, J VEG SCI, V25, P1167, DOI 10.1111/jvs.12190
   Mora F, 2017, J PLANT BIOCHEM BIOT, V26, P274, DOI 10.1007/s13562-016-0389-z
   Myburg AA, 2014, NATURE, V510, P356, DOI 10.1038/nature13308
   Myers N, 2003, BIOSCIENCE, V53, P916
   Oksanen J, 2022, R package version 2.6-2, DOI DOI 10.4135/9781412971874.N145
   Perozich J, 1999, PROTEIN SCI, V8, P137, DOI 10.1110/ps.8.1.137
   Prober SM, 2015, FRONT ECOL EVOL, V3, DOI 10.3389/fevo.2015.00065
   R Core Team, 2015, R LANG ENV STAT COMP
   Rellstab C, 2016, MOL ECOL, V25, P5907, DOI 10.1111/mec.13889
   Rellstab C, 2015, MOL ECOL, V24, P4348, DOI 10.1111/mec.13322
   Ren LP, 2014, BMC GENOMICS, V15, DOI 10.1186/1471-2164-15-844
   Riethoven JJM, 2010, METHODS MOL BIOL, V674, P33, DOI 10.1007/978-1-60761-854-6_3
   Rosenberg NA, 2004, MOL ECOL NOTES, V4, P137, DOI 10.1046/j.1471-8286.2003.00566.x
   Sampson J, 2018, BIOL J LINN SOC, V123, P545, DOI 10.1093/biolinnean/blx168
   Savolainen O, 2013, NAT REV GENET, V14, P807, DOI 10.1038/nrg3522
   Shaw RG, 2012, NEW PHYTOL, V195, P752, DOI 10.1111/j.1469-8137.2012.04230.x
   Silva OB, 2015, NEW PHYTOL, V208, P830, DOI 10.1111/nph.13505
   Simon TN, 2017, COPEIA, V105, P504, DOI 10.1643/CE-16-517
   Sork VL, 2018, J HERED, V109, P3, DOI 10.1093/jhered/esx091
   Sork VL, 2016, AM J BOT, V103, P33, DOI 10.3732/ajb.1500162
   Sridha S, 2006, PLANT J, V46, P124, DOI 10.1111/j.1365-313X.2006.02678.x
   Steane DA, 2017, BIOL J LINN SOC, V121, P484, DOI 10.1093/biolinnean/blw051
   Steane DA, 2014, MOL ECOL, V23, P2500, DOI 10.1111/mec.12751
   Swenson NG, 2007, AM J BOT, V94, P451, DOI 10.3732/ajb.94.3.451
   Valluru R, 2016, FRONT PLANT SCI, V7, DOI 10.3389/fpls.2016.00461
   van Ommen Kloeke AEE, 2012, GLOBAL ECOL BIOGEOGR, V21, P224, DOI 10.1111/j.1466-8238.2011.00667.x
   Vandepoele K, 2009, PLANT PHYSIOL, V150, P535, DOI 10.1104/pp.109.136028
   WEIR BS, 1984, EVOLUTION, V38, P1358, DOI [10.2307/2408641, 10.1111/j.1558-5646.1984.tb05657.x]
   Wickham H, 2009, USE R, P1, DOI 10.1007/978-0-387-98141-3
   Wittkopp PJ, 2012, NAT REV GENET, V13, P59, DOI 10.1038/nrg3095
   Woods A, 2005, BIOSCIENCE, V55, P761, DOI 10.1641/0006-3568(2005)055[0761:IAUDNB]2.0.CO;2
   Wray GA, 2007, NAT REV GENET, V8, P206, DOI 10.1038/nrg2063
   Xiao C, 2014, PLANT CELL, V26, P1018, DOI 10.1105/tpc.114.123968
   Zhang XW, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0049652
   Zhao JY, 2017, J EXP BOT, V68, P4295, DOI 10.1093/jxb/erx194
   Zou YP, 2017, GENOME BIOL, V18, DOI 10.1186/s13059-017-1378-9
NR 105
TC 42
Z9 46
U1 2
U2 47
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 MAY
PY 2019
VL 28
IS 10
BP 2502
EP 2516
DI 10.1111/mec.15092
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 IE2TQ
UT WOS:000472237600006
PM 30950536
DA 2025-01-10
ER

PT J
AU Baldwin, J
AF Baldwin, Jeff
TI Potential mitigation of and adaptation to climate-driven changes in
   California's highlands through increased beaver populations
SO CALIFORNIA FISH AND GAME
LA English
DT Article
DE beaver; Castor canadensis; climate forecasts; California highlands;
   hydrological changes; mitigation; wetland restoration
ID YELLOWSTONE-NATIONAL-PARK; BILL WILLIAMS RIVER; CASTOR-CANADENSIS;
   SIERRA-NEVADA; RIPARIAN VEGETATION; WET MEADOWS; FLOW REGIME; STREAM;
   CHANNEL; MANAGEMENT
AB Climate models forecast significant changes in California's temperature and precipitation patterns. Those changes are likely to affect fluvial and riparian habitat. Across the American West several researchers and civil society groups promote increased beaver (Castor canadensis) presence as a means to moderate such changes. This study reviews three literatures in an effort to evaluate the potential for beaver to adapt to and to mitigate anticipated changes in California's higher elevation land- and waterscapes. First, I provide a synopsis of modeled changes in temperatures and precipitation. Forecasts agree that temperatures will continue to increase, to 1.5-4.0 degrees C by 2060; however, forecasts for precipitation are more variable in sign and among models. Second, researchers anticipate climate-driven changes in stream and riparian areas and project that snowpacks and summer flows will continue to decline, winter and spring flood magnitudes will increase, spring stream recession will likely continue to occur earlier and more quickly, and highland fires will be more extensive. Each of these changes has important implications for wildlife and public lands managers. A third focus reviews beaver natural histories and finds that where beaver dams are persistent, they may sequester sediment and create wet meadows that can moderate floods, augment early summer baseflows, sequester carbon in soils and standing biomass, decrease ecological problems posed by earlier spring stream recession, and potentially help cool early summer and post-wildfire stream temperatures. However, due in part to currently limited habitat suitability and to conflicts with other human interests, mitigation would likely be most meaningful on local rather than statewide scales.
C1 [Baldwin, Jeff] Sonoma State Univ, Geog & Global Studies, 1801 East Cotati Ave, Rohnert Pk, CA 94928 USA.
C3 California State University System; Sonoma State University
RP Baldwin, J (corresponding author), Sonoma State Univ, Geog & Global Studies, 1801 East Cotati Ave, Rohnert Pk, CA 94928 USA.
EM Jeffrey.baldwin@sonoma.edu
CR ACS E, 1993, HYDROBIOLOGIA, V249, P125, DOI 10.1007/BF00008849
   Amaranthus M., 1989, P S FIRE WATERSHED M, P75
   Andersen DC, 2010, ECOHYDROLOGY, V3, P325, DOI 10.1002/eco.113
   [Anonymous], U IDAHO B
   [Anonymous], STAT ANAL SELECT
   [Anonymous], RM120 USDA FOR SERV
   [Anonymous], EFFECTS HUMAN INDUCE
   [Anonymous], 1942, GAME B
   [Anonymous], WYOM WAT STREAMS ZON
   [Anonymous], THESIS
   [Anonymous], RIVER RES APPL
   [Anonymous], GROUNDWATER DISCHARG
   [Anonymous], BAY DELTA MODELING F
   [Anonymous], ECOLOGICAL RESTORATI
   [Anonymous], INVESTIGATIONS BEAVE
   [Anonymous], ROCK MOUNT REG SOIL
   [Anonymous], PUBLIC INTEREST ENER
   [Anonymous], 1991, PHYS DIMENSIONS HYDR
   [Anonymous], PUBLIC INTEREST ENER
   [Anonymous], PAPER PRESENTED TO W
   [Anonymous], 2012, NOAA TECH MEMO NMFS
   [Anonymous], OUT CHAING CLIMATE 2
   [Anonymous], BRIEFING PAPER PLUMA
   [Anonymous], 2013, CWS201301 U CAL CTR
   [Anonymous], J CLIMATE
   [Anonymous], AM WAT RES ASS M REN
   [Anonymous], NW SCI
   [Anonymous], W65R UT DEP FISH GAM
   [Anonymous], LIVES GAME ANIMALS B
   [Anonymous], THESIS
   [Anonymous], T N AM WILDLIFE C
   Bailey JK, 2002, ECOLOGY, V83, P1701, DOI 10.1890/0012-9658(2002)083[1701:IAFAAE]2.0.CO;2
   Baker Bruce W., 2003, Lutra, V46, P173
   Baker BW, 2005, ECOL APPL, V15, P110, DOI 10.1890/03-5237
   Baldwin J., 2013, Yearb. Assoc. Pac. Coast Geogr, V75, P104
   Barnett TP, 2008, SCIENCE, V319, P1080, DOI 10.1126/science.1152538
   Bigler W, 2001, PHYS GEOGR, V22, P531, DOI 10.1080/02723646.2001.10642758
   Bonfils C, 2008, CLIMATIC CHANGE, V87, pS43, DOI 10.1007/s10584-007-9374-9
   BROWN GW, 1970, WATER RESOUR RES, V6, P1133, DOI 10.1029/WR006i004p01133
   BROWN S.T., 2011, Lakeline Wetlands, P34
   BUSHER PE, 1983, J MAMMAL, V64, P314, DOI 10.2307/1380566
   Butler D.R., 1994, The Canadian Geographer/Le Geographe canadien, V38, P76, DOI DOI 10.1111/J.1541-0064.1994.TB01519.X
   BUTLER DR, 1995, GEOMORPHOLOGY, V13, P255, DOI 10.1016/0169-555X(95)00031-Y
   Cayan DR, 2008, CLIMATIC CHANGE, V87, pS21, DOI 10.1007/s10584-007-9377-6
   Costa-Cabral M, 2013, CLIMATIC CHANGE, V116, P97, DOI 10.1007/s10584-012-0529-y
   Costa-Cabral M, 2013, CLIMATIC CHANGE, V116, P1, DOI 10.1007/s10584-012-0630-2
   Das T, 2009, J HYDROMETEOROL, V10, P871, DOI 10.1175/2009JHM1095.1
   Das T, 2013, J HYDROL, V501, P101, DOI 10.1016/j.jhydrol.2013.07.042
   Das T, 2011, CLIMATIC CHANGE, V109, P71, DOI 10.1007/s10584-011-0298-z
   DEBANO LF, 1987, WATER RESOUR BULL, V23, P463
   DeVries P, 2012, FISHERIES, V37, P246, DOI 10.1080/03632415.2012.687263
   Diffenbaugh NS, 2015, P NATL ACAD SCI USA, V112, P3931, DOI 10.1073/pnas.1422385112
   Dominguez F, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2011GL050762
   Donkor NT, 2000, PLANT ECOL, V148, P1, DOI 10.1023/A:1009860512339
   Eaton JG, 1996, LIMNOL OCEANOGR, V41, P1109, DOI 10.4319/lo.1996.41.5.1109
   EHRMAN TP, 1992, J N AM BENTHOL SOC, V11, P341, DOI 10.2307/1467556
   Freeman MC, 2001, ECOL APPL, V11, P179, DOI 10.1890/1051-0761(2001)011[0179:FAHEOJ]2.0.CO;2
   Gasith A, 1999, ANNU REV ECOL SYST, V30, P51, DOI 10.1146/annurev.ecolsys.30.1.51
   Gibson PP, 2014, AQUAT CONSERV, V24, P391, DOI 10.1002/aqc.2432
   Hamlet AF, 2005, J HYDROMETEOROL, V6, P330, DOI 10.1175/JHM420.1
   Hammersmark CT, 2008, RIVER RES APPL, V24, P735, DOI 10.1002/rra.1077
   Hayhoe K, 2004, P NATL ACAD SCI USA, V101, P12422, DOI 10.1073/pnas.0404500101
   Hidalgo HG, 2009, J CLIMATE, V22, P3838, DOI 10.1175/2009JCLI2470.1
   Hoffman J., 2013, Effects of Meadow Restoration on Stream Flow in the Feather River Watershed: A Review Based on Monitoring Data and Pertinent Research. Version 5.5 (final). With input and review from Feather River CRM Steering Committee members
   Hood GA, 2007, FOREST ECOL MANAG, V239, P200, DOI 10.1016/j.foreco.2006.12.005
   Ice GG, 2004, J FOREST, V102, P16
   Ives Ronald L., 1942, JOUR GEOMORPH, V5, P191
   Jager HI, 1999, T AM FISH SOC, V128, P222, DOI 10.1577/1548-8659(1999)128<0222:WHCCIS>2.0.CO;2
   James CD, 2012, CALIF FISH GAME, V98, P129
   Johnston CA, 1987, LANDSCAPE ECOL, V1, P47, DOI 10.1007/BF02275265
   Jowett IG, 2005, J FISH BIOL, V66, P1419, DOI 10.1111/j.0022-1112.2005.00693.x
   Klotz RL, 1998, CAN J FISH AQUAT SCI, V55, P1228, DOI 10.1139/cjfas-55-5-1228
   Knowles N, 2006, J CLIMATE, V19, P4545, DOI 10.1175/JCLI3850.1
   Kupferberg SJ, 1996, ECOL APPL, V6, P1332, DOI 10.2307/2269611
   Langhans SD, 2006, OECOLOGIA, V147, P501, DOI 10.1007/s00442-005-0282-2
   Lanman CW, 2013, CALIF FISH GAME, V99, P193
   Lautz LK, 2006, HYDROL PROCESS, V20, P183, DOI 10.1002/hyp.5910
   LIGON FK, 1995, BIOSCIENCE, V45, P183, DOI 10.2307/1312557
   Lind Amy J., 1996, Herpetological Review, V27, P62
   Little AM, 2012, ECOSCIENCE, V19, P246, DOI 10.2980/19-3-3498
   Loheide SP, 2009, HYDROGEOL J, V17, P229, DOI 10.1007/s10040-008-0380-4
   Lowry M.M., 1993, Groundwater elevations and temperature adjacent to a beaver pond in central Oregon
   Lytle DA, 2004, TRENDS ECOL EVOL, V19, P94, DOI 10.1016/j.tree.2003.10.002
   Marchetti MP, 2001, ECOL APPL, V11, P530, DOI 10.1890/1051-0761(2001)011[0530:EOFROF]2.0.CO;2
   MARET TJ, 1987, WATER RES, V21, P263, DOI 10.1016/0043-1354(87)90204-1
   Maurer EP, 2007, J GEOPHYS RES-ATMOS, V112, DOI 10.1029/2006JD008088
   McCullough DA., 1999, A Review and synthesis of effects of alterations to the water temperature regime on freshwater life stages of Salmonids, with special reference to Chinook salmon, DOI DOI 10.1089/GYN.2016.0069
   Meentemeyer RK, 1999, PHYS GEOGR, V20, P436, DOI 10.1080/02723646.1999.10642688
   Moir HJ, 2006, CAN J FISH AQUAT SCI, V63, P2567, DOI 10.1139/F06-137
   NAIMAN RJ, 1986, ECOLOGY, V67, P1254, DOI 10.2307/1938681
   NAIMAN RJ, 1984, OECOLOGIA, V62, P150, DOI 10.1007/BF00379007
   NAIMAN RJ, 1994, ECOLOGY, V75, P905, DOI 10.2307/1939415
   Nakano S, 1999, ECOLOGY, V80, P2435
   Neiman PJ, 2008, J HYDROMETEOROL, V9, P22, DOI 10.1175/2007JHM855.1
   Norton JB, 2014, J SOIL SEDIMENT, V14, P34, DOI 10.1007/s11368-013-0797-9
   Null SE, 2013, CLIMATIC CHANGE, V116, P149, DOI 10.1007/s10584-012-0459-8
   Paetzold A, 2008, J APPL ECOL, V45, P894, DOI 10.1111/j.1365-2664.2008.01463.x
   Parker G, 2003, J HYDRAUL ENG-ASCE, V129, P885, DOI 10.1061/(ASCE)0733-9429(2003)129:11(885)
   Persico L, 2009, QUATERNARY RES, V71, P340, DOI 10.1016/j.yqres.2008.09.007
   Peterson TC, 2013, B AM METEOROL SOC, V94, P821, DOI 10.1175/BAMS-D-12-00066.1
   Pierce DW, 2013, CLIM DYNAM, V40, P839, DOI 10.1007/s00382-012-1337-9
   Pollock MM, 2007, EARTH SURF PROC LAND, V32, P1174, DOI 10.1002/esp.1553
   Pollock MM, 2003, AM FISH S S, V37, P213
   PONCE VM, 1990, WATER RESOUR BULL, V26, P259
   Ralph FM, 2006, GEOPHYS RES LETT, V33, DOI 10.1029/2006GL026689
   Ripple WJ, 2000, BIOL CONSERV, V95, P361, DOI 10.1016/S0006-3207(00)00014-8
   ROOD SB, 1995, CAN J BOT, V73, P1250, DOI 10.1139/b95-136
   RUEDEMANN RUDOLF, 1938, SCIENCE, V88, P523, DOI 10.1126/science.88.2292.523
   Scheffer P.M., 1938, Soil Conservation, V3, P178
   Shafroth PB, 2002, ECOL APPL, V12, P107, DOI 10.1890/1051-0761(2002)012[0107:RVRTAD]2.0.CO;2
   Shafroth PB, 1998, WETLANDS, V18, P577, DOI 10.1007/BF03161674
   Shields FD, 2000, ENVIRON CONSERV, V27, P54, DOI 10.1017/S0376892900000072
   Smith J., 2007, Plant Disturbance Ecology: The Process and the Response, P603
   Stewart IT, 2004, CLIMATIC CHANGE, V62, P217, DOI 10.1023/B:CLIM.0000013702.22656.e8
   Stewart IT, 2005, J CLIMATE, V18, P1136, DOI 10.1175/JCLI3321.1
   Tague C, 2008, WATER RESOUR RES, V44, DOI 10.1029/2007WR006418
   Van Steeter MM, 1998, WATER RESOUR RES, V34, P287, DOI 10.1029/97WR02766
   Walsh J., 2014, Climate change impacts in the United States: the third national climate assessment, DOI [10.7930/J0KW5CXT., DOI 10.7930/J0KW5CXT]
   Wehner MF, 2013, CLIM DYNAM, V40, P59, DOI 10.1007/s00382-012-1393-1
   Westbrook CJ, 2006, WATER RESOUR RES, V42, DOI 10.1029/2005WR004560
   Westerling AL, 2011, CLIMATIC CHANGE, V109, P445, DOI 10.1007/s10584-011-0329-9
   Yarnell SM, 2010, BIOSCIENCE, V60, P114, DOI 10.1525/bio.2010.60.2.6
   Yeager L. E., 1954, Transactions 19th N. Amer. Wildlife Conf., P462
NR 123
TC 2
Z9 2
U1 2
U2 81
PU CALIFORNIA FISH AND GAME EDITOR
PI SACRAMENTO
PA 1416 NINTH ST, SACRAMENTO, CA 95814 USA
SN 0008-1078
EI 2331-0405
J9 CALIF FISH GAME
JI Calif. Fish Game
PD FAL
PY 2015
VL 101
IS 4
BP 218
EP 240
PG 23
WC Fisheries; Zoology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Fisheries; Zoology
GA DC3KB
UT WOS:000369117100003
DA 2025-01-10
ER

PT J
AU Csilléry, K
   Lalagüe, H
   Vendramin, GG
   González-Martínez, SC
   Fady, B
   Oddou-Muratorio, S
AF Csillery, Katalin
   Lalaguee, Hadrien
   Vendramin, Giovanni G.
   Gonzalez-Martinez, Santiago C.
   Fady, Bruno
   Oddou-Muratorio, Sylvie
TI Detecting short spatial scale local adaptation and epistatic selection
   in climate-related candidate genes in European beech (<i>Fagus
   sylvatica</i>) populations
SO MOLECULAR ECOLOGY
LA English
DT Article
DE abiotic stress; budburst phenology; F-ST outlier; gene network;
   haplotype; Ohta's test; variance components of linkage disequilibrium
ID QUANTITATIVE TRAIT LOCI; LINKAGE DISEQUILIBRIUM; NUCLEOTIDE DIVERSITY;
   CLINAL VARIATION; DIFFERENTIATION; HISTORY; RECONSTRUCTION;
   DETERMINANTS; PERFORMANCE; PHENOLOGY
AB Detecting signatures of selection in tree populations threatened by climate change is currently a major research priority. Here, we investigated the signature of local adaptation over a short spatial scale using 96 European beech (Fagus sylvatica L.) individuals originating from two pairs of populations on the northern and southern slopes of Mont Ventoux (south-eastern France). We performed both single and multilocus analysis of selection based on 53 climate-related candidate genes containing 546 SNPs. F-ST outlier methods at the SNP level revealed a weak signal of selection, with three marginally significant outliers in the northern populations. At the gene level, considering haplotypes as alleles, two additional marginally significant outliers were detected, one on each slope. To account for the uncertainty of haplotype inference, we averaged the Bayes factors over many possible phase reconstructions. Epistatic selection offers a realistic multilocus model of selection in natural populations. Here, we used a test suggested by Ohta based on the decomposition of the variance of linkage disequilibrium. Overall populations, 0.23% of the SNP pairs (haplotypes) showed evidence of epistatic selection, with nearly 80% of them being within genes. One of the between gene epistatic selection signals arose between an F-ST outlier and a nonsynonymous mutation in a drought response gene. Additionally, we identified haplotypes containing selectively advantageous allele combinations which were unique to high or low elevations and northern or southern populations. Several haplotypes contained nonsynonymous mutations situated in genes with known functional importance for adaptation to climatic factors.
C1 [Csillery, Katalin; Lalaguee, Hadrien; Fady, Bruno; Oddou-Muratorio, Sylvie] INRA, Ecol Forestiere Mediterraneenne UR629, F-84914 Avignon, France.
   [Lalaguee, Hadrien] Scuola Super Sant Anna, I-56127 Pisa, Italy.
   [Lalaguee, Hadrien; Vendramin, Giovanni G.] CNR, Inst Bisci & Bioresources, I-50019 Florence, Italy.
   [Gonzalez-Martinez, Santiago C.] CIFOR INIA, Forest Res Ctr, Madrid 28040, Spain.
C3 INRAE; Scuola Superiore Sant'Anna; Consiglio Nazionale delle Ricerche
   (CNR); Instituto Nacional Investigacion Tecnologia Agraria Alimentaria
   (INIA)
RP Oddou-Muratorio, S (corresponding author), INRA, Unite Rech Forestieres Mediterraneennes, Site Agroparc, F-84914 Avignon 9, France.
EM oddou@avignon.inra.fr
RI Csillery, Katalin/K-4741-2014; Giovanni G, Vendramin/K-9731-2014;
   Gonzalez-Martinez, Santiago C/H-2014-2012
OI Giovanni G, Vendramin/0000-0001-9921-7872; ODDOU-MURATORIO,
   Sylvie/0000-0003-2374-8313; Gonzalez-Martinez, Santiago
   C/0000-0002-4534-3766; Csillery, Katalin/0000-0003-0039-9296
FU EU Network of Excellence EvolTree [GOCE-016322]; ERA-Net BiodivERsA; ANR
   (France); MINECO (Spain); Italian MIUR project Biodiversitalia
   [RBAP10A2T4]; INRA-EFPA project 'Innovant'; AdapCon project
   [CGL2011-30182-C02-01]
FX We thank Pauline Garnier-Gere for her help with the cleaning and the
   analyses of candidate gene sequences, and Andrea Pluess for help and
   comments on our results and analyses. We thank Norbert Turion, Olivier
   Gilg, Frank Rei (INRA-UEFM) for fieldwork, Marianne Correard for GIS
   work, and Sara Torre and Federico Sebastiani for their help in the
   laboratory. All authors were supported by the EU Network of Excellence
   EvolTree (GOCE-016322). This research was also funded by the ERA-Net
   BiodivERsA, with the national funders ANR (France) and MINECO (Spain),
   part of the 2008 and 2012 BiodivERsA call for research proposals
   (projects LinkTree and TipTree). GGV was also supported by the Italian
   MIUR project Biodiversitalia (RBAP10A2T4). HL, SOM and BF were supported
   by INRA-EFPA project 'Innovant 2010'. SCGM was supported by AdapCon
   project (CGL2011-30182-C02-01).
CR Alberto FJ, 2013, GENETICS, V195, P495, DOI 10.1534/genetics.113.153783
   Alberto FJ, 2013, GLOBAL CHANGE BIOL, V19, P1645, DOI 10.1111/gcb.12181
   ALTSCHUL SF, 1990, J MOL BIOL, V215, P403, DOI 10.1006/jmbi.1990.9999
   [Anonymous], THESIS GEORG AUGUST
   [Anonymous], CANDIDATE GENE BASED
   Audigeos D, 2013, J EVOLUTION BIOL, V26, P529, DOI 10.1111/jeb.12069
   Beaumont MA, 1996, P ROY SOC B-BIOL SCI, V263, P1619, DOI 10.1098/rspb.1996.0237
   Black WC, 2008, ADV EXP MED BIOL, V627, P71, DOI 10.1007/978-0-387-78225-6_6
   Bresson CC, 2011, TREE PHYSIOL, V31, P1164, DOI 10.1093/treephys/tpr084
   Chen J, 2012, GENETICS, V191, P865, DOI 10.1534/genetics.112.140749
   Cheng YP, 2001, J HERED, V92, P65, DOI 10.1093/jhered/92.1.65
   De Mita S, 2013, MOL ECOL, V22, P1383, DOI 10.1111/mec.12182
   Eveno E, 2008, MOL BIOL EVOL, V25, P417, DOI 10.1093/molbev/msm272
   Excoffier L, 2009, HEREDITY, V103, P285, DOI 10.1038/hdy.2009.74
   EXCOFFIER L, 1992, GENETICS, V131, P479
   Fariello MI, 2013, GENETICS, V193, P929, DOI 10.1534/genetics.112.147231
   Fernández-López J, 2010, FOREST SYST, V19, P156, DOI 10.5424/fs/2010192-01311
   Foll M, 2008, GENETICS, V180, P977, DOI 10.1534/genetics.108.092221
   Fu WQ, 2013, ANNU REV GENOM HUM G, V14, P467, DOI 10.1146/annurev-genom-091212-153509
   Gauzere J, 2013, MOL ECOL, V22, P5001, DOI 10.1111/mec.12435
   Griffing B., 1960, Australian Journal of Biological Sciences, V13, P307
   Hansen MM, 2012, MOL ECOL, V21, P1311, DOI 10.1111/j.1365-294X.2011.05463.x
   Hansen TF, 2013, EVOLUTION, V67, P3501, DOI 10.1111/evo.12214
   Hudson RR, 2002, BIOINFORMATICS, V18, P337, DOI 10.1093/bioinformatics/18.2.337
   Jump AS, 2006, MOL ECOL, V15, P3469, DOI 10.1111/j.1365-294X.2006.03027.x
   Körner C, 2007, TRENDS ECOL EVOL, V22, P569, DOI 10.1016/j.tree.2007.09.006
   Kremer A, 2012, TREE GENET GENOMES, V8, P583, DOI 10.1007/s11295-012-0498-3
   Kujala ST, 2012, TREE GENET GENOMES, V8, P1451, DOI 10.1007/s11295-012-0532-5
   Lalagüe H, 2014, TREE GENET GENOMES, V10, P15, DOI 10.1007/s11295-013-0658-0
   Lander TA, 2011, MOL ECOL, V20, P5182, DOI 10.1111/j.1365-294X.2011.05356.x
   Le Corre V, 2003, GENETICS, V164, P1205
   Le Corre V, 2012, MOL ECOL, V21, P1548, DOI 10.1111/j.1365-294X.2012.05479.x
   Lehner B, 2011, TRENDS GENET, V27, P323, DOI 10.1016/j.tig.2011.05.007
   Li N, 2003, GENETICS, V165, P2213
   Lotterhos KE, 2014, MOL ECOL, V23, P2178, DOI 10.1111/mec.12725
   Ma XF, 2010, GENETICS, V186, P1033, DOI 10.1534/genetics.110.120873
   Mackay TFC, 2014, NAT REV GENET, V15, P22, DOI 10.1038/nrg3627
   Magri D, 2006, NEW PHYTOL, V171, P199, DOI 10.1111/j.1469-8137.2006.01740.x
   Mikola J., 1982, Silvae Fenn, V16, P178, DOI DOI 10.14214/SF.A15075
   Mosca E, 2014, NEW PHYTOL, V201, P180, DOI 10.1111/nph.12476
   Neale DB, 2011, NAT REV GENET, V12, P111, DOI 10.1038/nrg2931
   OHTA T, 1982, P NATL ACAD SCI-BIOL, V79, P1940, DOI 10.1073/pnas.79.6.1940
   Pannell JR, 2014, NEW PHYTOL, V201, P417, DOI 10.1111/nph.12495
   Pluess AR, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0033636
   Pritchard JK, 2010, CURR BIOL, V20, pR208, DOI 10.1016/j.cub.2009.11.055
   Savolainen O, 2007, CURR OPIN PLANT BIOL, V10, P162, DOI 10.1016/j.pbi.2007.01.011
   Schoville SD, 2012, ANNU REV ECOL EVOL S, V43, P23, DOI 10.1146/annurev-ecolsys-110411-160248
   Seifert S, 2012, EUR J FOREST RES, V131, P1761, DOI 10.1007/s10342-012-0630-9
   Stephens M, 2003, AM J HUM GENET, V73, P1162, DOI 10.1086/379378
   Storz JF, 2008, GENETICS, V180, P367, DOI 10.1534/genetics.108.088732
   Team RC, 2014, R: A Language and Environment for Statistical Computing
   Vilas A, 2012, J EVOLUTION BIOL, V25, P1364, DOI 10.1111/j.1420-9101.2012.02526.x
   Vitasse Y, 2009, CAN J FOREST RES, V39, P1259, DOI 10.1139/X09-054
   WEIR BS, 1984, EVOLUTION, V38, P1358, DOI [10.2307/2408641, 10.1111/j.1558-5646.1984.tb05657.x]
NR 54
TC 55
Z9 59
U1 1
U2 106
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 OCT
PY 2014
VL 23
IS 19
BP 4696
EP 4708
DI 10.1111/mec.12902
PG 13
WC Biochemistry & Molecular Biology; Ecology; Evolutionary Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Environmental Sciences & Ecology;
   Evolutionary Biology
GA AQ4DQ
UT WOS:000342743000006
PM 25156570
OA Green Published
DA 2025-01-10
ER

PT J
AU Prunier, J
   Gérardi, S
   Laroche, J
   Beaulieu, J
   Bousquet, J
AF Prunier, Julien
   Gerardi, Sebastien
   Laroche, Jerome
   Beaulieu, Jean
   Bousquet, Jean
TI Parallel and lineage-specific molecular adaptation to climate in boreal
   black spruce
SO MOLECULAR ECOLOGY
LA English
DT Article
DE adaptation; gene SNP; genetic lineages; natural selection;
   phylogeography; Picea mariana
ID SINGLE NUCLEOTIDE POLYMORPHISMS; DETECT CANDIDATE LOCI; WHITE SPRUCE;
   NORTH-AMERICAN; FREEZING TOLERANCE; MITOCHONDRIAL-DNA; GENETIC
   DIVERSITY; GLACIAL REFUGIA; GENOME SCANS; POPULATION
AB In response to selective pressure, adaptation may follow different genetic pathways throughout the natural range of a species due to historical differentiation in standing genetic variation. Using 41 populations of black spruce (Picea mariana), the objectives of this study were to identify adaptive genetic polymorphisms related to temperature and precipitation variation across the transcontinental range of the species, and to evaluate the potential influence of historical events on their geographic distribution. Population structure was first inferred using 50 control nuclear markers. Then, 47 candidate gene SNPs identified in previous genome scans were tested for relationship with climatic factors using an FST-based outlier method and regressions between allele frequencies and climatic variations. Two main intraspecific lineages related to glacial vicariance were detected at the transcontinental scale. Within-lineage analyses of allele frequencies allowed the identification of 23 candidate SNPs significantly related to precipitation and/or temperature variation, among which seven were common to both lineages, eight were specific to the eastern lineage and eight were specific to the western lineage. The implication of these candidate SNPs in adaptive processes was further supported by gene functional annotations. Multiple evidences indicated that the occurrence of lineage-specific adaptive SNPs was better explained by selection acting on historically differentiated gene pools rather than differential selection due to heterogeneity of interacting environmental factors and pleiotropic effects. Taken together, these findings suggest that standing genetic variation of potentially adaptive nature has been modified by historical events, hence affecting the outcome of recent selection and leading to different adaptive routes between intraspecific lineages.
C1 [Prunier, Julien; Gerardi, Sebastien; Beaulieu, Jean; Bousquet, Jean] Univ Laval, Canada Res Chair Forest & Environm Genom, Ctr Forest Res, Quebec City, PQ G1V 0A6, Canada.
   [Prunier, Julien; Gerardi, Sebastien; Laroche, Jerome; Bousquet, Jean] Univ Laval, Inst Syst & Integrat Biol, Quebec City, PQ G1V 0A6, Canada.
   [Beaulieu, Jean] Nat Resources Canada, Canadian Wood Fibre Ctr, Quebec City, PQ G1V 4C7, Canada.
C3 Laval University; Laval University; Natural Resources Canada
RP Bousquet, J (corresponding author), Univ Laval, Canada Res Chair Forest & Environm Genom, Ctr Forest Res, 1030 Ave Med, Quebec City, PQ G1V 0A6, Canada.
EM jean.bousquet@sbf.ulaval.ca
RI Bousquet, Jean/O-4221-2019
FU Fonds Quebecois de la recherche sur la nature et les technologies
   (F.Q.R.N.T.); National Sciences and Engineering Research Council of
   Canada (N.S.E.R.C.); Canadian Foundation for Innovation (C.F.I.); Genome
   Canada; Genome Quebec at Univ. Laval
FX This work was supported by grants from the Fonds Quebecois de la
   recherche sur la nature et les technologies (F.Q.R.N.T.), the National
   Sciences and Engineering Research Council of Canada (N.S.E.R.C.) and the
   Canadian Foundation for Innovation (C.F.I.), and the infrastructure
   support from the Arborea project funded by Genome Canada and Genome
   Quebec at Univ. Laval. We are grateful to L. Royer, S. Dagnault and D.
   Plourde (Canadian Forest Service), P. Charrette (Lakehead Univ.), G.
   Falk (Manitoba Conservation, Forestry Division), L. Corriveau
   (Weyerhaeuser Saskatchewan Ltd), N.K. Dhir (Alberta Sustainable Resource
   Development), C.C. Ying (British Columbia Ministry of Forests), D.
   Wortley (Canadian Department of Indian Affairs and Northern
   Development), M. Desponts and M. Perron (Ministere des Ressources
   Naturelles et de la Faune du Quebec), and A. Gagne (Centre d'Etude de la
   Foret, Univ. Laval) for their assistance with population sampling. We
   also thank S. Blais, F. Gagnon and S. Senneville (Canada Research Chair
   in Forest and Environmental Genomics, Univ. Laval) for laboratory
   assistance, and the team of A. Montpetit (Genome Quebec Innovation
   Centre, McGill Univ.) for handling the Sequenom genotyping assay. We
   also thank R. Petit (INRA, Bordeaux) and two anonymous reviewers for
   their helpful and constructive comments.
CR Abbott RJ, 2000, SCIENCE, V289, P1343, DOI 10.1126/science.289.5483.1343
   Akey JM, 2002, GENOME RES, V12, P1805, DOI 10.1101/gr.631202
   Anderson LL, 2006, P NATL ACAD SCI USA, V103, P12447, DOI 10.1073/pnas.0605310103
   Arendt J, 2008, TRENDS ECOL EVOL, V23, P26, DOI 10.1016/j.tree.2007.09.011
   Aubry KB, 2009, MOL ECOL, V18, P2668, DOI 10.1111/j.1365-294X.2009.04222.x
   Barrett RDH, 2011, NAT REV GENET, V12, P767, DOI 10.1038/nrg3015
   Beaulieu J, 2004, CAN J FOREST RES, V34, P531, DOI 10.1139/X03-224
   Beaulieu J, 2011, GENETICS, V188, P197, DOI 10.1534/genetics.110.125781
   Beaumont MA, 1996, P ROY SOC B-BIOL SCI, V263, P1619, DOI 10.1098/rspb.1996.0237
   Bedon F, 2007, BMC PLANT BIOL, V7, DOI 10.1186/1471-2229-7-17
   Bedon F, 2010, J EXP BOT, V61, P3847, DOI 10.1093/jxb/erq196
   Bierne N, 2011, MOL ECOL, V20, P2044, DOI 10.1111/j.1365-294X.2011.05080.x
   Bigras F.J., 2001, Conifer cold hardiness
   Blödner C, 2005, J PLANT PHYSIOL, V162, P549, DOI 10.1016/j.jplph.2004.09.005
   Bonin A, 2006, MOL BIOL EVOL, V23, P773, DOI 10.1093/molbev/msj087
   Bouillé M, 2005, AM J BOT, V92, P63, DOI 10.3732/ajb.92.1.63
   Bousquet Jean, 2007, V7, P93
   Campbell D, 2004, MOL BIOL EVOL, V21, P945, DOI 10.1093/molbev/msh101
   COCKERHAM CC, 1993, EVOLUTION, V47, P855, DOI 10.1111/j.1558-5646.1993.tb01239.x
   CONDIT R, 1995, ECOL MONOGR, V65, P419, DOI 10.2307/2963497
   Coop G, 2010, GENETICS, V185, P1411, DOI 10.1534/genetics.110.114819
   Corander J, 2008, COMPUTATION STAT, V23, P111, DOI 10.1007/s00180-007-0072-x
   Davis MB, 2001, SCIENCE, V292, P673, DOI 10.1126/science.292.5517.673
   De Carvalho D, 2010, MOL ECOL, V19, P1638, DOI 10.1111/j.1365-294X.2010.04595.x
   DeYoung BJ, 2006, PLANT J, V45, P1, DOI 10.1111/j.1365-313X.2005.02592.x
   Dong CH, 2006, P NATL ACAD SCI USA, V103, P8281, DOI 10.1073/pnas.0602874103
   Eckert AJ, 2009, GENETICS, V182, P1289, DOI 10.1534/genetics.109.102350
   El Kayal W, 2011, PLANT CELL ENVIRON, V34, P480, DOI 10.1111/j.1365-3040.2010.02257.x
   Elmer KR, 2011, TRENDS ECOL EVOL, V26, P298, DOI 10.1016/j.tree.2011.02.008
   Evanno G, 2005, MOL ECOL, V14, P2611, DOI 10.1111/j.1365-294X.2005.02553.x
   Eveno E, 2008, MOL BIOL EVOL, V25, P417, DOI 10.1093/molbev/msm272
   Excoffier L, 2009, HEREDITY, V103, P285, DOI 10.1038/hdy.2009.74
   Farrar J.L., 1995, TREES CANADA
   Ffrench-Constant RH, 2000, ANNU REV ENTOMOL, V45, P449, DOI 10.1146/annurev.ento.45.1.449
   Gamache I, 2003, MOL ECOL, V12, P891, DOI 10.1046/j.1365-294X.2003.01800.x
   Gasteiger E, 2003, NUCLEIC ACIDS RES, V31, P3784, DOI 10.1093/nar/gkg563
   Gérardi S, 2010, MOL ECOL, V19, P5265, DOI 10.1111/j.1365-294X.2010.04881.x
   Grivet D, 2011, MOL BIOL EVOL, V28, P101, DOI 10.1093/molbev/msq190
   Guillet-Claude C, 2004, MOL BIOL EVOL, V21, P2232, DOI 10.1093/molbev/msh235
   Hancock AM, 2008, PLOS GENET, V4, DOI 10.1371/journal.pgen.0040032
   Hancock AM, 2011, SCIENCE, V334, P83, DOI 10.1126/science.1209244
   Hancock AM, 2010, P NATL ACAD SCI USA, V107, P8924, DOI 10.1073/pnas.0914625107
   Hewitt GM, 1999, BIOL J LINN SOC, V68, P87, DOI 10.1111/j.1095-8312.1999.tb01160.x
   Hoekstra HE, 2003, MOL ECOL, V12, P1185, DOI 10.1046/j.1365-294X.2003.01788.x
   Holliday JA, 2010, NEW PHYTOL, V188, P501, DOI 10.1111/j.1469-8137.2010.03380.x
   Howe GT, 2003, CAN J BOT, V81, P1247, DOI [10.1139/b03-141, 10.1139/B03-141]
   Ingram J, 1996, ANNU REV PLANT PHYS, V47, P377, DOI 10.1146/annurev.arplant.47.1.377
   ISABEL N, 1995, P NATL ACAD SCI USA, V92, P6369, DOI 10.1073/pnas.92.14.6369
   Jaramillo-Correa JP, 2004, MOL ECOL, V13, P2735, DOI 10.1111/j.1365-294X.2004.02258.x
   Jaramillo-Correa JP, 2003, AM J BOT, V90, P1801, DOI 10.3732/ajb.90.12.1801
   Jaramillo-Correa JP, 2009, CAN J FOREST RES, V39, P286, DOI 10.1139/X08-181
   Joost S, 2007, MOL ECOL, V16, P3955, DOI 10.1111/j.1365-294X.2007.03442.x
   Joost S, 2008, MOL ECOL RESOUR, V8, P957, DOI 10.1111/j.1755-0998.2008.02162.x
   Jump AS, 2008, GLOBAL CHANGE BIOL, V14, P637, DOI 10.1111/j.1365-2486.2007.01521.x
   Jump AS, 2006, GLOBAL CHANGE BIOL, V12, P2163, DOI 10.1111/j.1365-2486.2006.01250.x
   Kalinowski ST, 2005, MOL ECOL NOTES, V5, P187, DOI 10.1111/j.1471-8286.2004.00845.x
   Kimchi-Sarfaty C, 2007, SCIENCE, V315, P525, DOI 10.1126/science.1135308
   Ladd AN, 2002, GENOME BIOL, V3
   Laval G, 2004, BIOINFORMATICS, V20, P2485, DOI 10.1093/bioinformatics/bth264
   LEGENDRE L., 1983, NUMERICAL ECOLOGY
   Luikart G, 2003, NAT REV GENET, V4, P981, DOI 10.1038/nrg1226
   Lynch M, 2000, GENETICS, V154, P459
   McKenney JL, 2007, PLANT ECOL, V193, P293, DOI 10.1007/s11258-007-9268-y
   Mechta-Grigoriou F, 2001, ONCOGENE, V20, P2378, DOI 10.1038/sj.onc.1204381
   Moellering ER, 2010, SCIENCE, V330, P226, DOI 10.1126/science.1191803
   Murray BG, 1998, ANN BOT-LONDON, V82, P3, DOI 10.1006/anbo.1998.0764
   Namroud MC, 2008, MOL ECOL, V17, P3599, DOI 10.1111/j.1365-294X.2008.03840.x
   Namroud MC, 2012, EVOL APPL, V5, P641, DOI 10.1111/j.1752-4571.2012.00242.x
   Namroud MC, 2010, J MOL EVOL, V70, P371, DOI 10.1007/s00239-010-9335-1
   Nielsen R, 2005, ANNU REV GENET, V39, P197, DOI 10.1146/annurev.genet.39.073003.112420
   Nosil P, 2009, MOL ECOL, V18, P375, DOI 10.1111/j.1365-294X.2008.03946.x
   Novembre J, 2009, NAT REV GENET, V10, P745, DOI 10.1038/nrg2632
   Pavy N, 2012, HEREDITY, V108, P273, DOI 10.1038/hdy.2011.72
   Pavy N, 2008, BMC GENOMICS, V9, DOI 10.1186/1471-2164-9-21
   Pelgas B, 2004, MOL BREEDING, V13, P263, DOI 10.1023/B:MOLB.0000022528.01656.c8
   Pelgas B, 2011, BMC GENOMICS, V12, DOI 10.1186/1471-2164-12-145
   Perron M, 1997, MOL ECOL, V6, P725, DOI 10.1046/j.1365-294X.1997.00243.x
   Perry DJ, 2001, CAN J FOREST RES, V31, P32, DOI 10.1139/cjfr-31-1-32
   Petit RJ, 2009, TRENDS ECOL EVOL, V24, P386, DOI 10.1016/j.tree.2009.02.011
   Petit RJ, 2005, MOL ECOL, V14, P689, DOI 10.1111/j.1365-294X.2004.02410.x
   Pritchard JK, 2000, GENETICS, V155, P945
   Prunier J, 2011, MOL ECOL, V20, P1702, DOI 10.1111/j.1365-294X.2011.05045.x
   Regniere J, 1996, ENVIRON ENTOMOL, V25, P869, DOI 10.1093/ee/25.5.869
   Renaut S, 2010, MOL ECOL, V19, P115, DOI 10.1111/j.1365-294X.2009.04477.x
   Richter-Boix A, 2011, MOL ECOL, V20, P1582, DOI 10.1111/j.1365-294X.2011.05025.x
   Rigault P, 2011, PLANT PHYSIOL, V157, P14, DOI 10.1104/pp.111.179663
   Root TL, 2003, NATURE, V421, P57, DOI 10.1038/nature01333
   Shafer ABA, 2010, MOL ECOL, V19, P4589, DOI 10.1111/j.1365-294X.2010.04828.x
   Storey JD, 2003, P NATL ACAD SCI USA, V100, P9440, DOI 10.1073/pnas.1530509100
   Storey K.B., 2004, FUNCTIONAL METABOLIS, P473, DOI DOI 10.1002/047167558X.CH17
   Storz JF, 2005, MOL ECOL, V14, P671, DOI 10.1111/j.1365-294X.2005.02437.x
   Sullivan JA, 2003, DEV BIOL, V260, P289, DOI 10.1016/S0012-1606(03)00212-4
   Sun WN, 2002, BBA-GENE STRUCT EXPR, V1577, P1, DOI 10.1016/S0167-4781(02)00417-7
   Thornton KR, 2007, HEREDITY, V98, P340, DOI 10.1038/sj.hdy.6800967
   Vasemägi A, 2005, MOL ECOL, V14, P3623, DOI 10.1111/j.1365-294X.2005.02690.x
   Viereck L.A., 1990, Silvics of North America, Vol. 1, V1, P227
   WRIGHT S, 1951, ANN EUGENIC, V15, P323
   Wright SI, 2005, MOL BIOL EVOL, V22, P506, DOI 10.1093/molbev/msi035
   Yamaguchi-Shinozaki K, 2006, ANNU REV PLANT BIOL, V57, P781, DOI 10.1146/annurev.arplant.57.032905.105444
NR 99
TC 55
Z9 61
U1 2
U2 59
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 SEP
PY 2012
VL 21
IS 17
BP 4270
EP 4286
DI 10.1111/j.1365-294X.2012.05691.x
PG 17
WC Biochemistry & Molecular Biology; Ecology; Evolutionary Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Environmental Sciences & Ecology;
   Evolutionary Biology
GA 995XB
UT WOS:000308047100012
PM 22805595
DA 2025-01-10
ER

PT J
AU Jagadish, SVK
   Craufurd, PQ
   Wheeler, TR
AF Jagadish, S. V. K.
   Craufurd, P. Q.
   Wheeler, T. R.
TI Phenotyping parents of mapping populations of rice for heat tolerance
   during anthesis
SO CROP SCIENCE
LA English
DT Article
ID ORYZA-SATIVA L.; HIGH-TEMPERATURE STRESS; ARACHIS-HYPOGAEA L.; SPIKELET
   STERILITY; POLLEN GERMINATION; SHORT EPISODES; HARVEST INDEX;
   JAPONICA-RICE; FRUIT-SET; SEED-SET
AB Seed set of rice (Oryza sativa L.) is highly sensitive to short episodes of high temperature at anthesis events that are likely to be more frequent in future climates. Breeding for tolerance is therefore an essential component of adaptation to climate variability and change. Experiments were conducted in 2003 and 2004 at optimum (30 degrees C daytime) and high (35 and 38 degrees C) air temperature using parents of some prominent mapping populations (i) to determine whether there were differences in the daily flowering pattern and hence a potential heat avoidance mechanism, and (ii) to identify rice genotypes having true heat tolerance during anthesis, that is, high seed set in spikelets exposed to high temperature. Rice cultivar CG14 (O. glaberrima) reached peak anthesis earlier in the morning (1.5 h after dawn) under both control (30 degrees C) and high (38 degrees C) temperature conditions than O. sativa genotypes (>= 3 h after dawn). Exposure to high temperature (centered on the time of peak anthesis) for 6 h reduced spikelet fertility more than exposure for 2 h, and fertility was lower at 38 degrees C than at 35 degrees C. Genotypic ranking for spikelet fertility at 35 and 38 degrees C was highly correlated in both 2003 and 2004. Fertility was also highly correlated across years, suggesting a consistent and reproducible response of spikelet fertility to temperature. The check cultivar N22 was the most heat tolerant genotype (64-86% fertility at 38 degrees C) and cultivars Azucena and Moroberekan the most susceptible (<8%).
C1 [Jagadish, S. V. K.; Craufurd, P. Q.; Wheeler, T. R.] Univ Reading, Plant Environm Lab, Reading RG2 9AF, Berks, England.
C3 University of Reading
RP Craufurd, PQ (corresponding author), Univ Reading, Plant Environm Lab, Cutbush Lane, Reading RG2 9AF, Berks, England.
EM p.q.craufurd@rdg.ac.uk
CR [Anonymous], RICE SCI INNOVATIONS
   [Anonymous], CLIM CHANG 2007 SYNT
   [Anonymous], IRRI RES PAPER SER
   Carriger S., 2007, Rice Today, V6, P10
   CHO, 1956, B NATL I AGR SCI, V6, P61
   EKANAYAKE IJ, 1989, ANN BOT-LONDON, V63, P257, DOI 10.1093/oxfordjournals.aob.a087740
   Hall A.E., 1993, PLANT BREED RES, V10, P129
   Jagadish SVK, 2007, J EXP BOT, V58, P1627, DOI 10.1093/jxb/erm003
   Kakani VG, 2002, PLANT CELL ENVIRON, V25, P1651, DOI 10.1046/j.1365-3040.2002.00943.x
   Khush GS, 2005, PLANT MOL BIOL, V59, P1, DOI 10.1007/s11103-005-2159-5
   Matsui T, 1999, ANN BOT-LONDON, V84, P501, DOI 10.1006/anbo.1999.0943
   Matsui T, 2002, ANN BOT-LONDON, V89, P683, DOI 10.1093/aob/mcf112
   Matsui T, 1997, JPN J CROP SCI, V66, P449, DOI 10.1626/jcs.66.449
   Matsui T, 2001, PLANT PROD SCI, V4, P90, DOI 10.1626/pps.4.90
   Matsui T, 1997, FIELD CROP RES, V51, P213, DOI 10.1016/S0378-4290(96)03451-X
   Matsui Tsutomu, 1999, Plant Production Science, V2, P196
   Prasad PVV, 2006, AGR FOREST METEOROL, V139, P237, DOI 10.1016/j.agrformet.2006.07.003
   Prasad PVV, 2006, FIELD CROP RES, V95, P398, DOI 10.1016/j.fcr.2005.04.008
   Prasad PVV, 1999, ANN BOT-LONDON, V84, P381, DOI 10.1006/anbo.1999.0926
   Prasad PVV, 2000, J EXP BOT, V51, P777, DOI 10.1093/jexbot/51.345.777
   Prasad PVV, 2001, AUST J PLANT PHYSIOL, V28, P233, DOI 10.1071/PP00127
   SATAKE T, 1978, JPN J CROP SCI, V47, P6, DOI 10.1626/jcs.47.6
   Wassmann R, 2007, RICE TODAY, P10
   Wheeler TR, 1996, J AGR SCI, V127, P37, DOI 10.1017/S0021859600077352
   Yoshida S., 1976, Laboratory Manual for Plant Physiological Studies of Rice, Ed, V3
   Ziska LH, 1996, AUST J PLANT PHYSIOL, V23, P791, DOI 10.1071/PP9960791
NR 26
TC 176
Z9 198
U1 1
U2 43
PU CROP SCIENCE SOC AMER
PI MADISON
PA 677 S SEGOE ROAD, MADISON, WI 53711 USA
SN 0011-183X
J9 CROP SCI
JI Crop Sci.
PD MAY-JUN
PY 2008
VL 48
IS 3
BP 1140
EP 1146
DI 10.2135/cropsci2007.10.0559
PG 7
WC Agronomy
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA 311YD
UT WOS:000256635400033
DA 2025-01-10
ER

PT J
AU Chen, YL
   Xie, ZYT
   Lan, GT
   Liu, YJ
   He, JR
   Li, Z
   Wu, C
   Xing, LD
   Li, WS
AF Chen, Yili
   Xie, Zhangyating
   Lan, Guangting
   Liu, Yanjin
   He, Jiarong
   Li, Zhao
   Wu, Can
   Xing, Lidan
   Li, Weishan
TI Molecular-level designed single electrolyte additive with
   multifunctional groups enabling high mechanical properties/fast Li plus
   kinetics interphase for wide-temperature nickel-rich/graphite batteries
SO CHEMICAL ENGINEERING JOURNAL
LA English
DT Article
DE Sophisticated functional additive; Boron-fluorophenyl-siloxy;
   Electrode/electrolyte interphase; All-climate performance
ID ION BATTERIES; CATHODE
AB High-voltage nickel-rich/graphite full-cells offer significant potential for enhancing the energy density of lithium-ion batteries (LIBs), yet rapid capacity degradation at extreme temperatures remains a critical challenge. We introduce a novel electrolyte additive, 5-(t-butyldimethylsilyloxy)-2-fluorophenylboronic acid pinacol ester (SOFPB), which incorporates multifunctional boron, phenyl-, fluorine, and siloxy groups to tackle this issue. In Li/NCM622 half-cells, 0.3 wt% SOFPB achieves a capacity retention 2.6 times that of the Baseline after 400 cycles at-30 degrees C, and maintains 78.4% and 77.5% capacity after 300 cycles at 25 degrees C and 55 degrees C, respectively, compared to 63.4% and 3.8% for the Baseline. This improvement is attributed to a robust cathode electrolyte interphase (CEI) with high lithium-ion conductivity and oxidative stability. Li/graphite half-cells with SOFPB show rapid capacity recovery at 0 degrees C and retain 99.6% and 72.4% capacity after 500 and 150 cycles at 25 degrees C and 55 degrees C, respectively, compared to 60.3% for the Baseline at 25 degrees C. This performance is due to a flexible solid electrolyte interphase (SEI) that improves lithium-ion diffusion. Furthermore, NCM622/graphite full-cells highlight the practical value of SOFPB, with retention of 91.6%/77.7%/97.7% after 200/150/50 cycles at 25 degrees C/-10 degrees C/55 degrees C, respectively, compared to 52.9%/25.2%/43.9% for the Baseline. The multifunctional design of SOFPB provides valuable insights for developing advanced electrolyte additives for high-voltage LIBs with broad climate adaptability.
C1 [Chen, Yili; Xie, Zhangyating; Lan, Guangting; Liu, Yanjin; He, Jiarong; Xing, Lidan; Li, Weishan] South China Normal Univ, Sch Chem, Guangzhou 510006, Peoples R China.
   [Chen, Yili; Xie, Zhangyating; Liu, Yanjin; He, Jiarong; Xing, Lidan; Li, Weishan] South China Normal Univ, Natl & Local Joint Engn Res Ctr MPTES High Energy, Engn Res Ctr MTEES, Res Ctr BMET Guangdong Prov, Guangzhou 510006, Peoples R China.
   [Chen, Yili; Xie, Zhangyating; Liu, Yanjin; He, Jiarong; Xing, Lidan; Li, Weishan] South China Normal Univ, Key Lab ETESPG GHEI, Guangzhou 510006, Peoples R China.
   [Li, Zhao; Wu, Can] GuangDong JinGuang High Tech Co Ltd, Shantou 515071, Peoples R China.
C3 South China Normal University; South China Normal University; South
   China Normal University
RP He, JR; Xing, LD (corresponding author), South China Normal Univ, Sch Chem, Guangzhou 510006, Peoples R China.
EM jiarong.he@m.scnu.edu.cn; xingld@scnu.edu.cn
RI He, Jiarong/AGZ-5972-2022; chen, yili/JAZ-1293-2023
FU National Natural Science Foundation of China [22379046]; Guangzhou
   Science and Technology Plan Project [2024A04J4354]; Guangdong Basic and
   Applied Basic Research Foundation [2024A1515010034]
FX This work is supported by the National Natural Science Foundation of
   China (Grant No. 22379046) , Guangzhou Science and Technology Plan
   Project (Grant No. 2024A04J4354) and Guangdong Basic and Applied Basic
   Research Foundation (Grant No. 2024A1515010034) .
CR Abazari R, 2024, SMALL, V20, DOI 10.1002/smll.202306353
   Cao Z, 2022, NANO ENERGY, V93, DOI 10.1016/j.nanoen.2021.106811
   Che YX, 2023, J POWER SOURCES, V559, DOI 10.1016/j.jpowsour.2023.232678
   Chen C, 2022, ADV FUNCT MATER, V32, DOI 10.1002/adfm.202107249
   Chen MS, 2023, CARBON ENERGY, V5, DOI 10.1002/cey2.459
   Chen S, 2024, CHEM ENG J, V479, DOI 10.1016/j.cej.2023.147813
   Chen YL, 2024, ENERGY STORAGE MATER, V71, DOI 10.1016/j.ensm.2024.103642
   ChineseSociety of Electrochemistry, 2024, J ELECTROCHEM, V30, P2024121, DOI [10.61558/2993-074X.3444, DOI 10.61558/2993-074X.3444]
   Fan XM, 2020, NANO ENERGY, V70, DOI 10.1016/j.nanoen.2020.104450
   Ge JM, 2023, ADV FUNCT MATER, V33, DOI 10.1002/adfm.202305803
   Hu LB, 2013, ELECTROCHEM COMMUN, V35, P76, DOI 10.1016/j.elecom.2013.08.009
   Jiang H, 2021, J PHYS CHEM LETT, V12, P10521, DOI 10.1021/acs.jpclett.1c02969
   Lan XW, 2023, ADV ENERGY MATER, V13, DOI 10.1002/aenm.202203449
   Li GJ, 2020, ACS APPL MATER INTER, V12, P37013, DOI 10.1021/acsami.0c05623
   Li JL, 2022, CHEM REV, V122, P903, DOI 10.1021/acs.chemrev.1c00565
   Li JY, 2018, ADV ENERGY MATER, V8, DOI 10.1002/aenm.201801957
   Li YQ, 2024, ADV FUNCT MATER, V34, DOI 10.1002/adfm.202312921
   Lin JL, 2022, ACS APPL ENERG MATER, V5, P11684, DOI 10.1021/acsaem.2c02160
   Liu QQ, 2023, ADV ENERGY MATER, V13, DOI 10.1002/aenm.202301742
   Ma XW, 2019, J ELECTROCHEM SOC, V166, pA711, DOI 10.1149/2.0801904jes
   Migas DB, 2023, J MATER CHEM C, V11, P12406, DOI 10.1039/d3tc01533e
   Park GT, 2023, ACS ENERGY LETT, V8, P3784, DOI 10.1021/acsenergylett.3c01322
   Shpylka DO, 2022, CERAM INT, V48, P19789, DOI 10.1016/j.ceramint.2022.03.253
   Song K, 2014, J PHYS CHEM LETT, V5, P1368, DOI 10.1021/jz5002924
   Stallard JC, 2022, JOULE, V6, P984, DOI 10.1016/j.joule.2022.04.001
   Sun CC, 2022, ADV MATER, V34, DOI 10.1002/adma.202206020
   Tan YH, 2021, ADV MATER, V33, DOI 10.1002/adma.202102134
   Tian YF, 2023, NAT COMMUN, V14, DOI 10.1038/s41467-023-43093-6
   Tishkevich DI, 2019, J ALLOY COMPD, V804, P139, DOI 10.1016/j.jallcom.2019.07.001
   Trukhanov AV, 2024, J ALLOY COMPD, V986, DOI 10.1016/j.jallcom.2024.174048
   Trukhanov SV, 2008, TECH PHYS+, V53, P49, DOI [10.1134/S106378420801009X, 10.1007/s11454-008-1009-2]
   Trukhanov SV, 2018, J MAGN MAGN MATER, V457, P83, DOI 10.1016/j.jmmm.2018.02.078
   Trukhanov SV, 2010, J EXP THEOR PHYS+, V111, P209, DOI 10.1134/S106377611008008X
   Vinnik DA, 2021, ACS APPL ELECTRON MA, V3, P1583, DOI 10.1021/acsaelm.0c01081
   Waheed MS, 2023, J PHYS CHEM SOLIDS, V175, DOI 10.1016/j.jpcs.2022.111173
   Wang HL, 2021, ADV ENERGY MATER, V11, DOI 10.1002/aenm.202101057
   Wang J.-Y., 2022, J. Electrochem., V28, P2108431, DOI [10.13208/j.electrochem.210843, DOI 10.13208/J.ELECTROCHEM.210843]
   Wang QY, 2023, CHINESE J CATAL, V54, P229, DOI 10.1016/S1872-2067(23)64532-2
   Wu DX, 2024, ANGEW CHEM INT EDIT, V63, DOI 10.1002/anie.202315608
   Wu Y, 2024, CHEM ENG J, V483, DOI 10.1016/j.cej.2024.149243
   Xiang WJ, 2022, J PHYS CHEM LETT, V13, P5151, DOI 10.1021/acs.jpclett.2c01183
   Xie ZYT, 2023, J ENERGY CHEM, V86, P197, DOI 10.1016/j.jechem.2023.07.010
   Xu K, 2002, J ELECTROCHEM SOC, V149, pA1079, DOI 10.1149/1.1490356
   Xu R, 2017, J ELECTROCHEM SOC, V164, pA3333, DOI 10.1149/2.1751713jes
   Yang C, 2024, ADV MATER, V36, DOI 10.1002/adma.202307220
   Yang YL, 2023, ANGEW CHEM INT EDIT, V62, DOI 10.1002/anie.202300057
   Zeng HP, 2024, ACS NANO, V18, P1969, DOI 10.1021/acsnano.3c07038
   Zhang XH, 2020, ADV ENERGY MATER, V10, DOI 10.1002/aenm.202000368
   Zhang Y., 2022, J. Electrochem., V28, DOI [10.13208/j.electrochem.210518, DOI 10.13208/J.ELECTROCHEM.210518]
   Zhivulin VE, 2023, ISCIENCE, V26, DOI 10.1016/j.isci.2023.107077
   Zhou TH, 2021, ACS ENERGY LETT, V6, P1711, DOI 10.1021/acsenergylett.1c00274
   Zhou YN, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms6381
   Zu CX, 2021, INFOMAT, V3, P648, DOI 10.1002/inf2.12190
   Zubar TI, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-71416-w
NR 54
TC 0
Z9 0
U1 7
U2 7
PU ELSEVIER SCIENCE SA
PI LAUSANNE
PA PO BOX 564, 1001 LAUSANNE, SWITZERLAND
SN 1385-8947
EI 1873-3212
J9 CHEM ENG J
JI Chem. Eng. J.
PD NOV 15
PY 2024
VL 500
AR 157218
DI 10.1016/j.cej.2024.157218
EA NOV 2024
PG 13
WC Engineering, Environmental; Engineering, Chemical
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering
GA L4L1N
UT WOS:001350440400001
DA 2025-01-10
ER

PT J
AU Iyer, R
   Kohlitz, J
AF Iyer, Ruhil
   Kohlitz, Jeremy
TI Climate impacts on rural sanitation: evidence from Burkina Faso,
   Bangladesh and Lao PDR
SO FRONTIERS IN WATER
LA English
DT Article
DE climate hazards; climate adaptation; sanitation & hygiene (WaSH);
   participation; rural sanitation; participatory research; sanitation
ID WATER; RESILIENCE; MANAGEMENT; SYSTEMS
AB Climate change is a real, emerging issue in the rural sanitation sector. In an already stressed context, they threaten sustained sanitation progress and outcomes. Yet, evidence gaps continue to exist on how climate impacts affect rural sanitation and hygiene practices and the narratives of people and households at the forefront, experiencing climate impacts on sanitation in rural areas are largely absent. The sector also needs more thinking on how programming can adapt to consider climate hazards. This paper builds evidence on climate impacts on rural sanitation practices through case studies in Burkina Faso, Bangladesh and Lao PDR. Studies were undertaken through various participatory methodologies to understand and respond to lived experience, differentially experienced impacts and tacit knowledge of climate impacts on rural sanitation. Climate hazards affect sanitation via numerous, dynamic interlinking pathways. The social context and local anthropogenic activities shape how these hazards impact physical access to sanitation infrastructure, access to local resources and markets, and livelihoods needed to support safe sanitation. These impacts include behaviours and practices, infrastructure, and people's capacity to invest in sanitation. Strong implications have emerged for how sanitation practice, research and policy must evolve to account for climate hazards to ensure sustained sanitation outcomes, systemic resilience and programme delivery. The rural sanitation sector must recognize the various interlinkages and distinct experiences of climate across people's daily lives as they have cascading impacts on sanitation practice. Climate considerations must be integrated at every stage of sanitation project delivery, and more holistic pathways must be explored, to ensure root causes of systemic issues such as poverty and vulnerability are considered for sustained and transformative outcomes.
C1 [Iyer, Ruhil] Inst Dev Studies, Brighton, England.
   [Iyer, Ruhil] Univ Sussex, Brighton, England.
   [Kohlitz, Jeremy] Univ Technol Sydney, Inst Sustainable Futures, Sydney, NSW, Australia.
C3 University of Sussex; University of Technology Sydney
RP Iyer, R (corresponding author), Inst Dev Studies, Brighton, England.; Iyer, R (corresponding author), Univ Sussex, Brighton, England.
EM r.iyer1@ids.ac.uk
OI Iyer, Ruhil/0000-0002-6223-9637
FU Sida grant is titled Accelerating The Momentum [2030, 12616]; UNICEF;
   WaterAid Bangladesh
FX The author(s) declare that financial support was received for the
   research, authorship, and/or publication of this article. Time for the
   research team and select research activities activities in Bangladesh
   and Burkina Faso were funded by Sida. The Sida grant is titled
   Accelerating The Momentum Towards Safely Managed Sanitation By 2030:
   Timely, Relevant And Actionable Learning. The grant number is Sida
   contribution No. 12616. funded research activities in Bangladesh. Staff
   time in Burkina Faso was funded by UNICEF. WaterAid Bangladesh also
   co-funded research activity costs.
CR Abrams AL, 2021, WATER-SUI, V13, DOI 10.3390/w13202810
   Al Rasheed A., 2013, Participatory WASH vulnerability assessment tool
   [Anonymous], 2019, Considering climate change in urban sanitation: conceptual approaches and practical implications
   Barua P., 2023, Disaster Risk Reduc. Resilience Climate Change Disaster Risk Adaptation, V18, P417, DOI [10.1007/978-3-031-22112-518, DOI 10.1007/978-3-031-22112-518]
   Berendes DM, 2017, ENVIRON SCI TECHNOL, V51, P3074, DOI 10.1021/acs.est.6b06019
   Birkmann J., 2022, CLIMATE CHANGE 2022
   Pedro JPB, 2020, J WATER SANIT HYG DE, V10, P397, DOI 10.2166/washdev.2020.019
   Braun V, 2012, APA HDB RES METHODS, V2, P57
   Brooks N., 2022, Report
   Chambers KG, 2022, ENVIRON SCI TECH LET, V9, P583, DOI 10.1021/acs.estlett.2c00267
   CHAMBERS R, 1994, WORLD DEV, V22, P1253, DOI 10.1016/0305-750X(94)90003-5
   Chambers R., 2008, Handbook on community-led total sanitation Institute of Development Studies (UK)/
   Ciss G., 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
   Cornish F., 2014, The SAGE handbook of qualitative data analysis, P79, DOI [10.4135/9781446282243, DOI 10.4135/9781446282243, 10.4135/9781446282243.n6]
   Dickin Sarah, 2023, Water Security, V20, DOI 10.1016/j.wasec.2023.100143
   Dickin S, 2020, NPJ CLEAN WATER, V3, DOI 10.1038/s41545-020-0072-8
   Dongre A R, 2007, World Health Popul, V9, P48
   GermanWatch, 2021, GLOBAL CLIMATE RISK
   Gordon Tallulah, 2021, Waterlines, V40, P107, DOI 10.3362/1756-3488.20-00012
   GWP and UNICEF, 2017, WASH Climate Resilient Development: Monitoring and Evaluation for Climate Relevant WASHs. Technical Brief
   Hazra S., 2002, Sci. C, V68, P309
   Heath TT, 2012, ENVIRON URBAN, V24, P619, DOI 10.1177/0956247812453540
   House S., 2017, Water supply and sanitation collaborative council (WSSCC)
   Howard G, 2021, NPJ CLEAN WATER, V4, DOI 10.1038/s41545-021-00130-5
   Howard G, 2021, AQUA-UK, V70, P438, DOI 10.2166/aqua.2021.127
   Howard G, 2010, J WATER CLIM CHANGE, V1, P2, DOI 10.2166/wcc.2010.205
   Hughes J, 2021, CLIM RISK MANAG, V31, DOI 10.1016/j.crm.2020.100262
   Hyde-Smith L, 2022, ENVIRON SCI TECHNOL, V56, P5306, DOI 10.1021/acs.est.1c07424
   Jerin T, 2023, INT J DISAST RISK RE, V95, DOI 10.1016/j.ijdrr.2023.103851
   Jones N, 2020, J WATER HEALTH, V18, P145, DOI 10.2166/wh.2020.088
   Kohlitz J., 2020, Climate change response for inclusive WASH: A guidance note for plan international Indonesia
   Kohlitz J., 2021, Brighton IDS, V2021, pe002, DOI [10.19088/SLH.2021.002, DOI 10.19088/SLH.2021.002]
   Kouassi HAA, 2023, PLOS ONE, V18, DOI 10.1371/journal.pone.0293395
   Kozole T, 2023, J WATER SANIT HYG DE, V13, P931, DOI 10.2166/washdev.2023.039
   Lebu S, 2024, J ENVIRON MANAGE, V354, DOI 10.1016/j.jenvman.2024.120264
   Levy K, 2016, ENVIRON SCI TECHNOL, V50, P4905, DOI 10.1021/acs.est.5b06186
   Logie C. H., 2023, Journal of Global Health Reports, V7, DOI [10.29392/001c.77885, DOI 10.29392/001C.77885]
   Luh J, 2017, SCI TOTAL ENVIRON, V592, P334, DOI 10.1016/j.scitotenv.2017.03.084
   MacArthur J, 2023, FRONT WATER, V5, DOI 10.3389/frwa.2023.1090002
   Mara D, 2018, J WATER SANIT HYG DE, V8, P1, DOI 10.2166/washdev.2017.048
   McGill BM, 2019, HYDROGEOL J, V27, P997, DOI 10.1007/s10040-018-1901-4
   Merriam S. B., 2019, Qualitative research in practice: Examples for discussion and analysis
   Ministry of Environment Forest and Climate Change Government of the People's Republic of Bangladesh, 2022, NATL ADAPTATION PLAN
   Mosler HJ, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0197483
   Nijhawan A, 2022, WATER-SUI, V14, DOI 10.3390/w14081293
   Norstrom AV, 2020, NAT SUSTAIN, V3, P182, DOI 10.1038/s41893-019-0448-2
   Nuzhat S., 2023, SLH learning brief 16
   Oates N., 2014, ODI: think change
   Odagiri M, 2017, INT J ENV RES PUB HE, V14, DOI 10.3390/ijerph14121572
   Peirson AE, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13158598
   Pisor AC, 2022, NAT CLIM CHANGE, V12, P213, DOI 10.1038/s41558-022-01303-x
   Righetto L, 2013, ADV WATER RESOUR, V60, P34, DOI 10.1016/j.advwatres.2013.07.006
   Robinson A., 2016, SUSTAINABLE SANITATI, P1
   Schmitt ML, 2017, CONFL HEALTH, V11, DOI 10.1186/s13031-017-0121-1
   Scorgie F, 2016, MED ANTHROPOL, V35, P161, DOI 10.1080/01459740.2015.1094067
   Sherpa AM, 2014, J WATER CLIM CHANGE, V5, P487, DOI 10.2166/wcc.2014.003
   Sorcher R, 2023, J WATER SANIT HYG DE, V13, P464, DOI 10.2166/washdev.2023.042
   Sultana F, 2022, GEOGR J, V188, P118, DOI 10.1111/geoj.12417
   Taylor C., 2021, Climate change and it's impacts in Burkina Faso. Policy brief, P12
   Teebken J, 2024, GLOBAL ENVIRON CHANG, V85, DOI 10.1016/j.gloenvcha.2024.102807
   The World Bank Group and the Asian Development, 2021, Climate Risk country profile: Ghana
   Thuita W, 2017, DEV PRACT, V27, P16, DOI 10.1080/09614524.2017.1256951
   Tshuma M, 2024, INT J ENVIRON HEAL R, V34, P466, DOI 10.1080/09603123.2022.2153809
   UTS-ISF and SNV, 2022, Report
   Vincent K, 2020, NAT CLIM CHANGE, V10, P877, DOI 10.1038/s41558-020-00910-w
   WHO and UNICEF, 2023, Progress on household drinking water, sanitation Online
   WHO and UNICEF, 2020, Progress on household drinking water, sanitation and hygiene 2000-2020
   Willetts J, 2022, ENVIRON PLAN B-URBAN, V49, P2129, DOI 10.1177/23998083221098740
   World Bank Climate Change Knowledge Portal, 2024, ABOUT US
   Yin R. K., 2009, CASE STUDY RES DESIG
NR 70
TC 0
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U2 2
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2624-9375
J9 FRONT WATER
JI Front. Water
PD SEP 11
PY 2024
VL 6
AR 1413225
DI 10.3389/frwa.2024.1413225
PG 12
WC Water Resources
WE Emerging Sources Citation Index (ESCI)
SC Water Resources
GA G9Q9V
UT WOS:001319911100001
OA gold
DA 2025-01-10
ER

PT J
AU Spaulding, NE
   Fernandez, IJ
   Gassett, PR
AF Spaulding, Nicole E.
   Fernandez, Ivan J.
   Gassett, Parker R.
TI University contributions to sustainability via state-level climate
   action plans in the USA
SO INTERNATIONAL JOURNAL OF SUSTAINABILITY IN HIGHER EDUCATION
LA English
DT Article; Early Access
DE Climate action planning; Coproduction; Global warming; Higher education;
   Knowledge networks; Science-policy interface
ID SCIENCE
AB PurposeThe purpose of this study was to conduct a preliminary analysis of the role of higher education institutions (HEIs) in state climate science assessment (CSA) and state climate adaptation plan (CAP) development in the USA.Design/methodology/approachThis study uses a content review of US state government and land grant (LG) university websites, including 36 CSAs and CAPs. These data informed the development of a tiered conceptual model of HEI engagement in state climate action planning. The conceptual model is evaluated through the lens of coproduction within knowledge networks.FindingsHEI contributions to state-level climate action planning in the USA are highly variable, ranging from minimal engagement to defined roles in the development and implementation of robust state CAPs. Novel approaches to optimize effective exchange between scientists and decision-makers that also increase the engagement of academia are needed.Practical implicationsThis study advocates for and provides a replicable example of HEI engagement in the development of mechanisms that increase the connectivity of in-state climate networks. Such mechanisms optimize information sharing and engagement, consequently building sustained capacity for in-state collaboration at the science-policy interface.Originality/valueHEIs, particularly LG universities, are a stable source of state-specific climate science and expert assistance that persist beyond national and state political cycles. To the best of the authors' knowledge, this research is the first to examine their unique contributions to climate science policy development and implementation. It investigates specifically the relationships and interactions between HEIs and state governments in the USA and offers a detailed case study from the state of Maine.
C1 [Spaulding, Nicole E.; Fernandez, Ivan J.; Gassett, Parker R.] Univ Maine, Maine Climate Sci Informat Exchange, Orono, ME 04469 USA.
C3 University of Maine System; University of Maine Orono
RP Spaulding, NE (corresponding author), Univ Maine, Maine Climate Sci Informat Exchange, Orono, ME 04469 USA.
EM nicole.spaulding@maine.edu; ivanjf@maine.edu; parker.gassett@maine.edu
FU University of Maine's Office of Innovation and Economic Development;
   U.S. Department of Commerce Project [5409529]
FX The authors appreciate the input from many individuals who were
   contacted in the development of this document and constructive input on
   earlier drafts of this document from Nathan Robbins of the Maine
   Department of Environmental Protection. This work was possible with
   support from the University of Maine's Office of Innovation and Economic
   Development and the U.S. Department of Commerce Project No. 5409529. The
   views expressed in this document are solely attributable to the authors
   and do not imply endorsement by any other entity.
CR [Anonymous], 2009, International Journal of Sustainability in Higher Education, DOI DOI 10.1108/14676370910972558
   Beier P, 2017, CONSERV LETT, V10, P288, DOI 10.1111/conl.12300
   Cash DW, 2006, SCI TECHNOL HUM VAL, V31, P465, DOI 10.1177/0162243906287547
   Cash DW, 2003, P NATL ACAD SCI USA, V100, P8086, DOI 10.1073/pnas.1231332100
   Dilling L, 2011, GLOBAL ENVIRON CHANG, V21, P680, DOI 10.1016/j.gloenvcha.2010.11.006
   Galford GL, 2016, CLIMATIC CHANGE, V138, P383, DOI 10.1007/s10584-016-1756-4
   Government of British Columbia, 2020, Clean BC climate preparedness and adaptation strategy: actions for 2022-2025
   Hetherington ED, 2020, FRONT MAR SCI, V7, DOI 10.3389/fmars.2020.00409
   Holmes KJ, 2020, EARTHS FUTURE, V8, DOI 10.1029/2019EF001402
   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]
   Kirchhoff CJ, 2019, B AM METEOROL SOC, V100, P2147, DOI 10.1175/BAMS-D-18-0138.1
   Kopp R.E., 2021, Eos, V102, DOI [10.1029/2021EO158178, DOI 10.1029/2021EO158178]
   Miao Q, 2019, ENVIRON POLICY GOV, V29, P376, DOI 10.1002/eet.1866
   Misra V, 2021, B AM METEOROL SOC, V102, pE367, DOI 10.1175/BAMS-D-19-0302.1
   Province of New Brunswick, 2016, Transitioning to a low-carbon economy New Brunswick's Climate Change Action Plan
   State of Montana, 2020, Montana Climate Solutions Plan
   State of Nevada, 2020, Nevada's 2020 Climate Strategy
   United States Department of State and the United States Executive Office of the President, 2021, LONG TERM STRAT US P
   Widhalm M, 2020, CLIMATIC CHANGE, V163, P1869, DOI 10.1007/s10584-020-02928-7
   Yocum HM, 2022, CONSERV SCI PRACT, V4, DOI 10.1111/csp2.608
NR 20
TC 0
Z9 0
U1 2
U2 2
PU EMERALD GROUP PUBLISHING LTD
PI Leeds
PA Floor 5, Northspring 21-23 Wellington Street, Leeds, W YORKSHIRE,
   ENGLAND
SN 1467-6370
EI 1758-6739
J9 INT J SUST HIGHER ED
JI Int. J. Sustain. High. Educ.
PD 2023 DEC 25
PY 2023
DI 10.1108/IJSHE-01-2023-0020
EA DEC 2023
PG 17
WC Green & Sustainable Science & Technology; Education & Educational
   Research
WE Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Education & Educational Research
GA CW1K4
UT WOS:001128178500001
DA 2025-01-10
ER

PT J
AU van de Logt, R
   van der Sluijs, T
   van Eekeren, N
AF van de Logt, Roos
   van der Sluijs, Thom
   van Eekeren, Nick
TI <i>Lumbricus</i><i> terrestris</i> abundance in grasslands on sandy
   soils in relation to soil texture, hydrology and earthworm community
SO EUROPEAN JOURNAL OF SOIL BIOLOGY
LA English
DT Article
DE Lumbricidae; Deep-burrowing earthworms; Ecosystem functioning;
   Grassland; Ecosystem engineers; Water regulation
ID ORGANIC-MATTER; APORRECTODEA-CALIGINOSA; COMPACTION; MANAGEMENT;
   ECOSYSTEM; BURROWS; GROWTH; L.; INOCULATION; POPULATIONS
AB Deep-burrowing (anecic) earthworm Lumbricus terrestris contributes to the crucial ecosystem service of water regulation. Their deep, vertical burrows facilitate water flow and deeper rooting, the former supporting the prevention of flooding and waterlogging, the latter improving drought tolerance. In Europe, these earthworms occur in agricultural grasslands on various soil types. However, their distribution pattern can be very heterogeneous. There is no conclusive set of soil biotic or abiotic factors that determines whether L. terrestris occurs or not. Through a better understanding of the L. terrestris distribution patterns we hope to gain more insight into their potential for climate adaptive water regulation.We executed a field inventory (n = 62) to assess the relationship between L. terrestris population density in grassland on sandy soils and soil silt content (loaminess), gley depth, epigeic earthworm population density and grassland age.We found positive correlations between soil silt concentrations and L. terrestris population densities. Gley depth slightly correlated with population density when presented in a model with silt concentration as a predictor. Presence and population density of L. terrestris correlated negatively with L. rubellus abundance. The number of years without mechanical soil disturbance and L. terrestris population density were not significantly related. Unexpectedly, we found L. terrestris in some very sandy soils. Our data was fitted into an existing predictive model based on land use and texture (by Lindahl et al., 2009), yielding 63% accuracy. Overall, this correlative study provides further insights into L. terrestris habitat selection, which helps us understand the species' potential for water regulation in the widespread grassland agro-ecosystems.
C1 [van de Logt, Roos; van der Sluijs, Thom; van Eekeren, Nick] Louis Bolk Inst, Kosterijland 3-5, NL-3981 AJ Bunnik, Netherlands.
RP van de Logt, R (corresponding author), Louis Bolk Inst, Kosterijland 3-5, NL-3981 AJ Bunnik, Netherlands.
EM r.vandelogt@louisbolk.nl
CR Andersen C., 1980, Soil biology as related to land use practices., P325
   Andriuzzi WS, 2015, PLANT SOIL, V397, P103, DOI 10.1007/s11104-015-2604-4
   [Anonymous], 2014, Zeszyty Naukowe
   [Anonymous], Grondwatertrappen Nederland'
   BALL DF, 1964, J SOIL SCI, V15, P84, DOI 10.1111/j.1365-2389.1964.tb00247.x
   Bastardie F, 2003, APPL SOIL ECOL, V24, P3, DOI 10.1016/S0929-1393(03)00071-4
   Beier C, 2012, ECOL LETT, V15, P899, DOI 10.1111/j.1461-0248.2012.01793.x
   Beylich A, 2010, SOIL TILL RES, V109, P133, DOI 10.1016/j.still.2010.05.010
   Blouin M, 2013, EUR J SOIL SCI, V64, P161, DOI 10.1111/ejss.12025
   Bodemtypes Nederland, Pdok
   Bouche M. B., 1977, Ecological Bulletins (Stockholm), P122
   Brown George G., 2004, P13
   Brown GG, 2000, EUR J SOIL BIOL, V36, P177, DOI 10.1016/S1164-5563(00)01062-1
   Butt KR, 1998, APPL SOIL ECOL, V9, P75, DOI 10.1016/S0929-1393(98)00057-2
   Capowiez Y, 2015, BIOL FERT SOILS, V51, P869, DOI 10.1007/s00374-015-1036-x
   Capowiez Y, 2009, SOIL TILL RES, V105, P209, DOI 10.1016/j.still.2009.09.002
   Capowiez Y, 2009, SOIL BIOL BIOCHEM, V41, P711, DOI 10.1016/j.soilbio.2009.01.006
   Chamberlain EJ, 2008, EUR J SOIL BIOL, V44, P554, DOI 10.1016/j.ejsobi.2008.07.010
   Ciscar JC, 2011, P NATL ACAD SCI USA, V108, P2678, DOI 10.1073/pnas.1011612108
   Curry James P., 2004, P91
   Decaëns T, 2003, PEDOBIOLOGIA, V47, P479, DOI 10.1078/0031-4056-00217
   Decaëns T, 2008, APPL SOIL ECOL, V39, P321, DOI 10.1016/j.apsoil.2008.01.007
   Deru JGC, 2018, APPL SOIL ECOL, V125, P26, DOI 10.1016/j.apsoil.2017.12.011
   Díaz-Zorita M, 2000, SOIL TILL RES, V54, P121, DOI 10.1016/S0167-1987(00)00089-1
   Ducasse V, 2021, APPL SOIL ECOL, V168, DOI 10.1016/j.apsoil.2021.104131
   EDWARDS CA, 1980, J APPL ECOL, V17, P533, DOI 10.2307/2402635
   Eriksen-Hamel NS, 2007, EUR J SOIL BIOL, V43, P142, DOI 10.1016/j.ejsobi.2006.11.005
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Frazao J, 2019, APPL SOIL ECOL, V142, P177, DOI 10.1016/j.apsoil.2019.04.022
   GUILD WJM, 1948, ANN APPL BIOL, V35, P181, DOI 10.1111/j.1744-7348.1948.tb07360.x
   Hawkins CL, 2008, SOIL SCI, V173, P186, DOI 10.1097/SS.0b013e318163a9ce
   Holmstrup M, 2011, ACTA AGR SCAND B-S P, V61, P583, DOI 10.1080/09064710.2010.526629
   JONES CG, 1994, OIKOS, V69, P373, DOI 10.2307/3545850
   Lee K. E., 1985, Earthworms: their ecology and relationships with soils and land use.
   Lees KJ, 2016, AGR ECOSYST ENVIRON, V232, P273, DOI 10.1016/j.agee.2016.07.026
   Lindahl AML, 2009, VADOSE ZONE J, V8, P911, DOI 10.2136/vzj2008.0140
   louisbolk, Doorbreken pendelende regenwormen schalterveen? | louis Bolk instituut
   LOW AJ, 1972, J SOIL SCI, V23, P363, DOI 10.1111/j.1365-2389.1972.tb01668.x
   Lowe CN, 2005, PEDOBIOLOGIA, V49, P401, DOI 10.1016/j.pedobi.2005.04.005
   Lowe CN, 2002, BIOL FERT SOILS, V35, P204, DOI 10.1007/s00374-002-0471-7
   Nieminen M, 2011, ECOL APPL, V21, P3162, DOI 10.1890/10-1801.1
   NORDSTRM S, 1974, PEDOBIOLOGIA, V14, P1
   Nuutinen V, 2003, PEDOBIOLOGIA, V47, P578, DOI 10.1016/S0031-4056(04)70241-3
   Nuutinen V, 2001, EUR J SOIL BIOL, V37, P301, DOI 10.1016/S1164-5563(01)01105-0
   Nuutinen V, 2011, PEDOBIOLOGIA, V54, pS167, DOI 10.1016/j.pedobi.2011.07.010
   Orlowsky B, 2012, CLIMATIC CHANGE, V110, P669, DOI 10.1007/s10584-011-0122-9
   Ouellet G, 2008, APPL SOIL ECOL, V39, P35, DOI 10.1016/j.apsoil.2007.11.003
   Palm J, 2013, PEDOBIOLOGIA, V56, P23, DOI 10.1016/j.pedobi.2012.08.007
   Pelosi C, 2009, EUR J SOIL BIOL, V45, P176, DOI 10.1016/j.ejsobi.2008.09.013
   Pitkanen J, 1997, SOIL BIOL BIOCHEM, V29, P463, DOI 10.1016/S0038-0717(96)00040-5
   Pöhlitz J, 2019, GEODERMA, V346, P52, DOI 10.1016/j.geoderma.2019.03.023
   Potvin LR, 2017, BIOL FERT SOILS, V53, P187, DOI 10.1007/s00374-016-1173-x
   R Core Team, 2020, R: A Language and Environment for Statistical Computing
   Reyer CPO, 2013, GLOBAL CHANGE BIOL, V19, P75, DOI 10.1111/gcb.12023
   Riley H, 2008, AGR ECOSYST ENVIRON, V124, P275, DOI 10.1016/j.agee.2007.11.002
   Rs. Team, 2020, RStudio
   Sairam RK, 2008, BIOL PLANTARUM, V52, P401, DOI 10.1007/s10535-008-0084-6
   Schils R.L.M, 2012, 30 vragen en antwoorden over bodemvruchtbaarheid
   Shipitalo Martin J., 2004, P183
   Sims R W., 1985, Earthworms: keys and notes for the identification and study of the species, V31
   Smith CW, 1997, SOIL TILL RES, V41, P53, DOI 10.1016/S0167-1987(96)01084-7
   Stockdill S.M.J., 1966, P NZ GRASSLAND ASS, P168
   STOP-BOWITZ C, 1969, Nytt Magasin for Zoologi (Oslo), V17, P169
   Uvarov AV, 2009, PEDOBIOLOGIA, V53, P1, DOI 10.1016/j.pedobi.2009.05.001
   Valckx J, 2011, PEDOBIOLOGIA, V54, pS139, DOI 10.1016/j.pedobi.2011.07.004
   Valckx J, 2009, APPL SOIL ECOL, V41, P315, DOI 10.1016/j.apsoil.2008.12.005
   van de Logt R, 2023, EUR J SOIL BIOL, V119, DOI 10.1016/j.ejsobi.2023.103536
   van der Meuten MJ, 2007, NETH J GEOSCI, V86, P117, DOI 10.1017/S001677460002312X
   Van der Veer G, 2006, Geochemical Soil Survey of the Netherlands', Atlas of Major and Trace Elements in Topsoil and Parent Material
   van Eekeren N, 2008, APPL SOIL ECOL, V40, P432, DOI 10.1016/j.apsoil.2008.06.010
   van Groenigen JW, 2014, SCI REP-UK, V4, DOI 10.1038/srep06365
   Wang XJ, 2016, MITIG ADAPT STRAT GL, V21, P81, DOI 10.1007/s11027-014-9571-6
   WATKIN BR, 1966, J BRIT GRASSLAND SOC, V21, P14
   Whalen JK, 2003, PEDOBIOLOGIA, V47, P801, DOI 10.1016/S0031-4056(04)70271-1
NR 74
TC 5
Z9 5
U1 3
U2 10
PU ELSEVIER FRANCE-EDITIONS SCIENTIFIQUES MEDICALES ELSEVIER
PI ISSY-LES-MOULINEAUX
PA 65 RUE CAMILLE DESMOULINS, CS50083, 92442 ISSY-LES-MOULINEAUX, FRANCE
SN 1164-5563
EI 1778-3615
J9 EUR J SOIL BIOL
JI Eur. J. Soil Biol.
PD NOV-DEC
PY 2023
VL 119
AR 103545
DI 10.1016/j.ejsobi.2023.103545
EA SEP 2023
PG 8
WC Ecology; Soil Science
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Agriculture
GA U2ML4
UT WOS:001083195400001
OA hybrid
DA 2025-01-10
ER

PT J
AU Auerbach, BM
   Savell, KRR
   Agosto, ER
AF Auerbach, Benjamin M.
   Savell, Kristen R. R.
   Agosto, Elizabeth R.
TI Morphology, evolution, and the whole organism imperative: Why
   evolutionary questions need multi-trait evolutionary quantitative
   genetics
SO AMERICAN JOURNAL OF BIOLOGICAL ANTHROPOLOGY
LA English
DT Article
DE evolvability; functional trait complex; G-matrix; human limb evolution;
   morphological integration
ID NATURAL-SELECTION; BODY PROPORTIONS; DIFFERENTIAL PRESERVATION;
   PHENOTYPIC CORRELATIONS; CLIMATIC ADAPTATION; POPULATION HISTORY;
   ADAPTIVE RADIATION; SERIAL HOMOLOGY; GENUS SAGUINUS; BERGMANNS RULE
AB Since Washburn's New Physical Anthropology, researchers have sought to understand the complexities of morphological evolution among anatomical regions in human and non-human primates. Researchers continue, however, to preferentially use comparative and functional approaches to examine complex traits, but these methods cannot address questions about evolutionary process and often conflate function with fitness. Moreover, researchers also tend to examine anatomical elements in isolation, which implicitly assumes independent evolution among different body regions. In this paper, we argue that questions asked in primate evolution are best examined using multiple anatomical regions subjected to model-bound methods built from an understanding of evolutionary quantitative genetics. A nascent but expanding number of studies over the last two decades use this approach, examining morphological integration, evolvability, and selection modeling. To help readers learn how to use these methods, we review fundamentals of evolutionary processes within a quantitative genetic framework, explore the importance of neutral evolutionary theory, and explain the basics of evolutionary quantitative genetics, namely the calculation of evolutionary potential for multiple traits in response to selection. Leveraging these methods, we demonstrate their use to understand non-independence in possible evolutionary responses across the limbs, limb girdles, and basicranium of humans. Our results show that model-bound quantitative genetic methods can reveal unexpected genetic covariances among traits that create a novel but measurable understanding of evolutionary complexity among multiple traits. We advocate for evolutionary quantitative genetic methods to be a standard whenever appropriate to keep studies of primate morphological evolution relevant for the next seventy years and beyond.
C1 [Auerbach, Benjamin M.] Univ Tennessee, Dept Anthropol, Knoxville, TN USA.
   [Auerbach, Benjamin M.] Univ Tennessee, Dept Ecol & Evolutionary Biol, Knoxville, TN USA.
   [Savell, Kristen R. R.] Sacred Heart Univ, Dept Biol, Fairfield, CT USA.
   [Agosto, Elizabeth R.] Indiana Univ Sch Med, Dept Anat Cell Biol & Physiol, Indianapolis, IN USA.
   [Auerbach, Benjamin M.] Univ Tennessee, Dept Anthropol, 1621 Cumberland Ave,Room 505, Knoxville, TN 37996 USA.
C3 University of Tennessee System; University of Tennessee Knoxville;
   University of Tennessee System; University of Tennessee Knoxville;
   Sacred Heart University; Indiana University System; Indiana University
   Bloomington; University of Tennessee System; University of Tennessee
   Knoxville
RP Auerbach, BM (corresponding author), Univ Tennessee, Dept Anthropol, 1621 Cumberland Ave,Room 505, Knoxville, TN 37996 USA.
EM auerbach@utk.edu
RI Savell, Kristen/JDM-4300-2023; Auerbach, Benjamin/M-7096-2019
OI Savell, Kristen/0000-0002-0022-6283; Auerbach,
   Benjamin/0000-0002-3435-4427; Agosto, Elizabeth/0000-0001-5355-8401
CR Ackermann RR, 2000, AM J PHYS ANTHROPOL, V111, P489, DOI 10.1002/(SICI)1096-8644(200004)111:4<489::AID-AJPA5>3.0.CO;2-U
   Ackermann RR, 2002, AM J PHYS ANTHROPOL, V117, P260, DOI 10.1002/ajpa.10038
   Ackermann RR, 2004, P NATL ACAD SCI USA, V101, P17946, DOI 10.1073/pnas.0405919102
   Ackermann RR, 2002, J HUM EVOL, V43, P167, DOI 10.1006/jhev.2002.0569
   Agosto ER, 2022, J HUM EVOL, V169, DOI 10.1016/j.jhevol.2022.103221
   Agosto ER, 2021, EVOL BIOL, V48, P221, DOI 10.1007/s11692-021-09532-2
   Alberch P., 1982, DEV EVOLUTION
   Machado FA, 2018, EVOLUTION, V72, P1399, DOI 10.1111/evo.13495
   [Anonymous], 1985, The Dialectical Biologist
   [Anonymous], 1932, The causes of evolution
   [Anonymous], J HUM EVOL, DOI [10.1016/j.jhevol.2022.103268, DOI 10.1016/J.JHEVOL.2022.103268]
   [Anonymous], 1877, Radical Review
   [Anonymous], 1937, Animal Breeding Plans
   Arlegi M, 2020, AM J PHYS ANTHROPOL, V171, P17, DOI 10.1002/ajpa.23950
   Arnold SJ, 2001, GENETICA, V112, P9, DOI 10.1023/A:1013373907708
   ARNOLD SJ, 1992, AM NAT, V140, pS85, DOI 10.1086/285398
   ARNOLD SJ, 1983, AM ZOOL, V23, P347, DOI 10.1093/icb/23.2.347
   Arnold SJ, 2008, EVOLUTION, V62, P2451, DOI 10.1111/j.1558-5646.2008.00472.x
   Ashton KG, 2000, AM NAT, V156, P390, DOI 10.1086/303400
   Auerbach B. M., 2007, THESIS JOHNS HOPKINS
   Auerbach BM, 2014, CAM S BIO EVOL ANTHR, V68, P235
   Auerbach BM, 2012, AM J PHYS ANTHROPOL, V149, P525, DOI 10.1002/ajpa.22154
   Auerbach BM, 2011, AM J PHYS ANTHROPOL, V144, P382, DOI 10.1002/ajpa.21418
   Auerbach BM., 2010, Human Variation in the Americas: the integration of archaeology and biological anthropology, P172
   Baab KL, 2018, EVOLUTION, V72, P2781, DOI 10.1111/evo.13637
   Bergmann KGLC., 1847, Gttinger Studien, V3, P595
   Betti L, 2015, AM J PHYS ANTHROPOL, V158, P132, DOI 10.1002/ajpa.22774
   Betti L, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0055909
   Betti L, 2012, HUM BIOL, V84, P139, DOI 10.3378/027.084.0203
   Bogin B, 2022, J PHYSIOL ANTHROPOL, V41, DOI 10.1186/s40101-022-00287-z
   Bolstad GH, 2014, PHILOS T R SOC B, V369, DOI 10.1098/rstb.2013.0255
   Boughner JC, 2016, DEVELOPMENTAL APPROACHES TO HUMAN EVOLUTION, P35
   Boyle EA, 2017, CELL, V169, P1177, DOI 10.1016/j.cell.2017.05.038
   Brown RL, 2014, BRIT J PHILOS SCI, V65, P549, DOI 10.1093/bjps/axt014
   BULMER MG, 1971, AM NAT, V105, P201, DOI 10.1086/282718
   BULMER MG, 1976, GENET RES, V28, P101, DOI 10.1017/S0016672300016797
   Burness G, 2013, P ROY SOC B-BIOL SCI, V280, DOI 10.1098/rspb.2013.1436
   Capdevila J, 2001, ANNU REV CELL DEV BI, V17, P87, DOI 10.1146/annurev.cellbio.17.1.87
   CHARLESWORTH B, 1982, EVOLUTION, V36, P474, DOI 10.1111/j.1558-5646.1982.tb05068.x
   CHEVERUD JM, 1995, AM NAT, V145, P63, DOI 10.1086/285728
   Cheverud JM, 1996, AM ZOOL, V36, P44
   CHEVERUD JM, 1988, EVOLUTION, V42, P958, DOI [10.2307/2408911, 10.1111/j.1558-5646.1988.tb02514.x]
   CHEVERUD JM, 1984, J THEOR BIOL, V110, P155, DOI 10.1016/S0022-5193(84)80050-8
   Conaway MA, 2022, EVOLUTION, V76, P2244, DOI 10.1111/evo.14595
   Conaway MA, 2018, AM J PHYS ANTHROPOL, V166, P661, DOI 10.1002/ajpa.23456
   Cowgill LW, 2012, AM J PHYS ANTHROPOL, V148, P557, DOI 10.1002/ajpa.22072
   DeGiorgio M, 2011, GENETICS, V189, P579, DOI 10.1534/genetics.111.129296
   Diogo R., 2012, COMP ANATOMY PHYLOGE
   Falconer D. S., 1996, Introduction to quantitative genetics.
   Fatah EEA, 2012, AM J PHYS ANTHROPOL, V149, P547, DOI 10.1002/ajpa.22156
   FELSENSTEIN J, 1985, AM NAT, V125, P1, DOI 10.1086/284325
   FISCHER R.A., 1919, EARTH ENV SCI T R SO, V52, P399, DOI [10.1017/S0080456800012163, DOI 10.1017/S0080456800012163]
   Fix A.G., 1999, MIGRATION COLONIZATI
   Futuyma DJ., 2017, Evolution, V4
   Garant D, 2007, FUNCT ECOL, V21, P434, DOI 10.1111/j.1365-2435.2006.01228.x
   Garland T, 2009, EXPERIMENTAL EVOLUTION: CONCEPTS, METHODS, AND APPLICATIONS OF SELECTION EXPERIMENTS, P1, DOI 10.1525/california/9780520247666.001.0001
   González-José R, 2004, AM J PHYS ANTHROPOL, V123, P69, DOI 10.1002/ajpa.10302
   GOULD SJ, 1979, PROC R SOC SER B-BIO, V205, P581, DOI 10.1098/rspb.1979.0086
   GOULD SJ, 1982, PALEOBIOLOGY, V8, P4, DOI 10.1017/S0094837300004310
   Grabowski M, 2017, METHODS ECOL EVOL, V8, P592, DOI 10.1111/2041-210X.12674
   Grabowski M, 2015, J HUM EVOL, V85, P94, DOI 10.1016/j.jhevol.2015.05.008
   Grabowski MW, 2013, EVOL BIOL, V40, P57, DOI 10.1007/s11692-012-9174-7
   Grabowski MW, 2011, EVOLUTION, V65, P1336, DOI 10.1111/j.1558-5646.2011.01226.x
   Green RM, 2019, DEV DYNAM, V248, P1232, DOI 10.1002/dvdy.110
   Green RM, 2017, NAT COMMUN, V8, DOI 10.1038/s41467-017-02037-7
   Greenberg R, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0040933
   GUGLIELMINOMATESSI CR, 1979, AM J PHYS ANTHROPOL, V50, P549, DOI 10.1002/ajpa.1330500407
   Hall BK., 1999, EVOLUTIONARY DEV BIO
   Hallgrímsson B, 2007, EVOL DEV, V9, P76, DOI 10.1111/j.1525-142X.2006.00139.x
   Hallgrímsson B, 2002, YEARB PHYS ANTHROPOL, V45, P131, DOI 10.1002/ajpa.10182
   Hallgrímsson B, 2020, GENET MED, V22, P1682, DOI 10.1038/s41436-020-0845-y
   Hallgrímsson B, 2009, EVOL BIOL, V36, P355, DOI 10.1007/s11692-009-9076-5
   Hammond AS, 2017, ANAT REC, V300, P828, DOI 10.1002/ar.23545
   Hansen TF, 2008, J EVOLUTION BIOL, V21, P1201, DOI 10.1111/j.1420-9101.2008.01573.x
   Hansen TF, 2003, J EXP ZOOL PART B, V296B, P23, DOI 10.1002/jez.b.00014
   Hansen TF, 2004, PHENOTYPIC INTEGRATION: STUDYING THE ECOLOGY AND EVOLUTION OF COMPLEX PHENOTYPES, P130
   Hansen TF, 1996, EVOLUTION, V50, P1404, DOI 10.1111/j.1558-5646.1996.tb03914.x
   Hansen TF, 2003, BIOSYSTEMS, V69, P83, DOI 10.1016/S0303-2647(02)00132-6
   Hansen TF, 2021, ANNU REV ECOL EVOL S, V52, P153, DOI 10.1146/annurev-ecolsys-011121-021241
   Hansen TF, 2019, EVOLUTION, V73, P689, DOI 10.1111/evo.13705
   Hansen TF, 2011, EVOL BIOL, V38, P258, DOI 10.1007/s11692-011-9127-6
   Harmon LJ, 2006, EVOLUTION, V60, P2622
   Harvati K, 2006, ANAT REC PART A, V288A, P1225, DOI 10.1002/ar.a.20395
   Harvey PH., 1991, The Comparative Method in Evolutionary Biology
   Hendry AP, 2019, FUNCT ECOL, V33, P84, DOI 10.1111/1365-2435.13244
   Hendry AP, 2017, PHILOS T R SOC B, V372, DOI 10.1098/rstb.2016.0028
   HIERNAUX J, 1976, HUM BIOL, V48, P757
   HIERNAUX J, 1975, ANN HUM BIOL, V2, P3, DOI 10.1080/03014467500000511
   Holliday TW, 2010, AM J PHYS ANTHROPOL, V142, P287, DOI 10.1002/ajpa.21226
   Holliday TW, 1997, J HUM EVOL, V32, P423, DOI 10.1006/jhev.1996.0111
   Holliday TW, 2001, AM J PHYS ANTHROPOL, V116, P26, DOI 10.1002/ajpa.1098
   Holliday TW, 1999, J HUM EVOL, V36, P549, DOI 10.1006/jhev.1998.0289
   HOULE D, 1991, EVOLUTION, V45, P630, DOI [10.2307/2409916, 10.1111/j.1558-5646.1991.tb04334.x]
   Houle D, 2022, ANNU REV ECOL EVOL S, V53, P137, DOI 10.1146/annurev-ecolsys-102320-090809
   Houle D, 2013, EVOLUTION, V67, P1116, DOI 10.1111/j.1558-5646.2012.01838.x
   Houle D, 2011, Q REV BIOL, V86, P3, DOI 10.1086/658408
   Hunley K, 2011, AM J PHYS ANTHROPOL, V146, P530, DOI 10.1002/ajpa.21506
   Hunley KL, 2016, HUM BIOL, V88, P219, DOI 10.13110/humanbiology.88.3.0219
   Jabbour RebeccaS., 2008, Geographic variation in the forelimb and hindlimb skeletons of African apes
   JAMES FC, 1970, ECOLOGY, V51, P365, DOI 10.2307/1935374
   Jones AG, 2012, J EVOLUTION BIOL, V25, P2210, DOI 10.1111/j.1420-9101.2012.02598.x
   Jones AG, 2003, EVOLUTION, V57, P1747
   Jung H, 2020, EVOL BIOL, V47, P293, DOI 10.1007/s11692-020-09514-w
   Katz DC, 2016, AM J PHYS ANTHROPOL, V160, P593, DOI 10.1002/ajpa.22896
   KIMURA M, 1968, NATURE, V217, P624, DOI 10.1038/217624a0
   KIMURA M, 1964, GENETICS, V49, P725
   Kolbe JJ, 2011, EVOLUTION, V65, P3608, DOI 10.1111/j.1558-5646.2011.01416.x
   Kurki HK, 2008, AM J PHYS ANTHROPOL, V136, P28, DOI 10.1002/ajpa.20774
   Kurki HK, 2012, AM J PHYS ANTHROPOL, V147, P462, DOI 10.1002/ajpa.22024
   LAMBERS H, 1992, ADV ECOL RES, V23, P187, DOI 10.1016/S0065-2504(08)60148-8
   LANDE R, 1985, P NATL ACAD SCI USA, V82, P7641, DOI 10.1073/pnas.82.22.7641
   LANDE R, 1986, PALEOBIOLOGY, V12, P343, DOI 10.1017/S0094837300003092
   LANDE R, 1979, EVOLUTION, V33, P234, DOI 10.1111/j.1558-5646.1979.tb04678.x
   LEROI AM, 1994, AM NAT, V143, P381, DOI 10.1086/285609
   Lewton KL, 2012, EVOL BIOL, V39, P126, DOI 10.1007/s11692-011-9143-6
   Li M, 2017, J ANAT, V230, P607, DOI 10.1111/joa.12576
   Liu H, 2006, AM J HUM GENET, V79, P230, DOI 10.1086/505436
   Love AC, 2003, PHILOS SCI, V70, P1015, DOI 10.1086/377385
   Love AC, 2022, PALEOBIOLOGY, V48, P186, DOI 10.1017/pab.2021.36
   Lucas LK, 2018, MOL ECOL RESOUR, V18, P892, DOI 10.1111/1755-0998.12777
   LYNCH M, 1993, BIOTIC INTERACTIONS AND GLOBAL CHANGE, P234
   Lynch M, 2007, The Origins of Genome Architecture
   Lynch Michael, 1998
   Machado FA, 2019, EVOLUTION, V73, P2518, DOI 10.1111/evo.13864
   Madrigal L., 2010, COMPANION BIOL ANTHR, P222, DOI [10.1002/9781444320039.ch12, DOI 10.1002/9781444320039.CH12]
   Mallard AM, 2017, ANAT REC, V300, P666, DOI 10.1002/ar.23547
   Marchini M, 2018, EVOLUTION, V72, P825, DOI 10.1111/evo.13447
   Marroig G, 2012, EVOLUTION, V66, P1506, DOI 10.1111/j.1558-5646.2011.01555.x
   Marroig G, 2010, EVOLUTION, V64, P1470, DOI 10.1111/j.1558-5646.2009.00920.x
   Marroig G, 2009, EVOL BIOL, V36, P136, DOI 10.1007/s11692-009-9051-1
   Martins EP, 2000, TRENDS ECOL EVOL, V15, P296, DOI 10.1016/S0169-5347(00)01880-2
   Martins EP, 1997, AM NAT, V149, P646, DOI 10.1086/286013
   Matsuoka T, 2005, NATURE, V436, P347, DOI 10.1038/nature03837
   MAYR E, 1956, EVOLUTION, V10, P105, DOI 10.1111/j.1558-5646.1956.tb02836.x
   McGlothlin JW, 2018, EVOL LETT, V2, P310, DOI 10.1002/evl3.72
   McGuigan K, 2009, TRENDS ECOL EVOL, V24, P305, DOI 10.1016/j.tree.2009.02.001
   Medina A, 2007, J BIOGEOGR, V34, P1439, DOI 10.1111/j.1365-2699.2007.01708.x
   Meiri S, 2003, J BIOGEOGR, V30, P331, DOI 10.1046/j.1365-2699.2003.00837.x
   Melo D, 2016, ANNU REV ECOL EVOL S, V47, P463, DOI 10.1146/annurev-ecolsys-121415-032409
   Mitteroecker P, 2022, AM J BIOL ANTHROPOL, V178, P181, DOI 10.1002/ajpa.24531
   Mitteroecker P, 2009, EVOL BIOL, V36, P377, DOI 10.1007/s11692-009-9075-6
   MOSIMANN JE, 1970, J AM STAT ASSOC, V65, P930, DOI 10.2307/2284599
   NEWMAN M T, 1960, Hum Biol, V32, P288
   Newman MT, 1953, AM ANTHROPOL, V55, P311, DOI 10.1525/aa.1953.55.3.02a00020
   Ohta T, 1996, THEOR POPUL BIOL, V49, P128, DOI 10.1006/tpbi.1996.0007
   Olsen E., 1958, Morphological Integration
   Parins-Fukuchi C, 2020, EVOLUTION, V74, P297, DOI 10.1111/evo.13923
   Pélabon C, 2021, EVOLUTION, V75, P2217, DOI 10.1111/evo.14284
   Pigliucci M, 2005, TRENDS ECOL EVOL, V20, P481, DOI 10.1016/j.tree.2005.06.001
   Pigliucci M, 2000, TRENDS ECOL EVOL, V15, P66, DOI 10.1016/S0169-5347(99)01762-0
   Pitchers WR, 2014, J EVOLUTION BIOL, V27, P2163, DOI 10.1111/jeb.12471
   Porto A, 2013, EVOLUTION, V67, P3305, DOI 10.1111/evo.12177
   R Core Team, 2022, R: A Language and Environment for Statistical Computing
   Ramachandran S, 2005, P NATL ACAD SCI USA, V102, P15942, DOI 10.1073/pnas.0507611102
   Randau M, 2018, EVOL BIOL, V45, P196, DOI 10.1007/s11692-017-9443-6
   Reusch T, 1998, HEREDITY, V81, P111, DOI 10.1046/j.1365-2540.1998.00368.x
   Reznick DN, 2019, ECOL LETT, V22, P233, DOI 10.1111/ele.13189
   Richard D, 2020, CELL, V181, P362, DOI 10.1016/j.cell.2020.02.057
   Roberts DF, 1953, AM J PHYS ANTHROP-NE, V11, P533, DOI 10.1002/ajpa.1330110404
   Roberts D.F., 1978, CLIMATE HUMAN VARIAB, VSecond
   Roff DA, 1996, EVOLUTION, V50, P1392, DOI [10.2307/2410877, 10.1111/j.1558-5646.1996.tb03913.x]
   Roff DA, 1999, J EVOLUTION BIOL, V12, P361, DOI 10.1046/j.1420-9101.1999.00036.x
   ROFF DA, 1995, HEREDITY, V74, P481, DOI 10.1038/hdy.1995.68
   Rolian C, 2020, WIRES DEV BIOL, V9, DOI 10.1002/wdev.373
   Rolian C, 2020, EVOLUTION, V74, P702, DOI 10.1111/evo.13900
   Rolian C, 2014, EVOL ANTHROPOL, V23, P93, DOI 10.1002/evan.21409
   Rolian C, 2010, EVOLUTION, V64, P1558, DOI 10.1111/j.1558-5646.2010.00944.x
   Rolian C, 2009, EVOL BIOL, V36, P100, DOI 10.1007/s11692-009-9049-8
   Roseman CC, 2007, BIOESSAYS, V29, P1185, DOI 10.1002/bies.20678
   Roseman CC, 2020, J EXP ZOOL PART B, V334, P100, DOI 10.1002/jez.b.22926
   Roseman CC, 2018, HUM BIOL, V90, P241, DOI 10.13110/humanbiology.90.4.05
   Roseman CC, 2016, AM J PHYS ANTHROPOL, V160, P582, DOI 10.1002/ajpa.22918
   Roseman CC, 2015, J HUM EVOL, V78, P80, DOI 10.1016/j.jhevol.2014.07.006
   Roseman CC, 2012, AM J PHYS ANTHROPOL, V147, P252
   Roseman CC, 2010, AM J PHYS ANTHROPOL, V143, P1, DOI 10.1002/ajpa.21341
   RUFF CB, 1991, J HUM EVOL, V21, P81, DOI 10.1016/0047-2484(91)90001-C
   Ruff CB, 2003, AM J PHYS ANTHROPOL, V120, P16, DOI 10.1002/ajpa.10118
   Ruff Christopher B., 1994, Yearbook of Physical Anthropology, V37, P65
   Savell KRR, 2022, AM J BIOL ANTHROPOL, V179, P431, DOI 10.1002/ajpa.24586
   Savell KRR, 2020, AM J PHYS ANTHROPOL, V172, P110, DOI 10.1002/ajpa.24004
   Savell KRR, 2016, P NATL ACAD SCI USA, V113, P9492, DOI 10.1073/pnas.1603632113
   Schlosser G, 2004, MODULARITY IN DEVELOPMENT AND EVOLUTION, P519
   Schluter D, 1996, EVOLUTION, V50, P1766, DOI 10.1111/j.1558-5646.1996.tb03563.x
   SCHOLANDER PF, 1955, EVOLUTION, V9, P15, DOI 10.2307/2405354
   SCHOLANDER PF, 1956, EVOLUTION, V10, P339, DOI 10.1111/j.1558-5646.1956.tb02859.x
   Schroeder L, 2017, EVOLUTION, V71, P2634, DOI 10.1111/evo.13361
   Schroeder L, 2017, J HUM EVOL, V111, P1, DOI 10.1016/j.jhevol.2017.06.004
   Sears KE, 2015, EVOLUTION, V69, P2543, DOI 10.1111/evo.12773
   Singh N, 2012, J HUM EVOL, V62, P155, DOI 10.1016/j.jhevol.2011.11.006
   Sniegula S, 2018, J EVOLUTION BIOL, V31, P853, DOI 10.1111/jeb.13269
   Sodini SM, 2018, GENETICS, V209, P941, DOI 10.1534/genetics.117.300630
   STEVENSON RD, 1986, J MAMMAL, V67, P312, DOI 10.2307/1380884
   STINSON S, 1990, AM J HUM BIOL, V2, P37, DOI 10.1002/ajhb.1310020105
   Stock JT, 2006, AM J PHYS ANTHROPOL, V131, P194, DOI 10.1002/ajpa.20398
   Sylvester AD, 2008, AM J PHYS ANTHROPOL, V137, P371, DOI 10.1002/ajpa.20880
   Symonds MRE, 2010, AM NAT, V176, P188, DOI 10.1086/653666
   Teixeira JC, 2019, P NATL ACAD SCI USA, V116, P15327, DOI 10.1073/pnas.1904824116
   Temple DH, 2008, AM J PHYS ANTHROPOL, V137, P164, DOI 10.1002/ajpa.20853
   Trinkaus E, 2014, P NATL ACAD SCI USA, V111, P4438, DOI 10.1073/pnas.1402439111
   Trinkaus Erik., 1981, ASPECTS HUMAN EVOLUT, P187
   Twede DR, 2003, P SOC PHOTO-OPT INS, V5159, P299, DOI 10.1117/12.506993
   Unger CM, 2021, ELIFE, V10, DOI 10.7554/eLife.67612
   Uyeda JC, 2011, P NATL ACAD SCI USA, V108, P15908, DOI 10.1073/pnas.1014503108
   Van Valen L, 1973, Evol Theory, V1, P1
   Villamil CI, 2018, EVOLUTION, V72, P490, DOI 10.1111/evo.13433
   Villmoare B, 2011, EVOL BIOL, V38, P88, DOI 10.1007/s11692-011-9108-9
   von Cramon-Taubadel N, 2022, J ANTHROPOL SCI, V100, P109, DOI [10.4436/jass.10012, 10.4436/JASS.10012]
   von Cramon-Taubadel N, 2019, EVOL ANTHROPOL, V28, P21, DOI 10.1002/evan.21761
   Waddington CH., 1957, The strategy of the genes
   WAGNER GP, 1990, Z ZOOL SYST EVOL, V28, P48
   Wagner GP, 1996, AM ZOOL, V36, P36
   Wagner GP, 1996, EVOLUTION, V50, P967, DOI 10.1111/j.1558-5646.1996.tb02339.x
   WAGNER GP, 1984, J MATH BIOL, V21, P77, DOI 10.1007/BF00275224
   Wagner GP, 2007, NAT REV GENET, V8, P473, DOI 10.1038/nrg2099
   Waitt DE, 1998, HEREDITY, V80, P310, DOI 10.1046/j.1365-2540.1998.00298.x
   Wall-Schffler C. M., 2020, EVOLUTIONARY BIOL HU
   Walsh B., 2018, Evolution and selection of quantitative traits, DOI DOI 10.1093/OSO/9780198830870.001.0001
   Walsh B, 2009, ANNU REV ECOL EVOL S, V40, P41, DOI 10.1146/annurev.ecolsys.110308.120232
   Wang Zexuan, 2022, Proceedings (IEEE Int Conf Bioinformatics Biomed), V2022, P1255, DOI [10.1109/bibm55620.2022.9995036, 10.1109/BIBM55620.2022.9995036]
   WASHBURN SL, 1951, T NEW YORK ACAD SCI, V13, P298, DOI 10.1111/j.2164-0947.1951.tb01033.x
   Weaver TD, 2015, P ROY SOC B-BIOL SCI, V282, DOI 10.1098/rspb.2015.1519
   Weinstein Karen J, 2011, Anat Res Int, V2011, P714624, DOI 10.1155/2011/714624
   Weinstein KJ, 2005, AM J PHYS ANTHROPOL, V128, P569, DOI 10.1002/ajpa.20137
   Whitlock MC, 1999, HEREDITY, V82, P117, DOI 10.1038/sj.hdy.6884960
   Wood CW, 2015, EVOLUTION, V69, P2927, DOI 10.1111/evo.12795
   Wright S, 1920, J AGRIC RES, V20, P0557
   Young M, 2022, SCI ADV, V8, DOI 10.1126/sciadv.abq4884
   Young M, 2019, CURR TOP DEV BIOL, V132, P311, DOI 10.1016/bs.ctdb.2018.12.007
   Young NM, 2017, INTEGR COMP BIOL, V57, P1293, DOI 10.1093/icb/icx115
   Young NM, 2010, P NATL ACAD SCI USA, V107, P3400, DOI 10.1073/pnas.0911856107
   Young NM, 2005, EVOLUTION, V59, P2691
   Zar J.H., 1999, Biostatistical Analysis
NR 232
TC 3
Z9 6
U1 1
U2 8
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 2692-7691
J9 AM J BIOL ANTHROPOL
JI Am. J. Biol. Anthropol.
PD AUG
PY 2023
VL 181
SU 76
BP 180
EP 211
DI 10.1002/ajpa.24733
EA APR 2023
PG 32
WC Anthropology; Evolutionary Biology
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Anthropology; Evolutionary Biology
GA L0MK6
UT WOS:000971935700001
PM 37060292
OA Bronze
DA 2025-01-10
ER

PT J
AU Zhai, SY
   Huang, PS
   Marshall, JC
   Lobegeiger, J
   Cramp, RL
   Parisi, MA
   Franklin, CE
   Prior, A
   Kurucz, K
   Hipsey, MR
AF Zhai, Sherry Y. Y.
   Huang, Peisheng
   Marshall, Jonathan C. C.
   Lobegeiger, Jaye
   Cramp, Rebecca L. L.
   Parisi, Monique A. A.
   Franklin, Craig E. E.
   Prior, Andrea
   Kurucz, Kamilla
   Hipsey, Matthew R. R.
TI Modelling prolonged stratification and hypoxia in dryland river
   waterholes during drought conditions
SO INLAND WATERS
LA English
DT Article
DE ecohydrological modelling; fish refugia; hypoxia; river waterhole;
   stratification; >
ID SALT-WEDGE ESTUARY; THERMAL STRATIFICATION; TEMPERATURE; VARIABILITY;
   LAKE; DYNAMICS; QUALITY; RISK; AUSTRALIA; NETWORK
AB Dryland river waterholes provide critical habitat and serve as refugia for aquatic animals during droughts, but the quality of these waterholes can often be severely compromised by hypoxic conditions that can lead to mass fish kills and loss of biodiversity. To assist river management, we developed a waterhole-scale ecohydrology model representing thermal stratification and dissolved oxygen regimes during prolonged drought periods in northern Murray-Darling Basin dryland rivers in Queensland, Australia. Model development focused around 6 typical waterholes in these rivers that were shallow (<5 m deep), highly turbid, and stratified with low dissolved oxygen. The model simulations utilised regional climate corrected for local factors such as diurnal vegetation shading and wind sheltering and successfully reproduced the prolonged stratification and hypoxia measured during drought conditions. The simulations highlight the distinct local climate each waterhole experiences due to the combined effects of river morphology and canopy cover that provide various degrees of solar shading and wind sheltering. The model can serve as a tool to inform water management decisions and climate adaptation strategies. Example scenarios demonstrate that (1) even where the canopy shading effect was small (5% at one site), further loss of riparian vegetation could increase temperature by 2-4 & DEG;C in warmer months with prolonged stratification; and (2) under an example RCP 8.5 climate change scenario, water temperature is likely to increase 2-10 & DEG;C, and oxygen saturation will decrease by 10% to 20% in the middle layers for most of the no-flow period by 2080-2099.
C1 [Zhai, Sherry Y. Y.; Huang, Peisheng; Kurucz, Kamilla; Hipsey, Matthew R. R.] Univ Western Australia, UWA Sch Agr & Environm, Aquat Ecodynam, Crawley, WA 6009, Australia.
   [Marshall, Jonathan C. C.; Lobegeiger, Jaye] Queensland Govt, Dept Environm & Sci, Dutton Pk, Australia.
   [Cramp, Rebecca L. L.; Parisi, Monique A. A.; Franklin, Craig E. E.] Univ Queensland, Sch Biol Sci, Brisbane, Australia.
   [Prior, Andrea] Queensland Govt, Dept Reg Dev Mfg & Water, Brisbane, Qld, Australia.
   [Marshall, Jonathan C. C.] Griffith Univ, Australian Rivers Inst, Nathan, Australia.
C3 University of Western Australia; University of Queensland; Griffith
   University
RP Zhai, SY (corresponding author), Univ Western Australia, UWA Sch Agr & Environm, Aquat Ecodynam, Crawley, WA 6009, Australia.
EM sherry.zhai@uwa.edu.au
RI Cramp, Rebecca/A-4488-2010
OI Zhai, Sherry Yi/0000-0002-9310-2844; Huang, Peisheng/0000-0002-8347-7175
FU Queensland Government [DES20418]; Queensland Water Modelling Network
FX This work was supported by Queensland Government: [Grant Number
   DES20418]. The project was also funded by the Queensland Water Modelling
   Network.
CR Acuña V, 2014, SCIENCE, V343, P1080, DOI 10.1126/science.1246666
   Agostinho AA, 2021, NEOTROP ICHTHYOL, V19, DOI 10.1590/1982-0224-2021-0037
   Andersen MR, 2017, P ROY SOC B-BIOL SCI, V284, DOI 10.1098/rspb.2017.1427
   Baldwin DS, 2022, MAR FRESHWATER RES, V73, P211, DOI 10.1071/MF20365
   Beitinger TL, 2000, ENVIRON BIOL FISH, V58, P237, DOI 10.1023/A:1007676325825
   Bird R.E., 1981, SIMPLIFIED CLEAR SKY
   Biswas TK, 2019, WATER RESOUR MANAG, V33, P1087, DOI 10.1007/s11269-018-2168-1
   Bormans M, 1997, ENVIRON MODELL SOFTW, V12, P329, DOI 10.1016/S1364-8152(97)00032-7
   Branco B, 2005, LIMNOL OCEANOGR-METH, V3, P190, DOI 10.4319/lom.2005.3.190
   Branco BF, 2009, AQUAT SCI, V71, P65, DOI 10.1007/s00027-009-8063-3
   Brookes JD., 2019, WATER QUALITY UNPUB
   Bruce LC, 2014, HYDROL EARTH SYST SC, V18, P1397, DOI 10.5194/hess-18-1397-2014
   Bunn SE, 2006, RIVER RES APPL, V22, P179, DOI 10.1002/rra.904
   Bunn SE, 2002, ENVIRON MANAGE, V30, P492, DOI 10.1007/s00267-002-2737-0
   Christianson KR, 2020, AQUAT SCI, V82, DOI 10.1007/s00027-019-0676-6
   Cockayne B, 2021, J ARID ENVIRON, V187, DOI 10.1016/j.jaridenv.2020.104428
   Condie SA, 2001, J HYDRAUL ENG, V127, P286, DOI 10.1061/(ASCE)0733-9429(2001)127:4(286)
   Davidson K, 2016, HARMFUL ALGAE, V53, P1, DOI 10.1016/j.hal.2015.11.005
   Diaz RJ, 2001, J ENVIRON QUAL, V30, P275, DOI 10.2134/jeq2001.302275x
   [ DSITI] Department of Science Information Technology and Innovation, 2015, WAT REF MAPP PERS AN
   Elo AR, 2005, NORD HYDROL, V36, P281
   [ FRDC] Fisheries Research and Development Corporation, 2022, NAT CARP CONTR PLAN
   Garner G, 2017, J HYDROL, V553, P471, DOI 10.1016/j.jhydrol.2017.03.024
   Haesemeyer M, 2020, MOL CELL ENDOCRINOL, V518, DOI 10.1016/j.mce.2020.110986
   Hamilton GS, 2007, HUM ECOL RISK ASSESS, V13, P1271, DOI 10.1080/10807030701655616
   Heiskanen JJ, 2015, J GEOPHYS RES-ATMOS, V120, P7412, DOI 10.1002/2014JD022938
   Herb WR, 2004, LAKE RESERV MANAGE, V20, P296, DOI 10.1080/07438140409354159
   Hipsey MR, 2019, GEOSCI MODEL DEV, V12, P473, DOI 10.5194/gmd-12-473-2019
   Hipsey MR, 2003, WATER RESOUR RES, V39, DOI 10.1029/2002WR001784
   Hipsey MR., 2022, MODELLING AQUATIC EC, DOI [10.5281/ZENODO.6516222, DOI 10.5281/ZENODO.6516222, 10.5281/zenodo.6516222]
   Hocking GC, 1999, INT REV HYDROBIOL, V84, P535
   Holgerson MA., 2022, WATER RESOUR RES, P58
   Huang PS, 2018, ECOL ENG, V118, P111, DOI 10.1016/j.ecoleng.2018.04.020
   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]
   Jobling M. A., 1997, Seminar seriessociety for experimental biology, V61, P225, DOI [10.1017/CBO9780511983375.010, DOI 10.1017/CBO9780511983375]
   Kim J, 2017, ECOL MODEL, V366, P27, DOI 10.1016/j.ecolmodel.2017.10.015
   Kirono DGC, 2020, WEATHER CLIM EXTREME, V30, DOI 10.1016/j.wace.2020.100280
   Kopf RK, 2019, BIOL INVASIONS, V21, P1857, DOI 10.1007/s10530-019-01967-1
   Ladwig R, 2021, HYDROL EARTH SYST SC, V25, P1009, DOI 10.5194/hess-25-1009-2021
   Liu JJ, 2020, SCI TOTAL ENVIRON, V723, DOI 10.1016/j.scitotenv.2020.138020
   Liu M, 2022, HYDROL PROCESS, V36, DOI 10.1002/hyp.14502
   Lobegeiger J.S., 2010, Refugial Waterholes Project. Research Highlights
   LOSORDO TM, 1991, ECOL MODEL, V54, P189, DOI 10.1016/0304-3800(91)90076-D
   Marshall J, 2018, SCIENCE, V359, P877, DOI 10.1126/science.aar7827
   Marshall JC, 2021, FRONT ENV SCI-SWITZ, V9, DOI 10.3389/fenvs.2021.671556
   Martinsen KT, 2019, HYDROBIOLOGIA, V826, P247, DOI 10.1007/s10750-018-3737-2
   Mcgregor GB, 2018, ENVIRON MANAGE, V61, P358, DOI 10.1007/s00267-017-0850-3
   McJannet D, 2014, MAR FRESHWATER RES, V65, P1131, DOI 10.1071/MF14035
   McPhee D, 2023, CONSERV PHYSIOL, V11, DOI 10.1093/conphys/coac087
   [ MDBA] Murray-Darling Basin Authority, 2019, MDBA PUBLICATION, V09/19
   Mosley LM, 2021, J ENVIRON MANAGE, V286, DOI 10.1016/j.jenvman.2021.112213
   Müller R, 2004, FISHERIES MANAG ECOL, V11, P251, DOI 10.1111/j.1365-2400.2004.00393.x
   Padisák J, 2003, HYDROBIOLOGIA, V506, P1, DOI 10.1023/B:HYDR.0000008630.49527.29
   Pollock MS, 2007, ENVIRON REV, V15, P1, DOI [10.1139/A06-006, 10.1139/a06-006]
   Preite CK, 2017, ANN LIMNOL-INT J LIM, V53, P221, DOI 10.1051/limn/2017008
   Rayner TS, 2009, ECOHYDROLOGY, V2, P440, DOI 10.1002/eco.73
   Sheldon F, 2022, MAR FRESHWATER RES, V73, P147, DOI 10.1071/MF21038
   Sheldon F, 2010, MAR FRESHWATER RES, V61, P864, DOI 10.1071/MF09289
   Sheldon F, 2010, MAR FRESHWATER RES, V61, P885, DOI 10.1071/MF09239
   Stewart IT, 2020, J HYDROL X, V7, DOI 10.1016/j.hydroa.2020.100054
   Stocks JR, 2022, MAR FRESHWATER RES, V73, P159, DOI 10.1071/MF20340
   Sun L., 2020, J ADV MODEL EARTH SY, V12, pe2019MS001971
   Syktus J., 2020, Queensland future climate dashboard: downscaled CMIP5 climate projections for Queensland
   Tooth S, 2000, EARTH-SCI REV, V51, P67, DOI 10.1016/S0012-8252(00)00014-3
   Vertessy R., 2019, Independent Assessment of the 201819 Fish Deaths in the Lower Darling
   Vilas MP, 2018, HYDROBIOLOGIA, V806, P411, DOI 10.1007/s10750-017-3376-z
   Wallace J, 2017, MAR FRESHWATER RES, V68, P650, DOI 10.1071/MF15468
   WANNINKHOF R, 1992, J GEOPHYS RES-OCEANS, V97, P7373, DOI 10.1029/92JC00188
   Webb BW, 1997, HYDROL PROCESS, V11, P79, DOI 10.1002/(SICI)1099-1085(199701)11:1<79::AID-HYP404>3.0.CO;2-N
NR 69
TC 0
Z9 0
U1 4
U2 9
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 2044-2041
EI 2044-205X
J9 INLAND WATERS
JI Inland Waters
PD APR 3
PY 2023
VL 13
IS 2
BP 272
EP 292
DI 10.1080/20442041.2023.2213629
EA APR 2023
PG 21
WC Limnology; Marine & Freshwater Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Marine & Freshwater Biology
GA U9MY6
UT WOS:001045467600001
OA hybrid
DA 2025-01-10
ER

PT J
AU Eyster, HN
   Beckage, B
AF Eyster, Harold N.
   Beckage, Brian
TI Arboreal Urban Cooling Is Driven by Leaf Area Index, Leaf Boundary Layer
   Resistance, and Dry Leaf Mass per Leaf Area: Evidence from a System
   Dynamics Model
SO ATMOSPHERE
LA English
DT Article
DE heat wave; urban heat island; climate adaptation; microclimate; conifer;
   local climate; urban planning; human health; broadleaf trees; system
   dynamics model
ID HEAT-ISLAND; GREEN ROOFS; WATER-USE; TRANSPIRATION; TREES; TEMPERATURE;
   IMPACT; MICROCLIMATE; EFFICIENCY; CAPACITY
AB Heat waves are becoming more frequent due to climate change. Summer heat waves can be particularly deadly in cities, where temperatures are already inflated by abundant impervious, dark surfaces (i.e., the heat island effect). Urban heat waves might be ameliorated by planting and maintaining urban forests. Previous observational research has suggested that conifers may be particularly effective in cooling cities. However, the observational nature of these studies has prevented the identification of the direct and indirect mechanisms that drive this differential cooling. Here, we develop a systems dynamics representation of urban forests to model the effects of the percentage cover of either conifers or broadleaf trees on temperature. Our model includes physiological and morphological differences between conifers and broadleaf trees, and physical feedback among temperature and energy fluxes. We apply the model to a case study of Vancouver, BC, Canada. Our model suggests that in temperate rainforest cities, conifers may by 1.0 degrees C cooler than broadleaf trees; this differential increases to 1.2 degrees C when percentage tree cover increases from 17% to 22% and to 1.7 degrees C at 30% cover. Our model suggests that these differences are due to three key tree traits: leaf area index, leaf boundary layer resistance, and dry mass per leaf area. Creating urban forests that optimize these three variables may not only sequester CO(2 )to mitigate global climate change but also be most effective at locally minimizing deadly urban heat waves.
C1 [Eyster, Harold N.; Beckage, Brian] Univ Vermont, Gund Inst Environm, Burlington, VT 05405 USA.
   [Eyster, Harold N.; Beckage, Brian] Univ Vermont, Dept Plant Biol, Burlington, VT 05405 USA.
C3 University of Vermont; University of Vermont
RP Eyster, HN (corresponding author), Univ Vermont, Gund Inst Environm, Burlington, VT 05405 USA.; Eyster, HN (corresponding author), Univ Vermont, Dept Plant Biol, Burlington, VT 05405 USA.
EM haroldeyster@gmail.com
RI Eyster, Harold/AAH-5659-2020
OI Eyster, Harold N/0000-0002-5571-3126; Beckage, Brian/0000-0002-5908-6924
FU Gund Postdoctoral Fellowship; Environment and Climate Change Canada
   [GCXE22S079]
FX This research was funded by a Gund Postdoctoral Fellowship to HNE and by
   Environment and Climate Change Canada (GCXE22S079).
CR Anguelovski I, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-31572-1
   Anguelovski I, 2019, PROG HUM GEOG, V43, P1064, DOI 10.1177/0309132518803799
   Apple ME, 2000, INT J PLANT SCI, V161, P127, DOI 10.1086/314237
   Asadian Y, 2009, WATER QUAL RES J CAN, V44, P16, DOI 10.2166/wqrj.2009.003
   Bonan G, 2019, CLIMATE CHANGE AND TERRESTRIAL ECOSYSTEM MODELING, P152
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   City of Vancouve Open Data Portal, 2022, STREET TREES
   Dare R, 2021, URBAN SCI, V5, DOI 10.3390/urbansci5010019
   De Bock A, 2023, BUILD ENVIRON, V229, DOI 10.1016/j.buildenv.2022.109926
   Diamond Head Consulting District of North, 2004, VANCOUVERFROMME MOUN
   Domkea GM, 2020, P NATL ACAD SCI USA, V117, P24649, DOI 10.1073/pnas.2010840117
   Environment and Climate Change Canada, 2021, NAT SMART CLIM SOL F
   Er KBH, 2005, BIOL CONSERV, V126, P410, DOI 10.1016/j.biocon.2005.06.023
   Eyster HN, 2023, PEOPLE NAT, V5, P455, DOI 10.1002/pan3.10453
   Eyster HN, 2022, ATMOSPHERE-BASEL, V13, DOI 10.3390/atmos13050830
   Fischer EM, 2015, NAT CLIM CHANGE, V5, P560, DOI 10.1038/nclimate2617
   GATES DM, 1968, ANN REV PLANT PHYSIO, V19, P211, DOI 10.1146/annurev.pp.19.060168.001235
   Georgi JN, 2010, BUILD ENVIRON, V45, P1401, DOI 10.1016/j.buildenv.2009.12.003
   Georgi N. J., 2006, Urban Ecosystems, V9, P195, DOI 10.1007/s11252-006-8590-9
   Grossman-Clarke S, 2005, J APPL METEOROL, V44, P1281, DOI 10.1175/JAM2286.1
   Hirabayashi S., 2022, I TREE ECO DRY DEPOS
   HOLMGREN P, 1965, PHYSIOL PLANTARUM, V18, P557, DOI 10.1111/j.1399-3054.1965.tb06917.x
   HUTCHISON BA, 1986, J ECOL, V74, P635, DOI 10.2307/2260387
   Jaffal I, 2012, RENEW ENERG, V43, P157, DOI 10.1016/j.renene.2011.12.004
   Java O, 2021, WATER-SUI, V13, DOI 10.3390/w13162217
   Java O, 2020, BALT J MOD COMPUT, V8, P379, DOI 10.22364/bjmc.2020.8.3.01
   Kerstiens G., 1996, CUTICLES INTEGRATED
   Kimura K, 2020, AGR FOREST METEOROL, V280, DOI 10.1016/j.agrformet.2019.107773
   Konarska J, 2016, INT J BIOMETEOROL, V60, P159, DOI 10.1007/s00484-015-1014-x
   Kong J, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su131910923
   Kramer PJ., 1995, WATER RELATIONS PLAN, DOI DOI 10.1016/J.SCITOTENV.2022.153664
   Leong M, 2018, BIOL LETTERS, V14, DOI 10.1098/rsbl.2018.0082
   LEWIS DA, 1977, PLANT PHYSIOL, V60, P609, DOI 10.1104/pp.60.4.609
   Liebard A., 2005, Traite d'architecture et d'urbanisme bioclimatiques: concevoir, edifier et amenager avec le developpement durable
   López A, 2012, SCI HORTIC-AMSTERDAM, V137, P49, DOI 10.1016/j.scienta.2012.01.022
   Martin TA, 1999, TREE PHYSIOL, V19, P435
   Metro Vancouver Land Cover Classification, 2019, OPEN DATA CATALOGUE
   Ministry of Public Safety & Solicitor General BC Coroners Service (BCCS), 2021, HEAT REL DEATHS KNOW
   Mitchell D, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/7/074006
   Mohammed A, 2021, BUILD ENVIRON, V206, DOI 10.1016/j.buildenv.2021.108276
   Molina MJ, 2004, J AIR WASTE MANAGE, V54, P644, DOI 10.1080/10473289.2004.10470936
   Monteiro MV, 2016, AUST J BOT, V64, P32, DOI 10.1071/BT15198
   Monteiroa MV, 2017, ENERG BUILDINGS, V141, P56, DOI 10.1016/j.enbuild.2017.02.011
   Nesbitt L, 2018, URBAN FOR URBAN GREE, V34, P240, DOI 10.1016/j.ufug.2018.07.009
   Netzer Y, 2009, IRRIGATION SCI, V27, P109, DOI 10.1007/s00271-008-0124-1
   Niinemets U, 1999, NEW PHYTOL, V144, P35, DOI 10.1046/j.1469-8137.1999.00466.x
   Nobel P. S., 1991, Physicochemical and environmental plant physiology.
   OKE TR, 1975, ATMOS ENVIRON, V9, P191, DOI 10.1016/0004-6981(75)90067-0
   Pace R, 2021, INT J BIOMETEOROL, V65, P277, DOI 10.1007/s00484-020-02030-8
   Pallardy S.G., 2008, Physiology of Woody Plants, V3, P454
   Peng SS, 2012, ENVIRON SCI TECHNOL, V46, P696, DOI 10.1021/es2030438
   Philip SY, 2022, EARTH SYST DYNAM, V13, P1689, DOI 10.5194/esd-13-1689-2022
   PIERCE LL, 1988, ECOLOGY, V69, P1762, DOI 10.2307/1941154
   Rahman MA, 2015, URBAN ECOSYST, V18, P371, DOI 10.1007/s11252-014-0407-7
   Rahman MA, 2020, BUILD ENVIRON, V170, DOI 10.1016/j.buildenv.2019.106606
   Raymond WW, 2022, ECOLOGY, V103, DOI 10.1002/ecy.3798
   Reich PB, 1998, FUNCT ECOL, V12, P948, DOI 10.1046/j.1365-2435.1998.00274.x
   Revich B.A., 2012, Stud Russ Econ Dev, V23, P195, DOI [10.1134/S1075700712020116, DOI 10.1134/S1075700712020116]
   Rowley F.B., 1932, ASHRAE T, V38, P33
   Russo S, 2014, J GEOPHYS RES-ATMOS, V119, P12500, DOI 10.1002/2014JD022098
   Sengupta M., 2015, NRELCP5D0064981
   Silva HR, 2009, J APPL METEOROL CLIM, V48, P657, DOI 10.1175/2008JAMC1962.1
   Simon H, 2018, LANDSCAPE URBAN PLAN, V174, P33, DOI 10.1016/j.landurbplan.2018.03.003
   SMITH WK, 1980, PLANT PHYSIOL, V65, P132, DOI 10.1104/pp.65.1.132
   Song JY, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/11/114018
   Spronken-Smith RA, 1998, INT J REMOTE SENS, V19, P2085, DOI 10.1080/014311698214884
   Takakura T, 2000, ENERG BUILDINGS, V31, P1, DOI 10.1016/S0378-7788(98)00063-2
   Theodosiou TG, 2003, ENERG BUILDINGS, V35, P909, DOI 10.1016/S0378-7788(03)00023-9
   Thomas SC, 2000, CAN J FOREST RES, V30, P1922, DOI 10.1139/cjfr-30-12-1922
   Vancouver Park Board, 2018, URB FOR STRAT 2018 U, P1
   Wang CH, 2019, REMOTE SENS ENVIRON, V227, P28, DOI 10.1016/j.rse.2019.03.024
   Wang CH, 2018, EARTHS FUTURE, V6, P1066, DOI 10.1029/2018EF000891
   Watts N, 2015, LANCET, V386, P1861, DOI 10.1016/S0140-6736(15)60854-6
   World Meteorological Organization, 2008, WMO-no. 8, DOI 10.1007/s00704-014-1218-8
   Yang JC, 2015, RENEW SUST ENERG REV, V47, P830, DOI 10.1016/j.rser.2015.03.092
   Zhu XG, 2010, ANNU REV PLANT BIOL, V61, P235, DOI 10.1146/annurev-arplant-042809-112206
NR 76
TC 5
Z9 5
U1 4
U2 26
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4433
J9 ATMOSPHERE-BASEL
JI Atmosphere
PD MAR
PY 2023
VL 14
IS 3
AR 552
DI 10.3390/atmos14030552
PG 17
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA F5OP5
UT WOS:000982841600001
OA gold
DA 2025-01-10
ER

PT J
AU Roca-Barceló, A
   Fecht, D
   Pirani, M
   Piel, FB
   Nardocci, AC
   Vineis, P
AF Roca-Barcelo, Aina
   Fecht, Daniela
   Pirani, Monica
   Piel, Frederic B.
   Nardocci, Adelaide C.
   Vineis, Paolo
TI Trends in Temperature-associated Mortality in Sao Paulo (Brazil) between
   2000 and 2018: an Example of Disparities in Adaptation to Cold and Heat
SO JOURNAL OF URBAN HEALTH-BULLETIN OF THE NEW YORK ACADEMY OF MEDICINE
LA English
DT Article
DE Urban health; Health inequalities; Climate change; Temperature;
   Mortality
ID CITY; SUSCEPTIBILITY; VULNERABILITY; IMPACT
AB Exposure to non-optimal temperatures remains the single most deathful direct climate change impact to health. The risk varies based on the adaptation capacity of the exposed population which can be driven by climatic and/or non-climatic factors subject to fluctuations over time. We investigated temporal changes in the exposure-response relationship between daily mean temperature and mortality by cause of death, sex, age, and ethnicity in the megacity of Sao Paulo, Brazil (2000-2018). We fitted a quasi-Poisson regression model with time-varying distributed-lag non-linear model (tv-DLNM) to obtain annual estimates. We used two indicators of adaptation: trends in the annual minimum mortality temperature (MMT), i.e., temperature at which the mortality rate is the lowest, and in the cumulative relative risk (cRR) associated with extreme cold and heat. Finally, we evaluated their association with annual mean temperature and annual extreme cold and heat, respectively to assess the role of climatic and non-climatic drivers. In total, we investigated 4,471,000 deaths from non-external causes. We found significant temporal trends for both the MMT and cRR indicators. The former was decoupled from changes in AMT, whereas the latter showed some degree of alignment with extreme heat and cold, suggesting the role of both climatic and non-climatic adaptation drivers. Finally, changes in MMT and cRR varied substantially by sex, age, and ethnicity, exposing disparities in the adaptation capacity of these population groups. Our findings support the need for group-specific interventions and regular monitoring of the health risk to non-optimal temperatures to inform urban public health policies.
C1 [Roca-Barcelo, Aina; Fecht, Daniela; Pirani, Monica; Piel, Frederic B.; Vineis, Paolo] Imperial Coll London, MRC Ctr Environm & Hlth, Sch Publ Hlth, Dept Epidemiol & Biostat, Norfolk Pl, London W2 1PG, England.
   [Fecht, Daniela] Imperial Coll London, Sch Publ Hlth, Natl Inst Hlth Res Hlth, Dept Epidemiol & Biostat,Protect Res Unit Chem &, Norfolk Pl, London W2 1PG, England.
   [Piel, Frederic B.] Imperial Coll London, Sch Publ Hlth, Natl Inst Hlth Res Hlth, Dept Epidemiol & Biostat,Protect Res Unit Environ, Norfolk Pl, London W2 1PG, England.
   [Nardocci, Adelaide C.] Univ Sao Paulo, Sch Publ Hlth, Dept Environm Hlth, Sao Paulo, Brazil.
C3 Imperial College London; Imperial College London; Imperial College
   London; Universidade de Sao Paulo
RP Roca-Barceló, A (corresponding author), Imperial Coll London, MRC Ctr Environm & Hlth, Sch Publ Hlth, Dept Epidemiol & Biostat, Norfolk Pl, London W2 1PG, England.
EM a.roca-barcelo@imperial.ac.uk
RI , Daniela/HRD-8206-2023; Nardocci, Adelaide/H-5003-2012
OI Nardocci, Adelaide Cassia/0000-0002-0961-4725; Roca Barcelo,
   Aina/0000-0002-3681-6517
FU Imperial College London PhD President Scholarship; MRC Centre for
   Environment and Health - Medical Research Council [MRC/S019669/1];
   National Institute for Health Research (NIHR) Health Protection Research
   Unit in Environmental Exposures and Health; MRC [MR/S019669/1] Funding
   Source: UKRI
FX The authors are grateful to Professors Majid Ezzati and Antonio
   Gasparrini for their input on an earlier version of this work. This
   study was supported by the Imperial College London PhD President
   Scholarship awarded to Aina Roca-Barcelo. This work was also partly
   supported by the MRC Centre for Environment and Health, which is funded
   by the Medical Research Council (MRC/S019669/1, 2019-2024) and by the
   National Institute for Health Research (NIHR) Health Protection Research
   Unit in Environmental Exposures and Health, a partnership between Public
   Health England (PHE) and Imperial College. Infrastructure support for
   the Department of Epidemiology and Biostatistics was provided by the
   National Institute for Health Research (NIHR) Imperial Biomedical
   Research Council (BRC). The funding sources had no role in the design of
   this study nor its execution, analyses, interpretation of the data, or
   decision to submit the results.
CR Achebak H, 2019, LANCET PLANET HEALTH, V3, pE297, DOI 10.1016/S2542-5196(19)30090-7
   Achebak H, 2018, PLOS MED, V15, DOI 10.1371/journal.pmed.1002617
   Akaike H, 1998, Sel. Pap. Hirotugu Akaike, P199, DOI [10.1007/978-1-4612-1694-015, DOI 10.1007/978-1-4612-1694-015]
   Arbuthnott K, 2016, ENVIRON HEALTH-GLOB, V15, DOI 10.1186/s12940-016-0102-7
   Åström DO, 2018, INT J BIOMETEOROL, V62, P1777, DOI 10.1007/s00484-018-1556-9
   Aring;strom DÖ, 2016, ENVIRON HEALTH PERSP, V124, P740, DOI 10.1289/ehp.1509692
   Barreca A, 2016, J POLIT ECON, V124, P105, DOI 10.1086/684582
   Barrett, 2015, SCI SEL, V123, P184, DOI [10.1093/aje/kwj147.A, DOI 10.1093/AJE/KWJ147.A]
   Beck HE, 2018, SCI DATA, V5, DOI 10.1038/sdata.2018.214
   Bell ML, 2008, INT J EPIDEMIOL, V37, P796, DOI 10.1093/ije/dyn094
   Chung Yeonseung, 2018, Environ Health Perspect, V126, P057002, DOI [10.1289/ehp2546, 10.1289/EHP2546]
   de Moraes SL, 2022, INT J HYG ENVIR HEAL, V239, DOI 10.1016/j.ijheh.2021.113861
   de Schrijver E, 2022, ENVIRON HEALTH PERSP, V130, DOI 10.1289/EHP9835
   de' Donato FK, 2015, INT J ENV RES PUB HE, V12, P15567, DOI 10.3390/ijerph121215006
   Ellena M, 2022, ENVIRON RES, V214, DOI 10.1016/j.envres.2022.114082
   Folkerts MA, 2020, FRONT PHYSIOL, V11, DOI 10.3389/fphys.2020.00225
   Follos F, 2020, SCI TOTAL ENVIRON, V747, DOI 10.1016/j.scitotenv.2020.141259
   Gasparrini A, 2010, STAT MED, V29, P2224, DOI 10.1002/sim.3940
   Gasparrini A, 2015, LANCET, V386, P369, DOI 10.1016/S0140-6736(14)62114-0
   Gasparrini A, 2016, AM J EPIDEMIOL, V183, P1027, DOI 10.1093/aje/kwv260
   Gasparrini A, 2015, ENVIRON HEALTH PERSP, V123, P1200, DOI 10.1289/ehp.1409070
   Gasparrini A, 2011, J STAT SOFTW, V43, P1, DOI 10.18637/jss.v043.i08
   Gouveia N, 2003, INT J EPIDEMIOL, V32, P390, DOI 10.1093/ije/dyg077
   Governo do Estado do Sao Paulo, 2016, DIARIO OFICIAL CIDAD, V61, P3
   Heo S, 2016, BMJ OPEN, V6, DOI 10.1136/bmjopen-2016-011786
   Hone T, 2019, LANCET GLOB HEALTH, V7, pE1575, DOI 10.1016/S2214-109X(19)30409-7
   IBGE, IBGE PORT IBGE
   Kamimura, 2019, P 5 INT C OPT APPL K, P1, DOI [10.13140/RG.2.2.16251.77601, DOI 10.13140/RG.2.2.16251.77601]
   Kephart JL, 2022, NAT MED, V28, P1700, DOI 10.1038/s41591-022-01872-6
   Kinney PL, 2018, ATMOSPHERE-BASEL, V9, DOI 10.3390/atmos9100409
   Lay CR, 2021, LANCET PLANET HEALTH, V5, pE338, DOI 10.1016/S2542-5196(21)00058-9
   Lee W, 2018, ENVIRON INT, V119, P379, DOI 10.1016/j.envint.2018.06.020
   Liu JW, 2020, SUSTAIN CITIES SOC, V57, DOI 10.1016/j.scs.2020.102131
   Lu P, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abab33
   Malta DC, 2020, POPUL HEALTH METR, V18, DOI 10.1186/s12963-020-00215-2
   Massuda A, 2018, BMJ GLOB HEALTH, V3, DOI 10.1136/bmjgh-2018-000829
   Mora C, 2017, NAT CLIM CHANGE, V7, P501, DOI [10.1038/nclimate3322, 10.1038/NCLIMATE3322]
   Sheridan SC, 2021, WEATHER CLIM SOC, V13, P95, DOI 10.1175/WCAS-D-20-0083.1
   Son JY, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab1cdb
   Son JY, 2016, INT J BIOMETEOROL, V60, P113, DOI 10.1007/s00484-015-1009-7
   Spangler KR, 2021, ENVIRON EPIDEMIOL, V5, DOI 10.1097/EE9.0000000000000136
   Sun SZ, 2019, SCI TOTAL ENVIRON, V666, P197, DOI 10.1016/j.scitotenv.2019.02.229
   Tobías A, 2021, ENVIRON EPIDEMIOL, V5, DOI 10.1097/EE9.0000000000000169
   Tobías A, 2017, EPIDEMIOLOGY, V28, P72, DOI 10.1097/EDE.0000000000000567
   Todd N, 2015, ENVIRON HEALTH PERSP, V123, P659, DOI 10.1289/ehp.1307771
   Vicedo-Cabrera AM, 2018, ENVIRON INT, V111, P239, DOI 10.1016/j.envint.2017.11.006
   Weitensfelder L, 2020, INT J ENV RES PUB HE, V17, DOI 10.3390/ijerph17010097
   World Health Organisation & United Nations, 2015, CLIM HLTH COUNTR PRO
   World Health Organization(WHO) & World Meteorological Organization (WMO), 2015, HEATW HLTH GUID WARN
   Yin Q, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-12663-y
   Yu WW, 2012, INT J BIOMETEOROL, V56, P569, DOI 10.1007/s00484-011-0497-3
   Zhao Q, 2021, LANCET PLANET HEALTH, V5, pE415, DOI 10.1016/S2542-5196(21)00081-4
NR 52
TC 5
Z9 5
U1 2
U2 9
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 1099-3460
EI 1468-2869
J9 J URBAN HEALTH
JI J. Urban Health
PD DEC
PY 2022
VL 99
IS 6
BP 1012
EP 1026
DI 10.1007/s11524-022-00695-7
EA NOV 2022
PG 15
WC Public, Environmental & Occupational Health; Medicine, General &
   Internal
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Public, Environmental & Occupational Health; General & Internal Medicine
GA 6T3PY
UT WOS:000881646300001
PM 36357626
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Varcoe-Cocks, M
   Lukomski, M
   Lelyveld, M
   Beltran, VL
   Breare, C
   Winter, C
AF Varcoe-Cocks, Michael
   Lukomski, Michal
   Lelyveld, MaryJo
   Beltran, Vincent Laudato
   Breare, Caitlin
   Winter, Cecilia
TI Developing an Adaptive Climate Control Strategy and Programme Monitoring
   Micro-change in Wooden Heritage Objects
SO STUDIES IN CONSERVATION
LA English
DT Article
DE Bizot Green Protocol; environmental guidelines; environmental
   monitoring; acoustic emission monitoring
ID ACOUSTIC-EMISSION; ENVIRONMENTAL-CONDITIONS; COLLECTIONS; DAMAGE
AB Recent environmental guidance in the cultural heritage field reflects the increasingly important objectives of sustainability and reduced carbon footprint. New and revised guidance from organisations such as the Bizot Group, IIC/ICOM-CC, AICCM, and ASHRAE share common principles, including consideration of passive low-energy environmental control methods, adoption of realistic target conditions given the building envelope and exterior climate, and support for broader environmental parameters for many classes of objects. Motivated by an interest in energy savings and security, as well as broad organisational involvement and buy-in for implementing environmental change, the National Gallery of Victoria (NGV) in Melbourne, Victoria, is adopting the Bizot Green Protocol (BGP) for its collection and for outgoing loans. Initial NGV trials of a transitionary 'soft Bizot' setting - temperature between 20 degrees C and 23 degrees C with 24-hour fluctuations of no more than +/- 1.5 degrees C and relative humidity between 46% and 56% with 24-hour fluctuations of no more than +/- 4% - demonstrated reduced energy use. The NGV and the Getty Conservation Institute are collaborating to examine object response during this environmental transition. In addition to visual monitoring of several works in the collection using macrophotography, acoustic emission (AE) monitoring will be carried out on a Flemish retable consisting of carved and polychromed wood and oil paint. AE monitoring is a highly sensitive technique that measures energy, in the form of transient elastic waves, released by and propagated through a material such as wood that has undergone brittle cracking. This has the potential benefit of detecting environmentally induced micro-changes in an object before damage is visible to the viewer.
C1 [Varcoe-Cocks, Michael; Lelyveld, MaryJo; Breare, Caitlin] Natl Gallery Victoria, Conservat Dept, Melbourne, Vic, Australia.
   [Lukomski, Michal; Beltran, Vincent Laudato; Winter, Cecilia] Getty Conservat Inst, Managing Collect Environm Program, Los Angeles, CA USA.
C3 Melbourne Genomics Health Alliance
RP Lelyveld, M (corresponding author), Natl Gallery Victoria, 180 St Kilda Rd, Melbourne, Vic 3004, Australia.
EM maryjo.lelyveld@ngv.vic.gov.au
RI Breare, Caitlin/JXX-6769-2024
OI Lukomski, Michal/0000-0001-7942-9026
CR AICCM, 2018, ENV GUIDELINES
   ANKERSMIT B., 2017, Managing Indoor Climate Risks in Museums
   [Anonymous], 2018, GREENER GOVT BUILDIN
   Ashley-Smith J., 1994, Studies in Conservation, V39, P28, DOI [https://doi.org/10.1179/sic.1994.39.Supplement-2.28, DOI 10.1179/SIC.1994.39.SUPPLEMENT-2.28]
   ASHRAE, 2019, Museums, Galleries, Archives and Libraries, ASHRAE Handbook-HVAC Applications
   ASHRAE, 2020, ANSI/ASHRAE Standard 55-2020 Thermal Environmental Conditions for Human Occupancy
   Atkinson JK, 2014, STUD CONSERV, V59, P205, DOI 10.1179/2047058414Y.0000000141
   BOERSMA F., 2014, Conservation Perspectives: The GCI Newsletter, V29, P4
   Bratasz L, 2013, STUD CONSERV, V58, P65, DOI 10.1179/2047058412Y.0000000061
   German Federal Government, 2021, CLIM CHANG ACT 2021
   Henderson J, 2018, J INST CONSERV, V41, P32, DOI 10.1080/19455224.2017.1422777
   Henry MC, 2018, STUD CONSERV, V63, P121, DOI 10.1080/00393630.2018.1473101
   Jacobs LynnF., 1998, EARLY NETHERLANDISH
   Jakiela S, 2007, STUD CONSERV, V52, P101, DOI 10.1179/sic.2007.52.2.101
   Laudato Beltran V, 2020, ACOUSTIC EMISSION MO
   Lukomski M, 2017, INSIGHT, V59, P256, DOI 10.1784/insi.2017.59.5.256
   Lukomski M, 2018, STUD CONSERV, V63, P181, DOI 10.1080/00393630.2018.1471892
   Mecklenburg MF., 1998, PAINTED WOOD HIST CO, P464
   Michalski S., 2007, IDEAL CLIMATE RISK M
   Michalski S., 2011, REFLECTIONS CONSERVA, P911
   NMDC, 2015, ENV SUSTAINABILITY R
   Staniforth S, 2014, STUD CONSERV, V59, P213, DOI 10.1179/2047058414Y.0000000142
   Strojecki M, 2014, STUD CONSERV, V59, P225, DOI 10.1179/2047058413Y.0000000096
NR 23
TC 1
Z9 1
U1 0
U2 6
PU ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
SN 0039-3630
EI 2047-0584
J9 STUD CONSERV
JI Stud. Conserv.
PD AUG 10
PY 2022
VL 67
SU 1
SI SI
BP 283
EP 292
DI 10.1080/00393630.2022.2076779
EA MAY 2022
PG 10
WC Archaeology; Art; Chemistry, Applied; Chemistry, Analytical;
   Spectroscopy
WE Science Citation Index Expanded (SCI-EXPANDED); Arts &amp; Humanities Citation Index (A&amp;HCI)
SC Archaeology; Art; Chemistry; Spectroscopy
GA 4E2ML
UT WOS:000807645200001
OA hybrid
DA 2025-01-10
ER

PT J
AU Miro, ME
   Groves, D
   Tincher, B
   Syme, J
   Tanverakul, S
   Catt, D
AF Miro, Michelle E.
   Groves, David
   Tincher, Bob
   Syme, James
   Tanverakul, Stephanie
   Catt, David
TI Adaptive water management in the face of uncertainty: Integrating
   machine learning, groundwater modeling and robust decision making
SO CLIMATE RISK MANAGEMENT
LA English
DT Article
DE Water resources management; Climate change; Drought; Groundwater;
   Machine learning; Random forest; Robust decision making; Climate
   adaptation; Southern California
ID CALIFORNIA WATER; RANDOM FOREST
AB This study examines climate change and water resources management challenges facing water suppliers in drought-prone regions and is particularly relevant to the American West, where agencies balance the management of imported and local water resources across multiple future uncertainties. We apply Robust Decision Making (RDM) to water management planning challenges facing the San Bernardino Valley Municipal Water District (Valley District) and investigate the performance of a machine learning-based representation of two local groundwater basins. To do so, we assess three machine learning methods-Random Forest (RF), Support Vector Machines (SVM) and Artificial Neural Networks (ANN)-and their ability to simulate the output of a high-resolution MODFLOW model. We find that RF produces the most accurate results, and thus we incorporate the RF version of the MODFLOW model into the study's RDM approach. This constitutes an advancement to the field of decisionmaking under deep uncertainty (DMDU) through a novel application of machine learning that shortens modeling run times and allows for a greater exploration of the uncertainty space, including a broad range of future climate changes and drought conditions. This paper also constitutes an advancement to the field of empirical groundwater modeling by showing that RF is capable of simulating average basin groundwater level changes. Our results also suggest that demand management can significantly reduce vulnerabilities to drought and other climate changes, and we provide recommendations on additional adaptive management options and key signposts to track for the Valley District.
C1 [Miro, Michelle E.; Groves, David; Syme, James; Tanverakul, Stephanie; Catt, David] RAND Corp, Santa Monica, CA 90406 USA.
   [Tincher, Bob] San Bernardino Valley Municipal Water Dist, San Bernardino, CA USA.
C3 RAND Corporation
RP Miro, ME (corresponding author), RAND Corp, Santa Monica, CA 90406 USA.
EM Michelle_Miro@rand.org
FU San Bernardino Valley Municipal Water District
FX This research was funded by the San Bernardino Valley Municipal Water
   District.
CR Almuhaylan MR, 2020, WATER-SUI, V12, DOI 10.3390/w12082297
   Amaranto A, 2018, J HYDROINFORM, V20, P1227, DOI 10.2166/hydro.2018.002
   Anandhi A, 2011, WATER RESOUR RES, V47, DOI 10.1029/2010WR009104
   [Anonymous], 2021, GEOSP INN FAC CAL AD
   [Anonymous], 2001, Machine Learning
   Basheer IA, 2000, J MICROBIOL METH, V43, P3, DOI 10.1016/S0167-7012(00)00201-3
   Beh EHY, 2017, ENVIRON MODELL SOFTW, V93, P92, DOI 10.1016/j.envsoft.2017.03.013
   Biau G, 2016, TEST-SPAIN, V25, P197, DOI 10.1007/s11749-016-0481-7
   Breiman L., 2018, RANDOMFOREST
   California Department of Water Resources, 2021, CALSIM 2
   California Department of Water Resources, 2021, HIST WAT DEV STAT WA
   California Department of Water Resources, 2018, RES GUID DWR PROV CL
   California Department of Water Resources, 2019, CAL WAT PLAN UPD 201
   Chen C, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-60698-9
   Feldman D, 2016, WESTS WATER MULTIPLE, P452
   Fischbach J., 2020, TIERNEY MANAGING HEA
   Fischbach J., 2015, HOSS MANAGING WATER
   Fritsch S., 2019, Neuralnet
   Geosciences Support Services Inc., 2020, UPP SANT AN RIV INT
   Giudici F, 2020, ENVIRON MODELL SOFTW, V127, DOI 10.1016/j.envsoft.2020.104681
   Golkarian A, 2018, ENVIRON MONIT ASSESS, V190, DOI 10.1007/s10661-018-6507-8
   Groves D., 2013, KEEFE ADAPTING CHANG
   Groves D., METROPOLITAN WATER D
   Groves D., 2008, Preparing for an Uncertain Future Climate in the Inland Empire: Identifying Robust Water Management Strategies
   Groves D.G., 2019, POPPER DECISION MAKI, V135, P163, DOI [10.1007/978-3-030-05252-2_7, DOI 10.1007/978-3-030-05252-2_7]
   Groves D. G., 2019, Preparing for Future Droughts in Lima, Peru
   Groves D.G., 2008, Water Resources IMPACT, V10, P14
   Groves DG, 2015, J WATER RES PLAN MAN, V141, DOI 10.1061/(ASCE)WR.1943-5452.0000471
   Hanak E, 2012, CLIMATIC CHANGE, V111, P17, DOI 10.1007/s10584-011-0241-3
   Herman JD, 2016, J WATER RES PLAN MAN, V142, DOI 10.1061/(ASCE)WR.1943-5452.0000701
   Herman JD, 2014, WATER RESOUR RES, V50, P7692, DOI 10.1002/2014WR015338
   ICF, 2020, UPP SANT AN RIV SAR
   KAHRL WL, 1976, CALIF HIST QUART, V55, P2, DOI 10.2307/25157605
   Kasprzyk JR, 2009, WATER RESOUR RES, V45, DOI 10.1029/2009WR008121
   Knoll L, 2019, SCI TOTAL ENVIRON, V668, P1317, DOI 10.1016/j.scitotenv.2019.03.045
   Kwakkel JH, 2017, ENVIRON MODELL SOFTW, V96, P239, DOI 10.1016/j.envsoft.2017.06.054
   Kwakkel JH, 2016, J WATER RES PLAN MAN, V142, DOI 10.1061/(ASCE)WR.1943-5452.0000626
   Lempert R., 2013, World Bank Policy Research Working Paper, DOI DOI 10.1596/1813-9450-6465
   Lempert RJ, 2006, MANAGE SCI, V52, P514, DOI 10.1287/mnsc.1050.0472
   Lempert RJ, 2010, TECHNOL FORECAST SOC, V77, P960, DOI 10.1016/j.techfore.2010.04.007
   Malekzadeh M, 2019, GROUNDWATER SUST DEV, V9, DOI 10.1016/j.gsd.2019.100279
   Miro M., 2018, MILLER ESTIMATING FU
   Miro ME, 2018, REMOTE SENS-BASEL, V10, DOI 10.3390/rs10010143
   Molina-Perez E, 2020, FRONT ROBOT AI, V7, DOI 10.3389/frobt.2020.00111
   Naghibi SA, 2017, WATER RESOUR MANAG, V31, P2761, DOI 10.1007/s11269-017-1660-3
   Noble WS, 2006, NAT BIOTECHNOL, V24, P1565, DOI 10.1038/nbt1206-1565
   Pierce D., CAYAN CLIMATE DROUGH
   Pincetl S, 2019, LANDSCAPE URBAN PLAN, V185, P210, DOI 10.1016/j.landurbplan.2019.01.011
   Rahmati O, 2016, CATENA, V137, P360, DOI 10.1016/j.catena.2015.10.010
   Sahoo S, 2017, WATER RESOUR RES, V53, P3878, DOI 10.1002/2016WR019933
   The Metropolitan Water District of Southern California, 2017, MOD SYST CAL WATERFI
   Tyralis H, 2019, WATER-SUI, V11, DOI 10.3390/w11050910
   Wang XH, 2018, APPL WATER SCI, V8, DOI 10.1007/s13201-018-0742-6
   Water Systems Consulting Inc., 2016, 2015 SAN BERN VALL R
   Wicks Lauren, 2020, USABLE GROUNDWATER S
NR 55
TC 27
Z9 28
U1 7
U2 47
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 100383
DI 10.1016/j.crm.2021.100383
EA DEC 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 XO8HO
UT WOS:000730419800001
OA gold
DA 2025-01-10
ER

PT J
AU Staudinger, MD
   Goyert, H
   Suca, JJ
   Coleman, K
   Welch, L
   Llopiz, JK
   Wiley, D
   Altman, I
   Applegate, A
   Auster, P
   Baumann, H
   Beaty, J
   Boelke, D
   Kaufman, L
   Loring, P
   Moxley, J
   Paton, S
   Powers, K
   Richardson, D
   Robbins, J
   Runge, J
   Smith, B
   Spiegel, C
   Steinmetz, H
AF Staudinger, Michelle D.
   Goyert, Holly
   Suca, Justin J.
   Coleman, Kaycee
   Welch, Linda
   Llopiz, Joel K.
   Wiley, David
   Altman, Irit
   Applegate, Andew
   Auster, Peter
   Baumann, Hannes
   Beaty, Julia
   Boelke, Deirdre
   Kaufman, Les
   Loring, Pam
   Moxley, Jerry
   Paton, Suzanne
   Powers, Kevin
   Richardson, David
   Robbins, Jooke
   Runge, Jeffrey
   Smith, Brian
   Spiegel, Caleb
   Steinmetz, Halley
TI The role of sand lances (<i>Ammodytes</i> sp.) in the Northwest Atlantic
   Ecosystem: A synthesis of current knowledge with implications for
   conservation and management
SO FISH AND FISHERIES
LA English
DT Article
DE Ammodytes; ecosystem-based management; forage fish; life history; sand
   lance; trophic ecology
ID WHALES BALAENOPTERA-ACUTOROSTRATA; TUNA THUNNUS-THYNNUS; COD
   GADUS-MORHUA; SHEARWATERS PUFFINUS-GRAVIS; INNER CONTINENTAL-SHELF;
   OFFSHORE WIND FARM; FORAGE FISH; GEORGES-BANK; MINKE WHALES; SOUTHERN
   GULF
AB The American sand lance (Ammodytes americanus, Ammodytidae) and the Northern sand lance (A. dubius, Ammodytidae) are small forage fishes that play an important functional role in the Northwest Atlantic Ocean (NWA). The NWA is a highly dynamic ecosystem currently facing increased risks from climate change, fishing and energy development. We need a better understanding of the biology, population dynamics and ecosystem role of Ammodytes to inform relevant management, climate adaptation and conservation efforts. To meet this need, we synthesized available data on the (a) life history, behaviour and distribution; (b) trophic ecology; (c) threats and vulnerabilities; and (d) ecosystem services role of Ammodytes in the NWA. Overall, 72 regional predators including 45 species of fishes, two squids, 16 seabirds and nine marine mammals were found to consume Ammodytes. Priority research needs identified during this effort include basic information on the patterns and drivers in abundance and distribution of Ammodytes, improved assessments of reproductive biology schedules and investigations of regional sensitivity and resilience to climate change, fishing and habitat disturbance. Food web studies are also needed to evaluate trophic linkages and to assess the consequences of inconsistent zooplankton prey and predator fields on energy flow within the NWA ecosystem. Synthesis results represent the first comprehensive assessment of Ammodytes in the NWA and are intended to inform new research and support regional ecosystem-based management approaches.
C1 [Staudinger, Michelle D.] US Geol Survey, US Dept Interior, Northeast Climate Adaptat Sci Ctr, Amherst, MA 01003 USA.
   [Staudinger, Michelle D.; Goyert, Holly; Steinmetz, Halley] Univ Massachusetts, Dept Environm Conservat, Amherst, MA 01003 USA.
   [Suca, Justin J.; Llopiz, Joel K.] Woods Hole Oceanog Inst, Dept Biol, Woods Hole, MA 02543 USA.
   [Suca, Justin J.] MIT WHOI Joint Program Oceanog, Woods Hole, MA USA.
   [Coleman, Kaycee; Spiegel, Caleb] US Fish & Wildlife Serv, Hadley, MA USA.
   [Welch, Linda] US Fish & Wildlife Serv, Maine Coastal Islands NWR, Rockland, ME USA.
   [Wiley, David; Powers, Kevin] NOAA, NOS, Stellwagen Bank Natl Marine Sanctuary, Scituate, MA USA.
   [Altman, Irit; Kaufman, Les] Boston Univ, Dept Biol, 5 Cummington St, Boston, MA 02215 USA.
   [Applegate, Andew; Boelke, Deirdre] New England Fishery Management Council, Newburyport, MA USA.
   [Auster, Peter] Myst Aquarium, Mystic, CT USA.
   [Auster, Peter; Baumann, Hannes] Univ Connecticut, Dept Marine Sci, Groton, CT 06340 USA.
   [Beaty, Julia] Mid Atlantic Fishery Management Council, Dover, DE USA.
   [Loring, Pam; Paton, Suzanne] US Fish & Wildlife Serv, Charlestown, RI USA.
   [Moxley, Jerry] Duke Univ, Marine Lab, Beaufort, NC 28516 USA.
   [Moxley, Jerry] Monterey Bay Aquarium, Monterey, CA USA.
   [Richardson, David] NOAA, Oceans & Climate Branch, NEFSC, NMFS, Narragansett, RI USA.
   [Robbins, Jooke] Ctr Coastal Studies, Provincetown, MA USA.
   [Runge, Jeffrey] Univ Maine, Sch Marine Sci, Portland, ME USA.
   [Runge, Jeffrey] Gulf Maine Res Inst, Portland, ME USA.
   [Smith, Brian] NOAA, Woods Hole, MA USA.
C3 United States Department of the Interior; United States Geological
   Survey; University of Massachusetts System; University of Massachusetts
   Amherst; Woods Hole Oceanographic Institution; Massachusetts Institute
   of Technology (MIT); United States Department of the Interior; US Fish &
   Wildlife Service; United States Department of the Interior; US Fish &
   Wildlife Service; National Oceanic Atmospheric Admin (NOAA) - USA;
   National Ocean Service, NOAA; Boston University; University of
   Connecticut; United States Department of the Interior; US Fish &
   Wildlife Service; Duke University; Monterey Bay Aquarium Research
   Institute; National Oceanic Atmospheric Admin (NOAA) - USA; University
   of Maine System; University of Maine Orono; Gulf of Maine Research
   Institute; National Oceanic Atmospheric Admin (NOAA) - USA
RP Staudinger, MD (corresponding author), US Geol Survey, US Dept Interior, Northeast Climate Adaptat Sci Ctr, Amherst, MA 01003 USA.
EM mstaudinger@usgs.gov
RI Auster, Peter/ABI-3568-2020; Smith, Brian/HOC-7713-2023; Staudinger,
   Michelle/KUL-3470-2024
OI Smith, Brian/0000-0002-7792-520X; Llopiz, Joel/0000-0002-7584-7471;
   Robbins, Jooke/0000-0002-6382-722X; Staudinger,
   Michelle/0000-0002-4535-2005
FU Mudge Foundation; NSF; DOI Northeast Climate Adaptation Science Center
   [G16AC00237]; National Science Foundation [OCE-1325451, OCE-1459087];
   National Marine Sanctuary Foundation [18-08-B-196]; Regional Sea Grant
   [RNE16-CTHCE-l]; U.S. Fish and Wildlife Service; NOAA Stellwagen Bank
   National Marine Sanctuary;  [NA14OAR4320158]
FX Mudge Foundation; NSF Graduate Research Fellowship; DOI Northeast
   Climate Adaptation Science Center, Grant/Award Number: G16AC00237;
   National Science Foundation, Grant/Award Number: OCE-1325451,
   OCE-1459087 and OCE-1459087; National Marine Sanctuary Foundation,
   Grant/Award Number: 18-08-B-196; Regional Sea Grant, Grant/Award Number:
   RNE16-CTHCE-l; CINAR Fellow, Grant/Award Number: NA14OAR4320158; NOAA
   Stellwagen Bank National Marine Sanctuary; U.S. Fish and Wildlife
   Service
CR Alder J, 2008, ANNU REV ENV RESOUR, V33, P153, DOI 10.1146/annurev.environ.33.020807.143204
   Alexander MA, 2018, ELEMENTA-SCI ANTHROP, V6, DOI 10.1525/elementa.191
   Althouse M. A., 2016, THESIS
   Altman I., 2014, SEA IDEAOBSERVATIO, V16, P245
   [Anonymous], 2013, CLIM VULNERABILITY
   [Anonymous], 2014, CLIMATE CHANGE IMPAC
   [Anonymous], 1967, Bull Naikai Reg Fish Res Lab
   [Anonymous], ATLANTIC ALCIDAE
   [Anonymous], 2007, THESIS
   [Anonymous], 2013, NAT OC POL IMPL PLAN
   [Anonymous], UND WORLD SAND LANC
   [Anonymous], 2001, Oceanography, V14, P76, DOI [10.5670/oceanog.2001.25, DOI 10.5670/OCEANOG.2001.25]
   [Anonymous], 2006, ECOSYSTEM RELATIONSH
   [Anonymous], NMFSNE216 NOAA
   [Anonymous], 2009, THESIS
   [Anonymous], SCI SERIES TECHNICAL
   Applegate A., 2019, DRAFT EXAMPLE FISHER
   Arnott SA, 2002, MAR ECOL PROG SER, V235, P223, DOI 10.3354/meps235223
   Arnott SA, 2002, MAR ECOL PROG SER, V238, P199, DOI 10.3354/meps238199
   Auster P. J., 1986, 821166 US FISH WILDL, P82
   Auster PJ, 1998, AM FISH S S, V22, P150
   Baillie SM, 2003, CAN J ZOOL, V81, P1598, DOI 10.1139/Z03-145
   Baumann H, 2018, BIOL LETTERS, V14, DOI 10.1098/rsbl.2018.0408
   Baumann H, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0067596
   Baumann H, 2011, P ROY SOC B-BIOL SCI, V278, P2265, DOI 10.1098/rspb.2010.2479
   Beck CA, 2007, J ANIM ECOL, V76, P490, DOI 10.1111/j.1365-2656.2007.01215.x
   Beever EA, 2016, CONSERV LETT, V9, P131, DOI 10.1111/conl.12190
   BIGELOW HENRY B., 1926, U S DEPT COMMERCE BULL BUR FISH, V40, P1
   Bopp L, 2013, BIOGEOSCIENCES, V10, P6225, DOI 10.5194/bg-10-6225-2013
   Boumans R, 2015, ECOSYST SERV, V12, P30, DOI 10.1016/j.ecoser.2015.01.004
   Bowen W. D, 2006, NAMMCO SCI PUBLICATI, V6, P123
   BOWEN WD, 1994, MAR ECOL PROG SER, V112, P1, DOI 10.3354/meps112001
   Bowen WD, 2002, MAR ECOL PROG SER, V244, P235, DOI 10.3354/meps244235
   Bowman RE, 2000, NMFSNE155 NOAA, DOI [10.5962/bhl.title.4024, DOI 10.5962/BHL.TITLE.4024]
   Branch TA, 2013, TRENDS ECOL EVOL, V28, P409, DOI 10.1016/j.tree.2013.03.003
   Breed GA, 2013, ECOL EVOL, V3, P3838, DOI 10.1002/ece3.754
   Brethes J.-C.F., 1992, Journal of Northwest Atlantic Fishery Science, V12, P41
   Breton AR, 2014, IBIS, V156, P35, DOI 10.1111/ibi.12100
   Brickman D, 2018, CONT SHELF RES, V156, P11, DOI 10.1016/j.csr.2018.01.001
   BROWN RGB, 1981, IBIS, V123, P19, DOI 10.1111/j.1474-919X.1981.tb00169.x
   BUCKLEY LJ, 1984, MAR ECOL PROG SER, V15, P91, DOI 10.3354/meps015091
   Burger A.E., 1990, Studies in Avian Biology, P71
   Burke CM, 2008, WATERBIRDS, V31, P372, DOI 10.1675/1524-4695-31.3.372
   Burthe S, 2012, MAR ECOL PROG SER, V454, P119, DOI 10.3354/meps09520
   Burthe SJ, 2014, MAR ECOL PROG SER, V507, P277, DOI 10.3354/meps10849
   Byron CJ, 2010, MAR ECOL PROG SER, V406, P239, DOI 10.3354/meps08570
   Caesar L, 2018, NATURE, V556, P191, DOI 10.1038/s41586-018-0006-5
   Calbet A, 2007, MAR BIOL, V151, P195, DOI 10.1007/s00227-006-0468-0
   Carruthers EH, 2005, J FISH BIOL, V66, P327, DOI 10.1111/j.0022-1112.2005.00594.x
   Chapdelaine G., 1996, STUDIES HIGH LATITUD, P27
   Chase BC, 2002, FISH B-NOAA, V100, P168
   Christiansen F, 2013, J EXP BIOL, V216, P427, DOI 10.1242/jeb.074518
   Churchill JH, 2011, FISH OCEANOGR, V20, P32, DOI 10.1111/j.1365-2419.2010.00563.x
   Ciannelli L, 1997, LOW WAKE FI, V97, P95
   *COSEWIC, 2013, COSEWIC ASS STAT REP
   Craddock JE, 2009, FISH B-NOAA, V107, P384
   Csirke J., 1988, FISH POPULATION DYNA
   DALLEY EL, 1987, FISH B-NOAA, V85, P631
   Danielsen NST, 2016, MAR ECOL PROG SER, V558, P97, DOI 10.3354/meps11859
   Dawe EG, 1997, CAN J FISH AQUAT SCI, V54, P200, DOI 10.1139/cjfas-54-S1-200
   Degraer S, 2016, Environmental impacts of offshore wind farms in the Belgian part of the North Sea: environmental impact monitoring reloaded
   Desprez M, 2000, ICES J MAR SCI, V57, P1428, DOI 10.1006/jmsc.2000.0926
   Deyle ER, 2013, P NATL ACAD SCI USA, V110, P6430, DOI 10.1073/pnas.1215506110
   Diamond AW, 2012, AM FISH S S, V79, P311
   Dibajnia M., 2011, INVESTIGATION DREDGI, V25
   Dickey-Collas M, 2014, ICES J MAR SCI, V71, P128, DOI 10.1093/icesjms/fst075
   Dixon HJ, 2017, FISH OCEANOGR, V26, P555, DOI 10.1111/fog.12216
   DURBIN EG, 1995, CONT SHELF RES, V15, P571, DOI 10.1016/0278-4343(94)00060-Z
   Eigaard OR, 2014, MAR ECOL PROG SER, V516, P267, DOI 10.3354/meps11064
   Erikstad KE, 2013, MAR ECOL PROG SER, V475, P267, DOI 10.3354/meps10084
   FOGARTY MJ, 1991, TRENDS ECOL EVOL, V6, P241, DOI 10.1016/0169-5347(91)90069-A
   Francis RC, 2007, FISHERIES, V32, P217, DOI 10.1577/1548-8446(2007)32[217:TCFBFS]2.0.CO;2
   Frank KT, 2013, ICES J MAR SCI, V70, P1299, DOI 10.1093/icesjms/fst111
   Frank KT, 2011, NATURE, V477, P86, DOI 10.1038/nature10285
   Frederiksen M, 2004, J APPL ECOL, V41, P1129, DOI 10.1111/j.0021-8901.2004.00966.x
   Frederiksen M, 2006, J ANIM ECOL, V75, P1259, DOI 10.1111/j.1365-2656.2006.01148.x
   Frederiksen M, 2011, MAR ECOL PROG SER, V432, P137, DOI 10.3354/meps09177
   Fricke R., 2019, Catalog of Fishes: Genera, Species
   Friedlaender AS, 2009, MAR ECOL PROG SER, V395, P91, DOI 10.3354/meps08003
   Friedland KD, 2018, GLOBAL ECOL BIOGEOGR, V27, P551, DOI 10.1111/geb.12717
   Friedland KD, 2015, CONT SHELF RES, V102, P47, DOI 10.1016/j.csr.2015.04.005
   Furness RW, 2002, ICES J MAR SCI, V59, P261, DOI 10.1006/jmsc.2001.1155
   Gamble RJ, 2009, ECOL MODEL, V220, P2570, DOI 10.1016/j.ecolmodel.2009.06.022
   Garrison LP, 2000, MAR ECOL PROG SER, V204, P243, DOI 10.3354/meps204243
   Gaston AJ, 2008, AUK, V125, P939, DOI 10.1525/auk.2008.07195
   Gelsleichter J, 1999, ENVIRON BIOL FISH, V54, P205, DOI 10.1023/A:1007527111292
   GILMAN SL, 1994, FISH B-NOAA, V92, P647
   Glaser SM, 2014, FISH FISH, V15, P616, DOI 10.1111/faf.12037
   Golet WJ, 2007, FISH B-NOAA, V105, P390
   Goyert HF, 2018, ICES J MAR SCI, V75, P1602, DOI 10.1093/icesjms/fsy020
   Goyert HF, 2015, BEHAVIOUR, V152, P861, DOI 10.1163/1568539X-00003260
   Goyert HF, 2014, OIKOS, V123, P1400, DOI 10.1111/oik.00814
   Goyert HF, 2014, MAR ECOL PROG SER, V506, P291, DOI 10.3354/meps10834
   Gray JS, 2006, INTEGR ENVIRON ASSES, V2, P196, DOI 10.1002/ieam.5630020213
   Green B, 2017, REINVENT TEACHER ED, P39
   Greene CH, 2007, SCIENCE, V315, P1084, DOI 10.1126/science.1136495
   Grieve BD, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-06524-1
   Guilbert J, 2015, GEOPHYS RES LETT, V42, P1888, DOI 10.1002/2015GL063124
   HAIN JHW, 1995, MAR MAMMAL SCI, V11, P464, DOI 10.1111/j.1748-7692.1995.tb00670.x
   Hansen BH, 2012, ECOTOX ENVIRON SAFE, V86, P38, DOI 10.1016/j.ecoenv.2012.09.009
   Hanson JM, 2002, J FISH BIOL, V60, P902, DOI 10.1006/jfbi.2002.1893
   Hare JA, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0146756
   Haug T, 2007, MAR BIOL RES, V3, P123, DOI 10.1080/17451000701358531
   Hazen EL, 2009, MAR ECOL PROG SER, V395, P75, DOI 10.3354/meps08108
   Head EJH, 1999, CAN J FISH AQUAT SCI, V56, P2463, DOI 10.1139/cjfas-56-12-2463
   Heaslip SG, 2014, CAN J ZOOL, V92, P309, DOI 10.1139/cjz-2013-0137
   Heinemann D., 1992, FORAGING ECOLO UNPUB
   Herr H., 2008, 15 ASCOBANS ADV COMM
   HISLOP JRG, 1991, J ZOOL, V224, P501, DOI 10.1111/j.1469-7998.1991.tb06039.x
   Hjermann DO, 2007, MAR ECOL PROG SER, V339, P283, DOI 10.3354/meps339283
   HOBSON ES, 1986, COPEIA, P223
   Holland GJ, 2005, MAR ECOL PROG SER, V303, P269, DOI 10.3354/meps303269
   Horne JB, 2016, MITOCHONDRIAL DNA A, V27, P4607, DOI 10.3109/19401736.2015.1101579
   Hunsicker ME, 2010, FISH FISH, V11, P421, DOI 10.1111/j.1467-2979.2010.00369.x
   Hunsicker ME, 2006, CAN J FISH AQUAT SCI, V63, P754, DOI 10.1139/f05-258
   ICES (International Council for the Exloration of the Seas), 2010, 2010ACOM57 ICES CM
   Irigoien X, 2011, MAR BIOL, V158, P1683, DOI 10.1007/s00227-011-1699-2
   Jech JM, 2016, CAN J FISH AQUAT SCI, V73, P1914, DOI 10.1139/cjfas-2016-0113
   Jech JM, 2012, AQUAT LIVING RESOUR, V25, P1, DOI 10.1051/alr/2012003
   Jedrey E.L., 2010, Bird Observer, V38, P146
   Jessopp MJ, 2013, MAR BIOL, V160, P2755, DOI 10.1007/s00227-013-2268-7
   Jessup DA, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0004550
   Ji RB, 2017, ICES J MAR SCI, V74, P1865, DOI 10.1093/icesjms/fsw253
   Ji RB, 2009, MAR ECOL PROG SER, V384, P187, DOI 10.3354/meps08032
   Jodice PGR, 2006, MAR ECOL PROG SER, V325, P267, DOI 10.3354/meps325267
   Johnson CL, 2011, PLOS ONE, V6, DOI [10.1371/journal.pone.0016491, 10.1371/journal.pone.0019210]
   Kane J, 2007, ICES J MAR SCI, V64, P909, DOI 10.1093/icesjms/fsm066
   Kelly JT, 2013, J FISH BIOL, V82, P959, DOI 10.1111/jfb.12030
   Kenney Robert D., 1996, P169
   Kirkham I. R., 1986, THESIS
   Klein ES, 2016, MAR ECOL PROG SER, V557, P237, DOI 10.3354/meps11886
   Koehn LE, 2017, ICES J MAR SCI, V74, P2448, DOI 10.1093/icesjms/fsx072
   Kuzuhara H, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0213611
   Laurel BJ, 2008, J PLANKTON RES, V30, P1051, DOI 10.1093/plankt/fbn057
   Lawson JW, 1997, CAN J ZOOL, V75, P2095, DOI 10.1139/z97-844
   Leonhard SB., 2011, EFFECT HORNS REV 1 O
   Lindeboom HJ, 2011, ENVIRON RES LETT, V6, DOI 10.1088/1748-9326/6/3/035101
   Lindegren M, 2018, FISH OCEANOGR, V27, P212, DOI 10.1111/fog.12246
   Link JS, 2008, N AM J FISH MANAGE, V28, P649, DOI 10.1577/M07-100.1
   Link JS, 2012, FISH RES, V114, P31, DOI 10.1016/j.fishres.2011.04.022
   Link JS, 2011, FISH FISH, V12, P152, DOI 10.1111/j.1467-2979.2011.00411.x
   Logan JM, 2015, ENVIRON BIOL FISH, V98, P1411, DOI 10.1007/s10641-014-0368-y
   Logan JM, 2011, MAR BIOL, V158, P73, DOI 10.1007/s00227-010-1543-0
   Loring P., 2019, Tracking Offshore Occurrence of Common Terns, Endangered Roseate Terns
   LYDERSEN C, 1991, HOLARCTIC ECOL, V14, P219
   MacLeod CD, 2007, BIOLOGY LETT, V3, P535, DOI 10.1098/rsbl.2007.0298
   MacLeod CD, 2007, BIOL LETTERS, V3, P185, DOI 10.1098/rsbl.2006.0588
   Macleod K, 2004, MAR ECOL PROG SER, V277, P263, DOI 10.3354/meps277263
   MAFMC (Mid-Atlantic Fishery Management Council), 2017, UNM FOR OMN AM
   Maps F, 2012, J PLANKTON RES, V34, P36, DOI 10.1093/plankt/fbr088
   McCusker MR, 2013, MOL ECOL RESOUR, V13, P177, DOI 10.1111/1755-0998.12043
   McQuinn IH, 2009, CAN J FISH AQUAT SCI, V66, P2256, DOI 10.1139/F09-143
   Melle W, 2014, PROG OCEANOGR, V129, P244, DOI 10.1016/j.pocean.2014.04.026
   MEYER TL, 1979, FISH B-NOAA, V77, P243
   Mid-Atlantic Management Council, 2019, EC APPR FISH MAN GUI
   Miller T., 2010, Estimation of Albatross IV to Henry B. Bigelow calibration factors
   MONTELEONE DM, 1986, MAR ECOL PROG SER, V30, P133, DOI 10.3354/meps030133
   Morley JW, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0196127
   Morse RE, 2017, J MARINE SYST, V165, P77, DOI 10.1016/j.jmarsys.2016.09.011
   Morse W., 1982, SPAWNING STOCK BIOMA
   Moustahfid H, 2009, ICES J MAR SCI, V66, P445, DOI 10.1093/icesjms/fsn217
   Moxley J. H., MARINE ECOLOGY PROGR
   Munroe T.A., 2002, BIGELOW SCHROEDERS F, P141
   Murase H., 2009, JARPNII REV N TOK JA
   MURPHY MA, 1995, FISH B-NOAA, V93, P577
   Murray CS, 2019, CONSERV PHYSIOL, V7, DOI 10.1093/conphys/coz084
   Murray CS, 2018, DIVERSITY-BASEL, V10, DOI 10.3390/d10030069
   Nelson EJ, 2013, FRONT ECOL ENVIRON, V11, P483, DOI 10.1890/120312
   NELSON G A, 1991, Journal of Northwest Atlantic Fishery Science, V11, P11
   Neve PB, 2000, NAMMCO SCI PUBL, V2, P92, DOI 10.7557/3.2974
   Nishikawa T, 2020, FISH OCEANOGR, V29, P52, DOI 10.1111/fog.12448
   Nizinski M.S., 2002, BIGELOW SCHROEDERS F, Vthird, P496
   NIZINSKI MS, 1990, FISH B-NOAA, V88, P241
   Northeast Regional Planning Body, 2016, NE OC PLAN
   Novak AJ, 2017, T AM FISH SOC, V146, P308, DOI 10.1080/00028487.2016.1264472
   Nye JA, 2009, MAR ECOL PROG SER, V393, P111, DOI 10.3354/meps08220
   Olsen E, 2003, MAR BIOL, V142, P13, DOI 10.1007/s00227-002-0934-2
   Orr JW, 2015, FISH B-NOAA, V113, P129, DOI 10.7755/FB.113.2.3
   Oskarsson GJ, 2008, J FISH BIOL, V72, P2655, DOI 10.1111/j.1095-8649.2008.01886.x
   Overholtz WJ, 2008, N AM J FISH MANAGE, V28, P247, DOI 10.1577/M06-267.1
   Overholtz WJ, 2007, ICES J MAR SCI, V64, P83, DOI 10.1093/icesjms/fsl009
   OVERHOLTZ WJ, 1979, FISH B-NOAA, V77, P285
   Parmesan C, 2007, GLOBAL CHANGE BIOL, V13, P1860, DOI 10.1111/j.1365-2486.2007.01404.x
   Patrick WS, 2015, FISHERIES, V40, P155, DOI 10.1080/03632415.2015.1024308
   PAYNE PM, 1989, MAR MAMMAL SCI, V5, P173, DOI 10.1111/j.1748-7692.1989.tb00331.x
   PAYNE PM, 1990, FISH B-NOAA, V88, P687
   PAYNE PM, 1986, FISH B-NOAA, V84, P271
   PEARSON WH, 1984, MAR ENVIRON RES, V11, P17, DOI 10.1016/0141-1136(84)90008-4
   Perretti CT, 2017, MAR ECOL PROG SER, V574, P1, DOI 10.3354/meps12183
   Pershing AJ, 2005, ICES J MAR SCI, V62, P1511, DOI 10.1016/j.icesjms.2005.04.025
   Pershing AJ, 2015, SCIENCE, V350, P809, DOI 10.1126/science.aac9819
   Petersen JK, 2006, AMBIO, V35, P75, DOI 10.1579/0044-7447(2006)35[75:OWFTTO]2.0.CO;2
   Pettigrew NR, 2005, DEEP-SEA RES PT II, V52, P2369, DOI 10.1016/j.dsr2.2005.06.033
   Piatt J. F., 1987, THESIS
   Piatt JF, 2018, FISH OCEANOGR, V27, P366, DOI 10.1111/fog.12258
   Pierce GJ, 2004, J MAR BIOL ASSOC UK, V84, P1241, DOI 10.1017/S0025315404010732h
   Pierson JJ, 2013, J PLANKTON RES, V35, P504, DOI 10.1093/plankt/fbt022
   Pikitch EK, 2004, SCIENCE, V305, P346, DOI 10.1126/science.1098222
   Pikitch EK., 2012, LITTLE FISH BIG IMPA, P108
   Pinsky ML, 2013, SCIENCE, V341, P1239, DOI 10.1126/science.1239352
   Pinsky ML, 2011, P NATL ACAD SCI USA, V108, P8317, DOI 10.1073/pnas.1015313108
   PINTO JM, 1984, MAR BIOL, V83, P193, DOI 10.1007/BF00394728
   Pirie L, 2012, STUD AVIAN BIOL, P185
   Pláganyi ÉE, 2014, FISH RES, V159, P68, DOI 10.1016/j.fishres.2014.05.011
   POLIS GA, 1989, ANNU REV ECOL SYST, V20, P297, DOI 10.1146/annurev.es.20.110189.001501
   Politis P. J., 2014, 1406 NE FISH SCI CTR, P14, DOI [10.7289/V5C53HVS, DOI 10.7289/V5C53HVS]
   POTTER D C, 1987, Journal of Northwest Atlantic Fishery Science, V7, P107
   Powers K.D., 1987, P372
   Powers KD, 2017, MAR ECOL PROG SER, V574, P211, DOI 10.3354/meps12168
   Pratte I, 2017, MAR ECOL PROG SER, V572, P243, DOI 10.3354/meps12144
   Purcell JE, 2001, MAR ECOL PROG SER, V210, P67, DOI 10.3354/meps210067
   Rawlins MA, 2012, J GEOPHYS RES-ATMOS, V117, DOI 10.1029/2012JD018137
   Reay P. J., 1970, SYNOPSIS BIOL DAT N
   RECCHIA CA, 1989, CAN J ZOOL, V67, P2140, DOI 10.1139/z89-304
   Record NR, 2019, OCEANOGRAPHY, V32, P162, DOI 10.5670/oceanog.2019.201
   Régnier T, 2018, J SEA RES, V134, P34, DOI 10.1016/j.seares.2018.01.003
   Regular PM, 2014, ECOSPHERE, V5, DOI 10.1890/ES14-00182.1
   Richardson DE, 2014, CAN J FISH AQUAT SCI, V71, P1349, DOI 10.1139/cjfas-2013-0489
   Robards MD, 2002, ENVIRON BIOL FISH, V64, P429, DOI 10.1023/A:1016151224357
   Robards MD, 1999, J EXP MAR BIOL ECOL, V242, P245, DOI 10.1016/S0022-0981(99)00102-1
   Robards MD, 1999, USDA FOR SERV PNW RE, pU2
   Robards MD, 1999, J FISH BIOL, V54, P1050, DOI 10.1111/j.1095-8649.1999.tb00857.x
   Rock JC, 2007, WATERBIRDS, V30, P579, DOI 10.1675/1524-4695(2007)030[0579:DCAACT]2.0.CO;2
   Rock JC, 2007, AVIAN CONSERV ECOL, V2
   Ronconi RA, 2010, MAR ECOL PROG SER, V419, P267, DOI 10.3354/meps08860
   Ronconi RA, 2014, MAR ECOL PROG SER, V514, P247, DOI 10.3354/meps10980
   Ruckelshaus M, 2008, BIOSCIENCE, V58, P53, DOI 10.1641/B580110
   Runge J. A., 2012, ADV ECOSYSTEM RES GU
   Runge JA, 2015, J PLANKTON RES, V37, P221, DOI 10.1093/plankt/fbu098
   Rutecki D., 2014, M12PS00009 US DEP IN
   Rutterford LA, 2015, NAT CLIM CHANGE, V5, P569, DOI 10.1038/nclimate2607
   Saba VS, 2016, J GEOPHYS RES-OCEANS, V121, P118, DOI 10.1002/2015JC011346
   SAFINA C, 1990, ECOLOGY, V71, P1804, DOI 10.2307/1937588
   Salisbury JE, 2018, BIOGEOCHEMISTRY, V141, P401, DOI 10.1007/s10533-018-0505-3
   Scopel L, 2019, MAR ECOL PROG SER, V626, P177, DOI 10.3354/meps13048
   SCOTT JS, 1968, J FISH RES BOARD CAN, V25, P1775, DOI 10.1139/f68-163
   SCOTT JS, 1973, J FISH RES BOARD CAN, V30, P451, DOI 10.1139/f73-075
   SEKIGUCHI H, 1977, B JPN SOC SCI FISH, V43, P417
   SELZER LA, 1988, MAR MAMMAL SCI, V4, P141, DOI 10.1111/j.1748-7692.1988.tb00194.x
   SHEALER DA, 1994, J FIELD ORNITHOL, V65, P349
   SHERMAN K, 1981, NATURE, V291, P486, DOI 10.1038/291486a0
   Sigurjónsson J, 2000, NAMMCO SCI PUBL, V2, P82, DOI 10.7557/3.2973
   Silva TL, 2019, MAR ECOL PROG SER, V609, P239, DOI 10.3354/meps12820
   Simpson A. C., 1968, TORREY CANYON DISAST
   Slacum HW, 2010, MAR COAST FISH, V2, P277, DOI 10.1577/C09-012.1
   Slott JM, 2006, GEOPHYS RES LETT, V33, DOI 10.1029/2006GL027445
   SMIGIELSKI AS, 1984, MAR ECOL PROG SER, V14, P287, DOI 10.3354/meps014287
   Smith ADM, 2011, SCIENCE, V333, P1147, DOI 10.1126/science.1209395
   Smith BE, 2007, J FISH BIOL, V71, P749, DOI 10.1111/j.1095-8649.2007.01540.x
   Smith BE, 2014, J EXP MAR BIOL ECOL, V461, P489, DOI 10.1016/j.jembe.2014.09.009
   Smith LA, 2015, ECOL APPL, V25, P373, DOI 10.1890/13-1656.1
   Staudinger M. D., 2004, THESIS
   Staudinger MD, 2019, FISH OCEANOGR, V28, P532, DOI 10.1111/fog.12429
   Staudinger MD, 2011, MAR POLLUT BULL, V62, P734, DOI 10.1016/j.marpolbul.2011.01.017
   Stenberg C, 2015, MAR ECOL PROG SER, V528, P257, DOI 10.3354/meps11261
   Stevick PT, 2006, J ZOOL, V270, P244, DOI 10.1111/j.1469-7998.2006.00128.x
   Suca JJ, 2018, PROG OCEANOGR, V165, P52, DOI 10.1016/j.pocean.2018.04.014
   Sydeman WJ, 2017, FISH OCEANOGR, V26, P379, DOI 10.1111/fog.12204
   Tamura T., 2009, EXP WORKSH REV ONG J
   Teffer AK, 2015, MAR BIOL, V162, P1823, DOI 10.1007/s00227-015-2715-8
   Thomas AC, 2017, ELEMENTA-SCI ANTHROP, V5, DOI 10.1525/elementa.240
   Thompson P, 2007, BIOL LETTERS, V3, P533, DOI 10.1098/rsbl.2007.0076
   Tien NSH, 2017, J SEA RES, V127, P194, DOI 10.1016/j.seares.2017.05.001
   Tucker S, 2009, MAR ECOL PROG SER, V384, P287, DOI 10.3354/meps08000
   Tyrrell MC, 2011, FISH RES, V108, P1, DOI 10.1016/j.fishres.2010.12.025
   van der Kooij J, 2008, J SEA RES, V60, P201, DOI 10.1016/j.seares.2008.07.003
   van Deurs M, 2012, MAR ECOL PROG SER, V458, P169, DOI 10.3354/meps09736
   van Deurs M, 2015, MAR ECOL PROG SER, V520, P235, DOI 10.3354/meps11092
   van Deurs M, 2011, MAR BIOL, V158, P2755, DOI 10.1007/s00227-011-1774-8
   van Deurs M, 2010, MAR ECOL PROG SER, V416, P201, DOI 10.3354/meps08763
   van Deurs M, 2009, MAR ECOL PROG SER, V381, P249, DOI 10.3354/meps07960
   Van Dyne G., 1969, The ecosystem concept in natural resource management
   Vandendriessche S., 2011, MONITORING EFFECTS O, P83
   Veit RR, 2017, FRONT ECOL EVOL, V5, DOI 10.3389/fevo.2017.00121
   Vikingsson GA, 2015, FRONT ECOL EVOL, V3, DOI 10.3389/fevo.2015.00006
   von Biela VR, 2019, MAR ECOL PROG SER, V613, P171, DOI 10.3354/meps12891
   Walsh HJ, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0137382
   Wanless S, 2004, MAR ECOL PROG SER, V279, P237, DOI 10.3354/meps279237
   Wanless S, 2018, MAR ECOL PROG SER, V600, P193, DOI 10.3354/meps12679
   Ware C, 2014, MAR MAMMAL SCI, V30, P494, DOI 10.1111/mms.12053
   Weinrich M, 1997, FISH B-NOAA, V95, P826
   Weinrich MT, 2001, MAR MAMMAL SCI, V17, P231, DOI 10.1111/j.1748-7692.2001.tb01268.x
   WESTIN DT, 1979, T AM FISH SOC, V108, P328, DOI 10.1577/1548-8659(1979)108<328:SAOBOT>2.0.CO;2
   Wiley D, 2011, BEHAVIOUR, V148, P575, DOI 10.1163/000579511X570893
   WINSLADE P, 1974, J FISH BIOL, V6, P587, DOI 10.1111/j.1095-8649.1974.tb05102.x
   WINTERS GH, 1983, CAN J FISH AQUAT SCI, V40, P409, DOI 10.1139/f83-059
   WINTERS GH, 1981, CAN J FISH AQUAT SCI, V38, P841, DOI 10.1139/f81-111
   Wright PJ, 2017, J EXP MAR BIOL ECOL, V486, P52, DOI 10.1016/j.jembe.2016.09.014
   Wright PJ, 2000, J SEA RES, V44, P243, DOI 10.1016/S1385-1101(00)00050-2
   Wuenschel MJ, 2013, FISH B-NOAA, V111, P352, DOI 10.7755/FB.111.4.5
   Yakola K., 2019, THESIS
   ZAMARRO J, 1992, NETH J SEA RES, V29, P229, DOI 10.1016/0077-7579(92)90023-8
NR 292
TC 43
Z9 47
U1 0
U2 23
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1467-2960
EI 1467-2979
J9 FISH FISH
JI Fish. Fish.
PD MAY
PY 2020
VL 21
IS 3
BP 522
EP 556
DI 10.1111/faf.12445
EA MAR 2020
PG 35
WC Fisheries
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Fisheries
GA LI2DO
UT WOS:000520760700001
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Sánchez-García, D
   Rubio-Bellido, C
   Del Río, JJM
   Pérez-Fargallo, A
AF Sanchez-Garcia, Daniel
   Rubio-Bellido, Carlos
   Martin Del Rio, Juan Jesus
   Perez-Fargallo, Alexis
TI Towards the quantification of energy demand and consumption through the
   adaptive comfort approach in mixed mode office buildings considering
   climate change
SO ENERGY AND BUILDINGS
LA English
DT Article
DE Adaptive comfort; Energy consumption; Energy demand; Natural
   ventilation; Performance simulation; Climate change
ID THERMAL COMFORT; FIELD; VENTILATION; TEMPERATURE; PERFORMANCE;
   SIMULATION; SYSTEMS
AB Heating, Ventilating and Air Conditioning (HVAC) systems represent one of the highest energy consumptions for office buildings. They are traditionally based on fixed setpoint temperatures during working hours and disregard outdoor conditions. The use of natural ventilation coupled with HVAC systems is frequently proposed when considering the global tendency towards reducing energy consumption in buildings. Buildings working under mixed mode instead of full air-conditioned mode, are a climate adaption development and usually lead to a decrease in energy consumption. However, there is no consensus on comfort thresholds and it is difficult to predict energy demand and consumption when considering global warming. This research focuses on quantifying the application of an adaptive comfort control mode in mixed mode office buildings. It consists of using daily setpoint temperatures based on the adaptive thermal comfort approach, in both present and future scenarios. The results show a 74.6% reduction in energy demand and a 59.7% drop in energy consumption when the adaptive comfort control implemented model (ACCIM) is applied in the current scenario. Results also establish that the ACCIM is more resilient to climate change, despite the fact that an increase in energy demand and consumption can be expected. The reduction of the energy demand ranges, with respect to the baseline model, from 31.0% currently to 39.1% in 2080, while energy consumption changes from 40.2% to 62.0% in 2080. (C) 2019 Elsevier B.V. All rights reserved.
C1 [Sanchez-Garcia, Daniel; Rubio-Bellido, Carlos; Martin Del Rio, Juan Jesus] Univ Seville, Dept Bldg Construct 2, Seville, Spain.
   [Perez-Fargallo, Alexis] Univ Bio Bio, Dept Bldg Sci, Concepcion, Chile.
   [Rubio-Bellido, Carlos] Higher Tech Sch Bldg Engn, Avda Reina Mercedes 4A, Seville, Spain.
C3 University of Sevilla; Universidad del Bio-Bio
RP Rubio-Bellido, C (corresponding author), Univ Seville, Dept Bldg Construct 2, Seville, Spain.; Rubio-Bellido, C (corresponding author), Higher Tech Sch Bldg Engn, Avda Reina Mercedes 4A, Seville, Spain.
EM carlosrubio@us.es
RI Martin-Del-Rio, Juan/K-7902-2014; Rubio-Bellido, Carlos/K-1861-2014;
   Perez Fargallo, Alexis/K-1975-2014; Sanchez Garcia, Daniel/T-2234-2017
OI Rubio-Bellido, Carlos/0000-0001-6719-8793; Perez Fargallo,
   Alexis/0000-0001-7071-7523; Sanchez Garcia, Daniel/0000-0002-3080-0821
FU "Direccion de Postgrado" at the University of the Bio-Bio; "Direccion de
   Investigacion y Creacion Artistica" at the University of the Bio-Bio;
   Becas Iberoamericanas. Jovenes Profesionales e Investigadores. Santander
   Universidades
FX The authors would like to acknowledge "Direccion de Investigacion y
   Creacion Artistica" and "Direccion de Postgrado" at the University of
   the Bio-Bio for financing this paper. In addition, the authors would
   like to acknowledge "Becas Iberoamericanas. Jovenes Profesionales e
   Investigadores. Santander Universidades" for financing the international
   mobility of Alexis Perez-Fargallo at the University of Cadiz.
CR [Anonymous], 2014, REPORT, DOI DOI 10.1007/S13398-014-0173-7.2
   [Anonymous], 2007, 15251 CEN
   [Anonymous], 2008, 20 20 2020 EUR CLIM
   ANSI/ASHRAE, 2014, ASHRAE GUID 14 2014
   Aparicio-Ruiz P, 2018, SUSTAIN CITIES SOC, V43, P77, DOI 10.1016/j.scs.2018.07.028
   Arets M. J. P., 2004, THERMISCHE BEHAAGLIJ
   Barbadilla-Martín E, 2018, ENERG BUILDINGS, V167, P281, DOI 10.1016/j.enbuild.2018.02.033
   Barbadilla-Martín E, 2017, BUILD ENVIRON, V123, P163, DOI 10.1016/j.buildenv.2017.06.042
   Belcher S. E., 2005, Building Services Engineering Research & Technology, V26, P49, DOI 10.1191/0143624405bt112oa
   Carlucci S, 2018, BUILD ENVIRON, V137, P73, DOI 10.1016/j.buildenv.2018.03.053
   Chen JL, 2018, ENERG BUILDINGS, V158, P1648, DOI 10.1016/j.enbuild.2017.12.004
   de Dear RJ, 2002, ENERG BUILDINGS, V34, P549, DOI 10.1016/S0378-7788(02)00005-1
   Ezzeldin S, 2013, ENERG BUILDINGS, V65, P368, DOI 10.1016/j.enbuild.2013.06.004
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Hoyt T, 2015, BUILD ENVIRON, V88, P89, DOI 10.1016/j.buildenv.2014.09.010
   Indraganti M, 2014, BUILD ENVIRON, V74, P39, DOI 10.1016/j.buildenv.2014.01.002
   Indraganti M, 2013, BUILD ENVIRON, V65, P195, DOI 10.1016/j.buildenv.2013.04.007
   International Energy Agency, 2017, EN EFF 2017, DOI [10.1787/9789264284234-en, DOI 10.1787/9789264284234-EN]
   International Energy Agency, 2017, EN EFF IND HIGHL, V102, DOI [10.1017/CB09781107415324.004, DOI 10.1017/CB09781107415324.004]
   Jentsch MF, 2013, RENEW ENERG, V55, P514, DOI 10.1016/j.renene.2012.12.049
   Kim J, 2017, ENERG BUILDINGS, V141, P274, DOI 10.1016/j.enbuild.2017.02.061
   Kramer RP, 2015, APPL ENERG, V158, P446, DOI 10.1016/j.apenergy.2015.08.044
   Lucon O, 2014, CLIMATE CHANGE 2014: MITIGATION OF CLIMATE CHANGE, P671
   Luo MH, 2015, BUILD ENVIRON, V88, P46, DOI 10.1016/j.buildenv.2014.06.019
   Manu S, 2016, BUILD ENVIRON, V98, P55, DOI 10.1016/j.buildenv.2015.12.019
   McCartney KJ, 2002, ENERG BUILDINGS, V34, P623, DOI 10.1016/S0378-7788(02)00013-0
   Oropeza-Perez I, 2017, ENERG BUILDINGS, V145, P251, DOI 10.1016/j.enbuild.2017.04.031
   Pérez-Fargallo A, 2018, ENERG POLICY, V113, P157, DOI 10.1016/j.enpol.2017.10.054
   Pérez-Fargallo A, 2017, INDOOR BUILT ENVIRON, V26, P980, DOI 10.1177/1420326X17713071
   R. and A. C. E. (ASHRAE) American Society of Heating, 2017, 552017 R ACE ASHRAE
   Rupp RF, 2018, ENERG BUILDINGS, V158, P1475, DOI 10.1016/j.enbuild.2017.11.047
   Salcido JC, 2016, ENERG BUILDINGS, V127, P1008, DOI 10.1016/j.enbuild.2016.06.054
   Sánchez CSG, 2017, BUILD ENVIRON, V114, P344, DOI 10.1016/j.buildenv.2016.12.029
   Sdnchez-Garcia D., 2017, HABITAT SUSTENTABLE, V7, P6, DOI [10.22320/07190700.2017.07.02.01, DOI 10.22320/07190700.2017.07.02.01]
   Spyropoulos GN, 2011, ENERG BUILDINGS, V43, P770, DOI 10.1016/j.enbuild.2010.12.015
   Thomas LE, 2017, BUILD RES INF, V45, P176, DOI 10.1080/09613218.2017.1252617
   van der Linden AC, 2006, ENERG BUILDINGS, V38, P8, DOI 10.1016/j.enbuild.2005.02.008
   Yun GY, 2016, BUILD ENVIRON, V105, P13, DOI 10.1016/j.buildenv.2016.05.027
NR 38
TC 76
Z9 85
U1 2
U2 38
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 2019
VL 187
BP 173
EP 185
DI 10.1016/j.enbuild.2019.02.002
PG 13
WC Construction & Building Technology; Energy & Fuels; Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Energy & Fuels; Engineering
GA HP1EC
UT WOS:000461407200014
DA 2025-01-10
ER

PT J
AU Fan, HY
   Yu, ZW
   Yang, GY
   Liu, TY
   Liu, TY
   Hung, CH
   Vejre, H
AF Fan, Huiying
   Yu, Zhaowu
   Yang, Gaoyuan
   Liu, Tsz Yiu
   Liu, Tsz Ying
   Hung, Carmem Huang
   Vejre, Henrik
TI How to cool hot-humid (Asian) cities with urban trees? An optimal
   landscape size perspective
SO AGRICULTURAL AND FOREST METEOROLOGY
LA English
DT Article
DE Urban tree; Urban cooling island effect; Threshold value of efficiency;
   Landscape indexes; Urban planning; Hot-humid city
ID LAND-SURFACE TEMPERATURE; MITIGATION TECHNOLOGIES; GREEN SPACES; HEAT
   ISLANDS; CLIMATE; RETRIEVAL; PATTERNS; IMPACTS; SHADE; PARKS
AB Urban areas typically experience higher temperatures compared to surrounding rural areas that is known as the urban heat island effect (UHI). Urban greenery is capable of mitigating the UHI by creating microclimates that are lower in temperature than their surroundings, which are known as urban cooling islands (UCI). Previous studies have proved the effectiveness of UCI from different perspectives. However, a specific optimal level of landscape patch size at a regional scale that can be implemented by urban planners has not been identified. In this study, we estimated the optimal patch size in seven selected hot-humid Asian cities with the help of Google Cloud Computing, Python Programming, as well as spatial and statistical analysis. A two-tier (two optimal patch sizes) distribution of the threshold value of efficiency (TVoE) of urban trees in this region was found. Eight landscape-level indexes were used to explore the variance of TVoE. The percentage of landscape (PLAND), edge density (ED), mean landscape shape index (Shape_MN), mean fractal dimension (FRAC_MN), largest patch index (LPI), and mean Euclidian nearest-neighbor distance (ENN_MN) were found to have no significant correlation with TVoE. While the average normalized difference vegetation index (NDVI_MN) and average background temperature (BGT_MN) were found to be highly associated with the variance in TVoE. Further, a concept model that can simulate the effects of NDVI_MN and BGT_MN was also proposed. These findings extend the understanding of the UCI effect of urban trees as well as providing a basis for scientific climate adaption planning in this region.
C1 [Yu, Zhaowu; Vejre, Henrik] Univ Copenhagen, Fac Sci, Dept Geosci & Nat Resource Management, DK-1958 Copenhagen, Denmark.
   [Fan, Huiying; Liu, Tsz Yiu; Liu, Tsz Ying; Hung, Carmem Huang] Hong Kong Univ Sci & Technol, Div Environm & Sustainabil, Hong Kong, Peoples R China.
   [Yang, Gaoyuan] Xiamen Univ, Sch Architecture & Civil Engn, Xiamen 361005, Peoples R China.
C3 University of Copenhagen; Hong Kong University of Science & Technology;
   Xiamen University
RP Yu, ZW (corresponding author), Univ Copenhagen, Fac Sci, Dept Geosci & Nat Resource Management, DK-1958 Copenhagen, Denmark.
EM asflsyfan@gmail.com; zhyu@ign.ku.dk; yanggaoyuanl@outlook.com;
   tyliuaa@connect.ust.hk; tyliuab@connect.ust.hk; chhungab@connect.ust.hk;
   hv@ign.ku.dk
RI Fan, Huiying/GRR-4677-2022; Gaoyuan, Yang/HKO-4087-2023; Yu,
   Zhaowu/E-8032-2016; Vejre, Henrik/P-7142-2014
OI Fan, Huiying ("Fizzy")/0000-0002-0351-386X; Yu,
   Zhaowu/0000-0003-4576-4541; Yang, Gaoyuan/0000-0002-9652-1323; Yang,
   Gaoyuan/0000-0001-9735-6529; Vejre, Henrik/0000-0002-6820-0389
FU Natural Science Foundation of China [41471150]; Chinese Scholarship
   Council (CSC)
FX This work was supported in part by the Natural Science Foundation of
   China (no. 41471150), in part by the Chinese Scholarship Council (CSC).
   We also thank the two anonymous reviewers and editors for their dozens
   of constructive and critical comments and suggestion.
CR Akbari H, 2001, SOL ENERGY, V70, P295, DOI 10.1016/S0038-092X(00)00089-X
   Akbari H, 2016, ENERG BUILDINGS, V133, P834, DOI 10.1016/j.enbuild.2016.09.067
   [Anonymous], 2002, BOUNDARY LAYER CLIMA, DOI DOI 10.4324/9780203407219
   [Anonymous], ENV SCI TECHNOL
   Asgarian A, 2015, URBAN ECOSYST, V18, P209, DOI 10.1007/s11252-014-0387-7
   Bao TLG, 2016, ISPRS INT GEO-INF, V5, DOI 10.3390/ijgi5020012
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   Buchin O, 2016, ENERG BUILDINGS, V114, P27, DOI 10.1016/j.enbuild.2015.06.038
   Buyantuyev A, 2010, LANDSCAPE ECOL, V25, P17, DOI 10.1007/s10980-009-9402-4
   Chen AL, 2014, URBAN FOR URBAN GREE, V13, P646, DOI 10.1016/j.ufug.2014.07.006
   Cheng XY, 2015, J URBAN PLAN DEV, V141, DOI 10.1061/(ASCE)UP.1943-5444.0000256
   Dell M, 2012, AM ECON J-MACROECON, V4, P66, DOI 10.1257/mac.4.3.66
   Demuzere M, 2014, J ENVIRON MANAGE, V146, P107, DOI 10.1016/j.jenvman.2014.07.025
   Doick KJ, 2014, SCI TOTAL ENVIRON, V493, P662, DOI 10.1016/j.scitotenv.2014.06.048
   Gillner S, 2015, LANDSCAPE URBAN PLAN, V143, P33, DOI 10.1016/j.landurbplan.2015.06.005
   Gorelick N, 2017, REMOTE SENS ENVIRON, V202, P18, DOI 10.1016/j.rse.2017.06.031
   Hamada S, 2013, URBAN FOR URBAN GREE, V12, P426, DOI 10.1016/j.ufug.2013.06.008
   Jenerette GD, 2007, LANDSCAPE ECOL, V22, P353, DOI 10.1007/s10980-006-9032-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
   Kadoorie Institute, 2010, HONG KONGS VULN GLOB
   Kong FH, 2014, LANDSCAPE URBAN PLAN, V128, P35, DOI 10.1016/j.landurbplan.2014.04.018
   Kuang WH, 2015, LANDSCAPE ECOL, V30, P357, DOI 10.1007/s10980-014-0128-6
   Li XM, 2013, LANDSCAPE URBAN PLAN, V114, P1, DOI 10.1016/j.landurbplan.2013.02.005
   Li XM, 2012, LANDSCAPE ECOL, V27, P887, DOI 10.1007/s10980-012-9731-6
   Lin WQ, 2015, LANDSCAPE URBAN PLAN, V134, P66, DOI 10.1016/j.landurbplan.2014.10.012
   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
   OKE TR, 1982, Q J ROY METEOR SOC, V108, P1, DOI 10.1002/qj.49710845502
   Oliveira S, 2011, BUILD ENVIRON, V46, P2186, DOI 10.1016/j.buildenv.2011.04.034
   Peng J, 2016, REMOTE SENS ENVIRON, V173, P145, DOI 10.1016/j.rse.2015.11.027
   Rahman MA, 2018, SCI TOTAL ENVIRON, V633, P100, DOI 10.1016/j.scitotenv.2018.03.168
   Ren ZB, 2013, FORESTS, V4, P868, DOI 10.3390/f4040868
   Roberts Brian., 2006, Urbanization and Sustainability in Asia
   Santamouris M, 2015, ENERG BUILDINGS, V98, P119, DOI 10.1016/j.enbuild.2014.09.052
   Santamouris M, 2014, SOL ENERGY, V103, P682, DOI 10.1016/j.solener.2012.07.003
   Shih WY, 2017, HABITAT INT, V60, P69, DOI 10.1016/j.habitatint.2016.12.006
   Sobrino JA, 2004, REMOTE SENS ENVIRON, V90, P434, DOI 10.1016/j.rse.2004.02.003
   Stewart ID, 2012, B AM METEOROL SOC, V93, P1879, DOI 10.1175/BAMS-D-11-00019.1
   Sun RH, 2018, LANDSCAPE URBAN PLAN, V178, P43, DOI 10.1016/j.landurbplan.2018.05.015
   Sun RH, 2017, ECOSYST SERV, V23, P38, DOI 10.1016/j.ecoser.2016.11.011
   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
   Yang P, 2016, ATMOS OCEAN SCI LETT, V9, P298, DOI 10.1080/16742834.2016.1191316
   Yap K.S., 2012, Urbanization in Southeast Asia: Issues and Impacts
   Yu XL, 2014, REMOTE SENS-BASEL, V6, P9829, DOI 10.3390/rs6109829
   Yu Zhao-wu, 2015, Yingyong Shengtai Xuebao, V26, P636
   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
   Yu ZT, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-20935-8
   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 52
TC 142
Z9 153
U1 24
U2 247
PU ELSEVIER SCIENCE BV
PI AMSTERDAM
PA PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
SN 0168-1923
EI 1873-2240
J9 AGR FOREST METEOROL
JI Agric. For. Meteorol.
PD FEB 15
PY 2019
VL 265
BP 338
EP 348
DI 10.1016/j.agrformet.2018.11.027
PG 11
WC Agronomy; Forestry; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Agriculture; Forestry; Meteorology & Atmospheric Sciences
GA HI9BV
UT WOS:000456751200028
DA 2025-01-10
ER

PT J
AU Kirk, NL
   Howells, EJ
   Abrego, D
   Burt, JA
   Meyer, E
AF Kirk, Nathan L.
   Howells, Emily J.
   Abrego, David
   Burt, John A.
   Meyer, Eli
TI Genomic and transcriptomic signals of thermal tolerance in heat-tolerant
   corals (<i>Platygyra daedalea</i>) of the Arabian/Persian Gulf
SO MOLECULAR ECOLOGY
LA English
DT Article
DE climate adaptation; heat tolerance; heritability; planula larvae;
   transcriptional stress response
ID REEF-BUILDING CORALS; DIFFERENTIAL GENE-EXPRESSION; CLIMATE-CHANGE;
   PORITES-ASTREOIDES; BLEACHING EVENTS; ACROPORA-TENUIS; DATA SETS;
   RNA-SEQ; STRESS; LARVAE
AB Scleractinian corals occur in tropical regions near their upper thermal limits and are severely threatened by rising ocean temperatures. However, several recent studies have shown coral populations can harbour genetic variation in thermal tolerance. Here, we have extended these approaches to study heat tolerance of corals in the Persian/Arabian Gulf, where heat-tolerant local populations experience extreme summer temperatures (up to 36 degrees C). To evaluate whether selection has depleted genetic variation in thermal tolerance, estimate potential future adaptive responses and understand the functional basis for these corals' unusual heat tolerance, we conducted controlled crosses in the Gulf coral Platygyra daedalea. Heat tolerance is highly heritable in this population (h(2) = 0.487-0.748), suggesting substantial potential for adaptive responses to selection for elevated temperatures. To identify genetic markers associated with this variation, we conducted genomewide SNP genotyping in parental corals and tested for relationships between paternal genotype and offspring thermal tolerance. Resulting multilocus SNP genotypes explained a large fraction of variation in thermal tolerance in these crosses (69%). To investigate the functional basis of these differences in thermal tolerance, we profiled transcriptional responses in tolerant and susceptible families, revealing substantial sire effects on transcriptional responses to thermal stress. We also studied sequence variation in these expressed sequences, identifying alleles and functional groups of differentially expressed genes associated with thermal tolerance. Our findings demonstrate that corals in this population harbour extensive genetic variation in thermal tolerance, and heat-tolerant phenotypes differ in both gene sequences and transcriptional stress responses from their susceptible counterparts.
C1 [Kirk, Nathan L.; Meyer, Eli] Oregon State Univ, Dept Integrat Biol, Corvallis, OR 97331 USA.
   [Howells, Emily J.; Burt, John A.] New York Univ Abu Dhabi, Ctr Genom & Syst Biol, Abu Dhabi, U Arab Emirates.
   [Abrego, David] Zayed Univ, Dept Nat Sci & Publ Hlth, Abu Dhabi, U Arab Emirates.
C3 Oregon State University; New York University; New York University Abu
   Dhabi; Zayed University
RP Kirk, NL (corresponding author), Oregon State Univ, Dept Integrat Biol, Corvallis, OR 97331 USA.
EM kirknat@gmail.com
RI Howells, Emily/J-1851-2012; Abrego, David/AAT-8120-2020; Kirk,
   Nathan/B-4065-2012; Burt, John/LWK-5347-2024
OI Howells, Emily/0000-0001-7732-2372; Abrego, David/0000-0003-3311-2730;
   Burt, John/0000-0001-6087-6424; Kirk, Nathan/0000-0002-7289-3907
FU New York University; Environment Agency
FX New York University; Environment Agency
CR ALTSCHUL SF, 1990, J MOL BIOL, V215, P403, DOI 10.1006/jmbi.1990.9999
   Ashburner M, 2000, NAT GENET, V25, P25, DOI 10.1038/75556
   Aswani S, 2015, FRONT MAR SCI, V2, DOI 10.3389/fmars.2015.00050
   Baird AH, 2009, ANNU REV ECOL EVOL S, V40, P551, DOI 10.1146/annurev.ecolsys.110308.120220
   Baird AH, 2009, TRENDS ECOL EVOL, V24, P16, DOI 10.1016/j.tree.2008.09.005
   Baker AC, 2004, CORAL HEALTH AND DISEASE, P177
   Barshis DJ, 2013, P NATL ACAD SCI USA, V110, P1387, DOI 10.1073/pnas.1210224110
   Bates D., 2013, Linear mixed-effects models using S4 classes
   Bauman AG, 2014, MAR ECOL PROG SER, V499, P115, DOI 10.3354/meps10662
   Bay RA, 2014, CURR BIOL, V24, DOI 10.1016/j.cub.2014.10.044
   Bellantuono AJ, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0050685
   Bellantuono AJ, 2012, P ROY SOC B-BIOL SCI, V279, P1100, DOI 10.1098/rspb.2011.1780
   BENJAMINI Y, 1995, J R STAT SOC B, V57, P289, DOI 10.1111/j.2517-6161.1995.tb02031.x
   Berkelmans R, 2006, P ROY SOC B-BIOL SCI, V273, P2305, DOI 10.1098/rspb.2006.3567
   BLACK NA, 1995, BIOL BULL, V188, P234, DOI 10.2307/1542301
   Breslin T, 2004, BMC BIOINFORMATICS, V5, DOI 10.1186/1471-2105-5-193
   Buddemeier RW, 2004, CORAL HEALTH AND DISEASE, P427
   Burt J, 2008, MAR BIOL, V154, P27, DOI 10.1007/s00227-007-0892-9
   Burt J, 2011, MAR ENVIRON RES, V72, P225, DOI 10.1016/j.marenvres.2011.08.005
   Carpenter KE, 2008, SCIENCE, V321, P560, DOI 10.1126/science.1159196
   Cavrak VV, 2014, PLOS GENET, V10, DOI 10.1371/journal.pgen.1004115
   Coles SL, 2013, MAR POLLUT BULL, V72, P323, DOI 10.1016/j.marpolbul.2012.09.006
   Collin R, 2016, ECOL EVOL, V6, P5623, DOI 10.1002/ece3.2317
   Crowder CM, 2017, MOL ECOL, V26, P3913, DOI 10.1111/mec.14162
   Császár NBM, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0009751
   D'Angelo C, 2015, ISME J, V9, P2551, DOI 10.1038/ismej.2015.80
   Desalvo MK, 2008, MOL ECOL, V17, P3952, DOI 10.1111/j.1365-294X.2008.03879.x
   Dixon GB, 2015, SCIENCE, V348, P1460, DOI 10.1126/science.1261224
   Doney SC, 2012, ANNU REV MAR SCI, V4, P11, DOI 10.1146/annurev-marine-041911-111611
   Falconer D.S., 1996, Quantitative Genetics
   Gates RD, 1999, AM ZOOL, V39, P30
   Gattuso JP, 2015, SCIENCE, V349, DOI 10.1126/science.aac4722
   Gillis J, 2010, NAT PROTOC, V5, P1148, DOI 10.1038/nprot.2010.78
   Grabherr MG, 2011, NAT BIOTECHNOL, V29, P644, DOI 10.1038/nbt.1883
   Graham EM, 2008, CORAL REEFS, V27, P529, DOI 10.1007/s00338-008-0361-z
   Hadfield JD, 2010, J STAT SOFTW, V33, P1, DOI 10.18637/jss.v033.i02
   Haryanti D, 2015, J MAR SCI ENG, V3, P509, DOI 10.3390/jmse3030509
   Hoegh-Guldberg O, 2008, SCIENCE, V321, P345, DOI 10.1126/science.1157897
   Hoegh-Guldberg O, 2007, SCIENCE, V318, P1737, DOI 10.1126/science.1152509
   Hoegh-Guldberg O, 2010, SCIENCE, V328, P1523, DOI 10.1126/science.1189930
   Hoey AS, 2016, DIVERSITY-BASEL, V8, DOI 10.3390/d8020012
   Howells EJ, 2014, SCI REP-UK, V4, DOI 10.1038/srep07484
   Howells EJ, 2016, GLOBAL CHANGE BIOL, V22, P2702, DOI 10.1111/gcb.13250
   Hume BCC, 2015, SCI REP-UK, V5, DOI 10.1038/srep08562
   Ito H, 2013, GENE, V518, P256, DOI 10.1016/j.gene.2013.01.034
   Kaniewska P, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0139223
   Karin Meyer, 2007, Journal of Zhejiang University-Science B, V8, P815, DOI 10.1631/jzus.2007.B0815
   Kelley LA, 2015, NAT PROTOC, V10, P845, DOI 10.1038/nprot.2015.053
   Kenkel CD, 2013, MOL ECOL, V22, P4335, DOI 10.1111/mec.12391
   Kenkel CD, 2017, NAT ECOL EVOL, V1, DOI 10.1038/s41559-016-0014
   KINSMAN DJJ, 1964, NATURE, V202, P1280, DOI 10.1038/2021280a0
   Kitchen SA, 2015, G3-GENES GENOM GENET, V5, P2441, DOI 10.1534/g3.115.020164
   Kleypas JA, 1999, AM ZOOL, V39, P146
   Kleypas JA, 2016, GLOBAL CHANGE BIOL, V22, P3539, DOI 10.1111/gcb.13347
   Lee HK, 2005, BMC BIOINFORMATICS, V6, DOI 10.1186/1471-2105-6-269
   Li G, 2009, J CELL BIOL, V186, P783, DOI 10.1083/jcb.200904060
   Logan CA, 2014, GLOBAL CHANGE BIOL, V20, P125, DOI 10.1111/gcb.12390
   Love MI, 2014, GENOME BIOL, V15, DOI 10.1186/s13059-014-0550-8
   Lundgren P, 2013, BMC GENET, V14, DOI 10.1186/1471-2156-14-9
   Mangubhai S, 2008, CORAL REEFS, V27, P117, DOI 10.1007/s00338-007-0297-8
   Mansour TA, 2016, GIGASCIENCE, V5, DOI 10.1186/s13742-016-0138-1
   Marioni JC, 2008, GENOME RES, V18, P1509, DOI 10.1101/gr.079558.108
   Masuta Y, 2018, BREEDING SCI, V68, P168, DOI 10.1270/jsbbs.17085
   Maynard JA, 2008, MAR BIOL, V155, P173, DOI 10.1007/s00227-008-1015-y
   Meyer E, 2011, MOL ECOL, V20, P3599, DOI 10.1111/j.1365-294X.2011.05205.x
   Meyer E, 2009, MAR ECOL PROG SER, V392, P81, DOI 10.3354/meps08208
   Meyer E, 2009, BMC GENOMICS, V10, DOI 10.1186/1471-2164-10-219
   Middlebrook R, 2008, J EXP BIOL, V211, P1050, DOI 10.1242/jeb.013284
   Miller KJ, 2008, J ANIM ECOL, V77, P713, DOI 10.1111/j.1365-2656.2008.01387.x
   Mkrtchian S, 1998, EUR J BIOCHEM, V251, P304, DOI 10.1046/j.1432-1327.1998.2510304.x
   Munday PL, 2013, ECOL LETT, V16, P1488, DOI 10.1111/ele.12185
   O'Connor MI, 2012, GLOBAL ECOL BIOGEOGR, V21, P693, DOI 10.1111/j.1466-8238.2011.00713.x
   Oliver TA, 2011, CORAL REEFS, V30, P429, DOI 10.1007/s00338-011-0721-y
   Palumbi SR, 2014, SCIENCE, V344, P895, DOI 10.1126/science.1251336
   Parra G, 2009, NUCLEIC ACIDS RES, V37, P289, DOI 10.1093/nar/gkn916
   Peck LS, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0066033
   Pietzenuk B, 2016, GENOME BIOL, V17, DOI 10.1186/s13059-016-1072-3
   Pinzón JH, 2015, ROY SOC OPEN SCI, V2, DOI 10.1098/rsos.140214
   Polato NR, 2013, MOL ECOL, V22, P1366, DOI 10.1111/mec.12163
   Portune KJ, 2010, MAR GENOM, V3, P51, DOI 10.1016/j.margen.2010.03.002
   Putnam HM, 2015, J EXP BIOL, V218, P2365, DOI 10.1242/jeb.123018
   Putnam HM, 2010, INVERTEBR BIOL, V129, P199, DOI 10.1111/j.1744-7410.2010.00199.x
   Rich JT, 2010, OTOLARYNG HEAD NECK, V143, P331, DOI 10.1016/j.otohns.2010.05.007
   Richardson AJ, 2012, BIOL LETTERS, V8, P907, DOI 10.1098/rsbl.2012.0530
   Riegl BM, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0024802
   Rose NH, 2016, GENOME BIOL EVOL, V8, P243, DOI 10.1093/gbe/evv258
   Rosic N, 2014, BMC GENOMICS, V15, DOI 10.1186/1471-2164-15-1052
   Ruiz-Jones LJ, 2017, SCI ADV, V3, DOI 10.1126/sciadv.1601298
   Rumble SM, 2009, PLOS COMPUT BIOL, V5, DOI 10.1371/journal.pcbi.1000386
   Sahoo SK, 2008, MOL CELLS, V26, P265
   Scheffers BR, 2016, SCIENCE, V354, DOI 10.1126/science.aaf7671
   Schoepf V, 2015, SCI REP-UK, V5, DOI 10.1038/srep17639
   Seneca FO, 2015, MOL ECOL, V24, P1467, DOI 10.1111/mec.13125
   SHEPPARD CRC, 1993, MAR POLLUT BULL, V27, P3, DOI 10.1016/0025-326X(93)90003-3
   Silverstein RN, 2015, GLOBAL CHANGE BIOL, V21, P236, DOI 10.1111/gcb.12706
   Smith EG, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0180169
   Thomas L, 2017, GLOBAL CHANGE BIOL, V23, P2197, DOI 10.1111/gcb.13639
   Thompson DM, 2009, P ROY SOC B-BIOL SCI, V276, P2893, DOI 10.1098/rspb.2009.0591
   Traylor-Knowles N, 2017, BIOL BULL-US, V232, P91, DOI 10.1086/692717
   Van Oppen MJH, 2017, GLOBAL CHANGE BIOL, V23, P3437, DOI 10.1111/gcb.13647
   van Oppen MJH, 2015, P NATL ACAD SCI USA, V112, P2307, DOI 10.1073/pnas.1422301112
   van Woesik R, 2012, ECOL EVOL, V2, P2474, DOI 10.1002/ece3.363
   Veron JEN, 2009, MAR POLLUT BULL, V58, P1428, DOI 10.1016/j.marpolbul.2009.09.009
   Visscher PM, 2008, NAT REV GENET, V9, P255, DOI 10.1038/nrg2322
   Voolstra CR, 2009, BMC GENOMICS, V10, DOI 10.1186/1471-2164-10-627
   Wang S, 2012, NAT METHODS, V9, P808, DOI [10.1038/NMETH.2023, 10.1038/nmeth.2023]
   Webster N, 2013, MOL ECOL, V22, P1854, DOI 10.1111/mec.12213
   Wilson AJ, 2010, J ANIM ECOL, V79, P13, DOI 10.1111/j.1365-2656.2009.01639.x
   Wilson JR, 1998, MAR BIOL, V131, P339, DOI 10.1007/s002270050327
   Yuyama I, 2012, J EXP MAR BIOL ECOL, V430, P17, DOI 10.1016/j.jembe.2012.06.020
NR 110
TC 44
Z9 46
U1 2
U2 67
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 DEC
PY 2018
VL 27
IS 24
BP 5180
EP 5194
DI 10.1111/mec.14934
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 HF9ZD
UT WOS:000454600500016
PM 30411823
OA Green Submitted
DA 2025-01-10
ER

PT J
AU Chevuturi, A
   Klingaman, NP
   Turner, AG
   Hannah, S
AF Chevuturi, Amulya
   Klingaman, Nicholas P.
   Turner, Andrew G.
   Hannah, Shaun
TI Projected Changes in the Asian-Australian Monsoon Region in 1.5°C and
   2.0°C Global-Warming Scenarios
SO EARTHS FUTURE
LA English
DT Article
DE Climate Change; Precipitation; Temperature; +1; 5{degree sign}C Warming;
   Asian-Australian Monsoon Region; +2; 0{degree sign}C Warming
ID FUTURE CLIMATE-CHANGE; 1.5 DEGREES-C; EXTREME PRECIPITATION;
   VARIABILITY; MODEL; RESPONSES; IMPACTS; RISK
AB In light of the Paris Agreement, it is essential to identify regional impacts of half a degree additional global warming to inform climate adaptation and mitigation strategies. We investigate the effects of 1.5 degrees C and 2.0 degrees C global warming above preindustrial conditions, relative to present day (2006-2015), over the Asian-Australian monsoon region (AAMR) using five models from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project. There is considerable intermodel variability in projected changes to mean climate and extreme events in 2.0 degrees C and 1.5 degrees C scenarios. There is high confidence in projected increases to mean and extreme surface temperatures over AAMR, as well as more-frequent persistent daily temperature extremes over East Asia, Australia, and northern India with an additional 0.5 degrees C warming, which are likely to occur. Mean and extreme monsoon precipitation amplify over AAMR, except over Australia at 1.5 degrees C where there is uncertainty in the sign of the change. Persistent daily extreme precipitation events are likely to become more frequent over parts of East Asia and India with an additional 0.5 degrees C warming. There is lower confidence in projections of precipitation change than in projections of surface temperature change. These results highlight the benefits of limiting the global-mean temperature change to 1.5 degrees C above preindustrial, as the severity of the above effects increases with an extra 0.5 degrees C warming.
C1 [Chevuturi, Amulya; Klingaman, Nicholas P.; Turner, Andrew G.] Univ Reading, NCAS Climate, Reading, Berks, England.
   [Chevuturi, Amulya; Klingaman, Nicholas P.; Turner, Andrew G.; Hannah, Shaun] Univ Reading, Dept Meteorol, Reading, Berks, England.
C3 UK Research & Innovation (UKRI); Natural Environment Research Council
   (NERC); NERC National Centre for Atmospheric Science; University of
   Reading; University of Reading
RP Chevuturi, A (corresponding author), Univ Reading, NCAS Climate, Reading, Berks, England.; Chevuturi, A (corresponding author), Univ Reading, Dept Meteorol, Reading, Berks, England.
EM a.chevuturi@reading.ac.uk
RI Turner, Andrew/D-2286-2009; Klingaman, Nicholas/H-4610-2012; Chevuturi,
   Amulya/P-5212-2016
OI Chevuturi, Amulya/0000-0003-2815-7221; Turner,
   Andrew/0000-0002-0642-6876
FU UK-China Research and Innovation Partnership Fund, through the Met
   Office Climate Science for Service Partnership (CSSP) China as part of
   the Newton Fund; NERC REAL Projections project [NE/N018591/1]; UK
   Natural Environment Research Council [NE/L010976/1]; Office of Science
   of the U.S. Department of Energy [DE-AC02-05CH11231]; NERC [ncas10008,
   NE/R015244/1, ncas10005, NE/N018591/1, ncas10003, NE/L010976/1] Funding
   Source: UKRI
FX A.C. and A.G.T. were supported by the UK-China Research and Innovation
   Partnership Fund, through the Met Office Climate Science for Service
   Partnership (CSSP) China, as part of the Newton Fund. A.G.T. was
   additionally supported by the NERC REAL Projections project
   (NE/N018591/1). N.P.K. was supported by an Independent Research
   Fellowship from the UK Natural Environment Research Council
   (NE/L010976/1). The authors thank the HAPPI project team and the
   modeling centers who contributed simulations. This research used science
   gateway resources of the National Energy Research Scientific Computing
   Center, a DOE Office of Science User Facility supported by the Office of
   Science of the U.S. Department of Energy under contract no.
   DE-AC02-05CH11231. HAPPI simulation data can be accessed at
   http://portal.nersc.gov/c20c/data/. ERA-Interim is available from the
   ECMWF archive (http://apps.ecmwf.int/datasets/data/interim-full-daily).
   GPCP data is available at
   https://www.esrl.noaa.gov/psd/data/gridded/data.gpcp.html. The HadCRUT4
   data is available from https://crudata.uea.ac.uk/cru/data/temperature/.
CR Adler RF, 2003, J HYDROMETEOROL, V4, P1147, DOI 10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2
   Alexander LV, 2009, INT J CLIMATOL, V29, P417, DOI 10.1002/joc.1730
   Allan RP, 2008, SCIENCE, V321, P1481, DOI 10.1126/science.1160787
   Allen MR, 2002, NATURE, V419, P224, DOI 10.1038/nature01092
   [Anonymous], CONTRIBUTION WORKING, DOI [DOI 10.1017/CBO9781107415324, 10.1017/CBO9781107415324]
   Bentsen M, 2013, GEOSCI MODEL DEV, V6, P687, DOI 10.5194/gmd-6-687-2013
   Brown JR, 2017, GEOPHYS RES LETT, V44, P5683, DOI 10.1002/2017GL073217
   Burke C, 2017, J CLIMATE, V30, P5205, DOI [10.1175/JCLI-D-16-0892.1, 10.1175/jcli-d-16-0892.1]
   Cherchi A, 2011, CLIM DYNAM, V37, P83, DOI 10.1007/s00382-010-0801-7
   Christensen JH, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1217
   Collins M, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1029
   Dee DP, 2011, Q J ROY METEOR SOC, V137, P553, DOI 10.1002/qj.828
   Emori S, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL023272
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Hallegatte S, 2016, NAT CLIM CHANGE, V6, P663, DOI 10.1038/NCLIMATE3057
   He B, 2016, CLIM DYNAM, V46, P2897, DOI 10.1007/s00382-015-2739-2
   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]
   Hijioka Y, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1327
   Hirabayashi Y, 2013, NAT CLIM CHANGE, V3, P816, DOI [10.1038/nclimate1911, 10.1038/NCLIMATE1911]
   Hsu PC, 2016, SPRINGER CLIMATE, P7, DOI 10.1007/978-3-319-21650-8_2
   Hsu PC, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2012GL051037
   Hu ZZ, 2000, GEOPHYS RES LETT, V27, P2681, DOI 10.1029/2000GL011550
   HULME M, 1994, INT J CLIMATOL, V14, P637, DOI 10.1002/joc.3370140604
   Hulme M, 2016, NAT CLIM CHANGE, V6, P222, DOI 10.1038/nclimate2939
   Im ES, 2017, SCI ADV, V3, DOI 10.1126/sciadv.1603322
   Irving DB, 2012, AUST METEOROL OCEAN, V62, P211
   Iversen T, 2013, GEOSCI MODEL DEV, V6, P389, DOI 10.5194/gmd-6-389-2013
   James R, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.457
   James R, 2014, NAT CLIM CHANGE, V4, P938, DOI 10.1038/nclimate2411
   Jourdain NC, 2013, CLIM DYNAM, V41, P3073, DOI 10.1007/s00382-013-1676-1
   King AD, 2017, NAT CLIM CHANGE, V7, P412, DOI [10.1038/NCLIMATE3296, 10.1038/nclimate3296]
   Kirkevåg A, 2013, GEOSCI MODEL DEV, V6, P207, DOI 10.5194/gmd-6-207-2013
   Kitoh A, 2013, J GEOPHYS RES-ATMOS, V118, P3053, DOI 10.1002/jgrd.50258
   Knutti R, 2016, NAT GEOSCI, V9, P13, DOI 10.1038/NGEO2595
   Lee JW, 2014, CLIM DYNAM, V42, P733, DOI 10.1007/s00382-013-1841-6
   Lewis SC, 2017, GEOPHYS RES LETT, V44, P9947, DOI 10.1002/2017GL074612
   Lobell DB, 2012, NAT CLIM CHANGE, V2, P186, DOI [10.1038/NCLIMATE1356, 10.1038/nclimate1356]
   May W, 2011, CLIM DYNAM, V37, P1843, DOI 10.1007/s00382-010-0942-8
   McCarthy MP, 2010, GEOPHYS RES LETT, V37, DOI 10.1029/2010GL042845
   Menon A, 2013, EARTH SYST DYNAM, V4, P287, DOI 10.5194/esd-4-287-2013
   Milly PCD, 2002, NATURE, V415, P514, DOI 10.1038/415514a
   Mitchell D, 2017, GEOSCI MODEL DEV, V10, P571, DOI 10.5194/gmd-10-571-2017
   Mitchell D, 2016, NAT CLIM CHANGE, V6, P735, DOI 10.1038/nclimate3055
   Morice CP, 2012, J GEOPHYS RES-ATMOS, V117, DOI 10.1029/2011JD017187
   Neale RB, 2013, J CLIMATE, V26, P5150, DOI 10.1175/JCLI-D-12-00236.1
   Patz JA, 2005, NATURE, V438, P310, DOI 10.1038/nature04188
   Pendergrass AG, 2015, GEOPHYS RES LETT, V42, P8767, DOI 10.1002/2015GL065854
   Pepin N, 2015, NAT CLIM CHANGE, V5, P424, DOI [10.1038/nclimate2563, 10.1038/NCLIMATE2563]
   Reichler T, 2008, B AM METEOROL SOC, V89, P303, DOI 10.1175/BAMS-89-3-303
   Reick CH, 2013, J ADV MODEL EARTH SY, V5, P459, DOI 10.1002/jame.20022
   Reisinger A, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1371
   Rogelj J, 2016, NATURE, V534, P631, DOI 10.1038/nature18307
   Rogelj J, 2016, NAT GEOSCI, V9, P187, DOI 10.1038/ngeo2668
   Sandeep S, 2014, CLIM DYNAM, V43, P103, DOI 10.1007/s00382-014-2135-3
   Schleussner C.-F., 2015, Earth System Change: Climate Scenarios, V6, P2447, DOI [10.5194/esdd-6-2447-2015, DOI 10.5194/ESDD-6-2447-2015]
   Schneider T, 2010, REV GEOPHYS, V48, DOI 10.1029/2009RG000302
   Seneviratne SI, 2016, NATURE, V529, P477, DOI 10.1038/nature16542
   Seneviratne SI, 2012, MANAGING THE RISKS OF EXTREME EVENTS AND DISASTERS TO ADVANCE CLIMATE CHANGE ADAPTATION, P109
   Shiogama H, 2014, SOLA, V10, P122, DOI 10.2151/sola.2014-025
   Sillmann J, 2017, GEOPHYS RES LETT, V44, P6383, DOI 10.1002/2017GL073229
   Soden BJ, 2006, J CLIMATE, V19, P3354, DOI [10.1175/JCLI3799.1, 10.1175/JCLI3990.1]
   Sperber K, 2013, CLIM DYNAM, V41, P2711, DOI 10.1007/s00382-012-1607-6
   Sperber K. R., 2017, GLOBAL MONSOON SYSTE, P79
   Stevens B, 2013, J ADV MODEL EARTH SY, V5, P146, DOI 10.1002/jame.20015
   Tokinaga H, 2012, NATURE, V491, P439, DOI 10.1038/nature11576
   Turner AG, 2009, ATMOS SCI LETT, V10, P152, DOI 10.1002/asl.223
   Turner AG, 2012, NAT CLIM CHANGE, V2, P587, DOI 10.1038/NCLIMATE1495
   United Nations, 2015, PAR AGR
   Vecchi GA, 2006, NATURE, V441, P73, DOI 10.1038/nature04744
   von Salzen K, 2013, ATMOS OCEAN, V51, P104, DOI 10.1080/07055900.2012.755610
   Wang B, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL022734
   Wang B, 2004, J CLIMATE, V17, P803, DOI 10.1175/1520-0442(2004)017<0803:ESOAMV>2.0.CO;2
   Wang B, 2014, CLIM DYNAM, V42, P83, DOI 10.1007/s00382-013-1769-x
   Wang B, 2012, CLIM DYNAM, V39, P1123, DOI 10.1007/s00382-011-1266-z
   Wang GJ, 2017, NAT CLIM CHANGE, V7, P568, DOI [10.1038/nclimate3351, 10.1038/NCLIMATE3351]
   Watanabe M, 2010, J CLIMATE, V23, P6312, DOI 10.1175/2010JCLI3679.1
   World Climate Research Programme, 2017, GLOB MONS SYST
   Zhang HQ, 2010, CLIM DYNAM, V35, P601, DOI 10.1007/s00382-009-0620-x
   Zhou TJ, 2009, CLIM DYNAM, V33, P1051, DOI 10.1007/s00382-008-0501-8
NR 79
TC 69
Z9 74
U1 1
U2 36
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 MAR
PY 2018
VL 6
IS 3
BP 339
EP 358
DI 10.1002/2017EF000734
PG 20
WC Environmental Sciences; Geosciences, Multidisciplinary; Meteorology &
   Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Geology; Meteorology & Atmospheric
   Sciences
GA GD0ED
UT WOS:000430171600005
OA Green Accepted, gold
DA 2025-01-10
ER

PT J
AU Hebda, AM
   Wachowiak, W
   Skrzyszewski, J
AF Hebda, Anna Maria
   Wachowiak, Witold
   Skrzyszewski, Jerzy
TI Long-term growth performance and productivity of Scots pine (<i>Pinus
   sylvestris</i> L.) populations
SO ACTA SOCIETATIS BOTANICORUM POLONIAE
LA English
DT Article
DE quantitative traits; quality traits; local adaptation; forest trees
ID CLIMATIC ADAPTATION; PROVENANCES; RESPONSES; DYNAMICS; TREES
AB The phenotypic differentiation of 16 provenances of Scots pine originating from a wide variety of habitats that range from lowland to southern highland locations in Poland was assessed during 47 years of their growth and development in the Carpathian Mountains. The traits, including height, diameter at breast height, stem straightness, and crown width, were used to evaluate the differentiation of the provenances in their juvenile period and at maturity and were examined for patterns of local adaptation. The populations from northern Poland were characterized by the best growth and productivity, whereas provenances from central Poland had the best stem quality. There were some changes in growth between provenances observed during the experiment, but the stand volume (m(3)/ha) in juvenile trees was closely correlated with that in mature trees (r = 0.979). There was a positive relationship between the productivity and the environmental conditions of the geographical origin of provenances with increasing values for the trees' productivity from south to north. Additionally, the elevation above sea level of the original populations was inversely correlated with the growth achieved by the progeny. In general, most populations from the species distribution range in Poland tested in the severe climate conditions of the Carpathian Mountains showed good growth performance under that environment, characterized by low temperatures and short growing periods. Provenances from climatic zones outside mountain regions demonstrated great growth and productivity, which proved to be the most important for competitively outperforming the local populations. Our study demonstrates good adaptive potential of the tested provenances, as selection will favor fast-growing genotypes under the predicted environmental change scenario.
C1 [Hebda, Anna Maria] Agr Univ Krakow, Fac Forestry, Inst Forest Ecol & Silviculture, Dept Genet & Forest Tree Breeding, 29 Listopada 46, PL-31425 Krakow, Poland.
   [Wachowiak, Witold] Polish Acad Sci, Inst Dendrol, Parkowa 5, PL-62035 Kornik, Poland.
   [Wachowiak, Witold] Adam Mickiewicz Univ, Fac Biol, Inst Environm Biol, Umultowska 89, PL-61614 Poznan, Poland.
   [Skrzyszewski, Jerzy] Agr Univ Krakow, Fac Forestry, Inst Forest Ecol & Silviculture, Dept Silviculture, 29 Listopada 46, PL-31425 Krakow, Poland.
C3 University of Agriculture in Krakow; Polish Academy of Sciences; Adam
   Mickiewicz University; University of Agriculture in Krakow
RP Hebda, AM (corresponding author), Agr Univ Krakow, Fac Forestry, Inst Forest Ecol & Silviculture, Dept Genet & Forest Tree Breeding, 29 Listopada 46, PL-31425 Krakow, Poland.
EM a.hebda@ur.krakow.pl
RI Hebda, Anna/IAP-0741-2023
OI Wachowiak, Witold/0000-0003-2898-3523; Hebda, Anna/0000-0002-3149-8644
FU Polish Ministry of Science and Higher Education [3405/ZGNiSzL/10-14,
   4425/ZGNiSzL/12-14]; Polish National Science Centre
   [DEC-2012/05/E/NZ9/03476]; Institute of Dendrology, Polish Academy of
   Sciences
FX The research was partly supported by the Polish Ministry of Science and
   Higher Education (grants Nos. 3405/ZGNiSzL/10-14 and
   4425/ZGNiSzL/12-14). WW acknowledges financial support from the Polish
   National Science Centre (grant No. DEC-2012/05/E/NZ9/03476) and the
   Institute of Dendrology, Polish Academy of Sciences.
CR Aitken SN, 2008, EVOL APPL, V1, P95, DOI 10.1111/j.1752-4571.2007.00013.x
   [Anonymous], SILVAE GENET
   [Anonymous], ELEMENTY GENETYKI HO
   [Anonymous], 2016, SERWIS KLIMATYCZNY
   Barzdajn W., 2006, Sylwan, V150, P8
   Barzdajn W, 2000, SYLWAN, V6, P41
   Barzdajn W., 2008, Sylwan, V4, P21
   Barzdajn W, 2008, SYLWAN, V152, P52
   Barzdajn W, 2016, DENDROBIOLOGY, V75, P67, DOI 10.12657/denbio.075.007
   Boratyski A., 1993, BIOL SOSNY ZWYCZAJNE, P45, DOI DOI 10.1038/NATURE02403
   Bruchwald A., 1996, Folia Forestalia Polonica. Seria A, Lesnictwo, P5
   Ceitel J, 2004, SERIA BIOL, V69, P275
   Chodzicki E., 1975, LESNICTWO, V11, P23, DOI [10.1038/ncomms5967, DOI 10.1038/NCOMMS5967]
   Davis MB, 2005, ECOLOGY, V86, P1704, DOI 10.1890/03-0788
   Eriksson G., 2008, PINUS SYLVESTRIS REC, DOI [10.1111/j.1469-8137.1992.tb01806.x, DOI 10.1111/J.1469-8137.1992.TB01806.X]
   Falconer D.S., 1996, Quantitative Genetics
   GIERTYCH M, 1979, SILVAE GENET, V28, P136
   GIERTYCH M, 1992, SILVAE GENET, V41, P133
   Giertych M., 1993, BIOL SOSNY ZWYCZAJNE, P325
   González-Martínez SC, 2006, GENETICS, V172, P1915, DOI 10.1534/genetics.105.047126
   Gunia S, 1978, WYBRANE ZAGADNIENIA, DOI [10.1139/x97-052, DOI 10.1139/X97-052]
   Helama S, 2013, DENDROBIOLOGY, V70, P27, DOI 10.12657/denbio.070.003
   Hess M., 1965, PIETRA KLIMATYCZNE P, V115
   Howe GT, 2003, CAN J BOT, V81, P1247, DOI [10.1139/b03-141, 10.1139/B03-141]
   Hurme P, 1997, CAN J FOREST RES, V27, P716, DOI 10.1139/cjfr-27-5-716
   Jump AS, 2005, ECOL LETT, V8, P1010, DOI 10.1111/j.1461-0248.2005.00796.x
   Li Hui-yu, 2005, Journal of Forestry Research (Harbin), V16, P216, DOI 10.1007/BF02856818
   Lindgren D., 1997, IUFRO World Series, V6, P73
   Matras J., 2006, ELEMENTY GENETYKI HO, P143
   Matyas C, 1996, EUPHYTICA, V92, P45, DOI 10.1007/BF00022827
   Naydenov KD, 2005, BIOCHEM SYST ECOL, V33, P1226, DOI 10.1016/j.bse.2005.07.011
   Oleksyn J., 1994, Sylwan, V138, P57
   Oleksyn J, 2000, TREE PHYSIOL, V20, P837
   OLEKSYN J, 1992, NEW PHYTOL, V120, P561, DOI 10.1111/j.1469-8137.1992.tb01806.x
   Oleksyn J, 2001, FOREST ECOL MANAG, V148, P207, DOI 10.1016/S0378-1127(00)00537-5
   OLEKSYN J, 1994, CAN J FOREST RES, V24, P2390, DOI 10.1139/x94-308
   Pretzsch H, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms5967
   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
   REICH PB, 1994, CAN J FOREST RES, V24, P306, DOI 10.1139/x94-044
   Sabor J., 1993, ZMIENNOSC SOSNY ZWYC
   Savolainen O, 2007, ANNU REV ECOL EVOL S, V38, P595, DOI 10.1146/annurev.ecolsys.38.091206.095646
   Shutyaev AM, 2000, SILVAE GENET, V49, P137
   Skrzyszewski J., 2004, CHARAKTERYSTYKA MORF
   Staszkiewicz J., 1993, Biologia sosny zwyczajnej, P33
   StatSoft, 2011, Statistica (data analysis software system)
   Stephan BR, 1996, SILVAE GENET, V45, P342
   Szeligowski H, 2016, SYLWAN, V160, P230
   White T. L., 2007, Forest genetics, DOI 10.1079/9781845932855.0000
   Wilczynski SB, 2013, EUR J FOREST RES, V132, P919, DOI 10.1007/s10342-013-0731-0
   Wright IJ, 2004, NATURE, V428, P821, DOI 10.1038/nature02403
NR 51
TC 6
Z9 6
U1 0
U2 1
PU POLSKIE TOWARZYSTWO BOTANICZNE
PI WARSAW
PA AL UJAZDOWSKIE 4, 00-478 WARSAW, POLAND
SN 0001-6977
EI 2083-9480
J9 ACTA SOC BOT POL
JI Acta Soc. Bot. Pol.
PY 2017
VL 86
IS 1
AR 3521
DI 10.5586/asbp.3521
PG 16
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA GN7JG
UT WOS:000439311400001
OA gold
DA 2025-01-10
ER

PT J
AU Phillipson, MC
   Emmanuel, R
   Baker, PH
AF Phillipson, Mark C.
   Emmanuel, Rohinton
   Baker, Paul H.
TI The durability of building materials under a changing climate
SO WILEY INTERDISCIPLINARY REVIEWS-CLIMATE CHANGE
LA English
DT Article
ID STOCHASTIC WEATHER GENERATORS; SERVICE LIFE; RAIN INDEX; IMPACT; RISK
AB Weathering of materials leads to degradation of the fabric of buildings which if left unchecked will lead to an increase in the rate, and possibly severity, of degradation. Adjustments to maintenance regimes could accommodate marginal changes to degradation rate. However, for significant increases in degradation rate, adaptations may be required. Globally, any new deterioration mechanisms are unlikely. However, in the future previously insignificant problems may start to become significant at a local level, for which there is a lack of local knowledge or experience. Adaptation in the context of existing buildings is a means to further protect the existing fabric, to consolidate performance and control the rate of deterioration. This adaptation goes beyond the scope of enhanced maintenance. For historic buildings, there will be tension between the need to conserve the building and simultaneously adapt in the face of increased climate change driven weathering. Impact studies are needed to identify priorities for adaptation by identifying the scale and impact of degradation-related defects for the future building stock. Such studies need to be integrated with authoritative information on projected future climate. Adaptation of building design is needed to ensure new buildings consider performance in both current and future climates. A whole-life approach to building design is needed. To achieve this building standards, building codes need to be developed which consider future climate design. Traditional vernacular styles may offer an opportunity for learning design lessons and adapting design practices that could help facilitate appropriate climate protection. WIREs Clim Change 2016, 7:590-599. doi: 10.1002/wcc.398 For further resources related to this article, please visit the .
C1 [Phillipson, Mark C.; Emmanuel, Rohinton; Baker, Paul H.] Glasgow Caledonian Univ, Sch Engn & Built Environm, Glasgow, Lanark, Scotland.
C3 Glasgow Caledonian University
RP Phillipson, MC (corresponding author), Glasgow Caledonian Univ, Sch Engn & Built Environm, Glasgow, Lanark, Scotland.
EM Mark.phillipson@gcu.ac.uk
RI Emmanuel, Rohinton/H-6313-2019
OI Emmanuel, Rohinton/0000-0002-3726-5892
CR Abu Bakar B.H., 2011, INT J INTEGR ENGINNE, V1, P111
   Addleson L., 1991, Performance of Material in Building
   Adger WN, 2005, GLOBAL ENVIRON CHANG, V15, P77, DOI [10.1016/j.gloenvcha.2005.03.001, 10.1016/j.gloenvcha.2004.12.005]
   Ahzahar N., 2011, PROCEDIA ENG 2 INT B, P249, DOI DOI 10.1016/J.PR0ENG.2011.11.162
   Almås AJ, 2011, BUILD RES INF, V39, P227, DOI 10.1080/09613218.2011.562025
   [Anonymous], 2005, Availability and Affordability of Insurance under Climate Change: A Growing Challenge for the US
   [Anonymous], 2017, CLIMATE CHANGE IMPAC
   Blocken BJE, 2010, EFFECT CLIMATE CHANG
   Boyd DW, 1963, 398 NAT RES COUNC CA
   BRE, 2002, 262 BRE
   Brimblecombe P., 2011, TERRA 2008 10 INT C, P278
   British Standards, 2014, 55342014 BS
   Brunskill R.W., 1978, Illustrated handbook of vernacular architecture
   BUTLIN RN, 1990, P ROY SOC EDINB B, V97, P255, DOI 10.1017/S0269727000005376
   Cabrera JG, 1996, CEMENT CONCRETE COMP, V18, P47, DOI 10.1016/0958-9465(95)00043-7
   Capon R., 2012, Climate Change Risk Assessment for the Built Environment Sector
   CASSAR M, 2007, ENG HIST FUTURES STA
   CASSAR M., 2005, CLIMATE CHANGE HIST
   Chand I, 2002, BUILD ENVIRON, V37, P549, DOI 10.1016/S0360-1323(01)00057-9
   Chaochanchaikul K, 2013, EXPRESS POLYM LETT, V7, P146, DOI 10.3144/expresspolymlett.2013.14
   Douglas J., 2013, Understanding building failures
   El-Dash K, 2011, J ASIAN ARCHIT BUILD, V10, P211, DOI 10.3130/jaabe.10.211
   Emmitt S, 2009, PRINCIPLES ARCHITECT
   European Commission, 2010, OFF J EUR UNION, V23
   Flourentzou F, 2000, ENERG BUILDINGS, V31, P167, DOI 10.1016/S0378-7788(99)00031-6
   Forster A. M., 2015, Structural Survey, V33, P52, DOI 10.1108/SS-03-2014-0013
   Forster AM, 2011, BUILD RES INF, V39, P654, DOI 10.1080/09613218.2011.621345
   Garvin SL, 1998, CONSTR BUILD MATER, V12, P289, DOI 10.1016/S0950-0618(98)00008-7
   Goudie AS, 1997, SALT WEATHERING HAZA, P256
   Graves H.M., 2000, Potential implications of climate change in the built environment
   Hamin EM, 2009, HABITAT INT, V33, P238, DOI 10.1016/j.habitatint.2008.10.005
   Haque N, 2011, DELAMINATION IN WOOD, WOOD PRODUCTS AND WOOD-BASED COMPOSITES, P197, DOI 10.1007/978-90-481-9550-3_10
   Heritage E., 2014, CONSERV B, V72, P9
   Holmes MJ, 2007, ENERG BUILDINGS, V39, P802, DOI 10.1016/j.enbuild.2007.02.009
   Kilsby CG, 2007, ENVIRON MODELL SOFTW, V22, P1705, DOI 10.1016/j.envsoft.2007.02.005
   Krishan A., 2001, Climate responsive architecture: A design handbook for energy efficient buildings
   LACY RE, 1976, DRIVING RAIN INDEX
   Lankester P, 2012, SCI TOTAL ENVIRON, V417, P248, DOI 10.1016/j.scitotenv.2011.12.026
   Liao K, 1998, J ADV MATER-COVINA, V30, P3
   Lourenço PB, 2014, BUILD PATHOL REHABIL, V2, P109, DOI 10.1007/978-3-642-39686-1_4
   Meikle J. L., 1994, Construction Management and Economics, V12, P315, DOI [10.1080/01446199400000041, DOI 10.1080/01446199400000041]
   Mills E, 2005, SCIENCE, V309, P1040, DOI 10.1126/science.1112121
   Milly PCD, 2002, NATURE, V415, P514, DOI 10.1038/415514a
   Mora EP, 2007, BUILD ENVIRON, V42, P1329, DOI 10.1016/j.buildenv.2005.11.004
   Nijland T.G., 2009, HERON, V54, P37
   Nofal M, 2011, EUR J WOOD WOOD PROD, V69, P619, DOI 10.1007/s00107-010-0508-9
   NORDVIK V., 2004, Construction Management and Economics, V22, P765, DOI DOI 10.1080/0144619042000213256
   Palmer TN, 2002, NATURE, V415, P512, DOI 10.1038/415512a
   Prikryl R., 2002, UNDERSTANDING MANAGI
   RIBA, 2007, LOW CARB TOOLK 08 WH
   Richardson B., 2002, DEFECTS DETERIORATIO
   SAUER P, 1987, BUILD ENVIRON, V22, P239, DOI 10.1016/0360-1323(87)90016-3
   SELDEN R, 1987, POLYM TEST, V7, P431, DOI 10.1016/0142-9418(87)90044-4
   Sharma A, 2011, RENEW SUST ENERG REV, V15, P871, DOI 10.1016/j.rser.2010.09.008
   Skalny J., 2002, Modern concrete technology
   Solomon S, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P19
   Steen A., 2003, BUILT HAND VERNACULA
   Tran T., 2013, Optimization of Natural Ventilation Design in Hot and Humid Climates Using Building Energy Simulation
   Uhlig H.H., 2011, UHLIGS CORROSION HDB, V51
   van Hoof J, 2008, BUILD ENVIRON, V43, P1023, DOI 10.1016/j.buildenv.2007.03.004
   Wilks DS, 2012, WIRES CLIM CHANGE, V3, P267, DOI 10.1002/wcc.167
   Wilks DS, 2010, WIRES CLIM CHANGE, V1, P898, DOI 10.1002/wcc.85
   Williams JW, 2007, P NATL ACAD SCI USA, V104, P5738, DOI 10.1073/pnas.0606292104
   Willows R., 2003, UKCIP TECHNICAL REPO
   Wilson E., 2010, SPATIAL PLANNING CLI
   Wong N.H., 2008, TROPICAL URBAN HEAT, V1st
   Wood C, 2004, CONSERVATION B, V45, P38
NR 67
TC 22
Z9 24
U1 2
U2 15
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1757-7780
EI 1757-7799
J9 WIRES CLIM CHANGE
JI Wiley Interdiscip. Rev.-Clim. Chang.
PD JUL-AUG
PY 2016
VL 7
IS 4
BP 590
EP 599
DI 10.1002/wcc.398
PG 10
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 DQ3CG
UT WOS:000379079800008
OA Green Accepted
DA 2025-01-10
ER

PT J
AU Preston, BL
   Mustelin, J
   Maloney, MC
AF Preston, Benjamin L.
   Mustelin, Johanna
   Maloney, Megan C.
TI Climate adaptation heuristics and the science/policy divide
SO MITIGATION AND ADAPTATION STRATEGIES FOR GLOBAL CHANGE
LA English
DT Article
DE Adaptation; Climate change; Heuristics; Cognitive reasoning;
   Science-policy interface
ID ADAPTIVE CAPACITY; CHANGE VULNERABILITY; POLICY; GOVERNANCE; RESILIENCE;
   ASSESSMENTS; KNOWLEDGE; FRAMEWORK; ORGANIZATIONS; PERCEPTIONS
AB The adaptation science enterprise has expanded rapidly in recent years, presumably in response to growth in demand for knowledge that can facilitate adaptation policy and practice. However, evidence suggests such investments in adaptation science have not necessarily translated into adaptation implementation. One potential constraint on adaptation may be the underlying heuristics that are used as the foundation for both adaptation research and practice. Here, we explore the adaptation academic literature with the objective of identifying adaptation heuristics, assessing the extent to which they have become entrenched within the adaptation discourse, and discussing potential weaknesses in their framing that could undermine adaptation efforts. This investigation is supported by a multi-method analysis that includes both a quantitative content analysis of the adaptation literature that evidences the use of adaptation heuristics and a qualitative analysis of the implications of such heuristics for enhancing or hindering the implementation of adaptation. Results demonstrate that a number of heuristic devices are commonly used in both the peer-reviewed adaptation literature as well as within grey literature designed to inform adaptation practitioners. Furthermore, the apparent lack of critical reflection upon the robustness of these heuristics for diverse contexts may contribute to potential cognitive bias with respect to the framing of adaptation by both researchers and practitioners. We discuss this phenomenon by drawing upon heuristic-analytic theory, which has explanatory utility in understanding both the origins of such heuristics as well as the measures that can be pursued toward the co-generation of more robust approaches to adaptation problem-solving.
C1 [Preston, Benjamin L.; Maloney, Megan C.] Oak Ridge Natl Lab, Climate Change Sci Inst, Oak Ridge, TN 37831 USA.
   [Preston, Benjamin L.; Maloney, Megan C.] Oak Ridge Natl Lab, Div Environm Sci, Oak Ridge, TN 37831 USA.
   [Mustelin, Johanna] Griffith Univ, Sch Environm, Griffith Climate Change Response Program, Southport, Qld 4222, Australia.
C3 United States Department of Energy (DOE); Oak Ridge National Laboratory;
   United States Department of Energy (DOE); Oak Ridge National Laboratory;
   Griffith University; Griffith University - Gold Coast Campus
RP Preston, BL (corresponding author), Oak Ridge Natl Lab, Climate Change Sci Inst, Bldg 2040,MS 6301,One Bethel Valley Rd,POB 2008, Oak Ridge, TN 37831 USA.
EM prestonbl@ornl.gov; j.mustelin@griffith.edu.au; maloneymc@ornl.gov
RI Nalau, Johanna/V-5692-2018; Preston, Benjamin/B-9001-2012
OI Nalau, Johanna/0000-0001-6581-3967; Preston,
   Benjamin/0000-0002-7966-2386
FU Oak Ridge National Laboratory's Laboratory Directed Research and
   Development Program; U.S. Department of Energy [DE-AC05-00OR22725];
   Griffith University
FX Benjamin Preston and Megan Maloney's contributions to this research were
   sponsored through Oak Ridge National Laboratory's Laboratory Directed
   Research and Development Program. ORNL is managed by UT-Battelle, LLC,
   for the U.S. Department of Energy under contract DE-AC05-00OR22725.
   Johanna Mustelin's contributions were supported through a Griffith
   University Postgraduate Research Scholarship. The authors also
   acknowledge the constructive comments of Richard J.T. Klein on an
   earlier draft of this paper.
CR Adger WN, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P717
   Adger WN, 2009, ADAPTING TO CLIMATE CHANGE: THRESHOLDS, VALUES, GOVERNANCE, P1, DOI 10.1017/CBO9780511596667.002
   Adger WN, 2009, CLIMATIC CHANGE, V93, P335, DOI 10.1007/s10584-008-9520-z
   Agrawal A, 2008, SOCIAL DEV WORKING P, V118
   Amstein S. R., 1969, JAIP, V35, P216, DOI [DOI 10.1080/01944366908977225, 10.1080/01944366908977225]
   Andersson KP, 2008, POLICY SCI, V41, P71, DOI 10.1007/s11077-007-9055-6
   [Anonymous], 2005, Journal of Environmental Policy Planning, DOI DOI 10.1080/15239080500251908
   [Anonymous], 1997, Pasteur's Quadrant: Basic Science and Technological Innovation
   [Anonymous], CLEAN EN DEV INV FRA
   [Anonymous], 1999, Who Is Rational? Studies of Individual Differences in Reasoning
   [Anonymous], 2008, CASE STUDIES ADAPTIV
   [Anonymous], BORDERS NEED STRATEG
   [Anonymous], 2008, 13 YAL SCH FOR ENV S
   [Anonymous], 1971, SCI KNOWLEDGE ITS SO
   [Anonymous], OP LEAST DEV COUNTR
   [Anonymous], CEC5002008071
   [Anonymous], AD CLIM CHANG AUSTR
   [Anonymous], AD CLIM CHANG NEW FI
   [Anonymous], 2012, OECD ENV WORKING PAP
   [Anonymous], 1996, RATIONALITY REASONIN
   [Anonymous], GATEKEEPER SERIES
   [Anonymous], MAK AD COUNT CONC OP
   Bäckstrand K, 2004, ENVIRON POLIT, V13, P695, DOI 10.1080/0964401042000274322
   Barnett J, 2008, ANN ASSOC AM GEOGR, V98, P102, DOI 10.1080/00045600701734315
   Barnett J, 2010, GLOBAL ENVIRON CHANG, V20, P211, DOI 10.1016/j.gloenvcha.2009.11.004
   Bauer N, 2011, CLIM CHANG, V114, P146
   Bennear LS, 2007, ENVIRON RESOUR ECON, V37, P111, DOI 10.1007/s10640-007-9110-y
   Berkes F, 2009, J ENVIRON MANAGE, V90, P1692, DOI 10.1016/j.jenvman.2008.12.001
   Berkhout F, 2006, CLIMATIC CHANGE, V78, P135, DOI 10.1007/s10584-006-9089-3
   Berrang-Ford L, 2011, GLOBAL ENVIRON CHANG, V21, P25, DOI 10.1016/j.gloenvcha.2010.09.012
   Bille R, 2008, SURV PERSPECT INTEGR, V1, P1
   Biringer J, 2005, TROPICAL FORESTS ADA
   Blackmore C, 2007, ENVIRON SCI POLICY, V10, P512, DOI 10.1016/j.envsci.2007.02.007
   Brick K, 2013, ENV DEV DISCUSSION P
   Brown A., 2011, Managing adaptation: Linking theory and practice
   Brunner Ronald., 2005, ADAPTIVE GOVERNANCE
   Brunner RonaldD., 2010, ADAPTIVE GOVERNANCE
   Buob S, 2008, 0804 BERN U, V08-04
   Burandt S, 2010, J CLEAN PROD, V18, P659, DOI 10.1016/j.jclepro.2009.09.010
   Burkett M, 2011, ASIA PACIFIC ISSUES, V98
   Burton I., 2006, Adaptation to Climate Change
   Burton Ian., 2009, EARTHSCAN READER ADA
   Burton P., 2009, Evaluation, V15, P263, DOI 10.1177/1356389009105881
   Burton P, 2013, URBAN POLICY RES, V31, P399, DOI 10.1080/08111146.2013.778196
   Buys L, 2012, REG ENVIRON CHANGE, V12, P237, DOI 10.1007/s10113-011-0253-6
   Campbell-Lendrum D, 2007, B WORLD HEALTH ORGAN, V85, P235, DOI 10.2471/BLT.06.039503
   Carter TR, 2007, C FUT CLIM WIND LOC
   Catchpole R., 2008, CURRENT STATUS PRACT
   Church J., 2010, UNDERSTANDING SEA LE, V1st
   Clark T.W., 2002, The Policy Process: A Practical Guide fo r Natural Resources Professionals
   Corfee-Morlot J, 2011, CLIMATIC CHANGE, V104, P169, DOI 10.1007/s10584-010-9980-9
   Cromp D, 2011, J AGRIC FOOD SYST CO, V2, P29, DOI 10.5304/jafscd.2012.022.010
   DCC, 2009, AUSTR CLIM CHANG SCI
   DCC (Department of Climate Change), 2007, NAT CLIM CHANG AS FR
   Dedekorkut A, 2010, AUST PLAN, V47, P203, DOI 10.1080/07293682.2010.508206
   Dessai S, 2004, CLIMATIC CHANGE, V64, P11, DOI 10.1023/B:CLIM.0000024781.48904.45
   Dessai S, 2009, ADAPTING TO CLIMATE CHANGE: THRESHOLDS, VALUES, GOVERNANCE, P64
   Dilling L, 2011, GLOBAL ENVIRON CHANG, V21, P680, DOI 10.1016/j.gloenvcha.2010.11.006
   Dovers S, 2009, GLOBAL ENVIRON CHANG, V19, P4, DOI 10.1016/j.gloenvcha.2008.06.006
   Dovers SR, 2010, WIRES CLIM CHANGE, V1, P212, DOI 10.1002/wcc.29
   Easterling W.E., 2004, Coping with climate change: The role of adaptation in the United States
   Ebi KL, 2011, CLIMATE CHANGE
   Evans JST, 2006, PSYCHON B REV, V13, P378, DOI 10.3758/BF03193858
   Evans JST, 2003, TRENDS COGN SCI, V7, P454, DOI 10.1016/j.tics.2003.08.012
   Fisher F., 2003, REFRAMING PUBLIC POL
   Flood R.L., 1996, DIVERSITY MANAGEMENT
   Folke C, 2005, ANNU REV ENV RESOUR, V30, P441, DOI 10.1146/annurev.energy.30.050504.144511
   Ford JD, 2011, ADV GLOB CHANGE RES, V42, P3, DOI 10.1007/978-94-007-0567-8_1
   Ford JD, 2011, CLIMATIC CHANGE, V106, P327, DOI 10.1007/s10584-011-0045-5
   Forester J, 1999, The Deliberative Practitioner: Encouraging Participatory Planning Processes
   Fung F, 2011, PHILOS T R SOC A, V369, P99, DOI 10.1098/rsta.2010.0293
   Gero A., 2012, Cross-scale barriers to climate change adaptation in local government
   Godin B, 2006, SCI TECHNOL HUM VAL, V31, P639, DOI 10.1177/0162243906291865
   Goldstein BE, 2009, ECOL SOC, V14
   Gowda MVR, 1999, POLICY SCI, V32, P59
   Graeff S., 2012, CROP PRODUCTION TECH
   Grasso M, 2010, JUSTICE IN FUNDING ADAPTATION UNDER THE INTERNATIONAL CLIMATE CHANGE REGIME, P1, DOI 10.1007/978-90-481-3439-7
   Hadjichristidis C, 2007, MEM COGNITION, V35, P2052, DOI 10.3758/BF03192937
   Hagmann J, 2002, AGR SYST, V73, P23, DOI 10.1016/S0308-521X(01)00098-1
   Hall M, 2012, YALE J INT LAW, V37, P310
   Hallegatte S, 2009, GLOBAL ENVIRON CHANG, V19, P240, DOI 10.1016/j.gloenvcha.2008.12.003
   Hammer SG, 2004, OUTL 2004 C AUSTR BU
   Handmer JW, 2009, EARTHSCAN READER ADA
   Hansen J, 2003, APPETITE, V41, P111, DOI 10.1016/S0195-6663(03)00079-5
   Hartzell-Nichols L, 2011, WIRES CLIM CHANGE, V2, P687, DOI 10.1002/wcc.132
   Hay J, 2006, SUSTAIN SCI, V1, P23, DOI 10.1007/s11625-006-0011-8
   Heazle M, 2010, SCI SOC SER, P1
   Hedger MerylynMckenzie., 2008, Desk Review: Evaluation of Adaptation to Climate Change from a Development Perspective
   Heltberg R, 2009, GLOBAL ENVIRON CHANG, V19, P89, DOI 10.1016/j.gloenvcha.2008.11.003
   Hickox WH, 2003, CLIMATE RES ISS SCI
   Hinkel J, 2011, GLOBAL ENVIRON CHANG, V21, P198, DOI 10.1016/j.gloenvcha.2010.08.002
   Houghton J.T., 2001, CONTRIBUTION WORKING, P1
   Hulme M, 2011, SCIENCE, V334, P764, DOI 10.1126/science.1211740
   Huntjens P, 2010, REG ENVIRON CHANGE, V10, P263, DOI 10.1007/s10113-009-0108-6
   IPCC, 2007, Climate Change 2007: The Physical Science Basis
   Irandoust S, 2009, SUSTAIN SCI, V4, P135, DOI 10.1007/s11625-009-0080-6
   Jerneck A, 2008, CLIM POLICY, V8, P170, DOI 10.3763/cpol.2007.0434
   Jones R. N., 2007, Mitigation and Adaptation Strategies for Global Change, V12, P685, DOI 10.1007/s11027-007-9094-5
   Jones RN, 2004, CLIMATIC CHANGE, V67, P13, DOI 10.1007/s10584-004-3761-2
   Jones RN, 2001, NAT HAZARDS, V23, P197, DOI 10.1023/A:1011148019213
   Kahneman D., 1982, Judgement under uncertainty: Heuristics and biases, P201, DOI [10.1017/CBO9780511809477.015, DOI 10.1017/CBO9780511809477.015]
   Kates RW, 2012, P NATL ACAD SCI USA, V109, P7156, DOI 10.1073/pnas.1115521109
   Keskitalo ECH, 2009, POLAR RES, V28, P60, DOI 10.1111/j.1751-8369.2009.00097.x
   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
   Klein R.J.T., 2009, CARBON CLIMATE LAW R, V3, P284, DOI DOI 10.21552/CCLR/2009/3/99
   Klein RJT, 2001, J COASTAL RES, V17, P531
   Klein RJT, 2013, 201301 NORDSTAR
   Kolev A, 2012, INVESTMENT GROWTH TI
   Kpadonou R. A. B., 2012, African Crop Science Journal, V20, P181
   Kuhn Thomas S., 1962, The structure of scientific revolutions
   Kuriakose Anne T., 2009, SOCIAL DEV WORKING P, V116
   Lambrou Y, 2006, GENDERR MISSING COMP
   Leeuwis C., 2002, WHEELBARROWS FULL FR
   Leiserowitz AA, 2005, RISK ANAL, V25, P1433, DOI 10.1111/j.1540-6261.2005.00690.x
   Lemos MC, 2008, IDS BULL-I DEV STUD, V39, P60
   Lesnikowski AC, 2015, MITIG ADAPT STRAT GL, V20, P277, DOI 10.1007/s11027-013-9491-x
   Li G, 2011, ADV GLOB CHANGE RES, V42, P289, DOI 10.1007/978-94-007-0567-8_21
   Lim B., 2005, Adaptation policy frameworks for climate change: Developing strategies, policies and measures
   Lin A, 2012, ECOL LAW Q IN PRESS
   Lorenzoni I, 2000, GLOBAL ENVIRON CHANG, V10, P145, DOI 10.1016/S0959-3780(00)00016-9
   Lynch AH, 2008, B AM METEOROL SOC, V89, P169, DOI 10.1175/BAMS-89-2-169
   MacLellan JI, 2007, BIBLIO REV CLIMATE C
   Mccarthy PD, 2012, ADV CLIM CHANG RES, V3, P22, DOI 10.3724/SP.J.1248.2012.00022
   McKinney M., 2010, West-Northwest Journal of Environmental Law and Policy, P307
   Measham T., 2012, Risk and social theory in environmental management
   Measham TG, 2011, MITIG ADAPT STRAT GL, V16, P889, DOI 10.1007/s11027-011-9301-2
   Moench M., 2009, The Earthscan reader on adaptation to climate change
   Moser S.C., 2009, GOVERNANCE ART OVERC
   Moser S, 2009, CLIMATIC CHANGE, V95, P11, DOI 10.1007/s10584-008-9539-1
   Moser SC, 2007, CREATING A CLIMATE FOR CHANGE: COMMUNICATING CLIMATE CHANGE AND FACILITATING SOCIAL CHANGE, P64, DOI 10.1017/CBO9780511535871.006
   Moser SC, 2010, P NATL ACAD SCI USA, V107, P22026, DOI 10.1073/pnas.1007887107
   Mustelin J, 2010, POPUL ENVIRON, V31, P371, DOI 10.1007/s11111-010-0107-z
   Mustelin J, 2013, THESIS GRIFFITH U
   Mustelin J, 2013, CLIM DEV, V5, P189, DOI 10.1080/17565529.2013.812953
   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
   Newstead SE, 2002, MEM COGNITION, V30, P129, DOI 10.3758/BF03195272
   NISTPASS (National Institute for Science and Technology Policy and Strategy Studies), 2011, 2 WORLD C CIT AS CLI
   Næss LO, 2005, GLOBAL ENVIRON CHANG, V15, P125, DOI 10.1016/j.gloenvcha.2004.10.003
   O'Brien KL, 2010, WIRES CLIM CHANGE, V1, P232, DOI 10.1002/wcc.30
   Oppermann E, 2011, CLIM DEV, V3, P71, DOI 10.3763/cdev.2010.0061
   Osman M, 2004, PSYCHON B REV, V11, P988, DOI 10.3758/BF03196730
   Park SE, 2012, GLOBAL ENVIRON CHANG, V22, P115, DOI 10.1016/j.gloenvcha.2011.10.003
   Parry M., 2009, ASSESSING COSTS ADAP
   Patt A, 2005, CR GEOSCI, V337, P411, DOI 10.1016/j.crte.2004.11.006
   Patt A, 2012, GEOGR TIDSSKR-DEN, V112, P174, DOI 10.1080/00167223.2012.742967
   Pelling M, 2005, GLOBAL ENVIRON CHANG, V15, P308, DOI 10.1016/j.gloenvcha.2005.02.001
   Petherick A, 2012, NAT CLIM CHANGE, V2, P144, DOI 10.1038/nclimate1423
   Pielke R, 2007, NATURE, V445, P597, DOI 10.1038/445597a
   Preston B., 2009, FRAMING VULNERABILIT
   Preston BL, 2009, MITIG ADAPT STRAT GL, V14, P251, DOI 10.1007/s11027-008-9163-4
   Preston B.L., 2013, Successful adaptation to climate change
   Preston BL, 2011, SUSTAIN SCI, V6, P177, DOI 10.1007/s11625-011-0129-1
   Preston BL, 2011, MITIG ADAPT STRAT GL, V16, P407, DOI 10.1007/s11027-010-9270-x
   Preston BL, 2009, CLIMATE CHANGE SOCIA
   Preston BL, 2010, MANAGING CLIMATE RIS
   PRICE MF, 2003, BUYING TIME USERS MA
   Prober SM, 2012, CLIMATIC CHANGE, V110, P227, DOI 10.1007/s10584-011-0092-y
   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]
   Raymondi AM, 2012, HUMAN SOCIAL DIMENSI
   Reisinger A, 2011, ADV GLOB CHANGE RES, V42, P303, DOI 10.1007/978-94-007-0567-8_22
   Richardson A., 1983, PARTICIPATION
   Richels RG, 2009, CLIMATIC CHANGE, V97, P289, DOI 10.1007/s10584-009-9730-z
   Rietbergen-McCracken J., 2007, The Forest Landscape Restoration Handbook, V2nd
   Rinner C, 2011, ISPRS BOOK SERIES, V9
   Saavedra C, 2009, HABITAT INT, V33, P246, DOI 10.1016/j.habitatint.2008.10.004
   Sadauskis R, 2011, THESIS STOCKHOLM U
   Satterthwaite D., 2007, HUMAN SETTLEMENTS DI
   Schipper E.L., 2009, The Earthscan Reader on Adaptation to Climate Change
   Schipper L., 2007, Working Papers - Tyndall Centre for Climate Change Research
   Schon D.A.M. Rein., 1994, FRAME REFLECTION RES
   Scott C., 2010, Adding value to policy analysis and advice
   Sheffer T, 2010, THESIS VIRGINIA POLY
   Simonsson L, 2011, ADV GLOB CHANGE RES, V42, P321, DOI 10.1007/978-94-007-0567-8_23
   Slovic P., 1982, JUDGMENT UNCERTAINTY, P463, DOI DOI 10.1017/CBO9780511809477.034
   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
   Sprague A, 2012, APPL STORMWATER MANA
   Streilein AS, 2008, THESIS U BRIT COLUMB
   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
   TOBLER WR, 1970, ECON GEOGR, V46, P234, DOI 10.2307/143141
   Todd M.C., 2010, Hydrol. Earth Syst. Sci. Discuss, V7, P7485, DOI DOI 10.5194/HESSD-7-7485-2010
   Tol RSJ, 2008, J COASTAL RES, V24, P432, DOI 10.2112/07A-0016.1
   Tol RSJ, 2005, ENVIRON SCI POLICY, V8, P572, DOI 10.1016/j.envsci.2005.06.011
   Tompkins EL, 2010, GLOBAL ENVIRON CHANG, V20, P627, DOI 10.1016/j.gloenvcha.2010.05.001
   Trench B, 2008, COMMUNICATING SCIENCE IN SOCIAL CONTEXTS: NEW MODELS, NEW PRACTICES, P119, DOI 10.1007/978-1-4020-8598-7_7
   U.S. EPA, 2009, SYNTH AD OPT COAST A
   UK Stationary Office, 2010, AD I CLIM CHANG 28 R
   UNDP (United Nations Development Programme), 2007, 200708 PALGR MCMILL
   UNFCCC (United Nations Framework Convention on Cli- mate Change), 2007, INV FIN FLOWS ADDR C
   UNFCCC (United Nations Framework Convention on Climate Change), 2007, SYNTH INF EC D UNPUB
   Urwin K, 2008, GLOBAL ENVIRON CHANG, V18, P180, DOI 10.1016/j.gloenvcha.2007.08.002
   Walker WD, 2010, ADAPTATION WORKING G
   Weber EU, 2010, WIRES CLIM CHANGE, V1, P332, DOI 10.1002/wcc.41
   Weinestedt H, 2009, 26000 ISO
   Wesselink A, 2008, ATTITUDES AFFECT IMP
   White House, 2009, 13514 WHIT HOUS
   Wilby RL, 2011, WATER ENVIRON J, V25, P271, DOI 10.1111/j.1747-6593.2010.00220.x
   Wilhelmi OV, 2010, ENVIRON RES LETT, V5, DOI 10.1088/1748-9326/5/1/014021
   Wolf J, 2010, GLOBAL ENVIRON CHANG, V20, P44, DOI 10.1016/j.gloenvcha.2009.09.004
   WYNNE B, 1991, SCI TECHNOL HUM VAL, V16, P111, DOI 10.1177/016224399101600108
   Wynne B, 2006, COMMUNITY GENET, V9, P211, DOI 10.1159/000092659
   Yuen E, 2013, MITIG ADAPT STRAT GL, V18, P567, DOI 10.1007/s11027-012-9376-4
   Yusoff S, 2011, ENV MANAGEMENT PRACT
   Ziervogel G, 2006, NAT RESOUR FORUM, V30, P294, DOI 10.1111/j.1477-8947.2006.00121.x
NR 207
TC 93
Z9 104
U1 1
U2 58
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 MAR
PY 2015
VL 20
IS 3
BP 467
EP 497
DI 10.1007/s11027-013-9503-x
PG 31
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA CB4ZM
UT WOS:000349637200008
DA 2025-01-10
ER

PT J
AU Müller, A
   Horna, V
   Zhang, CX
   Leuschner, C
AF Mueller, Annika
   Horna, Viviana
   Zhang, Chunxia
   Leuschner, Christoph
TI Different growth strategies determine the carbon gain and productivity
   of aspen collectives to be used in short-rotation plantations
SO BIOMASS & BIOENERGY
LA English
DT Article; Proceedings Paper
CT 1st International Conference on Lignocellulosic Ethanol
CY OCT 13-15, 2010
CL Copenhagen, DENMARK
DE Carbon gain; Genotypic variation; Growth performance; Leaf phaenology;
   Photosynthesis; Populus tremula
ID POPULUS-TREMULOIDES; POPLAR HYBRIDS; TRAITS; POPULATIONS; PARAMETERS;
   PHENOLOGY; CLONES; TRIALS; L.
AB Populus tremula is a favoured tree species in short-rotation forestry with a recognised large intraspecific variation in productivity. We compared the growth potential of 1-yr-old saplings of four Central European aspen collectives with different climate adaptation on a low-fertility site and searched for growth-determining physiological and morphological traits and their dependence on genetic constitution. Among the 35 investigated traits were photosynthetic capacity and mean assimilation rate, quantum yield and carboxylation efficiency, leaf water potential, leaf phaenology and the ratio of leaves lost to leaves produced (LP ratio), leaf size and total leaf area, axes length growth and canopy carbon gain as an estimate of productivity. The collectives differed by more than 30% in cumulative carbon gain with a large genotype effect, while mean assimilation rate and most photosynthetic and water status traits showed a relatively small intraspecific variation with no significant influence on the variation in C gain. The timing of the beginning of net leaf loss (leaf abscission > leaf production) in August differed between the four collectives and resulted in different maximum leaf areas and LP ratios, which were identified as key factors controlling C gain. Mean assimilation rate, though not related to cumulative C gain, was positively correlated with the light, CO2 and water use efficiencies of photosynthesis. We conclude that genotype selection for high-yielding aspen in short-rotation forestry at low-fertility sites should focus on the parameters leaf phaenology, LP ratio at the end of the growing season, and the resulting total leaf area as key traits. (C) 2012 Elsevier Ltd. All rights reserved.
C1 [Mueller, Annika; Horna, Viviana; Leuschner, Christoph] Univ Gottingen, Albrecht von Haller Inst Plant Sci, D-37073 Gottingen, Germany.
   [Zhang, Chunxia] Univ Gottingen, Busgen Inst, D-37077 Gottingen, Germany.
C3 University of Gottingen; University of Gottingen
RP Müller, A (corresponding author), LI COR Biosci GmbH, Siemensstr 25A, D-61352 Bad Homburg, Germany.
EM amuelle3@gwdg.de
OI Horna, Viviana/0000-0003-1273-2420
CR Bernacchi CJ, 2003, PLANT CELL ENVIRON, V26, P1419, DOI 10.1046/j.0016-8025.2003.01050.x
   Dayanandan S, 1998, THEOR APPL GENET, V96, P950, DOI 10.1007/s001220050825
   Dickmann DI, 2008, INT POPLAR COMMISSIO, P3
   HANSEN EA, 1991, BIOMASS BIOENERG, V1, P1, DOI 10.1016/0961-9534(91)90046-F
   Kanaga MK, 2008, CAN J FOREST RES, V38, P1690, DOI 10.1139/X08-012
   Lenz KE, 2010, ENVIRON POLLUT, V158, P1015, DOI 10.1016/j.envpol.2009.08.004
   Liesebach M, 1999, FOREST ECOL MANAG, V121, P25, DOI 10.1016/S0378-1127(98)00554-4
   Lojewski NR, 2009, TREE PHYSIOL, V29, P1133, DOI 10.1093/treephys/tpp046
   Makeschin F, 1999, FOREST ECOL MANAG, V121, P1
   Marron N, 2007, ENVIRON EXP BOT, V61, P103, DOI 10.1016/j.envexpbot.2007.04.002
   Meir P, 2007, PLANT ECOL, V192, P277, DOI 10.1007/s11258-007-9320-y
   Muller A, PHYSL VS MORPH UNPUB
   NEI M, 1972, AM NAT, V106, P283, DOI 10.1086/282771
   Peakall R, 2006, MOL ECOL NOTES, V6, P288, DOI 10.1111/j.1471-8286.2005.01155.x
   Pliura A, 2007, FOREST ECOL MANAG, V238, P92, DOI 10.1016/j.foreco.2006.09.082
   Rae AM, 2009, BMC PLANT BIOL, V9, DOI 10.1186/1471-2229-9-23
   Rahman MH, 2002, GENOME, V45, P1083, DOI [10.1139/g02-077, 10.1139/G02-077]
   Rowland DL, 2001, CAN J FOREST RES, V31, P845, DOI 10.1139/cjfr-31-5-845
   Schulze E D., 2002, Plant Ecology
   SINGH M, 1993, THEOR APPL GENET, V86, P437, DOI 10.1007/BF00838558
   Smulders MJM, 2001, MOL ECOL NOTES, V1, P188, DOI 10.1046/j.1471-8278.2001.00071.x
   Stanturf J.A., 2001, POPLAR CULTURE N AM, P153
   Suvanto LI, 2005, MOL ECOL, V14, P2851, DOI 10.1111/j.1365-294X.2005.02634.x
   UPOV, 1981, INT UN PROT NEW VAR
   Weih M, 2009, TREE PHYSIOL, V29, P1479, DOI 10.1093/treephys/tpp081
   Yu QB, 2001, SILVA FENN, V35, P15, DOI 10.14214/sf.600
NR 26
TC 5
Z9 5
U1 1
U2 35
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0961-9534
EI 1873-2909
J9 BIOMASS BIOENERG
JI Biomass Bioenerg.
PD NOV
PY 2012
VL 46
SI SI
BP 242
EP 250
DI 10.1016/j.biombioe.2012.08.020
PG 9
WC Agricultural Engineering; Biotechnology & Applied Microbiology; Energy &
   Fuels
WE Science Citation Index Expanded (SCI-EXPANDED); Conference Proceedings Citation Index - Science (CPCI-S)
SC Agriculture; Biotechnology & Applied Microbiology; Energy & Fuels
GA 067PJ
UT WOS:000313307300025
DA 2025-01-10
ER

PT J
AU van Heerwaarden, B
   Lee, RFH
   Wegener, B
   Weeks, AR
   Sgro, CM
AF van Heerwaarden, B.
   Lee, R. F. H.
   Wegener, B.
   Weeks, A. R.
   Sgro, C. M.
TI Complex patterns of local adaptation in heat tolerance in Drosophila
   simulans from eastern Australia
SO JOURNAL OF EVOLUTIONARY BIOLOGY
LA English
DT Article
DE cline; dynamic; heat tolerance; local adaptation; static
ID MICROSATELLITE VARIATION; GENE FLOW; PORCELAIN CRABS; SPECIES BORDERS;
   THERMAL-STRESS; CLIMATE-CHANGE; MELANOGASTER; POPULATIONS; LIMITS;
   RESISTANCE
AB Latitudinal clines are considered a powerful means of investigating evolutionary responses to climatic selection in nature. However, most clinal studies of climatic adaptation in Drosophila have involved species that contain cosmopolitan inversion polymorphisms that show clinal patterns themselves, making it difficult to determine whether the traits or inversions are under selection. Further, although climatic selection is unlikely to act on only one life stage in metamorphic organisms, a few studies have examined clinal patterns across life stages. Finally, clinal patterns of heat tolerance may also depend on the assay used. To unravel these potentially confounding effects on clinal patterns of thermal tolerance, we examined adult and larval heat tolerance traits in populations of Drosophila simulans from eastern Australia using static and dynamic (ramping 0.06 similar to degrees C similar to min-1) assays. We also used microsatellites markers to clarify whether demographic factors or selection are responsible for population differentiation along clines. Significant cubic clinal patterns were observed for adult static basal, hardened and dynamic heat knockdown time and static basal heat survival in larvae. In contrast, static, hardened larval heat survival increased linearly with latitude whereas no clinal association was found for larval ramping survival. Significant associations between adult and larval traits and climatic variables, and low population differentiation at microsatellite loci, suggest a role for climatic selection, rather than demographic processes, in generating these clinal patterns. Our results suggest that adaptation to thermal stress may be species and life-stage specific, complicating our efforts to understand the evolutionary responses to selection for increasing thermotolerance.
C1 [van Heerwaarden, B.; Lee, R. F. H.; Wegener, B.; Sgro, C. M.] Monash Univ, Sch Biol Sci, Melbourne, Vic 3800, Australia.
   [Weeks, A. R.] Univ Melbourne, Dept Genet, Parkville, Vic 3052, Australia.
C3 Monash University; University of Melbourne
RP Sgro, CM (corresponding author), Monash Univ, Sch Biol Sci, Buiding 18, Melbourne, Vic 3800, Australia.
EM carla.sgro@monash.edu
RI Weeks, Andrew/ABC-3048-2020; Sgro, Carla/G-5166-2010; van Heerwaarden,
   Belinda/A-4515-2012
OI van Heerwaarden, Belinda/0000-0003-2435-2900; Weeks,
   Andrew/0000-0003-3081-135X
FU Australian Research Council; Commonwealth Environment Research Facility
FX We thank the Australian Research Council for financial support to CMS
   and ARW. The Commonwealth Environment Research Facility also provided
   financial support to CMS. We would also like to thank Fiona Cockerell,
   Nicole Derycke, Belinda Williams and Winston Yee for technical support,
   and Vanessa Kellermann, Jennifer Sherriffs, Rebecca Hallas and Rob Goods
   for field collections.
CR Agis M, 2001, MOL ECOL, V10, P1197, DOI 10.1046/j.1365-294X.2001.01271.x
   Anderson AR, 2003, HEREDITY, V90, P195, DOI 10.1038/sj.hdy.6800220
   Arthur AL, 2008, J EVOLUTION BIOL, V21, P1470, DOI 10.1111/j.1420-9101.2008.01617.x
   Beerli P, 2001, P NATL ACAD SCI USA, V98, P4563, DOI 10.1073/pnas.081068098
   Bridle JR, 2009, P ROY SOC B-BIOL SCI, V276, P1507, DOI 10.1098/rspb.2008.1601
   Chapuis MP, 2007, MOL BIOL EVOL, V24, P621, DOI 10.1093/molbev/msl191
   Compton TJ, 2007, J EXP MAR BIOL ECOL, V352, P200, DOI 10.1016/j.jembe.2007.07.010
   Cossins A. R., 1987, Temperature biology of animals.
   Crawford NG, 2010, MOL ECOL RESOUR, V10, P556, DOI 10.1111/j.1755-0998.2009.02801.x
   David JR, 2004, GENETICA, V120, P151, DOI 10.1023/B:GENE.0000017638.02813.5a
   Duarte H, 2012, GLOBAL CHANGE BIOL, V18, P412, DOI 10.1111/j.1365-2486.2011.02518.x
   Earl DA, 2012, CONSERV GENET RESOUR, V4, P359, DOI 10.1007/s12686-011-9548-7
   Endler J.A., 1977, Monographs in Population Biology, pi
   Evanno G, 2005, MOL ECOL, V14, P2611, DOI 10.1111/j.1365-294X.2005.02553.x
   EXCOFFIER L, 1992, GENETICS, V131, P479
   Excoffier L, 2005, EVOL BIOINFORM, V1, P47, DOI 10.1177/117693430500100003
   Feder ME, 1996, J EXP BIOL, V199, P1837
   Feder ME, 1997, FUNCT ECOL, V11, P90, DOI 10.1046/j.1365-2435.1997.00060.x
   Folk DG, 2006, J EXP BIOL, V209, P3964, DOI 10.1242/jeb.02463
   Frentiu FD, 2010, EVOLUTION, V64, P1784, DOI 10.1111/j.1558-5646.2009.00936.x
   Goudet J, 1995, J HERED, V86, P485, DOI 10.1093/oxfordjournals.jhered.a111627
   HOFFMANN AA, 1994, TRENDS ECOL EVOL, V9, P223, DOI 10.1016/0169-5347(94)90248-8
   Hoffmann AA, 2004, TRENDS ECOL EVOL, V19, P482, DOI 10.1016/j.tree.2004.06.013
   HOFFMANN AA, 1993, AM NAT, V142, pS93, DOI 10.1086/285525
   Hoffmann AA, 2003, J THERM BIOL, V28, P175, DOI 10.1016/S0306-4565(02)00057-8
   Hoffmann AA, 2002, ECOL LETT, V5, P614, DOI 10.1046/j.1461-0248.2002.00367.x
   Hoffmann AA, 1997, J INSECT PHYSIOL, V43, P393, DOI 10.1016/S0022-1910(96)00108-4
   Hoffmann AA, 2007, GENETICA, V129, P133, DOI 10.1007/s10709-006-9010-z
   Hutter CM, 1998, MOL BIOL EVOL, V15, P1620, DOI 10.1093/oxfordjournals.molbev.a025890
   JAMES AC, 1995, GENETICS, V140, P659
   Jones SJ, 2009, BIOL BULL-US, V217, P73, DOI 10.1086/BBLv217n1p73
   Jost L, 2008, MOL ECOL, V17, P4015, DOI 10.1111/j.1365-294X.2008.03887.x
   KAWANISHI M, 1978, JPN J GENET, V53, P209, DOI 10.1266/jjg.53.209
   Kelty JD, 2001, J EXP BIOL, V204, P1659
   Kennington WJ, 2003, GENETICS, V165, P667
   Kingsolver JG, 2011, INTEGR COMP BIOL, V51, P719, DOI 10.1093/icb/icr015
   Kirkpatrick M, 1997, AM NAT, V150, P1, DOI 10.1086/286054
   Kirkpatrick M, 2006, GENETICS, V173, P419, DOI 10.1534/genetics.105.047985
   Krebs RA, 1995, BIOL J LINN SOC, V56, P517, DOI 10.1111/j.1095-8312.1995.tb01108.x
   Loeschcke V, 1996, EVOLUTION, V50, P2354, DOI [10.2307/2410704, 10.1111/j.1558-5646.1996.tb03623.x]
   Mercader RJ, 2008, ECOL ENTOMOL, V33, P537, DOI 10.1111/j.1365-2311.2008.01001.x
   Mitchell KA, 2010, FUNCT ECOL, V24, P694, DOI 10.1111/j.1365-2435.2009.01666.x
   Overgaard J, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0032758
   Parkash R, 2005, PHYSIOL ENTOMOL, V30, P353, DOI 10.1111/j.1365-3032.2005.00470.x
   Peakall R, 2006, MOL ECOL NOTES, V6, P288, DOI 10.1111/j.1471-8286.2005.01155.x
   PRINCE GJ, 1977, AUST J ZOOL, V25, P285, DOI 10.1071/ZO9770285
   Pritchard JK, 2000, GENETICS, V155, P945
   Rezende EL, 2011, FUNCT ECOL, V25, P111, DOI 10.1111/j.1365-2435.2010.01778.x
   Rousset F, 1997, GENETICS, V145, P1219
   Rousset F, 2008, MOL ECOL RESOUR, V8, P103, DOI 10.1111/j.1471-8286.2007.01931.x
   Santos M, 2011, FUNCT ECOL, V25, P1169, DOI 10.1111/j.1365-2435.2011.01908.x
   Sarup P, 2009, J EVOLUTION BIOL, V22, P1111, DOI 10.1111/j.1420-9101.2009.01725.x
   Sarup P, 2006, HEREDITY, V96, P479, DOI 10.1038/sj.hdy.6800828
   Schöfl G, 2006, MOL ECOL, V15, P3895, DOI 10.1111/j.1365-294X.2006.03065.x
   Sgrò CM, 2010, J EVOLUTION BIOL, V23, P2484, DOI 10.1111/j.1420-9101.2010.02110.x
   Sgrò CM, 2003, EVOLUTION, V57, P1846
   Sinervo B, 2010, SCIENCE, V328, P894, DOI 10.1126/science.1184695
   SLATKIN M, 1987, SCIENCE, V236, P787, DOI 10.1126/science.3576198
   Sokal R. R., 1995, Biometry: The Principles of Statistics in Biological Research
   Somero GN, 2010, J EXP BIOL, V213, P912, DOI 10.1242/jeb.037473
   Stillman JH, 2002, INTEGR COMP BIOL, V42, P790, DOI 10.1093/icb/42.4.790
   Stillman JH, 2000, PHYSIOL BIOCHEM ZOOL, V73, P200, DOI 10.1086/316738
   Terblanche JS, 2007, P ROY SOC B-BIOL SCI, V274, P2935, DOI 10.1098/rspb.2007.0985
   Terblanche JS, 2011, J EXP BIOL, V214, P3713, DOI 10.1242/jeb.061283
   Tomanek L, 1999, J EXP BIOL, V202, P2925
   van Heerwaarden B, 2009, P ROY SOC B-BIOL SCI, V276, P1517, DOI 10.1098/rspb.2008.1288
   Van Oosterhout C, 2004, MOL ECOL NOTES, V4, P535, DOI 10.1111/j.1471-8286.2004.00684.x
   Weeks AR, 2002, ECOL LETT, V5, P756, DOI 10.1046/j.1461-0248.2002.00380.x
   Weir BS., 1996, Genetic data analysis II, P445
NR 69
TC 26
Z9 29
U1 1
U2 60
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1010-061X
EI 1420-9101
J9 J EVOLUTION BIOL
JI J. Evol. Biol.
PD SEP
PY 2012
VL 25
IS 9
BP 1765
EP 1778
DI 10.1111/j.1420-9101.2012.02564.x
PG 14
WC Ecology; Evolutionary Biology; Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Evolutionary Biology; Genetics &
   Heredity
GA 989JA
UT WOS:000307554900008
PM 22775577
DA 2025-01-10
ER

PT J
AU Beier, CM
   Signell, SA
   Luttman, A
   DeGaetano, AT
AF Beier, Colin M.
   Signell, Stephen A.
   Luttman, Aaron
   DeGaetano, Arthur T.
TI High-resolution climate change mapping with gridded historical climate
   products
SO LANDSCAPE ECOLOGY
LA English
DT Article
DE Temperature trends; Climate maps; Parameter Regression Independent
   Slopes Model (PRISM); North American Regional Reanalysis (NARR);
   Downscaling; Climate adaptation
ID TEMPERATURE; PRECIPITATION; MODEL; INTERPOLATION; VARIABLES; SURFACES;
   MAXIMUM; CANADA; TRENDS
AB The detection of climate-driven changes in coupled human-natural systems has become a focus of climate research and adaptation efforts around the world. High-resolution gridded historical climate (GHC) products enable analysis of recent climatic changes at the local/regional scales most relevant for research and decision-making, but these fine-scale climate datasets have several caveats. We analyzed two 4 km GHC products to produce high-resolution temperature trend maps for the US Northeast from 1980 to 2009, and compared outputs between products and with an independent climate record. The two products had similar spatial climatologies for mean temperatures, agreed on temporal variability in regionally averaged trends, and agreed that warming has been greater for minimum versus maximum temperatures. Trend maps were highly heterogeneous, i.e., a patchy landscape of warming, cooling and stability that varied by month, but with local-scale anomalies persistent across months (e.g., cooling 'pockets' within warming zones). In comparing trend maps between GHC products, we found large local-scale disparities at high elevations and along coastlines; and where weather stations were sparse, a single-station disparity in input data resulted in a large zone of trend map disagreement between products. Preliminary cross-validation with an independent climate record indicated substantial and complex errors for both products. Our analysis provided novel landscape-scale insights on climate change in the US Northeast, but raised questions about scale and sources of uncertainty in high-resolution GHC products and differences among the many products available. Given rapid growth in their use, we recommend exercising caution in the analysis and interpretation of high-resolution climate maps.
C1 [Beier, Colin M.] SUNY Syracuse, Dept Forest & Nat Resources Management, Coll Environm Sci & Forestry, Adirondack Ecol Ctr, Syracuse, NY 13210 USA.
   [Signell, Stephen A.] SUNY, Coll Environm Sci & Forestry, Adirondack Ecol Ctr, Newcomb, NY USA.
   [Luttman, Aaron] Clarkson Univ, Dept Math & Comp Sci, Potsdam, NY USA.
   [DeGaetano, Arthur T.] Cornell Univ, Dept Earth & Atmospher Sci, NOAA, NE Reg Climate Ctr, Ithaca, NY USA.
C3 State University of New York (SUNY) System; State University of New York
   (SUNY) College of Environmental Science & Forestry; State University of
   New York (SUNY) System; SUNY Maritime College; State University of New
   York (SUNY) College of Environmental Science & Forestry; Clarkson
   University; Cornell University; National Oceanic Atmospheric Admin
   (NOAA) - USA
RP Beier, CM (corresponding author), SUNY Syracuse, Dept Forest & Nat Resources Management, Coll Environm Sci & Forestry, Adirondack Ecol Ctr, 1 Forestry Dr, Syracuse, NY 13210 USA.
EM cbeier@esf.edu
OI Luttman, Aaron/0000-0001-6639-0759
FU National Aeronautic and Space Administration [NNX09AK16G]; USDA-CSREES;
   NASA [113033, NNX09AK16G] Funding Source: Federal RePORTER
FX We thank the PRISM group for providing free access to their 4 km
   products and the University Consortium of Atmospheric Research (UCAR)
   for providing the Integrated Data Viewer (IDV). We also thank D. Bishop,
   R. Signell, B. Belcher and J. Wiley for assistance with data compilation
   and analysis. This research was supported by the National Aeronautic and
   Space Administration Biodiversity Program (#NNX09AK16G) and the
   USDA-CSREES McIntire-Stennis Cooperative Forestry Program.
CR Adrian R, 2009, LIMNOL OCEANOGR, V54, P2283, DOI 10.4319/lo.2009.54.6_part_2.2283
   [Anonymous], ORNLCDIAC118
   [Anonymous], GEOGR ANAL
   [Anonymous], USDA FOR SERV P
   [Anonymous], NETCDF C INTERFACE G
   [Anonymous], J AM STAT ASSOC
   [Anonymous], CLIMATE CHANGE 2007
   Beckage B, 2008, P NATL ACAD SCI USA, V105, P4197, DOI 10.1073/pnas.0708921105
   Daly C, 2002, CLIM RES, V22, P99, DOI 10.3354/cr022099
   DALY C, 1994, J APPL METEOROL, V33, P140, DOI 10.1175/1520-0450(1994)033<0140:ASTMFM>2.0.CO;2
   Daly C, 2008, INT J CLIMATOL, V28, P2031, DOI 10.1002/joc.1688
   Daly C, 2006, INT J CLIMATOL, V26, P707, DOI 10.1002/joc.1322
   DeGaetano AT, 2007, J APPL METEOROL CLIM, V46, P1981, DOI 10.1175/2007JAMC1536.1
   Di Luzio M, 2008, J APPL METEOROL CLIM, V47, P475, DOI 10.1175/2007JAMC1356.1
   Frumhoff PC, 2007, CONFRONTING CLIMATE
   Hayhoe K, 2008, MITIG ADAPT STRAT GL, V13, P425, DOI 10.1007/s11027-007-9133-2
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Hodgkins GA, 2002, INT J CLIMATOL, V22, P1819, DOI 10.1002/joc.857
   Jarvis CH, 2001, J APPL METEOROL, V40, P1075, DOI 10.1175/1520-0450(2001)040<1075:ACASFI>2.0.CO;2
   Kirshen P, 2008, MITIG ADAPT STRAT GL, V13, P437, DOI 10.1007/s11027-007-9130-5
   Mahmood R, 2006, INT J CLIMATOL, V26, P1091, DOI 10.1002/joc.1298
   Mesinger F, 2006, B AM METEOROL SOC, V87, P343, DOI 10.1175/BAMS-87-3-343
   Mitchell TD, 2005, INT J CLIMATOL, V25, P693, DOI 10.1002/joc.1181
   MORAN PAP, 1950, BIOMETRIKA, V37, P17, DOI 10.2307/2332142
   Parmesan C, 2003, NATURE, V421, P37, DOI 10.1038/nature01286
   Pielke RA, 2002, INT J CLIMATOL, V22, P421, DOI 10.1002/joc.706
   R Core Team, 2022, R: A Language and Environment for Statistical Computing
   REW R, 1990, IEEE COMPUT GRAPH, V10, P76, DOI 10.1109/38.56302
   Rosenzweig C, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P79
   Scott D, 2008, MITIG ADAPT STRAT GL, V13, P577, DOI 10.1007/s11027-007-9136-z
   Simpson JJ, 2005, ARCTIC, V58, P137
   Thornton PE, 1997, J HYDROL, V190, P214, DOI 10.1016/S0022-1694(96)03128-9
   Wang HL, 2009, J CLIMATE, V22, P2571, DOI 10.1175/2008JCL12359.1
   Wang T, 2006, INT J CLIMATOL, V26, P383, DOI 10.1002/joc.1247
   Wood AW, 2004, CLIMATIC CHANGE, V62, P189, DOI 10.1023/B:CLIM.0000013685.99609.9e
NR 35
TC 25
Z9 32
U1 0
U2 30
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 MAR
PY 2012
VL 27
IS 3
BP 327
EP 342
DI 10.1007/s10980-011-9698-8
PG 16
WC Ecology; Geography, Physical; Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Physical Geography; Geology
GA 889QE
UT WOS:000300087500002
DA 2025-01-10
ER

PT J
AU Crossman, ND
   Bryan, BA
   Summers, DM
AF Crossman, Neville D.
   Bryan, Brett A.
   Summers, David M.
TI Identifying priority areas for reducing species vulnerability to climate
   change
SO DIVERSITY AND DISTRIBUTIONS
LA English
DT Article
DE Climate adaptation; conservation planning; ecological restoration;
   ensemble forecast; resilience; species distribution modelling
ID SYSTEMATIC LANDSCAPE RESTORATION; DISPERSAL CORRIDORS; ENVELOPE MODELS;
   CHANGE IMPACTS; RANGE SHIFTS; LAND-USE; BIODIVERSITY; POLICY; MIGRATION;
   RISK
AB Aim The dimensions of species vulnerability to climate change are complex, and this impedes efforts to provide clear advice for conservation planning. In this study, we used a formal framework to assess species vulnerability to climate change quantifying exposure, sensitivity and adaptive capacity and then used this information to target areas for reducing vulnerability at a regional scale.
   Location The 6500-km(2) Mount Lofty Ranges region in South Australia.
   Methods We quantified the vulnerability of 171 plant species in a fragmented yet biologically important agro-ecological landscape, typical of many temperate zones globally. We specified exposure, using three climate change scenarios; sensitivity, as the adverse impact of climate change on species' spatial distribution; and adaptive capacity, as the ability of species to migrate calculated using dispersal kernels. Priority areas for reducing vulnerability were then identified by incorporating these various components into a single priority index.
   Results Climate change had a variable impact on species distributions. Those species whose range decreased or shifted geographically were attributed higher sensitivity than those species that increased geographic range or remained unchanged. The ability to adapt to range changes in response to shifting climates varies both spatially and between species. Areas of highest priority for reducing vulnerability were found at higher altitudes and lower latitudes with increasing severity of climate change.
   Main conclusions Our study demonstrates the use of a single spatially explicit index that identifies areas in the landscape for targeting specific conservation and restoration actions to reduce species vulnerability to climate change. Our index can be transferred to other regions around the world in which climate change poses an increasing threat to native species.
C1 [Crossman, Neville D.; Bryan, Brett A.; Summers, David M.] CSIRO Ecosyst Sci, Urrbrae, SA 5064, Australia.
C3 Commonwealth Scientific & Industrial Research Organisation (CSIRO)
RP Crossman, ND (corresponding author), CSIRO Ecosyst Sci, PMB2, Urrbrae, SA 5064, Australia.
EM neville.crossman@csiro.au
RI Summers, David/G-3540-2011; Bryan, Brett/F-8949-2010; Crossman,
   Neville/G-5433-2010
OI Bryan, Brett/0000-0003-4834-5641; Crossman, Neville/0000-0002-8002-3450
CR Adger WN, 2006, GLOBAL ENVIRON CHANG, V16, P268, DOI 10.1016/j.gloenvcha.2006.02.006
   [Anonymous], 2009, TECHNICAL SERIES
   [Anonymous], ANUCLIM USERS GUIDE
   [Anonymous], 2009, A Report to the Natural Resource Management Ministerial Council Commissioned By the Australian Government
   [Anonymous], 2006, CLIMATE CHANGE ENHAN
   Araujo M.B., 2009, Spatial conservation prioritization: Quantitative methods and computational tools, P172
   Araújo MB, 2011, ECOL LETT, V14, P484, DOI 10.1111/j.1461-0248.2011.01610.x
   Bakkenes M, 2002, GLOBAL CHANGE BIOL, V8, P390, DOI 10.1046/j.1354-1013.2001.00467.x
   Benito Garzón M, 2008, APPL VEG SCI, V11, P169, DOI 10.3170/2008-7-18348
   Berry PM, 2006, ENVIRON SCI POLICY, V9, P189, DOI 10.1016/j.envsci.2005.11.004
   Bickford S, 2004, J BIOGEOGR, V31, P787, DOI 10.1111/j.1365-2699.2003.01050.x
   Bryan BA, 2011, ECOL INDIC, V11, P199, DOI 10.1016/j.ecolind.2009.02.005
   Bryan BA, 2006, ENVIRON MANAGE, V37, P126, DOI 10.1007/s00267-004-0058-1
   Bryan BA, 2003, LANDSCAPE URBAN PLAN, V65, P237, DOI 10.1016/S0169-2046(03)00059-8
   Bryan BA, 2008, J ENVIRON MANAGE, V88, P1175, DOI 10.1016/j.jenvman.2007.06.003
   Bryan BA, 2011, CONSERV BIOL, V25, P172, DOI 10.1111/j.1523-1739.2010.01560.x
   Buisson L, 2010, GLOBAL CHANGE BIOL, V16, P1145, DOI 10.1111/j.1365-2486.2009.02000.x
   Carroll C, 2010, GLOBAL CHANGE BIOL, V16, P891, DOI 10.1111/j.1365-2486.2009.01965.x
   Carvalho SB, 2010, GLOBAL CHANGE BIOL, V16, P3257, DOI 10.1111/j.1365-2486.2010.02212.x
   Carwardine J, 2008, PLOS ONE, V3, DOI 10.1371/journal.pone.0002586
   Coetzee BWT, 2009, GLOBAL ECOL BIOGEOGR, V18, P701, DOI 10.1111/j.1466-8238.2009.00485.x
   Crossman ND, 2011, ECOL INDIC, V11, P183, DOI 10.1016/j.ecolind.2008.10.011
   Crossman ND, 2006, BIOL CONSERV, V128, P369, DOI 10.1016/j.biocon.2005.10.004
   Crossman ND, 2007, BIODIVERS CONSERV, V16, P3781, DOI 10.1007/s10531-007-9180-8
   Department of Sustainability Environment Water Population and Communities, 2010, AUSTR BIOR IBRA 6 1
   Diaz A., 2009, Ecological Restoration, V27, P257, DOI 10.3368/er.27.3.257
   Evans MC, 2011, DIVERS DISTRIB, V17, P437, DOI 10.1111/j.1472-4642.2011.00747.x
   Fielding AH, 1997, ENVIRON CONSERV, V24, P38, DOI 10.1017/S0376892997000088
   Fischer J, 2008, FRONT ECOL ENVIRON, V6, P382, DOI 10.1890/070019
   Foley JA, 2005, SCIENCE, V309, P570, DOI 10.1126/science.1111772
   Franklin JF, 2009, P NATL ACAD SCI USA, V106, P349, DOI 10.1073/pnas.0812016105
   Green RE, 2005, SCIENCE, V307, P550, DOI 10.1126/science.1106049
   Guisan A, 2000, ECOL MODEL, V135, P147, DOI 10.1016/S0304-3800(00)00354-9
   Hannah L, 2007, FRONT ECOL ENVIRON, V5, P131, DOI 10.1890/1540-9295(2007)5[131:PANIAC]2.0.CO;2
   Heikkinen RK, 2010, BIODIVERS CONSERV, V19, P695, DOI 10.1007/s10531-009-9728-x
   Hijmans RJ, 2006, GLOBAL CHANGE BIOL, V12, P2272, DOI 10.1111/j.1365-2486.2006.01256.x
   Hirzel AH, 2002, ECOLOGY, V83, P2027, DOI 10.1890/0012-9658(2002)083[2027:ENFAHT]2.0.CO;2
   Kingsford RT, 2009, CONSERV BIOL, V23, P834, DOI 10.1111/j.1523-1739.2009.01287.x
   Kozlov MV, 2008, CLIMATIC CHANGE, V87, P107, DOI 10.1007/s10584-007-9348-y
   Lehmann A, 2002, ECOL MODEL, V157, P189, DOI 10.1016/S0304-3800(02)00195-3
   Leiserowitz A, 2006, CLIMATIC CHANGE, V77, P45, DOI 10.1007/s10584-006-9059-9
   Malcolm JR, 2006, CONSERV BIOL, V20, P538, DOI 10.1111/j.1523-1739.2006.00364.x
   Marmion M, 2009, ECOL MODEL, V220, P3512, DOI 10.1016/j.ecolmodel.2008.10.019
   Marmion M, 2009, DIVERS DISTRIB, V15, P59, DOI 10.1111/j.1472-4642.2008.00491.x
   McBride MF, 2010, ECOL MODEL, V221, P2243, DOI 10.1016/j.ecolmodel.2010.04.012
   McCarty JP, 2001, CONSERV BIOL, V15, P320, DOI 10.1046/j.1523-1739.2001.015002320.x
   Midgley GF, 2006, DIVERS DISTRIB, V12, P555, DOI 10.1111/j.1366-9516.2006.00273.x
   Midgley GF, 2003, BIOL CONSERV, V112, P87, DOI 10.1016/S0006-3207(02)00414-7
   Mokany K, 2011, DIVERS DISTRIB, V17, P374, DOI 10.1111/j.1472-4642.2010.00735.x
   Neilson RP, 2005, BIOSCIENCE, V55, P749, DOI 10.1641/0006-3568(2005)055[0749:FRTGPM]2.0.CO;2
   Parmesan C, 2003, NATURE, V421, P37, DOI 10.1038/nature01286
   Pearson RG, 2005, BIOL CONSERV, V123, P389, DOI 10.1016/j.biocon.2004.12.006
   Pearson RG, 2003, GLOBAL ECOL BIOGEOGR, V12, P361, DOI 10.1046/j.1466-822X.2003.00042.x
   Pearson RG, 2006, J BIOGEOGR, V33, P1704, DOI 10.1111/j.1365-2699.2006.01460.x
   Peterson AT, 2003, GLOBAL CHANGE BIOL, V9, P647, DOI 10.1046/j.1365-2486.2003.00616.x
   Peterson AT, 2002, NATURE, V416, P626, DOI 10.1038/416626a
   Phillips S.J., 2006, Maxent software for species habitat modeling. Ver. 3.3.3k
   Phillips SJ, 2006, ECOL MODEL, V190, P231, DOI 10.1016/j.ecolmodel.2005.03.026
   Phillips SJ, 2008, ECOL APPL, V18, P1200, DOI 10.1890/07-0507.1
   PORTNOY S, 1993, EVOL ECOL, V7, P25, DOI 10.1007/BF01237733
   Raymond CM, 2009, ECOL ECON, V68, P1301, DOI 10.1016/j.ecolecon.2008.12.006
   Schneider SH, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P779
   Scholze M, 2006, P NATL ACAD SCI USA, V103, P13116, DOI 10.1073/pnas.0601816103
   Sommer JH, 2010, P ROY SOC B-BIOL SCI, V277, P2271, DOI 10.1098/rspb.2010.0120
   Stork NE, 2009, CONSERV BIOL, V23, P1438, DOI 10.1111/j.1523-1739.2009.01335.x
   Thomas CD, 2004, NATURE, V427, P145, DOI 10.1038/nature02121
   Thomas CD, 2006, TRENDS ECOL EVOL, V21, P415, DOI 10.1016/j.tree.2006.05.012
   Thuiller W, 2005, P NATL ACAD SCI USA, V102, P8245, DOI 10.1073/pnas.0409902102
   Thuiller W, 2004, GLOBAL CHANGE BIOL, V10, P2020, DOI 10.1111/j.1365-2486.2004.00859.x
   Tilman D, 2001, SCIENCE, V292, P281, DOI 10.1126/science.1057544
   Tscharntke T, 2005, ECOL LETT, V8, P857, DOI 10.1111/j.1461-0248.2005.00782.x
   Underwood E.C., 2008, PLOS ONE, V3, P7
   Vandermeer J, 2007, CONSERV BIOL, V21, P274, DOI 10.1111/j.1523-1739.2006.00582.x
   Vellend M, 2003, ECOLOGY, V84, P1067, DOI 10.1890/0012-9658(2003)084[1067:DOTSBD]2.0.CO;2
   Williams P, 2005, CONSERV BIOL, V19, P1063, DOI 10.1111/j.1523-1739.2005.00080.x
   Williams SE, 2008, PLOS BIOL, V6, P2621, DOI 10.1371/journal.pbio.0060325
   Wilson CD, 2011, DIVERS DISTRIB, V17, P182, DOI 10.1111/j.1472-4642.2010.00723.x
   Wilson RJ, 2005, ECOL LETT, V8, P1138, DOI 10.1111/j.1461-0248.2005.00824.x
   Zimmermann NE, 2009, P NATL ACAD SCI USA, V106, P19723, DOI 10.1073/pnas.0901643106
NR 79
TC 63
Z9 69
U1 1
U2 98
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 JAN
PY 2012
VL 18
IS 1
BP 60
EP 72
DI 10.1111/j.1472-4642.2011.00851.x
PG 13
WC Biodiversity Conservation; Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA 857CW
UT WOS:000297693300006
OA Green Submitted, hybrid
DA 2025-01-10
ER

PT J
AU Li, CY
   Junttila, O
   Ernstsen, A
   Heino, P
   Palva, ET
AF Li, CY
   Junttila, O
   Ernstsen, A
   Heino, P
   Palva, ET
TI Photoperiodic control of growth, cold acclimation and dormancy
   development in silver birch (<i>Betula pendula</i>) ecotypes
SO PHYSIOLOGIA PLANTARUM
LA English
DT Article
ID ENDOGENOUS ABSCISIC-ACID; FREEZING TOLERANCE; APICAL GROWTH;
   ENVIRONMENTAL-CONTROL; ECTOPIC EXPRESSION; SEASONAL-CHANGES;
   SALIX-PENTANDRA; WATER RELATIONS; LOW-TEMPERATURE; BUD DORMANCY
AB Survival and growth of temperate zone woody plants under changing seasonal conditions is dependent on proper timing of cold acclimation and development of vegetative dormancy, shortening photoperiod being an important primary signal to induce these adaptive responses. To elucidate the physiological basis for climatic adaptation in trees, we have characterized photoperiodic responses in the latitudinal ecotypes of silver birch (Betula pendula Roth) exposed to gradually shortening photoperiod under controlled conditions. In all ecotypes, shortening photoperiod triggered growth cessation, cold acclimation and dormancy development, that was accompanied by increases in endogenous abscisic acid (ABA) and decreases in indole-3-acetic acid (IAA). There were distinct differences between the ecotypes in the rates and degrees of these responses. The critical photoperiod and the photoperiodic sensitivity for growth cessation varied with latitudinal origin of the ecotype. The northern ecotype had a longer critical photoperiod and a greater photoperiodic sensitivity than the southern ecotype. Compared with the southern ecotypes, the northern ecotype was more responsive to shortening photoperiod, resulting in earlier cold acclimation, dormancy development, increase in ABA content and decrease in IAA content. However, at the termination of the experiment, all the ecotypes had reached approximately the same level of cold hardiness (-12 to -14degreesC), ABA content (2.1-2.3 mug g(-1) FW) and IAA content (17.2-20.3 ng g(-1) FW). In all ecotypes, increase in ABA levels preceded development of bud dormancy and maximum cold hardiness. IAA levels decreased more or less parallel with increasing cold hardiness and dormancy, suggesting a role of IAA in the photoperiodic control of growth, cold acclimation and dormancy development in birch.
C1 Univ Helsinki, Dept Biosci, Div Genet, FIN-00014 Helsinki, Finland.
   Univ Helsinki, Inst Biotechnol, Viikki Bioctr, FIN-00014 Helsinki, Finland.
   Chinese Acad Sci, Chengdu Inst Biol, Chengdu 610041, Peoples R China.
   Univ Tromso, Dept Biol, N-9037 Tromso, Norway.
   Univ Helsinki, Dept Appl Biol, FIN-00014 Helsinki, Finland.
C3 University of Helsinki; University of Helsinki; Chinese Academy of
   Sciences; Chengdu Institute of Biology, CAS; UiT The Arctic University
   of Tromso; University of Helsinki
RP Univ Helsinki, Dept Biosci, Div Genet, POB 56, FIN-00014 Helsinki, Finland.
EM tapio.palva@helsinki.fi
RI li, chun yang/D-6254-2013
OI li, chun yang/0000-0003-2895-2786
CR ALVIM R, 1976, PLANT PHYSIOL, V57, P474, DOI 10.1104/pp.57.4.474
   ALVIM R, 1979, PLANT PHYSIOL, V63, P774, DOI 10.1104/pp.63.4.774
   Baldwin BD, 1998, PHYSIOL PLANTARUM, V102, P201, DOI 10.1034/j.1399-3054.1998.1020207.x
   BARROS RS, 1986, PLANTA, V168, P530, DOI 10.1007/BF00392273
   BEHRINGER FJ, 1992, PLANTA, V188, P85, DOI 10.1007/BF00198943
   CHEN HH, 1983, PLANT PHYSIOL, V71, P362, DOI 10.1104/pp.71.2.362
   CHEN THH, 1983, PLANT PHYSIOL, V73, P71, DOI 10.1104/pp.73.1.71
   Davies W.J., 1991, Abscisic acid: Physiology and biochemistry
   EAGLES CF, 1963, NATURE, V199, P874, DOI 10.1038/199874a0
   EDLUND A, 1995, PLANT PHYSIOL, V108, P1043, DOI 10.1104/pp.108.3.1043
   FARMER RE, 1993, SILVAE GENET, V42, P148
   Fladung M, 1997, J PLANT PHYSIOL, V150, P420, DOI 10.1016/S0176-1617(97)80092-2
   GIRAUDAT J, 1994, PLANT MOL BIOL, V26, P1557, DOI 10.1007/BF00016490
   HABJORG A, 1972, Meldinger fra Norges Landbrukshogskole, V51, P1
   HABJORG A, 1978, MELD NORG LANDBRUKS, V57, P2
   HEIDE OM, 1974, PHYSIOL PLANTARUM, V30, P1, DOI 10.1111/j.1399-3054.1974.tb04983.x
   HOWE GT, 1995, PHYSIOL PLANTARUM, V93, P695, DOI 10.1111/j.1399-3054.1995.tb05119.x
   IRVING RM, 1967, PLANT PHYSIOL, V42, P1191, DOI 10.1104/pp.42.9.1191
   JOHANSEN LG, 1986, PHYSIOL PLANTARUM, V66, P409, DOI 10.1111/j.1399-3054.1986.tb05943.x
   JONES AM, 1991, PLANT PHYSIOL, V97, P352, DOI 10.1104/pp.97.1.352
   JUNTTILA O, 1976, PHYSIOL PLANTARUM, V38, P278, DOI 10.1111/j.1399-3054.1976.tb04004.x
   JUNTTILA O, 1982, J EXP BOT, V33, P1021, DOI 10.1093/jxb/33.5.1021
   JUNTTILA O, 1980, PHYSIOL PLANTARUM, V48, P347, DOI 10.1111/j.1399-3054.1980.tb03266.x
   JUNTTILA O, 1978, Z PFLANZENPHYSIOL, V87, P455, DOI 10.1016/S0044-328X(78)80151-2
   Junttila O, 1990, SCAND J FOREST RES, V5, P195, DOI 10.1080/02827589009382605
   LANG V, 1989, THEOR APPL GENET, V77, P729, DOI 10.1007/BF00261251
   LANG V, 1994, PLANT PHYSIOL, V104, P1341, DOI 10.1104/pp.104.4.1341
   LENTON JR, 1972, PLANTA, V106, P13, DOI 10.1007/BF00385469
   Li CY, 2002, PHYSIOL PLANTARUM, V116, P478, DOI 10.1034/j.1399-3054.2002.1160406.x
   MCKENZIE JS, 1974, J AM SOC HORTIC SCI, V99, P223
   MYKING T, 1997, THESIS AGR U NORWAY, V15
   NITSCH J. P., 1957, PROC AMER SOC HORT SCI, V70, P526
   Olsen JE, 1997, PLANT J, V12, P1339, DOI 10.1046/j.1365-313x.1997.12061339.x
   Olsen JE, 1997, PLANT CELL PHYSIOL, V38, P536, DOI 10.1093/oxfordjournals.pcp.a029202
   PARSONS LR, 1978, PLANT PHYSIOL, V62, P64, DOI 10.1104/pp.62.1.64
   Pauley S. S., 1954, Journal of the Arnold Arboretum, V35, P167
   POWELL LE, 1987, HORTSCIENCE, V22, P845
   RINNE P, 1994, PHYSIOL PLANTARUM, V90, P451, DOI 10.1111/j.1399-3054.1994.tb08801.x
   RINNE P, 1994, TREE PHYSIOL, V14, P549, DOI 10.1093/treephys/14.6.549
   Rinne P, 1998, PLANT CELL ENVIRON, V21, P601, DOI 10.1046/j.1365-3040.1998.00306.x
   Ross JJ, 2001, J PLANT GROWTH REGUL, V20, P346, DOI 10.1007/s003440010034
   SUKUMARAN N P, 1972, Hortscience, V7, P467
   Tamminen I, 2001, PLANT J, V25, P1, DOI 10.1046/j.1365-313x.2001.00927.x
   Thomas B., 1996, PHOTOPERIODISM PLANT, V2nd ed., P118
   WAREING PF, 1971, ANN REV PLANT PHYSIO, V22, P261, DOI 10.1146/annurev.pp.22.060171.001401
   WEISER CJ, 1970, SCIENCE, V169, P1269, DOI 10.1126/science.169.3952.1269
   Welling A, 1997, PHYSIOL PLANTARUM, V100, P119, DOI 10.1034/j.1399-3054.1997.1000112.x
   WRIGHT STC, 1975, J EXP BOT, V26, P161, DOI 10.1093/jxb/26.2.161
NR 48
TC 110
Z9 132
U1 1
U2 47
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0031-9317
EI 1399-3054
J9 PHYSIOL PLANTARUM
JI Physiol. Plant.
PD FEB
PY 2003
VL 117
IS 2
BP 206
EP 212
DI 10.1034/j.1399-3054.2003.00002.x
PG 7
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA 650VL
UT WOS:000181284000007
DA 2025-01-10
ER

PT J
AU Varyvoda, Y
   Foerster, TA
   Mikkola, J
   Mars, MM
AF Varyvoda, Yevheniia
   Foerster, Taylor Ann
   Mikkola, Joona
   Mars, Matthew M.
TI Promising Nature-Based Solutions to Support Climate Adaptation of
   Arizona's Local Food Entrepreneurs and Optimize One Health
SO SUSTAINABILITY
LA English
DT Article
DE nature-based solutions; local food systems; entrepreneurs; climate
   change; community innovation
ID WATER; AGRICULTURE; MITIGATION; FARMERS
AB This study explores the uptake and potential application of nature-based solutions (NbS) that are particularly promising for small-scale farmers, ranchers, and food entrepreneurs operating in arid and semi-arid regions. Studying the adoption of NbS by local food entrepreneurs (LFEs), including related strengths and limitations, remains an area of exploration due to their potential to optimize interventions that foster environmental sustainability at the intersection of people, animals, and natural ecosystems (i.e., One Health). A multi-method design was used, including literature review, questionnaires, and semi-structured key informant interviews to assess adaptation needs and NbS among a sample of LFEs located in Southern AZ, USA. The findings revealed that existing NbS have been introduced mostly through learning-by-doing practices that are bounded by economic and technological resource constraints. The paper describes a range of accessible approaches and practices that can be piloted and/or scaled up to enhance local food system resilience and contribute to the overlapping health of people, animals, and natural ecosystems. The priority adaptation pathways for NbS were identified to be funding and financing and the co-creation and sharing of knowledge through peer-to-peer and expert-to-peer approaches. The results suggested that AZ LFEs are likely to adopt NbS based on their capacity to address priority climate-driven issues, revenue generation potential, and seamless augmentation with existing food production and operational activities.
C1 [Varyvoda, Yevheniia] Univ Arizona, Mel & Enid Zuckerman Coll Publ Hlth, Tucson, AZ 85724 USA.
   [Foerster, Taylor Ann] Univ Arizona, Coll Social & Behav Sci, Tucson, AZ 85719 USA.
   [Mikkola, Joona] Univ Arizona, Arid Lands Resource Sci, Tucson, AZ 85719 USA.
   [Mars, Matthew M.] Univ Arizona, Coll Humanities, Tucson, AZ 85721 USA.
C3 University of Arizona; University of Arizona; University of Arizona;
   University of Arizona
RP Varyvoda, Y (corresponding author), Univ Arizona, Mel & Enid Zuckerman Coll Publ Hlth, Tucson, AZ 85724 USA.
EM varyvoda@arizona.edu; tfoerster@arizona.edu; joonamikkola@arizona.edu;
   mmars@arizona.edu
RI Mars, Matthew/AAT-1499-2020
FU The University of Arizona Health Sciences
FX No Statement Available
CR Acevedo M, 2020, NAT PLANTS, V6, P1231, DOI 10.1038/s41477-020-00783-z
   Adisasmito WB, 2022, PLOS PATHOG, V18, DOI 10.1371/journal.ppat.1010537
   AJZEN I, 1991, ORGAN BEHAV HUM DEC, V50, P179, DOI 10.1016/0749-5978(91)90020-T
   Al-Dawood A, 2017, ANN ANIM SCI, V17, P59, DOI 10.1515/aoas-2016-0068
   Amonette J.E., 2023, Technical Assessment of Potential Climate Impact and Economic Viability of Biochar Technologies for Small-Scale Agriculture in the Pacific Northwest
   [Anonymous], 2022, USDA Smart Nutrient Management
   [Anonymous], 2022, State Climate Summaries 2022 150-NJ
   AZDA Resilient Food Systems Infrastructure (RFSI), 2023, Program
   AZFB, 2022, Assessing Western Drought Conditions 2022: Arizona Farm Bureau
   Bainbridge DA, 2001, AGR WATER MANAGE, V48, P79, DOI 10.1016/S0378-3774(00)00119-0
   BIERNACKI P, 1981, SOCIOL METHOD RES, V10, P141, DOI 10.1177/004912418101000205
   Blaufelder C., 2021, A blueprint for scaling voluntary carbon markets to meet the climate challenge
   Bloomberg, 2023, Long-Term Carbon Offsets Outlook 2023
   Brears R. C., 2022, FINANCING NATURE BAS, P29, DOI DOI 10.1007/978-3-030-93325-8_3
   Brears R.C., 2022, Financing Nature-Based Solutions: Exploring Public, Private, and Blended Finance Models and Case Studies, P1
   Brugger J, 2013, GLOBAL ENVIRON CHANG, V23, P1830, DOI 10.1016/j.gloenvcha.2013.07.012
   Burton RJF, 2022, J RURAL STUD, V96, P270, DOI 10.1016/j.jrurstud.2022.10.006
   Census U.S, 2023, QuickFacts
   CEQ, 2023, Nature-Based Solutions Resource Guide 2.0
   Cibils AF, 2023, J ARID ENVIRON, V209, DOI 10.1016/j.jaridenv.2022.104886
   Condon L.E., 2023, The Presidential Advisory Commission on the Future of Agriculture and Food Production in a Drying Climate
   Corbin J.M., 2015, Basics of qualitative research: Techniques and procedures for developing grounded theory (4th ed), V4th, DOI 10.4135/9781452230153
   Crouch M, 2006, SOC SCI INFORM, V45, P483, DOI 10.1177/0539018406069584
   Danquah F O., 2019, Agricultural Research Technology, V21, P13, DOI [DOI 10.19080/ARTOAJ.2019.21.556150, 10.19080/ARTOAJ.2019.21.556150]
   de Lima CZ, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abeb9f
   den Heijer C, 2023, J ENVIRON MANAGE, V337, DOI 10.1016/j.jenvman.2023.117754
   Egan P.A., 2021, Environ. Sci. Agric. Food Sci
   EIB, 2023, Investing in Nature-Based Solutions. State-of-Play and Way Forward for Public and Private Financial Measures in Europe
   Frankson R., 2022, Arizona State Climate Summary 2022
   Garfin G, 2013, NCA REGION INPUT REP, P21, DOI 10.5822/978-1-61091-484-0_2
   Guinet Mae, 2023, Nat Commun, V14, P7416, DOI 10.1038/s41467-023-43234-x
   Haya B.K., 2024, Voluntary Registry Offsets Database V2024-10 2024
   Hovis M, 2023, J SOIL WATER CONSERV, V78, P500, DOI [10.2489/jSWC.2023.00131, 10.2489/jswc.2023.00131]
   Huang YW, 2023, RENEW SUST ENERG REV, V172, DOI 10.1016/j.rser.2022.113042
   Idowu O., 2014, Agricultural Experiment Station and Cooperative Extension Service, New Mexico State University Circular
   ILO UNEP IUCN, 2022, Decent Work in Nature-Based Solutions 2022
   Ishtiaque A, 2023, ENVIRON RES-CLIM, V2, DOI 10.1088/2752-5295/accb03
   IUCN, 2020, Guidance for using the IUCN Global Standard for Naturebased Solutions: first edition
   IUCN, 2023, Highlights Brief on WHO-IUCN Report on Designing NatureBased Solutions for Human Health
   Jarimi H, 2020, INT J LOW-CARBON TEC, V15, P253, DOI 10.1093/ijlct/ctz072
   Johnson B A., 2022, Nature-Based Solutions, V2, P100042, DOI DOI 10.1016/J.NBSJ.2022.100042
   Kacira M., 2022, Controlled Environment Agriculture
   Kragt ME, 2021, J CLEAN PROD, V321, DOI 10.1016/j.jclepro.2021.128967
   Lamonaca E, 2023, AGR FOOD SECUR, V11, DOI 10.1186/s40066-022-00399-w
   Librán-Embid F, 2023, AGRON SUSTAIN DEV, V43, DOI 10.1007/s13593-023-00896-7
   Lincoln Y. S., 1985, Naturalistic inquiry
   Lookadoo RE, 2020, J LAW MED ETHICS, V48, P653, DOI 10.1177/1073110520979372
   Lord J, 2021, NATURE, V598, P611, DOI 10.1038/s41586-021-03900-w
   Lynch H., 2018, Food Stud. Interdiscip. J, V8, P45, DOI [10.18848/2160-1933/CGP/v08i02/45-56, DOI 10.18848/2160-1933/CGP/V08I02/45-56]
   Mahmood A, 2018, SCI HORTIC-AMSTERDAM, V241, P241, DOI 10.1016/j.scienta.2018.06.078
   Maraveas C, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12093625
   Mars MM, 2019, RURAL SOCIOL, V84, P257, DOI 10.1111/ruso.12244
   Mars MM, 2018, RURAL SOCIOL, V83, P568, DOI 10.1111/ruso.12197
   Maxwell J.A, 2012, Qualitative Research Design. An Interactive Approach
   Mayor B, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13137413
   Miller ZD, 2019, ENVIRON MANAGE, V63, P366, DOI 10.1007/s00267-019-01139-w
   Mizik T, 2023, PRECIS AGRIC, V24, P384, DOI 10.1007/s11119-022-09934-y
   Mizik T, 2021, AGRONOMY-BASEL, V11, DOI 10.3390/agronomy11061096
   Mostafa A.M., 2022, Urban, Small-Scale, and Beginner Farmer Needs Assessment
   Mpanga I., 2022, High Tunnels: The University of Arizona Cooperative Extension
   Mpanga I., Contract No.: az18512020
   Mpanga I.K., 2023, The Palgrave Handbook of Global Sustainability, P381
   Mpanga IK, 2021, CURR RES ENVIRON SUS, V3, DOI 10.1016/j.crsust.2021.100067
   Mpanga IK, 2020, ADV SUSTAIN SYST, V4, DOI 10.1002/adsu.201900143
   Nabhan G.P., 2023, Future Scenarios Addressing Water Scarcity in the Lower Colorado River Basin
   NASS U, 2017 Census of Agriculture, Census Data Query Tool (CDQT) 2019
   Ntawuruhunga D, 2023, FOREST POLICY ECON, V150, DOI 10.1016/j.forpol.2023.102937
   Olle M, 2021, J HORTIC SCI BIOTECH, V96, P145, DOI 10.1080/14620316.2020.1810140
   Pathak A., 2022, Incorporating Nature-based Solutions in Community Climate Adaptation Planning. National Wildlife Federation
   Rai PK, 2023, J CLEAN PROD, V418, DOI 10.1016/j.jclepro.2023.138194
   Rao AP, 2022, CURR OPIN FOOD SCI, V47, DOI 10.1016/j.cofs.2022.100877
   Richards D., 2020, Building Sustainable Farms, Ranches, and Communities: A Guide to Federal Programs for Sustainable Agriculture, Forestry, Entrepreneurship, Conservation, Food Systems, and Community Development
   Robinson J.O., 2000, Why Grassfed Is Best!: The Surprising Benefits of Grassfed Meats, Eggs, and Dairy Products, P128
   Rosales BH, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su15042891
   Rust NA, 2022, ENVIRON MANAGE, V69, P31, DOI 10.1007/s00267-021-01546-y
   Salafsky N., 2021, Taking Nature-Based Solutions Programs to Scale
   Saliman A, 2022, RANGELAND ECOL MANAG, V84, P75, DOI 10.1016/j.rama.2022.06.001
   Senger I, 2017, J RURAL STUD, V49, P32, DOI 10.1016/j.jrurstud.2016.10.006
   Shrivastava C., 2023, Front. Food Sci. Technol, V3, P1100181, DOI [10.3389/frfst.2023.1100181, DOI 10.3389/FRFST.2023.1100181]
   Sojka M., 2022, Smart Agrochemicals for Sustainable Agriculture, P279
   Sutherland LA, 2017, LAND USE POLICY, V63, P428, DOI 10.1016/j.landusepol.2017.01.028
   Tariq Z, 2023, RSC ADV, V13, P24731, DOI 10.1039/d3ra03472k
   Thomas G, 2023, BIOMOLECULES, V13, DOI 10.3390/biom13060997
   Thompson A, 2023, SUSTAIN DEV, V31, P1991, DOI 10.1002/sd.2510
   Tucson C., 2023, Rainwater Harvesting Rebate
   UNEP, 2023, State of Finance for Nature: The Big Nature TurnaroundRepurposing $7 Trillion to Combat Nature Loss
   USDA, 2023, Report to Congress: A General Assessment of the Role of Agriculture and Forestry in U.S. Carbon Markets
   USDA, 2020, Evaluation of Cool Season Cover Crops in the Southwest Region
   USDA National Agricultural Statistics Service, 2018, About us
   Van Raalte D., 2023, Financing Nature-Based Solutions for Adaptation at Scale: Learning from Specialised Investment Managers and Nature Funds
   White D.D., 2023, Fifth National Climate Assessment
   White House Office of Science and Technology Policy, 2022, Report to the National Climate Task Force
   WIPO, 2022, Green Technology Book: Solutions for Climate Change Adaptation
   Zhao GX, 2024, GEOGR SUSTAIN, V5, P19, DOI 10.1016/j.geosus.2023.09.006
NR 94
TC 1
Z9 1
U1 7
U2 7
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD APR
PY 2024
VL 16
IS 8
AR 3176
DI 10.3390/su16083176
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 OW8I8
UT WOS:001210402200001
OA gold
DA 2025-01-10
ER

PT J
AU Carr, AB
   Trigg, MA
   Haile, AT
   Bernhofen, MV
   Alemu, AN
   Bekele, TW
   Walsh, CL
AF Carr, Andrew B.
   Trigg, Mark A.
   Haile, Alemseged Tamiru
   Bernhofen, Mark V.
   Alemu, Abel Negussie
   Bekele, Tilaye Worku
   Walsh, Claire L.
TI Using global datasets to estimate flood exposure at the city scale: an
   evaluation in Addis Ababa
SO FRONTIERS IN ENVIRONMENTAL SCIENCE
LA English
DT Article
DE floods; cities; global datasets; rain-on-grid model; hydraulic model;
   risk
ID RISK; HAZARD; VULNERABILITY; RESOLUTION; EFFICIENCY; SATELLITE;
   ACCURACY; ENHANCE; BASIN; DEM
AB Introduction: Cities located in lower income countries are global flood risk hotspots. Assessment and management of these risks forms a key part of global climate adaptation efforts. City scale flood risk assessments necessitate flood hazard information, which is challenging to obtain in these localities because of data quality/scarcity issues, and the complex multi-source nature of urban flood dynamics. A growing array of global datasets provide an attractive means of closing these data gaps, but their suitability for this context remains relatively unknown.Methods: Here, we test the use of relevant global terrain, rainfall, and flood hazard data products in a flood hazard and exposure assessment framework covering Addis Ababa, Ethiopia. To conduct the tests, we first developed a city scale rain-on-grid hydrodynamic flood model based on local data and used the model results to identify buildings exposed to flooding. We then observed how the results of this flood exposure assessment changed when each of the global datasets are used in turn to drive the hydrodynamic model in place of its local counterpart.Results and discussion: Results are evaluated in terms of both the total number of exposed buildings, and the spatial distribution of exposure across Addis Ababa. Our results show that of the datasets tested, the FABDEM global terrain and the PXR global rainfall data products provide the most promise for use at the city scale in lower income countries.
C1 [Carr, Andrew B.; Trigg, Mark A.] Univ Leeds, Sch Civil Engn, Leeds, England.
   [Haile, Alemseged Tamiru; Alemu, Abel Negussie; Bekele, Tilaye Worku] Int Water Management Inst, Addis Ababa, Ethiopia.
   [Bernhofen, Mark V.] Univ Oxford, Smith Sch Enterprise & Environm, Oxford, England.
   [Alemu, Abel Negussie; Bekele, Tilaye Worku] Arba Minch Univ, Water Technol Inst, Arba Minch, Ethiopia.
   [Walsh, Claire L.] Newcastle Univ, Sch Engn, Newcastle Upon Tyne, England.
C3 University of Leeds; CGIAR; International Water Management Institute
   (IWMI); University of Oxford; Arba Minch University; Newcastle
   University - UK
RP Carr, AB (corresponding author), Univ Leeds, Sch Civil Engn, Leeds, England.
EM a.b.carr@leeds.ac.uk
RI Trigg, Mark/A-5898-2010
FU UK Research and Innovation10.13039/100014013; GCRF [ES/S008179/1]
   Funding Source: UKRI
FX No Statement Available
CR 3SPROSPECT, 2021, 1D-2D flood modelling for the labasa by-pass Project, Fiji
   Adugna D, 2019, J HYDROL-REG STUD, V25, DOI 10.1016/j.ejrh.2019.100626
   Alaska Satellite Facility, 2015, PALSAR RTC DEM information
   Annis A, 2019, HYDROLOG SCI J, V64, P525, DOI 10.1080/02626667.2019.1591623
   [Anonymous], 2017, Climate Change Risk in Syria: Country Risk Profile
   Arcement G.J., 1984, GUIDE SELECTING MANN
   Bates PD, 2021, WATER RESOUR RES, V57, DOI 10.1029/2020WR028673
   Bekele TW., 2022, Nat Hazards Res, V2, P97, DOI [10.1016/j.nhres.2022.03.001, DOI 10.1016/J.NHRES.2022.03.001]
   Bernhofen MV, 2023, ENVIRON RES LETT, V18, DOI 10.1088/1748-9326/acd8d0
   Bernhofen MV, 2022, WATER RESOUR RES, V58, DOI 10.1029/2021WR031555
   Bernhofen MV, 2021, NAT HAZARD EARTH SYS, V21, P2829, DOI 10.5194/nhess-21-2829-2021
   Bernhofen MV, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aae014
   Birhanu D, 2016, PROCEDIA ENGINEER, V154, P696, DOI 10.1016/j.proeng.2016.07.571
   BMT Group Ltd, 2019, Catchment based flood mitigation and planning
   Brunner G. W., 2020, HEC-RAS hydraulic reference manual, V6
   Brunner G. W., 2020, CPD-68A)
   Cai T, 2019, INT J DISAST RISK RE, V35, DOI 10.1016/j.ijdrr.2019.101077
   Cantoni E, 2022, J HYDROL-REG STUD, V42, DOI 10.1016/j.ejrh.2022.101169
   Chen HL, 2018, J HYDROL, V559, P56, DOI 10.1016/j.jhydrol.2018.01.056
   Copernicus, 2021, Copernicus DEM - global and European digital elevation model
   Courty LG, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab370a
   Cronshey R., 1986, Urban hydrology for small watersheds
   da Costa RT, 2019, FRONT EARTH SC-SWITZ, V7, DOI 10.3389/feart.2019.00141
   De Paola F, 2018, HYDROLOGY-BASEL, V5, DOI 10.3390/hydrology5020028
   De Risi R, 2020, NAT HAZARDS, V100, P387, DOI 10.1007/s11069-019-03817-8
   Domeneghetti A, 2016, WATER RESOUR RES, V52, P2901, DOI 10.1002/2015WR017967
   Dottori F, 2016, ADV WATER RESOUR, V94, P87, DOI 10.1016/j.advwatres.2016.05.002
   Dusseau D., 2023, Climate risk assessment: Addis ababa, Ethiopia
   Egbinola CN, 2017, J FLOOD RISK MANAG, V10, P546, DOI 10.1111/jfr3.12157
   Ekeu-Wei IT, 2018, HYDROLOGY-BASEL, V5, DOI 10.3390/hydrology5030039
   Emerton R, 2020, INT J DISAST RISK RE, V50, DOI 10.1016/j.ijdrr.2020.101811
   Englhardt J, 2019, NAT HAZARD EARTH SYS, V19, P1703, DOI 10.5194/nhess-19-1703-2019
   Farr TG, 2007, REV GEOPHYS, V45, DOI 10.1029/2005RG000183
   Fathom, 2019, Fathom-global 2.0
   Fleischmann A, 2019, J HYDROL X, V3, DOI 10.1016/j.hydroa.2019.100027
   Gleason CJ, 2015, PROG PHYS GEOG, V39, P337, DOI 10.1177/0309133314567584
   Gleixner S, 2020, ATMOSPHERE-BASEL, V11, DOI 10.3390/atmos11090996
   Golder Associates, 2021, Satellite-based rainfall data closing meteorological data gaps
   Courty LG, 2019, J FLOOD RISK MANAG, V12, DOI 10.1111/jfr3.12550
   Haile AT, 2016, INT J APPL EARTH OBS, V52, P475, DOI 10.1016/j.jag.2016.06.021
   Hawker L., 2023, Natural Hazards and Earth System Sciences Discussions, P1, DOI [10.5194/nhess-2023-93, DOI 10.5194/NHESS-2023-93]
   Hawker L, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac4d4f
   Hawker L, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/abc216
   Hawker L, 2018, FRONT EARTH SC-SWITZ, V6, DOI 10.3389/feart.2018.00233
   Hersbach H, 2020, Q J ROY METEOR SOC, V146, P1999, DOI 10.1002/qj.3803
   Horrit M., 2009, Sewer capacity and infiltration analysis
   Keaney M., 2015, CITIES100: 100 solutions for climate action in cities
   Kettner A., 2019, Eos, V100, P19, DOI [10.1029/2019eo113857, DOI 10.1029/2019EO113857]
   Komi K, 2017, J HYDROL-REG STUD, V10, P122, DOI 10.1016/j.ejrh.2017.03.001
   Lamb R, 2009, P I CIVIL ENG-WAT M, V162, P363, DOI 10.1680/wama.2009.162.6.363
   Leopold L. B  ..., 1953, The Hydraulic Geometry of Stream Channels and Some Physiographic Implications, V252, DOI 10.3133/pp252
   Li CX, 2022, SCI REP-UK, V12, DOI 10.1038/s41598-022-07720-4
   Lindersson S, 2020, WIRES WATER, V7, DOI 10.1002/wat2.1424
   Lindsay J. B., 2018, A new method for the removal of off-terrain objects from LiDAR-derived raster surface models
   Lumbroso D, 2020, J FLOOD RISK MANAG, V13, DOI 10.1111/jfr3.12612
   Martel JL, 2021, J HYDROL ENG, V26, DOI 10.1061/(ASCE)HE.1943-5584.0002122
   McClean F., 2021, Hydrology Earth Syst. Sci. Discuss, P1, DOI [10.5194/hess-2021-153, DOI 10.5194/HESS-2021-153]
   McClean F, 2020, WATER RESOUR RES, V56, DOI 10.1029/2020WR028241
   Mercogliano P., 2022, Flood risk indicators for European cities from 1989 to 2018.Copernicus climate change service (C3S) climate data store (CDS)
   Merz B, 2009, NAT HAZARDS, V51, P437, DOI 10.1007/s11069-009-9452-6
   Minderhoud PSJ, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-11602-1
   Molinari D, 2019, INT J DISAST RISK RE, V33, P441, DOI 10.1016/j.ijdrr.2018.10.022
   Neal J, 2021, WATER RESOUR RES, V57, DOI 10.1029/2020WR028301
   Neal J, 2012, WATER RESOUR RES, V48, DOI 10.1029/2012WR012514
   OpenStreetMap contributors, 2022, OpenStreetMap contributors
   Quinn N, 2019, WATER RESOUR RES, V55, P1890, DOI 10.1029/2018WR024205
   Reder A, 2022, WEATHER CLIM EXTREME, V35, DOI 10.1016/j.wace.2022.100407
   Rentschler J, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-30727-4
   Rivosecchi A, 2023, WATER-SUI, V15, DOI 10.3390/w15223936
   Ross CW, 2018, SCI DATA, V5, DOI 10.1038/sdata.2018.91
   Rudari R., 2015, Improvement of the global flood model for the GAR 2015
   Ryan Ph., 2022, HYDROLOGY WATER RESO
   Saksena S, 2015, J HYDROL, V530, P180, DOI 10.1016/j.jhydrol.2015.09.069
   Sampson CC, 2015, WATER RESOUR RES, V51, P7358, DOI 10.1002/2015WR016954
   Sayers and Partners, 2019, A report for the inter-American development bank produced in association with vivid economics and aether
   Sayers P., 2020, Third UK climate change risk assessment (CCRA3): future flood risk
   Scharffenberg B., 2018, HYDROLOGIC MODELING
   Schumann GJP, 2013, WATER RESOUR RES, V49, P6248, DOI 10.1002/wrcr.20521
   Schumann GJP, 2018, FRONT EARTH SC-SWITZ, V6, DOI 10.3389/feart.2018.00225
   Schumann GJP, 2018, REMOTE SENS-BASEL, V10, DOI 10.3390/rs10081230
   Scottish Environment Protection Agency, 2018, Flood modelling guidance for responsible authorities
   Shouler M., 2021, City Water Resil. Approach
   Sirko W., 2021, Corr. abs/2107, P12283, DOI [10.48550/arXiv.2107.12283, DOI 10.48550/ARXIV.2107.12283]
   Tanim AH, 2022, WATER-SUI, V14, DOI 10.3390/w14071140
   Tellman B, 2021, NATURE, V596, P80, DOI 10.1038/s41586-021-03695-w
   Trigg MA, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/9/094014
   Trigg M. A., 2021, Global drought and flood: Observation Modeling, and Prediction, P181
   UK Environment Agency, 2019, What is the risk of flooding from surface water map?
   Uuemaa E, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12213482
   van de Giesen N, 2014, WIRES WATER, V1, P341, DOI 10.1002/wat2.1034
   van Leuwen Z., 2019, Improving surface water flood mapping: estimating local drainage rates
   Ward P.J., 2020, Aqueduct Floods Methodology, P1
   Ward PJ, 2015, NAT CLIM CHANGE, V5, P712, DOI 10.1038/nclimate2742
   Winsemius HC, 2013, HYDROL EARTH SYST SC, V17, P1871, DOI 10.5194/hess-17-1871-2013
   World Bank, 2015, Resilient Cities Program, P1
   Xing Y, 2022, J HYDROL, V605, DOI 10.1016/j.jhydrol.2021.127365
   Xu HQ, 2006, INT J REMOTE SENS, V27, P3025, DOI 10.1080/01431160600589179
   Yamazaki D, 2017, GEOPHYS RES LETT, V44, P5844, DOI 10.1002/2017GL072874
   Yamazaki D, 2013, WATER RESOUR RES, V49, P7221, DOI 10.1002/wrcr.20552
   Yamazaki D, 2011, WATER RESOUR RES, V47, DOI 10.1029/2010WR009726
   Yu DP, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/12/124011
   Zanaga D., 2021, ESA WORLDCOVER 10 M
   Zhao G, 2023, WATER RESOUR RES, V59, DOI 10.1029/2022WR032395
   Zhou XD, 2021, NAT HAZARD EARTH SYS, V21, P1071, DOI 10.5194/nhess-21-1071-2021
NR 104
TC 2
Z9 2
U1 3
U2 8
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 FEB 12
PY 2024
VL 12
AR 1330295
DI 10.3389/fenvs.2024.1330295
PG 14
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA IY4Z8
UT WOS:001169901300001
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Chi, HJ
   Wu, YH
   Zheng, HX
   Zhang, B
   Sun, ZH
   Yan, JH
   Ren, YK
   Guo, LA
AF Chi, Haojing
   Wu, Yanhong
   Zheng, Hongxing
   Zhang, Bing
   Sun, Zhonghua
   Yan, Jiaheng
   Ren, Yongkang
   Guo, Linan
TI Spatial patterns of climate change and associated climate hazards in
   Northwest China
SO SCIENTIFIC REPORTS
LA English
DT Article
ID HEAT WAVES; MORTALITY; EXTREMES; PRECIPITATION; IMPACTS
AB Northwest China (NWC) is experiencing noticeable climate change accompanied with increasing impacts of climate hazards induced by changes in climate extremes. Towards developing climate adaptation strategies to mitigate the negative climatic impacts on both the ecosystem and socioeconomic system of the region, this study investigates systematically the spatial patterns of climate change and the associated climate hazards across NWC based on high resolution reanalysis climate dataset for the period 1979 to 2018. We find that NWC overall is under a warming and wetting transition in climate with change rate of temperature and precipitation around 0.49 degrees C/10a and 22.8 mm/10a respectively. Characteristics of climate change over the NWC however vary considerably in space. According to significance of long-term trends in both temperature and aridity index for each 0.1 degrees x0.1 degrees grids, five types of climate change are identified across NWC, including warm-wetting, warm-drying, warm without wetting, wetting without warming and unchanging. The warm-wetting zone accounts for the largest proportion of the region (41%) and mainly locates in the arid or semi-arid northwestern NWC. Our findings show most region of NWC is under impacts of intensifying heatwave and rainstorm due to significant increases in high temperature extremes and precipitation extremes. The warming but without wetting zone is found under a more severe impact of heatwave, particularly for areas near northern Mount. Qinling and northern Loess Plateau. Areas with stronger wetting trend is suffering more from rainstorm.
C1 [Chi, Haojing; Wu, Yanhong; Zhang, Bing; Yan, Jiaheng; Ren, Yongkang] Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China.
   [Chi, Haojing; Wu, Yanhong; Zhang, Bing; Yan, Jiaheng; Ren, Yongkang] Int Res Ctr Big Data Sustainable Dev Goals, Beijing 100094, Peoples R China.
   [Chi, Haojing; Zhang, Bing; Yan, Jiaheng; Ren, Yongkang] Univ Chinese Acad Sci, Beijing 100049, Peoples R China.
   [Zheng, Hongxing] CSIRO Environm, Canberra, ACT 2601, Australia.
   [Sun, Zhonghua] Network & Informat Ctr Changjiang River Water Res, Wuhan 430010, Hubei, Peoples R China.
   [Guo, Linan] Chinese Acad Sci, Inst Tibetan Plateau Res, Beijing 100094, Peoples R China.
C3 Chinese Academy of Sciences; Aerospace Information Research Institute,
   CAS; Chinese Academy of Sciences; International Research Center of Big
   Data for Sustainable Development Goals; Chinese Academy of Sciences;
   University of Chinese Academy of Sciences, CAS; Commonwealth Scientific
   & Industrial Research Organisation (CSIRO); Chinese Academy of Sciences;
   Institute of Tibetan Plateau Research, CAS
RP Wu, YH (corresponding author), Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China.; Wu, YH (corresponding author), Int Res Ctr Big Data Sustainable Dev Goals, Beijing 100094, Peoples R China.; Zheng, HX (corresponding author), CSIRO Environm, Canberra, ACT 2601, Australia.
EM wuyh@radi.ac.cn; hongxing.zheng@csiro.au
RI Zhang, Bing/JOZ-7091-2023; yan, jiaheng/HOH-5992-2023; Zheng,
   Hongxing/E-6297-2017
FU National Key Research and Development Program of China [2021YFB3901202]
FX This work was jointly supported by the National Key Research and
   Development Program of China (2021YFB3901202). We would also like to
   thank the Climate Data Center, National Meteorological Information
   Center, China Meteorological Administration, for providing the long-term
   meteorological data.
CR AghaKouchak A, 2020, ANNU REV EARTH PL SC, V48, P519, DOI 10.1146/annurev-earth-071719-055228
   Allan RP, 2020, ANN NY ACAD SCI, V1472, P49, DOI 10.1111/nyas.14337
   [Anonymous], 2014, Climate Change 2013: The Physical Science Basis. Working Group I contribution to the fifth assessment report of the Intergovernmental Panel on Climate Change
   Baettig MB, 2007, GEOPHYS RES LETT, V34, DOI 10.1029/2006GL028159
   Basagaña X, 2011, EPIDEMIOLOGY, V22, P765, DOI 10.1097/EDE.0b013e31823031c5
   Chen JJ, 2019, ENVIRON INT, V128, P271, DOI 10.1016/j.envint.2019.04.049
   Chen VYJ, 2010, SCI TOTAL ENVIRON, V408, P2042, DOI 10.1016/j.scitotenv.2009.11.044
   Contractor S, 2021, J CLIMATE, V34, P3, DOI 10.1175/JCLI-D-19-0965.1
   Franzke CLE, 2014, NAT CLIM CHANGE, V4, P423, DOI 10.1038/nclimate2245
   Giorgi F, 2006, GEOPHYS RES LETT, V33, DOI 10.1029/2006GL025734
   He J., 2019, China meteorological forcing dataset (1979-2018)
   He J, 2020, SCI DATA, V7, DOI 10.1038/s41597-020-0369-y
   He WY, 2022, INT J CLIMATOL, V42, P8868, DOI 10.1002/joc.7779
   Hu XP, 2019, ECOL INDIC, V104, P626, DOI 10.1016/j.ecolind.2019.05.037
   Jansson P, 2003, J HYDROL, V282, P116, DOI 10.1016/S0022-1694(03)00258-0
   Ji F, 2014, NAT CLIM CHANGE, V4, P462, DOI [10.1038/NCLIMATE2223, 10.1038/nclimate2223]
   Kendall M. G., 1948, Rank correlation methods.
   Koppen W., 1900, Geographische Zeitschrift, V11, P593
   Kysely J, 2009, BMC PUBLIC HEALTH, V9, DOI 10.1186/1471-2458-9-19
   Li L, 2020, ADV METEOROL, V2020, DOI 10.1155/2020/1808404
   Liao XL, 2019, SCI TOTAL ENVIRON, V663, P644, DOI 10.1016/j.scitotenv.2019.01.290
   Liu JM, 2021, ADV CLIM CHANG RES, V12, P611, DOI 10.1016/j.accre.2021.08.002
   Lloyd EA, 2020, ANN NY ACAD SCI, V1469, P105, DOI 10.1111/nyas.14308
   Lu H, 2018, IEEE ACCESS, V6, P53593, DOI 10.1109/ACCESS.2018.2870151
   Lu J, 2023, ATMOSPHERE-BASEL, V14, DOI 10.3390/atmos14010119
   Lu S, 2021, ADV ATMOS SCI, V38, P1665, DOI 10.1007/s00376-021-0409-3
   Mann HB, 1945, ECONOMETRICA, V13, P245, DOI 10.2307/1907187
   Masson-Delmotte V, 2021, CLIMATE CHANGE 2021, DOI DOI 10.1017/9781009157896
   Mikhaylov A, 2020, ENTREP SUSTAIN ISS, V7, P2897, DOI 10.9770/jesi.2020.7.4(21)
   Mondal SK, 2022, ATMOS RES, V266, DOI 10.1016/j.atmosres.2021.105961
   Pan XD, 2020, EARTH SPACE SCI, V7, DOI 10.1029/2019EA000819
   PENMAN H. L., 1956, NETHERLANDS JOUR AGRIC SCI, V4, P9
   PENMAN HL, 1948, PROC R SOC LON SER-A, V193, P120, DOI 10.1098/rspa.1948.0037
   Piao SL, 2019, SCI CHINA EARTH SCI, V62, P1551, DOI 10.1007/s11430-018-9363-5
   Portmann RW, 2009, P NATL ACAD SCI USA, V106, P7324, DOI 10.1073/pnas.0808533106
   Robinson PJ, 2001, J APPL METEOROL, V40, P762, DOI 10.1175/1520-0450(2001)040<0762:OTDOAH>2.0.CO;2
   Rodell M, 2004, B AM METEOROL SOC, V85, P381, DOI 10.1175/BAMS-85-3-381
   Rummukainen M, 2012, WIRES CLIM CHANGE, V3, P115, DOI 10.1002/wcc.160
   Ryti NRI, 2016, ENVIRON HEALTH PERSP, V124, P12, DOI 10.1289/ehp.1408104
   Shi PJ, 2016, INT J DISAST RISK SC, V7, P216, DOI 10.1007/s13753-016-0094-5
   Shi Y., 2003, SCI TECHNOL REV, V2, P54
   Shi YF, 2007, CLIMATIC CHANGE, V80, P379, DOI 10.1007/s10584-006-9121-7
   [施雅风 Shi Yafeng], 2002, [冰川冻土, Journal of Glaciology and Geocryology], V24, P219
   Smith ET, 2018, INT J CLIMATOL, V38, pE807, DOI 10.1002/joc.5408
   [宋连春 Song Lianchun], 2003, [冰川冻土, Journal of Glaciology and Geocryology], V25, P143
   Sun QH, 2021, J CLIMATE, V34, P243, DOI 10.1175/JCLI-D-19-0892.1
   Sun Y, 2018, EARTHS FUTURE, V6, P1528, DOI 10.1029/2018EF000963
   Thornthwaite CW, 1948, GEOGR REV, V38, P55, DOI 10.2307/210739
   Tirkey AS, 2018, EGYPT J REMOTE SENS, V21, P49, DOI 10.1016/j.ejrs.2016.12.007
   Wang SM, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13071230
   Wang Y, 2021, THEOR APPL CLIMATOL, V143, P1017, DOI 10.1007/s00704-020-03457-0
   Wartenburger R., 2017, Geosci. Model Dev. Discuss, V2017, P1
   Wei LX, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph19116398
   [温婷婷 Wen Tingting], 2022, [干旱区研究, Arid Zone Research], V39, P684
   Wu XY, 2021, INT J CLIMATOL, V41, P393, DOI 10.1002/joc.6626
   Wu YH, 2019, SCI TOTAL ENVIRON, V660, P1555, DOI 10.1016/j.scitotenv.2019.01.119
   Xu YH, 2013, J EPIDEMIOL COMMUN H, V67, P519, DOI 10.1136/jech-2012-201899
   Yang J., 2021, Atmosphere, DOI [10.3390/atmos, DOI 10.3390/ATMOS]
   Yang K, 2010, AGR FOREST METEOROL, V150, P38, DOI 10.1016/j.agrformet.2009.08.004
   Yu HY, 2010, P NATL ACAD SCI USA, V107, P22151, DOI 10.1073/pnas.1012490107
   Yu R, 2020, WEATHER CLIM EXTREME, V30, DOI 10.1016/j.wace.2020.100295
   Yue Q., 2015, J ARID METEOROLOGY, V33
   Zhang Q, 2021, CHIN SCI B-CHIN, V66, P3757, DOI 10.1360/TB-2020-1396
   Zheng HX, 2009, J GEOPHYS RES-ATMOS, V114, DOI 10.1029/2009JD012203
   [郑景云 Zheng Jingyun], 2013, [科学通报, Chinese Science Bulletin], V58, P3088
   Zhou P, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14143497
   Zscheischler J, 2020, NAT REV EARTH ENV, V1, P333, DOI 10.1038/s43017-020-0060-z
NR 67
TC 10
Z9 11
U1 10
U2 32
PU NATURE PORTFOLIO
PI BERLIN
PA HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY
SN 2045-2322
J9 SCI REP-UK
JI Sci Rep
PD JUN 27
PY 2023
VL 13
IS 1
AR 10418
DI 10.1038/s41598-023-37349-w
PG 13
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA U9VW0
UT WOS:001088220200039
PM 37369846
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Schlaepfer, MA
   Lawler, JJ
AF Schlaepfer, Martin A.
   Lawler, Joshua J.
TI Conserving biodiversity in the face of rapid climate change requires a
   shift in priorities
SO WILEY INTERDISCIPLINARY REVIEWS-CLIMATE CHANGE
LA English
DT Article
DE biodiversity; conservation; non-native species; protected areas; values
ID NATURES CONTRIBUTIONS; CONSERVATION; CARBON; RESILIENCE; DECLINE
AB The field of conservation aims to protect biodiversity-the diversity of life on earth in all its forms. Traditional conservation objectives and measures have already been expanded and modified in response to shifting social values and climate-related challenges. As climate change progresses, we argue that these changes will need to be accelerated. First, an even greater fraction of conservation objectives will need to prioritize the basic well-being of humans, especially in areas where humans are strongly dependent on their natural surroundings. For example, urban biodiversity and low-impact forms of agriculture and forestry that reconcile biodiversity and contributions to humans should increasingly be viewed as compatible with conservation objectives. Second, more conservation measures will need to allow for, and even foster, changes in biodiversity. Indeed, changing species' characteristics and biotic community composition are not only adaptive responses to inevitable climate change but will, in many instances, also be necessary to maintain functioning ecosystems. Conversely, attempts to maintain biodiversity in a historical state will likely become increasingly difficult, expensive, and possibly counterproductive. Finally, in addition to continuing climate adaptation work, conservation efforts will need to focus more on reducing atmospheric carbon concentrations. We explore how collectively these changes are transforming the field of conservation and how they have the potential to lead to a more just and sustainable world despite impending climate change. This article is categorized under: Climate, Ecology, and Conservation > Conservation Strategies Climate, Nature, and Ethics > Comparative Environmental Values Climate and Development > Sustainability and Human Well-Being
C1 [Schlaepfer, Martin A.] Univ Geneva, Inst Environm Sci, Geneva, Switzerland.
   [Lawler, Joshua J.] Univ Washington, Sch Environm & Forest Sci, Washington, DC USA.
C3 University of Geneva; University of Washington
RP Schlaepfer, MA (corresponding author), Univ Geneva, Inst Environm Sci, Geneva, Switzerland.
EM martin.schlaepfer@unige.ch
OI Lawler, Joshua/0000-0002-8306-3175; Schlaepfer, Martin
   A./0000-0002-8752-6245
FU Universite de Geneve
FX We thank the participants of the Climate-talk series at the Institute
   for Environmental Sciences, University of Geneva, Anne Guerry, and two
   anonymous reviewers for their constructive comments on previous versions
   of this manuscript. Open access funding provided by Universite de
   Geneve.
CR Anderson K, 2012, NATURE, V484, P7, DOI 10.1038/484007a
   Ashley MV, 2003, BIOL CONSERV, V111, P115, DOI 10.1016/S0006-3207(02)00279-3
   Beaudrot L, 2016, ECOL APPL, V26, P1098, DOI 10.1890/15-0935
   Blumstein DT, 2002, ANIM CONSERV, V5, P87, DOI 10.1017/S1367943002002123
   Boulton CA, 2022, NAT CLIM CHANGE, V12, P271, DOI 10.1038/s41558-022-01287-8
   Büscher B, 2019, CONSERV SOC, V17, P283, DOI 10.4103/cs.cs_19_75
   Buscher Bram., 2020, CONSERVATION REVOLUT
   Callicott JB, 2000, US FOR SERV RMRS-P, V1, P24
   Camacho AE, 2010, ISSUES SCI TECHNOL, V26, P21
   Carroll ScottP., 2008, CONSERVATION BIOL EV
   Clark PU, 2016, NAT CLIM CHANGE, V6, P360, DOI 10.1038/NCLIMATE2923
   Clement S., 2021, GOVERNING ANTHROPOCE, P97, DOI [10.1007/978-3-030-60350-2_4, DOI 10.1007/978-3-030-60350-2_4]
   Colloff MJ, 2017, ENVIRON SCI POLICY, V68, P87, DOI 10.1016/j.envsci.2016.11.007
   Convention on Biological Diversity (CBD), 2021, PROP HEADL IND MON F
   Crandall KA, 2000, TRENDS ECOL EVOL, V15, P290, DOI 10.1016/S0169-5347(00)01876-0
   Cronin, 1995, UNCOMMON GROUND REIN
   Cuthbert RN, 2020, CONSERV BIOL, V34, P1579, DOI 10.1111/cobi.13592
   Daily G. C., 1997, Nature's services: societal dependence on natural ecosystems., P113
   Damjanovic K, 2017, MICROB BIOTECHNOL, V10, P1236, DOI 10.1111/1751-7915.12769
   Davis M, 2011, NATURE, V474, P153, DOI 10.1038/474153a
   Di Sacco A, 2021, GLOBAL CHANGE BIOL, V27, P1328, DOI 10.1111/gcb.15498
   Díaz S, 2018, SCIENCE, V359, P270, DOI 10.1126/science.aap8826
   Evans MC, 2021, ENVIRON CONSERV, V48, P151, DOI 10.1017/S0376892921000114
   Fargione JE, 2018, SCI ADV, V4, DOI 10.1126/sciadv.aat1869
   Ferreira J, 2018, NAT CLIM CHANGE, V8, P744, DOI 10.1038/s41558-018-0225-7
   Fitzpatrick BM, 2007, P NATL ACAD SCI USA, V104, P15793, DOI 10.1073/pnas.0704791104
   Fitzpatrick BM, 2010, P NATL ACAD SCI USA, V107, P3606, DOI 10.1073/pnas.0911802107
   Fletcher MS, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2022218118
   Foden WB, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.551
   Fox HE, 2009, FRONT ECOL ENVIRON, V7, P294, DOI 10.1890/09.WB.019
   Gardner CJ, 2021, FRONT CONSERV SCI, V2, DOI 10.3389/fcosc.2021.659912
   Griscom BW, 2017, P NATL ACAD SCI USA, V114, P11645, DOI 10.1073/pnas.1710465114
   Guiasu RC, 2018, BIOL PHILOS, V33, DOI 10.1007/s10539-018-9644-0
   Guo QF, 2021, J BIOGEOGR, V48, P253, DOI 10.1111/jbi.13943
   Heller NE, 2009, BIOL CONSERV, V142, P14, DOI 10.1016/j.biocon.2008.10.006
   Hobbs RJ, 2009, TRENDS ECOL EVOL, V24, P599, DOI 10.1016/j.tree.2009.05.012
   Hoegh-Guldberg O, 2008, SCIENCE, V321, P345, DOI 10.1126/science.1157897
   Johnson WE, 2010, SCIENCE, V329, P1641, DOI 10.1126/science.1192891
   Jones TA, 2009, FRONT ECOL ENVIRON, V7, P541, DOI 10.1890/080028
   Kareiva P., 2011, BREAKTHROUGH J, VFall 2011, P29
   Kareiva P, 2012, BIOSCIENCE, V62, P962, DOI 10.1525/bio.2012.62.11.5
   Kohler F, 2019, CONSERV BIOL, V33, P1014, DOI 10.1111/cobi.13304
   Kremen C, 2018, SCIENCE, V362, DOI 10.1126/science.aau6020
   Kull CA, 2015, GEOFORUM, V61, P122, DOI 10.1016/j.geoforum.2015.03.004
   Lackey RT, 2009, NORTHWEST SCI, V83, P291, DOI 10.3955/046.083.0312
   Lahsen M, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abdcf0
   Leo KL, 2019, OCEAN COAST MANAGE, V175, P180, DOI 10.1016/j.ocecoaman.2019.03.019
   Lynch AJ, 2021, FRONT ECOL ENVIRON, V19, P461, DOI 10.1002/fee.2377
   Mace GM, 2008, MOL ECOL, V17, P9, DOI 10.1111/j.1365-294X.2007.03455.x
   Mace GM, 2014, SCIENCE, V345, P1558, DOI 10.1126/science.1254704
   Maron M, 2016, BIOSCIENCE, V66, P489, DOI 10.1093/biosci/biw038
   Marris Emma., 2011, Rambunctious Garden: Saving Nature in a Post-Wild World, V1st
   Marvier M, 2020, FRONT ECOL ENVIRON, V18, P423, DOI 10.1002/fee.2256
   Marvier M, 2014, CONSERV BIOL, V28, P1, DOI 10.1111/cobi.12206
   Mascaro J, 2012, ECOL MONOGR, V82, P221, DOI 10.1890/11-1014.1
   Matallana-Puerto CA, 2022, ECOLOGY, V103, DOI 10.1002/ecy.3778
   May RF, 2015, BIOL CONSERV, V190, P179, DOI 10.1016/j.biocon.2015.06.004
   McLaughlin BC, 2022, BIOL CONSERV, V268, DOI 10.1016/j.biocon.2022.109497
   Morecroft MD, 2019, SCIENCE, V366, P1329, DOI 10.1126/science.aaw9256
   O'Neill DW, 2018, NAT SUSTAIN, V1, P88, DOI 10.1038/s41893-018-0021-4
   Obura DO, 2021, SCIENCE, V373, P746, DOI 10.1126/science.abh2234
   Otero I, 2020, CONSERV LETT, V13, DOI 10.1111/conl.12713
   Pascual U, 2021, NAT SUSTAIN, V4, P567, DOI 10.1038/s41893-021-00694-7
   Pascual U, 2017, CURR OPIN ENV SUST, V26-27, P7, DOI 10.1016/j.cosust.2016.12.006
   Pauchard A, 2018, PLOS BIOL, V16, DOI 10.1371/journal.pbio.2006686
   Pettorelli N, 2021, J APPL ECOL, V58, P2384, DOI 10.1111/1365-2664.13985
   Portner H.O., 2021, SCI OUTC IPBES IPCC
   Quilodran CS, 2020, COMMUN BIOL, V3, DOI 10.1038/s42003-020-1116-9
   Ramus AP, 2017, P NATL ACAD SCI USA, V114, P8580, DOI 10.1073/pnas.1700353114
   Raworth K., 2017, Doughnut Economics: Seven Ways to Think Like a 21st-Century Economist
   Raworth K, 2017, LANCET PLANET HEALTH, V1, pE48, DOI 10.1016/S2542-5196(17)30028-1
   Ricciardi A, 2009, TRENDS ECOL EVOL, V24, P248, DOI 10.1016/j.tree.2008.12.006
   Robertson JC, 2021, PEERJ, V9, DOI 10.7717/peerj.11802
   Ryan ME, 2009, P NATL ACAD SCI USA, V106, P11166, DOI 10.1073/pnas.0902252106
   Sagoff M, 2020, CONSERV BIOL, V34, P581, DOI 10.1111/cobi.13440
   Salo P, 2007, P ROY SOC B-BIOL SCI, V274, P1237, DOI 10.1098/rspb.2006.0444
   Sax DF, 2001, J BIOGEOGR, V28, P139, DOI 10.1046/j.1365-2699.2001.00536.x
   Schlaepfer MA, 2005, ECOL LETT, V8, P241, DOI 10.1111/j.1461-0248.2005.00730.x
   Schlaepfer MA, 2018, PLOS BIOL, V16, DOI 10.1371/journal.pbio.2005568
   Schlaepfer MA, 2011, CONSERV BIOL, V25, P428, DOI 10.1111/j.1523-1739.2010.01646.x
   Seddon N, 2019, NAT CLIM CHANGE, V9, P84, DOI 10.1038/s41558-019-0405-0
   Segar J, 2022, NAT SUSTAIN, V5, P649, DOI 10.1038/s41893-022-00882-z
   Shin YJ, 2022, GLOBAL CHANGE BIOL, V28, P2846, DOI 10.1111/gcb.16109
   Sjöman H, 2016, URBAN FOR URBAN GREE, V18, P237, DOI 10.1016/j.ufug.2016.06.011
   SOULE ME, 1985, BIOSCIENCE, V35, P727, DOI 10.2307/1310054
   Soulé M, 2013, CONSERV BIOL, V27, P895, DOI 10.1111/cobi.12147
   St-Laurent GP, 2021, COMMUN BIOL, V4, DOI 10.1038/s42003-020-01556-2
   Steffen W, 2015, SCIENCE, V347, DOI 10.1126/science.1259855
   Stein B A., 2014, Climate-Smart Conservation: Putting Adaptation Principles into Practice
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Tablado Z, 2010, CONSERV BIOL, V24, P1230, DOI 10.1111/j.1523-1739.2010.01483.x
   Van Oppen MJH, 2017, GLOBAL CHANGE BIOL, V23, P3437, DOI 10.1111/gcb.13647
   van Oppen MJH, 2015, P NATL ACAD SCI USA, V112, P2307, DOI 10.1073/pnas.1422301112
   Vellend M, 2007, TRENDS ECOL EVOL, V22, P481, DOI 10.1016/j.tree.2007.02.017
   Vizentin-Bugoni J, 2019, SCIENCE, V364, P78, DOI 10.1126/science.aau8751
   Wallach AD, 2020, CONSERV BIOL, V34, P997, DOI 10.1111/cobi.13447
   Warszawski L, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/4/044018
   Westemeier RL, 1998, SCIENCE, V282, P1695, DOI 10.1126/science.282.5394.1695
   Wyborn C., 2020, SEEDS CHANGE PROVOCA, DOI [10.13140/RG.2.2.22170.59848/3, DOI 10.13140/RG.2.2.22170.59848/3]
   Zafra-Calvo N, 2020, GLOBAL ENVIRON CHANG, V63, DOI 10.1016/j.gloenvcha.2020.102115
NR 100
TC 18
Z9 18
U1 8
U2 40
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1757-7780
EI 1757-7799
J9 WIRES CLIM CHANGE
JI Wiley Interdiscip. Rev.-Clim. Chang.
PD JAN
PY 2023
VL 14
IS 1
AR e798
DI 10.1002/wcc.798
EA SEP 2022
PG 14
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 8D0TN
UT WOS:000849660300001
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Kurth, D
AF Kurth, Detlef
TI City Models and Preventive Planning Strategies for Resilient Cities in
   Germany br
SO URBAN PLANNING
LA English
DT Article
DE climate change; pandemic; planning models; urban planning; urban
   resilience
AB In the face of the Covid-19 crisis, the city model of the new Leipzig Charter of the EU was re-evaluated. The existing urban development model of a mixed and compact city is to be mainly maintained because the urban density or building typology does not influence the spread of Covid-19. But the pandemic has made it clear how important green space and recreation areas are for inner city residential areas. This green space also becomes more important regarding climate adaptation measures to provide cooler air and ventilation. In the framework of the Leipzig Charter of the EU, the German ministry for building adopted the memorandum on Urban Resilience in May 2021. Resilience in this context means that we should not only repair the damage of disasters but also adapt to future crises and make our cities more resilient and sustainable. For this, we need to strengthen preventive strategies in urban development planning connected with urban renewal approaches and ask for extended city models. Planning shapes the future, including counteracting undesirable scenarios with preventive planning. In this sense, future planning and disaster control have common objectives-they take an interdisciplinary approach to prepare for future change, they want to anticipate and prevent danger, protect and expand the infrastructure, and serve the common good. In this article, I will point out how integrated urban development concepts should be extended with aspects of urban resilience, and which city models are important for the future.
C1 [Kurth, Detlef] Tech Univ Kaiserslautern, Chair Urban Planning, Kaiserslautern, Germany.
C3 University of Kaiserslautern
RP Kurth, D (corresponding author), Tech Univ Kaiserslautern, Chair Urban Planning, Kaiserslautern, Germany.
EM detlef.kurth@ru.uni-kl.de
CR [Anonymous], 2022, SMART CLIMATE CITY S
   Baugesetzbuch, 2022, BEK 26 04 2022
   Bundesinstitut fuer Bau- Stadtund Raumforschung, 2009, KLIM STADT
   Bundesministerium des Innern fur Bau und Heimat, 2020, NEUE LEIPZ CHART
   Bundesministerium des Innern fur Bau und Heimat, 2021, MEM URB RES
   Fekkak M., 2016, RESILIENTE STADT ZUK
   Knieling J., 2012, 12 HAF CIT U HAMB
   Koeksalan N., 2021, MEMORANDUM URBAN RES, P16
   Kunzmann K., 2021, PLANERIN, V2021, P9
   Kurth D, 2020, DISP, V56, P122, DOI 10.1080/02513625.2020.1906065
   Resilient Cities Network, 2022, HOME
   Resilient Rotterdam, 2022, US
   Rettich S., 2021, MEMORANDUM URBANE RE, P18
   UN Habitat, 2022, RES RISK RED
NR 14
TC 1
Z9 1
U1 2
U2 16
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 4
BP 90
EP 95
DI 10.17645/up.v7i4.5803
PG 6
WC Urban Studies
WE Emerging Sources Citation Index (ESCI)
SC Urban Studies
GA 5X1OC
UT WOS:000878374600007
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Rehman, K
   Khan, H
   Cho, YS
   Hong, SH
AF Rehman, Khawar
   Khan, Hammad
   Cho, Yong-Sik
   Hong, Seung Ho
TI Incident wave run-up prediction using the response surface methodology
   and neural networks
SO STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
LA English
DT Article
DE Solitary waves; Physical modeling; Artificial neural network (ANN);
   Submerged breakwaters; Wave run-up; Response surface methodology (RSM)
ID OPTIMIZATION
AB Submerged breakwaters (SBs) protect coastal areas from intense wave actions, such as inundation and erosion, by controlling the wave run up. The effective regulation of wave run-up heights depends on the accuracy of predictions made by the forecasting model and on understanding the relation between incident wave characteristics, SBs' geometry, and their configuration. This paper proposes models based on the Artificial neural network (ANN) and the Response surface methodology (RSM) to predict the maximum wave run-up heights over a series of rubble mound and caisson-type SBs under varying incident wave conditions. The data for the ANN and RSM models are obtained through physical modeling in the laboratory flume. The objectives of the study are to (1) provide robust tools for the prediction of the maximum wave run up under complex wave-structure interactions; (2) explore the optimum conditions for reducing the maximum run-up height and examine the interdependence of wave-structure characteristics; and (3) investigate the run-up prediction efficacy of the ANN and RSM models. Assessment of the prediction quality of the ANN and RSM models reveals that both techniques establish powerful tools for wave run-up prediction; however, the former offers a slightly better statistical performance. Well-trained ANN model such as Multi-layer perceptron and well-tested statistical methods have considerable potential for application in the development of climate adaptive coastal resilience plans because of their rapid and robust predictive capability.
C1 [Rehman, Khawar] Ghulam Ishaq Khan Inst Engn Sci & Technol, Dept Civil Engn, Topi 23460, Swabi, Pakistan.
   [Khan, Hammad] Ghulam Ishaq Khan Inst Engn Sci & Technol, Fac Mat & Chem Engn, Topi 23460, Swabi, Pakistan.
   [Cho, Yong-Sik] Hanyang Univ, Dept Civil & Environm Engn, Seoul 04763, South Korea.
   [Hong, Seung Ho] Hanyang Univ, Dept Civil & Environm Engn, Ansan 15588, South Korea.
C3 GIK Institute Engineering Science & Technology; GIK Institute
   Engineering Science & Technology; Hanyang University; Hanyang University
RP Hong, SH (corresponding author), Hanyang Univ, Dept Civil & Environm Engn, Ansan 15588, South Korea.
EM khawar.rehman@giki.edu.pk; hammad@giki.edu.pk; ysc59@hanyang.ac.kr;
   sehong@hanyang.ac.kr
RI khan, hammad/HRD-7248-2023; Cho, Yong-Sik/P-2091-2015
OI hong, seung ho/0000-0003-2469-4740; Rehman, Khawar/0000-0002-8468-8986
FU National Research Foundation of Korea (NRF) - Korea Government (MSIP)
   [2015R1A2A1A15054097]
FX This research was supported by the National Research Foundation of Korea
   (NRF) grant funded by the Korea Government (MSIP)
   (No.2015R1A2A1A15054097).
CR Agrawal JD, 2004, MAR STRUCT, V17, P536, DOI 10.1016/j.marstruc.2005.01.001
   Ahmadian AS, 2018, NEURAL COMPUT APPL, V29, P705, DOI 10.1007/s00521-016-2587-y
   BOX GEP, 1951, J R STAT SOC B, V13, P1, DOI 10.1111/j.2517-6161.1951.tb00067.x
   BRIGGS MJ, 1995, PURE APPL GEOPHYS, V144, P569, DOI 10.1007/BF00874384
   Castro A, 2011, J HYDRAUL RES, V49, P465, DOI 10.1080/00221686.2011.568197
   Cho Y-S., 1995, NUMERICAL SIMULATION
   Dehghani MH, 2020, J MOL LIQ, V302, DOI 10.1016/j.molliq.2020.112526
   DERRINGER G, 1980, J QUAL TECHNOL, V12, P214, DOI 10.1080/00224065.1980.11980968
   Dingemans MW., 1997, WATER WAVE PROPAGATI, V16
   Garson D., 1991, AI EXPERT
   Ghaedi M, 2014, SPECTROCHIM ACTA A, V125, P264, DOI 10.1016/j.saa.2013.12.082
   GIOVANNI M, 1983, FOOD TECHNOL-CHICAGO, V37, P41
   Günaydin K, 2011, CIV ENG ENVIRON SYST, V28, P165, DOI 10.1080/10286608.2010.526703
   Ha T, 2014, COAST ENG, V84, P38, DOI 10.1016/j.coastaleng.2013.11.003
   Hwang H-S., 2016, THESIS HANYANG U
   James SC, 2018, COAST ENG, V137, P1, DOI 10.1016/j.coastaleng.2018.03.004
   Khan SU, 2020, CHEMOSPHERE, V253, DOI 10.1016/j.chemosphere.2020.126673
   Kim DH, 2014, OCEAN ENG, V87, P185, DOI 10.1016/j.oceaneng.2014.06.001
   Körbahti BK, 2008, CHEM ENG J, V136, P25, DOI 10.1016/j.cej.2007.03.007
   Lee JW, 2020, NAT HAZARDS, V104, P1157, DOI 10.1007/s11069-020-04209-z
   LIU PLF, 1994, J WATERW PORT C-ASCE, V120, P594, DOI 10.1061/(ASCE)0733-950X(1994)120:6(594)
   Mohammadi F, 2019, CHEMOSPHERE, V237, DOI 10.1016/j.chemosphere.2019.124486
   Moon W-K., 2016, P ANN C KOR SOC COAS, P167
   Mulia IE, 2016, COAST ENG, V109, P1, DOI 10.1016/j.coastaleng.2015.11.010
   Myers RH, 2004, J QUAL TECHNOL, V36, P53, DOI 10.1080/00224065.2004.11980252
   Namekar S, 2009, GEOPHYS RES LETT, V36, DOI 10.1029/2009GL037184
   Panizzo A, 2007, COAST ENG, V54, P643, DOI 10.1016/j.coastaleng.2007.01.001
   Rehman K, 2018, J COASTAL RES, P1111, DOI 10.2112/SI85-223.1
   Romano M, 2009, J ASIAN EARTH SCI, V36, P29, DOI 10.1016/j.jseaes.2008.11.003
   Schio RR, 2021, CHEM ENG COMMUN, V208, P1081, DOI 10.1080/00986445.2020.1746655
   Watts, 1953, 33 US ARM CORPS ENG, P159
   Wei YX, 2010, WATER SCI ENG, V3, P304, DOI 10.3882/j.issn.1674-2370.2010.03.006
   Xie S, 2021, J HYDROL, V592, DOI 10.1016/j.jhydrol.2020.125605
   Yahya HSM, 2021, INT J HYDROGEN ENERG, V46, P24632, DOI 10.1016/j.ijhydene.2020.05.033
   Zhang LL, 2018, J CLEAN PROD, V197, P297, DOI 10.1016/j.jclepro.2018.05.267
   Zhang Y, 2010, BIORESOURCE TECHNOL, V101, P3153, DOI 10.1016/j.biortech.2009.12.080
NR 36
TC 8
Z9 8
U1 0
U2 5
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 1436-3240
EI 1436-3259
J9 STOCH ENV RES RISK A
JI Stoch. Environ. Res. Risk Assess.
PD JAN
PY 2022
VL 36
IS 1
BP 17
EP 32
DI 10.1007/s00477-021-02076-z
EA AUG 2021
PG 16
WC Engineering, Environmental; Engineering, Civil; Environmental Sciences;
   Statistics & Probability; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Environmental Sciences & Ecology; Mathematics; Water
   Resources
GA YD5CZ
UT WOS:000686854500001
DA 2025-01-10
ER

PT J
AU Duvat, VKE
   Volto, N
   Stahl, L
   Moatty, A
   Defossez, S
   Desarthe, J
   Grancher, D
   Pillet, V
AF Duvat, Virginie K. E.
   Volto, Natacha
   Stahl, Lucile
   Moatty, Annabelle
   Defossez, Stephanie
   Desarthe, Jeremy
   Grancher, Delphine
   Pillet, Valentin
TI Understanding interlinkages between long-term trajectory of exposure and
   vulnerability, path dependency and cascading impacts of disasters in
   Saint-Martin (Caribbean)
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article
DE Small islands; Social-ecological systems; Climate disasters; Cascading
   effects; Path dependencies; Adaptation
AB This empirical and interdisciplinary study investigates the contribution of deeply enrooted social-political factors to the accumulation of exposure and vulnerability and amplification of cascading impacts of disasters, with implications on the creation and reinforcement of path dependency maintaining social-ecological systems on a maladaptive trajectory. Applying the Trajectory of Exposure and Vulnerability approach to Saint-Martin (Caribbean), we more specifically highlight how the causal chain linking historical geopolitical and politicalinstitutional drivers to legal, economic, demographic, sociocultural, planning-related and environmental drivers, created the accumulation of exposure and vulnerability over time and contributed to the propagation and amplification of the impacts of tropical cyclones Irma and Jose? in 2017. We find that historical socialpolitical dynamics involving unsustainable development and settlement patterns, the weakness of local institutions, population mistrust in public authorities, high social inequalities and environmental degradation maintained Saint-Martin on a maladaptive trajectory through powerful reinforcing mechanisms operating both between and during cyclonic events. This study demonstrates that long-term interdisciplinary approaches are required for a better understanding of path dependency and the identification of levers to break it in risk-prone contexts. In Saint-Martin, breaking path dependency requires the alignment of local institutional capacities with national risk reduction policies, the promotion of social justice and involvement of local communities in decision making. This study therefore confirms the relevance of backward-looking approaches to support forward-looking climate adaptation.
C1 [Duvat, Virginie K. E.; Volto, Natacha; Stahl, Lucile; Moatty, Annabelle; Pillet, Valentin] La Rochelle Univ, CNRS, UMR LIENSs 7266, Batiment ILE,2 Rue Olympe Gouges, F-17000 La Rochelle, France.
   [Stahl, Lucile] Law Firm, 3 Rue Bouvier, F-26150 Die, France.
   [Defossez, Stephanie] Univ Paul Valery Montpellier 3, UMR GRED, Route Mende,Site St Charles, F-34199 Montpellier 5, France.
   [Desarthe, Jeremy] Caisse Cent Reassurance, 157 Blvd Haussmann, F-75008 Paris, France.
   [Grancher, Delphine] Univ Paris I Pantheon Sorbonne UPEC, CNRS, UMR 8591, 1 Pl Aristide Briand, F-92195 Meudon, France.
C3 Centre National de la Recherche Scientifique (CNRS); Institut de
   Recherche pour le Developpement (IRD); Universite de Montpellier;
   Universite Paris-Est-Creteil-Val-de-Marne (UPEC); Centre National de la
   Recherche Scientifique (CNRS); CNRS - Institute of Ecology & Environment
   (INEE)
RP Duvat, VKE (corresponding author), La Rochelle Univ, CNRS, UMR LIENSs 7266, Batiment ILE,2 Rue Olympe Gouges, F-17000 La Rochelle, France.
EM virginie.duvat@univ-lr.fr
RI Duvat, Virginie/GLN-3102-2022; Moatty, Annabelle/AFM-5586-2022
OI VOLTO, Natacha/0000-0002-7674-8926; Moatty,
   Annabelle/0000-0003-0175-646X
FU French Research Agency [ANR-18-OURA-0002-03]; CNES; Agence Nationale de
   la Recherche (ANR) [ANR-18-OURA-0002] Funding Source: Agence Nationale
   de la Recherche (ANR)
FX This work was supported by the French Research Agency
   [NoANR-18-OURA-0002-03]. The authors acknowledge support from the IGN
   for providing historical aerial photographs and from the CNES for the
   Airbus and Defence and Space 2017 satellite archive. They warmly thank
   local and national stakeholders from diverse institutions who helped
   understanding risk management in Saint-Martin as well as residents who
   participated in interviews in the post-cyclone context. The authors are
   grateful to Alexandre Magnan for useful comments on the first draft of
   this article.
CR Adamson GCD, 2018, GLOBAL ENVIRON CHANG, V48, P195, DOI 10.1016/j.gloenvcha.2017.12.003
   Alexander David, 2019, UCL Open Environ, V1, pe003, DOI 10.14324/111.444/ucloe.000003
   Alexander D, 2018, INT J DISAST RISK RE, V30, P180, DOI 10.1016/j.ijdrr.2018.03.006
   Barclay J, 2019, INT J DISAST RISK SC, V10, P149, DOI 10.1007/s13753-019-0215-z
   Barnett J., 2016, The Palgrave handbook of international development, P731, DOI DOI 10.1057/978-1-137-42724-3-40
   Barraqué B, 2020, ENVIRON HAZARDS-UK, V19, P285, DOI 10.1080/17477891.2019.1696738
   Bordner AS, 2020, GLOBAL ENVIRON CHANG, V61, DOI 10.1016/j.gloenvcha.2020.102054
   Borges-Mendez R., 2019, J EXTREME EVENTS, V6, P1940001, DOI [DOI 10.1142/S2345737619400013, https://doi.org/10.1142/S2345737619400013]
   Collodi J, 2021, DISASTERS, V45, P202, DOI 10.1111/disa.12423
   DDE Guadeloupe Service Amenagement et Urbanisme, 2008, GTRDDEG0508484AV2
   de Scally FA, 2014, INT J DISAST RISK RE, V7, P9, DOI 10.1016/j.ijdrr.2013.12.002
   Desarthe J., 2020, ANN MINES, V98
   Dilling L, 2015, WIRES CLIM CHANGE, V6, P413, DOI 10.1002/wcc.341
   Douglass K, 2020, P NATL ACAD SCI USA, V117, P8254, DOI 10.1073/pnas.1914211117
   Duvat VKE, 2020, SUSTAIN SCI, V15, P569, DOI 10.1007/s11625-019-00722-8
   Duvat V, 2019, GEOMORPHOLOGY, V325, P70, DOI 10.1016/j.geomorph.2018.09.029
   Duvat VKE, 2017, GLOBAL PLANET CHANGE, V158, P134, DOI 10.1016/j.gloplacha.2017.09.016
   Duvat VKE, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.478
   Fawcett D, 2017, GLOBAL ENVIRON CHANG, V45, P79, DOI 10.1016/j.gloenvcha.2017.05.002
   Felsenstein D, 2020, INT J DISAST RISK RE, V51, DOI 10.1016/j.ijdrr.2020.101842
   Fraser A., 2016, J EXTREME EVENTS, DOI [10.1142/S2345737616500081, DOI 10.1142/S2345737616500081]
   Fraser A, 2020, GLOBAL ENVIRON CHANG, V63, DOI 10.1016/j.gloenvcha.2020.102102
   Grislain-Letremy C., 2011, EC STAT, V447, P57
   Gustin P., 2017, REPENSER ILES NORD R
   Hilhorst D., 2004, MAPPING VULNERABILIT
   Holdschlag A, 2016, ANTHROPOCENE, V13, P80, DOI 10.1016/j.ancene.2016.03.002
   Holdschlag A, 2013, SUSTAIN SCI, V8, P407, DOI 10.1007/s11625-013-0216-6
   IEDOM, 2019, PAN SAINT MART NOT E
   IEDOM,, 2007, HOUS SAINT MART
   Intergov Panel Clim Chg, 2012, MANAGING THE RISKS OF EXTREME EVENTS AND DISASTERS TO ADVANCE CLIMATE CHANGE ADAPTATION, P1, DOI 10.1017/CBO9781139177245
   IPCC, 2019, IPCC SPECIAL REPORT, P249
   Jeffers JM, 2014, ENVIRON HAZARDS-UK, V13, P229, DOI 10.1080/17477891.2014.902800
   Jeffers JM, 2013, APPL GEOGR, V37, P44, DOI 10.1016/j.apgeog.2012.10.011
   Jeffry D., 2010, SAINT MARTIN DESTABI, P249
   Jurgilevich A, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa5508
   Lambert M., 2019, REV JURIDIQUE ENV, V44, P89
   Lauer M, 2013, GLOBAL ENVIRON CHANG, V23, P40, DOI 10.1016/j.gloenvcha.2012.10.011
   Lebel L, 2006, ECOL SOC, V11
   Lichtveld M, 2018, AM J PUBLIC HEALTH, V108, P28, DOI 10.2105/AJPH.2017.304193
   Look C., 2019, J EXTREME EVENTS, V06, P1940004, DOI DOI 10.1142/S2345737619400049
   Magnan A., 2008, NOROIS, V206, P37, DOI [10.4000/norois.242, DOI 10.4000/NOROIS.242]
   Magnan AK, 2018, ENVIRON SCI POLICY, V89, P393, DOI 10.1016/j.envsci.2018.09.002
   Marie Cl.-V., 1991, TRAVAIL ILLEGAL IMMI
   McLeman R, 2010, POPUL ENVIRON, V31, P286, DOI 10.1007/s11111-009-0087-z
   Medina N., 2019, J EXTREME EVENTS, P1950001, DOI [10.1142/S2345737619500015, DOI 10.1142/S2345737619500015]
   Medina N, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12041452
   Menoni S, 2020, INT J DISAST RISK RE, V51, DOI 10.1016/j.ijdrr.2020.101751
   Meteo-France, 2005, ATLAS CLIMATIQUE ENV
   Minist`ere des Outre-Mer, 2018, DOSSIER DE PRESSE, V22
   Moatty A., 2019, GEOCARREFOUR, V93 2
   Moatty A., 2020, ECHOGEO, P51, DOI [10.4000/echogeo.19017, DOI 10.4000/ECHOGEO.19017]
   Moulton AA., 2019, J EXTREME EVENTS, V6, P1940003, DOI [10.1142/S2345737619400037, DOI 10.1142/S2345737619400037]
   Nunn PD, 2009, CLIM RES, V40, P211, DOI 10.3354/cr00806
   Parsons M, 2019, GLOBAL ENVIRON CHANG, V56, P95, DOI 10.1016/j.gloenvcha.2019.03.008
   PEARL,, 2018, RISK RES FACT FIND N, P195
   Pelling M., 2001, Environmental Hazards, V3, P49
   Pescaroli G, 2018, SAFETY SCI, V110, P131, DOI 10.1016/j.ssci.2017.12.012
   Pescaroli G., 2015, Planet@Risk, V3, P58
   Pierson P, 2000, AM POLIT SCI REV, V94, P251, DOI 10.2307/2586011
   Rasmussen K, 2009, GEOGR TIDSSKR-DEN, V109, P1
   Redon M., 2007, ETUDES CARIBEENNES, DOI DOI 10.4000/ETUDESCARIBEENNES.962
   Redon M., 2014, ECHOGEO, P28, DOI 10.400/echogeo.13834
   Rey T, 2019, J MAR SCI ENG, V7, DOI 10.3390/jmse7070215
   Schultz J.M., 2018, DISASTER MED PUBLIC, DOI [10.1017/ dmp.2018.28, DOI 10.1017/DMP.2018.28]
   Schwarz AM, 2011, GLOBAL ENVIRON CHANG, V21, P1128, DOI 10.1016/j.gloenvcha.2011.04.011
   Servans G., 2017, ANAL SAINT MARTIN TE
   Spennemann DHR, 1996, ENVIRON MANAGE, V20, P337, DOI 10.1007/BF01203842
   Thomas K, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.565
   Walters BB, 2012, GEOGR TIDSSKR-DEN, V112, P135, DOI 10.1080/00167223.2012.741890
   Wise RM, 2014, GLOBAL ENVIRON CHANG, V28, P325, DOI 10.1016/j.gloenvcha.2013.12.002
NR 70
TC 16
Z9 17
U1 1
U2 23
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 2021
VL 67
AR 102236
DI 10.1016/j.gloenvcha.2021.102236
EA FEB 2021
PG 15
WC Environmental Sciences; Environmental Studies; Geography
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geography
GA RF5GB
UT WOS:000634865600009
OA Green Published
DA 2025-01-10
ER

PT J
AU Richards, TJ
   Karacic, A
   Apuli, RP
   Weih, M
   Ingvarsson, PK
   Rönnberg-Wästljung, AC
AF Richards, Thomas J.
   Karacic, Almir
   Apuli, Rami-Petteri
   Weih, Martin
   Ingvarsson, Par K.
   Ronnberg-Wastljung, Ann Christin
TI Quantitative genetic architecture of adaptive phenology traits in the
   deciduous tree,<i>Populus trichocarpa</i>(Torr. and Gray)
SO HEREDITY
LA English
DT Article
ID ASPEN POPULUS-TREMULA; BUD SET; POPLAR; GROWTH; TEMPERATURE;
   POPULATIONS; PHOTOPERIOD; MODEL; TREES; SENSITIVITY
AB In a warming climate, the ability to accurately predict and track shifting environmental conditions will be fundamental for plant survival. Environmental cues define the transitions between growth and dormancy as plants synchronise development with favourable environmental conditions, however these cues are predicted to change under future climate projections which may have profound impacts on tree survival and growth. Here, we use a quantitative genetic approach to estimate the genetic basis of spring and autumn phenology inPopulus trichocarpato determine this species capacity for climate adaptation. We measured bud burst, leaf coloration, and leaf senescence traits across two years (2017-2018) and combine these observations with measures of lifetime growth to determine how genetic correlations between phenology and growth may facilitate or constrain adaptation. Timing of transitions differed between years, although we found strong cross year genetic correlations in all traits, suggesting that genotypes respond in consistent ways to seasonal cues. Spring and autumn phenology were correlated with lifetime growth, where genotypes that burst leaves early and shed them late had the highest lifetime growth. We also identified substantial heritable variation in the timing of all phenological transitions (h(2) = 0.5-0.8) and in lifetime growth (h(2) = 0.8). The combination of additive variation and favourable genetic correlations in phenology traits suggests that populations of cultivated varieties of P. Trichocarpa may have the capability to adapt their phenology to climatic changes without negative impacts on growth.
C1 [Richards, Thomas J.; Apuli, Rami-Petteri; Ingvarsson, Par K.; Ronnberg-Wastljung, Ann Christin] Swedish Univ Agr Sci, Dept Plant Biol, Uppsala Bioctr, Linnean Ctr Plant Biol, POB 7080, SE-75007 Uppsala, Sweden.
   [Karacic, Almir; Weih, Martin] Swedish Univ Agr Sci, Linnean Ctr Plant Biol, Dept Crop Prod Ecol, POB 7043, SE-75007 Uppsala, Sweden.
   [Richards, Thomas J.] Uppsala Univ, EBC, Dept Ecol & Genet, Plant Ecol & Evolut, SE-75236 Uppsala, Sweden.
C3 Swedish University of Agricultural Sciences; Swedish University of
   Agricultural Sciences; Uppsala University
RP Richards, TJ (corresponding author), Swedish Univ Agr Sci, Dept Plant Biol, Uppsala Bioctr, Linnean Ctr Plant Biol, POB 7080, SE-75007 Uppsala, Sweden.; Richards, TJ (corresponding author), Uppsala Univ, EBC, Dept Ecol & Genet, Plant Ecol & Evolut, SE-75236 Uppsala, Sweden.
EM Thomas.richards@ebc.uu.se
RI richards, tom/L-2186-2019; Weih, Martin/H-5093-2011; Ingvarsson,
   Pär/G-2748-2010; Karacic, Almir/IWU-8380-2023
OI Weih, Martin/0000-0003-3823-9183; Ronnberg-Wastljung, Ann
   Christin/0000-0002-5241-7161; Ingvarsson, Par/0000-0001-9225-7521;
   Richards, Thomas/0000-0001-5945-6545
FU Swedish Research Council FORMAS [942-2016-1]
FX We are grateful to two anonymous reviewers, and the editors of this
   issue, who provided very constructive and insightful suggestions which
   improved the previous versions of the manuscript, and to Tegan Streeter
   for assistance collecting data in the field. This project was funded by
   the Swedish Research Council FORMAS, as part of the Climate-Adapted
   Poplar (CLAP) project (942-2016-1.).
CR Adams HD, 2015, GLOBAL CHANGE BIOL, V21, P4210, DOI 10.1111/gcb.13030
   [Anonymous], 2018, EVOLUTION SELECTION
   Basler D, 2012, AGR FOREST METEOROL, V165, P73, DOI 10.1016/j.agrformet.2012.06.001
   Bhalerao R, 2003, PLANT PHYSIOL, V131, P430, DOI 10.1104/pp.012732
   BRADSHAW HD, 1995, GENETICS, V139, P963
   Brelsford CC, 2019, TREE PHYSIOL, V39, P925, DOI 10.1093/treephys/tpz026
   Christensen K, 2003, BEHAV GENET, V33, P125, DOI 10.1023/A:1022501817781
   Chuine I, 2010, PHILOS T R SOC B, V365, P3149, DOI 10.1098/rstb.2010.0142
   Class B, 2020, EVOLUTION, V74, P1540, DOI 10.1111/evo.14034
   Cong N, 2017, J PLANT ECOL, V10, P744, DOI 10.1093/jpe/rtw084
   Cronk QCB, 2005, NEW PHYTOL, V166, P39, DOI 10.1111/j.1469-8137.2005.01369.x
   Evans LM, 2014, NAT GENET, V46, P1089, DOI 10.1038/ng.3075
   Fabbrini F, 2012, BMC PLANT BIOL, V12, DOI 10.1186/1471-2229-12-47
   Falconer D. S., 1996, Introduction to quantitative genetics.
   Fracheboud Y, 2009, PLANT PHYSIOL, V149, P1982, DOI 10.1104/pp.108.133249
   Hadfield JD, 2010, J STAT SOFTW, V33, P1, DOI 10.18637/jss.v033.i02
   Horvath DP, 2003, TRENDS PLANT SCI, V8, P534, DOI 10.1016/j.tplants.2003.09.013
   Howe GT, 2000, THEOR APPL GENET, V101, P632, DOI 10.1007/s001220051525
   Howe GT, 2003, CAN J BOT, V81, P1247, DOI [10.1139/b03-141, 10.1139/B03-141]
   Ingvarsson PK, 2008, GENETICS, V178, P2217, DOI 10.1534/genetics.107.082354
   Jansson S, 2007, ANNU REV PLANT BIOL, V58, P435, DOI 10.1146/annurev.arplant.58.032806.103956
   Karacic A, 2003, SCAND J FOREST RES, V18, P427, DOI 10.1080/02827580310009113
   KENNEDY BW, 1989, J ANIM SCI, V67, P1946
   Keskitalo J, 2005, PLANT PHYSIOL, V139, P1635, DOI 10.1104/pp.105.066845
   Lagercrantz U, 2009, J EXP BOT, V60, P2501, DOI 10.1093/jxb/erp139
   Leuchner M, 2007, AGR FOREST METEOROL, V142, P35, DOI 10.1016/j.agrformet.2006.10.014
   Luquez V, 2008, TREE GENET GENOMES, V4, P279, DOI 10.1007/s11295-007-0108-y
   Lynch Michael, 1998
   MacKenzie CM, 2018, AM J BOT, V105, P986, DOI 10.1002/ajb2.1108
   Marron N, 2010, TREE GENET GENOMES, V6, P533, DOI 10.1007/s11295-010-0270-5
   McKown AD, 2018, NEW PHYTOL, V220, P300, DOI 10.1111/nph.15273
   McKown AD, 2014, NEW PHYTOL, V203, P535, DOI 10.1111/nph.12815
   McKown AD, 2014, NEW PHYTOL, V201, P1263, DOI 10.1111/nph.12601
   Michelson IH, 2018, PHYSIOL PLANTARUM, V162, P123, DOI 10.1111/ppl.12593
   Olson MS, 2013, MOL ECOL, V22, P1214, DOI 10.1111/mec.12067
   Pliura A, 2014, BIOMASS BIOENERG, V70, P513, DOI 10.1016/j.biombioe.2014.09.011
   Polgar CA, 2011, NEW PHYTOL, V191, P926, DOI 10.1111/j.1469-8137.2011.03803.x
   Porth I, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0142864
   Porth I, 2015, BIOTECHNOL J, V10, P510, DOI 10.1002/biot.201400194
   Porth I, 2014, PLANT PHYSIOL, V164, P548, DOI 10.1104/pp.113.228783
   Rohde A, 2011, TREE PHYSIOL, V31, P472, DOI 10.1093/treephys/tpr038
   Rohde A, 2011, NEW PHYTOL, V189, P106, DOI 10.1111/j.1469-8137.2010.03469.x
   Sannigrahi P, 2010, BIOFUEL BIOPROD BIOR, V4, P209, DOI 10.1002/bbb.206
   Silva JCE, 2004, THEOR APPL GENET, V108, P1113, DOI 10.1007/s00122-003-1524-5
   Singh RK, 2017, NEW PHYTOL, V213, P511, DOI 10.1111/nph.14346
   Slavov GT, 2009, MOL ECOL, V18, P357, DOI 10.1111/j.1365-294X.2008.04016.x
   Triozzi PM, 2018, FRONT PLANT SCI, V9, DOI 10.3389/fpls.2018.01030
   Vitasse Y, 2009, AGR FOREST METEOROL, V149, P735, DOI 10.1016/j.agrformet.2008.10.019
   Weih M, 2004, CAN J FOREST RES, V34, P1369, DOI 10.1139/X04-090
   Wilson AJ, 2005, AM NAT, V166, pE177, DOI 10.1086/497441
   Yu Q, 2001, GROWTH PHENOLOGY HYB
   Zanewich KP, 2018, TREE PHYSIOL, V38, P789, DOI 10.1093/treephys/tpy019
   Zhou L, 2014, MOL ECOL, V23, P2486, DOI 10.1111/mec.12752
NR 53
TC 11
Z9 13
U1 0
U2 18
PU SPRINGERNATURE
PI LONDON
PA CAMPUS, 4 CRINAN ST, LONDON, N1 9XW, ENGLAND
SN 0018-067X
EI 1365-2540
J9 HEREDITY
JI Heredity
PD DEC
PY 2020
VL 125
IS 6
BP 449
EP 458
DI 10.1038/s41437-020-00363-z
EA SEP 2020
PG 10
WC Ecology; Evolutionary Biology; Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Evolutionary Biology; Genetics &
   Heredity
GA OP5AN
UT WOS:000567366300001
PM 32901141
OA hybrid, Green Submitted, Green Published
DA 2025-01-10
ER

PT J
AU Rasmussen, LV
   Kirchhoff, CJ
   Lemos, MC
AF Rasmussen, Laura Vang
   Kirchhoff, Christine J.
   Lemos, Maria Carmen
TI Adaptation by stealth: climate information use in the Great Lakes region
   across scales
SO CLIMATIC CHANGE
LA English
DT Article
ID BOUNDARY ORGANIZATIONS; WATER MANAGEMENT; KNOWLEDGE; SCIENCE;
   COPRODUCTION; GOVERNANCE; FORECASTS; PERCEPTIONS; USABILITY; POLICY
AB While there has been considerable focus on understanding barriers to climate information use associated with the character of climate knowledge, individuals' negative perception of its usability and constraints of decision-contexts, less attention has been paid to understanding how different scales of decision-making influence information use. In this study, we explore how water and resource managers' scales of decision-making and scope of decision responsibilities influence climate information use in two Great Lakes watersheds. We find that despite availability of tailored climate information, actual use of information remains low. Reasons include (a) lack of willingness to place climate on agendas because local managers perceive climate change as politically risky, (b) lack of formal mandate or authority at the city and county scale to translate climate information into on-the-ground action, (c) problems with the information itself, and (d) perceived lack of demand for climate information by those managers who have the mandate and authority to use (or help others use) climate information. Our findings suggest that (1) scientists and information brokers should produce information that meets a range of decision needs and reserve intensive tailoring efforts for decision makers who have willingness and authority to use climate information; (2) without support from higher levels of decision-making (e.g., state), it is unlikely that climate information use will accelerate significantly; and (3) the trend towards characterizing climate specific actions within a broader concept of sustainability practices, or "adaptation by stealth," should be supported as a component of the climate adaptation repertoire.
C1 [Rasmussen, Laura Vang; Lemos, Maria Carmen] Univ Michigan, Sch Nat Resources & Environm, Ann Arbor, MI 48109 USA.
   [Kirchhoff, Christine J.] Univ Connecticut, Storrs, CT USA.
C3 University of Michigan System; University of Michigan; University of
   Connecticut
RP Rasmussen, LV (corresponding author), Univ Michigan, Sch Nat Resources & Environm, Ann Arbor, MI 48109 USA.
EM laura_vang@yahoo.dk
RI rasmussen, laura/KWT-6198-2024
OI Rasmussen, Laura Vang/0000-0001-7786-6783; Kirchhoff,
   Christine/0000-0002-2686-6764; Lemos, Maria Carmen/0000-0001-6686-730X
CR Archie KM, 2014, J ENVIRON MANAGE, V133, P397, DOI 10.1016/j.jenvman.2013.12.015
   Briley L, 2015, CLIM RISK MANAG, V9, P41, DOI 10.1016/j.crm.2015.04.004
   Brown C, 2012, WATER RESOUR RES, V48, DOI 10.1029/2011WR011212
   Cash DW, 2006, ECOL SOC, V11
   Cash DW, 2000, GLOBAL ENVIRON CHANG, V10, P109, DOI 10.1016/S0959-3780(00)00017-0
   Cash DW, 2003, P NATL ACAD SCI USA, V100, P8086, DOI 10.1073/pnas.1231332100
   Darela JP, 2016, CLIMATIC CHANGE, V136, P413, DOI 10.1007/s10584-016-1635-z
   Dessai S, 2009, ADAPTING TO CLIMATE CHANGE: THRESHOLDS, VALUES, GOVERNANCE, P64
   Dilling L, 2015, REG ENVIRON CHANGE, V15, P657, DOI 10.1007/s10113-014-0668-y
   Dilling L, 2015, WEATHER CLIM SOC, V7, P5, DOI 10.1175/WCAS-D-14-00001.1
   Dow K, 2009, J AM WATER RESOUR AS, V45, P187, DOI 10.1111/j.1752-1688.2008.00270.x
   Eakin HC, 2014, GLOBAL ENVIRON CHANG, V27, P1, DOI 10.1016/j.gloenvcha.2014.04.013
   Eriksen S, 2011, CLIM DEV, V3, P7, DOI 10.3763/cdev.2010.0060
   Feldman DL, 2009, WEATHER CLIM SOC, V1, P9, DOI 10.1175/2009WCAS1007.1
   Gordon E.S., 2016, Climate in Context: Science and Society Partnering for Adaptation, P235, DOI 10
   Hulme M, 2008, T I BRIT GEOGR, V33, P5, DOI 10.1111/j.1475-5661.2007.00289.x
   IPCC, 2018, GLOB WARM 1 5C SUMM
   Cisneros BEJ, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P229
   Jones L, 2015, NAT CLIM CHANGE, V5, P812, DOI 10.1038/nclimate2701
   Kalafatis SE, 2015, GLOBAL ENVIRON CHANG, V32, P30, DOI 10.1016/j.gloenvcha.2015.02.007
   Kirchhoff CJ, 2016, WATER RESOUR RES, V52, P2951, DOI 10.1002/2015WR018431
   Kirchhoff CJ, 2015, CLIM RISK MANAG, V9, P20, DOI 10.1016/j.crm.2015.04.001
   Kirchhoff CJ, 2013, CLIMATIC CHANGE, V119, P495, DOI 10.1007/s10584-013-0703-x
   Kirchhoff CJ, 2013, ENVIRON SCI POLICY, V26, P6, DOI 10.1016/j.envsci.2012.07.001
   Lach D, 2003, CLIMATE WATER TRANSB
   Lemos MC, 2015, CURR OPIN ENV SUST, V12, P48, DOI 10.1016/j.cosust.2014.09.005
   Lemos MC, 2014, WEATHER CLIM SOC, V6, P273, DOI 10.1175/WCAS-D-13-00044.1
   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
   Marx SM, 2007, GLOBAL ENVIRON CHANG, V17, P47, DOI 10.1016/j.gloenvcha.2006.10.004
   Meadow AM, 2015, WEATHER CLIM SOC, V7, P179, DOI 10.1175/WCAS-D-14-00050.1
   Mearns LO, 2010, CLIMATIC CHANGE, V100, P77, DOI 10.1007/s10584-010-9841-6
   Moss RH, 2013, SCIENCE, V342, P696, DOI 10.1126/science.1239569
   National Climate Assessment (NCA), 2014, 2014 NAT CLIM ASS
   O'Brien K, 2004, CLIMATIC CHANGE, V64, P193, DOI 10.1023/B:CLIM.0000024668.70143.80
   Ostrom E., 2001, Update Newsletter of the International Human Dimensions Program on Global Environmental Change, P3
   Phadke R, 2015, CLIM RISK MANAG, V9, P62, DOI 10.1016/j.crm.2015.06.005
   Poff NL, 2016, NAT CLIM CHANGE, V6, P25, DOI [10.1038/nclimate2765, 10.1038/NCLIMATE2765]
   Rabe BG, 2007, GOVERNANCE, V20, P423, DOI 10.1111/j.1468-0491.2007.00365.x
   Rayner S, 2005, CLIMATIC CHANGE, V69, P197, DOI 10.1007/s10584-005-3148-z
   Reid H, 2014, CLIM DEV, V6, P291, DOI 10.1080/17565529.2014.973720
   Roncoli C, 2009, CLIMATIC CHANGE, V92, P433, DOI 10.1007/s10584-008-9445-6
   Soares MB, 2015, CLIM RISK MANAG, V10, P8, DOI 10.1016/j.crm.2015.07.001
   Weaver CP, 2013, WIRES CLIM CHANGE, V4, P39, DOI 10.1002/wcc.202
   Weber EU, 2006, CLIMATIC CHANGE, V77, P103, DOI 10.1007/s10584-006-9060-3
   Wolf J, 2011, WIRES CLIM CHANGE, V2, P547, DOI 10.1002/wcc.120
   Woodru SC, 2016, NAT CLIM CHANGE, V6, P796, DOI 10.1038/NCLIMATE3012
NR 47
TC 22
Z9 25
U1 0
U2 3
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 FEB
PY 2017
VL 140
IS 3-4
BP 451
EP 465
DI 10.1007/s10584-016-1857-0
PG 15
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 EK2GC
UT WOS:000393744800010
DA 2025-01-10
ER

PT J
AU Potter, S
   Rosauer, D
   Doody, JS
   Webb, MJ
   Eldridge, MDB
AF Potter, Sally
   Rosauer, Dan
   Doody, J. Sean
   Webb, Myfanwy J.
   Eldridge, Mark D. B.
TI Persistence of a potentially rare mammalian genus (<i>Wyulda</i>)
   provides evidence for areas of evolutionary refugia within the
   Kimberley, Australia
SO CONSERVATION GENETICS
LA English
DT Article
DE Wyulda squamicaudata; mtDNA; Northern Australia; Conservation; Genetics;
   Refugia
ID NORTHERN AUSTRALIA; WESTERN-AUSTRALIA; DNA POLYMORPHISM; PULMONATA
   CAMAENIDAE; AMPLIRHAGADA IREDALE; MITOCHONDRIAL-DNA; POPULATION-GROWTH;
   MONSOON TROPICS; CLIMATE-CHANGE; MIXED MODELS
AB Understanding the evolutionary and ecological processes that have shaped current patterns of biodiversity is crucial in the planning and implementation of broad scale conservation management. The temporal and spatial pattern of diversity across a landscape can help identify areas that have acted as climatically stable refugia historically, or do so currently. This has important implications for conservation efforts that try to maximise the evolutionary potential of species, as well as maintaining existing biodiversity. Northern Australia has recently reported catastrophic species decline, particularly in mammals, due to a series of threats. Here we apply an integrative approach utilising molecular analyses and spatial modelling to determine whether disjunct populations of a potentially rare, endemic mammal, the scaly-tailed possum (Wyulda squamicaudata) exhibit differentiation associated with biogeographic barriers or a recent decline. Significant but low genetic differentiation between the east and west Kimberley populations was detected. Principal component analyses indicate potential climatic niche differences that could support recent localised adaptations. Climatic reconstructions back to the last glacial maximum (LGM) indicate areas of suitable habitat have substantially shifted through time for W. squamicaudata and suggest multiple areas of refugia across the Kimberley since the LGM. Further comparative research is required to establish a biogeographical framework that will assist in our understanding of processes that have shaped biodiversity in northern Australia and assist in conservation planning.
C1 [Potter, Sally; Rosauer, Dan] Australian Natl Univ, Res Sch Biol, Canberra, ACT 0200, Australia.
   [Potter, Sally; Eldridge, Mark D. B.] Australian Museum, Australian Museum Res Inst, Sydney, NSW 2010, Australia.
   [Doody, J. Sean] Univ Newcastle, Sch Environm & Life Sci, Callaghan, NSW 2308, Australia.
C3 Australian National University; Australian Museum; University of
   Newcastle
RP Potter, S (corresponding author), Australian Natl Univ, Res Sch Biol, Canberra, ACT 0200, Australia.
EM sally.potter@anu.edu.au; dan.rosauer@anu.edu.au; jseandoody@gmail.com;
   rockpossum@yahoo.com.au; mark.eldridge@austmus.gov.au
RI Potter, Sally/AAZ-3392-2020; Webb, Myfanwy/AAQ-8608-2020; Rosauer,
   Dan/C-3735-2008
OI Potter, Sally/0000-0002-5150-7501; Rosauer, Dan/0000-0002-2371-1767;
   Eldridge, Mark/0000-0002-7109-0600
FU Chadwick Fellowship (Australian Museum); Australian Geographic Society;
   Monash University
FX We would like to thank the following people and institutions for
   providing samples or assisting with sample collection: Christina
   Castellano, Simon Clulow, Rosie Honin, Colin McHenry, David Pearson, Ian
   Radford, Western Australia Department of Environment and Conservation,
   Australian Wildlife Conservancy, Western Australian Museum, South
   Australian Museum and Australian Museum. Paleo-climate data were
   generously provided by Jeremy VanDerWal. We are also grateful to Craig
   Moritz for helpful comments on the manuscript. This research was
   supported by funding from the Chadwick Fellowship (Australian Museum),
   Australian Geographic Society and Monash University.
CR Alexander WB, 1919, J ROYAL SOC W AUSTR, V4, P31
   Amante C., 2009, NOAA TECHNICAL MEMOR, P19, DOI 10.7289/V5C8276M
   [Anonymous], 2001, Possums: The Brushtails, Ringtails and Greater Glider
   [Anonymous], 2009, TRACER V1 5
   Blacket Mark J., 2001, Journal of Mammalian Evolution, V8, P149, DOI 10.1023/A:1011322031747
   Bouckaert R., 2013, BEAST2: A software platform for Bayesian evolutionary analysis
   Bowman DMJS, 2010, J BIOGEOGR, V37, P201, DOI 10.1111/j.1365-2699.2009.02210.x
   Burbidge AA, 2008, MAMMALS AUSTR, P277
   Byrne M, 2008, MOL ECOL, V17, P4398, DOI 10.1111/j.1365-294X.2008.03899.x
   Byrne M, 2011, J BIOGEOGR, V38, P1635, DOI 10.1111/j.1365-2699.2011.02535.x
   Cadotte MW, 2012, ECOLOGY, V93, pS223, DOI 10.1890/11-0426.1
   Cassens I, 2005, SYST BIOL, V54, P363, DOI 10.1080/10635150590945377
   Catullo RA, 2014, J BIOGEOGR, V41, P659, DOI 10.1111/jbi.12230
   CRACRAFT J, 1991, Australian Systematic Botany, V4, P211, DOI 10.1071/SB9910211
   Department of Environment and Conservation Western Australia, 2013, THREAT PRIOR FAUN RA
   Doody JS, 2012, AUST MAMMAL, V34, P260, DOI 10.1071/AM11039
   Doughty Paul, 2011, Records of the Western Australian Museum, V26, P209
   Eldridge MDB, 2011, AUST J ZOOL, V59, P270, DOI 10.1071/ZO12012
   Excoffier L, 2005, EVOL BIOINFORM, V1, P47, DOI 10.1177/117693430500100003
   Fitzsimons J., 2010, Into oblivion: the disappearing native mammals of northern Australia
   Flannery T., 1987, P477
   Flannery T, 1994, MONOGRAPH PHALANGERI
   Fu YX, 1997, GENETICS, V147, P915
   Fuchs R, 2013, BIOGEOSCIENCES, V10, P1543, DOI 10.5194/bg-10-1543-2013
   Fujita MK, 2010, EVOLUTION, V64, P2293, DOI 10.1111/j.1558-5646.2010.00993.x
   Fumagalli L, 1997, MOL ECOL, V6, P1199, DOI 10.1046/j.1365-294X.1997.00298.x
   HASEGAWA M, 1985, J MOL EVOL, V22, P160, DOI 10.1007/BF02101694
   Houlder DJ, 2000, ANUCLIM USER GUIDE V
   Huelsenbeck JP, 2005, STAT BIOL HEALTH, P183, DOI 10.1007/0-387-27733-1_7
   Humphreys W.F., 1984, P162
   Jennings WB, 2005, EVOLUTION, V59, P2033
   Keppel G, 2012, GLOBAL ECOL BIOGEOGR, V21, P393, DOI 10.1111/j.1466-8238.2011.00686.x
   Klein C, 2009, ECOL APPL, V19, P206, DOI 10.1890/07-1684.1
   Köhler F, 2011, REC AUST MUS, V63, P167, DOI 10.3853/j.0067-1975.63.2011.1581
   Köhler F, 2010, REC AUST MUS, V62, P217, DOI 10.3853/j.0067-1975.62.2010.1554
   Legge S, 2008, WILDLIFE RES, V35, P33, DOI 10.1071/WR07016
   Legge S, 2011, AUSTRAL ECOL, V36, P791, DOI 10.1111/j.1442-9993.2010.02218.x
   Librado P, 2009, BIOINFORMATICS, V25, P1451, DOI 10.1093/bioinformatics/btp187
   Mackey Brendan G., 2008, Biodiversity (Ottawa), V9, P11
   McKnight M, 2008, IUCN 2013 IUCN RED L
   Melville J, 2011, MOL PHYLOGENET EVOL, V58, P257, DOI 10.1016/j.ympev.2010.11.025
   Meredith RW, 2008, AUST J ZOOL, V56, P395, DOI 10.1071/ZO08044
   Moritz C., 2013, Pacific Conservation Biology, V19, P343
   Oliver PM, 2012, WILDLIFE RES, V39, P429, DOI 10.1071/WR12024
   Oliver PM, 2010, BMC EVOL BIOL, V10, DOI 10.1186/1471-2148-10-386
   Osborne MJ, 2002, AUST J ZOOL, V50, P135, DOI 10.1071/ZO01070
   Osborne MJ, 2001, MOL PHYLOGENET EVOL, V20, P211, DOI 10.1006/mpev.2001.0960
   Posada D, 1998, BIOINFORMATICS, V14, P817, DOI 10.1093/bioinformatics/14.9.817
   Potter S, 2012, MOL ECOL, V21, P2254, DOI 10.1111/j.1365-294X.2012.05523.x
   Ramos-Onsins SE, 2002, MOL BIOL EVOL, V19, P2092, DOI 10.1093/oxfordjournals.molbev.a004034
   Ronquist F, 2003, BIOINFORMATICS, V19, P1572, DOI 10.1093/bioinformatics/btg180
   Rosauer D, 2009, MOL ECOL, V18, P4061, DOI 10.1111/j.1365-294X.2009.04311.x
   Rozas J, 2003, BIOINFORMATICS, V19, P2496, DOI 10.1093/bioinformatics/btg359
   Runcie MJ, 1999, WILDLIFE RES, V26, P367, DOI 10.1071/WR98015
   RUSSELLSMITH J, 1993, J VEG SCI, V4, P67, DOI 10.2307/3235734
   Singarayer JS, 2010, QUATERNARY SCI REV, V29, P43, DOI 10.1016/j.quascirev.2009.10.011
   Stamatakis A, 2008, SYST BIOL, V57, P758, DOI 10.1080/10635150802429642
   Stamatakis A, 2006, BIOINFORMATICS, V22, P2688, DOI 10.1093/bioinformatics/btl446
   Sunnucks P, 1996, MOL BIOL EVOL, V13, P510, DOI 10.1093/oxfordjournals.molbev.a025612
   Swofford D, 2002, PAUP 4 0B
   TAJIMA F, 1989, GENETICS, V123, P585
   Toon A, 2010, MOL ECOL, V19, P2980, DOI 10.1111/j.1365-294X.2010.04730.x
   Van der Wal J., 2012, SDMtools: Species distribution modelling tools: Tools for processing data associated with species distribution modelling exercises
   Wheeler D, 2001, P NATL ACAD SCI USA, V98, P1101, DOI 10.1073/pnas.98.3.1101
   Woinarski J, 2007, NATURE OF NORTHERN AUSTRALIA: NATURAL VALUES, ECOLOGICAL PROCESSES AND FUTURE PROSPECTS, P1
   Woinarski JCZ, 2011, CONSERV LETT, V4, P192, DOI 10.1111/j.1755-263X.2011.00164.x
NR 66
TC 7
Z9 11
U1 0
U2 19
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 1566-0621
EI 1572-9737
J9 CONSERV GENET
JI Conserv. Genet.
PD OCT
PY 2014
VL 15
IS 5
BP 1085
EP 1094
DI 10.1007/s10592-014-0601-4
PG 10
WC Biodiversity Conservation; Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Genetics & Heredity
GA AP6GD
UT WOS:000342174700008
DA 2025-01-10
ER

PT J
AU Jonkman, SN
   Hillen, MM
   Nicholls, RJ
   Kanning, W
   van Ledden, M
AF Jonkman, Sebastiaan N.
   Hillen, Marten M.
   Nicholls, Robert J.
   Kanning, Wim
   van Ledden, Mathijs
TI Costs of Adapting Coastal Defences to Sea-Level Rise-New Estimates and
   Their Implications
SO JOURNAL OF COASTAL RESEARCH
LA English
DT Article
DE Climate adaptation; engineering measures; dikes; flood protection; storm
   surge barriers; sea-level rise; unit costs
AB The cost of upgrading and raising coastal defences is an important consideration in societal response to sea-level rise. Currently available unit cost estimates have a limited empirical basis. This article presents new information on the unit costs of adapting coastal defences for three specific case studies in low-lying delta regions: The Netherlands, New Orleans, and Vietnam. Typical measures include dikes, flood walls, storm surge barriers, and nourishment. These unit cost estimates are significantly higher than earlier estimates that are still the main source of costs for global vulnerability assessments. Factors affecting these unit costs include local economic factors (material and labour costs), design choices related to the alignment of the system, and the types of measures for implementation of the system in an urban or rural environment. On the basis of an example for a Dutch sea dike, it is shown that the material quantities and associated costs are expected to rise linearly, in the case of depth-limited wave breaking, for the range of sea-level rise rates that are expected in the coming century. However, other factors, such as increasing costs for implementation of wider coastal defences in an urban environment and future changes in material and labour costs, could contribute to a nonlinear increase of the costs. Further collection and analysis of project information for coastal defence projects in other regions is recommended to strengthen the empirical basis of the cost estimates that are used for regional and global assessments.
C1 [Jonkman, Sebastiaan N.; Kanning, Wim; van Ledden, Mathijs] Delft Univ Technol, Fac Civil Engn & Geosci, Sect Hydraul Engn, NL-2628 CN Delft, Netherlands.
   [Hillen, Marten M.; van Ledden, Mathijs] Royal HaskoningDHV, Business Line Rivers Deltas & Coasts, Rotterdam, Netherlands.
   [Nicholls, Robert J.] Univ Southampton, Sch Civil Engn & Environm, Southampton SO17 1BJ, Hants, England.
   Deltares, NL-2629 HD Delft, Netherlands.
C3 Delft University of Technology; University of Southampton; Deltares
RP Jonkman, SN (corresponding author), Delft Univ Technol, Fac Civil Engn & Geosci, Sect Hydraul Engn, Stevinweg 1, NL-2628 CN Delft, Netherlands.
EM s.n.jonkman@tudelft.nl
RI ; Nicholls, Robert/G-3898-2010
OI Jonkman, Sebastiaan/0000-0003-0162-8281; Nicholls,
   Robert/0000-0002-9715-1109
FU U.K. Department for Energy and Climate Change (DECC)/Department for
   Environment, Food, and Rural Affairs (Defra) through the AVOID
   programme; National Science Foundation (NSF) under EFGRI [0836047];
   Directorate For Engineering; Emerging Frontiers & Multidisciplinary
   Activities [0836047] Funding Source: National Science Foundation
FX This research was funded by the U.K. Department for Energy and Climate
   Change (DECC)/Department for Environment, Food, and Rural Affairs
   (Defra) through the AVOID programme on avoiding dangerous climate
   change. This project was supported by the National Science Foundation
   (NSF) under EFGRI grant 0836047. Any opinions, findings, and conclusions
   or recommendations expressed in this material are those of the authors
   and do not necessarily reflect the views of the NSF. The contributions
   of Marli Geldenhuys, Ries Kluskens, M. Kok, J.K. Vrijling, and M.J.F.
   Stive are gratefully acknowledged.
CR AFPM (Advisory Committee Primary Water Defences), 2006, TUSS NAAR 2015 ADV F
   [Anonymous], 2007, FUTURE FLOODING COAS
   [Anonymous], 156 MIT JOINT PROGR
   [Anonymous], STATL
   [Anonymous], STRAT AD SEA LEV RIS
   [Anonymous], 2006, INVESTIGATION PERFOR
   [Anonymous], WORK TOG WAT FIND DE
   [Anonymous], 2007, AR4 CLIMATE CHANGE 2
   [Anonymous], PERF EV NEW ORL SE L
   ARCADIS and Fugro, 2006, KOST DIJKR 7 14 29
   Bos A.J., 2008, THESIS U AMSTERDAM A
   Dijkman J., 2007, WLZ4307 NETH WAT PAR
   Eijgenraam C. J. J., 2006, 62 CPB NETH BUR EC P
   Gilbert S., 1984, The Thames Barrier
   Grossi P., 2006, Flood risk in New Orleans: implications for future management and insurability
   Hanson S, 2011, CLIMATIC CHANGE, V104, P89, DOI 10.1007/s10584-010-9977-4
   Hillen M.M., 2010, Coastal Defence Cost Estimates. Case Study of the Netherlands
   Hillen MM, 2008, SAFETY STANDARDS PRO, DOI DOI 10.1016/j.coastaleng.2014.08.005
   Hinkel J., 2005, ADV GEOSCIENCES, P4, DOI [10.5194/adgeo-4-45-2005, DOI 10.5194/adgeo-4-45-2005]
   Hoozemans F.M.J., 1993, GLOBAL VULNERABILITY
   Jones H.P., 2012, NATURE CLIMATE CHANG, V2, P504
   Jongejan RB, 2008, HYDROBIOLOGIA, V605, P11, DOI 10.1007/s10750-008-9363-7
   Jonkman SN, 2009, RISK ANAL, V29, P676, DOI 10.1111/j.1539-6924.2008.01190.x
   Kok M., 2008, TOEKOMST NEDERLANDSE
   Linham M., 2010, Report 14 of the AVOID programme (AV/WS2/D1/R14)
   Mai C.V., 2010, THESIS DELFT U TECHN
   Mai CV, 2009, J COASTAL RES, V25, P105, DOI 10.2112/07-0888.1
   Mai CV., 2008, 4th International symposium on flood defence: managing flood risk, reliability and vulnerability, P931
   McRobie A, 2005, PHILOS T R SOC A, V363, P1263, DOI 10.1098/rsta.2005.1567
   Nicholls R. J., 2008, RANKING PORT CITIES, V1
   Nicholls RJ., 2010, UNDERSTANDING SEA LE, P17
   Nicholls RJ, 2008, CLIMATIC CHANGE, V91, P171, DOI 10.1007/s10584-008-9424-y
   Nicholls RJ, 2011, PHILOS T R SOC A, V369, P161, DOI [10.1098/rsta.2010.0291, 10.1098/rsta.2010.029]
   Penning-Rowsell E.C., 2003, The Benefits of Flood and Coastal Defence: Techniques and Data for 2003
   Pilarczyk K.W., 2002, P SOL COAST DIS C 20, P186
   Resio DT, 2008, PHYS TODAY, V61, P33, DOI 10.1063/1.2982120
   Rijkswaterstaat, 2009, NOUR PRES A ROOS
   Small C, 2003, J COASTAL RES, V19, P584
   Takeuchi K, 2002, WATER INT, V27, P20, DOI 10.1080/02508060208686974
   TITUS JG, 1991, COAST MANAGE, V19, P171, DOI 10.1080/08920759109362138
   Tol R.S.J., 2006, DIVA MODEL SOCIOECON
   Tol RichardS.J., 1997, Environmental Modelling and Assessment, V2, P151, DOI [DOI 10.1023/A:1019017529030, 10.1023/A:1019017529030]
   Turner & Townsend, 2012, INT CONSTR COST SURV
   USACE (U.S. Army Corps of Engineers), 2009, LOUIS COAST PROT RES
   Vafeidis AT, 2008, J COASTAL RES, V24, P917, DOI 10.2112/06-0725.1
   Van der Waart M., 2010, H2O, V7, P18
   Van Koningsveld M, 2008, J COASTAL RES, V24, P367, DOI 10.2112/07A-0010.1
   van Slobbe E, 2013, NAT HAZARDS, V65, P947, DOI 10.1007/s11069-012-0342-y
   van Stokkom HTC, 2005, WATER INT, V30, P76, DOI 10.1080/02508060508691839
   VANDANTZIG D, 1956, ECONOMETRICA, V24, P276, DOI 10.2307/1911632
   Yohe G, 1996, CLIMATIC CHANGE, V32, P387, DOI 10.1007/BF00140353
   Zhu X., 2010, Coastal erosion and flooding
NR 52
TC 102
Z9 118
U1 7
U2 100
PU COASTAL EDUCATION & RESEARCH FOUNDATION
PI COCONUT CREEK
PA 5130 NW 54TH STREET, COCONUT CREEK, FL 33073 USA
SN 0749-0208
EI 1551-5036
J9 J COASTAL RES
JI J. Coast. Res.
PD SEP
PY 2013
VL 29
IS 5
BP 1212
EP 1226
DI 10.2112/JCOASTRES-D-12-00230.1
PG 15
WC Environmental Sciences; Geography, Physical; Geosciences,
   Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Physical Geography; Geology
GA 243GL
UT WOS:000326304800022
DA 2025-01-10
ER

PT J
AU Ruthrauff, DR
   Dekinga, A
   Gill, RE 
   Piersma, T
AF Ruthrauff, Daniel R.
   Dekinga, Anne
   Gill, Robert E., Jr.
   Piersma, Theunis
TI IDENTICAL METABOLIC RATE AND THERMAL CONDUCTANCE IN ROCK SANDPIPER
   (<i>CALIDRIS PTILOCNEMIS</i>) SUBSPECIES WITH CONTRASTING NONBREEDING
   LIFE HISTORIES
SO AUK
LA English
DT Article
DE basal metabolic rate; BMR; Calidris ptilocnemis; metabolic rate;
   phenotypic flexibility; Rock Sandpiper; shorebirds; temperature effects;
   thermal conductance
ID DISTANCE MIGRANT SHOREBIRD; RED KNOTS; SEASONAL ACCLIMATIZATION;
   CLIMATIC ADAPTATION; ENERGY-EXPENDITURE; CARDUELINE FINCHES;
   BODY-COMPOSITION; BASAL; TEMPERATURE; BIRDS
AB Closely related species or subspecies can exhibit metabolic differences that reflect site-specific environmental conditions. Whether such differences represent fixed traits or flexible adjustments to local conditions, however, is difficult to predict across taxa. The nominate race of Rock Sandpiper (Calidris ptilocnemis) exhibits the most northerly nonbreeding distribution of any shorebird in the North Pacific, being common during winter in cold, dark locations as far north as upper Cook Inlet, Alaska (61 degrees N). By contrast, the tschuktschorum subspecies migrates to sites ranging from about 59 degrees N to more benign locations as far south as similar to 37 degrees N. These distributional extremes exert contrasting energetic demands, and we measured common metabolic parameters in the two subspecies held under identical laboratory conditions to determine whether differences in these parameters are reflected by their nonbreeding life histories. Basal metabolic rate and thermal conductance did not differ between subspecies, and the subspecies had a similar metabolic response to temperatures below their thermoneutral zone. Relatively low thermal conductance values may, however, reflect intrinsic metabolic adaptations to northerly latitudes. In the absence of differences in basic metabolic parameters, the two subspecies' nonbreeding distributions will likely be more strongly influenced by adaptations to regional variation in ecological factors such as prey density, prey quality, and foraging habitat. Received 19 April 2012, accepted 4 September 2012.
C1 [Ruthrauff, Daniel R.; Gill, Robert E., Jr.] US Geol Survey, Alaska Sci Ctr, Anchorage, AK 99508 USA.
   [Ruthrauff, Daniel R.; Dekinga, Anne; Piersma, Theunis] NIOZ Royal Netherlands Inst Sea Res, Dept Marine Ecol, NL-1790 AB Den Burg, Texel, Netherlands.
   [Ruthrauff, Daniel R.; Piersma, Theunis] Univ Groningen, Ctr Ecol & Evolutionary Studies, Anim Ecol Grp, NL-9700 CC Groningen, Netherlands.
C3 United States Department of the Interior; United States Geological
   Survey; Utrecht University; Royal Netherlands Institute for Sea Research
   (NIOZ); University of Groningen
RP Ruthrauff, DR (corresponding author), US Geol Survey, Alaska Sci Ctr, 4210 Univ Dr, Anchorage, AK 99508 USA.
EM druthrauff@usgs.gov
RI Piersma, Theunis/D-1871-2012
OI Piersma, Theunis/0000-0001-9668-466X
CR [Anonymous], 2002, Information and Likelihood Theory: A Basis for Model Selection and Inference
   [Anonymous], 1982, ANIMAL PHYSL PRINCIP
   [Anonymous], ARCTIC IN PRESS
   [Anonymous], DUR DAYL DARKN TABL
   [Anonymous], BIRDS N AM
   [Anonymous], HIST CLIM INF STAT D
   [Anonymous], 2011, R: A language and enviroment for statistical computing
   [Anonymous], SURF MET SOL EN
   [Anonymous], 1996, Size, function, and life history
   Bates D., 2013, Linear mixed-effects models using S4 classes
   Battley PF, 2005, PHYSIOLOGICAL ADAPTATIONS TO FEEDING INVERTEBRATES, P201
   Battley PF, 2012, J AVIAN BIOL, V43, P21, DOI 10.1111/j.1600-048X.2011.05473.x
   Blem C.R., 1990, Current Ornithology, V7, P59
   BLEM CR, 1981, CONDOR, V83, P370, DOI 10.2307/1367508
   Broggi J, 2005, EVOLUTION, V59, P1600
   Broggi J, 2004, J ANIM ECOL, V73, P967, DOI 10.1111/j.0021-8790.2004.00872.x
   Buehler DM, 2009, J ORNITHOL, V150, P815, DOI 10.1007/s10336-009-0402-6
   Buehler DM, 2005, CONDOR, V107, P497, DOI 10.1650/0010-5422(2005)107[0497:PDTAHD]2.0.CO;2
   CAREY C, 1978, J COMP PHYSIOL, V125, P101, DOI 10.1007/BF00686746
   CASTRO G, 1987, WILSON BULL, V99, P267
   Conover Boardman, 1944, FIELD MUS NAT HIST ZOOL SER, V29, P169
   Cooper SJ, 2002, PHYSIOL BIOCHEM ZOOL, V75, P386, DOI 10.1086/342256
   Dawson William R., 1996, P85
   DAWSON WR, 1976, J COMP PHYSIOL, V112, P317, DOI 10.1007/BF00692302
   Dutenhoffer MS, 1996, PHYSIOL ZOOL, V69, P1232, DOI 10.1086/physzool.69.5.30164255
   DYKSTRA CR, 1992, PHYSIOL ZOOL, V65, P422, DOI 10.1086/physzool.65.2.30158261
   GESSAMAN JA, 1988, PHYSIOL ZOOL, V61, P507, DOI 10.1086/physzool.61.6.30156159
   Griffiths R, 1996, P ROY SOC B-BIOL SCI, V263, P1251, DOI 10.1098/rspb.1996.0184
   HOHTOLA E, 1980, J COMP PHYSIOL, V136, P77, DOI 10.1007/BF00688626
   Hohtola Esa, 2004, Biological Papers of the University of Alaska, V27, P241
   IUPS Thermal Commission, 2003, J THERM BIOL, V28, P75
   Karasov William H., 1996, P61
   KERSTEN M, 1987, ARDEA, V75, P175
   KLAASSEN M, 1995, OECOLOGIA, V104, P424, DOI 10.1007/BF00341339
   Mazerolle M., 2011, AICcmodavg: model selection and multimodel inference based on (Q) AIC (c)
   MCNAB BK, 1980, PHYSIOL ZOOL, V53, P145, DOI 10.1086/physzool.53.2.30152577
   Mueller P, 2001, P NATL ACAD SCI USA, V98, P12550, DOI 10.1073/pnas.221456698
   NIEWIAROWSKI PH, 1993, ECOLOGY, V74, P1992, DOI 10.2307/1940842
   Packard GC, 1999, COMP BIOCHEM PHYS A, V122, P37, DOI 10.1016/S1095-6433(98)10170-8
   Piersma T, 1997, TRENDS ECOL EVOL, V12, P134, DOI 10.1016/S0169-5347(97)01003-3
   Piersma T, 2004, J AVIAN BIOL, V35, P99, DOI 10.1111/j.0908-8857.2004.03259.x
   PIERSMA T, 1995, J COMP PHYSIOL B, V165, P37, DOI 10.1007/BF00264684
   Piersma T, 2002, INTEGR COMP BIOL, V42, P51, DOI 10.1093/icb/42.1.51
   Piersma T, 1996, PHYSIOL ZOOL, V69, P191, DOI 10.1086/physzool.69.1.30164207
   Piersma T., 1996, Handbook of the Birds of the World, V3, P444
   Piersma T., 2011, The flexible phenotype: a body-centered integration of ecology, physiology, and behaviour
   Piersma T., 1996, Int. Wader Studies, V8, P122
   Piersma T, 2007, J ORNITHOL, V148, pS45, DOI 10.1007/s10336-007-0240-3
   Piersma T, 2011, J EXP BIOL, V214, P295, DOI 10.1242/jeb.046748
   PITELKA FA, 1974, AM ZOOL, V14, P185
   Pruett CL, 2005, CLIMATIC CHANGE, V68, P219, DOI 10.1007/s10584-005-1584-4
   Rezende EL, 2002, J EXP BIOL, V205, P101
   SCHOLANDER PF, 1955, EVOLUTION, V9, P15, DOI 10.2307/2405354
   SCHOLANDER PF, 1950, BIOL BULL-US, V99, P225, DOI 10.2307/1538740
   SCHOLANDER PF, 1950, BIOL BULL-US, V99, P259, DOI 10.2307/1538742
   STEARNS SC, 1989, FUNCT ECOL, V3, P259, DOI 10.2307/2389364
   Swanson DL, 2010, CURR ORNITHOL, V17, P75, DOI 10.1007/978-1-4419-6421-2_3
   SWANSON DL, 1991, CONDOR, V93, P538, DOI 10.2307/1368185
   Tieleman BI, 2007, COMP BIOCHEM PHYS A, V146, P194, DOI 10.1016/j.cbpa.2006.10.011
   van Gils JA, 2005, P ROY SOC B-BIOL SCI, V272, P2609, DOI 10.1098/rspb.2005.3245
   Van Gils JA, 2005, J ANIM ECOL, V74, P105, DOI 10.1111/j.1365-2656.2004.00903.x
   Van Gils JA, 2005, J ANIM ECOL, V74, P120, DOI 10.1111/j.1365-2656.2004.00904.x
   Vézina F, 2007, AM J PHYSIOL-REG I, V292, pR1287, DOI 10.1152/ajpregu.00683.2006
   Vézina F, 2006, J EXP BIOL, V209, P3141, DOI 10.1242/jeb.02338
   Vézina F, 2011, INTEGR COMP BIOL, V51, P394, DOI 10.1093/icb/icr044
   Vézina F, 2009, PHYSIOL BIOCHEM ZOOL, V82, P129, DOI 10.1086/596512
   WEATHERS WW, 1979, OECOLOGIA, V42, P81, DOI 10.1007/BF00347620
   WEST GC, 1972, COMP BIOCHEM PHYSIOL, V42, P867, DOI 10.1016/0300-9629(72)90393-3
   WHITE CM, 1977, OECOLOGIA, V27, P227, DOI 10.1007/BF00347468
   WIERSMA P, 1994, CONDOR, V96, P257, DOI 10.2307/1369313
   Wikelski M, 2003, P ROY SOC B-BIOL SCI, V270, P2383, DOI 10.1098/rspb.2003.2500
   Williams JB, 2004, J COMP PHYSIOL B, V174, P29, DOI 10.1007/s00360-003-0386-0
   Zuur Alain F., 2009, P1
NR 73
TC 10
Z9 10
U1 0
U2 26
PU OXFORD UNIV PRESS INC
PI CARY
PA JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA
EI 1938-4254
J9 AUK
JI AUK
PD JAN
PY 2013
VL 130
IS 1
BP 60
EP 68
DI 10.1525/auk.2012.12081
PG 9
WC Ornithology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Zoology
GA 091RZ
UT WOS:000315068800007
OA Green Published
DA 2025-01-10
ER

PT J
AU Noback, ML
   Harvati, K
   Spoor, F
AF Noback, Marlijn L.
   Harvati, Katerina
   Spoor, Fred
TI Climate-Related Variation of the Human Nasal Cavity
SO AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY
LA English
DT Article
DE nose; adaptation; geometric morphometrics; PLS
ID PARTIAL LEAST-SQUARES; HUMAN-BRAIN; AIR-FLOW; MORPHOLOGY; NOSE; FACE;
   TEMPERATURE; SHAPE; SIZE; HOMO
AB The nasal cavity is essential for humidifying and warming the air before it reaches the sensitive lungs. Because humans inhabit environments that can be seen as extreme from the perspective of respiratory function, nasal cavity shape is expected to show climatic adaptation. This study examines the relationship between modern human variation in the morphology of the nasal cavity and the climatic factors of temperature and vapor pressure, and tests the hypothesis that within increasingly demanding environments (colder and drier), nasal cavities will show features that enhance turbulence and air-wall contact to improve conditioning of the air. We use three-dimensional geometric morphometrics methods and multi-variate statistics to model and analyze the shape of the bony nasal cavity of 10 modern human population samples from five climatic groups. We report significant correlations between nasal cavity shape and climatic variables of both temperature and humidity. Variation in nasal cavity shape is correlated with a cline from cold dry climates to hot humid climates, with a separate temperature and vapor pressure effect. The bony nasal cavity appears mostly associated with temperature, and the nasopharynx with humidity. The observed climate-related shape changes are functionally consistent with an increase in contact between air and mucosal tissue in cold dry climates through greater turbulence during inspiration and a higher surface-to-volume ratio in the upper nasal cavity. Am J Phys Anthropol 145:599-614,2011. (C) 2011 Wiley-Liss, Inc.
C1 [Noback, Marlijn L.; Harvati, Katerina] Univ Tubingen, Dept Early Prehist & Quaternary Ecol, Senckenberg Ctr Human Evolut & Paleoecol, Paleoanthropol Sect, D-72070 Tubingen, Germany.
   [Noback, Marlijn L.; Spoor, Fred] UCL, Dept Cell & Dev Biol, London WC1E 6JJ, England.
   [Spoor, Fred] Max Planck Inst Evolutionary Anthropol, Dept Human Evolut, D-04103 Leipzig, Germany.
C3 Leibniz Association; Senckenberg Gesellschaft fur Naturforschung (SGN);
   Eberhard Karls University of Tubingen; University of London; University
   College London; Max Planck Society
RP Noback, ML (corresponding author), Univ Tubingen, Dept Early Prehist & Quaternary Ecol, Senckenberg Ctr Human Evolut & Paleoecol, Paleoanthropol Sect, Rumelinstr 23, D-72070 Tubingen, Germany.
EM marlijn.no-back@ifu.uni-tuebingen.de
RI Harvati, Katerina/A-5197-2008
FU Huygens Scholarship Programme-Talentprogramme [HSP-TP.07/192]
FX Grant sponsor: Huygens Scholarship Programme-Talentprogramme; Grant
   number: HSP-TP.07/192.
CR [Anonymous], 1958, The comparative anatomy and physiology of the nose and paranasal sinuses
   BAKER PT, 1988, HUMAN BIOL INTRO HUM, P437
   BEALS KL, 1984, CURR ANTHROPOL, V25, P301, DOI 10.1086/203138
   Bookstein F.L., 1991, Morphometric Tools for Landmark Data: Geometry and Biology
   Bookstein FL, 1996, DEV PSYCHOL, V32, P404
   Bookstein FL, 2003, J HUM EVOL, V44, P167, DOI 10.1016/S0047-2484(02)00201-4
   Brauer G., 1988, ANTHROPOLOGIE, P160
   CABANAC M, 1979, J PHYSIOL-LONDON, V286, P255, DOI 10.1113/jphysiol.1979.sp012617
   CAREY JW, 1981, AM J PHYS ANTHROPOL, V56, P313, DOI 10.1002/ajpa.1330560312
   Churchill SE, 2004, AM J HUM BIOL, V16, P625, DOI 10.1002/ajhb.20074
   Clement PAR, 2005, RHINOLOGY, V43, P169
   Cole P, 2000, AM J RHINOL, V14, P245, DOI 10.2500/105065800779954383
   COLE Ph., 1982, NOSE UPPER AIRWAY PH, P163
   Corey JP, 1998, OTOLARYNG HEAD NECK, V119, P389, DOI 10.1016/S0194-5998(98)70085-3
   COURTISS EH, 1983, PLAST RECONSTR SURG, V72, P9, DOI 10.1097/00006534-198307000-00003
   Davies A, 1932, J R ANTHROPOL INST G, V62, P337, DOI 10.2307/2843962
   DEAN MC, 1988, J HUM EVOL, V17, P715, DOI 10.1016/0047-2484(88)90026-7
   DEKLUNDER G, 1991, EUR J APPL PHYSIOL O, V62, P342, DOI 10.1007/BF00634970
   FRANCISCUS RG, 1991, AM J PHYS ANTHROPOL, V85, P419, DOI 10.1002/ajpa.1330850406
   Franciscus RG, 2003, AM J PHYS ANTHROPOL, P96
   FRANCISCUS RG, 1988, AM J PHYS ANTHROPOL, V75, P517, DOI 10.1002/ajpa.1330750409
   Gil JA, 1998, J CHEMOMETR, V12, P365, DOI 10.1002/(SICI)1099-128X(199811/12)12:6<365::AID-CEM519>3.0.CO;2-G
   Hall RL, 2005, AM J HUM BIOL, V17, P321, DOI 10.1002/ajhb.20122
   Harvati K, 2003, J HUM EVOL, V44, P107, DOI 10.1016/S0047-2484(02)00208-7
   Harvati K, 2007, VERTEBR PALEOBIOL PA, P239
   Harvati K, 2006, ANAT REC PART A, V288A, P1225, DOI 10.1002/ar.a.20395
   Hoyme St.L E Iscan MY., 1989, Reconstruction of Life From the Skeleton, P53
   Hubbe M, 2009, ANAT REC, V292, P1720, DOI 10.1002/ar.20976
   Inthavong K., 2007, P 16 AUSTRALASIAN FL, P842
   JESSEN C, 1992, J APPL PHYSIOL, V72, P664, DOI 10.1152/jappl.1992.72.2.664
   Keck T, 2000, RHINOLOGY, V38, P167
   Klingenberg CP, 2011, MOL ECOL RESOUR, V11, P353, DOI 10.1111/j.1755-0998.2010.02924.x
   Klingenberg CP, 2005, SYST BIOL, V54, P678, DOI 10.1080/10635150590947258
   Lieberman DE., 2011, EVOLUTION HUMAN HEAD
   Lockwood CA, 2002, J ANAT, V201, P447, DOI 10.1046/j.1469-7580.2002.00122.x
   Maloney SK, 2007, AM J PHYSIOL-REG I, V292, pR2059, DOI 10.1152/ajpregu.00809.2006
   Manfreda Evelyn, 2006, Anatomical Record Part B:The New Anatomist, V289, P184, DOI 10.1002/ar.b.20113
   MANTEL N, 1967, CANCER RES, V27, P209
   Mariak Z, 1999, J APPL PHYSIOL, V87, P1609, DOI 10.1152/jappl.1999.87.5.1609
   Mekjavic IB, 2002, J APPL PHYSIOL, V93, P65, DOI 10.1152/japplphysiol.00873.2001
   Mitteroecker P, 2009, EVOL BIOL, V36, P235, DOI 10.1007/s11692-009-9055-x
   Mlynski G, 2001, RHINOLOGY, V39, P197
   Morgan N. J., 1995, Rhinology (Utrecht), V33, P224
   MOWBRAY K, 2001, ATHENA REV, V4, P59
   Neff NA., 1980, A Survey of Multivariate Methods for Systematics
   O'Higgins P, 1998, J ANAT, V193, P251, DOI 10.1046/j.1469-7580.1998.19320251.x
   Relethford JH, 2004, AM J HUM BIOL, V16, P379, DOI 10.1002/ajhb.20045
   Relethford JH, 2001, HUM BIOL, V73, P629, DOI 10.1353/hub.2001.0073
   Rohlf FJ, 2000, SYST BIOL, V49, P740, DOI 10.1080/106351500750049806
   ROHLF FJ, 1993, TRENDS ECOL EVOL, V8, P129, DOI 10.1016/0169-5347(93)90024-J
   Rohlf JF., 1990, Proceedings of the Michigan Morphometrics Workshop, P227
   Roseman CC, 2004, P NATL ACAD SCI USA, V101, P12824, DOI 10.1073/pnas.0402637101
   SHEA BT, 1977, AM J PHYS ANTHROPOL, V47, P289, DOI 10.1002/ajpa.1330470209
   Slice DE, 1996, NATO ADV SCI INST SE, V284, P179
   Thomson A, 1923, J R ANTHROPOL INST G, V53, P92, DOI 10.2307/2843753
   ULIYANOV YP, 1998, OTOLARYNGOL HEAD NEC, V152, P152
   Van Oldenborgh GJ, 2005, J CLIMATE, V18, P3250, DOI 10.1175/JCLI3421.1
   Weiner JS, 1954, AM J PHYS ANTHROP-NE, V12, P615, DOI 10.1002/ajpa.1330120412
   Yokley TR, 2009, AM J PHYS ANTHROPOL, V138, P11, DOI 10.1002/ajpa.20893
NR 59
TC 153
Z9 175
U1 1
U2 43
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0002-9483
EI 1096-8644
J9 AM J PHYS ANTHROPOL
JI Am. J. Phys. Anthropol.
PD AUG
PY 2011
VL 145
IS 4
BP 599
EP 614
DI 10.1002/ajpa.21523
PG 16
WC Anthropology; Evolutionary Biology
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Anthropology; Evolutionary Biology
GA 797TJ
UT WOS:000293152700009
PM 21660932
DA 2025-01-10
ER

PT J
AU Joseph, JE
   Akinseye, FM
   Worou, ON
   Faye, A
   Konte, O
   Whitbread, AM
   Rötter, RP
AF Joseph, Jacob Emanuel
   Akinseye, Folorunso M.
   Worou, Omonlola Nadine
   Faye, Aliou
   Konte, Oumar
   Whitbread, Anthony M.
   Roetter, Reimund P.
TI Assessment of the relations between crop yield variability and the onset
   and intensity of the West African Monsoon
SO AGRICULTURAL AND FOREST METEOROLOGY
LA English
DT Article
DE West African Monsoon; Onset dates; Soil organic carbon; Plant available
   water capacity; Climate variability; APSIM
ID USE EFFICIENCY; WINTER-WHEAT; SEASON; TRENDS; RAINFALL; SENEGAL; REGION;
   MAIZE
AB Timely information on the onset of rain is essential for effectively adapting to climate variability and increasing the resilience of rain-fed systems. However, defining optimal sowing dates based on the onset of rain has been challenging. We compared and analyzed the West African Monsoon onset according to Raman's, modified Sivakumar's, Yamada's, and Liebmann's definitions using station data from 13 locations in Senegal from 1981 to 2020. Subsequently, we systematically analyzed the effect of the differently estimated monsoon onsets(WAM-OS) on maize development. To this end, we applied the set of the generated WAM-OS as sowing dates in simulations of maize growth and yields, applying the Agricultural Production Systems sIMulator(APSIM) at 13 locations representing different agroclimatic regions across Senegal. We examined the impact of the sowing dates under variable conditions of soil organic carbon(SOC) and plant available water capacity(PAWC). Our analysis showed statistically significant differences between the WAM-OS dates, rainfall characteristics computed for these, and maize yields simulated using different sowing dates according to the WAM-OS definitions. We found Liebmann's onset dates were most suitable for both hydrological and agronomic applications since they were characterized by the lowest probabilities of prolonged dry spells after onset, the highest amount of rainfall in the mid-season, and the highest simulated maize yields compared to other onset definitions. Our results highlight the importance of sowing dates and their accurate prediction for improving crop productivity in the study area. We also found SOC and PAWC were important factors that improved maize yields. We recommend improved access to climate information services to help smallholder farmers get timely information that helps them in their sowing decisions and encourage agronomic interventions that improve the SOC level, soil pore volume to retain more water and other soil properties directly(e.g., tillage) and indirectly(suited cropping systems) that contribute to enhancing crop productivity.
C1 [Joseph, Jacob Emanuel; Roetter, Reimund P.] Univ Gottingen, Trop Plant Prod & Agrosyst Modelling TROPAGS, Grisebachstr 6, D-37077 Gottingen, Germany.
   [Akinseye, Folorunso M.] Int Crop Res Inst Semiarid Trop ICRISAT, Kano, Nigeria.
   [Worou, Omonlola Nadine] Int Livestock Res Inst ILRI, Dakar, Senegal.
   [Faye, Aliou] ISRA Reg Ctr Excellence Dry Cereals & Associated, Thies 3320, Senegal.
   [Konte, Oumar] Agence Natl Aviat Civile & Meteorol ANACIM, Dakar, Senegal.
   [Roetter, Reimund P.] Univ Gottingen, Ctr Biodivers & Sustainable Land Use CBL, Buesgenweg 1, D-37077 Gottingen, Germany.
   [Joseph, Jacob Emanuel; Whitbread, Anthony M.] Int Livestock Res Inst ILRI, Dar Es Salaam, Tanzania.
C3 University of Gottingen; CGIAR; International Livestock Research
   Institute (ILRI); University of Gottingen; CGIAR; International
   Livestock Research Institute (ILRI)
RP Joseph, JE (corresponding author), Univ Gottingen, Trop Plant Prod & Agrosyst Modelling TROPAGS, Grisebachstr 6, D-37077 Gottingen, Germany.
EM j.emanuel@cgiar.org
RI Rotter, Reimund P./Y-9579-2019; Whitbread, Anthony/F-3068-2010
OI Rotter, Reimund P./0000-0002-3804-9964; Joseph, Jacob
   Emanuel/0000-0002-0214-7298; Whitbread, Anthony/0000-0003-4840-7670
FU Academy for International Agricultural Research (ACINAR); Tropical Plant
   Production and Agricultural Systems Modelling (TROPAGS) division in the
   Department of Crop Sciences, University of Gottingen, Germany;
   International Livestock Research Institute (ILRI); World Bank [173398]
FX This research was funded by the Academy for International Agricultural
   Research (ACINAR). ACINAR, commissioned by the German Federal Ministry
   for Economic Cooperation and Development (BMZ), is being carried out by
   ATSAF e.V. on behalf of the Deutsche Gesellschaft fuer Internationale
   Zusammenarbeit (GIZ) GmbH.We also acknowledge support from the Tropical
   Plant Production and Agricultural Systems Modelling (TROPAGS) division
   in the Department of Crop Sciences, University of Gottingen, Germany,
   the International Livestock Research Institute (ILRI), and the World
   Bank -funded AICCRA project (Accelerating Impacts of CGIAR Climate
   Research for Africa)-Project ID 173398-is acknowledged for funding the
   authors Jacob Emanuel Joseph and Anthony M Whitbread in this study.
CR Agbodan K.M.L., BASE, P248, DOI [10.25518/1780-4507.18799, DOI 10.25518/1780-4507.18799]
   Ahmed A., 2021, J SUSTAIN ENV PEACE, V4, P30, DOI [10.53537/jsep.2021.09.004, DOI 10.53537/JSEP.2021.09.004]
   Akinseye FM, 2016, THEOR APPL CLIMATOL, V124, P973, DOI 10.1007/s00704-015-1460-8
   Almorox J, 2022, AGR WATER MANAGE, V267, DOI 10.1016/j.agwat.2022.107613
   [Anonymous], 1998, P ESA C 5 NITR SLOV
   Bari SH, 2016, ATMOS RES, V176, P148, DOI 10.1016/j.atmosres.2016.02.008
   Bora SL, 2022, CURR SCI INDIA, V122, P801, DOI 10.18520/cs/v122/i7/801-811
   Córdova R, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11092623
   Dunning CM, 2018, J CLIMATE, V31, P9719, DOI [10.1175/JCLI-D-18-0102.1, 10.1175/jcli-d-18-0102.1]
   Dunning CM, 2016, J GEOPHYS RES-ATMOS, V121, P11405, DOI 10.1002/2016JD025428
   Elia EF, 2014, S AFR J LIBR INF, V80, P18, DOI 10.7553/80-1-180
   Faty A., 2018, INT J HYDROL, V2, DOI [10.15406/ijh.2018.02.00149, DOI 10.15406/IJH.2018.02.00149]
   Fitsum Bekele Fitsum Bekele, 2017, Agricultural Sciences, V8, P371, DOI 10.4236/as.2017.85028
   Fitzpatrick RGJ, 2015, J CLIMATE, V28, P8673, DOI 10.1175/JCLI-D-15-0265.1
   Geen R, 2020, REV GEOPHYS, V58, DOI 10.1029/2020RG000700
   Ghaley B.B., 2018, SIMULATION SOIL ORGA
   Ghimire R, 2017, AGRON J, V109, P706, DOI 10.2134/agronj2016.08.0462
   Hernández CM, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su132111739
   Hoffmann MP, 2020, EUR J AGRON, V119, DOI 10.1016/j.eja.2020.126089
   Hummel Diana, 2016, MIGR DEV, V5, P211, DOI [10.1080/21632324.2015.1022972, DOI 10.1080/21632324.2015.1022972]
   Jin N, 2018, SCI TOTAL ENVIRON, V642, P1, DOI 10.1016/j.scitotenv.2018.06.028
   Krell N, 2022, CLIM RISK MANAG, V35, DOI 10.1016/j.crm.2022.100396
   Lamega SA, 2021, CLIM RISK MANAG, V34, DOI 10.1016/j.crm.2021.100362
   Mandrini G, 2022, DATA BRIEF, V40, DOI 10.1016/j.dib.2021.107753
   Mertz O, 2009, ENVIRON MANAGE, V43, P804, DOI 10.1007/s00267-008-9197-0
   Middendorf BJ, 2021, AGR SYST, V190, DOI 10.1016/j.agsy.2021.103108
   Moeletsi ME, 2012, WATER SA, V38, P775, DOI 10.4314/wsa.v38i5.17
   Nelson WCD, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac77a3
   Nouaceur Z, 2020, WATER-SUI, V12, DOI 10.3390/w12061754
   Oelofse M, 2015, EUR J AGRON, V66, P62, DOI 10.1016/j.eja.2015.02.009
   Osabohien R., 2019, The Open Agriculture Journal, V13, P82, DOI [10.2174/1874331501913010082, DOI 10.2174/1874331501913010082]
   Porkka M, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abdd57
   Quagraine K. A., 2017, International Journal of Geosciences, V8, P305, DOI 10.4236/ijg.2017.83015
   Raman C.V.R., 1974, 216 IND MET DEP
   Read LK, 2015, WATER RESOUR RES, V51, P6381, DOI 10.1002/2015WR017089
   Rotter R, 1997, AGR SYST, V53, P69, DOI 10.1016/S0308-521X(96)00037-6
   Sarr MA, 2013, J HYDROL, V505, P326, DOI 10.1016/j.jhydrol.2013.09.032
   Sharma S, 2017, ARAB J GEOSCI, V10, DOI 10.1007/s12517-017-3096-8
   SIVAKUMAR MVK, 1988, AGR FOREST METEOROL, V42, P295, DOI 10.1016/0168-1923(88)90039-1
   SIVAKUMAR MVK, 1992, J CLIMATE, V5, P532, DOI 10.1175/1520-0442(1992)005<0532:EAODSF>2.0.CO;2
   Stern RD., 1981, Journal of Climatology, V66, P59, DOI DOI 10.1002/JOC.3370010107
   Sultan B, 2003, J CLIMATE, V16, P3407, DOI 10.1175/1520-0442(2003)016<3407:TWAMDP>2.0.CO;2
   Tiwari H, 2019, METEOROL ATMOS PHYS, V131, P627, DOI 10.1007/s00703-018-0592-7
   Vega I, 2020, J CLIMATE, V33, P7371, DOI 10.1175/JCLI-D-19-0734.1
   Wilcox C, 2018, J HYDROL, V566, P531, DOI 10.1016/j.jhydrol.2018.07.063
   World Meteorological Organization, 2017, WMO GUID CALC CLIM N, V1203
   Xu F, 2021, AGRONOMY-BASEL, V11, DOI 10.3390/agronomy11081452
   Yamada TJ, 2013, HYDROLOG SCI J, V58, P1276, DOI 10.1080/02626667.2013.814914
NR 48
TC 2
Z9 2
U1 3
U2 13
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 15
PY 2023
VL 333
AR 109431
DI 10.1016/j.agrformet.2023.109431
EA MAR 2023
PG 10
WC Agronomy; Forestry; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Forestry; Meteorology & Atmospheric Sciences
GA C8EQ4
UT WOS:000964189600001
OA Green Accepted
DA 2025-01-10
ER

PT J
AU Oakes, LE
   Ardoin, NM
   Lambin, EF
AF Oakes, Lauren E.
   Ardoin, Nicole M.
   Lambin, Eric F.
TI "I know, therefore I adapt?" Complexities of individual adaptation to
   climate-induced forest dieback in Alaska
SO ECOLOGY AND SOCIETY
LA English
DT Article
DE attitudes; climate change; forest management; individual adaptation;
   knowledge; place attachment; use values
ID YELLOW-CEDAR; ECOSYSTEM SERVICES; ENVIRONMENTAL-CHANGE; PLACE
   ATTACHMENT; OLD TREES; IMPACTS; PERCEPTIONS; KNOWLEDGE; CAPACITY; SELF
AB Individual actions to avoid, benefit from, or cope with climate change impacts partly shape adaptation; much research on adaptation has focused at the systems level, overlooking drivers of individual responses. Theoretical frameworks and empirical studies of environmental behavior identify a complex web of cognitive, affective, and evaluative factors that motivate stewardship. We explore the relationship between knowledge of, and adaptation to, widespread, climate-induced tree mortality to understand the cognitive (i.e., knowledge and learning), affective (i.e., attitudes and place attachment), and evaluative (i.e., use values) factors that influence how individuals respond to climate-change impacts. From 43 semistructured interviews with forest managers and users in a temperate forest, we identified distinct responses to local, climate-induced environmental changes that we then categorized as either behavioral or psychological adaptations. Interviewees developed a depth of knowledge about the dieback through a combination of direct, place-based experiences and indirect, mediated learning through social interactions. Knowing that the dieback was associated with climate change led to different adaptive responses among the interviewees, although knowledge alone did not explain this variation. Forest users reported psychological adaptations to process negative attitudes; these adaptations were spurred by knowledge of the causes, losses of intangible values, and impacts to a species to which they held attachment. Behavioral adaptations exclusive to a high level of knowledge included actions such as using the forests to educate others or changing transportation behaviors to reduce personal energy consumption. Managers integrated awareness of the dieback and its dynamics across spatial scales into current management objectives. Our findings suggest that adaptive management may occur from the bottom up, as individual managers implement new practices in advance of policies. As knowledge of climate-change impacts in local environments increases, resource users may benefit from programs and educational interventions that facilitate coping strategies.
C1 [Oakes, Lauren E.] Stanford Univ, Emmett Interdisciplinary Program Environm & Resou, Stanford, CA 94305 USA.
   [Ardoin, Nicole M.] Stanford Univ, Grad Sch Educ, Stanford, CA 94305 USA.
   [Ardoin, Nicole M.; Lambin, Eric F.] Stanford Univ, Woods Inst Environm, Stanford, CA 94305 USA.
   [Lambin, Eric F.] Stanford Univ, Sch Earth Energy & Environm Sci, Stanford, CA 94305 USA.
C3 Stanford University; Stanford University; Stanford University; Stanford
   University
RP Oakes, LE (corresponding author), Stanford Univ, Emmett Interdisciplinary Program Environm & Resou, Stanford, CA 94305 USA.
OI Oakes, Lauren/0000-0002-0049-1925; Ardoin, Nicole/0000-0002-3290-8211;
   Lambin, Eric/0000-0002-0673-5257
FU Stanford University's School of Earth, Energy, and Environmental
   Sciences; USDA Forest Service; Wilderness Society Gloria Barron
   Fellowship; National Science Foundation Graduate Research Fellowship;
   Emmett Interdisciplinary Program in Environment and Resources at
   Stanford University
FX Funding for this study was provided by Stanford University's School of
   Earth, Energy, and Environmental Sciences, the USDA Forest Service, and
   The Wilderness Society Gloria Barron Fellowship. L. E. O. was supported
   by a National Science Foundation Graduate Research Fellowship and the
   Emmett Interdisciplinary Program in Environment and Resources at
   Stanford University. We thank the study interviewees for sharing their
   perspectives and for their generosity in time, trust, and hospitality.
   The USDA Forest Service Forest Health, Sitka District Forest Service,
   Hoonah District Forest Service, and many community members provided
   housing support for the lead author during data collection. L.
   Petershoare and B. Lindekugel provided assistance identifying Native
   community members for study participation and reviewing participant
   groupings with sensitivity to legal perspectives on subsistence uses. We
   thank J. Felis for GIS support (Fig. 1), as well as C. Woolsey, R.
   Malczynski, and N. Wyman at Stanford University for coding assistance.
   Comments from F. Moore, A. Cravens, and A. Becker improved this
   manuscript, and W. Hoover provided copyedits.
CR 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]
   Adger WN, 2003, ECON GEOGR, V79, P387
   Albert DM, 2013, CONSERV BIOL, V27, P774, DOI 10.1111/cobi.12109
   Allen CD, 2010, FOREST ECOL MANAG, V259, P660, DOI 10.1016/j.foreco.2009.09.001
   [Anonymous], 2011, Living in Denial: Climate change, emotions, and everyday life
   [Anonymous], CUM YELL CED DECL
   [Anonymous], R10PR23 USDA SOR SER
   [Anonymous], 2001, Polar Rec.
   [Anonymous], TIP SHEET CLIM CHANG
   [Anonymous], 2007, CONTRIBUTION WORKING
   [Anonymous], 2002, Qualitative Research and Evaluation Methods
   [Anonymous], RM10MB603B USDA FOR
   [Anonymous], EOS T AM GEOPHYS UNI
   [Anonymous], 2012, Qualitative Inquiry and
   [Anonymous], ENVIRON EDUC RES
   [Anonymous], RM10MB603B USDAFS
   [Anonymous], PNWGTR917 DEP AGR FO
   [Anonymous], 2012, 1379 US GEOL SURV
   [Anonymous], 1987, J. Environ. Edu., DOI DOI 10.1080/00958964.1987.9943482
   Ardoin N.M., 2006, Canadian Journal of Environmental Education, V11, P112
   Ballard HL, 2010, ENVIRON EDUC RES, V16, P611, DOI 10.1080/13504622.2010.505440
   Bamberg S, 2007, J ENVIRON PSYCHOL, V27, P14, DOI 10.1016/j.jenvp.2006.12.002
   BANDURA A, 1977, PSYCHOL REV, V84, P191, DOI 10.1037/0033-295X.84.2.191
   Bandura A., 1977, SOCIAL LEARNING THEO, V1
   Beier C, 2011, ECOL SOC, V16
   Beier CM, 2008, ECOSYSTEMS, V11, P923, DOI 10.1007/s10021-008-9170-z
   Beier CM, 2008, CAN J FOREST RES, V38, P1319, DOI 10.1139/X07-240
   Benson MH, 2014, SOC NATUR RESOUR, V27, P777, DOI 10.1080/08941920.2014.901467
   BIRCH SK, 1983, J ENVIRON EDUC, V14, P26, DOI 10.1080/00958964.1983.9943478
   Blicharska M, 2014, CONSERV BIOL, V28, P1558, DOI 10.1111/cobi.12341
   Blicharska M, 2013, SCIENCE, V339, P904, DOI 10.1126/science.339.6122.904-b
   Bourdieu Pierre., 1998, STATE NOBILITY, VFirst
   Chapin FS, 2008, BIOSCIENCE, V58, P531, DOI 10.1641/B580609
   Crate SA, 2008, CURR ANTHROPOL, V49, P569, DOI 10.1086/529543
   D'Amore DV, 2006, GLOBAL CHANGE BIOL, V12, P524, DOI 10.1111/j.1365-2486.2006.01101.x
   DellaSala D.A., 2011, Temperate and boreal rainforests of the world: ecology and conservation, P1
   Devine-Wright P, 2009, J COMMUNITY APPL SOC, V19, P426, DOI 10.1002/casp.1004
   Doherty TJ, 2011, AM PSYCHOL, V66, P265, DOI 10.1037/a0023141
   FINGER M, 1994, J SOC ISSUES, V50, P141, DOI 10.1111/j.1540-4560.1994.tb02424.x
   Flint CG, 2006, FOREST ECOL MANAG, V227, P207, DOI 10.1016/j.foreco.2006.02.036
   Folke C, 2006, GLOBAL ENVIRON CHANG, V16, P253, DOI 10.1016/j.gloenvcha.2006.04.002
   Fonseca BA, 2011, EDUC PSYCHOL HANDB, P296
   Ford JD, 2010, GLOBAL ENVIRON CHANG, V20, P177, DOI 10.1016/j.gloenvcha.2009.10.008
   Fritze Jessica G, 2008, Int J Ment Health Syst, V2, P13, DOI 10.1186/1752-4458-2-13
   Gee K, 2010, ECOL COMPLEX, V7, P349, DOI 10.1016/j.ecocom.2010.02.008
   Glaser B., 1992, Basics of Grounded Theory Analysis
   Gonzalez L, 1998, ENVIRONMETRICS, V9, P53
   Gould RK, 2015, CONSERV BIOL, V29, P575, DOI 10.1111/cobi.12407
   Grothmann T, 2005, GLOBAL ENVIRON CHANG, V15, P199, DOI 10.1016/j.gloenvcha.2005.01.002
   Heimlich JE, 2008, ENVIRON EDUC RES, V14, P215, DOI 10.1080/13504620802148881
   Hennon PE, 2012, BIOSCIENCE, V62, P147, DOI 10.1525/bio.2012.62.2.8
   Kals E, 1999, ENVIRON BEHAV, V31, P178, DOI 10.1177/00139169921972056
   Kellert S., 1996, The value of life. biological diversity and human society
   Kellert S.R., 1997, Kinship to Mastery: Biophilia in human evolution and development
   Kellogg E.L., 1992, Coastal temperate rain forests: Ecological characteristics, status and distribution worldwide
   Kirsch S, 2001, CURR ANTHROPOL, V42, P167, DOI 10.1086/320006
   Klain SC, 2014, ECOL ECON, V107, P310, DOI 10.1016/j.ecolecon.2014.09.003
   Kollmuss A., 2012, Environmental Education Research, V8, P239
   Lakoff G, 2010, ENVIRON COMMUN, V4, P70, DOI 10.1080/17524030903529749
   Lambin EF, 2006, GLO CH IGBP, P1
   Lorenzoni I, 2007, GLOBAL ENVIRON CHANG, V17, P445, DOI 10.1016/j.gloenvcha.2007.01.004
   McArdle BH, 2001, ECOLOGY, V82, P290, DOI 10.1890/0012-9658(2001)082[0290:FMMTCD]2.0.CO;2
   Nie M., 2006, ENVIRON LAW, V36, P385
   O'Neill S, 2009, SCI COMMUN, V30, P355, DOI 10.1177/1075547008329201
   Ostrom E, 2009, SCIENCE, V325, P419, DOI 10.1126/science.1172133
   Otieno C, 2014, ENVIRON EDUC RES, V20, P612, DOI 10.1080/13504622.2013.833589
   R Core Team R, 2013, R: A language and environment for statistical computing
   Rajecki D.W., 1982, Attitudes Themes and Advances
   RAMSEY CE, 1976, J ENVIRON EDUC, V8, P10, DOI 10.1080/00958964.1976.9941552
   Reser JP, 2011, AM PSYCHOL, V66, P277, DOI 10.1037/a0023412
   Rogan R, 2005, J ENVIRON PSYCHOL, V25, P147, DOI 10.1016/j.jenvp.2005.03.001
   Rubinstein R.L., 1992, Place Attachment, P139, DOI [10.1007/978-1-4684-8753-4_7, DOI 10.1007/978-1-4684-8753-4_7]
   Russell R, 2013, ANNU REV ENV RESOUR, V38, P473, DOI 10.1146/annurev-environ-012312-110838
   Satterfield T, 2001, ENVIRON VALUE, V10, P331, DOI 10.3197/096327101129340868
   Scannell L, 2010, J ENVIRON PSYCHOL, V30, P1, DOI 10.1016/j.jenvp.2009.09.006
   Schaberg PG, 2011, FOREST ECOL MANAG, V262, P2142, DOI 10.1016/j.foreco.2011.08.004
   Schaberg PG, 2005, CAN J FOREST RES, V35, P2065, DOI 10.1139/X05-131
   Schultz P.W., 2002, PSYCHOL SUSTAINABLE, DOI [10.1007/978-1-4615-0995-0_4, DOI 10.1007/978-1-4615-0995-0_4]
   Schultz PW, 2004, J ENVIRON PSYCHOL, V24, P31, DOI 10.1016/S0272-4944(03)00022-7
   Schultz PW, 2001, J ENVIRON PSYCHOL, V21, P327
   Schultz PW, 2000, J SOC ISSUES, V56, P391, DOI 10.1111/0022-4537.00174
   Smit B, 2006, GLOBAL ENVIRON CHANG, V16, P282, DOI 10.1016/j.gloenvcha.2006.03.008
   Spittlehouse DL, 2005, FOREST CHRON, V81, P691, DOI 10.5558/tfc81691-5
   Stafford JM, 2000, THEOR APPL CLIMATOL, V67, P33, DOI 10.1007/s007040070014
   Stewart Hilary., 1984, Cedar: Tree of life to the Northwest Coast Indians
   Stokols Daniel., 1981, COGNITION SOC BEHAV, P441
   Sundblad EL, 2009, ENVIRON BEHAV, V41, P281, DOI 10.1177/0013916508314998
   Swim JK, 2011, AM PSYCHOL, V66, P241, DOI 10.1037/a0023220
   Trainor SF, 2009, POLAR RES, V28, P100, DOI 10.1111/j.1751-8369.2009.00101.x
   Turner BL, 2007, P NATL ACAD SCI USA, V104, P20666, DOI 10.1073/pnas.0704119104
   Uzzell DL, 2000, J ENVIRON PSYCHOL, V20, P307, DOI 10.1006/jevp.2000.0175
   Vaske J. J., 2001, The Journal of Environmental Education, V32, P16, DOI [10.1080/00958960109598658, DOI 10.1080/00958960109598658]
   Vaughan MB, 2014, J SUSTAIN TOUR, V22, P50, DOI 10.1080/09669582.2013.802326
   Williams D.R., 1989, P NRPA S LEIS RES
   Williams D.R., 1999, HUMAN DIMENSIONS ASS, P141
   Williams DR, 2003, FOREST SCI, V49, P830
   Wolf J, 2011, WIRES CLIM CHANGE, V2, P547, DOI 10.1002/wcc.120
NR 98
TC 27
Z9 31
U1 0
U2 34
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.
PY 2016
VL 21
IS 2
AR 40
DI 10.5751/ES-08464-210240
PG 26
WC Ecology; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA DR6ZF
UT WOS:000380049100037
OA Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Costantini, L
   Battilana, J
   Lamaj, F
   Fanizza, G
   Grando, MS
AF Costantini, Laura
   Battilana, Juri
   Lamaj, Flutura
   Fanizza, Girolamo
   Grando, Maria Stella
TI Berry and phenology-related traits in grapevine (<i>Vitis vinifera</i>
   L.):: From Quantitative Trait Loci to underlying genes
SO BMC PLANT BIOLOGY
LA English
DT Article
ID SEED DEVELOPMENT; LINKAGE MAPS; MICROSATELLITE REPEATS;
   GIBBERELLIC-ACID; GENOME LENGTH; IDENTIFICATION; SEQUENCE; FRUIT;
   SEEDLESSNESS; EXPRESSION
AB Background: The timing of grape ripening initiation, length of maturation period, berry size and seed content are target traits in viticulture. The availability of early and late ripening varieties is desirable for staggering harvest along growing season, expanding production towards periods when the fruit gets a higher value in the market and ensuring an optimal plant adaptation to climatic and geographic conditions. Berry size determines grape productivity; seedlessness is especially demanded in the table grape market and is negatively correlated to fruit size. These traits result from complex developmental processes modified by genetic, physiological and environmental factors. In order to elucidate their genetic determinism we carried out a quantitative analysis in a 163 individuals-F-1 segregating progeny obtained by crossing two table grape cultivars.
   Results: Molecular linkage maps covering most of the genome (2n = 38 for Vitis vinifera) were generated for each parent. Eighteen pairs of homologous groups were integrated into a consensus map spanning over 1426 cM with 341 markers (mainly microsatellite, AFLP and EST-derived markers) and an average map distance between loci of 4.2 cM. Segregating traits were evaluated in three growing seasons by recording flowering, veraison and ripening dates and by measuring berry size, seed number and weight. QTL (Quantitative Trait Loci) analysis was carried out based on single marker and interval mapping methods. QTLs were identified for all but one of the studied traits, a number of them steadily over more than one year. Clusters of QTLs for different characters were detected, suggesting linkage or pleiotropic effects of loci, as well as regions affecting specific traits. The most interesting QTLs were investigated at the gene level through a bioinformatic analysis of the underlying Pinot noir genomic sequence.
   Conclusion: Our results revealed novel insights into the genetic control of relevant grapevine features. They provide a basis for performing marker-assisted selection and testing the role of specific genes in trait variation.
C1 [Costantini, Laura; Battilana, Juri; Grando, Maria Stella] IASMA Res Ctr, Dept Genet & Mol Biol, I-38010 San Michele All Adige, TN, Italy.
   [Lamaj, Flutura; Fanizza, Girolamo] Univ Bari, DIBCA, I-70100 Bari, Italy.
C3 Fondazione Edmund Mach; Universita degli Studi di Bari Aldo Moro
RP Costantini, L (corresponding author), IASMA Res Ctr, Dept Genet & Mol Biol, Via E Mach 1, I-38010 San Michele All Adige, TN, Italy.
EM laura.costantini@iasma.it; juri.battilana@iasma.it; flutura_47@yahoo.it;
   fanizza@agr.uniba.it; stella.grando@iasma.it
RI ; Grando, Maria Stella/D-5448-2011
OI Costantini, Laura/0000-0001-6644-0912; Grando, Maria
   Stella/0000-0002-6889-1968
CR Adam-Blondon AF, 2004, THEOR APPL GENET, V109, P1017, DOI 10.1007/s00122-004-1704-y
   BATTILANA J, CANDIDATE GEN UNPUB
   Bendtsen JD, 2004, J MOL BIOL, V340, P783, DOI 10.1016/j.jmb.2004.05.028
   BENTAL Y, 1990, AM J ENOL VITICULT, V41, P142
   Bishop D.T., 1983, Statical analysis of DNA sequence data, P181
   Boss PK, 2006, FUNCT PLANT BIOL, V33, P31, DOI 10.1071/FP05191
   Boss PK, 2003, FUNCT PLANT BIOL, V30, P593, DOI 10.1071/FP02112
   Boss PK, 2002, NATURE, V416, P847, DOI 10.1038/416847a
   Boss PK, 2002, PLANT SCI, V162, P887, DOI 10.1016/S0168-9452(02)00034-1
   Boss PK, 2001, PLANT MOL BIOL, V45, P541, DOI 10.1023/A:1010634132156
   Bouquet A, 1996, VITIS, V35, P35
   Bowers JE, 1999, AM J ENOL VITICULT, V50, P243
   Bowers JE, 1996, GENOME, V39, P628, DOI 10.1139/g96-080
   Bowman JL, 2000, CURR OPIN PLANT BIOL, V3, P17, DOI 10.1016/S1369-5266(99)00035-7
   Cabezas JA, 2006, GENOME, V49, P1572, DOI 10.1139/G06-122
   Calonje M, 2004, PLANT PHYSIOL, V135, P1491, DOI 10.1104/pp.104.040832
   Carmona MJ, 2002, PLANT PHYSIOL, V130, P68, DOI 10.1104/pp.002428
   Cervera MT, 2001, GENETICS, V158, P787
   CHAKRAVARTI A, 1991, GENETICS, V128, P175
   Chaudhury AM, 1997, P NATL ACAD SCI USA, V94, P4223, DOI 10.1073/pnas.94.8.4223
   Chen QY, 1999, DEVELOPMENT, V126, P2715
   Chervin C, 2004, PLANT SCI, V167, P1301, DOI 10.1016/j.plantsci.2004.06.026
   CHURCHILL GA, 1994, GENETICS, V138, P963
   COOMBE BG, 1960, PLANT PHYSIOL, V35, P241, DOI 10.1104/pp.35.2.241
   Costantini L, 2007, AM J ENOL VITICULT, V58, P102
   Davies C, 1997, PLANT PHYSIOL, V115, P1155, DOI 10.1104/pp.115.3.1155
   Di Gaspero G, 2000, THEOR APPL GENET, V101, P301, DOI 10.1007/s001220051483
   Di Gaspero G, 2005, MOL BREEDING, V15, P11, DOI 10.1007/s11032-004-1362-4
   Doligez A, 2006, THEOR APPL GENET, V113, P369, DOI 10.1007/s00122-006-0295-1
   Doligez A, 2006, MOL BREEDING, V18, P109, DOI 10.1007/s11032-006-9016-3
   Doligez A, 2002, THEOR APPL GENET, V105, P780, DOI 10.1007/s00122-002-0951-z
   Doucleff M, 2004, THEOR APPL GENET, V109, P1178, DOI 10.1007/s00122-004-1728-3
   Duchêne E, 2005, AGRON SUSTAIN DEV, V25, P93, DOI 10.1051/agro:2004057
   Etienne C, 2002, THEOR APPL GENET, V105, P145, DOI 10.1007/s00122-001-0841-9
   Fanizza G, 2005, THEOR APPL GENET, V111, P658, DOI 10.1007/s00122-005-2016-6
   Fernandez L, 2006, PLANT PHYSIOL, V140, P537, DOI 10.1104/pp.105.067488
   Fernandez L, 2007, PLANT MOL BIOL, V63, P307, DOI 10.1007/s11103-006-9090-2
   Fischer BM, 2004, THEOR APPL GENET, V108, P501, DOI 10.1007/s00122-003-1445-3
   GENY L, 2005, ACTA HORTIC, V689, P243
   GERBER S, 1994, THEOR APPL GENET, V88, P289, DOI 10.1007/BF00223634
   Grando MS, 2003, THEOR APPL GENET, V106, P1213, DOI 10.1007/s00122-002-1170-3
   Hanania U, 2007, TRANSGENIC RES, V16, P515, DOI 10.1007/s11248-006-9044-0
   Hedden P, 1999, PLANT PHYSIOL, V119, P365, DOI 10.1104/pp.119.2.365
   HULBERT SH, 1988, GENETICS, V120, P947
   JACK T, 2004, PLANT CELL, P1
   Jaillon O, 2007, NATURE, V449, P463, DOI 10.1038/nature06148
   Joly D, 2004, PLANT SCI, V166, P1427, DOI 10.1016/j.plantsci.2003.12.041
   Jones CGL, 2006, J CANCER EDUC, V21, P26, DOI 10.1207/s15430154jce2101_9
   Carmona MJ, 2007, PLANT MOL BIOL, V63, P637, DOI 10.1007/s11103-006-9113-z
   KENDER W J, 1970, Hortscience, V5, P491
   Kimura PH, 1996, AM J ENOL VITICULT, V47, P152
   Kosambi DD, 1943, ANN EUGENIC, V12, P172, DOI 10.1111/j.1469-1809.1943.tb02321.x
   Kumar S, 2004, BRIEF BIOINFORM, V5, P150, DOI 10.1093/bib/5.2.150
   Kumaran MK, 2002, PLANT CELL, V14, P2761, DOI 10.1105/tpc.004911
   Lahogue F, 1998, THEOR APPL GENET, V97, P950, DOI 10.1007/s001220050976
   LANDER ES, 1989, GENETICS, V121, P185
   LANGE K, 1982, AM J HUM GENET, V34, P842
   Ledbetter C. A., 1989, Horticultural Reviews, V11, P159, DOI 10.1002/9781118060841.ch5
   LEDBETTER CA, 1990, J HORTIC SCI BIOTECH, V65, P269, DOI 10.1080/00221589.1990.11516056
   Lowe KM, 2006, THEOR APPL GENET, V112, P1582, DOI 10.1007/s00122-006-0264-8
   Mejía N, 2007, AM J ENOL VITICULT, V58, P499
   Merdinoglu D, 2005, MOL BREEDING, V15, P349, DOI 10.1007/s11032-004-7651-0
   Navarro C, 2004, DEVELOPMENT, V131, P3649, DOI 10.1242/dev.01205
   NITSCH JP, 1960, AM J BOT, V47, P566, DOI 10.2307/2439435
   Ohad N, 1999, PLANT CELL, V11, P407, DOI 10.1105/tpc.11.3.407
   Pellerone FI, 2001, VITIS, V40, P179
   Peng JR, 1997, GENE DEV, V11, P3194, DOI 10.1101/gad.11.23.3194
   Pérez FJ, 2000, AM J ENOL VITICULT, V51, P315
   Pflieger S, 2001, MOL BREEDING, V7, P275, DOI 10.1023/A:1011605013259
   Reynolds AG, 2006, AM J ENOL VITICULT, V57, P41
   Riaz S, 2004, THEOR APPL GENET, V108, P864, DOI 10.1007/s00122-003-1488-5
   Roux F, 2006, TRENDS PLANT SCI, V11, P375, DOI 10.1016/j.tplants.2006.06.006
   Salamov AA, 2000, GENOME RES, V10, P516, DOI 10.1101/gr.10.4.516
   Sawa S, 1999, PLANT CELL, V11, P69, DOI 10.1105/tpc.11.1.69
   Scott KD, 2000, THEOR APPL GENET, V100, P723, DOI 10.1007/s001220051344
   Sefc KM, 1999, GENOME, V42, P367, DOI 10.1139/gen-42-3-367
   Small I, 2004, PROTEOMICS, V4, P1581, DOI 10.1002/pmic.200300776
   Sreekantan L, 2006, FUNCT PLANT BIOL, V33, P1129, DOI 10.1071/FP06144
   SRINIVASAN C, 1978, PLANT PHYSIOL, V61, P127, DOI 10.1104/pp.61.1.127
   SUNG ZR, 1992, SCIENCE, V258, P1645, DOI 10.1126/science.258.5088.1645
   Symons GM, 2006, PLANT PHYSIOL, V140, P150, DOI 10.1104/pp.105.070706
   Terrier N, 2005, PLANTA, V222, P832, DOI 10.1007/s00425-005-0017-y
   THOMAS MR, 1993, THEOR APPL GENET, V86, P985, DOI 10.1007/BF00211051
   Thornsberry JM, 2001, NAT GENET, V28, P286, DOI 10.1038/90135
   Van Ooijen J., 2001, SOFTWARE CALCULATION
   van Ooijen JW., 2002, MapQTL 4.0: Software for the Calculation of QTL Positions on Genetic Maps
   Velasco R, 2007, PLOS ONE, V2, DOI 10.1371/journal.pone.0001326
   Voorrips RE, 2002, J HERED, V93, P77, DOI 10.1093/jhered/93.1.77
   VOS P, 1995, NUCLEIC ACIDS RES, V23, P4407, DOI 10.1093/nar/23.21.4407
   Waters Daniel L. E., 2005, Functional & Integrative Genomics, V5, P40, DOI 10.1007/s10142-004-0124-z
   WEAVER RJ, 1953, P AM SOC HORTIC SCI, V61, P135
NR 91
TC 150
Z9 171
U1 3
U2 63
PU BMC
PI LONDON
PA CAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND
SN 1471-2229
J9 BMC PLANT BIOL
JI BMC Plant Biol.
PD APR 17
PY 2008
VL 8
AR 38
DI 10.1186/1471-2229-8-38
PG 17
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA 306AS
UT WOS:000256219800001
PM 18419811
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Ibrahim, HM
   Alghamdi, AG
   Aly, AA
AF Ibrahim, Hesham M.
   Alghamdi, Abdulaziz G.
   Aly, Anwar A.
TI Assessing Drought Patterns in Al-Baha: Implications for Water Resources
   and Climate Adaptation
SO SUSTAINABILITY
LA English
DT Article
DE climate change; drought indices; temperature increase; rainfall
   variability; water scarcity; future projections; drought management;
   Al-Baha; arid regions
ID SAUDI-ARABIA; RAINFALL; IMPACTS
AB Due to growing water demands and changing hydro-meteorological variables brought on by climate change, drought is becoming an increasingly serious climate concern. The Al-Baha region of Saudi Arabia is the subject of this study because it is susceptible to both agricultural and meteorological droughts. This study investigates how climate change affects patterns of drought in Al-Baha by analyzing four drought indices (Agricultural Standardized Precipitation Index (aSPI), the Standardized Precipitation Index (SPI), the Rainfall Deficiency Index (RDI), and the Effective Reconnaissance Drought Index (eRDI)) for the years 1991-2022. Analysis of rainfall data was carried out to classify drought events according to their duration, frequency, and severity. Results showed that severe droughts occurred in 2009, 2010, 2012, 2016, and 2022, with 2010 being the worst year. Results also indicated a notable decrease in precipitation, which has resulted in extended dry spells. Several indices indicate that this tendency has significant ramifications for agriculture, particularly in areas where farming is a major economic activity. In addition, the possible occurrence of hydrological drought was also observed based on the negative values for the Reservoir Storage Index (RSI) in Al-Baha. Projections for the future under two Representative Concentration Pathways (RCPs) showed notable variations in temperature and precipitation. Both the RCP4.5 (low emission) and the RCP8.5 (high emission) projection scenarios indicate that drought conditions will likely worsen further. Depending on the emission scenario, it is projected to show a temperature increase of 1-2 degrees C, whereas the variability in precipitation projections indicates significant uncertainty, with a reduction change in the range of 1.2-27% between 2050 and 2100. The findings highlight the urgent need for proactive adaptation strategies, effective water resource management, and the development of sophisticated drought prediction tools. Addressing these challenges is crucial for sustaining agriculture and managing water scarcity in Saudi Arabia in the face of increasing drought risk.
C1 [Ibrahim, Hesham M.; Alghamdi, Abdulaziz G.] King Saud Univ, Coll Food & Agr Sci, Dept Soil Sci, POB 2460, Riyadh 11451, Saudi Arabia.
   [Ibrahim, Hesham M.] Suez Canal Univ, Fac Agr, Dept Soils & Water, Ismailia 41522, Egypt.
   [Aly, Anwar A.] Alexandria Univ, Fac Agr, Soil & Water Sci Dept, Alexandria 21545, Egypt.
C3 King Saud University; Egyptian Knowledge Bank (EKB); Suez Canal
   University; Egyptian Knowledge Bank (EKB); Alexandria University
RP Ibrahim, HM (corresponding author), King Saud Univ, Coll Food & Agr Sci, Dept Soil Sci, POB 2460, Riyadh 11451, Saudi Arabia.; Ibrahim, HM (corresponding author), Suez Canal Univ, Fac Agr, Dept Soils & Water, Ismailia 41522, Egypt.
EM habdou@ksu.edu.sa; agghamdi@ksu.edu.sa; aaaly@alexu.edu.eg
RI Ibrahim, Hesham/AAK-8589-2020
FU National Plan for Science, Technology and Innovation (MAARIFAH), King
   Abdulaziz City for Science and Technology, Kingdom of Saudi Arabia; 
   [2-17-04-001-0025]
FX This project was funded by the National Plan for Science, Technology and
   Innovation (MAARIFAH), King Abdulaziz City for Science and Technology,
   Kingdom of Saudi Arabia, Award Number (2-17-04-001-0025).
CR Adnan S, 2015, J METEOROL RES-PRC, V29, P837, DOI 10.1007/s13351-015-4113-z
   Al-Barakah FN, 2020, WATER RESOUR+, V47, P877, DOI 10.1134/S0097807820050073
   Al-Taher A. A., 1994, GEOJOURNAL, V33, P411, DOI [10.1007/BF00806424, DOI 10.1007/BF00806424]
   Alghamdi AG, 2023, ENVIRON EARTH SCI, V82, DOI 10.1007/s12665-022-10731-z
   Alghamdi AG, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su142013275
   Almazroui M, 2014, INT J CLIMATOL, V34, P808, DOI 10.1002/joc.3722
   Alotaibi BA, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su151310648
   Arnold JG, 1998, J AM WATER RESOUR AS, V34, P73, DOI 10.1111/j.1752-1688.1998.tb05961.x
   Athar H, 2015, ATMOS SCI LETT, V16, P373, DOI 10.1002/asl2.570
   Awasthi A, 2023, FRONT ENV SCI-SWITZ, V11, DOI 10.3389/fenvs.2023.1264757
   Boretti A, 2019, NPJ CLEAN WATER, V2, DOI 10.1038/s41545-019-0039-9
   DeNicola E, 2015, ANN GLOB HEALTH, V81, P342, DOI 10.1016/j.aogh.2015.08.005
   Edwards D., 1997, Characteristics of 20th century drought in the United States at multiple time scales, P1
   FAO, 2020, The State of Food and Agriculture 2020, DOI [10.4060/cb1447en, DOI 10.4060/CB1447EN]
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Hag-elsafi S, 2016, WEATHER, V71, P262, DOI 10.1002/wea.2783
   Hasanean H, 2015, CLIMATE, V3, P578, DOI 10.3390/cli3030578
   Herceg A, 2019, J HYDROL HYDROMECH, V67, P384, DOI 10.2478/johh-2019-0017
   Huntley B.J., 2023, Ecology of Angola, DOI [10.1007/978-3-031-18923-45, DOI 10.1007/978-3-031-18923-45]
   Kummerow C, 2000, J APPL METEOROL, V39, P1965, DOI 10.1175/1520-0450(2001)040<1965:TSOTTR>2.0.CO;2
   Leng GY, 2015, GLOBAL PLANET CHANGE, V126, P23, DOI 10.1016/j.gloplacha.2015.01.003
   [Masson-Delmotte IPCC. IPCC.], 2018, Global Warming of 1.5C
   MCKEE TB, 1993, P 8 C APPL CLIM AN C
   Mohammed A., 2011, Int. J. Water Resour. Arid Environ, V1, P65
   Oliver J.E., 2005, Encyclopedia of world climatology
   Ouko KO, 2023, COGENT SOC SCI, V9, DOI 10.1080/23311886.2023.2173716
   Pattnayak KC, 2023, EARTH SPACE SCI, V10, DOI 10.1029/2022EA002671
   Piao SL, 2010, NATURE, V467, P43, DOI 10.1038/nature09364
   Rojas O, 2020, WEATHER CLIM EXTREME, V27, DOI 10.1016/j.wace.2018.09.001
   Saeed S, 2019, CLIM DYNAM, V53, P5253, DOI 10.1007/s00382-019-04862-6
   Shiau JT, 2003, WATER RESOUR MANAG, V17, P463, DOI 10.1023/B:WARM.0000004958.93250.8a
   Smakhtin VU, 2007, ENVIRON MODELL SOFTW, V22, P880, DOI 10.1016/j.envsoft.2006.05.013
   Stocker T., 2014, CLIMATE CHANGE 2013, DOI DOI 10.1017/CBO9781107415324.024
   Tigkas D., 2013, P 8 INT C EWRA WAT R
   Tigkas D, 2019, THEOR APPL CLIMATOL, V135, P1435, DOI 10.1007/s00704-018-2451-3
   Tigkas D, 2015, EARTH SCI INFORM, V8, P697, DOI 10.1007/s12145-014-0178-y
   Treut H.Le., 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 (IPCC)
   Tsakiris G, 2007, WATER RESOUR MANAG, V21, P821, DOI 10.1007/s11269-006-9105-4
   UNESCO, 2020, United Nations World Water Development Report 2020: Water and Climate Change
   UNESCO HerEducationOurFuture, Global Education Monitoring Report 2020
   Vicente-Serrano SM, 2010, J CLIMATE, V23, P1696, DOI 10.1175/2009JCLI2909.1
   Wang B, 2023, NAT CLIM CHANGE, DOI 10.1038/s41558-023-01801-6
   Wolf J, 2023, LANCET, V401, P2060, DOI 10.1016/S0140-6736(23)00458-0
   World Bank, 2023, Background Paper Water Scarcity and Droughts
   Wyss D., 2022, Afr. J. Environ. Sci. Technol, V16, P173, DOI [10.5897/AJEST2022.3096, DOI 10.5897/AJEST2022.3096]
   Zargar A, 2011, ENVIRON REV, V19, P333, DOI [10.1139/A11-013, 10.1139/a11-013]
NR 46
TC 0
Z9 0
U1 0
U2 0
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD NOV
PY 2024
VL 16
IS 22
AR 9882
DI 10.3390/su16229882
PG 26
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 N7M2T
UT WOS:001366127100001
OA gold
DA 2025-01-10
ER

PT J
AU Weng, AF
   Liu, QY
   Lin, YY
   Nizamani, MM
   Wen, LS
   Zhou, YR
   Wang, HX
   Li, BY
AF Weng, Aifang
   Liu, Qunyue
   Lin, Yuying
   Nizamani, Mir Muhammad
   Wen, Linsheng
   Zhou, Yunrui
   Wang, Hongxin
   Li, Baoyin
TI Dynamic conservation strategies for protected areas of Fujian Province:
   From integrated perspective of the adaptability of habitat and carbon
   storage to climate
SO ECOLOGICAL INDICATORS
LA English
DT Article
DE Protected areas; Habitat quality; Carbon storage; Dynamic conservation;
   Climate adaptation
ID LAND-USE; PRIORITY AREAS; CONNECTIVITY; SIMULATION; QUALITY; CHINA;
   SCENARIOS; DRIVEN; SET
AB Traditional protected areas (PAs) with fixed boundaries are insufficient in the face of global climate change, undermining biodiversity conservation and climate impact mitigation. Fujian Province, a biodiversity hotspot in China, requires dynamic conservation strategies to maintain habitat quality (HQ) and carbon storage (CS). This research introduces a novel framework that integrates land-use simulation and ecosystem service valuation models to address conservation challenges under varying climate scenarios. We employ the System Dynamics (SD), the Patch-generating Land Use Simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to explore how future climate scenarios might alter land use, HQ, and CS, and determines the conservation priorities for Fujian Province by 2050 based on HQ, CS capacity, and a future vision for protection. Findings indicate: (1) Under SSP1-2.6, Fujian Province exhibits an increased demand for forests, grasslands, and water resources, while SSP2-4.5 and SSP5-8.5 predict an elevated demand for urban land, extending into inland areas. (2) In SSP1-2.6, HQ and CS are expected to improve, with average HQ projected to rise to 0.71 and CS to 15.63 Mg/ha by 2050. Conversely, under SSP5-8.5, HQ is anticipated to decline to 0.66, and CS to 15.14 Mg/ha. SSP2-4.5 shows moderate levels, with slight decreases in HQ to 0.69 and CS to 15.34 Mg/ha due to moderate urban expansion. Nature reserves demonstrate the highest potential, while national parks remain stable and ocean parks perform poorly. (3) Hotspots are primarily located in the western Wuyishan and central Daiyun mountain ranges. Conservation targets are recommended at 15%, 30%, and 43 % of Fujian Province's area for 2030, 2040, and 2050, respectively. This research provides a framework for enhancing protected areas, empowering governments to advance biodiversity conservation and achieve carbon neutrality.
C1 [Weng, Aifang; Lin, Yuying; Wen, Linsheng; Zhou, Yunrui; Li, Baoyin] Fujian Normal Univ, Coll Geog Sci, Fuzhou 350117, Peoples R China.
   [Weng, Aifang; Lin, Yuying; Wen, Linsheng; Zhou, Yunrui; Li, Baoyin] Fujian Normal Univ, Coll Carbon Neutral Future Technol, Fuzhou 350117, Peoples R China.
   [Weng, Aifang; Lin, Yuying; Wen, Linsheng; Zhou, Yunrui; Li, Baoyin] Fujian Normal Univ, State Key Lab Subtrop Mt Ecol, Minist Sci & Technol & Fujian Prov, Fuzhou 350117, Peoples R China.
   [Liu, Qunyue] Fujian Univ Technol, Coll Architecture & Urban Planning, Fuzhou 350118, Peoples R China.
   [Lin, Yuying] Fujian Normal Univ, Postdoctoral Res Stn Ecol, Fuzhou 350117, Peoples R China.
   [Lin, Yuying] Fujian Normal Univ, Sch Culture Tourism & Publ Adm, Fuzhou 350117, Peoples R China.
   [Nizamani, Mir Muhammad] Guizhou Univ, Coll Agr, Dept Plant Pathol, Guiyang 550025, Peoples R China.
   [Wang, Hongxin] Sanya Univ, Zhai Mingguo Academician Work Stn, Sanya 572000, Peoples R China.
   [Wang, Hongxin] Sanya Univ, New Liberal Arts Res & Dev Divison, Sanya 572000, Peoples R China.
C3 Fujian Normal University; Fujian Normal University; Fujian Normal
   University; Fujian University of Technology; Fujian Normal University;
   Fujian Normal University; Guizhou University; University of Sanya;
   University of Sanya
RP Lin, YY; Li, BY (corresponding author), Fujian Normal Univ, Coll Geog Sci, Fuzhou 350117, Peoples R China.; Lin, YY; Li, BY (corresponding author), Fujian Normal Univ, Coll Carbon Neutral Future Technol, Fuzhou 350117, Peoples R China.
EM linyuying2019@fjnu.edu.cn; liby@fjnu.edu.cn
FU Natural Science Foundation of Fujian Province [2023J01514]; Major
   Programs of the National Social Science Foundation of China
   [2021MZD024]; National Natural Science Foundation of China [41901221];
   Science and Technology Project of Fujian Forestry Bureau [SC-259]
FX The research was supported by the Natural Science Foundation of Fujian
   Province (2023J01514) , the Major Programs of the National Social
   Science Foundation of China (2021MZD024) , the National Natural Science
   Foundation of China (41901221) , and the Science and Technology Project
   of Fujian Forestry Bureau (SC-259) . Finally, we would like to thank the
   anonymous reviewers and the editors for their helpful comments that
   improved the manuscript substantially.
CR Asamoah EF, 2022, NAT CLIM CHANGE, V12, P593, DOI 10.1038/s41558-022-01363-z
   Bai Y, 2021, ONE EARTH, V4, P1491, DOI 10.1016/j.oneear.2021.09.010
   Belote RT, 2020, BIOSCIENCE, V70, P122, DOI 10.1093/biosci/biz148
   Bhola N, 2021, CONSERV BIOL, V35, P168, DOI 10.1111/cobi.13509
   Carroll C, 2021, GLOBAL CHANGE BIOL, V27, P3395, DOI 10.1111/gcb.15645
   Carroll C, 2018, GLOBAL CHANGE BIOL, V24, P5318, DOI 10.1111/gcb.14373
   Carvalho SB, 2011, BIOL CONSERV, V144, P2020, DOI 10.1016/j.biocon.2011.04.024
   Chauvenet ALM, 2020, ONE EARTH, V2, P479, DOI 10.1016/j.oneear.2020.04.013
   Chen X.F., 2018, Sci. Geogr. Sin., V29, P540
   Chen YD, 2020, SCI DATA, V7, DOI 10.1038/s41597-020-0421-y
   Chen YH, 2009, CONSERV BIOL, V23, P537, DOI 10.1111/j.1523-1739.2008.01084.x
   Chen ZZ, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13132621
   Chuai X.W., 2011, Resour. Sci., V33, P1930
   D'Aloia CC, 2019, FRONT ECOL EVOL, V7, DOI 10.3389/fevo.2019.00027
   Dai LM, 2019, J FORESTRY RES, V30, P2227, DOI 10.1007/s11676-018-0771-x
   Deng WJ, 2020, ECOL ENG, V153, DOI 10.1016/j.ecoleng.2020.105904
   Dinerstein E, 2020, SCI ADV, V6, DOI 10.1126/sciadv.abb2824
   Dobrowski SZ, 2021, COMMUN EARTH ENVIRON, V2, DOI 10.1038/s43247-021-00270-z
   Dobrowski SZ, 2016, NAT COMMUN, V7, DOI 10.1038/ncomms12349
   Fastre C, 2021, ONE EARTH, V4, P1635, DOI 10.1016/j.oneear.2021.10.014
   Feng CT, 2021, SCI TOTAL ENVIRON, V764, DOI 10.1016/j.scitotenv.2020.142895
   García FC, 2018, P NATL ACAD SCI USA, V115, P10989, DOI 10.1073/pnas.1805518115
   Gomes E, 2021, ENVIRON RES, V197, DOI 10.1016/j.envres.2021.111101
   Gotama R, 2024, ECOL INDIC, V160, DOI 10.1016/j.ecolind.2024.111683
   Griscom BW, 2017, P NATL ACAD SCI USA, V114, P11645, DOI 10.1073/pnas.1710465114
   Guo X, 2024, ENVIRON IMPACT ASSES, V104, DOI 10.1016/j.eiar.2023.107357
   He YT, 2022, LAND-BASEL, V11, DOI 10.3390/land11060858
   Hu WJ, 2020, FOREST ECOL MANAG, V478, DOI 10.1016/j.foreco.2020.118517
   Hu Y, 2024, ECOL INDIC, V158, DOI 10.1016/j.ecolind.2023.111525
   Huang JL, 2020, LAND USE POLICY, V97, DOI 10.1016/j.landusepol.2020.104772
   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, P22
   Iwamura T, 2013, GLOBAL ENVIRON CHANG, V23, P1277, DOI 10.1016/j.gloenvcha.2013.07.016
   Jung M, 2021, NAT ECOL EVOL, V5, P1499, DOI 10.1038/s41559-021-01528-7
   Lauf S, 2012, ENVIRON MODELL SOFTW, V27-28, P71, DOI 10.1016/j.envsoft.2011.09.005
   Lei JR, 2022, ECOL INDIC, V145, DOI 10.1016/j.ecolind.2022.109707
   Li DL, 2018, GLOBAL CHANGE BIOL, V24, P4095, DOI 10.1111/gcb.14327
   Li JY, 2021, ECOL INDIC, V129, DOI 10.1016/j.ecolind.2021.107936
   Li JX, 2023, LAND-BASEL, V12, DOI 10.3390/land12081536
   Li MY, 2023, LAND-BASEL, V12, DOI 10.3390/land12020399
   Li M, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14053086
   Li Sheng-peng, 2020, Yingyong Shengtai Xuebao, V31, P4080, DOI 10.13287/j.1001-9332.202012.019
   Li SP, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14164111
   Li W., 2023, Atmosphere, V14
   Li YJ, 2017, J GEOGR SCI, V27, P681, DOI 10.1007/s11442-017-1400-x
   Liang J, 2018, SCI TOTAL ENVIRON, V626, P22, DOI 10.1016/j.scitotenv.2018.01.086
   Liang X, 2021, COMPUT ENVIRON URBAN, V85, DOI 10.1016/j.compenvurbsys.2020.101569
   Liao WL, 2020, SCI BULL, V65, P1935, DOI 10.1016/j.scib.2020.07.014
   Lin WB, 2020, SCI TOTAL ENVIRON, V739, DOI 10.1016/j.scitotenv.2020.139899
   Lin XJ, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su142113757
   Lin YP, 2017, ENVIRON MODELL SOFTW, V90, P126, DOI 10.1016/j.envsoft.2017.01.003
   Littlefield CE, 2019, FRONT ECOL ENVIRON, V17, P270, DOI 10.1002/fee.2043
   Liu LL, 2019, ECOL INDIC, V107, DOI 10.1016/j.ecolind.2019.105566
   Liu XP, 2017, LANDSCAPE URBAN PLAN, V168, P94, DOI 10.1016/j.landurbplan.2017.09.019
   Locke H., 2013, George Wright Forum, V31, P359
   Ma ZY, 2023, LAND-BASEL, V12, DOI 10.3390/land12020297
   McGuire JL, 2016, P NATL ACAD SCI USA, V113, P7195, DOI 10.1073/pnas.1602817113
   Molotoks A, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0189
   Murakami D, 2021, FRONT BUILT ENVIRON, V7, DOI 10.3389/fbuil.2021.760306
   Oldekop JA, 2016, CONSERV BIOL, V30, P133, DOI 10.1111/cobi.12568
   Pecl GT, 2017, SCIENCE, V355, DOI 10.1126/science.aai9214
   Pei HW, 2022, SCI TOTAL ENVIRON, V809, DOI 10.1016/j.scitotenv.2021.151153
   Pettorelli N, 2021, J APPL ECOL, V58, P2384, DOI 10.1111/1365-2664.13985
   Pires APF, 2016, ECOLOGY, V97, P2750, DOI 10.1002/ecy.1501
   Polasky S, 2011, ENVIRON RESOUR ECON, V48, P219, DOI 10.1007/s10640-010-9407-0
   Pryce B., 2006, OKANAGAN ECOREGIONAL, V1
   Pu Y., 2013, FOR RESOUR MANAG, V3, P119, DOI [10.13466/j.cnki.lyzygl.2013.03.025, DOI 10.13466/J.CNKI.LYZYGL.2013.03.025]
   Raulino JBS, 2021, HYDROLOG SCI J, V66, P1321, DOI 10.1080/02626667.2021.1933491
   Ren DF, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su15054500
   Ren Y, 2011, PLANT SOIL, V345, P125, DOI 10.1007/s11104-011-0766-2
   Reside AE, 2018, BIODIVERS CONSERV, V27, P1, DOI 10.1007/s10531-017-1442-5
   Rodríguez SL, 2024, AGR ECOSYST ENVIRON, V360, DOI 10.1016/j.agee.2023.108795
   Song SX, 2020, ECOL INDIC, V112, DOI 10.1016/j.ecolind.2020.106071
   Soto-Navarro C, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0128
   Strassburg BBN, 2020, NATURE, V586, P724, DOI 10.1038/s41586-020-2784-9
   Su K, 2020, ECOL INDIC, V108, DOI 10.1016/j.ecolind.2019.105752
   Sun Fang-hu, 2023, Journal of Soil and Water Conservation, V37, P151, DOI 10.13870/j.cnki.stbcxb.2023.01.021
   Tan JB, 2019, ECOL MODEL, V410, DOI 10.1016/j.ecolmodel.2019.108783
   Tang F., 2021, China. Plos One, V16
   Tang F, 2020, ECOL INDIC, V117, DOI 10.1016/j.ecolind.2020.106719
   Tian J, 2023, FRONT ECOL EVOL, V11, DOI 10.3389/fevo.2023.1074410
   Tian L, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14102330
   Wan Daiji, 2023, Int J Environ Res Public Health, V20, DOI 10.3390/ijerph20043691
   Wang F, 2021, BIOL CONSERV, V253, DOI 10.1016/j.biocon.2020.108913
   Wang L, 2021, CONSERV BIOL, V35, P1797, DOI 10.1111/cobi.13733
   Wang R, 2011, ENERG POLICY, V39, P2740, DOI 10.1016/j.enpol.2011.02.043
   Wang Wei, 2021, Biodiversity Science, V29, P133, DOI 10.17520/biods.2020070
   Wang ZY, 2022, ECOL INDIC, V134, DOI 10.1016/j.ecolind.2021.108499
   Watson JEM, 2020, NATURE, V578, P360, DOI 10.1038/d41586-020-00446-1
   Wei H, 2021, CATENA, V202, DOI 10.1016/j.catena.2021.105256
   Wilson E.O., 2016, Half-Earth: Our Planet's Fight for Life
   Wu H, 2023, BIOL CONSERV, V284, DOI 10.1016/j.biocon.2023.110213
   Xu C, 2022, ECOL INDIC, V137, DOI 10.1016/j.ecolind.2022.108757
   Xu L., 2019, SUSTAINABILITY-BASEL, V11, DOI [10.3390/su11133513, DOI 10.3390/su11133513]
   Yang J, 2021, EARTH SYST SCI DATA, V13, P3907, DOI 10.5194/essd-13-3907-2021
   Yang R, 2020, SCI ADV, V6, DOI 10.1126/sciadv.abc3436
   Yu B, 2023, EXPERT SYST APPL, V233, DOI 10.1016/j.eswa.2023.120999
   Yue SJ, 2023, LAND-BASEL, V12, DOI 10.3390/land12091668
   Yun XB, 2021, SCI TOTAL ENVIRON, V785, DOI 10.1016/j.scitotenv.2021.147322
   Zhang MG, 2012, BIOL CONSERV, V153, P257, DOI 10.1016/j.biocon.2012.04.023
   Zhang SQ, 2022, SCI TOTAL ENVIRON, V833, DOI 10.1016/j.scitotenv.2022.155238
   Zhang SH, 2022, ECOL INDIC, V136, DOI 10.1016/j.ecolind.2022.108642
   Zhang T., 2017, INT C GREEN EN SUST
   Zhao BX, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14095303
   Zhao JS, 2016, ENVIRON EARTH SCI, V75, DOI 10.1007/s12665-015-5165-1
   Zheng HL, 2022, SCI REP-UK, V12, DOI 10.1038/s41598-022-19493-x
   Zhou J, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14053065
   Zhou L, 2020, SUSTAIN CITIES SOC, V55, DOI 10.1016/j.scs.2020.102045
   Zhu CM, 2020, ECOL INDIC, V117, DOI 10.1016/j.ecolind.2020.106654
   Zhu L, 2021, SCI ADV, V7, DOI 10.1126/sciadv.abe4261
NR 109
TC 1
Z9 1
U1 12
U2 12
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 1470-160X
EI 1872-7034
J9 ECOL INDIC
JI Ecol. Indic.
PD NOV
PY 2024
VL 168
AR 112773
DI 10.1016/j.ecolind.2024.112773
EA NOV 2024
PG 16
WC Biodiversity Conservation; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA L3O6Y
UT WOS:001349852700001
OA gold
DA 2025-01-10
ER

PT J
AU Han, WQ
   Zheng, JH
   Guan, JY
   Liu, YJ
   Liu, L
   Han, CQ
   Li, JH
   Li, CR
   Tian, RK
   Mao, XR
AF Han, Wanqiang
   Zheng, Jianghua
   Guan, Jingyun
   Liu, Yujia
   Liu, Liang
   Han, Chuqiao
   Li, Jianhao
   Li, Congren
   Tian, Ruikang
   Mao, Xurui
TI A greater negative impact of future climate change on vegetation in
   Central Asia: Evidence from trajectory/pattern analysis
SO ENVIRONMENTAL RESEARCH
LA English
DT Article
DE Central asia; Climate change; Vegetation estimation; Change trajectory;
   Machine learning
ID WATER-USE EFFICIENCY; DROUGHT; SHIFTS; PRODUCTIVITY; ADAPTATION; TREND
AB In the context of global warming, vegetation changes exhibit various patterns, yet previous studies have focused primarily on monotonic changes, often overlooking the complexity and diversity of multiple change processes. Therefore, it is crucial to further explore vegetation dynamics and diverse change trajectories in this region under future climate scenarios to obtain a more comprehensive understanding of local ecosystem evolution. In this study, we established an integrated machine learning prediction framework and a vegetation change trajectory recognition framework to predict the dynamics of vegetation in Central Asia under future climate change scenarios and identify its change trajectories, thus revealing the potential impacts of future climate change on vegetation in the region. The findings suggest that various future climate scenarios will negatively affect most vegetation in Central Asia, with vegetation change intensity increasing with increasing emission trajectories. Analyses of different time scales and trend variations consistently revealed more pronounced downward trends. Vegetation change trajectory analysis revealed that most vegetation has undergone nonlinear and dramatic changes, with negative changes outnumbering positive changes and curve changes outnumbering abrupt changes. Under the highest emission scenario (SSP5-8.5), the abrupt vegetation changes and curve changes are 1.7 times and 1.3 times greater, respectively, than those under the SSP1-2.6 scenario. When transitioning from lower emission pathways (SSP1-2.6, SSP2-4.5) to higher emission pathways (SSP3-7.0, SSP5-8.5), the vegetation change trajectories shift from neutral and negative curve changes to abrupt negative changes. Across climate scenarios, the key climate factors influencing vegetation changes are mostly evapotranspiration and soil moisture, with temperature and relative humidity exerting relatively minor effects. Our study reveals the negative response of vegetation in Central Asia to climate change from the perspective of vegetation dynamics and change trajectories, providing a scientific basis for the development of effective ecological protection and climate adaptation strategies.
C1 [Han, Wanqiang; Zheng, Jianghua; Liu, Yujia; Liu, Liang; Han, Chuqiao; Li, Jianhao; Li, Congren; Tian, Ruikang; Mao, Xurui] Xinjiang Univ, Coll Geog & Remote Sensing Sci, Urumqi 830046, Peoples R China.
   [Han, Wanqiang; Zheng, Jianghua; Guan, Jingyun; Liu, Yujia; Liu, Liang; Han, Chuqiao; Li, Jianhao; Li, Congren; Tian, Ruikang; Mao, Xurui] Xinjiang Univ, Key Lab Oasis Ecol, Urumqi 830046, Peoples R China.
   [Guan, Jingyun] Xinjiang Univ Finance & Econ, Coll Tourism, Urumqi 830012, Peoples R China.
C3 Xinjiang University; Xinjiang University; Xinjiang University of Finance
   & Economics
RP Zheng, JH (corresponding author), Xinjiang Univ, Coll Geog & Remote Sensing Sci, Urumqi 830046, Peoples R China.
EM zheng.jianghua@xju.edu.cn
RI Zhang, Yu/JQW-8689-2023; Li, JianHao/KVY-6212-2024; Tian,
   Ruikang/KQU-3788-2024
FU Key Labora-tory of Xinjiang Science and Technology Department
   [2022D04009]
FX We acknowledge the financial support provided by the Key Labora-tory of
   Xinjiang Science and Technology Department (Grant No. 2022D04009) . We
   also appreciate the assistance of Dr. Miguel Berdugo, a postdoctoral
   researcher in ecology at ETH Zurich, in the vegetation trajectory
   analysis.
CR Abbass K, 2022, ENVIRON SCI POLLUT R, V29, P42539, DOI 10.1007/s11356-022-19718-6
   Abel C, 2021, NAT SUSTAIN, V4, P25, DOI 10.1038/s41893-020-00597-z
   Ahlström A, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/5/054019
   Berdugo M, 2022, P NATL ACAD SCI USA, V119, DOI 10.1073/pnas.2123393119
   Berdugo M, 2020, SCIENCE, V367, P787, DOI 10.1126/science.aay5958
   Bernardino PN, 2020, GLOBAL ECOL BIOGEOGR, V29, P1230, DOI 10.1111/geb.13099
   Brugere L, 2023, FOREST ECOL MANAG, V539, DOI 10.1016/j.foreco.2023.120972
   Chen JL, 2023, SCI TOTAL ENVIRON, V895, DOI 10.1016/j.scitotenv.2023.165071
   Chen T, 2019, SCI TOTAL ENVIRON, V653, P1311, DOI 10.1016/j.scitotenv.2018.11.058
   Chen X, 2024, GLOB ECOL CONSERV, V49, DOI 10.1016/j.gecco.2023.e02791
   Chen ZF, 2023, GLOBAL CHANGE BIOL, V29, P1628, DOI 10.1111/gcb.16561
   Coppi A, 2022, PLANT SOIL, V471, P123, DOI 10.1007/s11104-021-05179-2
   de Jong R, 2012, GLOBAL CHANGE BIOL, V18, P642, DOI 10.1111/j.1365-2486.2011.02578.x
   del Campo AD, 2020, FOREST ECOL MANAG, V467, DOI 10.1016/j.foreco.2020.118156
   Dixit S, 2023, Ecological Risk and Security Research, V1, P49, DOI [10.59429/ersr.v1i1.49, DOI 10.59429/ERSR.V1I1.49]
   Fayech D, 2021, MODEL EARTH SYST ENV, V7, P1667, DOI 10.1007/s40808-020-00896-6
   Fazlioglu F, 2021, CLIMATIC CHANGE, V164, DOI 10.1007/s10584-021-02996-3
   Filatova T, 2016, ENVIRON MODELL SOFTW, V75, P333, DOI 10.1016/j.envsoft.2015.04.003
   Fischer EM, 2021, NAT CLIM CHANGE, V11, P689, DOI 10.1038/s41558-021-01092-9
   Gao Jb, 2017, EARTHS FUTURE, V5, P679, DOI 10.1002/2017EF000573
   Gonsamo A, 2021, GLOBAL CHANGE BIOL, V27, P3336, DOI 10.1111/gcb.15658
   Guan JY, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13224651
   Hasegawa T, 2021, NAT FOOD, V2, P587, DOI 10.1038/s43016-021-00335-4
   He L, 2023, SCI TOTAL ENVIRON, V858, DOI 10.1016/j.scitotenv.2022.159942
   Higgins SI, 2023, NAT GEOSCI, V16, P147, DOI 10.1038/s41561-022-01114-x
   Horion S, 2019, LAND DEGRAD DEV, V30, P951, DOI 10.1002/ldr.3282
   Horion S, 2016, GLOBAL CHANGE BIOL, V22, P2801, DOI 10.1111/gcb.13267
   Hossain ML, 2021, GLOB ECOL CONSERV, V30, DOI 10.1016/j.gecco.2021.e01768
   Huang SZ, 2017, WATER RESOUR MANAG, V31, P3667, DOI 10.1007/s11269-017-1692-8
   Ilyas M, 2021, J PLANT GROWTH REGUL, V40, P926, DOI 10.1007/s00344-020-10174-5
   Jeong SJ, 2011, GLOBAL CHANGE BIOL, V17, P2385, DOI 10.1111/j.1365-2486.2011.02397.x
   Jiang J, 2023, NAT GEOSCI, V16, P154, DOI 10.1038/s41561-022-01111-0
   Jiang J, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab7d03
   Jiang LL, 2023, SCI TOTAL ENVIRON, V893, DOI 10.1016/j.scitotenv.2023.164917
   Jiang YZ, 2019, J GEOPHYS RES-ATMOS, V124, P7647, DOI 10.1029/2019JD030542
   Kattel GR, 2022, BIODIVERS CONSERV, V31, P2017, DOI 10.1007/s10531-022-02417-6
   Kibler CL, 2023, AGR FOREST METEOROL, V339, DOI 10.1016/j.agrformet.2023.109560
   Kuzmina ZV, 2016, ARID ECOSYST, V6, P227, DOI 10.1134/S2079096116040028
   Lakhiar IA, 2024, AGRICULTURE-BASEL, V14, DOI 10.3390/agriculture14071141
   Lamprecht A, 2018, NEW PHYTOL, V220, P447, DOI 10.1111/nph.15290
   Li F, 2023, SCIENCE, V381, P672, DOI 10.1126/science.adf5041
   Li JH, 2024, SCI TOTAL ENVIRON, V933, DOI 10.1016/j.scitotenv.2024.173155
   Li LF, 2022, GEODERMA, V412, DOI 10.1016/j.geoderma.2022.115714
   Li SB, 2023, CATENA, V221, DOI 10.1016/j.catena.2022.106767
   Li SH, 2022, J GEOPHYS RES-BIOGEO, V127, DOI 10.1029/2021JG006421
   Li Z, 2015, J GEOPHYS RES-ATMOS, V120, P12345, DOI [10.1002/2015JD023618, 10.1002/2015JD023611]
   Li ZD, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac6002
   Lian XH, 2023, SCI TOTAL ENVIRON, V858, DOI 10.1016/j.scitotenv.2022.159995
   Lian X, 2021, NAT REV EARTH ENV, V2, P232, DOI 10.1038/s43017-021-00144-0
   Lian X, 2020, SCI ADV, V6, DOI 10.1126/sciadv.aax0255
   Lindenmayer DB, 2012, AUSTRAL ECOL, V37, P745, DOI 10.1111/j.1442-9993.2011.02351.x
   Liu L, 2023, J ENVIRON MANAGE, V344, DOI 10.1016/j.jenvman.2023.118734
   Liu L, 2023, J ENVIRON MANAGE, V328, DOI 10.1016/j.jenvman.2022.116997
   Liu Y, 2023, SCI TOTAL ENVIRON, V866, DOI 10.1016/j.scitotenv.2022.161250
   Ma YJ, 2021, ATMOSPHERE-BASEL, V12, DOI 10.3390/atmos12101341
   Masson-Delmotte V., 2018, GLOBAL WARMING 15 C
   McDowell N, 2008, NEW PHYTOL, V178, P719, DOI 10.1111/j.1469-8137.2008.02436.x
   McNally A, 2017, SCI DATA, V4, DOI 10.1038/sdata.2017.12
   Moore JW, 2022, SCIENCE, V376, P1421, DOI 10.1126/science.abo3608
   Morales A, 2023, FRONT PLANT SCI, V14, DOI 10.3389/fpls.2023.1128388
   Muluneh Melese Genete, 2021, Agriculture and Food Security, V10, DOI 10.1186/s40066-021-00318-5
   Nicholls JF, 2014, Q J ROY METEOR SOC, V140, P1399, DOI 10.1002/qj.2222
   Nicolai-Shaw N, 2017, REMOTE SENS ENVIRON, V203, P216, DOI [10.1016/j.rse.2017.06.014, 10.1016/j.rse.201]
   Nti IK, 2022, BIG DATA MIN ANAL, V5, P81, DOI 10.26599/BDMA.2021.9020028
   Nyamekye C, 2021, LAND DEGRAD DEV, V32, P7, DOI 10.1002/ldr.3654
   O'Sullivan M, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-32416-8
   Piao SL, 2008, NATURE, V451, P49, DOI 10.1038/nature06444
   Pichler M, 2023, METHODS ECOL EVOL, V14, P994, DOI 10.1111/2041-210X.14061
   Pugnaire FI, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aaz1834
   Qi Y, 2023, AGR WATER MANAGE, V277, DOI 10.1016/j.agwat.2022.108090
   Rahman MS, 2015, FOR SCI TECHNOL, V11, P126, DOI 10.1080/21580103.2014.957358
   Rishmawi K, 2016, REMOTE SENS-BASEL, V8, DOI 10.3390/rs8110910
   Rötzer T, 2019, SCI TOTAL ENVIRON, V676, P651, DOI 10.1016/j.scitotenv.2019.04.235
   Saatkamp A, 2023, GLOBAL ECOL BIOGEOGR, V32, P1113, DOI 10.1111/geb.13682
   Sha ZY, 2022, COMMUN EARTH ENVIRON, V3, DOI 10.1038/s43247-021-00333-1
   Smith P, 2020, GLOBAL CHANGE BIOL, V26, P1532, DOI 10.1111/gcb.14878
   Song X, 2021, ADV CLIM CHANG RES, V12, P584, DOI 10.1016/j.accre.2021.06.008
   Su JY, 2022, GEOPHYS RES LETT, V49, DOI 10.1029/2021GL097372
   Su YA, 2023, ENVIRON RES LETT, V18, DOI 10.1088/1748-9326/acf58e
   Swain DL, 2020, ONE EARTH, V2, P522, DOI 10.1016/j.oneear.2020.05.011
   Sweet SK, 2017, AGR FOREST METEOROL, V247, P571, DOI 10.1016/j.agrformet.2017.08.024
   Teng HF, 2023, ECOL INFORM, V75, DOI 10.1016/j.ecoinf.2023.102031
   Tietjen B, 2017, GLOBAL CHANGE BIOL, V23, P2743, DOI 10.1111/gcb.13598
   Wang H, 2022, GLOBAL CHANGE BIOL, V28, P4110, DOI 10.1111/gcb.16201
   Wang LX, 2022, NAT CLIM CHANGE, V12, P981, DOI 10.1038/s41558-022-01499-y
   Wang YX, 2024, EARTHS FUTURE, V12, DOI 10.1029/2022EF003395
   Wang ZZ, 2024, EARTHS FUTURE, V12, DOI 10.1029/2023EF003769
   Wei YQ, 2022, EARTHS FUTURE, V10, DOI 10.1029/2021EF002566
   Wu Y, 2021, GEOHEALTH, V5, DOI 10.1029/2021GH000390
   Xia JZ, 2019, J GEOPHYS RES-BIOGEO, V124, P2039, DOI 10.1029/2018JG004777
   Xu H, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-31826-y
   Yang LS, 2022, J HYDROL, V607, DOI 10.1016/j.jhydrol.2022.127533
   Yang YJ, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14235922
   Yang YT, 2023, NAT REV EARTH ENV, V4, P626, DOI 10.1038/s43017-023-00464-3
   Yao Y, 2023, GLOBAL CHANGE BIOL, V29, P3562, DOI 10.1111/gcb.16620
   You QL, 2021, CLIM DYNAM, V57, P17, DOI 10.1007/s00382-021-05691-2
   Yu HL, 2015, NEUROCOMPUTING, V166, P140, DOI 10.1016/j.neucom.2015.04.019
   Yu QY, 2021, METHODS ECOL EVOL, V12, P2117, DOI 10.1111/2041-210X.13686
   Yuan Y, 2021, J ENVIRON MANAGE, V298, DOI 10.1016/j.jenvman.2021.113330
   Zabin CJ, 2022, FRONT ECOL ENVIRON, V20, P310, DOI 10.1002/fee.2471
   Zhang RY, 2021, CURR OPIN ENV SUST, V48, P36, DOI 10.1016/j.cosust.2020.09.005
   Zhang YC, 2022, NAT CLIM CHANGE, V12, P581, DOI 10.1038/s41558-022-01374-w
   Zhao L, 2018, AGR FOREST METEOROL, V249, P198, DOI 10.1016/j.agrformet.2017.11.013
   Zhao Y, 2017, SCI CHINA EARTH SCI, V60, P1317, DOI 10.1007/s11430-017-9047-7
   Zhou J, 2017, CHINESE GEOGR SCI, V27, P772, DOI 10.1007/s11769-017-0907-5
   Zhou XC, 2020, AGR FOREST METEOROL, V281, DOI 10.1016/j.agrformet.2019.107845
   Zhou ZQ, 2020, ECOL INDIC, V117, DOI 10.1016/j.ecolind.2020.106642
   Zhou ZL, 2023, EARTHS FUTURE, V11, DOI 10.1029/2022EF003420
   Zhu BY, 2023, NPJ CLIM ATMOS SCI, V6, DOI 10.1038/s41612-023-00419-x
   Zhu XJ, 2023, SCI TOTAL ENVIRON, V857, DOI 10.1016/j.scitotenv.2022.159390
   Zhu ZC, 2021, SCIENCE, V373, DOI 10.1126/science.abg5673
   Zuo YF, 2022, ECOL INDIC, V143, DOI 10.1016/j.ecolind.2022.109429
NR 112
TC 0
Z9 0
U1 14
U2 14
PU ACADEMIC PRESS INC ELSEVIER SCIENCE
PI SAN DIEGO
PA 525 B ST, STE 1900, SAN DIEGO, CA 92101-4495 USA
SN 0013-9351
EI 1096-0953
J9 ENVIRON RES
JI Environ. Res.
PD DEC 1
PY 2024
VL 262
AR 119898
DI 10.1016/j.envres.2024.119898
EA SEP 2024
PN 2
PG 14
WC Environmental Sciences; Public, Environmental & Occupational Health
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Public, Environmental & Occupational
   Health
GA F4E0H
UT WOS:001309354400001
PM 39222727
DA 2025-01-10
ER

PT J
AU Wang, TN
   Feng, HC
   Poo, MCP
   Lau, YY
AF Wang, Tianni
   Feng, Haochen
   Poo, Mark Ching-Pong
   Lau, Yui-Yip
TI Analysis of the Network Efficiency of Chinese Ports in Global Shipping
   under the Impacts of Typhoons
SO SUSTAINABILITY
LA English
DT Article
DE port resilience; network efficiency; typhoon assessment
ID STORM SURGES; CITY
AB With the increasing volume of international trade and maritime demand, the requirements for the stability and reliability of the global shipping system are also increasing. The research on the network efficiency of Chinese ports for global shipping can not only examine the importance of Chinese ports in the shipping network but also find out the aspects that need to be improved in the construction of the port's climate adaptability in the resilience assessment to strengthen port construction and further improve the efficiency of the network. The current study builds a shipping network based on RCEP and systematically examines the key ports in China within the networks. The research paper aims to improve the resilience of the ports and the whole shipping network in response to typhoon disasters. As such, this paper focuses on shipping research based on complex networks and network multi-centricity analysis, followed by a ranking of ports. Firstly, this paper uses UCINET 6 software to build a global shipping network. Such a network evaluates the centrality of ports, calculates the degree of centrality, proximity to centrality, and centrality, and scores them according to the ranking. Then, it selects the top 20 ports in China according to the ranking and researches network efficiency for the listed ports considering the typhoon risks. The analysis of network robustness, average shortest path length, and network efficiency are carried out for the shipping network and China's essential port nodes in the network. According to the experimental results, no matter the robustness, average shortest path length, or network efficiency, when the important ports of China in the shipping network are affected, they will cause different degrees of impact, and the performance loss caused by multiple ports is higher than that of a single port. They emphasise the significant impact of typhoons on multiple ports and remind people to minimise losses as much as possible based on experimental results, ensuring the stable operation of ports and improving resilience in typhoon prevention under the changing climate. Additionally, they provide a solid foundation to further sustain global shipping network resilience.
C1 [Wang, Tianni; Feng, Haochen] Shanghai Maritime Univ, Coll Transport & Commun, Shanghai 201306, Peoples R China.
   [Poo, Mark Ching-Pong] Liverpool Hope Univ, Liverpool Hope Business Sch, Liverpool L16 9JD, England.
   [Lau, Yui-Yip] Hong Kong Polytech Univ, Sch Profess Educ & Execut Dev, Div Business & Hospitality Management, Hong Kong, Peoples R China.
C3 Shanghai Maritime University; Liverpool Hope University; Hong Kong
   Polytechnic University
RP Poo, MCP (corresponding author), Liverpool Hope Univ, Liverpool Hope Business Sch, Liverpool L16 9JD, England.
EM wangtn@shmtu.edu.cn; 202230610151@stu.shmtu.edu.cn; pooc@hope.ac.uk;
   yuiyip.lau@cpce-polyu.edu.hk
RI ; Poo, Mark Ching-Pong/Q-2235-2017
OI Lau, Yui Yip/0000-0002-2053-6238; Poo, Mark
   Ching-Pong/0000-0002-9921-3107
FU Shanghai Pujiang Program
FX No Statement Available
CR Aguas O, 2022, RES TRANSP ECON, V95, DOI 10.1016/j.retrec.2022.101234
   Al-Qudah AA, 2022, J SUSTAIN FINANC INV, V12, P44, DOI 10.1080/20430795.2021.1880219
   Alamoush A S., 2021, Journal of Shipping and Trade, V6, P19, DOI [10.1186/s41072021001016, DOI 10.1186/S41072021001016, 10.1186/s41072-021-00101-6, DOI 10.1186/S41072-021-00101-6]
   [陈芙英 Chen Fuying], 2016, [上海大学学报. 自然科学版, Journal of Shanghai University. Natural Science Edition], V22, P804
   Ding Yiting, 2024, Journal of Tropical Oceanography, V43, P126, DOI 10.11978/2023048
   Ding YM, 2017, NAT HAZARDS, V85, P559, DOI 10.1007/s11069-016-2586-4
   Fulzele V, 2022, TRANSPORT RES A-POL, V165, P285, DOI 10.1016/j.tra.2022.09.009
   Laxe FG, 2012, J TRANSP GEOGR, V24, P33, DOI 10.1016/j.jtrangeo.2012.06.005
   Guangyi P., 2020, J. Waterw. Harb, V41, P65
   He Y, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14159489
   [洪凯 Hong Kai], 2019, [热带气象学报, Journal of Tropical Meteorology], V35, P604
   Hou WH, 2021, APPL OCEAN RES, V106, DOI 10.1016/j.apor.2020.102447
   Irish JL, 2008, J PHYS OCEANOGR, V38, P2003, DOI 10.1175/2008JPO3727.1
   Jian W, 2019, OCEAN COAST MANAGE, V178, DOI 10.1016/j.ocecoaman.2019.04.023
   Lam JSL, 2017, OCEAN COAST MANAGE, V141, P43, DOI 10.1016/j.ocecoaman.2017.02.015
   Lau YY, 2024, OCEAN COAST MANAGE, V251, DOI 10.1016/j.ocecoaman.2024.107086
   Lau YY, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph19084499
   Lin MSM, 2023, SAFETY SCI, V167, DOI 10.1016/j.ssci.2023.106286
   Liu YM, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12081301
   Lu XQ, 2021, ADV ATMOS SCI, V38, P690, DOI 10.1007/s00376-020-0211-7
   Mou NX, 2020, IEEE ACCESS, V8, P181311, DOI 10.1109/ACCESS.2020.3028214
   Olbert AI, 2017, COAST ENG, V121, P278, DOI 10.1016/j.coastaleng.2016.12.006
   Ren ZL, 2020, J COASTAL RES, P766, DOI 10.2112/SI103-158.1
   Thomas A, 2019, OCEAN MODEL, V137, P1, DOI 10.1016/j.ocemod.2019.03.004
   Wan CP, 2021, OCEAN COAST MANAGE, V211, DOI 10.1016/j.ocecoaman.2021.105738
   Wang P, 2023, REG STUD MAR SCI, V60, DOI 10.1016/j.rsma.2023.102832
   Wang SD, 2011, ATMOS OCEAN SCI LETT, V4, P276, DOI 10.1080/16742834.2011.11446942
   [伍静 Wu Jing], 2019, [交通信息与安全, Journal of Transport Information and Safety], V37, P101
   Xiao ZQ, 2022, OCEAN COAST MANAGE, V228, DOI 10.1016/j.ocecoaman.2022.106295
   Yang J, 2019, J GEOPHYS RES-OCEANS, V124, P9590, DOI 10.1029/2019JC015249
   Yin J, 2016, WATER RESOUR RES, V52, P8685, DOI 10.1002/2016WR019102
   Ying M, 2014, J ATMOS OCEAN TECH, V31, P287, DOI 10.1175/JTECH-D-12-00119.1
   Yu YC, 2014, J CHIN INST ENG, V37, P595, DOI 10.1080/02533839.2012.736778
   Zhang CX, 2021, OCEAN COAST MANAGE, V213, DOI 10.1016/j.ocecoaman.2021.105880
   Zhang H., 2019, IOP Conference Series: Earth and Environmental Science
   Zhang Y, 2020, INT J DISAST RISK RE, V50, DOI 10.1016/j.ijdrr.2020.101719
NR 36
TC 3
Z9 3
U1 38
U2 45
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD APR
PY 2024
VL 16
IS 8
AR 3190
DI 10.3390/su16083190
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 QI9R3
UT WOS:001220369100001
OA gold
DA 2025-01-10
ER

PT J
AU Ranjbar, MH
   Etemad-Shahidi, A
   Kamranzad, B
AF Ranjbar, Mohammad Hassan
   Etemad-Shahidi, Amir
   Kamranzad, Bahareh
TI Modeling the combined impact of climate change and sea-level rise on
   general circulation and residence time in a semi-enclosed sea
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Climate change; Numerical modeling; Physical processes; Residence time;
   Sea-level rise; The Persian Gulf
ID PERSIAN-GULF; WATER-QUALITY; WIND; LAGOON; BAY; EUTROPHICATION;
   VULNERABILITY; SALINITY; RENEWAL; STRAIT
AB This study provides an assessment of possible changes in the general circulation and residence time in the Persian Gulf under potential future sea-level rise and changes in the wind field due to the climate change. To determine the climate-change-induced impacts, Mike 3 FlowModel FM was used to simulate hydrodynamic and transport processes in the Persian Gulf in both historical (1998-2014) and future periods (2081-2100). Historical simulation was driven by ERA-Interim data. A statistical approach was employed to modify the values and directions of the future wind field obtained from the Representative Concentration Pathway 4.5 and 8.5 (RCP4.5 and RCP8.5, respectively) scenarios derived from CMCC-CM model of the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The numerical model was calibrated and validated using measured data. Results indicated that in the historical period, residence time ranged between values of less than a month in the Strait of Hormuz and 10 years in the semi-enclosed area close to the south of Bahrain. The changes in wind field based on RCP 8.5 scenario were found to be the most disadvantageous for the Persian Gulf's capacity to flush dissolved pollutants out. Under this scenario, residence time would be 17% longer than that of historical one. This is mainly because the change in the wind field is large enough to overwhelm general circulation, showing a relationship between the residence time and the residual circulation. Impact of change in the wind field according to RCP 4.5 scenario on the modeled residence time is negligible. The numerical outputs also showed that the sea-level rise would slightly decrease the current velocity, resulting in a negligible increase in residence time. The findings of this study are intended to support establishing climate-adaptation management plans for coastal zones of the studied area in line with sustainable development goals. (C) 2020 Elsevier B.V. All rights reserved.
C1 [Ranjbar, Mohammad Hassan; Etemad-Shahidi, Amir] Griffith Univ, Sch Engn & Built Environm, Southport, Qld 4222, Australia.
   [Etemad-Shahidi, Amir] Edith Cowan Univ, Sch Engn, Joondalup, WA 6027, Australia.
   [Kamranzad, Bahareh] Kyoto Univ, Grad Sch Adv Integrated Studies Human Survivabil, Sakyo Ku, Yoshida Nakaadachi 1, Kyoto 6068306, Japan.
   [Kamranzad, Bahareh] Kyoto Univ, Hakubi Ctr Adv Res, Sakyo Ku, Yoshida Honmachi, Kyoto 6068501, Japan.
C3 Griffith University; Griffith University - Gold Coast Campus; Edith
   Cowan University; Kyoto University; Kyoto University
RP Ranjbar, MH (corresponding author), Griffith Univ, Sch Engn & Built Environm, Southport, Qld 4222, Australia.
EM m.ranjbar@griffith.edu.au
RI Ranjbar, Mohammad Hassan/IXD-9020-2023; Kamranzad, Bahareh/H-4982-2014;
   Etemad-Shahidi, Amir/H-8379-2012
OI Ranjbar, Mohammad Hassan/0000-0001-6796-5868; Kamranzad,
   Bahareh/0000-0002-8829-6007; Etemad-Shahidi, Amir/0000-0002-8489-7526
CR Abdelrhman MA, 2005, ESTUAR COAST SHELF S, V62, P339, DOI 10.1016/j.ecss.2004.09.021
   Aboobacker VM, 2011, GEOPHYS RES LETT, V38, DOI 10.1029/2010GL045736
   Allahdadi MN, 2017, OCEAN ENG, V129, P567, DOI 10.1016/j.oceaneng.2016.10.035
   Alosairi Y, 2011, J GEOPHYS RES-OCEANS, V116, DOI 10.1029/2010JC006769
   Alsahli MMM, 2016, GEOGR TIDSSKR-DEN, V116, P56, DOI 10.1080/00167223.2015.1121403
   [Anonymous], 2013, OPEN J MAR SCI, DOI DOI 10.4236/0JMS.2013.31001
   Berrisford P., 2009, ERA INTERIM ARCHIVE
   Breslow PB, 2002, RENEW ENERG, V27, P585, DOI 10.1016/S0960-1481(01)00110-0
   Carvalho D, 2017, RENEW ENERG, V101, P29, DOI 10.1016/j.renene.2016.08.036
   Cavalcante GH, 2012, J HYDROL, V468, P111, DOI 10.1016/j.jhydrol.2012.08.027
   Chen WB, 2015, ENVIRON FLUID MECH, V15, P491, DOI 10.1007/s10652-014-9367-y
   Church JA, 2013, SCIENCE, V342, P1445, DOI 10.1126/science.342.6165.1445-a
   Ciabatta L, 2016, J HYDROL, V541, P285, DOI 10.1016/j.jhydrol.2016.02.007
   Coles SL, 2013, MAR POLLUT BULL, V72, P323, DOI 10.1016/j.marpolbul.2012.09.006
   Csanady G. T., 1973, Journal of Physical Oceanography, V3, P429, DOI 10.1175/1520-0485(1973)003<0429:WIBMIL>2.0.CO;2
   Cucco A, 2006, ECOL MODEL, V193, P34, DOI 10.1016/j.ecolmodel.2005.07.043
   Deng JM, 2018, SCI TOTAL ENVIRON, V645, P1361, DOI 10.1016/j.scitotenv.2018.07.208
   DHI, 2012, MIKE 3 FLOW MOD FM
   Du JB, 2018, SCI TOTAL ENVIRON, V630, P707, DOI 10.1016/j.scitotenv.2018.02.265
   Fabiao JPF, 2016, OCEAN DYNAM, V66, P173, DOI 10.1007/s10236-015-0918-7
   Fourniotis NT, 2018, WATER-SUI, V10, DOI 10.3390/w10030237
   Hilton TW, 2008, J GEOPHYS RES-OCEANS, V113, DOI 10.1029/2007JC004247
   Hong B, 2020, J MARINE SYST, V201, DOI 10.1016/j.jmarsys.2019.103245
   Hong B, 2012, ESTUAR COAST SHELF S, V104, P33, DOI 10.1016/j.ecss.2012.03.014
   Howarth RW, 2000, ECOSYSTEMS, V3, P210, DOI 10.1007/s100210000020
   Hughes P., 1979, PROPOSAL PHYS OCEANO, V27
   Hunter J.R., 1983, P S WORKSH OC MOD KU, P37
   Johns W. E., 1998, OCEANOGRAPHY, V11, P58
   Johns WE, 2003, J GEOPHYS RES-OCEANS, V108, DOI 10.1029/2003JC001881
   Kämpf J, 2006, OCEAN SCI, V2, P27
   Kamranzad B, 2015, OCEAN DYNAM, V65, P777, DOI 10.1007/s10236-015-0833-y
   Kuang CP, 2017, J COASTAL RES, V33, P105, DOI 10.2112/JCOASTRES-D-16-00057.1
   Lokier SW, 2018, GEOMORPHOLOGY, V304, P64, DOI 10.1016/j.geomorph.2017.12.023
   Mahmoodzadeh D, 2014, J HYDROL, V519, P399, DOI 10.1016/j.jhydrol.2014.07.010
   Malhadas MS, 2010, OCEAN DYNAM, V60, P41, DOI 10.1007/s10236-009-0240-3
   Monsen NE, 2002, LIMNOL OCEANOGR, V47, P1545, DOI 10.4319/lo.2002.47.5.1545
   Montaño-Ley Y, 2019, ENVIRON FLUID MECH, V19, P137, DOI 10.1007/s10652-018-9619-3
   Oliveira A, 2011, J COASTAL RES, P1555
   Padman L., 2005, EARTH SP RES
   Pous S., 2012, OPEN J MAR SCI, V02, P131, DOI [10.4236/ojms.2012.24016, DOI 10.4236/ojms.2012.24016]
   Pous S, 2015, CONT SHELF RES, V94, P55, DOI 10.1016/j.csr.2014.12.008
   Ranjbar MH, 2018, OCEAN DYNAM, V68, P35, DOI 10.1007/s10236-017-1116-6
   Rehana S, 2012, J HYDROL, V444, P63, DOI 10.1016/j.jhydrol.2012.03.042
   REYNOLDS RM, 1993, MAR POLLUT BULL, V27, P35
   Sadrinasab M, 2004, GEOPHYS RES LETT, V31, DOI 10.1029/2004GL020425
   Sale PF, 2011, AMBIO, V40, P4, DOI 10.1007/s13280-010-0092-6
   Sheppard C, 2016, MAR POLLUT BULL, V105, P593, DOI 10.1016/j.marpolbul.2015.09.031
   Sheppard C, 2010, MAR POLLUT BULL, V60, P13, DOI 10.1016/j.marpolbul.2009.10.017
   Shirvani A, 2015, ARAB J GEOSCI, V8, P2121, DOI 10.1007/s12517-014-1278-1
   Spencer T, 2016, GLOBAL PLANET CHANGE, V139, P15, DOI 10.1016/j.gloplacha.2015.12.018
   Suara K, 2020, SCI TOTAL ENVIRON, V721, DOI 10.1016/j.scitotenv.2020.137715
   Thoppil PG, 2010, DEEP-SEA RES PT I, V57, P946, DOI 10.1016/j.dsr.2010.03.002
   UNESCO, 1981, PRACT SAL SCAL1978 I, P25
   Vermeer M, 2009, P NATL ACAD SCI USA, V106, P21527, DOI 10.1073/pnas.0907765106
   Wabnitz CCC, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0194537
   Wan YS, 2013, ECOL MODEL, V268, P93, DOI 10.1016/j.ecolmodel.2013.08.008
   Wang HQ, 2017, ESTUAR COAST, V40, P1028, DOI 10.1007/s12237-016-0197-7
   Wood JE, 2020, WATER RES, V173, DOI 10.1016/j.watres.2020.115555
   Xue P., 2015, AM GEOPH UN FALL M 2, V2015, pA31K
   Yao FC, 2010, J GEOPHYS RES-OCEANS, V115, DOI 10.1029/2009JC005781
   Yao FC, 2010, J GEOPHYS RES-OCEANS, V115, DOI 10.1029/2009JC005788
   Zahed F, 2008, CAN J CIVIL ENG, V35, P1476, DOI 10.1139/L08-087
NR 62
TC 17
Z9 17
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 OCT 20
PY 2020
VL 740
AR 140073
DI 10.1016/j.scitotenv.2020.140073
PG 15
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA NG5CL
UT WOS:000564000200008
PM 32562990
DA 2025-01-10
ER

PT C
AU Bakengesa, S
   Munishi, P
   Navrud, S
AF Bakengesa, Siima
   Munishi, Pantaleo
   Navrud, Stale
BE LealFilho, W
TI Potential Climate Change Impacts on Direct Economic Values From Wildlife
   in the Kilombero Ramsar Site, Tanzania
SO EXPERIENCES OF CLIMATE CHANGE ADAPTATION IN AFRICA
SE Climate Change Management
LA English
DT Proceedings Paper
CT Conference on Climate Change and Natural Resource Use in Eastern Africa:
   Impact, Adaptation and Mitigation
CY MAY 19-21, 2010
CL Multimedia Univ Coll, Nairobi, KENYA
SP Ecolog Soc Eastern Africa
HO Multimedia Univ Coll
DE Climate change; Direct wildlife economic value; Ramsar site; Ecological
   change
AB Tanzania is one of the world's leading nations in terms of wildlife conservation, with rich and diverse wildlife resources. Game controlled areas in Tanzania are used for wildlife conservation and most of them were set aside when human populations were low and global climate was stable. Under the climate change scenario realised for Tanzania for the next few decades, a 10% increase in annual inflow is predicted at the Kilombero Ramsar site. This may have varied impacts on the wildlife populations with consequences for the potential direct economic values from wildlife hunting. The current study assessed how rainfall may influence wildlife populations and their contribution to the national economy. Data was collected from discussions with game officials, literature searches, field observations and data was recorded for weather and hunting licences. We established a rainfall pattern based on trends observed over 40 years (1968-2008), and its correlation with wildlife outtake by both tourist and local hunters. The mean annual rainfall was 1,600 mm, with a probability of 0.90 of receiving (100 <= 300) of the mean annual rainfall especially for March and April point rainfall. Increased inflow of water is likely to be exacerbated by inflow from surrounding catchments. There were a total of 258 local and 78 tourist hunters respectively in the period from 2001 to 2008. There was a positive correlation between the number of animals hunted per species and point annual rainfall for buffalos, reedbuck, hippos, puku, warthog, crocodiles and hartebeest. Conversely, the availability of game birds declined with increased point rainfall. This would mean that revenues from buffalo, reedbuck, hippos, puku, warthog, crocodiles and hartebeest are likely to increase or remain the same with increasing point annual rainfall. On the other hand, hunting revenues from game birds is likely to decrease with point annual rainfall. The predicted hydrological change in the Kilombero River is likely to affect wildlife populations and the contribution of hunting industry to national earnings. Thus climate adaptation measures need to be instituted in order to accommodate climate-induced economic loses.
C1 [Bakengesa, Siima] Tanzania Forestry Res Inst, Directorate Forest Prod Res, POB 1854, Morogoro, Tanzania.
   [Munishi, Pantaleo] Sokoine Univ Agr, Fac Forestry & Nat Conservat, Morogoro, Tanzania.
   [Navrud, Stale] Univ Life Sci Norway, Dept Econ & Resource Management, As, Norway.
C3 Sokoine University of Agriculture; Norwegian University of Life Sciences
RP Bakengesa, S (corresponding author), Tanzania Forestry Res Inst, Directorate Forest Prod Res, POB 1854, Morogoro, Tanzania.
EM siima_b@yahoo.com
OI Navrud, Stale/0000-0002-6627-4595
FU government of Tanzania; Royal Kingdom of Norway via a NUFU project
FX We are very grateful to the government of Tanzania and Royal Kingdom of
   Norway for financial support via a NUFU project. We are grateful to
   TAFORI, SUA and the Norwegian University of Life Sciences (UMB) for
   supporting their staff during project implementation in Kilombero as
   well as District Natural Resources, the Game department and Ramsar
   Project staff for assistance in enabling and participating in field data
   collection
CR Alder LH, 1972, INTRO PROBABILITY ST, P373
   [Anonymous], 2009, KIL DISTR PROF, P83
   de Groot R.S., 2006, CBD Technical Series No. 27 Technical Series, V27
   Holmes J, 1995, NATURAL FOREST HDB T, VI, P395
   Intergovernmental Panel on Climate Change, 2001, CLIM CHANG 2001 SYNT
   Jackson IJ, 1971, ATMOSPHERIC PRESSURE, P34
   Jackson IJ, 1971, GEOGRAFISKA ANN A, V54A
   Jackson IJ, 1972, GEOGRAFISKA ANN, V4, P469
   Jones T, 1997, P 6 TAWIRI SCI C 3 6, P541
   Kashaigili J, 2005, P 6 TAWIRI SCI C 3 6, P87
   Kassam A., 2002, EXP AGR, V38, P389111, DOI [10.1017/s0014479702210194, DOI 10.1017/S0014479702210194]
   Mande M, 2009, ONLINE E AFRICAN MAG
   N'shala Rugemeleza, 1999, GRANTING HUNTING BLO, P18
   Nshubemuki L, 2008, FORESTERS VIEW AVERA
   Nshubemuki L, 1978, FORESTERS VIEW AVERA
   Primark RB, 2006, ESSENTIALS CONSERVAT
   Ramsar, 2008, INF SHEET KIL RAMS S
   Scholes R.J., 2004, Ecosystem services in southern Africa: a regional assessment
   Schuyt KD, 2005, ECOL ECON, V53, P177, DOI 10.1016/j.ecolecon.2004.08.003
   Tanzania Meteorological Agency (TMA), 2005, TANZ MET ANN REP
   Tarimo E, 2009, 7 TAWIRI SC IN PRESS
   URT (United Republic of Tanzania), 1998, WILDL POL TANZ, P36
   Walther GR, 2002, NATURE, V416, P389, DOI 10.1038/416389a
NR 23
TC 4
Z9 4
U1 0
U2 12
PU SPRINGER-VERLAG BERLIN
PI BERLIN
PA HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
SN 1610-2010
BN 978-3-642-22314-3
J9 CLIM CHANG MANAG
PY 2011
BP 33
EP +
DI 10.1007/978-3-642-22315-0_3
PG 5
WC Environmental Sciences; Environmental Studies
WE Conference Proceedings Citation Index - Science (CPCI-S); Conference Proceedings Citation Index - Social Science &amp; Humanities (CPCI-SSH)
SC Environmental Sciences & Ecology
GA BGF55
UT WOS:000322747100003
DA 2025-01-10
ER

PT J
AU Vento, B
   Rivera, J
   Ontivero, M
   Carretero, EM
AF Vento, Barbara
   Rivera, Juan
   Ontivero, Marcela
   Carretero, Eduardo Martinez
TI Insights into the Relationships between Morphological Traits of
   <i>Larrea divaricata</i> and Climate Variables in Southern South America
SO INTERNATIONAL JOURNAL OF PLANT SCIENCES
LA English
DT Article
DE morphological traits; leaf size; leaf shape; drylands; bioclimatic
   variables
ID LEAF SIZE; L-CUNEIFOLIA; TEMPERATURE; PRECIPITATION; INTERNODE;
   RESPONSES; DESERT; LEAVES; SHAPE
AB Premise of research. How vegetation adapts to environmental changes is one of the most important questions in plant science. Temperature and precipitation are considered the main climatic drivers of morphological variations in vegetation. Several studies have demonstrated that leaf morphology varies reliably with increasing latitude, and this is mostly attributed to changes in temperature and precipitation patterns. The morphological responses of plants to temperature and rainfall regimes in arid lands are still scarcely known and understood. We analyze the morphological variation in leaf traits (size and shape) as well as the internode distance in the species Larrea divaricata and their relationship with bioclimatic variables along a latitudinal gradient in central western Argentina.Methodology. We combined a set of morphological features and bioclimatic indexes using multivariate statistics and detected six relevant regions with clear differences in both plant morphology and climatic variables.Pivotal results. The largest foliar areas were located in sites with higher seasonal precipitation. Leaf shape was influenced by temperature, and the internode distances were larger under semihumid conditions.Conclusions. The plant traits of L. divaricata were influenced by the latitudinal gradient and the predominant climate conditions of each recognized region. The study of foliar morphology allowed us to identify environmental factors that potentially influenced morphological responses in the studied species. As a preliminary stage in our research, our contribution attempts to recognize woody plant adaptations to climate influence. Other environmental variables must be included in future work for a more complete analysis.
C1 [Vento, Barbara; Rivera, Juan; Ontivero, Marcela; Carretero, Eduardo Martinez] Consejo Nacl Invest Cient & Tecn, Ctr Cient Tecnol Mendoza, Inst Argentino Invest Zonas Aridas, Ave Ruiz Leal S-N,Parque Gen San Martin, RA-5500 Mendoza, Argentina.
   [Vento, Barbara; Rivera, Juan; Ontivero, Marcela; Carretero, Eduardo Martinez] Consejo Nacl Invest Cient & Tecn, Ctr Cient Tecnol Mendoza, Inst Argentino Nivol Glaciol & Ciencias Ambiental, Ave Ruiz Leal S-N,Parque Gen San Martin, RA-5500 Mendoza, Argentina.
C3 Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET);
   Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET)
RP Vento, B (corresponding author), Consejo Nacl Invest Cient & Tecn, Ctr Cient Tecnol Mendoza, Inst Argentino Invest Zonas Aridas, Ave Ruiz Leal S-N,Parque Gen San Martin, RA-5500 Mendoza, Argentina.; Vento, B (corresponding author), Consejo Nacl Invest Cient & Tecn, Ctr Cient Tecnol Mendoza, Inst Argentino Nivol Glaciol & Ciencias Ambiental, Ave Ruiz Leal S-N,Parque Gen San Martin, RA-5500 Mendoza, Argentina.
EM bvento@mendoza-conicet.gov.ar
CR Alcántara-Ayala O, 2020, PEERJ, V8, DOI 10.7717/peerj.8307
   Rivera JA, 2013, INT J CLIMATOL, V33, P834, DOI 10.1002/joc.3472
   Attarod P, 2018, J AGR SCI TECH-IRAN, V20, P1417
   Baltas E, 2007, METEOROL APPL, V14, P69, DOI 10.1002/met.7
   Baruch Z, 2017, AUSTRAL ECOL, V42, P553, DOI 10.1111/aec.12474
   Bergholz K, 2017, BASIC APPL ECOL, V25, P48, DOI 10.1016/j.baae.2017.11.001
   Cabrera A.L., 1976, Enciclopedia Argentina de Agricultura y Jardineria, V2nd
   Carretero EM, 2007, ARID LAND RES MANAG, V21, P273, DOI 10.1080/15324980701603409
   Carretero EM, 2002, APPL VEG SCI, V5, P127, DOI 10.1658/1402-2001(2002)005[0127:RTCOLD]2.0.CO;2
   CARRETERO EM, 1992, VEGETATIO, V101, P21, DOI 10.1007/BF00031912
   Carvalho SMP, 2002, ANN BOT-LONDON, V90, P111, DOI 10.1093/aob/mcf154
   DAVIS JM, 1980, QUATERNARY RES, V14, P337, DOI 10.1016/0033-5894(80)90015-0
   De Frenne P, 2013, J ECOL, V101, P784, DOI 10.1111/1365-2745.12074
   De Martonne E., 1925, Geographical Review, V15, P336, DOI DOI 10.2307/208490
   Doyle ME, 2020, INT J CLIMATOL, V40, P1716, DOI 10.1002/joc.6297
   Duval Valeria Soledad, 2015, Invest. Geog, P33
   Ellison AM, 2004, AM J BOT, V91, P1930, DOI 10.3732/ajb.91.11.1930
   EZCURRA E, 1991, ECOLOGY, V72, P23, DOI 10.2307/1938899
   Garreaud RD, 2009, PALAEOGEOGR PALAEOCL, V281, P180, DOI 10.1016/j.palaeo.2007.10.032
   Givnish T., 1979, Topics in plant population biology, P375, DOI DOI 10.1007/978-1-349-04627-0_17
   Gong HD, 2020, GLOB ECOL CONSERV, V22, DOI 10.1016/j.gecco.2020.e00904
   Grossi Gallegos H, ATLAS ENERGIA SOLAR
   Guo XL, 2020, GLOB ECOL CONSERV, V23, DOI 10.1016/j.gecco.2020.e01152
   Hamerlynck EP, 2000, PLANT ECOL, V148, P183, DOI 10.1023/A:1009896111405
   Harris I, 2020, SCI DATA, V7, DOI 10.1038/s41597-020-0453-3
   HAY RKM, 1990, NEW PHYTOL, V116, P233, DOI 10.1111/j.1469-8137.1990.tb04711.x
   He JY, 2020, GLOB ECOL CONSERV, V23, DOI 10.1016/j.gecco.2020.e01129
   Huff PM, 2003, PALAIOS, V18, P266, DOI 10.1669/0883-1351(2003)018<0266:DFFPEF>2.0.CO;2
   Huxman TE, 2004, OECOLOGIA, V141, P295, DOI 10.1007/s00442-003-1389-y
   Jobbágy EG, 2011, ECOL APPL, V21, P678, DOI 10.1890/09-1427.1
   Kanda N, 2020, ENVIRON RES COMMUN, V2, DOI 10.1088/2515-7620/ab9991
   Ladwig LM, 2019, J VEG SCI, V30, P963, DOI 10.1111/jvs.12777
   Langton FA, 1997, SCI HORTIC-AMSTERDAM, V69, P229, DOI 10.1016/S0304-4238(97)00020-4
   Liu MD, 2020, FORESTS, V11, DOI 10.3390/f11091010
   Mangiameli P, 1996, EUR J OPER RES, V93, P402, DOI 10.1016/0377-2217(96)00038-0
   Martnez Carretero E., 2013, RESTAURACION ECOLOGI, P14
   Mazzella MA, 2000, PLANTA, V210, P497, DOI 10.1007/PL00008157
   McKee ML, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0218884
   McPherson S, 2004, AUST J BOT, V52, P293, DOI 10.1071/BT03104
   Méndez E, 2008, REV FAC CIENC AGRAR, V40, P113
   Menzel A., 2006, Plant Growth and Climate Change, P70, DOI DOI 10.1002/9780470988695.CH4
   Miner BG, 2005, TRENDS ECOL EVOL, V20, P685, DOI 10.1016/j.tree.2005.08.002
   Naumburg E, 2004, NEW PHYTOL, V162, P323, DOI 10.1111/j.1469-8137.2004.01023.x
   Noy-Meir I., 1973, Annual Review of Ecology and Systematics, V4, P25, DOI 10.1146/annurev.es.04.110173.000325
   Odonnell M.S., Bioclimatic predictors for supporting ecological applications in the conterminous United States
   Peppe DJ, 2011, NEW PHYTOL, V190, P724, DOI 10.1111/j.1469-8137.2010.03615.x
   Quaye-Ballard JA, 2013, ADV MATER RES-SWITZ, V726-731, P3542, DOI 10.4028/www.scientific.net/AMR.726-731.3542
   R Core Team, 2019, R LANG ENV STAT COMP
   Rishmawi K, 2016, REMOTE SENS-BASEL, V8, DOI 10.3390/rs8110910
   Rivas-Martinez S, 2011, Global Geobotany, V1, P1, DOI DOI 10.5616/GG
   Rivera JA, 2020, FRONT CLIM, V2, DOI 10.3389/fclim.2020.587126
   Royer DL, 2008, NEW PHYTOL, V179, P808, DOI 10.1111/j.1469-8137.2008.02496.x
   Royer DL, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0007653
   Royer DL, 2005, AM J BOT, V92, P1141, DOI 10.3732/ajb.92.7.1141
   Salehi M, 2020, FRONT FOR GLOB CHANG, V3, DOI 10.3389/ffgc.2020.00019
   Schneider CA, 2012, NAT METHODS, V9, P671, DOI 10.1038/nmeth.2089
   Scoffoni C, 2011, PLANT PHYSIOL, V156, P832, DOI 10.1104/pp.111.173856
   Sheldon KS, 2015, GLOBAL ECOL BIOGEOGR, V24, P632, DOI 10.1111/geb.12284
   Souto CP, 2009, REV CHIL HIST NAT, V82, P209, DOI 10.4067/S0716-078X2009000200004
   Spicer R.A., 2000, Biotic Response to Global Change, the Last 145 Million Years, P244, DOI DOI 10.1017/CBO9780511535505.018
   SPICER RA, 1989, T RSE EARTH, V80, P321
   STOOKSBURY DE, 1991, THEOR APPL CLIMATOL, V44, P143, DOI 10.1007/BF00868169
   Tanrattana M, 2020, INT J PLANT SCI, V181, P419, DOI 10.1086/706855
   Vento B, 2021, CR PALEVOL, V20, P29, DOI 10.5852/cr-palevol2021v20a3
   Viale M, 2019, FRONT ENV SCI-SWITZ, V7, DOI 10.3389/fenvs.2019.00069
   Campanella MV, 2013, J PLANT RES, V126, P497, DOI 10.1007/s10265-012-0546-y
   Walsh R. P. D., 1981, Weather, V36, P201, DOI 10.1002/j.1477-8696.1981.tb05400.x
   Wilf P, 1997, PALEOBIOLOGY, V23, P373, DOI 10.1017/S0094837300019746
   Wilf P, 1998, GEOLOGY, V26, P203, DOI 10.1130/0091-7613(1998)026<0203:UFLAPI>2.3.CO;2
   Wolfe J., 1993, USGS Bulletin, V2040, P1, DOI DOI 10.3133/B2040
   Wright IJ, 2017, SCIENCE, V357, P917, DOI 10.1126/science.aal4760
   Xu F, 2009, PROG NAT SCI-MATER, V19, P1789, DOI 10.1016/j.pnsc.2009.10.001
   Yu XJ, 2020, AM J BOT, V107, P1481, DOI 10.1002/ajb2.1560
   Zhang XY, 2005, J GEOPHYS RES-ATMOS, V110, DOI 10.1029/2004JD005263
NR 74
TC 2
Z9 2
U1 1
U2 9
PU UNIV CHICAGO PRESS
PI CHICAGO
PA 1427 E 60TH ST, CHICAGO, IL 60637-2954 USA
SN 1058-5893
EI 1537-5315
J9 INT J PLANT SCI
JI Int. J. Plant Sci.
PD MAR 1
PY 2022
VL 183
IS 3
BP 220
EP 234
DI 10.1086/718387
EA MAR 2022
PG 15
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA 2A0UI
UT WOS:000756083400001
DA 2025-01-10
ER

PT J
AU Guitton, B
   Théra, K
   Tékété, ML
   Pot, D
   Kouressy, M
   Témé, N
   Rami, JF
   Vaksmann, M
AF Guitton, Baptiste
   Thera, Korotimi
   Tekete, Mohamed Laraine
   Pot, David
   Kouressy, Mamoutou
   Teme, Niaba
   Rami, Jean-Francois
   Vaksmann, Michel
TI Integrating genetic analysis and crop modeling: A major QTL can finely
   adjust photoperiod-sensitive sorghum flowering
SO FIELD CROPS RESEARCH
LA English
DT Article
DE Sorghum; Photoperiod-sensitivity; Flowering; Crop modeling; QTL; ELF3
ID QUANTITATIVE TRAIT LOCI; CIRCADIAN CLOCK; ELF3; TIME; TEMPERATURE;
   MATURITY; ENCODES; PROTEIN; PLANT; ARABIDOPSIS-ELF3
AB In West Africa Sudano-Sahelian zone, sorghum sensitivity to photoperiod is a major trait for flowering adjustment toward the end of the rainy season. This trait ensures that conditions for crop development are optimal. Improving the understanding of the genetic control of flowering time in sorghum is thus an important step toward breeding climate resilient varieties for meeting the challenge of climate smart agriculture. In the wake of green revolution, most sorghum breeders eliminated photoperiod sensitivity to develop early maturing varieties. The evidence is now that simultaneous improvement of production, yield stability and grain quality requires the development of photoperiod-sensitive varieties.
   A segregating sorghum population derived from a cross between two photoperiod sensitive elite parents was evaluated in three different locations and five environments. CERES crop model was applied to decompose the flowering time of each genotype into basic vegetative phase, critical photoperiod and photoperiod sensitivity. Phenology and model derived variables were used for genetic analysis.
   The three model parameters were controlled by specific genomic regions. A major QTL affecting critical photoperiod was identified, whereas only independent minor QTLs were found for basic vegetative phase and photoperiod sensitivity. Candidate gene analysis in the major QTL region allowed us to propose a candidate gene (ELF3) involved in the circadian clock as a key regulator of flowering time in photoperiod-sensitive sorghum. Our findings provide critical information supporting the development of photoperiod-sensitive genotypes specifically adapted to climate variability encountered in Sudano-Sahelian zone.
C1 [Guitton, Baptiste; Thera, Korotimi; Pot, David; Rami, Jean-Francois; Vaksmann, Michel] CIRAD, UMR AGAP, F-34398 Montpellier, France.
   [Vaksmann, Michel] CIRAD, UMR AGAP, BP 1813, Bamako, Mali.
   [Guitton, Baptiste; Thera, Korotimi; Pot, David; Rami, Jean-Francois; Vaksmann, Michel] Univ Montpellier, INRA, AGAP, CIRAD,Montpellier SupAgro, Montpellier, France.
   [Thera, Korotimi; Tekete, Mohamed Laraine; Kouressy, Mamoutou; Teme, Niaba] IER CRRA Sotuba, BP262, Bamako, Mali.
   [Tekete, Mohamed Laraine] USTTB FST, Bamako, Mali.
C3 CIRAD; Universite de Montpellier; CIRAD; CIRAD; INRAE; Universite de
   Montpellier; Institut Agro; Montpellier SupAgro; University of Science &
   Technology of Bamako
RP Vaksmann, M (corresponding author), CIRAD, UMR AGAP, F-34398 Montpellier, France.
EM baptiste.guitton@cirad.fr; korotimi.thera@cirad.fr;
   mohamed.tekete@ier.gouv.ml; david.pot@cirad.fr;
   mamoutou.kouressy@ier.gouv.ml; niaba.teme@ier.gouv.ml;
   jean-francols.rami@cirad.fr; michel.vaksmann@cirad.fr
RI Pot, David/AAA-3983-2021
FU Generation Challenge Programme [G4008.48]; Agropolis fondation [AF
   1301-010/FC 2013-1890]; Cariplo fondation [AF 1301-010/FC 2013-1890]
FX This work was supported by a grant from the Generation Challenge
   Programme (Grant Number G4008.48) and a grant from the Agropolis and
   Cariplo fondations (Grant Number: AF 1301-010/FC 2013-1890).
CR Abdulai AL, 2012, J AGRON CROP SCI, V198, P340, DOI 10.1111/j.1439-037X.2012.00523.x
   Ainsworth EA, 2010, PLANT PHYSIOL, V154, P526, DOI 10.1104/pp.110.161349
   Aitken Y., 1974, Flowering Time, Climate and Genotype: The Adaptation of Agricultural Species to Climate through Flowering Responses
   Alagarswamy G., 1991, Predict. Crop Phenol, P143
   [Anonymous], MUTATION CIRCADIAN C
   [Anonymous], AMELIORATION SORGHO
   [Anonymous], 1989, Modeling the growth and development of sorghum and pearl millet
   [Anonymous], 1967, ADV AGRON, DOI DOI 10.1016/S0065-2113(08)60737-3
   [Anonymous], DISCOVERY UTILIZATIO
   [Anonymous], GUIDE TOSSORGHUM BRE
   [Anonymous], CELL
   [Anonymous], SORGHUM MA5 AND MA6
   [Anonymous], GENETIC CHARACTERIZA
   [Anonymous], THEOR APPL GENET
   [Anonymous], SAT EJ
   Ashburner M, 2000, NAT GENET, V25, P25, DOI 10.1038/75556
   Bendix C, 2015, MOL PLANT, V8, P1135, DOI 10.1016/j.molp.2015.03.003
   Bieluszewski T, 2015, BMC PLANT BIOL, V15, DOI 10.1186/s12870-015-0461-1
   Boss PK, 2004, PLANT CELL, V16, pS18, DOI 10.1105/tpc.015958
   Broman KW, 2009, STAT BIOL HEALTH, P1, DOI 10.1007/978-0-387-92125-9_1
   Chantereau J, 2001, EUPHYTICA, V120, P183, DOI 10.1023/A:1017513608309
   Childs KL, 1997, PLANT PHYSIOL, V113, P611, DOI 10.1104/pp.113.2.611
   Covington MF, 2001, PLANT CELL, V13, P1305, DOI 10.1105/tpc.13.6.1305
   Craufurd PQ, 2009, J EXP BOT, V60, P2529, DOI 10.1093/jxb/erp196
   Craufurd PQ, 1999, THEOR APPL GENET, V99, P900, DOI 10.1007/s001220051311
   CURTIS DL, 1968, EXP AGR, V4, P93, DOI 10.1017/S0014479700022390
   El Mannai Y, 2011, GENET RESOUR CROP EV, V58, P983, DOI 10.1007/s10722-011-9737-y
   Folliard A, 2004, FIELD CROP RES, V89, P59, DOI 10.1016/j.fcr.2004.01.006
   Fu C, 2009, PLANT BIOLOGY, V11, P751, DOI 10.1111/j.1438-8677.2008.00156.x
   Garner WW, 1923, J AGRIC RES, V23, P0871
   Hicks KA, 1996, SCIENCE, V274, P790, DOI 10.1126/science.274.5288.790
   Hicks KA, 2001, PLANT CELL, V13, P1281, DOI 10.1105/tpc.13.6.1281
   Hyun Y, 2017, PLANT PHYSIOL, V173, P36, DOI 10.1104/pp.16.01523
   ILDevelopment_Corejeam, 2008, R A language and Environment for Statistical Computing
   Jones J.W., 1986, CERES-Maize: A simulation model of maize growth and development
   Kim WY, 2005, PLANT PHYSIOL, V139, P1557, DOI 10.1104/pp.105.067173
   Kouakou P. K., 2013, Journal of Applied Biosciences, V67, P5289
   Kouressy M, 2008, EUR J AGRON, V28, P195, DOI 10.1016/j.eja.2007.07.008
   Kouressy M, 2008, AGR FOREST METEOROL, V148, P357, DOI 10.1016/j.agrformet.2007.09.009
   Kouressy Mamoutou, 1998, P247
   Lafarge TA, 2002, FIELD CROP RES, V77, P137, DOI 10.1016/S0378-4290(02)00085-0
   LANDER E S, 1987, Genomics, V1, P174, DOI 10.1016/0888-7543(87)90010-3
   Langmead B, 2012, NAT METHODS, V9, P357, DOI [10.1038/NMETH.1923, 10.1038/nmeth.1923]
   LAURIE DA, 1995, GENOME, V38, P575, DOI 10.1139/g95-074
   LIN YR, 1995, GENETICS, V141, P391
   Liu XL, 2001, PLANT CELL, V13, P1293, DOI 10.1105/tpc.13.6.1293
   Mace ES, 2011, THEOR APPL GENET, V123, P169, DOI 10.1007/s00122-011-1575-y
   MAJOR DJ, 1990, CROP SCI, V30, P305, DOI 10.2135/cropsci1990.0011183X003000020012x
   MAJOR DJ, 1975, CROP SCI, V15, P174, DOI 10.2135/cropsci1975.0011183X001500020009x
   Manichaikul A, 2009, GENETICS, V181, P1077, DOI 10.1534/genetics.108.094565
   Matsubara K, 2008, THEOR APPL GENET, V117, P935, DOI 10.1007/s00122-008-0833-0
   Matsubara K, 2012, PLANT CELL PHYSIOL, V53, P709, DOI 10.1093/pcp/pcs028
   McCormick RF, 2018, PLANT J, V93, P338, DOI 10.1111/tpj.13781
   McWatters HG, 2000, NATURE, V408, P716, DOI 10.1038/35047079
   Messina C, 2006, Working with dynamic crop models: Evaluation, analysis, parameterization, P309
   Morgan PW., 2000, sorghum: origin, history, technology, and production, P240
   Mouradov A, 2002, PLANT CELL, V14, pS111, DOI 10.1105/tpc.001362
   Murphy RL, 2014, PLANT GENOME-US, V7, DOI 10.3835/plantgenome2013.11.0040
   Murphy RL, 2011, P NATL ACAD SCI USA, V108, P16469, DOI 10.1073/pnas.1106212108
   Olson SN, 2012, BIOFUEL BIOPROD BIOR, V6, P640, DOI 10.1002/bbb.1357
   QUINBY JR, 1966, CROP SCI, V6, P516, DOI 10.2135/cropsci1966.0011183X000600060005x
   Reed JW, 2000, PLANT PHYSIOL, V122, P1149, DOI 10.1104/pp.122.4.1149
   Risterucci AM, 2000, THEOR APPL GENET, V101, P948, DOI 10.1007/s001220051566
   Rooney WL, 1999, CROP SCI, V39, P397, DOI 10.2135/cropsci1999.0011183X0039000200016x
   Saito H, 2012, PLANT CELL PHYSIOL, V53, P717, DOI 10.1093/pcp/pcs029
   Sanon M, 2014, NJAS-WAGEN J LIFE SC, V68, P29, DOI 10.1016/j.njas.2013.11.004
   STEPHENS JC, 1967, CROP SCI, V7, P396, DOI 10.2135/cropsci1967.0011183X000700040036x
   Swaminathan MS, 2006, CROP SCI, V46, P2293, DOI 10.2135/cropsci2006.9999
   Tarumoto I, 2003, BREEDING SCI, V53, P353, DOI 10.1270/jsbbs.53.353
   Vaksmann M, 2008, CAH AGRIC, V17, P140
   Wang JW, 2014, J EXP BOT, V65, P4723, DOI 10.1093/jxb/eru246
   Yang ST, 2014, MOL BRAIN, V7, DOI 10.1186/s13041-014-0061-2
   Yang Y, 2013, MOL PLANT, V6, P202, DOI 10.1093/mp/sss062
   Yoshida R, 2009, NEW PHYTOL, V182, P838, DOI 10.1111/j.1469-8137.2009.02809.x
   Yuan QB, 2009, THEOR APPL GENET, V119, P675, DOI 10.1007/s00122-009-1078-2
   Zakhrabekova S, 2012, P NATL ACAD SCI USA, V109, P4326, DOI 10.1073/pnas.1113009109
   Zeng N, 2003, SCIENCE, V302, P999, DOI 10.1126/science.1090849
   Zhao J, 2012, LECT N MANAG SCI, V7, P3, DOI 10.1109/ICMMT.2012.6230073
   Zou GH, 2012, J EXP BOT, V63, P5451, DOI 10.1093/jxb/ers205
NR 79
TC 10
Z9 11
U1 1
U2 41
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 MAY 15
PY 2018
VL 221
BP 7
EP 18
DI 10.1016/j.fcr.2018.02.007
PG 12
WC Agronomy
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA GD8MT
UT WOS:000430767300002
DA 2025-01-10
ER

PT C
AU Branca, F
   Argento, S
AF Branca, F.
   Argento, S.
BE Tsimidou, MZ
   Polissiou, M
   Fernandez, JA
TI Evaluation of Saffron Pluriannual Growing Cycle in Central Sicily
SO III INTERNATIONAL SYMPOSIUM ON SAFFRON: FORTHCOMING CHALLENGES IN
   CULTIVATION, RESEARCH AND ECONOMICS
SE Acta Horticulturae
LA English
DT Proceedings Paper
CT 3rd International Symposium on Saffron - Forthcoming Challenges in
   Cultivation, Research and Economics
CY MAY 20-23, 2009
CL Krokos, GREECE
DE corm size; flowering period; stigmas production
ID CROCUS-SATIVUS L.; FLOWER FORMATION; TEMPERATURE; IDENTIFICATION;
   CROCETIN; CORMS; TIME
AB The cultivation of saffron (Crocus sativus L.) has recently attracted the interest of many farmers in inland areas of Sicily, where the crop was diffused from the twelfth century. At that time the stigmas were used to produce "Piacentinu Ennese", typical cheese aromatizated with saffron of Enna Province, recognized since some years by the Protected Designation of Origin (PDO). The cultivation of this species could help, in addition to ensure the brand PDO, to support the integrative farm income in marginal areas of the island characterized by low levels of farm mechanization as well as difficulties for irrigation. In this frame, we carried out a preliminary experimental trial to evaluate the productivity of the crop in central Sicily using corms acquired in Sardinia and classified into three weight categories:>40 g, 40 divided by 20 g and <20 g; the corms were transplanted the first decade of August 2004, plant density of 25 corms m(-2), and grown in dry conditions adopting polyannual growing cycle. After three years of production, we registered good crop adaptability to climatic conditions, high yields and a significant positive correlation between production of stigmas and corm size. The average yield of the three categories of corm weight was in the first year 0.6 g m(-2), in the second 1.9 g m(-2) and finally in the third it has dropped considerably with values equal to 0.4 g m(-2). The acquired information can support the cultivation of this species in the marginal areas of Sicily (Mathew, 1977; Basker et al., 1983; Fernandez, 2004; Argento et al., 2006; Gresta et al., 2008a, b).
C1 [Branca, F.; Argento, S.] Univ Catania, Dipartimento OrtoFloroArboricoltura & Tecnol Agro, I-95123 Catania, Italy.
C3 University of Catania
RP Branca, F (corresponding author), Univ Catania, Dipartimento OrtoFloroArboricoltura & Tecnol Agro, Via Valdisavoia 5, I-95123 Catania, Italy.
EM fbranca@unict.it
RI Argento, Sergio/AAG-9111-2020; Branca, Ferdinando/AEC-6730-2022
OI ARGENTO, SERGIO/0000-0003-1985-8288
CR Argento S., 2006, ATT 3 CONV IN PRESS
   BASKER D, 1983, ECON BOT, V37, P228, DOI 10.1007/BF02858789
   Behdani MA, 2004, ACTA HORTIC, P215, DOI 10.17660/ActaHortic.2004.650.24
   Carmona M, 2006, J AGR FOOD CHEM, V54, P973, DOI 10.1021/jf052297w
   Fernandez J. A., 2004, Recent research developments in plant science. Vol. 2, P127
   Gresta F, 2008, AGRON SUSTAIN DEV, V28, P95, DOI 10.1051/agro:2007030
   Gresta F, 2008, J SCI FOOD AGR, V88, P1144, DOI 10.1002/jsfa.3177
   International Organization for Standarization (ISO), 2003, 363212 ISO
   Lozano P, 1999, J CHROMATOGR A, V830, P477, DOI 10.1016/S0021-9673(98)00938-8
   Magesh V, 2006, MOL CELL BIOCHEM, V287, P127, DOI 10.1007/s11010-005-9088-0
   MATHEW B, 1977, PLANT SYST EVOL, V128, P89, DOI 10.1007/BF00985174
   McGimpsey JA, 1997, NEW ZEAL J CROP HORT, V25, P159, DOI 10.1080/01140671.1997.9514002
   Molina R, 2005, SCI HORTIC-AMSTERDAM, V103, P361, DOI 10.1016/j.scienta.2004.06.005
   Molina RV, 2005, J HORTIC SCI BIOTECH, V80, P319, DOI 10.1080/14620316.2005.11511937
   Molina RV, 2004, ACTA HORTIC, P39, DOI 10.17660/ActaHortic.2004.650.2
   Mollafilabi A, 2004, ACTA HORTIC, P195, DOI 10.17660/ActaHortic.2004.650.20
   Negbi M., 1999, SAFFRON CROCUS SATIV
   Rios JL, 1996, PHYTOTHER RES, V10, P189, DOI 10.1002/(SICI)1099-1573(199605)10:3<189::AID-PTR754>3.0.CO;2-C
   SAMPATHU SR, 1984, CRC CR REV FOOD SCI, V20, P123, DOI 10.1080/10408398409527386
   Tarantilis PA, 1997, J AGR FOOD CHEM, V45, P459, DOI 10.1021/jf960105e
NR 20
TC 9
Z9 9
U1 0
U2 7
PU INT SOC HORTICULTURAL SCIENCE
PI LEUVEN 1
PA PO BOX 500, 3001 LEUVEN 1, BELGIUM
SN 0567-7572
BN 978-90-66057-32-6
J9 ACTA HORTIC
PY 2010
VL 850
BP 153
EP 158
PG 6
WC Agronomy; Horticulture
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Agriculture
GA BDL66
UT WOS:000313674300024
DA 2025-01-10
ER

PT J
AU Ayyub, BM
   Sawaya, R
   Butry, DT
   Helgeson, J
   Oum, Y
   Loh, V
AF Ayyub, Bilal M.
   Sawaya, Ramsay
   Butry, David T.
   Helgeson, Jennifer
   Oum, Yumi
   Loh, Vincent
TI Risk Tolerance, Aversion, and Economics of Energy Utilities in Community
   Resilience to Wildfires
SO ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART
   A-CIVIL ENGINEERING
LA English
DT Article
DE Climate adaptation; Community resilience; Economics; Electric power
   utilities; Gas utilities; Risk aversion; Risk; Risk tolerance; Risk
   attitude; Wildfire
AB Electric and gas investor-owned utilities operate in a regulated environment and are scrutinized by media and stakeholders for key strategic and operational decisions. Some decisions entail significant risk, requiring special attention to risk tolerances and attitudes including risk aversion. Utilities typically institute enterprise risk management programs to efficiently and effectively manage safety, reliability, and financial risks for their customers, employees, and communities in a changing climate with intensifying risks, such as wildfire. Consequences from such events could include human life and property losses, health effects, environmental damage, service loss, and other indirect financial and economic impacts. A spectrum of risk quantification and management methods are available for assessing these hazards. Varying risk tolerances and attitudes of stakeholders creates situations that are central to decision-making where the safety, service delivery reliability, rate affordability, and the financial wellbeing of entities come together and interact in a complex manner. This paper sets context, defines key terms, and develops an innovative approach for methodically reflecting risk tolerance and attitude with a focus on risk aversion in informing risk management decisions by offering flexibility to account for preferences by stakeholders in a structured manner. The concept of risk-aversion amplification factors is proposed to reflect attitudes and preferences of decision makers in typical economic models used in benefit-cost analysis. Such amplification factors can be calibrated by applicable markets, such as insurance and catastrophe bond markets and used to estimate certainty-equivalent valuations of risks, costs, and benefits. The proposed methods are illustrated in the context of wildfire risk management for communities and utilities using two examples from these domains for enhancing resilience.
C1 [Ayyub, Bilal M.] Univ Maryland, Ctr Technol & Syst Management, Dept Civil & Environm Engn, College Pk, MD 20742 USA.
   [Ayyub, Bilal M.; Butry, David T.; Helgeson, Jennifer] Natl Inst Stand & Technol NIST, Engn Lab, Appl Econ Off, 100 Bur Dr, Gaithersburg, MD 20899 USA.
   [Ayyub, Bilal M.] Tongji Univ, Int Joint Res Ctr Resilient Infrastruct, Sch Civil Engn, 1239 Siping Rd, Shanghai 200092, Peoples R China.
   [Sawaya, Ramsay] KPMG, Power & Util Strategy, 1225 17th St,Suite 800, Denver, CO 80202 USA.
   [Sawaya, Ramsay] Resilient Asset Management Solut LLC, 12147 Beach St, Westminster, CO 80234 USA.
   [Oum, Yumi; Loh, Vincent] Pacific Gas & Elect Co PG&E, Enterprise Risk Analyt, 300 Lakeside Dr, Oakland, CA 94612 USA.
C3 University System of Maryland; University of Maryland College Park;
   National Institute of Standards & Technology (NIST) - USA; Tongji
   University
RP Ayyub, BM (corresponding author), Univ Maryland, Ctr Technol & Syst Management, Dept Civil & Environm Engn, College Pk, MD 20742 USA.; Ayyub, BM (corresponding author), Natl Inst Stand & Technol NIST, Engn Lab, Appl Econ Off, 100 Bur Dr, Gaithersburg, MD 20899 USA.; Ayyub, BM (corresponding author), Tongji Univ, Int Joint Res Ctr Resilient Infrastruct, Sch Civil Engn, 1239 Siping Rd, Shanghai 200092, Peoples R China.
EM ba@umd.edu; ramsaw7@comcast.net; david.butry@nist.gov;
   jennifer.helgeson@nist.gov; YxO2@pge.com; VKL2@pge.com
OI Helgeson, Jennifer/0000-0002-3692-7874; Oum, Yumi/0009-0006-9521-3173
FU Pacific Gas and Electric (PGE), KPMG LLP; National Institute of
   Standards and Technology (NIST); BMA Engineering, Inc.
FX The authors acknowledge the input of T. Brown and A. Tzamaras; and
   reviews by A. Maranghides, Dr. S. W. Gilbert, and T. Ibn Faiz; the
   guidance of R. Ito and A. Mani; and input of S. Elsibaie, C.C. Gore, and
   Ryan Flynn-deOnis. The financial support of Pacific Gas and Electric
   (PG&E), KPMG LLP, the National Institute of Standards and Technology
   (NIST), and BMA Engineering, Inc. is acknowledged.
CR [Anonymous], 2009, ISO Guide 73:2009
   [Anonymous], 2014, Risk analysis in engineering and economics
   [Anonymous], 2022, CLIMATE CHANGE INDIC
   [Anonymous], 2001, Elicitation of Expert Opinions for Uncertainty and Risks
   [Anonymous], 2006, Uncertainty Modeling and Analysis in Engineering and the Sciences
   [Anonymous], 2009, ISO 310002009 RISK M
   [Anonymous], 2013, Critical Infrastructure Security and Resilience, PPD-21
   ARTEMIS, 2023, Catastrophe bonds, insurance linked securities, reinsurance capital & investment, risk transfer intelligence
   ASTM, 2021, Standard guide for developing cost-effective community resilience strategies
   Ayyub BM, 2016, ASCE-ASME J RISK U B, V2, DOI 10.1115/1.4033518
   Ayyub BM, 2011, SCIENCE, V334, P1494, DOI 10.1126/science.334.6062.1494-a
   Boardman A.E., 2018, Cost-Benefit Analysis: Concepts and Practice, Vfourth
   Cal Fire, 2020, California fire hazard severity zone viewer
   Charness G, 2013, J ECON BEHAV ORGAN, V87, P43, DOI 10.1016/j.jebo.2012.12.023
   CPUC (California Public Utilities Commission), 2023, Risk assessment mitigation phase
   CPUC (California Public Utilities Commission), 2022, Decision D2212027. Risk-based Decision Framework, Appendix A
   CPUC (California Public Utilities Commission) and Boston Consulting Group, 2020, Reducing utility-related wildfire risk
   Emerson P. M., 2023, Intermediate microeconomics
   EO (Executive Order), 1993, Presidential Documents
   Foerch A., 2020, Shutdown costs Reagan library $150,000 a week in lost revenue
   Friedman M., 1976, PRICE THEORY
   Gilbert S. W., 2015, Community resilience economic decision guide for buildings and infrastructure systems
   Gilbert S, 2016, ASCE-ASME J RIS UNCE, V2, DOI 10.1061/AJRUA6.0000867
   Haine S., 2015, As low as reasonably practicable (ALARP) risk-informed decision framework applied to public utility safety
   Helgeson J. F., 2020, . NIST SP 1260
   Helgeson J. F., 2020, EDGe$ (Economic Decision Guide Software) online tool, software
   Hertwig R, 2019, PHILOS T R SOC B, V374, DOI 10.1098/rstb.2018.0140
   Hillson R., 2016, Understanding and managing risk attitude, V2nd ed.
   HSE (Health and Safety Executive), 1992, TOL RISK NUCL POW ST
   HSE (Health and Safety Executive), 2023, ALARP at a glance
   IAA (Institute of Actuaries of Australia), 2015, Developing the risk appetite framework of a life insurance business
   KAHNEMAN D, 1979, ECONOMETRICA, V47, P263, DOI 10.2307/1914185
   Kind J, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.446
   OMB (Office of Management and Budget), 2023, Circular A-4 OMB (draft for public comments) guidance to federal agencies on the development of regulatory analysis as required under Section 6(a)(3)(C) of Executive Order 12866 of September 30, 1993
   Polacek A., 2018, CATASTROPHE BONDS PR
   Rodriguez Mega Emiliano, 2019, Nature, V571, P312, DOI 10.1038/d41586-019-02141-2
   Sanchez R., 2019, Wildfire caused $500,000 in damage at Reagan Presidential Library
   Schindler S, 2017, J EXP SOC PSYCHOL, V69, P172, DOI 10.1016/j.jesp.2016.09.009
   Shao J, 2017, ASCE-ASME J RISK U A, V3, DOI 10.1061/AJRUA6.0000923
   Siemens, 2015, FIR PROT HIST BUILD
   TENGS TO, 1995, RISK ANAL, V15, P369, DOI 10.1111/j.1539-6924.1995.tb00330.x
   Thomas D., 2017, NIST Special Publication, DOI [DOI 10.6028/NIST.SP.1215, 10.6028/NIST.SP.1215]
   TRB (Transportation Research Board), 2018, Designing safety regulations for high-hazard industries
   US Department of Treasury, 2022, Annual report on the insurance industry
   US Supreme Court, 1980, Industrial Union Department, AFL-CIO v. American Petroleum Institute
   Varian H. R., 1984, MICROECONOMIC ANAL
NR 46
TC 0
Z9 0
U1 2
U2 4
PU ASCE-AMER SOC CIVIL ENGINEERS
PI RESTON
PA 1801 ALEXANDER BELL DR, RESTON, VA 20191-4400 USA
SN 2376-7642
J9 ASCE-ASME J RISK U A
JI ASCE-ASME J. Risk. Uncertain. Eng. Syst. Part A.-Civ. Eng.
PD JUN 1
PY 2024
VL 10
IS 2
AR 04024020
DI 10.1061/AJRUA6.RUENG-1254
PG 14
WC Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering
GA NT0R5
UT WOS:001202592400005
OA hybrid
DA 2025-01-10
ER

PT J
AU Afrin, R
   Sultana, R
   Alam, MS
AF Afrin, Raisa
   Sultana, Rumana
   Alam, Md. Shafiul
TI A Comprehensive analysis of drought vulnerability in the Barind region
   of Bangladesh: A socio-ecological systems approach
SO ECOLOGICAL INDICATORS
LA English
DT Article
DE Socio-ecological vulnerability; exposure; sensitivity; adaptive
   capacity; Entropy Weight Method
ID CLIMATE-CHANGE VULNERABILITY; LIVELIHOOD VULNERABILITY; ADAPTATION;
   RESILIENCE; FRAMEWORK; DETERMINANTS; COMMUNITIES; INDICATORS; CAPACITY;
   CONTEXT
AB The main objective of this study was to investigate the vulnerability to climate change in the drought-prone region of Bangladesh through the utilization of a social-ecological system framework. The research was conducted in three sub-districts of Bangladesh prone to drought: Atrai, Nachole, and Tanore. The entropy method used exposure, sensitivity, and adaptive capacity indicators to estimate vulnerability. The data was obtained by administering a structured questionnaire to 100 households and gathering meteorological information. The study's findings reveal that the Barind region, namely Atrai, Nachol, and Tanore, exhibit a high level of sensitivity to climate change, as evidenced by their respective sensitivity indices of 0.465, 0.47, and 0.507. Additionally, the region demonstrates moderate adaptive potential, as evidenced by their corresponding indices. Specifically, Atrai, Nachol, and Tanore possess scores of 0.577, -0.48, and -0.191, respectively. The study areas exhibit high drought severity exposure, as evidenced by the values of Atrai-0.555, Nachol-0.595, and Tanore0.551. Moreover, the study indicates that the capacity to handle drought is moderately vulnerable to climate change and requires economic cooperation to prepare for future conditions. Key initiatives include providing financial support for smallholder farmers, enforcing agricultural policies, investing in social capital, and implementing government-backed infrastructure and technology enhancements, all crucial for building resilience against climate change. The research findings can provide a foundation for making climate adaptation decisions in the Barind region and other comparable locations across the globe.
C1 [Afrin, Raisa; Alam, Md. Shafiul] Univ Rajshahi, Dept Geog & Environm Studies, Rajshahi 6205, Bangladesh.
   [Sultana, Rumana] Independent Univ Bangladesh IUB, Dept Environm Sci & Management, Bashundhara R-A, Dhaka, Bangladesh.
C3 University of Rajshahi; Independent University Bangladesh (IUB)
RP Alam, MS (corresponding author), Univ Rajshahi, Dept Geog & Environm Studies, Rajshahi 6205, Bangladesh.; Sultana, R (corresponding author), Independent Univ Bangladesh IUB, Dept Environm Sci & Management, Bashundhara R-A, Dhaka, Bangladesh.
EM raisaafrin19987@gmail.com; rumana.sultana@iub.edu.bd;
   shafiul_alam@ru.ac.bd
CR Abbas A, 2021, WATER-SUI, V13, DOI 10.3390/w13162237
   Alam ATMJ, 2011, RAJSHAHI U J ENV SCI, V1, P40
   Alam K, 2015, AGR WATER MANAGE, V148, P196, DOI 10.1016/j.agwat.2014.10.011
   Alamgir Mahiuddin, 2015, Applied Mechanics and Materials, V735, P186, DOI 10.4028/www.scientific.net/AMM.735.186
   Amiri V, 2014, ENVIRON EARTH SCI, V72, P3479, DOI 10.1007/s12665-014-3255-0
   Anik AR, 2021, INT J DISAST RISK RE, V65, DOI 10.1016/j.ijdrr.2021.102562
   [Anonymous], 2024, NASA power project
   Banglapedia, 2021, Barind track
   Barreteau O, 2020, ECOL SOC, V25, DOI 10.5751/ES-11402-250203
   Béné C, 2016, FOOD SECUR, V8, P123, DOI 10.1007/s12571-015-0526-x
   Brooks N, 2005, GLOBAL ENVIRON CHANG, V15, P151, DOI 10.1016/j.gloenvcha.2004.12.006
   Carr ER, 2008, GLOBAL ENVIRON CHANG, V18, P689, DOI 10.1016/j.gloenvcha.2008.06.004
   Cook BI, 2014, CLIM DYNAM, V43, P2607, DOI 10.1007/s00382-014-2075-y
   Dai AG, 2013, NAT CLIM CHANGE, V3, P52, DOI [10.1038/NCLIMATE1633, 10.1038/nclimate1633]
   Das M, 2022, ENVIRON SCI POLLUT R, V29, P61561, DOI 10.1007/s11356-021-15605-8
   Das M, 2020, ECOL INDIC, V119, DOI 10.1016/j.ecolind.2020.106815
   de Groot RS, 2010, ECOL COMPLEX, V7, P260, DOI 10.1016/j.ecocom.2009.10.006
   Eriksen S, 2011, CLIM DEV, V3, P7, DOI 10.3763/cdev.2010.0060
   Feng SF, 2022, J ARID ENVIRON, V202, DOI 10.1016/j.jaridenv.2022.104768
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Frazier TG, 2014, APPL GEOGR, V51, P158, DOI 10.1016/j.apgeog.2014.04.004
   Giri M, 2021, J CLEAN PROD, V307, DOI 10.1016/j.jclepro.2021.127213
   Gomez-Gomez JD, 2022, SCI TOTAL ENVIRON, V820, DOI 10.1016/j.scitotenv.2022.153128
   Gupta AK, 2020, ECOL INDIC, V109, DOI 10.1016/j.ecolind.2019.105787
   Hagenlocher M, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab225d
   Hagenlocher M, 2018, SCI TOTAL ENVIRON, V631-632, P71, DOI 10.1016/j.scitotenv.2018.03.013
   Hahn MB, 2009, GLOBAL ENVIRON CHANG, V19, P74, DOI 10.1016/j.gloenvcha.2008.11.002
   Hesselberg J, 2006, GEOJOURNAL, V67, P41, DOI 10.1007/s10708-006-9007-2
   Hoque MAA, 2017, INT J DISAST RISK RE, V22, P345, DOI 10.1016/j.ijdrr.2017.02.008
   Hossain MN, 2016, NAT HAZARDS, V83, P1007, DOI 10.1007/s11069-016-2360-7
   Hossain MS, 2020, REG ENVIRON CHANGE, V20, DOI 10.1007/s10113-020-01599-5
   Intergovernmental Panel on Climate Change (IPCC), 2022, WGII 6 ASS REP
   Ipcc, 2007, Climate Change 2007: The Fourth Assessment Report of the Intergovernmental Panel on Climate Change, P74
   Islam AMT, 2017, ADV METEOROL, V2017, DOI 10.1155/2017/3514381
   Jena R, 2020, IOP C SER EARTH ENV, V540, DOI 10.1088/1755-1315/540/1/012079
   Jiao WZ, 2019, AGR FOREST METEOROL, V268, P74, DOI 10.1016/j.agrformet.2019.01.008
   Keshavarz M, 2017, INT J DISAST RISK RE, V21, P223, DOI 10.1016/j.ijdrr.2016.12.012
   Kumar Praveen., 2021, Socio-Ecological Practice Research, V3, P397, DOI [https://doi.org/10.1007/s42532-021-00096-1, DOI 10.1007/S42532-021-00096-1]
   Lesk C, 2016, NATURE, V529, P84, DOI 10.1038/nature16467
   Li B, 2019, CHINESE GEOGR SCI, V29, P1052, DOI 10.1007/s11769-019-1076-5
   Liu HL, 2016, GLOBAL PLANET CHANGE, V137, P1, DOI 10.1016/j.gloplacha.2015.12.014
   Mardy T, 2018, CLIMATE, V6, DOI 10.3390/cli6020023
   McLaughlin P, 2011, ORGAN ENVIRON, V24, P269, DOI 10.1177/1086026611419862
   Naylor LA, 2019, REG ENVIRON CHANGE, V19, P1835, DOI 10.1007/s10113-019-01530-7
   O'Brien KL, 2000, GLOBAL ENVIRON CHANG, V10, P221, DOI 10.1016/S0959-3780(00)00021-2
   Omerkhil N, 2020, ECOL INDIC, V110, DOI 10.1016/j.ecolind.2019.105863
   Pandey R, 2018, ECOL INDIC, V90, P379, DOI 10.1016/j.ecolind.2018.03.031
   Pandey R, 2017, ECOL INDIC, V79, P338, DOI 10.1016/j.ecolind.2017.03.047
   Pandey R, 2012, MITIG ADAPT STRAT GL, V17, P487, DOI 10.1007/s11027-011-9338-2
   Pandey R, 2015, APPL GEOGR, V64, P74, DOI 10.1016/j.apgeog.2015.09.008
   Pei W, 2019, WATER RESOUR MANAG, V33, P2033, DOI 10.1007/s11269-019-02225-8
   Perera ENC, 2019, MODEL EARTH SYST ENV, V5, P1635, DOI 10.1007/s40808-019-00615-w
   Qin Z, 2022, ECOL INDIC, V140, DOI 10.1016/j.ecolind.2022.109020
   Rahman MR, 2016, ENVIRON EARTH SCI, V75, DOI 10.1007/s12665-016-5829-5
   Raikes J, 2021, CLIM RISK MANAG, V32, DOI 10.1016/j.crm.2021.100291
   Rana MMP., 2021, Environmental Challenges, V2, P100026, DOI [10.1016/j.envc.2021.100026, DOI 10.1016/J.ENVC.2021.100026]
   Reza A., 2014, International Journal of Ecosystem, V4, P150, DOI [DOI 10.5923/J.IJE.20140403.07, 10.5923/j.ije.20140403, DOI 10.5923/J.IJE.20140403]
   Sehgal VK, 2016, ENVIRON MONIT ASSESS, V188, DOI 10.1007/s10661-016-5187-5
   Shameem MIM, 2014, OCEAN COAST MANAGE, V102, P79, DOI 10.1016/j.ocecoaman.2014.09.002
   Shinbrot XA, 2019, ENVIRON MANAGE, V63, P583, DOI 10.1007/s00267-019-01152-z
   Smith JW, 2012, RURAL SOCIOL, V77, P380, DOI 10.1111/j.1549-0831.2012.00082.x
   STIGLER GJ, 1961, J POLIT ECON, V69, P213, DOI 10.1086/258464
   Sujakhu NM, 2018, WATER INT, V43, P165, DOI 10.1080/02508060.2017.1416445
   Sultana R., 2023, Environmental Challenges, V11, P100707, DOI [10.1016/j.envc.2023.100707, DOI 10.1016/J.ENVC.2023.100707]
   Tahasin Anika, 2023, PREPRINT, DOI [10.21203/rs.3.rs-3378881/v1, DOI 10.21203/RS.3.RS-3378881/V1]
   Tam J, 2013, ENVIRON SCI POLICY, V27, P114, DOI 10.1016/j.envsci.2012.12.004
   Thiault L, 2018, MAR POLICY, V88, P213, DOI 10.1016/j.marpol.2017.11.027
   Thomas T, 2016, NAT HAZARDS, V81, P1627, DOI 10.1007/s11069-016-2149-8
   Turner BL, 2003, P NATL ACAD SCI USA, V100, P8074, DOI 10.1073/pnas.1231335100
   Verburg P.H., 2016, Ambio, V45, P294
   Verburg PH, 2015, ANTHROPOCENE, V12, P29, DOI 10.1016/j.ancene.2015.09.004
   World Bank, 2018, Bangladesh: rising temperature affects living standards of 134 million people
   Zhang L., 2019, J SERV SCI MANAG, V12, P116, DOI [10.4236/jssm.2019.122007, DOI 10.4236/JSSM.2019.122007]
   Zhang Q, 2015, THEOR APPL CLIMATOL, V121, P337, DOI 10.1007/s00704-014-1234-8
   Zhang Q, 2019, CLIM DEV, V11, P525, DOI 10.1080/17565529.2018.1442808
   Zhao JC, 2018, ECOL INDIC, V91, P410, DOI 10.1016/j.ecolind.2018.04.016
   Zhi-Hong Z, 2006, J ENVIRON SCI, V18, P1020, DOI 10.1016/S1001-0742(06)60032-6
NR 77
TC 1
Z9 1
U1 6
U2 7
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 1470-160X
EI 1872-7034
J9 ECOL INDIC
JI Ecol. Indic.
PD MAR
PY 2024
VL 160
AR 111863
DI 10.1016/j.ecolind.2024.111863
EA MAR 2024
PG 13
WC Biodiversity Conservation; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA RH7F5
UT WOS:001226832700001
OA gold
DA 2025-01-10
ER

PT J
AU Ren, YS
   Derouiche, I
   Hassan, M
   Liu, PZ
AF Ren, Yi-Shuai
   Derouiche, Imen
   Hassan, Majdi
   Liu, Pei-Zhi
TI Do creditors price climate transition risks? A natural experiment based
   on China's carbon emission trading scheme
SO INTERNATIONAL REVIEW OF ECONOMICS & FINANCE
LA English
DT Article
DE Carbon emission trading scheme; Debt financing cost; Climate transition
   risk; Listed high -carbon firms; China; Difference -in -difference model
ID COST
AB The pursuit of carbon neutrality by China signifies the country's resolute commitment to proactively tackle climate change. However, traditional energy firms, which function as the pillars of the domestic economy, surely face a significant challenge in the form of "decarbonization." In light of climate transition risks, this study employs the difference-in-difference (DID) model to investigate the impact of China's carbon emission trading scheme (ETS) on the debt financing costs of listed high-carbon firms (HCFs). The findings indicate that the significant increase in debt financing costs of HCFs under ETS can be attributed to the "dual vulnerability" that HCFs exhibit, consisting of heightened credit risk and a diminished environmental reputation. Specifically, the implementation of ETS regulations results in elevated operating costs and future cash flow risks for firms, which subsequently escalates credit risk. This is especially true for establishments situated in regions characterized by high carbon emissions and high scores on the Low Carbon Economic Transition Assessment Index. Such data suggests creditors are progressively placing greater emphasis on the reputation of low-carbon environmental practices. Additional study suggests that firms that possess inferior qualification endowments, less external financing capabilities, and weaker risk-diverting capabilities are more susceptible to the effects of ETS and are subjected to more transformation pressure. The findings of this research hold substantial importance in terms of advancing ETS initiatives in a concentrated, phased, and clustered fashion, guaranteeing technological advancements and seamless transitions for HCFs throughout the carbon peak cycle, and eventually bolstering society's climate adaptability as a whole.
C1 [Ren, Yi-Shuai] Hunan Univ, Sch Publ Adm, Changsha, Peoples R China.
   [Ren, Yi-Shuai] Hunan Univ, Res Inst Digital Soc & Blockchain, Changsha, Peoples R China.
   [Ren, Yi-Shuai] Hunan Univ, Ctr Resource & Environm Management, Changsha, Peoples R China.
   [Ren, Yi-Shuai] Univ Auckland, Energy Ctr, 12 Grafton Rd, Auckland 1010, New Zealand.
   [Derouiche, Imen] Univ Luxembourg, Dept Econ & Management FDEF, Luxembourg, Luxembourg.
   [Hassan, Majdi] Univ Tunis, ESSEC, Tunis, Tunisia.
   [Liu, Pei-Zhi] China Tobacco Hunan Ind Co Ltd, Changsha 410004, Peoples R China.
   [Liu, Pei-Zhi] Yango Univ, YGU Digital Econ Acad YGDEA, Fuzhou, Peoples R China.
C3 Hunan University; Hunan University; Hunan University; University of
   Auckland; University of Luxembourg; Universite de Tunis; China National
   Tobacco Corporation
RP Liu, PZ (corresponding author), China Tobacco Hunan Ind Co Ltd, Changsha 410004, Peoples R China.
EM renyishuai1989@126.com; Imen.derouiche@uni.lu; majdi.hassen@gmail.com;
   liupeizhi@hnu.edu.cn
RI Der, Imen/KHY-3186-2024; Ren, Yishuai/AAB-9519-2019
OI DEROUICHE, Imen/0000-0002-9181-5146
FU National Natural Science Foundation of China [72104075, 72274056];
   National Social Science Fund of China [19AZD014]; Natural Science
   Foundation of Hunan Province [2022JJ40106, 20220615ZZ07110402]; China
   Association for Science and Technology [20220615ZZ07110402]; Hunan
   Social Science Achievement Review Committee [XSP21YBC087]; Hunan
   University Youth Talent Program
FX This work is financially supported by the National Natural Science
   Foundation of China (No. 72104075, 72274056) , the National Social
   Science Fund of China (No. 19AZD014) , the Natural Science Foundation of
   Hunan Province (No. 2022JJ40106) , China Association for Science and
   Technology (No. 20220615ZZ07110402) , Hunan Social Science Achievement
   Review Committee under Grant (No. XSP21YBC087) and Hunan University
   Youth Talent Program.
CR Agliardi E, 2021, J FINANC STABIL, V54, DOI 10.1016/j.jfs.2021.100868
   ALTMAN EI, 1968, J FINANC, V23, P589, DOI 10.2307/2978933
   [Anonymous], 2013, WORLD EN OUTL 2013
   Balachandran B, 2018, J BANK FINANC, V96, P249, DOI 10.1016/j.jbankfin.2018.09.015
   Ben-Nasr H, 2021, J CORP FINANC, V69, DOI 10.1016/j.jcorpfin.2021.102009
   BIS, 2000, Basel committee on banking 2 supervision
   BIS, 2020, GREEN SWAN CENTR BAN
   Bolton P, 2021, J FINANC ECON, V142, P517, DOI 10.1016/j.jfineco.2021.05.008
   Boubaker S., 2018, Research Handbook of Finance and Sustainability
   Boubaker S., 2021, Inalienable human capital and debt choice: Evidence from quasi-exogenous shocks
   Boubaker S., 2012, Board Directors and Corporate Social Responsibility
   Boubaker S, 2024, INT REV FINANC ANAL, V91, DOI 10.1016/j.irfa.2023.102961
   Boubaker S, 2022, FINANC RES LETT, V47, DOI 10.1016/j.frl.2022.102699
   Boubaker S, 2020, ECON MODEL, V91, P835, DOI 10.1016/j.econmod.2020.05.012
   Bushnell JB, 2013, AM ECON J-ECON POLIC, V5, P78, DOI 10.1257/pol.5.4.78
   Cai M. R., 2014, Science of Finance and Economics, V7, P41, DOI [10.3969/j.issn.1000-8306.2014.07.005, DOI 10.3969/J.ISSN.1000-8306.2014.07.005]
   Caragnano A, 2020, J ENVIRON MANAGE, V270, DOI 10.1016/j.jenvman.2020.110860
   Chen CH, 2022, INT REV ECON FINANC, V80, P82, DOI 10.1016/j.iref.2022.02.018
   Chen S.Y., 2012, EC RES J, V47, P32
   Chen XQ, 2023, INT REV ECON FINANC, V88, P1003, DOI 10.1016/j.iref.2023.07.053
   Chen ZH, 2023, INT REV ECON FINANC, V85, P295, DOI 10.1016/j.iref.2023.01.028
   Chen ZF, 2021, TECHNOL FORECAST SOC, V168, DOI 10.1016/j.techfore.2021.120744
   Cohen WM, 1996, REV ECON STAT, V78, P232, DOI 10.2307/2109925
   Coulson A.B., 1999, Corporate Social-Responsibility and Environmental Management, V6, P1, DOI [10.1002/(SICI)1099-0925(199903)6:1andlt;1::AID-EMA93andgt;3.0.CO;2-M, DOI 10.1002/(SICI)1099-0925(199903)6:1ANDLT;1::AID-EMA93ANDGT;3.0.CO;2-M, DOI 10.1002/(SICI)1099-0925(199903)6:13.0.CO;2-M]
   [邓路 Deng Lu], 2019, [管理科学学报, Journal of Management Sciences in China], V22, P22
   Diaz-Rainey I, 2021, INT REV FINANC ANAL, V76, DOI 10.1016/j.irfa.2021.101746
   Dong F, 2019, SCI TOTAL ENVIRON, V653, P565, DOI 10.1016/j.scitotenv.2018.10.395
   Du Y., 2017, China Ind. Econ, V12, P113, DOI [10.19581/j.cnki.ciejournal.20171214.007, DOI 10.19581/J.CNKI.CIEJOURNAL.20171214.007]
   Ehlers T, 2022, J BANK FINANC, V136, DOI 10.1016/j.jbankfin.2021.106180
   Fan X.Y., 2017, FINANCE TRADE EC, V38, P51
   Guo C, 2022, INT REV ECON FINANC, V82, P65, DOI 10.1016/j.iref.2022.06.002
   Huang BH, 2021, J CORP FINANC, V69, DOI 10.1016/j.jcorpfin.2021.101983
   Huang R, 2022, ENERG POLICY, V164, DOI 10.1016/j.enpol.2022.112873
   In SY, 2022, RENEW SUST ENERG REV, V154, DOI 10.1016/j.rser.2021.111881
   JACOBSON LS, 1993, AM ECON REV, V83, P685
   Jung J, 2018, J BUS ETHICS, V150, P1151, DOI 10.1007/s10551-016-3207-6
   Kleimeier S, 2021, ECON LETT, V205, DOI 10.1016/j.econlet.2021.109936
   Lang QQ, 2023, TECHNOL FORECAST SOC, V191, DOI 10.1016/j.techfore.2023.122480
   Lei YT, 2022, ENERG ECON, V115, DOI 10.1016/j.eneco.2022.106375
   Li CS, 2022, ENERG ECON, V108, DOI 10.1016/j.eneco.2022.105931
   [李广予 LI Guangzi], 2009, [金融研究, Financial Studies], P137
   Li L., 2015, Economic Research Journal, V50, P162
   Li X, 2022, TECHNOL FORECAST SOC, V178, DOI 10.1016/j.techfore.2022.121601
   Lin BQ, 2022, SUSTAIN PROD CONSUMP, V33, P28, DOI 10.1016/j.spc.2022.06.016
   Lin BQ, 2022, INT REV ECON FINANC, V77, P413, DOI 10.1016/j.iref.2021.10.005
   Liu CJ, 2020, ENVIRON RESOUR ECON, V75, P741, DOI 10.1007/s10640-020-00406-3
   Liu PZ, 2021, FINANC RES LETT, V43, DOI 10.1016/j.frl.2021.102141
   Lyu JY, 2020, J CLEAN PROD, V255, DOI 10.1016/j.jclepro.2020.120171
   Ma J., 2020, Tsinghua Financial Review, P31
   McGlade C, 2015, NATURE, V517, P187, DOI 10.1038/nature14016
   Megginson WL, 2014, J BANK FINANC, V48, P276, DOI 10.1016/j.jbankfin.2014.06.011
   MODIGLIANI F, 1958, AM ECON REV, V48, P261
   MYERS SC, 1984, J FINANC ECON, V13, P187, DOI 10.1016/0304-405X(84)90023-0
   Nguyen Q, 2023, INT REV FINANC ANAL, V85, DOI 10.1016/j.irfa.2022.102401
   Nordhaus W., 2013, The Climate Casino: Risk, Uncertainty, and Economics for a Warming World
   Ociepa-Kubicka A, 2017, ENVIRON RES, V156, P284, DOI 10.1016/j.envres.2017.02.027
   Oestreich AM, 2015, J BANK FINANC, V58, P294, DOI 10.1016/j.jbankfin.2015.05.005
   Ren S., 2019, W FORUM, V29, P101
   Ren SG, 2022, ENERG ECON, V112, DOI 10.1016/j.eneco.2022.106157
   Ren XH, 2021, SUSTAIN DEV, V29, P228, DOI 10.1002/sd.2144
   Ren YS, 2024, J ECON BEHAV ORGAN, V217, P227, DOI 10.1016/j.jebo.2023.10.032
   Ren YS, 2023, Q REV ECON FINANC, V90, P77, DOI 10.1016/j.qref.2023.05.006
   Ren YS, 2022, ENERG ECON, V111, DOI 10.1016/j.eneco.2022.106073
   Sen S, 2020, J ENVIRON ECON MANAG, V100, DOI 10.1016/j.jeem.2019.102277
   Sengupta P, 1998, ACCOUNT REV, V73, P459
   Seto KC, 2016, ANNU REV ENV RESOUR, V41, P425, DOI 10.1146/annurev-environ-110615-085934
   Shen H, 2019, Finance Trade Econ., V40, P144
   Thompson P., 2004, The British Accounting Review, V36, P197, DOI [10.1016/j.bar.2003.11.005, DOI 10.1016/J.BAR.2003.11.005]
   Wang B., 2020, Economic Perspectives, P84
   Wang CT, 2023, J CLEAN PROD, V411, DOI 10.1016/j.jclepro.2023.137286
   Wang C, 2022, CHIN J POPUL RESOUR, V20, P217, DOI 10.1016/j.cjpre.2022.09.002
   Wang W, 2022, ENERG ECON, V108, DOI 10.1016/j.eneco.2022.105906
   Wang WD, 2020, J CLEAN PROD, V251, DOI 10.1016/j.jclepro.2019.119690
   Weber O, 2010, BUS STRATEG ENVIRON, V19, P39, DOI 10.1002/bse.636
   Weitzman ML, 2009, REV ECON STAT, V91, P1, DOI 10.1162/rest.91.1.1
   Xiang JJ, 2022, INT REV ECON FINANC, V80, P1025, DOI 10.1016/j.iref.2022.03.006
   Yan H.Z., 2017, J FINANCIAL RES, V2017, P142, DOI DOI 10.12094/1002-7246(2017)06-0142-17
   Yang X., 2018, Economic Research Journal, V53, P133
   Yang XY, 2020, ENERG POLICY, V142, DOI 10.1016/j.enpol.2020.111492
   Zhang HL, 2023, FINANC RES LETT, V53, DOI 10.1016/j.frl.2023.103629
   Zhang YJ, 2021, ENERG ECON, V98, DOI 10.1016/j.eneco.2021.105224
   Zhou L.A., 2005, Q J ECON, V4, P623
NR 82
TC 7
Z9 7
U1 11
U2 31
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 1059-0560
EI 1873-8036
J9 INT REV ECON FINANC
JI Int. Rev. Econ. Financ.
PD MAR
PY 2024
VL 91
BP 138
EP 155
DI 10.1016/j.iref.2024.01.006
EA JAN 2024
PG 18
WC Business, Finance; Economics
WE Social Science Citation Index (SSCI)
SC Business & Economics
GA HY2A7
UT WOS:001162994000001
HC Y
HP N
DA 2025-01-10
ER

PT J
AU de Camargo, RR
   Penso, GA
   Pertille, RH
   Mayer, NA
   dos Santos, CEM
   Citadin, I
AF de Camargo, Robson Rosa
   Penso, Gener Augusto
   Pertille, Rafael Henrique
   Mayer, Newton Alex
   dos Santos, Carlos Eduardo Magalhaes
   Citadin, Idemir
TI Performance of clonal rootstocks for 'BRS-Kampai' peach and own-rooted
   trees in a mild-winter region
SO CIENCIA E AGROTECNOLOGIA
LA English
DT Article
DE Climate adaptation; training systems; selection index; peach production;
   Prunus sp
ID PLUM-BASED ROOTSTOCKS; GRAFT COMPATIBILITY; FRUIT; CULTIVARS; HYBRIDS;
   GROWTH; YIELD; VIGOR; ADAPTABILITY; POPULATION
AB The worldwide main peach-producing are adopting peach training systems with canopy size-controlling clonal rootstocks. However, most peach seedlings commercialised in Brazil are still on seed-propagated rootstocks, which are vigorous and heterogeneous. This study aimed to select rootstocks which induce desirable characteristics of fruit quality, yield efficiency, size control, adaptability and stability in the 'BRS-Kampai' grown in subtropical regions with mild winters. We used adaptability and stability methodology and multivariate selection index to determine yield components and fruit quality. The experiment was conducted in five cycles. The treatments consisted of 'BRS-Kampai' grafted onto 17 clonal rootstocks of Prunus spp. and own-rooted trees. The evaluated variables were yield per tree, yield per area, fruit mass, fruit diameter, fruit firmness, soluble solids content, titratable acidity, canopy volume and yield efficiency. The rootstocks 'Ishtara (R)', 'Genovesa', 'Santa Rosa' and 'Cadaman' always induced low yield and low fruit quality when used as clonal rootstocks for the 'BRS-Kampai' and showed no potential for use as rootstocks in subtropical humid regions with mild winters. The 'BRS-Kampai' own-rooted peach trees or those grafted onto 'Flordaguard', 'Okinawa' are alternatives for peach cultivation under the edaphoclimatic conditions of Pato Branco-PR, although the training and pruning systems must be adjusted due to high vigour. The clonal rootstocks 'Tsukuba-3' and 'Tsukuba-2' induced the highest production performance in the canopy cultivar BRS-Kampai, combining fruit quality, yield with higher stability, and yield efficiency making them the most suitable ones among the studied rootstocks.
C1 [de Camargo, Robson Rosa; Penso, Gener Augusto; Pertille, Rafael Henrique; Citadin, Idemir] Univ Tecnol Fed Parana, Programa Posgrad Agron, Pato Branco, PR, Brazil.
   [Mayer, Newton Alex] Embrapa Clima Temperado, Pelotas, RS, Brazil.
   [dos Santos, Carlos Eduardo Magalhaes] Univ Fed Vicosa UFV, Dept Agron, Vicosa, MG, Brazil.
C3 Pontificia Universidade Catolica do Parana; Universidade Tecnologica
   Federal do Parana; Empresa Brasileira de Pesquisa Agropecuaria
   (EMBRAPA); Universidade Federal de Vicosa
RP Citadin, I (corresponding author), Univ Tecnol Fed Parana, Programa Posgrad Agron, Pato Branco, PR, Brazil.
EM idemir@utfpr.edu.br
RI Penso, Gener/ABD-2838-2020; Santos, Carlos/H-2231-2012; Pertille, Rafael
   Henrique/N-1137-2017; Citadin, Idemir/H-2786-2016
OI Santos, Carlos/0000-0002-0575-7999; Mayer, Newton/0000-0001-6689-8202;
   Pertille, Rafael Henrique/0000-0002-4888-2001; Citadin,
   Idemir/0000-0001-9416-2761; Penso, Gener Augusto/0000-0002-1684-6102
FU National Council for Scientific and Technological Development (CNPq);
   Coordination for the Improvement of Higher Education Personnel (CAPES)
FX We would like to thank the National Council for Scientific and
   Technological Development (CNPq) and the Coordination for the
   Improvement of Higher Education Personnel (CAPES) for their financial
   support. The Intituto de Desenvolvimento Rural do Parana (IDR-Parana)
   and the Parana Meteorological System (SIMEPAR) for allowing us access to
   meteorological data. To EMBRAPA Clima Temperado for the partnership.
CR Alvares CA, 2013, METEOROL Z, V22, P711, DOI 10.1127/0941-2948/2013/0507
   Oliveira JAA, 2018, CROP BREED APPL BIOT, V18, P320, DOI 10.1590/1984-70332018v18n3n47
   [Anonymous], 2008, Mapa de solos do Estado do Parana
   [Anonymous], 2022, Crops and Livestock Products
   Anthony BM, 2021, AGRONOMY-BASEL, V11, DOI 10.3390/agronomy11101961
   Barreto C. F., 2017, African Journal of Agricultural Research, V12, P2933, DOI 10.5897/ajar2017.12626
   Basile B, 2003, TREE PHYSIOL, V23, P695, DOI 10.1093/treephys/23.10.695
   Raseira MDB, 2010, REV BRAS FRUTIC, V32, P1275, DOI 10.1590/S0100-29452011005000009
   Beckman TG, 2006, ACTA HORTIC, P289, DOI 10.17660/ActaHortic.2006.713.42
   BECKMAN TG, 1992, J AM SOC HORTIC SCI, V117, P377, DOI 10.21273/JASHS.117.3.377
   Bhering L. L., 2021, Estatistica experimental no Rbio
   Byrne D. H., 2012, Fruit breeding, P312
   Caruso T, 1997, J AM SOC HORTIC SCI, V122, P673, DOI 10.21273/JASHS.122.5.673
   Costa G, 2022, SCI HORTIC-AMSTERDAM, V296, DOI 10.1016/j.scienta.2022.110895
   Cruz C. D., 2015, Modelos biometricos aplicados ao melhoramento genetico, V1
   Da Silva D, 2014, ANN BOT-LONDON, V114, P643, DOI 10.1093/aob/mcu033
   De Jong T. M., 1994, California Tree Fruit Settlement Report
   Silva MGD, 2012, REV BRAS FRUTIC, V34, P525, DOI 10.1590/S0100-29452012000200026
   Edin M., 1994, Arboriculture Fruitiere, P20
   Faust M., 1999, Horticultural Reviews, V23, P179, DOI 10.1002/9780470650752.ch4
   Felipe AJ, 2009, HORTSCIENCE, V44, P196, DOI 10.21273/HORTSCI.44.1.196
   FINARDI N.L., 1998, A Cultura do Pessegueiro, P100
   Freire C. J. S., 2014, Adubacao e correcao do solo, P259
   Giorgi M, 2005, SCI HORTIC-AMSTERDAM, V107, P36, DOI 10.1016/j.scienta.2005.06.003
   Iglesias I, 2021, ACTA HORTIC, V1304, P163, DOI 10.17660/ActaHortic.2021.1304.24
   Iglesias Ignasi, 2020, Revista Fruticola, V42, P8
   Iglesias I, 2022, SCI HORTIC-AMSTERDAM, V296, DOI 10.1016/j.scienta.2022.110899
   Instituto Brasileiro de Geografia e Estatistica-IBGE, 2022, Producao pessego
   Layne R.E.C., 1987, ROOTSTOCKS FRUIT CRO, P185
   Lesmes-Vesga RA, 2022, HORTICULTURAE, V8, DOI 10.3390/horticulturae8070602
   Loreti F., 1992, Acta Horticulturae, P107
   Manganaris GA, 2022, SCI HORTIC-AMSTERDAM, V305, DOI 10.1016/j.scienta.2022.111390
   Massai R., 2004, Acta Horticulturae, P185
   Mathias C, 2008, REV BRAS FRUTIC, V30, P165, DOI 10.1590/S0100-29452008000100030
   Mayer Newton Alex, 2006, Rev. Bras. Frutic., V28, P231, DOI 10.1590/S0100-29452006000200017
   Mayer Newton Alex, 2021, Rev. Ceres, V68, P230, DOI [10.1590/0034-737X202168030009, 10.1590/0034-737x202168030009]
   Mayer NA, 2021, REV BRAS FRUTIC, V43, DOI 10.1590/0100-29452021115
   Mayer NA, 2020, SCI HORTIC-AMSTERDAM, V273, DOI 10.1016/j.scienta.2020.109609
   Mayer NA, 2017, REV BRAS FRUTIC, V39, DOI 10.1590/0100-29452017355
   Mestre L, 2015, SCI HORTIC-AMSTERDAM, V192, P475, DOI 10.1016/j.scienta.2015.05.020
   Minas IS, 2023, CROP PROD SCI HORTIC, P54, DOI 10.1079/9781789248456.0003
   Minas IS, 2018, SCI HORTIC-AMSTERDAM, V235, P307, DOI 10.1016/j.scienta.2018.01.028
   MULAMBA NN, 1978, EGYPT J GENET CYTOL, V7, P40
   NASR TA, 1977, SCI HORTIC-AMSTERDAM, V7, P225, DOI 10.1016/0304-4238(77)90019-X
   Natural Resources Conservation Service-U.S, 2022, Department of Agriculture. Inceptsols
   Neri D, 2022, SCI HORTIC-AMSTERDAM, V305, DOI 10.1016/j.scienta.2022.111348
   Oldoni CM, 2019, REV BRAS FRUTIC, V41, DOI 10.1590/0100-29452019086
   Olmstead MA, 2010, SCI HORTIC-AMSTERDAM, V124, P78, DOI 10.1016/j.scienta.2009.12.022
   Orazem P, 2011, FOOD CHEM, V124, P1691, DOI 10.1016/j.foodchem.2010.07.078
   Penso GA, 2018, REV BRAS FRUTIC, V40, DOI 10.1590/0100-29452018420
   Pereira FM, 2007, REV BRAS FRUTIC, V29, P172, DOI 10.1590/S0100-29452007000100036
   Pereira J. F. M., 2014, Pessegueiro, P282
   Pinochet J, 2002, ACTA HORTIC, P707, DOI 10.17660/ActaHortic.2002.592.99
   Quadros L. E., 2019, Ambiente & Agua, V12, P2258
   RAMMING DW, 1983, HORTSCIENCE, V18, P376
   Raseira M. C. B., 2014, Cultivares: Descricao e recomendacao, P73
   Reig G, 2020, SCI HORTIC-AMSTERDAM, V262, DOI 10.1016/j.scienta.2019.109035
   Reig G, 2019, SCI HORTIC-AMSTERDAM, V243, P392, DOI 10.1016/j.scienta.2018.08.038
   Reighard G. L., 2008, The peach: botany, production and uses, P193, DOI 10.1079/9781845933869.0193
   Reighard GL, 2002, ACTA HORTIC, P421, DOI 10.17660/ActaHortic.2002.592.57
   Reisser Jr C., 2014, Irrigacao, P328
   Sobierajski GDR, 2021, PESQUI AGROPECU BRAS, V56, DOI [10.1590/s1678-3921.pab2021.v56.02043, 10.1590/S1678-3921.pab2021.v56.02043]
   Rossi Andrea de, 2004, Rev. Bras. Frutic., V26, P446, DOI 10.1590/S0100-29452004000300018
   Rossi C.E., 2002, Arq. Inst. Biol., V69, P43, DOI 10.1590/1808-1657v69n2p0432002
   Saini AK, 2020, SCI HORTIC-AMSTERDAM, V268, DOI 10.1016/j.scienta.2020.109380
   Santana AS, 2020, CROP BREED APPL BIOT, V20, DOI 10.1590/1984-70332020v20n2a34
   Scariotto S, 2013, SCI HORTIC-AMSTERDAM, V155, P111, DOI 10.1016/j.scienta.2013.03.019
   Shahkoomahally S, 2021, FOOD SCI NUTR, V9, P401, DOI 10.1002/fsn3.2005
   SHERMAN WB, 1991, HORTSCIENCE, V26, P427, DOI 10.21273/HORTSCI.26.4.427
   Soil Survey Staf, 2022, Keys to Soil Taxonomy, V13
   Solari LI, 2006, PHYSIOL PLANTARUM, V128, P324, DOI 10.1111/j.1399-3054.2006.00747.x
   Souza AD, 2016, J SEED SCI, V38, P322, DOI 10.1590/2317-1545v38n4164650
   Weibel AM, 2011, ACTA HORTIC, V903, P815, DOI 10.17660/ActaHortic.2011.903.113
   Yan W, 2006, CAN J PLANT SCI, V86, P623, DOI 10.4141/P05-169
   Yan WK, 2007, CROP SCI, V47, P643, DOI 10.2135/cropsci2006.06.0374
   Yan WK, 2000, CROP SCI, V40, P597, DOI 10.2135/cropsci2000.403597x
   YOUNG E, 1984, J AM SOC HORTIC SCI, V109, P548
   Zarrouk O, 2005, SCI HORTIC-AMSTERDAM, V106, P502, DOI 10.1016/j.scienta.2005.04.011
   Zarrouk O, 2006, HORTSCIENCE, V41, P1389, DOI 10.21273/HORTSCI.41.6.1389
NR 79
TC 0
Z9 0
U1 2
U2 2
PU UNIV FEDERAL LAVRAS-UFLA
PI LAVRAS
PA CAIXA POSTAL 3037, LAVRAS, MG 37200-000, BRAZIL
SN 1413-7054
EI 1981-1829
J9 CIENC AGROTEC
JI Cienc. Agrotec.
PY 2024
VL 48
AR e003524
DI 10.1590/1413-7054202448003524
PG 13
WC Agriculture, Multidisciplinary; Agronomy
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA YY4F4
UT WOS:001272028200001
OA gold
DA 2025-01-10
ER

PT J
AU Powell, F
   Levine, A
   Ordonez-Gauger, L
AF Powell, Farrah
   Levine, Arielle
   Ordonez-Gauger, Lucia
TI Climate adaptation in the market squid fishery: fishermen responses to
   past variability associated with El Nino Southern Oscillation cycles
   inform our understanding of adaptive capacity in the face of future
   climate change
SO CLIMATIC CHANGE
LA English
DT Article
DE California Current; Diversification; Fishing strategy; Flexibility;
   Mobility; Range shift
ID FISHING COMMUNITIES; LOLIGO-OPALESCENS; VULNERABILITY; STRATEGIES;
   MANAGEMENT; IMPACTS; SHIFTS; DIVERSIFICATION; LIVELIHOODS; DYNAMICS
AB Evaluating the strategies fishermen have used to respond to short-term climate variability in the past can help inform our understanding of the adaptive capacity of a fishery in the face of anticipated future change. Using historic fishery landings, climate records, and fishermen surveys, we document how market squid fishermen respond to high seasonal and interannual climate variability associated with the El Nino Southern Oscillation (ENSO) and responses to hypothetical future scenarios of low abundance and range shift. Overall, fishermen have been able to adapt to dramatic shifts in the geographic range of the fishery given their high mobility, with fishermen with larger vessels expressing a willingness to travel greater distances than those with smaller vessels. Nearly half of fishermen stated that they would switch fisheries if market squid decreased dramatically in abundance, although fishermen who were older, had been in the fishery longer, were highly dependent on squid for income, and held only squid and/or coastal pelagic finfish permits were less likely to switch to another fishery in a scenario of lower abundance. While market squid fishermen have exhibited highly adaptive behavior in the face of past climate variability, recent (and likely future) range shifts across state boundaries, as well as closures of other fisheries, constrain fishermen's choices and emphasize the need for flexibility in management systems. Our study highlights the importance of considering connectivity between fisheries and monitoring and anticipating trans-jurisdictional range shifts to facilitate adaptive fishery management.
C1 [Powell, Farrah; Levine, Arielle; Ordonez-Gauger, Lucia] San Diego State Univ, Dept Geog, San Diego, CA 92182 USA.
   [Powell, Farrah] Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USA.
C3 California State University System; San Diego State University;
   University of California System; University of California Santa Barbara
RP Powell, F (corresponding author), San Diego State Univ, Dept Geog, San Diego, CA 92182 USA.; Powell, F (corresponding author), Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USA.
EM fpowell@sdsu.edu
RI Levine, Arielle/AAA-4817-2021
OI Powell, Farrah/0000-0002-0020-042X
FU National Science Foundation Coastal SEES Collaborative Research Grant
   [1600149]; Directorate For Geosciences; Division Of Ocean Sciences
   [1600149] Funding Source: National Science Foundation
FX We would like to acknowledge our funding source (National Science
   Foundation Coastal SEES Collaborative Research Grant, Award #1600149).
CR Aguilera SE, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0118992
   Alder J., 2006, On the multiple uses of forage fish: From ecosystems to markets, DOI DOI 10.14288/1.0074759
   Allison EH, 2001, MAR POLICY, V25, P377, DOI 10.1016/S0308-597X(01)00023-9
   Anderson SC, 2017, P NATL ACAD SCI USA, V114, P10797, DOI 10.1073/pnas.1702506114
   [Anonymous], 2018, Chinook Observer
   [Anonymous], Marine fisheries: experimental fishing permits, A.B. 1573, 2017-2018 Reg. Sess. Cal. 2018
   Bates K., 2018, Proposal for a Small-Scale Trial Squid Fishery North of Point Arena, California: Offered as an amendment/addition to the California Fishery Management Plan
   Bennett NJ, 2016, REG ENVIRON CHANGE, V16, P907, DOI 10.1007/s10113-015-0839-5
   Buil MP, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.612874
   Cai WJ, 2018, NATURE, V564, P201, DOI 10.1038/s41586-018-0776-9
   Cavole LM, 2016, OCEANOGRAPHY, V29, P273, DOI 10.5670/oceanog.2016.32
   CDFW [California Department of Fish and Wildlife], 2005, Market squid fishery management plan
   Chambers S, 2016, CALIFORNIAS SQUID SH
   Chasco BE, 2022, MAR COAST FISH, V14, DOI 10.1002/mcf2.10190
   Chavez F.P., 2017, Readying California Fisheries for Climate Change
   Checkley DM, 2009, PROG OCEANOGR, V83, P49, DOI 10.1016/j.pocean.2009.07.028
   Cinner JE, 2012, GLOBAL ENVIRON CHANG, V22, P12, DOI 10.1016/j.gloenvcha.2011.09.018
   Cinner JE, 2018, NAT CLIM CHANGE, V8, P117, DOI 10.1038/s41558-017-0065-x
   Cinner JE, 2015, NAT CLIM CHANGE, V5, P872, DOI 10.1038/NCLIMATE2690
   Coulthard S, 2015, SOCIOL RURALIS, V55, P275, DOI 10.1111/soru.12093
   Coulthard S, 2009, ADAPTING TO CLIMATE CHANGE: THRESHOLDS, VALUES, GOVERNANCE, P255
   Crona B, 2020, ONE EARTH, V3, P32, DOI 10.1016/j.oneear.2020.06.013
   Dubik BA, 2019, MAR POLICY, V99, P243, DOI 10.1016/j.marpol.2018.10.032
   Ess C., 2020, National Fishermen Forum
   FAO, 2022, The state of World Fisheries and Aquaculture 2022. Towards Blue Transformation, DOI [10.4060/ca9229en, 10.4060/cc0461en, DOI 10.4060/CC0461EN, DOI 10.4060/CA9229EN]
   Forsythe JW, 2004, MAR FRESHWATER RES, V55, P331, DOI 10.1071/MF03146
   Frawley TH, 2021, FISH FISH, V22, P280, DOI 10.1111/faf.12519
   Gourlie D., 2017, J Environ Law, V47, P179
   Halpern BS, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms8615
   Hollowed AB, 2001, PROG OCEANOGR, V49, P257, DOI 10.1016/S0079-6611(01)00026-X
   Islam MM, 2014, REG ENVIRON CHANGE, V14, P281, DOI 10.1007/s10113-013-0487-6
   Jackson GD, 2003, MAR BIOL, V142, P925, DOI 10.1007/s00227-002-1005-4
   Johnson TR, 2014, HUM ECOL REV, V20, P97
   Kasperski S, 2013, P NATL ACAD SCI USA, V110, P2076, DOI 10.1073/pnas.1212278110
   Lindegren M, 2018, REV FISH SCI AQUAC, V26, P400, DOI 10.1080/23308249.2018.1445980
   MAFMC [Mid-Atlantic Fishery Management Council], 2021, ASMFC MAFMC APPR CHA
   Maguire M., 2017, ALL IRELAND J HIGHER, V9
   Miller DD, 2018, GLOBAL CHANGE BIOL, V24, pE1, DOI 10.1111/gcb.13829
   Miller M., 2015, Alaska Public Media
   Mills KE, 2013, OCEANOGRAPHY, V26, P191, DOI 10.5670/oceanog.2013.27
   Morejohn G.V., 1978, California Department of Fish and Game Fish Bulletin, P67
   National Marine Fisheries Service (NMFS), 2018, NOAA TECH MEMO NMFS
   NOAA, 2019, COLD WARM EP SEAS
   NOAA [National Oceanic and Atmospheric Administration], 1993, ATL SEA SCALL FISH F
   ODFW [Oregon Department of Fish and Wildlife], 2021, AG IT SUMM EXH ATT 1
   Ojea E, 2020, ONE EARTH, V2, P544, DOI 10.1016/j.oneear.2020.05.012
   Olsen W., 2004, Developments in Sociology, V20, P103, DOI DOI 10.4324/9781315838120
   Palacios DM, 2004, J GEOPHYS RES-OCEANS, V109, DOI 10.1029/2004JC002380
   Patterson W., 2018, CDFW Projection and Datum Guidelines
   Pebesma E, 2018, R J, V10, P439
   Perretti CT, 2016, FISH OCEANOGR, V25, P491, DOI 10.1111/fog.12167
   PFMC [Pacific Fishery Management Council], 2008, STAT PAC COAST PEL S
   Pinsky ML, 2018, SCIENCE, V360, P1189, DOI 10.1126/science.aat2360
   Pinsky ML, 2014, OCEANOGRAPHY, V27, P146, DOI 10.5670/oceanog.2014.93
   Pinsky ML, 2012, CLIMATIC CHANGE, V115, P883, DOI 10.1007/s10584-012-0599-x
   Pomeroy C., 2010, Californias North Coast Fishing Communities Historical Perspective and Recent Trends, P340
   Pomeroy C., 2002, CALIFORNIAS WETFISH, P46
   Porzio D., 2008, Status of the Fisheries Report: Market Squid
   R Core Team, 2020, R: A Language and Environment for Statistical Computing
   Rahaim N., 2016, Monterey County Weekly
   Ralston S, 2018, FISH RES, V199, P12, DOI 10.1016/j.fishres.2017.11.009
   Reddy SMW, 2013, ECOL APPL, V23, P726, DOI 10.1890/12-1196.1
   Reiss CS, 2004, CAL COOP OCEAN FISH, V45, P87
   Reyers B, 2018, ANNU REV ENV RESOUR, V43, P267, DOI 10.1146/annurev-environ-110615-085349
   Robinson JPW, 2020, SCI ADV, V6, DOI 10.1126/sciadv.aaz0587
   Rubio I, 2022, ICES J MAR SCI, V79, P532, DOI 10.1093/icesjms/fsab065
   Savo V, 2017, FISH FISH, V18, P877, DOI 10.1111/faf.12212
   Schwing FB, 2010, J MARINE SYST, V79, P245, DOI 10.1016/j.jmarsys.2008.11.027
   Seara T, 2016, GLOBAL ENVIRON CHANG, V38, P49, DOI 10.1016/j.gloenvcha.2016.01.006
   Shaffril HAM, 2015, INT J CLIM CHANG STR, V7, P516, DOI 10.1108/IJCCSM-07-2014-0089
   Sievanen L, 2014, MARIT STUD, V13, DOI 10.1186/s40152-014-0009-2
   Sims DW, 2001, P ROY SOC B-BIOL SCI, V268, P2607, DOI 10.1098/rspb.2001.1847
   Soley T., 2018, Undark Magazine
   Stoll JS, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0178266
   Suatoni L., 2020, On the Move: How Fisheries Policy Can Address Shifting Fish Stocks - Fact Sheet
   Tims D, 2021, YACHATSNEWS
   Van Noord JE, 2017, MAR ECOL-EVOL PERSP, V38, DOI 10.1111/maec.12433
   van Putten IE, 2017, MAR POLICY, V76, P169, DOI 10.1016/j.marpol.2016.11.034
   Whitney CK, 2017, ECOL SOC, V22, DOI 10.5751/ES-09325-220222
   Wilson J, 2017, ECOL SOC, V22, DOI 10.5751/ES-09356-220243
   Xiu P, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-21247-7
   Young T, 2019, ICES J MAR SCI, V76, P93, DOI 10.1093/icesjms/fsy140
   Zeidberg LD, 2006, FISH B-NOAA, V104, P46
NR 83
TC 11
Z9 12
U1 0
U2 12
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 JUL
PY 2022
VL 173
IS 1-2
AR 1
DI 10.1007/s10584-022-03394-z
PG 21
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA 2Q8BM
UT WOS:000820643300001
PM 35811834
OA Green Published, Bronze
DA 2025-01-10
ER

PT J
AU Engelhard, GH
   Howes, EL
   Pinnegar, JK
   Le Quesne, WJF
AF Engelhard, Georg H.
   Howes, Ella L.
   Pinnegar, John K.
   Le Quesne, Will J. F.
TI Assessing the risk of climate change to aquaculture: a national-scale
   case study for the Sultanate of Oman
SO CLIMATE RISK MANAGEMENT
LA English
DT Article
DE Climate adaptation; Aquaculture; Climate resilience; Climate risk
   assessment; Food security; Sultanate of Oman; Seabream culture; Shrimp
   culture
ID FISHERIES; VULNERABILITY; TEMPERATURE; WELFARE; HEALTH; IMPACT; FUTURE
AB Aquaculture is expanding globally and is an increasingly important component of world food security. However, climate change can impact aquaculture through a variety of mechanisms varying by location and aquaculture type with implications for future productivity. Understanding the risks that climate change poses on different culture systems in different locations is important to enable the design of targeted adaptation and resilience building actions. Here we present an aquaculture climate risk assessment framework, applied to the aquaculture sector of the Sultanate of Oman, that identifies the sensitivity and exposure of different components of the sector to climate change risk.Oman has aspirations to significantly expand aquaculture over the next decade focussing on coastal shrimp ponds, finfish sea cages, land-based recirculating aquaculture systems, and ponds and raceways. We quantify overall climate risk as the combination of four risks: (1) species' temperature sensitivity, (2) flooding and storm surge exposure, (3) low-oxygen hazard and (4) disease vulnerability. Shrimp culture is identified as highest risk due to high exposure of shrimp ponds to flooding and storm surges, and high disease vulnerability. Seabream cage farming also faces high risk due to high thermal sensitivity and high potential of low-oxygen levels affecting sea cages. Following the risk assessment a stakeholder workshop was conducted to identify targeted adaptation measures for the different components of the sector. The framework for assessing climate risk to aquaculture demonstrated here is equally applicable at the regional, national or sub-national scale to support design of targeted resilience building actions and enhance food security.
C1 [Engelhard, Georg H.; Howes, Ella L.; Pinnegar, John K.; Le Quesne, Will J. F.] Ctr Environm Fisheries & Aquaculture Sci Cefas, Int Marine Climate Change Ctr iMC3, Lowestoft NR33 0HT, Suffolk, England.
   [Engelhard, Georg H.; Pinnegar, John K.] Univ East Anglia UEA, Sch Environm Sci, Norwich NR4 7TJ, Norfolk, England.
C3 Centre for Environment Fisheries & Aquaculture Science
RP Engelhard, GH (corresponding author), Ctr Environm Fisheries & Aquaculture Sci Cefas, Int Marine Climate Change Ctr iMC3, Lowestoft NR33 0HT, Suffolk, England.
EM georg.engelhard@cefas.co.uk
RI Pinnegar, John/C-4400-2012
OI Engelhard, Georg H./0000-0002-7821-7029
FU HSBC [C8004]
FX This study was funded by HSBC through contract C8004 Vulnerability of
   Fisheries to Climate Change in Oman. We are grateful for constructive
   feedback and discussions with David Ramos, Dawood Al Yahyai, Ed Peeler,
   Keith Jeffery, Grant Stentiford and Elena Couce, and to Caroline Whybrow
   for administrative support. The generation of ideas around adaptation
   has benefited from an online stakeholder workshop on 8-9 December 2020,
   and we acknowledge all those who contributed to the workshop with ideas
   and action prioritisation.
CR Acharya SS, 2016, DEEP-SEA RES PT I, V115, P240, DOI 10.1016/j.dsr.2016.07.004
   Ahmad I, 2017, AQUACULT INT, V25, P1215, DOI 10.1007/s10499-016-0108-8
   Al-Awadhi T, 2018, HUM ECOL RISK ASSESS, V24, P667, DOI 10.1080/10807039.2017.1396441
   Al-Buloshi A., 2014, Journal of Earth Science & Climatic Change, V5, P238
   Al-Gheilani H. M., 2011, Sultan Qaboos University Research Journal - Agricultural and Marine Sciences, V16, P23
   Al-Rashdi K. M., 2008, Sultan Qaboos University Research Journal - Agricultural and Marine Sciences, V13, P53
   Al-Rashdi K.M, 2011, AQUACULTURE RES DEV, P44
   Al-Rashdi KM., 2018, ASIAN J FISHERIES AQ, V2, P1
   Al-Yahyai D.S., 2004, AGR FISHERIES RES B, V1, P5
   AlYahyai D. S., 2017, NATL AQUACULTURE SEC
   [Anonymous], 2017, INNOTEC, DOI DOI 10.26461/13.02
   Araújo-Luna R, 2018, AQUAC RES, V49, P3845, DOI 10.1111/are.13851
   [Barange M. FAO FAO], 2018, Fisheries and, P654
   Basurco B., 2011, Sparidae: Biology and aquaculture of gilthead sea bream and other species, P1
   Bergh O, 2007, CLIMATE CHANGE ITS C
   Berillis P, 2016, OPEN LIFE SCI, V11, P270, DOI 10.1515/biol-2016-0028
   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
   Cheung WWL, 2013, NATURE, V497, P365, DOI 10.1038/nature12156
   Doubleday ZA, 2013, AQUACULT ENV INTERAC, V3, P163, DOI 10.3354/aei00058
   Elliott JM, 2010, J FISH BIOL, V77, P1793, DOI 10.1111/j.1095-8649.2010.02762.x
   FAO, 2022, The state of World Fisheries and Aquaculture 2022. Towards Blue Transformation, DOI [10.4060/ca9229en, 10.4060/cc0461en, DOI 10.4060/CC0461EN, DOI 10.4060/CA9229EN]
   Field C.B., 2012, MANAGING RISKS EXTRE
   Fritz HM, 2010, INDIAN OCEAN TROPICAL CYCLONES AND CLIMATE CHANGE, P255, DOI 10.1007/978-90-481-3109-9_30
   Gubbins M, 2013, MCCIP SCI REV, P318, DOI DOI 10.14465/2013.ARC33.318-327
   Handisyde N, 2017, FISH FISH, V18, P466, DOI 10.1111/faf.12186
   Hereher M, 2020, ENVIRON EARTH SCI, V79, DOI 10.1007/s12665-020-09113-0
   Hooper C, 2020, VIRUSES-BASEL, V12, DOI 10.3390/v12101120
   IPCC, 2019, OCEAN HYDROSPHERE CH
   IPCC, 2001, IPCC 2001 CLIM CHANG, P219
   Jennings S, 2016, FISH FISH, V17, P893, DOI 10.1111/faf.12152
   Kamermans P., 2020, CLIMATE CHANGE EUROP, DOI [10.25592/uhhfdm.804, DOI 10.25592/UHHFDM.804]
   Kaschner K., 2016, AQUAMAPS PREDICTED R
   Nguyen KAT, 2021, AQUACULT REP, V19, DOI 10.1016/j.aqrep.2021.100606
   Leung TLF, 2013, J APPL ECOL, V50, P215, DOI 10.1111/1365-2644.12017
   Lightner DV, 2012, J INVERTEBR PATHOL, V110, P184, DOI 10.1016/j.jip.2012.03.007
   Lincoln S., 2020, ROPME MARINE CLIMATE
   Little DC, 2016, P NUTR SOC, V75, P274, DOI 10.1017/S0029665116000665
   MAFW, 2019, FISH LAB OUTC PROM E, P57
   Maltby K.M., 2021, ROPME MARINE CLIMATE
   Mardones J.I., 2020, PICES SCI REP, P66
   McLean E., 2011, ENV BETTER MANAGEMEN, P80
   Monnereau I, 2017, FISH FISH, V18, P717, DOI 10.1111/faf.12199
   Noori R, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0212790
   Oppenheimer M, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1039
   Palenzuela O, 2014, INT J PARASITOL, V44, P189, DOI 10.1016/j.ijpara.2013.10.005
   Pavlidis M., 2011, Sparidae: Biology and aquaculture of gilthead sea bream and other species
   Payne MR, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2018086118
   Peeler E, 2018, DEV AQUATIC ANIMAL H
   Pernet F, 2021, ICES J MAR SCI, V78, P315, DOI 10.1093/icesjms/fsaa248
   Pinnegar JK, 2019, ICES J MAR SCI, V76, P1353, DOI 10.1093/icesjms/fsz052
   Piontkovski S. A., 2016, International Aquatic Research, V8, P49, DOI 10.1007/s40071-016-0124-3
   Piontkovski S. A., 2015, International Journal of Environmental Studies, V72, P256, DOI 10.1080/00207233.2015.1012361
   Poulain Florence, 2018, FAO Fisheries and Aquaculture Technical Paper, V627, P535
   Prins T, 2015, THESIS UTRECHT U NET, P150
   Queste BY, 2018, GEOPHYS RES LETT, V45, P4143, DOI 10.1029/2017GL076666
   Rafiq L, 2015, ADV SPACE RES, V56, P2235, DOI 10.1016/j.asr.2015.07.039
   Sainsbury NC, 2021, GLOBAL ENVIRON CHANG, V69, DOI 10.1016/j.gloenvcha.2021.102228
   SCHURMANN H, 1991, J EXP BIOL, V157, P75
   Seekao C, 2018, J FLOOD RISK MANAG, V11, pS805, DOI 10.1111/jfr3.12259
   Shepon A, 2021, GLOBAL ENVIRON CHANG, V69, DOI 10.1016/j.gloenvcha.2021.102285
   Soto Doris, 2018, FAO Fisheries and Aquaculture Technical Paper, V627, P465
   Stentiford GD, 2012, J INVERTEBR PATHOL, V110, P141, DOI 10.1016/j.jip.2012.03.013
   Theodorou JA, 2020, AQUACULT ECON MANAG, V24, P273, DOI 10.1080/13657305.2019.1708994
   Troell M, 2014, P NATL ACAD SCI USA, V111, P13257, DOI 10.1073/pnas.1404067111
   Vigen J., 2008, THESIS U BERGEN BERG, P1
   Walsh KJE, 2019, TROP CYCLONE RES REV, V8, P240, DOI 10.6057/2019TCRR04.04
NR 67
TC 11
Z9 12
U1 2
U2 29
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2212-0963
J9 CLIM RISK MANAG
JI CLIM. RISK MANAG.
PY 2022
VL 35
AR 100416
DI 10.1016/j.crm.2022.100416
EA FEB 2022
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 0D6CX
UT WOS:000776082300006
OA gold, Green Accepted
DA 2025-01-10
ER

PT J
AU Chan, D
   Rigden, A
   Proctor, J
   Chan, PW
   Huybers, P
AF Chan, Duo
   Rigden, Angela
   Proctor, Jonathan
   Chan, Pak Wah
   Huybers, Peter
TI Differences in Radiative Forcing, Not Sensitivity, Explain Differences
   in Summertime Land Temperature Variance Change Between CMIP5 and CMIP6
SO EARTHS FUTURE
LA English
DT Article
DE continental temperature variability; extreme events; soil moisture;
   radiative forcing; evapotranspiration; CMIP
ID SOIL-MOISTURE; CLIMATE; VARIABILITY; HUMIDITY
AB How summertime temperature variability will change with warming has important implications for climate adaptation and mitigation. CMIP5 simulations indicate a compound risk of extreme hot temperatures in western Europe from both warming and increasing temperature variance. CMIP6 simulations, however, indicate only a moderate increase in temperature variance that does not covary with warming. To explore this intergenerational discrepancy in CMIP results, we decompose changes in monthly temperature variance into those arising from changes in sensitivity to forcing and changes in forcing variance. Across models, sensitivity increases with local warming in both CMIP5 and CMIP6 at an average rate of 5.7 ([3.7, 7.9]; 95% c.i.) x 10(-3)degrees C per W m(-2) per degrees C warming. We use a simple model of moist surface energetics to explain increased sensitivity as a consequence of greater atmospheric demand (similar to 70%) and drier soil (similar to 40%) that is partially offset by the Planck feedback (similar to-10%). Conversely, forcing variance is stable in CMIP5 but decreases with warming in CMIP6 at an average rate of -21 ([-28, -15]; 95% c.i.) W-2 m(-4) per degrees C warming. We examine scaling relationships with mean cloud fraction and find that mean forcing variance decreases with decreasing cloud fraction at twice the rate in CMIP6 than CMIP5. The stability of CMIP6 temperature variance is, thus, a consequence of offsetting changes in sensitivity and forcing variance. Further work to determine which models and generations of CMIP simulations better represent changes in cloud radiative forcing is important for assessing risks associated with increased temperature variance.
C1 [Chan, Duo] Woods Hole Oceanog Inst, Dept Phys Oceanog, Woods Hole, MA 02543 USA.
   [Chan, Duo; Rigden, Angela; Huybers, Peter] Harvard Univ, Dept Earth & Planetary Sci, 20 Oxford St, Cambridge, MA 02138 USA.
   [Proctor, Jonathan] Harvard Univ, Ctr Environm, Cambridge, MA 02138 USA.
   [Proctor, Jonathan] Harvard Univ, Data Sci Initiat, Cambridge, MA 02138 USA.
   [Chan, Pak Wah] Univ Exeter, Coll Engn Math & Phys Sci, Exeter, Devon, England.
C3 Woods Hole Oceanographic Institution; Harvard University; Harvard
   University; Harvard University; University of Exeter
RP Chan, D (corresponding author), Woods Hole Oceanog Inst, Dept Phys Oceanog, Woods Hole, MA 02543 USA.; Chan, D (corresponding author), Harvard Univ, Dept Earth & Planetary Sci, 20 Oxford St, Cambridge, MA 02138 USA.
EM duo.chan@whoi.edu
RI Chan, Duo/AAO-3246-2020; Chan, Pak Wah/AHC-3743-2022
OI Huybers, Peter/0000-0002-3734-8145; Proctor,
   Jonathan/0000-0001-8053-8828; CHAN, DUO/0000-0002-8573-5115; Chan, Pak
   Wah/0000-0003-1843-5566
FU Harvard Global Institute; NSF [1903657]; Woods Hole Oceanographic
   Institute Weston Howland Jr.; Div Atmospheric & Geospace Sciences;
   Directorate For Geosciences [1903657] Funding Source: National Science
   Foundation
FX Conversations with L. Vargas Zeppetello and D. Battisti improved the
   content of this manuscript. This study was supported by the Harvard
   Global Institute and NSF (Award 1903657). D. Chan was also supported by
   the Woods Hole Oceanographic Institute Weston Howland Jr. Postdoctoral
   Fellowship.
CR [Anonymous], 2009, MEASUREMENT ERROR MO
   Berg A, 2018, J CLIMATE, V31, P4865, DOI 10.1175/JCLI-D-17-0757.1
   Bodas-Salcedo A, 2008, J GEOPHYS RES-ATMOS, V113, DOI 10.1029/2007JD009620
   Chan D, 2020, GEOPHYS RES LETT, V47, DOI 10.1029/2020GL087624
   Christidis N, 2013, GEOPHYS RES LETT, V40, P589, DOI 10.1002/grl.50159
   Dafka S, 2019, J GEOPHYS RES-ATMOS, V124, P12741, DOI 10.1029/2019JD031203
   Deb P, 2020, EARTHS FUTURE, V8, DOI 10.1029/2020EF001671
   Duan SQQ, 2020, GEOPHYS RES LETT, V47, DOI 10.1029/2020GL090997
   Emanuel K, 2008, B AM METEOROL SOC, V89, P347, DOI 10.1175/BAMS-89-3-347
   Eyring V, 2016, GEOSCI MODEL DEV, V9, P1937, DOI 10.5194/gmd-9-1937-2016
   Fischer EM, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2012GL052730
   Fischer EM, 2009, CLIM DYNAM, V33, P917, DOI 10.1007/s00382-008-0473-8
   GREGORY JM, 1995, Q J ROY METEOR SOC, V121, P1451, DOI 10.1256/smsqj.52610
   Harris I, 2020, SCI DATA, V7, DOI 10.1038/s41597-020-0453-3
   Held IM, 2000, ANNU REV ENERG ENV, V25, P441, DOI 10.1146/annurev.energy.25.1.441
   Heymsfield AJ, 1998, GEOPHYS RES LETT, V25, P1343, DOI 10.1029/98GL01089
   Hoag H., 2014, Nature, V16, P636, DOI [10.1038/nature.2014.16250, DOI 10.1038/NATURE.2014.16250]
   Holmes CR, 2016, J CLIMATE, V29, P2221, DOI 10.1175/JCLI-D-14-00735.1
   Horton RM, 2016, CURR CLIM CHANGE REP, V2, P242, DOI 10.1007/s40641-016-0042-x
   Huguenin MF, 2020, GEOPHYS RES LETT, V47, DOI 10.1029/2019GL086132
   Huntingford C, 2013, NATURE, V500, P327, DOI 10.1038/nature12310
   Jian BD, 2020, CLIM DYNAM, V54, P5145, DOI 10.1007/s00382-020-05277-4
   Jones M.B., 1985, Techniques in measuring bioproductivity and photosynthesis, V2nd, P26, DOI DOI 10.1016/B978-0-08-031999-5.50013-3
   Lenderink G, 2007, CLIMATIC CHANGE, V81, P233, DOI 10.1007/s10584-006-9229-9
   Markovsky I, 2007, SIGNAL PROCESS, V87, P2283, DOI 10.1016/j.sigpro.2007.04.004
   McKinnon KA, 2016, J GEOPHYS RES-ATMOS, V121, P8849, DOI 10.1002/2016JD025292
   Murray SA, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-51074-3
   Pascolini-Campbell M, 2021, NATURE, V593, P543, DOI 10.1038/s41586-021-03503-5
   Philipona R, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL023624
   Price JD, 2002, Q J ROY METEOR SOC, V128, P2059, DOI 10.1256/003590002320603539
   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]
   Rasmijn LM, 2018, NAT CLIM CHANGE, V8, P381, DOI 10.1038/s41558-018-0114-0
   Rhines A, 2013, P NATL ACAD SCI USA, V110, pE546, DOI 10.1073/pnas.1218748110
   Rigden AJ, 2020, NAT FOOD, V1, DOI 10.1038/s43016-020-0028-7
   Rowell DP, 2005, CLIM DYNAM, V25, P837, DOI 10.1007/s00382-005-0068-6
   Schlenker W, 2009, P NATL ACAD SCI USA, V106, P15594, DOI 10.1073/pnas.0906865106
   Seneviratne SI, 2010, EARTH-SCI REV, V99, P125, DOI 10.1016/j.earscirev.2010.02.004
   Soden BJ, 2008, J CLIMATE, V21, P3504, DOI 10.1175/2007JCLI2110.1
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Zeppetello LVR, 2020, J CLIMATE, V33, P5465, DOI 10.1175/JCLI-D-19-0887.1
   Vautard R, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/aba3d4
   Vignesh PP, 2020, EARTH SPACE SCI, V7, DOI 10.1029/2019EA000975
   York D, 2004, AM J PHYS, V72, P367, DOI 10.1119/1.1632486
   Zelinka MD, 2020, GEOPHYS RES LETT, V47, DOI 10.1029/2019GL085782
   Zeppetello LRV, 2020, GEOPHYS RES LETT, V47, DOI 10.1029/2020GL090197
   Zeppetello LRV, 2019, GEOPHYS RES LETT, V46, P2781, DOI 10.1029/2019GL082220
   Zeppetello LRV, 2022, J CLIMATE, V35, P2231, DOI 10.1175/JCLI-D-21-0236.1
NR 47
TC 3
Z9 3
U1 1
U2 22
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 FEB
PY 2022
VL 10
IS 2
AR e2021EF002402
DI 10.1029/2021EF002402
PG 16
WC Environmental Sciences; Geosciences, Multidisciplinary; Meteorology &
   Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Geology; Meteorology & Atmospheric
   Sciences
GA ZL1XA
UT WOS:000763473200008
OA gold, Green Published, Green Accepted
DA 2025-01-10
ER

PT J
AU Silva, R
   Eggimann, S
   Fierz, L
   Fiorentini, M
   Orehounig, K
   Baldini, L
AF Silva, Ricardo
   Eggimann, Sven
   Fierz, Leonie
   Fiorentini, Massimo
   Orehounig, Kristina
   Baldini, Luca
TI Opportunities for passive cooling to mitigate the impact of climate
   change in Switzerland
SO BUILDING AND ENVIRONMENT
LA English
DT Article
DE Night ventilation; Window shading; Space cooling demand; Climate
   adaptation; Buildings; Decarbonisation
ID ENERGY-SYSTEMS; BUILDINGS; DEMAND; TRENDS; OPTIMIZATION; CONSUMPTION;
   SIMULATION; FRAMEWORK; DRIVERS; NETWORK
AB Energy systems need to decarbonize rapidly whilst satisfying heating and cooling needs. In Switzerland, residential cooling has so far only a small impact on the national energy demand, but climate change and a larger uptake of cooling devices are expected to lead to future increases. This requires novel approaches for sustainable cooling solutions suitable for implementation at a national scale. Here, we explore the potential of night ventilation and window shading to reduce the buildings cooling demand in a changing climate. A physical bottom-up approach is used to simulate residential space cooling demand and to identify the passive cooling potential whilst considering a detailed representation of the Swiss building stock, featuring building age, construction properties, regional climate, urban layout and occupant behaviour. A supervised building type classification approach is applied to enable up-scaling to the national level. Results show that in 2050, the residential Swiss building stock will require a national cooling demand of around 10.2 TWh for a Representative Concentration Pathway scenario 4.5. Under such future climatic conditions, we simulated a potential to reduce the total cooling demand by 84%, with both passive cooling solutions combined. Individually, window shading could reduce cooling demands by 71% and night ventilation by 38%. We found that newer buildings (built after 2000) already account for about 50% of the total current cooling energy demand. Results demonstrate that night ventilation and window shading have the potential to mitigate the impact of climate change in Switzerland and to improve the sustainability and resilience of residential cooling.
C1 [Silva, Ricardo; Eggimann, Sven; Fierz, Leonie; Fiorentini, Massimo; Orehounig, Kristina] Empa, Urban Energy Syst Lab, Swiss Fed Labs Mat Sci & Technol, Dubendorf, Switzerland.
   [Baldini, Luca] ZHAW Zurich Univ Appl Sci, Sch Architecture Design & Civil Engn, Winterthur, Switzerland.
C3 Swiss Federal Institutes of Technology Domain; Swiss Federal
   Laboratories for Materials Science & Technology (EMPA); Zurich
   University of Applied Sciences
RP Eggimann, S (corresponding author), Empa, Urban Energy Syst Lab, Swiss Fed Labs Mat Sci & Technol, Dubendorf, Switzerland.
EM sven.eggimann@empa.ch
RI baldini, luca/AAB-4512-2020; Eggimann, Sven/K-5046-2016; Fiorentini,
   Massimo/R-8978-2019
OI Eggimann, Sven/0000-0003-3655-2328; Fiorentini,
   Massimo/0000-0002-9995-6672; Baldini, Luca/0000-0001-9513-4877; Silva,
   Ricardo/0000-0002-2988-9996
FU Swiss Competence Center for Energy Research on Future Energy Efficient
   Buildings & Districts SCCER-FEEB&D-WP5, Urban Planning for Smart &
   Resilient Cities/Communities) [1155002539]; Swiss Federal Office of
   Energy [SI/501894-01]
FX We acknowledge Khayatian F., Thrampoulidis E., Weber R., and Perera D.
   for their valuable insights and for assisting in the development of
   CESAR-P. R.S. and L.B. were supported by the Swiss Competence Center for
   Energy Research on Future Energy Efficient Buildings & Districts
   SCCER-FEEB&D-WP5, Urban Planning for Smart & Resilient
   Cities/Communities) (1155002539). S.E. was supported by the Swiss
   Federal Office of Energy (SI/501894-01).
CR Aebischer B., 2007, Proceedings eceee Summer Study Just do it!, P859
   Amber KP, 2018, ENERGY, V157, P886, DOI 10.1016/j.energy.2018.05.155
   Anand S, 2015, RENEW SUST ENERG REV, V41, P143, DOI 10.1016/j.rser.2014.08.042
   [Anonymous], 2019, OPENSTREETMAP CONTR
   [Anonymous], FREE COOLING AN OVER
   Artmann N, 2008, BUILD RES INF, V36, P111, DOI 10.1080/09613210701621919
   Artmann N, 2007, APPL ENERG, V84, P187, DOI 10.1016/j.apenergy.2006.05.004
   BAFU,, 2018, HITZ STADT GRUNDL EI, P1
   Belcher S. E., 2005, Building Services Engineering Research & Technology, V26, P49, DOI 10.1191/0143624405bt112oa
   Berger M, 2019, ENERG BUILDINGS, V202, DOI 10.1016/j.enbuild.2019.109372
   BFS,, 2017, EIDG GEN UND WOHN
   Bhamare DK, 2019, ENERG BUILDINGS, V198, P467, DOI 10.1016/j.enbuild.2019.06.023
   Biardeau LT, 2020, NAT SUSTAIN, V3, P25, DOI 10.1038/s41893-019-0441-9
   Bridge G, 2013, ENERG POLICY, V53, P331, DOI 10.1016/j.enpol.2012.10.066
   Bundesamt fur Energie, 2017, AUSF
   Burillo D, 2019, APPL ENERG, V236, P1, DOI 10.1016/j.apenergy.2018.11.039
   Cabeza L.F., 2021, Adv. Therm. Energy Storage Syst., VSecond, P595, DOI 10.1016/B978-0-12-819885-8.00020-6
   CH2018, 2018, CH2018 CLIM SCEN SWI
   Chambers J, 2019, ENERGY, V185, P136, DOI 10.1016/j.energy.2019.07.037
   Choobineh M, 2016, ELECTR POW SYST RES, V130, P230, DOI 10.1016/j.epsr.2015.09.010
   Christenson M, 2006, ENERG CONVERS MANAGE, V47, P671, DOI 10.1016/j.enconman.2005.06.009
   Crawley DB, 2001, ENERG BUILDINGS, V33, P319, DOI 10.1016/S0378-7788(00)00114-6
   De Jaeger I, 2020, ENERG BUILDINGS, V208, DOI 10.1016/j.enbuild.2019.109671
   Duda Richard O, 2001, Pattern Classification
   Duffie JA, 2013, SOLAR ENGINEERING OF THERMAL PROCESSES, 4TH EDITION, P1, DOI 10.1002/9781118671603
   Eggimann S., 2021, BULLETIN, P2
   Eggimann S, 2020, ENERGY, V195, DOI 10.1016/j.energy.2020.116947
   EURAC, 2014, RHC PLATF ANN EV
   Fierz L., 2021, HUES PLATFORM CESAR
   Fonseca JA, 2016, ENERG BUILDINGS, V113, P202, DOI 10.1016/j.enbuild.2015.11.055
   Frank T, 2005, ENERG BUILDINGS, V37, P1175, DOI 10.1016/j.enbuild.2005.06.019
   Geels FW, 2017, SCIENCE, V357, P1242, DOI 10.1126/science.aao3760
   Gomis LL, 2021, ENERG BUILDINGS, V231, DOI 10.1016/j.enbuild.2020.110597
   Hong T., 2008, ENERGYPLUS RUN TIME, V73, DOI [10.2172/951766, DOI 10.2172/951766]
   Huang KT, 2016, APPL ENERG, V184, P1230, DOI 10.1016/j.apenergy.2015.11.008
   Inayat A, 2019, RENEW SUST ENERG REV, V107, P360, DOI 10.1016/j.rser.2019.03.023
   Jiang WX, 2019, INT J REFRIG, V100, P93, DOI 10.1016/j.ijrefrig.2018.11.019
   Karlsen L, 2016, ENERG BUILDINGS, V118, P316, DOI 10.1016/j.enbuild.2016.03.014
   Kelbaugh D., 2019, The urban fix: Resilient cities in the war against climate change, heat islands and overpopulation, DOI [10.4324/9780429057441, DOI 10.4324/9780429057441]
   Khosla R, 2021, NAT SUSTAIN, V4, P201, DOI 10.1038/s41893-020-00627-w
   Landolt J, 2016, IND IS TRACK BUILD R, P1
   MACEACHREN AM, 1985, GEOGR ANN B, V67, P53, DOI 10.2307/490799
   MeteoSwiss,, 2020, IDAWEB
   Mohajeri N, 2019, RENEW ENERG, V143, P810, DOI 10.1016/j.renene.2019.05.033
   Mutschler R, 2021, APPL ENERG, V288, DOI 10.1016/j.apenergy.2021.116636
   Nanavatty R., 2019, WORLD EC FORUM
   Nicolas PG, 2012, REPORT EUR 25381, DOI [10.2790/56532, DOI 10.2790/56532]
   Pedregosa F, 2011, J MACH LEARN RES, V12, P2825
   Perera ATD, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-53653-w
   Perez D., 2011, P CISBAT 2011 CLEANT, P937
   Persson U., 2015, QUANTIFYING HEATING, V4, P25
   Ponmurugan M., 2021, REV PASSIVE COOLING, P555, DOI [10.1007/978-981-15-8319-3_55, DOI 10.1007/978-981-15-8319-3_55]
   Psomas T, 2017, ENERG BUILDINGS, V153, P18, DOI 10.1016/j.enbuild.2017.07.088
   Psomas T, 2016, ENERG BUILDINGS, V117, P138, DOI 10.1016/j.enbuild.2016.02.031
   Raczko E, 2017, EUR J REMOTE SENS, V50, P144, DOI 10.1080/22797254.2017.1299557
   Roca-Puigròs M, 2020, BUILD CITIES, V1, P579, DOI 10.5334/bc.61
   Roetzel A, 2010, RENEW SUST ENERG REV, V14, P1001, DOI 10.1016/j.rser.2009.11.005
   S.I.A. Zurich,, 2015, SIA 2024 2015 RAUMNU
   Saier MH, 2007, WATER AIR SOIL POLL, V181, P1, DOI 10.1007/s11270-007-9372-6
   Samuel DGL, 2013, BUILD ENVIRON, V66, P54, DOI 10.1016/j.buildenv.2013.04.016
   Santamouris M, 2013, ENERG BUILDINGS, V57, P74, DOI 10.1016/j.enbuild.2012.11.002
   Serrano S, 2017, ENERGY, V119, P425, DOI 10.1016/j.energy.2016.12.080
   Settembrini G., 2017, CLIMABAU PLANEN ANGE, P172
   Siecker J, 2017, RENEW SUST ENERG REV, V79, P192, DOI 10.1016/j.rser.2017.05.053
   Spinoni J, 2018, INT J CLIMATOL, V38, pE191, DOI 10.1002/joc.5362
   STEINIGER S., 2008, Transactions in GIS, V12, P31, DOI [10.1111/j.1467-9671.2008.01085.x, DOI 10.1111/J.1467-9671.2008.01085.X]
   Streicher KN, 2021, ENERG POLICY, V152, DOI 10.1016/j.enpol.2021.112220
   Streicher KN, 2019, ENERG BUILDINGS, V184, P300, DOI 10.1016/j.enbuild.2018.12.011
   Swisstopo,, 2019, SWISSBUILDINGS3D 1 0
   Thomson H, 2019, ENERG BUILDINGS, V196, P21, DOI 10.1016/j.enbuild.2019.05.014
   Totschnig G, 2017, ENERG POLICY, V103, P238, DOI 10.1016/j.enpol.2017.01.019
   Tvarne A., 2014, URBAN EUR
   Ürge-Vorsatz D, 2015, RENEW SUST ENERG REV, V41, P85, DOI 10.1016/j.rser.2014.08.039
   Valladares-Rendón LG, 2017, ENERG BUILDINGS, V140, P458, DOI 10.1016/j.enbuild.2016.12.073
   Wang D., 2016, CLIMA 2016 P 12 REHV
   Wang DH, 2018, ENERG BUILDINGS, V169, P9, DOI 10.1016/j.enbuild.2018.03.020
   Wang LP, 2017, ENERG BUILDINGS, V157, P218, DOI 10.1016/j.enbuild.2017.01.007
   Werner S, 2016, ENERGY, V110, P148, DOI 10.1016/j.energy.2015.11.028
   Wu R, 2017, APPL ENERG, V190, P634, DOI 10.1016/j.apenergy.2016.12.161
   Yu FW, 2014, ENRGY PROCED, V61, P2778, DOI 10.1016/j.egypro.2014.12.308
   Zeppini P, 2014, ENVIRON INNOV SOC TR, V11, P54, DOI 10.1016/j.eist.2013.10.002
   Zorn C., 2020, DEMAND SIDE MANAGEME
NR 82
TC 30
Z9 32
U1 3
U2 18
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 15
PY 2022
VL 208
AR 108574
DI 10.1016/j.buildenv.2021.108574
EA JAN 2022
PG 19
WC Construction & Building Technology; Engineering, Environmental;
   Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Engineering
GA 0H5AH
UT WOS:000778743600003
OA Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Welti, EAR
   Zajicek, P
   Frenzel, M
   Ayasse, M
   Bornholdt, T
   Buse, J
   Classen, A
   Dziock, F
   Engelmann, RA
   Englmeier, J
   Fellendorf, M
   Forschler, MI
   Fricke, U
   Ganuza, C
   Hippke, M
   Hoenselaar, G
   Kaus-Thiel, A
   Kerner, J
   Kilian, D
   Mandery, K
   Marten, A
   Monaghan, MT
   Morkel, C
   Muller, J
   Puffpaff, S
   Redlich, S
   Richter, R
   Rojas-Botero, S
   Scharnweber, T
   Scheiffarth, G
   Yanez, PS
   Schumann, R
   Seibold, S
   Steffan-Dewenter, I
   Stoll, S
   Tobisch, C
   Twietmeyer, S
   Uhler, J
   Vogt, J
   Weis, D
   Weisser, WW
   Wilmking, M
   Haase, P
AF Welti, Ellen A. R.
   Zajicek, Petr
   Frenzel, Mark
   Ayasse, Manfred
   Bornholdt, Tim
   Buse, Joern
   Classen, Alice
   Dziock, Frank
   Engelmann, Rolf A.
   Englmeier, Jana
   Fellendorf, Martin
   Foerschler, Marc, I
   Fricke, Ute
   Ganuza, Cristina
   Hippke, Mathias
   Hoenselaar, Guenter
   Kaus-Thiel, Andrea
   Kerner, Janika
   Kilian, Daniela
   Mandery, Klaus
   Marten, Andreas
   Monaghan, Michael T.
   Morkel, Carsten
   Mueller, Joerg
   Puffpaff, Stephanie
   Redlich, Sarah
   Richter, Ronny
   Rojas-Botero, Sandra
   Scharnweber, Tobias
   Scheiffarth, Gregor
   Yanez, Paul Schmidt
   Schumann, Rhena
   Seibold, Sebastian
   Steffan-Dewenter, Ingolf
   Stoll, Stefan
   Tobisch, Cynthia
   Twietmeyer, Soenke
   Uhler, Johannes
   Vogt, Juliane
   Weis, Dirk
   Weisser, Wolfgang W.
   Wilmking, Martin
   Haase, Peter
TI Temperature drives variation in flying insect biomass across a German
   malaise trap network
SO INSECT CONSERVATION AND DIVERSITY
LA English
DT Article
DE climate change; ecological gradients; insect monitoring; land cover;
   LTER; malaise trap; pollinator; thermal performance
ID ABUNDANCE; DECLINES; BIODIVERSITY; EXTINCTION; RESPONSES; FORESTS; SIZE;
   AGRICULTURE; ASSOCIATION; BUTTERFLIES
AB Among the many concerns for biodiversity in the Anthropocene, recent reports of flying insect loss are particularly alarming, given their importance as pollinators, pest control agents, and as a food source. Few insect monitoring programmes cover the large spatial scales required to provide more generalizable estimates of insect responses to global change drivers. We ask how climate and surrounding habitat affect flying insect biomass using data from the first year of a new monitoring network at 84 locations across Germany comprising a spatial gradient of land cover types from protected to urban and crop areas. Flying insect biomass increased linearly with temperature across Germany. However, the effect of temperature on flying insect biomass flipped to negative in the hot months of June and July when local temperatures most exceeded long-term averages. Land cover explained little variation in insect biomass, but biomass was lowest in forests. Grasslands, pastures, and orchards harboured the highest insect biomass. The date of peak biomass was primarily driven by surrounding land cover, with grasslands especially having earlier insect biomass phenologies. Standardised, large-scale monitoring provides key insights into the underlying processes of insect decline and is pivotal for the development of climate-adapted strategies to promote insect diversity. In a temperate climate region, we find that the positive effects of temperature on flying insect biomass diminish in a German summer at locations where temperatures most exceeded long-term averages. Our results highlight the importance of local adaptation in climate change-driven impacts on insect communities.
C1 [Welti, Ellen A. R.; Zajicek, Petr; Haase, Peter] Senckenberg Res Inst, Dept River Ecol & Conservat, D-63571 Gelnhausen, Germany.
   [Welti, Ellen A. R.; Zajicek, Petr; Haase, Peter] Nat Hist Museum Frankfurt, D-63571 Gelnhausen, Germany.
   [Frenzel, Mark] Helmholtz Ctr Environm Res, Community Ecol, Halle, Germany.
   [Ayasse, Manfred; Fellendorf, Martin] Ulm Univ, Inst Evolutionary Ecol & Conservat Genom, Ulm, Germany.
   [Bornholdt, Tim] Lower Oder Valley Natl Pk, Schwedt Oder, Ot Criewen, Germany.
   [Buse, Joern; Foerschler, Marc, I] Black Forest Natl Pk, Freudenstadt, Germany.
   [Classen, Alice; Fricke, Ute; Ganuza, Cristina; Kerner, Janika; Steffan-Dewenter, Ingolf] Univ Wurzburg, Bioctr, Anim Ecol & Trop Ecol, Wurzburg, Germany.
   [Dziock, Frank] Univ Appl Sci HTW Dresden, Anim Ecol, Dresden, Germany.
   [Engelmann, Rolf A.; Richter, Ronny] German Ctr Integrat Biodivers Res iDiv, Leipzig, Germany.
   [Engelmann, Rolf A.; Richter, Ronny] Univ Leipzig, Inst Biol, Systemat Bot & Funct Biodivers, Berlin, Germany.
   [Englmeier, Jana; Mueller, Joerg; Redlich, Sarah; Uhler, Johannes] Univ Wurzburg, Ecol Field Stn, Rauhenebrach, Germany.
   [Hippke, Mathias] Biospharenreservatsamt Schaalsee Elbe, Zarrentin, Germany.
   [Hoenselaar, Guenter; Morkel, Carsten] Kellerwald Edersee Natl Pk, Bad Wildungen, Germany.
   [Kaus-Thiel, Andrea] Hunsruck Hochwald Natl Pk, Birkenfeld, Germany.
   [Kilian, Daniela; Seibold, Sebastian] Berchtesgaden Natl Pk, Berchtesgaden, Germany.
   [Mandery, Klaus] Inst Biodiversitatsinformat eV, Ebern, Germany.
   [Marten, Andreas] Harz Natl Pk, Wernigerode, Germany.
   [Monaghan, Michael T.; Yanez, Paul Schmidt] Leibniz Inst Freshwater Ecol & Inland Fisheries I, Berlin, Germany.
   [Monaghan, Michael T.] Freie Univ, Inst Biol, Berlin, Germany.
   [Puffpaff, Stephanie] Natl Pk Amt Vorpommern, Born, Germany.
   [Richter, Ronny] Univ Leipzig, Inst Geog, Geoinformat & Remote Sensing, Leipzig, Germany.
   [Rojas-Botero, Sandra; Vogt, Juliane; Weisser, Wolfgang W.] Tech Univ Munich, Sch Life Sci, Freising Weihenstephan, Germany.
   [Scharnweber, Tobias; Wilmking, Martin] Univ Greifswald, Inst Bot & Landscape Ecol, Greifswald, Germany.
   [Scheiffarth, Gregor] Lower Saxon Wadden Sea Natl Pk Author, Wilhelmshaven, Germany.
   [Schumann, Rhena] Univ Rostock, Biol Stn Zingst, Zingst, Germany.
   [Schumann, Rhena] Univ Rostock, Inst Biol Sci, Math & Nat Sci, Rostock, Germany.
   [Seibold, Sebastian] Tech Univ Munich, Ecosyst Dynam & Forest Management Res Grp, Freising Weihenstephan, Germany.
   [Stoll, Stefan] Univ Appl Sci Trier, Environm Planning & Technol, Environm Campus Birkenfeld, Birkenfeld, Germany.
   [Tobisch, Cynthia] Weihenstephan Univ Appl Sci, Inst Ecol & Landscape, Freising Weihenstephan, Germany.
   [Twietmeyer, Soenke] Eifel Natl Pk, Schleiden Gemund, Germany.
   [Weis, Dirk] Biospharenreservat Oberlausitzer Heideund Teichla, Malschwitz Ot Wartha, Germany.
   [Haase, Peter] Univ Duisburg Essen, Fac Biol, Essen, Germany.
C3 Leibniz Association; Senckenberg Gesellschaft fur Naturforschung (SGN);
   Helmholtz Association; Helmholtz Center for Environmental Research
   (UFZ); Ulm University; University of Wurzburg; Leipzig University;
   University of Wurzburg; Leibniz Association; Leibniz Institut fur
   Gewasserokologie und Binnenfischerei (IGB); Free University of Berlin;
   Leipzig University; Technical University of Munich; Universitat
   Greifswald; University of Rostock; University of Rostock; Technical
   University of Munich; University of Duisburg Essen
RP Welti, EAR (corresponding author), Senckenberg Res Inst, Dept River Ecol & Conservat, D-63571 Gelnhausen, Germany.; Welti, EAR (corresponding author), Nat Hist Museum Frankfurt, D-63571 Gelnhausen, Germany.
EM elwelti@ksu.edu
RI Rojas-Botero, Sandra/ABT-4666-2022; Seibold, Sebastian/AAB-1455-2022;
   Kerner, Janika/IYS-6651-2023; Welti, Ellen/ABB-7810-2020; Frenzel,
   Mark/ABB-9845-2021; Monaghan, Michael/A-2589-2009; Ganuza,
   Cristina/AGZ-2694-2022; Steffan-Dewenter, Ingolf/AFJ-8134-2022; Haase,
   Peter/A-5644-2011; Weisser, Wolfgang/B-9718-2014; Scharnweber,
   Tobias/AAV-2390-2020; Wilmking, Martin/AAV-9310-2020; Wilmking,
   Martin/LFS-5364-2024; Fricke, Ute/GYT-9850-2022; Frenzel,
   Mark/D-4778-2015; Buse, Joern/G-6588-2015; Stoll, Stefan/D-5278-2011;
   Tobisch, Cynthia/JVO-9682-2024
OI Wilmking, Martin/0000-0003-4964-2402; Forschler, Marc
   I./0000-0001-5087-2585; Redlich, Sarah/0000-0001-5609-0576; Classen,
   Alice/0000-0002-7813-8806; Fricke, Ute/0000-0002-5284-4518; Scheiffarth,
   Gregor/0000-0002-1908-6401; Monaghan, Michael T./0000-0001-6200-2376;
   Kerner, Janika M./0000-0002-2355-081X; Frenzel,
   Mark/0000-0003-1068-2394; Buse, Joern/0000-0001-8226-1893; Engelmann,
   Rolf A./0000-0003-0262-5410; Morkel, Carsten/0000-0002-0623-9827; Stoll,
   Stefan/0000-0002-3656-417X; Ganuza, Cristina/0000-0002-4197-1829;
   Rojas-Botero, Sandra/0000-0002-0366-7383; Richter,
   Ronny/0000-0002-8728-7918; Welti, Ellen/0000-0001-6944-3422; Seibold,
   Sebastian/0000-0002-7968-4489; Steffan-Dewenter,
   Ingolf/0000-0003-1359-3944; Tobisch, Cynthia/0000-0002-2039-1462
FU eLTER PLUS project [871128]; DFG [AY12/6-4, WE3081/21-4, MO2142/1-1];
   Bavarian State Ministry of Science and the Arts via the Bavarian Climate
   Research Network bayklif; Bavarian State Ministry of Science and the
   Arts
FX The authors thank Beatrice Kulawig, Monika Baumeister, Michael Ehrhardt,
   Sebastian Flinkerbusch, Michael Hinz, Reinhard Holzel, Enno Klipp,
   Sebastian Keller, Linus Kramer, Gudrun Grimmer, Paula Kirschner, Beate
   Krischke, Johannes Lindner, Susanne Schiele, Verena Schmidt, Dragan
   Petrovic, Simon Potthast, Almuth Puschmann, Lena Unterbauer, Jan Weber,
   Roland Wollgarten, and the Auwaldstation Leipzig for assistance in the
   field and lab. The authors are grateful to the eLTER PLUS project (Grant
   Agreement No. 871128) for financial support to E.A.R.W. and P.H. This
   work was further supported by DFG AY12/6-4 to M.A., DFG WE3081/21-4 to
   W.W.W., DFG MO2142/1-1 to M.T.M., J.M. and P.S.Y., and the Bavarian
   State Ministry of Science and the Arts via the Bavarian Climate Research
   Network bayklif (projects 'LandKlif' and 'ADAPT'), and the Bavarian
   State Ministry of Science and the Arts.
CR Abatzoglou JT, 2018, SCI DATA, V5, DOI 10.1038/sdata.2017.191
   ATKINSON D, 1994, ADV ECOL RES, V25, P1, DOI 10.1016/S0065-2504(08)60212-3
   Baker NJ., 2021, Sci Total Environ, V785, P14685
   Barnes AD, 2016, PHILOS T R SOC B, V371, DOI 10.1098/rstb.2015.0279
   Barton K, 2019, MUMIN MULTIMODEL INF
   Baudier KM, 2015, J ANIM ECOL, V84, P1322, DOI 10.1111/1365-2656.12388
   Bender S., 2017, ANAL AUSGESUCHTER ST
   Bengtsson J, 2005, J APPL ECOL, V42, P261, DOI 10.1111/j.1365-2664.2005.01005.x
   Bergmann KGLC., 1847, Gttinger Studien, V3, P595
   Bernal JS, 2018, CURR OPIN INSECT SCI, V26, P76, DOI 10.1016/j.cois.2018.01.008
   Blois JL, 2013, P NATL ACAD SCI USA, V110, P9374, DOI 10.1073/pnas.1220228110
   Bongaarts J, 2019, POPUL DEV REV, V45, P680, DOI 10.1111/padr.12283
   Burkle LA, 2016, GLOBAL CHANGE BIOL, V22, P1644, DOI 10.1111/gcb.13149
   Burnham K.P., 2007, Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach
   Carvalheiro LG, 2020, ECOGRAPHY, V43, P209, DOI 10.1111/ecog.04656
   Contreras HL, 2013, J COMP PHYSIOL A, V199, P1053, DOI 10.1007/s00359-013-0829-3
   Coulthard E, 2019, BIOL CONSERV, V233, P213, DOI 10.1016/j.biocon.2019.02.023
   Cranmer L, 2012, OIKOS, V121, P562, DOI 10.1111/j.1600-0706.2011.19704.x
   Dangles O, 2011, ECOLOGY, V92, P733, DOI 10.1890/10-0329.1
   Daufresne M, 2009, P NATL ACAD SCI USA, V106, P12788, DOI 10.1073/pnas.0902080106
   Dennis EB, 2019, J INSECT CONSERV, V23, P369, DOI 10.1007/s10841-019-00135-z
   Diamond SE, 2014, ECOLOGY, V95, P2613, DOI 10.1890/13-1848.1
   Díaz S, 2019, SCIENCE, V366, P1327, DOI 10.1126/science.aax3100
   Didham RK, 2020, INSECT CONSERV DIVER, V13, P103, DOI 10.1111/icad.12408
   Eggleton P, 2020, ANNU REV ENV RESOUR, V45, P61, DOI 10.1146/annurev-environ-012420-050035
   European Union Copernicus Land Monitoring Service, 2018, EUR ENV AG EEA
   Fick SE, 2017, INT J CLIMATOL, V37, P4302, DOI 10.1002/joc.5086
   Forister ML, 2021, SCIENCE, V371, P1042, DOI 10.1126/science.abe5585
   Fox J., 2018, An R Companion to Applied Regression
   GeoBasis-DE/BKG, 2013, DIGITAL TERRAIN MODE
   Goulson D, 2018, PEERJ, V6, DOI 10.7717/peerj.5255
   Gurevitch J, 2010, ECOLOGY, V91, P2553, DOI 10.1890/09-1039.1
   Haase P, 2018, SCI TOTAL ENVIRON, V613, P1376, DOI 10.1016/j.scitotenv.2017.08.111
   Habel JC, 2019, BIODIVERS CONSERV, V28, P1343, DOI 10.1007/s10531-019-01741-8
   Haddad NM, 2000, OECOLOGIA, V124, P73, DOI 10.1007/s004420050026
   Hallmann CA, 2020, INSECT CONSERV DIVER, V13, P127, DOI 10.1111/icad.12377
   Hallmann CA, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0185809
   Harris I., 2014, International Journal of Climatology, V34, P623, DOI 10.1002/joc.3711
   Hausmann A, 2020, ECOL EVOL, V10, P4009, DOI 10.1002/ece3.6166
   Jachula J, 2018, J SCI FOOD AGR, V98, P2672, DOI 10.1002/jsfa.8761
   Janzen DH, 2019, BIOL CONSERV, V233, P102, DOI 10.1016/j.biocon.2019.02.030
   Jeliazkov A, 2016, GLOB ECOL CONSERV, V6, P208, DOI 10.1016/j.gecco.2016.02.008
   Ju RT, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-14989-3
   Karlsson D, 2020, BIODIVERS DATA J, V8, DOI 10.3897/BDJ.8.e56286
   Kaspari M, 2019, ECOLOGY, V100, DOI 10.1002/ecy.2888
   Kingsolver JG, 2008, EVOL ECOL RES, V10, P251
   Klockmann M, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0180968
   Koh LP, 2004, CONSERV BIOL, V18, P1571, DOI 10.1111/j.1523-1739.2004.00468.x
   Kühn E, 2008, ISR J ECOL EVOL, V54, P89, DOI 10.1560/IJEE.54.1.89
   Kühsel S, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms8989
   Lawson DA, 2019, ARTHROPOD-PLANT INTE, V13, P561, DOI 10.1007/s11829-019-09686-z
   Li DJ, 2021, GLOBAL CHANGE BIOL, V27, P892, DOI 10.1111/gcb.15461
   Losey JE, 2006, BIOSCIENCE, V56, P311, DOI 10.1641/0006-3568(2006)56[311:TEVOES]2.0.CO;2
   Macgregor CJ, 2019, NAT ECOL EVOL, V3, P1645, DOI 10.1038/s41559-019-1028-6
   Mattila N, 2006, CONSERV BIOL, V20, P1161, DOI 10.1111/j.1523-1739.2006.00404.x
   Merckx T, 2018, NATURE, V558, P113, DOI 10.1038/s41586-018-0140-0
   Montgomery DC, 2021, Introduction to linear Regression Analysis, DOI DOI 10.1080/01621459.1975.10479882
   Myhre G, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-52277-4
   Newbold T, 2020, FUNCT ECOL, V34, P684, DOI 10.1111/1365-2435.13500
   Owens ACS, 2020, BIOL CONSERV, V241, DOI 10.1016/j.biocon.2019.108259
   Pellegrino AC, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0075004
   Peters MK, 2019, NATURE, V568, P88, DOI 10.1038/s41586-019-1048-z
   Phillips BB, 2018, GLOBAL CHANGE BIOL, V24, P3226, DOI 10.1111/gcb.14130
   PIANKA ER, 1966, AM NAT, V100, P33, DOI 10.1086/282398
   Piano E, 2020, GLOBAL CHANGE BIOL, V26, P1196, DOI 10.1111/gcb.14934
   Pinheiro J., 2022, R package version 3.1-159, V3, P1
   Polidori C, 2020, ECOL ENTOMOL, V45, P130, DOI 10.1111/een.12781
   Potts SG, 2010, TRENDS ECOL EVOL, V25, P345, DOI 10.1016/j.tree.2010.01.007
   Pournelle G. H., 1953, Journal of Mammalogy, V34, P133
   QGIS, 2020, QGIS Geographic Information System
   Raven PH, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2002548117
   Rering CC, 2020, ECOSPHERE, V11, DOI 10.1002/ecs2.3254
   Rocha-Ortega M, 2020, P ROY SOC B-BIOL SCI, V287, DOI 10.1098/rspb.2019.2645
   ROOT RB, 1973, ECOL MONOGR, V43, P95, DOI 10.2307/1942161
   Rudolfs W., 1925, Journal of the New York Entomological Society, V33, P163
   Seibold S, 2019, NATURE, V574, P671, DOI 10.1038/s41586-019-1684-3
   Seibold S, 2015, CONSERV BIOL, V29, P382, DOI 10.1111/cobi.12427
   Shortall CR, 2009, INSECT CONSERV DIVER, V2, P251, DOI 10.1111/j.1752-4598.2009.00062.x
   Fenoglio MS, 2020, GLOBAL ECOL BIOGEOGR, V29, P1412, DOI 10.1111/geb.13107
   Sinclair BJ, 2016, ECOL LETT, V19, P1372, DOI 10.1111/ele.12686
   Stepanian PM, 2020, P NATL ACAD SCI USA, V117, P2987, DOI 10.1073/pnas.1913598117
   Svenningsen C.S., 2020, CONTRASTING IMPACTS, DOI 10.1101/2020.09.16.299404
   Termaat T, 2019, DIVERS DISTRIB, V25, P936, DOI 10.1111/ddi.12913
   Theodorou P, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-14496-6
   Thorpe AS, 2016, ECOSPHERE, V7, DOI 10.1002/ecs2.1627
   TOTLAND O, 1994, ECOGRAPHY, V17, P159, DOI 10.1111/j.1600-0587.1994.tb00089.x
   van C., 2019, EU BUTTERFLY INDICAT
   Vanbergen AJ, 2013, FRONT ECOL ENVIRON, V11, P251, DOI 10.1890/120126
   Wagner DL, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2002549117
   Wagner DL, 2020, ANNU REV ENTOMOL, V65, P457, DOI 10.1146/annurev-ento-011019-025151
   Warren R, 2018, SCIENCE, V360, P791, DOI 10.1126/science.aar3646
   Welti EAR, 2020, GLOBAL ECOL BIOGEOGR, V29, P1474, DOI 10.1111/geb.13119
   Welti EAR, 2020, P NATL ACAD SCI USA, V117, P7271, DOI 10.1073/pnas.1920012117
   Wepprich T, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0216270
   Wilson RJ, 2021, ECOL ENTOMOL, V46, P699, DOI 10.1111/een.12970
   Winfree R, 2011, ANNU REV ECOL EVOL S, V42, P1, DOI 10.1146/annurev-ecolsys-102710-145042
   Zuur Alain F., 2009, P1
NR 97
TC 42
Z9 44
U1 18
U2 113
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1752-458X
EI 1752-4598
J9 INSECT CONSERV DIVER
JI Insect. Conserv. Divers.
PD MAR
PY 2022
VL 15
IS 2
BP 168
EP 180
DI 10.1111/icad.12555
EA NOV 2021
PG 13
WC Biodiversity Conservation; Entomology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Entomology
GA ZP7UY
UT WOS:000720566700001
OA Green Published
DA 2025-01-10
ER

PT J
AU Ramirez-Ojeda, G
   Peralta, IE
   Rodriguez-Guzman, E
   Sahagún-Castellanos, J
   Chávez-Servia, JL
   Medina-Hinostroza, TC
   Rijalba-Vela, JR
   Vasquez-Núñez, LP
   Rodríguez-Pérez, JE
AF Ramirez-Ojeda, Gabriela
   Peralta, Iris Edith
   Rodriguez-Guzman, Eduardo
   Sahagun-Castellanos, Jaime
   Chavez-Servia, Jose Luis
   Medina-Hinostroza, Tulio Cecilio
   Rijalba-Vela, Jorge Rodrigo
   Vasquez-Nunez, Leopoldo Pompeyo
   Rodriguez-Perez, Juan Enrique
TI Edaphoclimatic Descriptors of Wild Tomato Species (<i>Solanum</i> Sect.
   Lycopersicon) and Closely Related Species (<i>Solanum</i> Sect.
   Juglandifolia and Sect. Lycopersicoides) in South America
SO FRONTIERS IN GENETICS
LA English
DT Article
DE wild tomatoes; edaphoclimatic diversity; ecological descriptors; genetic
   resources; canonical correlation analysis
ID ECOLOGICAL DESCRIPTORS; CLIMATIC ADAPTATION; COLD TOLERANCE;
   DOMESTICATION; GERMPLASM; CONSERVATION; BIOGEOGRAPHY; ECOGEOGRAPHY;
   HISTORY
AB Wild species related to cultivated tomato are essential genetic resources in breeding programs focused on food security to face future challenges. The ecogeographic analysis allows identifying the species adaptive ranges and most relevant environmental variables explaining their patterns of actual distribution. The objective of this research was to identify the diversity, ecological descriptors, and statistical relationship of 35 edaphoclimatic variables (20 climatic, 1 geographic and 14 edaphic variables) from 4,649 accessions of 12 wild tomato species and 4 closely related species classified in Solanum sect. Lycopersicon and clustered into four phylogenetic groups, namely "Lycopersicon group" (S. pimpinellifolium, S. cheesmaniae, and S. galapagense), "Arcanum group" (S. arcanum, S. chmielewskii, and S. neorickii), "Eriopersicon group" (S. habrochaites, S. huaylasense, S. corneliomulleri, S. peruvianum, and S. chilense), "Neolycopersicon group" (S. pennellii); and two phylogenetically related groups in Solanum sect. Juglandifolia (S. juglandifolium and S. ochranthum), and section Lycopersicoides (S. lycopersicoides and S. sitiens). The relationship between the climate and edaphic variables were determined by the canonical correlation analysis, reaching 89.2% of variation with the first three canonical correlations. The most significant climatic variables were related to humidity (annual evapotranspiration, annual precipitation, and precipitation of driest month) and physicochemical soil characteristics (bulk density, pH, and base saturation percentage). In all groups, ecological descriptors and diversity patterns were consistent with previous reports. Regarding edaphoclimatic diversity, 12 climate types and 17 soil units were identified among all species. This approach has promissory applications for biodiversity conservation and uses valuable genetic resources related to a leading crop.
C1 [Ramirez-Ojeda, Gabriela; Sahagun-Castellanos, Jaime; Rodriguez-Perez, Juan Enrique] Chapingo Autonomous Univ UACh, Inst Hort, Crop Sci Dept, Chapingo, Mexico.
   [Peralta, Iris Edith] Natl Univ Cuyo UNCUYO, Agr Sci Fac, Agron Dept, Mendoza, Argentina.
   [Peralta, Iris Edith] Sci Technol Ctr CONICET, Argentine Inst Arid Zones Res, Mendoza, Argentina.
   [Rodriguez-Guzman, Eduardo] Univ Guadalajara UdG, Univ Ctr Biol & Agr Sci, Agron Dept, Zapopan, Mexico.
   [Chavez-Servia, Jose Luis] Natl Polytech Inst IPN, Interdisciplinary Res Ctr Integral Reg Dev Oaxaca, Oaxaca, Oaxaca, Mexico.
   [Medina-Hinostroza, Tulio Cecilio] Minist Environm, Directorate Genet Resources & Biosafety, Lima, Peru.
   [Rijalba-Vela, Jorge Rodrigo; Vasquez-Nunez, Leopoldo Pompeyo] Natl Univ Pedro Ruiz Gallo UNPRG, Biol Sci Fac, Lambayeque, Peru.
C3 University Nacional Cuyo Mendoza
RP Rodríguez-Pérez, JE (corresponding author), Chapingo Autonomous Univ UACh, Inst Hort, Crop Sci Dept, Chapingo, Mexico.
RI Ramírez Ojeda, Gabriela/GPK-6113-2022; Rijalba Vela, Jorge
   Rodrigo/HSE-4265-2023; Rodriguez-Perez, Juan Enrique/C-7972-2014
OI Rijalba Vela, Jorge Rodrigo/0000-0002-3315-2153; Rodriguez-Perez, Juan
   Enrique/0000-0002-5841-0083
FU Chapingo Autonomous University [20001-C66]
FX This research received funding from Chapingo Autonomous University
   through project: D.G.I.P. 20001-C66.
CR Aflitos S, 2014, PLANT J, V80, P136, DOI 10.1111/tpj.12616
   [Anonymous], 2009, Harmonized World Soil Database version 1.1
   [Anonymous], SOLANACEAE SOURCE 20
   Arellano Rodríguez Luis Javier, 2013, Rev. Mex. Cienc. Agríc, V4, P753
   Balaguera-Lopez H.E., 2009, REV COLOMB CIENC HOR, V3, P199, DOI [10.17584/rcch.2009v3i2.1213, DOI 10.17584/RCCH.2009V3I2.1213]
   Beck HE, 2018, SCI DATA, V5, DOI 10.1038/sdata.2018.214
   Belanger J., 2019, The state of the world's biodiversity for food and agriculture
   Bergougnoux V, 2014, BIOTECHNOL ADV, V32, P170, DOI 10.1016/j.biotechadv.2013.11.003
   Burbano-Orjuela H, 2016, REV CIENC AGRIC, V33, P117, DOI 10.22267/rcia.163302.58
   Causse M., 2016, COMPEND PL GENOME, DOI 10.1007/978-3-662-53389-5
   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
   Chavez-Servia J.L., 2011, Utilizacion actual y potencial del jitomate silvestre mexicano
   Chen HY, 2015, BMC PLANT BIOL, V15, DOI 10.1186/s12870-015-0521-6
   Chetelat RT, 2009, EUPHYTICA, V167, P77, DOI 10.1007/s10681-008-9863-6
   Cordova-Tellez L., 2006, RECURSOS FITOGENETIC
   del Ambiente M., 2020, LINEA BASE DIVERSIDA
   Délices G, 2019, REV BIOL TROP, V67, P1023, DOI 10.15517/RBT.V67I4.33754
   Fick SE, 2017, INT J CLIMATOL, V37, P4302, DOI 10.1002/joc.5086
   Flores-Hernández LA, 2017, REV FITOTEC MEX, V40, P83
   Florido M., 2009, Cultivos Tropicales, V30, P57
   Foolad MR, 2000, J AM SOC HORTIC SCI, V125, P679, DOI 10.21273/JASHS.125.6.679
   GBIF.org, 2022, GBIF HOM PAG
   GETIS A, 1992, GEOGR ANAL, V24, P189, DOI 10.1111/j.1538-4632.1992.tb00261.x
   Godoy-Bürki Ana C., 2016, Ecol. austral, V26, P83
   Gonzalez P., 2013, ARNALDOA, V20, P301
   Grandillo S, 2011, WILD CROP RELATIVES: GENOMIC AND BREEDING RESOURCES - VEGETABLES, P129, DOI 10.1007/978-3-642-20450-0_9
   Hernández-Bautista A, 2014, INTERCIENCIA, V39, P327
   Hijmans R.J., 2002, Atlas of Wild Potatoes
   Hijmans RJ, 2001, AM J BOT, V88, P2101, DOI 10.2307/3558435
   Kantar MB, 2015, FRONT PLANT SCI, V6, DOI 10.3389/fpls.2015.00841
   Lin YP, 2020, AOB PLANTS, V12, DOI 10.1093/aobpla/plaa012
   Lobo-Burle M., 2013, PLANT GENET RESOUR N, V135, P1
   Luebert F, 2014, FRONT ECOL EVOL, V2, DOI 10.3389/fevo.2014.00027
   Fortuny-Fernandez NM, 2017, ACTA BOT MEX, V121, P7, DOI 10.21829/abm121.2017.1289
   Magallanes-López AM, 2020, AGROCIENCIA-MEXICO, V54, P779
   Martiny JBH, 2006, NAT REV MICROBIOL, V4, P102, DOI 10.1038/nrmicro1341
   Mittova V, 2004, J EXP BOT, V55, P1105, DOI 10.1093/jxb/erh113
   Nakazato T, 2010, AM J BOT, V97, P680, DOI 10.3732/ajb.0900216
   Nosenko T, 2016, MOL ECOL, V25, P2853, DOI 10.1111/mec.13637
   Parra-Quijano M, 2012, SPAN J AGRIC RES, V10, P419, DOI [10.5424/sjar/2012102-303-11, 10.5424/sjar/2011102-303-11]
   Pease JB, 2016, PLOS BIOL, V14, DOI 10.1371/journal.pbio.1002379
   Peralta I. E., 2008, Systematic Botany Monographs, V84
   Dinh QD, 2019, FRONT PLANT SCI, V10, DOI 10.3389/fpls.2019.01163
   Ramirez-Ojeda G., 2021, INT J AGR ENV BIORES, V06, P228, DOI [10.35410/IJAEB.2021.5641., DOI 10.35410/IJAEB.2021.5641]
   Ramírez-Ojeda G, 2021, PLANTS-BASEL, V10, DOI 10.3390/plants10050855
   Razali R, 2018, FRONT PLANT SCI, V9, DOI 10.3389/fpls.2018.01402
   Razifard H, 2020, MOL BIOL EVOL, V37, P1118, DOI 10.1093/molbev/msz297
   Rodriguez F, 2009, BMC EVOL BIOL, V9, DOI 10.1186/1471-2148-9-191
   Ruiz Corral José Ariel, 2013, Rev. Mex. Cienc. Agríc, V4, P829
   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
   Sandoval-Ceballos MG, 2021, PLANTS PEOPLE PLANET, V3, P703, DOI 10.1002/ppp3.10218
   SAS Institute, 2011, SAS STAT US GUID SOF
   Sotomayor Diego, 2019, Figshare, DOI 10.6084/m9.figshare.9880073.v1
   Spooner DM, 2010, AM J BOT, V97, P2049, DOI 10.3732/ajb.1000277
   Stam R., 2017, SUBSETS NLR GENES DR, P210559, DOI [10.1101/210559, DOI 10.1101/210559]
   Stam R, 2017, PEERJ, V5, DOI 10.7717/peerj.2910
   Steiner JJ, 1996, CROP SCI, V36, P439, DOI 10.2135/cropsci1996.0011183X003600020037x
   TGRC, 2021, TOM GEN RES CTR
   Tofalo R, 2013, FRONT MICROBIOL, V4, DOI 10.3389/fmicb.2013.00166
   Trabucco A., 2019, **DATA OBJECT**, DOI 10.6084/m9.figshare.7707605.v3
   Tropicos, 2021, MISS BOT GARD
   Unep-Wcmc, 2016, EST BIOD AM LAT CAR
   Venema JH, 2005, PLANT BIOLOGY, V7, P118, DOI 10.1055/s-2005-837495
   Vilchez D, 2019, ECOL APL, V18, P171, DOI 10.21704/rea.v18i2.1335
   Violle C, 2009, J PLANT ECOL-UK, V2, P87, DOI 10.1093/jpe/rtp007
   Zhao LX, 2005, HORTSCIENCE, V40, P43, DOI 10.21273/HORTSCI.40.1.43
NR 68
TC 9
Z9 9
U1 1
U2 10
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 1664-8021
J9 FRONT GENET
JI Front. Genet.
PD NOV 17
PY 2021
VL 12
AR 748979
DI 10.3389/fgene.2021.748979
PG 16
WC Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Genetics & Heredity
GA YF4LG
UT WOS:000741779500001
PM 34868219
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Fuldauer, LI
   Thacker, S
   Hall, JW
AF Fuldauer, Lena, I
   Thacker, Scott
   Hall, Jim W.
TI Informing national adaptation for sustainable development through
   spatial systems modelling
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article
DE Climate adaptation; Paris Agreement; Sustainable Development Goals
   (SDGs); Nationally Determined Contributions (NDCs); National Adaptation
   Plans (NAPs); Participatory systems modelling
ID CLIMATE-CHANGE; DEVELOPMENT GOALS; RISK; POLICY; LEVEL; INFRASTRUCTURE;
   VULNERABILITY; SCENARIOS; HOTSPOTS; IMPACTS
AB Acute climate-change hazards, such as floods or storm surges, can affect a nation's built and natural environment assets that are critical for development and achievement of the Sustainable Development Goals (SDGs). To reduce the impacts of such acute climate-change hazards and safeguard development, national decision-makers require evidence on where and how hazards affect SDG achievement to better inform adaptation. Here, we develop a systems methodology that spatially models the impacts of climate-change hazards across a nation's entire built and natural environment assets and its interdependent influences on the SDG targets to inform national adaptation. We apply our methodology in Saint Lucia through a participatory approach with decision-makers across 18 government ministries, academia, and the private sector. Results reveal that acute climate-change hazards can affect half of Saint Lucia's assets across 22 sectors, which can influence 89% of all SDG targets. Application of our methodology provided evidence on where and how to prioritise adaptation, thereby helping to add spatial granularity to 52 measures under Saint Lucia's National Adaptation Plan (NAP) as well as specificity on how limited capacity for cross-sectoral coordination can be directed to safeguard SDG targets. Adaptation does not necessarily imply investing in physical asset protection: results show the need to protect critical natural environments which provide important adaptation services to the built environment. As more nations develop and revise their NAPs and Nationally Determined Contributions under the Paris Agreement, strategic planning across sectors - as demonstrated in Saint Lucia - will be critical to facilitate adaptation that safeguards SDG achievement.
C1 [Fuldauer, Lena, I; Thacker, Scott; Hall, Jim W.] Univ Oxford, Environm Change Inst, South Parks Rd, Oxford OX1 3QY, England.
   [Thacker, Scott] UN Off Project Serv UNOPS, Marmorvej 51, DK-2050 Copenhagen, Denmark.
C3 University of Oxford
RP Fuldauer, LI (corresponding author), Univ Oxford, Environm Change Inst, South Parks Rd, Oxford OX1 3QY, England.
EM lena.fuldauer@eci.ox.ac.uk
RI Hall, Jim/ABF-1407-2020
OI Fuldauer, Lena I./0000-0002-2113-3334
FU UK Engineering and Physical Sciences Research Council [EP/N017064/1,
   EP/N509711/1]; United Nations Office for Project Services (UNOPS); EPSRC
   [EP/N017064/1] Funding Source: UKRI
FX This research was conducted at the Environmental Change Institute at the
   University of Oxford and was supported by the UK Engineering and
   Physical Sciences Research Council by grants EP/N017064/1 and
   EP/N509711/1 as well as the United Nations Office for Project Services
   (UNOPS). We thank the UNOPS team in Saint Lucia and the National
   Integrated Planning and Programme (NIPP) unit for facilitating this
   research, and all stakeholders consulted for providing valuable insights
   and verifying data. We further wish to thank colleagues at the
   University of Oxford and beyond for providing useful suggestions that
   improved this manuscript.
CR Adshead D., 2020, Saint Lucia: National infrastructure assessment
   Adshead D, 2021, EARTHS FUTURE, V9, DOI 10.1029/2020EF001699
   Adshead D, 2019, GLOBAL ENVIRON CHANG, V59, DOI 10.1016/j.gloenvcha.2019.101975
   Aerts JCJH, 2014, SCIENCE, V344, P472, DOI 10.1126/science.1248222
   Allison EH, 2009, FISH FISH, V10, P173, DOI 10.1111/j.1467-2979.2008.00310.x
   [Anonymous], 2016, SOCIOECONOMIC RESILI, DOI DOI 10.1596/1813-9450-7886
   Biagini B, 2014, GLOBAL ENVIRON CHANG, V25, P97, DOI 10.1016/j.gloenvcha.2014.01.003
   Briner S, 2012, AGR ECOSYST ENVIRON, V149, P50, DOI 10.1016/j.agee.2011.12.011
   Butler JRA, 2016, CLIM RISK MANAG, V12, P83, DOI 10.1016/j.crm.2015.11.003
   Cairns G, 2013, TECHNOL FORECAST SOC, V80, P1, DOI 10.1016/j.techfore.2012.08.005
   Carmin J, 2012, J PLAN EDUC RES, V32, P18, DOI 10.1177/0739456X11430951
   Central Statistical Office of Saint Lucia, 2018, EC TRAD STAT
   Charim, 2016, CARIBBEAN HDB RISK I
   Chester MV, 2020, NAT CLIM CHANGE, V10, P488, DOI 10.1038/s41558-020-0741-0
   Dawson RJ, 2018, PHILOS T R SOC A, V376, DOI 10.1098/rsta.2017.0298
   de Sherbinin A, 2014, CLIMATIC CHANGE, V123, P23, DOI 10.1007/s10584-013-0900-7
   Eriksen S, 2021, WORLD DEV, V141, DOI 10.1016/j.worlddev.2020.105383
   Fekete A, 2017, NAT HAZARDS, V86, P151, DOI 10.1007/s11069-016-2720-3
   Forestry Department Saint Lucia, 2009, LAND US MAP
   Fritz S, 2019, NAT SUSTAIN, V2, P922, DOI 10.1038/s41893-019-0390-3
   Fuldauer L.I., 2021, PREPRINT, DOI [10.21203/rs.3.rs-235355/v1, DOI 10.21203/RS.3.RS-235355/V1]
   Fuldauer LI, 2019, J CLEAN PROD, V223, P147, DOI 10.1016/j.jclepro.2019.02.269
   Gao J, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-15788-7
   Gomez-Echeverri L, 2018, PHILOS T R SOC A, V376, DOI 10.1098/rsta.2016.0444
   Government of Saint Lucia, 2019, SAINT LUC VOL REV RE
   Government of Saint Lucia, 2017, 3 NAT COMM CLIM CHAN
   Government of Saint Lucia, 2018, NAT AD PLAN SAINT LU
   Hall J.W., 2019, Adaptation of infrastructure systems: background paper for the global commission on adaptation
   Hall JW, 2016, The future of national infrastructure: A System-of-Systems Approach
   Hallegatte S, 2009, GLOBAL ENVIRON CHANG, V19, P240, DOI 10.1016/j.gloenvcha.2008.12.003
   Hardee K, 2010, MITIG ADAPT STRAT GL, V15, P113, DOI 10.1007/s11027-009-9208-3
   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]
   Hinkel J, 2015, NAT CLIM CHANGE, V5, P188, DOI 10.1038/nclimate2505
   IPCC, 2018, GLOB WARM 1 5C SUMM
   Jetten V, 2016, CHARIM PROJECT SAINT
   Jones HP, 2012, NAT CLIM CHANGE, V2, P504, DOI 10.1038/NCLIMATE1463
   Kanie N, 2019, SUSTAIN SCI, V14, P1745, DOI 10.1007/s11625-019-00729-1
   Kappes MS, 2012, NAT HAZARDS, V64, P1925, DOI 10.1007/s11069-012-0294-2
   Kelman I., 2009, ECOL ENVIRON ANTHROP, V5
   Kirchner M, 2015, ECOL ECON, V109, P161, DOI 10.1016/j.ecolecon.2014.11.005
   Koks EE, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-10442-3
   Koks E, 2018, NAT CLIM CHANGE, V8, P561, DOI 10.1038/s41558-018-0185-y
   Magnan AK, 2016, WIRES CLIM CHANGE, V7, P646, DOI 10.1002/wcc.409
   McNamara KE, 2020, NAT CLIM CHANGE, V10, P628, DOI 10.1038/s41558-020-0813-1
   Morgan EA, 2019, ENVIRON SCI POLICY, V93, P208, DOI 10.1016/j.envsci.2018.10.012
   Naesse LO, 2015, GLOBAL ENVIRON CHANG, V35, P534, DOI 10.1016/j.gloenvcha.2015.08.015
   Nerini FF, 2019, NAT SUSTAIN, V2, P674, DOI 10.1038/s41893-019-0334-y
   Nilsson M, 2018, SUSTAIN SCI, V13, P1489, DOI 10.1007/s11625-018-0604-z
   Nilsson M, 2016, NATURE, V534, P320, DOI 10.1038/534320a
   Noble IR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P833
   Palmer BJ, 2011, J COASTAL RES, P1390
   Pant R, 2018, J FLOOD RISK MANAG, V11, P22, DOI 10.1111/jfr3.12288
   Pant R., 2017, GGKP ANN C
   Pant R., 2014, ANAL INTERDEPENDENT, DOI [10.1 4453/isngi2013.proc.35, DOI 10.14453/ISNGI2013.PROC.35]
   Pradhan P, 2017, EARTHS FUTURE, V5, P1169, DOI 10.1002/2017EF000632
   Preston BL, 2011, MITIG ADAPT STRAT GL, V16, P407, DOI 10.1007/s11027-010-9270-x
   Raymond C, 2020, NAT CLIM CHANGE, V10, P611, DOI 10.1038/s41558-020-0790-4
   Reid H, 2014, COMMUNITY-BASED ADAPTATION TO CLIMATE CHANGE: SCALING IT UP, P3
   Sachs JD, 2019, NAT SUSTAIN, V2, P805, DOI 10.1038/s41893-019-0352-9
   Saier MH, 2007, WATER AIR SOIL POLL, V181, P1, DOI 10.1007/s11270-007-9372-6
   Schmidt-Traub G, 2017, NAT GEOSCI, V10, P547, DOI 10.1038/NGEO2985
   Simpson M., 2010, Quantification and Magnitude of Losses and Damages Resulting from the Impacts of Climate Change: Modelling the Transformational Impacts and Costs of Sea Level Rise in the Caribbean (Summary Document)
   Simpson NP, 2021, ONE EARTH, V4, P489, DOI 10.1016/j.oneear.2021.03.005
   Skourtos M, 2015, CLIMATIC CHANGE, V128, P307, DOI 10.1007/s10584-014-1168-2
   Stafford-Smith M, 2017, SUSTAIN SCI, V12, P911, DOI 10.1007/s11625-016-0383-3
   Termeer C, 2012, EUR POLIT SCI, V11, P41, DOI 10.1057/eps.2011.7
   Thacker S, 2019, NAT SUSTAIN, V2, P324, DOI 10.1038/s41893-019-0256-8
   Thacker S, 2017, RISK ANAL, V37, P2490, DOI 10.1111/risa.12840
   Thacker S, 2017, RELIAB ENG SYST SAFE, V167, P30, DOI 10.1016/j.ress.2017.04.023
   Tran LT, 2010, APPL GEOGR, V30, P191, DOI 10.1016/j.apgeog.2009.05.003
   UNFCCC, 2016, NEW EL DIM AD PAR AG
   UNFCCC, 2012, National Adaptation Plans. Technical Guidelines for the National Adaptation Plan Process
   van Westen C.J, 2016, NATL SCALE LANDSLIDE
   Verschuur J, 2020, GLOBAL ENVIRON CHANG, V65, DOI 10.1016/j.gloenvcha.2020.102179
   Ward P.J., 2020, AQUEDUCT FLOODS METH
   Willner SN, 2018, NAT CLIM CHANGE, V8, P594, DOI 10.1038/s41558-018-0173-2
   Xu ZC, 2020, NATURE, V577, P74, DOI 10.1038/s41586-019-1846-3
   Zscheischler J, 2018, NAT CLIM CHANGE, V8, P469, DOI 10.1038/s41558-018-0156-3
NR 78
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 2021
VL 71
AR 102396
DI 10.1016/j.gloenvcha.2021.102396
EA OCT 2021
PG 15
WC Environmental Sciences; Environmental Studies; Geography
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geography
GA WS3XH
UT WOS:000715117400001
DA 2025-01-10
ER

PT J
AU Ziter, CD
   Pedersen, EJ
   Kucharik, CJ
   Turner, MG
AF Ziter, Carly D.
   Pedersen, Eric J.
   Kucharik, Christopher J.
   Turner, Monica G.
TI Scale-dependent interactions between tree canopy cover and impervious
   surfaces reduce daytime urban heat during summer
SO PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF
   AMERICA
LA English
DT Article
DE urban heat island; urban forest; air temperature; ecosystem services;
   landscape context
ID SPATIAL HETEROGENEITY; ECOSYSTEM SERVICES; LAND-COVER; ISLAND; IMPACT;
   TEMPERATURE; MORTALITY; HEALTH; WAVES; VARIABILITY
AB As cities warm and the need for climate adaptation strategies increases, a more detailed understanding of the cooling effects of land cover across a continuum of spatial scales will be necessary to guide management decisions. We asked how tree canopy cover and impervious surface cover interact to influence daytime and nighttime summer air temperature, and how effects vary with the spatial scale at which land-cover data are analyzed (10-, 30-, 60-, and 90-m radii). A bicycle-mounted measurement system was used to sample air temperature every 5 m along 10 transects (similar to 7 km length, sampled 3-12 times each) spanning a range of impervious and tree canopy cover (0-100%, each) in a midsized city in the Upper Midwest United States. Variability in daytime air temperature within the urban landscape averaged 3.5 degrees C (range, 1.1-5.7 degrees C). Temperature decreased nonlinearly with increasing canopy cover, with the greatest cooling when canopy cover exceeded 40%. The magnitude of daytime cooling also increased with spatial scale and was greatest at the size of a typical city block (60-90 m). Daytime air temperature increased linearly with increasing impervious cover, but the magnitude of warming was less than the cooling associated with increased canopy cover. Variation in nighttime air temperature averaged 2.1 degrees C (range, 1.2-3.0 degrees C), and temperature increased with impervious surface. Effects of canopy were limited at night; thus, reduction of impervious surfaces remains critical for reducing nighttime urban heat. Results suggest strategies for managing urban land-cover patterns to enhance resilience of cities to climate warming.
C1 [Ziter, Carly D.; Turner, Monica G.] Univ Wisconsin, Dept Integrat Biol, Madison, WI 53706 USA.
   [Pedersen, Eric J.] Mem Univ Newfoundland, Dept Biol, St John, NF A1B 3X9, Canada.
   [Kucharik, Christopher J.] Univ Wisconsin, Dept Agron, 1575 Linden Dr, Madison, WI 53706 USA.
   [Kucharik, Christopher J.] Univ Wisconsin, Nelson Inst Environm Studies, Madison, WI 53706 USA.
   [Ziter, Carly D.] Concordia Univ, Dept Biol, Montreal, PQ H4B2A7, Canada.
C3 University of Wisconsin System; University of Wisconsin Madison;
   Memorial University Newfoundland; University of Wisconsin System;
   University of Wisconsin Madison; University of Wisconsin System;
   University of Wisconsin Madison; Concordia University - Canada
RP Ziter, CD; Turner, MG (corresponding author), Univ Wisconsin, Dept Integrat Biol, Madison, WI 53706 USA.; Ziter, CD (corresponding author), Concordia Univ, Dept Biol, Montreal, PQ H4B2A7, Canada.
EM carly.ziter@concordia.ca; turnermg@wisc.edu
RI Turner, Monica/B-2099-2010
OI Turner, Monica/0000-0003-1903-2822; Ziter, Carly/0000-0002-3731-9678
FU US National Science Foundation [DEB-1440297, DEB-1038759]; University of
   Wisconsin-Madison Vilas Trust; Natural Science and Engineering Research
   Council of Canada doctoral fellowship; Garden Club of America Zone VI
   Fellowship in Urban Forestry
FX We thank C. Gratton, E. Damschen, S. Carpenter, and J. Schatz for
   helpful comments on the development of these ideas. We appreciate
   logistical support from University of Wisconsin-Madison Instrument Maker
   Joel Lord, field assistance from Chloe Wardropper and Olivia Cope, and
   access to detailed canopy data from Tedward Erker. We acknowledge
   funding from the US National Science Foundation, especially the
   Long-Term Ecological Research (DEB-1440297) and Water Sustainability and
   Climate (DEB-1038759) Programs, and support to M.G.T. from the
   University of Wisconsin-Madison Vilas Trust. C.D.Z. acknowledges support
   from a Natural Science and Engineering Research Council of Canada
   doctoral fellowship, and Garden Club of America Zone VI Fellowship in
   Urban Forestry.
CR Abel DW, 2018, PLOS MED, V15, DOI 10.1371/journal.pmed.1002599
   Adams MP, 2014, LANDSCAPE URBAN PLAN, V132, P47, DOI 10.1016/j.landurbplan.2014.08.008
   Anderson GB, 2011, ENVIRON HEALTH PERSP, V119, P210, DOI 10.1289/ehp.1002313
   [Anonymous], THE WEATHER CHANNEL
   [Anonymous], 2018, SUST URB SYST ART LO
   Arnfield AJ, 2003, INT J CLIMATOL, V23, P1, DOI 10.1002/joc.859
   Aronson MFJ, 2017, FRONT ECOL ENVIRON, V15, P189, DOI 10.1002/fee.1480
   Basu R, 2009, ENVIRON HEALTH-GLOB, V8, DOI 10.1186/1476-069X-8-40
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   Brandsma T, 2012, J APPL METEOROL CLIM, V51, P1046, DOI 10.1175/JAMC-D-11-0206.1
   Buyantuyev A, 2010, LANDSCAPE ECOL, V25, P17, DOI 10.1007/s10980-009-9402-4
   Cadenasso ML, 2007, FRONT ECOL ENVIRON, V5, P80, DOI 10.1890/1540-9295(2007)5[80:SHIUER]2.0.CO;2
   Carpenter SR, 2007, BIOSCIENCE, V57, P323, DOI 10.1641/B570407
   Chen YC, 2018, SCI TOTAL ENVIRON, V626, P555, DOI 10.1016/j.scitotenv.2018.01.059
   Conway TM, 2016, URBAN FOR URBAN GREE, V17, P23, DOI 10.1016/j.ufug.2016.03.008
   Demographia, 2018, DEM WORLD URB AR URB
   Fortin MJ, 2005, SPATIAL ANALYSIS: A GUIDE FOR ECOLOGISTS
   Gage EA, 2017, URBAN ECOSYST, V20, P1229, DOI 10.1007/s11252-017-0675-0
   Gago EJ, 2013, RENEW SUST ENERG REV, V25, P749, DOI 10.1016/j.rser.2013.05.057
   Geschke A, 2018, J APPL ECOL, V55, P2320, DOI 10.1111/1365-2664.13183
   Grove M, 2018, ANN AM ASSOC GEOGR, V108, P524, DOI 10.1080/24694452.2017.1365585
   Harlan SL, 2007, RES SOC PROBL PUBLIC, V15, P173, DOI 10.1016/S0196-1152(07)15005-5
   Heusinkveld BG, 2014, J GEOPHYS RES-ATMOS, V119, P677, DOI 10.1002/2012JD019399
   Hiemstra JA, 2017, FUTURE CITY, V7, P7, DOI 10.1007/978-3-319-50280-9_2
   Hope D, 2003, P NATL ACAD SCI USA, V100, P8788, DOI 10.1073/pnas.1537557100
   Jenerette GD, 2016, LANDSCAPE ECOL, V31, P745, DOI 10.1007/s10980-015-0284-3
   Jenerette GD, 2011, ECOL APPL, V21, P2637, DOI 10.1890/10-1493.1
   Kammann EE, 2003, J R STAT SOC C-APPL, V52, P1, DOI 10.1111/1467-9876.00385
   Laaidi K, 2012, ENVIRON HEALTH PERSP, V120, P254, DOI 10.1289/ehp.1103532
   Li D, 2013, J APPL METEOROL CLIM, V52, P2051, DOI 10.1175/JAMC-D-13-02.1
   McGeehin MA, 2001, ENVIRON HEALTH PERSP, V109, P185, DOI 10.2307/3435008
   Mishra V, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/2/024005
   National Climatic Data Center, 2018, DAT TOOLS 1981 2010
   OKE TR, 1982, Q J ROY METEOR SOC, V108, P1, DOI 10.1002/qj.49710845502
   Patz JA, 2005, NATURE, V438, P310, DOI 10.1038/nature04188
   Pickett STA, 2017, URBAN ECOSYST, V20, P1, DOI 10.1007/s11252-016-0574-9
   Poland TM, 2006, J FOREST, V104, P118
   Rajkovich NB, 2016, INT J ENV RES PUB HE, V13, DOI 10.3390/ijerph13020159
   Rizwan AM, 2008, J ENVIRON SCI, V20, P120, DOI 10.1016/S1001-0742(08)60019-4
   Roman LA, 2018, URBAN FOR URBAN GREE, V31, P157, DOI 10.1016/j.ufug.2018.03.004
   Schatz J, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/9/094024
   Schatz J, 2014, J APPL METEOROL CLIM, V53, P2371, DOI 10.1175/JAMC-D-14-0107.1
   Schwarz K, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0122051
   Seto KC, 2017, P NATL ACAD SCI USA, V114, P8935, DOI 10.1073/pnas.1606037114
   Smoliak BV, 2015, J APPL METEOROL CLIM, V54, P1899, DOI 10.1175/JAMC-D-14-0239.1
   Stott I, 2015, FRONT ECOL ENVIRON, V13, P387, DOI 10.1890/140286
   Tan JG, 2010, INT J BIOMETEOROL, V54, P75, DOI 10.1007/s00484-009-0256-x
   US Bureau, 2010, STAT COUNT QUICK FAC
   White-Newsome JL, 2013, ENVIRON HEALTH PERSP, V121, P925, DOI 10.1289/ehp.1206176
   Wood S.N, 2017, Chapman & Hall/CRC texts in statistical science
   Wood SN, 2015, J ROY STAT SOC C, V64, P139, DOI 10.1111/rssc.12068
   Zhou WQ, 2017, LANDSCAPE ECOL, V32, P15, DOI 10.1007/s10980-016-0432-4
   Ziter C, 2018, ECOL APPL, V28, P643, DOI 10.1002/eap.1689
   Ziter CD, 2019, P NATL ACAD SCI USA, V116, P7575, DOI 10.1073/pnas.1817561116
NR 54
TC 415
Z9 463
U1 34
U2 367
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 APR 9
PY 2019
VL 116
IS 15
BP 7575
EP 7580
DI 10.1073/pnas.1817561116
PG 6
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA HS5UP
UT WOS:000463936900060
PM 30910972
OA Green Published
HC Y
HP N
DA 2025-01-10
ER

PT J
AU Blanckenhorn, WU
   Bauerfeind, SS
   Berger, D
   Davidowitz, G
   Fox, CW
   Guillaume, F
   Nakamura, S
   Nishimura, K
   Sasaki, H
   Stillwell, RC
   Tachi, T
   Schäfer, MA
AF Blanckenhorn, Wolf U.
   Bauerfeind, Stephanie S.
   Berger, David
   Davidowitz, Goggy
   Fox, Charles W.
   Guillaume, Frederic
   Nakamura, Satoshi
   Nishimura, Kinya
   Sasaki, Hitoshi
   Stillwell, R. Craig
   Tachi, Takuji
   Schaefer, Martin A.
TI Life history traits, but not body size, vary systematically along
   latitudinal gradients on three continents in the widespread yellow dung
   fly
SO ECOGRAPHY
LA English
DT Article
DE body size; development time; diapause; Fst; geographic differentiation;
   genetic differentiation; growth rate; latitudinal cline; life history;
   Qst
ID DROSOPHILA-MELANOGASTER; GENETIC DIFFERENTIATION; CLIMATIC ADAPTATION;
   PHOTOPERIODIC RESPONSE; POPULATION DIVERGENCE; GEOGRAPHIC-VARIATION;
   ADAPTIVE DIVERGENCE; QUANTITATIVE TRAIT; NATURAL-SELECTION; SEXUAL
   SELECTION
AB Large-scale clinal variation in body size and other life-history traits is common enough to have stimulated the postulation of several eco-geographical rules. Whereas some clinal patterns are clearly adaptive, the causes of others remain unclear. We present a comprehensive intraspecific population comparison for the cosmopolitan yellow dung fly Scathophaga stercoraria (Diptera: Scathophagidae) to check for consistent world-wide patterns. Common garden assessment of various life history traits permitted continental comparison of (clinal) quantitative genetic differentiation (Qst) with putatively neutral genetic differentiation (Fst) derived from field-caught flies. Latitudinal clines in fly development time, growth rate, and overwintering propensity were consistent among North American, European and Japanese populations. Increased winter dormancy incidence and duration at higher latitude, combined with a faster growth rate and shorter development time, suggest that flies are adaptated to season length more than to temperature. The resulting body size clines, in contrast, were not very consistent; importantly, they were not negative, as expected under seasonal constraints, but flat or even positive clines. Quantitative genetic differentiation Q(ST) exceeded neutral molecular variation F-ST for most traits, suggesting that natural selection plays a consistent role in mediating global dung fly life histories. We conclude that faster growth and development in response to shorter growing seasons at higher latitudes may indirectly counteract expected direct effects of temperature on body-size, potentially resulting in flat or inconsistent body size clines in nature.
C1 [Blanckenhorn, Wolf U.; Bauerfeind, Stephanie S.; Berger, David; Guillaume, Frederic; Schaefer, Martin A.] Univ Zurich, Dept Evolutionary Biol & Environm Studies, Zurich, Switzerland.
   [Berger, David] Uppsala Univ, Evolutionary Biol Ctr, Dept Ecol & Genet, Uppsala, Sweden.
   [Davidowitz, Goggy; Stillwell, R. Craig] Univ Arizona, Dept Entomol, Tucson, AZ USA.
   [Fox, Charles W.; Stillwell, R. Craig] Univ Kentucky, Dept Entomol, Lexington, KY USA.
   [Stillwell, R. Craig] Univ Lausanne, Dept Ecol & Evolut, Lausanne, Switzerland.
   [Nakamura, Satoshi] JIRCAS, Tsukuba, Ibaraki, Japan.
   [Nishimura, Kinya] Hokkaido Univ, Fis Sci, Hakodate, Hokkaido, Japan.
   [Sasaki, Hitoshi] Rakuno Gakuen Univ, Entomol Lab, Ebetsu, Hokkaido, Japan.
   [Tachi, Takuji] Kyushu Univ, Biosystemat Lab, Fukuoka, Fukuoka, Japan.
C3 University of Zurich; Uppsala University; University of Arizona;
   University of Kentucky; University of Lausanne; Japan International
   Research Center for Agricultural Sciences; Hokkaido University; Rakuno
   Gakuen University; Kyushu University
RP Blanckenhorn, WU (corresponding author), Univ Zurich, Dept Evolutionary Biol & Environm Studies, Zurich, Switzerland.
EM wolf.blanckenhorn@ieu.uzh.ch
RI Guillaume, Frederic/D-5021-2011; Fox, Charles/I-5274-2012
OI Blanckenhorn, Wolf/0000-0002-0713-3944; Fox, Charles/0000-0002-7545-7967
FU Swiss National Foundation [3100A0-111775]; Zoological Museum Zurich;
   Univ. of Zurich; JSPS; Direct For Biological Sciences; Division Of
   Integrative Organismal Systems [1053318] Funding Source: National
   Science Foundation
FX This work was supported by grant 3100A0-111775 from the Swiss National
   Foundation and several other grants over the years, the Zoological
   Museum Zurich, and the Univ. of Zurich. The JSPS funded an extended
   visit of WUB to Japan to complete the project.
CR [Anonymous], 1998, Genetics and Analysis of Quantitative Traits (Sinauer)
   Atkinson D, 1997, TRENDS ECOL EVOL, V12, P235, DOI 10.1016/S0169-5347(97)01058-6
   Berger D, 2011, EVOLUTION, V65, P2830, DOI 10.1111/j.1558-5646.2011.01392.x
   Blackburn Tim M., 1999, Diversity and Distributions, V5, P165, DOI 10.1046/j.1472-4642.1999.00046.x
   Blanckenhorn WU, 2010, J INSECT SCI, V10, DOI 10.1673/031.010.1101
   Blanckenhorn W. U., 2009, Phenotypic plasticity of insects: mechanisms and consequences, P369
   Blanckenhorn Wolf U., 2007, P106
   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
   Bradshaw WE, 2001, P NATL ACAD SCI USA, V98, P14509, DOI 10.1073/pnas.241391498
   Chenoweth SF, 2008, EVOLUTION, V62, P1437, DOI 10.1111/j.1558-5646.2008.00374.x
   Chown SL, 1999, BIOL REV, V74, P87, DOI 10.1017/S000632319800526X
   Chown SL, 2010, BIOL REV, V85, P139, DOI 10.1111/j.1469-185X.2009.00097.x
   CONOVER DO, 1990, OECOLOGIA, V83, P316, DOI 10.1007/BF00317554
   Demont M, 2008, J EVOLUTION BIOL, V21, P1492, DOI 10.1111/j.1420-9101.2008.01615.x
   Demont M, 2008, ECOL ENTOMOL, V33, P197, DOI 10.1111/j.1365-2311.2007.00951.x
   Fabian DK, 2015, J EVOLUTION BIOL, V28, P826, DOI 10.1111/jeb.12607
   Flatt T, 2016, MOL ECOL, V25, P1023, DOI 10.1111/mec.13534
   Gilbert KJ, 2015, MOL ECOL RESOUR, V15, P262, DOI 10.1111/1755-0998.12303
   Gilchrist GW, 2004, INTEGR COMP BIOL, V44, P461, DOI 10.1093/icb/44.6.461
   Gilchrist GW, 2004, EVOLUTION, V58, P768, DOI 10.1111/j.0014-3820.2004.tb00410.x
   Guédot C, 2009, ECOL ENTOMOL, V34, P158, DOI 10.1111/j.1365-2311.2008.01054.x
   Hangartner S, 2012, J EVOLUTION BIOL, V25, P1587, DOI 10.1111/j.1420-9101.2012.02546.x
   Huey RB, 2000, SCIENCE, V287, P308, DOI 10.1126/science.287.5451.308
   James AC, 1997, GENETICS, V146, P881
   Jann P, 2000, J EVOLUTION BIOL, V13, P927, DOI 10.1046/j.1420-9101.2000.00230.x
   Jetz W, 2009, ECOL LETT, V12, P1137, DOI 10.1111/j.1461-0248.2009.01369.x
   Kaufmann C, 2013, BIOL J LINN SOC, V108, P565, DOI 10.1111/j.1095-8312.2012.02042.x
   Kawakami T, 2011, MOL ECOL, V20, P2318, DOI 10.1111/j.1365-294X.2011.05105.x
   Klepsatel P, 2014, EVOLUTION, V68, P1385, DOI 10.1111/evo.12351
   Kraushaar U, 2002, EVOLUTION, V56, P307, DOI 10.1111/j.0014-3820.2002.tb01341.x
   Kraushaar U, 2002, HEREDITY, V89, P99, DOI 10.1038/sj.hdy.6800097
   Leinonen T, 2008, J EVOLUTION BIOL, V21, P1, DOI 10.1111/j.1420-9101.2007.01445.x
   LEVINTON JS, 1983, BIOL BULL, V165, P699, DOI 10.2307/1541472
   LEWONTIN RC, 1973, GENETICS, V74, P175
   MASAKI S, 1972, EVOLUTION, V26, P587, DOI 10.1111/j.1558-5646.1972.tb01966.x
   MASAKI S, 1967, EVOLUTION, V21, P725, DOI 10.1111/j.1558-5646.1967.tb03430.x
   McKay JK, 2002, TRENDS ECOL EVOL, V17, P285, DOI 10.1016/S0169-5347(02)02478-3
   Merilä J, 2001, J EVOLUTION BIOL, V14, P892, DOI 10.1046/j.1420-9101.2001.00348.x
   Merila J, 1997, BIOL J LINN SOC, V61, P243
   Mousseau TA, 1997, EVOLUTION, V51, P630, DOI [10.1111/j.1558-5646.1997.tb02453.x, 10.2307/2411138]
   Nylin S, 1998, ANNU REV ENTOMOL, V43, P63, DOI 10.1146/annurev.ento.43.1.63
   O'Hara RB, 2005, GENETICS, V171, P1331, DOI 10.1534/genetics.105.044545
   Palo JU, 2003, MOL ECOL, V12, P1963, DOI 10.1046/j.1365-294X.2003.01865.x
   Partridge L, 1997, EVOLUTION, V51, P632, DOI 10.1111/j.1558-5646.1997.tb02454.x
   ROFF D, 1980, OECOLOGIA, V45, P202, DOI 10.1007/BF00346461
   Rohner PT, 2017, EVOL DEV, V19, P147, DOI 10.1111/ede.12223
   Rohner PT, 2015, INSECT CONSERV DIVER, V8, P367, DOI 10.1111/icad.12114
   ROWE L, 1991, ECOLOGY, V72, P413, DOI 10.2307/2937184
   Schafer ., 2018, EVOLUTION
   Scharf I, 2010, CLIM RES, V43, P115, DOI 10.3354/cr00907
   Schmidt PS, 2005, EVOLUTION, V59, P1721, DOI 10.1111/j.0014-3820.2005.tb01821.x
   Shama LNS, 2011, MOL ECOL, V20, P2929, DOI 10.1111/j.1365-294X.2011.05156.x
   Shelomi M, 2012, AM NAT, V180, P511, DOI 10.1086/667595
   SPITZE K, 1993, GENETICS, V135, P367
   Storz JF, 2002, MOL ECOL, V11, P2537, DOI 10.1046/j.1365-294X.2002.01636.x
   Tauber M.J., 1986, SEASONAL ADAPTATIONS
   Van Buskirk J, 2010, OIKOS, V119, P1047, DOI 10.1111/j.1600-0706.2009.18349.x
   vanderHave TM, 1996, J THEOR BIOL, V183, P329, DOI 10.1006/jtbi.1996.0224
   vanVoorhies WA, 1996, EVOLUTION, V50, P1259, DOI 10.1111/j.1558-5646.1996.tb02366.x
   Whitlock MC, 2009, GENETICS, V183, P1055, DOI 10.1534/genetics.108.099812
   Zurbuchen A, 2010, BIOL CONSERV, V143, P669, DOI 10.1016/j.biocon.2009.12.003
   Zwaan BJ, 2000, HEREDITY, V84, P338, DOI 10.1046/j.1365-2540.2000.00677.x
NR 63
TC 21
Z9 22
U1 1
U2 24
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0906-7590
EI 1600-0587
J9 ECOGRAPHY
JI Ecography
PD DEC
PY 2018
VL 41
IS 12
BP 2080
EP 2091
DI 10.1111/ecog.03752
PG 12
WC Biodiversity Conservation; Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA HC5FW
UT WOS:000451829900014
OA Bronze
DA 2025-01-10
ER

PT J
AU Khezri, A
   Bennett, R
   Zevenbergen, J
AF Khezri, Adish
   Bennett, Rohan
   Zevenbergen, Jaap
TI Evaluating a Fit-For-Purpose Integrated Service-Oriented Land and
   Climate Change Information System for Mountain Community Adaptation
SO ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
LA English
DT Article
DE Integrated Land Information System; climate adaptation services;
   mountain community; Agile-inspired approach; Fit-For-Purpose Land
   Administration
ID AGILE SOFTWARE-DEVELOPMENT; MODEL
AB Climate change challenges mountain communities to prepare themselves via Community-Based Adaptation (CBA) plans that reduce vulnerability. This paper outlines the evaluation of a developed web-based information system to support CBA, referred to as a Mountain Community Adaptive System (MCAS). The web-based user interface visualizes collated data from data providers, integrating it with near real-time climate and weather datasets. The interface provides more up-to-date information than was previously available on the environment, particularly on land and climate. MCAS, a cloud-based Land Information System (LIS), was developed using an Agile-inspired approach offering system creation based on bare minimum system requirements and iterative development. The system was tested against Fit-For-Purpose Land Administration (FFP LA) criteria to assess the effectiveness in a case from Nepal. The results illustrate that an MCAS-style system can provide useful information such as land use status, adaptation options, near real-time rainfall and temperature details, amongst others, to enable services that can enhance CBA activities. The information can facilitate improved CBA planning and implementation at the mountain community level. Despite the mentioned benefits of MCAS, ensuring system access was identified as a key limitation: smartphones and mobile technologies still remain prohibitively expensive for members of mountain communities, and underlying information communication technology (ICT) infrastructures remain under-developed in the assessed mountain communities. The results of the evaluation further suggest that the land-related aspects of climate change should be added to CBA initiatives. Similarly, existing LIS could have functionalities extended to include climate-related variables that impact on land use, tenure, and development.
C1 [Khezri, Adish; Zevenbergen, Jaap] Univ Twente, Fac Geoinformat Sci & Earth Observat ITC, POB 217, NL-7500 AE Enschede, Netherlands.
   [Bennett, Rohan] Swinburne Univ Technol, Swinburne Business Sch, POB 218, Hawthorn, Vic 3122, Australia.
C3 University of Twente; Swinburne University of Technology
RP Khezri, A (corresponding author), Univ Twente, Fac Geoinformat Sci & Earth Observat ITC, POB 217, NL-7500 AE Enschede, Netherlands.
EM a.khezri@utwente.nl; rohanbennett@swin.edu.au;
   j.a.zevenbergen@utwente.nl
RI Zevenbergen`, Jaap/K-8695-2013; Bennett, Rohan/K-5086-2013
OI Khezri, Adish/0000-0003-1229-9356; Bennett, Rohan/0000-0002-1200-2068
FU Erasmus Mundus Action 2 Project SALAM, International Scholarship of the
   European Commission
FX This research was funded by Erasmus Mundus Action 2 Project SALAM,
   International Scholarship of the European Commission.
CR [Anonymous], CLIM CHANG 2014 IM A
   [Anonymous], 2004, Extreme Programming Explained: embrace change
   [Anonymous], 2012, Voluntary Guidelines on the Responsible Governance of Tenure of Land, Fisheries and Forests in the Context of National Food Security
   [Anonymous], GEOGRAPHICAL INFORM
   Ayers J, 2009, ENVIRONMENT, V51, P22, DOI 10.3200/ENV.51.4.22-31
   Bartoli F., 2012, P 2012 FIG WORK WEEK
   Barton JE, 2015, J SPAT SCI, V60, P311, DOI 10.1080/14498596.2015.997315
   Bennett RM, 2016, SURV REV, V47, P11, DOI 10.1080/00396265.2015.1097584
   Berrang-Ford L, 2011, GLOBAL ENVIRON CHANG, V21, P25, DOI 10.1016/j.gloenvcha.2010.09.012
   Bryman A., 2019, SOCIAL RES METHODS
   Bugs G, 2010, CITIES, V27, P172, DOI 10.1016/j.cities.2009.11.008
   Campelo ND, 2018, P I CIVIL ENG-GEOTEC, V171, P64, DOI 10.1680/jgeen.16.00198
   Cimato F., 2010, ADAPTING CLIMATE CHA, P78
   DeLone WH, 2003, J MANAGE INFORM SYST, V19, P9, DOI 10.1080/07421222.2003.11045748
   Dennis A., 2012, System analysis and design, V5th
   Dingsoyr T, 2012, J SYST SOFTWARE, V85, P1213, DOI 10.1016/j.jss.2012.02.033
   Eckstein David., 2017, GLOBAL CLIMATE RISK
   Enemark S., 2015, FIT FOR PURPOSE LAND
   Fassnacht KS, 2006, FOREST ECOL MANAG, V222, P167, DOI 10.1016/j.foreco.2005.09.026
   Furuholt B., 2015, P 2015 48 HAW INT C
   Gruen A, 2002, ISPRS J PHOTOGRAMM, V57, P1, DOI 10.1016/S0924-2716(02)00125-9
   Guest G., 2013, Participant observation. Chapter 3 in Collecting qualitative data: A field manual for applied research, P75
   Hammoudi K, 2010, INT ARCH PHOTOGRAMM, V38, P91
   Heltberg R, 2012, CLIM POLICY, V12, P143, DOI 10.1080/14693062.2011.582344
   International Centre for Integrated Mountain Development (ICIMOD), 2016, CIT SCI AID WINT FOG
   International Federation of Surveyors (FIG), 2014, SURV ROL MON MIT AD
   Johannessen LK, 2009, COMPUT SUPP COOP W J, V18, P607, DOI 10.1007/s10606-009-9097-8
   Khezri A, 2018, CLIMATE, V6, DOI 10.3390/cli6020047
   KING S, 2014, COMMUNITY BASED ADAP
   Kumar V, 2012, INF SECUR J, V21, P317, DOI 10.1080/19393555.2012.738376
   Li B, 2016, GEO-SPAT INF SCI, V19, P81, DOI 10.1080/10095020.2016.1179441
   Lieske DJ, 2015, ENVIRON MODELL SOFTW, V68, P98, DOI 10.1016/j.envsoft.2015.02.005
   Meso P, 2006, INFORM SYST MANAGE, V23, P19, DOI 10.1201/1078.10580530/46108.23.3.20060601/93704.3
   Ministry of Environment, 2010, CLIM CHANG VULN MAPP
   Misra H., 2008, P ENG MAN C, P1
   Mitchell D, 2015, LAND USE POLICY, V48, P190, DOI 10.1016/j.landusepol.2015.05.026
   Moe NB, 2010, INFORM SOFTWARE TECH, V52, P480, DOI 10.1016/j.infsof.2009.11.004
   Regmi B.R., REVISITING COMMUNITY
   Sarzynski A, 2015, URBAN CLIM, V14, P52, DOI 10.1016/j.uclim.2015.08.002
   Schwaber K., 2004, Agile project management with Scrum
   Simbizi D.M.C., 2016, Measuring land tenure security: a pro-poor perspective
   SJOBERG RW, 1983, APPL OPTICS, V22, P1702, DOI 10.1364/AO.22.001702
   Syomiti M., 2014, VULNERABILITY AGR WA
   Thapa D., 2011, 44 HAW INT C SYST SC, P1, DOI DOI 10.1109/HICSS.2011.142
   Wamsler C, 2014, ENVIRON URBAN, V26, P86, DOI 10.1177/0956247813516061
   Zevenbergen J., 2004, Nordic Journal of Surveying and Real Estate Research, V1, P11
   Zheng Y, 2016, CLIM DEV, V8, P110, DOI 10.1080/17565529.2015.1005037
NR 47
TC 5
Z9 5
U1 0
U2 8
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2220-9964
J9 ISPRS INT J GEO-INF
JI ISPRS Int. Geo-Inf.
PD SEP
PY 2018
VL 7
IS 9
AR 343
DI 10.3390/ijgi7090343
PG 20
WC Computer Science, Information Systems; Geography, Physical; Remote
   Sensing
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Computer Science; Physical Geography; Remote Sensing
GA GV0QR
UT WOS:000445767900011
OA Green Published, Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Griffis-Kyle, KL
AF Griffis-Kyle, Kerry L.
TI PHYSIOLOGY AND ECOLOGY TO INFORM CLIMATE ADAPTATION STRATEGIES FOR
   DESERT AMPHIBIANS
SO HERPETOLOGICAL CONSERVATION AND BIOLOGY
LA English
DT Article
DE climate change; collaboration; desert ecology; ecological interactions;
   habitat enhancement; head-starting; landscape planning; vulnerability
   assessment
ID SONORAN DESERT; BIODIVERSITY CONSERVATION; WILDLIFE MANAGEMENT;
   THERMAL-ACCLIMATION; MULTIPLE STRESSORS; BREEDING PHENOLOGY; LARVAL
   DEVELOPMENT; ANURAN AMPHIBIANS; ONTOGENIC CHANGE; RANGE SHIFTS
AB Many amphibian populations in desert environments are likely at risk of decline or extirpation due to more extreme weather driven by climate change. Most desert species are explosive breeders, taking advantage of rainfall large enough to potentially support reproduction. Hence, management strategies for amphibians in general may not apply to anurans in temperate and subtropical deserts. Sustaining populations of desert amphibians is complex in that we are managing species assemblages that are relatively vulnerable to climate change, while planning for an environment that will change in ways that are not clear. However, we can improve the success of proactive management by integrating physiology with ecology within the context of a changing climate. Explicit consideration of physiology and ecology can target efficient habitat management actions such as identifying where to add shading or to extend hydroperiod. This approach can also improve outcomes when re-establishing native fauna by identifying life stages robust to release. Further we can improve our management of invasive species by explicit consideration of physiological constraints on dispersal capability of the invasive species to help plan where to fragment habitat connectivity to block invasions. To effectively plan for desert amphibians and climate change, science, management and policy makers must openly communicate about what we know, what information we lack, and the limitations of our knowledge. By explicitly including physiology in our management decisions we can refine our approach and more efficiently apply limited resources of time and money.
C1 [Griffis-Kyle, Kerry L.] Texas Tech Univ, Dept Nat Resources Management, Box 42125, Lubbock, TX 79409 USA.
C3 Texas Tech University System; Texas Tech University
RP Griffis-Kyle, KL (corresponding author), Texas Tech Univ, Dept Nat Resources Management, Box 42125, Lubbock, TX 79409 USA.
EM kerry.griffis-kyle@ttu.edu
RI Griffis-Kyle, Kerry/AAE-6084-2020
OI Griffis-Kyle, Kerry/0000-0002-2887-9550
FU Desert Landscape Conservation Cooperatives (DLCC)
FX I dedicate this manuscript to the memory Dr. Jeffrey Kovatch, a great
   friend and physiologist who helped shape the original questions that
   generated this manuscript; you are deeply missed. I thank the Desert
   Landscape Conservation Cooperatives (DLCC) for inviting me to give the
   webinar this manuscript is based on and funding to assist in writing.
   Thanks to all who helped in editing versions of this manuscript
   including John Arnett, the DLCC Critical Management Question 6 Working
   Group, and the Griffis-Kyle lab writing group.
CR ALVARADO RH, 1972, PHYSIOL ZOOL, V45, P43, DOI 10.1086/physzool.45.1.30155925
   Amarasekare P, 2013, J ANIM ECOL, V82, P1240, DOI 10.1111/1365-2656.12112
   Angilletta MJ, 2009, BIO HABIT, P1, DOI 10.1093/acprof:oso/9780198570875.001.1
   [Anonymous], CONTRIBUTION WORKING, DOI [DOI 10.1017/CBO9781107415324, 10.1017/CBO9781107415324]
   Arizona Game and Fish Department, 2014, WILDL WAT DEV STAND
   ATKINSON D, 1994, ADV ECOL RES, V25, P1, DOI 10.1016/S0065-2504(08)60212-3
   Atkinson D, 2001, EXPTL BIOL REV, P269
   Augustine DJ, 2010, LANDSCAPE ECOL, V25, P913, DOI 10.1007/s10980-010-9469-y
   Bartelt PE, 2010, ECOL MODEL, V221, P2675, DOI 10.1016/j.ecolmodel.2010.07.009
   Beier P, 2015, CONSERV BIOL, V29, P613, DOI 10.1111/cobi.12511
   Beier P, 2010, CONSERV BIOL, V24, P701, DOI 10.1111/j.1523-1739.2009.01422.x
   Benard MF, 2015, GLOBAL CHANGE BIOL, V21, P1058, DOI 10.1111/gcb.12720
   BENTLEY PJ, 1966, SCIENCE, V152, P619, DOI 10.1126/science.152.3722.619
   BERVEN KA, 1979, EVOLUTION, V33, P609, DOI 10.1111/j.1558-5646.1979.tb04714.x
   Bradford D.F., 2005, Amphibian Declines: The Conservation Status of United States Species, P567
   BRADFORD DF, 1990, PHYSIOL ZOOL, V63, P1157, DOI 10.1086/physzool.63.6.30152638
   BRATTSTROM BH, 1968, COMP BIOCHEM PHYSIOL, V24, P93, DOI 10.1016/0010-406X(68)90961-4
   Brito JC, 2014, BIOL REV, V89, P215, DOI 10.1111/brv.12049
   BROWN HA, 1969, COPEIA, P138
   Cabrera-Guzmán E, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0070121
   Camargo JA, 2006, ENVIRON INT, V32, P831, DOI 10.1016/j.envint.2006.05.002
   Carey C, 2003, DIVERS DISTRIB, V9, P111, DOI 10.1046/j.1472-4642.2003.00011.x
   Cayan DR, 2010, P NATL ACAD SCI USA, V107, P21271, DOI 10.1073/pnas.0912391107
   Comrie AC, 2002, J ARID ENVIRON, V50, P573, DOI 10.1006/jare.2001.0866
   Coumou D, 2012, NAT CLIM CHANGE, V2, P491, DOI 10.1038/NCLIMATE1452
   Crawford J.A., 2005, Amphibian Declines: the Conservation Status of United States Species, P532
   Cromie R.L., 2012, Ramsar Wetland Disease Manual: Guidelines for Assessment, Monitoring and Management of Animal Disease in Wetlands
   Curtin CG, 2014, CONSERV BIOL, V28, P912, DOI 10.1111/cobi.12321
   Davison JE, 2012, BIODIVERS CONSERV, V21, P189, DOI 10.1007/s10531-011-0175-0
   Dawson TP, 2011, SCIENCE, V332, P53, DOI 10.1126/science.1200303
   Dell AI, 2014, J ANIM ECOL, V83, P70, DOI 10.1111/1365-2656.12081
   Dilling L., 2010, GLOBAL ENVIRON CHANG, V21, P680, DOI DOI 10.1016/J.GL0ENVCHA.2010.11.006
   DODD CK, 1991, HERPETOLOGICA, V47, P336
   Drake J. C., LANDSCAPE E IN PRESS
   Duarte H, 2012, GLOBAL CHANGE BIOL, V18, P412, DOI 10.1111/j.1365-2486.2011.02518.x
   Dubois N., 2011, Integrating climate change vulnerability assessments into adaptation planning: A case study using the NatureServe Climate Change Vulnerability Index to inform conservation planning for species in Florida
   Duellman W. E., 1986, Biology of Amphibians
   Early R, 2011, ECOL LETT, V14, P1125, DOI 10.1111/j.1461-0248.2011.01681.x
   Edwards GP, 2010, RANGELAND J, V32, P43, DOI 10.1071/RJ09037
   Elith J, 2010, METHODS ECOL EVOL, V1, P330, DOI 10.1111/j.2041-210X.2010.00036.x
   EPA (Environmental Protection Agency), 2013, AQ LIF AMB WAT QUAL
   Farrar E., 2005, Amphibian declines: the conservation status of United States species, P513
   Feder ME, 1999, ANNU REV PHYSIOL, V61, P243, DOI 10.1146/annurev.physiol.61.1.243
   FEDER ME, 1982, J THERM BIOL, V7, P23, DOI 10.1016/0306-4565(82)90015-8
   Feehan J, 2009, AGRON SUSTAIN DEV, V29, P409, DOI 10.1051/agro:2008066
   Feeley KJ, 2014, NAT CLIM CHANGE, V4, P405, DOI 10.1038/nclimate2207
   Ficetola GF, 2016, OECOLOGIA, V181, P683, DOI 10.1007/s00442-016-3610-9
   Ficetola GF, 2006, EVOL ECOL, V20, P143, DOI 10.1007/s10682-005-5508-6
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fitzgerald-Dehoog L, 2012, BIOL BULL-US, V223, P205, DOI 10.1086/BBLv223n2p205
   FLOYD RB, 1983, COMP BIOCHEM PHYS A, V75, P267, DOI 10.1016/0300-9629(83)90081-6
   Foden WB, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0065427
   Frankham R., 2004, PRIMER CONSERVATION
   García A, 2014, ENVIRON CONSERV, V41, P1, DOI 10.1017/S0376892913000349
   Germano JM, 2009, CONSERV BIOL, V23, P7, DOI 10.1111/j.1523-1739.2008.01123.x
   Gillooly JF, 2001, SCIENCE, V293, P2248, DOI 10.1126/science.1061967
   Goetting J., 2015, THESIS
   Gosner K. L., 1960, Herpetologica, V16, P183
   Griffis-Kyle KL, 2014, WILDLIFE SOC B, V38, P148, DOI 10.1002/wsb.358
   Griffiths RA, 2008, CONSERV BIOL, V22, P852, DOI 10.1111/j.1523-1739.2008.00967.x
   Griffs-Kyle KL, 2011, SOUTHWEST NAT, V56, P251, DOI 10.1894/N02-GC-212.1
   Groves CR, 2012, BIODIVERS CONSERV, V21, P1651, DOI 10.1007/s10531-012-0269-3
   Hannah L, 2002, GLOBAL ECOL BIOGEOGR, V11, P485, DOI 10.1046/j.1466-822X.2002.00306.x
   Harings NM, 2014, HERPETOLOGICA, V70, P123, DOI 10.1655/HERPETOLOGICA-D-12-00077
   Heard GW, 2014, ECOL APPL, V24, P650, DOI 10.1890/13-0389.1
   HEATWOLE H, 1972, Herpetologica, V28, P156
   HEATWOLE H, 1971, Herpetologica, V27, P365
   Heller NE, 2009, BIOL CONSERV, V142, P14, DOI 10.1016/j.biocon.2008.10.006
   Hillman S., 2009, Ecological and environmental physiology of amphibians
   HILLMAN SS, 1987, PHYSIOL ZOOL, V60, P608, DOI 10.1086/physzool.60.5.30156135
   Hoff KV, 1999, TADPOLES, P215
   Hofmann GE, 2010, ANNU REV PHYSIOL, V72, P127, DOI 10.1146/annurev-physiol-021909-135900
   Holmquist JG, 2011, BIOL CONSERV, V144, P518, DOI 10.1016/j.biocon.2010.10.007
   Hutchison Victor H., 1992, P206
   IPCC, 2018, GLOB WARM 1 5C SUMM
   Jarchow CJ, 2016, J HERPETOL, V50, P63, DOI 10.1670/14-172
   Kearney M, 2008, ECOGRAPHY, V31, P423, DOI 10.1111/j.0906-7590.2008.05457.x
   Kearney M, 2009, ECOL LETT, V12, P334, DOI 10.1111/j.1461-0248.2008.01277.x
   Kishida O, 2014, J ANIM ECOL, V83, P899, DOI 10.1111/1365-2656.12186
   Komuscu AU, 1998, CLIMATIC CHANGE, V40, P519, DOI 10.1023/A:1005349408201
   KREBS RA, 1994, FUNCT ECOL, V8, P730, DOI 10.2307/2390232
   Kujala H, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0053315
   Kunkel K.E., 2013, noaa technical report nesdis, P142
   Kuzmin SL, 1997, J HERPETOL, V31, P306, DOI 10.2307/1565404
   LANG T, 1987, DIS AQUAT ORGAN, V3, P159, DOI 10.3354/dao003159
   Lapola DM, 2009, GLOBAL BIOGEOCHEM CY, V23, DOI 10.1029/2008GB003357
   Lawler JJ, 2015, CONSERV BIOL, V29, P618, DOI 10.1111/cobi.12505
   Lawler JJ, 2010, CONSERV BIOL, V24, P38, DOI 10.1111/j.1523-1739.2009.01403.x
   LEE AK, 1967, SCIENCE, V157, P87, DOI 10.1126/science.157.3784.87
   Li YM, 2013, INTEGR ZOOL, V8, P145, DOI 10.1111/1749-4877.12001
   Loyola RD, 2013, BIODIVERS CONSERV, V22, P483, DOI 10.1007/s10531-012-0424-x
   Luja VH, 2010, BIOL INVASIONS, V12, P2979, DOI 10.1007/s10530-010-9713-z
   Martinez PJ, 2012, AQUAT INVASIONS, V7, P219, DOI 10.3391/ai.2012.7.2.008
   Mawdsley JR, 2009, CONSERV BIOL, V23, P1080, DOI 10.1111/j.1523-1739.2009.01264.x
   McIntyre NE, 2016, J WILDLIFE MANAGE, V80, P655, DOI 10.1002/jwmg.1059
   McKinney ML, 1997, ANNU REV ECOL SYST, V28, P495, DOI 10.1146/annurev.ecolsys.28.1.495
   Milanovich JR, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0012189
   Minckley TA, 2013, J ARID ENVIRON, V88, P213, DOI 10.1016/j.jaridenv.2012.09.001
   Mitchell NJ, 2001, P ROY SOC B-BIOL SCI, V268, P87, DOI 10.1098/rspb.2000.1334
   MOORE FR, 1989, HERPETOLOGICA, V45, P101
   Morey S.R., 2005, Amphibian declines: the conservation status of United States species, P519
   Morey SR, 2005, AMPHIBIAN DECLINES: THE CONSERVATION STATUS OF UNITED STATES SPECIES, P508
   Morin X, 2009, ECOLOGY, V90, P1301, DOI 10.1890/08-0134.1
   Navas CA, 2008, COMP BIOCHEM PHYS A, V151, P344, DOI 10.1016/j.cbpa.2007.07.003
   NEWMAN RA, 1987, OECOLOGIA, V71, P301, DOI 10.1007/BF00377299
   Newman RA, 1998, OECOLOGIA, V115, P9, DOI 10.1007/s004420050485
   Niehaus AC, 2012, J EXP BIOL, V215, P694, DOI 10.1242/jeb.058032
   Nosaka M, 2015, OIKOS, V124, P225, DOI 10.1111/oik.01662
   Noss R.F., 2006, CONNECTIVITY CONSERV, P587, DOI [10.1017/CBO9780511754821.026, DOI 10.1017/CBO9780511754821.026]
   Orizaola G, 2013, OECOLOGIA, V171, P873, DOI 10.1007/s00442-012-2456-z
   Pails John G., 2012, Proceedings of the Indiana Academy of Science, V121, P158
   Payne JL, 2007, P NATL ACAD SCI USA, V104, P10506, DOI 10.1073/pnas.0701257104
   Pechmann J.H.K., 1989, Wetlands Ecology and Management, V1, P3
   Petrie MD, 2014, J ARID ENVIRON, V103, P63, DOI 10.1016/j.jaridenv.2014.01.005
   Phillips SJ, 2006, ECOL MODEL, V190, P231, DOI 10.1016/j.ecolmodel.2005.03.026
   PIMM SL, 1988, AM NAT, V132, P757, DOI 10.1086/284889
   Pinder Alan W., 1992, P250
   Pineda E, 2009, J ANIM ECOL, V78, P182, DOI 10.1111/j.1365-2656.2008.01471.x
   Pörtner HO, 2007, SCIENCE, V315, P95, DOI 10.1126/science.1135471
   Pörtner HO, 2008, SCIENCE, V322, P690, DOI 10.1126/science.1163156
   Poiani KA, 2011, BIODIVERS CONSERV, V20, P185, DOI 10.1007/s10531-010-9954-2
   Polasik JS, 2016, J WILDLIFE MANAGE, V80, P540, DOI 10.1002/jwmg.1031
   Pressey RL, 2007, TRENDS ECOL EVOL, V22, P583, DOI 10.1016/j.tree.2007.10.001
   Purvis A, 2000, P ROY SOC B-BIOL SCI, V267, P1947, DOI 10.1098/rspb.2000.1234
   PUTNAM RW, 1977, COPEIA, P746
   Raffel TR, 2006, FUNCT ECOL, V20, P819, DOI 10.1111/j.1365-2435.2006.01159.x
   Raffel TR, 2013, NAT CLIM CHANGE, V3, P146, DOI [10.1038/nclimate1659, 10.1038/NCLIMATE1659]
   RALIN DB, 1972, COPEIA, P519, DOI 10.2307/1442924
   Relyea RA, 2002, ECOL MONOGR, V72, P523, DOI 10.1890/0012-9615(2002)072[0523:CIPITC]2.0.CO;2
   Rohr JR, 2013, CONSERV BIOL, V27, P741, DOI 10.1111/cobi.12086
   Rome Lawrence C., 1992, P183
   Rorabaugh J.C., 2005, Amphibian Declines. The Conservation Status of United States Species, P530
   Rosen P., 1994, RM-GTR-264: biodiversity and management of theMadrean Archipelago: the sky islands of southwestern United States and northwestern Mexico, P251
   Rosen Philip C., 1995, P452
   Rosset V, 2011, BIOL CONSERV, V144, P2311, DOI 10.1016/j.biocon.2011.06.009
   ROWE CL, 1995, OECOLOGIA, V102, P397, DOI 10.1007/BF00341351
   Rummer JL, 2014, GLOBAL CHANGE BIOL, V20, P1055, DOI 10.1111/gcb.12455
   Russo R.C., 1985, Fundamentals of aquatic toxicology, P455
   Salice CJ, 2012, J HERPETOL, V46, P675, DOI 10.1670/11-091
   Savage AE, 2015, EVOL APPL, V8, P560, DOI 10.1111/eva.12264
   Scarlett L, 2010, J N AM BENTHOL SOC, V29, P892, DOI 10.1899/09-135.1
   Scheffers BR, 2014, GLOBAL CHANGE BIOL, V20, P495, DOI 10.1111/gcb.12439
   Scott N.J. Jr, 1985, Occasional Papers the Museum of Southwestern Biology, P1
   Seager R, 2007, SCIENCE, V316, P1181, DOI 10.1126/science.1139601
   Seneviratne SI, 2010, EARTH-SCI REV, V99, P125, DOI 10.1016/j.earscirev.2010.02.004
   Shafer CL, 2014, ENVIRON SCI POLICY, V40, P26, DOI 10.1016/j.envsci.2014.04.006
   Sheridan JA, 2011, NAT CLIM CHANGE, V1, P401, DOI 10.1038/NCLIMATE1259
   SHERMAN E, 1980, COMP BIOCHEM PHYS A, V65, P227, DOI 10.1016/0300-9629(80)90229-7
   Shoemaker Vaughan H., 1992, P125
   Shoo LP, 2006, AUSTRAL ECOL, V31, P22, DOI 10.1111/j.1442-9993.2006.01539.x
   Shoo LP, 2011, J APPL ECOL, V48, P487, DOI 10.1111/j.1365-2664.2010.01942.x
   Sinervo B, 2010, SCIENCE, V328, P894, DOI 10.1126/science.1184695
   Slatyer RA, 2013, ECOL LETT, V16, P1104, DOI 10.1111/ele.12140
   Somero GN, 2002, INTEGR COMP BIOL, V42, P780, DOI 10.1093/icb/42.4.780
   Sprankle T., 2008, ENDANGER SPECIES B, V33, P15
   Sredl M.J., 2005, Amphibian Declines: The Conservation Status of United States Species, P596
   Stahlschmidt ZR, 2011, J ARID ENVIRON, V75, P681, DOI 10.1016/j.jaridenv.2011.03.006
   Stenseth NC, 2002, SCIENCE, V297, P1292, DOI 10.1126/science.1071281
   Stevenson LA, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0073830
   Sullivan B. K., 2005, AMPHIBIAN DECLINES C, P430
   SULLIVAN BK, 1989, J ARID ENVIRON, V17, P175, DOI 10.1016/S0140-1963(18)30904-2
   Sullivan BK, 1999, HERPETOLOGICA, V55, P334
   Tattersall GJ, 2012, COMPR PHYSIOL, V2, P2151, DOI 10.1002/cphy.c110055
   TEIPEL JW, 1971, BIOCHEMISTRY-US, V10, P792, DOI 10.1021/bi00781a011
   TEVIS L, 1966, ECOLOGY, V47, P766, DOI 10.2307/1934263
   Thomson RC., 2016, CALIFORNIA AMPHIBIAN
   THORSON TB, 1955, ECOLOGY, V36, P100, DOI 10.2307/1931435
   TINSLEY RC, 1995, AUST J ECOL, V20, P376, DOI 10.1111/j.1442-9993.1995.tb00553.x
   TOFT CA, 1980, OECOLOGIA, V47, P34, DOI 10.1007/BF00541772
   Tracy Christopher R., 2007, Copeia, V2007, P901, DOI 10.1643/0045-8511(2007)7[901:EOAIAC]2.0.CO;2
   Tromans D, 1998, HYDROMETALLURGY, V48, P327, DOI 10.1016/S0304-386X(98)00007-3
   Tylianakis JM, 2008, ECOL LETT, V11, P1351, DOI 10.1111/j.1461-0248.2008.01250.x
   Unmack P.J., 2008, Aridland Springs in North America: Ecology and Conservation
   Vignieri S, 2014, SCIENCE, V345, P393
   Vos CC, 2010, LANDSCAPE ECOL, V25, P1465, DOI 10.1007/s10980-010-9535-5
   VOSS SR, 1993, J HERPETOL, V27, P329, DOI 10.2307/1565156
   WARBURG M. R., 1965, AUSTRALIAN J ZOOL, V13, P317, DOI 10.1071/ZO9650317
   WARBURG MR, 1967, COMP BIOCHEM PHYSIOL, V20, P27, DOI 10.1016/0010-406X(67)90722-0
   Weiss JL, 2005, GLOBAL CHANGE BIOL, V11, P2065, DOI 10.1111/j.1365-2486.2005.01020.x
   While GM, 2014, ECOGRAPHY, V37, P921, DOI 10.1111/ecog.00521
   WILBUR HM, 1987, ECOLOGY, V68, P1437, DOI 10.2307/1939227
   Woodward B.D., 1991, P223
   Yang LH, 2010, ECOL LETT, V13, P1, DOI 10.1111/j.1461-0248.2009.01402.x
   Young JE, 2005, PHYSIOL BIOCHEM ZOOL, V78, P847, DOI 10.1086/432152
   Zuo WY, 2012, P ROY SOC B-BIOL SCI, V279, P1840, DOI 10.1098/rspb.2011.2000
   Zweifel R.G., 1977, American Museum Novitates, P1
   Zweifel R. G., 1968, Bulletin of the American Museum of Natural History, V140, P1
NR 187
TC 17
Z9 21
U1 2
U2 55
PU HERPETOLOGICAL CONSERVATION & BIOLOGY
PI CORVALLIS
PA C/O R BRUCE BURY, USGS FOREST & RANGELAND, CORVALLIS, OR 00000 USA
SN 2151-0733
EI 1931-7603
J9 HERPETOL CONSERV BIO
JI Herpetol. Conserv. Biol.
PD DEC
PY 2016
VL 11
IS 3
BP 563
EP 582
PG 20
WC Zoology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Zoology
GA EJ4QM
UT WOS:000393201900017
DA 2025-01-10
ER

PT J
AU Johnson, JE
   Welch, DJ
   Maynard, JA
   Bell, JD
   Pecl, G
   Robins, J
   Saunders, T
AF Johnson, Johanna E.
   Welch, David J.
   Maynard, Jeffrey A.
   Bell, Johann D.
   Pecl, Gretta
   Robins, Julie
   Saunders, Thor
TI Assessing and reducing vulnerability to climate change: Moving from
   theory to practical decision-support
SO MARINE POLICY
LA English
DT Article
DE Climate vulnerability; Assessment framework; Climate adaptation;
   Socio-ecological systems; Decision support
ID OPERATIONALIZING RESILIENCE; FISHERIES; CONSERVATION; ASSESSMENTS;
   MANAGEMENT; FRAMEWORK
AB As climate change continues to impact socio-ecological systems, tools that assist conservation managers to understand vulnerability and target adaptations are essential. Quantitative assessments of vulnerability are rare because available frameworks are complex and lack guidance for dealing with data limitations and integrating across scales and disciplines. This paper describes a semi-quantitative method for assessing vulnerability to climate change that integrates socio-ecological factors to address management objectives and support decision making. The method applies a framework first adopted by the Intergovernmental Panel on Climate Change and uses a structured 10-step process. The scores for each framework element are normalized and multiplied to produce a vulnerability score and then the assessed components are ranked from high to low vulnerability. Sensitivity analyses determine which indicators most influence the analysis and the resultant decision-making process so data quality for these indicators can be reviewed to increase robustness. Prioritisation of components for conservation considers other economic, social and cultural values with vulnerability rankings to target actions that reduce vulnerability to climate change by decreasing exposure or sensitivity and/or increasing adaptive capacity. This framework provides practical decision-support and has been applied to marine ecosystems and fisheries, with two case applications provided as examples: (1) food security in Pacific Island nations under climate-driven fish declines, and (2) fisheries in the Gulf of Carpentaria, northern Australia. The step-wise process outlined here is broadly applicable and can be undertaken with minimal resources using existing data, thereby having great potential to inform adaptive natural resource management in diverse locations.
C1 [Johnson, Johanna E.] C2O Coasts Climate Oceans, Cairns 4870, Australia.
   [Johnson, Johanna E.] James Cook Univ, Coll Marine & Environm Sci, Cairns 4870, Australia.
   [Welch, David J.] C2O Fisheries, Cairns 4870, Australia.
   [Welch, David J.] James Cook Univ, Coll Marine & Environm Sci, Ctr Sustainable Trop Fisheries & Aquaculture, Townsville, Qld 4811, Australia.
   [Maynard, Jeffrey A.] SymbioSeas & Marine Appl Res Ctr, Wilmington, NC 28411 USA.
   [Maynard, Jeffrey A.] CRIOBE, CNRS,EPHE, USR 3278, Lab dExcellence,CORAIL, Papetoai, Moorea, France.
   [Bell, Johann D.] Secretariat Pacific Community, Noumea, New Caledonia.
   [Pecl, Gretta] Univ Tasmania, Fisheries & Aquaculture Ctr, Inst Marine & Antarctic Studies, Hobart, Tas 7001, Australia.
   [Pecl, Gretta] Univ Tasmania, Ctr Marine Socioecol, Hobart, Tas 7001, Australia.
   [Robins, Julie] Agri Sci Queensland, Dept Agr & Fisheries, Brisbane, Qld, Australia.
   [Saunders, Thor] Northern Terr Dept Primary Ind & Fisheries, Darwin, NT 0800, Australia.
   [Bell, Johann D.] Univ Wollongong, Australian Natl Ctr Ocean Resources & Secur, Wollongong, NSW 2522, Australia.
C3 James Cook University; James Cook University; Universite PSL; Ecole
   Pratique des Hautes Etudes (EPHE); Centre National de la Recherche
   Scientifique (CNRS); CNRS - Institute of Ecology & Environment (INEE);
   University of Tasmania; University of Tasmania; Queensland Department of
   Agriculture & Fisheries; University of Wollongong
RP Johnson, JE (corresponding author), C2O Coasts Climate Oceans, Cairns 4870, Australia.; Johnson, JE (corresponding author), James Cook Univ, Coll Marine & Environm Sci, Cairns 4870, Australia.
EM johanna.johnson@jcu.edu.au; d.welch@c2o.net.au; maynardmarine@gmail.com;
   b.johann9@gmail.com; Gretta.Pecl@utas.edu.au;
   Julie.Robins@daf.qld.gov.au; thor.saunders@nt.gov.au
RI Johnson, Johanna/Y-6099-2019; Pecl, Gretta/D-7267-2011
OI Maynard, Dr Jeffrey/0000-0002-6444-6373; Bell,
   Johann/0000-0003-2152-536X; Pecl, Gretta/0000-0003-0192-4339
FU Great Barrier Reef Marine Park Authority; Secretariat of the Pacific
   Community; Australian AID; Australian Fisheries Management Authority;
   Protected Zone Joint Authority; Australian Government's Fisheries
   Research and Development Corporation [2013/0014]; Department of Climate
   Change and Energy Efficiency; European Research Commission Marie Curie
   Actions Fellowship; ARC Future Fellowship
FX Funding for this study and the case applications was provided by these
   institutions and programs: Great Barrier Reef Marine Park Authority,
   Secretariat of the Pacific Community, Australian AID, Australian
   Fisheries Management Authority and Protected Zone Joint Authority,
   Australian Government's Fisheries Research and Development Corporation
   (grant 2013/0014) and Department of Climate Change and Energy
   Efficiency. Funding was also provided by a European Research Commission
   Marie Curie Actions Fellowship and an ARC Future Fellowship. We are
   grateful to the many specialist scientists and local stakeholders that
   participated in the case examples. Figures were developed in
   collaboration with D. Tracey.
CR Akçakaya HR, 2006, GLOBAL CHANGE BIOL, V12, P2037, DOI 10.1111/j.1365-2486.2006.01253.x
   Allison EH, 2009, FISH FISH, V10, P173, DOI 10.1111/j.1467-2979.2008.00310.x
   [Anonymous], PRINCIPLES PRACTICE
   [Anonymous], CLIM CHANGE
   [Anonymous], VULNERABILITY TROPIC
   [Anonymous], CLIM DEV IN PRESS
   [Anonymous], VULNERABILITY TROPIC
   [Anonymous], 2011, SCANNING CONSERVATIO
   [Anonymous], 2011, VULNERABILITY TROPIC
   [Anonymous], PAC ISL REG COAST FI
   Anthony KRN, 2015, GLOBAL CHANGE BIOL, V21, P48, DOI 10.1111/gcb.12700
   Beaugrand G., 2015, MARINE BIODIVERSITY
   Beaugrand G, 2015, NAT CLIM CHANGE, V5, P695, DOI [10.1038/nclimate2650, 10.1038/NCLIMATE2650]
   Bell J., 2015, Building climate-resilient food systems for Pacific Islands
   Bell JD, 2013, NAT CLIM CHANGE, V3, P591, DOI 10.1038/NCLIMATE1838
   Bell JD, 2013, CLIMATIC CHANGE, V119, P199, DOI 10.1007/s10584-012-0606-2
   Bell JD, 2009, MAR POLICY, V33, P64, DOI 10.1016/j.marpol.2008.04.002
   Cinner JE, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0074321
   Davidson JL, 2013, ECOL SOC, V18, DOI 10.5751/ES-05607-180304
   Dawson TP, 2011, SCIENCE, V332, P53, DOI 10.1126/science.1200303
   Doubleday ZA, 2013, AQUACULT ENV INTERAC, V3, P163, DOI 10.3354/aei00058
   Foden WB, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0065427
   Füssel HM, 2007, GLOBAL ENVIRON CHANG, V17, P155, DOI 10.1016/j.gloenvcha.2006.05.002
   Füssel HM, 2006, CLIMATIC CHANGE, V75, P301, DOI 10.1007/s10584-006-0329-3
   Gardali T, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0029507
   Gillett R., 2009, Fisheries in the Economies of the Pacific Island Countries and Territories
   Hare JA, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0146756
   Heenan A, 2015, MAR POLICY, V57, P182, DOI 10.1016/j.marpol.2015.03.018
   Hobday AJ, 2011, FISH RES, V108, P372, DOI 10.1016/j.fishres.2011.01.013
   Holsten A, 2012, NAT HAZARDS, V64, P1977, DOI 10.1007/s11069-012-0147-z
   Johnson J.E., 2007, CLIMATE CHANGE GREAT
   Johnson JE, 2016, CLIMATIC CHANGE, V135, P611, DOI 10.1007/s10584-015-1583-z
   Johnson JE, 2010, REV FISH SCI, V18, P106, DOI 10.1080/10641260903434557
   Kelly PM, 2000, CLIMATIC CHANGE, V47, P325, DOI 10.1023/A:1005627828199
   Lankford AJ, 2014, WILDLIFE SOC B, V38, P386, DOI 10.1002/wsb.399
   Leith P, 2014, CLIMATIC CHANGE, V122, P55, DOI 10.1007/s10584-013-0984-0
   Marshall N. A., 2010, A framework for social adaptation to climate change: sustaining tropical coastal communitites and industries
   Marshall NA, 2007, ECOL SOC, V12, DOI 10.5751/es-01940-120101
   Martin TG, 2012, CONSERV BIOL, V26, P29, DOI 10.1111/j.1523-1739.2011.01806.x
   Maynard JA, 2015, BIOL CONSERV, V192, P109, DOI 10.1016/j.biocon.2015.09.001
   Metcalf SJ, 2015, ECOL SOC, V20, DOI 10.5751/ES-07509-200235
   Metternicht G, 2014, INT J CLIM CHANG STR, V6, P442, DOI 10.1108/IJCCSM-06-2013-0076
   Miller F, 2013, IMPACT ASSESS PROJ A, V31, P190, DOI 10.1080/14615517.2013.819724
   Pachauri RK, 2014, 2014 IEEE STUDENTS' CONFERENCE ON ELECTRICAL, ELECTRONICS AND COMPUTER SCIENCE (SCEECS)
   Pacifici M, 2015, NAT CLIM CHANGE, V5, P215, DOI 10.1038/NCLIMATE2448
   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]
   Rowland EL, 2011, ENVIRON MANAGE, V47, P322, DOI 10.1007/s00267-010-9608-x
   Schneider SH, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P779
   Singh PK, 2014, CLIMATIC CHANGE, V127, P475, DOI 10.1007/s10584-014-1275-0
   Small-Lorenz SL, 2013, NAT CLIM CHANGE, V3, P91, DOI 10.1038/nclimate1810
   Soares MB, 2012, INT J CLIM CHANG STR, V4, P6, DOI 10.1108/17568691211200191
   Thomas CD, 2011, METHODS ECOL EVOL, V2, P125, DOI 10.1111/j.2041-210X.2010.00065.x
   Tonmoy FN, 2014, WIRES CLIM CHANGE, V5, P775, DOI 10.1002/wcc.314
   Welch D. J., 2014, Vulnerability assessment and adaptations FRDC Project No: 2010/565 Report, P236
   Welch DJ, 2013, ASSESSING VULNERABIL, P114
NR 55
TC 41
Z9 45
U1 4
U2 74
PU ELSEVIER SCI LTD
PI London
PA 125 London Wall, London, ENGLAND
SN 0308-597X
EI 1872-9460
J9 MAR POLICY
JI Mar. Pol.
PD DEC
PY 2016
VL 74
BP 220
EP 229
DI 10.1016/j.marpol.2016.09.024
PG 10
WC Environmental Studies; International Relations
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; International Relations
GA EF7EY
UT WOS:000390494100027
DA 2025-01-10
ER

PT J
AU Evteev, AA
   Movsesian, AA
AF Evteev, Andrej A.
   Movsesian, Alla A.
TI Testing the association between human mid-facial morphology and climate
   using autosomal, mitochondrial, Y chromosomal polymorphisms and cranial
   non-metrics
SO AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY
LA English
DT Article
DE climatic adaptation; mid-face; population genetics
ID POPULATION HISTORY; GLOBAL PATTERNS; MANTEL TEST; DNA; DIVERSITY; MTDNA;
   MIGRATION; HETEROZYGOSITY; DISTANCES; SELECTION
AB ObjectivesTo figure out which and how many systems of genetic markers should be used to control for the effects of shared population history in studies examining the association between morphology and climate and to test cranial non-metric traits as an additional source of neutral distances for such studies.
   Materials and MethodsWe employed three systems of genetic markers (mtDNA, Y-chromosome and autosomal SNPs) and cranial non-metrics to control for potential impact of population history on apparent associations between climatic variables and mid-facial morphology found in a set of seven North Asian and one East Asian populations.
   ResultsA significant association between morphology and climate remained, independent of which of the four neutral distance matrices were used as a control. Matrices of neutral distances based on different systems of genetic markers show just one case of significant correlation among each other namely between the mtDNA and autosomal SNPs matrices. The correlation between the autosomal SNP and cranial non-metrics matrices is also fairly high but does not reach significance.
   DiscussionA combination of several sources of genetic information could provide a more robust control for the effect of shared population history compared to just one type of markers since each of them has its own sources of bias and each provides a slightly different view of genetic relationships among the populations. Use of cranial non-metrics in researches examining the association between morphology and climate appears promising as they produce results that are generally consistent with those obtained using genetic markers. Am J Phys Anthropol 159:517-522, 2016. (c) 2015 Wiley Periodicals, Inc.
C1 [Evteev, Andrej A.] Moscow MV Lomonosov State Univ, Anuchins Res Inst, 11 Mokhovaya St, Moscow 125009, Russia.
   [Evteev, Andrej A.] Moscow MV Lomonosov State Univ, Museum Anthropol, 11 Mokhovaya St, Moscow 125009, Russia.
   [Movsesian, Alla A.] Moscow MV Lomonosov State Univ, Dept Anthropol, 1-12 Leninskie Gory, Moscow 119991, Russia.
C3 Lomonosov Moscow State University; Lomonosov Moscow State University;
   Lomonosov Moscow State University
RP Evteev, AA (corresponding author), Moscow MV Lomonosov State Univ, Anuchins Res Inst, 11 Mokhovaya St, Moscow 125009, Russia.; Evteev, AA (corresponding author), Moscow MV Lomonosov State Univ, Museum Anthropol, 11 Mokhovaya St, Moscow 125009, Russia.
EM evteandr@gmail.com
RI Movsesian, Alla/AAF-9718-2021; Evteev, Andrej/H-6538-2014
OI Evteev, Andrej/0000-0002-6254-1203
FU Russian Science Foundation [14-50-00029]; Russian Foundation for Basic
   Research [13-06-00045a, 14-06-00442a]
FX Grant sponsor: Russian Science Foundation; Grant number: 14-50-00029;
   Grant sponsor: Russian Foundation for Basic Research; Grant number:
   13-06-00045a, 14-06-00442a.
CR Aimé C, 2015, AM J PHYS ANTHROPOL, V157, P217, DOI 10.1002/ajpa.22707
   [Anonymous], 1989, Cladistics
   BERRY AC, 1967, J ANAT, V101, P361
   Buikstra JE, 1994, ARKANSAS ARCHEOL SUR, V44, P85
   Derenko M, 2006, HUM GENET, V118, P591, DOI 10.1007/s00439-005-0076-y
   Evteev A, 2014, AM J PHYS ANTHROPOL, V153, P449, DOI 10.1002/ajpa.22444
   González-José R, 2004, AM J PHYS ANTHROPOL, V123, P69, DOI 10.1002/ajpa.10302
   Hammer O, 2001, PAST PALAEONTOLOGICA
   Hanihara T, 2003, AM J PHYS ANTHROPOL, V121, P241, DOI 10.1002/ajpa.10233
   Harvati K, 2006, ANAT REC PART A, V288A, P1225, DOI 10.1002/ar.a.20395
   Hauser G., 1989, EPIGENETIC VARIANTS
   Hernandez M, 1997, AM J PHYS ANTHROPOL, V103, P103, DOI 10.1002/(SICI)1096-8644(199705)103:1<103::AID-AJPA7>3.3.CO;2-B
   Herrera B, 2014, AM J PHYS ANTHROPOL, V154, P334, DOI 10.1002/ajpa.22513
   Heyer E, 2012, MOL ECOL, V21, P597, DOI 10.1111/j.1365-294X.2011.05406.x
   Perez SI, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0005746
   Jorde LB, 2000, AM J HUM GENET, V66, P979, DOI 10.1086/302825
   Kittles RA, 1999, AM J PHYS ANTHROPOL, V108, P381, DOI 10.1002/(SICI)1096-8644(199904)108:4<381::AID-AJPA1>3.0.CO;2-5
   Klingenberg CP, 2011, MOL ECOL RESOUR, V11, P353, DOI 10.1111/j.1755-0998.2010.02924.x
   Lazaridis I, 2014, NATURE, V513, P409, DOI 10.1038/nature13673
   Legendre P, 2010, MOL ECOL RESOUR, V10, P831, DOI 10.1111/j.1755-0998.2010.02866.x
   Lell JT, 2002, AM J HUM GENET, V70, P192, DOI 10.1086/338457
   Lum JK, 1998, AM J HUM GENET, V63, P613, DOI 10.1086/301949
   Malyarchuk BA, 1996, AM J HUM GENET, V59, P1167
   Merriwether DA, 1997, AM J PHYS ANTHROPOL, V102, P153, DOI 10.1002/(SICI)1096-8644(199702)102:2<153::AID-AJPA1>3.0.CO;2-#
   Movsesian A.A., 2005, Feneticheskii analiz v paleoantropologii
   Movsessian AA, 2005, RUSS J GENET+, V41, P1046, DOI 10.1007/s11177-005-0198-2
   NEI M, 1978, GENETICS, V89, P583
   Noback ML, 2011, AM J PHYS ANTHROPOL, V145, P599, DOI 10.1002/ajpa.21523
   Oota H, 2001, NAT GENET, V29, P20, DOI 10.1038/ng711
   OSSENBERG NS, 1976, AM J PHYS ANTHROPOL, V45, P701, DOI 10.1002/ajpa.1330450337
   Passarino G, 1998, AM J HUM GENET, V62, P420, DOI 10.1086/301702
   Pérez-Lezaun A, 1999, AM J HUM GENET, V65, P208, DOI 10.1086/302451
   Reich D, 2012, NATURE, V488, P370, DOI 10.1038/nature11258
   Relethford JH, 2004, HUM BIOL, V76, P499, DOI 10.1353/hub.2004.0060
   Relethford JH, 2010, AM J PHYS ANTHROPOL, V142, P105, DOI 10.1002/ajpa.21207
   Ricaut FX, 2010, AM J PHYS ANTHROPOL, V143, P355, DOI 10.1002/ajpa.21322
   Roseman CC, 2004, P NATL ACAD SCI USA, V101, P12824, DOI 10.1073/pnas.0402637101
   Roseman CC, 2007, BIOESSAYS, P1185
   Rubicz R, 2010, AM J PHYS ANTHROPOL, V143, P62, DOI 10.1002/ajpa.21290
   Ruiz-Pesini E, 2004, SCIENCE, V303, P223, DOI 10.1126/science.1088434
   Schurr TG, 2004, AM J HUM BIOL, V16, P420, DOI 10.1002/ajhb.20041
   Smith HF, 2009, AM J HUM BIOL, V21, P36, DOI 10.1002/ajhb.20805
   SMOUSE PE, 1986, SYST ZOOL, V35, P627, DOI 10.2307/2413122
   Stojanowski CM, 2006, YEARB PHYS ANTHROPOL, V49, P49, DOI 10.1002/ajpa.20517
   Su B, 1999, AM J HUM GENET, V65, P1718, DOI 10.1086/302680
   Sun C, 2007, GENOMICS, V89, P338, DOI 10.1016/j.ygeno.2006.11.005
   Tambets K, 2004, AM J HUM GENET, V74, P661, DOI 10.1086/383203
   Van Oldenborgh GJ, 2005, J CLIMATE, V18, P3250, DOI 10.1175/JCLI3421.1
   von Cramon-Taubadel N, 2009, AM J PHYS ANTHROPOL, V140, P205, DOI 10.1002/ajpa.21041
   von Cramon-Taubadel N, 2009, J HUM EVOL, V57, P179, DOI 10.1016/j.jhevol.2009.05.009
   Wilder JA, 2004, NAT GENET, V36, P1122, DOI 10.1038/ng1428
NR 51
TC 11
Z9 13
U1 0
U2 10
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0002-9483
EI 1096-8644
J9 AM J PHYS ANTHROPOL
JI Am. J. Phys. Anthropol.
PD MAR
PY 2016
VL 159
IS 3
BP 517
EP 522
DI 10.1002/ajpa.22894
PG 6
WC Anthropology; Evolutionary Biology
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Anthropology; Evolutionary Biology
GA DF1KD
UT WOS:000371097400012
PM 26567130
DA 2025-01-10
ER

PT J
AU Sun, X
   Renard, B
   Thyer, M
   Westra, S
   Lang, M
AF Sun, Xun
   Renard, Benjamin
   Thyer, Mark
   Westra, Seth
   Lang, Michel
TI A global analysis of the asymmetric effect of ENSO on extreme
   precipitation
SO JOURNAL OF HYDROLOGY
LA English
DT Article
DE ENSO; Asymmetric relationship; Extreme precipitation; Bayesian regional
   modeling; GEV distribution; Climate-informed model
ID NINO-SOUTHERN-OSCILLATION; CONTIGUOUS UNITED-STATES; EL-NINO; CLIMATE
   VARIABILITY; FREQUENCY-ANALYSIS; RAINFALL ANOMALIES; BAYESIAN FRAMEWORK;
   SUMMER RAINFALL; LA-NINA; EVENTS
AB The global and regional influence of the El Nino-Southern Oscillation (ENSO) phenomenon on extreme precipitation was analyzed using a global database comprising over 7000 high quality observation sites. To better quantify possible changes in relatively rare design-relevant precipitation quantiles (e.g. the 1 in 10 year event), a Bayesian regional extreme value model was used, which employed the Southern Oscillation Index (SOI) - a measure of ENSO - as a covariate. Regions found to be influenced by ENSO include parts of North and South America, southern and eastern Asia, South Africa, Australia and Europe. The season experiencing the greatest ENSO effect varies regionally, but in most of the ENSO-affected regions the strongest effect happens in boreal winter, during which time the 10-year precipitation for vertical bar SOI vertical bar = 20 (corresponding to either a strong El Nino or La Nina episode) can be up to 50% higher or lower than for SOI = 0 (a neutral phase). Importantly, the effect of ENSO on extreme precipitation is asymmetric, with most parts of the world experiencing a significant effect only for a single ENSO phase. This finding has important implications on the current understanding of how ENSO influences extreme precipitation, and will enable a more rigorous theoretical foundation for providing quantitative extreme precipitation intensity predictions at seasonal timescales. We anticipate that incorporating asymmetric impacts of ENSO on extreme precipitation will help lead to better-informed climate-adaptive design of flood-sensitive infrastructure. (C) 2015 Elsevier B.V. All rights reserved.
C1 [Sun, Xun] Columbia Univ, Earth Inst, Columbia Water Ctr, New York, NY 10027 USA.
   [Renard, Benjamin; Lang, Michel] Ctr Lyon Villeurbanne, Irstea, UR HHLY, F-69626 Villeurbanne, France.
   [Thyer, Mark; Westra, Seth] Univ Adelaide, Sch Civil Environm & Min Engn, Adelaide, SA 5005, Australia.
C3 Columbia University; INRAE; University of Adelaide
RP Sun, X (corresponding author), Columbia Univ, Earth Inst, Columbia Water Ctr, New York, NY 10027 USA.
EM xs2226@columbia.edu
RI Renard, Benjamin/O-3369-2019; Thyer, Mark/A-9630-2011; LANG,
   Michel/AFT-9040-2022; Westra, Seth/C-8268-2009
OI LANG, Michel/0000-0003-1417-1495; Westra, Seth/0000-0003-4023-6061;
   Renard, Benjamin/0000-0001-8447-5430; Sun, Xun/0000-0002-9985-3876
FU Australian Research Council (ARC) [DP150100411]; Electricite de France
   (EDF); Irstea DRI; Region Rhone-Alpes (Explora'doc); University of
   Adelaide (through ARC) [DP1094796]; American International Group
   [CU12-2326]; Australian Research Council [DP1094796] Funding Source:
   Australian Research Council
FX We wish to acknowledge Dr Lisa Alexander who provided us with the global
   observed extreme precipitation HadEx2 dataset. This data set is now
   available at http://www.climdex.org/index.html. We wish to acknowledge
   Prof. Upmanu Lall for suggestion and comments, and Prof. Dmitri Kavetski
   for providing the FORTRAN library DMSL. Rfortran software library (Thyer
   et al., 2011) is used for the data and commands transfer between FORTRAN
   and R. Dr Westra's time was supported by Australian Research Council
   (ARC) Discovery project DP150100411. We also wish to acknowledge the
   research funding provided by Electricite de France (EDF), Irstea DRI,
   Region Rhone-Alpes (Explora'doc), the University of Adelaide (through
   ARC Discovery Project DP1094796) and the American International Group
   (CU12-2326).
CR Ahern M, 2005, EPIDEMIOL REV, V27, P36, DOI 10.1093/epirev/mxi004
   Alexander LV, 2009, J GEOPHYS RES-ATMOS, V114, DOI 10.1029/2009JD012301
   Aryal SK, 2009, J HYDROMETEOROL, V10, P241, DOI 10.1175/2008JHM1007.1
   Bellenger H, 2014, CLIM DYNAM, V42, P1999, DOI 10.1007/s00382-013-1783-z
   BENJAMINI Y, 1995, J R STAT SOC B, V57, P289, DOI 10.1111/j.2517-6161.1995.tb02031.x
   Bernard E, 2013, J CLIMATE, V26, P7929, DOI 10.1175/JCLI-D-12-00836.1
   Blanchet J, 2011, ANN APPL STAT, V5, P1699, DOI 10.1214/11-AOAS464
   Cai W, 2009, GEOPHYS RES LETT, V36, DOI 10.1029/2009GL040163
   Cai W., 2012, Geophysical Research Letters, V39
   Cai WJ, 2010, J CLIMATE, V23, P4944, DOI 10.1175/2010JCLI3501.1
   Castello AF, 2004, INT J CLIMATOL, V24, P481, DOI 10.1002/joc.1011
   Cayan DR, 1999, J CLIMATE, V12, P2881, DOI 10.1175/1520-0442(1999)012<2881:EAHEIT>2.0.CO;2
   Chen JM, 2008, J METEOROL SOC JPN, V86, P297, DOI 10.2151/jmsj.86.297
   Coles S, 2003, J HYDROL, V273, P35, DOI 10.1016/S0022-1694(02)00353-0
   Coles S., 2001, An Introduction to Statistical Modeling of Extreme Values, DOI DOI 10.1007/978-1-4471-3675-0
   Cooley D., 2005, SPATIAL BAYESIAN HIE
   Curtis S, 2007, J HYDROMETEOROL, V8, P678, DOI 10.1175/JHM601.1
   Dai A, 1997, J CLIMATE, V10, P2943, DOI 10.1175/1520-0442(1997)010<2943:SOGLPV>2.0.CO;2
   Dai A, 2000, GEOPHYS RES LETT, V27, P1283, DOI 10.1029/1999GL011140
   Denham R, 2007, BAYESIAN ANAL, V2, P99, DOI 10.1214/07-BA205
   Donat MG, 2013, J GEOPHYS RES-ATMOS, V118, P2098, DOI 10.1002/jgrd.50150
   Favre AC, 2004, WATER RESOUR RES, V40, DOI 10.1029/2003WR002456
   Feng J, 2011, J GEOPHYS RES-ATMOS, V116, DOI 10.1029/2010JD015160
   Fernández HW, 2002, ING HIDRAUL MEX, V17, P5
   Fisher RA, 1928, P CAMB PHILOS SOC, V24, P180, DOI 10.1017/S0305004100015681
   Frey HC, 1999, RISK ANAL, V19, P109, DOI 10.1023/A:1006962412150
   Gelman A., 1992, Statistical Science, V7, P457, DOI DOI 10.1214/SS/1177011136
   Gershunov A, 1998, J CLIMATE, V11, P1575, DOI 10.1175/1520-0442(1998)011<1575:EIOIER>2.0.CO;2
   Gräler B, 2011, PROCEDIA ENVIRON SCI, V7, P206, DOI 10.1016/j.proenv.2011.07.036
   Grimm AM, 2011, STOCH ENV RES RISK A, V25, P537, DOI 10.1007/s00477-010-0420-1
   Grimm AM, 2009, J CLIMATE, V22, P1589, DOI 10.1175/2008JCLI2429.1
   Hanel M, 2009, J GEOPHYS RES-ATMOS, V114, DOI 10.1029/2009JD011712
   Hannachi A, 2001, J CLIMATE, V14, P2138, DOI 10.1175/1520-0442(2001)014<2138:TANIOT>2.0.CO;2
   Higgins RW, 2011, J HYDROMETEOROL, V12, P1056, DOI 10.1175/JHM-D-10-05039.1
   Hoerling MP, 1997, J CLIMATE, V10, P1769, DOI 10.1175/1520-0442(1997)010<1769:ENOLNA>2.0.CO;2
   Hoerling MP, 2001, J CLIMATE, V14, P1277, DOI 10.1175/1520-0442(2001)014<1277:ROTNCR>2.0.CO;2
   Jin EK, 2008, CLIM DYNAM, V31, P647, DOI 10.1007/s00382-008-0397-3
   Johnson F, 2011, J CLIMATE, V24, P3609, DOI 10.1175/2011JCLI3732.1
   Jones C, 2012, J CLIMATE, V25, P4898, DOI 10.1175/JCLI-D-11-00278.1
   Kane RP, 1999, INT J CLIMATOL, V19, P653, DOI 10.1002/(SICI)1097-0088(199905)19:6<653::AID-JOC379>3.0.CO;2-C
   Katz RW, 2002, ADV WATER RESOUR, V25, P1287, DOI 10.1016/S0309-1708(02)00056-8
   Kayano MT, 2006, J GEOPHYS RES-ATMOS, V111, DOI 10.1029/2005JD006142
   Kenyon J, 2010, J CLIMATE, V23, P6248, DOI 10.1175/2010JCLI3617.1
   Kiem AS, 2009, AUSTRALAS J WAT RESO, V13, P17, DOI 10.1080/13241583.2009.11465357
   King A.D., 2013, GEOPHYS RES LETT, P1
   Kripalani RH, 1997, INT J CLIMATOL, V17, P1155, DOI 10.1002/(SICI)1097-0088(199709)17:11<1155::AID-JOC188>3.0.CO;2-B
   Kruger AC, 1999, INT J CLIMATOL, V19, P59, DOI 10.1002/(SICI)1097-0088(199901)19:1<59::AID-JOC347>3.0.CO;2-B
   Kuczera G, 1999, WATER RESOUR RES, V35, P1551, DOI 10.1029/1999WR900012
   Kwon HH, 2008, J AM WATER RESOUR AS, V44, P436, DOI 10.1111/j.1752-1688.2008.00173.x
   Latif M., 2013, EGU GEN ASS C, P5348
   Li C, 2012, ADV ATMOS SCI, V29, P1129, DOI 10.1007/s00376-012-1248-z
   Lima CHR, 2010, J HYDROL, V383, P307, DOI 10.1016/j.jhydrol.2009.12.045
   Lima CHR, 2010, J HYDROL, V381, P65, DOI 10.1016/j.jhydrol.2009.11.026
   Lyon B, 2005, J CLIMATE, V18, P5095, DOI 10.1175/JCLI3598.1
   Mannshardt-Shamseldin EC, 2010, ANN APPL STAT, V4, P484, DOI 10.1214/09-AOAS287
   Martins ES, 2000, WATER RESOUR RES, V36, P737, DOI 10.1029/1999WR900330
   Meehl GA, 2007, GEOPHYS RES LETT, V34, DOI 10.1029/2007GL031027
   Min SK, 2013, J GEOPHYS RES-ATMOS, V118, P643, DOI 10.1002/jgrd.50164
   O'Hagan A., 2006, UNCERTAIN JUDGEMENTS
   OrtizBeviá MJ, 2010, J GEOPHYS RES-ATMOS, V115, DOI 10.1029/2009JD013387
   Ouarda TBMJ, 2011, J AM WATER RESOUR AS, V47, P496, DOI 10.1111/j.1752-1688.2011.00544.x
   Pscheidt I, 2009, INT J CLIMATOL, V29, P1988, DOI 10.1002/joc.1799
   Renard B, 2006, WATER RESOUR RES, V42, DOI 10.1029/2005WR004591
   Renard B, 2008, WATER RESOUR RES, V44, DOI 10.1029/2007WR006268
   Renard B, 2007, ADV WATER RESOUR, V30, P897, DOI 10.1016/j.advwatres.2006.08.001
   Renard B, 2011, WATER RESOUR RES, V47, DOI [10.1029/2010WR010089, 10.1029/2011WR010643]
   Renard B., 2013, Extremes in a Changing Climate, P39
   Renard B, 2006, STOCH ENV RES RISK A, V21, P97, DOI 10.1007/s00477-006-0047-4
   Ribatet M, 2012, STAT SINICA, V22, P813, DOI 10.5705/ss.2009.248
   ROPELEWSKI CF, 1987, MON WEATHER REV, V115, P1606, DOI 10.1175/1520-0493(1987)115<1606:GARSPP>2.0.CO;2
   Sardeshmukh PD, 2000, J CLIMATE, V13, P4268, DOI 10.1175/1520-0442(2000)013<4268:COPAWE>2.0.CO;2
   Schubert SD, 2008, J CLIMATE, V21, P22, DOI 10.1175/2007JCLI1705.1
   Shang HW, 2011, WATER RESOUR RES, V47, DOI 10.1029/2011WR010415
   Sun X, 2015, WATER RESOUR RES, V51, P6586, DOI 10.1002/2015WR017117
   Sun X, 2014, J HYDROL, V512, P53, DOI 10.1016/j.jhydrol.2014.02.025
   Thyer M, 2011, ENVIRON MODELL SOFTW, V26, P219, DOI 10.1016/j.envsoft.2010.05.007
   Tramblay Y, 2012, GLOBAL PLANET CHANGE, V82-83, P104, DOI 10.1016/j.gloplacha.2011.12.002
   VANHEERDEN J, 1988, J CLIMATOL, V8, P577, DOI 10.1002/joc.3370080603
   Ventura V, 2004, J CLIMATE, V17, P4343, DOI 10.1175/3199.1
   VICENS GJ, 1975, WATER RESOUR RES, V11, P405, DOI 10.1029/WR011i003p00405
   Viglione A, 2013, WATER RESOUR RES, V49, P675, DOI 10.1029/2011WR010782
   Wan SQ, 2013, INT J CLIMATOL, V33, P806, DOI 10.1002/joc.3466
   Ward PJ, 2014, HYDROL EARTH SYST SC, V18, P47, DOI 10.5194/hess-18-47-2014
   Ward PJ, 2014, P NATL ACAD SCI USA, V111, P15659, DOI 10.1073/pnas.1409822111
   Westra S, 2014, REV GEOPHYS, V52, P522, DOI 10.1002/2014RG000464
   Westra S, 2011, J HYDROL, V406, P119, DOI 10.1016/j.jhydrol.2011.06.014
   WOOD EF, 1975, WATER RESOUR RES, V11, P533, DOI 10.1029/WR011i004p00533
   WOOD EF, 1975, WATER RESOUR RES, V11, P839, DOI 10.1029/WR011i006p00839
   Wu AM, 2005, J CLIMATE, V18, P1736, DOI 10.1175/JCLI3372.1
   Wu RG, 2003, J CLIMATE, V16, P3742, DOI 10.1175/1520-0442(2003)016<3742:EOERAI>2.0.CO;2
NR 90
TC 127
Z9 134
U1 4
U2 104
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 2015
VL 530
BP 51
EP 65
DI 10.1016/j.jhydrol.2015.09.016
PG 15
WC Engineering, Civil; Geosciences, Multidisciplinary; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Geology; Water Resources
GA CW5QD
UT WOS:000365050600005
OA Green Submitted
DA 2025-01-10
ER

PT J
AU Schmitz, OJ
   Barton, BT
AF Schmitz, Oswald J.
   Barton, Brandon T.
TI Climate change effects on behavioral and physiological ecology of
   predator-prey interactions: Implications for conservation biological
   control
SO BIOLOGICAL CONTROL
LA English
DT Article
DE Natural enemies; Agricultural pests; Habitat conservation; Habitat
   domain; Biological control; Climate adaptation
ID NATURAL ENEMY BIODIVERSITY; TOP-DOWN CONTROL; HERBIVORE SUPPRESSION;
   INTRAGUILD PREDATION; SPECIES INTERACTIONS; ECOSYSTEM RESPONSES; CROP
   YIELD; BODY-SIZE; TEMPERATURE; ADAPTATION
AB Habitat management under the auspices of conservation biological control is a widely used approach to foster conditions that ensure a diversity of predator species can persist spatially and temporally within agricultural landscapes in order to control their prey (pest) species. However, an emerging new factor, global climate change, has the potential to disrupt existing conservation biological control programs. Climate change may alter abiotic conditions such as temperature, precipitation, humidity and wind that in turn could alter the life-cycle timing of predator and prey species and the behavioral nature and strength of their interactions. Anticipating how climate change will affect predator and prey communities represents an important research challenge. We present a conceptual framework-the habitat domain concept-that is useful for understanding contingencies in the nature of predator diversity effects on prey based on predator and prey spatial movement in their habitat. We illustrate how this framework can be used to forecast whether biological control by predators will become more effective or become disrupted due to changing climate. We discuss how changes in predator-prey interactions are contingent on the tolerances of predators and prey species to changing abiotic conditions as determined by the degree of local adaptation and phenotypic plasticity exhibited by species populations. We conclude by discussing research approaches that are needed to help adjust conservation biological control management to deal with a climate future. (C) 2013 Elsevier Inc. All rights reserved.
C1 [Schmitz, Oswald J.] Yale Univ, Sch Forestry & Environm Studies, New Haven, CT 06511 USA.
   [Barton, Brandon T.] Univ Wisconsin, Dept Zool, Madison, WI 53706 USA.
C3 Yale University; University of Wisconsin System; University of Wisconsin
   Madison
RP Schmitz, OJ (corresponding author), Yale Univ, Sch Forestry & Environm Studies, 370 Prospect St, New Haven, CT 06511 USA.
EM oswald.schmitz@yale.edu
FU Direct For Biological Sciences; Division Of Environmental Biology
   [1240892] Funding Source: National Science Foundation; Division Of
   Environmental Biology; Direct For Biological Sciences [1240804, 1241031]
   Funding Source: National Science Foundation
CR [Anonymous], 1993, BIOTIC INTERACTIONS
   Aquilino KM, 2005, OIKOS, V108, P275, DOI 10.1111/j.0030-1299.2005.13418.x
   Baker RHA, 2000, AGR ECOSYST ENVIRON, V82, P57, DOI 10.1016/S0167-8809(00)00216-4
   Barton BT, 2011, P ROY SOC B-BIOL SCI, V278, P3102, DOI 10.1098/rspb.2011.0030
   Barton BT, 2009, ECOL LETT, V12, P1317, DOI 10.1111/j.1461-0248.2009.01386.x
   Bijlsma R, 2005, J EVOLUTION BIOL, V18, P744, DOI 10.1111/j.1420-9101.2005.00962.x
   Both C, 2009, J ANIM ECOL, V78, P73, DOI 10.1111/j.1365-2656.2008.01458.x
   Cardinale BJ, 2003, ECOL LETT, V6, P857, DOI 10.1046/j.1461-0248.2003.00508.x
   Carroll SP, 2007, FUNCT ECOL, V21, P387, DOI 10.1111/j.1365-2435.2007.01289.x
   Chown SL, 2004, FUNCT ECOL, V18, P159, DOI 10.1111/j.0269-8463.2004.00825.x
   Chown SL, 2008, P ROY SOC B-BIOL SCI, V275, P1469, DOI 10.1098/rspb.2008.0137
   Crowder DW, 2014, BIOL CONTROL, V75, P8, DOI 10.1016/j.biocontrol.2013.10.010
   Cudmore TJ, 2010, J APPL ECOL, V47, P1036, DOI 10.1111/j.1365-2664.2010.01848.x
   DeBlock M., 2012, GLOBAL CHANGE BIOL
   Deutsch CA, 2008, P NATL ACAD SCI USA, V105, P6668, DOI 10.1073/pnas.0709472105
   Farnsworth EJ, 1995, J ECOL, V83, P967, DOI 10.2307/2261178
   Ferguson KI, 1996, OECOLOGIA, V108, P375, DOI 10.1007/BF00334664
   Finke DL, 2004, NATURE, V429, P407, DOI 10.1038/nature02554
   Forbes KJ, 2011, ECOL ENTOMOL, V36, P396, DOI 10.1111/j.1365-2311.2011.01268.x
   Gilman SE, 2010, TRENDS ECOL EVOL, V25, P325, DOI 10.1016/j.tree.2010.03.002
   Griffin JN, 2011, BIOL LETTERS, V7, P710, DOI 10.1098/rsbl.2011.0166
   Hairston NG, 2005, ECOL LETT, V8, P1114, DOI 10.1111/j.1461-0248.2005.00812.x
   Harmon JP, 2009, SCIENCE, V323, P1347, DOI 10.1126/science.1167396
   Hawlena D., 2010, AM NAT, V176, P536
   Hoffman A.N., 2012, FUNCTIONAL ECOLOGY
   HURD LE, 1990, ECOLOGY, V71, P2107, DOI 10.2307/1938624
   Klecka J, 2013, J ANIM ECOL, V82, P1031, DOI 10.1111/1365-2656.12078
   Kruse PD, 2008, ECOL ENTOMOL, V33, P305, DOI 10.1111/j.1365-2311.2007.00978.x
   Landis DA, 2000, ANNU REV ENTOMOL, V45, P175, DOI 10.1146/annurev.ento.45.1.175
   Lang A, 2003, OECOLOGIA, V134, P144, DOI 10.1007/s00442-002-1091-5
   Lang B, 2012, J ANIM ECOL, V81, P516, DOI 10.1111/j.1365-2656.2011.01931.x
   Letourneau DK, 2009, ANNU REV ECOL EVOL S, V40, P573, DOI 10.1146/annurev.ecolsys.110308.120320
   Lima SL, 2002, TRENDS ECOL EVOL, V17, P70, DOI 10.1016/S0169-5347(01)02393-X
   Losey JE, 1998, ECOLOGY, V79, P2143, DOI 10.2307/176717
   MARTIN AP, 1993, P NATL ACAD SCI USA, V90, P4087, DOI 10.1073/pnas.90.9.4087
   MCLAUGHLIN RL, 1989, AM NAT, V133, P654, DOI 10.1086/284943
   Mika AM, 2008, GLOBAL CHANGE BIOL, V14, P1721, DOI 10.1111/j.1365-2486.2008.01620.x
   Miller J.R.B., 2013, J ANIMAL ECOLOGY
   Northfield T.D., 2012, TRAIT MEDIATED INDIR
   Northfield TD, 2010, ECOL LETT, V13, P338, DOI 10.1111/j.1461-0248.2009.01428.x
   Oliver KM, 2010, ANNU REV ENTOMOL, V55, P247, DOI 10.1146/annurev-ento-112408-085305
   Palumbi SR, 2001, SCIENCE, V293, P1786, DOI 10.1126/science.293.5536.1786
   Pörtner HO, 2008, SCIENCE, V322, P690, DOI 10.1126/science.1163156
   POLIS GA, 1992, TRENDS ECOL EVOL, V7, P151, DOI 10.1016/0169-5347(92)90208-S
   Rall BC, 2012, PHILOS T R SOC B, V367, P2923, DOI 10.1098/rstb.2012.0242
   Rall BC, 2010, GLOBAL CHANGE BIOL, V16, P2145, DOI 10.1111/j.1365-2486.2009.02124.x
   Romero GQ, 2011, J ANIM ECOL, V80, P696, DOI 10.1111/j.1365-2656.2011.01808.x
   Rötter R, 1999, CLIMATIC CHANGE, V43, P651, DOI 10.1023/A:1005541132734
   Schmalhofer VR, 1999, ECOL ENTOMOL, V24, P345, DOI 10.1046/j.1365-2311.1999.00198.x
   Schmidt Oswald J., 2005, P256
   Schmitz 0.J., 2010, Resolving ecosystem complexity
   Schmitz OJ, 2003, BIOSCIENCE, V53, P1199, DOI 10.1641/0006-3568(2003)053[1199:ERTGCC]2.0.CO;2
   Schmitz OJ, 2001, ECOLOGY, V82, P2072, DOI 10.1890/0012-9658(2001)082[2072:EOTPSO]2.0.CO;2
   Schmitz OJ, 2007, ECOLOGY, V88, P2415, DOI 10.1890/06-0937.1
   Schoener TW, 2011, SCIENCE, V331, P426, DOI 10.1126/science.1193954
   Schulte PM, 2011, INTEGR COMP BIOL, V51, P691, DOI 10.1093/icb/icr097
   Sheldon KS, 2011, ECOL LETT, V14, P1191, DOI 10.1111/j.1461-0248.2011.01689.x
   Sokol-Hessner L, 2002, ECOLOGY, V83, P2367, DOI 10.1890/0012-9658(2002)083[2367:AEOMPS]2.0.CO;2
   Somero GN, 2010, J EXP BIOL, V213, P912, DOI 10.1242/jeb.037473
   Straub CS, 2008, ECOLOGY, V89, P1605, DOI 10.1890/07-0657.1
   Straub CS, 2008, BIOL CONTROL, V45, P225, DOI 10.1016/j.biocontrol.2007.05.013
   Straub CS, 2006, ECOLOGY, V87, P277, DOI 10.1890/05-0599
   Sunday JM, 2011, P ROY SOC B-BIOL SCI, V278, P1823, DOI 10.1098/rspb.2010.1295
   Thackeray SJ, 2010, GLOBAL CHANGE BIOL, V16, P3304, DOI 10.1111/j.1365-2486.2010.02165.x
   Thomson LJ, 2010, BIOL CONTROL, V52, P296, DOI 10.1016/j.biocontrol.2009.01.022
   Traill LW, 2010, J ANIM ECOL, V79, P937, DOI 10.1111/j.1365-2656.2010.01695.x
   Trussell GC, 2008, ECOLOGY, V89, P2798, DOI 10.1890/08-0250.1
   Tylianakis JM, 2008, ECOL LETT, V11, P1351, DOI 10.1111/j.1461-0248.2008.01250.x
   Tylianakis JM, 2014, BIOL CONTROL, V75, P77, DOI 10.1016/j.biocontrol.2013.10.003
   Tylianakis JM, 2010, BASIC APPL ECOL, V11, P657, DOI 10.1016/j.baae.2010.08.005
   Visser ME, 2008, P ROY SOC B-BIOL SCI, V275, P649, DOI 10.1098/rspb.2007.0997
   Vucic-Pestic O, 2011, GLOBAL CHANGE BIOL, V17, P1301, DOI 10.1111/j.1365-2486.2010.02329.x
   Welch KD, 2014, BIOL CONTROL, V75, P18, DOI 10.1016/j.biocontrol.2014.01.004
   Williams JW, 2007, FRONT ECOL ENVIRON, V5, P475, DOI 10.1890/070037
   Woodcock BA, 2011, J ANIM ECOL, V80, P495, DOI 10.1111/j.1365-2656.2010.01790.x
   Woodward G, 2002, J ANIM ECOL, V71, P1063, DOI 10.1046/j.1365-2656.2002.00669.x
   Zavaleta E, 2009, ANN NY ACAD SCI, V1162, P311, DOI 10.1111/j.1749-6632.2009.04448.x
NR 77
TC 76
Z9 80
U1 9
U2 219
PU ACADEMIC PRESS INC ELSEVIER SCIENCE
PI SAN DIEGO
PA 525 B ST, STE 1900, SAN DIEGO, CA 92101-4495 USA
SN 1049-9644
EI 1090-2112
J9 BIOL CONTROL
JI Biol. Control
PD AUG
PY 2014
VL 75
BP 87
EP 96
DI 10.1016/j.biocontrol.2013.10.001
PG 10
WC Biotechnology & Applied Microbiology; Entomology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biotechnology & Applied Microbiology; Entomology
GA AJ8ZI
UT WOS:000337996200010
DA 2025-01-10
ER

PT J
AU Sun, RH
   Chen, LD
AF Sun, Ranhao
   Chen, Liding
TI How can urban water bodies be designed for climate adaptation?
SO LANDSCAPE AND URBAN PLANNING
LA English
DT Article
DE Urban heat island; Urban cooling island; Microclimate; Land surface
   temperature; Landscape design
ID SURFACE-ENERGY BALANCE; HEAT-ISLAND; TEMPERATURE; MICROCLIMATE;
   LANDSCAPES; INTENSITY; ECOLOGY; COMFORT; IMPACT; MODEL
AB With rapid urbanization and population growth in Beijing, urban heat island (UHI) effects have become ever stronger. Methods for reducing the UHI effects by landscape design are becoming increasingly critical in urban planning studies. Water bodies form urban cooling islands (UCI) to mitigate the UHI effects. This study investigated the UCI intensity and efficiency of 197 water bodies in Beijing, and their relationships with four descriptors of microclimatic landscape design, including the water body area (WA), geometry (landscape shape index, LSI), location (DIST) in reference to a defined city center, and surrounding built-up proportion (PB). Data of land cover and land surface temperature (LST) were extracted from ASTER images of August 8 of 2007. The UCI intensity was defined as the maximum LST gradient outside a water body area, while the UCI efficiency was used to represent the UCI intensity per unit area of a water body. The results indicated that: (1) the mean UCI intensity and efficiency was 0.54 degrees C/hm and 1.76 degrees C/hm/ha, respectively: (2) the UCI intensity was positively correlated with WA and PB, and negatively correlated with LSI and DIST; and (3) the UCI efficiency was positively correlated with PB, and negatively correlated with WA, LSI and DIST. Results of this study may help urban planners and designers in decision making to achieve optimal urban landscape designs for a more ecologically sound and pleasant living environment. (C) 2011 Elsevier B.V. All rights reserved.
C1 [Sun, Ranhao; Chen, Liding] Chinese Acad Sci, Ecoenvironm Sci Res Ctr, Beijing 100085, Peoples R China.
C3 Chinese Academy of Sciences; Research Center for Eco-Environmental
   Sciences (RCEES)
RP Chen, LD (corresponding author), Chinese Acad Sci, Ecoenvironm Sci Res Ctr, Shuangqing Rd 18, Beijing 100085, Peoples R China.
EM rhsun@rcees.ac.cn; liding@rcees.ac.cn
RI sun, ranhao/AAM-6837-2021
OI Sun, Ranhao/0000-0003-2396-5131
FU Natural Science Foundation of China [40925003]; State Key Laboratory of
   Urban and Regional Ecology of China [SKLURE2008-1-02]
FX The work was financed by the Natural Science Foundation of China
   (40925003) and the Innovation Project of State Key Laboratory of Urban
   and Regional Ecology of China (SKLURE2008-1-02).
CR [Anonymous], WORLD URB PROSP 2009
   [Anonymous], 2008, WATER RECOVERY CLIMA
   BARRADAS VL, 1991, INT J BIOMETEOROL, V35, P24, DOI 10.1007/BF01040959
   Bastiaanssen WGM, 1998, J HYDROL, V212, P198, DOI 10.1016/S0022-1694(98)00254-6
   Bonan GB, 1997, CLIMATIC CHANGE, V37, P449, DOI 10.1023/A:1005305708775
   Bottyán Z, 2003, THEOR APPL CLIMATOL, V75, P233, DOI 10.1007/s00704-003-0735-7
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   BRISTOW KL, 1987, AGR FOREST METEOROL, V39, P49, DOI 10.1016/0168-1923(87)90015-3
   Buyantuyev A, 2010, LANDSCAPE ECOL, V25, P17, DOI 10.1007/s10980-009-9402-4
   Cai GY, 2011, INT J REMOTE SENS, V32, P1213, DOI 10.1080/01431160903469079
   Cao X, 2010, LANDSCAPE URBAN PLAN, V96, P224, DOI 10.1016/j.landurbplan.2010.03.008
   Chang CR, 2007, LANDSCAPE URBAN PLAN, V80, P386, DOI 10.1016/j.landurbplan.2006.09.005
   [丁海燕 Ding Haiyan], 2010, [气候变化研究进展, Advances in Climate Change Research], V6, P187
   Eliasson I, 2000, LANDSCAPE URBAN PLAN, V48, P31, DOI 10.1016/S0169-2046(00)00034-7
   Forman R., 1997, LAND MOSAICS ECOLOGY
   Georgi N. J., 2006, Urban Ecosystems, V9, P195, DOI 10.1007/s11252-006-8590-9
   Gillespie A, 1998, IEEE T GEOSCI REMOTE, V36, P1113, DOI 10.1109/36.700995
   Givoni Baruch., 1998, CLIMATE CONSIDERATIO
   Huang LM, 2008, BUILD ENVIRON, V43, P7, DOI 10.1016/j.buildenv.2006.11.025
   Hung T, 2006, INT J APPL EARTH OBS, V8, P34, DOI 10.1016/j.jag.2005.05.003
   Jauregui E, 1997, ATMOS ENVIRON, V31, P3821, DOI 10.1016/S1352-2310(97)00136-2
   JAUREGUI E, 1991, ENERG BUILDINGS, V15, P457
   Liu H, 2008, ENVIRON MONIT ASSESS, V144, P199, DOI 10.1007/s10661-007-9979-5
   Lovell ST, 2009, FRONT ECOL ENVIRON, V7, P212, DOI 10.1890/070178
   Makhzoumi JM, 2000, LANDSCAPE URBAN PLAN, V50, P167, DOI 10.1016/S0169-2046(00)00088-8
   McMichael AJ, 2000, B WORLD HEALTH ORGAN, V78, P1117
   Nichol JE, 2009, ATMOS RES, V94, P276, DOI 10.1016/j.atmosres.2009.06.011
   Oke T. R., 1987, Boundary layer climates, V2nd
   Patz JA, 2005, NATURE, V438, P310, DOI 10.1038/nature04188
   Rajasekar U, 2009, INT J REMOTE SENS, V30, P3531, DOI 10.1080/01431160802562289
   Rizwan AM, 2008, J ENVIRON SCI, V20, P120, DOI 10.1016/S1001-0742(08)60019-4
   Saaroni H, 2000, LANDSCAPE URBAN PLAN, V48, P1, DOI 10.1016/S0169-2046(99)00075-4
   Shashua-Bar L, 2000, ENERG BUILDINGS, V31, P221, DOI 10.1016/S0378-7788(99)00018-3
   Shashua-Bar L, 2009, LANDSCAPE URBAN PLAN, V92, P179, DOI 10.1016/j.landurbplan.2009.04.005
   Shi JiuXi Shi JiuXi, 2011, Scientia Silvae Sinicae, V47, P7
   Simonds JO, 2007, LANDSCAPE ARCHITECTU
   Slater G., 2010, THESIS U GUELPH GUEL
   [宋艳玲 Song Yanling], 2003, [中国生态农业学报, Chinese journal of eco-agriculture], V11, P126
   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
   Streutker DR, 2003, REMOTE SENS ENVIRON, V85, P282, DOI 10.1016/S0034-4257(03)00007-5
   Su Z, 2002, HYDROL EARTH SYST SC, V6, P85, DOI 10.5194/hess-6-85-2002
   Vanos JK, 2010, INT J BIOMETEOROL, V54, P319, DOI 10.1007/s00484-010-0301-9
   Weng QH, 2009, ISPRS J PHOTOGRAMM, V64, P335, DOI 10.1016/j.isprsjprs.2009.03.007
   Xiao RB, 2008, PHOTOGRAMM ENG REM S, V74, P451, DOI 10.14358/PERS.74.4.451
   Xu SL, 2009, ENVIRON MONIT ASSESS, V151, P289, DOI 10.1007/s10661-008-0270-1
   Yu C, 2006, ENERG BUILDINGS, V38, P105, DOI 10.1016/j.enbuild.2005.04.003
   Zhao CJ, 2011, BUILD ENVIRON, V46, P1174, DOI 10.1016/j.buildenv.2010.12.009
   [朱春阳 Zhu Chunyang], 2011, [生态学报, Acta Ecologica Sinica], V31, P383
NR 48
TC 254
Z9 298
U1 10
U2 232
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 MAR
PY 2012
VL 105
IS 1-2
BP 27
EP 33
DI 10.1016/j.landurbplan.2011.11.018
PG 7
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 913JU
UT WOS:000301874600005
DA 2025-01-10
ER

PT J
AU Medvedskyi, O
   Bleizgys, R
   Cesna, J
   Domeika, R
   Kukharets, S
   Hrudovij, R
AF Medvedskyi, Oleksandr
   Bleizgys, Rolandas
   Cesna, Jonas
   Domeika, Rolandas
   Kukharets, Savelii
   Hrudovij, Roman
TI The Study Design of a Double-Action Plate Vacuum Pump
SO PROCESSES
LA English
DT Article
DE injection pressure; rotation frequency; stator diameter; rotor length;
   eccentricity
ID TEAT CONDITION; MILKING; PERFORMANCE; EFFICIENCY
AB Rotary plate vacuum pumps have become widely used as a source of vacuum for milking systems. The main features of a plate vacuum pump include design simplicity, high efficiency, low cost and adaptability to climatic conditions. A plate vacuum pump requires the improvement of specific performance indicators. This refers to the indicator of specific productivity and specific energy intensity. It is possible to improve the vacuum pump by optimizing the design parameters and technological models of operation. The known studies allow the establishment of rational geometric parameters, the number of plates, the ratio of the main dimensions and eccentricity. However, the problem of reducing the degree of uneven air pumping from the vacuum system needs a scientific solution. The use of a vacuum cylinder in a vacuum line of an increased diameter partially solves the problem of vacuum pressure fluctuations. But such a decision requires additional material costs. In addition, the power of a vacuum pump increases to compensate for the pressure losses. In this study, the authors proposed the design of a double-action plate vacuum pump. It was proven that the simultaneous operation of combined rotors with plates shifted by 45 degrees decreased the degree of air pumping by 7.8%. The research results indicated that the productivity of the developed vacuum pump increased by 13.6%. The drive power increased by 12%, and the specific energy intensity was 20% lower than that of vacuum pumps with similar geometric parameters. The relationship between rational kinematic and design parameters of a double-action vacuum pump was established.
C1 [Medvedskyi, Oleksandr; Hrudovij, Roman] Polissia Natl Univ, Dept Agr Engn & Tech Serv, Staryi Blvd 7, UA-10007 Zhytomyr, Ukraine.
   [Bleizgys, Rolandas; Cesna, Jonas; Kukharets, Savelii] Vytautas Magnus Univ, Agr Acad, Dept Mech Energy & Biotechnol Engn, Studentu Str 11, LT-53362 Kaunas, Lithuania.
   [Domeika, Rolandas] Vytautas Magnus Univ, Agr Acad, Dept Agr Engn & Safety, Studentu Str 15A, LT-53362 Kaunas, Lithuania.
   [Kukharets, Savelii] Odessa State Agrarian Univ, Dept Agr Engn, Panteleimonivska St 13, UA-65012 Odessa, Ukraine.
C3 Ministry of Education & Science of Ukraine; Polissia National
   University; Vytautas Magnus University; Vytautas Magnus University;
   Ministry of Education & Science of Ukraine; Odesa State Agrarian
   University
RP Kukharets, S (corresponding author), Vytautas Magnus Univ, Agr Acad, Dept Mech Energy & Biotechnol Engn, Studentu Str 11, LT-53362 Kaunas, Lithuania.; Kukharets, S (corresponding author), Odessa State Agrarian Univ, Dept Agr Engn, Panteleimonivska St 13, UA-65012 Odessa, Ukraine.
EM aleksmedvedsky@gmail.com; rolandas.bleizgys@vdu.lt; jonas.cesna@vdu.lt;
   rolandas.domeika@vdu.lt; savelii.kukharets@vdu.lt; roma-grudovij@ukr.net
RI Medvedskyi, Oleksandr/A-8002-2018; Kukharets, Savelii/P-6067-2016
OI Kukharets, Savelii/0000-0002-5129-8746
CR Aliiev E., 2022, East.-Eur. J. Enterp. Technol, V4, P80, DOI [10.15587/1729-4061.2022.262215, DOI 10.15587/1729-4061.2022.262215]
   Aliiev E., 2022, East.-Eur. J. Enterp. Technol, V6, P62, DOI [10.15587/1729-4061.2022.267799, DOI 10.15587/1729-4061.2022.267799]
   [Anonymous], 1996, ISO 5707:2007
   Besier J, 2016, J DAIRY SCI, V99, P3096, DOI 10.3168/jds.2015-10340
   Bianchi G, 2015, APPL THERM ENG, V84, P276, DOI 10.1016/j.applthermaleng.2015.01.080
   Caria M, 2020, ANIMALS-BASEL, V10, DOI 10.3390/ani10071213
   Choo WC, 2021, INT J REFRIG, V131, P592, DOI 10.1016/j.ijrefrig.2021.08.004
   Dmytriv VT, 2020, INMATEH-AGRIC ENG, V61, P199, DOI 10.35633/inmateh-61-22
   Dmytriv VT, 2019, INMATEH-AGRIC ENG, V58, P57, DOI 10.35633/INMATEH-58-06
   Edward W., 2023, J. Fluids Eng, V44, P437, DOI [10.1115/1.4058184, DOI 10.1115/1.4058184]
   Geng KH, 2019, TRIBOL INT, V133, P111, DOI 10.1016/j.triboint.2018.11.030
   Golub G., 2018, East.-Eur. J. Enterp. Technol, V1, P12, DOI [10.15587/1729-4061.2018.121537, DOI 10.15587/1729-4061.2018.121537]
   Gu HD, 2022, INT J REFRIG, V142, P137, DOI 10.1016/j.ijrefrig.2022.06.009
   Gu HD, 2021, APPL THERM ENG, V186, DOI 10.1016/j.applthermaleng.2020.116526
   Hamaguchi M., 2024, Vac. Surf. Sci, V67, P156, DOI [10.1380/vss.67.156, DOI 10.1380/VSS.67.156]
   Khmelovskyi V., 2023, Conference Proceedings, V22, P357, DOI [10.22616/ERDev.2023.22.TF078, DOI 10.22616/ERDEV.2023.22.TF078]
   Kissell R. L., 2021, ALGORITHMIC TRADING, P197, DOI DOI 10.1016/B978-0-12-815630-8.00008-9
   Kong Q., 2021, PYTHON PROGRAMMING N, P279
   Lu K, 2023, ENERGIES, V16, DOI 10.3390/en16207035
   Lutsenko Mariia, 2021, Acta Sci., Anim. Sci., V43, pe51336, DOI 10.4025/actascianimsci.v43i1.51336
   Medvedskyi O, 2021, ENG RUR DEVELOP, P477, DOI 10.22616/ERDev.2021.20.TF099
   National University of Biological Resources and Nature Management of Ukraine Kyiv Ukraine Baki acoc oo caoBki: a. 72465 kpaa, 2012, Vacuum Pump of the Milking Plant Patent 72465 Ukraine, V16
   Odorcic M, 2019, ANIMAL, V13, pS94, DOI 10.1017/S1751731119000417
   Romeo G., 2020, Elements of Numerical Mathematical Economics with Excel Static and Dynamic Optimization, P695, DOI [10.1016/B978-0-12-817648-1.00013-X, DOI 10.1016/B978-0-12-817648-1.00013-X]
   Romero G, 2022, ANIMALS-BASEL, V12, DOI 10.3390/ani12010040
   Shailaj Kumar S., 2021, Int. J. Eng. Adv. Technol, V10, P155, DOI [10.35940/ijeat.C2252.0210321, DOI 10.35940/IJEAT.C2252.0210321]
   Shakya P, 2020, INT J REFRIG, V117, P23, DOI 10.1016/j.ijrefrig.2020.01.027
   Thaslim AA, 2014, APPL MECH MATER, V592-594, P1859, DOI 10.4028/www.scientific.net/AMM.592-594.1859
   Wernik J, 2017, APPL SCI-BASEL, V7, DOI 10.3390/app7121214
   Zhang YL, 2023, APPL SCI-BASEL, V13, DOI 10.3390/app13169378
   Zhytomir National Agroecological University, 2014, Vacuum Plate Rotor Pump Patent, Patent No. 106313
NR 31
TC 0
Z9 0
U1 5
U2 5
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2227-9717
J9 PROCESSES
JI Processes
PD AUG
PY 2024
VL 12
IS 8
AR 1731
DI 10.3390/pr12081731
PG 11
WC Engineering, Chemical
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering
GA E8Y3O
UT WOS:001305795600001
OA gold
DA 2025-01-10
ER

PT J
AU van Boheemen, LA
   Bou-Assi, S
   Uesugi, A
   Hodgins, KA
AF van Boheemen, Lotte A.
   Bou-Assi, Sarah
   Uesugi, Akane
   Hodgins, Kathryn A.
TI Rapid growth and defence evolution following multiple introductions
SO ECOLOGY AND EVOLUTION
LA English
DT Article
DE constitutive defence; evolution of increased competitive ability
   hypothesis; growth-defence trade-offs; inducible defence; invasive
   species; latitudinal adaptation; phenolic compounds; resource allocation
ID INCREASED COMPETITIVE ABILITY; AMBROSIA-ARTEMISIIFOLIA; INVASIVE PLANT;
   TRADE-OFFS; RESOURCE AVAILABILITY; ENEMY RELEASE; GENETIC
   DIFFERENTIATION; CONTEMPORARY EVOLUTION; BIOLOGICAL INVASIONS; HERBIVORY
   RESISTANCE
AB 1 Rapid adaptation can aid invasive populations in their competitive success. Resource allocation trade-off hypotheses predict higher resource availability or the lack of natural enemies in introduced ranges allow for increased growth and reproduction, thus contributing to invasive success. Evidence for such hypotheses is however equivocal and tests among multiple ranges over productivity gradients are required to provide a better understanding of the general applicability of these theories.
   2 Using common gardens, we investigated the adaptive divergence of various constitutive and inducible defence-related traits between the native North American and introduced European and Australian ranges, while controlling for divergence due to latitudinal trait clines, individual resource budgets, and population differentiation, using >11,000 SNPs.
   3 Rapid, repeated clinal adaptation in defence-related traits was apparent despite distinct demographic histories. We also identified divergence among ranges in some defence-related traits, although differences in energy budgets among ranges may explain some, but not all, defence-related trait divergence. We do not identify a general reduction in defence in concert with an increase in growth among the multiple introduced ranges as predicted trade-off hypotheses.
   4 Synthesis: The rapid spread of invasive species is affected by a multitude of factors, likely including adaptation to climate and escape from natural enemies. Unravelling the mechanisms underlying invasives' success enhances understanding of eco-evolutionary theory and is essential to inform management strategies in the face of ongoing climate change.
C1 [van Boheemen, Lotte A.; Bou-Assi, Sarah; Uesugi, Akane; Hodgins, Kathryn A.] Monash Univ, Sch Biol Sci, Clayton, Vic 3800, Australia.
C3 Monash University
RP van Boheemen, LA (corresponding author), Monash Univ, Sch Biol Sci, Clayton, Vic 3800, Australia.
EM la.vanboheemen@gmail.com
RI ; van Boheemen, Lotte Anna/C-5382-2017
OI Hodgins, Kathryn/0000-0003-2795-5213; van Boheemen, Lotte
   Anna/0000-0001-9199-7704; Uesugi, Akane/0000-0003-3363-5312
FU Monash University Startup Grant; ARC grant [DP180102531]
FX Monash University Startup Grant; ARC grant, Grant/Award Number:
   DP180102531
CR Agrawal A. A., 2010, Evolution After Darwin: The First 150Years, V150, P243
   Agrawal AA, 2003, ECOL LETT, V6, P712, DOI 10.1046/j.1461-0248.2003.00498.x
   Agrawal AA, 2015, AM NAT, V186, pE1, DOI 10.1086/681622
   Agrawal AA, 2011, FUNCT ECOL, V25, P420, DOI 10.1111/j.1365-2435.2010.01796.x
   Agrawal Anurag A., 1999, P45
   Allen WJ, 2017, GLOBAL ECOL BIOGEOGR, V26, P435, DOI 10.1111/geb.12550
   Allendorf F. W., 2003, Conservation Biology, V17, P24, DOI 10.1046/j.1523-1739.2003.02365.x
   [Anonymous], 2024, Package 'MuMIn'-Multi-Model Inference
   BASSETT IJ, 1975, CAN J PLANT SCI, V55, P463, DOI 10.4141/cjps75-072
   Bassman JH, 2004, PHOTOCHEM PHOTOBIOL, V79, P382, DOI 10.1562/SI-03-24.1
   Beaton LL, 2011, OIKOS, V120, P1413, DOI 10.1111/j.1600-0706.2011.18893.x
   Bhattacharya A, 2010, MOL PLANT PATHOL, V11, P705, DOI [10.1111/J.1364-3703.2010.00625.X, 10.1111/j.1364-3703.2010.00625.x]
   Bixenmann RJ, 2016, ECOL EVOL, V6, P6037, DOI 10.1002/ece3.2208
   BLOSSEY B, 1995, J ECOL, V83, P887, DOI 10.2307/2261425
   Blumenthal DM, 2006, ECOL LETT, V9, P887, DOI 10.1111/j.1461-0248.2006.00934.x
   Bossdorf O, 2005, OECOLOGIA, V144, P1, DOI 10.1007/s00442-005-0070-z
   Brandes D., 2006, Nachrichtenblatt des Deutschen Pflanzenschutzdienstes, V58, P286
   Campos-Vargas R, 2002, PHYSIOL PLANTARUM, V114, P73, DOI 10.1034/j.1399-3054.2002.1140111.x
   Cardarelli E, 2018, NEOBIOTA, P1, DOI [10.3897/neobiota.38.23562, 10.3897/neobiota.37.23562]
   Carrillo J, 2012, PLANT ECOL, V213, P945, DOI 10.1007/s11258-012-0055-z
   Chapman DS, 2014, GLOBAL CHANGE BIOL, V20, P192, DOI 10.1111/gcb.12380
   Chauvel B, 2006, J BIOGEOGR, V33, P665, DOI 10.1111/j.1365-2699.2005.01401.x
   Chown SL, 2015, EVOL APPL, V8, P23, DOI 10.1111/eva.12234
   Chun YJ, 2010, NEW PHYTOL, V185, P1100, DOI 10.1111/j.1469-8137.2009.03129.x
   Cipollini D, 2005, J CHEM ECOL, V31, P1255, DOI 10.1007/s10886-005-5284-3
   Cipollini D, 2012, BASIC APPL ECOL, V13, P432, DOI 10.1016/j.baae.2012.06.007
   Colautti RI, 2015, MOL ECOL, V24, P1999, DOI 10.1111/mec.13162
   Colautti RI, 2013, SCIENCE, V342, P364, DOI 10.1126/science.1242121
   Colautti RI, 2009, EVOL APPL, V2, P187, DOI 10.1111/j.1752-4571.2008.00053.x
   COLEY PD, 1985, SCIENCE, V230, P895, DOI 10.1126/science.230.4728.895
   Colomer-Ventura F, 2015, FUNCT ECOL, V29, P1475, DOI 10.1111/1365-2435.12463
   Constabel CP, 1998, PHYTOCHEMISTRY, V47, P507, DOI 10.1016/S0031-9422(97)00539-6
   Cronin JT, 2015, ECOLOGY, V96, P1115, DOI 10.1890/14-1091.1
   Dalin Peter, 2008, P89, DOI 10.1007/978-1-4020-8182-8_4
   Davis MA, 2000, J ECOL, V88, P528, DOI 10.1046/j.1365-2745.2000.00473.x
   DESROSARIOMARTI.H, 2015, PHIA POSTHOC INTERAC
   Dlugosch KM, 2015, NAT PLANTS, V1, DOI [10.1038/nplants.2015.66, 10.1038/NPLANTS.2015.66]
   Dlugosch KM, 2015, MOL ECOL, V24, P2095, DOI 10.1111/mec.13183
   Eigenbrode SD, 2008, BIOL INVASIONS, V10, P1373, DOI 10.1007/s10530-007-9212-z
   Endara MJ, 2011, FUNCT ECOL, V25, P389, DOI 10.1111/j.1365-2435.2010.01803.x
   Essl F, 2015, J ECOL, V103, P1069, DOI 10.1111/1365-2745.12424
   Estoup A, 2016, ANNU REV ECOL EVOL S, V47, P51, DOI 10.1146/annurev-ecolsys-121415-032116
   Facon B, 2006, TRENDS ECOL EVOL, V21, P130, DOI 10.1016/j.tree.2005.10.012
   Felker-Quinn E, 2013, ECOL EVOL, V3, P739, DOI 10.1002/ece3.488
   Fortuna TM, 2014, NEW PHYTOL, V204, P989, DOI 10.1111/nph.12983
   Franks SJ, 2008, AM NAT, V171, P678, DOI 10.1086/587078
   Fukano Y, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0049114
   Gaudeul M, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0017658
   Genton BJ, 2005, OECOLOGIA, V146, P404, DOI 10.1007/s00442-005-0234-x
   Gerber E, 2011, WEED RES, V51, P559, DOI 10.1111/j.1365-3180.2011.00879.x
   Gladieux P, 2011, BIOL INVASIONS, V13, P933, DOI 10.1007/s10530-010-9880-y
   GRIME JP, 1977, AM NAT, V111, P1169, DOI 10.1086/283244
   Gu X, 2014, ECOL ENTOMOL, V39, P1, DOI 10.1111/een.12054
   Hahn PG, 2016, TRENDS ECOL EVOL, V31, P646, DOI 10.1016/j.tree.2016.05.007
   Hauser MT, 2014, FRONT PLANT SCI, V5, DOI [10.3389/fpls.2014.00320, 10.3389/fpsyg.2014.00401]
   He WM, 2010, BIOL INVASIONS, V12, P3591, DOI 10.1007/s10530-010-9753-4
   Heredia JB, 2009, POSTHARVEST BIOL TEC, V51, P242, DOI 10.1016/j.postharvbio.2008.07.001
   Hodgins KA, 2011, J EVOLUTION BIOL, V24, P2731, DOI 10.1111/j.1420-9101.2011.02404.x
   Hodgins KA, 2018, ANN PLANT REV ONLINE, V1, P459, DOI 10.1002/9781119312994.apr0643
   Ito K, 2009, J THEOR BIOL, V260, P453, DOI 10.1016/j.jtbi.2009.07.002
   Jordan CY, 2015, ECOL EVOL, V5, pS962, DOI 10.1002/ece3.1821
   Joshi J, 2005, ECOL LETT, V8, P704, DOI 10.1111/j.1461-0248.2005.00769.x
   Katabuchi M, 2015, ECOL RES, V30, P1073, DOI 10.1007/s11284-015-1307-x
   Kazinczi G., 2008, Herbologia, V9, P55
   Keinänen M, 2001, J AGR FOOD CHEM, V49, P3553, DOI 10.1021/jf010200+
   Kessler A, 2002, ANNU REV PLANT BIOL, V53, P299, DOI 10.1146/annurev.arplant.53.100301.135207
   Koricheva J, 2004, AM NAT, V163, pE64, DOI 10.1086/382601
   Krishnamoorthy K, 2014, COMPUTATION STAT, V29, P215, DOI 10.1007/s00180-013-0445-2
   Kumschick S, 2013, J ECOL, V101, P378, DOI 10.1111/1365-2745.12044
   Lachmuth S, 2011, NEW PHYTOL, V192, P529, DOI 10.1111/j.1469-8137.2011.03808.x
   Lande R, 2015, MOL ECOL, V24, P2038, DOI 10.1111/mec.13037
   Lee CE, 2002, TRENDS ECOL EVOL, V17, P386, DOI 10.1016/S0169-5347(02)02554-5
   Lee J, 1997, PHYTOCHEMISTRY, V44, P589, DOI 10.1016/S0031-9422(96)00562-6
   Li ZH, 2010, MOLECULES, V15, P8933, DOI 10.3390/molecules15128933
   Lommen STE, 2018, BIOL INVASIONS, V20, P1475, DOI 10.1007/s10530-017-1640-9
   Macel M, 2017, OECOLOGIA, V184, P543, DOI 10.1007/s00442-017-3864-x
   Maron JL, 2001, OIKOS, V95, P361, DOI 10.1034/j.1600-0706.2001.950301.x
   Marwick B., 2018, cvequality: Tests for the equality of coefficients of variation from multiple groups
   MOLE S, 1994, OIKOS, V71, P3, DOI 10.2307/3546166
   Moles AT, 2011, NEW PHYTOL, V191, P777, DOI 10.1111/j.1469-8137.2011.03732.x
   Moles AT, 2011, FUNCT ECOL, V25, P380, DOI 10.1111/j.1365-2435.2010.01814.x
   Moreira X, 2014, ECOL LETT, V17, P537, DOI 10.1111/ele.12253
   Morris WF, 2006, OIKOS, V112, P102, DOI 10.1111/j.0030-1299.2006.14253.x
   Müller-Schärer H, 2014, WEED RES, V54, P109, DOI 10.1111/wre.12072
   Müller-Schärer H, 2004, TRENDS ECOL EVOL, V19, P417, DOI 10.1016/j.tree.2004.05.010
   Neilson EH, 2013, TRENDS PLANT SCI, V18, P250, DOI 10.1016/j.tplants.2013.01.001
   Orians CM, 2010, ANNU REV ENTOMOL, V55, P439, DOI 10.1146/annurev-ento-112408-085333
   Orrock JL, 2015, TRENDS ECOL EVOL, V30, P441, DOI 10.1016/j.tree.2015.06.005
   Oswalt Matthew L, 2008, Allergy Asthma Clin Immunol, V4, P130, DOI 10.1186/1710-1492-4-3-130
   Palmer B, 2012, BIOLOGICAL CONTROL OF WEEDS IN AUSTRALIA, P52
   Parker JD, 2013, ECOLOGY, V94, P985, DOI 10.1890/12-1810.1
   Prentis PJ, 2008, TRENDS PLANT SCI, V13, P288, DOI 10.1016/j.tplants.2008.03.004
   R Core Team, 2019, R LANG ENV STAT COMP
   Rasmann S, 2011, ECOL LETT, V14, P476, DOI 10.1111/j.1461-0248.2011.01609.x
   Rasmann S, 2009, ECOLOGY, V90, P2393, DOI 10.1890/08-1895.1
   Ricciardi A, 2007, CONSERV BIOL, V21, P329, DOI 10.1111/j.1523-1739.2006.00615.x
   Rius M, 2014, TRENDS ECOL EVOL, V29, P233, DOI 10.1016/j.tree.2014.02.003
   Sax DF, 2000, GLOBAL ECOL BIOGEOGR, V9, P363, DOI 10.1046/j.1365-2699.2000.00217.x
   Scheiner S M., 2001, Design and Analysis of Ecological Experiments, V2nd, P99, DOI [10.1093/oso/9780195131871.003.0006, DOI 10.1093/OSO/9780195131871.003.0006]
   Schrieber K, 2017, OIKOS, V126, P572, DOI 10.1111/oik.03781
   Sun Y, 2017, ECOSPHERE, V8, DOI 10.1002/ecs2.1731
   Taramarcaz P, 2005, SWISS MED WKLY, V135, P538
   Thébaud C, 2001, AM NAT, V157, P231, DOI 10.1086/318635
   Throop HL, 2005, OIKOS, V111, P91, DOI 10.1111/j.0030-1299.2005.14026.x
   Tian DL, 2012, PLANTA, V236, P1053, DOI 10.1007/s00425-012-1651-9
   Turner KG, 2015, ECOL EVOL, V5, P3183, DOI 10.1002/ece3.1599
   Turner KG, 2014, NEW PHYTOL, V202, P309, DOI 10.1111/nph.12634
   Uesugi A, 2017, EVOLUTION, V71, P1700, DOI 10.1111/evo.13247
   Uesugi A, 2016, J ECOL, V104, P876, DOI 10.1111/1365-2745.12542
   van Boheemen LA, 2017, MOL ECOL, V26, P5421, DOI 10.1111/mec.14293
   VAN NOORDWIJK AJ, 1986, AM NAT, V128, P137, DOI 10.1086/284547
   Van Zandt PA, 2007, ECOLOGY, V88, P1984, DOI 10.1890/06-1329.1
   VANSBOHEEMEN LA, 2018, NEW PHYTOL, V222, P1, DOI DOI 10.1101/420752
   Wang Y, 2013, ANN BOT-LONDON, V112, P751, DOI 10.1093/aob/mct129
   Wang Y, 2012, J ECOL, V100, P894, DOI 10.1111/j.1365-2745.2012.01980.x
   War AR, 2018, AOB PLANTS, V10, DOI 10.1093/aobpla/ply037
   War AR, 2012, PLANT SIGNAL BEHAV, V7, P1306, DOI 10.4161/psb.21663
   *WHO, 1998, GLOB SOL UV IND GLOB
   WILLEMSEN RW, 1975, AM J BOT, V62, P639, DOI 10.2307/2441944
   Woods EC, 2012, ECOL MONOGR, V82, P149, DOI 10.1890/11-1446.1
   Züst T, 2017, ANNU REV PLANT BIOL, V68, P513, DOI 10.1146/annurev-arplant-042916-040856
NR 121
TC 13
Z9 14
U1 4
U2 51
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 2045-7758
J9 ECOL EVOL
JI Ecol. Evol.
PD JUL
PY 2019
VL 9
IS 14
BP 7942
EP 7956
DI 10.1002/ece3.5275
EA JUN 2019
PG 15
WC Ecology; Evolutionary Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Evolutionary Biology
GA IN4KU
UT WOS:000478251100001
PM 31380062
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Warwell, MV
   Shaw, RG
AF Warwell, Marcus V.
   Shaw, Ruth G.
TI Climate-related genetic variation in a threatened tree species, <i>Pinus
   albicaulis</i>
SO AMERICAN JOURNAL OF BOTANY
LA English
DT Article
DE adaptive variation; aster models; bioclimate models; biogeography;
   climate-change impacts; ecological genetics; genecology; Pinaceae;
   provenance test; seed transfer
ID SEED TRANSFER GUIDELINES; ECOLOGICAL GENETICS; HEIGHT-GROWTH;
   DOUGLAS-FIR; ADAPTIVE SIGNIFICANCE; POPULATIONS; ADAPTATION; VEGETATION;
   DISPERSAL; HARDINESS
AB PREMISE OF THE STUDY:With ongoing climate change, understanding of intraspecific adaptive variation is critical for conservation and restoration of plant species. Such information is especially scarce for threatened and endangered tree species, such as Pinus albicaulis Engelm. Therefore, our principal aims were to assess adaptive variation and characterize its relationship with climate of seed origin.
   METHODS:We grew seedlings from 49 P. albicaulis populations representative of the interior northwestern United States in two common garden field experiments under warm-dry conditions that mimic climatic conditions predicted in the current century for areas within the species' range. Differences among populations were assessed for growth and survival. We then used regression to describe clines of apparent adaptive variation in relation to climate variation among the populations' origins.
   KEY RESULTS:We detected genetic divergence for growth and survival among populations of P. albicaulis. These differences corresponded to distinct climatic clines. Populations originating from locations with lower spring precipitation exhibited greater survival in response to natural drought. Populations originating from increasingly milder climates exhibited greater height growth under relatively limited stress in early years and greater fitness after 12 yr.
   CONCLUSIONS:The results suggest that P. albicaulis exhibits adaptive variation for drought tolerance and growth in response to selection pressures associated with variation in moisture availability and temperature, respectively. Even so, clinal variation was relatively gentle. Thus, apparent differences in local adaptation to climate among populations appears to be relatively low.
C1 [Warwell, Marcus V.] US Forest Serv, Rocky Mt Res Stn, USDA, 1221 S Main St, Moscow, ID 83843 USA.
   [Shaw, Ruth G.] Univ Minnesota, Dept Ecol Evolut & Behav, 1479 Gortner Ave, St Paul, MN 55108 USA.
C3 United States Department of Agriculture (USDA); United States Forest
   Service; University of Minnesota System; University of Minnesota Twin
   Cities
RP Warwell, MV (corresponding author), US Forest Serv, Rocky Mt Res Stn, USDA, 1221 S Main St, Moscow, ID 83843 USA.
EM mwarwell@fs.fed.us
RI Warwell, Marcus/AAY-9868-2020
FU USDA Rocky Mountain Research Station
FX The authors thank the USDA Rocky Mountain Research Station for funding.
   Many people provided assistance for this project including Donna
   Dekker-Robertson, Paul Leigh, Mose Harris IV, Amanda Link, Debra
   Eastman, and Drs. Charles Geyer, Nicholas Crookston, Gerald Rehfeldt,
   and Ned Klopfenstein. Thank you to Drs. Ned Klopfenstein, MeeSook Kim,
   Andrew David, Peter Tiffin, Jeannine Cavender-Bares, and three anonymous
   reviewers for their helpful comments on earlier drafts of this
   manuscript.
CR [Anonymous], 2011, Federal Register, V76, P42631
   [Anonymous], 2019, R LANG ENV STAT COMP
   [Anonymous], 1996, Keys to Soil Taxonomy, V7th
   ARISTA M, 1994, SILVAE GENET, V43, P155
   Bakker J. D., 2006, 5 GISF YAL U SCH FOR
   Bansal S, 2015, GLOBAL CHANGE BIOL, V21, P947, DOI 10.1111/gcb.12719
   Bower AD, 2008, AM J BOT, V95, P66, DOI 10.3732/ajb.95.1.66
   Bower AD, 2006, CAN J FOREST RES, V36, P1842, DOI 10.1139/X06-067
   Brosi BJ, 2009, FRONT ECOL ENVIRON, V7, P487, DOI 10.1890/080003
   Campbell R. K., 1974, Meddelelser fra Norsk Institutt for Skogforskning, V31, P544
   Clausen J., 1958, CARNEGIE I WASH PUBL, P615
   Cooper S. T., 1991, INTGTR236 USDA FOR S
   COSEWIC [Committee on the Status of Endangered Wildlife in Canada], 2012, CANADA GAZETTE, V146, P1162
   Darychuk N, 2012, CAN J FOREST RES, V42, P1530, DOI [10.1139/X2012-092, 10.1139/x2012-092]
   DAUBENMI.R, 1966, SCIENCE, V151, P291, DOI 10.1126/science.151.3708.291
   DAUBENMIRE R, 1968, ECOLOGY, V49, P431, DOI 10.2307/1934109
   Ellison AM, 2005, FRONT ECOL ENVIRON, V3, P479, DOI 10.1890/1540-9295(2005)003[0479:LOFSCF]2.0.CO;2
   *ENV CAN, 1994, CAN MONTHL CLIM DAT
   Falconer D. S., 1989, Introduction to quantitative genetics.
   Farnes P. E., 1990, GTRINT270 USDA FOR S
   Geyer CJ, 2007, BIOMETRIKA, V94, P415, DOI 10.1093/biomet/asm030
   Hamlin J., 2011, P HIGH 5 S MISS MONT
   Hamlin J. E., 2008, BREEDING GENETIC RES
   HESLOP-HARRISON J., 1964, ADVANCE ECOL RES, V2, P159
   HUTCHINS HE, 1982, OECOLOGIA, V55, P192, DOI 10.1007/BF00384487
   Johnson G. R., 2004, Native Plants Journal, V5, P131, DOI 10.2979/NPJ.2004.5.2.131
   Joyce DG, 2013, FOREST ECOL MANAG, V295, P173, DOI 10.1016/j.foreco.2012.12.024
   KAYA Z, 1994, TREE PHYSIOL, V14, P1277, DOI 10.1093/treephys/14.11.1277
   KING DA, 1990, AM NAT, V135, P809, DOI 10.1086/285075
   Larson ER, 2010, CAN J FOREST RES, V40, P476, DOI 10.1139/X10-005
   Leites LP, 2012, ECOL APPL, V22, P154, DOI 10.1890/11-0150.1
   LEVINS RICHARD, 1968
   Loya-Rebollar E, 2013, SILVAE GENET, V62, P86, DOI 10.1515/sg-2013-0011
   Mahalovich M.F., 1995, P 1995 NAT SILV WORK, P200
   Mahalovich MF, 2006, US FOR SERV RMRS-P, V43, P91
   Mattson D.J., 2001, Whitebark Pine Communities: Ecology and Restoration. Washington: Island Press, P121
   MATYAS C, 1992, SILVAE GENET, V41, P370
   MCGRAW JB, 1983, J THEOR BIOL, V103, P21, DOI 10.1016/0022-5193(83)90196-0
   Morgenstern E.K., 1996, Geographic variation in forest trees: genetic basis and application of knowledge in silviculture
   Mote PW, 2010, CLIMATIC CHANGE, V102, P29, DOI 10.1007/s10584-010-9848-z
   NAMKOONG G, 1976, FOREST SCI, V22, P2
   NAMKOONG G, 1972, THEOR APPL GENET, V42, P151, DOI 10.1007/BF00280791
   Ne'eman G, 2011, ANN BOT-LONDON, V108, P197, DOI 10.1093/aob/mcr104
   Page-Dumroese D. S., 1993, INTRN409 USDA FOR SE
   Rehfeldt G. E., 2006, GTR165 USDA FOR SERV
   Rehfeldt G. E., 2004, GTR134 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, 1995, FOREST ECOL MANAG, V78, P21, DOI 10.1016/0378-1127(95)03602-4
   REHFELDT GE, 1994, CAN J FOREST RES, V24, P670, DOI 10.1139/x94-090
   REHFELDT GE, 1982, SILVAE GENET, V31, P13
   REHFELDT GE, 1983, CAN J FOREST RES, V13, P405, DOI 10.1139/x83-061
   Rehfeldt GE, 2006, INT J PLANT SCI, V167, P1123, DOI 10.1086/507711
   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, 2010, MITIG ADAPT STRAT GL, V15, P283, DOI 10.1007/s11027-010-9217-2
   Richardson BA, 2002, MOL ECOL, V11, P215, DOI 10.1046/j.1365-294X.2002.01435.x
   Richardson BA, 2014, ECOL APPL, V24, P413, DOI 10.1890/13-0587.1
   Rothman K J, 1990, Epidemiology, V1, P43, DOI 10.1097/00001648-199001000-00010
   Shaw RG, 2008, AM NAT, V172, pE35, DOI 10.1086/588063
   SHEA KL, 1987, EVOLUTION, V41, P124, DOI [10.2307/2408977, 10.1111/j.1558-5646.1987.tb05775.x]
   St Clair JB, 2005, ANN BOT-LONDON, V96, P1199, DOI 10.1093/aob/mci278
   St Clair JB, 2013, EVOL APPL, V6, P933, DOI 10.1111/eva.12077
   TOMBACK D F, 1977, Living Bird, V16, P123
   Tomback D.F., 2001, Whitebark pine communities: Ecology and Restoration, P3
   Tuhkanen S., 1980, Acta Phytogeogr. Suec.
   Turesson G, 1925, HEREDITAS, V6, P147
   *US DEP COMM, 1994, US DIV STAT CLIM DAT, V1
   Warwell M.V., 2007, Proceedings of the conference whitebark pine: a Pacific Coast perspective, P139
   Weaver T., 2001, Whitbark Pine Communities: Ecology and Restoration, P41
   Weaver T., 1986, P CON TREE SEED INL, P68
   Ying CC, 2006, FOREST ECOL MANAG, V227, P1, DOI 10.1016/j.foreco.2006.02.028
NR 71
TC 15
Z9 15
U1 1
U2 32
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0002-9122
EI 1537-2197
J9 AM J BOT
JI Am. J. Bot.
PD AUG
PY 2017
VL 104
IS 8
BP 1205
EP 1218
DI 10.3732/ajb.1700139
PG 14
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA FQ8YT
UT WOS:000418649800009
PM 29756223
OA Bronze
DA 2025-01-10
ER

PT J
AU Kuussaari, M
   Heikkinen, RK
   Heliölä, J
   Luoto, M
   Mayer, M
   Rytteri, S
   von Bagh, P
AF Kuussaari, Mikko
   Heikkinen, Risto K.
   Heliola, Janne
   Luoto, Miska
   Mayer, Marianne
   Rytteri, Susu
   von Bagh, Peter
TI Successful translocation of the threatened Clouded Apollo butterfly
   (<i>Parnassius mnemosyne</i>) and metapopulation establishment in
   southern Finland
SO BIOLOGICAL CONSERVATION
LA English
DT Article
DE Assisted colonization; Dispersal barrier; Mark-release-recapture method;
   Reintroduction; Relocation; Residence time
ID LIFE-HISTORY TRAITS; CLIMATE-CHANGE; LEPIDOPTERA PAPILIONIDAE;
   FRAGMENTED LANDSCAPES; ASSISTED COLONIZATION; HABITAT RESTORATION;
   POPULATION-SIZE; HESPERIA-COMMA; REINTRODUCTION; CONSERVATION
AB Translocations have been advocated as a conservation tool helping species adapt to climate and land-use change, but well-documented examples of invertebrates' translocations are rare. The paper describes a successful translocation of the threatened Clouded Apollo butterfly (Parnassius mnemosyne) in Finland, compares this to a specific failed translocation, and presents conclusions for conservation planning as to factors contributing to the success. Two apparent key characteristics of the successful translocation were greater abundance of larval resources and less open landscape. The successful site was surrounded by forest, which strongly restricted emigration, crucially supporting the survival of the small initial population. Based on 20 mated females' translocation in 2000, the local population increased slowly, reaching 600 butterflies in 2011. A large translocation patch together with host-plant abundance enabled successful establishment of the local population. Availability of other suitable grassland patches sufficiently nearby was an additional key characteristic, facilitating the Clouded Apollo's expansion. However, the expansion rate was low; it took seven years for the butterflies to colonise the five nearest patches, only 10-200 m from the translocation patch. By 2013, they had colonised all suitable semi-natural grassland patches within 2 km from the translocation site and established a seemingly viable metapopulation with 11 subpopulations. The results point to the significance of local habitat area and landscape quality, along with conditions restricting emigration, in determination, of suitable translocation sites. (C) 2015 Elsevier Ltd. All rights reserved.
C1 [Kuussaari, Mikko; Heikkinen, Risto K.; Heliola, Janne; Rytteri, Susu] Finnish Environm Inst SYKE, Nat Environm Ctr, FI-00251 Helsinki, Finland.
   [Luoto, Miska] Univ Helsinki, Dept Geosci & Geog, FI-00014 Helsinki, Finland.
C3 Finnish Environment Institute; University of Helsinki
RP Kuussaari, M (corresponding author), Finnish Environm Inst SYKE, Nat Environm Ctr, POB 140, FI-00251 Helsinki, Finland.
EM mikko.kuussaari@ymparisto.fi
RI Heikkinen, Risto/AAN-6257-2020; Luoto, Miska/E-6693-2014; Kuussaari,
   Mikko/Y-4070-2019
OI Luoto, Miska/0000-0001-6203-5143; Kuussaari, Mikko/0000-0003-0264-9316;
   Rytteri, Susu/0000-0002-1289-3024
FU Metsahallitus; Finnish Ministry of the Environment, Societas Biologica
   Fennica Vanamo, Societas Entomologica Fennica; EU LIFE [LIFE10
   NAT/FI/0048]
FX We would like to thank Hannu Ormio for initiating the Clouded Apollo
   translocations and Svenska Litteratur Sallskapet, Metsahallitus and the
   Uusimaa Centre for Economic Development, Transport and the Environment
   for the positive attitude and permissions related to the translocations
   and their monitoring. We also thank Hanna Aho, Annika Harlio, Markus
   Haveri, Soili Huttunen, Elina Karhu, Marko Saarela, Elina Uotila, and
   Tea von Bonsdorff, for their help with the field work, and Raimo
   Virkkala and two anonymous reviewers, for helpful comments on the
   manuscript. We are grateful to Metsahallitus, the Finnish Ministry of
   the Environment, Societas Biologica Fennica Vanamo, Societas
   Entomologica Fennica, and the EU LIFE project titled 'Improving the
   Conservation Status of Species-rich Habitats' (LIFE10 NAT/FI/0048) for
   their part in the funding of the translocation project.
CR Andersen A, 2014, BIOL CONSERV, V175, P34, DOI 10.1016/j.biocon.2014.04.009
   Araújo MB, 2007, GLOBAL ECOL BIOGEOGR, V16, P743, DOI 10.1111/j.1466-8238.2007.00359.x
   Armstrong DP, 2008, TRENDS ECOL EVOL, V23, P20, DOI 10.1016/j.tree.2007.10.003
   Arponen A, 2013, BIOL CONSERV, V160, P234, DOI 10.1016/j.biocon.2013.01.018
   Austin MP, 1996, FOREST ECOL MANAG, V85, P95, DOI 10.1016/S0378-1127(96)03753-X
   Baguette M, 2013, J INSECT CONSERV, V17, P645, DOI 10.1007/s10841-013-9548-x
   Bennie J, 2008, ECOL MODEL, V216, P47, DOI 10.1016/j.ecolmodel.2008.04.010
   Bennie J, 2013, ECOL LETT, V16, P921, DOI 10.1111/ele.12129
   Boggs CL, 2006, J ANIM ECOL, V75, P466, DOI 10.1111/j.1365-2656.2006.01067.x
   Chan PK, 2006, RESTOR ECOL, V14, P645, DOI 10.1111/j.1526-100X.2006.00176.x
   Crone Elizabeth E., 2003, P561
   Davies ZG, 2006, J ANIM ECOL, V75, P247, DOI 10.1111/j.1365-2656.2006.01044.x
   Davies ZG, 2005, BIOL CONSERV, V124, P189, DOI 10.1016/j.biocon.2005.01.029
   Dover J, 2009, J INSECT CONSERV, V13, P3, DOI 10.1007/s10841-008-9135-8
   Eskildsen A, 2013, GLOBAL ECOL BIOGEOGR, V22, P1293, DOI 10.1111/geb.12078
   Ewen J.G., 2012, Reintroduction biology: integrating science and management
   Fischer J, 2000, BIOL CONSERV, V96, P1, DOI 10.1016/S0006-3207(00)00048-3
   Fred Marianne S., 2015, Conservation Evidence, V12, P8
   Hanski I, 2004, ON THE WINGS OF CHECKERSPOTS: A MODEL SYSTEM FOR POPULATION BIOLOGY, P264
   HARRISON S, 1989, ECOLOGY, V70, P1236, DOI 10.2307/1938181
   Heikkinen RK, 2005, P ROY SOC B-BIOL SCI, V272, P2203, DOI 10.1098/rspb.2005.3212
   Hill JK, 1996, J ANIM ECOL, V65, P725, DOI 10.2307/5671
   Hoegh-Guldberg O, 2008, SCIENCE, V321, P345, DOI 10.1126/science.1157897
   Hulden L., 2000, SUOMEN PERHOSTUTKIJA
   Konvicka M, 1999, J INSECT CONSERV, V3, P211, DOI 10.1023/A:1009641618795
   Kuussaari M, 1996, J ANIM ECOL, V65, P791, DOI 10.2307/5677
   Kuussaari M., 2013, BAPTRIA, V38, P70
   Lawson CR, 2012, J APPL ECOL, V49, P552, DOI 10.1111/j.1365-2664.2011.02098.x
   Liivamägi A, 2013, ENTOMOL FENNICA, V24, P186, DOI 10.33338/ef.8985
   Luoto M, 2003, AMBIO, V32, P447, DOI 10.1639/0044-7447(2003)032[0447:LOPSRA]2.0.CO;2
   Luoto M, 2002, J BIOGEOGR, V29, P1027, DOI 10.1046/j.1365-2699.2002.00728.x
   Luoto M, 2001, ECOGRAPHY, V24, P601, DOI 10.1034/j.1600-0587.2001.d01-215.x
   Marttila O, 1997, ANN ZOOL FENN, V34, P177
   McCune B, 2002, J VEG SCI, V13, P603, DOI 10.1111/j.1654-1103.2002.tb02087.x
   McIntire EJB, 2007, J APPL ECOL, V44, P725, DOI 10.1111/j.1365-2664.2007.01326.x
   Nowicki P, 2005, POPUL ECOL, V47, P203, DOI 10.1007/s10144-005-0223-2
   Oates MR, 1990, REV BUTTERFLY INTRO
   Öckinger E, 2010, ECOL LETT, V13, P969, DOI 10.1111/j.1461-0248.2010.01487.x
   Olden JD, 2011, CONSERV BIOL, V25, P40, DOI 10.1111/j.1523-1739.2010.01557.x
   Ovaskainen O, 2008, AM NAT, V171, P610, DOI 10.1086/587070
   Pelini SL, 2009, P NATL ACAD SCI USA, V106, P11160, DOI 10.1073/pnas.0900284106
   Pöyry J, 2009, GLOBAL CHANGE BIOL, V15, P732, DOI 10.1111/j.1365-2486.2008.01789.x
   Porter K, 2011, J INSECT CONSERV, V15, P111, DOI 10.1007/s10841-010-9328-9
   Ricketts TH, 2001, AM NAT, V158, P87, DOI 10.1086/320863
   Roland J, 2000, ECOLOGY, V81, P1642, DOI 10.1890/0012-9658(2000)081[1642:APBDEO]2.0.CO;2
   Schultz CB, 2008, ISR J ECOL EVOL, V54, P41, DOI 10.1560/IJEE.54.1.41
   Schultz CB, 2012, J ANIM ECOL, V81, P724, DOI 10.1111/j.1365-2656.2011.01947.x
   Seddon PJ, 2014, SCIENCE, V345, P406, DOI 10.1126/science.1251818
   Settele J, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P271
   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
   Thomas JA, 2009, SCIENCE, V325, P80, DOI 10.1126/science.1175726
   THOMAS JA, 1984, S ROYAL ENTOMOLOGICA, V11, P333
   Välimäki P, 2003, ECOGRAPHY, V26, P679, DOI 10.1034/j.1600-0587.2003.03551.x
   van Langevelde F, 2009, ANIM CONSERV, V12, P540, DOI 10.1111/j.1469-1795.2009.00281.x
   Van Swaay CAM, 2010, IUCN RED LIST THREAT, DOI 10.2305/IUCN.UK.2010-1.RLTS.T39491A10232607.en
   Vlasanek P, 2009, BIOLOGIA, V64, P1206, DOI 10.2478/s11756-009-0207-3
   Willis SG, 2009, CONSERV LETT, V2, P45, DOI 10.1111/j.1755-263X.2008.00043.x
   Wynhoff I, 1998, J INSECT CONSERV, V2, P47, DOI 10.1023/A:1009692723056
NR 59
TC 36
Z9 39
U1 1
U2 173
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0006-3207
EI 1873-2917
J9 BIOL CONSERV
JI Biol. Conserv.
PD OCT
PY 2015
VL 190
BP 51
EP 59
DI 10.1016/j.biocon.2015.05.011
PG 9
WC Biodiversity Conservation; Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA CO2FS
UT WOS:000358972200007
DA 2025-01-10
ER

PT J
AU Stojkovic, K
   Canovi, C
   Le, KC
   Ahmad, I
   Gaboreanu, I
   Johansson, S
   Delhomme, N
   Egertsdotter, U
   Street, NR
AF Stojkovic, Katja
   Canovi, Camilla
   Le, Kim-Cuong
   Ahmad, Iftikhar
   Gaboreanu, Ioana
   Johansson, Sofie
   Delhomme, Nicolas
   Egertsdotter, Ulrika
   Street, Nathaniel R.
TI A transcriptome atlas of zygotic and somatic embryogenesis in Norway
   spruce
SO PLANT JOURNAL
LA English
DT Article
DE Norway spruce; <italic>Picea abies</italic>; embryogenesis; embryo;
   transcriptome; differential expression
ID MEGAGAMETOPHYTE CELLS; SEED DEVELOPMENT; BRAZILIAN PINE; GENE-ONTOLOGY;
   PICEA-ABIES; ETHYLENE; MATURATION; GERMINATION; PROTEINS; SEQUENCE
AB Somatic embryogenesis (SE) is a powerful model system for studying embryo development and an important method for scaling up availability of elite and climate-adapted genetic material of Norway spruce (Picea abies L. Karst). However, there are several steps during the development of the somatic embryo (Sem) that are suboptimal compared to zygotic embryo (Zem) development. These differences are poorly understood and result in substantial yield losses during plant production, which limits cost-effective large-scale production of SE plants. This study presents a comprehensive data resource profiling gene expression during zygotic and somatic embryo development to support studies aiming to advance understanding of gene regulatory programmes controlling embryo development. Transcriptome expression patterns were analysed during zygotic embryogenesis (ZE) in Norway spruce, including separated samples of the female gametophytes and Zem, and at multiple stages during SE. Expression data from eight developmental stages of SE, starting with pro-embryogenic masses (PEMs) up until germination, revealed extensive modulation of the transcriptome between the early and mid-stage maturing embryos and at the transition of desiccated embryos to germination. Comparative analysis of gene expression changes during ZE and SE identified differences in the pattern of gene expression changes and functional enrichment of these provided insight into the associated biological processes. Orthologs of transcription factors known to regulate embryo development in angiosperms were differentially regulated during Zem and Sem development and in the different zygotic embryo tissues, providing clues to the differences in development observed between Zem and Sem. This resource represents the most comprehensive dataset available for exploring embryo development in conifers.
C1 [Stojkovic, Katja; Ahmad, Iftikhar; Gaboreanu, Ioana; Johansson, Sofie; Delhomme, Nicolas; Egertsdotter, Ulrika] Swedish Univ Agr Sci, Umea Plant Sci Ctr, Dept Forest Genet & Plant Physiol, SE-90187 Umea, Sweden.
   [Canovi, Camilla; Street, Nathaniel R.] Umea Univ, Umea Plant Sci Ctr, Dept Plant Physiol, SE-90187 Umea, Sweden.
   [Le, Kim-Cuong] Georgia Inst Technol, GW Woodruff Sch Mech Engn, Atlanta, GA USA.
   [Egertsdotter, Ulrika] Georgia Inst Technol Atlanta, Renewable Bioprod Inst, Atlanta, GA 30332 USA.
   [Street, Nathaniel R.] Umea Univ, Dept Plant Physiol, SciLifeLab, SE-90187 Umea, Sweden.
C3 Umea University; Swedish University of Agricultural Sciences; Umea
   University; University System of Georgia; Georgia Institute of
   Technology; University System of Georgia; Georgia Institute of
   Technology; SciLifeLab; Umea University
RP Egertsdotter, U (corresponding author), Swedish Univ Agr Sci, Umea Plant Sci Ctr, Dept Forest Genet & Plant Physiol, SE-90187 Umea, Sweden.; Street, NR (corresponding author), Umea Univ, Umea Plant Sci Ctr, Dept Plant Physiol, SE-90187 Umea, Sweden.; Egertsdotter, U (corresponding author), Georgia Inst Technol Atlanta, Renewable Bioprod Inst, Atlanta, GA 30332 USA.; Street, NR (corresponding author), Umea Univ, Dept Plant Physiol, SciLifeLab, SE-90187 Umea, Sweden.
EM ulrika.egertsdotter@slu.se; nathaniel.street@umu.se
RI Le, Cuong/JJC-8211-2023; Ahmad, Mirza/KHD-2053-2024; Delhomme,
   Nicolas/B-9187-2015; Street, Nathaniel/B-3920-2008
OI Street, Nathaniel/0000-0001-6031-005X
FU Kempe Foundation [SMK1340]; Trees for the Future (T4F) project; Knut and
   Alice Wallenberg Foundation; National Genomics Infrastructure in
   Genomics Production Stockholm - Science for Life Laboratory; Swedish
   Research Council
FX Katja Stojkovi & ccaron; was supported by a grant from the Kempe
   Foundation (SMK1340). Nathaniel Street and Ulrika Egertsdotter are
   supported by the Trees for the Future (T4F) project. This work was
   supported by grants from the Knut and Alice Wallenberg Foundation. The
   authors acknowledge support from the National Genomics Infrastructure in
   Genomics Production Stockholm funded by Science for Life Laboratory, the
   Knut and Alice Wallenberg Foundation and the Swedish Research Council,
   SNIC/Uppsala Multidisciplinary Center for Advanced Computational Science
   for assistance with massively parallel sequencing and access to the
   UPPMAX computational infrastructure and the Umea Plant Science Centre
   bioinformatics facility for support.
CR Ashburner M, 2000, NAT GENET, V25, P25, DOI 10.1038/75556
   Bai B, 2020, PLANT PHYSIOL, V182, P378, DOI 10.1104/pp.19.00644
   Bolger AM, 2014, BIOINFORMATICS, V30, P2114, DOI 10.1093/bioinformatics/btu170
   Borgstrom E, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0019119
   Cairney J, 2000, IN VITRO CELL DEV-PL, V36, P155, DOI 10.1007/s11627-000-0031-5
   Cairney J, 2007, NEW PHYTOL, V176, P511, DOI 10.1111/j.1469-8137.2007.02239.x
   Corbineau F, 2014, FRONT PLANT SCI, V5, DOI 10.3389/fpls.2014.00539
   Cui YD, 2021, FRONT IMMUNOL, V12, DOI 10.3389/fimmu.2021.690207
   Danisman S, 2016, FRONT PLANT SCI, V7, DOI 10.3389/fpls.2016.01930
   De La Torre AR, 2020, EVOL APPL, V13, P210, DOI 10.1111/eva.12839
   de Vega-Bartol JJ, 2013, BMC PLANT BIOL, V13, DOI 10.1186/1471-2229-13-123
   Durzan D., 2012, 2 INT C 20902 SOMATI
   Egertsdotter U, 2019, FRONT PLANT SCI, V10, DOI 10.3389/fpls.2019.00109
   Egertsdotter U, 2019, SCAND J FOREST RES, V34, P360, DOI 10.1080/02827581.2018.1441433
   El Meskaoui A, 2001, J EXP BOT, V52, P761, DOI 10.1093/jexbot/52.357.761
   El Meskaoui A, 2000, PHYSIOL PLANTARUM, V109, P333, DOI 10.1034/j.1399-3054.2000.100315.x
   Elbl P, 2015, PLANT CELL TISS ORG, V120, P903, DOI 10.1007/s11240-014-0523-3
   Evans E, 1972, Midwives Chron, V86, P118
   Fehér A, 2015, BBA-GENE REGUL MECH, V1849, P385, DOI 10.1016/j.bbagrm.2014.07.005
   Filonova LH, 2000, J EXP BOT, V51, P249, DOI 10.1093/jexbot/51.343.249
   Gentleman RC, 2004, GENOME BIOL, V5, DOI 10.1186/gb-2004-5-10-r80
   Grossmann S, 2007, BIOINFORMATICS, V23, P3024, DOI 10.1093/bioinformatics/btm440
   HAKMAN I, 1993, PHYSIOL PLANTARUM, V87, P148, DOI 10.1111/j.1399-3054.1993.tb00137.x
   Hassani SB, 2022, FRONT PLANT SCI, V13, DOI 10.3389/fpls.2022.838421
   He X, 2003, PLANT MOL BIOL, V51, P509, DOI 10.1023/A:1022319821591
   Jo L, 2014, TREE PHYSIOL, V34, P94, DOI 10.1093/treephys/tpt102
   Kermode AR, 2005, J PLANT GROWTH REGUL, V24, P319, DOI 10.1007/s00344-005-0110-2
   Kong LS, 1997, PHYSIOL PLANTARUM, V101, P23, DOI 10.1034/j.1399-3054.1997.1010104.x
   Kopylova E, 2012, BIOINFORMATICS, V28, P3211, DOI 10.1093/bioinformatics/bts611
   Kvaalen H, 1999, IN VITRO CELL DEV-PL, V35, P437, DOI 10.1007/s11627-999-0064-3
   Love MI, 2014, GENOME BIOL, V15, DOI 10.1186/s13059-014-0550-8
   Lu JR, 2011, PLANT CELL TISS ORG, V107, P25, DOI 10.1007/s11240-011-9952-4
   Lundin S, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0010029
   Mackay J, 2012, PLANT MOL BIOL, V80, P555, DOI 10.1007/s11103-012-9961-7
   Mamun NHA, 2018, IN VITRO CELL DEV-PL, V54, P612, DOI 10.1007/s11627-018-9911-4
   Merino I, 2016, BMC PLANT BIOL, V16, DOI 10.1186/s12870-016-0939-5
   Morel A, 2014, PLANTA, V240, P1075, DOI 10.1007/s00425-014-2125-z
   Müller M, 2015, PLANT PHYSIOL, V169, P32, DOI 10.1104/pp.15.00677
   Müssig C, 2010, PLANT BIOLOGY, V12, P381, DOI 10.1111/j.1438-8677.2009.00303.x
   Mulat M.W., 2020, PLANT GENE, V23, DOI [10.1016/j.plgene.2020.100230, DOI 10.1016/J.PLGENE.2020.100230]
   Nie YM, 2022, BMC PLANT BIOL, V22, DOI 10.1186/s12870-022-03554-4
   Nielsen UB, 2022, FRONT PLANT SCI, V13, DOI 10.3389/fpls.2022.989484
   Nystedt B, 2013, NATURE, V497, P579, DOI 10.1038/nature12211
   Owens J.N., 1984, REPROD CYCLE INTERIO
   OWENS JN, 1979, CAN J BOT, V57, P1557, DOI 10.1139/b79-194
   Poovaiah C, 2021, BMC PLANT BIOL, V21, DOI 10.1186/s12870-021-03143-x
   Pullman GS, 2014, NEW FOREST, V45, P353, DOI 10.1007/s11056-014-9407-y
   Pullman GS, 2003, PLANT CELL REP, V21, P747, DOI 10.1007/s00299-003-0586-9
   Raats M. M., 1992, Food Quality and Preference, V3, P89, DOI 10.1016/0950-3293(91)90028-D
   Raventós D, 1998, J BIOL CHEM, V273, P23313, DOI 10.1074/jbc.273.36.23313
   Rosvall O, 2019, SCAND J FOREST RES, V34, P333, DOI 10.1080/02827581.2018.1562565
   Rupps A, 2016, PLANTA, V243, P473, DOI 10.1007/s00425-015-2409-y
   Singh H., 1978, HDB PFLANZENANATOMIE, P187
   Soneson Charlotte, 2015, F1000Res, V4, P1521, DOI 10.12688/f1000research.7563.2
   Sundell D, 2015, NEW PHYTOL, V208, P1149, DOI 10.1111/nph.13557
   Tatematsu K, 2008, PLANT J, V53, P42, DOI 10.1111/j.1365-313X.2007.03308.x
   Trontin JF, 2016, METHODS MOL BIOL, V1359, P167, DOI 10.1007/978-1-4939-3061-6_8
   Uddenberg D, 2011, PLANTA, V234, P527, DOI 10.1007/s00425-011-1418-8
   Varis S, 2018, FRONT PLANT SCI, V9, DOI 10.3389/fpls.2018.01551
   Vetrici MA, 2021, PLANT DIRECT, V5, DOI 10.1002/pld3.333
   Von Arnold S., 2008, SPRUCE EMBRYOGENESIS, P31, DOI [10.1007/978-1-59745-273-13, DOI 10.1007/978-1-59745-273-13]
   Vuosku J, 2009, J EXP BOT, V60, P1375, DOI 10.1093/jxb/erp020
   Wang MH, 2015, SCI REP-UK, V5, DOI 10.1038/srep16923
   Yan Jie, 2021, Food Studies: An Interdisciplinary Journal, V12, P1, DOI 10.18848/2160-1933/CGP/v12i01/1-17
   Zhang YJ, 2023, ADV BIOL-GER, V7, DOI 10.1002/adbi.202200238
   Zhao HD, 2021, FRONT GENET, V12, DOI 10.3389/fgene.2021.616388
NR 66
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Z9 0
U1 12
U2 12
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0960-7412
EI 1365-313X
J9 PLANT J
JI Plant J.
PD DEC
PY 2024
VL 120
IS 5
BP 2238
EP 2252
DI 10.1111/tpj.17087
EA OCT 2024
PG 15
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA P0D3E
UT WOS:001342128400001
PM 39462439
OA hybrid, Green Submitted
DA 2025-01-10
ER

PT J
AU Regitsky, A
   da Rosa, J
AF Regitsky, Alec
   da Rosa, Jennifer
TI Extreme heat adaptation in urban areas: a comparative case study of New
   York City and New Orleans
SO LOCAL ENVIRONMENT
LA English
DT Article; Early Access
DE Extreme heat; climate adaptation; New York City; New Orleans; heat
   policy; cooling centre
ID HOT WEATHER; VULNERABILITY; MORTALITY
AB As the risk of extreme heat in urban centres becomes more frequent and intense, a comparative case study of New York City, New York's and New Orleans, Louisiana's policy responses to dangerous heat highlights past approaches to protecting vulnerable populations, where improvements can be made to best suit local needs, and the areas where solutions may still be implemented. Two cities at the forefront of the climate crisis in the United States, their policy approaches are guided by their histories, their existing adaptations and behaviours, and the harsh reality the changing climate has wrought. New York City has prioritised cooling centres as a safety measure, as the city is regularly seeing hundreds of heat-related deaths per year, often in unairconditioned homes. New Orleans has prioritised the installation of back-up energy generation following mass blackouts caused by Hurricane Ida in 2021 and deaths of at least 10 residents in the resulting excessive heat exposure. In New York, census tracts with the highest percentage of Black, elderly, and foreign-born populations were most likely to have reduced access to a cooling centre. In New Orleans, tracts with the highest percentage of Black, elderly, unemployed, and impoverished populations were most likely to have reduced access to a cooling centre. Comparing both city's codes, regulations, and policies, reviewing their emergency management communication strategies on social media, and performing GIS analysis on cooling centre locations against vulnerability criteria paints a clear picture of where heat policy stands in both cities and where it could potentially expand.
C1 [Regitsky, Alec] Johns Hopkins Univ, Energy Policy & Climate, Baltimore, MD 20001 USA.
   [da Rosa, Jennifer] Goucher Coll, Environm Sustainabil & Management, Baltimore, MD USA.
C3 Johns Hopkins University
RP Regitsky, A (corresponding author), Johns Hopkins Univ, Energy Policy & Climate, Baltimore, MD 20001 USA.
EM aregits1@alumni.jh.edu
OI da Rosa, Jennifer/0000-0003-0002-761X; Regitsky,
   Alec/0009-0003-0607-3411
CR Anderson J., 2019, Louisiana Morbidity Report. Louisiana Department of Public Health, V1, P11
   [Anonymous], 2019, National Weather Service Instruction 10-515: WFO Non-Precipitation Weather Products Specification
   [Anonymous], 2018, Climate Change Health Report
   [Anonymous], 2022, ArcGIS Living Atlas of the World
   [Anonymous], Home Energy Assistance Program (HEAP)
   Bailey ZD, 2017, LANCET, V389, P1453, DOI 10.1016/S0140-6736(17)30569-X
   Bogel-Burroughs N., 2021, The New York Times
   Bolitho A, 2017, LOCAL ENVIRON, V22, P682, DOI 10.1080/13549839.2016.1254169
   Chatlani S. P., 2021, WWNO 89.9 Public Radio
   City of New York, 2019, OneNYC 2050: A Livable Climate, V7
   City of New York's Mayor Office, 2020, Get Cool NYC: Mayor de Blasio Updates New Yorkers on COVID Summer Heat Plan Press release
   Climate Central, 2021, Hot Zones: Urban Heat Islands
   Department of Health and Mental Hygiene, 2022, 2022 New York City Heat-Related Mortality Report
   Ebi KL, 2021, LANCET, V398, P698, DOI 10.1016/S0140-6736(21)01208-3
   Eisenman DP, 2016, HEALTH PLACE, V41, P89, DOI 10.1016/j.healthplace.2016.08.007
   Gabbe CJ, 2021, J PLAN EDUC RES, DOI 10.1177/0739456X211053654
   Gaffin SR, 2008, THEOR APPL CLIMATOL, V94, P1, DOI 10.1007/s00704-007-0368-3
   GIS DCP, 2020, NYC DCP Mapping Portal
   Greater New Orleans Foundation, 2022, Foundation announces $1 million grant to community lighthouse project Press release
   Gronlund Carina J, 2014, Curr Epidemiol Rep, V1, P165
   Hawkins MD, 2017, WEATHER CLIM SOC, V9, P5, DOI 10.1175/WCAS-D-15-0037.1
   Ito K, 2018, EPIDEMIOLOGY, V29, P749, DOI 10.1097/EDE.0000000000000912
   Jay O, 2021, LANCET, V398, P709, DOI 10.1016/S0140-6736(21)01209-5
   Khourchid AM, 2022, BUILDINGS-BASEL, V12, DOI 10.3390/buildings12101519
   Louisiana Administrative Code, 2023, Title 48 Public Health-General
   Louisiana Climate Initiatives Task Force, 2022, Louisiana Climate Action Plan
   Louisiana Housing Corporation, 2022, Low Income Home Energy Assistance Program (LIHEAP): State of Louisiana Detailed Model State Plan
   Madrigano J, 2015, ENVIRON HEALTH PERSP, V123, P672, DOI 10.1289/ehp.1408178
   Manware M, 2022, GEOHEALTH, V6, DOI 10.1029/2022GH000695
   [Masson-Delmotte V. IPCC IPCC], 2021, Summary for Policy Makers
   Matte TD, 2016, HEALTH SECUR, V14, P64, DOI 10.1089/hs.2015.0059
   Mees HLP, 2015, REG ENVIRON CHANGE, V15, P1065, DOI 10.1007/s10113-014-0681-1
   National Weather Service New Orleans @NWSNewOrleans, Twitter
   National Weather Service New York NY @NWSNewYorkNY. n.d, Twitter
   Nayak SG, 2018, PUBLIC HEALTH, V161, P127, DOI 10.1016/j.puhe.2017.09.006
   New Orleans/Baton Rouge Weather Forecast Office, NWS LIX-Watch, Warning, Advisory Criteria
   New Orleans Health Department, 2021, Regulations Governing Housing Facilities for Seniors and Persons with Disabilities
   New Orleans Louisiana Code of Ordinances, 2023, Chapter 26-Buildings, Building Regulations and Housing Standards
   New Orleans Public Library, Find a Location Near You
   New Orleans Recreation Development Commission, Parks & Facilities
   New York City Construction Code, Building Code: Chapter 14-Exterior Walls
   New York City Construction Code, 2022, Building Code: Chapter 24-Glass and Glazing
   New York City Emergency Management, 2022, Heat Emergency Plan: Local Law 85 of 2020
   New York City Emergency Management @nycemergencymanagement. n.d.a, Instagram
   New York City Emergency Management @nycemergencymgt. n.d.b, Twitter
   New York City Mayor's Office of Recovery and Resiliency, 2018, Cool Neighborhoods NYC: A Comprehensive Approach to Keep Communities Safe in Extreme Heat
   New York City Panel on Climate Change, 2013, Climate Risk Information 2013: Observations, Climate Change Projections, and Maps
   New York Codes Rules and Regulations, 2023, Subchapter D-Adult-Care Facilities, VB-1
   New York Codes Rules and Regulations, 2004, Volume C (Title 10) Chapter V-Medical Facilities
   New York New York Weather Forecast Office, 2021, 90 Degree Day Information at Central Park (1869 to Present)
   New York New York Weather Forecast Office, National Weather Service New York, NY Excessive Heat Page
   Nicholls L., 2017, Heatwaves, Homes & Health: Why Household Vulnerability to Extreme Heat Is an Electricity Policy Issue
   NOLA Public Schools, 2020, New Orleans Public Schools Facility Procedures Handbook
   NOLA Ready @NOLAReady, Instagram
   NOLA Ready @NOLAReady. n.d.b, Twitter
   Office of Climate & Environmental Justice, NYC CoolRoofs
   Office of Homeland Security and Emergency Preparedness, 2021, Hazard Mitigation Plan
   Orleans Parish School Board, 2008, School Facilities Master Plan for Orleans Parish
   PRCNOLA, 2016, City Council Districts feature layer
   Rules of the City of New York, Health Code Article 49: Schools
   Spangler KR, 2022, SCI DATA, V9, DOI 10.1038/s41597-022-01405-3
   Talami R, 2020, ENERG BUILDINGS, V223, DOI 10.1016/j.enbuild.2020.110177
   The Trust for Public Land, 2023, Heat Severity-USA 2022 raster
   United States Census Bureau, 2021, Community Survey
   Vaidyanathan A, 2020, MMWR-MORBID MORTAL W, V69, P729, DOI 10.15585/mmwr.mm6924a1
   Vant-Hull B, 2018, B AM METEOROL SOC, V99, P2491, DOI 10.1175/BAMS-D-16-0280.1
   Yeung L., 2022, Overheated, Underserved: Expanding Cooling Center Access
NR 67
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Z9 0
U1 10
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 2024 JUN 20
PY 2024
DI 10.1080/13549839.2024.2368580
EA JUN 2024
PG 21
WC Green & Sustainable Science & Technology; Environmental Studies;
   Geography; Regional & Urban Planning; Urban Studies
WE Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology;
   Geography; Public Administration; Urban Studies
GA WH8O0
UT WOS:001254071400001
DA 2025-01-10
ER

PT J
AU Falcescu, V
   Cheval, S
   Micu, DM
   Dumitrescu, A
   Roznovietchi, I
   Dumitrascu, M
   Damian, N
AF Falcescu, Vladut
   Cheval, Sorin
   Micu, Dana Magdalena
   Dumitrescu, Alexandru
   Roznovietchi, Irena
   Dumitrascu, Monica
   Damian, Nicoleta
TI Climate services in Romania - an analysis of stakeholders' perceptions
   and needs
SO CLIMATE SERVICES
LA English
DT Article
DE Climate Services; Climate adaptation; Romania; Climate risk; Survey;
   Decision -making
ID LEARN
AB In recent years, the climate services market has increased significantly, especially in the Western European countries where they have become widely utilised in both the public and private sectors. In Romania, there is no specialised platform for those kinds of services, and the sector is in its beginnings. The current study is based on sociological research conducted as part of a national project aimed at increasing adaptive capacity to climate change. The purpose of the questionnaire that served as the study's base was to collect information about the extent to which climate services are used by organisations, their perception of the benefits of using the services, the technical characteristics of the services, and the future needs of stakeholders. Such an analysis is necessary to comprehend the existing market situation in Romania and to be able to establish the circumstances essential for an effective improvement of climate services and products based on the co-development concept. The main outcomes of the survey conducted at the national level (324 respondents) confirm the early stage of the national climate service market as (i) only a small share (34 %) of respondents are users of climate products and services (mostly from agriculture, forestry, water resources management, biodiversity, energy sectors) and (ii) climate data and products are insufficiently tailored at sectoral level. Most representative identified stakeholder needs refer to: temporal (i.e., monthly, seasonal) and spatial resolution (i.e., local, regional) and types of tailored climate products (i.e., monthly/seasonal weather forecasts, spatio-temporal maps and analysis tool). The study identified premises further development of the climate service market in Romania (i.e., widespread interest in using climate products and services among the non-users, perceived societal benefits of climate products and services).
C1 [Falcescu, Vladut; Cheval, Sorin] Babes Bolyai Univ, Doctoral Sch Geog, 5-7 Clinicilor Str, Cluj Napoca 400006, Romania.
   [Falcescu, Vladut; Cheval, Sorin; Micu, Dana Magdalena; Dumitrescu, Alexandru] Natl Meteorol Adm, 97 Sos Bucuresti Ploiesti, Bucharest 013686, Romania.
   [Roznovietchi, Irena; Dumitrascu, Monica; Damian, Nicoleta] Romanian Acad, Inst Geog, 12 Dimitrie Racovita St, Bucharest 023993, Romania.
C3 Babes Bolyai University from Cluj; Romanian Academy; Institute of
   Geography of Romanian Academy
RP Falcescu, V (corresponding author), Babes Bolyai Univ, Doctoral Sch Geog, 5-7 Clinicilor Str, Cluj Napoca 400006, Romania.
EM vladut.falcescu@ubbcluj.ro
RI Monica, Dumitrascu/U-9782-2017; Damian, Nicoleta/HLH-0697-2023; Cheval,
   Sorin/B-4506-2011; Micu, Dana Magdalena/O-8243-2014
OI Micu, Dana Magdalena/0000-0003-2429-6697; Dumitrascu,
   Monica/0000-0003-2806-2329
FU Romanian Ministry of Environment, Water and Forests [610/127579]
FX This work was conducted in the framework of the national project
   Strengthening Institutional Capacity for the Improvement of Climate
   Change Policies and Adaptation to the Impacts of Climate Change
   (RO-ADAPT), funded by the Romanian Ministry of Environment, Water and
   Forests (ID SIPOCA/MYSMIS no. 610/127579). The survey was an integral
   part of the analysis of the climate products and services categories
   needed for the development of national and regional Climate Change
   Adaptation Strategies and Action Plans.
CR [Anonymous], 2014, Earth Perspect, DOI DOI 10.1186/2194-6434-1-15
   Araneda-Cabrera RJ, 2021, SCI TOTAL ENVIRON, V790, DOI 10.1016/j.scitotenv.2021.148090
   Bessembinder J, 2019, CLIM SERV, V16, DOI 10.1016/j.cliser.2019.100135
   Guy P, 2016, EARTHS FUTURE, V4, P79, DOI 10.1002/2015EF000338
   Cheval S, 2022, THEOR APPL CLIMATOL, V149, P253, DOI 10.1007/s00704-022-04041-4
   Christel I, 2018, CLIM SERV, V9, P111, DOI 10.1016/j.cliser.2017.06.002
   Cortekar J, 2020, CLIM SERV, V17, DOI 10.1016/j.cliser.2019.100125
   Dincaa A. I., 2014, Human Geographies - Journal of Studies and Research in Human Geographies, V8, P27, DOI 10.5719/hgeo.2014.81.27
   Dumitrescu Alexandru, 2022, Zenodo, DOI 10.5281/ZENODO.4642463
   European Commission. Directorate General for Research and Innovation, 2015, A European research and innovation roadmap for climate services, DOI [10.2777/87968, DOI 10.2777/87968]
   Fraccaroli C, 2021, CLIM SERV, V23, DOI 10.1016/j.cliser.2021.100247
   GCA, 2020, State and Trends in Adaptation Report 2020, V1
   Ghassem R., 2013, Climate Science for Serving Society: Research, Modeling and Prediction Priorities, DOI [10.1007/978-94-007-6692-1, DOI 10.1007/978-94-007-6692-1]
   Guentchev G, 2023, CLIM SERV, V30, DOI 10.1016/j.cliser.2023.100352
   Hansen JW, 2019, FRONT SUSTAIN FOOD S, V3, DOI 10.3389/fsufs.2019.00021
   Hewitt C, 2012, NAT CLIM CHANGE, V2, P831, DOI 10.1038/nclimate1745
   Hoa E, 2018, CLIM SERV, V11, P86, DOI 10.1016/j.cliser.2018.08.001
   Institute of European Democrats, about us
   Jacobs KL, 2020, CLIM SERV, V20, DOI 10.1016/j.cliser.2020.100199
   Kolstad EW, 2019, B AM METEOROL SOC, V100, P1419, DOI 10.1175/BAMS-D-18-0201.1
   Kumar KSK, 2001, GLOBAL ENVIRON CHANG, V11, P147, DOI 10.1016/S0959-3780(01)00004-8
   Lawrence J, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.703902
   Le Cozannet G, 2017, J MAR SCI ENG, V5, DOI 10.3390/jmse5040049
   Lemos MC, 2012, NAT CLIM CHANGE, V2, P789, DOI [10.1038/NCLIMATE1614, 10.1038/nclimate1614]
   Lu JY, 2020, AGR FOREST METEOROL, V292, DOI 10.1016/j.agrformet.2020.108124
   Mendelsohn R, 2001, ENVIRON DEV ECON, V6, P85, DOI 10.1017/S1355770X01000055
   Micu MM, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14148689
   Panenko A, 2021, CLIM SERV, V24, DOI 10.1016/j.cliser.2021.100265
   Ramalho M, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph192416687
   Schneider P, 2020, CLIM RISK MANAG, V30, DOI 10.1016/j.crm.2020.100244
   Soares MB, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.587
   Soares MB, 2018, CLIM SERV, V9, P5, DOI 10.1016/j.cliser.2017.06.001
   Sultan B, 2020, CLIM SERV, V18, DOI 10.1016/j.cliser.2020.100166
   Tart S, 2020, CLIM SERV, V17, DOI 10.1016/j.cliser.2019.100109
   Tian CY, 2021, RENEW SUST ENERG REV, V143, DOI 10.1016/j.rser.2021.110799
   Tudose NC, 2023, CLIM SERV, V30, DOI 10.1016/j.cliser.2023.100340
   Vaughan C, 2018, WEATHER CLIM SOC, V10, P373, DOI 10.1175/WCAS-D-17-0030.1
   Vaughan C, 2014, WIRES CLIM CHANGE, V5, P587, DOI 10.1002/wcc.290
   Vincent K, 2018, CLIM SERV, V12, P48, DOI 10.1016/j.cliser.2018.11.001
   Wiréhn L, 2021, CLIM RISK MANAG, V34, DOI 10.1016/j.crm.2021.100370
   World Meteorological Organization & United Nations, 2011, ABOUT US
NR 41
TC 1
Z9 1
U1 2
U2 2
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2405-8807
J9 CLIM SERV
JI Clim. Serv.
PD APR
PY 2024
VL 34
AR 100476
DI 10.1016/j.cliser.2024.100476
EA APR 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 SE4S9
UT WOS:001232775000001
OA gold
DA 2025-01-10
ER

PT J
AU Michalek, AT
   Villarini, G
   Kim, T
   Quintero, F
   Krajewski, WF
AF Michalek, Alexander T.
   Villarini, Gabriele
   Kim, Taereem
   Quintero, Felipe
   Krajewski, Witold F.
TI Disentangling the Sources of Uncertainties in the Projection of Flood
   Risk Across the Central United States (Iowa)
SO GEOPHYSICAL RESEARCH LETTERS
LA English
DT Article
DE hydrology; uncertainty; projections
ID EARTH SYSTEM MODEL; LARGE ENSEMBLES; CLIMATE; VARIABILITY
AB We explore the projected changes in flood impacts across Iowa (central United States) and the associated uncertainties by forcing a hydrologic model with downscaled global climate model outputs and four Shared Socioeconomic Pathways. Our results point to projected increasing magnitude and variability in flooding across the state, especially for high-emission scenarios. Next, we partition the flood impacts' projections into: (a) the response of the global climate models to anthropogenic forcing, (b) scenario uncertainty due to emissions, and (c) internal climate variability. We find scenario uncertainty plays a small role, while climate model uncertainty and internal climate variability dominate the flood impacts' projections, with the contribution of model uncertainty increasing toward the end of this century. Insights from our work can be utilized by stakeholders to understand the current limitations of flood impact projections and provide suggestions about where modelers should focus efforts to reduce uncertainty.
   This study looks at how climate change is projected to affect floods in Iowa (central United States). The results suggest that flooding is projected to worsen and become more unpredictable, especially with higher greenhouse gas emissions. The main sources of uncertainty in these projections are the differences in climate models' response to forcings and natural climate variability. Understanding these uncertainties can help improve future climate change assessments for flood risk stakeholders such as agencies working toward climate adaptation and water management and improve related risk assessments and planning analysis.
   Climate models producing larger increases in flood peak magnitude typically produce larger changes in varianceClimate model uncertainty is dominant in the early 21st century, while internal climate variability dominates the later part of the 21st centuryUncertainty in flood peaks directly translates to flood risk across Iowa
C1 [Michalek, Alexander T.; Villarini, Gabriele; Kim, Taereem] Princeton Univ, Dept Civil & Environm Engn, Princeton, NJ 08540 USA.
   [Villarini, Gabriele; Kim, Taereem] Princeton Univ, High Meadows Environm Inst, Princeton, NJ USA.
   [Quintero, Felipe; Krajewski, Witold F.] Univ Iowa, Dept Civil & Environm Engn, IIHR Hydrosci & Engn, Iowa City, IA USA.
C3 Princeton University; Princeton University; University of Iowa
RP Michalek, AT (corresponding author), Princeton Univ, Dept Civil & Environm Engn, Princeton, NJ 08540 USA.
EM atmichalek@princeton.edu
RI Quintero, Felipe/AAC-3280-2019; Villarini, Gabriele/F-8069-2016
OI Krajewski, Witold/0000-0002-3477-9281; Villarini,
   Gabriele/0000-0001-9566-2370; Michalek, Alexander/0000-0002-0123-0428
FU Iowa Department of Transportation; Iowa Flood Center, IIHR-Hydroscience
   Engineering; U.S. Army Corps of Engineers' Institute for Water
   Resources;  [20-SPR2-002]
FX This work was supported in part by the Iowa Department of Transportation
   (Project 20-SPR2-002). The opinions, findings, and conclusions expressed
   in this publication are those of the author and not necessarily those of
   the Iowa Department of Transportation or the United States Department of
   Transportation, Federal Highway Administration. Support by the Iowa
   Flood Center, IIHR-Hydroscience & Engineering, and the U.S. Army Corps
   of Engineers' Institute for Water Resources is gratefully acknowledged.
CR Benjamini Y, 2001, ANN STAT, V29, P1165
   Bi DH, 2020, J SO HEMISPH EARTH, V70, P225, DOI 10.1071/ES19040
   Blanusa ML, 2023, CLIM DYNAM, V61, P1931, DOI 10.1007/s00382-023-06664-3
   Cannon AJ, 2015, J CLIMATE, V28, P6938, DOI 10.1175/JCLI-D-14-00754.1
   Cherchi A, 2019, J ADV MODEL EARTH SY, V11, P185, DOI 10.1029/2018MS001369
   Daly C, 2002, CLIM RES, V22, P99, DOI 10.3354/cr022099
   Deng X, 2022, EARTHS FUTURE, V10, DOI 10.1029/2021EF002645
   Deser C, 2020, NAT CLIM CHANGE, V10, P277, DOI 10.1038/s41558-020-0731-2
   Döscher R, 2022, GEOSCI MODEL DEV, V15, P2973, DOI 10.5194/gmd-15-2973-2022
   Dunne JP, 2020, J ADV MODEL EARTH SY, V12, DOI 10.1029/2019MS002015
   Eyring V, 2016, GEOSCI MODEL DEV, V9, P1937, DOI 10.5194/gmd-9-1937-2016
   Fatichi S, 2016, EARTHS FUTURE, V4, P240, DOI 10.1002/2015EF000336
   Giuntoli I, 2018, CLIMATIC CHANGE, V150, P149, DOI 10.1007/s10584-018-2280-5
   Gutjahr O, 2013, THEOR APPL CLIMATOL, V114, P511, DOI 10.1007/s00704-013-0834-z
   Hawkins E, 2011, CLIM DYNAM, V37, P407, DOI 10.1007/s00382-010-0810-6
   Hawkins E, 2009, B AM METEOROL SOC, V90, P1095, DOI 10.1175/2009BAMS2607.1
   IFFP, 2023, Iowa flood frequency and projections tool
   Kendall M. G., 1948, Rank correlation methods.
   Krajewski WF, 2017, B AM METEOROL SOC, V98, P539, DOI 10.1175/BAMS-D-15-00243.1
   Krishnan R, 2019, Current Trends in the Representation of Physical Processes in Weather and Climate Models, P183
   Leander R, 2007, J HYDROL, V332, P487, DOI 10.1016/j.jhydrol.2006.08.006
   Lee J, 2020, ASIA-PAC J ATMOS SCI, V56, P381, DOI 10.1007/s13143-019-00144-7
   Lehner F, 2020, EARTH SYST DYNAM, V11, P491, DOI 10.5194/esd-11-491-2020
   Mallakpour I, 2015, NAT CLIM CHANGE, V5, P250, DOI [10.1038/nclimate2516, 10.1038/NCLIMATE2516]
   Mantilla Ricardo., 2022, Extreme weather forecasting, V1st
   MASSEY FJ, 1951, J AM STAT ASSOC, V46, P68, DOI 10.2307/2280095
   Masson-Delmotte V, 2021, CLIMATE CHANGE 2021, DOI DOI 10.1017/9781009157896
   Mauritsen T, 2019, J ADV MODEL EARTH SY, V11, P998, DOI 10.1029/2018MS001400
   Merz B, 2021, NAT REV EARTH ENV, V2, P592, DOI 10.1038/s43017-021-00195-3
   Michalek A., 2023, HydrosShare, DOI [10.4211/hs.62102d9b9bc64b5-8efd3cde8192cd18, DOI 10.4211/HS.62102D9B9BC64B5-8EFD3CDE8192CD18]
   Michalek A, 2023, J HYDROL, V625, DOI 10.1016/j.jhydrol.2023.129957
   Michalek AT, 2023, WATER RESOUR RES, V59, DOI 10.1029/2022WR034166
   Paprotny D, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-04253-1
   Piani C, 2010, THEOR APPL CLIMATOL, V99, P187, DOI 10.1007/s00704-009-0134-9
   Prior J.C., 1991, LANDFORMS IOWA
   Pu Y, 2020, ADV ATMOS SCI, V37, P1081, DOI 10.1007/s00376-020-2032-0
   Quintero F, 2022, WATER-SUI, V14, DOI 10.3390/w14172610
   Quintero F, 2022, CLIM DYNAM, V59, P3167, DOI 10.1007/s00382-022-06233-0
   Small S., 2016, Read the Docs
   Smith JA, 2013, J HYDROMETEOROL, V14, P1810, DOI 10.1175/JHM-D-12-0191.1
   Smith RL, 2009, J AM STAT ASSOC, V104, P97, DOI 10.1198/jasa.2009.0007
   Sobel AH, 2023, P NATL ACAD SCI USA, V120, DOI 10.1073/pnas.2209631120
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Swart NC, 2019, GEOSCI MODEL DEV, V12, P4823, DOI 10.5194/gmd-12-4823-2019
   Tanoue M, 2016, SCI REP-UK, V6, DOI 10.1038/srep36021
   Tate E, 2016, NAT HAZARDS, V80, P2055, DOI 10.1007/s11069-015-2060-8
   Tatebe H, 2019, GEOSCI MODEL DEV, V12, P2727, DOI 10.5194/gmd-12-2727-2019
   Ventura V, 2004, J CLIMATE, V17, P4343, DOI 10.1175/3199.1
   Villarini G, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/abc5e5
   Villarini G, 2012, NAT CLIM CHANGE, V2, P604, DOI 10.1038/NCLIMATE1530
   Volodin EM, 2017, CLIM DYNAM, V49, P3715, DOI 10.1007/s00382-017-3539-7
   Wang YC, 2021, J ADV MODEL EARTH SY, V13, DOI 10.1029/2020MS002353
   Wood RR, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/ac10dd
   WRCP, 2023, WCRP coupled model intercomparison project (phase 6)
   Yip S, 2011, J CLIMATE, V24, P4634, DOI 10.1175/2011JCLI4085.1
   Yukimoto S, 2019, J METEOROL SOC JPN, V97, P931, DOI 10.2151/jmsj.2019-051
   Ziehn T, 2020, J SO HEMISPH EARTH, V70, P193, DOI 10.1071/ES19035
NR 57
TC 3
Z9 3
U1 3
U2 6
PU AMER GEOPHYSICAL UNION
PI WASHINGTON
PA 2000 FLORIDA AVE NW, WASHINGTON, DC 20009 USA
SN 0094-8276
EI 1944-8007
J9 GEOPHYS RES LETT
JI Geophys. Res. Lett.
PD NOV 28
PY 2023
VL 50
IS 22
AR e2023GL105852
DI 10.1029/2023GL105852
PG 12
WC Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology
GA Y6GF7
UT WOS:001106217200001
OA gold
DA 2025-01-10
ER

PT J
AU Vahedifard, F
   Azhar, M
   Brown, DC
AF Vahedifard, Farshid
   Azhar, Mohammed
   Brown, Dustin C.
TI Overrepresentation of Historically Underserved and Socially Vulnerable
   Communities Behind Levees in the United States
SO EARTHS FUTURE
LA English
DT Article
DE infrastructure equity; levees; flood risk; historically underserved and
   socially vulnerable communities (HUSVCs)
ID HAZARDS
AB Infrastructure equity is an immediate concern with levees, constituting the backbone of the U.S. protection against flooding. Flooding patterns are exacerbated by anthropogenic climate change in several regions, posing a significant risk to the economy, safety, and well-being of the nation. The evolving risk of flooding is shown to disproportionately affect historically underserved and socially vulnerable communities (HUSVCs). Here we compare the sociodemographic and socioeconomic composition of leveed and non-leveed U.S. communities and show a substantial overrepresentation of HUSVCs in leveed areas at the state, regional, and national levels. Further, we analyze the proportion of communities designated as "disadvantaged" in leveed versus non-leveed areas, revealing a substantially larger population of disadvantaged communities residing behind levees. Our analyses show that nationally, Hispanic are the most overrepresented population in leveed areas yielding a disparity percentage of 39.9%, followed by Native American (18.7%), Asian (17.7%), and Black (16.1%) communities. Communities characterized by low education, poverty, and disability exhibit a disproportionately higher presentation of 27.8%, 20.4%, and 5.4% in leveed areas across the U.S. In 43 states, disadvantaged communities are overrepresented behind levees, with a national disparity percentage of 40.6%. At the regional level, the highest disparity was observed in the Northeast (57.3%), followed by the West (51.3%), Southeast (38%), Midwest (29.2%), and Southwest (25%). The findings can enable decision- and policy-makers to identify hotspots within HUSVCs that need to be prioritized for enhancing the integrity and climate adaptation of their levee systems.
C1 [Vahedifard, Farshid; Azhar, Mohammed] Tufts Univ, Dept Civil & Environm Engn, Medford, MA 02155 USA.
   [Vahedifard, Farshid] United Nations Univ, Inst Water Environm & Hlth UNU INWEH, Hamilton, ON, Canada.
   [Brown, Dustin C.] Mississippi State Univ, Dept Sociol, Mississippi State, MS USA.
   [Brown, Dustin C.] Mississippi State Univ, Social Sci Res Ctr, Mississippi State, MS USA.
C3 Tufts University; Mississippi State University; Mississippi State
   University
RP Vahedifard, F (corresponding author), Tufts Univ, Dept Civil & Environm Engn, Medford, MA 02155 USA.; Vahedifard, F (corresponding author), United Nations Univ, Inst Water Environm & Hlth UNU INWEH, Hamilton, ON, Canada.
EM farshid.vahedifard@tufts.edu
OI Vahedifard, Farshid/0000-0001-8883-4533
FU National Oceanic and Atmospheric Administration (NOAA) [NA22NWS4680007]
FX The work is supported by the National Oceanic and Atmospheric
   Administration (NOAA) (Grant NA22NWS4680007).
CR [Anonymous], 2005, Methods for measuring cancer disparities: using data relevant to Healthy People 2010 cancer-related objectives
   ASCE, 2021, Report card on America's infrastructure: Levees
   Buchanan MK, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa6cb3
   Burton C., 2008, Natural Hazards Review, V9, P136, DOI 10.1061/(ASCE)1527-6988(2008)9:3(136)
   CDC. Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry/Geospatial Research Analysis and Services Program, CDC/ATSDR Social Vulnerability Index
   CEQ, 2022, Climate and economic justice screening tool (CEJST), ver. 1.0, released November 22
   CFR, 2023, 44 CFR.  65.10. Title 44
   Chakraborty J, 2014, NAT HAZARDS REV, V15, DOI 10.1061/(ASCE)NH.1527-6996.0000140
   Cutter SL, 2003, SOC SCI QUART, V84, P242, DOI 10.1111/1540-6237.8402002
   Dicker R.C., 2006, Principles of epidemiology in public health practice; an introduction to applied epidemiology and biostatistics
   Emrich CT, 2011, WEATHER CLIM SOC, V3, P193, DOI 10.1175/2011WCAS1092.1
   Federal Emergency Management Agency, 2020, Guidance for flood risk analysis and mapping
   FEMA, 2021, Equity action plan
   Finch C, 2010, POPUL ENVIRON, V31, P179, DOI 10.1007/s11111-009-0099-8
   Howell J, 2019, SOC PROBL, V66, P448, DOI 10.1093/socpro/spy016
   Infrastructure Investment and Jobs Act, 2022, President Biden's bipartisan infrastructure law
   Justice40 Initiative, 2022, Office of environmental management
   Knox RL, 2022, WATER RESOUR RES, V58, DOI 10.1029/2021WR031308
   Meng QM, 2023, SOC SCI MED, V318, DOI 10.1016/j.socscimed.2022.115618
   Moftakhari HR, 2017, P NATL ACAD SCI USA, V114, P9785, DOI 10.1073/pnas.1620325114
   Mohai Paul, 2009, Am J Public Health, V99 Suppl 3, pS649, DOI 10.2105/AJPH.2007.131383
   Morello-Frosch R, 2002, ENVIRON HEALTH PERSP, V110, P149, DOI 10.1289/ehp.02110s2149
   NLD, 2023, National levee database (NLD)
   Poussard C, 2021, FRONT WATER, V3, DOI 10.3389/frwa.2021.633046
   Qiang Y, 2019, J ENVIRON MANAGE, V232, P295, DOI 10.1016/j.jenvman.2018.11.039
   Rust S., 2023, Los Angeles Times
   Sanders BF, 2023, NAT SUSTAIN, V6, P47, DOI 10.1038/s41893-022-00977-7
   Tate E, 2021, NAT HAZARDS, V106, P435, DOI 10.1007/s11069-020-04470-2
   Tye MR., 2021, Impacts of future weather and climate extremes on United States infrastructure: Assessing and prioritizing adaptation actions, DOI [10.1061/9780784415863, DOI 10.1061/9780784415863]
   Vahedifard F., 2022, GeoStrata Magazine Archive, V26, P50
   Vahedifard F, 2020, J GEOTECH GEOENVIRON, V146, DOI 10.1061/(ASCE)GT.1943-5606.0002399
   Vitousek S, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-01362-7
   Wing OEJ, 2022, NAT CLIM CHANGE, V12, P156, DOI 10.1038/s41558-021-01265-6
NR 33
TC 5
Z9 5
U1 4
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 SEP
PY 2023
VL 11
IS 9
AR e2023EF003619
DI 10.1029/2023EF003619
PG 15
WC Environmental Sciences; Geosciences, Multidisciplinary; Meteorology &
   Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Geology; Meteorology & Atmospheric
   Sciences
GA R0TX0
UT WOS:001061564000001
OA gold
DA 2025-01-10
ER

PT J
AU Chen, WJ
   Jan, JF
   Chung, CH
   Liaw, SC
AF Chen, Wan-Jiun
   Jan, Jihn-Fa
   Chung, Chih-Hsin
   Liaw, Shyue-Cherng
TI Do Eco-Based Adaptation Measures Enhance Ecosystem Adaptation Services?
   Economic Evidence from a Study of Hillside Forests in a Fragile
   Watershed in Northeastern Taiwan
SO SUSTAINABILITY
LA English
DT Article
DE watershed protection; ecosystem assessment; ecosystem-based adaptation;
   ecosystem services; contingent valuation method
ID CLIMATE ADAPTATION; BIODIVERSITY; STRATEGIES; COEVOLUTION; MANAGEMENT;
   VALUES
AB As the risks of climate change keep increasing, countries have emphasized the ecosystem adaptation policy, and the United Nation Environmental Program (UNEP) aids countries to adapt to a warming world with eco-based adaptation (EbA) measures for good ecosystem governance for boosting ecosystem adaptation services (EAS). With the purpose of helping to indicate the magnitude of the benefits of EAS from local EbA measures, this study assesses the economic value of the EAS of hillside forests regarding the residents in a climate vulnerable watershed, the Lanyang River watershed, by applying a single-bounded contingent evaluation method. The demographic variables and motivation variables indexed by perceived impacts are influencing factors in the residents' willingness-to-pay. These variables are of significance in EbA policy application. The average economic value for each responding resident was estimated to be NT$ 793.65 on the basis of a survey of the residents' willingness to pay for EAS and the single-boundary contingent valuation method. The results verified that the residents depend on the protection of natural hillside ecosystems. Considering the complex interactions between ecosystems and humans, the EbA is demonstrated to be a crucial method for mitigating the consequences of climate change. Protecting hillside ecosystems in the Lanyang River watershed through soil and water management presents critical policy implications. Now that climate change has become an emergency, this case study shows the success of Taiwan's long manipulated EbA for EAS, with evidence of residents benefiting. This Taiwan case study has policy implications for the world and UNEP's global EbA program to maintain EAS.
C1 [Chen, Wan-Jiun] Chinese Culture Univ, Dept Econ, 55 HawKang Rd, Taipei 111, Taiwan.
   [Jan, Jihn-Fa] Natl Chengchi Univ, Dept Land Econ, 64,Sect 2,Zhinan Rd, Taipei 116, Taiwan.
   [Chung, Chih-Hsin] Natl Ilan Univ, Dept Forestry & Nat Resources, 1,Sect 1,Shennong Rd, Yilan 260, Taiwan.
   [Liaw, Shyue-Cherng] Natl Taiwan Normal Univ, Dept Geog, 162,Sect 1,Heping E Rd, Taipei 106, Taiwan.
C3 Chinese Culture University; National Chengchi University; National Ilan
   University; National Taiwan Normal University
RP Liaw, SC (corresponding author), Natl Taiwan Normal Univ, Dept Geog, 162,Sect 1,Heping E Rd, Taipei 106, Taiwan.
EM cwj@ulive.pccu.edu.tw; jfjan@nccu.edu.tw; chchung@ems.niu.edu.tw;
   liaw@ntnu.edu.tw
RI Liaw, Shyue-Cherng/O-4370-2019
OI JAN, JIHN-FA/0000-0002-8386-4896; Chen, Wan-Jiun/0000-0002-9088-3884;
   Liaw, Shyue-Cherng/0000-0001-8337-5390
CR Abson DJ, 2011, CONSERV BIOL, V25, P250, DOI 10.1111/j.1523-1739.2010.01623.x
   Al-Amin A, 2020, INT J DISAST RISK RE, V50, DOI 10.1016/j.ijdrr.2020.101708
   [Anonymous], 2023, TAIW FOR BUR PROGR C
   Banna H, 2016, CAH AGRIC, V25, DOI 10.1051/cagri/2016014
   Brink E, 2016, GLOBAL ENVIRON CHANG, V36, P111, DOI 10.1016/j.gloenvcha.2015.11.003
   CAMERON TA, 1991, LAND ECON, V67, P413, DOI 10.2307/3146548
   Chausson A, 2020, GLOBAL CHANGE BIOL, V26, P6134, DOI 10.1111/gcb.15310
   Chen WJ, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph19106193
   Colls A., 2009, Ecosystem-based adaptation: a natural response to climate change
   Crossman ND, 2013, ECOSYST SERV, V4, P4, DOI 10.1016/j.ecoser.2013.02.001
   Daly HE, 2005, SCI AM, V293, P100, DOI 10.1038/scientificamerican0905-100
   Darwin R., 1995, World agriculture and climate change: Economic adaptations
   Davoudi S, 2013, PLAN PRACT RES, V28, P307, DOI 10.1080/02697459.2013.787695
   Donatti CI, 2020, CLIMATIC CHANGE, V158, P413, DOI 10.1007/s10584-019-02565-9
   Filatova T, 2014, ENVIRON SCI POLICY, V37, P227, DOI 10.1016/j.envsci.2013.09.005
   Fritz M, 2017, THEOR PRACT URB SUST, P1, DOI 10.1007/978-3-319-56091-5_1
   Geneletti D, 2016, LAND USE POLICY, V50, P38, DOI 10.1016/j.landusepol.2015.09.003
   Global Ecovillage Network, 2022, CAT COMM REG WORLD
   Gowdy J., 2013, NATURAL RESOURCE MAN, V5
   Gual MA, 2010, ECOL ECON, V69, P707, DOI 10.1016/j.ecolecon.2008.07.020
   Harris JA, 2006, RESTOR ECOL, V14, P170, DOI 10.1111/j.1526-100X.2006.00136.x
   Hassan A, 2017, ADV BUS STRATEGY COM, P56, DOI 10.4018/978-1-5225-2107-5.ch004
   Hilty JA., 2019, CORRIDOR ECOLOGY LIN
   Iacob O, 2014, HYDROL RES, V45, P774, DOI 10.2166/nh.2014.184
   Iglesias A., 2006, Climate Variability, Modelling Tools and Agricultural Decision Making, P20
   Iglesias A, 2012, CLIMATIC CHANGE, V112, P143, DOI 10.1007/s10584-011-0344-x
   Iglesias A, 2011, REG ENVIRON CHANGE, V11, pS159, DOI 10.1007/s10113-010-0187-4
   Jobstvogt N, 2014, ECOSYST SERV, V10, P97, DOI 10.1016/j.ecoser.2014.09.006
   Kabisch N, 2016, ECOL SOC, V21, DOI 10.5751/ES-08373-210239
   Kalfas DG, 2020, INT J SUST DEV WORLD, V27, P310, DOI 10.1080/13504509.2020.1714786
   Kasper DV, 2008, HUM ECOL REV, V15, P12
   Klein RJT, 2010, NATO SCI PEACE SECUR, P157, DOI 10.1007/978-94-007-1770-1_9
   Larsen L, 2004, J AM PLANN ASSOC, V70, P374
   Lavorel S, 2015, GLOBAL CHANGE BIOL, V21, P12, DOI 10.1111/gcb.12689
   Li Chaokui, 2023, Int J Environ Res Public Health, V20, DOI 10.3390/ijerph20054517
   Li L, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph191911958
   Li Yuliang, 2023, Int J Environ Res Public Health, V20, DOI 10.3390/ijerph20053959
   Lin HI, 2019, ATMOSPHERE-BASEL, V10, DOI 10.3390/atmos10120753
   Maghsood FF, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11185053
   Masud MM, 2015, ENVIRON MONIT ASSESS, V187, DOI 10.1007/s10661-014-4254-z
   Müller A, 2019, FORESTS, V10, DOI 10.3390/f10020132
   Munang R, 2014, ENVIRONMENT, V56, P18, DOI 10.1080/00139157.2014.861676
   Munang R, 2013, CURR OPIN ENV SUST, V5, P67, DOI 10.1016/j.cosust.2012.12.001
   Muthee KW, 2018, INT J CLIM CHANG STR, V10, P533, DOI 10.1108/IJCCSM-06-2017-0140
   Nainggolan D, 2014, ROUT INT HANDB, P244
   Nalau J, 2018, ENVIRON SCI POLICY, V89, P357, DOI 10.1016/j.envsci.2018.08.014
   Navrud S, 2018, ENVIRON RESOUR ECON, V70, P249, DOI 10.1007/s10640-017-0119-6
   NORDHAUS WD, 1991, ECON J, V101, P920, DOI 10.2307/2233864
   O'Brien K, 2009, ECOL SOC, V14
   Ojea E., 2014, ROUTLEDGE HDB EC CLI
   Ojea E, 2015, CURR OPIN ENV SUST, V14, P41, DOI 10.1016/j.cosust.2015.03.006
   Olesen JE, 2002, EUR J AGRON, V16, P239, DOI 10.1016/S1161-0301(02)00004-7
   Pasquini L, 2015, ENVIRON DEV SUSTAIN, V17, P1121, DOI 10.1007/s10668-014-9594-x
   Perez A.A., 2010, Building resilience to climate change: Ecosystem-based adaptation and lessons from the field
   Perrings C, 2011, SCIENCE, V331, P1139, DOI 10.1126/science.1202400
   Prober SM, 2012, CLIMATIC CHANGE, V110, P227, DOI 10.1007/s10584-011-0092-y
   Reid H., 2019, Is ecosystem-based adaptation effective? Perceptions and Lessons Learned from 13 Project Sites
   Rizvi A R., 2015, Ecosystems based adaptation: Knowledge gaps in making an economic case for investing in nature based solutions for climate change, DOI DOI 10.3390/su8020144
   Roberts D, 2012, ENVIRON URBAN, V24, P167, DOI 10.1177/0956247811431412
   Sangalli P, 2021, URBAN SERVICES ECOSY, P317, DOI [10.1007/978-3-030-75929-2_17, DOI 10.1007/978-3-030-75929-2_17]
   Scarano FR, 2017, PERSPECT ECOL CONSER, V15, P65, DOI 10.1016/j.pecon.2017.05.003
   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
   Smit B., 2002, Mitigation and Adaptation Strategies for Global Change, V7, P85, DOI 10.1023/A:1015862228270
   Stein BA, 2013, FRONT ECOL ENVIRON, V11, P502, DOI 10.1890/120277
   SWCB Soil and Water Conservation Bureau, 2023, The 60th Anniversary Storybook of the Bureau of Soil and Water ConservationAbout Those Things on the Hillside
   Tietenberg T., 2018, Environmental and natural resource economics, V11th
   Ulterino M., 2004, ENV DES GUIDE, P1
   UNFCCC, 2011, DURB CLIM CHANG C NO
   UNFCCC, 2019, IPCC SPECIAL REPORT
   van den Bergh JCJM, 2003, J EVOL ECON, V13, P289, DOI 10.1007/s00191-003-0158-8
   Vignola R, 2015, AGR ECOSYST ENVIRON, V211, P126, DOI 10.1016/j.agee.2015.05.013
   Vignola R, 2009, MITIG ADAPT STRAT GL, V14, P691, DOI 10.1007/s11027-009-9193-6
   Wagner Felix., 2012, RCC Perspectives, V8, P81, DOI DOI 10.5282/RCC/5598
   Wamsler C, 2020, J CLEAN PROD, V247, DOI 10.1016/j.jclepro.2019.119154
   Wamsler C, 2016, CLIMATIC CHANGE, V137, P71, DOI 10.1007/s10584-016-1660-y
   Wamsler C, 2016, ECOL SOC, V21, DOI 10.5751/ES-08266-210131
   Wamsler C, 2015, ECOL SOC, V20, DOI 10.5751/ES-07489-200230
   Wamsler C, 2014, GLOBAL ENVIRON CHANG, V29, P189, DOI 10.1016/j.gloenvcha.2014.09.008
   Wang JW, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph192013295
   Wang X, 2010, ECOL ECON, V69, P2549, DOI 10.1016/j.ecolecon.2010.07.031
   Woroniecki S, 2019, ECOL SOC, V24, DOI 10.5751/ES-10854-240204
   Xu XB, 2020, GLOB ECOL CONSERV, V22, DOI 10.1016/j.gecco.2020.e01027
   Yuan K, 2023, INT J ENV RES PUB HE, V20, DOI 10.3390/ijerph20021475
   [张翼飞 ZHANG YiFei], 2007, [地球科学进展, Advance in Earth Sciences], V22, P1141
   Zhao Qinglei, 2023, Int J Environ Res Public Health, V20, DOI 10.3390/ijerph20065194
   Zhong Qikang, 2023, Int J Environ Res Public Health, V20, DOI 10.3390/ijerph20065095
   Zhuge Jing, 2023, Int J Environ Res Public Health, V20, DOI 10.3390/ijerph20065069
   Zölch T, 2018, J CLEAN PROD, V170, P966, DOI 10.1016/j.jclepro.2017.09.146
NR 89
TC 3
Z9 3
U1 3
U2 11
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD JUN
PY 2023
VL 15
IS 12
AR 9685
DI 10.3390/su15129685
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 K3YW3
UT WOS:001015837500001
OA gold
DA 2025-01-10
ER

PT J
AU Chen, BH
   Bai, YL
   Wang, JY
   Ke, QZ
   Zhou, ZX
   Zhou, T
   Pan, Y
   Wu, RX
   Wu, XF
   Zheng, WQ
   Xu, P
AF Chen, Baohua
   Bai, Yulin
   Wang, Jiaying
   Ke, Qiaozhen
   Zhou, Zhixiong
   Zhou, Tao
   Pan, Ying
   Wu, Renxie
   Wu, Xiongfei
   Zheng, Weiqiang
   Xu, Peng
TI Population structure and genome-wide evolutionary signatures reveal
   putative climate-driven habitat change and local adaptation in the large
   yellow croaker
SO MARINE LIFE SCIENCE & TECHNOLOGY
LA English
DT Article
DE Climate adaptation; Habitat change; Large yellow croaker;
   Phylogeographic structure
ID MITOCHONDRIAL INTROGRESSION; GENETIC PATTERNS; R PACKAGE; TEMPERATURE;
   MARINE; SELECTION; PARASITE; FISHES; CROCEA; TOOL
AB The large yellow croaker (Larimichthyscrocea) is one of the most economically valuable marine fish in China and is a notable species in ecological studies owing to a serious collapse of wild germplasm in the past few decades. The stock division and species distribution, which have important implications for ecological protection, germplasm recovery, and fishery resource management, have been debated since the 1960s. However, it is still uncertain even how many stocks exist in this species. To address this, we evaluated the fine-scale genetic structure of large yellow croaker populations distributed along the eastern and southern Chinese coastline based on 7.64 million SNP markers. Compared with the widely accepted stock boundaries proposed in the 1960s, our results revealed that a climate-driven habitat change probably occurred between the Naozhou (Nanhai) Stock and the Ming-Yuedong (Mindong) Stock. The boundary between these two stocks might have shifted northwards from the Pearl River Estuary to the northern area of the Taiwan Strait, accompanied by highly asymmetric introgression. In addition, we found divergent landscapes of natural selection between the stocks inhabiting northern and southern areas. The northern population exhibited highly agminated signatures of strong natural selection in genes related to developmental processes, whereas moderate and interspersed selective signatures were detected in many immune-related genes in the southern populations. These findings establish the stock status and genome-wide evolutionary landscapes of large yellow croaker, providing a basis for conservation, fisheries management and further evolutionary biology studies.
C1 [Chen, Baohua; Bai, Yulin; Wang, Jiaying; Ke, Qiaozhen; Zhou, Zhixiong; Zhou, Tao; Pan, Ying; Xu, Peng] Xiamen Univ, Coll Ocean & Earth Sci, Fujian Key Lab Genet & Breeding Marine Organisms, Xiamen 361102, Peoples R China.
   [Chen, Baohua; Ke, Qiaozhen; Zheng, Weiqiang; Xu, Peng] Ningde Fufa Fisheries Co Ltd, Natl Key Lab Mariculture Breeding, Ningde 352000, Peoples R China.
   [Chen, Baohua; Xu, Peng] Xiamen Univ, State Key Lab Marine Environm Sci, Xiamen 361102, Peoples R China.
   [Pan, Ying] Fujian Acad Agr Sci, Inst Biotechnol, Fuzhou 350000, Peoples R China.
   [Wu, Renxie] Guangdong Ocean Univ, Coll Fisheries, Zhanjiang 524088, Peoples R China.
   [Wu, Xiongfei] Ningbo Acad Oceanol & Fishery, Ningbo 315012, Peoples R China.
C3 Xiamen University; Xiamen University; Fujian Academy of Agricultural
   Sciences; Guangdong Ocean University
RP Xu, P (corresponding author), Xiamen Univ, Coll Ocean & Earth Sci, Fujian Key Lab Genet & Breeding Marine Organisms, Xiamen 361102, Peoples R China.; Xu, P (corresponding author), Ningde Fufa Fisheries Co Ltd, Natl Key Lab Mariculture Breeding, Ningde 352000, Peoples R China.; Xu, P (corresponding author), Xiamen Univ, State Key Lab Marine Environm Sci, Xiamen 361102, Peoples R China.
EM xupeng77@xmu.edu.cn
RI Chen, Baohua/AAG-5930-2021; Wu, Ren-xie/AAM-5214-2020
OI Bai, Yulin/0009-0008-8517-9180
FU National Key R&D Program of China [2022YFD2401002]; National Science
   Fund for Distinguished Young Scholars [32225049]; National Natural
   Science Foundation of China [U21A20264]; Special Foundation for Major
   Research Program of Fujian Province [2020NZ08003]; Major Special Funding
   for "Science and Technology Innovation 2025" in Ningbo [2021Z002]; Local
   Science and Technology Development Project Guide by The Central
   Government [2019L3032]; China Agriculture Research System [CARS-47];
   Alliance of International Science Organizations [ANSO-CR-PP-2021-03]
FX We acknowledge financial support from the National Key R&D Program of
   China (no. 2022YFD2401002), the National Science Fund for Distinguished
   Young Scholars (no. 32225049), the National Natural Science Foundation
   of China (no. U21A20264), the Special Foundation for Major Research
   Program of Fujian Province (no. 2020NZ08003), the Major Special Funding
   for "Science and Technology Innovation 2025" in Ningbo (no. 2021Z002),
   the Local Science and Technology Development Project Guide by The
   Central Government (no. 2019L3032), the China Agriculture Research
   System (no. CARS-47), and the Alliance of International Science
   Organizations (ANSO-CR-PP-2021-03).
CR Abdullah A, 2017, AQUACULT REP, V7, P57, DOI 10.1016/j.aqrep.2017.06.001
   Addo-Bediako A, 2000, P ROY SOC B-BIOL SCI, V267, P739, DOI 10.1098/rspb.2000.1065
   Avalos A, 2017, NAT COMMUN, V8, DOI 10.1038/s41467-017-01800-0
   Barnes TC, 2016, MAR FRESHWATER RES, V67, P1103, DOI 10.1071/MF15044
   Beitinger TL, 2000, ENVIRON BIOL FISH, V58, P237, DOI 10.1023/A:1007676325825
   Birstein VJ, 1997, ENVIRON BIOL FISH, V48, P427, DOI 10.1023/A:1007382724251
   BIRSTEIN VJ, 1993, CONSERV BIOL, V7, P773, DOI 10.1046/j.1523-1739.1993.740773.x
   Bosse M, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms5392
   Brodersen J, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0024022
   Callahan MW, 2021, MAR ECOL PROG SER, V663, P145, DOI 10.3354/meps13641
   Campana SE, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-73444-y
   Carbonell JA, 2021, J ANIM ECOL, V90, P1666, DOI 10.1111/1365-2656.13482
   Chen BH, 2019, SCI DATA, V6, DOI 10.1038/s41597-019-0194-3
   Chen F., 2011, J ZHEJIANG OCEAN U N, V30, P259
   [陈佳杰 Chen Jiajie], 2012, [中国水产科学, Journal of Fishery Sciences of China], V19, P310
   [谌微 Chen Wei], 2016, [中国水产科学, Journal of Fishery Sciences of China], V23, P1255
   China MOaaRaOTPSRO Center NFTE Fisheries CSO, 2021, CHINA FISHERY STAT Y
   Cingolani P, 2012, FLY, V6, P80, DOI 10.4161/fly.19695
   Cox MP, 2010, BMC BIOINFORMATICS, V11, DOI 10.1186/1471-2105-11-485
   Crispo E, 2005, CONSERV GENET, V6, P665, DOI 10.1007/s10592-005-9026-4
   CROW J F, 1970, P591, DOI 10.1093/bioinformatics/btr330
   De Summa S, 2017, BMC BIOINFORMATICS, V18, DOI 10.1186/s12859-017-1537-8
   Frichot E, 2015, METHODS ECOL EVOL, V6, P925, DOI 10.1111/2041-210X.12382
   Gao Guo-Qiang, 2010, Yichuan, V32, P248, DOI 10.3724/SP.J.1005.2010.00248
   Gautier M, 2017, MOL ECOL RESOUR, V17, P78, DOI 10.1111/1755-0998.12634
   Geraldi NR, 2019, FRONT MAR SCI, V6, DOI 10.3389/fmars.2019.00030
   Gleason FH, 2019, MAR FRESHWATER RES, V70, P1307, DOI 10.1071/MF18207
   Goudet J, 2005, MOL ECOL NOTES, V5, P184, DOI 10.1111/j.1471-8286.2004.00828.x
   Hollenbeck CM, 2019, ECOL EVOL, V9, P3141, DOI 10.1002/ece3.4936
   Hurst TP, 2007, J FISH BIOL, V71, P315, DOI 10.1111/j.1095-8649.2007.01596.x
   Jensen LF, 2008, P ROY SOC B-BIOL SCI, V275, P2859, DOI 10.1098/rspb.2008.0870
   Jeppesen E, 2010, HYDROBIOLOGIA, V646, P73, DOI 10.1007/s10750-010-0171-5
   Jezkova T, 2013, J EVOLUTION BIOL, V26, P1458, DOI 10.1111/jeb.12149
   Jiang S, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-48472-y
   Junge C, 2019, MAR BIOL, V166, DOI 10.1007/s00227-018-3454-4
   Karvonen A, 2013, ECOL EVOL, V3, P1507, DOI 10.1002/ece3.568
   Kavanagh KD, 2010, BMC EVOL BIOL, V10, DOI 10.1186/1471-2148-10-350
   Kawecki TJ, 2004, ECOL LETT, V7, P1225, DOI 10.1111/j.1461-0248.2004.00684.x
   LaFond EC, 1954, SCI MON, V78, P243
   Laugen AT, 2003, J EVOLUTION BIOL, V16, P996, DOI 10.1046/j.1420-9101.2003.00560.x
   Letunic I, 2019, NUCLEIC ACIDS RES, V47, pW256, DOI 10.1093/nar/gkz239
   Levänen R, 2018, ANN ZOOL FENN, V55, P15, DOI 10.5735/086.055.0103
   Li H, 2009, BIOINFORMATICS, V25, P1094, DOI [10.1093/bioinformatics/btp100, 10.1093/bioinformatics/btp324]
   Li M., 2013, J NINGBO U NSEE, V26, P1
   Li Qiuhua, 2023, Aquaculture and Fisheries, V8, P26, DOI 10.1016/j.aaf.2021.04.008
   Lin Neng-feng, 2012, Fujian Nongye Xuebao, V27, P661
   Liu C, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-018-37274-3
   Liu M, 2008, FISH FISH, V9, P219, DOI 10.1111/j.1467-2979.2008.00278.x
   LOENG H, 1989, Journal of Northwest Atlantic Fishery Science, V9, P103
   Luque JL, 2008, J FISH BIOL, V72, P189, DOI 10.1111/j.1095-8649.2007.01695.x
   Lynch M, 2007, J HERED, V98, P633, DOI [10.1093/jhered/esm073, DOI 10.1093/JHERED/ESM073]
   Melo-Ferreira J, 2005, MOL ECOL, V14, P2459, DOI 10.1111/j.1365-294X.2005.02599.x
   Mitchell SE, 2005, EVOLUTION, V59, P70, DOI 10.1111/j.0014-3820.2005.tb00895.x
   Munday PL, 2012, J EXP BIOL, V215, P3865, DOI 10.1242/jeb.074765
   Nagata N, 2007, MOL ECOL, V16, P4822, DOI 10.1111/j.1365-294X.2007.03569.x
   Nei M., 1987, Molecular evolutionary genetics, DOI [10.7312/nei-92038, DOI 10.7312/NEI-92038]
   Nimon KF, 2013, ORGAN RES METHODS, V16, P650, DOI 10.1177/1094428113493929
   O'Dwyer JE, 2021, MAR FRESHWATER RES, V72, P1457, DOI 10.1071/MF20323
   Orleans LA., 1980, FISHERIES, P237
   Perkins TA, 2012, AM NAT, V179, pE37, DOI 10.1086/663682
   Peters KJ, 2017, J EVOLUTION BIOL, V30, P1940, DOI 10.1111/jeb.13167
   Phillipsen IC, 2015, MOL ECOL, V24, P54, DOI 10.1111/mec.13003
   Picq S, 2016, ECOL EVOL, V6, P2109, DOI 10.1002/ece3.2028
   Pinsky ML, 2019, NATURE, V569, P108, DOI 10.1038/s41586-019-1132-4
   Purcell S, 2007, AM J HUM GENET, V81, P559, DOI 10.1086/519795
   Qian BY, 2016, MAR GENOM, V25, P95, DOI 10.1016/j.margen.2015.12.001
   Quinn BK, 2013, J CRUSTACEAN BIOL, V33, P527, DOI 10.1163/1937240X-00002150
   Rodríguez-Zárate CJ, 2018, P ROY SOC B-BIOL SCI, V285, DOI 10.1098/rspb.2018.0264
   Seabold S., 2010, P 9 PYTH SCI C AUST, V57, P10, DOI DOI 10.25080/MAJORA-92BF1922-011
   Sefc KM, 2017, HYDROBIOLOGIA, V791, P69, DOI 10.1007/s10750-016-2791-x
   Selkoe KA, 2010, MOL ECOL, V19, P3708, DOI 10.1111/j.1365-294X.2010.04658.x
   Sequeira F, 2020, J EVOLUTION BIOL, V33, DOI 10.1111/jeb.13562
   Sexton JP, 2014, EVOLUTION, V68, P1, DOI 10.1111/evo.12258
   Shine R, 2011, P NATL ACAD SCI USA, V108, P5708, DOI 10.1073/pnas.1018989108
   Stamatakis A, 2012, BIOINFORMATICS, V28, P2064, DOI 10.1093/bioinformatics/bts309
   Stamatakis A, 2014, BIOINFORMATICS, V30, P1312, DOI 10.1093/bioinformatics/btu033
   Stuart-Smith RD, 2017, NAT ECOL EVOL, V1, P1846, DOI 10.1038/s41559-017-0353-x
   Takegaki T, 2020, J EXP MAR BIOL ECOL, V530, DOI 10.1016/j.jembe.2020.151436
   Tang H, 2005, GENET EPIDEMIOL, V28, P289, DOI 10.1002/gepi.20064
   Tian M.-C., 1962, Stud. Mar. Sin., V2, P79
   Tibshirani R, 1996, J ROY STAT SOC B, V58, P267, DOI 10.1111/j.2517-6161.1996.tb02080.x
   Van der Auwera G. A., 2020, Genomics in the cloud: using Docker, GATK, and WDL in Terra
   Virtanen P, 2020, NAT METHODS, V17, P261, DOI 10.1038/s41592-019-0686-2
   Wang L, 2012, INT J MOL SCI, V13, P5584, DOI 10.3390/ijms13055584
   Wang XY, 2021, FISH RES, V235, DOI 10.1016/j.fishres.2020.105813
   Wang YQ, 2017, GENOM PROTEOM BIOINF, V15, P14, DOI 10.1016/j.gpb.2017.01.001
   Wu YD, 2021, AQUACULTURE, V540, DOI 10.1016/j.aquaculture.2021.736696
   Xu G, 1963, P 4 PLEN COMM FISH R, P39
   Xu G., 1962, STUDIA MAR SINICA, V2, P98
   [徐兆礼 Xu Zhaoli], 2011, [水产学报, Journal of Fisheries of China], V35, P429
   Yang B, 2021, AQUACULTURE, V535, DOI 10.1016/j.aquaculture.2021.736363
   Zhang CaiLan Zhang CaiLan, 2002, Journal of Shanghai Fisheries University, V11, P77
   Zhang J, 2015, ESTAUR WOR, P1, DOI 10.1007/978-3-319-16339-0
   Zhang QY., 2011, MOD FISH INFORM, V2, P3, DOI DOI 10.1002/HYP.8148
   Zhang Z, 2020, NUCLEIC ACIDS RES, V48, pD24, DOI 10.1093/nar/gkz913
   Zhao YF, 2018, MAR BIOTECHNOL, V20, P45, DOI 10.1007/s10126-017-9786-0
   Zheng XW, 2012, BIOINFORMATICS, V28, P3326, DOI 10.1093/bioinformatics/bts606
   Zhou Yi-fei, 2019, Nature Communications, V10, DOI [10.1038/s41467-019-13698-x, 10.1038/s41467-019-12821-2]
   Zhu HP, 2015, GENET MOL RES, V14, P10308, DOI 10.4238/2015.August.28.16
NR 99
TC 10
Z9 10
U1 13
U2 49
PU SPRINGERNATURE
PI LONDON
PA CAMPUS, 4 CRINAN ST, LONDON, N1 9XW, ENGLAND
SN 2096-6490
EI 2662-1746
J9 MAR LIFE SCI TECH
JI Mar. Life Sci. Tech.
PD MAY
PY 2023
VL 5
IS 2
BP 141
EP 154
DI 10.1007/s42995-023-00165-2
EA APR 2023
PG 14
WC Marine & Freshwater Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Marine & Freshwater Biology
GA H6ZB7
UT WOS:000965112300003
PM 37275538
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Paranunzio, R
   Guerrini, M
   Dwyer, E
   Alexander, PJ
   O'Dwyer, B
AF Paranunzio, Roberta
   Guerrini, Marco
   Dwyer, Edward
   Alexander, Paul J.
   O'Dwyer, Barry
TI Assessing Coastal Flood Risk in a Changing Climate for Dublin, Ireland
SO JOURNAL OF MARINE SCIENCE AND ENGINEERING
LA English
DT Article
DE coastal flooding; inundation; urban areas; sea level rise; coastal flood
   risk; socioeconomic vulnerability; climate adaptation
ID SEA-LEVEL RISE; EXTREME WAVE EVENTS; SOCIAL VULNERABILITY; HAZARD;
   EXPOSURE; EVOLUTION; CITIES; INDEX; CITY
AB With increasing urban expansion and population growth, coastal urban areas will be increasingly affected by climate change impacts such as extreme storm events, sea level rise and coastal flooding. To address coastal inundation risk for impact studies, integrated approaches accounting for flood hazard modelling, exposure and vulnerability of human and environmental systems are crucial. In this study, we model the impacts of sea level rise on coastal inundation depth for County Dublin, the most extensively urbanized area in Ireland, for the current period and for 2100 under two Representative Concentration Pathways RCP 4.5 and 8.5. A risk-centred approach has been considered by linking the information on coastal flood-prone areas to the exposure of the urban environment, in terms of potential future land cover changes, and to the socioeconomic vulnerability of the population. The results suggest significant challenges for Dublin city and the surrounding coastal areas, with an increase of around 26% and 67% in the number of administrative units considered at very high risk by the end of the century under a RCP 4.5 and 8.5, respectively. This study aims to contribute to existing coastal inundation research undertaken for Ireland by (i) providing a first-level screening of flooding hazards in the study area, (ii) demonstrating how land cover changes and socioeconomic vulnerability can contribute to the level of experienced risk and (iii) informing local authorities and at-risk communities so as to support them in the development of plans for adaptation and resilience.
C1 [Paranunzio, Roberta] Natl Res Council Italy, Inst Atmospher Sci & Climate CNR ISAC, I-10133 Turin, Italy.
   [Guerrini, Marco] Univ Coll Cork, MaREI Ctr, Environm Res Inst, Haulbowline Rd, Cork P43 C573, Ireland.
   [Dwyer, Edward] Randbee Consultants, Calle Carreteria 67 4 E, Malaga 29001, Spain.
   [Alexander, Paul J.] Cent Stat Off CSO, Census Geog, Dublin D11, Ireland.
   [O'Dwyer, Barry] KPMG Ireland, St Stephens Green, Dublin D02, Ireland.
C3 Consiglio Nazionale delle Ricerche (CNR); Istituto di Scienze
   dell'Atmosfera e del Clima (ISAC-CNR); University College Cork
RP Paranunzio, R (corresponding author), Natl Res Council Italy, Inst Atmospher Sci & Climate CNR ISAC, I-10133 Turin, Italy.
EM r.paranunzio@isac.cnr.it
RI Paranunzio, Roberta/N-2647-2019
OI Paranunzio, Roberta/0000-0002-2270-7467
FU Large Urban Area Adaptation (Urb-ADAPT) project in the EPA Research
   Programme 2014-2020 - Department of Communications, Climate Action and
   Environment [2015-CCRP-MS.25]; Environmental Protection Agency Ireland
   (EPA) [2015-CCRP-MS.25] Funding Source: Environmental Protection Agency
   Ireland (EPA)
FX This research received financial support of the Large Urban Area
   Adaptation (Urb-ADAPT) project (2015-CCRP-MS.25) in the EPA Research
   Programme 2014-2020, which is a Government of Ireland initiative funded
   by the Department of Communications, Climate Action and Environment,
   administered by the Environmental Protection Agency.
CR Abadie LM, 2020, OCEAN COAST MANAGE, V193, DOI 10.1016/j.ocecoaman.2020.105249
   ABPmer, 2017, R2784 ABPMER
   Adnan SG, 2016, NAT HAZARDS, V83, P1257, DOI 10.1007/s11069-016-2388-8
   Alexander PJ, 2014, ATMOSPHERE-BASEL, V5, P755, DOI 10.3390/atmos5040755
   Anderson CC, 2021, WATER-SUI, V13, DOI 10.3390/w13040577
   [Anonymous], 2004, Living with Risk: A global review of disaster reduction initiatives, VI
   Balica SF, 2012, NAT HAZARDS, V64, P73, DOI 10.1007/s11069-012-0234-1
   Bigi V, 2021, CLIMATE, V9, DOI 10.3390/cli9010012
   Binita KC, 2021, NAT HAZARDS, V105, P1963, DOI 10.1007/s11069-020-04385-y
   Bucherie A, 2022, INT J DISAST RISK RE, V73, DOI 10.1016/j.ijdrr.2022.102897
   C3S copernicus, COAST FLOOD IR
   Caloca-Casado S, 2018, THESIS NATL U IRELAN
   Camaro Garcia W., 2021, Climate Status Report for Ireland
   Cannon C, 2020, CLIM RISK MANAG, V27, DOI 10.1016/j.crm.2019.100210
   Carter JG, 2015, PROG PLANN, V95, P1, DOI 10.1016/j.progress.2013.08.001
   Copernicus Land Monitoring Service, CORINE LAND COV COP
   CSO, 2022, REG POP PROJ 2017 20
   CSO Census, 2016, SMALL AR POP STAT CS
   CSO Census of Population, 2022, PREL RES
   Cutter SL, 2003, SOC SCI QUART, V84, P242, DOI 10.1111/1540-6237.8402002
   data.gov, GOVT IRELAND DATA GO
   DCC Dublin City Council, 2017, CLIM CHANG ACT PLAN, P1
   de Sherbinin A, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.600
   Demuzere M, 2021, FRONT ENV SCI-SWITZ, V9, DOI 10.3389/fenvs.2021.637455
   Depietri Y, 2018, NAT HAZARD EARTH SYS, V18, P3363, DOI 10.5194/nhess-18-3363-2018
   Desmond M., 2017, SUMMARY STATE KNOWLE
   Devoy R., 2021, COASTAL ATLAS IRELAN
   Devoy RJN, 2008, J COASTAL RES, V24, P325, DOI 10.2112/07A-0007.1
   Di Paola G, 2021, ENVIRON EARTH SCI, V80, DOI 10.1007/s12665-021-09884-0
   Dublin City Council Dublin City Council dublincity, DUBLIN CITY COUNCIL
   Eastman J.R., 2018, Lecture Notes in Geoinformation and Cartography, DOI [10.1007/978-3-319-60801-3_36, DOI 10.1007/978-3-319-60801-3_36, 10.1007/978-3-319-60801-336, DOI 10.1007/978-3-319-60801-336]
   Emrich CT, 2020, ENVIRON HAZARDS-UK, V19, P228, DOI 10.1080/17477891.2019.1675578
   eumetsat, EUMETSAT STORM XAVER
   Flood S., 2012, QUANTIFYING IMPACTS, P37
   Flood S, 2014, OCEAN COAST MANAGE, V102, P19, DOI 10.1016/j.ocecoaman.2014.08.015
   Ghosh S, 2021, OCEAN COAST MANAGE, V209, DOI 10.1016/j.ocecoaman.2021.105641
   Giannakidou C, 2019, NAT HAZARDS, V97, P99, DOI 10.1007/s11069-019-03629-w
   Gotham KF, 2018, RISK ANAL, V38, P345, DOI 10.1111/risa.12830
   gov.ie, DHPLG NATL MARINE PL
   Hadipour V, 2020, WATER-SUI, V12, DOI 10.3390/w12092379
   Hardy RD, 2018, APPL GEOGR, V91, P10, DOI 10.1016/j.apgeog.2017.12.019
   Hauer ME, 2020, NAT REV EARTH ENV, V1, P28, DOI 10.1038/s43017-019-0002-9
   Hua JY, 2021, SUSTAIN CITIES SOC, V64, DOI 10.1016/j.scs.2020.102507
   Infomar, INFOMAR HOME
   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
   Janjic J., 2018, ADV SCI RES, V15, P145, DOI DOI 10.5194/asr-15-145-2018
   Jeffers JM, 2013, APPL GEOGR, V37, P44, DOI 10.1016/j.apgeog.2012.10.011
   Jiang LW, 2017, GLOBAL ENVIRON CHANG, V42, P193, DOI 10.1016/j.gloenvcha.2015.03.008
   KAISER HF, 1960, EDUC PSYCHOL MEAS, V20, P141, DOI 10.1177/001316446002000116
   Kantamaneni K, 2018, OCEAN COAST MANAGE, V158, P164, DOI 10.1016/j.ocecoaman.2018.03.039
   Kettle A.J., 2020, Adv. Geosci, V54, P137, DOI DOI 10.5194/ADGEO-54-137-2020
   Koks EE, 2015, ENVIRON SCI POLICY, V47, P42, DOI 10.1016/j.envsci.2014.10.013
   Ku H, 2021, OCEAN COAST MANAGE, V213, DOI 10.1016/j.ocecoaman.2021.105884
   Kulp SA, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-12808-z
   Langsdorf S., 2022, CLIMATE CHANGE 2022, DOI [10.1017/9781009325844, DOI 10.1017/9781009325844]
   Lawrence J, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.703902
   Lhomme S., 2019, Cybergeo, Eur ...  Geogr.  ..., V651, P1
   Lowe J.A., 2009, UK CLIMATE PROJECTIO
   Luque P, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.676452
   Martau E, 2020, NAT HAZARDS, V102, P275, DOI 10.1007/s11069-020-03925-w
   McEvoy S, 2021, OCEAN COAST MANAGE, V203, DOI 10.1016/j.ocecoaman.2020.105512
   Nardo M., 2008, Handbook on constructing composite indicators: Methodology and user guide
   Nejad AS, 2022, OCEAN SCI, V18, P511, DOI 10.5194/os-18-511-2022
   Nolan P., 2020, High-resolution Climate Projections for Ireland-A Multi-model Ensemble Approach, DOI DOI 10.13140/RG.2.2.28360.14084
   O'Brien L, 2018, NAT HAZARD EARTH SYS, V18, P729, DOI 10.5194/nhess-18-729-2018
   O'Neill BC, 2014, CLIMATIC CHANGE, V122, P387, DOI 10.1007/s10584-013-0905-2
   Okaka FO, 2019, INT J CLIM CHANG STR, V11, P592, DOI 10.1108/IJCCSM-03-2018-0026
   OPW, 2021, NAT COAST FLOOD HAZ
   OPW, 2018, FLOOD RISK MANAGEMEN, P245
   OPW Home Floodinfo.ie, FLOOD IE
   OPW RPS, 2011, IR COAST PROT STRAT
   Orford J, 2015, GLOBAL PLANET CHANGE, V133, P254, DOI 10.1016/j.gloplacha.2015.09.002
   OSI, ORDN SURV IR NAT MAP
   Paranunzio R., 2020, ASSESSING VULNERABIL
   Paranunzio R, 2021, URBAN CLIM, V40, DOI 10.1016/j.uclim.2021.100983
   Paranunzio R, 2019, ATMOSPHERE-BASEL, V10, DOI 10.3390/atmos10030117
   Patel P, 2020, URBAN CLIM, V32, DOI 10.1016/j.uclim.2020.100616
   Percival S, 2019, NAT HAZARDS, V97, P355, DOI 10.1007/s11069-019-03648-7
   pobal, POBAL POBAL MAPS POR
   Rasch RJ, 2016, ENVIRON URBAN, V28, P145, DOI 10.1177/0956247815620961
   Rizzo A, 2020, WATER-SUI, V12, DOI 10.3390/w12051405
   Roberts D.C., 2019, IPCC SPECIAL REPORT, P39, DOI [DOI 10.1017/9781009157964.002, 10.1017/9781009157964.002]
   Sánchez-García E, 2022, CLIM SERV, V28, DOI 10.1016/j.cliser.2022.100337
   Savic S, 2020, GEOGR PANNONICA, V24, P88, DOI 10.5937/gp24-25202
   Scicchitano G, 2021, MAR GEOL, V439, DOI 10.1016/j.margeo.2021.106556
   Seto KC, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0023777
   Sorg L, 2018, NAT HAZARDS, V92, P257, DOI 10.1007/s11069-018-3207-1
   Stevens AJ, 2015, NAT HAZARD EARTH SYS, V15, P1215, DOI 10.5194/nhess-15-1215-2015
   Stewart ID, 2012, B AM METEOROL SOC, V93, P1879, DOI 10.1175/BAMS-D-11-00019.1
   Sweeney J., 2020, Ireland and the Climate Crisis, V1 edn, P15
   Sweet WV, 2014, EARTHS FUTURE, V2, P579, DOI 10.1002/2014EF000272
   Tate E, 2021, NAT HAZARDS, V106, P435, DOI 10.1007/s11069-020-04470-2
   Török I, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10103780
   Vousdoukas MI, 2018, NAT CLIM CHANGE, V8, P776, DOI 10.1038/s41558-018-0260-4
   Vousdoukas MI, 2017, EARTHS FUTURE, V5, P304, DOI 10.1002/2016EF000505
   Walz Y, 2021, INT J DISAST RISK RE, V63, DOI 10.1016/j.ijdrr.2021.102425
   Wolff C, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-70928-9
   Wu T, 2021, ECOL INDIC, V129, DOI 10.1016/j.ecolind.2021.108006
   Luque AY, 2021, NAT HAZARDS, V109, P1297, DOI 10.1007/s11069-021-04879-3
NR 99
TC 11
Z9 11
U1 14
U2 38
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2077-1312
J9 J MAR SCI ENG
JI J. Mar. Sci. Eng.
PD NOV
PY 2022
VL 10
IS 11
AR 1715
DI 10.3390/jmse10111715
PG 28
WC Engineering, Marine; Engineering, Ocean; Oceanography
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Oceanography
GA 6C7TP
UT WOS:000882211900001
OA gold
DA 2025-01-10
ER

PT J
AU McClenachan, L
   Moulton, A
AF McClenachan, Loren
   Moulton, Allie
TI Transitions from wild-caught fisheries to shellfish and seaweed
   aquaculture increase gender equity in Maine
SO MARINE POLICY
LA English
DT Article
DE Gender; Fisheries transitions; Sustainable aquaculture; Climate
   adaptation; Lobster; Kelp
AB Transitions from wild-caught and high-input finfish aquaculture to low-input or non-fed aquaculture will help to meet global blue-growth goals. These industries may also increase participation by women as compared to wild -caught fisheries that have been traditionally male-dominated. Here we ask whether transitions to shellfish and seaweed (or non-fed) aquaculture increase gender equity in Maine's fisheries, where the lobster fishery has been dominant for three decades. We find that non-fed aquaculture has increased women's participation by more than four times; 23.1 % of shellfish and seaweed aquaculture license holders are female, compared to 4.8 % of lobster license holders. Women's participation is highest (37.8 %) within the fast-growing, but relatively low-value seaweed aquaculture sector and lowest (17.6 %) in higher-value oyster farming. Women hold half of the Limited Purpose Aquaculture licenses (a subclass of licenses intended to simplify the process of entering into aquaculture) for seaweed, suggesting that they function to increase women's participation. Women in these industries attribute differential female participation in non-fed aquaculture as compared to lobster fisheries to fewer gendered institutional barriers, an ability to achieve more independence in marketing and distribution, and more flexible working hours. Exclusionary institutions are still seen as barriers to success in non-fed aquaculture, but female farmers also report that they have created informal leadership roles focused on com-munity building and social responsibility. Together these results suggest that transitions to non-fed aquaculture have the potential to increase gender equity in this sector of seafood production, but further reducing gendered institutions is key to achieving this outcome.
C1 [McClenachan, Loren] Univ Victoria, Dept Hist, Ocean Hist Lab, Victoria, BC V8P 5C2, Canada.
   [McClenachan, Loren] Univ Victoria, Sch Environm Studies, Victoria, BC V8P 5C2, Canada.
   [Moulton, Allie] Colby Coll Environm Studies Program, Waterville, ME 04901 USA.
   [McClenachan, Loren] 3800 Finnerty Rd, Victoria, BC V8P 5C2, Canada.
C3 University of Victoria; University of Victoria
RP McClenachan, L (corresponding author), 3800 Finnerty Rd, Victoria, BC V8P 5C2, Canada.
EM lorenm@uvic.ca
RI Moulton, Allie/JDX-0410-2023
FU Environmental Studies Program, Colby College, Maine USA
FX We are grateful for funding from Environmental Studies Program, Colby
   College, Maine USA, Lily Wilson for assistance with interviews with
   female lobster fishers, and Madeline Brodrick for assistance with the
   media analysis and manuscript preparation.
CR Acheson JamesM., 1988, The Lobster Gangs of Maine
   [Anonymous], 2020, World Fisheries and aquaculture: The state of sustainability in action [Internet], DOI DOI 10.4060/CA9229EN
   Barrett LT, 2022, ECOSYST SERV, V53, DOI 10.1016/j.ecoser.2021.101396
   Bennett E, 2005, MAR POLICY, V29, P451, DOI 10.1016/j.marpol.2004.07.003
   Bennett NJ, 2021, MAR POLICY, V125, DOI 10.1016/j.marpol.2020.104387
   Blythe J, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9010126
   Brod M, 2009, QUAL LIFE RES, V18, P1263, DOI 10.1007/s11136-009-9540-9
   Campbell LM, 2021, MAR POLICY, V124, DOI 10.1016/j.marpol.2020.104361
   Braña CBC, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.666662
   Cleaver C, 2018, B MAR SCI, V94, P1215, DOI 10.5343/bms.2017.1107
   DMR, 2020, MAIN STAT LOBST LIC
   DMR, 2021, HIST MAIN LOBST LAND
   DMR, 2021, AQ LEAS APPL FORMS
   DMR, 2021, TOT MAIN AQ HARV VAL
   Farmery AK, 2021, ONE EARTH, V4, P28, DOI 10.1016/j.oneear.2020.12.002
   Froehlich HE, 2019, CURR BIOL, V29, P3087, DOI 10.1016/j.cub.2019.07.041
   Gibbs MT, 2007, ECOL INDIC, V7, P94, DOI 10.1016/j.ecolind.2005.10.004
   Gjedrem T, 2012, AQUACULTURE, V350, P117, DOI 10.1016/j.aquaculture.2012.04.008
   Gopal N., 2016, ASIAN FISH SCI, V29, P246
   Greene M., 2020, SPIRE
   KAPLAN IM, 1988, J CONTEMP ETHNOGR, V16, P491, DOI 10.1177/0891241688164004
   Kim J, 2019, PHYCOLOGIA, V58, P446, DOI 10.1080/00318884.2019.1625611
   Mangubhai S, 2021, MAR POLICY, V123, DOI 10.1016/j.marpol.2020.104287
   Mattison L., 2009, THESIS BROWN U
   McClenachan L, 2020, AMBIO, V49, P144, DOI 10.1007/s13280-019-01156-3
   Meinzen-Dick R, 2014, ANNU REV ENV RESOUR, V39, P29, DOI 10.1146/annurev-environ-101813-013240
   Saunders B, 2018, QUAL QUANT, V52, P1893, DOI 10.1007/s11135-017-0574-8
   Schwerdtner-Manez K., 2016, PERSPECTIVES OCEANS, P193
   Smith Bren., 2019, Eat Like a Fish: My adventures Farming the Ocean to Fight Climate Change, V1st
   Starks H, 2007, QUAL HEALTH RES, V17, P1372, DOI 10.1177/1049732307307031
   Steneck RS, 2011, CONSERV BIOL, V25, P904, DOI 10.1111/j.1523-1739.2011.01717.x
   Stoll JS, 2019, MAR POLICY, V107, DOI 10.1016/j.marpol.2019.103583
   Szymkowiak M, 2020, MAR POLICY, V115, DOI 10.1016/j.marpol.2020.103846
   Szymkowiak M, 2020, FRONT MAR SCI, V7, DOI 10.3389/fmars.2020.00299
   Thomas A, 2021, OCEAN COAST MANAGE, V205, DOI 10.1016/j.ocecoaman.2021.105571
   Valenti W.C., 2011, World Aquac, V42, P26
   Weeratunge N, 2010, FISH FISH, V11, P405, DOI 10.1111/j.1467-2979.2010.00368.x
   Wosu A, 2019, MAR POLICY, V108, DOI 10.1016/j.marpol.2019.103649
   Yarish C, 2017, EEBB Articles
   Yodanis Carrie., 2000, QUAL SOCIOL, V23, P267, DOI [10.1023/A:1005515926536, DOI 10.1023/A:1005515926536]
NR 40
TC 11
Z9 12
U1 1
U2 13
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 DEC
PY 2022
VL 146
AR 105312
DI 10.1016/j.marpol.2022.105312
EA SEP 2022
PG 7
WC Environmental Studies; International Relations
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; International Relations
GA 5A8GB
UT WOS:000863118500008
DA 2025-01-10
ER

PT J
AU Misra, V
   Irani, T
   Staal, L
   Morris, K
   Asefa, T
   Martinez, C
   Graham, W
AF Misra, Vasubandhu
   Irani, Tracy
   Staal, Lisette
   Morris, Kevin
   Asefa, Tirusew
   Martinez, Chris
   Graham, Wendy
TI The Florida Water and Climate Alliance (FloridaWCA): Developing a
   Stakeholder-Scientist Partnership to Create Actionable Science in
   Climate Adaptation and Water Resource Management
SO BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
LA English
DT Article
DE Adaptation; Climate services; Decision support; Risk assessment;
   Societal impacts
ID SURFACE-TEMPERATURE TRENDS; REGIONAL REANALYSIS DATA; PRECIPITATION;
   HYDROCLIMATE; KNOWLEDGE; FORECASTS; POLICY
AB The Florida Water and Climate Alliance (FloridaWCA) is a stakeholder-scientist partnership committed to increasing the relevance of climate science data and tools at time and space scales needed to support decision-making in water resource management, planning, and supply operations in Florida. Since 2010, a group of university researchers, public utility water resource managers and operators, water management district personnel, and local planners have engaged in a sustained collaboration for the development, sharing, and application of cutting-edge research to the practical issues of water management and distribution in the highly urbanized state of Florida. The authors, all members of FloridaWCA, present a case study of the organization's history, its achievements, and lessons learned at the organizational, scientific/technical, and personal levels. Their goals are to 1) describe how the organizational process has contributed to actionable science based on posing and answering questions of importance; 2) share its scientific impact and technical contributions; 3) demonstrate the value of such a stakeholder-scientist partnership, and 4) identify organizational and structural components that have influenced its effectiveness, including personal reflections. The FloridaWCA, having reached its tenth anniversary, continues to evolve today as a sustained stakeholder-scientist partnership resulting in both guiding researchers of what is applicable in the field (creating an area of research that is useful to society) while also helping the practitioners to push the envelope on the state-of-the practices that can be informed by current research.
C1 [Misra, Vasubandhu] Florida State Univ, Ctr Ocean Atmospher Predict Studies, Tallahassee, FL 32306 USA.
   [Misra, Vasubandhu] Florida State Univ, Dept Earth Ocean & Atmospher Sci, Tallahassee, FL 32306 USA.
   [Misra, Vasubandhu] Florida State Univ, Florida Climate Inst, Tallahassee, FL 32306 USA.
   [Irani, Tracy] Univ Florida, Dept Family Youth & Community Sci, Gainesville, FL USA.
   [Staal, Lisette; Graham, Wendy] Univ Florida, Water Inst, Gainesville, FL USA.
   [Morris, Kevin] Peace River Manasota Reg Water Supply Author, Lakewood Ranch, FL USA.
   [Asefa, Tirusew] Tampa Bay Water, Planning & Syst Decis Support, Clearwater, FL USA.
   [Asefa, Tirusew] Univ S Florida, Patel Coll Global Sustainabil, Tampa, FL 33620 USA.
   [Martinez, Chris] Univ Florida, Inst Food & Agr Sci, Dept Agr & Biol Engn, Gainesville, FL USA.
C3 State University System of Florida; Florida State University; State
   University System of Florida; Florida State University; State University
   System of Florida; Florida State University; State University System of
   Florida; University of Florida; State University System of Florida;
   University of Florida; State University System of Florida; University of
   South Florida; State University System of Florida; University of Florida
RP Misra, V (corresponding author), Florida State Univ, Ctr Ocean Atmospher Predict Studies, Tallahassee, FL 32306 USA.; Misra, V (corresponding author), Florida State Univ, Dept Earth Ocean & Atmospher Sci, Tallahassee, FL 32306 USA.; Misra, V (corresponding author), Florida State Univ, Florida Climate Inst, Tallahassee, FL 32306 USA.
EM vmisra@fsu.edu
RI Irani, Tracy/A-5417-2012
OI Irani, Tracy/0000-0003-1803-4359
FU NOAA Climate Program Office; Offices of Research at the Florida State
   University; University of Florida; NASA [80NSSC19K1199]
FX We would like to acknowledge the support of NOAA Climate Program Office,
   the Offices of Research at the Florida State University, and the
   University of Florida to support the Florida Climate Institute and the
   Water Institute, respectively, and NASA Grant 80NSSC19K1199.
CR Advisory Committee on Climate Change and Natural Resource Science (ACCCNRS), 2015, REP SECR INT
   [Anonymous], 2009, INF DEC CHANG CLIM
   [Anonymous], 2010, THEOR CULT SOC, DOI DOI 10.1177/0263276409361497
   [Anonymous], 2013, NOAA State of the Coast Report Series
   [Anonymous], 2018, Impacts, risks, and adaptation in the united states: Fourth national climate assessment, VII, P1515, DOI DOI 10.7930/NCA4.2018
   [Anonymous], 2015, Global Risks 2015, V10th
   Asefa T, 2014, J HYDROL, V508, P53, DOI 10.1016/j.jhydrol.2013.10.043
   Barnett TP, 2009, P NATL ACAD SCI USA, V106, P7334, DOI 10.1073/pnas.0812762106
   Bastola S, 2015, ENVIRON MODELL SOFTW, V73, P90, DOI 10.1016/j.envsoft.2015.08.005
   Bastola S, 2014, HYDROL PROCESS, V28, P1989, DOI 10.1002/hyp.9734
   Bastola S, 2013, EARTH INTERACT, V17, DOI 10.1175/2013EI000519.1
   Bastola S, 2013, J HYDROMETEOROL, V14, P1334, DOI 10.1175/JHM-D-12-096.1
   Becker KL, 2017, AM J EVAL, V38, P138, DOI 10.1177/1098214016664025
   Beier P, 2017, CONSERV LETT, V10, P288, DOI 10.1111/conl.12300
   Bhardwaj A, 2019, CLIM DYNAM, V53, P2931, DOI 10.1007/s00382-019-04669-5
   Bolson J, 2018, WATER RESOUR RES, V54, P3453, DOI 10.1029/2017WR021191
   Bolson J, 2013, REG ENVIRON CHANGE, V13, pS141, DOI 10.1007/s10113-013-0463-1
   Brekke LD, 2009, WATER RESOUR RES, V45, DOI 10.1029/2008WR006941
   Bremer S, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.482
   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
   Carlson E., 2011, CLIMATE SCENARIOS FL
   Cash DW, 2006, SCI TECHNOL HUM VAL, V31, P465, DOI 10.1177/0162243906287547
   Cash DW, 2003, P NATL ACAD SCI USA, V100, P8086, DOI 10.1073/pnas.1231332100
   Chang S, 2018, HYDROL EARTH SYST SC, V22, P4793, DOI 10.5194/hess-22-4793-2018
   Chini CM, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9010105
   Dilling L, 2011, GLOBAL ENVIRON CHANG, V21, P680, DOI 10.1016/j.gloenvcha.2010.11.006
   Farrelly M, 2011, GLOBAL ENVIRON CHANG, V21, P721, DOI 10.1016/j.gloenvcha.2011.01.007
   Gleick PH, 2003, ANNU REV ENV RESOUR, V28, P275, DOI 10.1146/annurev.energy.28.040202.122849
   Hwang S, 2013, HYDROL EARTH SYST SC, V17, P4481, DOI 10.5194/hess-17-4481-2013
   Hwang S, 2014, J AM WATER RESOUR AS, V50, P1010, DOI 10.1111/jawr.12154
   Hwang S, 2014, J HYDROL, V510, P513, DOI 10.1016/j.jhydrol.2013.11.042
   Hwang S, 2013, REG ENVIRON CHANGE, V13, pS69, DOI 10.1007/s10113-013-0406-x
   Jacobs K., 2002, CONNECTING SCI POLIC
   Jones J.J., 2017, FLORIDAS CLIMATE CHA, P83
   Kiparsky M, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0084946
   Kirchhoff CJ, 2013, ANNU REV ENV RESOUR, V38, P393, DOI 10.1146/annurev-environ-022112-112828
   Klotzbach PJ, 2011, J CLIMATE, V24, P1252, DOI 10.1175/2010JCLI3799.1
   Kofinas G., 2002, COMMUNITY CONTRIBUTI, P54
   Kolb D.A., 2000, EXPERIENTIAL LEARNIN
   Lemos MC, 2005, GLOBAL ENVIRON CHANG, V15, P57, DOI 10.1016/j.gloenvcha.2004.09.004
   Li HQ, 2014, CLIM DYNAM, V42, P1449, DOI 10.1007/s00382-013-1813-x
   Lövbrand E, 2011, SCI PUBL POLICY, V38, P225, DOI 10.3152/030234211X12924093660516
   Miller C., 2004, STATES OF KNOWLEDGE
   Misra V, 2013, J CLIMATE, V26, P1467, DOI 10.1175/JCLI-D-12-00241.1
   Misra V, 2012, J CLIMATE, V25, P3610, DOI 10.1175/JCLI-D-11-00170.1
   Misra V, 2018, NPJ CLIM ATMOS SCI, V1, DOI 10.1038/s41612-018-0016-x
   Misra V, 2018, CLIM DYNAM, V51, P2157, DOI 10.1007/s00382-017-4005-2
   Misra V, 2016, J GEOPHYS RES-ATMOS, V121, P7691, DOI 10.1002/2016JD024824
   Misra V, 2016, CLIM DYNAM, V46, P1277, DOI 10.1007/s00382-015-2645-7
   Misra V, 2014, CLIM DYNAM, V42, P1425, DOI 10.1007/s00382-013-1812-y
   Misra V, 2013, CLIM DYNAM, V40, P1361, DOI 10.1007/s00382-012-1382-4
   Nag B, 2014, EARTH INTERACT, V18, DOI 10.1175/EI-D-14-0007.1
   Nel JL, 2016, CONSERV BIOL, V30, P176, DOI 10.1111/cobi.12560
   Paulson C., 2017, Blueprint for One Water
   Rosenzweig C, 2010, NATURE, V467, P909, DOI 10.1038/467909a
   Sankarasubramanian A, 2009, WATER RESOUR RES, V45, DOI 10.1029/2009WR007821
   Sankarasubramanian A, 2009, J APPL METEOROL CLIM, V48, P1464, DOI 10.1175/2009JAMC2122.1
   Selman C, 2016, J GEOPHYS RES-ATMOS, V121, P7606, DOI 10.1002/2016JD025002
   Selman C, 2015, J GEOPHYS RES-ATMOS, V120, P180, DOI 10.1002/2014JD021812
   Selman C, 2013, REG ENVIRON CHANGE, V13, pS153, DOI 10.1007/s10113-013-0477-8
   Stefanova L, 2012, CLIM DYNAM, V38, P161, DOI 10.1007/s00382-010-0988-7
   Stickel B., 2013, WASTE OUR WATER ANN
   Tian D, 2014, J CLIMATE, V27, P8384, DOI 10.1175/JCLI-D-13-00481.1
   U.S. Census Bureau, 2012, CPH21 US CENS BUR
   U.S. Water Alliance, 2016, ON WAT ROADM SUST MA
   UN ESA, 2014, WORLD URB PROSP 2014
   Vogel Jason, 2017, Climate Services, V6, P65, DOI 10.1016/j.cliser.2017.07.003
   Vogel JM., 2015, Actionable Science in Practice: Co-Producing Climate Change Information for Water Utility Vulnerability Assessments
   Wall TU, 2017, WEATHER CLIM SOC, V9, P95, DOI 10.1175/WCAS-D-16-0008.1
   Water Institute, 2010, SYNTH PREL PHON M DI
   Wenger E., 1998, COMMUNITIES PRACTICE, DOI DOI 10.1017/CBO9780511803932
NR 72
TC 9
Z9 10
U1 0
U2 5
PU AMER METEOROLOGICAL SOC
PI BOSTON
PA 45 BEACON ST, BOSTON, MA 02108-3693, UNITED STATES
SN 0003-0007
EI 1520-0477
J9 B AM METEOROL SOC
JI Bull. Amer. Meteorol. Soc.
PD FEB
PY 2021
VL 102
IS 2
BP E367
EP E382
DI 10.1175/BAMS-D-19-0302.1
PG 16
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Meteorology & Atmospheric Sciences
GA RW9FZ
UT WOS:000646826000010
DA 2025-01-10
ER

PT J
AU Gros, C
   Bailey, M
   Schwager, S
   Hassan, A
   Zingg, R
   Uddin, MM
   Shahjahan, M
   Islam, H
   Lux, S
   Jaime, C
   de Perez, EC
AF Gros, Clemens
   Bailey, Meghan
   Schwager, Saroja
   Hassan, Ahmadul
   Zingg, Raymond
   Uddin, Muhammad Mamtaz
   Shahjahan, Mohammad
   Islam, Hasibul
   Lux, Stefanie
   Jaime, Catalina
   de Perez, Erin Coughlan
TI Household-level effects of providing forecast-based cash in anticipation
   of extreme weather events: Quasi-experimental evidence from humanitarian
   interventions in the 2017 floods in Bangladesh
SO INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
LA English
DT Article
DE Cash transfer; Climate adaptation; Vulnerability; Forecast; Floods;
   Bangladesh
ID CLIMATE; SYSTEMS; LIVES
AB In 2017, Bangladesh experienced the worst floods in recent decades. Based on a forecast and pre-defined trigger level, a Red Cross Red Crescent project distributed an unconditional cash grant of BDT 5000 (USD 60 equivalent) to 1039 poor households in highly vulnerable, flood-prone communities in the Brahmaputra river basin before an early flood peak. Systems that can deliver forecast-based cash grants are a potential adaptation strategy to deal with changes in extreme events linked to climate change. This paper presents the results of a mixed-methods, quasi-experimental study, based on a post-disaster household survey. The research assesses the effectiveness of the forecast-based cash distribution in helping beneficiaries to take preparatory early actions and reduce the negative impacts of the flood on their health, well-being, assets and livelihoods. The assessment shows that the cash grants contributed to improving households' access to food, a reduction in high-interest debt accrual of vulnerable households, and reduced psychosocial stress during and after the flood period, compared to a control group of similarly vulnerable and flood-affected communities that did not receive the forecast-based cash assistance. The intervention may also have prevented households from being forced to make destitution sales of valuable assets, as indicated by qualitative data collected in July, but we do not see these benefits sustained after a second flood peak in August 2017. There is a need for further research to assess the longer-term effects of forecast-based cash on the socio-economic development and well-being of the most vulnerable.
C1 [Gros, Clemens; Bailey, Meghan; Hassan, Ahmadul; Jaime, Catalina; de Perez, Erin Coughlan] Red Cross Red Crescent Climate Ctr, Anna van Saksenlaan 50, NL-2593 HT The Hague, Netherlands.
   [Bailey, Meghan] Univ Oxford, Environm Change Inst, 34 Broad St, Oxford OX1 3BD, England.
   [Schwager, Saroja; de Perez, Erin Coughlan] Columbia Univ, Int Res Inst Climate & Soc, Earth Inst, Palisades, NY 10964 USA.
   [Zingg, Raymond; Uddin, Muhammad Mamtaz; Shahjahan, Mohammad; Islam, Hasibul] German Red Cross Bangladesh, 684-686 Red Crescent Sarak, Dhaka 1217, Bangladesh.
   [Lux, Stefanie] German Red Cross, Carstennstr 58, D-12205 Berlin, Germany.
   [de Perez, Erin Coughlan] Vrije Univ Amsterdam, Inst Environm Studies IVM, De Boelelaan 1087, NL-1081 HV Amsterdam, Netherlands.
C3 University of Oxford; Columbia University; Vrije Universiteit Amsterdam
RP Gros, C (corresponding author), Rhinower Str 11, D-10437 Berlin, Germany.
EM gros@climatecentre.org
RI Md, Shahjahan/AAL-1278-2021
OI Jaime, Catalina/0000-0002-1053-8344; Gros, Clemens/0000-0001-6585-753X
FU German Federal Foreign Office, under the Action Plan of the Federal
   Foreign Office for humanitarian adaptation to climate change
FX This work was supported by the German Federal Foreign Office, under the
   Action Plan of the Federal Foreign Office for humanitarian adaptation to
   climate change.
CR Akhter SR, 2015, INT J DISAST RISK RE, V13, P313, DOI 10.1016/j.ijdrr.2015.07.011
   Alfieri L, 2012, ENVIRON SCI POLICY, V21, P35, DOI 10.1016/j.envsci.2012.01.008
   [Anonymous], 2016, CASH TRANSFERS WHAT
   Bailey S., 2015, Shaping policy for development State of evidence on humanitarian cash transfers Background Note for the High Level Panel on Humanitarian Cash Transfers
   Baqee Abdul., 1998, Peopling in the land of Allah Jane: Power, Peopling, and Environment: The case of the Char-Lands of Bangladesh
   Braman LM, 2013, DISASTERS, V37, P144, DOI 10.1111/j.1467-7717.2012.01297.x
   COHEN S, 1983, J HEALTH SOC BEHAV, V24, P385, DOI 10.2307/2136404
   Cumiskey L., 2015, INT J DISASTER RESIL, V6, P57, DOI DOI 10.1108/IJDRBE-08-2014-0062
   de Perez EC, 2015, NAT HAZARD EARTH SYS, V15, P895, DOI 10.5194/nhess-15-895-2015
   de Perez EC, 2016, HYDROL EARTH SYST SC, V20, P3549, DOI 10.5194/hess-20-3549-2016
   Ebi KL, 2004, B AM METEOROL SOC, V85, P1067, DOI 10.1175/BAMS-85-8-1067
   Feldman S, 2012, J PEASANT STUD, V39, P971, DOI 10.1080/03066150.2012.661719
   Fouillet A, 2008, INT J EPIDEMIOL, V37, P309, DOI 10.1093/ije/dym253
   Galindo G, 2013, SOCIO-ECON PLAN SCI, V47, P20, DOI 10.1016/j.seps.2012.11.002
   Ghosh S, 2014, ATMOS SCI LETT, V15, P157, DOI 10.1002/asl2.486
   Harriman L, 2014, ENVIRON DEV, V9, P93, DOI 10.1016/j.envclev.2013.12.001
   Hewitt C, 2012, NAT CLIM CHANGE, V2, P831, DOI 10.1038/nclimate1745
   IFRC, 2009, World disasters report 2009: focus on early warning, early action
   IFRC, 2018, EM PLAN ACT OP UPD B
   Knowlton K, 2014, INT J ENV RES PUB HE, V11, P3473, DOI 10.3390/ijerph110403473
   Krzysztofowicz R, 2001, J HYDROL, V249, P2, DOI 10.1016/S0022-1694(01)00420-6
   Langford G., 2016, LIVELIHOODS CHAR RIV
   Lodree EJ, 2011, J HUMANIT LOGIST SUP, V1, P50, DOI 10.1108/20426741111122411
   Philip S, 2019, HYDROL EARTH SYST SC, V23, P1409, DOI 10.5194/hess-23-1409-2019
   Priya S., 2017, Flood risk assessment and forecasting for the Ganges-Brahmaputra-Meghna river basins
   Red Cross Red Crescent Climate Centre, 2013, HLTH RISK MAN CHANG
   Rogers DP, 2013, DIR DEV, P1, DOI 10.1596/978-1-4648-0026-9
   Ross KW, 2009, ENVIRON RES LETT, V4, DOI 10.1088/1748-9326/4/2/024009
   Sai F., 2018, NAT HAZARDS EARTH SY, DOI [10.5194/nhess-2018-26, DOI 10.5194/NHESS-2018-26]
   Toufique KA, 2014, INT J DISAST RISK RE, V10, P236, DOI 10.1016/j.ijdrr.2014.08.008
   Watts N, 2018, LANCET, V391, P581, DOI 10.1016/S0140-6736(17)32464-9
   Webster PJ, 2013, NATURE, V493, P17, DOI 10.1038/493017a
   Webster PJ, 2010, B AM METEOROL SOC, V91, P1493, DOI 10.1175/2010BAMS2911.1
   Yang YCE, 2015, NAT HAZARDS, V75, P2773, DOI 10.1007/s11069-014-1459-y
NR 34
TC 32
Z9 34
U1 1
U2 15
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 DEC
PY 2019
VL 41
AR 101275
DI 10.1016/j.ijdrr.2019.101275
PG 11
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 JZ2HI
UT WOS:000504924200025
OA hybrid
DA 2025-01-10
ER

PT J
AU Hu, YM
   Ou, TH
   Huang, JB
   Gustavsson, T
   Bogren, J
AF Hu, Yumei
   Ou, Tinghai
   Huang, Jianbin
   Gustavsson, Torbjorn
   Bogren, Jorgen
TI Winter hoar frost conditions on Swedish roads in a warming climate
SO INTERNATIONAL JOURNAL OF CLIMATOLOGY
LA English
DT Article
DE climate change; hoar frost risk; North Atlantic oscillation; relative
   humidity; road surface temperature; Sweden
ID TRAFFIC ACCIDENTS; AIR ADVECTIONS; EXPERT-SYSTEM; SLIPPERINESS; WEATHER;
   VARIABILITY; REANALYSIS; PREDICTION; SWEDEN; BRIDGE
AB As one of the most common reasons for slippery roads in wintertime, hoar frost can reduce surface friction and affect traffic safety. The risk of winter road hoar frost is subjected to changes in the warming climate. A better understanding of these changes could lead to improved forecasting of hoar frost risk and provide information to policymakers in making climate adaptation strategies. In this work, the decadal variation in winter road hoar frost risk between 2000 and 2016 in Sweden was examined by using in situ observations from 244 stations in the Swedish Road Weather Information System. Results show that hoar frost risks have decreased in the south of Sweden (south of 59 degrees N), whilst increasing in central Sweden (approximately 59 degrees-65 degrees N). Hoar frost risk tends to increase (decrease) in regions where there is a relatively high (low) mean number of hoar frost risk days. Further analysis indicates that the strengthened winter North Atlantic Oscillation (NAO) over the last few decades, which resulted in warmer and wetter winters in Sweden, is the main cause of the changes. During strong positive NAO winters, the frequency of blocking anticyclones centred to the south-west of Sweden significantly decreased and led to more warm and moist air from south-west being transported to Sweden. The reduction in hoar frost risk in the southern part of Sweden is mainly due to an increase in road surface temperature, while the increasing hoar frost risk in central Sweden is dominated by the increase in relative humidity, which favours the occurrence of hoar frost.
C1 [Hu, Yumei; Ou, Tinghai; Huang, Jianbin; Gustavsson, Torbjorn; Bogren, Jorgen] Univ Gothenburg, Dept Earth Sci, Guldhedsgatan 5 A, S-41320 Gothenburg, Sweden.
   [Huang, Jianbin] Tsinghua Univ, Dept Earth Syst Sci, Beijing, Peoples R China.
C3 University of Gothenburg; Tsinghua University
RP Hu, YM (corresponding author), Univ Gothenburg, Dept Earth Sci, Guldhedsgatan 5 A, S-41320 Gothenburg, Sweden.
EM yumei.hu@gvc.gu.se
RI Huang, Jianbin/AAP-5941-2020; Ou, Tinghai/A-5068-2013
OI Ou, Tinghai/0000-0002-6847-4099
FU Swedish Transport Administration
FX Professor D. Chen in the Department of Earth Sciences, Goteborgs
   Universitet is gratefully acknowledged for the helpful discussions. We
   thank PhD E. Almkvist in the same department for downloading and reading
   the in situ observations. This research project was funded by the
   Swedish Transport Administration.
CR Andersson AK, 2007, METEOROL APPL, V14, P297, DOI 10.1002/met.32
   Andersson A, 2011, METEOROL APPL, V18, P125, DOI 10.1002/met.186
   Andreescu MP, 1998, CLIMATE RES, V9, P225, DOI 10.3354/cr009225
   [Anonymous], 2000, METEOROLOGY SCI ENG
   [Anonymous], 2013, CONTRIBUTION WORKING
   [Anonymous], SWED TRANSP ADM PUBL
   [Anonymous], 53 NCHRP
   Bulygina ON, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/2/025003
   Dai A, 2006, J CLIMATE, V19, P3589, DOI 10.1175/JCLI3816.1
   Davini P, 2014, CLIM DYNAM, V43, P71, DOI 10.1007/s00382-013-1873-y
   Dee DP, 2011, Q J ROY METEOR SOC, V137, P553, DOI 10.1002/qj.828
   Deser C, 2017, CLIM DYNAM, V49, P3141, DOI 10.1007/s00382-016-3502-z
   Galek G, 2015, ATMOS RES, V151, P120, DOI 10.1016/j.atmosres.2014.05.006
   Greenfield TM, 2006, J APPL METEOROL CLIM, V45, P517, DOI 10.1175/JAM2356.1
   GUSTAVSSON T, 1991, INT J CLIMATOL, V11, P315
   GUSTAVSSON T, 1990, METEOROL MAG, V119, P267
   HEWSON TD, 1992, METEOROL MAG, V121, P1
   Huang JB, 2017, NAT CLIM CHANGE, V7, P875, DOI 10.1038/s41558-017-0009-5
   Ihs A., 2002, WINTER MAINTENANCE S
   Karlsson P, 2001, METEOROL APPL, V8, P95
   Kjellstrom Erik, 2016, Clim Serv, V2-3, P15, DOI 10.1016/j.cliser.2016.06.004
   Kyte M, 2001, TRANSPORT RES REC, P60, DOI 10.3141/1776-08
   Liebmann B, 2010, B AM METEOROL SOC, V91, P1485, DOI 10.1175/2010BAMS3030.1
   Nordin L, 2015, THESIS
   Norrman J, 2000, METEOROL APPL, V7, P27, DOI 10.1017/S1350482700001407
   Norrman J, 2000, CLIMATE RES, V15, P185, DOI 10.3354/cr015185
   Ou TH, 2011, ACTA METEOROL SIN, V25, P517, DOI 10.1007/s13351-011-0410-3
   Rehborn H, 2014, J ADV TRANSPORT, V48, P1107, DOI 10.1002/atr.1254
   Simmons AJ, 2010, J GEOPHYS RES-ATMOS, V115, DOI 10.1029/2009JD012442
   SMHI, 2017, SVER KLIM HAR BLIV V
   Strong CK, 2010, TRANSPORT REV, V30, P677, DOI 10.1080/01441640903414470
   TAKLE ES, 1990, J APPL METEOROL, V29, P727, DOI 10.1175/1520-0450(1990)029<0727:BARFOA>2.0.CO;2
   Toms BA, 2017, J APPL METEOROL CLIM, V56, P1959, DOI 10.1175/JAMC-D-16-0199.1
NR 33
TC 5
Z9 5
U1 0
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 OCT
PY 2018
VL 38
IS 12
BP 4345
EP 4354
DI 10.1002/joc.5672
PG 10
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA GV7CH
UT WOS:000446279100001
DA 2025-01-10
ER

PT J
AU Sow, MD
   Segura, V
   Chamaillard, S
   Jorge, V
   Delaunay, A
   Lafon-Placette, C
   Fichot, R
   Faivre-Rampant, P
   Villar, M
   Brignolas, F
   Maury, S
AF Sow, Mamadou Dia
   Segura, Vincent
   Chamaillard, Sylvain
   Jorge, Veronique
   Delaunay, Alain
   Lafon-Placette, Clement
   Fichot, Regis
   Faivre-Rampant, Patricia
   Villar, Marc
   Brignolas, Franck
   Maury, Stephane
TI Narrow-sense heritability and <i>P</i><sub>ST</sub> estimates of DNA
   methylation in three <i>Populus nigra</i> L. populations under
   contrasting water availability
SO TREE GENETICS & GENOMES
LA English
DT Article
DE DNA methylation; h(2); P-ST; F-ST; Poplar; Water availability
ID SHOOT APICAL MERISTEM; PHENOTYPIC PLASTICITY; EPIGENETIC MEMORY;
   CLIMATIC ADAPTATION; GENE-EXPRESSION; SUGAR-BEET; DROUGHT; PATTERNS;
   GENOME; PLANTS
AB In a context of climate change and forest decline, a better understanding of the sources of tree flexibility involved in phenotypic plasticity and adaptation is needed. These last years, the role of epigenetics in the response to environmental variations has been established in several model plants at the genotype level but little is known at the level of natural populations grown in pedoclimatic sites. Here, we focused on three French natural populations of black poplar, a key pioneer tree from watersheds, planted in common garden and subjected to controlled variations of water availability. We estimated common genetic parameters such as narrow-sense heritability (h(2)), phenotypic differentiation index (P-ST), and the overall genetic differentiation index (F-ST) from genome-wide SNPs to evaluate the extent of epigenetic variations. Indeed, global DNA methylation levels from individuals exposed to drought or irrigated in a common garden were used. We found that the three populations were not distinguished by their levels of DNA methylation. However, a moderate drought was associated to a significant decrease in DNA methylation in the populations. Narrow-sense heritability and P-ST estimates of DNA methylation were similar to those found for biomass productivity. Heritability and P-ST were higher when trees were subjected to drought than in control condition. Negative genetic correlations between global DNA methylation and height or biomass were detected in drought condition only. Altogether, our data highlight that global DNA methylation acts as a genetic marker of natural population differentiation under drought stress in a pedoclimatic context.
C1 [Sow, Mamadou Dia; Chamaillard, Sylvain; Delaunay, Alain; Lafon-Placette, Clement; Fichot, Regis; Brignolas, Franck; Maury, Stephane] Univ Orleans, INRA, LBLGC, EA 1207,USC 1328, F-45067 Orleans, France.
   [Segura, Vincent; Jorge, Veronique; Villar, Marc] INRA, ONF, BioForA, F-45075 Orleans, France.
   [Lafon-Placette, Clement] Charles Univ Prague, Dept Bot, CZ-12800 Prague, Czech Republic.
   [Faivre-Rampant, Patricia] INRA, CEA IG CNG, EPGV, US1279, F-91057 Evry, France.
C3 INRAE; Universite de Orleans; INRAE; Charles University Prague; INRAE;
   Universite Paris Saclay
RP Maury, S (corresponding author), Univ Orleans, INRA, LBLGC, EA 1207,USC 1328, F-45067 Orleans, France.
EM stephane.maury@univ-orleans.fr
RI maury, sebastien/Q-6573-2018; Segura, Vincent/B-4656-2013; Sow,
   Mamadou/AFP-6476-2022; Jorge, Véronique/V-4165-2019; Lafon Placette,
   Clement/G-7599-2018; Fichot, Regis/A-3654-2015
OI Sow, Mamadou Dia/0000-0002-2815-4939; Maury,
   Stephane/0000-0003-0481-0847; VILLAR, Marc/0000-0001-9210-7072; Lafon
   Placette, Clement/0000-0001-6634-8104; Fichot,
   Regis/0000-0001-5527-4103; Segura, Vincent/0000-0003-1860-2256
FU "Ministere de la Recherche et Enseignement Superieur," France; "INRA
   DEPARTEMENT EFPA," France; project "PI EFPA-2010"; Agence Nationale de
   la Recherche (ANR); project "EPITREE" [ANR-17-CE32-0009-01]; Agence
   Nationale de la Recherche (ANR) [ANR-17-CE32-0009] Funding Source:
   Agence Nationale de la Recherche (ANR)
FX MDS obtained a PhD grant from the "Ministere de la Recherche et
   Enseignement Superieur," France. This work was funded by the "INRA
   DEPARTEMENT EFPA," France, with the project "PI EFPA-2010" and by the
   "Agence Nationale de la Recherche (ANR)" with the project "EPITREE"
   2018-2021, ANR-17-CE32-0009-01, http://www6.inra.fr/epitree-project/.
CR Allen CD, 2010, FOREST ECOL MANAG, V259, P660, DOI 10.1016/j.foreco.2009.09.001
   Alonso C, 2016, MOL ECOL RESOUR, V16, P80, DOI 10.1111/1755-0998.12426
   Alonso C, 2015, FRONT GENET, V6, DOI 10.3389/fgene.2015.00004
   Bewick AJ, 2017, CURR OPIN PLANT BIOL, V36, P103, DOI 10.1016/j.pbi.2016.12.007
   Bizet F, 2015, PHYSIOL PLANTARUM, V154, P39, DOI 10.1111/ppl.12271
   Bradshaw AD, 2006, NEW PHYTOL, V170, P644, DOI 10.1111/j.1469-8137.2006.01761.x
   Bräutigam K, 2013, ECOL EVOL, V3, P399, DOI 10.1002/ece3.461
   Bruce TJA, 2007, PLANT SCI, V173, P603, DOI 10.1016/j.plantsci.2007.09.002
   Causevic A, 2005, PLANT PHYSIOL BIOCH, V43, P681, DOI 10.1016/j.plaphy.2005.05.011
   Chamaillard S, 2011, TREE PHYSIOL, V31, P1076, DOI 10.1093/treephys/tpr089
   Conde D, 2017, PLANT CELL ENVIRON, V40, P2236, DOI 10.1111/pce.13019
   Cortijo S, 2014, SCIENCE, V343, P1145, DOI 10.1126/science.1248127
   Covarrubias-Pazaran G, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0156744
   de Rigo D, 2016, POPULUS NIGRA EUROPE
   Ding Y, 2012, NAT COMMUN, V3, DOI 10.1038/ncomms1732
   Dubin MJ, 2015, ELIFE, V4, DOI 10.7554/eLife.05255
   Faivre-Rampant P, 2016, MOL ECOL RESOUR, V16, P1023, DOI 10.1111/1755-0998.12513
   Feil R, 2012, NAT REV GENET, V13, P97, DOI 10.1038/nrg3142
   Fichot R, 2015, PLANT CELL ENVIRON, V38, P1233, DOI 10.1111/pce.12491
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fleta-Soriano E, 2016, FRONT PLANT SCI, V7, DOI 10.3389/fpls.2016.00143
   Garg R, 2015, SCI REP-UK, V5, DOI 10.1038/srep14922
   Goudet J, 2020, HIERFSTAT ESTIMATION
   Gourcilleau D, 2010, ANN FOREST SCI, V67, DOI 10.1051/forest/2009101
   Guarino F, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0131480
   Hamanishi ET, 2012, J EXP BOT, V63, P4959, DOI 10.1093/jxb/ers177
   Jansson S, 2007, ANNU REV PLANT BIOL, V58, P435, DOI 10.1146/annurev.arplant.58.032806.103956
   Kawakatsu T, 2016, CELL, V166, P492, DOI 10.1016/j.cell.2016.06.044
   Kooke R, 2015, PLANT CELL, V27, P337, DOI 10.1105/tpc.114.133025
   Lämke J, 2017, GENOME BIOL, V18, DOI 10.1186/s13059-017-1263-6
   Lafon-Placette C, 2018, J EXP BOT, V69, P537, DOI 10.1093/jxb/erx409
   Lafon-Placette C, 2013, NEW PHYTOL, V197, P416, DOI 10.1111/nph.12026
   Lambe P, 1997, IN VITRO CELL DEV-PL, V33, P155, DOI 10.1007/s11627-997-0015-9
   Lande R, 2009, J EVOLUTION BIOL, V22, P1435, DOI 10.1111/j.1420-9101.2009.01754.x
   Latzel V, 2013, NAT COMMUN, V4, DOI 10.1038/ncomms3875
   Law JA, 2010, NAT REV GENET, V11, P204, DOI 10.1038/nrg2719
   Le Paslier MC, 2016, PAG 24 PLANT AN GEN
   Lehtonen PK, 2009, MOL ECOL, V18, P4463, DOI 10.1111/j.1365-294X.2009.04364.x
   Leinonen T, 2008, J EVOLUTION BIOL, V21, P1, DOI 10.1111/j.1420-9101.2007.01445.x
   Liang D, 2014, BMC GENET, V15, DOI 10.1186/1471-2156-15-S1-S9
   Maher B, 2008, NATURE, V456, P18, DOI 10.1038/456018a
   Marron N, 2003, TREE PHYSIOL, V23, P1225, DOI 10.1093/treephys/23.18.1225
   Mauch-Mani B, 2017, ANNU REV PLANT BIOL, V68, P485, DOI 10.1146/annurev-arplant-042916-041132
   Merilä J, 2001, J EVOLUTION BIOL, V14, P892, DOI 10.1046/j.1420-9101.2001.00348.x
   Meyer P, 2015, J EXP BOT, V66, P3541, DOI 10.1093/jxb/eru502
   Mirouze M, 2011, CURR OPIN PLANT BIOL, V14, P267, DOI 10.1016/j.pbi.2011.03.004
   Monclus R, 2006, NEW PHYTOL, V169, P765, DOI 10.1111/j.1469-8137.2005.01630.x
   Nicotra AB, 2010, TRENDS PLANT SCI, V15, P684, DOI 10.1016/j.tplants.2010.09.008
   Niederhuth CE, 2016, GENOME BIOL, V17, DOI 10.1186/s13059-016-1059-0
   Plomion C, 2016, ANN FOREST SCI, V73, P77, DOI 10.1007/s13595-015-0488-3
   Porebski S, 1997, PLANT MOL BIOL REP, V15, P8, DOI 10.1007/BF02772108
   Raj S, 2011, P NATL ACAD SCI USA, V108, P12521, DOI 10.1073/pnas.1103341108
   Richards CL, 2017, ECOL LETT, V20, P1576, DOI 10.1111/ele.12858
   Robertson M, 2017, EVOL APPL, V10, P792, DOI 10.1111/eva.12482
   Schmitz RJ, 2013, NATURE, V495, P193, DOI 10.1038/nature11968
   Schönberger B, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0168623
   Seymour DK, 2017, CURR OPIN PLANT BIOL, V36, P56, DOI 10.1016/j.pbi.2017.01.005
   Shen X, 2014, PLOS GENET, V10, DOI 10.1371/journal.pgen.1004842
   Song YP, 2016, J EXP BOT, V67, P1477, DOI 10.1093/jxb/erv543
   Sork VL, 2018, J HERED, V109, P3, DOI 10.1093/jhered/esx091
   Speed D, 2012, AM J HUM GENET, V91, P1011, DOI 10.1016/j.ajhg.2012.10.010
   Sultan SE, 2009, ECOLOGY, V90, P1831, DOI 10.1890/08-1064.1
   Teyssier C, 2014, PHYSIOL PLANTARUM, V150, P271, DOI 10.1111/ppl.12081
   Teyssier E, 2008, PLANTA, V228, P391, DOI 10.1007/s00425-008-0743-z
   Toillon J, 2016, FOREST ECOL MANAG, V375, P55, DOI 10.1016/j.foreco.2016.05.023
   Trap-Gentil MV, 2011, J EXP BOT, V62, P2585, DOI 10.1093/jxb/erq433
   Tuskan GA, 2006, SCIENCE, V313, P1596, DOI 10.1126/science.1128691
   van Kleunen M, 2005, NEW PHYTOL, V166, P49, DOI 10.1111/j.1469-8137.2004.01296.x
   Vaughn MW, 2007, PLOS BIOL, V5, P1617, DOI 10.1371/journal.pbio.0050174
   Verhoeven KJF, 2016, MOL ECOL, V25, P1631, DOI 10.1111/mec.13617
   Vining Kelly J, 2012, BMC Genomics, V13, P27, DOI 10.1186/1471-2164-13-27
   WEIR BS, 1984, EVOLUTION, V38, P1358, DOI [10.2307/2408641, 10.1111/j.1558-5646.1984.tb05657.x]
   Yakovlev IA, 2017, FRONT PHYSIOL, V8, DOI 10.3389/fphys.2017.00674
   Yakovlev IA, 2016, PLANTA, V243, P1237, DOI 10.1007/s00425-016-2484-8
   Yakovlev IA, 2011, PLANT SCI, V180, P132, DOI 10.1016/j.plantsci.2010.07.004
   Yakovlev IA, 2010, NEW PHYTOL, V187, P1154, DOI 10.1111/j.1469-8137.2010.03341.x
   Yong WS, 2016, EPIGENET CHROMATIN, V9, DOI 10.1186/s13072-016-0075-3
   Zhu RQ, 2013, PLANTA, V237, P1483, DOI 10.1007/s00425-013-1858-4
NR 78
TC 17
Z9 19
U1 0
U2 46
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 1614-2942
EI 1614-2950
J9 TREE GENET GENOMES
JI Tree Genet. Genomes
PD OCT
PY 2018
VL 14
IS 5
AR 78
DI 10.1007/s11295-018-1293-6
PG 12
WC Forestry; Genetics & Heredity; Horticulture
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Forestry; Genetics & Heredity; Agriculture
GA GV4CU
UT WOS:000446045800001
DA 2025-01-10
ER

PT J
AU Keena, MA
   Sánchez, V
AF Keena, M. A.
   Sanchez, V.
TI Reproductive Behaviors of <i>Anoplophora glabripennis</i> (Coleoptera:
   Cerambycidae) in the Laboratory
SO JOURNAL OF ECONOMIC ENTOMOLOGY
LA English
DT Article
DE Asian longhorned beetle; invasive species; copulation; oviposition;
   reproduction
ID ASIAN LONGHORNED BEETLE; SPOTTED LONGICORN BEETLE; MALE-PRODUCED
   PHEROMONE; MATING-BEHAVIOR; POPULATIONS; VOLATILES; FECUNDITY; SURVIVAL;
   CHOICE; SAWYER
AB The reproductive behaviors of individual pairs of Anoplophora glabripennis (Motschulsky) (Coleoptera: Cerambycidae)-all combinations of three populations and three different ages-were observed in glass jars in the laboratory on Acer saccharum Marshall (Sapindales: Sapindaceae) host material. The virgin female occasionally made first contact, but mounting did not occur until the male antennated or palpated the female. If the female was receptive (older females initially less receptive than younger ones), the male mated with her immediately after mounting and initiated a prolonged pair-bond. When the female was not receptive, some males abandoned the attempt while most performed a short antennal wagging behavior. During the pair-bond, the male continuously grasped the female's elytral margins with his prothoracic tarsi or both pro-and mesothoracic tarsi. The male copulated in a series of three to four bouts (averaging three to five copulations each) during which the female chewed oviposition sites or walked on the host. Between bouts, the female oviposited and fertile eggs were deposited as soon as 43 min after the first copulation. Females became unreceptive again after copulation and the duration of the pair-bond depended on the male's ability to remain mounted. Some population differences were seen which may be climatic adaptations. A single pair-bond was sufficient for the female to achieve similar to 60% fertility for her lifetime, but female fecundity declined with age at mating. Under eradication conditions, mates will become more difficult to find and females that find mates will likely produce fewer progeny because they will be older at the time of mating.
C1 [Keena, M. A.; Sanchez, V.] US Forest Serv, Northern Res Stn, Northeastern Ctr Forest Hlth Res, USDA, Hamden, CT 06514 USA.
C3 United States Department of Agriculture (USDA); United States Forest
   Service
RP Keena, MA (corresponding author), US Forest Serv, Northern Res Stn, Northeastern Ctr Forest Hlth Res, USDA, Hamden, CT 06514 USA.
EM mkeena@fs.fed.us
RI Sánchez, Victor/KAM-5057-2024; Keena, Melody/W-7124-2019
OI Keena, Melody/0000-0003-3099-6243
CR ALCOCK J, 1994, ANNU REV ENTOMOL, V39, P1, DOI 10.1146/annurev.en.39.010194.000245
   EBERHARD WG, 1991, BIOL REV, V66, P1, DOI 10.1111/j.1469-185X.1991.tb01133.x
   FAUZIAH BA, 1987, APPL ENTOMOL ZOOL, V22, P272, DOI 10.1303/aez.22.272
   Fukaya M, 2005, APPL ENTOMOL ZOOL, V40, P63, DOI 10.1303/aez.2005.63
   Graves F, 2016, J INSECT BEHAV, V29, P615, DOI 10.1007/s10905-016-9587-8
   Haack RA, 2010, ANNU REV ENTOMOL, V55, P521, DOI 10.1146/annurev-ento-112408-085427
   Hanks LM., 2017, Cerambycidae of the world: biology and pest management, P133, DOI DOI 10.1057/978-1-137-45344-0_7
   He Ping, 1993, Acta Entomologica Sinica, V36, P51
   Hoover K, 2014, J CHEM ECOL, V40, P169, DOI 10.1007/s10886-014-0385-5
   HUGHES A L, 1979, Coleopterists Bulletin, V33, P45
   HUGHES AL, 1981, ANN ENTOMOL SOC AM, V74, P180, DOI 10.1093/aesa/74.2.180
   Keena MA, 2005, ANN ENTOMOL SOC AM, V98, P536, DOI 10.1603/0013-8746(2005)098[0536:PADFRA]2.0.CO;2
   Keena MA, 2002, ENVIRON ENTOMOL, V31, P490, DOI 10.1603/0046-225X-31.3.490
   Keena MA, 2006, ENVIRON ENTOMOL, V35, P912, DOI 10.1603/0046-225X-35.4.912
   Kobayashi H, 2003, APPL ENTOMOL ZOOL, V38, P141, DOI 10.1303/aez.2003.141
   LANCE DR, 2003, P USDA INT RES FOR G, P52
   Li Dejia, 1997, Journal of Northwest Forestry College, V12, P19
   Li Dejia, 1999, Journal of Beijing Forestry University, V21, P33
   Lingafelter S.W., 2002, REVISION GENUS ANOPL
   Lu W, 2013, J ECON ENTOMOL, V106, P215, DOI 10.1603/EC12251
   MCLAIN DK, 1987, BEHAV ECOL SOCIOBIOL, V20, P239, DOI 10.1007/BF00292176
   Meng PS, 2015, J INTEGR PEST MANAG, V6, DOI 10.1093/jipm/pmv003
   Meng PS, 2014, ENVIRON ENTOMOL, V43, P1379, DOI 10.1603/EN14129
   Morewood WD, 2004, J INSECT BEHAV, V17, P215, DOI 10.1023/B:JOIR.0000028571.52739.50
   Nehme ME, 2014, ENVIRON ENTOMOL, V43, P1034, DOI 10.1603/EN14049
   Nehme ME, 2010, ENVIRON ENTOMOL, V39, P169, DOI 10.1603/EN09177
   Nehme ME, 2009, ENVIRON ENTOMOL, V38, P1745, DOI 10.1603/022.038.0628
   Noldus Information Technology, 2013, OBS XT VERS 11 5 REF
   SAS Institute, 2015, SAS STAT US GUID VER
   Smith MT, 2002, ENVIRON ENTOMOL, V31, P76, DOI 10.1603/0046-225X-31.1.76
   Statistix, 2013, STAT WIND US MAN VER
   Thornhill R., 1983, pi
   Togashi K., 1998, KAGAKU SEIBUTSU, V36, P445
   Trotter RT, 2015, BIOL INVASIONS, V17, P3359, DOI 10.1007/s10530-015-0961-9
   U. S. Department of Agriculture Animal Plant Health Inspection Service Marketing and Regulatory Programs (USDA- APHIS-MRP), 2015, AS LONGH BEETL ER PR
   Wang Q, 1996, J INSECT BEHAV, V9, P47, DOI 10.1007/BF02213723
   WANG Q, 1990, ANN ENTOMOL SOC AM, V83, P860, DOI 10.1093/aesa/83.4.860
   Wang Qiao, 1996, Entomologist, V115, P40
   Yan J., 1992, Forest Insects of China, P455, DOI DOI 10.1673/031.009.2101
   YOKOI N, 1990, APPL ENTOMOL ZOOL, V25, P383, DOI 10.1303/aez.25.383
   YOKOI N, 1989, JPN J APPL ENTOMOL Z, V33, P175, DOI 10.1303/jjaez.33.175
   Zhang AJ, 2003, NATURWISSENSCHAFTEN, V90, P410, DOI 10.1007/s00114-003-0452-1
   Zhang AJ, 2002, Z NATURFORSCH C, V57, P553
   Zhou J. X., 1984, Scientia Silvae Sinicae, V20, P372
NR 44
TC 9
Z9 13
U1 0
U2 16
PU OXFORD UNIV PRESS INC
PI CARY
PA JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA
SN 0022-0493
EI 1938-291X
J9 J ECON ENTOMOL
JI J. Econ. Entomol.
PD APR
PY 2018
VL 111
IS 2
BP 620
EP 628
DI 10.1093/jee/tox355
PG 9
WC Entomology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Entomology
GA GB8II
UT WOS:000429319200016
PM 29420733
OA hybrid
DA 2025-01-10
ER

PT J
AU Rubio-Bellido, C
   Pérez-Fargallo, A
   Pulido-Arcas, JA
   Trebilcock, M
AF Rubio-Bellido, Carlos
   Perez-Fargallo, Alexis
   Pulido-Arcas, Jesus A.
   Trebilcock, Maureen
TI Application of adaptive comfort behaviors in Chilean social housing
   standards under the influence of climate change
SO BUILDING SIMULATION
LA English
DT Article
DE social housing energy policy; thermal performance; climate change;
   climate adaption; adaptive comfort
ID THERMAL COMFORT; WEATHER DATA; BUILDINGS; ENERGY; IMPACT; SIMULATION
AB Currently, energy performance indicators for buildings are associated with the primary energy source consumption, CO2 emissions or net energy distribution, which together set the building's energy efficiency. The evaluation is frequently based on setpoint temperatures and hours of operation. However, these fixed parameters are not suitable for social housing simulation as their performance tends to be in free running, excluding extremely cold or warm conditions. Therefore, a more successful assessment for the efficiency of these buildings is the users' capability to live within adaptive comfort ranges without air conditioning systems. The aim of this research is to analyze new Chilean standards for sustainable social housing in the context of climate change using the adaptive comfort approach addressed in EN 15251:2007. Using EnergyPlus simulation software, 16 parametric series are analyzed for current conditions and validated against on-site measurements. Meanwhile, a prediction for the climate in 2050 has also been taken into account. The case study is the most widespread low cost dwelling model. The study demonstrates that the period of time within thermal comfort conditions varies substantially if analysis is done using the adaptive comfort standard or the Sustainable Construction Code (CCS) for Chilean housing. Considering climate change, the percentage of time fluctuates from -19.00% to 24.30%. Concluding that the adaptive comfort model has a greater capacity to positively assess indoor temperatures for social housing in Central-Southern Chile. This research also establishes that it is possible to provide homes where standards are improved within comfort conditions without using artificial means, 99.67% of the time currently and 88.89% in the future.
C1 [Rubio-Bellido, Carlos] Univ Seville, Higher Tech Sch Bldg Engn, Dept Bldg Construct 2, Seville, Spain.
   [Perez-Fargallo, Alexis; Pulido-Arcas, Jesus A.] Univ Bio Bio, Fac Architecture Construct & Design, Dept Bldg Sci, Concepcion, Chile.
   [Trebilcock, Maureen] Univ Bio Bio, Fac Architecture Construct & Design, Dept Architectural Theory & Design, Concepcion, Chile.
C3 University of Sevilla; Universidad del Bio-Bio; Universidad del Bio-Bio
RP Rubio-Bellido, C (corresponding author), Univ Seville, Higher Tech Sch Bldg Engn, Dept Bldg Construct 2, Seville, Spain.
EM carlosrubio@us.es
RI Rubio-Bellido, Carlos/K-1861-2014; Pulido Arcas, Jesus
   Alberto/T-2129-2017; Trebilcock, Maureen/C-7148-2011; Perez Fargallo,
   Alexis/K-1975-2014
OI Rubio-Bellido, Carlos/0000-0001-6719-8793; Pulido Arcas, Jesus
   Alberto/0000-0002-7956-2203; Trebilcock, Maureen/0000-0002-1984-0259;
   Perez Fargallo, Alexis/0000-0001-7071-7523
FU FONDECYT - Chilean National Commission for Research in Science and
   Technology [3160806]
FX The authors belong to the Sustainable Architecture and Construction
   Research Group (GACS) at the University of the Bio-Bio and would like to
   acknowledge that this paper is part of the FONDECYT research project
   3160806 "Study of the feasible energy improvement standard for social
   housing in fuel poverty by means of post occupational adaptive comfort
   assessment and its progressive implementation" funded by the Chilean
   National Commission for Research in Science and Technology.
CR [Anonymous], 2018, 137902008 EN ISO
   [Anonymous], ASHRAE GUID 14 2014
   [Anonymous], 2013, WORLD EN OUTL 2013
   ASHRAE, 2013, ASHRAE STAND 55 2013
   Attia S, 2015, ENERG BUILDINGS, V102, P117, DOI 10.1016/j.enbuild.2015.05.017
   Belcher S. E., 2005, Building Services Engineering Research & Technology, V26, P49, DOI 10.1191/0143624405bt112oa
   Building Research Establishment, 2016, COD CONSTR SUST
   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]
   CEN, 2008, 156032008 EN
   CEN, 2007, 152172007 EN
   Chow DHC, 2012, INT J LOW-CARBON TEC, V7, P234, DOI 10.1093/ijlct/cts035
   CITEC UBB; DECON UC, 2012, MAN HERM AIR ED
   Comite Europeen de Normalisation (CEN), 2007, Standard EN 15251-2007
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Figueroa R, 2013, P 29 C PASS LOW EN A
   Guan L, 2009, BUILD ENVIRON, V44, P793, DOI 10.1016/j.buildenv.2008.05.021
   Humphreys MA, 2013, BUILD ENVIRON, V63, P40, DOI 10.1016/j.buildenv.2013.01.024
   Humphreys M.A., 1978, Building Research and Practice, V6, P92, DOI [10.1080/09613217808550656, DOI 10.1080/09613217808550656]
   International Organization for Standardization, 2004, ISO 8996
   IPCC, 2018, GLOB WARM 1 5C SUMM
   ISO, 2007, ISO 9920:2007
   Jentsch MF, 2008, ENERG BUILDINGS, V40, P2148, DOI 10.1016/j.enbuild.2008.06.005
   Jentsch MF, 2013, RENEW ENERG, V55, P514, DOI 10.1016/j.renene.2012.12.049
   Kunkel S., 2015, INDOOR AIR QUALITY T
   McCartney KJ, 2002, ENERG BUILDINGS, V34, P623, DOI 10.1016/S0378-7788(02)00013-0
   Met Office, 2016, UKS NAT WEATH SERV
   MINVU, 1992, DS 47 ORD GEN LEY GE
   MINVU, 2016, VIV MOD CONSTR SIT P
   MINVU, 2016, EST HIST
   MINVU, 2011, DS 01 REGL SIST INT
   MINVU, 2011, DS 49 REGL PROGR FON
   Mylona A, 2012, BUILD SERV ENG RES T, V33, P51, DOI 10.1177/0143624411428951
   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
   Fargallo AP, 2016, INF CONSTR, V68, DOI 10.3989/ic.15.048
   Fargallo AP, 2015, REV CONSTR, V14, P44, DOI 10.4067/S0718-915X2015000200006
   Programa de Estudios e Investigaciones en Energia (PRIEN), 2008, EST POT AH EN MED ME
   Royapoor M, 2015, ENERG BUILDINGS, V94, P109, DOI 10.1016/j.enbuild.2015.02.050
   Santamouris M, 2016, SOL ENERGY, V128, P61, DOI 10.1016/j.solener.2016.01.021
   UNEP, 2012, BUILD DES CONSTR FOR
NR 40
TC 30
Z9 33
U1 2
U2 35
PU TSINGHUA UNIV PRESS
PI BEIJING
PA B605D, XUE YAN BUILDING, BEIJING, 100084, PEOPLES R CHINA
SN 1996-3599
EI 1996-8744
J9 BUILD SIMUL-CHINA
JI Build. Simul.
PD DEC
PY 2017
VL 10
IS 6
BP 933
EP 947
DI 10.1007/s12273-017-0385-9
PG 15
WC Thermodynamics; Construction & Building Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Thermodynamics; Construction & Building Technology
GA FJ1WZ
UT WOS:000412512800012
DA 2025-01-10
ER

PT J
AU Luwesi, CN
   Obando, JA
   Shisanya, CA
AF Luwesi, Cush Ngonzo
   Obando, Joy Apiyo
   Shisanya, Chris Allan
TI The Impact of a Warming Micro-Climate on Muooni Farmers of Kenya
SO AGRICULTURE-BASEL
LA English
DT Article
DE micro-climate change; climate adaptation; vulnerability to drought
ID WATER-RESOURCES
AB Rainfed agriculture has become highly vulnerable to the depleting water resources in most arid and semi-arid tropics (ASATs) under the effect of climate change. The impact has certainly been very high in Muooni catchment where more than 99% of the natural forest has been cleared. The warming micro-climate is accelerated by extended deforestation, unsustainable irrigation, and water over-abstraction in the catchment by eucalyptus and other exotic trees. The dwindling crop yields add to the farmer's suffering. Farming communities have created various innovative ways of coping with a warming environment to increase their agriculture resiliency. These include, among others, rain water management, reforestation and agro-forestry. To what extent have these practices been disturbed by the increasing temperatures, and decreasing rainfalls and river discharges in Muooni catchment? This study used statistical forecast techniques to unveil the past, current and future variations of the micro-climate in Muooni catchment, and relevant factors determining farmers' vulnerability to drought. Muooni catchment is warming by 0.8 to 1.2 degrees C in a century as a result of a changing micro-climate. These changes are mainly driven by deforestation due to the high urbanization rate and agricultural practices in Muooni catchment. Centennial rainfall is subsequently plummeting at 30 to 50 mm while discharges are decreasing from 0.01 to 0.05 m(3<bold>)s(</bold>-1), with unmet water demands of 30% to 95% and above. In view of the current trends of the population growth and urbanization in Muooni, agricultural expansion is seriously threatened if no appropriate policy, extension service and science based emergency measures are put in place by the Government of Kenya.
C1 [Luwesi, Cush Ngonzo] IWMI, CGIAR Res Program Water, WLE, PMB CT 112, Cantonments, Accra, Ghana.
   [Obando, Joy Apiyo; Shisanya, Chris Allan] Kenyatta Univ, Dept Geog, POB 43844-00100, Nairobi, Kenya.
C3 CGIAR; International Water Management Institute (IWMI); Kenyatta
   University
RP Luwesi, CN (corresponding author), IWMI, CGIAR Res Program Water, WLE, PMB CT 112, Cantonments, Accra, Ghana.
EM cushngonzo@gmail.com; obandojoy@yahoo.com; chris.shisanya@gmail.com
RI Allan, Chrsitopher/ABE-7816-2020
OI Shisanya, Christopher Allan/0000-0002-2137-0372
FU "International Development Research Centre" (IDRC)-Ottawa, Canada; EU
FX We first acknowledge the valuable contributions of various anonymous
   reviewers and the academic editor of this paper. We are also grateful to
   the "International Development Research Centre" (IDRC)-Ottawa,
   Canada-that provided a grant from which a major part of this research
   was carried out. Information on the centre is available at www.idrc.ca.
   We also acknowledge the financial, material and technical supports
   received from the "Center for International Capacity Development" (CICD)
   of the Universitat Siegen (Germany) through the EU funded Project
   "Capacity Building in Integrated Watershed Management in Eastern Africa
   (IWMNet/EU Project). Their activities can be found at www.iwmnet.eu.
CR Abebe A., 2009, THESIS, V5, P1
   Aeschbacher J, 2005, MT RES DEV, V25, P155, DOI 10.1659/0276-4741(2005)025[0155:RWSIAH]2.0.CO;2
   Akaike H., 1977, P S APPL STAT, P27
   [Anonymous], FARM MANAGEMENT HD C
   [Anonymous], 2007, HUMAN DEV REPORT 200
   [Anonymous], 2010, Human Development Report 2010
   Bohling G., 2005, INTRO GEOSTATISTICS
   Box G.E.P., 1970, J Am Stat Assoc, V65, P1509, DOI DOI 10.1080/01621459.1970.10481180
   DAVIDSON JEH, 1981, J ECONOMETRICS, V16, P295, DOI 10.1016/0304-4076(81)90032-4
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Forch G, 2005, DAAD ALUMNI SUMMER S, V18, P1
   Gonzalez A., 1995, INCORPORATION GEOMOR, P179
   Gregory S., 2003, STAT METHODS GEOGRAP, P1
   Hulme M, 2001, CLIM RES, V17, P145, DOI 10.3354/cr017145
   Kenya National Bureau of Statistics (KNBS), 2010, KEN 2009 POP HOUS CE
   Krumme K., 2006, EFUECOLOGICAL FUNCTI, V5, P17
   Lal R, 1993, CONTROL B, V23, p[26, 43]
   Lal R, 2015, AGRON J, V107, P1526, DOI 10.2134/agronj15.0045
   Lenton R., 2009, INTEGRATED WATER RES
   LJUNG GM, 1978, BIOMETRIKA, V65, P297, DOI 10.2307/2335207
   Luwesi C. N., 2013, THESIS
   Luwesi C. N., 2011, HYDROECONOMIC APPROA, P27
   Luwesi C. N., 2010, HYDROECONOMIC INVENT
   Luwesi C. N., 2012, WARMING GREENINGTHE
   Luwesi C. N., 2015, CLIMATE CHANGE PROPO, V63, p[43, 60]
   Luwesi C. N., 2008, INT C FOR BIOEN CLIM
   Maddala G.S., 2007, Introduction to Econometrics", VThird
   Mathenge J. M., 2014, J AGRIC FOOD APPL SC, V2, p[113, 123]
   Meire P., 2008, EARTH ENV SCI SERIES, VIV
   Meire P, 2008, NATO SCI S SS IV EAR, V80, P1
   Merrey DJ, 2005, REG ENVIRON CHANGE, V5, P197, DOI 10.1007/s10113-004-0088-5
   Mogaka H., 2006, 69 WORLD BANK INT BA
   Molle F., 2008, Water Alternatives, V1, P131
   Mumma A., 2011, Kenya groundwater governance case study
   Musuva P., 2010, THESIS
   Notter B, 2007, J HYDROL, V343, P266, DOI 10.1016/j.jhydrol.2007.06.022
   Pachauri RK, 2004, GLOBAL ENVIRON CHANG, V14, P101, DOI 10.1016/j.gloenvcha.2003.12.004
   Paulot F, 2009, SCIENCE, V325, P730, DOI 10.1126/science.1172910
   Phillips J. G., 2003, DETERMINANTS FORECAS, P111
   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]
   Rodionov S., BRIEF OVERVIEW REGIM
   Scholl MA, 2007, WATER RESOUR RES, V43, DOI 10.1029/2007WR006011
   Shisanya C. A., 2014, ETHIOPIA, p[137, 172]
   Tiffen M., 1994, More people, less erosion: environmental recovery in Kenya
   Tushaar Shah Tushaar Shah, 2006, Economic and Political Weekly, V41, P3413
   Wambua P. P., 2015, COMPETITIVE FARMING, V63, P61
   Waswa P. F., 2006, OPPORTUNITIES CHALLE, V1, P52
   Webster A.L., 1995, Applied statistics of business and economics, V2nd
   Wise T.A., 2012, Resolving the Food Crisis: Assessing Global Policy Reforms Since
   Zorita E, 1999, J CLIMATE, V12, P2474, DOI 10.1175/1520-0442(1999)012<2474:TAMAAS>2.0.CO;2
NR 50
TC 3
Z9 3
U1 1
U2 18
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2077-0472
J9 AGRICULTURE-BASEL
JI Agriculture-Basel
PD MAR
PY 2017
VL 7
IS 3
AR 20
DI 10.3390/agriculture7030020
PG 21
WC Agronomy
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA ER3KA
UT WOS:000398694500005
OA gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Pool, JE
   Braun, DT
   Lack, JB
AF Pool, John E.
   Braun, Dylan T.
   Lack, Justin B.
TI Parallel Evolution of Cold Tolerance within <i>Drosophila
   melanogaster</i>
SO MOLECULAR BIOLOGY AND EVOLUTION
LA English
DT Article
DE Drosophila melanogaster; cold tolerance; parallel evolution; local
   adaptation
ID GENETIC REFERENCE PANEL; INBREEDING DEPRESSION; EUROPEAN ADMIXTURE;
   LOCAL ADAPTATION; GENOMIC ANALYSIS; POPULATION; REVEALS; AFRICAN;
   TRAITS; RESISTANCE
AB Drosophila melanogaster originated in tropical Africa before expanding into strikingly different temperate climates in Eurasia and beyond. Here, we find elevated cold tolerance in three distinct geographic regions: beyond the well-studied non-African case, we show that populations from the highlands of Ethiopia and South Africa have significantly increased cold tolerance as well. We observe greater cold tolerance in outbred versus inbred flies, but only in populations with higher inversion frequencies. Each cold-adapted population shows lower inversion frequencies than a closely-related warm-adapted population, suggesting that inversion frequencies may decrease with altitude in addition to latitude. Using the F-ST-based "Population Branch Excess" statistic (PBE), we found only limited evidence for parallel genetic differentiation at the scale of similar to 4 kb windows, specifically between Ethiopian and South African cold-adapted populations. And yet, when we looked for single nucleotide polymorphisms (SNPs) with codirectional frequency change in two or three cold-adapted populations, strong genomic enrichments were observed from all comparisons. These findings could reflect an important role for selection on standing genetic variation leading to "soft sweeps". One SNP showed sufficient codirectional frequency change in all cold-adapted populations to achieve experiment-wide significance: an intronic variant in the synaptic gene Prosap. Another codirectional outlier SNP, at senseless-2, had a strong association with our cold trait measurements, but in the opposite direction as predicted. More generally, proteins involved in neurotransmission were enriched as potential targets of parallel adaptation. The ability to study cold tolerance evolution in a parallel framework will enhance this classic study system for climate adaptation.
C1 [Pool, John E.; Braun, Dylan T.] Univ Wisconsin, Genet Lab, Madison, WI USA.
   [Lack, Justin B.] Ctr Canc Res, Natl Canc Inst, NIH, Bethesda, MD 20892 USA.
C3 University of Wisconsin System; University of Wisconsin Madison;
   National Institutes of Health (NIH) - USA; NIH National Cancer Institute
   (NCI)
RP Pool, JE (corresponding author), Univ Wisconsin, Genet Lab, Madison, WI USA.
EM jpool@wisc.edu
OI Pool, John/0000-0003-2968-9545
FU National Institutes of Health [R01 GM111797, F32 GM106594]
FX This work was funded by the National Institutes of Health through a
   grant to JEP [R01 GM111797] and a fellowship to JBL [F32 GM106594]. We
   thank Tom Turner and two anonymous reviewers for helpful comments on
   this manuscript.
CR Andersen JL, 2015, FUNCT ECOL, V29, P55, DOI 10.1111/1365-2435.12310
   Ayrinhac A, 2004, FUNCT ECOL, V18, P700, DOI 10.1111/j.0269-8463.2004.00904.x
   Bergland AO, 2016, MOL ECOL, V25, P1157, DOI 10.1111/mec.13455
   Bozicevic V, 2016, MOL ECOL, V25, P1175, DOI 10.1111/mec.13464
   Campbell M, 2012, P NATL ACAD SCI USA, V109, pE648, DOI 10.1073/pnas.1201176109
   Cavalli-Sforza LuigiL., 1969, Proc. 12th Int. Congr. Genet, V2, P405
   COHET Y, 1980, J THERM BIOL, V5, P69, DOI 10.1016/0306-4565(80)90002-9
   Collinge JE, 2006, J EVOLUTION BIOL, V19, P473, DOI 10.1111/j.1420-9101.2005.01016.x
   Comeron JM, 2012, PLOS GENET, V8, DOI 10.1371/journal.pgen.1002905
   Corbett-Detig RB, 2012, GENETICS, V192, P131, DOI 10.1534/genetics.112.141622
   Dahlgaard J, 2000, CONSERV BIOL, V14, P1187, DOI 10.1046/j.1523-1739.2000.99206.x
   Dieringer D, 2005, MOL ECOL, V14, P563, DOI 10.1111/j.1365-294X.2004.02422.x
   Duchen P, 2013, GENETICS, V193, P291, DOI 10.1534/genetics.112.145912
   Durham MF, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms5338
   Hancock AM, 2010, P NATL ACAD SCI USA, V107, P8924, DOI 10.1073/pnas.0914625107
   Hoffmann AA, 2003, J THERM BIOL, V28, P175, DOI 10.1016/S0306-4565(02)00057-8
   INOUE Y, 1992, EVOLUTION, V46, P797, DOI [10.1111/j.1558-5646.1992.tb02085.x, 10.2307/2409647]
   Jafar-Nejad H, 2004, MOL CELL BIOL, V24, P8803, DOI 10.1128/MCB.24.20.8803-8812.2004
   Kao JY, 2015, MOL ECOL, V24, P1499, DOI 10.1111/mec.13137
   Kapun M, 2016, MOL BIOL EVOL, V33, P1317, DOI 10.1093/molbev/msw016
   Kumar S, 2016, MOL BIOL EVOL, V33, P1870, DOI [10.1093/molbev/msw054, 10.1093/molbev/msv279]
   LACHAISE D, 1988, EVOL BIOL, V22, P159
   Lack JL, 2016, MOL BIOL EVOL, DOI [10.1093/mol-bev/msw195, DOI 10.1093/MOL-BEV/MSW195]
   Lack JB, 2016, P NATL ACAD SCI USA, V113, P1014, DOI 10.1073/pnas.1515964113
   Lack JB, 2015, GENETICS, V199, P1229, DOI 10.1534/genetics.115.174664
   Lange JD, 2016, MOL ECOL, V25, P3081, DOI 10.1111/mec.13671
   Langley CH, 2012, GENETICS, V192, P533, DOI 10.1534/genetics.112.142018
   Lee SF, 2013, MOL ECOL, V22, P2716, DOI 10.1111/mec.12301
   Lemeunier Francoise, 1992, P339
   Liebl FLW, 2008, BIOINFORM BIOL INSIG, V2, P369
   Mackay TFC, 2012, NATURE, V482, P173, DOI 10.1038/nature10811
   OHTA T, 1971, GENET RES, V18, P277, DOI 10.1017/S0016672300012684
   Overgaard J, 2011, J THERM BIOL, V36, P409, DOI 10.1016/j.jtherbio.2011.07.005
   Parkash R, 2010, J ZOOL, V280, P49, DOI 10.1111/j.1469-7998.2009.00641.x
   Pennings PS, 2006, PLOS GENET, V2, P1998, DOI 10.1371/journal.pgen.0020186
   Pool JE, 2015, MOL BIOL EVOL, V32, P3236, DOI 10.1093/molbev/msv194
   Pool JE, 2012, PLOS GENET, V8, DOI 10.1371/journal.pgen.1003080
   Reinhardt JA, 2014, GENETICS, V197, P361, DOI 10.1534/genetics.114.161463
   Svetec N, 2011, MOL ECOL, V20, P530, DOI 10.1111/j.1365-294X.2010.04951.x
   Tennessen JA, 2011, PLOS GENET, V7, DOI 10.1371/journal.pgen.1002127
   Thornton K, 2006, GENETICS, V172, P1607, DOI 10.1534/genetics.105.048223
   Turner TL, 2008, GENETICS, V179, P455, DOI 10.1534/genetics.107.083659
   Vermeulen CJ, 2013, J EVOLUTION BIOL, V26, P1890, DOI 10.1111/jeb.12183
   Weber AL, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0034745
   Yassin A, 2016, P NATL ACAD SCI USA, V113, P4771, DOI 10.1073/pnas.1522559113
   Yi X, 2010, SCIENCE, V329, P75, DOI 10.1126/science.1190371
   Zwarts L, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms10115
NR 47
TC 35
Z9 40
U1 0
U2 36
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 FEB
PY 2017
VL 34
IS 2
BP 349
EP 360
DI 10.1093/molbev/msw232
PG 12
WC Biochemistry & Molecular Biology; Evolutionary Biology; Genetics &
   Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Evolutionary Biology; Genetics &
   Heredity
GA EO2FF
UT WOS:000396511300006
PM 27777283
OA Green Submitted, Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Langham, GM
   Schuetz, JG
   Distler, T
   Soykan, CU
   Wilsey, C
AF Langham, Gary M.
   Schuetz, Justin G.
   Distler, Trisha
   Soykan, Candan U.
   Wilsey, Chad
TI Conservation Status of North American Birds in the Face of Future
   Climate Change
SO PLOS ONE
LA English
DT Article
ID RANGE SHIFTS; MODELS
AB Human-induced climate change is increasingly recognized as a fundamental driver of biological processes and patterns. Historic climate change is known to have caused shifts in the geographic ranges of many taxa and future climate change is expected to result in even greater redistributions of species. As a result, predicting the impact of climate change on future patterns of biodiversity will greatly aid conservation planning. Using the North American Breeding Bird Survey and Audubon Christmas Bird Count, two of the most comprehensive continental datasets of vertebrates in the world, and correlative distribution modeling, we assessed geographic range shifts for 588 North American bird species during both the breeding and non-breeding seasons under a range of future emission scenarios (SRES A2, A1B, B2) through the end of the century. Here we show that 314 species (53%) are projected to lose more than half of their current geographic range across three scenarios of climate change through the end of the century. For 126 species, loss occurs without concomitant range expansion; whereas for 188 species, loss is coupled with potential to colonize new replacement range. We found no strong associations between projected climate sensitivities and existing conservation prioritizations. Moreover, species responses were not clearly associated with habitat affinities, migration strategies, or climate change scenarios. Our results demonstrate the need to include climate sensitivity into current conservation planning and to develop adaptive management strategies that accommodate shrinking and shifting geographic ranges. The persistence of many North American birds will depend on their ability to colonize climatically suitable areas outside of current ranges and management actions that target climate adaptation.
C1 [Langham, Gary M.] Natl Audubon Soc, Washington, DC 20036 USA.
   [Schuetz, Justin G.; Distler, Trisha; Soykan, Candan U.; Wilsey, Chad] Natl Audubon Soc, San Francisco, CA USA.
RP Langham, GM (corresponding author), Natl Audubon Soc, Washington, DC 20036 USA.
EM climatescience@audubon.org
OI Langham, Gary/0009-0002-9479-6806; Wilsey, Chad/0000-0002-1448-1445
FU U.S. Fish and Wildlife Service [F11AP00380/912001-9700]
FX This work was supported by the U.S. Fish and Wildlife Service (contract
   #F11AP00380/912001-9700) to GML. The funders had no role in study
   design, data collection and analysis, decision to publish, or
   preparation of the manuscript.
CR [Anonymous], 2010, gbm: Generalized boosted regression models
   [Anonymous], 2003, The Structure and Dynamics of Geographic Ranges
   [Anonymous], 2013, IUCN RED LIST THREAT
   [Anonymous], 2015, Journal of Statistical Software, DOI DOI 10.18637/JSS.V067.I01
   Araújo MB, 2007, TRENDS ECOL EVOL, V22, P42, DOI 10.1016/j.tree.2006.09.010
   Beidleman CA, 2001, COLORADO PARTNERS FL
   Brown JH, 1996, ANNU REV ECOL SYST, V27, P597, DOI 10.1146/annurev.ecolsys.27.1.597
   Case MJ, 2015, BIOL CONSERV, V187, P127, DOI 10.1016/j.biocon.2015.04.013
   Cerovski AM, 2001, WYOMING BIRD CONSERV
   Distler T, 2015, J BIOGEOGR, V42, P976, DOI 10.1111/jbi.12479
   Dormann CF, 2013, ECOGRAPHY, V36, P27, DOI 10.1111/j.1600-0587.2012.07348.x
   Dunn EH, 2005, AUK, V122, P338, DOI 10.1642/0004-8038(2005)122[0338:ETSVOT]2.0.CO;2
   Elith J, 2008, J ANIM ECOL, V77, P802, DOI 10.1111/j.1365-2656.2008.01390.x
   Fink D, 2010, ECOL APPL, V20, P2131, DOI 10.1890/09-1340.1
   Fischlin A, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P211
   Freeman EA, 2008, ECOL MODEL, V217, P48, DOI 10.1016/j.ecolmodel.2008.05.015
   Garson GD., 2012, Variance Components Analysis
   Guisan A, 2005, ECOL LETT, V8, P993, DOI 10.1111/j.1461-0248.2005.00792.x
   Hijmans R. J., GEOGRAPHIC ANAL MODE
   Hijmans R. J., DISMO SPECIES DISTRI
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Lawler JJ, 2009, ECOLOGY, V90, P588, DOI 10.1890/08-0823.1
   Link WA, 2006, CONDOR, V108, P13, DOI 10.1650/0010-5422(2006)108[0013:AHMFRA]2.0.CO;2
   MacKenzie D.I., 2006, Occupancy estimation and modelling, DOI DOI 10.2981/0909-6396(2006)12[450:OEAMIP]2.0.CO;2
   McDonald KW, 2012, ECOL EVOL, V2, P3052, DOI 10.1002/ece3.410
   McKenney DW, 2006, AGR FOREST METEOROL, V138, P69, DOI 10.1016/j.agrformet.2006.03.012
   McKenney DW, 2011, B AM METEOROL SOC, V92, P1611, DOI 10.1175/2011BAMS3132.1
   McLachlan JS, 2007, CONSERV BIOL, V21, P297, DOI 10.1111/j.1523-1739.2007.00676.x
   Nenzén HK, 2011, ECOL MODEL, V222, P3346, DOI 10.1016/j.ecolmodel.2011.07.011
   Oksanen J, 2022, R package version 2.6-2, DOI DOI 10.4135/9781412971874.N145
   Panjabi A.O., 2012, PARTNERS FLIGHT TECH, V3
   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
   Peterson AT, 2009, EPIDEMICS-NETH, V1, P240, DOI 10.1016/j.epidem.2009.11.003
   Peterson AT, 2003, GLOBAL CHANGE BIOL, V9, P647, DOI 10.1046/j.1365-2486.2003.00616.x
   Phillips SJ, 2006, ECOL MODEL, V190, P231, DOI 10.1016/j.ecolmodel.2005.03.026
   ROOT T, 1988, ECOLOGY, V69, P330, DOI 10.2307/1940431
   Rowland EL, 2011, ENVIRON MANAGE, V47, P322, DOI 10.1007/s00267-010-9608-x
   Sauer J.R., 2012, The North American breeding bird survey
   Schneider SH, 2002, CLIMATE CHANGE OVERV
   Schuetz JG, 2015, ECOL APP IN PRESS
   Sekercioglu CH, 2008, CONSERV BIOL, V22, P140, DOI 10.1111/j.1523-1739.2007.00852.x
   Small-Lorenz SL, 2013, NAT CLIM CHANGE, V3, P91, DOI 10.1038/nclimate1810
   Stralberg D, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0006825
   Thomas CD, 2004, NATURE, V427, P145, DOI 10.1038/nature02121
   Tingley MW, 2012, GLOBAL CHANGE BIOL, V18, P3279, DOI 10.1111/j.1365-2486.2012.02784.x
   Tingley MW, 2009, P NATL ACAD SCI USA, V106, P19637, DOI 10.1073/pnas.0901562106
   U.S. Fish and Wildlife Service, 2008, BIRDS CONS CONC 2008
   Warren R, 2013, NAT CLIM CHANGE, V3, P678, DOI [10.1038/nclimate1887, 10.1038/NCLIMATE1887]
   Welsh AH, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0052015
   WIENS JA, 1989, FUNCT ECOL, V3, P385, DOI 10.2307/2389612
   Williams Stephen E, 2008, PLoS Biol, V6, P2621, DOI 10.1371/journal.pbio.0060325
   ,, 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 53
TC 94
Z9 111
U1 1
U2 132
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 SEP 2
PY 2015
VL 10
IS 9
AR e0135350
DI 10.1371/journal.pone.0135350
PG 16
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA CQ4ZT
UT WOS:000360613800029
PM 26333202
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Bisaro, A
   Kirk, M
   Zdruli, P
   Zimmermann, W
AF Bisaro, Alexander
   Kirk, Michael
   Zdruli, Pandi
   Zimmermann, Willi
TI GLOBAL DRIVERS SETTING DESERTIFICATION RESEARCH PRIORITIES: INSIGHTS
   FROM A STAKEHOLDER CONSULTATION FORUM
SO LAND DEGRADATION & DEVELOPMENT
LA English
DT Article
DE land degradation; desertification; biofuels; food crisis; climate
   adaptation; sustainable land management; organic production; food
   sovereignty
ID CARBON SEQUESTRATION; CLIMATE-CHANGE; ENVIRONMENTAL AGREEMENTS;
   SCIENTIFIC-KNOWLEDGE; LAND DEGRADATION; FOOD-PRICES; TRADE-OFFS;
   ADAPTATION; IMPACTS; MANAGEMENT
AB Recent rapid changes in global scale drivers of desertification, land degradation and drought (DLDD) have two important consequences for drylands. First, changes in these drivers, for example in food and energy prices, make improving interventions in drylands more urgent because of their potential impacts. Second, these changes introduce new knowledge gaps regarding both the potential impacts on social-ecological dryland systems and the design of options to take advantage of opportunities. This paper identifies the most salient research needs in DLDD in drylands brought on by global drivers. The question was addressed through an iterative stakeholder consultative forum. First, relevant global scale drivers were identified through a literature review and preliminary consultation. Next, stakeholders and experts were further consulted to identify research priorities given rise to by these drivers. Identified research priorities were as follows: (i) assessing impacts of rising prices on DLDD in mixed market and subsistence production contexts; (ii) assessing options and limits of agricultural modernisation on fragile lands; (iii) developing methods for assessing land-use trade-offs and mapping productive lands; (iv) modelling and participatory methods for monitoring and evaluating soil carbon sequestration; (v) developing policy frameworks to regulate impacts of investment on the environment and local livelihoods; (vi) participatory modelling for regional and local adaptation planning; and (vii) valuation of non-market land degradation outcomes including biodiversity loss. Concluding, we call for a forward-looking interdisciplinary drylands research agenda with an increased emphasis on governance to address these priorities. Copyright (c) 2013 John Wiley & Sons, Ltd.
C1 [Bisaro, Alexander] Global Climate Forum, D-10178 Berlin, Germany.
   [Kirk, Michael] Univ Marburg, Inst Cooperat Developing Countries IKE, D-35032 Marburg, Germany.
   [Zdruli, Pandi] CIHEAM Mediterranean Agron Inst Bari, Land & Water Resources Management Dept, I-70010 Valenzano, BA, Italy.
   [Zimmermann, Willi] Int Dev Specialist Land Policy & Land Management, D-72131 Ofterdingen, Germany.
C3 Philipps University Marburg; CIHEAM; CIHEAM BARI
RP Bisaro, A (corresponding author), Global Climate Forum, Neue Promenade 6, D-10178 Berlin, Germany.
EM sandy.bisaro@globalclimateforum.org
OI Bisaro, Alexander/0000-0003-4281-0012
FU German Federal Ministry of Education and Research (BMBF)
FX Funding for this research was provided by the German Federal Ministry of
   Education and Research (BMBF). We thank Franziska Schuetze and the
   anonymous reviewers of Land Degradation and Development for comments on
   earlier versions of this paper.
CR Achten WMJ, 2010, J ARID ENVIRON, V74, P164, DOI 10.1016/j.jaridenv.2009.08.010
   Adeel Z., 2005, ECOSYSTEMS HUMAN WEL
   Adger WN, 2003, ECON GEOGR, V79, P387
   Agrawal A., 2002, Drama of the commons, P41
   Akhtar-Schuster M, 2000, UNEP DESERT CONTR B, P42
   Anderson S, 2010, NEW FRONT SOC POLICY, P199
   [Anonymous], 2009, 8 UN FAO
   [Anonymous], 2008, World Development Report: Agriculture for Development
   Arndt C, 2008, AGR ECON-BLACKWELL, V39, P497, DOI 10.1111/j.1574-0862.2008.00355.x
   Bisaro A, 2013, ECOLOGY SOC UNPUB
   Borras SM, 2010, J PEASANT STUD, V37, P575, DOI 10.1080/03066150.2010.512448
   Brittaine R., 2010, INTEGRATED CROP MANA, V8, P1
   Cash DW, 2006, ECOL SOC, V11
   Chapagain AK, 2008, WATER INT, V33, P19, DOI 10.1080/02508060801927812
   Clave M, 2010, RAPPORTS DOCUMENTS C
   Cowie A, 2007, ENVIRON SCI POLICY, V10, P335, DOI 10.1016/j.envsci.2007.03.002
   Cudjoe G, 2010, FOOD POLICY, V35, P294, DOI 10.1016/j.foodpol.2010.01.004
   Danielsen F, 2009, CONSERV BIOL, V23, P348, DOI 10.1111/j.1523-1739.2008.01096.x
   Dessai S, 2004, CLIM POLICY, V4, P107
   FAO, 2009, LAND INN LAND RIGHTS, V349
   Farage PK, 2007, SOIL TILL RES, V94, P457, DOI 10.1016/j.still.2006.09.006
   Folke C, 2007, ECOL SOC, V12
   Geist HJ, 2004, BIOSCIENCE, V54, P817, DOI 10.1641/0006-3568(2004)054[0817:DCPOD]2.0.CO;2
   Global Mechanism, 2008, INT FIN STRAT SUST L
   Godfray HCJ, 2010, SCIENCE, V327, P812, DOI 10.1126/science.1185383
   Grainger A, 2009, LAND DEGRAD DEV, V20, P410, DOI 10.1002/ldr.898
   Halberg N., 2006, Global development of organic agriculture: challenges and prospects, P277, DOI 10.1079/9781845930783.0277
   Hazell P, 2001, STRATEGIES SUSTAINAB
   Headey D, 2008, AGR ECON-BLACKWELL, V39, P375, DOI 10.1111/j.1574-0862.2008.00345.x
   Headey D, 2011, FOOD POLICY, V36, P136, DOI 10.1016/j.foodpol.2010.10.003
   Hinkel J, 2013, ENV SCI POLICY UNPUB
   Holling C.S., 1973, Annual Rev Ecol Syst, V4, P1, DOI 10.1146/annurev.es.04.110173.000245
   Ivanic M, 2008, AGR ECON-BLACKWELL, V39, P405, DOI 10.1111/j.1574-0862.2008.00347.x
   Kuhlman T, 2010, LAND USE POLICY, V27, P22, DOI 10.1016/j.landusepol.2008.08.002
   LADA, 2008, DES INT POL IMP LUTT
   Lal R, 2004, ENVIRON MANAGE, V33, P528, DOI 10.1007/s00267-003-9110-9
   Lal R, 2009, LAND DEGRAD DEV, V20, P441, DOI 10.1002/ldr.934
   Lambin EF, 2001, GLOBAL ENVIRON CHANG, V11, P261, DOI [10.1016/S0959-3780(01)00007-3, 10.1146/annurev.energy.28.050302.105459]
   Lehmann J, 2007, NATURE, V447, P143, DOI 10.1038/447143a
   Liniger H, 2007, LAND IS GREENER
   Lipper L, 2010, RANGELAND ECOL MANAG, V63, P155, DOI 10.2111/REM-D-09-00009.1
   McShane TO, 2011, BIOL CONSERV, V144, P966, DOI 10.1016/j.biocon.2010.04.038
   Millard E, 2011, ENVIRON MANAGE, V48, P365, DOI 10.1007/s00267-011-9685-5
   Mortimore M., 2005, TERRITORY SCARCITY E
   MORTIMORE MJ, 1988, GEOGRAPHY, V73, P61
   Moser SC, 2010, P NATL ACAD SCI USA, V107, P22026, DOI 10.1073/pnas.1007887107
   Nkonya E, 2011, LAND DEGRAD DEV, V22, P240, DOI 10.1002/ldr.1048
   Nkonya E., 2008, Linkages between Land Management, Land Degradation and Poverty in Sub-Saharan Africa
   O'Brien KL, 2000, GLOBAL ENVIRON CHANG, V10, P221, DOI 10.1016/S0959-3780(00)00021-2
   Olsson L, 2005, J ARID ENVIRON, V63, P556, DOI 10.1016/j.jaridenv.2005.03.008
   Ostrom E, 2009, SCIENCE, V325, P419, DOI 10.1126/science.1172133
   Palmer C, 2012, LAND USE POLICY, V29, P83, DOI 10.1016/j.landusepol.2011.05.007
   Pan GX, 2009, AGR ECOSYST ENVIRON, V129, P344, DOI 10.1016/j.agee.2008.10.008
   Pender J., 2006, Strategies for sustainable land management in the East African Highlands, P165
   Pender J, 2009, FOOD CRISIS LAND
   Ponce-Hernandez R, 2010, LAND DEGRADATION AND DESERTIFICATION: ASSESSMENT, MITIGATION AND REMEDIATION, P49, DOI 10.1007/978-90-481-8657-0_5
   Reed MS, 2007, LAND DEGRAD DEV, V18, P249, DOI 10.1002/ldr.777
   Reed MS, 2006, ECOL ECON, V59, P406, DOI 10.1016/j.ecolecon.2005.11.008
   Reynolds JF, 2011, LAND DEGRAD DEV, V22, P166, DOI 10.1002/ldr.1104
   Reynolds JF, 2007, SCIENCE, V316, P847, DOI 10.1126/science.1131634
   Ridoutt BG, 2010, GLOBAL ENVIRON CHANG, V20, P113, DOI 10.1016/j.gloenvcha.2009.08.003
   Safriel U, 2008, SUSTAIN SCI, V3, P117, DOI 10.1007/s11625-007-0038-5
   Safriel U, 2009, LAND DEGRAD DEV, V20, P353, DOI 10.1002/ldr.935
   Seely M, 2008, GLOBAL PLANET CHANGE, V64, P236, DOI 10.1016/j.gloplacha.2008.07.006
   Shiferaw Bekele A., 2009, Environment Development and Sustainability, V11, P601, DOI 10.1007/s10668-007-9132-1
   Sivakumar MVK, 2007, AGR FOREST METEOROL, V142, P143, DOI 10.1016/j.agrformet.2006.03.025
   Smith MS, 2008, RANGELAND J, V30, P3, DOI 10.1071/RJ07063
   Smith P, 2007, AR4 CLIMATE CHANGE 2007: MITIGATION OF CLIMATE CHANGE, P497
   Stringer LC, 2007, LAND DEGRAD DEV, V18, P99, DOI 10.1002/ldr.760
   Stringer LC, 2012, ENVIRON SCI POLICY, V19-20, P121, DOI 10.1016/j.envsci.2012.02.004
   Stringer LC, 2009, ENVIRON SCI POLICY, V12, P748, DOI 10.1016/j.envsci.2009.04.002
   Thomas RJ, 2008, FUTURE OF DRYLANDS, P631
   Thornton PK, 2009, AGR SYST, V101, P113, DOI 10.1016/j.agsy.2009.05.002
   Tiffen M., 2002, Agroecological innovations: increasing food production with participatory development, P71
   Tilman D, 2011, P NATL ACAD SCI USA, V108, P20260, DOI 10.1073/pnas.1116437108
   Tompkins E. L., 2004, Ecology and Society, V9, P10
   Turner BL, 2007, P NATL ACAD SCI USA, V104, P20666, DOI 10.1073/pnas.0704119104
   UNCCD, 1994, UN CONV COMB DES THO
   Vermeulen S, 2010, J PEASANT STUD, V37, P899, DOI 10.1080/03066150.2010.512463
   Wodon Q, 2010, WORLD BANK RES OBSER, V25, P157, DOI 10.1093/wbro/lkp018
   World Bank, 2010, EC EV CLIM CHANG AD
   Wright BD, 2011, APPL ECON PERSPECT P, V33, P32, DOI 10.1093/aepp/ppq033
   Xu DY, 2010, J ARID ENVIRON, V74, P498, DOI 10.1016/j.jaridenv.2009.09.030
   Zhang F, 2011, PROD OP MAN SOC POMS
   ,, 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 85
TC 58
Z9 58
U1 3
U2 83
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 JAN
PY 2014
VL 25
IS 1
SI SI
BP 5
EP 16
DI 10.1002/ldr.2220
PG 12
WC Environmental Sciences; Soil Science
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Agriculture
GA AA6QW
UT WOS:000331224000002
DA 2025-01-10
ER

PT J
AU Norgate, M
   Chamings, J
   Pavlova, A
   Bull, JK
   Murray, ND
   Sunnucks, P
AF Norgate, Melanie
   Chamings, Jay
   Pavlova, Alexandra
   Bull, James K.
   Murray, Neil D.
   Sunnucks, Paul
TI Mitochondrial DNA Indicates Late Pleistocene Divergence of Populations
   of <i>Heteronympha merope</i>, an Emerging Model in Environmental Change
   Biology
SO PLOS ONE
LA English
DT Article
ID CLIMATE-CHANGE; MOLECULAR PHYLOGENY; RANGE EXPANSION; LEPIDOPTERA;
   MUTATION; BUTTERFLIES; EVOLUTION; PHYLOGEOGRAPHY; BIOGEOGRAPHY;
   SEQUENCES
AB Knowledge of historical changes in species range distribution provides context for investigating adaptive potential and dispersal ability. This is valuable for predicting the potential impact of environmental change on species of interest. Butterflies are one of the most important taxa for studying such impacts, and Heteronympha merope has the potential to provide a particularly valuable model, in part due to the existence of historical data on morphological traits and glycolytic enzyme variation. This study investigates the population genetic structure and phylogeography of H. merope, comparing the relative resolution achieved through partial DNA sequences of two mitochondrial loci, COI and ND5. These data are used to define the relationship between subspecies, showing that the subspecies are reciprocally monophyletic. On this basis, the Western Australian subspecies H. m. duboulayi is genetically distinct from the two eastern subspecies. Throughout the eastern part of the range, levels of migration and the timing of key population splits of potential relevance to climatic adaptation are estimated and indicate Late Pleistocene divergence both of the Tasmanian subspecies and of an isolated northern population from the eastern mainland subspecies H. m. merope. This information is then used to revisit historical data and provides support for the importance of clinal variation in wing characters, as well as evidence for selective pressure acting on allozyme loci phosphoglucose isomerase and phosphoglucomutase in H. merope. The study has thus confirmed the value of H. merope as a model organism for measuring responses to environmental change, offering the opportunity to focus on isolated populations, as well as a latitudinal gradient, and to use historical changes to test the accuracy of predictions for the future.
C1 [Norgate, Melanie; Chamings, Jay; Pavlova, Alexandra; Bull, James K.; Sunnucks, Paul] Monash Univ, Sch Biol Sci, Clayton, Vic, Australia.
   [Norgate, Melanie; Chamings, Jay; Pavlova, Alexandra; Bull, James K.; Sunnucks, Paul] Monash Univ, Australian Ctr Biodivers, Clayton, Vic, Australia.
   [Murray, Neil D.] La Trobe Univ, Dept Genet, Bundoora, Vic, Australia.
C3 Monash University; Monash University; La Trobe University
RP Norgate, M (corresponding author), Monash Univ, Sch Biol Sci, Clayton, Vic, Australia.
EM paul.sunnucks@sci.monash.edu.au
RI Pavlova, Alexandra/H-4749-2014
OI Pavlova, Alexandra/0000-0001-9455-4124; Sunnucks,
   Paul/0000-0002-8139-7059; Bull, James/0000-0002-0274-4359
FU Australian Research Council [DP0772837]; Australian Research Council
   [DP0772837] Funding Source: Australian Research Council
FX This work was supported by Australian Research Council grant DP0772837
   (http://www.arc.gov.au/). The funders had no role in study design, data
   collection and analysis, decision to publish, or preparation of the
   manuscript.
CR Albre J, 2008, MOL PHYLOGENET EVOL, V47, P196, DOI 10.1016/j.ympev.2008.01.009
   Ballard JWO, 2004, MOL ECOL, V13, P729, DOI 10.1046/j.1365-294X.2003.02063.x
   Ballard JWO, 2000, J MOL EVOL, V51, P64, DOI 10.1007/s002390010067
   Bandelt HJ, 1999, MOL BIOL EVOL, V16, P37, DOI 10.1093/oxfordjournals.molbev.a026036
   Beaumont LJ, 2005, ECOL MODEL, V186, P250, DOI 10.1016/j.ecolmodel.2005.01.030
   Braby M.F., 2000, Butterflies of Australia: their identification, biology and distribution, DOI [10.1071/9780643100770, DOI 10.1071/9780643100770]
   Braby MF, 2007, SYST ENTOMOL, V32, P2, DOI 10.1111/j.1365-3113.2006.00349.x
   Broughton RE, 2006, MOL BIOL EVOL, V23, P1516, DOI 10.1093/molbev/msl013
   Crozier L, 2004, ECOLOGY, V85, P231, DOI 10.1890/02-0607
   Dowling DK, 2008, TRENDS ECOL EVOL, V23, P546, DOI 10.1016/j.tree.2008.05.011
   EXCOFFIER L, 1992, GENETICS, V131, P479
   Excoffier L, 2005, EVOL BIOINFORM, V1, P47, DOI 10.1177/117693430500100003
   Frankham R, 1997, HEREDITY, V78, P311, DOI 10.1038/hdy.1997.46
   Fu YX, 1997, GENETICS, V147, P915
   Garrick RC, 2004, MOL ECOL, V13, P3329, DOI 10.1111/j.1365-294X.2004.02340.x
   GU HN, 1991, BIOCHEM GENET, V29, P345, DOI 10.1007/BF00554142
   Haag-Liautard C, 2008, PLOS BIOL, V6, P1706, DOI 10.1371/journal.pbio.0060204
   Hey J, 2007, P NATL ACAD SCI USA, V104, P2785, DOI 10.1073/pnas.0611164104
   Hughes L, 2000, TRENDS ECOL EVOL, V15, P56, DOI 10.1016/S0169-5347(99)01764-4
   Karl I, 2008, FUNCT ECOL, V22, P887, DOI 10.1111/j.1365-2435.2008.01438.x
   Kato Y, 2004, SYST ENTOMOL, V29, P1, DOI 10.1111/j.1365-3113.2004.00238.x
   Kearney M, 2009, ECOL LETT, V12, P334, DOI 10.1111/j.1461-0248.2008.01277.x
   Kearney M, 2009, FUNCT ECOL, V23, P528, DOI 10.1111/j.1365-2435.2008.01538.x
   Keith DA, 2008, BIOL LETTERS, V4, P560, DOI 10.1098/rsbl.2008.0049
   Lenormand T, 2002, TRENDS ECOL EVOL, V17, P183, DOI 10.1016/S0169-5347(02)02497-7
   Li W., 1997, MOL EVOLUTION
   Lunt DH, 1996, INSECT MOL BIOL, V5, P153, DOI 10.1111/j.1365-2583.1996.tb00049.x
   Marden JH, 2000, ANNU REV PHYSIOL, V62, P157, DOI 10.1146/annurev.physiol.62.1.157
   MCDONALD JH, 1991, NATURE, V351, P652, DOI 10.1038/351652a0
   McLaughlin JF, 2002, P NATL ACAD SCI USA, V99, P6070, DOI 10.1073/pnas.052131199
   Meiklejohn CD, 2007, TRENDS GENET, V23, P259, DOI 10.1016/j.tig.2007.03.008
   MILLER SA, 1988, NUCLEIC ACIDS RES, V16, P1215, DOI 10.1093/nar/16.3.1215
   Mitikka V, 2008, BIODIVERS CONSERV, V17, P623, DOI 10.1007/s10531-007-9287-y
   Morin X, 2008, BIOL LETTERS, V4, P573, DOI 10.1098/rsbl.2008.0181
   Narita S, 2007, GENETICA, V131, P241, DOI 10.1007/s10709-006-9134-1
   Nazari V, 2007, MOL PHYLOGENET EVOL, V42, P131, DOI 10.1016/j.ympev.2006.06.022
   Nei M., 2000, Molecular evolution and phylogenetics
   Ounap E, 2009, AUST J ENTOMOL, V48, P113, DOI 10.1111/j.1440-6055.2009.00695.x
   Parmesan C, 2003, NATURE, V421, P37, DOI 10.1038/nature01286
   Parmesan C, 1999, NATURE, V399, P579, DOI 10.1038/21181
   Parmesan C, 2006, ANNU REV ECOL EVOL S, V37, P637, DOI 10.1146/annurev.ecolsys.37.091305.110100
   PEARSE FK, 1982, EVOLUTION, V36, P1251, DOI 10.1111/j.1558-5646.1982.tb05494.x
   PEARSE FK, 1981, AUST J ZOOL, V29, P631
   PEARSE FK, 1978, GEOGRAPHIC VARIATION
   Quek SP, 2004, EVOLUTION, V58, P554, DOI 10.1111/j.0014-3820.2004.tb01678.x
   Rand DM, 1998, GENETICA, V102-3, P393, DOI 10.1023/A:1017006118852
   Rozas J, 2003, BIOINFORMATICS, V19, P2496, DOI 10.1093/bioinformatics/btg359
   Saastamoinen M, 2008, AM NAT, V171, pE701, DOI 10.1086/587531
   Schneider S, 1999, GENETICS, V152, P1079
   Scriber JM, 2002, ECOGRAPHY, V25, P184, DOI 10.1034/j.1600-0587.2002.250206.x
   SIMON C, 1994, ANN ENTOMOL SOC AM, V87, P651, DOI 10.1093/aesa/87.6.651
   Simonato M, 2007, MOL ECOL, V16, P2273, DOI 10.1111/j.1365-294X.2007.03302.x
   Sunnucks P, 1996, MOL BIOL EVOL, V13, P510, DOI 10.1093/oxfordjournals.molbev.a025612
   Sunnucks P, 2000, MOL ECOL, V9, P1699, DOI 10.1046/j.1365-294x.2000.01084.x
   TAJIMA F, 1989, GENETICS, V123, P585
   Tamura K, 2007, MOL BIOL EVOL, V24, P1596, DOI 10.1093/molbev/msm092
   Thomas I, 1996, J BIOGEOGR, V23, P717, DOI 10.1111/j.1365-2699.1996.tb00032.x
   Thomas JA, 2005, PHILOS T R SOC B, V360, P339, DOI 10.1098/rstb.2004.1585
   THOMPSON JD, 1994, NUCLEIC ACIDS RES, V22, P4673, DOI 10.1093/nar/22.22.4673
   Ward PI, 2004, MOL ECOL, V13, P3213, DOI 10.1111/j.1365-294X.2004.02293.x
   Watt WB, 1996, MOL BIOL EVOL, V13, P699, DOI 10.1093/oxfordjournals.molbev.a025631
   Yagi T, 2001, GENES GENET SYST, V76, P229, DOI 10.1266/ggs.76.229
   Yagi T, 1999, J MOL EVOL, V48, P42, DOI 10.1007/PL00006443
NR 63
TC 28
Z9 32
U1 0
U2 14
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 24
PY 2009
VL 4
IS 11
AR e7950
DI 10.1371/journal.pone.0007950
PG 13
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA 533MH
UT WOS:000272827500002
PM 19956696
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Tiwari, V
   Tulbure, MG
   Caineta, J
   Gaines, MD
   Perin, V
   Kamal, M
   Krupnik, TJ
   Aziz, MA
   Islam, AFMT
AF Tiwari, Varun
   Tulbure, Mirela G.
   Caineta, Julio
   Gaines, Mollie D.
   Perin, Vinicius
   Kamal, Mustafa
   Krupnik, Timothy J.
   Aziz, Md Abdullah
   Islam, A. F. M. Tariqul
TI Automated in-season rice crop mapping using Sentinel time-series data
   and Google Earth Engine: A case study in climate-risk prone Bangladesh
SO JOURNAL OF ENVIRONMENTAL MANAGEMENT
LA English
DT Article
DE Synthetic aperture radar; Random forest; Multi-otsu; Boro rice;
   Flooding; In-season maps
ID BORO RICE; PADDY RICE; MODIS-NDVI; AREA; SAR; INTENSIFICATION; IMPACTS;
   EXTENT
AB High-resolution mapping of rice fields is crucial for understanding and managing rice cultivation in countries like Bangladesh, particularly in the face of climate change. Rice is a vital crop, cultivated in small scale farms that contributes significantly to the economy and food security in Bangladesh. Accurate mapping can facilitate improved rice production, the development of sustainable agricultural management policies, and formulation of strategies for adapting to climatic risks.To address the need for timely and accurate rice mapping, we developed a framework specifically designed for the diverse environmental conditions in Bangladesh. We utilized Sentinel-1 and Sentinel-2 time-series data to identify transplantation and peak seasons and employed the multi-Otsu automatic thresholding approach to map rice during the peak season (April-May). We also compared the performance of a random forest (RF) classifier with the multi-Otsu approach using two different data combinations: D1, which utilizes data from the transplantation and peak seasons (D1 RF) and D2, which utilizes data from the transplantation to the harvest seasons (D2 RF).Our results demonstrated that the multi-Otsu approach achieved an overall classification accuracy (OCA) ranging from 61.18% to 94.43% across all crop zones. The D2 RF showed the highest mean OCA (92.15%) among the fourteen crop zones, followed by D1 RF (89.47%) and multi-Otsu (85.27%). Although the multi-Otsu approach had relatively lower OCA, it proved effective in accurately mapping rice areas prior to harvest, eliminating the need for training samples that can be challenging to obtain during the growing season.In-season rice area maps generated through this framework are crucial for timely decision-making regarding adaptive management in response to climatic stresses and forecasting area-wide productivity. The scalability of our framework across space and time makes it particularly suitable for addressing field data scarcity challenges in countries like Bangladesh and offers the potential for future operationalization.
C1 [Tiwari, Varun; Tulbure, Mirela G.; Caineta, Julio; Gaines, Mollie D.; Perin, Vinicius] North Carolina State Univ NCSU, Ctr Geospatial Analyt, Raleigh, NC 27695 USA.
   [Kamal, Mustafa; Krupnik, Timothy J.] Int Maize & Wheat Improvement Ctr CIMMYT, Dhaka, Bangladesh.
   [Aziz, Md Abdullah] Bangladesh Rice Res Inst BRRI, Dhaka, Bangladesh.
   [Islam, A. F. M. Tariqul] Bangladesh Agr Res Council BARC, Dhaka, Bangladesh.
C3 North Carolina State University; CGIAR; International Maize & Wheat
   Improvement Center (CIMMYT); Bangladesh Rice Research Institute (BRRI)
RP Tiwari, V (corresponding author), North Carolina State Univ NCSU, Ctr Geospatial Analyt, Raleigh, NC 27695 USA.
EM vtiwari@ncsu.edu
RI Krupnik, Timothy/J-6363-2019; Perin, Vinicius/ABI-7518-2020; Tiwari,
   Varun/KBQ-2274-2024; Tulbure, Mirela G/B-3030-2012
OI Tulbure, Mirela G/0000-0003-1456-183X; Aziz, Md.
   Abdullah/0000-0003-1662-6430; Islam, Dr. AFM
   Tariqul/0000-0001-6160-6274; Gaines, Mollie/0000-0001-9166-8150
FU Bill and Melinda Gates Foundation; USAID through the Cereal Systems
   Initiative for South Asia (CSISA); CGIAR Regional Integrated Initiative
   for Transforming Agrifood Systems in South Asia (TAFSSA)
FX <STRONG> </STRONG>The authors acknowledge the Department of Agricultural
   Extension (DAE) and CIMMYT staff who were involved in the collection of
   field data (sample points) and NASA for providing high-resolution
   Planet-Scope images under the NASA Small Satellite Data program. The
   authors would also like to acknowledge the graduate school writing
   center at North Carolina State University for improving the quality of
   the paper. This work was partially supported by the Bill and Melinda
   Gates Foundation and USAID through the Cereal Systems Initiative for
   South Asia (CSISA; https://csisa.org/), and the CGIAR Regional
   Integrated Initiative for Transforming Agrifood Systems in South Asia
   (TAFSSA;
   https://www.cgiar.org/initiative/20-transforming-agrifood-systems-in-sou
   th-asia-tafssa/). Accordingly, we would like to thank all funders who
   supported this research through their contributions to the CGIAR Trust
   Fund (https://www.cgiar.org/funders/). The views and opinions in this
   document are those of the authors and do not necessarily reflect those
   of the Gates Foundation, USAID, or CGIAR, and shall not be used for
   advertising purposes.
CR Acharjee TK, 2019, AGR SYST, V168, P131, DOI 10.1016/j.agsy.2018.11.006
   Ahmed MR, 2017, SENSORS-BASEL, V17, DOI 10.3390/s17102347
   Alam MS, 2019, INT GEOSCI REMOTE SE, P7330, DOI [10.1109/igarss.2019.8899084, 10.1109/IGARSS.2019.8899084]
   Ali MZ, 2018, EGYPT J REMOTE SENS, V21, pS29, DOI 10.1016/j.ejrs.2018.03.003
   Amani M, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12213561
   Amarnath G., 2017, Mapping multiple climate-related hazards in South Asia (No. 170; IWMI Research Report), DOI DOI 10.5337/2017.207
   Angmo R., 2019, Int. J. Curr. Microbiol. Appl. Sci, V8, P257, DOI [DOI 10.20546/IJCMAS.2019.801.238, 10.20546/ijcmas.2019.801.238, 10.20546/ijcmas.2019.802.031]
   [Anonymous], 2015, Adv. Rem. Sens, DOI DOI 10.4236/ARS.2015.44026
   [Anonymous], 2012, Second National Communication of Bangladesh to the United Nations Framework on Climate Change
   Anusha N, 2020, EGYPT J REMOTE SENS, V23, P207, DOI 10.1016/j.ejrs.2019.01.001
   Asada H., 2005, GEOGRAPHICAL REV JAP, V78, P783, DOI DOI 10.4157/GRJ.78.783
   Aziz MA, 2023, APPL GEOMAT, V15, P407, DOI 10.1007/s12518-023-00501-2
   Baraha S, 2022, J VIS COMMUN IMAGE R, V86, DOI 10.1016/j.jvcir.2022.103546
   Belgiu M, 2016, ISPRS J PHOTOGRAMM, V114, P24, DOI 10.1016/j.isprsjprs.2016.01.011
   Blickensdörfer L, 2022, REMOTE SENS ENVIRON, V269, DOI 10.1016/j.rse.2021.112831
   Brunner MI, 2021, WIRES WATER, V8, DOI 10.1002/wat2.1520
   Carrasco L, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11030288
   Chang L, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13010103
   Choi YW, 2021, CLIM DYNAM, V57, P3055, DOI 10.1007/s00382-021-05856-z
   Chowhan Sushan, 2019, J. Exp. Agric. Int., P1, DOI [10.9734/jeai/2019/v41i630436, DOI 10.9734/JEAI/2019/V41I630436]
   d'Andrimont R, 2021, REMOTE SENS ENVIRON, V266, DOI 10.1016/j.rse.2021.112708
   D'Odorico P, 2014, EARTHS FUTURE, V2, P458, DOI 10.1002/2014EF000250
   De Groote H, 2005, AGR SYST, V84, P21, DOI 10.1016/j.agsy.2004.06.008
   Dhar P, 2020, NAT MACH INTELL, V2, P423, DOI 10.1038/s42256-020-0219-9
   Duarte D, 2023, LAND-BASEL, V12, DOI 10.3390/land12020490
   Nguyen DB, 2016, REMOTE SENS LETT, V7, P1209, DOI 10.1080/2150704X.2016.1225172
   Faisal BMR, 2019, AGRIENGINEERING, V1, P356, DOI 10.3390/agriengineering1030027
   Farr TG, 2007, REV GEOPHYS, V45, DOI 10.1029/2005RG000183
   Felegari S, 2021, APPL SCI-BASEL, V11, DOI 10.3390/app112110104
   Fendrich AN, 2023, SCI TOTAL ENVIRON, V873, DOI 10.1016/j.scitotenv.2023.162300
   Food and Agriculture Organization (FAO), 2022, FAOSTAT
   Gella GW, 2021, ISPRS J PHOTOGRAMM, V175, P171, DOI 10.1016/j.isprsjprs.2021.03.004
   Giri Ananto, 2019, Sixth Geoinformation Science Symposium,, V38, DOI [10.1117/12.2549036, DOI 10.1117/12.2549036]
   Gorelick N, 2017, REMOTE SENS ENVIRON, V202, P18, DOI 10.1016/j.rse.2017.06.031
   Grenier M., 2008, ACCURACY ASSESSMENT METHOD FOR WETLAND OBJECT-BASED CLASSIFICATION, V6
   Gumma MK, 2014, ISPRS J PHOTOGRAMM, V91, P98, DOI 10.1016/j.isprsjprs.2014.02.007
   Gumma MK, 2011, J APPL REMOTE SENS, V5, DOI 10.1117/1.3619838
   Hao PY, 2020, SCI TOTAL ENVIRON, V733, DOI 10.1016/j.scitotenv.2020.138869
   Hasan E., 2013, Water Science, V27, P69, DOI [10.1016/J.WSJ.2013.12.007, DOI 10.1016/J.WSJ.2013.12.007]
   Holecz Francesco, 2022, Remote Sensing of Agriculture and Land Cover/Land Use Changes in South and Southeast Asian Countries, V105
   Hossain B, 2020, PROG DISASTER SCI, V6, DOI 10.1016/j.pdisas.2020.100079
   Hossain Mohammed Sadid, 2021, Dhaka University Journal of Biological Sciences, V30, P125, DOI 10.3329/dujbs.v30i1.51816
   Huang J, 2014, IEEE J-STARS, V7, P4374, DOI 10.1109/JSTARS.2014.2334332
   Huang WL, 2018, REMOTE SENS-BASEL, V10, DOI 10.3390/rs10050797
   Huq Saleemul, 2007, Climate Change Impacts and Responses in Bangladesh, P20
   Islam Delwarul, 2017, Aquatic Weeds Diversity of Bangladesh
   Islam MA, 2021, LAND USE POLICY, V101, DOI 10.1016/j.landusepol.2020.105159
   Islam MM, 2022, ASIA-PAC J REG SCI, V6, P47, DOI 10.1007/s41685-021-00220-9
   Islam Rahedul, 2021, Irrigated Rice Area Mapping over Bangladesh with Remotely Sensed Data from 2001 to 2018, V213, P10
   Jiang Q, 2023, REMOTE SENS-BASEL, V15, DOI 10.3390/rs15112794
   Jinao Yu, 2020, 2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), P2189, DOI 10.1109/ITAIC49862.2020.9339053
   Kabir M.S., 2020, Bang. Rice J., V24, P1, DOI [10.3329/BRJ.V24I2.53447, DOI 10.3329/BRJ.V24I2.53447]
   Kamal M, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12223688
   Karim MF, 2008, GLOBAL ENVIRON CHANG, V18, P490, DOI 10.1016/j.gloenvcha.2008.05.002
   Konduri VS, 2020, REMOTE SENS ENVIRON, V251, DOI 10.1016/j.rse.2020.112048
   Krupnik TJ, 2017, LAND USE POLICY, V60, P206, DOI 10.1016/j.landusepol.2016.10.001
   Liu YJ, 2022, AGR SYST, V195, DOI 10.1016/j.agsy.2021.103306
   Luo C, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13040561
   Mahboob M.G., 2016, P AS FLUX MIN REM SE, P2
   Mainuddin M, 2020, AGR WATER MANAGE, V240, DOI 10.1016/j.agwat.2020.106294
   Menze BH, 2009, BMC BIOINFORMATICS, V10, DOI 10.1186/1471-2105-10-213
   Miah MD, 2020, BANGLADESHS EC SOCIA, P237, DOI [10.1007/978-981-15-1683-2_8/COVER, DOI 10.1007/978-981-15-1683-2_8]
   More R, 2013, J INDIAN SOC REMOTE, V41, P597, DOI 10.1007/s12524-012-0228-1
   Mosleh MK, 2015, SENSORS-BASEL, V15, P769, DOI 10.3390/s150100769
   Mukul Sharif A., 2021, Invasive Alien Species, P1, DOI [10.1002/9781119607045.ch13, DOI 10.1002/9781119607045.CH13]
   Mullissa A, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13101954
   Musa ZN, 2015, HYDROL EARTH SYST SC, V19, P3755, DOI 10.5194/hess-19-3755-2015
   Muthayya S, 2014, ANN NY ACAD SCI, V1324, P7, DOI 10.1111/nyas.12540
   Nahar Mst Ashrafun, 2016, The Impact of Climate Change in Bangladesh on the Rice Market and Farm Households, V75
   Nayak S, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14095156
   Nelson A, 2014, LAND APPLICATIONS OF RADAR REMOTE SENSING, P121, DOI 10.5772/57443
   Nicholls R J., 2018, Ecosystem Services for Well-Being in Deltas, pE1, DOI DOI 10.1007/978-3-319-71093-8_30
   Nicolau A.P., 2021, ISPRS Open J. Photogramm. Remote Sens, V2, P100005, DOI [DOI 10.1016/J.OPHOTO.2021.100005, 10.1016/j.ophoto.2021.100005]
   Nowakowski A, 2021, INT J APPL EARTH OBS, V98, DOI 10.1016/j.jag.2021.102313
   Palash MS, 2017, OPEN AGRIC, V2, P175, DOI 10.1515/opag-2017-0018
   Pan ZK, 2015, INT J APPL EARTH OBS, V34, P188, DOI 10.1016/j.jag.2014.08.011
   Papademetriou M.K., 2000, Rice production in the Asia-Pacific region: issues and perspectives. Bridging the rice yield gap in the Asia-Pacific region
   Peña-Arancibia JL, 2021, REMOTE SENS APPL, V21, DOI 10.1016/j.rsase.2020.100460
   Perin V, 2022, REMOTE SENS ENVIRON, V270, DOI 10.1016/j.rse.2021.112796
   Planet Imagery Product Specifications, 2022, About us
   Qin YW, 2015, ISPRS J PHOTOGRAMM, V105, P220, DOI 10.1016/j.isprsjprs.2015.04.008
   Rahman M. Wakilur, 2009, Journal of Water Resource and Protection, V1, P216, DOI 10.4236/jwarp.2009.13027
   Rahman MM, 2014, 2014 ANNUAL GLOBAL ONLINE CONFERENCE ON INFORMATION AND COMPUTER TECHNOLOGY, P1, DOI 10.1109/GOCICT.2014.9
   Rahman Zubaidur, 2014, Role of Agriculture in Economic Growth of Bangladesh: A VAR Approach, V24
   Rana VK, 2019, REMOTE SENS APPL, V16, DOI 10.1016/j.rsase.2019.100271
   Rashid M, 2018, Bangladesh Rice J, V21, DOI [10.3329/brj.v21i1.37360, DOI 10.3329/BRJ.V21I1.37360]
   Saha MK, 2022, J ENVIRON MANAGE, V310, DOI 10.1016/j.jenvman.2022.114755
   Sapkota TB, 2021, SCI TOTAL ENVIRON, V786, DOI 10.1016/j.scitotenv.2021.147344
   Satapathy SC, 2018, NEURAL COMPUT APPL, V29, P1285, DOI 10.1007/s00521-016-2645-5
   Sayeed Ahmed, 2017, Rice Prices and Growth, and Poverty Reduction in Bangladesh, P45
   Shahed Mustafa Shahed Mustafa, 2015, International Journal of Climate Change: Impacts and Responses, V7, P1
   Shamsudduha M, 2020, EXPOS HEALTH, V12, P657, DOI 10.1007/s12403-019-00325-9
   Shamsuzzoha Md, 2022, Agricultural Information Research, V31, P32, DOI 10.3173/air.31.32
   Shew AM, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11101235
   Shew AM, 2019, ENVIRON SCI POLICY, V95, P46, DOI 10.1016/j.envsci.2019.02.004
   Singha M, 2019, SCI DATA, V6, DOI 10.1038/s41597-019-0036-3
   Sourav Md Abdullah All, 2017, Impact of Flash Flood on Boro Rice Production in Taherpur Upazila
   Stroppiana D, 2019, EUR J REMOTE SENS, V52, P206, DOI 10.1080/22797254.2019.1581583
   Vo TBT, 2018, SOIL SCI PLANT NUTR, V64, P47, DOI 10.1080/00380768.2017.1413926
   Thorp KR, 2021, REMOTE SENS ENVIRON, V265, DOI 10.1016/j.rse.2021.112679
   Tian JQ, 2021, IEEE J-STARS, V14, P10500, DOI 10.1109/JSTARS.2021.3120013
   Tiwari V, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0237324
   Tiwari Varun, 2021, Earth Observation Science and Applications for Risk Reduction and Enhanced Resilience in Hindu Kush Himalaya Region, P79, DOI [10.1007/978-3-030-73569-2_5, DOI 10.1007/978-3-030-73569-2_5]
   Tran KH, 2022, INT J APPL EARTH OBS, V107, DOI 10.1016/j.jag.2022.102692
   Uddin K, 2021, PROG DISASTER SCI, V11, DOI 10.1016/j.pdisas.2021.100185
   Uddin K, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11131581
   Waldner F, 2016, INT J REMOTE SENS, V37, P3196, DOI 10.1080/01431161.2016.1194545
   Waleed M, 2022, SCI REP-UK, V12, DOI 10.1038/s41598-022-17454-y
   Xiao W, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13050990
   Xiao XM, 2006, REMOTE SENS ENVIRON, V100, P95, DOI 10.1016/j.rse.2005.10.004
   Xie L, 2015, IEEE J-STARS, V8, P3812, DOI 10.1109/JSTARS.2014.2387214
   Xu XM, 2020, REG ENVIRON CHANGE, V20, DOI 10.1007/s10113-020-01650-5
   Yin Z, 2020, J ADV MODEL EARTH SY, V12, DOI 10.1029/2019MS001770
   Young LJ, 2022, STATS-BASEL, V5, P881, DOI 10.3390/stats5030051
   Zanaga Daniele, 2021, Zenodo, DOI 10.5281/ZENODO.5571935
   Zeigler RS, 2008, RICE, V1, P3, DOI 10.1007/s12284-008-9001-z
   Zhan P, 2021, REMOTE SENS ENVIRON, V252, DOI 10.1016/j.rse.2020.112112
   Zhao RK, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13020503
NR 118
TC 9
Z9 9
U1 4
U2 10
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
PY 2024
VL 351
AR 119615
DI 10.1016/j.jenvman.2023.119615
EA DEC 2023
PG 16
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA EI4U1
UT WOS:001138289800001
PM 38091728
OA hybrid
DA 2025-01-10
ER

PT J
AU Hlatini, VA
   Ncobela, CN
   Chimonyo, M
AF Hlatini, V. A.
   Ncobela, C. N.
   Chimonyo, M.
TI Influence of reduced dietary protein level on quality of pork carcasses
   in Windsnyer pigs
SO SOUTH AFRICAN JOURNAL OF ANIMAL SCIENCE
LA English
DT Article
DE back fat; dressing percentage; ham diameter; kidney weight; ideal
   protein level
ID GROWTH-PERFORMANCE; FINISHING PIGS; MEAT QUALITY; DETERGENT FIBER;
   VARYING LEVELS; LARGE WHITE; TRAITS; ENERGY; NITROGEN; MUSCLE
AB To promote the sustainable production of local pigs, their dietary protein requirements need to be determined. Meat production from these pigs when fed on appropriate diets, coupled with their adaptability to climatic extremes and disease and parasite challenges, could be of huge benefit to the pork industry. The objective of the study was to determine the carcass traits, primary pork cuts, and internal organ weights of pigs fed decreasing dietary protein levels. Thirty, slow-growing, Windsnyer male pigs were randomly allocated to six dietary treatments in a complete randomized design. There were five replications for each of the six treatments. Dietary crude protein levels in the six experimental diets were 193, 174, 154, 135, 116, and 97 g/kg, respectively. The diets were formulated to contain similar net energy levels of similar to 9.5 MJ/kg. Lysine, methionine, threonine, and tryptophan levels were the same for all diets. A two week adaptation was followed by an 8w feeding phase. At slaughter, pigs had an average weight of similar to 39.13 +/- 0.85 kg. Pigs were humanely slaughtered at the end of feeding period to determine carcass characteristics, primary pork cuts, and internal organ size. A negative linear relationship was observed between protein levels and cooler shrink. There was a positive linear relationship between protein level and dressing percentage, cooler shrink, and shoulder fat. There was a quadratic relationship between dietary protein level and shoulder fat, ham diameter, P2(3) backfat depth, and kidney weight. The thickness of dorsal fat at the last rib, the thickness of back fat, and the width of back fat at P2(2) increased linearly as protein level decreased. The reduction in dietary protein level had an influence on carcass traits, primal pork cuts, and internal organs in slow-growing Windsnyer pigs. A reduction in dietary protein level below 116 g/kg compromised ham diameter, P2(3) width of back fat thickness, shoulder fat, and kidney weight.
C1 [Hlatini, V. A.; Ncobela, C. N.] Agr Res Council, Anim Prod Inst, Nutr Bldg,Private Bag X2, ZA-0062 Irene, South Africa.
   [Chimonyo, M.] Univ Venda, Fac Sci Engn & Agr, Anim Sci, P Bag X5050, ZA-0950 Thohoyandou, Limpopo, South Africa.
C3 Agricultural Research Council of South Africa; Animal Production
   Research Institute, Agricultural Research Council; University of Venda
RP Chimonyo, M (corresponding author), Univ Venda, Fac Sci Engn & Agr, Anim Sci, P Bag X5050, ZA-0950 Thohoyandou, Limpopo, South Africa.
EM Michael.chimonyo@univen.ac.za
FU National Research Foundation; UKZN competitive [P530];  [102702]
FX The authors thank the UKZN competitive grant (P530) and National
   Research Foundation for funding this research (grant number; 102702) .
CR Abdou N, 2011, ANIM FEED SCI TECH, V169, P176, DOI 10.1016/j.anifeedsci.2011.07.002
   Ahamefule F. O., 2006, Pakistan Journal of Nutrition, V5, P248
   Alonso V, 2010, MEAT SCI, V85, P7, DOI 10.1016/j.meatsci.2009.11.015
   [Anonymous], 2008, SAS Users Guide: Statistics
   AOAC, 2016, Official Methods of Analysis of the AOAC
   Apple JK, 2017, J ANIM SCI, V95, P4971, DOI 10.2527/jas2017.1818
   CASTELL AG, 1994, CAN J ANIM SCI, V74, P519, DOI 10.4141/cjas94-073
   Halimani TE, 2012, TROP ANIM HEALTH PRO, V45, P81, DOI 10.1007/s11250-012-0177-2
   Hlatini VA, 2020, S AFR J ANIM SCI, V50, P643, DOI 10.4314/sajas.v50i5.1
   Hoffman LC., 2005, S AFR SOC ANIM SCI, V6, P25
   Hong J. S., 2016, Journal of Animal Science and Technology, V58, P37, DOI [10.1186/s40781-016-0119-z, 10.1186/s40781-016-0118-0]
   Kanengoni AT, 2014, J ANIM SCI, V92, P5739, DOI 10.2527/jas.2014-8067
   Kanengoni AT, 2004, ANIM SCI, V78, P61, DOI 10.1017/S1357729800053844
   Monteiro ANTR, 2017, LIVEST SCI, V198, P162, DOI 10.1016/j.livsci.2017.02.014
   National Research Council, 2012, Nutrient requirements of swine, V11
   Ncobela CN, 2018, S AFR J ANIM SCI, V48, P770, DOI 10.4314/sajas.v48i4.19
   Needham T, 2015, J ANIM SCI, V93, P4545, DOI 10.2527/jas.2015-9183
   Noblet J, 2001, ANIM RES, V50, P227, DOI 10.1051/animres:2001129
   Norgaard JV, 2014, ACTA AGR SCAND A-AN, V64, P123, DOI 10.1080/09064702.2014.943280
   Peres LM, 2014, REV BRAS ZOOTECN, V43, P369, DOI 10.1590/S1516-35982014000700005
   Pham KT, 2010, ASIAN AUSTRAL J ANIM, V23, P1034, DOI 10.5713/ajas.2010.90530
   Ruusunen M, 2007, LIVEST SCI, V107, P170, DOI 10.1016/j.livsci.2006.09.021
   Schweihofer J.P., 2011, CARCASS DRESSING PER
   Teye GA, 2006, MEAT SCI, V73, P157, DOI 10.1016/j.meatsci.2005.11.010
   VANSOEST PJ, 1973, J ASSOC OFF ANA CHEM, V56, P781
   VANSOEST PJ, 1991, J DAIRY SCI, V74, P3583, DOI 10.3168/jds.S0022-0302(91)78551-2
   Whittemore CT, 2001, ANIM SCI, V73, P3, DOI 10.1017/S1357729800058008
   Whittemore EC, 2003, ANIM SCI, V76, P89, DOI 10.1017/S1357729800053352
   Wood JD, 2004, MEAT SCI, V67, P651, DOI 10.1016/j.meatsci.2004.01.007
   YOUNG LG, 1968, CAN J ANIM SCI, V48, P71, DOI 10.4141/cjas68-010
   Zhang JH, 2007, J APPL GENET, V48, P363, DOI 10.1007/BF03195233
   Zhang JX, 2008, ASIAN AUSTRAL J ANIM, V21, P1785, DOI 10.5713/ajas.2008.80191
NR 32
TC 0
Z9 0
U1 0
U2 1
PU SOUTH AFRICAN JOURNAL OF ANIMAL SCIENCES
PI HATFIELD
PA C/O ESTIE KOSTER, PO BOX 13884, HATFIELD 0028, SOUTH AFRICA
SN 0375-1589
EI 2221-4062
J9 S AFR J ANIM SCI
JI South Afr. J. Anim. Sci.
PY 2022
VL 52
IS 6
BP 731
EP 742
DI 10.4314/sajas.v52i6.01
PG 12
WC Agriculture, Dairy & Animal Science
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA O4FZ4
UT WOS:001043402700001
OA gold
DA 2025-01-10
ER

PT J
AU Nowell, HK
   Holmes, CD
   Robertson, K
   Teske, C
   Hiers, JK
AF Nowell, H. K.
   Holmes, C. D.
   Robertson, K.
   Teske, C.
   Hiers, J. K.
TI A New Picture of Fire Extent, Variability, and Drought Interaction in
   Prescribed Fire Landscapes: Insights From Florida Government Records
SO GEOPHYSICAL RESEARCH LETTERS
LA English
DT Article
DE prescribed fire; wildfire; biomass burning; climate; remote sensing
ID UNITED-STATES; BURNED AREA; PARTICULATE MATTER; CLIMATE-CHANGE;
   FOREST-FIRES; AIR-QUALITY; WILDFIRE; EMISSIONS; CARBON; SAVANNA
AB Florida, United States, government records provide a new resource for studying fire in landscapes managed with prescribed fire. In Florida, most fire area (92%) is prescribed. Current satellite fire products, which underpin most air pollution emission inventories, detect only 25% of burned area, which alters airborne emissions and environmental impacts. Moreover, these satellite products can misdiagnose spatiotemporal variability of fires. Overall fire area in Florida decreases during drought conditions as prescribed fires are avoided, but satellite data do not reflect this pattern. This pattern is consistent with prescribed fire successfully reducing overall fire risk and damages. Human management of prescribed fires and fuels can, therefore, break the conventional link between drought and wildfire and play an important role in mitigating rising fire risk in a changing climate. These results likely apply in other regions of the world with similar fire regimes.
   Plain Language Summary Wildfires and prescribed (i.e., controlled) fires are major sources of air pollution, greenhouse gases, and aerosols. Accurately estimating emissions from fires is critical to understanding their impacts on the environment and for designing sound fire management policies. We show that for Florida, United States, current satellites-the primary tools for identifying the extent, location, and time of these fires-dramatically underestimate the amount of fire, poorly identify its variation in space and time and can mischaracterize its relationship to drought. Using government records of fires, where available, can overcome some satellite shortcomings and provide a more accurate picture of fire extent and variability. In Florida, these records show that land area consumed by fire decreases during drought conditions due to less prescribed burning, but this pattern is not detected by satellites. Similar results may be expected in other parts of the world with similar fire characteristics, including agricultural and savanna regions of South America, Africa, Europe, and Asia. Using prescribed fire can help land managers adapt to climate-driven changes in wildfire activity.
C1 [Nowell, H. K.; Holmes, C. D.] Florida State Univ, Dept Earth Ocean & Atmospher Sci, Tallahassee, FL 32306 USA.
   [Robertson, K.; Teske, C.; Hiers, J. K.] Tall Timbers Res Stn & Land Conservancy, Tallahassee, FL USA.
C3 State University System of Florida; Florida State University
RP Nowell, HK (corresponding author), Florida State Univ, Dept Earth Ocean & Atmospher Sci, Tallahassee, FL 32306 USA.
EM hak07@my.fsu.edu
RI Robertson, Kevin/AAT-9357-2021; Nowell, Holly/JXL-4811-2024; Holmes,
   Christopher/C-9956-2014
OI Nowell, Holly/0000-0001-7291-7887; Holmes,
   Christopher/0000-0002-2727-0954
FU NASA Atmospheric Composition Modeling and Analysis Program [NNX17AF60G]
FX This study was supported by the NASA Atmospheric Composition Modeling
   and Analysis Program under grant NNX17AF60G. We thank Scott Taylor and
   Bryan Williams of the FFS for the OBA and KBDI data. PDSI and SPI data
   for Florida were obtained from NESDIS/NCDC legacy servers
   (https://www7.ncdc.noaa.gov/CDO/CDODivisionalSelect.jsp). GFED, BAECV,
   MTBS, and HMS data locations are given in the references. TTRS and DoD
   data are available upon request from Kevin Hiers
   (jkhiers@talltimbers.org).
CR Abatzoglou JT, 2016, P NATL ACAD SCI USA, V113, P11770, DOI 10.1073/pnas.1607171113
   Abatzoglou JT, 2013, INT J WILDLAND FIRE, V22, P1003, DOI 10.1071/WF13019
   Addington RN, 2015, INT J WILDLAND FIRE, V24, P778, DOI 10.1071/WF14187
   Al-Saadi J, 2008, J APPL REMOTE SENS, V2, DOI 10.1117/1.2948785
   Amiro BD, 2001, CAN J FOREST RES, V31, P512, DOI 10.1139/cjfr-31-3-512
   Anderson LO, 2015, GLOBAL BIOGEOCHEM CY, V29, P1739, DOI 10.1002/2014GB005008
   [Anonymous], 2017, NAT CLIM CHANGE, V7, P755, DOI 10.1038/nclimate3432
   [Anonymous], 2016, 2014 NAT EM INV VERS
   [Anonymous], P 5 S FIR FOR MET OR
   [Anonymous], FIR INF STAT
   [Anonymous], NWCG SMOKE MANAGEMEN
   [Anonymous], MON TRENDS BURN SEV
   [Anonymous], 2011 NAT EM INV VERS
   [Anonymous], 1993, 8 C APPL CLIMATOLOGY
   [Anonymous], TECHN SUPP DOC PREP
   [Anonymous], GLOBAL FIRE EMISSION
   [Anonymous], AIR EM MOD 2014 VERS
   [Anonymous], TECHN SUPP DOC PREP
   [Anonymous], J GEOPHYS RES
   [Anonymous], 15 INT EM INV C REIN
   [Anonymous], EUR J WILDLIFE RES
   [Anonymous], 2015 NATL PRESCRIBED
   [Anonymous], 34 INT S REM SENS EN
   [Anonymous], 2017, SCI REP-UK, DOI DOI 10.1038/s41598-017-03739-0
   Aragao LEOC, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-017-02771-y
   Balch JK, 2017, P NATL ACAD SCI USA, V114, P2946, DOI 10.1073/pnas.1617394114
   Balch JK, 2015, BIOSCIENCE, V65, P893, DOI 10.1093/biosci/biv106
   Bond TC, 2013, J GEOPHYS RES-ATMOS, V118, P5380, DOI 10.1002/jgrd.50171
   Boschetti L, 2006, IEEE T GEOSCI REMOTE, V44, P1765, DOI 10.1109/TGRS.2006.874039
   Brey SJ, 2018, ATMOS CHEM PHYS, V18, P1745, DOI 10.5194/acp-18-1745-2018
   Cardoso MF, 2005, REMOTE SENS ENVIRON, V96, P212, DOI 10.1016/j.rse.2005.02.008
   Coetsee C, 2010, OECOLOGIA, V162, P1027, DOI 10.1007/s00442-009-1490-y
   Duncan BN, 2003, J GEOPHYS RES-ATMOS, V108, DOI 10.1029/2002JD002378
   Dwyer E, 2000, INT J REMOTE SENS, V21, P1289, DOI 10.1080/014311600210182
   Eidenshink J. C., 2007, Fire Ecology, V3, P3, DOI [10.4996/fireecology.0301003, DOI 10.4996/FIREECOLOGY.0301003]
   Engle DM, 2001, J RANGE MANAGE, V54, P2, DOI 10.2307/4003519
   Fernandes PM, 2003, INT J WILDLAND FIRE, V12, P117, DOI 10.1071/WF02042
   Giglio L, 2003, REMOTE SENS ENVIRON, V87, P273, DOI 10.1016/S0034-4257(03)00184-6
   Giglio L, 2009, REMOTE SENS ENVIRON, V113, P408, DOI 10.1016/j.rse.2008.10.006
   Giglio L, 2007, REMOTE SENS ENVIRON, V108, P407, DOI 10.1016/j.rse.2006.11.018
   Giglio L, 2013, J GEOPHYS RES-BIOGEO, V118, P317, DOI 10.1002/jgrg.20042
   Harris WN, 2007, ACTA OECOL, V32, P207, DOI 10.1016/j.actao.2007.05.001
   Hawbaker TJ, 2008, REMOTE SENS ENVIRON, V112, P2656, DOI 10.1016/j.rse.2007.12.008
   Hawbaker TJ, 2017, REMOTE SENS ENVIRON, V198, P504, DOI 10.1016/j.rse.2017.06.027
   Heddinghaus T. R., 1991, P 7 C APPL CLIM CIT, P242
   Hu XF, 2016, J GEOPHYS RES-ATMOS, V121, P2901, DOI 10.1002/2015JD024448
   Kasischke ES, 2002, INT J WILDLAND FIRE, V11, P131, DOI 10.1071/WF02023
   Kaulfus AS, 2017, ENVIRON SCI TECHNOL, V51, P11731, DOI 10.1021/acs.est.7b03292
   Keetch JJ., 1968, DROUGHT INDEX FOREST, Vvol 38
   Korontzi S, 2006, GLOBAL BIOGEOCHEM CY, V20, DOI 10.1029/2005GB002529
   Laris PS, 2005, REMOTE SENS ENVIRON, V99, P412, DOI 10.1016/j.rse.2005.09.012
   Larkin NK, 2014, FOREST ECOL MANAG, V317, P61, DOI 10.1016/j.foreco.2013.09.012
   Liu YQ, 2013, FOREST ECOL MANAG, V294, P120, DOI 10.1016/j.foreco.2012.06.049
   Marques S, 2011, EUR J FOREST RES, V130, P775, DOI 10.1007/s10342-010-0470-4
   McCarty JL, 2009, SCI TOTAL ENVIRON, V407, P5701, DOI 10.1016/j.scitotenv.2009.07.009
   Mistry J, 1998, PROG PHYS GEOG, V22, P425, DOI 10.1177/030913339802200401
   Palmer W.C., 1965, Meterological Drought
   Parisien MA, 2006, INT J WILDLAND FIRE, V15, P361, DOI 10.1071/WF06009
   Park RJ, 2007, ATMOS ENVIRON, V41, P7389, DOI 10.1016/j.atmosenv.2007.05.061
   Picotte JJ, 2011, REMOTE SENS-BASEL, V3, P1680, DOI 10.3390/rs3081680
   Pouliot G, 2017, J AIR WASTE MANAGE, V67, P613, DOI 10.1080/10962247.2016.1268982
   Prestemon JP, 2016, INT J WILDLAND FIRE, V25, P715, DOI 10.1071/WF15124
   Prestemon JP, 2010, FOREST SCI, V56, P181
   Price OF, 2012, INT J WILDLAND FIRE, V21, P297, DOI 10.1071/WF10079
   Price OF, 2010, INT J WILDLAND FIRE, V19, P35, DOI 10.1071/WF08167
   Prichard SJ, 2017, FOREST ECOL MANAG, V396, P217, DOI 10.1016/j.foreco.2017.03.035
   Randerson JT, 2012, J GEOPHYS RES-BIOGEO, V117, DOI 10.1029/2012JG002128
   Ruminski M., 2006, P 15 INT EM INV C, V15, P18
   Savadogo P, 2007, AGR ECOSYST ENVIRON, V118, P80, DOI 10.1016/j.agee.2006.05.002
   Schichtel BA, 2017, ENVIRON SCI TECHNOL, V51, P9846, DOI 10.1021/acs.est.7b00645
   Schroeder W, 2016, REMOTE SENS ENVIRON, V185, P210, DOI 10.1016/j.rse.2015.08.032
   Schultz MG, 2008, GLOBAL BIOGEOCHEM CY, V22, DOI 10.1029/2007GB003031
   Schweizer D, 2017, J ENVIRON MANAGE, V201, P345, DOI 10.1016/j.jenvman.2017.07.004
   Short KC, 2014, EARTH SYST SCI DATA, V6, P1, DOI 10.5194/essd-6-1-2014
   Soja AJ, 2009, J APPL REMOTE SENS, V3, DOI 10.1117/1.3148859
   Stephens SL, 2013, SCIENCE, V342, P41, DOI 10.1126/science.1240294
   Tosca MG, 2010, ATMOS CHEM PHYS, V10, P3515, DOI 10.5194/acp-10-3515-2010
   van der Werf GR, 2010, ATMOS CHEM PHYS, V10, P11707, DOI 10.5194/acp-10-11707-2010
   van der Werf GR, 2004, SCIENCE, V303, P73, DOI 10.1126/science.1090753
   van der Werf GR, 2017, EARTH SYST SCI DATA, V9, P697, DOI 10.5194/essd-9-697-2017
   Vicente-Serrano SM, 2010, J CLIMATE, V23, P1696, DOI 10.1175/2009JCLI2909.1
   Westerling AL, 2006, SCIENCE, V313, P940, DOI 10.1126/science.1128834
   Westerling AL, 2003, B AM METEOROL SOC, V84, P595, DOI 10.1175/BAMS-84-5-595
   Wiedinmyer C., 2011, GEOSCI MODEL DEV, V4, P625, DOI [10.5194/gmd-4-625-2011, DOI 10.5194/gmd-4-625-2011]
   Yokelson RJ, 2011, ATMOS CHEM PHYS, V11, P6787, DOI 10.5194/acp-11-6787-2011
   Zeng T, 2008, ENVIRON SCI TECHNOL, V42, P8401, DOI 10.1021/es800363d
NR 86
TC 42
Z9 50
U1 3
U2 34
PU AMER GEOPHYSICAL UNION
PI WASHINGTON
PA 2000 FLORIDA AVE NW, WASHINGTON, DC 20009 USA
SN 0094-8276
EI 1944-8007
J9 GEOPHYS RES LETT
JI Geophys. Res. Lett.
PD AUG 16
PY 2018
VL 45
IS 15
BP 7874
EP 7884
DI 10.1029/2018GL078679
PG 11
WC Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology
GA GR9XA
UT WOS:000443129500072
PM 31031448
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Molina, JT
   Arantes, CC
   Murry, BA
   Veselka, WI
   Anderson, JT
AF Molina, Joseph T.
   Arantes, Caroline C.
   Murry, Brent A.
   Veselka, Walter, IV
   Anderson, James T.
TI Integrating aquatic species, assemblage, and habitat climate change
   vulnerabilities into a watershed-scale decision support framework
SO ECOLOGICAL INDICATORS
LA English
DT Article
DE Climate change; Crayfish; Decision-support tool; Fish; Freshwater
   vulnerability; Watershed
ID LAND-USE; IMPACTS; CONSERVATION; WETLANDS; AREAS; FISH
AB Climate change is increasingly recognized as a serious threat to ecological systems, particularly freshwater systems. As a result, climate adaptation planning is more common in natural resource management. Because conservation resources are limited, decision support tools can help managers prioritize actions. We created the Species and Habitat-based Ecological Decision Support tool (wtrSHEDS) for conservation managers by integrating two distinct indices: one biologically based on aquatic watershed-scale species assemblages and the other a habitat climate change vulnerability index. To do this, we evaluated 60 crayfish and fish species in West Virginia, USA, using the NatureServe Climate Change Vulnerability Index under an A1B emissions scenario. The species vulnerability assessment results indicated that most species we assessed are vulnerable to climate change. Four species of fish and two species of crayfish had extremely high vulnerability due to their dependence on a specific hydrological cycle, sensitivity to barriers, and reproductive dependence on a thermal niche. Aggregating species at the watershed scale (8-digit hydrological unit code [HUC]) using an adapted weighted sum indicated which assemblages were the most and least vulnerable to climate change. Secondly, we created a unique habitat vulnerability index using the established Northeast Association of Fish and Wildlife Agencies habitat vulnerability index and an index of land cover vulnerability from the Forecast Scenario model's land cover change projections under the A1B emissions scenario to incorporate potential synergistic impacts of land use. Land cover projections were reclassified based on the assumption that developed land would have a higher potential to interact with climate change than forested lands synergistically. We combined the two habitat indices at the watershed scale (HUC 8) and performed a Hot Spot Analysis to 1) combine the assemblage and habitat vulnerability indices and 2) identify watersheds of conservation priority. This assessment methodology illustrates a means of identifying priority conservation areas in West Virginia that utilize pre-existing data, can be modified to suit management needs, and, therefore, one that managers across regions can readily apply to their system.
C1 [Molina, Joseph T.; Arantes, Caroline C.; Murry, Brent A.; Veselka, Walter, IV] West Virginia Univ, Sch Nat Resources, 1145 Evansdale Dr, Morgantown, WV 26506 USA.
   [Anderson, James T.] Clemson Univ, Belle W Baruch Inst Coastal Ecol & Forest Sci, James C Kennedy Waterfowl & Wetlands Conservat Ctr, Georgetown 29440, SC USA.
C3 West Virginia University; Clemson University
RP Molina, JT (corresponding author), West Virginia Univ, Sch Nat Resources, 1145 Evansdale Dr, Morgantown, WV 26506 USA.
EM Joseph.t.molina@wv.gov
RI Molina, Joseph/GZG-4512-2022
FU West Virginia Natural Heritage Program; West Virginia Water Research
   Institute [G21AP10620_WV, WRI-299]; USDA National Institute of Food and
   Agriculture McIntire Stennis Program [1026124, 1026001]; West Virginia
   University Research and Scholarship Advancement Grant Program [2814]
FX We thank Dr. Mack Frantz and the West Virginia Natural Heritage Program,
   as well as Jeff Bailey and Jason Morgan and the West Virginia Department
   of Environmental Protection for data access. We also thank Dr. Michael
   Strager for his assistance with spatial data acquisition. We thank
   Elizabeth Byers for her support and guidance at the start of this
   project. We also thank Ayla Bayne and Matthew Bane for their technical
   assistance during this research. Funding was provided by the West
   Virginia Water Research Institute (award number G21AP10620_WV, sub-award
   number WRI-299) , the USDA National Institute of Food and Agriculture
   McIntire Stennis Program (grant numbers 1026124 and 1026001) , and the
   West Virginia University Research and Scholarship Advancement Grant
   Program (grant number 2814) .
CR Albert JS, 2021, AMBIO, V50, P85, DOI 10.1007/s13280-020-01318-8
   [Anonymous], 2010, NOAA national centers for environmental. Information
   Bagne K., 2012, Grasslands
   Barbarossa V, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-21655-w
   BEAULAC MN, 1982, WATER RESOUR BULL, V18, P1013
   Becker G.C., 1983, FISHES WISCONSIN, P1052
   Bell S.S., 2018, THESIS VIRGINIA TECH
   Birk S, 2020, NAT ECOL EVOL, V4, P1060, DOI 10.1038/s41559-020-1216-4
   Bowser J, 2022, FISHES-BASEL, V7, DOI 10.3390/fishes7050263
   BRAAT L, 1991, ENV MANAG, V1, P57
   Burakowski EA, 2016, J CLIMATE, V29, P5141, DOI 10.1175/JCLI-D-15-0286.1
   Burkett V, 2000, J AM WATER RESOUR AS, V36, P313, DOI 10.1111/j.1752-1688.2000.tb04270.x
   Bush A, 2012, FRESHWATER BIOL, V57, P1689, DOI 10.1111/j.1365-2427.2012.02835.x
   Byers E., 2011, Climate change vulnerability assessment of species of concern in West Virginia
   Cea L, 2022, HYDROLOGY-BASEL, V9, DOI 10.3390/hydrology9030050
   Clark KE, 2006, WILDLIFE SOC B, V34, P419, DOI 10.2193/0091-7648(2006)34[419:AOMOSS]2.0.CO;2
   Cuba N, 2022, ENVIRON RES COMMUN, V4, DOI 10.1088/2515-7620/ac82de
   Dale VH, 1997, ECOL APPL, V7, P753, DOI 10.1890/1051-0761(1997)007[0753:TRBLUC]2.0.CO;2
   Executive Order, 2021, Federal Register, V86, P14008
   Farrell JM, 2010, HYDROBIOLOGIA, V647, P127, DOI 10.1007/s10750-009-0035-z
   Fernandez R, 2019, J APPL METEOROL CLIM, V58, P1079, DOI 10.1175/JAMC-D-18-0093.1
   Flebbe PA, 2006, T AM FISH SOC, V135, P1371, DOI 10.1577/T05-217.1
   Foden WB, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0065427
   Foley JA, 2005, SCIENCE, V309, P570, DOI 10.1126/science.1111772
   Fremling C.R., 1980, Atlas of North American Freshwater Fishes
   FRINK CR, 1991, J ENVIRON QUAL, V20, P717, DOI 10.2134/jeq1991.00472425002000040002x
   Furniss M.J., 2013, General Technical Report-Pacific Northwest Research Station
   Gallardo B, 2013, BIOL CONSERV, V160, P225, DOI 10.1016/j.biocon.2013.02.001
   Girvetz EH, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0008320
   Häder DP, 2019, SCI TOTAL ENVIRON, V682, P239, DOI 10.1016/j.scitotenv.2019.05.024
   Hebb A., 2007, CFCAS Project Report, VXI, P1
   Hossain MA, 2018, DIVERS DISTRIB, V24, P1830, DOI 10.1111/ddi.12831
   Jelinski DE, 1996, LANDSCAPE ECOL, V11, P129, DOI 10.1007/BF02447512
   Jezerinac R.F., 1995, Ohio Biol. Surv. Bull NS, P10
   Kaushal SS, 2010, FRONT ECOL ENVIRON, V8, P461, DOI 10.1890/090037
   Lankford AJ, 2014, WILDLIFE SOC B, V38, P386, DOI 10.1002/wsb.399
   Leal W, 2019, J CLEAN PROD, V232, P285, DOI 10.1016/j.jclepro.2019.05.309
   Lituma C. M., 2021, Appalachias coal-mined landscapes, P135, DOI [10.1007/978-3-030-57780-36, DOI 10.1007/978-3-030-57780-3_6]
   Lynch AJ, 2016, FISHERIES, V41, P346, DOI 10.1080/03632415.2016.1186016
   Mann ME, 2008, P NATL ACAD SCI USA, V105, P13252, DOI 10.1073/pnas.0805721105
   Manomet Center for Conservation Sciences and National Wildlife Federation, 2013, A report to the Northeastern Association of Fish and Wildlife Agencies and the North Atlantic Landscape Conservation Cooperative
   Medail F, 1997, ANN MO BOT GARD, V84, P112, DOI 10.2307/2399957
   Molina J.T., 2023, Thesis
   Morelli TL, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0159909
   Murry BA, 2020, FISHERIES MANAG ECOL, V27, P77, DOI 10.1111/fme.12392
   Myers BJE, 2017, REV FISH BIOL FISHER, V27, P339, DOI 10.1007/s11160-017-9476-z
   Nel JL, 2007, DIVERS DISTRIB, V13, P341, DOI 10.1111/j.1472-4642.2007.00308.x
   Nelitz M., 2013, Tools for climate change vulnerability assessments for watersheds
   Nicholson E, 2019, TRENDS ECOL EVOL, V34, P57, DOI 10.1016/j.tree.2018.10.006
   NOAA National Centers for Environmental Information (NCEI), MONTHL NAT CLIM REP
   Pebesma E, 2018, R J, V10, P439
   Pelling M., 2007, Cyberseminar on Population and Natural Hazards
   Pitchford JL, 2012, WETLANDS, V32, P21, DOI 10.1007/s13157-011-0259-3
   Poff N., 2002, Aquatic ecosystems and global climate change, P1
   Poplar-Jeffers IO, 2009, RESTOR ECOL, V17, P404, DOI 10.1111/j.1526-100X.2008.00396.x
   PRIEGEL GR, 1967, T AM FISH SOC, V96, P218, DOI 10.1577/1548-8659(1967)96[218:FOTFDA]2.0.CO;2
   Radinger J, 2017, GLOBAL CHANGE BIOL, V23, P4970, DOI 10.1111/gcb.13760
   Roessig JM, 2004, REV FISH BIOL FISHER, V14, P251, DOI 10.1007/s11160-004-6749-0
   Rosenzweig C., 2005, GLOBAL ENV CHANGE PA, V6, P51, DOI [10.1016/j.hazards.2004.12.001, DOI 10.1016/J.HAZARDS.2004.12.001]
   Seaber P.R., 1987, HYDROLOGIC UNIT MAPS, DOI 10.3133/wsp2294
   Shasteen D., 2007, Lampetra aepyptera, in the Shawnee National Forest
   Stephenson StevenL., 2013, A Natural History of the Central Appalachians
   Still SM, 2015, NAT AREA J, V35, P106, DOI 10.3375/043.035.0115
   Taylor J.R., 1990, ECOL PROCESS, P13
   Trenberth KE, 2018, J ENERGY NAT RESO LA, V36, P463, DOI 10.1080/02646811.2018.1450895
   Tuberville TD, 2015, ENVIRON MANAGE, V56, P822, DOI 10.1007/s00267-015-0537-6
   Vaz-Canosa P, 2023, ENVIRON CONSERV, V50, P12, DOI 10.1017/S0376892922000418
   Wamsler C, 2013, J CLEAN PROD, V50, P68, DOI 10.1016/j.jclepro.2012.12.008
   West JM, 2009, ENVIRON MANAGE, V44, P1001, DOI 10.1007/s00267-009-9345-1
   Whitney JE, 2016, FISHERIES, V41, P332, DOI 10.1080/03632415.2016.1186656
   Wickham JD, 2007, LANDSCAPE ECOL, V22, P179, DOI 10.1007/s10980-006-9040-z
   Wong D., 2009, The SAGE Handbook of Spatial Analysis. Ed. by, DOI DOI 10.4135/9780857020130.N7
   Young B.E., 2016, NatureServe
   Young BruceE., 2012, Wildlife Conservat. Chang. Climate, P129, DOI 10.1002/9781119943440.ch8
NR 74
TC 0
Z9 0
U1 7
U2 7
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 1470-160X
EI 1872-7034
J9 ECOL INDIC
JI Ecol. Indic.
PD SEP
PY 2024
VL 166
AR 112523
DI 10.1016/j.ecolind.2024.112523
EA AUG 2024
PG 13
WC Biodiversity Conservation; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA E3A9U
UT WOS:001301771700001
OA gold
DA 2025-01-10
ER

PT J
AU Vandergast, AG
   Kus, BE
   Wood, DA
   Milano, ER
   Preston, KL
AF Vandergast, Amy G.
   Kus, Barbara E.
   Wood, Dustin A.
   Milano, Elizabeth R.
   Preston, Kristine L.
TI Subspecies differentiation and range-wide genetic structure are driven
   by climate in the California gnatcatcher, a flagship species for coastal
   sage scrub conservation
SO EVOLUTIONARY APPLICATIONS
LA English
DT Article
DE demographic history; gene-environment associations; habitat
   fragmentation; Polioptila californica; RADseq; SNPs
ID EFFECTIVE POPULATION-SIZE; LINKAGE DISEQUILIBRIUM; DNA; DIVERSITY;
   UNITS; SEQUENCES; TAXONOMY; GENOMICS; MUTATION; PACKAGE
AB Understanding genetic structure and diversity within species can uncover associations with environmental and geographic attributes that highlight adaptive potential and inform conservation and management. The California gnatcatcher, Polioptila californica, is a small songbird found in desert and coastal scrub habitats from the southern end of Baja California Sur to Ventura County, California. Lack of congruence among morphological subspecies hypotheses and lack of measurable genetic structure found in a few genetic markers led to questions about the validity of subspecies within P. californica and the listing status of the coastal California gnatcatcher, P. c. californica. As a U.S. federally threatened subspecies, P. c. californica is recognized as a flagship for coastal sage scrub conservation throughout southern California. We used restriction site-associated DNA sequencing to develop a genomic dataset for the California gnatcatcher. We sampled throughout the species' range, examined genetic structure, gene-environment associations, and demographic history, and tested for concordance between genetic structure and morphological subspecies groups. Our data support two distinct genetic groups with evidence of restricted movement and gene flow near the U.S.- Mexico international border. We found that climate-associated outlier loci were more strongly differentiated than climate neutral loci, suggesting that local climate adaptation may have helped to drive differentiation after Holocene range expansions. Patterns of habitat loss and fragmentation are also concordant with genetic substructure throughout the southern California portion of the range. Finally, our genetic data supported the morphologically defined P. c. californica as a distinct group, but there was little evidence of genetic differentiation among other previously hypothesized subspecies in Baja California. Our data suggest that retaining and restoring connectivity, and protecting populations, particularly at the northern range edge, could help preserve existing adaptive potential to allow for future range expansion and long-term persistence of the California gnatcatcher.
C1 [Vandergast, Amy G.; Kus, Barbara E.; Wood, Dustin A.; Milano, Elizabeth R.; Preston, Kristine L.] US Geol Survey, Western Ecol Res Ctr, San Diego, CA 92101 USA.
C3 United States Department of the Interior; United States Geological
   Survey
RP Vandergast, AG (corresponding author), US Geol Survey, Western Ecol Res Ctr, San Diego, CA 92101 USA.
EM avandergast@usgs.gov
RI Vandergast, Amy/H-3618-2012
OI Milano, Elizabeth R./0000-0003-4143-9303; Kus,
   Barbara/0000-0002-3679-3044; Wood, Dustin/0000-0002-7668-9911;
   Vandergast, Amy G./0000-0002-7835-6571; Preston,
   Kristine/0000-0002-6958-1128
FU U.S. Fish and Wildlife Service; U.S. Geological Survey, Ecosystems
   Mission Area; U.S. Geological Survey, Western Ecological Research Center
FX U.S. Fish and Wildlife Service; U.S. Geological Survey, Ecosystems
   Mission Area; U.S. Geological Survey, Western Ecological Research Center
CR Ahrens CW, 2021, MOL ECOL RESOUR, V21, P1460, DOI 10.1111/1755-0998.13351
   Alexander DH, 2009, GENOME RES, V19, P1655, DOI 10.1101/gr.094052.109
   Allendorf FW, 2010, NAT REV GENET, V11, P697, DOI 10.1038/nrg2844
   AMEC, 2015, 32106C010 AMEC
   Andrews KR, 2016, NAT REV GENET, V17, P81, DOI 10.1038/nrg.2015.28
   [Anonymous], 1957, Checklist of North American Birds, V5th
   Atwood J.L., 1991, Bulletin Southern California Academy of Sciences, V90, P118
   Atwood J.L., 1998, POPULATION DYNAMICS
   Atwood J.L., 2020, BIRDS OF THE WORLD
   Atwood Jonathan L., 1993, P149
   Avise John C., 2004, P1
   Bailey Eric A., 1998, Western Birds, V29, P351
   BALL RM, 1992, AUK, V109, P626
   BARTON NH, 1985, ANNU REV ECOL SYST, V16, P113, DOI 10.1146/annurev.es.16.110185.000553
   Benjamini Y, 2001, ANN STAT, V29, P1165
   Berg N, 2015, J CLIMATE, V28, P6324, DOI 10.1175/JCLI-D-14-00624.1
   Bickford D, 2007, TRENDS ECOL EVOL, V22, P148, DOI 10.1016/j.tree.2006.11.004
   Catchen J, 2013, MOL ECOL, V22, P3124, DOI 10.1111/mec.12354
   Cavazos T, 2012, J CLIMATE, V25, P5904, DOI 10.1175/JCLI-D-11-00425.1
   Cayan DR, 2010, P NATL ACAD SCI USA, V107, P21271, DOI 10.1073/pnas.0912391107
   Clarke K., 2015, Getting Started With PRIMER v7, PRIMER-E
   Coates DJ, 2018, FRONT ECOL EVOL, V6, DOI 10.3389/fevo.2018.00165
   Crandall KA, 2000, TRENDS ECOL EVOL, V15, P290, DOI 10.1016/S0169-5347(00)01876-0
   Cronin MA, 1997, WILDLIFE SOC B, V25, P661
   Moura CCD, 2018, J AVIAN BIOL, V49, DOI 10.1111/jav.01692
   Degrandi TM, 2020, CYTOGENET GENOME RES, V160, P199, DOI 10.1159/000507768
   Dent R, 2012, PLOS ONE, V7, DOI [10.1371/journal.pone.0037135, 10.1371/journal.pone.0036889]
   Do C, 2014, MOL ECOL RESOUR, V14, P209, DOI 10.1111/1755-0998.12157
   Draheim HM, 2010, AUK, V127, P807, DOI 10.1525/auk.2010.09222
   Erickson Richard A., 1998, Western Birds, V29, P333
   Fitzpatrick John W., 2010, Ornithological Monographs, V67, P54
   Fleischer RC, 2006, BIOL LETT-UK, V2, P466, DOI 10.1098/rsbl.2006.0490
   Forester BR, 2018, MOL ECOL, V27, P2215, DOI 10.1111/mec.14584
   Frankham R, 2014, BIOL CONSERV, V170, P56, DOI 10.1016/j.biocon.2013.12.036
   Franklin I. R., 1980, Conservation Biology: An EvolutionaryEcological Perspective
   Funk WC, 2019, CONSERV GENET, V20, P115, DOI 10.1007/s10592-018-1096-1
   Funk WC, 2007, CONSERV GENET, V8, P1287, DOI 10.1007/s10592-006-9278-7
   Funk WC, 2007, MOL ECOL NOTES, V7, P284, DOI 10.1111/j.1471-8286.2006.01581.x
   Goodman RE, 2012, GLOBAL CHANGE BIOL, V18, P63, DOI 10.1111/j.1365-2486.2011.02538.x
   Goslee SC, 2007, J STAT SOFTW, V22, P1, DOI 10.18637/jss.v022.i07
   GRINNELL JOSEPH, 1926, PROC CALIFORNIA ACAD SCI, V15, P493
   Gutenkunst RN, 2009, PLOS GENET, V5, DOI 10.1371/journal.pgen.1000695
   Haig Susan M., 2010, Ornithological Monographs, V67, P24
   Haig SM, 2006, CONSERV BIOL, V20, P1584, DOI 10.1111/j.1523-1739.2006.00530.x
   Hohenlohe PA, 2021, MOL ECOL, V30, P62, DOI 10.1111/mec.15720
   Holderegger R, 2010, BASIC APPL ECOL, V11, P522, DOI 10.1016/j.baae.2010.06.006
   James F.C., 2010, Ornithological Monographs, V67, P1, DOI DOI 10.1525/OM.2010.67.1.1
   Jombart T, 2011, BIOINFORMATICS, V27, P3070, DOI 10.1093/bioinformatics/btr521
   Jones AT, 2016, HEREDITY, V117, P217, DOI 10.1038/hdy.2016.19
   Kam J, 2016, J CLIMATE, V29, P8269, DOI 10.1175/JCLI-D-15-0879.1
   Kamvar ZN, 2014, PEERJ, V2, DOI 10.7717/peerj.281
   Kennedy CM, 2019, GLOBAL CHANGE BIOL, V25, P811, DOI 10.1111/gcb.14549
   Keyghobadi N, 2007, CAN J ZOOL, V85, P1049, DOI 10.1139/Z07-095
   Klicka LB, 2016, CONSERV GENET, V17, P455, DOI 10.1007/s10592-015-0796-z
   Lewontin R., 1970, Annu Rev Ecol Syst, V1, P1, DOI [10.1146/annurev.es.01.110170.000245, DOI 10.1146/ANNUREV.ES.01.110170.000245]
   Li H, 2009, BIOINFORMATICS, V25, P2078, DOI 10.1093/bioinformatics/btp352
   Malinsky M, 2018, MOL BIOL EVOL, V35, P1284, DOI 10.1093/molbev/msy023
   Marcondes RS, 2021, AM NAT, V197, P592, DOI 10.1086/713386
   MAYR E, 1969, Biological Journal of the Linnean Society, V1, P311, DOI 10.1111/j.1095-8312.1969.tb00123.x
   McCormack JE, 2015, AUK, V132, P380, DOI 10.1642/AUK-14-184.1
   Mellink Eric, 1994, Western Birds, V25, P50
   MILLER SA, 1988, NUCLEIC ACIDS RES, V0016
   Mock P.J., 1992, ECOLOGY CALIFORNIA G
   Mock Patrick J., 1998, Western Birds, V29, P413
   MORITZ C, 1994, TRENDS ECOL EVOL, V9, P373, DOI 10.1016/0169-5347(94)90057-4
   Narum SR, 2006, CONSERV GENET, V7, P783, DOI 10.1007/s10592-005-9056-y
   NEI M, 1972, AM NAT, V106, P283, DOI 10.1086/282771
   Palsboll PJ, 2007, TRENDS ECOL EVOL, V22, P11, DOI 10.1016/j.tree.2006.09.003
   Patten MA, 2002, AUK, V119, P26, DOI 10.1642/0004-8038(2002)119[0026:DVMDOS]2.0.CO;2
   Patten MA, 2015, AUK, V132, P481, DOI 10.1642/AUK-15-1.1
   Patten Michael A., 2010, Ornithological Monographs, V67, P35
   Pembleton LW, 2013, MOL ECOL RESOUR, V13, P946, DOI 10.1111/1755-0998.12129
   Portik DM, 2017, MOL ECOL, V26, P5245, DOI 10.1111/mec.14266
   Preston Kristine L., 1998, Western Birds, V29, P242
   Ralls K, 2018, CONSERV LETT, V11, DOI 10.1111/conl.12412
   Remsen J.V. Jr, 2010, Ornithological Monographs, V67, P62
   Rossem A. J. van., 1931, Proceedings of the Biological Society of Washington, V44, P99
   Rossem A. J. van., 1931, Condor Berkeley, V33, P35
   Smeds L, 2016, GENOME RES, V26, P1211, DOI 10.1101/gr.204669.116
   Swain DL, 2015, GEOPHYS RES LETT, V42, P9999, DOI 10.1002/2015GL066628
   Swanson DL, 2009, EVOLUTION, V63, P184, DOI 10.1111/j.1558-5646.2008.00522.x
   TAJIMA F, 1989, GENETICS, V123, P585
   USFWS, 1993, FED REGISTER, V58, P16742
   Van Buskirk J, 2010, OIKOS, V119, P1047, DOI 10.1111/j.1600-0706.2009.18349.x
   VANDENWOLLENBERG AL, 1977, PSYCHOMETRIKA, V42, P207, DOI 10.1007/BF02294050
   Vandergast AG, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-018-37712-2
   VanTassel HLH, 2017, ECOL EVOL, V7, P10326, DOI 10.1002/ece3.3482
   Waples RK, 2016, HEREDITY, V117, P233, DOI 10.1038/hdy.2016.60
   Waples RS, 2008, MOL ECOL RESOUR, V8, P753, DOI 10.1111/j.1755-0998.2007.02061.x
   Waples RS, 2006, MOL ECOL, V15, P1419, DOI 10.1111/j.1365-294X.2006.02890.x
   Waples RS, 2005, MOL ECOL, V14, P3335, DOI 10.1111/j.1365-294X.2005.02673.x
   Weeks BC, 2020, ECOL LETT, V23, P316, DOI 10.1111/ele.13434
   WESTMAN WE, 1981, ECOLOGY, V62, P170, DOI 10.2307/1936680
   Winker Kevin, 2010, Ornithological Monographs, V67, P6
   Wood D.A., 2022, POLIOPTILA CALIFORNI, DOI [10.5066/P9MB2YE2, DOI 10.5066/P9MB2YE2]
   Wood DA, 2008, CONSERV GENET, V9, P1489, DOI 10.1007/s10592-007-9482-0
   Zink RM, 2004, P ROY SOC B-BIOL SCI, V271, P561, DOI 10.1098/rspb.2003.2617
   Zink RM, 2000, CONSERV BIOL, V14, P1394, DOI 10.1046/j.1523-1739.2000.99082.x
   Zink RM, 2013, AUK, V130, P449, DOI 10.1525/auk.2013.12241
NR 99
TC 2
Z9 2
U1 0
U2 7
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1752-4571
J9 EVOL APPL
JI Evol. Appl.
PD JUL
PY 2022
VL 15
IS 7
BP 1201
EP 1217
DI 10.1111/eva.13429
EA JUN 2022
PG 17
WC Evolutionary Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Evolutionary Biology
GA 3D5XT
UT WOS:000818632600001
PM 35899257
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Mkwambisi, DD
   Jew, EKK
   Dougill, AJ
AF Mkwambisi, David D.
   Jew, Eleanor K. K.
   Dougill, Andrew J.
TI Farmer Preparedness for Building Resilient Agri-Food Systems: Lessons
   From the 2015/2016 El Nino Drought in Malawi
SO FRONTIERS IN CLIMATE
LA English
DT Article
DE climate services; conservation agriculture (CA); sub-Saharan Africa;
   climate adaptation; disaster preparedness; climate smart agriculture
ID SUB-SAHARAN AFRICA; CONSERVATION AGRICULTURE; CLIMATE-CHANGE;
   SMALLHOLDER FARMERS; SOUTHERN AFRICA; SECURITY; GENDER; MAIZE; YIELD;
   CONSTRAINTS
AB Across sub-Saharan Africa, climate change is leading to increasingly erratic weather patterns that challenge farming practices, particularly for smallholder farmers. Preparing farmers for these changes and increasing their resilience to extreme weather events is critical for food security in areas where populations are increasing. The El Nino event of 2015/16 led to drought conditions in Malawi which are expected to become more normal in the future. This resulted in widespread crop failure and the need for external food aid. The experiences of Malawian farmers during this time creates an opportunity to identify areas where adaptations in land management practices as part of resilience building initiatives can prepare farmers for future climates. This paper presents results of household surveys and interviews of 201 farmers from a case study in southern Malawi. Half of the farmers surveyed practice Conservation Agriculture (CA), a Climate Smart Agriculture technology that increased resilience to this drought event. The majority of households relied on agriculture for all their livelihood streams, indicating that diversification away from sole dependence on agriculture would increase resilience. Our study shows that poorer, female farmers are less likely to practice CA than wealthier male farmers. Results also illustrate that while farmers had access to seasonal weather forecasts, a key tool to guide land preparation and planting, they remained reluctant to believe them or to amend cropping or land management practices. Agricultural extension services within Malawi can play a vital role in preparing farmers for future extreme weather events and ensuring forecast communication link to predicted agricultural impacts and land management actions for building resilience into agricultural systems. Extension services need to focus on supporting poorer female farmers to adopt CA practices and providing farmers with the tools and knowledge to respond effectively to seasonal and sub-seasonal climate information.
C1 [Mkwambisi, David D.] Malawi Univ Sci & Technol, MUST Inst Ind Res & Innovat, Limbe, Malawi.
   [Jew, Eleanor K. K.] Univ York, Dept Environm & Geog, York, England.
   [Dougill, Andrew J.] Univ Leeds, Sustainabil Res Inst, Sch Earth & Environm, Leeds, England.
C3 University of York - UK; University of Leeds
RP Jew, EKK (corresponding author), Univ York, Dept Environm & Geog, York, England.
EM eleanor.jew@york.ac.uk
FU UK's Natural Environment Research Council's (NERC); Department for
   International Development's (DfID) El Nino 2016 Programme [NE/P004091/1]
FX & nbsp;Funding was provided by the UK's Natural Environment Research
   Council's (NERC) and Department for International Development's (DfID)
   El Nino 2016 Programme [grant reference NE/P004091/1].
CR Andersson JA, 2014, AGR ECOSYST ENVIRON, V187, P116, DOI 10.1016/j.agee.2013.08.008
   [Anonymous], 2016, Human Development Reports
   [Anonymous], 2008, The Role of Conservation Agriculture: A Framework for Action, P1
   [Anonymous], 2012, NVivo
   [Anonymous], 2018, Hard hit by El nino : experiences, responses and options for Malawi, DOI [DOI 10.1596/30037, 10.1596/30037]
   [Anonymous], 2017, INT HOUS SURV 2016 2
   Berre D, 2017, FIELD CROP RES, V214, P113, DOI 10.1016/j.fcr.2017.08.026
   Blamey RC, 2018, INT J CLIMATOL, V38, P4276, DOI 10.1002/joc.5668
   Boillat S, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab45ad
   Bouwman TI, 2021, AGR ECOSYST ENVIRON, V307, DOI 10.1016/j.agee.2020.107224
   Brown AL, 2016, GLOBAL CHANGE BIOL, V22, P3461, DOI 10.1111/gcb.13380
   Brown B, 2018, LAND USE POLICY, V73, P331, DOI 10.1016/j.landusepol.2018.02.009
   Brown B, 2017, AGR SYST, V153, P11, DOI 10.1016/j.agsy.2017.01.012
   Chapota R., 2014, MEAS CASE STUDY, P8
   Chidanti-Malunga J, 2011, PHYS CHEM EARTH, V36, P1043, DOI 10.1016/j.pce.2011.08.012
   Chinse E, 2019, LAND DEGRAD DEV, V30, P533, DOI 10.1002/ldr.3190
   Chinsinga B, 2018, AFR REV-ABINGDON, V10, P140, DOI 10.1080/09744053.2018.1485253
   Chirwa E., 2013, ROLE PRIVATE SECTOR
   Chirwa EDorward A., 2013, Agricultural input subsidies: The recent Malawi experience
   Coulibaly Y., 2015, 112 CCAFS
   Dorward P., 2015, Participatory Integrated Climate Services for Agricultura (PICSA): Field Manual
   FAOSTAT, 2017, MAL COUNTR PROF
   Farnworth CR, 2016, INT J AGR SUSTAIN, V14, P142, DOI 10.1080/14735903.2015.1065602
   Giller KE, 2009, FIELD CROP RES, V114, P23, DOI 10.1016/j.fcr.2009.06.017
   GoM, 2020, MIN STAT AFF INP PRO
   GoM, 2015, PROSP 2015 2016 RAIN
   Government of Malawi, 2018, MAL NAT RES STRAT BR
   Habanyati Estone Jiji, 2020, Kasetsart Journal of Social Sciences, V41, P91
   Hadebe ST, 2017, J AGRON CROP SCI, V203, P177, DOI 10.1111/jac.12191
   Hart NCG, 2018, GEOPHYS RES LETT, V45, P11334, DOI 10.1029/2018GL079563
   Hermans TDG, 2021, LAND DEGRAD DEV, V32, P1809, DOI 10.1002/ldr.3833
   ITU, 2020, COUNTR ICT DAT
   Jew EKK, 2020, LAND USE POLICY, V95, DOI 10.1016/j.landusepol.2020.104612
   Kaumbata W, 2020, SMALL RUMINANT RES, V187, DOI 10.1016/j.smallrumres.2020.106095
   Kondylis F, 2016, WORLD DEV, V78, P436, DOI 10.1016/j.worlddev.2015.10.036
   Koppmair S, 2017, PUBLIC HEALTH NUTR, V20, P325, DOI [10.1017/S1368980016002135, 10.1017/s1368980016002135]
   Kotir Julius H., 2011, Environment Development and Sustainability, V13, P587, DOI 10.1007/s10668-010-9278-0
   Mittal N., 2017, FUTURE CLIMATE AFRIC
   Montt G, 2020, J AGR ECON, V71, P556, DOI 10.1111/1477-9552.12353
   Motsa NM, 2015, S AFR J SCI, V111, P38, DOI 10.17159/sajs.2015/20140252
   Mudege NN, 2017, GENDER PLACE CULT, V24, P1689, DOI [10.1080/0966369x.2017.1383363, 10.1080/0966369X.2017.1383363]
   Murray U, 2016, GEND TECHNOL DEV, V20, P117, DOI 10.1177/0971852416640639
   Mutegi J., 2015, FERTILISER RECCOMMEN
   National Statistical Office, 2015, STAT YB
   Ngwira AR, 2012, FIELD CROP RES, V132, P149, DOI 10.1016/j.fcr.2011.12.014
   Niang I, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1199
   Nkiaka E, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab4dfe
   NOAA, 2015, NAT WEATH SERV CLIM
   Pedzisa T., 2015, Journal of Sustainable Development, V8, P69
   Pelletier B, 2016, FOOD SECUR, V8, P469, DOI 10.1007/s12571-016-0576-8
   Quisumbing AR, 2010, WORLD DEV, V38, P581, DOI 10.1016/j.worlddev.2009.10.006
   Rajendran S., 2017, Agric Food Secur, V6, P50, DOI DOI 10.1186/S40066-017-0127-3
   Roudier P, 2014, CLIM RISK MANAG, V2, P42, DOI 10.1016/j.crm.2014.02.001
   Rurinda J, 2015, GLOBAL CHANGE BIOL, V21, P4588, DOI 10.1111/gcb.13061
   Shisanya S, 2016, FOOD SECUR, V8, P597, DOI 10.1007/s12571-016-0569-7
   Simelton E, 2013, CLIM DEV, V5, P123, DOI 10.1080/17565529.2012.751893
   Steinfield C., 2015, P 7 INT C INFORM COM, P1, DOI [10.1145/2737856.2738022, DOI 10.1145/2737856.2738022]
   Stevens T, 2016, SCI REP-UK, V6, DOI 10.1038/srep36241
   Steward PR, 2019, AGR ECOSYST ENVIRON, V277, P95, DOI 10.1016/j.agee.2018.07.009
   Steward PR, 2018, AGR ECOSYST ENVIRON, V251, P194, DOI 10.1016/j.agee.2017.09.019
   Tendall DM, 2015, GLOB FOOD SECUR-AGR, V6, P17, DOI 10.1016/j.gfs.2015.08.001
   The R Foundation for Statistical Computing, 2016, R VERS 3 3 2 2016 10
   The world bank, 2019, MAL OV
   USAID, 2016, MAL NIN MIT FACT SHE
   Valbuena D, 2012, FIELD CROP RES, V132, P175, DOI 10.1016/j.fcr.2012.02.022
   Vaughan C, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.586
   Vincent K, 2017, CLIM POLICY, V17, P189, DOI 10.1080/14693062.2015.1075374
   Waldman KB, 2017, ECOL ECON, V131, P222, DOI 10.1016/j.ecolecon.2016.09.006
   Wang B, 2019, P NATL ACAD SCI USA, V116, P22512, DOI 10.1073/pnas.1911130116
   Ward PS, 2016, AGR ECOSYST ENVIRON, V222, P67, DOI 10.1016/j.agee.2016.02.005
   Wekesah FM, 2019, INT J AGR SUSTAIN, V17, P78, DOI 10.1080/14735903.2019.1567245
   Whitfield S, 2019, GLOBAL ENVIRON CHANG, V55, P1, DOI 10.1016/j.gloenvcha.2019.01.004
   Wiggins S., 2013, LEAPING LEARNING LIN
NR 73
TC 5
Z9 7
U1 2
U2 10
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 JAN 20
PY 2021
VL 2
AR 584245
DI 10.3389/fclim.2020.584245
PG 14
WC Environmental Sciences; Environmental Studies
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology
GA L4VU3
UT WOS:001023266700001
OA gold, Green Accepted, Green Published
DA 2025-01-10
ER

PT J
AU Sena, LS
   Figueiredo, LAS
   dos Santos, GV
   Sousa, AD
   Santos, NPD
   Britto, FB
   Sarmento, JLR
   Brito, LF
AF Sena, Luciano Silva
   Silva Figueiredo Filho, Luiz Antonio
   dos Santos, Gleyson Vieira
   de Sousa Junior, Antonio
   da Silva Santos, Natanael Pereira
   Britto, Fabio Barros
   Rocha Sarmento, Jose Lindenberg
   Brito, Luiz Fernando
TI Genetic evaluation of tropical climate-adapted sheep for carcass traits
   including genomic information
SO SMALL RUMINANT RESEARCH
LA English
DT Article
DE Genomic parameters; Hair sheep; Longissimus dorsi; Santa Ines sheep;
   ssGBLUP
ID QUALITY TRAITS; PARAMETERS; MEAT; GROWTH
AB Santa Ines is a locally adapted hair sheep breed that is under large expansion in Brazil and other Tropical countries. This study aimed to evaluate the effect of different relationship matrices (A or H) on the estimation of genetic parameters and accuracy of (genomic) breeding values [(G)EBVs] for carcass traits measured in vivo in Santa Ines sheep. A total of 977, 890, 894, and 882 records for loin eye area (LEA), marbling score (MLE), subcutaneous fat thickness (SFT), and leg circumference (LEC), respectively, were included in this study. There were 1637 animals in the numerator relationship matrix (A). A total of 389 animals with phenotypic information were genotyped using the OvineSNP50 BeadChip. After the genotyping quality control, 388 samples and 42,748 SNPs remained in the dataset. The (co)variance components were estimated via Bayesian inference through single- and multi-trait analyses using the animal model with either the A or H matrix. The theoretical accuracies of (G)EBVs, Pearson correlation between breeding values estimated including or not genomic information, and Spearman rank correlation were used to evaluate the feasibility of incorporating genomic information in the analyses. Heritability estimates ranged from 0.12 +/- 0.06 (SFT, using the A matrix) to 0.29 +/- 0.07 (LEA, using the H matrix), in the single-trait analyses, and from 0.17 +/- 0.05 (SFT, using A) to 0.33 +/- 0.07 (LEA, using H), in a multi-trait setting. Direct genetic additive variance and heritability estimates were higher when including genomic information. Unfavorable and high genetic correlation was observed between LEA and SFT. The estimates of theoretical accuracy of (G)EBVs were higher in all the scenarios when genomic information was incorporated in the model. Gains in accuracy ranged from 0.013 to 0.039 units when genomic information was included in the analyses. Thus, if available, genomic information should be incorporated in the estimation of genetic parameters and breeding values for carcass traits measured in vivo in Santa Ines sheep.
C1 [Sena, Luciano Silva] Fed Univ Piaui UFPI, Agr Sci Ctr CCA, Grad Program Anim Sci, Campus Univ Minist Petronio Portella, BR-64049550 Teresina, PI, Brazil.
   [Silva Figueiredo Filho, Luiz Antonio] Fed Inst Educ Sci & Technol Maranhao IFMA, MA 340,Km 2, BR-65609899 Caxias, MA, Brazil.
   [dos Santos, Gleyson Vieira] Maranhao State Univ UEMA, Balsas Super Studies Ctr CESBA, Praca Goncalves Dias S-N, BR-65800000 Balsas, MA, Brazil.
   [de Sousa Junior, Antonio] Univ Fed Piaui, Agr Sci Ctr, Tech Sch Teresina, Campus Univ Minist Petronio Portella, BR-64049550 Teresina, PI, Brazil.
   [da Silva Santos, Natanael Pereira] UFPI, Dept Agron, Campus Prof Cinobelina Elvas,BR 135,Km 3, BR-64900000 Bom Jesus, PI, Brazil.
   [Britto, Fabio Barros] Univ Fed Piaui, Dept Biol, Campus Univ Minist Petronio Portella, BR-64049550 Teresina, PI, Brazil.
   [Rocha Sarmento, Jose Lindenberg] Univ Fed Piaui, Agr Sci Ctr, Dept Anim Sci, Campus Univ Minist Petronio Portella, BR-64049550 Teresina, PI, Brazil.
   [Brito, Luiz Fernando] Purdue Univ, Dept Anim Sci, Coll Agr, 270 S Russell St, W Lafayette, IN 47907 USA.
C3 Universidade Federal do Piaui; Instituto Federal do Maranhao;
   Universidade Estadual do Maranhao; Universidade Federal do Piaui;
   Universidade Federal do Piaui; Universidade Federal do Piaui; Purdue
   University System; Purdue University
RP Sarmento, JLR (corresponding author), Univ Fed Piaui, Agr Sci Ctr, Dept Anim Sci, Campus Univ Minist Petronio Portella, BR-64049550 Teresina, PI, Brazil.
EM sarmento@ufpi.edu.br
RI Sarmento, José/N-4860-2016; Santos, Gleyson/AAH-4896-2021; Pereira da
   Silva Santos, Natanael/AAV-5789-2020; Britto, Fabio/F-7042-2015
OI Brito, Luiz Fernando/0000-0002-5819-0922; Sarmento, Jose Lindenberg
   Rocha/0000-0002-4215-1515; Pereira da Silva Santos,
   Natanael/0000-0002-7538-5000; Sena, Luciano/0000-0003-0054-6655; Vieira
   dos Santos, Gleyson/0000-0003-3351-0632; Britto,
   Fabio/0000-0002-5705-5374
FU Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior - Brasil
   (CAPES) [001]; Brazilian National Institute of Science and Technology in
   Animal Science (INCT-CA) [465377/2014-9]; National Council for
   Scientific and Technological Development (CNPq) [481031/2012-0]; Federal
   University of Piaui (UFPI) [2013NE801717]; Foundation for Support to
   Research and Scientific and Technological Development of Maranhao
   (FAPEMA) [01488/16]
FX This study was partially funded by the Coordenacao de Aperfeicoamento de
   Pessoal de Nivel Superior - Brasil (CAPES) Finance code 001, which
   granted a Ph.D scholarship to the first author. The Brazilian National
   Institute of Science and Technology in Animal Science (INCT-CA) Process
   465377/2014-9, the National Council for Scientific and Technological
   Development (CNPq); Process 481031/2012-0), the Federal University of
   Piaui (UFPI) (Grant 2013NE801717), and the Foundation for Support to
   Research and Scientific and Technological Development of Maranhao
   (FAPEMA) (Process 01488/16) gave financial support for the genotyping of
   the animals.
CR Aguilar I, 2010, J DAIRY SCI, V93, P743, DOI 10.3168/jds.2009-2730
   Bakhshalizadeh S, 2016, SMALL RUMINANT RES, V134, P79, DOI 10.1016/j.smallrumres.2015.12.030
   Lobo RNB, 2019, J ANIM BREED GENET, V136, P313, DOI 10.1111/jbg.12396
   Brito LF, 2017, BMC GENET, V18, DOI 10.1186/s12863-017-0476-8
   Brito LF, 2017, SMALL RUMINANT RES, V154, P81, DOI 10.1016/j.smallrumres.2017.07.011
   Cheng WW, 2015, COMPR REV FOOD SCI F, V14, P523, DOI 10.1111/1541-4337.12149
   Ciappesoni G., 2014, 60 INT C MEAT SCI TE, DOI [10.13140/2.1.2762.6888, DOI 10.13140/2.1.2762.6888]
   Farah MM, 2018, PESQUI AGROPECU BRAS, V53, P717, DOI [10.1590/S0100-204X2018000600008, 10.1590/s0100-204x2018000600008]
   Gordo DGM, 2016, J ANIM SCI, V94, P1821, DOI 10.2527/jas.2015-0134
   Kiya CK, 2019, SMALL RUMINANT RES, V171, P57, DOI 10.1016/j.smallrumres.2018.12.007
   Misztal I., 2018, Manual for BLUPF90 family programs
   Mortimer SI, 2014, MEAT SCI, V96, P1016, DOI 10.1016/j.meatsci.2013.09.007
   Safari E, 2005, LIVEST PROD SCI, V92, P271, DOI 10.1016/j.livprodsci.2004.09.003
   Santana ML, 2013, J ANIM BREED GENET, V130, P394, DOI 10.1111/jbg.12029
   Sarmento JLR, 2006, ARQ BRAS MED VET ZOO, V58, P581, DOI 10.1590/S0102-09352006000400021
   SCHAEFFER LR, 1984, J DAIRY SCI, V67, P1567, DOI 10.3168/jds.S0022-0302(84)81479-4
   Figueiredo LAS, 2016, TROP ANIM HEALTH PRO, V48, P215, DOI 10.1007/s11250-015-0921-5
   VanRaden PM, 2008, J DAIRY SCI, V91, P4414, DOI 10.3168/jds.2007-0980
NR 18
TC 5
Z9 5
U1 0
U2 3
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0921-4488
EI 1879-0941
J9 SMALL RUMINANT RES
JI Small Ruminant Res.
PD JUL
PY 2020
VL 188
AR 106120
DI 10.1016/j.smallrumres.2020.106120
PG 5
WC Agriculture, Dairy & Animal Science
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA LW7YA
UT WOS:000539358700007
OA hybrid
DA 2025-01-10
ER

PT J
AU Xiong, Y
   Xie, XY
   Yang, YF
AF Xiong, Yao
   Xie, Xinyu
   Yang, Yunfeng
TI Evaluation and optimization of park cooling benefits based on cumulative
   impact and landscape pattern
SO SCIENTIFIC REPORTS
LA English
DT Article
DE Urban heat island; City park; Cooling benefit; Landscape pattern;
   Cumulative impacts
ID URBAN PARKS; HEAT; MORTALITY
AB City parks can cool the surrounding environment and mitigate the urban heat island (UHI) effect, considerable improving the city's adaptability to climate. In this study, 20 city parks in Nanjing, China, were considered, and four indexes for quantifying the cooling benefits from a cumulative impact perspective were proposed. These indexes are park cooling area (PCA), park cooling efficiency (PCE), park cooling intensity (PCI), and park cooling gradient (PCG). The results reveal the following: first, city parks have a positive impact on the surrounding thermal environment. The factors park area (PA), park perimeter (PP), landscape shape index (LSI), and normalized difference vegetation index (NDVI) determine cooling benefits. Second, PA and PP are significantly positively correlated with PCA but are significantly negatively correlated with PCE. LSI is negatively correlated with PCE, while NDVI is positively correlated with PCI and PCG. No significant correlation exists between the four cooling indexes and modified normalized difference water index(MNDWI). Finally, different parks exhibit variations in their ability to provide cooling benefits. Special or community parks are more appropriately situated in areas with constrained urban land resources. In designing comprehensive parks, the intricate boundary features and vegetation conditions need to be considered to optimize their cooling effects. Moreover, a larger number of residents are allowed to enjoy cooling services. The findings of this project will aid in the construction and optimization of city parks in future to combat the UHI effect.
C1 [Xiong, Yao] Nanjing Forestry Univ, Coll Art & Design, Nanjing, Peoples R China.
   [Xie, Xinyu] Lianyun Dist Cultural Ctr, Lianyungang, Peoples R China.
   [Yang, Yunfeng] Nanjing Forestry Univ, Coll Landscape Architecture, Nanjing, Peoples R China.
C3 Nanjing Forestry University; Nanjing Forestry University
RP Yang, YF (corresponding author), Nanjing Forestry Univ, Coll Landscape Architecture, Nanjing, Peoples R China.
EM yangyf@njfu.edu.cn
RI Yang, Yun-Feng/KIC-1158-2024
FU the National Natural Science Foundation of China [32171859]; National
   Natural Science Foundation of China [21YJCZH187]; Humanities and Social
   Science Research Project of the Ministry of Education; Qing Lan Project
   [SJCX22_0307]; Postgraduate Research &Practice Innovation Program of
   Jiangsu Province
FX This research was funded by the National Natural Science Foundation of
   China (32171859), the Humanities and Social Science Research Project of
   the Ministry of Education (21YJCZH187), the Sponsored by Qing Lan
   Project, the Postgraduate Research &Practice Innovation Program of
   Jiangsu Province (SJCX22_0307).
CR Algretawee H, 2022, URBAN CLIM, V45, DOI 10.1016/j.uclim.2022.101255
   Aram F, 2019, ENERGIES, V12, DOI 10.3390/en12203904
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   Brown RD, 2015, LANDSCAPE URBAN PLAN, V138, P118, DOI 10.1016/j.landurbplan.2015.02.006
   Cetin M, 2015, INT J SUST DEV WORLD, V22, P420, DOI 10.1080/13504509.2015.1061066
   Chang CR, 2007, LANDSCAPE URBAN PLAN, V80, P386, DOI 10.1016/j.landurbplan.2006.09.005
   Chen M, 2022, J CLEAN PROD, V334, DOI 10.1016/j.jclepro.2021.130252
   Cheung PK, 2019, LANDSCAPE URBAN PLAN, V192, DOI 10.1016/j.landurbplan.2019.103651
   China Meteorological Administration, 2023, China Climate Bulletin EB/OL
   Du CL, 2022, J ENVIRON MANAGE, V317, DOI 10.1016/j.jenvman.2022.115346
   Du L, 2014, IOP C SER EARTH ENV, V17, DOI 10.1088/1755-1315/17/1/012162
   Feng XJ, 2023, LAND-BASEL, V12, DOI 10.3390/land12020451
   Fouillet A, 2006, INT ARCH OCC ENV HEA, V80, P16, DOI 10.1007/s00420-006-0089-4
   Geng XL, 2022, SCI TOTAL ENVIRON, V823, DOI 10.1016/j.scitotenv.2022.153806
   Han DR, 2023, BUILD ENVIRON, V231, DOI 10.1016/j.buildenv.2023.110053
   Kang ZHY, 2023, BUILD ENVIRON, V243, DOI 10.1016/j.buildenv.2023.110673
   Li YL, 2021, URBAN FOR URBAN GREE, V65, DOI 10.1016/j.ufug.2021.127375
   Liang ZY, 2023, BUILD ENVIRON, V242, DOI 10.1016/j.buildenv.2023.110580
   Liao W, 2023, LANDSCAPE URBAN PLAN, V232, DOI 10.1016/j.landurbplan.2022.104681
   Liao W, 2021, URBAN FOR URBAN GREE, V62, DOI 10.1016/j.ufug.2021.127173
   Lin MX, 2021, J CLEAN PROD, V316, DOI 10.1016/j.jclepro.2021.128277
   Lin WQ, 2015, LANDSCAPE URBAN PLAN, V134, P66, DOI 10.1016/j.landurbplan.2014.10.012
   Liu ZH, 2022, COMMUN EARTH ENVIRON, V3, DOI 10.1038/s43247-022-00539-x
   Monteiro MV, 2016, URBAN FOR URBAN GREE, V16, P160, DOI 10.1016/j.ufug.2016.02.008
   Park CY, 2019, LANDSCAPE URBAN PLAN, V183, P26, DOI 10.1016/j.landurbplan.2018.10.022
   Pascal M, 2018, ENVIRON INT, V121, P189, DOI 10.1016/j.envint.2018.08.049
   Peng J, 2021, REMOTE SENS ENVIRON, V252, DOI 10.1016/j.rse.2020.112135
   Qiu J, 2023, ECOL INDIC, V154, DOI 10.1016/j.ecolind.2023.110550
   Shen ZC, 2024, ENVIRON SCI POLLUT R, V31, P14218, DOI 10.1007/s11356-023-31789-7
   Shi MQ, 2023, SCI TOTAL ENVIRON, V892, DOI 10.1016/j.scitotenv.2023.164603
   Shi MQ, 2023, SUSTAIN CITIES SOC, V93, DOI 10.1016/j.scs.2023.104519
   Sodoudi S, 2018, URBAN FOR URBAN GREE, V34, P85, DOI 10.1016/j.ufug.2018.06.002
   Song D, 2022, BUILD ENVIRON, V209, DOI 10.1016/j.buildenv.2021.108663
   Spronken-Smith RA, 1998, INT J REMOTE SENS, V19, P2085, DOI 10.1080/014311698214884
   Sun QH, 2019, ENVIRON INT, V128, P125, DOI 10.1016/j.envint.2019.04.025
   Sun X, 2020, URBAN FOR URBAN GREE, V55, DOI 10.1016/j.ufug.2020.126838
   Tian P, 2023, ENVIRON SCI POLLUT R, V30, P80931, DOI 10.1007/s11356-023-28088-6
   Vicedo-Cabrera AM, 2016, SWISS MED WKLY, V146, DOI 10.4414/smw.2016.14379
   Wang YS, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su141811700
   Xiao Y, 2023, SUSTAIN CITIES SOC, V98, DOI 10.1016/j.scs.2023.104817
   Xiao Y, 2023, SCI TOTAL ENVIRON, V868, DOI 10.1016/j.scitotenv.2023.161463
   Xu XL, 2017, CHINESE GEOGR SCI, V27, P818, DOI 10.1007/s11769-017-0910-x
   Yang GY, 2020, SUSTAIN CITIES SOC, V53, DOI 10.1016/j.scs.2019.101932
   Yang JR, 2022, SUSTAIN CITIES SOC, V79, DOI 10.1016/j.scs.2022.103684
   Yu XL, 2014, REMOTE SENS-BASEL, V6, P9829, DOI 10.3390/rs6109829
   Yu ZW, 2017, ECOL INDIC, V82, P152, DOI 10.1016/j.ecolind.2017.07.002
   Zhao MY, 2018, ECOL ECON, V152, P106, DOI 10.1016/j.ecolecon.2018.04.023
   Zhou W, 2023, SCI TOTAL ENVIRON, V890, DOI 10.1016/j.scitotenv.2023.164422
NR 48
TC 0
Z9 0
U1 8
U2 8
PU NATURE PORTFOLIO
PI BERLIN
PA HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY
SN 2045-2322
J9 SCI REP-UK
JI Sci Rep
PD OCT 23
PY 2024
VL 14
IS 1
AR 25092
DI 10.1038/s41598-024-76386-x
PG 14
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA K1D2Y
UT WOS:001341352800043
PM 39443557
OA gold
DA 2025-01-10
ER

PT J
AU Berman, DI
   Bulakhova, NA
   Meshcheryakova, EN
   Shekhovtsov, SV
AF Berman, D., I
   Bulakhova, N. A.
   Meshcheryakova, E. N.
   Shekhovtsov, S., V
TI Overwintering and cold tolerance in the Moor Frog (<i>Rana arvalis</i>)
   across its range
SO CANADIAN JOURNAL OF ZOOLOGY
LA English
DT Article
DE Rana arvalis; Moor Frog; geographic range; geographic variation of cold
   tolerance; overwintering temperature conditions; supercooling point;
   lower lethal temperature
ID FREEZING TOLERANCE; WOOD FROG; ADAPTATION; SYLVATICA; SURVIVAL;
   TEMPERATURES; HIBERNATION; POPULATION; EVOLUTION
AB Only two species of boreal Holarctic frogs (genus Rana Linnaeus, 1758) can survive freezing and overwinter on land; they are found in the subarctic and cold regions of North America (Wood Frog, Rana sylvatica LeConte, 1825) and Eurasia (Moor Frog, Rana arvalis Nilsson, 1842) and are an example of an unusual adaptive strategy of overwintering. Freeze tolerance (down to -16 degrees C) of R. sylvatica has been thoroughly studied; however, little is known about cold resistance of R. arvalis in cold regions. We found that R. arvalis from European Russia and from West Siberia tolerate freezing down to -12 or -16 degrees C, whereas frogs from the Danish population survived freezing only to -4 degrees C (Y. Voituron et al. 2009b; J. Comp. Physiol. B, 179: 223-230). All of these populations, according to mitochondrial DNA markers, are closely related. We suggest that the observed differences in cold tolerance (-4 degrees C vs. -12 or -16 degrees C) could be caused either by adaptations to climatic factors or by differences in experimental protocols. The northeastern boundary of the geographic range of R. arvalis in Yakutia coincides with the transitional area between discontinuous and continuous permafrost; beyond this area, winter soil temperature sharply declines. The lower lethal temperature and overwintering ecology of R. arvalis in Siberia are similar to those of the North American R. sylvatica.
C1 [Berman, D., I; Bulakhova, N. A.; Meshcheryakova, E. N.; Shekhovtsov, S., V] Inst Biol Problems North FEB RAS, Portovaya St 18, Magadan 685000, Russia.
   [Bulakhova, N. A.] Tomsk State Univ, Res Inst Biol & Biophys, Pr Lenina 36, Tomsk 634050, Russia.
   [Shekhovtsov, S., V] Inst Cytol & Genet SB RAS, Pr Lavrentieva 10, Novosibirsk 630090, Russia.
C3 Institute of Biological Problems of the North; Tomsk State University;
   Russian Academy of Sciences; Institute of Cytology & Genetics ICG SB RAS
RP Bulakhova, NA (corresponding author), Inst Biol Problems North FEB RAS, Portovaya St 18, Magadan 685000, Russia.
EM sigma44@mail.ru
RI Meshcheryakova, Elena/Q-2360-2017; Shekhovtsov, Sergei/AAZ-5347-2020;
   Bulakhova, Nina/S-3039-2017
OI Bulakhova, Nina/0000-0002-3000-6476
FU RFBR [16-04-00082-a, 19-0400312-a]; Budget project [0324-2019-0040-C-01]
FX We are grateful to Y.S. Korobeynikov and Y.S. Ravkin for their
   assistance with frog collection, as well as to an anonymous reviewer for
   improving the manuscript. Special thanks go to our colleague V. Fet for
   language editing of the text. The reported study was funded by RFBR
   (project nos. 16-04-00082-a and 19-0400312-a) and by Budget project
   0324-2019-0040-C-01.
CR [Anonymous], 2010, The Red Data Book of the Republic of Kazakhstan, VVolume 2
   Babik W, 2004, MOL ECOL, V13, P1469, DOI 10.1111/j.1365-294X.2004.02157.x
   Baker PJ, 2006, CAN J ZOOL, V84, P116, DOI 10.1139/Z05-183
   Bannikov A.G., 1977, OBRAZOVANIE
   Belimov G.T., 1979, ECOLOGY, V5, P92
   Berman DI, 2017, ZOOL ZH, V96, P1392, DOI 10.7868/S0044513417110034
   Berman D I, 2016, Dokl Biol Sci, V471, P276, DOI 10.1134/S0012496616060065
   Berman D I, 2016, Dokl Biol Sci, V468, P137, DOI 10.1134/S001249661603011X
   Berman D I, 2012, Dokl Biol Sci, V443, P97, DOI 10.1134/S0012496612020068
   Berman DI, 2016, POLAR BIOL, V39, P2411, DOI 10.1007/s00300-016-1916-z
   Berman DI., 1984, J EVOLUTIONARY BIOCH, V20, P323
   Borkin LJ, 1984, ECOLOGY FAUNISTIC AM, P89
   Bulakhova N.A., 2017, P 19 SEH EUR C HERP
   Bulakhova N.A., 2017, P 5 BIOL VIP C 10 20
   Costanzo JP, 2013, J EXP BIOL, V216, P3461, DOI 10.1242/jeb.089342
   COSTANZO JP, 1993, AM J PHYSIOL, V265, pR721, DOI 10.1152/ajpregu.1993.265.4.R721
   COSTANZO JP, 1991, J COMP PHYSIOL B, V161, P225, DOI 10.1007/BF00262302
   Ershov E. D., 1989, GEOCRYOLOGY USSR E S
   Excoffier L, 2005, EVOL BIOINFORM, V1, P47, DOI 10.1177/117693430500100003
   Goujon M, 2010, NUCLEIC ACIDS RES, V38, pW695, DOI 10.1093/nar/gkq313
   Irwin JT, 1999, CAN J ZOOL, V77, P1240, DOI 10.1139/cjz-77-8-1240
   Izyumenko S.A., 1989, CLIMATE USSR APPL 3, V3
   Knopp T, 2009, HEREDITY, V102, P174, DOI 10.1038/hdy.2008.91
   Krasavtsev B.A., 1939, ISS ECOL BIOCEN, V4, P253
   Larson DJ, 2014, J EXP BIOL, V217, P2193, DOI 10.1242/jeb.101931
   LAYNE JR, 1990, CAN J ZOOL, V68, P506, DOI 10.1139/z90-074
   LAYNE JR, 1995, J THERM BIOL, V20, P349, DOI 10.1016/0306-4565(94)00069-U
   Lee RE, 1998, ANNU REV PHYSIOL, V60, P55, DOI 10.1146/annurev.physiol.60.1.55
   LOTSHAW DP, 1977, COMP BIOCHEM PHYS A, V56, P287, DOI 10.1016/0300-9629(77)90239-0
   Matkovskiy AV., 2011, B SAMARA SCI CTR RAS, V13, P1130
   Richter-Boix A, 2011, MOL ECOL, V20, P1582, DOI 10.1111/j.1365-294X.2011.05025.x
   STOREY KB, 1984, J COMP PHYSIOL B, V155, P29, DOI 10.1007/BF00688788
   Storey KB, 2004, LIFE IN THE FROZEN STATE, P243, DOI 10.1201/9780203647073.ch7
   Terentyev PV., 1950, FROG
   Voituron Y, 2005, AM J PHYSIOL-REG I, V288, pR1563, DOI 10.1152/ajpregu.00711.2004
   Voituron Y, 2009, CRYOBIOLOGY, V58, P241, DOI 10.1016/j.cryobiol.2009.01.001
   Voituron Y, 2009, J COMP PHYSIOL B, V179, P223, DOI 10.1007/s00360-008-0307-3
   Yuan ZY, 2016, SYST BIOL, V65, P824, DOI 10.1093/sysbio/syw055
NR 38
TC 13
Z9 13
U1 2
U2 21
PU CANADIAN SCIENCE PUBLISHING
PI OTTAWA
PA 65 AURIGA DR, SUITE 203, OTTAWA, ON K2E 7W6, CANADA
SN 0008-4301
EI 1480-3283
J9 CAN J ZOOL
JI Can. J. Zool.
PD NOV
PY 2020
VL 98
IS 11
BP 705
EP 714
DI 10.1139/cjz-2019-0179
PG 10
WC Zoology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Zoology
GA OO6DP
UT WOS:000587468400002
DA 2025-01-10
ER

PT J
AU Asprilla, DB
   Valdés, CF
   Macías, RJ
   Chejne, F
AF Asprilla, Deybi B.
   Valdes, Carlos F.
   Macias, Robert J.
   Chejne, Farid
TI Evaluation of potential of energetic development in isolated zones with
   wide biodiversity: NIZ Choco-Colombia case study
SO THERMAL SCIENCE AND ENGINEERING PROGRESS
LA English
DT Article
DE Gasification; Energy potential; Residual biomass; Photovoltaic system;
   Hybrid system
ID FIXED-BED GASIFICATION; HYDROGEN-RICH GAS; BIOMASS GASIFICATION;
   DOWNDRAFT GASIFIER; PERFORMANCE EVALUATION; OPERATING PARAMETERS;
   COMBINED HEAT; SYSTEM; POWER; AIR
AB The implementation of a hybrid biomass gasification-photovoltaic system for electricity generation in isolated regions was evaluated. Experiments were carried out to test the gasification of agricultural residual biomass in a downdraft fixed-bed gasifier coupled to an internal combustion engine and a photovoltaic system with this setup, electricity was successfully generated by means of rice husk (RH) gasification, which produced a synthesis gas with a calorific value below 3-5 MJ/Nm(3). The gas was purified sufficiently to make it profitable in an engine through a simple cleaning system. The main contribution is given by the proposal of a hybrid system adapted to climatic conditions and renewable resources settled in the region; In order to have a portable and autonomous system. Where it can be concluded that a hybrid solar-biomass system is a versatile alternative to contribute to the generation and efficient use of electrical energy. The hybrid system provided a stable electricity supply of 24-27 kWh. Along with the analysis of residual biomass availability in the Choco region, this indicates that the implementation of technological alternatives such as the ones tested in this research are able to sustainably fulfill the energy needs of isolated communities by making use of the resources coming from their own agricultural activities. Also, the conclusions show that the best hybrid system, from the technician-economic point of view for the energy.
C1 [Asprilla, Deybi B.] Univ Tecnol Choco, Grp Invest Meteorol & Energia Renovables, Istmina, Choco, Colombia.
   [Asprilla, Deybi B.; Valdes, Carlos F.; Macias, Robert J.; Chejne, Farid] Univ Nacl Colombia, Fac Minas, TAYEA Grp, Escuela Proc & Energia, Medellin, Colombia.
C3 Universidad Nacional de Colombia
RP Chejne, F (corresponding author), Univ Nacl Colombia, Fac Minas, Escuela Proc & Energia, Medellin, Colombia.
EM fchejne@unal.edu.co
RI Valdés, Carlos/ABE-3774-2021
OI Valdes, Carlos/0000-0001-6836-7085; Macias Naranjo,
   Robert/0000-0003-2201-0405; Asprilla Mosquera, Deybi
   Brayan/0000-0002-8395-4306
FU Government of Choco; Colciencias
FX First of all, thanks to the living God for his mercy, kindness and love.
   A very special thanks to Farid Chejne Janna Ph.D. for his friendship,
   example-setting and unconditional support, which have allowed us to
   carry out this work. To the Government of Choco and Colciencias for the
   financial support. To the members of the research group Applied
   Thermodynamics and Alternative Energies (TAYEA) for the support and
   collaboration, especially Gloria Marrugo and Javier Ordonez. To the
   Project "Prototype of electric and thermal power generation in isolated
   nuclei of Ibero-America through hybridization -HIBRELEC". To Jose
   Humberto Arango, who always offered his support and helped me in
   carrying out the experimental tests.
CR Adams PWR, 2014, SUSTAIN ENERGY TECHN, V6, P129, DOI 10.1016/j.seta.2014.02.002
   Ahrenfeldt J, 2013, APPL THERM ENG, V50, P1407, DOI 10.1016/j.applthermaleng.2011.12.040
   [Anonymous], 2015, PLAN EN NAC COL ID E
   [Anonymous], 2017, INT EN OUTL 2017
   [Anonymous], 2016, WORLD EN OUTL 2016
   Arregi A, 2018, ENERG CONVERS MANAGE, V165, P696, DOI 10.1016/j.enconman.2018.03.089
   Bain R.L., 2011, Thermochemical processing of biomass conversion into fuels, chemical and power
   Balu E, 2012, BIORESOURCE TECHNOL, V108, P264, DOI 10.1016/j.biortech.2011.12.105
   Basu P, 2018, BIOMASS GASIFICATION, PYROLYSIS AND TORREFACTION: PRACTICAL DESIGN AND THEORY, 3RD EDITION, P1, DOI 10.1016/C2016-0-04056-1
   Basu P., 2013, BIOMASS GASIFICATION
   Bentouba S, 2016, APPL THERM ENG, V99, P713, DOI 10.1016/j.applthermaleng.2015.12.014
   Biagini E, 2015, BIORESOURCE TECHNOL, V194, P36, DOI 10.1016/j.biortech.2015.07.016
   Brandoni C, 2015, APPL THERM ENG, V75, P896, DOI 10.1016/j.applthermaleng.2014.10.023
   Bridgwater AV, 2003, CHEM ENG J, V91, P87, DOI 10.1016/S1385-8947(02)00142-0
   Brosowski A, 2016, BIOMASS BIOENERG, V95, P257, DOI 10.1016/j.biombioe.2016.10.017
   Chaves LI, 2016, RENEW SUST ENERG REV, V58, P491, DOI 10.1016/j.rser.2015.12.033
   Chopra S., 2007, AGR ENG INT CIGR J
   Escalante Hernandez H., 2010, Atlas del Potencial Energetico de la Biomasa Residual en Colombia
   Fonseca SD, 2017, AV CIENC ING, V8, P29
   Fryda L, 2008, ENERG CONVERS MANAGE, V49, P281, DOI 10.1016/j.enconman.2007.06.013
   Galindo AL, 2014, BIOMASS BIOENERG, V61, P236, DOI 10.1016/j.biombioe.2013.12.017
   Gobel B., 2004, P 2 WORLD C TECHN EX, V2, P2540
   González A, 2015, SUSTAINABILITY-BASEL, V7, P12787, DOI 10.3390/su70912787
   Gonzalez-Salazar MA, 2014, APPL ENERG, V136, P781, DOI 10.1016/j.apenergy.2014.07.004
   Guo FQ, 2014, INT J HYDROGEN ENERG, V39, P5625, DOI 10.1016/j.ijhydene.2014.01.130
   Halder PK, 2015, RENEW SUST ENERG REV, V51, P1636, DOI 10.1016/j.rser.2015.07.069
   Huang Y, 2013, APPL ENERG, V112, P518, DOI 10.1016/j.apenergy.2013.03.078
   Im-orb K, 2016, FUEL, V164, P361, DOI 10.1016/j.fuel.2015.10.018
   Jaojaruek K, 2011, BIORESOURCE TECHNOL, V102, P4834, DOI 10.1016/j.biortech.2010.12.024
   Kotowicz J, 2013, ENERGY, V52, P265, DOI 10.1016/j.energy.2013.02.048
   Liu HL, 2012, J NAT GAS CHEM, V21, P374, DOI 10.1016/S1003-9953(11)60379-4
   Lv P, 2007, RENEW ENERG, V32, P2173, DOI 10.1016/j.renene.2006.11.010
   Lv X, 2014, INT J HYDROGEN ENERG, V39, P20968, DOI 10.1016/j.ijhydene.2014.10.083
   Ma ZQ, 2012, ENERGY, V46, P140, DOI 10.1016/j.energy.2012.09.008
   Maleki A, 2017, ENERG CONVERS MANAGE, V153, P129, DOI 10.1016/j.enconman.2017.09.061
   Maleki A, 2017, SUSTAIN CITIES SOC, V34, P278, DOI 10.1016/j.scs.2017.06.023
   Maleki A, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9081314
   Maleki A, 2017, INT J HYDROGEN ENERG, V42, P15973, DOI 10.1016/j.ijhydene.2017.01.169
   Maleki A, 2016, BIOFUELS-UK, V7, P699, DOI 10.1080/17597269.2016.1192443
   Marrugo G, 2017, ENERG FUEL, V31, P9408, DOI 10.1021/acs.energyfuels.7b00665
   Marrugo G, 2016, ENERG FUEL, V30, P8386, DOI 10.1021/acs.energyfuels.6b01596
   Minminas and UPM, 2016, MINM UPM PROYECC REG
   Montuori L, 2015, RENEW ENERG, V83, P615, DOI 10.1016/j.renene.2015.04.068
   Mosquera L.Y., 2012, THESIS
   Pallozzi V, 2016, ENERG CONVERS MANAGE, V130, P34, DOI 10.1016/j.enconman.2016.10.039
   Patel VR, 2017, ENERGY, V119, P834, DOI 10.1016/j.energy.2016.11.057
   PERS Choco, 2016, DIAGN EN DEP CHOC
   Pode R, 2016, RENEW SUST ENERG REV, V53, P1468, DOI 10.1016/j.rser.2015.09.051
   Prando D, 2014, APPL THERM ENG, V71, P152, DOI 10.1016/j.applthermaleng.2014.06.043
   Reed T.B., 1988, HDB BIOMASS DOWNDRAF, V1
   Sarker S, 2015, ENERG CONVERS MANAGE, V103, P801, DOI 10.1016/j.enconman.2015.07.022
   Shah KK, 2015, ENERG CONVERS MANAGE, V105, P71, DOI 10.1016/j.enconman.2015.07.048
   Sharma AK, 2009, RENEW ENERG, V34, P1726, DOI 10.1016/j.renene.2008.12.030
   Son YI, 2011, BIOMASS BIOENERG, V35, P4215, DOI 10.1016/j.biombioe.2011.07.008
   Striugas N, 2014, APPL THERM ENG, V73, P1151, DOI 10.1016/j.applthermaleng.2014.09.007
   Susastriawan AAP, 2017, RENEW SUST ENERG REV, V76, P989, DOI 10.1016/j.rser.2017.03.112
   Uchman W, 2017, APPL THERM ENG, V126, P194, DOI 10.1016/j.applthermaleng.2017.07.142
   Unidad de Planeacion Minero Energetica-UPME, 2015, Integracion de las energias renovables no convencionales en Colombia
   United Nations and Framework Convention on Climate Change, 2015, PAR AGR C PART FRAM
   UPME, 2014, PLAN IND EXP COB E E
   UPME CREG DNP SSPD MME, 2006, IND COB EN EL NAT
   Wang JJ, 2015, APPL ENERG, V142, P317, DOI 10.1016/j.apenergy.2014.12.085
   Wang ZQ, 2015, FUEL, V150, P386, DOI 10.1016/j.fuel.2015.02.056
   Warnecke R, 2000, BIOMASS BIOENERG, V18, P489, DOI 10.1016/S0961-9534(00)00009-X
   Wei L, 2011, BIORESOURCE TECHNOL, V102, P6266, DOI 10.1016/j.biortech.2011.02.109
   Yin RZ, 2012, BIORESOURCE TECHNOL, V119, P15, DOI 10.1016/j.biortech.2012.05.085
   Yoon SJ, 2012, RENEW ENERG, V42, P163, DOI 10.1016/j.renene.2011.08.028
   Zhang LH, 2010, ENERG CONVERS MANAGE, V51, P969, DOI 10.1016/j.enconman.2009.11.038
NR 68
TC 4
Z9 5
U1 1
U2 8
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2451-9049
J9 THERM SCI ENG PROG
JI Therm. Sci. Eng. Prog.
PD DEC
PY 2018
VL 8
BP 109
EP 117
DI 10.1016/j.tsep.2018.08.010
PG 9
WC Thermodynamics; Energy & Fuels; Engineering, Mechanical; Mechanics
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Thermodynamics; Energy & Fuels; Engineering; Mechanics
GA VJ7ML
UT WOS:000621185500013
DA 2025-01-10
ER

PT J
AU Wentz, EA
   Solís, P
   Wang, CY
   Aguiar-Hernandez, C
   Courtright, H
   Dock, AJ
AF Wentz, Elizabeth A.
   Solis, Patricia
   Wang, Chuyuan
   Aguiar-Hernandez, Carlos
   Courtright, Hank
   Dock, Aaron J.
TI Planning for Heat Resilience and the Future of Residential Electricity
   Usage
SO ANNALS OF THE AMERICAN ASSOCIATION OF GEOGRAPHERS
LA English
DT Article
DE community resilience; COVID-19; housing; residential energy use; urban
   climate adaptation
ID ENERGY-CONSUMPTION; BUILT ENVIRONMENT; CLIMATE-CHANGE; URBAN; IMPACT;
   VULNERABILITY; TEMPERATURES; HEALTH; URBANIZATION; PHOENIX
AB Community resilience refers to the ability for a geographic area to respond and adapt to acute shocks and long-term stresses. Geography research is well positioned to examine how communities can adapt to the compounding effects of climate change. Our work aims to analyze the factors that influence residential electricity in the context of increasing urban temperatures in Maricopa County, Arizona, coupled with the COVID-19 pandemic. Using census tracts as our basis for analysis, we quantified factors that influence electricity use related to neighborhood characteristics, home structures, social situations, pricing policies, and work-from-home estimates. Our findings suggest that the structure of the home (e.g., number of rooms and house size) influences the variation in residential electricity use, whereas trees and small-area temperatures were not factors. We then compared above-median-income census tracts to those that were below the median income. We found fewer factors influenced electricity use in the lower income census tracts and that they were also related mostly to the home structure. Our analysis did not reveal that working from home was significant, but we did find that the average household size was significant and that the amount of influence increased from 2019 to 2020, suggesting that the stay-at-home policies from the pandemic did affect electricity use. As we consider and implement work-from-home strategies, families need to recognize that the home structure plays a crucial role in determining electricity usage.
C1 [Wentz, Elizabeth A.; Solis, Patricia] Arizona State Univ, Sch Geog Sci & Urban Planning, Tempe, AZ 85281 USA.
   [Wang, Chuyuan] Towson Univ, Dept Geog & Environm Planning, Towson, MD USA.
   [Aguiar-Hernandez, Carlos] Arizona State Univ, Coll Global Futures, Tempe, AZ USA.
   [Courtright, Hank; Dock, Aaron J.] Salt River Project, Tempe, AZ USA.
C3 Arizona State University; Arizona State University-Tempe; University
   System of Maryland; Towson University; Arizona State University; Arizona
   State University-Tempe
RP Wentz, EA (corresponding author), Arizona State Univ, Sch Geog Sci & Urban Planning, Tempe, AZ 85281 USA.
EM wentz@asu.edu
RI Solis, Patricia/AAO-6537-2021; Wang, Chuyuan/I-2662-2018
OI Wang, Chuyuan/0000-0002-6381-6424; Solis, Patricia/0000-0003-1374-9400
CR Aflaki A, 2017, CITIES, V62, P131, DOI 10.1016/j.cities.2016.09.003
   Alqasemi AS, 2021, SCI TOTAL ENVIRON, V767, DOI 10.1016/j.scitotenv.2020.144330
   Anderson GB, 2011, ENVIRON HEALTH PERSP, V119, P210, DOI 10.1289/ehp.1002313
   Baker Marissa G, 2020, PLoS One, V15, pe0232452, DOI 10.1371/journal.pone.0232452
   Barthelemy M, 2016, ENVIRON PLANN B, V43, P800, DOI 10.1177/0265813516649955
   Bayulken B, 2021, J CLEAN PROD, V288, DOI 10.1016/j.jclepro.2020.125569
   Benson ED, 1998, J REAL ESTATE FINANC, V16, P55, DOI 10.1023/A:1007785315925
   Bikomeye JC, 2021, INT J ENV RES PUB HE, V18, DOI 10.3390/ijerph18168420
   Bobrowska-Korzeniowska M, 2021, INT J OCCUP MED ENV, V34, P453, DOI 10.13075/ijomeh.1896.01651
   Brown MA, 2020, PROG ENERGY, V2, DOI 10.1088/2516-1083/abb954
   Bureau of Labor Statistics (BLS), 2023, US
   Buylova A, 2020, ENERG POLICY, V140, DOI 10.1016/j.enpol.2020.111439
   Calvert K, 2016, PROG HUM GEOG, V40, P105, DOI 10.1177/0309132514566343
   Castells-Quintana D, 2021, ECOL ECON, V189, DOI 10.1016/j.ecolecon.2021.107153
   Centers for Disease Control, 2021, HURR ID
   Central Arizona-Phoenix Long-Term Ecological Research, 2020, LAND COV MAPP CENTR
   Chapman S, 2017, LANDSCAPE ECOL, V32, P1921, DOI 10.1007/s10980-017-0561-4
   Chow WTL, 2012, PROF GEOGR, V64, P286, DOI 10.1080/00330124.2011.600225
   Cicala S, 2021, J PUBLIC ECON, V200, DOI 10.1016/j.jpubeco.2021.104461
   Clark DE, 2000, GROWTH CHANGE, V31, P385, DOI 10.1111/0017-4815.00134
   Cong SC, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-30146-5
   Dingel JI, 2020, J PUBLIC ECON, V189, DOI 10.1016/j.jpubeco.2020.104235
   Eisenman DP, 2016, HEALTH PLACE, V41, P89, DOI 10.1016/j.healthplace.2016.08.007
   Environmental Protection Agency, 2022, HOM PAG
   Ewing R, 2008, HOUS POLICY DEBATE, V19, P1, DOI 10.1080/10511482.2008.9521624
   Ezell JM, 2021, LANCET PLANET HEALTH, V5, pE309, DOI 10.1016/S2542-5196(21)00076-0
   Fraser AM, 2017, ENVIRON PLAN B-URBAN, V44, P1036, DOI 10.1177/0265813516657342
   Gorgani S., 2013, The Relationship between NDVI and LST in the Urban Area Of Mashhad
   Guardaro M, 2022, CLIM RISK MANAG, V35, DOI 10.1016/j.crm.2022.100415
   Guardaro M, 2023, AM J PUBLIC HEALTH, V113, P465, DOI 10.2105/AJPH.2023.307260
   Harlan SL, 2013, ENVIRON HEALTH PERSP, V121, P197, DOI 10.1289/ehp.1104625
   Hernández D, 2013, AM J PUBLIC HEALTH, V103, pE32, DOI 10.2105/AJPH.2012.301179
   Hidalgo-García D, 2022, SUSTAIN CITIES SOC, V87, DOI 10.1016/j.scs.2022.104166
   Hondula DM, 2015, CURR CLIM CHANGE REP, V1, P144, DOI 10.1007/s40641-015-0016-4
   Howard B, 2012, ENERG BUILDINGS, V45, P141, DOI 10.1016/j.enbuild.2011.10.061
   Huang WH, 2015, ENERGY, V87, P120, DOI 10.1016/j.energy.2015.04.101
   Isaac M, 2009, ENERG POLICY, V37, P507, DOI 10.1016/j.enpol.2008.09.051
   Iverson SA, 2020, PUBLIC HEALTH REP, V135, P631, DOI 10.1177/0033354920938006
   Jafino B A., 2020, Revised estimates of the impact of climate change on extreme poverty by 2030
   Jenerette GD, 2016, LANDSCAPE ECOL, V31, P745, DOI 10.1007/s10980-015-0284-3
   Jenkins K, 2016, ENERGY RES SOC SCI, V11, P174, DOI 10.1016/j.erss.2015.10.004
   Jones A, 2023, ENERG POLICY, V183, DOI 10.1016/j.enpol.2023.113811
   Kaza N, 2010, ENERG POLICY, V38, P6574, DOI 10.1016/j.enpol.2010.06.028
   Kear M. M., 2020, ARIZONA REPUBLIC
   Keith Meerow., 2020, J EXTREME EVENTS, DOI DOI 10.1142/S2345737620500037
   Kontokosta CE, 2020, J AM PLANN ASSOC, V86, P89, DOI 10.1080/01944363.2019.1647446
   Ku AL, 2022, APPL ENERG, V310, DOI 10.1016/j.apenergy.2022.118539
   Kuzemko C, 2020, ENERGY RES SOC SCI, V68, DOI 10.1016/j.erss.2020.101685
   Kwon M, 2023, ENERG POLICY, V183, DOI 10.1016/j.enpol.2023.113813
   Lemanski C, 2016, GEOGRAPHY, V101, P4
   Lou JH, 2021, ISCIENCE, V24, DOI 10.1016/j.isci.2021.103231
   Maricopa County Department of Public Health, 2021, MARICOPA COUNTY DEP
   Memmott T, 2023, ISCIENCE, V26, DOI 10.1016/j.isci.2023.106244
   Memmott T, 2021, NAT ENERGY, V6, P186, DOI 10.1038/s41560-020-00763-9
   Milosevic D, 2022, SCI TOTAL ENVIRON, V815, DOI 10.1016/j.scitotenv.2021.152782
   National Oceanic and Atmospheric Administration, 2021, HOM PAG
   Nieuwenhuijsen MJ, 2021, ENVIRON INT, V157, DOI 10.1016/j.envint.2021.106850
   Parida BR, 2021, SUSTAIN CITIES SOC, V75, DOI 10.1016/j.scs.2021.103336
   Patz JA, 2005, NATURE, V438, P310, DOI 10.1038/nature04188
   Perera ATD, 2020, NAT ENERGY, V5, P150, DOI 10.1038/s41560-020-0558-0
   Pour SH, 2020, SUSTAIN CITIES SOC, V62, DOI 10.1016/j.scs.2020.102373
   Psistaki K, 2023, ENVIRON RES, V216, DOI 10.1016/j.envres.2022.114831
   Reinwald F, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su131910606
   Roshan G, 2022, J CLEAN PROD, V352, DOI 10.1016/j.jclepro.2022.131498
   Salt River Project (SRP), 2022, HOM PAG
   Santamouris M, 2015, ENERG BUILDINGS, V91, P43, DOI 10.1016/j.enbuild.2015.01.027
   Saputra A., 2022, IOP Conference Series: Earth and Environmental Science, V986, DOI 10.1088/1755-1315/986/1/012069
   Scheier E, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-021-27673-y
   Schmeltz MT, 2019, INT J ENV RES PUB HE, V16, DOI 10.3390/ijerph16173091
   Shikwambana L, 2021, AEROSOL AIR QUAL RES, V21, DOI 10.4209/aaqr.200437
   Stewart ID, 2011, INT J CLIMATOL, V31, P200, DOI 10.1002/joc.2141
   Turner VK, 2023, NATURE, V619, P694, DOI 10.1038/d41586-023-02311-3
   Tzavali A, 2015, FRESEN ENVIRON BULL, V24, P4535
   U.S. Census Bureau, 2023, HOM PAG
   U.S. Energy Information Administration, 2023, HOM PAG
   United Nations (UN), 2022, HOM PAG
   Wai CY, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14010378
   Wang CY, 2022, INT J ENVIRON HEAL R, V32, P1147, DOI 10.1080/09603123.2020.1847258
   Wang CY, 2021, J URBAN HEALTH, V98, P344, DOI 10.1007/s11524-021-00520-7
   Wang Q, 2016, RENEW SUST ENERG REV, V54, P1563, DOI 10.1016/j.rser.2015.10.090
   Weiyu L., 2022, GEOSPATIAL DATA ANAL, P33
   White LV, 2018, NAT ENERGY, V3, P1101, DOI 10.1038/s41560-018-0285-y
   Xi ZJ, 2023, SCI TOTAL ENVIRON, V859, DOI 10.1016/j.scitotenv.2022.160270
   Zhao L, 2021, NAT CLIM CHANGE, V11, DOI 10.1038/s41558-020-00958-8
   Zhao N, 2021, ADV APPL ENERGY, V2, DOI 10.1016/j.adapen.2021.100019
   Zhao QS, 2018, URBAN FOR URBAN GREE, V32, P81, DOI 10.1016/j.ufug.2018.03.022
NR 86
TC 1
Z9 1
U1 3
U2 4
PU ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
SN 2469-4452
EI 2469-4460
J9 ANN AM ASSOC GEOGR
JI Ann. Am. Assoc. Geogr.
PD MAY 27
PY 2024
VL 114
IS 5
BP 918
EP 942
DI 10.1080/24694452.2024.2304188
EA JAN 2024
PG 25
WC Geography
WE Social Science Citation Index (SSCI)
SC Geography
GA RW5T4
UT WOS:001189720800001
OA hybrid
DA 2025-01-10
ER

PT J
AU Qian, Q
   Lau, KL
AF Qian, Quan
   Lau, Kit-ling
TI The effects of achievement goals and perceived reading instruction on
   Chinese student reading performance: Evidence from PISA 2018
SO JOURNAL OF RESEARCH IN READING
LA English
DT Article
DE PISA 2018; Chinese students; achievement goals; reading instructional
   practices
ID CLASSROOM ENVIRONMENT; HONG-KONG; MOTIVATION; ORIENTATION; ENGAGEMENT;
   STRATEGIES; CONTEXTS
AB Background Research has shown that achievement goals and reading instruction play important roles in students' reading performance. However, little is known about the specific effects of different types of achievement goals and reading instructional practices on reading performance in mainland China. Methods This study used Programme of International Student Assessment (PISA) 2018 data to examine the effects of Chinese students' achievement goals and perceived reading instruction on reading performance. Four districts in mainland China, Beijing, Shanghai, Jiangsu, and Zhejiang (B-S-J-Z), participated in PISA 2018. A profile of B-S-J-Z students' achievement goals and perceived reading instruction compared with those in other East Asian societies is presented. The relative contributions of different achievement goals, instructional practices at the student and school levels, and their interactive effects on reading performance are then examined by using hierarchical linear modelling. Results The results show that performance and avoidance goals are important for B-S-J-Z students' reading performance when classroom and school teaching environments are considered. The disciplinary climate, adaptative instruction and teachers' stimulation are positively related to reading performance at both the student and school levels. Some cross-level interactions between personal achievement goals and school reading instruction are found. Conclusions The findings suggest that achievement goals and reading instructional practices at both the student and school levels contribute to Chinese students' reading performance. The relationships between school reading instruction practices and students' reading performance vary for different achievement goals.
C1 [Qian, Quan; Lau, Kit-ling] Chinese Univ Hong Kong, Dept Curriculum & Instruct, Hong Kong, Peoples R China.
C3 Chinese University of Hong Kong
RP Qian, Q (corresponding author), Chinese Univ Hong Kong, Dept Curriculum & Instruct, Fac Educ, Shatin, Hong Kong, Peoples R China.
EM 422843209@qq.com
RI Qian, Quan/AAW-6995-2021; Lau, KL/IXX-1078-2023
OI Lau, Kit Ling/0000-0002-6696-6524
CR AMES C, 1992, J EDUC PSYCHOL, V84, P261, DOI 10.1037/0022-0663.84.3.261
   [Anonymous], SCI STUDIES READING, DOI [10.1207/s1532799xssr0303_2, DOI 10.1207/S1532799XSSR0303_2]
   Bakhtiarvand F, 2011, PROCD SOC BEHV, V28, DOI 10.1016/j.sbspro.2011.11.093
   Caro DH, 2016, STUD EDUC EVAL, V49, P30, DOI 10.1016/j.stueduc.2016.03.005
   Chen LH, 2009, CONTEMP EDUC PSYCHOL, V34, P298, DOI 10.1016/j.cedpsych.2009.06.006
   Chen WW, 2015, EDUC PSYCHOL-UK, V35, P714, DOI 10.1080/01443410.2014.893559
   Church MA, 2001, J EDUC PSYCHOL, V93, P43, DOI 10.1037//0022-0663.93.1.43
   De Naeghel J, 2014, READ WRIT, V27, P1547, DOI 10.1007/s11145-014-9506-3
   Duffy MC, 2015, COMPUT HUM BEHAV, V52, P338, DOI 10.1016/j.chb.2015.05.041
   Elliot AJ, 2005, J EDUC PSYCHOL, V97, P630, DOI 10.1037/0022-0663.97.4.630
   Elliot AJ, 1997, J PERS SOC PSYCHOL, V72, P218, DOI 10.1037/0022-3514.72.1.218
   Elliot AJ, 2018, INT J PSYCHOL, V53, P16, DOI 10.1002/ijop.12252
   Harackiewicz JM, 1998, EDUC PSYCHOL, V33, P1, DOI 10.1207/s15326985ep3301_1
   Hau KT, 2008, INT J PSYCHOL, V43, P865, DOI 10.1080/00207590701838030
   Hedges LV, 2007, EDUC EVAL POLICY AN, V29, P60, DOI 10.3102/0162373707299706
   Ho ESC, 2018, J RES READ, V41, P657, DOI 10.1111/1467-9817.12246
   Ho IT, 2008, INT J PSYCHOL, V43, P892, DOI 10.1080/00207590701836323
   Kaplan A, 2002, BRIT J EDUC PSYCHOL, V72, P191, DOI 10.1348/000709902158847
   Kaye MP, 2008, J SPORT EXERCISE PSY, V30, P110, DOI 10.1123/jsep.30.1.110
   Lau KL, 2008, EDUC PSYCHOL-UK, V28, P357, DOI 10.1080/01443410701612008
   Lau KL, 2016, ASIA-PAC EDUC RES, V25, P159, DOI 10.1007/s40299-015-0246-1
   Lau KC, 2017, INT J SCI EDUC, V39, P2128, DOI 10.1080/09500693.2017.1387947
   Lau S, 2008, J EDUC PSYCHOL, V100, P15, DOI 10.1037/0022-0663.100.1.15
   Lee K.H., 1996, Management Decision. Volume, V34, P65, DOI DOI 10.1108/EUM0000000004295
   Lenzi M, 2017, AM J COMMUN PSYCHOL, V60, P527, DOI 10.1002/ajcp.12174
   Linnenbrink E. A., 2004, ADV MOTIVATION ACHIE, V13, P159, DOI DOI 10.1016/S0749-7423(03)13006-3
   Linnenbrink E.A., 2001, MOTIVATION LEARNING, P251
   Linnenbrink EA, 2005, J EDUC PSYCHOL, V97, P197, DOI 10.1037/0022-0663.97.2.197
   Meece JL, 2006, ANNU REV PSYCHOL, V57, P487, DOI 10.1146/annurev.psych.56.091103.070258
   Meece JL, 2001, CONTEMP EDUC PSYCHOL, V26, P454, DOI 10.1006/ceps.2000.1071
   Murayama K, 2009, J EDUC PSYCHOL, V101, P432, DOI 10.1037/a0014221
   Newman RS, 1998, J EDUC PSYCHOL, V90, P644, DOI 10.1037/0022-0663.90.4.644
   OECD, 2019, PISA 2018 RES, VI, DOI [DOI 10.1787/B5FD1B8F-EN, 10.1787/b5fd1b8f-en]
   OECD, 2019, PISA 2018 assessment and analytical framework, DOI [DOI 10.1787/B25EFAB8-EN, 10.1787/b25efab8-en]
   OECD, 2019, PISA 2018 TECHN REP
   Peng S. L., 2017, Bulletin of Educational Psychology, V48, P371, DOI [10.6251/BEP.20160304, DOI 10.6251/BEP.20160304]
   Pintrich PR, 2000, J EDUC PSYCHOL, V92, P544, DOI 10.1037/0022-0663.92.3.544
   Ray JL, 2003, CONFLICT MANAG PEACE, V20, P1
   Rupley W.H., 2009, Reading and Writing Quarterly, V25, P119, DOI DOI 10.1080/10573560802690189
   Salili F, 2003, PSYCHOL SCHOOLS, V40, P51, DOI 10.1002/pits.10069
   Senko C, 2005, PERS SOC PSYCHOL B, V31, P1739, DOI 10.1177/0146167205281128
   Sideridis GD, 2011, J EXP EDUC, V79, P429, DOI 10.1080/00220973.2010.539634
   The Ministry of Education & People's Republic of China, 2011, CURR STAND BAS CHIN
   Urdan TC, 1997, CONTEMP EDUC PSYCHOL, V22, P165, DOI 10.1006/ceps.1997.0930
   Wang JHY, 2004, READ RES QUART, V39, P162, DOI 10.1598/RRQ.39.2.2
   Wang J, 2019, PSYCHOL SCHOOLS, V56, P1211, DOI 10.1002/pits.22271
   Watkins D., 2001, Teaching the Chinese learner: Psychological and pedagogical perspectives
   Wilson A., 2016, International Education Studies, V9, P12, DOI [10.5539/ies.v9n3p12, DOI 10.5539/IES.V9N3P12]
   Wolters CA, 2014, READ WRIT, V27, P503, DOI 10.1007/s11145-013-9454-3
   Wu XY, 2013, J EDUC PSYCHOL, V105, P622, DOI 10.1037/a0032792
   Zusho A, 2011, EDUC PSYCHOL-US, V46, P239, DOI 10.1080/00461520.2011.614526
NR 51
TC 16
Z9 17
U1 13
U2 104
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0141-0423
EI 1467-9817
J9 J RES READ
JI J. Res. Read.
PD FEB
PY 2022
VL 45
IS 1
BP 137
EP 156
DI 10.1111/1467-9817.12388
EA FEB 2022
PG 20
WC Education & Educational Research; Psychology, Educational
WE Social Science Citation Index (SSCI)
SC Education & Educational Research; Psychology
GA ZQ4QB
UT WOS:000758933700001
DA 2025-01-10
ER

PT J
AU Hall, KR
   Herbert, ME
   Sowa, SP
   Mysorekar, S
   Woznicki, SA
   Nejadhashemi, PA
   Wang, LZ
AF Hall, Kimberly R.
   Herbert, Matthew E.
   Sowa, Scott P.
   Mysorekar, Sagar
   Woznicki, Sean A.
   Nejadhashemi, Pouyan A.
   Wang, Lizhu
TI Reducing current and future risks: Using climate change scenarios to
   test an agricultural conservation framework
SO JOURNAL OF GREAT LAKES RESEARCH
LA English
DT Article
DE Climate adaptation; Climate change; Great lakes; Fish; Conservation
   outcomes; Agricultural impacts; Nutrient loading
ID UNITED-STATES; IMPACTS; FISH; SOIL; ADAPTATION; WISCONSIN; DROUGHT;
   RUNOFF; STREAM; US
AB Evaluating the potential effects of changes in climate on conservation practices can help inform strategies to protect freshwater biodiversity that are robust, even as conditions change. Here we apply a climate change "test" to a framework for estimating the amount of agricultural conservation practices needed to achieve desired fish conservation outcomes for four watersheds in the Saginaw Bay region of Michigan, USA. We developed three climate scenarios from global climate model outputs (high emissions scenario, "2080s" timeframe) to provide insight on potential impacts of a climate driver that represents a key uncertainty for this management system, the amount and timing of spring and summer precipitation. These scenarios were used as inputs to agricultural watershed models, which produced water quality outputs that we compared to thresholds in fish biodiversity metrics at the subwatershed scale. Our results suggest that impacts of climate change on evaporation rates and other aspects of hydrology will shift the relative importance of key stressors for fish (i.e., sediment loadings vs. nutrient concentrations) across these different watersheds, highlighting the need to design resilient implementation plans and policies. Overall, we found that changes in climate are likely to increase the need for agricultural conservation practices, but that increasing the implementation rate above current levels will likely remain a good investment under current and future climate conditions. (C) 2016 International Association for Great Lakes Research. Published by Elsevier B.V. All rights reserved.
C1 [Hall, Kimberly R.; Herbert, Matthew E.; Sowa, Scott P.; Mysorekar, Sagar] Nature Conservancy, 101 East Grand River Ave, Lansing, MI 48906 USA.
   [Woznicki, Sean A.; Nejadhashemi, Pouyan A.] Michigan State Univ, Dept Biosyst & Agr Engn, Farrall Agr Engn Halt 524 S Shaw Lane, E Lansing, MI 48824 USA.
   [Wang, Lizhu] Int Commiss, 100 Ouellette Ave,8th Floor, Windsor, ON N9A 6T3, Canada.
   [Woznicki, Sean A.] US EPA, Ecol & Human Community Anal Branch, Natl Exposure Res Lab, 109 TW Alexander Dr, Res Triangle Pk, NC 27711 USA.
C3 Nature Conservancy; Michigan State University; United States
   Environmental Protection Agency
RP Hall, KR (corresponding author), Nature Conservancy, 101 East Grand River Ave, Lansing, MI 48906 USA.
EM kimberly.hall@tnc.org
RI Nejadhashemi, A./AAJ-1832-2020; Wang, Lizhu/AAG-7481-2021; Herbert,
   Matt/S-2403-2019; Woznicki, Sean/ABD-9956-2020
OI Herbert, Matthew/0000-0002-8978-9145; Nejadhashemi, A.
   Pouyan/0000-0002-2502-0193; Woznicki, Sean/0000-0002-0369-2298; Hall,
   Kimberly R./0000-0002-7802-3558
FU Wildlife component of the USDA NRCS Conservation Effects Assessment
   Project [68-7482-9-512, 68-7482-11-501]; Charles Stewart Mott
   Foundation; Herbert H. and Grace A. Dow Foundation; Kresge Foundation
FX We thank the editors and two anonymous reviewers for helpful comments on
   this manuscript. We also thank Gust Annis for creating Fig. 1. Funding
   for the foundational components of this project was provided by the
   Wildlife component of the USDA NRCS Conservation Effects Assessment
   Project (Grant Agreements 68-7482-9-512 and 68-7482-11-501), the Charles
   Stewart Mott Foundation, and The Herbert H. and Grace A. Dow Foundation.
   Additional funding to address climate change was provided by Charles
   Stewart Mott Foundation and the Kresge Foundation.
CR [Anonymous], 973 MICH DEP NAT RES
   [Anonymous], 2011, SCANNING CONSERVATIO
   [Anonymous], AQ EC PLANN US PORT
   [Anonymous], 2013, OP STAND PRACT CONS
   [Anonymous], 2003, CONS IMPL CLIM CHANG
   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
   Biasutti M, 2015, HYDROL EARTH SYST SC, V19, P2945, DOI 10.5194/hess-19-2945-2015
   Bierbaum R, 2013, MITIG ADAPT STRAT GL, V18, P361, DOI 10.1007/s11027-012-9423-1
   Bosch NS, 2014, J GREAT LAKES RES, V40, P581, DOI 10.1016/j.jglr.2014.04.011
   Bosch NS, 2013, J GREAT LAKES RES, V39, P429, DOI 10.1016/j.jglr.2013.06.004
   Cross MS, 2012, ENVIRON MANAGE, V50, P341, DOI 10.1007/s00267-012-9893-7
   Dabney SM, 2012, J SOIL WATER CONSERV, V67, P343, DOI 10.2489/jswc.67.5.343
   Delgado JA, 2013, ADV AGRON, V121, P47, DOI 10.1016/B978-0-12-407685-3.00002-5
   Douglas-Mankin KR, 2013, J SOIL WATER CONSERV, V68, P41, DOI 10.2489/jswc.68.1.41
   Fales M, 2016, J GREAT LAKES RES, V42, P1372, DOI 10.1016/j.jglr.2016.09.010
   Foster G. R., 2008, USERS REFER IN PRESS
   Fowler HJ, 2007, INT J CLIMATOL, V27, P1547, DOI 10.1002/joc.1556
   Garbrecht JD, 2014, J SOIL WATER CONSERV, V69, P374, DOI 10.2489/jswc.69.5.374
   Girvetz EH, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0008320
   Groisman PY, 2012, J HYDROMETEOROL, V13, P47, DOI 10.1175/JHM-D-11-039.1
   Hall K.R., 2012, US NATL CLIMATE ASSE
   HARGREAVES GL, 1985, J IRRIG DRAIN ENG, V111, P113, DOI 10.1061/(ASCE)0733-9437(1985)111:2(113)
   Hatfield JL, 2013, MAR FRESHWATER RES, V64, P423, DOI 10.1071/MF12164
   Hay LE, 2000, J AM WATER RESOUR AS, V36, P387, DOI 10.1111/j.1752-1688.2000.tb04276.x
   John Howard Society of Ontario Standing Committee on Prison Conditions in Ontario, 2007, 2 REP BOARD REM ONT
   Kalcic MM, 2015, J AM WATER RESOUR AS, V51, P956, DOI 10.1111/1752-1688.12338
   Kalcic MM, 2015, J AM WATER RESOUR AS, V51, P973, DOI 10.1111/1752-1688.12336
   Legge JT, 2013, J SOIL WATER CONSERV, V68, P22, DOI 10.2489/jswc.68.1.22
   Lofgren BM, 2013, EARTH INTERACT, V17, DOI 10.1175/2013EI000532.1
   Lofgren BM, 2011, J GREAT LAKES RES, V37, P744, DOI 10.1016/j.jglr.2011.09.006
   Lyons J, 2010, J FISH BIOL, V77, P1867, DOI 10.1111/j.1095-8649.2010.02763.x
   Magalhaes MF, 2007, FRESHWATER BIOL, V52, P1494, DOI 10.1111/j.1365-2427.2007.01781.x
   Matthews WJ, 2003, FRESHWATER BIOL, V48, P1232, DOI 10.1046/j.1365-2427.2003.01087.x
   McDowell G, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/3/033001
   Milly PCD, 2008, SCIENCE, V319, P573, DOI 10.1126/science.1151915
   Mishra V, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2011GL050658
   Mishra V, 2010, J HYDROMETEOROL, V11, P46, DOI 10.1175/2009JHM1156.1
   Nearing MA, 2004, J SOIL WATER CONSERV, V59, P43
   Nearing MA, 2001, J SOIL WATER CONSERV, V56, P229
   Nejadhashemi AP, 2012, T ASABE, V55, P821
   Pacifici M, 2015, NAT CLIM CHANGE, V5, P215, DOI 10.1038/NCLIMATE2448
   Pryor SC, 2013, CLIM RES, V56, P61, DOI 10.3354/cr01143
   Pryor S. C., 2014, 3 NATL CLIMATE ASSES
   Sowa SP, 2016, J GREAT LAKES RES, V42, P1302, DOI 10.1016/j.jglr.2016.09.011
   Steen PJ, 2010, T AM FISH SOC, V139, P396, DOI 10.1577/T09-007.1
   Stein B A., 2014, Climate-Smart Conservation: Putting Adaptation Principles into Practice
   Tomer MD, 2014, J SOIL WATER CONSERV, V69, P365, DOI 10.2489/jswc.69.5.365
   Tomer MD, 2013, J SOIL WATER CONSERV, V68, p113A, DOI 10.2489/jswc.68.5.113A
   Trenberth KE, 2011, CLIM RES, V47, P123, DOI 10.3354/cr00953
   Wang LZ, 2011, FISHERIES, V36, P436, DOI 10.1080/03632415.2011.607075
   Watson RT, 2001, CLIMATE CHANGE 2001: IMPACTS, ADAPTATION, AND VULNERABILITY, pIX
   Whitehead PG, 2006, SCI TOTAL ENVIRON, V365, P260, DOI 10.1016/j.scitotenv.2006.02.040
   Woznicki SA, 2011, T ASABE, V54, P171
NR 54
TC 11
Z9 14
U1 1
U2 33
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0380-1330
J9 J GREAT LAKES RES
JI J. Gt. Lakes Res.
PD FEB
PY 2017
VL 43
IS 1
BP 59
EP 68
DI 10.1016/j.jglr.2016.11.005
PG 10
WC Environmental Sciences; Limnology; Marine & Freshwater Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Marine & Freshwater Biology
GA EJ5JW
UT WOS:000393255300006
OA Bronze
DA 2025-01-10
ER

PT J
AU Niles, MT
   Brown, M
   Dynes, R
AF Niles, Meredith T.
   Brown, Margaret
   Dynes, Robyn
TI Farmer's intended and actual adoption of climate change mitigation and
   adaptation strategies
SO CLIMATIC CHANGE
LA English
DT Article
ID PERCEPTIONS; KNOWLEDGE; BEHAVIOR; TECHNOLOGY; WISCONSIN; ATTITUDES;
   BARRIERS; EFFICACY; CORN
AB A growing body of work aims to understand the impacts of climate change on agriculture as well as farmer's perceptions of climate change and their likeliness to adopt adapting and mitigating behaviors. Despite this, little work has considered how intention to adopt differs from actual adoption of climate change practices in agriculture. Applying the Theory of Planned Behavior we aim to assess whether different factors affect intended versus actual adoption of climate behaviors among farmers in New Zealand. Data were collected through mixed methods (37 interviews and a telephone survey of 490 farmers) in two regions of New Zealand 2010-2012. Through multiple regression models we test hypotheses related to the Theory of Planned Behavior around the role of attitudes, subjective norms, and perceived capacity in affecting intended and actual adoption. Results suggest that there are different drivers of intended and actual adoption of climate change practices. Climate change attitudes and belief is only associated with intended not actual adoption. We find no evidence that subjective norms (climate change policy support) significantly influence either intention or actual adoption. Only perceived capacity and self-efficacy were important predictors of both intended and actual adoption. These results suggest a disconnect between intended and actual behavior change and that using data about intention as a guiding factor for program and policy design may not be prudent. Furthermore, fostering perceived capacity and self-efficacy for individuals may be crucial for encouraging both intended and actual adoption of climate adapting and mitigating behaviors.
C1 [Niles, Meredith T.] Univ Vermont, Dept Nutr & Food Sci & Food Syst Initiat, 109 Carrigan Dr,350 Marsh Life Sci Bldg, Burlington, VT 05405 USA.
   [Niles, Meredith T.] Harvard Univ, Kennedy Sch Govt, Sustainabil Sci Program, 79 JFK St,Mailbox 81, Cambridge, MA 02138 USA.
   [Brown, Margaret] Private Bag AgRes Ltd, Grasslands Res Ctr, Private Bag 11008, Palmerston North 4442, New Zealand.
   [Dynes, Robyn] AgResearch, Lincoln Res Ctr, Lincoln, NE, New Zealand.
C3 University of Vermont; Harvard University; AgResearch - New Zealand
RP Niles, MT (corresponding author), Univ Vermont, Dept Nutr & Food Sci & Food Syst Initiat, 109 Carrigan Dr,350 Marsh Life Sci Bldg, Burlington, VT 05405 USA.; Niles, MT (corresponding author), Harvard Univ, Kennedy Sch Govt, Sustainabil Sci Program, 79 JFK St,Mailbox 81, Cambridge, MA 02138 USA.
EM mtniles@uvm.edu; margaret.brown@agresearch.co.nz;
   robyn.dynes@agresearch.co.nz
OI Niles, Meredith/0000-0002-8323-1351; Dynes, Robyn/0000-0002-1740-2968
FU US National Science Foundation (NSF); US NSF IGERT grant - DGE
   [0801430]; New Zealand Foundation for Research, Science and Technology;
   AgResearch
FX Funding from the US National Science Foundation (NSF) Graduate Research
   fellowship, US NSF IGERT grant - DGE#0801430, the New Zealand Foundation
   for Research, Science and Technology, and AgResearch. We thank Mark
   Lubell and all of the farmers and stakeholders who participated in the
   project through interviews and surveys.
CR AJZEN I, 1991, ORGAN BEHAV HUM DEC, V50, P179, DOI 10.1016/0749-5978(91)90020-T
   Ajzen I, 2011, BASIC APPL SOC PSYCH, V33, P101, DOI 10.1080/01973533.2011.568834
   Arbuckle JG Jr, 2014, J SOIL WATER CONSERV, V69, P505, DOI 10.2489/jswc.69.6.505
   Arbuckle JG, 2013, CLIMATIC CHANGE, V118, P551, DOI 10.1007/s10584-013-0700-0
   Bandura A., 1986, SOCIAL FDN THOUGHT A
   Barham BL, 2004, AM J AGR ECON, V86, P61, DOI 10.1111/j.0092-5853.2004.00562.x
   Barham BL, 1996, AM J AGR ECON, V78, P1056, DOI 10.2307/1243861
   Barnes AP, 2009, AGR WATER MANAGE, V96, P1715, DOI 10.1016/j.agwat.2009.07.002
   Barnes AP, 2012, CLIMATIC CHANGE, V112, P507, DOI 10.1007/s10584-011-0226-2
   Broomell SB, 2015, GLOBAL ENVIRON CHANG, V32, P67, DOI 10.1016/j.gloenvcha.2015.03.001
   Bryan E, 2009, ENVIRON SCI POLICY, V12, P413, DOI 10.1016/j.envsci.2008.11.002
   Bullock D, 2012, ENVIRON POLIT, V21, P657, DOI 10.1080/09644016.2012.688359
   Challinor AJ, 2014, NAT CLIM CHANGE, V4, P287, DOI [10.1038/nclimate2153, 10.1038/NCLIMATE2153]
   Clark A.J., 2012, STAKEHOLDER REPORT S
   Contant C. K., 1997, American Journal of Alternative Agriculture, V12, P20, DOI 10.1017/S0889189300007153
   Costello A.B., 2005, PRACTICAL ASSESSMENT, DOI [10.7275/jyj1-4868, 10.7275/JYJ1-4868, DOI 10.7275/JYJ1-4868]
   Cox M, 2015, RANGELAND ECOL MANAG, V68, P119, DOI 10.1016/j.rama.2015.01.004
   Delgado JA, 2005, J SOIL WATER CONSERV, V60, P379
   Fickling D., 2003, GUARDIAN
   FISHER JD, 1994, HEALTH PSYCHOL, V13, P238, DOI 10.1037/0278-6133.13.3.238
   FISHER JD, 1992, PSYCHOL BULL, V111, P455, DOI 10.1037/0033-2909.111.3.455
   Fuglie K. O., 2001, Review of Agricultural Economics, V23, P386, DOI 10.1111/1467-9353.00068
   Garb Y, 2014, AGR SYST, V128, P13, DOI 10.1016/j.agsy.2014.04.003
   Greiner R, 2011, LAND USE POLICY, V28, P257, DOI 10.1016/j.landusepol.2010.06.006
   Haden VR, 2012, PLOS ONE, V7
   Hansen J, 2003, APPETITE, V41, P111, DOI 10.1016/S0195-6663(03)00079-5
   Jackson L.E., 2012, Adaptation Strategies for Agricultural Sustainability in Yolo County, P206
   Kellstedt PM, 2008, RISK ANAL, V28, P113, DOI 10.1111/j.1539-6924.2008.01010.x
   Knowler D, 2007, FOOD POLICY, V32, P25, DOI 10.1016/j.foodpol.2006.01.003
   Kristjanson P, 2012, FOOD SECUR, V4, P381, DOI 10.1007/s12571-012-0194-z
   Lorenzoni I, 2007, GLOBAL ENVIRON CHANG, V17, P445, DOI 10.1016/j.gloenvcha.2007.01.004
   Milfont TL, 2012, RISK ANAL, V32, P1003, DOI 10.1111/j.1539-6924.2012.01800.x
   Ministry for the Environment, 2013, NZ GREENH GAS INV 19
   Misovich SJ, 2003, J APPL SOC PSYCHOL, V33, P775, DOI 10.1111/j.1559-1816.2003.tb01924.x
   Mullan B., 2008, WLG200762 NAT I WAT
   National Institute for Water and Atmosphere, 2008, CLIM CHANG PROJ NZ
   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
   Nunnally J. C., 1978, Psychometric theory
   Prokopy LS, 2008, J SOIL WATER CONSERV, V63, P300, DOI 10.2489/63.5.300
   Prokopy LS, 2015, ENVIRON MANAGE, V56, P492, DOI 10.1007/s00267-015-0504-2
   Reimer AP, 2013, J SOIL WATER CONSERV, V68, P110, DOI 10.2489/jswc.68.2.110
   Rogers E.M., 2003, Diffusion of Innovations, V5th
   Ryan B, 1943, RURAL SOCIOL, V8, P15
   Semenza JC, 2008, AM J PREV MED, V35, P479, DOI 10.1016/j.amepre.2008.08.020
   Seo SN, 2008, ECOL ECON, V67, P109, DOI 10.1016/j.ecolecon.2007.12.007
   Smith N, 2014, RISK ANAL, V34, P937, DOI 10.1111/risa.12140
   Smith P, 2014, CLIMATE CHANGE 2014: MITIGATION OF CLIMATE CHANGE, P811
   Spence A, 2011, NAT CLIM CHANGE, V1, P46, DOI [10.1038/nclimate1059, 10.1038/NCLIMATE1059]
   Wood SA, 2014, GLOBAL ENVIRON CHANG, V25, P163, DOI 10.1016/j.gloenvcha.2013.12.011
   Zahran S, 2006, SOC NATUR RESOUR, V19, P771, DOI 10.1080/08941920600835528
NR 51
TC 160
Z9 176
U1 6
U2 79
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 MAR
PY 2016
VL 135
IS 2
BP 277
EP 295
DI 10.1007/s10584-015-1558-0
PG 19
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 DL2LI
UT WOS:000375465900006
OA hybrid
DA 2025-01-10
ER

PT J
AU Lovegrove, BG
AF Lovegrove, Barry G.
TI The evolution of mammalian body temperature: the Cenozoic
   supraendothermic pulses
SO JOURNAL OF COMPARATIVE PHYSIOLOGY B-BIOCHEMICAL SYSTEMIC AND
   ENVIRONMENTAL PHYSIOLOGY
LA English
DT Article
DE Body temperature; Mammals; Cursors; Supraendothermy; Metatarsal:femur
ID BASAL METABOLIC-RATE; MAXIMAL RUNNING SPEED; TERRESTRIAL MAMMALS; SHREWS
   MAMMALIA; ENDOTHERMY; MASS; VERTEBRATES; SORICIDAE; CONTINUUM; CLIMATE
AB In this study, I investigated the source(s) of variation in the body temperatures of mammals. I also attempted to reconstruct ancestral normothermic rest-phase body temperature states using a maximum parsimony approach. Body temperature at the familial level is not correlated with body mass. For small mammals, except the Macroscelidae, previously identified correlates, such as climate adaptation and zoogeography explained some, but not all, T (b) apomorphies. At the species level in large cursorial mammals, there was a significant correlation between body temperature and the ratio between metatarsal length and femur length, the proxy for stride length and cursoriality. With the exception of two primate families, all supraendothermic (T (b) > 37.9A degrees C) mammals are cursorial, including Artiodactyla, Lagomorpha, some large Rodentia, and Carnivora. The ruminant supraendothermic cursorial pulse is putatively associated with global cooling and vegetation changes following the Paleocene-Eocene Thermal Maximum. Reconstructed ancestral body temperatures were highly unrealistic deep within the mammalian phylogeny because of the lack of fossil T (b) data that effectively creates ghost lineages. However, it is anticipated that the method of estimating body temperature from the abundance of C-13-O-18 bonds in the carbonate component of tooth bioapatite in both extant and extinct animals may be a very promising tool for estimating the T (b) of extinct mammals. Fossil T (b) data are essential for discerning derived T (b) reversals from ancestral states, and verifying the dates of supraendothermic pulses.
C1 Univ KwaZulu Natal, Sch Biol & Conservat Sci, ZA-3209 Scottsville, South Africa.
C3 University of Kwazulu Natal
RP Lovegrove, BG (corresponding author), Univ KwaZulu Natal, Sch Biol & Conservat Sci, Private Bag X01, ZA-3209 Scottsville, South Africa.
EM lovegrove@ukzn.ac.za
RI Lovegrove, Barry/D-1320-2009
FU University of KwaZulu-Natal; National Research Foundation
FX This research was financed by publication incentive grants from the
   University of KwaZulu-Natal and the National Research Foundation.
CR Alroy J, 1998, SCIENCE, V280, P731, DOI 10.1126/science.280.5364.731
   [Anonymous], 2001, Biostatistical analysis
   Asher RJ, 2005, SCIENCE, V307, P1091, DOI 10.1126/science.1107808
   BENNETT AF, 1979, SCIENCE, V206, P649, DOI 10.1126/science.493968
   Bininda-Emonds ORP, 2007, NATURE, V446, P507, DOI 10.1038/nature05634
   Blomberg SP, 2003, EVOLUTION, V57, P717, DOI 10.1111/j.0014-3820.2003.tb00285.x
   Carrano MT, 1999, J ZOOL, V247, P29, DOI 10.1111/j.1469-7998.1999.tb00190.x
   Clarke A, 2010, BIOL REV, V85, P703, DOI 10.1111/j.1469-185X.2010.00122.x
   Clarke A, 2010, J ANIM ECOL, V79, P610, DOI 10.1111/j.1365-2656.2010.01672.x
   CROMPTON AW, 1978, NATURE, V272, P333, DOI 10.1038/272333a0
   Dubey S, 2007, MOL PHYLOGENET EVOL, V44, P126, DOI 10.1016/j.ympev.2006.12.002
   Eagle RA, 2011, SCIENCE, V333, P443, DOI 10.1126/science.1206196
   Eagle RA, 2010, P NATL ACAD SCI USA, V107, P10377, DOI 10.1073/pnas.0911115107
   Farmer CG, 2003, AM NAT, V162, P826, DOI 10.1086/380922
   Finarelli JA, 2006, SYST BIOL, V55, P301, DOI 10.1080/10635150500541698
   GARLAND T, 1983, J ZOOL, V199, P157, DOI 10.1111/j.1469-7998.1983.tb02087.x
   GARLAND T, 1993, J ZOOL, V229, P133, DOI 10.1111/j.1469-7998.1993.tb02626.x
   Garland T, 2000, AM NAT, V155, P346, DOI 10.1086/303327
   Harvey PH, 1991, COMP METHOD EVOLUTIO
   HEINRICH B, 1977, AM NAT, V111, P623, DOI 10.1086/283196
   Iriarte-Díaz J, 2002, J EXP BIOL, V205, P2897
   Janis Christine M., 1993, Journal of Mammalian Evolution, V1, P103, DOI 10.1007/BF01041590
   JANIS CM, 1993, ANNU REV ECOL SYST, V24, P467, DOI 10.1146/annurev.es.24.110193.002343
   Kemp TS, 2006, ZOOL J LINN SOC-LOND, V147, P473, DOI 10.1111/j.1096-3642.2006.00226.x
   Koteja P, 2004, PHYSIOL BIOCHEM ZOOL, V77, P1043, DOI 10.1086/423741
   Lavin SR, 2008, PHYSIOL BIOCHEM ZOOL, V81, P526, DOI 10.1086/590395
   Lovegrove BG, 2012, BIOL REV, V87, P128, DOI 10.1111/j.1469-185X.2011.00188.x
   Lovegrove BG, 2004, PHYSIOL BIOCHEM ZOOL, V77, P916, DOI 10.1086/425189
   Lovegrove BG, 2005, J COMP PHYSIOL B, V175, P231, DOI 10.1007/s00360-005-0477-1
   Lovegrove BG, 2003, J COMP PHYSIOL B, V173, P87, DOI 10.1007/s00360-002-0309-5
   Lovegrove BG, 2000, AM NAT, V156, P201, DOI 10.1086/303383
   Luo ZX, 2007, NATURE, V450, P1011, DOI 10.1038/nature06277
   Maddison W.P., 2019, Mesquite Project. Mesquite: A modular system for evolutionary analysis
   Matsui A, 2009, GENE, V441, P53, DOI 10.1016/j.gene.2008.08.024
   Refinetti R, 2010, FRONT BIOSCI-LANDMRK, V15, P564, DOI 10.2741/3634
   Rosa MGP, 1996, BRAIN BEHAV EVOLUT, V48, P121, DOI 10.1159/000113191
   Rowe TB, 2011, SCIENCE, V332, P955, DOI 10.1126/science.1203117
   Schmidt-Nielsen K, 1983, ANIMAL PHYSL ADAPTAT
   SPARTI A, 1992, PHYSIOL ZOOL, V65, P77, DOI 10.1086/physzool.65.1.30158240
   SPARTI A, 1990, COMP BIOCHEM PHYS A, V97, P391, DOI 10.1016/0300-9629(90)90629-7
   Withers PC, 2006, PHYSIOL BIOCHEM ZOOL, V79, P437, DOI 10.1086/501063
   Zachos J, 2001, SCIENCE, V292, P686, DOI 10.1126/science.1059412
NR 42
TC 28
Z9 32
U1 1
U2 35
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 0174-1578
EI 1432-136X
J9 J COMP PHYSIOL B
JI J. Comp. Physiol. B-Biochem. Syst. Environ. Physiol.
PD MAY
PY 2012
VL 182
IS 4
BP 579
EP 589
DI 10.1007/s00360-011-0642-7
PG 11
WC Physiology; Zoology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Physiology; Zoology
GA 929KR
UT WOS:000303061800010
PM 22234475
DA 2025-01-10
ER

PT J
AU Li, BZ
   Yu, W
   Liu, M
   Li, N
AF Li, Baizhan
   Yu, Wei
   Liu, Meng
   Li, Nan
TI Climatic Strategies of Indoor Thermal Environment for Residential
   Buildings in Yangtze River Region, China
SO INDOOR AND BUILT ENVIRONMENT
LA English
DT Article
DE Indoor thermal environment; Thermal comfort; Thermoneutral temperature;
   Building energy efficiency; Yangtze River Valley; Residential building
ID NATURAL VENTILATION; ADAPTIVE MODEL; COMFORT; TEMPERATURE; ASHRAE;
   ZONES; PMV
AB Yangtze River Valley is situated within the Hot Summer and Cold Winter zone, and residents in this region of China would require HVAC system to alleviate thermal comfort conditions, although this is tempered by the Design Code (DBJ50-071-2007) for energy efficiency. A 1-year survey of about 200 residential homes was carried out in eight cities covering the breadth of the region. The acceptable temperature range for the residents in this area was 16.3-28.1 degrees C and the thermal neutral temperature was found to be 27.6 degrees C in summers and 17.5 degrees C in winters. People in different area can vary in their adaptability and comfortableness. Therefore, there is a need to investigate the national comfort parameter introduced in the Code for Design of Heating and Ventilation and Air Conditioning (GB50019-2003). The results found that if air-conditioning system was set to 27.5 degrees C instead of 26 degrees C as required by GBJ19-87: Design Standard of Heating and Ventilation and Air Conditioning, a 16.5% saving of energy consumption could be achieved. The findings demonstrated the role of natural ventilation in the expansion of the thermal comfort zone for the residents, especially during the summer seasons. A climatic adaptability model has been established by this study to contribute to the passive climatic design strategies for a better economic and energy efficiency of buildings.
C1 [Yu, Wei] Chongqing Univ, Fac Urban Construct & Environm Engn, Key Lab Gorges Reservoir Reg Ecoenvironm 3, Minist Educ, Chongqing 400045, Peoples R China.
C3 Chongqing University
RP Yu, W (corresponding author), Chongqing Univ, Fac Urban Construct & Environm Engn, Key Lab Gorges Reservoir Reg Ecoenvironm 3, Minist Educ, Chongqing 400045, Peoples R China.
EM yuweixscq@126.com
RI li, bz/GVR-7133-2022
FU National Natural Science Foundation of China [50838009, 50678179];
   National Key Technologies R&D Program of China [2006BAJ01A05]; CSTC
   [2008AB7110]
FX This paper is based on research projects (50838009 and 50678179) funded
   by the National Natural Science Foundation of China; also funding of the
   Project (2006BAJ01A05) by the National Key Technologies R&D Program of
   China and Project (CSTC, 2008AB7110) by the Key Technologies R&D Program
   of Chongqing, China.
CR Auliciems A., 1986, ARCHIT SCI REV, V29, P67
   Budaiwi I, 2009, INDOOR BUILT ENVIRON, V18, P52, DOI 10.1177/1420326X08101531
   Chan MY, 2008, INDOOR BUILT ENVIRON, V17, P516, DOI 10.1177/1420326X08097388
   Chiang CM, 2009, INDOOR BUILT ENVIRON, V18, P346, DOI 10.1177/1420326X09337047
   *CHIN URB RES COMM, 2008, GREEN BUILD
   CHMUTINA K, 2010, 67 U NOTT CHIN POL I
   *CMA MET INF CTR, 2005, DED MET DAT SET AN B
   Daghigh R, 2009, INDOOR BUILT ENVIRON, V18, P113, DOI 10.1177/1420326X09103013
   De Dear R., 1998, ASHRAE Trans, V104, P145
   de Dear RJ, 2002, ENERG BUILDINGS, V34, P549, DOI 10.1016/S0378-7788(02)00005-1
   Fanger PO, 2002, ENERG BUILDINGS, V34, P533
   Fong KF, 2010, INDOOR BUILT ENVIRON, V19, P375, DOI 10.1177/1420326X09347427
   Humphreys M.A., 1978, Building Research and Practice, V6, P92, DOI [10.1080/09613217808550656, DOI 10.1080/09613217808550656]
   Hwang RL, 2006, ENERG BUILDINGS, V38, P53, DOI 10.1016/j.enbuild.2005.05.001
   JONES WP, 1985, FUNDAMENTAL PROPERTI, P4
   Lam JC, 2005, BUILD ENVIRON, V40, P277, DOI 10.1016/j.buildenv.2004.07.005
   LI B, 2003, J CHONGQING U ENGLIS, V10, P61
   Li BZ, 2010, INDOOR BUILT ENVIRON, V19, P405, DOI 10.1177/1420326X10377545
   Li BZ, 2010, INDOOR BUILT ENVIRON, V19, P221, DOI 10.1177/1420326X10365213
   Li BZ, 2009, RENEW ENERG, V34, P1994, DOI 10.1016/j.renene.2009.02.015
   [李楠 LI Nan], 2009, [重庆大学学报, Journal of Chongqing University], V32, P736
   Mui KWH, 2003, BUILD ENVIRON, V38, P837, DOI 10.1016/S0360-1323(03)00020-9
   Nicol F, 2004, ENERG BUILDINGS, V36, P628, DOI 10.1016/j.enbuild.2004.01.016
   Nicol JF, 2002, ENERG BUILDINGS, V34, P563, DOI 10.1016/S0378-7788(02)00006-3
   Park CS, 2008, INDOOR BUILT ENVIRON, V17, P324, DOI 10.1177/1420326X08093949
   *SAC, 1993, 5017893 SAC GB
   *TSINGH U BUILD EN, 2009, ANN DEV REP BUILD EN
   von Grabe J, 2008, INDOOR BUILT ENVIRON, V17, P103, DOI 10.1177/1420326X08089364
   Wong LT, 2009, INDOOR BUILT ENVIRON, V18, P336, DOI 10.1177/1420326X09337044
   Yang JH, 2009, INDOOR BUILT ENVIRON, V18, P301, DOI 10.1177/1420326X09105719
   Yang W., 2006, HV AC, V36, P95
   YAO R, 2003, J CHONGQING U ENGLIS, V10, P41
   Yao RM, 2009, RENEW ENERG, V34, P2697, DOI 10.1016/j.renene.2009.05.015
   Yao RM, 2009, BUILD ENVIRON, V44, P2089, DOI 10.1016/j.buildenv.2009.02.014
   Ye XJ, 2006, INDOOR AIR, V16, P320, DOI 10.1111/j.1600-0668.2006.00434.x
   Yik FWH, 2010, INDOOR BUILT ENVIRON, V19, P73, DOI 10.1177/1420326X09358021
   YIK WH, 1989, FAR E C ASHRAE, P78
   ZHANG M, CHINA NEEDS ENERGY E
NR 38
TC 67
Z9 69
U1 0
U2 67
PU SAGE PUBLICATIONS LTD
PI LONDON
PA 1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND
SN 1420-326X
EI 1423-0070
J9 INDOOR BUILT ENVIRON
JI Indoor Built Environ.
PD FEB
PY 2011
VL 20
IS 1
BP 101
EP 111
DI 10.1177/1420326X10394495
PG 11
WC Construction & Building Technology; Engineering, Environmental; Public,
   Environmental & Occupational Health
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Engineering; Public, Environmental &
   Occupational Health
GA 734HS
UT WOS:000288325800011
DA 2025-01-10
ER

PT J
AU Sun, C
   Southard, C
   Witonsky, DB
   Kittler, R
   Di Rienzo, A
AF Sun, Chang
   Southard, Catherine
   Witonsky, David B.
   Kittler, Ralf
   Di Rienzo, Anna
TI Allele-Specific Down-Regulation of <i>RPTOR</i> Expression Induced by
   Retinoids Contributes to Climate Adaptations
SO PLOS GENETICS
LA English
DT Article
ID UNCOUPLING PROTEIN GENE; GENOME SEQUENCE VARIATION; POSITIVE SELECTION;
   MAMMALIAN TARGET; RAPAMYCIN MTOR; NATURAL-SELECTION; SOFT SWEEPS; TOS
   MOTIF; ACID; RAPTOR
AB The mechanistic target of rapamycin (MTOR) pathway regulates cell growth, energy homeostasis, apoptosis, and immune response. The regulatory associated protein of MTOR encoded by the RPTOR gene is a key component of this pathway. A previous survey of candidate genes found that RPTOR contains multiple SNPs with strong correlations between allele frequencies and climate variables, consistent with the action of selective pressures that vary across environments. Using data from a recent genome scan for selection signals, we honed in on a SNP (rs11868112) 26 kb upstream to the transcription start site of RPTOR that exhibits the strongest association with temperature variables. Transcription factor motif scanning and mining of recently mapped transcription factor binding sites identified a binding site for POU class 2 homeobox 1 (POU2F1) spanning the SNP and an adjacent retinoid acid receptor (RAR) binding site. Using expression quantification, chromatin immunoprecipitation (ChIP), and reporter gene assays, we demonstrate that POU2F1 and RARA do bind upstream of the RPTOR gene to regulate its expression in response to retinoids; this regulation is affected by the allele status at rs11868112 with the derived allele resulting in lower expression levels. We propose a model in which the derived allele influences thermogenesis or immune response by altering MTOR pathway activity and thereby increasing fitness in colder climates. Our results show that signatures of genetic adaptations can identify variants with functional effects, consistent with the idea that selection signals may be used for SNP annotation.
C1 [Sun, Chang; Southard, Catherine; Witonsky, David B.; Kittler, Ralf; Di Rienzo, Anna] Univ Chicago, Dept Human Genet, Chicago, IL 60637 USA.
C3 University of Chicago
RP Sun, C (corresponding author), Univ Chicago, Dept Human Genet, Chicago, IL 60637 USA.
EM dirienzo@bsd.uchicago.edu
RI Kittler, Ralf/AAD-4258-2020; Sun, Chang/I-6326-2012; Kittler,
   Ralf/I-4662-2013
OI Di Rienzo, Anna/0000-0002-8982-9098; Kittler, Ralf/0000-0002-0098-6792
FU NIH [U01 GM61393, DK056670]
FX This work was supported in part by NIH grants U01 GM61393 and DK056670.
   The funders had no role in study design, data collection and analysis,
   decision to publish, or preparation of the manuscript.
CR Akey JM, 2009, GENOME RES, V19, P711, DOI 10.1101/gr.086652.108
   ALVAREZ R, 1995, J BIOL CHEM, V270, P5666, DOI 10.1074/jbc.270.10.5666
   [Anonymous], 1877, Radical Review
   Baab KL, 2010, AM J PHYS ANTHROPOL, V141, P97, DOI 10.1002/ajpa.21120
   Bentzinger CF, 2008, CELL METAB, V8, P411, DOI 10.1016/j.cmet.2008.10.002
   Bergmann KGLC., 1847, Gttinger Studien, V3, P595
   Biswas S, 2006, TRENDS GENET, V22, P437, DOI 10.1016/j.tig.2006.06.005
   Brooks SC, 1996, BLOOD, V87, P227
   Cavalli-Sforza LL, 2003, NAT GENET, V33, P266, DOI 10.1038/ng1113
   Choi KM, 2003, J BIOL CHEM, V278, P19667, DOI 10.1074/jbc.M301142200
   Coop G, 2010, GENETICS, V185, P1411, DOI 10.1534/genetics.110.114819
   Cunningham JT, 2007, NATURE, V450, P736, DOI 10.1038/nature06322
   Fernandez D, 2010, DISCOV MED, V9, P173
   Freemantle SJ, 2002, ONCOGENE, V21, P2880, DOI 10.1038/sj.onc.1205408
   Garrigan D, 2006, NAT REV GENET, V7, P669, DOI 10.1038/nrg1941
   Guernier V, 2004, PLOS BIOL, V2, P740, DOI 10.1371/journal.pbio.0020141
   Hancock AM, 2008, PLOS GENET, V4, DOI 10.1371/journal.pgen.0040032
   Hara K, 2002, CELL, V110, P177, DOI 10.1016/S0092-8674(02)00833-4
   Hermisson J, 2005, GENETICS, V169, P2335, DOI 10.1534/genetics.104.036947
   Hua SJ, 2009, CELL, V137, P1259, DOI 10.1016/j.cell.2009.04.043
   Hudson RR, 2002, BIOINFORMATICS, V18, P337, DOI 10.1093/bioinformatics/18.2.337
   Jablonski NG, 2000, J HUM EVOL, V39, P57, DOI 10.1006/jhev.2000.0403
   Ji LD, 2010, J PINEAL RES, V48, P133, DOI 10.1111/j.1600-079X.2009.00736.x
   Katzmarzyk PT, 1998, AM J PHYS ANTHROPOL, V106, P483, DOI 10.1002/(SICI)1096-8644(199808)106:4<483::AID-AJPA4>3.3.CO;2-K
   Kelley JL, 2008, ANNU REV GENOM HUM G, V9, P143, DOI 10.1146/annurev.genom.9.081307.164411
   Kim DH, 2002, CELL, V110, P163, DOI 10.1016/S0092-8674(02)00808-5
   Laplante M, 2009, J CELL SCI, V122, P3589, DOI 10.1242/jcs.051011
   Larose M, 1996, J BIOL CHEM, V271, P31533, DOI 10.1074/jbc.271.49.31533
   Leonard WR, 2002, AM J HUM BIOL, V14, P609, DOI 10.1002/ajhb.10072
   Liu WQ, 2005, CANCER RES, V65, P46
   Luca F, 2009, PLOS GENET, V5, DOI 10.1371/journal.pgen.1000489
   Mercader J, 2006, ENDOCRINOLOGY, V147, P5325, DOI 10.1210/en.2006-0760
   Nielsen R, 2007, NAT REV GENET, V8, P857, DOI 10.1038/nrg2187
   Nojima H, 2003, J BIOL CHEM, V278, P15461, DOI 10.1074/jbc.C200665200
   Novembre J, 2009, NAT REV GENET, V10, P745, DOI 10.1038/nrg2632
   Polak P, 2008, CELL METAB, V8, P399, DOI 10.1016/j.cmet.2008.09.003
   Pritchard JK, 2010, CURR BIOL, V20, pR208, DOI 10.1016/j.cub.2009.11.055
   Przeworski M, 2005, EVOLUTION, V59, P2312, DOI 10.1554/05-273.1
   Rabelo R, 1996, ENDOCRINOLOGY, V137, P3488, DOI 10.1210/en.137.8.3488
   Ramanathan A, 2009, P NATL ACAD SCI USA, V106, P22229, DOI 10.1073/pnas.0912074106
   Reich DE, 2002, NAT GENET, V32, P135, DOI 10.1038/ng947
   Roberts DF, 1953, AM J PHYS ANTHROP-NE, V11, P533, DOI 10.1002/ajpa.1330110404
   Sabeti PC, 2006, SCIENCE, V312, P1614, DOI 10.1126/science.1124309
   Sabeti PC, 2002, NATURE, V419, P832, DOI 10.1038/nature01140
   Sachidanandam R, 2001, NATURE, V409, P928, DOI 10.1038/35057149
   Schaim SS, 2003, CURR BIOL, V13, P797, DOI 10.1016/S0960-9822(03)00329-4
   Schieke SM, 2006, J BIOL CHEM, V281, P27643, DOI 10.1074/jbc.M603536200
   Shi H, 2009, AM J HUM GENET, V84, P534, DOI 10.1016/j.ajhg.2009.03.009
   Soprano DR, 2004, ANNU REV NUTR, V24, P201, DOI 10.1146/annurev.nutr.24.012003.132407
   Stephens M, 2006, NAT GENET, V38, P375, DOI 10.1038/ng1746
   Sun C, 2009, MUTAT RES-FUND MOL M, V662, P88, DOI 10.1016/j.mrfmmm.2009.01.001
   TAJIMA F, 1989, GENETICS, V123, P585
   TAJIMA F, 1983, GENETICS, V105, P437
   Teshima KM, 2006, GENETICS, V172, P713, DOI 10.1534/genetics.105.044065
   Thompson EE, 2004, AM J HUM GENET, V75, P1059, DOI 10.1086/426406
   Tsang CK, 2007, DRUG DISCOV TODAY, V12, P112, DOI 10.1016/j.drudis.2006.12.008
   Voight BF, 2006, PLOS BIOL, V4, P446, DOI 10.1371/journal.pbio.0040072
   Voight BF, 2005, P NATL ACAD SCI USA, V102, P18508, DOI 10.1073/pnas.0507325102
   Wang JR, 2004, MOL CELL BIOL, V24, P2423, DOI 10.1128/MCB.24.6.2423-2443.2004
   WATTERSON GA, 1975, THEOR POPUL BIOL, V7, P256, DOI 10.1016/0040-5809(75)90020-9
   Weichhart T, 2009, TRENDS IMMUNOL, V30, P218, DOI 10.1016/j.it.2009.02.002
   Wullschleger S, 2006, CELL, V124, P471, DOI 10.1016/j.cell.2006.01.016
   Xu DS, 2003, NEURON, V39, P513, DOI 10.1016/S0896-6273(03)00463-X
   Young DA, 2005, CURR OPIN PHARMACOL, V5, P418, DOI 10.1016/j.coph.2005.03.004
   Young JH, 2005, PLOS GENET, V1, P730, DOI 10.1371/journal.pgen.0010082
NR 65
TC 20
Z9 20
U1 0
U2 5
PU PUBLIC LIBRARY SCIENCE
PI SAN FRANCISCO
PA 1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA
SN 1553-7404
J9 PLOS GENET
JI PLoS Genet.
PD OCT
PY 2010
VL 6
IS 10
AR e1001178
DI 10.1371/journal.pgen.1001178
PG 10
WC Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Genetics & Heredity
GA 673GP
UT WOS:000283647800010
PM 21060808
OA Green Submitted, gold, Green Published
DA 2025-01-10
ER

PT J
AU McKay, JK
   Richards, JH
   Nemali, KS
   Sen, S
   Mitchell-Olds, T
   Boles, S
   Stahl, EA
   Wayne, T
   Juenger, TE
AF McKay, John K.
   Richards, James H.
   Nemali, Krishna S.
   Sen, Saunak
   Mitchell-Olds, Thomas
   Boles, Sandra
   Stahl, Eli A.
   Wayne, Tierney
   Juenger, Thomas E.
TI GENETICS OF DROUGHT ADAPTATION IN <i>ARABIDOPSIS THALIANA</i> II. QTL
   ANALYSIS OF A NEW MAPPING POPULATION, KAS-1 x TSU-1
SO EVOLUTION
LA English
DT Article
DE Adaptation; Arabidopsis thaliana; carbon isotope ratio; correlated
   traits; drought avoidance; drought escape; drought tolerance;
   transpiration; water-use efficiency
ID CARBON-ISOTOPE DISCRIMINATION; WATER-USE EFFICIENCY; TRANSPIRATION
   EFFICIENCY; STOMATAL CONDUCTANCE; CAUSAL RELATIONSHIPS; MICROSATELLITE
   LOCI; REPRODUCTIVE STAGE; LATITUDINAL CLINE; STRESS TOLERANCE;
   PLANT-RESPONSES
AB Despite compelling evidence that adaptation to local climate is common in plant populations, little is known about the evolutionary genetics of traits that contribute to climatic adaptation. A screen of natural accessions of Arabidopsis thaliana revealed Tsu-1 and Kas-1 to be opposite extremes for water-use efficiency and climate at collection sites for these accessions differs greatly. To provide a tool to understand the genetic basis of this putative adaptation, Kas-1 and Tsu-1 were reciprocally crossed to create a new mapping population. Analysis of F-3 families showed segregating variation in both delta C-13 and transpiration rate, and as expected these traits had a negative genetic correlation (r(g) = - 0.3). 346 RILs, 148 with Kas-1 cytoplasm and 198 with Tsu-1 cytoplasm, were advanced to the F-9 and genotyped using 48 microsatellites and 55 SNPs for a total of 103 markers. This mapping population was used for QTL analysis of delta C-13 using F-9 RIL means. Analysis of this reciprocal cross showed a large effect of cytoplasmic background, as well as two QTL for delta C-13. The Kas-1 x Tsu-1 mapping population provides a powerful new resource for mapping QTL underlying natural variation and for dissecting the genetic basis of water-use efficiency differences.
C1 [McKay, John K.] Colorado State Univ, Dept Bioagr Sci, Ft Collins, CO 80523 USA.
   [McKay, John K.] Colorado State Univ, Grad Degree Program Ecol, Ft Collins, CO 80523 USA.
   [Richards, James H.; Nemali, Krishna S.] Univ Calif Davis, Dept Land Air & Water Resources, Davis, CA 95616 USA.
   [Sen, Saunak] Univ Calif San Francisco, Dept Epidemiol & Biostat, San Francisco, CA 94143 USA.
   [Mitchell-Olds, Thomas; Boles, Sandra] Duke Univ, Dept Biol, Durham, NC 27708 USA.
   [Stahl, Eli A.] Univ Massachusetts Dartmouth, Dept Biol, N Dartmouth, MA 02747 USA.
   [Wayne, Tierney; Juenger, Thomas E.] Univ Texas Austin, Sect Integrat Biol, Austin, TX 78712 USA.
   [Wayne, Tierney; Juenger, Thomas E.] Univ Texas Austin, Inst Cellular & Mol Biol, Austin, TX 78712 USA.
C3 Colorado State University; Colorado State University; University of
   California System; University of California Davis; University of
   California System; University of California San Francisco; Duke
   University; University of Massachusetts System; University Massachusetts
   Dartmouth; University of Texas System; University of Texas Austin;
   University of Texas System; University of Texas Austin
RP McKay, JK (corresponding author), Colorado State Univ, Dept Bioagr Sci, Ft Collins, CO 80523 USA.
EM jkmckay@colostate.edu
RI McKay, John/K-3875-2012; Mitchell-Olds, Thomas/K-8121-2012
OI Mitchell-Olds, Thomas/0000-0003-3439-9921; McKay,
   John/0000-0003-4311-5513
FU U. S. National Science Foundation [DEB 0420111, DEB 0419969, 0618302];
   Direct For Biological Sciences; Division Of Environmental Biology
   [0618302] Funding Source: National Science Foundation
FX We thank O. Ervin for help with phenotyping experiments. This work was
   supported by the U. S. National Science Foundation (DEB 0420111, DEB
   0419969, 0618302), the California Agricultural Experiment Station, and
   the Colorado Agricultural Experiment Station.
CR [Anonymous], 2008, Plant Physiological Ecology
   Araus JL, 2002, ANN BOT-LONDON, V89, P925, DOI 10.1093/aob/mcf049
   Barton NH, 2002, NAT REV GENET, V3, P11, DOI 10.1038/nrg700
   BARTON NH, 1989, ANNU REV GENET, V23, P337, DOI 10.1146/annurev.ge.23.120189.002005
   BELL CJ, 1994, GENOMICS, V19, P137, DOI 10.1006/geno.1994.1023
   BOHNERT HJ, 1995, PLANT CELL, V7, P1099, DOI 10.1105/tpc.7.7.1099
   BOYER JS, 1982, SCIENCE, V218, P443, DOI 10.1126/science.218.4571.443
   Bray EA, 2004, J EXP BOT, V55, P2331, DOI 10.1093/jxb/erh270
   Bray EA, 1997, TRENDS PLANT SCI, V2, P48, DOI 10.1016/S1360-1385(97)82562-9
   Broman KW, 2003, BIOINFORMATICS, V19, P889, DOI 10.1093/bioinformatics/btg112
   Buckley TN, 2002, PROG BOT, V63, P309
   Caicedo AL, 2004, P NATL ACAD SCI USA, V101, P15670, DOI 10.1073/pnas.0406232101
   Chaves MM, 2004, J EXP BOT, V55, P2365, DOI 10.1093/jxb/erh269
   Chaves MM, 2003, FUNCT PLANT BIOL, V30, P239, DOI 10.1071/FP02076
   Christman MA, 2008, PLANT CELL ENVIRON, V31, P1170, DOI 10.1111/j.1365-3040.2008.01833.x
   CHURCHILL GA, 1994, GENETICS, V138, P963
   Clark RM, 2007, SCIENCE, V317, P338, DOI 10.1126/science.1138632
   COMSTOCK JP, 1992, P NATL ACAD SCI USA, V89, P7747, DOI 10.1073/pnas.89.16.7747
   Comstock JP, 2005, FUNCT PLANT BIOL, V32, P1089, DOI 10.1071/FP05117
   Comstock JP, 2002, J EXP BOT, V53, P195, DOI 10.1093/jexbot/53.367.195
   Condon AG, 2004, J EXP BOT, V55, P2447, DOI 10.1093/jxb/erh277
   Condon AG, 2002, CROP SCI, V42, P122, DOI 10.2135/cropsci2002.0122
   Dawson TE, 2002, ANNU REV ECOL SYST, V33, P507, DOI 10.1146/annurev.ecolsys.33.020602.095451
   Doerge RW, 1996, GENETICS, V142, P285
   Dudley SA, 1996, EVOLUTION, V50, P92, DOI 10.1111/j.1558-5646.1996.tb04475.x
   EHLERINGER JR, 1993, ANNU REV ECOL SYST, V24, P411, DOI 10.1146/annurev.es.24.110193.002211
   FARQUHAR GD, 1989, ANNU REV PLANT PHYS, V40, P503, DOI 10.1146/annurev.pp.40.060189.002443
   FARQUHAR GD, 1982, AUST J PLANT PHYSIOL, V9, P121, DOI 10.1071/PP9820121
   FARQUHAR GD, 1982, OECOLOGIA, V52, P121, DOI 10.1007/BF00349020
   Feder ME, 2003, NAT REV GENET, V4, P651, DOI 10.1038/nrg1128
   Fischer RA, 1998, CROP SCI, V38, P1467, DOI 10.2135/cropsci1998.0011183X003800060011x
   Fujita Y, 2005, PLANT CELL, V17, P3470, DOI 10.1105/tpc.105.035659
   Geber MA, 1997, OECOLOGIA, V109, P535, DOI 10.1007/s004420050114
   Gleick P.H., 1998, WORLDS WATER 1998 19
   Hausmann NJ, 2005, EVOLUTION, V59, P81
   Heschel MS, 2005, AM J BOT, V92, P37, DOI 10.3732/ajb.92.1.37
   Heschel MS, 2002, INT J PLANT SCI, V163, P907, DOI 10.1086/342519
   HUBICK KT, 1986, AUST J PLANT PHYSIOL, V13, P803, DOI 10.1071/PP9860803
   Johanson U, 2000, SCIENCE, V290, P344, DOI 10.1126/science.290.5490.344
   Juenger TE, 2006, MOL ECOL, V15, P1351, DOI 10.1111/j.1365-294X.2006.02774.x
   Juenger TE, 2005, PLANT CELL ENVIRON, V28, P697, DOI 10.1111/j.1365-3040.2004.01313.x
   Kawaguchi R, 2004, PLANT J, V38, P823, DOI 10.1111/j.1365-313X.2004.02090.x
   Kreps JA, 2002, PLANT PHYSIOL, V130, P2129, DOI 10.1104/pp.008532
   Lambrides CJ, 2004, CROP SCI, V44, P1642, DOI 10.2135/cropsci2004.1642
   Lanceras JC, 2004, PLANT PHYSIOL, V135, P384, DOI 10.1104/pp.103.035527
   LEBRETON C, 1995, J EXP BOT, V46, P853, DOI 10.1093/jxb/46.7.853
   LUDLOW MM, 1990, ADV AGRON, V43, P107
   LUDLOW MM, 1989, STRUCTURAL AND FUNCTIONAL RESPONSES TO ENVIRONMENTAL STRESSES : WATER SHORTAGE, P269
   Lynch Michael, 1998
   Masle J, 2005, NATURE, V436, P866, DOI 10.1038/nature03835
   Masle J., 1993, Stable isotopes and plant carbon-water relations., P371
   McKay JK, 2003, MOL ECOL, V12, P1137, DOI 10.1046/j.1365-294X.2003.01833.x
   McKay JK, 2001, P ROY SOC B-BIOL SCI, V268, P1715, DOI 10.1098/rspb.2001.1715
   Monneveux P, 2006, CROP SCI, V46, P180, DOI 10.2135/cropsci2005.04-0034
   New M, 2000, J CLIMATE, V13, P2217, DOI 10.1175/1520-0442(2000)013<2217:RTCSTC>2.0.CO;2
   NIENHUIS J, 1994, AM J BOT, V81, P943, DOI 10.2307/2445286
   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
   ORR HA, 1992, AM NAT, V140, P725, DOI 10.1086/285437
   Orr HA, 1998, EVOLUTION, V52, P935, DOI 10.1111/j.1558-5646.1998.tb01823.x
   Passioura JB, 1996, PLANT GROWTH REGUL, V20, P79, DOI 10.1007/BF00024003
   Price AH, 2002, J EXP BOT, V53, P989, DOI 10.1093/jexbot/53.371.989
   Rebetzke GJ, 2001, CROP SCI, V41, P1731, DOI 10.2135/cropsci2001.1731
   Reymond M, 2003, PLANT PHYSIOL, V131, P664, DOI 10.1104/pp.013839
   Richards RA, 1996, PLANT GROWTH REGUL, V20, P157, DOI 10.1007/BF00024012
   SCHULZE ED, 1986, ANNU REV PLANT PHYS, V37, P247, DOI 10.1146/annurev.pp.37.060186.001335
   Scott P, 2000, ANN BOT-LONDON, V85, P159, DOI 10.1006/anbo.1999.1006
   Seki M, 2002, PLANT J, V31, P279, DOI 10.1046/j.1365-313X.2002.01359.x
   Shinozaki K, 2003, CURR OPIN PLANT BIOL, V6, P410, DOI 10.1016/S1369-5266(03)00092-X
   STAM P, 1993, PLANT J, V3, P739, DOI 10.1111/j.1365-313X.1993.00739.x
   STEBBINS GL, 1952, AM NAT, V86, P33, DOI 10.1086/281699
   Stinchcombe JR, 2004, P NATL ACAD SCI USA, V101, P4712, DOI 10.1073/pnas.0306401101
   SUSEK RE, 1992, AUST J PLANT PHYSIOL, V19, P387, DOI 10.1071/PP9920387
   Symonds VV, 2004, MOL ECOL NOTES, V4, P768, DOI 10.1111/j.1471-8286.2004.00763.x
   Symonds VV, 2003, GENETICS, V165, P1475
   Teulat B, 2002, THEOR APPL GENET, V106, P118, DOI 10.1007/s00122-002-1028-8
   Thumma BR, 2001, J EXP BOT, V52, P203, DOI 10.1093/jexbot/52.355.203
   Uno Y, 2000, P NATL ACAD SCI USA, V97, P11632, DOI 10.1073/pnas.190309197
   Walter H., 1960, Klimadiagramm Weltatlas
   Walter H, 1968, Die Vegetation der Erde, VII
   WALTER H, 1964, VEGETATION ERDE, V1
   WHITTAKER R H, 1975, P385
   Woodson JD, 2008, NAT REV GENET, V9, P383, DOI 10.1038/nrg2348
   YAMAGUCHISHINOZAKI K, 1994, PLANT CELL, V6, P251, DOI 10.1105/tpc.6.2.251
   Yue B, 2006, GENETICS, V172, P1213, DOI 10.1534/genetics.105.045062
NR 85
TC 95
Z9 119
U1 0
U2 37
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0014-3820
EI 1558-5646
J9 EVOLUTION
JI Evolution
PD DEC
PY 2008
VL 62
IS 12
BP 3014
EP 3026
DI 10.1111/j.1558-5646.2008.00474.x
PG 13
WC Ecology; Evolutionary Biology; Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Evolutionary Biology; Genetics &
   Heredity
GA 380CI
UT WOS:000261442900006
PM 18691264
OA Bronze
DA 2025-01-10
ER

PT J
AU Kana, CÉ
   Djangue, MN
AF Kana, Collins Etienne
   Djangue, Marlyse Nankap
TI Evaluation of TAMSAT data for precipitation estimates in the northern
   part of Cameroon
SO PHYSIO-GEO
LA English
DT Article
DE evaluation; TAMSAT estimates; precipitations; spatial statistics; North
   Cameroon
ID ICE-SCATTERING; RAINFALL; SATELLITE; AFRICA; VALIDATION; RESOLUTION;
   PRODUCTS
AB Due to the lack of adequate ground rainfall data for adaptation to climate variability, satellite imagery has been used for some decades in highlighting the rainfall-generating clouds. Among the most common products of this type are TAMSAT data (Tropical Applications in Meteorology using SATellite data) for the precipitation estimates by a thresholding of cold-top clouds in the thermal infrared channel. Doubts persist, however, about the ability of these data to faithfully reproduce rainfall events in the sudano-sahelian zone particularly exposed to rainfall hazards. It therefore becomes necessary to evaluate them using the available ground observations. The objective of this contribution is therefore to validate the TAMSAT estimates in the northern Cameroon using the 24 ground stations for which continuous recorded data on precipitation are available between 2001 and 2011. Data processing includes the production of monthly and annual averages and various techniques of spatial analysis (spatial interpolation of point data and arithmetic operations on raster files). The results indicate that TAMSAT satellite products can partly fill in the deficiency of ground data, due to their ability to reproduce the main characteristics (monthly, interannual and spatial) of rainfall in the northern Cameroon. But the calibration of TAMSAT generally leads to biases: dry in the Sudanian zone and humid in the Sahelian zone. These biases can cause differences of 25 % from the total amount of rainfall.
C1 [Kana, Collins Etienne] Univ Dschang, BP 49, Dschang, Cameroon.
   [Djangue, Marlyse Nankap] Inst Natl Cartog, BP 157, Yaounde, Cameroon.
C3 Universite de Dschang
RP Kana, CÉ (corresponding author), Univ Dschang, BP 49, Dschang, Cameroon.
EM ckana71@yahoo.fr; djangue_ma@yahoo.fr
CR Asadullah A, 2008, HYDROLOG SCI J, V53, P1137, DOI 10.1623/hysj.53.6.1137
   Bergès JC, 2010, ANN GEOPHYS-GERMANY, V28, P289, DOI 10.5194/angeo-28-289-2010
   de Andrade FM, 2021, WEATHER FORECAST, V36, P265, DOI 10.1175/WAF-D-20-0054.1
   DELAHAYE F., 2013, THESIS U RENNES, V2
   Dinku T, 2007, INT J REMOTE SENS, V28, P1503, DOI 10.1080/01431160600954688
   Gaye A., 2004, Secheresse, V15, P287
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Huffman GJ, 2001, J HYDROMETEOROL, V2, P36, DOI 10.1175/1525-7541(2001)002<0036:GPAODD>2.0.CO;2
   KANA C.E., 2013, INT J ADV STUDIES RE, V4
   Laurent H, 1998, ATMOS RES, V48, P651, DOI 10.1016/S0169-8095(98)00051-9
   Maidment R., 2020, ADV GLOBAL CHANGE RE, P393
   Maidment RI, 2017, SCI DATA, V4, DOI 10.1038/sdata.2017.63
   Maidment RI, 2014, J GEOPHYS RES-ATMOS, V119, P10619, DOI 10.1002/2014JD021927
   Mathon V, 2002, J APPL METEOROL, V41, P1081, DOI 10.1175/1520-0450(2002)041<1081:MCSRIT>2.0.CO;2
   MCDOUGALL V.D., 1988, RELATIONSHIP RAINFAL
   MINEPDED/PNUD, 2012, MINISTERE ENV PROTEC
   MINEPDED/PNUD, 2015, MINISTERE ENV PROTEC
   Mohr KI, 1999, J APPL METEOROL, V38, P596, DOI 10.1175/1520-0450(1999)038<0596:TCTTRW>2.0.CO;2
   Munzimi YA, 2015, J APPL METEOROL CLIM, V54, P541, DOI 10.1175/JAMC-D-14-0052.1
   Nesbitt SW, 2000, J CLIMATE, V13, P4087, DOI 10.1175/1520-0442(2000)013<4087:ACOPFI>2.0.CO;2
   Nicholson SE, 2000, GLOBAL PLANET CHANGE, V26, P137, DOI 10.1016/S0921-8181(00)00040-0
   ONADEF, 1984, CART EC COUV VEG CAM
   Roca R, 2010, J APPL METEOROL CLIM, V49, P715, DOI 10.1175/2009JAMC2318.1
   SIGHOMNOU D., 2004, THESIS U YAOUNDE CAM
   Stein THM, 2019, WEATHER FORECAST, V34, P233, DOI 10.1175/WAF-D-18-0080.1
   Suchel J.B., 1988, THESIS U SAINT ETIEN
   Suzuki T, 2011, THEOR APPL CLIMATOL, V103, P39, DOI 10.1007/s00704-010-0276-9
   Tarnavsky E, 2014, J APPL METEOROL CLIM, V53, P2805, DOI 10.1175/JAMC-D-14-0016.1
   Thorne V, 2001, INT J REMOTE SENS, V22, P1951, DOI 10.1080/01431160152043658
   TOURE A., 1989, VALIDATION METHODES, P139
   TSALEFAC M, 2004, REV GEOGRAPHIE CAMER, V16, P56
   Wainwright CM, 2021, J CLIMATE, V34, P1367, DOI 10.1175/JCLI-D-20-0450.1
   Young M, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab94e9
   Zambrano-Bigiarini M, 2017, HYDROL EARTH SYST SC, V21, P1295, DOI 10.5194/hess-21-1295-2017
NR 34
TC 1
Z9 1
U1 0
U2 1
PU REVUES ORG
PI PARIS
PA CENTRE SOCIOLOGIE ORGANISATIONS CSO SCIENCES PO-CNRS, 27 RUE
   SAINT-GUILLAUME, PARIS, 75007, FRANCE
SN 1958-573X
J9 PHYSIO-GEO
JI Physio-Geo
PY 2023
VL 19
BP 49
EP 63
DI 10.4000/physio-geo.15221
PG 16
WC Geosciences, Multidisciplinary
WE Emerging Sources Citation Index (ESCI)
SC Geology
GA K2LY2
UT WOS:001014818100003
OA gold
DA 2025-01-10
ER

PT J
AU Azadi, H
   Moghaddam, SM
   Burkart, S
   Mahmoudi, H
   Van Passel, S
   Kurban, A
   Lopez-Carr, D
AF Azadi, Hossein
   Moghaddam, Saghi Movahhed
   Burkart, Stefan
   Mahmoudi, Hossein
   Van Passel, Steven
   Kurban, Alishir
   Lopez-Carr, David
TI Rethinking resilient agriculture: From Climate-Smart Agriculture to
   Vulnerable-Smart Agriculture
SO JOURNAL OF CLEANER PRODUCTION
LA English
DT Article
DE Vulnerability; Sustainable livelihood; Food security; Climate change;
   Small-scale farming
ID FOOD SECURITY; ADAPTATION; FARMERS; INTEGRATION; INSIGHTS; ETHIOPIA;
   IMPACTS; CONTEXT; GENDER
AB Climate-Smart Agriculture (CSA) is seeking to overcome the food security problem and develop rural livelihoods while minimizing negative impacts on the environment. However, when such synergies exist, the situation of small-scale farmers is often overlooked, and they are unable to implement new practices and technologies. Therefore, the main aim of this study is to improve CSA by adding the neglected but very important element "small-scale farmer", and introduce Vulnerable-Smart Agriculture (VSA) as a complete version of CSA. VSA indicates, based on the results of this study, that none of the decisions made by policymakers can be realistic and functional as long as the voice of the farmers influenced by their decisions is not heard. Therefore, to identify different levels for possible interventions and develop VSA monitoring indicators, a new conceptual framework needs to be developed. This study proposed such a framework consisting of five elements: prediction of critical incidents by farmers, measuring the consequences of incidents, identifying farmers' coping strategies, assessing farmers' livelihood capital when facing an incident, and adapting to climate incidents. The primary focus of this study is on farmers' learning and operational preparation to deal with tension and disasters at farm level. Understanding the implications of threats from climate change and the recognizing of coping mechanisms will contribute to an increase in understanding sustainable management.
C1 [Azadi, Hossein] Univ Ghent, Dept Geog, Ghent, Belgium.
   [Azadi, Hossein; Moghaddam, Saghi Movahhed] Czech Univ Life Sci Prague, Fac Environm Sci, Prague, Czech Republic.
   [Azadi, Hossein; Kurban, Alishir] Chinese Acad Sci, Xinjiang Inst Ecol & Geog, 818 South Beijing Rd, Urumqi 830011, Xinjiang, Peoples R China.
   [Burkart, Stefan] Alliance Biovers Int & Int Ctr Trop Agr CIAT, Trop Forages Program, Cali, Colombia.
   [Mahmoudi, Hossein] Shahid Beheshti Univ, Environm Sci Res Inst, Dept Agroecol, Tehran, Iran.
   [Van Passel, Steven] Univ Antwerp, Dept Engn Management, Antwerp, Belgium.
   [Kurban, Alishir] Chinese Acad Sci, Res Ctr Ecol & Environm Cent Asia, 818 South Beijing Rd, Urumqi 830011, Xinjiang, Peoples R China.
   [Kurban, Alishir] Univ Chinese Acad Sci, Beijing 100049, Peoples R China.
   [Kurban, Alishir] Sino Belgian Joint Lab Geoinformat, Urumqi 830011, Peoples R China.
   [Lopez-Carr, David] Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USA.
C3 Ghent University; Czech University of Life Sciences Prague; Chinese
   Academy of Sciences; Xinjiang Institute of Ecology & Geography, CAS;
   Shahid Beheshti University; University of Antwerp; Chinese Academy of
   Sciences; Chinese Academy of Sciences; University of Chinese Academy of
   Sciences, CAS; University of California System; University of California
   Santa Barbara
RP Azadi, H (corresponding author), Univ Ghent, Dept Geog, Ghent, Belgium.
EM hossein.azadi@ugent.be
RI Mahmoudi, Hossein/K-7153-2013; Movahhed Moghaddam, Saghi/GXH-9384-2022;
   Kurban, Alishir/AGK-9193-2022; Azadi, Hossein/E-2361-2011
OI Kurban, Alishir/0000-0001-9387-8127; Burkart,
   Stefan/0000-0001-5297-2184; Van Passel, Steven/0000-0002-6971-9246;
   Azadi, Hossein/0000-0002-5108-1993; Movahhed Moghaddam,
   Saghi/0000-0002-2809-9693
FU Strategic Priority Research Program of Chinese Academy of Sciences
   [XDA20060303]; Chinese Academy of Sciences President's International
   Fellowship Initiative (PIFI) [2021VCA0004]
FX This research paper was partly funded by the Strategic Priority Research
   Program of Chinese Academy of Sciences (Grant No. XDA20060303) and the
   Chinese Academy of Sciences President's International Fellowship
   Initiative (PIFI grant no. 2021VCA0004).
CR Abegunde VO, 2019, CLIMATE, V7, DOI 10.3390/cli7110132
   Abson DJ, 2012, APPL GEOGR, V35, P515, DOI 10.1016/j.apgeog.2012.08.004
   Adger W. N., 2003, Progress in Development Studies, V3, P179, DOI 10.1191/1464993403ps060oa
   Adger WN, 2006, GLOBAL ENVIRON CHANG, V16, P268, DOI 10.1016/j.gloenvcha.2006.02.006
   Ajayi O.C., 2012, EXTERNALITY EC MANAG, P167
   Ali A, 2017, CLIM RISK MANAG, V16, P183, DOI 10.1016/j.crm.2016.12.001
   Amaru S, 2013, APPL GEOGR, V39, P128, DOI 10.1016/j.apgeog.2012.12.006
   Amin A., 2015, Agric Res Commun, V2, P13
   Andrieu N, 2019, FRONT SUSTAIN FOOD S, V3, DOI 10.3389/fsufs.2019.00037
   [Anonymous], 2012, SUST SMALLH AGR FEED
   [Anonymous], 2011, CLIM SMART AGR INCR
   [Anonymous], 2016, Agriculture Food Security, DOI [10.1186/s40066-016-0075-3, DOI 10.1186/S40066-016-0075-3]
   [Anonymous], 2013, MODULE 7 CLIMATE SMA
   [Anonymous], 2014, Climate change 2014: synthesis report
   Antón J, 2013, GLOBAL ENVIRON CHANG, V23, P1726, DOI 10.1016/j.gloenvcha.2013.08.007
   Arbuckle JG, 2013, CLIMATIC CHANGE, V117, P943, DOI 10.1007/s10584-013-0707-6
   Asian Development Bank, 2017, CSA COUNTR PROF AS S, V28
   Azadi H, 2011, GLOBAL PLANET CHANGE, V78, P77, DOI 10.1016/j.gloplacha.2011.05.006
   Azadi H, 2011, TRENDS BIOTECHNOL, V29, P6, DOI 10.1016/j.tibtech.2010.10.002
   Boon HJ, 2012, NAT HAZARDS, V60, P381, DOI 10.1007/s11069-011-0021-4
   Brandt P, 2017, AGR SYST, V151, P234, DOI 10.1016/j.agsy.2015.12.011
   Burnham M, 2017, REG ENVIRON CHANGE, V17, P171, DOI 10.1007/s10113-016-0975-6
   Campbell BM, 2014, CURR OPIN ENV SUST, V8, P39, DOI 10.1016/j.cosust.2014.07.002
   Chandra A, 2018, CLIM POLICY, V18, P526, DOI 10.1080/14693062.2017.1316968
   Cohen PJ, 2016, AMBIO, V45, pS309, DOI 10.1007/s13280-016-0831-4
   Commission for Africa, 2005, OUR COMMON INTEREST
   Conant R.T., 2009, Rebuilding resilience: sustainable land management for climate mitigation and adaptation
   Debortoli NS, 2017, NAT HAZARDS, V86, P557, DOI 10.1007/s11069-016-2705-2
   Etzold B, 2016, GLOB MIGRAT ISS, V6, P105, DOI 10.1007/978-3-319-42922-9_6
   Fadina AMR, 2018, ENVIRONMENTS, V5, DOI 10.3390/environments5010015
   FAO, 2017, Climate smart agriculture sourcebook, V2
   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
   Goli I, 2020, J AGR ENVIRON ETHIC, V33, P187, DOI 10.1007/s10806-020-09822-3
   Greene R, 2011, GEOGR COMPASS, V5, P412, DOI 10.1111/j.1749-8198.2011.00431.x
   Gupta M, 2020, IEEE ACCESS, V8, P34564, DOI 10.1109/ACCESS.2020.2975142
   Hellin J, 2019, CLIMATE, V7, DOI 10.3390/cli7040048
   IISD, 2011, INT MIT AD AGR SECT
   Islam KK, 2019, FORESTS, V10, DOI 10.3390/f10030288
   Jamshidi O, 2020, CLIM DEV, V12, P923, DOI 10.1080/17565529.2019.1710097
   Jurgilevich A, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa5508
   Kanamaru H., 2018, CLIMATE RISKS VULNER
   Khatri-Chhetri A, 2017, AGR SYST, V151, P184, DOI 10.1016/j.agsy.2016.10.005
   Lipper L, 2014, NAT CLIM CHANGE, V4, P1068, DOI [10.1038/NCLIMATE2437, 10.1038/nclimate2437]
   Long TB, 2019, J CLEAN PROD, V232, P993, DOI 10.1016/j.jclepro.2019.05.212
   Mahendra Dev., 2011, CLIMATE CHANGE RURAL
   Makate C, 2016, SPRINGERPLUS, V5, DOI 10.1186/s40064-016-2802-4
   Martinez-Baron D, 2018, CURR OPIN ENV SUST, V31, P112, DOI 10.1016/j.cosust.2018.02.013
   Mathews JA, 2018, JAMBA-J DISASTER RIS, V10, DOI 10.4102/jamba.v10i1.492
   Mazhar R, 2021, J CLEAN PROD, V283, DOI 10.1016/j.jclepro.2020.124620
   Mersha AA, 2019, REG ENVIRON CHANGE, V19, P429, DOI 10.1007/s10113-018-1413-8
   Meynard J-M., 2012, Farming Systems Research into the 21st Century: The New Dynamic, P405, DOI DOI 10.1007/978-94-007-4503-218
   Mwongera C, 2017, AGR SYST, V151, P192, DOI 10.1016/j.agsy.2016.05.009
   Nyasimi M, 2017, CLIMATE, V5, DOI 10.3390/cli5030063
   Okediji R.L., 2019, INTELLECTUAL PROPERT, DOI [10.1007/978-981-13-2856-5_12, DOI 10.1007/978-981-13-2856-5_12]
   Ouedraogo I, 2018, CLIMATE, V6, DOI 10.3390/cli6010013
   Parente R, 2019, J INT BUS STUD, V50, P275, DOI 10.1057/s41267-018-0179-z
   Rahman HMT, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12145654
   Rakotovao NH, 2017, J CLEAN PROD, V140, P1165, DOI 10.1016/j.jclepro.2016.10.045
   Ramirez-Villegas J, 2013, AGR FOREST METEOROL, V170, P67, DOI 10.1016/j.agrformet.2011.09.005
   Reed MS, 2013, ECOL ECON, V94, P66, DOI 10.1016/j.ecolecon.2013.07.007
   Rosenstock T.S., 2016, CCAFS Working Paper No. 138
   Rudi LM, 2012, GLOBAL PLANET CHANGE, V86-87, P1, DOI 10.1016/j.gloplacha.2011.12.004
   Sattar R.A., 2017, INT J AGR EXTENSION, V5, P539
   Seebauer M, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/3/035006
   Siders AR, 2019, CLIMATIC CHANGE, V152, P239, DOI 10.1007/s10584-018-2272-5
   Sims REH, 2011, ENERGY SMART FOOD PE
   Singh C, 2018, CLIM DEV, V10, P389, DOI 10.1080/17565529.2017.1318744
   Sitaula BK, 2020, CLIMATE IMPACTS AGR, P347, DOI DOI 10.1007/978-3-030-37537-9_21
   Steenwerth KL., 2014, Agric Food Secur, V3, P1, DOI [10.1186/2048-7010-3-11, DOI 10.1186/2048-7010-3-11]
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Thornton TF, 2017, CLIMATIC CHANGE, V140, P5, DOI 10.1007/s10584-013-0884-3
   Torquebiau E, 2018, CAH AGRIC, V27, DOI 10.1051/cagri/2018010
   Totin E, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10061990
   Vall E., 2016, CAH AGRIC, V25, P15001
   Vervoort JM, 2014, GLOBAL ENVIRON CHANG, V28, P383, DOI 10.1016/j.gloenvcha.2014.03.001
   Vincent K, 2017, CLIM POLICY, V17, P189, DOI 10.1080/14693062.2015.1075374
   Woolf D, 2018, CLIM POLICY, V18, P1260, DOI 10.1080/14693062.2018.1427537
   Yengoh G.T, 2012, AGR FOOD SECUR, V1
   Zamasiya B, 2017, J ENVIRON MANAGE, V198, P233, DOI 10.1016/j.jenvman.2017.04.073
NR 79
TC 81
Z9 82
U1 7
U2 71
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 OCT 15
PY 2021
VL 319
AR 128602
DI 10.1016/j.jclepro.2021.128602
EA AUG 2021
PG 10
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 XM2RQ
UT WOS:000728681500005
OA Green Submitted
DA 2025-01-10
ER

PT J
AU Hall, D
   Olsson, J
   Zhao, W
   Kroon, J
   Wennström, U
   Wang, XR
AF Hall, David
   Olsson, Jenny
   Zhao, Wei
   Kroon, Johan
   Wennstrom, Ulfstand
   Wang, Xiao-Ru
TI Divergent patterns between phenotypic and genetic variation in Scots
   pine
SO PLANT COMMUNICATIONS
LA English
DT Article
DE clinal variation; cold hardiness; genetic diversity; population
   structure; Pinus sylvestris
ID QUANTITATIVE TRAIT LOCI; FROST HARDINESS; NUCLEOTIDE DIVERSITY;
   COLONIZATION HISTORY; POPULATION-STRUCTURE; LATITUDINAL CLINE;
   POPULUS-TREMULA; NEUTRAL MARKERS; SYLVESTRIS L.; ADAPTATION
AB In boreal forests, autumn frost tolerance in seedlings is a critical fitness component because it determines survival rates during regeneration. To understand the forces that drive local adaptation in this trait, we conducted freezing tests in a common garden setting for 54 Pinus sylvestris (Scots pine) populations (>5000 seedlings) collected across Scandinavia into western Russia, and genotyped 24 of these populations (>900 seedlings) at >10 000 SNPs. Variation in cold hardiness among populations, as measured by Q(ST), was above 80% and followed a distinct cline along latitude and longitude, demonstrating significant adaptation to climate at origin. In contrast, the genetic differentiation was very weak (mean F-ST 0.37%). Despite even allele frequency distribution in the vast majority of SNPs among all populations, a few rare alleles appeared at very high or at fixation in marginal populations restricted to northwestern Fennoscandia. Genotype-environment associations showed that climate variables explained 2.9% of the genetic differentiation, while genotype-phenotype associations revealed a high marker-estimated heritability of frost hardiness of 0.56, but identified no major loci. Very extensive gene flow, strong local adaptation, and signals of complex demographic history across markers are interesting topics of forthcoming studies on this species to better clarify signatures of selection and demography.
C1 [Hall, David; Olsson, Jenny; Zhao, Wei; Wang, Xiao-Ru] Umea Univ, Umea Plant Sci Ctr, Dept Ecol & Environm Sci, Umea, Sweden.
   [Zhao, Wei; Wang, Xiao-Ru] Beijing Forestry Univ, Coll Biol Sci & Technol, Adv Innovat Ctr Tree Breeding Mol Design, Beijing, Peoples R China.
   [Kroon, Johan; Wennstrom, Ulfstand] Forestry Res Inst Sweden Skogforsk, Uppsala, Sweden.
C3 Umea University; Beijing Forestry University; Skogforsk
RP Wang, XR (corresponding author), Umea Univ, Umea Plant Sci Ctr, Dept Ecol & Environm Sci, Umea, Sweden.; Wang, XR (corresponding author), Beijing Forestry Univ, Coll Biol Sci & Technol, Adv Innovat Ctr Tree Breeding Mol Design, Beijing, Peoples R China.
EM xiao-ru.wang@umu.se
RI Zhao, wei/ITT-0573-2023; Wang, Xiao-Ru/H-6811-2012; Hall,
   David/KHD-4359-2024
OI Zhao, Wei/0000-0001-9437-3198; Hall, David/0000-0001-8152-2713
FU NEFCO through the Programme for Environment and Climate Co-operation;
   Formas; TC4F; Carl Tryggers Stiftelse; Umea Plant Science Center, Sweden
FX Freezing tests were performed by Skogforsk and sponsored by NEFCO
   through the Programme for Environment and Climate Co-operation. This
   study was supported by grants from Formas, TC4F, Carl Tryggers
   Stiftelse, and Umea Plant Science Center, Sweden.
CR Alberto FJ, 2013, GLOBAL CHANGE BIOL, V19, P1645, DOI 10.1111/gcb.12181
   Andersson B, 2004, SILVAE GENET, V53, P76, DOI 10.1515/sg-2004-0014
   Andersson B, 1992, SCAND J FOREST RES, V7, P367, DOI 10.1080/02827589209382729
   Barton N, 2019, ELIFE, V8, DOI 10.7554/eLife.45380
   Bates D, 2015, J STAT SOFTW, V67, P1, DOI 10.18637/jss.v067.i01
   BENNETT KD, 1991, J BIOGEOGR, V18, P103, DOI 10.2307/2845248
   Bennie J, 2010, GLOBAL CHANGE BIOL, V16, P1503, DOI 10.1111/j.1365-2486.2009.02095.x
   Berlin M, 2009, SCAND J FOREST RES, V24, P288, DOI 10.1080/02827580903117396
   Bolger AM, 2014, BIOINFORMATICS, V30, P2114, DOI 10.1093/bioinformatics/btu170
   Bolstad BM., 2020, PreprocessCore: A Collection of Pre-processing Functions
   Bradburd GS, 2018, GENETICS, V210, P33, DOI 10.1534/genetics.118.301333
   Capblancq T, 2018, MOL ECOL RESOUR, V18, P1223, DOI 10.1111/1755-0998.12906
   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
   Caye K, 2016, MOL ECOL RESOUR, V16, P540, DOI 10.1111/1755-0998.12471
   Cheddadi R, 2006, GLOBAL ECOL BIOGEOGR, V15, P271, DOI [10.1111/j.1466-822x.2006.00226.x, 10.1111/j.1466-822X.2006.00226.x]
   Chen J, 2019, EVOL APPL, V12, P1539, DOI 10.1111/eva.12801
   Csilléry K, 2018, MOL ECOL, V27, P606, DOI 10.1111/mec.14499
   de Villemereuil P, 2014, MOL ECOL, V23, P2006, DOI 10.1111/mec.12705
   Dering M, 2017, DIVERS DISTRIB, V23, P540, DOI 10.1111/ddi.12546
   Dvornyk V, 2002, MOL BIOL EVOL, V19, P179, DOI 10.1093/oxfordjournals.molbev.a004070
   Excoffier L, 2010, MOL ECOL RESOUR, V10, P564, DOI 10.1111/j.1755-0998.2010.02847.x
   Foll M, 2008, GENETICS, V180, P977, DOI 10.1534/genetics.108.092221
   Forester BR, 2018, MOL ECOL, V27, P2215, DOI 10.1111/mec.14584
   Gienapp P, 2020, GLOBAL CHANGE BIOL, V26, P2737, DOI 10.1111/gcb.15058
   Hall D, 2007, EVOLUTION, V61, P2849, DOI 10.1111/j.1558-5646.2007.00230.x
   Hall D, 2020, HEREDITY, V124, P633, DOI 10.1038/s41437-020-0302-3
   Hall D, 2016, TREE GENET GENOMES, V12, DOI 10.1007/s11295-016-1073-0
   Hurme P, 1997, CAN J FOREST RES, V27, P716, DOI 10.1139/cjfr-27-5-716
   Jankowski A, 2017, FUNCT ECOL, V31, P2212, DOI 10.1111/1365-2435.12946
   Johnsen A, 2007, MOL ECOL, V16, P4867, DOI 10.1111/j.1365-294X.2007.03552.x
   Kullman L, 2008, QUATERNARY SCI REV, V27, P2467, DOI 10.1016/j.quascirev.2008.09.004
   Latta RG, 1998, AM NAT, V151, P283, DOI 10.1086/286119
   Le Corre V, 2003, GENETICS, V164, P1205
   Legendre P., 2019, **DATA OBJECT**
   Leinonen T, 2013, NAT REV GENET, V14, P179, DOI 10.1038/nrg3395
   Li H, 2011, BIOINFORMATICS, V27, P2987, DOI 10.1093/bioinformatics/btr509
   Li L., 2020, THESIS ACTA U UPSALI, P60
   Li Li H. H., ARXIV ARXIV13033997
   Ma XF, 2010, GENETICS, V186, P1033, DOI 10.1534/genetics.110.120873
   Meuwissen THE, 2001, GENETICS, V157, P1819
   Milesi P, 2019, EVOL APPL, V12, P1946, DOI 10.1111/eva.12855
   Nadeau S, 2016, ECOL EVOL, V6, P8649, DOI 10.1002/ece3.2550
   Naydenov K, 2007, BMC EVOL BIOL, V7, DOI 10.1186/1471-2148-7-233
   Neale DB, 2014, GENOME BIOL, V15, DOI 10.1186/gb-2014-15-3-r59
   OAKESHOTT JG, 1982, EVOLUTION, V36, P86, DOI 10.1111/j.1558-5646.1982.tb05013.x
   Pan J, 2015, MOL ECOL RESOUR, V15, P711, DOI 10.1111/1755-0998.12342
   Parducci L, 2012, SCIENCE, V335, P1083, DOI 10.1126/science.1216043
   Patterson N, 2006, PLOS GENET, V2, P2074, DOI 10.1371/journal.pgen.0020190
   Pedryc A., 2017, J FOR RES, P1
   Persson T, 2010, SILVA FENN, V44, P255, DOI 10.14214/sf.152
   Price AL, 2006, NAT GENET, V38, P904, DOI 10.1038/ng1847
   Pyhaejaervi T, 2020, EVOL APPL, V13, P11, DOI 10.1111/eva.12809
   Pyhäjärvi T, 2008, TREE GENET GENOMES, V4, P247, DOI 10.1007/s11295-007-0105-1
   Pyhäjärvi T, 2007, GENETICS, V177, P1713, DOI 10.1534/genetics.107.077099
   Rehfeldt GE, 2002, GLOBAL CHANGE BIOL, V8, P912, DOI 10.1046/j.1365-2486.2002.00516.x
   REHFELDT GE, 1989, FOREST ECOL MANAG, V28, P203, DOI 10.1016/0378-1127(89)90004-2
   Rigo D, 2016, EUROPEAN ATLAS FORES
   Savolainen O, 2004, FOREST ECOL MANAG, V197, P79, DOI 10.1016/j.foreco.2004.05.006
   Savolainen O, 2007, ANNU REV ECOL EVOL S, V38, P595, DOI 10.1146/annurev.ecolsys.38.091206.095646
   Semerikov VL, 2018, TREE GENET GENOMES, V14, DOI 10.1007/s11295-017-1222-0
   Shutyaev AM, 1997, SILVAE GENET, V46, P332
   SPITZE K, 1993, GENETICS, V135, P367
   Stinchcombe JR, 2004, P NATL ACAD SCI USA, V101, P4712, DOI 10.1073/pnas.0306401101
   Stromme CB, 2019, TREES-STRUCT FUNCT, V33, P79, DOI 10.1007/s00468-018-1760-6
   Sullivan A.R., 2020, THESIS UMEA UNIVERS
   Tollefsrud MM, 2009, HEREDITY, V102, P549, DOI 10.1038/hdy.2009.16
   Tsuda Y, 2016, MOL ECOL, V25, P2773, DOI 10.1111/mec.13654
   Tyrmi JS, 2020, G3-GENES GENOM GENET, V10, P2683, DOI 10.1534/g3.120.401285
   Wang IJ, 2014, MOL ECOL, V23, P5649, DOI 10.1111/mec.12938
   WEIR BS, 1984, EVOLUTION, V38, P1358, DOI [10.2307/2408641, 10.1111/j.1558-5646.1984.tb05657.x]
   Whitlock MC, 1999, GENET RES, V74, P215, DOI 10.1017/S0016672399004127
   Wright S, 1943, GENETICS, V28, P114
   Yeaman S, 2015, AM NAT, V186, pS74, DOI 10.1086/682405
   Zale R, 2018, QUATERNARY SCI REV, V185, P222, DOI 10.1016/j.quascirev.2018.02.005
   Zhao W, 2020, NEW PHYTOL, V228, P330, DOI 10.1111/nph.16619
   Zhou X, 2013, PLOS GENET, V9, DOI 10.1371/journal.pgen.1003264
   Zhou X, 2012, NAT GENET, V44, P821, DOI 10.1038/ng.2310
   Zimin A, 2014, GENETICS, V196, P875, DOI 10.1534/genetics.113.159715
   Zimmer K, 2018, SCAND J FOREST RES, V33, P6, DOI 10.1080/02827581.2017.1337919
NR 80
TC 17
Z9 19
U1 5
U2 25
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2590-3462
J9 PLANT COMMUN
JI Plant Commun.
PD JAN 11
PY 2021
VL 2
IS 1
SI SI
AR 100139
DI 10.1016/j.xplc.2020.100139
EA JAN 2021
PG 14
WC Biochemistry & Molecular Biology; Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Plant Sciences
GA SH3VL
UT WOS:000654065000008
PM 33511348
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Polsky, C
   Easterling, WE
AF Polsky, C
   Easterling, WE
TI Adaptation to climate variability and change in the US Great Plains: A
   multi-scale analysis of Ricardian climate sensitivities
SO AGRICULTURE ECOSYSTEMS & ENVIRONMENT
LA English
DT Article
DE Ricardian climate sensitivity; adaptation; multi-level modeling; climate
   change; land-use change; scalar dynamics; Great Plains; spatial scale
ID IMPACTS; ISSUES
AB The Ricardian approach to estimating climate change impacts is an important technique for incorporating how adaptations modulate the overall effect. Past Ricardian work expresses climate sensitivities in terms of local effects only, ignoring the influence on adaptation of broader-scale social, environmental and economic factors. This paper extends the Ricardian approach to account for influences at multiple spatial scales. Results from multi-level modeling support the hypothesis that a county's Ricardian climate sensitivity is influenced not only by its climate but also by social factors associated with the climate of the agro-climatic zone in which it is located. The model estimates a non-linear, hill-shaped relationship between July maximum temperatures and agricultural land values, with initial increases beneficial in all counties but more beneficial in districts of high interannual temperature variability. Farmers and institutions in districts of high variability have therefore adapted to be more resilient to variability than farmers in areas of comparatively stable climate. However, the underlying reasons for this lessened vulnerability are unclear and may be associated with unsustainable land-use practices. Future research should investigate the precise form of these local and extra-local adaptations to determine if implementing the adaptations elsewhere would compromise agricultural system sustainability. (C) 2001 Elsevier Science B.V. All rights reserved.
C1 Penn State Univ, Dept Geog, N Branch, NJ 08876 USA.
   Penn State Univ, Dept Geog, University Pk, PA 16802 USA.
C3 Pennsylvania Commonwealth System of Higher Education (PCSHE);
   Pennsylvania State University; Pennsylvania Commonwealth System of
   Higher Education (PCSHE); Pennsylvania State University; Pennsylvania
   State University - University Park
RP Penn State Univ, Dept Geog, 1031 Route 28, N Branch, NJ 08876 USA.
EM polsky@essc.psu.edu
CR Allen R.G., 1998, FAO Irrigation and Drainage Paper
   [Anonymous], 1997, Environmental Modeling and Assessment, DOI 10.1023/A:1019090117643
   [Anonymous], 1999, IMPACT CLIMATE CHANG
   [Anonymous], 1998, PEOPLE PIXELS LINKIN
   [Anonymous], 1985, CLIM IMP ASSES
   Anselin L., 1998, SPATIAL DEPENDENCE L
   Antle JM, 1996, AGR FOREST METEOROL, V80, P67, DOI 10.1016/0168-1923(95)02317-8
   Barnard CH, 1997, AM J AGR ECON, V79, P1642, DOI 10.2307/1244396
   Bryk A.S., 1992, Hierarchical linear Models: Applications and Data Analysis Methods
   Currie J.M., 1981, EC THEORY AGR LAND T
   Darwin R, 1999, CLIMATIC CHANGE, V41, P371, DOI 10.1023/A:1005421707801
   Easterling WE, 1998, AGR FOREST METEOROL, V90, P51, DOI 10.1016/S0168-1923(97)00091-9
   Easterling WE, 1997, GLOBAL ENVIRON CHANG, V7, P337, DOI 10.1016/S0959-3780(97)00016-2
   GARDNER BL, 1984, RISK MANAGEMENT AGR, P231
   Goldstein H., 1995, Multilevel statistical models. Kendall's library of statistics, V3
   Gutmann MP, 2000, CLIMATIC CHANGE, V44, P377, DOI 10.1023/A:1005624816499
   Hansen JW, 2000, AGR SYST, V65, P43, DOI 10.1016/S0308-521X(00)00025-1
   Hayami Y., 1985, Agricultural Development: An Agricultural Perspective
   Hox J.J., 1995, Applied Multi-Level Analysis, V2nd
   JONE K, 1997, SPATIAL ANAL MODELLI
   Kaufmann RK, 1997, AM J AGR ECON, V79, P178, DOI 10.2307/1243952
   Kreft I., 2004, INTRO MULTILEVEL MOD
   LEWANDROWSKI J, 1992, ECONOMIC ISSUES IN GLOBAL CLIMATE CHANGE, P132
   Lowrance R., 1986, American Journal of Alternative Agriculture, V1, P169, DOI 10.1017/S0889189300001260
   Mendelsohn R, 1996, AGR FOREST METEOROL, V80, P55, DOI 10.1016/0168-1923(95)02316-X
   MENDELSOHN R, 1994, AM ECON REV, V84, P753
   Mendelsohn R., 1993, COSTS IMPACTS BENEFI, P173
   MOELLERING H, 1972, GEOGR ANAL, V4, P34
   OLMSTEAD CW, 1968, P S QUANT METH GEOGR, P103
   OSGOOD DW, 1995, EVALUATION REV, V19, P3, DOI 10.1177/0193841X9501900101
   RAUDENBUSH SW, 2000, HLM, V5
   ROSENBERG NJ, 1987, GREAT PLAINS Q   WIN, P22
   ROSENBERG NJ, 1994, P 32 HANF S HLTH ENV
   Rossum S, 2000, PROF GEOGR, V52, P543, DOI 10.1111/0033-0124.00245
   Schneider SH, 2000, CLIMATIC CHANGE, V45, P203, DOI 10.1023/A:1005657421149
   Segerson K, 1999, IMPACT CLIMATE CHANG
   SINCLAIR R, 1967, ANN ASSOC AM GEOGR, V57, P72, DOI 10.1111/j.1467-8306.1967.tb00591.x
   Smit B, 1996, CLIMATIC CHANGE, V33, P7, DOI 10.1007/BF00140511
   SMITHERS J, 1997, AGR RESTRUCTURING SU, P169
   Snijders TAB., 2012, MULTILEVEL ANAL
   Turner B L, 1995, JOINT PUBLICATION IN
   TURNER BL, 1991, INT SOC SCI J, V43, P669
   *U TEX POP RES CTR, 1998, GREAT PLAINS POP ENV
   *USDA, 1995, AV VAL PER ACR FARM
   *USDOC, 2000, TABL CA1 3 PERS INC
   Veldkamp A, 1997, AGR SYST, V55, P1, DOI 10.1016/S0308-521X(95)00079-K
   WARRICK RA, 1980, CLIAMTIC CONSTRAINTS
NR 47
TC 73
Z9 88
U1 1
U2 35
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 2001
VL 85
IS 1-3
BP 133
EP 144
DI 10.1016/S0167-8809(01)00180-3
PG 12
WC Agriculture, Multidisciplinary; Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Agriculture; Environmental Sciences & Ecology
GA 438PN
UT WOS:000169062400009
DA 2025-01-10
ER

PT J
AU Campos, R
   Avila, H
   Esquinas, P
   Manzano, JL
   Vélez, M
AF Campos, Romulo
   Avila, Hector
   Esquinas, Paula
   Manzano, Jose Luis
   Velez, Mauricio
TI Morphological characterization of sweat glands in three bovine racial
   groups under tropical conditions
SO JOURNAL OF ANIMAL BEHAVIOUR AND BIOMETEOROLOGY
LA English
DT Article
DE bovine; climate adaptation; skin; thermoregulation
ID INDICUS; SKIN
AB The number, size, and distribution of sweat glands are involved in cattle adaptation and thermoregulation mechanisms. Similarly, variations among different racial groups during grazing merit a morphometric study. The present work aimed to compare sweat glands and hair follicles in three cattle breed groups under low trophic conditions. This study was conducted in a tropical inter-Andean valley located between 3'30 and 4'10 N and between 76'21 and 76'46 W, with three breed groups. They were Holstein (Bos taurus), Cebu (Bos indicus), and animals of the Harton del Valle breed, Colombian Creole cattle (Bos taurus). From each breed, seven animals were analyzed, and each individual had a skin biopsy taken from the cervical area, close to the scapular joint. For the histological assemblies, optical microscopy was used to analyze the thickness of the glandular epithelium, counting the number of sweat glands per square millimeter, sebaceous glands, and hair follicles. The statistical analysis included descriptive statistics and one-way analysis of variance to determine the effect of racial group. The analysis revealed that neither the thickness of the glandular epithelium nor the number of sweat glands varied among the three racial groups, whereas the number of sebaceous glands and the number of hair follicles significantly differed. Compared with zebu cattle, Creole Harton del Valle cattle presented a lower number of hair follicles, sweat glands and sebaceous glands.
C1 [Campos, Romulo; Manzano, Jose Luis; Velez, Mauricio] Univ Nacl Colombia Sede Palmira, Palmira, Colombia.
   [Avila, Hector] Fdn Univ Juan De Castellanos, Tunja Boyaca, Colombia.
C3 Universidad Nacional de Colombia
RP Campos, R (corresponding author), Univ Nacl Colombia Sede Palmira, Palmira, Colombia.
OI Campos-Gaona, Romulo/0000-0002-8626-4888
FU Universidad Nacional de Colombia, campus Palmira, Project Hermes
FX This research was funded by the Universidad Nacional de Colombia, campus
   Palmira, Project Hermes 60026-2023.
CR Adamina M, 2022, COLORECTAL DIS, V24, P708, DOI 10.1111/codi.16117
   Arango Gaviria Juliana, 2017, Ces. Med. Vet. Zootec., V12, P44, DOI 10.21615/cesmvz.12.1.4
   Asres A., 2014, J. Biol. Agric. Healthc, V4, P146
   Baker Lindsay B, 2019, Temperature (Austin), V6, P211, DOI 10.1080/23328940.2019.1632145
   Calicioglu O, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11010222
   Carvalho FA, 1995, J ANIM SCI, V73, P3570
   Das P, 2014, EXPLOR ANIM MED RES, V4, P183
   Henao FJ, 1986, Revista Veterinaria y Zootecnia de Caldas, V5, P63
   Holdridge L., 1982, Zonas de vida
   Jian W, 2014, INT J BIOMETEOROL, V58, P1087, DOI 10.1007/s00484-013-0700-9
   Landaeta-Hernández A, 2011, TROP ANIM HEALTH PRO, V43, P657, DOI 10.1007/s11250-010-9749-1
   Mateescu RG, 2023, FRONT GENET, V14, DOI 10.3389/fgene.2023.1107468
   Mohammed ESI, 2022, EXCLI J, V21, P1286, DOI 10.17179/excli2022-5335
   Nascimento CCN, 2019, J THERM BIOL, V86, DOI 10.1016/j.jtherbio.2019.102443
   Nascimento M. R. B. de M., 2015, Revista Ceres, V62, P129
   Rotter D, 2014, J MOL CELL CARDIOL, V74, P103, DOI 10.1016/j.yjmcc.2014.05.004
   Sanmiguel-Plaza RA, 2011, Revista Colombiana de Ciencia Animal, V4, P1
NR 17
TC 0
Z9 0
U1 0
U2 0
PU MALQUE PUBLISHING
PI MOSSORO
PA RUA DA PITOMBA, 703, MOSSORO, 59630-830, BRAZIL
EI 2318-1265
J9 J ANIM BEHAV BIOMETE
JI J. Anim. Behav. Biometeorol.
PD JUL
PY 2024
VL 12
IS 3
AR e2024024
DI 10.31893/jabb.2024024
PG 6
WC Agriculture, Dairy & Animal Science
WE Emerging Sources Citation Index (ESCI)
SC Agriculture
GA O1E1G
UT WOS:001368632800004
OA gold
DA 2025-01-10
ER

PT J
AU Eriksson, K
   Sjöström, J
   Plathner, FV
AF Eriksson, Kerstin
   Sjostrom, Johan
   Plathner, Frida Vermina
TI "This community will grow" - little concern for future wildfires in a
   dry and increasingly hotter Swedish rural community
SO REGIONAL ENVIRONMENTAL CHANGE
LA English
DT Article
DE Wildfire; Storyline; Narratives; Climate adaptation; Sweden
ID CLIMATE-CHANGE; FOREST-FIRES; DISASTER; RECOVERY; PLACE; RESPONSIBILITY;
   MANAGEMENT; DYNAMICS; EVENTS; HAZARD
AB Increased risk of wildfires is often highlighted in media coverage of climate change in the Nordic countries. How an increased risk is reflected in the concerns and adaptive measures within the most likely affected communities is nevertheless not known. This study investigates concerns and adaptation to wildfires in a rural community in south-eastern Sweden. The comparatively dry study area has a history of frequent but often low-consequence wildfires and is projected to experience Sweden's largest increase in severe fire weather towards 2100. Through narratives, this study elucidates potential wildfire concerns in this area and motivations behind adaptation measures. The narratives are compared to a physical causal network extracted from the literature on fires and their consequences in the region. Residents foresee an increased wildfire risk but do not consider it a threat to the future well-being of the community. Forest owners and homeowners express low commitment in preventive or adaptive measures. Instead, contrasting the reality of the twentieth century, the fire service is currently considered to be responsible for both preventing and suppressing fires. This attitude is attributed to the lack of severe implications from the generally well-managed fires in the region. Actions for prevention and adaptation seem triggered by media attention or experience from real high-consequence events occurring elsewhere, rather than local wildfire occurrence or climate change projections.
C1 [Eriksson, Kerstin; Sjostrom, Johan; Plathner, Frida Vermina] RISE Res Inst Sweden, Dept Fire & Safety, Scheelevagen 17, Ideon Beta 5, SE-22370 Lund, Sweden.
C3 RISE Research Institutes of Sweden
RP Eriksson, K (corresponding author), RISE Res Inst Sweden, Dept Fire & Safety, Scheelevagen 17, Ideon Beta 5, SE-22370 Lund, Sweden.
EM kerstin.eriksson@ri.se
RI Eriksson, Kerstin/AAJ-4848-2021; Plathner, Frida/LFU-9857-2024
OI Sjostrom, Johan/0000-0001-8670-062X; Vermina Plathner,
   Frida/0000-0001-5420-164X; Eriksson, Kerstin/0000-0002-0494-0089
FU Nordforsk
FX Francine Amon and Jonathan Gehandler are gratefully acknowledged for
   feedback on the manuscript and transcription, respectively. We would
   also like to thank our respondents and the reviewers and editors for
   their helpful feedback.
CR Ahti T., 1968, Annales Botanici Fennici, Helsinki, V5, P168
   Andresen SA, 2017, INT J DISAST RISK RE, V21, P27, DOI 10.1016/j.ijdrr.2016.11.009
   Andrews P.L., 1986, General Technical Report INT-194
   [Anonymous], 2004, Int For Fire News
   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]
   Aronsson M, 1980, Vitterhetsakademins konferenser, V4, P221
   Bateson M.C., 2007, Interchange, V38, P213, DOI DOI 10.1007/S10780-007-9030-3
   Berg BL, 2004, QUALITATIVE RES METH
   Bjorklund A, 2019, SVT Nyheter
   Bjornheden R, 2019, Report 1012-2019
   Brenkert-Smith H, 2012, ENVIRON MANAGE, V50, P1139, DOI 10.1007/s00267-012-9949-8
   Brohult L, 2019, SVT Nyheter,March 11
   Carroll MS, 2006, RURAL SOCIOL, V71, P261, DOI 10.1526/003601106777789701
   Carroll MS, 2011, SOC NATUR RESOUR, V24, P672, DOI 10.1080/08941921003681055
   Cohen JD, 2000, J FOREST, V98, P15
   Dickson-Hoyle S, 2021, SOC NATUR RESOUR, V34, P311, DOI 10.1080/08941920.2020.1819494
   DSB, 2014, Technical report
   Dupuy JL, 2020, ANN FOREST SCI, V77, DOI 10.1007/s13595-020-00933-5
   EAA European Environment Agency, 2021, Forest fires in Europe
   Edgeley CM, 2017, INT J DISAST RISK RE, V25, P137, DOI 10.1016/j.ijdrr.2017.09.009
   Eriksson K, 2023, The Modern Guide to the Multiple Streams Framework, P246, DOI [10.4337/9781802209822.00023, DOI 10.4337/9781802209822.00023]
   Evans J, 2011, APPL GEOGR, V31, P849, DOI 10.1016/j.apgeog.2010.09.005
   Granstrom A, 1990, Utveckling av vegetation och insektsfauna efter skogsbrand i sodra Sverige, slutrapport5316036-2
   Granström A, 2023, INT J WILDLAND FIRE, V32, P320, DOI 10.1071/WF22085
   Hanes CC, 2019, CAN J FOREST RES, V49, P256, DOI 10.1139/cjfr-2018-0293
   IPCC, 2023, Representative Concentration Pathways (RCPs)
   Johansson R, 2018, J CONTING CRISIS MAN, V26, P519, DOI 10.1111/1468-5973.12228
   Knez I, 2021, J ENVIRON PSYCHOL, V74, DOI 10.1016/j.jenvp.2021.101554
   Lidskog R, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10124457
   Lidskog R, 2016, SCAND J FOREST RES, V31, P148, DOI 10.1080/02827581.2015.1113308
   Malmberg G., 2010, EUR REG, V16, P191
   Manca A.R., 2014, Encyclopedia of Quality of Life and Well-Being Research, DOI [10.1007/978-94-007-0753-5_2739/, DOI 10.1007/978-94-007-0753-5_2739, 10.1007/978-94-007-0753-5_2739]
   Mortreux C, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab7834
   MSB [The Swedish Civil Contingencies Agency], 2022, indikatorer data analys
   Niklasson M., 2011, Brandhistorik i sydostra Sverige. Lansstyrelsens meddelandeserie, V2011, P14
   Norris FH, 2008, AM J COMMUN PSYCHOL, V41, P127, DOI 10.1007/s10464-007-9156-6
   Paschen JA, 2014, RES POLICY, V43, P1083, DOI 10.1016/j.respol.2013.12.006
   Patterson L, 2008, GEND MANAG, V23, P458, DOI 10.1108/17542410810897562
   Paveglio TB, 2019, FIRE-BASEL, V2, DOI 10.3390/fire2020026
   Petridou E, 2024, POLICY STUD J, V52, P73, DOI 10.1111/psj.12508
   Plathner FV, 2023, SAFETY SCI, V157, DOI 10.1016/j.ssci.2022.105928
   Reid K, 2020, GEOFORUM, V109, P35, DOI 10.1016/j.geoforum.2019.12.015
   Reid K, 2018, SOC NATUR RESOUR, V31, P442, DOI 10.1080/08941920.2017.1421734
   Russ A, 2015, J ENVIRON EDUC, V46, P73, DOI 10.1080/00958964.2014.999743
   SCB [Statistics Sweden], 2022, Markanvandningen i Sverige
   Schimmel J, 1997, CAN J FOREST RES, V27, P1207, DOI 10.1139/x97-072
   Seebauer S, 2018, J FLOOD RISK MANAG, V11, P305, DOI 10.1111/jfr3.12313
   SFS, SFS 2003:789
   SFS, SFS 2003:778
   Shepherd TG, 2019, P ROY SOC A-MATH PHY, V475, DOI 10.1098/rspa.2019.0013
   Shepherd TG, 2018, CLIMATIC CHANGE, V151, P555, DOI 10.1007/s10584-018-2317-9
   Silver A, 2015, J ENVIRON PSYCHOL, V42, P32, DOI 10.1016/j.jenvp.2015.01.004
   Sjöström J, 2023, FIRE SAFETY J, V136, DOI 10.1016/j.firesaf.2023.103743
   Sjostrom J, 2024, MSB 2300
   Sjostrom J, 2023, Brandsakert #5, V2023, P40
   SMHI, 2022, Ladda ner meteorologiska observationer
   SMHI, 2021, Enkel klimatscenariotjanst
   STOCKS BJ, 1989, FOREST CHRON, V65, P450, DOI 10.5558/tfc65450-6
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Swedish Forest Agency, 2021, Fastighetsoch agarstruktur i skogsbruk 2020, Sveriges officiella statistik JO1405
   Swedish Forest Agency, 2023, The forestry plan - an important tool
   Thaler T, 2019, ENVIRON SCI POLICY, V94, P101, DOI 10.1016/j.envsci.2018.12.012
   Twigg J., 2009, Characteristics of a disaster-resilient community
   Valinger E, 2011, FOREST ECOL MANAG, V262, P398, DOI 10.1016/j.foreco.2011.04.004
   Vallianou K., 2020, INT J PSYCHOL BEHAV, V14, P411
   van Vuuren DP, 2011, CLIMATIC CHANGE, V109, P5, DOI [10.1007/s10584-011-0148-z, 10.1007/s10584-011-0157-y]
   Van Wagner C. E., 1987, 35 CAN FOR SERV
   Van Wagner CE, 1970, Information Report PS-X-21
   Vermina Plathner F, 2022, ADV FOREST FIRE RES, P1157, DOI DOI 10.14195/978-989-26-2298-9_176
   Winter G, 2000, SOC NATUR RESOUR, V13, P33, DOI 10.1080/089419200279225
   Yang W, 2015, NAT HAZARD EARTH SYS, V15, P2037, DOI 10.5194/nhess-15-2037-2015
NR 71
TC 1
Z9 1
U1 1
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 JUN
PY 2024
VL 24
IS 2
AR 69
DI 10.1007/s10113-024-02227-2
PG 14
WC Environmental Sciences; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA OG4Y3
UT WOS:001206114900001
OA hybrid
DA 2025-01-10
ER

PT J
AU Biella, R
   Mazzoleni, M
   Brandimarte, L
   Di Baldassarre, G
AF Biella, Riccardo
   Mazzoleni, Maurizio
   Brandimarte, Luigia
   Di Baldassarre, Giuliano
TI Thinking systemically about climate services: Using archetypes to reveal
   maladaptation
SO CLIMATE SERVICES
LA English
DT Article
DE Climate Services; Maladaptation; System Archetypes; Adaptation;
   Inequality; Socio-ecological Systems; Co-creation
ID SOCIAL PREPAREDNESS; GLOBAL FRAMEWORK; FLOOD; ADAPTATION; DYNAMICS;
   RISK; LESSONS; SYSTEMS; IMPACT
AB Developing and implementing climate adaptation measures in complex socio-ecological systems can lead to unintended consequences, especially when those systems are undergoing rapid hydro -climatic and socioeconomic change. In these dynamic contexts, a systemic approach can make the difference between adaptive and maladaptive outcomes. This paper focuses on the use of climate services, often touted as no -regret solutions, and their potential to generate maladaptation. We explored the interactions between climate services and adaptation/maladaptation across five case studies affected by different types of natural hazards and characterized by a range of hydro -climatic and socio-economic conditions. Using system archetypes, we show how climate services can play a role in both producing and preventing maladaptation. The dynamics explored through system archetypes are: i) "fixes that fail", where short-sighted solutions fail to address the root causes of a problem; ii) "band aid solutions", where the benefits brought about in the short-term come at the expenses of delaying longterm adaptive actions; and iii) "success to the successful", where some groups increasingly benefit from climate services at the expenses of other groups. We demonstrate how these dynamics constitute maladaptive processes, as well as identifying the tools and theories that can be used in this type of assessment. Finally, we provide a framework and recommendations to guide the ex -ante assessment of maladaptation risk when designing and implementing climate services.
C1 [Biella, Riccardo; Di Baldassarre, Giuliano] Uppsala Univ, Dept Earth Sci, Uppsala, Sweden.
   [Biella, Riccardo; Di Baldassarre, Giuliano] Ctr Nat Hazards & Disaster Sci CNDS, Uppsala, Sweden.
   [Mazzoleni, Maurizio] Vrije Univ Amsterdam, IVM, Amsterdam, Netherlands.
   [Mazzoleni, Maurizio] Karolinska Inst, Dept Global Publ Hlth, Stockholm, Sweden.
   [Brandimarte, Luigia] KTH Stockholm, Dept Environm Engn & Sustainable Infrastruct, Stockholm, Sweden.
C3 Uppsala University; Centre of Natural Hazards & Disaster Science (CNDS);
   Vrije Universiteit Amsterdam; Karolinska Institutet; Royal Institute of
   Technology
RP Biella, R (corresponding author), Uppsala Univ, Dept Earth Sci, Uppsala, Sweden.; Biella, R (corresponding author), Ctr Nat Hazards & Disaster Sci CNDS, Uppsala, Sweden.
EM riccardo.biella@geo.uu.se
RI Mazzoleni, Maurizio/O-2566-2016
OI Biella, Riccardo/0000-0002-0640-5725
FU European Union [101037293]
FX We thank the Anonymous Reviewers for their insightful and constructive
   comments on this article. The research work was partly funded by the
   European Union's Horizon 2020 research and innovation programme under
   the Grant Agreement Number 101037293: ICISK Innovating Climate services
   through Integrating Scientific and local Knowledge.
CR Agovino M, 2019, ECOL INDIC, V105, P525, DOI 10.1016/j.ecolind.2018.04.064
   [Anonymous], 2000, Business Dynamics: Systems Thinking and Modeling for a Complex World
   Ashley L., 2020, Applyin climate services to transformative adapttaion in agriculture
   Barnet AF, 2021, CLIM SERV, V23, DOI 10.1016/j.cliser.2021.100249
   Barnett J, 2010, GLOBAL ENVIRON CHANG, V20, P211, DOI 10.1016/j.gloenvcha.2009.11.004
   Bartelet HA, 2022, REG ENVIRON CHANGE, V22, DOI 10.1007/s10113-022-01909-z
   Basialashvili T, 2015, J ENVIRON BIOL, V36, P33
   Boon E, 2022, CLIM SERV, V27, DOI 10.1016/j.cliser.2022.100314
   Boon E, 2021, FRONT CLIM, V3, DOI 10.3389/fclim.2021.615291
   Bordalo P, 2020, Q J ECON, V135, P1399, DOI 10.1093/qje/qjaa007
   Braman LM, 2013, DISASTERS, V37, P144, DOI 10.1111/j.1467-7717.2012.01297.x
   Guy P, 2016, EARTHS FUTURE, V4, P79, DOI 10.1002/2015EF000338
   Chandler D, 2019, RESILIENCE-ABINGDON, V7, P304, DOI 10.1080/21693293.2019.1605660
   Christel I, 2018, CLIM SERV, V9, P111, DOI 10.1016/j.cliser.2017.06.002
   Clatworthy Y, 2022, Developing triggers for forecast-based financing: how partnerships can strengthen anticipatory action
   Clatworthy Y., 2023, Anticipatory action in practice: acting early ahead of typhoons in the Philippines
   Clatworthy Y., 2023, The co-benefits of forecast-based financing and anticipatory action
   Di Baldassarre G, 2013, HYDROL EARTH SYST SC, V17, P3235, DOI 10.5194/hess-17-3235-2013
   Di Baldassarre G, 2013, HYDROL EARTH SYST SC, V17, P3295, DOI 10.5194/hess-17-3295-2013
   Di Baldassarre G, 2017, EARTH SYST DYNAM, V8, P1, DOI 10.5194/esd-8-225-2017
   Elsawah S, 2017, ENVIRON MODELL SOFTW, V93, P127, DOI 10.1016/j.envsoft.2017.03.001
   Eriksen S, 2011, CLIM DEV, V3, P7, DOI 10.3763/cdev.2010.0060
   Fedele G, 2019, ENVIRON SCI POLICY, V101, P116, DOI 10.1016/j.envsci.2019.07.001
   Fedele G, 2020, ECOL SOC, V25, DOI 10.5751/ES-11381-250125
   Fisher-Vanden K, 2013, CLIMATIC CHANGE, V117, P481, DOI 10.1007/s10584-012-0644-9
   Gain AK, 2020, REG ENVIRON CHANGE, V20, DOI 10.1007/s10113-020-01692-9
   Gain AK, 2021, INT J SUST DEV WORLD, V28, P109, DOI 10.1080/13504509.2020.1780647
   Garcia M, 2021, HYDROLOG SCI J, V66, P919, DOI 10.1080/02626667.2021.1903474
   Garcia M, 2020, J HYDROL, V590, DOI 10.1016/j.jhydrol.2020.125270
   Haer T, 2020, GLOBAL ENVIRON CHANG, V60, DOI 10.1016/j.gloenvcha.2019.102009
   Hallett LM, 2020, RESTOR ECOL, V28, P1017, DOI 10.1111/rec.13220
   Hansen JW, 2019, FRONT SUSTAIN FOOD S, V3, DOI 10.3389/fsufs.2019.00021
   Hewitt CD, 2020, B AM METEOROL SOC, V101, pE237, DOI 10.1175/BAMS-D-18-0211.1
   Hewitt C, 2012, NAT CLIM CHANGE, V2, P831, DOI 10.1038/nclimate1745
   Hewitt CD, 2021, CLIM SERV, V23, DOI 10.1016/j.cliser.2021.100240
   Jacob D., 2015, A European research and innovation roadmap for climate services., DOI [10.2777/702151, DOI 10.2777/702151]
   Jacobs KL, 2020, CLIM SERV, V20, DOI 10.1016/j.cliser.2020.100199
   JPI Climate ERA4CS, 2022, JPI Climate
   Juhola S, 2016, ENVIRON SCI POLICY, V55, P135, DOI 10.1016/j.envsci.2015.09.014
   Kates RW, 2012, P NATL ACAD SCI USA, V109, P7156, DOI 10.1073/pnas.1115521109
   Kirchhoff CJ, 2013, ANNU REV ENV RESOUR, V38, P393, DOI 10.1146/annurev-environ-022112-112828
   Larrosa C, 2016, CONSERV LETT, V9, P316, DOI 10.1111/conl.12240
   Lemos M. C., 2002, The use of seasonal climate forecasting in policymaking: Lessons from Northeast
   Lemos MC, 2012, NAT CLIM CHANGE, V2, P789, DOI [10.1038/NCLIMATE1614, 10.1038/nclimate1614]
   Li JP, 2015, ENCYCL ATMOS SCI 2, V6, P303, DOI [10.1016/B978-0-12-382225-3.00463-1, DOI 10.1016/B978-0-12-382225-3.00463-1]
   Lindberg F, 2018, ENVIRON MODELL SOFTW, V99, P70, DOI 10.1016/j.envsoft.2017.09.020
   Lindenmayer DB, 2010, P NATL ACAD SCI USA, V107, P21957, DOI 10.1073/pnas.1015696107
   Lopez MG, 2017, WATER RESOUR RES, V53, P522, DOI 10.1002/2016WR019387
   Lourenço TC, 2016, NAT CLIM CHANGE, V6, P13, DOI 10.1038/nclimate2836
   Magnan AK, 2016, WIRES CLIM CHANGE, V7, P646, DOI 10.1002/wcc.409
   Manzano M., 2007, Ensenanza De Las Ciencias De La Tierra, V15, P305
   Masih I, 2022, Characterization of the I-CISK Living Labs
   Mason SJ, 2022, CLIM SERV, V27, DOI 10.1016/j.cliser.2022.100306
   MEADOWS D H, 1972, P205
   Mirchi A, 2012, WATER RESOUR MANAG, V26, P2421, DOI 10.1007/s11269-012-0024-2
   Moallemi EA, 2022, EARTHS FUTURE, V10, DOI 10.1029/2022EF002873
   Moser SC, 2014, WIRES CLIM CHANGE, V5, P337, DOI 10.1002/wcc.276
   Musters CJM, 1998, ECOL ECON, V26, P243, DOI 10.1016/S0921-8009(97)00104-3
   Nabavi E, 2017, J CLEAN PROD, V140, P312, DOI 10.1016/j.jclepro.2016.03.032
   Naylor A, 2020, ONE EARTH, V2, P444, DOI 10.1016/j.oneear.2020.04.011
   Nost E, 2019, CLIMATIC CHANGE, V157, P27, DOI 10.1007/s10584-019-02383-z
   Perrels A, 2020, CLIM SERV, V17, DOI 10.1016/j.cliser.2020.100153
   Pruyt E., 2013, Small System Dynamics Models for Big Issues: Triple Jump Towards RealWorld Complexity
   Richardson GP, 2011, SYST DYNAM REV, V27, P219, DOI 10.1002/sdr.462
   Ridolfi E, 2020, HYDROLOG SCI J, V65, P12, DOI 10.1080/02626667.2019.1677907
   Savelli E, 2022, WIRES CLIM CHANGE, V13, DOI 10.1002/wcc.761
   Sawada Y, 2022, HYDROL EARTH SYST SC, V26, P4265, DOI 10.5194/hess-26-4265-2022
   Scott DJ, 2011, CLIM RES, V47, P111, DOI 10.3354/cr00952
   Senge P., 1990, 5 DISCIPLINE
   Soares MB, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.587
   Soares MB, 2018, CLIM SERV, V9, P5, DOI 10.1016/j.cliser.2017.06.001
   Solaraju-Murali B, 2022, CLIM SERV, V27, DOI 10.1016/j.cliser.2022.100303
   Sterman JD, 2001, CALIF MANAGE REV, V43, P8, DOI 10.2307/41166098
   Street RB, 2019, INT J DISAST RISK RE, V34, P28, DOI 10.1016/j.ijdrr.2018.12.001
   Tellman B, 2018, ECOL SOC, V23, DOI [10.5751/ES-09712-230101, 10.5751/es-09712-230101]
   United Nations, 2015, No.A/RES/70/1.
   Vaughan C, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.586
   Vaughan C, 2014, WIRES CLIM CHANGE, V5, P587, DOI 10.1002/wcc.290
   Verburg PH, 2016, GLOBAL ENVIRON CHANG, V39, P328, DOI 10.1016/j.gloenvcha.2015.08.007
   Vincent K, 2020, CLIM SERV, V20, DOI 10.1016/j.cliser.2020.100204
   Vincent K, 2018, CLIM SERV, V12, P48, DOI 10.1016/j.cliser.2018.11.001
   Vulturius G, 2020, J ENVIRON PLANN MAN, V63, P1177, DOI 10.1080/09640568.2019.1646228
   White GF, 1945, THESIS U CHICAGO, P225
   Wilkinson E., 2018, Forecasting, hazards, averting disasters: Implementing forecast-based early action at scale
   Wolstenholme EF, 2003, SYST DYNAM REV, V19, P7, DOI 10.1002/sdr.259
NR 85
TC 0
Z9 0
U1 3
U2 4
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2405-8807
J9 CLIM SERV
JI Clim. Serv.
PD APR
PY 2024
VL 34
AR 100490
DI 10.1016/j.cliser.2024.100490
EA MAY 2024
PG 13
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 UF3X2
UT WOS:001246617000001
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Hamilton, CW
   Smithwick, EAH
   Spellman, KV
   Baltensperger, AP
   Spellman, BT
   Chi, GQ
AF Hamilton, Casey W.
   Smithwick, Erica A. H.
   Spellman, Katie V.
   Baltensperger, Andrew P.
   Spellman, Blaine T.
   Chi, Guangqing
TI Predicting the suitable habitat distribution of berry plants under
   climate change
SO LANDSCAPE ECOLOGY
LA English
DT Article
DE Berries; Boreal; Climate change; Habitat suitability; Random forests;
   Species distribution model
ID SPECIES DISTRIBUTION MODELS; VACCINIUM-ULIGINOSUM; SHRUB EXPANSION;
   HUMAN HEALTH; IMPACTS; SHIFTS; RANGE; VEGETATION; COMMUNITY; RESPONSES
AB ContextClimate change is altering suitable habitat distributions of many species at high latitudes. Fleshy fruit-producing plants (hereafter, "berry plants") are important in arctic food webs and as subsistence resources for human communities, but their response to a warming and increasingly variable climate at a landscape scale has not yet been examined.ObjectivesWe aimed to identify environmental determinants of berry plant distribution and predict how climate change might shift these distributions.MethodsWe used species distribution models to identify characteristics and predict the distribution of suitable habitat under current (2006-2013) and future climate conditions (2081-2100; representative concentration pathways 4.5, 6.0, & 8.5) for five berry plant species: Vaccinium uliginosum L., Empetrum nigrum L., Rubus chamaemorus L., Vaccinium vitis-idaea L., and Viburnum edule (Michx.) Raf..ResultsElevation, soil characteristics, and January and July temperatures were important drivers of habitat distributions. Future suitable habitat predictions showed net declines in suitable habitat area for all species modeled under almost all future climate scenarios tested.ConclusionsOur work contributes to understanding potential geographic shifts in suitable berry plant habitat with climate change at a landscape scale. Shifting and retracting distributions may alter where communities can harvest, suggesting that access to these resources may become restricted in the future. Our prediction maps may help inform climate adaptation planning as communities anticipate shifting access to harvesting locations.
C1 [Hamilton, Casey W.; Smithwick, Erica A. H.] Penn State Univ, Dept Geog, University Pk, PA 16802 USA.
   [Smithwick, Erica A. H.] Penn State Univ, Earth & Environm Syst Inst, University Pk, PA 16802 USA.
   [Spellman, Katie V.; Baltensperger, Andrew P.] Univ Alaska Fairbanks, Int Arctic Res Ctr IARC, Fairbanks, AK 99775 USA.
   [Spellman, Blaine T.] United States Dept Agr, Nat Resources Conservat Serv, Washington, DC USA.
   [Chi, Guangqing] Penn State Univ, Dept Agr Econ Sociol & Educ, University Pk, PA 16802 USA.
   [Chi, Guangqing] Penn State Univ, Social Sci Res Inst, Populat Res Inst, University Pk, PA 16802 USA.
C3 Pennsylvania Commonwealth System of Higher Education (PCSHE);
   Pennsylvania State University; Pennsylvania State University -
   University Park; Pennsylvania Commonwealth System of Higher Education
   (PCSHE); Pennsylvania State University; Pennsylvania State University -
   University Park; University of Alaska System; University of Alaska
   Fairbanks; United States Department of Agriculture (USDA); Pennsylvania
   Commonwealth System of Higher Education (PCSHE); Pennsylvania State
   University; Pennsylvania State University - University Park;
   Pennsylvania Commonwealth System of Higher Education (PCSHE);
   Pennsylvania State University; Pennsylvania State University -
   University Park
RP Hamilton, CW (corresponding author), Penn State Univ, Dept Geog, University Pk, PA 16802 USA.
EM cwh5643@psu.edu
RI Chi, Guangqing/A-6989-2009; Hamilton, Casey/KMY-7365-2024
OI Chi, Guangqing/0000-0003-0888-7964; Smithwick, Erica/0000-0003-3497-2011
FU National Science Foundation; Togiak Natives Ltd; Bristol Bay Native
   Association [1828822, 1927827, 2032790, 2207436, 2220219]; National
   Science Foundation [PEN04623]; USDA National Institute of Food and
   Agriculture and Multistate Research Project [P2C HD041025]; Eunice
   Kennedy Shriver National Institute of Child Health and Human Development
   [G17ACOO213]; Alaska Berry Futures Project
FX We thank the NRCS for making berry plant location data available to us,
   and for comments and contributions from NRCS staff. In particular, we
   thank NRCS scientists Nathan Roe and Dr. Travis Nauman for helpful
   feedback during the review process. We are also grateful to Indigenous
   Alaskan communities and organizations, namely Choggiung Ltd., Togiak
   Natives Ltd, and the Bristol Bay Native Association, for granting
   permission for use of these data collected on their lands in this study.
   Appreciation is extended to the POLARIS team for constructive inputs and
   support throughout the course of this study. The research is supported
   in part by the National Science Foundation (Awards #1828822, #1927827,
   #2032790, #2207436, and #2220219), the USDA National Institute of Food
   and Agriculture and Multistate Research Project #PEN04623, the Eunice
   Kennedy Shriver National Institute of Child Health and Human Development
   (Award # P2C HD041025), and the Alaska Berry Futures Project (US
   Geologic Survey award G17ACOO213 through the Alaska Climate Adaptation
   Science Center).
CR Abolina L, 2023, PLANTS-BASEL, V12, DOI 10.3390/plants12030528
   Anderson D, 2018, HUM ECOL, V46, P849, DOI 10.1007/s10745-018-0038-3
   [Anonymous], 2022, Gridded Soil Survey Geographic
   [Anonymous], 2010, ENCY LIFE SCI, DOI [DOI 10.1002/9780470015902.A0022548, 10.1002/9780470015902.a0022548]
   Antao LH, 2022, NAT CLIM CHANGE, V12, P587, DOI 10.1038/s41558-022-01381-x
   Bagaria P, 2021, CLIM RISK MANAG, V31, DOI 10.1016/j.crm.2020.100264
   Baltensperger AP, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0132054
   Beauregard F, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0092642
   BELL JNB, 1973, J ECOL, V61, P289, DOI 10.2307/2258934
   Bever JD, 1997, J ECOL, V85, P561, DOI 10.2307/2960528
   Biau G, 2016, TEST-SPAIN, V25, P197, DOI 10.1007/s11749-016-0481-7
   Billerman SM, 2016, ECOL EVOL, V6, P7976, DOI 10.1002/ece3.2507
   Blewitt ME, 2008, NAT GENET, V40, P663, DOI 10.1038/ng.142
   Bokhorst S, 2008, GLOBAL CHANGE BIOL, V14, P2603, DOI 10.1111/j.1365-2486.2008.01689.x
   Bokhorst S, 2011, GLOBAL CHANGE BIOL, V17, P2817, DOI 10.1111/j.1365-2486.2011.02424.x
   Boulanger-Lapointe N, 2019, HUM ECOL, V47, P81, DOI 10.1007/s10745-018-0044-5
   Breiman L, 2001, MACH LEARN, V45, P5, DOI 10.1023/A:1010933404324
   Breiman L., 2001, Machine Learning, V45, P5, DOI 10.1023/A:1010933404324
   Breshears DD, 2008, P NATL ACAD SCI USA, V105, P11591, DOI 10.1073/pnas.0806579105
   Brinkman TJ, 2016, CLIMATIC CHANGE, V139, P413, DOI 10.1007/s10584-016-1819-6
   Bristol Bay Native Corporation, 2016, Bristol Bay Regional Guide
   Chatterjee S., 2006, REGRESSION ANAL EXAM, DOI DOI 10.1002/0470055464
   Chauvier Y, 2021, ECOL MONOGR, V91, DOI 10.1002/ecm.1433
   Chen C., 2004, Technical Report, V110, P24
   Chen IC, 2011, SCIENCE, V333, P1024, DOI 10.1126/science.1206432
   Clark John H., 2006, ALASKA FISHERY RESEARCH BULLETIN, V12, P1
   Coudun C, 2006, J BIOGEOGR, V33, P1750, DOI 10.1111/j.1365-2699.2005.01443.x
   de Witte LC, 2012, MOL ECOL, V21, P1081, DOI 10.1111/j.1365-294X.2011.05326.x
   Deacy WW, 2017, P NATL ACAD SCI USA, V114, P10432, DOI 10.1073/pnas.1705248114
   Drew CA, 2011, PREDICTIVE SPECIES AND HABITAT MODELING IN LANDSCAPE ECOLOOGY: CONCEPTS AND APPLICATIONS, P1, DOI 10.1007/978-1-4419-7390-0
   Ebrahimi A, 2022, FRONT FOR GLOB CHANG, V10, DOI 10.3389/ffgc.2022.970379
   Elith J, 2006, ECOGRAPHY, V29, P129, DOI 10.1111/j.2006.0906-7590.04596.x
   Elith J, 2009, ANNU REV ECOL EVOL S, V40, P677, DOI 10.1146/annurev.ecolsys.110308.120159
   Evans JS, 2011, PREDICTIVE SPECIES AND HABITAT MODELING IN LANDSCAPE ECOLOOGY: CONCEPTS AND APPLICATIONS, P139, DOI 10.1007/978-1-4419-7390-0_8
   Evans S, 2010, Technical Paper No. 375
   Feng L, 2020, FORESTS, V11, DOI 10.3390/f11080891
   Freeman EA, 2018, Modelmap: an R package for model creation and map production, V69
   Freeman EA, 2008, J STAT SOFTW, V23, P1
   Garamvoelgyi A, 2013, APPL ECOL ENV RES, V11, P79, DOI 10.15666/aeer/1101_079122
   Gaston KJ, 2001, GLOBAL ECOL BIOGEOGR, V10, P179, DOI 10.1046/j.1466-822x.2001.00225.x
   Genuer Robin, 2022, CRAN
   Genuer R, 2010, PATTERN RECOGN LETT, V31, P2225, DOI 10.1016/j.patrec.2010.03.014
   Gilman SE, 2010, TRENDS ECOL EVOL, V25, P325, DOI 10.1016/j.tree.2010.03.002
   Gould K, 2013, Viburnum edule: lowbush cranberry, mooseberry, squashberry, squawberry, crampbark, pembina, DOI [10.7939/R34M91C8X, DOI 10.7939/R34M91C8X]
   Guisan A, 2000, ECOL MODEL, V135, P147, DOI 10.1016/S0304-3800(00)00354-9
   Hanspach J, 2010, PERSPECT PLANT ECOL, V12, P219, DOI 10.1016/j.ppees.2010.04.002
   Hengl T, 2018, PEERJ, V6, DOI 10.7717/peerj.5518
   Herman-Mercer NM, 2020, HUM ECOL, V48, P85, DOI 10.1007/s10745-020-00138-4
   Hijmans Robert J, 2023, CRAN
   Hirabayashi K, 2022, SCI TOTAL ENVIRON, V845, DOI 10.1016/j.scitotenv.2022.157341
   Holloway P, 2006, Managing wild bog blueberry, lingonberry, cloudberry and crowberry stands in Alaska, P16
   Hupp J, 2015, INT J CIRCUMPOL HEAL, V74, DOI 10.3402/ijch.v74.28704
   Hupp JW, 2013, POLAR BIOL, V36, P1243, DOI 10.1007/s00300-013-1343-3
   IPCC, 2022, Climate Change 2022: Impacts, Adaptation and Vulnerability, DOI DOI 10.1017/9781009325844
   Iverson LR, 2019, FORESTS, V10, DOI 10.3390/f10040302
   Jacquemart AL, 1996, J ECOL, V84, P771, DOI 10.2307/2261339
   Jiménez-Valverde A, 2007, ACTA OECOL, V31, P361, DOI 10.1016/j.actao.2007.02.001
   Karst AL, 2011, ETHNOBIOL LETT, V2, P6
   Kearney M, 2009, ECOL LETT, V12, P334, DOI 10.1111/j.1461-0248.2008.01277.x
   Kellogg J, 2010, J AGR FOOD CHEM, V58, P3884, DOI 10.1021/jf902693r
   Krebs CJ, 2010, J MAMMAL, V91, P500, DOI 10.1644/09-MAMM-A-005.1
   Kuhn M, 2008, J STAT SOFTW, V28, P1, DOI 10.18637/jss.v028.i05
   Lenoir J, 2020, NAT ECOL EVOL, V4, P1044, DOI 10.1038/s41559-020-1198-2
   Li Q, 2022, HORTICULTURAE, V8, DOI 10.3390/horticulturae8121202
   MARKS TC, 1978, ANN BOT-LONDON, V42, P165, DOI 10.1093/oxfordjournals.aob.a085437
   Masson-Delmotte V, 2021, CLIMATE CHANGE 2021, DOI DOI 10.1017/9781009157896
   McGuire AD, 2009, ECOL MONOGR, V79, P523, DOI 10.1890/08-2025.1
   Mekonnen ZA, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abf28b
   Fernandes ACM, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12187657
   Mulder CPH, 2019, BOTANY, V97, P347, DOI 10.1139/cjb-2018-0209
   Myers-Smith IH, 2011, ENVIRON RES LETT, V6, DOI 10.1088/1748-9326/6/4/045509
   Naimi B, 2014, ECOGRAPHY, V37, P191, DOI 10.1111/j.1600-0587.2013.00205.x
   Nestby R, 2019, J BERRY RES, V9, P515, DOI 10.3233/JBR-190390
   Niskanen AKJ, 2019, DIVERS DISTRIB, V25, P809, DOI 10.1111/ddi.12889
   Oke OA, 2015, ECOL MODEL, V301, P72, DOI 10.1016/j.ecolmodel.2015.01.019
   Parmesan C, 2006, ANNU REV ECOL EVOL S, V37, P637, DOI 10.1146/annurev.ecolsys.37.091305.110100
   Pearson RG, 2013, NAT CLIM CHANGE, V3, P673, DOI [10.1038/nclimate1858, 10.1038/NCLIMATE1858]
   Pebesma E, 2018, R J, V10, P439
   Pecl GT, 2017, SCIENCE, V355, DOI 10.1126/science.aai9214
   Pielke R, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac4ebf
   Prevéy JS, 2020, AGR FOREST METEOROL, V280, DOI 10.1016/j.agrformet.2019.107803
   Ramalho Q, 2023, BIOL CONSERV, V279, DOI 10.1016/j.biocon.2023.109911
   Rantanen M, 2022, COMMUN EARTH ENVIRON, V3, DOI 10.1038/s43247-022-00498-3
   Redwood DG, 2008, INT J CIRCUMPOL HEAL, V67, P335, DOI 10.3402/ijch.v67i4.18346
   Regos A, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-40766-5
   Reich RM, 2018, J SUSTAIN FOREST, V37, P525, DOI 10.1080/10549811.2018.1433047
   Riahi K, 2011, CLIMATIC CHANGE, V109, P33, DOI 10.1007/s10584-011-0149-y
   Roe NA, 2022, J BIOGEOGR, V49, P753, DOI 10.1111/jbi.14344
   Scenarios Network for Alaska + Arctic Planning, 2015, Projected monthly and derived temperature products-771m CMIP5/AR5
   Seider JH, 2022, ARCT ANTARCT ALP RES, V54, P488, DOI 10.1080/15230430.2022.2121243
   Sofaer HR, 2019, BIOSCIENCE, V69, P544, DOI 10.1093/biosci/biz045
   Soil Survey Staff United States Department of Agriculture Natural Resources Conservation Service., 2022, Togiak National WildlifeRefuge
   Soil Survey Staff United States Department of Agriculture Natural Resources Conservation Service., 2022, Bristol Bay-Northern Alaska Peninsula,
   STEVENS GC, 1989, AM NAT, V133, P240, DOI 10.1086/284913
   SWETS JA, 1988, SCIENCE, V240, P1285, DOI 10.1126/science.3287615
   Syphard AD, 2010, J VEG SCI, V21, P177, DOI 10.1111/j.1654-1103.2009.01133.x
   Tape K, 2006, GLOBAL CHANGE BIOL, V12, P686, DOI 10.1111/j.1365-2486.2006.01128.x
   TAYLOR K, 1971, J ECOL, V59, P293, DOI 10.2307/2258468
   Team RC, 2021, R LANGUAGE ENV STAT
   Thiem B., 2003, Biol Lett, V40, P14
   Thomas CD, 2010, DIVERS DISTRIB, V16, P488, DOI 10.1111/j.1472-4642.2010.00642.x
   Thomson AM, 2011, CLIMATIC CHANGE, V109, P77, DOI 10.1007/s10584-011-0151-4
   Thuiller W, 2013, J VEG SCI, V24, P591, DOI 10.1111/jvs.12076
   United States Department of Agriculture Natural Resources Conservation Service, 2022, Agriculture Handbook, V296
   Valavi R, 2021, ECOGRAPHY, V44, P1731, DOI 10.1111/ecog.05615
   Van Beest FM, 2021, DIVERS DISTRIB, V27, P1706, DOI 10.1111/ddi.13362
   van Vuuren DP, 2011, CLIMATIC CHANGE, V109, P5, DOI [10.1007/s10584-011-0148-z, 10.1007/s10584-011-0157-y]
   Wang WJ, 2018, SCI TOTAL ENVIRON, V634, P1214, DOI 10.1016/j.scitotenv.2018.03.353
   Wilson RJ, 2005, ECOL LETT, V8, P1138, DOI 10.1111/j.1461-0248.2005.00824.x
   Xu WH, 2023, SCI TOTAL ENVIRON, V877, DOI 10.1016/j.scitotenv.2023.162722
NR 110
TC 1
Z9 1
U1 16
U2 32
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 FEB 7
PY 2024
VL 39
IS 2
AR 18
DI 10.1007/s10980-024-01839-7
PG 22
WC Ecology; Geography, Physical; Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Physical Geography; Geology
GA HW8J4
UT WOS:001162634300001
OA hybrid
DA 2025-01-10
ER

PT J
AU Marrah, MY
   Fall, M
   Almansour, H
AF Marrah, Mohammed Yassir
   Fall, Mamadou
   Almansour, Husham
TI Numerical simulation of ground thermal response in Canadian seasonal
   frost regions to climate warming
SO INTERNATIONAL JOURNAL OF GEO-ENGINEERING
LA English
DT Article
DE Climate change; Seasonal frost; Freeze-thaw cycles; Soils; Geotechnical;
   Foundation
ID PERMAFROST
AB To ensure that public infrastructure can safely provide essential services and support economic activities in seasonal frost regions, the design of their foundation systems must be updated and/or adapted to the impacts of climate change. This objective can only be achieved, if the impact of global warming on the soil thermal behaviour in Canadian seasonal frost regions is well-known and can be predicted. In the present paper, the results of a modeling study to assess and predict the effect of global warming on the thermal regimes of grounds in three Canadian seasonal frost regions (Ottawa, Sudbury, Toronto) are presented and discussed. The results show that future climate changes will significantly affect the soil thermal regimes in seasonal frost Canadian areas. The simulation results indicated a gradual loss in the frost penetration depth due to the climate change, in the three representative sites. The frost period duration will be shorter due to climate change in the three selected regions and will completely disappear in Ottawa and Toronto. However, the impact of climate change would not appear clearly in the first 40 years "up to 2060". The response of the ground to the effect of climate change is a function of the geotechnical characteristics of the ground and the climate conditions. The numerical tool developed and results obtained will be useful for the geotechnical design of climate-adaptive transportation structures in Canadian seasonal frost areas.
C1 [Marrah, Mohammed Yassir; Fall, Mamadou] Univ Ottawa, Dept Civil Engn, 161 Colonel By, Ottawa, ON K1N 6N5, Canada.
   [Almansour, Husham] Natl Res Council Canada, Ottawa, ON, Canada.
C3 University of Ottawa; National Research Council Canada
RP Fall, M (corresponding author), Univ Ottawa, Dept Civil Engn, 161 Colonel By, Ottawa, ON K1N 6N5, Canada.
EM mfall@uottawa.ca
FU National Research Council Canada
FX The study was supported by National Research Council Canada.
CR Booshehrian A, 2020, ACTA GEOTECH, V15, P883, DOI 10.1007/s11440-019-00786-x
   BUSH E, 2019, CANADAS CHANGING CLI
   Charron I, 2014, Ouranos, P86
   Chen YZ, 2020, COLD REG SCI TECHNOL, V176, DOI 10.1016/j.coldregions.2020.103091
   Crawford CB, 2002, NRC publications archive archives des publications du CNRC cool under fire
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Flynn DJ, 2015, Field and numerical studies of an instrumented highway Embankment in degrading Permafrost
   GEO-SLOPE International Ltd, 2014, Thermal modeling with TEMP/W 2014
   Goncharova OY, 2019, CATENA, V183, DOI 10.1016/j.catena.2019.104224
   Government of Canada, 2019, Climate data viewer
   Government of Canada, 2018, Senarios and climate models
   Government of Canada, 2011, Historical climate record
   Grasby Se, 2009, geological survey of Canada open file 6167, P35
   Marrah M, 2021, Numerical modeling of thermal and geotechnical response of soils in Canadian no-permafrost regions to climate warming, P191
   Meteoblue, 2019, Weather Ottawa
   Meteoblue, 2018, Weather Sudbury
   Meteoblue, 2018, Weather Toronto
   Natural Resources Canada, 2010, Geological survey of Canada
   Orlando B. A., 2004, Frozen Ground Engineering, V4th
   Osborn TJ, 2014, EARTH SYST SCI DATA, V6, P61, DOI 10.5194/essd-6-61-2014
   Panikom N, 2020, Climate change impact on rainfall-induced landslides in Ottawa sensitive marine clays, P214
   Rasmussen LH, 2018, COLD REG SCI TECHNOL, V146, P199, DOI 10.1016/j.coldregions.2017.10.011
   Slattery SR, 2011, Bedrock topography and sediment thickness mapping in the Edmonton-Calgary Corridor, Central Alberta: an overview of protocols and methodologies
   Smith MW, 2002, PERMAFROST PERIGLAC, V13, P1, DOI 10.1002/ppp.410
   Zhang TJ, 2005, REV GEOPHYS, V43, DOI 10.1029/2004RG000157
   Zhang X., 2019, Canada's changing climate report, P112
   Zhou FQ, 2009, COLD REG SCI TECHNOL, V56, P141, DOI 10.1016/j.coldregions.2008.12.004
NR 27
TC 5
Z9 5
U1 0
U2 1
PU SPRINGER SINGAPORE PTE LTD
PI SINGAPORE
PA 152 Beach Road, #21-01 Gateway East, SINGAPORE, SINGAPORE
SN 2092-9196
EI 2198-2783
J9 INT J GEO-ENG
JI Int. J. Geo-Eng.
PD SEP 27
PY 2023
VL 14
IS 1
AR 16
DI 10.1186/s40703-023-00196-9
PG 33
WC Engineering, Geological
WE Emerging Sources Citation Index (ESCI)
SC Engineering
GA T4KN6
UT WOS:001077694700001
OA gold
DA 2025-01-10
ER

PT J
AU Alemu, M
   Dessale, M
AF Alemu, Melese
   Dessale, Moges
TI Impacts of small-scale irrigation on rural households' income in north
   eastern Ethiopia
SO SUSTAINABLE WATER RESOURCES MANAGEMENT
LA English
DT Article
DE Binary logit model; Income; Propensity score matching; Small-scale
   irrigation
ID PROPENSITY SCORE; PROGRAMS
AB Irrigation is one means by which agricultural production can be increased to meet the growing food demand in Ethiopia. Small-scale irrigation is becoming the main mechanism in livelihood enhancement discourse especially in recent times when the rainfall pattern is becoming erratic in the country. Small-scale irrigation is a policy priority in Ethiopia for rural poverty alleviation and growth, as well as climate adaptation. The aim of the study is to examine the effect of small-scale irrigation on income of rural household in the North Eastern Ethiopia. The study used Taro proportional sampling techniques formula to get 200 sampling respondents of irrigation and non-irrigation users. Econometric model such as Propensity Score Matching method and binary logistic regression model were used to study the specific objectives, impact of use of small-scale irrigation on households' income and determinants of smallholder farmers' decision to participate in small-scale irrigation water use, respectively. The Propensity Score Matching model using logit estimate indicated that family size, credit access and subsidy with productive safety net program were found positive significant effect. The logit model discovered that sex, livestock holding size, dwelling distance from irrigation farm, and subsidy by productive safety net programme and credit access have determinant effect on decision participation in small-scale irrigation. Therefore, attention should be given by the government in expanding of modern irrigation practice and constructing improved storage house should be given priorities.
C1 [Alemu, Melese] Kebri Dehar Univ, Dept Agr Econ, Kebri Dehar, Ethiopia.
   [Dessale, Moges] Wollo Univ, Dept Agr Econ, POB 1145, Dessie, Ethiopia.
RP Dessale, M (corresponding author), Wollo Univ, Dept Agr Econ, POB 1145, Dessie, Ethiopia.
EM melesealemu10@gmail.com; mogesd2255@gmail.com
RI Alemu, Moges/AEM-5306-2022
OI Dessale, Moges/0000-0002-5744-7802
CR [Anonymous], 2006, BUILD PROGR PLAN ACC
   Atnafu T., 2007, CURRENT FUTURE PLANS
   Awulachew B., 2005, EXPERIENCES OPPORTUN
   Baker L., 2000, EVALUATING IMPACT DE, P1, DOI [10.1596/0-8213-4697-0, DOI 10.1596/0-8213-4697-0]
   Becker SO, 2002, STATA J, V2, P358, DOI 10.1177/1536867X0200200403
   Bhattarai M., 2002, IRRIGATION IMPACTS I
   BOARD (Bureau of Agriculture and Rural Development), 2010, ANN REPORT
   Caliendo M, 2008, J ECON SURV, V22, P31, DOI 10.1111/j.1467-6419.2007.00527.x
   Cobb-Clark DA, 2003, ECON REC, V79, P491, DOI 10.1111/j.1475-4932.2003.00148.x
   CSA (Central Statistical Authority), 2011, AGR FIG KEY FIND 200
   CSA (Central Statistical Authority), 2014, ANN REP FED DEM REP
   Dehejia RH, 2002, REV ECON STAT, V84, P151, DOI 10.1162/003465302317331982
   Frenken K., 2005, Irrigation in Africa in figures: AQUASTAT Survey, 2005, V29
   FRIEDLANDER D, 1995, AM ECON REV, V85, P923
   Getinet K, 2011, IMPACT SELECTED SMAL
   GoE (Government of Ethiopia), 2007, CLIMATE CHANGE NATL
   Gujarati D. N., 2003, BASIC ECONOMETRICS
   Gujarati D.N., 2003, BASIC ECONOMETRICS, V4th
   Hadush H., 2014, ADOPTION IMPACT MICR
   Hassen B., 2012, POVERTY FOOD SECURIT, P2
   Hussain I, 2004, IRRIG DRAIN, V53, P1, DOI 10.1002/ird.114
   Ichino A, 2007, J APPL EC
   IWMI (International Water Management Institute), 2010, IRRIGATION POTENTIAL
   Kawachi I., 2008, SOCIAL CAPITAL HLTH
   Leuven Edwin., 2003, PSMATCH2
   Lind J., 2020, LAND INVESTMENT POLI, P1
   Ministry of Agriculture and Rural Development (MoARD), 2006, PROD SAF NET PROGR P
   MOFED, 2010, TRENDS PROSP M MDGS
   MoFED, 2010, Growth and Transformation Plan (2010/11 2014/15); Federal Democratic Republic of Ethiopia
   MoFED, 2010, MILLENNIUM DEV GOALS
   MoWR, 2006, 5 YEAR IRR DEV PROGR
   Panagopoulos A, 2021, ENVIRON SCI POLLUT R, V28, P21009, DOI 10.1007/s11356-021-13332-8
   Pradhan M, 2002, WORLD BANK ECON REV, V16, P275, DOI 10.1093/wber/16.2.275
   Pufahl A, 2009, EUR REV AGRIC ECON, V36, P79, DOI 10.1093/erae/jbp001
   Rahma S, 2016, KHAT IMPACTS NEGATIV
   RKDOA (Raya Kobo District Office of Agriculture), 2017, ANN REP CROP P UNPUB
   RKDOA (Raya Kobo District Office of Agriculture), 2011, ANN REP CROP P UNPUB
   ROSENBAUM PR, 1983, BIOMETRIKA, V70, P41, DOI 10.1093/biomet/70.1.41
   ROSENBAUM PR, 1985, AM STAT, V39, P33, DOI 10.2307/2683903
   Sianesi B, 2004, REV ECON STAT, V86, P133, DOI 10.1162/003465304323023723
   Smith JA, 2005, J ECONOMETRICS, V125, P305, DOI 10.1016/j.jeconom.2004.04.011
   Smith LED, 2004, INT J WATER RESOUR D, V20, P243, DOI 10.1080/0790062042000206084
   Storck H, 1991, Farming systems and farm management practices of smallholders in the Hararghe highlands-a baseline survey
   UNDP, 2007, ANN REP UN DEV PROGR
   Von Braun J., 2008, WHAT EXPECT SCALING, P35
   Woldemariam P., 2017, AM J AGR FORESTRY, V5, P49, DOI [10.11648/j.ajaf.20170503.13, DOI 10.11648/J.AJAF.20170503.13]
   Yamane T., 1967, Statistics: An introductory analysis, V2nd ed
   Zaman H, 2001, ASSESSING POVERTY VU, P34
NR 48
TC 3
Z9 3
U1 1
U2 5
PU SPRINGER INT PUBL AG
PI CHAM
PA GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
SN 2363-5037
EI 2363-5045
J9 SUST WAT RESOUR MAN
JI Sustain. Wat. Resour. Manag.
PD FEB
PY 2022
VL 8
IS 1
AR 15
DI 10.1007/s40899-021-00600-1
PG 20
WC Water Resources
WE Emerging Sources Citation Index (ESCI)
SC Water Resources
GA YI0EB
UT WOS:000743529600001
DA 2025-01-10
ER

PT J
AU Sun, QQ
   Qi, Y
   Long, YF
AF Sun, Qianqian
   Qi, Yan
   Long, Yufei
TI A comparative case study of volcanic-rock vernacular dwelling and modern
   dwelling in terms of thermal performance and climate responsive design
   strategies in Hainan Island
SO JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING
LA English
DT Article
DE Climate-responsive design strategies; traditional volcanic-rock
   dwelling; modern dwelling; indoor environment; Hainan Island
ID BUILDINGS; ARCHITECTURE; VENTILATION; DIVERSITY; COASTAL; COMFORT;
   REGIONS
AB The volcanic-rock dwellings are a special kind of traditional vernacular architecture with high value of research, which located in the north of the Hainan Island in China. In order to clarify the thermal mechanism differences between volcanic-rock dwellings and modern dwellings in Haikou, the main factors affecting the thermal comfort of dwellings are analyzed through investigations of indoor thermal environment in the Yangshan lava area of Haikou. The results show that the volcanic-rock dwelling can achieve 10 h (from 23:30 to 9:30 the next day) with air temperature under 28.7 degrees C in a comfortable thermal indoor environment without air-conditioning cooling equipment, while the rooms on the ground floor of modern dwelling can achieve 1 h around sunrise, and the room on the top floor is completely outside the thermal comfort zone. Temperature difference between exterior and interior of volcanic-rock wall and wooden window can reach a maximum of 6.7 degrees C and 2.8 degrees C respectively, which shows that the envelope of volcanic-rock dwelling has a good thermal insulation performance. It is necessary to inherit the space prototypes and climate-adaptive strategies of traditional residential buildings when designing a new building, which play a significant role on providing a comfortable indoor thermal environment.
C1 [Sun, Qianqian; Qi, Yan; Long, Yufei] Xian Univ Architecture & Technol, Coll Architecture, Xian 710055, Shaanxi, Peoples R China.
   [Sun, Qianqian] Xian Univ Sci & Technol, Coll Architecture & Civil Engn, Xian, Shaanxi, Peoples R China.
C3 Xi'an University of Architecture & Technology; Xi'an University of
   Science & Technology
RP Sun, QQ (corresponding author), Xian Univ Architecture & Technol, Coll Architecture, Xian 710055, Shaanxi, Peoples R China.
EM sunqianqian1024@126.com
RI Sun, Qianqian/KVY-2334-2024
FU National Natural Science Foundation of China [51590913]; Education
   Department of Shaanxi Provincial Government foundation [20JK0237]
FX This work was supported by the National Natural Science Foundation of
   China [51590913]; Education Department of Shaanxi Provincial Government
   foundation [20JK0237].
CR Anna-Maria V, 2009, BUILD ENVIRON, V44, P1095, DOI 10.1016/j.buildenv.2008.05.026
   [Anonymous], 1998, ISO 7726
   [Anonymous], 2005, ERGONOMICS THERMAL E
   Bodach S, 2014, ENERG BUILDINGS, V81, P227, DOI 10.1016/j.enbuild.2014.06.022
   Chen QY, 2009, BUILD ENVIRON, V44, P848, DOI 10.1016/j.buildenv.2008.05.025
   China National Standard, 2012, GBT507852012
   China National Standard, 2013, 500342013 GB
   Chinese National Standard, 2016, Thermal design Code for civil building (GB50176-2016)
   de Dear RJ, 2002, ENERG BUILDINGS, V34, P549, DOI 10.1016/S0378-7788(02)00005-1
   Dili AS, 2010, BUILD ENVIRON, V45, P2218, DOI 10.1016/j.buildenv.2010.04.002
   Dili AS, 2010, ENERG BUILDINGS, V42, P917, DOI 10.1016/j.enbuild.2010.01.002
   Dinghai Y., 2009, HUAZHONG ARCHITECTUR, V3, P224
   Dinghai Y., 2013, Study on the Spatial Morphology of Traditional Settlement and Architecture in Hainan Island
   Du XY, 2016, J ASIAN ARCHIT BUILD, V15, P327, DOI 10.3130/jaabe.15.327
   Dunzhen L., 2019, HIST ANCIENT CHINESE
   Fanger P. O., 1970, Thermal comfort. Analysis and applications in environmental engineering.
   Fernandes J, 2019, RENEW ENERG, V142, P345, DOI 10.1016/j.renene.2019.04.098
   Gui Z., 2015, RES SUITABLE DESIGN
   Helena C., 1998, RENEWABLE SUSTAINABL, V2, P67, DOI DOI 10.1016/S1364-0321(98)00012-4
   Idham NC, 2018, FRONT ARCHIT RES, V7, P317, DOI 10.1016/j.foar.2018.06.006
   Jayasudha P, 2014, INDIAN J TRADIT KNOW, V13, P762
   Jing C., 2019, URBANISM ARCHITECTUR, V16, P26
   Juan G., 2018, CONSTRUCTION MAT DEC, V5, P66
   Kubota T, 2009, ENERG BUILDINGS, V41, P829, DOI 10.1016/j.enbuild.2009.03.008
   Li BZ, 2018, APPL THERM ENG, V129, P693, DOI 10.1016/j.applthermaleng.2017.10.072
   Michael A, 2017, ENERG BUILDINGS, V144, P333, DOI 10.1016/j.enbuild.2017.03.040
   Mohammadi A, 2018, J BUILD ENG, V16, P169, DOI 10.1016/j.jobe.2017.12.014
   Nguyen AT, 2011, BUILD ENVIRON, V46, P2088, DOI 10.1016/j.buildenv.2011.04.019
   Oikonomou A, 2011, BUILD ENVIRON, V46, P669, DOI 10.1016/j.buildenv.2010.09.012
   Oliver Paul, 1997, ENCY VERNACULAR ARCH
   Philokyprou M, 2017, BUILD ENVIRON, V111, P91, DOI 10.1016/j.buildenv.2016.10.010
   Priya RS, 2012, ENERG BUILDINGS, V49, P50, DOI 10.1016/j.enbuild.2011.09.033
   Rijal HB, 2010, BUILD ENVIRON, V45, P2743, DOI 10.1016/j.buildenv.2010.06.002
   Saljoughinejad S, 2015, BUILD ENVIRON, V92, P475, DOI 10.1016/j.buildenv.2015.05.005
   Shijun S., 2019, INTRO GREEN BUILDING
   Toe DHC, 2015, SOL ENERGY, V114, P229, DOI 10.1016/j.solener.2015.01.035
   Upadhyay A.K., 2006, J ASIAN ARCHIT BUILD, V5, P169, DOI DOI 10.3130/JAABE.5.169
   Widera B, 2021, RENEW SUST ENERG REV, V140, DOI 10.1016/j.rser.2021.110736
   Xiong Y., 2011, RES TRADITIONAL CONS
   Yongping W., 2013, HUAZHONG ARCHITECTUR, V1, P132
   Yoshinobu-ashihara, 2017, EXTERIOR DESIGN ARCH
   Zhang YF, 2010, BUILD ENVIRON, V45, P2562, DOI 10.1016/j.buildenv.2010.05.024
NR 42
TC 12
Z9 15
U1 6
U2 87
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 1346-7581
EI 1347-2852
J9 J ASIAN ARCHIT BUILD
JI J. Asian Archit. Build. Eng.
PD JUL 4
PY 2022
VL 21
IS 4
BP 1381
EP 1398
DI 10.1080/13467581.2021.1941990
EA JUL 2021
PG 18
WC Architecture; Construction & Building Technology
WE Science Citation Index Expanded (SCI-EXPANDED); Arts &amp; Humanities Citation Index (A&amp;HCI)
SC Architecture; Construction & Building Technology
GA 0X0WB
UT WOS:000673402300001
OA gold
DA 2025-01-10
ER

PT J
AU Nikanorova, AA
   Barashkov, NA
   Pshennikova, VG
   Nakhodkin, SS
   Gotovtsev, NN
   Romanov, GP
   Solovyev, AV
   Kuzmina, SS
   Sazonov, NN
   Fedorova, SA
AF Nikanorova, Alena A.
   Barashkov, Nikolay A.
   Pshennikova, Vera G.
   Nakhodkin, Sergey S.
   Gotovtsev, Nyurgun N.
   Romanov, Georgii P.
   Solovyev, Aisen V.
   Kuzmina, Sargylana S.
   Sazonov, Nikolay N.
   Fedorova, Sardana A.
TI The Role of Nonshivering Thermogenesis Genes on Leptin Levels Regulation
   in Residents of the Coldest Region of Siberia
SO INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
LA English
DT Article
DE leptin; nonshivering thermogenesis; UCP1; cold climate; adaptation;
   adipose tissue; Yakut population; Siberia; Russia
ID BROWN ADIPOSE-TISSUE; METABOLIC ADAPTATION; BLOOD-PRESSURE; POMC
   NEURONS; FOOD-INTAKE; OBESE GENE; HEALTHY; WEIGHT; ASSOCIATIONS;
   EXPRESSION
AB Leptin plays an important role in thermoregulation and is possibly associated with the microevolutionary processes of human adaptation to a cold climate. In this study, based on the Yakut population (n = 281 individuals) living in the coldest region of Siberia (t degrees minimum -71.2 degrees C), we analyze the serum leptin levels and data of 14 single nucleotide polymorphisms (SNPs) of 10 genes (UCP1, UCP2, UCP3, FNDC5, PPARGC1A, CIDEA, PTGS2, TRPV1, LEPR, BDNF) that are possibly involved in nonshivering thermogenesis processes. Our results demonstrate that from 14 studied SNPs of 10 genes, 2 SNPs (the TT rs3811787 genotype of the UCP1 gene and the GG rs6265 genotype of the BDNF gene) were associated with the elevated leptin levels in Yakut females (p < 0.05). Furthermore, of these two SNPs, the rs3811787 of the UCP1 gene demonstrated more indications of natural selection for cold climate adaptation. The prevalence gradient of the T-allele (rs3811787) of UCP1 increased from the south to the north across Eurasia, along the shore of the Arctic Ocean. Thereby, our study suggests the potential involvement of the UCP1 gene in the leptin-mediated thermoregulation mechanism, while the distribution of its allelic variants is probably related to human adaptation to a cold climate.
C1 [Nikanorova, Alena A.; Barashkov, Nikolay A.; Pshennikova, Vera G.; Gotovtsev, Nyurgun N.; Romanov, Georgii P.; Solovyev, Aisen V.] Yakut Sci Ctr Complex Med Problems, Lab Mol Genet, Yakutsk 677010, Sakha Republic, Russia.
   [Nakhodkin, Sergey S.; Romanov, Georgii P.; Solovyev, Aisen V.; Kuzmina, Sargylana S.; Sazonov, Nikolay N.; Fedorova, Sardana A.] MK Ammosov North Eastern Fed Univ, Lab Mol Biol, Yakutsk 677000, Sakha Republic, Russia.
C3 Yakut Science Centre of Complex Medical Problems; North-Eastern Federal
   University in Yakutsk
RP Barashkov, NA (corresponding author), Yakut Sci Ctr Complex Med Problems, Lab Mol Genet, Yakutsk 677010, Sakha Republic, Russia.
EM nikanorova.alena@mail.ru; barashkov2004@mail.ru; psennikovavera@mail.ru;
   sergnahod@mail.ru; donzcrew@mail.ru; gpromanov@gmail.com;
   nelloann@mail.ru; sskuzmina@bk.ru; saznikol@mail.ru;
   sardaanafedorova@mail.ru
RI Kuzmina, Sargylana/AAO-6271-2020; Fedorova, Sardana/K-5445-2017;
   Barashkov, Nikolay/F-1499-2017; Solovyev, Aisen/F-4012-2017; Nikanorova,
   Alena/L-1260-2017; Romanov, Georgii/E-6367-2017; Pshennikova,
   Vera/F-4031-2017; Nakhodkin, Sergey/K-8786-2017
OI Nikanorova, Alena/0000-0002-7129-6633; Barashkov, Nikolay
   A/0000-0002-6984-7934; Romanov, Georgii/0000-0002-2936-5818;
   Pshennikova, Vera/0000-0001-6866-9462; Nakhodkin,
   Sergey/0000-0002-6917-5760
FU Yakut Science Centre of Complex Medical Problems project: "Study of the
   genetic structure and burden of hereditary pathology of populations of
   the Republic of Sakha (Yakutia)''; Ministry of Science and Higher
   Education of the Russian Federation [FSRG-2020-0016]; Russian Foundation
   for Basic Research [18-05-600035_Arctika]
FX This study was supported by the Yakut Science Centre of Complex Medical
   Problems project: "Study of the genetic structure and burden of
   hereditary pathology of populations of the Republic of Sakha (Yakutia)",
   the Ministry of Science and Higher Education of the Russian Federation
   (FSRG-2020-0016), and the Russian Foundation for Basic Research
   (#18-05-600035_Arctika).
CR Ahima RS, 1999, ENDOCRINOLOGY, V140, P2755, DOI 10.1210/en.140.6.2755
   Anastasilakis AD, 2014, J CLIN ENDOCR METAB, V99, P3247, DOI 10.1210/jc.2014-1367
   Andersson J, 2012, INT J OBESITY, V36, P783, DOI 10.1038/ijo.2011.152
   Auton A., 2015, Nature, V526, P68, DOI DOI 10.1038/NATURE15393
   Baicy K, 2007, P NATL ACAD SCI USA, V104, P18276, DOI 10.1073/pnas.0706481104
   Bianco AC, 2013, LANCET DIABETES ENDO, V1, P250, DOI 10.1016/S2213-8587(13)70069-X
   Bjerregaard P, 2003, SCAND J PUBLIC HEALT, V31, P92, DOI 10.1080/14034940210133924
   Bribiescas RG, 2001, AM J PHYS ANTHROPOL, V115, P297, DOI 10.1002/ajpa.1085
   CAMPFIELD LA, 1995, SCIENCE, V269, P546, DOI 10.1126/science.7624778
   Cannon B, 2004, PHYSIOL REV, V84, P277, DOI 10.1152/physrev.00015.2003
   Chan JL, 2003, J CLIN INVEST, V111, P1409, DOI 10.1172/JCI200317490
   Commins SP, 2000, J BIOL CHEM, V275, P33059, DOI 10.1074/jbc.M006328200
   Considine RV, 1996, NEW ENGL J MED, V334, P292, DOI 10.1056/NEJM199602013340503
   Couillard C, 1997, DIABETOLOGIA, V40, P1178, DOI 10.1007/s001250050804
   Cowley MA, 2001, NATURE, V411, P480, DOI 10.1038/35078085
   Cox MM., 2000, LEHNINGER PRINCIPLES, V5
   DAVIS TRA, 1954, AM J PHYSIOL, V177, P222
   Guzman DD, 2014, DIS MARKERS, V2014, DOI 10.1155/2014/974503
   Efremova A, 2020, J PHYSIOL BIOCHEM, V76, P185, DOI 10.1007/s13105-019-00721-4
   Elias CF, 1999, NEURON, V23, P775, DOI 10.1016/S0896-6273(01)80035-0
   Elmquist JK, 1999, NEURON, V22, P221, DOI 10.1016/S0896-6273(00)81084-3
   Esteghamati A, 2010, METABOLISM, V59, P1730, DOI 10.1016/j.metabol.2010.04.016
   Farooqi IS, 2001, NATURE, V414, P34, DOI 10.1038/35102112
   Fischer AW, 2020, ENDOCR REV, V41, P232, DOI 10.1210/endrev/bnz016
   Fox CS, 1998, AM J CLIN NUTR, V68, P1053, DOI 10.1093/ajcn/68.5.1053
   Garfield AS, 2012, ENDOCRINOLOGY, V153, P4600, DOI 10.1210/en.2012-1282
   Garlid KD, 1996, J BIOL CHEM, V271, P2615, DOI 10.1074/jbc.271.5.2615
   GREEN ED, 1995, GENOME RES, V5, P5, DOI 10.1101/gr.5.1.5
   HALAAS JL, 1995, SCIENCE, V269, P543, DOI 10.1126/science.7624777
   Hancock AM, 2011, MOL BIOL EVOL, V28, P601, DOI 10.1093/molbev/msq228
   Harris RBS, 1998, ENDOCRINOLOGY, V139, P8, DOI 10.1210/en.139.1.8
   International Obesity Task Force, 1997, OB MAN GLOB EP REP W
   Irving BA, 2014, CURR OBES REP, V3, P235, DOI 10.1007/s13679-014-0091-1
   JOOSTEN HFP, 1974, METABOLISM, V23, P425, DOI 10.1016/0026-0495(74)90090-0
   Kaiyala KJ, 2016, MOL METAB, V5, P892, DOI 10.1016/j.molmet.2016.07.005
   Kaiyala KJ., 2009, ENCY NEUROSCIENCE, P1043, DOI [10.1016/b978-008045046-9.00447-2, 10.1016/B978-008045046-9.00447-2, DOI 10.1016/B978-008045046-9.00447-2]
   Kajimura S, 2014, ANNU REV PHYSIOL, V76, P225, DOI 10.1146/annurev-physiol-021113-170252
   Kindblom JM, 2009, J BONE MINER RES, V24, P785, DOI [10.1359/jbmr.081234, 10.1359/JBMR.081234]
   Koca TT, 2020, ACTA NEUROL BELG, V120, P595, DOI 10.1007/s13760-018-01063-6
   Koksharova EO, 2014, DIABETES MELLIT, V17, P5, DOI 10.14341/DM201445-15
   Leonard WR, 2014, AM J HUM BIOL, V26, P437, DOI 10.1002/ajhb.22524
   Leonard WR, 2005, ANNU REV ANTHROPOL, V34, P451, DOI 10.1146/annurev.anthro.34.081804.120558
   Lichtenbelt WDV, 2009, NEW ENGL J MED, V360, P1500, DOI 10.1056/NEJMoa0808718
   Luginbuehl I., 2010, THERMOREGULATION PHY, P157
   MacIver NJ, 2016, CLIN ENDOCRINOL, V85, P116, DOI 10.1111/cen.12963
   Mackintosh RM, 2001, OBES RES, V9, P462, DOI 10.1038/oby.2001.60
   Madsen L, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0011391
   Morrison SF, 2014, CELL METAB, V19, P741, DOI 10.1016/j.cmet.2014.02.007
   Nikanorova AA, 2020, INT J ENV RES PUB HE, V17, DOI 10.3390/ijerph17061854
   PELLEYMOUNTER MA, 1995, SCIENCE, V269, P540, DOI 10.1126/science.7624776
   Perez-Bravo F, 1998, INT J OBESITY, V22, P943, DOI 10.1038/sj.ijo.0800667
   Rasmussen-Torvik LJ, 2012, ANN EPIDEMIOL, V22, P705, DOI 10.1016/j.annepidem.2012.07.011
   Reynés B, 2015, AM J PHYSIOL-REG I, V309, pR824, DOI 10.1152/ajpregu.00221.2015
   Rezai-Zadeh K, 2013, PHYSIOL BEHAV, V121, P49, DOI 10.1016/j.physbeh.2013.02.014
   Romanova AN, 2019, YAKUT MED J, P6, DOI 10.25789/YMJ.2019.67.01
   Saito M, 2009, DIABETES, V58, P1526, DOI 10.2337/db09-0530
   Sazzini M, 2014, HEREDITY, V113, P259, DOI 10.1038/hdy.2014.24
   Shephard RJ, 1996, J SPORT MED PHYS FIT, V36, P186
   Snodgrass JJ, 2008, AM J PHYS ANTHROPOL, V137, P145, DOI 10.1002/ajpa.20851
   Sonoda S., 1991, HLA, V1, P685
   Suyila Q, 2013, OBES RES CLIN PRACT, V7, pE75, DOI 10.1016/j.orcp.2011.09.002
   Tomskiy MI, 2015, YAKUT MED J, P102
   TRAYHURN P, 1976, P NUTR SOC, V35, pA133
   VALENZUELA CY, 1987, REV MED CHILE, V115, P295
   Wang CF, 2010, BRAIN RES, V1336, P66, DOI 10.1016/j.brainres.2010.04.013
   Wang PTQ, 2020, NATURE, V583, P839, DOI 10.1038/s41586-020-2527-y
   Wauters M, 1998, Eat Weight Disord, V3, P124
   Zhang FM, 1997, NATURE, V387, P206, DOI 10.1038/387206a0
   Zhang YY, 2018, COMPR PHYSIOL, V8, P351, DOI 10.1002/cphy.c160041
   ZHANG YY, 1994, NATURE, V372, P425, DOI 10.1038/372425a0
NR 70
TC 7
Z9 7
U1 0
U2 4
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 1422-0067
J9 INT J MOL SCI
JI Int. J. Mol. Sci.
PD MAY
PY 2021
VL 22
IS 9
AR 4657
DI 10.3390/ijms22094657
PG 12
WC Biochemistry & Molecular Biology; Chemistry, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Chemistry
GA SC0SR
UT WOS:000650393100001
PM 33925025
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU van Jaarsveld, B
   Bennett, NC
   Kemp, R
   Czenze, ZJ
   McKechnie, AE
AF van Jaarsveld, Barry
   Bennett, Nigel C.
   Kemp, Ryno
   Czenze, Zenon J.
   McKechnie, Andrew E.
TI Heat tolerance in desert rodents is correlated with microclimate at
   inter- and intraspecific levels
SO JOURNAL OF COMPARATIVE PHYSIOLOGY B-BIOCHEMICAL SYSTEMS AND
   ENVIRONMENTAL PHYSIOLOGY
LA English
DT Article
DE Thermoregulation; Microclimate; Refugia; Variation
ID EVAPORATIVE COOLING CAPACITY; BASAL METABOLIC-RATE; AVIAN
   THERMOREGULATION; EVOLUTIONARY VARIATION; AETHOMYS-NAMAQUENSIS;
   THALLOMYS-PAEDULCUS; CLIMATIC ADAPTATION; THERMAL TOLERANCE;
   BODY-TEMPERATURE; DWELLING RODENT
AB Physiological diversity in thermoregulatory traits has been extensively investigated in both endo- and ectothermic vertebrates, with many studies revealing that thermal physiology has evolved in response to selection arising from climate. The majority of studies have investigated how adaptative variation in thermal physiology is correlated with broad-scale climate, but the role of fine-scale microclimate remains less clear. We hypothesised that the heat tolerance limits and evaporative cooling capacity of desert rodents are correlated with microclimates within species-specific diurnal refugia. We tested predictions arising from this hypothesis by comparing thermoregulation in the heat among arboreal black-tailed tree rats (Thallomys nigricauda), Namaqua rock rats (Micaelamys namaquensis) and hairy-footed gerbils (Gerbillurus paeba). Species and populations that occupy hotter diurnal microsites tolerated air temperatures (T-a) similar to 2-4 degrees C higher compared to those species occupying cooler, more thermally buffered microsites. Inter- and intraspecific variation in heat tolerance was attributable to similar to 30% greater evaporative water loss and similar to 44 % lower resting metabolic rates at high T-a, respectively. Our results suggest that microclimates within rodent diurnal refugia are an important correlate of intra- and interspecific physiological variation and reiterate the need to incorporate fine-scale microclimatic conditions when investigating adaptative variation in thermal physiology.
C1 [van Jaarsveld, Barry; Kemp, Ryno; Czenze, Zenon J.; McKechnie, Andrew E.] South African Natl Biodivers Inst, South African Res Chair Conservat Physiol, Pretoria, South Africa.
   [van Jaarsveld, Barry; Kemp, Ryno; Czenze, Zenon J.; McKechnie, Andrew E.] Univ Pretoria, DSI NRF Ctr Excellence, FitzPatrick Inst, Dept Zool & Entomol, Pretoria, South Africa.
   [Bennett, Nigel C.] Univ Pretoria, Mammal Res Inst, Dept Zool & Entomol, Pretoria, South Africa.
   [Czenze, Zenon J.] Univ New England, Ctr Behav & Physiol Ecol, Zool, Armidale, NSW, Australia.
C3 South African National Biodiversity Institute; University of Pretoria;
   University of Pretoria; University of New England
RP van Jaarsveld, B (corresponding author), South African Natl Biodivers Inst, South African Res Chair Conservat Physiol, Pretoria, South Africa.; van Jaarsveld, B (corresponding author), Univ Pretoria, DSI NRF Ctr Excellence, FitzPatrick Inst, Dept Zool & Entomol, Pretoria, South Africa.
EM u04464011@tuks.co.za
RI ; Bennett, Nigel/E-4238-2010; McKechnie, Andrew/E-4398-2010
OI Czenze, Zenon/0000-0002-1113-7593; Kemp, Ryno/0000-0002-5339-8783;
   Bennett, Nigel/0000-0001-9748-2947; McKechnie,
   Andrew/0000-0002-1524-1021; van Jaarsveld, Barry/0000-0001-5154-5922
FU SARChI chair of Mammal Behavioural Ecology and Physiology [64756];
   SARChI chair of Conservation Physiology [119754]
FX This project was jointly funded by the SARChI chair of Mammal
   Behavioural Ecology and Physiology (Grant number 64756) and the SARChI
   chair of Conservation Physiology (grant 119754) awarded to NCB and AEM,
   respectively. Any opinions, findings and conclusions or recommendations
   expressed in this material are those of the authors and do not
   necessarily reflect the views of the National Research Foundation.
CR Addo-Bediako A, 2000, P ROY SOC B-BIOL SCI, V267, P739, DOI 10.1098/rspb.2000.1065
   Addo-Bediako A, 2001, J INSECT PHYSIOL, V47, P1377, DOI 10.1016/S0022-1910(01)00128-7
   Angilletta MJ, 2002, J THERM BIOL, V27, P199, DOI 10.1016/S0306-4565(01)00084-5
   [Anonymous], R PACKAGE VERSION
   Araújo MB, 2013, ECOL LETT, V16, P1206, DOI 10.1111/ele.12155
   Arends A, 2001, COMP BIOCHEM PHYS A, V130, P105, DOI 10.1016/S1095-6433(01)00371-3
   Bates D, 2015, J STAT SOFTW, V67, P1, DOI 10.18637/jss.v067.i01
   BELL GP, 1986, J COMP PHYSIOL B, V156, P441, DOI 10.1007/BF01101107
   Boyles JG, 2012, J EXP ZOOL PART A, V317A, P73, DOI 10.1002/jez.723
   BOZINOVIC F, 1989, FUNCT ECOL, V3, P173, DOI 10.2307/2389298
   Bozinovic F, 2014, EVOL ECOL RES, V16, P143
   Bozinovic F, 2011, ANNU REV ECOL EVOL S, V42, P155, DOI 10.1146/annurev-ecolsys-102710-145055
   Bozinovic F, 2009, COMP BIOCHEM PHYS A, V152, P560, DOI 10.1016/j.cbpa.2008.12.015
   BROWER JE, 1966, ECOLOGY, V47, P46, DOI 10.2307/1935743
   CHAPPELL MA, 1981, PHYSIOL ZOOL, V54, P81, DOI 10.1086/physzool.54.1.30155807
   Clarke A, 2014, GLOBAL ECOL BIOGEOGR, V23, P1000, DOI 10.1111/geb.12185
   Coleman JC, 2010, PHYSIOL BEHAV, V99, P22, DOI 10.1016/j.physbeh.2009.10.006
   Conradie SR, 2019, P NATL ACAD SCI USA, V116, P14065, DOI 10.1073/pnas.1821312116
   Czenze ZJ, 2020, J THERM BIOL, V89, DOI 10.1016/j.jtherbio.2020.102542
   Czenze ZJ, 2020, FUNCT ECOL, V34, P1589, DOI 10.1111/1365-2435.13573
   DAWSON WILLIAM R., 1955, JOUR MAMMAL, V36, P543, DOI 10.2307/1375808
   Degen A.A., 1997, Ecophysiology of Small Desert Mammals
   DOWNS CT, 1990, J THERM BIOL, V15, P291, DOI 10.1016/0306-4565(90)90015-A
   Duffy GA, 2015, CURR OPIN INSECT SCI, V11, P84, DOI 10.1016/j.cois.2015.09.013
   ERSKINE DJ, 1982, J MAMMAL, V63, P267, DOI 10.2307/1380636
   Fick SE, 2017, INT J CLIMATOL, V37, P4302, DOI 10.1002/joc.5086
   Forsman A, 2015, HEREDITY, V115, P276, DOI 10.1038/hdy.2014.92
   Freckleton RP, 2009, J EVOLUTION BIOL, V22, P1367, DOI 10.1111/j.1420-9101.2009.01757.x
   French, 1993, BIOL HETEROMYIDAE
   GARLAND T, 1994, PHYSIOL ZOOL, V67, P797, DOI 10.1086/physzool.67.4.30163866
   Gerson AR, 2014, PHYSIOL BIOCHEM ZOOL, V87, P782, DOI 10.1086/678956
   HAIM A, 1987, J THERM BIOL, V12, P45, DOI 10.1016/0306-4565(87)90022-2
   HAIM A, 1993, J COMP PHYSIOL B, V163, P602, DOI 10.1007/BF00302120
   Jackson TP, 2002, J ARID ENVIRON, V51, P21, DOI 10.1006/jare.2001.0912
   Kearney MR, 2020, METHODS ECOL EVOL, V11, P38, DOI 10.1111/2041-210X.13330
   Keller I, 2012, MOL ECOL, V21, P782, DOI 10.1111/j.1365-294X.2011.05397.x
   Kemp R, 2020, EMU, V120, P216, DOI 10.1080/01584197.2020.1806082
   Kemp R, 2019, J COMP PHYSIOL B, V189, P131, DOI 10.1007/s00360-018-1190-1
   LASIEWSKI RC, 1966, COMP BIOCHEM PHYSIOL, V19, P445, DOI 10.1016/0010-406X(66)90153-8
   Lighton JRB, 2019, MEASURING METABOLIC RATES: A MANUAL FOR SCIENTISTS, 2ND EDITION, P1
   Lovegrove BG, 2014, PHYSIOL BIOCHEM ZOOL, V87, P30, DOI 10.1086/673313
   LOVEGROVE BG, 1994, AUST J ZOOL, V42, P65, DOI 10.1071/ZO9940065
   Lovegrove BG, 2003, J COMP PHYSIOL B, V173, P87, DOI 10.1007/s00360-002-0309-5
   LOVEGROVE BG, 1986, OECOLOGIA, V69, P551, DOI 10.1007/BF00410361
   LOVEGROVE BG, 1991, J THERM BIOL, V16, P199, DOI 10.1016/0306-4565(91)90026-X
   Luna F, 2017, COMP BIOCHEM PHYS A, V206, P87, DOI 10.1016/j.cbpa.2017.02.002
   Mathewson PD, 2017, GLOBAL CHANGE BIOL, V23, P1048, DOI 10.1111/gcb.13454
   McKechnie AE, 2016, J EXP BIOL, V219, P2137, DOI 10.1242/jeb.139733
   MCNAB BK, 1970, J EXP BIOL, V53, P329
   MCNAB BK, 1963, ECOL MONOGR, V33, P63, DOI 10.2307/1948477
   MCNAB BK, 1979, COMP BIOCHEM PHYS A, V62, P813, DOI 10.1016/0300-9629(79)90008-2
   Merilä J, 2014, EVOL APPL, V7, P1, DOI 10.1111/eva.12137
   Muggeo VMR, 2014, STAT MODEL, V14, P293, DOI 10.1177/1471082X13504721
   Naya DE, 2013, P ROY SOC B-BIOL SCI, V280, DOI 10.1098/rspb.2013.1629
   Naya DE, 2013, EVOLUTION, V67, P1463, DOI 10.1111/evo.12042
   Noakes MJ, 2019, COMP BIOCHEM PHYS A, V236, DOI 10.1016/j.cbpa.2019.06.022
   Noakes MJ, 2016, J EXP BIOL, V219, P859, DOI 10.1242/jeb.132001
   Novoa FF, 2005, REV CHIL HIST NAT, V78, P207
   O'Connor RS, 2017, J COMP PHYSIOL B, V187, P477, DOI 10.1007/s00360-016-1047-4
   Pettersen AK, 2018, J EXP BIOL, V221, DOI 10.1242/jeb.166876
   Piersma T, 2003, TRENDS ECOL EVOL, V18, P228, DOI 10.1016/S0169-5347(03)00036-3
   Potter KA, 2013, GLOBAL CHANGE BIOL, V19, P2932, DOI [10.1111/gcb.12257, 10.1111/]
   R Core Team, 2019, R LANG ENV STAT COMP
   Reher S, 2018, J COMP PHYSIOL B, V188, P1015, DOI 10.1007/s00360-018-1171-4
   Rezende EL, 2004, EVOLUTION, V58, P1361
   Riddell EA, 2019, P NATL ACAD SCI USA, V116, P21609, DOI 10.1073/pnas.1908791116
   Ruf T, 2015, BIOL REV, V90, P891, DOI 10.1111/brv.12137
   Rutherford M., 2006, Biomes and Bioregions of Southern Africa The vegetation of South Africa, Lesotho and Swaziland
   SCHMIDTNIELSEN B, 1950, ECOLOGY, V31, P75, DOI 10.2307/1931362
   SCHMIDTNIELSEN K, 1952, PHYSIOL REV, V32, P135, DOI 10.1152/physrev.1952.32.2.135
   Sears MW, 2016, P NATL ACAD SCI USA, V113, P10595, DOI 10.1073/pnas.1604824113
   Smit B, 2013, ECOLOGY, V94, P1142, DOI 10.1890/12-1511.1
   Suggitt AJ, 2011, OIKOS, V120, P1, DOI 10.1111/j.1600-0706.2010.18270.x
   Sunday JM, 2011, P ROY SOC B-BIOL SCI, V278, P1823, DOI 10.1098/rspb.2010.1295
   Swanson DL, 2009, EVOLUTION, V63, P184, DOI 10.1111/j.1558-5646.2008.00522.x
   Talbot WA, 2017, J EXP BIOL, V220, P3488, DOI 10.1242/jeb.161653
   Tieleman BI, 1999, PHYSIOL BIOCHEM ZOOL, V72, P87, DOI 10.1086/316640
   Toussaint DC, 2012, J COMP PHYSIOL B, V182, P1129, DOI 10.1007/s00360-012-0683-6
   Tracy CR., 2010, Properties of Air: a manual for use in biophysical ecology, V4th
   Tracy RL, 2000, J EXP BIOL, V203, P773
   Tracy RL, 2002, OECOLOGIA, V133, P449, DOI 10.1007/s00442-002-1059-5
   van Dyk M, 2019, J COMP PHYSIOL B, V189, P299, DOI 10.1007/s00360-019-01210-2
   WALSBERG GE, 1995, J EXP BIOL, V198, P213
   WEATHERS WW, 1981, PHYSIOL ZOOL, V54, P345, DOI 10.1086/physzool.54.3.30159949
   WEISSENBERG S, 1994, ISRAEL J ZOOL, V40, P135
   Welman S, 2018, CLIM RES, V74, P161, DOI 10.3354/cr01496
   White CR, 2003, PHYSIOL BIOCHEM ZOOL, V76, P122, DOI 10.1086/367940
   White CR, 2007, P ROY SOC B-BIOL SCI, V274, P287, DOI 10.1098/rspb.2006.3727
   Whitfield MC, 2015, J EXP BIOL, V218, P1705, DOI 10.1242/jeb.121749
   Withers PC, 2006, PHYSIOL BIOCHEM ZOOL, V79, P437, DOI 10.1086/501063
   Wolf BO, 2017, P ROY SOC B-BIOL SCI, V284, DOI 10.1098/rspb.2016.2523
NR 91
TC 19
Z9 20
U1 2
U2 13
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 0174-1578
EI 1432-136X
J9 J COMP PHYSIOL B
JI J. Comp. Physiol. B-Biochem. Syst. Environ. Physiol.
PD MAY
PY 2021
VL 191
IS 3
BP 575
EP 588
DI 10.1007/s00360-021-01352-2
EA FEB 2021
PG 14
WC Physiology; Zoology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Physiology; Zoology
GA RM8BM
UT WOS:000622652500001
PM 33638667
DA 2025-01-10
ER

PT J
AU Steiner, JL
   Briske, DD
   Brown, DP
   Rottler, CM
AF Steiner, Jean L.
   Briske, David D.
   Brown, David P.
   Rottler, Caitlin M.
TI Vulnerability of Southern Plains agriculture to climate change
SO CLIMATIC CHANGE
LA English
DT Article
ID DYNAMIC-RESPONSE INDICATORS; RANKING REGIME ANALYSIS; SHADED FEEDLOT
   CATTLE; HEAT-STRESS; PART; ADAPTATION; STRATEGIES; IMPACTS; YIELD; SOILS
AB Projections of greater interannual and intrannual climate variability, including increasing temperatures, longer and more intense drought periods, and more extreme precipitation events, present growing challenges for agricultural production in the Southern Plains of the USA. We assess agricultural vulnerabilities within this region to support identification and development of adaptation strategies at regional to local scales, where many management decisions are made. Exposure to the synergistic effects of warming, such as fewer and more intense precipitation events and greater overall weather variability, will uniquely affect rain-fed and irrigated cropping, high-value specialty crops, extensive and intensive livestock production, and forestry. Although the sensitivities of various agricultural sectors to climatic stressors can be difficult to identify at regional scales, we summarize that crops irrigated from the Ogallala aquifer possess a high sensitivity; rangeland beef cattle production a low sensitivity; and rain-fed crops, forestry, and specialty crops intermediate sensitivities. Numerous adaptation strategies have been identified, including drought contingency planning, increased soil health, improved forecasts and associated decision support tools, and implementation of policies and financial instruments for risk management. However, the extent to which these strategies are adopted is variable and influenced by both biophysical and socioeconomic considerations. Inadequate local- and regional-scale climate risk and resilience information suggests that climate vulnerability research and climate adaptation approaches need to include bottom-up approaches such as learning networks and peer-to-peer communication.
C1 [Steiner, Jean L.; Brown, David P.; Rottler, Caitlin M.] ARS, USDA, Grazinglands Res Lab, 7207 W Cheyenne St, El Reno, OK 73036 USA.
   [Briske, David D.] Texas A&M Univ, Dept Ecosyst Sci & Management, Centeq Bldg,Room 130C,MS 2120 TAMU, College Stn, TX 77843 USA.
C3 United States Department of Agriculture (USDA); Texas A&M University
   System; Texas A&M University College Station
RP Steiner, JL (corresponding author), ARS, USDA, Grazinglands Res Lab, 7207 W Cheyenne St, El Reno, OK 73036 USA.
EM jean.steiner@ars.usda.gov
CR Acosta-Martínez V, 2014, APPL SOIL ECOL, V84, P69, DOI 10.1016/j.apsoil.2014.06.005
   Adger WN, 2006, GLOBAL ENVIRON CHANG, V16, P268, DOI 10.1016/j.gloenvcha.2006.02.006
   Ahuja LR, 2007, J CROP IMPROV, V19, P73, DOI 10.1300/J411v19n01_04
   Anandhi A, 2016, CLIMATIC CHANGE, V136, P647, DOI 10.1007/s10584-016-1636-y
   [Anonymous], CLIMATE CHANGE AGR E
   [Anonymous], 2014, 2012 Census of Agriculture
   [Anonymous], NOAA TECHNICAL REPOR
   [Anonymous], 2011, WATER LEVEL CHANGES
   [Anonymous], 2008, PREL REV AD OPT CLIM
   [Anonymous], USDA ERS EC RES REP
   [Anonymous], EIB116 USDAERS
   [Anonymous], P OG AQ STEPS SUST
   [Anonymous], NAT GAP AN PROGR GAP
   [Anonymous], DROUGHT SO FORESTS I
   [Anonymous], GENETICS
   [Anonymous], STATEIMPACT OKLAHOMA
   [Anonymous], 2014, 3 NATL CLIM ASSESS
   [Anonymous], AGR APPL EC ASS AAE
   [Anonymous], EC RES SERV
   Ayres MP, 2000, SCI TOTAL ENVIRON, V262, P263, DOI 10.1016/S0048-9697(00)00528-3
   Backoulou G., 2014, Crop Manag, V13, P1, DOI [10.2134/CM-2014-0020-MG, DOI 10.2134/CM-2014-0020-MG]
   Baker JT, 2013, PLANT BIOSYST, V147, P40, DOI 10.1080/11263504.2012.736423
   Baumhardt RL, 2016, AGRON J, V108, P736, DOI 10.2134/agronj2015.0403
   Briske DD, 2015, FRONT ECOL ENVIRON, V13, P249, DOI 10.1890/140266
   Brown JR, 2016, J SOIL WATER CONSERV, V71, p55A, DOI 10.2489/jswc.71.3.55A
   Brown-Brandl TM, 2005, BIOSYST ENG, V90, P451, DOI 10.1016/j.biosystemseng.2004.12.006
   Burke JJ, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0122933
   Conaty WC, 2012, CROP SCI, V52, P1828, DOI 10.2135/cropsci2011.11.0581
   Eigenberg RA, 2005, BIOSYST ENG, V91, P111, DOI 10.1016/j.biosystemseng.2005.02.001
   Emendack Y., 2014, American Journal of Experimental Agriculture, V4, P1500, DOI 10.9734/AJEA/2014/11682
   Engle NL, 2011, GLOBAL ENVIRON CHANG, V21, P647, DOI 10.1016/j.gloenvcha.2011.01.019
   Fazey I, 2010, FRONT ECOL ENVIRON, V8, P414, DOI 10.1890/080215
   Franzen D, 2016, AGRON J, V108, P1775, DOI 10.2134/agronj2016.01.0041
   Hahn GL, 1999, J ANIM SCI, V77, P10
   Hatfield JL, 2011, AGRON J, V103, P351, DOI 10.2134/agronj2010.0303
   Hoerling M, 2013, J CLIMATE, V26, P2811, DOI 10.1175/JCLI-D-12-00270.1
   Hoffmann I, 2010, ANIM GENET, V41, P32, DOI 10.1111/j.1365-2052.2010.02043.x
   Howden SM, 2007, P NATL ACAD SCI USA, V104, P19691, DOI 10.1073/pnas.0701890104
   Izaurralde RC, 2011, AGRON J, V103, P371, DOI 10.2134/agronj2010.0304
   Jin VL, 2013, SOIL BIOL BIOCHEM, V58, P172, DOI 10.1016/j.soilbio.2012.11.024
   Joyce LA, 2013, RANGELAND ECOL MANAG, V66, P512, DOI 10.2111/REM-D-12-00142.1
   Kay RNB, 1997, J ARID ENVIRON, V37, P683, DOI 10.1006/jare.1997.0299
   Kunkel KE, 2013, B AM METEOROL SOC, V94, P499, DOI 10.1175/BAMS-D-11-00262.1
   Kunreuther H, 2014, CLIMATE CHANGE 2014: MITIGATION OF CLIMATE CHANGE, P151
   Lal R, 2016, J SOIL WATER CONSERV, V71, p85A, DOI 10.2489/jswc.71.4.85A
   Lehman RM, 2015, SUSTAINABILITY-BASEL, V7, P988, DOI 10.3390/su7010988
   Liu B, 2016, NAT CLIM CHANGE, V6, P1130, DOI 10.1038/NCLIMATE3115
   Marshall NA, 2010, GLOBAL ENVIRON CHANG, V20, P36, DOI 10.1016/j.gloenvcha.2009.10.003
   Mauget SA, 2014, J CLIMATE, V27, P9006, DOI 10.1175/JCLI-D-14-00040.1
   Mauget SA, 2014, J CLIMATE, V27, P9027, DOI 10.1175/JCLI-D-14-00041.1
   Mbuthia LW, 2015, SOIL BIOL BIOCHEM, V89, P24, DOI 10.1016/j.soilbio.2015.06.016
   McNulty Steven G., 1998, Ecological Studies, V128, P617
   Moore GW, 2016, ECOL APPL, V26, P602, DOI 10.1890/15-0330
   Mora C, 2013, PLOS BIOL, V11, DOI 10.1371/journal.pbio.1001682
   Nansen C, 2016, ANNU REV ENTOMOL, V61, P139, DOI 10.1146/annurev-ento-010715-023834
   Nelson R, 2010, ENVIRON SCI POLICY, V13, P18, DOI 10.1016/j.envsci.2009.09.007
   Nielsen DC, 2016, AGRON J, V108, P243, DOI 10.2134/agronj2015.0372
   Noble IR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P833
   O'Neill CJ, 2010, EVOL APPL, V3, P422, DOI 10.1111/j.1752-4571.2010.00151.x
   O'Reagain P, 2011, ANIM PROD SCI, V51, P210, DOI 10.1071/AN10106
   Ojima D., 2015, Great Plains Regional Technical Input Report
   Otkin JA, 2016, AGR FOREST METEOROL, V218, P230, DOI 10.1016/j.agrformet.2015.12.065
   Parsons CT, 2003, J RANGE MANAGE, V56, P334, DOI 10.2307/4004036
   Paustian K, 2016, NATURE, V532, P49, DOI 10.1038/nature17174
   Peck JC, 2007, AGRICULTURAL GROUNDWATER REVOLUTION: OPPORTUNITIES AND THREATS TO DEVELOPMENT, P296, DOI 10.1079/9781845931728.0296
   Pelling M, 2011, ADAPTATION TO CLIMATE CHANGE: FROM RESILIENCE TO TRANSFORMATION, P1
   Polley HW, 2013, RANGELAND ECOL MANAG, V66, P493, DOI 10.2111/REM-D-12-00068.1
   Porter JR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P485
   Silanikove N, 2000, LIVEST PROD SCI, V67, P1, DOI 10.1016/S0301-6226(00)00162-7
   Steiner J.L., 2015, SO PLAINS ASSESSMENT
   Stewart B. A., 1990, Dryland agriculture: strategies for sustainability., P151
   Sun G, 2008, AGR FOREST METEOROL, V148, P257, DOI 10.1016/j.agrformet.2007.08.010
   Thamo T, 2017, AGR SYST, V150, P99, DOI 10.1016/j.agsy.2016.10.013
   Torell LA, 2010, RANGELAND ECOL MANAG, V63, P415, DOI 10.2111/REM-D-09-00131.1
   Van de Water PK, 2001, GRANA, V40, P133, DOI 10.1080/00173130152625879
   Vitale P.P., 2014, J ASFMRA, P145
   Volder A, 2013, GLOBAL CHANGE BIOL, V19, P843, DOI 10.1111/gcb.12068
   Waldrip HM, 2015, SOIL SCI SOC AM J, V79, P1601, DOI 10.2136/sssaj2015.03.0090
   Weindl Isabelle, 2015, Environmental Research Letters, V10, DOI 10.1088/1748-9326/10/9/094021
   Wilcox BP, 2012, RANGELAND ECOL MANAG, V65, P313, DOI 10.2111/REM-D-11-00119.1
   Xue Q, 2014, CROP SCI, V54, P34, DOI 10.2135/cropsci2013.02.0108
   Zhang YQW, 2013, CLIMATIC CHANGE, V118, P183, DOI 10.1007/s10584-012-0642-y
NR 82
TC 84
Z9 101
U1 4
U2 51
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 2018
VL 146
IS 1-2
SI SI
BP 201
EP 218
DI 10.1007/s10584-017-1965-5
PG 18
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA FU2VH
UT WOS:000423707600017
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Paim, TD
   Borges, BO
   Lima, PDT
   Gomes, EF
   Dallago, BSL
   Fadel, R
   de Menezes, AM
   Louvandini, H
   Canozzi, MEA
   Barcellos, JOJ
   McManus, C
AF Paim, Tiago do Prado
   Borges, Barbara Oliveira
   Tavares Lima, Paulo de Mello
   Gomes, Edgard Franco
   Lima Dallago, Bruno Stefano
   Fadel, Rossala
   de Menezes, Adriana Morato
   Louvandini, Helder
   Andrighetto Canozzi, Maria Eugenia
   Jardim Barcellos, Julio Otavio
   McManus, Concepta
TI Thermographic evaluation of climatic conditions on lambs from different
   genetic groups
SO INTERNATIONAL JOURNAL OF BIOMETEOROLOGY
LA English
DT Article
DE Bioclimatology; Coat traits; Housing; Infrared; Thermal stress; Tropical
   conditions
ID HEAT-STRESS; SHEEP; FLEECE; COAT
AB In production systems the characterization of genetic resources in relation to their capacity to respond to environmental conditions is necessary. The objective of this study was to evaluate the use of infrared thermography for separation of animals from different genetic groups and determine which phenotypic traits are important for climatic adaptation. A total of 126 suckling lambs from four different genetic groups (Santa Ins - SI, Bergamasca - B, Bergamasca X Santa Ins - BS, and Ile de France X Santa Ins - IL) were used. The animals were divided into two groups, one housed and another in an outside paddock. Thermograph photographs were taken at four-hour intervals over three full days. Temperatures of the nose, skull, neck, fore and rear flanks and rump were measured, as well as coat depth, the density and length of hairs, reflectance and color. The daily temperature range during the experimental period was more than 20A degrees C, with animals experiencing heat (12 h to 15 h) and cold (24 h to 4 h) stress. The three main phenotypic traits that influenced genetic group separation were hair density, height of coat, and length of hairs. Thermograph temperatures were able to detect different responses of the genetic groups to the environment. Therefore, infrared thermography is a promising technique to evaluate the response of animals to the environment and to differentiate between genetic groups.
C1 [Paim, Tiago do Prado; Gomes, Edgard Franco; Louvandini, Helder] Univ Sao Paulo, CENA, BR-13416000 Piracicaba, SP, Brazil.
   [Borges, Barbara Oliveira] Univ Paulista Julio Mesquita, UNESP, Jaboticabal, Brazil.
   [Tavares Lima, Paulo de Mello; Lima Dallago, Bruno Stefano; Fadel, Rossala; de Menezes, Adriana Morato] Univ Brasilia, UnB, Fac Agron & Med Vet, Brasilia, DF, Brazil.
   [Andrighetto Canozzi, Maria Eugenia; Jardim Barcellos, Julio Otavio; McManus, Concepta] Univ Fed Rio Grande do Sul, Dept Anim Prod, Porto Alegre, RS, Brazil.
C3 Universidade de Sao Paulo; Universidade de Brasilia; Universidade
   Federal do Rio Grande do Sul
RP Paim, TD (corresponding author), Univ Sao Paulo, CENA, Ave Centenario 303,CP 96 CEP, BR-13416000 Piracicaba, SP, Brazil.
EM pradopaim@hotmail.com
RI Louvandini, Helder/C-9441-2012; Canozzi, Maria Eugênia/B-2166-2016;
   Pimentel, Concepta/I-4356-2012; Lima, Paulo de Mello
   Tavares/B-2331-2013; Paim, Tiago/C-9563-2012; Barcellos,
   Julio/A-9209-2013
OI Dallago, Bruno/0000-0003-4883-1076; Pimentel,
   Concepta/0000-0002-1106-8962; Lima, Paulo de Mello
   Tavares/0000-0002-6354-3139; Paim, Tiago/0000-0002-9486-7128;
   Andrighetto Canozzi, Maria Eugenia/0000-0001-9263-8113; Louvandini,
   Helder/0000-0001-7129-8463; Barcellos, Julio/0000-0001-9858-1728
FU CNPq; INCT-Pecuaria (CNPq-FAPEMIG); FAP-DF; FINATEC
FX To CNPq and INCT-Pecuaria (CNPq-FAPEMIG) for research scholarships, as
   well as FAP-DF and FINATEC for financial support.
CR ALEXANDER G, 1980, Proceedings of the Australian Society of Animal Production, V13, P329
   [Anonymous], 2010, Process synthesis for fuel ethanol production
   [Anonymous], FARM ANIMALS ENV
   [Anonymous], 2003, J ESTHET RESTOR DENT
   Baeta F.C., 1997, AMBIENCIA EDIFICACOE, VVolume 246
   BOND J, 1972, J ANIM SCI, V35, P820
   Burgos J. J., 1979, GANADERIA TROPICAL, P1
   Maia ASC, 2009, REV BRAS ZOOTECN, V38, P104, DOI 10.1590/S1516-35982009000100014
   Castanheira M, 2010, TROP ANIM HEALTH PRO, V42, P1821, DOI 10.1007/s11250-010-9643-x
   Chemineau P., 1993, WORLD ANIM REV, V77, P2
   da Nobrega JE, 2005, PESQUI VET BRASIL, V25, P171, DOI 10.1590/S0100-736X2005000300008
   Forrest RH, 2006, ANIM GENET, V37, P465, DOI 10.1111/j.1365-2052.2006.01508.x
   Foster LA, 2009, S AFR J ANIM SCI, V39, P224
   FRASER D, 1975, BRIT VET J, V131, P653, DOI 10.1016/S0007-1935(17)35136-9
   Gaughan JB, 2008, J ANIM SCI, V86, P226, DOI 10.2527/jas.2007-0305
   HOLMES CW, 1981, ANIM PROD, V32, P225, DOI 10.1017/S000335610002506X
   Holst G., 2000, COMMON SENSE APPROAC
   Lefcourt AM, 1996, J ANIM SCI, V74, P2633
   Marai IFM, 2007, SMALL RUMINANT RES, V71, P1, DOI 10.1016/j.smallrumres.2006.10.003
   Marai IFM, 2010, LIVEST SCI, V127, P89, DOI 10.1016/j.livsci.2009.08.001
   MCCUTCHEON S N, 1981, Proceedings of the New Zealand Society of Animal Production, V41, P209
   McManus C, 2009, TROP ANIM HEALTH PRO, V41, P95, DOI 10.1007/s11250-008-9162-1
   McManus C, 2011, TROP ANIM HEALTH PRO, V43, P121, DOI 10.1007/s11250-010-9663-6
   MONTY DE, 1991, SMALL RUMINANT RES, V4, P379, DOI 10.1016/0921-4488(91)90083-3
   Paiva SR, 2005, PESQUI AGROPECU BRAS, V40, P887, DOI 10.1590/S0100-204X2005000900008
   Radostits O M., 2002, Clinica Veterinaria, V9A edicao
   Silva RG., 2000, INTRO BIOCLIMATOLOGI, V1st edn
   Solomon S., 2007, PHYS SCI BASIS
   Titto EAL, 1998, P 1 S BRAS AMB PROD, P10
   Young B. A., 1981, Environmental aspects of housing for animal production. Proceedings of 31st Nottingham Easter School in Agricultural Science., P167
NR 30
TC 44
Z9 47
U1 0
U2 25
PU SPRINGER
PI NEW YORK
PA 233 SPRING ST, NEW YORK, NY 10013 USA
SN 0020-7128
EI 1432-1254
J9 INT J BIOMETEOROL
JI Int. J. Biometeorol.
PD JAN
PY 2013
VL 57
IS 1
BP 59
EP 66
DI 10.1007/s00484-012-0533-y
PG 8
WC Biophysics; Environmental Sciences; Meteorology & Atmospheric Sciences;
   Physiology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biophysics; Environmental Sciences & Ecology; Meteorology & Atmospheric
   Sciences; Physiology
GA 059RG
UT WOS:000312722200005
PM 22410825
DA 2025-01-10
ER

PT J
AU David, JR
   Gibert, P
   Moreteau, B
   Gilchrist, GW
   Huey, RB
AF David, JR
   Gibert, P
   Moreteau, B
   Gilchrist, GW
   Huey, RB
TI The fly that came in from the cold:: geographic variation of recovery
   time from low-temperature exposure in <i>Drosophila subobscura</i>
SO FUNCTIONAL ECOLOGY
LA English
DT Article
DE chill coma; climatic adaptation; cold tolerance; geographic variation;
   thermal physiology
ID TOLERANCE; MELANOGASTER; STRESS; POPULATIONS; VARIABILITY; ADAPTATION;
   RESISTANCE; LATITUDE; SERRATA; SIZE
AB 1. The time required for an ectotherm to recover from cold exposure is a useful, non-lethal index of cold tolerance. We explore how recovery times are affected by exposure to low temperatures, develop statistical methodologies, and study geographic variation in recovery time in four populations of Drosophila subobscura , a cold-tolerant species.
   2. We exposed flies to a low temperature (-7 degreesC to 1 degreesC) for 16 h, returned them to ambient temperature, and recorded the elapsed time ('recovery time') until they stood. Other flies were exposed to even colder temperatures (-11 degreesC to -7 degreesC), but for shorter times.
   3. Recovery times were inversely related to exposure temperature, but had a plateau between -6 degreesC and -4 degreesC.
   4. Populations had similar recovery times at 'warm' temperatures, but two subtropical populations had relatively long recovery times at colder temperatures.
   5. Inter-population differences were also evident in a regression analysis, and recovery times were inversely related to latitude (ordered-factor analysis). Populations differed slightly in the slopes of regressions but differed strongly in their intercepts.
   6. The physiological mechanisms underlying the non-linear responses are unknown, but the plateau region suggests that recovery time is governed by the interplay of two temperature-dependent processes. Two models are proposed for the interaction of these processes.
C1 Univ Washington, Dept Biol, Seattle, WA 98195 USA.
   CNRS, Lab Populat Genet & Evolut, CNRS, F-91198 Gif Sur Yvette, France.
   Univ Lyon, Lab Biometrie, F-69622 Villeurbanne, France.
   Coll William & Mary, Dept Biol, Williamsburg, VA 23187 USA.
C3 University of Washington; University of Washington Seattle; Universite
   Paris Saclay; Centre National de la Recherche Scientifique (CNRS);
   William & Mary
RP Huey, RB (corresponding author), Univ Washington, Dept Biol, Box 351800, Seattle, WA 98195 USA.
RI Huey, Raymond/F-1597-2010
OI Gibert, Patricia/0000-0002-9461-6820; Huey, Raymond/0000-0002-4962-8670
CR Addo-Bediako A, 2000, P ROY SOC B-BIOL SCI, V267, P739, DOI 10.1098/rspb.2000.1065
   [Anonymous], 1987, Temperature biology of animals
   Audibert A, 1996, TRENDS GENET, V12, P452, DOI 10.1016/0168-9525(96)99995-3
   BENJAMINI Y, 1995, J R STAT SOC B, V57, P289, DOI 10.1111/j.2517-6161.1995.tb02031.x
   COYNE JA, 1983, AM NAT, V122, P474, DOI 10.1086/284150
   Crawley M.J., 2002, STAT COMPUTING INTRO
   DAVID JEAN, 1965, BULL BIOL FRANCE BELG, V99, P369
   David RJ, 1998, J THERM BIOL, V23, P291, DOI 10.1016/S0306-4565(98)00020-5
   Gibert P, 2001, PHYSIOL BIOCHEM ZOOL, V74, P429, DOI 10.1086/320429
   Gibert P, 2001, EVOLUTION, V55, P1063, DOI 10.1554/0014-3820(2001)055[1063:CCTAMC]2.0.CO;2
   Hallas R, 2002, GENET RES, V79, P141, DOI 10.1017/S0016672301005523
   HAZEL J, 1995, ANNU REV PHYSIOL, V157, P19
   Hoffmann AA, 2003, J THERM BIOL, V28, P175, DOI 10.1016/S0306-4565(02)00057-8
   Hoffmann AA, 2002, ECOL LETT, V5, P614, DOI 10.1046/j.1461-0248.2002.00367.x
   Huey RB, 2000, SCIENCE, V287, P308, DOI 10.1126/science.287.5451.308
   Krimbas C., 1993, DROSOPHILA SUBOBSCUR
   Leather SR., 1993, ECOLOGY INSECT OVERW
   Lee RE, 1991, INSECTS LOW TEMPERAT
   Magiafoglou A, 2002, J EVOLUTION BIOL, V15, P763, DOI 10.1046/j.1420-9101.2002.00439.x
   Precht H., 1973, TEMPERATURE LIFE
   PREVOSTI A, 1955, COLD SPRING HARB SYM, V20, P294, DOI 10.1101/SQB.1955.020.01.028
   Rajaram S, 1999, GENETICS, V153, P1673
NR 22
TC 95
Z9 107
U1 0
U2 22
PU BLACKWELL PUBLISHING LTD
PI OXFORD
PA 9600 GARSINGTON RD, OXFORD OX4 2DG, OXON, ENGLAND
SN 0269-8463
J9 FUNCT ECOL
JI Funct. Ecol.
PD AUG
PY 2003
VL 17
IS 4
BP 425
EP 430
DI 10.1046/j.1365-2435.2003.00750.x
PG 6
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA 708NH
UT WOS:000184573900001
OA Bronze
DA 2025-01-10
ER

PT J
AU Cubry, P
   Pidon, H
   Ta, KN
   Tranchant-Dubreuil, C
   Thuillet, AC
   Holzinger, M
   Adam, H
   Kam, H
   Chrestin, H
   Ghesquière, A
   François, O
   Sabot, F
   Vigouroux, Y
   Albar, L
   Jouannic, S
AF Cubry, Philippe
   Pidon, Helene
   Ta, Kim Nhung
   Tranchant-Dubreuil, Christine
   Thuillet, Anne-Celine
   Holzinger, Maria
   Adam, Helene
   Kam, Honore
   Chrestin, Harold
   Ghesquiere, Alain
   Francois, Olivier
   Sabot, Francois
   Vigouroux, Yves
   Albar, Laurence
   Jouannic, Stefan
TI Genome Wide Association Study Pinpoints Key Agronomic QTLs in African
   Rice<i>Oryza glaberrima</i>
SO RICE
LA English
DT Article
DE African rice; Genome wide association study; Flowering time; Panicle
   architecture; RYMV; Climate variation
ID YELLOW-MOTTLE-VIRUS; ORYZA-GLABERRIMA; RESISTANCE GENE; FLOWERING TIME;
   DNAJ PROTEIN; RICE; ADAPTATION; PACKAGE; IMPUTATION; INTERACTS
AB Background African rice,Oryza glaberrima, is an invaluable resource for rice cultivation and for the improvement of biotic and abiotic resistance properties. Since its domestication in the inner Niger delta ca. 2500 years BP, African rice has colonized a variety of ecologically and climatically diverse regions. However, little is known about the genetic basis of quantitative traits and adaptive variation of agricultural interest for this species. Results Using a reference set of 163 fully re-sequenced accessions, we report the results of a Genome Wide Association Study carried out for African rice. We investigated a diverse panel of traits, including flowering date, panicle architecture and resistance toRice yellow mottle virus. For this, we devised a pipeline using complementary statistical association methods. First, using flowering time as a target trait, we found several association peaks, one of which co-localised with a well described gene in the Asian rice flowering pathway,OsGi, and identified new genomic regions that would deserve more study. Then we applied our pipeline to panicle- and resistance-related traits, highlighting some interesting genomic regions and candidate genes. Lastly, using a high-resolution climate database, we performed an association analysis based on climatic variables, searching for genomic regions that might be involved in adaptation to climatic variations. Conclusion Our results collectively provide insights into the extent to which adaptive variation is governed by sequence diversity within theO. glaberrimagenome, paving the way for in-depth studies of the genetic basis of traits of interest that might be useful to the rice breeding community.
C1 [Cubry, Philippe; Pidon, Helene; Tranchant-Dubreuil, Christine; Thuillet, Anne-Celine; Holzinger, Maria; Adam, Helene; Chrestin, Harold; Ghesquiere, Alain; Sabot, Francois; Vigouroux, Yves; Albar, Laurence; Jouannic, Stefan] Univ Montpellier, IDIADE, IRD, Montpellier, France.
   [Pidon, Helene] Leibniz Inst Plant Genet & Crop Plant Res IPK Gat, Seeland, Germany.
   [Ta, Kim Nhung; Jouannic, Stefan] Univ Montpellier, LMI RICE, AGI, IRD,CIRAD,USTH, Hanoi, Vietnam.
   [Ta, Kim Nhung] Natl Inst Genet, Mishima, Shizuoka, Japan.
   [Kam, Honore] INERA, Bobo Dioulasso, Burkina Faso.
   [Francois, Olivier] Univ Grenoblec Alpes, Ctr Natl Rech Sci, Grenoble, France.
C3 Institut de Recherche pour le Developpement (IRD); Universite de
   Montpellier; Leibniz Institut fur Pflanzengenetik und
   Kulturpflanzenforschung; Institut de Recherche pour le Developpement
   (IRD); CIRAD; Vietnam Academy of Science & Technology (VAST); University
   of Science & Technology of Hanoi (USTH); Research Organization of
   Information & Systems (ROIS); National Institute of Genetics (NIG) -
   Japan; Centre National de la Recherche Scientifique (CNRS)
RP Cubry, P; Vigouroux, Y; Albar, L; Jouannic, S (corresponding author), Univ Montpellier, IDIADE, IRD, Montpellier, France.; Jouannic, S (corresponding author), Univ Montpellier, LMI RICE, AGI, IRD,CIRAD,USTH, Hanoi, Vietnam.
EM philippe.cubry@ird.fr; yves.vigouroux@ird.fr; laurence.albar@ird.fr;
   stephane.jouannic@ird.fr
RI Francois, Olivier/AAQ-3137-2020; Christine,
   Tranchant-Dubreuil/JAC-6513-2023; adam, helene/GLU-1655-2022; vigouroux,
   Yves/A-9056-2011; thuillet, anne-céline/J-9836-2016; CUBRY,
   Philippe/B-5108-2008; Pidon, Helene/AAE-3199-2019; Francois,
   Olivier/A-6051-2012; Albar, Laurence/I-8077-2018; Sabot,
   Francois/B-7820-2010
OI CUBRY, Philippe/0000-0003-1561-8949; Adam, helene/0000-0003-0324-6201;
   Jouannic, Stefan/0000-0001-5777-3336; Pidon, Helene/0000-0002-9802-1787;
   thuillet, anne-celine/0000-0003-0774-2421; Francois,
   Olivier/0000-0003-2402-2442; Albar, Laurence/0000-0003-2832-1140;
   Vigouroux, Yves/0000-0002-8361-6040; Sabot, Francois/0000-0002-8522-7583
FU France Genomique French National infrastructure; Investissement d'avenir
   [ANR-10-INBS-09]; IRIGIN project; ANR grant [ANR-13-BSV7-0017];
   Agropolis Foundation ("Investissements d'avenir" programme)
   [ANR-10-LABX-0001-01]; Fondazione Cariplo [EVOREPRICE 1201-004];
   Agropolis Resources Center for Crop Conservation, Adaptation and
   Diversity (ARCAD); European Union FEDER program; Agropolis Foundation;
   ANR grant (AfriCrop project) [ANR-13-BSV7-0017]; French Ministere de
   l'Enseignement Superieur et de la Recherche; CGIAR research program on
   rice; Agence Nationale de la Recherche (ANR) [ANR-13-BSV7-0017] Funding
   Source: Agence Nationale de la Recherche (ANR)
FX This work was supported by a grant from the France Genomique French
   National infrastructure and funded as part of "Investissement d'avenir"
   (ANR-10-INBS-09) and the IRIGIN project (http://irigin.org) to FS, an
   ANR grant (ANR-13-BSV7-0017) to YV, and a grant from Agropolis
   Foundation (through the "Investissements d'avenir" programme
   (ANR-10-LABX-0001-01) and Fondazione Cariplo under the reference ID
   EVOREPRICE 1201-004 to SJ. YV is also supported by the Agropolis
   Resources Center for Crop Conservation, Adaptation and Diversity (ARCAD)
   with support from the European Union FEDER program and from the
   Agropolis Foundation. PC was supported by an ANR grant (AfriCrop
   project, ANR-13-BSV7-0017). The French Ministere de l'Enseignement
   Superieur et de la Recherche provided a PhD grant to HP. MH was
   supported by the CGIAR research program on rice.
CR AL-Tam F, 2013, BMC PLANT BIOL, V13, DOI 10.1186/1471-2229-13-122
   [Anonymous], 2012, BIOMETRY PRINCIPLES, DOI DOI 10.2307/2343822
   [Anonymous], 2016, GGPLOT2 ELEGANT GRAP, DOI DOI 10.1007/978-3-319-24277-4
   [Anonymous], 2020, R LANG ENV STAT COMP
   Bai XF, 2016, PLANT GENOME-US, V9, DOI 10.3835/plantgenome2015.11.0115
   Boisnard A, 2007, THEOR APPL GENET, V116, P53, DOI 10.1007/s00122-007-0646-6
   Brachi B, 2010, PLOS GENET, V6, DOI 10.1371/journal.pgen.1000940
   Browning SR, 2008, HUM GENET, V124, P439, DOI 10.1007/s00439-008-0568-7
   Caye K, 2019, MOL BIOL EVOL, V36, P852, DOI 10.1093/molbev/msz008
   Chen K, 2019, BMC PLANT BIOL, V19, DOI 10.1186/s12870-019-2007-4
   Choi JY, 2019, PLOS GENET, V15, DOI 10.1371/journal.pgen.1007414
   Crowell S, 2016, NAT COMMUN, V7, DOI 10.1038/ncomms10527
   Cubry P, 2018, CURR BIOL, V28, P2274, DOI 10.1016/j.cub.2018.05.066
   Dabney A., 2019, QVALUE Q VALUE ESTIM
   de Ronde D, 2014, FRONT PLANT SCI, V5, DOI 10.3389/fpls.2014.00307
   Dray S, 2007, J STAT SOFTW, V22, P1, DOI 10.18637/jss.v022.i04
   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
   Frichot E, 2013, MOL BIOL EVOL, V30, P1687, DOI 10.1093/molbev/mst063
   Gross J., 2015, Package 'nortest1.0-4.tar.gz'
   Harrell F. E., 2019, HMISC HARRELL MISCEL
   Hayama R, 2003, NATURE, V422, P719, DOI 10.1038/nature01549
   Hayashi N, 2010, PLANT J, V64, P498, DOI 10.1111/j.1365-313X.2010.04348.x
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Hori K, 2016, THEOR APPL GENET, V129, P2241, DOI 10.1007/s00122-016-2773-4
   Huang XH, 2012, NATURE, V490, P497, DOI 10.1038/nature11532
   Hyndman RJ, 2008, J STAT SOFTW, V27, P1, DOI 10.18637/jss.v027.i03
   Issaka S., 2012, Journal of Applied Biosciences, V50, P3501
   Kam H., 2013, African Journal of Agricultural Research, V8, P2703
   Kang HM, 2008, GENETICS, V178, P1709, DOI 10.1534/genetics.107.080101
   Kawahara Y, 2013, RICE, V6, DOI 10.1186/1939-8433-6-4
   Ta KN, 2018, BMC PLANT BIOL, V18, DOI 10.1186/s12870-018-1504-1
   Kouassi NK, 2005, PLANT DIS, V89, P124, DOI 10.1094/PD-89-0124
   Lee YS, 2015, J PLANT BIOL, V58, P353, DOI 10.1007/s12374-015-0425-x
   Lipka AE, 2012, BIOINFORMATICS, V28, P2397, DOI 10.1093/bioinformatics/bts444
   Lu LM, 2009, VIRUS GENES, V38, P320, DOI 10.1007/s11262-008-0324-z
   Marchini J, 2010, NAT REV GENET, V11, P499, DOI 10.1038/nrg2796
   Meyer RS, 2016, NAT GENET, V48, P1083, DOI 10.1038/ng.3633
   PATTERSON HD, 1976, BIOMETRIKA, V63, P83, DOI 10.2307/2335087
   Pidon H, 2020, BMC PLANT BIOL, V20, DOI 10.1186/s12870-020-02433-0
   Pidon H, 2017, THEOR APPL GENET, V130, P807, DOI 10.1007/s00122-017-2853-0
   Pinel A, 2000, ARCH VIROL, V145, P1621, DOI 10.1007/s007050070080
   Pinel-Galzi A, 2018, BIO-PROTOCOL, V8, DOI 10.21769/BioProtoc.2863
   PUTTERILL J, 1995, CELL, V80, P847, DOI 10.1016/0092-8674(95)90288-0
   Rebolledo MC, 2016, FRONT PLANT SCI, V7, DOI 10.3389/fpls.2016.01384
   Sarla N, 2005, CURR SCI INDIA, V89, P955
   Tao JH, 2018, PLANT PHYSIOL, V177, P713, DOI 10.1104/pp.18.00017
   Teo ZWN, 2014, TRENDS PLANT SCI, V19, P158, DOI 10.1016/j.tplants.2013.11.001
   Thiel H, 2012, MOL PLANT MICROBE IN, V25, P1058, DOI 10.1094/MPMI-03-12-0057-R
   Thiémélé D, 2010, THEOR APPL GENET, V121, P169, DOI 10.1007/s00122-010-1300-2
   Tsuji H, 2011, CURR OPIN PLANT BIOL, V14, P45, DOI 10.1016/j.pbi.2010.08.016
   Turner S.D., 2018, J. Open Source Softw, V3, P731, DOI [10.1101/005165, 10.21105/joss.00731, DOI 10.21105/JOSS.00731]
   Wang MH, 2014, NAT GENET, V46, P982, DOI 10.1038/ng.3044
   Wang YH, 2011, CURR OPIN PLANT BIOL, V14, P94, DOI 10.1016/j.pbi.2010.11.002
   Wang ZX, 1999, PLANT J, V19, P55, DOI 10.1046/j.1365-313X.1999.00498.x
   Wei T., 2021, R PACKAGE CORRPLOT V
   Xing YZ, 2010, ANNU REV PLANT BIOL, V61, P421, DOI 10.1146/annurev-arplant-042809-112209
   Yano K, 2019, P NATL ACAD SCI USA, V116, P21262, DOI 10.1073/pnas.1904964116
   Yano K, 2016, NAT GENET, V48, P927, DOI 10.1038/ng.3596
   Yu JM, 2006, NAT GENET, V38, P203, DOI 10.1038/ng1702
   Zhang C, 2019, BIOINFORMATICS, V35, P1786, DOI 10.1093/bioinformatics/bty875
   Zhang J, 2017, J INTEGR AGR, V16, P2686, DOI 10.1016/S2095-3119(17)61724-6
   Zhang ZW, 2010, NAT GENET, V42, P355, DOI 10.1038/ng.546
   Zhao K, 2011, NAT COMMUN, V2, DOI 10.1038/ncomms1467
   Zong TX, 2020, VIRUS RES, V281, DOI 10.1016/j.virusres.2020.197870
NR 65
TC 11
Z9 13
U1 1
U2 7
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 1939-8425
EI 1939-8433
J9 RICE
JI Rice
PD SEP 16
PY 2020
VL 13
IS 1
AR 66
DI 10.1186/s12284-020-00424-1
PG 12
WC Agronomy
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA NT6SE
UT WOS:000573067300001
PM 32936396
OA Green Published, gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Kergunteuil, A
   Humair, L
   Münzbergová, Z
   Rasmann, S
AF Kergunteuil, Alan
   Humair, Laureline
   Munzbergova, Zuzana
   Rasmann, Sergio
TI Plant adaptation to different climates shapes the strengths of
   chemically mediated tritrophic interactions
SO FUNCTIONAL ECOLOGY
LA English
DT Article
DE ecological gradients; entomopathogenic nematodes; indirect plant
   defences; multi-trophic interactions; plant-herbivore interactions; root
   herbivore; terpenoids volatile compounds
ID ROOT-FEEDING INSECTS; EVOLUTIONARY RESPONSES; HERBIVORE INTERACTIONS;
   LATITUDINAL PATTERNS; DEFENSE EVOLUTION; GROWTH; RESISTANCE;
   SPECIALIZATION; TEMPERATURE; METABOLITES
AB How plant traits evolve along geographical and climatic gradients has recently received increased attention because of anticipated climate change and associated shifts in insect distribution, whether they are herbivores or predators. This issue is particularly relevant for traits related to growth and anti-herbivore defence of plants, because both sets of traits are closely tied to fitness, and because being sessile organisms, plants tend to experience strong local selection. Despite widespread recognition that the abiotic environment imposes selection on plant traits, how temperature and water availability independently select for allocation to growth and defence against herbivores is not well-resolved, and even more so, when considering under-ground herbivory and tritrophic interactions involving plant herbivores and their predators. To address heritable, climate-driven variation in root traits mediating tritrophic interactions, we performed a common garden experiment with four populations of common red fescue (Festuca rubra) encompassing the four corners of a precipitation by temperature gradient matrix. We found that plants originating from wetter and warmer conditions, in addition to producing more biomass, also produced a blend of volatile organic compounds more attractive for predatory nematodes of root insect herbivores. Moreover, across populations, variation in nematode attraction was mediated by balancing the emissions of attractive and repulsive volatile compounds. Our work builds towards better understanding how plant adaptation to climate interacts with adaptations to herbivores and their predators. A plain language summary is available for this article.
C1 [Kergunteuil, Alan; Humair, Laureline; Rasmann, Sergio] Univ Neuchatel, Inst Biol, Funct Ecol Lab, Neuchatel, Switzerland.
   [Munzbergova, Zuzana] Charles Univ Prague, Fac Sci, Dept Bot, Prague, Czech Republic.
   [Munzbergova, Zuzana] Czech Acad Sci, Inst Bot, Pruhonice, Czech Republic.
C3 University of Neuchatel; Charles University Prague; Czech Academy of
   Sciences; Institute of Botany of the Czech Academy of Sciences
RP Rasmann, S (corresponding author), Univ Neuchatel, Inst Biol, Funct Ecol Lab, Neuchatel, Switzerland.
EM sergio.rasmann@unine.ch
RI Munzbergova, Zuzana/F-6321-2013; Rasmann, Sergio/T-5376-2017
OI Munzbergova, Zuzana/0000-0002-4026-6220; Rasmann,
   Sergio/0000-0002-3120-6226
FU Norwegian Research Council project NORKLIMA [184912]; GACR [19-00522S];
   MSMT; Swiss National Funds [159869, 179481]; Norwegian Research Council
   project KLIMAFORSK [244525]
FX The plant material upon which this research was based was collected from
   within the SEEDCLIM Climate Grid field sites in western Norway, PI
   Vigdis Vandvik, funded by the Norwegian Research Council projects
   NORKLIMA 184912 and KLIMAFORSK 244525. We thank V. Vandvik for letting
   us work in the climate grid. We also thank V. Hadincova for help with
   collecting and maintaining the plant material. Z.M. was supported by
   GACR 19-00522S and MSMT. S.R. was supported by Swiss National Funds
   159869 and 179481.
CR Agrawal AA, 2006, ECOLOGY, V87, pS132, DOI 10.1890/0012-9658(2006)87[132:PDS]2.0.CO;2
   Aitken SN, 2008, EVOL APPL, V1, P95, DOI 10.1111/j.1752-4571.2007.00013.x
   Ali JG, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0038146
   Ali JG, 2011, J ECOL, V99, P26, DOI 10.1111/j.1365-2745.2010.01758.x
   [Anonymous], 2021, ALPINE PLANT LIFE FU
   [Anonymous], DATA PLANT ADAPTATIO
   [Anonymous], 2016, PHYTOCHEMICAL LANDSC, DOI DOI 10.1515/9781400881208
   [Anonymous], 2012, PACKAGE NLME LINEAR
   [Anonymous], 1977, GEOGRAPHIC VARIATION
   [Anonymous], BIORXIV
   [Anonymous], 2010, EVOLUTION DARWIN 1
   Anstett DN, 2016, TRENDS ECOL EVOL, V31, P789, DOI 10.1016/j.tree.2016.07.011
   Bolser RC, 1996, ECOLOGY, V77, P2269, DOI 10.2307/2265730
   Breiman L., 2001, Machine Learning, V45, P5, DOI 10.1023/A:1010933404324
   CHAPIN FS, 1981, ECOLOGY, V62, P1000, DOI 10.2307/1936999
   Cheplick G.P., 2015, Approaches to plant evolutionary ecology
   Coley P.D., 1991, PLANT ANIMAL INTERAC
   COLEY PD, 1985, SCIENCE, V230, P895, DOI 10.1126/science.230.4728.895
   Coley PD, 1996, ANNU REV ECOL SYST, V27, P305, DOI 10.1146/annurev.ecolsys.27.1.305
   Davis MB, 2005, ECOLOGY, V86, P1704, DOI 10.1890/03-0788
   Defossez E, 2018, ECOL LETT, V21, P609, DOI 10.1111/ele.12926
   Dobzhansky T., 1950, American Scientist, V38, P209
   Dostálek T, 2016, AOB PLANTS, V8, DOI 10.1093/aobpla/plw026
   Dray S, 2007, J STAT SOFTW, V22, P1, DOI 10.18637/jss.v022.i04
   Etterson JR, 2001, SCIENCE, V294, P151, DOI 10.1126/science.1063656
   Fine PVA, 2004, SCIENCE, V305, P663, DOI 10.1126/science.1098982
   GALEN C, 1990, OIKOS, V59, P355, DOI 10.2307/3545146
   Godschalx AL, 2019, CURR OPIN INSECT SCI, V32, P104, DOI 10.1016/j.cois.2019.01.002
   Gouinguené SP, 2002, PLANT PHYSIOL, V129, P1296, DOI 10.1104/pp.001941
   Gyawaly S, 2016, J INTEGR PEST MANAG, V7, DOI 10.1093/jipm/pmw002
   Hahn PG, 2016, TRENDS ECOL EVOL, V31, P646, DOI 10.1016/j.tree.2016.05.007
   HILL JK, 1995, ECOL ENTOMOL, V20, P237, DOI 10.1111/j.1365-2311.1995.tb00453.x
   Hothorn T, 2008, BIOMETRICAL J, V50, P346, DOI 10.1002/bimj.200810425
   Johnson MTJ, 2016, ECOL ENTOMOL, V41, P112, DOI 10.1111/een.12280
   Johnson MTJ, 2011, NEW PHYTOL, V191, P589, DOI 10.1111/j.1469-8137.2011.03816.x
   Johnson SN, 2007, AGR FOREST ENTOMOL, V9, P39, DOI 10.1111/j.1461-9563.2006.00315.x
   Johnson SN, 2016, APPL SOIL ECOL, V108, P96, DOI 10.1016/j.apsoil.2016.07.017
   Johnson SN, 2015, ANNU REV ENTOMOL, V60, P517, DOI 10.1146/annurev-ento-010814-020608
   Kergunteuil A, 2019, ECOL LETT, V22, P292, DOI 10.1111/ele.13190
   Kergunteuil A, 2016, FRONT ECOL EVOL, V4, DOI 10.3389/fevo.2016.00084
   Klanderud K, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0130205
   Knappová J, 2018, BASIC APPL ECOL, V28, P76, DOI 10.1016/j.baae.2018.02.011
   Körner C, 2007, TRENDS ECOL EVOL, V22, P569, DOI 10.1016/j.tree.2007.09.006
   Koppenhöfer AM, 2004, J ECON ENTOMOL, V97, P1842, DOI 10.1603/0022-0493-97.6.1842
   Moles AT, 2007, GLOBAL ECOL BIOGEOGR, V16, P109, DOI 10.1111/j.1466-8238.2006.00259.x
   Moles AT, 2011, NEW PHYTOL, V191, P777, DOI 10.1111/j.1469-8137.2011.03732.x
   Moles AT, 2011, FUNCT ECOL, V25, P380, DOI 10.1111/j.1365-2435.2010.01814.x
   Montague JL, 2008, J EVOLUTION BIOL, V21, P234, DOI 10.1111/j.1420-9101.2007.01456.x
   Moore BD, 2014, NEW PHYTOL, V201, P733, DOI 10.1111/nph.12526
   Munzbergová Z, 2017, J ECOL, V105, P1358, DOI 10.1111/1365-2745.12762
   Oksanen J., 2013, Vegan: Community Ecology Package
   Parmesan C, 2006, ANNU REV ECOL EVOL S, V37, P637, DOI 10.1146/annurev.ecolsys.37.091305.110100
   Pellissier L, 2018, CURR OPIN INSECT SCI, V29, P126, DOI 10.1016/j.cois.2018.07.005
   Pellissier L, 2016, J ECOL, V104, P1116, DOI 10.1111/1365-2745.12580
   Pellissier L, 2016, NEW PHYTOL, V209, P1230, DOI 10.1111/nph.13649
   Pellissier L, 2014, ECOGRAPHY, V37, P950, DOI 10.1111/ecog.00833
   Pellissier L, 2012, ECOL EVOL, V2, P1818, DOI 10.1002/ece3.296
   Pilon J, 2003, PLANT ECOL, V165, P247, DOI 10.1023/A:1022252517488
   R Development Core Team, 2017, R: A language and environment for statistical computing
   Rasmann S, 2005, NATURE, V434, P732, DOI 10.1038/nature03451
   Rasmann S, 2014, J ECOL, V102, P930, DOI 10.1111/1365-2745.12253
   Rasmann S, 2014, FUNCT ECOL, V28, P46, DOI 10.1111/1365-2435.12135
   Rasmann S, 2012, J CHEM ECOL, V38, P615, DOI 10.1007/s10886-012-0118-6
   Rasmann S, 2011, ECOL LETT, V14, P476, DOI 10.1111/j.1461-0248.2011.01609.x
   Robert CAM, 2012, ECOL LETT, V15, P55, DOI 10.1111/j.1461-0248.2011.01708.x
   Rokaya MB, 2016, ACTA OECOL, V77, P168, DOI 10.1016/j.actao.2016.10.011
   Salazar D, 2012, P NATL ACAD SCI USA, V109, P12616, DOI 10.1073/pnas.1202907109
   Scheidel U, 2004, PLANT BIOLOGY, V6, P740, DOI 10.1055/s-2004-830352
   Schemske DW, 2009, ANNU REV ECOL EVOL S, V40, P245, DOI 10.1146/annurev.ecolsys.39.110707.173430
   Schoonhoven L. M., 2005, Insect-plant biology
   Skelly DK, 2007, CONSERV BIOL, V21, P1353, DOI 10.1111/j.1523-1739.2007.00764.x
   Stamp N, 2003, Q REV BIOL, V78, P23, DOI 10.1086/367580
   Steinbauer MJ, 2018, NATURE, V556, P231, DOI 10.1038/s41586-018-0005-6
   Stojanova B, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0194670
   Thaler JS, 1997, AM NAT, V149, P1139, DOI 10.1086/286042
   TURLINGS TCJ, 1990, SCIENCE, V250, P1251, DOI 10.1126/science.250.4985.1251
   Turlings TCJ, 2012, PLANT SOIL, V358, P47, DOI 10.1007/s11104-012-1295-3
   WOODS EC, 2011, ECOLOGICAL MONOGRAPH, V0082
   Zangerl AR, 1996, AM NAT, V147, P599, DOI 10.1086/285868
   Zehnder CB, 2009, ENVIRON ENTOMOL, V38, P1161, DOI 10.1603/022.038.0424
NR 80
TC 12
Z9 12
U1 3
U2 60
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0269-8463
EI 1365-2435
J9 FUNCT ECOL
JI Funct. Ecol.
PD OCT
PY 2019
VL 33
IS 10
BP 1893
EP 1903
DI 10.1111/1365-2435.13396
EA JUL 2019
PG 11
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA JC0TY
UT WOS:000477440900001
OA Bronze
DA 2025-01-10
ER

PT J
AU Mandryk, M
   Reidsma, P
   Kanellopoulos, A
   Groot, JCJ
   van Ittersum, MK
AF Mandryk, Maryia
   Reidsma, Pytrik
   Kanellopoulos, Argyris
   Groot, Jeroen C. J.
   van Ittersum, Martin K.
TI The role of farmers' objectives in current farm practices and adaptation
   preferences: a case study in Flevoland, the Netherlands
SO REGIONAL ENVIRONMENTAL CHANGE
LA English
DT Article
DE Multi-criteria decision-making; Multi-objective optimization;
   Agriculture; Arable farm
ID VEGETABLE FARMS; CLIMATE-CHANGE; DESIGN; MANAGEMENT; OPTIONS; GOALS;
   SCALE
AB The diversity in farmers' objectives and responses to external drivers is usually not considered in integrated assessment studies that investigate impacts and adaptation to climate and socio-economic change. Here, we present an approach to assess how farmers' stated objectives relate to their currently implemented practices and to preferred adaptation options, and we discuss what this implies for assessments of future changes. We based our approach on a combination of multi-criteria decision-making methods. We consistently assessed the importance of farmers' objectives and adaptation preferences from what farmers say (based on interviews), from what farmers actually do (by analysing current farm performance) and from what farmers want (through a selected alternative farm plan). Our study was performed for six arable farms in Flevoland, a province in the Netherlands. Based on interviews with farmers, we reduced the long list of possible objectives to the most important ones. The objectives we assessed included maximization of economic result and soil organic matter, and minimization of gross margin variance, working hours and nitrogen balance. In our sample, farmers' stated preferences in objectives were often not fully reflected in realized farming practices. Adaptation preferences of farmers largely resembled their current performance, but generally involved a trend towards stated preferences. Our results suggest that in Flevoland, although farmers do have more objectives, in practical decision-making they focus on economic result maximization, while for strategic decision-making they account for objectives influencing long-term performance and indicators associated with sustainability, in this case soil organic matter.
C1 [Mandryk, Maryia; Reidsma, Pytrik; Kanellopoulos, Argyris; van Ittersum, Martin K.] Univ Wageningen & Res Ctr, Plant Prod Syst Grp, NL-6700 AK Wageningen, Netherlands.
   [Groot, Jeroen C. J.] Univ Wageningen & Res Ctr, Farming Syst Ecol Grp, NL-6708 PB Wageningen, Netherlands.
C3 Wageningen University & Research; Wageningen University & Research
RP Mandryk, M (corresponding author), Univ Wageningen & Res Ctr, Plant Prod Syst Grp, POB 430, NL-6700 AK Wageningen, Netherlands.
EM maryia.mandryk@wur.nl
RI Groot, Jeroen/G-5279-2010; Kanellopoulos, Antonis/I-5437-2015; van
   Ittersum, Martin/J-8024-2014
OI Groot, Jeroen/0000-0001-6516-5170; Reidsma, Pytrik/0000-0003-2294-809X;
   van Ittersum, Martin/0000-0001-8611-6781
FU 'Scaling and Governance' programme of Wageningen University; Agri-Adapt
   project within the Dutch 'Climate changes Spatial Planning' programme
FX This research was funded by the 'Scaling and Governance' programme of
   Wageningen University and the Agri-Adapt project within the Dutch
   'Climate changes Spatial Planning' programme. We would like to thank all
   farmers that kindly provided us with their farm data, ranked the
   objectives and discussed the alternative farm plans.
CR [Anonymous], SOIL SCI PLANT NUTR
   [Anonymous], ALLERBOUW VOLLEGROND
   [Anonymous], 2009, J ENVIRON MANAGE, DOI DOI 10.1016/j.jenvman.2008.11.014
   Audsley E, 2006, ENVIRON SCI POLICY, V9, P148, DOI 10.1016/j.envsci.2005.11.008
   Berkhout ED, 2011, AGR SYST, V104, P63, DOI 10.1016/j.agsy.2010.09.006
   Berkhout ED, 2010, AGR ECON-BLACKWELL, V41, P265, DOI 10.1111/j.1574-0862.2010.00449.x
   Bindi M., 2010, Regional Environmental Change, P1
   Dijksterhuis A, 2010, ANNU REV PSYCHOL, V61, P467, DOI 10.1146/annurev.psych.093008.100445
   Dogliotti S, 2005, AGR SYST, V86, P29, DOI 10.1016/j.agsy.2004.08.002
   Dogliotti S, 2004, AGR SYST, V80, P277, DOI 10.1016/j.agsy.2003.08.001
   Dury J, 2012, AGRON SUSTAIN DEV, V32, P567, DOI 10.1007/s13593-011-0037-x
   Gómez-Limón JA, 2004, J AGR ECON, V55, P541, DOI 10.1111/j.1477-9552.2004.tb00114.x
   Gómez-Limón JA, 2003, EUR J OPER RES, V151, P569, DOI 10.1016/S0377-2217(02)00625-2
   Groot JCJ, 2012, AGR SYST, V110, P63, DOI 10.1016/j.agsy.2012.03.012
   Groot JCJ, 2011, METHODS ECOL EVOL, V2, P643, DOI 10.1111/j.2041-210X.2011.00114.x
   Hazell P.B.R., 1986, Mathematical Programming for Economic Analysis in Agriculture
   Hermans CML, 2010, ECOL MODEL, V221, P2177, DOI 10.1016/j.ecolmodel.2010.03.021
   Jager W, 2000, ECOL ECON, V35, P357, DOI 10.1016/S0921-8009(00)00220-2
   Janssen MA, 2001, J ECON PSYCHOL, V22, P745, DOI 10.1016/S0167-4870(01)00063-0
   Janssen S, 2007, AGR SYST, V94, P622, DOI 10.1016/j.agsy.2007.03.001
   Jones D, 2011, EUR J OPER RES, V213, P238, DOI 10.1016/j.ejor.2011.03.012
   Kanellopoulos A, 2014, EUR J AGRON, V52, P69, DOI 10.1016/j.eja.2013.10.003
   Kanellopoulos A, 2010, J AGR ECON, V61, P274, DOI 10.1111/j.1477-9552.2010.00241.x
   Mandryk M, 2012, LANDSCAPE ECOL, V27, P509, DOI [10.1007/s10980-012-9714-7, 10.1007/s10980-012-9721-8]
   Mayer DG, 2008, STUD COMPUT INTELL, P141
   Meerburg BG, 2009, J AGR SCI, V147, P511, DOI 10.1017/S0021859609990049
   Seo SN, 2010, FOOD POLICY, V35, P32, DOI 10.1016/j.foodpol.2009.06.004
   Nordström EM, 2009, CAN J FOREST RES, V39, P1979, DOI 10.1139/X09-107
   Prato T, 2010, ENVIRON MANAGE, V45, P577, DOI 10.1007/s00267-010-9427-0
   Reidsma P, 2010, EUR J AGRON, V32, P91, DOI 10.1016/j.eja.2009.06.003
   Romero C., 2003, MULTIPLE CRITERIA AN
   Rufino MC, 2011, FOOD POLICY, V36, P452, DOI 10.1016/j.foodpol.2011.03.004
   Sterk B, 2006, AGR SYST, V87, P211, DOI 10.1016/j.agsy.2004.11.008
   Sumpsi JM, 1997, EUR J OPER RES, V96, P64, DOI 10.1016/0377-2217(95)00338-X
   ten Berge HFM, 2000, EUR J AGRON, V13, P263, DOI 10.1016/S1161-0301(00)00078-2
   Tittonell P, 2007, AGR SYST, V95, P76, DOI 10.1016/j.agsy.2007.04.002
   Van Calker KJ, 2005, AGR HUM VALUES, V22, P53, DOI [10.1004/s10460-004-7230-3, 10.1007/s10460-004-7230-3]
   van der Ploeg JD, 2009, J ENVIRON MANAGE, V90, pS124, DOI 10.1016/j.jenvman.2008.11.022
   van Ittersum MK, 1998, AGR SYST, V58, P309, DOI 10.1016/S0308-521X(98)00033-X
NR 39
TC 51
Z9 60
U1 1
U2 49
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 AUG
PY 2014
VL 14
IS 4
BP 1463
EP 1478
DI 10.1007/s10113-014-0589-9
PG 16
WC Environmental Sciences; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA AM3EX
UT WOS:000339736700015
DA 2025-01-10
ER

PT J
AU Zera, AJ
AF Zera, Anthony J.
TI Microevolution of intermediary metabolism: evolutionary genetics meets
   metabolic biochemistry
SO JOURNAL OF EXPERIMENTAL BIOLOGY
LA English
DT Article
DE evolution; life history; lipid metabolism; electron transport;
   anthocyanin; enzyme polymorphism; metabolic control analysis; chemostat
   selection
ID HISTORY TRADE-OFFS; ALCOHOL-DEHYDROGENASE POLYMORPHISM;
   DROSOPHILA-MELANOGASTER; ADAPTIVE EVOLUTION; FAT-CONTENT; CORRELATED
   RESPONSES; POPULATION-GENETICS; PARALLEL EVOLUTION; FLIGHT CAPABILITY;
   LIPID-METABOLISM
AB During the past decade, microevolution of intermediary metabolism has become an important new research focus at the interface between metabolic biochemistry and evolutionary genetics. Increasing recognition of the importance of integrative studies in evolutionary analysis, the rising interest in 'evolutionary systems biology', and the development of various 'omics' technologies have all contributed significantly to this developing interface. The present review primarily focuses on five prominent areas of recent research on pathway microevolution: lipid metabolism and life-history evolution; the electron transport system, hybrid breakdown and speciation; glycolysis, alcohol metabolism and population adaptation in Drosophila; chemostat selection in microorganisms; and anthocyanin pigment biosynthesis and flower color evolution. Some of these studies have provided a new perspective on important evolutionary topics that have not been investigated extensively from a biochemical perspective (hybrid breakdown, parallel evolution). Other studies have provided new data that augment previous biochemical information, resulting in a deeper understanding of evolutionary mechanisms (allozymes and biochemical adaptation to climate, life-history evolution, flower pigments and the genetics of adaptation). Finally, other studies have provided new insights into how the function or position of an enzyme in a pathway influences its evolutionary dynamics, in addition to providing powerful experimental models for investigations of network evolution. Microevolutionary studies of metabolic pathways will undoubtedly become increasingly important in the future because of the central importance of intermediary metabolism in organismal fitness, the wealth of biochemical data being provided by various omics technologies, and the increasing influence of integrative and systems perspectives in biology.
C1 Univ Nebraska, Sch Biol Sci, Lincoln, NE 68588 USA.
C3 University of Nebraska System; University of Nebraska Lincoln
RP Zera, AJ (corresponding author), Univ Nebraska, Sch Biol Sci, Lincoln, NE 68588 USA.
EM azera1@unlnotes.unl.edu
FU National Science Foundation [IOS-0516973, IBN-0212486]
FX This paper is based on a talk given at the 2010 Journal of Experimental
   Biology Symposium on 'The Biology of Energy Expenditure', held in
   Murren, Switzerland. I thank the organizers of the symposium for
   inviting me to participate. I also thank W. F. Eanes, M. D. Rausher, J.
   Storz and two anonymous reviewers for thoughtful comments on a previous
   version of the manuscript. Finally, I gratefully acknowledge the
   National Science Foundation for continuous support of my research during
   the past 20 years, most recently grants IOS-0516973 and IBN-0212486.
CR [Anonymous], 2004, Speciation
   [Anonymous], 1997, Understanding the control of metabolism
   [Anonymous], 1974, GENETIC BASIS EVOLUT
   [Anonymous], 1942, Biology Symposium
   [Anonymous], 2002, Biochemical Adaptation
   ASANTE EA, 1991, GENET RES, V58, P123, DOI 10.1017/S0016672300029773
   ASANTE EA, 1989, GENET RES, V54, P155, DOI 10.1017/S0016672300028536
   Bagheri HC, 2004, GENETICS, V168, P1713, DOI 10.1534/genetics.104.028696
   BALDWIN E, 1970, INTRO COMP BIOCH
   Begun DJ, 1999, MOL BIOL EVOL, V16, P1816, DOI 10.1093/oxfordjournals.molbev.a026095
   Burton RS, 2006, AM NAT, V168, pS14, DOI 10.1086/509046
   CAVENER DR, 1981, P NATL ACAD SCI-BIOL, V78, P4444, DOI 10.1073/pnas.78.7.4444
   CLARK AG, 1990, EVOLUTION, V44, P637, DOI 10.1111/j.1558-5646.1990.tb05944.x
   Clegg MT, 2003, NAT REV GENET, V4, P206, DOI 10.1038/nrg1023
   Des Marais DL, 2010, EVOLUTION, V64, P2044, DOI 10.1111/j.1558-5646.2010.00972.x
   Dobzhansky T, 1936, GENETICS, V21, P113
   Dunham MJ, 2002, P NATL ACAD SCI USA, V99, P16144, DOI 10.1073/pnas.242624799
   Dykhuizen DE, 2009, EXPERIMENTAL EVOLUTION: CONCEPTS, METHODS, AND APPLICATIONS OF SELECTION EXPERIMENTS, P67
   DYKHUIZEN DE, 1990, TRENDS ECOL EVOL, V5, P257, DOI 10.1016/0169-5347(90)90067-N
   Dykhuizen DE, 2004, GENETICS, V167, P2015, DOI 10.1534/genetics.103.025205
   Eanes WF, 2006, P NATL ACAD SCI USA, V103, P19413, DOI 10.1073/pnas.0607095104
   Eanes WF, 2011, J EXP BIOL, V214, P165, DOI 10.1242/jeb.046458
   Eanes WF, 1999, ANNU REV ECOL SYST, V30, P301, DOI 10.1146/annurev.ecolsys.30.1.301
   Ehrenreich IM, 2006, AM J BOT, V93, P953, DOI 10.3732/ajb.93.7.953
   Ellison CK, 2006, EVOLUTION, V60, P1382, DOI 10.1111/j.0014-3820.2006.tb01217.x
   Feder M.E., 1992, Genes in Ecology, P365, DOI DOI 10.1038/nrg1319
   Feder ME, 2007, J EXP BIOL, V210, P1653, DOI 10.1242/jeb.02725
   Feder ME, 2005, J EVOLUTION BIOL, V18, P901, DOI 10.1111/j.1420-9101.2005.00921.x
   FELL DA, 1995, BIOCHEM J, V311, P35, DOI 10.1042/bj3110035
   Ferea TL, 1999, P NATL ACAD SCI USA, V96, P9721, DOI 10.1073/pnas.96.17.9721
   Flowers JM, 2007, MOL BIOL EVOL, V24, P1347, DOI 10.1093/molbev/msm057
   Fraser HB, 2010, P NATL ACAD SCI USA, V107, P2977, DOI 10.1073/pnas.0912245107
   FRERIKSEN A, 1994, GENETICS, V137, P1071
   FRERIKSEN A, 1991, J BIOL CHEM, V266, P21399
   Fry JD, 2008, EVOLUTION, V62, P66, DOI 10.1111/j.1558-5646.2007.00288.x
   Fry JD, 2004, INTEGR COMP BIOL, V44, P275, DOI 10.1093/icb/44.4.275
   Gershman B, 2007, PHYSIOL GENOMICS, V29, P24, DOI 10.1152/physiolgenomics.00061.2006
   GRACEY A, 2003, J EXP BIOL, V209, P1584
   Gracey AY, 2003, ANNU REV PHYSIOL, V65, P231, DOI 10.1146/annurev.physiol.65.092101.142716
   GRANNER D, 1990, J BIOL CHEM, V265, P10173
   Greenberg AJ, 2008, MOL BIOL EVOL, V25, P2537, DOI 10.1093/molbev/msn205
   HALL JG, 1983, EVOL BIOL, V16, P53
   Harrison JS, 2006, MOL BIOL EVOL, V23, P559, DOI 10.1093/molbev/msj058
   Harshman LG, 2007, TRENDS ECOL EVOL, V22, P80, DOI 10.1016/j.tree.2006.10.008
   Harshman LG, 1998, EVOLUTION, V52, P1679, DOI [10.1111/j.1558-5646.1998.tb02247.x, 10.2307/2411340]
   HASTINGS IM, 1990, GENET RES, V55, P55, DOI 10.1017/S0016672300025192
   Hochachka P W, 1973, COMP ANIMAL PHYSL, V1, P212
   Hoekstra HE, 2007, EVOLUTION, V61, P995, DOI 10.1111/j.1558-5646.2007.00105.x
   Ideker T, 2001, SCIENCE, V292, P929, DOI 10.1126/science.292.5518.929
   KACSER H, 1981, GENETICS, V97, P639
   Kacser H, 1979, BIOCHEM SOC T, V7, P1149, DOI 10.1042/bst0071149
   Koehn R.K., 1983, P115
   LABATE J, 1992, GENETICS, V132, P783
   Larracuente AM, 2008, TRENDS GENET, V24, P114, DOI 10.1016/j.tig.2007.12.001
   LAURIE CC, 1988, P NATL ACAD SCI USA, V85, P5161, DOI 10.1073/pnas.85.14.5161
   Lu YQ, 2003, MOL BIOL EVOL, V20, P1844, DOI 10.1093/molbev/msg197
   Matzkin LM, 2009, GENETICS, V182, P1279, DOI 10.1534/genetics.109.104927
   McKenzie M, 2003, MOL BIOL EVOL, V20, P1117, DOI 10.1093/molbev/msg132
   Merritt TJS, 2005, GENETICS, V171, P1707, DOI 10.1534/genetics.105.048249
   MIDDLETON RJ, 1983, GENETICS, V105, P633
   Mitton JB., 1997, Selection in Natural Populations
   Montooth KL, 2010, EVOLUTION, V64, P3364, DOI 10.1111/j.1558-5646.2010.01077.x
   Pagel M, 2008, EVOLUTIONARY GENOMICS AND PROTEOMICS, P1
   PAQUIN C, 1983, NATURE, V302, P495, DOI 10.1038/302495a0
   Powell FL, 2003, ANNU REV PHYSIOL, V65, P203, DOI 10.1146/annurev.physiol.65.092101.142711
   Quattrocchio F., 2006, The Science of Flavonoids, P97, DOI [10.1007/978-0-387-28822-2_4, DOI 10.1007/978-0-387-28822-24, 10.1007/978-0-387-28822-24]
   Ramsay H, 2009, MOL BIOL EVOL, V26, P1045, DOI 10.1093/molbev/msp021
   Rausher MD, 2008, J MOL EVOL, V67, P137, DOI 10.1007/s00239-008-9105-5
   Rausher MD, 2008, INT J PLANT SCI, V169, P7, DOI 10.1086/523358
   Rausher MD, 1999, MOL BIOL EVOL, V16, P266, DOI 10.1093/oxfordjournals.molbev.a026108
   Rawson PD, 2002, P NATL ACAD SCI USA, V99, P12955, DOI 10.1073/pnas.202335899
   Roff Derek A., 1992
   Rosenzweig F, 2009, EXPERIMENTAL EVOLUTION: CONCEPTS, METHODS, AND APPLICATIONS OF SELECTION EXPERIMENTS, P353
   SAVAGEAU MA, 1989, J THEOR BIOL, V141, P93, DOI 10.1016/S0022-5193(89)80011-6
   Selander K., 1976, Molecular evolution., P21
   Shirley BW, 1996, TRENDS PLANT SCI, V1, P377, DOI 10.1016/1360-1385(96)10040-6
   SOMERO GN, 1969, BIOCHEM J, V114, P237, DOI 10.1042/bj1140237
   St-Cyr J, 2008, MOL ECOL, V17, P1850, DOI 10.1111/j.1365-294X.2008.03696.x
   STANLEY SM, 1981, ANN ECOL SOC AUSTR, V11, P121
   Stearns S.C., 1992, pi
   Storz JF, 2010, EVOLUTION, V64, P2489, DOI 10.1111/j.1558-5646.2010.01044.x
   STREISFELD MA, 2010, EVOLUTION, DOI DOI 10.1111/J.1558-5646.2010.01128.X
   Streisfeld MA, 2009, NEW PHYTOL, V183, P751, DOI 10.1111/j.1469-8137.2009.02929.x
   Townsend C.R., 1981, PHYSL ECOLOGY EVOLUT
   VANDELDEN W, 1982, EVOL BIOL, V15, P187
   VANSTRALLEN NM, 2006, INTRO ECOLOGICAL GEN
   Verrelli BC, 2001, GENETICS, V159, P201
   Verrelli BC, 2001, GENETICS, V157, P1649
   WATT WB, 1991, FUNCT ECOL, V5, P145, DOI 10.2307/2389252
   Watt WB, 2000, ANNU REV GENET, V34, P593, DOI 10.1146/annurev.genet.34.1.593
   Willett CS, 2004, MOL BIOL EVOL, V21, P443, DOI 10.1093/molbev/msh031
   Wright KM, 2010, GENETICS, V184, P483, DOI 10.1534/genetics.109.110411
   Zera AJ, 2005, INTEGR COMP BIOL, V45, P511, DOI 10.1093/icb/45.3.511
   Zera AJ, 2004, PHYSIOL BIOCHEM ZOOL, V77, P255, DOI 10.1086/383500
   Zera AJ, 2003, EVOLUTION, V57, P586, DOI 10.1111/j.0014-3820.2003.tb01550.x
   Zera AJ, 2001, ANNU REV ECOL SYST, V32, P95, DOI 10.1146/annurev.ecolsys.32.081501.114006
   ZERA AJ, 2011, MOL MECH UNDERLYING
   ZERA AJ, 1985, COMPREHENSIVE INSECT, V10, P633
   Zera AJ, 2006, AM NAT, V167, P889, DOI 10.1086/503578
   Zera AJ, 2009, EXPERIMENTAL EVOLUTION: CONCEPTS, METHODS, AND APPLICATIONS OF SELECTION EXPERIMENTS, P217
   Zhao ZW, 2002, P NATL ACAD SCI USA, V99, P16829, DOI 10.1073/pnas.262533999
   Zufall RA, 2004, NATURE, V428, P847, DOI 10.1038/nature02489
NR 102
TC 36
Z9 40
U1 1
U2 40
PU COMPANY BIOLOGISTS LTD
PI CAMBRIDGE
PA BIDDER BUILDING, STATION RD, HISTON, CAMBRIDGE CB24 9LF, ENGLAND
SN 0022-0949
EI 1477-9145
J9 J EXP BIOL
JI J. Exp. Biol.
PD JAN
PY 2011
VL 214
IS 2
BP 179
EP 190
DI 10.1242/jeb.046912
PG 12
WC Biology; Zoology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Life Sciences & Biomedicine - Other Topics; Zoology
GA 697UW
UT WOS:000285545400005
PM 21177939
DA 2025-01-10
ER

PT J
AU Pizzol, J
   Pintureau, B
   Khoualdia, O
   Desneux, N
AF Pizzol, Jeannine
   Pintureau, Bernard
   Khoualdia, Othman
   Desneux, Nicolas
TI Temperature-dependent differences in biological traits between two
   strains of <i>Trichogramma cacoeciae</i> (Hymenoptera:
   Trichogrammatidae)
SO JOURNAL OF PEST SCIENCE
LA English
DT Article
DE Populations; Egg parasitoids; Fecundity; Emergence; Mortality; Life
   history
ID EUROPEAN CORN-BORER; SPECIES HYM TRICHOGRAMMATIDAE; HUBN LEP PYRALIDAE;
   REARING TEMPERATURE; COLD-STORAGE; PARASITISM; LEPIDOPTERA; PERFORMANCE;
   EVANESCENS; MANAGEMENT
AB Parasitoids' efficiency in controlling pests depends not only on their ability to parasitize their hosts but also on how much they are adapted to climatic conditions (notably temperature) of the area where they are planned to be released. In addition, the optimal conditions for production of parasitoids used for inundative releases like Trichogramma spp. may also vary largely as a function of strains. Using the parasitoid Trichogramma cacoeciae Marchal as biological model, we studied how temperature affects important parasitoid efficiency-related biological traits under laboratory conditions. Emergence, mortality rates and fecundity of two strains of T. cacoeciae, one originating from France (Alsace) and the other one from Tunisia (Degache), were compared at constant temperatures of 15, 20, 25 and 30 degrees C. The parasitoids of the French strain showed highest fecundity at 25 degrees C with wasps that had been reared at 20 or 25 degrees C. The Tunisian strain showed the highest fecundity at 25 degrees C, but only when wasps were previously reared at 25 or 30 degrees C. For both strains, the highest mortality occurred among wasps that had laid eggs at 30 degrees C. Emergence rates were relatively high at all temperatures, although the French strain did better at 15-25 degrees C and the Tunisian one at 20-30 degrees C. Because of the differences in biological traits of these two T. cacoeciae strains in relation to the temperature, a judicious choice must be made among the various strains when using this species in biological control programs.
C1 [Pizzol, Jeannine; Desneux, Nicolas] INRA UR880 URIH, F-06903 Sophia Antipolis, France.
   [Pintureau, Bernard] BF2I UMR INRA INSA Lyon, F-69621 Villeurbanne, France.
   [Khoualdia, Othman] Ctr Reg Rech Agr Oasienne, Degache 2260, Tunisia.
C3 INRAE; Institut National des Sciences Appliquees de Lyon - INSA Lyon;
   INRAE
RP Pizzol, J (corresponding author), INRA UR880 URIH, 400 Route Chappes,BP 167, F-06903 Sophia Antipolis, France.
EM jeannine.pizzol@sophia.inra.fr
RI Desneux, Nicolas/J-6262-2013
CR [Anonymous], 1990, ARTHROPOD BIOL CONTR
   [Anonymous], DIAPAUSE CHEZ TRICHO
   Ayvaz A, 2008, J STORED PROD RES, V44, P232, DOI 10.1016/j.jspr.2008.02.001
   Ayvaz A, 2008, J PEST SCI, V81, P57, DOI 10.1007/s10340-008-0192-2
   BABI A, 1994, C INRA 73 CAIR EG 4, P59
   BABI A, 1990, THESIS U MARSEILLE
   Cabello T., 1988, Colloques de l'INRA, V43, P155
   Carrière Y, 2001, AM NAT, V157, P570, DOI 10.1086/319931
   Consoli FL, 1995, J APPL ENTOMOL, V119, P667, DOI 10.1111/j.1439-0418.1995.tb01355.x
   DAUMAL J, 1975, Annales de Zoologie Ecologie Animale, V7, P45
   Desneux N, 2007, ANNU REV ENTOMOL, V52, P81, DOI 10.1146/annurev.ento.52.110405.091440
   Desneux N, 2010, J PEST SCI, V83, P197, DOI 10.1007/s10340-010-0321-6
   Frandon J, 2002, 2 C INT MOYENS ALT L, P33
   Hansen LS, 2002, J ECON ENTOMOL, V95, P50, DOI 10.1603/0022-0493-95.1.50
   Hazarika LK, 2009, ANNU REV ENTOMOL, V54, P267, DOI 10.1146/annurev.ento.53.103106.093359
   Kalyebi A, 2006, B ENTOMOL RES, V96, P305, DOI 10.1079/BER2006429
   KHOUALDIA O, 2008, CR C INT RAV AGR AFP, P215
   Khoualdia O., 1995, ANN INRAT, V68, P145
   Klug T, 2009, J PEST SCI, V82, P73, DOI 10.1007/s10340-008-0224-y
   KOT J, 1979, Polish Ecological Studies, V5, P5
   Li Li-Ying, 1994, P37
   Mansour M, 2010, J PEST SCI, V83, P243, DOI 10.1007/s10340-010-0291-8
   McDougall SJ, 1997, ENTOMOL EXP APPL, V83, P195, DOI 10.1023/A:1002903720301
   PAK GA, 1985, ENTOMOL EXP APPL, V38, P3, DOI 10.1007/BF00163346
   PARRA JRP, 1991, P 3 INT S TRICH OTH, V56, P81
   PAVLIK J, 1992, ZOOL JAHRB ALLG ZOOL, V96, P417
   Pintureau B., 1997, Miscellania Zoologica (Barcelona), V20, P11
   Pintureau B, 2009, LUTTE BIOL TRI UNPUB
   PINTUREAU B., 2008, ESPECES EUROPEENNES
   Pizzol J, 2005, BIOCONTROL SCI TECHN, V15, P527, DOI 10.1080/09583150500088934
   Pizzol J., 2004, Etudes bioecologiques de Trichogramma cacoeciae Marchal, parasitoide oophage de l'eudemis de la vigne, en vue de son utilisation en lutte biologique
   PIZZOL J, 1994, C INRA, V73, P27
   Pizzol J, 2008, ENTOMOL EXP APPL, V127, P72, DOI 10.1111/j.1570-7458.2008.00671.x
   Prasad RP, 2002, BIOL CONTROL, V25, P110, DOI 10.1016/S1049-9644(02)00050-6
   Pratissoli D, 2000, J APPL ENTOMOL, V124, P339, DOI 10.1046/j.1439-0418.2000.00477.x
   Ratte H.T., 1985, P33
   Reznik S.Y., 2006, Entomology Review, V86, P133, DOI DOI 10.1134/S0013873806020023
   RUSSO J, 1982, AGRONOMIE, V2, P517, DOI 10.1051/agro:19820603
   RUSSO J, 1982, AGRONOMIE, V2, P509, DOI 10.1051/agro:19820602
   Schöller M, 2001, ENTOMOL EXP APPL, V98, P35, DOI 10.1023/A:1018700408113
   Smith SM, 1996, ANNU REV ENTOMOL, V41, P375, DOI 10.1146/annurev.en.41.010196.002111
   Suckling DM, 2010, ANNU REV ENTOMOL, V55, P285, DOI 10.1146/annurev-ento-112408-085311
   Tabone E, 2010, J PEST SCI, V83, P251, DOI 10.1007/s10340-010-0292-7
   VOEGELE J, 1974, Entomophaga, V19, P341, DOI 10.1007/BF02371059
   Wang BD, 2004, ENVIRON ENTOMOL, V33, P787, DOI 10.1603/0046-225X-33.4.787
   Wiackowski S. K., 1966, Entomophaga, V11, P261, DOI 10.1007/BF02372960
NR 46
TC 76
Z9 82
U1 0
U2 70
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 1612-4758
EI 1612-4766
J9 J PEST SCI
JI J. Pest Sci.
PD DEC
PY 2010
VL 83
IS 4
BP 447
EP 452
DI 10.1007/s10340-010-0327-0
PG 6
WC Entomology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Entomology
GA 679WB
UT WOS:000284190400011
DA 2025-01-10
ER

PT J
AU Lee, TD
   Reich, PB
   Bolstad, PV
AF Lee, TD
   Reich, PB
   Bolstad, PV
TI Acclimation of leaf respiration to temperature is rapid and related to
   specific leaf area, soluble sugars and leaf nitrogen across three
   temperate deciduous tree species
SO FUNCTIONAL ECOLOGY
LA English
DT Article
DE Acer; common garden; global change; phenotypic plasticity; Quercus
ID DARK RESPIRATION; THERMAL-ACCLIMATION; PLANT RESPIRATION; ROOT
   RESPIRATION; POPULATIONS; EVOLUTION; NORTHERN; TRAITS; ALPINE; STARCH
AB 1. Rates of plant respiration are sensitive to temperature, and modulated by acclimation to prevailing temperature and adaptation to the climate of origin.
   2. Our objective was to evaluate the rapidity and magnitude of acclimation of leaf respiration (R-d) to natural temperature events in field-grown tree seedlings and to assess inter- and intraspecific variation across seasons and years.
   3. We measured R-d and associated traits of seedlings of three temperate deciduous species, Quercus alba L., Quercus rubra L. and Acer rubrum L., growing in a common garden in St Paul, Minnesota, USA. Seedlings of each species were derived from populations spanning their range from cool/dry (Minnesota/Wisconsin) to warm/moist (North Carolina/Louisiana) regions.
   4. Measurements at a common temperature (24 degrees C) were made during consecutive cool- and warm-weather systems (differing by 7-10.5 degrees C) across two growing seasons.
   5. R-d rates following the warmest temperatures were 62% lower, on average, than those following cool temperatures. There was little evidence that respiration per se, or its response to temperature, depended on adaptation to climate of origin.
   6. Temperature, specific leaf area, and leaf soluble sugar and nitrogen concentrations were important predictors of R-d and together explained 77% of the variation across species and populations.
   7. To predict forest CO2 exchange responses to global change accurately, parameters are needed that account for the acclimation of respiration to prevailing temperature.
C1 Univ Wisconsin, Dept Biol, Eau Claire, WI 54701 USA.
   Univ Minnesota, Dept Forest Resources, St Paul, MN 55108 USA.
C3 University of Wisconsin System; University of Minnesota System;
   University of Minnesota Twin Cities
RP Univ Wisconsin, Dept Biol, Phillips Hall 330, Eau Claire, WI 54701 USA.
EM leetd@uwec.edu
RI Reich, Paul/D-4321-2013
OI Reich, Peter/0000-0003-4424-662X; Lee, Tali/0000-0002-3933-6607
CR Ackerly DD, 2000, BIOSCIENCE, V50, P979, DOI 10.1641/0006-3568(2000)050[0979:TEOPET]2.0.CO;2
   Amthor Jeffrey S., 1994, P501
   Arnone JA, 1997, ARCTIC ALPINE RES, V29, P122
   Atkin OK, 2000, NEW PHYTOL, V147, P141, DOI 10.1046/j.1469-8137.2000.00683.x
   Atkin OK, 2000, PLANT CELL ENVIRON, V23, P15, DOI 10.1046/j.1365-3040.2000.00511.x
   Atkin OK, 2003, TRENDS PLANT SCI, V8, P343, DOI 10.1016/S1360-1385(03)00136-5
   Bolstad PV, 2003, TREE PHYSIOL, V23, P969, DOI 10.1093/treephys/23.14.969
   Collier DE, 1996, CAN J BOT, V74, P317, DOI 10.1139/b96-039
   Gunderson CA, 2000, TREE PHYSIOL, V20, P87
   HAISSIG BE, 1979, PHYSIOL PLANTARUM, V47, P151, DOI 10.1111/j.1399-3054.1979.tb03207.x
   HANSEN J, 1975, ANAL BIOCHEM, V68, P87, DOI 10.1016/0003-2697(75)90682-X
   *IPCC, 2001, 6 SESS IPCC WORK GRO, V2
   LARIGAUDERIE A, 1995, ANN BOT-LONDON, V76, P245, DOI 10.1006/anbo.1995.1093
   Lavigne MB, 1996, TREE PHYSIOL, V16, P847
   Loveys BR, 2003, GLOBAL CHANGE BIOL, V9, P895, DOI 10.1046/j.1365-2486.2003.00611.x
   Meir P, 2001, FUNCT ECOL, V15, P378, DOI 10.1046/j.1365-2435.2001.00534.x
   Mitchell KA, 1999, TREE PHYSIOL, V19, P861
   Oleksyn J, 2003, OECOLOGIA, V136, P220, DOI 10.1007/s00442-003-1265-9
   Oleksyn J, 2002, ANN FOR SCI, V59, P1, DOI 10.1051/forest:2001001
   Oleksyn Jacek, 1998, Silva Fennica, V32, P129
   Penning de Vries F.W.T., 1975, Ann. Bot, V39, P77
   Reich P. B., 2003, International Journal of Plant Sciences, V164, pS143, DOI 10.1086/374368
   Reich PB, 1996, FUNCT ECOL, V10, P768, DOI 10.2307/2390512
   Reich PB, 1998, OECOLOGIA, V114, P471, DOI 10.1007/s004420050471
   RYAN MG, 1995, PLANT CELL ENVIRON, V18, P765, DOI 10.1111/j.1365-3040.1995.tb00579.x
   Teskey RO, 1999, TREE PHYSIOL, V19, P519, DOI 10.1093/treephys/19.8.519
   Thornley JHM, 2000, ANN BOT-LONDON, V85, P55, DOI 10.1006/anbo.1999.0997
   Tjoelker MG, 1999, PLANT CELL ENVIRON, V22, P767, DOI 10.1046/j.1365-3040.1999.00435.x
   Turnbull MH, 2001, TREE PHYSIOL, V21, P571, DOI 10.1093/treephys/21.9.571
   Wythers KR, 2005, GLOBAL CHANGE BIOL, V11, P435, DOI 10.1111/j.1365-2486.2005.00922.x
NR 30
TC 90
Z9 115
U1 0
U2 72
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0269-8463
EI 1365-2435
J9 FUNCT ECOL
JI Funct. Ecol.
PD AUG
PY 2005
VL 19
IS 4
BP 640
EP 647
DI 10.1111/j.1365-2435.2005.01023.x
PG 8
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA 957TX
UT WOS:000231397300012
OA Bronze
DA 2025-01-10
ER

PT J
AU Steig, F
AF Steig, Florian
TI Imagining the flood: rationalities of governance in sinking cities
SO FRONTIERS IN POLITICAL SCIENCE
LA English
DT Article
DE sea level rise; climate adaptation; climate governance; climate futures;
   discourse; depoliticization; STS; poststructuralism
ID CLIMATE-CHANGE; POLITICAL ECOLOGY; CHANGE ADAPTATION; RISK-MANAGEMENT;
   LAND SUBSIDENCE; GREAT-GARUDA; FUTURE; MOBILITIES; POLICIES; JAKARTA
AB The rise in global sea levels poses a substantial, sometimes existential threat to coastal cities around the world, such as Bangkok, Lagos, or Jakarta. Adaptation projects range from hard infrastructure to nature-based solutions or 'planned retreat', often having severe implications in terms of equity and equality. Given the threat of urban flooding and submergence, this paper asks how 'the future' for these cities is imagined, and how sociotechnical imaginaries of climate futures inform policymaking. Using insights from poststructuralism and Science and Technology Studies (STS), I argue that the way of 'seeing' and 'knowing' sea level rise is constitutive of the rationalities that undergird the governing of rising water around the world. I trace the discrete operations of the discursive formations and imaginaries that have evolved globally around the issue of sea level rise, with their own distinctive logics. Analyzing a variety of globally circulating policy documents and local adaptation projects, I show how the governance of sea level rise is based on a very specific 'expert' knowledge that allows re-designing sinking cities 'from above'. This kind of knowledge, provided by a depoliticizing global network of consultants, designers, and development banks, privileges imaginaries of modernity and control using technology and engineering, as well as ideas on how populations in flood-prone areas are expected to govern themselves in the advent of rising sea levels. These imaginaries tend to marginalize alternative local adaptation practices, lead to unintended outcomes, and often discriminate against those who are already vulnerable to climate change impacts.
C1 [Steig, Florian] Univ Oxford, Sch Geog & Environm, Oxford, England.
C3 University of Oxford
RP Steig, F (corresponding author), Univ Oxford, Sch Geog & Environm, Oxford, England.
EM florian.steig@gtc.ox.ac.uk
OI Steig, Florian/0009-0009-5134-9425
FX The author(s) declare that no financial support was received for the
   research, authorship, and/or publication of this article.
CR Ajibade I, 2019, CLIMATIC CHANGE, V157, P299, DOI 10.1007/s10584-019-02535-1
   Ajibade I, 2017, INT J DISAST RISK RE, V26, P85, DOI 10.1016/j.ijdrr.2017.09.029
   Alvarez MK, 2019, INT J URBAN REGIONAL, V43, P227, DOI 10.1111/1468-2427.12757
   Andersson J, 2019, SCI TECHNOL HUM VAL, V44, P237, DOI 10.1177/0162243918791263
   Cao A, 2021, CURR OPIN ENV SUST, V50, P87, DOI 10.1016/j.cosust.2021.02.010
   [Anonymous], 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, P2539, DOI [10.1017/9781009325844.026, DOI 10.1017/9781009325844.026]
   [Anonymous], 2011, Guide to Climate Change Adaptation in Cities
   [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 10.2777/479582
   [Anonymous], 2014, HOMEOWNERS GUIDE RET
   [Anonymous], 2015, Investing in Urban Resilience: Protecting and Promoting Development in a Changing World
   Ao ZR, 2024, SCIENCE, V384, P301, DOI 10.1126/science.adl4366
   Appel H, 2018, PROMISE OF INFRASTRUCTURE, P1
   Arnall A, 2023, POLIT GEOGR, V102, DOI 10.1016/j.polgeo.2023.102839
   ARUP, Designing with water: Shanghai urban drainage masterplanning
   ARUP, 2022, Global sponge cities snapshot-Arup
   Atteridge A, 2018, WIRES CLIM CHANGE, V9, DOI 10.1002/wcc.500
   Beach D., 2013, PROCESS TRACING METH
   Beck S, 2011, REG ENVIRON CHANGE, V11, P297, DOI 10.1007/s10113-010-0136-2
   Berg N., 2017, The Guardian
   Bigger P, 2021, ANN AM ASSOC GEOGR, V111, P36, DOI 10.1080/24694452.2020.1749023
   Bigger P, 2020, ENVIRON PLAN E-NAT, V3, P601, DOI 10.1177/2514848619876539
   Broto VC, 2017, WORLD DEV, V93, P1, DOI 10.1016/j.worlddev.2016.12.031
   Butler C, 2011, ENVIRON PLANN C, V29, P533, DOI 10.1068/c09181j
   C40 Cities, 2016, Climate change adaptation in Delta cities. Good Practice Guide
   Carroll Patrick., 2006, Science, Culture, and Modern State Formation, DOI 10.1525/california/9780520247536.001.0001
   Çayli E, 2021, ANTIPODE, V53, P1377, DOI 10.1111/anti.12723
   Cities, 2022, How to adapt your city to sea level rise and coastal flooding
   CIWEM, Shanghai's urban drainage masterplan
   Clarke L.B., 1999, Mission improbable
   Coastal Risk Consulting, Accelerate resilience: Cutting-edge technology providing clients and customers property-cutting-edge technology providing clients and customers property-specific flood, natural hazard and climate impact risks and advisory services
   Collier SJ, 2021, ECON SOC, V50, P158, DOI 10.1080/03085147.2021.1903771
   Colven E., 2019, SOC SPACE CRITICAL G
   Colven E, 2020, CRIT ASIAN STUD, V52, P311, DOI 10.1080/14672715.2020.1793210
   Colven E, 2020, ENVIRON PLAN C-POLIT, V38, P961, DOI 10.1177/2399654420911947
   Colven E, 2017, WATER ALTERN, V10, P250
   Cox S, 2022, GEOGR J, V188, P294, DOI 10.1111/geoj.12437
   De Roeck F, 2019, GLOBAL ENVIRON CHANG, V55, P160, DOI 10.1016/j.gloenvcha.2019.02.006
   Eko Atlantic, Prime real estate and infrastructure in Africa-Eko Atlantic
   Elliott R, 2019, BRIT J SOCIOL, V70, P1067, DOI 10.1111/1468-4446.12381
   Ericson RV., 2003, Insurance as Governance
   Eriksen S, 2021, WORLD DEV, V141, DOI 10.1016/j.worlddev.2020.105383
   Eriksen SH, 2015, GLOBAL ENVIRON CHANG, V35, P523, DOI 10.1016/j.gloenvcha.2015.09.014
   Farbotko C, 2023, NAT CLIM CHANGE, V13, P750, DOI 10.1038/s41558-023-01733-1
   Farbotko C, 2022, ENVIRON SCI POLICY, V138, P182, DOI 10.1016/j.envsci.2022.10.001
   FEMA, 2022, Flood resilience for homeowners, renters & business owners
   Ferguson James., 1996, ANTIPOLITICS MACHINE
   Flyvbjerg B., 1998, RATIONALITY POWER DE
   Forsyth T, 2022, POLIT GEOGR, V98, DOI 10.1016/j.polgeo.2022.102691
   Forsyth T, 2021, GLOBALIZATIONS, V18, P966, DOI 10.1080/14747731.2020.1859766
   Foucault Michel., 2008, The History of Sexuality: The Will to Knowledge: Volume I, V1
   Goh K., 2021, FORM FLOW SPATIAL PO
   Goh K, 2023, TURNING UP THE HEAT, P222
   Goh K, 2020, URBAN STUD, V57, P2222, DOI 10.1177/0042098018807306
   Goldman Michael., 2004, EARTHLY POLITICS, P55
   Gordon C., 2009, The Foucault effect: Studies in governmentality; with two lectures by and an interview with Michel Foucault, P1
   Hajer MA, 2018, ENERGY RES SOC SCI, V44, P222, DOI 10.1016/j.erss.2018.01.013
   Harvey PennyHannah Knox., 2015, ROADS ANTHR INFRASTR
   Hasan S, 2022, WATER ALTERN, V15, P56
   Hasan S, 2021, WIRES WATER, V8, DOI 10.1002/wat2.1559
   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
   Herbeck J., 2022, Transformations of urban coastal nature(s): Meanings and paradoxes of nature-based solutions for climate adaptation in Southeast Asia in Human-Nature Interactions. eds. I. Misiune, D. Depellegrin, P61
   Hilbrandt H, 2022, INT J URBAN REGIONAL, V46, P896, DOI 10.1111/1468-2427.13106
   Hornidge AK, 2020, AM BEHAV SCI, V64, P1497, DOI 10.1177/0002764220947764
   ICLEI, 2018, Resilient cities report 2018: Tracking local progress on the resilience targets of SDG 11
   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]
   Jasanoff S., 2015, Dreamscapes of Modernity: Sociotechnical Imaginaries and the Fabrication of Power, P1, DOI [10.7208/chicago/9780226276663.001.0001, DOI 10.7208/CHICAGO/9780226276663.001.0001]
   Jasanoff S., 2013, International library of sociology, states of knowledge: The co-production of science and the social order, P1
   Jasanoff Sheila., 2004, Earthly Politics: Local and Global in Environmental Governance, P31
   Jha AK, 2012, CITIES AND FLOODING: A GUIDE TO INTEGRATED URBAN FLOOD RISK MANAGEMENT FOR THE 21ST CENTURY, P1, DOI 10.1596/978-0-8213-8866-2
   Johnson L, 2011, GLOBAL POLITICAL ECOLOGY, P185
   Kaika M, 2017, ENVIRON URBAN, V29, P89, DOI 10.1177/0956247816684763
   Keele S, 2019, CLIMATIC CHANGE, V157, P9, DOI 10.1007/s10584-019-02385-x
   Krger F., 2015, Cultures and disasters: Understanding cultural framings in disaster risk reduction
   Kundu D., 2020, Developing National Urban Policies, P13, DOI [10.1007/978-981-15-3738-75, DOI 10.1007/978-981-15-3738-75, 10.1007/978-981-15-3738-7_2, DOI 10.1007/978-981-15-3738-7_2]
   Laeni N, 2021, J ENVIRON POL PLAN, V23, P16, DOI 10.1080/1523908X.2020.1792858
   Lea D, 2022, RISK HAZARDS CRISIS, V13, P28, DOI 10.1002/rhc3.12222
   Leitner H, 2018, URBAN GEOGR, V39, P1276, DOI 10.1080/02723638.2018.1446870
   Leitner H, 2017, ROUTL LIT COMPAN, P194
   Lemke T, 2001, ECON SOC, V30, P190, DOI 10.1080/713766674
   Lovbrand E., 2014, Advances in international environmental politics, P161, DOI [10.1057/97811373389767, DOI 10.1057/97811373389767]
   Maas T., 2019, Flood risk management: Global case studies of governance, policy and communities, P69
   Machen R, 2021, T I BRIT GEOGR, V46, P555, DOI 10.1111/tran.12441
   Magnan AK, 2016, WIRES CLIM CHANGE, V7, P646, DOI 10.1002/wcc.409
   Malm A, 2013, CRIT SOCIOL, V39, P803, DOI 10.1177/0896920512437054
   McCann E, 2012, ENVIRON PLANN A, V44, P42, DOI 10.1068/a44178
   McCann E, 2011, ANN ASSOC AM GEOGR, V101, P107, DOI 10.1080/00045608.2010.520219
   Mehryar S, 2021, CLIM POLICY, V21, P133, DOI 10.1080/14693062.2020.1808439
   Miller C. A., 2013, International library of sociology, states of knowledge: The co-production of science and the social order, P46
   Miller C. A., 2001, Politics, science, and the environment, changing the atmosphere: Expert knowledge and environmental governance
   Minkman E, 2019, J ENVIRON PLANN MAN, V62, P1562, DOI 10.1080/09640568.2018.1527216
   Mitchell Timothy., 2009, Rule of Experts: Egypt, Techno-Politics, Modernity
   Nagorny-Koring NC, 2019, J ENVIRON POL PLAN, V21, P46, DOI 10.1080/1523908X.2018.1461083
   Neumann B, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0118571
   New York State Governor's Office of Storm Recovery, 2022, Living breakwaters project background and design
   Nightingale AJ, 2020, CLIM DEV, V12, P343, DOI 10.1080/17565529.2019.1624495
   Nixon R, 2011, SLOW VIOLENCE ENV PO, DOI [10.4159/harvard.9780674061194, DOI 10.4159/HARVARD.9780674061194]
   NL Platform, 2022, Water as leverage: What an integrated approach to resilient cities can do
   Nost E, 2022, GEOFORUM, V130, P23, DOI 10.1016/j.geoforum.2022.01.016
   Nyamwanza AM, 2015, ENVIRON DEV SUSTAIN, V17, P1183, DOI 10.1007/s10668-014-9599-5
   Oels A., 2005, J ENV POLICY PLANNIN, V7, P185, DOI DOI 10.1080/15239080500339661
   Ong A, 2011, STUD URBAN SOC CH, P205
   Oomen J, 2022, EUR J SOC THEORY, V25, P252, DOI 10.1177/1368431020988826
   Paprocki K., 2021, Threatening dystopias: The global politics of climate change adaptation in Bangladesh, DOI 10.7591/cornell/9781501759154.001.0001
   Paprocki K, 2022, GLOBAL ENVIRON CHANG, V73, DOI 10.1016/j.gloenvcha.2022.102487
   Paprocki K, 2019, ANTIPODE, V51, P295, DOI 10.1111/anti.12421
   Peck J, 2010, GEOFORUM, V41, P169, DOI 10.1016/j.geoforum.2010.01.002
   Ramalho J, 2019, ASIA PAC VIEWP, V60, P24, DOI 10.1111/apv.12208
   Remling E, 2023, ENVIRON PLAN C-POLIT, V41, P714, DOI 10.1177/23996544231154368
   Remling E, 2018, ENVIRON POLIT, V27, P477, DOI 10.1080/09644016.2018.1429207
   Rijkswaterstaat, Room for the Rivers
   Rose N, 2010, BRIT J SOCIOL, V61, P271, DOI 10.1111/j.1468-4446.2009.01247.x
   Rose NikolasS., 1999, POWERS FREEDOM REFRA
   Schipper ELF, 2020, ONE EARTH, V3, P409, DOI 10.1016/j.oneear.2020.09.014
   Scott James C., 1998, Seeing like a State: How Certain Schemes to Improve the Human Condition Have Failed
   Siriwardane-de Zoysa R, 2020, MAR POLICY, V112, DOI 10.1016/j.marpol.2019.103661
   Strauss BH, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/ac2e6b
   The Rockefeller Foundation, 2019, The Rockefeller Foundation launches new climate and resilience initiative; commits an initial $8 million to continue supporting global network of cities and chief resilience officers
   The Rockefeller Foundation and ARUP, 2014, City Reslience framework
   The Rockefeller Foundation The Resilience Shift SIWI and ARUP, 2019, The City water resilience approach
   Tichenor M, 2022, POLICY SOC, V41, P431, DOI 10.1093/polsoc/puac015
   van Beek L, 2022, ENVIRON SCI POLICY, V133, P193, DOI 10.1016/j.envsci.2022.03.024
   van Voorst R, 2015, ASIAN J SOC SCI, V43, P786, DOI 10.1163/15685314-04306007
   Wade M, 2019, SINGAPORE J TROP GEO, V40, P158, DOI 10.1111/sjtg.12262
   Wakefield S, 2020, ENVIRON PLAN E-NAT, V3, P761, DOI 10.1177/2514848619887461
   Wang T, 2020, FRONT ENV SCI-SWITZ, V8, DOI 10.3389/fenvs.2020.577357
   Watts MJ., 2020, The Routledge Handbook of Political Ecology, P19
   Weatherill CK, 2023, GEOFORUM, V145, DOI 10.1016/j.geoforum.2022.04.011
   Webber S, 2017, GEOFORUM, V85, P82, DOI 10.1016/j.geoforum.2017.07.009
   Wishart M., 2021, GRAY GREEN BLUE CONT
   WOOD D, 1993, SCI AM, V268, P88, DOI 10.1038/scientificamerican0593-88
   Yarina L., 2024, Places J, DOI [10.22269/240213, DOI 10.22269/240213]
   Yarina L., 2018, Places Journal, 2018, DOI DOI 10.22269/180327
   Yi T.-D., 2015, Global cities and climate change: The translocal relations of environmental governance, V3
   Zoll A., 2021, An accumulation of capital(s). The predicament of Indonesias Sinking City, P2
NR 135
TC 0
Z9 0
U1 10
U2 10
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 2673-3145
J9 FRONT POLIT SCI
JI Front. Polit. Sci.
PD JUL 24
PY 2024
VL 6
AR 1362526
DI 10.3389/fpos.2024.1362526
PG 14
WC International Relations; Political Science
WE Emerging Sources Citation Index (ESCI)
SC International Relations; Government & Law
GA A8F2P
UT WOS:001284834900001
OA Green Published
DA 2025-01-10
ER

PT J
AU Mehmood, K
   Anees, SA
   Muhammad, S
   Hussain, K
   Shahzad, F
   Liu, QJ
   Ansari, MJ
   Alharbi, SA
   Khan, WR
AF Mehmood, Kaleem
   Anees, Shoaib Ahmad
   Muhammad, Sultan
   Hussain, Khadim
   Shahzad, Fahad
   Liu, Qijing
   Ansari, Mohammad Javed
   Alharbi, Sulaiman Ali
   Khan, Waseem Razzaq
TI Analyzing vegetation health dynamics across seasons and regions through
   NDVI and climatic variables
SO SCIENTIFIC REPORTS
LA English
DT Article
DE NDVI; Climatic variability; Vegetation dynamics; Cross wavelet
   transform; Seasonal variations
AB This study assesses the relationships between vegetation dynamics and climatic variations in Pakistan from 2000 to 2023. Employing high-resolution Landsat data for Normalized Difference Vegetation Index (NDVI) assessments, integrated with climate variables from CHIRPS and ERA5 datasets, our approach leverages Google Earth Engine (GEE) for efficient processing. It combines statistical methodologies, including linear regression, Mann-Kendall trend tests, Sen's slope estimator, partial correlation, and cross wavelet transform analyses. The findings highlight significant spatial and temporal variations in NDVI, with an annual increase averaging 0.00197 per year (p < 0.0001). This positive trend is coupled with an increase in precipitation by 0.4801 mm/year (p = 0.0016). In contrast, our analysis recorded a slight decrease in temperature (- 0.01011 degrees C/year, p < 0.05) and a reduction in solar radiation (- 0.27526 W/m2/year, p < 0.05). Notably, cross-wavelet transform analysis underscored significant coherence between NDVI and climatic factors, revealing periods of synchronized fluctuations and distinct lagged relationships. This analysis particularly highlighted precipitation as a primary driver of vegetation growth, illustrating its crucial impact across various Pakistani regions. Moreover, the analysis revealed distinct seasonal patterns, indicating that vegetation health is most responsive during the monsoon season, correlating strongly with peaks in seasonal precipitation. Our investigation has revealed Pakistan's complex association between vegetation health and climatic factors, which varies across different regions. Through cross-wavelet analysis, we have identified distinct coherence and phase relationships that highlight the critical influence of climatic drivers on vegetation patterns. These insights are crucial for developing regional climate adaptation strategies and informing sustainable agricultural and environmental management practices in the face of ongoing climatic changes.
C1 [Mehmood, Kaleem; Hussain, Khadim; Liu, Qijing] Beijing Forestry Univ, Coll Forestry, Beijing 100083, Peoples R China.
   [Mehmood, Kaleem; Liu, Qijing] Beijing Forestry Univ, Key Lab Silviculture & Conservat, Minist Educ, Beijing 100083, Peoples R China.
   [Mehmood, Kaleem; Muhammad, Sultan] Univ Swat, Inst Forest Sci, Main Campus Charbagh, Swat 19120, Pakistan.
   [Anees, Shoaib Ahmad] Univ Agr, Dept Forestry, Dera Ismail Khan 29050, Pakistan.
   [Hussain, Khadim] Beijing Forestry Univ, State Forestry & Grassland Adm Key Lab Forest Reso, Beijing 100083, Peoples R China.
   [Shahzad, Fahad] Beijing Forestry Univ, Precis Forestry Key Lab Beijing, Beijing 100083, Peoples R China.
   [Ansari, Mohammad Javed] Mahatma Jyotiba Phule Rohilkhand Univ Bareilly, Hindu Coll Moradabad, Dept Bot, Moradabad 244001, India.
   [Alharbi, Sulaiman Ali] King Saud Univ, Dept Bot & Microbiol, Coll Sci, POB 2455, Riyadh 11451, Saudi Arabia.
   [Khan, Waseem Razzaq] Univ Putra Malaysia, Fac Forestry & Environm, Dept Forestry Sci & Biodivers, Serdang 43400, Malaysia.
   [Khan, Waseem Razzaq] Univ Trieste, Natl Inst Oceanog & Appl Geophys OGS, Adv Master Sustainable Blue Econ, I-34127 Trieste, Italy.
   [Khan, Waseem Razzaq] Univ Putra Malaysia, Inst Ekosains Borneo IEB, Bintulu Campus, Sarawak 97008, Malaysia.
C3 Beijing Forestry University; Beijing Forestry University; Beijing
   Forestry University; Beijing Forestry University; Mahatma Jyotiba Phule
   Rohilkhand University; King Saud University; Universiti Putra Malaysia;
   Istituto Nazionale di Oceanografia e di Geofisica Sperimentale;
   University of Trieste; Universiti Putra Malaysia
RP Liu, QJ (corresponding author), Beijing Forestry Univ, Coll Forestry, Beijing 100083, Peoples R China.; Liu, QJ (corresponding author), Beijing Forestry Univ, Key Lab Silviculture & Conservat, Minist Educ, Beijing 100083, Peoples R China.; Khan, WR (corresponding author), Univ Putra Malaysia, Fac Forestry & Environm, Dept Forestry Sci & Biodivers, Serdang 43400, Malaysia.; Khan, WR (corresponding author), Univ Trieste, Natl Inst Oceanog & Appl Geophys OGS, Adv Master Sustainable Blue Econ, I-34127 Trieste, Italy.; Khan, WR (corresponding author), Univ Putra Malaysia, Inst Ekosains Borneo IEB, Bintulu Campus, Sarawak 97008, Malaysia.
EM liuqijing@bjfu.edu.cn; khanwaseem@upm.edu.my
RI Anees, Shoaib/IRZ-7249-2023; Mehmood, Kaleem/GXZ-9880-2022; Khan,
   Waseem/AAV-7518-2020
OI Mehmood, Kaleem/0000-0002-7996-8684; Khan, Waseem/0000-0002-5981-2105
FU Universiti Putra Malaysia [9750500]
FX This research was funded by Universiti Putra Malaysia, Vote No. 9750500.
CR Abbas Z, 2021, PAK J BOT, V53, P1865, DOI 10.30848/PJB2021-5(43)
   Abramovich F, 2000, J ROY STAT SOC D-STA, V49, P1, DOI 10.1111/1467-9884.00216
   Ahmed K, 2016, STOCH ENV RES RISK A, V30, P747, DOI 10.1007/s00477-015-1117-2
   Akram M, 2022, FORESTS, V13, DOI 10.3390/f13081158
   Ali K., 2019, WATER-SUI, V11, P1855, DOI [DOI 10.3390/w11091855, 10.3390/w11091855]
   Amber S., 2014, Sci. J. Publ. Health, V2, P144
   Anees SA, 2022, J KING SAUD UNIV SCI, V34, DOI 10.1016/j.jksus.2022.102217
   Anees SA, 2022, J KING SAUD UNIV SCI, V34, DOI 10.1016/j.jksus.2022.101848
   Arouxet M. B., 2021, SEMA SIMAI Springer Series, V4
   Ashraf U., 2019, Econ Polit Wkly, P54
   Aslam MS, 2022, ENVIRON SCI POLLUT R, V29, P10091, DOI 10.1007/s11356-021-16161-x
   Au KN, 2023, GEOCARTO INT, V38, DOI 10.1080/10106049.2023.2229773
   Badshah MT, 2024, FRONT FOR GLOB CHANG, V7, DOI 10.3389/ffgc.2024.1345047
   Chen XX, 2023, REMOTE SENS-BASEL, V15, DOI 10.3390/rs15092388
   Chen ZT, 2023, LAND-BASEL, V12, DOI 10.3390/land12061223
   Cheng L.N., 2022, J. Remote Sens, V26, P348, DOI [10.11834/jrs.20211311, DOI 10.11834/JRS.20211311]
   Cherif I, 2023, REMOTE SENS-BASEL, V15, DOI 10.3390/rs15071766
   Chu HS, 2019, SCI TOTAL ENVIRON, V650, P2051, DOI 10.1016/j.scitotenv.2018.09.115
   de Moraes TJ, 2022, REV BRAS CIENC AMBIE, V57, P125, DOI 10.5327/Z217694781132
   Deng MS, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14143337
   Funk C, 2015, SCI DATA, V2, DOI 10.1038/sdata.2015.66
   Ghaderpour E, 2023, INT J APPL EARTH OBS, V118, DOI 10.1016/j.jag.2023.103241
   Godoy MRV, 2023, ENVIRON MODELL SOFTW, V165, DOI 10.1016/j.envsoft.2023.105711
   Grinsted A, 2004, NONLINEAR PROC GEOPH, V11, P561, DOI 10.5194/npg-11-561-2004
   Guo TT, 2022, IEEE ACCESS, V10, P58869, DOI 10.1109/ACCESS.2022.3179517
   He YH, 2012, CAN GEOGR-GEOGR CAN, V56, P492, DOI 10.1111/j.1541-0064.2012.00441.x
   Hersbach H, 2020, Q J ROY METEOR SOC, V146, P1999, DOI 10.1002/qj.3803
   Hill MJ, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12030406
   Hoell A, 2015, J CLIMATE, V28, P1511, DOI 10.1175/JCLI-D-14-00344.1
   Hu YG, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su15043572
   Huang DW, 2021, IJST-T CIV ENG, V45, P2779, DOI 10.1007/s40996-020-00575-7
   Huang J, 2022, PLANT SOIL, V475, P193, DOI 10.1007/s11104-021-05054-0
   Huang LT, 2023, FORESTS, V14, DOI 10.3390/f14030614
   Huang TC, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13122345
   Hussain S, 2020, ENVIRON SCI POLLUT R, V27, P39676, DOI 10.1007/s11356-019-06072-3
   Iftikhar S., 2019, Trends of Environmental Forensics in Pakistan
   Iqbal MF, 2018, THEOR APPL CLIMATOL, V134, P613, DOI 10.1007/s00704-017-2296-1
   Jun W, 2020, J BUS ECON MANAG, V21, P1185, DOI 10.3846/jbem.2020.12050
   Justice CO, 2002, REMOTE SENS ENVIRON, V83, P244, DOI 10.1016/S0034-4257(02)00076-7
   Khan WR, 2024, FORESTS, V15, DOI 10.3390/f15050747
   Kharl S., 2017, Sci. Int., V29, P841
   Kocaaslan S, 2021, IEEE ACCESS, V9, P125032, DOI 10.1109/ACCESS.2021.3110816
   Komorowski D, 2016, J MED SYST, V40, DOI 10.1007/s10916-015-0358-4
   Kwan C, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12233880
   Le HT, 2020, APPL SCI-BASEL, V10, DOI 10.3390/app10124058
   Lee HK, 2019, ENTROPY-SWITZ, V21, DOI 10.3390/e21121199
   Li CX, 2023, REMOTE SENS-BASEL, V15, DOI 10.3390/rs15122965
   Li Feilong, 2023, CAAI Transactions on Intelligent Systems, P496, DOI 10.11992/tis.202204020
   Liu XJ, 2023, REMOTE SENS ENVIRON, V284, DOI 10.1016/j.rse.2022.113341
   Liu Y, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/abb32f
   Martínez B, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14061310
   Martínez B, 2009, REMOTE SENS ENVIRON, V113, P1823, DOI 10.1016/j.rse.2009.04.016
   Mbatha N, 2018, CLIMATE, V6, DOI 10.3390/cli6040095
   Mehmood K, 2024, J FORESTRY RES, V35, DOI 10.1007/s11676-024-01734-6
   Mehmood K, 2024, TREES FOREST PEOPLE, V16, DOI 10.1016/j.tfp.2024.100521
   Mehmood K, 2024, ECOL INFORM, V80, DOI 10.1016/j.ecoinf.2024.102532
   Munoz Sabater J., 2019, Earth Syst Sci Data, V55, P5679
   Muñoz-Sabater J, 2021, EARTH SYST SCI DATA, V13, P4349, DOI 10.5194/essd-13-4349-2021
   Nadeem AA, 2023, REMOTE SENS-BASEL, V15, DOI 10.3390/rs15030812
   Ndayisaba F., 2017, Journal of Environmental Protection, V8, P464, DOI 10.4236/jep.2017.84033
   Pan SA, 2024, ECOL INDIC, V159, DOI 10.1016/j.ecolind.2024.111636
   Pan S, 2023, FORESTS, V14, DOI 10.3390/f14071438
   Partal T, 2006, HYDROL PROCESS, V20, P2011, DOI 10.1002/hyp.5993
   Pavliuk O, 2023, ALGORITHMS, V16, DOI 10.3390/a16020077
   Peterson P., AGU FALL M 2013
   Phiri M, 2020, GISCI REMOTE SENS, V57, P464, DOI 10.1080/15481603.2020.1733325
   Propastin P. P., 2006, Temporal responses of vegetation to climatic factors in Kazakhstan and Middle Asia temporal responses of vegetation to climatic factors in Kazakhstan and Middle Asia
   Qaisrani Zahid Naeem, 2021, Arabian Journal of Geosciences, V14, DOI 10.1007/s12517-020-06302-w
   Qasimi AB, 2022, RUSS J EARTH SCI, V22, DOI 10.2205/2022ES000812
   Quiroz R, 2011, ENVIRON MODELL SOFTW, V26, P201, DOI 10.1016/j.envsoft.2010.07.006
   Rasul G., 2012, CLIMATE CHANGE PAKIS
   Ren ZP, 2023, AGRONOMY-BASEL, V13, DOI 10.3390/agronomy13092296
   Rokni K, 2019, CATENA, V178, P59, DOI 10.1016/j.catena.2019.03.007
   Rosch A., 2014, WaveletComp: A guided tour through the R-package
   S A.S, 2011, Assessment of Forest Cover Decline in Pakistan: A GIS Perspective, V2
   Schmidbauer H., 2018, Comput Human Behav, P81
   Sebastian D. E., 2019, REMOTE SENS-BASEL, V11, DOI [10.3390/rs11222703, DOI 10.3390/rs11222703]
   Shekede MD, 2023, WATER SA, V49, P46, DOI 10.17159/wsa/2023.v49.i1.3950
   Shobairi SOR, 2022, CROAT J FOR ENG, V43, P457, DOI 10.5552/crojfe.2022.1340
   Sohail M., 2023, Tourism, Threat, and Opportunities for the Forest Resources: A Case Study of Gabin Jabaa, V3
   Souza UBD, 2022, DIGIT SIGNAL PROCESS, V120, DOI 10.1016/j.dsp.2021.103292
   Sultan Muhammad P., 2023, Assessment of Regeneration Response of Silver Fir (Abies Pindrow) to Slope, Aspect, and Altitude in Miandam Area in District Swat, V3
   Sun MM, 2023, REMOTE SENS-BASEL, V15, DOI 10.3390/rs15133353
   Sunny Agarwal A. S. Suchithra, 2021, Indian Journal of Ecology, V48, P453
   Taheri M, 2022, ENERGIES, V15, DOI 10.3390/en15041264
   Tian JQ, 2021, ISPRS J PHOTOGRAMM, V180, P29, DOI 10.1016/j.isprsjprs.2021.08.003
   Tran TV, 2021, LAND DEGRAD DEV, V32, P3507, DOI 10.1002/ldr.3934
   Tsela P, 2014, REMOTE SENS-BASEL, V6, P1275, DOI 10.3390/rs6021275
   Ullah S, 2018, ATMOS RES, V210, P1, DOI 10.1016/j.atmosres.2018.04.007
   Ullah S, 2016, J MT SCI-ENGL, V13, P1229, DOI 10.1007/s11629-015-3456-3
   Usman M, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12030580
   Usoltsev VA, 2022, APPL ECOL ENV RES, DOI 10.15666/aeer/2004_36833698
   Usoltsev VA, 2020, FORESTS, V11, DOI 10.3390/f11090906
   Usoltsev Vladimir Andreevich, 2020, Journal of Resources and Ecology, V11, P331, DOI 10.5814/j.issn.1674-764x.2020.04.001
   Velez S., 2023, J, V6, P421, DOI DOI 10.3390/J6030028
   Wang K, 2024, FUEL, V356, DOI 10.1016/j.fuel.2023.129584
   Wang M, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14215580
   Wang TY, 2023, AGR FOREST METEOROL, V341, DOI 10.1016/j.agrformet.2023.109636
   Wang YR, 2022, REMOTE SENS ENVIRON, V280, DOI 10.1016/j.rse.2022.113181
   Warren MA, 2019, REMOTE SENS ENVIRON, V225, P267, DOI 10.1016/j.rse.2019.03.018
   Weber M, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12152384
   Wei YJ, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14153803
   Wu R, 2023, REMOTE SENS-BASEL, V15, DOI 10.3390/rs15184426
   Yousafzai MT, 2022, FRONT PSYCHOL, V13, DOI 10.3389/fpsyg.2022.870555
   Zafar Z., 2020, Optics, V9, P1, DOI [10.11648/j.optics.20200901.11, DOI 10.11648/J.OPTICS.20200901.11]
   Zafar Z, 2024, EGYPT J REMOTE SENS, V27, P216, DOI 10.1016/j.ejrs.2024.03.003
   Zafar Z, 2023, PHYS GEOGR, DOI 10.1080/02723646.2023.2188633
   Zafar Z, 2023, ECOL INDIC, V146, DOI 10.1016/j.ecolind.2022.109788
   Zafar Z, 2021, WATER SUPPLY, V21, P927, DOI 10.2166/ws.2020.355
   Zeng YL, 2022, NAT REV EARTH ENV, V3, P477, DOI 10.1038/s43017-022-00298-5
   Zhang HKK, 2018, REMOTE SENS ENVIRON, V215, P482, DOI 10.1016/j.rse.2018.04.031
   Zhang J, 2022, J GEOPHYS RES-ATMOS, V127, DOI 10.1029/2021JD034959
   Zhang YJ, 2014, GLOBAL ECOL BIOGEOGR, V23, P144, DOI 10.1111/geb.12086
   Zhou JM, 2018, REMOTE SENS-BASEL, V10, DOI 10.3390/rs10081187
   Zhou YL, 2019, ENVIRON SCI TECHNOL, V53, P11960, DOI 10.1021/acs.est.9b01645
   Zhu XL, 2015, ISPRS J PHOTOGRAMM, V102, P222, DOI 10.1016/j.isprsjprs.2014.08.014
NR 116
TC 6
Z9 6
U1 9
U2 13
PU NATURE PORTFOLIO
PI BERLIN
PA HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY
SN 2045-2322
J9 SCI REP-UK
JI Sci Rep
PD MAY 23
PY 2024
VL 14
IS 1
AR 11775
DI 10.1038/s41598-024-62464-7
PG 22
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA RV7A3
UT WOS:001230489600026
PM 38783048
OA gold
DA 2025-01-10
ER

PT J
AU Torquato, PR
   Hahs, AK
   Szota, C
   Arndt, SK
   Sun, Q
   Hurley, J
   Livesley, SJ
AF Torquato, Patricia Rettondini
   Hahs, Amy K.
   Szota, Christopher
   Arndt, Stefan K.
   Sun, Qian (Chayn)
   Hurley, Joe
   Livesley, Stephen J.
TI Spatially analysed expansion of individual street tree crowns enables
   species-specific crown expansion predictions in different rainfall zones
SO URBAN FORESTRY & URBAN GREENING
LA English
DT Article
DE Urban forest; Tree species selection; Canopy cover; Tree inventory
ID STORMWATER CONTROL MEASURES; URBAN FOREST; DROUGHT RESISTANCE; ECOSYSTEM
   SERVICES; COVER CHANGE; GROWTH; CLIMATE; PHILADELPHIA; STRATEGIES;
   MORPHOLOGY
AB Many cities are developing ambitious future canopy cover targets in recognition of urban trees' numerous benefits. Selecting fast-growing and climate-adapted tree species is important to help achieve these targets. The assessment of growth performance of tree species is challenging, but essential for selecting species that grow in different environments. Often, remote sensing is used to measure canopy cover change at a landscape or neighbourhood scale in urban forests, but rarely at individual tree or species scales. In this study, we developed a novel spatial analysis method combining remotely sensed canopy cover mapping with georeferenced urban tree inventory data to identify individual tree crowns and measure crown expansion rates. We developed speciesspecific models of crown expansion rates for 20 most common street tree species growing in two rainfall zones (478-665 mm). Predicted crown areas at 10 years after planting ranged from 6.6 m2 to 43.7 m2. The species showed four different crown expansion responses at 10 years after planting: Fast and consistent growth; Fast but sensitive growth; Slow and consistent growth; Slow and sensitive growth. This study demonstrates a simple, but robust method to delineateindividual tree crowns that can be used to develop species-specific crown expansion models. It also shows the importance of developing species specific crown expansion models in different rainfall zones, as some tree species were clearly sensitive to rainfall differences. Using this spatial analysis method, urban forest managers can make informed decisions regarding tree species selection, considering rainfall zone specific environmental growth conditions, as well as space constraints and water availability.
C1 [Torquato, Patricia Rettondini; Hahs, Amy K.; Szota, Christopher; Arndt, Stefan K.; Livesley, Stephen J.] Univ Melbourne, Sch Agr Food & Ecosyst Sci, Burnley Campus,500 Yarra Blvd, Melbourne, Vic 3121, Australia.
   [Sun, Qian (Chayn)] RMIT Univ, Sch Sci, Melbourne, Vic, Australia.
   [Hurley, Joe] RMIT Univ, Sch Global Urban & Social Studies, Melbourne, Australia.
   [Torquato, Patricia Rettondini] 500 Yarra Blvd, Melbourne, Vic 3121, Australia.
C3 University of Melbourne; Royal Melbourne Institute of Technology (RMIT);
   Royal Melbourne Institute of Technology (RMIT)
RP Torquato, PR (corresponding author), 500 Yarra Blvd, Melbourne, Vic 3121, Australia.
EM ptorquato@unimelb.edu.au
RI Sun, Qian (Chayn)/H-9058-2019; Hurley, Joe/LFT-2730-2024; Arndt,
   Stefan/G-5021-2013; Livesley, Stephen/L-4731-2019
OI Hurley, Joe/0000-0003-4232-0902; Sun, Qian/0000-0002-5421-5838
FU Frank Keenan and Madeleine Selwyn-Smith Memorial Fund
FX This research was supported by Frank Keenan and Madeleine Selwyn-Smith
   Memorial Fund research scholarships, for which we are grateful. We
   kindly acknowledge the Urban Forest Planner from the City of Wyndham and
   the Unit Leader Parks and Urban Forest from the City of Whittlesea for
   providing the urban tree inventories spatial data.
CR Alonzo M, 2014, REMOTE SENS ENVIRON, V148, P70, DOI 10.1016/j.rse.2014.03.018
   Australian Building Codes Board (ABCB), 2023, about us
   Avolio ML, 2015, FRONT ECOL EVOL, V3, DOI 10.3389/fevo.2015.00073
   Berland A, 2020, URBAN ECOSYST, V23, P1253, DOI 10.1007/s11252-020-01015-0
   Bijoor NS, 2012, URBAN ECOSYST, V15, P195, DOI 10.1007/s11252-011-0196-1
   Butt N, 2018, GEO-GEOGR ENVIRON, V5, DOI 10.1002/geo2.52
   Caccetta P, 2016, INT J DIGIT EARTH, V9, DOI 10.1080/17538947.2015.1046510
   Chaturvedi RK, 2021, FOREST ECOL MANAG, V482, DOI 10.1016/j.foreco.2020.118740
   Conway TM, 2015, LANDSCAPE URBAN PLAN, V138, P1, DOI 10.1016/j.landurbplan.2015.01.007
   Dahlhausen J, 2018, INT J BIOMETEOROL, V62, P795, DOI 10.1007/s00484-017-1481-3
   Doick K.J., 2017, URBAN TREES RES C
   Erker T, 2019, REMOTE SENS ENVIRON, V229, P148, DOI 10.1016/j.rse.2019.03.037
   Parmehr EG, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13112062
   Gillner S, 2014, TREES-STRUCT FUNCT, V28, P1079, DOI 10.1007/s00468-014-1019-9
   Google Earth Pro, 2022, 2022 Google LLC. Version 7.3.4.8 248
   Grey V, 2018, LANDSCAPE URBAN PLAN, V178, P122, DOI 10.1016/j.landurbplan.2018.06.002
   GULLO MAL, 1988, NEW PHYTOL, V108, P267, DOI 10.1111/j.1469-8137.1988.tb04162.x
   Haaland C, 2015, URBAN FOR URBAN GREE, V14, P760, DOI 10.1016/j.ufug.2015.07.009
   Hanley PA, 2021, SCI TOTAL ENVIRON, V753, DOI 10.1016/j.scitotenv.2020.142012
   Hartigan M, 2021, LAND-BASEL, V10, DOI 10.3390/land10080809
   Huynh T, 2022, FORESTS, V13, DOI 10.3390/f13030486
   Kondo MC, 2020, LANCET PLANET HEALTH, V4, pE149, DOI 10.1016/S2542-5196(20)30058-9
   Livesley SJ, 2016, J ENVIRON QUAL, V45, P119, DOI 10.2134/jeq2015.11.0567
   Markesteijn L, 2009, J ECOL, V97, P311, DOI 10.1111/j.1365-2745.2008.01466.x
   McPherson E. G., 2016, General Technical Report - Pacific Southwest Research Station, USDA Forest Service
   Merry K, 2014, CITIES, V41, P123, DOI 10.1016/j.cities.2014.06.012
   Miller DL, 2020, REMOTE SENS ENVIRON, V240, DOI 10.1016/j.rse.2020.111646
   Nearmap, 2022, High resolution imagery
   Nitschke CR, 2017, LANDSCAPE URBAN PLAN, V167, P275, DOI 10.1016/j.landurbplan.2017.06.012
   NOAA, 2023, About us
   Nowak D.J., 2000, HDB URBAN COMMUNITY, P11
   Nowak DJ, 2012, URBAN FOR URBAN GREE, V11, P21, DOI 10.1016/j.ufug.2011.11.005
   Nowak David J., 2008, Arboriculture & Urban Forestry, V34, P347
   Ossola A, 2020, GLOBAL ECOL BIOGEOGR, V29, P1907, DOI 10.1111/geb.13169
   Paquette A, 2021, URBAN FOR URBAN GREE, V62, DOI 10.1016/j.ufug.2021.127157
   Parmehr EG, 2016, URBAN FOR URBAN GREE, V20, P160, DOI 10.1016/j.ufug.2016.08.011
   Pataki DE, 2011, ECOHYDROLOGY, V4, P341, DOI 10.1002/eco.209
   Pfautsch S, 2016, ECOL LETT, V19, P240, DOI 10.1111/ele.12559
   Pretzsch H, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-14831-w
   Pretzsch H, 2015, URBAN FOR URBAN GREE, V14, P466, DOI 10.1016/j.ufug.2015.04.006
   Pritzkow C, 2021, TREE PHYSIOL, V41, P1186, DOI 10.1093/treephys/tpaa176
   Rahman MA, 2011, URBAN FOR URBAN GREE, V10, P185, DOI 10.1016/j.ufug.2011.05.003
   Rötzer T, 2019, SCI TOTAL ENVIRON, V676, P651, DOI 10.1016/j.scitotenv.2019.04.235
   Roloff A, 2009, URBAN FOR URBAN GREE, V8, P295, DOI 10.1016/j.ufug.2009.08.002
   Roman LA, 2011, URBAN FOR URBAN GREE, V10, P269, DOI 10.1016/j.ufug.2011.05.008
   Rotzer T., 2021, Progress in Botany, V82, P405, DOI [DOI 10.1007/124_2020_46, DOI 10.1007/124202046]
   Sanders JR, 2014, URBAN FOR URBAN GREE, V13, P295, DOI 10.1016/j.ufug.2013.12.006
   Saunders P., 2019, REVISITING HENDERSON
   Sjöman H, 2018, URBAN ECOSYST, V21, P1171, DOI 10.1007/s11252-018-0791-5
   Staas L., 2017, 18 NATL STREET TREE, V17, P41
   Stewart S., 2017, Climate Victoria: Maximum Temperature (3DS-M; 9 second, approx. 250 m). v4, DOI [10.25919/5-5d9033d8cc7, DOI 10.25919/5-5D9033D8CC7]
   Stewart S., 2018, Climate Victoria: Minimum Temperature (3DS-TM; 9 second, approx. 250 m). v4, DOI [10.25919/5-5dc18621a12, DOI 10.25919/5-5DC18621A12]
   Stewart S., 2020, Climate Victoria: Precipitation (9 second, approx. 250 m). v3, DOI [10.25919/5-3be5193e301, DOI 10.25919/5-3BE5193E301]
   Szota C, 2019, LANDSCAPE URBAN PLAN, V182, P144, DOI 10.1016/j.landurbplan.2018.10.021
   Tyrvainen L., 2005, URBAN FORESTS TREES, P81
   Ucar Z, 2018, URBAN FOR URBAN GREE, V29, P248, DOI 10.1016/j.ufug.2017.12.001
   Urban J., 2010, Folia Oecologica, V37, P103
   Varol T, 2019, ENVIRON MONIT ASSESS, V191, DOI 10.1007/s10661-019-7299-1
   Wallace L, 2021, URBAN FOR URBAN GREE, V61, DOI 10.1016/j.ufug.2021.127106
   Warren RA, 2021, Q J ROY METEOR SOC, V147, P3201, DOI 10.1002/qj.4124
   White DA, 2000, TREE PHYSIOL, V20, P1157
   Wolf KL, 2020, INT J ENV RES PUB HE, V17, DOI 10.3390/ijerph17124371
   Zhang CY, 2015, REMOTE SENS-BASEL, V7, P7892, DOI 10.3390/rs70607892
   Ziter CD, 2019, P NATL ACAD SCI USA, V116, P7575, DOI 10.1073/pnas.1817561116
NR 64
TC 0
Z9 0
U1 3
U2 6
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 APR
PY 2024
VL 94
AR 128268
DI 10.1016/j.ufug.2024.128268
EA MAR 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 OU0L7
UT WOS:001209676400001
OA hybrid
DA 2025-01-10
ER

PT J
AU Turek, ME
   Nemes, A
   Holzkämper, A
AF Turek, Maria Eliza
   Nemes, Attila
   Holzkamper, Annelie
TI Sequestering carbon in the subsoil benefits crop transpiration at the
   onset of drought
SO SOIL
LA English
DT Article
ID SOIL ORGANIC-MATTER; HYDRAULIC CONDUCTIVITY; PEDOTRANSFER FUNCTIONS;
   GRAIN MAIZE; SANDY LOAM; MODEL; LIMITATIONS; POTENTIALS; AMENDMENTS;
   TILLAGE
AB Increasing soil organic carbon is promoted as a negative emission technology for the agricultural sector with a potential co-benefit for climate adaptation due to increased soil water retention. Field-scale hydrological models are powerful tools for evaluating how the agricultural systems would respond to the changing climate in upcoming years and decades, for predicting impacts, and for looking for measures that would help decrease drought-driven crop stress under current and future climatic conditions. We quantified how different levels of soil organic carbon (SOC) additions at varied soil depths are expected to influence drought-induced transpiration reduction (Tred dry ) in maize cultivated in Switzerland. Parameterization of the model based on a pedotransfer function (PTF) was validated against soil moisture data from a long-term lysimeter experiment with a typical Swiss soil, and the model was subsequently applied under climate forcing between 1981 until 2099, representative of three distinct climatic sites of Switzerland. We used the same PTF to indirectly assess the effects of SOC additions at different depths on soil hydraulic properties. We found a threshold in both the added amount of SOC (2 % added) and the depth of sequestering that SOC (top 65 cm), beyond which any additional benefit appears to be substantially reduced. However, adding at least 2 % SOC down to at least 65 cm depth can reduce Tred dry in maize, i.e. increase transpiration annually but mostly at the onset of summer drought, by almost 40 mm. We argue that SOC increases in subsoils can play a supporting role in mitigating drought impacts in rain-fed cropping in Switzerland.
C1 [Turek, Maria Eliza; Holzkamper, Annelie] Div Agroecol & Environm, Agroscope, Zurich, Switzerland.
   [Turek, Maria Eliza; Holzkamper, Annelie] Univ Bern, Oeschger Ctr Climate Change Res, Bern, Switzerland.
   [Nemes, Attila] Norwegian Univ Life Sci, Fac Environm & Nat Resource Management, As, Norway.
   [Nemes, Attila] Norwegian Inst Bioecon Res NIBIO, Div Environm & Nat Resources, As, Norway.
C3 Swiss Federal Research Station Agroscope; University of Bern; Norwegian
   University of Life Sciences; Norwegian Institute of Bioeconomy Research
RP Turek, ME (corresponding author), Div Agroecol & Environm, Agroscope, Zurich, Switzerland.; Turek, ME (corresponding author), Univ Bern, Oeschger Ctr Climate Change Res, Bern, Switzerland.
EM mariaeliza.turek@agroscope.admin.ch
OI Holzkamper, Annelie/0000-0002-1951-1041
FU Horizon 2020 Framework Programme [862756]; European Union [862695];
   European Joint Program for SOIL "Towards climate-smart sustainable
   management of agricultural soils" - European Union
FX This project was developed in the framework of the OPTAIN and SoilX-EJP
   SOIL projects. OPTAIN (OPtimal strategies to retAIN and re-use water and
   nutrients in small agricultural catchments across different
   soil-climatic regions in Europe, https://cordis.europa.eu, last access:
   1 November 2023) has received funding from the European Union's Horizon
   2020 research and innovation programme (grant agreement no. 862756).
   SoilX is part of the European Joint Program for SOIL "Towards
   climate-smart sustainable management of agricultural soils" (EJP SOIL)
   funded by the European Union Horizon 2020 research and innovation
   programme (grant agreement no. 862695). The authors thank Volker Prasuhn
   for providing full assistance with the lysimeter data.
CR Alcántara V, 2016, GLOBAL CHANGE BIOL, V22, P2939, DOI 10.1111/gcb.13289
   Angers DA, 2008, SOIL SCI SOC AM J, V72, P1370, DOI 10.2136/sssaj2007.0342
   Ankenbauer KJ, 2017, HYDROL PROCESS, V31, P891, DOI 10.1002/hyp.11070
   [Anonymous], 2023, Agroscope: Sortenversuche - Resultate Mais
   Arthur E, 2015, GEODERMA, V243, P175, DOI 10.1016/j.geoderma.2015.01.001
   BAFU, 2016, Hitze und Trockenheit im Sommer 2015, Auswirkungen auf Mensch und Umwelt
   BAFU, 2019, Hitze und Trockenheit im Sommer 2018
   Bai XX, 2019, GLOBAL CHANGE BIOL, V25, P2591, DOI 10.1111/gcb.14658
   Blanchy G, 2023, SOIL-GERMANY, V9, DOI 10.5194/soil-9-1-2023
   Bonfante A, 2020, GEODERMA, V361, DOI 10.1016/j.geoderma.2019.114079
   Bonfante A, 2019, SOIL-GERMANY, V5, P1, DOI 10.5194/soil-5-1-2019
   Caplan JS, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aau6635
   Carter MR, 2010, AGR ECOSYST ENVIRON, V136, P125, DOI 10.1016/j.agee.2009.12.005
   CH2018, 2018, CH2018 Climate Scenarios for Switzerland, Technical Report, DOI DOI 10.18751/CLIMATE/SCENARIOS/CH2018/1.0
   Coban O, 2022, SCIENCE, V375, P990, DOI 10.1126/science.abe0725
   Crystal-Ornelas R, 2021, AGR ECOSYST ENVIRON, V312, DOI 10.1016/j.agee.2021.107356
   de Wit A, 2019, AGR SYST, V168, P154, DOI 10.1016/j.agsy.2018.06.018
   Edeh IG, 2020, SCI TOTAL ENVIRON, V714, DOI 10.1016/j.scitotenv.2020.136857
   Eden M, 2017, AGRON SUSTAIN DEV, V37, DOI 10.1007/s13593-017-0419-9
   Fatichi S, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-14411-z
   Feng PY, 2022, AGRON SUSTAIN DEV, V42, DOI 10.1007/s13593-022-00818-z
   Food and Agriculture Organization of the United Nations, 2015, WORLD REF BAS SOIL R
   Guillaume T, 2022, GEODERMA, V406, DOI 10.1016/j.geoderma.2021.115529
   Guillaume T, 2021, AGR ECOSYST ENVIRON, V305, DOI 10.1016/j.agee.2020.107184
   Hartge K. H., 1980, Z. Pflanzenernaehr. Bodenk., V143, P254, DOI [10.1002/jpln.19801430219, DOI 10.1002/JPLN.19801430219]
   Holzkämper A, 2015, AGR FOREST METEOROL, V214, P219, DOI 10.1016/j.agrformet.2015.08.263
   Holzkämper A, 2020, AGR WATER MANAGE, V237, DOI 10.1016/j.agwat.2020.106202
   Holzkämper A, 2015, REG ENVIRON CHANGE, V15, P109, DOI 10.1007/s10113-014-0627-7
   Holzkämper A, 2013, AGR FOREST METEOROL, V168, P149, DOI 10.1016/j.agrformet.2012.09.004
   Jarvis N, 2013, HYDROL EARTH SYST SC, V17, P5185, DOI 10.5194/hess-17-5185-2013
   Kallenbach C, 2011, AGR ECOSYST ENVIRON, V144, P241, DOI 10.1016/j.agee.2011.08.020
   Kan ZR, 2020, CATENA, V188, DOI 10.1016/j.catena.2019.104428
   Krauss M, 2022, SOIL TILL RES, V216, DOI 10.1016/j.still.2021.105262
   Kroes J.G., 2008, SWAP VERSION 32 THEO
   Lal R, 2004, GEODERMA, V123, P1, DOI 10.1016/j.geoderma.2004.01.032
   Lal R, 2001, ADV AGRON, V71, P145, DOI 10.1016/S0065-2113(01)71014-0
   Larsbo M, 2016, VADOSE ZONE J, V15, DOI 10.2136/vzj2016.03.0021
   Libohova Z, 2018, J SOIL WATER CONSERV, V73, P411, DOI 10.2489/jswc.73.4.411
   Liu SN, 2021, ENVIRON SCI POLLUT R, V28, P2995, DOI 10.1007/s11356-020-10712-4
   Lu JR, 2020, J HYDROL, V589, DOI 10.1016/j.jhydrol.2020.125203
   Maharjan GR, 2018, SOIL TILL RES, V180, P210, DOI 10.1016/j.still.2018.03.009
   Meurer K. H. E., Glob. Change Biol.
   Meurer KHE, 2020, BIOGEOSCIENCES, V17, P5025, DOI 10.5194/bg-17-5025-2020
   Minasny B, 2018, EUR J SOIL SCI, V69, P39, DOI 10.1111/ejss.12475
   Minasny B, 2017, GEODERMA, V292, P59, DOI 10.1016/j.geoderma.2017.01.002
   Modak K, 2019, SOIL TILL RES, V195, DOI 10.1016/j.still.2019.104370
   MUALEM Y, 1976, WATER RESOUR RES, V12, P513, DOI 10.1029/WR012i003p00513
   Murphy B, 2015, IOP C SER EARTH ENV, V25, DOI 10.1088/1755-1315/25/1/012008
   Nasta P, 2021, J HYDROL-REG STUD, V37, DOI 10.1016/j.ejrh.2021.100903
   Nemes A, 2005, SOIL SCI SOC AM J, V69, P1330, DOI 10.2136/sssaj2004.0055
   Prasuhn V., 2016, NAS INT WORKSH APPL, P1
   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]
   Rawls WJ, 2004, DEV SOIL SCI, V30, P95, DOI 10.1016/S0166-2481(04)30006-1
   Renwick LLR, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/ac1468
   Rivier PA, 2022, J HYDROL HYDROMECH, V70, P74, DOI 10.2478/johh-2022-0004
   Smith P, 2008, PHILOS T R SOC B, V363, P789, DOI 10.1098/rstb.2007.2184
   Szabó B, 2021, GEOSCI MODEL DEV, V14, P151, DOI 10.5194/gmd-14-151-2021
   Topa D, 2021, CATENA, V199, DOI 10.1016/j.catena.2020.105102
   Turek Maria Eliza, 2023, Zenodo, DOI 10.5281/ZENODO.10068907
   University of Wageningen, SWAP Soil Water Atmosphere Plant
   Van Looy K, 2017, REV GEOPHYS, V55, P1199, DOI 10.1002/2017RG000581
   VANGENUCHTEN MT, 1980, SOIL SCI SOC AM J, V44, P892, DOI 10.2136/sssaj1980.03615995004400050002x
   Wagner B, 2004, J PLANT NUTR SOIL SC, V167, P236, DOI 10.1002/jpln.200321251
   Wang T, 2009, WATER RESOUR RES, V45, DOI 10.1029/2008WR006865
   Weber Tobias KD, 2020, Zenodo, DOI 10.5281/ZENODO.4281045
   Zhang XY, 2021, SOIL BIOL BIOCHEM, V156, DOI 10.1016/j.soilbio.2021.108213
NR 66
TC 0
Z9 0
U1 2
U2 6
PU COPERNICUS GESELLSCHAFT MBH
PI GOTTINGEN
PA BAHNHOFSALLEE 1E, GOTTINGEN, 37081, GERMANY
SN 2199-3971
EI 2199-398X
J9 SOIL-GERMANY
JI Soil
PD NOV 9
PY 2023
VL 9
IS 2
BP 545
EP 560
DI 10.5194/soil-9-545-2023
PG 16
WC Soil Science
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA IV3G2
UT WOS:001169066300001
OA gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Gabbe, CJ
   Chang, JS
   Kamson, M
   Seo, E
AF Gabbe, C. J.
   Chang, Jamie Suki
   Kamson, Morayo
   Seo, Euichan
TI Reducing heat risk for people experiencing unsheltered homelessness
SO INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
LA English
DT Article
DE Extreme heat; Urban heat island; Heat health; Climate adaptation;
   Homelessness; Unhoused
ID MARICOPA COUNTY; CLIMATE-CHANGE; EXTREME HEAT; URBAN HEAT; HEALTH;
   VULNERABILITY; WEATHER
AB Planners and policymakers are increasingly interested in heat resilience, but there is little evidence about heat exposure, health risks, and adaptive strategies among people experiencing homelessness. We took a nested, mixed-methods approach. First we identified where unhoused residents in Santa Clara County were disproportionately exposed to heat, and then examined how unhoused residents in these areas coped with heat and avoided heat-related illness. In the first stage, we used descriptive and spatial analyses to identify associations between unhoused residents, tree canopy, temperature, and other neighborhood characteristics. The neighborhoods in the top quartile of unhoused residents were two percent hotter than other neighborhoods demonstrating a dimension of urban thermal inequity. In the second stage, we conducted in-depth (n = 10) and encampment-based (n = 72) interviews with unhoused people to better understand their heat-related experiences and needs. We found that unhoused participants were exposed to extreme heat, which resulted in negative health consequences. Unhoused residents favored staying in places where they had more stability and were less likely to be "swept" (relocated). But, the more stable locations tended to have less access to shade and water, thus they faced difficult trade-offs. Additionally, many unhoused participants experienced challenges accessing air-conditioned spaces, including cooling centers, due to lack of information, transportation issues, and restrictive policies. The most important strategy for reducing the unhoused population's heat risk is housing provision, and interim approaches include outdoor spaces for unhoused people designed with heat considerations in mind, and inclusive air-conditioned indoor spaces.
C1 [Gabbe, C. J.; Kamson, Morayo; Seo, Euichan] Santa Clara Univ, Dept Environm Studies & Sci, 500 El Camino Real, Santa Clara, CA 95053 USA.
   [Chang, Jamie Suki] Santa Clara Univ, Dept Publ Hlth, 500 El Camino Real, Santa Clara, CA 95053 USA.
   [Chang, Jamie Suki] Univ Calif Berkeley, Sch Social Welf, 120 Haviland Hall, Berkeley, CA 94720 USA.
C3 Santa Clara University; Santa Clara University; University of California
   System; University of California Berkeley
RP Gabbe, CJ (corresponding author), Santa Clara Univ, Dept Environm Studies & Sci, 500 El Camino Real, Santa Clara, CA 95053 USA.
EM cgabbe@scu.edu; jamiechang@berkeley.edu; mkamson@alumni.scu.edu;
   eseo@alumni.scu.edu
OI Gabbe, C.J./0000-0002-0084-580X
FU Santa Clara University Environmental Justice; Common Good Research Grant
FX This research was funded by a Santa Clara University Environmental
   Justice and the Common Good Research Grant.
CR Aaby K., 2022, Thesis
   Applied Survey Research, 2022, County of Santa Clara: Point-in-time Report on Homelessness
   Baston D., 2020, EXACTEXTRACTR FAST E
   Berger T, 2022, LAND USE POLICY, V119, DOI 10.1016/j.landusepol.2022.106192
   Berisha V, 2017, WEATHER CLIM SOC, V9, P71, DOI 10.1175/WCAS-D-16-0033.1
   Bezgrebelna M, 2021, INT J ENV RES PUB HE, V18, DOI 10.3390/ijerph18115812
   Bivand RS, 2008, USE R, P1
   Byrne T, 2013, J URBAN AFF, V35, P607, DOI 10.1111/j.1467-9906.2012.00643.x
   Chakraborty T, 2020, ISPRS J PHOTOGRAMM, V168, P74, DOI 10.1016/j.isprsjprs.2020.07.021
   City of San Jose, General Plan 2040 (Spatial Data), 2020 City of San Jose Enterprise GIS
   County of Santa Clara, 2019, Santa Clara County Homeless Census and Survey Comprehensive Report
   Cusack L, 2013, AUST J PRIM HEALTH, V19, P250, DOI 10.1071/PY12048
   Dialesandro J, 2021, INT J ENV RES PUB HE, V18, DOI 10.3390/ijerph18030941
   Ebi KL, 2021, LANCET, V398, P698, DOI 10.1016/S0140-6736(21)01208-3
   Ehrenfeucht Renia., 2014, The Informal American City: Beyond Taco Trucks and Day Labor, P155
   Evans K, 2024, J PLAN EDUC RES, V44, P938, DOI 10.1177/0739456X211041392
   Every D, 2019, DISASTERS, V43, P799, DOI 10.1111/disa.12400
   Fahy B, 2019, INT J DISAST RISK RE, V39, DOI 10.1016/j.ijdrr.2019.101117
   Fiore N., 2020, San Jose, California community encampment report
   Fischel WilliamA., 2001, HOMEVOTER HYPOTHESIS
   Gabbe CJ, 2023, HOUS POLICY DEBATE, V33, P1078, DOI 10.1080/10511482.2022.2093938
   Giamarino C, 2023, J AM PLANN ASSOC, V89, P80, DOI 10.1080/01944363.2022.2050936
   Gronlund Carina J, 2014, Curr Epidemiol Rep, V1, P165
   Hajat S., 2023, Am. J. Publ. Health, DOI [10.2105/AJPH.2023.307351,e1-e4, DOI 10.2105/AJPH.2023.307351,E1-E4]
   Hanratty M, 2017, HOUS POLICY DEBATE, V27, P640, DOI 10.1080/10511482.2017.1282885
   Harlan SL, 2013, ENVIRON HEALTH PERSP, V121, P197, DOI 10.1289/ehp.1104625
   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]
   Herring C, 2019, AM SOCIOL REV, V84, P769, DOI 10.1177/0003122419872671
   Herring C, 2014, CITY COMMUNITY, V13, P285, DOI 10.1111/cico.12086
   Homelessness, 2021, National Alliance to End, State of homelessness: 2021 edition
   Hondula DM, 2015, CURR CLIM CHANGE REP, V1, P144, DOI 10.1007/s40641-015-0016-4
   Ioannou L.G., 2022, Temperature, P1
   Jesdale BM, 2013, ENVIRON HEALTH PERSP, V121, P811, DOI 10.1289/ehp.1205919
   Kidd SA, 2023, CLIM POLICY, V23, P623, DOI 10.1080/14693062.2023.2194280
   Lakhani N., 2022, The Guardian
   Lee S., 2001, Journal of Geographical Systems, V3, P369, DOI [DOI 10.1007/S101090100064, 10.1007/s101090100064, https://doi.org/10.1007/s101090100064]
   Lieberman ES, 2005, AM POLIT SCI REV, V99, P435, DOI 10.1017/S0003055405051762
   Lin S., 2023, February 19 Los Angeles Times
   Loftus-Farren Z, 2011, CALIF LAW REV, V99, P1037
   Luber G, 2008, AM J PREV MED, V35, P429, DOI 10.1016/j.amepre.2008.08.021
   Mahadevia D, 2020, ENVIRON URBAN ASIA, V11, P29, DOI 10.1177/0975425320906249
   Mitchell BC, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/11/115005
   Mitchell BC, 2014, GEOGR REV, V104, P459, DOI 10.1111/j.1931-0846.2014.12039.x
   National Alliance to End Homelessness, 2021, State of Homelessness: 2021 Edition
   National Weather Service, 2018, Weather-Related Fatality and Injury Statistics
   Nicolay M, 2016, INT J DISAST RISK RE, V18, P72, DOI 10.1016/j.ijdrr.2016.05.009
   Putnam H, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aadb44
   Ramin B, 2009, J URBAN HEALTH, V86, P654, DOI 10.1007/s11524-009-9354-7
   Richard MK, 2024, HOUS POLICY DEBATE, V34, P3, DOI 10.1080/10511482.2021.1981976
   Sampson NR, 2013, GLOBAL ENVIRON CHANG, V23, P475, DOI 10.1016/j.gloenvcha.2012.12.011
   Samuelson H, 2020, SCI TOTAL ENVIRON, V720, DOI [10.1016/j.scitotenv.2020.137296, 10.1016/J.scitotenv.2020.137296]
   Schwarz L, 2022, AM J PUBLIC HEALTH, V112, P98, DOI 10.2105/AJPH.2021.306557
   Semborski S, 2022, HEALTH PLACE, V75, DOI 10.1016/j.healthplace.2022.102776
   Settembrino MR, 2017, NAT HAZARDS REV, V18, DOI 10.1061/(ASCE)NH.1527-6996.0000256
   Sherwood SC, 2010, P NATL ACAD SCI USA, V107, P9552, DOI 10.1073/pnas.0913352107
   Simonton T., 2022, Las Vegas Rev.-Journal June 30
   Small ML, 2011, ANNU REV SOCIOL, V37, P57, DOI 10.1146/annurev.soc.012809.102657
   Smith C, 2019, SOC CURR, V6, P91, DOI 10.1177/2329496518812451
   Snow A., 2022, AP NEWS
   State of California, 2019, Extreme Heat Days & Warm Nights
   Swope CB, 2019, SOC SCI MED, V243, DOI 10.1016/j.socscimed.2019.112571
   Sy S., 2022, PBS News Hour
   U.S. Environmental Protection Agency, 2021, CLIMATE CHANGE INDIC
   US Census Bureau, 2020, 2015-2019 American community survey 5-year estimates
   Us Epa Cdc, 2016, EPA 430-R-16-061, P1
   US Forest Service, 2018, Urban Tree Canopy in California
   VanderMolen K, 2022, INT J DISAST RISK RE, V82, DOI 10.1016/j.ijdrr.2022.103288
   Walters V, 2014, HABITAT INT, V44, P211, DOI 10.1016/j.habitatint.2014.06.006
   Weare C., 2021, Safe Parking: Insights from a Review of National Programs
   Wilson B, 2020, J AM PLANN ASSOC, V86, P443, DOI 10.1080/01944363.2020.1759127
   Zander KK, 2021, SUSTAIN CITIES SOC, V74, DOI 10.1016/j.scs.2021.103194
NR 71
TC 10
Z9 10
U1 5
U2 17
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 OCT 1
PY 2023
VL 96
AR 103904
DI 10.1016/j.ijdrr.2023.103904
EA AUG 2023
PG 17
WC Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences;
   Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology; Meteorology & Atmospheric Sciences; Water Resources
GA W0DN7
UT WOS:001088423100001
DA 2025-01-10
ER

PT J
AU Ma, L
   Huang, GA
   Johnson, BA
   Chen, ZJ
   Li, MC
   Yan, ZY
   Zhan, WF
   Lu, H
   He, WQ
   Lian, DJ
AF Ma, Lei
   Huang, Guoan
   Johnson, Brian Alan
   Chen, Zhenjie
   Li, Manchun
   Yan, Ziyun
   Zhan, Wenfeng
   Lu, Heng
   He, Weiqiang
   Lian, Dongjie
TI Investigating urban heat-related health risks based on local climate
   zones: A case study of Changzhou in China
SO SUSTAINABLE CITIES AND SOCIETY
LA English
DT Article
DE Local climate zones; Mapping; Heat-related health risk; Land surface
   temperature retrieval; Urban Heat Island effects
ID VULNERABILITY INDEX; EXTREME HEAT; TEMPERATURE; WAVE; POPULATION;
   MORTALITY; FEATURES; ISLANDS; STRESS; SCALES
AB Assessing heat-related health risks is important for sustainable urban development. Although fine-scale infor-mation (e.g., at the community/neighborhood or city block level) is ideal for identifying and mitigating these risks, previous studies have preferred to work at the administrative unit level. High-resolution Local Climate Zone (LCZ) maps, i.e., maps of urban "zones" with different microclimates, could help to standardize the analyzing units. In this study, we proposed an LCZ-based risk assessment approach for this purpose. First, an LCZ map of the study site (Changzhou, China) was generated using multisource big data and machine-learning techniques. Next, Crichton's Risk Triangle framework, based on the hazard-exposure-vulnerability risk compo-nents, was employed to estimate heat-related health risks. Finally, the relationship between LCZ types and heat -related health risk levels was quantitatively analyzed in detail. The results indicated that at least 60% of LCZ1-5 (compact high-/mid-/low-rise, open high-/mid-rise areas) were designated as high-risk areas, while heat hazard mitigation and climate adaptation strategies in urban planning would benefit more from LCZ 6 (open low-rise). This study, based on the LCZ concept, shows the risk difference at the community level, and can be used for informing and implementing area-level urban planning strategies. It could contribute to global heat-related health risk analysis, since the LCZ is a globally consistent system for urban microclimate analysis.
C1 [Ma, Lei; Huang, Guoan; Chen, Zhenjie; Li, Manchun; Yan, Ziyun; He, Weiqiang; Lian, Dongjie] Nanjing Univ, Sch Geog & Ocean Sci, Jiangsu Prov Key Lab Geog Informat Sci & Technol, Key Lab Land Satellite Remote Sensing Applicat Min, Nanjing 210023, Peoples R China.
   [Johnson, Brian Alan] Inst Global Environm Strategies, Nat Resources & Ecosyst Serv, 2108-11 Kamiyamaguchi, Hayama, Kanagawa 2400115, Japan.
   [Zhan, Wenfeng] Nanjing Univ, Int Inst Earth Syst Sci, Jiangsu Prov Key Lab Geog Informat Sci & Technol, Nanjing 210023, Jiangsu, Peoples R China.
   [Lu, Heng] Sichuan Univ, State Key Lab Hydraul & Mt River Engn, Chengdu 610065, Peoples R China.
C3 Nanjing University; Nanjing University; Sichuan University
RP Ma, L (corresponding author), Nanjing Univ, Sch Geog & Ocean Sci, Jiangsu Prov Key Lab Geog Informat Sci & Technol, Key Lab Land Satellite Remote Sensing Applicat Min, Nanjing 210023, Peoples R China.
EM maleinju@gmail.com
RI MA, Lei/I-4597-2014; Chen, Zhenjie/S-2988-2019; Li,
   Mengchun/AGW-0259-2022; Zhan, Wenfeng/I-1137-2014
OI Zhan, Wenfeng/0000-0001-7487-821X; ma, lei/0000-0002-8331-7200; Lian,
   Dongjie/0000-0002-5185-2356; Li, Manchun/0009-0009-7357-5642; Chen,
   Zhenjie/0000-0002-3033-8470
FU National Natural Science Foundation of China [42171304, 41701374];
   Fundamental Research Funds for the Central Universities
FX This work was supported by the funding provided by the National Natural
   Science Foundation of China (42171304, 41701374) , and the Fundamental
   Research Funds for the Central Universities. Sincere thanks to the
   anonymous reviewers and members of the editorial team for the comments
   and contributions.
CR Amani-Beni M, 2018, URBAN FOR URBAN GREE, V32, P1, DOI 10.1016/j.ufug.2018.03.016
   [Anonymous], 2022, Climate Change 2022: Impacts, Adaptation and Vulnerability, P3, DOI DOI 10.1017/9781009325844.001
   Aubrecht C, 2013, ENVIRON INT, V56, P65, DOI 10.1016/j.envint.2013.03.005
   Baatz M., 2000, Multiresolution Segmentation: an optimization approach for high quality multi-scale image segmentation
   Bai L, 2016, ENVIRON HEALTH-GLOB, V15, DOI 10.1186/s12940-015-0081-0
   Ban J, 2017, SCI TOTAL ENVIRON, V579, P529, DOI 10.1016/j.scitotenv.2016.11.064
   Bao JZ, 2015, INT J ENV RES PUB HE, V12, P7220, DOI 10.3390/ijerph120707220
   Bechtel B, 2019, URBAN CLIM, V27, P24, DOI 10.1016/j.uclim.2018.10.001
   Bechtel B, 2012, IEEE J-STARS, V5, P1191, DOI 10.1109/JSTARS.2012.2189873
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   Broadbent AM, 2018, URBAN CLIM, V23, P309, DOI 10.1016/j.uclim.2017.05.002
   Buscail C, 2012, INT J HEALTH GEOGR, V11, DOI 10.1186/1476-072X-11-38
   Cai JX, 2017, REMOTE SENS ENVIRON, V202, P210, DOI 10.1016/j.rse.2017.06.039
   Chan EYY, 2012, J EPIDEMIOL COMMUN H, V66, P322, DOI 10.1136/jech.2008.085167
   Chen B, 2022, SUSTAIN CITIES SOC, V81, DOI 10.1016/j.scs.2022.103831
   Chen HQ, 2022, SCI BULL, V67, P1340, DOI 10.1016/j.scib.2022.05.006
   Chen Q, 2018, INT J HEALTH GEOGR, V17, DOI 10.1186/s12942-018-0135-y
   Chen TL, 2022, URBAN CLIM, V41, DOI 10.1016/j.uclim.2021.101054
   Crichton D., 1999, Nat Disaster Manag, P102
   DEFRIES RS, 1994, INT J REMOTE SENS, V15, P3567, DOI 10.1080/01431169408954345
   Dhainaut JF, 2004, CRIT CARE, V8, P1, DOI 10.1186/cc2404
   Dong JQ, 2020, LANDSCAPE URBAN PLAN, V203, DOI 10.1016/j.landurbplan.2020.103907
   Dong WH, 2014, SUSTAINABILITY-BASEL, V6, P7334, DOI 10.3390/su6107334
   Estoque RC, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-15218-8
   Gronlund CJ, 2015, ENVIRON RES, V136, P449, DOI 10.1016/j.envres.2014.08.042
   Guo B, 2021, IEEE ACCESS, V9, P34352, DOI 10.1109/ACCESS.2021.3059865
   Guo YM, 2022, MED-CAMBRIDGE, V3, P656, DOI 10.1016/j.medj.2022.09.004
   Han B, 2022, SUSTAIN CITIES SOC, V76, DOI 10.1016/j.scs.2021.103495
   Holec J, 2021, NAT HAZARDS, V108, P3099, DOI 10.1007/s11069-021-04816-4
   Hu KJ, 2017, ENVIRON SCI TECHNOL, V51, P1498, DOI 10.1021/acs.est.6b04355
   Hua JY, 2021, SUSTAIN CITIES SOC, V64, DOI 10.1016/j.scs.2020.102507
   Johnson DP, 2012, APPL GEOGR, V35, P23, DOI 10.1016/j.apgeog.2012.04.006
   La YN, 2020, URBAN CLIM, V33, DOI 10.1016/j.uclim.2020.100661
   Leconte F, 2015, BUILD ENVIRON, V83, P39, DOI 10.1016/j.buildenv.2014.05.005
   Li JX, 2011, REMOTE SENS ENVIRON, V115, P3249, DOI 10.1016/j.rse.2011.07.008
   Lindley SJ, 2006, J RISK RES, V9, P543, DOI 10.1080/13669870600798020
   Liu JW, 2022, LANCET PLANET HEALTH, V6, pE484, DOI 10.1016/S2542-5196(22)00117-6
   Loughnan ME, 2014, INT J EMERG SERV, V3, P6, DOI 10.1108/IJES-10-2012-0044
   Ma L, 2021, BUILD ENVIRON, V206, DOI 10.1016/j.buildenv.2021.108348
   Ma L, 2021, ATMOSPHERE-BASEL, V12, DOI 10.3390/atmos12091146
   Ma L, 2015, ISPRS J PHOTOGRAMM, V102, P14, DOI 10.1016/j.isprsjprs.2014.12.026
   Macintyre HL, 2021, ENVIRON INT, V154, DOI 10.1016/j.envint.2021.106530
   Mellander C, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0139779
   Morabito M., 2015, PLOS ONE, V10
   OECD, 2008, Handbook on constructing composite indicators: methodology and user guide, DOI DOI 10.1787/9789264043466-EN
   Paranunzio R, 2021, URBAN CLIM, V40, DOI 10.1016/j.uclim.2021.100983
   Peters A, 2021, NAT REV CARDIOL, V18, P1, DOI 10.1038/s41569-020-00473-5
   Pramanik S, 2022, SUSTAIN CITIES SOC, V81, DOI 10.1016/j.scs.2022.103808
   Reid CE, 2009, ENVIRON HEALTH PERSP, V117, P1730, DOI 10.1289/ehp.0900683
   Ren JY, 2022, J CLEAN PROD, V340, DOI 10.1016/j.jclepro.2022.130744
   Savic S, 2018, NAT HAZARDS, V91, P891, DOI 10.1007/s11069-017-3160-4
   Semenza JC, 1999, AM J PREV MED, V16, P269, DOI 10.1016/S0749-3797(99)00025-2
   Song JC, 2020, LANDSCAPE URBAN PLAN, V198, DOI 10.1016/j.landurbplan.2020.103794
   Song JL, 2021, SUSTAIN CITIES SOC, V74, DOI 10.1016/j.scs.2021.103159
   Stewart ID, 2012, B AM METEOROL SOC, V93, P1879, DOI 10.1175/BAMS-D-11-00019.1
   Sun YW, 2022, URBAN CLIM, V43, DOI 10.1016/j.uclim.2022.101169
   Tian P, 2021, SUSTAIN CITIES SOC, V74, DOI 10.1016/j.scs.2021.103208
   Tomlinson CJ, 2011, INT J HEALTH GEOGR, V10, DOI 10.1186/1476-072X-10-42
   UN D., 2018, 252 UN D
   Unal YS, 2013, THEOR APPL CLIMATOL, V112, P339, DOI 10.1007/s00704-012-0704-0
   UNDRR, 2022, Global Assessment Report On Disaster Risk Reduction 2022: Our world At risk: Transforming governance For a Resilient Future
   Verdonck ML, 2019, J ENVIRON MANAGE, V249, DOI 10.1016/j.jenvman.2019.06.111
   Verdonck ML, 2018, LANDSCAPE URBAN PLAN, V178, P183, DOI 10.1016/j.landurbplan.2018.06.004
   Verdonck ML, 2017, INT J APPL EARTH OBS, V62, P102, DOI 10.1016/j.jag.2017.05.017
   Wang MM, 2020, IEEE J-STARS, V13, P4689, DOI 10.1109/JSTARS.2020.3014586
   Wang MM, 2019, J GEOPHYS RES-ATMOS, V124, P299, DOI 10.1029/2018JD029330
   Wu JS, 2022, BUILD ENVIRON, V207, DOI 10.1016/j.buildenv.2021.108568
   Xia HP, 2022, REMOTE SENS ENVIRON, V273, DOI 10.1016/j.rse.2022.112972
   Xiang ZX, 2022, SUSTAIN CITIES SOC, V80, DOI 10.1016/j.scs.2022.103792
   Xu HQ, 2006, INT J REMOTE SENS, V27, P3025, DOI 10.1080/01431160600589179
   Yan ZY, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14153744
   Yang DY, 2021, LAND-BASEL, V10, DOI 10.3390/land10080820
   Yang J, 2020, URBAN CLIM, V34, DOI 10.1016/j.uclim.2020.100700
   Yao R, 2017, SCI TOTAL ENVIRON, V609, P742, DOI 10.1016/j.scitotenv.2017.07.217
   Zhang C, 2018, REMOTE SENS ENVIRON, V216, P57, DOI 10.1016/j.rse.2018.06.034
   Zhang K, 2015, ENVIRON HEALTH-GLOB, V14, DOI 10.1186/1476-069X-14-11
   Zhang QL, 2011, REMOTE SENS ENVIRON, V115, P2320, DOI 10.1016/j.rse.2011.04.032
   Zhang W, 2019, SCI TOTAL ENVIRON, V663, P852, DOI 10.1016/j.scitotenv.2019.01.240
   Zhang W, 2016, SUSTAINABILITY-BASEL, V8, DOI 10.3390/su8090885
   Zheng BH, 2022, URBAN CLIM, V43, DOI 10.1016/j.uclim.2022.101153
   Zhou L, 2022, ISPRS INT J GEO-INF, V11, DOI 10.3390/ijgi11080420
   Zhou Y, 2021, SUSTAIN CITIES SOC, V74, DOI 10.1016/j.scs.2021.103174
   Zhu XX, 2020, IEEE GEOSC REM SEN M, V8, P76, DOI 10.1109/MGRS.2020.2964708
NR 83
TC 44
Z9 46
U1 53
U2 212
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 APR
PY 2023
VL 91
AR 104402
DI 10.1016/j.scs.2023.104402
EA FEB 2023
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 9P7NO
UT WOS:000944467800001
HC Y
HP N
DA 2025-01-10
ER

PT J
AU Andreatta, G
   Montagnese, S
   Costa, R
AF Andreatta, Gabriele
   Montagnese, Sara
   Costa, Rodolfo
TI Natural alleles of the clock gene <i>timeless</i> differentially affect
   life-history traits in Drosophila
SO FRONTIERS IN PHYSIOLOGY
LA English
DT Article
DE circadian clock; timeless; developmental time; early-life fecundity;
   seasonality; photoperiodism; reproductive dormancy
ID CIRCADIAN CLOCK; BODY-SIZE; CLIMATIC ADAPTATION; LATITUDINAL CLINES;
   DIAPAUSE; MELANOGASTER; TEMPERATURE; SELECTION; OSCILLATIONS;
   POPULATIONS
AB Circadian clocks orchestrate a variety of physiological and behavioural functions within the 24-h day. These timekeeping systems have also been implicated in developmental and reproductive processes that span more (or less) than 24 h. Whether natural alleles of cardinal clock genes affect entire sets of life-history traits (i.e., reproductive arrest, developmental time, fecundity), thus providing a wider substrate for seasonal adaptation, remains unclear. Here we show that natural alleles of the timeless (tim) gene of Drosophila melanogaster, previously shown to modulate flies' propensity to enter reproductive dormancy, differentially affect correlated traits such as early-life fecundity and developmental time. Homozygous flies expressing the shorter TIM isoform (encoded by the s-tim allele) not only show a lower dormancy incidence compared to those homozygous for ls-tim (which produce both the short and an N-terminal additional 23-residues longer TIM isoform), but also higher fecundity in the first 12 days of adult life. Moreover, s-tim homozygous flies develop faster than ls-tim homozygous flies at both warm (25 degrees C) and cold (15 degrees C) temperatures, with the gap being larger at 15 degrees C. In summary, this phenotypic analysis shows that natural variants of tim affect a set of life-history traits associated with reproductive dormancy in Drosophila. We speculate that this provides further adaptive advantage in temperate regions (with seasonal changes) and propose that the underlying mechanisms might not be exclusively dependent on photoperiod, as previously suggested.
C1 [Andreatta, Gabriele; Costa, Rodolfo] Univ Padua, Dept Biol, Padua, Italy.
   [Andreatta, Gabriele] Univ Vienna, Max Perutz Labs, Vienna, Austria.
   [Montagnese, Sara] Univ Padua, Dept Med, Padua, Italy.
   [Montagnese, Sara; Costa, Rodolfo] Univ Surrey, Fac Hlth & Med Sci, Chronobiol, Guildford, England.
   [Costa, Rodolfo] Natl Res Council CNR, Inst Neurosci, Padua, Italy.
C3 University of Padua; Medical University of Vienna; University of Vienna;
   Vienna Biocenter (VBC); Max F. Perutz Laboratories (MFPL); University of
   Padua; University of Surrey
RP Andreatta, G; Costa, R (corresponding author), Univ Padua, Dept Biol, Padua, Italy.; Andreatta, G (corresponding author), Univ Vienna, Max Perutz Labs, Vienna, Austria.; Costa, R (corresponding author), Univ Surrey, Fac Hlth & Med Sci, Chronobiol, Guildford, England.; Costa, R (corresponding author), Natl Res Council CNR, Inst Neurosci, Padua, Italy.
EM gabriele.andreatta@univie.ac.at; rodolfo.costa@unipd.it
RI Andreatta, Gabriele/AAK-6596-2020
OI MONTAGNESE, SARA/0000-0003-2800-9923
FU Comparative Insect Chronobiology (CINCHRON); EU Horizon 2020, Marie
   Sklodowska-Curie Initial Training Network [765937]; Fondazione CaRiPaRo;
   Department of Biology at the University of Padua; ERC-CoG from Kristin
   Tessmar-Raible at the University of Vienna [819952]; European Research
   Council (ERC) [819952] Funding Source: European Research Council (ERC);
   Marie Curie Actions (MSCA) [765937] Funding Source: Marie Curie Actions
   (MSCA)
FX The work was supported by the grant Comparative Insect Chronobiology
   (CINCHRON), EU Horizon 2020, Marie Sklodowska-Curie Initial Training
   Network (grant agreement N degrees 765937) to RC. GA was supported by a
   doctoral fellowship from the Fondazione CaRiPaRo (Italy), a Junior
   Research Fellowship from the Department of Biology at the University of
   Padua (Italy), and a Postdoctoral fellowship funded with the ERC-CoG
   819952 (Maritime) from Kristin Tessmar-Raible at the University of
   Vienna (Austria).
CR Abrieux A, 2020, P NATL ACAD SCI USA, V117, P15293, DOI 10.1073/pnas.2004262117
   Andreatta G, 2020, J MOL BIOL, V432, P3525, DOI 10.1016/j.jmb.2020.03.009
   Andreatta G, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-20407-z
   Anduaga AM, 2019, ELIFE, V8, DOI 10.7554/eLife.44642
   Banerjee D, 2005, DEV CELL, V8, P287, DOI 10.1016/j.devcel.2004.12.006
   Beaver LM, 2003, J BIOL RHYTHM, V18, P463, DOI 10.1177/0748730403259108
   Beaver LM, 2002, P NATL ACAD SCI USA, V99, P2134, DOI 10.1073/pnas.032426699
   Boothroyd CE, 2007, PLOS GENET, V3, DOI 10.1371/journal.pgen.0030054
   Chown SL, 2010, BIOL REV, V85, P139, DOI 10.1111/j.1469-185X.2009.00097.x
   Damulewicz M, 2020, FRONT PHYSIOL, V11, DOI 10.3389/fphys.2020.00099
   DAVID J, 1967, J INSECT PHYSIOL, V13, P717, DOI 10.1016/0022-1910(67)90121-7
   Deppisch P, 2022, J BIOL RHYTHM, V37, P185, DOI 10.1177/07487304221082448
   Di Cara F, 2016, CURR BIOL, V26, P2469, DOI 10.1016/j.cub.2016.07.004
   Edelman TLB, 2016, G3-GENES GENOM GENET, V6, P4077, DOI 10.1534/g3.116.034165
   Emerson KJ, 2009, J COMP PHYSIOL A, V195, P825, DOI 10.1007/s00359-009-0460-5
   Foley LE, 2019, ELIFE, V8, DOI 10.7554/eLife.50063
   Garmier-Billard M., 2019, TRENDS MED, V19, P1, DOI [10.15761/tim.1000193, DOI 10.15761/TIM.1000193]
   Gesto J. S. M., 2010, THESIS U LEICESTER U
   Hahn DA, 2011, ANNU REV ENTOMOL, V56, P103, DOI 10.1146/annurev-ento-112408-085436
   Horn M, 2019, FRONT PHYSIOL, V10, DOI 10.3389/fphys.2019.01374
   Hunt LC, 2019, GENOME RES, V29, P1262, DOI 10.1101/gr.246884.118
   Kubrak OI, 2016, FRONT PHYSIOL, V7, DOI 10.3389/fphys.2016.00572
   Kubrak OI, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0113051
   Kumar S, 2006, BMC DEV BIOL, V6, DOI 10.1186/1471-213X-6-57
   KYRIACOU CP, 1990, HEREDITY, V64, P395, DOI 10.1038/hdy.1990.50
   Lamaze A, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-29293-6
   Layalle S, 2008, DEV CELL, V15, P568, DOI 10.1016/j.devcel.2008.08.003
   Lirakis M, 2018, J INSECT PHYSIOL, V107, P175, DOI 10.1016/j.jinsphys.2018.04.006
   Majercak J, 1999, NEURON, V24, P219, DOI 10.1016/S0896-6273(00)80834-X
   Mark B, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2023249118
   McBrayer Z, 2007, DEV CELL, V13, P857, DOI 10.1016/j.devcel.2007.11.003
   Montelli S, 2015, J BIOL RHYTHM, V30, P217, DOI 10.1177/0748730415583575
   Myers EM, 2003, CURR BIOL, V13, P526, DOI 10.1016/S0960-9822(03)00167-2
   Nagy D, 2019, PLOS GENET, V15, DOI 10.1371/journal.pgen.1008158
   Nagy D, 2018, J BIOL RHYTHM, V33, P117, DOI 10.1177/0748730417754116
   Olmedo M, 2017, ADV GENET, V97, P43, DOI 10.1016/bs.adgen.2017.05.001
   Pegoraro M, 2017, J INSECT PHYSIOL, V98, P238, DOI 10.1016/j.jinsphys.2017.01.015
   Pegoraro M, 2014, PLOS GENET, V10, DOI 10.1371/journal.pgen.1004603
   Peschel N, 2006, P NATL ACAD SCI USA, V103, P17313, DOI 10.1073/pnas.0606675103
   Peschel N, 2011, FEBS LETT, V585, P1435, DOI 10.1016/j.febslet.2011.02.028
   PITTENDRIGH CS, 1989, J BIOL RHYTHM, V4, P217
   PITTENDRIGH CS, 1991, J BIOL RHYTHM, V6, P299, DOI 10.1177/074873049100600402
   Ratajczak CK, 2009, ENDOCRINOLOGY, V150, P1879, DOI 10.1210/en.2008-1021
   Reppert SM, 2016, ANNU REV ENTOMOL, V61, P25, DOI 10.1146/annurev-ento-010814-020855
   Richard DS, 2001, J INSECT PHYSIOL, V47, P905, DOI 10.1016/S0022-1910(01)00063-4
   Rosato E, 1997, NUCLEIC ACIDS RES, V25, P455, DOI 10.1093/nar/25.3.455
   Sandrelli F, 2007, SCIENCE, V316, P1898, DOI 10.1126/science.1138426
   Saunders DS, 2020, ANNU REV ENTOMOL, V65, P373, DOI 10.1146/annurev-ento-011019-025116
   SAUNDERS DS, 1990, J INSECT PHYSIOL, V36, P195, DOI 10.1016/0022-1910(90)90122-V
   SAUNDERS DS, 1989, P NATL ACAD SCI USA, V86, P3748, DOI 10.1073/pnas.86.10.3748
   Schiesari L, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0163680
   Schmidt PS, 2008, P NATL ACAD SCI USA, V105, P16207, DOI 10.1073/pnas.0805485105
   Schmidt PS, 2008, EVOLUTION, V62, P1204, DOI 10.1111/j.1558-5646.2008.00351.x
   Schmidt PS, 2005, EVOLUTION, V59, P2616, DOI 10.1111/j.0014-3820.2005.tb00974.x
   Schmidt PS, 2005, EVOLUTION, V59, P1721, DOI 10.1111/j.0014-3820.2005.tb01821.x
   SEHGAL A, 1994, SCIENCE, V263, P1603, DOI 10.1126/science.8128246
   Shimizu T, 1997, HEREDITY, V79, P600, DOI 10.1038/hdy.1997.205
   Srivastava M, 2018, BMC DEV BIOL, V18, DOI 10.1186/s12861-018-0180-6
   Stillwell RC, 2010, OIKOS, V119, P1387, DOI 10.1111/j.1600-0706.2010.18670.x
   Takahashi JS, 2017, NAT REV GENET, V18, P164, DOI 10.1038/nrg.2016.150
   Tauber E, 2007, SCIENCE, V316, P1895, DOI 10.1126/science.1138412
   Varma V, 2019, BIOL OPEN, V8, DOI 10.1242/bio.042176
   Wijnen H, 2006, PLOS GENET, V2, P326, DOI 10.1371/journal.pgen.0020039
   Yadav P, 2014, BMC DEV BIOL, V14, DOI 10.1186/1471-213X-14-19
   Zonato V, 2018, J BIOL RHYTHM, V33, P15, DOI 10.1177/0748730417742309
   Zonato V, 2017, J INSECT PHYSIOL, V98, P267, DOI 10.1016/j.jinsphys.2017.01.017
   Zonato V, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0162370
NR 67
TC 2
Z9 2
U1 1
U2 6
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
EI 1664-042X
J9 FRONT PHYSIOL
JI Front. Physiol.
PD JAN 10
PY 2023
VL 13
AR 1092951
DI 10.3389/fphys.2022.1092951
PG 9
WC Physiology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Physiology
GA 8I7RE
UT WOS:000921926900001
PM 36703932
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Li, LJ
   Zhao, LL
   Fu, JB
   Sun, B
   Liu, CD
AF Li, Linjie
   Zhao, Linlin
   Fu, Jinbo
   Sun, Bin
   Liu, Changdong
TI Predicting the habitat suitability for populations of Pacific cod under
   different climate change scenarios considering intraspecific genetic
   variation
SO ECOLOGICAL INDICATORS
LA English
DT Article
DE Gadus macrocephalus; Intraspecific genetic variation; Niche
   differentiation; Habitat suitability; Climate change
ID SPECIES DISTRIBUTION MODELS; GADUS-MACROCEPHALUS; LOCAL ADAPTATION;
   RANGE SHIFTS; BERING-SEA; ECOSYSTEM; CONSERVATION; ASSOCIATIONS;
   COMMUNITIES; TEMPERATURE
AB Several studies have demonstrated the importance of integrating intraspecific genetic variation in forecasting the habitat suitability of species under climate change scenarios. The Pacific cod (Gadus macrocephalus) is an economically important fish species in the North Pacific that can be classified into western and eastern populations based on molecular phylogeographic data. Herein, we first quantified the realized niche of the two Pacific cod populations using n-dimensional hypervolumes and estimated the niche differentiation between the populations. We then projected the habitat suitability based on the georeferenced occurrence records and environmental predictors using species distribution models (SDMs) at the population and species levels. The low niche overlap demonstrated the marked niche differentiation between the two populations. The distinct responses of the populations to climate predictors implied that the population-level SDM produced more reliable projections than the corresponding species-level SDM. The model indicated that the eastern population expanded its suitable area northward, while maintaining most of its current habitat and exhibited resilience to climate impacts. However, the western population lost much of its current suitable area, while colonizing a new habitat in a small section of the offshore waters of the Japanese Sea, implying the vulnerability of this population to climate change. This study highlights the necessity of incorporating intraspecific genetic variation into SDMs to predict the habitat suitability of Pacific cod on the global scale. The spatiotemporal predictive maps of habitat suitability provide crucial information for designing climate-adaptive conservation and management strategies based on more precise taxonomic units for the sustainability of Pacific cod.
C1 [Li, Linjie; Fu, Jinbo; Sun, Bin; Liu, Changdong] Ocean Univ China, Dept Fisheries, 5 Yushan Rd, Qingdao, Shandong, Peoples R China.
   [Zhao, Linlin] Minist Nat Resources, Inst Oceanog 1, Qingdao, Shandong, Peoples R China.
C3 Ocean University of China; First Institute of Oceanography, Ministry of
   Natural Resources; Ministry of Natural Resources of the People's
   Republic of China
RP Liu, CD (corresponding author), Ocean Univ China, Dept Fisheries, 5 Yushan Rd, Qingdao, Shandong, Peoples R China.
EM changdong@ouc.edu.cn
RI linjie, li/HGV-2760-2022
OI Li, Linjie/0009-0008-6500-1502
FU National Key R&D Program of China [2020YFD0901205]
FX We are grateful to the Global Biodiversity Information Facility (GBIF),
   Ocean Biogeographic Information System (OBIS) and Bio-ORACLE v2.1
   datasets for providing us with the necessary data. This work was funded
   by the National Key R&D Program of China (2020YFD0901205).
CR Abookire AA, 2007, MAR BIOL, V150, P713, DOI 10.1007/s00227-006-0391-4
   Aiello-Lammens ME, 2015, ECOGRAPHY, V38, P541, DOI 10.1111/ecog.01132
   ALDERDICE DF, 1971, J FISH RES BOARD CAN, V28, P883, DOI 10.1139/f71-130
   Allouche O, 2006, J APPL ECOL, V43, P1223, DOI 10.1111/j.1365-2664.2006.01214.x
   [Anonymous], 1996, NMFSAFSC67 NOAA US D
   Araújo MB, 2006, J BIOGEOGR, V33, P1712, DOI 10.1111/j.1365-2699.2006.01482.x
   Araújo MB, 2005, GLOBAL CHANGE BIOL, V11, P1504, DOI 10.1111/j.1365-2486.2005.01000.x
   Assis J, 2018, GLOBAL ECOL BIOGEOGR, V27, P277, DOI 10.1111/geb.12693
   Barbet-Massin M, 2012, METHODS ECOL EVOL, V3, P327, DOI 10.1111/j.2041-210X.2011.00172.x
   Blonder B., 2018, HYPERVOLUME HIGH DIM
   Bosch S, 2018, DIVERS DISTRIB, V24, P144, DOI 10.1111/ddi.12668
   Cacciapaglia C, 2018, J BIOGEOGR, V45, P154, DOI 10.1111/jbi.13115
   Calkins D.G., 1998, BIOSPH CONSERV, V1, P33, DOI DOI 10.1086/603637
   Canino MF, 2010, MOL ECOL, V19, P4339, DOI 10.1111/j.1365-294X.2010.04815.x
   Cardoso P., 2021, R PACKAGE VERSION 2
   Carvalho JC, 2020, FRONT ECOL EVOL, V8, DOI 10.3389/fevo.2020.00243
   Chang YJ, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.731950
   Chefaoui RM, 2018, GLOBAL CHANGE BIOL, V24, P4919, DOI 10.1111/gcb.14401
   Chen YL, 2021, ECOL INDIC, V128, DOI 10.1016/j.ecolind.2021.107799
   Ciannelli L, 2020, ECOLOGY, V101, DOI 10.1002/ecy.2907
   Cohen D.M., 1990, FAO Fisheries Synopsis, V10, P442
   Collart F, 2021, J BIOGEOGR, V48, P415, DOI 10.1111/jbi.14009
   Cunningham KM, 2009, CAN J FISH AQUAT SCI, V66, P153, DOI 10.1139/F08-199
   Davis MB, 2001, SCIENCE, V292, P673, DOI 10.1126/science.292.5517.673
   Dean TA, 2000, ENVIRON BIOL FISH, V57, P271, DOI 10.1023/A:1007652730085
   Dormann CF, 2013, ECOGRAPHY, V36, P27, DOI 10.1111/j.1600-0587.2012.07348.x
   Dulvy NK, 2008, J APPL ECOL, V45, P1029, DOI 10.1111/j.1365-2664.2008.01488.x
   Elith J, 2009, ANNU REV ECOL EVOL S, V40, P677, DOI 10.1146/annurev.ecolsys.110308.120159
   FAO FishStatJ, 2020, FAO FISHSTATJ DAT 20
   Fossheim M, 2015, NAT CLIM CHANGE, V5, P673, DOI 10.1038/NCLIMATE2647
   Fu JB, 2021, PEERJ, V9, DOI 10.7717/peerj.12001
   Gaylord B, 2000, AM NAT, V155, P769, DOI 10.1086/303357
   Gibbs JP, 2001, BIOL CONSERV, V100, P15, DOI 10.1016/S0006-3207(00)00203-2
   Goldsmit J, 2018, BIOL INVASIONS, V20, P501, DOI 10.1007/s10530-017-1553-7
   GRANT WS, 1988, EVOLUTION, V42, P138, DOI 10.1111/j.1558-5646.1988.tb04114.x
   GRANT WS, 1987, CAN J FISH AQUAT SCI, V44, P490, DOI 10.1139/f87-061
   Gregor J, 2004, WATER RES, V38, P517, DOI 10.1016/j.watres.2003.10.033
   Guisan A, 2005, ECOL LETT, V8, P993, DOI 10.1111/j.1461-0248.2005.00792.x
   Guisan A., 2017, Habitat Suitability and Distribution Models: With Applications in R
   Hällfors MH, 2016, ECOL APPL, V26, P1154, DOI 10.1890/15-0926
   Hereford J, 2009, AM NAT, V173, P579, DOI 10.1086/597611
   Hirzel AH, 2006, ECOL MODEL, V199, P142, DOI 10.1016/j.ecolmodel.2006.05.017
   Hu ZM, 2021, MOL ECOL, V30, P3840, DOI 10.1111/mec.15996
   Huot Y, 2007, BIOGEOSCIENCES, V4, P853, DOI 10.5194/bg-4-853-2007
   Ikeda DH, 2017, GLOBAL CHANGE BIOL, V23, P164, DOI 10.1111/gcb.13470
   IUCN, 1996, IUCN RED LIST THREAT, DOI [10.2305/IUCN.UK.1996.RLTS.T8784A12931575.en, DOI 10.2305/IUCN.UK.1996.RLTS.T20855A9231471.EN]
   Jayathilake DRM, 2018, BIOL CONSERV, V226, P120, DOI 10.1016/j.biocon.2018.07.009
   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
   Kleisner KM, 2017, PROG OCEANOGR, V153, P24, DOI 10.1016/j.pocean.2017.04.001
   Kleisner KM, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0149220
   Koskimäki J, 2014, POPUL ECOL, V56, P341, DOI 10.1007/s10144-013-0411-4
   Kreyling J, 2011, RESTOR ECOL, V19, P433, DOI 10.1111/j.1526-100X.2011.00777.x
   Lecocq T, 2016, CONSERV LETT, V9, P281, DOI 10.1111/conl.12215
   Lenoir J, 2020, NAT ECOL EVOL, V4, P1044, DOI 10.1038/s41559-020-1198-2
   Li JC, 2021, J GEOPHYS RES-OCEANS, V126, DOI 10.1029/2020JC016696
   Lino A, 2019, MAMM BIOL, V94, P69, DOI 10.1016/j.mambio.2018.09.006
   Liu CR, 2013, J BIOGEOGR, V40, P778, DOI 10.1111/jbi.12058
   Liu CD, 2017, MAR FRESHWATER RES, V68, P270, DOI 10.1071/MF15374
   Ma SY, 2021, GLOBAL CHANGE BIOL, V27, P5310, DOI 10.1111/gcb.15815
   Ma SY, 2019, PROG OCEANOGR, V175, P183, DOI 10.1016/j.pocean.2019.04.008
   Mammola S, 2020, METHODS ECOL EVOL, V11, P986, DOI 10.1111/2041-210X.13424
   Marshall CE, 2014, MAR POLICY, V45, P330, DOI 10.1016/j.marpol.2013.09.003
   Mingle J, 2020, NEW YORK REV BOOKS, V67, P49
   Mondanaro A, 2021, ECOGRAPHY, V44, P1619, DOI 10.1111/ecog.05939
   Moss RH, 2010, NATURE, V463, P747, DOI 10.1038/nature08823
   Napazakov VV, 2008, RUSS J MAR BIOL+, V34, P452, DOI 10.1134/S1063074008070031
   Oney B, 2013, ECOL EVOL, V3, P437, DOI 10.1002/ece3.426
   Pearman PB, 2010, ECOGRAPHY, V33, P990, DOI 10.1111/j.1600-0587.2010.06443.x
   Penn JL, 2022, SCIENCE, V376, P524, DOI 10.1126/science.abe9039
   Peterson AT, 1999, SCIENCE, V285, P1265, DOI 10.1126/science.285.5431.1265
   Razgour O, 2019, P NATL ACAD SCI USA, V116, P10418, DOI 10.1073/pnas.1820663116
   Reid PC, 2009, ADV MAR BIOL, V56, P1, DOI 10.1016/S0065-2881(09)56001-4
   Robinson LM, 2011, GLOBAL ECOL BIOGEOGR, V20, P789, DOI 10.1111/j.1466-8238.2010.00636.x
   Sakuma K, 2019, ESTUAR COAST SHELF S, V229, DOI 10.1016/j.ecss.2019.106401
   Sakurai Y, 1996, FISHERIES SCI, V62, P222, DOI 10.2331/fishsci.62.222
   Sbrocco E. J., 2013, Ecology, V94, DOI DOI 10.1890/12-1358.1
   Schüller M, 2011, POLAR BIOL, V34, P549, DOI 10.1007/s00300-010-0913-x
   Seiler-Marie N, 2004, INT J HEAT MASS TRAN, V47, P5059, DOI 10.1016/j.ijheatmasstransfer.2004.06.009
   Skelly DK, 2007, CONSERV BIOL, V21, P1353, DOI 10.1111/j.1523-1739.2007.00764.x
   Smirnova MA, 2015, DOKL BIOCHEM BIOPHYS, V465, P389, DOI 10.1134/S1607672915060113
   Smith AB, 2019, TRENDS ECOL EVOL, V34, P260, DOI 10.1016/j.tree.2018.10.012
   Sorte CJB, 2010, GLOBAL ECOL BIOGEOGR, V19, P303, DOI 10.1111/j.1466-8238.2009.00519.x
   Spies I, 2020, EVOL APPL, V13, P362, DOI 10.1111/eva.12874
   Spies I, 2012, T AM FISH SOC, V141, P1557, DOI 10.1080/00028487.2012.711265
   Stevenson DE, 2019, POLAR BIOL, V42, P407, DOI 10.1007/s00300-018-2431-1
   Suda A, 2017, J FISH BIOL, V90, P61, DOI 10.1111/jfb.13154
   SWETS JA, 1988, SCIENCE, V240, P1285, DOI 10.1126/science.3287615
   Thuiller W., 2020, R PACKAGE VERSION, V3, P6
   Thuiller W, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-09519-w
   Tian YJ, 2008, PROG OCEANOGR, V77, P127, DOI 10.1016/j.pocean.2008.03.007
   Tulloch VJD, 2019, GLOBAL CHANGE BIOL, V25, P1263, DOI 10.1111/gcb.14573
   Walther GR, 2009, TRENDS ECOL EVOL, V24, P686, DOI 10.1016/j.tree.2009.06.008
   Yachi S, 1999, P NATL ACAD SCI USA, V96, P1463, DOI 10.1073/pnas.96.4.1463
   Yvon P., 2016, Structural Materials for Generation IV Nuclear Reactors, DOI [DOI 10.1016/C2014-0-03589-7, 10.1016/j.fbp.2019.05.001]
   Zhang ZX, 2021, DIVERS DISTRIB, V27, P684, DOI 10.1111/ddi.13225
   Zhang ZX, 2020, MAR ENVIRON RES, V159, DOI 10.1016/j.marenvres.2020.104993
   Zhang ZX, 2020, FRESHWATER BIOL, V65, P971, DOI 10.1111/fwb.13483
   Zhang ZX, 2019, ECOL INDIC, V104, P333, DOI 10.1016/j.ecolind.2019.05.023
   Zhao T, 2020, SCI TOTAL ENVIRON, V738, DOI 10.1016/j.scitotenv.2020.140269
NR 100
TC 8
Z9 8
U1 5
U2 50
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 1470-160X
EI 1872-7034
J9 ECOL INDIC
JI Ecol. Indic.
PD SEP
PY 2022
VL 142
AR 109248
DI 10.1016/j.ecolind.2022.109248
EA JUL 2022
PG 10
WC Biodiversity Conservation; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA 5R4JL
UT WOS:000874478300034
OA gold
DA 2025-01-10
ER

PT J
AU Haverkamp, J
AF Haverkamp, Jamie
TI Where's the Love? Recentring Indigenous and Feminist Ethics of Care for
   Engaged Climate Research
SO GATEWAYS-INTERNATIONAL JOURNAL OF COMMUNITY RESEARCH AND ENGAGEMENT
LA English
DT Article
DE Care; Relationality; Knowledge Production; Participatory Action
   Research; Climate Adaptation; Peru
ID CONSERVATION; POLITICS
AB Across a range of environmental change and crisis-driven research fields, including conservation, climate change and sustainability studies, the rhetoric of participatory and engaged research has become somewhat of a normative and mainstream mantra. Aligning with cautionary tales of participatory approaches, this article suggests that, all too often, 'engaged' research is taken up uncritically and without care, often by pragmatist, post-positivist and neoliberal action-oriented researchers, for whom the radical and relational practice of PAR is paradigmatically (ontologically, epistemologically and/or axiologically) incommensurable. Resisting depoliticised and rationalist interpretations of participatory methodologies, I strive in this article to hold space for the political, relational and ethical dimensions of collaboration and engagement.
   Drawing on four years of collaborative ethnographic climate research in the Peruvian Andes with campesinos of Quilcayhuanca, I argue that resituating Participatory Action Research (PAR) within a feminist and indigenous ethics of care more fully aligns with the radical participatory praxis for culturally appropriate transformation and the liberation of oppressed groups. Thus, I do not abandon the participatory methodology altogether, rather this article provides a hopeful reworking of the participatory methodology and, specifically, participatory and community-based adaptation (CBA) practices, in terms of a feminist and indigenous praxis of love-care-response. In so doing, I strive to reclaim the more radical feminist and Indigenous elements - the affective, relational and political origins of collaborative knowledge production - and rethink research in the rupture of climate crises, relationally. The ethico-political frictions and tensions inherent in engaged climate scholarship are drawn into sharp relief, and deep reflection on the responsibility researchers take on when asking questions in spaces and times of ecological loss, trauma and grief is offered.
C1 [Haverkamp, Jamie] James Madison Univ, Dept Sociol & Anthropol, Harrisonburg, VA 22807 USA.
C3 James Madison University
RP Haverkamp, J (corresponding author), James Madison Univ, Dept Sociol & Anthropol, Harrisonburg, VA 22807 USA.
OI Haverkamp, Jamie/0000-0001-6954-3423
CR Archibald JA, 2008, INDIGENOUS STORYWORK: EDUCATING THE HEART, MIND, BODY, AND SPIRIT, P1
   Benjaminsen TA, 2012, J PEASANT STUD, V39, P335, DOI 10.1080/03066150.2012.667405
   Berkes F, 2007, P NATL ACAD SCI USA, V104, P15188, DOI 10.1073/pnas.0702098104
   Borda O.Fals., 1988, KNOWLEDGE PEOPLES PO
   Brondizio ES, 2016, GLOBAL ENVIRON CHANG, V39, P318, DOI 10.1016/j.gloenvcha.2016.02.006
   Brosius J.Peter., 2005, COMMUNITIES CONSERVA
   Button Gregory V., 2009, Anthropology and Climate Change: From Encounters to Actions, P327
   Carey Mark., 2010, In the Shadow of Melting Glaciers: Climate Change and Andean Society, DOI [10.1093/med/9780199653478.003.0003, DOI 10.1093/MED/9780199653478.003.0003, DOI 10.1093/ACPROF:OSO/9780195396065.001.0001]
   CHAMBERS R, 1994, WORLD DEV, V22, P953, DOI 10.1016/0305-750X(94)90141-4
   Cooke B., 2001, Participation: the new tyranny?
   Coombes B, 2014, PROG HUM GEOG, V38, P845, DOI 10.1177/0309132513514723
   Crate SA, 2011, ANNU REV ANTHROPOL, V40, P175, DOI 10.1146/annurev.anthro.012809.104925
   De la Cadena M., 1998, Bulletin of Latin American Studies, V17, P143, DOI [DOI 10.1111/J.1470-9856.1998.TB00169.X, 10.1016/S0261-3050(97)00085-5]
   Demeritt D., 2015, The Routledge Handbook of Political Ecology
   Escobar A., 2020, Pluriversal politics: the real and the possible, DOI [10.1515/9781478012108, DOI 10.1515/9781478012108]
   Escobar A, 2016, AIBR-REV ANTROPOL IB, V11, P12, DOI 10.11156/aibr.110102
   Fairhead J, 2012, J PEASANT STUD, V39, P237, DOI 10.1080/03066150.2012.671770
   Fals-Borda Orlando., 1991, ACTION KNOWLEDGE, P3
   Fazey I, 2021, SUSTAIN SCI, V16, P1731, DOI 10.1007/s11625-021-00950-x
   Forsyth T, 2013, WIRES CLIM CHANGE, V4, P439, DOI 10.1002/wcc.231
   Freire P., 1993, PEDAGOGY OPPRESSED 3
   Haverkamp J, 2021, WORLD DEV, V137, DOI 10.1016/j.worlddev.2020.105152
   Haverkamp JAR, 2017, ENVIRON PLANN A, V49, P2673, DOI 10.1177/0308518X17707525
   Kanngieser A, 2020, HIST THEORY, V59, P385, DOI 10.1111/hith.12166
   Lindroth M, 2014, GLOB SOC, V28, P180, DOI 10.1080/13600826.2014.887557
   Massey Doreen B., 2005, For Space
   McGreavy B, 2021, SUSTAIN SCI, V16, P937, DOI 10.1007/s11625-021-00904-3
   Montgomery M, 2021, MLK JR LECT SERIES
   MOSSE D, 1994, DEV CHANGE, V25, P497, DOI 10.1111/j.1467-7660.1994.tb00524.x
   Nadasdy P, 2003, ARCTIC, V56, P367, DOI 10.14430/arctic634
   Nightingale AJ, 2020, CLIM DEV, V12, P343, DOI 10.1080/17565529.2019.1624495
   Norstrom AV, 2020, NAT SUSTAIN, V3, P182, DOI 10.1038/s41893-019-0448-2
   Peterson K, 2016, ANTHROPOLOGY AND CLIMATE CHANGE: FROM ACTIONS TO TRANSFORMATIONS, 2ND EDITION, P336
   Plumwood V., 1991, HYPATIA, V6, P3, DOI [DOI 10.1111/J.1527-2001.1991.TB00206.X, 10.1111/j.15272001.1991.tb00206.x, DOI 10.1111/J.15272001.1991.TB00206.X]
   Puig de la Bellacasa M., 2017, MATTERS CARE SPECULA, DOI [10.1017/S2753906700002096, DOI 10.1017/S2753906700002096]
   Rasmussen M.B., 2015, ANDEAN WATERWAYS RES
   Reid H, 2014, COMMUNITY-BASED ADAPTATION TO CLIMATE CHANGE: SCALING IT UP, P3
   Roncoli C, 2006, CLIM RES, V33, P81, DOI 10.3354/cr033081
   Smith L.T., 2005, The Sage handbook of Qualitative Research, V3rd
   Smith LindaTuhiwai., 2012, Decolonizing Methodologies: Research and Indigenous Peoples, V2nd
   Swyngedouw E, 2013, ACME, V12, P1
   TallBear K, 2014, J RES PRACT, V10
   Tsing AL, 2015, MUSHROOM AT THE END OF THE WORLD: ON THE POSSIBILITY OF LIFE IN CAPITALIST RUINS, P1, DOI 10.1515/9781400873548
   Tsing A, 2010, MANOA, V22, P191
   Whyte K, 2018, ENVIRON SOC, V9, P125, DOI 10.3167/ares.2018.090109
   Whyte KP, 2016, SUSTAIN SCI, V11, P25, DOI 10.1007/s11625-015-0296-6
   Willow A, 2015, AM INDIAN CULT RES J, V39, P29, DOI 10.17953/aicrj.39.2.willow
   Yeh ET, 2016, AREA, V48, P34, DOI 10.1111/area.12189
NR 48
TC 8
Z9 9
U1 0
U2 6
PU UNIV TECHNOLOGY, SYDNEY-UTS EPRESS
PI SYDNEY
PA BROADWAY, PO BOX 123, SYDNEY, NSW 2007, AUSTRALIA
SN 1836-3393
J9 GATEWAYS
JI Gateways
PD DEC
PY 2021
VL 14
IS 2
DI 10.5130/ijcre.v14i2.7782
PG 15
WC Social Sciences, Interdisciplinary
WE Emerging Sources Citation Index (ESCI)
SC Social Sciences - Other Topics
GA XX6YW
UT WOS:000736439300003
OA gold
DA 2025-01-10
ER

PT J
AU Neupane, RC
   Powell, JA
   Edwards, TC
AF Neupane, Ram C.
   Powell, James A.
   Edwards, Thomas C.
TI Connecting regional-scale tree distribution models with seed dispersal
   kernels
SO APPLIED MATHEMATICS AND COMPUTATION
LA English
DT Article
DE Homogenized seed digestion kernel; Motility; Landscape utilization;
   Residence time
ID SPECIES DISTRIBUTION MODELS; CLIMATE-CHANGE; FOREST INVENTORY; INVASION
   SPEEDS; AVAILABILITY; CONTRIBUTES; PREDICTION; COVER
AB Regional scale forest distribution models are important tools for biogeography and understanding the structure of forest communities in space. These models take climate and geographic variables as input and are therefore helpful for long-term decision support and climate adaptation planning. Generally, local processes of tree germination and seedling survival are resolved probabilistically with explanatory variables such as elevation, latitude, exposure, soil type, moisture availability, climate and weather inputs and 'trained' using landscape and regional presence-absence data and machine learning techniques. How seeds are distributed in these models, that is, determining the dispersal kernel, is far more problematic. The challenge is that variables conditioning vertebrate seed dispersal (motility and probability of utilization or caching in response to cover type) are not represented in large scale distribution models, and in fact vary on scales (10-100 meters) that are much smaller than the smallest pixel size for the distribution model (1-10 kilometers). We present a homogenized seed digestion kernel (HSDK) which incorporates this scale separation. Homogenization naturally links highly variable small-scale processes (like seed foraging and caching by birds and rodents) with large scale effects (like dispersal of seeds over tens of kilometers). We develop a homogenization strategy to predict seed dispersal on landscape scales, analytically linking small-scale variables (landscape fraction cover by tree type, gut residence times and cover type utilization by frugivorous birds) with large scale behaviors. Closed form approximations are developed in two dimensions for two limiting cases of seed handling behavior, and the approach is illustrated using landscape data and pinon-pine dispersal in a 630,000 square kilometer region in the southwestern US. (C) 2021 Elsevier Inc. All rights reserved.
C1 [Neupane, Ram C.] Texas A&M Univ Texarkana, Dept Math, 7101 Univ Ave, Texarkana, TX 75503 USA.
   [Powell, James A.] Utah State Univ, Dept Math & Stat, 3900 Old Main Hill, Logan, UT 84322 USA.
   [Edwards, Thomas C.] Utah State Univ, US Geol Survey, 5200 Old Main Hill, Logan, UT 84322 USA.
   [Edwards, Thomas C.] Utah State Univ, Dept Wildland Resources, 5200 Old Main Hill, Logan, UT 84322 USA.
C3 Texas A&M University System; Texas A&M University Texarkana; Utah System
   of Higher Education; Utah State University; Utah System of Higher
   Education; Utah State University; United States Department of the
   Interior; United States Geological Survey; Utah System of Higher
   Education; Utah State University
RP Neupane, RC (corresponding author), Texas A&M Univ Texarkana, Dept Math & Stat, 7101 Univ Ave, Texarkana, TX 75503 USA.
EM ram.neupane@tamut.edu
OI Neupane, Ram/0009-0002-3130-4130
FU US National Science Foundation [1614526]; Division Of Mathematical
   Sciences; Direct For Mathematical & Physical Scien [1614526] Funding
   Source: National Science Foundation
FX The authors wish to acknowledge support by US National Science
   Foundation grant #1614526. Comments by two anonymous reviewers and M.J.
   Garlick were helpful in improving the manuscript.
CR [Anonymous], 2013, GEN TECHNICAL REPORT
   Araújo MB, 2006, J BIOGEOGR, V33, P1677, DOI 10.1111/j.1365-2699.2006.01584.x
   Austin MP, 2011, J BIOGEOGR, V38, P1, DOI 10.1111/j.1365-2699.2010.02416.x
   Barbet-Massin M, 2014, DIVERS DISTRIB, V20, P1285, DOI 10.1111/ddi.12229
   Carlo TA, 2008, J ECOL, V96, P609, DOI 10.1111/j.1365-2745.2008.01379.x
   Carlo TA, 2013, ECOLOGY, V94, P301, DOI 10.1890/12-0913.1
   Casella G., 2001, Statistical Inference
   Cayuela H, 2018, MOL ECOL, V27, P3976, DOI 10.1111/mec.14848
   Clark JS, 1999, ECOLOGY, V80, P1475, DOI 10.2307/176541
   Coops NC, 2012, REMOTE SENS ENVIRON, V126, P160, DOI 10.1016/j.rse.2012.08.024
   Duncan JP, 2017, THEOR ECOL-NETH, V10, P287, DOI 10.1007/s12080-017-0329-0
   Elith J, 2009, ANNU REV ECOL EVOL S, V40, P677, DOI 10.1146/annurev.ecolsys.110308.120159
   Farber DH, 2019, J BIOGEOGR, V46, P2042, DOI 10.1111/jbi.13642
   Fraser KC, 2018, FRONT ECOL EVOL, V6, DOI 10.3389/fevo.2018.00150
   García D, 2011, ECOL MONOGR, V81, P103, DOI 10.1890/10-0470.1
   Garlick MJ, 2011, B MATH BIOL, V73, P2088, DOI 10.1007/s11538-010-9612-6
   Gibson J, 2014, ECOSYSTEMS, V17, P43, DOI 10.1007/s10021-013-9703-y
   GLYPHIS JP, 1981, OECOLOGIA, V48, P138, DOI 10.1007/BF00347002
   Gosper CR, 2005, DIVERS DISTRIB, V11, P549, DOI 10.1111/j.1366-9516.2005.00195.x
   Guisan A, 2005, ECOL LETT, V8, P993, DOI 10.1111/j.1461-0248.2005.00792.x
   Herrera JM, 2011, J ECOL, V99, P1100, DOI 10.1111/j.1365-2745.2011.01861.x
   Holmes M, 1995, Introduction to Perturbation Methods
   Homer C. H., 2012, US Geological Survey Fact Sheet, P1
   Howe H.F., 1986, P123
   HOWE HF, 1982, ANNU REV ECOL SYST, V13, P201, DOI 10.1146/annurev.es.13.110182.001221
   Jeffers R.M, 1995, DESIRED FUTURE CONDI, P191
   Jones LR, 2017, ECOL EVOL, V7, P5410, DOI 10.1002/ece3.3113
   Lobo JM, 2010, ECOGRAPHY, V33, P103, DOI 10.1111/j.1600-0587.2009.06039.x
   Luoto M, 2007, GLOBAL ECOL BIOGEOGR, V16, P34, DOI 10.1111/j.1466-8238.2006.00262.x
   Mathys A, 2014, FOREST ECOL MANAG, V313, P144, DOI 10.1016/j.foreco.2013.11.005
   Mckenney DW, 2007, BIOSCIENCE, V57, P939, DOI 10.1641/B571106
   Menke SB, 2009, GLOBAL ECOL BIOGEOGR, V18, P50, DOI 10.1111/j.1466-8238.2008.00420.x
   Nathan R, 2012, DISPERSAL ECOLOGY AND EVOLUTION, P187
   NEUBERT MG, 1995, THEOR POPUL BIOL, V48, P7, DOI 10.1006/tpbi.1995.1020
   Neupane R.C., 2015, Applied Mathematics, V6, P1506, DOI [DOI 10.4236/AM.2015.69135, 10.4236/am.2015.69135]
   Neupane RC, 2015, J THEOR BIOL, V387, P111, DOI 10.1016/j.jtbi.2015.09.029
   Peterman W, 2013, ECOHYDROLOGY, V6, P455, DOI 10.1002/eco.1284
   Powell JA, 2004, ECOLOGY, V85, P490, DOI 10.1890/02-0535
   Renne IJ, 2002, DIVERS DISTRIB, V8, P285, DOI 10.1046/j.1472-4642.2002.00150.x
   Rogers HS, 2019, AOB PLANTS, V11, DOI 10.1093/aobpla/plz042
   Sánchez-Fernández D, 2011, DIVERS DISTRIB, V17, P163, DOI 10.1111/j.1472-4642.2010.00716.x
   Schupp EW, 2010, NEW PHYTOL, V188, P333, DOI 10.1111/j.1469-8137.2010.03402.x
   Syphard AD, 2009, ECOGRAPHY, V32, P907, DOI 10.1111/j.1600-0587.2009.05883.x
   Tinkham WT, 2018, CAN J FOREST RES, V48, P1251, DOI 10.1139/cjfr-2018-0196
   Turchin Peter, 1998
   VANDERWALL SB, 1977, ECOL MONOGR, V47, P89, DOI 10.2307/1942225
   Wiens JA, 2009, P NATL ACAD SCI USA, V106, P19729, DOI 10.1073/pnas.0901639106
NR 47
TC 1
Z9 1
U1 1
U2 1
PU ELSEVIER SCIENCE INC
PI NEW YORK
PA STE 800, 230 PARK AVE, NEW YORK, NY 10169 USA
SN 0096-3003
EI 1873-5649
J9 APPL MATH COMPUT
JI Appl. Math. Comput.
PD JAN 1
PY 2022
VL 412
AR 126591
DI 10.1016/j.amc.2021.126591
EA AUG 2021
PG 17
WC Mathematics, Applied
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Mathematics
GA US0VH
UT WOS:000697154500033
OA Bronze
DA 2025-01-10
ER

PT J
AU Fischer, LJ
   Wernli, H
   Bresch, DN
AF Fischer, Luise J.
   Wernli, Heini
   Bresch, David N.
TI Widening the common space to reduce the gap between climate science and
   decision-making in industry
SO CLIMATE SERVICES
LA English
DT Article
DE Research-practice collaboration; Transdisciplinary; Hydropower;
   Usability gap; Decision-making; Climate change
ID TRANSDISCIPLINARY RESEARCH; NORTH-ATLANTIC; COPRODUCTION; INFORMATION;
   KNOWLEDGE; OSCILLATION; SCIENTISTS; USABILITY; FORECASTS
AB Climate change impacts lead to risks for natural and human systems. Climate sensitive decision-making in companies is vital to addressing the urgent need for making societies resilient to climate change and entailed risks. Providing and using state-of-the-art scientific knowledge in decision-making, an integral aspect of climate services, poses great challenges for climate scientists and decision-makers. This article aims to contribute to more informed decision-making processes in climate adaptation by addressing the question "How can climate scientists practically implement a transdisciplinary (TD) collaboration with an industry partner to reduce the gap between climate science and decision-making in industry?". We present an engagement framework that provides guidance to address this question. This framework conceptualizes the engagement using two spheres of interests offering the opportunity to explore and widen their overlap as a common space. We present a case study where we apply this framework to a TD collaboration for climate service provision with a Swiss hydropower industry stakeholder; leading to four practical recommendations for effectively using the proposed framework: (1) Secure an anchor person at management level of the decision-maker entity, (2) Be prepared to invest time into triggering and maintaining active engagement by all collaborators, (3) From the start, communicate the open nature of insights and solutions from the engagement process, (4) Be aware that you are working in a field of tension. The presented engagement framework and practical recommendations are particularly beneficial for climate scientists that are not yet familiar with TD collaborations and enables co-development of bespoke climate services.
C1 [Fischer, Luise J.; Bresch, David N.] Swiss Fed Inst Technol, Inst Environm Decis, Zurich, Switzerland.
   [Fischer, Luise J.; Wernli, Heini] Swiss Fed Inst Technol, Inst Atmospher & Climate Sci, Zurich, Switzerland.
   [Bresch, David N.] Fed Off Meteorol & Climatol MeteoSwiss, Zurich, Switzerland.
C3 Swiss Federal Institutes of Technology Domain; ETH Zurich; Swiss Federal
   Institutes of Technology Domain; ETH Zurich; Federal Office of
   Meteorology & Climatology (MeteoSwiss)
RP Fischer, LJ (corresponding author), Swiss Fed Inst Technol, Inst Environm Decis, Zurich, Switzerland.
EM luise.fischer@usys.ethz.ch
RI Bresch, David/D-5298-2018; Wernli, Heini/F-1099-2016
OI Fischer, Luise/0000-0001-9720-447X; Wernli, Heini/0000-0001-9674-4837
CR [Anonymous], 2008, HDB TRANSDISCIPLINAR
   [Anonymous], 2013, KNOWL MANAG DEV J, DOI [10.1093/oso/9780198792154.003.0009, DOI 10.1093/OSO/9780198792154.003.0009]
   [Anonymous], 2014, CLIM CHANG 2014 IMP
   Barsugli J.J., 2013, Eos Trans. Am. Geophys. Union, V94, P424, DOI DOI 10.1002/2013EO460005
   Beier P, 2017, CONSERV LETT, V10, P288, DOI 10.1111/conl.12300
   Bergmann M., 2012, Methods for transdisciplinary research
   Bremer S, 2019, CLIM SERV, V13, P42, DOI 10.1016/j.cliser.2019.01.003
   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
   Buontempo C, 2018, CLIM SERV, V9, P1, DOI 10.1016/j.cliser.2017.06.011
   Carew AL, 2010, FUTURES, V42, P1146, DOI 10.1016/j.futures.2010.04.025
   Cash D., 2002, FACULTY RES WORKING
   Cash DW, 2006, SCI TECHNOL HUM VAL, V31, P465, DOI 10.1177/0162243906287547
   Cassou C, 2008, NATURE, V455, P523, DOI 10.1038/nature07286
   Daniels E, 2020, CLIM SERV, V19, DOI 10.1016/j.cliser.2020.100181
   de Fontaine A., 2008, ADAPTING CLIMATE CHA
   Dee DP, 2011, Q J ROY METEOR SOC, V137, P553, DOI 10.1002/qj.828
   Dessai S, 2009, ADAPTING TO CLIMATE CHANGE: THRESHOLDS, VALUES, GOVERNANCE, P64
   Dilling L, 2011, GLOBAL ENVIRON CHANG, V21, P680, DOI 10.1016/j.gloenvcha.2010.11.006
   Feldman DL, 2009, WEATHER CLIM SOC, V1, P9, DOI 10.1175/2009WCAS1007.1
   Fundel VJ, 2019, Q J ROY METEOR SOC, V145, P210, DOI 10.1002/qj.3482
   Gaziulusoy AI, 2016, J CLEAN PROD, V123, P55, DOI 10.1016/j.jclepro.2015.08.049
   Gaziulusoy AI, 2013, J CLEAN PROD, V48, P139, DOI 10.1016/j.jclepro.2012.04.013
   Grams CM, 2017, NAT CLIM CHANGE, V7, P557, DOI [10.1038/nclimate3338, 10.1038/NCLIMATE3338]
   Hadorn GH, 2006, ECOL ECON, V60, P119, DOI 10.1016/j.ecolecon.2005.12.002
   Harris F, 2013, ENVIRON SCI POLICY, V31, P109, DOI 10.1016/j.envsci.2013.02.006
   Hewitt C, 2012, NAT CLIM CHANGE, V2, P831, DOI 10.1038/nclimate1745
   IEA, 2020, OV EL INF
   IPCC, 2018, GLOB WARM 1 5C SUMM
   Jacob D., 2015, A European Research and Innovation Roadmap for Climate Services
   Jahn T, 2012, ECOL ECON, V79, P1, DOI 10.1016/j.ecolecon.2012.04.017
   Jasanoff S., 1998, HUMAN CHOICE CLIMATE, V1, P1
   Kalafatis SE, 2019, WEATHER CLIM SOC, V11, P113, DOI 10.1175/WCAS-D-17-0115.1
   Keele S, 2019, CLIMATIC CHANGE, V157, P9, DOI 10.1007/s10584-019-02385-x
   Kirchhoff CJ, 2013, ANNU REV ENV RESOUR, V38, P393, DOI 10.1146/annurev-environ-022112-112828
   Klein Julie Thompson., 2010, The Oxford Handbook of Interdisciplinarity, V15
   Lang DJ, 2012, SUSTAIN SCI, V7, P25, DOI 10.1007/s11625-011-0149-x
   Leal W, 2020, CLIM CHANG MANAG, P3, DOI 10.1007/978-3-030-36875-3_1
   Lemos MC, 2014, WEATHER CLIM SOC, V6, P273, DOI 10.1175/WCAS-D-13-00044.1
   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
   Lourenço TC, 2016, NAT CLIM CHANGE, V6, P13, DOI 10.1038/nclimate2836
   Meadow AM, 2015, WEATHER CLIM SOC, V7, P179, DOI 10.1175/WCAS-D-14-00050.1
   Parker WS, 2019, B AM METEOROL SOC, V100, P1643, DOI 10.1175/BAMS-D-17-0325.1
   Pohl C., 2007, Principles for Designing Transdisciplinary Research
   Pohl C, 2017, GAIA, V26, P43, DOI 10.14512/gaia.26.1.10
   Porter JJ, 2017, ENVIRON SCI POLICY, V77, P9, DOI 10.1016/j.envsci.2017.07.004
   Raaphorst K, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12041512
   Schuck-Zöller S, 2018, SPRINGER CLIMATE, P105, DOI 10.1007/978-3-319-74669-2_8
   Singletary L, 2020, CLIM SERV, V20, DOI 10.1016/j.cliser.2020.100201
   Skelton M, 2019, CLIM SERV, V15, DOI 10.1016/j.cliser.2019.100113
   Swiss Federal Office of Energy SFOE, 2018, HYDR
   UVEK, 2017, ERSTES MASSNAHMENPAK
   van den Hurk B, 2018, CLIM SERV, V12, P59, DOI 10.1016/j.cliser.2018.11.002
   Vaughan C, 2014, WIRES CLIM CHANGE, V5, P587, DOI 10.1002/wcc.290
   VAUTARD R, 1990, MON WEATHER REV, V118, P2056, DOI 10.1175/1520-0493(1990)118<2056:MWROTN>2.0.CO;2
   Vincent K, 2018, CLIM SERV, V12, P48, DOI 10.1016/j.cliser.2018.11.001
   Vogel AL, 2013, AM J PREV MED, V45, P787, DOI 10.1016/j.amepre.2013.09.001
NR 58
TC 9
Z9 9
U1 0
U2 4
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2405-8807
J9 CLIM SERV
JI Clim. Serv.
PD AUG
PY 2021
VL 23
AR 100237
DI 10.1016/j.cliser.2021.100237
EA JUN 2021
PG 13
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 WB6BV
UT WOS:000703656300005
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Liu, L
   Basso, B
AF Liu, Lin
   Basso, Bruno
TI Impacts of climate variability and adaptation strategies on crop yields
   and soil organic carbon in the US Midwest
SO PLOS ONE
LA English
DT Article
ID NO-TILL; CORN; MODEL; MANAGEMENT; TERM; PRODUCTIVITY; TEMPERATURE;
   SENSITIVITY; RESPONSES; ROTATION
AB Climate change is likely to increase the frequency of drought and more extreme precipitation events. The objectives of this study were i) to assess the impact of extended drought followed by heavy precipitation events on yield and soil organic carbon (SOC) under historical and future climate, and ii) to evaluate the effectiveness of climate adaptation strategies (no-tillage and new cultivars) in mitigating impacts of increased frequencies of extreme events and warming. We used the validated SALUS crop model to simulate long-term maize and wheat yield and SOC changes of maize-soybean-wheat rotation cropping systems in the northern Midwest USA under conventional tillage and no-till for three climate change scenarios (one historical and two projected climates under the Representative Concentration Path (RCP) 4.5 and RCP6) and two precipitation changes (extreme precipitation occurring early or late season). Extended drought events caused additional yield reduction when they occurred later in the season (10-22% for maize and 5-13% for wheat) rather than in early season (5-17% for maize and 2-18% for wheat). We found maize grain yield declined under the projected climates, whereas wheat grain yield increased. No-tillage is able to reduce yield loss compared to conventional tillage and increased SOC levels (1.4-2.0 t/ha under the three climates), but could not reverse the adverse impact of climate change, unless early and new improved maize cultivars are introduced to increase yield and SOC under climate change. This study demonstrated the need to consider extreme weather events, particularly drought and extreme precipitation events, in climate impact assessment on crop yield and adaptation through no-tillage and new genetics reduces yield losses.
C1 [Liu, Lin; Basso, Bruno] Michigan State Univ, Dept Earth & Environm Sci, E Lansing, MI 48824 USA.
   [Basso, Bruno] Michigan State Univ, WK Kellogg Biol Stn, E Lansing, MI 48824 USA.
C3 Michigan State University; Michigan State University
RP Basso, B (corresponding author), Michigan State Univ, Dept Earth & Environm Sci, E Lansing, MI 48824 USA.; Basso, B (corresponding author), Michigan State Univ, WK Kellogg Biol Stn, E Lansing, MI 48824 USA.
EM basso@msu.edu
RI Basso, Bruno/AAF-1271-2019; Liu, Lin/ABC-6165-2020; Basso,
   Bruno/A-3128-2012
OI Basso, Bruno/0000-0003-2090-4616
FU US Department of Agriculture National Institute of Food and Agriculture
   [2015-6800723133]; U.S. National Science Foundation's Dynamics of
   Coupled Natural and Human Systems Program [1313677]; NSF's Kellogg
   Biological Station Long Term Ecological Research Site (NSF) [DEB
   1027253]; Environmental Science and Policy Program at Michigan State
   University; Michigan State University AgBioResearch; USDA/NIFA HATCH
   [MCL02368]; Direct For Biological Sciences; Division Of Environmental
   Biology [1313677] Funding Source: National Science Foundation
FX This work was partially funded by US Department of Agriculture National
   Institute of Food and Agriculture (award no. 2015-6800723133) to BB,
   U.S. National Science Foundation's Dynamics of Coupled Natural and Human
   Systems Program (award 1313677) to BB, with additional support from
   NSF's Kellogg Biological Station Long Term Ecological Research Site (NSF
   grant no. DEB 1027253); the Environmental Science and Policy Program at
   Michigan State University, and Michigan State University AgBioResearch
   and USDA/NIFA HATCH grant N. MCL02368 to BB.
CR [Anonymous], 2014, CLIMATE CHANGE IMPAC
   [Anonymous], 2011, CLIMATIC CHANGE, DOI DOI 10.1007/s10584-011-0157-y
   [Anonymous], FARMING ECOSYSTEM SE
   [Anonymous], 2014, NATL CLIMATE ASSESSM
   [Anonymous], SOIL WATER BALANCE P
   [Anonymous], 1995, KELLOGG BIOL STATION
   Asseng S, 2017, GLOBAL CHANGE BIOL, V23, P2464, DOI 10.1111/gcb.13530
   Balesdent J, 2000, SOIL TILL RES, V53, P215, DOI 10.1016/S0167-1987(99)00107-5
   Basso B, 2018, AGR ENV LETT, V3, DOI 10.2134/ael2018.05.0026
   Basso B., 2006, Italian Journal of Agronomy, V1, P677
   Basso B., 2015, The Ecology of Agricultural Landscapes: Long-Term Research on the Path to Sustainability, P252
   Basso B, 2018, AGR ENV LETT, V3, DOI 10.2134/ael2017.11.0039
   Basso B, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0127333
   Basso B, 2012, VADOSE ZONE J, V11, DOI 10.2136/vzj2011.0173
   Basso B, 2011, SOIL SCI SOC AM J, V75, P69, DOI 10.2136/sssaj2010.0115
   Bassu S, 2014, GLOBAL CHANGE BIOL, V20, P2301, DOI 10.1111/gcb.12520
   Brouder SM, 2014, AGR ECOSYST ENVIRON, V187, P11, DOI 10.1016/j.agee.2013.08.010
   Busari MA, 2015, INT SOIL WATER CONSE, V3, P119, DOI 10.1016/j.iswcr.2015.05.002
   Crawley H, 2018, POL PRESS SHORT, P29
   Dai SW, 2016, INT J CLIMATOL, V36, P517, DOI 10.1002/joc.4354
   Davidson EA, 2006, NATURE, V440, P165, DOI 10.1038/nature04514
   Derpsch Rolf, 2010, International Journal of Agricultural and Biological Engineering, V3, P1, DOI 10.3965/j.issn.1934-6344.2010.01.001-025
   Derpsch R., 2008, NO TILL FARMING SYST, V3, P7
   Doll JE, 2017, WEATHER CLIM SOC, V9, P739, DOI 10.1175/WCAS-D-16-0110.1
   Dzotsi KA, 2013, ECOL MODEL, V260, P62, DOI 10.1016/j.ecolmodel.2013.03.017
   Fischer EM, 2013, NAT CLIM CHANGE, V3, P1033, DOI [10.1038/NCLIMATE2051, 10.1038/nclimate2051]
   Friedlingstein P, 2006, J CLIMATE, V19, P3337, DOI 10.1175/JCLI3800.1
   Fung IY, 2005, P NATL ACAD SCI USA, V102, P11201, DOI 10.1073/pnas.0504949102
   Giller KE, 2015, FRONT PLANT SCI, V6, DOI 10.3389/fpls.2015.00870
   Halvorson AD, 2002, AGRON J, V94, P1429, DOI 10.2134/agronj2002.1429
   Hatfield JL, 2018, CLIMATIC CHANGE, V146, P263, DOI 10.1007/s10584-017-1997-x
   Huggins DR, 2008, SCI AM, V299, P70, DOI 10.1038/scientificamerican0708-70
   ISMAIL I, 1994, SOIL SCI SOC AM J, V58, P193, DOI 10.2136/sssaj1994.03615995005800010028x
   Jones JW, 2017, AGR SYST, V155, P240, DOI 10.1016/j.agsy.2016.05.014
   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, 2015, J SOIL WATER CONSERV, V70, p55A, DOI 10.2489/jswc.70.3.55A
   Lesk C, 2016, NATURE, V529, P84, DOI 10.1038/nature16467
   Liu L, 2017, GCB BIOENERGY, V9, P1320, DOI 10.1111/gcbb.12417
   Lobell DB, 2011, SCIENCE, V333, P616, DOI [10.1126/science.1206376, 10.1126/science.1204531]
   NESMITH DS, 1992, AGRON J, V84, P107, DOI 10.2134/agronj1992.00021962008400010021x
   Ogle SM, 2012, AGR ECOSYST ENVIRON, V149, P37, DOI 10.1016/j.agee.2011.12.010
   Pathak P, 2017, INT J WATER RESOUR D, V33, P1003, DOI 10.1080/07900627.2016.1238343
   Paustian KA., 1995, ADV SOIL SCI, P75
   Pittelkow CM, 2015, FIELD CROP RES, V183, P156, DOI 10.1016/j.fcr.2015.07.020
   Porter JR, 2005, PHILOS T R SOC B, V360, P2021, DOI 10.1098/rstb.2005.1752
   Raats M. M., 1992, Food Quality and Preference, V3, P89, DOI 10.1016/0950-3293(91)90028-D
   Rasmussen DJ, 2016, J APPL METEOROL CLIM, V55, P2301, DOI 10.1175/JAMC-D-15-0302.1
   Riha SJ, 1996, CLIMATIC CHANGE, V32, P293, DOI 10.1007/BF00142466
   Ritchie JT, 1998, SYST APPR S, V7, P79
   Robertson G.P., 2015, The ecology of agricultural landscapes: Longterm research on the path to sustainability, P1
   Rötter RP, 2018, FIELD CROP RES, V221, P142, DOI 10.1016/j.fcr.2018.02.023
   Sacks WJ, 2011, AGR FOREST METEOROL, V151, P882, DOI 10.1016/j.agrformet.2011.02.010
   Semenov MA, 1997, CLIMATIC CHANGE, V35, P397, DOI 10.1023/A:1005342632279
   Senthilkumar S, 2009, SOIL SCI SOC AM J, V73, P2078, DOI 10.2136/sssaj2009.0044
   Sindelar AJ, 2015, AGRON J, V107, P2241, DOI 10.2134/agronj15.0085
   Six J, 2004, GLOBAL CHANGE BIOL, V10, P155, DOI 10.1111/j.1529-8817.2003.00730.x
   Skaalsveen K, 2019, SOIL TILL RES, V189, P98, DOI 10.1016/j.still.2019.01.004
   Southworth J, 2000, AGR ECOSYST ENVIRON, V82, P139, DOI 10.1016/S0167-8809(00)00223-1
   Suleiman AA, 2003, SOIL SCI SOC AM J, V67, P377, DOI 10.2136/sssaj2003.0377
   Turmel MS, 2015, AGR SYST, V134, P6, DOI 10.1016/j.agsy.2014.05.009
   Westgate ME, 2011, CROP ADAPTATION TO CLIMATE CHANGE, P314
   Wiesmeier M, 2016, SCI REP-UK, V6, DOI 10.1038/srep32525
   Wuebbles Donald J., 2014, Eos, Transactions American Geophysical Union, V95, P149, DOI 10.1002/2014EO180001
NR 64
TC 46
Z9 53
U1 10
U2 55
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 JAN 28
PY 2020
VL 15
IS 1
AR e0225433
DI 10.1371/journal.pone.0225433
PG 20
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA LP8ZJ
UT WOS:000534605400007
PM 31990907
OA Green Published, Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Landman, WA
   Barnston, AG
   Vogel, C
   Savy, J
AF Landman, Willem A.
   Barnston, Anthony G.
   Vogel, Coleen
   Savy, Janique
TI Use of El Nino-Southern Oscillation related seasonal precipitation
   predictability in developing regions for potential societal benefit
SO INTERNATIONAL JOURNAL OF CLIMATOLOGY
LA English
DT Article
DE collaboration; emerging economies; ENSO; human development; seasonal
   climate modelling; skill
ID RAINFALL FORECASTS; MAKING LESSONS; CLIMATE; PREDICTION; AFRICA; RISK;
   INFORMATION; TEMPERATURE; COMBINATION; ANOMALIES
AB Some of the biggest emerging market economies include countries in South America, Asia and Africa. Broad-scale political and developmental similarities (e.g., societally impactful developmental challenges related to climate variability) offer opportunities for comparative research resulting in potentially improved understanding of the complexities of various climate adaptation interventions including disaster risk reduction. Countries or geographical regions of the world significantly affected by climate extremes may consider collaboration on issues such as understanding and modelling of the climate system, especially when there is a common, dominant and somewhat plausible climate mode such as the El Nino-Southern Oscillation (ENSO) affecting the regions' climate variability. Better ENSO and subsequent climate predictions alone, however, are not enough to reduce the risks associated with such events. The socio-economic and political context in which climate finds expression and in which climate forecasts have potential value also need to be understood. Here we present seasonal precipitation forecast skill over 20 geographical regions including emerging or developing regions, but also a few developed regions, in order to rank their ENSO-related seasonal rainfall predictability in an attempt to cluster regions of similar ENSO climate predictability. We then also provide some of the broad contours to investigate the level of human "development" within these clusters in order to begin to understand some of the socio-economic factors that configure vulnerabilities. Such profiles begin to show some areas of macro-level vulnerability that may then provide further possible inter-area collaborations, albeit at very gross level scales.
C1 [Landman, Willem A.; Savy, Janique] Univ Pretoria, Dept Geog Geoinformat & Meteorol, Pretoria, South Africa.
   [Barnston, Anthony G.] Columbia Univ, Earth Inst, Int Res Inst Climate & Soc, New York, NY USA.
   [Vogel, Coleen] Univ Witwatersrand, Global Change Inst, Johannesburg, South Africa.
C3 University of Pretoria; Columbia University; University of Witwatersrand
RP Landman, WA (corresponding author), Univ Pretoria, Dept Geog Geoinformat & Meteorol, Pretoria, South Africa.
EM willem.landman@up.ac.za
RI Landman, Willem/JVN-5114-2024; Barnston, Anthony/AHB-2825-2022
CR [Anonymous], 2002, Late Victorian holocausts: El Nino famines and the making of the third world
   [Anonymous], NAT RESOUR PERSPECT
   Archer ERM, 2017, CLIM RISK MANAG, V16, P22, DOI 10.1016/j.crm.2017.03.006
   Barnston AG, 2019, CLIM DYNAM, V53, P7215, DOI 10.1007/s00382-017-3603-3
   Barnston AG, 2010, J APPL METEOROL CLIM, V49, P493, DOI 10.1175/2009JAMC2325.1
   Beraki AF, 2015, J GEOPHYS RES-ATMOS, V120, P11151, DOI 10.1002/2015JD023839
   BRADLEY RS, 1987, NATURE, V327, P497, DOI 10.1038/327497a0
   Braman LM, 2013, DISASTERS, V37, P144, DOI 10.1111/j.1467-7717.2012.01297.x
   Bremer S, 2019, CLIM SERV, V13, P42, DOI 10.1016/j.cliser.2019.01.003
   Chowdhury O H, 1991, Bangladesh Dev Stud, V19, P125
   Conway D, 2017, NAT ENERGY, V2, P946, DOI 10.1038/s41560-017-0037-4
   Daly M, 2018, WEATHER CLIM SOC, V10, P693, DOI 10.1175/WCAS-D-18-0015.1
   Dewitt DG, 2005, MON WEATHER REV, V133, P2972, DOI 10.1175/MWR3016.1
   Dilling L, 2011, GLOBAL ENVIRON CHANG, V21, P680, DOI 10.1016/j.gloenvcha.2010.11.006
   Doblas-Reyes FJ, 2013, WIRES CLIM CHANGE, V4, P245, DOI 10.1002/wcc.217
   Eakin H, 2000, CLIMATIC CHANGE, V45, P19, DOI 10.1023/A:1005628631627
   Engelbrecht FA, 2011, WATER SA, V37, P647, DOI 10.4314/wsa.v37i5.2
   Fioramonti L., 2017, Wellbeing Economy: Success in a world with growth
   Gamoyo M, 2015, THEOR APPL CLIMATOL, V120, P311, DOI 10.1007/s00704-014-1171-6
   Grimm AM, 2015, J CLIMATE, V28, P9489, DOI 10.1175/JCLI-D-15-0116.1
   Grimm AM, 2011, J CLIMATE, V24, P1226, DOI 10.1175/2010JCLI3722.1
   Harris I, 2014, INT J CLIMATOL, V34, P623, DOI 10.1002/joc.3711
   Kiem AS, 2013, CLIM RES, V58, P29, DOI 10.3354/cr01181
   Kiem AS, 2011, WATER RESOUR RES, V47, DOI 10.1029/2010WR009803
   Kijazi AL, 2012, INT J CLIMATOL, V32, P874, DOI 10.1002/joc.2315
   Kirtman BP, 2014, B AM METEOROL SOC, V95, P585, DOI 10.1175/BAMS-D-12-00050.1
   LANDMAN W., 2014, Earth Perspectives, V1, P1, DOI DOI 10.1186/2194-6434-1-22
   Landman W. A., 2014, WCRP C LAT AM CAR DE
   Landman WA, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL022910
   Landman WA, 2018, THEOR APPL CLIMATOL, V0132
   Landman WA, 2014, WATER SA, V40, P615, DOI 10.4314/wsa.v40i4.6
   Landman WA, 2012, WEATHER FORECAST, V27, P489, DOI 10.1175/WAF-D-11-00078.1
   Landman WA, 2012, INT J CLIMATOL, V32, P303, DOI 10.1002/joc.2273
   Lemos MC, 2012, NAT CLIM CHANGE, V2, P789, DOI [10.1038/NCLIMATE1614, 10.1038/nclimate1614]
   Lemos MC, 2002, CLIMATIC CHANGE, V55, P479, DOI 10.1023/A:1020785826029
   Malherbe J, 2014, METEOROL APPL, V21, P733, DOI 10.1002/met.1402
   Mason SJ, 2001, B AM METEOROL SOC, V82, P619, DOI 10.1175/1520-0477(2001)082<0619:PPAAWE>2.3.CO;2
   Moron V, 2007, J CLIMATE, V20, P5244, DOI 10.1175/2007JCLI1623.1
   Morss RE, 2005, B AM METEOROL SOC, V86, P1593, DOI 10.1175/BAMS-86-11-1593
   Muchuru S, 2016, INT J CLIMATOL, V36, P2570, DOI 10.1002/joc.4513
   Muchuru S, 2014, WATER SA, V40, P461, DOI 10.4314/wsa.v40i3.9
   Pomposi C, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aacc4c
   Poolman E, 2014, WATER SA, V40, P729, DOI 10.4314/wsa.v40i4.18
   Ratnam JV, 2018, J APPL METEOROL CLIM, V57, P2697, DOI 10.1175/JAMC-D-18-0067.1
   Ratnam JV, 2016, J CLIMATE, V29, P2815, DOI 10.1175/JCLI-D-15-0435.1
   Risbey JS, 2009, MON WEATHER REV, V137, P3233, DOI 10.1175/2009MWR2861.1
   Roncoli C, 2009, CLIMATIC CHANGE, V92, P433, DOI 10.1007/s10584-008-9445-6
   Ropelewski CF, 1989, J CLIMATE, V2, P268, DOI 10.1175/1520-0442(1989)002<0268:PPAWTH>2.0.CO;2
   ROPELEWSKI CF, 1987, MON WEATHER REV, V115, P1606, DOI 10.1175/1520-0493(1987)115<1606:GARSPP>2.0.CO;2
   Sagar AD, 1998, ECOL ECON, V25, P249, DOI 10.1016/S0921-8009(97)00168-7
   Saha S, 2006, J CLIMATE, V19, P3483, DOI 10.1175/JCLI3812.1
   Shirvani A, 2016, INT J CLIMATOL, V36, P1887, DOI 10.1002/joc.4467
   Slater LJ, 2018, GEOPHYS RES LETT, V45, P6504, DOI 10.1029/2018GL077945
   Stockdale TN, 1998, NATURE, V392, P370, DOI 10.1038/32861
   Stuecker MF, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0201426
   Vogel C, 2007, GLOBAL ENVIRON CHANG, V17, P349, DOI 10.1016/j.gloenvcha.2007.05.002
   Wilks D.S., 2011, Statistical Methods in the Atmospheric Sciences, P676
   Yuan CX, 2014, CLIM DYNAM, V42, P3357, DOI 10.1007/s00382-013-1923-5
   Ziervogel G, 2004, CLIMATIC CHANGE, V65, P73, DOI 10.1023/B:CLIM.0000037492.18679.9e
NR 59
TC 15
Z9 16
U1 0
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 NOV 30
PY 2019
VL 39
IS 14
BP 5327
EP 5337
DI 10.1002/joc.6157
PG 11
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Meteorology & Atmospheric Sciences
GA JH6SM
UT WOS:000492898900008
OA Green Submitted
DA 2025-01-10
ER

PT J
AU Koier, E
   Horlings, E
AF Koier, Elizabeth
   Horlings, Edwin
TI How accurately does output reflect the nature and design of
   transdisciplinary research programmes?
SO RESEARCH EVALUATION
LA English
DT Article; Proceedings Paper
CT 18th International Conference on Science and Technology Indicators
   Translational Twists and Turns: Science as a Socio-Economic Endeavor
CY SEP 04-06, 2013
CL Berlin, GERMANY
DE transdisciplinary research; evaluation; bibliometrics; large research
   programmes; Web of science
ID HEALTH RESEARCH; SCIENCE; INTERDISCIPLINARY; POLICY; COMMUNICATION;
   PUBLICATIONS; PERFORMANCE; PROJECTS
AB Many of today's societal problems are wicked problems that require a new, transdisciplinary approach in which knowledge of scientists and stakeholders from different disciplines is integrated. The evaluation of transdisciplinary science requires a multi-method approach. Bibliometric analysis is consistently among the methods in multi-method evaluations. We analyse the accuracy of bibliometric evidence for the evaluation of transdisciplinary research by examining two large climate adaptation research programmes in the Netherlands. The assessment of accuracy involves a comparison of different approaches to defining and measuring involvement, output, and quality. We draw three conclusions with regard to accuracy. First, scientific output covers a fairly high amount of the scientific activities of the programmes, though information on funding agencies is not yet sufficiently accurate to reconstruct a programme's output through the Web of Science (WoS). Second, scientific output does not accurately reflect the nature and design of the programmes. The WoS appears to underestimate locally oriented and practically oriented research, non-academic actors rarely co-author scientific publications, and the contributions of non-academic organizations to projects could not be recognized from author affiliations. Third, our exploration of two alternative reproducible metrics (non-scientific output and download statistics) shows that it is too early to introduce such metrics into evaluation practices. The research agenda for transdisciplinary output metrics should focus on the development of a common definition of transdisciplinary research output and a typology of non-scientific outputs, as well as a discussion and assessment of the relative value of such outputs for the integration of knowledge.
C1 [Koier, Elizabeth; Horlings, Edwin] Rathenau Inst, Sci Syst Assessment Dept, NL-2593 HW The Hague, Netherlands.
C3 Royal Netherlands Academy of Arts & Sciences; Rathenau Institute (KNAW)
RP Koier, E (corresponding author), Rathenau Inst, Sci Syst Assessment Dept, Anna van Saksenlaan 51, NL-2593 HW The Hague, Netherlands.
EM e.koier@rathenau.nl
RI Horlings, Edwin/J-9279-2013
OI Horlings, Edwin/0000-0001-7787-8813
FU Dutch national research programme Knowledge for Climate [SSA01];
   Ministry of Infrastructure and the Environment
FX This work was supported by the Dutch national research programme
   Knowledge for Climate [grant number SSA01] (www.knowledgeforclimate.
   org). This work was part of a meta-project to monitor the organization,
   effects, and impacts of the programme called Comparative Monitoring of
   Knowledge for Climate. The Knowledge for Climate research programme is
   co-financed by the Ministry of Infrastructure and the Environment.
CR Abramo G, 2010, SCIENTOMETRICS, V84, P173, DOI 10.1007/s11192-009-0104-0
   [Anonymous], 2011, Altmetrics: A Manifesto
   [Anonymous], POLICY RES, DOI DOI 10.1016/0048-7333(94)01002-1
   [Anonymous], 2012, ARCH REV
   [Anonymous], 2008, Nat Sci Soc, DOI DOI 10.1051/NSS:2008035
   [Anonymous], P WEBSCI10 EXT FRONT
   Braam R, 2010, RES EVALUAT, V19, P173, DOI 10.3152/095820210X503465
   Breschi S, 2008, EUR MANAG REV, V5, P91, DOI 10.1057/emr.2008.9
   Choi BCK, 2006, CLIN INVEST MED, V29, P351
   Costas R, 2012, J AM SOC INF SCI TEC, V63, P1647, DOI 10.1002/asi.22692
   de Jong SPL, 2011, RES EVALUAT, V20, P61, DOI 10.3152/095820211X12941371876346
   European Commission, 2011, COM2011808
   FUNTOWICZ SO, 1993, FUTURES, V25, P739, DOI 10.1016/0016-3287(93)90022-L
   Geuna A, 2003, MINERVA, V41, P277, DOI 10.1023/B:MINE.0000005155.70870.bd
   Geuna A, 2006, RES POLICY, V35, P790, DOI 10.1016/j.respol.2006.04.005
   Guerrero- Bote V. P., 2014, SCIENTOMETRICS, P1
   Hegger D, 2012, ENVIRON SCI POLICY, V18, P52, DOI 10.1016/j.envsci.2012.01.002
   Hessels LK, 2014, RES EVALUAT, V23, P103, DOI 10.1093/reseval/rvu007
   Horlings E, 2013, SCIENTOMETRICS, V94, P1137, DOI 10.1007/s11192-012-0789-3
   Ingwersen P, 2007, RES EVALUAT, V16, P47, DOI 10.3152/095820207X196777
   Klein JT, 2008, AM J PREV MED, V35, pS116, DOI 10.1016/j.amepre.2008.05.010
   Lyall C, 2013, SCI PUBL POLICY, V40, P1, DOI 10.1093/scipol/scs113
   MERTON RK, 1957, AM SOCIOL REV, V22, P635, DOI 10.2307/2089193
   Meyer M, 2006, RES POLICY, V35, P1646, DOI 10.1016/j.respol.2006.09.013
   Pohl C, 2008, ENVIRON SCI POLICY, V11, P46, DOI 10.1016/j.envsci.2007.06.001
   Priem J, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0048753
   Probst C, 2011, RES EVALUAT, V20, P73, DOI 10.3152/095820211X12941371876102
   Rigby J, 2013, SCIENTOMETRICS, V94, P57, DOI 10.1007/s11192-012-0779-5
   Rigby J, 2011, RES EVALUAT, V20, P365, DOI 10.3152/095820211X13164389670392
   ROSENFIELD PL, 1992, SOC SCI MED, V35, P1343, DOI 10.1016/0277-9536(92)90038-R
   Schmoch U, 2010, RES EVALUAT, V19, P2, DOI 10.3152/095820210X492477
   Shuai X, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0047523
   Spaapen J, 2011, RES EVALUAT, V20, P211, DOI 10.3152/095820211X12941371876742
   Spangenberg JH, 2011, ENVIRON CONSERV, V38, P275, DOI 10.1017/S0376892911000270
   Stokols Daniel, 2003, Nicotine Tob Res, V5 Suppl 1, pS21
   Tijssen R. J. W., 2011, EVALUATION HIGHER ED, V12, P19
   van der Weijden I, 2012, SCI PUBL POLICY, V39, P285, DOI 10.1093/scipol/scr003
   Wagner CS, 2012, SCIENTOMETRICS, V90, P1001, DOI 10.1007/s11192-011-0481-z
   Wagner CS, 2011, J INFORMETR, V5, P14, DOI 10.1016/j.joi.2010.06.004
   Walter AI, 2007, EVAL PROGRAM PLANN, V30, P325, DOI 10.1016/j.evalprogplan.2007.08.002
   Wardenaar T., ENV SCI POL IN PRESS
NR 41
TC 20
Z9 21
U1 3
U2 47
PU OXFORD UNIV PRESS
PI OXFORD
PA GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND
SN 0958-2029
EI 1471-5449
J9 RES EVALUAT
JI Res. Evaluat.
PD JAN
PY 2015
VL 24
IS 1
BP 37
EP 50
DI 10.1093/reseval/rvu027
PG 14
WC Information Science & Library Science
WE Social Science Citation Index (SSCI); Conference Proceedings Citation Index - Social Science &amp; Humanities (CPCI-SSH)
SC Information Science & Library Science
GA CC1PW
UT WOS:000350114700005
DA 2025-01-10
ER

PT J
AU Careau, V
   Garant, D
   Humphries, MM
AF Careau, V.
   Garant, D.
   Humphries, M. M.
TI Free-ranging eastern chipmunks (<i>Tamias striatus</i>) infected with
   bot fly (<i>Cuterebra emasculator</i>) larvae have higher resting but
   lower maximum metabolism
SO CANADIAN JOURNAL OF ZOOLOGY
LA English
DT Article
DE aerobic scope; BMR; energetics; heliox; PMR; eastern chipmunk (Tamias
   striatus); summit metabolism; torpor
ID AEROBIC CAPACITY MODEL; OXYGEN-CONSUMPTION; CLIMATIC ADAPTATION;
   ENERGY-METABOLISM; DEER MICE; EVOLUTION; PARASITISM; RATES; BASAL;
   HOMEOTHERMS
AB Given the ubiquity and evolutionary importance of parasites, their effect on the energy budget of mammals remains surprisingly unclear. The eastern chipmunk (Landers striatus (L., 1758)) is a burrowing rodent that is commonly infected by cuterebrid bot fly (Cuterebra emasculator Fitch, 1856) larvae. We measured resting metabolic rate (RMR) and cold-induced Vo(2)-max (under heliox atmosphere) in 20 free-ranging individuals, of which 4 individuals were infected by one or two larva. We found that RMR was significantly higher in chipmunks infected by bot fly larvae (mean +/- SE = 0.88 +/- 0.05 W) than in uninfected individuals (0.74 +/- 0.02 W). In contrast, Vo(2)-max was significantly lower in chipmunks infected by bot fly larvae (4.96 +/- 0.70 W) than in uninfected individuals (6.37 +/- 0.16 W). Consequently, the aerobic scope (ratio of Vo(2)-max to RMR) was negatively correlated with the number of bot fly larvae (infected individuals = 5.74 +/- 1.03 W; noninfected individuals = 8.67 +/- 0.26 W). Finally, after accounting for the effects of body mass and bot fly parasitism on RMR and Vo(2)-max, there was no correlation between the two variables among individuals within our population. In addition to providing the first estimate of Vo(2)-max in T striatus, these results offer additional evidence that bot fly parasitism has significant impacts on the metabolic ecology of this host species.
C1 [Careau, V.; Garant, D.] Univ Sherbrooke, Dept Biol, Sherbrooke, PQ J1K 2R1, Canada.
   [Humphries, M. M.] McGill Univ, Quebec City, PQ H9X 3V9, Canada.
C3 University of Sherbrooke; McGill University
RP Careau, V (corresponding author), Univ Calif Riverside, Dept Biol, Riverside, CA 92521 USA.
EM vcareau@ucr.edu
RI Careau, Vincent/A-9778-2008; Garant, Dany/D-7406-2013
OI Careau, Vincent/0000-0002-2826-7837; Garant, Dany/0000-0002-8091-1044
FU Fonds de recherche du Quebec - Nature et technologies (FQRNT) team;
   Natural Sciences and Engineering Research Council of Canada (NSERC);
   NSERC; Canada Research Chair in Evolutionary Demography and Conservation
FX This paper is dedicated to Donald William Thomas, who sadly died too
   soon to contribute to the writing of this paper, but whose ideas,
   encouragement, and respirometry equipment rendered this project
   feasible. This research was supported by a Fonds de recherche du Quebec
   - Nature et technologies (FQRNT) team grant, Natural Sciences and
   Engineering Research Council of Canada (NSERC) discovery grants to
   M.M.H., and a NSERC doctoral scholarship to V.C. Animals were captured
   and handled with compliance to the Canadian Council on Animal Care
   (#2007-DT01-Universite de Sherbrooke) and the Ministere des Ressources
   Naturelles et de la Faune du Quebec (#2008-04-15-101-05-S-F). We
   acknowledge funding provided by the Canada Research Chair in
   Evolutionary Demography and Conservation allowed to F. Pelletier for the
   purchase of the heliox gaz tank. We thank all field assistants who
   helped collecting the data presented in this paper and P. Bourgault, M.
   Landry-Cuerrier, and D. Munro for coordination work. We are grateful to
   M. Chappell, M. Landry-Cuerrier, D. Reale, and two anonymous reviewers
   for comments on a previous draft of the manuscript.
CR Bartholomew G. A., 1964, Symposia of the Society for Experimental Biology, V18, P7
   BARTHOLOMEW GA, 1981, J EXP BIOL, V90, P17
   BENNETT AF, 1979, SCIENCE, V206, P649, DOI 10.1126/science.493968
   BENNETT GF, 1972, CAN J ZOOLOG, V50, P861, DOI 10.1139/z72-116
   BENNETT GORDON F., 1955, CANADIAN JOUR ZOOL, V33, P75, DOI 10.1139/z55-004
   Bergeron P, 2011, ECOLOGY, V92, P2027, DOI 10.1890/11-0766.1
   BOZINOVIC F, 1992, PHYSIOL ZOOL, V65, P921, DOI 10.1086/physzool.65.5.30158550
   Butler D., 2007, ASReml-R reference manual
   Careau V, 2012, J COMP PHYSIOL B, V182, P403, DOI 10.1007/s00360-011-0628-5
   Careau V, 2010, OECOLOGIA, V162, P303, DOI 10.1007/s00442-009-1466-y
   CATTS EP, 1982, ANNU REV ENTOMOL, V27, P313, DOI 10.1146/annurev.en.27.010182.001525
   CHAPPELL MA, 1995, PHYSIOL ZOOL, V68, P421, DOI 10.1086/physzool.68.3.30163777
   Degen AA, 2006, MICROMAMMALS AND MACROPARASITES: FROM EVOLUTIONARY ECOLOGY TO MANAGEMENT, P371, DOI 10.1007/978-4-431-36025-4_19
   HAYES JP, 1995, EVOLUTION, V49, P836, DOI 10.1111/j.1558-5646.1995.tb02320.x
   HAYES JP, 1989, PHYSIOL ZOOL, V62, P732, DOI 10.1086/physzool.62.3.30157924
   HAYES JP, 1990, FUNCT ECOL, V4, P495, DOI 10.2307/2389317
   HINDS DS, 1992, PHYSIOL ZOOL, V65, P188, DOI 10.1086/physzool.65.1.30158246
   KOTEJA P, 1987, COMP BIOCHEM PHYS A, V87, P205, DOI 10.1016/0300-9629(87)90447-6
   Koteja P, 1996, FUNCT ECOL, V10, P675, DOI 10.2307/2390179
   KUHNEN G, 1986, COMP BIOCHEM PHYS A, V84, P517, DOI 10.1016/0300-9629(86)90359-2
   Landry-Cuerrier M, 2008, ECOLOGY, V89, P3306, DOI 10.1890/08-0121.1
   Lemaître J, 2009, OECOLOGIA, V159, P283, DOI 10.1007/s00442-008-1219-3
   Levesque DL, 2010, J COMP PHYSIOL B, V180, P279, DOI 10.1007/s00360-009-0405-x
   Levesque DL, 2009, J EXP BIOL, V212, P1801, DOI 10.1242/jeb.027094
   Meagher S, 2001, CAN J ZOOL, V79, P554, DOI 10.1139/cjz-79-4-554
   Mueller P, 2001, P NATL ACAD SCI USA, V98, P12550, DOI 10.1073/pnas.221456698
   MUNGER JC, 1994, CAN J ZOOL, V72, P166, DOI 10.1139/z94-021
   Munro D, 2008, CAN J ZOOL, V86, P364, DOI 10.1139/Z08-008
   Munro D, 2005, J ANIM ECOL, V74, P692, DOI 10.1111/j.1365-2656.2005.00968.x
   Pinheiro J. C., 2009, Mixed-effects models in S and S-Plus, DOI DOI 10.1007/BF01313644
   Rezende EL, 2004, EVOLUTION, V58, P1361
   ROSENMANN M, 1974, AM J PHYSIOL, V226, P490, DOI 10.1152/ajplegacy.1974.226.3.490
   Scantlebury M, 2007, P ROY SOC B-BIOL SCI, V274, P2169, DOI 10.1098/rspb.2007.0690
   Schmidt-Nielsen K., 1984, Scaling why is animal size so important?
   SCHOLANDER PF, 1955, EVOLUTION, V9, P15, DOI 10.2307/2405354
   Slansky F, 2007, ANNU REV ENTOMOL, V52, P17, DOI 10.1146/annurev.ento.51.110104.151017
   Speakman JR, 2000, ADV ECOL RES, V30, P177
   Thomas DW, 1998, J THERM BIOL, V23, P377, DOI 10.1016/S0306-4565(98)00028-X
   WANG LCH, 1971, COMP BIOCHEM PHYSIOL, V38, P59
   WILLIAMS DD, 1973, COMP BIOCHEM PHYSIOL, V44, P1227, DOI 10.1016/0300-9629(73)90261-2
   WITHERS PC, 1977, J APPL PHYSIOL, V42, P120, DOI 10.1152/jappl.1977.42.1.120
NR 41
TC 13
Z9 15
U1 0
U2 32
PU CANADIAN SCIENCE PUBLISHING, NRC RESEARCH PRESS
PI OTTAWA
PA 65 AURIGA DR, SUITE 203, OTTAWA, ON K2E 7W6, CANADA
SN 0008-4301
EI 1480-3283
J9 CAN J ZOOL
JI Can. J. Zool.
PD MAR
PY 2012
VL 90
IS 3
BP 413
EP 421
DI 10.1139/Z2012-008
PG 9
WC Zoology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Zoology
GA 920HE
UT WOS:000302394100014
DA 2025-01-10
ER

PT J
AU Goolsby, JA
   DeBarro, PJ
   Kirk, AA
   Sutherst, RW
   Canas, L
   Ciomperlik, MA
   Ellsworth, PC
   Gould, JR
   Hartley, DM
   Hoelmer, KA
   Naranjo, SE
   Rose, M
   Roltsch, WJ
   Ruiz, RA
   Pickett, CH
   Vacek, DC
AF Goolsby, JA
   DeBarro, PJ
   Kirk, AA
   Sutherst, RW
   Canas, L
   Ciomperlik, MA
   Ellsworth, PC
   Gould, JR
   Hartley, DM
   Hoelmer, KA
   Naranjo, SE
   Rose, M
   Roltsch, WJ
   Ruiz, RA
   Pickett, CH
   Vacek, DC
TI Post-release evaluation of biological control of <i>Bemisia tabaci</i>
   biotype "B" in the USA and the development of predictive tools to guide
   introductions for other countries
SO BIOLOGICAL CONTROL
LA English
DT Article; Proceedings Paper
CT Antoni Van Leeuwenhoek Symposium
CY OCT, 2000
CL NETHERLANDS
DE climate matching; predictive evaluation; Eretmocerus; Encarsia;
   silverleaf whitefly; USA; Australia
ID ERETMOCERUS HALDEMAN HYMENOPTERA; NATURAL ENEMIES; NEW-ZEALAND;
   ALEYRODIDAE; GENNADIUS; APHELINIDAE; HEMIPTERA; AUSTRALIA
AB Climatic matching and pre-release performance evaluation were useful predictors of parasitoid establishment in a retrospective analysis of a classical biological control program against Bemisia tabaci biotype "B" in the USA. Laboratory evaluation of 19 imported and two indigenous parasitoid species in quarantine on B. tabaci showed that the Old World Eretmocerus spp, had the highest attack rate. The climate matching program CLIMEX was used to analyze the establishment patterns of five Old World Eretmocerus spp. introduced to the Western USA. The top matches +/-10% for the climate of the area of introduction and origin of the introduced parasitoids always included the species that established. The Old World Eretmocerus spp. came from regions characterized by many separate biotypes of B. tabaci other than "B," but are considered specialists of the B. tabaci complex as compared to the indigenous North American oligophagous Eretmocerus spp. This narrower host range and high attack rate combined with climatic adaptation may account for their establishment in the USA. A set of predictive tools and guidelines were used to select the best candidate for importation and possible release into Australia that has been recently invaded by the "B" biotype. The establishment patterns of the introduced Eretmocerus spp. and a comparison of climates of their respective locations in the USA were compared with the affected area in Australia. The best climatic match was the Lower Rio Grande Valley of Texas suggesting its dominant parasitoid, E. hayati ex. Pakistan be considered as the first candidate for evaluation as a biological control agent. Published by Elsevier Inc.
C1 USDA ARS, Australian Biol Control Lab, Indooroopilly, Qld 4068, Australia.
   CSIRO, Indooroopilly, Qld, Australia.
   USDA ARS, European Biol Control Lab, Montferrier Sur Lez, France.
   Ohio State Univ, Dept Entomol, Wooster, OH USA.
   USDA, APHIS, Mission Plant Protect Ctr, Edinburg, TX USA.
   Univ Arizona, Dept Entomol, Maricopa, AZ USA.
   USDA, APHIS, Otis Methods Dev Ctr, Buzzards Bay, MA USA.
   CSIRO, Canberra, ACT, Australia.
   USDA ARS, Western Cotton Res Lab, Maricopa, AZ USA.
   Bozeman Biol Control Inst, Bozeman, MT USA.
   CDFA, Biol Control Unit, Sacramento, CA USA.
C3 Commonwealth Scientific & Industrial Research Organisation (CSIRO);
   Commonwealth Scientific & Industrial Research Organisation (CSIRO);
   University System of Ohio; Ohio State University; United States
   Department of Agriculture (USDA); University of Arizona; United States
   Department of Agriculture (USDA); Commonwealth Scientific & Industrial
   Research Organisation (CSIRO); United States Department of Agriculture
   (USDA)
RP USDA ARS, Australian Biol Control Lab, 120 Meiers Rd, Indooroopilly, Qld 4068, Australia.
EM john.goolsby@csiro.au
RI Hartley, Diana/D-3556-2011; De Barro, Paul/C-1724-2008; Ellsworth,
   Peter/I-2524-2019
OI Ellsworth, Peter/0000-0002-2485-0830
CR Alegbejo MD, 2000, J SUSTAIN AGR, V17, P99
   Brown J. K., 1994, FAO (Food and Agriculture Organization of the United Nations) Plant Protection Bulletin, V42, P3
   CAMERON PJ, 1993, BIOCONTROL SCI TECHN, V3, P387, DOI 10.1080/09583159309355294
   De Barro PJ, 2000, MOL PHYLOGENET EVOL, V16, P29, DOI 10.1006/mpev.1999.0768
   De Barro PJ, 2000, AUST J ENTOMOL, V39, P259, DOI 10.1046/j.1440-6055.2000.00194.x
   De Barro PJ, 2000, ENTOMOL EXP APPL, V94, P93, DOI 10.1046/j.1570-7458.2000.00608.x
   DeBach P., 1964, BIOL CONTROL INSECT
   DEBARRO PJ, 1995, 36 COMM SCI IND ORG, P1
   EHLER LE, 1990, CRITICAL ISSUES IN BIOLOGICAL CONTROL, P111
   FLANERRY T, 2001, ETERNAL FRONTIER ECO
   Frohlich DR, 1999, MOL ECOL, V8, P1683, DOI 10.1046/j.1365-294x.1999.00754.x
   Goldson SL, 1997, AGR ECOSYST ENVIRON, V64, P115, DOI 10.1016/S0167-8809(97)00029-7
   Goolsby J, 1996, SOUTHWEST ENTOMOL, V21, P13
   Goolsby JA, 1998, BIOL CONTROL, V12, P127, DOI 10.1006/bcon.1998.0624
   GOOLSBY JA, 2000, 4 INT HYM C, P347
   GOULD J, 1998, USDAARS199801, P60
   Greathead D.J., 1986, P289
   Hoddle MS, 2002, INVASIVE ARTHROPODS IN AGRICULTURE: PROBLEMS AND SOLUTIONS, P395
   HOELMER KA, 2002, IN PRESS P 1 INT S B
   HOELMER KA, 1998, 199801 ARS USDA, P68
   HOELMER KA, 1998, 199801 ARS USDA, P70
   HOKKANEN HMT, 1989, CAN ENTOMOL, V121, P829, DOI 10.4039/Ent121829-10
   Kirk AA, 2000, B ENTOMOL RES, V90, P317, DOI 10.1017/S0007485300000444
   KIRK AA, 1993, ENTOMOPHAGA, V38, P405, DOI 10.1007/BF02374458
   KIRK AA, 1995, BEMISIA 1995 TAXONOM, P531
   Legaspi J.C., 1996, SUBTROPICAL PLANT SC, V48, P48
   Morales FJ, 2001, ARCH VIROL, V146, P415, DOI 10.1007/s007050170153
   PICKETT CH, 1999, 199901 ARS USDA, P83
   PICKETT CH, 2001, BIOL CONTROL PROGRAM, P12
   ROLTSCH WJ, 2001, BIOL CONTROL PROGRAM, P21
   Rose M, 1997, P ENTOMOL SOC WASH, V99, P1
   ROUSH RT, 1990, CRITICAL ISSUES IN BIOLOGICAL CONTROL, P263
   SIMMONS GS, 1998, USDAARS199801, P84
   SUTHERST RW, 1999, CDROM USER GUIDE
   WAAGE J, 1990, CRITICAL ISSUES IN BIOLOGICAL CONTROL, P135
   Zolnerowich G, 1998, P ENTOMOL SOC WASH, V100, P310
NR 36
TC 69
Z9 98
U1 0
U2 28
PU ACADEMIC PRESS INC ELSEVIER SCIENCE
PI SAN DIEGO
PA 525 B ST, STE 1900, SAN DIEGO, CA 92101-4495 USA
SN 1049-9644
EI 1090-2112
J9 BIOL CONTROL
JI Biol. Control
PD JAN
PY 2005
VL 32
IS 1
BP 70
EP 77
DI 10.1016/j.biocontrol.2004.07.012
PG 8
WC Biotechnology & Applied Microbiology; Entomology
WE Science Citation Index Expanded (SCI-EXPANDED); Conference Proceedings Citation Index - Science (CPCI-S)
SC Biotechnology & Applied Microbiology; Entomology
GA 889OA
UT WOS:000226451100011
DA 2025-01-10
ER

PT J
AU Roggema, R
AF Roggema, Rob
TI From Nature-Based to Nature-Driven: Landscape First for the Design of
   Moeder Zernike in Groningen
SO SUSTAINABILITY
LA English
DT Article
DE nature-based solutions; landscape and urban design; urban agriculture
   and food systems; coastal dynamics; Groningen
AB Global climate change impacts the future of urbanism. The future is increasingly uncertain, and current responses in urban planning practice are often human-centered. In general, this is a way to respond to change that is oriented towards improving the life of people in the short term, often extracting resources from the environment at dangerous levels. This impacts the entire ecological system, and turns out to be negative for biodiversity, resilience, and, ultimately, human life as well. Adaptation to climatic impacts requires a long-term perspective based in the understanding of nature. The objective of the presented research is to find explorative ways to respond to the unknown unknowns through designing and planning holistically for the Zernike campus in Groningen, the Netherlands. The methods used in this study comprise co-creative design-led approaches which are capable of integrating sectoral problems into a visionary future plan. The research findings show how embracing a nature-driven perspective to urban design increases the adaptive capacity, the ecological diversity, and the range of healthy food grown on a university campus. This study responds to questions of food safety, and growing conditions, of which the water availability is the most pressing. Considering the spatial concept, this has led to the necessity to establish a novel water connection between the site and the sea.
C1 [Roggema, Rob] Cittaideale, NL-6706 LC Wageningen, Netherlands.
   [Roggema, Rob] Western Sydney Univ, Inst Culture & Soc, Parramatta, NSW 2150, Australia.
C3 Western Sydney University
RP Roggema, R (corresponding author), Cittaideale, NL-6706 LC Wageningen, Netherlands.; Roggema, R (corresponding author), Western Sydney Univ, Inst Culture & Soc, Parramatta, NSW 2150, Australia.
EM rob@cittaideale.eu
RI Roggema, Robert/AFM-3455-2022
OI Roggema, Rob/0000-0003-2492-0779
CR Abhijith KV, 2017, ATMOS ENVIRON, V162, P71, DOI 10.1016/j.atmosenv.2017.05.014
   Almond R., 2020, Living Planet Report 2020-Bending the Curve of Biodiversity Loss (No. LPR2020)
   [Anonymous], 2015, The impact of green space on heat and air pollution in urban communities: A meta-narrative systematic review
   [Anonymous], 2006, FAO Food and nutrition, P119
   [Anonymous], 2019, IPCC SPECIAL REPORT, DOI [10.1017/9781009157964, DOI 10.1017/9781009157964]
   [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 10.2777/479582
   [Anonymous], 2017, TOESTAND NATUUR LAND
   Attema Jisk., 2014, KNMI'14: Climate Change scenarios for the 21st Century - A Netherlands perspective
   Baird, 1999, T I PROF ENG NZ, V26, P1
   Balz VE, 2018, PLAN THEOR, V17, P332, DOI 10.1177/1473095217721280
   Barton H., 1998, LOCAL ENVIRON, V3, P159, DOI 10.1080/13549839808725555
   Bird W., 2007, Natural Thinking: Investigating the links between the Natural Environment, Biodiversity and Health, V1st
   Bongaarts J, 2019, POPUL DEV REV, V45, P680, DOI 10.1111/padr.12283
   Boogerd A, 1997, J AM WATER RESOUR AS, V33, P731, DOI 10.1111/j.1752-1688.1997.tb04100.x
   Bosworth G., 2020, BASELINE STUDY FINAL
   Brennan A., 2011, The Stanford encyclopedia of philosophy
   Bureau of Crime Statistics and Research, MAPP RAT APPR DOM VI
   Capra F., 1996, WEB LIFE NEW SYNTHES
   Carrus G, 2015, LANDSCAPE URBAN PLAN, V134, P221, DOI 10.1016/j.landurbplan.2014.10.022
   CBS PBL RIVM WUR, 2020, BOERENLANDVOGELS 191
   Chamberlain, 2007, DESIGN RES NOW, P41
   Condon PatrickM., 2008, Design Charrettes for Sustainable Communities
   Cornish E., 2004, Futuring: The exploration of the future
   Cox DTC, 2018, LANDSCAPE URBAN PLAN, V179, P72, DOI 10.1016/j.landurbplan.2018.07.013
   Cox DTC, 2017, BIOSCIENCE, V67, P147, DOI 10.1093/biosci/biw173
   Crumley C.L., 1996, ENVIRON HIST-US, V1, P106, DOI [10.2307/3985066, DOI 10.2307/3985066]
   Crutzen PJ, 2002, NATURE, V415, P23, DOI 10.1038/415023a
   Davoudi S, 2014, ENVIRON PLANN C, V32, P360, DOI 10.1068/c12269
   Davy B, 2008, PLAN THEOR, V7, P301, DOI 10.1177/1473095208096885
   De Jong T.M., 1992, Kleine methodologie voor ontwerpend onderzoek
   De Vries S., 2020, INCREASING DROUGHT N
   de Waal JA, 2012, NETH J GEOSCI, V91, P385
   Denk T, 2010, INT J SOC RES METHOD, V13, P29, DOI 10.1080/13645570802583779
   Dovey, 2018, CAN PARKS MAKE KIDS
   du Plessis C, 2012, BUILD RES INF, V40, P7, DOI 10.1080/09613218.2012.628548
   Dye C, 2008, SCIENCE, V319, P766, DOI 10.1126/science.1150198
   Epstein LH, 2007, HEALTH PSYCHOL, V26, P381, DOI 10.1037/0278-6133.26.4.381
   Epstein LH, 2006, PSYCHOL SCI, V17, P654, DOI 10.1111/j.1467-9280.2006.01761.x
   EPSTEIN LH, 1985, J PEDIATR-US, V107, P358, DOI 10.1016/S0022-3476(85)80506-0
   Epstein LH, 2002, J PEDIATR-US, V140, P334, DOI 10.1067/mpd.2002.122395
   Erkens G., 2010, P EGU GEN ASS 2010 V, P12386
   Flouri E, 2019, BRIT J EDUC PSYCHOL, V89, P359, DOI 10.1111/bjep.12243
   Fry T., 2009, Design futuring, P71
   Gaffikin F, 2006, PLAN THEORY PRACT, V7, P159, DOI 10.1080/14649350600673070
   Gascon M, 2016, ENVIRON INT, V86, P60, DOI 10.1016/j.envint.2015.10.013
   Gidlöf-Gunnarsson A, 2007, LANDSCAPE URBAN PLAN, V83, P115, DOI 10.1016/j.landurbplan.2007.03.003
   Girardet H, 2017, STU ECO ECO, V6, P183, DOI 10.1007/978-3-319-38919-6_9
   Girardet Herbert., 2014, CREATING REGENERATIV, DOI DOI 10.4324/9781315764375
   Gladwell M., 2000, TIPPING POINT LITTLE
   Global Commission on Adaptation, 2019, AD NOW GLOB CALL LEA
   Haasnoot M., 2018, Mogelijke gevolgen van versnelde zeespiegelstijging voor het Deltaprogramma: Een verkenning (11202230-005-0002.)
   Hanssen R., P 20 EGU GEN ASS VIE, P17443
   Harland, 2009, P AHRC POSTGR C 2009, P141
   Hauberg J., 2011, AE... Revista Lusofona de Arquitectura e Educacao, V5, P46
   Hewitt CN, 2020, AMBIO, V49, P62, DOI 10.1007/s13280-019-01164-3
   Hocking V.T., 2010, Tackling Wicked Problems Through the Transdisciplinary Imagination, P242
   Horne, P ANZRSAI C CANB AUS
   Horstmann B., 2008, Framing Adaptation to Climate Change -- A Challenge for Building Institutions
   Husqvarna Group, 2013, GLOB GREEN SPAC REP
   INFRAM, 2019, RAPP E FAS BEL DROOG
   Jackson LE, 2003, LANDSCAPE URBAN PLAN, V64, P191, DOI 10.1016/S0169-2046(02)00230-X
   Kaplan R., 1989, The experience of nature: A psychological perspective
   KAPLAN S, 1995, J ENVIRON PSYCHOL, V15, P169, DOI 10.1016/0272-4944(95)90001-2
   Karnib A., 2017, Comput. Water Energy Environ. Eng, V6, P11, DOI DOI 10.4236/CWEEE.2017.61002
   Keeffe, LAND-BASEL
   Krasny M.E., 2015, Civic ecology: Adaptation and transformation from the ground up
   Kroes JG, 2011, AGR ECOSYST ENVIRON, V144, P370, DOI 10.1016/j.agee.2011.09.008
   Kumar P, 2019, ENVIRON INT, V133, DOI 10.1016/j.envint.2019.105181
   Kuo FE, 2001, ENVIRON BEHAV, V33, P343, DOI 10.1177/00139160121973025
   Kuo FE, 1998, ENVIRON BEHAV, V30, P28, DOI 10.1177/0013916598301002
   Lau S, 2009, LANDSCAPE RES, V34, P55, DOI 10.1080/01426390801981720
   Lennertz B., 2006, CHARRETTE HDB ESSENT
   Li DY, 2016, LANDSCAPE URBAN PLAN, V148, P149, DOI 10.1016/j.landurbplan.2015.12.015
   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
   Lottrup L, 2013, LANDSCAPE URBAN PLAN, V110, P5, DOI 10.1016/j.landurbplan.2012.09.002
   Louv, 2016, ESSENTIAL GUIDE NATU
   Maas J, 2009, J EPIDEMIOL COMMUN H, V63, P967, DOI 10.1136/jech.2008.079038
   Maas J, 2006, J EPIDEMIOL COMMUN H, V60, P587, DOI 10.1136/jech.2005.043125
   Maller C, 2006, HEALTH PROMOT INT, V21, P45, DOI 10.1093/heapro/dai032
   Marcus ClareCooper., 2007, Interdisciplinary Design and Research e-Journal, V1, P1
   Marselle M.R., 2014, Ecopsychology, V6, P134, DOI [DOI 10.1089/ECO.2014.0027, 10.1089/eco.2014.0027]
   Mccormick K., 2020, Cities, nature and innovation: new directions
   MCHARG I L, 1969, P197
   Mennis J, 2018, LANDSCAPE URBAN PLAN, V174, P1, DOI 10.1016/j.landurbplan.2018.02.008
   Merry U., 1995, COPING UNCERTAINTY I
   Milburn LAS, 2003, LANDSCAPE URBAN PLAN, V64, P47, DOI 10.1016/S0169-2046(02)00200-1
   Min KB, 2017, INT J PUBLIC HEALTH, V62, P647, DOI 10.1007/s00038-017-0958-5
   Ministerie van Infrastructuur en Milieu, 2020, DELT 2021
   Ministerie van LNV, 2019, EUROPESE LANDBOUW BE
   Mitchell R, 2007, J EPIDEMIOL COMMUN H, V61, P681, DOI 10.1136/jech.2006.053553
   Molotch H, 2000, AM SOCIOL REV, V65, P791, DOI 10.2307/2657514
   Morris D.J., 1982, SELF RELIANT CITIES
   Mougeot L. J. A., 1999, For hunger-proof cities: sustainable urban food systems., P11
   Mulder, 2019, P 4 BIENN RES DES C
   Mupedziswa R, 2017, DEV SO AFR, V34, P196, DOI 10.1080/0376835X.2016.1231057
   Núñez-Ríos JE, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12187558
   Okvat HA, 2011, AM J COMMUN PSYCHOL, V47, P374, DOI 10.1007/s10464-010-9404-z
   Pachauri RK, 2014, 2014 IEEE STUDENTS' CONFERENCE ON ELECTRICAL, ELECTRONICS AND COMPUTER SCIENCE (SCEECS)
   Portugali J., 2000, SELF ORG CITY
   POTTGENS JJE, 1991, IAHS-AISH P, V200, P99
   Pretty J, 2005, INT J ENVIRON HEAL R, V15, P319, DOI 10.1080/09603120500155963
   Pudup MB, 2008, GEOFORUM, V39, P1228, DOI 10.1016/j.geoforum.2007.06.012
   Raats PAC, 2015, AGR WATER MANAGE, V157, P12, DOI 10.1016/j.agwat.2014.08.022
   Reumer, 2014, WILDPARK ROTTERDAM S
   RITTEL HWJ, 1973, POLICY SCI, V4, P155, DOI 10.1007/BF01405730
   ROBERTS WO, 1976, P AM PHILOS SOC, V120, P230
   Rockström J, 2009, NATURE, V461, P472, DOI 10.1038/461472a
   Roggema, 2019, RECIPROCITY GIVING I
   Roggema, 2020, NATURE DRIVEN URBANI, V2
   Roggema, 2012, SWARM PLANNING DEV M
   Roggema R, 2009, ADAPTATION TO CLIMATE CHANGE: A SPATIAL CHALLENGE, P1, DOI 10.1007/978-1-4020-9359-3
   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., 2020, NATURE DRIVEN URBANI, V2, P9
   Roggema R., 2013, DESIGN CHARRETTE WAY, P335
   Roggema R., 2012, SWARMING LANDSCAPES, P260
   Roggema R., 2020, NATURE DRIVEN URBANI, V2, P81
   Roggema R, 2017, URBAN SCI, V1, DOI 10.3390/urbansci1010002
   Rosegrant MW, 2003, SCIENCE, V302, P1917, DOI 10.1126/science.1092958
   Rosemann J, 2001, RESEARCH BY DESIGN PROCEEDINGS A, P63
   Rougoor, 2016, LANDBOUW KLIMAATVERA
   Rouse W.B., 1991, Design for success: A human-centered approach to designing successful products and systems
   Schipper E.L.F., 2009, Adaptation to Climate Change
   Schoonbeek, 1976, P SPE EUR SPRING M A
   Schubert D, 2019, PLAN PERSPECT, V34, P3, DOI 10.1080/02665433.2018.1541758
   Schuetze T, 2013, WATER-SUI, V5, P593, DOI 10.3390/w5020593
   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
   Shore Randy., 2017, The Vancouver Sun
   Shuman Michael., 2013, Going local: Creating self-reliant communities in a global age
   Soderback Ingrid, 2004, Pediatr Rehabil, V7, P245, DOI 10.1080/13638490410001711416
   Soininen J, 2016, OIKOS, V125, P160, DOI 10.1111/oik.02241
   Soldaat, 2005, IND TRENDS AANT WEID
   Stoltz J., 2019, THESIS STOCKHOLM U S
   STUYFZAND PJ, 1995, WATER SCI TECHNOL, V31, P47, DOI 10.1016/0273-1223(95)00356-R
   Sullivan W.C., 2011, MAKING HLTH PLACES, P106, DOI [DOI 10.5822/978-1-61091-036-1_7, 10.5822/978-1-61091-036-1_7, DOI 10.1080/17538947.2016.1252434]
   Suykerbuyk W, 2018, PEERJ, V6, DOI 10.7717/peerj.5234
   Swann C, 2002, DES ISSUES, V18, P49, DOI 10.1162/07479360252756287
   Tait M., 2003, URBAN DES INT, V8, P37, DOI DOI 10.1057/PALGRAVE.UDI.9000092
   Taylor AF, 2002, J ENVIRON PSYCHOL, V22, P49, DOI 10.1006/jevp.2001.0241
   Thompson CW, 2014, PROCD SOC BEHV, V153, P10, DOI 10.1016/j.sbspro.2014.10.036
   Thompson CW, 2012, LANDSCAPE URBAN PLAN, V105, P221, DOI 10.1016/j.landurbplan.2011.12.015
   Thomson G, 2018, RESOUR CONSERV RECY, V132, P218, DOI 10.1016/j.resconrec.2017.01.010
   Tzoulas K, 2007, LANDSCAPE URBAN PLAN, V81, P167, DOI 10.1016/j.landurbplan.2007.02.001
   UNEP, 2021, Adaptation Gap Report 2021: The Gathering Storm-Adapting to Climate Change in a Post-Pandemic World
   van de Vijver F.J. R., 1997, METHODS DATA ANAL CR
   Van der Woud A., 2020, LANDSCHAP MENSEN NED, P445
   van Dijk-Wesselius JE, 2018, LANDSCAPE URBAN PLAN, V180, P15, DOI 10.1016/j.landurbplan.2018.08.003
   van Thienen-Visser K, 2017, NETH J GEOSCI, V96, pS105, DOI 10.1017/njg.2017.10
   Velstra J, 2011, IRRIG DRAIN, V60, P51, DOI 10.1002/ird.675
   Velstra J., 2012, VERZILTING LANDBOUWG
   Willett W, 2019, LANCET, V393, P447, DOI 10.1016/S0140-6736(18)31788-4
   World Health Organisation, 2015, Urban health
   Wright, 2013, W SYDNEY POLLIES WOU
   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
   Yang YJ, 2014, CURR OPIN CHEM ENG, V5, P22, DOI 10.1016/j.coche.2014.03.006
NR 159
TC 14
Z9 14
U1 2
U2 24
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 4
AR 2368
DI 10.3390/su13042368
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 QQ8ZA
UT WOS:000624806300001
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Eckert, AJ
   Wegrzyn, JL
   Pande, B
   Jermstad, KD
   Lee, JM
   Liechty, JD
   Tearse, BR
   Krutovsky, KV
   Neale, DB
AF Eckert, Andrew J.
   Wegrzyn, Jill L.
   Pande, Barnaly
   Jermstad, Kathleen D.
   Lee, Jennifer M.
   Liechty, John D.
   Tearse, Brandon R.
   Krutovsky, Konstantin V.
   Neale, David B.
TI Multilocus Patterns of Nucleotide Diversity and Divergence Reveal
   Positive Selection at Candidate Genes Related to Cold Hardiness in
   Coastal Douglas Fir (<i>Pseudotsuga menziesii</i> var. <i>menziesii</i>)
SO GENETICS
LA English
DT Article
ID QUANTITATIVE TRAIT LOCI; CONTROLLING ADAPTIVE TRAITS; LINKAGE
   DISEQUILIBRIUM; DEMOGRAPHIC HISTORY; POPULATION GENOMICS; ALLOZYME
   VARIATION; WESTERN OREGON; SITE-FREQUENCY; NORWAY SPRUCE; POLYMORPHISM
AB Forest trees exhibit remarkable adaptations to their environments. The genetic basis for phenotypic adaptation to climatic gradients has been established through a long history of common garden, provenance, and genecological studies. The identities of genes underlying these traits, however, have retrained elusive and thus so have the patterns of adaptive molecular diversity in forest tree genomes. Here, we report an analysis of diversity and divergence for a set of 121 cold-hardiness candidate genes in coastal Douglas fir (Pseudotsuga menziesii var. menziesii). Application of several different tests for neutrality, including those that incorporated demographic models, revealed signatures of selection consistent with selective sweeps at three to eight loci, depending upon the severity of a bottleneck event and the method used to detect selection. Given the high levels of recombination, these candidate genes are likely to be closely linked to the target of selection if not the genes themselves. Putative homologs in Arabidopsis act primarily to stabilize the plasma membrane and protect against denaturation of proteins at freezing temperatures. These results indicate that surveys of nucleotide diversity and divergence, when framed within the context of further association trapping experiments, will come full circle with respect: to their utility in the dissection of complex phenotypic traits into their genetic components.
C1 [Neale, David B.] Univ Calif Davis, Dept Plant Sci, Sect Evolut & Ecol, Davis, CA 95616 USA.
   [Eckert, Andrew J.] Univ Calif Davis, Ctr Populat Biol, Davis, CA 95616 USA.
   [Jermstad, Kathleen D.; Neale, David B.] US Forest Serv, Inst Forest Genet, Pacific SW Res Stn, USDA, Placerville, CA 95667 USA.
   [Krutovsky, Konstantin V.] Texas A&M Univ, Dept Ecosyst Sci & Management, College Stn, TX 77843 USA.
C3 University of California System; University of California Davis;
   University of California System; University of California Davis; United
   States Department of Agriculture (USDA); United States Forest Service;
   Texas A&M University System; Texas A&M University College Station
RP Neale, DB (corresponding author), Univ Calif Davis, Dept Plant Sci, Sect Evolut & Ecol, Mail Stop 6, Davis, CA 95616 USA.
EM dbneale@ucdavis.edu
RI Eckert, Andrew/E-4788-2011; Wegrzyn, Jill/H-3745-2019; Krutovsky,
   Konstantin/A-5419-2012
OI Krutovsky, Konstantin/0000-0002-8819-7084; Wegrzyn,
   Jill/0000-0001-5923-0888
FU U.S. Department of Agriculture National Research Initiative Plant Genome
   [04-712-0084]
FX The authors thank F. Thomas Ledig for contributing bigcone Douglas fir
   seeds, Valerie Hipkins and her staff at National Forest Genetics
   Laboratory for performing the DNA extractions, Katie Tsang and
   Jacqueline Silver for helping to obtain sequence data, and Jeff
   Ross-Ibarra for helpful discussion about demographic inference. The
   manuscript was much improved by comments from two anonymous reviewers.
   Funding for this project was made available through a U.S. Department of
   Agriculture National Research Initiative Plant Genome grant
   (04-712-0084).
CR Aitken SN, 1997, CAN J FOREST RES, V27, P1773, DOI [10.1139/cjfr-27-11-1773, 10.1139/x97-151]
   Aitken SN, 1996, CAN J FOREST RES, V26, P1828, DOI 10.1139/x26-208
   Ann W, 2007, MOL BIOL EVOL, V24, P90, DOI 10.1093/molbev/msl131
   [Anonymous], OXF SURV EVOL BIOL
   [Anonymous], THEORY PROBABILITY
   Baudry E, 2003, GENETICS, V165, P1619
   Begun DJ, 2007, PLOS BIOL, V5, P2534, DOI 10.1371/journal.pbio.0050310
   Breton G, 2003, PLANT PHYSIOL, V132, P64, DOI 10.1104/pp.102.015255
   Brown GR, 2004, P NATL ACAD SCI USA, V101, P15255, DOI 10.1073/pnas.0404231101
   CAMPBELL RK, 1979, ECOLOGY, V60, P1036, DOI 10.2307/1936871
   CAMPBELL RK, 1973, ECOLOGY, V54, P1148, DOI 10.2307/1935582
   Caro E, 2007, NATURE, V447, P213, DOI 10.1038/nature05763
   Clark RM, 2007, SCIENCE, V317, P338, DOI 10.1126/science.1138632
   Doerks T, 2000, TRENDS BIOCHEM SCI, V25, P483, DOI 10.1016/S0968-0004(00)01664-9
   Eckert AJ, 2009, GENETICS, V182, P1289, DOI 10.1534/genetics.109.102350
   Eckert AJ, 2009, TREE GENET GENOMES, V5, P225, DOI 10.1007/s11295-008-0183-8
   Evanno G, 2005, MOL ECOL, V14, P2611, DOI 10.1111/j.1365-294X.2005.02553.x
   Eveno E, 2008, MOL BIOL EVOL, V25, P417, DOI 10.1093/molbev/msm272
   Gaut BS, 2007, NAT REV GENET, V8, P77, DOI 10.1038/nrg1970
   Gillespie JH, 2001, EVOLUTION, V55, P2161
   GILMOUR SJ, 1991, PLANT MOL BIOL, V17, P1233, DOI 10.1007/BF00028738
   González-Martínez SC, 2006, NEW PHYTOL, V170, P227, DOI 10.1111/j.1469-8137.2006.01686.x
   Graham A., 1999, Late Cretaceous and Cenozoic History of North American Vegetation
   Heuertz M, 2006, GENETICS, V174, P2095, DOI 10.1534/genetics.106.065102
   HILL WG, 1988, THEOR POPUL BIOL, V33, P54, DOI 10.1016/0040-5809(88)90004-4
   Holliday JA, 2008, NEW PHYTOL, V178, P103, DOI 10.1111/j.1469-8137.2007.02346.x
   Howe GT, 2003, CAN J BOT, V81, P1247, DOI [10.1139/b03-141, 10.1139/B03-141]
   Hu X, 1997, PLANT MOL BIOL, V34, P949, DOI 10.1023/A:1005893119263
   HUDSON RR, 1995, PHILOS T R SOC B, V349, P19, DOI 10.1098/rstb.1995.0086
   HUDSON RR, 1985, GENETICS, V111, P147
   Ingvarsson PK, 2008, GENETICS, V180, P329, DOI 10.1534/genetics.108.090431
   Innan H, 2004, P NATL ACAD SCI USA, V101, P10667, DOI 10.1073/pnas.0401720101
   Jermstad KD, 1998, THEOR APPL GENET, V97, P762, DOI 10.1007/s001220050953
   Jermstad KD, 2003, GENETICS, V165, P1489
   Jermstad KD, 2001, THEOR APPL GENET, V102, P1142, DOI 10.1007/s001220000505
   Jermstad KD, 2001, THEOR APPL GENET, V102, P1152, DOI 10.1007/s001220000506
   Krutovsky KV, 2005, GENETICS, V171, P2029, DOI 10.1534/genetics.105.044420
   Krutovsky KV, 2004, GENETICS, V168, P447, DOI 10.1534/genetics.104.028381
   KRUTOVSKY KV, 2009, TREE GENET IN PRESS
   Le Corre V, 2003, GENETICS, V164, P1205
   Lee BH, 2005, PLANT CELL, V17, P3155, DOI 10.1105/tpc.105.035568
   LI P, 1989, CAN J FOREST RES, V19, P149, DOI 10.1139/x89-022
   Marjoram P, 2003, P NATL ACAD SCI USA, V100, P15324, DOI 10.1073/pnas.0306899100
   Marjoram P, 2006, NAT REV GENET, V7, P759, DOI 10.1038/nrg1961
   McKay JK, 2002, TRENDS ECOL EVOL, V17, P285, DOI 10.1016/S0169-5347(02)02478-3
   MERKLE SA, 1987, CAN J FOREST RES, V17, P402, DOI 10.1139/x87-069
   Morgenstern E.K., 1996, Geographic variation in forest trees: genetic basis and application of knowledge in silviculture
   Namroud MC, 2008, MOL ECOL, V17, P3599, DOI 10.1111/j.1365-294X.2008.03840.x
   Palmé AE, 2009, MOL BIOL EVOL, V26, P893, DOI 10.1093/molbev/msp010
   Palmé AE, 2008, MOL BIOL EVOL, V25, P2567, DOI 10.1093/molbev/msn194
   Pavy N, 2008, BMC GENOMICS, V9, DOI 10.1186/1471-2164-9-21
   Przeworski M, 2002, GENETICS, V160, P1179
   Pyhäjärvi T, 2007, GENETICS, V177, P1713, DOI 10.1534/genetics.107.077099
   Remington DL, 2001, P NATL ACAD SCI USA, V98, P11479, DOI 10.1073/pnas.201394398
   Romano PGN, 2004, PLANT PHYSIOL, V134, P1268, DOI 10.1104/pp.103.022160
   Ross-Ibarra J, 2009, GENETICS, V181, P1397, DOI 10.1534/genetics.108.097238
   Rozas J, 2003, BIOINFORMATICS, V19, P2496, DOI 10.1093/bioinformatics/btg359
   Santiago E, 2005, GENETICS, V169, P475, DOI 10.1534/genetics.104.032813
   Savolainen O, 2007, CURR OPIN PLANT BIOL, V10, P162, DOI 10.1016/j.pbi.2007.01.011
   Slatkin M, 1998, GENET RES, V71, P155, DOI 10.1017/S001667239800319X
   St Clair JB, 2006, CAN J BOT, V84, P1110, DOI 10.1139/B06-084
   St Clair JB, 2005, ANN BOT-LONDON, V96, P1199, DOI 10.1093/aob/mci278
   Städler T, 2009, GENETICS, V182, P205, DOI 10.1534/genetics.108.094904
   STAM P, 1993, PLANT J, V3, P739, DOI 10.1111/j.1365-313X.1993.00739.x
   Storey JD, 2003, ANN STAT, V31, P2013, DOI 10.1214/aos/1074290335
   Thomashow MF, 1999, ANNU REV PLANT PHYS, V50, P571, DOI 10.1146/annurev.arplant.50.1.571
   Viard F, 2001, GENOME, V44, P336, DOI 10.1139/gen-44-3-336
   Voight BF, 2006, PLOS BIOL, V4, P446, DOI 10.1371/journal.pbio.0040072
   WEGRZYN JL, 2009, BIOINFORMAT IN PRESS
   Wheeler NC, 2005, MOL BREEDING, V15, P145, DOI 10.1007/s11032-004-3978-9
   Wright SI, 2004, GENETICS, V168, P1071, DOI 10.1534/genetics.104.026500
   Yakovlev IA, 2006, TREE GENET GENOMES, V2, P39, DOI 10.1007/s11295-005-0031-z
   Zeng K, 2007, MOL BIOL EVOL, V24, P1562, DOI 10.1093/molbev/msm078
   Zeng K, 2007, MOL BIOL EVOL, V24, P1898, DOI 10.1093/molbev/msm119
   Zeng K, 2006, GENETICS, V174, P1431, DOI 10.1534/genetics.106.061432
NR 75
TC 81
Z9 92
U1 1
U2 32
PU OXFORD UNIV PRESS INC
PI CARY
PA JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA
SN 0016-6731
EI 1943-2631
J9 GENETICS
JI Genetics
PD SEP
PY 2009
VL 183
IS 1
BP 289
EP 298
DI 10.1534/genetics.109.103895
PG 10
WC Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Genetics & Heredity
GA 523IT
UT WOS:000272067000026
PM 19596906
OA Green Published, Bronze
DA 2025-01-10
ER

PT J
AU Li, H
   Hu, YF
   Batunacun
AF Li, Hao
   Hu, Yunfeng
   Batunacun
TI Responses of vegetation low-growth to extreme climate events on the
   Mongolian Plateau
SO GLOBAL ECOLOGY AND CONSERVATION
LA English
DT Article
DE Mongolian Plateau; vegetation sensitivity; Compound extreme climate;
   coincidence analysis
AB Since the 21st century began, the frequency and intensity of extreme climate events have significantly increased globally, becoming a widely recognized phenomenon of global change. These extreme events, including droughts and heatwaves, have profound impacts on the structure and function of ecosystems. This study focuses on the Mongolian Plateau. It utilizes meteorological and remote sensing vegetation data, combined with consistency and sensitivity analyses. These approaches aim to provide an in-depth understanding of the relationship between various extreme climate events and vegetation low-growth. The study found that extreme drought and extreme heat events are the primary drivers affecting vegetation low-growth on the Mongolian Plateau. The analysis results indicate that the sensitivity of vegetation to these extreme climate events is regulated by regional hydrothermal conditions, with vegetation in long-term drought areas being more susceptible to the suppression of extreme drought, while humid areas exhibit some resistance. As the temperature gradient increases, the sensitivity of vegetation to extreme high temperatures increases, while sensitivity to extreme low temperatures decreases. Furthermore, the study also revealed differences in the responses of different vegetation types to extreme events under the same climatic conditions, highlighting the ecological basis of ecosystem resilience and adaptability. This research not only enhances our understanding of vegetation dynamics under the influence of extreme climate events but also provides scientific evidence for ecological management and climate adaptation in the Mongolian Plateau region.
C1 [Li, Hao; Hu, Yunfeng] Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.
   [Li, Hao; Hu, Yunfeng] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China.
   [Batunacun] Inner Mongolia Normal Univ, Coll Geog Sci, Hohhot 010028, Inner Mongolia, 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; Inner Mongolia Normal University
RP Hu, YF (corresponding author), Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.; Batunacun (corresponding author), Inner Mongolia Normal Univ, Coll Geog Sci, Hohhot 010028, Inner Mongolia, Peoples R China.
EM huyf@lreis.ac.cn; batunacun@imnu.edu.cn
RI Hu, Yunfeng/A-1242-2019
FU National Natural Science Foundation of China [42371304]; National Key
   Research and Development Plan Program of China [2021YFD1300501]; Key
   Project of Innovation LREIS [KPI011]; Natural Science Foundation of
   Inner Mongolia Autonomous Region, China [2022QN04002]; Special Fund for
   Basic Research Business of Inner Mongolia Normal University
   [2022JBQN098]
FX Funding: This study was supported by the National Natural Science
   Foundation of China (42371304) ; the National Key Research and
   Development Plan Program of China [2021YFD1300501] ; the Key Project of
   Innovation LREIS (KPI011) ; the Natural Science Foundation of Inner
   Mongolia Autonomous Region, China (2022QN04002) ; and the Special Fund
   for Basic Research Business of Inner Mongolia Normal University
   (2022JBQN098) .
CR AghaKouchak A, 2020, ANNU REV EARTH PL SC, V48, P519, DOI 10.1146/annurev-earth-071719-055228
   Bai Y, 2022, ECOL INDIC, V141, DOI 10.1016/j.ecolind.2022.109150
   Bréda N, 2006, ANN FOREST SCI, V63, P625, DOI 10.1051/forest:2006042
   Chen HP, 2021, SCI BULL, V66, P749, DOI 10.1016/j.scib.2020.12.001
   Chen WZ, 2019, AGR FOREST METEOROL, V275, P47, DOI 10.1016/j.agrformet.2019.05.002
   Christian JI, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-26692-z
   Ciais P, 2005, NATURE, V437, P529, DOI 10.1038/nature03972
   Donges JF, 2016, EUR PHYS J-SPEC TOP, V225, P471, DOI 10.1140/epjst/e2015-50233-y
   Felton AJ, 2021, GLOBAL CHANGE BIOL, V27, P1127, DOI 10.1111/gcb.15480
   Freire S, 2015, INT GEOSCI REMOTE SE, P2541, DOI 10.1109/IGARSS.2015.7326329
   Gao B, 2023, ECOL INDIC, V151, DOI 10.1016/j.ecolind.2023.110291
   Giardina F, 2018, NAT GEOSCI, V11, P405, DOI 10.1038/s41561-018-0133-5
   Guo TT, 2020, PLANT PHYSIOL BIOCH, V154, P85, DOI 10.1016/j.plaphy.2020.06.008
   Hoover DL, 2014, ECOLOGY, V95, P2646, DOI 10.1890/13-2186.1
   Islam AMT, 2021, J ENVIRON MANAGE, V289, DOI 10.1016/j.jenvman.2021.112505
   Jiao WZ, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-24016-9
   Katul GG, 2009, PLANT CELL ENVIRON, V32, P968, DOI 10.1111/j.1365-3040.2009.01977.x
   Keenan TF, 2018, NAT CLIM CHANGE, V8, P825, DOI 10.1038/s41558-018-0258-y
   Knapp AK, 2017, NEW PHYTOL, V214, P41, DOI 10.1111/nph.14381
   Li CL, 2018, J CLEAN PROD, V179, P210, DOI 10.1016/j.jclepro.2018.01.113
   Li XY, 2019, AGR FOREST METEOROL, V269, P239, DOI 10.1016/j.agrformet.2019.01.036
   Lin DL, 2010, NEW PHYTOL, V188, P187, DOI 10.1111/j.1469-8137.2010.03347.x
   Liu DQ, 2024, AGR FOREST METEOROL, V347, DOI 10.1016/j.agrformet.2024.109918
   Lloret F, 2012, GLOBAL CHANGE BIOL, V18, P797, DOI 10.1111/j.1365-2486.2011.02624.x
   Macias-Fauria M, 2012, NAT CLIM CHANGE, V2, P613, DOI 10.1038/NCLIMATE1558
   Meng FH, 2023, AGR FOREST METEOROL, V341, DOI 10.1016/j.agrformet.2023.109689
   Miao LJ, 2016, NAT HAZARDS, V80, P727, DOI 10.1007/s11069-015-1992-3
   Nicolai-Shaw N, 2017, REMOTE SENS ENVIRON, V203, P216, DOI [10.1016/j.rse.2017.06.014, 10.1016/j.rse.201]
   Novick KA, 2016, NAT CLIM CHANGE, V6, P1023, DOI [10.1038/nclimate3114, 10.1038/NCLIMATE3114]
   Ombadi M, 2023, NATURE, V619, P305, DOI 10.1038/s41586-023-06092-7
   Parmesan C, 2003, NATURE, V421, P37, DOI 10.1038/nature01286
   Piao SL, 2019, SCI CHINA EARTH SCI, V62, P1551, DOI 10.1007/s11430-018-9363-5
   Piao SL, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms6018
   Piao SL, 2011, GLOBAL CHANGE BIOL, V17, P3228, DOI 10.1111/j.1365-2486.2011.02419.x
   Rammig A, 2015, BIOGEOSCIENCES, V12, P373, DOI 10.5194/bg-12-373-2015
   Resende AF, 2020, NEW PHYTOL, V227, P1790, DOI 10.1111/nph.16665
   Sapes G, 2021, NEW PHYTOL, V229, P3172, DOI 10.1111/nph.17134
   Seddon AWR, 2016, NATURE, V531, P229, DOI 10.1038/nature16986
   Seneviratne SI, 2010, EARTH-SCI REV, V99, P125, DOI 10.1016/j.earscirev.2010.02.004
   Sillmann J, 2008, CLIMATIC CHANGE, V86, P83, DOI 10.1007/s10584-007-9308-6
   Singh J, 2022, NAT CLIM CHANGE, V12, P163, DOI 10.1038/s41558-021-01276-3
   Smith MN, 2020, NAT PLANTS, V6, P1225, DOI 10.1038/s41477-020-00780-2
   Sulman BN, 2016, GEOPHYS RES LETT, V43, P9686, DOI 10.1002/2016GL069416
   Trenberth KE, 2014, NAT CLIM CHANGE, V4, P17, DOI 10.1038/NCLIMATE2067
   Vicente-Serrano SM, 2013, P NATL ACAD SCI USA, V110, P52, DOI 10.1073/pnas.1207068110
   Wu XC, 2018, GLOBAL CHANGE BIOL, V24, P504, DOI 10.1111/gcb.13920
   Xu YX, 2023, REMOTE SENS ENVIRON, V297, DOI 10.1016/j.rse.2023.113785
   Ye CC, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12152347
   Yuan WP, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aax1396
   Zeng X, 2022, GLOBAL CHANGE BIOL, V28, P6823, DOI 10.1111/gcb.16403
   Zhang P, 2020, SCIENCE, V370, P1095, DOI 10.1126/science.abb3368
   Zhang Y, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-32631-3
   Zhang Y, 2021, NAT ECOL EVOL, V5, P1490, DOI 10.1038/s41559-021-01551-8
   Zhang YC, 2023, AGR FOREST METEOROL, V331, DOI 10.1016/j.agrformet.2023.109323
   Zhong R, 2024, SCI TOTAL ENVIRON, V909, DOI 10.1016/j.scitotenv.2023.168488
   Zhou J, 2013, FOREST ECOL MANAG, V300, P33, DOI 10.1016/j.foreco.2013.01.007
   Zhou S, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aau5740
   Zscheischler J, 2017, SCI ADV, V3, DOI 10.1126/sciadv.1700263
   Zscheischler J, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/3/035001
NR 59
TC 0
Z9 0
U1 17
U2 17
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
EI 2351-9894
J9 GLOB ECOL CONSERV
JI Glob. Ecol. Conserv.
PD DEC
PY 2024
VL 56
AR e03292
DI 10.1016/j.gecco.2024.e03292
PG 14
WC Biodiversity Conservation; Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA M7T1N
UT WOS:001359513000001
OA gold
DA 2025-01-10
ER

PT J
AU Akomolafe, B
   Clarke, A
   Ayambire, R
AF Akomolafe, Bayode
   Clarke, Amelia
   Ayambire, Raphael
TI Climate Change Mitigation Perspectives from Sub-Saharan Africa: The
   Technical Pathways to Deep Decarbonization at the City Level
SO ATMOSPHERE
LA English
DT Article
DE Africa; cities; urban development; local government; climate; climate
   change; pathways; decarbonization; Sub-Saharan Africa; sustainable
   development
ID CARBON EMISSIONS; MULTILEVEL GOVERNANCE; ENERGY USE; CITIES; ADAPTATION;
   MANAGEMENT; RESPONSES; POLITICS; IMPACTS; SYSTEMS
AB The complex and multidimensional effect of climate change, coupled with low socioeconomic development, in Sub-Saharan Africa (SSA) makes the region vulnerable to the changing climate and threatens its inhabitants' survival, livelihood, and health. Subnational actions have been widely acclaimed as effective in combatting climate change. Local governments in SSA have been developing and implementing climate action plans to reduce greenhouse gas (GHG) emissions. In this article, we qualitatively assessed climate change mitigation technical pathways at the city level by studying four major African megacities' climate plans and actions. The cities studied are Accra, Ghana; Addis Ababa, Ethiopia; Lagos, Nigeria; and Nairobi, Kenya. This study provides insight into the novel and innovative policy design and instrumentation options to sustainably address climate change mitigation in SSA. With the past literature focusing on climate adaptation for the Global South, this study shows leading context-specific efforts in climate change mitigation that simultaneously address local sustainable development needs. Our assessment identified the prioritized technical pathways for climate change mitigation in the selected cities, as well as innovative techniques and areas for improvement. Given that it also identifies emerging best practices, this study's findings can be helpful to local governments and practitioners pursuing local deep decarbonization and international organizations supporting these programs.
C1 [Akomolafe, Bayode; Clarke, Amelia] Univ Waterloo, Sch Environm Enterprise & Dev SEED, Environm 3, Waterloo, ON N2L 3G1, Canada.
   [Ayambire, Raphael] Univ Manitoba, Dept City Planning, 66 Chancellor Circle, Winnipeg, MB R3T 2N2, Canada.
C3 University of Waterloo; University of Manitoba
RP Clarke, A (corresponding author), Univ Waterloo, Sch Environm Enterprise & Dev SEED, Environm 3, Waterloo, ON N2L 3G1, Canada.
EM bakomola@uwaterloo.ca; amelia.clarke@uwaterloo.ca;
   raphael.ayambire@umanitoba.ca
OI Ayambire, Raphael/0000-0002-3752-0830
CR Abiodun BJ, 2017, CLIMATIC CHANGE, V143, P399, DOI 10.1007/s10584-017-2001-5
   Abioja M O., 2021, African handbook of climate change adaptation, P275, DOI DOI 10.1007/978-3-030-45106-6_111
   Accra Metropolitan Assembly, 2021, C40 Cities
   Adepoju A, 2000, INT SOC SCI J, V52, P383, DOI 10.1111/1468-2451.00267
   AfDB, 2020, Drivers of Greenhouse Gas Emissions in Africa: Focus on Agriculture, Forestry and Other Land Use
   Agarana MC, 2016, PROCEDIA MANUF, V7, P596, DOI 10.1016/j.promfg.2016.12.089
   Åhman M, 2017, CLIM POLICY, V17, P634, DOI 10.1080/14693062.2016.1167009
   Altieri K., 2015, SDSN-IDDRI
   Apollo A, 2021, CLIMATE, V9, DOI 10.3390/cli9060093
   Atwoli L, 2022, BJPSYCH INT, V19, P86, DOI [10.20529/IJME.2022.083, 10.1192/bji.2022.14]
   Baarsch F, 2020, WORLD DEV, V126, DOI 10.1016/j.worlddev.2019.104699
   Barrett BFD, 2016, SUSTAINABILITY-BASEL, V8, DOI 10.3390/su8111197
   Bataille C, 2020, ENERGY STRATEG REV, V30, DOI 10.1016/j.esr.2020.100510
   Bernstein S, 2018, POLICY SCI, V51, P189, DOI 10.1007/s11077-018-9314-8
   Betsill MM, 2006, GLOBAL GOV, V12, P141, DOI 10.1163/19426720-01202004
   Bilal A., 2024, The Macroeconomic Impact of Climate Change: Global vs. Local Temperature
   Bossa AY, 2020, CLIMATE, V8, DOI 10.3390/cli8010011
   Broto VC, 2017, ENERG POLICY, V108, P755, DOI 10.1016/j.enpol.2017.01.009
   Bulkeley H, 2005, ENVIRON POLIT, V14, P42, DOI 10.1080/0964401042000310178
   Calderon C., 2018, Infrastructure development in Sub-Saharan Africa, DOI [10.1596/1813-9450-8425, DOI 10.1596/1813-9450-8425]
   Carbon City Neutral Alliance, 2014, Framework for Deep Carbon Reduction Planning, P134
   Carleton TA, 2016, SCIENCE, V353, DOI 10.1126/science.aad9837
   CDP CDP and ICLEI-Local Governments for Sustainability, 2022, About us
   Chen WY, 2015, CITIES, V44, P112, DOI 10.1016/j.cities.2015.01.005
   City of Addis Ababa Group C.C.C.L, 2021, Addis Ababa Climate Action Plan
   Clarke A., 2021, Guidebook for Climate Mitigation in Canadian Municipalities: Governance Options for Deep Decarbonization and Reaching Carbon Neutrality
   Collett KA, 2021, ENERGY STRATEG REV, V38, DOI 10.1016/j.esr.2021.100722
   Collier P, 2008, OXFORD REV ECON POL, V24, P337, DOI 10.1093/oxrep/grn019
   Connolly-Boutin L, 2016, REG ENVIRON CHANGE, V16, P385, DOI 10.1007/s10113-015-0761-x
   Couth R, 2010, WASTE MANAGE, V30, P2336, DOI 10.1016/j.wasman.2010.04.013
   Creswell J. W., 2012, QUAL INQ
   Cudjoe GP, 2021, CLIMATE, V9, DOI 10.3390/cli9100145
   Cunningham MA, 2021, CLIMATE, V9, DOI 10.3390/cli9040068
   Currie P.K., 2015, Masters Thesis
   Dada JT, 2021, FUTUR BUS J, V7, DOI 10.1186/s43093-021-00068-7
   Dahiru D., 2012, RES J ENVIRON EARTH, V4, P857
   Day R, 2016, ENERG POLICY, V93, P255, DOI 10.1016/j.enpol.2016.03.019
   Dioha MO, 2020, RENEW SUST ENERG REV, V117, DOI 10.1016/j.rser.2019.109510
   Dube K, 2024, J SUSTAIN TOUR, V32, P1811, DOI 10.1080/09669582.2023.2193355
   Eang ML., 2019, The Perspectives and Roles of Multinational Enterprises in Local Sustainable Development
   Eang M, 2023, BRQ-BUS RES Q, V26, P79, DOI 10.1177/23409444221140912
   Echendu AJ, 2022, SOC SCI-BASEL, V11, DOI 10.3390/socsci11020059
   Elias P, 2015, CURR OPIN ENV SUST, V13, P74, DOI 10.1016/j.cosust.2015.02.008
   Elijah VT, 2020, CLIMATE, V8, DOI 10.3390/cli8010003
   Fagbemi F, 2024, RES ECON, V78, P52, DOI 10.1016/j.rie.2024.01.001
   Faiyetole AA, 2019, INT SOCIOL, V34, P762, DOI 10.1177/0268580919867837
   Feor L, 2023, ENVIRONMENTS, V10, DOI 10.3390/environments10120203
   Gallagher CL, 2020, FRONT PUBLIC HEALTH, V8, DOI 10.3389/fpubh.2020.563358
   Gebre GG, 2021, CLIM RISK MANAG, V33, DOI 10.1016/j.crm.2021.100333
   Gillard R, 2016, WIRES CLIM CHANGE, V7, P251, DOI 10.1002/wcc.384
   Gilli M, 2024, J ENVIRON ECON MANAG, V127, DOI 10.1016/j.jeem.2024.103012
   Gross S., 2020, The challenge of decarbonizing heavy transport
   Güneralp B, 2017, P NATL ACAD SCI USA, V114, P8945, DOI 10.1073/pnas.1606035114
   Haile GG, 2020, EARTHS FUTURE, V8, DOI 10.1029/2020EF001502
   Haji S., 2016, Greenhouse Gas Emissions Inventory Report
   Haregu T.N., 2016, African Popul. Stud, V30, P2876, DOI [10.11564/30-2-889, DOI 10.11564/30-2-889]
   Haxeltine A., 2013, Social Frontiers: The Next Edge of Social Innovation Research
   Hendrix CS, 2007, POLIT GEOGR, V26, P695, DOI 10.1016/j.polgeo.2007.06.006
   Hogarth J.R., 2015, Low-Carbon Development in Sub-Saharan Africa, VVolume 10, DOI [10.17226/9690, DOI 10.17226/9690]
   Idowu IA, 2019, WASTE MANAGE, V87, P761, DOI 10.1016/j.wasman.2019.03.011
   Karimu A, 2015, OPEC ENERGY REV, V39, P322, DOI 10.1111/opec.12054
   Kennedy C, 2009, ENVIRON SCI TECHNOL, V43, P7297, DOI 10.1021/es900213p
   Kinda SR, 2019, COGENT ECON FINANC, V7, DOI 10.1080/23322039.2019.1640098
   Kling G, 2021, WORLD DEV, V137, DOI 10.1016/j.worlddev.2020.105131
   Koranteng C, 2011, ENERG BUILDINGS, V43, P555, DOI 10.1016/j.enbuild.2010.10.021
   Leal W, 2024, J CLEAN PROD, V438, DOI 10.1016/j.jclepro.2024.140794
   Lebling K., 2020, State of Climate Action-WRI
   Li X, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-28975-5
   Li XQ, 2022, CLIMATE, V10, DOI 10.3390/cli10110164
   Linton S., 2020, Masters Thesis
   Linton S, 2022, ENERGY RES SOC SCI, V86, DOI 10.1016/j.erss.2021.102422
   Linton S, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13010154
   Liousse C, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/3/035003
   Lombardi M, 2017, ENVIRON IMPACT ASSES, V66, P43, DOI 10.1016/j.eiar.2017.06.005
   Mapfumo P, 2017, CLIM DEV, V9, P439, DOI 10.1080/17565529.2015.1040365
   Mbow C, 2014, CURR OPIN ENV SUST, V6, P8, DOI 10.1016/j.cosust.2013.09.002
   Mercader-Moyano P, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12197914
   Ministry of Environment and Water Resources Lagos Climate Action Plan, 2020, Lagos
   Moore F.C., 2024, Learning, Catastrophic Risk, and Ambiguity in the Climate Change Era
   Mordecai EA, 2020, LANCET PLANET HEALTH, V4, pE416, DOI 10.1016/S2542-5196(20)30178-9
   Muluneh Melese Genete, 2021, Agriculture and Food Security, V10, DOI 10.1186/s40066-021-00318-5
   Musah-Surugu IJ, 2019, VOLUNTAS, V30, P312, DOI 10.1007/s11266-018-9962-5
   Nairobi City County, 2020, Nairobi City County Climate Action Plan
   Nairobi City County, 2019, Nairobi City County Air Quality Action Plan (2019-2023)
   Njoku P.O., 2018, OPEN ENV SCI, V10, P1, DOI [DOI 10.2174/1876325101810010001, 10.2174/1876325101810010001]
   Oberthür S, 2021, EARTH SYST GOV-NETH, V8, DOI 10.1016/j.esg.2020.100072
   Ogle SM, 2014, GLOBAL CHANGE BIOL, V20, P1, DOI 10.1111/gcb.12361
   Olubunmi OA, 2016, RENEW SUST ENERG REV, V59, P1611, DOI 10.1016/j.rser.2016.01.028
   Papadis E, 2020, ENERGY, V205, DOI 10.1016/j.energy.2020.118025
   Pelletier J, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aadc9a
   Pinkovskiy M, 2014, J ECON GROWTH, V19, P311, DOI 10.1007/s10887-014-9103-y
   Ravishankara A.R., 2021, BENEFITS COSTS MITIG
   Grau HR, 2008, ECOL SOC, V13
   Rissman J, 2020, APPL ENERG, V266, DOI 10.1016/j.apenergy.2020.114848
   Schilling J, 2020, REG ENVIRON CHANGE, V20, DOI 10.1007/s10113-020-01597-7
   Serdeczny O, 2017, REG ENVIRON CHANGE, V17, P1585, DOI 10.1007/s10113-015-0910-2
   Seto KC, 2021, ANNU REV ENV RESOUR, V46, P377, DOI 10.1146/annurev-environ-050120-113117
   Smith P, 2014, CLIMATE CHANGE 2014: MITIGATION OF CLIMATE CHANGE, P811
   Smith P, 2014, GLOBAL CHANGE BIOL, V20, P2708, DOI 10.1111/gcb.12561
   Somorin O. A., 2010, African Journal of Environmental Science and Technology, V4, P903
   Stadtler L, 2024, J MANAGE STUD, V61, P3327, DOI 10.1111/joms.13053
   Sverdlik A., 2021, Nairobi: City Scoping Study
   Taylor I., 2014, BROWN J WORLD AFFAIR, V21, P143
   Thambiran T, 2011, ATMOS ENVIRON, V45, P2683, DOI 10.1016/j.atmosenv.2011.02.059
   Tidman R, 2021, T ROY SOC TROP MED H, V115, P147, DOI 10.1093/trstmh/traa192
   Tomaszewski LE, 2020, INT J QUAL METH, V19, DOI 10.1177/1609406920967174
   Uduku O., 2021, African-CitiesOrg
   Uller C.M., 2013, African Lessons on Climate Change Risks for Agriculture
   Vermeulen SJ, 2012, ANNU REV ENV RESOUR, V37, P195, DOI 10.1146/annurev-environ-020411-130608
   Vörösmarty CJ, 2010, NATURE, V467, P555, DOI 10.1038/nature09440
   Wahab S., 2012, Masters Thesis
   Weldeghebrael E.H., 2021, Addis Ababa: City Scoping Study
   Wijaya A.S., 2014, IOP Conference Series: Earth and Environmental Science
   Williams A, 2012, ARCHIT DESIGN, V82, P66, DOI 10.1002/ad.1351
   Yengoh GT, 2020, ATMOSPHERE-BASEL, V11, DOI 10.3390/atmos11070753
NR 115
TC 1
Z9 1
U1 3
U2 3
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4433
J9 ATMOSPHERE-BASEL
JI Atmosphere
PD OCT
PY 2024
VL 15
IS 10
AR 1190
DI 10.3390/atmos15101190
PG 20
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA K2B6L
UT WOS:001341986700001
OA gold
DA 2025-01-10
ER

PT J
AU Zhao, J
   Guo, F
   Zhang, HC
   Dong, J
AF Zhao, Jun
   Guo, Fei
   Zhang, Hongchi
   Dong, Jing
TI Mechanisms of non-stationary influence of urban form on the diurnal
   thermal environment based on machine learning and MGWR analysis
SO SUSTAINABLE CITIES AND SOCIETY
LA English
DT Article
DE Urban form factors; Local climate zones; Land surface temperature;
   Multiscale geographically weighted regression
ID LOCAL CLIMATE ZONES; LAND-SURFACE TEMPERATURE; HEAT-ISLAND INTENSITY;
   SOCIOECONOMIC-FACTORS; AIR-TEMPERATURE; COVER; CONFIGURATION; SHANGHAI;
   DYNAMICS; FRACTION
AB The non-stationary impact of urban form at block scale on the diurnal thermal environment has not been extensively studied. To fill the gap, a comprehensive multi-scale research framework was constructed, integrating machine learning algorithms and multiscale geographically weighted regression (MGWR) analysis. The urban form types were extracted by machine learning algorithms from 2282 blocks of Dalian, a coastal city, and the contribution to the diurnal land surface temperature (LST) was evaluated. Based on MGWR, the nonstationary effects of urban form, human activity and spatial location on the diurnal LST were quantified, which indicated the contributing factors to the diurnal thermal differences among the form types. The result was as follows: 1) Blocks characterized by low vegetation and mid/low-rise buildings had the highest warming contribution for diurnal LST. 2) The impact of sky view factor (SVF) on diurnal temperature amplitude exhibited no significant spatial-temporal heterogeneity. 3) Building density had a prominent effect on diurnal temperature amplitude. 4) High-vegetation and open (SVF > 0.5) mid/mid-high/low-rise (15-50 m) buildings were recommended. This study provides a more precise basis for policymakers to develop climate adaptation strategies throughout day and night, particularly for coastal cities.
C1 [Zhao, Jun; Guo, Fei; Zhang, Hongchi; Dong, Jing] Dalian Univ Technol, Sch Architecture & Fine Art, Dalian, Peoples R China.
C3 Dalian University of Technology
RP Guo, F (corresponding author), Dalian Univ Technol, Sch Architecture & Fine Art, Dalian, Peoples R China.
EM guofei@dlut.edu.cn
RI Dong, Jing/KDM-6171-2024; Zhao, Jun/S-2104-2018; Guo, Fei/AIC-4983-2022
OI Dong, Jing/0000-0001-7054-5434; Guo, Fei/0000-0001-5739-9436
FU National Social Science Fund of China [18BGL233]
FX The authors declare the following financial interests/personal re-
   lationships which may be considered as potential competing interests:
   This study was supported by the National Social Science Fund of China
   (No. 18BGL233) .
CR Arthur D, 2007, PROCEEDINGS OF THE EIGHTEENTH ANNUAL ACM-SIAM SYMPOSIUM ON DISCRETE ALGORITHMS, P1027
   Aslam A, 2022, URBAN CLIM, V42, DOI 10.1016/j.uclim.2022.101120
   Badaro-Saliba N, 2021, URBAN CLIM, V37, DOI 10.1016/j.uclim.2021.100846
   Beck HE, 2018, SCI DATA, V5, DOI 10.1038/sdata.2018.214
   Cai Z, 2018, SUSTAIN CITIES SOC, V39, P487, DOI 10.1016/j.scs.2018.02.033
   Chen B, 2019, CLIM DYNAM, V52, P6377, DOI 10.1007/s00382-018-4528-1
   Chen CM, 2022, URBAN CLIM, V45, DOI 10.1016/j.uclim.2022.101248
   Chen XL, 2006, REMOTE SENS ENVIRON, V104, P133, DOI 10.1016/j.rse.2005.11.016
   Chen XL, 2020, URBAN CLIM, V31, DOI 10.1016/j.uclim.2019.100568
   Chen XA, 2021, BUILD ENVIRON, V197, DOI 10.1016/j.buildenv.2021.107878
   Chen YP, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12072974
   Cheng LD, 2019, SUSTAIN CITIES SOC, V47, DOI 10.1016/j.scs.2019.101501
   Chun B, 2017, ENVIRON PLAN B-URBAN, V44, P308, DOI 10.1177/0265813515624685
   Coseo P, 2014, LANDSCAPE URBAN PLAN, V125, P117, DOI 10.1016/j.landurbplan.2014.02.019
   Demuzere M, 2021, FRONT ENV SCI-SWITZ, V9, DOI 10.3389/fenvs.2021.637455
   Ding W, 2022, BUILD ENVIRON, V226, DOI 10.1016/j.buildenv.2022.109697
   Dong J, 2022, SCI TOTAL ENVIRON, V834, DOI 10.1016/j.scitotenv.2022.155307
   Equere V, 2020, SUSTAIN CITIES SOC, V56, DOI 10.1016/j.scs.2020.102021
   Gao SJ, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac9ecc
   Gao YJ, 2022, BUILD ENVIRON, V216, DOI 10.1016/j.buildenv.2022.109037
   Geletic J, 2019, BUILD ENVIRON, V156, P21, DOI 10.1016/j.buildenv.2019.04.011
   Giridharan R, 2007, BUILD ENVIRON, V42, P3669, DOI 10.1016/j.buildenv.2006.09.011
   Guo F, 2023, SUSTAIN CITIES SOC, V88, DOI 10.1016/j.scs.2022.104271
   Guo F, 2018, BUILD ENVIRON, V145, P177, DOI 10.1016/j.buildenv.2018.09.010
   Guo JM, 2020, SUSTAIN CITIES SOC, V61, DOI 10.1016/j.scs.2020.102286
   Hammerberg K, 2018, INT J CLIMATOL, V38, pE1241, DOI 10.1002/joc.5447
   Hämmerle M, 2011, THEOR APPL CLIMATOL, V105, P521, DOI 10.1007/s00704-011-0402-3
   He BJ, 2021, SUSTAIN CITIES SOC, V75, DOI 10.1016/j.scs.2021.103361
   Hidalgo J, 2019, URBAN CLIM, V27, P64, DOI 10.1016/j.uclim.2018.10.004
   Huang F, 2023, REMOTE SENS ENVIRON, V292, DOI 10.1016/j.rse.2023.113573
   Huang HC, 2020, SUSTAIN CITIES SOC, V55, DOI 10.1016/j.scs.2020.102024
   Huh MH, 2002, RECENT ADVANCES IN STATISTICAL RESEARCH AND DATA ANALYSIS, P115
   Joshi MY, 2022, BUILD ENVIRON, V224, DOI 10.1016/j.buildenv.2022.109574
   Lelovics E, 2014, CLIM RES, V60, P51, DOI 10.3354/cr01220
   Lemoine-Rodríguez R, 2022, SCI TOTAL ENVIRON, V830, DOI 10.1016/j.scitotenv.2022.154570
   Li JX, 2011, REMOTE SENS ENVIRON, V115, P3249, DOI 10.1016/j.rse.2011.07.008
   Li WJ, 2016, INT J REMOTE SENS, V37, P5632, DOI 10.1080/01431161.2016.1246775
   Li ZL, 2013, REMOTE SENS ENVIRON, V131, P14, DOI 10.1016/j.rse.2012.12.008
   Liu DD, 2020, ISPRS J PHOTOGRAMM, V159, P337, DOI 10.1016/j.isprsjprs.2019.11.021
   Liu HM, 2021, SCI TOTAL ENVIRON, V771, DOI 10.1016/j.scitotenv.2020.144810
   Liu HM, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11091016
   Lu YP, 2021, SUSTAIN CITIES SOC, V72, DOI 10.1016/j.scs.2021.103070
   Luo JM, 2023, SENSORS-BASEL, V23, DOI 10.3390/s23229206
   Mathew Aneesh, 2018, Remote Sensing Applications: Society and Environment, V11, P119, DOI 10.1016/j.rsase.2018.05.003
   Min M, 2019, SUSTAIN CITIES SOC, V50, DOI 10.1016/j.scs.2019.101637
   Montandon LM, 2008, REMOTE SENS ENVIRON, V112, P1835, DOI 10.1016/j.rse.2007.09.007
   Mushore TD, 2022, APPL SCI-BASEL, V12, DOI 10.3390/app122412774
   Myint SW, 2013, LANDSCAPE ECOL, V28, P959, DOI 10.1007/s10980-013-9868-y
   Ng E, 2011, LANDSCAPE URBAN PLAN, V101, P59, DOI 10.1016/j.landurbplan.2011.01.004
   Oliveira A, 2020, URBAN CLIM, V33, DOI 10.1016/j.uclim.2020.100631
   Oshan TM, 2019, ISPRS INT GEO-INF, V8, DOI 10.3390/ijgi8060269
   Overmars KP, 2003, ECOL MODEL, V164, P257, DOI 10.1016/S0304-3800(03)00070-X
   Peng YL, 2017, ENRGY PROCED, V142, P2884, DOI 10.1016/j.egypro.2017.12.412
   Perera NGR, 2018, URBAN CLIM, V23, P188, DOI 10.1016/j.uclim.2016.11.006
   Quan SJ, 2021, BUILD ENVIRON, V196, DOI 10.1016/j.buildenv.2021.107791
   Quan SJ, 2017, ENRGY PROCED, V105, P3777, DOI 10.1016/j.egypro.2017.03.883
   RAUPACH MR, 1994, BOUND-LAY METEOROL, V71, P211, DOI 10.1007/BF00709229
   Rodler A, 2019, URBAN CLIM, V28, DOI 10.1016/j.uclim.2019.100457
   Sheng L, 2017, ECOL INDIC, V72, P738, DOI 10.1016/j.ecolind.2016.09.009
   Shi ZP, 2022, ENVIRON SCI POLLUT R, V29, P74394, DOI [10.1007/s11356-022-21037-9, 10.16180/j.cnki.issn1007-7820.2022.09.002]
   Siddiqui A, 2021, SUSTAIN CITIES SOC, V75, DOI 10.1016/j.scs.2021.103374
   Silva AGL, 2021, BUILD ENVIRON, V192, DOI 10.1016/j.buildenv.2021.107634
   Sinaga KP, 2020, IEEE ACCESS, V8, P80716, DOI 10.1109/ACCESS.2020.2988796
   Speight JG, 2015, WOODHEAD PUBL SER EN, P175, DOI 10.1016/B978-0-85709-802-3.00008-4
   Stewart ID, 2012, B AM METEOROL SOC, V93, P1879, DOI 10.1175/BAMS-D-11-00019.1
   Su YF, 2012, LANDSCAPE URBAN PLAN, V107, P172, DOI 10.1016/j.landurbplan.2012.05.016
   Sun YW, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11080959
   Sun YW, 2018, SUSTAIN CITIES SOC, V40, P284, DOI 10.1016/j.scs.2017.12.004
   Verdonck ML, 2018, LANDSCAPE URBAN PLAN, V178, P183, DOI 10.1016/j.landurbplan.2018.06.004
   Wang B, 2017, RENEW ENERG, V113, P989, DOI 10.1016/j.renene.2017.06.057
   Wang F, 2015, REMOTE SENS-BASEL, V7, P4268, DOI 10.3390/rs70404268
   Wang J, 2020, ISPRS J PHOTOGRAMM, V159, P78, DOI 10.1016/j.isprsjprs.2019.11.001
   Wang J, 2016, INT J APPL EARTH OBS, V45, P55, DOI 10.1016/j.jag.2015.11.006
   Wang R, 2018, URBAN CLIM, V24, P567, DOI 10.1016/j.uclim.2017.10.001
   Weng QH, 2009, ISPRS J PHOTOGRAMM, V64, P335, DOI 10.1016/j.isprsjprs.2009.03.007
   Xu ZW, 2017, ENVIRON RES, V156, P770, DOI 10.1016/j.envres.2017.05.005
   Xue XY, 2022, SCI TOTAL ENVIRON, V843, DOI 10.1016/j.scitotenv.2022.156829
   Yang J, 2021, SUSTAIN CITIES SOC, V72, DOI 10.1016/j.scs.2021.103045
   Yang J, 2020, J CLEAN PROD, V275, DOI 10.1016/j.jclepro.2020.123767
   Yao X, 2022, SUSTAIN CITIES SOC, V86, DOI 10.1016/j.scs.2022.104165
   Yin CH, 2018, SCI TOTAL ENVIRON, V634, P696, DOI 10.1016/j.scitotenv.2018.03.350
   Yoo C, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12213552
   Youme SK, 2022, INT GEOSCI REMOTE SE, P3139, DOI 10.1109/IGARSS46834.2022.9883206
   Yu HT, 2019, J TRANSP GEOGR, V75, P147, DOI 10.1016/j.jtrangeo.2019.01.004
   Yu ZW, 2019, SCI TOTAL ENVIRON, V674, P242, DOI 10.1016/j.scitotenv.2019.04.088
   Zawadzka JE, 2021, LANDSCAPE URBAN PLAN, V214, DOI 10.1016/j.landurbplan.2021.104163
   Zhang HC, 2022, FRONT PUBLIC HEALTH, V10, DOI 10.3389/fpubh.2022.1024757
   Zhang P, 2023, LANDSCAPE URBAN PLAN, V237, DOI 10.1016/j.landurbplan.2023.104776
   Zheng YS, 2018, URBAN CLIM, V24, P419, DOI 10.1016/j.uclim.2017.05.008
   Zhou XL, 2020, SUSTAIN CITIES SOC, V55, DOI 10.1016/j.scs.2020.102060
   Zhou YF, 2021, ATMOS RES, V250, DOI 10.1016/j.atmosres.2020.105409
NR 91
TC 22
Z9 22
U1 99
U2 151
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 FEB
PY 2024
VL 101
AR 105194
DI 10.1016/j.scs.2024.105194
EA JAN 2024
PG 16
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 IW5M9
UT WOS:001169388100001
HC Y
HP N
DA 2025-01-10
ER

PT J
AU Dong, J
   Schwartz, Y
   Korolija, I
   Mumovic, D
AF Dong, Jie
   Schwartz, Yair
   Korolija, Ivan
   Mumovic, Dejan
TI The impact of climate change on cognitive performance of children in
   English school stock: A simulation study
SO BUILDING AND ENVIRONMENT
LA English
DT Article
DE School; Climate change; Cognitive performance; Climate resilience;
   Climate adaptation; Building stock modelling
ID INDOOR AIR-QUALITY; THERMAL COMFORT; OVERHEATING RISK; VENTILATION
   RATES; TEMPERATURE; CLASSROOMS; BUILDINGS; DWELLINGS
AB Children in England spend around 30% of their time in schools to gain knowledge and skills. Climate change could impact schools' thermal environments and children's learning performance by impairing their cognitive ability. This study presents an evaluation approach to investigating and quantifying climate change's impact on the cognitive performance of children across English school stocks. The study also evaluates the potential of possible strategies for mitigating the impacts of climate change. The results show that future climates are projected to increase cognitive performance loss of children in school archetypes representative of school stocks, with variations based on regional climate characteristics. Increasing ventilation rates proves to be an effective means of reducing cognitive performance loss, while its effectiveness diminishes as outdoor temperatures rise in the future. Thus, the introduction of air conditioning becomes a potentially more beneficial strategy, despite the associated increase in cooling energy demand. Moreover, higher ventilation rates in air-conditioned classrooms can further improve children's cognitive performance. The use of cognitive performance loss as a Key Performance Indicator (KPI) allows for better communication and understanding of climate change risks faced by schools among building and non-building experts. The proposed evaluation approach remains adjustable and can be continuously updated and enhanced as new insights from psychological research emerge.
C1 [Dong, Jie; Schwartz, Yair; Korolija, Ivan; Mumovic, Dejan] UCL, Inst Environm Design & Engn, Cent House,14 Upper Woburn Pl, London WC1H 0 NN, England.
C3 University of London; University College London
RP Dong, J (corresponding author), UCL, Inst Environm Design & Engn, Cent House,14 Upper Woburn Pl, London WC1H 0 NN, England.
EM ucbqjdo@ucl.ac.uk
RI Korolija, Ivan/KIA-3955-2024
OI Korolija, Ivan/0000-0003-3153-6070; Mumovic, Dejan/0000-0002-4914-9004;
   Schwartz, Yair/0000-0002-3526-2137
FU Engineering and Physical Sciences Research Council (EPSRC)
   [EP/T000090/1]; EPSRC [EP/T000090/1] Funding Source: UKRI
FX This work was partially funded by an Engineering and Physical Sciences
   Research Council (EPSRC) grant: Advancing School Performance: Indoor
   environmental quality, Resilience and Educational outcomes (ASPIRE,
   EP/T000090/1).
CR Akkose G, 2021, J BUILD ENG, V40, DOI 10.1016/j.jobe.2021.102294
   Altomonte S, 2020, BUILD ENVIRON, V180, DOI 10.1016/j.buildenv.2020.106949
   Amer O., 2015, International Journal of Environmental Science and Development, V6, P111, DOI DOI 10.7763/IJESD.2015.V6.571
   [Anonymous], 2016, WEATH DAT
   [Anonymous], 2022, AR5 SYNTH REP CLIM C
   Attia S, 2021, ENERG BUILDINGS, V239, DOI 10.1016/j.enbuild.2021.110869
   Azar E, 2020, ENERG BUILDINGS, V224, DOI 10.1016/j.enbuild.2020.110292
   Bakó-Biró Z, 2012, BUILD ENVIRON, V48, P215, DOI 10.1016/j.buildenv.2011.08.018
   CIBSE, 2008, CIBSE TM46, P13
   Clements-Croome DJ, 2008, BUILD ENVIRON, V43, P362, DOI 10.1016/j.buildenv.2006.03.018
   Coley D, 2012, BUILD ENVIRON, V55, P159, DOI 10.1016/j.buildenv.2011.12.011
   De Giuli V, 2012, BUILD ENVIRON, V56, P335, DOI 10.1016/j.buildenv.2012.03.024
   DfE, 2018, BB 101 GUID VENT THE
   Dodoo A, 2016, ENERGY, V97, P534, DOI 10.1016/j.energy.2015.12.086
   Dong J, 2023, BUILD SERV ENG RES T, V44, P333, DOI 10.1177/01436244231163084
   Dorizas PV, 2015, ENVIRON MONIT ASSESS, V187, DOI 10.1007/s10661-015-4503-9
   Duran Ö, 2021, J BUILD ENG, V42, DOI 10.1016/j.jobe.2021.102746
   Grassie D, 2022, BUILD CITIES, V3, P204, DOI 10.5334/bc.159
   Gupta R, 2015, BUILD SERV ENG RES T, V36, P196, DOI 10.1177/0143624414566242
   Hamdy M, 2017, BUILD ENVIRON, V122, P307, DOI 10.1016/j.buildenv.2017.06.031
   Hancock PA, 1998, ERGONOMICS, V41, P1169, DOI 10.1080/001401398186469
   Haverinen-Shaughnessy U, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0136165
   Homaei S, 2021, BUILD ENVIRON, V201, DOI 10.1016/j.buildenv.2021.108022
   Hviid CA, 2020, BUILD ENVIRON, V171, DOI 10.1016/j.buildenv.2019.106608
   Hwang RL, 2022, BUILD ENVIRON, V222, DOI 10.1016/j.buildenv.2022.109434
   Jaber AR, 2017, ENRGY PROCED, V122, P451, DOI 10.1016/j.egypro.2017.07.378
   Jiang J, 2021, BUILD ENVIRON, V196, DOI 10.1016/j.buildenv.2021.107803
   Jiang J, 2018, BUILD ENVIRON, V134, P102, DOI 10.1016/j.buildenv.2018.02.036
   Kavgic M, 2010, BUILD ENVIRON, V45, P1683, DOI 10.1016/j.buildenv.2010.01.021
   Kingsborough A, 2017, CLIM RISK MANAG, V16, P73, DOI 10.1016/j.crm.2017.01.001
   Korsavi SS, 2020, ENERG BUILDINGS, V214, DOI 10.1016/j.enbuild.2020.109857
   Kükrer E, 2021, J BUILD ENG, V44, DOI 10.1016/j.jobe.2021.102697
   Li H, 2021, J BUILD PERFORM SIMU, V14, P814, DOI 10.1080/19401493.2021.1876771
   Liu JJ, 2021, ENERG BUILDINGS, V247, DOI 10.1016/j.enbuild.2021.111124
   Mavrogianni A, 2014, BUILD ENVIRON, V78, P183, DOI 10.1016/j.buildenv.2014.04.008
   Mavrogianni A, 2012, BUILD ENVIRON, V55, P117, DOI 10.1016/j.buildenv.2011.12.003
   Mendell MJ, 2016, INDOOR AIR, V26, P546, DOI 10.1111/ina.12241
   Mohamed S, 2021, ENERG BUILDINGS, V250, DOI 10.1016/j.enbuild.2021.111291
   Montazami A, 2015, RENEW SUST ENERG REV, V46, P249, DOI 10.1016/j.rser.2015.02.012
   Mumovic D, 2009, BUILD ENVIRON, V44, P1466, DOI 10.1016/j.buildenv.2008.06.014
   Mumovic D, 2015, DESIGNING INTELLIGEN
   Mylona A, 2012, BUILD SERV ENG RES T, V33, P51, DOI 10.1177/0143624411428951
   NCM, 2016, National Calculation Methodology (NCM) Modelling Guide (For Buildings Other than Dwellings in England)
   Oikonomou E, 2012, BUILD ENVIRON, V57, P223, DOI 10.1016/j.buildenv.2012.04.002
   Pathan A, 2017, ENERG BUILDINGS, V141, P361, DOI 10.1016/j.enbuild.2017.02.049
   Porras-Salazar JA, 2021, BUILD ENVIRON, V203, DOI 10.1016/j.buildenv.2021.108037
   Sadrizadeh S, 2022, J BUILD ENG, V57, DOI 10.1016/j.jobe.2022.104908
   Schools, 2022, PUP THEIR CHAR
   Schwartz Y, 2021, ENERG BUILDINGS, V249, DOI 10.1016/j.enbuild.2021.111249
   Schwartz Y, 2022, ENERG BUILDINGS, V254, DOI 10.1016/j.enbuild.2021.111566
   Seppanen O., 2005, Ventilation and work performance in office work
   Shi YQ, 2021, FRONT PSYCHOL, V12, DOI 10.3389/fpsyg.2021.774548
   Singh MK, 2019, ENERG BUILDINGS, V188, P149, DOI 10.1016/j.enbuild.2019.01.051
   Siu CY, 2023, BUILD ENVIRON, V234, DOI 10.1016/j.buildenv.2023.110124
   Taylor J, 2014, INDOOR AIR, V24, P639, DOI 10.1111/ina.12116
   Teli D, 2013, BUILD RES INF, V41, P301, DOI 10.1080/09613218.2013.773493
   van Hooff T, 2014, BUILD ENVIRON, V82, P300, DOI 10.1016/j.buildenv.2014.08.027
   Vilia PN, 2017, FRONT PSYCHOL, V8, DOI 10.3389/fpsyg.2017.01064
   Wang C, 2021, BUILD ENVIRON, V193, DOI 10.1016/j.buildenv.2021.107647
   Wargocki P, 2020, BUILD ENVIRON, V173, DOI 10.1016/j.buildenv.2020.106749
   Wargocki P, 2019, BUILD ENVIRON, V157, P197, DOI 10.1016/j.buildenv.2019.04.046
   Wargocki P, 2017, BUILD ENVIRON, V112, P359, DOI 10.1016/j.buildenv.2016.11.020
   Wargocki P, 2013, BUILD ENVIRON, V59, P581, DOI 10.1016/j.buildenv.2012.10.007
   Yeganeh AJ, 2018, BUILD ENVIRON, V143, P701, DOI 10.1016/j.buildenv.2018.07.002
   Zhang F, 2019, APPL ENERG, V236, P760, DOI 10.1016/j.apenergy.2018.12.005
NR 65
TC 7
Z9 7
U1 6
U2 31
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 SEP 1
PY 2023
VL 243
AR 110607
DI 10.1016/j.buildenv.2023.110607
EA JUL 2023
PG 15
WC Construction & Building Technology; Engineering, Environmental;
   Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Engineering
GA P0CS1
UT WOS:001047410400001
OA Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Jiang, YF
   Jiang, SD
   Shi, TM
AF Jiang, Yunfang
   Jiang, Shidan
   Shi, Tiemao
TI Comparative Study on the Cooling Effects of Green Space Patterns in
   Waterfront Build-Up Blocks: An Experience from Shanghai
SO INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
LA English
DT Article
DE green space network; green space pattern; spatial morphology; cooling
   effect; ENVI-met simulation; boosted regression trees (BRT); marginal
   effect (ME); Shanghai
ID URBAN HEAT-ISLAND; REMOTE-SENSING DATA; SPATIAL-PATTERN; HABITAT
   AVAILABILITY; SURFACE-TEMPERATURE; IMPACT; AIR; CONNECTIVITY;
   VEGETATION; SCALE
AB Different structural patterns of waterfront green space networks in built-up areas have different synergistic cooling characteristics in cities. This study's aim is to determine what kinds of spatial structures and morphologies of waterfront green spaces offer a good cooling effect, combined with three different typical patterns in Shanghai. A multidimensional spatial influence variable system based on the cooling effect was constructed to describe the spatial structural and morphological factors of the green space network. The ENVI-met 4.3 software, developed by Michael Bruse at Bochum, German, was used to simulate the microclimate distribution data, combined with the boosted regression tree (BRT) model and the correlation analysis method. The results showed that at the network level, the distance from the water body and the connectivity of green space had a stronger cooling correlation. The orientation of green corridors consistent with a summer monsoon had larger cooling effect ranges. In terms of spatial morphology, the vegetation sky view factor (SVF) and Vegetation Surface Albedo (VSAlbedo) had an important correlation with air temperature (T), and the green corridor with a 20-25 m width had the largest marginal effect on cooling. These results will provide useful guidance for urban climate adaptive planning and design.
C1 [Jiang, Yunfang; Jiang, Shidan] East China Normal Univ, Ctr Modern Chinese City Studies, Sch Urban & Reg Sci, Shanghai 200062, Peoples R China.
   [Jiang, Yunfang; Jiang, Shidan] Inst Ecochongming, Shanghai 202162, Peoples R China.
   [Shi, Tiemao] Shenyang Jianzhu Univ, Inst Spatial Planning & Design, Shenyang 110168, Peoples R China.
C3 East China Normal University; Shenyang Jianzhu University
RP Jiang, YF (corresponding author), East China Normal Univ, Ctr Modern Chinese City Studies, Sch Urban & Reg Sci, Shanghai 200062, Peoples R China.; Jiang, YF (corresponding author), Inst Ecochongming, Shanghai 202162, Peoples R China.
EM yfjiang@re.ecnu.edu.cn; 51183902011@stu.ecnu.edu.cn; tiemaos@sjzu.edu.cn
OI Jiang, Yunfang/0000-0002-5025-4741
FU National Natural Science Foundation of China [51878279, 51878418,
   51578344]
FX This research was funded by the National Natural Science Foundation of
   China project (Grant Nos. 51878279; 51878418, and 51578344).
CR Alavipanah S, 2018, J CLEAN PROD, V177, P115, DOI 10.1016/j.jclepro.2017.12.187
   Ballinas M, 2016, URBAN FOR URBAN GREE, V20, P152, DOI 10.1016/j.ufug.2016.08.004
   Bernard J, 2018, CLIMATE, V6, DOI 10.3390/cli6030060
   Bodin Ö, 2010, ECOL MODEL, V221, P2393, DOI 10.1016/j.ecolmodel.2010.06.017
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   Bruse M, 1998, ENVIRON MODELL SOFTW, V13, P373, DOI 10.1016/S1364-8152(98)00042-5
   Chen M, 2019, BUILD ENVIRON, V158, P1, DOI 10.1016/j.buildenv.2019.04.058
   Debbage N, 2015, COMPUT ENVIRON URBAN, V54, P181, DOI 10.1016/j.compenvurbsys.2015.08.002
   Du HY, 2019, ECOL INDIC, V106, DOI 10.1016/j.ecolind.2019.105501
   Elith J, 2008, J ANIM ECOL, V77, P802, DOI 10.1111/j.1365-2656.2008.01390.x
   Forman RTT, 2016, LANDSCAPE ECOL, V31, P1653, DOI 10.1007/s10980-016-0424-4
   Grunwald L, 2020, LANDSCAPE URBAN PLAN, V201, DOI 10.1016/j.landurbplan.2020.103843
   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
   H Du, 2016, CHINA ECOL INDIC, V67, P31, DOI [10.1016/j.ecolind.2016.02.040, DOI 10.1016/J.ECOLIND.2016.02.040]
   Hathway EA, 2012, BUILD ENVIRON, V58, P14, DOI 10.1016/j.buildenv.2012.06.013
   Herb WR, 2005, WATER RESOUR RES, V41, DOI 10.1029/2003WR002613
   Hu YF, 2020, J ENVIRON MANAGE, V266, DOI 10.1016/j.jenvman.2020.110424
   Jaeger JAG, 2000, LANDSCAPE ECOL, V15, P115, DOI 10.1023/A:1008129329289
   Jaganmohan M, 2016, J ENVIRON QUAL, V45, P134, DOI 10.2134/jeq2015.01.0062
   JIANG YF, 2018, SUSTAINABILITY-BASEL, V10, DOI DOI 10.3390/su10093189
   Jiang YF, 2016, CITIES, V59, P80, DOI 10.1016/j.cities.2016.06.002
   Kong FH, 2014, LANDSCAPE URBAN PLAN, V128, P35, DOI 10.1016/j.landurbplan.2014.04.018
   Kruger EL, 2011, BUILD ENVIRON, V46, P621, DOI 10.1016/j.buildenv.2010.09.006
   Kuang WH, 2015, LANDSCAPE ECOL, V30, P357, DOI 10.1007/s10980-014-0128-6
   Lehmann I, 2014, ECOL INDIC, V42, P58, DOI 10.1016/j.ecolind.2014.02.036
   Liu YH, 2019, ECOL ENG, V140, DOI 10.1016/j.ecoleng.2019.105594
   Masoudi M, 2019, LANDSCAPE URBAN PLAN, V184, P44, DOI 10.1016/j.landurbplan.2018.10.023
   Monteiro MV, 2016, URBAN FOR URBAN GREE, V16, P160, DOI 10.1016/j.ufug.2016.02.008
   Mukhopadhyay S, 2003, IEEE T IMAGE PROCESS, V12, P533, DOI 10.1109/TIP.2003.810757
   Niu JQ, 2020, SCI TOTAL ENVIRON, V728, DOI 10.1016/j.scitotenv.2020.138757
   Nouri H, 2019, LANDSCAPE URBAN PLAN, V190, DOI 10.1016/j.landurbplan.2019.103613
   OKE TR, 1982, Q J ROY METEOR SOC, V108, P1, DOI 10.1002/qj.49710845502
   Oliveira S, 2011, BUILD ENVIRON, V46, P2186, DOI 10.1016/j.buildenv.2011.04.034
   Ostapowicz K, 2008, LANDSCAPE ECOL, V23, P1107, DOI 10.1007/s10980-008-9271-2
   Pascual-Hortal L, 2006, LANDSCAPE ECOL, V21, P959, DOI 10.1007/s10980-006-0013-z
   Peng J, 2016, REMOTE SENS ENVIRON, V173, P145, DOI 10.1016/j.rse.2015.11.027
   Ren ZB, 2013, FORESTS, V4, P868, DOI 10.3390/f4040868
   Robitu M, 2006, SOL ENERGY, V80, P435, DOI 10.1016/j.solener.2005.06.015
   Roebeling P, 2017, J ENVIRON PLANN MAN, V60, P482, DOI 10.1080/09640568.2016.1162138
   Santamouris M, 2018, J CIV ENG MANAG, V24, P638, DOI 10.3846/jcem.2018.6604
   Saura S, 2007, LANDSCAPE URBAN PLAN, V83, P91, DOI 10.1016/j.landurbplan.2007.03.005
   Saura S, 2010, ECOGRAPHY, V33, P523, DOI 10.1111/j.1600-0587.2009.05760.x
   Shi DC, 2020, SUSTAIN CITIES SOC, V55, DOI 10.1016/j.scs.2020.102065
   Shiflett SA, 2017, SCI TOTAL ENVIRON, V579, P495, DOI 10.1016/j.scitotenv.2016.11.069
   Skelhorn C, 2014, LANDSCAPE URBAN PLAN, V121, P129, DOI 10.1016/j.landurbplan.2013.09.012
   Soille P., 2003, Morphological Image Analysis: Principles and Applications
   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
   Tan Z, 2016, ENERG BUILDINGS, V114, P265, DOI 10.1016/j.enbuild.2015.06.031
   Theeuwes NE, 2013, J GEOPHYS RES-ATMOS, V118, P8881, DOI 10.1002/jgrd.50704
   Unger J, 2004, CLIM RES, V27, P253, DOI 10.3354/cr027253
   Vogt P, 2009, ECOL INDIC, V9, P64, DOI 10.1016/j.ecolind.2008.01.011
   Weather Underground Web, 2019, HONGQ DAIL OBS SHANG
   Wickham JD, 2010, LANDSCAPE URBAN PLAN, V94, P186, DOI 10.1016/j.landurbplan.2009.10.003
   Wilson JS, 2003, REMOTE SENS ENVIRON, V86, P303, DOI 10.1016/S0034-4257(03)00084-1
   Wong MS, 2010, BUILD ENVIRON, V45, P1880, DOI 10.1016/j.buildenv.2010.02.019
   Xie P, 2020, SUSTAIN CITIES SOC, V59, DOI 10.1016/j.scs.2020.102162
   Xiong X., 2018, THESIS GUANGZHOU U G
   Xue ZS, 2019, LANDSCAPE URBAN PLAN, V182, P92, DOI 10.1016/j.landurbplan.2018.10.015
   Yang GY, 2020, SUSTAIN CITIES SOC, V53, DOI 10.1016/j.scs.2019.101932
   Yang RM, 2016, ECOL INDIC, V60, P870, DOI 10.1016/j.ecolind.2015.08.036
   Yang XJ, 2014, ASIAN J CHEM, V26, P5644, DOI 10.14233/ajchem.2014.18181
   Yu H, 2020, ECOL MODEL, V432, DOI 10.1016/j.ecolmodel.2020.109202
   Yu Zhao-wu, 2015, Yingyong Shengtai Xuebao, V26, P636
   Yu ZW, 2020, URBAN FOR URBAN GREE, V49, DOI 10.1016/j.ufug.2020.126630
   Yu ZW, 2017, ECOL INDIC, V82, P152, DOI 10.1016/j.ecolind.2017.07.002
   [赵之重 Zhao Zhizhong], 2014, [干旱区研究, Arid Zone Research], V31, P1031
   Zhou W, 2019, J URBAN PLAN DEV, V145, DOI 10.1061/(ASCE)UP.1943-5444.0000520
NR 69
TC 30
Z9 31
U1 9
U2 152
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 1660-4601
J9 INT J ENV RES PUB HE
JI Int. J. Environ. Res. Public Health
PD NOV
PY 2020
VL 17
IS 22
AR 8684
DI 10.3390/ijerph17228684
PG 29
WC Environmental Sciences; Public, Environmental & Occupational Health
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Public, Environmental & Occupational
   Health
GA OY4BG
UT WOS:000594192600001
PM 33238472
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Santos, RA
   Flores-Colen, I
   Simoes, N
   Silvestre, JD
AF Santos, Rita Andrade
   Flores-Colen, Ines
   Simoes, Nuno
   Silvestre, Jose D.
TI Auto-responsive technologies for thermal renovation of opaque facades
SO ENERGY AND BUILDINGS
LA English
DT Article
DE Auto-responsive technologies; Adaptive strategies; Adaptive envelope;
   Opaque facades; Thermal Renovation
ID THERMOCHROMIC COATINGS; ENERGY STORAGE; PERFORMANCE; BUILDINGS; PCM;
   MORTAR; DESIGN; ROOFS
AB Auto-responsive technologies (ARTs) operate in an intrinsic mode undergoing reversible changes in one or more of their properties in direct response to external stimuli variations. The aim of this paper is to identify their potential use for the thermal renovation of opaque facades of buildings in order to reach climate adaptivity. Adaptive facade concept offers a huge potential for thermal renovation, by improving occupants' comfort, promoting sector decarbonization, and being an opportunity for adapting facades to climate change.
   A literature review permitted the systematization of thermal renovation adaptive strategies (TRAS) in which ARTs can be useful. The facade reversible changes (outputs) required for each strategy were identified, as well as the possible adaptation mechanisms to obtain them. The technologies responding within the recognized adaptation mechanisms were described and compared, their readiness level identified and their role within the TRAS was assigned.
   An approach to assess the suitability of each ART regarding TRAS for existing facades was conceived. It uses the criteria of aesthetic change, additional space and demolition needs, localization and area of intervention.
   The role of each ART within each TRAS, here systematized, will support the definition of the ART's operational range for each application and climate, and will promote the research and development of these technologies for thermal renovation of buildings' facades. (C) 2020 Elsevier B.V. All rights reserved.
C1 [Santos, Rita Andrade; Flores-Colen, Ines; Silvestre, Jose D.] Univ Lisboa UL, CERIS, Inst Super Tecn IST, Av Rovisco Pais 1, Lisbon 1049001, Portugal.
   [Simoes, Nuno] Univ Coimbra, FCTUC, Depart Civil Engn, ADAI LAETA,IteCons, Coimbra, Portugal.
C3 Universidade de Lisboa; Universidade de Coimbra
RP Santos, RA (corresponding author), Univ Lisboa UL, CERIS, Inst Super Tecn IST, Av Rovisco Pais 1, Lisbon 1049001, Portugal.
EM andrade.santos@tecnico.ulisboa.pt
RI Silvestre, José/C-1699-2009; Simões, Nuno/H-4062-2019; Simoes,
   Nuno/G-8735-2019; Flores-Colen, Ines/A-6635-2013
OI Simoes, Nuno/0000-0003-3418-0030; Andrade Santos,
   Rita/0000-0002-8625-476X; Flores-Colen, Ines/0000-0003-4038-6748
FU CERIS Research Centre, Instituto Superior Tecnico, Universidade de
   Lisboa; FCT Fundacao para a Ciencia e Tecnologia [PD/BD/135215/2017];
   Fundação para a Ciência e a Tecnologia [PD/BD/135215/2017] Funding
   Source: FCT
FX The authors acknowledge the support of the CERIS Research Centre,
   Instituto Superior Tecnico, Universidade de Lisboa, and also FCT
   Fundacao para a Ciencia e Tecnologia for the financial support to the
   first author through PhD scholarship no. PD/BD/135215/2017 in the scope
   of EcoCoRe Doctoral Programme.
CR Addington H.U.D. Michelle, 2008, SMART MAT NEW TECHNO
   Aelenei D, 2016, ENRGY PROCED, V91, P269, DOI 10.1016/j.egypro.2016.06.218
   Ahmed EM, 2015, J ADV RES, V6, P105, DOI 10.1016/j.jare.2013.07.006
   An B., 2018, P 2018 CHI C HUMAN F, P1, DOI [DOI 10.1145/3173574.3173834, 10.1145/3173574.3173834, 10.1145/3173574, DOI 10.1145/3173574]
   [Anonymous], 2020, EU Biodiversity Strategy
   [Anonymous], 2016, Off J Eur Union, P46
   Aresta C., 2017, OFF INT MIDT C EUR C
   Artola I., 2016, BOOSTING BUILDING RE
   Barret R., THERMADAPT REVOLUTIO
   Barrett R.M., 2016, ACTA NEUROPATHOL, P1
   Barrett R.M., 2016, ASME 2016 C SMART MA, DOI [10.1115/SMASIS2016-9014., DOI 10.1115/SMASIS2016-9014]
   Barrett RM, 2016, PROCEDIA ENGINEER, V145, P26, DOI 10.1016/j.proeng.2016.04.005
   Besir AB, 2018, RENEW SUST ENERG REV, V82, P915, DOI 10.1016/j.rser.2017.09.106
   Cui S, 2016, APPL ENERG, V168, P332, DOI 10.1016/j.apenergy.2016.01.058
   de Gracia A, 2015, ENERG BUILDINGS, V103, P414, DOI 10.1016/j.enbuild.2015.06.007
   Derome D, 2012, PHILOS MAG, V92, P3680, DOI 10.1080/14786435.2012.715248
   Desai D, 2014, CONSTR BUILD MATER, V67, P366, DOI 10.1016/j.conbuildmat.2013.12.104
   Economidou M., 2011, Europes Buildings under the Microscope. A Country-by-Country Review of the Energy Performance of Buildings
   Favoino F, 2017, ENERGY, V127, P301, DOI 10.1016/j.energy.2017.03.083
   Formentini M, 2018, AUTOMAT CONSTR, V85, P220, DOI 10.1016/j.autcon.2017.10.006
   Garshasbi S, 2019, SOL ENERG MAT SOL C, V191, P21, DOI 10.1016/j.solmat.2018.10.023
   Ge Q, 2016, SCI REP-UK, V6, DOI 10.1038/srep31110
   Hawkes E, 2010, P NATL ACAD SCI USA, V107, P12441, DOI 10.1073/pnas.0914069107
   Heier J, 2015, RENEW SUST ENERG REV, V42, P1305, DOI 10.1016/j.rser.2014.11.031
   Holstov A, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9030435
   Holstov A, 2015, CONSTR BUILD MATER, V98, P570, DOI 10.1016/j.conbuildmat.2015.08.136
   Iken O, 2019, SOL ENERGY, V179, P249, DOI 10.1016/j.solener.2018.12.062
   Jiang HY, 2006, ADV MATER, V18, P1471, DOI 10.1002/adma.200502266
   Jones RV, 2016, ENRGY PROCED, V88, P714, DOI 10.1016/j.egypro.2016.06.049
   Joulin A, 2014, APPL THERM ENG, V66, P171, DOI 10.1016/j.applthermaleng.2014.01.027
   Juaristi M., 2018, J FACADE DESIGN ENG, V6, P107, DOI DOI 10.7480/JFDE.2018.2.2216
   Juaristi M., 2018, J FACADE DES ENG, V6, DOI [10.7480/jfde.2018.3.2475, DOI 10.7480/JFDE.2018.3.2475]
   Juaristi M, 2018, BUILD ENVIRON, V144, P482, DOI 10.1016/j.buildenv.2018.08.028
   Karlessi T, 2009, SOL ENERGY, V83, P538, DOI 10.1016/j.solener.2008.10.005
   Kasinalis C, 2014, ENERG BUILDINGS, V79, P106, DOI 10.1016/j.enbuild.2014.04.045
   Kosny J., 2013, COST ANAL SIMPLE PHA, DOI [10.2172/1219890, DOI 10.2172/1219890.]
   Kosny J, 2015, ENG MATER PROCESS, P235, DOI 10.1007/978-3-319-14286-9_7
   Lai CM, 2014, ENERG BUILDINGS, V73, P37, DOI 10.1016/j.enbuild.2014.01.017
   Le Duigou A, 2016, MATER DESIGN, V96, P106, DOI 10.1016/j.matdes.2016.02.018
   Le Duigou A, 2017, IND CROP PROD, V99, P142, DOI 10.1016/j.indcrop.2017.02.004
   Lee AY, 2017, ENGINEERING-PRC, V3, P663, DOI 10.1016/J.ENG.2017.05.014
   Lee KO, 2015, ENERG BUILDINGS, V86, P86, DOI 10.1016/j.enbuild.2014.10.020
   Loonen R., CLIMATE ADAPTIVE BUI
   Loonen RCGM, 2013, RENEW SUST ENERG REV, V25, P483, DOI 10.1016/j.rser.2013.04.016
   Loonen R.C.G.M., 2011, P BUILD SIM 2011 12
   Loonen R.C.G.M., 2015, C P 10 ENERGY FORUM, P1274
   Lopez M., 2015, J. Facade Des. Eng, V3, P27, DOI DOI 10.3233/FDE-150026
   Ma YP, 2009, CEMENT CONCRETE RES, V39, P90, DOI 10.1016/j.cemconres.2008.10.006
   Nandakumar DK, 2018, ENERG ENVIRON SCI, V11, P2179, DOI 10.1039/c8ee00902c
   Novak V., 2019, THEORY APPL TRANSP P, V32, P29, DOI [10.1007/978-3-030-01806-1_3., DOI 10.1007/978-3-030-01806-1_3.]
   PEIPPO K, 1991, ENERG BUILDINGS, V17, P259, DOI 10.1016/0378-7788(91)90009-R
   Perez G, 2018, CONSTR BUILD MATER, V186, P884, DOI 10.1016/j.conbuildmat.2018.07.246
   Pesenti M, 2015, ENRGY PROCED, V70, P661, DOI 10.1016/j.egypro.2015.02.174
   Porritt SM, 2012, ENERG BUILDINGS, V55, P16, DOI 10.1016/j.enbuild.2012.01.043
   Reichert S, 2015, COMPUT AIDED DESIGN, V60, P50, DOI 10.1016/j.cad.2014.02.010
   Romano R., 2018, JOURNAL OF FACADE DESIGN ENGINEERING, V6, P65, DOI [10.7480/JFDE.2018.3.2478, DOI 10.7480/JFDE.2018.3.2478, 10.7480/jfde.2018.3.2478]
   Rüggeberg M, 2015, PLOS ONE, V10, DOI [10.1371/journal.pone.0120718, 10.1371/journal.pone.0119248]
   Safikhani T, 2014, RENEW SUST ENERG REV, V40, P450, DOI 10.1016/j.rser.2014.07.166
   Sharma M, 2017, ENERG BUILDINGS, V155, P459, DOI 10.1016/j.enbuild.2017.09.030
   Vailati C, 2018, ENERG BUILDINGS, V158, P1013, DOI 10.1016/j.enbuild.2017.10.042
   van Hooff T, 2015, BUILD ENVIRON, V83, P142, DOI 10.1016/j.buildenv.2014.10.006
   Velikov K., 2013, Design and Construction of High-performance Homes: Building Envelopes, Renewable Energies and Integrated Practice, P75
   Wood D, 2018, CONSTR BUILD MATER, V165, P782, DOI 10.1016/j.conbuildmat.2017.12.134
   Wood DM, 2016, INT J ARCHIT COMPUT, V14, P49, DOI 10.1177/1478077115625522
   Zhang P, 2015, ENRGY PROCED, V69, P699, DOI 10.1016/j.egypro.2015.03.080
   Zheng SJ, 2015, SOL ENERGY, V112, P263, DOI 10.1016/j.solener.2014.09.049
   Zhou Y, 2015, PROC IUTAM, P83, DOI 10.1016/j.piutam.2014.12.010
NR 67
TC 12
Z9 13
U1 6
U2 42
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 JUN 15
PY 2020
VL 217
AR 109968
DI 10.1016/j.enbuild.2020.109968
PG 14
WC Construction & Building Technology; Energy & Fuels; Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Energy & Fuels; Engineering
GA LL3RC
UT WOS:000531471400018
DA 2025-01-10
ER

PT J
AU Grifoni, RC
   Ottone, MF
   Prenna, E
AF Grifoni, Roberta Cocci
   Ottone, Maria Federica
   Prenna, Enrico
TI Tomographic Environmental Sections for Environmental Mitigation Devices
   in Historical Centers
SO ENERGIES
LA English
DT Article
DE tomographic environmental section (TENS) method; global warming; heat
   waves; urban acupuncture; computational fluid dynamics (CFD); outdoor
   comfort
AB Urban heat waves and the overall growing trend in the annual global temperature underline the importance of urban/architectural resilience and the need to reduce energy consumption. By designing urban voids, it is possible to create thermodynamic buffers, i.e., bubbles of controlled atmosphere that act as mediators between the natural and built environments, between the human body and the surrounding air, between meteorology and physiology (meteorological architecture). Multiple small actions in the urban fabric's open spaces, such as replacing dark pavements or inserting vegetation and green spaces, are intended to improve outdoor comfort conditions and therefore the resilience of the city itself. This not only benefits the place's quality, which is intrinsic to the new project, but also the insulating capacity of buildings, which are relieved of an external heat load. The design emphasis therefore changes from solid structures to the climate and weather conditions, which are invisible but perceivable. To design and control these constructed atmopheres, tomographic sections processed with computational fluid dynamics software (tomographic environmental section, TENS) becomes necessary. It allows the effects of an extreme event on an outdoor environment to be evaluated in order to establish the appropriate (adaptive) climate mitigation devices, especially in historical centers where energy retrofits are often discouraged. By fixing boundary conditions after a local intervention, the virtual environment can be simulated and then sliced to analyze initial values and verify the design improvements.
C1 [Grifoni, Roberta Cocci; Ottone, Maria Federica; Prenna, Enrico] Univ Camerino, SAD Sch Architecture & Design Eduardo Vittoria, Viale Rimembranza, I-63100 Ascoli Piceno, Italy.
C3 University of Camerino
RP Grifoni, RC (corresponding author), Univ Camerino, SAD Sch Architecture & Design Eduardo Vittoria, Viale Rimembranza, I-63100 Ascoli Piceno, Italy.
EM roberta.coccigrifoni@unicam.it; mariafederica.ottone@unicam.it;
   enrico.prenna@unicam.it
OI Cocci Grifoni, Roberta/0000-0002-7092-6293; OTTONE, Maria
   Federica/0000-0002-8454-8043
CR Ambrosini D, 2014, SUSTAINABILITY-BASEL, V6, P7013, DOI 10.3390/su6107013
   [Anonymous], 2000, P INT WORKSH WINDCH
   [Anonymous], 2015, 55 ASHRAE
   Bai XM, 2007, J IND ECOL, V11, P15, DOI 10.1162/jie.2007.1202
   Baynes T., 2009, TRAJECTORIES CHANGE
   Cocci Grifoni R., 2011, ECOL ENV, V155, P835
   De Sola-Morales M., 2008, MATTER OF THINGS
   Fanger P. O., 1970, Thermal comfort. Analysis and applications in environmental engineering.
   Ganis M, 2016, ENVIRON PLANN B, V43, P1075, DOI 10.1177/0265813515602260
   International Energy Agency International Energy Agency, 2014, INT EN AG 2014 ANN R
   Jendritzky G., 1990, METHODOLOGY SPATIALL, V114
   Jendritzky G., 2001, P WINDS C THERM STAN
   Katzschner L., 2007, P SUN WIND ARCH 24 I, P103
   Kottek M, 2006, METEOROL Z, V15, P259, DOI 10.1127/0941-2948/2006/0130
   Latini G., 2010, P THERM PERF EXT ENV
   Lerner J., 2014, URBAN ACUPUNCTURE IS
   Maciel CD, 2015, INT J LOW-CARBON TEC, V10, P165, DOI 10.1093/ijlct/ctt016
   Musco F., 2016, Counteracting Urban Heat Island Effects in a Global Climate Change Scenario
   Oke TR, 2006, THEOR APPL CLIMATOL, V84, P179, DOI [10.1007/s00704-005-0153-0, 10.1007/S00704-005-0153-0]
   Ottone M. F., 2012, P 28 INT PLEA C SUST, P6
   Pachauri R. K., 2014, IPCC CLIMATE CHANGE
   Petrucci E., 2015, P CULT HER INT C HER
   Piano R., 2014, G12420132014 ORE
   Pickup J., 1999, P 15 INT C BIOM INT
   Salata F, 2015, SUSTAINABILITY-BASEL, V7, P9012, DOI 10.3390/su7079012
   Secchi B., 2013, LA CITTA RICCHI CITT
   Tirabassi T, 1999, ATMOS ENVIRON, V33, P2427, DOI 10.1016/S1352-2310(98)00371-9
   Wiley J, 2009, AD ARCHITECTURAL DES, V79
   Wong NH., 2009, TROPICAL URBAN HEAT
NR 29
TC 4
Z9 4
U1 0
U2 18
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 1996-1073
J9 ENERGIES
JI Energies
PD MAR
PY 2017
VL 10
IS 3
AR 351
DI 10.3390/en10030351
PG 18
WC Energy & Fuels
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Energy & Fuels
GA ER3YR
UT WOS:000398736700091
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Johnsen, O
   Fossdal, CG
   Nagy, N
   Molmann, J
   Dæhlen, OG
   Skroppa, T
AF Johnsen, O
   Fossdal, CG
   Nagy, N
   Molmann, J
   Dæhlen, OG
   Skroppa, T
TI Climatic adaptation in <i>Picea abies</i> progenies is affected by the
   temperature during zygotic embryogenesis and seed maturation
SO PLANT CELL AND ENVIRONMENT
LA English
DT Article
DE Picea abies; adaptive traits; after effects; chitinases; climate change;
   epigenetic memory; maternal effects; phytochromes
ID AUTUMN FROST-HARDINESS; PLANTAGO-LANCEOLATA L; FAR-RED LIGHT; PHENOTYPIC
   CHANGES; DNA METHYLATION; NORTHERN CLONES; PARENTAL ENVIRONMENT;
   ARABIDOPSIS-THALIANA; ANTIFREEZE PROTEINS; EXPRESSION PATTERN
AB The temperature during maternal reproduction affects adaptive traits in progenies of Norway spruce (Picea abies (L) Karst.). Seed production in a cold environment advances bud set and cold acclimation in the autumn and dehardening and flushing in spring, whereas a warm reproductive environment delays timing of these traits. We repeated crosses between the same parents and produced seeds under contrasting temperatures. Elevated temperatures were applied at different time points from female meiosis to embryogenesis, followed by full-sib progeny tests in common environments. We measured timing of terminal bud formation, cold acclimation in the autumn and transcription levels of conifer phytochromes PhyO, PhyN, PhyP, and the class IV chitinase PaChi4 in these tests. No progeny differences were found that could be related to temperature differences during prezygotic stages and fertilization. In contrast, progeny performance was strongly associated with the degree-days from proembryo to mature seeds. Progenies with a warm embryonic history formed terminal buds later, were less hardy and expressed lower transcription levels of the Phy and PaChi4 genes. We hypothesize that temperature during zygotic embryogenesis and seed maturation regulates an 'epigenetic memory' in the progeny, involving differential expression of genes that may regulate bud phenology, cold acclimation and embryogenesis in Norway spruce.
C1 Agr Univ Norway, Norwegian Forest Res Inst, N-1432 As, Norway.
   Univ Tromso, Dept Biol, N-9037 Tromso, Norway.
   Oppland Forest Soc, Biri Nursery & Seed Improvement Ctr, N-2836 Biri, Norway.
C3 Norwegian University of Life Sciences; UiT The Arctic University of
   Tromso
RP Agr Univ Norway, Norwegian Forest Res Inst, Hogskoleveien 8, N-1432 As, Norway.
EM oystein.johnsen@skogforsk.no
RI Mølmann, Jørgen/AAM-4162-2021; Nagy, Nina/C-6887-2008; Skröppa,
   Tore/AAT-1299-2021; Fossdal, Carl Gunnar/C-5536-2008
OI Fossdal, Carl Gunnar/0000-0002-7390-7864
CR Aitken SN, 2001, TREE PHYSIOL SER, V1, P23
   [Anonymous], RAPPORT SKOGFORSK
   Bastow R, 2004, NATURE, V427, P164, DOI 10.1038/nature02269
   Bigras F.J., 2001, Conifer cold hardiness
   BJORNSTAD A, 1981, MEDD NOR I SKOGFORSK, V36, P1
   Brunner Amy M., 2004, BMC Plant Biology, V4, P14, DOI 10.1186/1471-2229-4-14
   Clapham D, 2001, TREE PHYSIOL SER, V1, P187
   Clapham DH, 1999, PLANT MOL BIOL, V40, P669, DOI 10.1023/A:1006204318499
   Clapham DH, 2002, PHYSIOL PLANTARUM, V114, P207, DOI 10.1034/j.1399-3054.2002.1140206.x
   Clapham DH, 1998, PHYSIOL PLANTARUM, V102, P71, DOI 10.1034/j.1399-3054.1998.1020110.x
   DAEHLEN AG, 1995, 195 SKOGF, P1
   Dalen LS, 2001, PHYSIOL PLANTARUM, V113, P533, DOI 10.1034/j.1399-3054.2001.1130412.x
   DAOUST AL, 1986, PHYSIOL PLANTARUM, V67, P141, DOI 10.1111/j.1399-3054.1986.tb02435.x
   Davis MB, 2001, SCIENCE, V292, P673, DOI 10.1126/science.292.5517.673
   DORMLING I, 1992, CAN J FOREST RES, V22, P88, DOI 10.1139/x92-013
   EDVARDSEN OM, 1996, 996 SKOGF, P1
   Eriksson ME, 2003, PLANT PHYSIOL, V132, P732, DOI 10.1104/pp.103.022343
   ERIKSSON ME, 2000, SILVESTRIA, V164
   ERIKSSON T, 1994, THESIS SWEDISH U AGR
   Falconer D. S., 1989, Introduction to quantitative genetics.
   Gendrel AV, 2002, SCIENCE, V297, P1871, DOI 10.1126/science.1074950
   GIANOLA D, 1981, GENETICS, V99, P357
   GORLA MS, 1986, THEOR APPL GENET, V72, P42, DOI 10.1007/BF00261452
   Griffith M, 2004, TRENDS PLANT SCI, V9, P399, DOI 10.1016/j.tplants.2004.06.007
   Hänninen H, 2001, TREE PHYSIOL SER, V1, P305
   Hietala AM, 2003, APPL ENVIRON MICROB, V69, P4413, DOI 10.1128/AEM.69.8.4413-4420.2003
   HON WC, 1995, PLANT PHYSIOL, V109, P879, DOI 10.1104/pp.109.3.879
   Honys D, 2003, PLANT PHYSIOL, V132, P640, DOI 10.1104/pp.103.020925
   HORMAZA JI, 1992, THEOR APPL GENET, V83, P663, DOI 10.1007/BF00226682
   Howe GT, 1996, PHYSIOL PLANTARUM, V97, P95, DOI 10.1111/j.1399-3054.1996.tb00484.x
   Jablonka E, 2002, ANN NY ACAD SCI, V981, P82
   JABLONKA E, 1995, LAMARCKIAN DIMENSION
   JOHNSEN O, 1995, TREE PHYSIOL, V15, P551, DOI 10.1093/treephys/15.7-8.551
   Johnsen O, 1996, THEOR APPL GENET, V92, P797, DOI 10.1007/BF00221890
   JOHNSEN O, 1994, CAN J FOREST RES, V24, P32, DOI 10.1139/x94-005
   Johnsen O, 2001, TREE PHYSIOL SER, V2, P207
   JOHNSEN O, 1994, SCAND J FOREST RES, V9, P333, DOI 10.1080/02827589409382849
   Johnsen O, 1989, SCAND J FOREST RES, V4, P331, DOI 10.1080/02827588909382570
   Johnsen O, 1989, SCAND J FOREST RES, V4, P317, DOI 10.1080/02827588909382569
   Johnsen O, 1989, SCAND J FOREST RES, V4, P351, DOI 10.1080/02827588909382572
   Johnsen O, 1989, SCAND J FOREST RES, V4, P343, DOI 10.1080/02827588909382571
   Johnson LM, 2002, CURR BIOL, V12, P1360, DOI 10.1016/S0960-9822(02)00976-4
   Kalisz S, 2004, TRENDS ECOL EVOL, V19, P309, DOI 10.1016/j.tree.2004.03.034
   Kevei É, 2003, PHYSIOL PLANTARUM, V117, P305, DOI 10.1034/j.1399-3054.2003.00049.x
   KOHMANN K, 1994, SILVAE GENET, V43, P329
   Lacey EP, 2000, EVOLUTION, V54, P1207, DOI 10.1111/j.0014-3820.2000.tb00555.x
   Lacey EP, 1996, EVOLUTION, V50, P865, DOI [10.1111/j.1558-5646.1996.tb03895.x, 10.2307/2410858]
   Matzke M, 2001, SCIENCE, V293, P1080, DOI 10.1126/science.1063051
   Meyer P, 2001, CURR OPIN PLANT BIOL, V4, P457, DOI 10.1016/S1369-5266(00)00200-4
   MULCAHY DL, 1979, SCIENCE, V206, P20, DOI 10.1126/science.206.4414.20
   Olsen JE, 1997, PLANT J, V12, P1339, DOI 10.1046/j.1365-313x.1997.12061339.x
   Ottaviano E., 1988, SEXUAL REPROD HIGHER, P35
   Owens JN, 2001, SCAND J FOREST RES, V16, P221, DOI 10.1080/028275801750285866
   OWENS JN, 1985, PIX53 FOR I PET NAT
   Passarinho PA, 2001, PLANTA, V212, P556, DOI 10.1007/s004250000464
   Paszkowski J, 2001, CURR OPIN PLANT BIOL, V4, P123, DOI 10.1016/S1369-5266(00)00147-3
   Quail PH, 2002, CURR OPIN CELL BIOL, V14, P180, DOI 10.1016/S0955-0674(02)00309-5
   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
   Sarvas R., 1968, COMM I FENN, V67, P1
   *SAS STAT, 1997, SOFTW CHANG ENH REL
   Saxe H, 2001, NEW PHYTOL, V149, P369, DOI 10.1046/j.1469-8137.2001.00057.x
   Schmidt M, 2002, J MOL EVOL, V54, P715, DOI 10.1007/s00239-001-0042-9
   Schmidtling RC, 2004, FORESTRY, V77, P287, DOI 10.1093/forestry/77.4.287
   SKROPPA T, 1994, SILVAE GENET, V43, P95
   Skroppa T., 2000, Forest genetics and sustainability. 4th International Consultation on Forest Genetics and Tree Breeding,  organized by IUFRO Division 2 "Physiology and Genetics"  in cooperation with FAO, and held in Beijing, China, 22-28 August 1998., P49
   SKROPPA T, 1994, SILVAE GENET, V43, P298
   Stoehr MU, 1998, CAN J FOREST RES, V28, P418, DOI 10.1139/cjfr-28-3-418
   Sung SB, 2004, NATURE, V427, P159, DOI 10.1038/nature02195
   Sung SB, 2004, CURR OPIN PLANT BIOL, V7, P4, DOI 10.1016/j.pbi.2003.11.010
   TANKSLEY SD, 1981, SCIENCE, V213, P453, DOI 10.1126/science.213.4506.453
   van Hengel AJ, 1998, PLANT PHYSIOL, V117, P43, DOI 10.1104/pp.117.1.43
   Wiweger M, 2003, J EXP BOT, V54, P2691, DOI 10.1093/jxb/erg299
   Wolffe AP, 1999, SCIENCE, V286, P481, DOI 10.1126/science.286.5439.481
NR 74
TC 129
Z9 137
U1 0
U2 60
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 2005
VL 28
IS 9
BP 1090
EP 1102
DI 10.1111/j.1365-3040.2005.01356.x
PG 13
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA 956FI
UT WOS:000231284300003
DA 2025-01-10
ER

PT J
AU Hung, HC
   Lu, YT
   Hung, CH
AF Hung, Hung-Chih
   Lu, Yu-Ting
   Hung, Chih-Hsuan
TI The determinants of integrating policy-based and community-based
   adaptation into coastal hazard risk management: a resilience approach
SO JOURNAL OF RISK RESEARCH
LA English
DT Article
DE Adaptation behavior; resilience; coastal hazard risk management; public
   adaptation; social capital; vulnerability
ID ADAPTIVE CAPACITY; CLIMATE-CHANGE; DECISION; VULNERABILITY; PERCEPTIONS;
   ASSESSMENTS; CYCLONE; PEOPLE; MODEL; POWER
AB A growing number of studies focus on improving the understanding of how the households' adaptations can be encouraged in the process of coastal hazards and risk management. Particularly, this process is undergoing a major paradigm shift as it moves from an approach dominated by policy-based adaptation to another one in which community-based resilience building is favored. Thus, this article aims to apply a resilience approach to improve the knowledge about how public measures influence private autonomous adaptation behavior, through a transdisciplinary investigation of household adaptation behavior and its determinants. The Resilience Framework of Household Autonomous Adaptation to Climate- and Weather-Related Hazard Risks (ROHACHR) is proposed and combined with a focus group meeting and multivariate analysis to compare pre-disaster, during a disaster, post-disaster adaptations, and resilience behavior of households. Using an empirical survey of the households in three coastal municipalities in Taiwan, we examine the relationships between public measures and private adaptations that provides three distinguishing types of household behavior: 'core', 'trust in governmental aid', and 'awareness and structures'. Results show that providing hazard risk information may be one step toward encouraging private autonomous adaptations. Several factors that help foster resilience also appear to be influential in households' adaptation decisions, such as specific and positive governmental aid, information trust, and social capital. Based on these results, it shows that the ROHACHR is useful to characterize households' adaptation and resilience behavior and explain how they respond to public measures. Finally, the policy implications of our findings for improving resilience of coastal communities and encouraging public-private collaboration in the process of hazard risk management are discussed.
C1 [Hung, Hung-Chih; Lu, Yu-Ting; Hung, Chih-Hsuan] Natl Taipei Univ, Dept Real Estate & Built Environm, New Taipei, Taiwan.
C3 National Taipei University
RP Hung, HC (corresponding author), Natl Taipei Univ, Dept Real Estate & Built Environm, New Taipei, Taiwan.
EM hung@mail.ntpu.edu.tw
RI lu, yuting/IIS-2826-2023
FU Ministry of Science and Technology, Taiwan [NSC101-2625-M-305-002,
   MOST102-2625-M-305-002]
FX The research was supported by the Ministry of Science and Technology,
   Taiwan [grant number NSC101-2625-M-305-002], and [grant number
   MOST102-2625-M-305-002].
CR Adger WN, 2005, SCIENCE, V309, P1036, DOI 10.1126/science.1112122
   Aldrich DP, 2011, NAT HAZARDS, V56, P595, DOI 10.1007/s11069-010-9577-7
   Allen KM, 2006, DISASTERS, V30, P81, DOI 10.1111/j.1467-9523.2006.00308.x
   [Anonymous], 2016, Urban adaptation to climate change in Europe 2016: Transforming cities in a changing climate
   [Anonymous], 2010, Designing Climate Change Adaptation Initiatives: A UNDP Toolkit for Practitioners
   [Anonymous], 1997, HDB HLTH BEHAV RES 1
   [Anonymous], 2012, DIRENAT IMP
   Arbuckle JG, 2013, CLIMATIC CHANGE, V118, P551, DOI 10.1007/s10584-013-0700-0
   Babcicky P, 2017, J RISK RES, V20, P1017, DOI 10.1080/13669877.2016.1147489
   Bandura A., 2005, Great minds in management, P9
   Boer H., 1996, PREDICTING HLTH BEHA, P95
   Brouwer R, 2013, CLIMATIC CHANGE, V117, P11, DOI 10.1007/s10584-012-0534-1
   Butler JRA, 2015, COAST MANAGE, V43, P346, DOI 10.1080/08920753.2015.1046802
   Cadag JRD, 2012, AREA, V44, P100, DOI 10.1111/j.1475-4762.2011.01065.x
   Cutter SL, 2008, GLOBAL ENVIRON CHANG, V18, P598, DOI 10.1016/j.gloenvcha.2008.07.013
   EPA, 2017, AD ACT GUID CLIM CHA
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Füssel HM, 2006, CLIMATIC CHANGE, V75, P301, DOI 10.1007/s10584-006-0329-3
   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
   Harvatt J, 2011, J RISK RES, V14, P63, DOI 10.1080/13669877.2010.503935
   Heltberg R, 2009, GLOBAL ENVIRON CHANG, V19, P89, DOI 10.1016/j.gloenvcha.2008.11.003
   Howe PD, 2011, GLOBAL ENVIRON CHANG, V21, P711, DOI 10.1016/j.gloenvcha.2011.02.001
   Hughey EP, 2011, RISK HAZARDS CRISIS, V2, DOI 10.2202/1944-4079.1076
   Hung HC, 2016, LAND USE POLICY, V50, P48, DOI 10.1016/j.landusepol.2015.08.029
   Hung HC, 2013, CLIMATIC CHANGE, V120, P491, DOI 10.1007/s10584-013-0819-z
   Hung HC, 2011, RISK ANAL, V31, P668, DOI 10.1111/j.1539-6924.2010.01539.x
   Hung HC, 2009, J RISK RES, V12, P239, DOI 10.1080/13669870802497702
   IRGC, 2015, Guidelines for Emerging Risk Governance
   Jones N, 2014, CLIMATIC CHANGE, V123, P133, DOI 10.1007/s10584-013-1049-0
   KAHNEMAN D, 1979, ECONOMETRICA, V47, P263, DOI 10.2307/1914185
   Kellens W, 2013, RISK ANAL, V33, P24, DOI 10.1111/j.1539-6924.2012.01844.x
   Kirshen P, 2008, CLIMATIC CHANGE, V90, P453, DOI 10.1007/s10584-008-9398-9
   Klinke A., 2001, J RISK RES, V4, P159, DOI [10.1080/136698701750128105, DOI 10.1080/136698701750128105]
   Lindell M., 2005, Natural Hazards Review, V6, P171, DOI DOI 10.1061/(ASCE)1527-6988(2003)4:4(176)
   Lindell MK, 2012, RISK ANAL, V32, P616, DOI 10.1111/j.1539-6924.2011.01647.x
   Mcleod E, 2015, COAST MANAGE, V43, P439, DOI 10.1080/08920753.2015.1046809
   Milman A, 2016, GLOBAL ENVIRON CHANG, V36, P46, DOI 10.1016/j.gloenvcha.2015.11.007
   Nelson DR, 2007, ANNU REV ENV RESOUR, V32, P395, DOI 10.1146/annurev.energy.32.051807.090348
   Paul SK, 2011, NAT HAZARDS, V57, P477, DOI 10.1007/s11069-010-9631-5
   Pelling M, 2005, GLOBAL ENVIRON CHANG, V15, P308, DOI 10.1016/j.gloenvcha.2005.02.001
   Poussin JK, 2014, ENVIRON SCI POLICY, V40, P69, DOI 10.1016/j.envsci.2014.01.013
   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]
   Sales RFM, 2009, OCEAN COAST MANAGE, V52, P395, DOI 10.1016/j.ocecoaman.2009.04.007
   Sharma U, 2009, CLIMATIC CHANGE, V94, P189, DOI [10.1007/s10584-009-9552-z, 10.1007/s10584-009-9552-Z]
   Terpstra T, 2013, ENVIRON BEHAV, V45, P993, DOI 10.1177/0013916512452427
   Thomas M, 2015, GLOBAL ENVIRON CHANG, V33, P71, DOI 10.1016/j.gloenvcha.2015.04.009
   TOBLER WR, 1970, ECON GEOGR, V46, P234, DOI 10.2307/143141
   Tucker CM, 2010, GLOBAL ENVIRON CHANG, V20, P23, DOI 10.1016/j.gloenvcha.2009.07.006
   UNISDR (United Nations International Strategy for Disaster Reduction), 2015, Sendai Framework for Disaster Risk Reduction 2015-2030
   United Nations Office for Disaster Risk Reduction (UNISDR), 2012, RED VULN EXP DIS AS
NR 51
TC 9
Z9 9
U1 2
U2 46
PU ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND
SN 1366-9877
EI 1466-4461
J9 J RISK RES
JI J. Risk Res.
PD OCT 3
PY 2019
VL 22
IS 10
BP 1205
EP 1223
DI 10.1080/13669877.2018.1454496
PG 19
WC Social Sciences, Interdisciplinary
WE Social Science Citation Index (SSCI)
SC Social Sciences - Other Topics
GA IY0NK
UT WOS:000486089800002
DA 2025-01-10
ER

PT J
AU Zhang, DY
   Guo, XP
   Rao, WH
   Pan, DM
   Cao, F
   Zhai, TY
   Zheng, WH
   Abubakar, YS
   Guan, X
   Chen, Z
   Pan, XH
AF Zhang, Dingyang
   Guo, Xueping
   Rao, Wenhua
   Pan, Danmei
   Cao, Fang
   Zhai, Tianyun
   Zheng, Wenhui
   Abubakar, Yakubu Saddeeq
   Guan, Xiong
   Chen, Zhi
   Pan, Xiaohong
TI A multi-stimuli-response metal-organic framework nanopesticide for smart
   weed control in agriculture
SO ENVIRONMENTAL SCIENCE-NANO
LA English
DT Article; Early Access
ID ONE-STEP ENCAPSULATION; ZIF-8; NANOPARTICLES; RETENTION; ADHESION;
   DELIVERY; PLANTS; RICE
AB Herbicides play an important role in weed control when it comes to ensuring a high and consistent yield in agriculture, but their effectiveness is often compromised by climatic variables. Therefore, improving the climatic adaptability of pesticides is crucial to ensure sustainable agricultural development. In this study, a novel bispyribac-sodium (BIS)-zeolitic imidazolate framework-8 (ZIF-8) nanopesticide (BIS@ZIF-8) with excellent multi-stimuli-responsive properties was synthesized. The nanopesticide BIS@ZIF-8 showed a multi-stimuli response and efficient weed control. In addition, the BIS@ZIF-8 nanocomposite showed strong resistance to rainwater erosion on leaf surfaces with a BIS retention rate of 76.26% under simulated rainwater, which was 41.54% higher than the BIS retention rate of the pure herbicide. Under UV light and acidic conditions, a high concentration of BIS was released from the BIS@ZIF-8 nanocomposite, resulting in an improved weed control effect. Further analyses showed that the BIS@ZIF-8 nanocomposite retained its structural stability and adhered to the weed under rainy conditions through electrostatic interaction. Conversely, the BIS@ZIF-8 nanocomposite was depolymerized under UV light irradiation and released BIS to kill weeds. In addition, BIS@ZIF-8 showed excellent herbicidal activity under field conditions with good biosafety. This work provides a new strategy to avoid environmental and climate-induced pesticide losses and paves the way for smart weed control in agriculture.
   Herbicides play an important role in weed control when it comes to ensuring a high and consistent yield in agriculture, but their effectiveness is often compromised by climatic variables.
C1 [Zhang, Dingyang; Guo, Xueping; Cao, Fang; Zhai, Tianyun; Zheng, Wenhui; Abubakar, Yakubu Saddeeq; Guan, Xiong; Pan, Xiaohong] Fujian Agr & Forestry Univ, Coll Plant Protect, State Key Lab Ecol Pest Control Fujian & Taiwan Cr, Fuzhou 350002, Fujian, Peoples R China.
   [Zhang, Dingyang; Guo, Xueping; Cao, Fang; Zhai, Tianyun; Zheng, Wenhui; Abubakar, Yakubu Saddeeq; Guan, Xiong; Pan, Xiaohong] Fujian Agr & Forestry Univ, Coll Plant Protect, Key Lab Biopesticide & Chem Biol, Minist Educ, Fuzhou 350002, Fujian, Peoples R China.
   [Chen, Zhi] Fujian Agr & Forestry Univ, Coll Resources & Environm, Fuzhou 350002, Fujian, Peoples R China.
   [Rao, Wenhua] Fujian Acad Agr Sci, Inst Plant protect, Fuzhou 350003, Peoples R China.
   [Pan, Danmei] Chinese Acad Sci, Fujian Inst Res Struct Matter, Fuzhou 350002, Fujian, Peoples R China.
   [Abubakar, Yakubu Saddeeq] Ahmadu Bello Univ, Fac Life Sci, Dept Biochem, Zaria, Nigeria.
C3 Fujian Agriculture & Forestry University; Fujian Agriculture & Forestry
   University; Fujian Agriculture & Forestry University; Fujian Academy of
   Agricultural Sciences; Chinese Academy of Sciences; Fujian Institute of
   Research on the Structure of Matter, CAS; Ahmadu Bello University
RP Pan, XH (corresponding author), Fujian Agr & Forestry Univ, Coll Plant Protect, State Key Lab Ecol Pest Control Fujian & Taiwan Cr, Fuzhou 350002, Fujian, Peoples R China.; Pan, XH (corresponding author), Fujian Agr & Forestry Univ, Coll Plant Protect, Key Lab Biopesticide & Chem Biol, Minist Educ, Fuzhou 350002, Fujian, Peoples R China.; Chen, Z (corresponding author), Fujian Agr & Forestry Univ, Coll Resources & Environm, Fuzhou 350002, Fujian, Peoples R China.
EM chenzhi0529@163.com; panxiaohong@163.com
RI Saddeeq, Abubakar/AAE-2073-2019; Pan, Xiaohong/KFQ-9529-2024; 张,
   丁阳/GQZ-1012-2022; 陈, 志/X-8951-2019
FU National Key Research and Development Program of China [2022YFD1400700];
   National Key R&D Program of China [1122YS01006]; Scientific Research
   Foundation of the Graduate School of FAFU; Open Funds of the Key
   Laboratory of Biopesticide [Keylab2020-04, 999077]; Ministry of
   Education, FAFU
FX This work was supported by the National Key R&D Program of China (grant
   no. 2022YFD1400700), the Scientific Research Foundation of the Graduate
   School of FAFU to Excellent Master's Thesis (1122YS01006), the Open
   Funds of the Key Laboratory of Biopesticide and Chemical Biology, and
   Ministry of Education, FAFU (Keylab2020-04). Dr. Baitong Liu (Department
   of Chemistry, The University of Hong Kong, Pokfulam Road, Hong Kong SAR
   999077, P. R. China) is gratefully acknowledged for supporting
   nanomaterial synthesis and analysis.
CR Abdollahi N, 2020, J HAZARD MATER, V387, DOI 10.1016/j.jhazmat.2019.121667
   Ahmed T, 2022, NANO TODAY, V45, DOI 10.1016/j.nantod.2022.101547
   BONNESTAOUREL D, 1992, BIOCHEM PHARMACOL, V44, P985, DOI 10.1016/0006-2952(92)90132-3
   Campos EVR, 2023, ACS SUSTAIN CHEM ENG, V11, P9900, DOI 10.1021/acssuschemeng.3c02282
   Cao XS, 2023, ACS NANO, V17, P15821, DOI 10.1021/acsnano.3c03701
   Deng XL, 2023, J AGR FOOD CHEM, V71, P1417, DOI 10.1021/acs.jafc.2c07616
   Ding GH, 2009, B ENVIRON CONTAM TOX, V83, P520, DOI 10.1007/s00128-009-9811-8
   FAO, 2023, Pesticides Use
   Guo ML, 2023, J AGR FOOD CHEM, V72, P300, DOI 10.1021/acs.jafc.3c05238
   Hoop M, 2018, APPL MATER TODAY, V11, P13, DOI 10.1016/j.apmt.2017.12.014
   Hu PG, 2020, ACS NANO, V14, P7970, DOI 10.1021/acsnano.9b09178
   Huang GS, 2021, APPL SURF SCI, V564, DOI 10.1016/j.apsusc.2021.150325
   Hunsche M, 2006, PEST MANAG SCI, V62, P839, DOI 10.1002/ps.1242
   Jia HL, 2024, PLANT PHYSIOL BIOCH, V207, DOI 10.1016/j.plaphy.2024.108430
   Kalsi NK, 2019, ECOTOX ENVIRON SAFE, V170, P375, DOI 10.1016/j.ecoenv.2018.12.005
   Koch K, 2006, ENVIRON EXP BOT, V56, P1, DOI 10.1016/j.envexpbot.2004.09.013
   Kostina-Bednarz M, 2023, REV ENVIRON SCI BIO, V22, P471, DOI 10.1007/s11157-023-09656-1
   Liang WL, 2022, ACS NANO, V16, P2762, DOI 10.1021/acsnano.1c09724
   Liang WL, 2021, ACS NANO, V15, P6987, DOI 10.1021/acsnano.0c10877
   Liang Y, 2020, J HAZARD MATER, V389, DOI 10.1016/j.jhazmat.2020.122075
   Liédana N, 2012, ACS APPL MATER INTER, V4, P5016, DOI 10.1021/am301365h
   Luo D, 2020, RSC ADV, V10, P7360, DOI 10.1039/d0ra00108b
   Ma HY, 2021, ACS APPL MATER INTER, V13, P44329, DOI 10.1021/acsami.1c11815
   Ma YJ, 2022, ACS APPL NANO MATER, V5, P11864, DOI 10.1021/acsanm.2c02856
   McDougall P., 2017, Proceedings The Global Agrochemical Market Trends by Crop
   Nairn JJ, 2016, PEST MANAG SCI, V72, P551, DOI 10.1002/ps.4022
   Pan XH, 2024, J AGR FOOD CHEM, V72, P7807, DOI 10.1021/acs.jafc.4c00833
   Pan XH, 2023, ENVIRON SCI-NANO, V10, P1441, DOI [10.1039/d3en00059a, 10.1039/D3EN00059A]
   Pan XH, 2023, ENVIRON SCI-NANO, V10, P41, DOI [10.1039/d2en00605g, 10.1039/D2EN00605G]
   Pettinari C, 2021, COORDIN CHEM REV, V446, DOI 10.1016/j.ccr.2021.214121
   Qu HB, 2023, CHEM ENG J, V473, DOI 10.1016/j.cej.2023.145284
   Rao WH, 2024, PEST MANAG SCI, V80, P3022, DOI 10.1002/ps.8010
   Rao WH, 2022, SUSTAIN CHEM PHARM, V30, DOI 10.1016/j.scp.2022.100811
   Rao WH, 2018, J AGR FOOD CHEM, V66, P3651, DOI 10.1021/acs.jafc.8b00575
   Rodrigues S, 2024, ENVIRON SCI TECHNOL, V58, P3213, DOI 10.1021/acs.est.3c08723
   Sharma N., 2020, Ecotoxicol. Environ. Saf, V191, P1102204
   Shi LX, 2020, ACS BIOMATER SCI ENG, V6, P4595, DOI 10.1021/acsbiomaterials.0c00935
   Shi NB, 2022, SCI TOTAL ENVIRON, V832, DOI 10.1016/j.scitotenv.2022.154987
   Taheri M, 2021, ACS MATER LETT, V3, P255, DOI 10.1021/acsmaterialslett.0c00522
   Ullah H, 2020, SCI TOTAL ENVIRON, V737, DOI 10.1016/j.scitotenv.2020.139558
   Venna SR, 2010, J AM CHEM SOC, V132, P18030, DOI 10.1021/ja109268m
   Wang DJ, 2022, NAT NANOTECHNOL, V17, P347, DOI 10.1038/s41565-022-01082-8
   Wang J, 2022, CHEM ENG J, V430, DOI 10.1016/j.cej.2021.132920
   Wu D, 2011, ADV FUNCT MATER, V21, P2927, DOI 10.1002/adfm.201002733
   Xu CL, 2023, ENVIRON SCI-NANO, V10, P2578, DOI [10.1039/d3en00300k, 10.1039/D3EN00300K]
   Yang C, 2018, CHINESE CHEM LETT, V29, P1421, DOI 10.1016/j.cclet.2018.02.014
   Yang LP, 2024, ACS NANO, V18, P6533, DOI 10.1021/acsnano.3c12352
   Yu ML, 2017, RSC ADV, V7, P11271, DOI 10.1039/c6ra27345a
   Yu RB, 2020, MICROPOR MESOPOR MAT, V308, DOI 10.1016/j.micromeso.2020.110494
   Zhang DX, 2021, ADV FUNCT MATER, V31, DOI 10.1002/adfm.202102027
   Zhang HF, 2019, MICROPOR MESOPOR MAT, V288, DOI 10.1016/j.micromeso.2019.109568
   Zhang LC, 2023, ADV SCI, V10, DOI 10.1002/advs.202300270
   Zhang Q, 2013, ENVIRON MONIT ASSESS, V185, P9743, DOI 10.1007/s10661-013-3287-z
   Zhao KF, 2019, ACS SUSTAIN CHEM ENG, V7, P13148, DOI 10.1021/acssuschemeng.9b02319
   Zhao X, 2018, J AGR FOOD CHEM, V66, P6504, DOI 10.1021/acs.jafc.7b02004
   Zheng HQ, 2016, J AM CHEM SOC, V138, P962, DOI 10.1021/jacs.5b11720
   Zheng L, 2018, J AGR FOOD CHEM, V66, P11560, DOI 10.1021/acs.jafc.8b02619
   Zhu H, 2016, J BIONIC ENG, V13, P213, DOI 10.1016/S1672-6529(16)60295-0
NR 58
TC 0
Z9 0
U1 9
U2 9
PU ROYAL SOC CHEMISTRY
PI CAMBRIDGE
PA THOMAS GRAHAM HOUSE, SCIENCE PARK, MILTON RD, CAMBRIDGE CB4 0WF, CAMBS,
   ENGLAND
SN 2051-8153
EI 2051-8161
J9 ENVIRON SCI-NANO
JI Environ. Sci.-Nano
PD 2024 SEP 27
PY 2024
DI 10.1039/d4en00695j
EA SEP 2024
PG 15
WC Chemistry, Multidisciplinary; Environmental Sciences; Nanoscience &
   Nanotechnology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Chemistry; Environmental Sciences & Ecology; Science & Technology -
   Other Topics
GA I3Q6K
UT WOS:001329439500001
DA 2025-01-10
ER

PT J
AU Vinodhkumar, B
   Ullah, S
   Kumar, TVL
   Al-Ghamdi, SG
AF Vinodhkumar, Buri
   Ullah, Safi
   Kumar, T. V. Lakshmi
   Al-Ghamdi, Sami G.
TI Amplification of temperature extremes in Arabian Peninsula under warmer
   worlds
SO SCIENTIFIC REPORTS
LA English
DT Article
DE Temperature extremes; NEX-GDDP-CMIP6; SSPs; Global warming levels;
   Arabian Peninsula
ID 1.5 DEGREES-C; PROJECTED CHANGES; PRECIPITATION; INDEXES; MODELS
AB The Paris Agreement and the Special Report on Global Warming of 1.5 degrees C from the Intergovernmental Panel on Climate Change (IPCC) highlighted the potential risks of climate change across different global warming levels (GWLs). The increasing occurrence of extreme high-temperature events is linked to a warmer climate that is particularly prevalent in the Arabian Peninsula (AP). This study investigates future changes in temperatures and related extremes over AP, under four GWLs, such as 1.5 degrees C, 2.0 degrees C, 3.0 degrees C, and 4.0 degrees C, with three different Shared Socioeconomic Pathways (SSPs: SSP1-2.6, SSP2-4.5, and SSP5-8.5). The study uses high-resolution datasets of 27 models from the NASA Earth Exchange Global Daily Downscaled Projections of the Coupled Model Intercomparison Project Phase 6 (NEX-GDDP-CMIP6). The results showed that the NEX-GDDP-CMIP6 individual models and their multi-model means reasonably captured the extreme temperature events. The summer maximum and winter minimum temperatures are projected to increase by 0.11-0.67 degrees C and 0.09-0.70 degrees C per decade under the selected SSPs. Likewise, the projected temperature extremes exhibit significant warming with varying degrees across the GWLs under the selected SSPs. The warm temperature extremes are projected to increase, while the cold extremes are projected to decrease under all GWLs and the selected SSPs. Overall, the findings provide a comprehensive assessment of temperature changes over AP in response to global warming, which can be helpful in the development of climate adaptation and mitigation strategies.
C1 [Vinodhkumar, Buri; Ullah, Safi; Al-Ghamdi, Sami G.] King Abdullah Univ Sci & Technol KAUST, Environm Sci & Engn Program, Biol & Environm Sci & Engn Div, Thuwal 239556900, Saudi Arabia.
   [Vinodhkumar, Buri; Ullah, Safi; Al-Ghamdi, Sami G.] King Abdullah Univ Sci & Technol KAUST, KAUST Climate & Livabil Initiat, Thuwal 239556900, Saudi Arabia.
   [Vinodhkumar, Buri] Natl Inst Technol Rourkela, Dept Earth & Atmospher Sci, Rourkela 769008, India.
   [Kumar, T. V. Lakshmi] Jawaharlal Nehru Univ, Sch Environm Sci, New Delhi 110067, India.
C3 King Abdullah University of Science & Technology; King Abdullah
   University of Science & Technology; National Institute of Technology
   (NIT System); National Institute of Technology Rourkela; Jawaharlal
   Nehru University, New Delhi
RP Al-Ghamdi, SG (corresponding author), King Abdullah Univ Sci & Technol KAUST, Environm Sci & Engn Program, Biol & Environm Sci & Engn Div, Thuwal 239556900, Saudi Arabia.; Al-Ghamdi, SG (corresponding author), King Abdullah Univ Sci & Technol KAUST, KAUST Climate & Livabil Initiat, Thuwal 239556900, Saudi Arabia.
EM sami.alghamdi@kaust.edu.sa
RI ; Al-Ghamdi, Sami/AAH-6959-2020; Ullah, Safi/X-6228-2019
OI Buri, Vinodh Kumar/0000-0002-3986-5277; Al-Ghamdi,
   Sami/0000-0002-7416-5153; Ullah, Safi/0000-0002-2328-8321
CR Airiken M, 2023, HUM ECOL RISK ASSESS, V29, P1261, DOI 10.1080/10807039.2023.2260493
   Ajjur SB, 2021, EARTH SPACE SCI, V8, DOI 10.1029/2021EA001817
   Almazroui M, 2020, EARTH SYST ENVIRON, V4, P611, DOI 10.1007/s41748-020-00183-5
   Almazroui M, 2020, ADV METEOROL, V2020, DOI 10.1155/2020/8828421
   Almazroui M, 2020, EARTH SYST ENVIRON, V4, P297, DOI 10.1007/s41748-020-00157-7
   Almazroui M, 2020, ATMOS RES, V239, DOI 10.1016/j.atmosres.2020.104913
   Almazroui M, 2019, ATMOSPHERE-BASEL, V10, DOI 10.3390/atmos10110675
   Almazroui M, 2019, ADV METEOROL, V2019, DOI 10.1155/2019/5395676
   Almazroui M, 2017, ATMOS RES, V194, P202, DOI 10.1016/j.atmosres.2017.05.005
   Almazroui M, 2012, INT J CLIMATOL, V32, P953, DOI 10.1002/joc.3446
   [Anonymous], 2015, C PARTIES ITS 21 SES, P32
   Bawadekji A, 2022, SCI REP-UK, V12, DOI 10.1038/s41598-021-04200-z
   Becsi B., 2024, Linking local climate scenarios to global warming levels: Applicability, prospects and uncertainties
   Bharath J, 2024, INT J CLIMATOL, V44, P217, DOI 10.1002/joc.8324
   Campbell JD, 2021, ATMOSPHERE-BASEL, V12, DOI 10.3390/atmos12030328
   Donat MG, 2013, J GEOPHYS RES-ATMOS, V118, P2098, DOI 10.1002/jgrd.50150
   Dosio A, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aab827
   Driouech F, 2020, EARTH SYST ENVIRON, V4, P477, DOI 10.1007/s41748-020-00169-3
   Francis D, 2024, SCI REP-UK, V14, DOI 10.1038/s41598-024-60976-w
   Gudoshava M, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/ab6b33
   Hauser M., 2022, Zenodo, DOI [10.5281/zenodo,7390473, DOI 10.5281/ZENODO,7390473]
   Hersbach H, 2020, Q J ROY METEOR SOC, V146, P1999, DOI 10.1002/qj.3803
   IPCC, 2018, GLOBAL WARMING 15 C, V1st, DOI [10.1017/9781009157940, DOI 10.1017/9781009157940]
   IPCC, 2022, Global warming of 1.5 C: IPCC special report on impacts of global warming. of 1.5 C above pre-industrial levels in context of strengthening response to climate. change, sustainable development, and efforts to eradicate poverty, P313, DOI [DOI 10.1017/9781009157940, 10.1017/9781009157940.006]
   James R, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.457
   Kumar TVL, 2023, GLOBAL PLANET CHANGE, V226, DOI 10.1016/j.gloplacha.2023.104137
   [Masson-Delmotte V. IPCC IPCC], 2021, Summary for Policy Makers
   McCabe M., 2023, Climate Futures Report: Saudi Arabia in a 3-Degrees Warmer World, DOI [10.25781/KAUST-8XY63, DOI 10.25781/KAUST-8XY63]
   Navarro-Racines C, 2020, SCI DATA, V7, DOI 10.1038/s41597-019-0343-8
   Odnoletkova N, 2021, J APPL METEOROL CLIM, V60, P1055, DOI 10.1175/JAMC-D-20-0273.1
   Park T, 2023, EARTHS FUTURE, V11, DOI 10.1029/2022EF003330
   Qin PH, 2022, ATMOS RES, V273, DOI 10.1016/j.atmosres.2022.106165
   Rao KK, 2024, SCI REP-UK, V14, DOI 10.1038/s41598-023-49910-8
   Rao KK, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-73245-3
   Schleussner CF, 2022, COMMUN EARTH ENVIRON, V3, DOI 10.1038/s43247-022-00467-w
   Seneviratne S. I., 2021, Climate Change 2021-The Physical Science Basis, P1513, DOI [DOI 10.1017/9781009157896.013, 10.1017/9781009157896.013]
   Seneviratne SI, 2020, EARTHS FUTURE, V8, DOI 10.1029/2019EF001474
   Shi Y, 2018, ADV CLIM CHANG RES, V9, P192, DOI 10.1016/j.accre.2018.06.003
   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
   Ullah S, 2024, SCI REP-UK, V14, DOI 10.1038/s41598-024-54766-7
   Ullah S, 2020, ATMOS RES, V246, DOI 10.1016/j.atmosres.2020.105122
   Varela R, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0242477
   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
   World Meteorological Organization, 2024, State of the Global Climate 2023
   Wu F, 2023, HYDROL RES, V54, P703, DOI 10.2166/nh.2023.140
   Wu XY, 2021, INT J CLIMATOL, V41, P5766, DOI 10.1002/joc.7152
   Xu LL, 2023, ENVIRON RES LETT, V18, DOI 10.1088/1748-9326/acbfd0
   Zhang XB, 2011, WIRES CLIM CHANGE, V2, P851, DOI 10.1002/wcc.147
   Zhang YQ, 2024, SCI TOTAL ENVIRON, V916, DOI 10.1016/j.scitotenv.2024.170133
   Zhang YQ, 2023, SCI TOTAL ENVIRON, V876, DOI 10.1016/j.scitotenv.2023.162822
NR 52
TC 3
Z9 3
U1 6
U2 6
PU NATURE PORTFOLIO
PI BERLIN
PA HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY
SN 2045-2322
J9 SCI REP-UK
JI Sci Rep
PD JUL 18
PY 2024
VL 14
IS 1
AR 16604
DI 10.1038/s41598-024-67514-8
PG 13
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA ZB5J8
UT WOS:001272840900001
PM 39025891
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Rezaiy, R
   Shabri, A
AF Rezaiy, Reza
   Shabri, Ani
TI Improving Drought Prediction Accuracy: A Hybrid EEMD and Support Vector
   Machine Approach with Standardized Precipitation Index
SO WATER RESOURCES MANAGEMENT
LA English
DT Article
DE Time series; ARIMA; SVM; EEMD; Drought forecasting
AB This work combines the Support Vector Machine (SVM) model with Ensemble Empirical Mode Decomposition (EEMD) to present a novel method for drought prediction. The EEMD-SVM model is assessed for drought forecasting, comparing it to conventional Auto Regressive Integrated Moving Average (ARIMA) and SVM models. This study uses monthly precipitation data from Bamyan province in Central Afghanistan, spanning January 1970 to December 2019, including Standardized Precipitation Index (SPI) timelines: SPI 3, SPI 6, SPI 9, and SPI 12. To evaluate predictive effectiveness, statistical measures such as R-squared (R-2), mean absolute error (MAE), and root-mean-square error (RMSE) are used. Each SPI series is decomposed into Intrinsic Mode Functions (IMFs) and a residual series using the EEMD approach. The next stage projects each IMF component and residual using the appropriate SVM model. The final step creates an ensemble forecast for the original SPI series by combining the anticipated results of the residual series with the modeled IMFs. Compared to traditional ARIMA and SVM models, results show that the EEMD-SVM technique greatly improves drought forecasting accuracy, especially for mid- and long-term SPI. For example, in the testing period, SPI 9 yields an RMSE of 0.1632, MAE of 0.1208, and R-2 of 0.9357, while for SPI 12, RMSE is 0.1078, MAE is 0.0745, and R-2 is 0.9141, indicating the best criteria with the lowest RMSE and MAE and highest R-2 compared to conventional ARIMA and SVM. This novel technology could enhance the capacity to forecast drought episodes, leading to more efficient water resource management and climate adaptation plans.
C1 [Rezaiy, Reza; Shabri, Ani] Univ Teknol Malaysia UTM, Fac Sci, Dept Math Sci, UTM Johor BahruJohor Bahru, Johor Baharu 81310, Malaysia.
C3 Universiti Teknologi Malaysia
RP Rezaiy, R (corresponding author), Univ Teknol Malaysia UTM, Fac Sci, Dept Math Sci, UTM Johor BahruJohor Bahru, Johor Baharu 81310, Malaysia.
EM rezarezaiy@graduate.utm.my
RI Rezaiy, Reza/KUD-6281-2024
OI Rezaiy, Reza/0000-0002-2958-6610
FU Afghanistan's Ministry of Higher Education
FX The first author would like to express gratitude to Kabul Education
   University (KEU) for the study leave and Afghanistan's Ministry of
   Higher Education for the scholarship.
CR Achite M, 2023, WATER-SUI, V15, DOI 10.3390/w15040765
   AKAIKE H, 1974, IEEE T AUTOMAT CONTR, VAC19, P716, DOI 10.1109/TAC.1974.1100705
   Alawsi MA, 2022, HYDROLOGY-BASEL, V9, DOI 10.3390/hydrology9070115
   [Anonymous], 2018, Journal of Geoscience and Environment Protection, DOI [10.4236/gep.2018.68003, DOI 10.4236/GEP.2018.68003]
   Belayneh A, 2016, ATMOS RES, V172, P37, DOI 10.1016/j.atmosres.2015.12.017
   Belayneh A, 2012, APPL COMPUT INTELL S, V2012, DOI 10.1155/2012/794061
   Bhuva VV, 2023, ASSESSMENT DROUGHT U, P341
   Box G. E. P., 1976, Time Series Analysis: Forecasting and Control
   Cacciamani C, 2007, WATER SCI TECHNOL LI, V62, P29
   Cherkassky V, 2004, NEURAL NETWORKS, V17, P113, DOI 10.1016/S0893-6080(03)00169-2
   Debert S, 2011, EXP FLUIDS, V50, P339, DOI 10.1007/s00348-010-0925-x
   Deepa D, 2022, LECT NOTES CIVIL ENG, V191, P145, DOI 10.1007/978-981-16-5839-6_13
   Deo RC, 2017, ATMOS RES, V184, P149, DOI 10.1016/j.atmosres.2016.10.004
   Djerbouai S, 2016, WATER RESOUR MANAG, V30, P2445, DOI 10.1007/s11269-016-1298-6
   Elliott G, 1996, ECONOMETRICA, V64, P813, DOI 10.2307/2171846
   Frotan MS, 2019, P GSRD GLOB SOC RES
   Guttman NB, 1998, J AM WATER RESOUR AS, V34, P113, DOI 10.1111/j.1752-1688.1998.tb05964.x
   Guttman NB, 1999, J AM WATER RESOUR AS, V35, P311, DOI 10.1111/j.1752-1688.1999.tb03592.x
   Han J, 2023, ENVIRON MONIT ASSESS, V195, DOI 10.1007/s10661-023-12062-3
   Hayes MJ, 2005, BOOK SOIL P, V86, P53
   International Federation of Red Cross and Red Crescent Societies, 2021, EMERGENCY PLAN ACTIO
   Kalita DJ, 2023, EXPERT SYST APPL, V213, DOI 10.1016/j.eswa.2022.119189
   Kecman V., 2001, LEARNING SOFT COMPUT
   Kontopoulou VI, 2023, FUTURE INTERNET, V15, DOI 10.3390/fi15080255
   Kumar R, 2016, HYDROL EARTH SYST SC, V20, P1117, DOI 10.5194/hess-20-1117-2016
   김은희, 2004, Communications for Statistical Applications and Methods, V11, P323
   Libanda B, 2022, PHYS CHEM EARTH, V126, DOI 10.1016/j.pce.2022.103147
   Liu XP, 2022, J HYDROINFORM, V24, P535, DOI 10.2166/hydro.2022.146
   MCKEE TB, 1993, P 8 C APPL CLIM AN C
   Mishra AK, 2005, STOCH ENV RES RISK A, V19, P326, DOI 10.1007/s00477-005-0238-4
   Mishra AK, 2010, J HYDROL, V391, P204, DOI 10.1016/j.jhydrol.2010.07.012
   Mokhtarzad M, 2017, ENVIRON EARTH SCI, V76, DOI 10.1007/s12665-017-7064-0
   Moriasi DN, 2007, T ASABE, V50, P885, DOI 10.13031/2013.23153
   Raghavendra NS, 2014, APPL SOFT COMPUT, V19, P372, DOI 10.1016/j.asoc.2014.02.002
   Rezaiy R, 2024, WATER SCI TECHNOL, V89, P745, DOI 10.2166/wst.2024.028
   Rezaiy R, 2023, MATEMATIKA, V39, P239
   Rezaiy R, 2023, J WATER CLIM CHANGE, V14, P3345, DOI 10.2166/wcc.2023.431
   SCHWARZ G, 1978, ANN STAT, V6, P461, DOI 10.1214/aos/1176344136
   Singh Rashmi, 2022, Climate Change and Water Security: Select Proceedings of VCDRR 2021. Lecture Notes in Civil Engineering (178), P231, DOI 10.1007/978-981-16-5501-2_19
   Sobral BS, 2018, INT J CLIMATOL, V38, P3896, DOI 10.1002/joc.5542
   Tan YX, 2023, ARCH COMPUT METHOD E, V30, P1111, DOI 10.1007/s11831-022-09828-2
   Tigkas D, 2022, HYDROLOGY-BASEL, V9, DOI 10.3390/hydrology9060100
   Tigkas D, 2017, ENVIRON PROCESS, V4, pS137, DOI 10.1007/s40710-017-0219-x
   Tsakiris G, 2007, WATER RESOUR MANAG, V21, P821, DOI 10.1007/s11269-006-9105-4
   Vapnik VN., 1995, The Nature of Statistical Learning Theory, DOI [10.1007/978-1-4757-2440-0, DOI 10.1007/978-1-4757-2440-0]
   Weatherspark, 2024, AVERAGE WEATHER BAMY
   Wu H, 2007, INT J CLIMATOL, V27, P65, DOI 10.1002/joc.1371
   Wu ZH, 2009, ADV DATA SCI ADAPT, V1, P1, DOI 10.1142/S1793536909000047
   Yihdego Y, 2019, ARAB J GEOSCI, V12, DOI 10.1007/s12517-019-4237-z
   Zargar A, 2011, ENVIRON REV, V19, P333, DOI [10.1139/A11-013, 10.1139/a11-013]
   Zhang J, 2010, MECH SYST SIGNAL PR, V24, P2104, DOI 10.1016/j.ymssp.2010.03.003
   Zhang YH, 2020, NAT RESOUR RES, V29, P1447, DOI 10.1007/s11053-019-09512-6
NR 52
TC 5
Z9 5
U1 5
U2 5
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 OCT
PY 2024
VL 38
IS 13
BP 5255
EP 5277
DI 10.1007/s11269-024-03912-x
EA JUN 2024
PG 23
WC Engineering, Civil; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Water Resources
GA H8S3M
UT WOS:001259385900001
DA 2025-01-10
ER

PT J
AU Li, Q
   Dai, XY
   Hu, ZH
   Islam, AMT
   Karim, MR
   Fahim, CS
   Islam, HMT
   Fattah, MA
   Rahman, MM
   Pal, SC
AF Li, Qi
   Dai, Xinyu
   Hu, Zhenghua
   Islam, Abu Reza Md. Towfiqul
   Karim, Md. Rezaul
   Fahim, Chowdhury Sharifuddin
   Islam, H. M. Touhidul
   Fattah, Md. Abdul
   Rahman, Md. Mostafizar
   Pal, Subodh Chandra
TI Spatiotemporal trend analysis of hydroclimatic variables and their
   probable causes of changes in a hoar basin
SO THEORETICAL AND APPLIED CLIMATOLOGY
LA English
DT Article
ID CHANGE-POINT DETECTION; CLIMATE-CHANGE; NORTHEAST INDIA; RIVER-BASIN;
   TEMPERATURE; RAINFALL; PRECIPITATION; BRAHMAPUTRA; VARIABILITY; IMPACTS
AB Understanding trends in hydroclimatic variables is crucial for linking local climatic drivers with regional water use practices, particularly in a vulnerable Haor basin in tropical country like Bangladesh. This study evaluated the spatiotemporal trends in hydroclimatic variables at annual and seasonal scales using advanced statistical methods, including the Modified Mann-Kendall (MK) test, Sen's slope, Sequential Mann-Kendal, Pettitt test, and linear regression model. Additionally, Detrended Fluctuation Analysis (DFA) and Morlet Wavelet Analysis (MWA) were utilized to analyze historical periodic cycles and predict future trends. Results show a significant decrease in annual and seasonal surface water levels (SWL) and rainfall, except for the monsoon, while both maximum and minimum temperatures simultaneously increased. The decline in annual SWL at a rate of 1.18 m/year was influenced by an increase in maximum temperature at a rate of 0.03 degrees C/year and a decrease in annual total rainfall at a rate of 5.25 mm/year. DFA analysis suggests long-term correlations among these variables, predicting future increases in temperature but continued decreases in rainfall and SWL. Periodic cycles with various frequencies were observed in rainfall, maximum, and minimum temperatures. ECMWF ERA5 reanalysis datasets attribute these changes to higher pre-monsoon geopotential heights, lower relative humidity, and higher monsoon rainfall associated with lower surface pressure. The findings of the study will help develop targeted climate adaptation strategies to mitigate the adverse effects on agriculture, biodiversity, and freshwater availability in the region. The overall study provides essential data that can inform water resource management strategies.
C1 [Li, Qi; Dai, Xinyu; Hu, Zhenghua] Nanjing Univ Informat Sci & Technol, Sch Ecol & Appl Meteorol, Nanjing 210044, Peoples R China.
   [Islam, Abu Reza Md. Towfiqul; Karim, Md. Rezaul; Islam, H. M. Touhidul] Begum Rokeya Univ, Dept Disaster Management, Rangpur 5400, Bangladesh.
   [Islam, Abu Reza Md. Towfiqul] Daffodil Int Univ, Dept Dev Studies, Dhaka 1216, Bangladesh.
   [Fahim, Chowdhury Sharifuddin] Bangladesh Univ Profess, Fac Sci & Technol, Dept Environm Sci, Dhaka 1216, Bangladesh.
   [Fattah, Md. Abdul] Florida State Univ, Dept Geog, Tallahassee, FL 32306 USA.
   [Rahman, Md. Mostafizar] Bangladesh Meteorol Dept, Dhaka, Bangladesh.
   [Pal, Subodh Chandra] Univ Burdwan, Dept Geog, Bardhaman 713104, West Bengal, India.
C3 Nanjing University of Information Science & Technology; Daffodil
   International University; State University System of Florida; Florida
   State University; University of Burdwan
RP Li, Q (corresponding author), Nanjing Univ Informat Sci & Technol, Sch Ecol & Appl Meteorol, Nanjing 210044, Peoples R China.; Islam, AMT (corresponding author), Begum Rokeya Univ, Dept Disaster Management, Rangpur 5400, Bangladesh.; Islam, AMT (corresponding author), Daffodil Int Univ, Dept Dev Studies, Dhaka 1216, Bangladesh.
EM liqix123@sina.com; daixinyu08@126.com; zhhu@nuist.edu.cn;
   towfiq_dm@brur.ac.bd; rezauldsm@gmail.com; fahimthelionheart@gmail.com;
   touhidul02@gmail.com; mafattah.kuet@gmail.com; mostafiz.bmd16@gmail.com;
   subodh.rsgis@gmail.com
RI Islam, H. M. Touhidul/ABC-2522-2020; Fattah, Abdul/AAR-8927-2021; Islam,
   Abu/AAN-8105-2020
OI Pal, Subodh Chandra/0000-0003-0805-8007; Islam, H. M.
   Touhidul/0000-0003-2146-2864
FX The authors would like to thank the Bangladesh Meteorological Department
   (BMD) and Bangladesh Water Development Board (BWDB) for providing
   datasets for this research.
CR Ahlen I, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-81137-3
   Akhter S, 2019, QUATERN INT, V513, P80, DOI 10.1016/j.quaint.2019.01.022
   Alam E, 2023, PLOS ONE, V18, DOI 10.1371/journal.pone.0292668
   Bari SH, 2016, ATMOS RES, V176, P148, DOI 10.1016/j.atmosres.2016.02.008
   BHWDB, 2012, HAOR MASTER PLAN
   Chakraborty D, 2017, ENVIRON PROCESS, V4, P937, DOI 10.1007/s40710-017-0263-6
   Chatterjee SK., 2012, ENVIRON CHEM, V46, P4
   Choudhury BA, 2019, J GEOPHYS RES-ATMOS, V124, P227, DOI 10.1029/2018JD029625
   CHOWDHURY MAI, 2016, J BIODIVERS ENVIRON, V8, P181
   Dabral PP, 2016, GLOBAL NEST J, V18, P494
   Dadson SJ., 2019, Water Science, Policy, and Management, V1st, P11, DOI DOI 10.1002/9781119520627.CH2
   Das J, 2021, THEOR APPL CLIMATOL, V143, P1557, DOI 10.1007/s00704-020-03508-6
   Das J, 2020, MAUSAM, V71, P33
   Das J, 2019, SPAT INF RES, V27, P411
   Das J, 2018, SPAT INF RES, V26, P271, DOI 10.1007/s41324-018-0173-3
   Dash SK, 2012, GLOBAL PLANET CHANGE, V98-99, P31, DOI 10.1016/j.gloplacha.2012.07.006
   Datta P, 2019, SPAT INF RES, V27, P475, DOI 10.1007/s41324-019-00250-8
   Fabio Di Nunno, 2022, Arabian Journal of Geosciences, V15, DOI 10.1007/s12517-022-09906-6
   Fattah MA, 2022, THEOR APPL CLIMATOL, V148, P285, DOI 10.1007/s00704-022-03943-7
   Feizi V., 2014, ECOPERSIA, V2, P727
   Feng G, 2016, J APPL METEOROL CLIM, V55, P1425, DOI 10.1175/JAMC-D-15-0265.1
   Forootan E, 2019, SOIL WATER RES, V14, P163, DOI 10.17221/154/2018-SWR
   Ghose B, 2021, THEOR APPL CLIMATOL, V144, P1077, DOI 10.1007/s00704-021-03584-2
   Ghosh S, 2012, J EARTH SYST SCI, V121, P637, DOI 10.1007/s12040-012-0181-y
   Hossain MA., 2015, EC AGR, V1, P124
   India Meteorological Department, 2018, PURCH CLIM DAT
   Islam AMT, 2024, THEOR APPL CLIMATOL, DOI 10.1007/s00704-024-04892-z
   Islam AMT, 2022, THEOR APPL CLIMATOL, V147, P1263, DOI 10.1007/s00704-021-03909-1
   Islam AMT, 2021, THEOR APPL CLIMATOL, V143, P33, DOI 10.1007/s00704-020-03411-0
   Islam AMT, 2020, THEOR APPL CLIMATOL, V141, P869, DOI 10.1007/s00704-020-03244-x
   Islam AMT, 2020, METEOROL ATMOS PHYS, V132, P793, DOI 10.1007/s00703-019-00720-6
   Islam ARMT, 2015, INT J GEOPHYS, V2015, DOI 10.1155/2015/840168
   Islam AT, 2019, THEOR APPL CLIMATOL, V138, P97, DOI 10.1007/s00704-019-02818-8
   Jhajharia D, 2012, HYDROL PROCESS, V26, P421, DOI 10.1002/hyp.8140
   Jhajharia D, 2011, INT J CLIMATOL, V31, P1353, DOI 10.1002/joc.2164
   Kendall, 1975, ECONOMETRICA, V13, P245
   Kulkarni A., 2020, Assessment of climate change over the Indian Region, P47, DOI [10.1007/978-981-15-4327-23, DOI 10.1007/978-981-15-4327-23, 10.1007/978-981-15-4327-2_3]
   Li M, 2018, SCI TOTAL ENVIRON, V625, P496, DOI 10.1016/j.scitotenv.2017.12.317
   Mallick J, 2022, THEOR APPL CLIMATOL, V148, P329, DOI 10.1007/s00704-021-03914-4
   Mallick J, 2022, THEOR APPL CLIMATOL, V147, P307, DOI 10.1007/s00704-021-03828-1
   Mondol M., 2023, BANGLADESH METEOROL, V135, P57, DOI [10.1007/s00703-023-00995-w, DOI 10.1007/S00703-023-00995-W]
   Morshed SR, 2021, REMOTE SENS APPL, V24, DOI 10.1016/j.rsase.2021.100658
   Mullick MRA, 2019, GLOBAL PLANET CHANGE, V172, P104, DOI 10.1016/j.gloplacha.2018.10.001
   Nath H, 2024, THEOR APPL CLIMATOL, V155, P3693, DOI 10.1007/s00704-024-04843-8
   Pachauri R. K., 2007, CLIMATE CHANGE 2007, P104, DOI DOI 10.1017/CBO9780511546013
   Pawar Uttam, 2022, Arabian Journal of Geosciences, V15, DOI 10.1007/s12517-022-09646-7
   Pawar U, 2023, CLIMATE, V11, DOI 10.3390/cli11080163
   Pettitt A. N., 1979, Applied Statistics, V28, P126, DOI 10.2307/2346729
   Prakash S, 2014, CURR SCI INDIA, V107, P1582
   Praveen B, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-67228-7
   Prevedello JA, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0213368
   Rahman MR, 2016, CLIM DYNAM, V46, P2943, DOI 10.1007/s00382-015-2742-7
   Rahman MS, 2019, SCI TOTAL ENVIRON, V690, P370, DOI 10.1016/j.scitotenv.2019.06.529
   Rahman MM, 2020, HYDROLOG SCI J, V65, P33, DOI 10.1080/02626667.2019.1676427
   Rana M., 2007, Pakistan Journal of Meteorology, V4, P7
   Ravindranath NH, 2011, CURR SCI INDIA, V101, P384
   Real MKH, 2023, THEOR APPL CLIMATOL, V152, P167, DOI 10.1007/s00704-023-04382-8
   Renard B., 2006, HOUILLE BLANCHE, V6, P46
   Roxy MK, 2017, NAT COMMUN, V8, DOI 10.1038/s41467-017-00744-9
   Salam R, 2021, NAT HAZARDS, V106, P509, DOI 10.1007/s11069-020-04473-z
   Salam R, 2020, J HYDROL, V590, DOI 10.1016/j.jhydrol.2020.125241
   Salam R, 2020, ENVIRON DEV SUSTAIN, V22, P4509, DOI 10.1007/s10668-019-00395-4
   Sen Z, 2014, J HYDROL ENG, V19, P635, DOI 10.1061/(ASCE)HE.1943-5584.0000811
   Sneyers R., 1990, ATMOS RES, P192, DOI [DOI 10.1016/0169-8095(93)90010-L, 10.1016/0169-8095(93)90010-l]
   Terao T, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL023010
   Terao T, 2013, J METEOROL SOC JPN, V91, P1, DOI 10.2151/jmsj.2013-101
   Tong SQ, 2019, SCI TOTAL ENVIRON, V649, P75, DOI 10.1016/j.scitotenv.2018.08.262
   Toride K, 2018, SCI TOTAL ENVIRON, V626, P244, DOI 10.1016/j.scitotenv.2018.01.004
   Ullah S, 2019, INT J CLIMATOL, V39, P1457, DOI 10.1002/joc.5894
   Varotsos CA, 2006, INT J REMOTE SENS, V27, P3593, DOI 10.1080/01431160600617236
   Whitehead PG, 2015, ENVIRON SCI-PROC IMP, V17, P1057, DOI [10.1039/c4em00619d, 10.1039/C4EM00619D]
   Yue S, 2002, HYDROL PROCESS, V16, P1807, DOI 10.1002/hyp.1095
   Zannat F., 2019, BANGLADESH EUR J GEO, V1, P35, DOI [10.34154/2019-EJGS-0101-35-56/euraass, DOI 10.34154/2019-EJGS-0101-35-56/EURAASS]
NR 73
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 AUG
PY 2024
VL 155
IS 8
BP 7413
EP 7432
DI 10.1007/s00704-024-05074-7
EA JUN 2024
PG 20
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA E0R1F
UT WOS:001257458300001
DA 2025-01-10
ER

PT J
AU Starosta, D
AF Starosta, Daniel
TI Raised under bad stars: negotiating a culture of disaster preparedness
SO DISASTER PREVENTION AND MANAGEMENT
LA English
DT Article; Early Access
DE Culture; Storytelling; Folklore; Climate adaptation; Indigenous
   knowledge
ID INDIGENOUS KNOWLEDGE; CLIMATE; ISLAND
AB PurposeThe ways communities have regarded disasters and natural hazards in the cultural sphere can provide a lens to inform the understanding of their ability to withstand shocks and the factors that led to such conditions. Only by tracing the complexities of creating, transmitting and preserving a culture of preparedness among disaster-vulnerable communities can researchers and practitioners claim to be working toward policy that is informed by the communities' own experience and design policy or programming on their behalf.Design/methodology/approachIn efforts to prevent, respond to and recover from disasters, what alternatives are available to top-down strategies for imposing expert knowledge on lay publics? How is the context of communities' socioecological context understood in the development of programs and policy on their behalf? What can be learned from community narratives and cultural practices to inform disaster risk reduction?FindingsI collected examples of how different communities perceive, prevent and respond to disaster through art, music and literature and analyzed how these were embedded into local narratives and how historical context influenced such approaches. My findings show that communities use cultural practices to contextualize experiences of hazards into their collective narrative; that is, storytelling and commemoration make disasters comprehensible. By incorporating such findings into existing policies and programs, institutions may be able to more effectively apply them to affected communities or build new ones around their actual needs and experiences.Originality/valueBy framing disasters as an anthropological inquiry, practitioners can better recognize the influence of a place's nuance in the disaster management canon-guided by these details, not despite them.
C1 [Starosta, Daniel] Univ Calif Berkeley, Goldman Sch Publ Policy, Berkeley, CA 94720 USA.
C3 University of California System; University of California Berkeley
RP Starosta, D (corresponding author), Univ Calif Berkeley, Goldman Sch Publ Policy, Berkeley, CA 94720 USA.
EM starostad@berkeley.edu
CR [Anonymous], 1855, Catfish and keystone
   [Anonymous], 1855, Kawaraban namazu-e ni miru Edo Meiji no saigai joho-Ishimoto collection kara
   [Anonymous], 1855, Artist unkown
   [Anonymous], 1855, Artist unknown
   [Anonymous], Catfish competition of strength
   Athukorala PC, 2012, ASIAN ECON J, V26, P211, DOI 10.1111/j.1467-8381.2012.02083.x
   Crate SA, 2011, ANNU REV ANTHROPOL, V40, P175, DOI 10.1146/annurev.anthro.012809.104925
   Dafoe T., 2022, Artnet News
   Dahdouh-Guebas F, 2005, CURR BIOL, V15, pR443, DOI 10.1016/j.cub.2005.06.008
   de Freitas N., 1999, Visual Representations and Interpretations, P62, DOI [10.1007/978-1-4471-0563-3_7, DOI 10.1007/978-1-4471-0563-3_7]
   Douglas, 2017, IMG_20170521_095358
   Ellis EC, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2023483118
   Fanta V, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-09102-3
   Gadeng AN, 2018, IOP C SER EARTH ENV, V145, DOI 10.1088/1755-1315/145/1/012041
   Gaiman N., 2017, The View from the Cheap Seats: Selected Non-fiction, VFirst Edition, P5
   Hamblyn Richard., 2014, Tsunami. Nature and culture
   Henshall K, 2014, WHEN THE TSUNAMI CAME TO SHORE: CULTURE AND DISASTER IN JAPAN, P179, DOI 10.1163/9789004268319_010
   Hoffman S., 2002, Anthropologica, V45, DOI [10.2307/25606126, DOI 10.2307/25606126]
   Huet M.H., 2012, The Culture of Disaster, The University of Chicago Press, Japan's Success in Risk Reduction Highlighted on March 11 Anniversary
   Ishiwatari M, 2021, NAT HAZARDS REV, V22, DOI 10.1061/(ASCE)NH.1527-6996.0000423
   Jogia J., 2014, Built and Human Environment Review, V7, P1
   Jones L. M., 2018, The Big Ones: How Natural Disasters Have Shaped Us (and What We Can Do about Them), VFirst edition, P77
   Kamakau SamuelM., 1976, The Works of the People of Old, Na hana a ka Po'e Kahiko
   Kelman I, 2012, GEOGRAPHY, V97, P12
   Kennedy Philip., 2016, ILLUSTRATION CHRONIC
   Lazrus H, 2012, ANNU REV ANTHROPOL, V41, P285, DOI 10.1146/annurev-anthro-092611-145730
   MacGillivray BH, 2018, ENVIRON SCI POLICY, V89, P116, DOI 10.1016/j.envsci.2018.07.014
   McAdoo BG, 2006, EARTHQ SPECTRA, V22, pS661, DOI 10.1193/1.2204966
   McAdoo BG, 2009, NAT HAZARDS, V48, P73, DOI 10.1007/s11069-008-9249-z
   Nakai S., 2021, ETropic: Electronic Journal of Studies in the Tropics, V20, P114, DOI [10.25120/etropic.20.2.2021.3810, DOI 10.25120/ETROPIC.20.2.2021.3810]
   Namazu-tron, 2011, " English: earthquake early warning unit, FM radio type, Iris Ohyama, model:EQA-001. Front view (upper), rear view (lower) ", Own work, Wikimedia Commons
   ONG WJ, 1969, AM ANTHROPOL, V71, P634, DOI 10.1525/aa.1969.71.4.02a00030
   Perilla JL, 2002, J SOC CLIN PSYCHOL, V21, P20, DOI 10.1521/jscp.21.1.20.22404
   Quarantelli E.L., 1987, Disaster studies: An analysis of the social historical factors affecting the development of research in the area
   Quin M., 2021, Locus: The Seton Hall Journal of Undergraduate Research, V4
   Rahman A, 2017, IOP C SER EARTH ENV, V56, DOI 10.1088/1755-1315/56/1/012018
   Schwartz SB, 2015, LAWRENCE STONE LECT, pIX
   Simmons-Duffin S., 2011, NPR
   Smith Neil., 2006, UNDERSTANDING KATRIN
   Smits G, 2006, J SOC HIST, V39, P1045, DOI 10.1353/jsh.2006.0057
   Starrs R., 2014, Global Oriental
   Sutton SA, 2021, INT J DISAST RISK RE, V65, DOI 10.1016/j.ijdrr.2021.102527
   Syafwina, 2014, PROCEDIA ENVIRON SCI, V20, P573, DOI 10.1016/j.proenv.2014.03.070
   Tapol, 2000, Aceh: Ecological War Zone
   Vale L., 2014, PLACES J, V2014, DOI [10.22269/141215, DOI 10.22269/141215]
   Vellut G., 2013, Yaesu, wikimedia commons
   Webb GaryR., 2018, HDB DISASTER RES, P109
   Yoon H.-K., 1991, Geo Journal, V25, P387, DOI [10.1007/BF02439490, DOI 10.1007/BF02439490]
   Yustisia Lestari Titie, 2020, MATEC Web of Conferences, V331, DOI 10.1051/matecconf/202033101007
NR 49
TC 0
Z9 0
U1 7
U2 7
PU EMERALD GROUP PUBLISHING LTD
PI Leeds
PA Floor 5, Northspring 21-23 Wellington Street, Leeds, W YORKSHIRE,
   ENGLAND
SN 0965-3562
EI 1758-6100
J9 DISASTER PREV MANAG
JI Disaster Prev. Manag.
PD 2024 MAY 7
PY 2024
DI 10.1108/DPM-09-2023-0231
EA MAY 2024
PG 17
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 PP0S7
UT WOS:001215170700001
DA 2025-01-10
ER

PT J
AU Hansen, R
   Mattes, A
   Meier, M
   Kurths, A
AF Hansen, Rieke
   Mattes, Anna
   Meier, Maren
   Kurths, Andreas
TI Reorienting urban green infrastructure planning towards biodiversity -
   Perspectives and ongoing debates from Germany
SO URBAN FORESTRY & URBAN GREENING
LA English
DT Article
DE Nature-based solutions; Sustainable urban development; Urban nature;
   Urban planning; Urban wilderness; Synergies
ID CITY
AB The concept of green infrastructure has the potential to promote planning and implementation of multifunctional green and blue spaces that tackle several urban sustainability issues. Around 2016, German governmental institutions initiated a discourse on green infrastructure as a planning approach at the federal level. This initiative resulted, amongst other, in an urban green infrastructure planning concept tailored for the German planning context. This initial framing of the concept was broad and relatively open. It was supposed to address a wide range of disciplines in field of urban green and blue spaces and integrate their perspectives. In this short communication, we use the example from Germany to discuss how concepts such urban green infrastructure could, or should, evolve in the light of changing socio-political priorities. In response to calls for action on ecosystem and biodiversity loss, we propose shifting the focus of green infrastructure planning explicitly to biodiversity. However, reframing around a specific topic might exclude actors with other priorities and reduce the integrative potential of the concept. Therefore, we suggest how biodiversity can be defined as a cross-cutting issue that creates synergies with other urban sustainability goals such as climate adaptation or social cohesion and avoids narrowing the integrative idea. We use eight best practice cases to illustrate that biodiversity goals can go hand in hand with other urban sustainability goals. Based on these cases, we conclude that urban green infrastructure provides a solid framework that allows a shift in priorities towards biodiversity, while the integrated approach is maintained. These considerations are derived from an on-going research and development project that aims to make the green infrastructure concept actionable for German cities.
C1 [Hansen, Rieke] Hsch Geisenheim Univ, Inst Open Space Dev, Von Lade Str 1, D-65366 Geisenheim, Germany.
   [Mattes, Anna; Meier, Maren; Kurths, Andreas] Freiraum GmbH, Gneisenaustr 41, D-10961 Berlin, Germany.
RP Hansen, R (corresponding author), Hsch Geisenheim Univ, Inst Open Space Dev, Von Lade Str 1, D-65366 Geisenheim, Germany.
EM rieke.hansen@hs-gm.de
OI Kurths, Andreas/0009-0007-2360-1561; Hansen, Rieke/0000-0002-4230-1579
FU Federal Agency for Nature Conservation (BfN); Federal Ministry for the
   Environment, Nature Conservation, Nuclear Safety and Consumer Protection
   (BMUV) [FKZ: 3520810800]
FX This work was supported by the Federal Agency for Nature Conservation
   (BfN) with funds from the Federal Ministry for the Environment, Nature
   Conservation, Nuclear Safety and Consumer Protection (BMUV) (FKZ:
   3520810800) .
CR Albert C, 2017, PLAN PRACT RES, V32, P227, DOI 10.1080/02697459.2014.973683
   [Anonymous], 2021, Principles for ecosystem restoration to guide the United Nations Decade 2021-2030
   Apfelbeck B, 2020, LANDSCAPE URBAN PLAN, V200, DOI 10.1016/j.landurbplan.2020.103817
   Barra M., 2022, Ecology of green roofs: Summary of the GROOVES (Green roofs verified ecosystem services) study
   BMU, 2019, Masterplan Stadtnatur: Massnahmenprogramm der Bundesregierung fur eine lebendige Stadt
   BMUB, 2018, White Paper: Green Spaces in the City - For a more liveable future
   BMUV, 2022, Federal Action Plan on Nature-based Solutions for Climate and Biodiversity: Key issues paper
   Carver S, 2021, CONSERV BIOL, V35, P1882, DOI 10.1111/cobi.13730
   Danford RS, 2018, URBAN FOR URBAN GREE, V29, P377, DOI 10.1016/j.ufug.2017.11.014
   Davoudi S, 2015, PLAN THEOR, V14, P316, DOI 10.1177/1473095215575919
   decadeonrestoration, UNEP and FAO Urban Areas
   EC, 2021, Evaluating the Impact of Nature-based Solutions: A Handbook for Practitioners
   Egerer M, 2022, RENEW AGR FOOD SYST, V37, P371, DOI 10.1017/S1742170522000199
   EU, 2020, (COM (2020) 380)
   Gann GD, 2019, RESTOR ECOL, V27, pS3, DOI 10.1111/rec.13035
   German Federal Agency for Nature Conservation, 2017, Federal Green Infrastructure Concept
   Grabowski ZJ, 2022, FRONT ECOL ENVIRON, V20, P152, DOI 10.1002/fee.2445
   Hall DM, 2017, CONSERV BIOL, V31, P24, DOI 10.1111/cobi.12840
   Hansen R., 2021, Socio-Ecological Practice Research, DOI [DOI 10.1007/S42532-021-00087-2, 10.1007/s42532-021-00087]
   Hansen R., 2018, Stadt. + Grun, V2018, P39
   Hansen R., 2017, Pointers for municipal practice
   Hansen R, 2023, EUR PLAN STUD, V31, P2401, DOI 10.1080/09654313.2022.2139594
   Heiland S., 2017, Fachgutachten. Bfn-Schriften, V457
   Klaus VH, 2021, BASIC APPL ECOL, V52, P82, DOI 10.1016/j.baae.2021.02.010
   Kowarik I, 2021, LANDSC ARCHIT FRONT, V9, P92, DOI 10.15302/J-LAF-1-030025
   Lindschulte K., 2018, Grune Infrastruktur im urbanen Raum: Grundlagen, Planung und Umsetzung
   Maller C, 2021, CITIES, V113, DOI 10.1016/j.cities.2021.103155
   Matsler M, 2021, LANDSCAPE URBAN PLAN, V214, DOI 10.1016/j.landurbplan.2021.104145
   Mattijssen TJM, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11205781
   Mell I, 2017, INT PLAN STUD, V22, P333, DOI 10.1080/13563475.2017.1291334
   Munter C, 2019, Neue Landschaft, P8
   Seitz B, 2022, URBAN ECOSYST, V25, P927, DOI 10.1007/s11252-021-01198-0
   Teremy V.N., 2021, 4D, V59, P84, DOI [10.36249/59.6, DOI 10.36249/59.6]
NR 33
TC 2
Z9 2
U1 15
U2 40
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 DEC
PY 2023
VL 90
AR 128155
DI 10.1016/j.ufug.2023.128155
EA NOV 2023
PG 7
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 CR0X2
UT WOS:001126863600001
OA hybrid
DA 2025-01-10
ER

PT J
AU Tolan, J
   Yang, H
   Nosarzewski, B
   Couairon, G
   Vo, HV
   Brandt, J
   Spore, J
   Majumdar, S
   Haziza, D
   Vamaraju, J
   Moutakanni, T
   Bojanowski, P
   Johns, T
   White, B
   Tiecke, T
   Couprie, C
AF Tolan, Jamie
   Yang, Hung -, I
   Nosarzewski, Benjamin
   Couairon, Guillaume
   V. Vo, Huy
   Brandt, John
   Spore, Justine
   Majumdar, Sayantan
   Haziza, Daniel
   Vamaraju, Janaki
   Moutakanni, Theo
   Bojanowski, Piotr
   Johns, Tracy
   White, Brian
   Tiecke, Tobias
   Couprie, Camille
TI Very high resolution canopy height maps from RGB imagery using
   self-supervised vision transformer and convolutional decoder trained on
   aerial lidar
SO REMOTE SENSING OF ENVIRONMENT
LA English
DT Article
DE LIDAR; GEDI; Canopy height; Deep learning; Self -supervised learning;
   Vision transformers
ID ESTIMATING AREA; CARBON; ACCURACY
AB Vegetation structure mapping is critical for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. Repeated measurements of these data allow for the observation of deforestation or degradation of existing forests, natural forest regeneration, and the implementation of sustainable agricultural practices like agroforestry. Assessments of tree canopy height and crown projected area at a high spatial resolution are also important for monitoring carbon fluxes and assessing tree-based land uses, since forest structures can be highly spatially heterogeneous, especially in agroforestry systems. Very high resolution satellite imagery (less than one meter (1 m) Ground Sample Distance) makes it possible to extract information at the tree level while allowing monitoring at a very large scale. This paper presents the first high-resolution canopy height map concurrently produced for multiple sub-national jurisdictions. Specifically, we produce very high resolution canopy height maps for the states of California and Sao Paulo, a significant improvement in resolution over the ten meter (10 m) resolution of previous Sentinel / GEDI based worldwide maps of canopy height. The maps are generated by the extraction of features from a self-supervised model trained on Maxar imagery from 2017 to 2020, and the training of a dense prediction decoder against aerial lidar maps. We also introduce a post -processing step using a convolutional network trained on GEDI observations. We evaluate the proposed maps with set-aside validation lidar data as well as by comparing with other remotely sensed maps and field-collected data, and find our model produces an average Mean Absolute Error (MAE) of 2.8 m and Mean Error (ME) of 0.6 m.
C1 [Tolan, Jamie; Yang, Hung -, I; Nosarzewski, Benjamin; Vamaraju, Janaki; Johns, Tracy; White, Brian; Tiecke, Tobias] Meta, 1 Hacker Way, Menlo Pk, CA 94025 USA.
   [Couairon, Guillaume; V. Vo, Huy; Haziza, Daniel; Moutakanni, Theo; Bojanowski, Piotr; Couprie, Camille] Fundamental Res FAIR, Meta, 1 Hacker Way, Menlo Pk, CA 94025 USA.
   [Brandt, John; Spore, Justine] World Resources Inst, 10 G St NE 800, Washington, DC 20002 USA.
   [Majumdar, Sayantan] Desert Res Inst, 2215 Raggio Pkwy, Reno, NV 89512 USA.
C3 Nevada System of Higher Education (NSHE); Desert Research Institute NSHE
RP Brandt, J (corresponding author), World Resources Inst, 10 G St NE 800, Washington, DC 20002 USA.
EM john.brandt@wri.org
RI couprie, camille/H-4092-2014; Vo, Hoang/HRC-8699-2023; Majumdar,
   Sayantan/HJP-6033-2023
CR Adam M, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12233948
   Astola H, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13122392
   Azevedo T., 2018, Mapbiomas Initiative: Mapping Annual Land Cover and Land Use Changes in Brazil from 1985 to 2017
   Bhat SF, 2021, PROC CVPR IEEE, P4008, DOI 10.1109/CVPR46437.2021.00400
   Brandt M, 2020, NATURE, V587, P78, DOI 10.1038/s41586-020-2824-5
   Camarretta N, 2020, NEW FOREST, V51, P573, DOI 10.1007/s11056-019-09754-5
   Cook-Patton SC, 2020, NATURE, V585, P545, DOI 10.1038/s41586-020-2686-x
   Csillik O, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-54386-6
   Cuni-Sanchez A, 2021, NATURE, V596, P536, DOI 10.1038/s41586-021-03728-4
   da Luz N.B., 2018, Pesquisa Florestal Bras, V38, DOI [10.4336/2018.pfb.38e201701493, DOI 10.4336/2018.PFB.38E201701493]
   Dos-Santos M.N., 2019, LIDAR SURVEYS SELECT
   Dosovitskiy A., 2021, INT C LEARN REPR
   Dosovitskiy A, 2021, Arxiv, DOI arXiv:2010.11929
   Dubayah R., Gedi l3 Gridded Land Surface Metrics
   Dubayah R.O., 2022, GEDI L4A Footprint Level Aboveground Biomass Density, DOI DOI 10.3334/ORNLDAAC/2056
   Dubayah R, 2020, SCI REMOTE SENSING, V1, DOI 10.1016/j.srs.2020.100002
   Duncanson L, 2020, REMOTE SENS ENVIRON, V242, DOI 10.1016/j.rse.2020.111779
   Eigen D, 2014, ADV NEUR IN, V27
   Fayad I, 2023, Arxiv, DOI [arXiv:2304.11487, 10.48550/ARXIV.2304.11487, DOI 10.48550/ARXIV.2304.11487]
   Friedlingstein P, 2019, EARTH SYST SCI DATA, V11, P1783, DOI 10.5194/essd-11-1783-2019
   Fu H, 2018, Arxiv, DOI arXiv:1708.08267
   Gibril MBA, 2023, DRONES-BASEL, V7, DOI 10.3390/drones7020093
   Hancock S, 2019, EARTH SPACE SCI, V6, P294, DOI 10.1029/2018EA000506
   Hansen MC, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/3/034008
   Hanson MA, 2012, SCIENCE, V335, P851, DOI [10.1126/science.1244693, 10.1126/science.1215904]
   Harris NL, 2021, NAT CLIM CHANGE, V11, DOI 10.1038/s41558-020-00976-6
   He KM, 2022, PROC CVPR IEEE, P15979, DOI 10.1109/CVPR52688.2022.01553
   Khosravipour A, 2014, PHOTOGRAMM ENG REM S, V80, P863, DOI 10.14358/PERS.80.9.863
   Lang N., 2022, arXiv, DOI 10.48550/arXiv.2204.08322
   Lang N, 2022, REMOTE SENS ENVIRON, V268, DOI 10.1016/j.rse.2021.112760
   Li B, 2018, PATTERN RECOGN, V83, P328, DOI 10.1016/j.patcog.2018.05.029
   Li W, 2020, INT J APPL EARTH OBS, V92, DOI 10.1016/j.jag.2020.102163
   Liu S., 2023, In Review, DOI [10.21203/rs.3.rs- 2573442/v1, DOI 10.21203/RS.3.RS-2573442/V1]
   Luo WJ, 2016, ADV NEUR IN, V29
   Luyssaert S, 2008, NATURE, V455, P213, DOI 10.1038/nature07276
   Maioli V, 2020, Historia Ambiental Latinoamericana y Caribena (HALAC) revista de la Solcha, V10, P46, DOI [DOI 10.32991/2237, 10.32991/2237-]
   Mapzen, 2017, Amazon. Terrain Tiles on AWS
   Markus T, 2017, REMOTE SENS ENVIRON, V190, P260, DOI 10.1016/j.rse.2016.12.029
   Maxwell AE, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13132591
   Miangoleh S. Mahdi H., 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), P9680, DOI 10.1109/CVPR46437.2021.00956
   Mugabowindekwe M, 2023, NAT CLIM CHANGE, V13, P91, DOI 10.1038/s41558-022-01544-w
   National Ecological Observatory Network (NEON), 2022, Ecosystem Structure (dp3.30015.001)
   Olofsson P, 2014, REMOTE SENS ENVIRON, V148, P42, DOI 10.1016/j.rse.2014.02.015
   Oquab M, 2024, Arxiv, DOI arXiv:2304.07193
   Popkin G, 2015, NATURE, V523, P20, DOI 10.1038/523020a
   Potapov P, 2021, REMOTE SENS ENVIRON, V253, DOI 10.1016/j.rse.2020.112165
   Ranftl R, 2021, 2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021), P12159, DOI 10.1109/ICCV48922.2021.01196
   Reed CJ, 2023, Arxiv, DOI arXiv:2212.14532
   Reytar K., 2020, Unasylva (English ed.), V71, P62
   Ribeiro MC., 2011, Biodiversity hotspots, P405, DOI [DOI 10.1007/978-3-642-20992-521, 10.1007/978-3-642-20992-521]
   Ronneberger O, 2015, LECT NOTES COMPUT SC, V9351, P234, DOI 10.1007/978-3-319-24574-4_28
   Schacher A, 2023, REMOTE SENS-BASEL, V15, DOI 10.3390/rs15051407
   Schwartz M, 2022, Arxiv, DOI [arXiv:2212.10265, 10.4855 0/ARXIV.2212.10265, DOI 10.48550/ARXIV.2212.10265]
   Silva CA, 2021, REMOTE SENS ENVIRON, V253, DOI 10.1016/j.rse.2020.112234
   Singh Mannat, 2022, CVPR
   Sirko W, 2021, Arxiv, DOI [arXiv:2107.12283, 10.48550/arXiv.2107.12283, DOI 10.48550/ARXIV.2107.12283]
   Skole DL, 2021, FORESTS, V12, DOI 10.3390/f12121652
   Stehman SV, 2014, INT J REMOTE SENS, V35, P4923, DOI 10.1080/01431161.2014.930207
   Stephenson NL, 2014, NATURE, V507, P90, DOI 10.1038/nature12914
   Tesfay F., 2022, Int. J. For. Res, V1, P4729336, DOI DOI 10.1155/2022/4729336
   University of California Santa Barbara, 2021, OpenTopo
   Vallauri Daniel, 2005, P150, DOI 10.1007/0-387-29112-1_21
   Viani RAG, 2018, TROP CONSERV SCI, V11, DOI [10.1177/1940082918790222, 10.1177/1940082918780916]
   Wagner F.H., 2023, arXiv
   Wang W, 2022, IEEE GEOSCI REMOTE S, V19, DOI 10.1109/LGRS.2022.3187135
   Weinstein B, 2021, PLOS COMPUT BIOL, V17, DOI 10.1371/journal.pcbi.1009180
   Xu ZY, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13183585
   Yanai RD, 2020, ENVIRON RES LETT, V15, DOI 10.1088/1748-9326/abb96f
   Zhang Z., 2017, arXiv, DOI DOI 10.48550/ARXIV.1711.10684
NR 69
TC 31
Z9 31
U1 32
U2 52
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 JAN 1
PY 2024
VL 300
AR 113888
DI 10.1016/j.rse.2023.113888
EA NOV 2023
PG 22
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 Z1PL4
UT WOS:001109870700001
OA Green Submitted, hybrid
DA 2025-01-10
ER

PT J
AU Ferranti, E
   Cook, S
   Greenham, SV
   Grayson, N
   Futcher, J
   Salter, K
AF Ferranti, Emma
   Cook, Samuel
   Greenham, Sarah Victoria
   Grayson, Nick
   Futcher, Julie
   Salter, Kat
TI Incorporating Heat Vulnerability into Local Authority Decision Making:
   An Open Access Approach
SO SUSTAINABILITY
LA English
DT Article
DE climate adaptation; climate resilience; heat-risk management, Nature
   Based Solutions, Action Research
ID URBAN HEAT; OVERHEATING RISK; CLIMATE-CHANGE; ISLAND; SURFACE;
   TEMPERATURE; BIRMINGHAM; GEOMETRY; IMPACT; AREAS
AB High temperatures and heatwaves are becoming more frequent, but heat vulnerability is rarely considered within local authority city design and statutory land-use planning processes. Here, we describe an approach to assess heat vulnerability in Birmingham, the second largest city in the UK. The approach uses open access data and GIS techniques that are available for built environment practitioners. Heat vulnerability is assessed by combining four datasets: surface temperatures, Local Climate Zones, green space, and Indices of Multiple Deprivation. The assessment shows that central and eastern areas of Birmingham that have the most compact urban form, least green space, and highest levels of deprivation are most vulnerable to heat. We evaluated the approach against previous climate research, examined the approach and datasets at the local scale, and described how heat vulnerability can be (and is being) incorporated into decision making. This project combines three key innovations: (1) the decision-centric process that focuses the method on the decision that needs to be made, minimizing inertia related to scientific or modeling uncertainty and reducing resource-intensity; (2) the co-creation process with Birmingham City Council, who have statutory powers for planning within the city, thereby ensuring that heat vulnerability is embedded within decisions on the suitability, design, and location of sites for future development; and (3) the open access and technically appropriate methodology which can be applied to any urban area in the UK, using the open access datasets described here, or globally, using locally applicable data sources.
C1 [Ferranti, Emma; Cook, Samuel] Univ Birmingham, Sch Engn, Birmingham B15 2TT, England.
   [Greenham, Sarah Victoria; Salter, Kat] Univ Birmingham, Sch Geog Earth & Environm Sci, Birmingham B15 2TT, England.
   [Grayson, Nick] Birmingham City Council, Birmingham B1 1BB, England.
   [Futcher, Julie] Anglia Ruskin Univ, Sch Engn & Built Environm, Cambridge CB1 1PT, England.
C3 University of Birmingham; University of Birmingham; Anglia Ruskin
   University
RP Ferranti, E (corresponding author), Univ Birmingham, Sch Engn, Birmingham B15 2TT, England.; Greenham, SV (corresponding author), Univ Birmingham, Sch Geog Earth & Environm Sci, Birmingham B15 2TT, England.
EM e.ferranti@bham.ac.uk; s.greenham@bham.ac.uk
RI Salter, Kat/HOH-4462-2023
OI Greenham, Sarah/0000-0001-7505-5645; Salter, Kat/0000-0002-5982-9054;
   Ferranti, Emma/0000-0002-0494-5349
FU Engineering and Physical Sciences Research Council [EP/R007365/1];
   Natural Environment Research Council [NE/S003487/1]; University of
   Birmingham
FX This research was funded by an Engineering and Physical Sciences
   Research Council awarded to Ferranti: EP/R007365/1. Greenham
   acknowledges funding from Natural Environment Research Council:
   NE/S003487/1. The APC was funded by University of Birmingham.
CR Adaptation Research Alliance, 2021, Adaptation Research for Impact Principles
   Allen SK, 2018, ENVIRON SCI POLICY, V87, P1, DOI 10.1016/j.envsci.2018.05.013
   [Anonymous], 2012, The UK Climate Change Risk Assessment 2012 Evidence Report
   [Anonymous], 2023, Blue Sky National Tree Map
   [Anonymous], 2014, Biophilic Cities
   [Anonymous], 2023, MHCLG 2023. National Planning Policy Framework
   [Anonymous], 2017, CIBSE TM59 Design Methodology for the Assessment of Overheating Risk in Homes
   [Anonymous], 2021, Treeconomics 2021. Birminghams Urban Forest Master Plan
   Armson D, 2012, URBAN FOR URBAN GREE, V11, P245, DOI 10.1016/j.ufug.2012.05.002
   Azam MG, 2022, MITIG ADAPT STRAT GL, V27, DOI 10.1007/s11027-022-10013-w
   Azevedo JA, 2016, REMOTE SENS-BASEL, V8, DOI 10.3390/rs8020153
   Bassett R., 2015, The Urban Climatic Map: A Methodology for Sustainable Urban Planning, P252, DOI [10.4324/9781315717616, DOI 10.4324/9781315717616]
   Bassett R, 2017, Q J ROY METEOR SOC, V143, P2016, DOI 10.1002/qj.3062
   Birmingham City Council, 2022, Environmental Justice Map
   Birmingham City Council, 2022, City of Nature Plan-February 2022
   Birmingham City Council, 2019, Deprivation in Birmingham'
   Birmingham City Council, 2022, Our Future Birmingham City Plan. Birmingham Local Plan Issues and Options
   Birmingham City Council, 2020, Birmingham earns prestigious Tree Cities of the World status
   Bohnenstengel SI, 2014, Q J ROY METEOR SOC, V140, P687, DOI 10.1002/qj.2144
   Chapman L, 2015, B AM METEOROL SOC, V96, P1545, DOI 10.1175/BAMS-D-13-00193.1
   Chapman L, 2013, URBAN CLIM, V3, P7, DOI 10.1016/j.uclim.2013.04.001
   Chen L, 2012, INT J CLIMATOL, V32, P121, DOI 10.1002/joc.2243
   CIBSE, 2013, ABOUT US
   Climate Change Committee COP26, 2021, Key Outcomes and Next Steps for the UK
   Cutter SL, 2003, SOC SCI QUART, V84, P242, DOI 10.1111/1540-6237.8402002
   Demuzere M., 2022, Zenodo
   Demuzere M, 2022, EARTH SYST SCI DATA, V14, P3835, DOI 10.5194/essd-14-3835-2022
   Elliott H, 2020, BUILDINGS-BASEL, V10, DOI 10.3390/buildings10120219
   EMU, 2022, EMU Analytics Building Heights
   ENVI-met, 2023, ENVI-met Software
   Environment Agency, 2023, National LIDAR Programme
   Environmental Audit Committee, 2018, Environmental Audit
   Estoque RC, 2017, SCI TOTAL ENVIRON, V577, P349, DOI 10.1016/j.scitotenv.2016.10.195
   Feng JL, 2021, INT J CLIMATOL, V41, pE445, DOI 10.1002/joc.6697
   Feng JL, 2019, Q J ROY METEOR SOC, V145, P3284, DOI 10.1002/qj.3619
   Ferranti E.J.S., 2021, A Trees and Design Action Group (TDAG) Guidance Document, DOI [10.25500/epapers.bham.00003452, DOI 10.25500/EPAPERS.BHAM.00003452]
   Ferranti E, 2018, METEOROL APPL, V25, P195, DOI 10.1002/met.1681
   Ferranti EJS, 2022, PROC INST CIV ENG-U, V175, P103, DOI 10.1680/jurdp.21.00006a
   Fischer EM, 2010, NAT GEOSCI, V3, P398, DOI 10.1038/NGEO866
   Gago EJ, 2013, RENEW SUST ENERG REV, V25, P749, DOI 10.1016/j.rser.2013.05.057
   Gamero-Salinas JC, 2020, BUILD ENVIRON, V171, DOI 10.1016/j.buildenv.2020.106664
   GHA Overheating in New Homes, 2019, GHA-Overheating-in-New-Homes-Tool-and-Guidance
   Greater London Authority, 2021, Urban Greening Factor. London Plan Guidance (LPG)
   Greater London Authority, 2022, Report prepared for the Greater London Authority by Bloomberg Assosciates
   Greenham S.V., 2023, Mapping Climate Risk and Vulnerability with Publicly Available Data. A Guidance Document Produced by the WM-Air Project, University of Birmingham
   Grifoni RC, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14020688
   Hart M, 2009, THEOR APPL CLIMATOL, V95, P397, DOI 10.1007/s00704-008-0017-5
   Heaviside C, 2015, Q J ROY METEOR SOC, V141, P1429, DOI 10.1002/qj.2452
   Heaviside C, 2016, ENVIRON HEALTH-GLOB, V15, DOI 10.1186/s12940-016-0100-9
   Hollis D, 2018, CTR ENV DATA ANAL
   Jaroszweski D., 2021, The Third UK Climate Change Risk Assessment Technical Report
   Jaroszweski D, 2015, METEOROL APPL, V22, P470, DOI 10.1002/met.1477
   Jones A, 2009, PREV MED, V49, P500, DOI 10.1016/j.ypmed.2009.10.012
   Kappou S, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14095159
   Kendon M., 2022, UNPRECEDENTED EXTREM
   Kendon M, 2020, INT J CLIMATOL, V40, DOI 10.1002/joc.6726
   Kim HG, 2016, NAT HAZARDS, V81, P1683, DOI 10.1007/s11069-016-2151-1
   Klinsky S, 2020, BUILD CITIES, V1, P412, DOI 10.5334/bc.65
   Leis JL, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12166458
   Liu ZX, 2021, BUILD ENVIRON, V200, DOI 10.1016/j.buildenv.2021.107939
   Macintyre HL, 2018, SCI TOTAL ENVIRON, V610, P678, DOI 10.1016/j.scitotenv.2017.08.062
   Maragno D, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12031056
   Mavrogianni A, 2017, BUILD RES INF, V45, P119, DOI 10.1080/09613218.2016.1208431
   Mears M, 2019, GEOFORUM, V103, P126, DOI 10.1016/j.geoforum.2019.04.016
   Met Office, 2022, A Milestone in UK Climate History
   Mohajerani A, 2017, J ENVIRON MANAGE, V197, P522, DOI 10.1016/j.jenvman.2017.03.095
   Monteiro MV H. P, 2019, FOR RES
   Moss JL, 2019, URBAN FOR URBAN GREE, V37, P65, DOI 10.1016/j.ufug.2018.07.023
   Murage P, 2020, ENVIRON INT, V134, DOI 10.1016/j.envint.2019.105292
   National Statistics, 2019, ENGLISH INDICES DEPR
   Negev M, 2020, BMJ-BRIT MED J, V371, DOI 10.1136/bmj.m3000
   Oikonomou E, 2012, BUILD ENVIRON, V57, P223, DOI 10.1016/j.buildenv.2012.04.002
   Oke T. R., 2017, Urban Climates, DOI [10.1017/9781139016476, DOI 10.1017/9781139016476]
   OKE TR, 1981, J CLIMATOL, V1, P237, DOI 10.1002/joc.3370010304
   Opach T, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12031179
   Ordnance Survey, 2023, MasterMap Greenspace
   Ordnance Survey, 2023, OS MasterMap Building Height Attribute
   Ordnance Survey, 2023, OS Open Greenspace
   Ozarisoy B, 2019, ENERG BUILDINGS, V187, P201, DOI 10.1016/j.enbuild.2019.01.030
   Phelan PE, 2015, ANNU REV ENV RESOUR, V40, P285, DOI 10.1146/annurev-environ-102014-021155
   Potts D.A., 2023, Environ. Sci. Policy
   Rahman MA, 2020, BUILD ENVIRON, V170, DOI 10.1016/j.buildenv.2019.106606
   Ranger N, 2013, EURO J DECIS PROCESS, V1, P233, DOI 10.1007/s40070-013-0014-5
   Ridgley H., 2020, Improving access to greenspace: A new review for 2020
   Santamouris M, 2020, ENERG BUILDINGS, V207, DOI 10.1016/j.enbuild.2019.109482
   Sayigh A., 2022, Achieving Building Comfort by Natural Means, DOI [10.1007/978-3-031-04714-5, DOI 10.1007/978-3-031-04714-5]
   SIMD, 2020, Scottish Index of Multiple Deprivation 2020
   Stewart ID, 2012, B AM METEOROL SOC, V93, P1879, DOI 10.1175/BAMS-D-11-00019.1
   Tiwari A, 2021, ENVIRON POLLUT, V274, DOI 10.1016/j.envpol.2020.115898
   Tomlinson CJ, 2013, WEATHER, V68, P44, DOI 10.1002/wea.1998
   Tomlinson CJ, 2012, INT J CLIMATOL, V32, P214, DOI 10.1002/joc.2261
   Treeplotter, 2023, Tree Mapping Software Suite for Birmingham
   UKCP18, 2023, UK Climate Projections User Interface
   Unger J, 2004, CLIM RES, V27, P253, DOI 10.3354/cr027253
   Warren EL, 2016, SCI DATA, V3, DOI 10.1038/sdata.2016.38
   Wong NH, 2021, NAT REV EARTH ENV, V2, P166, DOI 10.1038/s43017-020-00129-5
   Yang XY, 2017, INT J CLIMATOL, V37, P890, DOI 10.1002/joc.4747
   Yu JS, 2021, ENVIRON HEALTH-GLOB, V20, DOI 10.1186/s12940-021-00708-z
   Yuan B, 2021, J ENVIRON MANAGE, V295, DOI 10.1016/j.jenvman.2021.113116
   Zhao JC, 2020, LANDSCAPE URBAN PLAN, V204, DOI 10.1016/j.landurbplan.2020.103927
NR 100
TC 2
Z9 2
U1 5
U2 7
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD SEP
PY 2023
VL 15
IS 18
AR 13501
DI 10.3390/su151813501
PG 23
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 FM1X3
UT WOS:001146134200001
OA gold
DA 2025-01-10
ER

PT J
AU Messina, T
   Figueira, R
   Santos, JML
AF Messina, Tainan
   Figueira, Rui
   Santos, Jose M. L.
TI Integrating local and ecological knowledge to assess the benefits of
   trees for ecosystem services: A holistic process-based methodology
SO ECOSYSTEM SERVICES
LA English
DT Article
DE Avifauna; Bird guilds; Annual crops; Pest control services; Food systems
   resilience
ID INSECTIVOROUS BIRDS; PEST-CONTROL; BIODIVERSITY; PREDATION; FARMLAND;
   OAK
AB Management decisions in agriculture regarding landscape structure, biodiversity conservation, food production, climate adaptation and other planetary issues need to be supported by sound data and innovative solutions. The food system can and must become a part of the solution, particularly if it integrates nature-based solutions promoting biodiversity as services, such as pest control provided by local birds. Birds have been shown to contribute to invertebrates' predation and pest control, among many ecosystem services, in agricultural landscapes, especially where trees are present. Trees are also services providers and can contribute to ecosystem regulation, shelter and foraging of species, among other important contributions. In this study, we developed a methodology that integrates species, trait, and crop data; pest predation indicators and local farmers' expertise, to determine the consumption of pests by birds, in intensive farming systems of Central Portugal. Our aim was to investigate the relationship between birds and service provision over a tree gradient, at the landscape level. For that, we used point count data to estimate the daily consumption of invertebrates by birds, based on energy requirements and life cycle characteristics of each species. Using species guilds, we related habitat requirements to pest control services, which showed higher predation in annual crops close to trees or woody vegetation compared to the ones with just crops. Further, we analysed the methodology's main challenges and strengths. Lastly, we concluded that the holistic characteristic of the developed process would guide stakeholders and policy' elaboration more effectively, as we have learnt that farmers' participation enabled more accurate analysis and results and could bring them closer to the research process.
C1 [Messina, Tainan; Santos, Jose M. L.] Univ Lisbon, Ctr Forest Studies, Associated Lab TERRA, Inst Super Agron, P-1349017 Lisbon, Portugal.
   [Figueira, Rui] Univ Lisbon, Lab Associado, Inst Super Agron, CIBIO InBio,Ctr Investigaca Biodiversidade & Recur, P-1349017 Lisbon, Portugal.
   [Figueira, Rui] Univ Porto, Ctr Investigaca Biodiversidade & Recursos Genet, CIBIO InBio, Lab Associado, Campus Agr Vairao, P-4485661 Vairao, Portugal.
C3 Universidade de Lisboa; Universidade de Lisboa; Universidade do Porto
RP Messina, T (corresponding author), Univ Lisbon, Ctr Forest Studies, Associated Lab TERRA, Inst Super Agron, P-1349017 Lisbon, Portugal.
EM tmessina@campus.ul.pt
RI Figueira, Rui/C-4977-2009
OI Figueira, Rui/0000-0002-8351-4028
FU Higher Institute of Agronomy, University of Lisbon
   [PTDC/ASP-AGR/29771/2017]; Portuguese Science and Technology Institute
   (FCT)
FX We are very thankful for the participation of landowners and farmers who
   have helped with data validation and as important sources of knowledge;
   the Optimus Prime Project for making the collection of this data
   possible by funding this research; Professor Jose & nbsp;Carlos Franco
   for the help with ideas and taxonomy doubts regarding pests. This work
   was supported by the Higher Institute of Agronomy, University of Lisbon,
   under the project: Optimus Prime project (PTDC/ASP-AGR/29771/2017) ,
   funded by the Portuguese Science and Technology Institute (FCT) . The
   project aims to investigate the ecological benefits provided by the
   ecological focus areas of farmland areas, in order to provide guidelines
   aiming to increment benefits to ecosystem services and farmland
   producers.
CR [Anonymous], GBIF Backbone Taxonomy, DOI DOI 10.15468/39OMEI
   Barbaro L, 2017, J APPL ECOL, V54, P500, DOI 10.1111/1365-2664.12740
   Barrios Edmundo, 2018, International Journal of Biodiversity Science Ecosystem Services & Management, V14, P1, DOI 10.1080/21513732.2017.1399167
   Belkacem A. B., 2015, 22 BEN C ZOOL ROYAL
   Block William M., 1993, Current Ornithology, V11, P35
   Brondizio ES, 2019, Global assessment report on biodiversity and ecosystem services, DOI [10.5281/zenodo.3831673, DOI 10.5281/ZENODO.3831673]
   Campedelli T, 2018, J NAT CONSERV, V46, P66, DOI 10.1016/j.jnc.2018.09.002
   Commission E., 2019, DIR AGR RURAL, P1
   de Snoo GR, 2013, CONSERV LETT, V6, P66, DOI 10.1111/j.1755-263X.2012.00296.x
   DEFRA, 2002, PN0908 DEFRA
   DGAV, 2020, DGAV MED PROD VET FL
   EP IPM, 2009, DIR 2009 128 EC EUR, P71
   eur-lex, DIRECTIVE 2009 147 E
   Gaglio M, 2019, ECOL MODEL, V403, P23, DOI 10.1016/j.ecolmodel.2019.04.019
   García D, 2018, AGR ECOSYST ENVIRON, V254, P233, DOI 10.1016/j.agee.2017.11.034
   Gaston KJ, 2018, BIOSCIENCE, V68, P264, DOI 10.1093/biosci/biy005
   Grashof-Bokdam CJ, 2005, LANDSCAPE ECOL, V20, P417, DOI 10.1007/s10980-004-5646-1
   Green RE, 2005, SCIENCE, V307, P550, DOI 10.1126/science.1106049
   Haines-Young R., 2010, Ecosystem Ecology: a new synthesis, P110, DOI [10.1017/CBO9780511750458.007, DOI 10.1017/CBO9780511750458.007]
   Herren H.R., 2021, RETHINKING FOOD AGR, P149
   Kolkert HL, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-84633-8
   Kremen C, 2018, SCIENCE, V362, DOI 10.1126/science.aau6020
   Maas B, 2015, J APPL ECOL, V52, P735, DOI 10.1111/1365-2664.12409
   MARQUIS RJ, 1994, ECOLOGY, V75, P2007, DOI 10.2307/1941605
   Milligan MC, 2016, BIOL CONSERV, V194, P58, DOI 10.1016/j.biocon.2015.11.028
   Nyffeler M, 2018, SCI NAT-HEIDELBERG, V105, DOI 10.1007/s00114-018-1571-z
   Optimus Prime Project, 2022, METH REP PREP FIELD
   Optimus Prime Project, 2022, FIN REP OPT PRIM PRO, DOI [10.17605/OSF.IO/2WHZY, DOI 10.17605/OSF.IO/2WHZY]
   Park CR, 2008, ECOL RES, V23, P1015, DOI 10.1007/s11284-008-0469-1
   Philpott SM, 2009, ECOL APPL, V19, P1858, DOI 10.1890/08-1928.1
   Potschin MB, 2011, PROG PHYS GEOG, V35, P575, DOI 10.1177/0309133311423172
   REGANOLD JP, 1990, SCI AM, V262, P112, DOI 10.1038/scientificamerican0690-112
   Ricklefs R. E., 1969, Smithsonian Contributions to Zoology, V9, P1, DOI [DOI 10.5479/SI.00810282.9, 10.5479/si.00810282.9]
   Robinson RA, 2002, J APPL ECOL, V39, P157, DOI 10.1046/j.1365-2664.2002.00695.x
   Storchová L, 2018, GLOBAL ECOL BIOGEOGR, V27, P400, DOI 10.1111/geb.12709
   Tela M, 2021, PLOS ONE, V16, DOI 10.1371/journal.pone.0255638
   the scikit-bio development team, 2020, scikit-bio: A Bioinformatics Library for Data Scientists, Students, and Developers
   Tscharntke T, 2005, ECOL LETT, V8, P857, DOI 10.1111/j.1461-0248.2005.00782.x
   Whelan CJ, 2015, J ORNITHOL, V156, pS227, DOI 10.1007/s10336-015-1229-y
NR 39
TC 2
Z9 2
U1 1
U2 17
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2212-0416
J9 ECOSYST SERV
JI Ecosyst. Serv.
PD OCT
PY 2023
VL 63
AR 101556
DI 10.1016/j.ecoser.2023.101556
EA AUG 2023
PG 10
WC Ecology; Environmental Sciences; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA S1TX8
UT WOS:001069077200001
OA hybrid
DA 2025-01-10
ER

PT J
AU Zhang, Y
   Xu, H
   Wang, Z
   Jie, HL
   Gao, FC
   Cai, MQ
   Wang, K
   Chen, DF
   Guo, R
   Lin, ZG
   Niu, QS
   Ji, T
AF Zhang, Yi
   Xu, Hao
   Wang, Zhi
   Jie, Haoliang
   Gao, Fuchao
   Cai, Minqi
   Wang, Kang
   Chen, Dafu
   Guo, Rui
   Lin, Zheguang
   Niu, Qingsheng
   Ji, Ting
TI A key gene for the climatic adaptation of <i>Apis cerana</i> populations
   in China according to selective sweep analysis
SO BMC GENOMICS
LA English
DT Article
DE Apis cerana; Adaptive radiation distribution; Climate change; Population
   genomics; Selective sweep analysis
ID GENOMIC ANALYSES; CELL-GROWTH; HISTORY; DIVERSITY; EXTINCTION; REVEAL
AB BackgroundApis cerana is widely distributed in China and, prior to the introduction of western honeybees, was the only bee species kept in China. During the long-term natural evolutionary process, many unique phenotypic variations have occurred among A. cerana populations in different geographical regions under varied climates. Understanding the molecular genetic basis and the effects of climate change on the adaptive evolution of A. cerana can promote A. cerana conservation in face of climate change and allow for the effective utilization of its genetic resources.ResultTo investigate the genetic basis of phenotypic variations and the impact of climate change on adaptive evolution, A. cerana workers from 100 colonies located at similar geographical latitudes or longitudes were analyzed. Our results revealed an important relationship between climate types and the genetic variation of A. cerana in China, and a greater influence of latitude compared with longitude was observed. Upon selection and morphometry analyses combination for populations under different climate types, we identified a key gene RAPTOR, which was deeply involved in developmental processes and influenced the body size.ConclusionThe selection of RAPTOR at the genomic level during adaptive evolution could allow A. cerana to actively regulate its metabolism, thereby fine-tuning body sizes in response to harsh conditions caused by climate change, such as food shortages and extreme temperatures, which may partially elucidate the size differences of A. cerana populations. This study provides crucial support for the molecular genetic basis of the expansion and evolution of naturally distributed honeybee populations.
C1 [Zhang, Yi; Cai, Minqi; Wang, Kang; Lin, Zheguang; Ji, Ting] Yangzhou Univ, Coll Anim Sci & Technol, Jiangsu 225009, Peoples R China.
   [Xu, Hao] Anhui Acad Agr Sci, Sericultural Res Inst, Hefei 230061, Peoples R China.
   [Wang, Zhi; Niu, Qingsheng] Apiculture Sci Inst Jilin Prov, Jilin 132108, Peoples R China.
   [Jie, Haoliang] Jinzhong Agr & Rural Affairs Bur, Jinzhong 030601, Peoples R China.
   [Gao, Fuchao] Heilongjiang Acad Agr Sci, Mudanjiang Branch, Mudanjiang 157043, Peoples R China.
   [Chen, Dafu; Guo, Rui] Fujian Agr & Forestry Univ, Coll Anim Sci, Coll Bee Sci, Fuzhou 350002, Peoples R China.
C3 Yangzhou University; Anhui Academy of Agricultural Sciences;
   Heilongjiang Academy of Agricultural Sciences; Fujian Agriculture &
   Forestry University
RP Ji, T (corresponding author), Yangzhou Univ, Coll Anim Sci & Technol, Jiangsu 225009, Peoples R China.; Niu, QS (corresponding author), Apiculture Sci Inst Jilin Prov, Jilin 132108, Peoples R China.
EM 1463199779@qq.com; tji@yzu.edu.cn
RI Lin, Zheguang/HLG-7875-2023
OI Lin, Zheguang/0000-0003-4270-9360
CR Alexander DH, 2009, GENOME RES, V19, P1655, DOI 10.1101/gr.094052.109
   Barrett JC, 2005, BIOINFORMATICS, V21, P263, DOI 10.1093/bioinformatics/bth457
   Batchelor CL, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-11601-2
   Boggs CL, 2016, CURR OPIN INSECT SCI, V17, P69, DOI 10.1016/j.cois.2016.07.004
   Cardoen D, 2011, MOL ECOL, V20, P4070, DOI 10.1111/j.1365-294X.2011.05254.x
   Chen C, 2018, MOL BIOL EVOL, V35, P2260, DOI 10.1093/molbev/msy130
   Chen C, 2016, MOL BIOL EVOL, V33, P1337, DOI 10.1093/molbev/msw017
   Chen H, 2021, J PROTEOME RES, V20, P2240, DOI 10.1021/acs.jproteome.0c00776
   Chen X, 2012, INSECT BIOCHEM MOLEC, V42, P665, DOI 10.1016/j.ibmb.2012.05.004
   Clark PU, 2009, SCIENCE, V325, P710, DOI 10.1126/science.1172873
   Cleland EE, 2007, TRENDS ECOL EVOL, V22, P357, DOI 10.1016/j.tree.2007.04.003
   Corby-Harris V, 2019, J INSECT PHYSIOL, V116, P1, DOI 10.1016/j.jinsphys.2019.04.001
   Corona M, 2016, CURR OPIN INSECT SCI, V13, P55, DOI 10.1016/j.cois.2015.12.003
   Diao QY, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-017-17338-6
   Diniz JAF, 2013, GENET MOL BIOL, V36, P475, DOI 10.1590/S1415-47572013000400002
   Duran A, 2011, MOL CELL, V44, P134, DOI 10.1016/j.molcel.2011.06.038
   Garcia RA, 2014, SCIENCE, V344, P486, DOI 10.1126/science.1247579
   Géminard C, 2009, CELL METAB, V10, P199, DOI 10.1016/j.cmet.2009.08.002
   Guertin DA, 2006, CURR BIOL, V16, P958, DOI 10.1016/j.cub.2006.03.084
   Hallmann CA, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0185809
   Halsch CA, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2002543117
   Harris JE, 2019, BIOL CONSERV, V240, DOI 10.1016/j.biocon.2019.108219
   Hoffmann AA, 2011, NATURE, V470, P479, DOI 10.1038/nature09670
   HUDSON RR, 1992, GENETICS, V132, P583
   Ilyasov RA, 2019, J APIC SCI, V63, P289, DOI [10.2478/jas-2019-0024, 10.2478/JAS-2019-0024]
   Ilyasov RA, 2018, J APIC SCI, V62, P189, DOI [10.2478/jas-2018-0018, 10.2478/JAS-2018-0018]
   Ji YK, 2020, SCI ADV, V6, DOI 10.1126/sciadv.abd3590
   Jones JC, 2004, SCIENCE, V305, P402, DOI 10.1126/science.1096340
   Lan L, 2021, INSECTS, V12, DOI 10.3390/insects12100891
   Layalle S, 2008, DEV CELL, V15, P568, DOI 10.1016/j.devcel.2008.08.003
   Lee G, 2007, BIOCHEM BIOPH RES CO, V357, P1154, DOI 10.1016/j.bbrc.2007.04.086
   Li H, 2009, BIOINFORMATICS, V25, P1754, DOI 10.1093/bioinformatics/btp324
   Lin T, 2014, NAT GENET, V46, P1220, DOI 10.1038/ng.3117
   Liu NN, 2022, BMC GENOMICS, V23, DOI 10.1186/s12864-022-08298-x
   Mattila HR, 2007, SCIENCE, V317, P362, DOI 10.1126/science.1143046
   McKenna A, 2010, GENOME RES, V20, P1297, DOI 10.1101/gr.107524.110
   Mihaylova MM, 2011, NAT CELL BIOL, V13, P1016, DOI 10.1038/ncb2329
   Mutti NS, 2011, J EXP BIOL, V214, P3977, DOI 10.1242/jeb.061499
   Oldroyd BP, 2007, TRENDS ECOL EVOL, V22, P408, DOI 10.1016/j.tree.2007.06.001
   Park D, 2015, BMC GENOMICS, V16, DOI 10.1186/1471-2164-16-1
   Patel A, 2007, PLOS ONE, V2, DOI 10.1371/journal.pone.0000509
   Pfeifer B, 2014, MOL BIOL EVOL, V31, P1929, DOI 10.1093/molbev/msu136
   Purcell S, 2007, AM J HUM GENET, V81, P559, DOI 10.1086/519795
   Román-Palacios C, 2020, P NATL ACAD SCI USA, V117, P4211, DOI 10.1073/pnas.1913007117
   Ronai I, 2016, ADV STUD BEHAV, V48, P251, DOI 10.1016/bs.asb.2016.03.002
   Salcido DM, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-019-57226-9
   Scheffers BR, 2016, SCIENCE, V354, DOI 10.1126/science.aaf7671
   Shi P, 2020, ECOL EVOL, V10, P13427, DOI 10.1002/ece3.6946
   Soroye P, 2020, SCIENCE, V367, P685, DOI 10.1126/science.aax8591
   Szlachcic E, 2021, BIOLOGY-BASEL, V10, DOI 10.3390/biology10090861
   Takáts S, 2015, AUTOPHAGY, V11, P1209, DOI 10.1080/15548627.2015.1059559
   Telonis-Scott M, 2009, J INSECT PHYSIOL, V55, P549, DOI 10.1016/j.jinsphys.2009.01.010
   Terhorst J, 2017, NAT GENET, V49, P303, DOI 10.1038/ng.3748
   Urban MC, 2015, SCIENCE, V348, P571, DOI 10.1126/science.aaa4984
   van der Zee R, 2012, J APICULT RES, V51, P91, DOI 10.3896/IBRA.1.51.1.12
   Vilella AJ, 2009, GENOME RES, V19, P327, DOI 10.1101/gr.073585.107
   Wallberg A, 2017, PLOS GENET, V13, DOI 10.1371/journal.pgen.1006792
   Wallberg A, 2016, PLOS GENET, V12, DOI 10.1371/journal.pgen.1006097
   Wallberg A, 2014, NAT GENET, V46, P1081, DOI 10.1038/ng.3077
   Wang K, 2010, NUCLEIC ACIDS RES, V38, DOI 10.1093/nar/gkq603
   Wang ZL, 2020, FRONT GENET, V11, DOI 10.3389/fgene.2020.00279
   Warren R, 2018, SCIENCE, V360, P791, DOI 10.1126/science.aar3646
   Wei Y, 2014, CELL DEATH DIFFER, V21, P1460, DOI 10.1038/cdd.2014.63
   Wheeler DE, 2014, INSECT MOL BIOL, V23, P113, DOI 10.1111/imb.12065
   Xu K, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0179922
   Yang JA, 2011, AM J HUM GENET, V88, P76, DOI 10.1016/j.ajhg.2010.11.011
NR 66
TC 1
Z9 1
U1 4
U2 26
PU BMC
PI LONDON
PA CAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND
SN 1471-2164
J9 BMC GENOMICS
JI BMC Genomics
PD MAR 6
PY 2023
VL 24
IS 1
AR 100
DI 10.1186/s12864-023-09167-x
PG 15
WC Biotechnology & Applied Microbiology; Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biotechnology & Applied Microbiology; Genetics & Heredity
GA 9O5LA
UT WOS:000943641900001
PM 36879226
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Feng, W
   Jing, WQ
   Zhen, M
   Zhang, J
   Luo, W
   Qin, ZM
AF Feng, Wei
   Jing, Wenqiang
   Zhen, Meng
   Zhang, Jin
   Luo, Wei
   Qin, Zeming
TI The difference in thermal comfort between southern and northern Chinese
   living in the Xi'an cold climate region
SO ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
LA English
DT Article
DE The cold region in China; Neutral temperature; Expected temperature;
   Regional differences; Thermal history
ID TEMPERATURE; MICROCLIMATE; ENVIRONMENTS; ADAPTATION; SPACES; MODEL;
   PERCEPTIONS; GUANGZHOU; SENSATION
AB A year-long longitudinal survey regarding perceptions of outdoor thermal conditions and thermal comfort was conducted in Xi'an, a City in a Chinese cold region. The survey included micrometeorological measurements and a longitudinal questionnaire. The thermal comfort and adaptability of southern Chinese (people from Changsha and Guangzhou) and northern Chinese (people from Xi'an) in Xi'an were studied from the three aspects of psychological, physiological, and behavioral differences. The results of similar studies in other regions were compared with those of this study. Regarding psychological differences, northerners were more adapted to Xi'an's climate than southerners, with an expected temperatures of 20.7celcius and 24.1celcius for northerners and for southerners, respectively. Regarding physiological differences, the neutral temperature of the northern population was 22.12celcius, while that of the southern population was 21.12celcius. The neutral temperature for the southern population in Xi'an is similar to that of northern people living in Xi'an. Regarding behavioral differences, northerners were more likely than southerners to maintain their thermal comfort by adjusting their clothing when they experienced a change in the outdoor environment. This study not only indicates that there were differences regarding the thermal comfort of people originating different regions but also provided support for fully explaining the mechanism of climate adaptation of human thermal comfort. In addition, this work provides basic data regarding formulating outdoor thermal comfort standards and provided data support for personalized thermal comfort.
C1 [Feng, Wei] Xi An Jiao Tong Univ, Sch Humanities & Social Sci, Xian 710049, Peoples R China.
   [Jing, Wenqiang; Zhang, Jin; Luo, Wei; Qin, Zeming] Xian Eurasia Univ, Sch Human Settlements & Civil Engn, Xian 710055, Peoples R China.
   [Zhen, Meng] Xi An Jiao Tong Univ, Sch Human Settlements & Civil Engn, Dept Architecture, Xian 710049, Peoples R China.
C3 Xi'an Jiaotong University; Xi'an Jiaotong University
RP Jing, WQ (corresponding author), Xian Eurasia Univ, Sch Human Settlements & Civil Engn, Xian 710055, Peoples R China.
EM jing_wenqiang@163.com
OI Jing, wenqiang/0000-0002-2036-5782
FU NSFC General Project [51808440]; China Postdoctoral Science Foundation
   [2021M692564]; Opening Fund of Key Laboratory of Interactive Media
   Design and Equipment Service Innovation, the Ministry of Culture and
   Tourism [20205]; Scientific Research Platform of Eurasia University
   [2022XJPT01]
FX The study was supported by the NSFC General Project (grant number
   51808440), China Postdoctoral Science Foundation (grant number
   2021M692564), and the Opening Fund of Key Laboratory of Interactive
   Media Design and Equipment Service Innovation, the Ministry of Culture
   and Tourism (grant number 20205, the "The Innovation Team of Eurasia
   University" of Xi'an Eurasia University (2021XJTD01), and the Scientific
   Research Platform of Eurasia University (2022XJPT01).
CR Aljawabra F, 2018, INT J BIOMETEOROL, V62, P1901, DOI 10.1007/s00484-018-1592-5
   [Anonymous], 2009, ASHRAE HDB FUND
   [Anonymous], 1998, ISO77261998E
   Bouden C, 2005, ENERG BUILDINGS, V37, P952, DOI 10.1016/j.enbuild.2004.12.003
   Cao B, 2012, P INDOOR AIR C
   Changsha Municipal Bureau of Statistics, 2021, CHANGSH STAT YB
   Chen X, 2018, BUILD ENVIRON, V143, P548, DOI 10.1016/j.buildenv.2018.07.041
   Cheung PK, 2018, INT J CLIMATOL, V38, P5037, DOI 10.1002/joc.5732
   Chow HW, 2017, INT J ENV RES PUB HE, V14, DOI 10.3390/ijerph14040448
   Corgnati SP, 2009, BUILD ENVIRON, V44, P785, DOI 10.1016/j.buildenv.2008.05.023
   deDear RJ, 1997, INT J BIOMETEOROL, V40, P141, DOI 10.1007/s004840050035
   Donnini G., 1997, ASHRAE T, V103, P205
   Fanger P.O., 1972, THERMAL COMFORT
   Farghal A, 2008, P C AIR CONDITIONING
   Galindo T, 2018, BUILD ENVIRON, V138, P235, DOI 10.1016/j.buildenv.2018.04.024
   Gautam B, 2020, BUILD ENVIRON, V185, DOI 10.1016/j.buildenv.2020.107237
   Guangdong Municipal Bureau of Statistics, 2022, GUANGD STAT YB
   Höppe P, 1999, INT J BIOMETEOROL, V43, P71, DOI 10.1007/s004840050118
   Kenawy I, 2021, BUILD ENVIRON, V195, DOI 10.1016/j.buildenv.2021.107746
   Lai DY, 2017, ENERG BUILDINGS, V151, P476, DOI 10.1016/j.enbuild.2017.07.009
   Lam CKC, 2021, BUILD ENVIRON, V198, DOI 10.1016/j.buildenv.2021.107877
   Lam CKC, 2021, SCI TOTAL ENVIRON, V760, DOI 10.1016/j.scitotenv.2020.144141
   Lee JY, 2013, J THERM BIOL, V38, P70, DOI 10.1016/j.jtherbio.2012.11.004
   Liu WW, 2016, ENERG BUILDINGS, V128, P190, DOI 10.1016/j.enbuild.2016.06.086
   Matzarakis A, 2007, INT J BIOMETEOROL, V51, P323, DOI 10.1007/s00484-009-0261-0
   McCullough E.a., 1985, ASHRAE Transactions, V91, P29
   Mui KWH, 2003, BUILD ENVIRON, V38, P837, DOI 10.1016/S0360-1323(03)00020-9
   Nicol JF, 1999, ENERG BUILDINGS, V30, P261, DOI 10.1016/S0378-7788(99)00011-0
   Nikolopoulou M, 2003, ENERG BUILDINGS, V35, P95, DOI 10.1016/S0378-7788(02)00084-1
   Nikolopoulou M, 2007, BUILD ENVIRON, V42, P3691, DOI 10.1016/j.buildenv.2006.09.008
   Pantavou K, 2013, BUILD ENVIRON, V66, P82, DOI 10.1016/j.buildenv.2013.02.014
   Salata F, 2017, SUSTAIN CITIES SOC, V30, P79, DOI 10.1016/j.scs.2017.01.006
   Shaanxi Provincial Bureau of Statistics, 2021, SHAANX STAT YB
   Shahi DK, 2021, BUILD ENVIRON, V191, DOI 10.1016/j.buildenv.2020.107569
   Shooshtarian S, 2016, SUSTAIN CITIES SOC, V26, P119, DOI 10.1016/j.scs.2016.06.005
   Shukuya, 2020, B ENV, V185, P107237, DOI [10.1016/j.buildenv.2020.107237, DOI 10.1016/J.BUILDENV.2020.107237]
   Taki AH, 1999, BUILD SERV ENG RES T, V20, P205
   Tao P, 1991, INDOOR AIR
   Thapa S, 2020, ENERG BUILDINGS, V213, DOI 10.1016/j.enbuild.2020.109767
   Tian Y, 2022, SCI TOTAL ENVIRON, V808, DOI 10.1016/j.scitotenv.2021.152079
   Wang YF, 2018, URBAN FOR URBAN GREE, V32, P99, DOI 10.1016/j.ufug.2018.04.005
   Wang ZJ, 2011, BUILD ENVIRON, V46, P2170, DOI 10.1016/j.buildenv.2011.04.029
   Wang ZJ, 2010, ENERG BUILDINGS, V42, P2406, DOI 10.1016/j.enbuild.2010.08.010
   Xi TY, 2020, BUILD ENVIRON, V173, DOI 10.1016/j.buildenv.2020.106757
   Xi'an Statistics Bureau, 2020, XIAN STAT YB
   Xie YX, 2018, BUILD ENVIRON, V132, P45, DOI 10.1016/j.buildenv.2018.01.025
   Yan HY, 2019, ENERG BUILDINGS, V204, DOI 10.1016/j.enbuild.2019.109475
   Yang ZM., 2022, GLOB ENV CHANG HUMAN, V2022, P74
   Yung EHK, 2019, LANDSCAPE URBAN PLAN, V185, P44, DOI 10.1016/j.landurbplan.2019.01.003
   Zheng WX, 2017, EFFECTS REGIONAL SEA
NR 50
TC 3
Z9 3
U1 3
U2 28
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 APR
PY 2023
VL 30
IS 16
BP 48062
EP 48077
DI 10.1007/s11356-023-25640-2
EA FEB 2023
PG 16
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA F2ZB7
UT WOS:000930833200012
PM 36749522
DA 2025-01-10
ER

PT J
AU Comte, V
   Schneider, L
   Calanca, P
   Zufferey, V
   Rebetez, M
AF Comte, Valentin
   Schneider, Leonard
   Calanca, Pierluigi
   Zufferey, Vivian
   Rebetez, Martine
TI Future climatic conditions may threaten adaptation capacities for
   vineyards along Lake Neuchatel, Switzerland
SO OENO ONE
LA English
DT Article
DE bioclimatic index; climate adaptation; climate change; regional climate
   model; viticulture suitability
ID MODIFIED GRAPE COMPOSITION; FROST DAMAGE; WATER STATUS; WINE;
   VITICULTURE; TEMPERATURE; REGIONS; QUALITY; TRENDS; RISK
AB In Switzerland, as elsewhere in the world, climate change is challenging viticulture. Knowledge of the potential impacts is essential for preparing adaptation measures. Two aspects directly impacted by increasing temperatures are the choice of grapevine varieties and the location of vineyards. To help address these impacts, we analysed future trends in two bioclimatic indices, average growing season temperature (GST) and Huglin's heliothermal index (HI), in the Swiss canton of Neuchatel. We conducted our analysis based on regional climate change scenarios referring to the emission pathways RCP4.5 and RCP8.5. Under the assumption of RCP8.5, trends in GST and HI indicate that the climate in this region will become too hot for most grapevine varieties currently cultivated, especially Pinot noir. Moreover, adaptation problems under RCP8.5 are expected to originate from an increase in climate extremes in both temperature and precipitation. Results based on RCP4.5 indicate a broader scope for adaptation, as the climate will remain suitable for a larger number of grapevine varieties within the current altitudinal limits of the Neuchatel vineyards. In theory, an altitudinal shift of Pinot noir would also be possible under this emission pathway. In practice, however, the possibility of establishing vineyards above 600 m would be limited by the presence of protected forests and rocky areas. Our results highlight that vineyards in this region will need important adaptation measures if anthropic greenhouse gas emissions do not decrease rapidly and considerably, limiting the global temperature increase to < 1.5 degrees C.
C1 [Comte, Valentin; Schneider, Leonard; Rebetez, Martine] Univ Neuchatel, Inst Geog, Neuchatel, Switzerland.
   [Comte, Valentin; Schneider, Leonard; Rebetez, Martine] Swiss Fed Inst Forest, Snow & Landscape Res WSL, Neuchatel, Switzerland.
   [Calanca, Pierluigi] Agroscope Reckenholz, Zurich, Switzerland.
   [Zufferey, Vivian] Agroscope Forschungszentrum, Pully, Pully, Switzerland.
C3 University of Neuchatel; Swiss Federal Institutes of Technology Domain;
   Swiss Federal Institute for Forest, Snow & Landscape Research; Swiss
   Federal Research Station Agroscope
RP Comte, V (corresponding author), Univ Neuchatel, Inst Geog, Neuchatel, Switzerland.; Comte, V (corresponding author), Swiss Fed Inst Forest, Snow & Landscape Res WSL, Neuchatel, Switzerland.
EM valentin.comte@unine.ch
OI Calanca, Pierluigi/0000-0003-3113-2885; Schneider,
   Leonard/0000-0001-5688-7745; Comte, Valentin/0000-0002-0621-9850
FU Swiss Federal Office for Agriculture; canton of Neuchatel, winegrowing
   municipalities; wine producers' associations
FX This research was funded by the Swiss Federal Office for Agriculture
   (pilot program 'Adaptation to climate change' coordinated by the Federal
   Office for the Environment), the canton of Neuchatel, winegrowing
   municipalities, and wine producers' associations. Part of the
   temperature data were provided by the National Centre for Climate
   Services, MeteoSwiss (Swiss Federal Office of Meteorology and
   Climatology) and Agrometeo by Agroscope (Swiss Center of Excellence for
   Agricultural Research). The authors are grateful to Melissa Dawes for
   her useful comments and suggestions for improving the manuscript.
CR [Anonymous], 2006, FINE WINE TERROIR GE
   [Anonymous], 2018, Technical report
   [Anonymous], 1978, Comptes Rendus de l'Academie d'Agriculture France
   Battaglini A, 2009, REG ENVIRON CHANGE, V9, P61, DOI 10.1007/s10113-008-0053-9
   Boé J, 2020, CLIM DYNAM, V54, P2981, DOI 10.1007/s00382-020-05153-1
   Bonfante A, 2017, AGR SYST, V152, P100, DOI 10.1016/j.agsy.2016.12.009
   Bonfante A, 2022, OENO ONE, V56, P375, DOI 10.20870/oeno-one.2022.56.2.5448
   Bramley RGV, 2011, AUST J GRAPE WINE R, V17, P217, DOI 10.1111/j.1755-0238.2011.00136.x
   Brillante L, 2018, J SCI FOOD AGR, V98, P691, DOI 10.1002/jsfa.8516
   Comte V, 2022, THEOR APPL CLIMATOL, V147, P423, DOI 10.1007/s00704-021-03836-1
   Cook BI, 2016, NAT CLIM CHANGE, V6, P715, DOI [10.1038/NCLIMATE2960, 10.1038/nclimate2960]
   de Orduña RM, 2010, FOOD RES INT, V43, P1844, DOI 10.1016/j.foodres.2010.05.001
   Dequin S, 2017, OENO ONE, V51, P205, DOI 10.20870/oeno-one.2016.0.0.1584
   Doutreloup S, 2022, OENO ONE, V56, P1, DOI 10.20870/oeno-one.2022.56.3.5356
   Duchêne E, 2005, AGRON SUSTAIN DEV, V25, P93, DOI 10.1051/agro:2004057
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fraga H, 2012, FOOD ENERGY SECUR, V1, P94, DOI 10.1002/fes3.14
   Fraga H, 2017, OENO ONE, V51, P61, DOI 10.20870/oeno-one.2016.0.0.1621
   Hawkins E, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2011GL050087
   Huglin P., 1998, Biologie et ecologie de la vigne
   Jones G., 2007, CLIMATE VITICULTURE
   Jones G. V., 2010, Journal of Wine Research, V21, P103, DOI 10.1080/09571264.2010.530091
   Jones G. V., 2022, MANAGING WINE QUAL, P727, DOI DOI 10.1016/B978-0-08-102067-8.00015-4
   Jones GV, 2005, CLIMATIC CHANGE, V73, P319, DOI 10.1007/s10584-005-4704-2
   KLIEWER WM, 1977, AM J ENOL VITICULT, V28, P96
   Laget F, 2008, J INT SCI VIGNE VIN, V42, P113
   Lovisolo C, 2008, NEW PHYTOL, V180, P642, DOI 10.1111/j.1469-8137.2008.02592.x
   Masson-Delmotte V., 2021, Climate Change, V3, P31, DOI DOI 10.1017/9781009157896.001
   Meinshausen M, 2011, CLIMATIC CHANGE, V109, P213, DOI 10.1007/s10584-011-0156-z
   Molitor D, 2019, OENO ONE, V53, P409, DOI 10.20870/oeno-one.2019.53.3.2329
   Morales-Castilla I, 2020, P NATL ACAD SCI USA, V117, P2864, DOI 10.1073/pnas.1906731117
   Moriondo M, 2013, CLIMATIC CHANGE, V119, P825, DOI 10.1007/s10584-013-0739-y
   Nesbitt A, 2022, OENO ONE, V56, P69, DOI 10.20870/oeno-one.2022.56.3.5398
   OIV, 2012, OIV GUID VIT ZON MET
   Quenol H., 2019, XXXIIE C INT LAIC
   R Core Team, 2022, R: A Language and Environment for Statistical Computing
   Raupach TH, 2021, NAT REV EARTH ENV, V2, P213, DOI 10.1038/s43017-020-00133-9
   Rebetez M, 2008, THEOR APPL CLIMATOL, V91, P27, DOI 10.1007/s00704-007-0296-2
   Schultz H. R., 2000, Australian Journal of Grape and Wine Research, V6, P2, DOI 10.1111/j.1755-0238.2000.tb00156.x
   Schwingshackl C, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab4949
   Sgubin G, 2018, AGR FOREST METEOROL, V250, P226, DOI 10.1016/j.agrformet.2017.12.253
   Spangenberg JE, 2018, SCI TOTAL ENVIRON, V635, P178, DOI 10.1016/j.scitotenv.2018.04.078
   Spayd SE, 2002, AM J ENOL VITICULT, V53, P171
   Stock M, 2005, ACTA HORTIC, P29, DOI 10.17660/ActaHortic.2005.689.1
   Tilloy V, 2015, INT J FOOD MICROBIOL, V213, P49, DOI 10.1016/j.ijfoodmicro.2015.06.027
   Tonietto J, 2004, AGR FOREST METEOROL, V124, P81, DOI 10.1016/j.agrformet.2003.06.001
   Unwin T., 2005, WINE VINE HIST GEOGR, DOI 10.4324/9780203013267
   Van Leeuwen C, 2009, J INT SCI VIGNE VIN, V43, P121
   Van Leeuwen Cornelis, 2006, Journal of Wine Research, V17, P1, DOI 10.1080/09571260600633135
   van Leeuwen C, 2017, OENO ONE, V51, P147, DOI 10.20870/oeno-one.2016.0.0.1647
   van Leeuwen C, 2016, J WINE ECON, V11, P150, DOI 10.1017/jwe.2015.21
   Vitasse Y, 2018, CLIMATIC CHANGE, V149, P233, DOI 10.1007/s10584-018-2234-y
   Vitasse Y, 2018, AGR FOREST METEOROL, V248, P60, DOI 10.1016/j.agrformet.2017.09.005
   Zufferey V, 2011, J EXP BOT, V62, P3885, DOI 10.1093/jxb/err081
   Zufferey V., 2022, VIGNE ANATOMIE PHYSI
   Zurbenko IG, 2018, WIRES COMPUT STAT, V10, DOI 10.1002/wics.1419
NR 56
TC 1
Z9 1
U1 0
U2 5
PU INT VITICULTURE & ENOLOGY SOC-IVES
PI VILLENAVE D ORNON
PA INST SCI VIGNE VIN-ISVV, 210 CHEMIN DE LEYSOTTE, VILLENAVE D ORNON,
   FRANCE
EI 2494-1271
J9 OENO ONE
JI OENE One
PY 2023
VL 57
IS 2
BP 85
EP 100
DI 10.20870/oeno-one.2023.57.2.7194
PG 16
WC Food Science & Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Food Science & Technology
GA P8PN5
UT WOS:001053236500007
OA gold, Green Accepted
DA 2025-01-10
ER

PT J
AU Hua, T
   Zhao, WW
   Cherubini, F
   Hu, XP
   Pereira, P
AF Hua, Ting
   Zhao, Wenwu
   Cherubini, Francesco
   Hu, Xiangping
   Pereira, Paulo
TI Strengthening protected areas for climate refugia on the Tibetan
   Plateau, China
SO BIOLOGICAL CONSERVATION
LA English
DT Article
DE Protected areas; Climate refugia; Nature reserves; Biodiversity; Tibetan
   Plateau; Conservation planning
ID VEGETATION GREEN-UP; NATURE-RESERVES; PHENOLOGY; CONSERVATION;
   BIODIVERSITY; SATELLITE; VELOCITY; BIRD; HETEROGENEITY; COMMUNITIES
AB Protected areas (PAs) are at the forefront of efforts to conserve and restore biodiversity, while climate change can risk compromising the ecological benefits of PAs. Therefore, targeting conservation and adaptation efforts necessitate a well-understand of the relationship between PAs and climate refugia, defined as the regions can buffer the impact of climate change. Recent attempts to identify climate refugia were primarily based on terrain -mediated features or climatic velocity, ignoring the ecosystem's internal processes. This work identified climate refugia on the Tibetan Plateau (TP), an amplifier of drastic global climate warming, based on environmental diversity, phenology stability and climatic velocity, highlighting the capacity to cope with extreme weather events, synchronization with plant growth cycles and future climate adaptation, respectively. The results show the distribution of climate refugia using different environmental diversity indicators (e.g., vegetation and topography) vary slightly but differs substantially from the priorities using phenology stability and climatic velocity. For instance, the high distribution probability of climate refugia derived from environmental diversity and climatic velocity is mainly concentrated at low (<3000 m) or high elevations (>6000 m), while the one using phenology stability is mainly observed at 3000 m-3800 m. The inconsistent distribution of different types of refugia weakens the potential of functional complementarity. The existing nature reserves, the primary type of PAs in China, have critical conservation gaps in different types of climate refugia, indicating the urgency of incorporating climate refugia into PAs conservation planning on TP. Our work could help inform local conser-vation policies and improve the effectiveness of PAs.
C1 [Hua, Ting; Zhao, Wenwu] Beijing Normal Univ, Fac Geog Sci, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China.
   [Hua, Ting; Zhao, Wenwu] Beijing Normal Univ, Fac Geog Sci, Inst Land Surface Syst & Sustainable Dev, Beijing 100875, Peoples R China.
   [Cherubini, Francesco; Hu, Xiangping] Norwegian Univ Sci & Technol NTNU, Ind Ecol Programme, Trondheim, Norway.
   [Cherubini, Francesco; Hu, Xiangping] Norwegian Univ Sci & Technol NTNU, Dept Energy & Proc Engn, Trondheim, Norway.
   [Pereira, Paulo] Mykolas Romeris Univ, Environm Management Ctr, Ate G 20, LT-08303 Vilnius, Lithuania.
C3 Beijing Normal University; Beijing Normal University; Norwegian
   University of Science & Technology (NTNU); Norwegian University of
   Science & Technology (NTNU); Mykolas Romeris University
RP Zhao, WW (corresponding author), Beijing Normal Univ, Fac Geog Sci, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China.
EM zhaoww@bnu.edu.cn
RI Pereira, Paulo/O-1845-2016; Hu, Xiangping/ABE-8984-2020; Cherubini,
   Francesco/AFS-6064-2022; zhao, wenwu/L-7716-2018
OI Cherubini, Francesco/0000-0002-7147-4292; zhao,
   wenwu/0000-0001-5342-354X; Hua, Ting/0000-0002-1605-9010
FU Second Tibetan Plateau Scientific Expedition and Research Program;
   National Nat-ural Science Foundation of China; Norwegian Research
   Council; Fundamental Research Funds for the Central Universities; 
   [2019QZKK0405];  [41861134038];  [286773]
FX Acknowledgements This research was funded by the Second Tibetan Plateau
   Scientific Expedition and Research Program (2019QZKK0405) , the National
   Nat-ural Science Foundation of China (41861134038) , the Norwegian
   Research Council (No. 286773) , and the Fundamental Research Funds for
   the Central Universities.
CR Alagador D, 2014, J APPL ECOL, V51, P703, DOI 10.1111/1365-2664.12230
   Asamoah EF, 2021, NAT CLIM CHANGE, V11, P1105, DOI 10.1038/s41558-021-01223-2
   Ashcroft MB, 2010, J BIOGEOGR, V37, P1407, DOI 10.1111/j.1365-2699.2010.02300.x
   Brito-Morales I, 2018, TRENDS ECOL EVOL, V33, P441, DOI 10.1016/j.tree.2018.03.009
   Carroll C, 2017, GLOBAL CHANGE BIOL, V23, P4508, DOI 10.1111/gcb.13679
   Chen J, 2004, REMOTE SENS ENVIRON, V91, P332, DOI 10.1016/j.rse.2004.03.014
   Cong N, 2017, AGR FOREST METEOROL, V232, P650, DOI 10.1016/j.agrformet.2016.10.021
   Cong N, 2012, AGR FOREST METEOROL, V165, P104, DOI 10.1016/j.agrformet.2012.06.009
   Dobrowski SZ, 2021, COMMUN EARTH ENVIRON, V2, DOI 10.1038/s43247-021-00270-z
   Dobrowski SZ, 2011, GLOBAL CHANGE BIOL, V17, P1022, DOI 10.1111/j.1365-2486.2010.02263.x
   Doxa A, 2012, AGR ECOSYST ENVIRON, V148, P83, DOI 10.1016/j.agee.2011.11.020
   Doxa A, 2010, J APPL ECOL, V47, P1348, DOI 10.1111/j.1365-2664.2010.01869.x
   Elsen P.R., 2021, ECOGRAPHY, P1
   Elsen PR, 2020, REMOTE SENS ENVIRON, V236, DOI 10.1016/j.rse.2019.111514
   Farwell LS, 2020, ECOL APPL, V30, DOI 10.1002/eap.2157
   Field C.B., 2014, WORKING GROUP 2 CONT, P1, DOI [10.1017/CBO9781107415379, DOI 10.1017/CBO9781107415379]
   Ganguly S, 2010, REMOTE SENS ENVIRON, V114, P1805, DOI 10.1016/j.rse.2010.04.005
   Garcia RA, 2014, SCIENCE, V344, P486, DOI 10.1126/science.1247579
   Gillson L, 2013, TRENDS ECOL EVOL, V28, P135, DOI 10.1016/j.tree.2012.10.008
   Gomes E, 2021, ENVIRON RES, V197, DOI 10.1016/j.envres.2021.111101
   Gonçalves-Souza D, 2021, SCI ADV, V7, DOI 10.1126/sciadv.abh2932
   Groves CR, 2012, BIODIVERS CONSERV, V21, P1651, DOI 10.1007/s10531-012-0269-3
   Gruber S, 2004, PERMAFROST PERIGLAC, V15, P299, DOI 10.1002/ppp.501
   Guo XY, 2017, INT J CLIMATOL, V37, P1117, DOI [10.1002/joc.4727, 10.1002/joc.5246]
   Hamann A, 2015, GLOBAL CHANGE BIOL, V21, P997, DOI 10.1111/gcb.12736
   Hansen AJ, 2020, NAT ECOL EVOL, V4, P1377, DOI 10.1038/s41559-020-1274-7
   Hoffmann S, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-12603-w
   Hua T, 2022, GLOB ECOL CONSERV, V34, DOI 10.1016/j.gecco.2022.e02053
   Huang YZ, 2019, LAND USE POLICY, V80, P224, DOI 10.1016/j.landusepol.2018.10.020
   Jeong SJ, 2011, J GEOPHYS RES-ATMOS, V116, DOI 10.1029/2010JD014633
   Joppa LN, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0008273
   Keppel G, 2012, GLOBAL ECOL BIOGEOGR, V21, P393, DOI 10.1111/j.1466-8238.2011.00686.x
   Kleijn D, 2020, ADV ECOL RES, V63, P127, DOI 10.1016/bs.aecr.2020.08.004
   Kong LQ, 2021, NAT ECOL EVOL, V5, P1309, DOI 10.1038/s41559-021-01520-1
   Kuang XX, 2016, J GEOPHYS RES-ATMOS, V121, P3979, DOI 10.1002/2015JD024728
   Levin N, 2007, DIVERS DISTRIB, V13, P692, DOI 10.1111/j.1472-4642.2007.00372.x
   Li SC, 2020, ECOSYST SERV, V43, DOI 10.1016/j.ecoser.2020.101090
   Li Y, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms7603
   Loarie SR, 2009, NATURE, V462, P1052, DOI 10.1038/nature08649
   Maxwell SL, 2019, GLOB ECOL CONSERV, V18, DOI 10.1016/j.gecco.2019.e00649
   Meddens AJH, 2018, BIOSCIENCE, V68, P944, DOI 10.1093/biosci/biy103
   Menzel A, 2006, GLOBAL ECOL BIOGEOGR, V15, P498, DOI 10.1111/j.1466-822x.2006.00247.x
   Michalak JL, 2020, FRONT ECOL ENVIRON, V18, P254, DOI 10.1002/fee.2207
   Michalak JL, 2018, CONSERV BIOL, V32, P1414, DOI 10.1111/cobi.13130
   Morelli TL, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0159909
   Myers N, 2000, NATURE, V403, P853, DOI 10.1038/35002501
   National Development and Reform Commission of China, 2019, CIRC NAT DEV REF COM
   Oliver T, 2010, ECOL LETT, V13, P473, DOI 10.1111/j.1461-0248.2010.01441.x
   Ordonez A, 2014, NAT CLIM CHANGE, V4, P811, DOI [10.1038/NCLIMATE2337, 10.1038/nclimate2337]
   Pecl GT, 2017, SCIENCE, V355, DOI 10.1126/science.aai9214
   Piao SL, 2006, GLOBAL CHANGE BIOL, V12, P672, DOI 10.1111/j.1365-2486.2006.01123.x
   Pillay R, 2022, FRONT ECOL ENVIRON, V20, P10, DOI 10.1002/fee.2420
   Plard F, 2014, PLOS BIOL, V12, DOI 10.1371/journal.pbio.1001828
   Reed TE, 2013, SCIENCE, V340, P488, DOI 10.1126/science.1232870
   Shen MG, 2014, AGR FOREST METEOROL, V189, P71, DOI 10.1016/j.agrformet.2014.01.003
   Shen MG, 2011, AGR FOREST METEOROL, V151, P1711, DOI 10.1016/j.agrformet.2011.07.003
   Silveira EMO, 2021, REMOTE SENS ENVIRON, V258, DOI 10.1016/j.rse.2021.112368
   Stein A, 2014, ECOL LETT, V17, P866, DOI 10.1111/ele.12277
   Stralberg D, 2020, CONSERV LETT, V13, DOI 10.1111/conl.12712
   Stralberg D, 2020, FRONT ECOL ENVIRON, V18, P261, DOI 10.1002/fee.2188
   Studer S, 2007, INT J BIOMETEOROL, V51, P405, DOI 10.1007/s00484-006-0080-5
   Sun J, 2020, SCI BULL, V65, P1405, DOI 10.1016/j.scib.2020.04.035
   Thackeray SJ, 2010, GLOBAL CHANGE BIOL, V16, P3304, DOI 10.1111/j.1365-2486.2010.02165.x
   Tittensor DP, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aay9969
   UN, 2015, TRANSF OUR WORLD 203
   UN - United Nations, 2019, 73 SESSION
   Virah-Sawmy M, 2009, ECOL MONOGR, V79, P557, DOI 10.1890/08-1210.1
   White MA, 1997, GLOBAL BIOGEOCHEM CY, V11, P217, DOI 10.1029/97GB00330
   Williams JW, 2007, FRONT ECOL ENVIRON, V5, P475, DOI 10.1890/070037
   Wolf AA, 2017, P NATL ACAD SCI USA, V114, P3463, DOI 10.1073/pnas.1608357114
   Wootten A, 2017, J APPL METEOROL CLIM, V56, P3245, DOI 10.1175/JAMC-D-17-0087.1
   Wu RD, 2011, FRONT ECOL ENVIRON, V9, P383, DOI 10.1890/100093
   Xu WH, 2017, P NATL ACAD SCI USA, V114, P1601, DOI 10.1073/pnas.1620503114
   Yu HY, 2010, P NATL ACAD SCI USA, V107, P22151, DOI 10.1073/pnas.1012490107
   Zhang JJ, 2018, BIOL CONSERV, V227, P1, DOI 10.1016/j.biocon.2018.08.016
   Zhang Q, 2018, AGR FOREST METEOROL, V248, P408, DOI 10.1016/j.agrformet.2017.10.026
   Zhang XY, 2006, J GEOPHYS RES-BIOGEO, V111, DOI 10.1029/2006JG000217
NR 77
TC 11
Z9 11
U1 19
U2 112
PU ELSEVIER SCI LTD
PI London
PA 125 London Wall, London, ENGLAND
SN 0006-3207
EI 1873-2917
J9 BIOL CONSERV
JI Biol. Conserv.
PD NOV
PY 2022
VL 275
AR 109781
DI 10.1016/j.biocon.2022.109781
EA OCT 2022
PG 11
WC Biodiversity Conservation; Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA 6Q0GB
UT WOS:000891299100001
OA Green Submitted
DA 2025-01-10
ER

PT J
AU Ordonez, L
   Vallejo, E
   Amariles, D
   Mesa, J
   Esquivel, A
   Llanos-Herrera, L
   Prager, SD
   Segura, C
   Valencia, JJ
   Duarte, CJ
   Rojas, DC
   Obando, D
   Ramirez-Villegas, J
AF Ordonez, Leonardo
   Vallejo, Eliana
   Amariles, Daniel
   Mesa, Jeison
   Esquivel, Alejandra
   Llanos-Herrera, Lizeth
   Prager, Steven D.
   Segura, Cristian
   Valencia, Jhon Jairo
   Duarte, Carmen Julio
   Rojas, Diana Carolina
   Obando, Diego
   Ramirez-Villegas, Julian
TI Applying agroclimatic seasonal forecasts to improve rainfed maize
   agronomic management in Colombia
SO CLIMATE SERVICES
LA English
DT Article
DE Agronomy; Climate services; Crop modeling; Climate variability; Planting
   dates; Seasonal forecast
ID CLIMATE SERVICES; WATER PRODUCTIVITY; CROPPING SYSTEM; AGRICULTURE;
   PRECIPITATION; YIELD; PREDICTABILITY; IRRIGATION; FARMERS; MODELS
AB Climate variability affects crop production in multiple and often complex ways. The development and use hybrid crops with greater productivity and tolerance to climate shocks is one of the approaches to climate adaptation and agricultural intensification. Since hybrid crops are more expensive for the producer, risk management is of paramount importance. Here, we pose that there is high potential for the Colombian maize sector to use crop -specific climate services for risk reduction. We used the CERES-Maize crop model connected to seasonal climate forecasts developed via Canonical Correlation Analysis (CCA) across key maize growing areas in Colombia to assess the performance of a maize-specific agroclimatic forecast to inform two key decisions, namely, the choice of sowing dates and genotypes. We find that the agroclimatic models perform well at discriminating yield categories (above, below, and normal) with discrimination capacity of up to 70-80 % for the 'below normal' and 'above + below normal' categories. Consistent with this, agroclimatic forecasts typically predict the optimal planting date with an error of 3 pentads or less. They also predict the optimal choice of genotype correctly around 50-70 % of the time depending on the site or season of interest. Notably, we identify specific cases in which the agroclimatic forecast is misleading but argue that the overall value of the forecasts outweighs these cases. Future work should focus on expanding the scope of the agroclimatic prediction to include other relevant farming decisions that are influenced by climate, and on the improvement of climate forecast performance.
C1 [Ordonez, Leonardo; Vallejo, Eliana; Amariles, Daniel; Mesa, Jeison; Esquivel, Alejandra; Llanos-Herrera, Lizeth; Prager, Steven D.; Rojas, Diana Carolina] Int Ctr Trop Agr CIAT, Km 17 Recta Cali-Palmira, Cali 763537, Colombia.
   [Segura, Cristian; Valencia, Jhon Jairo; Duarte, Carmen Julio] Federac Nacl Cereales & Leguminosas, Cota, Cundinamarca, Colombia.
   [Obando, Diego] Int Ctr Trop Agr CIAT, Tegucigalpa, Honduras.
   [Ramirez-Villegas, Julian] CGIAR Res Program Climate Change Agr & Food Secur, Biovers Int, Via San Domenico 1, Rome, Italy.
   [Ramirez-Villegas, Julian] Wageningen Univ & Res, Plant Prod Syst Grp, Wageningen, Netherlands.
   [Ramirez-Villegas, Julian] Int Ctr Trop Agr CIAT, Biovers Int, Via San Domenico 1, Rome, Italy.
C3 Alliance; International Center for Tropical Agriculture - CIAT;
   Alliance; International Center for Tropical Agriculture - CIAT;
   Alliance; Bioversity International; Wageningen University & Research;
   Alliance; International Center for Tropical Agriculture - CIAT;
   Bioversity International
RP Ramirez-Villegas, J (corresponding author), CGIAR Res Program Climate Change Agr & Food Secur, Biovers Int, Via San Domenico 1, Rome, Italy.; Ramirez-Villegas, J (corresponding author), Wageningen Univ & Res, Plant Prod Syst Grp, Wageningen, Netherlands.; Ramirez-Villegas, J (corresponding author), Int Ctr Trop Agr CIAT, Biovers Int, Via San Domenico 1, Rome, Italy.
EM j.r.villegas@cgiar.org
RI Ramirez-Villegas, Julian/AAY-8073-2020; Prager, Steven/ABD-2092-2020
FU Climate Services for Resilient Development (CSRD)-United States Agency
   for International Development (USAID) Award [AID-BFS-G-11-00002-10, MTO
   069018]; Climate Change, Agriculture and Food Security (CCAFS), under
   the project Agroclimas [G135]; CGIAR Trust Fund; AgriLAC Resiliente One
   CGIAR Initiative [G206]; National Cereals and Legumes Federation
   (FENALCE)
FX This work was carried out under the Climate Services for Resilient
   Development (CSRD)-United States Agency for International Development
   (USAID) Award#: AID-BFS-G-11-00002-10 towards the CGIAR Fund (MTO
   069018). CSRD (http:// www.cs4rd.org/) brings together public and
   private organizations and agencies committed to realizing the potential
   to enhance climate resilience and climate-smart policies and practices
   throughout the world, particularly in developing countries. We
   acknowledge support from the Climate Change, Agriculture and Food
   Security (CCAFS), under the project Agroclimas (Project ID# G135,
   http://bit.ly/2i3V0Nh). CCAFS is carried out with support from CGIAR
   Trust Fund Donors and through bilateral funding agreements. For details
   please visit https://ccafs.cgiar.org/donors. We also acknowledge the
   support of the AgriLAC Resiliente One CGIAR Initiative (Project ID#
   G206). The views expressed in this paper cannot be taken to reflect the
   official opinions of these organizations. We also gratefully acknowledge
   the Insituto de Hidrologia, Meteorologia y Estudios Ambientales (IDEAM)
   for providing access to their weather station data, and for discussion
   on the CCA-based forecast model results presented here. Authors thank
   the Ministry of Agriculture and Rural Development (MADR) of Colombia,
   the National Cereals and Legumes Federation (FENALCE), for their
   financial support, and for their contribution with data and insights for
   this study.
CR Alfaro EJ, 2018, INT J CLIMATOL, V38, pE255, DOI 10.1002/joc.5366
   Anderson WB, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aaw1976
   [Anonymous], 2018, 234 CCAFS
   [Anonymous], 2015, Retorica al suspiro de queja
   Basso B, 2016, ADV AGRON, V136, P27, DOI 10.1016/bs.agron.2015.11.004
   BERNARDI M, 2013, UNDERSTANDING USER N
   Blundo Canto G., 2016, MAPEO ACTORES NECESI
   Bouroncle C, 2019, CLIM SERV, V16, DOI 10.1016/j.cliser.2019.100137
   Breiman Leo, 2001, MACH LEARN, V45, P5
   Capa-Morocho M, 2016, AGR SYST, V149, P75, DOI 10.1016/j.agsy.2016.08.008
   Chiputwa B, 2022, AGR SYST, V195, DOI 10.1016/j.agsy.2021.103309
   Ciat, 2020, CLIM SERV RES DEV CS
   Coelho CAS, 2006, J CLIMATE, V19, P3704, DOI 10.1175/JCLI3801.1
   Comas LH, 2019, AGR WATER MANAGE, V212, P433, DOI 10.1016/j.agwat.2018.07.015
   Cordano E., 2012, EUROPEAN GEOSCIENCES
   Córdoba-Machado S, 2015, CLIM DYNAM, V44, P1293, DOI 10.1007/s00382-014-2232-3
   Corpoica, 2017, SIST EXP MOD AD PREV
   Recalde-Coronel GC, 2014, J APPL METEOROL CLIM, V53, P1471, DOI 10.1175/JAMC-D-13-0133.1
   Dayamba DS, 2018, CLIM SERV, V12, P27, DOI 10.1016/j.cliser.2018.07.003
   DeJonge KC, 2012, ECOL MODEL, V231, P113, DOI 10.1016/j.ecolmodel.2012.01.024
   Esquivel A, 2018, CLIM SERV, V12, P36, DOI 10.1016/j.cliser.2018.09.001
   *FENALCE, 2017, CER REV
   Fernandes K, 2020, WEATHER FORECAST, V35, P437, DOI 10.1175/WAF-D-19-0122.1
   Fraisse CW, 2006, COMPUT ELECTRON AGR, V53, P13, DOI 10.1016/j.compag.2006.03.002
   Funk C, 2015, SCI DATA, V2, DOI 10.1038/sdata.2015.66
   Giraldo D., 2020, 299 MTA CCAFS
   GLAHN HR, 1968, J ATMOS SCI, V25, P23, DOI 10.1175/1520-0469(1968)025<0023:CCAIRT>2.0.CO;2
   Goddard L, 2001, INT J CLIMATOL, V21, P1111, DOI 10.1002/joc.636
   Guido Z, 2020, CLIM RISK MANAG, V30, DOI 10.1016/j.crm.2020.100247
   Haigh T, 2018, B AM METEOROL SOC, V99, P1781, DOI 10.1175/BAMS-D-17-0253.1
   Ham YG, 2019, NATURE, V573, P568, DOI 10.1038/s41586-019-1559-7
   Hammer GL, 1996, AUST J AGR RES, V47, P717, DOI 10.1071/AR9960717
   Han EJ, 2019, COMPUT ELECTRON AGR, V161, P241, DOI 10.1016/j.compag.2018.06.034
   Hansen JW, 2011, EXP AGR, V47, P205, DOI 10.1017/S0014479710000876
   Hansen JW, 2009, AGR SYST, V101, P80, DOI 10.1016/j.agsy.2009.03.005
   Heinemann AB, 2021, INT J CLIMATOL, V41, pE283, DOI 10.1002/joc.6684
   Hotelling H, 1936, BIOMETRIKA, V28, P321, DOI 10.1093/biomet/28.3-4.321
   Iizumi T, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms4712
   Jarvis A, 2019, MAIZ COLOMBIA VISION
   Jiménez D, 2019, GLOB FOOD SECUR-AGR, V23, P256, DOI 10.1016/j.gfs.2019.08.004
   Jones C.A., 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
   Jones PG, 2000, AGRON J, V92, P445, DOI 10.2134/agronj2000.923445x
   Klemm T, 2017, AGR FOREST METEOROL, V232, P384, DOI 10.1016/j.agrformet.2016.09.005
   Llanos-Herrera L, 2014, RCLIMTOOL USER MANUA
   Lubkov A.S., 2019, IOP Conf. Ser.: Earth Environ. Sci, V386, DOI [10.1088/1755-1315/386/1/012040, DOI 10.1088/1755-1315/386/1/012040]
   MacCarthy DS, 2017, FRONT PLANT SCI, V8, DOI 10.3389/fpls.2017.00031
   MADR, 2021, MAIZ DIR CAD AGR FOR
   Loboguerrero AM, 2018, CLIM RISK MANAG, V22, P67, DOI 10.1016/j.crm.2018.08.001
   Mason S.J., 2017, Climate Predictability Tool Version 15.5.10
   Masuka B, 2017, CROP SCI, V57, P168, DOI 10.2135/cropsci2016.05.0343
   McCrea R, 2005, INT J CLIMATOL, V25, P1127, DOI 10.1002/joc.1164
   Muñoz AG, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-69625-4
   Pazos J.R.C., 2018, INTERINSTITUTIONAL R, P250, DOI [10.1007/978-3-319-70187-5_19, DOI 10.1007/978-3-319-70187-5_19]
   Ramirez-Villegas J., 2018, ORMS TODAY, P20
   Ray DK, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms6989
   Roel A, 2007, Climate Prediction and Agriculture: Advances and Challenges, P89, DOI 10.1007/978-3-540-44650-7_10
   Saha S, 2014, J CLIMATE, V27, P2185, DOI 10.1175/JCLI-D-12-00823.1
   Semenov MA, 2007, CLIM RES, V34, P71, DOI 10.3354/cr034071
   Soler CMT, 2007, EUR J AGRON, V27, P165, DOI 10.1016/j.eja.2007.03.002
   Sotelo S, 2020, COMPUT ELECTRON AGR, V174, DOI 10.1016/j.compag.2020.105486
   Tall A, 2018, CLIM SERV, V11, P1, DOI 10.1016/j.cliser.2018.06.001
   Thorp KR, 2008, COMPUT ELECTRON AGR, V64, P276, DOI 10.1016/j.compag.2008.05.022
   Trenberth KE, 2016, NAT CLIM CHANGE, V6, P1057, DOI 10.1038/nclimate3170
   Vaughan Catherine, 2016, Climate Services, V4, P65, DOI 10.1016/j.cliser.2016.11.004
   Vaughan C, 2019, CLIM SERV, V15, DOI 10.1016/j.cliser.2019.100104
   Vaughan C, 2018, WEATHER CLIM SOC, V10, P373, DOI 10.1175/WCAS-D-17-0030.1
   Vaughan C, 2014, WIRES CLIM CHANGE, V5, P587, DOI 10.1002/wcc.290
   Vogel Jason, 2017, Climate Services, V6, P65, DOI 10.1016/j.cliser.2017.07.003
   Waha K, 2013, GLOBAL ENVIRON CHANG, V23, P130, DOI 10.1016/j.gloenvcha.2012.11.001
   Weisheimer A, 2014, J R SOC INTERFACE, V11, DOI 10.1098/rsif.2013.1162
   White JW, 2011, FIELD CROP RES, V124, P357, DOI 10.1016/j.fcr.2011.07.001
   WILLMOTT CJ, 1985, J GEOPHYS RES-OCEANS, V90, P8995, DOI 10.1029/JC090iC05p08995
   Xue CY, 2008, IRRIGATION SCI, V26, P459, DOI 10.1007/s00271-008-0107-2
NR 74
TC 3
Z9 3
U1 2
U2 8
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2405-8807
J9 CLIM SERV
JI Clim. Serv.
PD DEC
PY 2022
VL 28
AR 100333
DI 10.1016/j.cliser.2022.100333
EA OCT 2022
PG 13
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 6Z9TG
UT WOS:000898109500002
OA gold
DA 2025-01-10
ER

PT J
AU Mizukami, N
   Newman, AJ
   Littell, JS
   Giambelluca, TW
   Wood, AW
   Gutmann, ED
   Hamman, JJ
   Gergel, DR
   Nijssen, B
   Clark, MP
   Arnold, JR
AF Mizukami, Naoki
   Newman, Andrew J.
   Littell, Jeremy S.
   Giambelluca, Thomas W.
   Wood, Andrew W.
   Gutmann, Ethan D.
   Hamman, Joseph J.
   Gergel, Diana R.
   Nijssen, Bart
   Clark, Martyn P.
   Arnold, Jeffrey R.
TI New projections of 21st century climate and hydrology for Alaska and
   Hawai?i
SO CLIMATE SERVICES
LA English
DT Article
DE Hydrology; Climate; Projections; Ensembles; Alaska; Hawai ?i
ID CHANGE SCENARIOS; DATA SET; MODEL; UNCERTAINTY; RIVER; TEMPERATURE;
   RAINFALL; IMPACTS; REGIMES; WATER
AB In the United States, high-resolution, century-long, hydroclimate projection datasets have been developed for water resources planning, focusing on the contiguous United States (CONUS) domain. However, there are few statewide hydroclimate projection datasets available for Alaska and HawaiModified Letter Turned Commai. The limited information on hydroclimatic change motivates developing hydrologic scenarios from 1950 to 2099 using climate-hydrology impact modeling chains consisting of multiple statistically downscaled climate projections as input to hydrologic model simulations for both states. We adopt an approach similar to the previous CONUS hydrologic assessments where: 1) we select the outputs from ten global climate models (GCM) from the Coupled Model Intercomparison Project Phase 5 with Representative Concentration Pathways 4.5 and 8.5; 2) we perform statistical downscaling to generate climate input data for hydrologic models (12-km grid-spacing for Alaska and 1km for HawaiModified Letter Turned Commai); and 3) we perform process-based hydrologic model simulations. For Alaska, we have advanced the hydrologic model configuration from CONUS by using the full water-energy balance computation, frozen soils and a simple glacier model. The simulations show that robust warming and increases in precipitation produce runoff increases for most of Alaska, with runoff reductions in the currently glacierized areas in Southeast Alaska. For HawaiModified Letter Turned Commai, we produce the projections at high resolution (1 km) which highlight high spatial variability of climate variables across the state, and a large spread of runoff across the GCMs is driven by a large precipitation spread across the GCMs. Our new ensemble datasets assist with state-wide climate adaptation and other water planning.
C1 [Mizukami, Naoki; Newman, Andrew J.; Wood, Andrew W.; Gutmann, Ethan D.; Hamman, Joseph J.] Natl Ctr Atmospher Res, Boulder, CO 80305 USA.
   [Littell, Jeremy S.] US Geol Survey Alaska Climate Adaptat Sci Ctr, Anchorage, AK USA.
   [Giambelluca, Thomas W.] Univ Hawaii Manoa, Dept Geog, Honolulu, HI USA.
   [Hamman, Joseph J.] CarbonPlan, San Francisco, CA USA.
   [Gergel, Diana R.] BlackRock, Charlotte, NC USA.
   [Nijssen, Bart] Univ Washington Civil & Environm Engn, Seattle, WA USA.
   [Clark, Martyn P.] Univ Saskatchewan, Ctr Hydrol, Canmore, AB, Canada.
   [Arnold, Jeffrey R.] US Army Corps Engineers, Responses Climate Change Program, Seattle, WA USA.
   [Arnold, Jeffrey R.] MITRE Corp, Mclean, VA USA.
C3 National Center Atmospheric Research (NCAR) - USA; University of Hawaii
   System; University of Hawaii Manoa; University of Saskatchewan; United
   States Department of Defense; United States Army; U.S. Army Corps of
   Engineers; MITRE Corporation
RP Mizukami, N (corresponding author), Natl Ctr Atmospher Res, Boulder, CO 80305 USA.
EM mizukami@ucar.edu
RI Mizukami, Naoki/J-7027-2015; Nijssen, Bart/B-1013-2012; Clark,
   Martyn/A-5560-2015; Gutmann, Ethan/I-5728-2012
OI Gutmann, Ethan/0000-0003-4077-3430; Giambelluca,
   Thomas/0000-0002-6798-3780
FU U.S Army Corps of Engineers Climate Preparedness and Resilience program;
   National Center for Atmospheric Research (NCAR); National Science
   Foundation [1852977]
FX This work was financially supported by the U.S Army Corps of En-gineers
   Climate Preparedness and Resilience program, and by the Na-tional Center
   for Atmospheric Research (NCAR), which is a major facility sponsored by
   the National Science Foundation under Coopera-tive Agreement No.
   1852977. The simulations and visualization pre-sented for this paper
   were produced through the Cheyenne and Casper computational resources
   (doi:10.5065/D6RX99HX) at the NCAR-Wyoming Supercomputing Center
   supported by the National Science Foundation and operated by NCAR's
   Computational and Information Systems Laboratory. We thank Ryan Toohey
   and three anonymous re-viewers for comments that improved the
   manuscript.
CR Abatzoglou JT, 2018, SCI DATA, V5, DOI 10.1038/sdata.2017.191
   Addor N, 2017, HYDROL EARTH SYST SC, V21, P5293, DOI 10.5194/hess-21-5293-2017
   Addor N, 2014, WATER RESOUR RES, V50, P7541, DOI 10.1002/2014WR015549
   [Anonymous], 2014, DOWNSCALED CMIP3 CMI
   [Anonymous], 2013, Downscaled CMIP3 and CMIP5 climate projections: Release of downscaled CMIP5 climate projections, comparison with preceding information, and summary of user needs
   Bahr DB, 1997, WATER RESOUR RES, V33, P1669, DOI 10.1029/97WR00824
   Bassiouni M, 2013, HYDROL PROCESS, V27, P1484, DOI 10.1002/hyp.9298
   Bathke DJ, 2019, B AM METEOROL SOC, V100, P2665, DOI 10.1175/BAMS-D-19-0223.1
   Baumberger C, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.454
   Beamer JP, 2017, WATER RESOUR RES, V53, P7502, DOI 10.1002/2016WR020033
   Beamer JP, 2016, WATER RESOUR RES, V52, P3888, DOI 10.1002/2015WR018457
   Bennett KE, 2012, J CLIMATE, V25, P5711, DOI 10.1175/JCLI-D-11-00417.1
   Bevington AR, 2022, REMOTE SENS ENVIRON, V270, DOI 10.1016/j.rse.2021.112862
   Chegwidden OS, 2019, EARTHS FUTURE, V7, P623, DOI 10.1029/2018EF001047
   Cherkauer KA, 1999, J GEOPHYS RES-ATMOS, V104, P19599, DOI 10.1029/1999JD900337
   Clark MP, 2016, CURR CLIM CHANGE REP, V2, P55, DOI 10.1007/s40641-016-0034-x
   Enquist CAF, 2017, FRONT ECOL ENVIRON, V15, P541, DOI 10.1002/fee.1733
   Fiddes J, 2014, GEOSCI MODEL DEV, V7, P387, DOI 10.5194/gmd-7-387-2014
   Frazier AG, 2017, INT J CLIMATOL, V37, P2522, DOI 10.1002/joc.4862
   Friedl M., 2019, NASA EOSDIS Land Processes Distributed Active Archive Center, DOI DOI 10.5067/MODIS/MCD12Q1.006
   Gergel D.R, 2019, THESIS U WASHINGTON
   Giambelluca T.W., 2014, Evapotranspiration of Hawai'i
   Giambelluca TW, 2013, B AM METEOROL SOC, V94, P313, DOI 10.1175/BAMS-D-11-00228.1
   Gutmann E, 2014, WATER RESOUR RES, V50, P7167, DOI 10.1002/2014WR015559
   Hamman J., 2015, VIC 4 2 GLACIER
   Hawkins E, 2009, B AM METEOROL SOC, V90, P1095, DOI 10.1175/2009BAMS2607.1
   Hay LE, 2010, CLIMATIC CHANGE, V100, P509, DOI 10.1007/s10584-010-9805-x
   Hayward GD, 2017, PNW-GTR-950
   Hengl T, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0169748
   Hinzman LD, 2005, CLIMATIC CHANGE, V72, P251, DOI 10.1007/s10584-005-5352-2
   Hurtt GC, 2020, GEOSCI MODEL DEV, V13, P5425, DOI 10.5194/gmd-13-5425-2020
   Jin HJ, 2022, WATER-SUI, V14, DOI 10.3390/w14030372
   Kao S.-C., 2016, United States10, Patent No. [2172/1340431, 21721340431]
   Kay AL, 2009, CLIMATIC CHANGE, V92, P41, DOI 10.1007/s10584-008-9471-4
   Lader R, 2020, INT J CLIMATOL, V40, P169, DOI 10.1002/joc.6201
   Lader R, 2017, J APPL METEOROL CLIM, V56, P2393, DOI 10.1175/JAMC-D-16-0415.1
   Lawrence DM, 2008, CLIM DYNAM, V30, P145, DOI 10.1007/s00382-007-0278-1
   Liang X, 1994, J GEOPHYS RES-ATMOS, V99, P14415, DOI 10.1029/94JD00483
   Littell JS, 2018, WATER-SUI, V10, DOI 10.3390/w10050668
   Longman RJ, 2019, J HYDROMETEOROL, V20, P489, DOI 10.1175/JHM-D-18-0112.1
   Mair A., 2019, US GEOLOGICAL SURVEY
   Maurer EP, 2014, B AM METEOROL SOC, V95, P1011, DOI 10.1175/BAMS-D-13-00126.1
   Mendoza PA, 2015, J HYDROMETEOROL, V16, P762, DOI 10.1175/JHM-D-14-0104.1
   Mizukami N, 2017, WATER RESOUR RES, V53, P8020, DOI 10.1002/2017WR020401
   Mizukami N, 2016, J HYDROMETEOROL, V17, P73, DOI 10.1175/JHM-D-14-0187.1
   MONTEITH J.L., 1973, Principles of environmental physics
   Najafi MR, 2011, HYDROL PROCESS, V25, P2814, DOI 10.1002/hyp.8043
   Newman AJ, 2022, B AM METEOROL SOC, V103, pE1213, DOI 10.1175/BAMS-D-21-0316.1
   Newman AJ, 2020, J GEOPHYS RES-ATMOS, V125, DOI 10.1029/2020JD032696
   Newman AJ, 2019, J HYDROMETEOROL, V20, P509, DOI 10.1175/JHM-D-18-0113.1
   Oubeidillah AA, 2014, HYDROL EARTH SYST SC, V18, P67, DOI 10.5194/hess-18-67-2014
   Panofsky H.A., 1968, SOME APPL STAT METEO, P224
   Parker WS, 2020, PHILOS SCI, V87, P457, DOI 10.1086/708691
   Pfeffer WT, 2014, J GLACIOL, V60, P537, DOI 10.3189/2014JoG13J176
   Prudhomme C, 2009, CLIMATIC CHANGE, V93, P177, DOI 10.1007/s10584-008-9464-3
   Rakovec O, 2019, J GEOPHYS RES-ATMOS, V124, P13991, DOI 10.1029/2019JD030767
   Rasmussen R, 2011, J CLIMATE, V24, P3015, DOI 10.1175/2010JCLI3985.1
   Reclamation, 2011, TECHNICAL MEMORANDUM
   Reclamation, 2020, COMP DOWNSC LOCA BCS
   Safeeq M, 2012, HYDROL PROCESS, V26, P2745, DOI 10.1002/hyp.8328
   Schar C, 1996, GEOPHYS RES LETT, V23, P669, DOI 10.1029/96GL00265
   Schuurman G.W., 2020, Resist-accept-direct (RAD): a framework for the 21st-century natural resource manager, DOI DOI 10.36967/NRR-2283597
   Sicart JE, 2008, J GEOPHYS RES-ATMOS, V113, DOI 10.1029/2008JD010406
   Simpson IR, 2021, J CLIMATE, V34, P6355, DOI 10.1175/JCLI-D-21-0055.1
   Snover AK, 2013, CONSERV BIOL, V27, P1147, DOI 10.1111/cobi.12163
   Sun QH, 2020, B AM METEOROL SOC, V101, pE409, DOI 10.1175/BAMS-D-18-0258.1
   Surfleet CG, 2013, HYDROL PROCESS, V27, P3560, DOI 10.1002/hyp.9485
   Tachikawa T., 2011, ASTER Global Digital Elevation Model Version 2 Summary of Validation Results
   Terando A., 2020, USING INFORM GLOBAL, DOI [10.3133/ ofr20201058, DOI 10.3133/OFR20201058]
   Thompson LM, 2021, FISHERIES, V46, P8, DOI 10.1002/fsh.10506
   Thornton P., 2016, DAYMET DAILY SURFACE
   Thornton PE, 1999, AGR FOREST METEOROL, V93, P211, DOI 10.1016/S0168-1923(98)00126-9
   Timm OE, 2015, J GEOPHYS RES-ATMOS, V120, P92, DOI 10.1002/2014JD022059
   Tokarska KB, 2020, SCI ADV, V6, DOI 10.1126/sciadv.aaz9549
   Vano JA, 2014, B AM METEOROL SOC, V95, P59, DOI 10.1175/BAMS-D-12-00228.1
   Vidal JP, 2016, HYDROL EARTH SYST SC, V20, P3651, DOI 10.5194/hess-20-3651-2016
   Walsh JE, 2018, ENVIRON MODELL SOFTW, V110, P38, DOI 10.1016/j.envsoft.2018.03.021
   Williamson MS, 2021, REV MOD PHYS, V93, DOI 10.1103/RevModPhys.93.025004
   Wood AW, 2004, CLIMATIC CHANGE, V62, P189, DOI 10.1023/B:CLIM.0000013685.99609.9e
   Wootten AM, 2021, INT J CLIMATOL, V41, P980, DOI 10.1002/joc.6716
   Xue L., 2020, Bull. of Atmos. Sci. Technol, V1, P459, DOI DOI 10.1007/S42865-020-00022-5
   Yang Y, 2019, WATER RESOUR RES, V55, P7784, DOI 10.1029/2018WR024178
   Zhang CX, 2016, J CLIMATE, V29, P8333, DOI 10.1175/JCLI-D-16-0038.1
NR 83
TC 7
Z9 8
U1 0
U2 3
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2405-8807
J9 CLIM SERV
JI Clim. Serv.
PD AUG
PY 2022
VL 27
AR 100312
DI 10.1016/j.cliser.2022.100312
EA AUG 2022
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 5A2UM
UT WOS:000862746900001
OA gold
DA 2025-01-10
ER

PT J
AU Pang, B
   Zhao, JY
   Zhang, JX
   Yang, L
AF Pang, Bo
   Zhao, Jingyuan
   Zhang, Jianxin
   Yang, Li
TI How to plan urban green space in cold regions of China to achieve the
   best cooling efficiency
SO URBAN ECOSYSTEMS
LA English
DT Article
DE Urban heat island; Urban green space; Urban cold island; Threshold value
   of efficiency; Water; land ratio; Urban planning; Climate adaptation
ID LAND-SURFACE TEMPERATURE; HEAT-ISLAND; MITIGATION TECHNOLOGIES;
   LANDSCAPE; CLIMATE; PARKS; XIAN; URBANIZATION; VEGETATION; MEGACITIES
AB With the acceleration of urbanization, the urban heat island (UHI) effect has intensified. Urban green space can retard the UHI effect. However, most existing studies have only focused on hot regions, while little attention has been given to cold regions that also have summer heat protection requirements. Furthermore, existing researc has not classified urban green spaces according to the presence or absence of water, which can lead to inaccurate results. This paper takes four cities in cold regions of China as examples and studies the cooling effects of two different types of urban green space. The results indicate that in cold regions of China, green spaces containing water bodies have a stronger cooling effect than those without water. For green spaces without water, the cooling intensity is related to the background temperature and green space areas, while for green spaces containing water bodies, the area of the internal water body is the key influencing factor. Specifically, there is a threshold value of efficiency (TVoE) for the green space areas without water in cold region cities of China, which is approximately 0.52 ha, while there is no TVoE for the green space areas containing water bodies. Additionally, there is a TVoE for the water/land ratio of the green spaces containing water bodies of approximately 0.5. The methods and results of this study can provide a reference for future research and for urban planners and managers designing urban green spaces.
C1 [Pang, Bo; Zhao, Jingyuan; Zhang, Jianxin; Yang, Li] Changan Univ, Dept Architecture, Xian 701164, Peoples R China.
C3 Chang'an University
RP Zhao, JY (corresponding author), Changan Univ, Dept Architecture, Xian 701164, Peoples R China.
EM zjytougao@outlook.com
RI Zhang, Jianxin/ABH-2317-2021; Yang, Li/K-4137-2018; pang,
   bo/LMN-5984-2024
OI Zhao, Jingyuan/0000-0002-1278-5322
FU Project Funding To Scientific Research Innovation Team of Shaanxi
   Provincial Universities [2020TD-029]; Key Research and Development
   Program of Shaanxi Province [2021SF-464]; Shaanxi National Science
   Foundation [2019JM-475]; Fundamental Research Funds for the Central
   Universities [300102411401, 300102411610]
FX This work was financially supported by the Project Funding To Scientific
   Research Innovation Team of Shaanxi Provincial Universities
   (No.2020TD-029) and the Key Research and Development Program of Shaanxi
   Province (No.2021SF-464) and Shaanxi National Science Foundation (No.
   2019JM-475) and the Fundamental Research Funds for the Central
   Universities (No. 300102411401;No. 300102411610).
CR Abutaleb K., 2015, Adv. Remote Sens, V4, P35, DOI [10.4236/ars.2015.41004, DOI 10.4236/ARS.2015.41004]
   Akbari H, 2016, ENERG BUILDINGS, V133, P834, DOI 10.1016/j.enbuild.2016.09.067
   Asgarian A, 2015, URBAN ECOSYST, V18, P209, DOI 10.1007/s11252-014-0387-7
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   Cao X, 2010, LANDSCAPE URBAN PLAN, V96, P224, DOI 10.1016/j.landurbplan.2010.03.008
   Chang CR, 2007, LANDSCAPE URBAN PLAN, V80, P386, DOI 10.1016/j.landurbplan.2006.09.005
   Chen SJ, 2021, REMOTE SENS ENVIRON, V265, DOI 10.1016/j.rse.2021.112648
   Chrysoulakis N, 2013, LANDSCAPE URBAN PLAN, V112, P100, DOI 10.1016/j.landurbplan.2012.12.005
   Churkina G, 2017, ENVIRON SCI TECHNOL, V51, P6120, DOI 10.1021/acs.est.6b06514
   Deng ZW, 2019, ADV SPACE RES, V63, P2144, DOI 10.1016/j.asr.2018.12.005
   Luciano ACD, 2021, COMPUT ELECTRON AGR, V184, DOI 10.1016/j.compag.2021.106063
   Du HY, 2016, ECOL INDIC, V67, P31, DOI 10.1016/j.ecolind.2016.02.040
   Eliasson I, 1996, ATMOS ENVIRON, V30, P379, DOI 10.1016/1352-2310(95)00033-X
   Estoque RC, 2017, SCI TOTAL ENVIRON, V577, P349, DOI 10.1016/j.scitotenv.2016.10.195
   Fan C, 2015, PROG PHYS GEOG, V39, P199, DOI 10.1177/0309133314567583
   Fan HY, 2019, AGR FOREST METEOROL, V265, P338, DOI 10.1016/j.agrformet.2018.11.027
   Feng M, 2013, REMOTE SENS ENVIRON, V134, P276, DOI 10.1016/j.rse.2013.02.031
   Feng M, 2012, COMPUT GEOSCI-UK, V38, P9, DOI 10.1016/j.cageo.2011.04.011
   [冯晓刚 Feng Xiaogang], 2012, [生态学报, Acta Ecologica Sinica], V32, P7355
   Feyisa GL, 2014, LANDSCAPE URBAN PLAN, V123, P87, DOI 10.1016/j.landurbplan.2013.12.008
   Gao Y, 2019, APPL ECOL ENV RES, V17, P231, DOI 10.15666/aeer/1701_231244
   Gunawardena KR, 2017, SCI TOTAL ENVIRON, V584, P1040, DOI 10.1016/j.scitotenv.2017.01.158
   Hang HT, 2018, URBAN CLIM, V24, P1, DOI 10.1016/j.uclim.2018.01.001
   Hu YH, 2019, ISPRS J PHOTOGRAMM, V156, P160, DOI 10.1016/j.isprsjprs.2019.08.012
   Huang X, 2018, J NW FOREST U
   Jaganmohan M, 2016, J ENVIRON QUAL, V45, P134, DOI 10.2134/jeq2015.01.0062
   Kalnay E, 2003, NATURE, V423, P528, DOI 10.1038/nature01675
   Kaza N, 2013, LANDSCAPE URBAN PLAN, V110, P74, DOI 10.1016/j.landurbplan.2012.10.015
   Kong FH, 2014, URBAN FOR URBAN GREE, V13, P846, DOI 10.1016/j.ufug.2014.09.009
   Kuang WH, 2015, LANDSCAPE ECOL, V30, P357, DOI 10.1007/s10980-014-0128-6
   Li XX, 2016, REMOTE SENS ENVIRON, V174, P233, DOI 10.1016/j.rse.2015.12.022
   Li ZL, 2013, REMOTE SENS ENVIRON, V131, P14, DOI 10.1016/j.rse.2012.12.008
   Liang BQ, 2011, IEEE J-STARS, V4, P43, DOI 10.1109/JSTARS.2010.2060316
   Lin WQ, 2015, LANDSCAPE URBAN PLAN, V134, P66, DOI 10.1016/j.landurbplan.2014.10.012
   Liu SH, 2019, PHYS CHEM EARTH, V110, P185, DOI 10.1016/j.pce.2018.11.007
   Manoli G, 2019, NATURE, V573, P55, DOI 10.1038/s41586-019-1512-9
   Mikami T, 2009, 7 INT C URB CLIM YOK
   Le MT, 2019, E3S WEB CONF, V97, DOI 10.1051/e3sconf/20199701013
   Mohan M, 2013, THEOR APPL CLIMATOL, V112, P647, DOI 10.1007/s00704-012-0758-z
   Oke T. R., 2017, Urban Climates, DOI [10.1017/9781139016476, DOI 10.1017/9781139016476]
   OKE TR, 1989, PHILOS T ROY SOC B, V324, P335, DOI 10.1098/rstb.1989.0051
   Peng J, 2020, LANDSCAPE URBAN PLAN, V202, DOI 10.1016/j.landurbplan.2020.103873
   Peng J, 2016, REMOTE SENS ENVIRON, V173, P145, DOI 10.1016/j.rse.2015.11.027
   Pollio AC, 2016, Q REV BIOL, V91, P212
   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
   Santarnouris M, 2015, ENERG BUILDINGS, V98, P125, DOI 10.1016/j.enbuild.2014.08.050
   Stanley M., 2019, The rise of China's supercities: New era of urbanization
   Stanley Morgan, 2018, RIS CHIN SUP NEW ER
   Sun RH, 2012, LANDSCAPE URBAN PLAN, V105, P27, DOI 10.1016/j.landurbplan.2011.11.018
   Sun Y, 2014, NAT CLIM CHANGE, V4, P1082, DOI 10.1038/NCLIMATE2410
   Taleghani M, 2018, RENEW SUST ENERG REV, V81, P2011, DOI 10.1016/j.rser.2017.06.010
   Theeuwes NE, 2013, J GEOPHYS RES-ATMOS, V118, P8881, DOI 10.1002/jgrd.50704
   Tsou JY, 2017, URBAN SCI, V1, DOI 10.3390/urbansci1010010
   Vöelker S, 2015, HEALTH PLACE, V35, P196, DOI 10.1016/j.healthplace.2014.10.015
   Voogt JA, 2003, REMOTE SENS ENVIRON, V86, P370, DOI 10.1016/S0034-4257(03)00079-8
   Weng QH, 2011, IEEE T GEOSCI REMOTE, V49, P4080, DOI 10.1109/TGRS.2011.2128874
   Wong PPY, 2016, BUILD ENVIRON, V95, P199, DOI 10.1016/j.buildenv.2015.09.024
   Wu JS, 2020, ECOL INDIC, V117, DOI 10.1016/j.ecolind.2020.106699
   Wu ZF, 2019, ENVIRON REV, V27, P241, DOI 10.1139/er-2018-0029
   Yang GY, 2020, SUSTAIN CITIES SOC, V53, DOI 10.1016/j.scs.2019.101932
   Yang JW, 2010, SCI CHINA EARTH SCI, V53, P64, DOI 10.1007/s11430-009-0185-x
   Yu K, 2020, SCI TOTAL ENVIRON, V727, DOI 10.1016/j.scitotenv.2020.138750
   Yu Zhao-wu, 2015, Yingyong Shengtai Xuebao, V26, P636
   Yu ZW, 2021, SUSTAIN CITIES SOC, V74, DOI 10.1016/j.scs.2021.103135
   Yu ZW, 2020, URBAN FOR URBAN GREE, V49, DOI 10.1016/j.ufug.2020.126630
   Yu ZW, 2020, APPL ENERG, V264, DOI 10.1016/j.apenergy.2020.114724
   Yu ZW, 2021, LANDSCAPE ECOL, V36, P2165, DOI 10.1007/s10980-020-00982-1
   Yu ZW, 2017, ECOL INDIC, V82, P152, DOI 10.1016/j.ecolind.2017.07.002
   Yu ZT, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-20935-8
   Yuan, 2014, J TIANJIN U SOCIAL S
   Zhang AiYin Zhang AiYin, 2019, Journal of Beijing Forestry University, V41, P1
   Zheng YM, 2022, SUSTAIN CITIES SOC, V76, DOI 10.1016/j.scs.2021.103338
   Zhilin MA, 2010, ECOL ENV SCI
   Zhou DC, 2018, SCI TOTAL ENVIRON, V628-629, P415, DOI 10.1016/j.scitotenv.2018.02.074
   Zölch T, 2016, URBAN FOR URBAN GREE, V20, P305, DOI 10.1016/j.ufug.2016.09.011
NR 76
TC 17
Z9 17
U1 20
U2 117
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 1083-8155
EI 1573-1642
J9 URBAN ECOSYST
JI Urban Ecosyst.
PD AUG
PY 2022
VL 25
IS 4
BP 1181
EP 1198
DI 10.1007/s11252-022-01202-1
EA MAR 2022
PG 18
WC Biodiversity Conservation; Ecology; Environmental Sciences; Urban
   Studies
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology; Urban
   Studies
GA 2Y8WF
UT WOS:000767069800001
OA Green Submitted
DA 2025-01-10
ER

PT J
AU Wong-Parodi, G
   Garfin, DR
AF Wong-Parodi, Gabrielle
   Garfin, Dana Rose
TI Hurricane adaptation behaviors in Texas and Florida: exploring the roles
   of negative personal experience and subjective attribution to climate
   change
SO ENVIRONMENTAL RESEARCH LETTERS
LA English
DT Article
DE climate adaptation; vulnerability; local adaptation strategies; disaster
   preparedness
ID CHANGE MITIGATION; RISK PERCEPTION; PUBLIC PERCEPTIONS; NATURAL HAZARDS;
   PEOPLE; DETERMINANTS; DISASTERS; MODEL
AB Understanding the motivation to adopt personal household adaptation behaviors in the face of climate change-related hazards is essential for developing and implementing behaviorally realistic interventions that promote well-being and health. Escalating extreme weather events increase the number of those directly exposed and adversely impacted by climate change. But do people attribute these negative events to climate change? Such subjective attribution may be a cognitive process whereby the experience of negative climate-change-related events may increase risk perceptions and motivate people to act. Here we surveyed a representative sample of 1846 residents of Florida and Texas, many of whom had been repeatedly exposed to hurricanes on the Gulf Coast, facing the 2020 Atlantic hurricane season. We assessed prior hurricane negative personal experiences, climate-change-related subjective attribution (for hurricanes), risk appraisal (perceived probability and severity of a hurricane threat), hurricane adaptation appraisal (perceived efficacy of adaptation measures and self-efficacy to address the threat of hurricanes), and self-reported hurricane personal household adaptation. Our findings suggest that prior hurricane negative personal experiences and subjective attribution are associated with greater hurricane risk appraisal. Hurricane subjective attribution moderated the relationship between hurricane negative personal experiences and risk appraisal; in turn, negative hurricane personal experiences, hurricane risk appraisal, and adaptation appraisal were positively associated with self-reported hurricane personal adaptation behaviors. Subjective attribution may be associated with elevated perceived risk for specific climate hazards. Communications that help people understand the link between their negative personal experiences (e.g. hurricanes) and climate change may help guide risk perceptions and motivate protective actions, particularly in areas with repeated exposure to threats.
C1 [Wong-Parodi, Gabrielle] Stanford Univ, Dept Earth Syst Sci, Stanford, CA 94305 USA.
   [Wong-Parodi, Gabrielle] Stanford Univ, Woods Inst Environm, Stanford, CA 94305 USA.
   [Garfin, Dana Rose] Univ Calif Irvine, Sue & Bill Gross Sch Nursing, Irvine, CA USA.
   [Garfin, Dana Rose] Univ Calif Irvine, Program Publ Hlth, Irvine, CA USA.
C3 Stanford University; Stanford University; University of California
   System; University of California Irvine; University of California
   System; University of California Irvine
RP Wong-Parodi, G (corresponding author), Stanford Univ, Dept Earth Syst Sci, Stanford, CA 94305 USA.; Wong-Parodi, G (corresponding author), Stanford Univ, Woods Inst Environm, Stanford, CA 94305 USA.
EM gwongpar@stanford.edu
RI Garfin, Dana/AAY-4021-2020
OI Wong-Parodi, Gabrielle/0000-0001-5207-7489; Garfin, Dana
   Rose/0000-0002-0435-9307
FU National Science Foundation [BCS-1760764, SES1811883, BCS-1902925,
   SES-2030139]; National Center for Atmospheric Research - National
   Science Foundation [M0856145];  [K01 MD013910]; National Institute on
   Minority Health and Health Disparities [K01MD013910] Funding Source: NIH
   RePORTER
FX This research was supported by the National Science Foundation under
   Grants BCS-1760764, SES1811883, BCS-1902925, and SES-2030139 and the
   National Center for Atmospheric Research sponsored by the National
   Science Foundation under Cooperative Agreement No. M0856145. Dana Rose
   Garfin was supported by K01 MD013910.
CR Akerlof K, 2013, GLOBAL ENVIRON CHANG, V23, P81, DOI 10.1016/j.gloenvcha.2012.07.006
   Blennow K, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su132112055
   Blennow K, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0050182
   Bradford RA, 2012, NAT HAZARD EARTH SYS, V12, P2299, DOI 10.5194/nhess-12-2299-2012
   Brody SD, 2008, ENVIRON BEHAV, V40, P72, DOI 10.1177/0013916506298800
   Broomell SB, 2015, GLOBAL ENVIRON CHANG, V32, P67, DOI 10.1016/j.gloenvcha.2015.03.001
   Carman JP, 2020, GLOBAL ENVIRON CHANG, V61, DOI 10.1016/j.gloenvcha.2020.102062
   Cutter SL, 2018, ENVIRONMENT, V60, P16, DOI 10.1080/00139157.2018.1517518
   Demski C, 2017, CLIMATIC CHANGE, V140, P149, DOI 10.1007/s10584-016-1837-4
   Deng Y, 2017, SCI TOTAL ENVIRON, V581, P840, DOI 10.1016/j.scitotenv.2017.01.022
   Emanuel K, 2020, P NATL ACAD SCI USA, V117, P13194, DOI 10.1073/pnas.2007742117
   Gliem JA., 2003, 2003 MIDW RES PRACT, DOI DOI 10.1016/B978-0-444-88933-1.50023-4
   Grothmann T, 2005, GLOBAL ENVIRON CHANG, V15, P199, DOI 10.1016/j.gloenvcha.2005.01.002
   Ho MC, 2008, RISK ANAL, V28, P635, DOI 10.1111/j.1539-6924.2008.01040.x
   Hoogendoorn G, 2020, J RISK RES, V23, P1577, DOI 10.1080/13669877.2020.1749114
   Howe PD, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab466a
   IPCC, 2018, GLOB WARM 1 5C SUMM
   JANZ NK, 1984, HEALTH EDUC QUART, V11, P1, DOI 10.1177/109019818401100101
   Kellens W, 2013, RISK ANAL, V33, P24, DOI 10.1111/j.1539-6924.2012.01844.x
   Keller C, 2006, RISK ANAL, V26, P631, DOI 10.1111/j.1539-6924.2006.00773.x
   Klotzbach P., 2020, Extended range forecast of Atlantic seasonal hurricane activity and landfall strike probability for 2020
   Kossin James P, 2020, Proc Natl Acad Sci U S A, V117, P11975, DOI 10.1073/pnas.1920849117
   Lee GE, 2018, ANN AM ASSOC GEOGR, V108, P718
   Lujala P, 2015, LOCAL ENVIRON, V20, P489, DOI 10.1080/13549839.2014.887666
   Maloney EK, 2011, SOC PERSONAL PSYCHOL, V5, P206, DOI 10.1111/j.1751-9004.2011.00341.x
   Ogunbode CA, 2019, CLIM POLICY, V19, P703, DOI 10.1080/14693062.2018.1560242
   Ogunbode CA, 2019, GLOBAL ENVIRON CHANG, V54, P31, DOI 10.1016/j.gloenvcha.2018.11.005
   Osberghaus D, 2015, ECOL ECON, V110, P36, DOI 10.1016/j.ecolecon.2014.12.010
   Popova L, 2012, HEALTH EDUC BEHAV, V39, P455, DOI 10.1177/1090198111418108
   Reser JP., 2012, Public risk perceptions, understandings, and responses to climate change and natural disasters in Australia and Great Britain, P298
   Shi J, 2016, NAT CLIM CHANGE, V6, P759, DOI [10.1038/NCLIMATE2997, 10.1038/nclimate2997]
   Siegrist M, 2008, RISK ANAL, V28, P771, DOI 10.1111/j.1539-6924.2008.01049.x
   Sobel AH, 2016, SCIENCE, V353, P242, DOI 10.1126/science.aaf6574
   Spence A, 2011, NAT CLIM CHANGE, V1, P46, DOI [10.1038/nclimate1059, 10.1038/NCLIMATE1059]
   Stock A, 2021, INT J DISAST RISK SC, V12, P312, DOI 10.1007/s13753-021-00350-w
   Taber KS, 2018, RES SCI EDUC, V48, P1273, DOI 10.1007/s11165-016-9602-2
   Taylor A, 2014, RISK ANAL, V34, P1995, DOI 10.1111/risa.12234
   Thaker J, 2021, J ENVIRON PSYCHOL, V77, DOI 10.1016/j.jenvp.2021.101685
   Thompson RR, 2019, JAMA NETW OPEN, V2, DOI 10.1001/jamanetworkopen.2018.6228
   Tschakert P, 2010, ECOL SOC, V15
   U.S. Census Bureau, 2024, Historical Tables
   van der Linden S, 2015, J ENVIRON PSYCHOL, V41, P112, DOI 10.1016/j.jenvp.2014.11.012
   van Valkengoed AM, 2019, NAT CLIM CHANGE, V9, P158, DOI 10.1038/s41558-018-0371-y
   Weiner R, 2021, CLIMATIC CHANGE, V164, DOI 10.1007/s10584-021-03032-0
   Whitmarsh L, 2008, J RISK RES, V11, P351, DOI 10.1080/13669870701552235
   Witte K., 1996, Handbook of communication and emotion, P50
   Wong-Parodi G, 2022, J ENVIRON PSYCHOL, V79, DOI 10.1016/j.jenvp.2021.101728
   Wong-Parodi G, 2018, WEATHER CLIM SOC, V10, P747, DOI 10.1175/WCAS-D-17-0138.1
   Zanocco C, 2019, GLOBAL ENVIRON CHANG, V59, DOI 10.1016/j.gloenvcha.2019.101984
NR 49
TC 11
Z9 14
U1 5
U2 32
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 MAR 1
PY 2022
VL 17
IS 3
AR 034033
DI 10.1088/1748-9326/ac4858
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 ZJ7NX
UT WOS:000762491000001
PM 36506931
OA Green Accepted, gold, Green Published
DA 2025-01-10
ER

PT J
AU Nawaz, S
   Satterfield, T
AF Nawaz, Sara
   Satterfield, Terre
TI Climate solution or corporate co-optation? US and Canadian publics'
   views on agricultural gene editing
SO PLOS ONE
LA English
DT Article
ID GENETICALLY-MODIFIED FOOD; CONSUMER ACCEPTANCE; GREEN-REVOLUTION;
   BIOTECHNOLOGY; PERCEPTIONS; TRUST; POLITICS; POLICY; VALUES; GMOS
AB The dexterity and affordability of gene-editing technologies promise wide-ranging applications in agriculture. Aiming to take advantage of this, proponents emphasize benefits such as the climate-mitigating promises of gene editing. Critics, on the other hand, argue that gene editing will perpetuate industrialized forms of agriculture and its concomitant environmental and social problems. Across a representative sample of US and Canadian residents (n = 1478), we investigate public views and perceptions of agricultural gene editing. We advance existing survey-based studies, which tend to focus on whether knowledge, familiarity, trust, or perceptions of naturalness predict views on gene editing. Instead, we examine whether broader societal concerns about industrialized food systems-a key claim about genetic engineering launched by critics-predicts comfort with gene editing. We also explore the predictive power of views of climate change as an urgent problem, following proponent arguments. Survey results explore gene editing views in reference to specific cases (e.g., drought-tolerant wheat) and specific alternatives (e.g., versus pesticide use). We find that people critical of industrialized food systems were most likely to express overall absolute opposition to the technology, whereas those concerned with the imminence of climate change were more likely to support climate-relevant gene editing. Our findings suggest the need for further research into the conditions upon which public groups find gene editing compelling or not-namely, if applications enhance or counter industrial food systems, or offer particular climate adaptive benefits. Furthermore, we argue that attention to broader societal priorities in surveys of perceptions may help address calls for responsible research and innovation as concerns gene editing.
C1 [Nawaz, Sara; Satterfield, Terre] Univ British Columbia, Inst Resources Environm & Sustainabil, Vancouver, BC, Canada.
   [Nawaz, Sara] Univ Oxford, Inst Sci Innovat & Soc, Oxford, England.
C3 University of British Columbia; University of Oxford
RP Nawaz, S (corresponding author), Univ British Columbia, Inst Resources Environm & Sustainabil, Vancouver, BC, Canada.; Nawaz, S (corresponding author), Univ Oxford, Inst Sci Innovat & Soc, Oxford, England.
EM sara.a.nawaz@gmail.com
RI Nawaz, Sara/JTU-0895-2023
OI Nawaz, Sara/0000-0003-4337-1453
FU Genome British Columbia [SOC005]
FX Genome British Columbia SOC005.
CR Agresti A., 2010, Analysis of Ordinal Categorical Data
   Amin L, 2011, AFR J BIOTECHNOL, V10, P12435
   [Anonymous], 2019, Climate change and land
   [Anonymous], 2007, Science as Culture, DOI 10.1080/09505430701387953
   Bain C, 2020, AGR HUM VALUES, V37, P265, DOI 10.1007/s10460-019-09980-9
   Baron J, 1997, ORGAN BEHAV HUM DEC, V70, P1, DOI 10.1006/obhd.1997.2690
   Baron J, 2009, PSYCHOL LEARN MOTIV, V50, P133, DOI 10.1016/S0079-7421(08)00404-0
   BARTLETT MS, 1951, BIOMETRIKA, V38, P337, DOI 10.1093/biomet/38.3-4.337
   Bogner A, 2018, FRONT PLANT SCI, V9, DOI 10.3389/fpls.2018.01884
   Brooks S, 2005, SOCIOL RURALIS, V45, P360, DOI 10.1111/j.1467-9523.2005.00310.x
   Brown T. A., 2015, Confirmatory factor analysis for applied research
   Burgess MM, 2014, PUBLIC UNDERST SCI, V23, P48, DOI 10.1177/0963662512472160
   Burget M, 2017, SCI ENG ETHICS, V23, P1, DOI 10.1007/s11948-016-9782-1
   Capstick S, 2015, WIRES CLIM CHANGE, V6, P35, DOI 10.1002/wcc.321
   Carolan MS, 2010, THEOR CULT SOC, V27, P110, DOI 10.1177/0263276409350360
   Carroll D, 2017, YALE J BIOL MED, V90, P653
   Costa-Font M, 2008, FOOD POLICY, V33, P99, DOI 10.1016/j.foodpol.2007.07.002
   Cox E, 2020, NAT CLIM CHANGE, V10, P744, DOI 10.1038/s41558-020-0823-z
   de Wit MM, 2022, AGR HUM VALUES, V39, P733, DOI 10.1007/s10460-021-10284-0
   de Wit MM, 2020, ELEMENTA-SCI ANTHROP, V8, DOI 10.1525/elementa.405
   Diamond E, 2020, ENVIRON POLIT, V29, P1199, DOI 10.1080/09644016.2020.1740547
   Durant RF, 2005, EUR UNION POLIT, V6, P181, DOI 10.1177/1465116505051982
   Farhat S, 2019, SEMIN CELL DEV BIOL, V96, P91, DOI 10.1016/j.semcdb.2019.05.003
   Fiske AP, 1997, POLIT PSYCHOL, V18, P255, DOI 10.1111/0162-895X.00058
   Fitting E, 2006, AGR HUM VALUES, V23, P15, DOI 10.1007/s10460-004-5862-y
   Frewer L, 2004, FOOD CHEM TOXICOL, V42, P1181, DOI 10.1016/j.fct.2004.02.002
   Frewer LJ, 2016, CRIT REV FOOD SCI, V56, P1728, DOI 10.1080/10408398.2013.801337
   Frewer LJ, 2011, TRENDS FOOD SCI TECH, V22, P442, DOI 10.1016/j.tifs.2011.05.005
   Frewer LJ, 2013, TRENDS FOOD SCI TECH, V30, P142, DOI 10.1016/j.tifs.2013.01.003
   Gaskell G, 2004, RISK ANAL, V24, P185, DOI 10.1111/j.0272-4332.2004.00421.x
   Giménez EH, 2011, J PEASANT STUD, V38, P109, DOI 10.1080/03066150.2010.538578
   Gray K, 2016, PERSPECT PSYCHOL SCI, V11, P325, DOI 10.1177/1745691616635598
   Gregory R, 2021, CLIMATIC CHANGE, V166, DOI 10.1007/s10584-021-03102-3
   Hartley S, 2016, PLOS BIOL, V14, DOI 10.1371/journal.pbio.1002453
   Hartung F, 2014, PLANT J, V78, P742, DOI 10.1111/tpj.12413
   Helliwell R, 2019, AGR HUM VALUES, V36, P779, DOI 10.1007/s10460-019-09956-9
   House L., 2004, AgBioForum, V7, P113
   Jacobsen SE, 2013, AGRON SUSTAIN DEV, V33, P651, DOI 10.1007/s13593-013-0138-9
   Jansen K, 2015, J PEASANT STUD, V42, P213, DOI 10.1080/03066150.2014.945166
   Johnson BB, 2020, J RISK RES, V23, P1467, DOI 10.1080/13669877.2019.1687577
   KAISER HF, 1970, PSYCHOMETRIKA, V35, P401, DOI 10.1007/BF02291817
   Kato-Nitta N, 2019, PALGR COMMUN, V5, DOI 10.1057/s41599-019-0328-4
   Kiss SJ, 2020, CAN J POLIT SCI, V53, P439, DOI 10.1017/S0008423920000177
   Kjeldaas S, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13147643
   Kofler N, 2018, SCIENCE, V362, P527, DOI 10.1126/science.aat4612
   Leiserowitz A, 2006, CLIMATIC CHANGE, V77, P45, DOI 10.1007/s10584-006-9059-9
   Libarkin JC, 2018, CLIMATIC CHANGE, V150, P403, DOI 10.1007/s10584-018-2279-y
   Lucht JM, 2015, VIRUSES-BASEL, V7, P4254, DOI 10.3390/v7082819
   Lusser M, 2013, NEW BIOTECHNOL, V30, P437, DOI 10.1016/j.nbt.2013.02.004
   Macnaghten P., 2015, GOVERNING AGR SUSTAI, DOI 10.4324/9781315709468
   Macnaghten P, 2016, J RESPONSIBLE INNOV, V3, P282, DOI 10.1080/23299460.2016.1255700
   Macnaghten P, 2016, ESSAYS BIOCHEM, V60, P347, DOI 10.1042/EBC20160048
   Marquart-Pyatt ST, 2014, GLOBAL ENVIRON CHANG, V29, P246, DOI 10.1016/j.gloenvcha.2014.10.004
   Massel K, 2021, THEOR APPL GENET, V134, P1691, DOI 10.1007/s00122-020-03764-0
   McAfee K, 2003, GEOFORUM, V34, P203, DOI 10.1016/S0016-7185(02)00089-1
   McComas KA, 2014, APPETITE, V78, P8, DOI 10.1016/j.appet.2014.02.006
   Mielby H, 2013, AGR HUM VALUES, V30, P471, DOI 10.1007/s10460-013-9430-1
   Muringai V, 2020, CAN J AGR ECON, V68, P47, DOI 10.1111/cjag.12221
   Myers TA, 2013, NAT CLIM CHANGE, V3, P343, DOI [10.1038/NCLIMATE1754, 10.1038/nclimate1754]
   Myskja BK, 2020, SCI ENG ETHICS, V26, P2601, DOI 10.1007/s11948-020-00222-4
   Nawaz S., PRECISIONTHREE PERCE
   Nawaz S, 2020, ELEMENTA-SCI ANTHROP, V8, DOI 10.1525/elementa.429
   NBAB (Norwegian Biotechnology Advisory Board), 2018, FORWARD LOOKING REGU
   Onyekachi OG, 2019, EFFECT CLIMATE CHANG, DOI [10.5772/intechopen.82681, DOI 10.5772/INTECHOPEN.82681]
   Owen R., 2013, RESPONSIBLE INNOVATI, P27, DOI DOI 10.1002/9781118551424.CH2
   Patel R, 2013, J PEASANT STUD, V40, P1, DOI 10.1080/03066150.2012.719224
   Patel R, 2009, J PEASANT STUD, V36, P663, DOI 10.1080/03066150903143079
   Pingali PL, 2012, P NATL ACAD SCI USA, V109, P12302, DOI 10.1073/pnas.0912953109
   Poortinga W, 2005, RISK ANAL, V25, P199, DOI 10.1111/j.0272-4332.2005.00579.x
   Poortinga W, 2011, GLOBAL ENVIRON CHANG, V21, P1015, DOI 10.1016/j.gloenvcha.2011.03.001
   Rose KM, 2020, ENVIRON COMMUN, V14, P1017, DOI 10.1080/17524032.2019.1710227
   Royzman EB, 2020, PERSPECT PSYCHOL SCI, V15, P250, DOI 10.1177/1745691619873550
   Scott SE, 2016, PERSPECT PSYCHOL SCI, V11, P315, DOI 10.1177/1745691615621275
   Searchinger T., 2019, CREATING SUSTAINABLE
   SHAPIRO SS, 1965, BIOMETRIKA, V52, P591, DOI 10.2307/2333709
   Shew AM, 2018, GLOB FOOD SECUR-AGR, V19, P71, DOI 10.1016/j.gfs.2018.10.005
   Shi JR, 2017, PLANT BIOTECHNOL J, V15, P207, DOI 10.1111/pbi.12603
   Siegrist M, 2000, RISK ANAL, V20, P195, DOI 10.1111/0272-4332.202020
   St-Laurent GP, 2018, CLIMATIC CHANGE, V151, P573, DOI 10.1007/s10584-018-2310-3
   Stone GD, 2002, CURR ANTHROPOL, V43, P611, DOI 10.1086/341532
   Tetlock PE, 2017, AM ECON REV, V107, P96, DOI 10.1257/aer.p20171110
   Thomas M, 2015, GLOBAL ENVIRON CHANG, V33, P71, DOI 10.1016/j.gloenvcha.2015.04.009
   van Mil A., 2017, POTENTIAL USES GENET
   Vanloqueren G, 2009, RES POLICY, V38, P971, DOI 10.1016/j.respol.2009.02.008
   Waltz E, 2015, NAT BIOTECHNOL, V33, P326, DOI 10.1038/nbt0415-326c
   Wang LL, 2017, PROG MOL BIOL TRANSL, V149, P187, DOI 10.1016/bs.pmbts.2017.03.010
   Wunderlich S, 2015, ADV NUTR, V6, P842, DOI 10.3945/an.115.008870
   Yadav Reena., 2021, MICROBIOMES GLOBAL C, P267, DOI DOI 10.1007/978-981-33-4508-9_15
   Yu WQ, 2019, BMC PLANT BIOL, V19, DOI 10.1186/s12870-019-1939-z
NR 89
TC 5
Z9 7
U1 0
U2 12
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
PY 2022
VL 17
IS 3
AR e0265635
DI 10.1371/journal.pone.0265635
PG 19
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA 1R8XY
UT WOS:000803647900032
PM 35313327
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Neale, DB
   Zimin, A
   Zaman, S
   Scott, AD
   Shrestha, B
   Workman, RE
   Puiu, D
   Allen, BJ
   Moore, ZJ
   Sekhwal, MK
   De La Torre, AR
   McGuire, PE
   Burns, E
   Timp, W
   Wegrzyn, JL
   Salzberg, SL
AF Neale, David B.
   Zimin, Aleksey, V
   Zaman, Sumaira
   Scott, Alison D.
   Shrestha, Bikash
   Workman, Rachael E.
   Puiu, Daniela
   Allen, Brian J.
   Moore, Zane J.
   Sekhwal, Manoj K.
   De La Torre, Amanda R.
   McGuire, Patrick E.
   Burns, Emily
   Timp, Winston
   Wegrzyn, Jill L.
   Salzberg, Steven L.
TI Assembled and annotated 26.5 Gbp coast redwood genome: a resource for
   estimating evolutionary adaptive potential and investigating hexaploid
   origin
SO G3-GENES GENOMES GENETICS
LA English
DT Article
DE genome assembly and annotation; coast redwood; Sequoia sempervirens;
   conifer; gymnosperm; hexaploid genome
ID PICEA-GLAUCA GENOME; SEQUOIA-SEMPERVIRENS; FUNCTIONAL-ANALYSIS;
   SEQUENCE; GENE; ARABIDOPSIS; POLYPLOIDY; EXPRESSION; ALIGNMENT;
   RETROTRANSPOSONS
AB Sequencing, assembly, and annotation of the 26.5 Gbp hexaploid genome of coast redwood (Sequoia sempervirens) was completed leading toward discovery of genes related to climate adaptation and investigation of the origin of the hexaploid genome. Deep-coverage short-read Illumina sequencing data from haploid tissue from a single seed were combined with long-read Oxford Nanopore Technologies sequencing data from diploid needle tissue to create an initial assembly, which was then scaffolded using proximity ligation data to produce a highly contiguous final assembly, SESE 2.1, with a scaffold N50 size of 44.9Mbp. The assembly included several scaffolds that span entire chromosome arms, confirmed by the presence of telomere and centromere sequences on the ends of the scaffolds. The structural annotation produced 118,906 genes with 113 containing introns that exceed 500Kbp in length and one reaching 2Mb. Nearly 19Gbp of the genome represented repetitive content with the vast majority characterized as long terminal repeats, with a 2.9:1 ratio of Copia to Gypsy elements that may aid in gene expression control. Comparison of coast redwood to other conifers revealed species-specific expansions for a plethora of abiotic and biotic stress response genes, including those involved in fungal disease resistance, detoxification, and physical injury/structural remodeling and others supporting flavonoid biosynthesis. Analysis of multiple genes that exist in triplicate in coast redwood but only once in its diploid relative, giant sequoia, supports a previous hypothesis that the hexaploidy is the result of autopolyploidy rather than any hybridizations with separate but closely related conifer species.
C1 [Neale, David B.; Scott, Alison D.; Allen, Brian J.; Moore, Zane J.; McGuire, Patrick E.] Univ Calif Davis, Dept Plant Sci, One Shields Ave, Davis, CA 95616 USA.
   [Zimin, Aleksey, V; Puiu, Daniela; Timp, Winston; Salzberg, Steven L.] Johns Hopkins Univ, Dept Biomed Engn, Baltimore, MD 21218 USA.
   [Zimin, Aleksey, V; Puiu, Daniela; Timp, Winston; Salzberg, Steven L.] Johns Hopkins Univ, Ctr Computat Biol, Baltimore, MD 21211 USA.
   [Zaman, Sumaira; Shrestha, Bikash; Wegrzyn, Jill L.] Univ Connecticut, Dept Ecol & Evolutionary Biol, Storrs, CT 06269 USA.
   [Zaman, Sumaira] Univ Connecticut, Dept Comp Sci & Engn, Storrs, CT 06269 USA.
   [Workman, Rachael E.; Timp, Winston] Johns Hopkins Univ, Dept Mol Biol & Genet, Baltimore, MD 21205 USA.
   [Sekhwal, Manoj K.; De La Torre, Amanda R.] No Arizona Univ, Sch Forestry, Flagstaff, AZ 86011 USA.
   [Burns, Emily] Save Redwoods League, San Francisco, CA 94104 USA.
   [Wegrzyn, Jill L.] Univ Connecticut, Inst Syst Genom, Storrs, CT 06269 USA.
   [Salzberg, Steven L.] Johns Hopkins Univ, Dept Comp Sci, Baltimore, MD 21218 USA.
   [Salzberg, Steven L.] Johns Hopkins Univ, Dept Biostat, Baltimore, MD 21205 USA.
   [Scott, Alison D.] Max Planck Inst Plant Breeding Res, Dept Chromosome Biol, D-50829 Cologne, Nrw, Germany.
   [Burns, Emily] Sky Isl Alliance, 406 S 4th Ave, Tucson, AZ 85701 USA.
C3 University of California System; University of California Davis; Johns
   Hopkins University; Johns Hopkins University; University of Connecticut;
   University of Connecticut; Johns Hopkins University; Northern Arizona
   University; University of Connecticut; Johns Hopkins University; Johns
   Hopkins University; Max Planck Society
RP Neale, DB; McGuire, PE (corresponding author), Univ Calif Davis, Dept Plant Sci, One Shields Ave, Davis, CA 95616 USA.
EM dbneale@ucdavis.edu; pemcguire@ucdavis.edu
RI Sekhwal, Manoj/HHZ-1661-2022; Wegrzyn, Jill/H-3745-2019; Timp,
   Winston/B-5215-2008; Salzberg, Steven/F-6162-2011
FU Save the Redwoods League, San Francisco, CA, USA [127]; HPC Facility
   within the Institute for Systems Genomics at the University of
   Connecticut, Storrs, CT, USA; NSF [SIBR 1943371, IOS-1744309]; USDA NIFA
   grant [ARZZ19-0258]; NIH [R44-Gm134994, R01 HG006677]; National Human
   Genome Research Institute [R01HG006677] Funding Source: NIH RePORTER
FX This work was supported by grant #127 from Save the Redwoods League, San
   Francisco, CA, USA, with special recognition to Ralph Eschenbach and
   Carol Joy Provan. Annotation and comparative genomics analysis were
   supported by the HPC Facility within the Institute for Systems Genomics
   at the University of Connecticut, Storrs, CT, USA. B.S. was supported by
   NSF grant SIBR 1943371. M.K.S. was supported by USDA NIFA grant
   ARZZ19-0258 awarded to A.R.D.L.T., W.T., and R.E.W. were supported in
   part by NIH grant R44-Gm134994. W.T. has two patents (USPTO 8,748,091
   and 8,394,584) licensed to Oxford Nanopore Technologies. S.L.S., A.V.Z.,
   and D.P. were supported in part by NIH grant R01 HG006677 and by NSF
   grant IOS-1744309.
CR Ahuja M. R., 2017, Biodiversity and Conservation of Woody Plants, Sustainable Development and Biodiversity 17, V17, P69
   Ahuja MR, 2005, SILVAE GENET, V54, P59, DOI 10.1515/sg-2005-0010
   Ahuja MR, 2002, SILVAE GENET, V51, P93
   [Anonymous], 2011, SICKLE SLIDING WINDO
   [Anonymous], 2008, Repeatmodeler open-1.0
   Apweiler R, 2004, NUCLEIC ACIDS RES, V32, pD115, DOI [10.1093/nar/gkh131, 10.1093/nar/gkw1099]
   Baduel P, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-13730-0
   Barbour MichaelG., 2001, Coast Redwood: A Natural and Cultural History
   Baucom RS, 2009, PLOS GENET, V5, DOI 10.1371/journal.pgen.1000732
   Baulin EF, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0233978
   Birol I, 2013, BIOINFORMATICS, V29, P1492, DOI 10.1093/bioinformatics/btt178
   Breidenbach N, 2020, SCI DATA, V7, DOI 10.1038/s41597-020-00576-1
   Burns E.E., 2018, State of Redwoods Conservation Report: a Tale of Two Forests, Coast Redwoods, Giant Sequoia
   Caballero M, 2019, GENOM PROTEOM BIOINF, V17, P305, DOI 10.1016/j.gpb.2019.04.002
   Casacuberta JM, 2003, GENE, V311, P1, DOI 10.1016/S0378-1119(03)00557-2
   Celedon JM, 2019, NEW PHYTOL, V224, P1444, DOI 10.1111/nph.15984
   Chamala S, 2013, SCIENCE, V342, P1516, DOI 10.1126/science.1241130
   Chen XB, 2003, PLANT CELL, V15, P1170, DOI 10.1105/tpc.010926
   COLEMAN GD, 1993, PLANT PHYSIOL, V102, P53, DOI 10.1104/pp.102.1.53
   Danecek P, 2011, BIOINFORMATICS, V27, P2156, DOI 10.1093/bioinformatics/btr330
   De La Torre AR, 2022, PLANT J, V109, P7, DOI 10.1111/tpj.15592
   Edgar RC, 2004, NUCLEIC ACIDS RES, V32, P1792, DOI 10.1093/nar/gkh340
   Edgar RC, 2010, BIOINFORMATICS, V26, P2460, DOI 10.1093/bioinformatics/btq461
   Emms DM, 2019, GENOME BIOL, V20, DOI 10.1186/s13059-019-1832-y
   Falk T, 2018, DATABASE-OXFORD, DOI 10.1093/database/bay084
   Farjon A., 2013, The IUCN Red List of Threatened Species 2013, DOI [DOI 10.2305/IUCN.UK.2013-1.RLTS.T34051A2841558.EN, 10.2305/IUCN.UK.2013-1.RLTS.T34025A2840746.en]
   Gremme G, 2005, INFORM SOFTWARE TECH, V47, P965, DOI 10.1016/j.infsof.2005.09.005
   Guttman DS, 2001, MOL PLANT MICROBE IN, V14, P145, DOI 10.1094/MPMI.2001.14.2.145
   Hart AJ, 2020, MOL ECOL RESOUR, V20, P591, DOI 10.1111/1755-0998.13106
   Heyn P, 2015, BIOESSAYS, V37, P148, DOI 10.1002/bies.201400138
   Hirayoshi I., 1943, Adv Zool Bot, V2, P73
   Hoff KJ, 2016, BIOINFORMATICS, V32, P767, DOI 10.1093/bioinformatics/btv661
   Howe KL, 2020, NUCLEIC ACIDS RES, V48, pD689, DOI 10.1093/nar/gkz890
   Hsu YH, 2017, PLANT J, V89, P325, DOI 10.1111/tpj.13387
   Hu Gang, 2019, Curr Protoc Protein Sci, V95, pe71, DOI 10.1002/cpps.71
   Jeong YM, 2006, PLANT PHYSIOL, V140, P196, DOI 10.1104/pp.105.071316
   Joly-Lopez Z, 2017, FRONT PLANT SCI, V8, DOI 10.3389/fpls.2017.02027
   Jones P, 2014, BIOINFORMATICS, V30, P1236, DOI 10.1093/bioinformatics/btu031
   Kalyaanamoorthy S, 2017, NAT METHODS, V14, P587, DOI [10.1038/NMETH.4285, 10.1038/nmeth.4285]
   Katoh K, 2014, METHODS MOL BIOL, V1079, P131, DOI 10.1007/978-1-62703-646-7_8
   KHOSHOO TN, 1959, EVOLUTION, V13, P24, DOI 10.2307/2405943
   Kim D, 2019, NAT BIOTECHNOL, V37, P907, DOI 10.1038/s41587-019-0201-4
   Kimura Y, 2001, PLANT CELL PHYSIOL, V42, P1345, DOI 10.1093/pcp/pce171
   Kumar S, 2018, MOL BIOL EVOL, V35, P1547, DOI 10.1093/molbev/msy096
   Kuser J. E., 1995, Forest Genetic Resources, P21
   Kuzmin DA, 2019, BMC BIOINFORMATICS, V20, DOI 10.1186/s12859-018-2570-y
   Lai CP, 2017, PLANT MOL BIOL, V95, P181, DOI 10.1007/s11103-017-0648-y
   Lanner R.M., 1999, CONIFERS CALIFORNIA
   Li H, 2009, BIOINFORMATICS, V25, P2078, DOI 10.1093/bioinformatics/btp352
   Li ST, 2014, PLANT SIGNAL BEHAV, V9, DOI 10.4161/psb.27522
   Lorimer CG, 2009, FOREST ECOL MANAG, V258, P1038, DOI 10.1016/j.foreco.2009.07.008
   Manai J, 2013, BioTechnologia J Biotechnol Comput Biol Bionanotechnol, V94, P239
   Marçais G, 2018, PLOS COMPUT BIOL, V14, DOI 10.1371/journal.pcbi.1005944
   Marcais G, 2011, BIOINFORMATICS, V27, P764, DOI 10.1093/bioinformatics/btr011
   Matasci N, 2014, GIGASCIENCE, V3, DOI 10.1186/2047-217X-3-17
   Minh BQ, 2020, MOL BIOL EVOL, V37, P1530, DOI 10.1093/molbev/msaa015
   Monat Cecile, 2016, Mob Genet Elements, V6, pe1241050, DOI 10.1080/2159256X.2016.1241050
   Montojo Jason, 2014, F1000Res, V3, P153, DOI 10.12688/f1000research.4572.1
   Mosca E, 2019, G3-GENES GENOM GENET, V9, P2039, DOI 10.1534/g3.119.400083
   Neale DB, 2017, G3-GENES GENOM GENET, V7, P3157, DOI 10.1534/g3.117.300078
   Neale DB, 2014, GENOME BIOL, V15, DOI 10.1186/gb-2014-15-3-r59
   Ni MH, 2020, CARBOHYD RES, V498, DOI 10.1016/j.carres.2020.108172
   Nystedt B, 2013, NATURE, V497, P579, DOI 10.1038/nature12211
   Ou SJ, 2018, PLANT PHYSIOL, V176, P1410, DOI 10.1104/pp.17.01310
   Parra G, 2011, NUCLEIC ACIDS RES, V39, P5328, DOI 10.1093/nar/gkr043
   Peña MJ, 2004, PLANT PHYSIOL, V134, P443, DOI 10.1104/pp.103.027508
   Putnam NH, 2016, GENOME RES, V26, P342, DOI 10.1101/gr.193474.115
   Quinlan AR, 2010, BIOINFORMATICS, V26, P841, DOI 10.1093/bioinformatics/btq033
   Raj M, 2005, SILVAE GENET, V54, P126, DOI 10.1515/sg-2005-0020
   Rath M, 2010, PLANT SOIL, V334, P137, DOI 10.1007/s11104-010-0373-7
   Raudvere U, 2019, NUCLEIC ACIDS RES, V47, pW191, DOI 10.1093/nar/gkz369
   Richardson LGL, 2011, PLANT SIGNAL BEHAV, V6, P1897, DOI 10.4161/psb.6.12.18023
   Rognes T, 2016, PEERJ, V4, DOI 10.7717/peerj.2584
   Rose AB, 2019, FRONT GENET, V9, DOI 10.3389/fgene.2018.00672
   Savolainen O, 2007, CURR OPIN PLANT BIOL, V10, P162, DOI 10.1016/j.pbi.2007.01.011
   SAYLOR LC, 1970, CYTOLOGIA, V35, P294, DOI 10.1508/cytologia.35.294
   Scott AD, 2020, G3-GENES GENOM GENET, V10, P3907, DOI 10.1534/g3.120.401612
   Scott AD, 2016, NEW PHYTOL, V211, P186, DOI 10.1111/nph.13930
   Seppey M, 2019, METHODS MOL BIOL, V1962, P227, DOI 10.1007/978-1-4939-9173-0_14
   Smit AFA, 2019, REPEATMASKER 4 0 9
   STEBBINS GL, 1948, SCIENCE, V108, P95, DOI 10.1126/science.108.2796.95
   Stevens KA, 2016, GENETICS, V204, P1613, DOI 10.1534/genetics.116.193227
   Su Gang, 2014, Curr Protoc Bioinformatics, V47, DOI 10.1002/0471250953.bi0813s47
   Volkov V, 2021, PLANTS-BASEL, V10, DOI 10.3390/plants10010038
   Vurture GW, 2017, BIOINFORMATICS, V33, P2202, DOI 10.1093/bioinformatics/btx153
   Warren RL, 2015, PLANT J, V83, P189, DOI 10.1111/tpj.12886
   Waterhouse RM, 2013, NUCLEIC ACIDS RES, V41, pD358, DOI 10.1093/nar/gks1116
   WEIR BS, 1984, EVOLUTION, V38, P1358, DOI [10.2307/2408641, 10.1111/j.1558-5646.1984.tb05657.x]
   Wheeler DL, 2005, PLANT PHYSIOL, V138, P1280, DOI 10.1104/pp.104.058842
   Workman R, 2018, Protocol Exchange, V00, P1, DOI [DOI 10.1038/PROTEX.2018.059, 10.1038/protex.2018.059, 10. 1038/protex.2018.059]
   Wu TD, 2005, BIOINFORMATICS, V21, P1859, DOI 10.1093/bioinformatics/bti310
   Xu SQ, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-09235-5
   Yang ZH, 2007, MOL BIOL EVOL, V24, P1586, DOI 10.1093/molbev/msm088
   Yang ZY, 2012, MOL PHYLOGENET EVOL, V64, P452, DOI 10.1016/j.ympev.2012.05.004
   Yuan JY, 2020, BMC BIOL, V18, DOI 10.1186/s12915-020-00909-x
   Zhang BP, 2017, PLANTS-BASEL, V6, DOI 10.3390/plants6040065
   Zhang MP, 2012, NAT PROTOC, V7, P467, DOI 10.1038/nprot.2011.455
   Zhang S J., 2020, GENOM PROTEOM BIOINF, V18, P321, DOI DOI 10.1016/j.gpb.2018.07.009
   Zimin A, 2014, GENETICS, V196, P875, DOI 10.1534/genetics.113.159715
   Zimin AV, 2017, GENOME RES, V27, P787, DOI 10.1101/gr.213405.116
   Zimin AV, 2013, BIOINFORMATICS, V29, P2669, DOI 10.1093/bioinformatics/btt476
NR 101
TC 21
Z9 22
U1 3
U2 20
PU OXFORD UNIV PRESS INC
PI CARY
PA JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA
SN 2160-1836
J9 G3-GENES GENOM GENET
JI G3-Genes Genomes Genet.
PD JAN
PY 2022
VL 12
IS 1
AR jkab380
DI 10.1093/g3journal/jkab380
EA DEC 2021
PG 13
WC Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Genetics & Heredity
GA YI3YD
UT WOS:000743786100013
OA Green Published
DA 2025-01-10
ER

PT J
AU Petkova, EP
   Dimitrova, LK
   Sera, F
   Gasparrini, A
AF Petkova, Elisaveta P.
   Dimitrova, Lyudmila K.
   Sera, Francesco
   Gasparrini, Antonio
TI Mortality attributable to heat and cold among the elderly in Sofia,
   Bulgaria
SO INTERNATIONAL JOURNAL OF BIOMETEOROLOGY
LA English
DT Article
DE Temperature; Heat; Cold; Mortality; Bulgaria
ID TIME-SERIES ANALYSIS; CARDIOVASCULAR MORTALITY; SEX-DIFFERENCES;
   AIR-POLLUTION; TEMPERATURE; RESPONSES; ASSOCIATIONS; EXERCISE; CITIES;
   WAVES
AB Although a number of epidemiological studies have examined the effects of non-optimal temperatures on mortality in Europe, evidence about the mortality risks associated with exposures to hot and cold temperatures in Bulgaria is scarce. This study provides evidence about mortality attributable to non-optimal temperatures in adults aged 65 and over in Sofia, Bulgaria, between 2000 and 2017. We quantified the relationship between the daily mean temperature and mortality in the total elderly adult population aged 65 and over, among males and females aged 65 and over, as well as individuals aged 65-84 and 85 years or older. We used a distributed lag non-linear model with a 25-day lag to fully capture the effects of both cold and hot temperatures and calculated the fractions of mortality attributable to mild and extreme hot and cold temperatures. Cold temperatures had a greater impact on mortality than hot temperatures during the studied period. Most of the temperature-attributable mortality was due to moderate cold, followed by moderate heat, extreme cold, and extreme heat. The total mortality attributable to non-optimal temperatures was greater among females compared to males and among individuals aged 85 and over compared to those aged 65 to 84. The findings of this study can serve as a foundation for future research and policy development aimed at characterizing and reducing the risks from temperature exposures among vulnerable populations in the country, climate adaptation planning and improved public health preparedness, and response to non-optimal temperatures.
C1 [Petkova, Elisaveta P.] Columbia Univ, Dept Earth & Environm Sci, New York, NY USA.
   [Dimitrova, Lyudmila K.] Prof Asen Zlatarov Univ, Dept Comp & Informat Technol, Burgas, Bulgaria.
   [Sera, Francesco; Gasparrini, Antonio] London Sch Hyg & Trop Med, Dept Publ Hlth Environm & Soc, London WC1H 9SH, England.
   [Gasparrini, Antonio] London Sch Hyg & Trop Med, Ctr Stat Methodol, London, England.
   [Gasparrini, Antonio] London Sch Hyg & Trop Med, Ctr Climate Change & Planetary Hlth, London, England.
C3 Columbia University; University of Burgas; University of London; London
   School of Hygiene & Tropical Medicine; University of London; London
   School of Hygiene & Tropical Medicine; University of London; London
   School of Hygiene & Tropical Medicine
RP Petkova, EP (corresponding author), Columbia Univ, Dept Earth & Environm Sci, New York, NY USA.
EM elisaveta.petkova@columbia.edu
RI Petkova, Elisaveta/V-2588-2019; Sera, Francesco/C-8176-2011; Gasparrini,
   Antonio/F-7627-2012
OI Dimitrova, Lyudmila/0000-0001-7006-8156; Sera,
   Francesco/0000-0002-8890-6848; Petkova, Elisaveta/0000-0003-3620-3232;
   Gasparrini, Antonio/0000-0002-2271-3568
FU Frontiers of Science Program at Columbia University; Medical Research
   Council-UK [MR/M022625/1]; Natural Environment Research Council UK
   [NE/R009384/1]; European Union [820655]; MRC [MR/R013349/1,
   MR/M022625/1] Funding Source: UKRI; NERC [NE/R009384/1] Funding Source:
   UKRI
FX This study was partially funded by the Frontiers of Science Program at
   Columbia University. In addition, AG and FS were supported by the
   Medical Research Council-UK (Grant ID: MR/M022625/1), the Natural
   Environment Research Council UK (Grant ID: NE/R009384/1), and the
   European Union's Horizon 2020 Project Exhaustion (Grant ID: 820655).
CR Aboubakri O, 2019, J THERM BIOL, V82, P76, DOI 10.1016/j.jtherbio.2019.03.013
   Achebak H, 2019, LANCET PLANET HEALTH, V3, pE297, DOI 10.1016/S2542-5196(19)30090-7
   Anderson BG, 2009, EPIDEMIOLOGY, V20, P205, DOI 10.1097/EDE.0b013e318190ee08
   ANDERSON GS, 1995, EUR J APPL PHYSIOL O, V71, P95, DOI 10.1007/BF00854965
   Armstrong B, 2019, ENVIRON HEALTH PERSP, V127, DOI 10.1289/EHP5430
   Åström DO, 2019, MEDICINA-LITHUANIA, V55, DOI 10.3390/medicina55080429
   Åström DO, 2018, INT J BIOMETEOROL, V62, P1777, DOI 10.1007/s00484-018-1556-9
   Atsumi A, 2013, CIRC J, V77, P1854, DOI 10.1253/circj.CJ-12-0916
   Bai L, 2014, SCI TOTAL ENVIRON, V485, P41, DOI 10.1016/j.scitotenv.2014.02.094
   Balmain BN, 2018, BIOMED RES INT, V2018, DOI 10.1155/2018/8306154
   Benmarhnia T, 2015, EPIDEMIOLOGY, V26, P781, DOI 10.1097/EDE.0000000000000375
   BITTEL J, 1975, J PHYSIOL-LONDON, V250, P475, DOI 10.1113/jphysiol.1975.sp011066
   Bunker A, 2016, EBIOMEDICINE, V6, P258, DOI 10.1016/j.ebiom.2016.02.034
   Curriero FC, 2002, AM J EPIDEMIOL, V155, P80, DOI 10.1093/aje/155.1.80
   Davídkovová H, 2014, BMC PUBLIC HEALTH, V14, DOI 10.1186/1471-2458-14-480
   Dufour A, 2007, EUR J APPL PHYSIOL, V100, P19, DOI 10.1007/s00421-007-0396-9
   FALK B, 1994, J APPL PHYSIOL, V76, P72, DOI 10.1152/jappl.1994.76.1.72
   Fouillet A, 2006, INT ARCH OCC ENV HEA, V80, P16, DOI 10.1007/s00420-006-0089-4
   Gagnon D, 2013, J APPL PHYSIOL, V114, P394, DOI 10.1152/japplphysiol.00877.2012
   Gagnon D, 2012, J PHYSIOL-LONDON, V590, P5963, DOI 10.1113/jphysiol.2012.240739
   Gagnon D, 2011, J PHYSIOL-LONDON, V589, P6205, DOI 10.1113/jphysiol.2011.219220
   Gasparrini A., 2020, DISTRIBUTED LAG LINE
   Gasparrini A, 2015, LANCET, V386, P369, DOI 10.1016/S0140-6736(14)62114-0
   Gasparrini A, 2014, BMC MED RES METHODOL, V14, DOI 10.1186/1471-2288-14-55
   Goggins WB, 2013, ENVIRON HEALTH-GLOB, V12, DOI 10.1186/1476-069X-12-59
   Graczyk D, 2019, THEOR APPL CLIMATOL, V136, P1259, DOI 10.1007/s00704-018-2554-x
   GRAHAM TE, 1988, MED SCI SPORT EXER, V20, pS185, DOI 10.1249/00005768-198810001-00017
   Hajat S, 2007, OCCUP ENVIRON MED, V64, P93, DOI 10.1136/oem.2006.029017
   Hajat S, 2010, J EPIDEMIOL COMMUN H, V64, P753, DOI 10.1136/jech.2009.087999
   Hoegh-Guldberg O., 2018, Global warming of 1.5C
   Hondula DM, 2014, INT J BIOMETEOROL, V58, P109, DOI 10.1007/s00484-012-0619-6
   Inoue Y, 1996, EUR J APPL PHYSIOL O, V74, P78, DOI 10.1007/BF00376498
   Kaltsatou A, 2018, J GERIATR MED GERONT, V4
   Keatinge WR, 2000, BRIT MED J, V321, P670, DOI 10.1136/bmj.321.7262.670
   Kenney WL, 1997, AM J PHYSIOL-HEART C, V272, pH1609, DOI 10.1152/ajpheart.1997.272.4.H1609
   Kenney WL, 2003, J APPL PHYSIOL, V95, P2598, DOI 10.1152/japplphysiol.00202.2003
   Kenney WL, 1996, J APPL PHYSIOL, V80, P512, DOI 10.1152/jappl.1996.80.2.512
   Kottek M, 2006, METEOROL Z, V15, P259, DOI 10.1127/0941-2948/2006/0130
   LANE K, 2018, INT J ENV RES PUB HE, V15
   Li GuoXing Li GuoXing, 2012, Journal of Environment and Health, V29, P483
   Liu CQ, 2015, AM J PHYSIOL-HEART C, V309, pH1793, DOI 10.1152/ajpheart.00199.2015
   Ma WJ, 2014, ENVIRON RES, V134, P127, DOI 10.1016/j.envres.2014.07.007
   McMichael AJ, 2008, INT J EPIDEMIOL, V37, P1121, DOI 10.1093/ije/dyn086
   Ministry of Environment and Water (MEW), 2019, NAT CLIM CHANGE AD S
   Moghadamnia MT, 2017, PEERJ, V5, DOI 10.7717/peerj.3574
   Nawrot TS, 2007, J EPIDEMIOL COMMUN H, V61, P146, DOI 10.1136/jech.2005.044263
   Ng CFS, 2016, GLOBAL ENVIRON CHANG, V39, P234, DOI 10.1016/j.gloenvcha.2016.05.006
   Nguyen JL, 2014, INDOOR AIR, V24, P103, DOI 10.1111/ina.12052
   Okazaki K, 2002, J APPL PHYSIOL, V93, P1630, DOI 10.1152/japplphysiol.00222.2002
   Orru H, 2017, INT J BIOMETEOROL, V61, P963, DOI 10.1007/s00484-016-1270-4
   Pascal M, 2018, ENVIRON INT, V121, P189, DOI 10.1016/j.envint.2018.08.049
   Pattenden S, 2003, J EPIDEMIOL COMMUN H, V57, P628, DOI 10.1136/jech.57.8.628
   Pfeifer K, 2020, INT J ENV RES PUB HE, V17, DOI 10.3390/ijerph17217719
   Qin RX, 2017, SCI TOTAL ENVIRON, V575, P1530, DOI 10.1016/j.scitotenv.2016.10.033
   Ren C, 2008, OCCUP ENVIRON MED, V65, P255, DOI 10.1136/oem.2007.033878
   Robine JM, 2008, CR BIOL, V331, P171, DOI 10.1016/j.crvi.2007.12.001
   ROCKLOV J, 2014, GLOBAL HEALTH ACTION, V7, P1
   Rodrigues M, 2019, INT J BIOMETEOROL, V63, P549, DOI 10.1007/s00484-019-01685-2
   SAGAWA S, 1988, J GERONTOL, V43, pM1, DOI 10.1093/geronj/43.1.M1
   Semenza JC, 1996, NEW ENGL J MED, V335, P84, DOI 10.1056/NEJM199607113350203
   Sheridan SC, 2004, B AM METEOROL SOC, V85, P1931, DOI 10.1175/BAMS-85-12-1931
   Shibasaki M., 2013, J Phys Fit Sport Med, DOI [10.7600/jpfsm.2.37, DOI 10.7600/JPFSM.2.37]
   Smith ET, 2019, SCI TOTAL ENVIRON, V647, P342, DOI 10.1016/j.scitotenv.2018.07.466
   Son JY, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab1cdb
   Son JY, 2016, INT J BIOMETEOROL, V60, P113, DOI 10.1007/s00484-015-1009-7
   Son JY, 2011, ENVIRON RES LETT, V6, DOI 10.1088/1748-9326/6/3/034027
   World Health Organization, 2019, ACT PLAN IMPR PUBL H
   Yang J, 2016, ENVIRON INT, V92-93, P232, DOI 10.1016/j.envint.2016.04.001
   Yanovich R, 2020, PHYSIOLOGY, V35, P177, DOI 10.1152/physiol.00035.2019
   Ye XF, 2012, ENVIRON HEALTH PERSP, V120, P19, DOI [10.1289/ehp.1003198, 10.1289/ehp.120-a19]
   Yu WW, 2011, HEART, V97, P1089, DOI 10.1136/hrt.2010.217166
   Zeng J, 2017, INT J ENV RES PUB HE, V14, DOI 10.3390/ijerph14111383
NR 72
TC 26
Z9 26
U1 3
U2 16
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 0020-7128
EI 1432-1254
J9 INT J BIOMETEOROL
JI Int. J. Biometeorol.
PD JUN
PY 2021
VL 65
IS 6
BP 865
EP 872
DI 10.1007/s00484-020-02064-y
EA JAN 2021
PG 8
WC Biophysics; Environmental Sciences; Meteorology & Atmospheric Sciences;
   Physiology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biophysics; Environmental Sciences & Ecology; Meteorology & Atmospheric
   Sciences; Physiology
GA SH5OM
UT WOS:000606159800002
PM 33416949
DA 2025-01-10
ER

PT J
AU Hahn, MB
   Kemp, C
   Ward-Waller, C
   Donovan, S
   Schmidt, JI
   Bauer, S
AF Hahn, Micah B.
   Kemp, Catherine
   Ward-Waller, Chelsea
   Donovan, Shannon
   Schmidt, Jennifer I.
   Bauer, Stephanie
TI Collaborative climate mitigation and adaptation planning with
   university, community, and municipal partners: a case study in
   Anchorage, Alaska
SO LOCAL ENVIRONMENT
LA English
DT Article
DE Climate change; climate adaptation; climate action planning;
   municipal-university collaboration; community engagement
ID INNOVATION; IMPACTS; PLANS
AB Cities around the world are creating formal planning documents proposing local actions to mitigate and prepare for the impacts of climate change. Despite a growing number of examples of such plans and "toolkits" that outline the process for undertaking these planning efforts, many cities are still struggling to know where to start. Furthermore, meta-analyses of existing climate action plans show that many suffer from similar limitations including lack of scientific input, failure to consider strategies across multiple sectors within local government, limited public involvement, narrow focus on mitigation, and lack of detail regarding implementation and monitoring. This paper describes our process for developing the Anchorage Climate Action Plan and our experience fusing a three-way partnership between the municipal government, a local university, and the broader Anchorage, Alaska community. We describe the nuts and bolts of our funding, leadership structure, and technical working sessions and reflect on the key structural, political, and social elements that catalysed plan development, adoption, and implementation. Our experience suggests that public support from municipal leaders, commitment from local experts, a dedicated steering committee, a diverse set of stakeholders, and a good working relationship with the local government officials (e.g. Assembly members or City Council) are critical to creating a successful framework for climate mitigation and adaptation planning in a community. Collaborative planning with a local university that prioritises community-engagement can support the development of a robust planning document that integrates local scientific expertise and is representative of the community it is meant to serve.
C1 [Hahn, Micah B.] Univ Alaska Anchorage, Inst Circumpolar Hlth Studies, 3211 Providence Dr,BOC3 270, Anchorage, AK 99508 USA.
   [Kemp, Catherine] Municipal Anchorage, Anchorage, AK USA.
   [Ward-Waller, Chelsea] Univ Alaska Anchorage, Anchorage, AK USA.
   [Donovan, Shannon] Univ Alaska Anchorage, Dept Geog & Environm Studies, Anchorage, AK USA.
   [Schmidt, Jennifer I.] Univ Alaska Anchorage, Inst Social & Econ Res, Anchorage, AK USA.
   [Bauer, Stephanie] Univ Alaska Anchorage, Dept Philosophy, Anchorage, AK USA.
C3 University of Alaska System; University of Alaska Anchorage; University
   of Alaska System; University of Alaska Anchorage; University of Alaska
   System; University of Alaska Anchorage; University of Alaska System;
   University of Alaska Anchorage; University of Alaska System; University
   of Alaska Anchorage
RP Hahn, MB (corresponding author), Univ Alaska Anchorage, Inst Circumpolar Hlth Studies, 3211 Providence Dr,BOC3 270, Anchorage, AK 99508 USA.
EM mbhahn@alaska.edu
OI Donovan, Shannon/0000-0002-8347-584X
FU University of Alaska Faculty Initiative Fund; University of Alaska
   Anchorage Center for Community Engagement and Learning Resilient Cities
   grant; Jack and Martha Roderick Sustainability Fund
FX This work was supported by the University of Alaska Faculty Initiative
   Fund; the University of Alaska Anchorage Center for Community Engagement
   and Learning Resilient Cities grant; and the Jack and Martha Roderick
   Sustainability Fund.
CR Allahwala A, 2013, J GEOGR, V112, P43, DOI 10.1080/00221341.2012.692702
   [Anonymous], 2018, NY TIMES
   ARNSTEIN SR, 1969, J AM I PLANNERS, V35, P216, DOI 10.1080/01944366908977225
   Baker I, 2012, LANDSCAPE URBAN PLAN, V107, P127, DOI 10.1016/j.landurbplan.2012.05.009
   Bassett E, 2010, J AM PLANN ASSOC, V76, P435, DOI 10.1080/01944363.2010.509703
   Bierbaum R, 2013, MITIG ADAPT STRAT GL, V18, P361, DOI 10.1007/s11027-012-9423-1
   Burton P, 2013, URBAN POLICY RES, V31, P399, DOI 10.1080/08111146.2013.778196
   Combest-Friedman C, 2019, CURR OPIN ENV SUST, V39, P160, DOI 10.1016/j.cosust.2019.10.006
   Curry Joanne E., 2016, METROPOLITAN U, V27
   Dessai S, 2004, CLIM POLICY, V4, P107
   Farrell C. R., 2018, IMAGINING ANCHORAGE, P374
   Furco A, 2010, PHI DELTA KAPPAN, V91, P16, DOI 10.1177/003172171009100504
   Haight Keagan, 2016, LEMON GROVE CLIMATE
   ICLEI, 2019, CLIM EQ
   ICMA, 2014, U PARTN LOC GOV INN
   Institute for Local Government and California Air Resources Board, 2010, HARN POW YOUR COMM A
   Jackson A, 2019, PLAN PRACT RES, V34, P318, DOI 10.1080/02697459.2019.1578917
   Koza M., 2000, EUR MANAG J, V18, P146, DOI DOI 10.1016/S0263-2373(99)00086-9
   Markon C., 2018, Impacts, Risks, and Adaptationin the United States: Fourth National Climate Assessment, Volume, VII, P1185, DOI [10.7930/NCA4.2018.CH, DOI 10.7930/NCA4.2018.CH26]
   Mastrandrea MD, 2010, CLIMATIC CHANGE, V100, P87, DOI 10.1007/s10584-010-9827-4
   Meeker D., 2017, A synthesis of climate adaptation planning needs in Alaska Native communities
   Moser S.C., 2012, Identifying and Overcoming Barriers to Climate Change Adaptation in San Francisco Bay: Results from Case Studies
   Moss RH, 2013, SCIENCE, V342, P696, DOI 10.1126/science.1239569
   Norris KC, 2007, ETHNIC DIS, V17, P27
   Pearce TD, 2009, POLAR RES, V28, P10, DOI 10.1111/j.1751-8369.2008.00094.x
   Portland Development Commission, 2005, PUBL PART MAN
   Preston BL, 2011, MITIG ADAPT STRAT GL, V16, P407, DOI 10.1007/s11027-010-9270-x
   Schlossberg M, 2018, URBAN BOOK SERIES, P251, DOI 10.1007/978-3-319-55967-4_17
   Shi LD, 2015, J AM PLANN ASSOC, V81, P191, DOI 10.1080/01944363.2015.1074526
   Stults M, 2017, MITIG ADAPT STRAT GL, V22, P1249, DOI 10.1007/s11027-016-9725-9
   Tang ZH, 2010, J ENVIRON PLANN MAN, V53, P41, DOI 10.1080/09640560903399772
   U.S.Census Bureau, 2019, AM FACTFINDER
   Wheeler S, 2008, J AM PLANN ASSOC, V74, P481, DOI 10.1080/01944360802377973
   Wiewel W, 1998, J PLAN EDUC RES, V17, P291, DOI 10.1177/0739456X9801700404
   Wiseman J, 2010, INT J CLIM CHANG STR, V2, P134, DOI 10.1108/17568691011040399
   Woodru SC, 2016, NAT CLIM CHANGE, V6, P796, DOI 10.1038/NCLIMATE3012
   Yuen Tina., 2017, GUIDE EQUITABLE COMM
NR 37
TC 7
Z9 11
U1 2
U2 24
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 648
EP 665
DI 10.1080/13549839.2020.1811655
EA AUG 2020
PG 18
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:000564121600001
DA 2025-01-10
ER

PT J
AU Olazcuaga, L
   Loiseau, A
   Parrinello, H
   Paris, M
   Fraimout, A
   Guedot, C
   Diepenbrock, LM
   Kenis, M
   Zhang, JP
   Chen, X
   Borowiec, N
   Facon, B
   Vogt, H
   Price, DK
   Vogel, H
   Prud'homme, B
   Estoup, A
   Gautier, M
AF Olazcuaga, Laure
   Loiseau, Anne
   Parrinello, Hugues
   Paris, Mathilde
   Fraimout, Antoine
   Guedot, Christelle
   Diepenbrock, Lauren M.
   Kenis, Marc
   Zhang, Jinping
   Chen, Xiao
   Borowiec, Nicolas
   Facon, Benoit
   Vogt, Heidrun
   Price, Donald K.
   Vogel, Heiko
   Prud'homme, Benjamin
   Estoup, Arnaud
   Gautier, Mathieu
TI A Whole-Genome Scan for Association with Invasion Success in the Fruit
   Fly <i>Drosophila suzukii</i> Using Contrasts of Allele Frequencies
   Corrected for Population Structure
SO MOLECULAR BIOLOGY AND EVOLUTION
LA English
DT Article
DE biological invasions; Drosophila suzukii; GWAS; BayPass; Pool-Seq
ID INTRODUCED POPULATIONS; CLIMATIC ADAPTATION; EVOLUTION; SELECTION;
   POLYMORPHISM; GENETICS; DIVERGENCE; SEQUENCE; DIAPAUSE; ECOLOGY
AB Evidence is accumulating that evolutionary changes are not only common during biological invasions but may also contribute directly to invasion success. The genomic basis of such changes is still largely unexplored. Yet, understanding the genomic response to invasion may help to predict the conditions under which invasiveness can be enhanced or suppressed. Here, we characterized the genome response of the spotted wing drosophila Drosophila suzukii during the worldwide invasion of this pest insect species, by conducting a genome-wide association study to identify genes involved in adaptive processes during invasion. Genomic data from 22 population samples were analyzed to detect genetic variants associated with the status (invasive versus native) of the sampled populations based on a newly developed statistic, we called C-2, that contrasts allele frequencies corrected for population structure. We evaluated this new statistical framework using simulated data sets and implemented it in an upgraded version of the program BAYPASS. We identified a relatively small set of single-nucleotide polymorphisms that show a highly significant association with the invasive status of D. suzukii populations. In particular, two genes, RhoGEF64C and cpo, contained single-nucleotide polymorphisms significantly associated with the invasive status in the two separate main invasion routes of D. suzukii. Our methodological approaches can be applied to any other invasive species, and more generally to any evolutionary model for species characterized by nonequilibrium demographic conditions for which binary covariables of interest can be defined at the population level.
C1 [Olazcuaga, Laure; Loiseau, Anne; Fraimout, Antoine; Estoup, Arnaud; Gautier, Mathieu] INRAE, UMR CBGP, IRD, Cirad,Montpellier SupAgro, Montferrier Sur Lez, France.
   [Parrinello, Hugues] Univ Montpellier, INSERM, CNRS, Biocampus Montpellier,MGX, Montpellier, France.
   [Paris, Mathilde; Prud'homme, Benjamin] Aix Marseille Univ, IBDM, CNRS, Marseille, France.
   [Guedot, Christelle] Univ Wisconsin, Dept Entomol, Madison, WI 53706 USA.
   [Diepenbrock, Lauren M.] NC State Univ, Dept Entomol & Plant Pathol, Raleigh, NC USA.
   [Kenis, Marc] CABI, Delemont, Switzerland.
   [Zhang, Jinping] Chinese Acad Agr Sci, MoA CABI Joint Lab Biosafety, Beixiaguan, Haidian Qu, Peoples R China.
   [Chen, Xiao] Yunnan Agr Univ, Coll Plant Protect, Kunming, Yunnan, Peoples R China.
   [Borowiec, Nicolas] Univ Cote Azur, Sophia Antipolis, UMR INRAE, Sophia Agrobiotech Inst,CNRS, Nice, France.
   [Facon, Benoit] INRAE, UMR Peuplements Vegetaux & Bioagresseurs Milieu T, St Pierre, La Reunion, France.
   [Vogt, Heidrun] Julius Kuhn Inst JKI, Fed Res Ctr Cultivated Plants, Inst Plant Protect Fruit Crops & Viticulture, Dossenheim, Germany.
   [Price, Donald K.] Univ Nevada, Sch Life Sci, Las Vegas, NV 89154 USA.
   [Vogel, Heiko] Max Planck Inst Chem Ecol, Dept Entomol, Jena, Germany.
C3 CIRAD; Institut de Recherche pour le Developpement (IRD); INRAE;
   Institut Agro; Montpellier SupAgro; Institut National de la Sante et de
   la Recherche Medicale (Inserm); Centre National de la Recherche
   Scientifique (CNRS); Universite de Montpellier; Centre National de la
   Recherche Scientifique (CNRS); Aix-Marseille Universite; University of
   Wisconsin System; University of Wisconsin Madison; North Carolina State
   University; Chinese Academy of Agricultural Sciences; Yunnan
   Agricultural University; Universite Cote d'Azur; INRAE; Centre National
   de la Recherche Scientifique (CNRS); INRAE; Julius Kuhn-Institut; Nevada
   System of Higher Education (NSHE); University of Nevada Las Vegas; Max
   Planck Society
RP Estoup, A; Gautier, M (corresponding author), INRAE, UMR CBGP, IRD, Cirad,Montpellier SupAgro, Montferrier Sur Lez, France.
EM arnaud.estoup@inrae.fr; mathieu.gautier@inrae.fr
RI Kenis, Marc/HMD-4929-2023; Olazcuaga, Laure/AAK-5710-2020; Price,
   Donald/F-7722-2011
OI Olazcuaga, Laure/0000-0001-9100-1305; Kenis, Marc/0000-0002-3179-0872;
   Fraimout, Antoine/0000-0003-4552-3553; Guedot,
   Christelle/0000-0002-6558-9886; Parrinello, Hugues/0000-0002-1151-001X;
   Price, Donald/0000-0003-2501-8373; PARIS, Mathilde/0000-0001-6166-6672
FU National Research Fund ANR (France) [ANR-16-CE02-0015-01];
   Languedoc-Roussillon Region (France) through the European Union Program
   FEDER FSE IEJ 2014-2020 (project CPADROL); INRA Scientific Department
   SPE (AAP-SPE 2016); INRA Scientific Department SPE (AAP-SPE 2018);
   France Genomique National infrastructure [ANR-10-INBS-09]
FX We wish to thank our three anonymous reviewers for their very helpful
   and constructive comments. A.E., M.G., and L.O. acknowledge financial
   support from the National Research Fund ANR (France) through the project
   ANR-16-CE02-0015-01 (SWING), the Languedoc-Roussillon Region (France)
   through the European Union Program FEDER FSE IEJ 2014-2020 (project
   CPADROL), and the INRA Scientific Department SPE (AAP-SPE 2016 and
   2018). MGX acknowledges financial support from France Genomique National
   infrastructure, funded as part of "Investissement d'avenir" program
   managed by Agence Nationale pour la Recherche (contract ANR-10-INBS-09).
   We are grateful to the genotoul bioinformatics platform Toulouse
   Midi-Pyrenees for providing computing resources, Nicolas Rode for useful
   discussions, and comments on a previous version of the article and
   Nicolas Ris, Jon Koch, Masahito Kimura, Simon Fellous, Vincent Debat,
   Marta Pascual, Ruth Hufbauer, Marindia Depra, Isabel Martinez, Pierre
   Girod, and Maxi Richmond for help in collecting some of the Drosophila
   suzukii samples.
CR Adrion JR, 2014, MOL BIOL EVOL, V31, P3148, DOI 10.1093/molbev/msu246
   Alberto FJ, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-03206-y
   Asplen MK, 2015, J PEST SCI, V88, P469, DOI 10.1007/s10340-015-0681-z
   Balanyá J, 2006, SCIENCE, V313, P1773, DOI 10.1126/science.1131002
   Barrett SCH, 2015, MOL ECOL, V24, P1927, DOI 10.1111/mec.13014
   Bock DG, 2015, MOL ECOL, V24, P2277, DOI 10.1111/mec.13032
   Bonhomme M, 2010, GENETICS, V186, P241, DOI 10.1534/genetics.104.117275
   Charlesworth B., 1994, CAMBRIDGE STUDIES MA, V2
   Chen SF, 2018, BIOINFORMATICS, V34, P884, DOI 10.1093/bioinformatics/bty560
   Chiu JC, 2013, G3-GENES GENOM GENET, V3, P2257, DOI 10.1534/g3.113.008185
   Cini A, 2012, B INSECTOL, V65, P149
   Clemente F, 2018, PLOS GENET, V14, DOI 10.1371/journal.pgen.1007191
   Colautti RI, 2015, MOL ECOL, V24, P1999, DOI 10.1111/mec.13162
   Colautti RI, 2013, SCIENCE, V342, P364, DOI 10.1126/science.1242121
   Coop G, 2010, GENETICS, V185, P1411, DOI 10.1534/genetics.110.114819
   Cornuet JM, 2014, BIOINFORMATICS, V30, P1187, DOI 10.1093/bioinformatics/btt763
   de Villemereuil P, 2015, METHODS ECOL EVOL, V6, P1248, DOI 10.1111/2041-210X.12418
   de Villemereuil P, 2014, MOL ECOL, V23, P2006, DOI 10.1111/mec.12705
   Dlugosch KM, 2015, MOL ECOL, V24, P2095, DOI 10.1111/mec.13183
   Ellstrand NC, 2000, P NATL ACAD SCI USA, V97, P7043, DOI [10.1073/pnas.97.13.7043, 10.1007/s10681-006-5939-3]
   Eoche-Bosy D, 2017, MOL ECOL, V26, P4700, DOI 10.1111/mec.14240
   Estoup A, 2016, ANNU REV ECOL EVOL S, V47, P51, DOI 10.1146/annurev-ecolsys-121415-032116
   Excoffier L, 2008, TRENDS ECOL EVOL, V23, P347, DOI 10.1016/j.tree.2008.04.004
   Facon B, 2011, CURR BIOL, V21, P424, DOI 10.1016/j.cub.2011.01.068
   Fariello MI, 2017, MOL ECOL, V26, P3700, DOI 10.1111/mec.14141
   Foll M, 2014, AM J HUM GENET, V95, P394, DOI 10.1016/j.ajhg.2014.09.002
   Fraimout A, 2017, MOL BIOL EVOL, V34, P980, DOI 10.1093/molbev/msx050
   François O, 2016, MOL ECOL, V25, P454, DOI 10.1111/mec.13513
   Frichot E, 2015, HEREDITY, V115, P22, DOI 10.1038/hdy.2015.7
   Frichot E, 2013, MOL BIOL EVOL, V30, P1687, DOI 10.1093/molbev/mst063
   Gautier M, 2018, CURR BIOL, V28, P3296, DOI 10.1016/j.cub.2018.08.023
   Gautier M, 2015, GENETICS, V201, P1555, DOI 10.1534/genetics.115.181453
   Gautier M, 2013, MOL ECOL, V22, P3766, DOI 10.1111/mec.12360
   Grau J, 2015, BIOINFORMATICS, V31, P2595, DOI 10.1093/bioinformatics/btv153
   Günther T, 2013, GENETICS, V195, P205, DOI 10.1534/genetics.113.152462
   Hivert V, 2018, GENETICS, V210, P315, DOI 10.1534/genetics.118.300900
   Hoskins RA, 2015, GENOME RES, V25, P445, DOI 10.1101/gr.185579.114
   Hudson RR, 2002, BIOINFORMATICS, V18, P337, DOI 10.1093/bioinformatics/18.2.337
   Janitz M, 2006, HANDB EXP PHARM, V173, P97
   Jeffreys H., 1961, Oxford Classics Series, V3rd
   Kankare Maaria, 2010, BMC Ecology, V10, P3, DOI 10.1186/1472-6785-10-3
   Karageorgi M, 2017, CURR BIOL, V27, P847, DOI 10.1016/j.cub.2017.01.055
   Koboldt DC, 2012, GENOME RES, V22, P568, DOI 10.1101/gr.129684.111
   Kruschke J., 2014, Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan
   Lee CE, 2008, EVOL APPL, V1, P427, DOI 10.1111/j.1752-4571.2008.00039.x
   Lee CE, 2002, TRENDS ECOL EVOL, V17, P386, DOI 10.1016/S0169-5347(02)02554-5
   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]
   Li YF, 2008, EVOLUTION, V62, P2984, DOI 10.1111/j.1558-5646.2008.00486.x
   MUELLER LD, 1981, P NATL ACAD SCI-BIOL, V78, P1303, DOI 10.1073/pnas.78.2.1303
   Ochocki BM, 2017, NAT COMMUN, V8, DOI 10.1038/ncomms14315
   Ometto L, 2013, GENOME BIOL EVOL, V5, P745, DOI 10.1093/gbe/evt034
   Paris M, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-67373-z
   Pavlidis P, 2012, MOL BIOL EVOL, V29, P3237, DOI 10.1093/molbev/mss136
   Peng B, 2005, BIOINFORMATICS, V21, P3686, DOI 10.1093/bioinformatics/bti584
   Pickrell JK, 2012, PLOS GENET, V8, DOI 10.1371/journal.pgen.1002967
   Puzey J, 2014, MOL ECOL, V23, P4472, DOI 10.1111/mec.12875
   Refoyo-Martínez A, 2019, GENOME RES, V29, P1506, DOI 10.1101/gr.246777.118
   Reznick DN, 2019, ECOL LETT, V22, P233, DOI 10.1111/ele.13189
   Roesti M, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms9767
   ROUGHGARDEN J, 1971, ECOLOGY, V52, P453, DOI 10.2307/1937628
   Schlötterer C, 2014, NAT REV GENET, V15, P749, DOI 10.1038/nrg3803
   Schmidt PS, 2008, P NATL ACAD SCI USA, V105, P16207, DOI 10.1073/pnas.0805485105
   Schmidt PS, 2008, EVOLUTION, V62, P1204, DOI 10.1111/j.1558-5646.2008.00351.x
   Schmidt PS, 2005, EVOLUTION, V59, P1721, DOI 10.1111/j.0014-3820.2005.tb01821.x
   Storey JD, 2003, P NATL ACAD SCI USA, V100, P9440, DOI 10.1073/pnas.1530509100
   Wang M, 2019, BMC BIOINFORMATICS, V20, DOI 10.1186/s12859-019-2597-8
   WEIR BS, 1984, EVOLUTION, V38, P1358, DOI [10.2307/2408641, 10.1111/j.1558-5646.1984.tb05657.x]
   Welles S.R., 2019, POPULATION GENOMICS, P655, DOI [10.1007/13836_2018_22, DOI 10.1007/13836_2018_22, 10.1007/13836201822]
   Westram AM, 2014, MOL ECOL, V23, P4603, DOI 10.1111/mec.12883
   Williams JL, 2016, SCIENCE, V353, P482, DOI 10.1126/science.aaf6268
   Wu NN, 2019, NAT ECOL EVOL, V3, P105, DOI 10.1038/s41559-018-0746-5
NR 72
TC 48
Z9 51
U1 5
U2 66
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 AUG
PY 2020
VL 37
IS 8
BP 2369
EP 2385
DI 10.1093/molbev/msaa098
PG 17
WC Biochemistry & Molecular Biology; Evolutionary Biology; Genetics &
   Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Evolutionary Biology; Genetics &
   Heredity
GA NV5SL
UT WOS:000574381000018
PM 32302396
OA hybrid, Green Published, Green Submitted
DA 2025-01-10
ER

PT J
AU Xie, W
   Huang, JK
   Wang, JX
   Cui, Q
   Robertson, R
   Chen, K
AF Xie, Wei
   Huang, Jikun
   Wang, Jinxia
   Cui, Qi
   Robertson, Ricky
   Chen, Kevin
TI Climate change impacts on China's agriculture: The responses from market
   and trade
SO CHINA ECONOMIC REVIEW
LA English
DT Article
DE Climate change; Food security; Market; Trade; China
ID FOOD SECURITY; WORLD
AB China's food security has been facing several challenges, which are likely to be worsened due to climate change. The purpose of this paper is to provide an evidence on the impacts of climate change on China's agriculture, with particular attention to the market and trade responses. Using projected crop yield changes for China and its' main trading partners under changing climate, we employ an agricultural partial equilibrium model (CAPSiM) and a linked national and global equilibrium model (CAPSiM-GTAP) to assess the impacts on food production, price, trade and self-sufficiency of China. Our results show that climate change will have significant effects on crop production though with large differences among crops. Under the worst climate change scenario RCP 8.5, wheat yield in China is projected to decline by 9.4% by 2050, which is the biggest yield reduction among the crops. However, the market can also respond to the climate change, as farmers can change inputs in response to reduced yields and rising prices. As a result, production losses for most crops are dampened. For example, wheat production loss under RCP8.5 reduces to only 4.3% due to market response. The adverse impacts on crop production will be further reduced after accounting for the trade response as farmers adjust production to much higher prices in the more severely affected countries. The paper concludes that we need to learn more from farmers who optimize their production decisions in response to the market and trade signals during climate change. A major policy implication is that policymakers need to mainstream the market and trade responses into national plans for climate adaptation.
C1 [Xie, Wei; Huang, Jikun; Wang, Jinxia; Cui, Qi] Peking Univ, China Ctr Agr Policy, Sch Adv Agr Sci, Beijing 100871, Peoples R China.
   [Robertson, Ricky; Chen, Kevin] Int Food Policy Res Inst, Washington, DC 20005 USA.
   [Cui, Qi] Beijing Normal Univ, Sch Econ & Resource Management, Beijing Key Lab Study Sci Tech Strategy Urban Gre, Beijing 100875, Peoples R China.
C3 Peking University; CGIAR; International Food Policy Research Institute
   (IFPRI); Beijing Normal University
RP Huang, JK; Cui, Q (corresponding author), Peking Univ, China Ctr Agr Policy, Sch Adv Agr Sci, Beijing 100871, Peoples R China.; Cui, Q (corresponding author), Beijing Normal Univ, Sch Econ & Resource Management, Beijing Key Lab Study Sci Tech Strategy Urban Gre, Beijing 100875, Peoples R China.
EM jkhuang.ccap@pku.edu.cn; cuiqi.ccap@pku.edu.cn
RI Chen, Kevin/D-6769-2011
OI Cui, Qi/0000-0002-3704-8257
FU Ministry of Science and Technology, China [2012CB955700]; National
   Natural Sciences Foundation of China [71503243, 71873009, 71333013];
   NSFC-CGIAR [71161140351]; Australian Centre for International
   Agricultural Research [ADP/2010/070]; National Social Science Fund of
   China [16AJL009]
FX The authors acknowledge their respective financial supports from
   Ministry of Science and Technology, China (2012CB955700), National
   Natural Sciences Foundation of China (71503243; 71873009; 71333013),
   NSFC-CGIAR (71161140351), Australian Centre for International
   Agricultural Research (ADP/2010/070), and National Social Science Fund
   of China (16AJL009).
CR Ali T, 2017, GLOB FOOD SECUR-AGR, V12, P139, DOI 10.1016/j.gfs.2016.11.003
   [Anonymous], CLIMATE CHANGE 2014
   [Anonymous], 1997, Global Trade Analysis: Modeling and Applications
   Baldos ULC, 2015, FOOD SECUR, V7, P275, DOI 10.1007/s12571-015-0435-z
   Brown ME, 2017, FOOD POLICY, V68, P154, DOI 10.1016/j.foodpol.2017.02.004
   Calzadilla A, 2013, CLIMATIC CHANGE, V120, P357, DOI 10.1007/s10584-013-0822-4
   Cui Q, 2018, J CLEAN PROD, V176, P1245, DOI 10.1016/j.jclepro.2017.11.165
   Edition Committee of China's National Assessment Report on Climate Change, 2015, CHIN NAT ASS REP CLI
   FAOSTAT, 2017, FAOSTAT ONL DAT 2017
   Horridge M., 2005, POVERTY WTO IMPACTS
   Huang J K, 2003, J NANJING AGRI U SOC, V3, P30
   Huang JK, 2017, J INTEGR AGR, V16, P2933, DOI 10.1016/S2095-3119(17)61756-8
   Li N. H., 2004, CHINAS AGR POLICY SI
   Li RL, 2013, J INTEGR AGR, V12, P1402, DOI 10.1016/S2095-3119(13)60552-3
   [梁玉莲 Liang Yulian], 2016, [热带气象学报, Journal of Tropical Meteorology], V32, P183
   Lin ED, 2005, PHILOS T R SOC B, V360, P2149, DOI 10.1098/rstb.2005.1743
   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
   Nelson GC, 2014, P NATL ACAD SCI USA, V111, P3274, DOI 10.1073/pnas.1222465110
   OECD/FAO, 2018, OECD FAO AGR OUTL
   Parry ML, 2004, GLOBAL ENVIRON CHANG, V14, P53, DOI 10.1016/j.gloenvcha.2003.10.008
   Piao SL, 2010, NATURE, V467, P43, DOI 10.1038/nature09364
   REILLY J, 1993, AM ECON REV, V83, P306
   Robinson S, 2014, AGR ECON-BLACKWELL, V45, P21, DOI 10.1111/agec.12087
   Roson R., 2010, GTAP C
   Tao F, 2008, AGR FOREST METEOROL, V148, P94, DOI 10.1016/j.agrformet.2007.09.012
   Walmsley TL, 2012, DYNAMIC MODELING AND APPLICATIONS FOR GLOBAL ECONOMIC ANALYSIS, P136
   Wang J. X., 2016, 9 IEEE SENS ARR MULT, P1
   Wang J. X., 2009, CLIMATE CHANGE WATER
   Wang JX, 2014, J INTEGR AGR, V13, P1, DOI 10.1016/S2095-3119(13)60588-2
   Wu SH, 2014, CHIN J POPUL RESOUR, V12, P95, DOI 10.1080/10042857.2014.910878
   Xiong W, 2007, CLIMATIC CHANGE, V85, P433, DOI 10.1007/s10584-007-9284-x
   Xiong W, 2009, CLIM RES, V40, P23, DOI 10.3354/cr00802
   Xiong W, 2009, GLOBAL ENVIRON CHANG, V19, P34, DOI 10.1016/j.gloenvcha.2008.10.006
   Yang J, 2012, CHINA ECON REV, V23, P651, DOI 10.1016/j.chieco.2010.06.009
   Zhai F., 2009, Asian Development Review, V26, P206
   Zhou SD, 2017, CHINA AGR ECON REV, V9, P643, DOI [10.1108/CAER-10-2016-0173, 10.1108/caer-10-2016-0173]
NR 37
TC 59
Z9 59
U1 23
U2 188
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 AUG
PY 2020
VL 62
AR 101256
DI 10.1016/j.chieco.2018.11.007
PG 13
WC Economics
WE Social Science Citation Index (SSCI)
SC Business & Economics
GA NM1CO
UT WOS:000567842300023
DA 2025-01-10
ER

PT J
AU Evteev, AA
   Grosheva, AN
AF Evteev, Andrej A.
   Grosheva, Alexandra N.
TI Nasal cavity and maxillary sinuses form variation among modern humans of
   Asian descent
SO AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY
LA English
DT Article
DE climatic adaptation; computed tomography; human variation; maxillary
   sinuses; nasal cavity
ID MIDFACIAL MORPHOLOGY; ECOGEOGRAPHIC VARIATION; COMPUTED-TOMOGRAPHY;
   POPULATION HISTORY; CLIMATE; VOLUME; ASSOCIATION; RELIABILITY; PATTERNS;
   FLATNESS
AB Objectives This study explores variation, covariation, and ecogeographic pattern of the nasal cavity, maxillary sinuses, and external midfacial skeleton across 15 populations of east Asian origin inhabiting the Far East, Siberia, Alaska and Greenland. Materials and Methods We have collected linear measurements of the internal nasal cavity, maxillary sinus and external midfacial skeleton as well as volumes and surface areas of three-dimensional models of the cavity. A set of seven climatic variables, mtDNA and Y-chromosome genetic matrices and a matrix of geographic distances were also utilized. Results A strong association between form of the nasal cavity and climate was found, whereby all north Asian groups display increased volumes, areas and lengths of the cavity, and surface area to volume ratios (SA/V). Most of Siberian groups exhibit not only large and long, but also wide and tall nasal cavity. The Eskimo-Aleutian speaking groups possess cavities that are vertically short and narrow but of a high SA/V ratio. The sinuses exhibit an exceptionally high level of within- and between-group variation which supports the views on the sinus as an architectural byproduct. Both volume and area of the nasal cavity can be reliably estimated based on a set of simple and repeatable linear measurements. Discussion While the nasal cavity and maxillary sinus are both larger in a larger facial skeleton, there is a strong inverse relationship between them at a given facial size. Our results do not support the notion that the shape of the internal nasal cavity is more strongly associated with climate compared to the external midfacial morphology.
C1 [Evteev, Andrej A.] Lomonosov Moscow State Univ, Anuchins Res Inst, 11 Mokhovaya St, Moscow 125009, Russia.
   [Evteev, Andrej A.] Lomonosov Moscow State Univ, Museum Anthropol, 11 Mokhovaya St, Moscow 125009, Russia.
   [Grosheva, Alexandra N.] Russian Acad Sci, Vavilov Inst Gen Genet, Moscow, Russia.
C3 Lomonosov Moscow State University; Lomonosov Moscow State University;
   Russian Academy of Sciences; Vavilov Institute of General Genetics
RP Evteev, AA (corresponding author), Lomonosov Moscow State Univ, Anuchins Res Inst, 11 Mokhovaya St, Moscow 125009, Russia.; Evteev, AA (corresponding author), Lomonosov Moscow State Univ, Museum Anthropol, 11 Mokhovaya St, Moscow 125009, Russia.
EM evteandr@gmail.com
RI Evteev, Andrej/H-6538-2014
FU Russian Foundation for Basic Research [17-29-04125, 18-09-00487]
FX Russian Foundation for Basic Research, Grant/Award Numbers: 17-29-04125,
   18-09-00487
CR [Anonymous], THESIS
   Butaric LN, 2018, AM J HUM BIOL, V30, DOI 10.1002/ajhb.23104
   Butaric LN, 2016, AM J PHYS ANTHROPOL, V160, P483, DOI 10.1002/ajpa.22986
   Butaric LN, 2015, ANAT REC, V298, P1710, DOI 10.1002/ar.23182
   Butaric LN, 2010, AM J PHYS ANTHROPOL, V143, P426, DOI 10.1002/ajpa.21331
   CAREY JW, 1981, AM J PHYS ANTHROPOL, V56, P313, DOI 10.1002/ajpa.1330560312
   CAVALLISFORZA LL, 1967, AM J HUM GENET, V19, P233, DOI 10.2307/2406616
   Charles CM, 1930, AM J PHYS ANTHROPOL, V14, P177, DOI 10.1002/ajpa.1330140204
   Cole P., 1982, NOSE UPPER AIRWAY PH, P351
   Copes L.E., 2012, THESIS
   Davies A, 1932, J R ANTHROPOL INST G, V62, P337, DOI 10.2307/2843962
   Evteev A. A., 2018, EUR SOC STUD HUM EV
   Evteev A, 2014, AM J PHYS ANTHROPOL, V153, P449, DOI 10.1002/ajpa.22444
   Evteev AA, 2017, J HUM EVOL, V107, P36, DOI 10.1016/j.jhevol.2017.02.008
   Evteev AA, 2016, AM J PHYS ANTHROPOL, V159, P517, DOI 10.1002/ajpa.22894
   FRANCISCUS RG, 1991, AM J PHYS ANTHROPOL, V85, P419, DOI 10.1002/ajpa.1330850406
   Fu QM, 2013, P NATL ACAD SCI USA, V110, P2223, DOI 10.1073/pnas.1221359110
   Fukase H, 2016, AM J HUM BIOL, V28, P343, DOI 10.1002/ajhb.22786
   Hammer O., 2001, PAST PALAEONTOLOGICA
   Hanihara T, 2000, AM J PHYS ANTHROPOL, V111, P105, DOI 10.1002/(SICI)1096-8644(200001)111:1<105::AID-AJPA7>3.0.CO;2-O
   Harvati K, 2006, ANAT REC PART A, V288A, P1225, DOI 10.1002/ar.a.20395
   Holton N, 2013, ANAT REC, V296, P414, DOI 10.1002/ar.22655
   Howells WW., 1989, SKULL SHAPES MAP
   Hubbe M, 2009, ANAT REC, V292, P1720, DOI 10.1002/ar.20976
   Keck T, 2000, RHINOLOGY, V38, P167
   Klingenberg CP, 2011, MOL ECOL RESOUR, V11, P353, DOI 10.1111/j.1755-0998.2010.02924.x
   Maddux SD, 2017, ANAT REC, V300, P209, DOI 10.1002/ar.23447
   Maddux SD, 2017, AM J PHYS ANTHROPOL, V162, P103, DOI 10.1002/ajpa.23100
   Marks T. N., 2018, EUR SOC STUD HUM EV
   Márquez S, 2008, ANAT REC, V291, P1420, DOI 10.1002/ar.20785
   Noback ML, 2011, AM J PHYS ANTHROPOL, V145, P599, DOI 10.1002/ajpa.21523
   Papadopoulos MA, 2005, J CRANIO MAXILL SURG, V33, P229, DOI 10.1016/j.jcms.2005.02.003
   Rae TC, 2003, AM J PRIMATOL, V59, P153, DOI 10.1002/ajp.10072
   Reich D, 2012, NATURE, V488, P370, DOI 10.1038/nature11258
   Relethford JH, 2010, AM J PHYS ANTHROPOL, V142, P105, DOI 10.1002/ajpa.21207
   Roseman CC, 2004, P NATL ACAD SCI USA, V101, P12824, DOI 10.1073/pnas.0402637101
   SHEA BT, 1977, AM J PHYS ANTHROPOL, V47, P289, DOI 10.1002/ajpa.1330470209
   Stull KE, 2014, FORENSIC SCI INT, V238, P133, DOI 10.1016/j.forsciint.2014.03.005
   van Oldenborgh GJ, 2005, OCEAN SCI, V1, P81, DOI 10.5194/os-1-81-2005
   WALKER JE, 1961, AM J MED, V30, P259, DOI 10.1016/0002-9343(61)90097-3
   Wong ENM, 2017, GENOME RES, V27, P1, DOI 10.1101/gr.202945.115
   Woo TL, 1934, BIOMETRIKA, V26, P196, DOI 10.1093/biomet/26.1-2.196
   Yokley T. R., 2005, ANN M PAL ANTHR SOC
   Yokley TR, 2009, AM J PHYS ANTHROPOL, V138, P11, DOI 10.1002/ajpa.20893
   Zollikofer CPE, 2008, ANAT REC, V291, P1446, DOI 10.1002/ar.20784
NR 45
TC 19
Z9 21
U1 0
U2 5
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0002-9483
EI 1096-8644
J9 AM J PHYS ANTHROPOL
JI Am. J. Phys. Anthropol.
PD JUL
PY 2019
VL 169
IS 3
BP 513
EP 525
DI 10.1002/ajpa.23841
PG 13
WC Anthropology; Evolutionary Biology
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Anthropology; Evolutionary Biology
GA ID6SU
UT WOS:000471810100010
PM 30985926
DA 2025-01-10
ER

PT J
AU Berman, A
AF Berman, A.
TI An overview of heat stress relief with global warming in perspective
SO INTERNATIONAL JOURNAL OF BIOMETEOROLOGY
LA English
DT Article
DE Dairy cattle; Gradual warming; Episodic heat; Stress alleviation
ID YIELDING DAIRY-COWS; FORCED VENTILATION; TROPICAL CLIMATE; COOLING
   SYSTEMS; HOLSTEIN COWS; MILK-YIELD; CATTLE; HOT; RADIATION; SHADE
AB Global warming seems more probable, whether as gradual warming or increased frequency of warmer episodes. The productivity of cattle in temperate countries will decline unless counteracting steps are adopted. The probability of pre-emptive breeding for maintaining temperate breed performance coupled with heat stress tolerance is too low to be adopted for counteracting warming. The expected warming will mostly involve temperature increases. These will indirectly affect radiant heat gain in animals owing to reduced radiant heat dissipation from the body by convective heat loss, which results in an increased sensitivity to incoming radiant heat at higher air temperatures. These necessitate an emphasis on increasing convective heat loss by structure design and forced air flow by fans. Convective heat loss diminishes with increasing air temperatures. Evaporative heat loss remains the alternative. Evaporative cooling of the ambient requires partial enclosing of the space surrounding the animals and is limited by the humidity in ambient air. An alternative was developed of coupling forced ventilation with wetting of animal surface. The exchange of ambient air flowing on animal surface makes the evaporation practically independent of air humidity and the loss of heat from animal surface practically independent of the surface to air temperature gradient. The coupling of forced ventilation with wetting combination may be attained in various parts of the dairy farm, the holding area of the milking parlour, the feeding trip and the resting area. Each of these requires differing structural and technological adaptations. Climate and farming systems vary between locations which require specific solutions.
C1 [Berman, A.] Hebrew Univ Jerusalem, Dept Anim Sci, Fac Agr, Rehovot Campus, IL-76100 Rehovot, Israel.
C3 Hebrew University of Jerusalem
RP Berman, A (corresponding author), Hebrew Univ Jerusalem, Dept Anim Sci, Fac Agr, Rehovot Campus, IL-76100 Rehovot, Israel.
EM amiel.berman@mail.huji.ac.il
CR Angrecka S, 2016, ANN ANIM SCI, V16, P887, DOI 10.1515/aoas-2015-0096
   [Anonymous], 2001, Nutrient requirements of dairy cattle, V7th, P381
   ARAVE C W, 1991, Journal of Dairy Science, V74, P280
   ARKIN H, 1991, T ASAE, V34, P2550
   Armstrong DV, 2007, POULTRY SCI, V86, P539
   Berman A, 2006, J DAIRY SCI, V89, P3817, DOI 10.3168/jds.S0022-0302(06)72423-7
   BERMAN A, 1963, AUST J AGR RES, V14, P874, DOI 10.1071/AR9630874
   BERMAN A, 1985, J DAIRY SCI, V68, P1488, DOI 10.3168/jds.S0022-0302(85)80987-5
   Berman A, 2014, INT J BIOMETEOROL, V58, P1683, DOI 10.1007/s00484-013-0712-5
   Berman A, 2004, J DAIRY SCI, V87, P1400, DOI 10.3168/jds.S0022-0302(04)73289-0
   Berman A, 2012, J DAIRY SCI, V95, P3021, DOI 10.3168/jds.2011-4844
   Berman A, 2011, J DAIRY SCI, V94, P2147, DOI 10.3168/jds.2010-3962
   BERMAN A, 1973, International Journal of Biometeorology, V17, P167, DOI 10.1007/BF01809804
   Berman A, 2010, J DAIRY SCI, V93, P242, DOI 10.3168/jds.2009-2601
   Berman A, 2009, J ANIM SCI, V87, P3413, DOI 10.2527/jas.2008-1104
   BERMAN A, 1971, AUST J AGR RES, V22, P671, DOI 10.1071/AR9710671
   Berman A, 1987, ADAPTIVE PHYSL STRES
   Berman A, 1973, INT J BIOMETEOROL, V1, P88
   BLAKE RW, 1986, J DAIRY SCI, V69, P1098, DOI 10.3168/jds.S0022-0302(86)80507-0
   Branton C, 1966, SO COOP S B, P114
   Brosh A, 2010, J ANIM SCI, V88, P315, DOI 10.2527/jas.2009-2108
   BROWN WH, 1974, T ASAE, V17, P513
   Brown-Brandl TM, 2017, ANIMAL, V11, P1344, DOI [10.1017/S1751731116002664, 10.1017/s1751731116002664]
   Bucklin R. A., 1993, Applied Engineering in Agriculture, V9, P123
   BUFFINGTON DE, 1983, T ASAE, V26, P1798
   Calegari F, 2016, INT J BIOMETEOROL, V60, P605, DOI 10.1007/s00484-015-1056-0
   da Silva RG, 2010, INT J BIOMETEOROL, V54, P5, DOI 10.1007/s00484-009-0244-1
   Dikmen S, 2014, J DAIRY SCI, V97, P5508, DOI 10.3168/jds.2014-8087
   Eigenberg RA, 2010, INT J BIOMETEOROL, V54, P601, DOI 10.1007/s00484-010-0381-6
   FLAMENBAUM I, 1986, J DAIRY SCI, V69, P3140, DOI 10.3168/jds.S0022-0302(86)80778-0
   Flamenbaum I, 1984, 35 ANN M EAAP HAG NE
   Flamenbaum I, 2010, J REPROD DEVELOP, V56, pS36, DOI 10.1262/jrd.1056S36
   FOLMAN Y, 1979, J DAIRY RES, V46, P411, DOI 10.1017/S0022029900017441
   ITTNER NR, 1951, J ANIM SCI, V10, P184, DOI 10.2527/jas1951.101184x
   KELLY C. F., 1948, AGRIC ENGINEERING, V29, P239
   Kelly CF, 1950, AGR ENG, V31, P601
   Khongdee S, 2010, ANIM SCI J, V81, P606, DOI 10.1111/j.1740-0929.2010.00771.x
   McDowell RE, 1996, J DAIRY SCI, V79, P1292, DOI 10.3168/jds.S0022-0302(96)76484-6
   Nardone A, 2010, LIVEST SCI, V130, P57, DOI 10.1016/j.livsci.2010.02.011
   Oliveira SEO, 2014, TROP ANIM HEALTH PRO, V46, P1413, DOI 10.1007/s11250-014-0657-7
   Ornes S, 2018, P NATL ACAD SCI USA, V115, P8232, DOI 10.1073/pnas.1811393115
   Ortiz XA, 2011, J DAIRY SCI, V94, P1026, DOI 10.3168/jds.2010-3126
   Palacio S, 2015, J DAIRY SCI, V98, P6085, DOI 10.3168/jds.2014-8932
   Shoshani E, 2013, ANIMAL, V7, P176, DOI 10.1017/S1751731112001085
   Talbott C. W., 1998, Journal of Dairy Science, V81, P140
   THIAGARAJAN M, 1991, INDIAN J ANIM SCI, V61, P1222
   WOLFENSON D, 1988, J DAIRY SCI, V71, P3497, DOI 10.3168/jds.S0022-0302(88)79956-7
   WOLFENSON D, 1988, J DAIRY SCI, V71, P809, DOI 10.3168/jds.S0022-0302(88)79621-6
   Wright N C, 1954, PROGR PHYSL FARM ANI, V1, P191
NR 49
TC 23
Z9 28
U1 2
U2 37
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 0020-7128
EI 1432-1254
J9 INT J BIOMETEOROL
JI Int. J. Biometeorol.
PD APR
PY 2019
VL 63
IS 4
BP 493
EP 498
DI 10.1007/s00484-019-01680-7
PG 6
WC Biophysics; Environmental Sciences; Meteorology & Atmospheric Sciences;
   Physiology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biophysics; Environmental Sciences & Ecology; Meteorology & Atmospheric
   Sciences; Physiology
GA HQ7PJ
UT WOS:000462612800006
PM 30739158
DA 2025-01-10
ER

PT J
AU McFadgen, BK
AF McFadgen, Belinda K.
TI Connecting policy change, experimentation, and entrepreneurs: advancing
   conceptual and empirical insights
SO ECOLOGY AND SOCIETY
LA English
DT Article
DE bricolage; climate adaptation; Dutch water management; policy change
   strategies; policy entrepreneur; policy experimentation
ID CLIMATE GOVERNANCE; DYNAMICS; COMANAGEMENT; FRAMEWORK; LESSONS
AB With global environmental problems worsening, policy makers and nonstate actors are looking for viable solutions through policy innovation, entrepreneurship, and experimentation. Research into the use of experiments to innovate is increasing, but the role of experimentation in policy change has yet to be specifically addressed in the context of climate governance. My aim is to improve understanding by examining how entrepreneurs, key agents of change, might use experiments to advance their climate innovations. Policy entrepreneurs can benefit in several ways from using experiments, including assessing public response to new ideas and learning. I address the question: What role can experiments play in an entrepreneur's change strategies? To answer this, a set of 18 policy experiments from Dutch water management was analyzed to understand how the policy experiments functioned as 4 different policy change strategies. The results revealed that organizers use experiments to evaluate their preformed ideas, to soften local communities to the idea of experimentation, to build broad but centrally controlled coalitions, and to link with influential political actors and national programs to maintain visibility and relevance. These insights formed a list of suggestions that the experiment organizers identified as key to the change strategies. Based on this, a number of recommendations about design choices were made for entrepreneurs who want to experiment. Analyzing experiments as change strategies contributes a novel perspective on how policy experiments function as venues for invention and provides useful suggestions on how experiments can be designed to improve their influence over policy-making processes.
C1 [McFadgen, Belinda K.] Vrije Univ, Inst Environm Studies, Amsterdam, Netherlands.
C3 Vrije Universiteit Amsterdam
RP McFadgen, BK (corresponding author), Vrije Univ, Inst Environm Studies, Amsterdam, Netherlands.
FU Dutch Knowledge for Climate program
FX Thank you to the Dutch Knowledge for Climate program, which funded this
   research.
CR [Anonymous], 2003, SOCIAL EXPT PUBLIC P
   [Anonymous], 1987, Rational ecology: Environmental and political economy
   Ansell CK, 2016, ECOL ECON, V130, P64, DOI 10.1016/j.ecolecon.2016.05.016
   Antikainen R, 2017, J CLEAN PROD, V169, P216, DOI 10.1016/j.jclepro.2017.06.184
   Bai XM, 2010, ENVIRON SCI POLICY, V13, P312, DOI 10.1016/j.envsci.2010.03.011
   BAUMGARTNER FR, 1991, J POLIT, V53, P1044, DOI 10.2307/2131866
   Baumgartner FrankR., 2002, Policy Dynamics
   Beem B, 2007, MAR POLICY, V31, P540, DOI 10.1016/j.marpol.2006.12.001
   Berkhout F, 2010, ENVIRON SCI POLICY, V13, P261, DOI 10.1016/j.envsci.2010.03.010
   Bernstein S, 2018, POLICY SCI, V51, P189, DOI 10.1007/s11077-018-9314-8
   Brodkin EZ, 2000, SOC SERV REV, V74, P507, DOI 10.1086/516423
   Broto VC, 2013, GLOBAL ENVIRON CHANG, V23, P92, DOI 10.1016/j.gloenvcha.2012.07.005
   Caniglia G, 2017, J CLEAN PROD, V169, P39, DOI 10.1016/j.jclepro.2017.05.164
   Cohen Steven., 1988, EFFECTIVE PUBLIC MAN
   Ettelt S, 2015, EVALUATION-US, V21, P292, DOI 10.1177/1356389015590737
   Farrelly M, 2011, GLOBAL ENVIRON CHANG, V21, P721, DOI 10.1016/j.gloenvcha.2011.01.007
   Fischer F., 1995, EVALUATING PUBLIC PO
   Haynes Laura, 2021, Test, learn, adapt: Developing public policy with randomised controlled trial, DOI [10.2139/ssrn.2131581, DOI 10.2139/SSRN.2131581]
   Hildén M, 2017, J CLEAN PROD, V169, P1, DOI 10.1016/j.jclepro.2017.09.019
   Hoffmann M.J., 2011, CLIMATE GOVERNANCE C
   Huitema D, 2018, POLICY SCI, V51, P143, DOI 10.1007/s11077-018-9321-9
   Huitema D, 2010, ECOL SOC, V15
   John P, 2017, EXPERIMENTS IN PUBLIC MANAGEMENT RESEARCH: CHALLENGES AND CONTRIBUTIONS, P476
   Kingdon JW, 1995, Agendas, alternatives and public policies, V2nd
   Kivimaa P, 2017, J CLEAN PROD, V169, P17, DOI 10.1016/j.jclepro.2017.01.027
   Laakso S, 2017, J CLEAN PROD, V169, P8, DOI 10.1016/j.jclepro.2017.04.140
   Martí I, 2009, INSTITUTIONAL WORK: ACTORS AND AGENCY IN INSTITUTIONAL STUDIES OF ORGANIZATIONS, P92, DOI 10.1017/CBO9780511596605.004
   Massey E, 2015, J WATER CLIM CHANGE, V6, P9, DOI 10.2166/wcc.2014.110
   McFadgen B, 2018, POLICY SCI, V51, P161, DOI 10.1007/s11077-017-9276-2
   McFadgen B, 2017, J ENVIRON PLANN MAN, V60, P1765, DOI 10.1080/09640568.2016.1256808
   Meijerink S., 2010, Ecology and Society, V15
   Meijerink S, 2009, WATER POLICY ENTREPRENEURS: A RESEARCH COMPANION TO WATER TRANSITIONS AROUND THE GLOBE, P23
   Millo Y., 2006, SCI PUBL POLICY, V33, P179, DOI [10.3152/147154306781779046, DOI 10.3152/147154306781779046]
   Mintrom M, 2017, ENVIRON PLAN C-POLIT, V35, P1362, DOI 10.1177/2399654417708440
   Mintrom Michael., 2000, POLICY ENTREPRENEURS
   Nair S, 2015, WATER RESOUR MANAG, V29, P4945, DOI 10.1007/s11269-015-1081-0
   Olsson P, 2006, ECOL SOC, V11, DOI 10.5751/ES-01595-110118
   Olsson P, 2017, ECOL SOC, V22, DOI 10.5751/ES-09310-220231
   Peters B.G., 1998, EXPT SOC ESSAYS HONO, P125
   Pieraccini M, 2016, ENVIRON POLIT, V25, P729, DOI 10.1080/09644016.2015.1090372
   Roberts NC., 1992, REV POLICY RES, V11, P55, DOI DOI 10.1111/J.1541-1338.1992.TB00332.X
   SABATIER PA, 1988, POLICY SCI, V21, P129, DOI 10.1007/BF00136406
   Sanderson I, 2002, PUBLIC ADMIN, V80, P1, DOI 10.1111/1467-9299.00292
   Schon D.A.M. Rein., 1994, FRAME REFLECTION RES
   Simons A, 2018, POLICY SOC, V37, P14, DOI 10.1080/14494035.2017.1375248
   Smith A, 2007, TECHNOL ANAL STRATEG, V19, P427, DOI 10.1080/09537320701403334
   van Buuren A, 2009, PUBLIC MANAG REV, V11, P375, DOI 10.1080/14719030902798289
   van der Heijden J, 2014, POLICY SCI, V47, P249, DOI 10.1007/s11077-013-9184-z
   van Popering-Verkerk J, 2017, J CLEAN PROD, V169, P225, DOI 10.1016/j.jclepro.2017.04.141
   Weiland S, 2017, J CLEAN PROD, V169, P30, DOI 10.1016/j.jclepro.2017.06.182
   YOUNG OR, 1991, INT ORGAN, V45, P281, DOI 10.1017/S0020818300033117
NR 51
TC 8
Z9 9
U1 2
U2 25
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 2019
VL 24
IS 1
AR 30
DI 10.5751/ES-10673-240130
PG 20
WC Ecology; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA HS8XU
UT WOS:000464153200016
OA Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Durmaz, E
   Benson, C
   Kapun, M
   Schmidt, P
   Flatt, T
AF Durmaz, Esra
   Benson, Clare
   Kapun, Martin
   Schmidt, Paul
   Flatt, Thomas
TI An inversion supergene in <i>Drosophila</i> underpins latitudinal clines
   in survival traits
SO JOURNAL OF EVOLUTIONARY BIOLOGY
LA English
DT Article
DE adaptation; clines; Drosophila melanogaster; inversion; life history;
   supergene; survival; temperature
ID AMINO-ACID POLYMORPHISM; GENOME-WIDE PATTERNS; LIFE-HISTORY CLINES;
   NATURAL-POPULATIONS; BODY-SIZE; CLIMATIC ADAPTATION; ADAPTIVE EVOLUTION;
   EASTERN AUSTRALIA; LOCAL ADAPTATION; COLD RESISTANCE
AB Chromosomal inversions often contribute to local adaptation across latitudinal clines, but the underlying selective mechanisms remain poorly understood. We and others have previously shown that a clinal inversion polymorphism in Drosophila melanogaster, In(3R)Payne, underpins body size clines along the North American and Australian east coasts. Here, we ask whether this polymorphism also contributes to clinal variation in other fitness-related traits, namely survival traits (lifespan, survival upon starvation and survival upon cold shock). We generated homokaryon lines, either carrying the inverted or standard chromosomal arrangement, isolated from populations approximating the endpoints of the North American cline (Florida, Maine) and phenotyped the flies at two growth temperatures (18 degrees C, 25 degrees C). Across both temperatures, high-latitude flies from Maine lived longer and were more stress resistant than low-latitude flies from Florida, as previously observed. Interestingly, we find that this latitudinal pattern is partly explained by the clinal distribution of the In(3R)P polymorphism, which is at similar to 50% frequency in Florida but absent in Maine: inverted karyotypes tended to be shorter-lived and less stress resistant than uninverted karyotypes. We also detected an interaction between karyotype and temperature on survival traits. As In(3R)P influences body size and multiple survival traits, it can be viewed as a supergene', a cluster of tightly linked loci affecting multiple complex phenotypes. We conjecture that the inversion cline is maintained by fitness trade-offs and balancing selection across geography; elucidating the mechanisms whereby this inversion affects alternative, locally adapted phenotypes across the cline is an important task for future work.
C1 [Durmaz, Esra; Benson, Clare; Kapun, Martin; Flatt, Thomas] Univ Lausanne, Dept Ecol & Evolut, Lausanne, Switzerland.
   [Durmaz, Esra; Kapun, Martin; Flatt, Thomas] Univ Fribourg, Dept Biol, CH-1700 Fribourg, Switzerland.
   [Benson, Clare] Univ Manchester, Sch Biol Sci, Manchester, Lancs, England.
   [Schmidt, Paul] Univ Penn, Dept Biol, Philadelphia, PA 19104 USA.
C3 University of Lausanne; University of Fribourg; University of
   Manchester; University of Pennsylvania
RP Flatt, T (corresponding author), Univ Fribourg, Dept Biol, CH-1700 Fribourg, Switzerland.
EM thomas.flatt@unifr.ch
RI Flatt, Thomas/AAE-7329-2019; Kapun, Martin/I-3536-2019; Durmaz Mitchell,
   Esra/AEW-0609-2022
OI Benson, Clare/0000-0002-3031-6896; Durmaz Mitchell, Esra
   M./0000-0002-4345-2264; Flatt, Thomas/0000-0002-5990-1503; Schmidt,
   Paul/0000-0002-8076-6705; Kapun, Martin/0000-0002-3810-0504
FU Swiss National Science Foundation (SNSF) [PP00P3_133641, PP00P3_165836,
   310030E-164207]; National Institutes of Health (NIH) [R01GM100366];
   National Science Foundation (NSF) [DEB 0921307]; Swiss National Science
   Foundation (SNF) [310030E-164207, PP00P3_165836] Funding Source: Swiss
   National Science Foundation (SNF)
FX We thank the members of the Flatt and Schmidt laboratories for
   discussion and help in the laboratory. Our research was financially
   supported by the Swiss National Science Foundation (SNSF PP00P3_133641;
   PP00P3_165836; 310030E-164207 to TF), the National Institutes of Health
   (NIH R01GM100366 to PS) and the National Science Foundation (NSF DEB
   0921307 to PS). We also thank two anonymous reviewers as well as Fred
   Mery and Wolf Blanckenhorn for helpful comments on our study.
CR Adrion JR, 2015, TRENDS GENET, V31, P434, DOI 10.1016/j.tig.2015.05.006
   Andersen JL, 2015, FUNCT ECOL, V29, P55, DOI 10.1111/1365-2435.12310
   Anderson AR, 2005, MOL ECOL, V14, P851, DOI 10.1111/j.1365-294X.2005.02445.x
   Anderson AR, 2003, HEREDITY, V90, P195, DOI 10.1038/sj.hdy.6800220
   [Anonymous], 1937, GENETICS ORIGIN SPEC
   [Anonymous], 1971, Genetics of the Evolutionary Process
   Azevedo RBR, 1998, EVOLUTION, V52, P1353, DOI [10.2307/2411305, 10.1111/j.1558-5646.1998.tb02017.x]
   Bergland AO, 2016, MOL ECOL, V25, P1157, DOI 10.1111/mec.13455
   Corbett-Detig RB, 2012, PLOS GENET, V8, DOI 10.1371/journal.pgen.1003056
   COYNE JA, 1987, GENETICS, V117, P727
   DAS A, 1991, GENOME, V34, P618, DOI 10.1139/g91-094
   De Jong G, 2003, J GENET, V82, P207, DOI 10.1007/BF02715819
   DOBZHANSKY T, 1947, GENETICS, V32, P142
   DOBZHANSKY T, 1947, EVOLUTION, V1, P1, DOI 10.2307/2405399
   Dobzhansky T, 1943, GENETICS, V28, P162
   Duvernell DD, 2003, MOL ECOL, V12, P1277, DOI 10.1046/j.1365-294X.2003.01841.x
   ETGES WJ, 1989, AM NAT, V133, P83, DOI 10.1086/284903
   Fabian DK, 2015, J EVOLUTION BIOL, V28, P826, DOI 10.1111/jeb.12607
   Fabian DK, 2012, MOL ECOL, V21, P4748, DOI 10.1111/j.1365-294X.2012.05731.x
   Flatt T, 2016, MOL ECOL, V25, P1023, DOI 10.1111/mec.13534
   Flatt T, 2013, Q REV BIOL, V88, P185, DOI 10.1086/671484
   Flatt T, 2009, BBA-GEN SUBJECTS, V1790, P951, DOI 10.1016/j.bbagen.2009.07.010
   Hoffmann AA, 2010, J EXP BIOL, V213, P870, DOI 10.1242/jeb.037630
   Hoffmann AA, 2005, FUNCT ECOL, V19, P222, DOI 10.1111/j.1365-2435.2005.00959.x
   Hoffmann AA, 2004, TRENDS ECOL EVOL, V19, P482, DOI 10.1016/j.tree.2004.06.013
   Hoffmann AA, 2007, GENETICA, V129, P133, DOI 10.1007/s10709-006-9010-z
   Hoffmann AA, 2008, ANNU REV ECOL EVOL S, V39, P21, DOI 10.1146/annurev.ecolsys.39.110707.173532
   INOUE Y, 1979, JPN J GENET, V54, P69, DOI 10.1266/jjg.54.69
   Kapun M, 2016, J EVOLUTION BIOL, V29, P1059, DOI 10.1111/jeb.12847
   Kapun M, 2016, MOL BIOL EVOL, V33, P1317, DOI 10.1093/molbev/msw016
   Kapun M, 2014, MOL ECOL, V23, P1813, DOI 10.1111/mec.12594
   Kennington WJ, 2007, GENETICS, V177, P549, DOI 10.1534/genetics.107.074336
   Kirkpatrick M, 2006, GENETICS, V173, P419, DOI 10.1534/genetics.105.047985
   Kirkpatrick M, 2012, GENETICS, V190, P1153, DOI 10.1534/genetics.112.139899
   KNIBB WR, 1981, GENETICS, V98, P833
   KNIBB WR, 1982, GENETICA, V58, P213, DOI 10.1007/BF00128015
   Lemeunier Francoise, 1992, P339
   Lowry DB, 2010, PLOS BIOL, V8, DOI 10.1371/journal.pbio.1000500
   Macdonald SS, 2004, J INSECT PHYSIOL, V50, P695, DOI 10.1016/j.jinsphys.2004.05.004
   Mathur V, 2017, EVOLUTION, V71, P465, DOI 10.1111/evo.13144
   Matzkin LM, 2005, GENETICS, V170, P1143, DOI 10.1534/genetics.104.038810
   METTLER LE, 1977, GENETICS, V87, P169
   NASSAR R, 1973, EVOLUTION, V27, P558, DOI 10.1111/j.1558-5646.1973.tb00705.x
   Paaby AB, 2008, PLOS ONE, V3, DOI 10.1371/journal.pone.0001987
   Paaby AB, 2014, EVOLUTION, V68, P3395, DOI 10.1111/evo.12546
   Paaby AB, 2010, MOL ECOL, V19, P760, DOI 10.1111/j.1365-294X.2009.04508.x
   Paaby AB, 2009, FLY, V3, P29, DOI 10.4161/fly.3.1.7771
   Rako L, 2006, GENETICA, V128, P373, DOI 10.1007/s10709-006-7375-7
   Rane RV, 2015, MOL ECOL, V24, P2423, DOI 10.1111/mec.13161
   Schaeffer SW, 2008, EVOLUTION, V62, P3082, DOI 10.1111/j.1558-5646.2008.00504.x
   Schmidt PS, 2008, P NATL ACAD SCI USA, V105, P16207, DOI 10.1073/pnas.0805485105
   Schmidt PS, 2008, EVOLUTION, V62, P1204, DOI 10.1111/j.1558-5646.2008.00351.x
   Schmidt PS, 2005, EVOLUTION, V59, P2616, DOI 10.1111/j.0014-3820.2005.tb00974.x
   Schmidt PS, 2005, EVOLUTION, V59, P1721, DOI 10.1111/j.0014-3820.2005.tb01821.x
   Schmidt PS, 2000, P NATL ACAD SCI USA, V97, P10861, DOI 10.1073/pnas.190338897
   Schwander T, 2014, CURR BIOL, V24, pR288, DOI 10.1016/j.cub.2014.01.056
   Sperlich D., 1986, Genetics and Biology of Drosophila, V3e, P257
   STALKER HD, 1980, GENETICS, V95, P211
   Tatar M, 2001, AM NAT, V158, P248, DOI 10.1086/321320
   TUCIC N, 1979, EVOLUTION, V33, P350, DOI 10.2307/2407625
   Weeks AR, 2002, ECOL LETT, V5, P756, DOI 10.1046/j.1461-0248.2002.00380.x
   WRIGHT S, 1946, GENETICS, V31, P125
NR 62
TC 27
Z9 29
U1 0
U2 19
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1010-061X
EI 1420-9101
J9 J EVOLUTION BIOL
JI J. Evol. Biol.
PD SEP
PY 2018
VL 31
IS 9
BP 1354
EP 1364
DI 10.1111/jeb.13310
PG 11
WC Ecology; Evolutionary Biology; Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Evolutionary Biology; Genetics &
   Heredity
GA GS5HI
UT WOS:000443688100008
PM 29904977
OA Green Submitted, Green Accepted, Bronze
DA 2025-01-10
ER

PT J
AU Sodoudi, S
   Zhang, HW
   Chi, XL
   Müller, F
   Li, HD
AF Sodoudi, Sahar
   Zhang, Huiwen
   Chi, Xiaoli
   Mueller, Felix
   Li, Huidong
TI The influence of spatial configuration of green areas on microclimate
   and thermal comfort
SO URBAN FORESTRY & URBAN GREENING
LA English
DT Article
DE ENVI-met; Landscape metrics; Park cool island (PCI); Rayman;
   Physiologically equivalent temperature (PET); Vegetation type
ID LAND-SURFACE TEMPERATURE; URBAN HEAT-ISLAND; CLIMATE-CHANGE; LANDSCAPE
   PATTERN; VEGETATION; STREET; MORTALITY; PHOENIX; IMPACT; SPACES
AB It has been shown that the spatial configuration of a green area can strongly influence its cooling effect. However, the specific correlation has not been sufficiently studied. To systematically clarify the correlation between the spatial configuration and the cooling effect of green areas, 25 idealized scenarios are designed and simulated using the microclimate model ENVI-met. These 25 scenarios represent green areas with five different spatial configurations (integrated green area, sparse dotted green areas, dense dotted green areas, belt-shaped green areas parallel to wind direction, and belt-shaped green areas vertical to wind direction) and five vegetation types (trees with big canopies, trees with small canopies, hedges and shrubs, 50 cm grass, and 10 cm grass). The human thermal comfort of each scenario is evaluated by means of physiologically equivalent temperature (PET) using Rayman. The results reveal the influence of the fragmentation degree (quantified by the patch density and edge density), shape complexity (quantified by the land shape index), orientation of green belt, and vegetation type on the cooling effect of a green area. The spatial configuration and the vegetation type of green areas were found jointly affecting the efficiency of the green areas' cooling effect. The highest cooling effect appears at 2 pm, reaching 6.3 K in the scenario of belt-shaped green areas parallel to the wind direction and with big canopy trees. The conclusions of this paper can provide suggestions for the climate-adaptive design and planning of urban green areas in the future.
C1 [Sodoudi, Sahar; Zhang, Huiwen; Chi, Xiaoli; Mueller, Felix; Li, Huidong] Free Univ Berlin, Inst Meteorol, Carl Heinrich Becker Weg 6-10, D-12165 Berlin, Germany.
C3 Free University of Berlin
RP Sodoudi, S (corresponding author), Free Univ Berlin, Inst Meteorol, Carl Heinrich Becker Weg 6-10, D-12165 Berlin, Germany.
EM sodoudi@zedat.fu-berlin.de; zhanghuiwen@zedat.fu-berlin.de;
   xiaoli@zedat.fu-berlin.de; mueller.f@fu-berlin.de;
   huidong.li@met.fu-berlin.de
RI Sodoudi, Sahar/L-7534-2017; Li, Huidong/AAT-9574-2020
FU German Ministry of Research and Education [FKZ01LP1602 A];
   Berlin-Brandenburg Academy of Science (BBAW); China Scholarship Council
   (CSC)
FX This study contributes to the research program "Urban Climate Under
   Change ([UC]<SUP>2</SUP>)", funded by the German Ministry of Research
   and Education (FKZ01LP1602 A). The authors are grateful to the project "
   Cooling effect of the historical garden 'Tiergarten' in Berlin" financed
   by Berlin-Brandenburg Academy of Science (BBAW), German Weather Service
   (DWD) for the data of the station Tempelhof, and China Scholarship
   Council (CSC) for the financial support. They also thank David Mottram
   for his valuable proofreading of this paper.
CR Ahmed KS, 2003, ENERG BUILDINGS, V35, P103, DOI 10.1016/S0378-7788(02)00085-3
   Andreou E, 2013, RENEW ENERG, V55, P182, DOI 10.1016/j.renene.2012.12.040
   [Anonymous], TEMP FELD K5 RD DVD
   [Anonymous], 2010, INT J BIOMETEOROL, DOI DOI 10.1007/s00484-009-0261-0
   [Anonymous], PNWGTR351 US DEP AGR
   Bai L, 2014, ENVIRON RES, V132, P212, DOI 10.1016/j.envres.2014.04.002
   Bi P, 2011, ASIA-PAC J PUBLIC HE, V23, p27S, DOI 10.1177/1010539510391644
   Boukhabla M, 2012, ENRGY PROCED, V18, P73, DOI 10.1016/j.egypro.2012.05.019
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   Bruse M, 1998, ENVIRON MODELL SOFTW, V13, P373, DOI 10.1016/S1364-8152(98)00042-5
   Cao X, 2010, LANDSCAPE URBAN PLAN, V96, P224, DOI 10.1016/j.landurbplan.2010.03.008
   CHANDLER TJ, 1962, GEOGR J, V128, P279, DOI 10.2307/1794042
   Chang CR, 2007, LANDSCAPE URBAN PLAN, V80, P386, DOI 10.1016/j.landurbplan.2006.09.005
   Chen AL, 2014, URBAN FOR URBAN GREE, V13, P646, DOI 10.1016/j.ufug.2014.07.006
   Chen AL, 2014, ECOL INDIC, V45, P424, DOI 10.1016/j.ecolind.2014.05.002
   Connors JP, 2013, LANDSCAPE ECOL, V28, P271, DOI 10.1007/s10980-012-9833-1
   Eludoyin O.M., 2014, Atmospheric and Climate Sciences, V4, P696, DOI DOI 10.4236/ACS.2014.44063
   Farajzadeh H, 2012, THEOR APPL CLIMATOL, V107, P451, DOI 10.1007/s00704-011-0492-y
   Forman R.T. T., 1995, Land Mosaics: The Ecology of Landscapes and Regions, Cambridge
   Gabriel KMA, 2011, ENVIRON POLLUT, V159, P2044, DOI 10.1016/j.envpol.2011.01.016
   Gómez-Muñoz VM, 2010, LANDSCAPE URBAN PLAN, V94, P149, DOI 10.1016/j.landurbplan.2009.09.002
   Gulyás A, 2006, BUILD ENVIRON, V41, P1713, DOI 10.1016/j.buildenv.2005.07.001
   Hardin Perry J., 2007, Urban Forestry & Urban Greening, V6, P63, DOI 10.1016/j.ufug.2007.01.005
   Hatvani-Kovacs G, 2016, SUSTAIN CITIES SOC, V26, P278, DOI 10.1016/j.scs.2016.06.019
   Hedquist BC, 2014, BUILD ENVIRON, V72, P377, DOI 10.1016/j.buildenv.2013.11.018
   Hilbrandt Hanna., 2016, Urban Geography, P1
   Höppe P, 1999, INT J BIOMETEOROL, V43, P71, DOI 10.1007/s004840050118
   Jansson C., 2006, Urban microclimate and surface hydro meteorological processes
   JAUREGUI E, 1991, ENERG BUILDINGS, V15, P457
   Kolokotroni M, 2007, SOL ENERGY, V81, P102, DOI 10.1016/j.solener.2006.06.005
   Lee H, 2016, LANDSCAPE URBAN PLAN, V148, P37, DOI 10.1016/j.landurbplan.2015.12.004
   Lehmann I, 2014, ECOL INDIC, V42, P58, DOI 10.1016/j.ecolind.2014.02.036
   Li HD, 2018, THEOR APPL CLIMATOL, V134, P67, DOI 10.1007/s00704-017-2253-z
   Li HD, 2018, SCI TOTAL ENVIRON, V624, P262, DOI 10.1016/j.scitotenv.2017.11.360
   Li HD, 2016, ENVIRON EARTH SCI, V75, DOI 10.1007/s12665-016-5786-z
   Li R, 2014, THEOR APPL CLIMATOL, V117, P613, DOI 10.1007/s00704-013-1027-5
   Li XM, 2013, LANDSCAPE URBAN PLAN, V114, P1, DOI 10.1016/j.landurbplan.2013.02.005
   Li XM, 2012, LANDSCAPE ECOL, V27, P887, DOI 10.1007/s10980-012-9731-6
   Liu H, 2008, ENVIRON MONIT ASSESS, V144, P199, DOI 10.1007/s10661-007-9979-5
   Maimaitiyiming M, 2014, ISPRS J PHOTOGRAMM, V89, P59, DOI 10.1016/j.isprsjprs.2013.12.010
   Mathey J, 2015, J URBAN PLAN DEV, V141, DOI 10.1061/(ASCE)UP.1943-5444.0000275
   Matzarakis A, 1999, INT J BIOMETEOROL, V43, P76, DOI 10.1007/s004840050119
   Matzarakis A, 1997, INT J BIOMETEOROL, V41, P34, DOI 10.1007/s004840050051
   MAYER H, 1987, THEOR APPL CLIMATOL, V38, P43, DOI 10.1007/BF00866252
   Meehl GA, 2004, SCIENCE, V305, P994, DOI 10.1126/science.1098704
   Middel A, 2014, LANDSCAPE URBAN PLAN, V122, P16, DOI 10.1016/j.landurbplan.2013.11.004
   Nastos PT, 2012, THEOR APPL CLIMATOL, V108, P591, DOI 10.1007/s00704-011-0555-0
   Niemelä J, 1999, BIODIVERS CONSERV, V8, P119, DOI 10.1023/A:1008817325994
   Nikolopoulou M, 2006, BUILD ENVIRON, V41, P1455, DOI 10.1016/j.buildenv.2005.05.031
   Park M, 2012, BUILD ENVIRON, V56, P38, DOI 10.1016/j.buildenv.2012.02.015
   PATTON D R, 1975, Wildlife Society Bulletin, V3, P171
   Perini K, 2014, URBAN FOR URBAN GREE, V13, P495, DOI 10.1016/j.ufug.2014.03.003
   Sarrat C, 2006, ATMOS ENVIRON, V40, P1743, DOI 10.1016/j.atmosenv.2005.11.037
   Shashua-Bar L, 2000, ENERG BUILDINGS, V31, P221, DOI 10.1016/S0378-7788(99)00018-3
   Spronken-Smith RA, 1998, INT J REMOTE SENS, V19, P2085, DOI 10.1080/014311698214884
   Taha H, 1997, ENERG BUILDINGS, V25, P99, DOI 10.1016/S0378-7788(96)00999-1
   Taleghani M, 2014, BUILD ENVIRON, V73, P138, DOI 10.1016/j.buildenv.2013.12.006
   Thorsson S, 2007, INT J CLIMATOL, V27, P1983, DOI 10.1002/joc.1537
   Thorsson S, 2011, INT J CLIMATOL, V31, P324, DOI 10.1002/joc.2231
   Vailshery LS, 2013, URBAN FOR URBAN GREE, V12, P408, DOI 10.1016/j.ufug.2013.03.002
   Vitasse Y, 2009, OECOLOGIA, V161, P187, DOI 10.1007/s00442-009-1363-4
   Vos CC, 2008, J APPL ECOL, V45, P1722, DOI 10.1111/j.1365-2664.2008.01569.x
   Wang YP, 2015, URBAN FOR URBAN GREE, V14, P8, DOI 10.1016/j.ufug.2014.11.005
   Wania A, 2012, J ENVIRON MANAGE, V94, P91, DOI 10.1016/j.jenvman.2011.06.036
   Weng QH, 2004, REMOTE SENS ENVIRON, V89, P467, DOI 10.1016/j.rse.2003.11.005
   WILMERS F, 1991, ENERG BUILDINGS, V15, P507
   Wong NH, 2005, HABITAT INT, V29, P547, DOI 10.1016/j.habitatint.2004.04.008
   Zerbe S, 2002, FOREST ECOL MANAG, V167, P27, DOI 10.1016/S0378-1127(01)00686-7
   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
NR 70
TC 169
Z9 182
U1 35
U2 364
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 2018
VL 34
BP 85
EP 96
DI 10.1016/j.ufug.2018.06.002
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 GQ3KK
UT WOS:000441562200010
DA 2025-01-10
ER

PT J
AU Ariani, A
   Teran, JCBMY
   Gepts, P
AF Ariani, Andrea
   Mier y Teran, Jorge Carlos Berny
   Gepts, Paul
TI Spatial and Temporal Scales of Range Expansion in Wild <i>Phaseolus
   vulgaris</i>
SO MOLECULAR BIOLOGY AND EVOLUTION
LA English
DT Article
DE climate adaptation; coalescent analysis; crop wild relatives;
   genotyping-by-sequencing; long-distance dispersal
ID 2 GENE POOLS; CHLOROPLAST DNA VARIATION; DISTANCE SEED DISPERSAL;
   ARABIDOPSIS-THALIANA; POPULATION-STRUCTURE; HYBRID WEAKNESS; COMMON;
   DIVERSITY; DOMESTICATION; ORIGIN
AB The wild progenitor of common-bean has an exceptionally large distribution from northern Mexico to northwestern Argentina, unusual among crop wild progenitors. This research sought to document major events of range expansion that led to this distribution and associated environmental changes. Through the use of genotyping-by-sequencing (similar to 20,000 SNPs) and geographic information systems applied to a sample of 246 accessions of wild Phaseolus vulgaris, including 157 genotypes of the Mesoamerican, 77 of the southern Andean, and 12 of the Northern Peru-Ecuador gene pools, we identified five geographically distinct subpopulations. Three of these subpopulations belong to the Mesoamerican gene pool (Northern and Central Mexico, Oaxaca, and Southern Mexico, Central America and northern South America) and one each to the Northern Peru-Ecuador (PhI) and the southern Andean gene pools. The five subpopulations were distributed in different floristic provinces of the Neotropical seasonally dry forest and showed distinct distributions for temperature and rainfall resulting in decreased local potential evapotranspiration (PhI and southern Andes groups) compared with the two Mexican groups. Three of these subpopulations represent long-distance dispersal events from Mesoamerica into Northern Peru-Ecuador, southern Andes, and Central America and Colombia, in chronological order. Of particular note is that the dispersal to Northern Peru-Ecuador markedly predates the dispersal to the southern Andes (similar to 400 vs. similar to 100 ky), consistent with the ancestral nature of the phaseolin seed protein and chloroplast sequences observed in the PhI group. Seed dispersal in common bean can be, therefore, described at different spatial and temporal scales, from localized, annual seed shattering to longaEuroEdistance, evolutionarily rare migration.
C1 [Ariani, Andrea; Mier y Teran, Jorge Carlos Berny; Gepts, Paul] Univ Calif Davis, Dept Plant Sci, Sect Crop & Ecosyst Sci, Davis, CA 95616 USA.
C3 University of California System; University of California Davis
RP Gepts, P (corresponding author), Univ Calif Davis, Dept Plant Sci, Sect Crop & Ecosyst Sci, Davis, CA 95616 USA.
EM plgepts@ucdavis.edu
RI Gepts, Paul/B-4417-2009
OI Gepts, Paul/0000-0002-1056-4665; Ariani, Andrea/0000-0002-3356-5329;
   Berny Mier y Teran, Jorge C./0000-0003-3709-9131
FU NIH S10 Instrumentation Grant [S10RR029668, S10RR027303]; Agriculture
   and Food Research Initiative (AFRI) Competitive Grant from the USDA
   National Institute of Food and Agriculture [2013-67013-21224]; NIFA
   [577414, 2013-67013-21224] Funding Source: Federal RePORTER
FX This work used the Vincent J. Coates Genomics Sequencing Laboratory at
   UC Berkeley, supported by NIH S10 Instrumentation Grants S10RR029668 and
   S10RR027303. This project was supported by Agriculture and Food Research
   Initiative (AFRI) Competitive Grant No. 2013-67013-21224 from the USDA
   National Institute of Food and Agriculture. We thank the Genetic
   Resources Unit of the Centro Internacional de Agricultura Tropical
   (CIAT, Cali, Colombia) and the Western Regional Plant Introduction
   Station of the USDA (Pullman, WA) for providing samples of wild P.
   vulgaris used in this study.
CR Ariani A, 2016, MOL BREEDING, V36, DOI 10.1007/s11032-016-0512-9
   Balanzà V, 2016, DEVELOPMENT, V143, P3372, DOI 10.1242/dev.135202
   Bellucci E, 2014, PLANT CELL, V26, P1901, DOI 10.1105/tpc.114.124040
   BERGLUNDBRUCHER O, 1976, ECON BOT, V30, P257, DOI 10.1007/BF02909734
   Bialozyt R, 2006, J EVOLUTION BIOL, V19, P12, DOI 10.1111/j.1420-9101.2005.00995.x
   Bitocchi E, 2013, NEW PHYTOL, V197, P300, DOI 10.1111/j.1469-8137.2012.04377.x
   Bitocchi E, 2012, P NATL ACAD SCI USA, V109, pE788, DOI 10.1073/pnas.1108973109
   Blair ME, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0043027
   Brucher H., 1988, Genetic resources of Phaseolus beans., P185
   Burkart A., 1953, Zuchter, V23, P65, DOI 10.1007/BF00712180
   Cain ML, 2000, AM J BOT, V87, P1217, DOI 10.2307/2656714
   Caye K, 2016, MOL ECOL RESOUR, V16, P540, DOI 10.1111/1755-0998.12471
   Chacón S MI, 2007, PLANT SYST EVOL, V266, P175, DOI 10.1007/s00606-007-0536-z
   Cortés AJ, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0062898
   CROW J F, 1970, P591, DOI 10.1093/bioinformatics/btr330
   Csilléry K, 2012, METHODS ECOL EVOL, V3, P475, DOI 10.1111/j.2041-210X.2011.00179.x
   DEBOUCK DG, 1993, ECON BOT, V47, P408, DOI 10.1007/BF02907356
   Debouck DG, 1991, COMMON BEANS RES CRO
   Delgado-Salinas A, 1999, SYST BOT, V24, P438, DOI 10.2307/2419699
   Edgar RC, 2004, NUCLEIC ACIDS RES, V32, P1792, DOI 10.1093/nar/gkh340
   Excoffier L, 2013, PLOS GENET, V9, DOI 10.1371/journal.pgen.1003905
   Excoffier L, 2010, MOL ECOL RESOUR, V10, P564, DOI 10.1111/j.1755-0998.2010.02847.x
   Fofana B, 2001, GENET RESOUR CROP EV, V48, P437, DOI 10.1023/A:1012016030318
   Ford-Lloyd BV, 2011, BIOSCIENCE, V61, P559, DOI 10.1525/bio.2011.61.7.10
   Freyre R, 1996, ECON BOT, V50, P195, DOI 10.1007/BF02861451
   FREYTAG G.F., 2002, TAXONOMY DISTRIBUTIO, DOI 10.3/JQUERY-UI.JS
   Gabriel SB, 2002, SCIENCE, V296, P2225, DOI 10.1126/science.1069424
   GENTRY HS, 1969, ECON BOT, V23, P55, DOI 10.1007/BF02862972
   GEPTS P, 1985, J HERED, V76, P447, DOI 10.1093/oxfordjournals.jhered.a110142
   GEPTS P, 1986, ECON BOT, V40, P469, DOI [10.1007/BF02859659, 10.1007/BF02859660]
   Gepts P, 1998, HORTSCIENCE, V33, P1124, DOI 10.21273/HORTSCI.33.7.1124
   Gepts Paul, 2008, V1, P113
   Gutierrez Salgado A., 1995, Genetic Resources and Crop Evolution, V42, P15, DOI 10.1007/BF02310680
   Hannah MA, 2007, NEW PHYTOL, V176, P537, DOI 10.1111/j.1469-8137.2007.02215.x
   HUDSON RR, 1992, GENETICS, V132, P583
   Jombart T, 2008, BIOINFORMATICS, V24, P1403, DOI 10.1093/bioinformatics/btn129
   KAMI J, 1995, P NATL ACAD SCI USA, V92, P1101, DOI 10.1073/pnas.92.4.1101
   KOENIG R, 1989, THEOR APPL GENET, V78, P809, DOI 10.1007/BF00266663
   KOINANGE EMK, 1992, J HERED, V83, P135, DOI 10.1093/oxfordjournals.jhered.a111173
   Koinange EMK, 1996, CROP SCI, V36, P1037, DOI 10.2135/cropsci1996.0011183X003600040037x
   Kwak M, 2009, CROP SCI, V49, P554, DOI 10.2135/cropsci2008.07.0421
   Kwak M, 2009, THEOR APPL GENET, V118, P979, DOI 10.1007/s00122-008-0955-4
   Lee TH, 2014, BMC GENOMICS, V15, DOI 10.1186/1471-2164-15-162
   Lenser T, 2013, PLANT J, V76, P545, DOI 10.1111/tpj.12321
   Li H, 2009, BIOINFORMATICS, V25, P1094, DOI [10.1093/bioinformatics/btp100, 10.1093/bioinformatics/btp324]
   Liepelt S, 2002, P NATL ACAD SCI USA, V99, P14590, DOI 10.1073/pnas.212285399
   Lischer HEL, 2012, BIOINFORMATICS, V28, P298, DOI 10.1093/bioinformatics/btr642
   Mamidi S, 2013, HEREDITY, V110, P267, DOI 10.1038/hdy.2012.82
   Marechal R, 1978, ETUDE TAXONOMIQUE GR
   McBryde FW., 1947, SMITHSONIAN I PUBLIC, V4, P1
   Medina V, 2017, FIELD CROP RES, V206, P128, DOI 10.1016/j.fcr.2017.02.010
   MIRANDA-COLIN S, 1967, Agrociencia, V1, P99
   Nathan R, 2003, OIKOS, V103, P261, DOI 10.1034/j.1600-0706.2003.12146.x
   Papa R, 2003, THEOR APPL GENET, V106, P239, DOI 10.1007/s00122-002-1085-z
   Petit RJ, 2004, FOREST ECOL MANAG, V197, P117, DOI 10.1016/j.foreco.2004.05.009
   Petit RJ, 2002, FOREST ECOL MANAG, V156, P5, DOI 10.1016/S0378-1127(01)00645-4
   Pires MM, 2018, ECOGRAPHY, V41, P153, DOI 10.1111/ecog.03163
   PRAKKEN R., 1934, GENETICA, V16, P177, DOI 10.1007/BF02071498
   Purcell S, 2007, AM J HUM GENET, V81, P559, DOI 10.1086/519795
   REMSEN JV, 1984, SCIENCE, V224, P171, DOI 10.1126/science.224.4645.171
   Rendón-Anaya M, 2017, PHYTOTAXA, V313, P259, DOI 10.11646/phytotaxa.313.3.3
   Rendón-Anaya M, 2017, GENOME BIOL, V18, DOI 10.1186/s13059-017-1190-6
   Rodriguez M, 2016, NEW PHYTOL, V209, P1781, DOI 10.1111/nph.13713
   Sandom C, 2014, P ROY SOC B-BIOL SCI, V281, DOI 10.1098/rspb.2013.3254
   Schmutz J, 2014, NAT GENET, V46, P707, DOI 10.1038/ng.3008
   Serrano-Serrano ML, 2010, MOL PHYLOGENET EVOL, V54, P76, DOI 10.1016/j.ympev.2009.08.028
   SHII CT, 1980, J HERED, V71, P218, DOI 10.1093/oxfordjournals.jhered.a109353
   SINGH SP, 1991, ECON BOT, V45, P379, DOI 10.1007/BF02887079
   Sirolli H, 2015, GENET RESOUR CROP EV, V62, P115, DOI 10.1007/s10722-014-0139-9
   Sorte FAL, 2016, P R SOC B, V283
   Stenoien HK, 2005, MOL ECOL, V14, P137, DOI 10.1111/j.1365-294X.2004.02359.x
   Sukumaran J, 2010, BIOINFORMATICS, V26, P1569, DOI 10.1093/bioinformatics/btq228
   Suzuki M, 2009, PLANT PROD SCI, V12, P217, DOI 10.1626/pps.12.217
   TAJIMA F, 1989, GENETICS, V123, P585
   Toro CO, 1990, CIAT PUBL, V181
   van Heerwaarden J, 2011, P NATL ACAD SCI USA, V108, P1088, DOI 10.1073/pnas.1013011108
   Viana DS, 2016, P ROY SOC B-BIOL SCI, V283, DOI 10.1098/rspb.2015.2406
   Vlasova A, 2016, GENOME BIOL, V17, DOI 10.1186/s13059-016-0883-6
   Wegmann D, 2010, BMC BIOINFORMATICS, V11, DOI 10.1186/1471-2105-11-116
   Xavier A, 2016, BMC BIOINFORMATICS, V17, DOI 10.1186/s12859-016-0899-7
   Zeven AC, 1997, EUPHYTICA, V94, P319, DOI 10.1023/A:1002940220241
NR 81
TC 41
Z9 49
U1 1
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 JAN
PY 2018
VL 35
IS 1
BP 119
EP 131
DI 10.1093/molbev/msx273
PG 13
WC Biochemistry & Molecular Biology; Evolutionary Biology; Genetics &
   Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Evolutionary Biology; Genetics &
   Heredity
GA FS1PH
UT WOS:000419548800011
PM 29069389
OA Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Nalau, J
   Becken, S
   Noakes, S
   Mackey, B
AF Nalau, J.
   Becken, S.
   Noakes, S.
   Mackey, B.
TI Mapping Tourism Stakeholders' Weather and Climate Information-Seeking
   Behavior in Fiji
SO WEATHER CLIMATE AND SOCIETY
LA English
DT Article
ID CHANGE ADAPTATION; WINTER TOURISM; DECISION-MAKING; POLICY; DEMAND;
   PREFERENCES; VULNERABILITY; PERCEPTIONS; KNOWLEDGE; FORECAST
AB Tourism is inherently dependent on weather and climate, and its sustainability and resilience to adverse weather and climate impacts is greatly enhanced by providing tailored climate services to tourism sector stakeholders. Climate services need to integrate standard weather forecasts, with early warning systems, seasonal forecasts, and long-term projections of climatic changes in order to meet the information needs of the sector. While a growing number of studies address the potential climate change impacts on tourism, little is known about how the tourism sector accesses, uses, and analyses the available weather and climate information.
   This research presents findings from an exploratory study on weather and climate information-seeking behavior of 15 private and public tourism sector stakeholders in the Republic of Fiji. The results show a variety of weather and climate information-seeking paths in use, which differ depending on levels of professional responsibility, weather and climate literacy, and information and digital competency. Those with high weather information literacy access a broader variety of sources. Hence, their interpretation does not focus only on their own location, but "weather'' is seen as a broad spatial phenomenon that might or might not result in adverse effects in their location. Understanding diverse weather and climate information-seeking paths can aid in better targeting climate and adaptation services across different stakeholder groups. Especially in the context of small island developing states (SIDS), the integration of traditional, local, and scientific knowledge as information sources is likely to provide a more useful and context-specific basis for climate adaptation planning within the sector.
C1 [Nalau, J.; Mackey, B.] Griffith Univ, Griffith Climate Change Response Program, Southport, Qld, Australia.
   [Nalau, J.; Becken, S.; Noakes, S.] Griffith Univ, Griffith Inst Tourism, Southport, Qld, Australia.
C3 Griffith University; Griffith University - Gold Coast Campus; Griffith
   University; Griffith University - Gold Coast Campus
RP Nalau, J (corresponding author), Griffith Univ, Griffith Climate Change Response Program, Southport, Qld, Australia.; Nalau, J (corresponding author), Griffith Univ, Griffith Inst Tourism, Southport, Qld, Australia.
EM j.nalau@griffith.edu.au
RI Mackey, Brendan/ABE-3805-2020; Becken, Susanne/AFK-2875-2022; Nalau,
   Johanna/V-5692-2018
OI Mackey, Brendan/0000-0003-1996-4064; Becken,
   Susanne/0000-0002-3348-2750; Nalau, Johanna/0000-0001-6581-3967
CR [Anonymous], 2008, Climate Change and Tourism. Responding to Global Challenges
   [Anonymous], 2007, The Honest Broker: Making Sense of Science in Policy and Politics
   Aylen J, 2014, CLIMATIC CHANGE, V127, P183, DOI 10.1007/s10584-014-1261-6
   Ayscue EP, 2015, TOURISM GEOGR, V17, P603, DOI 10.1080/14616688.2015.1053974
   Bafaluy D, 2014, REG ENVIRON CHANGE, V14, P1995, DOI 10.1007/s10113-013-0450-6
   Bawden D, 2001, J DOC, V57, P218, DOI 10.1108/EUM0000000007083
   Bazeley P., 2016, WORLDWIDE HOSP TOURI, V8, P578, DOI [10.1108/WHATT-06-2016-0033, DOI 10.1108/WHATT-06-2016-0033]
   Bazeley P., 2012, CLIMATE CHANGE TOURI
   Bazeley P., 2007, Qualitative data analysis with NVivo
   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
   Bloodhart B, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0141526
   Bonzanigo L, 2016, J SUSTAIN TOUR, V24, P637, DOI 10.1080/09669582.2015.1122013
   Catts R., 2012, Journal of Information Literacy, V6, P4, DOI DOI 10.11645/6.2.1746
   Chand SS, 2014, WEATHER CLIM SOC, V6, P445, DOI 10.1175/WCAS-D-13-00053.1
   Conway D, 2014, NAT CLIM CHANGE, V4, P339, DOI 10.1038/NCLIMATE2199
   Curtis S, 2011, B AM METEOROL SOC, V92, P361, DOI 10.1175/2010BAMS2983.1
   de Freitas CR, 2003, INT J BIOMETEOROL, V48, P45, DOI 10.1007/s00484-003-0177-z
   Dilling L, 2015, WEATHER CLIM SOC, V7, P5, DOI 10.1175/WCAS-D-14-00001.1
   Dilling L, 2011, GLOBAL ENVIRON CHANG, V21, P680, DOI 10.1016/j.gloenvcha.2010.11.006
   Dubois G, 2016, CLIMATIC CHANGE, V136, P339, DOI 10.1007/s10584-016-1620-6
   Endler C, 2010, INT J BIOMETEOROL, V54, P45, DOI 10.1007/s00484-009-0251-2
   Ezzy D., 2002, QUALITATIVE ANAL PRA
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Finucane ML, 2013, WEATHER CLIM SOC, V5, P293, DOI 10.1175/WCAS-D-12-00039.1
   Fontana A., 2003, Collecting and Interpreting Qualitative Materials, V2nd
   Gaskell G., 2000, QUALITATIVE RES TEXT, V5th, P38, DOI DOI 10.4135/9781849209731
   Gibbs GR, 2007, Analyzing qualitative data, V703, P38, DOI DOI 10.4135/9781849208574
   Goosen H, 2014, REG ENVIRON CHANGE, V14, P1035, DOI 10.1007/s10113-013-0513-8
   Gössling S, 2012, ANN TOURISM RES, V39, P36, DOI 10.1016/j.annals.2011.11.002
   Hay JE, 2013, SUSTAIN SCI, V8, P303, DOI 10.1007/s11625-013-0220-x
   Hazeleger W, 2015, NAT CLIM CHANGE, V5, P107, DOI 10.1038/NCLIMATE2450
   Hewer MJ, 2015, THEOR APPL CLIMATOL, V121, P401, DOI 10.1007/s00704-014-1228-6
   Holstein J.A., 2003, INSIDE INTERVIEWING
   Hopkins D, 2013, REG ENVIRON CHANGE, V13, P449, DOI 10.1007/s10113-012-0352-z
   Hughey KFD, 2014, GLOBAL ENVIRON CHANG, V27, P168, DOI 10.1016/j.gloenvcha.2014.03.004
   Jeuring J. H. G., 2013, Journal of Vacation Marketing, V19, P209, DOI 10.1177/1356766712457104
   Jeuring J, 2013, TOURISM MANAGE, V37, P193, DOI 10.1016/j.tourman.2013.02.004
   Johnston A, 2012, NORTH REV, P69
   Kahlor LA, 2007, MEDIA PSYCHOL, V10, P414, DOI 10.1080/15213260701532971
   King A., 2016, CONVERSATION
   Klint L. M., 2012, Tourism in Marine Environments, V8, P91, DOI 10.3727/154427312X13262430524225
   Kuruppu N, 2015, WEATHER CLIM EXTREME, V7, P72, DOI [10.1016/j.wace.2014.06.001, 10.1010/j.wace.2014.06.001]
   Lebel L, 2013, MITIG ADAPT STRAT GL, V18, P1057, DOI 10.1007/s11027-012-9407-1
   Leiserowitz A, 2006, CLIMATIC CHANGE, V77, P45, DOI 10.1007/s10584-006-9059-9
   Lemos MC, 2015, CURR OPIN ENV SUST, V12, P48, DOI 10.1016/j.cosust.2014.09.005
   Lewins A., 2007, USING SOFTWARE QUALI, DOI DOI 10.4135/9780857025012.D85
   Linnenluecke MK, 2012, BUS STRATEG ENVIRON, V21, P17, DOI 10.1002/bse.708
   Lorenzoni I, 2007, GLOBAL ENVIRON CHANG, V17, P445, DOI 10.1016/j.gloenvcha.2007.01.004
   Lourenço TC, 2016, NAT CLIM CHANGE, V6, P13, DOI 10.1038/nclimate2836
   Mahon R., 2013, EVALUATING BUSINESS, V32
   Martin BG, 2005, ANN TOURISM RES, V32, P571, DOI 10.1016/j.annals.2004.08.004
   Matzarakis A, 2006, TOUR PLAN DEV, V3, P99, DOI 10.1080/14790530600938279
   Michailidou AV, 2016, TOURISM MANAGE, V55, P1, DOI 10.1016/j.tourman.2016.01.010
   Miles M.B., 1995, Qualitative data analysis: An expanded sourcebook
   Montz BE, 2015, METEOROL APPL, V22, P323, DOI 10.1002/met.1457
   Nalau J, 2016, CLIM DEV, V8, P365, DOI 10.1080/17565529.2015.1064809
   Nalau J, 2015, ENVIRON SCI POLICY, V54, P349, DOI 10.1016/j.envsci.2015.07.022
   Nurse LA, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1613
   Pütz M, 2011, MT RES DEV, V31, P357, DOI 10.1659/MRD-JOURNAL-D-11-00039.1
   Punch K.F., 2005, Introduction to social research: Quantitative and qualitative approaches
   Rossello J, 2014, CLIMATIC CHANGE, V124, P119, DOI 10.1007/s10584-014-1086-3
   Rutty M, 2014, WEATHER CLIM SOC, V6, P293, DOI 10.1175/WCAS-D-13-00052.1
   Sarewitz D, 2004, PHILOS TODAY, V48, P67, DOI 10.5840/philtoday200448Supplement8
   Sarewitz D, 2007, ENVIRON SCI POLICY, V10, P5, DOI 10.1016/j.envsci.2006.10.001
   Scott D, 2010, PROCEDIA ENVIRON SCI, V1, P146, DOI 10.1016/j.proenv.2010.09.011
   Scott D, 2016, J SUSTAIN TOUR, V24, P8, DOI 10.1080/09669582.2015.1062021
   Scott DJ, 2011, CLIM RES, V47, P111, DOI 10.3354/cr00952
   Shakeela A, 2015, J SUSTAIN TOUR, V23, P65, DOI 10.1080/09669582.2014.918135
   SPTO, 2016, ANN REV TOUR ARR PAC
   Stewart AE, 2012, WEATHER CLIM SOC, V4, P172, DOI 10.1175/WCAS-D-11-00033.1
   Tervo K, 2008, SCAND J HOSP TOUR, V8, P317, DOI 10.1080/15022250802553696
   Uyarra MC, 2005, ENVIRON CONSERV, V32, P11, DOI 10.1017/S0376892904001808
   Warren Carol., 2010, DISCOVERING QUALITAT, V2nd
   Weaver CP, 2013, WIRES CLIM CHANGE, V4, P39, DOI 10.1002/wcc.202
   Wilson J., 2011, DISTRIBUTION CLIMATE
   Wilson J, 2011, NEW ZEAL GEOGR, V67, P148, DOI 10.1111/j.1745-7939.2011.01208.x
   WILSON TD, 1981, J DOC, V37, P3, DOI 10.1108/eb026702
   WMO, 2016, CLIM SERV INTR
   Yu GM, 2009, CLIMATIC CHANGE, V95, P551, DOI 10.1007/s10584-009-9565-7
   Zabini F, 2015, METEOROL APPL, V22, P495, DOI 10.1002/met.1480
NR 82
TC 23
Z9 29
U1 4
U2 89
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 JUL
PY 2017
VL 9
IS 3
BP 377
EP 391
DI 10.1175/WCAS-D-16-0078.1
PG 15
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 FB1SY
UT WOS:000405925000004
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Vacchiano, G
   Garbarino, M
   Lingua, E
   Motta, R
AF Vacchiano, Giorgio
   Garbarino, Matteo
   Lingua, Emanuele
   Motta, Renzo
TI Forest dynamics and disturbance regimes in the Italian Apennines
SO FOREST ECOLOGY AND MANAGEMENT
LA English
DT Article
DE Forest dynamics; Italy; Land use change; Mediterranean mountains;
   Natural disturbances; Palaeoecology
ID FAGUS-SYLVATICA L.; CLIMATE-CHANGE; NORTHERN APENNINES; NATIONAL-PARK;
   QUATERNARY HISTORY; GENETIC DIVERSITY; SOUTHERN EUROPE; BEECH;
   VEGETATION; MANAGEMENT
AB Forests of the Apennines are characterised by high canopy cover and high tree species diversity (being at the interface between two major climatic zones of Europe), and provide important ecosystem functions to millions of people. They exemplify cutting-edge themes such as forest ecology in warmer climates, consequences of heavy land use, and resilience at the trailing edge of the distribution of many European forest species (Silver fir, Norway spruce, Beech, Black pine, Birch).
   We introduce the setting under the geological and climatological point of view and review the literature on the interactions between these long-term drivers and the specific, structural, and genetic diversity of these forest communities (e.g., effects of glacial refugia or tectonic/volcanic activity), followed by a brief outline of what little is known about natural disturbance regimes and their range of variability. Anthropogenic disturbances (fire, grazing) and land use changes (abandonment of cropland and pasture) have been by far the main drivers of forest dynamics at least for the last two millennia, determining for examples overageing of coppices, treeline advances, forest encroachment on former agricultural land.
   We suggest considerations about the interplay between these land use changes and disturbance drivers (e.g. fuel continuity), summarize comparisons between managed and unmanaged forests (e.g., increase in tree size, deadwood, biodiversity indicators), and elaborate on current proposals for climate-adapted management, highlighting specific and genetic diversity as an important source of resilience and adaptive potential. (C) 2016 Elsevier B.V. All rights reserved.
C1 [Vacchiano, Giorgio; Motta, Renzo] Univ Turin, DISAFA, Largo Braccini 2, I-10095 Grugliasco, TO, Italy.
   [Garbarino, Matteo] Univ Politecn Marche, D3A,Via Brecce Bianche, I-60131 Ancona, Italy.
   [Lingua, Emanuele] Univ Padua, TESAF, Viale Univ 16, I-35020 Legnaro, PD, Italy.
C3 University of Turin; Marche Polytechnic University; University of Padua
RP Vacchiano, G (corresponding author), Univ Turin, DISAFA, Largo Braccini 2, I-10095 Grugliasco, TO, Italy.
EM giorgio.vacchiano@unito.it; matteo.garbarino@univpm.it;
   emanuele.lingua@unipd.it; renzo.motta@unito.it
RI Vacchiano, Giorgio/H-3645-2019; Vacchiano, Giorgio/C-4494-2008; Lingua,
   Emanuele/B-2941-2008; Garbarino, Matteo/N-4686-2015; Motta,
   Renzo/B-5542-2008
OI Vacchiano, Giorgio/0000-0001-8100-0659; Lingua,
   Emanuele/0000-0001-9515-7657; Garbarino, Matteo/0000-0002-9010-1731;
   Motta, Renzo/0000-0002-1631-3840
CR Alessandrini A, 2011, FOREST ECOL MANAG, V262, P1950, DOI 10.1016/j.foreco.2011.08.025
   Allevato E, 2010, J ARCHAEOL SCI, V37, P2365, DOI 10.1016/j.jas.2010.04.010
   [Anonymous], 2013, Annals of Silvicultural Research, DOI DOI 10.12899/ASR-771
   [Anonymous], ITALIA FORESTALE MON
   [Anonymous], 2007, Biogeographia, DOI [DOI 10.21426/B6110070, 10.21426/B6110070]
   Ascoli D, 2015, FOREST ECOL MANAG, V353, P126, DOI 10.1016/j.foreco.2015.05.031
   Bagnato S., 2014, Forest@, V11, P52, DOI 10.3832/efor1191-011
   Bebi P, 2017, FOREST ECOL MANAG, V388, P43, DOI 10.1016/j.foreco.2016.10.028
   Benesperi R, 2012, BIODIVERS CONSERV, V21, P3555, DOI 10.1007/s10531-012-0380-5
   Bengtsson J, 2000, FOREST ECOL MANAG, V132, P39, DOI 10.1016/S0378-1127(00)00378-9
   BERGER AL, 1978, J ATMOS SCI, V35, P2362, DOI [10.1175/1520-0469(1978)035<2362:LTVODI>2.0.CO;2, 10.1016/0033-5894(78)90064-9]
   Bertoldi R., 1981, Ateneo Parmense, Acta Naturalia, V16, P147
   Biondi E, 2015, PLANT BIOSYST, V149, P603, DOI 10.1080/11263504.2015.1044481
   BOCQUET G, 1978, Candollea, V33, P269
   Bottalico F., 2015, ATT 2 C INT SELV, V1, P257
   Bracchetti L, 2012, LANDSCAPE URBAN PLAN, V104, P157, DOI 10.1016/j.landurbplan.2011.09.005
   Bradshaw RHW, 2010, FOREST ECOL MANAG, V259, P2204, DOI 10.1016/j.foreco.2009.11.035
   Branch NP, 2014, QUATERN INT, V353, P34, DOI 10.1016/j.quaint.2013.07.053
   Brown AG, 2013, J QUATERNARY SCI, V28, P71, DOI 10.1002/jqs.2591
   Brunetti M, 2006, INT J CLIMATOL, V26, P345, DOI 10.1002/joc.1251
   Brunetti M, 2001, INT J CLIMATOL, V21, P299, DOI 10.1002/joc.613
   Brunialti G, 2010, PLANT BIOSYST, V144, P221, DOI 10.1080/11263500903560959
   Calamini G., 2011, Italia Forestale e Montana, V66, P365
   Calò C, 2012, PALAEOGEOGR PALAEOCL, V323, P110, DOI 10.1016/j.palaeo.2012.01.038
   Carminati E, 2003, GEOPHYS RES LETT, V30, DOI 10.1029/2003GL017001
   Carminati E, 2012, TECTONOPHYSICS, V579, P173, DOI 10.1016/j.tecto.2012.01.026
   Casanova P., 2005, ITALIA FORESTALE MON, V60, P213
   Catorci A, 2012, POL J ECOL, V60, P79
   Cavazzoni Zanotti, 1907, BOSCHI E FERROVIE
   Chirici G., 2013, ITALIA FORESTALE MON, V65, P475
   Ciucci P, 2008, URSUS, V19, P130, DOI 10.2192/07PER012.1
   Compostella C, 2014, HOLOCENE, V24, P393, DOI 10.1177/0959683613518588
   Conedera M, 2004, VEG HIST ARCHAEOBOT, V13, P161, DOI 10.1007/s00334-004-0038-7
   Coppini M, 2007, FOREST ECOL MANAG, V249, P18, DOI 10.1016/j.foreco.2007.04.035
   Corona P, 2008, PLANT BIOSYST, V142, P509, DOI 10.1080/11263500802410850
   Corona P, 2014, IFOREST, V7, P300, DOI 10.3832/ifor1123-007
   Corpo Forestale dello Stato, 2016, INC BOSCH NEL 2015
   Corso G., 2005, ATT 9 C AS, V9, P799
   Costantini M., 2010, RADICI SOSTENIBILITA
   Cremaschi M, 2011, ATT 43 RIUN SCI ET R, P225
   Cutini A, 2011, ANN FOREST SCI, V68, P667, DOI 10.1007/s13595-011-0072-4
   De Philippis A., 1937, CLASSIFICAZIONI INDI
   De Sillo R., 2012, Plant Sociology, V49, P3, DOI 10.7338/pls2012491S1/01
   Devoti R, 2008, EARTH PLANET SC LETT, V273, P163, DOI 10.1016/j.epsl.2008.06.031
   Di Filippo A, 2007, J BIOGEOGR, V34, P1873, DOI 10.1111/j.1365-2699.2007.01747.x
   Di Filippo A, 2010, ANN FOREST SCI, V67, DOI 10.1051/forest/2010031
   Di Rita F, 2013, QUATERN INT, V288, P73, DOI 10.1016/j.quaint.2011.11.011
   Di Rita F, 2009, HOLOCENE, V19, P295, DOI 10.1177/0959683608100574
   Dibari C, 2015, ITAL J AGRON, V10, P109, DOI 10.4081/ija.2015.659
   Edwards AC, 2007, QUATERN INT, V162, P172, DOI 10.1016/j.quaint.2006.10.027
   Ellenberg H., 1986, VEGETATION MITTELEUR
   European Commission (EC), 2013, FOR FIR EUR MIDDL E
   Fabbri E, 2007, MOL ECOL, V16, P1661, DOI 10.1111/j.1365-294X.2007.03262.x
   Falcucci A, 2007, LANDSCAPE ECOL, V22, P617, DOI 10.1007/s10980-006-9056-4
   FAO, 2010, GLOB FOR RES ASS
   Florenzano GT, 2004, ITAL J ZOOL, V71, P317, DOI 10.1080/11250000409356589
   Gehrig-Fasel J, 2007, J VEG SCI, V18, P571, DOI 10.1111/j.1654-1103.2007.tb02571.x
   Giorgi F, 2008, GLOBAL PLANET CHANGE, V63, P90, DOI 10.1016/j.gloplacha.2007.09.005
   Guido MA, 2013, HOLOCENE, V23, P1517, DOI 10.1177/0959683613496294
   Henne PD, 2013, LANDSCAPE ECOL, V28, P819, DOI 10.1007/s10980-012-9782-8
   HUNTLEY B, 1989, J BIOGEOGR, V16, P551, DOI 10.2307/2845210
   Joannin S, 2012, CLIM PAST, V8, P1973, DOI 10.5194/cp-8-1973-2012
   Kulakowski D, 2017, FOREST ECOL MANAG, V388, P120, DOI 10.1016/j.foreco.2016.07.037
   Leonardi S, 2012, J HERED, V103, P408, DOI 10.1093/jhered/ess004
   Leonelli G, 2011, AMBIO, V40, P264, DOI 10.1007/s13280-010-0096-2
   Lionello P, 2006, DEV EARTH ENV SCI, V4, P1
   Lionello P., 2010, CAMBIAMENTI CLIMATIC, P81
   Lippi MM, 2007, VEG HIST ARCHAEOBOT, V16, P267, DOI 10.1007/s00334-006-0090-6
   Long JN, 2014, ANN FOREST SCI, V71, P325, DOI 10.1007/s13595-013-0351-3
   Lovreglio R, 2010, IFOREST, V3, P8, DOI 10.3832/ifor0521-003
   Luchi N, 2014, FOREST PATHOL, V44, P372, DOI 10.1111/efp.12109
   Luchi N., 2016, PLANT DIS
   Luchi N, 2016, IFOREST, V9, P49, DOI 10.3832/ifor1436-008
   Magri D, 2006, NEW PHYTOL, V171, P199, DOI 10.1111/j.1469-8137.2006.01740.x
   Magri D, 2015, REV PALAEOBOT PALYNO, V218, P267, DOI 10.1016/j.revpalbo.2014.08.012
   Mancini N. M., 2016, Italia Forestale e Montana, V71, P31
   Marchetti M., 2010, Italia Forestale e Montana, V65, P679
   Marchetti M, 2010, PLANT BIOSYST, V144, P130, DOI 10.1080/11263500903560470
   Mensing S, 2013, ANN BOT-COENOL PLANT, V3, P121, DOI 10.4462/annbotrm-10243
   Mercuri A.M., 2013, MISCELLANEA INGV, V18, P128
   MIPAAF, 2007, INV NAZ FOR SERB CAR
   MONTANARI C, 1989, GRANA, V28, P305, DOI 10.1080/00173138909427443
   Motta R., 2013, ITALIA FORESTALE MON, V65, P591
   Muller SD, 2007, J BIOGEOGR, V34, P876, DOI 10.1111/j.1365-2699.2006.01665.x
   Munafo M., 2015, COMUNI COMUNITA APPE
   Negro M, 2014, FOREST ECOL MANAG, V328, P300, DOI 10.1016/j.foreco.2014.05.049
   Nicolaci A, 2015, IFOREST, V8, P497, DOI 10.3832/ifor1041-007
   Nocentini S, 2009, IFOREST, V2, P105, DOI 10.3832/ifor0499-002
   Paffetti D, 2012, FOREST ECOL MANAG, V284, P34, DOI 10.1016/j.foreco.2012.07.026
   Palombo C, 2013, PLANT BIOSYST, V147, P1, DOI 10.1080/11263504.2013.772081
   Palombo C, 2014, J VEG SCI, V25, P571, DOI 10.1111/jvs.12101
   Pasquale G Di, 2010, PLANT BIOSYST, V144, P865
   Patrone G., 1953, CONTRIBUTO STATO ENT
   Pedrotti F., 2003, ECOL STU AN, P73
   Petit RJ, 2002, FOREST ECOL MANAG, V156, P49, DOI 10.1016/S0378-1127(01)00634-X
   Pezzi G., 2007, Forest@-Journal Silviculture For. Ecol, V4, P79
   Pezzi G, 2011, LANDSCAPE ECOL, V26, P1463, DOI 10.1007/s10980-011-9661-8
   Piccioli L., 1923, SELVICOLTURA
   Piermattei A., EUR J FORES IN PRESS
   Pignatti G., 2011, Forest Journal of Silviculture and Forest Ecology, V8, P1, DOI [DOI 10.3832/EF0R0650-008, 10.3832/efor0650-008, DOI 10.3832/EFOR0650-008]
   Piotti A., 2014, MONTANA, V69, P115
   Piovesan G, 2008, GLOBAL CHANGE BIOL, V14, P1265, DOI 10.1111/j.1365-2486.2008.01570.x
   PLINI P., 1989, NATURA MONTAGNA, V36, P21
   Puddu A, 2003, FOREST ECOL MANAG, V180, P37, DOI 10.1016/S0378-1127(02)00607-2
   Ravazzi C, 2002, REV PALAEOBOT PALYNO, V120, P131, DOI 10.1016/S0034-6667(01)00149-X
   Ray N., 2001, INTERNET ARCHAEOL, V11, DOI [10.11141/ia.11.2, DOI 10.11141/IA.11.2]
   Regione Toscana D. P. G. R., 2003, B UFFICIALE REGIONE, V37, P32
   Romano D., 1987, QUADERNI MONTE BOSCH
   Rosenbaum G, 2004, TECTONICS, V23, DOI 10.1029/2003TC001518
   ROSSIGNOLSTRICK M, 1989, NATURE, V342, P413, DOI 10.1038/342413a0
   Sadori L, 2016, QUATERNARY SCI REV, V136, P173, DOI 10.1016/j.quascirev.2015.09.020
   Sadori L, 2015, REV PALAEOBOT PALYNO, V218, P217, DOI 10.1016/j.revpalbo.2014.02.004
   Schulz T, 2014, BIODIVERS CONSERV, V23, P3425, DOI 10.1007/s10531-014-0817-0
   Seidl R, 2014, NAT CLIM CHANGE, V4, P806, DOI [10.1038/nclimate2318, 10.1038/NCLIMATE2318]
   Temperli C, 2012, ECOL APPL, V22, P2065, DOI 10.1890/12-0210.1
   TINNER W, 1995, B SOC TICINESE SCI N, V83, P91
   Tinner W, 2013, ECOL MONOGR, V83, P419, DOI 10.1890/12-2231.1
   Tonon G, 2005, ANN FOREST SCI, V62, P669, DOI 10.1051/forest:2005059
   Travaglini D, 2012, PLANT BIOSYST, V146, P175, DOI 10.1080/11263504.2011.650731
   Triglia A., 2014, RAPPORTO SINTESI DIS
   Tzedakis PC, 1995, QUATERNARY SCI REV, V14, P967, DOI 10.1016/0277-3791(95)00042-9
   UZUNOV D., 2005, INFORM BOT ITALIANO, V37, P386
   Vacchiano G, 2016, MT RES DEV, V36, P41, DOI 10.1659/MRD-JOURNAL-D-15-00075.1
   Vacchiano G, 2014, SCI TOTAL ENVIRON, V472, P778, DOI 10.1016/j.scitotenv.2013.11.101
   Vacchiano G, 2012, IFOREST, V5, P113, DOI 10.3832/ifor0614-005
   Vacchiano G, 2012, EUR J FOREST RES, V131, P989, DOI 10.1007/s10342-011-0570-9
   Valese E, 2014, ANTHROPOCENE, V6, P63, DOI 10.1016/j.ancene.2014.06.006
   Valsecchi V, 2008, HOLOCENE, V18, P603, DOI 10.1177/0959683608089213
   Valva V.L., 1992, Plant Biosyst, V126, P131, DOI [10.1080/11263509209430271, DOI 10.1080/11263509209430271]
   van Gils H, 2010, FOREST ECOL MANAG, V259, P433, DOI 10.1016/j.foreco.2009.10.040
   van Gils H, 2008, APPL VEG SCI, V11, P539, DOI 10.3170/2008-7-18568
   VENANZONI R, 1993, LANDSCAPE URBAN PLAN, V24, P55, DOI 10.1016/0169-2046(93)90083-P
   Vettraino AM, 2005, EUR J PLANT PATHOL, V111, P169, DOI 10.1007/s10658-004-1882-0
   Vignali Giuseppe, 2015, Forest@, V12, P16, DOI 10.3832/efor1539-012
   Vizzarri M, 2015, FORESTS, V6, P1810, DOI 10.3390/f6061810
   Wang L, 2012, HYDROL EARTH SYST SC, V16, P2585, DOI 10.5194/hess-16-2585-2012
   Watson CS, 1996, J BIOGEOGR, V23, P805, DOI 10.1111/j.1365-2699.1996.tb00041.x
   Westphal C, 2006, FOREST ECOL MANAG, V223, P75, DOI 10.1016/j.foreco.2005.10.057
   Ziaco E, 2012, FOREST ECOL MANAG, V286, P28, DOI 10.1016/j.foreco.2012.09.005
NR 139
TC 56
Z9 58
U1 6
U2 90
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 MAR 15
PY 2017
VL 388
BP 57
EP 66
DI 10.1016/j.foreco.2016.10.033
PG 10
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Forestry
GA ES4RA
UT WOS:000399521200006
OA Green Submitted
DA 2025-01-10
ER

PT J
AU Ma, L
   Ahuja, LR
   Islam, A
   Trout, TJ
   Saseendran, SA
   Malone, RW
AF Ma, L.
   Ahuja, L. R.
   Islam, A.
   Trout, T. J.
   Saseendran, S. A.
   Malone, R. W.
TI Modeling yield and biomass responses of maize cultivars to climate
   change under full and deficit irrigation
SO AGRICULTURAL WATER MANAGEMENT
LA English
DT Article
DE Systems modeling; RZWQM; DSSAT; Cultivar traits; Climate adaptation;
   Crop simulation; Irrigation management; Colorado
ID CHANGE IMPACTS; ADAPTATION STRATEGIES; PLANTING DATE; MANAGEMENT; SOIL;
   VARIABILITY; OPTIONS; SYSTEMS; CROPS
AB With as much as 4.8 degrees C increase in air temperature by end of 21st century, new crop cultivars are needed for adapting to the new climate. The objective of this study was to identify maize (Zea mays L) cultivar parameters that maintain yield under projected climate for late in the 21st century under full and deficit irrigation in a semi-arid region. The Root Zone Water Quality Model (RZWQM2) was calibrated with four years of maize data from northeastern Colorado, USA, under various irrigation conditions and was then used to simulate climate change effects on maize production with current management practices. Results showed that projected climate change decreased yield by 21% and biomass by 7% late in the 21st century (2070-2091) under full irrigation, compared to yield in the current climate (1992-2013). Under deficit irrigation, the corresponding reductions were 14% and 3%, respectively. Using the cultivar parameters calibrated with RZWQM2 for southern Colorado condition did not show yield decrease under future climate, but it simulated much lower yield under current climate in northeastern Colorado. A cultivar from the DSSAT (Decision Support Systems for Agrotechnology Transfer) crop database (GL 482) produced similar yield to experimental data under current climate and increased yield by 4% at full irrigation under future climate in northeastern Colorado. Using Latin Hypercube Sampling (LHS), we also identified 70 cultivars with longer maturity duration (between silking and physiological maturity) and higher grain filling rate for mitigating climate change effects on maize production. These two identified traits can guide plant breeders in developing cultivars for the future. Published by Elsevier B.V.
C1 [Ma, L.; Ahuja, L. R.] USDA ARS, Agr Syst Res Unit, Ft Collins, CO 80526 USA.
   [Islam, A.] ICAR Res Complex, Div Nat Resources Management NRM, New Delhi 110012, India.
   [Trout, T. J.] USDA ARS, Water Management & Syst Res Unit, Ft Collins, CO 80526 USA.
   [Saseendran, S. A.] USDA ARS, Crop Prod Syst Res Unit, Stoneville, MS 38776 USA.
   [Malone, R. W.] USDA ARS, Natl Lab Agr & Environm, Ames, IA 50011 USA.
C3 United States Department of Agriculture (USDA); United States Department
   of Agriculture (USDA); United States Department of Agriculture (USDA);
   United States Department of Agriculture (USDA)
RP Ma, L (corresponding author), USDA ARS, Agr Syst Res Unit, Ft Collins, CO 80526 USA.
EM Liwang.Ma@ars.usda.gov
RI malone, rob/JYP-5668-2024; Islam, Adlul/AAD-8508-2021
OI Islam, Adlul/0000-0001-5828-1114; Ma, Liwang/0000-0002-7451-5221; ,
   Robert/0000-0001-5498-3864; Trout, Thomas/0000-0003-1896-9170
CR Ahuja L.R., 2000, The Root Zone Water Quality Model, P372
   Allen R. G., 1998, FAO Irrigation and Drainage Paper
   Bhuvaneswari K, 2014, J AGROMETEOROL, V16, P38
   Brisson N, 2011, ACTA HORTIC, V889, P167, DOI 10.17660/ActaHortic.2011.889.18
   Dharmarathna WRSS, 2014, SUSTAIN SCI, V9, P103, DOI 10.1007/s11625-012-0192-2
   Ding DY, 2016, CLIMATIC CHANGE, V138, P157, DOI 10.1007/s10584-016-1714-1
   Estes LD, 2013, GLOBAL CHANGE BIOL, V19, P3762, DOI 10.1111/gcb.12325
   Fang Q.X., 2014, USE SYSTEM MODELS OP, P1
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Guo RP, 2010, AGR WATER MANAGE, V97, P1185, DOI 10.1016/j.agwat.2009.07.006
   Hamlet A.F., 2010, Statistical downscaling techniques for global climate model simulations of temperature and precipitation with application to water resources planning studies
   Islam A, 2012, T ASABE, V55, P2135
   Islam A, 2012, AGR WATER MANAGE, V110, P94, DOI 10.1016/j.agwat.2012.04.004
   Jones JW, 2003, EUR J AGRON, V18, P235, DOI 10.1016/S1161-0301(02)00107-7
   Kassie BT, 2013, ENVIRON MANAGE, V52, P1115, DOI 10.1007/s00267-013-0145-2
   Ko JH, 2012, CLIMATIC CHANGE, V111, P445, DOI [10.1007/s10584-011-0175-9, 10.1007/S10584-011-0175-9]
   Lavania D, 2015, PLANT PHYSIOL BIOCH, V86, P100, DOI 10.1016/j.plaphy.2014.11.019
   Liu ZJ, 2013, GLOBAL CHANGE BIOL, V19, P3481, DOI 10.1111/gcb.12324
   Lobell DB, 2011, SCIENCE, V333, P616, DOI [10.1126/science.1206376, 10.1126/science.1204531]
   Lopez-Norliega I., 2012, FLOWS STRESS AVAILAB, P88
   Ma L, 2007, T ASABE, V50, P1705, DOI 10.13031/2013.23962
   Ma L, 2000, T ASAE, V43, P883, DOI 10.13031/2013.2984
   Ma L, 2006, AGR SYST, V87, P274, DOI 10.1016/j.agsy.2005.02.001
   Ma LW, 2016, AGRON J, V108, P171, DOI 10.2134/agronj2015.0206
   Ma LW, 2012, AGR WATER MANAGE, V103, P140, DOI 10.1016/j.agwat.2011.11.005
   Meinshausen M, 2011, CLIMATIC CHANGE, V109, P213, DOI 10.1007/s10584-011-0156-z
   Meza FJ, 2008, AGR SYST, V98, P21, DOI 10.1016/j.agsy.2008.03.005
   Monzon JP, 2007, FIELD CROP RES, V101, P44, DOI 10.1016/j.fcr.2006.09.007
   Moradi R, 2014, MITIG ADAPT STRAT GL, V19, P1223, DOI 10.1007/s11027-013-9470-2
   Moradi R, 2013, MITIG ADAPT STRAT GL, V18, P265, DOI 10.1007/s11027-012-9410-6
   Nendel C, 2014, EUR J AGRON, V52, P47, DOI 10.1016/j.eja.2012.09.005
   Rezaei EE, 2014, EUR J AGRON, V55, P77, DOI 10.1016/j.eja.2014.02.001
   Saseendran SA, 2015, AGR WATER MANAGE, V157, P65, DOI 10.1016/j.agwat.2014.09.002
   Singh P, 2014, MITIG ADAPT STRAT GL, V19, P509, DOI 10.1007/s11027-012-9446-7
   Singh P, 2014, J AGROMETEOROL, V16, P52
   Singh P, 2014, EUR J AGRON, V52, P123, DOI 10.1016/j.eja.2013.09.018
   Stocker, 2014, CLIMATE CHANGE 2013
   Tachie-Obeng E, 2013, ENVIRON DEV, V5, P131, DOI 10.1016/j.envdev.2012.11.008
   Wang ZZ, 2016, ENVIRON MODELL SOFTW, V84, P99, DOI 10.1016/j.envsoft.2016.06.016
   Wood AW, 2002, J GEOPHYS RES-ATMOS, V107, DOI 10.1029/2001JD000659
   Yu QY, 2014, J INTEGR AGR, V13, P1599, DOI 10.1016/S2095-3119(14)60805-4
NR 41
TC 38
Z9 43
U1 3
U2 104
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 JAN 31
PY 2017
VL 180
BP 88
EP 98
DI 10.1016/j.agwat.2016.11.007
PN A
PG 11
WC Agronomy; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Water Resources
GA EG0RX
UT WOS:000390741000009
DA 2025-01-10
ER

PT C
AU Barney, DL
   Hummer, KE
   Robertson, NL
   Gilmore, BS
AF Barney, D. L.
   Hummer, K. E.
   Robertson, N. L.
   Gilmore, B. S.
BE Tanovic, B
TI <i>Ribes</i> L. Gene Bank Management in the United States
SO X INTERNATIONAL RUBUS AND RIBES SYMPOSIUM
SE Acta Horticulturae
LA English
DT Proceedings Paper
CT 10th International Rubus and Ribes Symposium
CY JUN 22-26, 2011
CL Zlatibor, SERBIA
SP Int Soc Hort Sci (ISHS), Sirogojno Co, Ploeger, Agro Market, BSK, Visys, Galenika - Fitofarmacija, Weremczuk, Syngenta, Univ Belgrade, Fac Agr, Inst Pesticide & Environm Protect
DE currant; gooseberry; genebank; genetic resources; germplasm
ID GOOSEBERRY; PCR; NIGRUM
AB A world collection of Ribes species and cultivars is maintained by the U. S. Department of Agriculture, Agricultural Research Service, National Plant Germplasm System (NPGS). The NPGS is a cooperative effort by State, Federal, and private organizations to preserve plant genetic diversity by acquiring, preserving, evaluating, documenting, and distributing crop germplasm. The program provides scientists and breeders around the world with access to genetically diverse plant materials to help develop new cultivars that are resistant to pests, diseases, and environmental stresses. Clonal material and seeds from species and cultivars of currants and gooseberries were collected from throughout North America, Europe, Asia, and South America, in accordance with international treaty requirements. Future efforts will continue to fill genetic gaps in collections. The Ribes collection is maintained at the National Clonal Germplasm Repository (NCGR) in Corvallis, Oregon and its worksite at the Arctic and Subarctic Plant Gene Bank (ASPGB) in Palmer, Alaska. Accessions are evaluated for climatic adaptability, growth characteristics, fruit characteristics, and disease susceptibility. Resistance to white pine blister rust (Cronartium ribicola J. C. Fisch.), powdery mildew (Podosphaera mors-uvae [Schwein] U. Braun & S. Takam and Podosphaera macularis [Wallr.] U. Braun & S. Takam), and other common diseases is determined through field observations and laboratory tests. The collection is screened for Tomato ringspot, Arabis mosaic, Tobacco rattle, Gooseberry vein-banding viruses, and phytoplasmas. Genetic fingerprints for standard cultivars are being developed through molecular marker analysis using simple sequence repeats (SSRs). Information on the Ribes collection and public access for requesting accessions is available online through the Germplasm Resources Information Network (GRIN). GRIN is available at http://www.ars-grin.gov/npgs.
C1 [Barney, D. L.; Robertson, N. L.] ARS, USDA, Arctic & Subarctic Plant Gene Bank, Palmer, AK 99645 USA.
   [Hummer, K. E.; Gilmore, B. S.] United States Dept Agr, Natl Clonal Germplasm Repository, Agr Res Serv, Corvallis, OR USA.
C3 United States Department of Agriculture (USDA); United States Department
   of Agriculture (USDA)
RP Barney, DL (corresponding author), ARS, USDA, Arctic & Subarctic Plant Gene Bank, Palmer, AK 99645 USA.
OI Hummer, Kim/0000-0003-4110-7501
CR Brennan R, 2008, EUPHYTICA, V161, P19, DOI 10.1007/s10681-007-9412-8
   Cavanna M, 2009, GENOME, V52, P839, DOI [10.1139/G09-057, 10.1139/g09-057]
   Dalton DT, 2010, PLANT DIS, V94, P461, DOI 10.1094/PDIS-94-4-0461
   DENG SJ, 1991, J MICROBIOL METH, V14, P53, DOI 10.1016/0167-7012(91)90007-D
   GRIESBACH JA, 1995, PLANT DIS, V79, P1054, DOI 10.1094/PD-79-1054
   Jennings TN, 2011, MOL ECOL RESOUR, V11, P1060, DOI 10.1111/j.1755-0998.2011.03033.x
   Jones AT, 2001, PLANT DIS, V85, P417, DOI 10.1094/PDIS.2001.85.4.417
   Lane L., 1993, PLANT DIS VIRAL VIRO, P1
   MURASHIGE T, 1962, PHYSIOL PLANTARUM, V15, P473, DOI 10.1111/j.1399-3054.1962.tb08052.x
   Nassuth A, 2000, J VIROL METHODS, V90, P37, DOI 10.1016/S0166-0934(00)00211-1
   Picton DD, 2003, HORTTECHNOLOGY, V13, P365, DOI 10.21273/HORTTECH.13.2.0365
   REED BM, 1995, CRYO-LETT, V16, P131
   You FM, 2008, BMC BIOINFORMATICS, V9, DOI 10.1186/1471-2105-9-253
NR 13
TC 0
Z9 0
U1 0
U2 8
PU INT SOC HORTICULTURAL SCIENCE
PI LEUVEN 1
PA PO BOX 500, 3001 LEUVEN 1, BELGIUM
SN 0567-7572
BN 978-90-66052-08-6
J9 ACTA HORTIC
PY 2012
VL 946
BP 73
EP 76
PG 4
WC Agronomy; Horticulture
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Agriculture
GA BDH71
UT WOS:000313283300008
DA 2025-01-10
ER

PT J
AU Swanson, DL
   Garland, T
AF Swanson, David L.
   Garland, Theodore, Jr.
TI THE EVOLUTION OF HIGH SUMMIT METABOLISM AND COLD TOLERANCE IN BIRDS AND
   ITS IMPACT ON PRESENT-DAY DISTRIBUTIONS
SO EVOLUTION
LA English
DT Article
DE Allometry; comparative method; energetics; evolutionary physiology;
   metabolic rate; metabolic theory of ecology; physiology
ID IN-HOUSE FINCHES; PHYLOGENETIC ANALYSIS; THERMOGENIC CAPACITY;
   OXYGEN-CONSUMPTION; SEASONAL-VARIATION; CONFIDENCE-INTERVALS; AVIAN
   DISTRIBUTIONS; CLIMATIC ADAPTATION; TEMPERATURE; BASAL
AB Summit metabolic rate (M-sum, maximum cold-induced metabolic rate) is positively correlated with cold tolerance in birds, suggesting that high M-sum is important for residency in cold climates. However, the phylogenetic distribution of high M-sum among birds and the impact of its evolution on current distributions are not well understood. Two potential adaptive hypotheses might explain the phylogenetic distribution of high M-sum among birds. The cold adaptation hypothesis contends that species wintering in cold climates should have higher M-sum than species wintering in warmer climates. The flight adaptation hypothesis suggests that volant birds might be capable of generating high M-sum as a byproduct of their muscular capacity for flight; thus, variation in M-sum should be associated with capacity for sustained flight, one indicator of which is migration. We collected M-sum data from the literature for 44 bird species and conducted both conventional and phylogenetically informed statistical analyses to examine the predictors of M-sum variation. Significant phylogenetic signal was present for log body mass, log mass-adjusted M-sum, and average temperature in the winter range. In multiple regression models, log body mass, winter temperature, and clade were significant predictors of log M-sum. These results are consistent with a role for climate in determining M-sum in birds, but also indicate that phylogenetic signal remains even after accounting for associations indicative of adaptation to winter temperature. Migratory strategy was never a significant predictor of log M-sum in multiple regressions, a result that is not consistent with the flight adaptation hypothesis.
C1 [Swanson, David L.] Univ S Dakota, Dept Biol, Vermillion, SD 57069 USA.
   [Garland, Theodore, Jr.] Univ Calif Riverside, Dept Biol, Riverside, CA 92521 USA.
C3 University of South Dakota; University of California System; University
   of California Riverside
RP Swanson, DL (corresponding author), Univ S Dakota, Dept Biol, Vermillion, SD 57069 USA.
EM david.swanson@usd.edu; tgarland@ucr.edu
OI Garland, Theodore/0000-0002-7916-3552
FU NSF EPSCoR [0091948, DEB-0416085]; American Philosophical Society;
   University of South Dakota Office of Research
FX Funding for this study was provided by NSF EPSCoR grant 0091948, the
   American Philosophical Society, and the University of South Dakota
   Office of Research. In addition, TG was supported by NSF DEB-0416085. We
   thank A. McKechnie, J. Williams, P. Wiersma, J. Olson, and two anonymous
   reviewers for valuable comments on earlier versions of this manuscript,
   and F. Bozinovic, E. Rezende, P. Sabat, and T. Maddocks for providing
   information on metabolic rates for Chilean birds and Lichenostomus
   fuscus. Finally, DLS thanks Mark Dixon for help with statistical
   analyses and G. Ribak for help with Matlab.
CR [Anonymous], AM J PHYSL REG I
   Arens JR, 2005, PHYSIOL BIOCHEM ZOOL, V78, P579, DOI 10.1086/430235
   Arnaiz-Villena A, 1998, CELL MOL LIFE SCI, V54, P1031, DOI 10.1007/s000180050230
   Barker FK, 2004, P NATL ACAD SCI USA, V101, P11040, DOI 10.1073/pnas.0401892101
   BENNETT AF, 1991, J EXP BIOL, V160, P1
   Berggren WilliamA., 1992, ECOENCE OLIGOCENE CL, P1
   Blomberg SP, 2003, EVOLUTION, V57, P717, DOI 10.1111/j.0014-3820.2003.tb00285.x
   Blomberg SP, 2002, J EVOLUTION BIOL, V15, P899, DOI 10.1046/j.1420-9101.2002.00472.x
   Blondel J, 1998, TRENDS ECOL EVOL, V13, P488, DOI 10.1016/S0169-5347(98)01461-X
   BOZINOVIC F, 1989, FUNCT ECOL, V3, P173, DOI 10.2307/2389298
   Canterbury G, 2002, ECOLOGY, V83, P946, DOI 10.1890/0012-9658(2002)083[0946:MAACCO]2.0.CO;2
   CASTRO G, 1989, ECOLOGY, V70, P1181, DOI 10.2307/1941385
   CHRISTIDIS L, 1991, CONDOR, V93, P302, DOI 10.2307/1368946
   Clobert J, 1998, J EVOLUTION BIOL, V11, P329
   Cooper SJ, 2002, PHYSIOL BIOCHEM ZOOL, V75, P386, DOI 10.1086/342256
   DAWSON WR, 1976, J COMP PHYSIOL, V112, P317, DOI 10.1007/BF00692302
   DAWSON WR, 1983, PHYSIOL ZOOL, V56, P353, DOI 10.1086/physzool.56.3.30152600
   DAWSON WR, 1983, AM J PHYSIOL, V245, pR755, DOI 10.1152/ajpregu.1983.245.6.R755
   Duncan RP, 2007, ECOLOGY, V88, P324, DOI 10.1890/0012-9658(2007)88[324:TTMTOE]2.0.CO;2
   Fain MG, 2004, EVOLUTION, V58, P2558
   Feduccia A, 2003, TRENDS ECOL EVOL, V18, P172, DOI 10.1016/S0169-5347(03)00017-X
   FEDUCCIA A, 1995, SCIENCE, V267, P637, DOI 10.1126/science.267.5198.637
   FELSENSTEIN J, 1985, AM NAT, V125, P1, DOI 10.1086/284325
   Freckleton RP, 2002, AM NAT, V160, P712, DOI 10.1086/343873
   Garland T, 2000, AM NAT, V155, P346, DOI 10.1086/303327
   Garland T, 1999, AM ZOOL, V39, P374
   Garland T, 2005, J EXP BIOL, V208, P3015, DOI 10.1242/jeb.01745
   GARLAND T, 1992, SYST BIOL, V41, P18, DOI 10.2307/2992503
   GARLAND T, 1993, SYST BIOL, V42, P265, DOI 10.2307/2992464
   GARLAND T, 1991, ANNU REV ECOL SYST, V22, P193, DOI 10.1146/annurev.es.22.110191.001205
   GARLAND T, 1992, AM NAT, V140, P509, DOI 10.1086/285424
   Gibb GC, 2007, MOL BIOL EVOL, V24, P269, DOI 10.1093/molbev/msl158
   Guglielmo CG, 2002, AM J PHYSIOL-REG I, V282, pR1405, DOI 10.1152/ajpregu.00267.2001
   HART J. S., 1962, PHYSIOL ZOOL, V35, P224
   Hill Richard W., 1993, P131
   HINDS DS, 1993, J EXP BIOL, V182, P41
   Hutcheon James M., 2004, Journal of Mammalian Evolution, V11, P257, DOI 10.1023/B:JOMM.0000047340.25620.89
   Ives AR, 2007, SYST BIOL, V56, P252, DOI 10.1080/10635150701313830
   James HF, 2005, AUK, V122, P1049, DOI 10.1642/0004-8038(2005)122[1049:PFATRO]2.0.CO;2
   Lavin SR, 2008, PHYSIOL BIOCHEM ZOOL, V81, P526, DOI 10.1086/590395
   Liknes ET, 1996, J AVIAN BIOL, V27, P279, DOI 10.2307/3677259
   Lougheed SC, 2000, MOL PHYLOGENET EVOL, V17, P367, DOI 10.1006/mpev.2000.0843
   Marsh R.L., 1989, Advances in Comparative and Environmental Physiology, V4, P205
   Mayr G, 2005, BIOL REV, V80, P515, DOI 10.1017/S1464793105006779
   McKechnie AE, 2004, PHYSIOL BIOCHEM ZOOL, V77, P502, DOI 10.1086/383511
   McKechnie AE, 2006, P ROY SOC B-BIOL SCI, V273, P931, DOI 10.1098/rspb.2005.3415
   McWilliams SR, 2004, J AVIAN BIOL, V35, P377, DOI 10.1111/j.0908-8857.2004.03378.x
   Muñoz-Garcia A, 2005, PHYSIOL BIOCHEM ZOOL, V78, P1039, DOI 10.1086/432852
   Nishibori M, 2002, J HERED, V93, P439, DOI 10.1093/jhered/93.6.439
   NOVOA FF, 1990, COMP BIOCHEM PHYS A, V95, P181, DOI 10.1016/0300-9629(90)90029-R
   O'Meara BC, 2006, EVOLUTION, V60, P922
   OCONNOR TP, 1995, J COMP PHYSIOL B, V165, P298, DOI 10.1007/BF00367313
   REPASKY RR, 1991, ECOLOGY, V72, P2274, DOI 10.2307/1941577
   Reynolds PS, 1996, AM NAT, V147, P735, DOI 10.1086/285877
   Rezende EL, 2002, J EXP BIOL, V205, P101
   Rezende EL, 2004, EVOLUTION, V58, P1361
   Rezende EL, 2001, AUK, V118, P781, DOI 10.1642/0004-8038(2001)118[0781:SACEOA]2.0.CO;2
   Rezende EL, 2006, J APPL PHYSIOL, V101, P477, DOI 10.1152/japplphysiol.00042.2006
   Roberts TJ, 1996, J EXP BIOL, V199, P1651
   ROOT T, 1988, ECOLOGY, V69, P330, DOI 10.2307/1940431
   ROSENMANN M, 1974, AM J PHYSIOL, V226, P490, DOI 10.1152/ajplegacy.1974.226.3.490
   SAARELA S, 1995, J COMP PHYSIOL B, V165, P366, DOI 10.1007/BF00387307
   SWANSON DL, 1990, AUK, V107, P561
   Swanson DL, 2006, J EXP BIOL, V209, P466, DOI 10.1242/jeb.02024
   Swanson DL, 1999, J AVIAN BIOL, V30, P245, DOI 10.2307/3677350
   Swanson DL, 1995, AUK, V112, P870, DOI 10.2307/4089019
   Swanson DL, 1999, PHYSIOL BIOCHEM ZOOL, V72, P566, DOI 10.1086/316696
   Swanson DL, 1997, CONDOR, V99, P478, DOI 10.2307/1369954
   Swanson DL, 2001, J COMP PHYSIOL B, V171, P475, DOI 10.1007/s003600100197
   Vaanholt LM, 2007, J EXP BIOL, V210, P2013, DOI 10.1242/jeb.001974
   WEATHERS WW, 1979, OECOLOGIA, V42, P81, DOI 10.1007/BF00347620
   Wiersma P, 2007, P NATL ACAD SCI USA, V104, P9340, DOI 10.1073/pnas.0702212104
   Wolfe JA., 1982, Climate in Earth History, P154
NR 73
TC 95
Z9 115
U1 0
U2 47
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0014-3820
EI 1558-5646
J9 EVOLUTION
JI Evolution
PD JAN
PY 2009
VL 63
IS 1
BP 184
EP 194
DI 10.1111/j.1558-5646.2008.00522.x
PG 11
WC Ecology; Evolutionary Biology; Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Evolutionary Biology; Genetics &
   Heredity
GA 394TB
UT WOS:000262469600015
PM 18803689
DA 2025-01-10
ER

PT J
AU Viherä-Aarnio, A
   Velling, P
AF Vihera-Aarnio, Anneli
   Velling, Pirkko
TI Seed Transfers of Silver Birch (<i>Betula pendula</i>) from the Baltic
   to Finland Effect on Growth and Stem Quality
SO SILVA FENNICA
LA English
DT Article
DE Betula pendula; climatic adaptation; provenance; stem defect; yield
ID FREEZING TOLERANCE; WOODY PLANTS; ECOTYPES; ORIGIN
AB Silver birch (Betula pendula Roth) seed origins from the Baltic countries, Finland and Russia were compared for survival, growth and stem quality, and the effect of latitudinal seed transfer distance examined in two provenance trials. The trials were located on moist upland forest soils at Tuusula (60 degrees 21'N) in southern Finland and at Viitasaari (63 degrees 11'N) in central Finland. The material consisted of 21 stand and single tree origins ranging from latitudes 54 degrees to 63 degrees N. Survival, height, dbh, relative stem taper, stem volume/ha and the proportion of trees with a stem defect (vertical branch or forked stem), were assessed when the trees were 22 years old. Significant differences were detected among the origins regarding all the measured traits in both trials. Southern Finnish origins produced the highest volume per unit area in central Finland, whereas Estonian and north Latvian stand seed origins, as well as the southern Finnish plus tree origins, were the most productive ones in southern Finland. The more southern the origin, the higher was the proportion of trees with a stem defect in both trials. The latitudinal seed transfer distance had a significant but relatively small effect on survival, stem volume/ha and proportion of trees with a stern defect. The proportion of trees with a stein defect increased linearly in relation to the seed transfer distance from the south. The relationship of both survival and stem volume/ha to the seed transfer distance was curvilinear. Volume/ha was increased by transferring seed from ca. 2 degrees of latitude from the south. A longer transfer from the south, as well as transfer from the north, decreased the yield.
C1 [Vihera-Aarnio, Anneli; Velling, Pirkko] Finnish Forest Res Inst, Vantaa Res Unit, FI-01301 Vantaa, Finland.
C3 Natural Resources Institute Finland (Luke)
RP Viherä-Aarnio, A (corresponding author), Finnish Forest Res Inst, Vantaa Res Unit, POB 18, FI-01301 Vantaa, Finland.
EM anneli.vihera-aarnio@metla.fi; pirkko.velling@metla.fi
FU Finnish Academy
FX Mr Erkki Kosonen, Mr Veijo Hakamdki, Mr Juhani Mdkinen and Mr Heimo
   Tynkkynen made the measurements, and the data was put to electronic form
   by Mrs Tuula Viitanen. Ms MariaLeena Annala assisted in preliminary
   processing of the data, and Mrs Anne Siika and Mrs Sari Elomaa drew the
   figures. Dr Risto Hdkkinen gave us valuable advice in the statistical
   analysis. Dr Michael Starr revised the Enalish text. Prof. Katri
   Kdrkk5inen and Dr Matti Haapanen read the manuscript critically. We wish
   to thank them all for their help and co-operation. We also wish to thank
   the Finnish Forest and Park Service for providing the experimental site
   and for co-operation in establishment and early management of the trial
   at Viitasaari. This study was financed by the Finnish Academy as a part
   of the Life-2000 Research programme of biological functions.
CR [Anonymous], THESIS U JOENSUU
   [Anonymous], 1949, ACTA FOR FENN
   [Anonymous], FINN STAT YB FOR 200
   CLAUSEN KE, 1968, P 8 LAK STAT FOR TRE, P1
   Erken T., 1972, Sveriges Skogsvardsforbunds Tidskrift, V70, P435
   HABJORG P, 1972, MELDINGER NORGES LAN, V51
   HABJORG P, 1978, MELDINGER NORGES LAN, V57
   Hagman M., 1980, Silva Fennica, V14, P32
   HAGQVIST R, 1998, 13 FDN FOR TREE BREE
   HAGQVIST R, 1991, SUMMARY PRODUCTION G, P12
   HEIKINHEIMO O., 1949, COMMUN INST FOREST FENNIAL, V37, P1
   Heiskanen V., 1966, ACTA FORESTALIA FENN, V80
   Heräjärvi H, 2002, FOREST PROD J, V52, P40
   Johnsson H., 1967, Association for Forest Tree Breeding. Yearbook 1966., P90
   Johnsson H., 1976, ARSBOK, V1976, P48
   JOHNSSON H, 1951, SVEN PAPPERSTIDN, V54, P412
   JUNTTILA O, 1993, NATO ADV SCI INST SE, V244, P43
   Karkkainen M., 1986, Silva Fennica, V20, P45
   KELLOMAKI S, 1996, PUBLICATIONS ACAD FI, P252
   Kleinschmit J., 1980, Forst- und Holzwirt, V35, P81
   Kleinschmit J., 2002, Forst und Holz, V57, P470
   Kleinschmit J., 1998, Forst und Holz, V53, P99
   Koski V., 1985, Crop physiology of forest trees. Proceedings of an international conference on managing forest trees as cultivated plants, held in Finland, 23-28 July 1984, P167
   Laasasenaho J., 1982, COMMUN I FENN, V108, P1
   LAIVINS M, 2003, EARTH ENV SCI, V654, P7
   LANGHAMMER A, 1982, SUMMARY GROWTH STUDI, V61
   Lanner R. M., 1976, Tree physiology and yield improvement - shoot and cambial growth., P223
   Li CY, 2003, TREES-STRUCT FUNCT, V17, P127, DOI 10.1007/s00468-002-0214-2
   Li CY, 2002, PHYSIOL PLANTARUM, V116, P478, DOI 10.1034/j.1399-3054.2002.1160406.x
   MARTTILA V, 2005, 12005 PUBL MIN AGR F
   *METS OY, 2006, HYV METS SUOS
   NIEMISTO P, 1995, SCAND J FOREST RES, V10, P235, DOI 10.1080/02827589509382889
   Niemisto P, 1997, FOLIA FOR, V4, P439
   NITSCH J. P., 1957, PROC AMER SOC HORT SCI, V70, P526
   Pollard D. F. W., 1976, Tree physiology and yield improvement - shoot and cambial growth., P245
   RAULO J, 1978, Silva Fennica, V12, P17
   Raulo J., 1979, COMMUNICATIONES I FO, V97
   Raulo J., 1977, COMMUNICATIONES I FO, V90
   RAULO J, 1976, COMMUNICATIONES I FO, V88
   SHARIK TL, 1976, CAN J BOT, V54, P2122, DOI 10.1139/b76-228
   Stener L.-G., 1995, SKOGFORSK REDOGORELS, V1, P1
   Stener L-G., 1997, SKOGFORSK REDOGORELS, V3, P1
   STENER LG, 1997, SKOGFORSK REDOGORELS, V6, P1
   Sutinen R, 2002, CAN J FOREST RES, V32, P1158, DOI [10.1139/x02-076, 10.1139/X02-076]
   Talkkari A, 1998, FOREST ECOL MANAG, V106, P97, DOI 10.1016/S0378-1127(97)00300-9
   Velling P., 2002, Forst und Holz, V57, P459
   Velling P, 1979, FOLIA FORESTALIA, V379
   Viherä-Aarnio A, 2005, TREE PHYSIOL, V25, P101, DOI 10.1093/treephys/25.1.101
   Viherä-Aarnio A, 2006, TREE PHYSIOL, V26, P1013, DOI 10.1093/treephys/26.8.1013
   Viherä-Aarnio A, 2006, FOREST ECOL MANAG, V229, P325, DOI 10.1016/j.foreco.2006.04.011
   VIHERAAARNIO A, 1994, NORW J AGR SCI S, V18, P19
   WAREING PF, 1956, ANNU REV PLANT PHYS, V7, P191, DOI 10.1146/annurev.pp.07.060156.001203
   WEISER CJ, 1970, SCIENCE, V169, P1269, DOI 10.1126/science.169.3952.1269
NR 53
TC 18
Z9 18
U1 0
U2 8
PU FINNISH SOC FOREST SCIENCE-NATURAL RESOURCES INST FINLAND
PI VANTAA
PA PO BOX 18, FI-01301 VANTAA, FINLAND
SN 0037-5330
EI 2242-4075
J9 SILVA FENN
JI Silva. Fenn.
PY 2008
VL 42
IS 5
BP 735
EP 751
AR 226
DI 10.14214/sf.226
PG 17
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Forestry
GA 389FK
UT WOS:000262076400004
OA Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Huey, RB
   Moreteau, B
   Moreteau, JC
   Gibert, P
   Gilchrist, GW
   Ives, AR
   Garland, T
   David, JR
AF Huey, Raymond B.
   Moreteau, Brigitte
   Moreteau, Jean-Claude
   Gibert, Patricia
   Gilchrist, George W.
   Ives, Anthony R.
   Garland, Theodore, Jr.
   David, Jean R.
TI Sexual size dimorphism in a <i>Drosophila</i> clade, the
   <i>D-obscura</i> group
SO ZOOLOGY
LA English
DT Article
DE comparative method; female/male ratio; Rensch's rule; thorax length;
   wing length
ID PHYLOGENETIC ANALYSIS; REACTION NORMS; CLIMATIC ADAPTATION; BODY-SIZE;
   EVOLUTION; MELANOGASTER; TEMPERATURE; TRAITS
AB The Drosophila obscura clade consists of about 41 species, of which 20 were used for analyses of wing and thorax length. Our primary goal was to investigate the magnitude of sexual size dimorphism (SSD) of these traits within this clade and to test Rensch's Rule [when females are larger than males, SSD (e.g., female/male ratio) should decrease with body size]. Our secondary goal was methodological and involved evaluating for these flies alternative measures of SSD (female/male ratio, female/male absolute difference, female/male relative difference), developing a bootstrap method to estimate the magnitude of intraspecific variation in SSD, and applying a new method of estimating allometric relationships that is phylogenetically based and incorporates error variance in both traits. All indices of SSD were strongly correlated for both size traits. Nevertheless, female/male ratio is the best index here: it is easily interpretable and essentially independent of size. For both traits, SSD (F/M) varied interspecifically, showed a strong phylogenctic signal, but did not differ for the main phylogenetic subgroups or correlate with latitude. Factors underlying variation in SSD in this clade are elusive and might include genetic drift. SSD (wing) tended to decrease with increasing size, as predicted by Rensch's Rule, though not consistently so. SSD (thorax) was unrelated to size. However, analysis of published data for thorax length of Drosophila spp. (N = 42) with a larger size range showed that SSD decreased significantly with increasing size (consistent with Rensch's Rule), suggesting our ability to detect SSD-size relations in the D. obscura data may be limited by low statistical power. (c) 2006 Elsevier GmbH. All rights reserved.
C1 Univ Washington, Dept Biol, Seattle, WA 98195 USA.
   CNRS, Lab Evolut Gen & Speciat, F-91198 Gif Sur Yvette, France.
   Univ Metz, Equipe Demecol, Lab Biodivers & Fonctionnement Ecosyst, UFR Sci Fondamentales & Appl, F-57070 Metz, France.
   Univ Lyon 1, CNRS, UMR 5558, Lab Biomet & Biol Evolut, F-69622 Villeurbanne, France.
   Coll William & Mary, Dept Biol, Williamsburg, VA 23187 USA.
   Univ Wisconsin, Dept Zool, Madison, WI 53706 USA.
   Univ Calif Riverside, Dept Biol, Riverside, CA 92521 USA.
C3 University of Washington; University of Washington Seattle; Centre
   National de la Recherche Scientifique (CNRS); Universite Paris Saclay;
   Universite de Lorraine; Universite Claude Bernard Lyon 1; Centre
   National de la Recherche Scientifique (CNRS); CNRS - Institute of
   Ecology & Environment (INEE); VetAgro Sup; William & Mary; University of
   Wisconsin System; University of Wisconsin Madison; University of
   California System; University of California Riverside
RP Huey, RB (corresponding author), Univ Washington, Dept Biol, Box 351800, Seattle, WA 98195 USA.
EM hueyrb@u.washington.edu
RI Huey, Raymond/F-1597-2010; Ives, Anthony/A-5698-2008
OI Huey, Raymond/0000-0002-4962-8670; Garland,
   Theodore/0000-0002-7916-3552; Gibert, Patricia/0000-0002-9461-6820
CR Andersson Malte, 1994
   [Anonymous], 2005, Drosophila. A laboratory handbook
   Blomberg SP, 2003, EVOLUTION, V57, P717, DOI 10.1111/j.0014-3820.2003.tb00285.x
   CABRERA VM, 1983, EVOLUTION, V37, P675, DOI 10.1111/j.1558-5646.1983.tb05589.x
   Cardillo M, 2002, J ANIM ECOL, V71, P79, DOI 10.1046/j.0021-8790.2001.00577.x
   Cox RM, 2005, PHYSIOL BIOCHEM ZOOL, V78, P531, DOI 10.1086/430226
   Cox RM, 2003, EVOLUTION, V57, P1653, DOI 10.1554/02-227
   Darwin C., 1871, DESCENT MAN SELECTIO, V2
   DAVID JEAN, 1965, BULL BIOL FRANCE BELG, V99, P369
   David JR, 2003, J GENET, V82, P79, DOI 10.1007/BF02715810
   DAVID JR, 1994, GENET SEL EVOL, V26, P229, DOI 10.1051/gse:19940305
   DAVID JR, 2006, IN PRESS GENETICA
   Fairbairn DJ, 1997, ANNU REV ECOL SYST, V28, P659, DOI 10.1146/annurev.ecolsys.28.1.659
   FELSENSTEIN J, 1985, AM NAT, V125, P1, DOI 10.1086/284325
   Freckleton RP, 2002, AM NAT, V160, P712, DOI 10.1086/343873
   Garland T, 2004, INTEGR COMP BIOL, V44, P556
   Garland T, 1999, AM ZOOL, V39, P374
   Garland T, 2005, J EXP BIOL, V208, P3015, DOI 10.1242/jeb.01745
   GARLAND T, 1992, SYST BIOL, V41, P18, DOI 10.2307/2992503
   GARLAND T, 1993, SYST BIOL, V42, P265, DOI 10.2307/2992464
   GARLAND T, 1991, ANNU REV ECOL SYST, V22, P193, DOI 10.1146/annurev.es.22.110191.001205
   GARLAND T, 1992, AM NAT, V140, P509, DOI 10.1086/285424
   Gibert P, 2001, PHYSIOL BIOCHEM ZOOL, V74, P429, DOI 10.1086/320429
   Gibert P, 2001, EVOLUTION, V55, P1063, DOI 10.1554/0014-3820(2001)055[1063:CCTAMC]2.0.CO;2
   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]
   IVES AR, UNPUB SYST BIOL
   Karan D, 1999, GENET SEL EVOL, V31, P491, DOI 10.1051/gse:19990505
   Karan D, 2000, GENETICA, V108, P91, DOI 10.1023/A:1004090517967
   Kopp A, 2001, NATURE, V410, P611, DOI 10.1038/35069125
   LLOPART A, 2000, NATURE, V408, P553
   LOVICH JE, 1992, GROWTH DEVELOP AGING, V56, P181
   Matos M, 2002, J EVOLUTION BIOL, V15, P673, DOI 10.1046/j.1420-9101.2002.00405.x
   Moreteau B, 1997, CR ACAD SCI III-VIE, V320, P833, DOI 10.1016/S0764-4469(97)85020-2
   Moreteau B, 2003, J ZOOL SYST EVOL RES, V41, P64, DOI 10.1046/j.1439-0469.2003.00195.x
   O'Grady PM, 1999, MOL PHYLOGENET EVOL, V12, P124, DOI 10.1006/mpev.1998.0598
   PAGEL MD, 1992, J THEOR BIOL, V156, P431, DOI 10.1016/S0022-5193(05)80637-X
   PITNICK S, 1995, P NATL ACAD SCI USA, V92, P10614, DOI 10.1073/pnas.92.23.10614
   POWELL J.R., 1997, PROGR PROSPECTS EVOL
   RANTA E, 1994, OIKOS, V70, P313, DOI 10.2307/3545768
   RAYNER JMV, 1985, J ZOOL, V206, P415
   Reeve JP, 1999, HEREDITY, V83, P697, DOI 10.1038/sj.hdy.6886160
   RENARD E, 2000, EVOLUTION FAMILLE AM
   Rensch B., 1960, EVOLUTION SPECIES LE
   Rezende EL, 2004, EVOLUTION, V58, P1361
   SCHOENER TW, 1967, SCIENCE, V155, P474, DOI 10.1126/science.155.3761.474
   SHINE R, 1978, OECOLOGIA, V33, P269, DOI 10.1007/BF00348113
   Smith RJ, 2002, INT J PRIMATOL, V23, P1095, DOI 10.1023/A:1019654100876
   Sokal RR., 2012, Biometry, V4
NR 48
TC 30
Z9 32
U1 0
U2 16
PU ELSEVIER GMBH
PI MUNICH
PA HACKERBRUCKE 6, 80335 MUNICH, GERMANY
SN 0944-2006
J9 ZOOLOGY
JI Zoology
PY 2006
VL 109
IS 4
BP 318
EP 330
DI 10.1016/j.zool.2006.04.003
PG 13
WC Zoology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Zoology
GA 107JV
UT WOS:000242167900006
PM 16978850
DA 2025-01-10
ER

PT J
AU Chen, B
   Kang, L
AF Chen, B
   Kang, L
TI Can greenhouses eliminate the development of cold resistance of the
   leafminers?
SO OECOLOGIA
LA English
DT Article
DE cold resistance; gene flow; habitat changes; latitudinal variation;
   Liriomyza
ID SUPERCOOLING POINTS; DROSOPHILA-SERRATA; SOUTHERN BORDER; LEAF-MINER;
   HARDINESS; TOLERANCE; POPULATIONS; ADAPTATION; STRATEGIES; PATTERNS
AB Latitudinal patterns for quantitative traits in insect are commonly used to investigate climatic adaptation. We compare the cold resistance of the leafminer (Liriomyza sativae) pupa among populations distributed from tropical to temperate regions, incorporating the thermal overwintering limit of the insect's range. The patterns of cold resistance for northern and southern populations differ. The southern populations significantly increased their cold resistance with latitude, showing a latitudinal pattern independent of seasons, acclimation regimes, and assay methods. In contrast, the northern populations showed no stable patterns; they were always intermediate in cold hardiness between the low-latitude and high-latitude populations within the overwintering limit. Integration of these data with those of the biologically similar congeneric leafminer, L. huidobrensis, suggests that a pattern shift in stress tolerance associated with the overwintering range limit is probably a general adaptive strategy adopted by freeze-intolerant species that have a high-latitude boundary of distribution, but can only overwinter and develop in protected greenhouses in harsh seasons. Considering the widespread availability of greenhouses for overwintering insects in northern China, we speculated that the large-scale existence of thermally-buffered microhabitats in greenhouses might eliminate the development of cold resistance of the leafminer populations. However, results suggest a strong selection for increased cold resistance for natural populations of Liriomyza species at higher latitudes that can overwinter in the field, but not for populations at latitudes above the thermal limit. Thus, habitat modification associated with greenhouses can limit gene flow and reduce cold tolerances even at latitudes above where the leafminers can overwinter in the field.
C1 Chinese Acad Sci, Inst Zool, State Key Lab Integrated Management Pest Insects, Beijing 100080, Peoples R China.
C3 Chinese Academy of Sciences; Institute of Zoology, CAS
RP Chinese Acad Sci, Inst Zool, State Key Lab Integrated Management Pest Insects, Bei Si Huan W Rd 25, Beijing 100080, Peoples R China.
EM lkang@ioz.ac.cn
RI Kang, Le/ABD-1116-2022; Chen, Bing/C-4837-2019
OI Chen, Bing/0000-0002-1238-3948; Kang, Le/0000-0003-4262-2329
CR Akinci S, 1998, ACTA HORTIC, P87
   [Anonymous], 1973, SERIES ENTOMOLOGICA
   [Anonymous], 1999, Physiological Diversity and Its Ecological Implications
   BLOCK W, 1982, ECOL ENTOMOL, V7, P1, DOI 10.1111/j.1365-2311.1982.tb00638.x
   BLOCK W, 1982, OIKOS, V38, P157, DOI 10.2307/3544015
   CANNON RJC, 1988, BIOL REV, V63, P23, DOI 10.1111/j.1469-185X.1988.tb00468.x
   Case TJ, 2000, AM NAT, V155, P583, DOI 10.1086/303351
   Castilla N, 2002, ACTA HORTIC, P135, DOI 10.17660/ActaHortic.2002.582.11
   Chen B, 2004, ENVIRON ENTOMOL, V33, P155, DOI 10.1603/0046-225X-33.2.155
   Chen B, 2002, CRYOLETTERS, V23, P173
   Chen B., 2002, PLANT Q, V16, P138
   CHEN B, 2005, IN PRESS APPL ENTOMO, V40
   Danks HV, 1996, EUR J ENTOMOL, V93, P383
   Fuller SJ, 1999, MOL ECOL, V8, P1867, DOI 10.1046/j.1365-294x.1999.00782.x
   GUO JM, 2000, PLANT QUARANTINE, V14, P190
   Hatherly IS, 2004, ENTOMOL EXP APPL, V111, P97, DOI 10.1111/j.0013-8703.2004.00148.x
   Hodkinson ID, 1999, J ANIM ECOL, V68, P1259, DOI 10.1046/j.1365-2656.1999.00372.x
   Hoffmann AA, 2003, J THERM BIOL, V28, P175, DOI 10.1016/S0306-4565(02)00057-8
   Hoffmann AA, 2001, EVOLUTION, V55, P1621, DOI 10.1111/j.0014-3820.2001.tb00681.x
   Hoffmann AA, 2000, BIOSCIENCE, V50, P217, DOI 10.1641/0006-3568(2000)050[0217:ESAAEF]2.3.CO;2
   Hu MG., 1995, CHINA VEGETABLE, V3, P7
   Jenkins NL, 1999, EVOLUTION, V53, P1823, DOI 10.2307/2640443
   JING H, 2003, HORTICULTURE N CHINA, V1, P56
   Jing XH, 2003, ECOL ENTOMOL, V28, P151, DOI 10.1046/j.1365-2311.2003.00497.x
   Kimura MT, 2004, OECOLOGIA, V140, P442, DOI 10.1007/s00442-004-1605-4
   Kirk WDJ, 2003, AGR FOREST ENTOMOL, V5, P301, DOI 10.1046/j.1461-9563.2003.00192.x
   Klok CJ, 2003, FUNCT ECOL, V17, P858, DOI 10.1111/j.1365-2435.2003.00794.x
   Magiafoglou A, 2002, J EVOLUTION BIOL, V15, P763, DOI 10.1046/j.1420-9101.2002.00439.x
   McDonald JR, 1997, B ENTOMOL RES, V87, P497, DOI 10.1017/S0007485300041365
   McDonald JR, 2000, PHYSIOL ENTOMOL, V25, P159, DOI 10.1046/j.1365-3032.2000.00179.x
   *MDD, 2002, CLIM ATL PEOPL REP C
   PARRELLA MP, 1987, ANNU REV ENTOMOL, V32, P201, DOI 10.1146/annurev.en.32.010187.001221
   RAAPHORST MGM, 2003, ACTA HORTICUT, V611, P57
   Reitz SR, 2002, ENTOMOL EXP APPL, V102, P101, DOI 10.1023/A:1015861716270
   Sinclair BJ, 2003, J INSECT PHYSIOL, V49, P1049, DOI 10.1016/j.jinsphys.2003.08.002
   VANLENTEREN JC, 1988, ANNU REV ENTOMOL, V33, P239, DOI 10.1146/annurev.en.33.010188.001323
   Voituron Y, 2002, AM NAT, V160, P255, DOI 10.1086/341021
   Warren MS, 2001, NATURE, V414, P65, DOI 10.1038/35102054
   Worland MR, 2001, FUNCT ECOL, V15, P515, DOI 10.1046/j.0269-8463.2001.00547.x
   Zhao YX, 2000, J APPL ENTOMOL, V124, P185, DOI 10.1046/j.1439-0418.2000.00463.x
NR 40
TC 9
Z9 15
U1 1
U2 15
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 0029-8549
EI 1432-1939
J9 OECOLOGIA
JI Oecologia
PD JUN
PY 2005
VL 144
IS 2
BP 187
EP 195
DI 10.1007/s00442-005-0051-2
PG 9
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA 944VU
UT WOS:000230459800002
PM 15800738
DA 2025-01-10
ER

PT J
AU Simon, MN
   Rothier, PS
   Donihue, CM
   Herrel, A
   Kolbe, JJ
AF Simon, Monique N.
   Rothier, Priscila S.
   Donihue, Colin M.
   Herrel, Anthony
   Kolbe, Jason J.
TI Can extreme climatic events induce shifts in adaptive potential? A
   conceptual framework and empirical test with <i>Anolis</i> lizards
SO JOURNAL OF EVOLUTIONARY BIOLOGY
LA English
DT Article
DE extreme climate; limb morphology; lizards; locomotion; natural selection
ID MORPHOLOGICAL INTEGRATION; DIRECTIONAL SELECTION; DIFFERENTIAL
   EPISTASIS; COMPARING EVOLVABILITY; PHENOTYPIC INTEGRATION; QUANTITATIVE
   GENETICS; LOCOMOTOR PERFORMANCE; CLINGING PERFORMANCE; PERCH DIAMETER;
   EVOLUTION
AB Multivariate adaptation to climatic shifts may be limited by trait integration that causes genetic variation to be low in the direction of selection. However, strong episodes of selection induced by extreme climatic pressures may facilitate future population-wide responses if selection reduces trait integration and increases adaptive potential (i.e., evolvability). We explain this counter-intuitive framework for extreme climatic events in which directional selection leads to increased evolvability and exemplify its use in a case study. We tested this hypothesis in two populations of the lizard Arias scriptus that experienced hurricane-induced selection on limb traits. We surveyed populations immediately before and after the hurricane as well as the offspring of post-hurricane survivors, allowing us to estimate both selection and response to selection on key functional traits: forelimb length, hindlimb length, and toepad area. The direct selection was parallel in both islands and strong in several limb traits. Even though overall limb integration did not change after the hurricane, both populations showed a non-significant tendency toward increased evolvability after the hurricane despite the direction of selection not being aligned with the axis of most variance (i.e., body size). The population with comparably lower between-limb integration showed a less constrained response to selection. Hurricane-induced selection, not aligned with the pattern of high trait correlations, likely conflicts with selection occurring during normal ecological conditions that favours functional coordination between limb traits, and would likely need to be very strong and more persistent to elicit a greater change in trait integration and evolvability. Future tests of this hypothesis should use G-matrices in a variety of wild organisms experiencing selection due to extreme climatic events.
C1 [Simon, Monique N.] Oklahoma State Univ, Dept Integrat Biol, Stillwater, OK 74075 USA.
   [Rothier, Priscila S.] Museum Natl Hist Nat, UMR 7179, Paris, France.
   [Donihue, Colin M.] Brown Univ, Inst Brown Environm & Soc, Providence, RI 02912 USA.
   [Herrel, Anthony] Museum Natl Hist Nat, Ctr Natl Rech Sci, UMR 7179, Paris, France.
   [Herrel, Anthony] Univ Antwerp, Dept Biol, Funct Morphol Lab, Antwerp, Belgium.
   [Herrel, Anthony] Univ Ghent, Evolutionary Morphol Vertebrates, Ghent, Belgium.
   [Kolbe, Jason J.] Univ Rhode Isl, Dept Biol Sci, Kingston, RI 02881 USA.
C3 Oklahoma State University System; Oklahoma State University -
   Stillwater; Museum National d'Histoire Naturelle (MNHN); Centre National
   de la Recherche Scientifique (CNRS); CNRS - Institute of Ecology &
   Environment (INEE); Brown University; Museum National d'Histoire
   Naturelle (MNHN); Centre National de la Recherche Scientifique (CNRS);
   CNRS - Institute of Ecology & Environment (INEE); University of Antwerp;
   Ghent University; University of Rhode Island
RP Simon, MN (corresponding author), Oklahoma State Univ, Dept Integrat Biol, Stillwater, OK 74075 USA.
EM monique.nouailhetas@gmail.com
RI ; Nouailhetas Simon, Monique/KWA-7153-2024; Herrel, Anthony/C-3712-2013
OI Rothier, Priscila S./0000-0003-3017-6528; Nouailhetas Simon,
   Monique/0000-0003-0106-2660; Herrel, Anthony/0000-0003-0991-4434
FU Pine Cay Homeowners Association; US National Science Foundation
FX Pine Cay Homeowners Association; US National Science Foundation
CR Adams DC, 2019, EVOLUTION, V73, P2352, DOI 10.1111/evo.13867
   Adams DC, 2013, METHODS ECOL EVOL, V4, P393, DOI 10.1111/2041-210X.12035
   Aerts P, 2000, NETH J ZOOL, V50, P261, DOI 10.1163/156854200505865
   Arnold SJ, 2001, GENETICA, V112, P9, DOI 10.1023/A:1013373907708
   Arnold SJ, 2008, EVOLUTION, V62, P2451, DOI 10.1111/j.1558-5646.2008.00472.x
   Assis APA, 2016, P ROY SOC B-BIOL SCI, V283, DOI 10.1098/rspb.2016.1615
   Bender MA, 2010, SCIENCE, V327, P454, DOI 10.1126/science.1180568
   BURGER R, 1993, J THEOR BIOL, V162, P487, DOI 10.1006/jtbi.1993.1101
   Calsbeek R, 2008, EVOLUTION, V62, P1137, DOI 10.1111/j.1558-5646.2008.00356.x
   Cheverud JM, 2004, J EXP ZOOL PART B, V302B, P424, DOI 10.1002/jez.b.21008
   CHEVERUD JM, 1995, AM NAT, V145, P63, DOI 10.1086/285728
   CHEVERUD JM, 1988, EVOLUTION, V42, P958, DOI [10.2307/2408911, 10.1111/j.1558-5646.1988.tb02514.x]
   CHEVERUD JM, 1984, J THEOR BIOL, V110, P155, DOI 10.1016/S0022-5193(84)80050-8
   Chevin LM, 2013, EVOLUTION, V67, P708, DOI 10.1111/j.1558-5646.2012.01809.x
   Crandell KE, 2014, ZOOLOGY, V117, P363, DOI 10.1016/j.zool.2014.05.001
   Debaere SF, 2021, FUNCT ECOL, V35, P2026, DOI 10.1111/1365-2435.13848
   Diniz JAF, 2019, ECOGRAPHY, V42, P1124, DOI 10.1111/ecog.04264
   Donihue CM, 2020, P NATL ACAD SCI USA, V117, P10429, DOI 10.1073/pnas.2000801117
   Donihue CM, 2018, NATURE, V560, P88, DOI 10.1038/s41586-018-0352-3
   Dufour CMS, 2019, J ZOOL, V309, P77, DOI 10.1111/jzo.12685
   Elstrott J, 2004, BIOL J LINN SOC, V83, P389, DOI 10.1111/j.1095-8312.2004.00402.x
   Etterson JR, 2001, SCIENCE, V294, P151, DOI 10.1126/science.1063656
   Etterson JR, 2004, EVOLUTION, V58, P1459, DOI 10.1111/j.0014-3820.2004.tb01727.x
   Falconer D. S., 1996, Introduction to quantitative genetics.
   Fischer EM, 2021, NAT CLIM CHANGE, V11, P689, DOI 10.1038/s41558-021-01092-9
   Foster KL, 2012, J EXP BIOL, V215, P2288, DOI 10.1242/jeb.069856
   Gamble T, 2019, INTEGR COMP BIOL, V59, P193, DOI 10.1093/icb/icz010
   Gienapp P, 2017, TRENDS ECOL EVOL, V32, P897, DOI 10.1016/j.tree.2017.09.004
   Grabowski M, 2017, METHODS ECOL EVOL, V8, P592, DOI 10.1111/2041-210X.12674
   Grant PR, 2017, PHILOS T R SOC B, V372, DOI 10.1098/rstb.2016.0146
   Hagey TJ, 2014, ZOOMORPHOLOGY, V133, P111, DOI 10.1007/s00435-013-0207-2
   Hansen TF, 2008, J EVOLUTION BIOL, V21, P1201, DOI 10.1111/j.1420-9101.2008.01573.x
   Hellmann JJ, 2007, BIOL CONSERV, V137, P599, DOI 10.1016/j.biocon.2007.03.018
   Hereford J, 2004, EVOLUTION, V58, P2133
   Herrel A, 2008, P NATL ACAD SCI USA, V105, P4792, DOI 10.1073/pnas.0711998105
   HILL WG, 1982, P NATL ACAD SCI-BIOL, V79, P142, DOI 10.1073/pnas.79.1.142
   HOULE D, 1992, GENETICS, V130, P195
   Irschick DJ, 1998, EVOLUTION, V52, P219, DOI 10.1111/j.1558-5646.1998.tb05155.x
   Jones AG, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms4709
   Knutson TR, 2010, NAT GEOSCI, V3, P157, DOI 10.1038/NGEO779
   Kolbe JJ, 2015, J HERPETOL, V49, P284, DOI 10.1670/13-104
   Kolbe JJ, 2011, EVOLUTION, V65, P3608, DOI 10.1111/j.1558-5646.2011.01416.x
   LANDE R, 1979, EVOLUTION, V33, P402, DOI 10.1111/j.1558-5646.1979.tb04694.x
   LANDE R, 1983, EVOLUTION, V37, P1210, DOI [10.2307/2408842, 10.1111/j.1558-5646.1983.tb00236.x]
   Liu Y, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms10033
   Lowie A, 2019, J EXP BIOL, V222, DOI 10.1242/jeb.188805
   Marroig G, 2001, EVOLUTION, V55, P2576
   Marroig G, 2012, EVOLUTION, V66, P1506, DOI 10.1111/j.1558-5646.2011.01555.x
   McGlothlin J.W., 2021, BIORXIV, V46
   McGlothlin JW, 2018, EVOL LETT, V2, P310, DOI 10.1002/evl3.72
   Melo Diogo, 2015, F1000Res, V4, P925
   Melo D, 2015, P NATL ACAD SCI USA, V112, P470, DOI 10.1073/pnas.1322632112
   Nadeau CP, 2019, ECOGRAPHY, V42, P1280, DOI 10.1111/ecog.04404
   O'Keefe FR, 2022, SYST BIOL, V71, P810, DOI 10.1093/sysbio/syab088
   Pavlicev M, 2008, EVOLUTION, V62, P199, DOI 10.1111/j.1558-5646.2007.00255.x
   Pavlicev M, 2011, P ROY SOC B-BIOL SCI, V278, P1903, DOI 10.1098/rspb.2010.2113
   Pavlicev M, 2009, EVOL BIOL, V36, P157, DOI 10.1007/s11692-008-9042-7
   Penna A, 2017, EVOLUTION, V71, P2370, DOI 10.1111/evo.13304
   Perry G, 2004, ANIM BEHAV, V67, P37, DOI 10.1016/j.anbehav.2003.02.003
   Peschel AR, 2021, EVOLUTION, V75, P73, DOI 10.1111/evo.14131
   Phillips PC, 1999, EVOLUTION, V53, P1506, DOI [10.1111/j.1558-5646.1999.tb05414.x, 10.2307/2640896]
   Porto A, 2013, EVOLUTION, V67, P3305, DOI 10.1111/evo.12177
   Quintero I, 2013, GLOBAL ECOL BIOGEOGR, V22, P422, DOI 10.1111/geb.12001
   Raats M. M., 1992, Food Quality and Preference, V3, P89, DOI 10.1016/0950-3293(91)90028-D
   Rabe AM, 2020, BIOL J LINN SOC, V130, P156, DOI 10.1093/biolinnean/blaa022
   Roff DA, 1996, EVOLUTION, V50, P1392, DOI [10.2307/2410877, 10.1111/j.1558-5646.1996.tb03913.x]
   Roff DA, 2012, EVOLUTION, V66, P2953, DOI 10.1111/j.1558-5646.2012.01656.x
   RUIBAL R, 1965, J MORPHOL, V117, P271, DOI 10.1002/jmor.1051170302
   Sodini SM, 2018, GENETICS, V209, P941, DOI 10.1534/genetics.117.300630
   Styga JM, 2019, HEREDITY, V122, P696, DOI 10.1038/s41437-018-0152-4
   Walsh B, 2009, ANNU REV ECOL EVOL S, V40, P41, DOI 10.1146/annurev.ecolsys.110308.120232
   Weatherbee S.D., 2008, MECH CHONDROGENESIS, P93
   WILLIS JH, 1991, EVOLUTION, V45, P441, DOI [10.2307/2409678, 10.1111/j.1558-5646.1991.tb04418.x]
NR 73
TC 1
Z9 1
U1 0
U2 6
PU OXFORD UNIV PRESS
PI OXFORD
PA GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND
SN 1010-061X
EI 1420-9101
J9 J EVOLUTION BIOL
JI J. Evol. Biol.
PD JAN
PY 2023
VL 36
IS 1
BP 195
EP 208
DI 10.1111/jeb.14115
EA NOV 2022
PG 14
WC Ecology; Evolutionary Biology; Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Evolutionary Biology; Genetics &
   Heredity
GA 7T9DD
UT WOS:000881417100001
PM 36357963
OA Green Submitted
DA 2025-01-10
ER

PT J
AU Rita, A
AF Rita, Angelo
TI Functional responses of Sycamore maple and Italian alder to the
   Mediterranean climate
SO TREES-STRUCTURE AND FUNCTION
LA English
DT Article
DE Hydraulic conductivity; Trade-off; Acer pseudoplatanus L.; Alnus cordata
   Desf.; Wood anatomy
ID HYDRAULIC CONDUCTANCE; ACER-PSEUDOPLATANUS; WATER TRANSPORT; XYLEM
   EMBOLISM; SEVERE DROUGHT; RADIAL GROWTH; QUERCUS-ILEX; VULNERABILITY;
   TREES; CAVITATION
AB Analysis of tree-ring anatomical features of co-occurring Sycamore maple and Italian alder showed species-specific xylem hydraulic traits revealing functional adaptation to climate at their southernmost distribution limit.
   The impact of rising temperature and changing rainfall patterns is expected to alter the drought resistance limits of Mediterranean plants. Water shortage negatively affects plant hydraulic conductance, increasing plant vulnerability to drought-induced xylem embolism. This phenomenon may force maple-alder ecosystems, affecting the competitive balance between these two species at their southernmost distribution limit. By developing a tree-ring series of xylem anatomical features, we evaluated the relationship between the climate and the functional xylem anatomy of sycamore and alder woody species that coexist in the same area. We hypothesized that variation in xylem anatomy between the two species is driven by plasticity and trade-offs between safety from drought-induced embolism and water transport efficiency. Sycamore maple and Italian alder had several distinctive anatomical traits, revealing successful plant hydraulic properties, such as hydraulic conductivity and vulnerability to embolism. Surprisingly, the xylem hydraulic architecture of maple did not reflect the trade-off between the efficiency of the conducting system and safety against embolism, whereas a shift towards a more efficient xylem configuration was observed for alder during periods of water shortage. Alder trees primarily adjusted their architecture by reducing the size of larger vessels, which are more vulnerable to embolism. In particular, a strong trade-off between xylem traits in alder facilitated high xylem plasticity, allowing rapid hydraulic adjustment to annual climatic variability. This response may represent an important determinant of individual performance, and may have the potential to shape the functional diversity and ecology of this forest community.
C1 [Rita, Angelo] Univ Basilicata, Scuola Sci Agr Forestali Alimentari & Ambientali, I-85100 Potenza, Italy.
C3 University of Basilicata
RP Rita, A (corresponding author), Univ Basilicata, Scuola Sci Agr Forestali Alimentari & Ambientali, Viale dellAteneo Lucano 10, I-85100 Potenza, Italy.
EM angelo.rita@unibas.it
RI Rita, Angelo/E-1233-2015
OI Rita, Angelo/0000-0002-6579-7925
FU MIUR-PRIN [2012E3F3LK]; "Ente Parco Nazionale del Pollino'', Rotonda,
   Italy, within the project 'Un laboratorio naturale permanente nel Parco
   Nazionale del Pollino'
FX The author thank M. Borghetti (Universita della Basilicata, Potenza
   Italy) for scientific guidance, L. Todaro (Universita della Basilicata,
   Potenza Italy) for technical assistance and A. Lapolla (Universita della
   Basilicata, Potenza Italy) for precious help in field work. Research
   jointly funded by MIUR-PRIN Grant No. 2012E3F3LK 'Global change effects
   on the productivity and radiative forcing of Italian forests: a novel
   retrospective, experimental and prognostic analysis' and by "Ente Parco
   Nazionale del Pollino'', Rotonda, Italy, within the project 'Un
   laboratorio naturale permanente nel Parco Nazionale del Pollino'.
CR Abrantes J, 2013, TREES-STRUCT FUNCT, V27, P655, DOI 10.1007/s00468-012-0820-6
   Akaike H., 1973, P 2 INT S INF THEOR, P267, DOI [10.1007/978-1-4612-0919-5_38, DOI 10.1007/978-1-4612-1694-015, 10.1007/978-1-4612-1694-0]
   Anderegg WRL, 2014, OECOLOGIA, V175, P11, DOI 10.1007/s00442-013-2875-5
   Anderegg WRL, 2012, P NATL ACAD SCI USA, V109, P233, DOI 10.1073/pnas.1107891109
   [Anonymous], 2007, AR4 CLIM CHANG 2007
   [Anonymous], MAN ICAO STAND ATM E
   [Anonymous], FOREST TREE BREEDING
   [Anonymous], 1997, Growth control in Woody plants, DOI DOI 10.1016/B978-012424210-4/50007-3
   [Anonymous], 2009, EUFORGEN TECHNICAL G
   [Anonymous], 1990, Generalized additive models
   Arbellay E, 2012, J EXP BOT, V63, P3271, DOI 10.1093/jxb/ers050
   BORGHETTI M, 1989, CAN J FOREST RES, V19, P1071, DOI 10.1139/x89-163
   Broadmeadow MSJ, 2005, FORESTRY, V78, P145, DOI 10.1093/forestry/cpi014
   Brodribb TJ, 2003, PLANT PHYSIOL, V132, P2166, DOI 10.1104/pp.103.023879
   Bunn AG, 2008, DENDROCHRONOLOGIA, V26, P115, DOI 10.1016/j.dendro.2008.01.002
   CARLQUIST S, 1977, AM J BOT, V64, P887, DOI 10.2307/2442382
   Choat B, 2008, NEW PHYTOL, V177, P608, DOI 10.1111/j.1469-8137.2007.02317.x
   Choat B, 2012, NATURE, V491, P752, DOI 10.1038/nature11688
   Cochard H, 2015, PLANT CELL ENVIRON, V38, P201, DOI 10.1111/pce.12391
   Cook E.R. L.A. Kairiukstis., 2013, METHODS DENDROCHRONO
   Corcuera L, 2004, TREES-STRUCT FUNCT, V18, P83, DOI 10.1007/s00468-003-0284-9
   Corona P., 1989, Italia Forestale e Montana, V44, P391
   De Martonne E, 1926, Bulletin de lAssociation de Gographes Franais, V9, P3, DOI DOI 10.3406/BAGF.1926.6321
   Fonti P, 2010, NEW PHYTOL, V185, P42, DOI 10.1111/j.1469-8137.2009.03030.x
   Gao XJ, 2006, GEOPHYS RES LETT, V33, DOI 10.1029/2005GL024954
   Gea-Izquierdo G, 2012, TREE PHYSIOL, V32, P401, DOI 10.1093/treephys/tps026
   Giorgi F, 2008, GLOBAL PLANET CHANGE, V63, P90, DOI 10.1016/j.gloplacha.2007.09.005
   Hacke UG, 2001, OECOLOGIA, V126, P457, DOI 10.1007/s004420100628
   Hacke UG, 2006, TREE PHYSIOL, V26, P689, DOI 10.1093/treephys/26.6.689
   Hartmann H, 2013, NEW PHYTOL, V200, P340, DOI 10.1111/nph.12331
   HOLMES R L, 1983, Tree-Ring Bulletin, V43, P69
   Kölling C, 2007, GEFAHRST REINHALT L, V67, P259
   Lemoine D, 2001, ANN FOR SCI, V58, P723, DOI 10.1051/forest:2001159
   Lens F, 2011, NEW PHYTOL, V190, P709, DOI 10.1111/j.1469-8137.2010.03518.x
   Lindner M, 2014, J ENVIRON MANAGE, V146, P69, DOI 10.1016/j.jenvman.2014.07.030
   Loepfe L, 2007, J THEOR BIOL, V247, P788, DOI 10.1016/j.jtbi.2007.03.036
   LOGULLO MA, 1995, PLANT CELL ENVIRON, V18, P661, DOI 10.1111/j.1365-3040.1995.tb00567.x
   Maherali H, 2004, ECOLOGY, V85, P2184, DOI 10.1890/02-0538
   Martínez-Vilalta J, 2008, GLOBAL CHANGE BIOL, V14, P2868, DOI 10.1111/j.1365-2486.2008.01685.x
   Martínez-Vilalta J, 2002, OECOLOGIA, V133, P19, DOI 10.1007/s00442-002-1009-2
   McDowell NG, 2011, PLANT PHYSIOL, V155, P1051, DOI 10.1104/pp.110.170704
   Mencuccini M, 2003, PLANT CELL ENVIRON, V26, P163, DOI 10.1046/j.1365-3040.2003.00991.x
   Morecroft MD, 2008, FORESTRY, V81, P59, DOI 10.1093/forestry/cpm045
   Nardini A, 1999, ANN FOR SCI, V56, P371, DOI 10.1051/forest:19990502
   Nardini A, 1999, PLANT CELL ENVIRON, V22, P109, DOI 10.1046/j.1365-3040.1999.00382.x
   Nardini A, 2012, NEW PHYTOL, V196, P788, DOI 10.1111/j.1469-8137.2012.04294.x
   Olano JM, 2013, FUNCT ECOL, V27, P1295, DOI 10.1111/1365-2435.12144
   Peñuelas J, 2011, GLOBAL ECOL BIOGEOGR, V20, P597, DOI 10.1111/j.1466-8238.2010.00608.x
   Poorter L, 2010, NEW PHYTOL, V185, P481, DOI 10.1111/j.1469-8137.2009.03092.x
   R Core Team R, 2013, R: A language and environment for statistical computing
   Sevanto S, 2014, PLANT CELL ENVIRON, V37, P153, DOI 10.1111/pce.12141
   Sperry JS, 2008, PLANT CELL ENVIRON, V31, P632, DOI 10.1111/j.1365-3040.2007.01765.x
   Sperry JS, 2006, AM J BOT, V93, P1490, DOI 10.3732/ajb.93.10.1490
   SPERRY JS, 1994, ECOLOGY, V75, P1736, DOI 10.2307/1939633
   SPERRY JS, 1993, PLANT CELL ENVIRON, V16, P279, DOI [10.1111/j.1365-3040.1993.tb00870.x, 10.1111/j.1365-3040.1994.tb02021.x]
   Taneda H, 2008, TREE PHYSIOL, V28, P1641, DOI 10.1093/treephys/28.11.1641
   Tissier J, 2004, ANN FOREST SCI, V61, P81, DOI 10.1051/forest:2003087
   TYREE MT, 1991, NEW PHYTOL, V119, P345, DOI 10.1111/j.1469-8137.1991.tb00035.x
   Tyree MT., 2002, SPR S WOOD, P284
   Wheeler JK, 2005, PLANT CELL ENVIRON, V28, P800, DOI 10.1111/j.1365-3040.2005.01330.x
   Wood S.N., 2006, Generalized additive models: An introduction with R. Chapman and Hall
   YAMAGUCHI DK, 1991, CAN J FOREST RES, V21, P414, DOI 10.1139/x91-053
NR 62
TC 3
Z9 3
U1 4
U2 30
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 2015
VL 29
IS 6
BP 1907
EP 1916
DI 10.1007/s00468-015-1271-7
PG 10
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Forestry
GA CX5AE
UT WOS:000365711700024
DA 2025-01-10
ER

PT J
AU Li, YM
   Dlugosch, KM
   Enquist, BJ
AF Li, Yue M.
   Dlugosch, Katrina M.
   Enquist, Brian J.
TI Novel spatial analysis methods reveal scale-dependent spread and infer
   limiting factors of invasion by Sahara mustard
SO ECOGRAPHY
LA English
DT Article
ID EVOLUTION; ECOLOGY; PLANT; CLIMATE; DYNAMICS; GENOTYPES; HISTORY;
   PATTERN; BIOLOGY; SHAPE
AB Multiple scale-dependent ecological processes influence species distributions. Uncovering these drivers of dynamic range boundaries can provide fundamental ecological insights and vital knowledge for species management. We develop a transferable methodology that uses widely available data and tools to determine critical scales in range expansion and to infer dominating scale-dependent forces that influence spread. We divide a focal geographic region into different sized square cells, representing different spatial scales. We then used herbarium records to determine the species' occupancy of cells at each spatial scale. We calculated the growth in cell occupancy across scales to infer the scale dependent expansion rate. This is the first time such a box-counting' method is used to study range expansion. We coupled this multi-scale analysis with species distribution models to determine the range and spatial scales where suitable climate allows the species to spread, and where other factors may be influencing the expansion. We demonstrate our methodology by assessing the spread of invasive Sahara mustard in North America. We detect critical scales where its spread is limited (100-500 km) or unconstrained (5-50 km) by climatic variables. Using climate-based models to assess the similarity of climate envelopes in its native and invaded range, we find that the climate in the invaded range generally predicts the native distribution, suggesting that either there has been little local adaptation to climate occurring since introduction or the biological interaction experienced in the invaded range has not driven the species to occupy climatic conditions much different from its native range. Our novel method can be broadly utilized in other studies to generate critical insights into the scale dependency of different ecological drivers that influence the spread and distribution limits, as well as to help parameterizing predictions of future spread, and thus inform management decisions.
C1 [Li, Yue M.; Dlugosch, Katrina M.; Enquist, Brian J.] Univ Arizona, Dept Ecol & Evolutionary Biol, Tucson, AZ 85721 USA.
C3 University of Arizona
RP Li, YM (corresponding author), Univ Arizona, Dept Ecol & Evolutionary Biol, Tucson, AZ 85721 USA.
EM liyue@email.arizona.edu
RI Enquist, Brian/B-6436-2008
OI Enquist, Brian/0000-0002-6124-7096; Li, Yue/0000-0002-2564-6129;
   Dlugosch, Katrina/0000-0002-7302-6637
FU US Marine Corps Air Stations, Yuma; Luke Air Force
FX John Donoghue II, Irena Simova and Jin Wu guided us to cross the
   mysterious terrain of ArcGIS. Naia Morueta-Holme circled many MaxEnt
   pitfalls that might have trapped us. Cal-IPC and Cameron Barrows shared
   important data of Sahara mustard recorded in the Californian deserts.
   Mara MacKinnon and Kimberly Byers spent months finding the latitude and
   longitude coordinates of hundreds of herbarium records. We thank Cameron
   Barrows, Aaryn Olsson, and Peter Chesson, who inspired critical
   improvement on the manuscript. We also thank all the herbarium
   collectors for documenting the history of Sahara mustard invasion.
   Funding was proved to YML by the US Marine Corps Air Stations, Yuma and
   Luke Air Force.
CR Akasaka M, 2012, J VEG SCI, V23, P33, DOI 10.1111/j.1654-1103.2011.01332.x
   ALSHEHBAZ IA, 1977, SYST BOT, V2, P327, DOI 10.2307/2418468
   [Anonymous], 1983, The fractal geometry of nature
   Arim M, 2006, P NATL ACAD SCI USA, V103, P374, DOI 10.1073/pnas.0504272102
   Baker H. G., 1965, The genetics of colonizing species: Proc. 1st Internat. Union biol Sci., Asilomar, California., P147
   Bangle DN, 2008, WEST N AM NATURALIST, V68, P334, DOI 10.3398/1527-0904(2008)68[334:SGOTIP]2.0.CO;2
   Barrett SCH, 2008, MOL ECOL, V17, P373, DOI 10.1111/j.1365-294X.2007.03503.x
   Barrows CW, 2009, BIOL INVASIONS, V11, P673, DOI 10.1007/s10530-008-9282-6
   Baskin CC, 2006, WEED SCI, V54, P549, DOI 10.1614/WS-05-034R.1
   Brown JH, 1996, ANNU REV ECOL SYST, V27, P597, DOI 10.1146/annurev.ecolsys.27.1.597
   Catford JA, 2009, DIVERS DISTRIB, V15, P22, DOI 10.1111/j.1472-4642.2008.00521.x
   CAUGHLEY G, 1987, J ANIM ECOL, V56, P751, DOI 10.2307/4946
   Crooks J. A., 1999, Invasive species and biodiversity management. Based on papers presented at the Norway/United Nations (UN) Conference on Alien Species, 2nd Trondheim Conference on Biodiversity, Trondheim, Norway, 1-5 July 1996., P103
   Davis MB, 2001, SCIENCE, V292, P673, DOI 10.1126/science.292.5517.673
   Delisle F, 2003, J BIOGEOGR, V30, P1033, DOI 10.1046/j.1365-2699.2003.00897.x
   Dlugosch KM, 2008, MOL ECOL, V17, P4583, DOI 10.1111/j.1365-294X.2008.03932.x
   Dlugosch KM, 2008, ECOL LETT, V11, P701, DOI 10.1111/j.1461-0248.2008.01181.x
   Elith J, 2011, DIVERS DISTRIB, V17, P43, DOI 10.1111/j.1472-4642.2010.00725.x
   Elith J, 2010, METHODS ECOL EVOL, V1, P330, DOI 10.1111/j.2041-210X.2010.00036.x
   Ellstrand NC, 2000, P NATL ACAD SCI USA, V97, P7043, DOI [10.1073/pnas.97.13.7043, 10.1007/s10681-006-5939-3]
   Estrada-Villegas S, 2012, ECOLOGY, V93, P1183, DOI 10.1890/11-0275.1
   Foxcroft LC, 2009, DIVERS DISTRIB, V15, P367, DOI 10.1111/j.1472-4642.2008.00544.x
   Gaston KJ, 2009, P R SOC B, V276, P1395, DOI 10.1098/rspb.2008.1480
   GREIGSMITH P, 1979, J ECOL, V67, P755, DOI 10.2307/2259213
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Hinata K, 1980, BRASSICA CROPS WILD, P223
   Hinata K., 1975, TOHOKU J AGR RES, V25, P58
   Holt RD, 2005, SPECIES INVASIONS: INSIGHTS INTO ECOLOGY, EVOLUTION, AND BIOGEORGRAPHY, P259
   Holt RD, 2003, EVOL ECOL RES, V5, P159
   Holt RD, 2011, AM NAT, V178, pS6, DOI 10.1086/661784
   Kinlan BP, 2005, SPECIES INVASIONS: INSIGHTS INTO ECOLOGY, EVOLUTION, AND BIOGEORGRAPHY, P381
   Kirkpatrick M, 1997, AM NAT, V150, P1, DOI 10.1086/286054
   Kot M, 1996, ECOLOGY, V77, P2027, DOI 10.2307/2265698
   Kramer-Schadt S, 2013, DIVERS DISTRIB, V19, P1366, DOI 10.1111/ddi.12096
   LONSDALE WM, 1993, J ECOL, V81, P513, DOI 10.2307/2261529
   MacArthur R.H., 1972, pvii
   Marie R., 1965, FLORE AFRIQUE NORD
   Marushia RG, 2012, INVAS PLANT SCI MANA, V5, P217, DOI 10.1614/IPSM-D-11-00074.1
   McGill BJ, 2010, SCIENCE, V328, P575, DOI 10.1126/science.1188528
   MILLER ANTHONY., 1996, FLORA OF THE ARABIAN PENINSULA AND SOCOTRA
   Minnich R.A., 2000, INVASIVE PLANTS CALI, P68
   MORSE DR, 1985, NATURE, V314, P731, DOI 10.1038/314731a0
   Parker IM, 2003, CONSERV BIOL, V17, P59, DOI 10.1046/j.1523-1739.2003.02019.x
   Pearson RG, 2003, GLOBAL ECOL BIOGEOGR, V12, P361, DOI 10.1046/j.1466-822X.2003.00042.x
   Phillips BL, 2010, J EVOLUTION BIOL, V23, P2595, DOI 10.1111/j.1420-9101.2010.02118.x
   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
   Pysek P, 2005, ECOSCIENCE, V12, P302, DOI 10.2980/i1195-6860-12-3-302.1
   Pysek P, 2008, DIVERS DISTRIB, V14, P355, DOI 10.1111/j.1472-4642.2007.00431.x
   Ricklefs RE, 2005, SPECIES INVASIONS: INSIGHTS INTO ECOLOGY, EVOLUTION, AND BIOGEORGRAPHY, P165
   Ritchie ME, 1998, EVOL ECOL, V12, P309, DOI 10.1023/A:1006552200746
   ROOT T, 1988, J BIOGEOGR, V15, P489, DOI 10.2307/2845278
   Sakai AK, 2001, ANNU REV ECOL SYST, V32, P305, DOI 10.1146/annurev.ecolsys.32.081501.114037
   Sexton JP, 2009, ANNU REV ECOL EVOL S, V40, P415, DOI 10.1146/annurev.ecolsys.110308.120317
   Townsend CC., 1980, FLORA IRAQ
   Trader Melissa R., 2006, Madrono, V53, P313, DOI 10.3120/0024-9637(2006)53[313:SPBTNB]2.0.CO;2
   Veldtman R, 2010, DIVERS DISTRIB, V16, P159, DOI 10.1111/j.1472-4642.2009.00632.x
   Wangen SR, 2006, J APPL ECOL, V43, P258, DOI 10.1111/j.1365-2664.2006.01138.x
   Wethey DS, 2002, INTEGR COMP BIOL, V42, P872, DOI 10.1093/icb/42.4.872
   Whittaker RJ, 2001, J BIOGEOGR, V28, P453, DOI 10.1046/j.1365-2699.2001.00563.x
   WIENS JA, 1989, FUNCT ECOL, V3, P385, DOI 10.2307/2389612
   Wiens JJ, 2010, ECOL LETT, V13, P1310, DOI 10.1111/j.1461-0248.2010.01515.x
   Zohary M., 1980, CONSPECTUS FLORAE OR
NR 63
TC 11
Z9 14
U1 0
U2 38
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0906-7590
EI 1600-0587
J9 ECOGRAPHY
JI Ecography
PD MAR
PY 2015
VL 38
IS 3
BP 311
EP 320
DI 10.1111/ecog.00722
PG 10
WC Biodiversity Conservation; Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA CD0HK
UT WOS:000350751200010
DA 2025-01-10
ER

PT J
AU Tyagi, S
   Sahany, S
   Saraswat, D
   Mishra, SK
   Dubey, A
   Niyogi, D
AF Tyagi, Shoobhangi
   Sahany, Sandeep
   Saraswat, Dharmendra
   Mishra, Saroj Kanta
   Dubey, Amlendu
   Niyogi, Dev
TI Implications of CMIP6 Models-Based Climate Biases and Runoff Sensitivity
   on Runoff Projection Uncertainties Over Central India
SO INTERNATIONAL JOURNAL OF CLIMATOLOGY
LA English
DT Article
DE climate biases; CMIP6 models; constrained runoff uncertainty;
   non-stationarity; runoff sensitivity
ID DATA SET; SIMULATIONS; IMPACTS; SWAT; CORDEX; TOOL; TEMPERATURE;
   VARIABILITY; CALIBRATION; SCENARIOS
AB Accurate runoff projections are vital for developing climate adaptation strategies, yet significant uncertainties persist. The commonly employed approaches to constrain these uncertainties rely on the stationarity of climate biases and runoff sensitivity, which may not hold for climate-sensitive regions (e.g., semi-arid regions). This study investigates the validity of the stationarity assumption across 29 CMIP6 models, encompassing diverse climate biases (Dry Warm, Wet Warm, Dry Cold, and Wet Cold), utilising a semi-arid region in central India as a testbed. The implications of this assumption on runoff projection uncertainties were comprehensively assessed across the runoff modelling chain for three time periods (the 2030s, 2060s and 2090s) based on the Soil and Water Assessment Tool (SWAT) simulations. The results highlight the non-stationary nature of climate biases and runoff sensitivity under future scenarios, challenging the widespread applicability of common uncertainty-constraining approaches. Moreover, the impact of non-stationarity on runoff projection uncertainty was found to be strongly influenced by the choice of GCMs, preprocessing methods and climate change scenarios. In the 2030s, GCMs dominate runoff uncertainty, with dry models exhibiting similar to 10%-15% higher uncertainty compared to warm models, which is further amplified when interacting with warm biases. However, from the mid-century onwards, the bias-adjustment approaches and climate change scenarios significantly shape runoff projection uncertainties under non-stationary conditions. These findings emphasise the potential of climate bias and runoff sensitivity-based GCM selection for reducing runoff uncertainty in near-future assessment (2030s). For mid-term and long-term runoff projections, addressing diverse climate biases through bias-adjustment approaches is more viable. This study offers critical insights to prioritise the development of a non-stationarity-based approach for reliable runoff projections in climate-sensitive regions.
C1 [Tyagi, Shoobhangi; Mishra, Saroj Kanta; Dubey, Amlendu] Indian Inst Technol Delhi, Delhi, India.
   [Tyagi, Shoobhangi; Saraswat, Dharmendra; Niyogi, Dev] Purdue Univ, W Lafayette, IN 47907 USA.
   [Sahany, Sandeep] Ctr Climate Res Singapore, Singapore, Singapore.
   [Niyogi, Dev] Univ Texas Austin, Austin, TX USA.
C3 Indian Institute of Technology System (IIT System); Indian Institute of
   Technology (IIT) - Delhi; Purdue University System; Purdue University;
   University of Texas System; University of Texas Austin
RP Tyagi, S (corresponding author), Indian Inst Technol Delhi, Delhi, India.; Tyagi, S (corresponding author), Purdue Univ, W Lafayette, IN 47907 USA.; Sahany, S (corresponding author), Ctr Climate Res Singapore, Singapore, Singapore.
EM shoobha.93@gmail.com; sandeep_sahany@nea.gov.sg
RI tyagi, Shoobhangi/IUN-4125-2023; Sahany, Sandeep/KXR-6801-2024; Niyogi,
   Dev/H-6326-2013
OI Niyogi, Dev/0000-0002-1848-5080; Tyagi, Shoobhangi/0000-0002-1583-8100
FU Science and Engineering Research Board (SERB), Department of Science and
   Technology, Government of India; Overseas Visiting Doctoral Fellowship
   (OVDF) program; Elliott Centennial Endowment at the University of Texas
   at Austin [80NSSC21K1008]
FX We thank the Science and Engineering Research Board (SERB), Department
   of Science and Technology, Government of India for providing an
   opportunity of collaborative research through the Overseas Visiting
   Doctoral Fellowship (OVDF) program. S.T. thanks the Department of
   Agricultural and Biological Engineering, Purdue University, DST CoE in
   climate modelling at IIT Delhi, and Yes Foundation for providing the
   resources and infrastructure to conduct this research. D.N. benefited
   from John E. "Brick" Elliott Centennial Endowment at the University of
   Texas at Austin, and NASA CyGNSS Science Team 80NSSC21K1008.
CR Abbasa N., 2016, ENGINEERING, V8, P716, DOI DOI 10.4236/ENG.2016.810065
   Abbaspour K., 2015, Neprashtechnology.Ca, DOI [DOI 10.1007/S00402-009-1032-4, 10.1007/s00402-009-1032-4]
   Abbaspour KC, 2015, J HYDROL, V524, P733, DOI 10.1016/j.jhydrol.2015.03.027
   Abeysingha NS, 2016, SPRINGERPLUS, V5, DOI 10.1186/s40064-016-2905-y
   Bellprat O, 2013, GEOPHYS RES LETT, V40, P4042, DOI 10.1002/grl.50737
   Bosshard T, 2013, WATER RESOUR RES, V49, P1523, DOI 10.1029/2011WR011533
   Cammarano D, 2018, AGR FOREST METEOROL, V248, P109, DOI 10.1016/j.agrformet.2017.09.007
   CECB, 2020, AGRICULTURE
   Chai YF, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/ac3795
   Chakraborty A., 2021, TRANSACTIONS, V43, P93
   Chakraborty A., 2018, T I INDIAN GEOGR, V40, P25
   Chandu N, 2023, ENVIRON MONIT ASSESS, V195, DOI 10.1007/s10661-023-11137-5
   Chaudhary S, 2017, J HYDROL, V546, P204, DOI 10.1016/j.jhydrol.2017.01.023
   Chen JX, 2014, J HYDROL, V517, P595, DOI 10.1016/j.jhydrol.2014.05.075
   Chiew FHS, 2010, GEOGR COMPASS, V4, DOI 10.1111/j.1749-8198.2009.00318.x
   Chowdhury P, 2019, CLIM DYNAM, V52, P4463, DOI 10.1007/s00382-018-4391-0
   Christensen JH, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL035694
   Das P. K., 2023, J AGR PHYS, V23, P170
   Dey A, 2022, J HYDROL, V607, DOI 10.1016/j.jhydrol.2022.127579
   Dobler C, 2012, HYDROL EARTH SYST SC, V16, P4343, DOI 10.5194/hess-16-4343-2012
   Elguindi N, 2014, CLIMATIC CHANGE, V122, P523, DOI 10.1007/s10584-013-1020-0
   Gao JG, 2019, J HYDROL, V568, P551, DOI 10.1016/j.jhydrol.2018.10.041
   Gassman PW, 2007, T ASABE, V50, P1211, DOI 10.13031/2013.23637
   Gaur S, 2021, J WATER CLIM CHANGE, V12, P384, DOI 10.2166/wcc.2020.254
   Giuntoli I, 2018, CLIMATIC CHANGE, V150, P149, DOI 10.1007/s10584-018-2280-5
   Gupta V, 2018, J HYDROL, V567, P489, DOI 10.1016/j.jhydrol.2018.10.012
   Habib E, 2014, REMOTE SENS-BASEL, V6, P6688, DOI 10.3390/rs6076688
   Hausfather Z, 2022, NATURE, V605, P26, DOI 10.1038/d41586-022-01192-2
   Heo JH, 2019, WATER-SUI, V11, DOI 10.3390/w11071475
   Her Y, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-41334-7
   Huang SC, 2014, INT J CLIMATOL, V34, P3780, DOI 10.1002/joc.3945
   Hui Y, 2020, HYDROL RES, V51, P925, DOI 10.2166/nh.2020.254
   Jain S, 2019, ATMOS RES, V228, P152, DOI 10.1016/j.atmosres.2019.05.026
   Jose DM, 2022, SCI REP-UK, V12, DOI 10.1038/s41598-022-08786-w
   Kabir T, 2022, WATER RESOUR RES, V58, DOI 10.1029/2021WR030828
   Krishnan N, 2018, ENVIRON EARTH SCI, V77, DOI 10.1007/s12665-018-7619-8
   Lehner F., 2021, HYDROL EARTH SYST SC, V2021, P1
   Lehner F., 2023, ADV STAT CLIM METEOR, V9, P29, DOI [10.5194/ascmo-9-29-2023, DOI 10.5194/ASCMO-9-29-2023]
   Lehner F, 2019, NAT CLIM CHANGE, V9, P926, DOI 10.1038/s41558-019-0639-x
   Maraun D, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2012GL051210
   Maraun D, 2021, J GEOPHYS RES-ATMOS, V126, DOI 10.1029/2020JD032824
   Maraun D, 2016, CURR CLIM CHANGE REP, V2, P211, DOI 10.1007/s40641-016-0050-x
   Maurer EP, 2014, HYDROL EARTH SYST SC, V18, P915, DOI 10.5194/hess-18-915-2014
   McDermid S, 2016, CURR SCI INDIA, V110, P1257
   Mehan S, 2016, CLIMATE, V4, DOI 10.3390/cli4040056
   Mei YW, 2016, J HYDROMETEOROL, V17, P1407, DOI 10.1175/JHM-D-15-0081.1
   Miao CY, 2023, EARTHS FUTURE, V11, DOI 10.1029/2022EF003286
   Mishra SK, 2018, THEOR APPL CLIMATOL, V133, P1133, DOI 10.1007/s00704-017-2237-z
   Mishra V, 2020, SCI DATA, V7, DOI 10.1038/s41597-020-00681-1
   Misra S, 2018, THEOR APPL CLIMATOL, V134, P1179, DOI 10.1007/s00704-017-2307-2
   Mittelstet AR, 2015, INT J AGR BIOL ENG, V8, P110, DOI 10.3965/j.ijabe.20150803.950
   Moriasi DN, 2015, T ASABE, V58, P1609
   Muerth MJ, 2013, HYDROL EARTH SYST SC, V17, P1189, DOI 10.5194/hess-17-1189-2013
   Nahar J, 2017, J HYDROL, V549, P148, DOI 10.1016/j.jhydrol.2017.03.045
   Nguyen H., 2018, Climate Dynamics, V50, P129, DOI [10.1007/s00382-017-3592-2, 10.1007/s00382-016-3510-z]
   Pai DS, 2014, MAUSAM, V65, P1
   Pai N, 2011, T ASABE, V54, P1649, DOI 10.13031/2013.39854
   Pastén-Zapata E, 2022, WATER RESOUR MANAG, V36, P3545, DOI 10.1007/s11269-022-03212-2
   Pierce DW, 2015, J HYDROMETEOROL, V16, P2421, DOI 10.1175/JHM-D-14-0236.1
   Raju BMK, 2013, CURR SCI INDIA, V105, P492
   Raju KS, 2020, J WATER CLIM CHANGE, V11, P577, DOI 10.2166/wcc.2020.128
   Refsgaard JC, 2013, MITIG ADAPT STRAT GL, V18, P337, DOI 10.1007/s11027-012-9366-6
   Sankarasubramanian A, 2001, WATER RESOUR RES, V37, P1771, DOI 10.1029/2000WR900330
   Senatore A, 2022, J HYDROL-REG STUD, V42, DOI 10.1016/j.ejrh.2022.101120
   Sharifi A, 2021, J HYDROL, V603, DOI 10.1016/j.jhydrol.2021.127045
   Sharma S., 2018, J PHARMACOGN PHYTOCH, V7, P2873
   Singh G, 2019, APPL ENG AGRIC, V35, P723, DOI 10.13031/aea.13295
   Singh J, 2020, CLIMATIC CHANGE, V162, P1323, DOI 10.1007/s10584-020-02786-3
   Srivastava AK, 2009, ATMOS SCI LETT, V10, P249, DOI 10.1002/asl.232
   Sun P, 2024, GLOBAL PLANET CHANGE, V236, DOI 10.1016/j.gloplacha.2024.104428
   Sun P, 2023, SCI TOTAL ENVIRON, V878, DOI 10.1016/j.scitotenv.2023.162980
   Swain S., 2015, INT J ADV ENG RES ST, V87, P89
   Swain S., 2022, ENV CHALLENGES, V8, DOI [10.1016/j.envc.2022.100579, DOI 10.1016/J.ENVC.2022.100579]
   Swain S, 2017, 2017 2ND INTERNATIONAL CONFERENCE FOR CONVERGENCE IN TECHNOLOGY (I2CT), P358, DOI 10.1109/I2CT.2017.8226151
   Switanek MB, 2017, HYDROL EARTH SYST SC, V21, P2649, DOI 10.5194/hess-21-2649-2017
   Tang Y, 2019, J GEOPHYS RES-ATMOS, V124, P11932, DOI 10.1029/2018JD030129
   Teng J, 2015, HYDROL EARTH SYST SC, V19, P711, DOI 10.5194/hess-19-711-2015
   Themessl MJ, 2012, CLIMATIC CHANGE, V112, P449, DOI 10.1007/s10584-011-0224-4
   Thrasher B, 2022, SCI DATA, V9, DOI 10.1038/s41597-022-01393-4
   Tripathi B. P., 2019, INT J CURR MICROBIOL, V8, P807, DOI DOI 10.20546/IJCMAS.2019.809.096
   Tyagi S, 2019, MODEL EARTH SYST ENV, V5, P1, DOI 10.1007/s40808-018-0513-2
   Vema VK, 2020, STOCH ENV RES RISK A, V34, P973, DOI 10.1007/s00477-020-01814-z
   Verma M. K., 2019, INT J HYDROL SCI TEC, V9, P640, DOI [10.1504/IJHST.2019.103444, DOI 10.1504/IJHST.2019.10025126, 10.1504/IJHST.2019.10025126]
   Wang H, 2018, HYDROL PROCESS, V32, P1301, DOI 10.1002/hyp.11509
   Wang HM, 2020, EARTHS FUTURE, V8, DOI 10.1029/2020EF001602
   Wang HM, 2019, HYDROL EARTH SYST SC, V23, P4033, DOI 10.5194/hess-23-4033-2019
   Wang YP, 2018, INT J CLIMATOL, V38, pE330, DOI 10.1002/joc.5375
   Wei XL, 2018, J HYDROL ENG, V23, DOI 10.1061/(ASCE)HE.1943-5584.0001696
   Willkofer F, 2018, J HYDROL-REG STUD, V19, P25, DOI 10.1016/j.ejrh.2018.06.010
   Xiong R, 2021, WATER RESOUR RES, V57, DOI 10.1029/2020WR029397
   Zhang XB, 2011, WIRES CLIM CHANGE, V2, P851, DOI 10.1002/wcc.147
   Zhu XP, 2019, WATER-SUI, V11, DOI 10.3390/w11102130
   Zscheischler J, 2018, NAT CLIM CHANGE, V8, P469, DOI 10.1038/s41558-018-0156-3
NR 93
TC 0
Z9 0
U1 6
U2 6
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 DEC 30
PY 2024
VL 44
IS 16
BP 5727
EP 5744
DI 10.1002/joc.8661
EA OCT 2024
PG 18
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA O9Z4Q
UT WOS:001342980400001
OA hybrid
DA 2025-01-10
ER

PT J
AU Yang, B
   Qiao, L
   Zheng, XW
   Zheng, J
   Wu, BB
   Li, XH
   Zhao, JJ
AF Yang, Bin
   Qiao, Ling
   Zheng, Xingwei
   Zheng, Jun
   Wu, Bangbang
   Li, Xiaohua
   Zhao, Jiajia
TI Quantitative Trait Loci Mapping of Heading Date in Wheat under
   Phosphorus Stress Conditions
SO GENES
LA English
DT Article
DE wheat; heading date; phosphorus stress; quantitative trait loci (QTL);
   molecular markers; candidate genes; wheat breeding; stress tolerance
ID BREAD WHEAT; GENE; PHOTOPERIOD; YIELD; ARCHITECTURE; RESPONSES; BARLEY;
   PLANTS; RICE; IDENTIFICATION
AB Wheat (Triticum aestivum L.) is a crucial cereal crop, contributing around 20% of global caloric intake. However, challenges such as diminishing arable land, water shortages, and climate change threaten wheat production, making yield enhancement crucial for global food security. The heading date (HD) is a critical factor influencing wheat's growth cycle, harvest timing, climate adaptability, and yield. Understanding the genetic determinants of HD is essential for developing high-yield and stable wheat varieties. This study used a doubled haploid (DH) population from a cross between Jinmai 47 and Jinmai 84. QTL analysis of HD was performed under three phosphorus (P) treatments (low, medium, and normal) across six environments, using Wheat15K high-density SNP technology. The study identified 39 QTLs for HD, distributed across ten chromosomes, accounting for 2.39% to 29.52% of the phenotypic variance. Notably, five stable and major QTLs (Qhd.saw-3A.7, Qhd.saw-3A.8, Qhd.saw-3A.9, Qhd.saw-4A.4, and Qhd.saw-4D.3) were consistently detected across varying P conditions. The additive effects of these major QTLs showed that favorable alleles significantly delayed HD. There was a clear trend of increasing HD delay as the number of favorable alleles increased. Among them, Qhd.saw-3A.8, Qhd.saw-3A.9, and Qhd.saw-4D.3 were identified as novel QTLs with no prior reports of HD QTLs/genes in their respective intervals. Candidate gene analysis highlighted seven highly expressed genes related to Ca2+ transport, hormone signaling, glycosylation, and zinc finger proteins, likely involved in HD regulation. This research elucidates the genetic basis of wheat HD under P stress, providing critical insights for breeding high-yield, stable wheat varieties suited to low-P environments.
C1 [Yang, Bin; Qiao, Ling; Zheng, Xingwei; Zheng, Jun; Wu, Bangbang; Li, Xiaohua; Zhao, Jiajia] Shanxi Agr Univ, Inst Wheat Res, Linfen 041000, Peoples R China.
C3 Shanxi Agricultural University
RP Zhao, JJ (corresponding author), Shanxi Agr Univ, Inst Wheat Res, Linfen 041000, Peoples R China.
EM sxxmsyb83@126.com; qiaolingsmile@163.com; smilezxw@126.com;
   sxnkyzj@126.com; bangbang_wu@126.com; lixiaohualff@163.com;
   zhaojiajia@sxau.edu.cn
FU Science and Technology Major Project of Shanxi Province
   [202201140601025-2]; Science and Technology Major Project of Shanxi
   Province [YDZJSX2022A033, YDZJSX20231A039]; Central Leading Local
   Technology Development Fund Project of Shanxi Province
FX This research was funded by the Science and Technology Major Project of
   Shanxi Province (202201140601025-2) and the Central Leading Local
   Technology Development Fund Project of Shanxi Province (YDZJSX2022A033
   and YDZJSX20231A039).
CR Addison CK, 2016, EUPHYTICA, V209, P665, DOI 10.1007/s10681-016-1650-1
   Alvarez MA, 2016, FUNCT INTEGR GENOMIC, V16, P365, DOI 10.1007/s10142-016-0490-3
   Basavaraddi PA, 2021, PLANTS-BASEL, V10, DOI 10.3390/plants10030533
   Baute J, 2017, PLANT CELL PHYSIOL, V58, P962, DOI 10.1093/pcp/pcx035
   Beales J, 2007, THEOR APPL GENET, V115, P721, DOI 10.1007/s00122-007-0603-4
   Benaouda S, 2022, THEOR APPL GENET, V135, P2833, DOI 10.1007/s00122-022-04152-6
   Busse-Wicher M, 2014, MATRIX BIOL, V35, P25, DOI 10.1016/j.matbio.2013.10.001
   Cao SH, 2020, THEOR APPL GENET, V133, P1811, DOI 10.1007/s00122-020-03562-8
   Chen ZY, 2020, THEOR APPL GENET, V133, P1825, DOI 10.1007/s00122-020-03556-6
   Chiou TJ, 2011, ANNU REV PLANT BIOL, V62, P185, DOI 10.1146/annurev-arplant-042110-103849
   Cuthbert JL, 2008, THEOR APPL GENET, V117, P595, DOI 10.1007/s00122-008-0804-5
   Decousset L, 2000, THEOR APPL GENET, V101, P1202, DOI 10.1007/s001220051598
   Devi KD, 2013, SPRINGERPLUS, V2, DOI 10.1186/2193-1801-2-669
   Ding YD, 2023, FRONT PLANT SCI, V14, DOI 10.3389/fpls.2023.1296197
   Distelfeld A, 2009, CURR OPIN PLANT BIOL, V12, P178, DOI 10.1016/j.pbi.2008.12.010
   Dixon LE, 2018, PLANT CELL, V30, P563, DOI 10.1105/tpc.17.00961
   Dubcovsky J, 2007, SCIENCE, V316, P1862, DOI 10.1126/science.1143986
   El-Feki WM, 2018, AGRONOMY-BASEL, V8, DOI 10.3390/agronomy8080133
   Fan XL, 2019, FRONT PLANT SCI, V10, DOI 10.3389/fpls.2019.00187
   Gao SX, 2020, PLANT SCI, V293, DOI 10.1016/j.plantsci.2020.110420
   Griffiths S, 2003, PLANT PHYSIOL, V131, P1855, DOI 10.1104/pp.102.016188
   Griffiths S, 2009, THEOR APPL GENET, V119, P383, DOI 10.1007/s00122-009-1046-x
   Hu JM, 2020, THEOR APPL GENET, V133, P917, DOI 10.1007/s00122-019-03515-w
   Jung C, 2009, TRENDS PLANT SCI, V14, P563, DOI 10.1016/j.tplants.2009.07.005
   Khlestkina EK, 2009, EUPHYTICA, V165, P579, DOI 10.1007/s10681-008-9783-5
   Kippes N, 2015, P NATL ACAD SCI USA, V112, pE5401, DOI 10.1073/pnas.1514883112
   Kudla J, 2010, PLANT CELL, V22, P541, DOI 10.1105/tpc.109.072686
   Lambers H, 2015, NAT PLANTS, V1, DOI [10.1038/NPLANTS.2015.109, 10.1038/nplants.2015.109]
   Lee HS, 2014, PLANT BIOTECHNOL REP, V8, P443, DOI 10.1007/s11816-014-0337-0
   Lewis S, 2008, J EXP BOT, V59, P3595, DOI 10.1093/jxb/ern209
   Li FJ, 2018, THEOR APPL GENET, V131, P1903, DOI 10.1007/s00122-018-3122-6
   Li YT, 2020, BMC PLANT BIOL, V20, DOI 10.1186/s12870-020-02539-5
   Liu G, 2014, THEOR APPL GENET, V127, P2415, DOI 10.1007/s00122-014-2387-7
   Liu H, 2021, PLANTS-BASEL, V10, DOI 10.3390/plants10030593
   López-Arredondo DL, 2014, ANNU REV PLANT BIOL, V65, P95, DOI 10.1146/annurev-arplant-050213-035949
   Luo W, 2016, CROP SCI, V56, P2410, DOI 10.2135/cropsci2015.11.0700
   Lynch JP, 2001, PLANT SOIL, V237, P225, DOI 10.1023/A:1013324727040
   Ma C, 2023, PLANTS-BASEL, V12, DOI 10.3390/plants12040847
   McCouch SR, 1997, PLANT MOL BIOL, V35, P89, DOI 10.1023/A:1005711431474
   Meng L, 2015, CROP J, V3, P269, DOI 10.1016/j.cj.2015.01.001
   Meng QF, 2012, AGR ECOSYST ENVIRON, V146, P93, DOI 10.1016/j.agee.2011.10.015
   Mohler V, 2004, EUPHYTICA, V138, P33, DOI 10.1023/B:EUPH.0000047056.58938.76
   Mohler V, 2016, J APPL GENET, V57, P467, DOI 10.1007/s13353-016-0349-2
   Nezhad NM, 2019, EUPHYTICA, V215, DOI 10.1007/s10681-019-2450-1
   Ni WM, 2004, PLANT PHYSIOL, V134, P1574, DOI 10.1104/pp.103.031971
   Niu YF, 2013, ANN BOT-LONDON, V112, P391, DOI 10.1093/aob/mcs285
   Péret B, 2014, PLANT PHYSIOL, V166, P1713, DOI 10.1104/pp.114.244541
   Raghothama KG, 2005, PLANT SOIL, V274, P37, DOI 10.1007/s11104-004-2005-6
   Richardson AE, 2009, CROP PASTURE SCI, V60, P124, DOI 10.1071/CP07125
   Risseeuw EP, 2003, PLANT J, V34, P753, DOI 10.1046/j.1365-313X.2003.01768.x
   Rouached H, 2010, MOL PLANT, V3, P288, DOI 10.1093/mp/ssp120
   Rustgi S, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0070526
   Sasaki T, 2002, NATURE, V420, P312, DOI 10.1038/nature01184
   Shen JB, 2011, PLANT PHYSIOL, V156, P997, DOI 10.1104/pp.111.175232
   Sherman JD, 2014, CROP SCI, V54, P1, DOI 10.2135/cropsci2012.12.0710
   Shi CN, 2019, BMC PLANT BIOL, V19, DOI 10.1186/s12870-018-1591-z
   Smith SE, 1998, CROP SCI, V38, P1125, DOI 10.2135/cropsci1998.0011183X003800050003x
   Snape JW, 2001, EUPHYTICA, V119, P185, DOI 10.1023/A:1017594422176
   Strejcková B, 2021, INT J MOL SCI, V22, DOI 10.3390/ijms222212284
   Sun CW, 2017, PLANT BIOTECHNOL J, V15, P953, DOI 10.1111/pbi.12690
   Vance CP, 2003, NEW PHYTOL, V157, P423, DOI 10.1046/j.1469-8137.2003.00695.x
   Wang X, 2022, ENVIRON EXP BOT, V201, DOI 10.1016/j.envexpbot.2022.104972
   Wilhelm EP, 2009, THEOR APPL GENET, V118, P285, DOI 10.1007/s00122-008-0898-9
   Wu BP, 2020, BMC PLANT BIOL, V20, DOI 10.1186/s12870-020-02655-2
   Xu HW, 2022, THEOR APPL GENET, V135, P389, DOI 10.1007/s00122-021-03971-3
   Yan L, 2003, P NATL ACAD SCI USA, V100, P6263, DOI 10.1073/pnas.0937399100
   Yan L, 2006, P NATL ACAD SCI USA, V103, P19581, DOI 10.1073/pnas.0607142103
   Yan LL, 2004, SCIENCE, V303, P1640, DOI 10.1126/science.1094305
   Yang B, 2024, AGRONOMY-BASEL, V14, DOI 10.3390/agronomy14040692
   Yang B, 2022, FRONT PLANT SCI, V13, DOI 10.3389/fpls.2022.1019012
NR 70
TC 1
Z9 1
U1 11
U2 11
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4425
J9 GENES-BASEL
JI Genes
PD SEP
PY 2024
VL 15
IS 9
AR 1150
DI 10.3390/genes15091150
PG 16
WC Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Genetics & Heredity
GA H4F6V
UT WOS:001323021000001
PM 39336741
OA gold
DA 2025-01-10
ER

PT J
AU Deng, HJ
   Liu, K
   Feng, JL
   Xiong, YZ
AF Deng, Haojian
   Liu, Kai
   Feng, JiaLi
   Xiong, Yongzhu
TI Tackling the modifiable areal unit problem: Enhancing urban
   sustainability through improved land surface temperature and its
   influencing factors analysis
SO SUSTAINABLE CITIES AND SOCIETY
LA English
DT Article
DE Land surface temperature (LST); Optimal parameters-based geographical
   detector (OPGD) model; Modifiable areal unit problem (MAUP); Interaction
   detector; Scale effect
ID HEAT ISLANDS; CHINA; MAGNITUDE; DATASET; IMPACTS
AB Exploring the modifiable areal unit problem (MAUP) in land surface temperature (LST) and its influencing factors is crucial for understanding LST variation patterns and quantifying the factors' impact. Neglecting the MAUP could lead to an incomplete understanding of LST changes and their driving mechanisms. This study used optimal parameters-based geographical detector and gradient boosting regressor models to investigate the MAUP in LST and its influencing factors. The analysis covered 87 cities across seven climate zones in China, examining MAUP in 12 spatial scales to discern the scale and zoning effects on LST and its influencing factors. The research findings were as follows: (1) The sensitivity of LST influencing factors to spatial scales exhibited both spatial and temporal heterogeneity. Significant differences in the q-values of LST influencing factors were observed across various climate zones and periods (daytime and nighttime), with human factors, particularly those related to residents' work, buildings, life, and rest, showing higher spatial scale dependency than natural factors. (2) Zoning effects significantly impacted the q-values of LST influencing factors and were closely linked to the discretization methods and quantities used, which could alter the trends of these q-values. (3) Across the 12 spatial scales, more than 67.34 % of LST influencing factor interaction types were classified as bi-variable enhancement types. The q-values for LST influencing factor interactions were higher and more stable than those of single factors. LST influencing factor interactions in transitional climate zones exhibited high sensitivity to spatial scales. This research enhances our understanding of LST variations, providing valuable insights for urban climate adaptability planning and the development of climate-resilient cities.
C1 [Deng, Haojian; Liu, Kai] Sun Yat Sen Univ, Guangdong Prov Engn Res Ctr Publ Secur & Disaster, Sch Geog & Planning, Guangdong Prov Key Lab Urbanizat & Geosimulat, Guangzhou 510006, Peoples R China.
   [Liu, Kai] Southern Marine Sci & Engn Guangdong Lab, Zhuhai 519000, Peoples R China.
   [Feng, JiaLi] Shenzhen Inst Meteorol Innovat, Guangdong Hong Kong Macao Greater Bay Area Weather, Shenzhen 518000, Peoples R China.
   [Xiong, Yongzhu] Jiaying Univ, Sch Geog & Tourism, Meizhou 514015, Peoples R China.
   [Xiong, Yongzhu] Guangdong Prov Key Lab Conservat & Precis Utilizat, Meizhou 514105, Peoples R China.
C3 Sun Yat Sen University; Jiaying University
RP Liu, K (corresponding author), Sun Yat Sen Univ, Guangdong Prov Engn Res Ctr Publ Secur & Disaster, Sch Geog & Planning, Guangdong Prov Key Lab Urbanizat & Geosimulat, Guangzhou 510006, Peoples R China.; Liu, K (corresponding author), Southern Marine Sci & Engn Guangdong Lab, Zhuhai 519000, Peoples R China.
EM denghj9@mail2.sysu.edu.cn; liuk6@mail.sysu.edu.cn; jxf545@gbamwf.com;
   xiongyz@jyu.edu.cn
RI feng, Jiali/AAG-5458-2021; Liu, Kai/K-7307-2015
OI feng, jiali/0000-0002-8082-5525; Liu, Kai/0000-0002-1829-7557; Haojian,
   Deng/0000-0003-3724-8571
FU Shenzhen Science and Technology Innovation Commission
   [KCXFZ20230731094905010]; National Natural Science Foundation of China
   [42,205,088, 42,201,353]; Innovation Group Project of Southern Marine
   Science and Engineering, Guangdong Laboratory (Zhuhai) [311,021,004]
FX This research was funded by Shenzhen Science and Technology Innovation
   Commission, grant number: KCXFZ20230731094905010, National Natural
   Science Foundation of China, grant number: 42,205,088 and 42,201,353,
   and the Innovation Group Project of Southern Marine Science and
   Engineering, Guangdong Laboratory (Zhuhai) , grant numbers: 311,021,004.
CR Ahmed G, 2022, ENVIRON ENG SCI, V39, P928, DOI 10.1089/ees.2021.0556
   Ali R. A., 2023, City, Territory and Architecture, V10, DOI [10.1186/s40410-023-00212-6, DOI 10.1186/S40410-023-00212-6]
   [Anonymous], 2022, ArcGIS Pro: Release 3.0
   Bai HX, 2023, ANN AM ASSOC GEOGR, V113, P2512, DOI 10.1080/24694452.2023.2223700
   Block A, 2004, GEOPHYS RES LETT, V31, DOI 10.1029/2004GL019852
   Chen L, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13020323
   Chen ZQ, 2021, EARTH SYST SCI DATA, V13, P889, DOI 10.5194/essd-13-889-2021
   Clinton N, 2013, REMOTE SENS ENVIRON, V134, P294, DOI 10.1016/j.rse.2013.03.008
   CPGPRC (Central People's Government of the People's Republic of China), 2014, Notification by the Standard of State Council on Adjusting the Urban Scale
   Dai ZX, 2019, ECOL INDIC, V97, P77, DOI 10.1016/j.ecolind.2018.09.041
   DAVIS FW, 1991, PHOTOGRAMM ENG REM S, V57, P689
   de Andrade SC, 2021, INT J GEOGR INF SCI, V35, P43, DOI 10.1080/13658816.2020.1755039
   Deng HJ, 2024, GEO-SPAT INF SCI, DOI 10.1080/10095020.2024.2336593
   Deng HJ, 2023, LAND-BASEL, V12, DOI 10.3390/land12091800
   Deng HJ, 2021, J URBAN PLAN DEV, V147, DOI 10.1061/(ASCE)UP.1943-5444.0000735
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Flanner MG, 2009, GEOPHYS RES LETT, V36, DOI 10.1029/2008GL036465
   Gao F, 2021, INT J GEOGR INF SCI, V35, P1905, DOI 10.1080/13658816.2020.1863410
   Gao J., 2022, China Regional 250m Fractional Vegetation Cover Data Set (2000-2022)
   Gehlke CE, 1934, J AM STAT ASSOC, V29, P169, DOI 10.2307/2277827
   Geng XL, 2023, SUSTAIN CITIES SOC, V89, DOI 10.1016/j.scs.2022.104303
   Guo FX, 2023, SUSTAIN CITIES SOC, V97, DOI 10.1016/j.scs.2023.104788
   Guo JH, 2024, SUSTAIN CITIES SOC, V100, DOI 10.1016/j.scs.2023.105003
   Han DR, 2022, BUILD ENVIRON, V226, DOI 10.1016/j.buildenv.2022.109770
   He QS, 2023, COMPUT ENVIRON URBAN, V105, DOI 10.1016/j.compenvurbsys.2023.102023
   Hou HR, 2023, INT J APPL EARTH OBS, V122, DOI 10.1016/j.jag.2023.103411
   Hu D, 2022, INT J APPL EARTH OBS, V106, DOI 10.1016/j.jag.2021.102648
   Jamali AA, 2022, J ENVIRON MANAGE, V302, DOI 10.1016/j.jenvman.2021.113970
   Jelinski DE, 1996, LANDSCAPE ECOL, V11, P129, DOI 10.1007/BF02447512
   Josselin D, 2019, ISPRS INT J GEO-INF, V8, DOI 10.3390/ijgi8030156
   Lai JM, 2021, ISPRS J PHOTOGRAMM, V176, P182, DOI 10.1016/j.isprsjprs.2021.04.009
   Li D, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aau4299
   Lin ZL, 2024, SUSTAIN CITIES SOC, V101, DOI 10.1016/j.scs.2024.105190
   Liu J, 2020, URBAN CLIM, V33, DOI 10.1016/j.uclim.2020.100659
   Liu MB, 2023, J CLEAN PROD, V415, DOI 10.1016/j.jclepro.2023.137878
   Luan XL, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12030391
   Luyssaert S, 2014, NAT CLIM CHANGE, V4, P389, DOI [10.1038/nclimate2196, 10.1038/NCLIMATE2196]
   Manoli G, 2019, NATURE, V573, P55, DOI 10.1038/s41586-019-1512-9
   MHC (Ministry of Housing and Urban-Rural Development of the People's Republic of China), 2012, Residential Design Code
   Naserikia M, 2022, SCI REP-UK, V12, DOI 10.1038/s41598-022-19431-x
   Openshaw S., 1984, Concepts and techniques in modern geography
   Patel S, 2024, SUSTAIN CITIES SOC, V104, DOI 10.1016/j.scs.2024.105273
   Peng J, 2020, REMOTE SENS ENVIRON, V246, DOI 10.1016/j.rse.2020.111866
   Peng J, 2018, REMOTE SENS ENVIRON, V215, P255, DOI 10.1016/j.rse.2018.06.010
   Peng SZ, 2019, EARTH SYST SCI DATA, V11, P1931, DOI 10.5194/essd-11-1931-2019
   Perini K., 2021, innovations in ventilative cooling, P213
   Song JC, 2020, LANDSCAPE URBAN PLAN, V198, DOI 10.1016/j.landurbplan.2020.103794
   Song YZ, 2020, GISCI REMOTE SENS, V57, P593, DOI 10.1080/15481603.2020.1760434
   [孙佳彬 Sun Jiabin], 2022, [地域研究与开发, Areal Research and Development], V41, P167
   [陶于祥 Tao Yuxiang], 2018, [西南大学学报. 自然科学版, Journal of Southwest University. Natural Science Edition], V40, P145
   Tian H, 2024, J GEOGR SCI, V34, P375, DOI 10.1007/s11442-024-2209-z
   Turner B., 1990, EARTH TRANSFORMED HU
   UN. United Nations NEWS, 2023, Global perspective Human storiesGlobal boiling era' comes as cooperation lacking
   United Nations, 2015, TRANSF OUR WORLD 203
   Wang J. F., 2023, Statistical Modeling of Spatially Stratified Heterogeneous Data
   Wang JF, 2010, INT J GEOGR INF SCI, V24, P107, DOI 10.1080/13658810802443457
   Wang P, 2022, J CLEAN PROD, V340, DOI 10.1016/j.jclepro.2022.130804
   Wang W, 2021, J ARID ENVIRON, V186, DOI 10.1016/j.jaridenv.2020.104415
   Wong D.W., 2004, WorldMinds Geogr Perspect 100 Probl Commem 100th Anniv Assoc Am Geogr 1904-2004, P571, DOI [10.4135/9780857020130.n7, DOI 10.4135/9780857020130.N7]
   Wu WB, 2023, REMOTE SENS ENVIRON, V291, DOI 10.1016/j.rse.2023.113578
   Wu ZQ, 2022, SCI TOTAL ENVIRON, V838, DOI 10.1016/j.scitotenv.2022.156348
   Yang J, 2021, EARTH SYST SCI DATA, V13, P3907, DOI 10.5194/essd-13-3907-2021
   Yi Y, 2021, LAND-BASEL, V10, DOI 10.3390/land10101025
   Yu LX, 2023, SCI TOTAL ENVIRON, V896, DOI 10.1016/j.scitotenv.2023.165255
   Yu YR, 2023, REMOTE SENS-BASEL, V15, DOI 10.3390/rs15112814
   Yuan Y, 2022, ENVIRON INT, V170, DOI 10.1016/j.envint.2022.107574
   Zhou DC, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/7/074009
NR 67
TC 1
Z9 1
U1 29
U2 29
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 105747
DI 10.1016/j.scs.2024.105747
EA AUG 2024
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 E2F6C
UT WOS:001301215100001
DA 2025-01-10
ER

PT J
AU Kivimäki, I
   Van Moorter, B
   Saerens, M
AF Kivimaki, Ilkka
   Van Moorter, Bram
   Saerens, Marco
TI Sensitivity to network perturbations in the randomized shortest paths
   framework: theory and applications in ecological connectivity
SO JOURNAL OF PHYSICS-COMPLEXITY
LA English
DT Article
DE corridors; linear response theory; migration; sensitivity analysis;
   spatial conservation prioritization; susceptibility; Rangifer rangifer
ID RANGE SHIFTS; MIGRATION; CORRIDORS; CONTRIBUTE; SELECTION; GRAPH
AB The randomized shortest paths (RSP) framework, developed for network analysis, extends traditional proximity and distance measures between two nodes, such as shortest path distance and commute cost distance (related to resistance distance). Consequently, the RSP framework has gained popularity in studies on landscape connectivity within ecology and conservation, where the behavior of animals is neither random nor optimal. In this work, we study how local perturbations in a network affect proximity and distance measures derived from the RSP framework. For this sensitivity analysis, we develop computable expressions for derivatives with respect to weights on the edges or nodes of the network. Interestingly, the sensitivity of expected cost to edge or node features provides a new signed network centrality measure, the negative covariance between edge/node visits and path cost, that can be used for pinpointing strong and weak parts of a network. It is also shown that this quantity can be interpreted as minus the endured expected detour (in terms of cost) when constraining the walk to pass through the node or the edge. Our demonstration of this framework focuses on a migration corridor for wild reindeer (Rangifer rangifer) in Southern Norway. By examining the sensitivity of the expected cost of movement between winter and calving ranges to perturbations in local areas, we have identified priority areas crucial for the conservation of this migration corridor. This innovative approach not only holds great promise for conservation and restoration of migration corridors, but also more generally for connectivity corridors between important areas for biodiversity (e.g. protected areas) and climate adaptation. Furthermore, the derivations and computational methods introduced in this work present fundamental features of the RSP framework. These contributions are expected to be of interest to practitioners applying the framework across various disciplines, ranging from ecology, transport and communication networks to machine learning.
C1 [Kivimaki, Ilkka] Finnish Inst Occupat Hlth, Helsinki, Finland.
   [Van Moorter, Bram] Norwegian Inst Nat Res, Oslo, Norway.
   [Saerens, Marco] Catholic Univ Louvain, ICTEAM, Louvain La Neuve, Belgium.
C3 Finnish Institute of Occupational Health; Norwegian Institute Nature
   Research; Universite Catholique Louvain
RP Van Moorter, B (corresponding author), Norwegian Inst Nat Res, Oslo, Norway.
EM bram.van.moorter@nina.no
OI Van Moorter, Bram/0000-0002-3196-1993
FU Norges Forskningsrdhttp://dx.doi.org/10.13039/501100005416 [287925];
   Research Council of Norway
FX The work was supported by the Grant 287925 from the Research Council of
   Norway. The authors thank two anonymous reviewers for their constructive
   comments on this work.
CR Alagador D, 2016, METHODS ECOL EVOL, V7, P853, DOI 10.1111/2041-210X.12524
   [Anonymous], 2011, Statistical mechanics in a nutshell
   [Anonymous], 2007, Statistical Physics of Particles
   [Anonymous], 2005, Matrix Algebra
   Bavaud F, 2012, LECT NOTES COMPUT SC, V7710, P68, DOI 10.1007/978-3-642-35386-4_6
   Beier P, 2008, CONSERV BIOL, V22, P836, DOI 10.1111/j.1523-1739.2008.00942.x
   Berger J, 2004, CONSERV BIOL, V18, P320, DOI 10.1111/j.1523-1739.2004.00548.x
   Bezanson J, 2017, SIAM REV, V59, P65, DOI 10.1137/141000671
   Bolger DT, 2008, ECOL LETT, V11, P63
   Brandes U, 2005, LECT NOTES COMPUT SC, V3404, P533
   Brennan A, 2018, LANDSCAPE ECOL, V33, P955, DOI 10.1007/s10980-018-0642-z
   Caswell Hal, 2001, pi
   Chandra A. K., 1989, Proceedings of the Twenty First Annual ACM Symposium on Theory of Computing, P574, DOI 10.1145/73007.73062
   Chen IC, 2011, SCIENCE, V333, P1024, DOI 10.1126/science.1206432
   Christofides N., 1975, Graph Theory: An Algorithmic Approach (Computer Science and Applied Mathematics)
   Cover T. M., 2005, Elements of Information Theory, DOI DOI 10.1002/047174882X.CH2
   Daigle RM, 2020, METHODS ECOL EVOL, V11, P570, DOI 10.1111/2041-210X.13349
   Fletcher RJ, 2019, ECOL LETT, V22, P1680, DOI 10.1111/ele.13333
   Fouss F., 2016, Algorithms and Models for Network Data and Link Analysis
   Fouss F, 2007, IEEE T KNOWL DATA EN, V19, P355, DOI 10.1109/TKDE.2007.46
   Françoisse K, 2017, NEURAL NETWORKS, V90, P90, DOI 10.1016/j.neunet.2017.03.010
   FREEMAN LC, 1977, SOCIOMETRY, V40, P35, DOI 10.2307/3033543
   Fullman TJ, 2017, MOV ECOL, V5, P1, DOI 10.1186/s40462-017-0095-z
   García-Díez S, 2011, PATTERN RECOGN, V44, P1172, DOI 10.1016/j.patcog.2010.11.020
   Gondran M., 1984, Graphs and algorithms
   Gruber B, 2015, MOL ECOL RESOUR, V15, P1172, DOI 10.1111/1755-0998.12381
   Guex G, 2019, NETW SCI, V7, P88, DOI 10.1017/nws.2018.29
   Harris Grant, 2009, Endangered Species Research, V7, P55, DOI 10.3354/esr00173
   Harville D. A., 1997, Matrix Algebra from a Statistician's Perspective
   Hodgson JA, 2016, METHODS ECOL EVOL, V7, P1558, DOI 10.1111/2041-210X.12614
   Jalkanen J, 2020, LANDSCAPE ECOL, V35, P353, DOI 10.1007/s10980-019-00950-4
   JAYNES ET, 1957, PHYS REV, V106, P620, DOI 10.1103/PhysRev.106.620
   Kivimäki I, 2020, J COMPLEX NETW, V8, DOI 10.1093/comnet/cnaa024
   Kivimäki I, 2016, SCI REP-UK, V6, DOI 10.1038/srep19668
   Kivimäki I, 2014, PHYSICA A, V393, P600, DOI 10.1016/j.physa.2013.09.016
   Kivimki I., 2018, PhD Thesis
   Klein DJ, 2010, J MATH CHEM, V47, P1209, DOI 10.1007/s10910-009-9635-0
   KLEIN DJ, 1993, J MATH CHEM, V12, P81, DOI 10.1007/BF01164627
   Klein DJ, 2002, CROAT CHEM ACTA, V75, P633
   Kukkala AS, 2017, LANDSCAPE ECOL, V32, P5, DOI 10.1007/s10980-016-0446-y
   Kuramoto Y., 1984, Chemical Turbulence
   Lebichot B, 2018, NEUROCOMPUTING, V275, P224, DOI 10.1016/j.neucom.2017.06.054
   Lebichot B, 2014, IEEE T NEUR NET LEAR, V25, P1173, DOI 10.1109/TNNLS.2013.2290281
   Leleux P, 2021, DATA MIN KNOWL DISC, V35, P986, DOI 10.1007/s10618-021-00742-y
   Long JA, 2019, LANDSCAPE ECOL, V34, P2509, DOI 10.1007/s10980-019-00883-y
   Manik D, 2017, PHYS REV E, V95, DOI 10.1103/PhysRevE.95.012319
   Marx AJ, 2020, ECOGRAPHY, V43, P518, DOI 10.1111/ecog.04891
   McGuire JL, 2016, P NATL ACAD SCI USA, V113, P7195, DOI 10.1073/pnas.1602817113
   Moilanen A., 2009, Spatial conservation prioritization: Quantitative methods and computational tools, P196
   Muenzel D, 2023, CONSERV BIOL, V37, DOI 10.1111/cobi.14008
   Nellemann C, 2003, BIOL CONSERV, V113, P307, DOI 10.1016/S0006-3207(03)00048-X
   Newman MEJ, 2005, SOC NETWORKS, V27, P39, DOI 10.1016/j.socnet.2004.11.009
   Nuñez TA, 2013, CONSERV BIOL, V27, P407, DOI 10.1111/cobi.12014
   Ovaskainen O, 2003, THEOR POPUL BIOL, V64, P481, DOI 10.1016/S0040-5809(03)00102-3
   Ovaskainen O, 2003, MATH BIOSCI, V181, P165, DOI 10.1016/S0025-5564(02)00150-5
   Panzacchi M, 2016, J ANIM ECOL, V85, P32, DOI 10.1111/1365-2656.12386
   Panzacchi M, 2015, ECOGRAPHY, V38, P659, DOI 10.1111/ecog.01075
   Peck CP, 2017, ECOSPHERE, V8, DOI 10.1002/ecs2.1969
   Pouzols FM, 2014, LANDSCAPE ECOL, V29, P789, DOI 10.1007/s10980-014-0031-1
   Ranjan G, 2013, PHYSICA A, V392, P3833, DOI 10.1016/j.physa.2013.04.013
   Rodrigues FA, 2016, PHYS REP, V610, P1, DOI 10.1016/j.physrep.2015.10.008
   Saerens M, 2009, NEURAL COMPUT, V21, P2363, DOI 10.1162/neco.2009.11-07-643
   Saura S, 2010, ECOGRAPHY, V33, P523, DOI 10.1111/j.1600-0587.2009.05760.x
   Sawyer H, 2009, ECOL APPL, V19, P2016, DOI 10.1890/08-2034.1
   Sedgewick Robert., 2002, ALGORITHMS C PART 5, V3rd
   Strand O., 2011, Technical Report
   Thurfjell H, 2014, MOV ECOL, V2, DOI 10.1186/2051-3933-2-4
   van Etten J, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0012060
   Van Moorter B, 2023, ECOLOGY, V104, DOI 10.1002/ecy.4105
   Van Moorter B, 2021, ECOGRAPHY, V44, P870, DOI 10.1111/ecog.05351
   Vors LS, 2009, GLOBAL CHANGE BIOL, V15, P2626, DOI 10.1111/j.1365-2486.2009.01974.x
   Wilcove DS, 2008, PLOS BIOL, V6, P1361, DOI 10.1371/journal.pbio.0060188
   Winograd T., 1999, Stanford Digit. Libraries Work. Pap., DOI DOI 10.1007/978-3-319-08789-410
   Yen L., 2008, P 14 ACM SIGKDD INT, P785, DOI DOI 10.1145/1401890.1401984
NR 74
TC 0
Z9 0
U1 0
U2 1
PU IOP Publishing Ltd
PI BRISTOL
PA TEMPLE CIRCUS, TEMPLE WAY, BRISTOL BS1 6BE, ENGLAND
EI 2632-072X
J9 J PHYS-COMPLEXITY
JI J. Phys.-Complex.
PD JUN 1
PY 2024
VL 5
IS 2
AR 025017
DI 10.1088/2632-072X/ad4841
PG 27
WC Mathematics, Interdisciplinary Applications; Multidisciplinary Sciences;
   Physics, Mathematical
WE Emerging Sources Citation Index (ESCI)
SC Mathematics; Science & Technology - Other Topics; Physics
GA SM1O9
UT WOS:001234780800001
OA gold
DA 2025-01-10
ER

PT J
AU Sahoo, S
   Singha, C
   Govind, A
AF Sahoo, Satiprasad
   Singha, Chiranjit
   Govind, Ajit
TI Prediction of pulse suitability in rice fallow areas using fuzzy
   AHP-based machine learning methods in Eastern India
SO PADDY AND WATER ENVIRONMENT
LA English
DT Article
DE Rice fallow areas; Pulse suitability; Fuzzy-AHP; Machine learning
ID LAND SUITABILITY; INFORMATION; CROPS
AB In Eastern India, a widespread practice known as "rice fallow pulse" (RFP) involves using the soil's remaining moisture to grow a short-duration pulse crop. For rainfed systems, it is an excellent practice of climate adaptation. To help farmers make informed decisions about where to plant what and to help policymakers create favorable conditions for timely seed distribution, it is imperative to forecast the appropriateness of pulse crops both geographically and temporally. Using fuzzy AHP (FAHP)-based machine learning methods, we tried to detect pulse appropriateness both geographically and temporally while considering fifteen natural, climatic, environment, and soil health-related characteristics in the Western Lateritic Zone of the Indian State of West Bengal. According to the findings, all machine learning (ML) techniques identified high-suitability zones in the districts of Murshidabad, Birbhum, Paschim Bardhaman, Paschim Medinipur, and Jhargram. By using machine learning techniques such as shrinkage discriminant analysis (SDA), neural network (nnet), random forest (RF), Naive Bayes (NB), rule-based C5.0, genetic algorithm (GA), and particle swarm optimization (PSO), it was found that moderate suitability zones were visible in some areas of Murshidabad, Birbhum, Paschim Bardhaman, Paschim Medinipur, and Purulia. Additionally, it was noted that all ML approaches revealed maximum low suitability zones in certain areas of Birbhum, Bankura, Purba Bardhaman, Purulia, and Murshidabad. Finally, district-level yearly pulse yields of minor, chickpea, and pigeonpea verified the precision of the ML-based models. We have devised a structure to assess pulse suitability analysis to improve crop and land productivity. One of the world's most populous regions can use the data to inform policy decisions that will improve food and nutritional security in the face of shifting economic and environmental conditions.
C1 [Sahoo, Satiprasad; Govind, Ajit] Int Ctr Agr Res Dry Areas ICARDA, 2 Port Said,Victoria Sq,Ismail El Shaaer Bldg,15A, Cairo 11728, Egypt.
   [Singha, Chiranjit] Visva Bharati, Inst Agr, Dept Agr Engn, Birbhum 731236, West Bengal, India.
C3 CGIAR; International Center for Agricultural Research in the Dry Areas
   (ICARDA); Visva Bharati University
RP Sahoo, S (corresponding author), Int Ctr Agr Res Dry Areas ICARDA, 2 Port Said,Victoria Sq,Ismail El Shaaer Bldg,15A, Cairo 11728, Egypt.
EM satispss@gmail.com
RI Sahoo, Dr. Satiprasad/AAG-2660-2021; Singha, Chiranjit/LTD-8193-2024;
   Govind, Ajit/F-1693-2010
OI Singha, Dr. Chiranjit/0000-0003-1204-1750; Sahoo,
   Satiprasad/0000-0002-6490-7432
FU Project "Integration of Digital Augmentation for sustainable
   Agroecosystem in Western Lateritic Zone under National Hydrology
   Project, West Bengal"; International Centre for Agricultural Research in
   the Dry Areas (ICARDA)
FX We acknowledge the project "Integration of Digital Augmentation for
   sustainable Agroecosystem in Western Lateritic Zone under National
   Hydrology Project, West Bengal" under which this work is mapped. The
   author also convey special thanks the International Centre for
   Agricultural Research in the Dry Areas (ICARDA) for supporting necessary
   logistics for this research work.
CR Abatzoglou JT, 2018, SCI DATA, V5, DOI 10.1038/sdata.2017.191
   Ahmad F, 2018, CONTEMP TRENDS GEOSC, V7, P214, DOI 10.2478/ctg-2018-0015
   Bandyopadhyay S, 2009, INT J REMOTE SENS, V30, P879, DOI 10.1080/01431160802395235
   Bandyopadhyayl S., 2006, INT J GEOINF, V2, P1
   Bhullar A, 2023, SCI REP-UK, V13, DOI 10.1038/s41598-023-33840-6
   Breiman L., 2001, Machine Learning, V45, P5, DOI 10.1023/A:1010933404324
   Butt AH, 2018, BIOMED ENG ONLINE, V17, DOI 10.1186/s12938-018-0600-7
   Cartwright H., 2015, METHOD MOL BIOL, DOI [10.1007/978-1-4939-2239_0, DOI 10.1007/978-1-4939-2239_0]
   Chandrakala M, 2022, COMMUN SOIL SCI PLAN, V53, P675, DOI 10.1080/00103624.2022.2028807
   Chang DY, 1996, EUR J OPER RES, V95, P649, DOI 10.1016/0377-2217(95)00300-2
   Chiranjit Singha Chiranjit Singha, 2018, International Journal of Bio-resource and Stress Management, V9, P323, DOI 10.23910/ijbsm/2018.9.3.1869
   Cutforth HW, 2007, AGRON J, V99, P1684, DOI 10.2134/agronj2006.0310s
   Danodia A, 2021, ENVIRON DEV SUSTAIN, V23, P15432, DOI 10.1007/s10668-021-01305-3
   Dhanalakshmi A, 2020, COMMUN SOIL SCI PLAN, V51, P2670, DOI 10.1080/00103624.2020.1845353
   Ernawati L, 2008, PREDIKSI STATUS KEAK
   Fischer G., 2008, Global Agro-ecological Zones Assessment for Agriculture (GAEZ 2008), P10
   Giannarakis G, 2022, IEEE COMPUT SOC CONF, P1441, DOI 10.1109/CVPRW56347.2022.00150
   Gumma MK, 2018, GISCI REMOTE SENS, V55, P926, DOI 10.1080/15481603.2018.1482855
   Hossen B, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su132212360
   Hussein F, 2001, PROC INT CONF DOC, P1240, DOI 10.1109/ICDAR.2001.953980
   Jamil M, 2018, GEOJOURNAL, V83, P595, DOI 10.1007/s10708-017-9788-5
   Kennedy J, 1995, 1995 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS PROCEEDINGS, VOLS 1-6, P1942, DOI 10.1109/icnn.1995.488968
   Kumar KK, 2011, CLIM DYNAM, V36, P2159, DOI 10.1007/s00382-010-0974-0
   Mandal S, 2020, APPL GEOGR, V122, DOI 10.1016/j.apgeog.2020.102249
   Mandal VP, 2020, SPAT INF RES, V28, P589, DOI 10.1007/s41324-020-00315-z
   Mikhailov L, 2004, APPL SOFT COMPUT, V5, P23, DOI 10.1016/j.asoc.2004.04.001
   Moller AB, 2021, AGRONOMY-BASEL, V11, DOI 10.3390/agronomy11040703
   Pekel JF, 2016, NATURE, V540, P418, DOI 10.1038/nature20584
   Peter BG, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-72384-x
   Poggio L M., 2020, Soils Natural Environ, V1, DOI [DOI 10.5194/SOIL-7-217-2021, DOI 10.5194/SOIL-2020-65]
   Poggio L, 2021, SOIL-GERMANY, V7, P217, DOI 10.5194/soil-7-217-2021
   Radocaj D, 2022, AGRONOMY-BASEL, V12, DOI 10.3390/agronomy12092210
   Ramup Penki, 2022, Progress in Agricultural Engineering Sciences, V18, P77, DOI 10.1556/446.2022.00050
   Ravikumar D., 2019, J PHARMACOG PHYTOCHE, V8, P2128
   Ray M., 2013, International Journal of Bio-resource and Stress Management, V4, P293
   Sabater J.Munoz., 2019, COPERNICUS CLIMATE C
   Sahoo S, 2021, ACTA GEOPHYS, V69, P175, DOI 10.1007/s11600-020-00509-x
   Satishkumar U., 2019, INT J CURR MICROBIOL, V8, P1302, DOI [10.20546/ijcmas.2019.812.159, DOI 10.20546/IJCMAS.2019.812.159]
   Shivran R., 2016, Indian J Agron, V61, pS71
   Singh RK., 2021, MAPPING MONITORING M, P21, DOI [10.1201/9781003181293-3, DOI 10.1201/9781003181293-3]
   Singha C, 2020, AGRICULTURE-BASEL, V10, DOI 10.3390/agriculture10060213
   Straffelini E, 2023, AGR SYST, V208, DOI 10.1016/j.agsy.2023.103647
   Swain KC, 2020, ISPRS INT J GEO-INF, V9, DOI 10.3390/ijgi9120720
   Xue L, 2023, ECOL INDIC, V148, DOI 10.1016/j.ecolind.2022.109837
   Zuber V, 2009, BIOINFORMATICS, V25, P2700, DOI 10.1093/bioinformatics/btp460
NR 45
TC 1
Z9 1
U1 3
U2 5
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 1611-2490
EI 1611-2504
J9 PADDY WATER ENVIRON
JI Paddy Water Environ.
PD JUL
PY 2024
VL 22
IS 3
BP 341
EP 359
DI 10.1007/s10333-024-00970-0
EA MAR 2024
PG 19
WC Agricultural Engineering; Agronomy
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA YJ8T2
UT WOS:001177478700001
DA 2025-01-10
ER

PT J
AU Andreozzi, CL
   Dawson, TE
   Kitzes, J
   Merenlender, AM
AF Andreozzi, Chelsea L.
   Dawson, Todd E.
   Kitzes, Justin
   Merenlender, Adina M.
TI Influence of microclimate and forest management on bat species faced
   with global change
SO CONSERVATION BIOLOGY
LA English
DT Article
DE acoustic monitoring; Chiroptera; climate change; climate refugia; forest
   management; habitat suitability
ID CLIMATE-CHANGE; SUMMER FOG; TEMPERATURE; CONSERVATION; ABUNDANCE;
   RESPONSES; SELECTION; COAST
AB Climate refugia, areas where climate is expected to remain relatively stable, can offer a near-term safe haven for species sensitive to warming temperatures and drought. Understanding the influence of temperature, moisture, and disturbance on sensitive species is critical during this time of rapid climate change. Coastal habitats can serve as important refugia. Many of these areas consist of working forestlands, and there is a growing recognition that conservation efforts worldwide must consider the habitat value of working lands, in addition to protected areas, to effectively manage large landscapes that support biodiversity. The sensitivity of forest bats to climate and habitat disturbance makes them a useful indicator taxon. We tested how microclimate and forest management influence habitat use for 13 species of insectivorous bats in a large climate refugium in a global biodiversity hotspot. We examined whether bat activity during the summer dry season is greater in forests where coastal fog provides moisture and more stable temperatures across both protected mature stands and those regularly logged. Acoustic monitoring was conducted at a landscape scale with 20 study sites, and generalized linear mixed models were used to examine the influence of habitat variables. Six species were positively associated with warmer nighttime temperature, and 5 species had a negative relationship with humidity or a positive relationship with climatic moisture deficit. Our results suggest that these mammals may have greater climate adaptive capacity than expected, and, for now, that habitat use may be more related to optimal foraging conditions than to avoidance of warming temperatures and drought. We also determined that 12 of the 13 regionally present bat species were regularly detected in commercial timberland stands. Because forest bats are highly mobile, forage over long distances, and frequently change roosts, the stewardship of working forests must be addressed to protect these species.
C1 [Andreozzi, Chelsea L.; Merenlender, Adina M.] Univ Calif Berkeley, Dept Environm Sci Policy & Management, 130 Mulford Hall, Berkeley, CA 94720 USA.
   [Dawson, Todd E.] Univ Calif Berkeley, Dept Integrat Biol, Berkeley, CA 94720 USA.
   [Kitzes, Justin] Univ Pittsburgh, Dept Biol Sci, Pittsburgh, PA USA.
C3 University of California System; University of California Berkeley;
   University of California System; University of California Berkeley;
   Pennsylvania Commonwealth System of Higher Education (PCSHE); University
   of Pittsburgh
RP Andreozzi, CL (corresponding author), Univ Calif Berkeley, Dept Environm Sci Policy & Management, 130 Mulford Hall, Berkeley, CA 94720 USA.
EM chelsea.andreozzi@gmail.com
RI Dawson, Todd/ABO-2712-2022
OI Andreozzi, Chelsea/0000-0001-6794-8427
FU National Science Foundation Graduate Research Fellowship Program; Save
   the Redwoods League, The Conservation Fund; Lyme Timber Company;
   University of California Natural Reserve System - NSF Graduate Research
   Fellowship Program; Save the Redwoods League; Carol Baird Fund; Bob
   Berry Scholarship Fund; University of California, Berkeley's Department
   of Environmental Science, Policy, and Management's Forestry Endowment
   Fund; Wildlife and Fisheries Oliver Lyman Fund, and Researcher Starter
   Grant
FX We thank S. Feirer for advising on methods for geospatial analysis of
   stream channel, K. Heise for significant fieldwork support, and A.
   Middleton for comments on earlier drafts of this manuscript. We are also
   grateful to participating landowners and land managers who provided
   access to study sites, including California Department of Forestry and
   Fire Protection, California State Parks, Mailliard Family, Mendocino
   Redwood Company, North Coast Resource Management, Save the Redwoods
   League, The Conservation Fund, The Lyme Timber Company, and University
   of California Natural Reserve System. R. Douglas, L. Webb, P. Steele, S.
   Martin, T. Fuller, B. O'Neil, S. Fullerton, S. Kelly, E. Burns, and K.
   Shrive provided critical support for securing research permissions and
   strategizing monitoring locations. C.L.A. was funded by the NSF Graduate
   Research Fellowship Program; Save the Redwoods League; Carol Baird Fund;
   Bob Berry Scholarship Fund; and the University of California, Berkeley's
   Department of Environmental Science, Policy, and Management's Forestry
   Endowment Fund, Wildlife and Fisheries Oliver Lyman Fund, and Researcher
   Starter Grant.
CR Ackerly DD, 2020, FRONT ECOL ENVIRON, V18, P288, DOI 10.1002/fee.2204
   Adams AM, 2012, METHODS ECOL EVOL, V3, P992, DOI 10.1111/j.2041-210X.2012.00244.x
   Adams RA, 2018, J ZOOL, V304, P268, DOI 10.1111/jzo.12526
   Adams RA, 2008, J ANIM ECOL, V77, P1115, DOI 10.1111/j.1365-2656.2008.01447.x
   Adams RA, 2010, ECOLOGY, V91, P2437, DOI 10.1890/09-0091.1
   Amorim F, 2015, MAMM BIOL, V80, P228, DOI 10.1016/j.mambio.2015.01.005
   Anderson MG, 2014, CONSERV BIOL, V28, P959, DOI 10.1111/cobi.12272
   [Anonymous], 2005, Bat Ecology
   Armstrong A., 2021, USE REDWOOD BASAL HO
   Balantic C, 2021, CONSERV SCI PRACT, V3, DOI 10.1111/csp2.497
   Bender MJ, 2015, SOUTHEAST NAT, V14, P231, DOI 10.1656/058.014.0203
   Blakey RV, 2019, ECOL EVOL, V9, P5324, DOI 10.1002/ece3.5121
   Britzke ER, 2013, ACTA THERIOL, V58, P109, DOI 10.1007/s13364-013-0131-3
   Brooks JD, 2017, FOREST ECOL MANAG, V400, P19, DOI 10.1016/j.foreco.2017.05.045
   Burns E. E., 2018, SAVE REDWOODS LEAGUE
   CALFIRE-FRAP, 2015, VEGETATION FVEG CALF
   California Native Plant Society (CNPS), 2023, SEQUOIA SEMPERVIRENS
   California Natural Diversity Database (CNDDB), 2022, SPECIAL ANIMALS LIST
   Cappelli MP, 2021, GLOB ECOL CONSERV, V28, DOI 10.1016/j.gecco.2021.e01608
   Carroll C, 2021, CONSERV BIOL, V35, P155, DOI 10.1111/cobi.13531
   Cid N, 2017, WATER-SUI, V9, DOI 10.3390/w9010052
   Ciechanowski M, 2007, CAN J ZOOL, V85, P1249, DOI 10.1139/Z07-090
   Conenna I, 2021, GLOBAL ECOL BIOGEOGR, V30, P1014, DOI 10.1111/geb.13278
   Cowan P., 2017, A GIS approach to identifying the distribution and structure of coast redwood across its range
   Daly C, 2008, INT J CLIMATOL, V28, P2031, DOI 10.1002/joc.1688
   Dawson TE, 1998, OECOLOGIA, V117, P476, DOI 10.1007/s004420050683
   Denzinger A, 2013, FRONT PHYSIOL, V4, DOI 10.3389/fphys.2013.00164
   Diffenbaugh NS, 2015, P NATL ACAD SCI USA, V112, P3931, DOI 10.1073/pnas.1422385112
   Dobrowski SZ, 2011, GLOBAL CHANGE BIOL, V17, P1022, DOI 10.1111/j.1365-2486.2010.02263.x
   Dodd LE, 2012, FOREST ECOL MANAG, V267, P262, DOI 10.1016/j.foreco.2011.12.016
   Dormann CF, 2013, ECOGRAPHY, V36, P27, DOI 10.1111/j.1600-0587.2012.07348.x
   Duggan SharonE., 2005, Guide to the California Forest Practice Act and Related Laws
   Elsen PR, 2017, ECOLOGY, V98, P337, DOI 10.1002/ecy.1669
   Erasmy M, 2021, FOREST ECOL MANAG, V497, DOI 10.1016/j.foreco.2021.119509
   Evelyn MJ, 2004, BIOL CONSERV, V115, P463, DOI 10.1016/S0006-3207(03)00163-0
   Fellers GM, 2002, J MAMMAL, V83, P167, DOI 10.1644/1545-1542(2002)083<0167:HUAFBO>2.0.CO;2
   Fire and Resource Assessment Program (Calif.), 1970, CALIFORNIA TREE SEED
   Fischer DT, 2009, J BIOGEOGR, V36, P783, DOI 10.1111/j.1365-2699.2008.02025.x
   Fjelldal MA, 2021, OECOLOGIA, V197, P129, DOI 10.1007/s00442-021-05022-6
   Food and Agriculture Organization (FAO). United Nations Environment Programme (UNEP), 2020, STATE WORLDS FORESTS, DOI [10.4060/ca8642en, DOI 10.4060/CA8642EN]
   Frick WF, 2020, ANN NY ACAD SCI, V1469, P5, DOI 10.1111/nyas.14045
   Gauthier S., 2009, ECOSYSTEM MANAGEMENT
   Gellman ST, 1996, J MAMMAL, V77, P255, DOI 10.2307/1382726
   Grantham T., 2018, North Coast Summary Report, California's Fourth Climate Change Assessment
   GreenInfo Network, 2016, CPAD 2016A
   Hayes JP, 1997, J MAMMAL, V78, P514, DOI 10.2307/1382902
   Hiatt C., 2012, Atmospheric and Climate Sciences, V2, P525, DOI 10.4236/acs.2012.24047
   Johnstone JA, 2010, P NATL ACAD SCI USA, V107, P4533, DOI 10.1073/pnas.0915062107
   Kennedy JP, 2014, ACTA CHIROPTEROL, V16, P53, DOI 10.3161/150811014X683264
   Kremen C, 2018, SCIENCE, V362, DOI 10.1126/science.aau6020
   Law BS, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0191471
   Linton DM, 2018, J ANIM ECOL, V87, P1080, DOI 10.1111/1365-2656.12832
   Loeb S.C., 2015, PLAN N AM BAT MONITO
   Loeb SC, 2013, ECOL EVOL, V3, P103, DOI 10.1002/ece3.440
   Mazurek MJ, 2004, FOREST ECOL MANAG, V193, P321, DOI 10.1016/j.foreco.2004.01.013
   Morris AD, 2010, J WILDLIFE MANAGE, V74, P26, DOI 10.2193/2008-471
   Muñoz-Sáez A, 2021, CONSERV BIOL, V35, P274, DOI 10.1111/cobi.13567
   NAGORSEN D.W., 1993, Bats of British Columbia
   Noss R.F., 2013, REDWOOD FOREST HIST
   Palecki M., 2021, US climate normals 2020: US hourly climate normals (19912020)
   Parsons S., 1996, Bioacoustics, V7, P33
   Patriquin KJ, 2003, WILDLIFE SOC B, V31, P475
   Pye D, 2021, WEATHER, V76, P110, DOI 10.1002/wea.3935
   PYE JD, 1971, NATURE, V229, P572, DOI 10.1038/229572b0
   Raats M. M., 1992, Food Quality and Preference, V3, P89, DOI 10.1016/0950-3293(91)90028-D
   Rojas IM, 2022, CONSERV BIOL, V36, DOI 10.1111/cobi.13834
   Sawaske SR, 2015, ECOHYDROLOGY, V8, P695, DOI 10.1002/eco.1537
   Schmidly D.J., 1991, BATS OF TEXAS
   Schmitz OJ, 2015, NAT AREA J, V35, P190, DOI 10.3375/043.035.0120
   Seidman VM, 2001, J MAMMAL, V82, P738, DOI 10.1644/1545-1542(2001)082<0738:BAAISI>2.0.CO;2
   Sherwin HA, 2013, MAMMAL REV, V43, P171, DOI 10.1111/j.1365-2907.2012.00214.x
   Moreira TBS, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0145710
   Smith TN, 2021, DIVERS DISTRIB, V27, P1152, DOI 10.1111/ddi.13264
   STUDIER EH, 1970, J MAMMAL, V51, P302, DOI 10.2307/1378480
   Szewczak J.M., 2011, Automated acoustic identification of bats
   Thomas AJ, 2013, ACTA CHIROPTEROL, V15, P121, DOI 10.3161/150811013X667920
   Thurman LL, 2022, CONSERV BIOL, V36, DOI 10.1111/cobi.13838
   Torregrosa A, 2016, EARTH SPACE SCI, V3, P46, DOI 10.1002/2015EA000119
   U.S. Geological Survey, 2020, 1 METER DIGITAL ELEV
   Wang TL, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0156720
   Weller Theodore J., 2012, U S Forest Service General Technical Report PSW, V238, P447
   Wright DW, 2021, FOREST ECOL MANAG, V494, DOI 10.1016/j.foreco.2021.119359
   Zielinski WJ, 1999, CONSERV BIOL, V13, P160, DOI 10.1046/j.1523-1739.1999.97424.x
   Zurr AF., 2013, A beginners guide to GLM and GLMM with R: A frequentist and Bayesian perspective for ecologists
NR 84
TC 3
Z9 4
U1 7
U2 14
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0888-8892
EI 1523-1739
J9 CONSERV BIOL
JI Conserv. Biol.
PD AUG
PY 2024
VL 38
IS 4
AR e14246
DI 10.1111/cobi.14246
EA MAR 2024
PG 13
WC Biodiversity Conservation; Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA ZJ2Q8
UT WOS:001180401600001
PM 38445689
OA hybrid
DA 2025-01-10
ER

PT J
AU Schulze, J
   Gehrmann, S
   Somvanshi, A
   Rudolph-Cleff, A
AF Schulze, Joachim
   Gehrmann, Simon
   Somvanshi, Avikal
   Rudolph-Cleff, Annette
TI From District to City Scale: The Potential of Water-Sensitive Urban
   Design (WSUD)
SO WATER
LA English
DT Article
DE water-sensitive urban design; WSUD; integrated water resource management
   system; IWRMS; climate adaptive cities; climate resilience
AB The summer of 2022 was one of the hottest and driest summers that Germany experienced in the 21st century. Water levels in rivers sank dramatically with many dams and reservoirs running dry; as a result, fields could not be irrigated sufficiently, and even power generation and supply were affected. The impact of abnormally high temperatures for extended periods (heatwaves) is not restricted to nature and the economy but is also a considerable public health burden. Experts worldwide agree that these extreme weather events are being driven by climate change and will increase in intensity and frequency in the future. The adverse impact of these extreme weather events multiplies among dense urban environments, e.g., through heat islands. This calls for cities to take action to heat-proof and water-secure their urban developments. Water-Sensitive Urban Design (WSUD) is one such approach to mitigate the aforementioned challenges by leveraging the urban water ecosystem with special attention to the subject of water reclamation, retention, treatment and distribution. This paper introduces and builds upon a prototype of WSUD that centers around an artificial lake as an integrated water resource management system (IWRMS) fed by treated grey water and storm water obtained from two housing blocks flanking the water reservoir. Based on the specifications of this prototype, indicators of site suitability are derived and applied to identify potential locations for replicable projects in the city of Darmstadt. The results confirm the impact WSUD can have: a total of 22 sites with 2527 apartments are found suitable for prototype implementation in Darmstadt. Savings in town water consumption from these 22 sites would add up to 147 million liters. Further benefits include the provision of 24 million liters of irrigation water, storm water retention, adiabatic cooling during heatwave, increased biodiversity and the improvement in livability of the sites and the city.
C1 [Schulze, Joachim; Gehrmann, Simon; Somvanshi, Avikal; Rudolph-Cleff, Annette] Tech Univ Darmstadt, Fac Architecture Urban Design & Dev, D-64287 Darmstadt, Germany.
C3 Technical University of Darmstadt
RP Schulze, J (corresponding author), Tech Univ Darmstadt, Fac Architecture Urban Design & Dev, D-64287 Darmstadt, Germany.
EM schulze@stadt.tu-darmstadt.de; gehrmann@stadt.tu-darmstadt.de;
   avikals@gmail.com; rudolph@stadt.tu-darmstadt.de
OI Somvanshi, Avikal/0009-0008-6731-3876
FU LOEWE initiative (Hesse, Germany)
FX This work has been funded by the LOEWE initiative (Hesse, Germany)
   within the emergenCITY center.
CR Aboelnga HT, 2019, RESOURCES-BASEL, V8, DOI 10.3390/resources8040178
   Amt fur Wirtschaft und Stadtentwicklung (AWS), 2020, Statistik und Stadtforschung: Statistische Berichte 1/2020-Wissenschaftsstadt Darmstadt-Sonderbeitrag: Klimawandel in Darmstadt
   Amt fur Wirtschaft und Stadtentwicklung (AWS), 2022, Statistik und Stadtforschung: Zahlen in Kurze
   Amt fur Wirtschaft und Stadtentwicklung (AWS, Statistik und Stadtforschung, Statistik und Stadtforschung
   Arbeitsgemeinschaft Landtechnik und Landwirtschaftliches Bauwesen in Bayern e.V. (ALB), 2020, Beratungsblatt bef7- Ausgabe, V1
   Australian Capital Territory (ACT), 2014, Water Sensitive Urban Design-Review Report
   Bahr C., 2010, Aktenzeichen, V10, P17
   Baranzelli C., 2019, The Future of Cities: Opportunities, Challenges and the Way Forward
   Bundesministerium fur Umwelt Naturschutz nukleare Sicherheit und Verbraucherschutz (BMUV), 2020, Zweiter Fortschrittsbericht zur Deutschen Anpassungsstrategie an den Klimawandel
   Bundesministerium fur Wirtschaft und Energie (BMWi), 2014, Sanierungsbedarf im Gebaudebestand-Ein Beitrag zur Energieeffizienzstrategie Gebaude
   Cornel P., 2006, Semizentrale Ver- und Entsorgungssysteme fur urbane Raume Chinas-Teilprojekt 1
   Depietri Y, 2013, INT J DISAST RISK RE, V6, P98, DOI 10.1016/j.ijdrr.2013.10.001
   Deutsche Energie-Agentur GmbH (dena), 2016, Der dena Gebaudereport 2016-Statistiken und Analysen zur Energieeffizienz im Gebaudebestand
   DLR Rheinlandpfalz (DLRRLP), Dienstleistungszentrum Landlicher Raum Rheinlandpfalz
   DWD, 2022, About us
   EEA, 2020, URB AD EUR CIT TOWNS, DOI [10.2800/324620, DOI 10.2800/324620]
   European Centre for Medium-Range Weather Forecasts (ECMWF), 2022, ecmwf
   European Enviroment Agency (EEA, Urban Adaptation to Climate Change in Europe 2016-Transforming Cities in a Changing Climate
   Federal Ministry for the Environment Nature Conservation Building and Nuclear Safety (BMUV), 2017, Recommendations for Actio Heat-Action Plans to Protect Human Health
   Feng WJ, 2022, J ENVIRON MANAGE, V301, DOI 10.1016/j.jenvman.2021.113830
   Feuerwehr Wiesbaden (FWW), Abteilung Vorbeugender Brandschutz
   Gross A, 2015, GREYWATER REUSE, P1, DOI 10.1201/b18217
   Hamburg Wasser, 2024, Hamburg Water Cycle
   Hatt BE, 2006, J ENVIRON MANAGE, V79, P102, DOI 10.1016/j.jenvman.2005.06.003
   He CY, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-25026-3
   Hegger M., 2012, Abschlussbericht: UrbanReNet-EnEff:Stadt-Verbundprojekt Netzoptimierung-Teilprojekt: Vernetzte regenerative Energiekonzepte im Siedlungs- und Landschaftsraum
   Hessisches Ministerium fur Umwelt Klimaschutz Landwirtschaft und Verbraucherschutz (HMUKLV), 2017, Integrierter Klimaschutzplan Hessen 2025
   IP BAU, 1994, Alterungsverhalten von Bauteilen und Unterhaltskosten-Grundlagendaten fur den Unterhalt und die Erneuerung von Wohnbauten
   Joint Steering Committee for Water Sensitive Cities (JSCWSC), 2009, Evaluating Options for Water Sensitive Urban Design-A National Guide
   Juan YK, 2016, WATER-SUI, V8, DOI 10.3390/w8110546
   Katzschner L, 2016, Endbericht Klimafunktionskarte Wissenschaftsstadt Darmstadt-Gesamtstadtische Klimaanalyse mit Planungsempfehlungen und Integration der Zukunftigen Baulichen sowie Klimatischen Veranderungen
   Keith L., 2022, Pasreport 600 Planning for Urban Heat Resilience
   Kuller M, 2017, ENVIRON MODELL SOFTW, V96, P265, DOI 10.1016/j.envsoft.2017.07.003
   LINACRE ET, 1977, AGR METEOROL, V18, P409, DOI 10.1016/0002-1571(77)90007-3
   National Oceanic and Atmospheric Administration (NOAA) and National Integrated Drought Information System (NIDIS), 2022, About us
   Nutzmann G., 2016, Elemente einer analytischen Hydrologie-Prozesse-Wechselwirkungen-Modelle
   Radcliffe JC, 2019, APPROACHES TO WATER SENSITIVE URBAN DESIGN: POTENTIAL, DESIGN, ECOLOGICAL HEALTH, URBAN GREENING, ECONOMICS, POLICIES, AND COMMUNITY PERCEPTIONS, P1, DOI 10.1016/B978-0-12-812843-5.00001-0
   Raether E, 2022, Zeit Online
   Regionalverband FrankfurtRheinMain (RFRM), 2021, Metropolregion FrankfurtRheinMain, Region FrankfurtRheinMain
   Sharma AK, 2016, WATER-SUI, V8, DOI 10.3390/w8070272
   Stadt Heilbronn, 2024, Bundesgartenschau-Gelande
   Statistische Bundesamt Destatis, 2023, About us
   Steensen BM, 2022, CLIM DYNAM, V58, P3393, DOI 10.1007/s00382-021-06105-z
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   U.S. Environmental Protection Agency (USEPA), 1999, Manual: Constructed Wetlands Treatment of Municipal Wastewaters
   Umweltbundesamt (UBA), 2021, Klimawirkungs- und Risikoanalyse 2021 fur Deutschland-Kurzfassung
   Umweltbundesamt (UBA), 2022, Die Risiken des Klimawandels fur Deutschland-Ergebnisse der Klimawirkungs- und Risikoanalyse 2021 sowie Schlussfolgerungen der Interministeriellen Arbeitsgruppe Anpassung an den Klimawandel
   United Nations, 2017, Techinical Report
   United Nations, Population Dynamics: The World's Cities in 2018
   United Nations (UN), 2022, United Nations Climate Change
   van de Walle A, 2023, ENVIRON SCI ECOTECH, V16, DOI 10.1016/j.ese.2023.100277
   Varouchakis EA, 2018, WATER POLICY, V20, P175, DOI 10.2166/wp.2017.182
   Werner P., 2013, Integriertes Klimaschutzkonzept fur die Wissenschaftsstadt Darmstadt
   WMO, 2022, BBC News
   Wong THF, 2006, AUSTRALAS J WAT RESO, V10, P213, DOI 10.1080/13241583.2006.11465296
NR 55
TC 2
Z9 2
U1 14
U2 17
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4441
J9 WATER-SUI
JI Water
PD FEB
PY 2024
VL 16
IS 4
AR 582
DI 10.3390/w16040582
PG 37
WC Environmental Sciences; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Water Resources
GA JI4H5
UT WOS:001172518400001
OA gold
DA 2025-01-10
ER

PT J
AU Lezama-Ochoa, N
   Brodie, S
   Welch, H
   Jacox, MG
   Buil, MP
   Fiechter, J
   Cimino, M
   Muhling, B
   Dewar, H
   Becker, EA
   Forney, KA
   Costa, D
   Benson, SR
   Farchadi, N
   Braun, C
   Lewison, R
   Bograd, S
   Hazen, EL
AF Lezama-Ochoa, Nerea
   Brodie, Stephanie
   Welch, Heather
   Jacox, Michael G.
   Buil, Mercedes Pozo
   Fiechter, Jerome
   Cimino, Megan
   Muhling, Barbara
   Dewar, Heidi
   Becker, Elizabeth A.
   Forney, Karin A.
   Costa, Daniel
   Benson, Scott R.
   Farchadi, Nima
   Braun, Camrin
   Lewison, Rebecca
   Bograd, Steven
   Hazen, Elliott L.
TI Divergent responses of highly migratory species to climate change in the
   California Current
SO DIVERSITY AND DISTRIBUTIONS
LA English
DT Article
DE California Current System; centre of gravity; climate change; downscaled
   ocean projections; earth system model; habitat suitability index;
   species distribution model
ID FISHERIES MANAGEMENT; DISTRIBUTION SHIFTS; MARINE; IMPACTS;
   BIODIVERSITY; HABITAT; SHELF
AB Aim: Marine biodiversity faces unprecedented threats from anthropogenic climate change. Ecosystem responses to climate change have exhibited substantial variability in the direction and magnitude of redistribution, posing challenges for developing effective climate-adaptive marine management strategies.Location: The California Current Ecosystem (CCE), USA.
   Methods: We project suitable habitat for 10 highly migratory species in the California Current System using an ensemble of three high-resolution (similar to 10 km) downscaled ocean projections under the Representative Concentration Pathway 8.5 (RCP8.5). Spanning the period from 1980 to 2100, our analysis focuses on assessing the direction and distance of distributional shifts, as well as changes in core habitat area for each species.
   Results: Our findings reveal a divergent response among species to climate impacts. Specifically, four species were projected to undergo significant poleward shifts exceeding 100 km, and gain habitat (similar to 7%-60%) in response to climate change. Conversely, six species were projected to shift towards the coast, resulting in a loss of habitat ranging from 10% to 66% by the end of the century. These divergent responses could typically be characterized by the mode of thermoregulation (i.e. ectotherm vs. endotherm) and species' affiliations with cool and productive upwelled waters that are characteristic of the region. Furthermore, our study highlights an increase in niche overlap between protected species and those targeted by fisheries, which may lead to increased human interaction events under climate change.
   Main Conclusions: By providing valuable species distribution projections, our research contributes to the understanding of climate change effects on marine biodiversity and offers critical insight and support for developing climate-ready management of protected and fished species.
C1 [Lezama-Ochoa, Nerea; Brodie, Stephanie; Welch, Heather; Jacox, Michael G.; Buil, Mercedes Pozo; Fiechter, Jerome; Cimino, Megan; Muhling, Barbara; Becker, Elizabeth A.; Costa, Daniel; Bograd, Steven; Hazen, Elliott L.] Univ Calif Santa Cruz, Inst Marine Sci, 1156 High St, Santa Cruz, CA 95064 USA.
   [Lezama-Ochoa, Nerea; Brodie, Stephanie; Welch, Heather; Jacox, Michael G.; Buil, Mercedes Pozo; Cimino, Megan; Bograd, Steven; Hazen, Elliott L.] Natl Ocean & Atmospher Adm, Environm Res Div, Southwest Fisheries Sci Ctr, Natl Marine Fisheries Serv, Monterey, CA USA.
   [Jacox, Michael G.] NOAA, Phys Sci Lab, Earth Syst Res Labs, Boulder, CO USA.
   [Muhling, Barbara; Dewar, Heidi] Natl Ocean & Atmospher Adm, Natl Marine Fisheries Serv, Fisheries Resources Div, Southwest Fisheries Sci Ctr, La Jolla, CA USA.
   [Becker, Elizabeth A.] ManTech Int Corp Inc, Solana Beach, CA USA.
   [Forney, Karin A.] Natl Ocean & Atmospher Adm, Calif Current Marine Mammal Assessment Program, Natl Marine Fisheries Serv, Southwest Fisheries Sci Ctr, Moss Landing, CA USA.
   [Forney, Karin A.; Benson, Scott R.] San Jose State Univ, Moss Landing Marine Labs, Moss Landing, CA USA.
   [Benson, Scott R.] Natl Ocean & Atmospher Adm, Natl Marine Fisheries Serv, Marine Mammal & Turtle Div, Southwest Fisheries Sci Ctr, Moss Landing, CA USA.
   [Farchadi, Nima; Lewison, Rebecca] San Diego State Univ, San Diego, CA USA.
   [Braun, Camrin] Woods Hole Oceanog Inst, Biol Dept, Woods Hole, MA USA.
   [Brodie, Stephanie] CSIRO Environm, Brisbane, Qld, Australia.
C3 University of California System; University of California Santa Cruz;
   National Oceanic Atmospheric Admin (NOAA) - USA; National Oceanic
   Atmospheric Admin (NOAA) - USA; National Oceanic Atmospheric Admin
   (NOAA) - USA; National Oceanic Atmospheric Admin (NOAA) - USA; Moss
   Landing Marine Laboratories; California State University System; San
   Jose State University; National Oceanic Atmospheric Admin (NOAA) - USA;
   California State University System; San Diego State University; Woods
   Hole Oceanographic Institution; Commonwealth Scientific & Industrial
   Research Organisation (CSIRO)
RP Lezama-Ochoa, N (corresponding author), Univ Calif Santa Cruz, Inst Marine Sci, 1156 High St, Santa Cruz, CA 95064 USA.
EM nlezamao@ucsc.edu
RI Fiechter, Jerome/AAM-7786-2020; Buil, Mercedes/O-3335-2017; Welch,
   Heather/T-3494-2019; Costa, Daniel/KJK-3910-2024; Hazen,
   Elliott/G-4149-2014
OI Welch, Heather/0000-0002-5464-1140; Pozo Buil,
   Mercedes/0000-0003-3638-271X
FU NOAA's Climate and Fisheries Adaptation CAFA Program; NOAA's Southwest
   Fisheries Science Center's Marine Turtle Research Program; NASA Research
   Opportunities in Space and Earth Sciences Program; NOAA's OAR Climate
   Program Office [NA22OAR4310560];  [NA20OAR4310507]
FX We thank all data holders for the contribution with their data to this
   study. We also thank Melissa Cronin for her English correction of the
   first draft. Tracking data were collected as part of the Tagging of
   Pacific Predators (TOPP) program and NOAA's Southwest Fisheries Science
   Center's Marine Turtle Research Program. Funding. This work was
   supported by the NASA Research Opportunities in Space and Earth Sciences
   Program. NLO and SB received funding from NOAA's OAR Climate Program
   Office (Award no. NA22OAR4310560). BM was partially supported by funding
   from NOAA's Climate and Fisheries Adaptation CAFA Program
   (NA20OAR4310507). The results from this study can be viewed and
   interacted with on the Fisheries and Climate Toolkit (FaCeT) dashboard
   ().
CR Abrahms B, 2019, P NATL ACAD SCI USA, V116, P5582, DOI 10.1073/pnas.1819031116
   Albers HJ, 2023, REV ENV ECON POLICY, V17, P111, DOI 10.1086/724179
   Bakun A, 2015, CURR CLIM CHANGE REP, V1, P85, DOI 10.1007/s40641-015-0008-4
   Becker EA, 2020, ECOL EVOL, V10, P5759, DOI 10.1002/ece3.6316
   Becker EA, 2019, DIVERS DISTRIB, V25, P626, DOI 10.1111/ddi.12867
   Benson SR, 2011, ECOSPHERE, V2, DOI 10.1890/ES11-00053.1
   Blair M.E., 2022, Frontiers of Biogeography, V14
   Block BA, 2011, NATURE, V475, P86, DOI 10.1038/nature10082
   Bograd SJ, 2023, ANNU REV MAR SCI, V15, P303, DOI 10.1146/annurev-marine-032122-021945
   Bonebrake TC, 2018, BIOL REV, V93, P284, DOI 10.1111/brv.12344
   Braun CD, 2023, SCI ADV, V9, DOI 10.1126/sciadv.adi2718
   Brodie S, 2022, GLOBAL CHANGE BIOL, V28, P6586, DOI 10.1111/gcb.16371
   Brodie S, 2018, FRONT MAR SCI, V5, DOI 10.3389/fmars.2018.00219
   Buil MP, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.612874
   Burgess MG, 2023, ICES J MAR SCI, V80, P1163, DOI 10.1093/icesjms/fsad045
   Canadas A, 2018, ECOL INDIC, V85, P128, DOI 10.1016/j.ecolind.2017.10.021
   Carroll G, 2019, GLOBAL ECOL BIOGEOGR, V28, P1561, DOI 10.1111/geb.12984
   Champion C, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.622299
   Chasco BE, 2022, MAR COAST FISH, V14, DOI 10.1002/mcf2.10190
   Checkley DM, 2009, PROG OCEANOGR, V83, P49, DOI 10.1016/j.pocean.2009.07.028
   Cheung WWL, 2015, PROG OCEANOGR, V130, P19, DOI 10.1016/j.pocean.2014.09.003
   Cheung WWL, 2009, FISH FISH, V10, P235, DOI 10.1111/j.1467-2979.2008.00315.x
   Conners MG, 2022, FRONT MAR SCI, V9, DOI 10.3389/fmars.2022.897104
   Costa D P., 2021, Ethology and Behavioral Ecology of Otariids and the Odobenid, P21
   Doney SC, 2012, ANNU REV MAR SCI, V4, P11, DOI 10.1146/annurev-marine-041911-111611
   Eguchi T, 2017, FISH OCEANOGR, V26, P17, DOI 10.1111/fog.12181
   Elith J, 2009, ANNU REV ECOL EVOL S, V40, P677, DOI 10.1146/annurev.ecolsys.110308.120159
   Free CM, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0224347
   Grose SO, 2020, FRONT MAR SCI, V7, DOI 10.3389/fmars.2020.00547
   Hazen EL, 2018, SCI ADV, V4, DOI 10.1126/sciadv.aar3001
   Hazen EL, 2013, NAT CLIM CHANGE, V3, P234, DOI 10.1038/NCLIMATE1686
   Hijmans R. J., 2014, GEOSPHERE SPHERICAL
   Hobday AJ, 2018, FRONT MAR SCI, V5, DOI 10.3389/fmars.2018.00137
   Hobday AJ, 2014, REV FISH BIOL FISHER, V24, P415, DOI 10.1007/s11160-013-9326-6
   Holsman KK, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-18300-3
   Jacox MG, 2018, J GEOPHYS RES-OCEANS, V123, P7332, DOI 10.1029/2018JC014187
   Jones MC, 2015, ICES J MAR SCI, V72, P741, DOI 10.1093/icesjms/fsu172
   Kaplan IC, 2012, PROG OCEANOGR, V102, P5, DOI 10.1016/j.pocean.2012.03.009
   Karp MA, 2019, ICES J MAR SCI, V76, P1305, DOI 10.1093/icesjms/fsz048
   Kleisner KM, 2017, PROG OCEANOGR, V153, P24, DOI 10.1016/j.pocean.2017.04.001
   Koehn LE, 2022, PLOS ONE, V17, DOI 10.1371/journal.pone.0272120
   Kot CY, 2023, BIOL CONSERV, V283, DOI 10.1016/j.biocon.2023.110142
   MacLeod Colin D., 2009, Endangered Species Research, V7, P125, DOI 10.3354/esr00197
   Maxwell SM, 2020, SCIENCE, V367, P252, DOI 10.1126/science.aaz9327
   Melbourne-Thomas J, 2022, REV FISH BIOL FISHER, V32, P231, DOI 10.1007/s11160-021-09641-3
   Mills KE, 2013, OCEANOGRAPHY, V26, P191, DOI 10.5670/oceanog.2013.27
   Morley JW, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0196127
   Muhling BA, 2020, FRONT MAR SCI, V7, DOI 10.3389/fmars.2020.00589
   Nasby-Lucas N, 2019, ANIM BIOTELEM, V7, DOI 10.1186/s40317-019-0174-6
   Neveu E, 2016, OCEAN MODEL, V99, P133, DOI 10.1016/j.ocemod.2015.11.012
   Palacios-Abrantes J, 2023, PLOS ONE, V18, DOI 10.1371/journal.pone.0279025
   Pecl GT, 2017, SCIENCE, V355, DOI 10.1126/science.aai9214
   Pecl GT, 2014, CLIMATIC CHANGE, V127, P505, DOI 10.1007/s10584-014-1284-z
   Peer AC, 2014, N AM J FISH MANAGE, V34, P94, DOI 10.1080/02755947.2013.847877
   Perry AL, 2005, SCIENCE, V308, P1912, DOI 10.1126/science.1111322
   Pinsky ML, 2021, POPUL ECOL, V63, P17, DOI 10.1002/1438-390X.12050
   Pinsky ML, 2019, NATURE, V569, P108, DOI 10.1038/s41586-019-1132-4
   Poloczanska ES, 2016, FRONT MAR SCI, V3, DOI 10.3389/fmars.2016.00062
   Poloczanska ES, 2013, NAT CLIM CHANGE, V3, P919, DOI [10.1038/nclimate1958, 10.1038/NCLIMATE1958]
   Polovina JJ, 2011, ICES J MAR SCI, V68, P986, DOI 10.1093/icesjms/fsq198
   Rosenzweig C, 2008, NATURE, V453, P353, DOI 10.1038/nature06937
   Saba VS, 2007, J APPL ECOL, V44, P395, DOI 10.1111/j.1365-2664.2007.01276.x
   Santora JA, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-019-14215-w
   SCHOENER TW, 1968, ECOLOGY, V49, P704, DOI 10.2307/1935534
   Schroeder ID, 2022, ECOL INDIC, V144, DOI 10.1016/j.ecolind.2022.109520
   Sirovic A, 2015, ENDANGER SPECIES RES, V28, P61, DOI 10.3354/esr00676
   Smith JA, 2023, PROG OCEANOGR, V211, DOI 10.1016/j.pocean.2023.102973
   Smith JA, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.630607
   Smith JA, 2021, FISH OCEANOGR, V30, P437, DOI 10.1111/fog.12529
   Veneziani M, 2009, J GEOPHYS RES-OCEANS, V114, DOI 10.1029/2008JC004774
   Warren DL, 2008, EVOLUTION, V62, P2868, DOI 10.1111/j.1558-5646.2008.00482.x
   Warren DL, 2021, ECOGRAPHY, V44, P504, DOI 10.1111/ecog.05485
   Welch H, 2020, CONSERV BIOL, V34, P589, DOI 10.1111/cobi.13417
NR 73
TC 7
Z9 7
U1 7
U2 15
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 FEB
PY 2024
VL 30
IS 2
DI 10.1111/ddi.13800
EA DEC 2023
PG 14
WC Biodiversity Conservation; Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA EO5T0
UT WOS:001117604100001
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Boogaard, F
   Rooze, D
   Stuurman, R
AF Boogaard, Floris
   Rooze, Daan
   Stuurman, Roelof
TI The Long-Term Hydraulic Efficiency of Green Infrastructure under Sea
   Level: Performance of Raingardens, Swales and Permeable Pavement in New
   Orleans
SO LAND
LA English
DT Article
DE hydraulic performance; green Infrastructure; raingarden; swales;
   permeable pavement
ID RUNOFF; WATER
AB Greater New Orleans is surrounded by wetlands, the Mississippi River and two lakes. Excess rain can only be drained off with pumping systems or by evaporation due to the bowl-like shape of a large part of the city. As part of the solution to make New Orleans climate adaptive, green infrastructure has been implemented that enable rainfall infiltration and evapotranspiration of stored water after Hurricane Katrina in 2005. The long-term efficiency of infiltrating water under sea level with low permeable soils and high groundwater tables is often questioned. Therefore, research was conducted with the full-scale testing method measuring the infiltration capacity of 15 raingardens and 6 permeable pavements installed in the period 2011-2022. The results show a high variation of empty times for raingardens and swales: 0.7 to 54 m/d. The infiltration capacity decreased after saturation (ca 30% decrease in empty time after refilling storage volume) but all the tested green infrastructure met the guideline to be drained within 48 h. This is in contrast with the permeable pavement: only two of the six tested locations had an infiltration capacity higher than the guideline 10 inch/h (254 mm/h). The results are discussed with multiple stakeholders that participated in ClimateCafe New Orleans. Whether the results are considered unacceptable depends on a number of factors, including its intended purpose, site specific characteristics and most of all stakeholder expectations and perceptions. The designing, planning and scheduling of maintenance requirements for green infrastructure by stormwater managers can be carried out with more confidence so that green infrastructure will continue to perform satisfactorily over the intended design life and can mitigate the effects of heavy rainfall and droughts in the future.
C1 [Boogaard, Floris; Rooze, Daan; Stuurman, Roelof] Deltares, Daltonlaan 600, NL-3584 BK Utrecht, Netherlands.
   [Boogaard, Floris] Hanze Univ Appl Sci, Res Ctr Built Environm NoorderRuimte, NL-9747 AS Groningen, Netherlands.
C3 Deltares
RP Boogaard, F (corresponding author), Deltares, Daltonlaan 600, NL-3584 BK Utrecht, Netherlands.; Boogaard, F (corresponding author), Hanze Univ Appl Sci, Res Ctr Built Environm NoorderRuimte, NL-9747 AS Groningen, Netherlands.
EM floris.boogaard@deltares.nl
RI Boogaard, Floris/V-6308-2019
OI Boogaard, Floris/0000-0002-1434-4838
FU City of New Orleans (National Disaster and Resilience Competition); SIA
   [SVB/RAAK.PUB07.015]
FX This research was funded by City of New Orleans (supported with a grant
   of the National Disaster and Resilience Competition) and by SIA, grant
   number SVB/RAAK.PUB07.015 project Groenblauwe oplossingen, kansen en
   risico's' (Green Infrastructure: changes and challenges).
CR Adams V, 2009, AM ETHNOL, V36, P615, DOI 10.1111/j.1548-1425.2009.01199.x
   [Anonymous], 2009, Standard Test Method for Infiltration Rate of in Place Pervious Concrete
   [Anonymous], 2014, GREEN INFR
   Asleson BC, 2009, J AM WATER RESOUR AS, V45, P1019, DOI 10.1111/j.1752-1688.2009.00344.x
   Ballard B.W., 2017, THE SUDS MANUAL
   Barrett ME, 2008, J IRRIG DRAIN ENG, V134, P556, DOI 10.1061/(ASCE)0733-9437(2008)134:5(556)
   Boogaard F, 2019, WATER-SUI, V11, DOI 10.3390/w11020320
   Boogaard FC, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12093694
   Boogaard FC, 2022, WATER-SUI, V14, DOI 10.3390/w14060840
   Burkett V.R., 2003, Proc. USGS aquifer mechanics and subsidence interest group conference, P63
   Carter L.M., 2014, CLIMATE CHANGE IMPAC, P396, DOI [DOI 10.7930/J0NP22CB, 10.7930/J0N-P22CB, DOI 10.7930/J0N-P22CB]
   Chen LM, 2020, SCI TOTAL ENVIRON, V749, DOI 10.1016/j.scitotenv.2020.141352
   Chen LM, 2019, WATER-SUI, V11, DOI 10.3390/w11030444
   Chini CM, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9010105
   Chopra M, 2010, J HYDROL ENG, V15, P426, DOI 10.1061/(ASCE)HE.1943-5584.0000117
   Coleri E, 2013, J ENVIRON MANAGE, V129, P164, DOI 10.1016/j.jenvman.2013.07.005
   Davis AP, 2012, J HYDROL ENG, V17, P604, DOI 10.1061/(ASCE)HE.1943-5584.0000467
   Deletic A, 2001, J HYDROL, V248, P168, DOI 10.1016/S0022-1694(01)00403-6
   Fletcher TD, 2013, ADV WATER RESOUR, V51, P261, DOI 10.1016/j.advwatres.2012.09.001
   Fletcher TD, 2015, URBAN WATER J, V12, P525, DOI 10.1080/1573062X.2014.916314
   Gilbert JK, 2006, WATER RES, V40, P826, DOI 10.1016/j.watres.2005.12.006
   Koritz Amy., 2009, CIVIC ENGAGEMENT WAK
   Kumar P, 2021, EARTH-SCI REV, V217, DOI 10.1016/j.earscirev.2021.103603
   Langeveld JG, 2012, WATER RES, V46, P6868, DOI 10.1016/j.watres.2012.06.001
   Li H, 2013, J ENVIRON MANAGE, V118, P144, DOI 10.1016/j.jenvman.2013.01.016
   Lin ZZ, 2020, POL J ENVIRON STUD, V29, P3225, DOI 10.15244/pjoes/114262
   Lucke T., 2014, Urban, Planning and Transport Research: An Open Access Journal, V2, P22, DOI [10.1080/21650020.2014.893200, DOI 10.1080/21650020.2014.893200]
   Lucke T, 2011, BUILD RES INF, V39, P603, DOI 10.1080/09613218.2011.602182
   Mallum F, 2022, SHIMA, V16, P61, DOI 10.21463/shima.146
   Nguyen NPT, 2022, WATER-SUI, V14, DOI 10.3390/w14142143
   NOAA-NCEI, LAK AIRP
   Nougues L., 2022, H20 WATER MATTERS, P36
   Pezzaniti D, 2009, P I CIVIL ENG-WAT M, V162, P211, DOI 10.1680/wama.2009.00034
   Restemeyer B, 2021, LAND-BASEL, V10, DOI 10.3390/land10010005
   Rodak CM, 2020, WATER ENVIRON RES, V92, P1552, DOI 10.1002/wer.1403
   Rushton BT, 2001, J WATER RES PL-ASCE, V127, P172, DOI 10.1061/(ASCE)0733-9496(2001)127:3(172)
   VanEssen, US
   Veldkamp TIE, 2022, WATER-SUI, V14, DOI 10.3390/w14132080
   Vollaers V, 2021, BLUE-GREEN SYST, V3, P31, DOI 10.2166/bgs.2021.002
   Waggonner D., 2014, Built Environment, V40, P281, DOI DOI 10.2148/BENV.40.2.281
   Wang JS, 2022, WATER RES, V221, DOI 10.1016/j.watres.2022.118755
   Winston RJ, 2016, J ENVIRON MANAGE, V169, P132, DOI 10.1016/j.jenvman.2015.12.026
NR 42
TC 5
Z9 5
U1 2
U2 23
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-445X
J9 LAND-BASEL
JI Land
PD JAN
PY 2023
VL 12
IS 1
AR 171
DI 10.3390/land12010171
PG 14
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA 8C5KM
UT WOS:000917647100001
OA gold
DA 2025-01-10
ER

PT J
AU Banzhaf, E
   Bulley, HN
   Inkoom, JN
   Elze, S
AF Banzhaf, Ellen
   Bulley, Henry N.
   Inkoom, Justice Nana
   Elze, Sebastian
TI Mapping Open Data and Big Data to Address Climate Resilience of Urban
   Informal Settlements in Sub-Saharan Africa
SO CLIMATE
LA English
DT Article
DE EO data; big data; land cover; urban land use; environmental pressures;
   demographic information; temporal scale; spatial scale; informal
   settlements; climate resilience; Sub-Saharan Africa
AB This perspective paper highlights the potentials, limitations, and combinations of openly available Earth observation (EO) data and big data in the context of environmental research in urban areas. The aim is to build the resilience of informal settlements to climate change impacts. In particular, it highlights the types, categories, spatial and temporal scales of publicly available big data. The benefits of publicly available big data become clear when looking at issues such as the development and quality of life in informal settlements within and around major African cities. Sub-Saharan African (SSA) cities are among the fastest growing urban areas in the world. However, they lack spatial information to guide urban planning towards climate-adapted cities and fair living conditions for disadvantaged residents who mostly reside in informal settlements. Therefore, this study collected key information on freely available data such as data on land cover, land use, and environmental hazards and pressures, demographic and socio-economic indicators for urban areas. They serve as a vital resource for success of many other related local studies, such as the transdisciplinary research project "DREAMS-Developing REsilient African cities and their urban environMent facing the provision of essential urban SDGs". In the era of exponential growth of big data analytics, especially geospatial data, their utility in SSA is hampered by the disparate nature of these datasets due to the lack of a comprehensive overview of where and how to access them. This paper aims to provide transparency in this regard as well as a resource to access such datasets. Although the limitations of such big data are also discussed, their usefulness in assessing environmental hazards and human exposure, especially to climate change impacts, are emphasised.
C1 [Banzhaf, Ellen; Elze, Sebastian] UFZ Helmholtz Ctr Environm Res, Dept Urban & Environm Sociol, Permoser Str 15, D-04318 Leipzig, Germany.
   [Bulley, Henry N.] CUNY, Borough Manhattan Community Coll, Dept Social Sci Human Serv & Criminal Justice, New York, NY 10007 USA.
   [Inkoom, Justice Nana] Martin Luther Univ Halle Wittenberg, Inst Geosci & Geog, Dept Sustainable Landscape Dev, Von Seckendorff Pl 4, D-06120 Halle, Saale, Germany.
C3 Helmholtz Association; Helmholtz Center for Environmental Research
   (UFZ); City University of New York (CUNY) System; Martin Luther
   University Halle Wittenberg
RP Banzhaf, E (corresponding author), UFZ Helmholtz Ctr Environm Res, Dept Urban & Environm Sociol, Permoser Str 15, D-04318 Leipzig, Germany.
EM ellen.banzhaf@ufz.de
OI Banzhaf, Ellen/0000-0002-4740-1202; Elze, Sebastian/0000-0003-2677-0153
FU Belmont Forum;  [FU 1000/4-1];  [RA-312/21]
FX This research was funded by the Belmont Forum under grant number FU
   1000/4-1 Belmont Forum; RA-312/21.
CR Abunyewah M, 2018, PROCEDIA ENGINEER, V212, P238, DOI 10.1016/j.proeng.2018.01.031
   Acharjya DP, 2016, INT J ADV COMPUT SC, V7, P511
   [Anonymous], 2022, The Revision of World Population Prospects
   BMI, 2021, OP DAT STRAT BUND
   Committee on Scientific Accomplishments of Earth Observations from Space National Research Council, 2008, EARTH OBS SPAC 1 50, P6, DOI [10.17226/11991, DOI 10.17226/11991]
   Dhar TK, 2016, J URBAN DES, V21, P234, DOI 10.1080/13574809.2015.1133224
   European Commission, EUR STRAT DAT 2020
   Finn BM, 2023, URBAN STUD, V60, P405, DOI 10.1177/00420980221098946
   Georganos S., 2021, THESIS
   Ghamisi P, 2019, IEEE GEOSC REM SEN M, V7, P6, DOI 10.1109/MGRS.2018.2890023
   Hirschmugl M, 2017, CURR FOR REP, V3, P32, DOI 10.1007/s40725-017-0047-2
   Huang X, 2019, ISPRS J PHOTOGRAMM, V152, P119, DOI 10.1016/j.isprsjprs.2019.04.010
   Inkoom JN, 2018, J ENVIRON MANAGE, V209, P393, DOI 10.1016/j.jenvman.2017.12.027
   Joubert A., 2019, P 18 C E BUSINESS E, P101
   Kleemann J, 2017, LANDSCAPE URBAN PLAN, V165, P280, DOI 10.1016/j.landurbplan.2017.02.004
   Morgner C, 2020, URBAN FORUM, V31, P489, DOI 10.1007/s12132-020-09389-2
   Ono H, 2020, JPN ARCHIT REV, V3, P384, DOI 10.1002/2475-8876.12161
   Palacios-Lopez D, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11216056
   Pesaresi M., 2016, JRC103150
   Pritchard R, 2022, ENVIRON DEV, V42, DOI 10.1016/j.envdev.2021.100695
   Schmidli J, 2006, INT J CLIMATOL, V26, P679, DOI 10.1002/joc.1287
   Simiyu S, 2019, URBAN FORUM, V30, P223, DOI 10.1007/s12132-018-9346-3
   UNDESA, 2018, REV WORLD URB PROSP
   UNstats, 2019, Sustainable development goal 11-sustainable cities and communities
   Wang XT, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11020163
   World Wide Web Foundation, 2022, OPEN DATA BAROMETER
   Xu ZF, 2019, SCI CHINA EARTH SCI, V62, P365, DOI 10.1007/s11430-018-9261-5
   Yang J, 2021, EARTH SYST SCI DATA, V13, P3907, DOI 10.5194/essd-13-3907-2021
   Young JC, 2021, GEOJOURNAL, V86, P2227, DOI 10.1007/s10708-020-10184-6
   Zhu XL, 2018, REMOTE SENS-BASEL, V10, DOI 10.3390/rs10040527
NR 30
TC 0
Z9 0
U1 0
U2 3
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2225-1154
J9 CLIMATE
JI Climate
PD DEC
PY 2022
VL 10
IS 12
AR 186
DI 10.3390/cli10120186
PG 16
WC Meteorology & Atmospheric Sciences
WE Emerging Sources Citation Index (ESCI)
SC Meteorology & Atmospheric Sciences
GA 7D5DD
UT WOS:000900510100001
OA gold
DA 2025-01-10
ER

PT J
AU Quinn, C
   Quintana, A
   Blaine, T
   Chandra, A
   Epanchin, P
   Pitter, S
   Thiaw, W
   Shek, A
   Blate, GM
   Zermoglio, F
   Pleuss, E
   Teka, H
   Gudo, ES
   Dissanayake, G
   Colborn, J
   Trtanj, J
   Balbus, J
AF Quinn, Colin
   Quintana, Amanda
   Blaine, Tegan
   Chandra, Amit
   Epanchin, Pete
   Pitter, Shanna
   Thiaw, Wassila
   Shek, Amalhin
   Blate, Geoffrey M.
   Zermoglio, Fernanda
   Pleuss, Elizabeth
   Teka, Hiwot
   Gudo, Eduardo Samo
   Dissanayake, Gunawardena
   Colborn, James
   Trtanj, Juli
   Balbus, John
TI Linking science and action to improve public health capacity for climate
   preparedness in lower- and middle-income countries
SO CLIMATE POLICY
LA English
DT Article
DE Climate adaptation; capacity building; public health; lower- and
   middle-income countries; programme design
AB By 2030, the direct adaptation costs to the health sector due to climate change are expected to cost between USD$2 to USD$4 billion a year. People in many low- and middle-income countries already suffer from several health challenges, such as malnutrition and a high occurrence of infectious diseases, challenges that will be intensified by climate change and variability. Furthermore, these countries often have health systems with a limited capacity to adapt to and prepare for future climate scenarios. As a result, many of the poorest and most vulnerable countries are likely to bear the brunt of health impacts resulting from climate change and variability. The Intergovernmental Panel on Climate Change identified health as the sector with the greatest potential to reduce the impacts of climate change in many lower- and middle-income countries if adaptation measures are taken. In this paper, we use case studies from a project funded by the United States Agency for International Development (USAID) to examine how to design programmes to reduce climate risks in the health sector. The USAID project called the Adaptation, Thought Leadership, and Assessment (ATLAS) Project and it assisted public health institutions in lower- and middle-income countries. Four specific cases are presented: in Mozambique, supporting the National Institute of Health of to launch a climate and health research observatory; in Ethiopia, working with the Ministry of Health to include climate and weather information into malaria early warning systems; in sub-Saharan Africa, improving our understanding of the relationship between temperature and malaria to inform malaria elimination interventions; and working across all project countries (globally) to manage extreme heat to reduce impacts on human health and well-being. We analyze these four ATLAS Project case examples to identify lessons and opportunities for future decisions and investment in climate and health care system management and capacity building programmes.
C1 [Quinn, Colin; Chandra, Amit; Epanchin, Pete; Shek, Amalhin; Blate, Geoffrey M.; Zermoglio, Fernanda; Pleuss, Elizabeth] US Agcy Int Dev, 1300 Penn Ave NW, Washington, DC 20004 USA.
   [Quintana, Amanda] US Global Change Res Program, Washington, DC USA.
   [Blaine, Tegan] Blue Cairn Grp, Washington, DC USA.
   [Pitter, Shanna; Thiaw, Wassila; Trtanj, Juli] NOAA, Silver Spring, MD USA.
   [Teka, Hiwot] US Agcy Int Dev, Presidents Malaria Initiat, Addis Ababa, Ethiopia.
   [Gudo, Eduardo Samo] Mozamb Natl Inst Hlth, Maputo, Mozambique.
   [Dissanayake, Gunawardena] US Agcy Int Dev, Presidents Malaria Initiat, Yangon, Myanmar.
   [Colborn, James] Clinton Hlth Access Initiat, Boston, MA USA.
   [Balbus, John] NIEHS, NIH, Bethesda, MD USA.
C3 United States Agency for International Development (USAID); National
   Oceanic Atmospheric Admin (NOAA) - USA; United States Agency for
   International Development (USAID); United States Agency for
   International Development (USAID); National Institutes of Health (NIH) -
   USA; NIH National Institute of Environmental Health Sciences (NIEHS)
RP Quinn, C (corresponding author), US Agcy Int Dev, 1300 Penn Ave NW, Washington, DC 20004 USA.
EM cquinn@usaid.gov
OI Quintana, Amanda V./0000-0001-8750-2908; Chandra,
   Amit/0000-0003-3815-3267
FU United States Agency for International Development (USAID)
FX The authors thank the Interagency Cross Cutting Group on Climate Change
   and Human Health (CCHHG), under the United States Global Change Research
   Programme (USGCRP) for their contribution to help frame the ideas in
   this article. The authors thank the researchers, staff, and consultants
   of the United States Agency for International Development (USAID) funded
   Adaptation, Thought Leadership and Assessment (ATLAS) Project for their
   extensive research and capacity building efforts under the project, and
   general dedication to strengthening the climate change adaptation for
   the international development field. The Authors would also like to
   thank public health professionals in the Mozambique Ministry of Health
   and Ethiopia Ministry of Health for leading the integration of climate
   information into public health decision making.
CR Abel GJ, 2019, GLOBAL ENVIRON CHANG, V54, P239, DOI 10.1016/j.gloenvcha.2018.12.003
   [Anonymous], 2018, CLIMATE CHANGE HLTH
   [Anonymous], 2007, HUMAN DEV REPORT 200
   Costello A., 2009, Lancet, V373, P1693, DOI DOI 10.1016/S0140-6736(09)60935-1
   Edenhofer O., 2014, Climate Change 2014: Mitigation of Climate Change
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Frumkin H, 2008, AM J PUBLIC HEALTH, V98, P435, DOI 10.2105/AJPH.2007.119362
   Galler S, 2021, Infrastructure. United states agency for international development
   Hess JJ, 2012, ENVIRON HEALTH PERSP, V120, P171, DOI 10.1289/ehp.1103515
   Horn LM, 2018, INT J ENV RES PUB HE, V15, DOI 10.3390/ijerph15040709
   Moda HM, 2019, INT J ENV RES PUB HE, V16, DOI 10.3390/ijerph16183458
   Rigaud KantaKumari., 2018, GROUNDSWELL PREPARIN
   Singh R., 2019, Red Cross Red Crescent Climate Centre
   United States Agency for International Development (USAID), 2020, INFL CLIM MAL INC MA
   United States Agency for International Development (USAID), 2020, BRIEF NOT SHIFT BURD
   United States Agency for International Development (USAID), 2019, HEAT WAV HUM HLTH EM
   United States Agency for International Development (USAID), 2020, 5 YEARS PROGR CLIM R
   United States Agency for International Development (USAID), PATHW PEAC ADDR CONF
   United States Agency for International Development (USAID), 2020, SHIFT BURD MAL RISKS
   Watts N, 2019, LANCET, V394, P1836, DOI 10.1016/S0140-6736(19)32596-6
   WHO, 2015, Operational framework for building climate resilient health systems
NR 21
TC 4
Z9 4
U1 3
U2 20
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 NOV 26
PY 2022
VL 22
IS 9-10
BP 1146
EP 1154
DI 10.1080/14693062.2022.2098228
EA JUL 2022
PG 9
WC Environmental Studies; Public Administration
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Public Administration
GA 6C2II
UT WOS:000837646900001
DA 2025-01-10
ER

PT C
AU Kataoka, I
   Matsuoka, M
   Beppu, K
   Ohtani, M
AF Kataoka, I.
   Matsuoka, M.
   Beppu, K.
   Ohtani, M.
BE Atak, A
TI High temperature tolerance of Sanuki Kiwicco® kiwifruit interspecific
   hybrid <i>Actinidia rufa</i> x <i>A</i>. <i>chinensis</i> var.
   <i>chinensis</i>
SO X INTERNATIONAL SYMPOSIUM ON KIWIFRUIT
SE Acta Horticulturae
LA English
DT Proceedings Paper
CT 10th International Symposium on Kiwifruit
CY SEP 27-30, 2021
CL Yalova, TURKEY
SP Int Soc Hort Sci, Division Vine and Berry Fruits, Int Soc Hort Sci, Division Temperate Tree Fruits, Int Soc Hort Sci, Working Group Kiwifruit Culture and Management, Guney Agripark, Zespri, Jingold S p a, Marmara Tarim, Plant & Food Res, Unitec S p A, AG Tarim, Aydogan Fidancilik, Gumus Tarim, Cengiz Fidancilik, Fruit Control Equipments, Miko Japan, Vitroplant
DE climate adaptability; breeding; cuticular layer; global warming; heat
   stress; temperature damage; photosynthesis
ID PHOTOSYNTHESIS
AB Temperature rise of these years due to the global climate change adversely affects kiwifruit production in Japan. Excessively high temperature during summer often causes physiological disorder. Cultivars of the Sanuki Kiwicco (R) series are the interspecific hybrid between Actinidia rufa, indigenous to warm regions in Japan and diploid A. chinensis var. chinensis, the kiwifruit. Their market popularity is increasing because of the high productivity and excellent eating quality. In this research, high temperature tolerance of the hybrid cultivars was evaluated in comparison with their parents. In the field, A. chinensis var. chinensis kiwifruit suffered substantial leaf damage in 2016 and 2018 hot summers, while the leaves of A. rufa were not damaged at all and the interspecific cultivars were slightly affected. By high temperature treatment during daytime ranging from 35 to 45 degrees C for 7 days in the framework covered with plastic film, severe leaf damage and inhibition of photosynthesis occurred in the potted plants of A. chinensis var. chinensis (FCM1). In contrast, leaf damage was much less in A. rufa (Fuchu) and interspecific hybrids 'Kagawa UP-Ki4' and 'Kagawa UP-Ki 5'. The photosynthetic activity remained until the end of the treatment, while the photosynthetic rate considerably dropped. Six days after the treatment was completed, photosynthetic rate mostly recovered in A. rufa and interspecific hybrids but not in A. chinensis var. chinensis. Cuticular transpiration of adult leaf was relatively larger in A. chinensis var. chinensis than in A. rufa and interspecific hybrids. On the adaxial sides of adult leaves, a cuticular layer developed in A. chinensis, A. rufa and the interspecific hybrids, while on abaxial side, it was observed only in A. rufa and interspecific hybrids. These results showed that the high temperature tolerance of A. rufa was passed to the progeny and suggested that A. rufa is valuable material for breeding kiwifruit cultivars adapted to warmer climatic conditions.
C1 [Kataoka, I.; Matsuoka, M.; Beppu, K.] Kagawa Univ, Fac Agr, Miki, Kagawa 7610795, Japan.
   [Ohtani, M.] Kagawa Prefectural Agr Res Stn, Fuchu Fruit Tree Res Inst, Sakaide, Kagawa 7620024, Japan.
C3 Kagawa University
RP Kataoka, I (corresponding author), Kagawa Univ, Fac Agr, Miki, Kagawa 7610795, Japan.
EM kataoka.ikuo@kagawa-u.ac.jp
FU JSPS KAKENHI [JP26450036]
FX This study was supported partly by JSPS KAKENHI Grant Number JP26450036.
CR Bardi L, 2020, FRONT AGRON, V2, DOI 10.3389/fagro.2020.580659
   Chaudhary S, 2020, FRONT PLANT SCI, V11, DOI 10.3389/fpls.2020.587264
   Govindaraj M., 2018, Breeding Cultivars for Heat Stress Tolerance in Staple Food Crops (IntechOpen), DOI [10.5772/intechopen.76480, DOI 10.5772/INTECHOPEN.76480]
   GREER DH, 1988, PLANTA, V174, P152, DOI 10.1007/BF00394766
   Kataoka I, 2014, ACTA HORTIC, V1059, P85
   Kataoka I, 2011, ACTA HORTIC, P77, DOI 10.17660/ActaHortic.2011.913.7
   Kisaki G, 2019, J PLANT PATHOL, V101, P1211, DOI 10.1007/s42161-019-00349-9
   LAING WA, 1985, NEW ZEAL J AGR RES, V28, P117, DOI 10.1080/00288233.1985.10427004
   Ohba H., 2006, Flora of Japan, VIIa, P1
   Phivnil K, 2004, J JPN SOC HORTIC SCI, V73, P244, DOI 10.2503/jjshs.73.244
   Schuster AC, 2016, AOB PLANTS, V8, DOI 10.1093/aobpla/plw027
   Suezawa K, 2018, ACTA HORTIC, V1218, P413, DOI 10.17660/ActaHortic.2018.1218.57
   Yamashita T., 2021, Bulletin Kagawa Agric. Exp. Station, V72, P11
   Yano T, 2011, ACTA HORTIC, P517, DOI 10.17660/ActaHortic.2011.913.69
   Yoshikawa K., 1991, J. Japanese Soc. Revegetation Technology, V17, P203, DOI [10.7211/jjsrt.17.203, DOI 10.7211/JJSRT.17.203]
NR 15
TC 2
Z9 2
U1 1
U2 1
PU INT SOC HORTICULTURAL SCIENCE
PI LEUVEN 1
PA PO BOX 500, 3001 LEUVEN 1, BELGIUM
SN 0567-7572
EI 2406-6168
BN 978-94-62613-31-7
J9 ACTA HORTIC
PY 2022
VL 1332
BP 23
EP 29
DI 10.17660/ActaHortic.2022.1332.4
PG 7
WC Agricultural Engineering; Agriculture, Multidisciplinary; Horticulture
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Agriculture
GA BV8AD
UT WOS:001074589900005
DA 2025-01-10
ER

PT J
AU Konorov, EA
   Yurchenko, V
   Patraman, I
   Lukashev, A
   Oyun, N
AF Konorov, Evgenii A.
   Yurchenko, Vyacheslav
   Patraman, Ivan
   Lukashev, Alexander
   Oyun, Nadezhda
TI The effects of genetic drift and genomic selection on differentiation
   and local adaptation of the introduced populations of <i>Aedes
   albopictus</i> in southern Russia
SO PEERJ
LA English
DT Article
DE Pathogen vector; Population genomics; Cold adaptation; Invasive species;
   Asian tiger mosquito
ID ASIAN TIGER MOSQUITO; COLD-ACCLIMATION; INVASIVE MOSQUITO; VECTOR
   STATUS; UP-REGULATION; GLOBAL RISK; FLESH FLY; DIAPAUSE; AEGYPTI;
   HARDINESS
AB Background: Asian tiger mosquito Aedes albopictus is an arbovirus vector that has spread from its native habitation areal in Southeast Asia throughout North and South Americas, Europe, and Africa. Ae. albopictus was first detected in the Southern Federal District of the Russian Federation in the subtropical town of Sochi in 2011. In subsequent years, this species has been described in the continental areas with more severe climate and lower winter temperatures.
   Methods: Genomic analysis of pooled Ae. albopictus samples collected in the mosquito populations in the coastal and continental regions of the Krasnodar Krai was conducted to look for the genetic changes associated with the spread and potential cold adaptation in Ae. albopictus.
   Results: The results of the phylogenetic analysis based on mitochondrial genomes corresponded well with the hypothesis that Ae. albopictus haplotype A1a2a1 was introduced into the region from a single source. Population analysis revealed the role of dispersal and genetic drift in the local adaptation of the Asian tiger mosquito. The absence of shared haplotypes between the samples and high fixation indices suggest that gene flow between samples was heavily restricted. Mitochondrial and genomic differentiation together with different distances between dispersal routes, natural and anthropogenic barriers and local effective population size reduction could lead to difficulties in local climatic adaptations due to reduced selection effectiveness. We have found genomic regions with selective sweep patterns which can be considered as having been affected by recent selection events. The genes located in these regions participate in neural protection, lipid conservation, and cuticle formation during diapause. These processes were shown to be important for cold adaptation in the previous transcriptomic and proteomic studies. However, the population history and relatively low coverage obtained in the present article could have negatively affect sweep detection.
C1 [Konorov, Evgenii A.] Russian Acad Sci, Vavilov Inst Gen Genet, Moscow, Russia.
   [Konorov, Evgenii A.] Russian Acad Sci, VM Gorbatov Fed Res Ctr Food Syst, Moscow, Russia.
   [Yurchenko, Vyacheslav; Patraman, Ivan; Lukashev, Alexander; Oyun, Nadezhda] Sechenov Univ, Martsinovsky Inst Med Parasitol Trop & Vector Bor, Moscow, Russia.
   [Yurchenko, Vyacheslav] Univ Ostrava, Life Sci Res Ctr, Ostrava, Czech Republic.
   [Patraman, Ivan; Oyun, Nadezhda] Minist Hlth Russian Federat, Fed State Budgetary Inst, Natl Res Ctr Epidemiol & Microbiol, Moscow, Russia.
   [Oyun, Nadezhda] Lomonosov Moscow State Univ, Biol Fac, Dept Entomol, Moscow, Russia.
C3 Russian Academy of Sciences; Vavilov Institute of General Genetics;
   Russian Academy of Sciences; Sechenov First Moscow State Medical
   University; University of Ostrava; Ministry of Health of the Russian
   Federation; Lomonosov Moscow State University
RP Konorov, EA (corresponding author), Russian Acad Sci, Vavilov Inst Gen Genet, Moscow, Russia.; Konorov, EA (corresponding author), Russian Acad Sci, VM Gorbatov Fed Res Ctr Food Syst, Moscow, Russia.
EM casqy@yandex.ru
RI Konorov, Evgenii/AAC-5893-2021; Lukashev, Alexander/G-2777-2013; Oyun,
   Nadezhda/AAW-4690-2021; Yurchenko, Vyacheslav/E-4532-2013
OI Yurchenko, Vyacheslav/0000-0003-4765-3263; Konorov,
   Evgenii/0000-0001-8748-9117; Oyun, Nadezhda/0000-0001-9279-4386
FU Russian Science Foundation (RSF) [19-75-00091]; European Regional Funds
   [CZ.02.1.01/16_019/0000759]; Russian Science Foundation [19-75-00091]
   Funding Source: Russian Science Foundation
FX Collection of mosquitoes, sample preparation, and bioinformatics were
   supported by the Russian Science Foundation (RSF) (project No.
   19-75-00091, "Genetic analysis of vector capacity and cold adaptation in
   Asian tiger mosquito Aedes albopictus from lab-contained and introduced
   natural populations from Russian Federation"). Sequencing of mosquito
   genomes was provided by the European Regional Funds (project No.
   CZ.02.1.01/16_019/0000759). The funders had no role in study design,
   data collection and analysis, decision to publish, or preparation of the
   manuscript.
CR Akiner MM, 2016, PLOS NEGLECT TROP D, V10, DOI 10.1371/journal.pntd.0004664
   Asgharian H, 2015, P ROY SOC B-BIOL SCI, V282, DOI 10.1098/rspb.2015.0728
   Battaglia V, 2016, FRONT GENET, V7, DOI 10.3389/fgene.2016.00208
   Benedict MQ, 2007, VECTOR-BORNE ZOONOT, V7, P76, DOI 10.1089/vbz.2006.0562
   Benitez EM, 2021, ACTA TROP, V216, DOI 10.1016/j.actatropica.2020.105744
   Bennett KL, 2021, EVOL APPL, V14, P1301, DOI 10.1111/eva.13199
   Bolger AM, 2014, BIOINFORMATICS, V30, P2114, DOI 10.1093/bioinformatics/btu170
   Bozicevic V, 2016, MOL ECOL, V25, P1175, DOI 10.1111/mec.13464
   Bushnell B., 2014, BBTools suite
   Chen LZ, 2010, J INSECT PHYSIOL, V56, P247, DOI 10.1016/j.jinsphys.2009.10.008
   Conesa A, 2005, BIOINFORMATICS, V21, P3674, DOI 10.1093/bioinformatics/bti610
   Coop G, 2010, GENETICS, V185, P1411, DOI 10.1534/genetics.110.114819
   Dunning LT., 2013, THESIS U AUCKLAND
   Fedorova M, 2018, PROBLEMS PARTICULARL, V2, P101, DOI [10.21055/0370-1069-2018-2-101-105, DOI 10.21055/0370-1069-2018-2-101-10510]
   Fedorova M. V., 2019, Parazitologiya (St. Petersburg), V53, P518, DOI 10.1134/S0031184719060073
   Fedorova M. V, 2019, Meditsinskaya Parazitologiya i Parazitarnye Bolezni, P47, DOI 10.33092/0025-8326mp2019.1.47-55
   Ganushkina L. A., 2013, Meditsinskaya Parazitologiya i Parazitarnye Bolezni, P45
   Ganushkina L. A., 2012, Meditsinskaya Parazitologiya i Parazitarnye Bolezni, P3
   Ganushkina LA, 2016, VECTOR-BORNE ZOONOT, V16, P58, DOI 10.1089/vbz.2014.1761
   Gardner LM, 2016, LANCET INFECT DIS, V16, P522, DOI 10.1016/S1473-3099(16)00176-6
   Garzón MJ, 2021, MED VET ENTOMOL, V35, P97, DOI 10.1111/mve.12474
   Gautier M, 2015, GENETICS, V201, P1555, DOI 10.1534/genetics.115.181453
   Gautier M, 2013, MOL ECOL, V22, P3766, DOI 10.1111/mec.12360
   Gratz NG, 2004, MED VET ENTOMOL, V18, P215, DOI 10.1111/j.0269-283X.2004.00513.x
   Gutsevich AV, 1970, FAUNA USSR DIPTERA M, V3
   HANSON SM, 1994, J MED ENTOMOL, V31, P192, DOI 10.1093/jmedent/31.2.192
   Hivert V, 2018, GENETICS, V210, P315, DOI 10.1534/genetics.118.300900
   Huber K, 2002, MOL ECOL, V11, P1629, DOI 10.1046/j.1365-294X.2002.01555.x
   Jensen JD, 2007, GENETICS, V176, P2371, DOI 10.1534/genetics.106.069450
   Katoh K, 2005, NUCLEIC ACIDS RES, V33, P511, DOI 10.1093/nar/gki198
   Kayukawa T, 2007, INSECT BIOCHEM MOLEC, V37, P1160, DOI 10.1016/j.ibmb.2007.07.007
   Kayukawa T, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0008277
   Kim M, 2006, J INSECT PHYSIOL, V52, P1226, DOI 10.1016/j.jinsphys.2006.09.007
   Kofler R, 2011, BIOINFORMATICS, V27, P3435, DOI 10.1093/bioinformatics/btr589
   Kofler R, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0015925
   Konorov EA, 2018, RUSS J GENET+, V54, P218, DOI [10.1134/S1022795418020102, 10.1134/s1022795418020102]
   Kostal V, 1998, J COMP PHYSIOL B, V168, P453, DOI 10.1007/s003600050165
   Kotsakiozi P, 2018, PARASITE VECTOR, V11, DOI 10.1186/s13071-018-2933-2
   Kotsakiozi P, 2017, ECOL EVOL, V7, P10143, DOI 10.1002/ece3.3514
   Kramer IM, 2020, PARASITE VECTOR, V13, DOI 10.1186/s13071-020-04054-w
   Kress A, 2016, J VECTOR ECOL, V41, P142, DOI 10.1111/jvec.12206
   Lanfear R, 2012, MOL BIOL EVOL, V29, P1695, DOI 10.1093/molbev/mss020
   Leviyang S, 2017, BIOINFORMATICS, V33, P2455, DOI 10.1093/bioinformatics/btx187
   Mallard F, 2018, GENOME BIOL, V19, DOI 10.1186/s13059-018-1503-4
   Manni M, 2017, PLOS NEGLECT TROP D, V11, DOI 10.1371/journal.pntd.0005332
   McKenna A, 2010, GENOME RES, V20, P1297, DOI 10.1101/gr.107524.110
   Medley KA, 2019, J APPL ECOL, V56, P2518, DOI 10.1111/1365-2664.13480
   Medley KA, 2015, MOL ECOL, V24, P284, DOI 10.1111/mec.12925
   Michaud MR, 2006, J INSECT PHYSIOL, V52, P1073, DOI 10.1016/j.jinsphys.2006.07.005
   Multini LC, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0220773
   Parker DJ, 2015, HEREDITY, V115, P13, DOI 10.1038/hdy.2015.6
   Parker DJ, 2018, GENOME BIOL EVOL, V10, P2086, DOI 10.1093/gbe/evy147
   Paupy C, 2004, AM J TROP MED HYG, V71, P73, DOI 10.4269/ajtmh.2004.71.73
   Pavlides SC, 2011, J INSECT PHYSIOL, V57, P635, DOI 10.1016/j.jinsphys.2011.03.022
   Pavlidis P, 2013, MOL BIOL EVOL, V30, P2224, DOI 10.1093/molbev/mst112
   Pichler V, 2019, PLOS NEGLECT TROP D, V13, DOI 10.1371/journal.pntd.0007554
   Poelchau MF, 2013, P ROY SOC B-BIOL SCI, V280, DOI 10.1098/rspb.2013.0143
   Pool JE, 2017, MOL BIOL EVOL, V34, P349, DOI 10.1093/molbev/msw232
   Popov IO, 2017, PROBLEMS ECOLOGICAL, V28, P51, DOI [10.21513/0207-2564-2017-3-51-71, DOI 10.21513/0207-2564-2017-3-51-71]
   Rambaut A, 2018, SYST BIOL, V67, P901, DOI 10.1093/sysbio/syy032
   Reinhold JM, 2018, INSECTS, V9, DOI 10.3390/insects9040158
   Reynolds JA, 2012, J INSECT PHYSIOL, V58, P966, DOI 10.1016/j.jinsphys.2012.04.013
   Rinehart JP, 2006, J MED ENTOMOL, V43, P713, DOI 10.1603/0022-2585(2006)43[713:ECADTI]2.0.CO;2
   Romi Roberto, 2001, Annali dell'Istituto Superiore di Sanita, V37, P241
   Ronquist F, 2012, SYST BIOL, V61, P539, DOI 10.1093/sysbio/sys029
   [СЕРГИЕВ Владимир Петрович SERGIEV V.P.], 2014, [Эпидемиология и инфекционные болезни. Актуальные вопросы, Epidemiologiya i infektsionnye bolezni. Aktual'nye voprosy], P9
   Shaikevich EV, 2018, VAVILOVSKII ZH GENET, V22, P574
   Sherpa S, 2019, EVOLUTION, V73, P1793, DOI 10.1111/evo.13801
   Sherpa S, 2019, MOL ECOL, V28, P2360, DOI 10.1111/mec.15071
   Sherpa S, 2018, INFECT GENET EVOL, V58, P145, DOI 10.1016/j.meegid.2017.12.018
   Shorthouse D.P., 2010, SimpleMappr, an online tool to produce publication-quality point maps
   Stirling C, 2010, BMC HEALTH SERV RES, V10, DOI 10.1186/1472-6963-10-122
   Storey KB, 2012, CAN J ZOOL, V90, P456, DOI 10.1139/Z2012-011
   Sycheva K. A., 2020, Meditsinskaya Parazitologiya i Parazitarnye Bolezni, P3, DOI 10.33092/0025-8326mp2020.2.03-08
   Thomas CD, 2001, NATURE, V411, P577, DOI 10.1038/35079066
   Thomas SM, 2012, PARASITE VECTOR, V5, DOI 10.1186/1756-3305-5-100
   Tippelt L, 2020, PARASITE VECTOR, V13, DOI 10.1186/s13071-020-04386-7
   Tsuda Y, 2001, ENVIRON ENTOMOL, V30, P855, DOI 10.1603/0046-225X-30.5.855
   Urbanski JM, 2010, P ROY SOC B-BIOL SCI, V277, P2683, DOI 10.1098/rspb.2010.0362
   Wilches R, 2014, THESIS IMU
   Xia QY, 2004, SCIENCE, V306, P1937, DOI 10.1126/science.1102210
   Yang S, 2018, GENE, V642, P9, DOI 10.1016/j.gene.2017.11.002
   Yasjukevich V. V., 2013, Probl. Ecol. Monit Ecosyst Modell, V25, P314
   Zabashta M. V., 2016, Meditsinskaya Parazitologiya i Parazitarnye Bolezni, P10
   Zé-Zé L, 2020, PLOS NEGLECT TROP D, V14, DOI 10.1371/journal.pntd.0008657
   Zhang HD, 2016, MITOCHONDRIAL DNA A, V27, P2787, DOI 10.3109/19401736.2015.1053067
NR 86
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U1 1
U2 22
PU PEERJ INC
PI LONDON
PA 341-345 OLD ST, THIRD FLR, LONDON, EC1V 9LL, ENGLAND
SN 2167-8359
J9 PEERJ
JI PeerJ
PD JUL 21
PY 2021
VL 9
AR e11776
DI 10.7717/peerj.11776
PG 23
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA TM2WA
UT WOS:000675411000003
PM 34327056
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Bigelow, SW
   Looney, CE
   Cannon, JB
AF Bigelow, Seth W.
   Looney, Christopher E.
   Cannon, Jeffery B.
TI Hurricane effects on climate-adaptive silviculture treatments to
   longleaf pine woodland in southwestern Georgia, USA
SO FORESTRY
LA English
DT Article
ID SOUTHEASTERN UNITED-STATES; FOREST VEGETATION; DISTURBANCE; MANAGEMENT;
   WINDTHROW; DAMAGE; DIVERSITY; GROWTH; REGION; ECOSYSTEMS
AB The Adaptive Silviculture for Climate Change (ASCC) network tests silvicultural treatments to promote 'resistance' or 'resilience' to climate change or speed 'transition' to new forest types. Based on projected increases in air temperatures and within-season dry periods in southeastern USA, we installed resistance, resilience and transition treatments involving species selection and varied intensities of density reduction, plus an untreated control, in mixed Longleaf pine-hardwood woodland in southwest Georgia USA. Within a year of treatment a tropical cyclone, Hurricane Michael, exposed the site to the unforeseen climatic stress of >44-m s(-1) winds. We measured inventory plots post-cyclone and compared the data to pre-storm and pre-treatment values. We analysed stand density index (metric SDI, species maximum value = 1000), stand complexity index (SCI), composition and individual tree characteristics. The ASCC treatments decreased both SDI (from 220 to 124 in the transition treatment) and SCI. The cyclone did not greatly decrease SDI (mean decrease 4.5 per cent) and decreased SCI only in the Controls. Xeric hardwoods were more prone to damage than other functional groups, and ordination showed that the cyclone shifted species composition to greater Longleaf pine dominance. Taller trees were more Likely to be damaged, except in the resilience treatment, which had a relatively Large representation of shorter, more easily damaged xeric hardwoods. The open canopy of the Longleaf-hardwood woodland, only 22 per cent of maximum SDI before treatment, evidently fostered wind-firmness, thereby Limiting the destructive effect of the cyclone. The sensitivity of xeric hardwoods to hurricane damage suggests that there may be a trade-off between wind tolerance and drought tolerance among functional groups. Maintaining a mixture of drought and wind-resistant species, as in the resilience treatments, may provide broader insurance against multiple climate change impacts in Longleaf pine and other forested systems dominated by a single foundation species.
C1 [Bigelow, Seth W.; Cannon, Jeffery B.] Jones Ctr Ichauway, Newton, GA 39870 USA.
   [Looney, Christopher E.] Colorado State Univ, Dept Forest & Rangeland Stewardship, Ft Collins, CO 80523 USA.
   [Looney, Christopher E.] US Forest Serv, Pacific Southwest Res Stn, USDA, 1731 Res Pk Dr, Davis, CA 95618 USA.
C3 Colorado State University; United States Department of Agriculture
   (USDA); United States Forest Service
RP Bigelow, SW (corresponding author), Jones Ctr Ichauway, Newton, GA 39870 USA.
EM seth.bigeiow@jonesctr.org
RI Looney, Christopher/IUN-6310-2023; Cannon, Jeffery/J-4447-2019; Bigelow,
   Seth/A-2551-2008
OI Looney, Christopher/0000-0002-3645-8406; Bigelow,
   Seth/0000-0002-0052-191X
FU National Science Foundation [1910811]; Colorado State University, Warner
   College of Natural Resources, Department of Forest and Rangeland
   Stewardship; Division Of Environmental Biology; Direct For Biological
   Sciences [1910811] Funding Source: National Science Foundation
FX Jones Center at Ichauway with additional support provided by the
   National Science Foundation (grant number 1910811); Colorado State
   University, Warner College of Natural Resources, Department of Forest
   and Rangeland Stewardship.
CR Allen CD, 2015, ECOSPHERE, V6, DOI 10.1890/ES15-00203.1
   [Anonymous], 2017, R PACKAGE VERSION 14
   Beven J.L., 2019, NATL HURRICANE CTR C, P1
   Bhatia KT, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-08471-z
   Böhner J, 2009, DEV SOIL SCI, V33, P195, DOI 10.1016/S0166-2481(08)00008-1
   Boose ER, 2004, ECOL MONOGR, V74, P335, DOI 10.1890/02-4057
   Bottero A, 2017, J APPL ECOL, V54, P1605, DOI 10.1111/1365-2664.12847
   Burnham K. P., 2002, Model Selection and Multimodel Inference
   Cannon JB, 2016, LANDSCAPE ECOL, V31, P2097, DOI 10.1007/s10980-016-0384-8
   Chambers JQ, 2007, SCIENCE, V318, P1107, DOI 10.1126/science.1148913
   Chrestensen R.H.B., 2019, **DATA OBJECT**
   Conrad O, 2015, GEOSCI MODEL DEV, V8, P1991, DOI 10.5194/gmd-8-1991-2015
   Costanza JK, 2015, J ENVIRON MANAGE, V151, P186, DOI 10.1016/j.jenvman.2014.12.032
   Dale VH, 2001, BIOSCIENCE, V51, P723, DOI 10.1641/0006-3568(2001)051[0723:CCAFD]2.0.CO;2
   Dhote JF, 2005, ECOL STUD-ANAL SYNTH, V176, P291
   Ducey MJ, 2009, WEST J APPL FOR, V24, P5, DOI 10.1093/wjaf/24.1.5
   Fargione J, 2007, P ROY SOC B-BIOL SCI, V274, P871, DOI 10.1098/rspb.2006.0351
   Franklin J.F., 2007, USDA FOREST SERVICE
   Gardiner B, 2000, ECOL MODEL, V129, P1, DOI 10.1016/S0304-3800(00)00220-9
   Garms C, 2019, FORESTRY, V92, P417, DOI 10.1093/forestry/cpy038
   Gilliam FS, 2006, APPL VEG SCI, V9, P83, DOI 10.1658/1402-2001(2006)9[83:NDATPO]2.0.CO;2
   GLITZENSTEIN JS, 1988, FOREST ECOL MANAG, V25, P269, DOI 10.1016/0378-1127(88)90092-8
   Gonzalez-Benecke CA, 2014, FOREST SCI, V60, P43, DOI 10.5849/forsci.12-074
   Greenwell BM, 2018, R J, V10, P381
   GRESHAM CA, 1991, BIOTROPICA, V23, P420, DOI 10.2307/2388261
   Griess VC, 2011, CAN J FOREST RES, V41, P1141, DOI [10.1139/X11-042, 10.1139/x11-042]
   Hanewinkel M, 2014, FORESTRY, V87, P525, DOI 10.1093/forestry/cpu008
   Harrell FE, 2015, SPRINGER SER STAT, DOI 10.1007/978-3-319-19425-7
   Holland AM, 2019, J NAT CONSERV, V47, P38, DOI 10.1016/j.jnc.2018.11.006
   Holling C.S., 1973, Annual Rev Ecol Syst, V4, P1, DOI 10.1146/annurev.es.04.110173.000245
   Jactel H, 2009, ANN FOREST SCI, V66, DOI 10.1051/forest/2009054
   Jeong GY, 2009, WOOD FIBER SCI, V41, P51
   Johnsen KH, 2009, SOUTH J APPL FOR, V33, P178, DOI 10.1093/sjaf/33.4.178
   KRUSKAL JB, 1964, PSYCHOMETRIKA, V29, P1, DOI 10.1007/BF02289565
   Lavoie S, 2012, FOREST ECOL MANAG, V269, P158, DOI 10.1016/j.foreco.2011.12.018
   Lavorel Sandra, 1999, Diversity and Distributions, V5, P3, DOI 10.1046/j.1472-4642.1999.00033.x
   Lohmander P, 1987, SCAND J FOREST RES, V2, P227, DOI 10.1080/02827588709382460
   Long J. N., 1990, Western Journal of Applied Forestry, V5, P93
   McCune B, 2002, Analysis of Ecological Communities
   McCune B.M.M, 2016, MJM SOFTWARE DESIGN
   Millar CI, 2007, ECOL APPL, V17, P2145, DOI 10.1890/06-1715.1
   Mitchell RJ, 2014, FOREST ECOL MANAG, V327, P316, DOI 10.1016/j.foreco.2013.12.003
   MONK CD, 1968, AM MIDL NAT, V79, P441, DOI 10.2307/2423190
   Montgomery D., Design and Analysis of Experiments, Vninth
   Mori AS, 2013, BIOL REV, V88, P349, DOI 10.1111/brv.12004
   Morin X, 2014, ECOL LETT, V17, P1526, DOI 10.1111/ele.12357
   Moser WK, 2002, FORESTRY, V75, P443, DOI 10.1093/forestry/75.4.443
   Nagel LM, 2017, J FOREST, V115, P167, DOI 10.5849/jof.16-039
   Nagel TA, 2006, FOREST ECOL MANAG, V226, P268, DOI 10.1016/j.foreco.2006.01.039
   NationalWeather Service, 2018, HURR MICH HITS GEORG
   O'Hara KL, 2013, FORESTRY, V86, P401, DOI 10.1093/forestry/cpt012
   Peck J.E., 2010, MjM Software Design
   Perkins MW, 2008, FOREST ECOL MANAG, V255, P1618, DOI 10.1016/j.foreco.2007.11.020
   Peterson CJ, 2019, FORESTRY, V92, P444, DOI 10.1093/forestry/cpz025
   Pinheiro J., 2022, R package version 3.1-159, V3, P1
   Powell EJ, 2015, J CLIMATE, V28, P1592, DOI 10.1175/JCLI-D-14-00410.1
   Provencher L., 2001, Ecological Restoration, V19, P92, DOI 10.3368/er.19.2.92
   Pukkala T, 2016, FOREST ECOL MANAG, V372, P120, DOI 10.1016/j.foreco.2016.04.014
   QGIS Development Team, 2018, OGIS GEOGR INF SYST
   R Core Team, 2022, R: A Language and Environment for Statistical Computing
   Raymond P, 2009, J FOREST, V107, P405
   Reineke LH, 1933, J AGRIC RES, V46, P0627
   Rich RL, 2007, J ECOL, V95, P1261, DOI 10.1111/j.1365-2745.2007.01301.x
   Richards SA, 2008, J APPL ECOL, V45, P218, DOI 10.1111/j.1365-2664.2007.01377.x
   Roberts MR, 2007, FOREST ECOL MANAG, V242, P58, DOI 10.1016/j.foreco.2007.01.043
   RUEL JC, 1995, FOREST CHRON, V71, P434, DOI 10.5558/tfc71434-4
   Schomaker M. E., 2007, General Technical Report - Southern Research Station, USDA Forest Service
   Shaw JD, 2007, SOUTH J APPL FOR, V31, P28, DOI 10.1093/sjaf/31.1.28
   SMITH VG, 1987, CAN J FOREST RES, V17, P1080, DOI 10.1139/x87-166
   Spellman H, 1999, MANAGEMENT MIXED SPE, P245
   Stanturf JA, 2007, FOREST ECOL MANAG, V250, P119, DOI 10.1016/j.foreco.2007.03.015
   U.S. Geoloical Survey, 2016, NAT MAP 3D EL PROGR
   Van Lear DH, 2005, FOREST ECOL MANAG, V211, P150, DOI 10.1016/j.foreco.2005.02.014
   VANLEAR DH, 1977, SOIL SCI SOC AM J, V41, P989, DOI 10.2136/sssaj1977.03615995004100050036x
   Wang H, 2010, J HYDROMETEOROL, V11, P1007, DOI 10.1175/2010JHM1229.1
   Weishampel JF, 2007, REMOTE SENS ENVIRON, V109, P142, DOI 10.1016/j.rse.2006.12.016
NR 76
TC 17
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U1 2
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PU OXFORD UNIV PRESS
PI OXFORD
PA GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND
SN 0015-752X
EI 1464-3626
J9 FORESTRY
JI Forestry
PD JUL
PY 2021
VL 94
IS 3
BP 395
EP 406
DI 10.1093/forestry/cpaa042
PG 12
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Forestry
GA TU1WG
UT WOS:000680830000006
OA hybrid
DA 2025-01-10
ER

PT J
AU Mi, CX
   Shatwell, T
   Ma, J
   Xu, YQ
   Su, FL
   Rinke, K
AF Mi, Chenxi
   Shatwell, Tom
   Ma, Jun
   Xu, Yaqian
   Su, Fangli
   Rinke, Karsten
TI Ensemble warming projections in Germany's largest drinking water
   reservoir and potential adaptation strategies
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Rappbode Reservoir; Thermal structure; Climate change; CE-QUAL-W2;
   Selective water withdrawal
ID DEEP SUBTROPICAL RESERVOIR; THERMAL STRATIFICATION; CLIMATE-CHANGE;
   RAPPBODE RESERVOIR; DISSOLVED-OXYGEN; MIXING REGIMES; ARCTIC LAKES;
   TEMPERATURE; MODEL; WITHDRAWAL
AB The thermal structure in reservoirs affects the development of aquatic ecosystems, and can be substantially influenced by climate change and management strategies. We applied a two-dimensional hydrodynamic model to explore the response of the thermal structure in Germany's largest drinking water reservoir, Rappbode Reservoir, to future climate projections and different water withdrawal strategies. We used projections for representative concentration pathways (RCP) 2.6, 6.0 and 8.5 from an ensemble of 4 different global climate models. Simulation results showed that epilimnetic water temperatures in the reservoir strongly increased under all three climate scenarios. Hypoli mnetic temperatures remained rather constant under RCP 2.6 and RCP 6.0 but increased markedly under RCP 8.5. Under the intense warming in RCP 8.5, hypolimnion temperatures were projected to rise from 5 degrees C to 8 degrees C by the end of the century. Stratification in the reservoir was projected to be more stable under RCP 6.0 and RCP 8.5, but did not show significant changes under RCP 2.6. Similar results were found with respect to the light intensity within the mixed-layer. Moreover, the results suggested that surface with-drawal can be an effective adaptation strategy under strong climate warming (RCP 8.5) to reduce surface warming and avoid hypolimnetic warming. This study documents how global scale climate projections can be translated into site-specific climate impacts to derive adaptation strategies for reservoir operation. Moreover, our results illustrate that the most intense warming scenario, i.e. RCP 8.5, demands far-reaching climate adaptation while the mitigation scenario (RCP 2.6) does not require adaptation of reservoir management before 2100. (C) 2020 The Authors. Published by Elsevier B.V.
C1 [Mi, Chenxi; Shatwell, Tom; Rinke, Karsten] Helmholtz Ctr Environm Res, Dept Lake Res, Magdeburg, Germany.
   [Mi, Chenxi; Su, Fangli] Shenyang Agr Univ, Coll Water Conservancy, Shenyang, Peoples R China.
   [Ma, Jun; Xu, Yaqian] Hubei Univ Technol, Hubei Key Lab Ecol Restorat River Lakes & Algal U, Wuhan, Peoples R China.
C3 Helmholtz Association; Helmholtz Center for Environmental Research
   (UFZ); Shenyang Agricultural University; Hubei University of Technology
RP Mi, CX (corresponding author), Helmholtz Ctr Environm Res, Dept Lake Res, Magdeburg, Germany.
EM chenxi.mi@ufz.de
RI Ma, Jun/IUQ-7857-2023; Rinke, Karsten/E-6163-2016; Shatwell,
   Tom/ABF-1308-2020; Shatwell, Tom/K-2937-2013; Mi, Chenxi/S-1612-2018
OI Shatwell, Tom/0000-0002-4520-7916; Mi, Chenxi/0000-0003-2323-1832; Ma,
   Jun/0000-0001-7836-8081
FU German Science Foundation [RI 2040/4-1]; ERA4CS-Project "WateXr" from
   the German Federal Ministry of Education and Research [01LS1713A];
   National Natural Science Foundation of China [31670711, 7170030840];
   China Scholarship Council [201608210145]
FX The authors are grateful to the Rappbode Reservoir authority
   (Talsperrenbetrieb Sachsen-Anhalt), the Fernwasserversorgung
   ElbaueOstharz GmbH and German Weather Service (DWD) for provision of the
   hydrological and meteorological data. The authors acknowledge the
   project "Oxygen dynamics in large reservoirs: A new framework for
   understanding the formation of metalimnetic oxygen minima (Acronym:
   newMOM)" funded by the German Science Foundation under grant RI
   2040/4-1, the ERA4CS-Project "WateXr" funded under grant 01LS1713A from
   the German Federal Ministry of Education and Research, as well as the
   National Natural Science Foundation of China (31670711, 7170030840). The
   authors also acknowledge financial support from the China Scholarship
   Council (201608210145). Finally, we would like to thank two anonymous
   reviewers for their constructive comments to an earlier version of this
   manuscript.
CR [Anonymous], 2016, R LANG ENV STAT COMP
   [Anonymous], 2008, IPCC EXP M REP NEW S
   [Anonymous], 2014, Climate change 2014: synthesis report
   Arhonditsis GB, 2004, MAR ECOL PROG SER, V271, P13, DOI 10.3354/meps271013
   Ayala Ana I., 2020, Hydrology and Earth System Sciences, V24, P3311, DOI 10.5194/hess-24-3311-2020
   BOLTON D, 1980, MON WEATHER REV, V108, P1046, DOI 10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2
   Bonnet MP, 2000, AQUAT SCI, V62, P105, DOI 10.1007/s000270050001
   Bueche T, 2015, CLIM DYNAM, V44, P371, DOI 10.1007/s00382-014-2259-5
   Carr MK, 2020, ENVIRON ENG SCI, V37, P78, DOI 10.1089/ees.2019.0146
   Chuo MY, 2019, ECOL MODEL, V392, P236, DOI 10.1016/j.ecolmodel.2018.11.017
   Cole T.M., 2006, CE QUAL W2 2 DIMENSI
   Coloso JJ, 2011, AQUAT SCI, V73, P305, DOI 10.1007/s00027-010-0177-0
   Downing JA, 2006, LIMNOL OCEANOGR, V51, P2388, DOI 10.4319/lo.2006.51.5.2388
   England MH, 2015, NAT CLIM CHANGE, V5, P394, DOI 10.1038/nclimate2575
   Eyring V, 2016, GEOSCI MODEL DEV, V9, P1937, DOI 10.5194/gmd-9-1937-2016
   Fan CW, 2008, SCI TOTAL ENVIRON, V393, P326, DOI 10.1016/j.scitotenv.2007.12.018
   Fang X, 2009, LIMNOL OCEANOGR, V54, P2359, DOI 10.4319/lo.2009.54.6_part_2.2359
   Feldbauer J, 2020, ENVIRON SCI EUR, V32, DOI 10.1186/s12302-020-00324-7
   Fenocchi A, 2018, CLIM DYNAM, V51, P3521, DOI 10.1007/s00382-018-4094-6
   Frieler K, 2017, GEOSCI MODEL DEV, V10, P4321, DOI 10.5194/gmd-10-4321-2017
   Hempel S, 2013, EARTH SYST DYNAM, V4, P219, DOI 10.5194/esd-4-219-2013
   Hipel K.W, 1994, Time series modeling of water resources and environmental systems
   Horn H, 2015, INT REV HYDROBIOL, V100, P43, DOI 10.1002/iroh.201401743
   Huber MB, 2017, GEOPHYS RES LETT, V44, P1402, DOI 10.1002/2016GL071587
   Ito R, 2020, GEOSCI MODEL DEV, V13, P859, DOI 10.5194/gmd-13-859-2020
   Jin JX, 2019, PEERJ, V7, DOI 10.7717/peerj.6925
   Kerimoglu O, 2013, WATER RESOUR RES, V49, P7518, DOI [10.1002/2013WR013520, 10.1002/20]
   Kirillin G, 2013, J HYDROL, V496, P47, DOI 10.1016/j.jhydrol.2013.05.023
   Kirillin G, 2010, BOREAL ENVIRON RES, V15, P279
   Kobler UG, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10061968
   Kreling J, 2017, LIMNOL OCEANOGR, V62, P348, DOI 10.1002/lno.10430
   Lewis WM, 2019, WATER RESOUR RES, V55, P1988, DOI 10.1029/2018WR023555
   Liu M, 2019, SCI TOTAL ENVIRON, V651, P614, DOI 10.1016/j.scitotenv.2018.09.215
   Lopez A, 2015, CLIMATIC CHANGE, V132, P15, DOI 10.1007/s10584-014-1292-z
   Ma Shengwei, 2008, Lakes & Reservoirs Research and Management, V13, P51, DOI 10.1111/j.1440-1770.2007.00353.x
   Meinshausen M, 2011, CLIMATIC CHANGE, V109, P213, DOI 10.1007/s10584-011-0156-z
   Mi CX, 2020, WATER RES, V175, DOI 10.1016/j.watres.2020.115701
   Mi CX, 2019, ENVIRON SCI EUR, V31, DOI 10.1186/s12302-019-0202-4
   Mi CX, 2018, INT REV HYDROBIOL, V103, P71, DOI 10.1002/iroh.201701916
   Müller B, 2012, ENVIRON SCI TECHNOL, V46, P9964, DOI 10.1021/es301422r
   Northrop PJ, 2014, J CLIMATE, V27, P8793, DOI 10.1175/JCLI-D-14-00265.1
   O'Reilly CM, 2015, GEOPHYS RES LETT, V42, P10773, DOI 10.1002/2015GL066235
   Park H, 2018, CLIMATIC CHANGE, V151, P365, DOI 10.1007/s10584-018-2322-z
   Posch T, 2012, NAT CLIM CHANGE, V2, P809, DOI [10.1038/nclimate1581, 10.1038/NCLIMATE1581]
   Read JS, 2014, ECOL MODEL, V291, P142, DOI 10.1016/j.ecolmodel.2014.07.029
   Read JS, 2011, ENVIRON MODELL SOFTW, V26, P1325, DOI 10.1016/j.envsoft.2011.05.006
   Rinke K, 2013, ENVIRON EARTH SCI, V69, P523, DOI 10.1007/s12665-013-2464-2
   Rose KC, 2016, LIMNOL OCEANOGR LETT, V1, P44, DOI 10.1002/lol2.10027
   Sadeghian A, 2018, ENVIRON MODELL SOFTW, V101, P73, DOI 10.1016/j.envsoft.2017.12.009
   Sahoo GB, 2016, LIMNOL OCEANOGR, V61, P496, DOI 10.1002/lno.10228
   Sahoo GB, 2013, CLIMATIC CHANGE, V116, P71, DOI 10.1007/s10584-012-0600-8
   Saros JE, 2016, LIMNOL OCEANOGR, V61, P1530, DOI 10.1002/lno.10314
   Schmidt W., 1928, GEOGR ANN, V10, P145, DOI DOI 10.2307/519789
   SEN PK, 1968, J AM STAT ASSOC, V63, P1379
   Services G. D., 2016, EARTH2OBSERVE WFDEI
   Shatwell T, 2019, HYDROL EARTH SYST SC, V23, P1533, DOI 10.5194/hess-23-1533-2019
   Smith LA, 2002, P NATL ACAD SCI USA, V99, P2487, DOI 10.1073/pnas.012580599
   Straile D, 2003, LIMNOL OCEANOGR, V48, P1432, DOI 10.4319/lo.2003.48.4.1432
   Straile D, 2010, GLOBAL CHANGE BIOL, V16, P2844, DOI 10.1111/j.1365-2486.2009.02158.x
   SWINBANK WC, 1963, Q J ROY METEOR SOC, V89, P339, DOI 10.1002/qj.49708938105
   Tan ZL, 2018, WATER RESOUR RES, V54, P4681, DOI [10.1029/2017WR022334, 10.1029/2017wr022334]
   Tan ZL, 2017, J ADV MODEL EARTH SY, V9, P2190, DOI 10.1002/2017MS001028
   Terry JA, 2017, WATER-SUI, V9, DOI 10.3390/w9020131
   Thiery W, 2014, TELLUS A, V66, DOI 10.3402/tellusa.v66.21390
   Trolle D, 2019, SCI TOTAL ENVIRON, V657, P627, DOI 10.1016/j.scitotenv.2018.12.055
   Uhlmann W., 2017, MODEL BASED STUDY DI
   Valerio G, 2015, HYDROL PROCESS, V29, P767, DOI 10.1002/hyp.10183
   Warszawski L, 2014, P NATL ACAD SCI USA, V111, P3228, DOI 10.1073/pnas.1312330110
   Weber M, 2017, J ENVIRON MANAGE, V197, P96, DOI 10.1016/j.jenvman.2017.03.020
   Wentzky VC, 2018, FRESHWATER BIOL, V63, P1063, DOI 10.1111/fwb.13116
   Wiens JA, 2009, P NATL ACAD SCI USA, V106, P19729, DOI 10.1073/pnas.0901639106
   Williams D.T., 1981, P S SURFACE WATER IM, P1329, DOI DOI 10.1111/J.1463-1326.2006.00573.X
   Winslow LA, 2017, LIMNOL OCEANOGR, V62, P2168, DOI 10.1002/lno.10557
   Woolway RI, 2019, NAT GEOSCI, V12, P271, DOI 10.1038/s41561-019-0322-x
   Yang K, 2019, WATER RESOUR RES, V55, P4688, DOI [10.1029/2019wr025316, 10.1029/2019WR025316]
   Yang K, 2018, SCI TOTAL ENVIRON, V624, P859, DOI 10.1016/j.scitotenv.2017.12.119
   Zhang YL, 2014, LIMNOL OCEANOGR, V59, P1193, DOI 10.4319/lo.2014.59.4.1193
   Zheng TG, 2017, WATER SCI TECH-W SUP, V17, P279, DOI 10.2166/ws.2016.133
NR 78
TC 29
Z9 29
U1 3
U2 47
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 15
PY 2020
VL 748
AR 141366
DI 10.1016/j.scitotenv.2020.141366
PG 12
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA OF2MX
UT WOS:000581049800062
PM 32798870
OA hybrid
DA 2025-01-10
ER

PT J
AU Acosta, M
   van Wessel, M
   van Bommel, S
   Ampaire, EL
   Jassogne, L
   Feindt, PH
AF Acosta, Mariola
   van Wessel, Margit
   van Bommel, Severine
   Ampaire, Edidah L.
   Jassogne, Laurence
   Feindt, Peter H.
TI The power of narratives: Explaining inaction on gender mainstreaming in
   Uganda's climate change policy
SO DEVELOPMENT POLICY REVIEW
LA English
DT Article
DE Africa; climate change; gender mainstreaming; ideational power; policy
   narrative; Uganda
ID ADAPTATION
AB Motivation Gender mainstreaming has been increasingly viewed as a fundamental element of agricultural climate adaptation policies. However, the expectation that gender-mainstreaming efforts would contribute towards greater gender equality has been mostly disappointed. Our starting point is this disjuncture between a firm establishment of the gender mainstreaming discourse and the limited visible effects in reducing gender inequalities. Purpose To understand this disjuncture we examine the meanings through which policy makers relate to, and dis/engage with gender issues. The article draws attention to the role of narratives in micro-processes of policymaking that support, perpetuate or create resistance against the concept of gender mainstreaming, or against policy change more broadly. Approach and methods The study deploys a multi-step narrative analysis in which we identify story episodes, co-construct stories, identify and interpret the narratives and finally study these narratives in interaction. The empirical material consists of thirty semi-standardized expert interviews as well as excerpts from ten multi-stakeholder meetings on the themes of climate change, agriculture, rural livelihoods and gender in Uganda. Findings The analysis reveals a complex ecology of 22 stories, clustered in five main narratives. While most stories unfold a Gender Equality narrative, four competing narratives emerge. Shifts during conversations from the Gender Equality narrative to other narratives reveal that the discursive engagement with gender mainstreaming is accompanied by simultaneous resistance, deconstruction and revocation. These narrative shifts exercise four distinct power effects: They (1) shift blame for ineffective gender implementation; (2) legitimize policy inaction; (3) foreground and naturalize patriarchy; and (4) promote the diversion of resources. The implicit communicative strategies exercise powerthroughideas (persuade listeners that the equality narrative is inappropriate), poweroverideas (gender equality ideas are rejected or frustrated) and powerinideas (entrenched patriarchy ideas are reproduced). Policy implications Attention to ideational power through policy narrative contributes to explain implementation issues with gender mainstreaming in Uganda, and is likely to be relevant beyond this case.
C1 [Acosta, Mariola; van Wessel, Margit; van Bommel, Severine; Feindt, Peter H.] Wageningen Univ, Strateg Commun Grp, Wageningen, Netherlands.
   [Acosta, Mariola; Ampaire, Edidah L.; Jassogne, Laurence] Int Inst Trop Agr, Kampala, Uganda.
   [van Bommel, Severine] Univ Queensland, Sch Agr & Food Sci, Gatton, Australia.
   [Ampaire, Edidah L.] Int Dev Res Ctr, Nairobi, Kenya.
   [Jassogne, Laurence] Opus Insights, The Hague, Netherlands.
   [Feindt, Peter H.] Humboldt Univ, Albrecht Daniel Thaer Inst Agr & Hort Sci, Berlin, Germany.
C3 Wageningen University & Research; University of Queensland; Humboldt
   University of Berlin
RP Acosta, M (corresponding author), Wageningen Univ, Strateg Commun Grp, Wageningen, Netherlands.
EM mariola.acosta@wur.nl
RI van Bommel, Severine/AAA-7002-2020
OI van Bommel, Severine/0000-0002-7782-9162; Acosta,
   Mariola/0000-0003-4456-1283
FU CGIAR Fund Donors
FX This work was implemented as part of 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. The
   views expressed in this document cannot be taken to reflect the official
   opinions of these organizations.
CR Acosta M., 2015, Gender and Climate Change in Uganda: Effects of Policy and Institutional Frameworks [Info Note]
   Aguilar L., 2010, Gender and Climate Change: An Introduction, P173
   Allwood G, 2013, WOMEN STUD INT FORUM, V39, P42, DOI 10.1016/j.wsif.2013.01.008
   Alston M, 2014, WOMEN STUD INT FORUM, V47, P287, DOI 10.1016/j.wsif.2013.01.016
   Ampaire EL, 2020, CLIMATIC CHANGE, V158, P43, DOI 10.1007/s10584-019-02447-0
   [Anonymous], 2015, Gender in climate-smart agriculture. Module 18 for the gender in agriculture sourcebook
   [Anonymous], 2 NAT DEV PLAN NDPII
   [Anonymous], 2015, UG NAT CLIM CHANG PO
   [Anonymous], 2002, POLITICAL ANAL CRITI
   [Anonymous], 1994, NARRATIVE POLICY ANA, DOI [10.1515/9780822381891, DOI 10.1515/9780822381891]
   Arora-Jonsson S., 2013, GENDER DEV ENV GOVER, P15
   Arora-Jonsson S, 2014, WOMEN STUD INT FORUM, V47, P295, DOI 10.1016/j.wsif.2014.02.009
   BACHRACH P, 1962, AM POLIT SCI REV, V56, P947, DOI 10.2307/1952796
   Benedetti Fanny., 2012, Women's rights in Uganda: gaps between policy and practice
   Bevir M.Rhodes., 2006, GOVERNANCE STORIES
   Bhattarai B, 2015, WORLD DEV, V70, P122, DOI 10.1016/j.worlddev.2015.01.003
   Brouwers R., 2013, 556 ISS
   Bustelo M., 2003, EVALUATION-US, V9, P383, DOI DOI 10.1177/135638900300900402
   Carstensen MB, 2016, J EUR PUBLIC POLICY, V23, P318, DOI 10.1080/13501763.2015.1115534
   Cooper E., 2010, 159 CPRC OV DEV I
   Cornwall A, 2007, DEV CHANGE, V38, P1, DOI 10.1111/j.1467-7660.2007.00400.x
   Debusscher P, 2013, DEV CHANGE, V44, P1111, DOI 10.1111/dech.12052
   ECOSOC, 1997, 19972 ECOSOC UN EC S
   Eerdewijk A.van., 2016, The Palgrave Handbook of Gender and Development, P117, DOI DOI 10.1007/978-1-137-38273-39
   Fischer F., 2003, REFRAMING PUBLIC POL, P161
   Godden N., 2013, RES ACTION POLICY AD, P251
   Hankivsky O, 2005, CAN J POLIT SCI, V38, P977, DOI 10.1017/S0008423905040783
   Ingram M, 2019, J ENVIRON POL PLAN, V21, P492, DOI 10.1080/1523908X.2015.1113513
   Jalusic V, 2009, ROUTL ECPR STUD EUR, P52
   Jin JJ, 2015, SCI TOTAL ENVIRON, V538, P942, DOI 10.1016/j.scitotenv.2015.07.027
   Jones M., 2014, SCI STORIES, DOI DOI 10.1057/9781137485861[RETRIEVED:08.02.2023]
   Jost C, 2016, CLIM DEV, V8, P133, DOI 10.1080/17565529.2015.1050978
   Lejano R, 2013, AM COMP ENVIRON POLI, P1
   Lukes S., 2005, Power: A Radical View, V2nd
   Meier P, 2011, SOC POLIT, V18, P469, DOI 10.1093/sp/jxr020
   Moncrieffe J., 2004, UGANDAS POLITICAL EC
   Moser C., 2005, Gender and Development, V13, P11, DOI [DOI 10.1080/13552070512331332283, DOI 10.1177/097300520700300102]
   Moser C., 2005, INT FEM J POLIT, V7, P576, DOI DOI 10.1080/14616740500284573
   Mukhopadhyay M, 2004, IDS BULL-I DEV STUD, V35, P95, DOI 10.1111/j.1759-5436.2004.tb00161.x
   Republic of Uganda, 2013, UG COUNTR VIS 2040
   Rhodes R.A. W., 2011, Everyday life in British government
   ROE EM, 1991, WORLD DEV, V19, P287, DOI 10.1016/0305-750X(91)90177-J
   Shenhav SR, 2015, Analyzing Social Narratives
   UN Women, 2015, IMPL GEND RESP CLIM
   UN-REDD, 2013, GUID NOT GEND SENS R
   Wagenaar H., 2014, Meaning in action: interpretation and dialogue in policy analysis
   Walby S, 2005, SOC POLIT, V12, P321, DOI 10.1093/sp/jxi018
   Wittman A, 2010, REV INT STUD, V36, P51, DOI 10.1017/S0260210509990507
   Yanow Dvora., 2000, Conducting Interpretive Policy Analysis
NR 49
TC 15
Z9 16
U1 5
U2 13
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 SEP
PY 2020
VL 38
IS 5
BP 555
EP 574
DI 10.1111/dpr.12458
EA JUN 2020
PG 20
WC Development Studies
WE Social Science Citation Index (SSCI)
SC Development Studies
GA NH7RW
UT WOS:000539695800001
OA hybrid
DA 2025-01-10
ER

PT S
AU Iqbal, MM
   Erskine, W
   Berger, JD
   Udall, JA
   Nelson, MN
AF Iqbal, Muhammad Munir
   Erskine, William
   Berger, Jens D.
   Udall, Joshua A.
   Nelson, Matthew N.
BE Singh, KB
   Kamphuis, LG
   Nelson, MN
TI Genomics of Yellow Lupin (<i>Lupinus luteus</i> L.)
SO LUPIN GENOME
SE Compendium of Plant Genomes
LA English
DT Article; Book Chapter
ID ANGUSTIFOLIUS L.; MOSAIC-VIRUS; DOMESTICATION; RESISTANCE; CROP; GENES;
   LEGUME; MAP; ADAPTATION; DIVERSITY
AB Yellow lupin (Lupinus luteus L.) is a minor annual legume crop valued for its productivity in highly infertile, acidic soils and for its very high protein seeds. Yellow lupin belongs to the 'Old World' group of lupin species and is closely related to narrow-leafed lupin. Yellow lupin shares similar climatic adaptation to narrow-leafed lupin over which it offers some additional advantages such as greater water-logging tolerance and disease resistance. Despite its promise, yellow lupin is grown only as a niche crop in Australia, Europe and South America, and has attracted very limited breeding attention to date. Major constraints to the wider uptake of yellow lupin as a crop include lack of diversity in the domesticated gene pool and a historic focus on adaptation to a limited range of environments. Current varieties are also sensitive to some abiotic stresses (notably drought, extreme temperatures, salinity and alkalinity) and to sap-sucking insects such as aphids. Good genetic resources are available for yellow lupin including extensive seed collections that capture much of the species-wide diversity and three recombinant inbred line populations. Until recently, yellow lupin has lagged behind its well-resourced sister species narrow-leafed lupin in terms of genomic resources but is now catching up. Transcriptomic datasets have been used to generate molecular markers and to investigate the causes of flower and pod abortion. The first genetic map for yellow lupin was recently released, which is being used to investigate phenology, domestication traits and productivity under water-limiting conditions. Transgenesis methods have been developed for yellow lupin, a key enabling technology for future genome editing activities. Efforts are underway to develop a high-quality reference genome sequence for yellow lupin. These developing resources will help researchers acquire knowledge and molecular tools to equip lupin breeders to overcome the restraints on broader adoption of this promising legume crop.
C1 [Iqbal, Muhammad Munir] Univ Western Australia, Sch Agr & Environm, Perth, WA, Australia.
   [Iqbal, Muhammad Munir; Erskine, William; Nelson, Matthew N.] Univ Western Australia, UWA Inst Agr, Perth, WA, Australia.
   [Iqbal, Muhammad Munir; Erskine, William] Univ Western Australia, Ctr Plant Breeding & Genet, Perth, WA, Australia.
   [Berger, Jens D.; Nelson, Matthew N.] CSIRO Agr & Food, Perth, WA, Australia.
   [Udall, Joshua A.] USDA ARS, Southern Plains Agr Res Ctr, College Stn, TX USA.
   [Nelson, Matthew N.] Royal Bot Gardens, Ardingly, England.
C3 University of Western Australia; University of Western Australia;
   University of Western Australia; Commonwealth Scientific & Industrial
   Research Organisation (CSIRO); United States Department of Agriculture
   (USDA); Royal Botanic Gardens, Kew
RP Nelson, MN (corresponding author), Univ Western Australia, UWA Inst Agr, Perth, WA, Australia.
EM munirqbl@gmail.com; william.erskine@uwa.edu.au; jens.berger@csiro.au;
   jaudall1@gmail.com; matthew.nelson@csiro.au
RI Udall, Joshua/A-7298-2009; Nelson, Matthew/A-1421-2008; Iqbal, Muhammad
   Munir/K-1673-2013
OI Nelson, Matthew/0000-0001-6766-4117; Iqbal, Muhammad
   Munir/0000-0002-8603-5348
CR Adhikari KN, 2012, CROP PASTURE SCI, V63, P444, DOI 10.1071/CP12189
   [Anonymous], 1998, LUPINS CROP PLANTS B
   Azani N, 2017, TAXON, V66, P44, DOI 10.12705/661.3
   Baird NA, 2008, PLOS ONE, V3, DOI 10.1371/journal.pone.0003376
   Berger JD, 2008, AUST J AGR RES, V59, P691, DOI 10.1071/AR07384
   Berger JD, 2014, J EXP BOT, V65, P6219, DOI 10.1093/jxb/eru006
   Berger JD, 2012, THEOR APPL GENET, V124, P637, DOI 10.1007/s00122-011-1736-z
   Berlandier FA, 2003, AUST J EXP AGR, V43, P1357, DOI 10.1071/EA02186
   Bortesi L, 2015, BIOTECHNOL ADV, V33, P41, DOI 10.1016/j.biotechadv.2014.12.006
   Chaves MM, 2003, FUNCT PLANT BIOL, V30, P239, DOI 10.1071/FP02076
   Clements J, 2009, SABRAO J BREED GENET, V41
   Cowling WA, 2009, CROP PASTURE SCI, V60, P1009, DOI 10.1071/CP08223
   COWLING WA, 1998, LUPINS CROP PLANTS B
   Drummond CS, 2012, SYST BIOL, V61, P443, DOI 10.1093/sysbio/syr126
   Edwards OR, 2003, B ENTOMOL RES, V93, P403, DOI 10.1079/BER2003256
   Foley RC, 2015, BMC PLANT BIOL, V15, DOI 10.1186/s12870-015-0485-6
   French RJ, 2001, AUST J AGR RES, V52, P945, DOI 10.1071/AR00084
   Gladstones J. S., 1970, Field Crop Abstracts, V23, P123
   Glazinska P, 2017, FRONT PLANT SCI, V8, DOI 10.3389/fpls.2017.00641
   Glencross B, 2008, LUPINS HLTH WEALTH LUPINS HLTH WEALTH
   Hackbarth J., 1955, Zeitschrift fur Pflanzenzuchtung, V35, P149
   Hackbarth J., 1951, Zeitschrift fur Pflanzenzuchtung, V30, P198
   Hane JK, 2017, PLANT BIOTECHNOL J, V15, P318, DOI 10.1111/pbi.12615
   HONDELMANN W, 1984, THEOR APPL GENET, V68, P1, DOI 10.1007/BF00252301
   Iqbal MM, 2019, GENETICS ADAPTATION
   Iqbal MM, 2019, BMC GENET, V20, DOI 10.1186/s12863-019-0767-3
   Jones RAC, 1996, ANN APPL BIOL, V129, P523, DOI 10.1111/j.1744-7348.1996.tb05774.x
   Kordan B, 2019, J ECON ENTOMOL, V112, P465, DOI 10.1093/jee/toy349
   Kroc M, 2014, THEOR APPL GENET, V127, P1237, DOI 10.1007/s00122-014-2294-y
   Lambers H, 2013, AM J BOT, V100, P263, DOI 10.3732/ajb.1200474
   Lemmon ZH, 2018, NAT PLANTS, V4, P766, DOI 10.1038/s41477-018-0259-x
   Li H, 2000, PLANT CELL REP, V19, P634, DOI 10.1007/s002990050785
   Martin GE, 2014, ANN BOT-LONDON, V113, P1197, DOI 10.1093/aob/mcu050
   Mousavi-Derazmahalleh M, 2018, THEOR APPL GENET, V131, P2543, DOI 10.1007/s00122-018-3171-x
   Mousavi-Derazmahalleh M, 2018, THEOR APPL GENET, V131, P887, DOI 10.1007/s00122-017-3045-7
   Naganowska B, 2003, ANN BOT-LONDON, V92, P349, DOI 10.1093/aob/mcg145
   Nelson MN, 2006, THEOR APPL GENET, V113, P225, DOI 10.1007/s00122-006-0288-0
   Nelson MN, 2017, NEW PHYTOL, V213, P220, DOI 10.1111/nph.14094
   Nelson MN, 2010, DNA RES, V17, P73, DOI 10.1093/dnares/dsq001
   Ogura T, 2014, PROTEOMICS, V14, P1543, DOI 10.1002/pmic.201300511
   Ogura T, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0080369
   Osorio CE, 2018, GENET RESOUR CROP EV, V65, P1281, DOI 10.1007/s10722-018-0613-x
   Osorio CE, 2018, ELECTRON J BIOTECHN, V31, P44, DOI 10.1016/j.ejbt.2017.11.002
   Parra-González LB, 2012, BMC GENOMICS, V13, DOI 10.1186/1471-2164-13-425
   Phan HTT, 2007, DNA RES, V14, P59, DOI 10.1093/dnares/dsm009
   Piornos JA, 2015, FOOD RES INT, V76, P719, DOI 10.1016/j.foodres.2015.07.013
   Robertson NL, 2009, PLANT DIS, V93, DOI 10.1094/PDIS-93-3-0319A
   Sansaloni CP, 2011, BMC Proc, V5, P54, DOI [10.1186/1753-6561-5-S7-P54, DOI 10.1186/1753-6561-5-S7-P54]
   Stinchcombe JR, 2008, HEREDITY, V100, P158, DOI 10.1038/sj.hdy.6800937
   Stoddard FL, 2006, EUPHYTICA, V147, P167, DOI 10.1007/s10681-006-4723-8
   Susek K, 2019, GENES-BASEL, V10, DOI 10.3390/genes10040259
   Susek K, 2016, FRONT PLANT SCI, V7, DOI 10.3389/fpls.2016.01152
   Taylor CM, 2019, PLANT CELL ENVIRON, V42, P174, DOI 10.1111/pce.13320
   Troll H.-J., 1940, ZUCHTER, V12, P129, DOI 10.1007/BF01813207
   Troll H. J., 1940, Pflanzenbau, V16, P403
   Varshney R, 2011, ROOT GENOMICS
   Wolko B, 2011, WILD CROP RELATIVES: GENOMIC AND BREEDING RESOURCES: LEGUME CROPS AND FORAGES, P153, DOI 10.1007/978-3-642-14387-8_9
   Zehnder GW, 2001, ENTOMOL EXP APPL, V98, P259, DOI 10.1023/A:1018935124671
NR 58
TC 4
Z9 4
U1 0
U2 1
PU SPRINGER INTERNATIONAL PUBLISHING AG
PI CHAM
PA GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
SN 2199-4781
EI 2199-479X
BN 978-3-030-21270-4; 978-3-030-21269-8
J9 COMPEND PL GENOME
PY 2020
BP 151
EP 159
DI 10.1007/978-3-030-21270-4_11
D2 10.1007/978-3-030-21270-4
PG 9
WC Biochemistry & Molecular Biology; Plant Sciences; Genetics & Heredity
WE Book Citation Index – Science (BKCI-S)
SC Biochemistry & Molecular Biology; Plant Sciences; Genetics & Heredity
GA BR9XI
UT WOS:000680187600013
DA 2025-01-10
ER

PT J
AU Liu, XF
   Xu, M
   Guo, JL
   Zhu, RJ
AF Liu, Xiangfeng
   Xu, Miao
   Guo, Juanli
   Zhu, Renjie
TI Numerical study on the energy performance of building zones with
   transparent water storage envelopes
SO SOLAR ENERGY
LA English
DT Article
DE Energy performance; Water wall; Transparent water storage envelope;
   Thermal mass; Passive cooling; Energy simulation
AB Researches on water wall passive solar technologies, especially the numerical study on the energy performance of building zones with Transparent Water Storage Envelopes (TWSEs), are reported in this paper. TWSE is a climatic adaptive building envelope consisting of visually transparent modular water containers, exterior shading devices, water supply and return pipes. It is an upgraded water wall that can serve both as an energy efficient facade and an auxiliary water cistern in a building. Currently the energy simulation involving transparent water walls cannot be explicitly done in all energy simulation programs because transparent envelopes are always predefined as the surfaces without thermal mass due to the embedded algorithms complied with ISO15099 standard. A numerical approach based on the integrated energy and computational fluid dynamics (IE&CFD) simulation was developed for solving the energy simulation problem related with TWSEs. A simplified optical model of TWSE was proposed and validated through light transmission testing. Meanwhile, cooling and heating loads of a zone with TWSEs and conventional glazing in summer and winter months were studied. The thermal performance of a TWSE relative to the conventional glazing was also investigated via the comparative thermal box testing. Based on the simulation and testing results, it reveals that TWSEs can exceed most high performance coated glazing with regard to solar radiation control, and they are also exceptional energy efficient transparent envelopes that can outperform the ASHRAE standard window and conventional glazing in terms of cooling and heating load reduction as long as being configured and operated properly according to their physical characteristics and outdoor climatic condition. Furthermore, the innovative technical paradigm of TWSEs, along with the numerical approach developed for their energy simulation, demonstrates a wide range of versatility to be implemented in research and practice for ultra low energy buildings.
C1 [Liu, Xiangfeng; Guo, Juanli; Zhu, Renjie] Tianjin Univ, Sch Architecture, 92 Weijin Rd, Tianjin 300072, Peoples R China.
   [Xu, Miao] KTH Royal Inst Technol, Sch Architecture & Built Environm, S-10044 Stockholm, Sweden.
C3 Tianjin University; Royal Institute of Technology
RP Liu, XF (corresponding author), Tianjin Univ, Sch Architecture, 92 Weijin Rd, Tianjin 300072, Peoples R China.
EM archliuxf@163.com
OI Liu, Xiangfeng/0000-0003-0138-4782
CR ANSYS Inc, 2009, DISCR ORD DO RAD MOD
   ASHRAE, 2016, ASHRAE Standard 90.1
   Bainbridge A. D, 1981, WATER WALL SOLAR DES
   Crawley DB, 2008, BUILD ENVIRON, V43, P661, DOI 10.1016/j.buildenv.2006.10.027
   Davis C, 1993, BRIT PAVILION SEVILL
   Fernández-González A, 2007, SOL ENERGY, V81, P581, DOI 10.1016/j.solener.2006.09.010
   Flagge I, 2002, T HERZOG ARCHITECTUR, P14
   HALE GM, 1973, APPL OPTICS, V12, P555, DOI 10.1364/AO.12.000555
   International Organization for Standardisation, 2003, 15099 ISO
   Lawrence Berkeley National Laboratory (LBNL), 2018, IGDB INT GLAZ DAT
   LBNL, 2018, OPTICS KNOWL BAS
   Liu X. J., 2012, Master's thesis
   Liu XF, 2019, J BUILD PHYS, V42, P692, DOI 10.1177/1744259118789452
   McClelland J.F., 1981, Patent, Patent No. [US4286576, 4286576]
   NACO, 2018, MET LOUV GLASS LOUV
   National Renewable Energy Laboratory (NREL), 2018, ENERGYPLUS DOC ENG R
   Paul J.K., 1979, Passive Solar Energy Design and Materials
   Pittsley J, 2008, TROMBE WALL ENERGY E
   Robinson BS, 2013, SOL ENERGY, V87, P76, DOI 10.1016/j.solener.2012.10.008
   Sanders M. R, 2006, CURTAIN WALLS NOT JU
   Scott P, 2018, OPTICAL ABSORPTION W
   U.S. Department of Energy, 2009, SOL DEC 2009 U AR
   US EIA, 2018, CONS EFF
   Wang WL, 2013, ENERG BUILDINGS, V64, P218, DOI 10.1016/j.enbuild.2013.05.007
   Wu T, 2016, SOL ENERGY, V136, P533, DOI 10.1016/j.solener.2016.07.026
   Wu T, 2016, SOL ENERGY, V133, P141, DOI 10.1016/j.solener.2016.04.001
   Xiangfeng Liu., 2007, Architectural Science Review, V50, P18, DOI DOI 10.3763/ASRE.2007.5003
   Xiangfeng Liu., 2008, Architectural Science Review, V51, P109
NR 28
TC 9
Z9 9
U1 0
U2 28
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0038-092X
EI 1471-1257
J9 SOL ENERGY
JI Sol. Energy
PD MAR 1
PY 2019
VL 180
BP 690
EP 706
DI 10.1016/j.solener.2019.01.044
PG 17
WC Energy & Fuels
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Energy & Fuels
GA HU1VN
UT WOS:000465060000060
DA 2025-01-10
ER

PT J
AU Xu, H
   Huang, Q
   Liu, G
   Zhang, Q
AF Xu, Hong
   Huang, Qiong
   Liu, Gang
   Zhang, Qi
TI A quantitative study of the climate-responsive design strategies of
   ancient timber-frame halls in northern China based on field measurements
SO ENERGY AND BUILDINGS
LA English
DT Article
DE Ancient timber-frame hall; Cold region; Climate responsive design;
   Thermal comfort; Field measurement
ID KERALA TRADITIONAL ARCHITECTURE; COMFORTABLE INDOOR ENVIRONMENT; PASSIVE
   CONTROL METHODS; SUMMER; BUILDINGS; DWELLINGS; VILLAGE; REGION; HOUSES;
   WINTER
AB The risks of global warming and the depletion of fossil fuels call for a re-examination of traditional buildings, which have shown satisfactory climate adaptability. Although vernacular dwellings have received considerable attention, few studies investigate other building types. In this paper, the thermal environments of ancient timber-frame halls in northern China were investigated based on field measurements to obtain more evidence of traditional ecological ideology and related strategies. As one of the main types of public buildings in ancient China, six typical halls with different orientations, openings, and ceilings but similar spatial scales and materials were selected; their air temperature, relative humidity (RH), air speed, surface temperature, and globe temperature on typical summer and winter days were measured. The results show that the indoor air temperature of the ancient halls under free-running conditions fluctuated between 22.52 and 29.46 degrees C in summer and between -8.91 and -2.64 degrees C in winter, meaning that the indoor environments are comfortable in summer but too cold in winter according to GB/T 50785-2012, which is the Chinese standard for evaluating indoor thermal environments. Further analysis shows that the key strategy for comfort in summer is to have high heat capacity to provide shelter from hot air and solar gains; natural ventilation is considered to be merely an auxiliary approach. Climate-responsive design strategies for winter consist of a south-facing orientation with a maximum window-to-wall ratio and significant thermal insulation to utilize solar gains and to provide shelter from cold air. In addition, the results reveal that ancient halls are limited in their ability to use climatic resources due to technical restrictions. (C) 2016 Elsevier B.V. All rights reserved.
C1 [Xu, Hong; Huang, Qiong; Liu, Gang; Zhang, Qi] Tianjin Univ, Sch Architecture, Tianjin 300072, Peoples R China.
C3 Tianjin University
RP Huang, Q (corresponding author), Tianjin Univ, Sch Architecture, Tianjin 300072, Peoples R China.
EM amy.xuhong@outlook.com; qhuang@tju.edu.cn; lglgmike@163.com;
   zhangqi_arch@vip.163.com
FU National Natural Science Foundation of China [51338006]; Programme of
   Introducing Talents of Discipline to Universities [B13011]
FX This research was financially supported by the National Natural Science
   Foundation of China (Grant No. 51338006) and by the Programme of
   Introducing Talents of Discipline to Universities (No. B13011). We would
   like to thank the Institute of Architectural History and Theory in
   School of Architecture, Tianjin University, for providing the valuable
   drawings of ancient Chinese buildings.
CR [Anonymous], 1970, Thermal Comfort
   [Anonymous], 2005, ERGONOMICS THERMAL E
   [Anonymous], 2004, THERMAL ENV CONDITIO
   [Anonymous], 1993, 5017693 GB
   Asan H, 2006, BUILD ENVIRON, V41, P615, DOI 10.1016/j.buildenv.2005.02.020
   Asan H, 2000, ENERG BUILDINGS, V32, P197, DOI 10.1016/S0378-7788(00)00044-X
   Bouillot J, 2008, J ENVIRON MANAGE, V87, P287, DOI 10.1016/j.jenvman.2006.10.029
   Cantin R, 2010, BUILD ENVIRON, V45, P473, DOI 10.1016/j.buildenv.2009.07.010
   Climatic Data Center of CMA National Meteorological Information Center Department of Building Science and Technology of Tsinghua University, 2005, MET DAT SET BUILD TH
   de Dear RJ, 2002, ENERG BUILDINGS, V34, P549, DOI 10.1016/S0378-7788(02)00005-1
   Dedear R., 1998, ASHRAE T, V104
   Dili AS, 2011, ENERG BUILDINGS, V43, P653, DOI 10.1016/j.enbuild.2010.11.006
   Dili AS, 2010, BUILD ENVIRON, V45, P2218, DOI 10.1016/j.buildenv.2010.04.002
   Dili AS, 2010, ENERG BUILDINGS, V42, P917, DOI 10.1016/j.enbuild.2010.01.002
   Dili AS, 2010, BUILD ENVIRON, V45, P1134, DOI 10.1016/j.buildenv.2009.10.018
   GB/T, 2012, GB/T 50785-2012
   Gou SQ, 2015, BUILD ENVIRON, V86, P151, DOI 10.1016/j.buildenv.2014.12.003
   Indraganti M, 2010, BUILD ENVIRON, V45, P2709, DOI 10.1016/j.buildenv.2010.05.030
   Kim TJ, 2010, BUILD ENVIRON, V45, P51, DOI 10.1016/j.buildenv.2009.05.016
   Lee KH, 1996, ENERG BUILDINGS, V23, P207, DOI 10.1016/0378-7788(95)00946-9
   Lin BR, 2004, ENERG BUILDINGS, V36, P73, DOI 10.1016/S0378-7788(03)00090-2
   Manioglu G, 2008, BUILD ENVIRON, V43, P1301, DOI 10.1016/j.buildenv.2007.03.014
   National Bureau of Statistics of the People's Republic China, 2006, INT STAT YB 2006
   Nguyen AT, 2011, BUILD ENVIRON, V46, P2088, DOI 10.1016/j.buildenv.2011.04.019
   Oikonomou A, 2011, BUILD ENVIRON, V46, P669, DOI 10.1016/j.buildenv.2010.09.012
   Ooka R, 2002, BUILD ENVIRON, V37, P319, DOI 10.1016/S0360-1323(00)00085-8
   People's Education Press, 2015, 8 GRADE GEOGRAPHY
   Singh MK, 2010, BUILD ENVIRON, V45, P320, DOI 10.1016/j.buildenv.2009.06.009
   Singh MK, 2009, BUILD ENVIRON, V44, P878, DOI 10.1016/j.buildenv.2008.06.008
   Sözen MS, 2007, BUILD ENVIRON, V42, P1810, DOI 10.1016/j.buildenv.2006.01.019
   Tzikopoulos AF, 2005, ENERG BUILDINGS, V37, P529, DOI 10.1016/j.enbuild.2004.09.002
NR 31
TC 15
Z9 15
U1 8
U2 99
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 2016
VL 133
BP 306
EP 320
DI 10.1016/j.enbuild.2016.09.047
PG 15
WC Construction & Building Technology; Energy & Fuels; Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Energy & Fuels; Engineering
GA ED7XZ
UT WOS:000389087300029
DA 2025-01-10
ER

PT J
AU Chapman, S
   Watson, JEM
   McAlpine, CA
AF Chapman, S.
   Watson, J. E. M.
   McAlpine, C. A.
TI Large seasonal and diurnal anthropogenic heat flux across four
   Australian cities
SO JOURNAL OF SOUTHERN HEMISPHERE EARTH SYSTEMS SCIENCE
LA English
DT Article
ID URBAN CLIMATE; EXTREME HEAT; IMPACT; EMISSIONS; MELBOURNE; MORTALITY;
   TEMPERATURE; MORBIDITY; TOKYO; DISCHARGES
AB Anthropogenic heat release is a key component of the urban heat island. However, it is often excluded from studies of the urban heat island because reliable estimates are not available. This omission is important because anthropogenic heat can contribute up to 4 degrees C to the urban heat island, and increases heat stress to urban residents. The exclusion of anthropogenic heat means the urban heat is-land effect on temperatures may be under-estimated. Here we estimate anthropogenic heat for four Australian capital cities (Brisbane, Sydney, Melbourne and Adelaide) to inform the management of the urban heat island in a changing climate. Anthropogenic heat release was calculated using 2011 population census data and an inventory of hourly traffic volume, building electricity and gas use. Melbourne had the highest annual daily average anthropogenic heat emissions, which reached 376 W/m(2) in the city centre during the daytime, while Brisbane's emissions were 261 W/m2 and Sydney's were 256 W/m(2). Adelaide had the lowest emissions, with a daily average of 39 W/m(2) in the city centre. Emissions varied within and among the four cities and decreased rapidly with distance from the city centre, to < 5 W/m(2) at 20 km from the city in Brisbane, and 15 km in Adelaide. The highest emissions were found in the city centres during working hours. The peak emissions reached in the centre of Melbourne are similar to the peak emissions in London and Tokyo, where anthropogenic heat is a large component of the urban heat island. This indicates that anthropogenic heat could be an important contributor to the urban heat island in Australian capital cities, and needs to be considered in climate adaptation studies. This is an important problem because climate change, combined with an ageing population and urban growth, could double the deaths from heatwaves in Australian cities over the next 40 years.
C1 [Chapman, S.; Watson, J. E. M.; McAlpine, C. A.] Univ Queensland, Sch Geog Planning & Environm Management, Brisbane, Qld, Australia.
   [Watson, J. E. M.] Wildlife Conservat Soc, Global Conservat Program, New York, NY USA.
C3 University of Queensland; Wildlife Conservation Society
RP Chapman, S (corresponding author), Univ Queensland, Sch Geog Planning & Environm Management, St Lucia, Qld 4072, Australia.
EM s.chapman@uq.edu.au
RI McAlpine, Clive/A-3907-2010; Chapman, Sarah/ABB-4800-2021; Watson,
   James/D-8779-2013
OI McAlpine, Clive/0000-0003-0457-8144; Watson, James/0000-0003-4942-1984;
   Chapman, Sarah/0000-0002-3141-8616
CR Allen L, 2011, INT J CLIMATOL, V31, P1990, DOI 10.1002/joc.2210
   [Anonymous], STATSTAT AUSTR CIT 2
   [Anonymous], 3218 0 REG POP GROWT
   [Anonymous], 2007, EST URB TRAFF CONG C
   [Anonymous], SUMM STAT BRISBANE A
   [Anonymous], 2011, Main Structure and Greater Capital City Statistical Areas
   [Anonymous], 2010, AUSTRALASIAN TRANSPO
   [Anonymous], J ENV PLANNING MANAG
   [Anonymous], 2013, 3218 0 REG POP GROWT
   [Anonymous], 9208 0 SURV MOT VEH
   [Anonymous], GUID AUSTR EN STAT
   [Anonymous], ACT FLOW
   [Anonymous], AGGR PRIC DEM 2011 2
   [Anonymous], 30 MIN VOL ANN EDW S
   [Anonymous], SUMM STAT MELBOURNE
   [Anonymous], 2014, PLAN GROW SYDN
   [Anonymous], SUMM STAT ADELAIDE
   [Anonymous], 1367 0 STAT TERR STA
   [Anonymous], MELB CBD
   [Anonymous], CLIM CLASS MAPS
   [Anonymous], SYDN TRAFF COUNT DAT
   [Anonymous], STAT AR LEV 2 SA2 AS
   [Anonymous], J APPL METEOROLOGY C
   [Anonymous], P NDR96 C NAT DIS RE
   [Anonymous], 2014 AUSTR EN UPD
   [Anonymous], 4604 0 EN ACC
   [Anonymous], TYP HOURL TRAFF VOL
   [Anonymous], 2013, BRISB VIS 2031
   [Anonymous], 2011, CENS POP HOUS
   [Anonymous], 2014, DEMOGR RES
   Argüeso D, 2014, CLIM DYNAM, V42, P2183, DOI 10.1007/s00382-013-1789-6
   Australian Bureau of Statistics, 2013, POP PROJ AUSTR 2012
   Bi P, 2011, ASIA-PAC J PUBLIC HE, V23, p27S, DOI 10.1177/1010539510391644
   Black MT, 2015, B AM METEOROL SOC, V96, pS145, DOI 10.1175/BAMS-D-15-00097.1
   Bohnenstengel SI, 2014, Q J ROY METEOR SOC, V140, P687, DOI 10.1002/qj.2144
   Coutts AM, 2008, INT J CLIMATOL, V28, P1943, DOI 10.1002/joc.1680
   Coutts AM, 2007, J APPL METEOROL CLIM, V46, P477, DOI 10.1175/JAM2462.1
   Cowan T, 2014, J CLIMATE, V27, P5851, DOI 10.1175/JCLI-D-14-00092.1
   Dhakal S, 2004, ENERG CONVERS MANAGE, V45, P1107, DOI 10.1016/j.enconman.2003.08.012
   Dhakal S, 2003, ENERG CONVERS MANAGE, V44, P1487, DOI 10.1016/S0196-8904(02)00145-0
   Fan HL, 2005, ATMOS ENVIRON, V39, P73, DOI 10.1016/j.atmosenv.2004.09.031
   Ferreira MJ, 2011, THEOR APPL CLIMATOL, V104, P43, DOI 10.1007/s00704-010-0322-7
   Fischer EM, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2011GL050576
   Guan L, 2009, BUILD RES INF, V37, P43, DOI 10.1080/09613210802611025
   Hajat S, 2010, LANCET, V375, P856, DOI 10.1016/S0140-6736(09)61711-6
   Hallenbeck M., 1997, Vehicle volume distributions by classification
   Hanna EG, 2011, ASIA-PAC J PUBLIC HE, V23, p14S, DOI 10.1177/1010539510391457
   Hondula DM, 2014, ENVIRON HEALTH PERSP, V122, P831, DOI 10.1289/ehp.1307496
   Hughes L., 2016, SILENT KILLER CLIMAT
   Ichinose T, 1999, ATMOS ENVIRON, V33, P3897, DOI 10.1016/S1352-2310(99)00132-6
   Keay K, 2005, ACCIDENT ANAL PREV, V37, P109, DOI 10.1016/j.aap.2004.07.005
   Khan SM, 2001, BOUND-LAY METEOROL, V100, P487, DOI 10.1023/A:1019284332306
   KIMURA F, 1991, ATMOS ENVIRON B-URB, V25, P155, DOI 10.1016/0957-1272(91)90050-O
   Kobayashi T, 2011, PROF GEOGR, V63, P113, DOI 10.1080/00330124.2010.533565
   Kusaka H, 2012, J METEOROL SOC JPN, V90B, P47, DOI 10.2151/jmsj.2012-B04
   Laaidi K, 2012, ENVIRON HEALTH PERSP, V120, P254, DOI 10.1289/ehp.1103532
   Lee SH, 2009, THEOR APPL CLIMATOL, V96, P291, DOI 10.1007/s00704-008-0040-6
   Luber G, 2008, AM J PREV MED, V35, P429, DOI 10.1016/j.amepre.2008.08.021
   McGeehin MA, 2001, ENVIRON HEALTH PERSP, V109, P185, DOI 10.2307/3435008
   Medina-Ramón M, 2007, OCCUP ENVIRON MED, V64, P827, DOI 10.1136/oem.2007.033175
   Menut L, 2012, ATMOS ENVIRON, V49, P233, DOI 10.1016/j.atmosenv.2011.11.057
   Milojevic A, 2011, EPIDEMIOLOGY, V22, pS182, DOI 10.1097/01.ede.0000392239.91165.65
   OKE TR, 1988, PROG PHYS GEOG, V12, P471, DOI 10.1177/030913338801200401
   Palmer G, 2012, SUSTAINABILITY-BASEL, V4, P1525, DOI 10.3390/su4071525
   Peel MC, 2007, HYDROL EARTH SYST SC, V11, P1633, DOI 10.5194/hess-11-1633-2007
   Quah AKL, 2012, ATMOS ENVIRON, V46, P92, DOI 10.1016/j.atmosenv.2011.10.015
   R Core Team, 2015, R LANG ENV STAT COMP
   Sailor DJ, 2015, ATMOS ENVIRON, V118, P7, DOI 10.1016/j.atmosenv.2015.07.016
   Sailor DJ, 2011, INT J CLIMATOL, V31, P189, DOI 10.1002/joc.2106
   Sailor DJ, 2004, ATMOS ENVIRON, V38, P2737, DOI 10.1016/j.atmosenv.2004.01.034
   Smith C, 2009, THEOR APPL CLIMATOL, V98, P19, DOI 10.1007/s00704-008-0086-5
   Taha H, 1997, ENERG BUILDINGS, V25, P99, DOI 10.1016/S0378-7788(96)00999-1
   Wienert U, 2005, METEOROL Z, V14, P677, DOI 10.1127/0941-2948/2005/0069
NR 73
TC 12
Z9 14
U1 1
U2 20
PU CSIRO PUBLISHING
PI CLAYTON
PA UNIPARK, BLDG 1, LEVEL 1, 195 WELLINGTON RD, LOCKED BAG 10, CLAYTON, VIC
   3168, AUSTRALIA
EI 2206-5865
J9 J SO HEMISPH EARTH
JI J. South Hemisph. Earth Syst. Sci.
PY 2016
VL 66
IS 3
BP 342
EP 360
PG 19
WC Meteorology & Atmospheric Sciences; Oceanography
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences; Oceanography
GA ED7NX
UT WOS:000389054200006
DA 2025-01-10
ER

PT J
AU Townsend, PA
   Masters, KL
AF Townsend, Patricia A.
   Masters, Karen L.
TI Lattice-work corridors for climate change: a conceptual framework for
   biodiversity conservation and social-ecological resilience in a tropical
   elevational gradient
SO ECOLOGY AND SOCIETY
LA English
DT Article
DE buffer capacity; climate adaptation; community involvement; conservation
   incentives; Costa Rica; environmental services payments; forest
   landscape restoration; habitat priority-setting; landscape connectivity;
   reforestation; resilient ecosystems; resilient livelihoods; riparian
   zones; tropical mountain ecosystems
ID ADAPTIVE MANAGEMENT; RANGE SHIFTS; AGRICULTURAL LANDSCAPES;
   ENVIRONMENTAL SERVICES; AGROFORESTRY SYSTEMS; REMNANT TREES; LAND
   FACETS; CONNECTIVITY; DIVERSITY; FORESTS
AB Rapid climate change poses complex challenges for conservation, especially in tropical developing countries where biodiversity is high while financial and technical resources are limited. The complexity is heightened by uncertainty in predicted effects, both for ecological systems and human communities that depend heavily on natural resource extraction and use. Effective conservation plans and measures must be inexpensive, fast-acting, and able to increase the resilience of both the ecosystem and the social-ecological system. We present conservation practitioners with a framework that strategically integrates climate change planning into connectivity measures for tropical mountain ecosystems in Costa Rica. We propose a strategy for doubling the amount of habitat currently protected in riparian corridors using measures that are relatively low cost and fast-acting, and will employ and expand human capital. We argue that habitat connectivity must be enhanced along latitudinal gradients, but also within the same elevational bands, via a lattice-work corridor system. This is needed to facilitate range shifts for mobile species and evolutionary adaptation for less mobile species. We think that conservation measures within the elevational bands must include conservation-friendly land uses that improve current and future human livelihoods under dynamic conditions. Key components include community involvement, habitat priority-setting, forest landscape restoration, and environmental services payments. Our approach is fundamentally adaptive in that the conservation measures employed are informed by on-the-ground successes and failures and modified accordingly, but are relatively low risk and fast-acting. Our proposal, if implemented, would satisfy tenets of climate-smart conservation, improve the resilience of human and ecological communities, and be a model for other locations facing similar challenges.
C1 [Townsend, Patricia A.] Univ Washington, Seattle, WA 98195 USA.
   [Masters, Karen L.] Council Int Educ Exchange, Sao Paulo, Brazil.
C3 University of Washington; University of Washington Seattle
RP Townsend, PA (corresponding author), Univ Washington, Seattle, WA 98195 USA.
FU United States Environmental Protection Agency (EPA) under the Science to
   Achieve Results (STAR) Graduate Fellowship Program; National Garden
   Club; Groom lab
FX M. Groom, J. Lawler, N. Nadkarni, J. Hoffman, S. Riechard, and the Groom
   and Lawler labs provided helpful comments on earlier drafts. Suggestions
   from three anonymous reviewers also greatly improved the manuscript. C.
   Gomez assisted with map making. Funding for P. A. Townsend came from the
   United States Environmental Protection Agency (EPA) under the Science to
   Achieve Results (STAR) Graduate Fellowship Program. EPA has not
   officially endorsed this publication, and these views may not reflect
   those of EPA. Additional funding for P. A. Townsend came from the
   National Garden Club and the Groom lab.
CR [Anonymous], PLAN ESTR PROGR NAC
   [Anonymous], 2012, SPECIAL REPORT WORKI
   [Anonymous], MONTEVERDE ECOLOGY C
   [Anonymous], 2012, WEARING UNCERTAIN
   Beier P, 2010, CONSERV BIOL, V24, P701, DOI 10.1111/j.1523-1739.2009.01422.x
   Bennett G., 2004, Integrating biodiversity conservation and sustainable use: Lessons learned from ecological networks
   Berkes F, 2000, ECOL APPL, V10, P1251, DOI 10.2307/2641280
   Burlingame L. J., 2000, Monteverde: ecology and conservation of a tropical cloud forest., P351
   Colwell RK, 2008, SCIENCE, V322, P258, DOI 10.1126/science.1162547
   Davis MB, 2001, SCIENCE, V292, P673, DOI 10.1126/science.292.5517.673
   Dawson IK, 2013, BIODIVERS CONSERV, V22, P301, DOI 10.1007/s10531-012-0429-5
   Dawson TP, 2011, SCIENCE, V332, P53, DOI 10.1126/science.1200303
   Early R, 2011, ECOL LETT, V14, P1125, DOI 10.1111/j.1461-0248.2011.01681.x
   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
   Foster P, 2001, EARTH-SCI REV, V55, P73, DOI 10.1016/S0012-8252(01)00056-3
   Haber WA., 2000, MONTEVERDE, P39
   Haber WA., 1996, An introduction to cloud forest trees: Monteverde, Costa Rica
   Hannah L, 2008, BIOL LETTERS, V4, P590, DOI 10.1098/rsbl.2008.0270
   Hansen L, 2010, CONSERV BIOL, V24, P63, DOI 10.1111/j.1523-1739.2009.01404.x
   Harris JA, 2006, RESTOR ECOL, V14, P170, DOI 10.1111/j.1526-100X.2006.00136.x
   Harvey CA, 1998, AGROFOREST SYST, V44, P37, DOI 10.1023/A:1006122211692
   Harvey CA, 2000, ECOL APPL, V10, P155, DOI 10.1890/1051-0761(2000)010[0155:WESDIA]2.0.CO;2
   Harvey CA, 2000, ECOL APPL, V10, P1762, DOI 10.1890/1051-0761(2000)010[1762:COAWBF]2.0.CO;2
   Harvey CA, 2008, CONSERV BIOL, V22, P8, DOI 10.1111/j.1523-1739.2007.00863.x
   Harvey CA, 2007, BIODIVERS CONSERV, V16, P2257, DOI 10.1007/s10531-007-9194-2
   Hoegh-Guldberg O, 2008, SCIENCE, V321, P345, DOI 10.1126/science.1157897
   HOLDRIDGE L R, 1966, Adansonia, V6, P199
   Holling C.S., 1973, Annual Rev Ecol Syst, V4, P1, DOI 10.1146/annurev.es.04.110173.000245
   HUNTER ML, 1988, CONSERV BIOL, V2, P375, DOI 10.1111/j.1523-1739.1988.tb00202.x
   Kartzinel TR, 2013, J ECOL, V101, P1429, DOI 10.1111/1365-2745.12145
   Krosby M, 2010, CONSERV BIOL, V24, P1686, DOI 10.1111/j.1523-1739.2010.01585.x
   Lawler JJ, 2010, FRONT ECOL ENVIRON, V8, P35, DOI 10.1890/070146
   Lawton R. O., 1980, BRENESIA, V8, P101
   León MC, 2006, AGROFOREST SYST, V68, P15, DOI 10.1007/s10457-005-5831-5
   Lugo AE, 2009, BIOTROPICA, V41, P589, DOI 10.1111/j.1744-7429.2009.00550.x
   MURCIA C, 1995, TRENDS ECOL EVOL, V10, P58, DOI 10.1016/S0169-5347(00)88977-6
   National Research Council, 2010, WORKSH
   Nelson DR, 2007, ANNU REV ENV RESOUR, V32, P395, DOI 10.1146/annurev.energy.32.051807.090348
   Newton AC, 2012, ECOL SOC, V17, DOI 10.5751/ES-04572-170121
   Nielsen K., 2000, Monteverde: Ecology and Conservation of a Tropical Cloud Forest, P448
   Olsson P, 2004, ENVIRON MANAGE, V34, P75, DOI 10.1007/s00267-003-0101-7
   Pounds JA, 2006, NATURE, V439, P161, DOI 10.1038/nature04246
   Pounds JA, 1999, NATURE, V398, P611, DOI 10.1038/19297
   Raxworthy CJ, 2008, GLOBAL CHANGE BIOL, V14, P1703, DOI 10.1111/j.1365-2486.2008.01596.x
   Ray DK, 2009, J GEOPHYS RES-ATMOS, V114, DOI 10.1029/2007JD009565
   Raymond CM, 2010, J ENVIRON MANAGE, V91, P1766, DOI 10.1016/j.jenvman.2010.03.023
   Reed MS, 2008, BIOL CONSERV, V141, P2417, DOI 10.1016/j.biocon.2008.07.014
   Resasco J, 2014, ECOLOGY, V95, P2033, DOI 10.1890/14-0169.1
   Root TL, 2005, P NATL ACAD SCI USA, V102, P7465, DOI 10.1073/pnas.0502286102
   Seastedt TR, 2008, FRONT ECOL ENVIRON, V6, P547, DOI 10.1890/070046
   Sinclair SJ, 2010, ECOL SOC, V15, DOI 10.5751/ES-03089-150108
   Stork NE, 2009, CONSERV BIOL, V23, P1438, DOI 10.1111/j.1523-1739.2009.01335.x
   Stringer LC, 2006, ECOL SOC, V11
   Swallow BM, 2009, ECOL SOC, V14
   Tompkins EL, 2004, ECOL SOC, V9
   Townsend P. A., 2011, THESIS U WASHINGTON
   Walker B, 2004, ECOL SOC, V9
   Wessels KJ, 1999, BIOL CONSERV, V89, P21, DOI 10.1016/S0006-3207(98)00133-5
   Williams JW, 2007, FRONT ECOL ENVIRON, V5, P475, DOI 10.1890/070037
   Wunder S, 2007, CONSERV BIOL, V21, P48, DOI 10.1111/j.1523-1739.2006.00559.x
   Zuchowski W., 2007, TROPICAL PLANTS COST
NR 62
TC 26
Z9 30
U1 1
U2 77
PU RESILIENCE ALLIANCE
PI WOLFVILLE
PA ACADIA UNIV, BIOLOGY DEPT, WOLFVILLE, NS B0P 1X0, CANADA
SN 1708-3087
J9 ECOL SOC
JI Ecol. Soc.
PY 2015
VL 20
IS 2
AR 1
DI 10.5751/ES-07324-200201
PG 11
WC Ecology; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA CM3ZB
UT WOS:000357622800006
OA Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Wadsworth, CB
   Woods, WA
   Hahn, DA
   Dopman, EB
AF Wadsworth, C. B.
   Woods, W. A.
   Hahn, D. A.
   Dopman, E. B.
TI One phase of the dormancy developmental pathway is critical for the
   evolution of insect seasonality
SO JOURNAL OF EVOLUTIONARY BIOLOGY
LA English
DT Article
DE diapause; dormancy; European corn borer; life history; physiology;
   speciation
ID EUROPEAN CORN-BORER; PITCHER-PLANT MOSQUITO; LIFE-HISTORY TRAITS;
   FLOWERING TIME GENE; OXYGEN-CONSUMPTION; PUPAL DIAPAUSE; PHOTOPERIODIC
   RESPONSE; GEOGRAPHIC-VARIATION; CLIMATIC ADAPTATION; PHEROMONE STRAINS
AB Evolutionary change in the timing of dormancy enables animals and plants to adapt to changing seasonal environments and can result in ecological speciation. Despite its clear biological importance, the mechanisms underlying the evolution of dormancy timing in animals remain poorly understood because of a lack of anatomical landmarks to discern which phase of dormancy an individual is experiencing. Taking advantage of the nearly universal characteristic of metabolic suppression during insect dormancy (diapause), we use patterns of respiratory metabolism to document physiological landmarks of dormancy and test which of the distinct phases of the dormancy developmental pathway contribute to a month-long shift in diapause timing between a pair of incipient moth species. Here, we show that divergence in life cycle between the earlier-emerging E-strain and the later-emerging Z-strain of European corn borer (ECB) is clearly explained by a delay in the timing of the developmental transition from the diapause maintenance phase to the termination phase. Along with recent findings indicating that life-cycle differences between ECB strains stem from allelic variation at a single sex-linked locus, our results demonstrate how dramatic shifts in animal seasonality can result from simple developmental and genetic changes. Although characterizing the multiple phases of the diapause developmental programme in other locally adapted populations and species will undoubtedly yield surprises about the nature of animal dormancy, results in the ECB moth suggest that focusing on genetic variation in the timing of the dormancy termination phase may help explain how (or whether) organisms rapidly respond to global climate change, expand their ranges after accidental or managed introductions, undergo seasonal adaptation, or evolve into distinct species through allochronic isolation.
C1 [Wadsworth, C. B.; Woods, W. A.; Dopman, E. B.] Tufts Univ, Dept Biol, Medford, MA 02155 USA.
   [Hahn, D. A.] Univ Florida, Dept Entomol & Nematol, Gainesville, FL 32611 USA.
C3 Tufts University; State University System of Florida; University of
   Florida
RP Dopman, EB (corresponding author), Tufts Univ, Dept Biol, 200 Boston Ave, Medford, MA 02155 USA.
EM erik.dopman@tufts.edu
RI Hahn, Daniel/B-6971-2012
OI Hahn, Daniel/0000-0003-0165-7488; Dopman, Erik/0000-0002-8633-5527
FU USDA [2010-65106-20610]; NSF [DEB-1257251, IOS-1051890, 2011116050];
   Division Of Environmental Biology; Direct For Biological Sciences
   [1257251] Funding Source: National Science Foundation; Division Of
   Integrative Organismal Systems; Direct For Biological Sciences [1051890]
   Funding Source: National Science Foundation
FX We would like to thank the DopChewLew laboratory group for advice and
   comments on an early version of the manuscript and Jeff Feder and Greg
   Ragland for insightful discussions on the evolution of insect life
   cycles. The study was supported by the USDA (EBD: 2010-65106-20610) and
   NSF (EBD: DEB-1257251; DAH: IOS-1051890; CBW: 2011116050).
CR ADEDOKUN TA, 1985, J INSECT PHYSIOL, V31, P229, DOI 10.1016/0022-1910(85)90124-6
   ALEXANDER RD, 1968, Q REV BIOL, V43, P1, DOI 10.1086/405628
   [Anonymous], 2004, Speciation
   BECK SD, 1960, J INSECT PHYSIOL, V4, P304, DOI 10.1016/0022-1910(60)90056-1
   BECK SD, 1964, AM NAT, V98, P329, DOI 10.1086/282330
   Bradshaw WE, 2008, MOL ECOL, V17, P157, DOI 10.1111/j.1365-294X.2007.03509.x
   Bradshaw WE, 1998, ECOLOGY, V79, P1458, DOI 10.1890/0012-9658(1998)079[1458:FCOHDI]2.0.CO;2
   Bradshaw WE, 2004, EVOLUTION, V58, P1748, DOI 10.1111/j.0014-3820.2004.tb00458.x
   Bradshaw WE, 2001, P NATL ACAD SCI USA, V98, P14509, DOI 10.1073/pnas.241391498
   Bradshaw WE, 2006, SCIENCE, V312, P1477, DOI 10.1126/science.1127000
   Caffrey D.J., 1927, A progress report on the investigations of the European corn borer
   Caicedo AL, 2004, P NATL ACAD SCI USA, V101, P15670, DOI 10.1073/pnas.0406232101
   CHAPLIN SB, 1982, ECOL ENTOMOL, V7, P249, DOI 10.1111/j.1365-2311.1982.tb00664.x
   Chiang GCK, 2011, MOL ECOL, V20, P3336, DOI 10.1111/j.1365-294X.2011.05181.x
   Chiang GCK, 2009, P NATL ACAD SCI USA, V106, P11661, DOI 10.1073/pnas.0901367106
   Coles ND, 2010, GENETICS, V184, P799, DOI 10.1534/genetics.109.110304
   Denlinger D.L., 2005, P615
   DENLINGER DL, 1972, J INSECT PHYSIOL, V18, P871, DOI 10.1016/0022-1910(72)90026-1
   DENLINGER DL, 1981, EVOLUTION, V35, P1247, DOI 10.1111/j.1558-5646.1981.tb04993.x
   Denlinger DL, 2002, ANNU REV ENTOMOL, V47, P93, DOI 10.1146/annurev.ento.47.091201.145137
   Dopman EB, 2005, P NATL ACAD SCI USA, V102, P14706, DOI 10.1073/pnas.0502054102
   Dopman EB, 2010, EVOLUTION, V64, P881, DOI 10.1111/j.1558-5646.2009.00883.x
   ECKENRODE CJ, 1983, ENVIRON ENTOMOL, V12, P393, DOI 10.1093/ee/12.2.393
   Feder JL, 1999, ENTOMOL EXP APPL, V91, P211, DOI 10.1023/A:1003603918154
   Filchak KE, 2000, NATURE, V407, P739, DOI 10.1038/35037578
   GLOVER TJ, 1992, ARCH INSECT BIOCHEM, V20, P107, DOI 10.1002/arch.940200203
   GLOVER TJ, 1991, ENVIRON ENTOMOL, V20, P1356, DOI 10.1093/ee/20.5.1356
   Gomi T, 2007, ENTOMOL EXP APPL, V125, P179, DOI 10.1111/j.1570-7458.2007.00616.x
   Hahn DA, 2007, J INSECT PHYSIOL, V53, P760, DOI 10.1016/j.jinsphys.2007.03.018
   Hodek I, 2002, EUR J ENTOMOL, V99, P163, DOI 10.14411/eje.2002.024
   Hung HY, 2012, P NATL ACAD SCI USA, V109, pE1913, DOI 10.1073/pnas.1203189109
   Kostál V, 2006, J INSECT PHYSIOL, V52, P113, DOI 10.1016/j.jinsphys.2005.09.008
   Kostal V, 1998, J INSECT PHYSIOL, V44, P165, DOI 10.1016/S0022-1910(97)00047-4
   Kunte K, 2011, PLOS GENET, V7, DOI 10.1371/journal.pgen.1002274
   LIEBHERR J, 1975, ANN ENTOMOL SOC AM, V68, P305, DOI 10.1093/aesa/68.2.305
   Lighton JRB, 2019, MEASURING METABOLIC RATES: A MANUAL FOR SCIENTISTS, 2ND EDITION, DOI 10.1093/oso/9780198830399.001.0001
   Mathias D, 2007, GENETICS, V176, P391, DOI 10.1534/genetics.106.068726
   Matsuo Y, 2006, FUNCT ECOL, V20, P300, DOI 10.1111/j.1365-2435.2006.01097.x
   MCLEOD DGR, 1963, BIOL BULL-US, V124, P84, DOI 10.2307/1539570
   MCLEOD DGR, 1979, CAN ENTOMOL, V111, P233, DOI 10.4039/Ent111233-3
   Munyiri FN, 2004, J INSECT PHYSIOL, V50, P295, DOI 10.1016/j.jinsphys.2004.01.005
   Nylin S, 1998, ANNU REV ENTOMOL, V43, P63, DOI 10.1146/annurev.ento.43.1.63
   Ording GJ, 2010, OECOLOGIA, V162, P523, DOI 10.1007/s00442-009-1493-8
   Ragland GJ, 2009, J INSECT PHYSIOL, V55, P344, DOI 10.1016/j.jinsphys.2008.12.013
   ROELOFS WL, 1985, J CHEM ECOL, V11, P829, DOI 10.1007/BF01012071
   Schmidt PS, 2008, P NATL ACAD SCI USA, V105, P16207, DOI 10.1073/pnas.0805485105
   Schmidt PS, 2005, EVOLUTION, V59, P1721, DOI 10.1111/j.0014-3820.2005.tb01821.x
   Scott SM, 1987, BIOL SURVEY CANADA M, V62, P452, DOI 10.1086/415671
   Scriber JM, 2011, INSECT SCI, V18, P121, DOI 10.1111/j.1744-7917.2010.01367.x
   Scriber JM, 2005, ENTOMOL EXP APPL, V115, P247, DOI 10.1111/j.1570-7458.2005.00285.x
   Sim C, 2008, P NATL ACAD SCI USA, V105, P6777, DOI 10.1073/pnas.0802067105
   Singtripop T, 2007, J INSECT PHYSIOL, V53, P933, DOI 10.1016/j.jinsphys.2007.03.005
   SKOPIK S D, 1986, Journal of Biological Rhythms, V1, P145, DOI 10.1177/074873048600100205
   SKOPIK S D, 1986, Journal of Biological Rhythms, V1, P137, DOI 10.1177/074873048600100204
   SKOPIK SD, 1976, J COMP PHYSIOL, V111, P249, DOI 10.1007/BF00606467
   Stinchcombe JR, 2004, P NATL ACAD SCI USA, V101, P4712, DOI 10.1073/pnas.0306401101
   TAKEDA M, 1985, J COMP PHYSIOL A, V156, P653, DOI 10.1007/BF00619114
   TAUBER CA, 1977, SCIENCE, V197, P592, DOI 10.1126/science.197.4303.592
   Tauber E, 2007, SCIENCE, V316, P1895, DOI 10.1126/science.1138412
   Tauber M.J., 1986, SEASONAL ADAPTATIONS
   Wilczek AM, 2010, PHILOS T R SOC B, V365, P3129, DOI 10.1098/rstb.2010.0128
   Williams CM, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0034470
   Williams KD, 2006, P NATL ACAD SCI USA, V103, P15911, DOI 10.1073/pnas.0604592103
   WIPKING W, 1995, J INSECT PHYSIOL, V41, P47, DOI 10.1016/0022-1910(94)00079-V
NR 64
TC 31
Z9 36
U1 1
U2 80
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1010-061X
EI 1420-9101
J9 J EVOLUTION BIOL
JI J. Evol. Biol.
PD NOV
PY 2013
VL 26
IS 11
BP 2359
EP 2368
DI 10.1111/jeb.12227
PG 10
WC Ecology; Evolutionary Biology; Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Evolutionary Biology; Genetics &
   Heredity
GA 238WV
UT WOS:000325983400007
PM 24016035
OA Bronze
DA 2025-01-10
ER

PT J
AU Maloney, A
   Dang, QL
   Godakanda, PM
   Thomson, A
AF Maloney, A.
   Dang, Q. L.
   Godakanda, P. M.
   Thomson, A.
TI Genetic variation in growth and leaf traits associated with local
   adaptation to climate in yellow birch (<i> Betula</i> alleghaniensis
   Britton)
SO BOTANY
LA English
DT Article
DE Betula alleghaniensis; adaptive variation; leaf morphology; growth;
   biomass allocation; carbon isotope ratio
ID CARBON-ISOTOPE DISCRIMINATION; HIGHER PHOTOSYNTHETIC CAPACITY; WATER
   RELATIONS; DROUGHT ADAPTATIONS; GENOTYPIC VARIATION; PROVENANCE TESTS;
   ROOT MORPHOLOGY; TREE MORTALITY; GAS-EXCHANGE; PENDULA ROTH
AB Understanding patterns of variation in functional traits of hardwood trees is crucial for conserving and managing North American temperate forests under climate change. This study examined provenance variation of yellow birch (Betula alleghaniensis Britton) in growth, biomass allocation, leaf morphology, and stable carbon isotope composition. Trees were grown from 10 seed sources originating from across Canada and the northern USA. Height and diameter were not significantly related to climate at seed origin, suggesting that variation may be better explained by site factors, such as soil pH and soil moisture. In contrast, carbon isotope composition and leaf morphological traits were significantly correlated to climate variables including temperature, precipitation, and solar radiation. Provenances from warmer, drier localities tended to have higher stable carbon isotope ratio (813C), greater specific leaf area, and narrower leaf width than their counterparts from cooler, wetter climates. Thus, variation in leaf morphological traits appears to be involved in adaptation of yellow birch to variation in temperature and moisture availability across the species' range. Our results suggest that there may exist potential for selection and breeding of drought-resistant yellow birch genotypes to aid in reforestation under climate change.
C1 [Maloney, A.; Dang, Q. L.; Godakanda, P. M.; Thomson, A.] Lakehead Univ, Fac Nat Resources Management, Thunder Bay, ON, Canada.
C3 Lakehead University
RP Thomson, A (corresponding author), Lakehead Univ, Fac Nat Resources Management, Thunder Bay, ON, Canada.
EM athomson@lakeheadu.ca
RI Thomson, Ashley/S-1028-2019
OI Dang, Qing-Lai/0000-0002-5930-248X; Thomson, Ashley/0000-0001-6684-5282
FU Lakehead University Tri-Agency Grant Enhancement Program [1467157]
FX This research was supported by a National Sciences and Engineering
   Research Council (NSERC) postgraduate scholarship awarded to A. Maloney
   and by Lakehead University Tri-Agency Grant Enhancement Program funding
   provided to A. Thomson (grant no. 1467157) .r ship awarded to A. Maloney
   and by Lakehead University Tri-Agency Grant Enhancement Program funding
   provided to A. Thomson (grant no. 1467157) .
CR ABRAMS MD, 1990, TREE PHYSIOL, V6, P305, DOI 10.1093/treephys/6.3.305
   ABRAMS MD, 1994, TREE PHYSIOL, V14, P833, DOI 10.1093/treephys/14.7-8-9.833
   ABRAMS MD, 1988, FOREST SCI, V34, P200
   ABRAMS MD, 1990, FUNCT ECOL, V4, P727, DOI 10.2307/2389439
   Aitken SN, 2016, EVOL APPL, V9, P271, DOI 10.1111/eva.12293
   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], 2008, Plant Physiological Ecology
   Aspelmeier S, 2006, TREES-STRUCT FUNCT, V20, P42, DOI 10.1007/s00468-005-0011-9
   Aubin I, 2016, ENVIRON REV, V24, P164, DOI 10.1139/er-2015-0072
   Beaudet M, 1998, CAN J FOREST RES, V28, P1007, DOI 10.1139/cjfr-28-7-1007
   BOYER JS, 1968, PLANT PHYSIOL, V43, P1056, DOI 10.1104/pp.43.7.1056
   Canavar O., 2014, Australian Journal of Crop Science, V8, P232
   Clausen K. E., 1973, Proceedings of the twentieth northeastern forest tree improvement conference, University of New Hampshire, Durham, 31 July - 2 August, 1972., P90
   Clausen K. E., 1975, Proceedings, 22nd Northeastern Forest Tree Improvement Conference 1974., P138
   Clausen K. E., 1968, Proceedings of the 15th Northeastern Forest Tree Improvement Conference held at Morgantown, W. Va., July 25-26, 1967., P2
   Clausen K. E., 1969, Birch symposium proceedings. Northeastern Forest Experiment Station, Forest Service, US Department of Agriculture, Upper Darby, Pa., P86
   Clausen K.E., 8 LAK STAT FOR TREE, P0
   Clausen K.E., 1977, P 10 CENTR STAT FOR, P9
   Clausen K.E., 1973, USDA FOREST SERVICE
   CLAUSEN KE, 1980, SILVAE GENET, V29, P108
   DANCIK B P, 1975, Canadian Journal of Forest Research, V5, P149, DOI 10.1139/x75-021
   Dawson TE, 2002, ANNU REV ECOL SYST, V33, P507, DOI 10.1146/annurev.ecolsys.33.020602.095451
   DONSELMAN HM, 1982, ECOLOGY, V63, P962, DOI 10.2307/1937236
   Erdmann G.G., 1990, Silvics of North America: 2. Agriculture Handbook 654, P133, DOI DOI 10.1017/S1751731117001768
   Etterson JR, 2020, ECOL APPL, V30, DOI 10.1002/eap.2092
   FARQUHAR GD, 1989, ANNU REV PLANT PHYS, V40, P503, DOI 10.1146/annurev.pp.40.060189.002443
   Fonseca CR, 2000, J ECOL, V88, P964, DOI 10.1046/j.1365-2745.2000.00506.x
   Fowler D., 1988, PROVENANCE TEST YELL
   Gaucher C, 2005, TREE PHYSIOL, V25, P93, DOI 10.1093/treephys/25.1.93
   George JP, 2020, EVOL APPL, V13, P2422, DOI 10.1111/eva.13034
   Guo XL, 2020, TREE PHYSIOL, V40, P1639, DOI 10.1093/treephys/tpaa096
   Hsiao TC, 2000, J EXP BOT, V51, P1595, DOI 10.1093/jexbot/51.350.1595
   Kaluthota S, 2015, TREE PHYSIOL, V35, P936, DOI 10.1093/treephys/tpv069
   Kassambara Alboukadel, 2020, CRAN
   Knutzen F, 2015, TREE PHYSIOL, V35, P949, DOI 10.1093/treephys/tpv057
   Lauteri M, 1997, FUNCT ECOL, V11, P675, DOI 10.1046/j.1365-2435.1997.00140.x
   Leigh A, 2017, PLANT CELL ENVIRON, V40, P237, DOI 10.1111/pce.12857
   Leitch AR, 2008, SCIENCE, V320, P481, DOI 10.1126/science.1153585
   Leites LP, 2019, PERSPECT PLANT ECOL, V37, P64, DOI 10.1016/j.ppees.2019.02.002
   Lesser MR, 2004, SILVAE GENET, V53, P141, DOI 10.1515/sg-2004-0026
   Leuschner C, 2020, PERSPECT PLANT ECOL, V47, DOI 10.1016/j.ppees.2020.125576
   Logan K.T., 1965, DEP, V1121, P1
   Lopez GA, 2003, CAN J FOREST RES, V33, P2108, DOI 10.1139/X03-132
   Markesteijn L, 2009, J ECOL, V97, P311, DOI 10.1111/j.1365-2745.2008.01466.x
   Matías L, 2019, ENVIRON EXP BOT, V163, P78, DOI 10.1016/j.envexpbot.2019.04.011
   Miljkovic D, 2019, ALPINE BOT, V129, P163, DOI 10.1007/s00035-019-00227-1
   Moles AT, 2014, J VEG SCI, V25, P1167, DOI 10.1111/jvs.12190
   Neale DB, 2011, NAT REV GENET, V12, P111, DOI 10.1038/nrg2931
   Nicotra AB, 2010, TRENDS PLANT SCI, V15, P684, DOI 10.1016/j.tplants.2010.09.008
   Nicotra AB, 2011, FUNCT PLANT BIOL, V38, P535, DOI 10.1071/FP11057
   Niemczyk M, 2019, FORESTS, V10, DOI 10.3390/f10111041
   Niinemets Ü, 2006, NEW PHYTOL, V171, P91, DOI 10.1111/j.1469-8137.2006.01741.x
   O'Brien EK, 2007, J APPL ECOL, V44, P583, DOI 10.1111/j.1365-2664.2007.01313.x
   OLEARY MH, 1988, BIOSCIENCE, V38, P328, DOI 10.2307/1310735
   Olivas-García JM, 2000, CAN J FOREST RES, V30, P1581, DOI 10.1139/cjfr-30-10-1581
   Otto SP, 2000, ANNU REV GENET, V34, P401, DOI 10.1146/annurev.genet.34.1.401
   Parisod C, 2010, NEW PHYTOL, V186, P5, DOI 10.1111/j.1469-8137.2009.03142.x
   Pedlar JH, 2021, J ECOL, V109, P2271, DOI 10.1111/1365-2745.13605
   Peng CH, 2011, NAT CLIM CHANGE, V1, P467, DOI 10.1038/NCLIMATE1293
   Pyakurel A., 2013, Open Journal of Ecology, V3, P284, DOI 10.4236/oje.2013.34033
   Rehfeldt GE, 1999, ECOL MONOGR, V69, P375, DOI 10.1890/0012-9615(1999)069[0375:GRTCIP]2.0.CO;2
   ROACH DA, 1987, ANNU REV ECOL SYST, V18, P209, DOI 10.1146/annurev.es.18.110187.001233
   Santini A., 2004, Investigacion Agraria, Sistemas y Recursos Forestales, V13, P47
   Savolainen O, 2007, ANNU REV ECOL EVOL S, V38, P595, DOI 10.1146/annurev.ecolsys.38.091206.095646
   Sebastian-Azcona J, 2020, FRONT PLANT SCI, V11, DOI 10.3389/fpls.2020.00208
   Sharik T.L., 1975, CAN J BOT CAN BOT, V54, P2122, DOI [10.1139/b76-22810.1139/b76-228, DOI 10.1139/B76-22810.1139/B76-228]
   SHARIK TL, 1979, CAN J BOT, V57, P1932, DOI 10.1139/b79-242
   Sokal R. R., 1995, Biometry: The Principles of Statistics in Biological Research
   Soolanayakanahally RY, 2015, FRONT PLANT SCI, V6, DOI 10.3389/fpls.2015.00528
   Stojnic S, 2022, TREES-STRUCT FUNCT, V36, P497, DOI 10.1007/s00468-021-02224-6
   Taeger S, 2013, FOREST ECOL MANAG, V307, P30, DOI 10.1016/j.foreco.2013.06.053
   Tenkanen A, 2021, TREE PHYSIOL, V41, P974, DOI 10.1093/treephys/tpaa148
   Thomson AM, 2008, CAN J FOREST RES, V38, P157, DOI 10.1139/X07-122
   Thomson AM, 2015, TREE GENET GENOMES, V11, DOI 10.1007/s11295-015-0922-6
   Van De Peer Y, 2017, NAT REV GENET, V18, P411, DOI 10.1038/nrg.2017.26
   Vitasse Y, 2009, CAN J FOREST RES, V39, P1259, DOI 10.1139/X09-054
   Wang TL, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0156720
   Warren CR, 2005, TREE PHYSIOL, V25, P1369, DOI 10.1093/treephys/25.11.1369
   WEARSTLER KA, 1977, CAN J BOT, V55, P2778, DOI 10.1139/b77-316
   Wei T., 2021, R PACKAGE CORRPLOT V
   WESTGATE ME, 1985, PLANTA, V164, P540, DOI 10.1007/BF00395973
   Wright IJ, 2004, NATURE, V428, P821, DOI 10.1038/nature02403
   Wright IJ, 2005, GLOBAL ECOL BIOGEOGR, V14, P411, DOI 10.1111/j.1466-822x.2005.00172.x
   Xu F, 2009, PROG NAT SCI-MATER, V19, P1789, DOI 10.1016/j.pnsc.2009.10.001
   Yates MJ, 2010, FUNCT ECOL, V24, P485, DOI 10.1111/j.1365-2435.2009.01678.x
   Zhang XL, 2004, PLANT SCI, V166, P791, DOI 10.1016/j.plantsci.2003.11.016
NR 87
TC 0
Z9 0
U1 1
U2 2
PU CANADIAN SCIENCE PUBLISHING
PI OTTAWA
PA 123 Slater Street, Suite 610, OTTAWA, ON K1P 5H2, CANADA
SN 1916-2790
EI 1916-2804
J9 BOTANY
JI Botany
PD APR
PY 2024
VL 102
IS 4
BP 198
EP 210
DI 10.1139/cjb-2023-0095
EA MAR 2024
PG 13
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA TE8A1
UT WOS:001233243400001
DA 2025-01-10
ER

PT J
AU Apostolopoulos, AS
   Philips, TK
AF Apostolopoulos, A. S.
   Philips, T. Keith
TI CONSEQUENCES OF THE GLOBAL CLIMATE CRISIS ON THE CAVE BEETLE
   <i>DARLINGTONEA KENTUCKENSIS</i> VALENTINE BASED ON THERMAL TOLERANCE
   AND DEHYDRATION RESISTANCE
SO JOURNAL OF CAVE AND KARST STUDIES
LA English
DT Article
ID DWELLING BEETLES; WATER-LOSS; TEMPERATE; EVOLUTION; RANGE; ACCLIMATION;
   CRUSTACEANS; MECHANISMS
AB Rising temperatures and diminishing groundwater availability due to the current climate crisis are predicted to expose cave faunas in eastern North America to unprecedented environmental conditions that could prove detrimental to their unique ecosystems. Organisms that inhabit relatively stable environments like caves are known to develop narrow physiological tolerances. Cave habitats with their organisms are simple ecosystems whose homogeneity offers an ideal system for testing the ability of a highly specialized fauna to tolerate abiotic changes. We tested the capability of a cave-specialized beetle in the eastern United States, Darlingtonea kentuckensis Valentine, to withstand future climatic shifts in its environment. We exposed individuals to a range of relative humidities and temperatures for 10 days. The data strongly suggest that there is a temperature threshold for the survival of D. kentuckensis, but it is a higher thermal tolerance than would be expected in an environment that has not fluctuated in recent evolutionary time and suggests remnant physiological characteristics of ancestral epigean carabids. Decreasing the relative humidity in the environment resulted in a much more dramatic decline in survival, indicating highly evolved specialization for constant high-humidity environments. The narrow humidity threshold in which troglobionts can survive may be a much more apparent limiting factor than temperature in adapting to climatic shifts within a cave environment.
C1 [Apostolopoulos, A. S.; Philips, T. Keith] Western Kentucky Univ, Dept Biol, Systemat & Evolut Lab, 1906 Coll Hts Blvd, Bowling Green, KY 42101 USA.
C3 Western Kentucky University
RP Apostolopoulos, AS (corresponding author), Western Kentucky Univ, Dept Biol, Systemat & Evolut Lab, 1906 Coll Hts Blvd, Bowling Green, KY 42101 USA.
EM athanasios.apostolopoulos742@topper.wku.edu
FU Kentucky Speleological Survey; Western Kentucky University
FX This research was supported by funds from the Kentucky Speleological
   Survey and internal funding from Western Kentucky University through a
   graduate research grant and a graduate research fellowship. We thank
   John Andersland, Jarrett Johnson, and Albert Meier for their valuable
   advice, David Schill for aiding in beetle collection, and land-owners
   for permission to sample in Wind Cave. We are grateful for the comments
   from two anonymous reviewers that improved the manuscript.
CR [Anonymous], 2013, Karst hydrogeology and geomorphology, DOI [10.1002/9781118684986, DOI 10.1002/9781118684986]
   Badino G., 2004, International Journal of Speleology, V33, P103
   Badino G, 2010, ACTA CARSOLOGICA, V39, P427
   Barr T.C., 1969, DISTRIBUTIONAL HIST, V1, P67
   Barr T.C., 1979, AM MUS NOVIT, V2682
   Barr T. C. Jr., 1968, P35
   BARR TC, 1965, AM MIDL NAT, V73, P73, DOI 10.2307/2423321
   BARR TC, 1985, ANNU REV ECOL SYST, V16, P313, DOI 10.1146/annurev.es.16.110185.001525
   Bernabò P, 2011, J THERM BIOL, V36, P206, DOI 10.1016/j.jtherbio.2011.03.002
   Boyd OF, 2020, SUBTERR BIOL, V34, P1, DOI 10.3897/subtbiol.34.46348
   Cardoso P, 2011, BIOL CONSERV, V144, P2647, DOI 10.1016/j.biocon.2011.07.024
   Cardoso P, 2011, BIOL CONSERV, V144, P2432, DOI 10.1016/j.biocon.2011.06.020
   Christman MC, 2005, J BIOGEOGR, V32, P1441, DOI 10.1111/j.1365-2699.2005.01263.x
   Covington MD, 2015, ACTA CARSOLOGICA, V44, P363
   Culver DC, 2009, FRESHWATER BIOL, V54, P918, DOI 10.1111/j.1365-2427.2007.01856.x
   Delay B., 1978, MEMOIRES BIOSPELEOLO, V5
   Di Lorenzo T, 2017, WATER-SUI, V9, DOI 10.3390/w9120951
   Domínguez-Villar D, 2015, CLIM DYNAM, V45, P569, DOI 10.1007/s00382-014-2226-1
   Faille A, 2010, MOL PHYLOGENET EVOL, V54, P97, DOI 10.1016/j.ympev.2009.10.008
   FEDER ME, 1978, PHYSIOL ZOOL, V51, P7, DOI 10.1086/physzool.51.1.30158660
   FUTUYMA DJ, 1988, ANNU REV ECOL SYST, V19, P207, DOI 10.1146/annurev.es.19.110188.001231
   Grabowski G.J., 2001, CONTRIBUTIONS GEOLOG
   GRIFFITH DM, 1993, ECOLOGY, V74, P1373, DOI 10.2307/1940067
   Hedin MC, 1997, MOL BIOL EVOL, V14, P309, DOI 10.1093/oxfordjournals.molbev.a025766
   HUEY RB, 1989, TRENDS ECOL EVOL, V4, P131, DOI 10.1016/0169-5347(89)90211-5
   HUMPHREYS WF, 1990, COMP BIOCHEM PHYS A, V95, P101, DOI 10.1016/0300-9629(90)90016-L
   Issartel J, 2005, COMP BIOCHEM PHYS A, V141, P1, DOI 10.1016/j.cbpb.2005.02.013
   Kentucky Geological Survey, MISS PER
   Kirichenko-Babko M, 2020, FORESTS, V11, DOI 10.3390/f11101074
   KREBS RA, 1994, FUNCT ECOL, V8, P730, DOI 10.2307/2390232
   Kriegel P, 2021, AGR FOREST ENTOMOL, V23, P400, DOI 10.1111/afe.12441
   Lencioni V, 2010, J THERM BIOL, V35, P354, DOI 10.1016/j.jtherbio.2010.07.004
   Lewis J J., 2005, Proceedings of the 2005 National Cave and Karst Management Symposium: NCKMS Steering Committee, P15
   Maddison DR, 2019, MOL PHYLOGENET EVOL, V132, P151, DOI 10.1016/j.ympev.2018.11.006
   Mammola S, 2018, ECOGRAPHY, V41, P233, DOI 10.1111/ecog.02902
   Markle TM, 2018, ECOL EVOL, V8, P4644, DOI 10.1002/ece3.4006
   Marsh T.G., 1969, THESIS U KENTUCKY
   Mermillod-Blondin F, 2013, J EXP BIOL, V216, P1683, DOI 10.1242/jeb.081232
   Monaghan P, 2009, ECOL LETT, V12, P75, DOI 10.1111/j.1461-0248.2008.01258.x
   Moore G.W., 1964, SPECIAL PAPER 76, P313, DOI [10.1130/SPE76-p305, DOI 10.1130/SPE76-P305]
   NEVE G, 1994, SERIES ENTOM, V51, P189
   Novak T, 2014, INT J SPELEOL, V43, P265, DOI 10.5038/1827-806X.43.3.3
   Pallarés S, 2021, ANIM CONSERV, V24, P482, DOI 10.1111/acv.12654
   Pallarés S, 2019, ECOL EVOL, V9, P13731, DOI 10.1002/ece3.5782
   Peck Stewart B., 1998, Journal of Caves and Karst Studies, V60, P18
   Perry RW, 2013, ENVIRON REV, V21, P28, DOI 10.1139/er-2012-0042
   Ribera I, 2010, BMC EVOL BIOL, V10, DOI 10.1186/1471-2148-10-29
   Rizzo V, 2015, BMC EVOL BIOL, V15, DOI 10.1186/s12862-015-0288-2
   Rogowitz GL, 1999, J COMP PHYSIOL B, V169, P179, DOI 10.1007/s003600050209
   Romero A, 2009, ECOL BIODIVERS CONS, P1, DOI 10.1017/CBO9780511596841
   Romero A, 2011, AM SCI, V99, P144, DOI 10.1511/2011.89.144
   Shah AA, 2017, INTEGR COMP BIOL, V57, P977, DOI 10.1093/icb/icx101
   Smith R.L., 1986, ELEMENTS ECOLOGY, V2d, P328
   SMITHSON PA, 1991, THEOR APPL CLIMATOL, V44, P65, DOI 10.1007/BF00865553
   Snowman CV, 2010, J ARACHNOL, V38, P49, DOI 10.1636/A09-057.1
   Soares D, 2020, ANAT REC, V303, P15, DOI 10.1002/ar.24044
   Somero George N., 2005, Frontiers in Zoology, V2, P1, DOI 10.1186/1742-9994-2-1
   STEVENS GC, 1989, AM NAT, V133, P240, DOI 10.1086/284913
   Sustek Z, 2017, J HYDROL HYDROMECH, V65, P333, DOI 10.1515/johh-2017-0048
   Tomanek L, 2008, PHYSIOL BIOCHEM ZOOL, V81, P709, DOI 10.1086/590163
   Tuttle M. D., 2011, BAT CONSERVATION MAN, P19
   US EPA, 2016, PUBLICATIONS, V430-F-16-019
   Valentine J.M., 1952, Geological Survey of Alabama: Museum Paper, V34, P1
   Yao ZY, 2016, SCI REP-UK, V6, DOI 10.1038/srep35757
   Yoder JA, 2011, J COMP PHYSIOL B, V181, P595, DOI 10.1007/s00360-011-0555-5
NR 65
TC 0
Z9 0
U1 0
U2 3
PU NATL SPELEOLOGICAL SOC
PI HUNTSVILLE
PA 2813 CAVE AVE, HUNTSVILLE, AL 35810-4431 USA
SN 1090-6924
EI 2331-3714
J9 J CAVE KARST STUD
JI J. Cave Karst Stud.
PD DEC
PY 2022
VL 84
IS 4
BP 119
EP 127
DI 10.4311/2021LSC0132
PG 9
WC Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology
GA 7S6DR
UT WOS:000910842800002
OA gold
DA 2025-01-10
ER

PT J
AU Diz-Mellado, E
   López-Cabeza, VP
   Roa-Fernández, J
   Rivera-Gómez, C
   Galán-Marín, C
AF Diz-Mellado, Eduardo
   Lopez-Cabeza, Victoria Patricia
   Roa-Fernandez, Jorge
   Rivera-Gomez, Carlos
   Galan-Marin, Carmen
TI Energy-saving and thermal comfort potential of vernacular urban block
   porosity shading
SO SUSTAINABLE CITIES AND SOCIETY
LA English
DT Article
DE Mediterranean courtyard; Urban microclimate; GIS; Shading; PET; Energy
   -saving
ID DIURNAL TEMPERATURE-RANGE; HEAT MITIGATION STRATEGIES; RESPONSIVE
   DESIGN; HOT-SUMMER; CLIMATE; COURTYARDS; PERFORMANCE; INDOOR; IMPACT;
   MICROCLIMATES
AB Built environment configurations of vernacular architecture are the result of an evolutionary adaptation to climatic conditions, while the historic districts of many cities worldwide are shaped by their extensive architectural heritage. These factors, coupled with the present day awareness and renewed interest in the passive retrofitting of buildings, have prompted a review of traditional strategies, most notably direct solar radiation management through courtyard perforations. Although the vernacular courtyard microclimate has been discussed in the literature in recent years, few studies have successfully translated its climatic benefits to the city scale in order to assess its real potential. There is a notable absence of overall urban estimations of the impact on energy-saving and thermal comfort of some of the most effective strategies, such as the use of shading devices. Combining stateof-the-art GIS-based tools and statistical data analysis from field monitoring campaigns this research performs a large-scale evaluation in urban courtyards in the historic centre of a Mediterranean city. Based on the results obtained it can be stated that a widespread use of shading devices can increase the number of hours of comfort, according to PET, by 27% and can reduce global cooling demand by 31%.
C1 [Diz-Mellado, Eduardo; Lopez-Cabeza, Victoria Patricia; Roa-Fernandez, Jorge; Rivera-Gomez, Carlos; Galan-Marin, Carmen] Univ Seville, Inst Univ Arquitectura & Ciencias Construcc, Escuela Tecn Super Arquitectura, Avda Reina Mercedes 2, Seville 41012, Spain.
C3 University of Sevilla
RP Galán-Marín, C (corresponding author), Univ Seville, Inst Univ Arquitectura & Ciencias Construcc, Escuela Tecn Super Arquitectura, Avda Reina Mercedes 2, Seville 41012, Spain.
EM ediz@us.es; vlopez7@us.es; jroa@us.es
RI RIVERA-GOMEZ, CARLOS/M-9170-2014; Diz-Mellado, Eduardo/AAH-9808-2019;
   Roa Fernandez, Jorge/S-1250-2018; Galan-Marin, Carmen/M-9023-2014;
   Lopez-Cabeza, Victoria Patricia/AAC-6214-2020
OI Roa Fernandez, Jorge/0000-0003-1254-3443; Galan-Marin,
   Carmen/0000-0003-1929-3280; Diz-Mellado, Eduardo/0000-0002-2039-1307;
   Lopez-Cabeza, Victoria Patricia/0000-0002-5257-1281
FU FEDER Una forma de hacer Europa [RTI2018-093521-B-C33,
   PID2021-124539OB-I00, MCIN/AEI/10.13039/501100011033]; Consejeria de
   Fomento, Infraestructuras y Ordenacion del Territorio, Junta de
   Andalucia [US.20-11]; Ministerio de Educacion, Cultura y Deportes
   [FPU17/05036, FPU18/04783]; IUACC; Universidad de Sevilla
FX This work has been supported by the projects RTI2018-093521-B-C33 and
   PID2021-124539OB-I00 funded by MCIN/AEI/10.13039/501100011033 and by
   "FEDER Una forma de hacer Europa"; US.20-11 funded by Consejeria de
   Fomento, Infraestructuras y Ordenacion del Territorio, Junta de
   Andalucia; and the Ministerio de Educacion, Cultura y Deportes via a
   pre-doctoral contract granted to V.P. L -C. [FPU17/05036] and E. D -M
   [FPU18/04783] . It has also been supported by the IUACC and Universidad
   de Sevilla, via the internationalization grant within the VIIPPI-US
   program. The authors gratefully acknowledge AEMET (State Meteorological
   Agency) for the data supplied. Special thanks to the association "Patios
   de la Axerquia (PAX)" of Cordova for theirs help letting us visiting the
   buildings, and granting permissions to carry out the monitoring
   campaigns.
CR Abadie LM, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab185c
   Abdulkareem HA, 2016, PROCD SOC BEHV, V216, P662, DOI 10.1016/j.sbspro.2015.12.054
   Abou Hweij W, 2017, ENERG BUILDINGS, V139, P755, DOI 10.1016/j.enbuild.2017.01.071
   Akbari H, 2021, SUSTAIN ENERGY TECHN, V48, DOI 10.1016/j.seta.2021.101594
   Al-Hafith O, 2017, ENRGY PROCED, V122, P889, DOI 10.1016/j.egypro.2017.07.382
   Cantón MA, 2014, RENEW ENERG, V69, P437, DOI 10.1016/j.renene.2014.03.065
   Anderson GB, 2018, CLIMATIC CHANGE, V146, P455, DOI 10.1007/s10584-016-1779-x
   Anna-Maria V, 2009, BUILD ENVIRON, V44, P1095, DOI 10.1016/j.buildenv.2008.05.026
   [Anonymous], 2017, DRAFT Low Impact Development (LID) Stormwater Management Guidance Manual, P1
   [Anonymous], 2022, Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions: EU Energy Strategy
   [Anonymous], 2022, INTANGIBLE HERITAGE
   [Anonymous], 2022, HIST CTR CORDOBA UNE
   [Anonymous], 2022, 10 POPULATION MEDITE
   [Anonymous], 2022, FIESTA PATIOS CORDOB
   Callejas IJA, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12156135
   Barros VR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1133
   Berkovic S, 2012, SOL ENERGY, V86, P1173, DOI 10.1016/j.solener.2012.01.010
   Chan SY, 2021, SUSTAIN CITIES SOC, V64, DOI 10.1016/j.scs.2020.102512
   Chatzipoulka C, 2020, CITIES, V100, DOI 10.1016/j.cities.2020.102645
   Chen Lei, 2022, Zenodo
   Chen L, 2022, ENERG BUILDINGS, V256, DOI 10.1016/j.enbuild.2021.111757
   Cindel S., 2018, J DES BUILT ENV, V18, P1
   Cohen P, 2013, APPL GEOGR, V37, P1, DOI 10.1016/j.apgeog.2012.11.001
   de la Flor FJS, 2021, J CLEAN PROD, V320, DOI 10.1016/j.jclepro.2021.128742
   DeFries R.S., 2019, The missing economic risks in assessments of climate change impacts
   Diz-Mellado E., 2020, Multidisciplinary Digital Publishing Institute Proceedings, V38, P13, DOI 10.3390/proceedings2019038013
   Diz-Mellado E.M., 2020, REHABEND, P1645
   Diz-Mellado E, 2021, BUILD ENVIRON, V203, DOI 10.1016/j.buildenv.2021.108094
   Diz-Mellado E, 2021, MATHEMATICS-BASEL, V9, DOI 10.3390/math9101142
   Diz-Mellado E, 2020, APPL SCI-BASEL, V10, DOI 10.3390/app10217648
   Elgheznawy D, 2021, BUILD ENVIRON, V202, DOI 10.1016/j.buildenv.2021.108046
   Estrada Francisco, 2017, Nature Climate Change, V7, P403, DOI 10.1038/nclimate3301
   Euroepan Parliament, 2022, DIRECTIVE 20072EC EU
   Galan-Marin C., 2018, PROCEEDINGS, V2, P1390, DOI [10.3390/proceedings2221390, DOI 10.3390/PROCEEDINGS2221390]
   Galan-Marin C., 2021, ENHANCING URBAN MICR, DOI [10.1007/978-3-030-78566-6, DOI 10.1007/978-3-030-78566-6]
   Ghaffarianhoseini A, 2015, BUILD ENVIRON, V87, P154, DOI 10.1016/j.buildenv.2015.02.001
   Government S, 2022, CART CAT
   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]
   Hallegatte S, 2013, NAT CLIM CHANGE, V3, P802, DOI [10.1038/nclimate1979, 10.1038/NCLIMATE1979]
   Höppe P, 2002, ENERG BUILDINGS, V34, P661, DOI 10.1016/S0378-7788(02)00017-8
   Huang LJ, 2016, ENERG BUILDINGS, V128, P697, DOI 10.1016/j.enbuild.2016.07.006
   Hunt A, 2011, CLIMATIC CHANGE, V104, P13, DOI 10.1007/s10584-010-9975-6
   Idae, 2011, IDAE, V5, P7
   Indices T, 2018, RAYMAN PRO
   IPCC, 2018, IPCC SR15, V2, P17
   Jamei E, 2016, RENEW SUST ENERG REV, V54, P1002, DOI 10.1016/j.rser.2015.10.104
   Karahan F, 2020, J ASIAN ARCHIT BUILD, V19, P490, DOI 10.1080/13467581.2020.1758108
   Kim SW, 2021, SCI TOTAL ENVIRON, V779, DOI 10.1016/j.scitotenv.2021.146389
   Kottek M, 2006, METEOROL Z, V15, P259, DOI 10.1127/0941-2948/2006/0130
   Lai DY, 2020, SCI TOTAL ENVIRON, V742, DOI 10.1016/j.scitotenv.2020.140092
   Lee HYJ, 2022, URBAN CLIM, V44, DOI 10.1016/j.uclim.2022.101210
   Lee W, 2018, ENVIRON INT, V119, P379, DOI 10.1016/j.envint.2018.06.020
   Lee W, 2018, ENVIRON INT, V110, P123, DOI 10.1016/j.envint.2017.10.018
   Lim YH, 2012, SCI TOTAL ENVIRON, V417, P55, DOI 10.1016/j.scitotenv.2011.12.048
   Liu Y, 2022, SUSTAIN CITIES SOC, V85, DOI 10.1016/j.scs.2022.104081
   Lizana J, 2022, SUSTAIN CITIES SOC, V78, DOI 10.1016/j.scs.2021.103590
   López-Cabeza VP, 2018, BUILD ENVIRON, V144, P129, DOI 10.1016/j.buildenv.2018.08.013
   Lopez-Cabeza V.P., 2020, THERMODYNAMIC PERFOR, P17, DOI [10.3390/proceedings2019038017, DOI 10.3390/PROCEEDINGS2019038017]
   Ma HQ, 2021, SUSTAIN CITIES SOC, V72, DOI 10.1016/j.scs.2021.103069
   Ma X, 2019, SOL ENERGY, V179, P210, DOI 10.1016/j.solener.2018.12.001
   Marcal NA, 2019, BUILD ENVIRON, V152, P145, DOI 10.1016/j.buildenv.2019.02.016
   Matzarakis A, 1999, INT J BIOMETEOROL, V43, P76, DOI 10.1007/s004840050119
   Matzarakis A, 1997, INT J BIOMETEOROL, V41, P34, DOI 10.1007/s004840050051
   Migliari M, 2022, SUSTAIN CITIES SOC, V81, DOI 10.1016/j.scs.2022.103852
   Muhaisen AS, 2006, BUILD ENVIRON, V41, P1731, DOI 10.1016/j.buildenv.2005.07.016
   Muhaisen AS, 2006, BUILD ENVIRON, V41, P1050, DOI 10.1016/j.buildenv.2005.04.027
   Muhaisen AS, 2005, BUILD ENVIRON, V40, P1619, DOI 10.1016/j.buildenv.2004.12.018
   Nasrollahi N, 2017, SUSTAIN CITIES SOC, V35, P449, DOI 10.1016/j.scs.2017.08.017
   Oktay D, 2002, BUILD ENVIRON, V37, P1003, DOI 10.1016/S0360-1323(01)00086-5
   Open Source Geospatial Foundation (OSGeo), 2022, QGIS
   Lopez-Cabeza VP, 2022, SUSTAIN CITIES SOC, V81, DOI 10.1016/j.scs.2022.103872
   López-Cabeza VP, 2022, J BUILD PERFORM SIMU, V15, P39, DOI 10.1080/19401493.2021.2001571
   Pearlmutter D, 2017, ENERG BUILDINGS, V144, P295, DOI 10.1016/j.enbuild.2017.03.067
   Philokyprou M, 2017, BUILD ENVIRON, V111, P91, DOI 10.1016/j.buildenv.2016.10.010
   Qaid A, 2015, INT J BIOMETEOROL, V59, P657, DOI 10.1007/s00484-014-0878-5
   Rivera-Gómez C, 2019, SUSTAIN CITIES SOC, V51, DOI 10.1016/j.scs.2019.101740
   Rodríguez-Algeciras J, 2018, RENEW ENERG, V125, P840, DOI 10.1016/j.renene.2018.01.082
   Rojas-Fernández J, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9122255
   Sadafi N, 2011, ENERG BUILDINGS, V43, P887, DOI 10.1016/j.enbuild.2010.12.009
   Safarzadeh H, 2005, BUILD ENVIRON, V40, P89, DOI 10.1016/j.buildenv.2004.04.014
   Santamouris M, 2017, SOL ENERGY, V154, P14, DOI 10.1016/j.solener.2016.12.006
   Shashua-Bar L, 2009, LANDSCAPE URBAN PLAN, V92, P179, DOI 10.1016/j.landurbplan.2009.04.005
   Soflaei F, 2017, ENERG BUILDINGS, V143, P71, DOI 10.1016/j.enbuild.2017.03.027
   Taleghani M, 2018, RENEW SUST ENERG REV, V81, P2011, DOI 10.1016/j.rser.2017.06.010
   Taleghani M, 2015, BUILD ENVIRON, V83, P65, DOI 10.1016/j.buildenv.2014.03.014
   Taleghani M, 2014, SOL ENERGY, V103, P108, DOI 10.1016/j.solener.2014.01.033
   Technical Committee CTN 100, 2020, 167981 UNEEN TECHN C, P1
   Toe DHC, 2015, SOL ENERGY, V114, P229, DOI 10.1016/j.solener.2015.01.035
   Ulpiani G, 2019, BUILD ENVIRON, V156, P46, DOI 10.1016/j.buildenv.2019.04.007
   Ulpiani G, 2019, APPL ENERG, V239, P1091, DOI 10.1016/j.apenergy.2019.01.231
   UNE, 2022, 1592762009 UNEEN ISO
   Yang B, 2017, SUSTAIN CITIES SOC, V28, P387, DOI 10.1016/j.scs.2016.10.011
   Yang XY, 2012, BUILD ENVIRON, V57, P38, DOI 10.1016/j.buildenv.2012.03.022
   Zamani Z, 2018, RENEW SUST ENERG REV, V93, P580, DOI 10.1016/j.rser.2018.05.055
   Zhao Q., 2021, Energy and Built Environment, V2, P21, DOI [DOI 10.1016/J.ENBENV.2020.05.007, 10.1016/j.enbenv.2020.05.007]
   Zones C., 2012, LOCAL CLIMATE ZONES, P108, DOI [10.1175/BAMS-D-11-00019.2, DOI 10.1175/BAMS-D-11-00019.2]
NR 96
TC 15
Z9 15
U1 11
U2 39
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 FEB
PY 2023
VL 89
AR 104325
DI 10.1016/j.scs.2022.104325
EA DEC 2022
PG 17
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 7Z5UM
UT WOS:000915624200001
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Hernández, MEO
   Arteaga, GA
   Zuazo, MAR
AF Orozco Hernandez, Maria Estela
   Alvarez Arteaga, Gustavo
   Reyes Zuazo, Maria Antonieta
TI Social aptitude of environmental perception in the Bicentennial
   Metropolitan Park, city of Toluca, Mexico
SO REVISTA DE URBANISMO
LA Spanish
DT Article
DE environmental perception; green areas; social aptitude; urban park
AB Inclusive urbanization incorporates green areas as a strategy for adaptation to climate variation, at the local level the sodas capacity for resilient management of urban parks is unknown. The study analyzes social aptitude through environmental perception in the Bicentennial Metropolitan Park. The question and the construct propose: how does environmental perception influence social fitness? Sodas aptitude is an adaptive capacity conditioned by subjective and sociocultural factors. Through a non-experimental design, direct observation and a questionnaire applied to a sample of visitors and residents, the perception pattern and the areas of opportunity for environmental improvement are identified. The results establish that social aptitude exhibits a low level of empathy and intersubjectivity, lack of participation, especially in states of neutrality and indifference, due to economic and personal problems. It is concluded that the social potential of adaptive capacity is articulated through value judgments that define a strong pro-environmental disposition, the selection and classification of improvement options that imply needs and expectations of environmental responsibility, social participation linked to emotional well-being and benefits of recreation, sports and health. The operation depends on the decision system that organizes the continuous improvement programs and projects, the cooperation and negotiation processes, and the regulatory framework for the socio-ecological management of green areas in Toluca.
C1 [Orozco Hernandez, Maria Estela; Alvarez Arteaga, Gustavo; Reyes Zuazo, Maria Antonieta] Univ Autonoma Estado Mexico, Toluca, Mexico.
RP Hernández, MEO (corresponding author), Univ Autonoma Estado Mexico, Toluca, Mexico.
EM eorozcoh61@hotmail.com
OI Orozco-Hernandez, Maria Estela/0000-0003-4816-7742
CR Alea Garcia A., 2006, Odiseo, Revista electronica de pedagogia, V3, P1
   Alvarez P., 2010, REV PSICODIDACT, V14, P245
   [Anonymous], SIST NORM EQ URB
   [Anonymous], DEL ZON METR MEX
   [Anonymous], 2017, NUEV AG URB
   Arista I. A., 2008, ANALISIS HOGAR ESCUE
   BARBEROUSSE Paulette, 2008, Rev. Electronica Educ., VXII, P95, DOI DOI 10.15359/REE.12-2.6
   Briceno J., 2012, Educere, V16, P267
   Cabezas M. M., 2010, REV FILOSOFIA FACTOT, P76
   Candela A., 2012, I NACL EVALUACION ED
   CAPEL Horacio, 1973, Revista de Geografia, Barcelona, V7, P58
   Cendra J., 2015, 2 C UPC SOST 2015 BA
   Cerati TM, 2016, ESTUD DEMOGR URBANOS, V31, P87, DOI 10.24201/edu.v31i1.1504
   Ciompi Luc, 2007, Rev. Asoc. Esp. Neuropsiq., V27, P153, DOI 10.4321/s0211-57352007000200013
   Contreras Francoise, 2006, Divers.: Perspect. Psicol., V2, P311
   Coordinacion General de Conservacion Ecologica Delegacion Regional Toluca [CG[ERT], 2017, AFL PARQ METR BIC 20
   Covarrubias Pizarro Pedro, 2018, IE Rev. investig. educ. REDIECH, V9, P53
   Cuervo L., 2010, PERCEPCION CONOCIMIE
   de Echeverri APN., 2007, GESTION AMBIENTE, V10, P5
   Diaz F., 2006, ENSELIANZA SITUADA V
   Durán M, 2007, REV LAT AM PSICOL, V39, P287
   FALCON Antoni., 2007, Espacios verdes para una ciudad sostenible. Planificacion, proyecto
   Febles M., 2001, Hacia un enfoque holistico del Medio Ambiente desde la Psicologia Ambiental. Facultad de Psicologia
   Fernández Moreno Yara, 2008, Espiral (Guadalaj.), V15, P179
   Flores-Xolocotzi Ramiro, 2010, Rev. mex. de cienc. forestales, V1, P17
   FLORES-XOLOCOTZI Ramiro, 2012, Frontera norte, V24, P165
   Garcia L., 2015, REV VIRTUAL U CATALI, P253
   GARCIA MR, 2006, REV GEOGR NORTE GD, P45
   Gimenez G., 1999, Perfiles latinoamericanos, V15, P119
   Gomera A., 2008, La conciencia ambiental como herramienta para la educacion ambiental: conclusiones y reflexiones de un estudio en el ambito universitario
   Gomez T., 2010, REV VENEZ ECON CIENC, V16, P13
   Guerra M. T., 2012, I NACL EVALUACION ED, P79
   Gutierrez Vera D., 2003, PEDAGOGIA Y SABERES, P21, DOI [10.17227/01212494.18pys21.32, DOI 10.17227/01212494.18PYS21.32]
   H. Ayuntamiento de Toluca, 2013, PLAN MUN DES URB TOL
   H. Ayuntamiento municipio de Toluca, 2013, INV AR VERD MUN TOL
   Hernandez F.C., 2014, Metodologia de la Investigacion
   Herrera Soria José, 2014, ccm, V18, P126
   INEGI, 2016, INV NAC VIV 2016
   Instituto Nacional de Estadistica Geografia e Informatica. [INEGI], 2015, CAR ENT URB 2014
   Laca F. A., 2005, ENSELIANZA INVESTIGA, V10, P117
   Lupano Perugini María Laura, 2010, Cienc. Psicol., V4, P43
   Marion De la Cruz R., 2018, REV IBEROAMERICANA C, V5, P51
   Marron M. J., 1999, DIDACTICA GEOGRAFICA, V2, P85
   Melgarejo Vargas., 1994, ALTERIDADES, V4, P47
   Mikulic I. M., 2009, C INT PRACT PROF PSI, P511
   Millennium Ecosystem Assessment (MEA), 2005, EC HUM WEE BEING SYN
   Morales F. J., 2012, PAPELES GEOGRAFIA, P137
   Morales J. P., 2011, RECURSOS NATURALES A, P47
   OMS, 2018, FIS VIS
   OSTROM E., 2000, GACETA ECOLOGICA, V54, P43
   Padilla y Sotelo L., 2012, REV INVESTIGACIONES, P99, DOI [10.14350/rig.30335, DOI 10.14350/RIG.30335]
   Parales-Quenza CJ, 2007, REV LAT AM PSICOL, V39, P351
   Rivera-Jacinto Marco, 2009, Rev. perú. med. exp. salud publica, V26, P338
   Rizo Garcia Marta, 2006, CINTA MOEBIO
   Roth Eric U., 2000, Revista Ciencia y Cultura, V8, P63
   Sierra R., 1995, Tecnicas de investigacion social: teoria y ejercicios, V10
   Tabara J., 2018, REV INT SOCIOL, V59, P127, DOI [10.3989/ris.2001.i28.745, DOI 10.3989/RIS.2001.128.745]
   Tito O., 2013, REV INFORM CIENTIFIC, V80, P1
   Uribe M. L., 2014, PROCESOS HISTORICOS, P100
   Valadez A., 2002, REV ELECT PSICOLOGIA, V5, P2
   Valera S., 2015, ELEMENTOS BASICOS PS
   Vargas Andrés, 2018, Lect. Econ., P183, DOI 10.17533/udea.le.n88a06
   Vélez Restrepo Luis Aníbal, 2009, Rev. geogr. Norte Gd., P31
   Walker M, 2011, UNIVERSITAS, P85, DOI 10.17163/uni.n15.2011.03
   Ysunza M., 2003, CURRICULAR RES MEXIC, P125
   Zamorano B., 2009, REV EL ACTUAL INV ED, V9, P1
NR 66
TC 0
Z9 0
U1 0
U2 5
PU UNIV CHILE, FAC ARQUITECTURA & URBANISMO
PI SANTIAGO
PA CASILLA 3387, SANTIAGO, 00000, CHILE
SN 0717-5051
J9 REV URBAN
JI Rev. Urban.
PD JUN
PY 2020
VL 42
BP 151
EP 175
DI 10.5354/0717-5051.2020.56964
PG 25
WC Urban Studies
WE Emerging Sources Citation Index (ESCI)
SC Urban Studies
GA MG6YO
UT WOS:000546175900011
OA gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Ross, A
AF Ross, Andrew
TI Easy to say, hard to do: integrated surface water and groundwater
   management in the Murray-Darling Basin
SO WATER POLICY
LA English
DT Article
DE Entitlements; Governance; Groundwater; Integrated; Management
   organization; Murray-Darling Basin; Rules; Surface water
AB Integrated management of surface water and groundwater can provide efficient and flexible use of water through wet and dry periods, and address the impacts of water use on other users and the environment. It can also help adaptation to climate variation and uncertainty by means of supply diversification, storage and exchange. Integrated water management is affected by surface water and groundwater resources and their connections, water use, infrastructure, governance arrangements and interactions. Although the Murray-Darling Basin is considered to be a leading example of integrated water management, surface water and groundwater resources are generally managed separately. Key reasons for this separation include the historical priority given to surface water development, the relative neglect of groundwater management, shortfalls in information about connections between groundwater and surface water and their impacts, gaps and exemptions in surface water and groundwater use entitlements and rules, coordination problems, and limited stakeholder engagement. Integration of surface water and groundwater management can be improved by the establishment of more comprehensive water use entitlements and rules, with extended carry-over periods and legislated rules for aquifer storage and recovery. Collective surface water and groundwater management offers greater efficiency and better risk management than uncoordinated individual action. There are opportunities for more effective engagement of stakeholders in planning and implementation through decentralized catchment scale organizations.
C1 Australian Natl Univ, Fenner Sch Environm & Soc, Canberra, ACT 0200, Australia.
C3 Australian National University
RP Ross, A (corresponding author), Australian Natl Univ, Fenner Sch Environm & Soc, GPO Box 4, Canberra, ACT 0200, Australia.
EM a.ross@anu.edu.au
OI ross, andrew/0000-0001-5204-8485
CR Agrawal A, 2001, WORLD DEV, V29, P1649, DOI 10.1016/S0305-750X(01)00063-8
   Agrawal A., 2009, M SOC DIM CLIM CHANG
   [Anonymous], 2008, WATER MURRAY DARLING
   [Anonymous], 2009, AUSTR WAT REF 2009 2
   [Anonymous], 2008, RECOMMENDATIONS MODE
   [Anonymous], 2001, AUSTR WAT RES ASS 20
   [Anonymous], 2008, REPORT AUSTR GOVT CS
   [Anonymous], 2009, 18 WORLD IMACS MODSI
   Blomquist W., 2004, 3636 WORLD BANK
   Blomquist WilliamA., 1992, Dividing the waters: Governing groundwater in southern California
   Bowmer K., 2003, 28 INT HYDR WAT RES
   Bressers H., 2009, GOVERNANCE COMPLEXIT
   Brodie R., 2007, ADAPTIVE MANAGEMENT
   Connell D., 2007, MANAGING WATER AUSTR
   Council of Australian Government (CoAG), 2004, INT AGR NAT WAT IN
   Daniell KA, 2010, ECOL SOC, V15
   Evans R., 2007, IMPACT GROUNDWATER U
   Fullagar I., 2006, GROUNDWATER SURFACE, P353
   Fullagar I., 2004, RIVERS AQUIFERS CONJ
   Gardner Alex., 2009, Water Resources Law
   [GHD Pty Ltd AGT Pty Ltd], 2011, FEAS MAN AQ RECH AGR
   Halstead Paul, 1989, BAD YEAR EC CULTURAL, DOI [DOI 10.1017/CBO9780511521218, 10.1017/CBO9780511521218]
   Holling C.S., 1978, Adaptive environmental assessment and management
   Hostetler S., 2007, SCI DECISION MAKERS
   Lucy J., 2008, REGULATION LAWS AUST
   Macumber P., 2001, 9 MURR DARL BAS GROU
   Murray-Darling Basin Authority, 2010, GUID PROP BAS PLAN T
   National Water Commision (NWC), 2005, REG WAT RES ASS
   National Water Commission (NWC), 2010, AUSTR WAT MARK REP
   *NWC, 2007, AUSTR WAT RES 2005 B
   O'Keefe Vanessa, 2011, 52 GHD HAMST CONS NA
   Ostrom E, 2009, SCIENCE, V325, P419, DOI 10.1126/science.1172133
   PAHL-WOSTL C., 2007, ADAPTIVE INTEGRATED
   Richardson S., 2011, BASIN FUTURES
   Robins L, 2007, GEOGR RES-AUST, V45, P273, DOI 10.1111/j.1745-5871.2007.00460.x
   Ross A, 2008, INNOVATION IN ENVIRONMENTAL POLICY: INTEGRATING THE ENVIRONMENT FOR SUSTAINABILITY, P289
   Schlager E, 2008, EMBRACING WATERSHED POLITICS, P1
   Schlager E, 2007, AGRICULTURAL GROUNDWATER REVOLUTION: OPPORTUNITIES AND THREATS TO DEVELOPMENT, P131, DOI 10.1079/9781845931728.0131
   SMITH DI, 2001, WATER AUSTR
   Sophocleous M, 2002, HYDROGEOL J, V10, P52, DOI 10.1007/s10040-001-0170-8
   Sophocleous M, 2007, GROUND WATER, V45, P393, DOI 10.1111/j.1745-6584.2007.00322.x
   Thomas G.A., 2001, Designing successful groundwater banking programs in the Central Valley: lessons from experience
   Walters C., 1986, ADAPTIVE MANAGEMENT
   Winter TC., 1998, Groundwater and surface water: a single resource, V1139
   Woessner WW, 2000, GROUND WATER, V38, P423, DOI 10.1111/j.1745-6584.2000.tb00228.x
NR 45
TC 16
Z9 20
U1 0
U2 31
PU IWA PUBLISHING
PI LONDON
PA ALLIANCE HOUSE, 12 CAXTON ST, LONDON SW1H0QS, ENGLAND
SN 1366-7017
J9 WATER POLICY
JI Water Policy
PY 2012
VL 14
IS 4
BP 709
EP 724
DI 10.2166/wp.2012.129
PG 16
WC Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Water Resources
GA 965YC
UT WOS:000305802700010
DA 2025-01-10
ER

PT J
AU Kremenic, T
   Varotto, M
   Ferrarese, F
AF Kremenic, Tanja
   Varotto, Mauro
   Ferrarese, Francesco
TI Forgotten Ecological Corridors: A GIS Analysis of the Ditches and Hedges
   in the Roman Centuriation Northeast of Padua
SO SUSTAINABILITY
LA English
DT Article
DE heritage landscape management; historical rural landscapes; Roman
   limitatio; agroecological infrastructure; GIS digitisation
ID DRAINAGE NETWORKS
AB Studying historical rural landscapes beyond their archaeological and cultural significance, as has typically been addressed in previous research, is important in the context of current environmental challenges. Some historical rural landscapes, such as Roman land divisions, have persisted for more than 2000 years and may still contribute to sustainability goals. To assess this topic, the hydraulic and vegetation network of the centuriation northeast of Padua were studied, emphasising their multiple benefits. Their length, distribution, and evolution over time (2008-2022) were vectorised and measured using available digital terrain models and orthophotographs in a geographic information system (GIS). The results revealed a significant decline in the length of water ditches and hedgerows across almost all examined areas, despite their preservation being highlighted in regional and local spatial planning documents. These findings indicate the need for a better understanding of the local dynamics driving such trends and highlight the importance of adopting a more tailored approach to their planning. This study discusses the GIS metrics utilised and, in this way, contributes to landscape monitoring and restoration actions. Finally, a multifunctional approach to the sustainable planning of this area is proposed here-one that integrates the cultural archaeological heritage in question with environmental preservation and contemporary climate adaptation and mitigation strategies.
C1 [Kremenic, Tanja] Univ Insubria, Dept Human Sci Innovat & Terr, I-22100 Como, Italy.
   [Varotto, Mauro; Ferrarese, Francesco] Univ Padua, Dept Hist & Geog Sci & Ancient World, I-35141 Padua, Italy.
C3 University of Insubria; University of Padua
RP Kremenic, T (corresponding author), Univ Insubria, Dept Human Sci Innovat & Terr, I-22100 Como, Italy.
EM tanja.kremenic@uninsubria.it; mauro.varotto@unipd.it;
   francesco.ferrarese@unipd.it
RI Varotto, Mauro/GPF-8597-2022
FU Ministry of Education; Merit
FX This research is part of a PRIN project (Progetti di ricerca di
   rilevante interesse nazionale) titled 'Law and "Good Practices" in Land
   Management between Roman Antiquity and Today's Reality: A Sustainable
   Use of Land in the Light of Roman Land Surveying Texts' 2022-2025,
   coordinated by the Catholic University of Milano (L'Universita Cattolica
   del Sacro Cuore) and funded by Ministry of Education and Merit.
CR [Anonymous], 2020, Ministero per i Beni e le Attivita Culturali Piano Territoriale Regionale di Coordinamento-Documento per la Valorizzazione del Paesaggio Veneto
   [Anonymous], 2008, Valutazione Ambientale Strategica di Piano di Assetto Territoriale del Comune di Borgoricco, P13
   [Anonymous], 2012, Natural England Commissioned Report NECR102
   [Anonymous], 2005, Ecosystems and human well-being: Desertification synthesis
   [Anonymous], 2014, Linee Guida Sulle Buone Pratiche in Materia di Paesaggio del Graticolato Romano; Piano di Assetto del Territorio Intercomunale (P.A.T.I.) del Camposampierese, Provincia di Padova
   [Anonymous], Regione del Veneto Piano Territoriale Regionale di Coordinamento
   ARPAV Carta dei Suoli della Provincia di Padova, 2013, Provincia di Padova, P200
   ARPAV Provincia di Venezia, 2008, I Suoli della Provincia di Venezia, P268
   Borin M., 1997, Irrigation and Drainage Systems, V11, P61, DOI 10.1023/A:1005719329440
   Bosio L., 1989, Misurare la Terra: Centuriazione e Coloni nel Mondo Romano
   Caravello G.U., 1999, HUM ECOL REV, V6, P45
   centroculturalealdorossi, Centuriation Museum of Borgoricco/Museo Della Centuriazione Romana
   Columella L.J.M., 1941, De Re Rustica, V10
   Council of Europe, 2000, European Treaty Series, V176
   Cucchiaro S, 2021, AGR WATER MANAGE, V256, DOI 10.1016/j.agwat.2021.107083
   Dal Pozzo A., 2019, Lapporto Della Geogr. Tra Rivol. e Riforme, V32, P2489
   Dal Pozzo A., 2017, Ph.D. Dissertation
   Dal Pozzolo L., 2001, Fuori Citt
   DallAglio L., 2009, AGRI CENTURIATI, V6, P279
   de Haas T, 2017, J ARCHAEOL SCI-REP, V15, P470, DOI 10.1016/j.jasrep.2016.07.012
   Doermann L., 2023, Earth Observatory
   Dollinger J, 2015, AGRON SUSTAIN DEV, V35, P999, DOI 10.1007/s13593-015-0301-6
   Dover J.W., 2019, The Ecology of Hedgerows and Field Margins, P1, DOI [10.4324/9781315121413, DOI 10.4324/9781315121413]
   European Commission, 2021, EU Biodiversity Strategy for 2030: bringing nature back into our lives
   European Environment Agency (EEA), Copernicus Catalogue
   European Union, 2023, Nature Restoration Law
   Ferrario V., 2009, The New Urban QuestionUrbanism Beyond Neo-Liberalism, P637
   Harper K, 2018, SCIENCE OF ROMAN HISTORY: BIOLOGY, CLIMATE, AND THE FUTURE OF THE PAST, P11
   Herzon I, 2008, BIOL CONSERV, V141, P1171, DOI 10.1016/j.biocon.2008.03.005
   idt2.regione.veneto.it, Regione del Veneto-Il Geoportale dei dati Territoriali
   Kane S.C., 2022, Just One Rain Away: The Ethnography of River-City Flood Control
   Kratschmer S, 2024, BASIC APPL ECOL, V78, P28, DOI 10.1016/j.baae.2024.04.010
   Lachmann K., 2018, Gromatici Veteres Ex Recensione Caroli Lachmanni (Corpvs Agrimensorvm Romanorvm)
   Levavasseur F, 2012, HYDROL PROCESS, V26, P3393, DOI 10.1002/hyp.8422
   lsi-lastem, The Laghetti Plan
   Martellozzo Forin E., 2019, Disegni e Documenti per la Ricostruzione della Storia del Territorio, P37
   Matteazzi M., 2012, J. Anc. Stud, V3, P317
   McKenzie E., 1994, Privatopia: Homeowner Associations and the Rise of Residential Private Government
   Mengotti C., 2013, Antico e Sempre Nuovo: LAgro Centuriato a Nord-Est di Padova dalle Origini Allet Contemporanea, P19
   Pelgrom J., 2018, MELANGES LECOLE FRAN, V130.1, DOI [https://doi.org/10.4000/mefra.4770, DOI 10.4000/MEFRA.4770]
   Ragozhina N., 2024, BBC17 May
   Regoli E., 1993, Misurare la Terra: Centuriazione e Coloni nel Mondo Romano, P98
   Rodríguez-Antón A, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su15043388
   Santoro A, 2024, LANDSCAPE ECOL, V39, DOI 10.1007/s10980-024-01940-x
   Shaw RF, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0138306
   Smith William., 1898, A Concise Dictionary of Greek and Roman Antiquities Base on Sir William Smith's Larger Dictionary, and Incorporating the Results of Modern Research
   Sofia G, 2017, SCI REP-UK, V7, DOI 10.1038/srep40527
   Sofia G, 2017, LAND-BASEL, V6, DOI 10.3390/land6010003
   Sofia G, 2014, ANTHROPOCENE, V6, P48, DOI 10.1016/j.ancene.2014.06.005
   Tozzi P., 1987, Memoria della Terra, Storia dellUomo
   Turri E., 2001, La Megalopoli Padana, V3rd ed.
   UNESCO Netherlands Commission, 2021, Changing Minds, Not the Climate: Culture-Based Solutions to Local Climate Adaptation
   Varotto M., 2005, Le Terre della Tergola: Vicende e Luoghi dAcqua in Territorio Vigontino
   Varotto M., 2012, Antico e Sempre Nuovo: Lagro Centuriato a Nord-Est di Padova Dalle Origini Allet Contemporanea, P347
   Varro M.T., 1934, Rerum Rusticarum Libri Tres
NR 55
TC 0
Z9 0
U1 3
U2 3
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD OCT
PY 2024
VL 16
IS 20
AR 8962
DI 10.3390/su16208962
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 K1L9F
UT WOS:001341577900001
OA gold
DA 2025-01-10
ER

PT J
AU Charters, D
   Brown, RP
   Abrams, G
   Di Modica, K
   Pirson, S
   De Groote, I
   Ghiraldi, L
   Meloro, C
AF Charters, Daniel
   Brown, Richard P.
   Abrams, Gregory
   Di Modica, Kevin
   Pirson, Stephane
   De Groote, Isabelle
   Ghiraldi, Luca
   Meloro, Carlo
TI Mandibular ecomorphology in the genus <i>ursus</i> (Ursidae, Carnivora):
   relevance for the palaeoecological adaptations of cave bears (<i>U.
   spelaeus</i>) from Scladina cave
SO HISTORICAL BIOLOGY
LA English
DT Article; Early Access
DE Quaternary; palaeoclimate; evolutionary ecology; mandible; geometric
   morphometrics; Carnivora
ID COMPLETE MITOCHONDRIAL GENOME; BROWN BEAR; PALEOBIOLOGICAL IMPLICATIONS;
   GEOMETRIC MORPHOMETRICS; FUNCTIONAL-MORPHOLOGY; CLIMATE SURFACES; R
   PACKAGE; SHAPE; MIDDLE; REVEAL
AB Considerable morphological and ecological diversity has been found in extinct and extant members of the bear genus, Ursus, and appears to be key in explaining how they have thrived across vast ecological gradients. One example is the cave bear Ursus spelaeus. We applied 2D geometric morphometric techniques to describe morphological changes in the mandibles of extant Ursus species to further interpret the palaeoecology of U. spelaeus. Ursus species were discriminated using their mandibular morphology, which showed intra and interspecific shape variation that was indirectly linked to climatic adaptations through dietary variation. Mandibles of bears that inhabit colder, drier and more seasonal environments were generally slender with large diastema and a dorsoventrally smaller ramus. In contrast, species from warmer environments with higher levels of precipitation were found to have a dorsoventrally taller ramus (relative to the corpus). Discriminant function analyses of the morphology of U. spelaeus suggested adaptations to a series of fluctuating environments through time, helping to assess previously proposed Marine Isotope Stages for sedimentary deposits in Scladina Cave. Our geometric morphometrics analyses of bear mandibular ecomorphology demonstrates how geometric morphometrics provides a valuable tool to enhance paleoenvironmental reconstructions within deposits of the same fossil site.
C1 [Charters, Daniel; Brown, Richard P.; De Groote, Isabelle; Meloro, Carlo] Liverpool John Moores Univ, Res Ctr Evolutionary Anthropol & Palaeoecol, Sch Biol & Environm Sci, Liverpool, England.
   [Abrams, Gregory] Univ Ghent, Dept Archaeol, Reasearch Lab Biol Anthropol, ArcheOs, Ghent, Belgium.
   [Abrams, Gregory; Di Modica, Kevin] Scladina Cave Archaeol Ctr, Espace Museal Andenne, Andenne, Belgium.
   [Pirson, Stephane] Serv Publ Wallonie, Agence Wallonne Patrimoine, Direct Sci & Tech, Namur, Belgium.
   [Pirson, Stephane] Univ Liege, Ctr Europeen Archeometrie, Liege, Belgium.
   [De Groote, Isabelle] Univ Ghent, Dept Archaeol, Ghent, Belgium.
   [Ghiraldi, Luca] Museo Regionale Sci Nat Torino, Sez Zool, Turin, Italy.
C3 Liverpool John Moores University; Ghent University; University of Liege;
   Ghent University
RP Charters, D (corresponding author), Liverpool John Moores Univ, Res Ctr Evolutionary Anthropol & Palaeoecol, Sch Biol & Environm Sci, Liverpool, England.
EM D.J.Charters@2019.Ljmu.ac.uk
RI De Groote, Isabelle/AAB-4086-2020; Meloro, Carlo/U-4527-2019; Modica,
   Kévin/M-5148-2015
FU SYNTHESYS+ H2020 project [ES-TAF-2882]
FX D. Charters research visit to Madrid, Spain, was financially supported
   by SYNTHESYS+ H2020 project [ES-TAF-2882]: Ecomorphological evolution of
   cave and brown bears across the European Quaternary.
CR Adams DC, 2004, ITAL J ZOOL, V71, P5, DOI 10.1080/11250000409356545
   Adams Dean, 2024, CRAN
   Adams DC, 2015, EVOLUTION, V69, P823, DOI 10.1111/evo.12596
   Adams DC, 2013, METHODS ECOL EVOL, V4, P393, DOI 10.1111/2041-210X.12035
   [Anonymous], 1968, Pleistocene Mammals of Europe
   [Anonymous], 2014, The Scladina I-4A Juvenile Neandertal (Andenne, Belgium), Palaeoanthropology and Context
   AZZAROLI A, 1983, PALAEOGEOGR PALAEOCL, V44, P117, DOI 10.1016/0031-0182(83)90008-1
   Baken EK, 2021, METHODS ECOL EVOL, V12, P2355, DOI 10.1111/2041-210X.13723
   Barnes I, 2002, SCIENCE, V295, P2267, DOI 10.1126/science.1067814
   Baryshnikov G., 2007, Fauna of Russia and Neighboring Countries, new series, V147
   Baryshnikov Gennady F., 2013, Russian Journal of Theriology, V12, P107
   Baryshnikov GF, 2011, QUATERN INT, V245, P350, DOI 10.1016/j.quaint.2011.02.035
   Bastin B., 1992, Le contexte, V27, P59
   Beck HE, 2018, SCI DATA, V5, DOI 10.1038/sdata.2018.214
   Blain HA, 2014, CR PALEVOL, V13, P681, DOI 10.1016/j.crpv.2014.03.006
   Bocherens H, 2006, J HUM EVOL, V50, P370, DOI 10.1016/j.jhevol.2005.12.002
   Bocherens H, 1997, QUATERNARY RES, V48, P370, DOI 10.1006/qres.1997.1927
   Bocherens H., 2006, When Neanderthals and Modern Humans Met, P129
   Bocherens H, 2019, HIST BIOL, V31, P410, DOI 10.1080/08912963.2018.1465419
   Bocherens H, 2015, QUATERNARY SCI REV, V117, P42, DOI 10.1016/j.quascirev.2015.03.018
   Bocherens H, 2014, QUATERN INT, V339, P112, DOI 10.1016/j.quaint.2013.06.026
   Bocherens H, 2011, QUATERN INT, V245, P238, DOI 10.1016/j.quaint.2010.12.020
   Bon C, 2008, P NATL ACAD SCI USA, V105, P17447, DOI 10.1073/pnas.0806143105
   Bookstein FL, 1996, B MATH BIOL, V58, P313, DOI 10.1016/0092-8240(95)00329-0
   Bookstein FL., 1991, MORPHOMETRIC TOOLS L
   Cáceres N, 2014, J BIOGEOGR, V41, P501, DOI 10.1111/jbi.12203
   Charters D, 2022, PALAEOGEOGR PALAEOCL, V587, DOI 10.1016/j.palaeo.2021.110787
   Charters D, 2019, QUATERNARY SCI REV, V205, P76, DOI 10.1016/j.quascirev.2018.12.012
   Collyer ML, 2015, HEREDITY, V115, P357, DOI 10.1038/hdy.2014.75
   Collyer M. L., 2021, RRPP. Linear Model Evaluation with Randomized Residuals in a Permutation Procedure
   Collyer Michael, 2024, CRAN
   Collyer ML, 2018, METHODS ECOL EVOL, V9, P1772, DOI 10.1111/2041-210X.13029
   Cordy JM., 1992, Recherches aux grottes de Sclayn Volume 1: Le contexte. tudes et Recherches Archologiques de lUniversit de Lige, V27, P79
   Croizet A., 1828, Recherches Sur Les Ossemens Fossils du Dpartement du Puy-de-Dme, P224
   Cuvier G., 1823, Recherches sur les Ossemens fossiles
   Dabney J, 2013, P NATL ACAD SCI USA, V110, P15758, DOI 10.1073/pnas.1314445110
   Devze de Chabriol JS., 1827, Essai gologique et minralogique sur les environs dlssoire, department du Puy-de-Dme, et principalement sur la montagne de Boulade, avec la description et des figures lithographies des ossemens fossils qui ont t recueillis
   Fick SE, 2017, INT J CLIMATOL, V37, P4302, DOI 10.1002/joc.5086
   Figueirido B, 2009, J ZOOL, V277, P70, DOI 10.1111/j.1469-7998.2008.00511.x
   Fuchs M, 2015, BMC EVOL BIOL, V15, DOI 10.1186/s12862-015-0521-z
   Funk C, 2015, EARTH SYST SCI DATA, V7, P275, DOI 10.5194/essd-7-275-2015
   García-Vázquez A, 2023, MAMMAL RES, V68, P63, DOI 10.1007/s13364-022-00654-2
   Garsia N., 2003, Osos y otros carnivoros de la Sierra de Atapuerca
   GOWER JC, 1975, PSYCHOMETRIKA, V40, P33, DOI 10.1007/BF02291478
   Haesaerts P., 1992, Recherches aux grottes de Sclayn Volume 1: Le contexte. tudes et Recherches Archologiques de lUniversit de Lige, V27, P33
   Hailer F, 2012, SCIENCE, V336, P344, DOI 10.1126/science.1216424
   HANNI C, 1994, P NATL ACAD SCI USA, V91, P12336, DOI 10.1073/pnas.91.25.12336
   Hijmans R. J., 2001, Plant Genetic Resources Newsletter, P15
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Hijmans RJ., 2012, DIVA-GIS Version 7.5
   Karger DN, 2017, SCI DATA, V4, DOI 10.1038/sdata.2017.122
   Klingenberg CP, 2013, HYSTRIX, V24, P15, DOI 10.4404/hystrix-24.1-7691
   Klingenberg CP, 2011, MOL ECOL RESOUR, V11, P353, DOI 10.1111/j.1755-0998.2010.02924.x
   Knapp M, 2009, MOL ECOL, V18, P1225, DOI 10.1111/j.1365-294X.2009.04088.x
   Koppen W., 1936, Handbuch der Klimatologie, P7
   Krajcarz M, 2016, QUATERNARY SCI REV, V131, P51, DOI 10.1016/j.quascirev.2015.10.028
   Krechmar MA, 1995, RUSS J ECOL+, V26, P436
   Kumar V, 2017, SCI REP-UK, V7, DOI 10.1038/srep46487
   Lambeck K, 2002, NATURE, V419, P199, DOI 10.1038/nature01089
   Linnaeus C., 1758, HOLMIAE LAURENTII SA, P1, DOI [10.5962/bhl.title.542, DOI 10.5962/BHL.TITLE.542]
   Liu SP, 2014, CELL, V157, P785, DOI 10.1016/j.cell.2014.03.054
   Loreille O, 2001, CURR BIOL, V11, P200, DOI 10.1016/S0960-9822(01)00046-X
   Männel TT, 2007, GLOBAL ECOL BIOGEOGR, V16, P583, DOI 10.1111/j.1466-8238.2007.00322.x
   López-García JM, 2017, HIST BIOL, V29, P1125, DOI 10.1080/08912963.2017.1288229
   Martin L.D., 1989, P536
   MCLELLAN B, 1994, BEARS - THEIR BIOLOGY AND MANAGEMENT, P85
   Meloro C, 2022, QUATERNARY SCI REV, V281, DOI 10.1016/j.quascirev.2022.107419
   Meloro C, 2017, J ZOOL SYST EVOL RES, V55, P269, DOI 10.1111/jzs.12171
   Meloro C, 2011, EVOL BIOL, V38, P465, DOI 10.1007/s11692-011-9135-6
   Meloro C, 2011, J VERTEBR PALEONTOL, V31, P428, DOI 10.1080/02724634.2011.550357
   Meloro C, 2008, ZOOL J LINN SOC-LOND, V154, P832, DOI 10.1111/j.1096-3642.2008.00429.x
   Miller W, 2012, P NATL ACAD SCI USA, V109, pE2382, DOI 10.1073/pnas.1210506109
   Mitteroecker P, 2013, HYSTRIX, V24, P59, DOI 10.4404/hystrix-24.1-6369
   Mitteroecker P, 2009, EVOL BIOL, V36, P235, DOI 10.1007/s11692-009-9055-x
   Pallas PS., 1780, Fasciculus XIV, V1, P1
   Pasitschniak-Arts Maria, 1993, Mammalian Species, V439, P1
   Peel MC, 2007, HYDROL EARTH SYST SC, V11, P1633, DOI 10.5194/hess-11-1633-2007
   Peigné S, 2009, P NATL ACAD SCI USA, V106, P15390, DOI 10.1073/pnas.0907373106
   Pérez-Ramos A, 2020, SCI ADV, V6, DOI 10.1126/sciadv.aay9462
   Pérez-Ramos A, 2019, HIST BIOL, V31, P461, DOI 10.1080/08912963.2018.1525366
   Phipps C.J., 1774, VOYAGE N POLE UNDERT
   Pirson S., 2008, Memoirs of the Geological Survey of Belgium, V55, P71
   Pirson S., 2007, Stratigraphie, Sdimentogense et Paloenvironnement, V1, P435
   Prez-Ramos A., 2020, Three-dimensional dental topography and feeding ecology in the extinct cave bear. Biol, DOI [10.1098/rsbl.2020.0792, DOI 10.1098/RSBL.2020.0792]
   QUINIF Y, 1994, B SOC GEOL FR, V165, P603
   Raats M. M., 1992, Food Quality and Preference, V3, P89, DOI 10.1016/0950-3293(91)90028-D
   Rabeder G., 2003, P 9 INT CAV BEAR C C, P49
   Rabeder G., 2008, HOHLE, V59, P59
   Rabeder G., 2010, MITTEILUNG KOMMISSIO, V17, P1
   Rabeder G., 2011, Mitt der Kommission fr Quartrforschung der sterreichischen Akad der Wissen, V20, P43
   Raia P, 2004, ITAL J ZOOL, V71, P45, DOI 10.1080/11250000409356549
   Rinker DC, 2019, P NATL ACAD SCI USA, V116, P13446, DOI 10.1073/pnas.1901093116
   Rohlf FJ, 2015, HYSTRIX, V26, P9, DOI 10.4404/hystrix-26.1-11264
   Rohlf FJ, 2000, SYST BIOL, V49, P740, DOI 10.1080/106351500750049806
   ROHLF FJ, 1990, SYST ZOOL, V39, P40, DOI 10.2307/2992207
   ROHLF FJ, 1993, TRENDS ECOL EVOL, V8, P129, DOI 10.1016/0169-5347(93)90024-J
   Rosenmuller JC., 1794, LL.AA.M. in Theatro anatomicoLipsiensi Prosector assumto socio Io. Chr. Aug. Heinroth Lips
   Rossi M., 2001, Cadernos Laboratorio Xeoloxico de Laxe, V26, P317
   Sharief A, 2020, GLOB ECOL CONSERV, V21, DOI 10.1016/j.gecco.2019.e00900
   Simonet P., 1992, Recherches aux grottes de Sclayn Volume 1: Le contexte. Etudes et Recherches Archologiques de lUniversit de Lige, V27, P127
   Slice DE, 2007, ANNU REV ANTHROPOL, V36, P261, DOI 10.1146/annurev.anthro.34.081804.120613
   Stiller M, 2014, QUATERN INT, V339, P224, DOI 10.1016/j.quaint.2013.09.023
   Valdiosera CE, 2008, P NATL ACAD SCI USA, V105, P5123, DOI 10.1073/pnas.0712223105
   Van Heteren A.H., 2009, SLOVENSKY KRAS ACTA, V47, P33
   Van Heteren AH, 2019, HIST BIOL, V31, P500, DOI 10.1080/08912963.2018.1547901
   van Heteren AH, 2019, HIST BIOL, V31, P485, DOI 10.1080/08912963.2018.1487965
   van Heteren AH, 2016, ORG DIVERS EVOL, V16, P299, DOI 10.1007/s13127-015-0238-2
   van Heteren AH, 2014, QUATERN INT, V339, P209, DOI 10.1016/j.quaint.2013.10.056
   von Reichenau W., 1904, Jahrbucherdes Nassauischen Vereins fur Naturkunde, V57, P1
   Zelditch ML., 2004, Geometric Morphometrics for Biologists: A Primer
   Zollikofer CPE, 2002, P ROY SOC B-BIOL SCI, V269, P801, DOI 10.1098/rspb.2002.1960
NR 111
TC 0
Z9 0
U1 6
U2 6
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 2024 AUG 4
PY 2024
DI 10.1080/08912963.2024.2377703
EA AUG 2024
PG 15
WC Biology; Paleontology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Life Sciences & Biomedicine - Other Topics; Paleontology
GA A6T1F
UT WOS:001283831500001
OA hybrid
DA 2025-01-10
ER

PT J
AU Wang, Q
   Wang, HT
   Ren, LH
   Chen, JL
   Wang, XA
AF Wang, Qi
   Wang, Haitao
   Ren, Lanhong
   Chen, Jianli
   Wang, Xiaona
TI Hourly impact of urban features on the spatial distribution of land
   surface temperature: A study across 30 cities
SO SUSTAINABLE CITIES AND SOCIETY
LA English
DT Article
DE Diurnal cycle; Land surface temperature; Machine learning; Urban
   morphology; Google earth engine
ID HEAT-ISLAND; AIR-TEMPERATURE; CLIMATE-CHANGE; COVER; VARIABILITY;
   PATTERN
AB Global warming and the urban heat island effect exacerbate excessive heat in urban environments, adversely impacting human health. Effective urban planning can mitigate these effects by influencing land surface temperature (LST). While previous studies have examined the influence of urban features on LST across seasons and between day and night, detailed hour-by-hour comparisons remain unexplored. This study addresses this gap by analyzing the hourly impacts of various urban features on LST in 30 U.S. cities using geostationary weather satellite data. We employed cloud-based analytics and machine learning techniques to aggregate data from thousands of images, identifying the relative importance and correlation curve of each urban feature on LST at each hour. Our findings revealed two distinct correlation patterns: dynamic daytime patterns with significant hourly variability and stable nocturnal patterns with minimal hourly differences. These results demonstrate that sunlight intensity greatly affects the correlation between urban features and LST. Urban planners should therefore consider broader patterns rather than focusing on specific hours. These insights provide valuable guidance for landscape and urban planners in developing strategies for climate adaptation and heatwave mitigation, contributing to the growing body of literature on sustainable cities.
C1 [Wang, Qi; Wang, Xiaona] Hebei Agr Univ, Coll Landscape Architecture & Tourism, Baoding 071000, Peoples R China.
   [Wang, Haitao] Tianjin Chengjian Univ, Sch Architecture, Tianjin 300384, Peoples R China.
   [Ren, Lanhong] Nanjing Tech Univ, Coll Art & Design, Nanjing 211816, Peoples R China.
   [Chen, Jianli] Univ Utah, Dept Civil & Environm Engn, Salt Lake City, UT 84112 USA.
C3 Hebei Agricultural University; Tianjin Chengjian University; Nanjing
   Tech University; Utah System of Higher Education; University of Utah
RP Wang, Q (corresponding author), Hebei Agr Univ, 2596 Lekai South St, Baoding 071000, Peoples R China.
EM wikiwang0421@hebau.edu.cn
RI Wang, Qi/HRE-4389-2023
OI Wang, Qi/0000-0001-6270-4650
FU National Natural Science Foundation of China [52208019]
FX This work was supported by National Natural Science Foundation of China
   [grant number 52208019] .
CR Adeyeri OE, 2024, SUSTAIN CITIES SOC, V101, DOI 10.1016/j.scs.2023.105072
   Alexander C, 2021, INT J APPL EARTH OBS, V95, DOI 10.1016/j.jag.2020.102265
   Beck HE, 2018, SCI DATA, V5, DOI 10.1038/sdata.2018.214
   Bera D, 2022, J CLEAN PROD, V379, DOI 10.1016/j.jclepro.2022.134735
   Bokaie M, 2016, SUSTAIN CITIES SOC, V23, P94, DOI 10.1016/j.scs.2016.03.009
   Botje D, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14102296
   Burke M, 2015, NATURE, V527, P235, DOI 10.1038/nature15725
   Cai XY, 2023, HUM SOC SCI COMMUN, V10, DOI 10.1057/s41599-023-02209-5
   Cao X, 2010, LANDSCAPE URBAN PLAN, V96, P224, DOI 10.1016/j.landurbplan.2010.03.008
   Chang Y, 2021, SCI TOTAL ENVIRON, V763, DOI 10.1016/j.scitotenv.2020.144224
   Chen DS, 2022, SCI TOTAL ENVIRON, V825, DOI 10.1016/j.scitotenv.2022.154006
   Chen XT, 2022, SUSTAIN CITIES SOC, V87, DOI 10.1016/j.scs.2022.104247
   Chen Y, 2023, SUSTAIN CITIES SOC, V89, DOI 10.1016/j.scs.2022.104374
   Dewan A, 2021, SUSTAIN CITIES SOC, V71, DOI 10.1016/j.scs.2021.102926
   Dewitz Jon, 2023, USGS
   Estoque RC, 2017, SCI TOTAL ENVIRON, V577, P349, DOI 10.1016/j.scitotenv.2016.10.195
   Fisher A, 2019, J MACH LEARN RES, V20
   Friedman JH, 2001, ANN STAT, V29, P1189, DOI 10.1214/aos/1013203451
   Gao K, 2020, SCI TOTAL ENVIRON, V740, DOI 10.1016/j.scitotenv.2020.139754
   Gasparrini A, 2017, LANCET PLANET HEALTH, V1, pE360, DOI 10.1016/S2542-5196(17)30156-0
   Guha S, 2018, EUR J REMOTE SENS, V51, P667, DOI 10.1080/22797254.2018.1474494
   Han DR, 2023, SUSTAIN CITIES SOC, V99, DOI 10.1016/j.scs.2023.104933
   Herfort B, 2023, NAT COMMUN, V14, DOI 10.1038/s41467-023-39698-6
   Hesselbarth MHK, 2019, ECOGRAPHY, V42, P1648, DOI 10.1111/ecog.04617
   Ho HC, 2014, REMOTE SENS ENVIRON, V154, P38, DOI 10.1016/j.rse.2014.08.012
   Kashki A, 2021, URBAN CLIM, V37, DOI 10.1016/j.uclim.2021.100832
   Lemus-Canovas M, 2020, SCI TOTAL ENVIRON, V699, DOI 10.1016/j.scitotenv.2019.134307
   Li DHW, 2012, ENERGY, V42, P103, DOI 10.1016/j.energy.2012.03.044
   Li HF, 2021, BUILD ENVIRON, V204, DOI 10.1016/j.buildenv.2021.108132
   Li Z, 2022, SUSTAIN CITIES SOC, V78, DOI 10.1016/j.scs.2021.103392
   Liang SL, 2001, REMOTE SENS ENVIRON, V76, P213, DOI 10.1016/S0034-4257(00)00205-4
   Lin ZL, 2024, SUSTAIN CITIES SOC, V101, DOI 10.1016/j.scs.2024.105190
   Lin ZL, 2023, BUILD ENVIRON, V243, DOI 10.1016/j.buildenv.2023.110732
   Logan TM, 2020, REMOTE SENS ENVIRON, V247, DOI 10.1016/j.rse.2020.111861
   Lu LL, 2023, SUSTAIN CITIES SOC, V92, DOI 10.1016/j.scs.2023.104505
   Massaro E, 2023, NAT COMMUN, V14, DOI 10.1038/s41467-023-38596-1
   Mohajerani A, 2017, J ENVIRON MANAGE, V197, P522, DOI 10.1016/j.jenvman.2017.03.095
   Molnar C, 2020, COMM COM INF SC, V1323, P417, DOI 10.1007/978-3-030-65965-3_28
   NOAA, 2019, GOES-R series product definition and users' guide
   O'Brien RM, 2007, QUAL QUANT, V41, P673, DOI 10.1007/s11135-006-9018-6
   Oke T. R., 2017, Urban Climates, DOI [10.1017/9781139016476, DOI 10.1017/9781139016476]
   Pande CB, 2024, J CLEAN PROD, V444, DOI 10.1016/j.jclepro.2024.141035
   Peng J, 2018, REMOTE SENS ENVIRON, V215, P255, DOI 10.1016/j.rse.2018.06.010
   Potapov P, 2021, REMOTE SENS ENVIRON, V253, DOI 10.1016/j.rse.2020.112165
   Ramakrishnan S, 2017, APPL ENERG, V194, P410, DOI 10.1016/j.apenergy.2016.04.084
   Refaeilzadeh P., 2009, ENCY DATABASE SYSTEM, V5, P532, DOI [DOI 10.1007/978-0-387-39940-9565, DOI 10.1007/978-0-387-39940-9_565, 10.1007/978-0-387-39940-9_565]
   Ren JY, 2023, ISCIENCE, V26, DOI 10.1016/j.isci.2022.105820
   Smith IA, 2023, SCI TOTAL ENVIRON, V857, DOI 10.1016/j.scitotenv.2022.159663
   Smith R.B., 2010, The heat budget of the earth's surface deduced from space"
   Song JC, 2020, LANDSCAPE URBAN PLAN, V198, DOI 10.1016/j.landurbplan.2020.103794
   Stevens FR, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0107042
   Sun FY, 2020, J CLEAN PROD, V258, DOI 10.1016/j.jclepro.2020.120706
   Tan XY, 2021, SUSTAIN CITIES SOC, V67, DOI 10.1016/j.scs.2021.102711
   Tang CL, 2023, ATMOSPHERE-BASEL, V14, DOI 10.3390/atmos14030576
   Trlica A, 2017, EARTHS FUTURE, V5, P1084, DOI 10.1002/2017EF000569
   Trost J. E., 1986, Qualitative Sociology, V9, P54, DOI [10.1007/bf00988249, DOI 10.1007/BF00988249]
   Ullah S, 2023, WEATHER CLIM EXTREME, V40, DOI 10.1016/j.wace.2023.100570
   Wang Q, 2023, SUSTAIN CITIES SOC, V91, DOI 10.1016/j.scs.2023.104432
   Wang Q, 2022, SUSTAIN CITIES SOC, V79, DOI 10.1016/j.scs.2022.103722
   Wei GE, 2024, ENVIRON IMPACT ASSES, V106, DOI 10.1016/j.eiar.2024.107533
   Wu WB, 2022, LANDSCAPE URBAN PLAN, V226, DOI 10.1016/j.landurbplan.2022.104499
   Yan H, 2014, BUILD ENVIRON, V76, P44, DOI 10.1016/j.buildenv.2014.03.007
   Yao X, 2022, SUSTAIN CITIES SOC, V86, DOI 10.1016/j.scs.2022.104165
   Yu WB, 2024, ISCIENCE, V27, DOI 10.1016/j.isci.2024.109728
   Zeng P, 2022, SUSTAIN CITIES SOC, V78, DOI 10.1016/j.scs.2021.103599
   Zhang MM, 2024, SUSTAIN CITIES SOC, V106, DOI 10.1016/j.scs.2024.105345
   Zhang MM, 2024, J ENVIRON MANAGE, V356, DOI 10.1016/j.jenvman.2024.120560
   Zhang MM, 2023, SUSTAIN CITIES SOC, V96, DOI 10.1016/j.scs.2023.104663
   Zhang MM, 2023, URBAN CLIM, V47, DOI 10.1016/j.uclim.2022.101347
   Zhang R, 2023, SUSTAIN CITIES SOC, V99, DOI 10.1016/j.scs.2023.104981
   Zhang ZC, 2023, URBAN CLIM, V49, DOI 10.1016/j.uclim.2023.101553
   Zhou WQ, 2014, LANDSCAPE ECOL, V29, P153, DOI 10.1007/s10980-013-9950-5
   Zhou WQ, 2011, LANDSCAPE URBAN PLAN, V102, P54, DOI 10.1016/j.landurbplan.2011.03.009
NR 73
TC 0
Z9 0
U1 22
U2 22
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 OCT 15
PY 2024
VL 113
AR 105701
DI 10.1016/j.scs.2024.105701
EA JUL 2024
PG 17
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 A7T3V
UT WOS:001284520800001
DA 2025-01-10
ER

PT J
AU Zeng, P
   Liu, YY
   Tian, T
   Che, Y
   Helbich, M
AF Zeng, Peng
   Liu, Yaoyi
   Tian, Tian
   Che, Yue
   Helbich, Marco
TI Geographic inequalities in park visits to mitigate thermal discomfort: A
   novel approach based on thermal differences and cellular population data
SO URBAN FORESTRY & URBAN GREENING
LA English
DT Article
DE Urban park; Population density; Thermal comfort; Cooling accessibility;
   Supply -demand mismatch
ID GREEN SPACES; ACCESSIBILITY; DISPARITIES; ACCESS; MODEL; CITY; AIR
AB Climate change-intensified urban warming has brought attention to urban parks' spatial allocation due to their cooling effects. However, conventional accessibility assessments of park cooling effects consider temperature and size, overlooking critical factors such as thermal comfort and supply and demand differences in thermal environments, which more accurately represent public thermal stress. We developed a multimode Gaussian-based Huff three-step floating catchment area method based on thermal stress differences between population locations and parks. This method integrates thermal comfort and cellular population data to assess the spatial mismatch between the supply and demand for park cooling services in Shanghai. Our findings show that most central and developing urban areas have excellent park cooling accessibility. However, considering population demand, central Shanghai requires improved internal park planning to enhance the cooling supply. In contrast, Shanghai's suburban areas exhibit significant supply-demand imbalances, especially in the south and southeast; they require an enhanced cooling supply through planning interventions. Incorporating thermal comfort differences into calculations shifts the highest per capita cooling supply area from the outer suburbs to the suburbs, substantially reducing areas with high demand but low supply. Our novel analytical approach to assessing park cooling accessibility can assist policymakers in developing precise climate adaptation strategies.
C1 [Zeng, Peng; Liu, Yaoyi; Tian, Tian; Che, Yue] East China Normal Univ, Sch Ecol & Environm Sci, Shanghai Key Lab Urban Ecol Proc & Ecorestorat, Inst Ecochongming IEC, Shanghai 200241, Peoples R China.
   [Zeng, Peng; Helbich, Marco] Univ Utrecht, Fac Geosci, Dept Human Geog & Spatial Planning, NL-3584 CS Utrecht, Netherlands.
C3 East China Normal University; Utrecht University
RP Che, Y (corresponding author), East China Normal Univ, Sch Ecol & Environm Sci, Shanghai 200241, Peoples R China.
EM yche@des.ecnu.edu.cn
RI liu, yuxin/GRY-3592-2022; Zeng, Peng/KMX-9694-2024; Che,
   Yue/GRE-7952-2022
FU Program of the Science and Technology Commission of Shanghai
   Municipality [22dz1208004]; Fundamental Research Funds for the Central
   Universities [2022ECNU-XWK-XK001, YBNLTS2023-013]; China Scholarship
   Council (CSC) [202206140068]
FX This research was supported by the program of the Science and Technology
   Commission of Shanghai Municipality (Grant No. 22dz1208004) , and the
   Fundamental Research Funds for the Central Universities (Grant No.
   2022ECNU-XWK-XK001; Grant No. YBNLTS2023-013) . Peng Zeng was funded by
   the China Scholarship Council (CSC) (Grant No. 202206140068) .
CR AghaKouchak A, 2020, ANNU REV EARTH PL SC, V48, P519, DOI 10.1146/annurev-earth-071719-055228
   ANSELIN L, 1995, GEOGR ANAL, V27, P93, DOI 10.1111/j.1538-4632.1995.tb00338.x
   Benali A, 2012, REMOTE SENS ENVIRON, V124, P108, DOI 10.1016/j.rse.2012.04.024
   Bondarenko Maksym, 2020, UOSIR, DOI 10.5258/SOTON/WP00698
   Buzan JR, 2015, GEOSCI MODEL DEV, V8, P151, DOI 10.5194/gmd-8-151-2015
   Cao YN, 2021, LAND USE POLICY, V108, DOI 10.1016/j.landusepol.2021.105536
   Chen M, 2022, J CLEAN PROD, V334, DOI 10.1016/j.jclepro.2021.130252
   Chen YY, 2018, URBAN FOR URBAN GREE, V31, P130, DOI 10.1016/j.ufug.2018.02.005
   Dai D, 2011, LANDSCAPE URBAN PLAN, V102, P234, DOI 10.1016/j.landurbplan.2011.05.002
   Dong JQ, 2020, LANDSCAPE URBAN PLAN, V203, DOI 10.1016/j.landurbplan.2020.103907
   Du CL, 2022, J ENVIRON MANAGE, V317, DOI 10.1016/j.jenvman.2022.115346
   Feng L, 2020, ECOL INDIC, V110, DOI 10.1016/j.ecolind.2019.105798
   Feng RD, 2023, LANDSCAPE URBAN PLAN, V231, DOI 10.1016/j.landurbplan.2022.104643
   Gao Z, 2022, SUSTAIN CITIES SOC, V81, DOI 10.1016/j.scs.2022.103870
   Gunawardena KR, 2017, SCI TOTAL ENVIRON, V584, P1040, DOI 10.1016/j.scitotenv.2017.01.158
   Guo SH, 2019, LANDSCAPE URBAN PLAN, V191, DOI 10.1016/j.landurbplan.2019.103642
   He BJ, 2021, ENVIRON RES, V193, DOI 10.1016/j.envres.2020.110584
   Hu SJ, 2020, CITIES, V105, DOI 10.1016/j.cities.2020.102815
   Hu Y., 2005, APPL METEOROLOGY
   Hua JY, 2021, SUSTAIN CITIES SOC, V64, DOI 10.1016/j.scs.2020.102507
   Khavarian-Garmsir AR, 2023, CITIES, V132, DOI 10.1016/j.cities.2022.104101
   Kuras ER, 2017, ENVIRON HEALTH PERSP, V125, DOI 10.1289/EHP556
   Li QF, 2020, INJURY PREV, V26, P116, DOI 10.1136/injuryprev-2018-043071
   [李仕峰 Li Shifeng], 2013, [地理与地理信息科学, Geography and Geo-information Science], V29, P112
   Li YL, 2023, LANDSCAPE URBAN PLAN, V239, DOI 10.1016/j.landurbplan.2023.104842
   Liang HL, 2023, SUSTAIN CITIES SOC, V91, DOI 10.1016/j.scs.2023.104456
   Lin WQ, 2015, LANDSCAPE URBAN PLAN, V134, P66, DOI 10.1016/j.landurbplan.2014.10.012
   Lin Y, 2020, J CLEAN PROD, V262, DOI 10.1016/j.jclepro.2020.121411
   Liu D, 2021, URBAN FOR URBAN GREE, V59, DOI 10.1016/j.ufug.2021.127029
   Luo J, 2014, T GIS, V18, P436, DOI 10.1111/tgis.12096
   Millward H, 2013, J TRANSP GEOGR, V28, P101, DOI 10.1016/j.jtrangeo.2012.11.012
   Parsons K., 2007, Human thermal environments: the effects of hot, moderate, and cold environments on human health, comfort and performance, DOI 10.1201/9781420025248
   Peng J, 2021, REMOTE SENS ENVIRON, V252, DOI 10.1016/j.rse.2020.112135
   Pereira RHM, 2019, J TRANSP GEOGR, V74, P321, DOI 10.1016/j.jtrangeo.2018.12.005
   Pinto LV, 2022, GEOGR SUSTAIN, V3, P74, DOI 10.1016/j.geosus.2022.03.001
   Qiu KB, 2020, SUSTAIN CITIES SOC, V52, DOI 10.1016/j.scs.2019.101864
   Shanghai Municipal Bureau of Statistics, 2021, Shanghai Statistical Yearbook 2021.
   Shanghai Municipal People's Government, 2018, Shanghai Master Plan (20172035)
   Shen YA, 2017, URBAN FOR URBAN GREE, V27, P59, DOI 10.1016/j.ufug.2017.06.018
   Shi MQ, 2023, SUSTAIN CITIES SOC, V93, DOI 10.1016/j.scs.2023.104519
   Shi Y, 2021, SCI TOTAL ENVIRON, V771, DOI 10.1016/j.scitotenv.2021.145381
   Sims K., 2023, LandScan Global 2022 Version 2022), DOI [10.48690/1529167, DOI 10.48690/1529167]
   Skelhorn C, 2014, LANDSCAPE URBAN PLAN, V121, P129, DOI 10.1016/j.landurbplan.2013.09.012
   Subal J, 2021, INT J HEALTH GEOGR, V20, DOI 10.1186/s12942-021-00263-3
   Thom EC., 1959, Weatherwise, V12, P57, DOI [10.1080/00431672.1959.9926960, DOI 10.1080/00431672.1959.9926960]
   Wan N, 2012, INT J GEOGR INF SCI, V26, P1073, DOI 10.1080/13658816.2011.624987
   Wang F., 2014, QUANTITATIVE METHODS
   Wong NH, 2021, NAT REV EARTH ENV, V2, P166, DOI 10.1038/s43017-020-00129-5
   Wu CY, 2021, FRONT ENV SCI-SWITZ, V9, DOI 10.3389/fenvs.2021.657969
   Wu LF, 2021, ECOL INDIC, V121, DOI 10.1016/j.ecolind.2020.107080
   Wu W, 2023, URBAN FOR URBAN GREE, V82, DOI 10.1016/j.ufug.2023.127893
   Xiao Y, 2019, LANDSCAPE URBAN PLAN, V181, P80, DOI 10.1016/j.landurbplan.2018.09.013
   Xu HQ, 2017, ENERG BUILDINGS, V150, P598, DOI 10.1016/j.enbuild.2017.06.003
   Yu ZW, 2020, URBAN FOR URBAN GREE, V49, DOI 10.1016/j.ufug.2020.126630
   Zare S, 2018, WEATHER CLIM EXTREME, V19, P49, DOI 10.1016/j.wace.2018.01.004
   Zeng P, 2024, BUILD ENVIRON, V253, DOI 10.1016/j.buildenv.2024.111291
   Zeng P, 2022, LANDSCAPE URBAN PLAN, V226, DOI 10.1016/j.landurbplan.2022.104490
   Zeng P, 2022, SUSTAIN CITIES SOC, V82, DOI 10.1016/j.scs.2022.103899
   Zhang KT, 2023, NAT PROD RES, DOI [10.1080/14786419.2023.2291823, 10.1109/NOMS56928.2023.10154321, 10.1038/s41586-023-05911-1, 10.1038/s44222-023-00064-2]
   Zhou CH, 2022, CITIES, V129, DOI 10.1016/j.cities.2022.103804
NR 60
TC 0
Z9 0
U1 10
U2 10
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 128419
DI 10.1016/j.ufug.2024.128419
EA JUN 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 XF5T9
UT WOS:001260288800001
DA 2025-01-10
ER

PT J
AU Peng, J
   Dan, YZ
   Yu, XY
   Xu, DM
   Yang, ZW
   Wang, Q
AF Peng, Jian
   Dan, Yuzhuo
   Yu, Xiaoyu
   Xu, Dongmei
   Yang, Zhiwei
   Wang, Qi
TI Response of urban green space cooling effect to urbanization in the
   Three Ring Road area of Changsha City
SO SUSTAINABLE CITIES AND SOCIETY
LA English
DT Article
DE Urban green space; Cooling effect; Response to urbanization; Stage
   characteristics; Dominant factors
ID HEAT-ISLAND; CLIMATE; PATTERNS; IMPACT; SIZE
AB The significance of urban green space (UGS) in alleviating the urban heat island effect has attracted increasing attentions. The size, growth dynamics, and surroundings of UGS evolve with urbanization. However, the impact of these changes on the UGS cooling remains unknown, hindering the formulation of targeted greening policies at different urbanization stages. Focused on the Three Ring Road area in Changsha City, comprehensive urbanization indexes from 2000 to 2020 were computed, identifying the periods characterized by high-speed growth, transition, and steady development. By calculating the cooling indicators of UGS, employing partial correlation analysis and geographic detectors, this study clarified the determinants of the cooling effect of UGS. Results revealed that urbanization significantly impacted the cooling effect of UGS, with the cooling gradient, intensity, range, and distance exhibiting a gradual increase. Meanwhile, cooling efficiency demonstrated an initial ascent followed by a subsequent decline. Notably, the pivotal factors influencing the cooling effect of UGS shifted from external factors (surrounding construction land and ecological land) to internal factors (growth status), and eventually to the synergy of both internal and external factors. This study contributed valuable insights for delineating optimal UGS cooling strategies across diverse urbanization stages to improve urban climate adaptability.
C1 [Peng, Jian; Yu, Xiaoyu; Xu, Dongmei; Yang, Zhiwei] Peking Univ, Coll Urban & Environm Sci, Lab Earth Surface Proc, Minist Educ, Beijing 100871, Peoples R China.
   [Dan, Yuzhuo; Wang, Qi] Peking Univ, Sch Urban Planning & Design, Shenzhen Grad Sch, Key Lab Environm & Urban Sci, Shenzhen 518055, Peoples R China.
C3 Peking University; Peking University
RP Peng, J (corresponding author), Peking Univ, Coll Urban & Environm Sci, Lab Earth Surface Proc, Minist Educ, Beijing 100871, Peoples R China.
EM jianpeng@urban.pku.edu.cn
RI qi, wang/JUV-2984-2023; Xu, Dongmei/X-6544-2019; Yu,
   Xiaoyu/JMB-8461-2023; Zhang, Hongyang/IAR-1565-2023; Peng,
   Jian/AAO-6397-2020
OI peng, jian/0000-0003-0332-0248
FU National Natural Science Foundation of China [U20A2084]
FX <BOLD>Acknowledgements</BOLD> This research was financially supported by
   National Natural Science Foundation of China (U20A2084) .
CR Asgarian A, 2015, URBAN ECOSYST, V18, P209, DOI 10.1007/s11252-014-0387-7
   Bartesaghi-Koc C, 2020, LANDSCAPE URBAN PLAN, V203, DOI 10.1016/j.landurbplan.2020.103893
   Cao C, 2016, NAT COMMUN, V7, DOI 10.1038/ncomms12509
   Catford JA, 2022, TRENDS ECOL EVOL, V37, P158, DOI 10.1016/j.tree.2021.09.007
   Chang CR, 2007, LANDSCAPE URBAN PLAN, V80, P386, DOI 10.1016/j.landurbplan.2006.09.005
   Chang Yue, 2023, Sustainable Cities and Society, DOI 10.1016/j.scs.2023.104833
   Chapman S, 2017, LANDSCAPE ECOL, V32, P1921, DOI 10.1007/s10980-017-0561-4
   Cheng XY, 2022, ENVIRON INT, V169, DOI 10.1016/j.envint.2022.107489
   Dan YZ, 2022, SUSTAIN CITIES SOC, V78, DOI 10.1016/j.scs.2021.103586
   Dronova I, 2018, URBAN FOR URBAN GREE, V34, P44, DOI 10.1016/j.ufug.2018.05.009
   Du HY, 2017, URBAN FOR URBAN GREE, V27, P24, DOI 10.1016/j.ufug.2017.06.008
   Dugord PA, 2014, COMPUT ENVIRON URBAN, V48, P86, DOI 10.1016/j.compenvurbsys.2014.07.005
   Fan HY, 2019, AGR FOREST METEOROL, V265, P338, DOI 10.1016/j.agrformet.2018.11.027
   Hou HR, 2023, INT J APPL EARTH OBS, V122, DOI 10.1016/j.jag.2023.103411
   Hu YF, 2021, ENVIRON SCI POLLUT R, V28, P33096, DOI 10.1007/s11356-020-12086-z
   [刘新 Liu Xin], 2013, [长江流域资源与环境, Resources and Environment in the Yangtze Basin], V22, P1543
   Manoli G, 2019, NATURE, V573, P55, DOI 10.1038/s41586-019-1512-9
   Masoudi M, 2019, LANDSCAPE URBAN PLAN, V184, P44, DOI 10.1016/j.landurbplan.2018.10.023
   Monteiro MV, 2016, URBAN FOR URBAN GREE, V16, P160, DOI 10.1016/j.ufug.2016.02.008
   Peng J, 2024, NPJ URBAN SUSTAIN, V4, DOI 10.1038/s42949-024-00152-1
   Peng J, 2021, REMOTE SENS ENVIRON, V252, DOI 10.1016/j.rse.2020.112135
   Peng J, 2016, REMOTE SENS ENVIRON, V173, P145, DOI 10.1016/j.rse.2015.11.027
   Qian Y, 2022, ADV ATMOS SCI, V39, P819, DOI 10.1007/s00376-021-1371-9
   Qiao Z, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12050794
   Richards DR, 2020, URBAN FOR URBAN GREE, V50, DOI 10.1016/j.ufug.2020.126651
   Schwaab J, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-26768-w
   Shen HF, 2016, REMOTE SENS ENVIRON, V172, P109, DOI 10.1016/j.rse.2015.11.005
   Trusilova K, 2013, J APPL METEOROL CLIM, V52, P2296, DOI 10.1175/JAMC-D-12-0209.1
   [王劲峰 Wang Jinfeng], 2017, [地理学报, Acta Geographica Sinica], V72, P116
   Wang Q, 2023, LANDSCAPE ECOL, V38, P2965, DOI 10.1007/s10980-023-01763-2
   Wei J, 2021, REMOTE SENS ENVIRON, V252, DOI 10.1016/j.rse.2020.112136
   Wu B, 2023, INT J APPL EARTH OBS, V124, DOI 10.1016/j.jag.2023.103495
   Xiao R, 2021, LAND USE POLICY, V109, DOI 10.1016/j.landusepol.2021.105700
   Yan L, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13224601
   Yang GY, 2020, SUSTAIN CITIES SOC, V53, DOI 10.1016/j.scs.2019.101932
   Yang J, 2021, EARTH SYST SCI DATA, V13, P3907, DOI 10.5194/essd-13-3907-2021
   Yang ZW, 2024, SUSTAIN CITIES SOC, V106, DOI 10.1016/j.scs.2024.105386
   Yang ZW, 2021, SUSTAIN CITIES SOC, V73, DOI 10.1016/j.scs.2021.103140
   Ye HP, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13173415
   Yin J, 2019, LANDSCAPE ECOL, V34, P2949, DOI 10.1007/s10980-019-00932-6
   Yu ZW, 2020, URBAN FOR URBAN GREE, V49, DOI 10.1016/j.ufug.2020.126630
   Yu ZW, 2017, ECOL INDIC, V82, P152, DOI 10.1016/j.ecolind.2017.07.002
   Zhao JC, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13163282
   Zhou WQ, 2021, ONE EARTH, V4, P1764, DOI 10.1016/j.oneear.2021.11.010
NR 44
TC 3
Z9 3
U1 33
U2 40
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 AUG 15
PY 2024
VL 109
AR 105534
DI 10.1016/j.scs.2024.105534
EA MAY 2024
PG 11
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 UM6W6
UT WOS:001248526900002
DA 2025-01-10
ER

PT J
AU Schug, GR
   Buikstra, JE
   DeWitte, SN
   Baker, BJ
   Berger, E
   Buzon, MR
   Davies-Barrett, AM
   Goldstein, L
   Grauer, AL
   Gregoricka, LA
   Halcrow, SE
   Knudson, KJ
   Larsen, CS
   Martin, DL
   Nystrom, KC
   Perry, MA
   Roberts, CA
   Santos, AL
   Stojanowski, CM
   Suby, JA
   Temple, DH
   Tung, TA
   Vlok, M
   Watson-Glen, T
   Zakrzewski, SR
AF Schug, Gwen Robbins
   Buikstra, Jane E.
   DeWitte, Sharon N.
   Baker, Brenda J.
   Berger, Elizabeth
   Buzon, Michele R.
   Davies-Barrett, Anna M.
   Goldstein, Lynne
   Grauer, Anne L.
   Gregoricka, Lesley A.
   Halcrow, Sian E.
   Knudson, Kelly J.
   Larsen, Clark Spencer
   Martin, Debra L.
   Nystrom, Kenneth C.
   Perry, Megan A.
   Roberts, Charlotte A.
   Santos, Ana Luisa
   Stojanowski, Christopher M.
   Suby, Jorge A.
   Temple, Daniel H.
   Tung, Tiffiny A.
   Vlok, Melandri
   Watson-Glen, Tatyana
   Zakrzewski, Sonia R.
TI Climate change, human health, and resilience in the Holocene
SO PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF
   AMERICA
LA English
DT Article
DE climate adaptation; equitable sustainability; environmental health;
   IPCC; UN Sustainable Development Goals
ID CULTURAL RESPONSES; DISEASE; IPCC; BP; BIOARCHAEOLOGY; EVOLUTION;
   PATTERNS; MOBILITY; EVENT; AD
AB Climate change is an indisputable threat to human health, especially for societies already confronted with rising social inequality, political and economic uncertainty, and a cascade of concurrent environmental challenges. Archaeological data about past climate and environment provide an important source of evidence about the potential challenges humans face and the long-term outcomes of alternative short-term adaptive strategies. Evidence from well-dated archaeological human skeletons and mummified remains speaks directly to patterns of human health over time through changing circumstances. Here, we describe variation in human epidemiological patterns in the context of past rapid climate change (RCC) events and other periods of past environmental change. Case studies confirm that human communities responded to environmental changes in diverse ways depending on historical, sociocultural, and biological contingencies. Certain factors, such as social inequality and disproportionate access to resources in large, complex societies may influence the probability of major sociopolitical disruptions and reorganizations-commonly known as "collapse." This survey of Holocene human- environmental relations demonstrates how flexibility, variation, and maintenance of Indigenous knowledge can be mitigating factors in the face of environmental more rapid and of greater magnitude than the RCC events and other environmental changes we discuss here, these constraints of modernity we must address.
C1 [Schug, Gwen Robbins; Watson-Glen, Tatyana] Univ North Carolina Greensboro, Dept Biol, Greensboro, NC 27412 USA.
   [Buikstra, Jane E.; Baker, Brenda J.; Knudson, Kelly J.; Stojanowski, Christopher M.] Arizona State Univ, Ctr Bioarchaeol Res, Sch Human Evolut & Social Change, Tempe, AZ 85287 USA.
   [DeWitte, Sharon N.] Univ South Carolina, Dept Anthropol, Columbia, SC 29208 USA.
   [Berger, Elizabeth] Univ Calif Riverside, Dept Anthropol, Riverside, CA 92521 USA.
   [Buzon, Michele R.] Purdue Univ, Dept Anthropol, W Lafayette, IN 47907 USA.
   [Davies-Barrett, Anna M.] Univ Leicester, Dept Archaeol & Ancient Hist, Leicester LE1 7RH, England.
   [Goldstein, Lynne] Michigan State Univ, Dept Anthropol, E Lansing, MI 48824 USA.
   [Grauer, Anne L.] Loyola Univ Chicago, Dept Anthropol, Chicago, IL 60660 USA.
   [Gregoricka, Lesley A.] Univ S Alabama, Dept Sociol Anthropol & Social Work, Mobile, AL 36688 USA.
   [Halcrow, Sian E.] Univ Otago, Dept Anat, Dunedin 9016, New Zealand.
   [Larsen, Clark Spencer; Nystrom, Kenneth C.] Ohio State Univ, Dept Anthropol, Columbus, OH 43210 USA.
   [Martin, Debra L.; Perry, Megan A.] Univ Nevada, Dept Anthropol, Las Vegas, NV 89154 USA.
   [Nystrom, Kenneth C.; Roberts, Charlotte A.] State Univ New York New Paltz, Dept Anthropol, New Paltz, NY 12401 USA.
   [Perry, Megan A.; Santos, Ana Luisa] East Carolina Univ, Dept Anthropol, Greenville, NC 27858 USA.
   [Roberts, Charlotte A.] Univ Durham, Dept Archaeol, Durham DH1 3LE, England.
   [Santos, Ana Luisa; Suby, Jorge A.] Univ Coimbra, Res Ctr Anthropol & Hlth, Ctr Invest Antropol & Saude, Dept Life Sci, P-3000456 Coimbra, Portugal.
   [Suby, Jorge A.; Temple, Daniel H.] Natl Univ Ctr Buenos Aires Prov, Fac Social Sci, Consejo Nacl Cient Tecn, Dept Archaeol,Bioarchaeol Res Grp,Inst Invest Arqu, RA-7630 Buenos Aires, Argentina.
   [Temple, Daniel H.; Tung, Tiffiny A.] George Mason Univ, Dept Sociol & Anthropol, Fairfax, VA 22030 USA.
   [Tung, Tiffiny A.; Vlok, Melandri] Vanderbilt Univ, Dept Anthropol, Nashville, TN 37235 USA.
   [Vlok, Melandri; Zakrzewski, Sonia R.] Univ Sydney, Sydney Southeast Asia Ctr, Sydney, NSW 2006, Australia.
   [Zakrzewski, Sonia R.] Univ Southampton, Dept Archaeol, Southampton SO17 1BF, England.
C3 University of North Carolina; University of North Carolina Greensboro;
   Arizona State University; Arizona State University-Tempe; University of
   South Carolina System; University of South Carolina Columbia; University
   of California System; University of California Riverside; Purdue
   University System; Purdue University; University of Leicester; Michigan
   State University; Loyola University Chicago; University of South
   Alabama; University of Otago; University System of Ohio; Ohio State
   University; Nevada System of Higher Education (NSHE); University of
   Nevada Las Vegas; State University of New York (SUNY) System; SUNY New
   Paltz; University of North Carolina; East Carolina University; Durham
   University; Universidade de Coimbra; Consejo Nacional de Investigaciones
   Cientificas y Tecnicas (CONICET); George Mason University; Vanderbilt
   University; University of Sydney; University of Southampton
RP Schug, GR (corresponding author), Univ North Carolina Greensboro, Dept Biol, Greensboro, NC 27412 USA.
EM gmrobbin@uncg.edu
RI Zakrzewski, Sonia/AAA-9200-2022; DeWitte, Sharon/JQW-0434-2023; SANTOS,
   ANA/JPK-6411-2023; SCHUG, GWEN/AAN-8980-2020; Halcrow, Siân/C-2037-2018;
   Davies-Barrett, Anna/AAU-1178-2021; Roberts, Charlotte Ann/H-2622-2019
OI Robbins Schug, Gwen/0000-0002-3928-9230; Roberts, Charlotte
   Ann/0000-0002-2259-807X; DeWitte, Sharon/0000-0003-0754-8485; Halcrow,
   Sian/0000-0001-6038-7997; Buikstra, Jane/0000-0003-0206-0165; Goldstein,
   Lynne/0000-0002-3908-418X; Baker, Brenda/0000-0002-9277-7815; Buzon,
   Michele/0000-0002-1177-0962; Davies-Barrett, Anna/0000-0002-1555-1468
CR Gallegos-Riofrío CA, 2021, GEOFORUM, V127, P1, DOI 10.1016/j.geoforum.2021.09.011
   Arkush E, 2013, J ARCHAEOL RES, V21, P307, DOI 10.1007/s10814-013-9065-1
   Arponen VPJ, 2019, ARCHAEOL DIALOG, V26, P1, DOI 10.1017/S1380203819000059
   Baker Brenda., 2015, Migration and Disruptions: Toward a Unifying Theory of Ancient and Contemporary Migrations
   Berger E., 2020, The Routledge Handbook of the Bioarchaeology of Climate and Environmental Change, P83, DOI DOI 10.4324/9781351030465-6
   Betsinger TK, 2021, AM J PHYS ANTHROPOL, V175, P79, DOI 10.1002/ajpa.24249
   Blair JMA, 2015, NAT REV MICROBIOL, V13, P42, DOI 10.1038/nrmicro3380
   Blakey ML, 1998, TRANSFORM ANTHROPOL, V7, P53, DOI DOI 10.1525/TRAN.1998.7.1.53
   Buikstra JaneE., 2019, Ortner's Identification of Pathological Conditions in Human Skeletal Remains, VThird, DOI [10.1016/C2011-0-06880-1, DOI 10.1016/C2011-0-06880-1]
   Burke KD, 2018, P NATL ACAD SCI USA, V115, P13288, DOI 10.1073/pnas.1809600115
   Ceballos G, 2015, SCI ADV, V1, DOI 10.1126/sciadv.1400253
   Choithani C, 2021, WORLD DEV, V146, DOI 10.1016/j.worlddev.2021.105617
   Cook BI, 2018, CURR CLIM CHANGE REP, V4, P164, DOI 10.1007/s40641-018-0093-2
   Crema ER, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0154809
   Cullen HM, 2000, GEOLOGY, V28, P379, DOI 10.1130/0091-7613(2000)28<379:CCATCO>2.0.CO;2
   deMenocal PB, 2001, SCIENCE, V292, P667, DOI 10.1126/science.1059827
   DeWitte SN, 2022, BIOARCHAEOLOGY INT, V6, P108, DOI 10.5744/bi.2020.0024
   Dhavalikar M.K., 1988, The First Farmers of the Deccan
   Doherty SJ, 2009, B AM METEOROL SOC, V90, P497, DOI 10.1175/2008BAMS2643.1
   Dykstra MP, 2021, ACAD MED, V96, P951, DOI 10.1097/ACM.0000000000004072
   Geber J, 2018, VICTIMS IRELANDS GRE
   Giosan L, 2012, P NATL ACAD SCI USA, V109, pE1688, DOI 10.1073/pnas.1112743109
   Godde K, 2020, AM J PHYS ANTHROPOL, V173, P168, DOI 10.1002/ajpa.24081
   Gowland RL, 2012, AM J PHYS ANTHROPOL, V147, P301, DOI 10.1002/ajpa.21648
   Gowland RL, 2015, AM J PHYS ANTHROPOL, V158, P530, DOI 10.1002/ajpa.22820
   Grada Cormac., 2009, Famine: A Short History
   Green MH, 2020, AM HIST REV, V125, P1601, DOI 10.1093/ahr/rhaa511
   Gregoricka L. A, 2020, ROUTLEDGE HDB BIOARC, P431
   Hadley C, 2012, AM J PHYS ANTHROPOL, V149, P72, DOI 10.1002/ajpa.22161
   Harper K, 2010, INT J ENV RES PUB HE, V7, P675, DOI 10.3390/ijerph7020675
   Harrod R.P., 2013, Bioarchaeology of Climate Change and Violence: Ethical Considerations
   Hernandez J., 2022, FRESH BANANA LEAVES
   Horocholyn K., 2017, Bioarchaeology International, V1, P101
   Izdebski A, 2022, NAT ECOL EVOL, V6, P297, DOI 10.1038/s41559-021-01652-4
   Jaffe Y, 2021, J WORLD PREHIST, V34, P595, DOI 10.1007/s10963-021-09160-w
   Jaffe YY, 2021, HOLOCENE, V31, P169, DOI 10.1177/0959683620970254
   Juengst S.L., 2020, The Routledge Handbook of the Bioarchaeology of Climate and Environmental Change, P345
   Kemp L, 2022, P NATL ACAD SCI USA, V119, DOI 10.1073/pnas.2108146119
   King CL, 2017, ARCHAEOL RES ASIA, V11, P27, DOI 10.1016/j.ara.2017.05.003
   Klunk J, 2022, NATURE, V611, P312, DOI 10.1038/s41586-022-05349-x
   Knudson KJ, 2009, AM J PHYS ANTHROPOL, V138, P473, DOI 10.1002/ajpa.20965
   Kohler TA, 2020, AM ANTIQUITY, V85, P627, DOI 10.1017/aaq.2020.68
   Koyama S., 1979, SENRI ETHNOL STUD, V2, P1
   Larsen CS, 2019, P NATL ACAD SCI USA, V116, P12615, DOI 10.1073/pnas.1904345116
   Larsen CS, 2018, ANNU REV ANTHROPOL, V47, P295, DOI 10.1146/annurev-anthro-102116-041441
   Lee MSJ, 2018, INT IMMUNOL, V30, P121, DOI 10.1093/intimm/dxx076
   Liu FG, 2012, HOLOCENE, V22, P1181, DOI 10.1177/0959683612441839
   Marciniak Stephanie., 2019, Paleogenomics: Genome-Scale Analysis of Ancient DNA, P115, DOI [DOI 10.1007/13836_2018_52, 10.1007/13836_2018_52]
   Martin D. L, 2020, ROUTLEDGE HDB BIOARC, P301
   Monot M, 2009, NAT GENET, V41, P1282, DOI 10.1038/ng.477
   Morens DM, 2004, NATURE, V430, P242, DOI 10.1038/nature02759
   Nelson EA, 2020, INT J PALEOPATHOL, V29, P128, DOI 10.1016/j.ijpp.2019.12.006
   Nystrom K. C., 2020, ROUTLEDGE HDB BIOARC, P159
   Possehl GL, 1997, J WORLD PREHIST, V11, P425, DOI 10.1007/BF02220556
   Ran M, 2019, QUATERN INT, V521, P158, DOI 10.1016/j.quaint.2019.05.030
   Redfern R, 2020, ROUTLEDGE HDB BIOARC, P279
   Robbins Schug G, 2022, BIOARCHAEOLOGY CLIMA
   Robbins Schug G., 2022, BIOARCHAEOL INT, V6, P179
   Robbins Schug G., 2019, BIOARCHAEOLOGISTS SP, P133
   Robbins Schug G., 2020, ROUTLEDGE HDB BIOARC
   Scaffidi BK, 2020, J ARCHAEOL SCI, V117, DOI 10.1016/j.jas.2020.105121
   Schmidhuber J, 2007, P NATL ACAD SCI USA, V104, P19703, DOI 10.1073/pnas.0701976104
   Schug G R., 2016, A Companion to South Asia in the Past, P255
   Schug GR, 2014, AM J PHYS ANTHROPOL, V155, P243, DOI 10.1002/ajpa.22536
   Sen A.K., 1981, POVERTY FAMINES
   Singer M., 2009, INTRO SYNDEMICS CRIT
   Smith KR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P709
   Solomon S., 2007, Climate Change 2007The Physical Science Basis: Working Group I Contribution to the Fourth Assessment Report of the IPCC, V4
   Staubwasser M, 2003, GEOPHYS RES LETT, V30, DOI 10.1029/2002GL016822
   Staubwasser M, 2006, QUATERNARY RES, V66, P372, DOI 10.1016/j.yqres.2006.09.001
   Stephens L, 2019, SCIENCE, V365, P897, DOI 10.1126/science.aax1192
   Stewart AJ, 2020, SCI ADV, V6, DOI 10.1126/sciadv.abd4201
   Stojanowski CM, 2014, AM J PHYS ANTHROPOL, V154, P79, DOI 10.1002/ajpa.22474
   Stojanowski CM, 2011, AM J PHYS ANTHROPOL, V146, P49, DOI 10.1002/ajpa.21542
   Sultana F, 2022, POLIT GEOGR, V99, DOI 10.1016/j.polgeo.2022.102638
   Temple D.H., 2019, Hunter-gatherer adaptation and resilience: a bioarchaeological perspective
   Temple D. H., 2019, Hunter-gatherer adaptation and resilience: a bioarchaeological perspective, P85
   Tierney JE, 2017, SCI ADV, V3, DOI 10.1126/sciadv.1601503
   Tishkoff SA, 2002, NAT REV GENET, V3, P611, DOI 10.1038/nrg865
   Torres-Rouff C., 2020, The Routledge Handbook of the Bioarchaeology of Climate and Environmental Change, P332
   Trenberth KE, 2011, CLIM RES, V47, P123, DOI 10.3354/cr00953
   Tung TA, 2021, CURR ANTHROPOL, V62, pS125, DOI 10.1086/712305
   Tung TiffinyA., 2016, The Archaeology of Food and Warfare: Food Insecurity in Prehistory, P193, DOI DOI 10.1007/978-3-319-18506-4_10
   Vincent O, 2020, J RURAL STUD, V80, P302, DOI 10.1016/j.jrurstud.2020.10.002
   Vlok M, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-83978-4
   Wagner DM, 2014, LANCET INFECT DIS, V14, P319, DOI 10.1016/S1473-3099(13)70323-2
   Wells JCK, 2016, FRONT PUBLIC HEALTH, V4, DOI 10.3389/fpubh.2016.00145
   WHO, 2010, WORLD MALARIA REPORT 2010, P1
   Woodward A, 2014, LANCET, V383, P1185, DOI 10.1016/S0140-6736(14)60576-6
   Wright Rita P., 2009, The Ancient Indus: Urbanism, Economy, and Society
NR 90
TC 32
Z9 34
U1 16
U2 50
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 JAN 24
PY 2023
VL 120
IS 4
AR e2209472120
DI 10.1073/pnas.2209472120
PG 10
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA 9K1HE
UT WOS:000940623700009
PM 36649426
OA Green Published, hybrid, Green Accepted
HC Y
HP N
DA 2025-01-10
ER

PT J
AU Zhao, XR
   Zhang, JX
   Wang, HE
   Li, HY
   Qu, CQ
   Wen, JH
   Zhang, XY
   Zhu, T
   Nie, CS
   Li, XH
   Muhatai, G
   Wang, L
   Lv, XZ
   Yang, WF
   Zhao, CJ
   Bao, HG
   Li, JY
   Zhu, B
   Cao, GM
   Xiong, WJ
   Ning, ZH
   Qu, LJ
AF Zhao, Xiurong
   Zhang, Jinxin
   Wang, Huie
   Li, Haiying
   Qu, Changqing
   Wen, Junhui
   Zhang, Xinye
   Zhu, Tao
   Nie, Changsheng
   Li, Xinghua
   Muhatai, Gemingguli
   Wang, Liang
   Lv, XueZe
   Yang, Weifang
   Zhao, Chunjiang
   Bao, Haigang
   Li, Junying
   Zhu, Bo
   Cao, Guomin
   Xiong, Wenjie
   Ning, Zhonghua
   Qu, Lujiang
TI Genomic and transcriptomic analyses reveal genetic adaptation to cold
   conditions in the chickens
SO GENOMICS
LA English
DT Article
DE Adaptation; Cold tolerance; Chicken; ptgs2; dnah5
ID HIGH-ALTITUDE; STRESS; GOATS
AB Under the pressure of natural and artificial selection, domestic animals, including chickens, have evolved unique mechanisms of genetic adaptations such as high-altitude adaptation, hot and arid climate adaptation, and desert adaptation. Here, we investigated the genetic basis of cold tolerance in chicken by integrating whole-genome and transcriptome sequencing technologies. Genome-wide comparative analyses of 118 chickens living in different latitudes showed 46 genes and several pathways that may be involved in cold adaptation. The results of the functional enrichment analysis of differentially expressed genes proved the important role of metabolic pathways and immune-related pathways in cold tolerance in chickens. The subsequent integration of whole genome and transcriptome sequencing technology further identified six genes - dnah5 (dynein axonemal heavy chain 5), ptgs2 (prostaglandin-endoperoxide synthase 2), inhba (inhibin beta A subunit), irx2 (iroquois homeobox 2), ensgalg00000054917, and ensgalg00000046652 - requiring more detailed studies. In addition, we also discov-ered different allele frequency distributions of five SNPs (single nucleotide polymorphisms) within ptgs2 and nine SNPs within dnah5 in chickens in different latitudes, suggesting strong selective pressure of these two genes in chickens. We provide a novel insight into the genetic adaptation in chickens to cold environments, and provide a reference for evaluating and developing adaptive chicken breeds in cold environments.
C1 [Zhao, Xiurong; Zhang, Jinxin; Wen, Junhui; Zhang, Xinye; Zhu, Tao; Nie, Changsheng; Li, Xinghua; Zhao, Chunjiang; Bao, Haigang; Li, Junying; Ning, Zhonghua; Qu, Lujiang] China Agr Univ, Coll Anim Sci & Technol, Natl Engn Lab Anim Breeding, Dept Anim Genet & Breeding,State Key Lab Anim Nutr, Beijing 100193, Peoples R China.
   [Wang, Huie; Muhatai, Gemingguli] Xinjiang Prod & Construct Corps Key Lab Protect &, Alar 843300, Xinjiang, Peoples R China.
   [Li, Haiying] Xinjiang Agr Univ, Coll Anim Sci, Urumqi 830000, Peoples R China.
   [Qu, Changqing] Fuyang Normal Univ, Engn Technol Res Ctr Antiaging Chinese Herbal Med, Fuyang 236037, Anhui, Peoples R China.
   [Wang, Liang; Lv, XueZe; Yang, Weifang] Beijing Municipal Gen Stn Anim Sci, Beijing 100107, Peoples R China.
   [Zhu, Bo] Anim Hlth Supervis Inst Zhuozhou, Zhuozhou 072750, Hebei, Peoples R China.
   [Cao, Guomin] Anim Husb Stn Fangchenggang, Fangchenggang 538001, Guangxi, Peoples R China.
   [Xiong, Wenjie] Anim Dis Prevent & Control Ctr Fangchenggang, Fangchenggang 538001, Guangxi, Peoples R China.
C3 China Agricultural University; Xinjiang Agricultural University; Fuyang
   Normal University
RP Qu, LJ (corresponding author), China Agr Univ, Coll Anim Sci & Technol, Natl Engn Lab Anim Breeding, Dept Anim Genet & Breeding,State Key Lab Anim Nutr, Beijing 100193, Peoples R China.
EM 1602978784@qq.com; 1599436449@qq.com; whedky@126.com; lhy-3@163.com;
   qucq518@163.com; wjh8545@qq.com; xinye_leaf@163.com; zhutao@cau.edu.cn;
   changshengnie@cau.edu.cn; 920230688@qq.com; gmgl-113@foxmail.com;
   wangliangcau@139.com; lvxueze0310@163.com; carspstp@126.com;
   cjzhao@cau.edu.cn; baohaigang@cau.edu.cn; lijunying@cau.edu.cn;
   13931368862@163.com; caoguomin2003@163.com; 269696329@qq.com;
   ningzhh@cau.edu.cn; quluj@163.com
RI Muhatai, Gemingguli/JOZ-2407-2023; li, haiying/KJL-3941-2024; Li,
   Xinghua/I-8308-2014; qu, changqing/HSI-4312-2023; XIE,
   WANYING/JNR-9259-2023
OI Li, Xinghua/0000-0003-2156-5775; Muhatai, Gemingguli/0009-0000-3208-4403
FU Earmarked fund for the Beijing Innovation Team of the Modern
   Agro-industry Technology Research System [BAIC04-2021]; Open project of
   Xinjiang Production & Construction Corps Key Laboratory of Protection
   and Utilization of Biological Resources in Tarim Basin [BRZD2104]
FX This work was supported by the earmarked fund for the Beijing Innovation
   Team of the Modern Agro-industry Technology Research System
   (BAIC04-2021) and open project of Xinjiang Production & Construction
   Corps Key Laboratory of Protection and Utilization of Biological
   Resources in Tarim Basin (BRZD2104) . We thank all the research
   assistants who contributed to this work.
CR Anamthathmakula P, 2021, ENDOCRINOLOGY, V162, DOI 10.1210/endocr/bqab025
   [Anonymous], 1989, Cladistics
   Ashour AA, 2020, TOXICS, V8, DOI 10.3390/toxics8020038
   Borsoi A, 2015, AVIAN PATHOL, V44, P490, DOI 10.1080/03079457.2015.1086976
   Chen XY, 2014, MOL BIOL REP, V41, P2243, DOI 10.1007/s11033-014-3075-z
   Chen XY, 2011, ITAL J ANIM SCI, V10, P38, DOI 10.4081/ijas.2011.e8
   Cheviron ZA, 2012, P NATL ACAD SCI USA, V109, P8635, DOI 10.1073/pnas.1120523109
   Danecek P, 2021, GIGASCIENCE, V10, DOI 10.1093/gigascience/giab008
   Danecek P, 2011, BIOINFORMATICS, V27, P2156, DOI 10.1093/bioinformatics/btr330
   Debonne M, 2008, WORLD POULTRY SCI J, V64, P309, DOI 10.1017/S0043933908000056
   Deveci D, 2002, J EXP BIOL, V205, P829
   Dobin A, 2013, BIOINFORMATICS, V29, P15, DOI 10.1093/bioinformatics/bts635
   Eda M, 2021, ANIM FRONT, V11, P52, DOI 10.1093/af/vfab016
   Díaz-Hernández ME, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0058549
   Fallahshahroudi A, 2021, GENETICS, V217, DOI 10.1093/genetics/iyaa050
   Flori L, 2019, MOL ECOL, V28, P1009, DOI 10.1111/mec.15004
   Followay B, 2020, TRANSL SPORTS MED, V3, P464, DOI 10.1002/tsm2.165
   Frare C, 2017, FASEB J, V31
   Gheyas AA, 2021, MOL BIOL EVOL, V38, P4268, DOI 10.1093/molbev/msab156
   Jehl F., FRONT GENET, V12, P2021
   Kim D, 2015, NAT METHODS, V12, P357, DOI [10.1038/NMETH.3317, 10.1038/nmeth.3317]
   Kim ES, 2016, HEREDITY, V116, P255, DOI 10.1038/hdy.2015.94
   Kumar H, 2019, ANIMALS-BASEL, V9, DOI 10.3390/ani9121076
   Lawal RA, 2021, ANIM GENET, V52, P385, DOI 10.1111/age.13091
   Li H, 2010, BIOINFORMATICS, V26, P589, DOI 10.1093/bioinformatics/btp698
   Librado P, 2015, P NATL ACAD SCI USA, V112, pE6889, DOI 10.1073/pnas.1513696112
   Liu XF, 2021, EVOL APPL, V14, P860, DOI 10.1111/eva.13168
   Love MI, 2014, GENOME BIOL, V15, DOI 10.1186/s13059-014-0550-8
   Luo W, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-71421-z
   Lv FH, 2014, MOL BIOL EVOL, V31, P3324, DOI 10.1093/molbev/msu264
   Mani R, 2020, J GENET, V99, DOI 10.1007/s12041-019-1168-0
   McKenna A, 2010, GENOME RES, V20, P1297, DOI 10.1101/gr.107524.110
   Noorai RE, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0040974
   Pertea M, 2015, NAT BIOTECHNOL, V33, P290, DOI 10.1038/nbt.3122
   Purcell S, 2007, AM J HUM GENET, V81, P559, DOI 10.1086/519795
   Radchuk V, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-10924-4
   Ribeiro MN, 2018, J APPL ANIM RES, V46, P1036, DOI 10.1080/09712119.2018.1456439
   Sejian V, 2018, ANIMAL, V12, pS431, DOI 10.1017/S1751731118001945
   Shen JF, 2020, FRONT GENET, V11, DOI 10.3389/fgene.2020.00094
   Tian SL, 2020, ISCIENCE, V23, DOI 10.1016/j.isci.2020.101644
   Walugembe M., 2019, DETECTION SELECTION, P9
   Wang MS, 2020, CELL RES, V30, P693, DOI 10.1038/s41422-020-0349-y
   Wang MS, 2015, MOL BIOL EVOL, V32, P1880, DOI 10.1093/molbev/msv071
   WEIR BS, 1984, EVOLUTION, V38, P1358, DOI [10.2307/2408641, 10.1111/j.1558-5646.1984.tb05657.x]
   Wu HG, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms6188
   Xia T, 2021, MAMM BIOL, V101, P861, DOI 10.1007/s42991-021-00135-0
   Xie SS, 2017, ASIAN AUSTRAL J ANIM, V30, P1507, DOI 10.5713/ajas.16.0957
   Yang J, 2016, MOL BIOL EVOL, V33, P2576, DOI 10.1093/molbev/msw129
   Zaiss AK, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0101263
   Zhang Z, 2018, EUR THYROID J, V7, P279, DOI 10.1159/000493976
NR 50
TC 7
Z9 8
U1 2
U2 22
PU ACADEMIC PRESS INC ELSEVIER SCIENCE
PI SAN DIEGO
PA 525 B ST, STE 1900, SAN DIEGO, CA 92101-4495 USA
SN 0888-7543
EI 1089-8646
J9 GENOMICS
JI Genomics
PD NOV
PY 2022
VL 114
IS 6
AR 110485
DI 10.1016/j.ygeno.2022.110485
EA OCT 2022
PG 9
WC Biotechnology & Applied Microbiology; Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biotechnology & Applied Microbiology; Genetics & Heredity
GA 5K8UD
UT WOS:000869994500003
PM 36126832
OA gold
DA 2025-01-10
ER

PT J
AU Yumagulova, L
   Vertinsky, I
AF Yumagulova, Lilia
   Vertinsky, Ilan
TI Managing trade-offs between specific and general resilience: Insights
   from Canada's Metro Vancouver region
SO CITIES
LA English
DT Article
DE Specific and general resilience; Urban and regional resilience;
   Trade-offs; Flood risk governance; Sea-level rise
ID CLIMATE ADAPTATION; URBAN; LESSONS; COPRODUCTION; PERSPECTIVE;
   SYNERGIES; EQUITY; FACE
AB The concept of resilience has captured the imagination of urbanists and city managers. While the literature on urban and regional resilience has proliferated, our understanding of resilience trade-offs that elected municipal officials and city staff make in their daily practice remains limited. This article addresses this lacuna by examining specific and general resilience trade-offs through a case study of urban and regional planning for floods and sea-level rise in Canada's Metro Vancouver region. We identify the mechanisms that ensure the maintenance of long-term options that are essential to the development of general resilience and highlight the barriers and forces that constrain the investment in general resilience. We find that while there are many examples of nuance and depth in practitioners' deliberations about resilience trade-offs involving fiscal, equity, spatial, temporal, and design dimensions, examples of the application of a consistent transparent framework to incorporate these tradeoffs to support overall decision-making are lacking. We find that in the absence of such explicit frameworks, fiscal and political considerations tend to dominate. While there were some clear mechanisms to articulate tradeoffs leading to specific resilience gains at the municipal level, the losses to general resilience at the regional level remained somewhat unintended and implicit.
C1 [Yumagulova, Lilia; Vertinsky, Ilan] Univ British Columbia, Sauder Sch Business, Vancouver, BC V6T 1Z4, Canada.
C3 University of British Columbia
RP Yumagulova, L (corresponding author), Univ British Columbia, Sauder Sch Business, Vancouver, BC V6T 1Z4, Canada.
EM lily.yumagulova@gmail.com; ilan.vertinsky@ubc.ca
FU Social Sciences and Humanities Research Council of Canada (SSHRC)
   [410-2011-0597]
FX This paper was in part funded through the the Social Sciences and
   Humanities Research Council of Canada (SSHRC) grant 410-2011-0597.
CR Aguilar-Barajas I, 2019, ENVIRON SCI POLICY, V99, P37, DOI 10.1016/j.envsci.2019.05.021
   Allen CR, 2018, ECOL SOC, V23, DOI 10.5751/ES-09920-230103
   Anguelovski I, 2016, J PLAN EDUC RES, V36, P333, DOI 10.1177/0739456X16645166
   [Anonymous], 2011, An emergency management framework for Canada
   [Anonymous], 2006, Resilience Thinking: Sustaining Ecosystems and People in a Changing World
   Arlington Group Planning + Architecture Inc, 2008, FLOOD HAZ AREA LAND
   Berkes F., 2003, Navigating social and ecological systems: building resilience for complexity and change, DOI DOI 10.1017/CBO9780511541957
   Brown A, 2012, ENVIRON URBAN, V24, P531, DOI 10.1177/0956247812456490
   Bush J, 2019, CITIES, V95, DOI 10.1016/j.cities.2019.102483
   Butler WH, 2016, J PLAN EDUC RES, V36, P319, DOI 10.1177/0739456X16647161
   Cantelmo A., 2019, IMF WORKING PAPERS, V19, P1, DOI [10.5089/9781498302654.001, DOI 10.5089/9781498302654.001]
   Carlson JM, 2000, PHYS REV LETT, V84, P2529, DOI 10.1103/PhysRevLett.84.2529
   Carpenter SR, 2012, SUSTAINABILITY-BASEL, V4, P3248, DOI 10.3390/su4123248
   Chelleri L, 2015, ENVIRON URBAN, V27, P181, DOI 10.1177/0956247814550780
   Chen HX, 2020, INT J ENV RES PUB HE, V17, DOI 10.3390/ijerph17041231
   Chu E, 2017, CITIES, V60, P378, DOI 10.1016/j.cities.2016.10.016
   Crick F, 2018, SCI TOTAL ENVIRON, V636, P192, DOI 10.1016/j.scitotenv.2018.04.239
   Davoudi S, 2012, PLAN THEORY PRACT, V13, P299, DOI 10.1080/14649357.2012.677124
   Di Baldassarre G, 2018, HYDROL EARTH SYST SC, V22, P5629, DOI 10.5194/hess-22-5629-2018
   DNV, 2009, DISTR N VANC REP COU
   Dodman D, 2017, INT J URBAN SUSTAIN, V9, P97, DOI 10.1080/19463138.2017.1345740
   Driessen PPJ, 2016, ECOL SOC, V21, DOI 10.5751/ES-08921-210453
   Eakin H, 2009, ADAPTING TO CLIMATE CHANGE: THRESHOLDS, VALUES, GOVERNANCE, P212
   Folke C, 2006, GLOBAL ENVIRON CHANG, V16, P253, DOI 10.1016/j.gloenvcha.2006.04.002
   Folke Carl., 2003, Individual and Structural Determinants of Environmental Practice, P226, DOI [10.4324/9781315252377-9, DOI 10.4324/9781315252377-9]
   Fraser Basin Council, 2016, LOW MAINL FLOOD NAN
   GRAHAM J., 1995, Risk vs risk: Tradeoffs in protecting health and the environment
   Gregory RS, 2002, ENVIRON VALUE, V11, P461, DOI 10.3197/096327102129341181
   Hansen SF, 2008, J RISK RES, V11, P475, DOI 10.1080/13669870802124413
   Hegger DLT, 2016, ECOL SOC, V21, DOI 10.5751/ES-08854-210452
   Holling C.S., 1986, Sustainable development of the biosphere/, P217
   Ishtiaque A, 2017, ECOL SOC, V22, DOI [10.5751/ES-09186-220305, 10.5751/es-09186-220305]
   Jeuken A, 2015, J WATER CLIM CHANGE, V6, P711, DOI 10.2166/wcc.2014.141
   Klinsky S, 2012, GLOBAL ENVIRON CHANG, V22, P862, DOI 10.1016/j.gloenvcha.2012.05.008
   Macintosh A, 2013, MITIG ADAPT STRAT GL, V18, P1035, DOI 10.1007/s11027-012-9406-2
   Matin N, 2018, WORLD DEV, V109, P197, DOI 10.1016/j.worlddev.2018.04.020
   McEvoy D, 2006, P I CIVIL ENG-MUNIC, V159, P185, DOI 10.1680/muen.2006.159.4.185
   Mees H, 2017, J ENVIRON POL PLAN, V19, P827, DOI 10.1080/1523908X.2017.1299623
   Metro Vancouver, 2012, DISC PAP BEST PRACT
   Moraci F, 2016, PROCD SOC BEHV, V223, P818, DOI 10.1016/j.sbspro.2016.05.281
   National Research Council, 2012, Disaster Resilience, DOI [10.17226/13457, DOI 10.17226/13457]
   Ostrom E, 2004, ECOL ECON, V49, P488, DOI 10.1016/j.ecolecon.2004.01.010
   Renn O, 2006, LAND USE POLICY, V23, P34, DOI 10.1016/j.landusepol.2004.08.005
   Sellberg MM, 2018, J ENVIRON MANAGE, V217, P906, DOI 10.1016/j.jenvman.2018.04.012
   Sellberg MM, 2015, ECOL SOC, V20, DOI 10.5751/ES-07258-200143
   Sharifi A, 2014, ENRGY PROCED, V61, P1491, DOI 10.1016/j.egypro.2014.12.154
   Tanner T, 2015, NAT CLIM CHANGE, V5, P23, DOI 10.1038/NCLIMATE2431
   Therrien MC, 2020, J CONTING CRISIS MAN, V28, P83, DOI 10.1111/1468-5973.12283
   TOBIN GA, 1995, WATER RESOUR BULL, V31, P359, DOI 10.1111/j.1752-1688.1995.tb04025.x
   Tuhkanen H, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10061924
   UK Cabinet Office, 2011, INFR CORP RES PROGR
   Viguié V, 2012, NAT CLIM CHANGE, V2, P334, DOI 10.1038/NCLIMATE1434
   Walker B, 2011, ECOL SOC, V16
   Walker BH, 2009, ECOL SOC, V14
   Wallace D, 2008, ECOL SOC, V13
   Wilkinson C., 2010, Critical Planning, V17, P2
   Wiréhn L, 2020, REG ENVIRON CHANGE, V20, DOI 10.1007/s10113-020-01585-x
   Wong CP, 2015, ECOL LETT, V18, P108, DOI 10.1111/ele.12389
   World Economic Forum, 2019, GLOBAL RISKS REP 202, V15th
   Yumagulova L., 2018, URBAN REGIONAL RESIL
   Yumagulova L, 2020, CAMB J REG ECON SOC, V13, P293, DOI 10.1093/cjres/rsaa029
   Yumagulova L, 2019, ENVIRON SCI POLICY, V100, P66, DOI 10.1016/j.envsci.2019.05.022
NR 62
TC 6
Z9 7
U1 6
U2 36
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 DEC
PY 2021
VL 119
AR 103319
DI 10.1016/j.cities.2021.103319
EA AUG 2021
PG 11
WC Urban Studies
WE Social Science Citation Index (SSCI)
SC Urban Studies
GA WD2HA
UT WOS:000704767300007
DA 2025-01-10
ER

PT J
AU Méndez-Vigo, B
   Ausín, I
   Zhu, WS
   Mollá-Morales, A
   Balasubramanian, S
   Alonso-Blanco, C
AF Mendez-Vigo, Belen
   Ausin, Israel
   Zhu, Wangsheng
   Molla-Morales, Almudena
   Balasubramanian, Sureshkumar
   Alonso-Blanco, Carlos
TI Genetic Interactions and Molecular Evolution of the Duplicated Genes
   <i>ICARUS2</i> and <i>ICARUS1</i> Help Arabidopsis Plants Adapt to
   Different Ambient Temperatures
SO PLANT CELL
LA English
DT Article
ID NATURAL VARIATION; FLOWERING TIME; COMPLEX; TRNA(HIS); TRAITS;
   INCOMPATIBILITIES; DIVERSIFICATION; TRANSFORMATION; POLYMORPHISM;
   RESPONSES
AB Understanding how plants adapt to ambient temperatures has become a major challenge prompted by global climate change. This has led to the identification of several genes regulating the thermal plasticity of plant growth and flowering time. However, the mechanisms accounting for the natural variation and evolution of such developmental plasticity remain mostly unknown. In this study, we determined that natural variation at ICARUS2 (ICA2), which interacts genetically with its homolog ICA1, alters growth and flowering time plasticity in relation to temperature in Arabidopsis (Arabidopsis thaliana). Transgenic analyses demonstrated multiple functional effects for ICA2 and supported the notion that structural polymorphisms in ICA2 likely underlie its natural variation. Two major ICA2 haplogroups carrying distinct functionally active alleles showed high frequency, strong geographic structure, and significant associations with climatic variables related to annual and daily fluctuations in temperature. Genome analyses across the plant phylogeny indicated that the prevalent plant ICA genes encoding two tRNA(His) guanylyl transferase 1 units evolved similar to 120 million years ago during the early divergence of mono- and dicotyledonous clades. In addition, ICA1/ICA2 duplication occurred specifically in the Camelineae tribe (Brassicaceae). Thus, ICA2 appears to be ubiquitous across plant evolution and likely contributes to climate adaptation through modifications of thermal developmental plasticity in Arabidopsis.
C1 [Mendez-Vigo, Belen; Ausin, Israel; Molla-Morales, Almudena; Alonso-Blanco, Carlos] CSIC, Ctr Nacl Biotecnol, E-28049 Madrid, Spain.
   [Zhu, Wangsheng; Balasubramanian, Sureshkumar] Monash Univ, Sch Biol Sci, Clayton, Vic 3800, Australia.
   [Zhu, Wangsheng] Max Planck Inst Dev Biol, Dept Mol Biol, D-72076 Tubingen, Germany.
C3 Consejo Superior de Investigaciones Cientificas (CSIC); CSIC - Centro
   Nacional de Biotecnologia (CNB); Monash University; Max Planck Society
RP Alonso-Blanco, C (corresponding author), CSIC, Ctr Nacl Biotecnol, E-28049 Madrid, Spain.
EM calonso@cnb.csic.es
RI Ausin, Israel/A-7065-2011; Balasubramanian, Sureshkumar/AAS-6919-2020;
   Alonso-Blanco, Carlos/F-8864-2016
OI Alonso-Blanco, Carlos/0000-0002-4738-5556; Balasubramanian,
   Sureshkumar/0000-0002-1057-2606; Zhu, Wangsheng/0000-0001-7773-3438;
   Molla-Morales, Almudena/0000-0001-9465-0490; Mendez-Vigo,
   Belen/0000-0002-9850-536X
FU Agencia Estatal de Investigacion of Spain; Fondo Europeo de Desarrollo
   Regional (Union Europea) [BIO2016-75754-P]; Australian Research Council
   [DP0983875, FT100100377]; Australian Research Council [FT100100377]
   Funding Source: Australian Research Council
FX We thank Mercedes Ramiro for technical assistance. This work has been
   funded by the Agencia Estatal de Investigacion of Spain and the Fondo
   Europeo de Desarrollo Regional (Union Europea) (grant BIO2016-75754-P to
   C.A.-B.) and by the Australian Research Council (Discovery grant
   DP0983875 and ARC-Future Fellowship FT100100377 to S.B.).
CR Alcázar R, 2012, CURR OPIN PLANT BIOL, V15, P205, DOI 10.1016/j.pbi.2012.01.002
   Alcázar R, 2010, NAT GENET, V42, P1135, DOI 10.1038/ng.704
   Alings F, 2015, RNA, V21, P202, DOI 10.1261/rna.048199.114
   Alonso-Blanco C, 1999, P NATL ACAD SCI USA, V96, P4710, DOI 10.1073/pnas.96.8.4710
   Alonso-Blanco C, 2016, CELL, V166, P481, DOI 10.1016/j.cell.2016.05.063
   [Anonymous], 1997, Embnew News
   [Anonymous], 2007, The origins of genomic architecture
   Balasubramanian S, 2006, PLOS GENET, V2, P980, DOI 10.1371/journal.pgen.0020106
   Bikard D, 2009, SCIENCE, V323, P623, DOI 10.1126/science.1165917
   Bita CE, 2013, FRONT PLANT SCI, V4, DOI 10.3389/fpls.2013.00273
   Bomblies K, 2007, PLOS BIOL, V5, P1962, DOI 10.1371/journal.pbio.0050236
   Bomblies K, 2010, ANNU REV PLANT BIOL, V61, P109, DOI 10.1146/annurev-arplant-042809-112146
   Box MS, 2015, CURR BIOL, V25, P194, DOI 10.1016/j.cub.2014.10.076
   Brock MT, 2010, MOL ECOL, V19, P1187, DOI 10.1111/j.1365-294X.2010.04538.x
   Caicedo AL, 2009, MOL BIOL EVOL, V26, P699, DOI 10.1093/molbev/msn300
   Clough SJ, 1998, PLANT J, V16, P735, DOI 10.1046/j.1365-313x.1998.00343.x
   Czechowski T, 2005, PLANT PHYSIOL, V139, P5, DOI 10.1104/pp.105.063743
   Edvardson S, 2016, NEUROGENETICS, V17, P219, DOI 10.1007/s10048-016-0487-z
   Fernández V, 2016, PLANT J, V86, P426, DOI 10.1111/tpj.13183
   Franks SJ, 2014, EVOL APPL, V7, P123, DOI 10.1111/eva.12112
   GALBRAITH DW, 1983, SCIENCE, V220, P1049, DOI 10.1126/science.220.4601.1049
   Gallego-Bartolomé J, 2010, MOL BIOL EVOL, V27, P1247, DOI 10.1093/molbev/msq012
   Gu WF, 2003, GENE DEV, V17, P2889, DOI 10.1101/gad.1148603
   Hanikenne M, 2008, NATURE, V453, P391, DOI 10.1038/nature06877
   Haug-Baltzell A, 2017, BIOINFORMATICS, V33, P2197, DOI 10.1093/bioinformatics/btx144
   Heinemann IU, 2012, NUCLEIC ACIDS RES, V40, P333, DOI 10.1093/nar/gkr696
   Huang CH, 2016, MOL BIOL EVOL, V33, P394, DOI 10.1093/molbev/msv226
   Jung JH, 2016, SCIENCE, V354, P886, DOI 10.1126/science.aaf6005
   Kliebenstein DJ, 2008, PLOS ONE, V3, DOI 10.1371/journal.pone.0001838
   Kliebenstein DJ, 2001, PLANT CELL, V13, P681, DOI 10.1105/tpc.13.3.681
   Kroymann J, 2003, P NATL ACAD SCI USA, V100, P14587, DOI 10.1073/pnas.1734046100
   Kumar SV, 2012, NATURE, V484, P242, DOI 10.1038/nature10928
   LAZO GR, 1991, BIO-TECHNOL, V9, P963, DOI 10.1038/nbt1091-963
   Lee JH, 2013, SCIENCE, V342, P628, DOI 10.1126/science.1241097
   Lee K, 2017, BIOCHEM BIOPH RES CO, V490, P400, DOI 10.1016/j.bbrc.2017.06.054
   Legris M, 2016, SCIENCE, V354, P897, DOI 10.1126/science.aaf5656
   Lutz U, 2017, ELIFE, V6, DOI [10.7554/eLife.22114, 10.7554/elife.22114]
   Lutz U, 2015, PLOS GENET, V11, DOI 10.1371/journal.pgen.1005588
   Lynch M, 2004, TRENDS GENET, V20, P544, DOI 10.1016/j.tig.2004.09.001
   Lyons E, 2008, PLANT J, V53, P661, DOI 10.1111/j.1365-313X.2007.03326.x
   McClung CR, 2016, FRONT PLANT SCI, V7, DOI 10.3389/fpls.2016.01266
   Méndez-Vigo B, 2016, PLANT CELL ENVIRON, V39, P272, DOI 10.1111/pce.12608
   Nicotra AB, 2010, TRENDS PLANT SCI, V15, P684, DOI 10.1016/j.tplants.2010.09.008
   Orioli A, 2017, BIOESSAYS, V39, DOI 10.1002/bies.201600158
   Panchy N, 2016, PLANT PHYSIOL, V171, P2294, DOI 10.1104/pp.16.00523
   Phillips PC, 2008, NAT REV GENET, V9, P855, DOI 10.1038/nrg2452
   Placido A, 2010, NUCLEIC ACIDS RES, V38, P7711, DOI 10.1093/nar/gkq646
   Prasad KVSK, 2012, SCIENCE, V337, P1081, DOI 10.1126/science.1221636
   Quint M, 2016, NAT PLANTS, V2, DOI [10.1038/NPLANTS.2015.190, 10.1038/nplants.2015.190]
   Raina M, 2014, FRONT GENET, V5, DOI 10.3389/fgene.2014.00171
   Raschke A, 2015, BMC PLANT BIOL, V15, DOI 10.1186/s12870-015-0566-6
   Rice TS, 2005, EUKARYOT CELL, V4, P832, DOI 10.1128/EC.4.4.832-835.2005
   Rosa M, 2013, PLANT CELL, V25, P1990, DOI 10.1105/tpc.112.104067
   Sanchez-Bermejo E, 2016, PLANT CELL ENVIRON, V39, P1353, DOI 10.1111/pce.12690
   Science Alert, 2014, HER TIN HUM TWIG TRE
   Soltis PS, 2016, CURR OPIN PLANT BIOL, V30, P159, DOI 10.1016/j.pbi.2016.03.015
   Sureshkumar S, 2016, NAT PLANTS, V2, DOI [10.1038/NPLANTS.2016.55, 10.1038/nplants.2016.55]
   Tamura K, 2011, MOL BIOL EVOL, V28, P2731, DOI 10.1093/molbev/msr121
   Tasset C, 2018, PLOS GENET, V14, DOI 10.1371/journal.pgen.1007280
   Trontin C, 2014, PLANT J, V78, P121, DOI 10.1111/tpj.12454
   Verhage L, 2014, TRENDS PLANT SCI, V19, P583, DOI 10.1016/j.tplants.2014.03.009
   Vlad D, 2014, SCIENCE, V343, P780, DOI 10.1126/science.1248384
   Vlad D, 2010, PLOS GENET, V6, DOI 10.1371/journal.pgen.1000945
   Zhu L, 2018, SCI CHINA LIFE SCI, V61, P155, DOI 10.1007/s11427-017-9167-5
   Zhu WS, 2015, PLOS GENET, V11, DOI 10.1371/journal.pgen.1005085
NR 65
TC 4
Z9 5
U1 0
U2 6
PU OXFORD UNIV PRESS INC
PI CARY
PA JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA
SN 1040-4651
EI 1532-298X
J9 PLANT CELL
JI Plant Cell
PD JUN
PY 2019
VL 31
IS 6
BP 1222
EP 1237
DI 10.1105/tpc.18.00938
PG 16
WC Biochemistry & Molecular Biology; Plant Sciences; Cell Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Plant Sciences; Cell Biology
GA IC7PE
UT WOS:000471166900020
OA Bronze, Green Published
DA 2025-01-10
ER

PT J
AU Prudencio, L
   Choi, R
   Esplin, E
   Ge, MY
   Gillard, N
   Haight, J
   Belmont, P
   Flint, C
AF Prudencio, Liana
   Choi, Ryan
   Esplin, Emily
   Ge, Muyang
   Gillard, Natalie
   Haight, Jeffrey
   Belmont, Patrick
   Flint, Courtney
TI The Impacts of Wildfire Characteristics and Employment on the Adaptive
   Management Strategies in the Intermountain West
SO FIRE-SWITZERLAND
LA English
DT Article
DE fire management; climate adaptation; wildfire mitigation; fire policy
   and decision-making; fire economics
AB Widespread development and shifts from rural to urban areas within the Wildland-Urban Interface (WUI) has increased fire risks to local populations, as well as introduced complex and long-term costs and benefits to communities. We use an interdisciplinary approach to investigate how trends in fire characteristics influence adaptive management and economies in the Intermountain Western US (IMW). Specifically, we analyze area burned and fire frequency in the IMW over time, how fires in urban or rural settings influence local economies and whether fire trends and economic impacts influence managers' perspectives and adaptive decision-making. Our analyses showed some increasing fire trends at multiple levels. Using a non-parametric event study model, we evaluated the effects of fire events in rural and urban areas on county-level private industry employment, finding short- and long-term positive effects of fire on employment at several scales and some short-term negative effects for specific sectors. Through interviewing 20 fire managers, we found that most recognize increasing fire trends and that there are both positive and negative economic effects of fire. We also established that many of the participants are implementing adaptive fire management strategies and we identified key challenges to mitigating increasing fire risk in the IMW.
C1 [Prudencio, Liana; Choi, Ryan; Esplin, Emily; Ge, Muyang; Gillard, Natalie; Haight, Jeffrey; Belmont, Patrick; Flint, Courtney] Utah State Univ, Climate Adaptat Sci, Logan, UT 84322 USA.
   [Prudencio, Liana; Gillard, Natalie; Haight, Jeffrey; Belmont, Patrick] Utah State Univ, Dept Watershed Sci, Logan, UT 84322 USA.
   [Choi, Ryan; Haight, Jeffrey; Flint, Courtney] Utah State Univ, Ecol Ctr, Logan, UT 84322 USA.
   [Choi, Ryan] Utah State Univ, Dept Wildland Resources, Logan, UT 84322 USA.
   [Esplin, Emily] Utah State Univ, Dept Environm & Soc, Logan, UT 84322 USA.
   [Ge, Muyang] Utah State Univ, Dept Appl Econ, Logan, UT 84322 USA.
   [Flint, Courtney] Utah State Univ, Dept Sociol Social Work & Anthropol, Logan, UT 84322 USA.
C3 Utah System of Higher Education; Utah State University; Utah System of
   Higher Education; Utah State University; Utah System of Higher
   Education; Utah State University; Utah System of Higher Education; Utah
   State University; Utah System of Higher Education; Utah State
   University; Utah System of Higher Education; Utah State University; Utah
   System of Higher Education; Utah State University
RP Prudencio, L (corresponding author), Utah State Univ, Climate Adaptat Sci, Logan, UT 84322 USA.; Prudencio, L (corresponding author), Utah State Univ, Dept Watershed Sci, Logan, UT 84322 USA.
EM liana.prudencio@aggiemail.usu.edu; choirt@gmail.com;
   emilyesplin@aggiemail.usu.edu; muyang.ge@aggiemail.usu.edu;
   natalie.j.gillard@aggiemail.usu.edu; jeffrey.haight@aggiemail.usu.edu;
   patrick.belmont@usu.edu; Courtney.Flint@usu.edu
OI Esplin, Emily/0000-0003-2737-4857; Belmont, Patrick/0000-0002-8244-3854;
   Haight, Jeffrey/0000-0002-3773-1566; Choi, Ryan/0000-0003-2020-5671;
   Prudencio, Liana/0000-0001-5361-9841
FU National Science Foundation [1633756]; Direct For Education and Human
   Resources; Division Of Graduate Education [1633756] Funding Source:
   National Science Foundation
FX Funding for this research came from the National Science Foundation
   (Grant #1633756).
CR Abatzoglou JT, 2016, P NATL ACAD SCI USA, V113, P11770, DOI 10.1073/pnas.1607171113
   Ager AA, 2015, RISK ANAL, V35, P1393, DOI 10.1111/risa.12373
   [Anonymous], 2016, R LANG ENV STAT COMP
   [Anonymous], Bureau of Labor Statistics Quarterly census of employment and wages program
   Boyatzis R. E., 1998, Transforming qualitative information: Thematic analysis and code development
   Braun V, 2021, QUAL RES PSYCHOL, V18, P328, DOI 10.1080/14780887.2020.1769238
   California Fire Alliance, 2001, CHAR FIR THREAT WILD, P1
   Calkin DE, 2014, P NATL ACAD SCI USA, V111, P746, DOI 10.1073/pnas.1315088111
   Calkin DE, 2013, INT J WILDLAND FIRE, V22, P212, DOI 10.1071/WF11075
   Charnley S, 2015, HUM ORGAN, V74, P329, DOI 10.17730/0018-7259-74.4.329
   Dale L., 2010, The true cost of wildfire in the western U.S.: Western Forestry Lead- ership Coalition
   Daniel T.C., 2007, People, Fire, and Forests
   Davis EJ, 2014, SOC NATUR RESOUR, V27, P983, DOI 10.1080/08941920.2014.905812
   Dennison PE, 2014, GEOPHYS RES LETT, V41, P2928, DOI 10.1002/2014GL059576
   Dunn CJ, 2017, INT J WILDLAND FIRE, V26, P551, DOI 10.1071/WF17089
   Eidenshink J. C., 2007, Fire Ecology, V3, P3, DOI [10.4996/fireecology.0301003, DOI 10.4996/FIREECOLOGY.0301003]
   Fitch RA, 2018, FOREST POLICY ECON, V87, P101, DOI 10.1016/j.forpol.2017.11.006
   Gan JB, 2015, J ENVIRON MANAGE, V159, P186, DOI 10.1016/j.jenvman.2015.06.014
   Garfin G., 2014, Climate Change Impacts in the United States: The Third National Climate Assessment, DOI DOI 10.7930/J08G8HMN
   Halpern CB, 2013, ECOL MONOGR, V83, P221, DOI 10.1890/12-1696.1
   Hammer RB, 2009, SOC NATUR RESOUR, V22, P777, DOI 10.1080/08941920802714042
   Homer C, 2015, PHOTOGRAMM ENG REM S, V81, P345, DOI 10.14358/PERS.81.5.345
   Ingalsbee T, 2017, INT J WILDLAND FIRE, V26, P557, DOI 10.1071/WF17062
   Katuwal H, 2017, INT J WILDLAND FIRE, V26, P604, DOI 10.1071/WF17054
   Knapp PA, 1998, GLOBAL ECOL BIOGEOGR, V7, P259, DOI 10.2307/2997600
   Lynch DL, 2004, J FOREST, V102, P42
   McGranahan D.A., 1999, NATURAL AMENITIES DR
   Mote P., 2014, CH 21 NW CLIMATE CHA, P487, DOI DOI 10.7930/J04Q7RWX
   Nielsen-Pincus M, 2014, FOREST POLICY ECON, V38, P199, DOI 10.1016/j.forpol.2013.08.010
   Nielsen-Pincus M, 2013, J FOREST, V111, P404, DOI 10.5849/jof.13-012
   Olson R., 2015, Wildland Fire Management Futures: Insights from a Foresight Panel; General Technical Report NRS-152
   Paveglio T, 2017, NAT HAZARDS, V87, P1083, DOI 10.1007/s11069-017-2810-x
   Paveglio TB, 2015, J RURAL STUD, V41, P72, DOI 10.1016/j.jrurstud.2015.07.006
   Paveglio TB, 2015, FOREST SCI, V61, P298, DOI 10.5849/forsci.14-036
   Paveglio TB, 2015, INT J WILDLAND FIRE, V24, P212, DOI 10.1071/WF14091
   Paveglio TB, 2012, HUM ECOL REV, V19, P110
   Radeloff VC, 2005, ECOL APPL, V15, P799, DOI 10.1890/04-1413
   Radeloff VC, 2018, P NATL ACAD SCI USA, V115, P3314, DOI 10.1073/pnas.1718850115
   Schoennagel T, 2004, BIOSCIENCE, V54, P661, DOI 10.1641/0006-3568(2004)054[0661:TIOFFA]2.0.CO;2
   Stewart SI, 2007, J FOREST, V105, P201
   Theobald DM, 2007, LANDSCAPE URBAN PLAN, V83, P340, DOI 10.1016/j.landurbplan.2007.06.002
   Thompson MP, 2017, INT J WILDLAND FIRE, V26, P562, DOI 10.1071/WF16137
   Thompson MP., 2016, Risk management: Core principles and practices, and their relevance to wildland fire
   United States Census Bureau, 2018, STATS STOR NEW YEARS
   United States Census Bureau, 2015, CART BOUND SHAP
   USFS, 2015, RIS COST FIR OP EFF, P1
   van Mantgem PJ, 2013, ECOL LETT, V16, P1151, DOI 10.1111/ele.12151
   Westerling AL, 2006, SCIENCE, V313, P940, DOI 10.1126/science.1128834
NR 48
TC 3
Z9 6
U1 0
U2 5
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
SN 2571-6255
J9 FIRE-BASEL
JI Fire-Switzerland
PD DEC
PY 2018
VL 1
IS 3
AR 46
DI 10.3390/fire1030046
PG 23
WC Ecology; Forestry
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Forestry
GA VK4JU
UT WOS:000697562900013
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Davis, RA
   Watson, DM
AF Davis, Robert A.
   Watson, David M.
TI Vagrants as vanguards of range shifts in a dynamic world
SO BIOLOGICAL CONSERVATION
LA English
DT Article
ID CLIMATE-CHANGE; IMPACTS; BIODIVERSITY; COLONIZATION; CONSERVE; AVIFAUNA;
   DECLINE
AB The recent capture and removal to captivity of the first Nicobar Pigeon in Australia on the basis of biosecurity concerns, provides a compelling opportunity to examine how we manage species that naturally disperse to new territories. With the spectre of increasing climate change there is an increasing recognition of the need for species to expand or shift their ranges as part of natural adaptation. The occurrence of vagrants is a natural phenomenon that may be increasing as a result of climate change and other disturbances, but self-introduced organisms are known world-wide in multiple taxa. Although most vagrants are short-lived and of little lasting ecological consequence, some represent the forerunners of climate adaptation individuals best placed to found new populations beyond their previous range. In contrast to invasive species for which policies and legislative instruments are commonplace (including watch lists of the world's worst invaders), policy makers have failed to consider the inherent dynamism of distributional ranges and the important role of vagrants as first responders to environmental change. The application of ad-hoc policies considering individual vagrants as a biosecurity risk is ill-informed, ecologically indefensible, and potentially counter-productive. We articulate the need for a new framework to consider vagrants as climate refugees and challenge conservation managers and on-ground practitioners to take active roles in determining how they are both viewed and managed.
C1 [Davis, Robert A.] Edith Cowan Univ, Sch Sci, 100 Joondalup Dr, Joondalup, WA 6027, Australia.
   [Davis, Robert A.] Univ Western Australia, Sch Biol Sci, 35 Stirling Highway, Crawley, WA 6009, Australia.
   [Watson, David M.] Charles Sturt Univ, Inst Land Water & Soc, POB 789, Albury, NSW 2640, Australia.
C3 Edith Cowan University; University of Western Australia; Charles Sturt
   University
RP Davis, RA (corresponding author), Edith Cowan Univ, Sch Sci, 100 Joondalup Dr, Joondalup, WA 6027, Australia.
EM robert.davis@ecu.edu.au
RI Watson, David/N-9760-2018; Davis, Robert/F-6621-2012
OI Davis, Robert/0000-0002-9062-5754
CR [Anonymous], 2017, ABC News
   [Anonymous], 2000, 100 WORLDS WORST INV
   Australian Geographic, 2017, END DOD REL FOUND WA
   Barlow B. A., 1984, FLORA AUSTR, P68
   Birdlife Australia Rarities Committee, 2017, IND OF CAS
   Clout Mick N., 2000, P369
   Cook JL, 2003, BIODIVERS CONSERV, V12, P187, DOI 10.1023/A:1021986927560
   Doherty TS, 2015, J BIOGEOGR, V42, P964, DOI 10.1111/jbi.12469
   Gibbons JW, 2000, BIOSCIENCE, V50, P653, DOI 10.1641/0006-3568(2000)050[0653:TGDORD]2.0.CO;2
   Gill F, 2018, IOC WORLD BIRD LIST, DOI [10. 14344/ioc. ml. 8. 1, DOI 10.14344/I0C.ML.8.1, 10.14344/IOC.ML.8.1]
   Gilroy JJ, 2017, CONSERV LETT, V10, P238, DOI 10.1111/conl.12246
   Hoegh-Guldberg O, 2008, SCIENCE, V321, P345, DOI 10.1126/science.1157897
   Jiguet F, 2013, IBIS, V155, P194, DOI 10.1111/ibi.12001
   Lees AC, 2014, GLOBAL ECOL BIOGEOGR, V23, P405, DOI 10.1111/geb.12129
   Loarie SR, 2009, NATURE, V462, P1052, DOI 10.1038/nature08649
   Pysek P, 2008, DIVERS DISTRIB, V14, P355, DOI 10.1111/j.1472-4642.2007.00431.x
   Pysek P, 2012, GLOBAL CHANGE BIOL, V18, P1725, DOI 10.1111/j.1365-2486.2011.02636.x
   Ruffino L, 2015, WILDLIFE RES, V42, P185, DOI 10.1071/WR15047
   Runge CA, 2017, CONSERV LETT, V10, P765, DOI 10.1111/conl.12345
   Sinervo B, 2010, SCIENCE, V328, P894, DOI 10.1126/science.1184695
   Smith TB, 2014, ANNU REV ECOL EVOL S, V45, P1, DOI 10.1146/annurev-ecolsys-120213-091747
   Thiengo SC, 2007, BIOL INVASIONS, V9, P693, DOI 10.1007/s10530-006-9069-6
   Urban MC, 2015, SCIENCE, V348, P571, DOI 10.1126/science.aaa4984
   Watson D M., 2011, Mistletoes of Southern Australia
   Wiles GJ, 2003, CONSERV BIOL, V17, P1350, DOI 10.1046/j.1523-1739.2003.01526.x
   Zhan S, 2014, NATURE, V514, P317, DOI 10.1038/nature13812
NR 26
TC 21
Z9 21
U1 0
U2 4
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0006-3207
EI 1873-2917
J9 BIOL CONSERV
JI Biol. Conserv.
PD AUG
PY 2018
VL 224
BP 238
EP 241
DI 10.1016/j.biocon.2018.06.006
PG 4
WC Biodiversity Conservation; Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA GN9PY
UT WOS:000439537600027
DA 2025-01-10
ER

PT J
AU Meze-Hausken, E
   Patt, A
   Fritz, S
AF Meze-Hausken, Elisabeth
   Patt, Anthony
   Fritz, Steffen
TI Reducing climate risk for micro-insurance providers in Africa: A case
   study of Ethiopia
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article
DE Spatial diversification; Ethiopia; Climate insurance; Climate adaptation
AB Recurrent climate hazards challenge subsistence farmers in developing countries. Reliance on various diversification strategies and traditional risk sharing among kin and families has serious limitations, such as the problem of covariate risk within such networks. Index-based crop insurance could help to reduce people's climate-related risk, but raising the necessary capital to make insurance schemes financially secure is difficult for micro-insurance providers. We examine the extent to which spatial pooling of micro-insurance schemes could reduce these capital requirements. We simulate a hypothetical insurance market operating in Ethiopia, using rainfall data and yield estimates for 15 stations. By performing a Monte Carlo analysis, risk capital required to keep the probability of financial ruin below a threshold value is identified. We investigate the marginal benefits of pooling increasing numbers of sites, as well as the relationship between the benefits of pooling and the spatial covariance of rainfall. We find spatial diversification to offer considerable savings in required capitalization with as few as three sites pooled, as well as a weak but significant relationship between rainfall covariance and those benefits. The results suggest that spatial pooling may be an attractive option for micro-insurers, worthy of a detailed case-by-case analysis when designing index-insurance schemes. (C) 2008 Elsevier Ltd. All rights reserved.
C1 [Meze-Hausken, Elisabeth; Patt, Anthony; Fritz, Steffen] Int Inst Appl Syst Anal, A-2361 Laxenburg, Austria.
C3 International Institute for Applied Systems Analysis (IIASA)
RP Meze-Hausken, E (corresponding author), Int Inst Appl Syst Anal, Schlosspl 1, A-2361 Laxenburg, Austria.
EM Elisabeth.Meze@gjensidige.no
RI Patt, Anthony/E-5437-2017
OI Patt, Anthony/0000-0001-8428-8707; , Steffen/0000-0003-0420-8549
FU Austrian Academy of Sciences; Norwegian Research Council
FX This work has been funded by the Austrian Academy of Sciences and the
   Norwegian Research Council.
CR Adger W. N., 2003, Progress in Development Studies, V3, P179, DOI 10.1191/1464993403ps060oa
   [Anonymous], 2003, MULTINATIONAL FINANC, DOI DOI 10.17578/7-3/4-5
   ANTLE JM, 1995, AM J AGR ECON, V77, P741, DOI 10.2307/1243244
   Bals C, 2006, CLIM POLICY, V6, P637
   Boko M, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P433
   BROMLEY DW, 1989, ECON DEV CULT CHANGE, V37, P719, DOI 10.1086/451757
   Brooks N., 2004, Adaptation Policy Framework for Climate Change, P165
   CASTALDI A, 2004, CATASTROPHE RISK REI, P169
   Conway D, 2000, GEOGR J, V166, P49, DOI 10.1111/j.1475-4959.2000.tb00006.x
   EZZATABADI MA, 2006, P 4 INT S PIST ALM T
   FAO, 1984, AGDPETH78003 FAO
   Gardner B., 1986, CROP INSURANCE AGR D
   Glauber J. W., 2004, American Journal of Agricultural Economics, V86, P1179, DOI 10.1111/j.0002-9092.2004.00663.x
   Gurenko E., 2004, Catastrophe Risk and Reinsurance
   HERRING R, 2004, BROOKINGS WHARTON PA
   Hess U., 2005, 13 WORLD BANK, P1, DOI 10.1186/s12889-016-3840-0
   HOCHRAINER S, 2007, FEASIBILITY RISK FIN, P53
   Hoeppe P, 2006, CLIM POLICY, V6, P607, DOI 10.1080/14693062.2006.9685627
   Klopper E, 2006, CLIMATIC CHANGE, V76, P73, DOI 10.1007/s10584-005-9019-9
   Linnerooth-Bayer J, 2005, SCIENCE, V309, P1044, DOI 10.1126/science.1116783
   Linnerooth-Bayer J, 2006, CLIM POLICY, V6, P621
   MECHLER R, 2006, IIASA PROVENTION CON
   Meze-Hausken Elisabeth., 2000, Mitigation and Adaptation Strategies for Global Change, V5, P379, DOI [DOI 10.1023/A:1026570529614, 10.1023/A:1026570529614]
   Osgood Daniel E., 2007, Climate Risk Management in Africa: Learning from Practice, P75
   Patt AG, 2007, SCIENCE, V318, P49, DOI 10.1126/science.1147909
   Roncoli C, 2001, CLIM RES, V19, P119, DOI 10.3354/cr019119
   Scoones Ian., 1996, HAZARDS OPPORTUNITIE
   SKEES J, 1999, 55 EPDT INT FOOD RES
   *SWISS RE, 1996, INS RISK CAP
   *UNDP, 2000, COP CLIM VAR SUBS AF
   VELTHUIZEN H, 1995, AGROMETEOROLOGY SERI, V10
   Washington R, 2006, B AM METEOROL SOC, V87, P1355, DOI 10.1175/BAMS-87-10-1355
   Watkins K., 2005, HUMAN DEV REPORT 200
   Watson RT, 2001, CLIMATE CHANGE 2001: IMPACTS, ADAPTATION, AND VULNERABILITY, pIX
   White P., 2005, Disaster risk reduction: a development concern. A scoping study on links between disaster risk reduction
   *WORLD FOOD PROG, 2007, WFPEB1200710
   Yohe G, 2002, GLOBAL ENVIRON CHANG, V12, P25, DOI 10.1016/S0959-3780(01)00026-7
NR 37
TC 35
Z9 39
U1 1
U2 23
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 FEB
PY 2009
VL 19
IS 1
BP 66
EP 73
DI 10.1016/j.gloenvcha.2008.09.001
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 425RS
UT WOS:000264655400009
DA 2025-01-10
ER

PT J
AU Hartinger, SM
   Palmeiro-Silva, YK
   Llerena-Cayo, C
   Blanco-Villafuerte, L
   Escobar, LE
   Diaz, A
   Sarmiento, JH
   Lescano, AG
   Melo, O
   Rojas-Rueda, D
   Takahashi, B
   Callaghan, M
   Chesini, F
   Dasgupta, S
   Posse, CG
   Gouveia, N
   de Carvalho, AM
   Miranda-Chacón, Z
   Mohajeri, N
   Pantoja, C
   Robinson, EJZ
   Salas, MF
   Santiago, R
   Sauma, E
   Santos-Vega, M
   Scamman, D
   Sergeeva, M
   de Camargo, TS
   Sorensen, C
   Umaña, JD
   Yglesias-González, M
   Walawender, M
   Buss, D
   Romanello, M
AF Hartinger, Stella M.
   Palmeiro-Silva, Yasna K.
   Llerena-Cayo, Camila
   Blanco-Villafuerte, Luciana
   Escobar, Luis E.
   Diaz, Avriel
   Sarmiento, Juliana Helo
   Lescano, Andres G.
   Melo, Oscar
   Rojas-Rueda, David
   Takahashi, Bruno
   Callaghan, Max
   Chesini, Francisco
   Dasgupta, Shouro
   Posse, Carolina Gil
   Gouveia, Nelson
   de Carvalho, Aline Martins
   Miranda-Chacon, Zaray
   Mohajeri, Nahid
   Pantoja, Chrissie
   Robinson, Elizabeth J. Z.
   Salas, Maria Fernanda
   Santiago, Raquel
   Sauma, Enzo
   Santos-Vega, Mauricio
   Scamman, Daniel
   Sergeeva, Milena
   de Camargo, Tatiana Souza
   Sorensen, Cecilia
   Umana, Juan D.
   Yglesias-Gonzalez, Marisol
   Walawender, Maria
   Buss, Daniel
   Romanello, Marina
TI The 2023 Latin America report of the Lancet Countdown on health and
   climate change: the imperative for health-centred climate-resilient
   development
SO LANCET REGIONAL HEALTH-AMERICAS
LA English
DT Article
DE Climate change; Health; Health risks; Latin America; South America;
   Central America; Climatic impact- drivers; Impacts; Adaptation;
   Mitigation; Economy; Policy
ID IMPACTS
AB In 2023, a series of climatological and political events unfolded, partly driving forward the global climate and health agenda while simultaneously exposing important disparities and vulnerabilities to climate-related events. On the policy front, a signi fi cant step forward was marked by the inaugural Health Day at COP28, acknowledging the profound impacts of climate change on health. However, the fi rst-ever Global Stocktake showed an important gap between the current progress and the targets outlined in the Paris Agreement, underscoring the urgent need for further and decisive action. From a Latin American perspective, some questions arise: How do we achieve the change that is needed? How to address the vulnerabilities to climate change in a region with long standing social inequities? How do we promote intersectoral collaboration to face a complex problem such as climate change? The debate is still ongoing, and in many instances, it is just starting. The renamed regional centre Lancet Countdown Latin America (previously named Lancet Countdown South America) expanded its geographical scope adding Mexico and fi ve Central American countries: Costa Rica, El Salvador, Guatemala, Honduras, and Panama, as a response to the need for stronger collaboration in a region with signi fi cant social disparities, including research capacities and funding. The centre is an independent and multidisciplinary collaboration that tracks the links between health and climate change in Latin America, following the global Lancet Countdown ' s methodologies and fi ve domains. The Lancet Countdown Latin America work hinges on the commitment of 23 regional academic institutions, United Nations agencies, and 34 researchers who generously contribute their time and expertise. Building from the fi rst report, the 2023 report of the Lancet Countdown Latin America, presents 34 indicators that track the relationship between health and climate change up to 2022, aiming at providing evidence to public decisionmaking with the purpose of improving the health and wellbeing of Latin American populations and reducing social inequities through climate actions focusing on health. This report shows that Latin American populations continue to observe a growing exposure to changing climatic conditions. A warming trend has been observed across all countries in Latin America, with severe direct impacts. In 2022, people were exposed to ambient temperatures, on average, 0.38 degrees C higher than in 1986 - 2005, with Paraguay experiencing the highest anomaly (+1.9 degrees C), followed by Argentina (+1.2 degrees C) and Uruguay (+0.9 degrees C) (indicator 1.1.1). In 2013 - 2022, infants were exposed to 248% more heatwave days and people over 65 years old were exposed to 271% more heatwave days than in 1986 - 2005 (indicator 1.1.2). Also, compared to 1991 - 2000, in 2013 - 2022, there were 256 and 189 additional annual hours per person, during which ambient heat posed at least moderate and high risk of heat stress during light outdoor physical activity in Latin America, respectively (indicator 1.1.3). Finally, the region had a 140% increase in heat -related mortality from 2000 - 2009 to 2013 - 2022 (indicator 1.1.4). Changes in ecosystems have led to an increased risk of wild fi res, exposing individuals to very or extremely high fi re danger for more extended periods (indicator 1.2.1). Additionally, the transmission potential for dengue by Aedes aegypti mosquitoes has risen by 54% from 1951 - 1960 to 2013 - 2022 (indicator 1.
   3), which aligns with the recent outbreaks and increasing dengue cases observed across Latin America in recent months. Based on the 2023 report of the Lancet Countdown Latin America, there are three key messages that Latin America needs to further explore and advance for a health -centred climate -resilient development. Latin American countries require intersectoral public policies that simultaneously increase climate resilience, reduce social inequities, improve population health, and reduce greenhouse gas (GHG) emissions . The fi ndings show that adaptation policies in Latin America remain weak, with a pressing need for robust vulnerability and adaptation (V&A) assessments to address climate risks effectively. Unfortunately, such assessments are scarce. Up to 2021, Brazil is the only country that has completed and off i cially reported a V&A to the 2021 Global Survey conducted by the World Health Organization (WHO). Argentina, Guatemala, and Panama have also conducted them, but they have not been reported (indicator 2.1.1). Similarly, efforts in developing and implementing Health National Adaptation Plans (HNAPs) are varied and limited in scope. Brazil, Chile, and Uruguay are the only countries that have an HNAP (indicator 2.1.2). Moreover, self -reported city -level climate change risk assessments are very limited in the region (indicator 2.1.3). The collaboration between meteorological and health sectors remains insuff i cient, with only Argentina, Brazil, Colombia, and Guatemala self -reporting some level of integration (indicator 2.2.1), hindering comprehensive responses to climate -related health risks in the region. Additionally, despite the urgent need for action, there has been minimal progress in increasing urban greenspaces across the region since 2015, with only Colombia, Nicaragua, and Venezuela showing slight improvements (indicator 2.2.2). Compounding these challenges is the decrease in funding for climate change adaptation projects in Latin America, as evidenced by the 16% drop in funds allocated by the Green Climate Fund (GCF) in 2022 compared to 2021. Alarmingly, none of the funds approved in 2022 were directed toward climate change and health projects, highlighting a critical gap in addressing health -related climate risks From a vulnerability perspective, the Mosquito Risk Index (MoRI) indicates an overall decrease in severe mosquitoborne disease risk in the region due to improvements in water, sanitation, and hygiene (WASH) (indicator 2.3.1). Brazil and Paraguay were the only countries that showed an increase in this indicator. It is worth noting that signi fi cant temporal variation within and between countries still persists, suggesting inadequate preparedness for climate-related changes. Overall, population health is not solely determined by the health sector, nor are climate policies a sole responsibility of the environmental sector. More and stronger intersectoral collaboration is needed to pave development pathways that consider solid adaptation to climate change, greater reductions of GHG emissions, and that increase social equity and population health. These policies involve sectors such as fi nance, transport, energy, housing, health, and agriculture, requiring institutional structures and policy instruments that allow long-term intersectoral collaboration. Latin American countries need to accelerate an energy transition that prioritises people ' s health and wellbeing, reduces energy poverty and air pollution, and maximises health and economic gains .
   In Latin America, there is a notable disparity in energy transition, with electricity generation from coal increasing by an average of 2.6% from 1991 - 2000 to 2011 - 2020, posing a challenge to efforts aimed at phasing out coal (indicator 3.1.1). However, this percentage increase is conservative as it may not include all the fossil fuels for thermoelectric electricity generation, especially during climate-related events and when hydropower is affected (Panel 4). Yet, renewable energy sources have been growing, increasing by an average of 5.7% during the same period. Access to clean fuels for cooking remains a concern, with 46.3% of the rural population in Central America and 23.3% in South America lacking access to clean fuels in 2022 (indicator 3.1.2). It is crucial to highlight the concerning overreliance on fossil fuels, particularly lique fi ed petroleum gas (LPG), as a primary cooking fuel. A signi fi cant majority of Latin American populations, approximately 74.6%, rely on LPG for cooking. Transitioning to cleaner heating and cooking alternatives could also have a health bene fi t by reducing household air pollution-related mortality. Fossil fuels continue to dominate road transport energy in Latin America, accounting for 96%, although some South American countries are increasing the use of biofuels (indicator 3.1.3). Premature mortality attributable to fossil-fuel-derived PM 2.5 has shown varied trends across countries, increasing by 3.9% from 2005 to 2020 across Latin America, which corresponds to 123.5 premature deaths per million people (indicator 3.2.1). The Latin American countries with the highest premature mortality rate attributable to PM 2.5 in 2020 were Chile, Peru, Brazil, Colombia, Mexico, and Paraguay. Of the total premature deaths attributable to PM 2.5 in 2020, 19.1% was from transport, 12.3% from households, 11.6% from industry, and 11% from agriculture. From emission and capture of GHG perspective, commodity-driven deforestation and expansion of agricultural land remain major contributors to tree cover loss in the region, accounting for around 80% of the total loss (indicator 3.3). Additionally, animal-based food production in Latin America contributes 85% to agricultural CO 2 equivalent emissions, with Argentina, Brazil, Panama, Paraguay, and Uruguay ranking highest in per capita emissions (indicator 3.4.1). From a health perspective, in 2020, approximately 870,000 deaths were associated with imbalanced diets, of which 155,000 (18%) were linked to high intake of red and processed meat and dairy products (indicator 3.4.2). Energy transition in Latin America is still in its infancy, and as a result, millions of people are currently exposed to dangerous levels of air pollution and energy poverty (i.e., lack of access to essential energy sources or services). As shown in this report, the levels of air pollution, outdoors and indoors, are a signi fi cant problem in the whole region, with marked disparities between urban and rural areas. In 2022, Peru, Chile, Mexico, Guatemala, Colombia, El Salvador, Brazil, Uruguay, Honduras, Panama, and Nicaragua were in the top 100 most polluted countries globally. Transitioning to cleaner sources of energy, phasing out fossil fuels, and promoting better energy eff i ciency in the industrial and housing sectors are not only climate mitigation measures but also huge health and economic opportunities for more prosperous and healthy societies.
   Latin American countries need to increase climate fi nance through permanent fi scal commitments and multilateral development banks to pave climate-resilient development pathways . Climate change poses signi fi cant economic costs, with investments in mitigation and adaptation measures progressing slowly. In 2022, economic losses due to weather-related extreme events in Latin America were US$15.6 billion - an amount mainly driven by fl oods and landslides in Brazil - representing 0.28% of Latin America ' s Gross Domestic Product (GDP) (indicator 4.1.1). In contrast to high-income countries, most of these losses lack insurance coverage, imposing a substantial fi nancial strain on affected families and governments. Heat -related mortality among individuals aged 65 and older in Latin America reached alarming levels, with losses exceeding the equivalent of the average income of 451,000 people annually (indicator 4.1.2). Moreover, the total potential income loss due to heat -related labour capacity reduction amounted to 1.34% of regional GDP, disproportionately affecting the agriculture and construction sectors (indicator 4.1.3). Additionally, the economic toll of premature mortality from air pollution was substantial, equivalent to a signi fi cant portion of regional GDP (0.61%) (indicator 4.1.4). On a positive note, clean energy investments in the region increased in 2022, surpassing fossil fuel investments. However, in 2020, all countries reviewed continued to offer net -negative carbon prices, revealing fossil fuel subsidies totalling US$23 billion. Venezuela had the highest net subsidies relative to current health expenditure (123%), followed by Argentina (10.5%), Bolivia (10.3%), Ecuador (8.3%), and Chile (5.6%) (indicator 4.2.1). Fossil fuel -based energy is today more expensive than renewable energy. Fossil fuel burning drives climate change and damages the environment on which people depend, and air pollution derived from the burning of fossil fuels causes seven million premature deaths each year worldwide, along with a substantial burden of disease. Transitioning to sustainable, zero -emission energy sources, fostering healthier food systems, and expediting adaptation efforts promise not only environmental bene fi ts but also signi fi cant economic gains. However, to implement mitigation and adaptation policies that also improve social wellbeing and prosperity, stronger and solid fi nancial systems are needed. Climate fi nance in Latin American countries is scarce and strongly depends on political cycles, which threatens adequate responses to the current and future challenges. Progress on the climate agenda is lagging behind the urgent pace required. While engagement with the intersection of health and climate change is increasing, government involvement remains inadequate. Newspaper coverage of health and climate change has been on the rise, peaking in 2022, yet the proportion of climate change articles discussing health has declined over time (indicator 5.1). Although there has been signi fi cant growth in the number of scienti fi c papers focusing on Latin America, it still represents less than 4% of global publications on the subject (indicator 5.3). And, while health was mentioned by most Latin American countries at the UN General Debate in 2022, only a few addressed the intersection of health and climate change, indicating a lack of awareness at the governmental level (indicator 5.4).
   The 2023 Lancet Countdown Latin America report underscores the cascading and compounding health impacts of anthropogenic climate change, marked by increased exposure to heatwaves, wild fi res, and vector -borne diseases. Speci fi cally, for Latin America, the report emphasises three critical messages: the urgent action to implement intersectoral public policies that enhance climate resilience across the region; the pressing need to prioritise an energy transition that focuses on health co -bene fi ts and wellbeing, and lastly, that need for increasing climate fi nance by committing to sustained fi scal efforts and engaging with multilateral development banks. By understanding the problems, addressing the gaps, and taking decisive action, Latin America can navigate the challenges of climate change, fostering a more sustainable and resilient future for its population. Spanish and Portuguese translated versions of this Summary can be found in Appendix B and C, respectively. The full translated report in Spanish is available in Appendix D. Copyright (c) 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY -NC license (http://creativecommons.org/licenses/by-nc/4.0/).
C1 [Hartinger, Stella M.; Llerena-Cayo, Camila; Blanco-Villafuerte, Luciana; Lescano, Andres G.; Yglesias-Gonzalez, Marisol] Univ Peruana Cayetano Heredia, Ctr Latino Americano Excelencia Cambio Climat & Sa, Lima, Peru.
   [Palmeiro-Silva, Yasna K.; Walawender, Maria; Romanello, Marina] UCL, Inst Global Hlth, London, England.
   [Llerena-Cayo, Camila] Pontificia Univ Catolica Chile, Ctr Polit Publ UC, Santiago, Chile.
   [Escobar, Luis E.] Virginia Tech, Dept Fish & Wildlife Conservat, Blacksburg, VA USA.
   [Diaz, Avriel] Columbia Univ, Int Res Inst Climate & Soc, New York, NY USA.
   [Sarmiento, Juliana Helo] Univ Los Andes, Fac Econ, Bogota, Colombia.
   [Melo, Oscar] Pontificia Univ Catolica Chile, Ctr Interdisciplinario Cambio Global, Santiago, Chile.
   [Rojas-Rueda, David] Colorado State Univ, Environm & Radiol Hlth Sci, Ft Collins, CO USA.
   [Takahashi, Bruno] Michigan State Univ, Dept Commun, E Lansing, MI USA.
   [Callaghan, Max] Mercator Res Inst, Global Commons & Climate Change, Berlin, Germany.
   [Chesini, Francisco] Univ Buenos Aires, Fac Med, Dept Salud Publ, Buenos Aires, Argentina.
   [Dasgupta, Shouro; Robinson, Elizabeth J. Z.] Ctr Euro Mediterraneo Cambiamenti Climat CMCC, Venice, Italy.
   [Posse, Carolina Gil] London Sch Econ & Polit Sci LSE, Grantham Res Inst Climate Change & Environm, London, England.
   [Gouveia, Nelson] Univ Buenos Aires, Fac Ciencias Sociales, Buenos Aires, Argentina.
   [de Carvalho, Aline Martins] Univ Sao Paulo, Fac Med, Dept Med Prevent, Sao Paulo, Brazil.
   [Miranda-Chacon, Zaray] Univ Sao Paulo, Fac Saude Publ, Dept Nutr, Sao Paulo, Brazil.
   [Mohajeri, Nahid] Univ Costa Rica, Med Sch, San Pedro, Costa Rica.
   [Pantoja, Chrissie] UCL, Inst Environm Design & Engn, Bartlett Sch Environm Energy & Resources, London, England.
   [Pantoja, Chrissie] Duke Univ, Nicholas Sch Environm, Durham, NC USA.
   [Pantoja, Chrissie] Duke Univ, Sanford Sch Policy Policy, Durham, NC USA.
   [Salas, Maria Fernanda] Univ Pacifico, Dept Acad Econ, Lima, Peru.
   [Santiago, Raquel] Univ Costa Rica, San Pedro, Costa Rica.
   [Sauma, Enzo] Univ Fed Goias, Fac Nutr, Goiania, GO, Brazil.
   [Santos-Vega, Mauricio] Pontificia Univ Catolica Chile, Engn Fac, Santiago, Chile.
   [Santos-Vega, Mauricio; Umana, Juan D.] Univ Andes, Grp Biol & Matemat Computac BIOMAC, Bogota, Colombia.
   [Scamman, Daniel] Univ Los Andes, Dept Ciencias Biol, Bogota, Colombia.
   [Sergeeva, Milena] Global Climate & Hlth Alliance, Berkeley, CA USA.
   [de Camargo, Tatiana Souza] Univ Fed Rio Grande do Sul, Fac Educ, Porto Alegre, Brazil.
   [Sorensen, Cecilia] Columbia Univ, Columbia Irving Med Ctr, Mailman Sch Publ Hlth, Dept Environm Hlth Sci,Dept Emergency Med, New York, NY USA.
   [Buss, Daniel] Pan Amer Hlth Org, Washington, DC USA.
   [Rojas-Rueda, David] Colorado State Univ, Colorado Sch Publ Hlth, Ft Worth, CO USA.
C3 Universidad Peruana Cayetano Heredia; University of London; University
   College London; Pontificia Universidad Catolica de Chile; Virginia
   Polytechnic Institute & State University; Columbia University;
   Universidad de los Andes (Colombia); Pontificia Universidad Catolica de
   Chile; Colorado State University; Michigan State University; University
   of Buenos Aires; Centro Euro-Mediterraneo sui Cambiamenti Climatici
   (CMCC); University of London; London School Economics & Political
   Science; University of Buenos Aires; Universidade de Sao Paulo;
   Universidade de Sao Paulo; Universidad Costa Rica; University of London;
   University College London; Duke University; Duke University; Universidad
   del Pacifico Peru; Universidad Costa Rica; Universidade Federal de
   Goias; Pontificia Universidad Catolica de Chile; Universidad de los
   Andes (Colombia); Universidad de los Andes (Colombia); Universidade
   Federal do Rio Grande do Sul; Columbia University; NewYork-Presbyterian
   Hospital; Pan American Health Organization; Colorado School of Public
   Health; Colorado State University
RP Hartinger, SM (corresponding author), Ave Honorio Delgado 430, Lima 15102, Peru.
EM stella.hartinger.p@upch.pe
RI Carvalho, Aline/AAO-9144-2020; Callaghan, Max/I-1769-2019; Lescano,
   Andres/M-9849-2019; Escobar, Luis/I-2204-2019; Yglesias-Gonzalez,
   Marisol/JLK-9207-2023; Dasgupta, Shouro/ABE-7831-2020; melo,
   oscar/AAC-7164-2020; melo, oscar/N-8872-2014
OI Mohajeri, Nahid/0000-0002-7339-5109; Blanco Villafuerte,
   Luciana/0000-0002-8137-1887; Palmeiro-Silva, Yasna
   K/0000-0001-6664-1079; Robinson, Elizabeth/0000-0002-4950-0183;
   Llerena-Cayo, Camila/0000-0002-8130-4449; melo,
   oscar/0000-0002-9136-5413
CR Abramo L, 2020, CIENC SAUDE COLETIVA, V25, P1587, DOI 10.1590/1413-81232020255.32802019
   Amoadu M, 2023, J CLIM CHANGE HEALTH, V12, DOI 10.1016/j.joclim.2023.100249
   [Anonymous], 2023, LANCET REG HEALTH-AM, V22, DOI 10.1016/j.lana.2023.100539
   [Anonymous], 2023, Household air pollution [Internet]
   Armendariz B., 2017, The economics of contemporary Latin America
   Beck HE, 2018, SCI DATA, V5, DOI 10.1038/sdata.2018.214
   Buonocore JJ, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab49bc
   Cafiero C, 2018, MEASUREMENT, V116, P146, DOI 10.1016/j.measurement.2017.10.065
   Calderon A, 2021, Indice de vulnerabilidad al cambio climatico de la Republica de Panama
   Carbon Disclosure Project, 2022, cities climate risk and vulnerability assessments
   Cardenas M, 2022, The challenges of climate mitigation in Latin America and the Caribbean: some proposals for action
   Chen Y, 2020, LANDSCAPE URBAN PLAN, V204, DOI 10.1016/j.landurbplan.2020.103919
   Climate Funds Update, 2022, Climate funds update
   COES. COES SINAC (Comite de Operacion Economica del Sistema Interconectado Nacional), 2024, About us
   Columbia University, 2017, Global Consortium on climate and health education: about
   COP28, 2023, Over 120 countries back COP28 UAE Climate and Health Declaration delivering breakthrough moment for health in climate talks
   COP28 UEA, 2024, COP28 declaration on climate and health
   Copernicus, 2023, Copernicus EMS rapid mapping activation viewer
   Copernicus ECMWF, 2023, Copernicus: november 2023-remarkable year continues, with warmest boreal autumn. 2023 will be the warmest year on record | Copernicus
   Cronin J, 2018, CLIMATIC CHANGE, V151, P79, DOI 10.1007/s10584-018-2265-4
   Curtis PG, 2018, SCIENCE, V361, P1108, DOI 10.1126/science.aau3445
   da Silva CFA, 2023, ENVIRON MONIT ASSESS, V195, DOI 10.1007/s10661-023-11174-0
   Diehl T, 2021, INT J PUBLIC OPIN R, V33, P197, DOI 10.1093/ijpor/edz040
   Ebi KL, 2021, LANCET, V398, P698, DOI 10.1016/S0140-6736(21)01208-3
   FAO, 2023, Food balance sheets 2010-2021: global, regional and country trends, DOI [10.4060/cc8088-n, DOI 10.4060/CC8088-N]
   Fernandez-Guzman D, 2023, LANCET REG HEALTH-AM, V26, DOI 10.1016/j.lana.2023.100602
   Fritz M, 2017, THEOR PRACT URB SUST, P187, DOI 10.1007/978-3-319-56091-5_11
   Garcia CK, 2022, BMJ MED, V1, DOI 10.1136/bmjmed-2022-000239
   GCF, 2020, Increasing health sector's capacities and strengthening coordination on climate action in Argentina at national and subnational levels
   Global Burden of Disease Collaborative Network, 2022, Global Burden of Disease Study 2021 (GBD 2021) Results
   Gonzalez Fernando A. I, 2020, Ecologia Austral, V30, P260, DOI 10.25260/EA.20.30.2.0.1050
   Green Climate Fund, 2023, Project portfolio
   Green Climate Fund, 2023, Country Readiness: GCF's Readiness Programme provides resources for countries to efficiently engage with GCF
   Gruenwald T, 2023, INT J ENV RES PUB HE, V20, DOI 10.3390/ijerph20010075
   Hartinger SM, 2023, LANCET REG HEALTH-AM, V20, DOI 10.1016/j.lana.2023.100470
   Horton R, 2024, LANCET, V403, P1122, DOI 10.1016/S0140-6736(24)00575-0
   IEA, 2023, Latin America Energy Outlook 2023
   International Energy Agency, 2022, World Energy Balances
   International Energy Agency, 2023, World Energy Investment 2023
   International Energy Agency, 2021, Climate impacts on Latin American hydropower
   Internet World Stats, 2022, Facebook world stats and penetration in the world-Facebook statistics
   IQAir, 2023, World's most polluted cities 2023
   Jeswani HK, 2020, P ROY SOC A-MATH PHY, V476, DOI 10.1098/rspa.2020.0351
   Johnson J, 2010, CHEM ENG NEWS, V88, P9
   Kanavos P., 2019, Latin Ame- rica Healthcare System Overview. A Comparative Analysis of Fiscal Space in Heal- thcare
   Kenny GP, 2010, CAN MED ASSOC J, V182, P1053, DOI 10.1503/cmaj.081050
   Kew S, 2023, Strong influence of climate change in uncharacteristic early spring heat in South America, DOI [10.25561/106753, DOI 10.25561/106753]
   Kogel C, 2022, The Impact of Air Pollution on Labour Productivity in France. Documents de Travail du Centre d'Economie de la Sorbonne
   Kovats RS, 2003, LANCET, V362, P1481, DOI 10.1016/S0140-6736(03)14695-8
   León-Sicairos N, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph191610318
   Li Y, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-29601-0
   Lieber R, 2022, GEOPHYS RES LETT, V49, DOI 10.1029/2022GL100553
   Lippert I, 2023, ENERGY RES SOC SCI, V100, DOI 10.1016/j.erss.2023.103087
   Melo O, 2023, Costos asociados a la inaccion frente al cambio climatico en Chile: sintesis
   Ministerio de Salud de Neuquen, 2023, Plan de accion de salud y cambio climcitico de la provincia de Neuquen
   Ministerio de Salud Pitblica de la provincia de Misiones, 2023, Plan de accion de salud y cambio climcitico de la provincia de Misiones
   Ministerio de Salud Pitblica de Tucuman, 2023, Plan provincial de salud y cambio climcitico
   Ministerio de Salud y Desarrollo Social-Argentina, 2019, Clima y Salud en la Argentina: Diagnostico de Situacion 2019
   Mohajeri N, 2023, LANCET PLANET HEALTH, V7, pe660, DOI 10.1016/S2542-5196(23)00133-X
   Moran A., 2013, Evaluacion de los Indicadores de vulnerabilidad social ante el Cambio Climatico en areas urbanas de Guatemala
   Motschmann A, 2020, CLIMATIC CHANGE, V162, P837, DOI 10.1007/s10584-020-02770-x
   NASA Earth Observatory, 2023, Reservoirs run dry in montevideo
   Nix E, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/aca1d2
   NOAA, 2023, NOAA declares the arrival of El Nino
   NU CEPAL, 2023, Social panorama of Latin America and the Caribbean 2023: labour inclusion as a key axis of inclusive social development
   Oboist U, 2019, METHODS ECOL EVOL, V10, P1357, DOI 10.1111/2041-210X.13205
   OCHA, 2023, Chile: floods-jun 2023
   OECD, 2021, How's life in Latin America?: measuring well-being for policy making, DOI [10.1787/2965f4fe-en, DOI 10.1787/2965F4FE-EN]
   Organismo Andino de Salud-Convenio Hipolito Unanue Organizacion Panamericana de la Salud, 2020, Plan andino de salud y cambio climatico 2020-2025
   Organizacion Panamericana de la Salud, 2021, Agenda para las Americas sobre salud. Medioambiente y cambio climcitico
   Organizacion Panamericana de la Salud, El Mercosur aprueba su nueva Estrategia de Salud y Cambio Climatico, con el soporte tecnico de la OPS-OPS/OMS | Organizacion Panamericana de la Salud
   Ortiz-Ospina Esteban, 2023, OUR WORLD DATA
   Ortiz-Prado E, 2023, LANCET REG HEALTH-AM, V27, DOI 10.1016/j.lana.2023.100601
   PAHO, 2023, PAHO/WHO data-dengue
   Palmeiro Y, 2023, Health at a glance: Latin America and the caribbean 2023
   Palmeiro-Silva YK, 2023, LANCET REG HEALTH-AM, V26, DOI 10.1016/j.lana.2023.100605
   Palmeiro-Silva YK, 2023, LANCET REG HEALTH-AM, V26, DOI 10.1016/j.lana.2023.100580
   Palmeiro-Silva YK, 2021, REV SAUDE PUBL, V55, DOI 10.11606/s1518-8787.2021055002891
   Palmeiro-Silva YK, 2021, Revista Panamericana de Salud Publica, V45, P1
   Pan American Health Organization, 2019, Caribbean action plan on health and climate change
   Paz-Soldan VA, 2023, LANCET REG HEALTH-AM, V26, DOI 10.1016/j.lana.2023.100604
   Pérez-Díaz PL, 2022, SMART INNOV SYST TEC, V259, P173, DOI 10.1007/978-981-16-5792-4_18
   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]
   Repitblica de Argentina, 2023, Plan de Accion de los Lineamientos de Politica de Ganaderia Bovina Sostenible-GBS 2023-2050
   Repitblica de Nicaragua, 2022, Decreto de aprobacion de la Politica Nacional de Cambio Climcitico
   Rifai SW, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab402f
   Romanello M, 2023, LANCET, V402, P2346, DOI 10.1016/S0140-6736(23)01859-7
   Romero-Alvarez D, 2017, REV CHIL INFECTOL, V34, P289, DOI 10.4067/S0716-10182017000300015
   Roundtable on Environmental Health Sciences R, 2014, NEXUS BIOFUELS CLIMA
   Sarmiento JH, 2023, LANCET REG HEALTH-AM, V26, DOI 10.1016/j.lana.2023.100606
   Springmann M, 2018, LANCET PLANET HEALTH, V2, pE451, DOI [10.1016/S2542-5196(18)30206-7, 10.1016/s2542-5196(18)30206-7]
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Swiss Re Institute, 2023, Sigma explorer
   Takahashi B, 2023, LANCET REG HEALTH-AM, V26, DOI 10.1016/j.lana.2023.100603
   The International Charter Space and Major Disasters, 2023, Flooding in Chile-activations-international disasters charter
   The International Charter Space and Major Disasters, Extratropical cyclone in southern Brazil-activations-international disasters charter
   The Sustainability Consortium World Resources Institute University of Maryland, 2023, Tree Cover Loss by Driver
   The World Bank, 2022, Urban population (% of total population)
   Toreti A, 2023, Drought in Central America and Mexico: august 2023: GDO analytical report, DOI [10.2760/00589, DOI 10.2760/00589]
   Tremblay JC, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2102463118
   UNFCCC, 2023, 1 GLOBAL STOCKTAKE O
   Warburton DER, 2017, CURR OPIN CARDIOL, V32, P541, DOI 10.1097/HCO.0000000000000437
   WHO, 2009, WHO TECH REP SER, V958, P1
   WHO, 2023, Alliance for transformative action on climate and health
   WHO/UNICEF, 2023, WHO/UNICEF joint monitoring programme for water supply. Sanitation and Hygiene (JMP)
   World Health Organization, 2023, Infodemic management
   World Health Organization, 2023, Electronic IHR states parties selfassessment annual reporting tool
   World Health Organization, 2023, Proportion of population with primary reliance on polluting fuels and technologies for cooking (%)
   World Health Organization, 2022, Ambient (Outdoor) Air Pollution
   World Health Organization, 2023, Population with primary reliance on polluting fuels and technologies for cooking
   World Health Organization, 2021, WHO HLTH CLIM CHANG
   World Health Organization (WHO), 2021, Particulate Matter (PM 2.5 and PM 10), Ozone, Nitrogen Dioxide, Sulfur Dioxide and Carbon Monoxide
   World Meteorological Organization, 2023, State of the climate in Latin America and the Caribbean
   Xu RB, 2020, NEW ENGL J MED, V383, P2173, DOI 10.1056/NEJMsr2028985
   Yalew SG, 2020, NAT ENERGY, V5, P794, DOI 10.1038/s41560-020-0664-z
   Yglesias-González M, 2023, PLOS ONE, V18, DOI 10.1371/journal.pone.0290767
   ,, 2023, The state of food security and nutrition in the world 2023: urbanization, agrifood systems transformation and healthy diets across the rural-urban continuum, DOI 10.4060/cc3017en
NR 117
TC 11
Z9 11
U1 42
U2 43
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2667-193X
J9 LANCET REG HEALTH-AM
JI Lancet Regional Health-Americas
PD MAY
PY 2024
VL 33
AR 100746
DI 10.1016/j.lana.2024.100746
EA MAY 2024
PG 35
WC Health Care Sciences & Services; Public, Environmental & Occupational
   Health
WE Emerging Sources Citation Index (ESCI)
SC Health Care Sciences & Services; Public, Environmental & Occupational
   Health
GA UC9T6
UT WOS:001245987200001
PM 38800647
OA Green Published, gold, Green Accepted
DA 2025-01-10
ER

PT J
AU Klein, T
AF Klein, Tuvaal
TI Degrees of exclusion: The politics of heat adaptation in
   Palestine-Israel, 1950-1980
SO ENVIRONMENT AND PLANNING E-NATURE AND SPACE
LA English
DT Article; Early Access
DE Climate adaptation; colonialism; environmental history; indigenous
   knowledge; politics of knowledge
ID BEDOUIN; SCIENCE
AB This article investigates the development of Israeli heat adaptation research from 1950 to 1980 and its role in advancing Israeli nation-building and settler-colonial policies. Focusing on the scientific career of the Zionist military doctor Ezra Sohar, renowned for reforming the Israeli Defence Forces' "water discipline," the article traces the emergence of Israeli thermal physiological research. It reveals the shift from the view that certain races were better adapted to specific climates to a "universalized" notion of acclimatization as a physiological process possible to anyone. The universal notion of acclimatization created new forms of exclusion, as the indigenous Arab-Palestinian population, particularly Bedouins, lost their perceived racial advantage in heat adaptation; Jewish-Israeli thermal physiologists argued that Jews were better adapted to heat due to cultural factors. Finally, the article follows Sohar's advocacy for air conditioning, which he promoted as the "ideal solution" for establishing a Western, "developed" Israeli society. Thus, the article demonstrates how the rise of air conditioning during this period further reinforced the exclusion and marginalization of Bedouin communities. It illustrates how planetary dynamics of climate injustice and colonialist policies manifest locally and highlights heat exposure as a form of colonial violence. Sohar's story provides insight into a scientific community driven by the ambition to conquer heat, reflecting a political logic that, to this day, leaves neither past heat adaptation practices nor air conditioning as possible solutions for Bedouin communities coping with a rapidly warming planet.
C1 [Klein, Tuvaal] Tel Aviv Univ, IL-6997801 Tel Aviv, Israel.
C3 Tel Aviv University
RP Klein, T (corresponding author), Tel Aviv Univ, IL-6997801 Tel Aviv, Israel.
EM tuvaal.klein@gmail.com
CR Aderet O., 2014, Ha'aretz
   Aleksandrowicz O, 2017, ARCHIT SCI REV, V60, P371, DOI 10.1080/00038628.2017.1354812
   Algazi G., 2023, Hityashvut vehitnagdut beisrael/falastin Settlement and Resistence in Israel/Palestine, P164
   Algazi G, 2024, J PALESTINE STUD, V53, P7, DOI 10.1080/0377919X.2024.2327951
   Almog Oz., 2000, SABRA CREATION NEW J
   Anderson CW, 2017, J PALESTINE STUD, V47, P39, DOI 10.1525/jps.2017.47.1.39
   Anderson Warwick., 2008, Colonial Pathologies: American Tropical Medicine, Race, and Hygiene in the Philippines
   Barak O., 2024, Heat: A History
   Barakat Nora Elizabeth., 2023, Bedouin Bureaucrats: Mobility and Property in the Ottoman Empire
   Basile S.:., 2014, Cool: How Air Conditioning Changed Everything
   Braverman I., 2023, SETTLING NATURE CONS
   Cohen N., 2024, New under the sun: Early Zionist encounters with the climate in Palestine
   Cooper G., 1998, AIR CONDITIONING AM
   Davis DK, 2005, GEOFORUM, V36, P509, DOI 10.1016/j.geoforum.2004.08.003
   Dopaz L., 2023, Findings from the Household Expenditure 2019-2021
   Efron N, 2011, ZYGON, V46, P413, DOI 10.1111/j.1467-9744.2010.01192.x
   Epstein Y., 2011, Harefua Hatzvait, V8, P65
   Epstein Y, 2006, IND HEALTH, V44, P388, DOI 10.2486/indhealth.44.388
   FALAH G, 1985, J PALESTINE STUD, V14, P35, DOI 10.1525/jps.1985.14.2.00p0126b
   Grossman Sara J., 2023, Immeasurable Weather: Meteorological Data and Settler Colonialism from 1820 to Hurricane Sandy
   Günel G, 2018, INT J MIDDLE E STUD, V50, P573, DOI 10.1017/S0020743818000570
   Hamstead ZA, 2023, PLAN THEORY PRACT, V24, P153, DOI 10.1080/14649357.2023.2201604
   Helman Anat., 2003, J ISR HIST, V22, P71
   Hirsch D, 2023, JEWISH SOC STUD, V28, P23, DOI 10.2979/jewisocistud.28.1.02
   Hirsch D, 2009, INT J MIDDLE E STUD, V41, P577, DOI 10.1017/S0020743809990079
   Horowitz M., 2022, Thermal Physiology: A Worldwide History
   Hsu HL, 2023, AM LIT HIST, V35, P769, DOI 10.1093/alh/ajad001
   Israel Central Bureau of Statistics, Israel's population since the establishment of the state and until today
   Israel Electric Corporation, Historical landmarks-Israel Electric Corporation
   Israeli Meteorological Service, 2022, Omes hahom vemekadem i-hanohut heat stress and the Discomfort Index
   Kabha M, 2003, MIDDLE EASTERN STUD, V39, P169, DOI 10.1080/00263200412331301727
   Koheji M., 2024, Middle East Report, V311
   Latour Bruno, 2007, REASSEMBLING SOCIAL, DOI DOI 10.1017/CBO9781107415324.004
   LIVINGSTONE DN, 1987, HIST SCI, V25, P359, DOI 10.1177/007327538702500402
   Meiton Fredrik., 2019, ELECT PALESTINE CAPI
   Meloni Maurizio., 2016, POLITICAL BIOL SCI S
   Mercer H, 2023, WIRES CLIM CHANGE, V14, DOI 10.1002/wcc.851
   Mitchell T., 2002, Rule of experts: Egypt, technopolitics, modernity
   Musat RP., 2023, Complex Social Systems in Dynamic Environments. Lecture Notes in Networks and Systems, P297
   Nasasra M, 2020, MIDDLE EASTERN STUD, V56, P64, DOI 10.1080/00263206.2019.1651719
   Nash L, 2006, INESCAPABLE ECOLOGIES: A HISTORY OF ENVIRONMENT, DISEASE, AND KNOWLEDGE, P1
   Neumann B, 2011, SCHUST SER ISR STUD, P1
   Norris Jacob., 2013, LAND PROGR PALESTINE
   Novick Tamar, 2023, Milk and Honey: Technologies of Plenty in the Making of the Holy Land
   Penslar DerekJ., 1991, Zionism and Technocracy: The Engineering of Jewish Settlement in Palestine, 1870-1918
   Pickering Andrew., 2010, The Mangle of Practice: Time, Agency, and Science, DOI 10.7208/chicago/9780226668253.001.0001
   Pinhas S., 2020, Journal of Levantine Studies, V10, P111
   Rabinbach Anson., 1990, The Human Motor: Energy, Fatigue, and the Origins of Modernity
   Randalls S, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.466
   Randazzo T, 2020, ECON MODEL, V90, P273, DOI 10.1016/j.econmod.2020.05.001
   Reardon J, 2005, IN-FORMATION, P1
   Roghanchi P, 2018, SAF HEALTH WORK-KR, V9, P10, DOI 10.1016/j.shaw.2017.04.002
   Seidler S., 2014, Ha'aretz
   Seikaly Sherene., 2016, Men of Capital: Scarcity and Economy in Mandate Palestine, DOI DOI 10.1515/9780804796729
   Senor D., 2009, START UP NATION STOR
   Shaalan H., 2022, Ynet
   Starosielski N, 2021, Element, P1
   Veracini L, 2019, INTERVENTIONS-UK, V21, P568, DOI 10.1080/1369801X.2018.1547213
   Veracini L, 2013, J PALESTINE STUD, V42, P26, DOI 10.1525/jps.2013.42.2.26
   Weitzman E., 2015, Saf hamidbar, qav haimut The Conflict Shoreline
   Wishnitzer Avner., 2015, READING CLOCKS TURCA
   Zerubavel Y, 2008, SOC RES, V75, P315
NR 62
TC 0
Z9 0
U1 2
U2 2
PU SAGE PUBLICATIONS INC
PI THOUSAND OAKS
PA 2455 TELLER RD, THOUSAND OAKS, CA 91320 USA
SN 2514-8486
EI 2514-8494
J9 ENVIRON PLAN E-NAT
JI Environ. Plan. E-Nat. Space
PD 2024 OCT 21
PY 2024
DI 10.1177/25148486241289755
EA OCT 2024
PG 21
WC Environmental Studies; Geography
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geography
GA J8T5H
UT WOS:001339731400001
DA 2025-01-10
ER

PT J
AU Wang, ZJ
   Zhang, WC
   Zhou, YY
   Zhang, QY
   Kulkarni, KP
   Melmaiee, K
   Tian, YW
   Dong, M
   Gao, ZX
   Su, YN
   Yu, H
   Xu, GH
   Li, YD
   He, H
   Liu, QK
   Sun, HY
AF Wang, Zejia
   Zhang, Wanchen
   Zhou, Yangyan
   Zhang, Qiyan
   Kulkarni, Krishnanand P.
   Melmaiee, Kalpalatha
   Tian, Youwen
   Dong, Mei
   Gao, Zhaoxu
   Su, Yanning
   Yu, Hong
   Xu, Guohui
   Li, Yadong
   He, Hang
   Liu, Qikun
   Sun, Haiyue
TI Genetic and epigenetic signatures for improved breeding of cultivated
   blueberry
SO HORTICULTURE RESEARCH
LA English
DT Article
ID READ ALIGNMENT; GENOME; METHYLATION; RESOURCES; SEQUENCE; FORMAT; MODEL;
   TOOL
AB Blueberry belongs to the Vaccinium genus and is a highly popular fruit crop with significant economic importance. It was not until the early twentieth century that they began to be domesticated through extensive interspecific hybridization. Here, we collected 220 Vaccinium accessions from various geographical locations, including 154 from the United States, 14 from China, eight from Australia, and 29 from Europe and other countries, comprising 164 Vaccinium corymbosum, 15 Vaccinium ashei, 10 lowbush blueberries, seven half-high blueberries, and others. We present the whole-genome variation map of 220 accessions and reconstructed the hundred-year molecular history of interspecific hybridization of blueberry. We focused on the two major blueberry subgroups, the northern highbush blueberry (NHB) and southern highbush blueberry (SHB) and identified candidate genes that contribute to their distinct traits in climate adaptability and fruit quality. Our analysis unveiled the role of gene introgression from Vaccinium darrowii and V. ashei into SHB in driving the differentiation between SHB and NHB, potentially facilitating SHB's adaptation to subtropical environments. Assisted by genome-wide association studies, our analysis suggested VcTBL44 as a pivotal gene regulator governing fruit firmness in SHB. Additionally, we conducted whole-genome bisulfite sequencing on nine NHB and 12 SHB cultivars, and characterized regions that are differentially methylated between the two subgroups. In particular, we discovered that the beta-alanine metabolic pathway genes were enriched for DNA methylation changes. Our study provides high-quality genetic and epigenetic variation maps for blueberry, which offer valuable insights and resources for future blueberry breeding.
C1 [Wang, Zejia; Zhou, Yangyan; Zhang, Qiyan; Gao, Zhaoxu; Su, Yanning; He, Hang; Liu, Qikun] Peking Univ, Sch Adv Agr Sci, State Key Lab Prot & Plant Gene Res, 5 Yiheyuan Rd, Beijing 100871, Peoples R China.
   [Zhang, Wanchen; Tian, Youwen; Dong, Mei; Li, Yadong; Sun, Haiyue] Jilin Agr Univ, Coll Hort, Jilin Prov Lab Crop Germplasm Resources, 2888 Xincheng St, Changchun 130118, Peoples R China.
   [Kulkarni, Krishnanand P.; Melmaiee, Kalpalatha] Delaware State Univ, Dept Agr & Nat Resources, Dover, DE 19901 USA.
   [Yu, Hong] Jiangsu Prov & Chinese Acad Sci, Inst Bot, Nanjing 210014, Peoples R China.
   [Xu, Guohui] Dalian Univ, Coll Life & Hlth, Dalian 116622, Peoples R China.
C3 Peking University; Jilin Agricultural University; Delaware State
   University; Institute of Botany, Jiangsu Province & Chinese Academy of
   Sciences; Dalian University
RP He, H; Liu, QK (corresponding author), Peking Univ, Sch Adv Agr Sci, State Key Lab Prot & Plant Gene Res, 5 Yiheyuan Rd, Beijing 100871, Peoples R China.; Sun, HY (corresponding author), Jilin Agr Univ, Coll Hort, Jilin Prov Lab Crop Germplasm Resources, 2888 Xincheng St, Changchun 130118, Peoples R China.
EM 2101112264@stu.pku.edu.cn; wanchenzhang@foxmail.com;
   yangyan_zhou@pku.edu.cn; qiyanzhang@pku.edu.cn; kkulkarni@desu.edu;
   kmelmaiee@desu.edu; tianyouwen5219@163.com; dongmei4790@163.com;
   gaozx@pku.edu.cn; 2101112263@stu.pku.edu.cn; njyuhong@vip.sina.com;
   xugh520@163.com; blueberryli@163.com; hehang@pku.edu.cn;
   qikunliu@pku.edu.cn; haiyue-sun@hotmail.com
RI Cheng, Zhenzhou/G-2393-2014; Kulkarni, Krishnanand/AAA-5746-2021
OI Melmaiee, Kalpalatha/0000-0001-5310-9200; /0000-0002-0032-2662; Su,
   Yanning/0009-0005-5156-373X
FU State Key Laboratory of Protein and Plant Gene Research; Project of
   Science and Technology Development of Jilin Province, China
   [20220508099RC]; Project of Development and Reform Commission of Jilin
   Province, China [2023C035-4]; School of Advanced Agricultural Sciences
   at Peking University
FX This work was supported by funds from the State Key Laboratory of
   Protein and Plant Gene Research, the Project of Science and Technology
   Development of Jilin Province, China (20220508099RC), the Project of
   Development and Reform Commission of Jilin Province, China (2023C035-4)
   and startup funds from the School of Advanced Agricultural Sciences at
   Peking University. We express our gratitude for the computational
   resources provided by the High-performance Computing Platform of Peking
   University. We are grateful to Dr Massimo Iorizzo at North Carolina
   State University for his generous help with curating the classification
   of blueberry accessions. Additionally, we extend our thanks to Xiaowen
   Wang, Yilin Zhang, Han Zhou, Yi Liu, and Minghan Huang for their
   valuable discussion and input on data analysis. We are also thankful to
   Xinyue Lu, Xuanzhi Cheng, and Cuimei Zhang for their technical support.
CR Alexander DH, 2009, GENOME RES, V19, P1655, DOI 10.1101/gr.094052.109
   ALTSCHUL SF, 1990, J MOL BIOL, V215, P403, DOI 10.1006/jmbi.1990.9999
   Ballington JR, 2009, ACTA HORTIC, V810, P49, DOI 10.17660/ActaHortic.2009.810.2
   Ballington JR, 2001, HORTSCIENCE, V36, P213, DOI 10.21273/HORTSCI.36.2.213
   Basak I, 2014, J BIOL CHEM, V289, P14458, DOI 10.1074/jbc.M114.548156
   Berka M, 2022, J EXP BOT, V73, P1894, DOI 10.1093/jxb/erab549
   Blaker KM, 2014, J SCI FOOD AGR, V94, P2785, DOI 10.1002/jsfa.6626
   Campa A, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0206361
   Capella-Gutiérrez S, 2009, BIOINFORMATICS, V25, P1972, DOI 10.1093/bioinformatics/btp348
   Cappai F, 2018, AGRONOMY-BASEL, V8, DOI 10.3390/agronomy8090174
   Chen CJ, 2020, MOL PLANT, V13, P1194, DOI 10.1016/j.molp.2020.06.009
   Chen SF, 2018, BIOINFORMATICS, V34, P884, DOI 10.1093/bioinformatics/bty560
   Cingolani P, 2012, FLY, V6, P80, DOI 10.4161/fly.19695
   Colle M, 2019, GIGASCIENCE, V8, DOI 10.1093/gigascience/giz012
   Cui FQ, 2022, PLANT COMMUN, V3, DOI 10.1016/j.xplc.2022.100307
   Danecek P, 2021, GIGASCIENCE, V10, DOI 10.1093/gigascience/giab008
   Danecek P, 2011, BIOINFORMATICS, V27, P2156, DOI 10.1093/bioinformatics/btr330
   Faria A, 2010, PHYTOTHER RES, V24, P1862, DOI 10.1002/ptr.3213
   Faust GG, 2012, BIOINFORMATICS, V28, P2417, DOI 10.1093/bioinformatics/bts456
   Ferrao LFV, 2020, NEW PHYTOL, V226, P1725, DOI 10.1111/nph.16459
   Ferrao LFV, 2018, FRONT ECOL EVOL, V6, DOI 10.3389/fevo.2018.00107
   Forney CF., 2022, Foods, V11
   Fouad WM, 2009, TRANSGENIC RES, V18, P707, DOI 10.1007/s11248-009-9258-z
   Guo H, 2023, SCI CHINA LIFE SCI, V66, P1888, DOI 10.1007/s11427-022-2299-5
   Guo WL, 2018, BIOINFORMATICS, V34, P381, DOI 10.1093/bioinformatics/btx595
   Guo WL, 2013, BMC GENOMICS, V14, DOI 10.1186/1471-2164-14-774
   Huang BW, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-27117-7
   Jühling F, 2016, GENOME RES, V26, P256, DOI 10.1101/gr.196394.115
   Kalt W, 2020, ADV NUTR, V11, P224, DOI 10.1093/advances/nmz065
   Kang HM, 2010, NAT GENET, V42, P348, DOI 10.1038/ng.548
   Kaplan F, 2004, PLANT PHYSIOL, V136, P4159, DOI 10.1104/pp.104.052142
   Kim D, 2019, NAT BIOTECHNOL, V37, P907, DOI 10.1038/s41587-019-0201-4
   Koboldt DC, 2009, BIOINFORMATICS, V25, P2283, DOI 10.1093/bioinformatics/btp373
   Krishna P, 2003, J PLANT GROWTH REGUL, V22, P289, DOI 10.1007/s00344-003-0058-z
   Krzhizhanovskaya VV., 2020, Easing multiscale model design and coupling with MUSCLE 3
   Kulkarni KP, 2021, INT J MOL SCI, V22, DOI 10.3390/ijms22010163
   Kumar P, 2009, NAT PROTOC, V4, P1073, DOI 10.1038/nprot.2009.86
   Lang ZB, 2017, P NATL ACAD SCI USA, V114, pE4511, DOI 10.1073/pnas.1705233114
   Langmead B, 2012, NAT METHODS, V9, P357, DOI [10.1038/NMETH.1923, 10.1038/nmeth.1923]
   Law JA, 2010, NAT REV GENET, V11, P204, DOI 10.1038/nrg2719
   Letunic I, 2021, NUCLEIC ACIDS RES, V49, pW293, DOI 10.1093/nar/gkab301
   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]
   Li NY, 2022, GENOME BIOL, V23, DOI 10.1186/s13059-022-02756-1
   Liang ZC, 2019, NAT COMMUN, V10, DOI [10.1038/s41467-019-09135-8, 10.1038/s41467-019-13255-6]
   Liao Y, 2019, NUCLEIC ACIDS RES, V47, DOI 10.1093/nar/gkz114
   Lobos GA, 2015, FRONT PLANT SCI, V6, DOI 10.3389/fpls.2015.00782
   Love MI, 2014, GENOME BIOL, V15, DOI 10.1186/s13059-014-0550-8
   Ma ZY, 2018, NAT GENET, V50, P803, DOI 10.1038/s41588-018-0119-7
   Manzanero BR, 2023, BMC PLANT BIOL, V23, DOI 10.1186/s12870-023-04124-y
   Martin SH, 2015, MOL BIOL EVOL, V32, P244, DOI 10.1093/molbev/msu269
   Minh BQ, 2020, MOL BIOL EVOL, V37, P1530, DOI 10.1093/molbev/msaa015
   MURRAY MG, 1980, NUCLEIC ACIDS RES, V8, P4321, DOI 10.1093/nar/8.19.4321
   Nishiyama S, 2021, HEREDITY, V126, P194, DOI 10.1038/s41437-020-00362-0
   Ou SJ, 2019, GENOME BIOL, V20, DOI 10.1186/s13059-019-1905-y
   Planas-Riverola A, 2019, DEVELOPMENT, V146, DOI 10.1242/dev.151894
   Price MN, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0009490
   Purcell S, 2007, AM J HUM GENET, V81, P559, DOI 10.1086/519795
   Quinlan AR, 2010, BIOINFORMATICS, V26, P841, DOI 10.1093/bioinformatics/btq033
   Retamales JB, 2012, CROP PROD SCI HORTIC, P1, DOI 10.1079/9781845939045.0000
   Rivera S, 2021, DATA BRIEF, V38, DOI 10.1016/j.dib.2021.107313
   Shen C, 2020, MOL PLANT, V13, P1250, DOI 10.1016/j.molp.2020.07.003
   Shen YT, 2018, GENOME BIOL, V19, DOI 10.1186/s13059-018-1516-z
   Shi YN, 2022, J INTEGR PLANT BIOL, V64, P1649, DOI 10.1111/jipb.13316
   Song QX, 2017, GENOME BIOL, V18, DOI 10.1186/s13059-017-1229-8
   Stacklies W, 2007, BIOINFORMATICS, V23, P1164, DOI 10.1093/bioinformatics/btm069
   Stuart T, 2016, ELIFE, V5, DOI 10.7554/eLife.20777
   Tian T, 2023, NAT GENET, V55, P496, DOI 10.1038/s41588-023-01297-y
   Wang LL, 2022, PLANT PHYSIOL, V188, P1189, DOI 10.1093/plphys/kiab531
   Weiss CL, 2018, BMC BIOINFORMATICS, V19, DOI 10.1186/s12859-018-2128-z
   Wu TZ, 2021, INNOVATION-AMSTERDAM, V2, DOI 10.1016/j.xinn.2021.100141
   Yan HD, 2020, BIOINFORMATICS, V36, P4269, DOI 10.1093/bioinformatics/btaa519
   Yang L., 2022, Fruit Res, V2, P1
   Yocca AE, 2023, HORTIC RES-ENGLAND, V10, DOI 10.1093/hr/uhad202
   Yu JL, 2021, HORTIC RES-ENGLAND, V8, DOI 10.1038/s41438-021-00641-9
   Zhang JS, 2018, NAT GENET, V50, P1565, DOI 10.1038/s41588-018-0237-2
   Zhao GW, 2019, NAT GENET, V51, P1607, DOI 10.1038/s41588-019-0522-8
NR 77
TC 1
Z9 1
U1 20
U2 20
PU OXFORD UNIV PRESS INC
PI CARY
PA JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA
SN 2662-6810
EI 2052-7276
J9 HORTIC RES-ENGLAND
JI Hortic. Res.-England
PD JUL 1
PY 2024
VL 11
IS 7
AR uhae138
DI 10.1093/hr/uhae138
EA JUL 2024
PG 16
WC Plant Sciences; Genetics & Heredity; Horticulture
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences; Genetics & Heredity; Agriculture
GA YS9A5
UT WOS:001270582600008
PM 38988623
OA gold
DA 2025-01-10
ER

PT J
AU Kangas, R
   Ayers-Rigsby, S
   Savarese, M
   Paramygin, V
   Sheng, YP
AF Kangas, Rachael
   Ayers-Rigsby, Sara
   Savarese, Michael
   Paramygin, Vladimir
   Sheng, Y. Peter
TI Assessing Vulnerability and Prioritization of Cultural Assets for
   Climate Change Planning in Collier County, Southwest Florida
SO SUSTAINABILITY
LA English
DT Article
DE climate change; resiliency planning; archaeology; site prioritization;
   sea level rise mapping; vulnerability analysis; sea level rise; cultural
   resources; adaptation planning; Geo Tool
ID ARCHAEOLOGICAL SITES; COASTAL INUNDATION; HERITAGE; RESOURCES; RISK
AB Cultural resources are often overlooked in climate change and resiliency planning, despite them being integral to community identity and the restoration of a sense of normalcy after significant weather events. This vulnerability assessment demonstrates how cultural resources can be included in planning efforts, and how they can be prioritized based on specific criteria. To complete this assessment, a working group with local land managers and cultural resource professionals was formed, and members employed a sophisticated Geo Tool, ACUNE (Adaptation of Coastal Urban and Natural Ecosystems) for climate adaptation, to predict how cultural resources throughout Collier County, Florida, would be impacted in two specific climate scenarios. The working group selected ten significant sites in the county and used ACUNE to prioritize action at these sites, using a matrix of hazard exposure, sensitivity, adaptive capacity, and the environmental, social, and economic consequences of the loss of these sites. Based on the results of our case study vulnerability assessment of cultural resources in Collier County, the next decade (2020 to 2030) has the potential to increase the number of sites at risk of storm flooding from 267 to 318, alerting managers that immediate action is needed for the sites of greatest value. The analysis of 10 case study sites is presented to demonstrate an approach for land managers and other cultural resource professionals to prioritize action at their own sites.
C1 [Kangas, Rachael] Univ S Florida, Florida Publ Archaeol Network, Tampa, FL 33612 USA.
   [Ayers-Rigsby, Sara] Florida Atlantic Univ, Florida Publ Archaeol Network, Boca Raton, FL 33431 USA.
   [Savarese, Michael] Florida Gulf Coast Univ, Dept Marine & Earth Sci, Ft Myers, FL 33965 USA.
   [Paramygin, Vladimir; Sheng, Y. Peter] Univ Florida, Engn Sch Sustainable Infrastruct & Environm, Gainesville, FL 32603 USA.
C3 State University System of Florida; University of South Florida; State
   University System of Florida; Florida Atlantic University; State
   University System of Florida; Florida Gulf Coast University; State
   University System of Florida; University of Florida
RP Kangas, R (corresponding author), Univ S Florida, Florida Publ Archaeol Network, Tampa, FL 33612 USA.
EM kangasr@usf.edu; pva@ufl.edu; ypsheng@ufl.edu
RI Paramygin, Vladimir/N-9759-2014
OI Paramygin, Vladimir/0000-0002-5171-2089; Ayers-Rigsby,
   Sara/0000-0001-6757-3135; Sheng, Peter/0000-0001-8827-1451; Kangas,
   Rachael/0009-0009-8055-1251
FU NOAA; Florida Department of Environmental Protection
FX We would like to acknowledge Chip Birdsong, FPAN, all members of the
   ACUNE interest and working groups, including Austin Bell of the Marco
   Island Historical Society, Steve Bertone of Rookery Bay National
   Estuarine Research Reserve, Jeff Carter of Rookery Bay National
   Estuarine Research Reserve, Alison Elgart of Florida Gulf Coast
   University, Bill Locascio of Florida Gulf Coast University, Victoria
   Menchaca of Big Cypress National Preserve, William Stanton of the
   Florida Department of Environmental Protection, and Craig Woodward
   resident of Marco Island and Everglades City, among others, Collier
   County NAACP, Coalition of Immokalee Workers, Seminole Tribe of Florida.
CR AECOM, 2020, City of Naples Climate Change Vulnerability Assessment
   [Anonymous], 2007, City Time
   [Anonymous], 2017, Regional Climate Change Compact: Regional Climate Action Plan 2.0
   [Anonymous], 2012, Regional Climate Action Plan
   [Anonymous], 2018, Florida Adaptation Planning Guidebook Florida Coastal Management Program
   [Anonymous], 2011, Recommendation on the Historic Urban Landscape, including a glossary of definitions
   [Anonymous], 2022, Regional Climate Change Compact: Regional Climate Action Plan 3.0 Recommendations
   [Anonymous], Archaeological Resources Protection Act of 1979
   Ayers-Rigsby S, 2023, HIST ARCHAEOL, V57, P619, DOI 10.1007/s41636-023-00418-y
   Bolt MR, 2019, ECOL RESTOR, V37, P171, DOI 10.3368/er.37.3.171
   Bronin S.C., 2023, HIST CULT PRES ROUND
   Buffington KJ, 2021, PLOS ONE, V16, DOI 10.1371/journal.pone.0256707
   CASSAR M., 2005, CLIMATE CHANGE HIST
   Collier County Cultural Resources Vulnerability Assessment, 2022, Using the ACUNE Decision Support Tool.
   colliercountyfl, Collier County Population and Demographics
   Cook I, 2021, J ISL COAST ARCHAEOL, V16, P553, DOI 10.1080/15564894.2019.1605430
   Daly C, 2014, CONSERV MANAGE ARCHA, V16, P268, DOI 10.1179/1350503315Z.00000000086
   Dawson T, 2020, P NATL ACAD SCI USA, V117, P8280, DOI 10.1073/pnas.1912246117
   dos fl, Florida Master Site File
   Fatoric S, 2017, CLIMATIC CHANGE, V142, P227, DOI 10.1007/s10584-017-1929-9
   Fitzpatrick SM, 2015, J ISL COAST ARCHAEOL, V10, P3, DOI 10.1080/15564894.2015.1013647
   Florida Department of State: Florida Division of Historical Resources, 2021, Abandoned African-American Cemeteries Task Force.
   Florida Division of Historic Resources, 2004, Archaeological Stabilization Guide: Case Studies in Protecting Archaeological Sites
   Hale JC, 2021, QUATERNARY SCI REV, V258, DOI 10.1016/j.quascirev.2021.106867
   Hall CM, 2016, J HERIT TOUR, V11, P10, DOI 10.1080/1743873X.2015.1082573
   Halligan JJ, 2016, SCI ADV, V2, DOI 10.1126/sciadv.1600375
   Hambrecht G, 2017, AM ANTIQUITY, V82, P627, DOI 10.1017/aaq.2017.30
   Harkin D., 2019, A Guide to Climate Change Impacts on Scotlands Historic Environment
   Holmes TJ, 2021, J ENVIRON PLANN MAN, V64, P2214, DOI 10.1080/09640568.2020.1865885
   International Criminal Court Office of the Prosecutor, 2021, Policy on Cultural Heritage
   International Institute for Environment and Development, 2023, Living in the Shadow of Loss and Damage: Uncovering Non-Economic Impacts
   Kangas R., 2023, AAP
   Miller SE, 2018, CONSERV MANAGE ARCHA, V20, P234, DOI 10.1080/13505033.2018.1516455
   Nash CL, 2018, CONSERV MANAGE ARCHA, V20, P285, DOI 10.1080/13505033.2018.1558392
   National Park Service,, Natural Resource Report
   Newsom B, 2023, ADV ARCHAEOL PRACT, V11, P302, DOI 10.1017/aap.2023.14
   Nickerson C., 2020, Public. Purp. J, V17, P69
   noaa, NOAA Shoreline Mileage of the United States
   Orr SA, 2021, HIST ENVIRON POLICY, V12, P434, DOI 10.1080/17567505.2021.1957264
   Paulson M.M., 2022, Climate Change and Human Responses, P111
   Ramieri E., 2011, Methods for assessing coastal vulnerability to climate change
   Reeder-Myers LA, 2015, J ISL COAST ARCHAEOL, V10, P436, DOI 10.1080/15564894.2015.1008074
   Rick TC, 2020, P NATL ACAD SCI USA, V117, P8250, DOI 10.1073/pnas.2003612117
   Rockman M, 2020, P NATL ACAD SCI USA, V117, P8295, DOI 10.1073/pnas.1914213117
   Rockman Marcy., 2012, ARCHAEOLOGY SOC ITS, P193, DOI DOI 10.1007/978-1-4419-9881-1_14
   Sesana E, 2021, WIRES CLIM CHANGE, V12, DOI 10.1002/wcc.710
   Sheng P., 2021, Assessing the Role of Natural and Nature-Based Features (NNBF) for Reducing Flood, Wave, and Property Damage during Storms in a Changing Climate
   Sheng P., 2017, Report on a Cooperative Agreement with NOAA NCCOS started on June 1st, 2017: An Overview of the Project
   Sheng Y.P., 2023, Overview: ACUNE and ACUNE+ Projects funded by NOAA/NCCOS focusing on Collier County, Florida
   Sheng Y.P., 2022, Environmental Research Letters, V17, P044055, DOI DOI 10.1088/1748-9326/AC50D1
   Sheng YP, 2022, SCI REP-UK, V12, DOI 10.1038/s41598-022-07010-z
   Sheng YP, 2017, HYDROBIOLOGIA, V803, P87, DOI 10.1007/s10750-017-3201-8
   southeastfloridaclimatecompact, Southeast Florida Regional Climate Change Compact
   State of California Native American Heritage Commission, Understanding Cultural Resources.
   Sweet W. V., 2017, NOSCOOPS083 NOAA
   Tampa Bay Regional Resiliency Coalition, About us
   The Norwegian Directorate for Cultural Heritage, 2021, Climate Strategy for Cultural Environment Management 20212030
   UNESCO, 2019, Climate Change and the Loss of Cultural Heritage
   United States Postal Service, Postal Facts: Smallest Post Office.
   Westley K, 2023, J ISL COAST ARCHAEOL, V18, P251, DOI 10.1080/15564894.2021.1955778
   Yang K, 2019, NAT HAZARDS, V99, P1105, DOI 10.1007/s11069-019-03807-w
NR 61
TC 0
Z9 0
U1 4
U2 5
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD JUN
PY 2024
VL 16
IS 11
AR 4741
DI 10.3390/su16114741
PG 27
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 UG5T6
UT WOS:001246925500001
OA gold
DA 2025-01-10
ER

PT J
AU Zhou, H
   Tao, FL
   Chen, Y
   Yin, LC
   Wang, YC
   Li, YB
   Zhang, S
AF Zhou, Hong
   Tao, Fulu
   Chen, Yi
   Yin, Lichang
   Wang, Yicheng
   Li, Yibo
   Zhang, Shuai
TI Climate change reduces agricultural total factor productivity in major
   agricultural production areas of China even with continuously increasing
   agricultural inputs
SO AGRICULTURAL AND FOREST METEOROLOGY
LA English
DT Article
DE Agricultural inputs; Agricultural outputs; Agricultural production
   efficiency; Climate change impact
ID HEAT-STRESS; CROP YIELDS; TEMPERATURE; IMPACTS; GROWTH; WHEAT; SCENARIO;
   TRENDS
AB Agricultural total factor productivity (ATFP) is a crucial measure that determines the aggregate agricultural output per unit of aggregate input. ATFP is sensitive to climate change; however, the impacts of climate change on ATFP have rarely been investigated despite its significance. In this study, we employ the Malmquist index methods to calculate the ATFP from 1981 to 2019 based on detailed census data at the prefecture level across China. Furthermore, we project the ATFP in the period of 2020-2060 under the Societal Development Pathway (SSP) 1-2.6 and SSP3-7.0. The results showed that, during 1981-2019, the ATFP of China increased significantly, ranging from 0.74 to 38.95. The joint changes in temperature and precipitation benefited ATFP growth in some prefectures in northwestern, northeastern and southern China but reduced it in the Huang -Huai -Hai Region. During 2031-2060, ATFP is projected to be more positively affected by climate change in northern China than in southern China. Some regions such as the Northwest Arid Region, most of the Northeast China and Southwest China Region will benefit from climate change. However, some major agricultural production areas including the Huang -Huai -Hai Region and southeast China are expected to be negatively affected by climate change. Our findings highlight the need to consider the impacts of climate change on ATFP when developing climate adaptation strategies in agriculture.
C1 [Zhou, Hong; Tao, Fulu; Chen, Yi; Yin, Lichang; Wang, Yicheng; Li, Yibo; Zhang, Shuai] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China.
   [Zhou, Hong; Tao, Fulu; Chen, Yi; Yin, Lichang; Wang, Yicheng; Li, Yibo; Zhang, Shuai] Univ Chinese Acad Sci, Coll Resources & Environm, 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 Tao, FL (corresponding author), Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China.; Tao, FL (corresponding author), Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China.
EM taofl@igsnrr.ac.cn
RI Yin, Lichang/AAS-4914-2020; Li, Yongqing/KRO-3098-2024
OI Tao, F/0000-0001-8574-0080; Li, Yibo/0000-0002-7965-0406
FU National Natural Science Founda- tion of China [42061144003, 41977405];
   CAS- CSIRO Joint Project
FX <BOLD>Acknowledgements</BOLD> This study was supported by the National
   Natural Science Founda- tion of China (Project Nos. 42061144003,
   41977405) and the CAS- CSIRO Joint Project.
CR Alvarez IC, 2020, J STAT SOFTW, V95, DOI 10.18637/jss.v095.i03
   Bai HZ, 2022, FRONT PLANT SCI, V13, DOI 10.3389/fpls.2022.829580
   Boote KJ, 2018, EUR J AGRON, V100, P99, DOI 10.1016/j.eja.2017.09.002
   Butler EE, 2013, NAT CLIM CHANGE, V3, P68, DOI [10.1038/NCLIMATE1585, 10.1038/nclimate1585]
   Chancellor W, 2021, FOOD POLICY, V102, DOI 10.1016/j.foodpol.2021.102091
   Chen S, 2021, J DEV ECON, V148, DOI 10.1016/j.jdeveco.2020.102557
   Chen Y, 2018, EARTH SYST DYNAM, V9, P543, DOI 10.5194/esd-9-543-2018
   Coelli, 2005, An introduction to efficiency and productivity analysis.
   Coelli TJ, 2005, AGR ECON-BLACKWELL, V32, P115, DOI 10.1111/j.0169-5150.2004.00018.x
   Coomes OT, 2019, NAT SUSTAIN, V2, P22, DOI 10.1038/s41893-018-0200-3
   Fuglie K.O., 2013, Glob. J. Emerg. Market Econ., V5, P23
   Fuglie KO, 2018, GLOB FOOD SECUR-AGR, V17, P73, DOI 10.1016/j.gfs.2018.05.001
   Han HB, 2018, ENVIRON SCI POLLUT R, V25, P32096, DOI 10.1007/s11356-018-3142-4
   He J, 2020, SCI DATA, V7, DOI 10.1038/s41597-020-0369-y
   Kryszak L, 2023, INT J EMERG MARK, V18, P148, DOI 10.1108/IJOEM-04-2020-0428
   Lachaud MA, 2017, CLIMATIC CHANGE, V143, P445, DOI 10.1007/s10584-017-2013-1
   Lange S., 2020, ISIMIP3B BIAS ADJUST
   Lange S., 2020, ISIMIP3BASD (2.4.1).
   Lange S, 2019, GEOSCI MODEL DEV, V12, P3055, DOI 10.5194/gmd-12-3055-2019
   Liang XZ, 2017, P NATL ACAD SCI USA, V114, pE2285, DOI 10.1073/pnas.1615922114
   Liu B, 2016, AGR FOREST METEOROL, V222, P45, DOI 10.1016/j.agrformet.2016.03.006
   Lobell DB, 2007, ENVIRON RES LETT, V2, DOI 10.1088/1748-9326/2/1/014002
   Lobell DB, 2008, SCIENCE, V319, P607, DOI 10.1126/science.1152339
   Lobell DB, 2011, SCIENCE, V333, P616, DOI [10.1126/science.1206376, 10.1126/science.1204531]
   Lu J, 2021, J GEOPHYS RES-BIOGEO, V126, DOI 10.1029/2021JG006327
   Masson-Delmotte V., 2021, Climate Change 2021: The Physical Science Basis, P41
   Moore F, 2020, arXiv
   O'Neill BC, 2016, GEOSCI MODEL DEV, V9, P3461, DOI 10.5194/gmd-9-3461-2016
   Ogundari K, 2021, ENVIRON SCI POLLUT R, V28, P30035, DOI 10.1007/s11356-021-12684-5
   Ortiz-Bobea A, 2021, NAT CLIM CHANGE, V11, P306, DOI 10.1038/s41558-021-01000-1
   Pongratz J, 2012, NAT CLIM CHANGE, V2, P101, DOI [10.1038/NCLIMATE1373, 10.1038/nclimate1373]
   Ray DK, 2012, NAT COMMUN, V3, DOI 10.1038/ncomms2296
   Rezaei EE, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-23101-2
   Sheng Y, 2020, AUST J AGR RESOUR EC, V64, P82, DOI 10.1111/1467-8489.12327
   Skendzic S, 2021, INSECTS, V12, DOI 10.3390/insects12050440
   Tao FL, 2022, AGR FOREST METEOROL, V316, DOI 10.1016/j.agrformet.2022.108865
   Tao FL, 2015, EUR J AGRON, V71, P44, DOI 10.1016/j.eja.2015.08.003
   Tao FL, 2012, CLIM RES, V54, P233, DOI 10.3354/cr01131
   Tao FL, 2012, EUR J AGRON, V43, P201, DOI 10.1016/j.eja.2012.07.005
   Tao J, 2018, INT J CLIMATOL, V38, P2029, DOI 10.1002/joc.5314
   Van Beveren I, 2012, J ECON SURV, V26, P98, DOI 10.1111/j.1467-6419.2010.00631.x
   Wheeler T, 2013, SCIENCE, V341, P508, DOI 10.1126/science.1239402
   Xiao DP, 2021, FRONT EARTH SC-SWITZ, V9, DOI 10.3389/feart.2021.811621
   Xiao DengPan Xiao DengPan, 2012, Zhongguo Shengtai Nongye Xuebao / Chinese Journal of Eco-Agriculture, V20, P1539, DOI 10.3724/SP.J.1011.2012.01539
   [许尔琪 Xu E Q], 2021, [全球变化数据学报, Journal of Global Change Data & Discovery], V5, P19
   Yang XG, 2015, AGR FOREST METEOROL, V208, P76, DOI 10.1016/j.agrformet.2015.04.024
   [云雅如 Yin Yaru], 2005, [自然资源学报, Journal of Natural Resources], V20, P697
   Zhang Y., 2008, Self-incompatibility in flowering plants; evolution, diversity and mechanisms, P3
   Zhang Y, 2006, GEOPHYS RES LETT, V33, DOI 10.1029/2006GL027229
NR 49
TC 5
Z9 5
U1 18
U2 32
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 15
PY 2024
VL 349
AR 109953
DI 10.1016/j.agrformet.2024.109953
EA MAR 2024
PG 8
WC Agronomy; Forestry; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Forestry; Meteorology & Atmospheric Sciences
GA OQ6G3
UT WOS:001208772900001
DA 2025-01-10
ER

PT J
AU Dong, J
   Schwartz, Y
   Korolija, I
   Mumovic, D
AF Dong, J.
   Schwartz, Y.
   Korolija, I.
   Mumovic, D.
TI Unintended consequences of English school stock energy-efficient
   retrofit on cognitive performance of children under climate change
SO BUILDING AND ENVIRONMENT
LA English
DT Article
DE Building stock; School children; Cognitive performance; Climate change;
   Retrofitting; Meta -analysis
ID CLASSROOM VENTILATION RATES; ADAPTATION MEASURES; UK; BUILDINGS;
   QUALITY; TEMPERATURE; CONSUMPTION
AB School building stock retrofit forms a key part of UK's commitment to net-zero carbon target by 2050. However, with a changing climate, the retrofit of school buildings may have unintended consequences on classroom thermal environments and cognitive performance of children in non-heating seasons. This paper aims to quantify the impact of school stock retrofit in accordance with increasingly tightening energy efficiency regulatory requirements on cognitive performance of English children, while also exploring the potential adaptation measures under climate change. The results indicate that English schools that undergo envelope insulation exhibit higher Cognitive Performance Loss (CPL) of children compared to their original conditions. Passive climate adaptation measures, especially increased daytime ventilation rate was found to be an effective strategy for mitigating the impact of climate change on cognitive performance. However, the benefits of passive measures will diminish as the climate warms, while air conditioning will be required to maintain cognitive performance loss at relatively low levels. In addition to the reduction of heating load, envelope insulation can provide benefits for English schools in cooler climatic regions from both cognitive performance and energy point of view. The study calls for the CPL to be added as one of the key performance indicators when considering the long-term impact of climate change on schools. This would enable policy makers and relevant stakeholders to make more holistic decisions regarding school stock retrofit while ensuring that classrooms are conducive to learning.
C1 [Dong, J.; Schwartz, Y.; Korolija, I.; Mumovic, D.] UCL, UCL Inst Environm Design & Engn, Cent House,14 Upper Woburn Pl, London WC1H 0NN, England.
C3 University of London; University College London
RP Dong, J (corresponding author), UCL, UCL Inst Environm Design & Engn, Cent House,14 Upper Woburn Pl, London WC1H 0NN, England.
EM ucbqjdo@ucl.ac.uk
RI Korolija, Ivan/KIA-3955-2024
OI Korolija, Ivan/0000-0003-3153-6070; Schwartz, Yair/0000-0002-3526-2137;
   Mumovic, Dejan/0000-0002-4914-9004
CR Akkose G, 2021, J BUILD ENG, V40, DOI 10.1016/j.jobe.2021.102294
   AlFaris F, 2016, J CLEAN PROD, V135, P794, DOI 10.1016/j.jclepro.2016.06.172
   [Anonymous], 2023, Helping Schools Get the Most Out of Heat Pumps
   [Anonymous], 2022, EnergyPlus energy simulation software v. 8.9
   Attia S, 2021, ENERG BUILDINGS, V239, DOI 10.1016/j.enbuild.2021.110869
   B.B. DfE,, 2018, Guidelines on Ventilation, Thermal Comfort, and Indoor Air Quality in Schools, P101
   Bakó-Biró Z, 2012, BUILD ENVIRON, V48, P215, DOI 10.1016/j.buildenv.2011.08.018
   Baniassadi A, 2018, BUILD ENVIRON, V132, P263, DOI 10.1016/j.buildenv.2018.01.037
   Birol F, 2018, The Future of Cooling: Opportunities for Energy-Efficient Air Conditioning, P526
   BRAC, 1965, Building and Buildings, The Building Regulations 1965
   BRAC, 1976, Building and Buildings, The Building Regulations 1976
   Brogger M, 2018, RENEW SUST ENERG REV, V82, P1489, DOI 10.1016/j.rser.2017.05.239
   Bull Jamie., 2014, International Journal of Sustainable Built Environment, V3, P1, DOI DOI 10.1016/J.IJSBE.2014.07.002
   Burman E, 2018, FRONT BUILT ENVIRON, V4, DOI 10.3389/fbuil.2018.00022
   Carratt A, 2020, J CLEAN PROD, V263, DOI 10.1016/j.jclepro.2020.121408
   Chen DD, 2023, BUILD ENVIRON, V245, DOI 10.1016/j.buildenv.2023.110967
   CIBSE, 2015, Integrated school design
   CIBSE, 2008, TM46 EN BENCHM
   CIBSE, 2010, CIBSE UK Weather Data Sets
   Csobod E., 2014, SINPHONIE - Schools Indoor Pollution Health Observatory Network in Europe
   Dascalaki EG, 2011, ENERG BUILDINGS, V43, P718, DOI 10.1016/j.enbuild.2010.11.017
   de Santoli L, 2014, ENERG BUILDINGS, V68, P196, DOI 10.1016/j.enbuild.2013.08.028
   Dimoudi A, 2013, ADV BUILD ENERGY RES, V7, P20, DOI 10.1080/17512549.2012.740904
   Dong J, 2023, BUILD SERV ENG RES T, V44, P333, DOI 10.1177/01436244231163084
   Dong J, 2023, BUILD ENVIRON, V243, DOI 10.1016/j.buildenv.2023.110607
   EFA, 2014, Property Data Survey Programme: Survey Manual Part 1 Overview and Methodology
   Fisk WJ, 2015, BUILD ENVIRON, V86, P70, DOI 10.1016/j.buildenv.2014.12.024
   Grassie D, 2022, BUILD CITIES, V3, P204, DOI 10.5334/bc.159
   Gupta R, 2021, ENERG BUILDINGS, V252, DOI 10.1016/j.enbuild.2021.111418
   Gupta R, 2015, BUILD SERV ENG RES T, V36, P196, DOI 10.1177/0143624414566242
   Haverinen-Shaughnessy U, 2011, INDOOR AIR, V21, P121, DOI 10.1111/j.1600-0668.2010.00686.x
   Haverinen-Shaughnessy U, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0136165
   Heracleous C, 2021, J BUILD ENG, V44, DOI 10.1016/j.jobe.2021.103358
   Herrera M, 2017, BUILD SERV ENG RES T, V38, P602, DOI 10.1177/0143624417705937
   HM Government, 2022, Approved Document L2B: Conservation of Fuel and Power in New Buildings Other than Dwellings
   HM Government Brac, 2016, Approved Document L2B: Conservation of Fuel and Power in New Buildings Other than Dwellings, 2013 edition with 2016 amendments
   Homaei S, 2021, BUILD ENVIRON, V201, DOI 10.1016/j.buildenv.2021.108022
   Jenkins DP, 2009, BUILD ENVIRON, V44, P490, DOI 10.1016/j.buildenv.2008.04.012
   Kavgic M, 2010, BUILD ENVIRON, V45, P1683, DOI 10.1016/j.buildenv.2010.01.021
   Kolokotsa D, 2019, ADV BUILD ENERGY RES, V13, P193, DOI 10.1080/17512549.2018.1488612
   Korsavi SS, 2020, ENERG BUILDINGS, V214, DOI 10.1016/j.enbuild.2020.109857
   Kükrer E, 2021, J BUILD ENG, V44, DOI 10.1016/j.jobe.2021.102697
   Lan L, 2022, INDOOR AIR, V32, DOI 10.1111/ina.12916
   Li DHW, 2012, ENERGY, V42, P103, DOI 10.1016/j.energy.2012.03.044
   Li H, 2021, J BUILD PERFORM SIMU, V14, P814, DOI 10.1080/19401493.2021.1876771
   Li WL, 2017, ENERGY, V141, P2445, DOI 10.1016/j.energy.2017.11.071
   Mendell MJ, 2016, INDOOR AIR, V26, P546, DOI 10.1111/ina.12241
   Met Office, 2022, UK Climate Projections: Headline Findings
   Moazzen N, 2020, APPL ENERG, V268, DOI 10.1016/j.apenergy.2020.115046
   Mohamed S, 2021, J BUILD ENG, V43, DOI 10.1016/j.jobe.2021.103141
   Mohamed S, 2021, ENERG BUILDINGS, V250, DOI 10.1016/j.enbuild.2021.111291
   Montazami A, 2015, RENEW SUST ENERG REV, V46, P249, DOI 10.1016/j.rser.2015.02.012
   Mylona A, 2012, BUILD SERV ENG RES T, V33, P51, DOI 10.1177/0143624411428951
   NCM, 2016, National Calculation Methodology (NCM) Modelling Guide (For Buildings Other than Dwellings in England)
   Ortiz M, 2020, ENERG BUILDINGS, V221, DOI 10.1016/j.enbuild.2020.110102
   Pereira LD, 2014, RENEW SUST ENERG REV, V40, P911, DOI 10.1016/j.rser.2014.08.010
   Porras-Salazar JA, 2021, BUILD ENVIRON, V203, DOI 10.1016/j.buildenv.2021.108037
   Porras-Salazar JA, 2018, INDOOR AIR, V28, P892, DOI 10.1111/ina.12501
   Porritt SM, 2012, ENERG BUILDINGS, V55, P16, DOI 10.1016/j.enbuild.2012.01.043
   Rawat M., 2022, Energy and Built Environment, V3, P327, DOI [10.1016/j.enbenv.2021.03.001, DOI 10.1016/J.ENBENV.2021.03.001]
   Schwartz Y, 2021, ENERG BUILDINGS, V249, DOI 10.1016/j.enbuild.2021.111249
   Schwartz Y, 2022, ENERG BUILDINGS, V254, DOI 10.1016/j.enbuild.2021.111566
   Shi YQ, 2021, FRONT PSYCHOL, V12, DOI 10.3389/fpsyg.2021.774548
   Shrubsole C, 2019, INDOOR BUILT ENVIRON, V28, P100, DOI 10.1177/1420326X17753513
   Shrubsole C, 2014, INDOOR BUILT ENVIRON, V23, P340, DOI 10.1177/1420326X14524586
   Singh MK, 2019, ENERG BUILDINGS, V188, P149, DOI 10.1016/j.enbuild.2019.01.051
   Siu CY, 2023, BUILD ENVIRON, V234, DOI 10.1016/j.buildenv.2023.110124
   Smith GC, 2013, BUILD SERV ENG RES T, V34, P55, DOI 10.1177/0143624412468761
   Sun KY, 2020, BUILD ENVIRON, V177, DOI 10.1016/j.buildenv.2020.106842
   Tahsildoost M, 2015, ENERG BUILDINGS, V104, P65, DOI 10.1016/j.enbuild.2015.06.079
   Tällberg R, 2019, SOL ENERG MAT SOL C, V200, DOI 10.1016/j.solmat.2019.02.041
   UK Parliament, 2019, The Climate Change Act 2008 (2050 Target Amendment) Order 2019
   van Hooff T, 2016, ENERGY, V94, P811, DOI 10.1016/j.energy.2015.11.036
   van Hooff T, 2014, BUILD ENVIRON, V82, P300, DOI 10.1016/j.buildenv.2014.08.027
   Vilia PN, 2017, FRONT PSYCHOL, V8, DOI 10.3389/fpsyg.2017.01064
   Wang C, 2021, BUILD ENVIRON, V193, DOI 10.1016/j.buildenv.2021.107647
   Wargocki P, 2020, BUILD ENVIRON, V173, DOI 10.1016/j.buildenv.2020.106749
   Wargocki P, 2019, BUILD ENVIRON, V157, P197, DOI 10.1016/j.buildenv.2019.04.046
   Wargocki P, 2017, BUILD ENVIRON, V112, P359, DOI 10.1016/j.buildenv.2016.11.020
   Wargocki P, 2013, BUILD ENVIRON, V59, P581, DOI 10.1016/j.buildenv.2012.10.007
   Yeganeh AJ, 2018, BUILD ENVIRON, V143, P701, DOI 10.1016/j.buildenv.2018.07.002
NR 81
TC 1
Z9 1
U1 5
U2 7
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 FEB 1
PY 2024
VL 249
AR 111107
DI 10.1016/j.buildenv.2023.111107
EA DEC 2023
PG 14
WC Construction & Building Technology; Engineering, Environmental;
   Engineering, Civil
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Construction & Building Technology; Engineering
GA GB8C5
UT WOS:001150280000001
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Munschek, M
   Witt, R
   Kaltofen, K
   Segar, J
   Wirth, C
   Weigelt, A
   Engelmann, RA
   Staude, IR
AF Munschek, Marius
   Witt, Reinhard
   Kaltofen, Katrin
   Segar, Josiane
   Wirth, Christian
   Weigelt, Alexandra
   Engelmann, Rolf A.
   Staude, Ingmar R.
TI Putting conservation gardening into practice
SO SCIENTIFIC REPORTS
LA English
DT Article
ID PLANT DISPERSAL; BIODIVERSITY; EXTINCTION; MANAGEMENT; RICHNESS
AB Conservation gardening (CG) represents a socio-ecological approach to address the decline of native plant species and transform the gardening industry into an innovative conservation tool. However, essential information regarding amenable plants, their ecological requirements for gardening, and commercial availability remains limited and not readily available. In this study, we present a workflow using Germany as a case study to bridge this knowledge gap. We synthesized the Red Lists of all 16 federal states in Germany, and text-mined a comprehensive platform for garden plants, as well as multiple German producers of native plants. To provide accessible information, we developed a user-friendly app (https://conservation-gardening.shinyapps.io/app-en/) that offers region-specific lists of CG plants, along with practical guidance for planting and purchasing. Our findings reveal that a median of 845 plant species are red-listed across federal states (ranging from 515 to 1123), with 41% of these species amenable to gardening (ranging from 29 to 53%), resulting in a total of 988 CG species. Notably, 66% of these species (650) are already available for purchase. Additionally, we observed that many CG plants exhibit drought tolerance and require less fertilizer on average, with implications for long-term urban planning and climate adaptation. Collaborating with gardening experts, we present a selection of purchasable CG balcony plants for each federal state, highlighting the feasibility of CG even for individuals without gardens. With a multitude of declining plants amenable to gardening and the vital role of gardens as refuges and green corridors, CG holds substantial potential to catalyze transformative change in bending the curve of biodiversity loss.
C1 [Munschek, Marius; Wirth, Christian; Weigelt, Alexandra; Engelmann, Rolf A.; Staude, Ingmar R.] Univ Leipzig, Inst Biol, Leipzig, Germany.
   [Witt, Reinhard; Kaltofen, Katrin] Nat Gartenplaner, Regensburg, Germany.
   [Segar, Josiane; Wirth, Christian; Weigelt, Alexandra; Staude, Ingmar R.] German Ctr Integrat Biodivers Res iDiv, Leipzig, Germany.
   [Wirth, Christian; Engelmann, Rolf A.] Univ Leipzig, Bot Garden, Leipzig, Germany.
C3 Leipzig University; Leipzig University
RP Staude, IR (corresponding author), Univ Leipzig, Inst Biol, Leipzig, Germany.; Staude, IR (corresponding author), German Ctr Integrat Biodivers Res iDiv, Leipzig, Germany.
EM ingmar.staude@uni-leipzig.de
RI Wirth, Christian/A-4446-2016; Staude, Ingmar/AGF-6702-2022; Weigelt,
   Alexandra/JCN-8278-2023
OI Weigelt, Alexandra/0000-0001-6242-603X; Staude,
   Ingmar/0000-0003-2306-8780; Munschek, Marius/0000-0002-2115-5293;
   Engelmann, Rolf A./0000-0003-0262-5410
FU Projekt DEAL
FX Open Access funding enabled and organized by Projekt DEAL.
CR Auffret AG, 2011, APPL VEG SCI, V14, P291, DOI 10.1111/j.1654-109X.2011.01124.x
   Baldock KCR, 2019, NAT ECOL EVOL, V3, P363, DOI 10.1038/s41559-018-0769-y
   Berthon K, 2021, LANDSCAPE URBAN PLAN, V205, DOI 10.1016/j.landurbplan.2020.103959
   Biesmeijer JC, 2006, SCIENCE, V313, P351, DOI 10.1126/science.1127863
   Bongaarts J, 2019, POPUL DEV REV, V45, P680, DOI 10.1111/padr.12283
   Bullock JM, 2020, J VEG SCI, V31, P943, DOI 10.1111/jvs.12888
   Bullock JM, 2018, TRENDS ECOL EVOL, V33, P958, DOI 10.1016/j.tree.2018.09.008
   Bundesamt fur Naturschutz (BfN), 2019, Nature Awareness Study
   Cazalis V, 2023, FRONT ECOL ENVIRON, V21, P85, DOI 10.1002/fee.2540
   Dewaelheyns V, 2013, LANDSCAPE URBAN PLAN, V116, P25, DOI 10.1016/j.landurbplan.2013.03.010
   Frankie Gordon, 2019, Journal of Pollination Ecology, V25, P16
   Goddard MA, 2013, ECOL ECON, V86, P258, DOI 10.1016/j.ecolecon.2012.07.016
   Griffiths-Lee J, 2022, J INSECT CONSERV, V26, P299, DOI 10.1007/s10841-022-00387-2
   Hari V, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-68872-9
   Hodkinson DJ, 1997, J APPL ECOL, V34, P1484, DOI 10.2307/2405264
   Holz H, 2022, PLANTS PEOPLE PLANET, V4, P303, DOI 10.1002/ppp3.10251
   Huhta AP, 2007, NORD J BOT, V25, P372, DOI 10.1111/j.0107-055X.2008.00131.x
   Ignatieva M, 2013, J ARCHIT URBAN, V37, P1, DOI 10.3846/20297955.2013.786284
   Ismail SA, 2021, CONSERV LETT, V14, DOI 10.1111/conl.12825
   Kirchner F, 2003, CONSERV BIOL, V17, P401, DOI 10.1046/j.1523-1739.2003.01392.x
   Ladouceur E, 2018, CONSERV LETT, V11, DOI 10.1111/conl.12381
   Lindemann-Matthies P, 2013, BIOL CONSERV, V159, P37, DOI 10.1016/j.biocon.2012.12.011
   Lughadha EN, 2020, PLANTS PEOPLE PLANET, V2, P389, DOI 10.1002/ppp3.10146
   Mace GM, 2018, NAT SUSTAIN, V1, P448, DOI 10.1038/s41893-018-0130-0
   Majewska AA, 2020, CONSERV BIOL, V34, P15, DOI 10.1111/cobi.13271
   Maunder Mike, 1998, Curtis's Botanical Magazine, V15, P124, DOI 10.1111/1467-8748.00152
   McCarthy DP, 2012, SCIENCE, V338, P946, DOI 10.1126/science.1229803
   Metzing D., 2018, ROTE LISTE GEFAHRDET
   Millard JW, 2021, CONSERV BIOL, V35, P472, DOI 10.1111/cobi.13701
   Mumaw L, 2017, J ENVIRON PSYCHOL, V52, P92, DOI 10.1016/j.jenvp.2017.05.003
   Pearse WD, 2018, ECOSPHERE, V9, DOI 10.1002/ecs2.2105
   Preisinger H., 2000, Berichte des Botanischen Vereins zu Hamburg
   Reichard SH, 2001, BIOSCIENCE, V51, P103, DOI 10.1641/0006-3568(2001)051[0103:HAAPOI]2.0.CO;2
   Rolim RG, 2022, ACTA BOT BRAS, V36, DOI 10.1590/0102-33062021abb0155
   Rudd H, 2002, RESTOR ECOL, V10, P368, DOI 10.1046/j.1526-100X.2002.02041.x
   Segar J, 2022, NAT SUSTAIN, V5, P649, DOI 10.1038/s41893-022-00882-z
   Shaw A. E., 2016, APPL ENV ED COMMUNIC, V15, P214, DOI 10.1080/1533015X.2016.1181014
   Smith RM, 2006, BIOL CONSERV, V129, P312, DOI 10.1016/j.biocon.2005.10.045
   Soga M, 2022, NAT SUSTAIN, V5, P374, DOI 10.1038/s41893-021-00818-z
   Soga M, 2016, FRONT ECOL ENVIRON, V14, P94, DOI 10.1002/fee.1225
   Statistisches Bundesamt, 2022, Bodenflache insgesamt nach Nutzungsarten in Deutschland
   Staude IR, 2023, RESTOR ECOL, V31, DOI 10.1111/rec.13931
   Staude IR, 2022, ECOL LETT, V25, P466, DOI 10.1111/ele.13937
   Tew NE, 2022, J APPL ECOL, V59, P801, DOI 10.1111/1365-2664.14094
   Venter O, 2016, NAT COMMUN, V7, DOI 10.1038/ncomms12558
   Wang X, 2022, BUILD ENVIRON, V217, DOI 10.1016/j.buildenv.2022.109082
   Watson JEM, 2014, NATURE, V515, P67, DOI 10.1038/nature13947
   Witt R., 1994, Pflege
   Witt R., 2013, Planung, Pflanzen, Tiere, Menschen, Pflege
   Wohlfahrt G, 2019, NAT ECOL EVOL, V3, P1668, DOI 10.1038/s41559-019-1017-9
   World Bank, 2022, Statista
   Zehnsdorf A, 2019, WATER-SUI, V11, DOI 10.3390/w11091845
NR 52
TC 3
Z9 3
U1 2
U2 10
PU NATURE PORTFOLIO
PI BERLIN
PA HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY
SN 2045-2322
J9 SCI REP-UK
JI Sci Rep
PD AUG 31
PY 2023
VL 13
IS 1
AR 12671
DI 10.1038/s41598-023-39432-8
PG 11
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA Q8GM9
UT WOS:001059852100012
PM 37652902
OA Green Published, Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Chieppa, J
   Feller, IC
   Harris, K
   Dorrance, S
   Sturchio, MA
   Gray, E
   Tjoelker, MG
   Aspinwall, MJ
AF Chieppa, Jeff
   Feller, Ilka C.
   Harris, Kylie
   Dorrance, Susannah
   Sturchio, Matthew A.
   Gray, Eve
   Tjoelker, Mark G.
   Aspinwall, Michael J.
TI Thermal acclimation of leaf respiration is consistent in tropical and
   subtropical populations of two mangrove species
SO JOURNAL OF EXPERIMENTAL BOTANY
LA English
DT Article
DE Climatic adaptation; freeze tolerance; genetic differentiation;
   homeostasis; New World mangroves; respiration
ID ADAPTIVE PHENOTYPIC PLASTICITY; RHIZOPHORA-MANGLE; AVICENNIA-GERMINANS;
   DARK RESPIRATION; PLANT-GROWTH; RED MANGROVE; TEMPERATURE-ACCLIMATION;
   LOCAL ADAPTATION; MOUNTAIN PASSES; ATMOSPHERIC CO2
AB Populations from different climates often show unique growth responses to temperature, reflecting temperature adaptation. Yet, whether populations from different climates differ in physiological temperature acclimation remains unclear. Here, we test whether populations from differing thermal environments exhibit different growth responses to temperature and differences in temperature acclimation of leaf respiration. We grew tropical and subtropical populations of two mangrove species (Avicennia germinans and Rhizophora mangle) under ambient and experimentally warmed conditions in a common garden at the species' northern range limit. We quantified growth and temperature responses of leaf respiration (R) at seven time points over similar to 10 months. Warming increased productivity of tropical populations more than subtropical populations, reflecting a higher temperature optimum for growth. In both species, R measured at 25 degrees C declined as seasonal temperatures increased, demonstrating thermal acclimation. Contrary to our expectations, acclimation of R was consistent across populations and temperature treatments. However, populations differed in adjusting the temperature sensitivity of R (Q(10)) to seasonal temperatures. Following a freeze event, tropical Avicennia showed greater freeze damage than subtropical Avicennia, while both Rhizophora populations appeared equally susceptible. We found evidence of temperature adaptation at the whole-plant scale but little evidence for population differences in thermal acclimation of leaf physiology. Studies that examine potential costs and benefits of thermal acclimation in an evolutionary context may provide new insights into limits of thermal acclimation.
C1 [Chieppa, Jeff; Harris, Kylie; Dorrance, Susannah; Sturchio, Matthew A.; Gray, Eve; Aspinwall, Michael J.] Univ North Florida, Dept Biol, Jacksonville, FL 32224 USA.
   [Chieppa, Jeff; Aspinwall, Michael J.] Auburn Univ, Coll Forestry & Wildlife Sci, Auburn, AL 36849 USA.
   [Feller, Ilka C.] Smithsonian Environm Res Ctr, Edgewater, MD 21037 USA.
   [Tjoelker, Mark G.] Western Sydney Univ, Hawkesbury Inst Environm, Penrith, NSW, Australia.
   [Aspinwall, Michael J.] Format Environm LLC, 1631 Alhambra Blvd,Suite 220, Sacramento, CA 95816 USA.
C3 State University System of Florida; University of North Florida; Auburn
   University System; Auburn University; Smithsonian Institution;
   Smithsonian Environmental Research Center; Western Sydney University
RP Chieppa, J (corresponding author), Univ North Florida, Dept Biol, Jacksonville, FL 32224 USA.; Chieppa, J (corresponding author), Auburn Univ, Coll Forestry & Wildlife Sci, Auburn, AL 36849 USA.
EM jjchieppa@gmail.com
RI Aspinwall, Michael/ABH-9774-2020; Aspinwall, Michael/M-2083-2014;
   Tjoelker, Mark/M-2413-2016
OI Gray, Eve/0000-0002-3992-5161; Aspinwall, Michael/0000-0003-0199-2972;
   Tjoelker, Mark/0000-0003-4607-5238
FU USDA-NIFA [2019-67013-29161]; University of North Florida; Auburn
   University; Garden Club of America Award in Coastal Wetlands Studies
FX Support for MJA and JC was provided by USDA-NIFA award 2019-67013-29161,
   the University of North Florida, and Auburn University. Additional
   support for MAS was provided by the Garden Club of America Award in
   Coastal Wetlands Studies.
CR Alongi DM, 2014, ANNU REV MAR SCI, V6, P195, DOI 10.1146/annurev-marine-010213-135020
   AMTHOR JS, 1984, PLANT CELL ENVIRON, V7, P561, DOI 10.1111/1365-3040.ep11591833
   Arnold PA, 2019, PHILOS T R SOC B, V374, DOI 10.1098/rstb.2018.0185
   Arnone JA, 1997, ARCTIC ALPINE RES, V29, P122
   Aspinwall MJ, 2021, TREE PHYSIOL, V41, P103, DOI 10.1093/treephys/tpaa107
   Aspinwall MJ, 2019, GLOBAL CHANGE BIOL, V25, P1665, DOI 10.1111/gcb.14590
   Aspinwall MJ, 2017, FUNCT PLANT BIOL, V44, P1075, DOI [10.1071/FP17110, 10.1071/fp17110]
   Aspinwall MJ, 2016, NEW PHYTOL, V212, P354, DOI 10.1111/nph.14035
   Atkin OK, 2005, ADV PHOTO RESPIRAT, V18, P95
   Atkin OK, 2006, GLOBAL CHANGE BIOL, V12, P500, DOI 10.1111/j.1365-2486.2006.01114.x
   Atkin OK, 2000, PLANT CELL ENVIRON, V23, P15, DOI 10.1046/j.1365-3040.2000.00511.x
   Atkin OK, 2003, TRENDS PLANT SCI, V8, P343, DOI 10.1016/S1360-1385(03)00136-5
   Atkin OK, 2015, NEW PHYTOL, V206, P614, DOI 10.1111/nph.13253
   AZCONBIETO J, 1983, PLANT PHYSIOL, V73, P681, DOI 10.1104/pp.73.3.681
   Bokhorst S, 2018, PLANTA, V247, P635, DOI 10.1007/s00425-017-2813-6
   Bolstad PV, 2003, TREE PHYSIOL, V23, P969, DOI 10.1093/treephys/23.14.969
   Bossdorf O, 2008, ECOL LETT, V11, P106, DOI 10.1111/j.1461-0248.2007.01130.x
   Byars SG, 2007, EVOLUTION, V61, P2925, DOI 10.1111/j.1558-5646.2007.00248.x
   Cavanaugh KC, 2015, GLOBAL CHANGE BIOL, V21, P1928, DOI 10.1111/gcb.12843
   Cook-Patton SC, 2015, FUNCT ECOL, V29, P1332, DOI 10.1111/1365-2435.12443
   Crous KY, 2018, GLOBAL CHANGE BIOL, V24, P4626, DOI 10.1111/gcb.14330
   Crous KY, 2011, GLOBAL CHANGE BIOL, V17, P1560, DOI 10.1111/j.1365-2486.2010.02325.x
   Dangremond EM, 2016, ECOL EVOL, V6, P5087, DOI 10.1002/ece3.2270
   de Boeck HJ, 2012, GLOBAL CHANGE BIOL, V18, P2860, DOI 10.1111/j.1365-2486.2012.02734.x
   Devaney John L., 2021, Estuarine, Coastal and Shelf Science, V248, P262, DOI 10.1016/j.ecss.2020.107015
   Dewar RC, 1999, GLOBAL CHANGE BIOL, V5, P615, DOI 10.1046/j.1365-2486.1999.00253.x
   Dodd RS, 2002, MOL ECOL, V11, P1327, DOI 10.1046/j.1365-294X.2002.01525.x
   Donato DC, 2011, NAT GEOSCI, V4, P293, DOI [10.1038/NGEO1123, 10.1038/ngeo1123]
   Drake JE, 2015, GLOBAL CHANGE BIOL, V21, P459, DOI 10.1111/gcb.12729
   Duarte CM, 2017, BIOGEOSCIENCES, V14, P301, DOI 10.5194/bg-14-301-2017
   Duarte CM, 2013, NAT CLIM CHANGE, V3, P961, DOI [10.1038/NCLIMATE1970, 10.1038/nclimate1970]
   Feeley KJ, 2007, ECOL LETT, V10, P461, DOI 10.1111/j.1461-0248.2007.01033.x
   Feng TJ, 2021, J HYDROL, V593, DOI 10.1016/j.jhydrol.2020.125819
   Ghalambor CK, 2007, FUNCT ECOL, V21, P394, DOI 10.1111/j.1365-2435.2007.01283.x
   Ghalambor CK, 2006, INTEGR COMP BIOL, V46, P5, DOI 10.1093/icb/icj003
   Gunderson CA, 2010, GLOBAL CHANGE BIOL, V16, P2272, DOI 10.1111/j.1365-2486.2009.02090.x
   Heskel MA, 2016, P NATL ACAD SCI USA, V113, P3832, DOI 10.1073/pnas.1520282113
   JANZEN DH, 1967, AM NAT, V101, P233, DOI 10.1086/282487
   Kennedy JP, 2020, MOL ECOL, V29, P704, DOI 10.1111/mec.15365
   Kennedy JP, 2017, J BIOGEOGR, V44, P335, DOI 10.1111/jbi.12813
   Kennedy JP, 2016, AM J BOT, V103, P260, DOI 10.3732/ajb.1500183
   Kimball BA., 2020, P 21 INT GRASSL C
   KORNER C, 1988, SYM SOC EXP BIOL, V42, P25
   Kurimoto K, 2004, PLANT CELL ENVIRON, V27, P853, DOI 10.1111/j.1365-3040.2004.01191.x
   Kvaalen H, 2008, NEW PHYTOL, V177, P49, DOI 10.1111/j.1469-8137.2007.02222.x
   Lee TD, 2005, FUNCT ECOL, V19, P640, DOI 10.1111/j.1365-2435.2005.01023.x
   Lin DL, 2010, NEW PHYTOL, V188, P187, DOI 10.1111/j.1469-8137.2010.03347.x
   Lutz MJ, 2007, J GEOPHYS RES-OCEANS, V112, DOI 10.1029/2006JC003706
   MARKLEY JL, 1982, CAN J BOT, V60, P2704, DOI 10.1139/b82-330
   Meir P, 2001, FUNCT ECOL, V15, P378, DOI 10.1046/j.1365-2435.2001.00534.x
   Mimura M, 2010, J EVOLUTION BIOL, V23, P249, DOI 10.1111/j.1420-9101.2009.01910.x
   Molina-Montenegro MA, 2012, BIOL INVASIONS, V14, P21, DOI 10.1007/s10530-011-0055-2
   Norby RJ, 2004, NEW PHYTOL, V162, P281, DOI 10.1111/j.1469-8137.2004.01047.x
   O'Sullivan OS, 2017, GLOBAL CHANGE BIOL, V23, P209, DOI 10.1111/gcb.13477
   O'Sullivan OS, 2013, PLANT CELL ENVIRON, V36, P1268, DOI 10.1111/pce.12057
   Osland MJ, 2020, J ECOL, V108, P654, DOI 10.1111/1365-2745.13285
   Osland MJ, 2019, ESTUAR COAST, V42, P1084, DOI 10.1007/s12237-019-00533-1
   Osland MJ, 2017, ECOLOGY, V98, P125, DOI 10.1002/ecy.1625
   Ow LF, 2010, GLOBAL CHANGE BIOL, V16, P288, DOI 10.1111/j.1365-2486.2009.01892.x
   Pagter M, 2013, PHYSIOL PLANTARUM, V147, P75, DOI 10.1111/j.1399-3054.2012.01650.x
   PENNINGDEVRIES FWT, 1975, ANN BOT-LONDON, V39, P77
   Pickens CN, 2011, ESTUAR COAST, V34, P824, DOI 10.1007/s12237-010-9358-2
   Pil MW, 2011, AM J BOT, V98, P1031, DOI 10.3732/ajb.1000392
   Raats M. M., 1992, Food Quality and Preference, V3, P89, DOI 10.1016/0950-3293(91)90028-D
   Rodríguez-Calcerrada J, 2010, TREE PHYSIOL, V30, P214, DOI 10.1093/treephys/tpp104
   Ross MS, 2009, GLOBAL CHANGE BIOL, V15, P1817, DOI 10.1111/j.1365-2486.2009.01900.x
   Rustad LE, 2001, OECOLOGIA, V126, P543, DOI 10.1007/s004420000544
   RYAN MG, 1991, ECOL APPL, V1, P157, DOI 10.2307/1941808
   Sandoval-Castro E, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0093358
   Silim SN, 2010, PHOTOSYNTH RES, V104, P19, DOI 10.1007/s11120-010-9527-y
   Slot M, 2015, OECOLOGIA, V177, P885, DOI 10.1007/s00442-014-3159-4
   Smith MN, 2020, NAT PLANTS, V6, P1225, DOI 10.1038/s41477-020-00780-2
   Song WM, 2020, ENVIRON RES COMMUN, V2, DOI 10.1088/2515-7620/ab7a77
   Sturchio MA, 2022, GLOBAL CHANGE BIOL, V28, P612, DOI 10.1111/gcb.15938
   Suárez N, 2005, TREES-STRUCT FUNCT, V19, P721, DOI 10.1007/s00468-005-0001-y
   THORNLEY JH, 1970, NATURE, V227, P304, DOI 10.1038/227304b0
   Tjoelker MG, 2009, NEW PHYTOL, V181, P218, DOI 10.1111/j.1469-8137.2008.02624.x
   Tjoelker MG, 2008, GLOBAL CHANGE BIOL, V14, P782, DOI 10.1111/j.1365-2486.2008.01548.x
   Tjoelker MG, 2018, PLANT CELL ENVIRON, V41, P501, DOI 10.1111/pce.13126
   van Kleunen M, 2005, NEW PHYTOL, V166, P49, DOI 10.1111/j.1469-8137.2004.01296.x
   VIA S, 1993, AM NAT, V142, P352, DOI 10.1086/285542
   Wang H, 2020, GLOBAL CHANGE BIOL, V26, P2573, DOI 10.1111/gcb.14980
   Way DA, 2010, TREE PHYSIOL, V30, P669, DOI 10.1093/treephys/tpq015
   Wilson RS, 2002, TRENDS ECOL EVOL, V17, P66, DOI 10.1016/S0169-5347(01)02384-9
   Xiong FSS, 2000, AM J BOT, V87, P700, DOI 10.2307/2656856
   Zhang KQ, 2016, ECOSPHERE, V7, DOI 10.1002/ecs2.1366
   Zhu LL, 2021, NEW PHYTOL, V229, P1312, DOI 10.1111/nph.16929
   Zomlefer WB, 2006, CASTANEA, V71, P239, DOI 10.2179/05-33.1
NR 88
TC 2
Z9 2
U1 4
U2 22
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 MAY 19
PY 2023
VL 74
IS 10
BP 3174
EP 3187
AR 2
DI 10.1093/jxb/erad093
EA APR 2023
PG 14
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA G7QT6
UT WOS:000963152700001
PM 36882067
DA 2025-01-10
ER

PT J
AU Voskamp, I
   Timmermans, W
   Roosenschoon, O
   Kranendonk, R
   van Rooij, S
   van Hattum, T
   Sterk, M
   Pedroli, B
AF Voskamp, Ilse
   Timmermans, Wim
   Roosenschoon, Onno
   Kranendonk, Remco
   van Rooij, Sabine
   van Hattum, Tim
   Sterk, Marjolein
   Pedroli, Bas
TI Long-Term Visioning for Landscape-Based Spatial Planning-Experiences
   from Two Regional Cases in The Netherlands
SO LAND
LA English
DT Article
DE landscape-based planning; normative scenario; landscape vision; climate
   adaptation; circular resource management; land use transition;
   stakeholder engagement; boundary concept
ID URBAN; MANAGEMENT; DESIGN; ECOLOGY; FUTURE; GREEN
AB Normative scenarios for long-term (e.g., 100 years) landscape development can be very inspiring to imagine outside the box landscape futures, without being obliged to define concrete policy objectives for the shorter term. However, it remains challenging to translate such long-term visions into clear transition pathways. We draw upon a landscape-based design approach to local spatial planning to foster a transition to a well-functioning landscape, resilient to various external pressures. Inspired by a national visioning exercise for the Netherlands in 2120, two local case studies at municipal level in the Netherlands are analysed, aiming to identify in what ways the setup of a regional landscape-based design study using future visions can optimise the spatial planning process. Therefore, this comparative case study analysed the cases on the landscape-based approach, the design process, and the future visions formulated. The comparison shows that fostering abiotic differences safeguards sustainable and resilient landscapes; moreover, co-creation relying on representative local actors appears fundamental for shared solutions, while a landscape-based approach guarantees transitions to adaptive and biodiverse landscapes. We conclude that a shared long-term future landscape vision is a crucial source of inspiration to solve today's spatial planning problems. The constellation of the stakeholder group involved and the methodological setup of a visioning process are determinative for the way a long-term vision is suited to informing spatial planning for a sustainable future.
C1 [Voskamp, Ilse; Timmermans, Wim; Roosenschoon, Onno; Kranendonk, Remco; van Rooij, Sabine; van Hattum, Tim; Sterk, Marjolein] Wageningen Univ & Res, Dept Wageningen Environm Res, POB 47, NL-6700 AA Wageningen, Netherlands.
   [Pedroli, Bas] Wageningen Univ, Wageningen Univ & Res, Land Use Planning Grp, POB 47, NL-6700 AA Wageningen, Netherlands.
C3 Wageningen University & Research; Wageningen University & Research
RP Pedroli, B (corresponding author), Wageningen Univ, Wageningen Univ & Res, Land Use Planning Grp, POB 47, NL-6700 AA Wageningen, Netherlands.
EM bas.pedroli@wur.nl
RI Pedroli, Bas/E-1352-2016
OI Pedroli, Bas/0000-0003-3450-447X; Voskamp, Ilse/0000-0001-5828-8682;
   Roosenschoon, Onno/0000-0003-2502-7229; van Rooij,
   Sabine/0000-0001-5436-4780
CR Ahern J, 2013, LANDSCAPE ECOL, V28, P1203, DOI 10.1007/s10980-012-9799-z
   Altes WKK, 2016, PLAN PRACT RES, V31, P420, DOI 10.1080/02697459.2016.1198556
   Arts B, 2017, ANNU REV ENV RESOUR, V42, P439, DOI 10.1146/annurev-environ-102016-060932
   BAKKER T.W.M., 1979, DUINEN DUINVALLEIEN
   Baptist M., 2019, A nature-based future for the Netherlands in 2120. Knowledge Base Program Nature Inclusive Transitions project number KB-36-003-004
   De Jonge H, 2022, GEN POLICY LETT MINI, P15
   EC, 2020, P INFORMAL M MINISTE
   EC/UN-HABITAT, 2016, STATE EUROPEAN CITIE, P216
   Fleming RC, 2021, J EUR ENVIRON PLAN L, V18, P164, DOI 10.1163/18760104-18010010
   Frantzeskaki N, 2019, ENVIRON SCI POLICY, V93, P101, DOI 10.1016/j.envsci.2018.12.033
   Glas P, 2021, SPOOR 2 BRIEFADVIES, P10
   Hegger D, 2020, ENVIRON SCI POLICY, V106, P157, DOI 10.1016/j.envsci.2020.02.002
   Iwaniec DM, 2020, LANDSCAPE URBAN PLAN, V197, DOI 10.1016/j.landurbplan.2020.103744
   Keesstra S, 2022, LAND-BASEL, V11, DOI 10.3390/land11071062
   Kempenaar A, 2021, EUR PLAN STUD, V29, P762, DOI 10.1080/09654313.2020.1781792
   Kempenaar A, 2016, LANDSCAPE URBAN PLAN, V149, P20, DOI 10.1016/j.landurbplan.2016.01.002
   Kuiper JJ, 2022, ECOSYST PEOPLE, V18, P329, DOI 10.1080/26395916.2022.2065360
   Lembi RC, 2020, BIOTA NEOTROP, V20, DOI 10.1590/1676-0611-BN-2019-0904
   Lemmens P., 2017, Techne: Research in Philosophy and Technology, V21, P114, DOI [10.5840/techne2017212/363, DOI 10.5840/TECHNE2017212/363]
   Luederitz C, 2013, LANDSCAPE URBAN PLAN, V118, P40, DOI 10.1016/j.landurbplan.2013.06.002
   Mansur AV, 2022, ENVIRON SCI POLICY, V131, P46, DOI 10.1016/j.envsci.2022.01.013
   Mazzucato M., 2017, Mission-oriented innovation policy
   McPhearson T., 2021, NPJ URBAN SUSTAIN, V1, P5, DOI [10.1038/s42949-021-00017-x, DOI 10.1038/S42949-021-00017-X]
   McPhearson T, 2016, CURR OPIN ENV SUST, V22, P33, DOI 10.1016/j.cosust.2017.04.004
   McPhearson T, 2016, BIOSCIENCE, V66, P198, DOI 10.1093/biosci/biw002
   Mens M, 2021, ENVIRON MODELL SOFTW, V143, DOI 10.1016/j.envsoft.2021.105100
   Milburn LAS, 2003, LANDSCAPE URBAN PLAN, V64, P47, DOI 10.1016/S0169-2046(02)00200-1
   Montanarella L, 2021, LAND USE POLICY, V100, DOI 10.1016/j.landusepol.2020.104950
   Nassauer JI, 2012, LANDSCAPE URBAN PLAN, V106, P221, DOI 10.1016/j.landurbplan.2012.03.014
   Opdam P, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10010220
   Opdam P, 2013, LANDSCAPE ECOL, V28, P1439, DOI 10.1007/s10980-013-9925-6
   Pinto Correia T, 2018, EUROPEAN LANDSCAPES, P286
   Primdahl J, 2018, DEFINING LANDSCAPE DEMOCRACY: A PATH TO SPATIAL JUSTICE, P153
   Raaphorst K, 2019, J LANDSC ARCHIT, V14, P42, DOI 10.1080/18626033.2019.1673569
   Rotmans J., 2010, Transitions to Sustainable Development: New Directions in the Study of Long Term Transformative Change, V1st, P103
   Scott M, 2016, PLAN THEORY PRACT, V17, P267, DOI 10.1080/14649357.2016.1158907
   Senge P., 2004, PRESENCE HUMAN PURPO
   Star SL, 2010, SCI TECHNOL HUM VAL, V35, P601, DOI 10.1177/0162243910377624
   Swart R, 2021, URBAN PLAN, V6, P4, DOI 10.17645/up.v6i4.4360
   Timmermans W., 2015, ROOTED CITY EUROPEAN
   Timmermans W., 2022, STAD 2120 NATUURLIJK
   van Rooij S, 2021, LAND-BASEL, V10, DOI 10.3390/land10010016
   VINK A.P.A., 1975, LAND USE ADV AGR
   Visser S, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11236792
   Wiek A, 2014, SUSTAIN SCI, V9, P497, DOI [10.1007/s11625-013-0208-6, 10.1007/s11625-011-0154-0]
NR 45
TC 0
Z9 0
U1 2
U2 11
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-445X
J9 LAND-BASEL
JI Land
PD JAN
PY 2023
VL 12
IS 1
AR 38
DI 10.3390/land12010038
PG 15
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA 7Y8GR
UT WOS:000915111000001
OA gold
DA 2025-01-10
ER

PT J
AU Clifford, KR
   Travis, WR
AF Clifford, Katherine R.
   Travis, William R.
TI The New (Ab)Normal: Outliers, Everyday Exceptionality, and the Politics
   of Data Management in the Anthropocene
SO ANNALS OF THE AMERICAN ASSOCIATION OF GEOGRAPHERS
LA English
DT Article
DE climate adaptation; data exclusions; environmental change; extreme
   events; rarity
ID CLIMATE-CHANGE; OZONE; WATER; SCIENCE; MODELS; BACK; LONG; ERA
AB The Anthropocene affects how we manage the environment in many ways, perhaps most importantly by undermining how past conditions act as baselines for future expectations. In a period when historical analogues become less meaningful, we need to forge new practices and methods of environmental monitoring and management, including how to categorize, manage, and analyze the deluge of environmental data. In particular, we need practices to detect emerging hazards, changing baselines, and amplified risk. Some current data practices, however, especially the designation and dismissal of outliers, might mislead efforts to better adapt to new environmental conditions. In this article we ask these questions: What are the politics of determining what counts as "abnormal" and is worthy of exclusion in an era of the ever-changing "normal"? What do data exclusions, often in the form of outliers, do to our ability to understand and regulate in the Anthropocene? We identify a recursive process of distortion at play where constructing categories of abnormal-normal allows for the exclusion of "outliers" from data sets, which ultimately produces a false rarity and hides environmental changes. To illustrate this, we draw on a handful of examples in regulatory science and management, including the Exceptional Event Rule of the Clean Air Act, beach erosion models for nourishment projects, and the undetected ozone hole. We conclude with a call for attention to the construction of "normal" and "abnormal" events, systems, data, and natures in the Anthropocene.
C1 [Clifford, Katherine R.; Travis, William R.] Univ Colorado, Western Water Assessment, Inst Res Environm Sci, Boulder, CO 80302 USA.
   [Travis, William R.] Univ Colorado, Dept Geog, Boulder, CO 80309 USA.
C3 University of Colorado System; University of Colorado Boulder;
   University of Colorado System; University of Colorado Boulder
RP Clifford, KR (corresponding author), Univ Colorado, Western Water Assessment, Inst Res Environm Sci, Boulder, CO 80302 USA.
EM katie.clifford@colorado.edu; william.travis@colorado.edu
OI Clifford, Katherine/0000-0002-1385-8765; Travis,
   William/0000-0002-9197-1317
FU Western Water Assessment - U.S. National Oceanic and Atmospheric
   Administration under Climate Program Office [NA10OAR4310214WWA]
FX Parts of this work was supported by the Western Water Assessment, funded
   by the U.S. National Oceanic and Atmospheric Administration under
   Climate Program Office grant #NA10OAR4310214WWA.
CR [Anonymous], 1995, Beach Nourishment and Protection, DOI DOI 10.17226/4984
   Bowker GeoffreyC., 2008, MEMORY PRACTICES SCI
   Bowker Geofrey C, 2000, Classification and its consequences
   Buck HJ, 2015, ANN ASSOC AM GEOGR, V105, P369, DOI 10.1080/00045608.2014.973005
   Canguilhem Georges., 2008, KNOWLEDGE LIFE
   Cantor A, 2016, GEOFORUM, V72, P49, DOI 10.1016/j.geoforum.2016.01.007
   Castree N, 2014, GEOGR COMPASS, V8, P436, DOI 10.1111/gec3.12141
   Clarke AdeleE., 1992, RIGHT TOOLS JOB WORK
   Clifford KR, 2021, SOC NATUR RESOUR, V34, P135, DOI 10.1080/08941920.2020.1780358
   Coleman H., 2019, MASSIVE SCI     0108
   Cronon W, 1995, UNCOMMON GROUND, P69
   Crutzen PJ, 2003, CLIMATIC CHANGE, V61, P251, DOI 10.1023/B:CLIM.0000004708.74871.62
   Davis DK, 2016, HIST SUSTAIN FUTUR, P1
   Desrosieres Alain., 2002, POLITICS LARGE NUMBE
   Dillon L, 2019, ANN AM ASSOC GEOGR, V109, P545, DOI 10.1080/24694452.2018.1511410
   Duvall ChrisS., 2018, The Palgrave Handbook of Critical Physical Geography, P107, DOI DOI 10.1007/978-3-319-71461-56
   Earthquake Engineering Research Institute, 2011, JAP TOH TSYN MARCH 1
   Edwards PN, 2001, POLIT SCI ENVIRONM, P31
   FARMAN JC, 1985, NATURE, V315, P207, DOI 10.1038/315207a0
   Frickel S, 2007, TECHNOL SOC, V29, P181, DOI 10.1016/j.techsoc.2007.01.007
   Frickel S, 2010, SCI TECHNOL HUM VAL, V35, P444, DOI 10.1177/0162243909345836
   Gitelman L, 2013, INFRASTRUCT SER, P1
   Hacking I., 1990, The Taming of Chance
   Haraway D.J., 2016, STAYING TROUBLE MAKI, DOI 10.1215/9780822373780
   Haraway D, 2015, ENVIRON HUMANITIES, V6, P159, DOI 10.1215/22011919-3615934
   Harden CP, 2012, ANN ASSOC AM GEOGR, V102, P737, DOI 10.1080/00045608.2012.678035
   Hayhoe K., 2018, OUR CHANGING CLIMATE, P72, DOI DOI 10.7930/NCA4.2018.CH2
   Hirsch SL, 2020, ENVIRON PLAN E-NAT, V3, P40, DOI 10.1177/2514848619857523
   Jasanoff S., 2004, STATES KNOWLEDGE COP
   King Sarashka, 2018, British Arachnological Society Newsletter, V143, P2
   Kirtman B, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P953
   Kleinman DL, 2013, SCI TECHNOL HUM VAL, V38, P492, DOI 10.1177/0162243912442575
   Lave R, 2012, ENVIRON SOC, V3, P19, DOI 10.3167/ares.2012.030103
   Lewis SL, 2015, NATURE, V519, P171, DOI 10.1038/nature14258
   Lewis SC, 2017, B AM METEOROL SOC, V98, P1139, DOI 10.1175/BAMS-D-16-0183.1
   Mansfield B, 2017, ANN AM ASSOC GEOGR, V107, P22, DOI 10.1080/24694452.2016.1230418
   Mansfield B, 2015, ANN ASSOC AM GEOGR, V105, P284, DOI 10.1080/00045608.2014.973802
   Maricopa Association of Governments, PM 10 MON DAT
   McKenzie D, 2014, EARTHS FUTURE, V2, P35, DOI 10.1002/2013EF000180
   Milly PCD, 2008, SCIENCE, V319, P573, DOI 10.1126/science.1151915
   Moore JasonW., 2016, ANTHROPOCENE CAPITAL
   Murphy Michelle., 2006, Sick Building Syndrome and the Problem of Uncertainty : Environmental Politics, Technoscience, and Women Workers
   National Research Council, 2014, LESS LEARN FUK NUCL
   Pilkey O, 2013, GEOL SOC AM SPEC PAP, V502, P135, DOI 10.1130/2013.2502(07)
   Pilkey Orrin H., 2007, Useless arithmetic: why environmental scientists can't predict the future
   Pine KH, 2015, CHI 2015: PROCEEDINGS OF THE 33RD ANNUAL CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, P3147, DOI 10.1145/2702123.2702298
   Porter T. M., 1996, Trust in Numbers
   Purdy Jedediah., 2015, After Nature: A Politics for the Anthropocene
   Ribes D, 2013, INFRASTRUCT SER, P147
   Romm J, 2011, NATURE, V478, P450, DOI 10.1038/478450a
   Ruhl JB, 2011, VANDERBILT LAW REV, V64, P1
   Sayre N.F., 2017, The Politics of Scale: A History of Rangeland Science, DOI [10.7208/chicago/9780226083391.001.0001, DOI 10.7208/CHICAGO/9780226083391.001.0001]
   Sedell JK, 2021, GEOFORUM, V123, P162, DOI 10.1016/j.geoforum.2019.04.008
   Simon GL, 2011, SOC NATUR RESOUR, V24, P95, DOI 10.1080/08941920903284374
   Stakhiv EZ, 2011, J AM WATER RESOUR AS, V47, P1183, DOI 10.1111/j.1752-1688.2011.00589.x
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   STOLARSKI RS, 1986, NATURE, V322, P808, DOI 10.1038/322808a0
   The Fukushima Nuclear Accident Independent Investigation Commission, 2012, NAT DIET JAP
   Thieler ER, 2000, J COASTAL RES, V16, P48
   Toimil A, 2020, COAST ENG, V156, DOI 10.1016/j.coastaleng.2019.103611
   Ureta S, 2020, ENVIRON PLAN E-NAT, V3, P3, DOI 10.1177/2514848619898092
   von Hobe M, 2007, SCIENCE, V318, P1878, DOI 10.1126/science.1151597
   Walsh J., 2014, Climate change impacts in the United States: the third national climate assessment, DOI [10.7930/J0KW5CXT., DOI 10.7930/J0KW5CXT]
   Wheatley S, 2017, RISK ANAL, V37, P99, DOI 10.1111/risa.12587
   Wigley TML, 2009, CLIMATIC CHANGE, V97, P67, DOI 10.1007/s10584-009-9654-7
   Williams JW, 2007, FRONT ECOL ENVIRON, V5, P475, DOI 10.1890/070037
   Williams Raymond., 1977, KEYWORDS VOCABULARY
   Worster D., 2004, DUST BOWL SO PLAINS, DOI [10.1086/ahr/85.3.732, DOI 10.1086/AHR/85.3.732]
   YOUNG RS, 1995, J COASTAL RES, V11, P875
   Zalasiewicz J, 2010, ENVIRON SCI TECHNOL, V44, P2228, DOI 10.1021/es903118j
NR 70
TC 1
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
SN 2469-4452
EI 2469-4460
J9 ANN AM ASSOC GEOGR
JI Ann. Am. Assoc. Geogr.
PD AUG 7
PY 2020
VL 111
IS 3
BP 932
EP 943
DI 10.1080/24694452.2020.1785836
EA AUG 2020
PG 12
WC Geography
WE Social Science Citation Index (SSCI)
SC Geography
GA QY1HW
UT WOS:000557947100001
DA 2025-01-10
ER

PT J
AU Song, JC
   Chen, W
   Zhang, JJ
   Huang, K
   Hou, BY
   Prishchepov, AV
AF Song, Jinchao
   Chen, Wei
   Zhang, Jianjun
   Huang, Ke
   Hou, Boyan
   Prishchepov, Alexander, V
TI Effects of building density on land surface temperature in China:
   Spatial patterns and determinants
SO LANDSCAPE AND URBAN PLANNING
LA English
DT Article
DE Land surface temperature; Building density; Climate zone; Urban
   planning; Remote sensing
ID URBAN HEAT-ISLAND; DIFFERENCE VEGETATION INDEX; SOIL-WATER CONTENT;
   IMPERVIOUS SURFACE; LANDSCAPE STRUCTURE; SEMIARID BOTSWANA; WINDOW
   ALGORITHM; CLIMATE-CHANGE; NDVI RESPONSE; HUMAN HEALTH
AB The effects of building density on land surface temperature (LST) and its spatial patterns remain poorly understood over large areas. Using Landsat 8 satellite imagery, we quantified the effects of building density on land surface temperature (K) across 21 cities in China and analysed their spatial patterns, possible factors, and mechanisms. Results showed that the effects of building density on LST were more significant in areas with dry climates compared to humid climates. The spatial variability in the effects of building density on LST was closely related to climate conditions, soil type, and vegetation. The results from stepwise regression analysis showed that precipitation (climate) controlled the spatial variability, indicating that there is a complex mechanism underlying these potential factors. Furthermore, the results from climatic zoning statistics revealed that the K-values of northern Chinese cities were positively correlated with the areas of local water bodies. However, the K-values of southern Chinese cities were significantly and positively correlated with the mean annual temperature and aridity and were negatively correlated with population density. Stepwise regression results further indicated that the mean annual temperature may be the most influential factor for southern cities. These results highlight the spatial variance and different determinants of K and suggest that climate-adapted urban design and planning standards are needed in different climate zones.
C1 [Song, Jinchao; Huang, Ke; Prishchepov, Alexander, V] Univ Copenhagen, Dept Geosci & Nat Resource Management, DK-1350 Copenhagen, Denmark.
   [Chen, Wei; Zhang, Jianjun] China Univ Geosci Beijing, Sch Land Sci & Technol, Beijing 100083, Peoples R China.
   [Zhang, Jianjun] Minist Land & Resources, Key Lab Land Consolidat & Rehabil, Beijing 100083, Peoples R China.
   [Huang, Ke] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China.
   [Hou, Boyan] Xian Tieyi Sch, Int Cooperat Sch, Xian 710054, Peoples R China.
C3 University of Copenhagen; China University of Geosciences; Ministry of
   Natural Resources of the People's Republic of China; Chinese Academy of
   Sciences; Institute of Geographic Sciences & Natural Resources Research,
   CAS
RP Song, JC (corresponding author), Univ Copenhagen, Dept Geosci & Nat Resource Management, DK-1350 Copenhagen, Denmark.; Zhang, JJ (corresponding author), China Univ Geosci Beijing, Sch Land Sci & Technol, Beijing 100083, Peoples R China.; Zhang, JJ (corresponding author), Minist Land & Resources, Key Lab Land Consolidat & Rehabil, Beijing 100083, Peoples R China.
EM songjinchao08@163.com; zhangjianjun@cugb.edu.cn
RI ; Prishchepov, Alexander/H-6708-2012
OI Chen, Wei/0009-0005-5433-3809; Prishchepov,
   Alexander/0000-0003-2375-1651
CR [Anonymous], [No title captured]
   [Anonymous], [No title captured]
   Azhdari A, 2018, SUSTAIN CITIES SOC, V41, P853, DOI 10.1016/j.scs.2018.06.034
   Barsi JA, 2014, REMOTE SENS-BASEL, V6, P10232, DOI 10.3390/rs61010232
   Cao X, 2010, LANDSCAPE URBAN PLAN, V96, P224, DOI 10.1016/j.landurbplan.2010.03.008
   CARNAHAN WH, 1990, REMOTE SENS ENVIRON, V33, P65, DOI 10.1016/0034-4257(90)90056-R
   Chen XL, 2006, REMOTE SENS ENVIRON, V104, P133, DOI 10.1016/j.rse.2005.11.016
   Chen X, 2017, SUSTAIN CITIES SOC, V32, P87, DOI 10.1016/j.scs.2017.03.013
   Dai ZX, 2018, SCI TOTAL ENVIRON, V626, P1136, DOI 10.1016/j.scitotenv.2018.01.165
   Du HY, 2016, SCI TOTAL ENVIRON, V571, P461, DOI 10.1016/j.scitotenv.2016.07.012
   Estoque RC, 2017, SCI TOTAL ENVIRON, V577, P349, DOI 10.1016/j.scitotenv.2016.10.195
   FARRAR TJ, 1994, REMOTE SENS ENVIRON, V50, P121, DOI 10.1016/0034-4257(94)90039-6
   Feng YN, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11151802
   Fily M, 2003, REMOTE SENS ENVIRON, V85, P328, DOI 10.1016/S0034-4257(03)00011-7
   Friedl MA, 2002, REMOTE SENS ENVIRON, V79, P344, DOI 10.1016/S0034-4257(01)00284-X
   Georgescu M, 2013, NAT CLIM CHANGE, V3, P37, DOI 10.1038/nclimate1656
   Gillies RR, 1997, INT J REMOTE SENS, V18, P3145, DOI 10.1080/014311697217026
   GILLIES RR, 1995, J APPL METEOROL, V34, P745, DOI 10.1175/1520-0450(1995)034<0745:TRSOSS>2.0.CO;2
   Goward SN, 2002, REMOTE SENS ENVIRON, V79, P225, DOI 10.1016/S0034-4257(01)00275-9
   Goward SN., 1981, Phys Geog, V2, P19, DOI DOI 10.1080/02723646.1981.10642202
   Gray MA, 2018, AGR FOREST METEOROL, V249, P81, DOI 10.1016/j.agrformet.2017.11.018
   Guo GH, 2016, ENVIRON MODELL SOFTW, V84, P427, DOI 10.1016/j.envsoft.2016.06.021
   He F, 2014, GEOPHYS RES LETT, V41, P623, DOI 10.1002/2013GL058085
   Huang B., 1989, GEOGR S, V21, P10
   Huang GL, 2011, J ENVIRON MANAGE, V92, P1753, DOI 10.1016/j.jenvman.2011.02.006
   Imhoff ML, 2010, REMOTE SENS ENVIRON, V114, P504, DOI 10.1016/j.rse.2009.10.008
   Kovats RS, 2005, RISK ANAL, V25, P1409, DOI 10.1111/j.1539-6924.2005.00688.x
   Lang SW, 2004, ENERG BUILDINGS, V36, P1191, DOI 10.1016/j.enbuild.2003.09.014
   Larson R.C., 1997, Geocarto International, V12, P5, DOI DOI 10.1080/10106049709354592
   Li JX, 2011, REMOTE SENS ENVIRON, V115, P3249, DOI 10.1016/j.rse.2011.07.008
   Li WF, 2014, ECOL INDIC, V47, P171, DOI 10.1016/j.ecolind.2014.08.015
   Li XM, 2012, LANDSCAPE ECOL, V27, P887, DOI 10.1007/s10980-012-9731-6
   Lin PY, 2017, LANDSCAPE URBAN PLAN, V168, P48, DOI 10.1016/j.landurbplan.2017.09.024
   Lou XQ, 2015, INT J COGN INFORM NA, V9, P1, DOI 10.4018/IJCINI.2015010101
   Lu DS, 2006, REMOTE SENS ENVIRON, V102, P146, DOI 10.1016/j.rse.2006.02.010
   Ma T, 2014, REMOTE SENS LETT, V5, P165, DOI 10.1080/2150704X.2014.890758
   Mathew Aneesh, 2018, Remote Sensing Applications: Society and Environment, V11, P119, DOI 10.1016/j.rsase.2018.05.003
   McMichael AJ, 2006, LANCET, V367, P859, DOI 10.1016/S0140-6736(06)68079-3
   Meng QY, 2018, REMOTE SENS ENVIRON, V204, P826, DOI 10.1016/j.rse.2017.09.019
   Mohegh A, 2018, CLIMATE, V6, DOI 10.3390/cli6040098
   Morabito M, 2016, SCI TOTAL ENVIRON, V551, P317, DOI 10.1016/j.scitotenv.2016.02.029
   Myint SW, 2013, LANDSCAPE ECOL, V28, P959, DOI 10.1007/s10980-013-9868-y
   Nakayama T, 2010, LANDSCAPE URBAN PLAN, V96, P57, DOI 10.1016/j.landurbplan.2010.02.003
   Nichol JE, 1996, J APPL METEOROL, V35, P135, DOI 10.1175/1520-0450(1996)035<0135:HRSTPR>2.0.CO;2
   NICHOLSON SE, 1994, REMOTE SENS ENVIRON, V50, P107, DOI 10.1016/0034-4257(94)90038-8
   Pal S, 2017, EGYPT J REMOTE SENS, V20, P125, DOI 10.1016/j.ejrs.2016.11.003
   Peng J, 2018, REMOTE SENS ENVIRON, V215, P255, DOI 10.1016/j.rse.2018.06.010
   Peng J, 2016, REMOTE SENS ENVIRON, V173, P145, DOI 10.1016/j.rse.2015.11.027
   Peng SS, 2012, ENVIRON SCI TECHNOL, V46, P696, DOI 10.1021/es2030438
   Prado RTA, 2005, ENERG BUILDINGS, V37, P295, DOI 10.1016/j.enbuild.2004.03.009
   Qin Z, 2001, INT J REMOTE SENS, V22, P3719, DOI 10.1080/01431160010006971
   Quattrochi D., 1998, PROJECT ATLANTA ATLA
   Ren GY, 2017, J METEOROL RES-PRC, V31, P3, DOI 10.1007/s13351-017-6195-2
   Sandholt I, 2002, REMOTE SENS ENVIRON, V79, P213, DOI 10.1016/S0034-4257(01)00274-7
   Schneider A, 2010, REMOTE SENS ENVIRON, V114, P1733, DOI 10.1016/j.rse.2010.03.003
   Schwarz N, 2012, ECOL INDIC, V18, P693, DOI 10.1016/j.ecolind.2012.01.001
   Sharma R, 2016, URBAN CLIM, V15, P70, DOI 10.1016/j.uclim.2016.01.004
   Simpson JR, 1997, ENERG BUILDINGS, V25, P127, DOI 10.1016/S0378-7788(96)01002-X
   SOBRINO JA, 1991, REMOTE SENS ENVIRON, V38, P19, DOI 10.1016/0034-4257(91)90069-I
   Sobrino JA, 2008, IEEE T GEOSCI REMOTE, V46, P316, DOI 10.1109/TGRS.2007.904834
   Song JC, 2019, COMPUT ENVIRON URBAN, V77, DOI 10.1016/j.compenvurbsys.2019.101364
   Song JC, 2019, LANDSCAPE URBAN PLAN, V190, DOI 10.1016/j.landurbplan.2019.05.011
   Song JC, 2018, REMOTE SENS-BASEL, V10, DOI 10.3390/rs10111737
   Song Y, 2016, ADV SPACE RES, V57, P96, DOI 10.1016/j.asr.2015.10.036
   Spronken-Smith RA, 1998, INT J REMOTE SENS, V19, P2085, DOI 10.1080/014311698214884
   Sun RH, 2013, BUILD ENVIRON, V65, P90, DOI 10.1016/j.buildenv.2013.04.001
   Wang F, 2015, REMOTE SENS-BASEL, V7, P4268, DOI 10.3390/rs70404268
   Weng QH, 2004, REMOTE SENS ENVIRON, V89, P467, DOI 10.1016/j.rse.2003.11.005
   Weng QH, 2006, PHOTOGRAMM ENG REM S, V72, P1275, DOI 10.14358/PERS.72.11.1275
   Wu SH, 2005, SCI CHINA SER D, V48, P1510, DOI 10.1360/04yd0009
   Xiao RB, 2007, J ENVIRON SCI-CHINA, V19, P250, DOI 10.1016/S1001-0742(07)60041-2
   Xu HQ, 2018, BUILD ENVIRON, V136, P98, DOI 10.1016/j.buildenv.2018.03.035
   Xue XF, 2006, ANN ENTOMOL SOC AM, V99, P1057, DOI 10.1603/0013-8746(2006)99[1057:EMAEOB]2.0.CO;2
   Yang FL, 2004, INT J CLIMATOL, V24, P1625, DOI 10.1002/joc.1094
   Yin YH, 2005, CHINESE SCI BULL, V50, P2226, DOI 10.1360/04wd264
   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 F, 2019, ISPRS J PHOTOGRAMM, V153, P48, DOI 10.1016/j.isprsjprs.2019.04.017
   Zhang YS, 2009, INT J APPL EARTH OBS, V11, P256, DOI 10.1016/j.jag.2009.03.001
   Zhao L, 2014, NATURE, V511, P216, DOI 10.1038/nature13462
   Zhao QS, 2015, REMOTE SENS-BASEL, V7, P12135, DOI 10.3390/rs70912135
   Zheng BJ, 2014, LANDSCAPE URBAN PLAN, V130, P104, DOI 10.1016/j.landurbplan.2014.07.001
   Zhou DC, 2014, REMOTE SENS ENVIRON, V152, P51, DOI 10.1016/j.rse.2014.05.017
   Zhou WQ, 2011, LANDSCAPE URBAN PLAN, V102, P54, DOI 10.1016/j.landurbplan.2011.03.009
NR 84
TC 107
Z9 111
U1 27
U2 168
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29a, 1043 NX AMSTERDAM, NETHERLANDS
SN 0169-2046
EI 1872-6062
J9 LANDSCAPE URBAN PLAN
JI Landsc. Urban Plan.
PD JUN
PY 2020
VL 198
AR 103794
DI 10.1016/j.landurbplan.2020.103794
PG 13
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 LG4FO
UT WOS:000528059000014
HC Y
HP N
DA 2025-01-10
ER

PT J
AU Salas-Pérez, JD
   Jordán-Garza, AG
   Salas-Monreal, D
AF de Jesus Salas-Perez, Jose
   Guillermo Jordan-Garza, Adan
   Salas-Monreal, David
TI Climate variability over the reef corridor of the southwestern Gulf of
   Mexico
SO ATMOSFERA
LA English
DT Article
DE Sistema Arrecifal Veracruzano National Park; Los Tuxtlas reefs;
   long-term linear trends; extreme values; ENSO signal; AMO signal
ID SEA-SURFACE TEMPERATURE; NCAR REANALYSIS DATA; WINTER PRECIPITATION;
   CORAL; VERACRUZ; RAINFALL; CIRCULATION; RESPONSES; GRADIENT; IMPACTS
AB Local and regional climate trends drive rates of change in coastal ecosystems. To better understand local climate, 35-year-long time series of air temperature, relative humidity and rainfall were analyzed along the reef corridor of the southwestern Gulf of Mexico. Data came from a climatological model and to assess its local performance, differences with in situ records were estimated when available. All three variables showed coherence with the record of the North Atlantic high-pressure system (also known as the Bermuda High) at similar times and periods between 4 to 8 and >10 years, evidencing the influence, at this regional scale, of El Nifio Southern Oscillation (ENSO) and the Atlantic Multidecadal Oscillation (AMO). Positive and negative anomalies showed linear trends depicting an increase of warmer and moister events during a seasonal climatology at the reef corridor of the southwestern Gulf of Mexico and a relatively higher correlation (> 0.5) with the AMO mode. Return periods of extreme values varied between 5 and 10 years. In general, trends and extreme events showed similar patterns at a regional scale, but the increase in rainfall is expected to be larger near the central location of the study area. A higher frequency of extreme events could threaten local ecosystems and human populations; therefore, plans and actions at local scales of governance are needed to achieve preemptive climate adaptation.
C1 [de Jesus Salas-Perez, Jose; Guillermo Jordan-Garza, Adan] Univ Veracruzana, Fac Ciencias Biol & Agr, Tuxpan, Veracruz, Mexico.
   [Salas-Monreal, David] Univ Veracruzana, Inst Ciencias Marinas & Pesquerias, Boca Del Rio, Veracruz, Mexico.
C3 Universidad Veracruzana; Universidad Veracruzana
RP Salas-Pérez, JD (corresponding author), Univ Veracruzana, Fac Ciencias Biol & Agr, Tuxpan, Veracruz, Mexico.
EM jsalasp39@yahoo.es
RI Jordán-Garza, Adán/HTR-8435-2023
OI Jordan-Garza, Adan Guillermo/0000-0002-9856-2276
CR Adger WN, 2005, GLOBAL ENVIRON CHANG, V15, P77, DOI [10.1016/j.gloenvcha.2005.03.001, 10.1016/j.gloenvcha.2004.12.005]
   Bruno JF, 2007, PLOS BIOL, V5, P1220, DOI 10.1371/journal.pbio.0050124
   Carricart-Ganivet JP, 2001, B MAR SCI, V68, P133
   Chollett I, 2012, MAR POLLUT BULL, V64, P956, DOI 10.1016/j.marpolbul.2012.02.016
   Cooley D, 2009, CLIMATIC CHANGE, V97, P77, DOI 10.1007/s10584-009-9627-x
   Cowpertwait PSP, 2009, USE R, P1, DOI 10.1007/978-0-387-88698-5_1
   Salas-Pérez JD, 2016, CIENC MAR, V42, P49, DOI 10.7773/cm.v42i1.2551
   deVelasco GG, 1996, J GEOPHYS RES-OCEANS, V101, P18127, DOI 10.1029/96JC01442
   Easterling DR, 1997, SCIENCE, V277, P364, DOI 10.1126/science.277.5324.364
   Enfield DB, 2001, GEOPHYS RES LETT, V28, P2077, DOI 10.1029/2000GL012745
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Gilleland E, 2016, J STAT SOFTW, V72, P1, DOI 10.18637/jss.v072.i08
   Grinsted A, 2004, NONLINEAR PROC GEOPH, V11, P561, DOI 10.5194/npg-11-561-2004
   Henderson KG, 1996, PHYS GEOGR, V17, P93, DOI 10.1080/02723646.1996.10642576
   Heron SF, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0012210
   Hoegh-Guldberg O, 2007, SCIENCE, V318, P1737, DOI 10.1126/science.1152509
   INEGI, 2020, Censo de Poblacion y Vivienda 2020
   Jiménez-Badillo L, 2008, FISHERIES MANAG ECOL, V15, P19, DOI 10.1111/j.1365-2400.2007.00565.x
   Jin D, 2010, J GEOPHYS RES-ATMOS, V115, DOI 10.1029/2009JD012660
   Jordán-Dahlgren E, 2003, LATIN AMERICAN CORAL REEFS, P131, DOI 10.1016/B978-044451388-5/50007-2
   Jordán-Garza AG, 2017, CONT SHELF RES, V138, P32, DOI 10.1016/j.csr.2017.03.002
   Kalnay E, 1996, B AM METEOROL SOC, V77, P437, DOI 10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2
   Katz RW, 2003, CLIMATIC CHANGE, V60, P189, DOI 10.1023/A:1026054330406
   Klein Tank A.M.G., 2009, Guidelines on Analysis of Extremes in a Changing Climate in Support of Informed Decisions for Adaptation
   Kucharski F, 2010, B AM METEOROL SOC, V91, P381, DOI 10.1175/2009BAMS2834.1
   Kuffner IB, 2015, ESTUAR COAST, V38, P1085, DOI 10.1007/s12237-014-9875-5
   Labat D, 2005, J HYDROL, V314, P289, DOI 10.1016/j.jhydrol.2005.04.004
   Li WH, 2011, J CLIMATE, V24, P1499, DOI 10.1175/2010JCLI3829.1
   Marshall J, 2001, INT J CLIMATOL, V21, P1863, DOI 10.1002/joc.693
   Matlab, 2017, POL STAT
   Mendoza-Cantú A, 2011, J ENVIRON MANAGE, V92, P1706, DOI 10.1016/j.jenvman.2011.02.008
   Mesinger F, 2006, B AM METEOROL SOC, V87, P343, DOI 10.1175/BAMS-87-3-343
   Milly PCD, 2002, NATURE, V415, P514, DOI 10.1038/415514a
   Moberg F, 1999, ECOL ECON, V29, P215, DOI 10.1016/S0921-8009(99)00009-9
   Murphy JM, 2004, NATURE, V430, P768, DOI 10.1038/nature02771
   Nieto S, 2004, INT J CLIMATOL, V24, P361, DOI 10.1002/joc.999
   Ortegren JT, 2011, J APPL METEOROL CLIM, V50, P1177, DOI 10.1175/2010JAMC2566.1
   Palumbi SR, 2014, SCIENCE, V344, P895, DOI 10.1126/science.1251336
   Pandolfi JM, 2011, SCIENCE, V333, P418, DOI 10.1126/science.1204794
   Pinheiro J., 2011, R package version 3, V3, P1
   Precht WF, 2004, FRONT ECOL ENVIRON, V2, P307
   R Core Team, 2016, R: A Language and Environment for Statistical Computing
   Rivera-Guzmán NE, 2014, OCEAN COAST MANAGE, V87, P30, DOI 10.1016/j.ocecoaman.2013.10.007
   Ruane AC, 2010, J HYDROMETEOROL, V11, P1205, DOI 10.1175/2010JHM1193.1
   Ruiz-Morenol D, 2012, DIS AQUAT ORGAN, V100, P249, DOI 10.3354/dao02488
   Pérez JDS, 2012, ESTUAR COAST SHELF S, V100, P102, DOI 10.1016/j.ecss.2012.01.002
   Salas-P?rez, 2018, OCEANOGRAPHY REEF CO
   Salas-Perez JJ, 2008, ATMOSFERA, V21, P281
   Salas-Pérez JJ, 2011, ATMOSFERA, V24, P221
   Salas-Perez J. J., 2007, INVESTIGACIONES CIEN, P17
   Saravanan R, 2000, J CLIMATE, V13, P2177, DOI 10.1175/1520-0442(2000)013<2177:IBTAVA>2.0.CO;2
   Sheridan SC, 2003, INT J CLIMATOL, V23, P27, DOI 10.1002/joc.863
   Smith TM, 2008, J CLIMATE, V21, P2283, DOI 10.1175/2007JCLI2100.1
   STAHLE DW, 1992, B AM METEOROL SOC, V73, P1947, DOI 10.1175/1520-0477(1992)073<1947:RAAOSR>2.0.CO;2
   Tang ZH, 2010, J ENVIRON PLANN MAN, V53, P41, DOI 10.1080/09640560903399772
   Tejeda-Martinez A., 2006, INUNDACIONES 2005 ES
   Tett S. F. B., 2002, Journal of Geophysical Research, V107, pACL10, DOI 10.1029/2000JD000028
   Tolika K, 2006, INT J CLIMATOL, V26, P935, DOI 10.1002/joc.1290
   Tunnell J.W., 2007, Coral Reefs of the Southern Gulf of Mexico
   Walther GR, 2002, NATURE, V416, P389, DOI 10.1038/416389a
   Wiles GC, 2014, HOLOCENE, V24, P198, DOI 10.1177/0959683613516815
   Zhu JH, 2013, J CLIMATE, V26, P1018, DOI 10.1175/JCLI-D-12-00168.1
NR 62
TC 2
Z9 2
U1 0
U2 12
PU CENTRO CIENCIAS ATMOSFERA UNAM
PI MEXICO CITY
PA CIRCUITO EXTERIOR, MEXICO CITY CU 04510, MEXICO
SN 0187-6236
EI 2395-8812
J9 ATMOSFERA
JI Atmosfera
PD APR
PY 2020
VL 33
IS 2
BP 143
EP 157
DI 10.20937/ATM.52730
PG 15
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA PD7YT
UT WOS:000597896400003
OA Green Published, Bronze
DA 2025-01-10
ER

PT J
AU Jhong, BC
   Huang, J
   Tung, CP
AF Jhong, Bing-Chen
   Huang, Jung
   Tung, Ching-Pin
TI Spatial Assessment of Climate Risk for Investigating Climate Adaptation
   Strategies by Evaluating Spatial-Temporal Variability of Extreme
   Precipitation
SO WATER RESOURCES MANAGEMENT
LA English
DT Article
DE Climate change; Spatial assessment; Climate risk; Adaptation strategy;
   Precipitation extremes; Joint probability distribution; Copula function
ID FUTURE JOINT PROBABILITY; HUMAN HEALTH; COPULA; IMPACTS; TEMPERATURE;
   FRAMEWORK; DROUGHT; VULNERABILITY; PATTERNS; WEATHER
AB In response to the impacts of extreme precipitation on human or natural systems under climate change, the development of climate risk assessment approach is a crucial task. In this paper, a novel risk assessing approach based on a climate risk assessment framework with copula-based approaches is proposed. Firstly, extreme precipitation indices (EPIs) and their marginal distributions are estimated for historical and future periods. Next, the joint probability distributions of extreme precipitation are constructed by copula methods and tested by goodness-of-fit indices. The future joint probabilities and joint return periods (JRPs) of the EPIs are then evaluated. Finally, change rates of JRPs for future periods are estimated to assess climate risk with the quantitative data of exposure and vulnerability of a protected target. An actual application in Taiwan Island is successfully conducted for climate risk assessment with the impacts of extreme precipitation. The results indicate that most of regions in Taiwan Island might have higher potential climate risk under different scenarios in the future. The future joint probabilities of precipitation extremes might cause the high risk of landslide and flood disasters in the mountainous area, and of inundation in the plain area. In sum, the proposed climate risk assessing approach is expected to be useful for assisting decision makers to draft adaptation strategies and face high risk of the possible occurrence of natural disasters.
C1 [Jhong, Bing-Chen] Kyoto Univ, Grad Sch Engn, Dept Civil & Earth Resources Engn, Kyoto 6158540, Japan.
   [Huang, Jung; Tung, Ching-Pin] Natl Taiwan Univ, Dept Bioenvironm Syst Engn, Taipei 10617, Taiwan.
C3 Kyoto University; National Taiwan University
RP Jhong, BC (corresponding author), Kyoto Univ, Grad Sch Engn, Dept Civil & Earth Resources Engn, Kyoto 6158540, Japan.
EM jhongbc0516@gmail.com
OI Jhong, Bing-Chen/0000-0003-3817-3946
FU Taiwan Climate Change Projection and Information Platform Project
   (TCCIP) - Ministry of Science and Technology (MOST)
FX The authors are grateful to the Taiwan Climate Change Projection and
   Information Platform Project (TCCIP) funded by Ministry of Science and
   Technology (MOST) providing the projections of general circulation
   models with the climate scenarios and revised by the method of bias
   correction and spatial disaggregation. The authors would also like to
   appreciate all colleagues and students from Sustainable Development
   Laboratory (SDLab) in the Department of Bioenvironmental Systems
   Engineering, who contributed to this study.
CR Allen SK, 2018, ENVIRON SCI POLICY, V87, P1, DOI 10.1016/j.envsci.2018.05.013
   [Anonymous], 2017, NAT HAZARDS EARTH SY, DOI [DOI 10.5194/NHESS-17-1231-2017, 10.5194/nhess-17-1231-2017]
   [Anonymous], FCCCSBSTA2004INF13
   [Anonymous], 2001, CLIMATE CHANGE 2001
   [Anonymous], 2014, CLIM DYN, DOI DOI 10.1007/S00382-013-1851-4
   [Anonymous], 2004, Int. Rev. Financ. Anal., DOI [DOI 10.1016/J.IRFA.2004.01.007, DOI 10.1016/J.IRFA.2004.01.007]]
   Chen CW, 2015, PROG EARTH PLANET SC, V2, DOI 10.1186/s40645-015-0049-2
   Fan YR, 2016, THEOR APPL CLIMATOL, V125, P381, DOI 10.1007/s00704-015-1505-z
   Goswami UP, 2018, ATMOS RES, V212, P273, DOI 10.1016/j.atmosres.2018.05.019
   Haines A, 2006, PUBLIC HEALTH, V120, P585, DOI 10.1016/j.puhe.2006.01.002
   Jhong BC, 2018, WATER RESOUR MANAG, V32, P4253, DOI 10.1007/s11269-018-2045-y
   Jhong BC, 2017, J HYDROL, V547, P236, DOI 10.1016/j.jhydrol.2017.01.057
   Karl TR, 1999, CLIMATIC CHANGE, V42, P3, DOI 10.1023/A:1005491526870
   Kunkel KE, 1999, B AM METEOROL SOC, V80, P1077, DOI 10.1175/1520-0477(1999)080<1077:TFIWAC>2.0.CO;2
   Li JF, 2015, GLOBAL PLANET CHANGE, V124, P107, DOI 10.1016/j.gloplacha.2014.11.012
   Lin CY, 2017, TERR ATMOS OCEAN SCI, V28, P43, DOI 10.3319/TAO.2016.06.14.01(CCA)
   Lin GF, 2015, J HYDROL, V521, P302, DOI 10.1016/j.jhydrol.2014.12.009
   Liu J, 2015, CLIMATIC CHANGE, V132, P741, DOI 10.1007/s10584-015-1478-z
   Liu TM, 2009, PADDY WATER ENVIRON, V7, P301, DOI 10.1007/s10333-009-0177-7
   Madadgar S, 2017, GEOPHYS RES LETT, V44, P7799, DOI 10.1002/2017GL073606
   Mann ME, 2017, SCI REP-UK, V7, DOI 10.1038/srep45242
   McMichael AJ, 2006, LANCET, V367, P859, DOI 10.1016/S0140-6736(06)68079-3
   Nandintsetseg B, 2007, INT J CLIMATOL, V27, P341, DOI 10.1002/joc.1404
   Nelsen R. B., 2006, INTRO COPULAS, V2nd ed. edn
   Peduzzi P, 2009, NAT HAZARD EARTH SYS, V9, P1149, DOI 10.5194/nhess-9-1149-2009
   Peterson T.C., 2005, World Meteorological Organization Bulletin, V54, P83
   Petley D, 2012, GEOLOGY, V40, P927, DOI 10.1130/G33217.1
   Qian LX, 2018, HYDROL PROCESS, V32, P212, DOI 10.1002/hyp.11406
   Rana A, 2017, THEOR APPL CLIMATOL, V129, P321, DOI 10.1007/s00704-016-1774-1
   Ronco P, 2017, ADV WATER RESOUR, V110, P562, DOI 10.1016/j.advwatres.2017.08.003
   Salvadori G, 2004, WATER RESOUR RES, V40, DOI 10.1029/2004WR003133
   Shieh SL., 2000, Users guide for typhoon forecasting in the Taiwan area (VIII)
   Sillmann J, 2008, CLIMATIC CHANGE, V86, P83, DOI 10.1007/s10584-007-9308-6
   Sisco MR, 2017, CLIMATIC CHANGE, V143, P227, DOI 10.1007/s10584-017-1984-2
   Smith BA, 2015, FOOD RES INT, V68, P78, DOI 10.1016/j.foodres.2014.07.006
   Su FC, 2014, ENVIRON INT, V63, P236, DOI 10.1016/j.envint.2013.11.004
   Sun DY, 2012, WATER-SUI, V4, P272, DOI 10.3390/w4010272
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Terzi S, 2019, J ENVIRON MANAGE, V232, P759, DOI 10.1016/j.jenvman.2018.11.100
   Tung CP, 2019, WATER-SUI, V11, DOI 10.3390/w11030497
   Tung ChingPin Tung ChingPin, 2014, British Journal of Environment and Climate Change, V4, P27, DOI 10.9734/BJECC/2014/8572
   van Vuuren DP, 2011, CLIMATIC CHANGE, V109, P95, DOI 10.1007/s10584-011-0152-3
   Volpi E, 2014, WATER RESOUR RES, V50, P885, DOI 10.1002/2013WR014214
   Voss R, 2002, INT J CLIMATOL, V22, P755, DOI 10.1002/joc.757
   Wahl T, 2012, NAT HAZARD EARTH SYS, V12, P495, DOI 10.5194/nhess-12-495-2012
   Wahl T, 2015, NAT CLIM CHANGE, V5, P1093, DOI [10.1038/nclimate2736, 10.1038/NCLIMATE2736]
   Weaver CP, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa7494
   Wong PP, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P361
   Wright, 1984, WGEN MODEL GENERATIN
   Wu CC, 1999, B AM METEOROL SOC, V80, P67, DOI 10.1175/1520-0477(1999)080<0067:TATCUA>2.0.CO;2
   Zhang DD, 2015, NAT HAZARDS, V75, P2199, DOI 10.1007/s11069-014-1419-6
   ,, 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 52
TC 15
Z9 16
U1 5
U2 59
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 AUG
PY 2019
VL 33
IS 10
BP 3377
EP 3400
DI 10.1007/s11269-019-02306-8
PG 24
WC Engineering, Civil; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Water Resources
GA IR9TX
UT WOS:000481790200003
DA 2025-01-10
ER

PT J
AU Klein, JA
   Tucker, CM
   Steger, CE
   Nolin, A
   Reid, R
   Hopping, KA
   Yeh, ET
   Pradhan, MS
   Taber, A
   Molden, D
   Ghate, R
   Choudhury, D
   Alcántara-Ayala, I
   Lavorel, S
   Müller, B
   Grêt-Regamey, A
   Boone, RB
   Bourgeron, P
   Castellanos, E
   Chen, XD
   Dong, SK
   Keiler, M
   Seidl, R
   Thorn, J
   Yager, K
AF Klein, Julia A.
   Tucker, Catherine M.
   Steger, Cara E.
   Nolin, Anne
   Reid, Robin
   Hopping, Kelly A.
   Yeh, Emily T.
   Pradhan, Meeta S.
   Taber, Andrew
   Molden, David
   Ghate, Rucha
   Choudhury, Dhrupad
   Alcantara-Ayala, Irasema
   Lavorel, Sandra
   Mueller, Birgit
   Gret-Regamey, Adrienne
   Boone, Randall B.
   Bourgeron, Patrick
   Castellanos, Edwin
   Chen, Xiaodong
   Dong, Shikui
   Keiler, Margreth
   Seidl, Roman
   Thorn, Jessica
   Yager, Karina
TI An integrated community and ecosystem-based approach to disaster risk
   reduction in mountain systems
SO ENVIRONMENTAL SCIENCE & POLICY
LA English
DT Article
DE Disasters; Governance; Mountains; Nepal; Resilience; Sustainable
   development
ID CLIMATE-CHANGE; GORKHA EARTHQUAKE; NEPAL; ADAPTATION; RESILIENCE;
   KNOWLEDGE; IMPACTS; HEALTH; PREPAREDNESS; MANAGEMENT
AB The devastating 2015 earthquakes in Nepal highlighted the need for effective disaster risk reduction (DRR) in mountains, which are inherently subject to hazards and increasingly vulnerable to extreme events. As multiple UN policy frameworks stress, DRR is crucial to mitigate the mounting environmental and socioeconomic costs of disasters globally. However, specialized DRR guidelines are needed for biodiverse, multi-hazard regions like mountains. Ecosystem-based disaster risk reduction (Eco-DRR) emphasizes ecosystem conservation, restoration, and sustainable management as key elements for DRR. We propose that integrating the emerging field of Eco-DRR with community-based DRR (CB-DRR) will help address the increasing vulnerabilities of mountain people and ecosystems. Drawing on a global mountain synthesis, we present paradoxes that create challenges for DRR in mountains and examine these paradoxes through examples from the 2015 Nepal earthquakes. We propose four principles for integrated CB- and Eco-DRR that address these challenges: (1) governance and institutional arrangements that fit local needs; (2) empowerment and capacity-building to strengthen community resilience; (3) discovery and sharing of constructive practices that combine local and scientific knowledge; and (4) approaches focused on well-being and equity. We illustrate the reinforcing relationship between integrated CB- and Eco-DRR principles with examples from other mountain systems worldwide. Coordinated community and ecosystem-based actions offer a potential path to achieve DRR, climate adaptation, sustainable development, and biodiversity conservation for vulnerable ecosystems and communities worldwide.
C1 [Klein, Julia A.; Steger, Cara E.; Reid, Robin; Boone, Randall B.; Thorn, Jessica] Colorado State Univ, Campus Delivery 1476, Ft Collins, CO 80523 USA.
   [Tucker, Catherine M.] Univ Florida, Gainesville, FL 32611 USA.
   [Nolin, Anne] Univ Nevada, Reno, NV 89557 USA.
   [Hopping, Kelly A.] Boise State Univ, Boise, ID 83725 USA.
   [Yeh, Emily T.; Bourgeron, Patrick] Univ Colorado, Boulder, CO 80309 USA.
   [Pradhan, Meeta S.] Mt Inst, Himalayan Program, Kathmandu, Nepal.
   [Taber, Andrew] UN Food & Agr Org, Rome, Italy.
   [Molden, David; Ghate, Rucha; Choudhury, Dhrupad] Int Ctr Integrated Mt Dev, Kathmandu, Nepal.
   [Alcantara-Ayala, Irasema] Natl Autonomous Univ Mexico UNAM, Inst Geog, Mexico City, DF, Mexico.
   [Lavorel, Sandra] CNRS, Grenoble, France.
   [Mueller, Birgit] UFZ Helmholtz Ctr Environm Res, D-04318 Leipzig, Germany.
   [Gret-Regamey, Adrienne; Seidl, Roman] ETH, CH-8093 Zurich, Switzerland.
   [Castellanos, Edwin] Univ Valle Guatemala, Guatemala City, Guatemala.
   [Chen, Xiaodong] Univ N Carolina, Chapel Hill, NC 27599 USA.
   [Dong, Shikui] Beijing Normal Univ, Beijing 100875, Peoples R China.
   [Keiler, Margreth] Univ Bern, Inst Geog, CH-3012 Bern, Switzerland.
   [Yager, Karina] SUNY Stony Brook, Stony Brook, NY 11794 USA.
C3 Colorado State University; State University System of Florida;
   University of Florida; Nevada System of Higher Education (NSHE);
   University of Nevada Reno; Boise State University; University of
   Colorado System; University of Colorado Boulder; Food & Agriculture
   Organization of the United Nations (FAO); Universidad Nacional Autonoma
   de Mexico; Centre National de la Recherche Scientifique (CNRS);
   Helmholtz Association; Helmholtz Center for Environmental Research
   (UFZ); Swiss Federal Institutes of Technology Domain; ETH Zurich;
   Universidad del Valle de Guatemala; University of North Carolina;
   University of North Carolina Chapel Hill; Beijing Normal University;
   University of Bern; State University of New York (SUNY) System; Stony
   Brook University
RP Klein, JA (corresponding author), Colorado State Univ, Campus Delivery 1476, Ft Collins, CO 80523 USA.
EM Julia.klein@colostate.edu; tuckerc@ufl.edu; cara.steger@colostate.edu;
   anolin@unr.edu; Robin.Reid@mountain.org; kellyhopping@boisestate.edu;
   emily.yeh@Colorado.EDU; mpradhan@mountain.org; Andrew.taber@fao.org;
   David.Molden@icimod.org; Rucha.Ghate@icimod.org;
   Dhrupad.Choudhury@icimod.org; Irasema@igg.unam.mx;
   sandra.lavorel@ujf-grenoble.fr; birgit.mueller@ufz.de; gret@ethz.ch;
   Randall.Boone@Colostate.edu; Patrick.Bourgeron@colorado.edu;
   ecastell@uvg.edu.gr; chenxd@email.unc.edu; dongshikui@sina.com;
   margreth.keiler@giub.unibe.ch; R.Seidl@oeko.de;
   karina.yager@stonybrook.edu
RI Yager, Karina/ISS-4961-2023; Dong, Shikui/GQA-6626-2022; Seidl,
   Roman/G-5943-2012; Hopping, Kelly/LDF-4152-2024; Chen, Xiao
   Dong/ADG-8612-2022; Lavorel, Sandra/AGM-2903-2022; Müller,
   Birgit/AFH-8212-2022; Alcántara-Ayala, Irasema/G-8639-2017;
   Grêt-Regamey, Adrienne/AAZ-7546-2021; Boone, Randall/N-6566-2013; YEH,
   EMILY/O-7909-2014; Tucker, Catherine May/G-5333-2012; Gret-Regamey,
   Adrienne/HPE-6858-2023; Keiler, Margreth/F-4258-2012
OI Thorn, Jessica/0000-0003-2108-2554; YEH, EMILY/0000-0002-4401-2404;
   Tucker, Catherine May/0000-0003-3151-5376; Gret-Regamey,
   Adrienne/0000-0001-8156-9503; Klein, Julia/0000-0003-1486-7994;
   Castellanos, Edwin/0000-0001-9775-0518; Keiler,
   Margreth/0000-0001-9168-023X; Hopping, Kelly/0000-0002-0557-0526;
   Molden, David/0000-0003-3201-9518; Yager, Karina/0000-0003-4938-5012;
   Seidl, Roman/0000-0002-6658-8789; Muller, Birgit/0000-0001-8780-4420
FU NSF [DEB-1414106]; Mountain Research Initiative; GCRF [ES/P011500/1]
   Funding Source: UKRI
FX We thank the mountain experts from the Mountain Sentinels Collaborative
   Network who contributed survey data. This work was supported by NSF
   grant #DEB-1414106 and the Mountain Research Initiative.
CR Adhikari B, 2017, DISASTER MED PUBLIC, V11, P625, DOI 10.1017/dmp.2016.195
   Adhikari B, 2016, FRONT PUBLIC HEALTH, V4, DOI 10.3389/fpubh.2016.00121
   ADPC, 2017, DIS EC
   Alcántara-Ayala I, 2016, J MT SCI-ENGL, V13, P2079, DOI 10.1007/s11629-015-3823-0
   Alexander DE, 2013, NAT HAZARD EARTH SYS, V13, P2707, DOI 10.5194/nhess-13-2707-2013
   Allen KM, 2006, DISASTERS, V30, P81, DOI 10.1111/j.1467-9523.2006.00308.x
   [Anonymous], 2018, EM DAT EM EV DAT
   [Anonymous], 2015, SFDRR SENDAI FRAMEWO
   [Anonymous], HIMALAYA
   [Anonymous], 2015, EC HUM IMP DIS LAST
   [Anonymous], IRIN NEWS
   [Anonymous], 2009, NSDRM NATL STRATEGY
   Baharmand H, 2017, INT J DISAST RISK RE, V24, P549, DOI 10.1016/j.ijdrr.2017.07.007
   Beniston M, 2003, CLIMATIC CHANGE, V59, P5, DOI 10.1023/A:1024458411589
   Bennike R. B, 2017, Himalaya: The Journal of the Association for Nepal and Himalayan Studies, V37, P55
   Brain KA, 2017, EXTRACT IND SOC, V4, P410, DOI 10.1016/j.exis.2017.03.001
   Brink E, 2016, GLOBAL ENVIRON CHANG, V36, P111, DOI 10.1016/j.gloenvcha.2015.11.003
   Brunson J, 2017, MATERN CHILD HLTH J, V21, P2267, DOI 10.1007/s10995-017-2350-8
   Buckley D, 2015, LESSON RISKS CLIMATE
   Budhathoki SS, 2017, J FAM PLAN REPROD H, V43, P157, DOI 10.1136/jfprhc-2016-101481
   Byers A.C., 2015, POSTEARTHQUAKE ASSES
   Byers AC, 2014, GEOGRAPHY, V99, P143
   Carpenter S, 2016, DISASTERS, V40, P411, DOI 10.1111/disa.12164
   Chaudhary P, 2017, REPROD HEALTH MATTER, V25, P25, DOI 10.1080/09688080.2017.1405664
   Crane O, 2017, HEALTH POLICY PLANN, V32, P48, DOI 10.1093/heapol/czx115
   Cutter SL, 2015, NATURE, V522, P277, DOI 10.1038/522277a
   Cutter SL, 2008, GLOBAL ENVIRON CHANG, V18, P598, DOI 10.1016/j.gloenvcha.2008.07.013
   Daly P, 2017, ENVIRON URBAN, V29, P403, DOI 10.1177/0956247817721403
   Das P, 2013, CASE STUDIES FLASH F
   Doswald N, 2014, CLIM DEV, V6, P185, DOI 10.1080/17565529.2013.867247
   ESPARZA AX, J PLAN ED RES, V20, P23
   Estrella M, 2013, ROLE ECOSYSTEM MANAG
   FAO-Food and Agriculture Organization of the United Nations, 2015, Mapping the vulnerability of mountain peoples to food insecurity
   Gallen SF, 2017, TECTONOPHYSICS, V714, P173, DOI 10.1016/j.tecto.2016.10.031
   Ghale S., 2015, HEART MATTER
   Global Administrative Areas, 2018, GADM DAT GLOB ADM AR
   Greene MC, 2017, CONFL HEALTH, V11, DOI 10.1186/s13031-017-0123-z
   Gyawali B, 2017, DISASTER MED PUBLIC, V11, P153, DOI 10.1017/dmp.2016.121
   Hall ML, 2017, PUBLIC HEALTH, V145, P39, DOI 10.1016/j.puhe.2016.12.031
   Hopping KA, 2016, ECOL SOC, V21, DOI 10.5751/ES-08009-210125
   Hu YJ, 2017, GEOGR ANAL, V49, P175, DOI 10.1111/gean.12117
   Huairou Commission, 2015, GLOB COMM RES FUND
   IPCC SR15, 2018, SUMM POL MAK SPEC RE
   Kargel JS, 2016, SCIENCE, V351, DOI 10.1126/science.aac8353
   Karkee R, 2016, FRONT PUBLIC HEALTH, V4, DOI 10.3389/fpubh.2016.00177
   Keiler M, 2010, PHILOS T R SOC A, V368, P2461, DOI 10.1098/rsta.2010.0047
   Klein J.A., EARTHS FUT
   Klein JA, 2014, GLOBAL ENVIRON CHANG, V28, P141, DOI 10.1016/j.gloenvcha.2014.03.007
   Kohler Thomas., 2014, Mountains and climate chance. A global concern
   Korner C., 2005, MILLENIUM ECOSYSTEM, P681
   Körner C, 2017, ALPINE BOT, V127, P1, DOI 10.1007/s00035-016-0182-6
   Lee ACK, 2016, PUBLIC HEALTH, V133, P99, DOI 10.1016/j.puhe.2016.01.007
   Liang GL, 2016, NAT HAZARDS, V81, P1385, DOI 10.1007/s11069-015-2127-6
   Maharajan A., 2017, 4 HIAWARE
   Mat Ministry of Labourr and Employment, 2014, LAB MIGR EMPL
   Mercer J, 2010, DISASTERS, V3-1, P214
   Mishra A, 2017, INT J DISAST RISK RE, V22, P167, DOI 10.1016/j.ijdrr.2017.03.008
   Murton G, 2016, EURASIAN GEOGR ECON, V57, P403, DOI 10.1080/15387216.2016.1236349
   Nelson A., 2015, CLASSQUAKE WHAT GLOB
   Newnham E, 2015, COMMUNITY ENGAGEMENT
   Oliver-Smith A, 2017, INT J DISAST RISK RE, V22, P469, DOI 10.1016/j.ijdrr.2016.10.006
   Ostrom E, 2009, SCIENCE, V325, P419, DOI 10.1126/science.1172133
   Pepin N, 2015, NAT CLIM CHANGE, V5, P424, DOI [10.1038/nclimate2563, 10.1038/NCLIMATE2563]
   Rasul G., 2015, STRATEGIC FRAMEWORK
   [Renaud FabriceG. UNU (United Nations University) UNU (United Nations University)], 2013, The Role of Ecosystems in Disaster Risk Reduction
   Reyers B, 2015, P NATL ACAD SCI USA, V112, P7362, DOI 10.1073/pnas.1414374112
   Shaw R., 2003, The Australian Journal of Emergency Management, V18, P28
   Sherpa L.N., 2015, KATHMANDU POST  0803
   Sherpa P., 2017, HIMALAYA, V37
   Squier L, 2018, LIVING THREAT EARTHQ
   Sudmeier-Rieux KI, 2014, DISASTER PREV MANAG, V23, P67, DOI 10.1108/DPM-12-2012-0143
   Tengö M, 2017, CURR OPIN ENV SUST, V26-27, P17, DOI 10.1016/j.cosust.2016.12.005
   Trinity College University of Toronto, 2016, IS SHIM PRINC PROM Q
   Turner AG, 2012, NAT CLIM CHANGE, V2, P587, DOI 10.1038/NCLIMATE1495
   UN Women, 2011, WOM NAT DIS VIETN FA
   UNDP:United Nations Development Programme, 2015, MAK CAS EC BAS AD
   United Nations International Strategy for Disaster Reduction [UNISDR], 2009, Terminology On Disaster Risk Reduction
   USAID:United States Agency for International Development, 2015, HIGH MOUNT AD PARTN
   Wendelbo M., 2016, Report for European Institute for Asian Studies
   World Bank, 2013, ETH US SOC SAF NET D
   Wymann vonDach S., 2017, SAFER LIVES LIVELIHO
   Yeh ET, 2014, HUM ECOL, V42, P61, DOI 10.1007/s10745-013-9625-5
   Zimmermann M, 2015, MT RES DEV, V35, P195, DOI 10.1659/MRD-JOURNAL-D-15-00006.1
NR 83
TC 65
Z9 67
U1 9
U2 76
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
PD APR
PY 2019
VL 94
BP 143
EP 152
DI 10.1016/j.envsci.2018.12.034
PG 10
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA IH7GR
UT WOS:000474672500015
DA 2025-01-10
ER

PT S
AU Feja, K
   Lütje, S
   Neumann, L
   Mönter, L
   Otto, KH
   Siegmund, A
AF Feja, Katharina
   Luetje, Svenja
   Neumann, Lena
   Moenter, Leif
   Otto, Karl-Heinz
   Siegmund, Alexander
BE Filho, WL
   Lackner, B
   McGhie, H
TI Climate ChangeS Cities-A Project to Enhance Students' Evaluation and
   Action Competencies Concerning Climate Change Impacts on Cities
SO ADDRESSING THE CHALLENGES IN COMMUNICATING CLIMATE CHANGE ACROSS VARIOUS
   AUDIENCES
SE Climate Change Management
LA English
DT Article; Book Chapter
ID BEHAVIOR
AB Concerning the social acceptance and realization of adaptation strategies, a raising awareness on the impacts of climate change among the population is indispensable, especially among young people as future decision makers. In this context, the article presents the structure and implementation of the environmental education project "Klimawandel findet Stadt" (Climate changeS cities), carried out in cooperation between the universities of Bochum, Heidelberg and Trier. The project shall facilitate the development of students' evaluation and action competencies with regard to climate change consequences and sustainable adaptation strategies by using a new educational concept of climate change communication. It implies the design of learning modules with an emphasis on health and risk prevention, urban climate and planning, and urban ecology and biodiversity. External stakeholders, e.g. biological stations, environmental departments and municipal offices, are involved in the planning and implementation of the above mentioned modules leading to an enhanced cross-sectoral cooperation of institutions. The methodical approach of the project is based on the dialectical intertwining of a three-step approach of spheres, namely observation sphere, laboratory sphere and sphere of action. In the spheres, students are confronted cognitively and affectively with climate change. Thereby, students shall be enabled and motivated to understand, evaluate and communicate climate adaptation strategies. As the concept is so far only normatively justified, there is need for empirical evidence of its effectiveness. In order to address this need, three efficacy studies are designed. If the methodical-didactical concept proves to be efficient, it could be implemented as a new form of climate change communication in educational institutions.
C1 [Feja, Katharina; Otto, Karl-Heinz] Ruhr Univ, Dept Didact Geog, Univ Str 104, D-44799 Bochum, Germany.
   [Luetje, Svenja; Moenter, Leif] Univ Trier, Geog & Its Didact, Behring Str 21, D-54296 Trier, Germany.
   [Neumann, Lena; Siegmund, Alexander] Heidelberg Univ Educ, Res Grp Earth Observat rgeo, Dept Geog, Czernyring 22 11 12, D-69115 Heidelberg, Germany.
   [Siegmund, Alexander] Heidelberg Univ, Heidelberg Ctr Environm, Berliner Str 48, D-69120 Heidelberg, Germany.
   [Siegmund, Alexander] Heidelberg Univ, Inst Geog, Berliner Str 48, D-69120 Heidelberg, Germany.
C3 Ruhr University Bochum; Universitat Trier; Ruprecht Karls University
   Heidelberg; Ruprecht Karls University Heidelberg; Ruprecht Karls
   University Heidelberg
RP Neumann, L (corresponding author), Heidelberg Univ Educ, Res Grp Earth Observat rgeo, Dept Geog, Czernyring 22 11 12, D-69115 Heidelberg, Germany.
EM katharina.feja@rub.de; luetje@uni-trier.de;
   lena.neumann@ph-heidelberg.de
CR [Anonymous], 2022, Confronting Uncertainty in Climate Policy
   [Anonymous], 1990, OKOLOGISCHE PSYCHOLO
   [Anonymous], 2007, Climate Change 2007-The Physical Science Basis Contribution of Working Group I to the Fourth Assessment Report of the IPCC
   [Anonymous], 2015, MON 2015 DTSCH ANP K
   [Anonymous], 2014, Roadmap for Implementing the Global Action Programme on Education for Sustainable Development
   AUSUBEL DP, 1962, EDUC LEADERSHIP, V20, P113
   BfN-Federal Agency for Nature Conservation, 2006, BIOL VIELF KLIM GEF
   Bogner FX, 2012, FACHDIDAKTISCHE FORS, V2, P163
   BRUNER JS, 1961, HARVARD EDUC REV, V31, P21
   Chiari S., 2016, GW-Unterricht, V1, P5, DOI [https://doi.org/10.1553/gw-unterricht141s5, DOI 10.1553/GW-UNTERRICHT141S5]
   DESTATIS-Federal Statistical Office of Germany, 2016, STAT JB DEUTSCHL INT
   Edenhofer Ottmar, CLIMATE CHANGE 2014
   EEA, 2016, EEA report No 12/2016
   Federal Cabinet of Germany, 2008, GERM STRAT AD CLIM C
   Federal Cabinet of Germany, 2011, AD ACT PLAN GERM STR
   Fishbein M, 1997, SOZIALPSYCHOLOGIE EI
   German Advisory Council on Global Change, 2011, WORLD TRANS SOC CONT
   German Geographical Society (DGfG), 2014, BILD FACH GEOGR MITT
   Hemmer I, 2010, GEOGRAPHIEDIDAKTISCH
   Jacobeit J, 2007, KLIMAWANDEL EINBLICK, P1
   Kaiser F.G., 2008, Umweltpsychologie, V12, P56
   Kaiser FG, 1998, J APPL SOC PSYCHOL, V28, P395, DOI 10.1111/j.1559-1816.1998.tb01712.x
   Kaiser FG, 2004, PERS INDIV DIFFER, V36, P1531, DOI 10.1016/j.paid.2003.06.003
   Kaiser FG, 2007, J ENVIRON PSYCHOL, V27, P242, DOI 10.1016/j.jenvp.2007.06.004
   Katzenstein H, 1995, UMWELTBEWUSSTSEIN UM
   KM-BW-Ministry of Education Youth and Sports Baden-Wuerttemberg, 2016, GEM BILD SEK BILD 20
   Lazonder AW, 2016, REV EDUC RES, V86, P681, DOI 10.3102/0034654315627366
   Lehmann J., 1999, Befunde empirischer Forschung zu Umweltbildung und Umweltbewusstsein
   Lewin K., 1936, A dynamic theory of personality
   Li M, 2017, ZWEITSPRACHFORDERUNG
   McClelland DC, 1987, CUP ARCH
   Milner J, 2012, CURR OPIN ENV SUST, V4, P398, DOI 10.1016/j.cosust.2012.09.011
   Moser SC, 2014, WIRES CLIM CHANGE, V5, P337, DOI 10.1002/wcc.276
   Moser SC, 2010, WIRES CLIM CHANGE, V1, P31, DOI 10.1002/wcc.11
   Murray H.A., 1938, EXPORATIONS PERSONAL
   MWWK-RLP-Ministry of Education Science Further Education and Culture of Rhineland-Palatinate, 2016, LEHRPL GES FACH ERDK
   Otto K.-H., 2012, GEOGRAPHIEDIDAKTIK T, P133
   PEW (PEW Research Center), 2017, Globally, People Point to ISIS and Climate Change as Leading Security Threats
   Rheinberg F, 2001, DIAGNOSTICA, V47, P57, DOI 10.1026//0012-1924.47.2.57
   Rheinberg Falko:., 2004, Motivationsdiagnostik
   Schick A., 2001, Lexikon Nachhaltiges Wirtschaften
   Schon L-H, 2011, EMPIRISCHE FUNDIERUN, V1, P7
   United Nations, 2017, New Urban Agenda
   United Nations Educational Scientific and Cultural Organisation (UNESCO), 2020, ED SUST DEV ROADM
   Vollmeyer R, 2005, MOTIVATIONSPSYCHOLOG, P9
   WBGU, 2016, Humanity on the Move: Unlocking the Transformative Power of Cities
   Wilde M., 2009, Z F R DIDAKTIK NATUR, V15, P31, DOI DOI 10.5771/9783845220314-31
   Wilhelmi V, 2011, PRAXIS GEOGRAPHIE, V2, P4
   Winiwarter Verena, 2008, UMWELTVERHALTEN GESC, P158
   Wittig R, 2012, KLIMAWANDEL BIODIVER, P290
   ,, 2017, EEA Report
NR 51
TC 4
Z9 4
U1 3
U2 4
PU SPRINGER INTERNATIONAL PUBLISHING AG
PI CHAM
PA GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
SN 1610-2010
BN 978-3-319-98294-6; 978-3-319-98293-9
J9 CLIM CHANG MANAG
PY 2019
BP 159
EP 174
DI 10.1007/978-3-319-98294-6_11
D2 10.1007/978-3-319-98294-6
PG 16
WC Communication; Environmental Studies
WE Book Citation Index – Social Sciences & Humanities (BKCI-SSH)
SC Communication; Environmental Sciences & Ecology
GA BT0II
UT WOS:000788001200012
DA 2025-01-10
ER

PT J
AU Hublin, JJ
AF Hublin, J. J.
TI The origin of Neandertals
SO PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF
   AMERICA
LA English
DT Article
DE Acheulean; climate; Homo heidelbergensis; Homo sapiens; Pleistocene
ID POPULATION-STRUCTURE; MIDDLE PLEISTOCENE; COLD ADAPTATION; EVOLUTION;
   HOMININ; HOMO; ATAPUERCA-TD6; DIVERSITY; SIMA
AB Western Eurasia yielded a rich Middle (MP) and Late Pleistocene (LP) fossil record documenting the evolution of the Neandertals that can be analyzed in light of recently acquired paleogenetical data, an abundance of archeological evidence, and a well-known environmental context. Their origin likely relates to an episode of recolonization of Western Eurasia by hominins of African origin carrying the Acheulean technology into Europe around 600 ka. An enhancement of both glacial and interglacial phases may have played a crucial role in this event, as well as in the subsequent evolutionary history of the Western Eurasian populations. In addition to climatic adaptations and an increase in encephalization, genetic drift seems to have played a major role in their evolution. To date, a clear speciation event is not documented, and the most likely scenario for the fixation of Neandertal characteristics seems to be an accretion of features along the second half of the MP. Although a separation time for the African and Eurasian populations is difficult to determine, it certainly predates OIS 11 as phenotypic Neandertal features are documented as far back as and possibly before this time. It is proposed to use the term "Homo rhodesiensis" to designate the large-brained hominins ancestral to H. sapiens in Africa and at the root of the Neandertals in Europe, and to use the term "Homo neanderthalensis" to designate all of the specimens carrying derived metrical or non-metrical features used in the definition of the LP Neandertals.
C1 Max Planck Inst Evolutionary Anthropol, D-04103 Leipzig, Germany.
C3 Max Planck Society
RP Hublin, JJ (corresponding author), Max Planck Inst Evolutionary Anthropol, D-04103 Leipzig, Germany.
EM hublin@eva.mpg.de
CR ANTONIO R, 1998, GEOBIOS, V31, P687
   Arsuaga JL, 1997, J HUM EVOL, V33, P219, DOI 10.1006/jhev.1997.0133
   BAILEY SE, 2002, THESIS ARIZ STATE, P236
   Bermudez De Castro J. M., 1997, Science (Washington D C), V276, P1392, DOI 10.1126/science.276.5317.1392
   de Castro JM, 2008, J HUM EVOL, V55, P729, DOI 10.1016/j.jhevol.2008.03.006
   Bischoff JL, 2007, J ARCHAEOL SCI, V34, P763, DOI 10.1016/j.jas.2006.08.003
   BRAUER G, 1989, HUMAN REVOLUTION, P123
   Bruner E, 2003, P NATL ACAD SCI USA, V100, P15335, DOI 10.1073/pnas.2536671100
   Bruner E, 2007, VERTEBR PALEOBIOL PA, P23
   Carbonell E, 2005, P NATL ACAD SCI USA, V102, P5674, DOI 10.1073/pnas.0501841102
   Carbonell E, 2008, NATURE, V452, P465, DOI 10.1038/nature06815
   Churchill SE, 2007, VERTEBR PALEOBIOL PA, P113
   de León MSP, 2001, NATURE, V412, P534, DOI 10.1038/35087573
   Dean D, 1998, J HUM EVOL, V34, P485, DOI 10.1006/jhev.1998.0214
   Dennell R, 1996, ANTIQUITY, V70, P535, DOI 10.1017/S0003598X00083691
   Foley R, 1997, CAMB ARCHAEOL J, V7, P3, DOI 10.1017/S0959774300001451
   Gagneux P, 1999, P NATL ACAD SCI USA, V96, P5077, DOI 10.1073/pnas.96.9.5077
   Green RE, 2008, CELL, V134, P416, DOI 10.1016/j.cell.2008.06.021
   Gunz P, 2009, P NATL ACAD SCI USA, V106, P6094, DOI 10.1073/pnas.0808160106
   Harvati K, 2004, P NATL ACAD SCI USA, V101, P1147, DOI 10.1073/pnas.0308085100
   HARVATI K, 2009, J HUM EVOL IN PRESS
   Hawks JD, 2001, J HUM EVOL, V40, pA10
   Helmke JP, 2003, QUATERNARY SCI REV, V22, P1717, DOI 10.1016/S0277-3791(03)00126-4
   Helmke JP, 2003, J QUATERNARY SCI, V18, P183, DOI 10.1002/jqs.735
   Hoffecker JF., 2002, DESOLATE LANDSCAPES
   Holliday TW, 1997, AM J PHYS ANTHROPOL, V104, P245, DOI 10.1002/(SICI)1096-8644(199710)104:2<245::AID-AJPA10>3.0.CO;2-#
   Hrdlicka A, 1927, J R ANTHROPOL INST G, V57, P249, DOI 10.2307/2843704
   Hublin J.-J., 2001, HUMAN ROOTS AFRICA A, P99
   Hublin JJ, 2009, CR PALEVOL, V8, P503, DOI 10.1016/j.crpv.2009.04.001
   Hublin JJ, 1998, NEANDERTALS AND MODERN HUMANS IN WESTERN ASIA, P295
   HUBLIN JJ, 1988, HOMME NEANDERTAL ANA, P81
   Imbrie J., 1984, Milankovitch and Climate: Understanding the Response to Astronomical Forcing, -, V1, P269
   Krause J, 2007, NATURE, V449, P902, DOI 10.1038/nature06193
   LANDE R, 1979, EVOLUTION, V33, P1210
   LIEBERMAN D, EVOLUTION H IN PRESS
   Loutre MF, 2003, EARTH PLANET SC LETT, V212, P213, DOI 10.1016/S0012-821X(03)00235-8
   Martinón-Torres M, 2007, P NATL ACAD SCI USA, V104, P13279, DOI 10.1073/pnas.0706152104
   MARTINONTORRES M, 2005, DENT PERSPECTIVES HU, P65
   Mounier A, 2009, J HUM EVOL, V56, P219, DOI 10.1016/j.jhevol.2008.12.006
   Noonan JP, 2006, SCIENCE, V314, P1113, DOI 10.1126/science.1131412
   Parfitt SA, 2005, NATURE, V438, P1008, DOI 10.1038/nature04227
   Poli MS, 2000, GEOLOGY, V28, P807, DOI 10.1130/0091-7613(2000)028<0807:MSCINA>2.3.CO;2
   Premo LS, 2009, P NATL ACAD SCI USA, V106, P33, DOI 10.1073/pnas.0809194105
   Richards MP, 2009, P NATL ACAD SCI USA, V106, P16034, DOI 10.1073/pnas.0903821106
   Rightmire GP, 2008, EVOL ANTHROPOL, V17, P8, DOI 10.1002/evan.20160
   Rightmire GP, 1998, EVOL ANTHROPOL, V6, P218, DOI 10.1002/(SICI)1520-6505(1998)6:6<218::AID-EVAN4>3.0.CO;2-6
   ROGERS AR, 1983, GENETICS, V105, P985
   Rosas A, 2007, VERTEBR PALEOBIOL PA, P37
   ROUGLER H, 2003, ETUDE DESCRIPTIVE CO, P424
   Serre D, 2004, PLOS BIOL, V2, P313, DOI 10.1371/journal.pbio.0020057
   Smith TM, 2007, P NATL ACAD SCI USA, V104, P20220, DOI 10.1073/pnas.0707051104
   Steegmann AT, 2002, AM J HUM BIOL, V14, P566, DOI 10.1002/ajhb.10070
   Stiner MC, 2006, HUM ECOL, V34, P693, DOI 10.1007/s10745-006-9041-1
   Stringer CB, 1999, J HUM EVOL, V37, P873, DOI 10.1006/jhev.1999.0367
   STRINGER CB, 1994, INTERD CONT, P149
   Tattersall I, 2000, EVOL ANTHROPOL, V9, P2, DOI 10.1002/(SICI)1520-6505(2000)9:1<2::AID-EVAN2>3.0.CO;2-2
   Tuffreau A., 1995, DEFINITION INTERPRET, P413
   Turq A., 1996, Paleo Revista Archeological Prehistorique, V8, P161, DOI 10.3406/pal.1996.911
   Weaver TD, 2008, P NATL ACAD SCI USA, V105, P4645, DOI 10.1073/pnas.0709079105
   Weaver TD, 2007, J HUM EVOL, V53, P135, DOI 10.1016/j.jhevol.2007.03.001
   Weaver TD, 2009, P NATL ACAD SCI USA, V106, P8151, DOI 10.1073/pnas.0812554106
   White M, 2003, CURR ANTHROPOL, V44, P598, DOI 10.1086/377653
   Wolpoff MH, 2009, AM J PHYS ANTHROPOL, V139, P91, DOI 10.1002/ajpa.20930
   Woodward AS, 1921, NATURE, V108, P371, DOI 10.1038/108371a0
NR 64
TC 322
Z9 355
U1 1
U2 122
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 22
PY 2009
VL 106
IS 38
BP 16022
EP 16027
DI 10.1073/pnas.0904119106
PG 6
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI); Arts &amp; Humanities Citation Index (A&amp;HCI)
SC Science & Technology - Other Topics
GA 497PF
UT WOS:000270071600007
PM 19805257
OA Green Published, Bronze
DA 2025-01-10
ER

PT J
AU Bonfanti, J
   Hedde, M
   Cortet, J
   Krogh, PH
   Larsen, KS
   Holmstrup, M
AF Bonfanti, Jonathan
   Hedde, Mickael
   Cortet, Jerome
   Krogh, Paul Henning
   Larsen, Klaus S.
   Holmstrup, Martin
TI Communities of Collembola show functional resilience in a long-term
   field experiment simulating climate change
SO PEDOBIOLOGIA
LA English
DT Article
DE Trait; Climate change; Collembola; Community-weighted mean; Resilience;
   Soil fauna
ID BELOW-GROUND BIODIVERSITY; BODY-SIZE; SOIL INVERTEBRATES; ATMOSPHERIC
   CO2; RESPONSES; TEMPERATURE; DIVERSITY; TRAITS; SPRINGTAIL; DROUGHT
AB Soil ecosystems, and the fauna they host, are known to provide many services and communities of Collembola can be used as bioindicators of soil functionality. Climate change is often expected to threaten Collembola, however, it is possible that it could also favour them. Previous studies have shown that the structure of collembolan communities can be shaped by long-term adaptation to climate, and that temperature plays a major role in the variation of species traits. In this study, we evaluated how the functional composition and structure of collembolan communities are impacted by climate change using an experimental climate manipulation design. The study used data from the CLIMAITE experiment, which was carried out in Denmark in an unmanaged heath/grassland ecosystem that was subjected to the simulated predicted climate for the year 2075. The climate manipulation experiment parameters included elevated temperature, elevated concentration of atmospheric CO2 and extended drought, which were tested alone and in combination on a total of 48 plots, including controls. Collembola were sampled using 10-cm-depth soil cores after 1, 2 and 8 years of climate manipulation. We posited (i) that a stimulating factor (elevated CO2) would increase mean body length, and (ii) that an inhibiting factor (drought) would favour traits indicating a euedaphic life or an ability to present resistance mechanisms (scales, ecomorphosis) and would reduce functional structure indices through environmental filtering. The results did not support these hypotheses. While the findings showed sporadic effects of the climatic treatments on the functional composition and structure, they did not demonstrate any general community response pattern. This may be due to limitations of the study in terms of climatic intensity or community assembly, opening perspectives for future experiments in terms of the choice of traits and measurements.
C1 [Bonfanti, Jonathan; Cortet, Jerome] Univ Paul Valery Montpellier 3, CEFE, Univ Montpellier, CNRS,EPHE,IRD, Montpellier, France.
   [Hedde, Mickael] Univ Montpellier, CIRAD, IRD, Eco&Sols,INRAE,Montpellier SupAgro, Montpellier, France.
   [Krogh, Paul Henning; Holmstrup, Martin] Aarhus Univ, Dept Ecosci, Vejlsovej 25, DK-8600 Silkeborg, Denmark.
   [Larsen, Klaus S.] Univ Copenhagen, Dept Geosci & Nat Resource Management, Rolighedsvej 23, DK-1958 Frederiksberg, Denmark.
C3 Universite PSL; Ecole Pratique des Hautes Etudes (EPHE); Institut Agro;
   Montpellier SupAgro; CIRAD; Centre National de la Recherche Scientifique
   (CNRS); Institut de Recherche pour le Developpement (IRD); Universite
   Paul-Valery; Universite de Montpellier; INRAE; Institut Agro;
   Montpellier SupAgro; CIRAD; Institut de Recherche pour le Developpement
   (IRD); Universite de Montpellier; Aarhus University; University of
   Copenhagen
RP Bonfanti, J (corresponding author), Univ Paul Valery Montpellier 3, CEFE, Batiment J,Route Mende, F-34199 Montpellier, France.
EM jonathan.bonfanti@gmail.com
RI Holmstrup, Martin/E-8731-2017; Holmstrup, Martin/I-7463-2013; Krogh,
   Paul Henning/B-3566-2009; Hedde, Mickael/K-5195-2016; Larsen, Klaus
   Steenberg/C-7549-2015
OI Bonfanti, Jonathan/0000-0003-0049-4410; Holmstrup,
   Martin/0000-0001-8395-6582; Krogh, Paul Henning/0000-0003-2033-553X;
   Hedde, Mickael/0000-0002-6733-3622; Larsen, Klaus
   Steenberg/0000-0002-1421-6182; Cortet, Jerome/0000-0002-7410-8626
FU Universite Paul-Valery Montpellier 3; Villum Foundation; Air Liquide
   Denmark A/S; DONG Energy; INCREASE project ('Integrated Network on
   Climate-change Research Activities on Shrubland Ecosystems') [227628]
FX JB received a PhD grant from Universit ' e Paul-Val ' ery Montpellier 3.
   The CLIMAITE experiment was supported by the Villum Foundation, Air
   Liquide Denmark A/S, DONG Energy and the INCREASE project (`Integrated
   Network on Climate-change Research Activities on Shrubland Ecosystems')
   (EC FP7-Infrastructure-2008-1 Grant Agreement 227628). The authors would
   like to thank all the BETSI database project managers and contributors.
   JB is grateful for the constructive remarks on the preliminary results
   from his colleagues during the TEBIS network annual meeting and the SFE2
   2018 International Conference on Ecological Sciences. The authors would
   also like to thank Zdenek Gavor for his helpful expertise on Collembola
   identification. We are thankful to C. Barreto and Z. Lindo for leading
   this special issue and to the reviewers who helped us improving our
   manuscript.
CR Angilletta MJ, 2009, BIO HABIT, P1, DOI 10.1093/acprof:oso/9780198570875.001.1
   [Anonymous], 2001, CLIMATE CHANGE 2001, DOI DOI 10.1256/004316502320517344
   [Anonymous], 2017, R PACKAGE VERSION
   [Anonymous], 1997, BIOL SPRINGTAILS INS
   Bahrndorff S, 2006, J INSECT PHYSIOL, V52, P951, DOI 10.1016/j.jinsphys.2006.06.005
   Bardgett RD, 2014, NATURE, V515, P505, DOI 10.1038/nature13855
   Barreto C, 2021, PEDOBIOLOGIA, V89, DOI 10.1016/j.pedobi.2021.150772
   Bates D, 2015, J STAT SOFTW, V67, P1, DOI 10.18637/jss.v067.i01
   Berg MP, 2013, SOIL ECOLOGY AND ECOSYSTEM SERVICES, P136
   Birkemoe T, 2000, FUNCT ECOL, V14, P693, DOI 10.1046/j.1365-2435.2000.00478.x
   Blankinship JC, 2011, OECOLOGIA, V165, P553, DOI 10.1007/s00442-011-1909-0
   Block W, 1996, EUR J ENTOMOL, V93, P325
   Bonfanti J., 2021, THESIS U PAUL VALERY
   Bonfanti J, 2018, FUNCT ECOL, V32, P2562, DOI 10.1111/1365-2435.13194
   Bradford MA, 2016, NAT CLIM CHANGE, V6, P751, DOI [10.1038/NCLIMATE3071, 10.1038/nclimate3071]
   Brown JH, 2004, ECOLOGY, V85, P1771, DOI 10.1890/03-9000
   Carapelli A, 2001, ZOOL SCR, V30, P115, DOI 10.1046/j.1463-6409.2001.00055.x
   Cassagnau Paul, 1974, 9 CONGRESSO NAZIONAL, P227
   Chase JM, 2014, J VEG SCI, V25, P319, DOI 10.1111/jvs.12159
   Cornwell WK, 2006, ECOLOGY, V87, P1465, DOI 10.1890/0012-9658(2006)87[1465:ATTFHF]2.0.CO;2
   Cortet J, 1998, ACTA OECOL, V19, P413, DOI 10.1016/S1146-609X(98)80047-7
   da Silva PM, 2016, APPL SOIL ECOL, V97, P69, DOI 10.1016/j.apsoil.2015.07.018
   Deutsch CA, 2008, P NATL ACAD SCI USA, V105, P6668, DOI 10.1073/pnas.0709472105
   Dietzen CA, 2019, GLOBAL CHANGE BIOL, V25, P2970, DOI 10.1111/gcb.14699
   Dunger W., 2011, SYNOPSES PALAEARCT 1
   Fjellberg A., 2007, FAUNA ENTOMOL SCAD, V42, P1, DOI 10.1163/ej.9789004157705.i-265
   Fjellberg A., 1998, The Collembola of Fennoscandia and Denmark, Part I: Poduromorpha, Fauna entomologica Scandinavica
   Fox J., 2018, An R Companion to Applied Regression
   Garnier E, 2004, ECOLOGY, V85, P2630, DOI 10.1890/03-0799
   Gisin H., 1960, Collembolenfauna Europas
   Griffiths HM, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0145598
   Haugwitz MS, 2014, PLANT SOIL, V374, P211, DOI 10.1007/s11104-013-1855-1
   Hedde M, 2012, ENVIRON POLLUT, V164, P59, DOI 10.1016/j.envpol.2012.01.017
   Heemsbergen DA, 2004, SCIENCE, V306, P1019, DOI 10.1126/science.1101865
   Herrando-Pérez S, 2019, J ANIM ECOL, V88, P247, DOI 10.1111/1365-2656.12914
   Holmstrup M, 2002, J INSECT PHYSIOL, V48, P961, DOI 10.1016/S0022-1910(02)00175-0
   Holmstrup M, 2018, FUNCT ECOL, V32, P1304, DOI 10.1111/1365-2435.13058
   Holmstrup M, 2017, SCI REP-UK, V7, DOI 10.1038/srep41388
   Holmstrup M, 2015, EUR J SOIL BIOL, V70, P15, DOI 10.1016/j.ejsobi.2015.06.004
   Holmstrup M, 2014, J THERM BIOL, V45, P117, DOI 10.1016/j.jtherbio.2014.09.001
   Holmstrup M, 2013, J INSECT PHYSIOL, V59, P1104, DOI 10.1016/j.jinsphys.2013.08.015
   Hothorn T, 2008, BIOMETRICAL J, V50, P346, DOI 10.1002/bimj.200810425
   Briones MJI, 2009, SOIL BIOL BIOCHEM, V41, P315, DOI 10.1016/j.soilbio.2008.11.003
   IPCC (Intergovernmental Panel on Climate Change), 2018, Global Warming of 1.5C
   Joimel S, 2017, SCI TOTAL ENVIRON, V584, P614, DOI 10.1016/j.scitotenv.2017.01.086
   Jucevica E, 2006, PEDOBIOLOGIA, V50, P177, DOI 10.1016/j.pedobi.2005.10.006
   Kardol P, 2011, APPL SOIL ECOL, V47, P37, DOI 10.1016/j.apsoil.2010.11.001
   Krab EJ, 2013, SOIL BIOL BIOCHEM, V59, P16, DOI 10.1016/j.soilbio.2012.12.012
   Kærsgaard CW, 2004, J INSECT PHYSIOL, V50, P5, DOI 10.1016/j.jinsphys.2003.09.003
   Laliberté E, 2010, ECOLOGY, V91, P299, DOI 10.1890/08-2244.1
   Larsen K.S., 2019, METEOROLOGICAL SITE, DOI [10.17894/UCPH.E58A99C2-DA7B, DOI 10.17894/UCPH.E58A99C2-DA7B]
   Lavelle P, 2006, EUR J SOIL BIOL, V42, pS3, DOI 10.1016/j.ejsobi.2006.10.002
   Le S, 2008, J STAT SOFTW, V25, P1, DOI 10.18637/jss.v025.i01
   Liefting M, 2008, BIOL J LINN SOC, V94, P265, DOI 10.1111/j.1095-8312.2008.00969.x
   MACFADYEN A, 1961, J ANIM ECOL, V30, P171, DOI 10.2307/2120
   Meehan ML, 2020, PEDOBIOLOGIA, V83, DOI 10.1016/j.pedobi.2020.150672
   Mikkelsen TN, 2008, FUNCT ECOL, V22, P185, DOI 10.1111/j.1365-2435.2007.01362.x
   Moretti M, 2017, FUNCT ECOL, V31, P558, DOI 10.1111/1365-2435.12776
   Mouchet MA, 2010, FUNCT ECOL, V24, P867, DOI 10.1111/j.1365-2435.2010.01695.x
   Mouillot D, 2013, TRENDS ECOL EVOL, V28, P167, DOI 10.1016/j.tree.2012.10.004
   Pendall E, 2004, NEW PHYTOL, V162, P311, DOI 10.1111/j.1469-8137.2004.01053.x
   Pey B, 2014, BASIC APPL ECOL, V15, P194, DOI 10.1016/j.baae.2014.03.007
   Phillips HRP, 2017, NAT ECOL EVOL, V1, DOI 10.1038/s41559-017-0103
   Poinsot-Balaguer Nicole, 1990, SECHERESSE, V1, P265
   Potapow M., 2001, ABHANDLUNGEN BERICHT, V3, P1, DOI DOI 10.1016/J.APSOIL.2015.07.018
   Raffard A, 2019, BIOL REV, V94, P648, DOI 10.1111/brv.12472
   Raymond-Leónard LJ, 2019, SOIL BIOL BIOCHEM, V138, DOI 10.1016/j.soilbio.2019.107608
   Rezende EL, 2014, FUNCT ECOL, V28, P799, DOI 10.1111/1365-2435.12268
   Rillig MC, 2019, SCIENCE, V366, P886, DOI 10.1126/science.aay2832
   Rudis B., 2017, Ggalt: Extra coordinate systems, 'geoms', statistical transformations, scales and fonts for 'ggplot2
   Rustad LE, 2001, OECOLOGIA, V126, P543, DOI 10.1007/s004420000544
   Salmon S, 2014, SOIL BIOL BIOCHEM, V75, P73, DOI 10.1016/j.soilbio.2014.04.002
   Santorufo L, 2015, EUR J SOIL BIOL, V70, P46, DOI 10.1016/j.ejsobi.2015.07.003
   Schleuter D, 2010, ECOL MONOGR, V80, P469, DOI 10.1890/08-2225.1
   Schöb C, 2012, NEW PHYTOL, V196, P824, DOI 10.1111/j.1469-8137.2012.04306.x
   Siefert A, 2015, ECOL LETT, V18, P1406, DOI 10.1111/ele.12508
   Sjursen H, 2001, J INSECT PHYSIOL, V47, P1021, DOI 10.1016/S0022-1910(01)00078-6
   Sunday JM, 2012, NAT CLIM CHANGE, V2, P686, DOI 10.1038/NCLIMATE1539
   Tsiafouli MA, 2005, APPL SOIL ECOL, V29, P17, DOI 10.1016/j.apsoil.2004.10.002
   Ulrich W, 2010, GLOBAL ECOL BIOGEOGR, V19, P905, DOI 10.1111/j.1466-8238.2010.00565.x
   van der Wurff AWG, 2003, MOL ECOL, V12, P1349, DOI 10.1046/j.1365-294X.2003.01811.x
   van Dooremalen C, 2010, J INSECT PHYSIOL, V56, P178, DOI 10.1016/j.jinsphys.2009.10.002
   VERHOEF HA, 1983, HOLARCTIC ECOL, V6, P387
   Vestergård M, 2015, APPL SOIL ECOL, V92, P54, DOI 10.1016/j.apsoil.2015.03.002
   Villéger S, 2008, ECOLOGY, V89, P2290, DOI 10.1890/07-1206.1
   Violle C, 2007, OIKOS, V116, P882, DOI 10.1111/j.2007.0030-1299.15559.x
   Wall DH, 2008, GLOBAL CHANGE BIOL, V14, P2661, DOI 10.1111/j.1365-2486.2008.01672.x
   Wall DH, 2015, SCIENCE, V347, P695, DOI 10.1126/science.aaa8493
   Wang D, 2012, OECOLOGIA, V169, P1, DOI 10.1007/s00442-011-2172-0
   Warton DI, 2011, ECOLOGY, V92, P3, DOI 10.1890/10-0340.1
   Wickham H., 2016, GGPLOT2 ELEGANT GRAP, DOI DOI 10.1007/978-0-387-98141-3_1
   Wieczynski DJ, 2019, P NATL ACAD SCI USA, V116, P587, DOI 10.1073/pnas.1813723116
   Wolters V, 2000, BIOSCIENCE, V50, P1089, DOI 10.1641/0006-3568(2000)050[1089:EOGCOA]2.0.CO;2
   Woon JS, 2019, INSECT SOC, V66, P57, DOI 10.1007/s00040-018-0664-1
   Zimdars B., 1994, Synopses on palaearctic collembola, volume 1: Tullbergiinae
   Zinger L, 2019, MOL ECOL, V28, P528, DOI 10.1111/mec.14919
   Zoë LD, 2015, SOIL BIOL BIOCHEM, V91, P271, DOI 10.1016/j.soilbio.2015.09.003
NR 97
TC 7
Z9 8
U1 7
U2 60
PU ELSEVIER GMBH
PI MUNICH
PA HACKERBRUCKE 6, 80335 MUNICH, GERMANY
SN 0031-4056
EI 1873-1511
J9 PEDOBIOLOGIA
JI Pedobiologia
PD MAR
PY 2022
VL 90
AR 150789
DI 10.1016/j.pedobi.2022.150789
EA JAN 2022
PG 10
WC Ecology; Soil Science
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Agriculture
GA YP9XS
UT WOS:000748973600005
OA Green Published, Bronze
DA 2025-01-10
ER

PT J
AU Blackburn, HD
   Krehbiel, B
   Ericsson, SA
   Wilson, C
   Caetano, AR
   Paiva, SR
AF Blackburn, H. D.
   Krehbiel, B.
   Ericsson, S. A.
   Wilson, C.
   Caetano, A. R.
   Paiva, S. R.
TI A fine structure genetic analysis evaluating ecoregional adaptability of
   a <i>Bos taurus</i> breed (Hereford)
SO PLOS ONE
LA English
DT Article
ID ENVIRONMENT INTERACTION; CLIMATE-CHANGE; ZEBU CATTLE; MILES CITY; LINE
   1; GENOTYPE; ANCESTRY; TEMPERATURE; POPULATIONS; ADAPTATIONS
AB Ecoregional differences contribute to genetic environmental interactions and impact animal performance. These differences may become more important under climate change scenarios. Utilizing genetic diversity within a species to address such problems has not been fully explored. In this study Hereford cattle were genotyped with 50K Bead Chip or 770K Bovine Bead Chip to test the existence of genetic structure in five U.S. ecoregions characterized by precipitation, temperature and humidity and designated: cool arid (CA), cool humid (CH), transition zone (TZ), warm arid (WA), and warm humid (WH). SNP data were analyzed in three sequential analyses. Broad genetic structure was evaluated with STRUCTURE, and ADMIXTURE software using 14,312 SNPs after passing quality control variables. The second analysis was performed using principal coordinate analysis with 66 Tag SNPs associated in the literature with various aspects of environmental stressors (e.g., heat tolerance) or production (e.g., milk production). In the third analysis TreeSelect was used with the 66 SNPs to evaluate if ecoregional allelic frequencies deviated from a central frequency and by so doing are indicative of directional selection. The three analyses suggested subpopulation structures associated with ecoregions from where animals were derived. ADMIXTURE and PCA results illustrated the importance of temperature and humidity and confirm subpopulation assignments. Comparisons of allele frequencies with TreeSelect showed ecoregion differences, in particular the divergence between arid and humid regions. Patterns of genetic variability obtained by medium and high density SNP chips can be used to acclimatize a temperately derived breed to various ecoregions. As climate change becomes an important factor in cattle production, this study should be used as a proof of concept to review future breeding and conservation schemes aimed at adaptation to climatic events.
C1 [Blackburn, H. D.; Krehbiel, B.; Wilson, C.] USDA ARS, Natl Anim Germplasm Program, Ft Collins, CO 80522 USA.
   [Krehbiel, B.] Colorado State Univ, Dept Anim Sci, Ft Collins, CO 80523 USA.
   [Ericsson, S. A.] Sul Ross Univ, Alpine, TX USA.
   [Caetano, A. R.; Paiva, S. R.] EMBRAPA Recursos Genet & Biotechnol Brasilia, Brasilia, DF, Brazil.
   [Caetano, A. R.; Paiva, S. R.] EMBRAPA LABEX, Ft Collins, CO USA.
C3 United States Department of Agriculture (USDA); Colorado State
   University; Texas State University System; Empresa Brasileira de
   Pesquisa Agropecuaria (EMBRAPA)
RP Blackburn, HD (corresponding author), USDA ARS, Natl Anim Germplasm Program, Ft Collins, CO 80522 USA.
EM Harvey.Blackburn@ars.usda.gov
RI Paiva, Samuel/G-6404-2012
FU USDA-ARS; Dixon Water Foundation; Dixon Water Foundation (Marfa, TX)
FX USDA-ARS provided funding through there normal program funding to the
   National Animal Germplasm Program. The Dixon Water Foundation provided
   funds for genotyping a portion of the cattle. None of these funds were
   obtained via a competitive grant system. The American Hereford
   Association (Kansas City, MO) for providing pedigree and genomic
   information for this study; Dixon Water Foundation (Marfa, TX) for
   supporting a portion of the genotyping expenses; and Dr. Larry Kuehn
   ARS/USDA (Clay Center, NB) for contributing the Hereford genotypes from
   the "2000 Bull Project".
CR Alexander DH, 2009, GENOME RES, V19, P1655, DOI 10.1101/gr.094052.109
   [Anonymous], 1996, Food and Agriculture Organization of the United Nations (FAO) Animal Production and Health Paper No. 127
   Arguez A., 2012, 7 NCDC
   Arguez A, 2012, B AM METEOROL SOC, V93, P1687, DOI 10.1175/BAMS-D-11-00197.1
   Battisti DS, 2009, SCIENCE, V323, P240, DOI 10.1126/science.1164363
   Bhatia G, 2011, AM J HUM GENET, V89, P368, DOI 10.1016/j.ajhg.2011.07.025
   Blackburn H.D., 2014, P WORLD C GENETICS A
   Bohmanova J, 2008, J DAIRY SCI, V91, P840, DOI 10.3168/jds.2006-142
   Bohmanova J, 2007, J DAIRY SCI, V90, P1947, DOI 10.3168/jds.2006-513
   Bray TC, 2009, ANIM GENET, V40, P393, DOI 10.1111/j.1365-2052.2009.01850.x
   CARTWRIGHT TC, 1955, J ANIM SCI, V14, P350, DOI 10.2527/jas1955.142350x
   CARTWRIGHT TC, 1980, J ANIM SCI, V50, P1221, DOI 10.2527/jas1980.5061221x
   Cleveland MA, 2005, J ANIM SCI, V83, P992
   Collier RJ, 2008, J DAIRY SCI, V91, P445, DOI 10.3168/jds.2007-0540
   de Jong G, 2002, LIVEST PROD SCI, V78, P195, DOI 10.1016/S0301-6226(02)00096-9
   Easterling W, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P273
   Edea Zewdu, 2013, Frontiers in Genetics, V4, P35, DOI 10.3389/fgene.2013.00035
   Falconer D. S., INTRO QUANTITATIVE G, P464
   FRISCH JE, 1981, J AGR SCI-CAMBRIDGE, V96, P23, DOI 10.1017/S0021859600031841
   Gibbs RA, 2009, SCIENCE, V324, P528, DOI 10.1126/science.1167936
   Golden B.L., 1992, AGR EXPT STATION TEC
   Hammond AC, 1996, J ANIM SCI, V74, P295
   Hansen PJ, 2004, ANIM REPROD SCI, V82-3, P349, DOI 10.1016/j.anireprosci.2004.04.011
   Hayes BJ, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0006676
   Hoffmann I, 2010, ANIM GENET, V41, P32, DOI 10.1111/j.1365-2052.2010.02043.x
   Hu ZL, 2013, NUCLEIC ACIDS RES, V41, pD871, DOI 10.1093/nar/gks1150
   KOGER M, 1979, J ANIM SCI, V49, P396, DOI 10.2527/jas1979.492396x
   Kopelman NM, 2015, MOL ECOL RESOUR, V15, P1179, DOI 10.1111/1755-0998.12387
   Kuehn LA, 2011, J ANIM SCI, V89, P1742, DOI 10.2527/jas.2010-3530
   LCI, 1970, PATT TRANS LOSS
   Leesburg VLR, 2014, J ANIM SCI, V92, P2387, DOI 10.2527/jas.2013-6890
   Lin BZ, 2010, ANIM SCI J, V81, P281, DOI 10.1111/j.1740-0929.2010.00744.x
   MacNeil MD, 2009, J ANIM SCI, V87, P2489, DOI 10.2527/jas.2009-1909
   Mattar M, 2011, J ANIM SCI, V89, P2349, DOI 10.2527/jas.2010-3770
   Menne MJ, 2012, J ATMOS OCEAN TECH, V29, P897, DOI 10.1175/JTECH-D-11-00103.1
   Nardone A, 2010, LIVEST SCI, V130, P57, DOI 10.1016/j.livsci.2010.02.011
   Norman HD, 2005, J DAIRY SCI, V88, P812, DOI 10.3168/jds.S0022-0302(05)72746-6
   O'Neill CJ, 2010, EVOL APPL, V3, P422, DOI 10.1111/j.1752-4571.2010.00151.x
   PAHNISH OF, 1985, J ANIM SCI, V61, P1146, DOI 10.2527/jas1985.6151146x
   Peakall R, 2012, BIOINFORMATICS, V28, P2537, DOI 10.1093/bioinformatics/bts460
   Peel MC, 2007, HYDROL EARTH SYST SC, V11, P1633, DOI 10.5194/hess-11-1633-2007
   Pritchard JK, 2000, GENETICS, V155, P945
   REYNOLDS WL, 1980, J ANIM SCI, V51, P860, DOI 10.2527/jas1980.514860x
   Robinson TP, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0096084
   SCOTT IM, 1983, INT J BIOMETEOROL, V27, P47, DOI 10.1007/BF02186300
   Seo SN, 2008, AGR ECON-BLACKWELL, V38, P151, DOI 10.1111/j.1574-0862.2008.00289.x
   WHEELER TL, 1990, J ANIM SCI, V68, P3677
   Wright S., 1932, P 6 INT C GEN, VI, P355
NR 48
TC 19
Z9 22
U1 0
U2 0
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 MAY 1
PY 2017
VL 12
IS 5
AR e0176474
DI 10.1371/journal.pone.0176474
PG 15
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA ET9RJ
UT WOS:000400645000035
PM 28459870
OA Green Published, gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Kovac, H
   Käfer, H
   Petrocelli, I
   Stabentheiner, A
AF Kovac, Helmut
   Kaefer, Helmut
   Petrocelli, Iacopo
   Stabentheiner, Anton
TI Comparison of thermal traits of <i>Polistes dominula</i> and <i>Polistes
   gallicus</i>, two European paper wasps with strongly differing
   distribution ranges
SO JOURNAL OF COMPARATIVE PHYSIOLOGY B-BIOCHEMICAL SYSTEMIC AND
   ENVIRONMENTAL PHYSIOLOGY
LA English
DT Article
DE Polistes dominula; Polistes gallicus; Thermal limits; Metabolic rate;
   Body temperature; Environment
ID ISOLATED HONEYBEES HYMENOPTERA; GLOSSINA-PALLIDIPES DIPTERA; INSECT
   COLD-HARDINESS; METABOLIC-RATE; DROSOPHILA-MELANOGASTER;
   GEOGRAPHIC-VARIATION; CHILL-COMA; WATER-LOSS; METHODOLOGICAL CONTEXT;
   TEMPERATURE TOLERANCE
AB The two paper wasps, Polistes dominula and Polistes gallicus, are related species with strongly differing distribution ranges. We investigated thermal tolerance traits (critical thermal limits and metabolic response to temperature) to gain knowledge about physiological adaptations to their local climate conditions and to get evidence for the reasons of P. dominula's successful dispersion. Body and ambient temperature measurements at the nests revealed behavioural adaptations to microclimate. The species differed clearly in critical thermal minimum (P. dominula -1.4 degrees C, P. gallicus -0.4 degrees C), but not significantly in critical thermal maximum of activity (P. dominula 47.1 degrees C, P. gallicus 47.6 degrees C). The metabolic response did not reveal clear adaptations to climate conditions. At low and high temperatures, the metabolic rate of P. dominula was higher, and at intermediate temperatures, we determined higher values in P. gallicus. However, the species exhibited remarkably differing thermoregulatory behaviour at the nest. On average, P. gallicus tolerated a thoracic temperature up to similar to 41 degrees C, whereas P. dominula already tried at similar to 37 degrees C to keep the thorax below ambient temperature. We suggest this to be an adaptation to the higher mean ambient temperature we measured at the nest during a breeding season. Although we determined for P. dominula a 0.5 degrees C larger thermal tolerance range, we do not presume this parameter to be solely responsible for the successful distribution of P. dominula. Additional factors, such as the thermal tolerance of the queens could limit the overwintering success of P. gallicus in a harsher climate.
C1 [Kovac, Helmut; Kaefer, Helmut; Stabentheiner, Anton] Karl Franzens Univ Graz, Inst Zool, Univ Pl 2, A-8010 Graz, Austria.
   [Petrocelli, Iacopo] Univ Florence, Dipartimento Biol, Via Madonna del Piano 6, I-50019 Sesto Fiorentino, Italy.
C3 University of Graz; University of Florence
RP Kovac, H; Stabentheiner, A (corresponding author), Karl Franzens Univ Graz, Inst Zool, Univ Pl 2, A-8010 Graz, Austria.
EM helmut.kovac@uni-graz.at; anton.stabentheiner@uni-graz.at
RI Käfer, Helmut/AAE-8772-2021
OI Kafer, Helmut/0000-0002-6261-5794; Kovac, Helmut/0000-0001-9340-5207
FU University of Graz; Austrian Science Fund (FWF) [P20802-B16,
   P25042-B16]; Austrian Science Fund (FWF) [P25042] Funding Source:
   Austrian Science Fund (FWF)
FX Open access funding provided by University of Graz. The research was
   funded by the Austrian Science Fund (FWF): P20802-B16, P25042-B16. We
   thank Stefano Turillazzi who gave us a warm welcome at his department
   and support during experiments. We greatly appreciate the help with data
   evaluation by Michaela Bodner, Lena Kovac, Christine Malej and Lucas
   Schauberger.
CR Addo-Bediako A, 2002, FUNCT ECOL, V16, P332, DOI 10.1046/j.1365-2435.2002.00634.x
   Andersen JL, 2015, FUNCT ECOL, V29, P55, DOI 10.1111/1365-2435.12310
   APCC, 2014, Osterreichischer Sachstandsbericht Klimawandel 2014 (AAR14)
   Ayrinhac A, 2004, FUNCT ECOL, V18, P700, DOI 10.1111/j.0269-8463.2004.00904.x
   Bale JS, 1996, EUR J ENTOMOL, V93, P369
   BALE JS, 1987, J INSECT PHYSIOL, V33, P899, DOI 10.1016/0022-1910(87)90001-1
   Carpenter James M., 1996, American Museum Novitates, V3188, P1
   Cervo R, 2000, INSECT SOC, V47, P155, DOI 10.1007/PL00001694
   Chown S.L., 2004, Mechanisms and Patterns, DOI [DOI 10.1093/ACPROF:OSO/9780198515494.001.0001, DOI 10.1093/ACPROF:OSO/9780198515494.003.0003]
   Chown SL, 2002, COMP BIOCHEM PHYS B, V131, P587, DOI 10.1016/S1096-4959(02)00017-9
   Chown SL, 2009, FUNCT ECOL, V23, P133, DOI 10.1111/j.1365-2435.2008.01481.x
   Clarke A, 2004, FUNCT ECOL, V18, P243, DOI 10.1111/j.0269-8463.2004.00841.x
   Clarke A, 2004, FUNCT ECOL, V18, P252, DOI 10.1111/j.0269-8463.2004.00842.x
   Crailsheim K, 1999, ENTOMOL GEN, V24, P01
   David JR, 2003, FUNCT ECOL, V17, P425, DOI 10.1046/j.1365-2435.2003.00750.x
   Gallego B, 2016, J THERM BIOL, V56, P113, DOI 10.1016/j.jtherbio.2015.12.006
   Gaston KJ, 2009, AM NAT, V174, P595, DOI 10.1086/605982
   Gaston KJ, 1999, OIKOS, V86, P584, DOI 10.2307/3546663
   Gibert P, 2001, EVOLUTION, V55, P1063, DOI 10.1554/0014-3820(2001)055[1063:CCTAMC]2.0.CO;2
   Hack MA, 1997, PHYSIOL ENTOMOL, V22, P325, DOI 10.1111/j.1365-3032.1997.tb01176.x
   Hartfelder K, 2013, J APICULT RES, V52, DOI 10.3896/IBRA.1.52.1.06
   Hazell SP, 2011, J INSECT PHYSIOL, V57, P1085, DOI 10.1016/j.jinsphys.2011.04.004
   Hazell SP, 2008, PHYSIOL ENTOMOL, V33, P389, DOI 10.1111/j.1365-3032.2008.00637.x
   Höcherl N, 2016, J THERM BIOL, V60, P171, DOI 10.1016/j.jtherbio.2016.07.012
   Höcherl N, 2015, ECOSPHERE, V6, DOI 10.1890/ES15-00254.1
   Hoffmann AA, 2010, J EXP BIOL, V213, P870, DOI 10.1242/jeb.037630
   HOFFMANN AA, 2012, FUNCTIONAL ECOLOGY, V27, P934, DOI DOI 10.1111/J.1365-2435.2012.02036.X
   Hu XP, 2004, ENVIRON ENTOMOL, V33, P197, DOI 10.1603/0046-225X-33.2.197
   HUEY RB, 1979, AM ZOOL, V19, P357
   Käfer H, 2015, J COMP PHYSIOL B, V185, P647, DOI 10.1007/s00360-015-0915-7
   Käfer H, 2012, J INSECT PHYSIOL, V58, P679, DOI 10.1016/j.jinsphys.2012.01.015
   Kellermann V, 2012, P NATL ACAD SCI USA, V109, P16228, DOI 10.1073/pnas.1207553109
   Klok CJ, 2004, J EXP BIOL, V207, P2361, DOI 10.1242/jeb.01023
   Klok CJ, 2003, BIOL J LINN SOC, V78, P401, DOI 10.1046/j.1095-8312.2003.00154.x
   Klok CJ, 1997, J INSECT PHYSIOL, V43, P685, DOI 10.1016/S0022-1910(97)00001-2
   Kovac H, 1999, J INSECT PHYSIOL, V45, P183, DOI 10.1016/S0022-1910(98)00115-2
   Kovac H, 2007, J INSECT PHYSIOL, V53, P1250, DOI 10.1016/j.jinsphys.2007.06.019
   Kovac H, 2009, J INSECT PHYSIOL, V55, P959, DOI 10.1016/j.jinsphys.2009.06.012
   Lancaster LT, 2015, J BIOGEOGR, V42, P1953, DOI 10.1111/jbi.12553
   Lutterschmidt WI, 1997, CAN J ZOOL, V75, P1553, DOI 10.1139/z97-782
   MacMillan HA, 2011, J INSECT PHYSIOL, V57, P12, DOI 10.1016/j.jinsphys.2010.10.004
   Magozzi S, 2015, GLOBAL CHANGE BIOL, V21, P181, DOI 10.1111/gcb.12695
   Maysov A, 2011, J THERM BIOL, V36, P64, DOI 10.1016/j.jtherbio.2010.11.004
   Overgaard J, 2011, J THERM BIOL, V36, P409, DOI 10.1016/j.jtherbio.2011.07.005
   Pekkarinen A, 1999, ENTOMOL FENNICA, V10, P191, DOI 10.33338/ef.84021
   SCHMARANZER S, 1988, J COMP PHYSIOL B, V158, P135, DOI 10.1007/BF01075826
   Sgrò CM, 2010, J EVOLUTION BIOL, V23, P2484, DOI 10.1111/j.1420-9101.2010.02110.x
   Sheldon KS, 2014, ECOLOGY, V95, P2134, DOI 10.1890/13-1703.1
   Sinclair BJ, 2006, J INSECT PHYSIOL, V52, P29, DOI 10.1016/j.jinsphys.2005.09.002
   Sinclair BJ, 2001, CRYO-LETT, V22, P125
   Smit Jan, 2003, Nederlandse Faunistische Mededelingen, V18, P81
   Stabentheiner A., 1987, Thermology, V2, P563
   Stabentheiner A, 2003, J INSECT PHYSIOL, V49, P881, DOI 10.1016/S0022-1910(03)00148-3
   Stabentheiner A, 1999, ENTOMOL GEN, V24, P13
   Stabentheiner A, 2012, THERMOCHIM ACTA, V534, P77, DOI 10.1016/j.tca.2012.02.006
   STEINER A., 1930, ZEITSCHR WISS BIOL ABT C ZEIISCHR VERGLEICH PHYS IOL, V11, P461
   Stevens MM, 2010, J EXP BIOL, V213, P2209, DOI 10.1242/jeb.040170
   Terblanche JS, 2008, J INSECT PHYSIOL, V54, P114, DOI 10.1016/j.jinsphys.2007.08.007
   Terblanche JS, 2007, P ROY SOC B-BIOL SCI, V274, P2935, DOI 10.1098/rspb.2007.0985
   Terblanche JS, 2006, AM J TROP MED HYG, V74, P786, DOI 10.4269/ajtmh.2006.74.786
   Terblanche JS, 2011, J EXP BIOL, V214, P3713, DOI 10.1242/jeb.061283
   Terblanche JS, 2009, PHYSIOL BIOCHEM ZOOL, V82, P495, DOI 10.1086/605361
   Tomlinson S, 2015, COMP BIOCHEM PHYS A, V190, P61, DOI 10.1016/j.cbpa.2015.09.004
   Tomlinson S, 2015, J INSECT PHYSIOL, V78, P62, DOI 10.1016/j.jinsphys.2015.04.011
   Vesala L, 2012, J EXP BIOL, V215, P2891, DOI 10.1242/jeb.069948
   Vorhees AS, 2013, PHYSIOL BIOCHEM ZOOL, V86, P73, DOI 10.1086/668851
   Watson SA, 2014, OECOLOGIA, V174, P45, DOI 10.1007/s00442-013-2767-8
   Woydak H, 2006, Abh. Westfalischen Mus. Naturkunde, V68, P3
NR 68
TC 19
Z9 19
U1 0
U2 17
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 0174-1578
EI 1432-136X
J9 J COMP PHYSIOL B
JI J. Comp. Physiol. B-Biochem. Syst. Environ. Physiol.
PD FEB
PY 2017
VL 187
IS 2
BP 277
EP 290
DI 10.1007/s00360-016-1041-x
PG 14
WC Physiology; Zoology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Physiology; Zoology
GA EO1CV
UT WOS:000396436100002
PM 27744515
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Abid, M
   Schilling, J
   Scheffran, J
   Zulfiqar, F
AF Abid, Muhammad
   Schilling, Janpeter
   Scheffran, Juergen
   Zulfiqar, Farhad
TI Climate change vulnerability, adaptation and risk perceptions at farm
   level in Punjab, Pakistan
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Climate change; Vulnerability; Risks; Adaptation; Agriculture; Punjab;
   Pakistan
ID VARIABILITY; AGRICULTURE; STRATEGIES
AB Pakistan is among the countries highly exposed and vulnerable to climate change. The country has experienced many severe floods, droughts and storms over the last decades. However, little research has focused on the investigation of vulnerability and adaptation to climate-related risks in Pakistan. Against this backdrop, this article investigates the farm level risk perceptions and different aspects of vulnerability to climate change including sensitivity and adaptive capacity at farm level in Pakistan. We interviewed a total of 450 farming households through structured questionnaires in three districts of Punjab province of Pakistan. This study identified a number of climate-related risks perceived by farm households such as extreme temperature events, insect attacks, animal diseases and crop pests. Limited water availability, high levels of poverty and a weak role of local government in providing proper infrastructure were the factors that make farmers more sensitive to climate-related risks. Uncertainty or reduction in crop and livestock yields; changed cropping calendars and water shortage were the major adverse impacts of climate-related risks reported by farmers in the study districts. Better crop production was reported as the only positive effect. Further, this study identified a number of farm level adaptation methods employed by farm households that include changes in crop variety, crop types, planting dates and input mix, depending upon the nature of the climate-related risks. Lack of resources, limited information, lack of finances and institutional support were some constraints that limit the adaptive capacity of farm households. This study also reveals a positive role of cooperation and negative role of conflict in the adaptation process. The study suggests to address the constraints to adaptation and to improve farm level cooperation through extended outreach and distribution of institutional services, particularly climate-specific farm advisory services. (C) 2015 Elsevier B.V. All rights reserved.
C1 [Abid, Muhammad; Schilling, Janpeter; Scheffran, Juergen] Univ Hamburg, Inst Geog, Res Grp Climate Change & Secur CLISEC, Grindelberg 7, D-20144 Hamburg, Germany.
   [Abid, Muhammad] Sch Integrated Climate Syst Sci, Grindelberg 5, D-20144 Hamburg, Germany.
   [Schilling, Janpeter] Int Alert, London, England.
   [Zulfiqar, Farhad] Asian Inst Technol, Sch Environm Resources & Dev, Bangkok, Thailand.
C3 University of Hamburg; Asian Institute of Technology
RP Abid, M (corresponding author), Univ Hamburg, Inst Geog, Res Grp Climate Change & Secur CLISEC, Grindelberg 7, D-20144 Hamburg, Germany.
EM muhammad.abid@uni-hamburg.de
RI Abid, Muhammad/J-8581-2017; Zulfiqar, Farhad/J-8719-2017; Scheffran,
   Jurgen/M-6876-2019; Abid, Muhammad/B-1206-2014
OI Scheffran, Jurgen/0000-0002-7171-3062; Abid,
   Muhammad/0000-0002-7691-4066; Zulfiqar, Farhad/0000-0002-3945-9172
FU Higher Education Commission (HEC), Pakistan
   [1-1/PM/OSS-II/Batch-4/Germany/2012/9493]; Deutscher Akademischer
   Austauschdienst (DAAD) [91549521]; Kompetenzzentrum Nachhaltige
   Universitat (KNU) [Anschub_34_2013]; Deutsche Forschungsgemeinschaft
   (DFG) [EXC177]
FX This study is part of a Ph.D. research at University of Hamburg, Germany
   at the School of Integrated Climate System Sciences (SICSS). We
   gratefully acknowledge the funding sources for this Ph.D. research:
   Higher Education Commission (HEC), Pakistan (Ref:
   1-1/PM/OSS-II/Batch-4/Germany/2012/9493); Deutscher Akademischer
   Austauschdienst (DAAD) (91549521); Kompetenzzentrum Nachhaltige
   Universitat (KNU) (Anschub_34_2013) and the Research Group Climate
   Change and Security (CLISEC) in the Exzellence Cluster "Integrated
   Climate System Analysis and Prediction" (CliSAP) supported by Deutsche
   Forschungsgemeinschaft (DFG) (EXC177). We also thank the local
   agricultural extension departments of three districts in Punjab,
   Pakistan, local farmer representatives for their cooperation and
   coordination in the process of successful data collection. Last but not
   least, we are very thankful to the farm households for their precious
   time and our survey team members, Mr. Muhammad Usman, Mr. Muhammad
   Haseeb Raza and Muhammad Ikhlaq Mansoor for their endless efforts to
   conduct the households' interviews during March and April 2014.
CR Abbas F, 2013, EARTH INTERACT, V17, DOI 10.1175/2013EI000528.1
   Abid M, 2015, EARTH SYST DYNAM, V6, P225, DOI 10.5194/esd-6-225-2015
   Abid M, 2011, SOIL ENVRON, V30, P78
   Abid M, 2011, PAK J AGR SCI, V48, P75
   Adger WN, 2006, GLOBAL ENVIRON CHANG, V16, P268, DOI 10.1016/j.gloenvcha.2006.02.006
   Adger WN, 2005, GLOBAL ENVIRON CHANG, V15, P77, DOI [10.1016/j.gloenvcha.2005.03.001, 10.1016/j.gloenvcha.2004.12.005]
   Ahmad M., 2013, CLIMATE CHANGE AGR F
   Ahmed MN, 2011, BUS ECON HORIZ, V4, P1
   Akram N., 2011, J SUSTAIN DEV, V4, P163, DOI DOI 10.5539/JSD.V4N3P163
   Ali, 2012, P INT SEM AN IND JAK
   Ali S., 2013, GROUNDWATER DEPLETIO
   [Anonymous], 2014, Cities and climate change initiative-abridged report: Islamabad Pakistan, climate change vulnerability assessment
   [Anonymous], UNEP POLICY SERIES
   [Anonymous], 2003, CLIMATE CHANGE ADAPT, DOI DOI 10.1142/P298
   [Anonymous], P SEM STRAT ADDR PRE
   [Anonymous], 2007, Working Group II
   [Anonymous], THESIS U AGR FAISALA
   Asif M., 2013, CLIMATIC CHANGE
   Baig A., 2014, PAKISTAN BUS REV, V15, P600
   Barnett J, 2007, POLIT GEOGR, V26, P639, DOI 10.1016/j.polgeo.2007.03.003
   Baylis N., 2006, T7 3 FORESIGHT INFEC
   Belliveau S, 2006, GLOBAL ENVIRON CHANG, V16, P364, DOI 10.1016/j.gloenvcha.2006.03.003
   Berg B. L., 2004, Qualitative Research Methods for the Social Sciences
   Bogner A, 2009, RES METHODS SER, P1, DOI 10.1057/9780230244276
   BOS, 2013, PUNJ DEV STAT
   Brooks N., 2003, Tyndall Centre for Climate Change Research, DOI DOI 10.1086/379713
   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
   Bukhari M., 2011, PAKISTAN VIS, P12
   Cutter SL, 2003, SOC SCI QUART, V84, P242, DOI 10.1111/1540-6237.8402002
   DAVIDSON A.P., 2001, Dilemmas of Agricultural Extension in Pakistan: Food for thought
   Deressa T., 2005, AGREKON, V44, P524, DOI [10.1080/03031853.2005.9523726, DOI 10.1080/03031853.2005.9523726]
   DOI, 2012, PREINV STUD DISTR GU
   DOI, 2012, PREINV STUD DISTR RA
   DOI, 2012, PREINV STUD DISTR TO
   Drafor I., 2005, LOCAL INFORM SYSTEMS
   Easterling DR, 2000, B AM METEOROL SOC, V81, P417, DOI 10.1175/1520-0477(2000)081<0417:OVATIE>2.3.CO;2
   Engle NL, 2011, GLOBAL ENVIRON CHANG, V21, P647, DOI 10.1016/j.gloenvcha.2011.01.019
   ESRI, 2015, NAT GEOGR WORLD MAP
   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
   Field C.B., 2014, IMPACTS ADAPTATION A, P1048
   Gorst A, 2015, 214 CTR CLIM CHANG E
   Hammad Badar Hammad Badar, 2002, International Journal of Agriculture and Biology, V4, P267
   Hanif U., 2010, The Pakistan Development Review, P771, DOI DOI 10.30541/V49I4IIPP.771-798
   Hatfield J.L., 2015, WEATHER CLIM EXTREME, DOI [11.1016/j.wace.2015.08, DOI 11.1016/J.WACE.2015.08]
   Hussain A., 2015, ICIMOD P
   Hussain SS, 2007, AGR SYST, V94, P494, DOI 10.1016/j.agsy.2006.12.001
   IFAD, 2014, RUR POV PAK RUR POV
   Inayatullah Jan Inayatullah Jan, 2012, Sarhad Journal of Agriculture, V28, P521
   Joshi K.D., 2015, POVERTY ENV NEXUS US
   Kelly PM, 2000, CLIMATIC CHANGE, V47, P325, DOI 10.1023/A:1005627828199
   Khan A., 2003, INT APO SEM ENH EXT
   LAL R, 1987, CRC CR REV PLANT SCI, V5, P303, DOI 10.1080/07352688709382244
   Lebel P, 2015, RISK MANAG-UK, V17, P1, DOI 10.1057/rm.2015.4
   [Lemmen DonaldS. Natural Resources Canada Natural Resources Canada], 2004, CLIMATE CHANGE IMPAC
   Luqman M., 2014, RURAL WOMENS INVOLVE
   Maida Zahid Maida Zahid, 2011, Science International (Lahore), V23, P313
   McCarthy J.J., 2001, CLIMATE CHANGE IMPAC
   Moser SC, 2008, CLIMATIC CHANGE, V87, pS309, DOI 10.1007/s10584-007-9384-7
   Muhammad Ashfaq Muhammad Ashfaq, 2012, Sarhad Journal of Agriculture, V28, P493
   Nazli H., 2012, Pakistan Rural Household Panel Survey 2012 (Round 1): Methodology and Community Characteristics (No. 7)
   NGWA, 2013, FACTS GLOB GROUNDW U, V9, P2013
   O'Brien G, 2006, DISASTERS, V30, P64, DOI 10.1111/j.1467-9523.2006.00307.x
   Patt AG, 2008, GLOBAL ENVIRON CHANG, V18, P458, DOI 10.1016/j.gloenvcha.2008.04.002
   PBS, 1998, POP CENS
   Rahman S., 2014, Int J Adv Res Manag Soc Sci, V3, P125
   Rana M.A., 2014, 19 PSSP IFPRI
   Rasul G., 2011, Pakistan Journal of Meteorology, V8, P53
   Reid H., 2007, IIED BRIEFING PAPERS
   Schilling J., 2013, Environment and Natural Resources Research, V3, P27
   Shafiq M, 2000, AGR ECON, V22, P321, DOI 10.1111/j.1574-0862.2000.tb00078.x
   Sheikh M.M., 2005, REGION WISE CLIMATE
   Sial M. H., 2012, Pakistan Economic and Social Review, V50, P139
   Siddiqui R., 2012, Pakistan Development Review, V4, DOI [10.30541/v51i4iipp.261-276, DOI 10.30541/V51I4IIPP.261-276]
   Skinner M.W., 2004, MITIG ADAPT STRAT GL, V7, P85
   Smithers J, 1997, GLOBAL ENVIRON CHANG, V7, P129, DOI 10.1016/S0959-3780(97)00003-4
   Tingju Z., 2014, 002 PSSP IFPRI
   Turner BL, 2003, P NATL ACAD SCI USA, V100, P8074, DOI 10.1073/pnas.1231335100
   van Aalst MK, 2008, GLOBAL ENVIRON CHANG, V18, P165, DOI 10.1016/j.gloenvcha.2007.06.002
   Wandel J., 2000, Agricultural and environmental sustainability in the new countryside, P30
   Wheaton E., 1999, Mitigation and Adaptation Strategies for Global Change, V4, P215, DOI DOI 10.1023/A:1009660700150
   Yasin M., 2010, PESTICIDE ACTION NET, P37
NR 82
TC 256
Z9 271
U1 6
U2 188
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 MAR 15
PY 2016
VL 547
BP 447
EP 460
DI 10.1016/j.scitotenv.2015.11.125
PG 14
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA DD0ST
UT WOS:000369630600047
PM 26836405
DA 2025-01-10
ER

PT J
AU Innangi, M
   Schenk, MK
   d'Alessandro, F
   Pinto, S
   Menta, C
   Papa, S
   Fioretto, A
AF Innangi, Michele
   Schenk, Manfred K.
   d'Alessandro, Francesco
   Pinto, Stefania
   Menta, Cristina
   Papa, Stefania
   Fioretto, Antonietta
TI Field and microcosms decomposition dynamics of European beech leaf
   litter: Influence of climate, plant material and soil with focus on N
   and Mn
SO APPLIED SOIL ECOLOGY
LA English
DT Article
DE Climate; Fagus sylvatica; Leaf litter decomposition; Litter quality;
   Manganese; Microcosms
ID FAGUS-SYLVATICA L.; DECAYING LEAVES; MIXED STANDS; CARBON POOLS; FOREST;
   QUALITY; RATES; NITROGEN; LIGNIN; TEMPERATURE
AB Leaf litter decomposition is one of the key phenomena in forest ecology. The patterns and trends of decomposition are related to the complex interaction of climate, soil biota and litter quality. The decay dynamics for the European beech are well-known for middle Europe, but lesser investigated in the Mediterranean area. In this study, we investigated mass loss and nutrient dynamics, especially nitrogen and manganese, in two Mediterranean beech forest located in northern and southern Italy. We used a litterbag experiment with leaves of each forest incubated in their own area of origin and vice versa. Moreover, we also used microcosms to follow early stages of decomposition under controlled conditions. The aims of this study were to investigate the role of climate and soil/litter quality at the different stages of decomposition and assess the response of diverse soils to changes in temperature and humidity. The results showed a faster field decomposition for the southern (warmer) site compared to the northern (colder) site, whereas under stable conditions in microcosms this trend reversed, implying different microbial adaptations to climate. Moreover, changes in temperature and humidity triggered complex microbial response during litter decay. Additionally, whereas our results showed trends of nitrogen concentration comparable to previous studies, the role of manganese in decomposition was very relevant even from the early stages. Noticeably, manganese was generally lower in both sites compared to middle Europe, but it was higher in the northern site than in the southern one. Manganese concentration, however, strongly increased for those leaves that had a lower initial content in all conditions, giving evidence of a strong mobilization of this nutrient and its essential role for decomposition in Mediterranean beech forests. (C) 2015 Elsevier B.V. All rights reserved.
C1 [Innangi, Michele; d'Alessandro, Francesco; Papa, Stefania; Fioretto, Antonietta] Univ Naples 2, Dept Environm Biol Pharmaceut Sci & Technol, I-81100 Caserta, Italy.
   [Schenk, Manfred K.] Leibniz Univ Hannover, Inst Plant Nutr, D-30419 Hannover, Germany.
   [Pinto, Stefania; Menta, Cristina] Univ Parma, Dept Life Sci, I-43121 Parma, Italy.
C3 Universita della Campania Vanvitelli; Leibniz University Hannover;
   University of Parma
RP Innangi, M (corresponding author), Vivaldi 43, I-81100 Caserta, Italy.
EM michele.innangi@unina.it
RI Innangi, Michele/M-2205-2015
OI Menta, Cristina/0000-0002-6680-6424; Papa, Stefania/0000-0002-8315-3154
CR Albers D, 2004, SOIL BIOL BIOCHEM, V36, P155, DOI 10.1016/j.soilbio.2003.09.002
   Alvarez Romero M., 2012, DISTRIBUZIONE SOSTAN
   Amoriello T., 2000, ANN I SPER SELV, V30, P129
   Andriuzzi WS, 2013, SOIL BIOL BIOCHEM, V64, P136, DOI 10.1016/j.soilbio.2013.04.016
   Bååth E, 2003, SOIL BIOL BIOCHEM, V35, P955, DOI 10.1016/S0038-0717(03)00154-8
   Behrens T., 2011, ABHANGIGKEIT SORTE S
   Berg B, 2007, BIOGEOCHEMISTRY, V82, P29, DOI 10.1007/s10533-006-9050-6
   Berg B, 2010, BIOGEOCHEMISTRY, V100, P57, DOI 10.1007/s10533-009-9404-y
   Berg B, 1996, CAN J BOT, V74, P659, DOI 10.1139/b96-084
   Berg B., 2014, Decomposition, Humus Formation, Carbon Sequestration, V3rd
   Berg B., 2006, ADV ECOL RES, P38
   Berg B, 2013, CAN J FOREST RES, V43, P1127, DOI 10.1139/cjfr-2013-0097
   Berg MP, 1998, BIOL FERT SOILS, V26, P313, DOI 10.1007/s003740050382
   Brandstätter C, 2013, PLANT SOIL, V371, P139, DOI 10.1007/s11104-013-1671-7
   Bussotti F, 2005, TREE PHYSIOL, V25, P211, DOI 10.1093/treephys/25.2.211
   Chamberlain PM, 2006, SOIL BIOL BIOCHEM, V38, P2655, DOI 10.1016/j.soilbio.2006.03.021
   Climate Change, 2013, The physical science basis
   Cortez J, 1998, SOIL BIOL BIOCHEM, V30, P783, DOI 10.1016/S0038-0717(97)00163-6
   Cortez J, 2001, SOIL BIOL BIOCHEM, V33, P2023, DOI 10.1016/S0038-0717(01)00124-9
   Cortez J, 1998, SOIL BIOL BIOCHEM, V30, P795, DOI 10.1016/S0038-0717(97)00164-8
   Cortez J, 1996, SOIL BIOL BIOCHEM, V28, P443, DOI 10.1016/0038-0717(96)00005-3
   COUTEAUX MM, 1995, TRENDS ECOL EVOL, V10, P63, DOI 10.1016/S0169-5347(00)88978-8
   d'Annunzio R, 2008, SOIL BIOL BIOCHEM, V40, P322, DOI 10.1016/j.soilbio.2007.08.011
   Davidson EA, 2006, NATURE, V440, P165, DOI 10.1038/nature04514
   de la Rubia T, 2002, RES MICROBIOL, V153, P547, DOI 10.1016/S0923-2508(02)01357-8
   DIXON RK, 1994, SCIENCE, V263, P185, DOI 10.1126/science.263.5144.185
   Ellenberg H., 2010, Veg. Mitteleur
   Fioretto A, 2005, APPL VEG SCI, V8, P13, DOI 10.1111/j.1654-109X.2005.tb00624.x
   Fioretto A, 2005, SOIL BIOL BIOCHEM, V37, P1083, DOI 10.1016/j.soilbio.2004.11.007
   Fioretto A, 2000, SOIL BIOL BIOCHEM, V32, P1847, DOI 10.1016/S0038-0717(00)00158-9
   Frank K., 1998, PHOSPHORUS RECOMMEND, P25
   Guckland A, 2009, J PLANT NUTR SOIL SC, V172, P500, DOI 10.1002/jpln.200800072
   Harris D, 2001, SOIL SCI SOC AM J, V65, P1853, DOI 10.2136/sssaj2001.1853
   Hyvönen R, 2007, NEW PHYTOL, V173, P463, DOI 10.1111/j.1469-8137.2007.01967.x
   Briones MJI, 2010, SOIL BIOL BIOCHEM, V42, P960, DOI 10.1016/j.soilbio.2010.02.013
   Incerti G, 2011, APPL SOIL ECOL, V49, P148, DOI 10.1016/j.apsoil.2011.06.004
   Innangi M., 2014, THESIS U NAPLES ITAL
   Joergensen RG, 2009, EUR J SOIL BIOL, V45, P285, DOI 10.1016/j.ejsobi.2009.04.006
   Kamitsuji H, 2004, APPL MICROBIOL BIOT, V65, P287, DOI 10.1007/s00253-003-1543-9
   Kaspari M, 2008, ECOL LETT, V11, P35, DOI 10.1111/j.1461-0248.2007.01124.x
   Knoepp JD, 2000, FOREST ECOL MANAG, V138, P357, DOI 10.1016/S0378-1127(00)00424-2
   Kooijman AM, 2009, FOREST ECOL MANAG, V257, P1732, DOI 10.1016/j.foreco.2009.01.030
   Langenbruch C, 2012, PLANT SOIL, V352, P389, DOI 10.1007/s11104-011-1004-7
   Leoni A., 2008, Studio della biodiversita vegetale e del popolamento a microartropodi edafici nella riserva naturale di Guadine Pardaccio
   Liski J, 2003, GLOBAL CHANGE BIOL, V9, P575, DOI 10.1046/j.1365-2486.2003.00605.x
   Meier IC, 2010, GLOBAL CHANGE BIOL, V16, P1035, DOI 10.1111/j.1365-2486.2009.02074.x
   MELILLO JM, 1982, ECOLOGY, V63, P621, DOI 10.2307/1936780
   Moorhead DL, 2006, ECOL MONOGR, V76, P151, DOI 10.1890/0012-9615(2006)076[0151:ATMOLD]2.0.CO;2
   Mosello Rosario, 2002, Journal of Limnology, V61, P77
   OLSON JS, 1963, ECOLOGY, V44, P322, DOI 10.2307/1932179
   Ono K, 2013, BIOGEOCHEMISTRY, V112, P7, DOI 10.1007/s10533-011-9682-z
   Osono T, 2007, ECOL RES, V22, P955, DOI 10.1007/s11284-007-0390-z
   Palma C, 2000, J BIOTECHNOL, V77, P235, DOI 10.1016/S0168-1656(99)00218-7
   Ponge JF, 2003, SOIL BIOL BIOCHEM, V35, P935, DOI 10.1016/S0038-0717(03)00149-4
   Romani AM, 2006, ECOLOGY, V87, P2559, DOI 10.1890/0012-9658(2006)87[2559:IOBAFO]2.0.CO;2
   Ross D S., 1995, Recommended Methods for Determining Soil Cation Exchange Capacity, P75
   Rutigliano F.A., 1989, EC ATT TERZ C NAZ SO, P837
   Rutigliano FA, 1998, BIOL FERT SOILS, V27, P119, DOI 10.1007/s003740050409
   Rutigliano FA, 1996, SOIL BIOL BIOCHEM, V28, P101, DOI 10.1016/0038-0717(95)00120-4
   Sariyildiz T, 2005, FOREST ECOL MANAG, V210, P303, DOI 10.1016/j.foreco.2005.02.043
   Sariyildiz T, 2003, SOIL BIOL BIOCHEM, V35, P391, DOI 10.1016/S0038-0717(02)00290-0
   Sariyildiz Temel, 2005, Turkish Journal of Agriculture and Forestry, V29, P429
   Satti P, 2003, J ECOL, V91, P173, DOI 10.1046/j.1365-2745.2003.00756.x
   Song B, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0033217
   Swift M.J., 1979, Decomposition in Terrestrial Ecosystems, V5
   TAYLOR BR, 1989, ECOLOGY, V70, P97, DOI 10.2307/1938416
   Trap J, 2013, FOREST ECOL MANAG, V302, P338, DOI 10.1016/j.foreco.2013.03.011
   Trofymow JA, 2002, CAN J FOREST RES, V32, P789, DOI 10.1139/X01-117
   van Vliet PCJ, 2004, APPL SOIL ECOL, V25, P147, DOI 10.1016/j.apsoil.2003.08.004
   von Wuehlisch G., 2008, EUFORGEN Technical Guidelines for genetic conservation and use for European beech (Fagus sylvatica), P1
   Warncke D., 1998, Recommended chemical soil test procedures for the North Central Region, V221, P31
NR 71
TC 18
Z9 24
U1 0
U2 114
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0929-1393
EI 1873-0272
J9 APPL SOIL ECOL
JI Appl. Soil Ecol.
PD SEP
PY 2015
VL 93
BP 88
EP 97
DI 10.1016/j.apsoil.2015.04.007
PG 10
WC Soil Science
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA CI5HI
UT WOS:000354785300011
DA 2025-01-10
ER

PT J
AU Pathak, TB
   Jones, JW
   Fraisse, CW
AF Pathak, T. B.
   Jones, J. W.
   Fraisse, C. W.
TI COTTON YIELD FORECASTING FOR THE SOUTHEASTERN UNITED STATES USING
   CLIMATE INDICES
SO APPLIED ENGINEERING IN AGRICULTURE
LA English
DT Article
DE Climate indices; Cotton yield; Yield forecast; Principal component
   regression
ID PRINCIPAL COMPONENTS; TROPICAL ATLANTIC; EL-NINO; OSCILLATION; PACIFIC;
   CIRCULATION; PREDICTION; MODEL; ENSO; USA
AB The United States cotton industry is one of the major economic drivers of the country accounting for more than $25 billion in products and services annually The southeastern United States holds a major share of total cotton production in the United States. Although cotton is considered as a drought tolerant crop, climate variability may adversely impact cotton production. An effective way to reduce agricultural vulnerability to climate variability is through the implementation of effective adaptation strategies. Knowing cotton yield forecast in advance based on climate information such as using large scale climate indices, would aid the growers in making informed decisions to adapt to climate risk. The objectives of this study were to evaluate the relationships between large-scale climate indices and cotton yield and to evaluate the skill of cotton yield forecasts. Seven January and February month oceanic and atmospheric climate indices were correlated with May-September temperature, precipitation, and county average cotton yield for 64 counties in Georgia and Alabama. All climate indices were then summarized using a principal component analysis and regressed against historic cotton yield for 64 counties to obtain empirical models for cotton yield forecasting. The yield forecasts were evaluated using leave one out cross validation. Results indicated that January and February monthly climate indices exhibited statistically significant correlations with climate during the cotton growing season as well as with cotton yields. With a lead time of approximately 2 months before the typical planting period on the southeastern United States, about 77% of the counties in Georgia and 70% of the counties in Alabama showed statistically significant correlations between observed and forecasted cotton yields. Climate indices showed potential to forecast cotton yield in the southeastern United States with significant lead time.
C1 [Pathak, T. B.; Jones, J. W.; Fraisse, C. W.] Univ Florida, Dept Agr & Biol Engn, Gainesville, FL 32611 USA.
C3 State University System of Florida; University of Florida
RP Pathak, TB (corresponding author), Univ Florida, Dept Agr & Biol Engn, Gainesville, FL 32611 USA.
EM tpathak2@unl.edu
RI Pathak, Tapan/K-2867-2019
OI Fraisse, Clyde W./0000-0001-9875-2187
CR Alexandrov VA, 2001, CLIMATE RES, V17, P33, DOI 10.3354/cr017033
   Baigorria GA, 2008, J APPL METEOROL CLIM, V47, P76, DOI 10.1175/2007JAMC1523.1
   Baigorria GA, 2007, CLIM RES, V34, P211, DOI 10.3354/cr00703
   Baigorria GA, 2010, AGRON J, V102, P187, DOI 10.2134/agronj2009.0201
   BARNSTON AG, 1991, J CLIMATE, V4, P203, DOI 10.1175/1520-0442(1991)004<0203:MOSONH>2.0.CO;2
   Barreiro A, 2005, DYNAM ATMOS OCEANS, V39, P61, DOI 10.1016/j.dynatmoce.2004.10.013
   BELL GD, 1995, B AM METEOROL SOC, V76, P681, DOI 10.1175/1520-0477(1995)076<0681:ACAWTM>2.0.CO;2
   Chiang JCH, 2004, J CLIMATE, V17, P4143, DOI 10.1175/JCLI4953.1
   Enfield DB, 1996, GEOPHYS RES LETT, V23, P3305, DOI 10.1029/96GL03231
   Enfield DB, 1999, J GEOPHYS RES-OCEANS, V104, P7841, DOI 10.1029/1998JC900109
   Hansen JW, 2005, PHILOS T R SOC B, V360, P2037, DOI 10.1098/rstb.2005.1747
   Hansen JW, 1998, J CLIMATE, V11, P404, DOI 10.1175/1520-0442(1998)011<0404:EIOAIT>2.0.CO;2
   IDSO SB, 1979, REMOTE SENS ENVIRON, V8, P267, DOI 10.1016/0034-4257(79)90006-3
   Jagtap SS, 2002, AGR SYST, V74, P415, DOI 10.1016/S0308-521X(02)00048-3
   Jones J. W., 2005, PUBLICATION SE CLIMA
   Jones JW, 2000, AGR ECOSYST ENVIRON, V82, P169, DOI 10.1016/S0167-8809(00)00225-5
   JONES PN, 1994, AGR SYST, V46, P427, DOI 10.1016/0308-521X(94)90105-O
   Kiladis GN, 1989, J CLIMATE, V2, P1069, DOI 10.1175/1520-0442(1989)002<1069:GCAAWE>2.0.CO;2
   Kossin JP, 2007, B AM METEOROL SOC, V88, P1767, DOI 10.1175/BAMS-88-11-1767
   Kumar V., 2000, AGRON J, V92, P1047
   Lee DE, 2009, J MAMMAL, V90, P1, DOI 10.1644/08-MAMM-A-130.1
   Lobell DB, 2007, ENVIRON RES LETT, V2, DOI 10.1088/1748-9326/2/1/014002
   Martinez CJ, 2009, INT J CLIMATOL, V29, P1680, DOI 10.1002/joc.1817
   MASSY WF, 1965, J AM STAT ASSOC, V60, P234, DOI 10.2307/2283149
   Mennis J, 2001, INT J REMOTE SENS, V22, P3077, DOI 10.1080/01431160152558251
   MO KC, 1986, MON WEATHER REV, V114, P2488, DOI 10.1175/1520-0493(1986)114<2488:TEGHTD>2.0.CO;2
   Mo KC, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL034656
   Mote T. L., 1986, PHYSICAL GEOGR, V17, P497
   NASS/USDA (National Agricultural Statistics-United States Department of Agriculture), 2008, ACREAGE
   OBrien JJO, 1996, B AM METEOROL SOC, V77, P773
   PLACKETT RL, 1983, INT STAT REV, V51, P59, DOI 10.2307/1402731
   ROPELEWSKI CF, 1986, MON WEATHER REV, V114, P2352, DOI 10.1175/1520-0493(1986)114<2352:NAPATP>2.0.CO;2
   SAKAMOTO CM, 1978, AGR METEOROL, V19, P305, DOI 10.1016/0002-1571(78)90018-3
   Schwing FB, 2002, PROG OCEANOGR, V53, P115, DOI 10.1016/S0079-6611(02)00027-7
   Stenseth NC, 2003, P ROY SOC B-BIOL SCI, V270, P2087, DOI 10.1098/rspb.2003.2415
   SUTTER JM, 1992, J CHEMOMETR, V6, P217, DOI 10.1002/cem.1180060406
   Thompson DWJ, 2001, SCIENCE, V293, P85, DOI 10.1126/science.1058958
   TRENBERTH KE, 1994, CLIM DYNAM, V9, P303, DOI 10.1007/BF00204745
   USDA ERS, 2009, COTT WOOL YB
   Vimont DJ, 2007, GEOPHYS RES LETT, V34, DOI 10.1029/2007GL029683
   WALKER GK, 1989, AGR FOREST METEOROL, V44, P339, DOI 10.1016/0168-1923(89)90027-0
   Wang CZ, 2008, J CLIMATE, V21, P2437, DOI 10.1175/2007JCLI2029.1
   Washington R, 2000, INT J CLIMATOL, V20, P473, DOI 10.1002/(SICI)1097-0088(200004)20:5<473::AID-JOC506>3.0.CO;2-O
   Xie SP, 2005, J CLIMATE, V18, P5, DOI 10.1175/JCLI-3249.1
   Yamagata T., 2010, J CLIMATOL, V23, P455
NR 45
TC 5
Z9 5
U1 0
U2 24
PU AMER SOC AGRICULTURAL & BIOLOGICAL ENGINEERS
PI ST JOSEPH
PA 2950 NILES RD, ST JOSEPH, MI 49085-9659 USA
SN 0883-8542
EI 1943-7838
J9 APPL ENG AGRIC
JI Appl. Eng. Agric.
PD SEP
PY 2012
VL 28
IS 5
BP 711
EP 723
PG 13
WC Agricultural Engineering
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA 029JW
UT WOS:000310492600011
DA 2025-01-10
ER

PT J
AU Chen, WQ
   Lin, ZQ
   Hu, S
AF Chen, Wenqian
   Lin, Zequn
   Hu, Sheng
TI An All-Weather Sol<bold>-</bold>Gel Thermochromic Energy-Saving Smart
   Window
SO ACS APPLIED MATERIALS & INTERFACES
LA English
DT Article
DE sol-gel; aqueous synthesis; all-weather; thermal responsive;
   frost-resistant
ID VO2; HYDRATION; FILMS; GLASS
AB Thermochromic smart windows achieve energy conservation and emission reduction by regulating the energy exchange in buildings. However, their widespread application in architecture has been hindered by issues such as poor frost resistance, limited durability, high costs, recycling challenges, and suitability only for specific climates (such as tropical climates). To address these challenges, we have successfully developed a high-performance thermochromic window, which is an intelligent window based on a thermochromic solution of poly(vinyl alcohol) acetal and LiCl, encapsulated in a glass/thermal liquid/low-E structure. This thermochromic window exhibits scalability, frost-resistance, durability and all-climate adaptability (referred to as SFDA window, with the thermochromic liquid termed SFDA liquid). First, the SFDA liquid reported here utilizes an efficient one-pot aqueous synthesis technique to directly produce a polyvinyl acetal solution. This process not only supports large-scale production but also incorporates LiCl in situ, endowing the liquid with excellent frost resistance. Second, the concentration is purposefully adjusted to the entangled concentration to facilitate the sol-gel transition, ensuring durability during long-term use. Additionally, windows containing SFDA liquid demonstrate excellent performance, maintaining up to approximately 84% light transmittance and 70.7% solar radiation at 20 degrees C. Third, our SFDA window achieves high-efficiency energy savings compared to traditional thermochromic windows across all-weather conditions. Through indoor simulations, we found that SFDA window can cut energy consumption by 64.6% relative to traditional glass windows in the summer. In the winter, compared to traditional glass windows, windows containing SFDA liquid can reduce heating energy consumption by 52.3%. In simulations conducted across 33 cities worldwide, SFDA liquid windows achieved a total monthly energy savings of 1179.8 MWh compared to commercial Low-E window. With its outstanding energy efficiency, the SFDA smart window opens up a brand-new development pathway in the field of green economy.
C1 [Chen, Wenqian; Lin, Zequn; Hu, Sheng] Guangdong Univ Technol, Sch Chem Engn & Light Ind, Guangzhou 510006, Peoples R China.
C3 Guangdong University of Technology
RP Hu, S (corresponding author), Guangdong Univ Technol, Sch Chem Engn & Light Ind, Guangzhou 510006, Peoples R China.
EM husheng@gdut.edu.cn
RI chen, wenqian/GRS-6775-2022
FU SCUT
FX Special thanks go to Dr. Yubin Ke and Dr. Zhenhua Xie (from China
   Spallation Neutron Source) for their help in neutron scattering, and to
   Dr. Xiaolong Liu and Yan Tong from SCUT for their assistance and helpful
   discussions in variable temperature nuclear magnetic resonance.
CR Brugnoni M, 2019, POLYM CHEM-UK, V10, P2397, DOI 10.1039/c8py01699b
   Budtova T, 2016, CELLULOSE, V23, P5, DOI 10.1007/s10570-015-0779-8
   Chen GQ, 2023, ADV MATER, V35, DOI 10.1002/adma.202211716
   Chen R, 2019, ADV OPT MATER, V7, DOI 10.1002/adom.201900101
   Cuce E, 2015, RENEW SUST ENERG REV, V41, P695, DOI 10.1016/j.rser.2014.08.084
   Cui YY, 2018, JOULE, V2, P1707, DOI 10.1016/j.joule.2018.06.018
   Dragan CA, 2011, APPL BIOCHEM BIOTECH, V163, P965, DOI 10.1007/s12010-010-9100-3
   Etale A, 2023, CHEM REV, DOI 10.1021/acs.chemrev.2c00477
   Gao J, 2003, LANGMUIR, V19, P5212, DOI 10.1021/la0269762
   Gao YF, 2012, NANO ENERGY, V1, P221, DOI 10.1016/j.nanoen.2011.12.002
   Gao YF, 2012, ENERG ENVIRON SCI, V5, P8234, DOI 10.1039/c2ee21119j
   Geng X, 2022, ACS APPL MATER INTER, V14, P19736, DOI 10.1021/acsami.2c03113
   Ghosh S, 2023, ACS NANO, V17, P19767, DOI 10.1021/acsnano.3c03693
   Barba MI, 2016, ANAL CHIM ACTA, V919, P20, DOI 10.1016/j.aca.2016.03.022
   Ke YJ, 2018, ADV FUNCT MATER, V28, DOI 10.1002/adfm.201800113
   Kollias N, 2011, PHOTOCHEM PHOTOBIOL, V87, P1474, DOI 10.1111/j.1751-1097.2011.00980.x
   Kuang ZY, 2019, ACS APPL MATER INTER, V11, P37026, DOI 10.1021/acsami.9b10286
   Lee HY, 2017, CHEM MATER, V29, P6947, DOI 10.1021/acs.chemmater.7b02402
   Li XX, 2023, MATER HORIZ, V10, P4452, DOI 10.1039/d3mh00892d
   Li XH, 2019, JOULE, V3, P290, DOI 10.1016/j.joule.2018.10.019
   Liang X, 2018, J MATER CHEM C, V6, P7054, DOI 10.1039/c8tc01274a
   Liang X, 2017, ACS APPL MATER INTER, V9, P40810, DOI 10.1021/acsami.7b11582
   Liang X, 2017, NANOSCALE HORIZ, V2, P319, DOI 10.1039/c7nh00105c
   Liang X, 2017, MATER HORIZ, V4, P878, DOI 10.1039/c7mh00224f
   Lin CJ, 2022, SCI ADV, V8, DOI 10.1126/sciadv.abn7359
   Lin J, 2018, NAT MATER, V17, P261, DOI 10.1038/s41563-017-0006-0
   Ling H, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-21086-7
   Liu S, 2021, ADV FUNCT MATER, V31, DOI 10.1002/adfm.202010426
   Liu ZL, 2023, FOOD CHEM, V408, DOI 10.1016/j.foodchem.2022.135202
   Mähler J, 2012, INORG CHEM, V51, P425, DOI 10.1021/ic2018693
   Malarde D, 2017, ACS OMEGA, V2, P1040, DOI 10.1021/acsomega.7b00042
   Nakamura A, 2021, SOL ENERG MAT SOL C, V232, DOI 10.1016/j.solmat.2021.111348
   Nakamura C, 2019, IND ENG CHEM RES, V58, P6424, DOI 10.1021/acs.iecr.9b00407
   Paik T, 2014, ACS NANO, V8, P797, DOI 10.1021/nn4054446
   Santos AJ, 2023, CHEM MATER, V35, P4435, DOI 10.1021/acs.chemmater.3c00613
   Shao ZW, 2024, NAT SUSTAIN, V7, DOI 10.1038/s41893-024-01349-z
   Shao ZW, 2022, NAT ELECTRON, V5, P45, DOI 10.1038/s41928-021-00697-4
   Shen WB, 2023, LASER PHOTONICS REV, V17, DOI 10.1002/lpor.202200207
   Sui XJ, 2021, CHEM ENG J, V419, DOI 10.1016/j.cej.2021.129478
   Tarantini M, 2011, ENERGY, V36, P2473, DOI 10.1016/j.energy.2011.01.039
   Wang H, 2018, ANGEW CHEM INT EDIT, V57, P1627, DOI 10.1002/anie.201712781
   Wang SC, 2021, SCIENCE, V374, P1501, DOI 10.1126/science.abg0291
   Wheeler LM, 2017, NAT COMMUN, V8, DOI 10.1038/s41467-017-01842-4
   Youngblood N, 2022, ACS PHOTONICS, V9, P90, DOI 10.1021/acsphotonics.1c01128
   Zhang QH, 2021, ADV FUNCT MATER, V31, DOI 10.1002/adfm.202100686
   Zhang Y, 2019, APPL ENERG, V254, DOI 10.1016/j.apenergy.2019.113690
   Zhao L, 2014, NATURE, V511, P216, DOI 10.1038/nature13462
   Zhou Y, 2020, J FLUID MECH, V903, DOI 10.1017/jfm.2020.611
   Zhu JT, 2016, ACS APPL MATER INTER, V8, P29742, DOI 10.1021/acsami.6b11202
NR 49
TC 0
Z9 0
U1 6
U2 6
PU AMER CHEMICAL SOC
PI WASHINGTON
PA 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
SN 1944-8244
EI 1944-8252
J9 ACS APPL MATER INTER
JI ACS Appl. Mater. Interfaces
PD DEC 12
PY 2024
VL 16
IS 51
BP 70863
EP 70873
DI 10.1021/acsami.4c14369
EA DEC 2024
PG 11
WC Nanoscience & Nanotechnology; Materials Science, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics; Materials Science
GA Q2O8A
UT WOS:001376039800001
PM 39663993
DA 2025-01-10
ER

PT J
AU Weidmüller, N
   Knopp, JM
   Beber, J
   Krnjaja, GM
   Banzhaf, E
AF Weidmueller, Nicola
   Knopp, Julius Matthias
   Beber, Josip
   Krnjaja, Gordana Mikulcic
   Banzhaf, Ellen
TI Local planning scenario for shading from trees as an urban nature-based
   solution
SO CITY AND ENVIRONMENT INTERACTIONS
LA English
DT Article
DE Urban heat stress; Spatial analysis; Town; EC Nature Restoration Law;
   Central and Southern Europe
ID GREEN INFRASTRUCTURE; CITIES
AB With more than 75% of the European Union's population living in urban areas covering 21.5% of the EU territory, the importance of climate-resilient cities, towns and suburbs has increased dramatically. However, the rising impact of human-induced land-use changes on ecosystem services (ES) poses a major challenge to the urban environment. This study focuses on scenario development for nature-based solutions (NbS) in a European town with its intense development area. The concept is exemplified in a town in Croatia, Grad Velika Gorica (GVG), that like many others cities undergoes urbanisation processes with limited resources. It serves as a showpiece for the influence of NbS, in particular street trees along various paths. Using spatial analysis and modelling, the approach explores NbS for future urbanisation. The results, supported by quantitative analysis, show that 49% of cycle lanes and footpaths in GVG can be shaded by strategically planted street trees. The shading scenario analysis provides a nuanced perspective on the potential of NbS, offering insights into the key tasks for a climate-resilient city and opportunities towards equitable, green and healthy urban areas. In the context of urbanisation processes and climate adaptation, the study is in line with the overarching objectives of the European Commission which emphasises the need for sustainable NbS alternatives to address environmental challenges. The findings contribute to the framework of informed decision-making towards urban climate resilience. It also supports the pursuit of a sustainable local governance for climate-adjusted environmental quality in urban planning. As towns and cities grapple with the imperative of balancing urban development with environmental protection, this research highlights the central role of NbS, particularly street trees, in shaping climate-resilient and more sustainable urban environments for human well-being in cities.
C1 [Weidmueller, Nicola; Knopp, Julius Matthias; Banzhaf, Ellen] UFZ Helmholtz Ctr Environm Res, Permoserstr 15, D-04318 Magdeburg, Germany.
   [Beber, Josip] Zelena Energetska Zadruga, Bozidareviceva 13, Zagreb, Croatia.
   [Krnjaja, Gordana Mikulcic] Urban Planning Dept, City Velika Gor, Trg kralja Tomislava 34, Velika Gorica 10410, Croatia.
C3 Helmholtz Association; Helmholtz Center for Environmental Research (UFZ)
RP Banzhaf, E (corresponding author), UFZ Helmholtz Ctr Environm Res, Permoserstr 15, D-04318 Magdeburg, Germany.
EM nicola2112@web.de; Julius.knopp@ufz.de; josip.beber@zez.coop;
   gordana.mikulcic.krnjaja@gorcia.hr; ellen.banzhaf@ufz.de
OI Banzhaf, Ellen/0000-0002-4740-1202
FU EC funded REGREEN project under the European Union [821016]
FX This contribution is an excerpt from a M.Sc. thesis at University of
   Osnabrueck and Helmholtz-Centre for Environmental Research-UFZ. It is
   integrated in the EC funded REGREEN project under the European Union's
   Horizon 2020 research and innovation program (grant no. 821016) .
CR [Anonymous], FSC Forests and forest management in Croatia,
   [Anonymous], City of Velika Gorica City of Velika Gorica: Intelligent City Transformation Overview: ICC Final Deliverable
   Banzhaf E., 2023, Recommendations for Potential Target Values in Cities: Deliverable N3.5. (WP N3 Mapping and Modelling of Ecosystem Services)
   Climate Data Klima Zagreb (Kroatien), DATEN UND GRAPHEN ZUM KLIMA UND WETTER IN ZAGREB
   Croatian Bureau of Statistics, 2011, Census data 2011.
   Croatian Bureau of Statistics, 2022, CENSUS POPULATION HO
   de Vries S, 2013, SOC SCI MED, V94, P26, DOI 10.1016/j.socscimed.2013.06.030
   Deorbiting and Collision, 2022, Proposal for a Regulation of the European Parliament and of the Council on horizontal cybersecurity requirements for products with digital elements and amending Regulation (EU) 2019/1020
   European Commission, Biodiversity Strategy for 2030
   European Environmental Agency, 2020, Urban adaptation in Europe: how cities and towns respond to climate change
   eurostat Statistics Explained, 2023, Urban-rural Europe-introduction
   Grandin G., 2023, Guidelines for urban and territorial planning: incorporating NBS in urban land use planning: Deliverable N6.5
   Interreg, 2018, Cycle friendly traffic calming on the F3 cycle highway
   Alaoui HI, 2023, MODEL EARTH SYST ENV, V9, P4313, DOI 10.1007/s40808-023-01697-3
   Jones L., 2022, Nat. Based Solut, V2, P100041, DOI [10.1016/j.nbsj.2022.100041, DOI 10.1016/J.NBSJ.2022.100041]
   Kaluarachichi T., 2020, Influence of surface types on surface temperature reduction through tree shading, DOI [10.13140/RG.2.2.27394.20162, DOI 10.13140/RG.2.2.27394.20162]
   Karakus CB, 2019, ASIA-PAC J ATMOS SCI, V55, P669
   Lee I, 2018, ATMOSPHERE-BASEL, V9, DOI 10.3390/atmos9030091
   Maas J, 2009, HEALTH PLACE, V15, P586, DOI 10.1016/j.healthplace.2008.09.006
   Meerow S, 2017, LANDSCAPE URBAN PLAN, V159, P62, DOI 10.1016/j.landurbplan.2016.10.005
   Mikulcic Krnjaja G., 2023, Unpublished interview conducted by Nicola Weidmuller
   Millennium Ecosystem Assessment and World Resources Institute, 2005, Ecosystems and human well-being: Synthesis; a report of the Millennium Ecosystem Assessment Online
   Mohajerani A, 2017, J ENVIRON MANAGE, V197, P522, DOI 10.1016/j.jenvman.2017.03.095
   Norton BA, 2015, LANDSCAPE URBAN PLAN, V134, P127, DOI 10.1016/j.landurbplan.2014.10.018
   Pezzagno M, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13169163
   Roy S, 2012, URBAN FOR URBAN GREE, V11, P351, DOI 10.1016/j.ufug.2012.06.006
   Sachsisches Landesamt fur Umwelt Landwirtschaft und Geologie (LfULG), 2020, Strassenbaume im landlichen Raum: Pflanzempfehlungen fur strassenbegleitende Baumreihen und Alleen
   Schröter M, 2012, EUR J FOREST RES, V131, P787, DOI 10.1007/s10342-011-0552-y
   The World Bank, 2022, Urban population (% of total population)
   Thompson CW, 2016, INT J ENV RES PUB HE, V13, DOI 10.3390/ijerph13040440
   Wang JX, 2018, ECOL INDIC, V85, P758, DOI 10.1016/j.ecolind.2017.09.018
   Wang YS, 2021, SUSTAIN CITIES SOC, V75, DOI 10.1016/j.scs.2021.103281
   Wu JS, 2020, ECOL INDIC, V117, DOI 10.1016/j.ecolind.2020.106699
   Zacharias J, 2016, TRANSPORT RES REC, P17, DOI 10.3141/2587-03
NR 34
TC 0
Z9 0
U1 6
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 AUG
PY 2024
VL 23
AR 100154
DI 10.1016/j.cacint.2024.100154
EA JUN 2024
PG 6
WC Environmental Sciences; Environmental Studies; Meteorology & Atmospheric
   Sciences
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA WW0C1
UT WOS:001257780700001
OA gold
DA 2025-01-10
ER

PT J
AU Somorowska, U
AF Somorowska, Urszula
TI Assessing the Impact of Climate Change on Snowfall Conditions in Poland
   Based on the Snow Fraction Sensitivity Index
SO RESOURCES-BASEL
LA English
DT Article
DE climate change; snow fraction; sensitivity; snow-rain transition;
   prediction; midlatitudes; Central Europe
ID PRECIPITATION; TEMPERATURE; ELASTICITY; STREAMFLOW; WATER
AB This study focuses on temperature and snowfall conditions in Poland, both of which were analyzed from 1981 to 2020. A 40-year record of daily snow fraction time series values was reconstructed using a unique and global multi-source weighted-ensemble precipitation (MSWEP) product, which provided a spatially and temporally consistent reference for the assessment of meteorological conditions. The average states and trends in snow fraction and temperature were analyzed across several years, focusing on the 6-month cold season (November-April). The impact of temperature on the snow fraction pattern was assessed by introducing a snow fraction sensitivity index. To predict short-term changes in snow conditions, a proxy model was established; it incorporated historical trends in the snow fraction as well as its mean state. This study provides clear evidence that the snow fraction is principally controlled by increases in temperature. A warming climate will thus cause a decline in the snow fraction, as we observed in vast lowland areas. Given the ongoing global warming, by the 2050s, snow-dominated areas may go from covering 86% to only 30% of the country's surface; they will be converted into transient rain-snow areas. Our results demonstrate that a decline in snow water resources has already occurred, and these resources are expected to diminish further in the near future. New insights into the sensitivity of the snow fraction to climate warming will expand our collective knowledge of the magnitude and spatial extent of snow degradation. Such widespread changes have implications for the timing and availability of soil and groundwater resources as well as the timing and likelihood of floods and droughts. Thus, these findings will provide valuable information that can inform environmental managers of the importance of changing snowfall conditions, guiding them to include this aspect in future climate adaptation strategies.
C1 [Somorowska, Urszula] Univ Warsaw, Fac Geog & Reg Studies, Dept Hydrol, Krakowskie Przedmiescie 30, PL-00927 Warsaw, Poland.
C3 University of Warsaw
RP Somorowska, U (corresponding author), Univ Warsaw, Fac Geog & Reg Studies, Dept Hydrol, Krakowskie Przedmiescie 30, PL-00927 Warsaw, Poland.
EM usomorow@uw.edu.pl
RI Somorowska, Urszula/P-4227-2019
OI Somorowska, Urszula/0000-0001-9861-5107
FU Faculty of Geography and Regional Studies at the University of Warsaw in
   Poland
FX The author thanks the editors and reviewers for their insightful
   comments and helpful suggestions. The author acknowledges the MSWEP
   dataset (version 3.5z), which is available via
   https://www.gloh2o.org/mswep/ (accessed on 23 March 2023). The author
   also acknowledges the E-OBS dataset (version 25.0e) from the EU-FP6
   project ENSEMBLES (http://ensembles-eu.metoffice.com; accessed on 19
   June 2022) and the data providers of the ECA&D project
   (http://www.ecad.eu; accessed on 19 June 2022); version 25.0e of the
   dataset was downloaded from the Copernicus Climate Change Service at
   https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php
   (accessed on 19 June 2022). The author also acknowledges the gridded
   Northern Hemisphere 50% rain-snow Ts threshold product (a formatted
   version of the observational dataset), which was downloaded from the
   DRYAD: spatial variations in the rain-snow temperature threshold across
   the Northern Hemisphere (https://doi.org/10.5061/dryad.c9h35) (accessed
   on 31 January 2022). Additionally, the author acknowledges the
   meteorological data, which are available via
   https://danepubliczne.imgw.pl/data/ (accessed on 25 March 2024) and were
   prepared by the Institute of Meteorology and Water Management in Poland.
CR Andréassian V, 2016, HYDROL EARTH SYST SC, V20, P4503, DOI 10.5194/hess-20-4503-2016
   [Anonymous], Spearman's Correlation (n.d.)
   Aygün O, 2020, PROG PHYS GEOG, V44, P338, DOI 10.1177/0309133319878123
   Beck HE, 2019, B AM METEOROL SOC, V100, P473, DOI 10.1175/BAMS-D-17-0138.1
   Bonsoms J, 2023, CRYOSPHERE, V17, P1307, DOI 10.5194/tc-17-1307-2023
   Choi G, 2010, J CLIMATE, V23, P5305, DOI 10.1175/2010JCLI3644.1
   Clark MP, 1999, INT J CLIMATOL, V19, P27, DOI 10.1002/(SICI)1097-0088(199901)19:1<27::AID-JOC346>3.0.CO;2-N
   Cornes RC, 2018, J GEOPHYS RES-ATMOS, V123, P9391, DOI 10.1029/2017JD028200
   Crausbay SD, 2017, B AM METEOROL SOC, V98, P2543, DOI 10.1175/BAMS-D-16-0292.1
   Czernecki B, 2017, THEOR APPL CLIMATOL, V127, P481, DOI 10.1007/s00704-015-1647-z
   Danielescu S., 2022, Reference Manual
   Dierauer JR, 2021, CAN WATER RESOUR J, V46, P168, DOI 10.1080/07011784.2021.1960894
   Domínguez-Tuda M, 2021, J HYDROL, V603, DOI 10.1016/j.jhydrol.2021.126720
   Dong WH, 2022, J CLIMATE, V35, P5573, DOI 10.1175/JCLI-D-22-0026.1
   Elsner MM, 2010, CLIMATIC CHANGE, V102, P225, DOI 10.1007/s10584-010-9855-0
   Eythorsson D, 2023, REMOTE SENS APPL, V30, DOI 10.1016/j.rsase.2023.100954
   Falarz M., 2021, Climate Change in Poland. Past, Present, Future., P375, DOI DOI 10.1007/978-3-030-70328-8
   Falarz M, 2018, QUAEST GEOGR, V37, P7, DOI 10.2478/quageo-2018-0002
   Fontrodona-Bach A, 2018, GEOPHYS RES LETT, V45, P12312, DOI 10.1029/2018GL079799
   Ford CM, 2021, SCI TOTAL ENVIRON, V793, DOI 10.1016/j.scitotenv.2021.148483
   Ford CM, 2020, J HYDROL, V590, DOI 10.1016/j.jhydrol.2020.125517
   Ghazi B, 2023, SCI REP-UK, V13, DOI 10.1038/s41598-023-46199-5
   Graczyk D, 2017, THEOR APPL CLIMATOL, V129, P459, DOI 10.1007/s00704-016-1786-x
   Greene CA, 2019, GEOCHEM GEOPHY GEOSY, V20, P3774, DOI 10.1029/2019GC008392
   Harpold AA, 2017, HYDROL EARTH SYST SC, V21, P1, DOI 10.5194/hess-21-1-2017
   Harpold AA, 2015, GEOPHYS RES LETT, V42, P8011, DOI 10.1002/2015GL065855
   Hotovy O, 2023, HYDROLOG SCI J, V68, P572, DOI 10.1080/02626667.2023.2177544
   Howat IM, 2005, J GEOPHYS RES-EARTH, V110, DOI 10.1029/2005JF000356
   Jenicek M, 2020, HYDROL EARTH SYST SC, V24, P3475, DOI 10.5194/hess-24-3475-2020
   Jennings KS, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-03629-7
   Kang DH, 2016, SCI REP-UK, V6, DOI 10.1038/srep19299
   Kottek M, 2006, METEOROL Z, V15, P259, DOI 10.1127/0941-2948/2006/0130
   Krasting JP, 2013, J CLIMATE, V26, P7813, DOI 10.1175/JCLI-D-12-00832.1
   Kundzewicz ZW, 2018, ACTA GEOPHYS, V66, P1509, DOI 10.1007/s11600-018-0220-4
   Lin WQ, 2022, INT J CLIMATOL, V42, P1841, DOI 10.1002/joc.7339
   Liu GS, 2008, J GEOPHYS RES-ATMOS, V113, DOI 10.1029/2007JD009766
   López-Moreno JI, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa70cb
   Luce CH, 2014, WATER RESOUR RES, V50, P9447, DOI 10.1002/2013WR014844
   Lupikasza E., 2021, Climate Change in Poland. Past, Present, P349, DOI [10.1007/978-3-030-70328-813, DOI 10.1007/978-3-030-70328-8_13]
   Lupikasza EB, 2023, ADV CLIM CHANG RES, V14, P97, DOI 10.1016/j.accre.2022.11.012
   Moraga JS, 2021, J HYDROL, V603, DOI 10.1016/j.jhydrol.2021.126806
   Mudryk LR, 2017, GEOPHYS RES LETT, V44, P919, DOI 10.1002/2016GL071789
   Newton BW, 2021, WATER-SUI, V13, DOI 10.3390/w13081013
   Nouri M, 2021, J HYDROL, V603, DOI 10.1016/j.jhydrol.2021.126858
   Ombadi M, 2023, NATURE, V619, P305, DOI 10.1038/s41586-023-06092-7
   Pearson's Correlation, ABOUT US
   Peters-Lidard CD, 2021, CLIMATIC CHANGE, V165, DOI 10.1007/s10584-021-03057-5
   Pons F.M.E., 2022, Adv. Stat. Climatol. Meteorol. Oceanogr, V8, P155, DOI [10.5194/ascmo-8-155-2022, DOI 10.5194/ASCMO-8-155-2022]
   Qi Y, 2021, ECOL INDIC, V133, DOI 10.1016/j.ecolind.2021.108351
   Quante L, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-95979-4
   Radziejewski M, 2004, HYDROLOG SCI J, V49, P39, DOI 10.1623/hysj.49.1.39.54002
   Räisänen J, 2008, CLIM DYNAM, V30, P307, DOI 10.1007/s00382-007-0289-y
   Safeeq M, 2016, INT J CLIMATOL, V36, P3175, DOI 10.1002/joc.4545
   Sankarasubramanian A, 2001, WATER RESOUR RES, V37, P1771, DOI 10.1029/2000WR900330
   Solon J, 2018, GEOGR POL, V91, P143, DOI 10.7163/GPol.0115
   Sturm M, 2017, WATER RESOUR RES, V53, P3534, DOI 10.1002/2017WR020840
   Szwed M., 2021, Climate Change in Poland, P513, DOI [10.1007/978-3-030-70328-8_21, DOI 10.1007/978-3-030-70328-8_21]
   Tomczyk AM, 2021, ATMOSPHERE-BASEL, V12, DOI 10.3390/atmos12010068
   Trenberth KE, 2011, CLIM RES, V47, P123, DOI 10.3354/cr00953
   Ustrnul Z., 2021, CLIMATE CHANGE POLAN, P275, DOI DOI 10.1007/978-3-030-70328-8_11
   Vlach V, 2020, WATER-SUI, V12, DOI 10.3390/w12123575
   Wibig J, 2023, INT J CLIMATOL, V43, P6925, DOI 10.1002/joc.8178
   Wieder WR, 2022, P NATL ACAD SCI USA, V119, DOI 10.1073/pnas.2202393119
   Ye HC, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/1/014052
NR 64
TC 1
Z9 1
U1 2
U2 2
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2079-9276
J9 RESOURCES-BASEL
JI Resources-Basel
PD MAY
PY 2024
VL 13
IS 5
AR 60
DI 10.3390/resources13050060
PG 18
WC Green & Sustainable Science & Technology; Environmental Sciences
WE Emerging Sources Citation Index (ESCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA RY9X2
UT WOS:001231347200001
OA gold
DA 2025-01-10
ER

PT J
AU Leal, JL
   Milesi, P
   Hodková, E
   Zhou, QJ
   James, J
   Eklund, DM
   Pyhäjärvi, T
   Salojärvi, J
   Lascoux, M
AF Leal, J. Luis
   Milesi, Pascal
   Hodkova, Eva
   Zhou, Qiujie
   James, Jennifer
   Eklund, D. Magnus
   Pyhajarvi, Tanja
   Salojarvi, Jarkko
   Lascoux, Martin
TI Complex Polyploids: Origins, Genomic Composition, and Role of
   Introgressed Alleles
SO SYSTEMATIC BIOLOGY
LA English
DT Article
DE Allopolyploidy; autopolyploidy; Betula; gene flow; genomic polarization;
   homoeologs; interploidal; introgressive hybridization; polyploid
   phylogenetics; polyploidization simulation; reticulate evolution
ID PHYLOGENETIC-RELATIONSHIPS; SPECIES NETWORKS; GENE FLOW; REPRODUCTIVE
   ISOLATION; NATURAL HYBRIDIZATION; ARABIDOPSIS-THALIANA;
   BAYESIAN-INFERENCE; FREEZING TOLERANCE; MOLECULAR EVIDENCE; TRIPLOID
   HYBRIDS
AB Introgression allows polyploid species to acquire new genomic content from diploid progenitors or from other unrelated diploid or polyploid lineages, contributing to genetic diversity and facilitating adaptive allele discovery. In some cases, high levels of introgression elicit the replacement of large numbers of alleles inherited from the polyploid's ancestral species, profoundly reshaping the polyploid's genomic composition. In such complex polyploids, it is often difficult to determine which taxa were the progenitor species and which taxa provided additional introgressive blocks through subsequent hybridization. Here, we use population-level genomic data to reconstruct the phylogenetic history of Betula pubescens (downy birch), a tetraploid species often assumed to be of allopolyploid origin and which is known to hybridize with at least four other birch species. This was achieved by modeling polyploidization and introgression events under the multispecies coalescent and then using an approximate Bayesian computation rejection algorithm to evaluate and compare competing polyploidization models. We provide evidence that B. pubescens is the outcome of an autoploid genome doubling event in the common ancestor of B. pendula and its extant sister species, B. platyphylla, that took place approximately 178,000-188,000 generations ago. Extensive hybridization with B. pendula, B. nana, and B. humilis followed in the aftermath of autopolyploidization, with the relative contribution of each of these species to the B. pubescens genome varying markedly across the species' range. Functional analysis of B. pubescens loci containing alleles introgressed from B. nana identified multiple genes involved in climate adaptation, while loci containing alleles derived from B. humilis revealed several genes involved in the regulation of meiotic stability and pollen viability in plant species.
C1 [Leal, J. Luis; Milesi, Pascal; Hodkova, Eva; Zhou, Qiujie; James, Jennifer; Lascoux, Martin] Uppsala Univ, Dept Ecol & Genet, Plant Ecol & Evolut, Norbyvagen 18D, S-75236 Uppsala, Sweden.
   [Milesi, Pascal; Lascoux, Martin] Uppsala Univ, Sci Life Lab SciLifeLab, S-75237 Uppsala, Sweden.
   [Hodkova, Eva] Czech Univ Life Sci Prague, Fac Environm Sci, Kamycka 129, Prague 16521, Czech Republic.
   [Eklund, D. Magnus] Uppsala Univ, Dept Organismal Biol, Physiol & Environm Toxicol, Norbyvagen 18A, S-75236 Uppsala, Sweden.
   [Pyhajarvi, Tanja] Univ Helsinki, Fac Biol & Environm Sci, Organismal & Evolutionary Biol Res Program, POB 65 Viikinkaari 1, Helsinki 00014, Finland.
   [Pyhajarvi, Tanja] Univ Helsinki, Viikki Plant Sci Ctr, POB 65 Viikinkaari 1, Helsinki 00014, Finland.
   [Pyhajarvi, Tanja] Univ Helsinki, Dept Forest Sci, Helsinki 00014, Finland.
   [Salojarvi, Jarkko] Nanyang Technol Univ, Sch Biol Sci, 60 Nanyang Dr, Singapore 637551, Singapore.
C3 Uppsala University; Uppsala University; SciLifeLab; Czech University of
   Life Sciences Prague; Uppsala University; University of Helsinki;
   University of Helsinki; University of Helsinki; Nanyang Technological
   University
RP Lascoux, M (corresponding author), Uppsala Univ, Dept Ecol & Genet, Plant Ecol & Evolut, Norbyvagen 18D, S-75236 Uppsala, Sweden.
EM martin.lascoux@ebc.uu.se
RI Zhou, Qiujie/KBQ-2500-2024; Leal, J. Luis/LRT-3182-2024; Pyhäjärvi,
   Tanja/ABD-4161-2021; Salojarvi, Jarkko/E-9103-2016
OI Salojarvi, Jarkko/0000-0002-4096-6278; Leal, J. L./0000-0003-0731-7329;
   Lascoux, Martin/0000-0003-1699-9042; Pyhajarvi,
   Tanja/0000-0001-6958-5172
FU Swedish Research Council for Sustainable Development (FORMAS) [SNIC
   2017/7-149, SNIC 2020/9-84]; Uppsala Multidisciplinary Center for
   Advanced Computational Science (UPPMAX)
FX The computations were performed on resources provided by the Swedish
   National Infrastructure for Computing (SNIC) at the Uppsala
   Multidisciplinary Center for Advanced Computational Science (UPPMAX)
   under Project # SNIC 2017/7-149 and at the High Performance Computing
   Center North (HPC2N) under Project # SNIC 2020/9-84.
CR Albert VA, 2013, SCIENCE, V342, P1467, DOI 10.1126/science.1241089
   Albertin Warren, 2012, Proc Biol Sci, V279, P2497, DOI 10.1098/rspb.2012.0434
   Anamthawat-Jónsson K, 2003, PLANT CELL TISS ORG, V75, P99, DOI 10.1023/A:1025063123552
   ANAMTHAWATJONSSON K, 1990, HEREDITAS, V112, P65, DOI 10.1111/j.1601-5223.1990.tb00138.x
   Arnold B, 2015, MOL BIOL EVOL, V32, P1382, DOI 10.1093/molbev/msv089
   Arnold BJ, 2016, P NATL ACAD SCI USA, V113, P8320, DOI 10.1073/pnas.1600405113
   Ashburner K., 2013, The genus Betula: a taxonomic revision of birches
   ATKINSON MD, 1992, J ECOL, V80, P837, DOI 10.2307/2260870
   Aury JM, 2006, NATURE, V444, P171, DOI 10.1038/nature05230
   Baack E, 2015, NEW PHYTOL, V207, P968, DOI 10.1111/nph.13424
   Baduel P, 2018, FRONT ECOL EVOL, V6, DOI 10.3389/fevo.2018.00117
   Bagherieh-Najjar MB, 2005, PLANT J, V43, P789, DOI 10.1111/j.1365-313X.2005.02501.x
   Bao SD, 2001, NATURE, V411, P969, DOI 10.1038/35082110
   Barker MS, 2016, NEW PHYTOL, V210, P391, DOI 10.1111/nph.13698
   BARTON NH, 1989, NATURE, V341, P497, DOI 10.1038/341497a0
   Beaumont MA, 2002, GENETICS, V162, P2025
   Beaumont MA, 2019, ANNU REV STAT APPL, V6, P379, DOI 10.1146/annurev-statistics-030718-105212
   Berthelot C, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms4657
   Bertrand YJK, 2015, SYST BIOL, V64, P448, DOI 10.1093/sysbio/syv004
   Bleeker W, 2003, MOL ECOL, V12, P1831, DOI 10.1046/j.1365-294X.2003.01854.x
   Bleeker W, 2001, MOL ECOL, V10, P2013, DOI 10.1046/j.1365-294X.2001.01341.x
   Blischak PD, 2018, ANNU REV ECOL EVOL S, V49, P253, DOI 10.1146/annurev-ecolsys-121415-032302
   Bomblies K, 2023, PLANT REPROD, V36, P107, DOI 10.1007/s00497-022-00448-1
   Bomblies K, 2015, NEW PHYTOL, V208, P306, DOI 10.1111/nph.13499
   Bowers JE, 2003, NATURE, V422, P433, DOI 10.1038/nature01521
   Braasch I., 2012, Polyploidy and Genome Evolution, P341, DOI [DOI 10.1007/978-3-642-31442-117, 10.1007/978-3-642-31442-1_17, DOI 10.1007/978-3-642-31442-1_17]
   BROWN IR, 1979, NEW PHYTOL, V83, P801, DOI 10.1111/j.1469-8137.1979.tb02311.x
   Bryant D, 2004, MOL BIOL EVOL, V21, P255, DOI 10.1093/molbev/msh018
   Burns R, 2021, NAT ECOL EVOL, V5, P1367, DOI 10.1038/s41559-021-01525-w
   Caldwell KS, 2009, GENETICS, V181, P671, DOI 10.1534/genetics.108.097279
   CAO H, 1994, PLANT CELL, V6, P1583, DOI 10.1105/tpc.6.11.1583
   Cerca J, 2021, GENOME BIOL EVOL, V13, DOI 10.1093/gbe/evab262
   Chalhoub B, 2014, SCIENCE, V345, P950, DOI 10.1126/science.1253435
   Chen S, 2021, HORTIC RES-ENGLAND, V8, DOI 10.1038/s41438-021-00481-7
   Chen XS, 2016, ELIFE, V5, DOI 10.7554/eLife.17214
   Cheng H, 2019, GENOME BIOL, V20, DOI 10.1186/s13059-019-1744-x
   Chenuil A, 1999, HEREDITY, V82, P373, DOI 10.1038/sj.hdy.6884890
   Chester M, 2012, P NATL ACAD SCI USA, V109, P1176, DOI 10.1073/pnas.1112041109
   Cifuentes M, 2010, NEW PHYTOL, V186, P29, DOI 10.1111/j.1469-8137.2009.03084.x
   Cingolani P, 2012, FLY, V6, P80, DOI 10.4161/fly.19695
   Clark LV, 2015, J EXP BOT, V66, P4213, DOI 10.1093/jxb/eru511
   Comai L, 2005, NAT REV GENET, V6, P836, DOI 10.1038/nrg1711
   CORNISHBOWDEN A, 1985, NUCLEIC ACIDS RES, V13, P3021, DOI 10.1093/nar/13.9.3021
   Danecek P, 2021, GIGASCIENCE, V10, DOI 10.1093/gigascience/giab008
   Dasmahapatra KK, 2012, NATURE, V487, P94, DOI 10.1038/nature11041
   De Bodt S, 2005, TRENDS ECOL EVOL, V20, P591, DOI 10.1016/j.tree.2005.07.008
   DeGroot WJ, 1997, J ECOL, V85, P241, DOI 10.2307/2960655
   Dehal P, 2005, PLOS BIOL, V3, P1700, DOI 10.1371/journal.pbio.0030314
   Ding JH, 2021, NEW PHYTOL, V232, P2339, DOI 10.1111/nph.17350
   Dong MA, 2011, P NATL ACAD SCI USA, V108, P7241, DOI 10.1073/pnas.1103741108
   Dowling TE, 1997, ANNU REV ECOL SYST, V28, P593, DOI 10.1146/annurev.ecolsys.28.1.593
   Eidesen PB, 2015, MOL ECOL, V24, P3993, DOI 10.1111/mec.13289
   Ellstrand NC, 2014, AM J BOT, V101, P737, DOI 10.3732/ajb.1400024
   Enns LC, 2005, PLANT MOL BIOL, V58, P333, DOI 10.1007/s11103-005-4526-7
   Excoffier L, 2013, PLOS GENET, V9, DOI 10.1371/journal.pgen.1003905
   Excoffier L, 2009, ANNU REV ECOL EVOL S, V40, P481, DOI 10.1146/annurev.ecolsys.39.110707.173414
   Falush D, 2007, MOL ECOL NOTES, V7, P574, DOI 10.1111/j.1471-8286.2007.01758.x
   FELBER F, 1991, J EVOLUTION BIOL, V4, P195, DOI 10.1046/j.1420-9101.1991.4020195.x
   Filiault DL, 2008, P NATL ACAD SCI USA, V105, P3157, DOI 10.1073/pnas.0712174105
   Fletcher W, 2009, MOL BIOL EVOL, V26, P1879, DOI 10.1093/molbev/msp098
   Fontaine MC, 2015, SCIENCE, V347, DOI 10.1126/science.1258524
   Fraïsse C, 2021, MOL ECOL RESOUR, V21, P2629, DOI 10.1111/1755-0998.13323
   Freyman WA, 2023, METHODS ECOL EVOL, V14, P1230, DOI 10.1111/2041-210X.14072
   Fujiwara S, 2008, PLANT CELL, V20, P2960, DOI 10.1105/tpc.108.061531
   Gaeta RT, 2010, NEW PHYTOL, V186, P18, DOI 10.1111/j.1469-8137.2009.03089.x
   Grant PR, 2020, P NATL ACAD SCI USA, V117, P7888, DOI 10.1073/pnas.2000388117
   GRANT PR, 1992, SCIENCE, V256, P193, DOI 10.1126/science.256.5054.193
   Gutenkunst RN, 2009, PLOS GENET, V5, DOI 10.1371/journal.pgen.1000695
   Hajdu A, 2015, PLANT J, V83, P794, DOI 10.1111/tpj.12926
   Hardigan MA, 2017, P NATL ACAD SCI USA, V114, pE9999, DOI 10.1073/pnas.1714380114
   Hartung F, 2008, PLOS GENET, V4, DOI 10.1371/journal.pgen.1000285
   Heitzeberg F, 2004, PLANT J, V38, P954, DOI 10.1111/j.1365-313X.2004.02097.x
   Heled J, 2010, MOL BIOL EVOL, V27, P570, DOI 10.1093/molbev/msp274
   Higgins JD, 2011, PLANT J, V65, P492, DOI 10.1111/j.1365-313X.2010.04438.x
   Hohmann N, 2017, BMC GENOMICS, V18, DOI 10.1186/s12864-017-4220-6
   Hohmann N, 2014, BMC EVOL BIOL, V14, DOI 10.1186/s12862-014-0224-x
   HOWLAND DE, 1995, NEW PHYTOL, V130, P117, DOI 10.1111/j.1469-8137.1995.tb01821.x
   Hu Q, 2018, FRONT PLANT SCI, V9, DOI 10.3389/fpls.2018.01236
   Husband BC, 2004, BIOL J LINN SOC, V82, P537, DOI 10.1111/j.1095-8312.2004.00339.x
   Huson DH, 2006, MOL BIOL EVOL, V23, P254, DOI 10.1093/molbev/msj030
   Ingvarsson PK, 2008, GENETICS, V178, P2217, DOI 10.1534/genetics.107.082354
   Jadwiszczak KA, 2012, TREE GENET GENOMES, V8, P1017, DOI 10.1007/s11295-012-0482-y
   Järvinen P, 2004, AM J BOT, V91, P1834, DOI 10.3732/ajb.91.11.1834
   Jeffers R. M., 1971, RES I FOREST GENETIC, P17
   Jiang XY, 2021, NAT ECOL EVOL, V5, P1382, DOI 10.1038/s41559-021-01523-y
   Johnsson H., 1944, Botaniska Notiser, P85
   Jombart T, 2010, BMC GENET, V11, DOI 10.1186/1471-2156-11-94
   Jones G, 2013, SYST BIOL, V62, P467, DOI 10.1093/sysbio/syt012
   Jorgensen MH, 2011, BMC EVOL BIOL, V11, DOI 10.1186/1471-2148-11-346
   Joubès J, 2008, PLANT MOL BIOL, V67, P547, DOI 10.1007/s11103-008-9339-z
   Jung JH, 2016, SCIENCE, V354, P886, DOI 10.1126/science.aaf6005
   Kaczorowski KA, 2003, PLANT CELL, V15, P2654, DOI 10.1105/tpc.015065
   Kamm J, 2020, J AM STAT ASSOC, V115, P1472, DOI 10.1080/01621459.2019.1635482
   Keightley PD, 2018, GENETICS, V209, P897, DOI 10.1534/genetics.118.301120
   Keller I, 2013, MOL ECOL, V22, P2848, DOI 10.1111/mec.12083
   Kellis M, 2004, NATURE, V428, P617, DOI 10.1038/nature02424
   Kim HJ, 2002, PLANT J, V29, P693, DOI 10.1046/j.1365-313X.2002.01249.x
   Kim M, 2008, SCIENCE, V322, P1116, DOI 10.1126/science.1164371
   Kim Y, 2013, PLANT J, V75, P364, DOI 10.1111/tpj.12205
   Kim YJ, 2016, P NATL ACAD SCI USA, V113, P14858, DOI 10.1073/pnas.1618618114
   Koch MA, 2007, P NATL ACAD SCI USA, V104, P6272, DOI 10.1073/pnas.0701338104
   Koch MA, 2019, J EXP BOT, V70, P55, DOI 10.1093/jxb/ery340
   Koropachinskii IY, 2013, CONTEMP PROBL ECOL+, V6, P350, DOI 10.1134/S1995425513040045
   Krehenwinkel H, 2013, MOL ECOL, V22, P2232, DOI 10.1111/mec.12223
   Lafon-Placette C, 2017, P NATL ACAD SCI USA, V114, pE1027, DOI 10.1073/pnas.1615123114
   Lamichhaney S, 2015, NATURE, V518, P371, DOI 10.1038/nature14181
   Lashermes P, 2016, G3-GENES GENOM GENET, V6, P2937, DOI 10.1534/g3.116.030858
   Lautenschlager U, 2020, BMC BIOINFORMATICS, V21, DOI 10.1186/s12859-020-03750-9
   Leal JL, 2023, SYST BIOL, V72, P372, DOI 10.1093/sysbio/syad009
   Legris M, 2016, SCIENCE, V354, P897, DOI 10.1126/science.aaf5656
   Li FG, 2015, NAT BIOTECHNOL, V33, P524, DOI 10.1038/nbt.3208
   Li H, 2009, BIOINFORMATICS, V25, P1094, DOI [10.1093/bioinformatics/btp100, 10.1093/bioinformatics/btp324]
   Li JH, 2005, RHODORA, V107, P69, DOI 10.3119/04-14.1
   Li JH, 2007, SYST BOT, V32, P357, DOI 10.1600/036364407781179699
   Li LL, 2022, NEW PHYTOL, V236, P1976, DOI 10.1111/nph.18480
   Li X, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0201854
   Li Z, 2018, P NATL ACAD SCI USA, V115, P4713, DOI 10.1073/pnas.1710791115
   Lihová J, 2007, ANN BOT-LONDON, V99, P1083, DOI 10.1093/aob/mcm056
   Lim CJ, 2020, PLANT PHYSIOL, V184, P1097, DOI 10.1104/pp.20.00439
   Liu ZR, 2001, PLANT J, V26, P329, DOI 10.1046/j.1365-313X.2001.01031.x
   Lloyd A, 2018, NEW PHYTOL, V217, P367, DOI 10.1111/nph.14836
   Lloyd A, 2016, CURR OPIN PLANT BIOL, V30, P116, DOI 10.1016/j.pbi.2016.02.004
   Ma LM, 2009, PLOS PATHOG, V5, DOI 10.1371/journal.ppat.1000354
   Macqueen DJ, 2014, P ROY SOC B-BIOL SCI, V281, DOI 10.1098/rspb.2013.2881
   Maddison WP, 2006, SYST BIOL, V55, P21, DOI 10.1080/10635150500354928
   Mallet J, 2005, TRENDS ECOL EVOL, V20, P229, DOI 10.1016/j.tree.2005.02.010
   Mallet J, 2007, NATURE, V446, P279, DOI 10.1038/nature05706
   Mallet J, 2016, BIOESSAYS, V38, P140, DOI 10.1002/bies.201500149
   Mallo D, 2016, SYST BIOL, V65, P334, DOI 10.1093/sysbio/syv082
   Mandel JR, 2017, J SYST EVOL, V55, P405, DOI 10.1111/jse.12265
   Marburger S, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-13159-5
   Marhold K, 2006, PLANT SYST EVOL, V259, P143, DOI 10.1007/s00606-006-0417-x
   Maruyama K, 2009, PLANT PHYSIOL, V150, P1972, DOI 10.1104/pp.109.135327
   McCormack JE, 2009, SYST BIOL, V58, P501, DOI 10.1093/sysbio/syp045
   McDonald DB, 2008, P NATL ACAD SCI USA, V105, P10837, DOI 10.1073/pnas.0712002105
   McKenna A, 2010, GENOME RES, V20, P1297, DOI 10.1101/gr.107524.110
   Meier JI, 2017, NAT COMMUN, V8, DOI 10.1038/ncomms14363
   Merret R, 2013, CELL REP, V5, P1279, DOI 10.1016/j.celrep.2013.11.019
   Minh BQ, 2020, MOL BIOL EVOL, V37, P1530, DOI 10.1093/molbev/msaa015
   Mirarab S, 2016, SYST BIOL, V65, P366, DOI 10.1093/sysbio/syu063
   Monnahan P, 2019, NAT ECOL EVOL, V3, P457, DOI 10.1038/s41559-019-0807-4
   Morgan C, 2021, CURR BIOL, V31, P4713, DOI 10.1016/j.cub.2021.08.028
   Muñoz-Rodríguez P, 2018, CURR BIOL, V28, P1246, DOI 10.1016/j.cub.2018.03.020
   Nibau C, 2022, PLANT J, V111, P1110, DOI 10.1111/tpj.15879
   Feliner GN, 2020, FRONT GENET, V11, DOI 10.3389/fgene.2020.00792
   Nossa CW, 2014, GIGASCIENCE, V3, DOI 10.1186/2047-217X-3-9
   Novikova PY, 2020, PLOS GENET, V16, DOI 10.1371/journal.pgen.1008769
   Novikova PY, 2017, MOL BIOL EVOL, V34, P957, DOI 10.1093/molbev/msw299
   Oberprieler C, 2017, METHODS ECOL EVOL, V8, P835, DOI 10.1111/2041-210X.12694
   Opgenoorth L, 2021, GIGASCIENCE, V10, DOI 10.1093/gigascience/giab010
   Oxelman B, 2017, ANNU REV ECOL EVOL S, V48, P543, DOI 10.1146/annurev-ecolsys-110316-022729
   Palme AE, 2004, MOL ECOL, V13, P167, DOI 10.1046/j.1365-294X.2003.02034.x
   Pardo-Diaz C, 2012, PLOS GENET, V8, DOI 10.1371/journal.pgen.1002752
   Pickrell JK, 2012, PLOS GENET, V8, DOI 10.1371/journal.pgen.1002967
   Rabiee M, 2019, MOL PHYLOGENET EVOL, V130, P286, DOI 10.1016/j.ympev.2018.10.033
   Ramsey J, 1998, ANNU REV ECOL SYST, V29, P467, DOI 10.1146/annurev.ecolsys.29.1.467
   Ramsey J, 2002, ANNU REV ECOL SYST, V33, P589, DOI 10.1146/annurev.ecolsys.33.010802.150437
   Renard J, 2020, PLANT CELL ENVIRON, V43, P2523, DOI 10.1111/pce.13822
   Rieseberg LH, 1999, HEREDITY, V83, P363, DOI 10.1038/sj.hdy.6886170
   Rieseberg LH, 2007, SCIENCE, V317, P910, DOI 10.1126/science.1137729
   Rius M, 2014, TRENDS ECOL EVOL, V29, P233, DOI 10.1016/j.tree.2014.02.003
   Robertson FM, 2017, GENOME BIOL, V18, DOI 10.1186/s13059-017-1241-z
   Rothfels CJ, 2021, NEW PHYTOL, V230, P66, DOI 10.1111/nph.17105
   Roux C, 2015, MOL ECOL, V24, P1047, DOI 10.1111/mec.13078
   Salojarvi J., 2023, BIORXIV, p2023.09.06.556570
   Salojärvi J, 2017, NAT GENET, V49, P904, DOI 10.1038/ng.3862
   Schenk MF, 2008, TREE GENET GENOMES, V4, P911, DOI 10.1007/s11295-008-0162-0
   Schmickl R, 2021, NEW PHYTOL, V230, P457, DOI 10.1111/nph.17204
   Schmickl R, 2017, J EXP BOT, V68, P5453, DOI 10.1093/jxb/erx297
   Schwager EE, 2017, BMC BIOL, V15, DOI 10.1186/s12915-017-0399-x
   Seear PJ, 2020, PLOS GENET, V16, DOI 10.1371/journal.pgen.1008900
   Seehausen O, 2006, P ROY SOC B-BIOL SCI, V273, P1987, DOI 10.1098/rspb.2006.3539
   Séguéla-Arnaud M, 2015, P NATL ACAD SCI USA, V112, P4713, DOI 10.1073/pnas.1423107112
   Seo M, 2006, PLANT J, V48, P354, DOI 10.1111/j.1365-313X.2006.02881.x
   Serra H, 2018, P NATL ACAD SCI USA, V115, P2437, DOI 10.1073/pnas.1713071115
   Shen H, 2007, PLANT PHYSIOL, V145, P1471, DOI 10.1104/pp.107.107227
   Shi X, 2015, PLANT CELL PHYSIOL, V56, P497, DOI 10.1093/pcp/pcu193
   Sicard A, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms8960
   Slotte T, 2008, MOL BIOL EVOL, V25, P1472, DOI 10.1093/molbev/msn092
   Solís-Lemus C, 2017, MOL BIOL EVOL, V34, P3292, DOI 10.1093/molbev/msx235
   Soltis PS, 2009, ANNU REV PLANT BIOL, V60, P561, DOI 10.1146/annurev.arplant.043008.092039
   Somers DE, 1998, SCIENCE, V282, P1488, DOI 10.1126/science.282.5393.1488
   Spoelhof JP, 2017, J SYST EVOL, V55, P340, DOI 10.1111/jse.12253
   Stebbins G., 1971, CHROMOSOMAL EVOLUTIO
   STEBBINS GL, 1956, AM J BOT, V43, P890, DOI 10.2307/2439006
   STERN K., 1965, SILVAE GENET, V14, P56
   Suarez-Gonzalez A, 2018, NEW PHYTOL, V217, P416, DOI 10.1111/nph.14779
   Sun FM, 2017, PLANT J, V92, P452, DOI 10.1111/tpj.13669
   Tavare S, 1997, GENETICS, V145, P505
   Than C, 2008, BMC BIOINFORMATICS, V9, DOI 10.1186/1471-2105-9-322
   Thorsson AET, 2001, J HERED, V92, P404, DOI 10.1093/jhered/92.5.404
   Truong C, 2007, J EVOLUTION BIOL, V20, P369, DOI 10.1111/j.1420-9101.2006.01190.x
   Tsuda Y, 2017, MOL ECOL, V26, P589, DOI 10.1111/mec.13885
   Van De Peer Y, 2017, NAT REV GENET, V18, P411, DOI 10.1038/nrg.2017.26
   Wagner ND, 2020, FRONT PLANT SCI, V11, DOI 10.3389/fpls.2020.01077
   Walters S. M., 1968, Proceedings of the Botanical Society of the British Isles, V7, P179
   Wang N, 2021, MOL PHYLOGENET EVOL, V160, DOI 10.1016/j.ympev.2021.107126
   Wang N, 2016, ANN BOT-LONDON, V117, P1023, DOI 10.1093/aob/mcw048
   Wang N, 2014, MOL ECOL, V23, P2771, DOI 10.1111/mec.12768
   Wang Z, 2019, NAT PLANTS, V5, P810, DOI 10.1038/s41477-019-0452-6
   Wen DQ, 2018, SYST BIOL, V67, P735, DOI 10.1093/sysbio/syy015
   Whitney KD, 2006, AM NAT, V167, P794, DOI 10.1086/504606
   Winkler M, 2017, MOL ECOL RESOUR, V17, P877, DOI 10.1111/1755-0998.12641
   Wolfe KH, 1997, NATURE, V387, P708, DOI 10.1038/42711
   Wood TE, 2009, P NATL ACAD SCI USA, V106, P13875, DOI 10.1073/pnas.0811575106
   Wu Y, 2021, NATL SCI REV, V8, DOI 10.1093/nsr/nwaa277
   Xiong ZY, 2021, G3-GENES GENOM GENET, V11, DOI 10.1093/g3journal/jkaa011
   Yan Z, 2022, SYST BIOL, V71, P706, DOI 10.1093/sysbio/syab081
   Yano R, 2005, PLANT PHYSIOL, V138, P837, DOI 10.1104/pp.104.056374
   Yant L, 2013, CURR BIOL, V23, P2151, DOI 10.1016/j.cub.2013.08.059
   Yoshida K, 2013, ELIFE, V2, DOI 10.7554/eLife.00731
   Zhang C, 2018, BMC BIOINFORMATICS, V19, DOI 10.1186/s12859-018-2129-y
   Zhang C, 2018, MOL BIOL EVOL, V35, P504, DOI 10.1093/molbev/msx307
   Zhang TF, 2021, FRONT PSYCHOL, V12, DOI 10.3389/fpsyg.2021.660564
   Zhou BBS, 2000, NATURE, V408, P433, DOI 10.1038/35044005
   Zohren J, 2016, MOL ECOL, V25, P2413, DOI 10.1111/mec.13644
NR 216
TC 3
Z9 3
U1 7
U2 10
PU OXFORD UNIV PRESS
PI OXFORD
PA GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND
SN 1063-5157
EI 1076-836X
J9 SYST BIOL
JI Syst. Biol.
PD APR 17
PY 2024
VL 73
IS 2
BP 392
EP 418
DI 10.1093/sysbio/syae012
EA APR 2024
PG 27
WC Evolutionary Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Evolutionary Biology
GA ZU5X4
UT WOS:001203806900001
PM 38613229
OA Green Submitted, hybrid
DA 2025-01-10
ER

PT J
AU Kichloo, MA
   Sharma, K
   Sharma, N
AF Kichloo, Muzaffar A.
   Sharma, Koustubh
   Sharma, Neeraj
TI Climate casualties or human disturbance? Shrinking distribution of the
   three large carnivores in the Greater Himalaya
SO CLIMATIC CHANGE
LA English
DT Article
DE Snow leopard; Common leopard; Asiatic black bear; Climate change;
   Multi-season occupancy analysis; Local ecological knowledge; Imperfect
   detection
ID LEOPARD PANTHERA-UNCIA; ASIATIC BLACK BEARS; SNOW LEOPARDS; CONSERVATION
   BIOGEOGRAPHY; RESOURCE SELECTION; URSUS-AMERICANUS; EXTINCTION RISK;
   SITE OCCUPANCY; WILD PREY; HABITAT
AB Mammalian carnivores are key to our understanding of ecosystem dynamics, but most of them are threatened with extinction all over the world. Conservating large carnivores is often an arduous task considering the complex relationship between humans and carnivores, and the diverse range and reasons of threats they face. Climate change is exacerbating the situation further by interacting with most existing threats and amplifying their impacts. The Mountains of Central and South Asia are warming twice as rapidly as the rest of the northern hemisphere. There has been limited research on the effect of climate change and other variables on large carnivores. We studied the patterns in spatio-temporal distribution of three sympatric carnivores, common leopard, snow leopard, and Asiatic black bear in Kishtwar high altitude National Park, a protected area in the Great Himalayan region of Jammu and Kashmir. We investigated the effects of key habitat characteristics as well as human disturbance and climatic factors to understand the spatio-temporal change in their distributions between the early 1990s and around the year 2016-2017. We found a marked contraction in the distribution of the three carnivores between the two time periods. While snow leopard shifted upwards and further away from human settlements, common leopard and Asiatic black bear suffered higher rates of local extinctions at higher altitudes and shifted to lower areas with more vegetation, even if that brought them closer to settlements. We also found some evidence that snow leopards were less likely to have faced range contraction in areas with permanent glaciers. Our study underscores the importance of climate adaptive conservation practices for long-term management in the Greater Himalaya, including the monitoring of changes in habitat, and space-use patterns by human communities and wildlife.
C1 [Kichloo, Muzaffar A.] Govt Degree Coll Banihal, Dept Environm Sci, Banihal, Jammu & Kashmir, India.
   [Sharma, Koustubh] Snow Leopard Trust, Global Snow Leopard & Ecosyst Protect Program, Bishkek, Kyrgyzstan.
   [Sharma, Neeraj] Univ Jammu, Inst Mt Environm, Jammu, India.
C3 University of Jammu
RP Sharma, K (corresponding author), Snow Leopard Trust, Global Snow Leopard & Ecosyst Protect Program, Bishkek, Kyrgyzstan.
EM omar.mzfr@gmail.com; koustubhsharma@gmail.com; nirazsharma@gmail.com
RI Sharma, Koustubh/AEU-6505-2022; Kichloo, Muzaffar A/JWP-0412-2024;
   Sharma, Neeraj/ABH-0361-2022
OI Sharma, Koustubh/0000-0001-7301-441X; Kichloo, Muzaffar
   A/0000-0001-9720-4912
CR Abade L, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0204370
   Anderson DR, 2002, J WILDLIFE MANAGE, V66, P912, DOI 10.2307/3803155
   [Anonymous], 2008, IUCN 2012 IUCN RED L
   Bashir T, 2018, MAMM BIOL, V92, P11, DOI 10.1016/j.mambio.2018.04.004
   Bista Rabindra, 2013, Zoology and Ecology, V23, P83, DOI 10.1080/21658005.2013.774813
   BROWN JH, 1984, AM NAT, V124, P255, DOI 10.1086/284267
   Cardillo M, 2005, SCIENCE, V309, P1239, DOI 10.1126/science.1116030
   Ceballos G, 2005, SCIENCE, V309, P603, DOI 10.1126/science.1114015
   Charoo SA., 2009, 51 WILDL I IND, P51
   Duquette JF, 2017, CAN J ZOOL, V95, P203, DOI 10.1139/cjz-2016-0031
   Estes JA, 2011, SCIENCE, V333, P301, DOI 10.1126/science.1205106
   Forrest JL, 2012, BIOL CONSERV, V150, P129, DOI 10.1016/j.biocon.2012.03.001
   Garshelis D., 2016, The IUCN Red List of Threatened Species, V2016
   Ghoshal A, 2019, ORYX, V53, P620, DOI 10.1017/S0030605317001107
   Gubbi S, 2020, PEERJ, V8, DOI 10.7717/peerj.10072
   Hilaluddin Hilaluddin, 2013, Indian Forester, V139, P872
   Hiller TL, 2015, URSUS, V26, P116, DOI 10.2192/URSUS-D-15-00023.1
   Inskip C, 2009, ORYX, V43, P18, DOI 10.1017/S003060530899030X
   IUCN, 2016, The IUCN Red List of Threatened Species
   Jackson RM, 2006, WILDLIFE SOC B, V34, P772, DOI 10.2193/0091-7648(2006)34[772:ESLPAU]2.0.CO;2
   Janecka JE, 2011, J MAMMAL, V92, P771, DOI 10.1644/10-MAMM-A-036.1
   Kichloo Muzaffar A., 2021, Asian Journal of Animal Sciences, V15, P19
   Kshettry A, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0177013
   Li J, 2016, BIOL CONSERV, V203, P188, DOI 10.1016/j.biocon.2016.09.026
   Linnell JDC, 2000, BIODIVERS CONSERV, V9, P857, DOI 10.1023/A:1008969104618
   Liu F, 2009, DIVERS DISTRIB, V15, P649, DOI 10.1111/j.1472-4642.2009.00571.x
   Lomolino M.V., 2010, Biogeography, V4th edition
   Lovari S, 2013, J ZOOL, V291, P127, DOI 10.1111/jzo.12053
   MacKenzie D. I., 2004, Animal Biodiversity and Conservation, V27, P461
   MacKenzie D. I., 2018, Occupancy Estimation and Modeling Inferring Patterns and Dynamics of Species Occurrence, V2nd
   MacKenzie D.I., 2006, Occupancy estimation and modelling, DOI DOI 10.2981/0909-6396(2006)12[450:OEAMIP]2.0.CO;2
   MacKenzie DI, 2003, ECOLOGY, V84, P2200, DOI 10.1890/02-3090
   Maurer JM, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aav7266
   McCarthy KP, 2008, J WILDLIFE MANAGE, V72, P1826, DOI 10.2193/2008-040
   McCarthy TM., 2003, SNOW LEOPARD SURVIVA, P145
   McLellan BN, 2011, CAN J ZOOL, V89, P546, DOI 10.1139/Z11-026
   Mishra C, 2004, J APPL ECOL, V41, P344, DOI 10.1111/j.0021-8901.2004.00885.x
   OLI MK, 1994, J MAMMAL, V75, P998, DOI 10.2307/1382482
   Pillay R, 2011, BIOL CONSERV, V144, P1567, DOI 10.1016/j.biocon.2011.01.026
   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]
   QGIS Development Team, 2022, QGIS Geographic Information System
   Richardson DM, 2010, DIVERS DISTRIB, V16, P313, DOI 10.1111/j.1472-4642.2010.00660.x
   Ripple WJ, 2014, SCIENCE, V343, P151, DOI 10.1126/science.1241484
   Royle JA, 2006, ECOLOGY, V87, P835, DOI 10.1890/0012-9658(2006)87[835:GSOMAF]2.0.CO;2
   RStudio Team, 2022, RStudio: Integrated Development for R. RStudio
   Sathyakumar S, 2001, URSUS-SERIES, V12, P21
   Segan DB, 2016, GLOB ECOL CONSERV, V5, P12, DOI 10.1016/j.gecco.2015.11.002
   Sharma K, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0101319
   Sillero-Zubiri C, 2001, CONSERV BIOL SER, V5, P282
   Stein A. B., 2020, IUCN red list threat. Species, V2020, DOI [10.2305/IUCN.UK.2020-1.RLTS.T15954A163991139.en, DOI 10.2305/IUCN.UK.2020-1.RLTS.T15954A163991139.EN]
   Stetz JB, 2019, ECOGRAPHY, V42, P237, DOI 10.1111/ecog.03556
   Strampelli P, 2018, MAMM BIOL, V89, P14, DOI 10.1016/j.mambio.2017.12.003
   Takahata C, 2017, J WILDLIFE MANAGE, V81, P1254, DOI 10.1002/jwmg.21305
   Taubmann J, 2016, ORYX, V50, P220, DOI 10.1017/S0030605315000502
   Thomas CD, 2004, NATURE, V427, P145, DOI 10.1038/nature02121
   Treves A, 2003, CONSERV BIOL, V17, P1491, DOI 10.1111/j.1523-1739.2003.00059.x
   van der Hoeven Christiaan A., 2004, Journal for Nature Conservation (Jena), V12, P193, DOI 10.1016/j.jnc.2004.06.003
   Wang TM, 2017, BIOL CONSERV, V210, P47, DOI 10.1016/j.biocon.2016.03.014
   Wegge P, 2012, WILDLIFE BIOL, V18, P131, DOI 10.2981/11-049
   Whittaker RJ, 2005, DIVERS DISTRIB, V11, P3, DOI 10.1111/j.1366-9516.2005.00143.x
   Wiegand T, 2008, ECOL MONOGR, V78, P87, DOI 10.1890/06-1870.1
   Zeller KA, 2011, BIOL CONSERV, V144, P892, DOI 10.1016/j.biocon.2010.12.003
NR 62
TC 2
Z9 2
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 SEP
PY 2023
VL 176
IS 9
AR 118
DI 10.1007/s10584-023-03582-5
PG 17
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA P1WW5
UT WOS:001048625200001
DA 2025-01-10
ER

PT J
AU Chakrabarty, S
   Mufumbo, R
   Windpassinger, S
   Jordan, D
   Mace, E
   Snowdon, R
   Hathorn, A
AF Chakrabarty, Subhadra
   Mufumbo, Raphael
   Windpassinger, Steffen
   Jordan, David
   Mace, Emma
   Snowdon, Rod J.
   Hathorn, Adrian
TI Genetic and genomic diversity in the sorghum gene bank collection of
   Uganda
SO BMC PLANT BIOLOGY
LA English
DT Article
DE Sorghum bicolor; Genetic diversity; Population structure; Cold
   tolerance; Temperate climate adaptation; Genome-wide association study;
   Genebank
ID QUANTITATIVE TRAIT LOCI; MIXED-MODEL; ASSOCIATION; TEMPERATURE;
   DIVERSIFICATION; DOMESTICATION; ADAPTATION; HISTORY; MOENCH
AB Background The Plant Genetic Resources Centre at the Uganda National Gene Bank houses has over 3000 genetically diverse landraces and wild relatives of Sorghum bicolor accessions. This genetic diversity resource is untapped, under-utilized, and has not been systematically incorporated into sorghum breeding programs. In this study, we characterized the germplasm collection using whole-genome SNP markers (DArTseq). Discriminant analysis of principal components (DAPC) was implemented to study the racial ancestry of the accessions in comparison to a global sorghum diversity set and characterize the sub-groups present in the Ugandan (UG) germplasm. Results Population structure and phylogenetic analysis revealed the presence of five subgroups among the Ugandan accessions. The samples from the highlands of the southwestern region were genetically distinct as compared to the rest of the population. This subset was predominated by the caudatum race and unique in comparison to the other sub-populations. In this study, we detected QTL for juvenile cold tolerance by genome-wide association studies (GWAS) resulting in the identification of 4 markers associated (-log10p > 3) to survival under cold stress under both field and climate chamber conditions, located on 3 chromosomes (02, 06, 09). To our best knowledge, the QTL on Sb09 with the strongest association was discovered for the first time. Conclusion This study demonstrates how genebank genomics can potentially facilitate effective and efficient usage of valuable, untapped germplasm collections for agronomic trait evaluation and subsequent allele mining. In face of adverse climate change, identification of genomic regions potentially involved in the adaptation of Ugandan sorghum accessions to cooler climatic conditions would be of interest for the expansion of sorghum production into temperate latitudes.
C1 [Chakrabarty, Subhadra; Mufumbo, Raphael; Windpassinger, Steffen; Snowdon, Rod J.] Justus Liebig Univ, Dept Plant Breeding, Giessen, Germany.
   [Mufumbo, Raphael] Natl Agr Res Labs, Uganda Natl Gene Bank, Kampala, Uganda.
   [Jordan, David; Mace, Emma; Hathorn, Adrian] Univ Queensland, Queensland Alliance Agr & Food Innovat, Warwick, Qld 4370, Australia.
C3 Justus Liebig University Giessen; University of Queensland
RP Snowdon, R (corresponding author), Justus Liebig Univ, Dept Plant Breeding, Giessen, Germany.
EM Rod.Snowdon@agrar.uni-giessen.de
RI Hathorn, Adrian/F-7478-2011; Mace, Emma/C-8129-2011
OI Snowdon, Rod/0000-0001-5577-7616
FU German Research Foundation (DFG) [SN 14/21-1]
FX Open Access funding enabled and organized by Projekt DEAL. The study was
   funded by grant number SN 14/21-1 from the German Research Foundation
   (DFG) to RJS.
CR Akatwijuka R., 2016, African Crop Science Journal, V24, P179
   Akbari M, 2006, THEOR APPL GENET, V113, P1409, DOI 10.1007/s00122-006-0365-4
   Aulchenko YS, 2007, GENETICS, V177, P577, DOI 10.1534/genetics.107.075614
   Bekele WA, 2014, PLANT CELL ENVIRON, V37, P707, DOI 10.1111/pce.12189
   Boyles RE, 2019, PLANT J, V97, P19, DOI 10.1111/tpj.14113
   Brenton ZW, 2016, GENETICS, V204, P21, DOI 10.1534/genetics.115.183947
   Browning BL, 2018, AM J HUM GENET, V103, P338, DOI 10.1016/j.ajhg.2018.07.015
   Buchfink B, 2015, NAT METHODS, V12, P59, DOI 10.1038/nmeth.3176
   Burow G, 2011, MOL BREEDING, V28, P391, DOI 10.1007/s11032-010-9491-4
   Chakrabarty S, 2021, FRONT PLANT SCI, P2574
   Cooper M, 2014, CROP PASTURE SCI, V65, P311, DOI 10.1071/CP14007
   Craufurd PQ, 1999, THEOR APPL GENET, V99, P900, DOI 10.1007/s001220051311
   DEWET JMJ, 1971, ECON BOT, V25, P128, DOI 10.1007/BF02860074
   Dong SS, 2021, BRIEF BIOINFORM, V22, DOI 10.1093/bib/bbaa227
   Fiedler K, 2014, THEOR APPL GENET, V127, P1935, DOI 10.1007/s00122-014-2350-7
   Gabriel SB, 2002, SCIENCE, V296, P2225, DOI 10.1126/science.1069424
   Gabur I, 2019, THEOR APPL GENET, V132, P733, DOI 10.1007/s00122-018-3233-0
   Granato ISC, 2018, MOL BREEDING, V38, DOI 10.1007/s11032-018-0844-8
   Hariprasanna K., 2015, Sorghum Molecular Breeding, P3, DOI [DOI 10.1007/978-81-322-2422-8_1, 10.1007/978-81-322-2422-8, 10.1007/978-81-322-2422-8_1]
   Jombart T, 2010, BMC GENET, V11, DOI 10.1186/1471-2156-11-94
   Kim M, 2021, BIORXIV, DOI 10.31.466691
   Mace E, 2019, THEOR APPL GENET, V132, P751, DOI 10.1007/s00122-018-3212-5
   Mace ES, 2008, BMC GENOMICS, V9, DOI 10.1186/1471-2164-9-26
   Mann J., 1983, Texas Agricultural Experiment Station, Bulletin, V1, P128074
   Mbabwine Y, 2004, PLANT GENET RESOUR I, V472, P71
   McCormick RF, 2018, PLANT J, V93, P338, DOI 10.1111/tpj.13781
   Mekbib Firew, 2008, Journal of New Seeds, V9, P43, DOI 10.1080/15228860701879299
   Morris GP, 2013, P NATL ACAD SCI USA, V110, P453, DOI 10.1073/pnas.1215985110
   National Research Council (U.S.), 1996, Lost crops of Africa
   Paradis E, 2004, BIOINFORMATICS, V20, P289, DOI [10.1093/bioinformatics/btg412, 10.1093/bioinformatics/bty633]
   Paterson AH, 2009, NATURE, V457, P551, DOI 10.1038/nature07723
   Pressoir G, 2004, HEREDITY, V92, P95, DOI 10.1038/sj.hdy.6800388
   Purcell S, 2007, AM J HUM GENET, V81, P559, DOI 10.1086/519795
   Reddy V. G., 2002, International Sorghum and Millets Newsletter, V43, P15
   Ritter KB, 2007, EUPHYTICA, V157, P161, DOI 10.1007/s10681-007-9408-4
   Rutayisire A, 2021, INT J AGRON, V2021, P10, DOI DOI 10.1155/2021/8875205
   Schaffasz A, 2019, AGRONOMY-BASEL, V9, DOI 10.3390/agronomy9090535
   Schaffasz A, 2019, AGRONOMY-BASEL, V9, DOI 10.3390/agronomy9090508
   Smith O, 2019, NAT PLANTS, V5, P369, DOI 10.1038/s41477-019-0397-9
   Snowden J.D., 1936, The cultivated races of sorghum
   Sorghum DH, 1988, LONGMAN SCI TECHNICA
   STEMLER ABL, 1975, B TORREY BOT CLUB, V102, P325, DOI 10.2307/2484758
   Stich B, 2008, GENETICS, V178, P1745, DOI 10.1534/genetics.107.079707
   Tao YF, 2020, PLANT BIOTECHNOL J, V18, P1093, DOI 10.1111/pbi.13284
   Thurber CS, 2013, GENOME BIOL, V14, DOI 10.1186/gb-2013-14-6-r68
   Wenzl P, 2006, BMC GENOMICS, V7, DOI 10.1186/1471-2164-7-206
   Xie LX, 2014, J INTEGR PLANT BIOL, V56, P749, DOI 10.1111/jipb.12190
   Yu Guangchuang, 2020, Curr Protoc Bioinformatics, V69, pe96, DOI 10.1002/cpbi.96
   Zeng YF, 2020, FRONT PLANT SCI, V10, DOI 10.3389/fpls.2019.01663
   Zhou XN, 2021, INT J MOL SCI, V22, DOI 10.3390/ijms22020758
NR 50
TC 4
Z9 4
U1 1
U2 14
PU BMC
PI LONDON
PA CAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND
SN 1471-2229
J9 BMC PLANT BIOL
JI BMC Plant Biol.
PD JUL 29
PY 2022
VL 22
IS 1
AR 378
DI 10.1186/s12870-022-03770-y
PG 11
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA 3I9HC
UT WOS:000833017700005
PM 35906543
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Myint, SW
   Aggarwal, R
   Zheng, BJ
   Wentz, EA
   Holway, J
   Fan, C
   Selover, NJ
   Wang, CY
   Fischer, HA
AF Myint, Soe W.
   Aggarwal, Rimjhim
   Zheng, Baojuan
   Wentz, Elizabeth A.
   Holway, Jim
   Fan, Chao
   Selover, Nancy J.
   Wang, Chuyuan
   Fischer, Heather A.
TI Adaptive Crop Management under Climate Uncertainty: Changing the Game
   for Sustainable Water Use
SO ATMOSPHERE
LA English
DT Article
DE crop type; evapotranspiration; Landsat; water consumption; drought;
   multiple cropping practices
ID SUPPORT VECTOR MACHINE; ENERGY-BALANCE; MAPPING EVAPOTRANSPIRATION; USE
   EFFICIENCY; SOIL-MOISTURE; HEAT FLUXES; CALIBRATION; RESOURCES; STORAGE;
   YIELD
AB Water supplies are projected to become increasingly scarce, driving farmers, energy producers, and urban dwellers towards an urgent and emerging need to improve the effectiveness and the efficiency of water use. Given that agricultural water use is the largest water consumer throughout the U.S. Southwest, this study sought to answer two specific research questions: (1) How does water consumption vary by crop type on a metropolitan spatial scale? (2) What is the impact of drought on agricultural water consumption? To answer the above research questions, 92 Landsat images were acquired to generate fine-resolution daily evapotranspiration (ET) maps at 30 m spatial resolution for both dry and wet years (a total of 1095 ET maps), and major crop types were identified for the Phoenix Active Management Area. The study area has a subtropical desert climate and relies almost completely on irrigation for farming. Results suggest that there are some factors that farmers and water managers can control. During dry years, crops of all types use more water. Practices that can offset this higher water use include double or multiple cropping practice, drought tolerant crop selection, and optimizing the total farmed area. Double and multiple cropping practices result in water savings because soil moisture is retained from one planting to another. Further water savings occur when drought tolerant crop types are selected, especially in dry years. Finally, disproportionately large area coverage of high water consuming crops can be balanced and/or reduced or replaced with more water efficient crops. This study provides strong evidence that water savings can be achieved through policies that create incentives for adopting smart cropping strategies, thus providing important guidelines for sustainable agriculture management and climate adaptation to improve future food security.
C1 [Myint, Soe W.; Wentz, Elizabeth A.] Arizona State Univ, Sch Geog Sci & Urban Planning, Tempe, AZ 85287 USA.
   [Aggarwal, Rimjhim] Arizona State Univ, Sch Sustainabil, Tempe, AZ 85287 USA.
   [Zheng, Baojuan] South Dakota State Univ, Geospatial Sci Ctr Excellence, Brookings, SD 57006 USA.
   [Holway, Jim] Lincoln Inst Land Policy, Babbitt Ctr Land & Water Policy, Phoenix, AZ 85028 USA.
   [Fan, Chao] Univ Idaho, Dept Geog, Moscow, ID 83844 USA.
   [Selover, Nancy J.] Arizona State Univ, Arizona State Climate Off, Tempe, AZ 85287 USA.
   [Wang, Chuyuan] Towson Univ, Dept Geog & Environm Planning, Towson, MD 21252 USA.
   [Fischer, Heather A.] Oregon State Univ, Ctr Res Lifelong STEM Learning, Corvallis, OR 97331 USA.
C3 Arizona State University; Arizona State University-Tempe; Arizona State
   University; Arizona State University-Tempe; South Dakota State
   University; University of Idaho; Arizona State University; Arizona State
   University-Tempe; University System of Maryland; Towson University;
   Oregon State University
RP Myint, SW (corresponding author), Arizona State Univ, Sch Geog Sci & Urban Planning, Tempe, AZ 85287 USA.
EM Soe.Myint@asu.edu; rimjhim.aggarwal@asu.edu; baojuan5@vt.edu;
   wentz@asu.edu; jholway@lincolninst.edu; cfan@uidaho.edu;
   selover@asu.edu; cwang@towson.edu; heather.fischer@oregonstate.edu
RI Aggarwal, Rimjhim/D-4812-2012; Myint, Soe/E-8500-2015; Wang,
   Chuyuan/I-2662-2018
OI Aggarwal, Rimjhim/0000-0002-3579-5363; Fischer,
   Heather/0000-0003-2530-3529; Myint, Soe/0000-0001-7809-1211; Wang,
   Chuyuan/0000-0002-6381-6424; Fan, Chao/0000-0002-6037-8940
FU National Oceanic and Atmospheric Administration [NA12OAR4310100];
   National Science Foundation [DEB-1026865, SES-0951366, SES-0345945,
   CNS-1639227]
FX The study was funded by National Oceanic and Atmospheric Administration
   (grant number: NA12OAR4310100). We also would like to acknowledge the
   support by National Science Foundation under grant number DEB-1026865
   for Central Arizona-Phoenix Long-Term Ecological Research (CAPLTER),
   grant numbers SES-0951366 & SES-0345945 for Decision Center for a Desert
   City (DCDC), grant number CNS-1639227 for INFEWS/T2: Flexible Model
   Compositions and Visual Representations for Planning and Policy
   Decisions at the Sub-regional level of the food-energy-water nexus.
CR Allen, 2008, P PEC 17 FUT LOAD IM
   Allen RG., 2005, The ASCE standardized reference evapotranspiration equation, V1
   Allen R, 2011, HYDROL PROCESS, V25, P4011, DOI 10.1002/hyp.8408
   Allen RG, 2007, J IRRIG DRAIN ENG, V133, P380, DOI [10.1061/(ASCE)0733-9437(2007)133:4(380), 10.1061/(ASCE)0733-9437(2007)133:4(395)]
   Allen RG, 2013, J AM WATER RESOUR AS, V49, P563, DOI 10.1111/jawr.12056
   Amarasinghe U.A., 2014, Global water demand projections: Past, present and future, DOI [DOI 10.5337/2014.212, https://doi.org/10.5337/2014.212]
   [Anonymous], 2010, Arizona water atlas
   [Anonymous], 2002, THESIS UTAH STATE U
   Barnett TP, 2008, SCIENCE, V319, P1080, DOI 10.1126/science.1152538
   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
   Blake, 2018, MINIMUM TILLAGE SPEL
   Bonfils C, 2008, J CLIMATE, V21, P6404, DOI 10.1175/2008JCLI2397.1
   Christensen JH, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P847
   Congalton RG, 2008, ASSESSING ACCURACY R
   Dise NB, 2009, SCIENCE, V326, P810, DOI 10.1126/science.1174268
   Easterling D. R., 2017, CLIMATE SCI SPECIAL, P207, DOI DOI 10.7930/J0H993CC
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fleck B.E., 2013, THESIS U ARIZONA TUC
   Flörke M, 2018, NAT SUSTAIN, V1, P51, DOI 10.1038/s41893-017-0006-8
   Foody GM, 2004, REMOTE SENS ENVIRON, V93, P107, DOI 10.1016/j.rse.2004.06.017
   Fouli Y, 2012, AGR WATER MANAGE, V115, P104, DOI 10.1016/j.agwat.2012.08.014
   Frisvold, 2015, DEV SUSTAINABILITY M, P20
   Garfin G., 2014, Climate Change Impacts in the United States: The Third National Climate Assessment, DOI DOI 10.7930/J08G8HMN
   Goldstein AH, 2000, AGR FOREST METEOROL, V101, P113, DOI 10.1016/S0168-1923(99)00168-9
   Gregory MM, 2005, RENEW AGR FOOD SYST, V20, P81, DOI [10.1079/RAF200493, 10.1079/RAF2004093]
   Hafeez Mohsin., 2007, INT J RIVER BASIN MA, V5, P49, DOI DOI 10.1080/15715124.2007.9635305
   Hamlet AF, 2007, J CLIMATE, V20, P1468, DOI 10.1175/JCLI4051.1
   Hendrickx JMH, 2016, J AM WATER RESOUR AS, V52, P89, DOI 10.1111/1752-1688.12371
   Hendrickx JMH, 2005, PROC SPIE, V5811, P138, DOI 10.1117/12.603361
   Holmgren M, 2006, FRONT ECOL ENVIRON, V4, P87, DOI 10.1890/1540-9295(2006)004[0087:ECESAA]2.0.CO;2
   Hong SH, 2005, PROC SPIE, V5811, P147, DOI 10.1117/12.603385
   Hong SH, 2011, INT J REMOTE SENS, V32, P6457, DOI 10.1080/01431161.2010.512929
   Hong SH, 2009, J HYDROL, V370, P122, DOI 10.1016/j.jhydrol.2009.03.002
   Hunt PG, 1997, J PROD AGRIC, V10, P462, DOI 10.2134/jpa1997.0462
   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
   Joyce BA, 2002, T ASAE, V45, P315, DOI 10.13031/2013.8526
   Kaplan S, 2012, PHOTOGRAMM ENG REM S, V78, P849, DOI 10.14358/PERS.78.8.849
   Karl T. R., 2009, Global climate change impacts in the United States
   Kenny J.F., 2009, US Geological Survey Circular, V1344
   Lapola DM, 2009, GLOBAL BIOGEOCHEM CY, V23, DOI 10.1029/2008GB003357
   Lobell DB, 2013, NAT CLIM CHANGE, V3, P497, DOI [10.1038/nclimate1832, 10.1038/NCLIMATE1832]
   Lundquist JD, 2011, WATER RESOUR RES, V47, DOI 10.1029/2010WR010050
   Malmqvist Bjorn, 2008, P19, DOI 10.1017/CBO9780511751790.004
   Meko DM, 2007, GEOPHYS RES LETT, V34, DOI 10.1029/2007GL029988
   Olesen JE, 2011, EUR J AGRON, V34, P96, DOI 10.1016/j.eja.2010.11.003
   Plaza Antonio, 2009, Remote Sensing of Environment, V113, pS110, DOI 10.1016/j.rse.2007.07.028
   Porter JR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P485
   Rauscher SA, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL034424
   Shao Y, 2012, ISPRS J PHOTOGRAMM, V70, P78, DOI 10.1016/j.isprsjprs.2012.04.001
   Smith RG, 2017, WATER RESOUR RES, V53, P2133, DOI 10.1002/2016WR019861
   Stahlschmidt ZR, 2011, J ARID ENVIRON, V75, P681, DOI 10.1016/j.jaridenv.2011.03.006
   U.S. Department of Agriculture (USDA), 2008, 2007 CENS AGR, V3
   U.S. Department of Agriculture (USDA), 2014, REG CONS PARTN PROGR
   U.S. Department of Agriculture (USDA)-National Agricultural Statistics Service (NASS), 2004, 2004 AR AGR STAT B
   U.S. Department of Agriculture (USDA)-Natural Resources Conservation Service (NRCS), 2006, USDA HDB
   Unger PW, 1998, J SOIL WATER CONSERV, V53, P200
   Vörösmarty CJ, 2000, SCIENCE, V289, P284, DOI 10.1126/science.289.5477.284
   Wang CY, 2021, SCI TOTAL ENVIRON, V763, DOI 10.1016/j.scitotenv.2020.144605
   Wang HX, 2001, AGR WATER MANAGE, V48, P151, DOI 10.1016/S0378-3774(00)00118-9
   Woodhouse C. A., 2006, Water Resources Research, V42, pW05415, DOI 10.1029/2005WR004455
   Zhang YQ, 2004, AGR WATER MANAGE, V64, P107, DOI 10.1016/S0378-3774(03)00201-4
   Zheng BJ, 2015, INT J APPL EARTH OBS, V34, P103, DOI 10.1016/j.jag.2014.07.002
NR 64
TC 6
Z9 6
U1 1
U2 14
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4433
J9 ATMOSPHERE-BASEL
JI Atmosphere
PD AUG
PY 2021
VL 12
IS 8
AR 1080
DI 10.3390/atmos12081080
PG 26
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA UF9JD
UT WOS:000688881500001
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Bessah, E
   Boakye, EA
   Agodzo, SK
   Nyadzi, E
   Larbi, I
   Awotwi, A
AF Bessah, Enoch
   Boakye, Emmanuel A.
   Agodzo, Sampson K.
   Nyadzi, Emmanuel
   Larbi, Isaac
   Awotwi, Alfred
TI Increased seasonal rainfall in the twenty-first century over Ghana and
   its potential implications for agriculture productivity
SO ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
LA English
DT Article
DE Climate modelling; Ghana; Rainfall; RCP 4; 5; RCP 8; 5; SDSM-DC
ID STATISTICAL DOWNSCALING MODEL; CLIMATE-CHANGE IMPACTS; EXTREME
   PRECIPITATION; CHANGE PROJECTIONS; CORDEX-AFRICA; TEMPERATURE; SDSM;
   BASIN; VARIABILITY; SCENARIOS
AB The slightest change in rainfall could have a significant impact on rain-fed agriculture in countries like Ghana. This study evaluated for the first time the performance of the statistical downscaling model (SDSM-DC) at 2m spatial resolution in simulating rainfall in Ghana for the base period 1981-2010. It further analysed the projected changes in seasonal rainfall pattern across different agro-ecological zones for the twenty-first century under RCP 4.5 and 8.5 emission scenarios over Ghana. Ensemble mean of simulated rainfall data (2011-2099) generated by 43 GCMs in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were used as base factors for local future climate scenarios generation. Performance analysis of SDSM-DC shows a Nash-Sutcliffe efficiency, percent bias and RMSE observations standard deviation ratio of 0.88, -19 and 0.34, respectively. Generally, seasonal rainfall amount is expected to increase between 10 and 40% in all the agro-ecological zones in Ghana by the end of the twenty-first century. Off-season rainfall in December-February shows more than 100% increase in the Guinea Savannah zone. Rainfall projected under RCP 4.5 was on average 2% higher than RCP 8.5 in all the seasons throughout the century. Based on these results, it is appropriate to suggest a high incidence of flooding across Ghana in the twenty-first century. This could have dire consequences on agriculture which contribute to a large proportion of Ghana's GDP. Therefore, for sustainable food production and security in the twenty-first century, Ghana needs climate adaptation policies and programmes that encourage the design and implementation of early warning systems of meteorological hazards and the introduction of new crop varieties that are flood tolerant.
C1 [Bessah, Enoch] Univ Ibadan, Pan African Univ, Inst Life & Earth Sci Including Hlth & Agr, Ibadan, Oyo State, Nigeria.
   [Bessah, Enoch; Agodzo, Sampson K.] Kwame Nkrumah Univ Sci & Technol, Dept Agr & Biosyst Engn, PMB, Kumasi, Ghana.
   [Boakye, Emmanuel A.] Kwame Nkrumah Univ Sci & Technol, Fac Renewable Nat Resources, Dept Silviculture & Forest Management, PMB, Kumasi, Ghana.
   [Nyadzi, Emmanuel] Wageningen Univ & Res, Water Syst & Global Change Grp, POB 47, NL-6700 AA Wageningen, Netherlands.
   [Larbi, Isaac] Univ Environm & Sustainable Dev, Sch Sustainable Dev, Dept Water Resources Dev, Somanya, Ghana.
   [Awotwi, Alfred] Univ Dev Studies, Dept Geoinformat & Spatial Dev, Navrongo, Ghana.
C3 University of Ibadan; Kwame Nkrumah University Science & Technology;
   Kwame Nkrumah University Science & Technology; Wageningen University &
   Research; University for Development Studies
RP Bessah, E (corresponding author), Univ Ibadan, Pan African Univ, Inst Life & Earth Sci Including Hlth & Agr, Ibadan, Oyo State, Nigeria.; Bessah, E (corresponding author), Kwame Nkrumah Univ Sci & Technol, Dept Agr & Biosyst Engn, PMB, Kumasi, Ghana.
EM enoch.bessah@gmail.com; emmanuel.boakye@knust.edu.gh; skagodzo7@usa.net;
   Emmanuel.nyadzi@wur.nl; larbi.i@edu.wascal.org; awor73@yahoo.com
RI Agodzo, Samspon/JNR-9873-2023; Larbi, Isaac/GNH-5792-2022; Bessah,
   Enoch/E-7243-2018
OI Attoh, Emmanuel Mawuli Nii Armah Nyadzi/0000-0001-6527-852X; Awotwi,
   Alfred/0000-0003-0296-7138; Bessah, Enoch/0000-0002-2187-2022; Boakye,
   Emmanuel Amoah/0000-0002-0993-4964
CR Abbasnia M, 2016, MODEL EARTH SYST ENV, V2, DOI 10.1007/s40808-016-0112-z
   Abdo KS, 2009, HYDROL PROCESS, V23, P3661, DOI 10.1002/hyp.7363
   Abkar A, 2014, ARID BIOME SCI RES J, V4, P11
   Abubakari A. H., 2012, Journal of Soil Science and Environmental Management, V3, P84
   ACHEAMPONG PK, 1982, GEOGR ANN A, V64, P199, DOI 10.2307/520646
   Adem AnwarA., 2014, NILE RIVER BASIN, P363, DOI [10.1007/978-3-319-02720-3_19, DOI 10.1007/978-3-319-02720-3_19]
   Adu-Prah S, 2019, AFR GEOGR REV, V38, P172, DOI 10.1080/19376812.2017.1404923
   Afrooz A H., 2015, Proceedings of Watershed Management Symposium, P36, DOI [10.1061/9780784479322.004, DOI 10.1061/9780784479322.004]
   Aguilar MY, 2009, CLIM RES, V40, P187, DOI 10.3354/cr00805
   Ahmed KF, 2015, CLIMATIC CHANGE, V133, P321, DOI 10.1007/s10584-015-1462-7
   Amekudzi LK, 2015, CLIMATE, V3, P416, DOI 10.3390/cli3020416
   Amirabadizadeh M., 2016, INT J WATER RESOUR E, V8, P120, DOI [DOI 10.5897/IJWREE2016.0585, 10.5897/IJWREE2016.0585]
   [Anonymous], 2017, WORLD DEV IND
   AQUASTAT Survey, 2005, IRR AFR FIG GHAN
   Aryee JNA, 2018, INT J CLIMATOL, V38, P1201, DOI 10.1002/joc.5238
   Asante FA, 2015, CLIMATE, V3, P78, DOI 10.3390/cli3010078
   Ashiq MW, 2010, THEOR APPL CLIMATOL, V99, P239, DOI 10.1007/s00704-009-0140-y
   Asumadu-Sarkodie S., 2015, Advances in Applied Science Research, V6, P53
   Azad S, 2015, COMP STAT DOWNSC TEC
   Babel MS, 2015, THEOR APPL CLIMATOL, V119, P239, DOI 10.1007/s00704-014-1097-z
   Bader O, 2008, BMC MICROBIOL, V8, DOI 10.1186/1471-2180-8-116
   Bedia J, 2013, CLIMATIC CHANGE, V120, P229, DOI 10.1007/s10584-013-0787-3
   Bekele HM, 2009, EVALUATION CLIMATE C
   Bessah E, 2020, J WATER CLIM CHANGE, V11, P1263, DOI 10.2166/wcc.2019.258
   Bessah E, 2018, MODEL EARTH SYST ENV, V4, P919, DOI 10.1007/s40808-018-0479-0
   Casanueva A, 2014, CLIMATIC CHANGE, V127, P547, DOI 10.1007/s10584-014-1270-5
   Chen FW, 2012, PADDY WATER ENVIRON, V10, P209, DOI 10.1007/s10333-012-0319-1
   Chen ST, 2010, J HYDROL, V385, P13, DOI 10.1016/j.jhydrol.2010.01.021
   CHEROS F, 2016, INT J RIVER BASIN MA, V14, P151
   Chu JT, 2010, THEOR APPL CLIMATOL, V99, P149, DOI 10.1007/s00704-009-0129-6
   Church J.A., 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
   CIAT, 2011, PRED IMP CLIM CHANG
   Codjoe SNA, 2011, REG ENVIRON CHANGE, V11, P753, DOI 10.1007/s10113-011-0211-3
   Crawford T, 2007, CLIM RES, V34, P145, DOI 10.3354/cr034145
   Dickson K.B., 1995, A New Geography of Ghana
   Dosio A, 2016, CLIM DYNAM, V46, P1599, DOI 10.1007/s00382-015-2664-4
   Dressler M., 2007, THESIS
   Ekwezuo CS, 2018, PAKISTAN J METEOROLO, V37, P233, DOI [10.4314/njt.v37i1.31, DOI 10.4314/NJT.V37I1.31]
   ELLIS J, 1994, BIOSCIENCE, V44, P340, DOI 10.2307/1312384
   Endris HS, 2013, J CLIMATE, V26, P8453, DOI 10.1175/JCLI-D-12-00708.1
   Farajzadeh M, 2015, THEOR APPL CLIMATOL, V120, P377, DOI 10.1007/s00704-014-1157-4
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fiori A., 2012, Int J Water Sci, V1, DOI 10.5772/52890
   Giorgi F., 2009, Bulletin - World Meteorological Organization, V58, P175
   GSS, 2011, ANN REPORT
   Gulacha MM, 2017, PHYS CHEM EARTH, V100, P62, DOI 10.1016/j.pce.2016.10.003
   Hashmi MZ, 2011, STOCH ENV RES RISK A, V25, P475, DOI 10.1007/s00477-010-0416-x
   Haylock MR, 2006, INT J CLIMATOL, V26, P1397, DOI 10.1002/joc.1318
   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]
   Hewitson B., 2012, CLIVAR Exch. No, V17, P6
   Hoegh-Guldberg O., 2018, Global warming of 1.5C
   Honaker J., 2018, AMELIA II: A Program for Missing Data
   Honaker J, 2011, J STAT SOFTW, V45, P1
   Huang J, 2011, STOCH ENV RES RISK A, V25, P781, DOI 10.1007/s00477-010-0441-9
   Ibn Musah AA, 2018, CLIMATE, V6, DOI 10.3390/cli6040086
   Kisembe J, 2019, THEOR APPL CLIMATOL, V137, P1117, DOI 10.1007/s00704-018-2643-x
   Klutse N.A. B., 2013, Research Journal of Agriculture and Environmental Management, V2, P394
   Knox J. W., 2013, WHAT ARE PROJECTED I
   Kolavalli S, 2012, 01161 IFPRI
   Koukidis EN, 2009, ATMOS OCEAN, V47, P1, DOI 10.3137/AO924.2009
   Läderach P, 2013, CLIMATIC CHANGE, V119, P841, DOI 10.1007/s10584-013-0774-8
   Liepert BG, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/1/014006
   Liu ZF, 2011, INT J CLIMATOL, V31, P2006, DOI 10.1002/joc.2211
   Lu GY, 2008, COMPUT GEOSCI-UK, V34, P1044, DOI 10.1016/j.cageo.2007.07.010
   Mahmood R, 2013, THEOR APPL CLIMATOL, V113, P27, DOI 10.1007/s00704-012-0765-0
   Manzanas R, 2014, CLIMATIC CHANGE, V124, P805, DOI 10.1007/s10584-014-1100-9
   McSweeney C, 2010, B AM METEOROL SOC, V91, P157, DOI 10.1175/2009BAMS2826.1
   Meinshausen M, 2011, CLIMATIC CHANGE, V109, P213, DOI 10.1007/s10584-011-0156-z
   Mensah C., 2016, Atmospheric and Climate Sciences, V6, P300, DOI 10.4236/acs.2016.62025
   MFA, 2018, CLIM CHANG PROF GHAN
   Moriasi DN, 2007, T ASABE, V50, P885, DOI 10.13031/2013.23153
   Mullan D, 2012, INT J CLIMATOL, V32, P2007, DOI 10.1002/joc.2414
   Niang I, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1199
   Okafor G, 2019, THEOR APPL CLIMATOL, V137, P2803, DOI 10.1007/s00704-018-2746-4
   Osman Yassin Z., 2016, Water Science, V30, P61, DOI 10.1016/j.wsj.2016.10.002
   Owusu K., 2013, International Journal of Geosciences, V4, P785, DOI 10.4236/ijg.2013.44072
   Owusu K, 2018, WEATHER, V73, P46, DOI 10.1002/wea.2999
   Owusu K, 2009, WEATHER, V64, P115, DOI 10.1002/wea.255
   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]
   Roy-Macauley H., 2017, IFPRI Research Monograph, DOI [10.2499/9780896298712, DOI 10.2499/9780896298712, 10.2499/9780896292048]
   Salon S, 2008, CLIM RES, V38, P31, DOI 10.3354/cr00757
   Shongwe ME, 2009, J CLIMATE, V22, P3819, DOI 10.1175/2009JCLI2317.1
   Souvignet M, 2010, HYDROLOG SCI J, V55, P41, DOI 10.1080/02626660903526045
   Stanturf J.A., 2011, Ghana Climate Change Vulnerability and Adaptation Assessment
   Stennett-Brown RK, 2017, INT J CLIMATOL, V37, P4828, DOI 10.1002/joc.5126
   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
   Sultan B, 2003, J CLIMATE, V16, P3407, DOI 10.1175/1520-0442(2003)016<3407:TWAMDP>2.0.CO;2
   Tachie-Obeng E, 2014, J DISASTER RES, V9, P422, DOI 10.20965/jdr.2014.p0422
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Timilsena YP, 2016, GUMS AND STABILISERS FOR THE FOOD INDUSTRY 18: HYDROCOLLOID FUNCTIONALITY FOR AFFORDABLE AND SUSTAINABLE GLOBAL FOOD SOLUTIONS, P65
   Tschakert P, 2010, CLIMATIC CHANGE, V103, P471, DOI 10.1007/s10584-009-9776-y
   UNEP, 2017, COUNTR LEV IMP CLIM
   UPEI, 2018, ISL DAT CLIM REC DAY
   Wilby RL, 2014, CLIM RES, V61, P259, DOI 10.3354/cr01254
   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., 2008, P WAT TRIB EXP ZAR S
   Wilby RL, 1997, PROG PHYS GEOG, V21, P530, DOI 10.1177/030913339702100403
   Wilby RL, 2002, ENVIRON MODELL SOFTW, V17, P147
   Wilby RL, 2006, WATER RESOUR RES, V42, DOI 10.1029/2005WR004065
   World Bank, 2010, EC AD CLIM CHANG
   Yates DN, 2015, CLIM RISK MANAG, V10, P35, DOI 10.1016/j.crm.2015.06.001
   Yengoh G. T., 2010, Journal of Agricultural Science (Toronto), V2, P3
NR 103
TC 13
Z9 15
U1 0
U2 6
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 AUG
PY 2021
VL 23
IS 8
BP 12342
EP 12365
DI 10.1007/s10668-020-01171-5
EA JAN 2021
PG 24
WC Green & Sustainable Science & Technology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA SY2NV
UT WOS:000604829300001
DA 2025-01-10
ER

PT J
AU Tourneur, JC
   Meunier, J
AF Tourneur, Jean-Claude
   Meunier, Joel
TI Variations in seasonal (not mean) temperatures drive rapid adaptations
   to novel environments at a continent scale
SO ECOLOGY
LA English
DT Article
DE adaptation; climate change; Dermaptera; invasion; reproductive strategy;
   temperature
ID FORFICULA-AURICULARIA DERMAPTERA; EUROPEAN EARWIG; CLIMATE-CHANGE;
   LIFE-HISTORY; SIBLING COOPERATION; PARENTAL BEHAVIOR; PLASTIC RESPONSES;
   INVASION BIOLOGY; EARLY EVOLUTION; HEAT WAVES
AB The recent development of human societies has led to major, rapid, and often inexorable changes in the environment of most animal species. Over the last decades, a growing number of studies formulated predictions on the modalities of animal adaptation to novel or changing environments, questioning how and at what speed animals should adapt to such changes, discussing the levels of risks imposed by changes in the mean and/or variance of temperatures on animal performance, and exploring the underlying roles of phenotypic plasticity and genetic inheritance. These fundamental predictions, however, remain poorly tested using field data. Here, we tested these predictions using a unique continental-scale data set in the European earwig Forficula auricularia L., a univoltine insect introduced in North America one century ago. We conducted a common garden experiment, in which we measured 13 life-history traits in 4,158 field-sampled earwigs originating from 19 populations across North America. Our results first demonstrate that 10 of the 13 measured life-history traits are associated with two sets of variations in seasonal temperatures, that is, winter-summer and autumn-spring. We found, however, no association with the overall mean monthly temperatures of the invaded locations. Furthermore, our use of a common garden setup reveals that the observed patterns of variation in earwigs' life-history traits are not mere plastic responses to their current environment, but are either due to their genetic background and/or to the environmental conditions they experienced during early life development. Overall, these findings provide continent-scale support to the claims that adaptation to thermal changes can occur quickly (in less than 100 generations), even in insects with long life cycles, and emphasize the importance of variation in seasonal temperature over mean population temperatures in climate adaptation.
C1 [Tourneur, Jean-Claude] Univ Quebec Montreal, Dept Sci Biol, 141 Ave President Kennedy, Montreal, PQ H2X 1Y4, Canada.
   [Meunier, Joel] Univ Tours, IRBI, UMR 7261, CNRS, Tours, France.
C3 University of Quebec; University of Quebec Montreal; Centre National de
   la Recherche Scientifique (CNRS); CNRS - Institute of Ecology &
   Environment (INEE); Universite de Tours
RP Meunier, J (corresponding author), Univ Tours, IRBI, UMR 7261, CNRS, Tours, France.
EM joel.meunier@univ-tours.fr
RI Meunier, Joel/A-1067-2017
OI Meunier, Joel/0000-0001-6893-2064
CR ADAMCZEWSKI JZ, 1993, CAN J ZOOL, V71, P1221, DOI 10.1139/z93-167
   Albouy V., 1990, DERMAPTERES PERCE OR
   Altizer S, 2006, ECOL LETT, V9, P467, DOI 10.1111/j.1461-0248.2005.00879.x
   Bellard C, 2016, ECOSPHERE, V7, DOI 10.1002/ecs2.1241
   BENJAMINI Y, 1995, J R STAT SOC B, V57, P289, DOI 10.1111/j.2517-6161.1995.tb02031.x
   Blanckenhorn WU, 2018, ECOGRAPHY, V41, P2080, DOI 10.1111/ecog.03752
   Bodensteiner BL, 2019, ECOL EVOL, V9, P2791, DOI 10.1002/ece3.4956
   Boos S, 2014, BEHAV ECOL, V25, P754, DOI 10.1093/beheco/aru046
   Chevin LM, 2010, PLOS BIOL, V8, DOI 10.1371/journal.pbio.1000357
   Corl A, 2018, CURR BIOL, V28, P2970, DOI 10.1016/j.cub.2018.06.075
   Courchamp F, 2017, TRENDS ECOL EVOL, V32, P13, DOI 10.1016/j.tree.2016.11.001
   Crumb S. E, 1941, USDA TECHNICAL B, V766
   Danks HV, 2000, J INSECT PHYSIOL, V46, P837, DOI 10.1016/S0022-1910(99)00204-8
   Diehl JMC, 2018, BEHAV ECOL, V29, P128, DOI 10.1093/beheco/arx140
   Elgar M.A., 1992, Science, V258, P1969
   English S, 2016, AM NAT, V187, P620, DOI 10.1086/685644
   FALCONER DS, 1990, GENET RES, V56, P57, DOI 10.1017/S0016672300028883
   Falk J, 2014, AM NAT, V183, P547, DOI 10.1086/675364
   Fox RJ, 2019, PHILOS T R SOC B, V374, DOI 10.1098/rstb.2018.0174
   Franks SJ, 2014, EVOL APPL, V7, P123, DOI 10.1111/eva.12112
   Fretwell JR., 1972, POPULATIONS SEASONAL
   Gingras J, 2001, CAN ENTOMOL, V133, P269, DOI 10.4039/Ent133269-2
   Guillet S, 2000, CAN ENTOMOL, V132, P49, DOI 10.4039/Ent13249-1
   Hill MP, 2019, PEST MANAG SCI, V75, P134, DOI 10.1002/ps.5192
   Hill MP, 2016, BIOL INVASIONS, V18, P883, DOI 10.1007/s10530-016-1088-3
   Holt R. D., 1990, TRENDS ECOL EVOL, V5, P590
   Huey RB, 2000, SCIENCE, V287, P308, DOI 10.1126/science.287.5451.308
   Hulme PE, 2017, BIOL REV, V92, P1297, DOI 10.1111/brv.12282
   Hulme PE, 2009, J APPL ECOL, V46, P10, DOI 10.1111/j.1365-2664.2008.01600.x
   Janion-Scheepers C, 2018, P NATL ACAD SCI USA, V115, P145, DOI 10.1073/pnas.1715598115
   Jeschke JM, 2005, P NATL ACAD SCI USA, V102, P7198, DOI 10.1073/pnas.0501271102
   Kingsolver JG, 2013, FUNCT ECOL, V27, P1415, DOI 10.1111/1365-2435.12145
   Koch LK, 2014, BMC EVOL BIOL, V14, DOI 10.1186/1471-2148-14-125
   Kölliker M, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms7850
   Körner M, 2018, J THERM BIOL, V74, P116, DOI 10.1016/j.jtherbio.2018.03.021
   Körner M, 2016, BEHAV ECOL, V27, P1775, DOI 10.1093/beheco/arw113
   Kohlmeier P, 2016, J EVOLUTION BIOL, V29, P1867, DOI 10.1111/jeb.12916
   Kölliker M, 2007, BEHAV ECOL SOCIOBIOL, V61, P1489, DOI 10.1007/s00265-007-0381-7
   Kramer J, 2015, J EVOLUTION BIOL, V28, P1299, DOI 10.1111/jeb.12655
   Kramer J, 2016, BEHAV ECOL, V27, P494, DOI 10.1093/beheco/arv181
   LAMB RJ, 1975, CAN ENTOMOL, V107, P819, DOI 10.4039/Ent107819-8
   LAMB RJ, 1976, CAN ENTOMOL, V108, P609, DOI 10.4039/Ent108609-6
   Levis NA, 2016, TRENDS ECOL EVOL, V31, P563, DOI 10.1016/j.tree.2016.03.012
   Littler F. M., 1918, Journal of Economic Entomology, V11, P472, DOI 10.1093/jee/11.6.472
   Meehl GA, 2004, SCIENCE, V305, P994, DOI 10.1126/science.1098704
   Merilä J, 2014, EVOL APPL, V7, P1, DOI 10.1111/eva.12137
   Meunier J, 2012, EVOL ECOL, V26, P669, DOI 10.1007/s10682-011-9510-x
   Miller JS, 2012, ANIM BEHAV, V83, P1387, DOI 10.1016/j.anbehav.2012.03.006
   Moerkens R, 2012, J APPL ENTOMOL, V136, P490, DOI 10.1111/j.1439-0418.2011.01676.x
   Nylin S, 1998, ANNU REV ENTOMOL, V43, P63, DOI 10.1146/annurev.ento.43.1.63
   Paaijmans KP, 2013, GLOBAL CHANGE BIOL, V19, P2373, DOI 10.1111/gcb.12240
   Parmesan C, 2006, ANNU REV ECOL EVOL S, V37, P637, DOI 10.1146/annurev.ecolsys.37.091305.110100
   Polidori C, 2020, ECOL ENTOMOL, V45, P130, DOI 10.1111/een.12781
   Quarrell SR, 2018, BIOL INVASIONS, V20, P1553, DOI 10.1007/s10530-017-1646-3
   Quarrell SR, 2016, CHEMOECOLOGY, V26, P173, DOI 10.1007/s00049-016-0216-y
   Ratz T, 2016, OECOLOGIA, V182, P443, DOI 10.1007/s00442-016-3685-3
   Rohner PT, 2019, J EVOLUTION BIOL, V32, P463, DOI 10.1111/jeb.13429
   Sandrin L, 2015, ECOL ENTOMOL, V40, P159, DOI 10.1111/een.12171
   Singh S, 2018, J THERM BIOL, V71, P180, DOI 10.1016/j.jtherbio.2017.11.010
   Smiseth PT, 2014, EVOLUTION OF INSECT MATING SYSTEMS, P221
   Stoks R, 2014, EVOL APPL, V7, P42, DOI 10.1111/eva.12108
   Thesing J, 2015, P ROY SOC B-BIOL SCI, V282, DOI 10.1098/rspb.2015.1617
   TOURNEUR JC, 1992, CAN ENTOMOL, V124, P1055, DOI 10.4039/Ent1241055-6
   Tourneur JC, 2018, CAN ENTOMOL, V150, P511, DOI 10.4039/tce.2018.24
   Tourneur JC, 2017, CAN ENTOMOL, V149, P600, DOI 10.4039/tce.2017.33
   Van Buskirk J, 2009, J EVOLUTION BIOL, V22, P852, DOI 10.1111/j.1420-9101.2009.01685.x
   Van Meyel S, 2019, BEHAV ECOL, V30, P756, DOI 10.1093/beheco/arz012
   VANCASSEL M, 1980, REPROD NUTR DEV, V20, P759, DOI 10.1051/rnd:19800502
   VANCASSEL M, 1984, ADV STUD BEHAV, V14, P51, DOI 10.1016/S0065-3454(08)60299-5
   Vasseur DA, 2014, P ROY SOC B-BIOL SCI, V281, DOI 10.1098/rspb.2013.2612
   Vogelweith F, 2017, J INSECT PHYSIOL, V103, P64, DOI 10.1016/j.jinsphys.2017.10.007
   WALKER KA, 1993, J CHEM ECOL, V19, P2029, DOI 10.1007/BF00983805
   Weiss C, 2014, ETHOLOGY, V120, P923, DOI 10.1111/eth.12261
   Williams CM, 2017, INTEGR COMP BIOL, V57, P921, DOI 10.1093/icb/icx122
   Williams JW, 2007, P NATL ACAD SCI USA, V104, P5738, DOI 10.1073/pnas.0606292104
   Wirth T, 1998, EVOLUTION, V52, P260, DOI [10.2307/2410942, 10.1111/j.1558-5646.1998.tb05160.x]
   Wong JWY, 2014, J EVOLUTION BIOL, V27, P2420, DOI 10.1111/jeb.12484
   Zhang YB, 2019, BIOL CONTROL, V135, P57, DOI 10.1016/j.biocontrol.2019.04.013
NR 78
TC 18
Z9 19
U1 1
U2 27
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0012-9658
EI 1939-9170
J9 ECOLOGY
JI Ecology
PD APR
PY 2020
VL 101
IS 4
DI 10.1002/ecy.2973
EA FEB 2020
PG 13
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA LV0CG
UT WOS:000511507100001
PM 31945185
OA Green Submitted
DA 2025-01-10
ER

PT C
AU Blok, C
   Leyh, R
   Romero, EJB
   van Os, EA
   van der Salm, C
AF Blok, C.
   Leyh, R.
   Romero, E. J. Baeza
   van Os, E. A.
   van der Salm, C.
BE Fernandez, JA
   DelAmor, FM
   Sadka, A
TI An investment order tool to guide development of greenhouse horticulture
   for two specific regions
SO XI INTERNATIONAL SYMPOSIUM ON PROTECTED CULTIVATION IN MILD WINTER
   CLIMATES AND I INTERNATIONAL SYMPOSIUM ON NETTINGS AND SCREENS IN
   HORTICULTURE
SE Acta Horticulturae
LA English
DT Proceedings Paper
CT 11th International Symposium on Protected Cultivation in Mild Winter
   Climates / 1st International Symposium on Nettings and Screens in
   Horticulture
CY JAN 27-31, 2019
CL Tenerife, SPAIN
SP Int Soc Hort Sci
DE economics; decision support; cultivation system; greenhouse type;
   Mediterranean
ID CLIMATE; DESIGN
AB Growers worldwide often lack means to find the economically soundest order of investing. Authorities face similar problems when deciding which developments to stimulate. For Dutch greenhouse horticulture, models for production, climate, revenue and costs, allow selection of an optimal investment order. This approach was widened into "Adaptive Greenhouse Methodology" which allows evaluation of worldwide climate and greenhouse technology combinations. However, running the models requires expert skills. Our goal was to deliver a simplified software tool, which would allow horticultural suppliers, researchers and growers to autonomously rank alternative investments, for a specific combination of region, greenhouse design and crop. The Investment Order Tool was developed in cooperation with selected horticultural supply companies for the regions Almeria in Spain and the Jordan Valley. In Spain, a flat roofed Parral type greenhouse was compared to an industrial multi-span greenhouse. In Jordan a single tunnel greenhouse was compared to an industrial multi-span greenhouse with passive crop based cooling. The Investment Order Tool uses a one-time run of the Adaptive Greenhouse Methodology based on local information. This data set allows further off-line calculations. All adaptions in greenhouse construction and cultivation system are defined as relative production changes from the local standard. The adaptations are provided with their specific costs and benefits. The investments compared include: reverse osmosis; substrates; nutrient dosing; climate-adapted cultivars; recirculation of drainage water; ventilation capacity; shading screens and thermal screens. The Investment Order Tool informed growers on the investment order with the highest return on investment and the investment order with the lowest demand for capital. Nursery specificity was realized by permitting user defined yield and market price level per month and by defining a first and second class for product quality. It is hoped the Investment Order Tool encourages growers and local authorities to base investment decisions on increasingly solid knowledge.
C1 [Blok, C.; Leyh, R.; Romero, E. J. Baeza; van Os, E. A.; van der Salm, C.] Wageningen Univ & Res, Greenhouse Hort, Bleiswijk, Netherlands.
C3 Wageningen University & Research
RP Blok, C (corresponding author), Wageningen Univ & Res, Greenhouse Hort, Bleiswijk, Netherlands.
EM Chris.Blok@WUR.nl
FU RVO (the ministry of Agriculture, Nature and Food Quality); Top Sector
   Horticulture and Propagation
FX We are grateful for the financial support by RVO (the ministry of
   Agriculture, Nature and Food Quality) and the Top Sector Horticulture
   and Propagation as well as for the financial and active expert support
   provided by the companies Grodan (growing media), Priva (greenhouse
   automation), Ludvig Svensson (climate screens) and Bakker Brothers
   (breeding of greenhouse crops).
CR Baeza EJ, 2005, ACTA HORTIC, P465, DOI 10.17660/ActaHortic.2005.691.56
   Bakker J. C., 2009, Chronica Horticulturae, V49, P19
   Baptista FJ, 2012, CROP PROT, V32, P144, DOI 10.1016/j.cropro.2011.11.005
   Blok C., 2017, GTB1447 WAG U RES
   De Groot N., 2018, HORTICULTURE IN JORD
   De Zwart H. F., 1996, Ph.D. Dissertation,
   Dickson RW, 2016, SCI HORTIC-AMSTERDAM, V200, P36, DOI 10.1016/j.scienta.2015.12.034
   Elings A., 2013, GREENHOUSE DESIGNS M
   Fileccia T., 2015, JORDAN WATER FOOD CH
   Garcia-Balaguer M. L., 2017, Acta Horticulturae, P959, DOI 10.17660/actahortic.2017.1170.123
   Garcia-Garcia M. C., 2016, SISTEMA PRODUCCION H
   Goudriaan J., 1994, MODELLING POTENTIAL, P238, DOI DOI 10.1007/978-94-011-0750-1
   Hemming S, 2014, ACTA HORTIC, V1037, P65
   JDoS, 2018, JORD DEP STAT AGR ST
   Ketter NC, 2015, ACTA HORTIC, V1104, P95, DOI 10.17660/ActaHortic.2015.1104.15
   Montero JI, 2013, SPAN J AGRIC RES, V11, P32, DOI 10.5424/sjar/2013111-411-11
   Os E. A. van, 2017, Acta Horticulturae, P65, DOI 10.17660/actahortic.2017.1176.9
   Romero EJB, 2020, ACTA HORTIC, V1268, P43, DOI 10.17660/ActaHortic.2020.1268.6
   Short TH, 2002, ACTA HORTIC, P141, DOI 10.17660/ActaHortic.2002.578.16
   SONNEVELD C, 1991, NETH J AGR SCI, V39, P115
   Speetjens B., 2012, 1189 GTB WAG U RES
   Tuzel Y., 2017, Acta Horticulturae, P889
   Van Os E.A., 2009, 281 WAG U RES
   Vanthoor B. H. E., 2011, A model-based greenhouse design method
   Vanthoor BHE, 2011, BIOSYST ENG, V110, P363, DOI 10.1016/j.biosystemseng.2011.06.001
   Xu G, 2004, PLANT SOIL, V263, P297, DOI 10.1023/B:PLSO.0000047743.19391.42
NR 26
TC 2
Z9 2
U1 0
U2 1
PU INT SOC HORTICULTURAL SCIENCE
PI LEUVEN 1
PA PO BOX 500, 3001 LEUVEN 1, BELGIUM
SN 0567-7572
EI 2406-6168
BN 978-94-62612-66-2
J9 ACTA HORTIC
PY 2020
VL 1268
BP 27
EP 34
DI 10.17660/ActaHortic.2020.1268.4
PG 8
WC Environmental Sciences; Horticulture
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Environmental Sciences & Ecology; Agriculture
GA BU7XF
UT WOS:000945477800004
DA 2025-01-10
ER

PT J
AU Tognelli, MF
   Anderson, EP
   Jiménez-Segura, LF
   Chuctaya, J
   Chocano, L
   Maldonado-Ocampo, JA
   Mesa-Salazar, L
   Mojica, JI
   Carvajal-Vallejos, FM
   Correa, V
   Ortega, H
   Romero, JFR
   Sánchez-Duarte, P
   Cox, NA
   Hidalgo, M
   Prado, PJ
   Lasso, CA
   Sarmiento, J
   Velásquez, MA
   Villa-Navarro, FA
AF Tognelli, Marcelo F.
   Anderson, Elizabeth P.
   Jimenez-Segura, Luz F.
   Chuctaya, Junior
   Chocano, Luisa
   Maldonado-Ocampo, Javier A.
   Mesa-Salazar, Lina
   Mojica, Jose I.
   Carvajal-Vallejos, Fernando M.
   Correa, Vanessa
   Ortega, Hernan
   Rivadeneira Romero, Juan F.
   Sanchez-Duarte, Paula
   Cox, Neil A.
   Hidalgo, Max
   Jimenez Prado, Pedro
   Lasso, Carlos A.
   Sarmiento, Jaime
   Velasquez, Miguel A.
   Villa-Navarro, Francisco A.
TI Assessing conservation priorities of endemic freshwater fishes in the
   Tropical Andes region
SO AQUATIC CONSERVATION-MARINE AND FRESHWATER ECOSYSTEMS
LA English
DT Article
DE climate change; fish; gap analysis; protected areas; red list; river
ID PROTECTED AREAS; CLIMATE-CHANGE; RESERVE NETWORK; BIODIVERSITY;
   CHALLENGES; DIVERSITY; MANAGEMENT; PROGRESS; THREATS
AB Assessing the effectiveness of protected areas for sustaining species and identifying priority sites for their conservation is vital for decision making, particularly for freshwater fishes in South America, the global centre of freshwater fish diversity. Several conservation planning studies have used threatened freshwater fishes or species that are vulnerable to climate change as conservation targets, but none has included both in priority-setting analysis. The objectives of this study were to identify gaps in the coverage of the existing protected areas in representing the endemic freshwater fishes of the Tropical Andes region, and to identify conservation priority areas that adequately cover threatened species and species vulnerable to climate change. Data on 648 freshwater fishes from the Tropical Andes were used to identify gaps in the protected area coverage, and to identify conservation priority sites under three scenarios: (i) prioritize threatened species; (ii) prioritize species that are vulnerable to climate change; and (iii) prioritize both threatened species and species vulnerable to climate change. A total of 571 species (88% of all species) were not covered by any protected areas; most of them are restricted to <= 10 catchments. To represent both threatened species and species vulnerable to climate change in the third scenario, 635 catchments were identified as priority areas, representing 26.5% of the study area. The number of irreplaceable catchments for this scenario is 475, corresponding to 22.5% of the total area. The results of this study could be crucial for designing strategies for the effective protection of native fish populations in the Tropical Andes, and for planning proactive climate adaptation. It is hoped that the identification of priority areas, particularly irreplaceable catchments, will help to guide conservation and management decisions in the Andean region.
C1 [Tognelli, Marcelo F.; Cox, Neil A.] IUCN, CI, Biodivers Assessment Unit, Arlington, VA USA.
   [Anderson, Elizabeth P.] Florida Int Univ, Dept Earth & Environm, Miami, FL 33199 USA.
   [Anderson, Elizabeth P.] Florida Int Univ, Inst Water & Environm, Miami, FL 33199 USA.
   [Jimenez-Segura, Luz F.] Univ Antioquia, Inst Biol, Grp Ictiol, Medellin, Colombia.
   [Chuctaya, Junior] Univ Fed Rio Grande do Sul, Porto Alegre, RS, Brazil.
   [Chuctaya, Junior; Chocano, Luisa; Correa, Vanessa; Ortega, Hernan; Hidalgo, Max; Velasquez, Miguel A.] Univ Nacl Mayor San Marcos, Museo Hist Nat, Lima, Peru.
   [Maldonado-Ocampo, Javier A.] Pontificia Univ Javeriana, Dept Biol, Bogota, Colombia.
   [Mesa-Salazar, Lina; Sanchez-Duarte, Paula; Lasso, Carlos A.] Inst Invest Recursos Biol Alexander von Humboldt, Bogota, Colombia.
   [Mojica, Jose I.] Univ Nacl Colombia, Inst Ciencias Natur, Bogota, Colombia.
   [Carvajal-Vallejos, Fernando M.] FAUNAGUA, Cochabamba, Bolivia.
   [Rivadeneira Romero, Juan F.] Univ Cent Ecuador, Fac Ciencias Biol, Quito, Ecuador.
   [Jimenez Prado, Pedro] Pontificia Univ Catolica Ecuador Sede Esmeraldas, Esmeraldas, Ecuador.
   [Sarmiento, Jaime] Museo Nacl Hist Nat, La Paz, Bolivia.
   [Villa-Navarro, Francisco A.] Univ Tolima, Fac Ciencias, Ibague, Colombia.
C3 State University System of Florida; Florida International University;
   State University System of Florida; Florida International University;
   Universidad de Antioquia; Universidade Federal do Rio Grande do Sul;
   Universidad Nacional Mayor de San Marcos; Pontificia Universidad
   Javeriana; Alliance; International Center for Tropical Agriculture -
   CIAT; Universidad Nacional de Colombia; Universidad Central del Ecuador;
   Universidad del Tolima
RP Tognelli, MF (corresponding author), IUCN, CI, Biodivers Assessment Unit, 2011 Crystal Dr,Suite 500, Arlington, VA 22202 USA.
EM marcelo.tognelli@iucn.org
RI Hidalgo, Max/AAB-7891-2019; Carvajal-Vallejos, Fernando/AGO-7079-2022;
   Tognelli, Marcelo/L-3958-2019; Chuctaya Vasquez, Junior/M-2503-2016
OI Hidalgo, Max/0000-0002-0071-5159; Maldonado Ocampo, Javier
   Alejandro/0000-0003-3024-237X; Chuctaya Vasquez,
   Junior/0000-0002-8876-4675; Jimenez Prado, Pedro/0000-0002-7681-9309;
   Rivadeneira, Juan Francisco/0000-0002-3293-8381; Chocano Arevalo,
   Luisa/0000-0001-5344-552X; Tognelli, Marcelo/0000-0002-9761-4505
FU Conservation International; John D. and Catherine T. MacArthur
   Foundation
FX Conservation International; John D. and Catherine T. MacArthur
   Foundation, Grant/Award Number: Comprehensive assessments to understand
   and mitigate the impacts of development on freshwater biodiversity in
   the Tropical Andes
CR Abell R, 2007, BIOL CONSERV, V134, P48, DOI 10.1016/j.biocon.2006.08.017
   Anderson EP, 2018, SCI ADV, V4, DOI 10.1126/sciadv.aao1642
   Anderson EP, 2011, CONSERV BIOL, V25, P30, DOI 10.1111/j.1523-1739.2010.01568.x
   [Anonymous], 2009, SPATIAL CONSERVATION
   Asner GP, 2013, P NATL ACAD SCI USA, V110, P18454, DOI 10.1073/pnas.1318271110
   Autoridad Nacional de Acuicultura y Pesca (AUNAP), 2016, MERC ESP ORN EST ALZ
   Balian EV, 2008, HYDROBIOLOGIA, V595, P627, DOI 10.1007/s10750-007-9246-3
   Ball I. R., 2009, SPATIAL CONSERVATION, P185
   Barthem RB, 2017, SCI REP-UK, V7, DOI 10.1038/srep41784
   Bond NR, 2014, DIVERS DISTRIB, V20, P931, DOI 10.1111/ddi.12213
   Bush A, 2013, DIVERS DISTRIB, V19, P86, DOI 10.1111/ddi.12007
   Carr J., 2016, ESTADO CONSERVACI N, P127
   Carrizo SF, 2017, J APPL ECOL, V54, P1209, DOI 10.1111/1365-2664.12842
   Carvajal-Quintero JD, 2017, CONSERV LETT, V10, P708, DOI 10.1111/conl.12336
   Carwardine J, 2008, PLOS ONE, V3, DOI 10.1371/journal.pone.0002586
   CBD, 2010, STRATEGICPLAN CONVEN
   Chessman BC, 2013, J APPL ECOL, V50, P969, DOI 10.1111/1365-2664.12104
   Collen B, 2014, GLOBAL ECOL BIOGEOGR, V23, P40, DOI 10.1111/geb.12096
   Comte L, 2017, NAT CLIM CHANGE, V7, P718, DOI 10.1038/NCLIMATE3382
   Comte L, 2013, FRESHWATER BIOL, V58, P625, DOI 10.1111/fwb.12081
   Darwall WRT, 2011, CONSERV LETT, V4, P474, DOI 10.1111/j.1755-263X.2011.00202.x
   Dudgeon D, 2006, BIOL REV, V81, P163, DOI 10.1017/S1464793105006950
   Esselman PC, 2011, FRESHWATER BIOL, V56, P71, DOI 10.1111/j.1365-2427.2010.02417.x
   Fausch KD, 2002, BIOSCIENCE, V52, P483, DOI 10.1641/0006-3568(2002)052[0483:LTRBTG]2.0.CO;2
   Fernanda Jimenez-Segura Luz, 2014, Biota Colombiana, V15, P3
   Finer M, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0035126
   Finer M, 2008, PLOS ONE, V3, DOI 10.1371/journal.pone.0002932
   Forsberg BR, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0182254
   Frederico RG, 2016, AQUAT CONSERV, V26, P91, DOI 10.1002/aqc.2658
   Frederico RG, 2018, BIOL CONSERV, V219, P12, DOI 10.1016/j.biocon.2017.12.032
   Game E.T., 2008, MARXAN USER MANUAL M
   García JA, 2014, THEMATA, P247, DOI 10.12795/themata.2014.i50.12
   Greenwood O, 2016, J APPL ECOL, V53, P885, DOI 10.1111/1365-2664.12602
   Heller NE, 2009, BIOL CONSERV, V142, P14, DOI 10.1016/j.biocon.2008.10.006
   Herbert ME, 2010, CONSERV BIOL, V24, P1002, DOI 10.1111/j.1523-1739.2010.01460.x
   Hermoso V, 2016, AQUAT CONSERV, V26, P3, DOI 10.1002/aqc.2681
   Hermoso V, 2015, J ENVIRON MANAGE, V161, P358, DOI 10.1016/j.jenvman.2015.07.023
   Hermoso V, 2015, FRESHWATER BIOL, V60, P698, DOI 10.1111/fwb.12519
   Hermoso V, 2012, DIVERS DISTRIB, V18, P448, DOI 10.1111/j.1472-4642.2011.00879.x
   Holland RA, 2012, BIOL CONSERV, V148, P167, DOI 10.1016/j.biocon.2012.01.016
   MANCERA-RODRÍGUEZ NÉSTOR JAVIER, 2008, Acta biol.Colomb., V13, P23
   Jiménez-Segura LF, 2016, J FISH BIOL, V89, P65, DOI 10.1111/jfb.13018
   Jimenez-Segura L. F., 2016, ESTADO CONSERVACION, P36
   Juffe-Bignoli D, 2016, AQUAT CONSERV, V26, P133, DOI 10.1002/aqc.2638
   Lawler JJ, 2003, CONSERV BIOL, V17, P875, DOI 10.1046/j.1523-1739.2003.01638.x
   Lawrence DJ, 2011, CONSERV LETT, V4, P364, DOI 10.1111/j.1755-263X.2011.00185.x
   Lehner B, 2013, HYDROL PROCESS, V27, P2171, DOI 10.1002/hyp.9740
   Linke S, 2011, FRESHWATER BIOL, V56, P6, DOI 10.1111/j.1365-2427.2010.02456.x
   Markovic D, 2014, DIVERS DISTRIB, V20, P1097, DOI 10.1111/ddi.12232
   Moilanen A, 2008, FRESHWATER BIOL, V53, P577, DOI 10.1111/j.1365-2427.2007.01906.x
   Moreau MA, 2007, ENVIRON CONSERV, V34, P12, DOI 10.1017/S0376892907003566
   Moyle PB, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0063883
   Myers BJE, 2017, REV FISH BIOL FISHER, V27, P339, DOI 10.1007/s11160-017-9476-z
   Nel JL, 2007, DIVERS DISTRIB, V13, P341, DOI 10.1111/j.1472-4642.2007.00308.x
   Nel JL, 2009, AQUAT CONSERV, V19, P474, DOI 10.1002/aqc.1010
   Ormerod SJ, 2010, FRESHWATER BIOL, V55, P1, DOI 10.1111/j.1365-2427.2009.02395.x
   Palmer MA, 2009, ENVIRON MANAGE, V44, P1053, DOI 10.1007/s00267-009-9329-1
   Pelicice FM, 2017, FISH FISH, V18, P1119, DOI 10.1111/faf.12228
   Poff NL, 1997, BIOSCIENCE, V47, P769, DOI 10.2307/1313099
   Raghavan R, 2016, AQUAT CONSERV, V26, P78, DOI 10.1002/aqc.2653
   Reis RE, 2016, J FISH BIOL, V89, P12, DOI 10.1111/jfb.13016
   Rodrigues ASL, 2007, ANNU REV ECOL EVOL S, V38, P713, DOI 10.1146/annurev.ecolsys.38.091206.095737
   Russi D., 2013, EC ECOSYSTEMS BIODIV, V78, P118
   Saunders DL, 2002, CONSERV BIOL, V16, P30, DOI 10.1046/j.1523-1739.2002.99562.x
   SCOTT JM, 1993, WILDLIFE MONOGR, P1
   Stewart RR, 2005, ENVIRON MODEL ASSESS, V10, P203, DOI 10.1007/s10666-005-9001-y
   Strayer DL, 2010, J N AM BENTHOL SOC, V29, P344, DOI 10.1899/08-171.1
   Swenson JJ, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0018875
   Thieme ML., 2010, Fresh water: the essence of life, P123
   Tognelli M.F., 2016, ESTADO CONSERVACI N
   Toussaint A, 2016, SCI REP-UK, V6, DOI 10.1038/srep22125
   Turschwell MP, 2018, AQUAT CONSERV, V28, P575, DOI 10.1002/aqc.2864
   Vörösmarty CJ, 2010, NATURE, V467, P555, DOI 10.1038/nature09440
   World Wide Fund for Nature (WWF), 2016, RISK RES NEW ER
NR 74
TC 23
Z9 24
U1 1
U2 26
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 JUL
PY 2019
VL 29
IS 7
SI SI
BP 1123
EP 1132
DI 10.1002/aqc.2971
PG 10
WC Environmental Sciences; Marine & Freshwater Biology; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Marine & Freshwater Biology; Water
   Resources
GA IJ3RL
UT WOS:000475822100010
DA 2025-01-10
ER

PT J
AU Feng, HH
   Zou, B
AF Feng, Huihui
   Zou, Bin
TI A greening world enhances the surface-air temperature difference
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Surface-air temperature difference; Vegetation; Climate and environment
   change; Contribution; Global
ID LAND-USE; SPATIAL VARIABILITY; VEGETATION CHANGE; SOIL-MOISTURE; COVER
   CHANGES; CLIMATE; HIATUS; ACCELERATION; URBANIZATION; EMISSIVITY
AB The surface-air temperature difference (Ts-Ta) is a critical variable for tracking climatic and environmental change. Vegetation has unavoidably affected the temperature by altering surface properties, while the magnitude of this effect has remained unknown. This study aimed to investigate the patterns of global Ts-Ta and quantify the contribution of vegetation change. Trend analysis, correlation analysis and a trajectory-based method were adopted for the investigation. The results demonstrated that the global Ts-Ta decreased by -0.140 K from 2001 to 2016. The greening trend covered 24.46% of the land and played a profound role in changing Ts-Ta. In particular, vegetation changes resulted in -0.0022 K, -0.0092 K and - 0.0043 K of the Ts-Ta decreases at the global, greening and browning levels, respectively accounting for 11.58%, 35.38% and 20.38% of the total decrease. Physically, vegetation influenced Ts-Ta mainly by altering atmospheric properties, rather than surface properties. Specifically, the greening of the surface reduced the albedo at a rate of -0.0003/year over 20% of the global land and enhanced atmospheric water vapor by 3 x 10(-5) g/m(3) over approximately 40% of the land. Meanwhile, the effect of vegetation change varied with coverage. A reduction in albedo caused by vegetation change occurred equally over different vegetated conditions, while the enhancement of atmospheric water vapor occurred mainly in sparsely (0.10 < NDVI < 0.30) and densely (0.55 < NDVI < 0.70) vegetated regions. Under these conditions, the vegetation change mainly affected Ts-Ta in sparsely vegetated regions (NDVI < 0.4). The results of this study are helpful for understanding the physical mechanism behind changes in global Ts-Ta and support climatic adaptation and environmental management. (C) 2018 Elsevier B.V. All rights reserved.
C1 [Feng, Huihui; Zou, Bin] Cent South Univ, Sch Geosci & Infophys, Changsha 410083, Hunan, Peoples R China.
   Chinese Minist Educ, Key Lab Metallogen Predict Nonferrous Met & Geol, Changsha 410083, Hunan, Peoples R China.
C3 Central South University
RP Feng, HH; Zou, B (corresponding author), Cent South Univ, Sch Geosci & Infophys, Changsha 410083, Hunan, Peoples R China.
EM hhfeng@csu.edu.cn; 210010@csu.edu.cn
RI Feng, Huihui/V-1807-2019
OI Feng, Huihui/0000-0003-1535-9940
FU National Key Research and Development Program [2016YFC0206205]; National
   Natural Science Foundation of China [41501034]; Natural Science
   Foundation of Hunan Province [2018JJ2498]
FX This work was supported in part by the National Key Research and
   Development Program [grant numbers 2016YFC0206205], the National Natural
   Science Foundation of China [grant numbers 41501034] and the Natural
   Science Foundation of Hunan Province [grant numbers 2018JJ2498]. We
   highly appreciate the editor and anonymous reviewers for their
   constructive comments on this manuscript.
CR [Anonymous], 1988, INTRO BOUNDARY LAYER, DOI DOI 10.1007/978-94-009-3027-8
   Aragao LEOC, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-017-02771-y
   Arneth A, 2017, NAT GEOSCI, V10, P79, DOI [10.1038/NGEO2882, 10.1038/ngeo2882]
   Brown PT, 2017, NATURE, V552, P45, DOI 10.1038/nature24672
   BRUTSAERT W, 1975, WATER RESOUR RES, V11, P742, DOI 10.1029/WR011i005p00742
   Campbell J. B., 2011, Introduction to remote sensing
   CERES, 2017, CERES SYN1DEG ED4A D
   Church J.A., 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
   Cox PM, 2000, NATURE, V408, P184, DOI 10.1038/35041539
   Dai AG, 2015, NAT CLIM CHANGE, V5, P555, DOI 10.1038/nclimate2605
   Dai AG, 2011, WIRES CLIM CHANGE, V2, P45, DOI 10.1002/wcc.81
   de Jong R, 2012, GLOBAL CHANGE BIOL, V18, P642, DOI 10.1111/j.1365-2486.2011.02578.x
   Ellison D, 2017, GLOBAL ENVIRON CHANG, V43, P51, DOI 10.1016/j.gloenvcha.2017.01.002
   Evan AT, 2015, J CLIMATE, V28, P108, DOI 10.1175/JCLI-D-14-00039.1
   Fan Y, 2008, J GEOPHYS RES-ATMOS, V113, DOI 10.1029/2007JD008470
   Feng HH, 2017, J HYDROL, V550, P220, DOI 10.1016/j.jhydrol.2017.04.056
   Feng HH, 2016, SCI REP-UK, V6, DOI 10.1038/srep32782
   Feng HH, 2015, SCI REP-UK, V5, DOI 10.1038/srep18018
   Feng HH, 2014, IEEE J-STARS, V7, P4010, DOI 10.1109/JSTARS.2013.2264718
   Feng HH, 2014, J HYDROL, V514, P337, DOI 10.1016/j.jhydrol.2014.04.044
   Feng HH, 2014, ADV SPACE RES, V53, P463, DOI 10.1016/j.asr.2013.11.028
   Feulner G, 2013, J CLIMATE, V26, P7136, DOI 10.1175/JCLI-D-12-00636.1
   FRANK TD, 1984, ANN ASSOC AM GEOGR, V74, P393, DOI 10.1111/j.1467-8306.1984.tb01462.x
   Gelaro R, 2017, J CLIMATE, V30, P5419, DOI 10.1175/JCLI-D-16-0758.1
   Gordon LJ, 2005, P NATL ACAD SCI USA, V102, P7612, DOI 10.1073/pnas.0500208102
   Hansen J, 2010, REV GEOPHYS, V48, DOI 10.1029/2010RG000345
   Hansen J, 2006, P NATL ACAD SCI USA, V103, P14288, DOI 10.1073/pnas.0606291103
   Held IM, 2000, ANNU REV ENERG ENV, V25, P441, DOI 10.1146/annurev.energy.25.1.441
   Houghton RA, 2012, BIOGEOSCIENCES, V9, P5125, DOI 10.5194/bg-9-5125-2012
   Hua LJ, 2008, THEOR APPL CLIMATOL, V93, P179, DOI 10.1007/s00704-007-0339-8
   Jasechko S, 2013, NATURE, V496, P347, DOI 10.1038/nature11983
   Jia AL, 2016, REMOTE SENS-BASEL, V8, DOI 10.3390/rs8020090
   Jiang P., 2018, REMOTE SENS
   Jones PD, 2012, J GEOPHYS RES-ATMOS, V117, DOI 10.1029/2011JD017139
   Jones PD, 1999, REV GEOPHYS, V37, P173, DOI 10.1029/1999RG900002
   Kato S, 2013, J CLIMATE, V26, P2719, DOI 10.1175/JCLI-D-12-00436.1
   Kosaka Y, 2013, NATURE, V501, P403, DOI 10.1038/nature12534
   Lambin EF, 1997, PROG PHYS GEOG, V21, P375, DOI 10.1177/030913339702100303
   Lawrence D, 2015, NAT CLIM CHANGE, V5, P27, DOI [10.1038/NCLIMATE2430, 10.1038/nclimate2430]
   Lean J., 2009, J CLIMATOL, V11, P3069
   Lean JL, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL034864
   Lee S, 2017, GEOPHYS RES LETT, V44, P10654, DOI 10.1002/2017GL075375
   LEGATES DR, 1990, THEOR APPL CLIMATOL, V41, P11, DOI 10.1007/BF00866198
   Li Y, 2018, SCI ADV, V4, DOI 10.1126/sciadv.aar4182
   Liu YB, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/9/094010
   Mahmood R, 2014, INT J CLIMATOL, V34, P929, DOI 10.1002/joc.3736
   Makarieva AM, 2013, THEOR APPL CLIMATOL, V111, P79, DOI 10.1007/s00704-012-0643-9
   Medhaug I, 2017, NATURE, V545, P41, DOI 10.1038/nature22315
   Meehl GA, 2004, J CLIMATE, V17, P3721, DOI 10.1175/1520-0442(2004)017<3721:CONAAF>2.0.CO;2
   Meehl GA, 2014, NAT CLIM CHANGE, V4, P898, DOI [10.1038/NCLIMATE2357, 10.1038/nclimate2357]
   Meinshausen M, 2009, NATURE, V458, P1158, DOI 10.1038/nature08017
   MORAN MS, 1994, REMOTE SENS ENVIRON, V49, P246, DOI 10.1016/0034-4257(94)90020-5
   Oki T, 2006, SCIENCE, V313, P1068, DOI 10.1126/science.1128845
   Ongoma V, 2017, METEOROL ATMOS PHYS, V129, P131, DOI 10.1007/s00703-016-0462-0
   Pielke RA, 2011, WIRES CLIM CHANGE, V2, P828, DOI 10.1002/wcc.144
   Rahmstorf S, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa6825
   RAMANATHAN V, 1986, J GEOPHYS RES-ATMOS, V91, P8649, DOI 10.1029/JD091iD08p08649
   Rechid D, 2009, THEOR APPL CLIMATOL, V95, P245, DOI 10.1007/s00704-008-0003-y
   Shen MG, 2015, P NATL ACAD SCI USA, V112, P9299, DOI 10.1073/pnas.1504418112
   Sobrino JA, 2004, REMOTE SENS ENVIRON, V90, P434, DOI 10.1016/j.rse.2004.02.003
   Solano R., 2010, MODIS Vegetation Index User's Guide (MOD13 Series) Version 2.00, P1
   Staley D. O., 1972, Journal of Applied Meteorology, V11, P349, DOI 10.1175/1520-0450(1972)011<0349:EAEUCS>2.0.CO;2
   STEWART JB, 1994, J APPL METEOROL, V33, P1110, DOI 10.1175/1520-0450(1994)033<1110:SHFRST>2.0.CO;2
   Stott PA, 2000, SCIENCE, V290, P2133, DOI 10.1126/science.290.5499.2133
   Tett S. F. B., 2002, Journal of Geophysical Research, V107, pACL10, DOI 10.1029/2000JD000028
   Valor E, 1996, REMOTE SENS ENVIRON, V57, P167, DOI 10.1016/0034-4257(96)00039-9
   Vancutsem C, 2010, REMOTE SENS ENVIRON, V114, P449, DOI 10.1016/j.rse.2009.10.002
   VANDEGRIEND AA, 1993, INT J REMOTE SENS, V14, P1119, DOI 10.1080/01431169308904400
   Veal K., 2016, EGU GEN ASS C, P18
   Wang LX, 2014, GEOPHYS RES LETT, V41, P6753, DOI 10.1002/2014GL061439
   Watanabe M, 2014, NAT CLIM CHANGE, V4, P893, DOI [10.1038/NCLIMATE2355, 10.1038/nclimate2355]
   Wolf J, 2010, GLOBAL ENVIRON CHANG, V20, P44, DOI 10.1016/j.gloenvcha.2009.09.004
   Xie SP, 2016, NAT GEOSCI, V9, P29, DOI [10.1038/NGEO2581, 10.1038/ngeo2581]
   Yan XH, 2016, EARTHS FUTURE, V4, P472, DOI 10.1002/2016EF000417
   Zhang J, 2015, J GEOPHYS RES-ATMOS, V120, P8065, DOI 10.1002/2015JD023395
   Zhang RH, 2017, NAT CLIM CHANGE, V7, P238, DOI 10.1038/nclimate3257
   Zhu ZC, 2016, NAT CLIM CHANGE, V6, P791, DOI [10.1038/NCLIMATE3004, 10.1038/nclimate3004]
   Zou B, 2019, ENVIRON INT, V125, P529, DOI 10.1016/j.envint.2018.10.045
NR 78
TC 42
Z9 47
U1 1
U2 124
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 2019
VL 658
BP 385
EP 394
DI 10.1016/j.scitotenv.2018.12.210
PG 10
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA HI1AI
UT WOS:000456175700038
PM 30579196
DA 2025-01-10
ER

PT J
AU Rolandi, C
   Lighton, JRB
   de la Vega, GJ
   Schilman, PE
   Mensch, J
AF Rolandi, Carmen
   Lighton, John R. B.
   de la Vega, Gerardo J.
   Schilman, Pablo E.
   Mensch, Julian
TI Genetic variation for tolerance to high temperatures in a population of
   <i>Drosophila melanogaster</i>
SO ECOLOGY AND EVOLUTION
LA English
DT Article
DE climatic adaptation; CTmax; DGRP; global warming scenario; GWAS; SNPs
ID THERMAL LIMITS; HEAT-RESISTANCE; REFERENCE PANEL; CLIMATE; EVOLUTIONARY;
   EXPRESSION; CAPACITY; IMPACTS; STRESS; PLASTICITY
AB The range of thermal tolerance is one of the main factors influencing the geographic distribution of species. Climate change projections predict increases in average and extreme temperatures over the coming decades; hence, the ability of living beings to resist these changes will depend on physiological and adaptive responses. On an evolutionary scale, changes will occur as the result of selective pressures on individual heritable differences. In this work, we studied the genetic basis of tolerance to high temperatures in the fly Drosophila melanogaster and whether this species presents sufficient genetic variability to allow expansion of its upper thermo-tolerance limit. To do so, we used adult flies derived from a natural population belonging to the Drosophila Genetic Reference Panel, for which genomic sequencing data are available. We characterized the phenotypic variation of the upper thermal limit in 34 lines by measuring knockdown temperature (i.e., critical thermal maximum [CTmax]) by exposing flies to a ramp of increasing temperature (0.25 degrees C/min). Fourteen percent of the variation in CTmax is explained by the genetic variation across lines, without a significant sexual dimorphism. Through a genomewide association study, 12 single nucleotide polymorphisms associated with the CTmax were identified. In most of these SNPs, the less frequent allele increased the upper thermal limit suggesting that this population harbors raw genetic variation capable of expanding its heat tolerance. This potential upper thermal tolerance increase has implications under the global warming scenario. Past climatic records show a very low incidence of days above CTmax (10 days over 25 years); however, future climate scenarios predict 243 days with extreme high temperature above CTmax from 2045 to 2070. Thus, in the context of the future climate warming, rising temperatures might drive the evolution of heat tolerance in this population by increasing the frequency of the alleles associated with higher CTmax.
C1 [Rolandi, Carmen; Schilman, Pablo E.] Univ Buenos Aires, Fac Ciencias Exactas & Nat, DBBEA, IBBEA,CONICET, Buenos Aires, DF, Argentina.
   [Lighton, John R. B.] Sable Syst Int, Las Vegas, NV USA.
   [de la Vega, Gerardo J.] INTA EEA Bariloche, GEPI, San Carlos De Bariloche, Rio Negro, Argentina.
   [Mensch, Julian] Univ Buenos Aires, Fac Ciencias Exactas & Nat, DEGE, IEGEBA,CONICET, Buenos Aires, DF, Argentina.
C3 Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET);
   University of Buenos Aires; Instituto Nacional de Tecnologia
   Agropecuaria (INTA); University of Buenos Aires; Consejo Nacional de
   Investigaciones Cientificas y Tecnicas (CONICET)
RP Schilman, PE; Mensch, J (corresponding author), Univ Buenos Aires, Fac Ciencias Exactas & Nat, Buenos Aires, DF, Argentina.
EM schilman@bg.fcen.uba.ar; jmensch@ege.fcen.uba.ar
RI Lighton, John/A-9691-2009; Schilman, Pablo/GLR-8952-2022; MENSCH,
   JULIAN/GYD-5497-2022
OI Lighton, John/0000-0002-9264-924X; Schilman, Pablo/0000-0003-1485-1650;
   MENSCH, JULIAN/0000-0002-2298-4309
CR Angilletta MJ, 2009, BIO HABIT, P1, DOI 10.1093/acprof:oso/9780198570875.001.1
   [Anonymous], 2006, Drosophila: A Guide to Species Identification and Use
   [Anonymous], INT J GENOMICS
   [Anonymous], 2002, Biochemical Adaptation
   Bates D, 2015, J STAT SOFTW, V67, P1, DOI 10.18637/jss.v067.i01
   Birch-Machin I, 2005, GENOME BIOL, V6, DOI 10.1186/gb-2005-6-7-r63
   Blackburn S, 2014, J EXP BIOL, V217, P1918, DOI 10.1242/jeb.099184
   Bozinovic F, 2011, ANNU REV ECOL EVOL S, V42, P155, DOI 10.1146/annurev-ecolsys-102710-145055
   Bush A, 2016, ECOL LETT, V19, P1468, DOI 10.1111/ele.12696
   Chen GC, 2008, AUTOPHAGY, V4, P37, DOI 10.4161/auto.5141
   Chown S., 2004, Insect physiological ecology: mechanisms and patterns
   Chown SL, 2009, FUNCT ECOL, V23, P133, DOI 10.1111/j.1365-2435.2008.01481.x
   Coumou D, 2012, NAT CLIM CHANGE, V2, P491, DOI 10.1038/NCLIMATE1452
   De La Vega GJ, 2018, MED VET ENTOMOL, V32, P1, DOI 10.1111/mve.12262
   Deutsch CA, 2008, P NATL ACAD SCI USA, V105, P6668, DOI 10.1073/pnas.0709472105
   Easterling DR, 2000, SCIENCE, V289, P2068, DOI 10.1126/science.289.5487.2068
   Fallis LC, 2011, GENETICA, V139, P1331, DOI 10.1007/s10709-012-9635-z
   Giannakou ME, 2001, J EXP BIOL, V204, P3703
   Hangartner S, 2016, FUNCT ECOL, V30, P442, DOI 10.1111/1365-2435.12499
   Hervas S, 2017, BIOINFORMATICS, V33, P2779, DOI 10.1093/bioinformatics/btx301
   Hoffmann AA, 1997, J INSECT PHYSIOL, V43, P393, DOI 10.1016/S0022-1910(96)00108-4
   Huang W, 2014, GENOME RES, V24, P1193, DOI 10.1101/gr.171546.113
   Iliadi KG, 2008, P NATL ACAD SCI USA, V105, P19986, DOI 10.1073/pnas.0810698105
   Jensen LT, 2008, CELL STRESS CHAPERON, V13, P177, DOI 10.1007/s12192-008-0020-x
   Juneja P, 2016, BMC GENOMICS, V17, DOI 10.1186/s12864-016-3333-7
   Knight D, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0132548
   Kuznetsova A, 2017, J STAT SOFTW, V82, P1, DOI 10.18637/jss.v082.i13
   Levine MT, 2011, MOL BIOL EVOL, V28, P249, DOI 10.1093/molbev/msq197
   Lighton JRB, 2004, J EXP BIOL, V207, P1903, DOI 10.1242/jeb.00970
   Lutterschmidt WI, 1997, CAN J ZOOL, V75, P1561, DOI 10.1139/z97-783
   Mackay TFC, 2012, NATURE, V482, P173, DOI 10.1038/nature10811
   Mitchell KA, 2010, FUNCT ECOL, V24, P694, DOI 10.1111/j.1365-2435.2009.01666.x
   Nielsen MM, 2006, CELL STRESS CHAPERON, V11, P325, DOI 10.1379/CSC-207.1
   Overgaard J, 2014, GLOBAL CHANGE BIOL, V20, P1738, DOI 10.1111/gcb.12521
   Overgaard J, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0032758
   Pappas C, 2007, COMP BIOCHEM PHYS A, V146, P355, DOI 10.1016/j.cbpa.2006.11.010
   Parmesan C, 2000, B AM METEOROL SOC, V81, P443, DOI 10.1175/1520-0477(2000)081<0443:IOEWAC>2.3.CO;2
   Pool JE, 2015, MOL BIOL EVOL, V32, P3236, DOI 10.1093/molbev/msv194
   Pool JE, 2012, PLOS GENET, V8, DOI 10.1371/journal.pgen.1003080
   R Core Team, 2017, R LANG ENV STAT COMP
   Rezende EL, 2011, FUNCT ECOL, V25, P111, DOI 10.1111/j.1365-2435.2010.01778.x
   Richter K, 2010, MOL CELL, V40, P253, DOI 10.1016/j.molcel.2010.10.006
   Robertson RM, 2012, CURR OPIN NEUROBIOL, V22, P724, DOI 10.1016/j.conb.2012.01.008
   Robertson RM, 2004, J THERM BIOL, V29, P351, DOI 10.1016/j.jtherbio.2004.08.073
   Santos M, 2011, FUNCT ECOL, V25, P1169, DOI 10.1111/j.1365-2435.2011.01908.x
   Sgrò CM, 2010, J EVOLUTION BIOL, V23, P2484, DOI 10.1111/j.1420-9101.2010.02110.x
   Sorensen JG, 2013, J EXP BIOL, V216, P809, DOI 10.1242/jeb.076356
   Sorensen JG, 2016, CURR OPIN INSECT SCI, V17, P98, DOI 10.1016/j.cois.2016.08.003
   Sorensen JG, 2005, CELL STRESS CHAPERON, V10, P312, DOI 10.1379/CSC-128R1.1
   Sorensen JG, 2003, ECOL LETT, V6, P1025, DOI 10.1046/j.1461-0248.2003.00528.x
   Sunday JM, 2014, P NATL ACAD SCI USA, V111, P5610, DOI 10.1073/pnas.1316145111
   Terblanche JS, 2011, J EXP BIOL, V214, P3713, DOI 10.1242/jeb.061283
   Vega G. J. de la, 2015, Ecography, V38, P851
   Zhao L, 2015, PLOS GENET, V11, DOI 10.1371/journal.pgen.1005184
NR 54
TC 25
Z9 29
U1 0
U2 24
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 2045-7758
J9 ECOL EVOL
JI Ecol. Evol.
PD NOV
PY 2018
VL 8
IS 21
BP 10374
EP 10383
DI 10.1002/ece3.4409
PG 10
WC Ecology; Evolutionary Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Evolutionary Biology
GA HA5WV
UT WOS:000450351400002
PM 30464811
OA Green Published
DA 2025-01-10
ER

PT J
AU Mikula, O
   Sumbera, R
   Aghová, T
   Mbau, JS
   Katakweba, AS
   Sabuni, CA
   Bryja, J
AF Mikula, Ondrej
   Sumbera, Radim
   Aghova, Tatiana
   Mbau, Judith S.
   Katakweba, Abdul S.
   Sabuni, Christopher A.
   Bryja, Josef
TI Evolutionary history and species diversity of African pouched mice
   (Rodentia: Nesomyidae: <i>Saccostomus</i>)
SO ZOOLOGICA SCRIPTA
LA English
DT Article
ID MYOMYS-STENOCEPHALEMYS COMPLEX; POPULATION-DYNAMICS; CLIMATIC
   ADAPTATION; GENETIC-DIVERGENCE; STATISTICAL-METHOD; MUROID RODENTS;
   MOLE-RATS; PHYLOGENY; MODEL; DIVERSIFICATION
AB We explore diversity of African pouched mice, genus Saccostomus (Rodentia, Nesomyidae), by sampling molecular and morphological variation across their continental-scale distribution in southern and eastern African savannahs and woodlands. Both mitochondrial (cytochrome b) and nuclear DNA (IRBP, RAG1) as well as skull morphology confirm the distinction between two recognized species, S.campestris and S.mearnsi, with disjunct distribution in the Zambezian and Somali-Maasai bioregions, respectively. Molecular dating suggests the divergence of these taxa occurred in the Early Pliocene, 3.9Ma before present, whereas the deepest divergences within each of them are only as old as 2.0Ma for S.mearnsi and 1.4Ma for S.campestris. Based on cytochrome b phylogeny, we defined five clades (three within S.campestris, two in S.mearnsi) whose species status was considered in the light of nuclear DNA markers and morphology. We conclude that S.campestris group consists of two subspecies S.campestris campestris (Peters, 1846; comprising two cytochrome b clades) and S.campestris mashonae (de Winton, 1897) that are moderately differentiated, albeit distinct in IRBP and skull form. They likely hybridize to a limited extent along the Kafue-Zambezi Rivers. Saccostomus mearnsi group consists of two species, S.mearnsi (Heller, 1910) and S.umbriventer (Miller, 1910), that are markedly differentiated in both nuclear markers and skull form and may possibly co-occur in south-western Kenya and north-eastern Tanzania. Analysis of historical demography suggests both subspecies of S.campestris experienced population expansion dated to the Last Glacial. In the present range of S.campestris group, the distribution modelling suggests a moderate fragmentation of suitable habitats during the last glacial cycle, whereas in the range of S.mearnsi group it predicts substantial shifts of its occurrence in the same period.
C1 [Mikula, Ondrej] Acad Sci Czech Republ, Inst Anim Physiol & Genet, Veveri 97, Brno 60200, Czech Republic.
   [Mikula, Ondrej; Aghova, Tatiana; Bryja, Josef] Acad Sci Czech Republ, Inst Vertebrate Biol, Brno, Czech Republic.
   [Sumbera, Radim] Univ South Bohemia, Dept Zool, Fac Sci, Ceske Budejovice, Czech Republic.
   [Aghova, Tatiana; Bryja, Josef] Masaryk Univ, Dept Bot & Zool, Fac Sci, Brno, Czech Republic.
   [Mbau, Judith S.] Univ Nairobi, Coll Agr & Vet Sci, Nairobi, Kenya.
   [Katakweba, Abdul S.; Sabuni, Christopher A.] Sokoine Univ Agr, Ctr Pest Management, Morogoro, Tanzania.
C3 Czech Academy of Sciences; Institute of Animal Physiology & Genetics of
   the Czech Academy of Sciences; Czech Academy of Sciences; Institute of
   Vertebrate Biology of the Czech Academy of Sciences; University of South
   Bohemia Ceske Budejovice; Masaryk University Brno; University of
   Nairobi; Sokoine University of Agriculture
RP Mikula, O (corresponding author), Acad Sci Czech Republ, Inst Anim Physiol & Genet, Veveri 97, Brno 60200, Czech Republic.
EM onmikula@gmail.com; sumbera@prf.jcu.cz; tatiana.aghova@gmail.com;
   jsyombua04@yahoo.com; katakweba@suanet.ac.tz; sabunic03@gmail.com;
   bryja@brno.cas.cz
RI Mikula, Ondrej/F-9729-2014; Bryja, Josef/C-3013-2008; Sumbera,
   Radim/D-9072-2016
OI Bryja, Josef/0000-0003-0516-7742; Sumbera, Radim/0000-0001-8658-9378
FU GACR Czech Science Foundation [P506-10-0983, 15-20229S]
FX This study was supported by the projects of the GACR Czech Science
   Foundation, nos. P506-10-0983 and 15-20229S. For help in the field and
   with logistics, we acknowledge W.N. Chitaukali, H.
   Konvickova-Patzenhauerova, J. Krasova, M. Lovy, R. Makundi, V. Mazoch,
   J. Skliba, J. Vrbova Komarkova and all local collaborators. A. Bryjova,
   D. Chovanec and H. Konvikova-Patzenhauerova helped with genotyping. For
   permission to carry out the research and to collect specimens, we are
   obliged to the National Research Council and Forestry Department in
   Malawi, the National Council for Science and Technology, the Kenyan
   Forest Service and the Kenyan Wildlife Service, the Ethiopian Wildlife
   Conservation Authority, Sokoine University in Morogoro, and Zambian
   Wildlife Authority. We would also like to thank the curators of the
   collections, R. Baker (TTU), J. Britton-Davidian (ISEM), J. Chupasko
   (MCZ), C. Conroy (MVZ), G. Csorba (HNHM), N. Duncan (AMNH), P. Jenkins
   (BMNH), T. Kerney (TM), D. Lunde (USNM), C. Mateke (LM), F. Mayer (ZMB),
   D. Moerike (SMNS), V. Nicolas (MNHN), E. Verheyen (RBINS), V. Volpato
   (SMF) and W. Wendelen (RMCA), for providing us with tissue samples and
   allowing us to study the skeletal material in their care. T. Kearney
   (TM), N. Lange (ZMB) and M. Omura (MCZ) contributed by taking images of
   type material. We thank M. McDonough for language correction and
   comments on the earlier version of the manuscript. The paper was also
   significantly improved by comments of M. Carleton, C. Denys and one
   anonymous reviewer.
CR Adams DC, 2013, METHODS ECOL EVOL, V4, P393, DOI 10.1111/2041-210X.12035
   [Anonymous], THESIS
   [Anonymous], BERICHT BEKANNTMACHU
   [Anonymous], P ZOOLOGICAL SOC LON
   [Anonymous], RODENTS SO AFRICA
   [Anonymous], P ZOOLOGICAL SOC LON
   [Anonymous], 2014, HEXAGON BINNING OVER
   [Anonymous], 1986, Lecture of Mathematics for Life Science
   [Anonymous], P ZOOLOGICAL SOC LON
   [Anonymous], ANN MUSEE ROYAL AF 8
   [Anonymous], REISE NACH MOSSAMBIQ
   [Anonymous], B MUSEUM COMP ZOOLOG
   [Anonymous], 2014, Tracer v. 1.6
   [Anonymous], ANN TRANSVAAL MUSEUM
   [Anonymous], SMITHSONIAN MISCELLA
   [Anonymous], B CARNEGIE MUSEUM NA
   [Anonymous], SMITHSONIAN MISCELLA
   [Anonymous], ANN TRANSVAAL MUSEUM
   [Anonymous], ANN MAGAZINE NATURAL
   [Anonymous], SPERICH AUXILIARY FU
   [Anonymous], EARTH PLANETARY SCI
   Arbour JH, 2014, METHODS ECOL EVOL, V5, P16, DOI 10.1111/2041-210X.12128
   Bartáková V, 2015, J BIOGEOGR, V42, P1832, DOI 10.1111/jbi.12567
   BARTON NH, 1979, HEREDITY, V43, P333, DOI 10.1038/hdy.1979.86
   Bastien P, 2005, COMPUT STAT DATA AN, V48, P17, DOI 10.1016/j.csda.2004.02.005
   Bensmail H, 1996, J AM STAT ASSOC, V91, P1743, DOI 10.2307/2291604
   Berger SA, 2011, SYST BIOL, V60, P291, DOI 10.1093/sysbio/syr010
   Bertrand F., 2014, Partial Least Squares Regression for Generalized Linear Models
   Beuning KRM, 2011, PALAEOGEOGR PALAEOCL, V303, P81, DOI 10.1016/j.palaeo.2010.01.025
   Blonder B., 2015, hypervolume: High-dimensional kernel density estimation and geometry operations. R package version 1.4.1
   Blonder B, 2014, GLOBAL ECOL BIOGEOGR, V23, P595, DOI 10.1111/geb.12146
   Bouckaert R, 2014, PLOS COMPUT BIOL, V10, DOI 10.1371/journal.pcbi.1003537
   Braconnot P, 2007, CLIM PAST, V3, P261, DOI 10.5194/cp-3-261-2007
   Bryja J, 2014, BMC EVOL BIOL, V14, DOI 10.1186/s12862-014-0256-2
   Carleton M.D., 1984, P289
   Cohen AS, 2007, P NATL ACAD SCI USA, V104, P16422, DOI 10.1073/pnas.0703873104
   Colangelo P, 2007, MOL PHYLOGENET EVOL, V42, P797, DOI 10.1016/j.ympev.2006.10.001
   Corti M, 2004, J ZOOL, V262, P413, DOI 10.1017/S0952836903004795
   Corti M, 1999, ITAL J ZOOL, V66, P341, DOI 10.1080/11250009909356275
   Corti M, 2005, BELG J ZOOL, V135, P197
   Cotterill F.P.D., 2003, P11
   Demos TC, 2014, MOL PHYLOGENET EVOL, V71, P41, DOI 10.1016/j.ympev.2013.10.014
   DENYS C, 1992, GEOBIOS-LYON, V25, P145, DOI 10.1016/S0016-6995(09)90044-4
   Denys C, 1999, HUMAN EVOLUT SER, P226
   Denys C., 1987, P118
   DENYS C, 1988, MAMMALIA, V52, P497
   Denys C, 2011, VERTEBR PALEOBIOL PA, P15, DOI 10.1007/978-90-481-9962-4_2
   Drummond AJ, 2005, MOL BIOL EVOL, V22, P1185, DOI [10.1093/molbev/msi103, 10.1093/molbev/mss075]
   Dryden I., 1998, Statistical Shape Analysis
   ELLISON GTH, 1993, GLOBAL ECOL BIOGEOGR, V3, P41, DOI 10.2307/2997458
   ELLISON GTH, 1993, ACTA THERIOL, V38, P49, DOI 10.4098/AT.arch.93-4
   Fabre PH, 2012, BMC EVOL BIOL, V12, DOI 10.1186/1471-2148-12-88
   Fadda C, 2001, BIOCHEM SYST ECOL, V29, P585, DOI 10.1016/S0305-1978(00)00087-9
   Faulkes CG, 2004, MOL ECOL, V13, P613, DOI 10.1046/j.1365-294X.2004.02099.x
   Faulkes CG, 2010, BIOL J LINN SOC, V100, P337, DOI 10.1111/j.1095-8312.2010.01418.x
   Fraley C, 2012, TECHNICAL REPORT NO
   Galan M, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0048374
   Galster S, 2007, ONE DEGREE RESOLUTIO
   Geraads Denis, 2001, Palaeovertebrata (Montpellier), V30, P89
   Gernhard T, 2008, J THEOR BIOL, V253, P769, DOI 10.1016/j.jtbi.2008.04.005
   GORDON DH, 1980, S AFR J SCI, V76, P559
   GORDON DH, 1986, S AFR J ZOOL, V21, P95
   HASEGAWA M, 1985, J MOL EVOL, V22, P160, DOI 10.1007/BF02101694
   Hijmans R.J., 2021, GEOGRAPHIC DATA ANAL
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Horn A, 2012, EVOLUTION, V66, P882, DOI 10.1111/j.1558-5646.2011.01478.x
   Jansa SA, 2004, MOL PHYLOGENET EVOL, V31, P256, DOI 10.1016/j.ympev.2003.07.002
   Johnson JB, 2004, TRENDS ECOL EVOL, V19, P101, DOI 10.1016/j.tree.2003.10.013
   KASS RE, 1995, J AM STAT ASSOC, V90, P773, DOI 10.1080/01621459.1995.10476572
   Keesing F, 1998, OECOLOGIA, V116, P381, DOI 10.1007/s004420050601
   Keesing F, 2014, BIOSCIENCE, V64, P487, DOI 10.1093/biosci/biu059
   Keller C, 2010, AM J PHYS ANTHROPOL, V142, P125, DOI 10.1002/ajpa.21209
   Kessing F, 1998, J MAMMAL, V79, P919
   Krämer N, 2011, J AM STAT ASSOC, V106, P697, DOI 10.1198/jasa.2011.tm10107
   KRZANOWSKI WJ, 1987, BIOMETRICS, V43, P575, DOI 10.2307/2531996
   Lecompte É, 2002, CR BIOL, V325, P827, DOI 10.1016/S1631-0691(02)01488-9
   Librado P, 2009, BIOINFORMATICS, V25, P1451, DOI 10.1093/bioinformatics/btp187
   Makundi RH, 2010, AFR J ECOL, V48, P313, DOI 10.1111/j.1365-2028.2009.01109.x
   Maputla NW, 2011, J ZOOL, V285, P180, DOI 10.1111/j.1469-7998.2011.00825.x
   McDonough MM, 2015, MOL ECOL, V24, P5248, DOI 10.1111/mec.13374
   Mein P., 2004, Communications of the Geological Survey of Namibia, V13, P43
   Mein Pierre, 2006, Bulletin Mensuel de la Societe Linneenne de Lyon, V75, P183
   Metz MR, 2001, BIOTROPICA, V33, P182, DOI 10.1111/j.1744-7429.2001.tb00167.x
   Miller G. S., 1910, Smithsonian Institution Miscellaneous Collection, V54
   Montgelard C, 2012, ACTA OECOL, V42, P50, DOI 10.1016/j.actao.2012.02.001
   Moore AE, 2012, S AFR J GEOL, V115, P551, DOI 10.2113/gssajg.115.4.551
   Moore A.E., 2007, Large rivers: Geomorphology and Management, P311
   Musser G.G., 2005, Mammal species of the World. A taxonomic and geographic reference, V2, P894
   Nicolas V, 2009, BIOL J LINN SOC, V98, P29, DOI 10.1111/j.1095-8312.2009.01273.x
   Nychka D, 2015, FIELDS TOOLS SPATIAL
   O'Leary MA., 2012, MORPHOBANK 30 WEB AP
   Oba S, 2003, BIOINFORMATICS, V19, P2088, DOI 10.1093/bioinformatics/btg287
   Otto-Bliesner BL, 2006, SCIENCE, V311, P1751, DOI 10.1126/science.1120808
   Paradis E, 2004, BIOINFORMATICS, V20, P289, DOI [10.1093/bioinformatics/btg412, 10.1093/bioinformatics/bty633]
   Peter BM, 2013, EVOLUTION, V67, P3274, DOI 10.1111/evo.12202
   Piry S, 2012, MOL ECOL RESOUR, V12, P1151, DOI 10.1111/j.1755-0998.2012.03171.x
   Posada D, 1998, BIOINFORMATICS, V14, P817, DOI 10.1093/bioinformatics/14.9.817
   Potts R, 2013, QUATERNARY SCI REV, V73, P1, DOI 10.1016/j.quascirev.2013.04.003
   R Core Team, 2015, R LANG ENV STAT COMP
   Raiche G., 2010, R Package Version, V2
   Raîche G, 2013, METHODOLOGY-EUR, V9, P23, DOI 10.1027/1614-2241/a000051
   Rautenbach I L., 1982, Mammals of the Transvaal
   Reed DN, 2007, VERTEBR PALEOBIOL PA, P217, DOI 10.1007/978-1-4020-3098-7_9
   Roberts A., 1951, MAMMALS S AFRICA
   ROHLF FJ, 1990, SYST ZOOL, V39, P40, DOI 10.2307/2992207
   Ronquist F, 2012, SYST BIOL, V61, P539, DOI 10.1093/sysbio/sys029
   RYAN JM, 1989, J MAMMAL, V70, P267, DOI 10.2307/1381507
   Schenk JJ, 2013, SYST BIOL, V62, P837, DOI 10.1093/sysbio/syt050
   Schwann H, 1906, P ZOOL SOC LOND, V1906, P101
   SCHWARZ G, 1978, ANN STAT, V6, P461, DOI 10.1214/aos/1176344136
   Skinner J., 2005, The Mammals of the Southern African Subregion, P51, DOI DOI 10.1017/CBO9781107340992
   Smithers R.H.N., 1971, MAMMALS BOTSWANA, P1
   Stacklies W, 2007, BIOINFORMATICS, V23, P1164, DOI 10.1093/bioinformatics/btm069
   Stamatakis A, 2014, BIOINFORMATICS, V30, P1312, DOI 10.1093/bioinformatics/btu033
   Stanhope MJ, 1992, MOL PHYLOGENET EVOL, V1, P148, DOI 10.1016/1055-7903(92)90026-D
   Stankiewicz J, 2006, J AFR EARTH SCI, V44, P75, DOI 10.1016/j.jafrearsci.2005.11.008
   Stephens M, 2001, AM J HUM GENET, V68, P978, DOI 10.1086/319501
   Steppan SJ, 2004, SYST BIOL, V53, P533, DOI 10.1080/10635150490468701
   Swynnerton G.H., 1951, Journal of the East Africa Natural History Society, V20, P274
   TAJIMA F, 1989, GENETICS, V123, P585
   Taylor PJ, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0041744
   Teeling EC, 2000, NATURE, V403, P188, DOI 10.1038/35003188
   Terryn L., 2007, African Rodentia
   Trauth MH, 2010, QUATERNARY SCI REV, V29, P2981, DOI 10.1016/j.quascirev.2010.07.007
   Werdelin L., 2010, Cenozoic Mammals of Africa
   Winkens A, 2010, PEDESTRIAN AND EVACUATION DYNAMICS 2008, P263, DOI 10.1007/978-3-642-04504-2_22
   Winkler AJ, 2002, J HUM EVOL, V42, P237, DOI 10.1006/jhev.2001.0501
   Winkler Alisa J., 1997, Topics in Geobiology, V14, P311
NR 128
TC 24
Z9 24
U1 1
U2 29
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0300-3256
EI 1463-6409
J9 ZOOL SCR
JI Zool. Scr.
PD NOV
PY 2016
VL 45
IS 6
BP 595
EP 617
DI 10.1111/zsc.12179
PG 23
WC Evolutionary Biology; Zoology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Evolutionary Biology; Zoology
GA DZ7VI
UT WOS:000386075500003
DA 2025-01-10
ER

PT J
AU Klein, JA
   Hopping, KA
   Yeh, ET
   Nyima, Y
   Boone, RB
   Galvin, KA
AF Klein, Julia A.
   Hopping, Kelly A.
   Yeh, Emily T.
   Nyima, Yonten
   Boone, Randall B.
   Galvin, Kathleen A.
TI Unexpected climate impacts on the Tibetan Plateau: Local and scientific
   knowledge in findings of delayed summer
SO GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
LA English
DT Article
DE Climate change; Local ecological knowledge; Tibetan Plateau; Phenology;
   Pastoralism
ID PASTORALISTS ECOLOGICAL KNOWLEDGE; GREEN-UP DATES; SPRING PHENOLOGY;
   INDIGENOUS KNOWLEDGE; RAINFALL VARIABILITY; ENVIRONMENTAL-CHANGE;
   CONSENSUS ANALYSIS; MENTAL MODELS; TIME-SERIES; SEA-ICE
AB Knowledge of climate change and its impacts can facilitate adaptation efforts. However, complex system dynamics, data scarcity, and heterogeneity often generate both contradictory findings and unexpected climate change impacts. Here we present local ecological knowledge of climate and ecological change in central Tibet to support the finding of delayed summer on the Tibetan Plateau, a finding that has been subject to vigorous, ongoing debate based on Western scientific data. Tibetans who actively herd on a daily basis and are located at higher elevations were most likely to notice changes in seasonality, reported as later start of summer and green-up, and as delayed and shortened livestock milking season. Local meteorological data, indigenous observations of higher snowlines and long-term animal number data suggest that a regional warming trend, rather than land use change, may underlie the delayed phenology trends. We demonstrate that local ecological knowledge can reveal counter-intuitive outcomes and help resolve apparent contradictions through its strengths in situations of high variability, ability to integrate over a range of variables and time scales, and operation outside of Western scientific logic. This suggests local knowledge does not exist to be confirmed or disproved by Western science, but rather can also advance Western science and help contribute to its debates. It is precisely points of apparent contradiction within and between knowledge systems that are most productive for more extensive inquiry. Future research on climate change, and climate adaptation policy-making, will benefit from careful, contextual dialog with local observations, focusing on observable biophysical phenomena that are affected by temperature and precipitation and that are important to livelihoods. (C) 2014 Elsevier Ltd. All rights reserved.
C1 [Klein, Julia A.; Hopping, Kelly A.; Boone, Randall B.] Colorado State Univ, Dept Ecosyst Sci & Sustainabil, Ft Collins, CO 80523 USA.
   [Klein, Julia A.; Hopping, Kelly A.; Boone, Randall B.; Galvin, Kathleen A.] Colorado State Univ, Nat Resource Ecol Lab, Ft Collins, CO 80523 USA.
   [Yeh, Emily T.] Univ Colorado, Dept Geog, Boulder, CO 80309 USA.
   [Nyima, Yonten] Sichuan Univ, Inst Social Dev & Western China Dev Studies, Chengdu 610064, Sichuan, Peoples R China.
   [Galvin, Kathleen A.] Colorado State Univ, Dept Anthropol, Ft Collins, CO 80523 USA.
C3 Colorado State University; Colorado State University; University of
   Colorado System; University of Colorado Boulder; Sichuan University;
   Colorado State University
RP Klein, JA (corresponding author), Colorado State Univ, Dept Ecosyst Sci & Sustainabil, Campus Delivery 1476, Ft Collins, CO 80523 USA.
EM Julia.Klein@colostate.edu; Kelly.Hopping@colostate.edu;
   emily.yeh@colorado.edu; yundanni@colorado.edu;
   Randall.Boone@colostate.edu; Kathleen.Galvin@colostate.edu
RI Hopping, Kelly/LDF-4152-2024; YEH, EMILY/O-7909-2014; Boone,
   Randall/N-6566-2013
OI Hopping, Kelly/0000-0002-0557-0526; YEH, EMILY/0000-0002-4401-2404;
   Nyima, Yonten/0000-0001-9058-8992; Boone, Randall/0000-0003-3362-2976
FU NSF [SBE-0624315]
FX We thank D. Tsering for conducting fieldwork, J. Snodgrass for help with
   CCA, D. Ojima for his assistance, the Tibetans in Nagchu and Amdo for
   their contributions to this project, and three anonymous reviewers for
   their improvements to the manuscript. This work was supported by NSF
   SBE-0624315.
CR Agrawal A, 2002, INT SOC SCI J, V54, P287, DOI 10.1111/1468-2451.00382
   AGRAWAL A, 1995, DEV CHANGE, V26, P413, DOI 10.1111/j.1467-7660.1995.tb00560.x
   Alexander C, 2011, BIOSCIENCE, V61, P477, DOI 10.1525/bio.2011.61.6.10
   [Anonymous], GEOCARTO INT
   [Anonymous], 2021, ALPINE PLANT LIFE FU
   [Anonymous], 2005, J GEOPHYS RES
   [Anonymous], 2002, Ucinet 6 for Windows
   [Anonymous], HIMALAYA
   [Anonymous], RETIRE LIVESTOCK RES
   [Anonymous], 1998, IS SCI MULTICULTURAL
   [Anonymous], HUM ECOL
   [Anonymous], DIVINE DYADS ANCIENT
   [Anonymous], CLIMATE CHANGE 2007
   Arft AM, 1999, ECOL MONOGR, V69, P491, DOI 10.1890/0012-9615(1999)069[0491:ROTPTE]2.0.CO;2
   Atran S, 1999, P NATL ACAD SCI USA, V96, P7598, DOI 10.1073/pnas.96.13.7598
   Berkes F., 1999, Sacred ecology: Traditional ecological knowledge and resource management
   Berkes F, 2007, P NATL ACAD SCI USA, V104, P15188, DOI 10.1073/pnas.0702098104
   Berkes F, 2009, FUTURES, V41, P6, DOI 10.1016/j.futures.2008.07.003
   Bicker Alan., 2000, Indigenous Environmental Knowledge and Its Transformations: Critical Anthropological Perspectives, DOI [DOI 10.4324/9780203479568, 10.4324/9780203479568]
   Bollig M, 1999, HUM ECOL, V27, P493, DOI 10.1023/A:1018783725398
   Breiman L., 1984, Classification and Regression Trees, DOI 10.1201/9781315139470
   Brosius JP, 1997, HUM ECOL, V25, P47, DOI 10.1023/A:1021983819369
   Byg A, 2009, GLOBAL ENVIRON CHANG, V19, P156, DOI 10.1016/j.gloenvcha.2009.01.010
   Chen H, 2011, P NATL ACAD SCI USA, V108, pE93, DOI 10.1073/pnas.1100091108
   Cleland EE, 2007, TRENDS ECOL EVOL, V22, P357, DOI 10.1016/j.tree.2007.04.003
   Cong N, 2013, GLOBAL CHANGE BIOL, V19, P881, DOI 10.1111/gcb.12077
   Cook BI, 2012, P NATL ACAD SCI USA, V109, P9000, DOI 10.1073/pnas.1118364109
   Crona B, 2013, CLIMATIC CHANGE, V119, P519, DOI 10.1007/s10584-013-0708-5
   Dorji T, 2013, GLOBAL CHANGE BIOL, V19, P459, DOI 10.1111/gcb.12059
   Dove MR, 2002, INT SOC SCI J, V54, P349, DOI 10.1111/1468-2451.00387
   Dunne JA, 2003, ECOL MONOGR, V73, P69, DOI 10.1890/0012-9615(2003)073[0069:SMFPRT]2.0.CO;2
   Fernández-Giménez ME, 2012, HUM ECOL, V40, P287, DOI 10.1007/s10745-012-9463-x
   Fernandez-Gimenez ME, 2000, ECOL APPL, V10, P1318, DOI 10.1890/1051-0761(2000)010[1318:TROMNP]2.0.CO;2
   Forkel M, 2013, REMOTE SENS-BASEL, V5, P2113, DOI 10.3390/rs5052113
   Forsyth Tim., 2011, Knowing nature: Conversations at the intersection of political ecology and science studies, P31
   Gearheard S, 2010, CLIMATIC CHANGE, V100, P267, DOI 10.1007/s10584-009-9587-1
   Goldman M, 2007, ENVIRON PLANN D, V25, P307, DOI 10.1068/d0505
   Gupta Akhil., 1998, POSTCOLONIAL DEV
   HARAWAY D, 1988, FEMINIST STUD, V14, P575, DOI 10.2307/3178066
   HIRSCH RM, 1984, WATER RESOUR RES, V20, P727, DOI 10.1029/WR020i006p00727
   Hoogstra MA, 2008, FOREST SCI, V54, P316
   Huber T, 1997, J ROY ANTHROPOL INST, V3, P577, DOI 10.2307/3034768
   Huntington H, 2004, AMBIO, P18
   Ingold Tim., 2000, BODY SOC, V6, P183, DOI DOI 10.1177/1357034X00006003010
   Jones NA, 2011, ECOL SOC, V16
   Jönsson P, 2004, COMPUT GEOSCI-UK, V30, P833, DOI 10.1016/j.cageo.2004.05.006
   Keeling CD, 1996, NATURE, V382, P146, DOI 10.1038/382146a0
   Klein JA, 2011, ADV GLOB CHANGE RES, V42, P423, DOI 10.1007/978-94-007-0567-8_31
   Laborde S, 2012, P NATL ACAD SCI USA, V109, P6441, DOI 10.1073/pnas.1113740109
   Laidler GJ, 2006, CLIMATIC CHANGE, V78, P407, DOI 10.1007/s10584-006-9064-z
   Latour Bruno., 1986, Science in Action: How to Follow Scientists and Engineers Through Society
   Lefale PF, 2010, CLIMATIC CHANGE, V100, P317, DOI 10.1007/s10584-009-9722-z
   Li CY, 2013, ENVIRON MANAGE, V52, P894, DOI 10.1007/s00267-013-0139-0
   Li L, 2010, ARCT ANTARCT ALP RES, V42, P449, DOI 10.1657/1938-4246-42.4.449
   Li TM, 2000, COMP STUD SOC HIST, V42, P149, DOI 10.1017/S0010417500002632
   Li Y, 2005, ERGONOMICS, V48, P234, DOI 10.1080/0014013042000327715
   Liu XD, 2000, INT J CLIMATOL, V20, P1729, DOI 10.1002/1097-0088(20001130)20:14<1729::AID-JOC556>3.0.CO;2-Y
   Lowe Celia., 2006, Wild Profusion: Biodiversity Conservation in an Indonesian Archipelago
   Marin A, 2010, GLOBAL ENVIRON CHANG, V20, P162, DOI 10.1016/j.gloenvcha.2009.10.004
   Menzel A, 2006, GLOBAL CHANGE BIOL, V12, P1969, DOI 10.1111/j.1365-2486.2006.01193.x
   Miller D.J., 1999, Rangelands, V21, P16, DOI DOI 10.2307/4001503
   Miller D.J., 2000, Nomadic Peoples, V4, P83, DOI DOI 10.3167/082279400782310674
   Miller ML, 2004, CROSS-CULT RES, V38, P289, DOI 10.1177/1069397104264278
   Naess LO, 2013, WIRES CLIM CHANGE, V4, P99, DOI 10.1002/wcc.204
   Nichols T, 2004, ARCTIC, V57, P68
   Nogués-Bravo D, 2007, GLOBAL ENVIRON CHANG, V17, P420, DOI 10.1016/j.gloenvcha.2006.11.007
   Ostrom E, 2007, P NATL ACAD SCI USA, V104, P15176, DOI 10.1073/pnas.0701886104
   Ovuka M, 2000, GEOGR ANN A, V82A, P107, DOI 10.1111/j.0435-3676.2000.00116.x
   Piao SL, 2011, AGR FOREST METEOROL, V151, P1599, DOI 10.1016/j.agrformet.2011.06.016
   Raffles H, 2002, INT SOC SCI J, V54, P325, DOI 10.1111/1468-2451.00385
   RAM J, 1988, ARCTIC ALPINE RES, V20, P325, DOI 10.2307/1551264
   [Reid Walter. Institute World Resources and Millennium Ecosystem Assessment Institute World Resources and Millennium Ecosystem Assessment], 2006, BRIDGING SCALES KNOW, V2
   ROMNEY AK, 1986, AM ANTHROPOL, V88, P313, DOI 10.1525/aa.1986.88.2.02a00020
   Root TL, 2003, NATURE, V421, P57, DOI 10.1038/nature01333
   Rosenzweig C, 2008, NATURE, V453, P353, DOI 10.1038/nature06937
   Rosner B., 2011, Fundamentals of Biostatistics, V7th
   Ruelle ML, 2011, ECON BOT, V65, P295, DOI 10.1007/s12231-011-9168-x
   Salick J, 2012, J STUD RELIG NAT CUL, V6, P447, DOI 10.1558/jsrnc.v6i4.447
   Schaller G.B., 1998, Wildlife of the Tibetan steppe
   Seidl R, 2013, J ENVIRON MANAGE, V114, P461, DOI 10.1016/j.jenvman.2012.09.028
   Shen MG, 2013, P NATL ACAD SCI USA, V110, pE2329, DOI 10.1073/pnas.1304625110
   Shen MG, 2011, AGR FOREST METEOROL, V151, P1711, DOI 10.1016/j.agrformet.2011.07.003
   Shen MG, 2011, P NATL ACAD SCI USA, V108, pE91, DOI 10.1073/pnas.1018390108
   SOLLOD AE, 1990, HUM ECOL, V18, P267, DOI 10.1007/BF00889156
   Starn O., 2007, INDIGENOUS EXPERIENC
   Stone-Jovicich SS, 2011, ECOL SOC, V16
   Strauss Sarah., 2003, WEATHER CLIMATE CULT
   Turnbull D., 2000, Masons, Tricksters, and Cartographers
   Walker MD, 1999, HYDROL PROCESS, V13, P2315, DOI 10.1002/(SICI)1099-1085(199910)13:14/15<2315::AID-HYP888>3.0.CO;2-A
   Wang T, 2013, P NATL ACAD SCI USA, V110, pE2854, DOI 10.1073/pnas.1306157110
   Weatherhead E, 2010, GLOBAL ENVIRON CHANG, V20, P523, DOI 10.1016/j.gloenvcha.2010.02.002
   Weller SC, 2007, FIELD METHOD, V19, P339, DOI 10.1177/1525822X07303502
   West ColinThor., 2003, WEATHER CLIMATE CULT
   Wolkovich EM, 2012, NATURE, V485, P494, DOI 10.1038/nature11014
   Wu XC, 2013, GLOBAL CHANGE BIOL, V19, P870, DOI 10.1111/gcb.12086
   Xu JC, 2009, CONSERV BIOL, V23, P520, DOI 10.1111/j.1523-1739.2009.01237.x
   Yan ZL, 2005, NOMAD PEOPLES, V9, P31, DOI 10.3167/082279405781826155
   Yeh ET, 2013, SOC CULT GEOGR, V14, P318, DOI 10.1080/14649365.2013.765025
   Yeh ET, 2011, AREA, V43, P165, DOI 10.1111/j.1475-4762.2010.00976.x
   Yi SH, 2011, P NATL ACAD SCI USA, V108, pE94, DOI 10.1073/pnas.1100394108
   Yu HY, 2010, P NATL ACAD SCI USA, V107, P22151, DOI 10.1073/pnas.1012490107
   Zhang GL, 2013, P NATL ACAD SCI USA, V110, P4309, DOI 10.1073/pnas.1210423110
NR 102
TC 101
Z9 114
U1 1
U2 106
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 SEP
PY 2014
VL 28
BP 141
EP 152
DI 10.1016/j.gloenvcha.2014.03.007
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 AR8QG
UT WOS:000343839100013
DA 2025-01-10
ER

PT J
AU Kankare, M
   Salminen, TS
   Lampinen, H
   Hoikkala, A
AF Kankare, Maaria
   Salminen, Tiina S.
   Lampinen, Hanna
   Hoikkala, Anneli
TI Sequence variation in <i>couch potato</i> and its effects on
   life-history traits in a northern malt fly, <i>Drosophila montana</i>
SO JOURNAL OF INSECT PHYSIOLOGY
LA English
DT Article
DE Couch potato; Development time; Photoperiod; Reproductive diapause
ID MOSQUITO CULEX-PIPIENS; REPRODUCTIVE DIAPAUSE; CLIMATIC ADAPTATION;
   GENE-EXPRESSION; MELANOGASTER; PROTEINS; POLYMORPHISM; FAMILY
AB Couch potato (cpo) has previously been connected to reproductive diapause in several insect species including Drosophila melanogaster, where it has been suggested to provide a link between the insulin signalling pathway and the hormonal control of diapause. In the first part of the study we sequenced nearly 3.6 kb of this gene in a northern Drosophila species (Drosophila montana) with a robust photoperiodically determined diapause and found several types of polymorphisms along the sequenced area. We also found variation among five Drosophila virilis group species in the length of the 5th exon of cpo and in the site of the stop codon at the end of this exon. The second part of the study was targeted on a deletion of six amino acids located in the last section of exon 5, which in D. melanogaster, is translated only in one short transcript lacking the following exons. The studied deletion appeared to be extremely rare in the wild D. montana population where it was found, but its frequency rapidly increased during laboratory culture. qPCR analyses showed the expression level of the deletion allele to be significantly downregulated in both the diapausing and non-diapausing females compared to the wild type allele. At the phenotypic level, the deletion and the decreased expression of cpo transcript involving it did not have direct effect on the incidence of female reproductive diapause, but it was associated with a reduction in development time under diapause-inducing conditions. This suggests that while the cpo transcript containing the prolonged version of the 5th exon with a stop codon is clearly associated with fly development time, the exons with RNA domains included in other transcripts of the gene may be more directly related to diapause regulation. (C) 2011 Elsevier Ltd. All rights reserved.
C1 [Kankare, Maaria; Salminen, Tiina S.; Lampinen, Hanna; Hoikkala, Anneli] Univ Jyvaskyla, Ctr Excellence Evolutionary Res, Dept Biol & Environm Sci, Jyvaskyla 40014, Finland.
C3 University of Jyvaskyla
RP Kankare, M (corresponding author), Univ Jyvaskyla, Ctr Excellence Evolutionary Res, Dept Biol & Environm Sci, POB 35, Jyvaskyla 40014, Finland.
EM maaria.kankare@jyu.fi
OI Salminen, Tiina Susanna/0000-0002-7232-0754; Hoikkala,
   Anneli/0000-0001-5407-7992; Kankare, Maaria/0000-0003-1541-9050
FU Finnish Centre of Excellence in Evolutionary Research; Finnish Academy
   [40014]; Finnish Cultural Foundation
FX We thank several colleagues and two anonymous referees for very useful
   discussions and suggestions. We would also like to thank Jaana Haka for
   most of the sequencing work, Ville Hoikkala for preparing Figs. 5 and 6
   and Laura Vesala for Fig. 7, Pekka Lankinen for providing the isofemale
   lines for D. lummei and Jackson Jennings for revising the language. The
   work has been supported by The Finnish Centre of Excellence in
   Evolutionary Research, by the Finnish Academy (project 40014) to Anneli
   Hoikkala and by the Finnish Cultural Foundation to Tiina Salminen.
CR [Anonymous], 1969, Drosoph. Inf. Serv
   Baker DA, 2009, BMC GENOMICS, V10, DOI 10.1186/1471-2164-10-242
   BELLEN HJ, 1992, GENE DEV, V6, P2125, DOI 10.1101/gad.6.11.2125
   BELLEN HJ, 1992, GENETICS, V131, P365
   Denlinger DL, 2002, ANNU REV ENTOMOL, V47, P93, DOI 10.1146/annurev.ento.47.091201.145137
   DeVries A. L., 1969, SCIENCE, V163, P1074
   Duman JG, 2004, J INSECT PHYSIOL, V50, P259, DOI 10.1016/j.jinsphys.2003.12.003
   Emerson KJ, 2009, TRENDS GENET, V25, P217, DOI 10.1016/j.tig.2009.03.009
   Fielenbach N, 2008, GENE DEV, V22, P2149, DOI 10.1101/gad.1701508
   Glasscock E, 2005, GENETICS, V169, P2137, DOI 10.1534/genetics.104.028357
   GLOOR G., 1992, DIS, V71, P148
   HALL JC, 1994, SCIENCE, V264, P1702, DOI 10.1126/science.8209251
   Harvie PD, 1998, GENETICS, V149, P217
   Ikeno T, 2010, BMC BIOL, V8, DOI 10.1186/1741-7007-8-116
   Kandul NP, 2009, BMC GENET, V10, DOI 10.1186/1471-2156-10-67
   Kankare Maaria, 2010, BMC Ecology, V10, P3, DOI 10.1186/1472-6785-10-3
   LANKINEN P, 1993, HEREDITY, V71, P210, DOI 10.1038/hdy.1993.126
   Lee SF, 2011, MOL ECOL, V20, P2973, DOI 10.1111/j.1365-294X.2011.05155.x
   Lumme J., 1978, EVOLUTION INSECTS MI
   NYLIN S, 1989, ECOL ENTOMOL, V14, P209, DOI 10.1111/j.1365-2311.1989.tb00771.x
   Ragland GJ, 2010, P NATL ACAD SCI USA, V107, P14909, DOI 10.1073/pnas.1007075107
   Schmidt PS, 2008, P NATL ACAD SCI USA, V105, P16207, DOI 10.1073/pnas.0805485105
   Schmidt PS, 2005, EVOLUTION, V59, P1721, DOI 10.1111/j.0014-3820.2005.tb01821.x
   Shimamoto A, 1996, P NATL ACAD SCI USA, V93, P10913, DOI 10.1073/pnas.93.20.10913
   Sim C, 2008, P NATL ACAD SCI USA, V105, P6777, DOI 10.1073/pnas.0802067105
   Tauber E, 2007, SCIENCE, V316, P1895, DOI 10.1126/science.1138412
   Teets N. M., 2008, AM J PHYSIOL-REG I, V294, P6
   Tyukmaeva VI, 2011, ECOL EVOL, V1, P160, DOI 10.1002/ece3.14
   Vesala L, 2012, INSECT MOL BIOL, V21, P107, DOI 10.1111/j.1365-2583.2011.01119.x
   WATABE H-A, 1983, Kontyu, V51, P628
   WHARTON KA, 1985, CELL, V40, P55, DOI 10.1016/0092-8674(85)90308-3
   Williams KD, 2006, P NATL ACAD SCI USA, V103, P15911, DOI 10.1073/pnas.0604592103
   Zhang QR, 2011, J INSECT PHYSIOL, V57, P620, DOI 10.1016/j.jinsphys.2011.02.003
NR 33
TC 4
Z9 4
U1 0
U2 14
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0022-1910
J9 J INSECT PHYSIOL
JI J. Insect Physiol.
PD FEB
PY 2012
VL 58
IS 2
BP 256
EP 264
DI 10.1016/j.jinsphys.2011.11.016
PG 9
WC Entomology; Physiology; Zoology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Entomology; Physiology; Zoology
GA 912VK
UT WOS:000301829300006
PM 22138635
DA 2025-01-10
ER

PT C
AU Tahir, MM
   Usman, IMS
   Che-Ani, AI
   Surat, M
   Abdullah, NAG
   Nor, MFIM
AF Tahir, M. M.
   Usman, I. M. S.
   Che-Ani, A. I.
   Surat, M.
   Abdullah, N. A. G.
   Nor, M. F. I. Md.
BE Mastorakis, N
   Helmis, C
   Papageorgiou, CD
   Bulucea, CA
   Panagopoulos, T
TI Reinventing the Traditional Malay Architecture: Creating a Socially
   Sustainable and Responsive Community in Malaysia through the
   Introduction of the Raised Floor Innovation (Part1)
SO ENERGY, ENVIRONMENT, ECOSYSTEMS, DEVELOPMENT AND LANDSCAPE ARCHITECTURE
SE Energy and Environmental Engineering Series
LA English
DT Proceedings Paper
CT 5th International Conference on Energy, Environment, Ecosystems and
   Sustainable Development/2nd International Conference on Landscape
   Architecture
CY SEP 28-30, 2009
CL Vouliagmeni, GREECE
DE sustainable; ultra low energy; terrace housing; tropics; traditional
   Malay house; raised floor
AB The traditional Malay house embodies the form of traditional Malay living. In the Malay's haste for Western-type progress and modernity, many of its virtues have been abandoned. The traditional Malay house has evolved and adapted to the Malay needs, culture and environment. It may not be grandiose like some modern-day homes, but upon closer inspection, reveals sublime architectural qualities that express the way of life, culture and ingenious climatic adaptation of its users. The traditional Malay house has been designed to suit the local climatic requirements using various ventilation and solar control devices, and low thermal capacity building materials. The most literally ignored aspects of the traditional Malay house is the fact that the building is constructed on stilts. The traditional raised floor design involves issues such as ventilation, lighting, thermal comfort, safety and security as well as social aspects. This research dissects the superior qualities of the traditional Malay house and reveals why it is an unrivalled type of dwelling for inhabitants of the tropical climate. In particular, it intends to show how building on stilts is a fundamental aspect of sustainability. In Malaysia especially, the introduction of the stilt component could create a more integrated and responsive social culture long lost and yearned for. Therefore, this research intends to explore the sustainable aspects of our traditional architecture in creating a uniquely new design for in-house habitation as well as providing for an aesthetically pleasing look. Comparison has been made to the ubiquitous terrace housing community in Malaysia. It suggests a possible and promising way of increasing the livability of terrace housing with a sustainable approach and with the incorporation of the raised floor innovation.
C1 [Tahir, M. M.; Usman, I. M. S.; Che-Ani, A. I.; Surat, M.; Abdullah, N. A. G.; Nor, M. F. I. Md.] Univ Kebangsaan Malaysia, Dept Architecture, Fac Engn, Bangi, Malaysia.
C3 Universiti Kebangsaan Malaysia
RP Tahir, MM (corresponding author), Univ Kebangsaan Malaysia, Dept Architecture, Fac Engn, Bangi, Malaysia.
EM ismar@vlsi.eng.ukm.my
RI Che-Ani, Adi/H-5350-2011
CR ALI KM, 1983, THESIS U YORK
   Aziz Deraman A, 2000, TAMADUN MELAYU PEMBI
   Gibbs P., 1987, Building a Malay house
   HANAFI Z, 1999, REKABENTUK BANGUNAN
   IBRAHIM Y, 1995, PEMBANDARAN KEJIRANA
   Powell Robert., 1993, The Asian House: Contemporary Housesof Southeast Asia
   RASDI MTM, 2005, HOUSING ARCHITECTURA
   RASDI MTM, 2003, HOUSING CRISIS MALAY
   TAYLOR BB, 1987, MIMAR HOUSES CONCEPT
   WATERSON R, 1989, LIVING HOUSE
   YUAN LJ, 1981, MALAY HOUSE REDISCOV
   [No title captured]
NR 12
TC 0
Z9 0
U1 0
U2 10
PU WORLD SCIENTIFIC AND ENGINEERING ACAD AND SOC
PI ATHENS
PA AG LOANNOU THEOLOGOU 17-23, 15773 ZOGRAPHOU, ATHENS, GREECE
BN 978-960-474-125-0
J9 ENERGY ENVIRON ENG S
PY 2009
BP 278
EP +
PG 3
WC Energy & Fuels; Engineering, Environmental; Environmental Sciences
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Energy & Fuels; Engineering; Environmental Sciences & Ecology
GA BOI18
UT WOS:000276696400044
DA 2025-01-10
ER

PT J
AU Hua, HH
   Nguyen, MA
   Ngo, TTT
AF Hua, Hieu Hong
   Nguyen, Minh Anh
   Ngo, Thuy Thanh Thi
TI Collective and individual adaptation of rice farmers to climatic
   variability in the Vietnamese Mekong Delta
SO COGENT SOCIAL SCIENCES
LA English
DT Article
DE Adaptation; climatic variability; collective action; community
   governance; livelihoods; social capital
ID ADAPTIVE CAPACITY; DETERMINANTS; LIVELIHOODS; MANAGEMENT; IMPACT; FLOOD
AB This study delves into the intricate challenges posed by climate variability for rice farmers in the Vietnamese Mekong Delta. It systematically explores the patterns of climate variability and their profound impacts on rice production across diverse areas within the delta. Through an examination of both collective and individual responses to these challenges, the study identifies local rice adaptation strategies. Data collection methods include focus group discussions and semi-structured interviews. The findings unveil notable regional disparities, with farmers in Can Tho and Bac Lieu facing more severe impacts of climate variability during different rice crops compared to those in An Giang province. Can Tho farmers navigate floods and sudden cold, while their counterparts in Bac Lieu contend with risks associated with saline intrusion due to water shortages in the Mekong River and compromised sluice gates. Bac Lieu's farmers face additional constraints, such as compromised harvests due to heavy rain, resulting in lower quality and prices. This study underscores the importance of collective actions, such as water drainage in Can Tho and freshwater storage in Bac Lieu, in mitigating climate variability. Unfortunately, local innovations in collective action have been constrained by disagreements and conflicts among different stakeholder groups. In light of this, the implications suggest that climate variability in the Mekong has become increasingly complex in recent years, particularly with issues like saline intrusion and drought. Collective adaptation through government intervention at various levels remains a viable strategy to encourage different communities of rice producers to adapt to climate variability.
C1 [Hua, Hieu Hong; Nguyen, Minh Anh; Ngo, Thuy Thanh Thi] Can tho Univ, Dept Sociol, Can Tho, Vietnam.
C3 Can Tho University
RP Hua, HH (corresponding author), Can tho Univ, Dept Sociol, Can Tho, Vietnam.
EM hhhieu@ctu.edu.vn
OI Nguyen Anh, Minh/0009-0003-3501-6598
FU Australian Centre for International Agricultural Research; Australian
   Centre for International Agricultural Research; Can Tho and Bac Lieu
FX The authors express their sincere gratitude to the Australian Centre for
   International Agricultural Research for providing the John Allwright
   Fellowship for our research endeavors. We extend our appreciation to the
   farmers, local authorities, rice brokers and owners of the combine
   harvesters in the provinces of An Giang, Can Tho and Bac Lieu. Their
   cooperation and generosity in allowing us to conduct data collection in
   their respective local areas have been invaluable to the success of our
   study.
CR Adedapo A., 2017, RUHUNA J SCI, V8, P44, DOI [https://doi.org/10.4038/rjs.v8i1.25, DOI 10.4038/rjs.v8i1.25]
   Adger WN, 2003, ECON GEOGR, V79, P387
   Adger WN, 1999, WORLD DEV, V27, P249, DOI 10.1016/S0305-750X(98)00136-3
   Ajetomobi J., 2011, Tropical and Subtropical Agroecosystems, V14, P613
   Ankrah DA, 2023, COGENT FOOD AGR, V9, DOI 10.1080/23311932.2022.2148323
   [Anonymous], 2007, Climate change 2007: The physical science basis, summary for policymakers
   Anyoha N. O., 2013, Net Journal of Agricultural Science, V1, P42
   Baudoin MA, 2014, CLIM DEV, V6, P122, DOI 10.1080/17565529.2013.844677
   Biggs EM, 2013, CLIM DEV, V5, P165, DOI 10.1080/17565529.2013.789791
   Binh N.T., 2015, Vulnerability and Adaptation to Salinity Intrusion in the Mekong Delta of Vietnam
   Bowles S, 2002, ECON J, V112, pF419, DOI 10.1111/1468-0297.00077
   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
   Can N. D., 2010, Tropical deltas and coastal zones: Food production, communities and environment at the land and water interface, P307, DOI 10.1079/9781845936181.0307
   Can NguyenDuy., 2007, Challenges to Sustainable Development in the Mekong Delta: Regional and National Policy Issues and Research Needs, P69
   Chosokabe M, 2015, LECT NOTES BUS INF P, V218, P3, DOI 10.1007/978-3-319-19515-5_1
   Climate Change Coordination Office, 2015, K hoch hnh ng ng ph bin i kh hu giai on 2015-2030 Action plan for response to climate change 20152030
   Deressa TT, 2011, J AGR SCI-CAMBRIDGE, V149, P23, DOI 10.1017/S0021859610000687
   Tran DD, 2020, WATER-SUI, V12, DOI 10.3390/w12113282
   Ellis F, 2000, J AGR ECON, V51, P289, DOI 10.1111/j.1477-9552.2000.tb01229.x
   Grimm AM, 2011, STOCH ENV RES RISK A, V25, P537, DOI 10.1007/s00477-010-0420-1
   Hadgu G., 2014, RES J AGR ENV SCI, V1, P15
   Dang HL, 2014, ENVIRON MANAGE, V54, P331, DOI 10.1007/s00267-014-0299-6
   Hoanh C. T., 2003, Water Policy, V5, P475
   Hossain PR, 2021, FRONT SUSTAIN FOOD S, V5, DOI 10.3389/fsufs.2021.677069
   Hua H. H., 2018, Farmers decision-making in relation to rice-based farming systems in the Vietnamese Mekong Delta
   Huu P. C., 2011, Pedobiologia, V54, P217
   Kalinga A. S., 2022, J. Geogr. Assoc. Tanzania, V41, P1, DOI [10.56279/jgat.v41i2.191, DOI 10.56279/JGAT.V41I2.191]
   Le Coq Jean-Francois., 2005, Japanese Journal of Southeast Asian Studies, V42, P519
   Lovell C.D., 2002, New Directions for Community Colleges, V117, P91, DOI https://doi.org/10.1002/cc.56
   McKinlay P., 2016, Policy Quarterly, V12, DOI [https://doi.org/10.26686/pq.v12i4.4627, DOI 10.26686/PQ.V12I4.4627]
   Modarresi M., 2015, Research Journal of Environmental Sciences, V9, P296
   Mulyasari Gita, 2022, IOP Conference Series: Earth and Environmental Science, V1016, DOI 10.1088/1755-1315/1016/1/012020
   Newton MJ, 2020, ECOL SOC, V25, DOI 10.5751/ES-11304-250102
   Nguyen KV, 2013, ECOL SOC, V18, DOI 10.5751/ES-05427-180313
   Nguyen-Trung K, 2020, VULNERABILITY IN A MOBILE WORLD, P71, DOI 10.1108/978-1-78756-911-920191007
   Ofuoku A. U., 2011, Agricultura - Revista de Știința și Practica Agricola, V79-80, P129
   Scoones I., 1998, Working Paper - Institute of Development Studies, University of Sussex
   Scoones I, 2009, J PEASANT STUD, V36, P171, DOI 10.1080/03066150902820503
   Smit B, 2006, GLOBAL ENVIRON CHANG, V16, P282, DOI 10.1016/j.gloenvcha.2006.03.008
   Thoai TQ, 2018, LAND USE POLICY, V70, P224, DOI 10.1016/j.landusepol.2017.10.023
   Tran TA, 2019, AGR WATER MANAGE, V216, P89, DOI 10.1016/j.agwat.2019.01.020
   Tran TA, 2019, INT J WATER RESOUR D, V35, P326, DOI 10.1080/07900627.2018.1437713
   Trana TA, 2018, LEARN CULT SOC INTER, V16, P31, DOI 10.1016/j.lcsi.2017.11.002
   Tran DD, 2022, ENVIRON TECHNOL INNO, V28, DOI 10.1016/j.eti.2022.102834
   Tuong TP, 2003, PADDY WATER ENVIRON, V1, P65, DOI 10.1007/s10333-003-0015-2
   Williams LJ, 2016, CLIM DEV, V8, P423, DOI 10.1080/17565529.2015.1085362
   Yamba S, 2019, COGENT SOC SCI, V5, DOI 10.1080/23311886.2019.1646626
NR 48
TC 1
Z9 1
U1 1
U2 1
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 2331-1886
J9 COGENT SOC SCI
JI Cogent Soc. Sci.
PD DEC 31
PY 2024
VL 10
IS 1
AR 2390181
DI 10.1080/23311886.2024.2390181
PG 25
WC Social Sciences, Interdisciplinary
WE Emerging Sources Citation Index (ESCI)
SC Social Sciences - Other Topics
GA D5W3V
UT WOS:001296877800001
OA gold
DA 2025-01-10
ER

PT J
AU Hague, MTJ
   Shropshire, JD
   Caldwell, CN
   Statz, JP
   Stanek, KA
   Conner, WR
   Cooper, BS
AF Hague, Michael T. J.
   Shropshire, J. Dylan
   Caldwell, Chelsey N.
   Statz, John P.
   Stanek, Kimberly A.
   Conner, William R.
   Cooper, Brandon S.
TI Temperature effects on cellular host-microbe interactions explain
   continent-wide endosymbiont prevalence
SO CURRENT BIOLOGY
LA English
DT Article
ID CYTOPLASMIC INCOMPATIBILITY; DROSOPHILA-MELANOGASTER; WOLBACHIA
   INFECTION; GEOGRAPHIC-VARIATION; STABLE INTRODUCTION; HORIZONTAL
   TRANSFER; EVOLUTION; POPULATIONS; SYMBIONTS; LIFE
AB Endosymbioses influence host physiology, reproduction, and fitness, but these relationships require efficient microbe transmission between host generations to persist. Maternally transmitted Wolbachia are the most common known endosymbionts,(1) but their frequencies vary widely within and among host populations for unknown reasons.(2,3) Here, we integrate genomic, cellular, and phenotypic analyses with mathematical models to provide an unexpectedly simple explanation for global wMel Wolbachia prevalence in Drosophila melanogaster Cooling temperatures decrease wMel cellular abundance at a key stage of host oogenesis, producing temperature-dependent variation in maternal transmission that plausibly explains latitudinal clines of wMel frequencies on multiple continents, wMel sampled from a temperate climate targets the germline more efficiently in the cold than a recently differentiated tropical variant (similar to 2,200 years ago), indicative of rapid wMel adaptation to climate. Genomic analyses identify a very narrow list of wMel alleles-most notably, a derived stop codon in the major Wolbachia surface protein WspB-that underlie thermal sensitivity of cellular Wolbachia abundance and covary with temperature globally. Decoupling temperate wMel and host genomes further reduces transmission in the cold, a pattern that is characteristic of host-microbe co-adaptation to a temperate climate. Complex interactions among Wolbachia, hosts, and the environment (GxGxE) mediate wMel cellular abundance and maternal transmission, implicating temperature as a key determinant of Wolbachia spread and equilibrium frequencies, in conjunction with Wolbachia effects on host fitness and reproduction,(4,6) Our results motivate the strategic use of locally selected wMel variants for Wolbachia-based biocontrol efforts, which protect millions of individuals from arboviruses that cause human disease.(6)
C1 [Hague, Michael T. J.; Shropshire, J. Dylan; Caldwell, Chelsey N.; Statz, John P.; Conner, William R.; Cooper, Brandon S.] Univ Montana, Div Biol Sci, 32 Campus Dr, Missoula, MT 59812 USA.
   [Stanek, Kimberly A.] Univ Montana, Dept Chem & Biochem, 32 Campus Dr, Missoula, MT 59812 USA.
C3 University of Montana System; University of Montana; University of
   Montana System; University of Montana
RP Hague, MTJ; Cooper, BS (corresponding author), Univ Montana, Div Biol Sci, 32 Campus Dr, Missoula, MT 59812 USA.
EM michael.hague@mso.umt.edu; brandon.cooper@umontana.edu
RI Shropshire, Dylan/HLW-2408-2023
OI Caldwell, Chelsey/0000-0001-9841-7848; Shropshire,
   Dylan/0000-0003-4221-2178; Hague, Michael/0000-0003-0641-2420; Statz,
   John/0000-0002-1592-4455
FU National Institutes of Health [R35GM124701]; National Institute of
   General Medical Sciences [R35GM124701] Funding Source: NIH RePORTER
FX We especially thank M. Turelli, W. Sullivan, and J. McCutcheon for very
   useful discussions. K. Van Vaerenberghe provided valuable feedback that
   improved the manuscript. We also thank T. Wheeler for laboratory
   assistance and D. Begun for sharing flies. We thank the Center for
   Biomolecular Structure and Dynamics, the Environmental Control for
   Organismal Research facility, and the Genomics Core at the University of
   Montana. The study was funded by National Institutes of Health grant no.
   R35GM124701 (to B.S.C.).
CR Adame MF, 2021, BIOL LETTERS, V17, DOI 10.1098/rsbl.2021.0052
   Anbutsu H, 2008, APPL ENVIRON MICROB, V74, P6053, DOI 10.1128/AEM.01503-08
   ANDERSON RM, 1982, PARASITOLOGY, V85, P411, DOI 10.1017/S0031182000055360
   Armenteros JJA, 2019, NAT BIOTECHNOL, V37, P420, DOI 10.1038/s41587-019-0036-z
   Baldridge GD, 2016, ARCH MICROBIOL, V198, P53, DOI 10.1007/s00203-015-1154-8
   Bates D, 2015, J STAT SOFTW, V67, P1, DOI 10.18637/jss.v067.i01
   Beckmann JF, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2113271118
   Bergland AO, 2014, PLOS GENET, V10, DOI 10.1371/journal.pgen.1004775
   Blanquart F, 2013, ECOL LETT, V16, P1195, DOI 10.1111/ele.12150
   Bordenstein SR, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0029106
   Brownlie JC, 2009, PLOS PATHOG, V5, DOI 10.1371/journal.ppat.1000368
   Buffalo V, 2020, P NATL ACAD SCI USA, V117, P20672, DOI 10.1073/pnas.1919039117
   BULL JJ, 1991, J THEOR BIOL, V149, P63, DOI 10.1016/S0022-5193(05)80072-4
   Bushnell B, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0185056
   Canty C., 2017, boot: Bootstrap R (S-Plus) functions
   Carrington LB, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0022565
   Cattel J, 2016, INSECT MOL BIOL, V25, P595, DOI 10.1111/imb.12245
   Christensen S, 2019, BMC MICROBIOL, V19, DOI 10.1186/s12866-019-1579-3
   Christie PJ, 2014, BBA-MOL CELL RES, V1843, P1578, DOI 10.1016/j.bbamcr.2013.12.019
   Clancy DJ, 1998, ENTOMOL EXP APPL, V86, P13, DOI 10.1023/A:1003043814761
   Conner WR, 2017, ECOL EVOL, V7, P9391, DOI 10.1002/ece3.3449
   Cooper BS, 2019, GENETICS, V212, P1399, DOI 10.1534/genetics.119.302349
   Cooper BS, 2017, GENETICS, V205, P333, DOI 10.1534/genetics.116.196238
   Corbin C, 2017, HEREDITY, V118, P10, DOI 10.1038/hdy.2016.71
   CORREIA JJ, 1983, ANNU REV BIOPHYS BIO, V12, P211, DOI 10.1146/annurev.bb.12.060183.001235
   Early AM, 2013, MOL ECOL, V22, P5765, DOI 10.1111/mec.12530
   Emerson KJ, 2009, TRENDS GENET, V25, P217, DOI 10.1016/j.tig.2009.03.009
   ESRI, 2011, ArcGIS Desktop: Release 10
   Ferree PM, 2005, PLOS PATHOG, V1, P111, DOI 10.1371/journal.ppat.0010014
   Ferri E, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0020843
   Fisher RM, 2017, NAT COMMUN, V8, DOI 10.1038/ncomms15973
   Fox DA, 2014, J AM CHEM SOC, V136, P9938, DOI 10.1021/ja503093y
   Frank SA, 1997, AM NAT, V150, pS80, DOI 10.1086/286051
   Funkhouser-Jones LJ, 2018, CURR BIOL, V28, P1692, DOI 10.1016/j.cub.2018.04.010
   Gabler Felix, 2020, Curr Protoc Bioinformatics, V72, pe108, DOI 10.1002/cpbi.108
   Gerth M, 2017, NAT MICROBIOL, V2, DOI 10.1038/nmicrobiol.2016.241
   Gong JT, 2020, CURR BIOL, V30, P4837, DOI 10.1016/j.cub.2020.09.033
   Hadfield SJ, 1999, NATURE, V402, P482, DOI 10.1038/45002
   Hague MTJ, 2020, MBIO, V11, DOI 10.1128/mBio.01768-20
   Hague MTJ, 2020, GENETICS, V215, P1117, DOI 10.1534/genetics.120.303330
   Hedges LM, 2008, SCIENCE, V322, P702, DOI 10.1126/science.1162418
   Herre EA, 1999, TRENDS ECOL EVOL, V14, P49, DOI 10.1016/S0169-5347(98)01529-8
   Hoffmann AA, 2011, NATURE, V476, P454, DOI 10.1038/nature10356
   HOFFMANN AA, 1986, EVOLUTION, V40, P692, DOI 10.1111/j.1558-5646.1986.tb00531.x
   Hoffmann AA, 1998, GENETICS, V148, P221
   HOFFMANN AA, 1990, GENETICS, V126, P933
   Hoffmann AA, 1997, INFLUENTIAL PASSENGERS, P42
   Höhna S, 2016, SYST BIOL, V65, P726, DOI 10.1093/sysbio/syw021
   Horst JP, 1999, TRENDS MICROBIOL, V7, P29, DOI 10.1016/S0966-842X(98)01424-3
   Ilinsky Y, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0054373
   Ishmael N, 2009, MICROBIOL-SGM, V155, P2211, DOI 10.1099/mic.0.027581-0
   Kapun M., 2021, MOL BIOL EVOL
   Kapun M, 2020, MOL BIOL EVOL, V37, P2661, DOI 10.1093/molbev/msaa120
   Kawecki TJ, 2004, ECOL LETT, V7, P1225, DOI 10.1111/j.1461-0248.2004.00684.x
   Kofler R, 2011, BIOINFORMATICS, V27, P3435, DOI 10.1093/bioinformatics/btr589
   Kohl M., 2020, MKpower: Power analysis and sample size calculation. R package version 0.5
   Kriesner P, 2018, EVOLUTION, V72, P1475, DOI 10.1111/evo.13506
   Kriesner P, 2016, EVOLUTION, V70, P979, DOI 10.1111/evo.12923
   Kriesner P, 2013, PLOS PATHOG, V9, DOI 10.1371/journal.ppat.1003607
   Lau MJ, 2021, PLOS NEGLECT TROP D, V15, DOI 10.1371/journal.pntd.0009179
   Lau MJ, 2020, J MED ENTOMOL, V57, P1567, DOI 10.1093/jme/tjaa074
   Li H, 2011, BIOINFORMATICS, V27, P2987, DOI 10.1093/bioinformatics/btr509
   Li H, 2010, BIOINFORMATICS, V26, P589, DOI 10.1093/bioinformatics/btp698
   Lipsitch M, 1996, EVOLUTION, V50, P1729, DOI 10.1111/j.1558-5646.1996.tb03560.x
   López-Madrigal S, 2019, FEMS MICROBIOL LETT, V366, DOI 10.1093/femsle/fnz232
   Machado HE, 2021, ELIFE, V10, DOI 10.7554/eLife.67577
   Martin M., 2011, EMBnetJ, V17, P10, DOI DOI 10.14806/EJ.17.1.200
   Martinez J, 2014, PLOS PATHOG, V10, DOI 10.1371/journal.ppat.1004369
   Mateos M, 2006, GENETICS, V174, P363, DOI 10.1534/genetics.106.058818
   McCutcheon JP, 2019, CURR BIOL, V29, pR485, DOI 10.1016/j.cub.2019.03.032
   McCutcheon JP, 2012, NAT REV MICROBIOL, V10, P13, DOI 10.1038/nrmicro2670
   McFall-Ngai M, 2013, P NATL ACAD SCI USA, V110, P3229, DOI 10.1073/pnas.1218525110
   McKenna A, 2010, GENOME RES, V20, P1297, DOI 10.1101/gr.107524.110
   McMeniman CJ, 2009, SCIENCE, V323, P141, DOI 10.1126/science.1165326
   Meany MK, 2019, EVOLUTION, V73, P1278, DOI 10.1111/evo.13745
   Mitrovski P, 2001, P ROY SOC B-BIOL SCI, V268, P2163, DOI 10.1098/rspb.2001.1787
   Moran NA, 2008, ANNU REV GENET, V42, P165, DOI 10.1146/annurev.genet.41.110306.130119
   Murdock CC, 2014, SCI REP-UK, V4, DOI 10.1038/srep03932
   Myachina F, 2017, DEVELOPMENT, V144, P4573, DOI 10.1242/dev.156109
   Newton ILG, 2020, J BACTERIOL, V202, DOI 10.1128/JB.00589-19
   Nikoh N, 2014, P NATL ACAD SCI USA, V111, P10257, DOI 10.1073/pnas.1409284111
   Nikolouli K, 2018, J PEST SCI, V91, P489, DOI 10.1007/s10340-017-0944-y
   Nunes MDS, 2008, MOL BIOL EVOL, V25, P2493, DOI 10.1093/molbev/msn199
   Oliver KM, 2014, FUNCT ECOL, V28, P341, DOI 10.1111/1365-2435.12133
   Oliver KM, 2010, ANNU REV ENTOMOL, V55, P247, DOI 10.1146/annurev-ento-112408-085305
   Olsen K, 2001, HEREDITY, V86, P731, DOI 10.1046/j.1365-2540.2001.00892.x
   ONEILL SL, 1992, P NATL ACAD SCI USA, V89, P2699, DOI 10.1073/pnas.89.7.2699
   Osborne SE, 2009, PLOS PATHOG, V5, DOI 10.1371/journal.ppat.1000656
   Paradis E, 2010, BIOINFORMATICS, V26, P419, DOI 10.1093/bioinformatics/btp696
   Pfaffl MW, 2001, NUCLEIC ACIDS RES, V29, DOI 10.1093/nar/29.9.e45
   R Development Core Team, 2009, R: a language and environment for statistical computing
   Raychoudhury R, 2009, EVOLUTION, V63, P165, DOI 10.1111/j.1558-5646.2008.00533.x
   Reinhardt JA, 2014, GENETICS, V197, P361, DOI 10.1534/genetics.114.161463
   Reynolds KT, 2002, GENET RES, V80, P79, DOI 10.1017/S0016672302005827
   Rice DW, 2017, GENOME BIOL EVOL, V9, P1925, DOI 10.1093/gbe/evx139
   Richardson MF, 2012, PLOS GENET, V8, DOI 10.1371/journal.pgen.1003129
   Riegler M, 2005, CURR BIOL, V15, P1428, DOI 10.1016/j.cub.2005.06.069
   Ross PA, 2020, PLOS NEGLECT TROP D, V14, DOI 10.1371/journal.pntd.0007958
   Ross PA, 2019, ANNU REV GENET, V53, P93, DOI 10.1146/annurev-genet-112618-043609
   Ross PA, 2019, PLOS NEGLECT TROP D, V13, DOI 10.1371/journal.pntd.0007357
   Ross PA, 2017, PLOS PATHOG, V13, DOI 10.1371/journal.ppat.1006006
   Russell SL, 2019, CURR TOP DEV BIOL, V135, P315, DOI 10.1016/bs.ctdb.2019.04.007
   Russell SL, 2018, PLOS PATHOG, V14, DOI 10.1371/journal.ppat.1007216
   Schmidt PS, 2005, EVOLUTION, V59, P1721, DOI 10.1111/j.0014-3820.2005.tb01821.x
   Schneider CA, 2012, NAT METHODS, V9, P671, DOI 10.1038/nmeth.2089
   Seemann T, 2014, BIOINFORMATICS, V30, P2068, DOI 10.1093/bioinformatics/btu153
   Serbus LR, 2007, PLOS PATHOG, V3, P1930, DOI 10.1371/journal.ppat.0030190
   Serbus LR, 2015, PLOS PATHOG, V11, DOI 10.1371/journal.ppat.1004777
   Sheehan KB, 2016, MBIO, V7, DOI 10.1128/mBio.00622-16
   Shi M, 2018, P ROY SOC B-BIOL SCI, V285, DOI 10.1098/rspb.2018.1165
   Shropshire J.D., 2021, Male age and Wolbachia dynamics: determining how fast and why bacterial densities and cytoplasmic incompatibility strengths vary, DOI [10.1101/2021.06.01.446638, DOI 10.1101/2021.06.01.446638]
   Shropshire JD, 2020, ELIFE, V9, DOI 10.7554/eLife.61989
   Singmann H., 2020, afex: Analysis of factorial experiments, 2021
   Siozios S, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0055390
   Slynko V, 2009, J AM CHEM SOC, V131, P1274, DOI 10.1021/ja808682v
   Stirling C, 2010, BMC HEALTH SERV RES, V10, DOI 10.1186/1472-6963-10-122
   Stoy KS, 2020, J EVOLUTION BIOL, V33, P1656, DOI 10.1111/jeb.13715
   Sutton ER, 2014, BMC GENOMICS, V15, DOI 10.1186/1471-2164-15-928
   Teixeira L, 2008, PLOS BIOL, V6, P2753, DOI 10.1371/journal.pbio.1000002
   Thiem S., 2014, A genetic manipulation system for Wolbachia in mosquitoes
   TURELLI M, 1994, EVOLUTION, V48, P1500, DOI 10.1111/j.1558-5646.1994.tb02192.x
   TURELLI M, 1995, GENETICS, V140, P1319
   Turelli M, 2018, CURR BIOL, V28, P963, DOI 10.1016/j.cub.2018.02.015
   Utarini A, 2021, NEW ENGL J MED, V384, P2177, DOI 10.1056/NEJMoa2030243
   Veneti Z, 2004, APPL ENVIRON MICROB, V70, P5366, DOI 10.1128/AEM.70.9.5366-5372.2004
   Versace E, 2014, MOL ECOL, V23, P802, DOI 10.1111/mec.12643
   Wade MJ, 2007, NAT REV GENET, V8, P185, DOI 10.1038/nrg2031
   Walker T, 2011, NATURE, V476, P450, DOI 10.1038/nature10355
   Waterhouse A, 2018, NUCLEIC ACIDS RES, V46, pW296, DOI 10.1093/nar/gky427
   Weeks AR, 2007, PLOS BIOL, V5, P997, DOI 10.1371/journal.pbio.0050114
   Weinert LA, 2015, P ROY SOC B-BIOL SCI, V282, DOI 10.1098/rspb.2015.0249
   Werren JH, 2008, NAT REV MICROBIOL, V6, P741, DOI 10.1038/nrmicro1969
   Wheeler TB, 2021, ECOL EVOL, V11, P10054, DOI 10.1002/ece3.7782
   Wu M, 2004, PLOS BIOL, V2, P327, DOI 10.1371/journal.pbio.0020069
   Yang JY, 2015, NUCLEIC ACIDS RES, V43, pW174, DOI 10.1093/nar/gkv342
   Zhang B, 2019, P NATL ACAD SCI USA, V116, P24712, DOI 10.1073/pnas.1915307116
   Zhang CX, 2017, NUCLEIC ACIDS RES, V45, pW291, DOI 10.1093/nar/gkx366
   Zimmermann L, 2018, J MOL BIOL, V430, P2237, DOI 10.1016/j.jmb.2017.12.007
   Zug R, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0038544
NR 139
TC 31
Z9 35
U1 1
U2 29
PU CELL PRESS
PI CAMBRIDGE
PA 50 HAMPSHIRE ST, FLOOR 5, CAMBRIDGE, MA 02139 USA
SN 0960-9822
EI 1879-0445
J9 CURR BIOL
JI Curr. Biol.
PD FEB 28
PY 2022
VL 32
IS 4
BP 878
EP +
DI 10.1016/j.cub.2021.11.065
EA FEB 2022
PG 20
WC Biochemistry & Molecular Biology; Biology; Cell Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Life Sciences & Biomedicine - Other
   Topics; Cell Biology
GA ZY9WK
UT WOS:000772929200005
PM 34919808
OA Bronze, Green Accepted
DA 2025-01-10
ER

PT J
AU Truong, QC
   Nguyen, TH
   Tatsumi, K
   Pham, VT
   Tri, VPD
AF Truong, Quang Chi
   Nguyen, Thao Hong
   Tatsumi, Kenichi
   Pham, Vu Thanh
   Tri, Van Pham Dang
TI A Land-Use Change Model to Support Land-Use Planning in the Mekong Delta
   (MEKOLUC)
SO LAND
LA English
DT Article
DE cellular automata; GAMA; multi-criteria decision; Mekong Delta; land-use
   change
ID COVER CHANGE; CELLULAR-AUTOMATA; SIMULATION
AB Agricultural land-use changes pose challenges for land managers in terms of ensuring the implementation of local land-use plans. This paper aims to build a land-use change model named MEKOLUC (Mekong Delta land-use change) for simulating land-use changes under the impacts of socioeconomic factors (profitability of land-use types, societal impacts on neighborhoods) and environmental factors (soil, salinity, persistence of salinity). The salinity diffusion map was generated using GAMA software and employed Markov cellular automata to depict the spread of salinity under the influence of dike and sluice gate system operations. The land-use decision-making process was based on multi-criteria selection of the main factors, which were land suitability, land convertibility, density of land use in the neighborhood and profitability of land-use patterns. The input data for the case study were historical land-use maps from 2005, 2010 and 2015 of Soc Trang, a coastal province in the Mekong Delta. The model was calibrated using a land-use map from 2010 (with kappa = 0.86) and was verified with land-use maps from 2015 and 2020 with deviations from 0 to 19%. The simulated results showed that shrimp-rice farming areas have been shrinking, even though these are recommended as sustainable farming systems. Inversely, intensive rice crops tended to change to rice-vegetable crops, vegetable crops or perennial fruit trees, which are projected to be well adapted to climate and salinity intrusion by 2030. This case study shows that the developed model is an essential tool for helping land managers and farmers build land-use plans.
C1 [Truong, Quang Chi; Pham, Vu Thanh; Tri, Van Pham Dang] Can Tho Univ, Coll Environm & Nat Resources, Can Tho 94100, Vietnam.
   [Nguyen, Thao Hong] Coll Technol & Econ Can Tho, Dept Resource & Environm Management, Can Tho 94100, Vietnam.
   [Tatsumi, Kenichi] Tokyo Univ Agr & Technol, Inst Agr, Div Environm & Agr Engn, Tokyo 1830054, Japan.
   [Tri, Van Pham Dang] Can Tho Univ, Res Inst Climate Change, Can Tho 94100, Vietnam.
C3 Can Tho University; Tokyo University of Agriculture & Technology; Can
   Tho University
RP Tri, VPD (corresponding author), Can Tho Univ, Coll Environm & Nat Resources, Can Tho 94100, Vietnam.; Tri, VPD (corresponding author), Can Tho Univ, Res Inst Climate Change, Can Tho 94100, Vietnam.
EM tcquang@ctu.edu.vn; nhthao@ctec.edu.vn; tatsumi@go.tuat.ac.jp;
   ptvu@ctu.edu.vn; vpdtri@ctu.edu.vn
RI Tatsumi, Kenichi/G-1077-2013; Truong, Quang/ITT-3879-2023; Nguyen,
   D./Q-6703-2017; TATSUMI, Kenichi/LRT-0676-2024; Minh, Vo
   Quang/S-9905-2019
OI TATSUMI, Kenichi/0000-0001-6763-6909; Thanh Vu,
   Pham/0000-0002-4379-4504; Minh, Vo Quang/0000-0001-8574-7151; Truong,
   Quang Chi/0000-0002-1496-4519
FU Can Tho University Improvement Project [VN14-P6]; Japanese ODA loan;
   Grants-in-Aid for Scientific Research [21H02314] Funding Source: KAKEN
FX This study was funded in part by the Can Tho University Improvement
   Project VN14-P6, supported by a Japanese ODA loan.
CR Bakker MM, 2015, LANDSCAPE ECOL, V30, P273, DOI 10.1007/s10980-014-0116-x
   Bong B.B., 2018, ADAPTATION OPTIONS R
   Briassoulis H., 2009, Encyclopaedia of Life Support Systems (EOLSS), V1, P126
   Castella JC, 2005, ECOL SOC, V10
   Chen LP, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0200493
   Department of Land Resources, 2014, CTU SOIL MAP MEK DEL
   Drogoul A, 2016, FRONT ENV SCI-SWITZ, V4, DOI 10.3389/fenvs.2016.00019
   Eastman JR, 2020, LAND-BASEL, V9, DOI 10.3390/land9110407
   Fao, 1981, FAO SOILS B
   Feng YL, 2018, ISPRS INT J GEO-INF, V7, DOI 10.3390/ijgi7100403
   Gilbert N.G., 2008, AGENT BASED MODELS
   GSO (General Statistics Office), 2021, Statistic Yeabook of Vietnam 2020
   Handavu F, 2019, FOREST POLICY ECON, V100, P75, DOI 10.1016/j.forpol.2018.10.010
   Hassan Z, 2016, SPRINGERPLUS, V5, DOI 10.1186/s40064-016-2414-z
   Herzberg R, 2019, LAND-BASEL, V8, DOI 10.3390/land8060090
   Hien N.X., 2016, SMCN 2009 021 THEME
   Loc HH, 2017, ECOSYST SERV, V26, P377, DOI 10.1016/j.ecoser.2016.04.007
   Korres N., 2017, WATER RESOURCES RURA, V9, P12, DOI DOI 10.1016/J.WRR.2016.10.001
   Lambin EF, 2001, GLOBAL ENVIRON CHANG, V11, P261, DOI [10.1016/S0959-3780(01)00007-3, 10.1146/annurev.energy.28.050302.105459]
   Le QB, 2010, ECOL INFORM, V5, P203, DOI 10.1016/j.ecoinf.2010.02.001
   Lee SK, 2020, INT J CLIM CHANG STR, V12, P639, DOI 10.1108/IJCCSM-04-2020-0032
   Li XM, 2016, DISCRETE DYN NAT SOC, V2016, DOI 10.1155/2016/8061069
   Mahiny AS, 2012, ENVIRON PLANN B, V39, P925, DOI 10.1068/b37092
   Nath B, 2020, ISPRS INT GEO-INF, V9, DOI 10.3390/ijgi9020134
   Cerrillo RMN, 2020, ISPRS INT J GEO-INF, V9, DOI 10.3390/ijgi9070458
   Noszczyk T, 2019, HUM ECOL RISK ASSESS, V25, P1377, DOI 10.1080/10807039.2018.1468994
   Ozah AP, 2010, INT ARCH PHOTOGRAMM, V38-4-8, P75
   Palmate SS, 2017, APPL GEOGR, V82, P11, DOI 10.1016/j.apgeog.2017.03.001
   Pan XH, 2021, LAND-BASEL, V10, DOI 10.3390/land10070688
   Parker DC, 2003, ANN ASSOC AM GEOGR, V93, P314, DOI 10.1111/1467-8306.9302004
   Pham V.N., 2021, SCI TECHNOL J AGR RU, V2, P175
   Quang CNX, 2021, IOP C SER EARTH ENV, V652, DOI 10.1088/1755-1315/652/1/012020
   Quang Chi Truong, 2016, Multi-Agent-Based Simulation XVI. International Workshop, MABS 2015. Revised Selected Papers: LNCS 9568, P146, DOI 10.1007/978-3-319-31447-1_10
   Quang T.C, 2017, J SCI CAN THO U, V2017, P144, DOI [10.22144/ctu.jsi.2017.063, DOI 10.22144/CTU.JSI.2017.063]
   Schneeberger N, 2007, LAND USE POLICY, V24, P349, DOI 10.1016/j.landusepol.2006.04.003
   Sfa FE, 2020, ECOL COMPLEX, V43, DOI 10.1016/j.ecocom.2020.100851
   Shooshtari SJ, 2020, J INDIAN SOC REMOTE, V48, P81, DOI 10.1007/s12524-019-01054-x
   Soc Trang DONRE, 2005, LAND USE INVENTORY S, V2005
   Soc Trang Statistic Office, 2020, STAT YB SOC TRANG PR
   Soc Trang Statistic Office, 2010, STAT YB SOC TRANG PR
   Soc Trang Statistic Office, 2005, STAT YB SOC TRANG PR
   Soc Trang Statistic Office, 2015, STAT YB SOC TRANG PR
   Taillandier P., 2014, P 4 INT C COMPL SYST
   Taillandier P, 2019, GEOINFORMATICA, V23, P299, DOI 10.1007/s10707-018-00339-6
   Taillandier P, 2016, LECT NOTES ARTIF INT, V10003, P154, DOI 10.1007/978-3-319-46840-2_10
   Thanh Vu P., 2013, J SCI CAN THO U, V27, P68
   Valbuena D, 2010, LANDSCAPE ECOL, V25, P185, DOI 10.1007/s10980-009-9380-6
   van Vliet J, 2013, ECOL MODEL, V261, P32, DOI 10.1016/j.ecolmodel.2013.03.019
   Vu P.T., 2014, Can Tho Univ. J. Sci., V31, P106
   Wang CJ, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11030301
   Wassmann R, 2004, CLIMATIC CHANGE, V66, P89, DOI 10.1023/B:CLIM.0000043144.69736.b7
   Wu D., 2008, ENQUAD Report 2008-19, P1
   Young Kenneth B., 2002, Vietnam's Rice Economy: Developments and Prospects
   Zhu J, 2021, ENVIRON PLAN B-URBAN, V48, P1841, DOI 10.1177/2399808320949889
NR 54
TC 12
Z9 13
U1 8
U2 40
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-445X
J9 LAND-BASEL
JI Land
PD FEB
PY 2022
VL 11
IS 2
AR 297
DI 10.3390/land11020297
PG 16
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA ZL5MP
UT WOS:000763721400001
OA gold
DA 2025-01-10
ER

PT J
AU Apriyana, Y
   Surmaini, E
   Estiningtyas, W
   Pramudia, A
   Ramadhani, F
   Suciantini, S
   Susanti, E
   Purnamayani, R
   Syahbuddin, H
AF Apriyana, Yayan
   Surmaini, Elza
   Estiningtyas, Woro
   Pramudia, Aris
   Ramadhani, Fadhlullah
   Suciantini, Suciantini
   Susanti, Erni
   Purnamayani, Rima
   Syahbuddin, Haris
TI The Integrated Cropping Calendar Information System: A Coping Mechanism
   to Climate Variability for Sustainable Agriculture in Indonesia
SO SUSTAINABILITY
LA English
DT Article
DE climate variability; adaptation; food security; information system;
   cropping calendar
ID RAINFALL ONSET; ENSO; MONSOON; SEASON; CONTINENT; IMPACT; JAVA; SST
AB Climate change and its variability are some of the most critical threats to sustainable agriculture, with potentially severe consequences on Indonesia's agriculture, such as changes in rainfall patterns, especially the onset of the wet season and the temporal distribution of rainfall. Most Indonesian farmers receive support from agricultural extension services, and therefore, design their agricultural calendar based on personal experience without considering global climate phenomena, such as La Nina and El Nino, which difficult to interpret on a local scale. This paper describes the Integrated Cropping Calendar Information System (ICCIS) as a mechanism for adapting to climate variability. The ICCIS contains recommendations on planting time, cropping pattern, planting area, varieties, fertilizers, agricultural machinery, potential livestock feed, and crop damage due to climate extremes for rice, maize, and soybean. To accelerate the dissemination of information, the ICCIS is presented in an integrated web-based information system. The ICCIS is disseminated to extension workers and farmers by Task Force of the Assessment Institute for Agricultural Technology (AIAT) located in each province. Based on the survey results, it is known that the ICCIS adoption rate is moderate to high. The AIAT must actively encourage and support the ICCIS Task Force team in each province. Concerning the technological recommendations, it is necessary to update the recommendations for varieties, fertilizer, and feed to be more compatible with local conditions. More accurate information and more intensive dissemination can enrich farmers' knowledge, allowing for a better understanding of climate hazards and maintaining agricultural production.
C1 [Apriyana, Yayan; Surmaini, Elza; Estiningtyas, Woro; Pramudia, Aris; Ramadhani, Fadhlullah; Suciantini, Suciantini; Susanti, Erni] Indonesia Agcy Agr Res & Dev, Indonesian Agroclimate & Hydrol Res Inst, Jl Tentara Pelajar 1A, Bogor 16111, Indonesia.
   [Ramadhani, Fadhlullah] Massey Univ, Sch Agr & Environm, Geosci, Palmerston North 4410, New Zealand.
   [Purnamayani, Rima] Indonesia Agcy Agr Res & Dev, Indonesia Ctr Agr Technol Assessment & Dev, Jl Tentara Pelajar 10, Bogor 16124, Indonesia.
   [Syahbuddin, Haris] Indonesia Agcy Agr Res & Dev, Jl Ragunan 29 Pasar Minggu, Jakarta 12540, Indonesia.
C3 Indonesian Agency for Agricultural Research & Development; Massey
   University; Indonesian Agency for Agricultural Research & Development;
   Indonesian Agency for Agricultural Research & Development
RP Surmaini, E (corresponding author), Indonesia Agcy Agr Res & Dev, Indonesian Agroclimate & Hydrol Res Inst, Jl Tentara Pelajar 1A, Bogor 16111, Indonesia.
EM yanapri66@gmail.com; elzasurmaini@gmail.com; woro_esti@yahoo.com;
   arispramudia@yahoo.com; fadhlullah@pertanian.go.id;
   suciantini@yahoo.com; susanti_erni@yahoo.com; rimacahyo@gmail.com;
   harissyahbuddin@yahoo.com
RI Apriyana, Yayan/IUN-5391-2023; Ramadhani, Fadhlullah/AAL-6374-2021
OI Ramadhani, Fadhlullah/0000-0003-1642-9234; Surmaini,
   Elza/0000-0002-2540-6504; Suciantini, Suciantini/0000-0002-2835-8173;
   Pramudia, Aris/0000-0001-8745-6358; Apriyana, Yayan/0000-0003-1809-6103;
   Estiningtyas, Woro/0000-0002-5514-2132
FU Indonesia Agency for Agricultural Research and Development [SP
   DIPA-018.09.2.648694/2019]
FX This research was funded by Indonesia Agency for Agricultural Research
   and Development, grant number SP DIPA-018.09.2.648694/2019.
CR Aldrian E, 2007, THEOR APPL CLIMATOL, V87, P41, DOI 10.1007/s00704-006-0218-8
   Aldrian E, 2004, CLIM DYNAM, V22, P795, DOI 10.1007/s00382-004-0418-9
   Amien I, 1996, WATER AIR SOIL POLL, V92, P29
   [Anonymous], 2010, NILE BASIN WATER SCI, V3, P13
   [Anonymous], 1957, INSTRUCTIONS TABLES
   Apriyana Y., 2018, P IOP C SERIES EARTH
   As-syakur A, 2014, INT J CLIMATOL, V34, P3825, DOI 10.1002/joc.3939
   Azis A., 2019, INNOV SCI INF SERV N, V16, P3226
   Azis A., 2020, P NATL SEM US LOC VA, V1, P25
   Boer R, 2020, THEOR APPL CLIMATOL, V139, P1435, DOI 10.1007/s00704-019-03055-9
   Bouroncle C, 2019, CLIM SERV, V16, DOI 10.1016/j.cliser.2019.100137
   Brewer CA, 2002, ANN ASSOC AM GEOGR, V92, P662, DOI 10.1111/1467-8306.00310
   Budiharti U., 2015, MAPPING DEV RICE COR
   Chang CP, 2004, J CLIMATE, V17, P665, DOI 10.1175/1520-0442(2004)017<0665:OTRBWM>2.0.CO;2
   Darna N., 2018, JURNAL ILMU MANAJEME, V5, P287, DOI [10.2827/jeim.v5i1.1359, DOI 10.2827/JEIM.V5I1.1359]
   Dewi ER, 2021, IOP C SER EARTH ENV, V648, DOI 10.1088/1755-1315/648/1/012105
   Estiningtyas W., 2016, J SUMBERD LAHAN, VSpecial Edition, P85
   Hamada JI, 2002, J METEOROL SOC JPN, V80, P285, DOI 10.2151/jmsj.80.285
   Hatta Muhammad, 2020, Jurnal Tanah Tropika, V25, P93, DOI 10.5400/jts.2020.v25i2.93-106
   Haylock M, 2001, J CLIMATE, V14, P3882, DOI 10.1175/1520-0442(2001)014<3882:SCAPOI>2.0.CO;2
   Hidayat R, 2016, IOP C SER EARTH ENV, V31, DOI 10.1088/1755-1315/31/1/012043
   Kai T., 2020, Journal of Agricultural Chemistry and Environment, V9, P331, DOI [10.4236/jacen.2020.94024, DOI 10.4236/JACEN.2020.94024]
   Kalpalatha C., 2018, IOSR J HUMANIT SOC S, V23, P17
   Kiratiratanapruk K, 2020, J SENSORS, V2020, DOI 10.1155/2020/7041310
   Kotera A, 2014, PADDY WATER ENVIRON, V12, P343, DOI 10.1007/s10333-013-0386-y
   Kousky VE, 2007, WEATHER FORECAST, V22, P353, DOI 10.1175/WAF987.1
   Leinonen I, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11010246
   Mase AS, 2014, WEATHER CLIM SOC, V6, P47, DOI 10.1175/WCAS-D-12-00062.1
   Ministry of Agrarian Affair and Spatial Planning/National Land Agency, 2019, NAT RIC FIELD MAP
   Ministry of Agriculture, 2007, FERT REC N P K LOC S
   Mugalavai EM, 2008, AGR FOREST METEOROL, V148, P1123, DOI 10.1016/j.agrformet.2008.02.013
   MURAKAMI T, 1994, J METEOROL SOC JPN, V72, P719, DOI 10.2151/jmsj1965.72.5_719
   Naylor R, 2002, B INDONES ECON STUD, V38, P75, DOI 10.1080/000749102753620293
   Naylor RL, 2001, CLIMATIC CHANGE, V50, P255, DOI 10.1023/A:1010662115348
   Naylor RL, 2007, P NATL ACAD SCI USA, V104, P7752, DOI 10.1073/pnas.0701825104
   Odekunle TO, 2005, THEOR APPL CLIMATOL, V81, P101, DOI 10.1007/s00704-004-0108-x
   Qiu ZJ, 2020, SENSORS-BASEL, V20, DOI 10.3390/s20154082
   Ramadhani F, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12213613
   Rose DC, 2016, AGR SYST, V149, P165, DOI 10.1016/j.agsy.2016.09.009
   Runtunuwu E., 2013, PENGEMB INOV PERTAN, V6, P44
   Runtunuwu E., 2012, J. Sumberdaya Lahan, V6, P67
   Runtunuwu E., 2011, J ECOLAB, V5, P1, DOI [10.20886/jklh.2011.5.1.1-14, DOI 10.20886/JKLH.2011.5.1.1-14]
   Saji NH, 2003, J CLIMATE, V16, P2735, DOI 10.1175/1520-0442(2003)016<2735:SOSASW>2.0.CO;2
   Salack S, 2011, THEOR APPL CLIMATOL, V106, P1, DOI 10.1007/s00704-011-0414-z
   Satyawardhana H., 2018, IOP Conference Series: Earth and Environmental Science, V166, DOI 10.1088/1755-1315/166/1/012030
   Saxe H, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10093184
   Setyorini D., 2011, DETERMINATION RECOMM
   Subardja V O., 2016, Journal of Degraded and Mining Lands Management, V3, P543, DOI DOI 10.15243/JDMLM.2016.032.543
   Sun Z., P 2019 8 INT C AGR A, P1
   Surmaini E, 2015, THEOR APPL CLIMATOL, V121, P669, DOI 10.1007/s00704-014-1258-0
   Susanti E., 2021, INDONESIAN SOIL CLIM, V45, P12, DOI [10.21082/jti.v45n1.2021.47-58, DOI 10.21082/JTI.V45N1.2021.47-58]
   Susilo GE, 2013, HYDROLOG SCI J, V58, P539, DOI 10.1080/02626667.2013.772298
   Syahbuddin H., 2018, APPL TECHNOLOGICAL I
   Xue Y, 2003, J CLIMATE, V16, P1601, DOI 10.1175/1520-0442-16.10.1601
   Yegbemey RN, 2014, CLIM RISK MANAG, V3, P13, DOI 10.1016/j.crm.2014.04.001
   Yulianti A., 2016, INT J ADV SCI ENG IN, V6, P92, DOI [10.18517/ijaseit.6.1.659, DOI 10.18517/IJASEIT.6.1.659]
   Yuliarso M.Z., 2020, J AGRISEP KAJI MASAL, V19, P407, DOI [10.31186/agrisep.19.2.407-416, DOI 10.31186/AGRISEP.19.2.407-416]
NR 57
TC 17
Z9 17
U1 1
U2 13
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2071-1050
J9 SUSTAINABILITY-BASEL
JI Sustainability
PD JUN
PY 2021
VL 13
IS 11
AR 6495
DI 10.3390/su13116495
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 SR0WI
UT WOS:000660766000001
OA gold
DA 2025-01-10
ER

PT J
AU Fornai, C
   Webb, NM
   Urciuoli, A
   Krenn, VA
   Corron, LK
   Haeusler, M
AF Fornai, Cinzia
   Webb, Nicole M.
   Urciuoli, Alessandro
   Krenn, Viktoria A.
   Corron, Louise K.
   Haeusler, Martin
TI New insights on hip bone sexual dimorphism in adolescents and adults
   using deformation-based geometric morphometrics
SO JOURNAL OF ANTHROPOLOGICAL SCIENCES
LA English
DT Article
DE Pelvic morphology; Sex-related variation; Ontogeny; Deformetrica;
   Diffeomorphism
ID COMPUTED-TOMOGRAPHY; TRAITS; SHAPE; SIZE; MORPHOLOGY; ASYMMETRY;
   ONTOGENY; STATURE; INFANT; PELVIS
AB Morphological variation of the human pelvis, and particularly the hip bone, mainly results from both female-specific selective pressure related to the give birth of large-headed newborns, and constraints in both sexes for efficient bipedal locomotion, abdominal stability, and adaptation to climate. Hip bone morphology has thus been extensively investigated using several approaches, although the nuances of inter-individual and sex-related variation are still underappreciated, and the effect of sex on ontogenetic patterns is debated. Here, we employ a landmark-free, deformation-based morphometric approach to explore variation in modern human hip bone shape and size from middle adolescence to adulthood. Virtual surface models of the hip bone were obtained from 147 modern human individuals (70 females and 77 males) including adolescents, and young and mature adults. The 3D meshes were registered by rotation, translation, and uniform scaling prior to analysis in Deformetrica. The orientation and amplitude of deviations of individual specimens relative to a global mean were assessed using Principal Component Analysis, while colour maps and vectors were employed for visualisation purposes. Deformation-based morphometrics is a time-efficient and objective method free of observer-dependent biases that allows accurate shape characterisation of general and more subtle morphological variation. Here, we captured nuanced hip bone morphology revealing ontogenetic trends and sex-based variation in arcuate line curvature, greater sciatic notch shape, pubic body and rami length, acetabular expansion, and height-to-width proportions of the ilium. The observed ontogenetic trends showed a higher degree of bone modelling of the lesser pelvis of adolescent females, while male variation was mainly confined to the greater pelvis.
C1 [Fornai, Cinzia; Webb, Nicole M.; Krenn, Viktoria A.; Haeusler, Martin] Univ Zurich, Inst Evolutionary Med, Winterthurerstr 190, CH-8057 Zurich, Switzerland.
   [Fornai, Cinzia; Krenn, Viktoria A.] Univ Vienna, Dept Evolutionary Anthropol, Djerassipl 1, A-1030 Vienna, Austria.
   [Fornai, Cinzia] Vienna Sch Interdisciplinary Dent, Wasserzeile 35, A-34000 Klosterneuburg, Austria.
   [Webb, Nicole M.] Eberhard Karls Univ Tubingen, Dept Palaeoanthropol, Inst Archaeol Sci, Senckenberg Ctr Human Evolut & Palaeoenvironm, Ruemelinstr 23, D-72070 Tubingen, Germany.
   [Urciuoli, Alessandro] Univ Autonoma Barcelona, Inst Catala Paleontol Miquel Crusafont, Edifici ICTA ICP,Campus UAB,C Columns S-N, Barcelona 08193, Spain.
   [Corron, Louise K.] Univ Nevada, Dept Anthropol, 1664 N Virginia St, Reno, NV 89557 USA.
C3 University of Zurich; University of Vienna; Eberhard Karls University of
   Tubingen; Leibniz Association; Senckenberg Gesellschaft fur
   Naturforschung (SGN); Autonomous University of Barcelona; Institut
   Catala de Paleontologia Miquel Crusafont (ICP); Nevada System of Higher
   Education (NSHE); University of Nevada Reno
RP Fornai, C (corresponding author), Univ Zurich, Inst Evolutionary Med, Winterthurerstr 190, CH-8057 Zurich, Switzerland.; Fornai, C (corresponding author), Univ Vienna, Dept Evolutionary Anthropol, Djerassipl 1, A-1030 Vienna, Austria.; Fornai, C (corresponding author), Vienna Sch Interdisciplinary Dent, Wasserzeile 35, A-34000 Klosterneuburg, Austria.
EM cinzia.fornai@univie.ac.at; nicole.webb@ifu.uni-tuebingen.de
RI Fornai, Cinzia/AAB-6451-2020; Urciuoli, Alessandro/AAV-4918-2020
OI Haeusler, Martin/0000-0002-9100-4183; Urciuoli,
   Alessandro/0000-0002-6265-8962; Corron, Louise/0000-0002-4788-6203
FU Swiss National Science Foundation (SNF) [31003A_176319/1]; Agencia
   Estatal de Investigacion [PID2020-117289GB-I00, PID2020-116908GB-I00];
   Generalitat de Catalunya (CERCA Programme);  [BCV-2020-1-0008]
FX We thank the following persons and institutions for granting access to
   or otherwise facilitating data acqui-sition: Karin Wilschke-Schrotta and
   Sabine Egg-ers, Department of Anthropology, Natural History Museum
   Vienna; Kathia Chaumoitre, UMR7268 Anthropologie bioculturelle, Droit,
   Ethique et Sante and Assistance Publique des Hopitaux de Marseille,
   Marseille; Martin Friess and Veronique Laborde, Musee de l'Homme, Paris;
   Marcia Ponce de Leon, Marc Scherrer, Jody Weissmann, Anthropological
   Institute and Museum, University of Zurich, Zurich; Jocelyne Desideri,
   Laboratory of Prehistoric Archae-ology and Anthropology, University of
   Geneva, Geneva; Harald Wilfing, Katrin Schafer, Katarina Matiasek,
   Department of Evolutionary Anthropol-ogy, University of Vienna, Vienna.
   We thank Stepha-nie Cole, University of Nevada, Reno, and Yaro-slav
   Bruek, Universite de Bordeaux, UMR 5199 PACEA, and Charles University,
   Prague, for the in-depth conversations on subadult sex estimation,
   sexual dimorphism, and maturation of the pelvis. The Barcelona
   Supercomputing Center granted computational time to AU (project No
   BCV-2020-1-0008) . C.F., N.M.W., V.A.K. and M.H. were financially
   supported by the Swiss National Science Foundation (SNF grant No
   31003A_176319/1) . AU was funded by the Agencia Estatal de Investigacion
   (PID2020-117289GB-I00 and PID2020-116908GB-I00, AEI/FEDER, EU) and the
   Generalitat de Catalunya (CERCA Programme) .
CR ABITBOL MM, 1987, J HUM EVOL, V16, P243, DOI 10.1016/0047-2484(87)90001-7
   [Anonymous], 1980, J HUM EVOL, V9, P517
   [Anonymous], 2018, LMODEL2 MODEL 2 REGR
   Bass W.M., 1995, HUMAN OSTEOLOGY LAB
   Beaudet A, 2021, J HUM EVOL, V156, DOI 10.1016/j.jhevol.2021.103010
   Beaudet A, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-60837-2
   Beaudet A, 2016, J HUM EVOL, V95, P104, DOI 10.1016/j.jhevol.2016.04.004
   Betti L, 2018, P ROY SOC B-BIOL SCI, V285, DOI 10.1098/rspb.2018.1807
   Betti L, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0055909
   Bilfeld MF, 2013, J FORENSIC SCI, V58, P303, DOI 10.1111/1556-4029.12037
   Bône A, 2018, LECT NOTES COMPUT SC, V11167, P3, DOI 10.1007/978-3-030-04747-4_1
   Bookstein F.L., 1991, Morphometric Tools for Landmark Data: Geometry and Biology
   Bookstein FL, 2018, COURSE IN MORPHOMETRICS FOR BIOLOGISTS: GEOMETRY AND STATISTICS FOR STUDIES OF ORGANISMAL FORM, P1, DOI 10.1017/9781108120418
   Brown WM, 2008, P NATL ACAD SCI USA, V105, P12938, DOI 10.1073/pnas.0710420105
   Bruzek J, 2002, AM J PHYS ANTHROPOL, V117, P157, DOI 10.1002/ajpa.10012
   Buikstra J. E., 1994, Standards for data collection from human skeletal remains, DOI DOI 10.1002/AJHB.1310070519
   Bytheway JA, 2010, J FORENSIC SCI, V55, P859, DOI 10.1111/j.1556-4029.2010.01374.x
   Charles BE, 2010, GEOMETRIC MORPHOMETR
   COLEMAN WH, 1969, AM J PHYS ANTHROPOL, V31, P125, DOI 10.1002/ajpa.1330310202
   Corron LK, 2021, FORENSIC SCI INT, V325, DOI 10.1016/j.forsciint.2021.110854
   Cox SL, 2021, AM J PHYS ANTHROPOL, V176, P652, DOI 10.1002/ajpa.24399
   Dray S, 2007, J STAT SOFTW, V22, P1, DOI 10.18637/jss.v022.i04
   Dunsworth HM, 2020, EVOL ANTHROPOL, V29, P108, DOI 10.1002/evan.21834
   Durrleman S, 2012, LECT NOTES COMPUT SC, V7512, P223, DOI 10.1007/978-3-642-33454-2_28
   Durrleman S, 2012, J HUM EVOL, V62, P74, DOI 10.1016/j.jhevol.2011.10.004
   Fischer B, 2021, NAT ECOL EVOL, V5, P625, DOI 10.1038/s41559-021-01425-z
   Fischer B, 2017, ANAT REC, V300, P698, DOI 10.1002/ar.23549
   Fischer B, 2015, P NATL ACAD SCI USA, V112, P5655, DOI 10.1073/pnas.1420325112
   Fischer MCM, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-49573-4
   FLANDER LB, 1978, AM J PHYS ANTHROPOL, V49, P103, DOI 10.1002/ajpa.1330490116
   Franklin D, 2005, HOMO, V55, P213, DOI 10.1016/j.jchb.2004.08.001
   Genoves S., 1959, B MEMOIRES SOCIETE D, V10, P3, DOI 10.3406/bmsap.1959.2750
   Glaunes J. A., 2006, 1 MICCAI WORKSH MATH
   Grunstra NDS, 2019, AM J HUM BIOL, V31, DOI 10.1002/ajhb.23227
   Gunz P, 2005, DEV PRIMATOL-PROG PR
   Gunz P, 2013, HYSTRIX, V24, P103, DOI 10.4404/hystrix-24.1-6292
   Haeusler M, 2021, BIOL REV, V96, P2031, DOI 10.1111/brv.12744
   Hausler M., 2004, RECHTSMEDIZIN, V14, P356
   Huseynov A, 2016, P NATL ACAD SCI USA, V113, P5227, DOI 10.1073/pnas.1517085113
   Isran M. Y., 2013, The human skeleton in forensic medicine, V3rd
   Iuliano-Burns S, 2009, J CLIN ENDOCR METAB, V94, P1638, DOI 10.1210/jc.2008-1522
   Karsten JK, 2018, AM J PHYS ANTHROPOL, V165, P604, DOI 10.1002/ajpa.23372
   Klales AR, 2012, AM J PHYS ANTHROPOL, V149, P104, DOI 10.1002/ajpa.22102
   Klales AR., 2020, SEX ESTIMATION HUMAN, DOI DOI 10.1016/B978-0-12-815767-1.00006-7
   Krantz S.G., 2013, The Implicit Function Theorem
   Krenn VA, 2022, ANTHROPOL ANZ, V79, P211, DOI 10.1127/anthranz/2021/1415
   Krishan K, 2016, FORENSIC SCI INT, V261, DOI 10.1016/j.forsciint.2016.02.007
   Krogman WM., 1962, HUMAN SKELETON FOREN
   Kuchar M, 2021, INT J LEGAL MED, V135, P1617, DOI 10.1007/s00414-021-02501-6
   Kurki HK, 2007, AM J PHYS ANTHROPOL, V133, P1152, DOI 10.1002/ajpa.20636
   Mestekova S, 2015, J FORENSIC SCI, V60, P1295, DOI 10.1111/1556-4029.12817
   Mitteroecker P., 2021, B MEMOIRES SOC ANTHR, V33, DOI [10.4000/bmsap.7460, DOI 10.4000/BMSAP.7460]
   Oikonomopoulou EK, 2017, INT J LEGAL MED, V131, P1731, DOI 10.1007/s00414-017-1655-x
   PHENICE TW, 1969, AM J PHYS ANTHROPOL, V30, P297, DOI 10.1002/ajpa.1330300214
   R Development Core Team, 2009, R: a language and environment for statistical computing
   Rantalainen T, 2016, BONE, V93, P71, DOI 10.1016/j.bone.2016.09.015
   Rmoutilová R, 2017, LEGAL MED-TOKYO, V26, P52, DOI 10.1016/j.legalmed.2017.03.004
   Robertson HI, 2019, AM J PHYS ANTHROPOL, V169, P689, DOI 10.1002/ajpa.23860
   ROGERS T, 1994, J FORENSIC SCI, V39, P1047
   ROSENBERG KR, 1992, YEARB PHYS ANTHROPOL, V35, P89
   Rusk KM, 2016, AM J PHYS ANTHROPOL, V159, P646, DOI 10.1002/ajpa.22926
   Schlager S., 2013, PhD dissertation
   SCHUTKOWSKI H, 1993, AM J PHYS ANTHROPOL, V90, P199, DOI 10.1002/ajpa.1330900206
   Slice DE, 2005, DEV PRIMATOL-PROG PR, P1, DOI 10.1007/0-387-27614-9_1
   Stansfield E, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2022159118
   Steyn M, 2004, HOMO, V54, P197, DOI 10.1078/0018-442X-00076
   Tague RG, 2003, J MAMMAL, V84, P1464, DOI 10.1644/BME-009
   Tobolsky VA, 2016, AM J HUM BIOL, V28, P804, DOI 10.1002/ajhb.22870
   Torres-Tamayo N, 2018, AM J PHYS ANTHROPOL, V167, P777, DOI 10.1002/ajpa.23705
   Urciuoli A, 2018, P EUROPEAN SOC HUMAN
   Urciuoli A, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2015215118
   Urciuoli A, 2020, ELIFE, V9, DOI 10.7554/eLife.51261
   Veneziano A, 2018, AM J PHYS ANTHROPOL, V166, P473, DOI 10.1002/ajpa.23431
   Waldeyer HWG, 1899, BECKENTOPOGRAPHISCHA
   Waltenberger L, 2021, AM J PHYS ANTHROPOL, V174, P846, DOI 10.1002/ajpa.24204
   Warrener AG, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0118903
   WASHBURN SL, 1960, SCI AM, V203, P63
   WEAVER DS, 1980, AM J PHYS ANTHROPOL, V52, P191, DOI 10.1002/ajpa.1330520205
   Webb NM, 2021, AM J PHYS ANTHROPOL, V174, P111
   Weber GW, 2011, VIRTUAL ANTHROPOLOGY: GUIDE TO A NEW INTERDISCIPLINARY FIELD, P1, DOI 10.1007/978-3-211-49347-2
   Wells JCK, 2017, ANAT REC, V300, P716, DOI 10.1002/ar.23540
   Wilson LAB, 2017, AM J PHYS ANTHROPOL, V162, P255, DOI 10.1002/ajpa.23114
   Zanolli C, 2018, J HUM EVOL, V116, P1, DOI 10.1016/j.jhevol.2017.11.002
   Zech WD, 2012, FORENSIC SCI INT, V221, P39, DOI 10.1016/j.forsciint.2012.03.022
   ZELDITCH ML, 1995, SYST BIOL, V44, P179, DOI 10.2307/2413705
   Zhan MJ, 2018, LEGAL MED-TOKYO, V34, P21, DOI 10.1016/j.legalmed.2018.07.003
NR 86
TC 4
Z9 5
U1 0
U2 2
PU IST ITALIANO ANTROPOLOGIA
PI ROMA
PA UNIV SAPIENZA, DIPARTIMENTO DI BIOLOGIA ANIMALE E DELL UOMO, PE LE A
   MORO 5, ROMA, 00185, ITALY
SN 1827-4765
EI 2037-0644
J9 J ANTHROPOL SCI
JI J. Anthropol. Sci.
PY 2021
VL 99
BP 117
EP 134
DI 10.4436/jass.99017
PG 18
WC Anthropology
WE Social Science Citation Index (SSCI)
SC Anthropology
GA YK5UE
UT WOS:000745276600006
PM 34958307
DA 2025-01-10
ER

PT J
AU Ranga, P
   Prakash, R
   Mrinal, N
AF Ranga, Poonam
   Prakash, Ravi
   Mrinal, Nirotpal
TI Sibling <i>Drosophila</i> species (<i>Drosophila leontia</i> and
   <i>Drosophila kikkawai</i>) show divergence for thermotolerance along a
   latitudinal gradient
SO EVOLUTIONARY ECOLOGY
LA English
DT Article
DE Heat tolerance; Cold tolerance; Latitudinal clines; Hardening capacity;
   D. leontia; D. kikkawai
ID STRESS RESISTANCE TRAITS; UPPER THERMAL LIMITS; EASTERN AUSTRALIA;
   HARDENING CAPACITY; GENETIC-VARIATION; HEAT-RESISTANCE; LIFE-HISTORY;
   MELANOGASTER; ACCLIMATION; TEMPERATURE
AB Understanding adaptations to climatic stresses has been a longstanding issue in evolutionary biology. Clinal patterns for stress tolerance traits at interspecific as well as intraspecific levels provide an opportunity to comprehend the adaptive divergence acquired in the closely related species among different geographical populations. In the present study, we investigated the geographical differences for basal as well as induced thermal tolerance (hardening) in two sympatric sibling Drosophila species (D. leontia and D. kikkawai) along a latitudinal transect (South: 8A degrees 06'N to North: 32A degrees 40'N) across India. A higher relative abundance of D. leontia was observed in the southern localities (tropical) while D. kikkawai was more abundant in the northern localities (sub-tropical). Both the species showed a negative cline for heat tolerance along the latitude i.e. following a trend of increased tolerance level in the southern populations compared to northern ones. Contrarily, a positive cline for cold tolerance was evident in D. kikkawai, while such intra-specific population differences were non-significant in D. leontia. Further, we found the evidence for heat and cold hardening effects only in D. kikkawai. In D. kikkawai, higher hardening capacity for heat as well as cold tolerance was observed in northern populations compared to southern populations, despite lower basal heat tolerance in northern populations. In conclusion, clinal patterns for hardening capacity for heat and cold tolerance in D. kikkawai while absence of the same in D. leontia suggest divergent evolutionary history of these two sympatric sibling species.
C1 [Ranga, Poonam; Mrinal, Nirotpal] South Asian Univ, Fac Life Sci & Biotechnol, Mol Biol Lab, New Delhi 110021, India.
   [Prakash, Ravi] Maharshi Dayanand Univ, Dept Genet, Rohtak 124001, Haryana, India.
C3 South Asian University (SAU); Maharshi Dayanand University
RP Ranga, P (corresponding author), South Asian Univ, Fac Life Sci & Biotechnol, Mol Biol Lab, New Delhi 110021, India.
EM prgenetics@yahoo.in
RI Prakash, Ravi/JYP-0200-2024
OI RANGA, POONAM/0000-0002-0978-4759
CR Addo-Bediako A, 2000, P ROY SOC B-BIOL SCI, V267, P739, DOI 10.1098/rspb.2000.1065
   Angilletta MJ, 2009, BIO HABIT, P1, DOI 10.1093/acprof:oso/9780198570875.001.1
   Angilletta MJ, 2003, TRENDS ECOL EVOL, V18, P234, DOI 10.1016/S0169-5347(03)00087-9
   [Anonymous], CLIM TABL OBS IND
   [Anonymous], 1987, Temperature biology of animals
   [Anonymous], 2006, A guide to species identification and use
   Arthur AL, 2008, J EVOLUTION BIOL, V21, P1470, DOI 10.1111/j.1420-9101.2008.01617.x
   Berrigan D, 1998, BIOL J LINN SOC, V64, P449, DOI 10.1006/bijl.1998.0232
   Chown SL, 2007, ADV INSECT PHYSIOL, V33, P50
   Cooper BS, 2010, J EVOLUTION BIOL, V23, P2346, DOI 10.1111/j.1420-9101.2010.02095.x
   Cooper BS, 2012, J THERM BIOL, V37, P211, DOI 10.1016/j.jtherbio.2012.01.001
   Gibert P, 2001, PHYSIOL BIOCHEM ZOOL, V74, P429, DOI 10.1086/320429
   Guerra D, 1997, GENET SEL EVOL, V29, P497, DOI 10.1051/gse:19970406
   Hoffmann AA, 2010, J EXP BIOL, V213, P870, DOI 10.1242/jeb.037630
   Hoffmann AA, 2005, FUNCT ECOL, V19, P222, DOI 10.1111/j.1365-2435.2005.00959.x
   HOFFMANN AA, 1993, AM NAT, V142, pS93, DOI 10.1086/285525
   Hoffmann AA, 2003, J THERM BIOL, V28, P175, DOI 10.1016/S0306-4565(02)00057-8
   Hoffmann AA, 2002, ECOL LETT, V5, P614, DOI 10.1046/j.1461-0248.2002.00367.x
   HOFFMANN AA, 1990, J INSECT PHYSIOL, V36, P885, DOI 10.1016/0022-1910(90)90176-G
   Hoffmann AA, 2007, GENETICA, V129, P133, DOI 10.1007/s10709-006-9010-z
   Karan D, 1998, ECOL ENTOMOL, V23, P391, DOI 10.1046/j.1365-2311.1998.00157.x
   Kellermann V, 2012, P NATL ACAD SCI USA, V109, P16228, DOI 10.1073/pnas.1207553109
   Kellermann V, 2009, SCIENCE, V325, P1244, DOI 10.1126/science.1175443
   Kellett M, 2005, FUNCT ECOL, V19, P853, DOI 10.1111/j.1365-2435.2005.01025.x
   KIMURA MT, 1988, EVOLUTION, V42, P1288, DOI [10.2307/2409012, 10.1111/j.1558-5646.1988.tb04188.x]
   Lemeunier F., 1986, Genetics and Biology of Drosophila, V3e, P147
   LEVINS R, 1969, AM NAT, V103, P483, DOI 10.1086/282616
   Lindsey CF, 2012, GENETICA, V139, P1331
   LOESCHCKE V, 1994, BIOL J LINN SOC, V52, P83, DOI 10.1111/j.1095-8312.1994.tb00980.x
   Mitchell KA, 2011, FUNCT ECOL, V25, P661, DOI 10.1111/j.1365-2435.2010.01821.x
   Overgaard J, 2011, AM NAT, V178, pS80, DOI 10.1086/661780
   Ragland GJ, 2008, EVOLUTION, V62, P1345, DOI 10.1111/j.1558-5646.2008.00367.x
   Rako L, 2006, J INSECT PHYSIOL, V52, P94, DOI 10.1016/j.jinsphys.2005.09.007
   Ramniwas S, 2012, J INSECT PHYSIOL, V58, P1525, DOI 10.1016/j.jinsphys.2012.08.009
   Sarup P, 2010, J EVOLUTION BIOL, V23, P957, DOI 10.1111/j.1420-9101.2010.01965.x
   Schilthuizen M, 2014, EVOL APPL, V7, P56, DOI 10.1111/eva.12116
   Sgrò CM, 2010, J EVOLUTION BIOL, V23, P2484, DOI 10.1111/j.1420-9101.2010.02110.x
   Stratman R, 1998, FUNCT ECOL, V12, P965, DOI 10.1046/j.1365-2435.1998.00270.x
   TSACAS L, 1977, ANN SOC ENTOMOL FR, V13, P675
NR 39
TC 9
Z9 10
U1 0
U2 18
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0269-7653
EI 1573-8477
J9 EVOL ECOL
JI Evol. Ecol.
PD FEB
PY 2017
VL 31
IS 1
BP 93
EP 117
DI 10.1007/s10682-016-9880-1
PG 25
WC Ecology; Evolutionary Biology; Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Evolutionary Biology; Genetics &
   Heredity
GA EK6EE
UT WOS:000394017000007
DA 2025-01-10
ER

PT J
AU Perpinyà-Vallès, M
   Machefer, M
   Ameztegui, A
   Escorihuela, MJ
   Brandt, M
   Romero, L
AF Perpinya-Valles, Marti
   Machefer, Melissande
   Ameztegui, Aitor
   Escorihuela, Maria Jose
   Brandt, Martin
   Romero, Laia
TI Quantification of Carbon Stocks at the Individual Tree Level in Semiarid
   Regions in Africa
SO JOURNAL OF REMOTE SENSING
LA English
DT Article
ID ABOVEGROUND BIOMASS; FORESTS; MAP
AB Quantifying tree resources is essential for effectively implementing climate adaptation strategies and supporting local communities. In the Sahel, where tree presence is scattered, measuring carbon becomes challenging. We present an approach to estimating aboveground carbon (AGC) at the individual tree level using a combination of very high-resolution imagery, field-collected data, and machine learning algorithms. We populated an AGC database from in situ measurements using allometric equations and carbon conversion factors. We extracted satellite spectral information and tree crown area upon segmenting each tree crown. We then trained and validated an artificial neural network to predict AGC from these variables. The validation at the tree level resulted in an R2 of 0.66, a root mean square error (RMSE) of 373.85 kg, a relative RMSE of 78.6%, and an overestimation bias of 47 kg. When aggregating results at coarser spatial resolutions, the relative RMSE decreased for all areas, with the median value at the plot level being under 30% in all cases. Within our areas of study, we obtained a total of 3,900 Mg, with an average carbon content per tree of 330 kg. A benchmarking analysis against published carbon maps showed that 9 out of 10 underestimate AGC stocks, in comparison to our results, in the areas of study. An additional comparison against a method using only crown area to determine AGC showed an improved performance, including spectral signature. This study improves crown-based biomass estimations for areas where unmanned aerial vehicle or height data are not available and validates at the individual tree level using solely satellite imagery.
C1 [Perpinya-Valles, Marti; Machefer, Melissande; Romero, Laia] Lobelia Earth SL, Barcelona 08005, Spain.
   [Perpinya-Valles, Marti; Ameztegui, Aitor] Univ Lleida, Dept Agr & Forest Sci & Engn, Lleida 25198, Spain.
   [Ameztegui, Aitor] Joint Res Unit CTFC AGROTECNIO CERCA, Solsona 25280, Spain.
   [Escorihuela, Maria Jose] isardSAT SL, Barcelona 08005, Spain.
   [Brandt, Martin] Univ Copenhagen, Dept Geosci & Nat Resource Management, Copenhagen, Denmark.
   [Machefer, Melissande] European Commiss, Joint Res Ctr, Ispra, VA, Italy.
C3 Universitat de Lleida; University of Copenhagen; European Commission
   Joint Research Centre; EC JRC ISPRA Site
RP Perpinyà-Vallès, M (corresponding author), Lobelia Earth SL, Barcelona 08005, Spain.; Perpinyà-Vallès, M (corresponding author), Univ Lleida, Dept Agr & Forest Sci & Engn, Lleida 25198, Spain.
EM marti.perpinya@lobelia.earth
FU Intermon Oxfam Spain; AGAUR [2021 DI 121]; MCIN AEI [DIN2020-010982];
   European Union "NextGenerationEU/PRTR"; Generalitat de Catalunya; ESA
   Network of Resources Initiative
FX This work was partly conducted in the Jeunesse Sahelienne pour l'Action
   Climatique (JESAC) project, which is funded by Intermon Oxfam Spain, and
   under Industrial PhD grants AGAUR (2021 DI 121) and DIN2020-010982
   financed by MCIN AEI 10.13039/501100011033 and by European Union
   "NextGenerationEU/PRTR". Aitor Ameztegui is funded by a Serra-Hunter
   fellowship from Generalitat de Catalunya. This work was supported by the
   ESA Network of Resources Initiative.
CR Abdi AM, 2022, J REMOTE SENS-PRC, V2022, DOI 10.34133/2022/9835284
   Anderegg WRL, 2020, SCIENCE, V368, P1327, DOI 10.1126/science.aaz7005
   [Anonymous], 2019, Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories
   Avitabile V, 2016, GLOBAL CHANGE BIOL, V22, P1406, DOI 10.1111/gcb.13139
   Axelsson CR, 2017, BIOGEOSCIENCES, V14, P3239, DOI 10.5194/bg-14-3239-2017
   Bouvet A, 2018, REMOTE SENS ENVIRON, V206, P156, DOI 10.1016/j.rse.2017.12.030
   Brandt M, 2020, NATURE, V587, P78, DOI 10.1038/s41586-020-2824-5
   Brandt M, 2015, GLOBAL CHANGE BIOL, V21, P1610, DOI 10.1111/gcb.12807
   Brown S, 1997, 134 FAO
   Chave J, 2005, OECOLOGIA, V145, P87, DOI 10.1007/s00442-005-0100-x
   Chave J, 2014, GLOBAL CHANGE BIOL, V20, P3177, DOI 10.1111/gcb.12629
   Colgan MS, 2014, TREES-STRUCT FUNCT, V28, P91, DOI 10.1007/s00468-013-0932-7
   David RM, 2022, REMOTE SENS ENVIRON, V282, DOI 10.1016/j.rse.2022.113232
   Dubayah RO, 2023, ORNL DAAC, DOI 10.3334/ORNLDAAC/2299
   Fagan ME, 2020, GLOBAL CHANGE BIOL, V26, P4679, DOI 10.1111/gcb.15187
   Forkuor G, 2020, REMOTE SENS ENVIRON, V236, DOI 10.1016/j.rse.2019.111496
   Garzelli A, 2004, INT GEOSCI REMOTE SE, P81
   Gonzalez P, 2001, CLIMATE RES, V17, P217, DOI 10.3354/cr017217
   Hanan NP, 2020, ORNL DAAC, DOI 10.3334/ORNLDAAC/1777
   Harris NL, 2021, NAT CLIM CHANGE, V11, DOI 10.1038/s41558-020-00976-6
   Henry M, 2013, IFOREST, V6, pE1, DOI 10.3832/ifor0901-006
   Henry M, 2011, SILVA FENN, V45, P477, DOI 10.14214/sf.38
   Hiernaux P, 2023, FOREST ECOL MANAG, V529, DOI 10.1016/j.foreco.2022.120653
   Gascón LH, 2019, FORESTS, V10, DOI 10.3390/f10020107
   Magarik YAS, 2020, URBAN FOR URBAN GREE, V47, DOI 10.1016/j.ufug.2019.126481
   Marques P, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11070855
   Mbow C, 2015, REMOTE SENS-BASEL, V7, P4048, DOI 10.3390/rs70404048
   Mugabowindekwe M, 2023, NAT CLIM CHANGE, V13, P91, DOI 10.1038/s41558-022-01544-w
   Pennington RT, 2009, ANNU REV ECOL EVOL S, V40, P437, DOI 10.1146/annurev.ecolsys.110308.120327
   Petrescu AMR, 2012, BIOGEOSCIENCES, V9, P3437, DOI 10.5194/bg-9-3437-2012
   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]
   Santoro M, 2021, CEDA Archive, DOI [10.5285/5f331c418-9f4935b8eb1b836f8a91b8, DOI 10.5285/5F331C418-9F4935B8EB1B836F8A91B8]
   Santoro M., 2018, **DATA OBJECT** **DATA OBJECT**
   Santoro Maurizio, 2023, CEDA, DOI 10.5285/AF60720C1E404A9E9D2C145D2B2EAD4E
   Sha ZY, 2022, COMMUN EARTH ENVIRON, V3, DOI 10.1038/s43247-021-00333-1
   Skole DL, 2021, FORESTS, V12, DOI 10.3390/f12121652
   Steininger M, 2021, MACH LEARN, V110, P2187, DOI 10.1007/s10994-021-06023-5
   Tanabe K., 2006, 2006 IPCC Guidelines for National Greenhouse Gas Inventories
   Tucker C, 2023, NATURE, V615, P80, DOI 10.1038/s41586-022-05653-6
   Vorster AG, 2020, CARBON BAL MANAGE, V15, DOI 10.1186/s13021-020-00143-6
   Weinstein BG, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11111309
   Xu L, 2021, SCI ADV, V7, DOI 10.1126/sciadv.abe9829
   Yao L, 2021, ECOL INDIC, V125, DOI 10.1016/j.ecolind.2021.107591
   Zhao YJ, 2021, INT J APPL EARTH OBS, V101, DOI 10.1016/j.jag.2021.102358
NR 44
TC 0
Z9 0
U1 0
U2 0
PU AMER ASSOC ADVANCEMENT SCIENCE
PI WASHINGTON
PA 1200 NEW YORK AVE, NW, WASHINGTON, DC 20005 USA
EI 2694-1589
J9 J REMOTE SENS-PRC
JI J. Remote Sens.
PD DEC 17
PY 2024
VL 4
AR 0359
DI 10.34133/remotesensing.0359
PG 15
WC Environmental Sciences; Geosciences, Multidisciplinary; Remote Sensing;
   Imaging Science & Photographic Technology
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology; Geology; Remote Sensing; Imaging
   Science & Photographic Technology
GA P6Q0G
UT WOS:001379117900001
OA gold
DA 2025-01-10
ER

PT J
AU Yan, D
   Jin, ZP
   Zhou, YT
   Li, MM
   Zhang, ZH
   Wang, TJ
   Zhuang, BL
   Li, S
   Xie, M
AF Yan, Dan
   Jin, Zhipeng
   Zhou, Yiting
   Li, Mengmeng
   Zhang, Zihan
   Wang, Tijian
   Zhuang, Bingliang
   Li, Shu
   Xie, Min
TI Anthropogenically and meteorologically modulated summertime ozone trends
   and their health implications since China's clean air actions
SO ENVIRONMENTAL POLLUTION
LA English
DT Article
ID TROPOSPHERIC NO2 COLUMNS; SURFACE OZONE; PARTICULATE MATTER; POLLUTION;
   EMISSIONS; SENSITIVITY; CLIMATE; QUALITY; VARIABILITY; SIMULATION
AB Elevated ozone (O-3) has emerged as the major air quality concern since China's clean air actions, offsetting the health benefits gained from improved air quality. Given the shifted ozone chemical regimes and recently boosted extreme weather in China, it's essential to rethink the O-3 trends since 2013 for evaluations of air pollution mitigation policy. Here, we examine the anthropogenically and meteorologically modulated summertime O-3 trends across China at different stages of the clean air actions using multi-source observations combined with multi-model calculations. Ozone increases steadily in China between 2013-2022, with a fast increase rate of 4.4 mu g m(-3) yr(-1) in Phase I and a much smaller 0.6 mu g m(-3) yr(-1) in Phase II of Action Plan. Results highlight that the deteriorative O-3 pollution in Phase I and early Phase II is dominated by the nonlinear O-3-emission response. Persistent decline in O-3 precursors has shifted its chemical regime in urban areas and began to show a positive influence on ozone mitigation in recent years. Meteorological influence on O-3 variations is minor until 2019 (similar to 10%), but it greatly accelerates or relieves the O-3 pollution after then, showing comparable contribution to emissions. Epidemiological model predicts totally 0.8-3.0 thousand yr(-1) more deaths across China with altered anthropogenic emissions since clean air actions, and additional health burdens by -1.5-0.3 thousand yr(-1) from perturbated meteorology. This study calls for stringent emission control and climate adaptation strategies to attain the ozone pollution mitigation in China.
C1 [Yan, Dan; Jin, Zhipeng; Zhou, Yiting; Li, Mengmeng; Zhang, Zihan; Wang, Tijian; Zhuang, Bingliang; Li, Shu] Nanjing Univ, Sch Atmospher Sci, Nanjing 210023, Peoples R China.
   [Li, Mengmeng] Frontiers Sci Ctr Crit Earth Mat Cycling, Nanjing 210023, Peoples R China.
   [Xie, Min] Nanjing Normal Univ, Sch Environm, Nanjing 210023, Peoples R China.
C3 Nanjing University; Nanjing Normal University
RP Li, MM (corresponding author), Nanjing Univ, Sch Atmospher Sci, Nanjing 210023, Peoples R China.
EM mengmengli2015@nju.edu.cn
RI Zhang, Zihan/Y-7713-2018; Li, Mengmeng/Z-3722-2019; Jin,
   Zhipeng/GLN-3206-2022
FU National Key Basic Research Development Program of China
   [2022YFC3701105]; National Natural Science Foundation of China
   [42293322, 41975153]; Research Funds for the Frontiers Science Center
   for Critical Earth Material Cycling, Nanjing University
FX This study is supported by the National Key Basic Research Development
   Program of China (2022YFC3701105) , the National Natural Science
   Foundation of China (42293322, 41975153) and the Research Funds for the
   Frontiers Science Center for Critical Earth Material Cycling, Nanjing
   University.
CR Chen L, 2020, SCI TOTAL ENVIRON, V744, DOI 10.1016/j.scitotenv.2020.140837
   Chen X, 2020, ATMOS ENVIRON, V220, DOI 10.1016/j.atmosenv.2019.117060
   Chen XK, 2021, GEOPHYS RES LETT, V48, DOI 10.1029/2021GL092816
   Council C.S., 2013, Action Plan of Air Pollution Prevention and Control
   Council C.S., 2018, Three-year Action Plan for Blue Sky Protection
   Dang RJ, 2021, SCI TOTAL ENVIRON, V754, DOI 10.1016/j.scitotenv.2020.142394
   Dang RJ, 2019, GEOPHYS RES LETT, V46, P12511, DOI 10.1029/2019GL084605
   Fan SJ, 2020, SCI TOTAL ENVIRON, V701, DOI 10.1016/j.scitotenv.2019.134721
   Grell GA, 2002, FOURTH CONFERENCE ON ATMOSPHERIC CHEMISTRY: URBAN, REGIONAL AND GLOBAL SCALE IMPACTS OF AIR POLLUTANTS, P224
   Guenther A, 2006, ATMOS CHEM PHYS, V6, P3181, DOI 10.5194/acp-6-3181-2006
   Gupta M, 2015, ATMOS ENVIRON, V122, P220, DOI 10.1016/j.atmosenv.2015.09.039
   Han H, 2020, ATMOS CHEM PHYS, V20, P203, DOI 10.5194/acp-20-203-2020
   Hersbach H, 2020, Q J ROY METEOR SOC, V146, P1999, DOI 10.1002/qj.3803
   Hu JL, 2016, ATMOS CHEM PHYS, V16, P10333, DOI 10.5194/acp-16-10333-2016
   Huang J, 2018, LANCET PLANET HEALTH, V2, pE313, DOI 10.1016/S2542-5196(18)30141-4
   Irie H, 2012, ATMOS MEAS TECH, V5, P2403, DOI 10.5194/amt-5-2403-2012
   Jin XM, 2015, J GEOPHYS RES-ATMOS, V120, P7229, DOI 10.1002/2015JD023250
   Kang MJ, 2021, ENVIRON SCI TECH LET, V8, P289, DOI 10.1021/acs.estlett.1c00036
   Li C., 2022, Accelerated Reduction of Air Pollutants in China, 2017-2020, V803
   Li K, 2020, ATMOS CHEM PHYS, V20, P11423, DOI 10.5194/acp-20-11423-2020
   Li K, 2019, P NATL ACAD SCI USA, V116, P422, DOI 10.1073/pnas.1812168116
   Li M., 2023, Sci. Bull.
   Li M, 2019, ATMOS CHEM PHYS, V19, P8897, DOI 10.5194/acp-19-8897-2019
   Li MM, 2021, ATMOS ENVIRON, V246, DOI 10.1016/j.atmosenv.2020.118130
   Li MM, 2017, J GEOPHYS RES-ATMOS, V122, P3116, DOI 10.1002/2016JD026182
   Liu F, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/11/114002
   Liu J, 2021, ENVIRON POLLUT, V277, DOI 10.1016/j.envpol.2021.116770
   Liu YM, 2020, ATMOS CHEM PHYS, V20, P6305, DOI 10.5194/acp-20-6305-2020
   Liu YM, 2020, ATMOS CHEM PHYS, V20, P6323, DOI 10.5194/acp-20-6323-2020
   Liu Y, 2008, ATMOS CHEM PHYS, V8, P1531, DOI 10.5194/acp-8-1531-2008
   Liu YX, 2023, ENVIRON SCI TECHNOL, V57, P8954, DOI 10.1021/acs.est.3c00054
   Lu X, 2020, ENVIRON SCI TECH LET, V7, P240, DOI 10.1021/acs.estlett.0c00171
   Lu X, 2019, ATMOS CHEM PHYS, V19, P8339, DOI 10.5194/acp-19-8339-2019
   Lu X, 2018, ENVIRON SCI TECH LET, V5, P487, DOI 10.1021/acs.estlett.8b00366
   Luo M, 2018, GEOPHYS RES LETT, V45, P13060, DOI 10.1029/2018GL080306
   Ma CQ, 2019, J GEOPHYS RES-ATMOS, V124, P7393, DOI 10.1029/2019JD030421
   Ma MC, 2019, ATMOS CHEM PHYS, V19, P12195, DOI 10.5194/acp-19-12195-2019
   Maji KJ, 2021, ENVIRON POLLUT, V269, DOI 10.1016/j.envpol.2020.116183
   MEE, 2013, Chinese environmental statistical bulletin
   Mozaffar A, 2020, CURR POLLUT REP, V6, P250, DOI 10.1007/s40726-020-00149-1
   Nie DY, 2021, ATMOS RES, V249, DOI 10.1016/j.atmosres.2020.105328
   Qu YW, 2018, ADV ATMOS SCI, V35, P1381, DOI 10.1007/s00376-018-8027-4
   Racherla PN, 2009, ENVIRON SCI TECHNOL, V43, P571, DOI 10.1021/es800854f
   Saathoff H, 2001, GEOPHYS RES LETT, V28, P1957, DOI 10.1029/2000GL012619
   Seinfeld J. H., 2006, Atmospheric chemistry and physics: from air pollution to climate change
   Shah V, 2020, ATMOS CHEM PHYS, V20, P1483, DOI 10.5194/acp-20-1483-2020
   Shen L, 2019, ATMOS CHEM PHYS, V19, P6551, DOI 10.5194/acp-19-6551-2019
   Silver B, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aae718
   Smith A, 2011, B AM METEOROL SOC, V92, P704, DOI 10.1175/2011BAMS3015.1
   Sun L.H., 2022, Influence of Using Different Chemical Mechanisms on Simulations of Ozone and its Precursors in the Troposphere of Shanghai, China, V289
   Tai APK, 2010, ATMOS ENVIRON, V44, P3976, DOI 10.1016/j.atmosenv.2010.06.060
   Underwood GM, 2001, J GEOPHYS RES-ATMOS, V106, P18055, DOI 10.1029/2000JD900552
   Wang HL, 2021, J GEOPHYS RES-ATMOS, V126, DOI 10.1029/2020JD034317
   Wang P, 2008, ATMOS RES, V89, P289, DOI 10.1016/j.atmosres.2008.03.013
   Wang PF, 2019, SCI TOTAL ENVIRON, V662, P297, DOI 10.1016/j.scitotenv.2019.01.227
   Wang WN, 2021, ATMOS CHEM PHYS, V21, P7253, DOI 10.5194/acp-21-7253-2021
   Wang WJ, 2022, ATMOS CHEM PHYS, V22, P8935, DOI 10.5194/acp-22-8935-2022
   Watson L, 2016, ATMOS ENVIRON, V142, P271, DOI 10.1016/j.atmosenv.2016.07.051
   Wei W, 2019, ATMOS ENVIRON, V218, DOI 10.1016/j.atmosenv.2019.116984
   Wu K, 2022, ENVIRON POLLUT, V300, DOI 10.1016/j.envpol.2022.118914
   Xiao QY, 2022, ENVIRON SCI TECHNOL, V56, P6922, DOI 10.1021/acs.est.1c04548
   Xu BY, 2022, ATMOS RES, V279, DOI 10.1016/j.atmosres.2022.106384
   Xu BY, 2022, CHIN SCI B-CHIN, V67, P784, DOI 10.1360/TB-2021-1091
   Yan D, 2023, ATMOS POLLUT RES, V14, DOI 10.1016/j.apr.2023.101843
   [叶伟鹏 Ye Weipeng], 2020, [环境科学学报, Acta Scientiae Circumstantiae], V40, P2644
   Yin H, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/ac3e22
   Zaveri RA, 1999, J GEOPHYS RES-ATMOS, V104, P30387, DOI 10.1029/1999JD900876
   Zhang L., 2023, Science of the Total Environment, V903
   Zhao H, 2022, SCI TOTAL ENVIRON, V817, DOI 10.1016/j.scitotenv.2022.153011
   Zhao T, 2018, ENVIRON RES, V165, P459, DOI 10.1016/j.envres.2018.04.015
   Zheng B, 2021, EARTH SYST SCI DATA, V13, P2895, DOI 10.5194/essd-13-2895-2021
   Zheng B, 2018, ATMOS CHEM PHYS, V18, P14095, DOI 10.5194/acp-18-14095-2018
   Zheng YX, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa8a32
NR 73
TC 9
Z9 9
U1 21
U2 58
PU ELSEVIER SCI LTD
PI London
PA 125 London Wall, London, ENGLAND
SN 0269-7491
EI 1873-6424
J9 ENVIRON POLLUT
JI Environ. Pollut.
PD FEB 15
PY 2024
VL 343
AR 123234
DI 10.1016/j.envpol.2023.123234
EA JAN 2024
PG 11
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA GN7G8
UT WOS:001153410100001
PM 38154777
DA 2025-01-10
ER

PT J
AU Yin, J
   Xue, Y
   Xu, BD
   Ji, YP
   Zhang, CL
   Ren, YP
   Chen, Y
AF Yin, Jie
   Xue, Ying
   Xu, Binduo
   Ji, Yupeng
   Zhang, Chongliang
   Ren, Yiping
   Chen, Yong
TI Potential impacts of ocean warming on energy flow and fisheries
   production in an overexploited ecosystem: Implication for effective
   fisheries management
SO ECOLOGICAL INDICATORS
LA English
DT Article
DE Ocean warming; Fisheries management; Fisheries ecosystems; Ecopath with
   Ecosim
ID CLIMATE-CHANGE; MARINE FISHERIES; TROPHIC AMPLIFICATION; FISH
   PRODUCTION; VULNERABILITY; MODELS; ECOPATH; TRENDS; GROWTH; SHELF
AB The influences of ocean warming on marine lives have accelerated over the 21st century, greatly altering the structure and function of marine food webs and causing distributional shifts, species invasions, and changes in productivity. It is imperative to clarify the overall ecosystem responses to ocean warming and develop fisheries management strategies adaptive to the ecosystem changes. In this study, the potential impacts of ocean warming on trophic structure, energy flows, and fisheries production of an overexploited ecosystem were examined, and the effectiveness of fisheries management in mitigating warming impacts were also evaluated. We constructed a mass-balance food web model in Haizhou Bay and simulated three climate scenarios (RCPs 2.6, 4.5, and 8.5) along with different levels of fishing pressure, in order to examine the ecosystem responses to the combined changes in fishing and climate changes. Results showed that the total biomass of commercial species and fisheries catches would decline with rising temperature, especially under the RCP8.5 scenario. Ocean warming could induce lower trophic transfer efficiency and decrease energy recycling capacity within the food web, leading to large losses in total biomass and total production. Reducing fishing intensity could help mitigate the negative effects of ocean warming on fisheries productivity, but was insufficient to maintain ecological properties. Moreover, the effectiveness of such alternative measures would be diminished with increased greenhouse gas emissions, especially under the climate scenario of RCP8.5. The findings of this study highlight the need to slow the rise of sea temperature and implement climate-adaptive fisheries management in the future.
C1 [Yin, Jie; Xue, Ying; Xu, Binduo; Ji, Yupeng; Zhang, Chongliang; Ren, Yiping] Ocean Univ China, Coll Fisheries, Lab Fisheries Ecosyst Monitoring & Assessment, Qingdao 266003, Peoples R China.
   [Ren, Yiping] Pilot Natl Lab Marine Sci & Technol Qingdao, Lab Marine Fisheries & Food Prod Proc, Qingdao 266237, Peoples R China.
   [Yin, Jie; Xue, Ying; Xu, Binduo; Ji, Yupeng; Zhang, Chongliang; Ren, Yiping] Minist Educ, Field Observat Res Stn Haizhou Bay Fishery Ecosyst, Qingdao 266003, Peoples R China.
   [Yin, Jie; Chen, Yong] SUNY Stony Brook, Sch Marine & Atmospher Sci, Stony Brook, NY 11794 USA.
   [Zhang, Chongliang] Ocean Univ China, Fisheries Coll, 5 Yushan Rd, Qingdao 266003, Peoples R China.
C3 Ocean University of China; Laoshan Laboratory; State University of New
   York (SUNY) System; Stony Brook University; Ocean University of China
RP Zhang, CL (corresponding author), Ocean Univ China, Coll Fisheries, Lab Fisheries Ecosyst Monitoring & Assessment, Qingdao 266003, Peoples R China.; Zhang, CL (corresponding author), Minist Educ, Field Observat Res Stn Haizhou Bay Fishery Ecosyst, Qingdao 266003, Peoples R China.; Zhang, CL (corresponding author), Ocean Univ China, Fisheries Coll, 5 Yushan Rd, Qingdao 266003, Peoples R China.
EM zhangclg@ouc.edu.cn
FU National Key R & D Program of China [2019YFD0901204, 2019YFD0901205]
FX This research was funded by the National Key R & D Program of China
   [2019YFD0901204] , [2019YFD0901205] . We extend our gratitude to Dr.
   Haiqing Yu for his provision of the FVCOM data.
CR Ahrens RNM, 2012, FISH FISH, V13, P41, DOI 10.1111/j.1467-2979.2011.00432.x
   Allison EH, 2009, FISH FISH, V10, P173, DOI 10.1111/j.1467-2979.2008.00310.x
   Anderson CM, 2019, FISH FISH, V20, P268, DOI 10.1111/faf.12339
   Angilletta MJ, 2006, J THERM BIOL, V31, P541, DOI 10.1016/j.jtherbio.2006.06.002
   [Anonymous], 1986, Growth and development: ecosystems phenomenology
   [Anonymous], 2014, IPCC 5 ASSESSMENT SY, P167
   Bastardie F, 2022, FRONT MAR SCI, V9, DOI 10.3389/fmars.2022.947150
   Bentley JW, 2017, ECOL MODEL, V360, P94, DOI 10.1016/j.ecolmodel.2017.07.002
   Bernhardt JR, 2013, ANNU REV MAR SCI, V5, P371, DOI 10.1146/annurev-marine-121211-172411
   Bindoff N. L., 2022, The Ocean and Cryosphere in a Changing Climate, P447, DOI [DOI 10.1017/9781009157964.007, 10.1017/9781009157964.007]
   Blanchard JL, 2012, PHILOS T R SOC B, V367, P2979, DOI 10.1098/rstb.2012.0231
   Bopp L, 2013, BIOGEOSCIENCES, V10, P6225, DOI 10.5194/bg-10-6225-2013
   Brander KM, 2007, P NATL ACAD SCI USA, V104, P19709, DOI 10.1073/pnas.0702059104
   Brander K, 2010, J MARINE SYST, V79, P389, DOI 10.1016/j.jmarsys.2008.12.015
   Brodziak J, 2002, B MAR SCI, V70, P589
   Bryndum-Buchholz A, 2021, FISH FISH, V22, P1248, DOI 10.1111/faf.12586
   Bryndum-Buchholz A, 2020, FACETS, V5, P105, DOI 10.1139/facets-2019-0035
   Burnham KP, 2004, SOCIOL METHOD RES, V33, P261, DOI 10.1177/0049124104268644
   Chagaris DD, 2015, MAR COAST FISH, V7, P44, DOI 10.1080/19425120.2014.966216
   Cheung WWL, 2018, GLOBAL CHANGE BIOL, V24, P5149, DOI 10.1111/gcb.14390
   Cheung WWL, 2016, SCIENCE, V354, P1591, DOI 10.1126/science.aag2331
   Cheung WWL, 2013, NATURE, V497, P365, DOI 10.1038/nature12156
   Cheung WWL, 2010, GLOBAL CHANGE BIOL, V16, P24, DOI 10.1111/j.1365-2486.2009.01995.x
   Christensen V, 1998, J FISH BIOL, V53, P128, DOI 10.1111/j.1095-8649.1998.tb01023.x
   CHRISTENSEN V, 1992, ECOL MODEL, V61, P169, DOI 10.1016/0304-3800(92)90016-8
   Christensen V., 2008, Ecopath With Ecosim 6 User Guide, P235
   Chust G, 2014, GLOBAL CHANGE BIOL, V20, P2124, DOI 10.1111/gcb.12562
   Doney SC, 2012, ANNU REV MAR SCI, V4, P11, DOI 10.1146/annurev-marine-041911-111611
   ELLIOTT JM, 1975, FRESHWATER BIOL, V5, P287, DOI 10.1111/j.1365-2427.1975.tb00142.x
   Farmery AK, 2019, J ENVIRON MANAGE, V249, DOI 10.1016/j.jenvman.2019.07.001
   Fath BD, 2019, OCEAN COAST MANAGE, V174, P1, DOI 10.1016/j.ocecoaman.2019.03.007
   FINN JT, 1980, ECOLOGY, V61, P562, DOI 10.2307/1937422
   Free CM, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0224347
   Free CM, 2019, SCIENCE, V363, P979, DOI 10.1126/science.aau1758
   Froese R, 2022, FishBase
   Fulton EA, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0084242
   Gaines SD, 2018, SCI ADV, V4, DOI 10.1126/sciadv.aao1378
   Gårdmark A, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0449
   Gattuso JP, 2018, FRONT MAR SCI, V5, DOI 10.3389/fmars.2018.00337
   Gazeau F, 2007, GEOPHYS RES LETT, V34, DOI 10.1029/2006GL028554
   Gerber LR, 2014, ECOSPHERE, V5, DOI 10.1890/ES13-00336.1
   Guo B.H., 2004, Marine Environment of China Offshore and Adjacent Sea Area
   Hall SJ, 2004, FISH FISH, V5, P1, DOI 10.1111/j.1467-2960.2004.00133.x
   Halpern BS, 2008, SCIENCE, V319, P948, DOI 10.1126/science.1149345
   Halpern BS, 2007, CONSERV BIOL, V21, P1301, DOI 10.1111/j.1523-1739.2007.00752.x
   Han Y., 2018, CHIN RURAL EC, V9, P14
   Hansen G, 2016, REG ENVIRON CHANGE, V16, P527, DOI 10.1007/s10113-015-0760-y
   Henson SA, 2017, NAT COMMUN, V8, DOI 10.1038/ncomms14682
   IPCC, 2018, Global Warming of 1.5 ℃
   Jackson JBC, 2001, SCIENCE, V293, P629, DOI 10.1126/science.1059199
   Karnauskas M, 2021, FISH FISH, V22, P646, DOI 10.1111/faf.12538
   Koskela J, 1997, AQUACULT INT, V5, P351, DOI 10.1023/A:1018316224253
   Kroeker KJ, 2013, GLOBAL CHANGE BIOL, V19, P1884, DOI 10.1111/gcb.12179
   Lam VWY, 2020, NAT REV EARTH ENV, V1, P440, DOI 10.1038/s43017-020-0071-9
   Lam VWY, 2016, SCI REP-UK, V6, DOI 10.1038/srep32607
   [李雪童 Li Xuetong], 2021, [中国水产科学, Journal of Fishery Sciences of China], V28, P451
   Link JS, 2010, ECOL MODEL, V221, P1580, DOI 10.1016/j.ecolmodel.2010.03.012
   Liu Jing Liu Jing, 2011, Biodiversity Science, V19, P764, DOI 10.3724/SP.J.1003.2011.06164
   Liu Q, 2012, J OCEAN U CHINA, V11, P557, DOI 10.1007/s11802-012-2099-z
   Mackinson S, 2009, ECOL MODEL, V220, P2972, DOI 10.1016/j.ecolmodel.2008.10.021
   Martín-López B, 2014, ECOL INDIC, V37, P220, DOI 10.1016/j.ecolind.2013.03.003
   Melnychuk MC, 2017, P NATL ACAD SCI USA, V114, P178, DOI 10.1073/pnas.1609915114
   Muñoz NJ, 2015, NAT CLIM CHANGE, V5, P163, DOI 10.1038/NCLIMATE2473
   National Marine Data and Information Service, 2020, Blue Book on Marine Climate Chane in China
   ODUM EP, 1985, BIOSCIENCE, V35, P419, DOI 10.2307/1310021
   Odum WE., 1975, Estuarine Research, P265
   [欧阳力剑 OUYANG Li-jian], 2010, [渔业科学进展, Progress in Fishery Sciences], V31, P23
   Palomares MLD., 2020, Sealifebase
   Pauly D, 1998, SCIENCE, V279, P860, DOI 10.1126/science.279.5352.860
   Perry RI, 2010, J MARINE SYST, V79, P427, DOI 10.1016/j.jmarsys.2008.12.017
   Planque B, 2010, J MARINE SYST, V79, P403, DOI 10.1016/j.jmarsys.2008.12.018
   Pörtner HO, 2008, SCIENCE, V322, P690, DOI 10.1126/science.1163156
   Poloczanska ES, 2016, FRONT MAR SCI, V3, DOI 10.3389/fmars.2016.00062
   Poloczanska ES, 2013, NAT CLIM CHANGE, V3, P919, DOI [10.1038/nclimate1958, 10.1038/NCLIMATE1958]
   Punt AE, 2016, FISH FISH, V17, P303, DOI 10.1111/faf.12104
   Punt AE, 2014, ICES J MAR SCI, V71, P2208, DOI 10.1093/icesjms/fst057
   Rhein M, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P255
   Saint-Béat B, 2015, ECOL INDIC, V52, P458, DOI 10.1016/j.ecolind.2014.12.017
   Scott Erin, 2016, SoftwareX, V5, P25, DOI 10.1016/j.softx.2016.02.002
   Seabra R, 2015, SCI REP-UK, V5, DOI 10.1038/srep12930
   Serpetti N, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-13220-7
   Shen GM, 2014, MAR POLICY, V44, P265, DOI 10.1016/j.marpol.2013.09.012
   Skern-Mauritzen M, 2016, FISH FISH, V17, P165, DOI 10.1111/faf.12111
   Smith ADM, 2011, SCIENCE, V333, P1147, DOI 10.1126/science.1209395
   Stock CA, 2014, BIOGEOSCIENCES, V11, P7125, DOI 10.5194/bg-11-7125-2014
   Stortini CH, 2015, ICES J MAR SCI, V72, P1731, DOI 10.1093/icesjms/fsv022
   Su S, 2020, FISH FISH, V21, P435, DOI 10.1111/faf.12439
   Sumaila UR, 2020, FRONT MAR SCI, V7, DOI 10.3389/fmars.2020.00523
   Sun M, 2023, FISH FISH, V24, P142, DOI 10.1111/faf.12715
   Tanaka K, 2016, FISH RES, V177, P137, DOI 10.1016/j.fishres.2016.01.010
   [唐议 TANG Yi], 2009, [资源科学, Resources Science], V31, P1061
   Townsend H, 2019, FRONT MAR SCI, V6, DOI 10.3389/fmars.2019.00641
   Tsoukali S, 2016, MAR ECOL PROG SER, V555, P151, DOI 10.3354/meps11758
   ULANOWICZ RE, 1980, J THEOR BIOL, V85, P223, DOI 10.1016/0022-5193(80)90019-3
   Ulanowicz RE, 2004, COMPUT BIOL CHEM, V28, P321, DOI 10.1016/j.compbiolchem.2004.09.001
   Ullah H, 2018, PLOS BIOL, V16, DOI 10.1371/journal.pbio.2003446
   Walther GR, 2009, TRENDS ECOL EVOL, V24, P686, DOI 10.1016/j.tree.2009.06.008
   Wang YB, 2020, FRONT MAR SCI, V7, DOI 10.3389/fmars.2020.00164
   Wernberg T, 2011, J EXP MAR BIOL ECOL, V400, P7, DOI 10.1016/j.jembe.2011.02.021
   Williams SE, 2008, PLOS BIOL, V6, P2621, DOI 10.1371/journal.pbio.0060325
   Williamson P., 2021, The Impacts of Climate Change, P115, DOI DOI 10.1016/B978-0-12-822373-4.00024-0
   Wilson JR, 2018, CONSERV LETT, V11, DOI 10.1111/conl.12452
   Wo J, 2022, ICES J MAR SCI, V79, P218, DOI 10.1093/icesjms/fsab257
   Wu Xiao-tong, 2019, Yingyong Shengtai Xuebao, V30, P2829, DOI 10.13287/j.1001-9332.201908.033
   Xing QW, 2020, ECOL INDIC, V116, DOI 10.1016/j.ecolind.2020.106479
   Xu BD, 2015, ENVIRON MONIT ASSESS, V187, DOI 10.1007/s10661-015-4483-9
   Yin J, 2023, PROG OCEANOGR, V211, DOI 10.1016/j.pocean.2023.102976
   Yin J, 2021, SCI TOTAL ENVIRON, V763, DOI 10.1016/j.scitotenv.2020.144205
   Yu HG, 2008, MAR POLICY, V32, P351, DOI 10.1016/j.marpol.2007.07.004
   Zhang CL, 2015, ICES J MAR SCI, V72, P2223, DOI 10.1093/icesjms/fsv086
   Zhao X., 2012, Chinese Fishery Statistics
NR 111
TC 0
Z9 1
U1 7
U2 19
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 1470-160X
EI 1872-7034
J9 ECOL INDIC
JI Ecol. Indic.
PD JAN
PY 2024
VL 158
AR 111433
DI 10.1016/j.ecolind.2023.111433
EA DEC 2023
PG 12
WC Biodiversity Conservation; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA FL3U3
UT WOS:001145914000001
OA gold
DA 2025-01-10
ER

PT J
AU Zahed, LM
   Abbaspour, M
AF Zahed, L. Mohaghegh
   Abbaspour, M.
TI Determination and prioritization of criteria to design urban energy
   resilience conceptual model (part 2)
SO INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY
LA English
DT Article
DE Energy resilience; Urban planning; Resilience index; Resilience model;
   Climate change
ID LOW-CARBON; CLIMATE; SYSTEMS; WATER; INFRASTRUCTURE; VULNERABILITY;
   FEASIBILITY; CONSUMPTION; ADAPTATION; INDICATORS
AB Currently, approximately 60% of the global population resides in urban areas. Urban energy resilience can be distinguished into two categories: short-term resilience-the ability to cope with natural disasters, and long-term resilience-the ability to withstand the adverse impacts of climate change. In this study, the outcomes of the previous study, which prioritized 34 sub-criteria based on a four-factor classification: technical/infrastructural, built environment, governance, and socio-cultural aspects of both short and long-term approaches, are employed as the basis for the comprehensive resilience management model. The fuzzy analytic hierarchy process is used to quantify each resilience sub-criterion by considering four aspects of availability, affordability, availability, and acceptability. A novel integrated index, the urban energy circular resilience index, is introduced by utilizing these quantified sub-criteria to evaluate the energy resilience of urban areas. The calculated circular resilience index value for Tehran city as a case study was reported as 33.12 and 26.47% in short-term and long-term resilience, respectively, compared to the ideal city. These findings highlight the need for a detailed action plan to ensure the energy resilience of Tehran. To improve the energy resilience of the city, several action plans have been prioritized, including the generation and provision of energy from renewable sources, energy consumption management, climate adaptation, financial and executive mechanisms to reinforce existing laws, incentive methods, and public awareness. This study's comprehensive resilience model and index enable organizations to manage the energy supply, reduce energy consumption, and mitigate the various effects of climate change effectively.
C1 [Zahed, L. Mohaghegh] Islamic Azad Univ, Dept Nat Resources & Environm, Sci & Res Branch, Tehran, Iran.
   [Abbaspour, M.] Sharif Univ Technol, Fac Mech Engn, Tehran, Iran.
C3 Islamic Azad University; Sharif University of Technology
RP Abbaspour, M (corresponding author), Sharif Univ Technol, Fac Mech Engn, Tehran, Iran.
EM abbpor@sharif.edu
RI Abbaspour, Madjid/U-3256-2019
OI Abbaspour, Madjid/0000-0003-2867-857X; Mohaghegh Zahed,
   Leila/0000-0002-7021-5256
CR Ahmadi S, 2021, RENEW SUST ENERG REV, V144, DOI 10.1016/j.rser.2021.110988
   Ali-Toudert F, 2020, PROG PLANN, V140, DOI 10.1016/j.progress.2019.03.001
   Alibasic H, 2018, SUSTAIN DEV GOAL SER, P1, DOI 10.1007/978-3-319-72568-0
   Ang BW, 2015, RENEW SUST ENERG REV, V42, P1077, DOI 10.1016/j.rser.2014.10.064
   Arghandeh R, 2014, IEEE POWER ENERGY M, V12, P76, DOI 10.1109/MPE.2014.2331902
   Attia S, 2021, ENERG BUILDINGS, V239, DOI 10.1016/j.enbuild.2021.110869
   Bagheri M, 2019, APPL ENERG, V239, P1212, DOI 10.1016/j.apenergy.2019.02.031
   Bene Christophe, 2018, Climate and Development, V10, P116, DOI 10.1080/17565529.2017.1301868
   Berardi U, 2014, APPL ENERG, V115, P411, DOI 10.1016/j.apenergy.2013.10.047
   Bibri Simon Elias, 2020, Energy Informatics, V3, DOI [10.1186/s42162-020-00130-8, 10.1186/s42162-020-00108-6]
   Blum H, 2012, ENERG ECON, V34, P1982, DOI 10.1016/j.eneco.2012.08.013
   Bouffard F, 2008, ENERG POLICY, V36, P4504, DOI 10.1016/j.enpol.2008.09.060
   Buckley N, 2021, ENERGIES, V14, DOI 10.3390/en14154445
   Charoenkit S, 2014, RENEW SUST ENERG REV, V38, P509, DOI 10.1016/j.rser.2014.06.012
   Chaudry M., 2011, BUILDING RESILIENT U
   Cohen S., 2021, Geopolitics History and International Relations, V13, P97, DOI https://doi.org/10.22381/GHIR13120219
   Colenbrander S., 2018, COALIT URBAN T LONDO, V10, P3
   Costa A, 2024, IISE TRANS, V56, P411, DOI 10.1080/24725854.2022.2123116
   de Magalhaes RF, 2022, URBAN CLIM, V46, DOI 10.1016/j.uclim.2022.101296
   Dong KY, 2021, ENERG ECON, V104, DOI 10.1016/j.eneco.2021.105659
   Esfandi S, 2022, SUSTAIN CITIES SOC, V76, DOI 10.1016/j.scs.2021.103458
   Eskridge M., 2019, Contemporary Readings in Law Social Justice, V11, P63, DOI DOI 10.22381/CRLSJ11220199
   Esteban M, 2014, ENERGY, V68, P756, DOI 10.1016/j.energy.2014.02.045
   Fankhauser S, 2018, WIRES CLIM CHANGE, V9, DOI 10.1002/wcc.495
   Faraji J, 2021, SUSTAIN CITIES SOC, V65, DOI 10.1016/j.scs.2020.102578
   Fastenrath S, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11030693
   Feng XH, 2020, CITIES, V104, DOI 10.1016/j.cities.2020.102722
   Gargari MZ, 2021, ENERGY, V221, DOI 10.1016/j.energy.2021.119782
   Gargari MZ, 2020, ENERGY, V196, DOI 10.1016/j.energy.2020.117091
   Ghaffarpour R, 2018, ENERGY, V158, P1092, DOI 10.1016/j.energy.2018.06.022
   Grubler A., 2012, Global Energy Assessment-Toward a Sustainable Future, P1307, DOI [10.1017/cbo9780511793677.024, DOI 10.1017/CBO9780511793677.024]
   He PJ, 2019, ENERG ECON, V84, DOI 10.1016/j.eneco.2019.104569
   Hussain A, 2019, APPL ENERG, V240, P56, DOI 10.1016/j.apenergy.2019.02.055
   Hussey K, 2012, ECOL SOC, V17, DOI 10.5751/ES-04641-170131
   Jabareen Y, 2013, CITIES, V31, P220, DOI 10.1016/j.cities.2012.05.004
   Kennedy C, 2013, ENERG POLICY, V59, P773, DOI 10.1016/j.enpol.2013.04.031
   Khezri R, 2022, IEEE T IND APPL, V58, P2471, DOI 10.1109/TIA.2021.3133340
   Konstantinou C, 2022, IEEE CONSUM ELECTR M, V11, P33, DOI 10.1109/MCE.2021.3055492
   Kruyt B, 2009, ENERG POLICY, V37, P2166, DOI 10.1016/j.enpol.2009.02.006
   Lee T, 2014, ENERG POLICY, V74, P311, DOI 10.1016/j.enpol.2014.08.023
   Lin ST, 2018, BUS STRATEG ENVIRON, V27, P1679, DOI 10.1002/bse.2233
   Linkov Igor, 2013, Environment Systems & Decisions, V33, P471, DOI 10.1007/s10669-013-9485-y
   Manfren M, 2011, APPL ENERG, V88, P1032, DOI 10.1016/j.apenergy.2010.10.018
   Kumar NM, 2020, ENERGIES, V13, DOI 10.3390/en13164193
   Manshadi SD, 2015, IEEE T SMART GRID, V6, P2283, DOI 10.1109/TSG.2015.2397318
   Marique AF, 2014, ENERG BUILDINGS, V82, P114, DOI 10.1016/j.enbuild.2014.07.006
   McGuirk P, 2014, URBAN STUD, V51, P2717, DOI 10.1177/0042098014533732
   Meerow S, 2019, LOCAL ENVIRON, V24, P793, DOI 10.1080/13549839.2019.1645103
   Minne L, 2013, ELECT TRANSMISSION S, P239
   Minuto FD, 2022, RENEW SUST ENERG REV, V168, DOI 10.1016/j.rser.2022.112859
   Molyneaux L, 2012, ENERG POLICY, V47, P188, DOI 10.1016/j.enpol.2012.04.057
   Mulugetta Y, 2010, ENERG POLICY, V38, P7546, DOI 10.1016/j.enpol.2010.05.049
   Mutani G, 2021, ENERG EFFIC, V14, DOI 10.1007/s12053-021-09962-z
   Mutani G, 2021, ENERG BUILDINGS, V240, DOI 10.1016/j.enbuild.2021.110906
   Mutani G, 2018, J SUSTAIN DEV ENERGY, V6, P694, DOI 10.13044/j.sdewes.d6.0203
   Nazari-Heris M, 2020, J ENERGY STORAGE, V31, DOI 10.1016/j.est.2020.101574
   Nazemi M, 2020, IEEE T SUSTAIN ENERG, V11, P795, DOI 10.1109/TSTE.2019.2907613
   Newell B, 2011, ECOL SOC, V16
   Nolden C, 2020, RENEW SUST ENERG REV, V122, DOI 10.1016/j.rser.2020.109722
   Novotny V, 2013, BUILD RES INF, V41, P589, DOI 10.1080/09613218.2013.804764
   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
   Pickering B, 2021, APPL ENERG, V285, DOI 10.1016/j.apenergy.2021.116465
   Ratti C, 2005, ENERG BUILDINGS, V37, P762, DOI 10.1016/j.enbuild.2004.10.010
   Ritchie H, 2013, ENERG POLICY, V63, P311, DOI 10.1016/j.enpol.2013.08.021
   Roege PE, 2014, ENERG POLICY, V72, P249, DOI 10.1016/j.enpol.2014.04.012
   Rosales-Asensio E, 2019, ENERGY, V172, P1005, DOI 10.1016/j.energy.2019.02.043
   Rutherford J, 2014, URBAN STUD, V51, P1353, DOI 10.1177/0042098013500090
   Salimi M, 2020, SUSTAIN CITIES SOC, V54, DOI 10.1016/j.scs.2019.101948
   Santamouris M, 2014, SOL ENERGY, V103, P682, DOI 10.1016/j.solener.2012.07.003
   Scanlon BR, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/4/045033
   Serdar MZ, 2022, SUSTAIN CITIES SOC, V76, DOI 10.1016/j.scs.2021.103452
   Shari A, 2021, J CLEAN PROD, V293, DOI 10.1016/j.jclepro.2021.125912
   Sharifi A, 2022, ENVIRON PLAN B-URBAN, V49, P1536, DOI 10.1177/23998083211058798
   Sharifi A, 2019, CITIES, V85, P1, DOI 10.1016/j.cities.2018.11.023
   Sharma KD, 2020, SOC RESPONSIB J, V16, P917, DOI 10.1108/SRJ-06-2019-0210
   Shaw A, 2014, GLOBAL ENVIRON CHANG, V25, P41, DOI 10.1016/j.gloenvcha.2014.01.002
   Shi QX, 2022, INT J ELEC POWER, V138, DOI 10.1016/j.ijepes.2021.107860
   Silvast A., 2019, ENERGY DIMENSIONS UR, P298
   Sola A, 2020, SUSTAIN CITIES SOC, V54, DOI 10.1016/j.scs.2019.101872
   Sovacool BK, 2011, ENERGY, V36, P5343, DOI 10.1016/j.energy.2011.06.043
   Sturiale L, 2019, CLIMATE, V7, DOI 10.3390/cli7100119
   Sun H, 2022, PROCESS SAF ENVIRON, V162, P987, DOI 10.1016/j.psep.2022.05.002
   T.E. Commission, 2008, Official Journal of the European Union
   UNDESA, 2018, WORLD URB PROSP 2014
   Venkateswaran B, 2020, CSEE J POWER ENERGY, V6, P816, DOI 10.17775/CSEEJPES.2019.01280
   Vera I, 2007, ENERGY, V32, P875, DOI 10.1016/j.energy.2006.08.006
   Voskamp IM, 2015, BUILD ENVIRON, V83, P159, DOI 10.1016/j.buildenv.2014.07.018
   Wang MD, 2018, J CLEAN PROD, V203, P1119, DOI 10.1016/j.jclepro.2018.08.350
   Wang XN, 2018, ENVIRON SCI TECHNOL, V52, P3257, DOI 10.1021/acs.est.7b04659
   Wardekker A, 2020, CITIES, V101, DOI 10.1016/j.cities.2020.102691
   Watson J.P., 2014, CONCEPTUAL FRAMEWORK
   Willis Henry H., 2015, Measuring the resilience of energy distribution systems, P38
   Yao S., 2018, 2018 IEEE International Conference on PMAPS, P1, DOI 10.1109/PMAPS.2018.8440544
   Zahed LM, 2022, INT J ENVIRON SCI TE, V19, P3593, DOI 10.1007/s13762-022-03949-8
   Zaman R, 2021, ENERGY RES SOC SCI, V71, DOI 10.1016/j.erss.2020.101805
   Zhang W, 2020, APPL ENERG, V279, DOI 10.1016/j.apenergy.2020.115716
   Zhou Q, 2021, HABITAT INT, V111, DOI 10.1016/j.habitatint.2021.102348
   US
NR 99
TC 0
Z9 0
U1 14
U2 26
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 1735-1472
EI 1735-2630
J9 INT J ENVIRON SCI TE
JI Int. J. Environ. Sci. Technol.
PD SEP
PY 2023
VL 20
IS 9
BP 9649
EP 9662
DI 10.1007/s13762-023-05058-6
EA JUL 2023
PG 14
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA P2ZI8
UT WOS:001026613800012
DA 2025-01-10
ER

PT J
AU Kekulandala, B
   Cunningham, R
   Jacobs, B
AF Kekulandala, Bhathiya
   Cunningham, Rebecca
   Jacobs, Brent
TI Exploring social networks in a small tank cascade system in Northcentral
   Sri Lanka: First steps to establishing adaptive governance
SO ENVIRONMENTAL DEVELOPMENT
LA English
DT Article
DE Small tank cascades; Social networks; Water governance; Climate
   adaptation; Adaptive governance
ID SUSTAINABLE DEVELOPMENT; COMANAGEMENT; RESILIENCE; PERCEPTIONS; COMMONS
AB Systems of irrigation governance that are community-led, flexible, and adaptive are better suited to meet the needs of local communities, resolve conflicts and minimize risks posed by a changing climate. Small Tank Cascade Systems (STCS) in Sri Lanka's dry zone have been critical to ensuring food and livelihood securities of local communities, and governance of STCS to reduce future climate risks will assume increased significance. Adaptive co-management (ACM) practices could reconcile complex natural resources management issues by incorporating flexible communitybased resource management systems tailored to specific geographical places and contexts, supported by organizations working at various scales. We sought opportunities to enhance existing systems of resource governance through ACM as a response to the uncertainty surrounding changes in climate. The first steps were to identify actors and processes related to the governance of Palugaswewa STCS through the cultivation meeting; a key decision process for resource management. We used social network analysis (SNA) with a survey of 48 farmers to identify key actors, their roles and responsibilities, practices and decision processes. The findings indicate that current decision processes are compartmentalized within the cascade system with less collaboration among actors in the upper, middle and lower parts of the cascade than anticipated. We conclude that governance structures of STCS could be improved by recognizing and incorporating informal actors, farmer subgroups, existing social relationships and community norms. To minimize future climate risks, information provision to farmers needs to recognize existing information flows in local networks, develop strategies to enhance existing relationships, build on existing adaptive/flexible decision processes, foster collaboration across the cascade system and develop governance mechanisms that operate at cascade/catchment level.
C1 [Kekulandala, Bhathiya; Cunningham, Rebecca; Jacobs, Brent] Univ Technol Sydney, Inst Sustainable Futures, 235 Jones St,Bldg 10,Level 10, Ultimo 2007, Australia.
C3 University of Technology Sydney
RP Kekulandala, B (corresponding author), Univ Technol Sydney, Inst Sustainable Futures, 235 Jones St,Bldg 10,Level 10, Ultimo 2007, Australia.
EM Bhathiya.Kekulandala@alumni.uts.edu.au
RI Cunningham, Rebecca/KDN-7378-2024
OI Kekulandala, Bhathiya/0000-0002-1872-4926; Cunningham,
   Rebecca/0000-0001-8066-9019
CR Abeyratne S.D., 1985, Sri Lanka Journal of Social Sciences, V8, P131
   Ade-Ibijola A, 2018, INT CONF SOFT COMP, P79, DOI 10.1109/ISCMI.2018.8703221
   Aheeyar M.M. M., 2000, Proceedings of the National Workshop on Food Security and Small Tank Systems in Sri Lanka, P64
   Aheeyar M.M. M., 1999, Sri Lanka Journal of Social Sciences, V22, P27
   [Anonymous], 2002, Ucinet 6 for Windows
   [Anonymous], 1951, Sociometry, Experimental method, and the science of society
   Armitage D, 2008, GLOBAL ENVIRON CHANG, V18, P86, DOI 10.1016/j.gloenvcha.2007.07.002
   Armitage DR, 2009, FRONT ECOL ENVIRON, V7, P95, DOI 10.1890/070089
   Bandyopadhyay S., 2010, Models for social networks with statistical applications p, P256
   Begum S., 1987, Minor Tank Water Management in the Dry Zone of Sri Lanka
   Berkes F., 2007, Adaptive Co-Management: Collaboration, Learning, and Multi-Level Governance Issue 1992, P360
   Biradar C.M., 2009, REMOTE SENS-BASEL
   Birthal P. S., 2006, Indian Journal of Agricultural Economics, V61, P328
   Bodin O, 2011, Social networks and natural resource management: Uncovering the social fabric of environmental governance, DOI [10.1017/CBO9780511894985, DOI 10.1017/CBO9780511894985]
   Bodin Ö, 2009, GLOBAL ENVIRON CHANG, V19, P366, DOI 10.1016/j.gloenvcha.2009.05.002
   Borgatti S. P., 2006, Computational & Mathematical Organization Theory, V12, P21, DOI 10.1007/s10588-006-7084-x
   Borgatti S.P., 2018, Analyzing Social Networks
   Bryman A., 2012, SOCIAL RES METHODS, DOI [10.1017/CBO9781107415324.004, DOI 10.1017/CBO9781107415324.004]
   Crona BI, 2006, ECOL SOC, V11
   Cunningham R, 2016, CLIM POLICY, V16, P894, DOI 10.1080/14693062.2015.1052955
   Dayaratne M.H. S., 1991, IIMI Country Paper - Sri Lanka
   de Fraiture C, 2010, AGR WATER MANAGE, V97, P502, DOI 10.1016/j.agwat.2009.08.008
   de la Poterie AT, 2018, ECOL SOC, V23, DOI 10.5751/ES-10175-230321
   De Silva CS, 2007, AGR WATER MANAGE, V93, P19, DOI 10.1016/j.agwat.2007.06.003
   Dharmasena PB, 2010, LANDSCAPES AND SOCIETIES: SELECTED CASES, P341, DOI 10.1007/978-90-481-9413-1_21
   Di Baldassarre G, 2019, WATER RESOUR RES, V55, P6327, DOI 10.1029/2018WR023901
   Eriyagama N., 2010, Proceedings of the national conference on water, food security and climate change in Sri Lanka. Volume 2: water quality, environment and climate change. Colombo, 9-11 June, 2009, P99
   Esham M, 2018, ENVIRON DEV SUSTAIN, V20, P1017, DOI 10.1007/s10668-017-9945-5
   Folke C, 2005, ANNU REV ENV RESOUR, V30, P441, DOI 10.1146/annurev.energy.30.050504.144511
   Folke C, 2002, AMBIO, V31, P437, DOI 10.1639/0044-7447(2002)031[0437:RASDBA]2.0.CO;2
   FREEMAN LC, 1977, SOCIOMETRY, V40, P35, DOI 10.2307/3033543
   Gain AK, 2021, INT J SUST DEV WORLD, V28, P109, DOI 10.1080/13504509.2020.1780647
   Groce JE, 2019, CONSERV BIOL, V33, P53, DOI 10.1111/cobi.13127
   Isaac ME, 2007, ECOL SOC, V12
   Kekulandala B, 2021, CLIM DEV, V13, P337, DOI 10.1080/17565529.2020.1772709
   Marambe B., 2015, Handbook of Climate Change Adaptation, P1759, DOI [DOI 10.1007/978-3-642-38670-1120, 10.1007/978-3-642-38670-1_120]
   Mase AS, 2014, WEATHER CLIM SOC, V6, P47, DOI 10.1175/WCAS-D-12-00062.1
   Meinzen-Dick R., 1998, Agriculture and Human Values, V15, P337, DOI 10.1023/A:1007533018254
   Merrey D.J., 1988, Strategies for farmer participation in irrigation management in Sri Lanka: Past experiences and future requirements
   Ministry of Agriculture Fao, 2016, PROP DECL GIAHS CASC
   Nidumolu U, 2020, WEATHER CLIM EXTREME, V27, DOI 10.1016/j.wace.2018.06.001
   Nijman C., 1992, Irrigation Decision-making processes and conditions:A case study of the Sri Lanka's Kirindi Oya Irrigation and Settlement Project
   Olsson P, 2004, ENVIRON MANAGE, V34, P75, DOI 10.1007/s00267-003-0101-7
   Ostrom E, 1999, SCIENCE, V284, P278, DOI 10.1126/science.284.5412.278
   OSTROM E, 1993, J ECON PERSPECT, V7, P93, DOI 10.1257/jep.7.4.93
   OSTROM E, 1993, WATER RESOUR RES, V29, P1907, DOI 10.1029/92WR02991
   Ostrom E., 1992, Crafting institutionsfor self-governing irrigation systems, DOI [DOI 10.1002/RRR.3450080314, 10.1002/rrr.3450080314]
   Ostrom E., 1990, GOVERNING COMMONS EV
   Panabokke C.R., 1999, Small tank cascade systems of the Rajarata-their setting, distribution patterns and hydrology p, P48
   Panabokke C.R., 2002, Small Tanks in Sri Lanka: Evolution, Present Status, and Issues, DOI [10.5337/2011.0050, DOI 10.5337/2011.0050]
   Plummer R, 2007, ECOL ECON, V61, P62, DOI 10.1016/j.ecolecon.2006.09.025
   Plummer R, 2017, ECOL SOC, V22, DOI 10.5751/ES-09436-220319
   Plummer R, 2012, ECOL SOC, V17, DOI 10.5751/ES-04952-170311
   Prell C., 2012, SOCIAL NETWORK ANAL
   Rahman F., 2008, J BANGLADESH AGRI UN, V6, P261, DOI [10.3329/jbau.v6i2.4820, DOI 10.3329/JBAU.V6I2.4820, DOI 10.3329/jbau.v6i2.4820]
   Rockström J, 2000, PHYS CHEM EARTH PT B, V25, P275, DOI 10.1016/S1464-1909(00)00015-0
   Rogers P., 2003, TEC BACKGROUND PAPER
   Roncoli C, 2002, SOC NATUR RESOUR, V15, P409, DOI 10.1080/08941920252866774
   Scott James C., 1998, Seeing like a State: How Certain Schemes to Improve the Human Condition Have Failed
   Senaratne A.H., 2013, Shared Beliefs, Expectations and Surprises: Adaptation Decisions of Village Tank Farmers in Sri Lanka
   Shah T., 2007, Groundwater: a global assessment of scale and significance. Water for food, water for life: a comprehensive assessment of water management in agriculture
   Stein C, 2011, PHYS CHEM EARTH, V36, P1085, DOI 10.1016/j.pce.2011.07.083
   Sumane S, 2018, J RURAL STUD, V59, P232, DOI 10.1016/j.jrurstud.2017.01.020
   Nguyen TPL, 2016, AGR SYST, V143, P205, DOI 10.1016/j.agsy.2016.01.001
   Uphoff N., 1986, Getting the Process Right: Improving Water Management with Farmer Organization and Participation
   Wickramagamage P, 2016, THEOR APPL CLIMATOL, V125, P427, DOI 10.1007/s00704-015-1492-0
   Wijekoon W.M. S. M., 2016, Proceedings of the 7th International Conference on Sustainable Built Environment, P9
   Wood BA, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0105203
NR 68
TC 6
Z9 6
U1 0
U2 7
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2211-4645
EI 2211-4653
J9 ENVIRON DEV
JI Environ. Dev.
PD JUN
PY 2023
VL 46
AR 100847
DI 10.1016/j.envdev.2023.100847
EA APR 2023
PG 14
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA D5BJ8
UT WOS:000968882400001
DA 2025-01-10
ER

PT J
AU Wang, AQ
   Tao, H
   Ding, G
   Zhang, BL
   Huang, JL
   Wu, QY
AF Wang, Anqian
   Tao, Hui
   Ding, Gang
   Zhang, Baolei
   Huang, Jinlong
   Wu, Quanyuan
TI Global cropland exposure to extreme compound drought heatwave events
   under future climate change
SO WEATHER AND CLIMATE EXTREMES
LA English
DT Article
DE Compound drought heatwave events; Cropland exposure; CMIP6; Global and
   continent
ID DRY-HOT EVENTS; POPULATION EXPOSURE; CHINA; RISK
AB The risk of compound drought heatwave events (CDHEs) and their persistence has intensified in recent decades and is expected to increase faster in the future. Projecting future changes in the CDHEs and the area of the cropland exposed to CDHEs under different scenarios is critical for climate adaptation and sustainable devel-opment. In this study, we analyze cropland exposure to extreme CDHEs at the global and continental scales under different Shared Socioeconomic Pathways (SSPs) scenarios for the mid-term (2041-2060) and long-term (2081-2100) of the 21st century by using 14 CMIP6 GCMs and LUH2 land-use data. We find that the extreme CDHEs with high frequency are mainly located in tropical areas. The frequency of extreme CDHEs in the future will be much higher than that of the baseline period (1995-2014), and the increased frequency will be more obvious with the emissions increase. Overall, the global total cropland exposure in warm season during the 1995-2014 period will be 148.05 x 103 km2 month-1. Exposure in the mid-term and long-term will be 868.68-1801.25 and 1058.58-3887.54 x 103 km2 month-1 under the different SSP scenarios. The climate effect will be the dominant driving factor for the increase in cropland exposure. Cropland exposure to extreme CDHEs will increase on all continents, especially in Asia and Africa. Our findings provide scientific evidence of the benefit of limiting low-emission scenarios which will effectively reduce cropland exposure to CDHEs under future climate change.
C1 [Wang, Anqian; Zhang, Baolei; Wu, Quanyuan] Shandong Normal Univ, Coll Geog & Environm, Jinan 250358, Peoples R China.
   [Tao, Hui] Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, Urumqi 830011, Peoples R China.
   [Ding, Gang] Dept Emergency Management Xinjiang Uygur Autonomou, Risk Monitoring & Comprehens Disaster Reduct Div, Urumqi 830011, Peoples R China.
   [Huang, Jinlong] Nanjing Univ Informat Sci & Technol, Inst Disaster Risk Management, Collaborat Innovat Ctr Forecast & Evaluat Meteorol, Sch Geog Sci, Nanjing 210044, Peoples R China.
C3 Shandong Normal University; Chinese Academy of Sciences; Xinjiang
   Institute of Ecology & Geography, CAS; Nanjing University of Information
   Science & Technology
RP Tao, H (corresponding author), Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, Urumqi 830011, Peoples R China.
EM taohui@ms.xjb.ac.cn
OI Zhang, Baolei/0000-0001-8866-6728
FU Natural Science Foundation of Shandong Province, China [ZR2021QD139];
   Postdoctoral Innova- tion Project of Shandong Province [2021BHCX54];
   National Science Foundation of China [41971023]
FX This work was supported by the Natural Science Foundation of Shandong
   Province, China (ZR2021QD139) , the Postdoctoral Innova- tion Project of
   Shandong Province (2021BHCX54) , and the National Science Foundation of
   China (41971023) .
CR AghaKouchak A, 2014, GEOPHYS RES LETT, V41, P8847, DOI 10.1002/2014GL062308
   Alizadeh MR, 2020, SCI ADV, V6, DOI 10.1126/sciadv.aaz4571
   Chen J, 2020, J CLEAN PROD, V277, DOI 10.1016/j.jclepro.2020.123275
   Chen J, 2018, EARTH SYST DYNAM, V9, P1097, DOI 10.5194/esd-9-1097-2018
   Chen M, 2020, SCI DATA, V7, DOI 10.1038/s41597-020-00669-x
   Das J, 2022, SCI TOTAL ENVIRON, V806, DOI 10.1016/j.scitotenv.2021.150424
   Eyring V, 2016, GEOSCI MODEL DEV, V9, P1937, DOI 10.5194/gmd-9-1937-2016
   Feng SF, 2019, SCI TOTAL ENVIRON, V689, P1228, DOI 10.1016/j.scitotenv.2019.06.373
   Feng Y, 2021, INT J CLIMATOL, V41, pE1085, DOI 10.1002/joc.6755
   Garcia-Pen~a G.E., 1837, PHIL T BIOL SCI, V376, DOI [10.1098/rstb, DOI 10.1098/RSTB]
   Gidden MJ, 2019, GEOSCI MODEL DEV, V12, P1443, DOI 10.5194/gmd-12-1443-2019
   GRINGORTEN II, 1963, J GEOPHYS RES, V68, P813, DOI 10.1029/JZ068i003p00813
   Hao ZC, 2020, THEOR APPL CLIMATOL, V142, P321, DOI 10.1007/s00704-020-03317-x
   Hao ZC, 2019, J HYDROL, V572, P243, DOI 10.1016/j.jhydrol.2019.03.001
   Hao ZC, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aaee96
   Harris I, 2020, SCI DATA, V7, DOI 10.1038/s41597-020-0453-3
   He Y, 2022, SCI TOTAL ENVIRON, V824, DOI 10.1016/j.scitotenv.2022.153885
   He Y, 2022, INT J CLIMATOL, V42, P5038, DOI 10.1002/joc.7518
   Hofer S, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-20011-8
   Hu Q, 2020, SCI TOTAL ENVIRON, V746, DOI 10.1016/j.scitotenv.2020.141035
   Hurtt GC, 2020, GEOSCI MODEL DEV, V13, P5425, DOI 10.5194/gmd-13-5425-2020
   Immerzeel WW, 2010, SCIENCE, V328, P1382, DOI 10.1126/science.1183188
   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]
   Leonard M, 2014, WIRES CLIM CHANGE, V5, P113, DOI 10.1002/wcc.252
   Lesk C, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abeb35
   Lesk C, 2016, NATURE, V529, P84, DOI 10.1038/nature16467
   Li HB, 2010, J GEOPHYS RES-ATMOS, V115, DOI 10.1029/2009JD012882
   Li W, 2022, J METEOROL RES-PRC, V36, P37, DOI 10.1007/s13351-022-1112-8
   Libonati R, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac462e
   Liu WB, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/ac188f
   Liu Z, 2017, SCI REP-UK, V7, DOI 10.1038/srep43909
   Luo M, 2022, GEOPHYS RES LETT, V49, DOI 10.1029/2022GL097714
   Luo M, 2018, CLIM DYNAM, V51, P2707, DOI 10.1007/s00382-017-4038-6
   Lutz AF, 2022, NAT CLIM CHANGE, V12, P566, DOI 10.1038/s41558-022-01355-z
   Ma F, 2021, SCI TOTAL ENVIRON, V772, DOI 10.1016/j.scitotenv.2021.145004
   Ma L, 2020, GEOSCI MODEL DEV, V13, P3203, DOI 10.5194/gmd-13-3203-2020
   Mazdiyasni O, 2015, P NATL ACAD SCI USA, V112, P11484, DOI 10.1073/pnas.1422945112
   MCKEE TB, 1993, P 8 C APPL CLIM AN C
   Miralles DG, 2019, ANN NY ACAD SCI, V1436, P19, DOI 10.1111/nyas.13912
   Mishra V, 2020, NPJ CLIM ATMOS SCI, V3, DOI 10.1038/s41612-020-0113-5
   Mondal SK, 2021, SCI TOTAL ENVIRON, V771, DOI 10.1016/j.scitotenv.2021.145186
   Mukherjee S, 2020, J GEOPHYS RES-ATMOS, V125, DOI 10.1029/2019JD031943
   Potapov P, 2022, NAT FOOD, V3, P19, DOI 10.1038/s43016-021-00429-z
   Ray DK, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms6989
   Seneviratne SI, 2010, EARTH-SCI REV, V99, P125, DOI 10.1016/j.earscirev.2010.02.004
   Siebert S, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa702f
   Smirnov O, 2016, CLIMATIC CHANGE, V138, P41, DOI 10.1007/s10584-016-1716-z
   Song Y, 2021, EARTH SPACE SCI, V8, DOI 10.1029/2021EA001799
   Su BD, 2018, P NATL ACAD SCI USA, V115, P10600, DOI 10.1073/pnas.1802129115
   Su BD, 2016, ATMOS RES, V178, P138, DOI 10.1016/j.atmosres.2016.03.023
   Summary for Policymakers, 2001, CLIMATE CHANGE 2001, P2
   Tang ZF, 2022, PLOS ONE, V17, DOI 10.1371/journal.pone.0264980
   Thornthwaite CW, 1948, GEOGR REV, V38, P55, DOI 10.2307/210739
   Ullah I, 2022, EARTHS FUTURE, V10, DOI 10.1029/2021EF002240
   Vicente-Serrano SM, 2010, J CLIMATE, V23, P1696, DOI 10.1175/2009JCLI2909.1
   Wang AQ, 2022, INT J CLIMATOL, V42, P7938, DOI 10.1002/joc.7685
   Wang AQ, 2020, EARTHS FUTURE, V8, DOI 10.1029/2019EF001448
   Weber T, 2020, EARTHS FUTURE, V8, DOI 10.1029/2019EF001473
   Wen SS, 2019, ATMOS RES, V218, P296, DOI 10.1016/j.atmosres.2018.12.003
   WILLMOTT CJ, 1985, J CLIMATOL, V5, P589, DOI 10.1002/joc.3370050602
   Wu XY, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac4c5b
   Wu XY, 2020, J HYDROL, V583, DOI 10.1016/j.jhydrol.2020.124580
   Yu R, 2020, WEATHER CLIM EXTREME, V30, DOI 10.1016/j.wace.2020.100295
   Yu R, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-71312-3
   Yuan X, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-12692-7
   Zhai JQ, 2020, ATMOS RES, V246, DOI 10.1016/j.atmosres.2020.105111
   Zhang Q, 2022, EARTHS FUTURE, V10, DOI 10.1029/2022EF002833
   Zhang W, 2021, FRONT EARTH SC-SWITZ, V9, DOI 10.3389/feart.2021.673495
   Zhang Y, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac43e0
   Zhang YQ, 2021, LAND-BASEL, V10, DOI 10.3390/land10101021
   Zhou J, 2020, ATMOS RES, V242, DOI 10.1016/j.atmosres.2020.104979
   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
   Zscheischler J, 2017, SCI ADV, V3, DOI 10.1126/sciadv.1700263
NR 75
TC 29
Z9 30
U1 39
U2 139
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2212-0947
J9 WEATHER CLIM EXTREME
JI Weather Clim. Extremes
PD JUN
PY 2023
VL 40
AR 100559
DI 10.1016/j.wace.2023.100559
EA MAR 2023
PG 11
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA D9DR2
UT WOS:000971664600001
OA gold
DA 2025-01-10
ER

PT J
AU Slater, KR
   Robinson, JB
AF Slater, Kimberley R.
   Robinson, John B.
TI Transformational climate actions by cities
SO BUILDINGS & CITIES
LA English
DT Article
DE cities; climate adaptation; climate mitigation; co- production;
   implementation; local government; policy; practice; transdisciplinary;
   transformation; urban
ID PLANS; QUALITY
AB With their predominantly coastal geographies, rapidly growing populations, and emissions -intensive activities, cities are highly vulnerable and major contributors to climate change. Their role as cultural centers, and commerce and innovation hubs, means they are also promising sources of solutions. Taken together, these factors demand a closer examination of the progress and solutions that cities are making to mitigate climate change and adapt to its impacts. However, research on the extent and effectiveness of cities' implementation efforts is underdeveloped. There is a need to better understand if and how cities are rolling out effective implementation measures, what effects (intended and unintended) such measures are having, and whether their implementation efforts are achieving the transformational changes needed to realize a low carbon, climateresilient future. This editorial introduces the special issue by exploring these issues and reflecting perspectives from a variety of disciplines both within and outside academia, and in relation to diverse cities in the Global North and South. To better understand the practical dimensions of implementation, and the various obstacles and opportunities faced by public and private sector actors in progressing climate action targets and goals, the editors invited submissions reflective of co -produced research. Though not all took this form, some did and helped to foreground the experiences of those actors who arguably have the most power and responsibility to advance implementation measures, and seed the very institutional arrangements needed for deeper, multisectoral climate action. Collectively, the content of the special issue points to a need for significant investment, policy change, social innovation, and cooperation across societal scales.
C1 [Slater, Kimberley R.; Robinson, John B.] Univ Toronto, Munk Sch Global Affairs & Publ Policy, Toronto, ON, Canada.
   [Robinson, John B.] Univ Toronto, Sch Environm, Toronto, ON, Canada.
C3 University of Toronto; University of Toronto
RP Slater, KR (corresponding author), Univ Toronto, Munk Sch Global Affairs & Publ Policy, Toronto, ON, Canada.
EM kim.slater@utoronto.ca
OI Robinson, John/0000-0003-4559-5565
FU Mitacs [514923]
FX The authors gratefully acknowledge funding from Mitacs (Fund 514923) for
   the project 'Co-designing and Communicating Equitable and
   Transformational Climate Actions' and for funding the editorial APC.
CR [Anonymous], 2019, TransformTO-Background.
   C40 Cities, 2021, C40 annual report.
   Geels FW, 2012, J TRANSP GEOGR, V24, P471, DOI 10.1016/j.jtrangeo.2012.01.021
   Guyadeen D, 2019, CLIMATIC CHANGE, V152, P121, DOI 10.1007/s10584-018-2312-1
   Horney J, 2017, J PLAN EDUC RES, V37, P56, DOI 10.1177/0739456X16628605
   Kane J. W., 2022, Not according to plan: Exploring gaps in city climate planning and the need for regional action
   Kuramochi T., 2019, Research Report, V2019
   Otto A, 2021, CLIMATIC CHANGE, V167, DOI 10.1007/s10584-021-03142-9
   Purcell B., 2019, TAF's review of Toronto's climate emergency declaration
   Stevens MR, 2015, J ENVIRON PLANN MAN, V58, P1988, DOI 10.1080/09640568.2014.973479
   United Nations, 2015, MILL DEV GOALS REP 2, DOI DOI 10.18356/6CD11401-EN
NR 11
TC 4
Z9 4
U1 1
U2 3
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 2023
VL 4
IS 1
BP 74
EP 82
DI 10.5334/bc.285
PG 9
WC Construction & Building Technology
WE Emerging Sources Citation Index (ESCI)
SC Construction & Building Technology
GA ON9V3
UT WOS:001208080400004
OA gold
DA 2025-01-10
ER

PT J
AU Ullmann, AL
   Haag, I
   Bulbulshoev, U
AF Ullmann, A. L.
   Haag, I.
   Bulbulshoev, U.
TI Ecological Calendars of the Pamir Mountains: Illustrating the Importance
   of Context-Specificity for Food Security
SO GEOHEALTH
LA English
DT Article
DE transdisciplinary research; Indigenous knowledge; praxis; climate
   adaptation; human ecology; iconographic communication
ID CLIMATE-CHANGE; CENTRAL-ASIA; TIME
AB Communities in the Pamir Mountains of Central Asia are among the most vulnerable to climate change due to their geographic location and subsistence-based livelihoods. Historically, ecological calendars supported their agropastoral lifestyles which provided anticipatory capacity to seasonal changes. Due to decades of Soviet colonization and socioecological transformations, knowledge of these ecological calendars fell into disuse. In 2016, Savnob and Roshorv, two villages in the Bartang Valley of Tajikistan, began the revitalization of these calendars using a participatory action research process through knowledge co-generation. We undertook a comparative analysis to investigate the importance of context-specificity to ensure food security and reduce their vulnerability to climate change. A preliminary analysis of the temperature regime and local language terms, relating to the positioning and quality of land, framed our methods-of-analysis. We compared the villagers' ecological calendars by focusing on indicator species, potentially threatening weather events, land-use, livelihood activities, and the role of the vernal equinox. Despite their close geographic proximity, context-specificity determined by distinct microecologies influences the timing and practice of these communities' livelihood activities. These villages have different dependencies on biotic and abiotic events, crops, and land-use; all of which affect food security and survival. These differences contributed to mutual support between the two villages, increased the availability of food, and thereby, lowered their vulnerability to climate change. As Savnob's and Roshorv's ecological calendars are updated with changing climate, they can once again enhance their anticipatory capacity while reducing their vulnerability.
C1 [Ullmann, A. L.] Tech Univ Munich, Sch Life Sci, Freising Weihenstephan, Germany.
   [Haag, I.] Heidelberg Univ, South Asia Inst, Heidelberg, Germany.
   [Bulbulshoev, U.] Univ Cent Asia, Sch Profess & Continuing Educ, Khorog, Tajikistan.
C3 Technical University of Munich; Ruprecht Karls University Heidelberg;
   University of Central Asia
RP Ullmann, AL (corresponding author), Tech Univ Munich, Sch Life Sci, Freising Weihenstephan, Germany.
EM anna.ullmann@tum.de
OI Ullmann, Anna/0000-0001-5059-5020; Haag, Isabell/0000-0002-3308-5245
FU "Mountains as Sentinels of ChangeCollaborative Research Belmont Forum:
   Ecological Calendars and Climate Adaptation in the Pamirs (ECCAP)"
   project - National Science Foundation (NSF) [1630490]; Deutsche
   Forschungsgemeinschaft (DFG) [SA 775/12-1]; Italian National Research
   Council (CNR) [B51J11000840001]; Rita Allen Foundation [NS-2111-02233];
   Projekt DEAL; ICER; Directorate For Geosciences [1630490] Funding
   Source: National Science Foundation
FX The authors are grateful to the village members of Savnob and Roshorv
   for their commitment to the Ecological Calendars and Climate Adaptation
   in the Pamirs project. The authors would like to express our gratitude
   to the Ecological Calendars and Climate Adaptation in the Pamirs
   Principal Investigators including KarimAly Kassam (Cornell University),
   Cyrus Samimi (University of Bayreuth), Antonio Trabucco (Padua
   University), and Jianchu Xu (Chinese Academy of Sciences). The authors
   also appreciatively acknowledge constructive comments made by the two
   anonymous reviewers and special issue co-editors Felice Wyndham and
   Morgan Ruelle (Clark University) as well as the support from Aishwarya
   Shankar who helped to visualize and develop all figures in the paper.
   This research would not have been possible without the Department of
   Natural Resources and the Environment at Cornell University, the
   Atkinson Center for a Sustainable Future, and the Belmont Forum (NSF).
   International funding for research in the Pamir Mountains of Central
   Asia was provided by the "Mountains as Sentinels of ChangeCollaborative
   Research Belmont Forum: Ecological Calendars and Climate Adaptation in
   the Pamirs (ECCAP)" project, supported by the National Science
   Foundation (NSF, Award 1630490), the Deutsche Forschungsgemeinschaft
   (DFG, Award SA 775/12-1), and the Italian National Research Council
   (CNR, Award B51J11000840001). Funding to support open access publication
   of this work was provided by the Rita Allen Foundation under Agreement
   NS-2111-02233. Undergraduate Research Assistants Thomas Senftl; and
   Graduate Research Assistants Talia Chorover, Sarah Holden, Kayla
   Scheimreif, Tobias Kraudzun, as well as Dr. Simone Mereu aided in data
   collection related to ecological calendars in the Pamirs.
   Community-based translators include Shahlo Saradbekova (Savnob),
   Topchibek Bekov (Savnob), Saradbek Tohirbekov (Roshorv), and Tohir
   Saradbekov (Savnob and Roshorv). Open Access funding enabled and
   organized by Projekt DEAL.
CR ADJAYE JK, 1987, J ETHNIC STUD, V15, P71
   Andreev M. S., 1958, TADZHIKI DOLINY KHUF, V2nd ed.
   [Anonymous], 2021, The State of Food and Agriculture 2021: Making agrifood systems more resilient to shocks and stresses, DOI [10.4060/cb4476-n, DOI 10.4060/CB4476-N, 10.4060/cb4476en, DOI 10.4060/CB4476EN]
   Bliss F., 2006, SOCIAL EC CHANGE PAM
   Bobojonov I, 2014, AGR ECOSYST ENVIRON, V188, P245, DOI 10.1016/j.agee.2014.02.033
   Cochran F, 2016, SUSTAIN SCI, V11, P69, DOI 10.1007/s11625-015-0303-y
   Ekbolsho D., 2017, COMMUNICATION
   Evans-Pritchard EE, 1939, AFRICA, V12, P189, DOI 10.2307/1155085
   Feng S, 2004, THEOR APPL CLIMATOL, V78, P247, DOI 10.1007/s00704-004-0061-8
   Finaev Alexander F., 2016, [Geography, Environment, Sustainability, Geography, Environment, Sustainability], V9, P88, DOI 10.15356/2071-9388_03v09_2016_06
   Frich P, 2002, CLIMATE RES, V19, P193, DOI 10.3354/cr019193
   Gentle P, 2012, ENVIRON SCI POLICY, V21, P24, DOI 10.1016/j.envsci.2012.03.007
   Gulbahor I., 2017, COMMUNICATION
   Haag I., 2019, GEOGRAPHISCHE RUNDSC, V71, P26
   Haag I, 2021, CLIMATIC CHANGE, V165, DOI 10.1007/s10584-021-02988-3
   Haag I, 2019, CLIMATE, V7, DOI 10.3390/cli7100123
   Hu ZY, 2014, J CLIMATE, V27, P1143, DOI 10.1175/JCLI-D-13-00064.1
   Kassam K.-A., 2013, CONTINUITY CHANGE CU, P303, DOI [10.1007/978-1-4614-5702-2_12, DOI 10.1007/978-1-4614-5702-2_12]
   Kassam K.A., 2021, UNDERSTANDING CLIMAT, P153, DOI DOI 10.2307/J.CTV21HRH8R.10
   Kassam K.A., 2022, RHYTHMS LAND INDIGEN
   Kassam K.A. S., 2009, Biocultural diversity and indigenous ways of knowing: human ecology in the Arctic
   Kassam KA, 2021, HUM ECOL, V49, P509, DOI 10.1007/s10745-021-00269-2
   Kassam KA, 2011, J PERSIANATE STUD, V4, P146, DOI 10.1163/187471611X600369
   Kassam KA, 2009, HUM ECOL, V37, P677, DOI 10.1007/s10745-009-9284-8
   Kassam KAS, 2022, GEOHEALTH, V6, DOI 10.1029/2022GH000614
   Kassam KAS, 2018, HUM ECOL, V46, P249, DOI 10.1007/s10745-018-9970-5
   Kicherer S., 2018, IDENTITY HIST T NATI, P173
   Kislyakov N., 1966, TADZHIKI KARATEGINA
   Kohler T, 2010, MT RES DEV, V30, P53, DOI 10.1659/MRD-JOURNAL-D-09-00086.1
   Lentz W., 1939, ZEITRECHNUNG NURISTA, V7
   Manandhar S., 2018, CLIMATE VULNERABILIT
   McKemey M, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12030995
   Nabhan G.P., 2009, Where Our Food Comes From: Retracing Nikolay Vavilov's Quest to End Famine
   Retnowati A, 2014, PROCEDIA ENVIRON SCI, V20, P785, DOI 10.1016/j.proenv.2014.03.095
   Rosenberg N.J., 1983, Microclimate: The Biological Environment
   Shakarshoevich S. L., 2017, COMMUNICATION
   Skendzic S, 2021, INSECTS, V12, DOI 10.3390/insects12050440
   Sommer R, 2013, AGR ECOSYST ENVIRON, V178, P78, DOI 10.1016/j.agee.2013.06.011
   Ullmann A. L., 2022, COMMUNITY SCI, V1, DOI [10.1029/2022CSJ00000, DOI 10.1029/2022CSJ00000]
   Ware J, 2019, HUNGER STRIKE CLIMAT
   Woodward E, 2019, GLOB HEALTH PROMOT, V26, P26, DOI 10.1177/1757975919832241
NR 41
TC 5
Z9 5
U1 0
U2 6
PU AMER GEOPHYSICAL UNION
PI WASHINGTON
PA 2000 FLORIDA AVE NW, WASHINGTON, DC 20009 USA
SN 2471-1403
J9 GEOHEALTH
JI GeoHealth
PD DEC
PY 2022
VL 6
IS 12
AR e2022GH000610
DI 10.1029/2022GH000610
PG 17
WC Environmental Sciences; Public, Environmental & Occupational Health
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Public, Environmental & Occupational
   Health
GA 8R7DQ
UT WOS:000928051700002
PM 36467255
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Bienvenido-Huertas, D
   Sánchez-García, D
   Rubio-Bellido, C
AF Bienvenido-Huertas, David
   Sanchez-Garcia, Daniel
   Rubio-Bellido, Carlos
TI Adaptive setpoint temperatures to reduce the risk of energy poverty? A
   local case study in Seville
SO ENERGY AND BUILDINGS
LA English
DT Article
DE Energy poverty; Adaptive setpoint temperatures; Dwellings; Adaptive
   comfort; Electricity price
ID THERMAL HABITABILITY CONDITIONS; FUEL POVERTY; ZERO-ENERGY; BUILDINGS;
   EFFICIENCY; CLIMATE; HEALTH; IMPACT; INCOME; COLD
AB The reduction of energy poverty is among the main current challenges. One of the recent approaches is based on the reduction of the energy consumption through the climate adaptability of users. This research analyses the possibility of using adaptive setpoint temperatures to reduce the risk of energy poverty. A total of 6528 cases are considered in the south of Spain in 2015 and 2016 with actual data of temperature, hourly prices from the Voluntary Price for the Small Consumer, and the mean household incomes in both years. The energy consumption and expense are compared to both the static setpoints established by the Spanish Technical Building Code and the adaptive setpoints based on EN 16798-1:2019. In the annual calculation, by using both static and adaptive setpoints, the results show that the situation of energy poverty would only affect the family units belonging to the first decile of incomes. However, a monthly analysis identifies that the coldest or warmest months influence more deciles: for example, January 2015 affected until decile 8. The results also show that adaptive setpoints could reduce the risk of energy poverty in most cases, being more significant in Categories II and III from EN 16798-1:2019, in which this risk is reduced in all months of the year and in all deciles. This study aims to throw light on the use of HVAC systems according to the adaptation of users to reduce monthly the risk of energy poverty. (C) 2020 Elsevier B.V. All rights reserved.
C1 [Bienvenido-Huertas, David; Sanchez-Garcia, Daniel; Rubio-Bellido, Carlos] Univ Seville, Dept Bldg Construct 2, Seville, Spain.
C3 University of Sevilla
RP Bienvenido-Huertas, D (corresponding author), Higher Tech Sch Bldg Engn, Ave Reina Mercedes 4A, Seville, Spain.
EM jbienvenido@us.es
RI Rubio-Bellido, Carlos/K-1861-2014; Sanchez Garcia, Daniel/T-2234-2017;
   Bienvenido Huertas, Jose David/I-2976-2018
OI Rubio-Bellido, Carlos/0000-0001-6719-8793; Sanchez Garcia,
   Daniel/0000-0002-3080-0821; Bienvenido Huertas, Jose
   David/0000-0003-0716-8589
FU European Regional Development Fund (ERDF) [US-125546]; Consejeria de
   Economia y Conocimiento de la Junta de Andalucia (Spain)
FX The authors would like to acknowledge to the research project ``Nuevo
   Analisis Integral de la Pobreza Energetica en Andalucia (NAIPE).
   Prediccion, evaluacion y adaptacion al cambio climatico de hogares
   vulnerables desde una perspectiva economica, ambiental y social
   (US-125546)"funded by the European Regional Development Fund (ERDF) and
   by the ``Consejeria de Economia y Conocimiento de la Junta de Andalucia
   (Spain)" for support this research.
CR Abrahamson V, 2009, J PUBLIC HEALTH-UK, V31, P119, DOI 10.1093/pubmed/fdn102
   [Anonymous], 2007, 152512007 EN EUR COM
   [Anonymous], [No title captured]
   Atanasiu B., 2014, BUILD PERFORM I EUR
   Attia S, 2017, ENERG BUILDINGS, V155, P439, DOI 10.1016/j.enbuild.2017.09.043
   Bienvenido-Huertas D, 2020, ENERGY, V190, DOI 10.1016/j.energy.2019.116448
   Bienvenido-Huertas D, 2020, BUILD ENVIRON, V170, DOI 10.1016/j.buildenv.2019.106612
   Bienvenido-Huertas D, 2020, SUSTAIN CITIES SOC, V53, DOI 10.1016/j.scs.2019.101944
   Bienvenido-Huertas D, 2019, ENERG BUILDINGS, V198, P38, DOI 10.1016/j.enbuild.2019.05.063
   Boardman B, 1991, Fuel Poverty: From Cold Homes to Affordable Warmth
   Braubach M, 2013, INT J PUBLIC HEALTH, V58, P331, DOI 10.1007/s00038-012-0441-2
   Castaño-Rosa R, 2020, ENERGY RES SOC SCI, V60, DOI 10.1016/j.erss.2019.101325
   Castaño-Rosa R, 2019, ENERG BUILDINGS, V193, P36, DOI 10.1016/j.enbuild.2019.03.039
   de Mena JoseMaria., 1985, Historia de Sevilla
   Dominguez-Amarillo S., 2016, Monografias
   Dubois G, 2019, ENERGY RES SOC SCI, V52, P144, DOI 10.1016/j.erss.2019.02.001
   EN, 2019, 1679812019 EN EUR CO
   Feijó-Muñoz J, 2019, ENERG BUILDINGS, V188, P226, DOI 10.1016/j.enbuild.2019.02.023
   Gangolells M, 2016, J CLEAN PROD, V112, P3895, DOI 10.1016/j.jclepro.2015.05.105
   Ge J, 2018, J BUILD ENG, V18, P321, DOI 10.1016/j.jobe.2018.03.022
   Healy JD, 2004, ENERG POLICY, V32, P207, DOI 10.1016/S0301-4215(02)00265-3
   Herrero S. Tirado, 2016, POVERTY VULNERABILIT, V1a
   Hoyt T, 2015, BUILD ENVIRON, V88, P89, DOI 10.1016/j.buildenv.2014.09.010
   Intelligent Energy Europe, 2009, EUR FUEL POV EN EFF
   Isherwood B.C. Hancock., 1979, Household Expenditure on Fuel: Distributional Aspects
   Kurtz F, 2015, INF CONSTR, V67, DOI 10.3989/ic.14.062
   Liddell C, 2015, PUBLIC HEALTH, V129, P191, DOI 10.1016/j.puhe.2014.11.007
   Liddell C, 2016, J PUBLIC HEALTH-UK, V38, P806, DOI 10.1093/pubmed/fdv184
   Lu DB, 2020, J BUILD ENG, V30, DOI 10.1016/j.jobe.2020.101223
   Marin de Teran Luis, 1980, Sevilla: Centro Urbano y Barriadas
   Mastropietro P, 2019, ENERGY RES SOC SCI, V56, DOI 10.1016/j.erss.2019.101222
   Middlemiss L, 2015, ENERGY RES SOC SCI, V6, P146, DOI 10.1016/j.erss.2015.02.001
   Ormandy D, 2016, ADV BUILD ENERGY RES, V10, P84, DOI 10.1080/17512549.2015.1014845
   Parkinson T, 2020, ENERG BUILDINGS, V206, DOI 10.1016/j.enbuild.2019.109559
   Ren ZG, 2018, APPL ENERG, V210, P152, DOI 10.1016/j.apenergy.2017.10.110
   Rosenow J, 2013, ENERG POLICY, V62, P1194, DOI 10.1016/j.enpol.2013.07.103
   Sánchez-García D, 2020, APPL SCI-BASEL, V10, DOI 10.3390/app10041513
   Sánchez-García D, 2020, BUILD SIMUL-CHINA, V13, P51, DOI 10.1007/s12273-019-0560-2
   Sánchez-García D, 2019, ENERGIES, V12, DOI 10.3390/en12081498
   Sánchez-García D, 2019, ENERG BUILDINGS, V187, P173, DOI 10.1016/j.enbuild.2019.02.002
   Sánchez-García D, 2017, REV HABITAT SUSTENTA, V7, P7, DOI 10.22320/07190700.2017.07.02.01
   Sanchez-Guevara C, 2019, ENERG BUILDINGS, V190, P132, DOI 10.1016/j.enbuild.2019.02.024
   Sánchez-Guevara C, 2015, BUILD RES INF, V43, P737, DOI 10.1080/09613218.2014.984573
   Sánchez CSG, 2020, ENERG BUILDINGS, V223, DOI 10.1016/j.enbuild.2020.110157
   Sánchez CSG, 2020, ENERG POLICY, V144, DOI 10.1016/j.enpol.2020.111653
   Sánchez CSG, 2018, ENERG BUILDINGS, V169, P127, DOI 10.1016/j.enbuild.2018.03.038
   Sánchez CSG, 2017, BUILD ENVIRON, V114, P344, DOI 10.1016/j.buildenv.2016.12.029
   Sanz-Hernández A, 2019, ENERG POLICY, V124, P286, DOI 10.1016/j.enpol.2018.10.001
   Seebauer S, 2018, ENERGY RES SOC SCI, V46, P311, DOI 10.1016/j.erss.2018.08.006
   Semprini G, 2017, ENERG BUILDINGS, V156, P327, DOI 10.1016/j.enbuild.2017.09.044
   Shortt N, 2007, HEALTH PLACE, V13, P99, DOI 10.1016/j.healthplace.2005.10.004
   Sorrell S, 2007, ENERG POLICY, V35, P1858, DOI 10.1016/j.enpol.2006.06.008
   Sorrell S, 2015, RENEW SUST ENERG REV, V47, P74, DOI 10.1016/j.rser.2015.03.002
   Spanish Institute of Statistics, 2020, ACT UN EMPL RAT REG
   Spanish Institute of Statistics, 2011, CENS POP HOUS 2011
   Spanish Institute of Statistics, 2019, ATL DISTR HOUS INC
   Spanish Institute of Statistics, 2020, DEM POP
   Subhashini S, 2018, J BUILD ENG, V18, P395, DOI 10.1016/j.jobe.2018.04.014
   Lima CKT, 2020, PSYCHIAT RES, V287, DOI 10.1016/j.psychres.2020.112915
   The Government of Spain, 2019, NAT STRAT EN POV 201
   Thomson H, 2013, ENERG POLICY, V52, P563, DOI 10.1016/j.enpol.2012.10.009
   Tirado Herrero S., 2012, ENERGY POVERTY SPAIN
   Tirado Herrero S., 2014, ENERGY POVERTY SPAIN
   Uche-Soria M, 2020, ENERG POLICY, V140, DOI 10.1016/j.enpol.2020.111423
   Ürge-Vorsatz D, 2012, ENERG POLICY, V49, P83, DOI 10.1016/j.enpol.2011.11.093
   Vilches A, 2017, ENERG POLICY, V100, P283, DOI 10.1016/j.enpol.2016.10.016
   Wu W, 2018, ENERG CONVERS MANAGE, V177, P605, DOI 10.1016/j.enconman.2018.09.084
NR 67
TC 17
Z9 17
U1 1
U2 12
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 JAN 15
PY 2021
VL 231
AR 110571
DI 10.1016/j.enbuild.2020.110571
PG 16
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 PN6FX
UT WOS:000604573800006
OA Green Accepted
DA 2025-01-10
ER

PT J
AU Yousaf, AA
   Abbasi, KS
   Ahmad, A
   Hassan, I
   Sohail, A
   Qayyum, A
   Akram, MA
AF Yousaf, Ali Asad
   Abbasi, Kashif Sarfraz
   Ahmad, Asif
   Hassan, Imran
   Sohail, Asma
   Qayyum, Abdul
   Akram, Muhammad Aaqib
TI Physico-chemical and Nutraceutical Characterization of Selected
   Indigenous Guava (<i>Psidium guajava</i> L.) Cultivars
SO FOOD SCIENCE AND TECHNOLOGY
LA English
DT Article
DE guava cultivars; nutraceutical characterization; principal component
   analysis
ID ANTIOXIDANT ACTIVITY; CHEMICAL-COMPOSITION; PHYSICAL-PROPERTIES;
   PHENOLIC CONTENT; FRUIT; ATTRIBUTES; QUALITY
AB In order to ascertain physicochemical and nutraceutical attributes, indigenous guava (Psidium guajava L) cultivars were comprehensively characterized. Eight cultivars namely Gola, Chota Gola, Surahi, Choti Surahi, Sufaida, Sdabahar, Lal Badshah and Karela were selected due to their climatic adaptability and commercial suitability. All the cultivars showed significant variations in terms of their studied quality attributes. Amongst physical characteristics, Gola exhibited highest (79.9 mm(3)) GMD with lowest (50.3 mm(3)) was estimated in Choti Surahi. Insignificant varietal differences were observed in most of the proximate parameters as well as in mineral contents. Nutraceutical estimations showed significant variation in ascorbic acid (222.26-289.43 mg/100 g), total phenolic contents (94.06-190.64 mg GAE/100 g), total flavonoid contents (81.30-154.19 mg QE/100 g) and radical scavenging activity (27.70-78.15%) in the selected cultivars. A highly significant correlation (R-2 = 0.9970 p < 0.05) was observed between ascorbic acid and radical scavenging activity. In sensory evaluation, Gola received over all maximum scores (8.8) amongst its counterparts. Processed data were then analyzed using Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA). The combination of PCA and HCA yielded in a sufficient discrimination of the examined guava cultivars. In PCA analysis, first two PCA components explained 65.98% of the total variation. Dendrogram successfully classified the tested cultivars into three major groups featuring dissimilarities amongst the cultivars. Research outcome will provide baseline for the farmers, researchers, exporters and other stalk holders to realize the ultimate potential of indigenous guava cultivars for their appropriate commercial utilization.
C1 [Yousaf, Ali Asad; Abbasi, Kashif Sarfraz; Ahmad, Asif; Sohail, Asma; Akram, Muhammad Aaqib] Pir Mehr Ali Shah Arid Agr Univ, Inst Food & Nutr Sci, Rawalpindi, Pakistan.
   [Hassan, Imran] Pir Mehr Ali Shah Arid Agr Univ, Dept Hort, Rawalpindi, Pakistan.
   [Qayyum, Abdul] Univ Haripur, Dept Agron, Haripur City, Pakistan.
C3 Arid Agriculture University; Arid Agriculture University
RP Abbasi, KS (corresponding author), Pir Mehr Ali Shah Arid Agr Univ, Inst Food & Nutr Sci, Rawalpindi, Pakistan.
EM kash_if33@uaar.edu.pk
RI Hassan, Imran/HJZ-3524-2023; Ahmad, Asif/GWB-9399-2022; Qayyum,
   Abdul/ABD-6603-2021; Yousaf, Ali/AAA-4907-2019; Ahmad, Asif/G-2373-2011
OI QAYYUM, ABDUL/0000-0001-5322-7936; Abbasi, Kashif
   Sarfraz/0000-0002-4002-2103; Yousaf, Ali Asad/0000-0001-8727-9689;
   Ahmad, Asif/0000-0003-4657-7561; Sohail, Asma/0000-0002-0154-1365
CR Abbasi KS, 2019, FOOD SCI TECH-BRAZIL, V39, P308, DOI 10.1590/fst.26217
   Abbasi KS, 2016, J APPL BOT FOOD QUAL, V89, P142, DOI 10.5073/JABFQ.2016.089.017
   Aberoumand A, 2009, FOOD ANAL METHOD, V2, P116, DOI 10.1007/s12161-008-9038-z
   Ahmadi H., 2008, American-Eurasian Journal of Agricultural and Environmental Science, V3, P703
   Ahmed A, 2020, J FOOD PROCESS PRES, V44, DOI 10.1111/jfpp.14336
   Ali D. O., 2014, J AGR APPL SCI, V2, P27
   Ali S, 2011, SCI HORTIC-AMSTERDAM, V130, P386, DOI 10.1016/j.scienta.2011.05.040
   Alothman M, 2009, FOOD CHEM, V115, P785, DOI 10.1016/j.foodchem.2008.12.005
   Amerine M.A., 2013, PRINCIPLES SENSORY E
   [Anonymous], 1996, Trace Elements in Human Nutrition and Health
   AOAC, 2016, Official Methods of Analysis of the AOAC
   Badii A, 2012, INT J PREVENTIVE MED, V3, pS124
   Baryeh EA, 2001, J FOOD ENG, V47, P321, DOI 10.1016/S0260-8774(00)00136-9
   Bashir HA, 2003, FOOD CHEM, V80, P557, DOI 10.1016/S0308-8146(02)00345-X
   Chiveu J, 2019, J APPL BOT FOOD QUAL, V92, P151, DOI 10.5073/JABFQ.2019.092.021
   Cruz R., 2011, Practical Food and Research
   Demir F, 2003, J FOOD ENG, V60, P335, DOI 10.1016/S0260-8774(03)00056-6
   Dube A., 2019, J PHARMACOGNOSY PHYT, V8, P68
   Flores G, 2015, FOOD CHEM, V170, P327, DOI 10.1016/j.foodchem.2014.08.076
   Food and Agricultural Organization of the United Nations-FAO, 2017, PRODUCTION MANGOES M
   Gharibzahedi SMT, 2017, TRENDS FOOD SCI TECH, V62, P119, DOI 10.1016/j.tifs.2017.02.017
   Government of Pakistan. Ministry of National Food Science and Research, 2018, AGR STAT PAKISTAN EC
   Granato D, 2018, TRENDS FOOD SCI TECH, V72, P83, DOI 10.1016/j.tifs.2017.12.006
   Gull J, 2012, MOLECULES, V17, P3165, DOI 10.3390/molecules17033165
   Gupta M., 2018, RADICAL REORGANIZATI, P1, DOI 10.1007/978-3-319-54528-8_85-1
   Han H, 2018, REC NAT PROD, V12, P397, DOI 10.25135/rnp.46.17.09.155
   Hassimotto NMA, 2005, J AGR FOOD CHEM, V53, P2928, DOI 10.1021/jf047894h
   Ho R, 2012, NAT PROD RES, V26, P274, DOI 10.1080/14786419.2011.585610
   Iatridi V, 2019, NUTRIENTS, V11, DOI 10.3390/nu11010129
   Imran-ul-Haq, 2013, PAK J AGR SCI, V50, P707
   Ishtiaq Hassan Ishtiaq Hassan, 2012, Journal of Agricultural Research (Lahore), V50, P129
   Joseph B., 2011, International Journal of pharma and bio sciences, V2, P53
   Kadam D. M., 2012, International Journal of Food Science and Nutrition Engineering, V2, P7, DOI 10.5923/j.food.20120201.02
   Kaur S, 2009, FOOD BIOPROCESS TECH, V2, P96, DOI 10.1007/s11947-008-0119-1
   Khushk A. M., 2009, Journal of Agricultural Research (Lahore), V47, P201
   Kyriacou MC, 2020, SCI HORTIC-AMSTERDAM, V263, DOI 10.1016/j.scienta.2019.109116
   dos Santos WNL, 2017, MICROCHEM J, V133, P583, DOI 10.1016/j.microc.2017.04.029
   Mehmood A, 2014, SCI HORTIC-AMSTERDAM, V172, P221, DOI 10.1016/j.scienta.2014.04.005
   Muhammad Usman Muhammad Usman, 2012, African Journal of Biotechnology, V11, P10182, DOI 10.5897/AJB11.4311
   Murmu SB, 2018, FOOD CHEM, V245, P820, DOI 10.1016/j.foodchem.2017.11.104
   Oms-Oliu G, 2008, POSTHARVEST BIOL TEC, V50, P87, DOI 10.1016/j.postharvbio.2008.03.005
   Padilla-Ramirez JS, 2012, ACTA HORTIC, V959, P15
   Pereira MC, 2014, FOOD SCI TECH-BRAZIL, V34, P258, DOI 10.1590/fst.2014.0049
   Qannari E, 2017, CURR OPIN FOOD SCI, V15, P8, DOI 10.1016/j.cofs.2017.04.001
   Rajkumar, 2016, INDIAN J AGR SCI, V86, P1595
   Rana S, 2015, J FOOD SCI TECH MYS, V52, P8148, DOI 10.1007/s13197-015-1881-5
   Rehman SU, 2020, PATHOGENS, V9, DOI 10.3390/pathogens9030240
   Rodríguez Narciso N, 2010, Biotecnol Apl, V27, P238
   Rueda F. D., 2005, Guava (Psidium guajava L.) fruit phytochemicals
   Sahoo NR, 2015, SCI HORTIC-AMSTERDAM, V182, P1, DOI 10.1016/j.scienta.2014.10.029
   Sandhu KS, 2001, J FOOD SCI TECH MYS, V38, P622
   Shetgar S., 2017, International Journal of Oral Health & Medical Research, V3, P28
   Sinha M., 2017, J. Pharmacogn. Phytochem., V6, P856
   Soares FD, 2007, FOOD CHEM, V100, P15, DOI 10.1016/j.foodchem.2005.07.061
   Steel RGD., 1997, Principles and procedures of statistics: a biometrical approach
   Tanwar B., 2014, INT J AGR FOOD SCI T, V5, P47
   Uddin MS, 2002, J FOOD ENG, V51, P21, DOI 10.1016/S0260-8774(01)00031-0
   Upadhyay R, 2019, ROLE OF FUNCTIONAL FOOD SECURITY IN GLOBAL HEALTH, P365, DOI 10.1016/B978-0-12-813148-0.00021-9
   Verma M, 2018, INT FOOD RES J, V25, P762
   Waldron K W, 2003, Compr Rev Food Sci Food Saf, V2, P128, DOI 10.1111/j.1541-4337.2003.tb00019.x
   White PJ, 2009, NEW PHYTOL, V182, P49, DOI 10.1111/j.1469-8137.2008.02738.x
   Yahia EM, 2018, FRUIT AND VEGETABLE PHYTOCHEMICALS: CHEMISTRY AND HUMAN HEALTH, VOLS I & II, 2ND EDITION, P1
   Yusof S., 2003, ENCY FOOD SCI NUTR, P2985, DOI [DOI 10.1016/B0-12-227055-X/005721, 10.1016/B0-12-227055-X/005721, DOI 10.1016/B0-12-227055-X/00572-1]
NR 63
TC 20
Z9 22
U1 0
U2 6
PU SOC BRASILEIRA CIENCIA TECNOLOGIA ALIMENTOS
PI CAMPINAS
PA AV BRASIL 2880, CAXIA POSTAL 271 CEP 13001-970, CAMPINAS, SAO PAULO
   00000, BRAZIL
SN 0101-2061
EI 1678-457X
J9 FOOD SCI TECH-BRAZIL
JI Food Sci. Technol.
PD JAN-MAR
PY 2021
VL 41
IS 1
BP 47
EP 58
DI 10.1590/fst.35319
PG 12
WC Food Science & Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Food Science & Technology
GA RC5OJ
UT WOS:000632850100007
OA gold
DA 2025-01-10
ER

PT J
AU Daniels, E
   Bharwani, S
   Swartling, ÅG
   Vulturius, G
   Brandon, K
AF Daniels, Elizabeth
   Bharwani, Sukaina
   Swartling, Asa Gerger
   Vulturius, Gregor
   Brandon, Karen
TI Refocusing the climate services lens: Introducing a framework for
   co-designing "transdisciplinary knowledge integration processes" to
   build climate resilience
SO CLIMATE SERVICES
LA English
DT Article
DE Co-exploration; Co-production; Climate services; Capacity development;
   Integrated climate information; Transdisciplinary knowledge integration
ID COPRODUCTION; SCIENCE; INFORMATION
AB This paper seeks to reconceptualize climate services in light of the prevailing inability of existing climate information to spur needed policy and action. We propose refocusing the climate services lens by moving away from a narrow, supply-driven emphasis on products. Instead, we advocate moving towards a process-centric approach defined by transdisciplinary collaboration that purposefully seeks to bring about fundamental, long-term benefits. Such benefits include increased human and institutional capacity, and the creation of relationships that are essential components of science-informed decision-making for climate adaptation and beyond. Work underpinning this paper consists of a review of existing climate services guidance, and analyses of a survey of climate services stakeholders, and a climate information co-production process case study in Lusaka, Zambia. We identify elements needed to support complex, real-world decision-making that many existing climate services fail to sufficiently consider. We respond by introducing a framework (Tandem), which consists of structured elements and practical, guiding questions informed by empirical analysis. To lay the foundation for both science-informed policy and policy-informed science, the Tandem framework puts forward guidance to achieve three goals: 1) to improve the ways in which all participants work together to purposefully design transdisciplinary knowledge integration processes (co-exploration and co-production processes that bring together different knowledge types across the science-society interface); 2) to co-explore decision-relevant needs for the co-production of integrated climate information (i.e., decision-relevant climate and non-climate information); and, 3) to increase individual and institutional capacities, collaboration, communication and networks that can translate this information into climate-resilient decision-making and action.
C1 [Daniels, Elizabeth; Bharwani, Sukaina; Brandon, Karen] SEI, Oxford Eco Ctr, Roger House, Oxford OX2 0ES, England.
   [Swartling, Asa Gerger; Vulturius, Gregor] SEI Headquarters, Linnegatan 87D,Box 24218, S-10451 Stockholm, Sweden.
   [Vulturius, Gregor] Univ Edinburgh, Sch Geosci, Edinburgh, Midlothian, Scotland.
C3 Stockholm Environment Institute; University of Edinburgh
RP Bharwani, S (corresponding author), SEI, Oxford Eco Ctr, Roger House, Oxford OX2 0ES, England.
EM sukaina.bharwani@sei.org
RI Gerger Swartling, Asa/J-1420-2018
OI Gerger Swartling, Asa/0000-0003-3616-7323; Bharwani,
   Sukaina/0000-0002-0152-4565
FU UK Department for International Development (DFID); Natural Environment
   Research Council (NERC) under the FRACTAL project [NE/M020355/1];
   Swedish International Development Cooperation Agency (Sida) through
   SEI's Initiative on Climate Services; University of Oxford's Santander
   SME Universities Internship Programme; NERC [NE/M020355/1, NE/M020347/1]
   Funding Source: UKRI
FX This work was supported by the UK Department for International
   Development (DFID) and the Natural Environment Research Council (NERC)
   under the FRACTAL project [grant number NE/M020355/1]; the Swedish
   International Development Cooperation Agency (Sida) through SEI's
   Initiative on Climate Services; and, the University of Oxford's
   Santander SME Universities Internship Programme. These funding sources
   had no involvement in the study design, collection, analysis and
   interpretation of data or in the preparation or writing of this article.
CR Andre K., 2020, SEI Discussion Brief
   [Anonymous], 2015, ETHICAL FRAMEWORK CL
   [Anonymous], 2015, EUROPEAN RES INNOVAT
   [Anonymous], 2014, Earth Perspect, DOI DOI 10.1186/2194-6434-1-15
   [Anonymous], Computerunterstutzung Qualitative content analy
   Arrighi J, 2016, WORKING PAPER SERIES, V7
   Biskupska N., TESTING TANDEM FRAME
   Guy P, 2016, EARTHS FUTURE, V4, P79, DOI 10.1002/2015EF000338
   Bremer S, 2019, CLIM SERV, V13, P42, DOI 10.1016/j.cliser.2019.01.003
   Bremer S, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.482
   Butterfield R., 2020, USING AGR SECTOR LEN
   CARE International, 2018, PRACT GUID PART SCEN
   Carter S., 2019, Coproduction of African weather and climate services
   Cash DW, 2003, P NATL ACAD SCI USA, V100, P8086, DOI 10.1073/pnas.1231332100
   Christel I, 2018, CLIM SERV, V9, P111, DOI 10.1016/j.cliser.2017.06.002
   Cortekar J., 2017, EU MACS DELIVERABLE
   Daniels E., 2019, SEI brief
   Dilling L, 2011, GLOBAL ENVIRON CHANG, V21, P680, DOI 10.1016/j.gloenvcha.2010.11.006
   Dorward P., 2015, Participatory Integrated Climate Services for Agricultura (PICSA): Field Manual
   FUNTOWICZ SO, 1993, FUTURES, V25, P739, DOI 10.1016/0016-3287(93)90022-L
   Goosen H, 2014, REG ENVIRON CHANGE, V14, P1035, DOI 10.1007/s10113-013-0513-8
   Harvey B, 2019, ENVIRON POLICY GOV, V29, P107, DOI 10.1002/eet.1834
   Jack C., 2019, CLIMATE INFORM DISTI
   Jack CD, 2020, CLIM RISK MANAG, V29, DOI 10.1016/j.crm.2020.100239
   Klein RJT, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P899
   Klein RJT, 2014, ENVIRON SCI POLICY, V40, P101, DOI 10.1016/j.envsci.2014.01.011
   Larosa F, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab304d
   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
   Long QX., 2020, NAT MED, V26, P845, DOI [DOI 10.1038/S41591-020-0897-1, DOI 10.1038/s41591-020-0897-1]
   Mayring P., 2000, QUALITATIVE CONTENT, V1, P1, DOI 10.17169/fqs-1.2.1089
   McNie EC, 2007, ENVIRON SCI POLICY, V10, P17, DOI 10.1016/j.envsci.2006.10.004
   Meadow AM, 2015, WEATHER CLIM SOC, V7, P179, DOI 10.1175/WCAS-D-14-00050.1
   Norstrom AV, 2020, NAT SUSTAIN, V3, P182, DOI 10.1038/s41893-019-0448-2
   Pelling M, 2008, ENVIRON PLANN A, V40, P867, DOI 10.1068/a39148
   Porter JJ, 2017, ENVIRON SCI POLICY, V77, P9, DOI 10.1016/j.envsci.2017.07.004
   Pretorius L., 2019, 8 FRACTAL
   Reed MG, 2018, SOC NATUR RESOUR, V31, P39, DOI 10.1080/08941920.2017.1383545
   Rodela R, 2019, ENVIRON POLICY GOV, V29, P83, DOI 10.1002/eet.1842
   Salamanca A., INTEGRATED FRAMEWORK
   Santos T., CODESIGNING CLIMATE
   Schipper ELF, 2016, INT J DISASTER RESIL, V7, P216, DOI 10.1108/IJDRBE-03-2015-0014
   Scott D., 2019, FRACTAL Working Paper 7
   Soares MB, 2016, CLIMATIC CHANGE, V137, P89, DOI 10.1007/s10584-016-1671-8
   Steynor A, 2016, CLIM RISK MANAG, V13, P95, DOI 10.1016/j.crm.2016.03.001
   Tall A., 2014, LEARNING GOOD PRACTI
   Taylor I, 2017, ROUT STUD GLOB INF, P3
   Turnhout E, 2020, CURR OPIN ENV SUST, V42, P15, DOI 10.1016/j.cosust.2019.11.009
   Vaughan C, 2014, WIRES CLIM CHANGE, V5, P587, DOI 10.1002/wcc.290
   Vincent K, 2018, CLIM SERV, V12, P48, DOI 10.1016/j.cliser.2018.11.001
   Vincent K, 2017, CLIM POLICY, V17, P189, DOI 10.1080/14693062.2015.1075374
   WMO, 2016, SUPPL TECHN GUID NAT, P1170
   WMO, 2018, EXP TEAM US INT CLIM
NR 53
TC 61
Z9 63
U1 1
U2 18
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2405-8807
J9 CLIM SERV
JI Clim. Serv.
PD AUG
PY 2020
VL 19
AR 100181
DI 10.1016/j.cliser.2020.100181
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 OG6YQ
UT WOS:000582027500005
OA gold
DA 2025-01-10
ER

PT J
AU Breili, K
   Simpson, MJR
   Klokkervold, E
   Ravndal, OR
AF Breili, Kristian
   Simpson, Matthew James Ross
   Klokkervold, Erlend
   Ravndal, Oda Roaldsdotter
TI High-accuracy coastal flood mapping for Norway using lidar data
SO NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
LA English
DT Article
ID SEA-LEVEL RISE; FENNOSCANDIA
AB Using new high-accuracy light detection and ranging (lidar) elevation data we generate coastal flooding maps for Norway. Thus far, we have mapped similar to 80 % of the coast, for which we currently have data of sufficient accuracy to perform our analysis. Although Norway is generally at low risk from sea level rise largely owing to its steep topography and land uplift due to glacial isostatic adjustment, the maps presented here show that, on local scales, many parts of the coast are potentially vulnerable to flooding. There is a considerable amount of infrastructure at risk along the relatively long and complicated coastline. Nationwide we identify a total area of 400 km(2), 105 000 buildings, and 510 km of roads that are at risk of flooding from a 200-year storm surge event at present. These numbers will increase to 610 km(2), 137 000, and 1340 km with projected sea level rise to 2090 (95th percentile of RCP8.5 as recommended in planning). We find that some of our results are likely biased high owing to erroneous mapping (at least for lower water levels close to the tidal datum which delineates the coastline). A comparison of control points from different terrain types indicates that the elevation model has a root-mean-square error of 0.26 m and is the largest source of uncertainty in our mapping method. The coastal flooding maps and associated statistics are freely available, and alongside the development of coastal climate services, will help communicate the risks of sea level rise and storm surge to stakeholders. This will in turn aid coastal management and climate adaptation work in Norway.
C1 [Breili, Kristian; Simpson, Matthew James Ross] Norwegian Mapping Author, Geodet Inst, N-3507 Honefoss, Norway.
   [Breili, Kristian] Norwegian Univ Life Sci, Fac Sci & Technol, N-1432 As, Norway.
   [Klokkervold, Erlend] Norwegian Mapping Author, Geog Informat Syst Dev, N-3507 Honefoss, Norway.
   [Ravndal, Oda Roaldsdotter] Norwegian Mapping Author, Hydrog Serv, N-4021 Stavanger, Norway.
C3 Norwegian University of Life Sciences
RP Breili, K (corresponding author), Norwegian Mapping Author, Geodet Inst, N-3507 Honefoss, Norway.; Breili, K (corresponding author), Norwegian Univ Life Sci, Fac Sci & Technol, N-1432 As, Norway.
EM kristian.breili@kartverket.no
OI J.R. Simpson, Matthew/0009-0000-3408-1492
CR Almås AJ, 2012, BUILD RES INF, V40, P245, DOI 10.1080/09613218.2012.690953
   Aunan K, 2008, J COASTAL RES, V24, P403, DOI 10.2112/07A-0013.1
   Bamber JL, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aac2f0
   Breili K, 2017, J MAR SCI ENG, V5, DOI 10.3390/jmse5030029
   Church J.A., 2013, The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, P1137, DOI DOI 10.1017/CB09781107415315.026
   Clark PU, 2016, NAT CLIM CHANGE, V6, P360, DOI 10.1038/NCLIMATE2923
   Cooper HM, 2013, CLIMATIC CHANGE, V121, P635, DOI 10.1007/s10584-013-0987-x
   Cooper HM, 2013, PROG PHYS GEOG, V37, P745, DOI 10.1177/0309133313496835
   DeConto RM, 2016, NATURE, V531, P591, DOI 10.1038/nature17145
   Edwards TL, 2019, NATURE, V566, P58, DOI 10.1038/s41586-019-0901-4
   Gesch DB, 2018, FRONT EARTH SC-SWITZ, V6, DOI 10.3389/feart.2018.00230
   Gesch DB, 2013, J COASTAL RES, P197, DOI [10.2112/SI63-016.1, 10.2112/S163-016.1]
   Gesch DB, 2009, J COASTAL RES, V25, P49, DOI [10.2112/SI53-006.1, 10.2112/S153-006.1]
   Kartverket: Forprosjekt, 2014, TECH REP
   Kierulf HP, 2014, J GEOPHYS RES-SOL EA, V119, P6613, DOI 10.1002/2013JB010889
   Le Cozannet G, 2017, J MAR SCI ENG, V5, DOI 10.3390/jmse5040049
   LI ZL, 1992, PHOTOGRAMM REC, V14, P113
   Naess A, 2009, STRUCT SAF, V31, P325, DOI 10.1016/j.strusafe.2008.06.021
   Nicholls RJ., 2010, UNDERSTANDING SEA LE, P17
   Nicholls RJ, 2010, SCIENCE, V328, P1517, DOI 10.1126/science.1185782
   Olesen O, 2013, NORW J GEOL, V93, P189
   Ouassou Mohammed, 2015, International Journal of Navigation and Observation, V2015, DOI 10.1155/2015/346498
   Passeri DL, 2015, EARTHS FUTURE, V3, P159, DOI 10.1002/2015EF000298
   Poulter B, 2008, INT J GEOGR INF SCI, V22, P167, DOI 10.1080/13658810701371858
   Reutebuch SE, 2003, CAN J REMOTE SENS, V29, P527, DOI 10.5589/m03-022
   Roelvink D, 2009, COAST ENG, V56, P1133, DOI 10.1016/j.coastaleng.2009.08.006
   Rowley R.J., 2007, Eos, Transactions American Geophysical Union, V88, P105
   Sibson R., 1981, INTERPRETING MULTIVA, P21, DOI DOI 10.1007/3-540-26772-7_8
   Simpson M. J. R., 2015, TECH REP
   Simpson MJR, 2017, J MAR SCI ENG, V5, DOI 10.3390/jmse5030036
   Skjong M, 2013, J COASTAL RES, V29, P1029, DOI 10.2112/JCOASTRES-D-12-00208.1
   Solheim D, 2000, Symposium of the IAG, V7, P154
   Stocker, 2014, CLIMATE CHANGE 2013
   Strauss BH, 2015, P NATL ACAD SCI USA, V112, P13508, DOI 10.1073/pnas.1511186112
   Strauss BH, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/1/014033
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Titus J. G., 1995, TECH REP
   Vestol O, 2006, J GEODESY, V80, P248, DOI 10.1007/s00190-006-0063-7
   Vousdoukas MI, 2018, NAT CLIM CHANGE, V8, P776, DOI 10.1038/s41558-018-0260-4
   Vousdoukas MI, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-04692-w
NR 40
TC 10
Z9 10
U1 1
U2 8
PU COPERNICUS GESELLSCHAFT MBH
PI GOTTINGEN
PA BAHNHOFSALLEE 1E, GOTTINGEN, 37081, GERMANY
SN 1561-8633
EI 1684-9981
J9 NAT HAZARD EARTH SYS
JI Nat. Hazards Earth Syst. Sci.
PD FEB 27
PY 2020
VL 20
IS 2
BP 673
EP 694
DI 10.5194/nhess-20-673-2020
PG 22
WC Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences;
   Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology; Meteorology & Atmospheric Sciences; Water Resources
GA KS2QQ
UT WOS:000518155300003
OA gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Yan, JL
   Zhou, WQ
   Jenerette, GD
AF Yan, Jingli
   Zhou, Weiqi
   Jenerette, G. Darrel
TI Testing an energy exchange and microclimate cooling hypothesis for the
   effect of vegetation configuration on urban heat
SO AGRICULTURAL AND FOREST METEOROLOGY
LA English
DT Article
DE Configuration; Scale; Urban; Microclimate; MASTER; Remote sensing;
   Vegetation
ID LAND-SURFACE TEMPERATURE; LANDSCAPE PATTERN; AIR-TEMPERATURE; CENTRAL
   ARIZONA; CLIMATE-CHANGE; PHOENIX; ISLAND; IMPACTS; DYNAMICS; COVER
AB While an effect of urban vegetation configuration on land surface temperature (LST) has been identified worldwide, the mechanism underlying configuration-LST relationships remains unclear as most urban LST data only resolve to neighborhood scales. Here we ask: does urban vegetation provide more cooling arranged in fewer and larger patches or more numerous but smaller patches in the Phoenix metropolitan area, Arizona, USA? We hypothesized the combination of energy exchanges between adjacent patches and microclimate cooling induced by vegetation are key processes determining how configuration affects LST. Using high resolution thermal data (7 m), we evaluated predictions from this hypothesis through a multiple scale analysis spanning from within individual patches to among neighborhoods. We found tree cover is the dominant factor influencing urban cooling and that tree and grass configurations also substantially affect cooling, with effects generally exceeding 40% that of tree cover. The effects of tree and grass cover and configuration on LST were scale-dependent and reflect differences from within individual patches to among neighborhoods. In general, greater edge density and shape complexities of vegetation patches cool the landscape but may warm individual vegetation patches. Conversely, increasing individual vegetation patch size and reducing shape complexity may lead to cooler vegetation patches but a hotter landscape. Our findings suggest more edge area strengthens energy exchanges between vegetation and surroundings and more vegetation core area lead to greater cooling within individual patches. Through applications of high resolution thermal remote sensing, we are able to more directly connect effects of land cover composition and configuration to LST distributions that can help cities plan and evaluate local climate adaptation strategies.
C1 [Yan, Jingli; Jenerette, G. Darrel] Univ Calif Riverside, Dept Bot & Plant Sci, Riverside, CA 92521 USA.
   [Zhou, Weiqi] Chinese Acad Sci, Res Ctr Ecoenvironm Sci, State Key Lab Urban & Reg Ecol, 18 Shuangqing Rd, Beijing 100085, Peoples R China.
   [Zhou, Weiqi] Univ Chinese Acad Sci, 19 Yuquan Rd, Beijing 100049, Peoples R China.
C3 University of California System; University of California Riverside;
   Chinese Academy of Sciences; Research Center for Eco-Environmental
   Sciences (RCEES); Chinese Academy of Sciences; University of Chinese
   Academy of Sciences, CAS
RP Jenerette, GD (corresponding author), Univ Calif Riverside, Dept Bot & Plant Sci, Riverside, CA 92521 USA.
EM darrel.jenerette@ucr.edu
RI Zhou, Weiqi/G-2427-2010
OI Jenerette, G. Darrel/0000-0003-2387-7537; Yan,
   Jingli/0000-0001-7907-0068
FU National Aeronautics and Space Administration (NASA) [NNX12AQ02G,
   NNX15AF36G]; National Science Foundation (NSF) [CBET-1444758]
FX This research was supported by National Aeronautics and Space
   Administration (NASA) through grants NNX12AQ02G and NNX15AF36G, and
   National Science Foundation (NSF) through grant CBET-1444758.
CR AKAIKE H, 1974, IEEE T AUTOMAT CONTR, VAC19, P716, DOI 10.1109/TAC.1974.1100705
   Akbari H, 2005, ENERG POLICY, V33, P721, DOI 10.1016/j.enpol.2003.10.001
   Baatz M., 2008, Progressing from object-based to object-oriented image analysis, P29
   Benz UC, 2004, ISPRS J PHOTOGRAMM, V58, P239, DOI 10.1016/j.isprsjprs.2003.10.002
   Bernstein LS, 2005, P SOC PHOTO-OPT INS, V5806, P668, DOI 10.1117/12.603359
   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
   Chow WTL, 2012, B AM METEOROL SOC, V93, P517, DOI 10.1175/BAMS-D-11-00011.1
   Connors JP, 2013, LANDSCAPE ECOL, V28, P271, DOI 10.1007/s10980-012-9833-1
   Coutts AM, 2016, REMOTE SENS ENVIRON, V186, P637, DOI 10.1016/j.rse.2016.09.007
   Crum SM, 2017, J APPL METEOROL CLIM, V56, P2531, DOI 10.1175/JAMC-D-17-0054.1
   Deng CB, 2013, REMOTE SENS ENVIRON, V131, P262, DOI 10.1016/j.rse.2012.12.020
   Didham RK, 1999, BIOTROPICA, V31, P17, DOI 10.1111/j.1744-7429.1999.tb00113.x
   Fan C, 2015, PROG PHYS GEOG, V39, P199, DOI 10.1177/0309133314567583
   Grimm NB, 2004, URBAN ECOSYST, V7, P199, DOI DOI 10.1023/B:UEC0.0000044036.59953.A1
   Heinl M, 2015, LANDSCAPE URBAN PLAN, V134, P33, DOI 10.1016/j.landurbplan.2014.10.003
   Hook SJ, 2001, REMOTE SENS ENVIRON, V76, P93, DOI 10.1016/S0034-4257(00)00195-4
   Ignatieva M, 2015, URBAN FOR URBAN GREE, V14, P383, DOI 10.1016/j.ufug.2015.04.003
   Jenerette GD, 2018, LANDSCAPE ECOL, V33, P1655, DOI 10.1007/s10980-018-0708-y
   Jenerette GD, 2016, LANDSCAPE ECOL, V31, P745, DOI 10.1007/s10980-015-0284-3
   Jenerette GD, 2001, LANDSCAPE ECOL, V16, P611, DOI 10.1023/A:1013170528551
   Jiao M, 2017, AGR FOREST METEOROL, V247, P293, DOI 10.1016/j.agrformet.2017.08.013
   Johnson B.R., 1998, In-Scene Atmospheric Compensation: Application to SEBASS Data Collected at the ARM Site
   KEALY PS, 1993, IEEE T GEOSCI REMOTE, V31, P1155, DOI 10.1109/36.317447
   Köppen W, 2011, METEOROL Z, V20, P351, DOI 10.1127/0941-2948/2011/105
   Kong FH, 2014, LANDSCAPE URBAN PLAN, V128, P35, DOI 10.1016/j.landurbplan.2014.04.018
   LAURANCE WF, 1991, BIOL CONSERV, V55, P77, DOI 10.1016/0006-3207(91)90006-U
   Leuzinger S, 2010, AGR FOREST METEOROL, V150, P56, DOI 10.1016/j.agrformet.2009.08.006
   Li JX, 2011, REMOTE SENS ENVIRON, V115, P3249, DOI 10.1016/j.rse.2011.07.008
   Li XM, 2013, LANDSCAPE URBAN PLAN, V114, P1, DOI 10.1016/j.landurbplan.2013.02.005
   Li XM, 2012, LANDSCAPE ECOL, V27, P887, DOI 10.1007/s10980-012-9731-6
   Li XX, 2017, LANDSCAPE URBAN PLAN, V163, P107, DOI 10.1016/j.landurbplan.2017.02.009
   Li XX, 2016, REMOTE SENS ENVIRON, V174, P233, DOI 10.1016/j.rse.2015.12.022
   Li XX, 2014, INT J APPL EARTH OBS, V33, P321, DOI 10.1016/j.jag.2014.04.018
   Litvak E, 2016, J ARID ENVIRON, V134, P87, DOI 10.1016/j.jaridenv.2016.06.016
   MATLACK GR, 1994, J ECOL, V82, P113, DOI 10.2307/2261391
   McDonald RI, 2020, ECOSYSTEMS, V23, P137, DOI 10.1007/s10021-019-00395-5
   Myint Soe, 2015, Ecosystem Health and Sustainability, V1, P15, DOI 10.1890/EHS14-0028.1
   Peng J, 2018, REMOTE SENS ENVIRON, V215, P255, DOI 10.1016/j.rse.2018.06.010
   Ren P, 2015, REMOTE SENS-BASEL, V7, P14259, DOI 10.3390/rs71014259
   ROSENFELD AH, 1995, ENERG BUILDINGS, V22, P255, DOI 10.1016/0378-7788(95)00927-P
   Ruddell D, 2013, CLIM RES, V55, P201, DOI 10.3354/cr01130
   Saura S, 2004, LANDSCAPE ECOL, V19, P197, DOI 10.1023/B:LAND.0000021724.60785.65
   Saura S, 2001, PHOTOGRAMM ENG REM S, V67, P1027
   Shashua-Bar L, 2000, ENERG BUILDINGS, V31, P221, DOI 10.1016/S0378-7788(99)00018-3
   Shiflett SA, 2017, SCI TOTAL ENVIRON, V579, P495, DOI 10.1016/j.scitotenv.2016.11.069
   Skelhorn C, 2014, LANDSCAPE URBAN PLAN, V121, P129, DOI 10.1016/j.landurbplan.2013.09.012
   Song J, 2014, LANDSCAPE URBAN PLAN, V123, P145, DOI 10.1016/j.landurbplan.2013.11.014
   Stone B, 2012, LANDSCAPE URBAN PLAN, V107, P263, DOI 10.1016/j.landurbplan.2012.05.014
   Sun RH, 2017, ECOSYST SERV, V23, P38, DOI 10.1016/j.ecoser.2016.11.011
   Takebayashi H, 2009, SOL ENERGY, V83, P1211, DOI 10.1016/j.solener.2009.01.019
   Taleghani M, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/2/024003
   Tayyebi A, 2018, INT J REMOTE SENS, V39, P3010, DOI 10.1080/01431161.2018.1437292
   Tayyebi A, 2016, SCI TOTAL ENVIRON, V548, P60, DOI 10.1016/j.scitotenv.2016.01.049
   Weng QH, 2004, REMOTE SENS ENVIRON, V89, P467, DOI 10.1016/j.rse.2003.11.005
   Weng QH, 2006, REMOTE SENS ENVIRON, V104, P119, DOI 10.1016/j.rse.2006.05.002
   Weng QH, 2009, ISPRS J PHOTOGRAMM, V64, P335, DOI 10.1016/j.isprsjprs.2009.03.007
   Weng QH, 2008, IEEE J-STARS, V1, P154, DOI 10.1109/JSTARS.2008.917869
   Wetherley EB, 2018, REMOTE SENS ENVIRON, V213, P18, DOI 10.1016/j.rse.2018.04.051
   Wu JG, 2004, LANDSCAPE ECOL, V19, P125, DOI 10.1023/B:LAND.0000021711.40074.ae
   WU JG, 1991, ECOL MODEL, V58, P249, DOI 10.1016/0304-3800(91)90039-4
   Yan JL, 2018, URBAN FOR URBAN GREE, V31, P230, DOI 10.1016/j.ufug.2018.01.021
   Yang CB, 2017, REMOTE SENS-BASEL, V9, DOI 10.3390/rs9101066
   Yokohari M, 2001, LANDSCAPE URBAN PLAN, V53, P17, DOI 10.1016/S0169-2046(00)00123-7
   Zhang X, 2009, INT J REMOTE SENS, V30, P2105, DOI 10.1080/01431160802549252
   Zhang YS, 2013, INT J REMOTE SENS, V34, P168, DOI 10.1080/01431161.2012.712227
   Zhang YJ, 2017, LANDSCAPE URBAN PLAN, V165, P162, DOI 10.1016/j.landurbplan.2017.04.009
   Zhao XF, 2010, INT J SUST DEV WORLD, V17, P311, DOI 10.1080/13504509.2010.490333
   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
NR 70
TC 36
Z9 38
U1 6
U2 94
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 2019
VL 279
AR 107666
DI 10.1016/j.agrformet.2019.107666
PG 11
WC Agronomy; Forestry; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Agriculture; Forestry; Meteorology & Atmospheric Sciences
GA JS3GO
UT WOS:000500197400002
OA Bronze
DA 2025-01-10
ER

PT J
AU Xu, LL
   Cui, SH
   Tang, JX
   Nguyen, M
   Liu, JH
   Zhao, YC
AF Xu, Lilai
   Cui, Shenghui
   Tang, Jianxiong
   Minh Nguyen
   Liu, Jiahui
   Zhao, Yanchuang
TI Assessing the adaptive capacity of urban form to climate stress: a case
   study on an urban heat island
SO ENVIRONMENTAL RESEARCH LETTERS
LA English
DT Article
DE climate stress; urban form; adaptive capacity; land use; assessment
   approach
ID LAND-SURFACE TEMPERATURE; SEA-LEVEL RISE; CITIES LEAD; IMPACT; WAVES;
   CONFIGURATION; METROPOLITAN; MITIGATION; PATTERN; SHAPE
AB Urban land planning shapes the urban form and is considered to be one of the many tools important for climate adaptation. Yet there is little knowledge about the adaptive capacity of urban forms to climate stress, or of an appropriate assessment method. Through a case study on the urban heat island (UHI) in Xiamen City, China, we propose a novel approach that integrates several aspects to assess the adaptive capacity of urban form to climate stress. These aspects include the calculation of urban form, the determination of climate stress and land use modeling. Our results demonstrate that this approach is applicable for assessing the adaptive capacity of urban form in the historical, current and future multitime scales. Both urban planning aspects (e.g. population density, land use mix, road density and percentage of green open space) and landscape features (e.g. shape complexity, contiguity and compactness) are found to be key urban form drivers affecting UHI. The adaptive capacity of the urban form to UHI in Xiamen City has been declining dramatically, and is expected to continue to decline in the future as long as adaptation continues to not be integrated in urban land use planning. Our analysis suggests that urban managers need to review the past development model of land use and rethink the current approach to urban planning: most urgent is the need to take full account of adaptation in future land use planning and implementation, so as to enhance climate resilience.
C1 [Xu, Lilai; Cui, Shenghui; Tang, Jianxiong] Chinese Acad Sci, Inst Urban Environm, Key Lab Urban Environm & Hlth, Xiamen 361021, Peoples R China.
   [Xu, Lilai; Cui, Shenghui; Tang, Jianxiong] Xiamen Key Lab Urban Metab, Xiamen 361021, Peoples R China.
   [Tang, Jianxiong] Univ Chinese Acad Sci, Beijing 100049, Peoples R China.
   [Minh Nguyen] Commmonwealth Sci & Ind Res Org, Land & Water Flagship, Clayton, Vic 3168, Australia.
   [Liu, Jiahui; Zhao, Yanchuang] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China.
C3 Chinese Academy of Sciences; Institute of Urban Environment, CAS;
   Chinese Academy of Sciences; University of Chinese Academy of Sciences,
   CAS; Commonwealth Scientific & Industrial Research Organisation (CSIRO);
   Chinese Academy of Sciences; The Institute of Remote Sensing & Digital
   Earth, CAS
RP Cui, SH (corresponding author), Chinese Acad Sci, Inst Urban Environm, Key Lab Urban Environm & Hlth, Xiamen 361021, Peoples R China.; Cui, SH (corresponding author), Xiamen Key Lab Urban Metab, Xiamen 361021, Peoples R China.
EM shcui@iue.ac.cn
RI Nguyen, Minh/A-6100-2008; Cui, shenghui/B-3926-2008; Yang,
   Zhan/GQG-9995-2022
OI Nguyen, Minh/0000-0001-9686-875X
FU National Key Research and Development Program of China [2017YFC0506603];
   National Natural Science Foundation of China [41371205, 41661144032];
   Bureau of International Co-operation Chinese Academy of Sciences
   [132C35KYSB20150005]
FX This study was supported by the National Key Research and Development
   Program of China (2017YFC0506603), the National Natural Science
   Foundation of China (41371205 and 41661144032), and the Bureau of
   International Co-operation Chinese Academy of Sciences
   (132C35KYSB20150005).
CR Adachi SA, 2014, J APPL METEOROL CLIM, V53, P1886, DOI 10.1175/JAMC-D-13-0194.1
   Aerts JCJH, 2014, SCIENCE, V344, P472, DOI 10.1126/science.1248222
   Alobaydi D, 2016, PROCEDIA ENGINEER, V145, P820, DOI 10.1016/j.proeng.2016.04.107
   Angel S., 2010, PLANET CITIES URBAN
   Angel S, 2010, CAN GEOGR-GEOGR CAN, V54, P441, DOI 10.1111/j.1541-0064.2009.00304.x
   Bai XM, 2014, NATURE, V509, P158, DOI 10.1038/509158a
   Bereitschaft B, 2014, APPL SPAT ANAL POLIC, V7, P119, DOI 10.1007/s12061-013-9092-9
   Biesbroek GR, 2009, HABITAT INT, V33, P230, DOI 10.1016/j.habitatint.2008.10.001
   Bilskie MV, 2014, GEOPHYS RES LETT, V41, P927, DOI 10.1002/2013GL058759
   Birkmann J, 2016, NATURE, V537, P605, DOI 10.1038/537605a
   Bulkeley H, 2013, ROUTL CRIT INTRO URB, P1
   Buyantuyev A, 2010, LANDSCAPE ECOL, V25, P17, DOI 10.1007/s10980-009-9402-4
   Cao C, 2016, NAT COMMUN, V7, DOI 10.1038/ncomms12509
   Chen MP, 2015, CLIMATIC CHANGE, V128, P367, DOI 10.1007/s10584-014-1163-7
   Cinner JE, 2018, NAT CLIM CHANGE, V8, P117, DOI 10.1038/s41558-017-0065-x
   Connors JP, 2013, LANDSCAPE ECOL, V28, P271, DOI 10.1007/s10980-012-9833-1
   Debbage N, 2015, COMPUT ENVIRON URBAN, V54, P181, DOI 10.1016/j.compenvurbsys.2015.08.002
   Di Gregorio M, 2017, ENVIRON SCI POLICY, V67, P35, DOI 10.1016/j.envsci.2016.11.004
   Du HY, 2016, SCI TOTAL ENVIRON, V571, P461, DOI 10.1016/j.scitotenv.2016.07.012
   Estoque RC, 2017, SCI TOTAL ENVIRON, V577, P349, DOI 10.1016/j.scitotenv.2016.10.195
   Fang QH, 2016, SCIENCE, V354, P425, DOI 10.1126/science.aak9826
   Forman RTT, 2016, NATURE, V537, P608, DOI 10.1038/537608a
   Founda D, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-11407-6
   Gage EA, 2017, URBAN ECOSYST, V20, P1229, DOI 10.1007/s11252-017-0675-0
   Gao L, 2017, NATURE, V544, P217, DOI 10.1038/nature21694
   Grimmond S, 2007, GEOGR J, V173, P83, DOI 10.1111/j.1475-4959.2007.232_3.x
   Gunawardena KR, 2017, SCI TOTAL ENVIRON, V584, P1040, DOI 10.1016/j.scitotenv.2017.01.158
   Hathway EA, 2012, BUILD ENVIRON, V58, P14, DOI 10.1016/j.buildenv.2012.06.013
   Hinkel J, 2018, NAT CLIM CHANGE, V8, P570, DOI 10.1038/s41558-018-0176-z
   Hogarth JR, 2016, SUSTAINABILITY-BASEL, V8, DOI 10.3390/su8030228
   Hung HC, 2013, CLIMATIC CHANGE, V120, P491, DOI 10.1007/s10584-013-0819-z
   Juhola S, 2015, MITIG ADAPT STRAT GL, V20, P99, DOI 10.1007/s11027-013-9481-z
   LAGRO J, 1991, PHOTOGRAMM ENG REM S, V57, P285
   Lentz EE, 2016, NAT CLIM CHANGE, V6, P696, DOI [10.1038/NCLIMATE2957, 10.1038/nclimate2957]
   Li D, 2013, J APPL METEOROL CLIM, V52, P2051, DOI 10.1175/JAMC-D-13-02.1
   Li JX, 2011, REMOTE SENS ENVIRON, V115, P3249, DOI 10.1016/j.rse.2011.07.008
   Li XX, 2016, REMOTE SENS ENVIRON, V174, P233, DOI 10.1016/j.rse.2015.12.022
   Mechler R, 2016, SCIENCE, V354, P290, DOI 10.1126/science.aag2514
   Mora C, 2017, NAT CLIM CHANGE, V7, P501, DOI [10.1038/nclimate3322, 10.1038/NCLIMATE3322]
   Muscato C, 2017, WHAT IS URBAN FORM D
   Oke T, 2011, URBAN HEAT ISLAND RO, P20
   Pancost RD, 2016, NAT GEOSCI, V9, P264, DOI 10.1038/ngeo2690
   Peng J, 2016, REMOTE SENS ENVIRON, V173, P145, DOI 10.1016/j.rse.2015.11.027
   Prein AF, 2017, NAT CLIM CHANGE, V7, P48, DOI [10.1038/nclimate3168, 10.1038/NCLIMATE3168]
   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]
   Qiao Z, 2014, ADV METEOROL, V2014, DOI 10.1155/2014/187169
   [Renaud FabriceG. UNU (United Nations University) UNU (United Nations University)], 2013, The Role of Ecosystems in Disaster Risk Reduction
   Rizwan AM, 2008, J ENVIRON SCI, V20, P120, DOI 10.1016/S1001-0742(08)60019-4
   Rosenzweig C, 2010, NATURE, V467, P909, DOI 10.1038/467909a
   Schwarz N, 2015, J URBAN PLAN DEV, V141, DOI 10.1061/(ASCE)UP.1943-5444.0000263
   Seto KC, 2017, P NATL ACAD SCI USA, V114, P8935, DOI 10.1073/pnas.1606037114
   Seto KC, 2014, CLIMATE CHANGE 2014: MITIGATION OF CLIMATE CHANGE, P923
   Shen L, 2016, GEOPHYS RES LETT, V43, P4017, DOI 10.1002/2016GL068432
   Smit B, 2001, CLIMATE CHANGE 2001: IMPACTS, ADAPTATION, AND VULNERABILITY, P877
   Stone B, 2010, ENVIRON HEALTH PERSP, V118, P1425, DOI 10.1289/ehp.0901879
   United Nations, 2015, WORLD URB PROSP 2014
   Wamsler C, 2013, J CLEAN PROD, V50, P68, DOI 10.1016/j.jclepro.2012.12.008
   Wang CY, 2016, REMOTE SENS-BASEL, V8, DOI 10.3390/rs8030185
   Ward K, 2016, SCI TOTAL ENVIRON, V569, P527, DOI 10.1016/j.scitotenv.2016.06.119
   Watson RT, 2001, CLIMATE CHANGE 2001: IMPACTS, ADAPTATION, AND VULNERABILITY, pIX
   Winsemius HC, 2016, NAT CLIM CHANGE, V6, P381, DOI [10.1038/nclimate2893, 10.1038/NCLIMATE2893]
   Xiamen Urban Planning & Design Institute, 2017, XIAM MAST PLANN 2017
   Xiamen Urban Planning & Design Institute, 2015, XIAM MAST PLANN 2011
   Xiamen Urban Planning & Design Institute, 2004, XIAM MAST PLANN 2004
   Yang QQ, 2017, SCI REP, V7
   Zhou B, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-04242-2
NR 66
TC 33
Z9 35
U1 10
U2 107
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 APR
PY 2019
VL 14
IS 4
AR 044013
DI 10.1088/1748-9326/aafe27
PG 13
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA HR5RP
UT WOS:000463204900002
OA gold
DA 2025-01-10
ER

PT J
AU Giampieri, MA
   DuBois, B
   Allred, S
   Bunting-Howarth, K
   Fisher, K
   Moy, J
   Sanderson, EW
AF Giampieri, Mario A.
   DuBois, Bryce
   Allred, Shorna
   Bunting-Howarth, Katherine
   Fisher, Kim
   Moy, Jesse
   Sanderson, Eric W.
TI Visions of resilience: lessons from applying a digital democracy tool in
   New York's Jamaica Bay watershed
SO URBAN ECOSYSTEMS
LA English
DT Article
DE Visionmaker; Climate adaptation; Green infrastructure; Urban estuary;
   Community-based planning
ID CITY PANEL; CLIMATE; ADAPTATION; SCIENCE
AB Resilience to extreme weather events and other sudden changes is an issue facing many communities in the early twenty-first century. Planning to respond to disasters is particularly complicated in densely inhabited, multi-jurisdictional urban social-ecological systems like the watershed of Jamaica Bay, a large urbanized estuary on the south side of New York City. This area contains parklands managed by New York City, the National Park Service, and other agencies, four sewage treatment plants, three former landfills, and urban and suburban communities, all of which were heavily impacted by Hurricane Sandy in 2012. Here successful resilience planning and response requires participation from a wide variety of government and civil society players each with different types of knowledge, value systems, and expectations about what resilience means. To investigate how visions of future resilience differed among several communities living in or concerned with Jamaica Bay, New York, we deployed a free, Internet-based modeling framework called Visionmaker that enabled interactive scenario creation and testing. Through a series of standardized workshops, we recruited participants from a variety of different communities of practice (i.e. researchers, land managers, educators, non-governmental organization staff, and community board members) to design visions of resilience. Visions spanned terrestrial and marine environments and contained natural and built ecosystems. Most users favored increasing resilience through expanding salt marsh and green infrastructure while, for the most part, keeping the built city landscape of streets and buildings intact. We compare and contrast these visions and discuss the implications for future resilience planning in coastal cities.
C1 [Giampieri, Mario A.; Fisher, Kim; Moy, Jesse; Sanderson, Eric W.] Wildlife Conservat Soc, 2300 Southern Blvd, Bronx, NY 10460 USA.
   [Giampieri, Mario A.] MIT, Dept Urban Studies & Planning, 77 Massachusetts Ave, Cambridge, MA 02139 USA.
   [DuBois, Bryce; Allred, Shorna] Cornell Univ, Dept Nat Resources, 102 Fernow Hall, Ithaca, NY 14853 USA.
   [Bunting-Howarth, Katherine] Cornell Univ, New York Sea Grant, 112 Rice Hall, Ithaca, NY 14853 USA.
C3 Wildlife Conservation Society; Massachusetts Institute of Technology
   (MIT); Cornell University; Cornell University
RP Giampieri, MA (corresponding author), Wildlife Conservat Soc, 2300 Southern Blvd, Bronx, NY 10460 USA.; Giampieri, MA (corresponding author), MIT, Dept Urban Studies & Planning, 77 Massachusetts Ave, Cambridge, MA 02139 USA.
EM mariogiampieri@gmail.com
RI Sanderson, Eric/O-1664-2019
OI Allred, Shorna/0000-0001-6237-0638; SANDERSON, ERIC
   W./0000-0002-7477-0193
FU United States Department of the Interior, National Park Service
   [P14AC01473]; Rockefeller Foundation; Brooke Astor Fund for New York
   City Education at the New York Community Trust; Summit Foundation;
   Science and Resilience Institute at Jamaica Bay
FX This study was supported by funding from the United States Department of
   the Interior, National Park Service [Cooperative agreement: P14AC01473].
   Additional funding for development of Visionmaker was provided by the
   Rockefeller Foundation, Brooke Astor Fund for New York City Education at
   the New York Community Trust, and the Summit Foundation. We would also
   like to acknowledge and thank all the participants in the Visionmaker
   workshops and the support of the Science and Resilience Institute at
   Jamaica Bay for this effort.
CR Adger WN, 2003, ECON GEOGR, V79, P387
   [Anonymous], 2013, HURR SAND REB STRATO
   [Anonymous], 2013, ROCKW BEACH QUEENS R
   [Anonymous], 2006, Resilience Thinking: Sustaining Ecosystems and People in a Changing World
   Black F.R., 1981, Jamaica Bay: a History. Cultural Resource Management Study No. 3, Gateway National Recreation Area, New York
   Brossard D, 2013, SCIENCE, V339, P40, DOI 10.1126/science.1232329
   Buxton H. T., 1995, 9276 US GEOL SURV
   Callon M., 1999, SCI TECHNOLOGY SOC, V4, P81, DOI https://doi.org/10.1177/097172189900400106
   Hegger D, 2012, ENVIRON SCI POLICY, V18, P52, DOI 10.1016/j.envsci.2012.01.002
   Holling C.S., 1973, Annual Rev Ecol Syst, V4, P1, DOI 10.1146/annurev.es.04.110173.000245
   Horton R, 2015, ANN NY ACAD SCI, V1336, P36, DOI 10.1111/nyas.12593
   Horton R, 2015, ANN NY ACAD SCI, V1336, P18, DOI 10.1111/nyas.12586
   Kates RW, 2006, P NATL ACAD SCI USA, V103, P14653, DOI 10.1073/pnas.0605726103
   Kingston R., 2007, CARTOGR J, V44, P138, DOI DOI 10.1179/000870407X213459
   Lane SN, 2011, T I BRIT GEOGR, V36, P15, DOI 10.1111/j.1475-5661.2010.00410.x
   Manzo LC, 2006, J PLAN LIT, V20, P335, DOI 10.1177/0885412205286160
   McNie EC, 2007, ENVIRON SCI POLICY, V10, P17, DOI 10.1016/j.envsci.2006.10.004
   Mitchell VG, 2001, ENVIRON MODELL SOFTW, V16, P615, DOI 10.1016/S1364-8152(01)00029-9
   Orton P, 2012, J GEOPHYS RES-OCEANS, V117, DOI 10.1029/2012JC008220
   Patton M Q., 2002, Qualitative research evaluation methods, P40
   Reed MS, 2008, BIOL CONSERV, V141, P2417, DOI 10.1016/j.biocon.2008.07.014
   Sanderson Eric., 2009, MANNAHATTA NATURAL H
   Sanderson EW, 2016, NORTHEAST NAT, V23, P277, DOI 10.1656/045.023.0208
   Sanderson Eric W., 2016, Prospects for Resilience: Insights from New York Citys Jamaica Bay
   Scileppi E, 2007, GEOCHEM GEOPHY GEOSY, V8, DOI 10.1029/2006GC001463
   Seijger C, 2013, ENVIRON SCI POLICY, V29, P103, DOI 10.1016/j.envsci.2013.02.007
   Shirky C., 2008, Here Comes Everybody: The Power of Organizing Without Organizations
   Spence A, 2012, RISK ANAL, V32, P957, DOI 10.1111/j.1539-6924.2011.01695.x
   Sullivan BL, 2009, BIOL CONSERV, V142, P2282, DOI 10.1016/j.biocon.2009.05.006
   Surowiecki James, 2005, WISDOM CROWDS, DOI DOI 10.5555/1095645
   Swanson L., 2016, PROSPECTS RESILIENCE
   Talke SA, 2014, GEOPHYS RES LETT, V41, P3149, DOI 10.1002/2014GL059574
   Trope Y, 2010, PSYCHOL REV, V117, P440, DOI 10.1037/a0018963
   U. S. Census Bureau (, 2016, METR MICR STAT AR
   U. S. Census Bureau Population Estimates Program, 2016, QUICKFACTS QUEEN COU
   U. S. Census Bureau Population Estimates Program, 2016, QUICKFACTS KINGS COU
   U. S. Congress, 1916, ORG ACT OF 1916
   Vörösmarty CJ, 1989, GLOBAL BIOGEOCHEM CY, V3, P241, DOI 10.1029/GB003i003p00241
   Vorosmarty CJ, 1996, WATER RESOUR RES, V32, P3137, DOI 10.1029/96WR01333
   Wenger E., 1999, Communities of practice: Learning, meaning, and identity, V1, DOI DOI 10.1017/CBO9780511803932
   Wilsdon J., 2004, See-Through Science: Why Public Engagement Needs to Move Upstream
NR 41
TC 4
Z9 4
U1 1
U2 40
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 1083-8155
EI 1573-1642
J9 URBAN ECOSYST
JI Urban Ecosyst.
PD FEB
PY 2019
VL 22
IS 1
SI SI
BP 1
EP 17
DI 10.1007/s11252-017-0701-2
PG 17
WC Biodiversity Conservation; Ecology; Environmental Sciences; Urban
   Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Biodiversity & Conservation; Environmental Sciences & Ecology; Urban
   Studies
GA HJ7SL
UT WOS:000457397500001
OA Green Submitted, Bronze
DA 2025-01-10
ER

PT J
AU Stults, M
   Woodruff, SC
AF Stults, Missy
   Woodruff, Sierra C.
TI Looking under the hood of local adaptation plans: shedding light on the
   actions prioritized to build local resilience to climate change
SO MITIGATION AND ADAPTATION STRATEGIES FOR GLOBAL CHANGE
LA English
DT Article
DE Adaptation; Local government; Planning; Strategies; Action; Resilience;
   Community
ID ADAPTIVE CAPACITY; URBAN CLIMATE; OVERCOMING BARRIERS; QUALITY;
   METAANALYSIS; CALIFORNIA; IMPACTS; STATES; WATER
AB In the face of a changing climate, many United States (US) local governments are creating plans to prepare. These plans layout how a community is vulnerable to existing and future changes in climate as well as what actions they propose taking to prepare. The actions included in these plans provide insight into what local governments feel they have the ability to undertake, as well as what actions they believe are important to building resilience. To date, little to no analysis has been conducted on the content of these plans, leaving researchers, practitioners, and those supporting communities with limited understanding of what gaps need to be filled or how best to support locally prioritized climate action. This paper analyzes the content of 43 stand alone climate adaptation plans from US local communities to identify the types of actions proposed and how those actions compare to what researchers indicate the communities should be prioritizing based on regional climate projections. The results indicate that local communities include numerous and varied actions in their adaptation plans and that the majority of communities are selecting actions that are theoretically appropriate given projected changes in regional climate. Yet some types of actions, such as building codes and advocacy, are not being widely used. These results contrast with previous studies, which found that local communities focus primarily on capacity building approaches. Findings also demonstrate that plans rarely contain significant details about how actions will be implemented, raising questions about whether plans will translate into real-world projects.
C1 [Stults, Missy] Univ Michigan, Sch Nat Resources & Environm, 440 Church St, Ann Arbor, MI 48109 USA.
   [Woodruff, Sierra C.] Univ North Carolina Chapel Hill, Curriculum Environm & Ecol, Venable Hall,Campus Box 3275, Chapel Hill, NC 27599 USA.
C3 University of Michigan System; University of Michigan; University of
   North Carolina School of Medicine; University of North Carolina;
   University of North Carolina Chapel Hill
RP Stults, M (corresponding author), Univ Michigan, Sch Nat Resources & Environm, 440 Church St, Ann Arbor, MI 48109 USA.
EM Missy.stults@gmail.com; sscheleg@live.unc.edu
FU National Science Foundation
FX Partial financial support for this research was provided by the National
   Science Foundation's Graduate Research Fellowship Program.
CR [Anonymous], PREP CLIM CHANG GUID
   [Anonymous], 11901 NAT I STAND TE
   [Anonymous], PROVIA GUID ASS VULN
   [Anonymous], BEING PREP CLIM CHAN
   [Anonymous], 1 USC BUR
   [Anonymous], CLIMATE CHANGE IMPAC
   [Anonymous], COMM BAS AD US CRIT
   [Anonymous], LOCAL CLIMATE ACTION
   [Anonymous], 2014, ANN 2 GLOSS WORK GRO
   [Anonymous], 2012, MANAGING RISKS EXTRE
   [Anonymous], CAL AD PLANN GUID
   [Anonymous], PROM PRACT AD RES RE
   [Anonymous], CLIMATE ADAPTATION F
   [Anonymous], 2013, MITIG ADAPT STRAT GL, DOI DOI 10.1007/s11027-012-9423-1
   [Anonymous], 2012, NVivo qualitative data analysis software (Version 10)
   [Anonymous], 2014, GLOBAL ENVIRON CHANG, DOI DOI 10.1016/j.gloenvcha.2014.01.003
   [Anonymous], 2014, EVOL APPL, DOI DOI 10.1111/eva.12137
   [Anonymous], CLIMATE SMART COMMUN
   Baker I, 2012, LANDSCAPE URBAN PLAN, V107, P127, DOI 10.1016/j.landurbplan.2012.05.009
   Barnett J, 2010, GLOBAL ENVIRON CHANG, V20, P211, DOI 10.1016/j.gloenvcha.2009.11.004
   Bassett E, 2010, J AM PLANN ASSOC, V76, P435, DOI 10.1080/01944363.2010.509703
   Bedsworth LW, 2010, J AM PLANN ASSOC, V76, P477, DOI 10.1080/01944363.2010.502047
   Berke P, 2014, J AM PLANN ASSOC, V80, P310, DOI 10.1080/01944363.2014.976585
   Berke P, 2013, CITYSCAPE, V15, P181
   Berke P, 2012, NAT HAZARDS REV, V13, P139, DOI 10.1061/(ASCE)NH.1527-6996.0000063
   Berke P, 2011, SUSTAINABILITY-BASEL, V3, P1, DOI 10.3390/su3010001
   Berke P, 2009, J PLAN LIT, V23, P227, DOI 10.1177/0885412208327014
   Berrang-Ford L, 2011, GLOBAL ENVIRON CHANG, V21, P25, DOI 10.1016/j.gloenvcha.2010.09.012
   Boyer MA, 2017, LOCAL ENVIRON, V22, P67, DOI 10.1080/13549839.2016.1160372
   Brody SD, 2005, J AM PLANN ASSOC, V71, P159, DOI 10.1080/01944360508976690
   Burby RaymondJ., 2000, Natural Hazards Review, V1, P99
   Carmin JoAnn., 2012, Progress and Challenges in Urban Climate Adaptation Planning: Results of a Global Survey
   Cutter SL, 2008, GLOBAL ENVIRON CHANG, V18, P598, DOI 10.1016/j.gloenvcha.2008.07.013
   Eakin H, 2006, ANNU REV ENV RESOUR, V31, P365, DOI 10.1146/annurev.energy.30.050504.144352
   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
   Ekstrom JA, 2014, URBAN CLIM, V9, P54, DOI 10.1016/j.uclim.2014.06.002
   Engle NL, 2013, CLIMATIC CHANGE, V118, P291, DOI 10.1007/s10584-012-0657-4
   Environmental Protection Agency, 2014, BEING PREP CLIM CHAN
   Felgenhauer T, 2013, GLOBAL ENVIRON CHANG, V23, P1556, DOI 10.1016/j.gloenvcha.2013.09.018
   Fidelman PIJ, 2013, GLOBAL ENVIRON CHANG, V23, P800, DOI 10.1016/j.gloenvcha.2013.02.016
   Ford JD, 2013, ECOL SOC, V18, DOI 10.5751/ES-05732-180340
   Friend R, 2014, URBAN CLIM, V7, P6, DOI 10.1016/j.uclim.2013.08.001
   Fu XY, 2013, NAT HAZARDS, V69, P1607, DOI 10.1007/s11069-013-0766-z
   Fu XY, 2013, CITIES, V32, P60, DOI 10.1016/j.cities.2013.03.001
   Hansen Laura., 2013, The State of Adaptation in the United States: An Overview. A Report for the John D. and Catherine T. MacArthur Foundation
   Highfield WE, 2013, NAT HAZARDS REV, V14, P229, DOI 10.1061/(ASCE)NH.1527-6996.0000114
   Horney JenniferA., 2012, Challenges, V3, P183
   Hughes S, 2015, URBAN CLIM, V14, P17, DOI 10.1016/j.uclim.2015.06.003
   Jenerette GD, 2011, ECOL APPL, V21, P2637, DOI 10.1890/10-1493.1
   Krippendorff K., 2013, Content analysis, V3rd
   Larsen L, 2015, FRONT ECOL ENVIRON, V13, P486, DOI 10.1890/150103
   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
   Lyles W, 2014, J PLAN EDUC RES, V34, P433, DOI 10.1177/0739456X14549752
   Lyles W, 2014, LANDSCAPE URBAN PLAN, V122, P89, DOI 10.1016/j.landurbplan.2013.11.010
   Mimura N, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P869
   Moloney S, 2015, URBAN CLIM, V14, P30, DOI 10.1016/j.uclim.2015.06.009
   Moser SC, 2015, URBAN CLIM, V14, P111, DOI 10.1016/j.uclim.2015.06.006
   O'Neill MS, 2010, INT J PUBLIC HEALTH, V55, P105, DOI 10.1007/s00038-009-0071-5
   Petersen A.S., 2014, Michigan J. Sustain, V2, P9
   Pincetl S, 2015, LOCAL ENVIRON, V20, P850, DOI 10.1080/13549839.2015.1042778
   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
   Ray A.D., 2015, Michigan J. Sustain, V3, P24
   Shi LD, 2015, J AM PLANN ASSOC, V81, P191, DOI 10.1080/01944363.2015.1074526
   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
   Stevens MR, 2014, J PLAN EDUC RES, V34, P77, DOI 10.1177/0739456X13513614
   Stults Missy., 2015, LIVING CLIMATE CHANG, P285
   Tompkins EL, 2010, GLOBAL ENVIRON CHANG, V20, P627, DOI 10.1016/j.gloenvcha.2010.05.001
   Travis WR, 2010, CLIMATIC CHANGE, V98, P1, DOI 10.1007/s10584-009-9661-8
   Welsh LW, 2013, ECOL SOC, V18, DOI 10.5751/ES-05484-180207
   Woodruff Sierra C., 2016, Nature Climate Change, V6, P796, DOI 10.1038/nclimate3012
   World Bank, 2011, WORLD DEVELOPMENT REPORT 2011: CONFLICT, SECURITY AND DEVELOPMENT, P1, DOI 10.1596/978-0-8213-8439-8
NR 75
TC 51
Z9 55
U1 1
U2 8
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 DEC
PY 2017
VL 22
IS 8
BP 1249
EP 1279
DI 10.1007/s11027-016-9725-9
PG 31
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA FK1VV
UT WOS:000413272600007
DA 2025-01-10
ER

PT J
AU Zanon, BD
   Roeffen, B
   Czapiewska, KM
   de Graaf-Van Dinther, RE
   Mooij, PR
AF Zanon, B. Dal Bo
   Roeffen, B.
   Czapiewska, K. M.
   de Graaf-Van Dinther, R. E.
   Mooij, P. R.
TI Potential of floating production for delta and coastal cities
SO JOURNAL OF CLEANER PRODUCTION
LA English
DT Article
DE Land scarcity; Floating urbanization; Water-food-energy nexus; Coastal
   cities; Climate adaptation; Resilience
ID ENVIRONMENTAL IMPACTS; URBAN METABOLISM; MICROALGAE; CO2; CULTIVATION;
   MANAGEMENT; BIODIESEL; ECOLOGY
AB The disruption of nutrient cycles caused by human activities such as agriculture and burning fossil fuels is impacting ecosystem services on global and local scales. The increasing concentration of carbon dioxide in the atmosphere contributes to rising global temperatures and ocean acidification, whereas the accumulation of nutrients in water systems is leading to degradation of water quality and biodiversity. City populations play a major role in carbon dioxide and nutrient emissions as 'end consumers' of resources. The current challenge towards more resource-efficient cities is to transform urban metabolism from linear to cyclical. Discharged nutrients and carbon dioxide can be used as input for algae, which fixate carbon very efficiently into energetic storage compounds as starch or lipids. However, cities often lack the space to implement large-scale algae production. This article evaluates the potential of reusing nutrients and carbon dioxide to produce algae, food and biofuel on water nearby coastal and delta cities. First, nutrients and carbon dioxide discharge is estimated and two scenarios are developed. From the cities nutrient production, the potential algal yield is evaluated and translated into feed, food and oil yields. Two delta cities are chosen as case studies: Rotterdam and Metro Manila. The conclusion of this article is that Floating Production can help cities increasing their resilience in the field of food and energy. Floating Production can also contribute to a solution for global land shortage. The combination of food and energy production with floating urban development provides a climate-proof urban expansion in delta and coastal areas. (C) 2017 Elsevier Ltd. All rights reserved.
C1 [Zanon, B. Dal Bo; Roeffen, B.; Czapiewska, K. M.; de Graaf-Van Dinther, R. E.] DeltaSync, Molengraaffsingel 12, NL-2629 JD Delft, Netherlands.
   [Roeffen, B.; Czapiewska, K. M.; de Graaf-Van Dinther, R. E.] Blue21, Molengraaffsingel 12, NL-2629 JD Delft, Netherlands.
   [de Graaf-Van Dinther, R. E.] Rotterdam Univ Appl Sci, Heijplaatstr 23, Rotterdam, Netherlands.
   [Mooij, P. R.] Delft Univ Technol, Dept Biotechnol, Julianalaan 67, NL-2628 BC Delft, Netherlands.
C3 Delft University of Technology
RP Zanon, BD (corresponding author), DeltaSync, Molengraaffsingel 12, NL-2629 JD Delft, Netherlands.
EM barbara@deltasync.nl
FU Centre of Expertise Delta Technology; Topsector Water
FX We thank the Centre of Expertise Delta Technology and the Topsector
   Water for providing funds for the research. The authors are also
   grateful to the comments from two anonymous reviewers who took time to
   read and give their feedback on the paper.
CR Agudelo-Vera CM, 2012, RESOUR CONSERV RECY, V64, P3, DOI 10.1016/j.resconrec.2012.01.014
   [Anonymous], 2005, TIMBER FUEL FIBER EC
   [Anonymous], 2010, CURRENT STATUS POTEN
   [Anonymous], 2014, GREENH GAS EQ CALC
   [Anonymous], 2014, CO2 Emissions from Fuel Combustion
   [Anonymous], ALGAE BIOFUELS ENERG
   [Anonymous], 2012, World Development Indicators 2012
   [Anonymous], 2012, Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change
   [Anonymous], 2014, FAOSTAT
   Becker EW, 2007, BIOTECHNOL ADV, V25, P207, DOI 10.1016/j.biotechadv.2006.11.002
   Belay A, 1996, J APPL PHYCOL, V8, P303, DOI 10.1007/BF02178573
   Borowitzka M.A., 2013, ALGAE FOR BIOFUELS A
   Burson A, 2016, LIMNOL OCEANOGR, V61, P869, DOI 10.1002/lno.10257
   Carbon Capture Journal, 2013, CARBON CAPTURE J
   Chang K., 2009, Interdisciplinary Studies on Environmental Chemistry - Environmental Research in Asia, P261
   Chisti Y, 2007, BIOTECHNOL ADV, V25, P294, DOI 10.1016/j.biotechadv.2007.02.001
   Cuellar-Bermudez SP, 2015, J CLEAN PROD, V98, P53, DOI 10.1016/j.jclepro.2014.03.034
   de Lima RLP, 2015, INNOVATIVE DYNAMIC W
   Dismukes GC, 2008, CURR OPIN BIOTECH, V19, P235, DOI 10.1016/j.copbio.2008.05.007
   Douglas SE, 2003, ADV PHOTO RESPIRAT, V14, P1
   Ernst L, 2015, J CLEAN PROD, P1
   FAO, 2013, WORLD LIV 2013 CHANG
   FAO, 2014, 589 FAO
   Flesch A, 2013, ALGAE BIOFUELS ENERG, P233, DOI [10.1007/978-94-007-5479-9_14, DOI 10.1007/978-94-007-5479-9_14]
   Gerber P.J., 2013, Tackling Climate Change through Livestock-A Global Assessment of Emissions and Mitigation Opportunities
   Global CCS Institute, 2012, CO2 CAPT TECHN
   Gouveia L., 2008, FOOD CHEM RES DEV, P75
   Harris L, 2013, BIORESOURCE TECHNOL, V144, P420, DOI 10.1016/j.biortech.2013.06.125
   Jonsson H., 2004, 20042 ECOSANRES PROG, P35
   Kalmykova Y, 2012, J IND ECOL, V16, P928, DOI 10.1111/j.1530-9290.2012.00541.x
   KELLEY AC, 1984, POPUL DEV REV, V10, P419, DOI 10.2307/1973513
   Kennedy C, 2011, ENVIRON POLLUT, V159, P1965, DOI 10.1016/j.envpol.2010.10.022
   Keyzer M, 2010, ECONOMIST-NETHERLAND, V158, P411, DOI 10.1007/s10645-010-9150-5
   KHALLAF EA, 1987, HYDROBIOLOGIA, V146, P57, DOI 10.1007/BF00007577
   Konig B., 2016, ECOCYCLES, V2, P2632
   Leduc WRWA, 2013, J CLEAN PROD, V39, P180, DOI 10.1016/j.jclepro.2012.09.014
   Li YC, 2011, BIORESOURCE TECHNOL, V102, P10861, DOI 10.1016/j.biortech.2011.09.064
   Lowe E.A., 1995, J CLEAN PROD, V3, P47, DOI [DOI 10.1016/0959-6526(95)00045-G, 10.1016/0959-6526(95)00045-G]
   Manninen K., 2015, J CLEAN PROD
   Marcotullio PJ, 2007, SUSTAIN SCI, V2, P27, DOI 10.1007/s11625-006-0019-0
   Mooij PR, 2015, CURR OPIN BIOTECH, V33, P46, DOI 10.1016/j.copbio.2014.11.001
   Mooij PR, 2013, ENERG ENVIRON SCI, V6, P3404, DOI 10.1039/c3ee42912a
   Nayak M, 2013, J MICROBIOL BIOTECHN, V23, P1260, DOI 10.4014/jmb.1302.02044
   Naylor RL, 2000, NATURE, V405, P1017, DOI 10.1038/35016500
   Norsker NH, 2011, BIOTECHNOL ADV, V29, P24, DOI 10.1016/j.biotechadv.2010.08.005
   Patrício J, 2015, J CLEAN PROD, V106, P389, DOI 10.1016/j.jclepro.2014.08.069
   Pincetl S, 2012, LANDSCAPE URBAN PLAN, V107, P193, DOI 10.1016/j.landurbplan.2012.06.006
   Plomp A.J., 2013, VERKENNING ROTTERDAM
   Rakocy J. E., 2012, Aquaculture Production Systems, V1, P343, DOI [10.1002/9781118250105.ch14, DOI 10.1002/9781118250105.CH14]
   Richardson J. W., 2010, AgBioForum, V13, P119
   Sharif Hossain A. B. M., 2008, American Journal of Biochemistry and Biotechnology, V4, P250
   Slade R, 2013, BIOMASS BIOENERG, V53, P29, DOI 10.1016/j.biombioe.2012.12.019
   Spangenberg JH, 2010, ECOL COMPLEX, V7, P327, DOI 10.1016/j.ecocom.2010.04.007
   Stephens E, 2010, NAT BIOTECHNOL, V28, P126, DOI 10.1038/nbt0210-126
   Strande L, 2014, FAECAL SLUDGE MANAGEMENT: SYSTEMS APPROACH FOR IMPLEMENTATION AND OPERATION, P1
   Sudhakar K., 2012, Iranica Journal of Energy and Environment, V3, P232, DOI DOI 10.5829/IDOSI.IJEE.2012.03.03.3273
   Svirejeva-Hopkins A., 2011, EUROPEAN NITROGEN AS, V12, P249
   Tartiel M.B., 2008, 8 INT S TIL AQ, P801
   The Rockefeller Foundation, 2015, RESILIENCE
   Usher PK, 2014, BIOFUELS-UK, V5, P331, DOI 10.1080/17597269.2014.913925
   Walsh Brian J, 2015, Carbon Balance Manag, V10, P26
   Wang B, 2008, APPL MICROBIOL BIOT, V79, P707, DOI 10.1007/s00253-008-1518-y
   Wang LA, 2010, APPL BIOCHEM BIOTECH, V162, P1174, DOI 10.1007/s12010-009-8866-7
   Weyer KM, 2010, BIOENERG RES, V3, P204, DOI 10.1007/s12155-009-9046-x
NR 64
TC 18
Z9 19
U1 1
U2 51
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 10
PY 2017
VL 151
BP 10
EP 20
DI 10.1016/j.jclepro.2017.03.048
PG 11
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 ES5ZA
UT WOS:000399624000002
DA 2025-01-10
ER

PT J
AU Cao, Q
   Yu, DY
   Georgescu, M
   Han, Z
   Wu, JG
AF Cao, Qian
   Yu, Deyong
   Georgescu, Matei
   Han, Zhe
   Wu, Jianguo
TI Impacts of land use and land cover change on regional climate: a case
   study in the agro-pastoral transitional zone of China
SO ENVIRONMENTAL RESEARCH LETTERS
LA English
DT Article
DE land use and land cover change; climate change; agro-pastoral
   transitional zone; land surface biophysical parameter; landscape
   pattern; mitigation and adaptation strategy
ID PARAMETERIZATION; SENSITIVITY; ALBEDO; ENERGY; MODEL
AB Assessing the impacts of land use and land cover change (LUCC) on regional climate is essential for understanding land-atmosphere interactions and for designing climate adaptation andmitigation strategies. Using the weather research and forecasting (WRF) model, we examined how different land use and land cover patterns affect regional climate in the agro-pastoral transitional zone of North China, whose environmental and socioeconomic conditions are sensitive to climate change. We parameterized WRF using land use and land cover maps corresponding to 2001 and 2010 conditions, which differ in the representation of four land surface biophysical parameters: vegetation fraction, leaf area index (LAI), albedo, and emissivity. From 2001 to 2010, vegetation fraction and LAI increased in summer, emissivity increased and albedo decreased in winter. Our WRF simulations show that differences in land use and land cover patterns led to widespread reduction in summer temperature with local cooling on the order of 1 degrees C, and extensive increase in winter temperature with local warming exceeding 0.8 degrees C. By contrast, simulations using the default landscape representation, provided by WRF itself, show only minor and random changes in temperature. Model evaluation further reveals that our simulations with appropriate land surface properties improve the performance of the WRF model. Our findings demonstrate that LUCC in Northern China has altered the regional climate over the past decade. The magnitude and spatial patterns of temperature changes quantified by our simulations provide useful information for understanding the impacts of LUCC on climate and for developing mitigation and adaptation strategies in arid and semiarid regions.
C1 [Cao, Qian; Yu, Deyong; Wu, Jianguo] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, CHESS, Beijing 100875, Peoples R China.
   [Georgescu, Matei] Arizona State Univ, Sch Geog Sci & Urban Planning, Tempe, AZ 85287 USA.
   [Han, Zhe] Chinese Acad Sci, Key Lab Reg Climate Environm Temperate East Asia, Beijing 100875, Peoples R China.
   [Wu, Jianguo] Arizona State Univ, Sch Life Sci, Tempe, AZ 85287 USA.
   [Wu, Jianguo] Arizona State Univ, Sch Sustainabil, Tempe, AZ 85287 USA.
C3 Beijing Normal University; Arizona State University; Arizona State
   University-Tempe; Chinese Academy of Sciences; Arizona State University;
   Arizona State University-Tempe; Arizona State University; Arizona State
   University-Tempe
RP Yu, DY (corresponding author), Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, CHESS, Beijing 100875, Peoples R China.
EM dyyucas@163.com
RI Georgescu, Matei/G-5442-2011; Wu, Jianguo/G-6267-2010
OI Cao, Qian/0000-0002-0580-7407
FU National Basic Research Program of China (973 Program) [2014CB954301];
   Fund for Creative Research Groups of National Natural Science Foundation
   of China [41321001]; NSF [EAR-1204774]; Division Of Earth Sciences;
   Directorate For Geosciences [1204774] Funding Source: National Science
   Foundation
FX This work was supported by the National Basic Research Program of China
   (973 Program) under Grant 2014CB954301 and the Fund for Creative
   Research Groups of National Natural Science Foundation of China under
   Grant 41321001. MG was supported by NSF under Grant EAR-1204774.
CR AVISSAR R, 1989, MON WEATHER REV, V117, P2113, DOI 10.1175/1520-0493(1989)117<2113:APOHLS>2.0.CO;2
   Brovkin V, 2004, GLOBAL CHANGE BIOL, V10, P1253, DOI 10.1111/j.1365-2486.2004.00812.x
   CHARNEY J, 1977, J ATMOS SCI, V34, P1366, DOI 10.1175/1520-0469(1977)034<1366:ACSOTE>2.0.CO;2
   Chase TN, 1996, J GEOPHYS RES-ATMOS, V101, P7393, DOI 10.1029/95JD02417
   de Noblet-Ducoudré N, 2012, J CLIMATE, V25, P3261, DOI 10.1175/JCLI-D-11-00338.1
   Feddema JJ, 2005, SCIENCE, V310, P1674, DOI 10.1126/science.1118160
   Foley JA, 2005, SCIENCE, V309, P570, DOI 10.1126/science.1111772
   Ge QS, 2014, INT J CLIMATOL, V34, P187, DOI 10.1002/joc.3677
   Georgescu M, 2009, GEOPHYS RES LETT, V36, DOI 10.1029/2009GL040477
   Georgescu M, 2014, P NATL ACAD SCI USA, V111, P2909, DOI 10.1073/pnas.1322280111
   Georgescu M, 2011, P NATL ACAD SCI USA, V108, P4307, DOI 10.1073/pnas.1008779108
   Grossman-Clarke S, 2010, J APPL METEOROL CLIM, V49, P1649, DOI 10.1175/2010JAMC2362.1
   Gutman G, 1998, INT J REMOTE SENS, V19, P1533, DOI 10.1080/014311698215333
   Kalnay E, 2003, NATURE, V423, P528, DOI 10.1038/nature01675
   Kalnay E., 2003, Atmospheric modeling, data assimilation, and predictability
   Kanamitsu M, 2002, B AM METEOROL SOC, V83, P1631, DOI [10.1175/BAMS-83-11-1631(2002)083<1631:NAR>2.3.CO;2, 10.1175/Bams-83-11-1631]
   Kumar A, 2014, J APPL METEOROL CLIM, V53, P1362, DOI 10.1175/JAMC-D-13-0247.1
   Li D, 2013, J GEOPHYS RES-ATMOS, V118, P11918, DOI 10.1002/2013JD020657
   Li Z, 2009, ATMOS OCEAN SCI LETT, V2, P237, DOI 10.1080/16742834.2009.11446802
   Liang XZ, 2005, J GEOPHYS RES-ATMOS, V110, DOI 10.1029/2004JD005579
   Long C.N., 2004, The Shortwave (SW) Clear-Sky Detection and Fitting Algorithm : Algorithm Operational Details and Explanations
   Niyogi D, 2010, EVOLUTION PROCESS, P67
   Opdam P, 2009, LANDSCAPE ECOL, V24, P715, DOI 10.1007/s10980-009-9377-1
   PIELKE RA, 1990, LANDSCAPE ECOL, V4, P133, DOI 10.1007/BF00132857
   RAUPACH MR, 1991, VEGETATIO, V91, P105, DOI 10.1007/BF00036051
   Sellers PJ, 1996, J CLIMATE, V9, P706, DOI 10.1175/1520-0442(1996)009<0706:ARLSPF>2.0.CO;2
   Sellers PJ, 1997, SCIENCE, V275, P502, DOI 10.1126/science.275.5299.502
   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]
   Song J, 1999, INT J BIOMETEOROL, V42, P153, DOI 10.1007/s004840050099
   Vitousek PM, 1997, SCIENCE, V277, P494, DOI 10.1126/science.277.5325.494
   Weaver CP, 2001, B AM METEOROL SOC, V82, P269, DOI 10.1175/1520-0477(2001)082<0269:ADCBHM>2.3.CO;2
   Wu F, 2013, ADV METEOROL, V2013, DOI 10.1155/2013/520803
   Wu JG, 2015, LANDSCAPE ECOL, V30, P1579, DOI 10.1007/s10980-015-0209-1
   Wu JG, 2013, LANDSCAPE ECOL, V28, P999, DOI 10.1007/s10980-013-9894-9
   Zhou L, 2003, J GEOPHYS RES-ATMOS, V108, DOI 10.1029/2003JD004083
   Zhou LM, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/6/064012
NR 36
TC 157
Z9 167
U1 13
U2 215
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 2015
VL 10
IS 12
AR 124025
DI 10.1088/1748-9326/10/12/124025
PG 12
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA CZ7NO
UT WOS:000367286300032
OA gold
DA 2025-01-10
ER

PT J
AU Lim-Camacho, L
   Hobday, AJ
   Bustamante, RH
   Farmery, A
   Fleming, A
   Frusher, S
   Green, BS
   Norman-López, A
   Pecl, GT
   Plaganyi, ÉE
   Schrobback, P
   Thebaud, O
   Thomas, L
   van Putten, I
AF Lim-Camacho, Lilly
   Hobday, Alistair J.
   Bustamante, Rodrigo H.
   Farmery, Anna
   Fleming, Aysha
   Frusher, Stewart
   Green, Bridget S.
   Norman-Lopez, Ana
   Pecl, Gretta T.
   Plaganyi, Eva E.
   Schrobback, Peggy
   Thebaud, Olivier
   Thomas, Linda
   van Putten, Ingrid
TI Facing the wave of change: stakeholder perspectives on climate
   adaptation for Australian seafood supply chains
SO REGIONAL ENVIRONMENTAL CHANGE
LA English
DT Article
DE Adaptation planning; Climate scenarios; Perception analysis;
   Sustainability
ID FISHERIES MANAGEMENT; MARINE; IMPACTS; COMMUNICATION; VULNERABILITY
AB Climate change is one of the most important issues confronting the sustainable supply of seafood, with projections suggesting major effects on wild and farmed fisheries worldwide. While climate change has been a consideration for Australian fisheries and aquaculture management, emphasis in both research and adaptation effort has been at the production end of supply chains-impacts further along the chain have been overlooked to date. A holistic biophysical and socio-economic system view of seafood industries, as represented by end-to-end supply chains, may lead to an additional set of options in the face of climate change, thus maximizing opportunities for improved fishery profitability, while also reducing the potential for maladaptation. In this paper, we explore Australian seafood industry stakeholder perspectives on potential options for adaptation along seafood supply chains based on future potential scenarios. Stakeholders, representing wild capture and aquaculture industries, provided a range of actions targeting different stages of the supply chain. Overall, proposed strategies were predominantly related to the production end of the supply chain, suggesting that greater attention in developing adaptation options is needed at post-production stages. However, there are chain-wide adaptation strategies that can present win-win scenarios, where commercial objectives beyond adaptation can also be addressed alongside direct or indirect impacts of climate. Likewise, certain adaptation strategies in place at one stage of the chain may have varying implications on other stages of the chain. These findings represent an important step in understanding the role of supply chains in effective adaptation of fisheries and aquaculture industries to climate change.
C1 [Lim-Camacho, Lilly] Climate Adaptat Flagship, Pullenvale, Qld 4069, Australia.
   [Hobday, Alistair J.; Fleming, Aysha; van Putten, Ingrid] CSIRO Marine & Atmospher Res, Climate Adaptat Flagship, Castray Esplanade, Hobart, Tas 7001, Australia.
   [Bustamante, Rodrigo H.; Norman-Lopez, Ana; Plaganyi, Eva E.; Thebaud, Olivier; Thomas, Linda] CSIRO Marine & Atmospher Res, Climate Adaptat Flagship, Brisbane, Qld 4001, Australia.
   [Farmery, Anna; Frusher, Stewart; Green, Bridget S.; Pecl, Gretta T.] Univ Tasmania, Inst Marine & Antarctic Studies, Hobart, Tas 7001, Australia.
   [Schrobback, Peggy] Queensland Univ Technol, Brisbane, Qld 4001, Australia.
C3 Commonwealth Scientific & Industrial Research Organisation (CSIRO);
   Commonwealth Scientific & Industrial Research Organisation (CSIRO);
   Commonwealth Scientific & Industrial Research Organisation (CSIRO);
   University of Tasmania; Queensland University of Technology (QUT)
RP Lim-Camacho, L (corresponding author), Climate Adaptat Flagship, 1 Technol Court, Pullenvale, Qld 4069, Australia.
EM lilly.lim-camacho@csiro.au
RI Thomas, Linda/Q-2521-2018; Hobday, Alistair/A-1460-2012; van putten,
   ingrid/AAV-1301-2021; Green, Bridget/G-3368-2014; Thebaud,
   Olivier/D-9792-2011; Schrobback, Peggy/X-4697-2019; Fleming,
   Aysha/E-8753-2011; Farmery, Anna/H-9696-2014; Norman, Ana/K-4501-2012;
   Pecl, Gretta/D-7267-2011; Lim-Camacho, Lilly/A-7502-2015; Bustamante,
   Rodrigo/B-4307-2009; Frusher, Stewart/G-5117-2014; Plaganyi,
   Eva/C-5130-2011
OI Thomas, Linda/0000-0001-8989-8109; Fleming, Aysha/0000-0001-9895-1928;
   Farmery, Anna/0000-0002-8938-0040; Norman, Ana/0000-0002-3193-0951;
   Pecl, Gretta/0000-0003-0192-4339; Thebaud, Olivier/0000-0001-8665-3827;
   Lim-Camacho, Lilly/0000-0002-4897-1186; Bustamante,
   Rodrigo/0000-0002-9787-338X; Frusher, Stewart/0000-0003-2493-3676;
   Plaganyi, Eva/0000-0002-4740-4200
FU FRDC-DCCEE on behalf of the Australian Government [FRDC 2012/233]
FX This research was part of the 'Growth opportunities and critical
   elements in the value chain for wild fisheries and aquaculture in a
   changing climate (FRDC 2012/233)' which was supported by funding from
   the FRDC-DCCEE on behalf of the Australian Government. We are grateful
   to all the stakeholders who provided information on supply chains.
CR ABARES, 2011, AUSTR FISH STAT, V2010
   Allison EH, 2009, FISH FISH, V10, P173, DOI 10.1111/j.1467-2979.2008.00310.x
   Andersen PH, 2001, J BUS IND MARK, V16, P167, DOI 10.1108/08858620110389786
   [Anonymous], 2000, STATE WORLD FISHERIE
   [Anonymous], IMPLICATIONS CLIMATE
   [Anonymous], 2012, 1301 0 YB AUSTR 2012
   [Anonymous], 1999, Introduction to Supply Chain Management
   [Anonymous], 2010, CONTRIBUTION FISH IN
   Asche F, 2007, APPL ECON, V39, P2535, DOI 10.1080/00036840500486524
   Barnett J, 2010, GLOBAL ENVIRON CHANG, V20, P211, DOI 10.1016/j.gloenvcha.2009.11.004
   Bell JD, 2013, NAT CLIM CHANGE, V3, P591, DOI 10.1038/NCLIMATE1838
   Bohensky E, 2011, GLOBAL ENVIRON CHANG, V21, P876, DOI 10.1016/j.gloenvcha.2011.03.009
   Bourlakis M. A., 2008, FOOD SUPPLY CHAIN MA
   Brander K, 2010, J MARINE SYST, V79, P389, DOI 10.1016/j.jmarsys.2008.12.015
   Brown CJ, 2010, GLOBAL CHANGE BIOL, V16, P1194, DOI 10.1111/j.1365-2486.2009.02046.x
   Cheung WWL, 2013, NATURE, V497, P365, DOI 10.1038/nature12156
   Christopher M., 1992, Logistics and Supply Chain Management: Strategies for reducing costs and improving services
   Christopher M., 2001, International Journal of Physical Distribution Logistics Management, V31, P235, DOI [DOI 10.1108/09600030110394914, 10.1108/09600030110394910]
   Cochrane K., 2009, FAO FISH AQUAC TECH, V530, P212
   DAFF, 2010, NAT CLIM CHANG FISH
   Farmery A, 2014, J CLEAN PROD, V64, P368, DOI 10.1016/j.jclepro.2013.10.016
   Fleming A, 2014, CLIM RISK MANAG, V1, P39, DOI 10.1016/j.crm.2013.12.003
   Frusher SD, 2014, REV FISH BIOL FISHER, V24, P593, DOI 10.1007/s11160-013-9325-7
   Fulton EA, 2011, ICES J MAR SCI, V68, P1329, DOI 10.1093/icesjms/fsr032
   Fulton EA, 2009, 18 WORLD IMACS MODSI
   Garcia SM, 2010, PHILOS T R SOC B, V365, P2869, DOI 10.1098/rstb.2010.0171
   Gregory R, 2006, ECOL APPL, V16, P2411, DOI 10.1890/1051-0761(2006)016[2411:DAMCFA]2.0.CO;2
   Grönroos C, 2004, J BUS IND MARK, V19, P99, DOI 10.1108/08858620410523981
   Henson S, 2007, GLOBAL SUPPLY CHAINS, STANDARDS AND THE POOR: HOW THE GLOBALIZATION OF FOOD SYSTEMS AND STANDARDS AFFECTS RURAL DEVELOPMENT AND POVERTY, P26, DOI 10.1079/9781845931858.0026
   Johnson J.E., 2007, CLIMATE CHANGE GREAT
   Johnson JE, 2010, REV FISH SCI, V18, P106, DOI 10.1080/10641260903434557
   Kaiser MJ, 2006, CONSERV BIOL, V20, P392, DOI 10.1111/j.1523-1739.2006.00319.x
   Koehn JD, 2011, MAR FRESHWATER RES, V62, P1148, DOI 10.1071/MF11139
   LEITH PB, 2010, CLIMATE CHANGE ADAPT
   Leung TLF, 2013, J APPL ECOL, V50, P215, DOI 10.1111/1365-2644.12017
   Linnane A, 2010, FISH RES, V105, P163, DOI 10.1016/j.fishres.2010.04.001
   Lough JM, 2011, MAR FRESHWATER RES, V62, P984, DOI 10.1071/MF10272
   Marshall N, 2013, ECOSYSTEMS, V16, P797, DOI 10.1007/s10021-013-9651-6
   Merino G, 2012, GLOBAL ENVIRON CHANG, V22, P795, DOI 10.1016/j.gloenvcha.2012.03.003
   Norman-López A, 2014, AUST J AGR RESOUR EC, V58, P43, DOI 10.1111/1467-8489.12020
   Norman-López A, 2013, FISH RES, V148, P18, DOI 10.1016/j.fishres.2012.02.026
   Norman-López A, 2011, CLIM CHANG ECON, V2, P209, DOI 10.1142/S2010007811000279
   Nursey-Bray M, 2012, MAR POLICY, V36, P753, DOI 10.1016/j.marpol.2011.10.015
   Palutikof JP, 2010, GLOBAL ENVIRON CHANG, V20, P218, DOI 10.1016/j.gloenvcha.2010.03.002
   Parker RWR, 2012, ENVIRON SCI TECHNOL, V46, P4958, DOI 10.1021/es2040703
   Pecl G., 2009, Rep. Dep. Clim. Change Dep. Clim. Change
   Pecl GT, 2011, DRAFT CLIMATE CHAN 1
   Plagányi ÉE, 2011, ICES J MAR SCI, V68, P1305, DOI 10.1093/icesjms/fsr049
   Plagányi ÉE, 2013, P NATL ACAD SCI USA, V110, P3639, DOI 10.1073/pnas.1217822110
   QSR International, 2013, NVIV 10 10 0 303 0 3
   Saldana J, 2016, The Coding Manual for Qualitative Researchers
   Sands A, 2011, 111 ABARES
   Shaw A, 2009, GLOBAL ENVIRON CHANG, V19, P447, DOI 10.1016/j.gloenvcha.2009.04.002
   Sheppard SRJ, 2011, FUTURES, V43, P400, DOI 10.1016/j.futures.2011.01.009
   Smith ADM, 2007, ICES J MAR SCI, V64, P633, DOI 10.1093/icesjms/fsm041
   Smith ADM, 2008, FISH RES, V94, P373, DOI 10.1016/j.fishres.2008.06.006
   Smith MD, 2010, SCIENCE, V327, P784, DOI 10.1126/science.1185345
   Soosay C, 2012, SUPPLY CHAIN MANAG, V17, P68, DOI 10.1108/13598541211212212
   Tompkins EL, 2010, GLOBAL ENVIRON CHANG, V20, P627, DOI 10.1016/j.gloenvcha.2010.05.001
   United Nations Environment Programme (UNEP), 2009, ROL SUPPL CHAINS ADD, V80
   United Nations Global Compact (UNGC), 2012, BUS CLIM CHANG AD RE
   Van derVorst Jack., 2002, INT J PHYS DISTRIBUT, V32, P409, DOI DOI 10.1108/09600030210437951
   Vervoort JM, 2010, FUTURES, V42, P604, DOI 10.1016/j.futures.2010.04.031
   Watson RA, 2013, MAR POLICY, V42, P1, DOI 10.1016/j.marpol.2013.01.022
   Ziegler F, 2011, J IND ECOL, V15, P527, DOI 10.1111/j.1530-9290.2011.00344.x
NR 65
TC 33
Z9 37
U1 1
U2 58
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 APR
PY 2015
VL 15
IS 4
BP 595
EP 606
DI 10.1007/s10113-014-0670-4
PG 12
WC Environmental Sciences; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA CD8VK
UT WOS:000351374300003
DA 2025-01-10
ER

PT J
AU Prober, SM
   Stol, J
   Piper, M
   Gupta, VVSR
   Cunningham, S
AF Prober, Suzanne M.
   Stol, Jacqui
   Piper, Melissa
   Gupta, V. V. S. R.
   Cunningham, Saul A.
TI Towards climate-resilient restoration in mesic eucalypt woodlands:
   characterizing topsoil biophysical condition in different degradation
   states
SO PLANT AND SOIL
LA English
DT Article
DE Agricultural landscapes; Climate adaptation; Climate change; Plant-soil
   interactions; Soil carbon; Soil health
ID SOUTH-EASTERN AUSTRALIA; LAND-USE; PHYSIOLOGICAL PROFILES; MICROBIAL
   COMMUNITIES; WATER INFILTRATION; ECOSYSTEM FUNCTION; GRASSY WOODLANDS;
   SOIL COMPACTION; BULK-DENSITY; VEGETATION
AB Investments in restoring native vegetation must increasingly allow for likely impacts of climate change, requiring re-evaluation of limits to ecological recovery and persistence. Nutrient enrichment and weed invasion are significant limits to restoration in mesic ecosystems, but in a drying climate, limits could shift towards more fundamental ecosystem functions. We used a state and transition framework to identify landuse-related changes in topsoil biophysical characteristics likely to influence climate resilience in mesic temperate eucalypt woodlands.
   We compared topsoil condition in little-modified 'reference' states of the native ground-layer (dominated by tall tussock grasses) with four degraded ground-layer states identified in our state and transition framework. We hypothesized that 'nutrient-depleted' states (dominated by short tussock grasses) and 'nutrient-enriched' states (dominated by exotic annuals) would exhibit characteristics reflecting increased and decreased ecosystem vulnerability to a drying climate respectively.
   Our hypothesis that nutrient-depleted states are more vulnerable to a drying climate was supported by their significantly slower soil-water infiltration rates and significantly lower levels of topsoil carbon, clay, micro-invertebrates, microbial activity and modeled water holding capacity than reference states. However, degradation was less pronounced beneath trees, and our prediction regarding enriched states was supported only for carbon.
   Topsoil biophysical characteristics associated with different ground-layer states are predictable using a state and transition framework. Climate resilience of nutrient-depleted states appears compromised by topsoil biophysical degradation, indicating increasing need for attention in mesic ecosystems predicted to become drier under climate change.
C1 [Prober, Suzanne M.] CSIRO Ecosyst Sci & Sustainable Agr Flagship, Floreat, WA 6913, Australia.
   [Stol, Jacqui; Piper, Melissa; Cunningham, Saul A.] CSIRO Ecosyst Sci & Sustainable Agr Flagship, Canberra, ACT 2601, Australia.
   [Gupta, V. V. S. R.] CSIRO Ecosyst Sci & Sustainable Agr Flagship, Glen Osmond, SA 5064, Australia.
C3 Commonwealth Scientific & Industrial Research Organisation (CSIRO);
   Commonwealth Scientific & Industrial Research Organisation (CSIRO);
   Commonwealth Scientific & Industrial Research Organisation (CSIRO)
RP Prober, SM (corresponding author), CSIRO Ecosyst Sci & Sustainable Agr Flagship, Private Bag 5, Floreat, WA 6913, Australia.
EM Suzanne.Prober@csiro.au
RI stol, jacqui/I-8118-2016; Vadakattu, Gupta/C-1722-2009; Cunningham,
   Saul/B-9947-2009; Prober, Suzanne/G-6465-2010
OI Vadakattu, Gupta/0000-0001-9774-6471; Cunningham,
   Saul/0000-0003-0703-6893; Prober, Suzanne/0000-0002-6518-239X
FU Australian government through Caring for our Country
FX This study was supported by the Australian government through Caring for
   our Country. We thank E. Lindsay for helping conceive and obtain funds
   for the project, S. Kroker for laboratory MicroResp analysis, Steve
   Marvanek for assistance with soil classifications, J. Speijers for
   statistical advice, and the many land managers who allowed us to sample
   their woodlands.
CR [Anonymous], 2008, Encyclopedia of Soil Science, DOI DOI 10.1007/978-1-4020-3995-9_548
   [Anonymous], NSW AGR FISHERIES TE
   [Anonymous], 2002, AUSTR SOIL CLASSIFIC
   [Anonymous], 2005, SOIL EROSION CONSERV, DOI DOI 10.1111/J.1365-2389.2005.0756F.X
   Arnold S, 2012, AGR ECOSYST ENVIRON, V163, P61, DOI 10.1016/j.agee.2012.05.020
   Asbjornsen H, 2011, J PLANT ECOL, V4, P3, DOI 10.1093/jpe/rtr005
   Baldock JA., 1999, SOIL ANAL INTERPRETA, P159
   Barton PS, 2009, BIOL CONSERV, V142, P1701, DOI 10.1016/j.biocon.2009.03.005
   BELSKY AJ, 1993, J APPL ECOL, V30, P143, DOI 10.2307/2404278
   Bilotta GS, 2007, ADV AGRON, V94, P237, DOI 10.1016/S0065-2113(06)94006-1
   Briggs SV, 2008, AUST J BOT, V56, P590, DOI 10.1071/BT08046
   Campbell CD, 2003, APPL ENVIRON MICROB, V69, P3593, DOI 10.1128/AEM.69.6.3593-3599.2003
   Cass A., 1999, SOIL ANAL INTERPRETA, P95
   Chan KY, 2001, SOIL USE MANAGE, V17, P217, DOI 10.1079/SUM200180
   Chen IC, 2011, SCIENCE, V333, P1024, DOI 10.1126/science.1206432
   Colloff MJ, 2010, RESTOR ECOL, V18, P65, DOI 10.1111/j.1526-100X.2010.00667.x
   Drewry JJ, 2008, AUST J SOIL RES, V46, P237, DOI 10.1071/SR07125
   Eldridge DJ, 2005, AUSTRAL ECOL, V30, P336, DOI 10.1111/j.1442-9993.2005.01478.x
   Evans TA, 2011, NAT COMMUN, V2, DOI 10.1038/ncomms1257
   Garland JL, 1997, FEMS MICROBIOL ECOL, V24, P289, DOI 10.1111/j.1574-6941.1997.tb00446.x
   Geeves G, 1995, PHYS CHEM MORPHOLOGI
   Greenwood KL, 2001, AUST J EXP AGR, V41, P1231, DOI 10.1071/EA00102
   Gupta V.V., 2011, RAINFED FARMING SYST, P149
   Harris JA, 2006, RESTOR ECOL, V14, P170, DOI 10.1111/j.1526-100X.2006.00136.x
   Heneghan L, 2008, RESTOR ECOL, V16, P608, DOI 10.1111/j.1526-100X.2008.00477.x
   Hobbs RichardJ., 2009, NEW MODELS ECOSYSTEM
   INDORANTE SJ, 1990, SOIL SCI SOC AM J, V54, P560, DOI 10.2136/sssaj1990.03615995005400020047x
   Jackson J, 2001, AUST J AGR RES, V52, P377, DOI 10.1071/AR00012
   Janik LJ, 2007, AUST J SOIL RES, V45, P73, DOI 10.1071/SR06083
   Knox O. G. G., 2009, Aspects of Applied Biology, P129
   Li CH, 2002, CAN J SOIL SCI, V82, P147, DOI 10.4141/S01-026
   Lindberg N, 2002, J APPL ECOL, V39, P924, DOI 10.1046/j.1365-2664.2002.00769.x
   Lindo Z, 2003, CAN J FOREST RES, V33, P1610, DOI [10.1139/x03-080, 10.1139/X03-080]
   Lindsay EA, 2012, BIOL INVASIONS, V14, P203, DOI 10.1007/s10530-011-9997-7
   Manzoni S, 2012, ECOLOGY, V93, P930, DOI 10.1890/11-0026.1
   McCune B., 2011, MULTIVARIATE ANAL EC
   McIntyre S, 2008, AGR ECOSYST ENVIRON, V128, P251, DOI 10.1016/j.agee.2008.06.015
   McIntyre S, 2007, AGR ECOSYST ENVIRON, V119, P11, DOI 10.1016/j.agee.2006.06.013
   MOORE C. W. E., 1957, AUSTRALIAN JOUR BOT, V5, P44, DOI 10.1071/BT9570044
   MOORE C. W. E., 1953, AUSTRALIAN JOUR BOT, V1, P548, DOI 10.1071/BT9530548
   MOORE RM, 1993, NATURAL GRASSLANDS E, P315
   Pankhurst CE, 1995, AUST J EXP AGR, V35, P1015, DOI 10.1071/EA9951015
   Parmesan C, 2006, ANNU REV ECOL EVOL S, V37, P637, DOI 10.1146/annurev.ecolsys.37.091305.110100
   Poiani KA, 2011, BIODIVERS CONSERV, V20, P185, DOI 10.1007/s10531-010-9954-2
   Pollacco JAP, 2008, CAN J SOIL SCI, V88, P761, DOI 10.4141/CJSS07120
   Prober SM, 2002, AUST J BOT, V50, P699, DOI 10.1071/BT02052
   Prober SM, 2008, INT J WILDLAND FIRE, V17, P586, DOI 10.1071/WF07077
   Prober SM, 2012, BIODIVERS CONSERV, V21, P1627, DOI 10.1007/s10531-012-0268-4
   Prober SM, 2012, CLIMATIC CHANGE, V110, P227, DOI 10.1007/s10584-011-0092-y
   Prober SM, 2011, AUST J BOT, V59, P369, DOI 10.1071/BT11026
   Prober SM, 2009, BIOL INVASIONS, V11, P171, DOI 10.1007/s10530-008-9222-5
   Scholes RJ, 1997, ANNU REV ECOL SYST, V28, P517, DOI 10.1146/annurev.ecolsys.28.1.517
   Skinner AK, 2009, AUSTRAL ECOL, V34, P698, DOI 10.1111/j.1442-9993.2009.01977.x
   Skjemstad JO, 1998, AUST J EXP AGR, V38, P667, DOI 10.1071/EA97143
   Smallbone LT, 2007, AUST J BOT, V55, P818, DOI 10.1071/BT07106
   Steel RG., 1981, PRINCIPLES PROCEDURE
   Suding KN, 2011, ANNU REV ECOL EVOL S, V42, P465, DOI 10.1146/annurev-ecolsys-102710-145115
   Teague WR, 2011, AGR ECOSYST ENVIRON, V141, P310, DOI 10.1016/j.agee.2011.03.009
   Tongway DJ., 2011, Restoring disturbed landscapes: putting principles into practice
   Toy T.J., 2002, Soil Erosion: Processes, Prediction, Measurement, and Control
   Tschapek M, 1984, Z PFLANZ BODENKUNDE, V147, P7
   Vallejo VR, 2012, NEW FOREST, V43, P561, DOI 10.1007/s11056-012-9325-9
   Whalley R. D. B., 1978, Australian Rangeland Journal, V1, P174
   Whisenant SG, 2002, HANDBOOK OF ECOLOGICAL RESTORATION, VOL 1, P83
   Whitford WG, 1996, BIODIVERS CONSERV, V5, P185, DOI 10.1007/BF00055829
   Yates CJ, 2000, AUSTRAL ECOL, V25, P36, DOI 10.1111/j.1442-9993.2000.tb00005.x
NR 66
TC 17
Z9 18
U1 5
U2 71
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 2014
VL 383
IS 1-2
BP 231
EP 244
DI 10.1007/s11104-014-2170-1
PG 14
WC Agronomy; Plant Sciences; Soil Science
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Plant Sciences
GA AP9QY
UT WOS:000342415800017
DA 2025-01-10
ER

PT J
AU García, MM
   López, F
   Alfaro, A
   Ariza, J
   Tapias, R
AF Garcia, M. M.
   Lopez, F.
   Alfaro, A.
   Ariza, J.
   Tapias, R.
TI The use of Tagasaste (<i>Chamaecytisus proliferus</i>) from different
   origins for biomass and paper production
SO BIORESOURCE TECHNOLOGY
LA English
DT Article
DE Tagasaste; Chamaecytisus proliferus; pulp; paper; biomass
ID CYNARA-CARDUNCULUS L; CHEMICAL-COMPOSITION; FORMIC-ACID; ASPEN WOOD;
   PULP; CELLULOSE; AUTOHYDROLYSIS; PALMENSIS; KINETICS
AB In order to identify faster-growing non-woody species usable for biomass and paper production, four Tagasastes (Chamaecytisus proliferus) from different origins are tested. All the Tagasaste species (T. Huelva, T. Australia, T. New Zealand and T. La Palma island) show a good soil and climatic adaptation to Southwest Spain. The studied Tagasaste provenances shows biomass productivity ranges from 1.0 t ha(-1) yr(-1) to 3.4 t ha(-1) yr(-1) (o.d.b.) and 25.3 t ha(-1) yr(-1) to 49.4 t ha(-1) yr(-1) under Mediterranean conditions for first and second year sprouts, respectively. The quantity of solubles and extractives shows similar values when compared with wood materials. A relatively lower lignin content in Tagasaste (from 13.7% to 17.1%) species has been found with respect to other vegetal species. The alpha-celullose contents (43.6-45.3%) were in the range of the normal values expected for the other non-wood raw materials. The study confirms the feasibility of the organocell yield pulping process to Tagasaste provenances. Organocell processes provide an efficient delignification (kappa index from 7.2 to 10.9 and pulp yield from 43.6% to 54.1 %). The best results are obtained for the physical properties of paper sheets for Tagasaste from Australia in the second year, with values of tensile index of 16.0 kNm/kg, burst index of 1.12 MPa m(2)/kg and tear index of 0.55 Nm(2)/kg. (c) 2007 Elsevier Ltd. All rights reserved.
C1 [Garcia, M. M.; Lopez, F.; Alfaro, A.; Ariza, J.; Tapias, R.] Huelva Univ, Dept Chem Engn, Huelva 21071, Spain.
C3 Universidad de Huelva
RP López, F (corresponding author), Huelva Univ, Dept Chem Engn, Fuerzas Armada S-N, Huelva 21071, Spain.
EM baldovin@uhu.es
RI Martinez, Ascension/AAG-9748-2020; Garcia, Maider/AAL-9333-2021; Lopez,
   Francisco/D-9882-2015; Tapias Martin, Raul/K-6624-2017
OI Lopez, Francisco/0000-0002-1415-230X; Tapias Martin,
   Raul/0000-0001-6100-3908
CR Abad S, 2000, HOLZFORSCHUNG, V54, P544, DOI 10.1515/HF.2000.092
   ALCAIDE LJ, 1993, TAPPI J, V76, P169
   Ali F, 1997, J SCI IND RES INDIA, V56, P618
   ALONSO L, 1976, ANAL QUIMICO MADERAS
   Ananda J, 2003, J ENVIRON MANAGE, V68, P343, DOI 10.1016/S0301-4797(03)00082-3
   Antunes A, 2000, IND CROP PROD, V12, P85, DOI 10.1016/S0926-6690(00)00040-6
   BAYER J, 1999, ING QUIM, V3, P177
   Botello JI, 1999, J CHEM TECHNOL BIOT, V74, P141, DOI 10.1002/(SICI)1097-4660(199902)74:2<141::AID-JCTB1>3.0.CO;2-0
   BRINK ROBERT H., 1960, SOIL SCI, V89, P157, DOI 10.1097/00010694-196003000-00006
   CAPPELLETTO P, 1999, MISCANTHUS GIGANTEUS, V11, P205
   Cordeiro N, 2004, IND CROP PROD, V19, P147, DOI 10.1016/j.indcrop.2003.09.001
   Cross AF, 1999, PLANT ECOL, V145, P11, DOI 10.1023/A:1009865020145
   Dapía S, 2002, BIOMASS BIOENERG, V22, P213, DOI 10.1016/S0961-9534(01)00073-3
   de Paz JM, 2006, J ENVIRON MANAGE, V79, P150, DOI 10.1016/j.jenvman.2005.06.002
   DEESPINOSA MJ, 1993, ALBEAR, V3, P30
   Díaz MJ, 2007, IND CROP PROD, V26, P142, DOI 10.1016/j.indcrop.2007.02.003
   Díaz MJ, 2005, IND CROP PROD, V21, P211, DOI 10.1016/j.indcrop.2004.04.009
   Díaz MJ, 2004, IND ENG CHEM RES, V43, P1875, DOI 10.1021/ie030611a
   *FAO, 2006, FAOST FOR DAT
   FERNANDEZ J, 1996, FINC ORD BAD JUNT EX, P5
   Garrote G, 2002, WOOD SCI TECHNOL, V36, P111, DOI 10.1007/s00226-001-0132-2
   Gilarranz MA, 1999, IND ENG CHEM RES, V38, P3324, DOI 10.1021/ie990161f
   Gominho J, 2001, IND CROP PROD, V13, P1, DOI 10.1016/S0926-6690(00)00044-3
   HERNANDEZ C, 1996, ENERGIA BIOMASA, P11
   JIMENEZ L, 1997, INVESTIGACION TECNIC, V131, P130
   *JUNT EXTR, 1996, JORN CULT ALT AL
   Khristova P, 2002, IND CROP PROD, V15, P229, DOI 10.1016/S0926-6690(01)00118-2
   Lafay B, 2001, APPL ENVIRON MICROB, V67, P396, DOI 10.1128/AEM.67.1.396-402.2001
   Law KN, 2001, BIORESOURCE TECHNOL, V77, P1, DOI 10.1016/S0960-8524(00)00140-1
   López F, 2004, CHEM ENG RES DES, V82, P1029, DOI 10.1205/0263876041580730
   LORA JH, 1992, AICHE P FOR PROD S 1, P35
   Maximo C, 1998, 7TH INTERNATIONAL CONFERENCE ON BIOTECHNOLOGY IN THE PULP AND PAPER INDUSTRY, VOL B, pB23
   MENDEZ P, 1988, 37 REUN CIENT SOC ES, P11
   NETO CP, 1992, HOLZFORSCHUNG, V46, P69, DOI 10.1515/hfsg.1992.46.1.69
   Parajó JC, 2004, TRENDS FOOD SCI TECH, V15, P115, DOI 10.1016/j.tifs.2003.09.009
   PARAJO JC, 1993, HOLZFORSCHUNG, V47, P188, DOI 10.1515/hfsg.1993.47.3.188
   PEREIRA H, 1986, APPITA, V39, P455
   Rodríguez-Echeverría S, 2003, J APPL MICROBIOL, V95, P1367, DOI 10.1046/j.1365-2672.2003.02118.x
   Rowell RM, 1998, P TECH AS P, P43
   SNOOK LC, 1982, AUST ANIM PROD AUST, V15, P589
   SNOOK LC, 1982, J AUST I AGR SCI, V1, P12
   Sun RC, 2004, SEP SCI TECHNOL, V39, P391, DOI 10.1081/SS-120027565
   TWOSEND RJ, 1987, P NZ GRASSLAND ASS, V48, P109
   Ulrich A, 2000, MICROBIOL-UK, V146, P2997, DOI 10.1099/00221287-146-11-2997
   Ververis C, 2004, IND CROP PROD, V19, P245, DOI 10.1016/j.indcrop.2003.10.006
   WEBB CJ, 1985, NEW ZEAL J BOT, V23, P597, DOI 10.1080/0028825X.1985.10434230
   Wise L. E., 1946, Paper Trade Journal, V122, P35
   Yáñez R, 2000, TAPPI J, V83, P54
   Zalidis G, 2002, AGR ECOSYST ENVIRON, V88, P137, DOI 10.1016/S0167-8809(01)00249-3
NR 49
TC 9
Z9 11
U1 0
U2 7
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0960-8524
EI 1873-2976
J9 BIORESOURCE TECHNOL
JI Bioresour. Technol.
PD JUN
PY 2008
VL 99
IS 9
BP 3451
EP 3457
DI 10.1016/j.biortech.2007.08.004
PG 7
WC Agricultural Engineering; Biotechnology & Applied Microbiology; Energy &
   Fuels
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Biotechnology & Applied Microbiology; Energy & Fuels
GA 281EI
UT WOS:000254479300018
PM 17881228
DA 2025-01-10
ER

PT J
AU Rhoné, B
   Remoué, C
   Galic, N
   Goldringer, I
   Bonnin, I
AF Rhone, Benedicte
   Remoue, Carine
   Galic, Nathalie
   Goldringer, Isabelle
   Bonnin, Isabelle
TI Insight into the genetic bases of climatic adaptation in experimentally
   evolving wheat populations
SO MOLECULAR ECOLOGY
LA English
DT Article
DE adaptation; differentiation; experimental populations; flowering time;
   growth habit; Triticum aestivum L.
ID PATHOGEN INFECTION; ALLELIC VARIATION; FLOWERING TIME; GROWTH HABIT;
   VERNALIZATION; EVOLUTION; SELECTION; VRN-1; DIFFERENTIATION; RESISTANCE
AB Experimental populations evolving under natural selection represent an interesting tool to study genetic bases of adaptation. Evolution of genes possibly involved in adaptive response can be followed together with the corresponding phenotypic traits. Using experimental populations of hexaploid wheat, we studied the evolution of flowering time, a major adaptive trait that synchronizes the initiation of reproduction and the occurrence of favourable environmental conditions. During 12 generations, three populations were grown in contrasted environments (Vervins North France, Le Moulon near Paris, Toulouse South France) under the influence of natural selection, drift, mutation and recombination. Evolution of diversity at the major gene VRN-1 involved in wheat vernalization response has been analysed jointly with earliness estimated in controlled conditions. Whatever the population, rapid phenotypic changes as well as parallel genotypic variations were observed in the first seven generations, probably as the result of selection acting on this major gene which explains 80% of the trait variation overall. Different allelic combinations at physically unlinked copies of VRN-1 located on distinct genomes (A, B and D) were selected between populations. As theoretically expected, due to population differentiation, a high level of genetic diversity was maintained overall in generation 12. Surprisingly, in two populations out of three, the emergence of new alleles by mutation or migration, coupled with temporal variable selection or frequency-dependent selection, allowed to maintain within-population diversity despite local genetic drift and natural selection. This result may plead for an evolutionary approach of wheat genetic resource conservation.
C1 [Rhone, Benedicte; Remoue, Carine; Galic, Nathalie; Goldringer, Isabelle; Bonnin, Isabelle] Univ Paris 11, CNRS, INRA, AgrParisTech,UMR Genet Vegetale, F-91190 Gif Sur Yvette, France.
C3 Universite Paris Saclay; INRAE; Centre National de la Recherche
   Scientifique (CNRS)
RP Rhoné, B (corresponding author), Univ Paris 11, CNRS, INRA, AgrParisTech,UMR Genet Vegetale, F-91190 Gif Sur Yvette, France.
EM rhone@moulon.inra.fr
RI Rhoné, Bénédicte/AAE-8120-2022
OI Rhone, Benedicte/0000-0002-4198-622X; Remoue, Carine/0000-0002-2653-5084
CR Andersen CH, 2004, TRENDS PLANT SCI, V9, P105, DOI 10.1016/j.tplants.2004.01.002
   [Anonymous], 2002, FSTAT VERSION 2 9 3
   Barton NH, 2002, NAT REV GENET, V3, P11, DOI 10.1038/nrg700
   Belkhir K, 2004, GENETIX 4.05, logiciel sous Windows TM pour la genetique des populations
   Bonnin I, 2001, MOL ECOL, V10, P1371, DOI 10.1046/j.1365-294X.2001.01278.x
   Boutin-Ganache I, 2001, BIOTECHNIQUES, V31, P24, DOI 10.2144/01311bm02
   Caicedo AL, 2004, P NATL ACAD SCI USA, V101, P15670, DOI 10.1073/pnas.0406232101
   Carter AJR, 2005, THEOR POPUL BIOL, V68, P179, DOI 10.1016/j.tpb.2005.05.002
   Doebley J, 1998, PLANT CELL, V10, P1075, DOI 10.1105/tpc.10.7.1075
   Dvorak J, 2000, CHROMOSOMA, V109, P410, DOI 10.1007/s004120000093
   Ehrenreich IM, 2006, AM J BOT, V93, P953, DOI 10.3732/ajb.93.7.953
   ELZINGA IA, 2007, TRENDS ECOL EVOL, V8, P432
   Enjalbert J, 2000, GENETICS, V156, P1973
   Enjalbert J, 1999, J EXP BOT, V50, P283, DOI 10.1093/jexbot/50.332.283
   Excoffier L, 2005, EVOL BIOINFORM, V1, P47, DOI 10.1177/117693430500100003
   Fu DL, 2005, MOL GENET GENOMICS, V273, P54, DOI 10.1007/s00438-004-1095-4
   Glémin S, 2006, P ROY SOC B-BIOL SCI, V273, P3011, DOI 10.1098/rspb.2006.3657
   Goldringer I, 2001, GENET SEL EVOL, V33, pS441, DOI 10.1186/BF03500894
   Goldringer I, 2006, ANN BOT-LONDON, V98, P805, DOI 10.1093/aob/mcl160
   Goudet J, 1996, GENETICS, V144, P1933
   Hanocq E, 2007, THEOR APPL GENET, V114, P569, DOI 10.1007/s00122-006-0459-z
   Hanson BD, 2005, CROP SCI, V45, P1610, DOI 10.2135/cropsci2004.0443
   Hedrick P.W., 2005, Genetics of Populations
   Korves TM, 2003, PLANT PHYSIOL, V133, P339, DOI 10.1104/pp.103.027094
   Law CN, 1997, NEW PHYTOL, V137, P19, DOI 10.1046/j.1469-8137.1997.00814.x
   LEBOULCH V, 1994, GENET SEL EVOL, V26, pS221, DOI 10.1051/gse:19940715
   Loskutov IG, 2001, EUPHYTICA, V117, P125, DOI 10.1023/A:1004073904939
   Loukoianov A, 2005, PLANT PHYSIOL, V138, P2364, DOI 10.1104/pp.105.064287
   Mitchell-Olds T, 2006, NATURE, V441, P947, DOI 10.1038/nature04878
   Mouradov A, 2002, PLANT CELL, V14, pS111, DOI 10.1105/tpc.001362
   Nei M., 1987, MOL EVOLUTIONARY GEN, DOI DOI 10.7312/NEI-92038-010
   ORR HA, 2005, GENETIC THEORY ADAPT, V6, P119
   Paillard S, 2000, THEOR APPL GENET, V101, P449, DOI 10.1007/s001220051502
   Peters AD, 1999, J EVOLUTION BIOL, V12, P460, DOI 10.1046/j.1420-9101.1999.00053.x
   Purugganan MD, 2000, MOL ECOL, V9, P1451, DOI 10.1046/j.1365-294x.2000.01016.x
   Putterill J, 2004, BIOESSAYS, V26, P363, DOI 10.1002/bies.20021
   RAYMOND M, 1995, J HERED, V86, P248, DOI 10.1093/oxfordjournals.jhered.a111573
   Remington DL, 2003, INT J PLANT SCI, V164, pS7, DOI 10.1086/367812
   Rhoné B, 2007, THEOR APPL GENET, V114, P787, DOI 10.1007/s00122-006-0477-x
   Roux F, 2006, TRENDS PLANT SCI, V11, P375, DOI 10.1016/j.tplants.2006.06.006
   SAS Institute, 2000, SAS STAT US GUID VER
   Schlötterer C, 2002, CURR OPIN GENET DEV, V12, P683, DOI 10.1016/S0959-437X(02)00349-0
   Sherman JD, 2004, CROP SCI, V44, P1832, DOI 10.2135/cropsci2004.1832
   Staden R, 2000, Methods Mol Biol, V132, P115
   STELMAKH AF, 1987, EUPHYTICA, V36, P513, DOI 10.1007/BF00041495
   WEIR BS, 1984, EVOLUTION, V38, P1358, DOI [10.2307/2408641, 10.1111/j.1558-5646.1984.tb05657.x]
   Wray GA, 2007, NAT REV GENET, V8, P206, DOI 10.1038/nrg2063
   Yan L, 2003, P NATL ACAD SCI USA, V100, P6263, DOI 10.1073/pnas.0937399100
   Yan L, 2006, P NATL ACAD SCI USA, V103, P19581, DOI 10.1073/pnas.0607142103
   Yan L, 2004, THEOR APPL GENET, V109, P1677, DOI 10.1007/s00122-004-1796-4
   Zuker M, 2003, NUCLEIC ACIDS RES, V31, P3406, DOI 10.1093/nar/gkg595
NR 51
TC 37
Z9 39
U1 0
U2 24
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 FEB
PY 2008
VL 17
IS 3
BP 930
EP 943
DI 10.1111/j.1365-294X.2007.03619.x
PG 14
WC Biochemistry & Molecular Biology; Ecology; Evolutionary Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Environmental Sciences & Ecology;
   Evolutionary Biology
GA 254AK
UT WOS:000252558500018
PM 18194164
DA 2025-01-10
ER

PT C
AU Tumuhairwe, JB
   Rwakaikara-Silver, MC
   Muwanga, S
   Natigo, S
AF Tumuhairwe, J. B.
   Rwakaikara-Silver, M. C.
   Muwanga, S.
   Natigo, S.
BE Bationo, A
   Waswa, B
   Kihara, J
   Kimetu, J
TI Screening legume green manure for climatic adaptability and farmer
   acceptance in the semi-arid agro-ecological zone of Uganda
SO ADVANCES IN INTEGRATED SOIL FERTILITY MANAGEMENT IN SUB-SAHARAN AFRICA:
   CHALLENGES AND OPPORTUNITIES
LA English
DT Proceedings Paper
CT Biannual Meeting on Advances in Integrated Soil Fertility Management in
   Sub-Saharan Africa - Challenges and Opportunities
CY MAY, 2004
CL Yaounde, CAMEROON
DE Canavalia ensiformis; Crotalaria grahamiana; Crotalaria ochroleuca;
   Lablab purpureum; Mucuna pruriens; soil fertility; Tephrosia vogelli
ID SYSTEMS
AB Crop yields in Uganda are severely limited by declining soil fertility. Nitrogen (N), phosphorus (P) and soil organic matter (SOM) are the most limiting factors, yet legume green manures are known to fix N-2 and increase SOM. Legume green manure technology has proved suitable for smallholder and subsistence farmers in sub-Saharan Africa. In Uganda, the spread of the technology has so far been concentrated in the central and eastern part of the country. Therefore, this study aimed at scaling out the legume green manure technology in the western semi-arid and cattle corridor zone of Uganda through on-farm researcher-designed, researcher/farmer managed village trials. For this purpose the six legumes namely Crotalaria grahamiana, Crotalaria ochroleuca, Mucuna pruriens, Canavalia ensiformis, Lablab purpureum and Tephrosia vogelli were tested in plot of 10 m by 10 m in a randomized complete block design whereby each farm site represented a replicate. Six months after planting of the legumes, farmers were individually asked to select their preferred species and to name the reasons for their choice. Subsequently, the legume biomass was determined and incorporated in the soil prior to planting maize. C. ensiformis and T vogelli were the most and least preferred species, respectively, C. ensiformsis yielded the highest (5.2 t ha(-1)) and T vogelli the lowest (2.0 t ha(-1)) biomass. Highest maize grain yields were obtained from plots of M. pruriens (3.5 t ha(-1)), but they were not significantly different from those of C. ensiformis with 3.4 t ha(-1). Incorporation of the natural fallow vegetation led to the lowest maize grain yields (1.9 tha(-1)).
C1 [Tumuhairwe, J. B.; Rwakaikara-Silver, M. C.; Muwanga, S.] Makerere Univ, Dept Soil Sci, POB 7062, Kampala, Uganda.
   [Natigo, S.] Fac Farm, Kampala, Uganda.
C3 Makerere University
RP Tumuhairwe, JB (corresponding author), Makerere Univ, Dept Soil Sci, POB 7062, Kampala, Uganda.
EM jbtumuhairewe@agric.mak.ac.ug
OI Tumuhairwe, John Baptist/0000-0001-9766-9170
FU AfNet-TSBF/CIAT
FX The authors are very grateful to AfNet-TSBF/CIAT for the financial and
   technical support to conduct the study.
CR Bekunda M. A., 1997, Replenishing soil fertility in Africa. Proceedings of an international symposium, Indianapolis, USA, 6 November 1996., P63
   Fischler M, 1999, AGROFOREST SYST, V47, P123, DOI 10.1023/A:1006234523163
   FISCHLER M, 1997, THESIS ETH ZURICH
   LAL R, 1991, P COV CROPS CLEAN WA, P1
   Mureithi J.G., 2003, TROPICAL SUBTROPICAL, V1, P57
   Okalebo J.R., 1993, LAB METHODS SOIL PLA
   Sanchez PA, 1997, PHILOS T R SOC B, V352, P949, DOI 10.1098/rstb.1997.0074
   Walaga C., 2000, Nutrients on the Move- Soil Fertility Dynamics in African farming Systems, P29
   Wortmann CS, 1998, AGR ECOSYST ENVIRON, V71, P115, DOI 10.1016/S0167-8809(98)00135-2
NR 9
TC 1
Z9 2
U1 0
U2 7
PU SPRINGER
PI DORDRECHT
PA PO BOX 17, 3300 AA DORDRECHT, NETHERLANDS
BN 978-1-4020-5759-5
PY 2007
BP 255
EP 259
DI 10.1007/978-1-4020-5760-1_22
PG 5
WC Agriculture, Multidisciplinary; Agronomy; Soil Science
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Agriculture
GA BGZ61
UT WOS:000251577700022
DA 2025-01-10
ER

PT J
AU Cevallos, B
   Aller-Rojas, O
   Aponte, H
   Moreno, B
AF Cevallos, Bruno
   Aller-Rojas, Oscar
   Aponte, Hector
   Moreno, Bernabe
TI Carbon capture by stipitate kelp forests in Peru: insights from
   population assessment of <i>Lessonia trabeculata</i> at 15°S
SO JOURNAL OF APPLIED PHYCOLOGY
LA English
DT Article
DE Macroalgae; Lessoniaceae; Marine forests; Blue carbon; Humboldt Current;
   Outwelling
ID NORTHERN CHILE; MACROCYSTIS-INTEGRIFOLIA; NIGRESCENS PHAEOPHYCEAE;
   ORGANIC-MATTER; STANDING STOCK; WAVE EXPOSURE; BROWN ALGA; SE-PACIFIC;
   LAMINARIALES; BIOMASS
AB Marine forests are key providers of ecosystem services globally with increasing recognition of their relevance in the context of climate adaptation and mitigation. Along the Southeast Pacific, these forests sustain productive and intricate trophic webs, serving as crucial sustenance for coastal systems and subsidies for deeper habitats. This study aimed to estimate the contribution of Lessonia trabeculata to the local blue carbon pathways within the southern sector of the largest coastal protected area in Peru, Reserva Nacional San Fernando (RNSF). By integrating remote sensing, scientific diving, and the traditional knowledge of artisanal divers, we conducted a comprehensive assessment and conservative estimates of carbon captured by these forests during the austral winter of 2021 using the least destructive assessment methods. We conservatively estimated similar to 1300 t C captured as standing stock by L. trabeculata in the southern sector of RNSF. Said biomass-held carbon assimilation would annually release similar to 1300 t C m(2) y(-1) as detritus, of which, once exported could potentially yield to similar to 130 t C m(2) y(-1) sequestered in deep-sea sediments. Detrital productivity of L. trabeculata was calculated for the first time in Peru, along with the social and environmental cost of emissions equivalent to the amount of carbon captured (855.8k US$) and potentially removed by the standing stock (85.7k US$). In addition, we present an overview of the conservation state of the kelp population in the coastal protected area, along with allometric equations for estimating biomass based on biometric measurements easily attainable underwater. This study represents the continuation of a pioneering effort towards the understanding of blue carbon in marine forests of Peru. Our study contributes to advancing the understanding and management of these ecosystems in the face of climate challenges. The implications for the rapidly growing blue carbon field in the region's socioecological context are further discussed.
C1 [Cevallos, Bruno; Aller-Rojas, Oscar; Aponte, Hector; Moreno, Bernabe] Univ Cientif Sur, Carrera Biol Marina, Lima, Peru.
   [Cevallos, Bruno; Aponte, Hector; Moreno, Bernabe] Univ Cientif Sur, Coastal Ecosyst Peru Res Grp COEPeru, Lima, Peru.
   [Moreno, Bernabe] Polish Acad Sci, Marine Ecol Dept, Inst Oceanol, Sopot, Poland.
   [Moreno, Bernabe] Univ Cientif Sur, Comun Acuat Res Grp, Lima, Peru.
C3 Universidad Cientifica del Sur (CIENTIFICA); Universidad Cientifica del
   Sur (CIENTIFICA); Polish Academy of Sciences; Institute of Oceanology of
   the Polish Academy of Sciences; Universidad Cientifica del Sur
   (CIENTIFICA)
RP Moreno, B (corresponding author), Univ Cientif Sur, Carrera Biol Marina, Lima, Peru.; Moreno, B (corresponding author), Univ Cientif Sur, Coastal Ecosyst Peru Res Grp COEPeru, Lima, Peru.; Moreno, B (corresponding author), Polish Acad Sci, Marine Ecol Dept, Inst Oceanol, Sopot, Poland.; Moreno, B (corresponding author), Univ Cientif Sur, Comun Acuat Res Grp, Lima, Peru.
EM bmorenole@cientifica.edu.pe
RI Moreno, Bernabé/HGU-3920-2022; Gil, Bruno/ADE-6576-2022; Aponte,
   Héctor/JCE-3444-2023
OI Cevallos Gil, Bruno/0000-0002-5765-0608; Aponte Ubillus,
   Hector/0000-0001-5249-9534
FU KfW; Universidad Cientifica del Sur [2021-2]
FX Research funds were granted by KfW and co-managed by the Peruvian Trust
   Fund for National Parks and Protected Areas (PROFONANPE), Servicio
   Nacional de & Aacute;reas Naturales Protegidas (SERNANP), and the
   Economic and Social Research Consortium (CIES). The project led by BM
   was entitled "Determinacion de la distribucion, la biomasa e importancia
   ecologica del 'Aracanto palo' Lessonia trabeculata en el ambito marino
   de la Reserva Nacional San Fernando" (Beca SERNANP 2020 A1 Equipo
   IMP-05). BC was co-funded by the internal research grant Beca Cabieses
   2021-2-Universidad Cientifica del Sur. Sampling permit was granted by
   Ministerio de la Produccion (PRODUCE) to BM through the R.D.
   No00166-2021-PRODUCE/DGPCHDI.
CR Abukawa K, 2013, LIMNOLOGY, V14, P39, DOI 10.1007/s10201-012-0383-7
   Aller-Rojas O, 2020, CARBON MANAG, V11, P525, DOI 10.1080/17583004.2020.1808765
   Vega JMA, 2018, LAT AM J AQUAT RES, V46, P258, DOI 10.3856/vol46-issue2-fulltext-2
   Alvarez Rojas C, 2023, GUIA IMPLEMENTACION
   Amano C, 2022, NAT GEOSCI, V15, P1041, DOI 10.1038/s41561-022-01081-3
   [Anonymous], 2013, Aquatic Photosynthesis
   Aramayo V., 2021, Boletin Instituto del Mar del Per, V36, P476
   Casares FA, 2016, EVOL ECOL, V30, P953, DOI 10.1007/s10682-016-9849-0
   Attridge CM, 2022, MAR ECOL PROG SER, V702, P39, DOI 10.3354/meps14191
   Atwood TB, 2020, FRONT MAR SCI, V7, DOI 10.3389/fmars.2020.00165
   Avila-Peltroche J, 2022, BOT MAR, V65, P209, DOI 10.1515/bot-2022-0002
   Baskett ML, 2005, ECOL APPL, V15, P882, DOI 10.1890/04-0723
   Bayley DTI, 2021, ONE ECOSYSTEM, V6, DOI 10.3897/oneeco.6.e62811
   Beckensteiner J, 2020, OCEAN COAST MANAGE, V183, DOI 10.1016/j.ocecoaman.2019.104961
   Bolton JJ, 2016, AQUAT BOT, V132, P1, DOI 10.1016/j.aquabot.2016.02.006
   Bolton JJ, 2010, HELGOLAND MAR RES, V64, P263, DOI 10.1007/s10152-010-0211-6
   BRADYCAMPBELL MM, 1984, MAR ECOL PROG SER, V18, P79, DOI 10.3354/meps018079
   Buck-Wiese H, 2022, P NATL ACAD SCI USA, V120, DOI 10.1073/pnas.2210561119
   Bularz B, 2022, ECOSPHERE, V13, DOI 10.1002/ecs2.3958
   Cai J., Seaweeds and microalgae: an overview for unlocking their potential in global aquaculture development, DOI DOI 10.4060/CB5670EN
   Campos L, 2021, MAR POLICY, V133, DOI 10.1016/j.marpol.2021.104737
   Campos L, 2021, ESTUAR COAST SHELF S, V252, DOI 10.1016/j.ecss.2021.107266
   CAMUS PA, 1992, MAR ECOL PROG SER, V90, P193, DOI 10.3354/meps090193
   Carbajal P, 2022, AQUAT CONSERV, V32, P14, DOI 10.1002/aqc.3745
   Chen YY, 2022, FRONT PSYCHOL, V13, DOI 10.3389/fpsyg.2022.768773
   Chevallier A., 2021, MARINE COASTAL ECOSY, P27, DOI [10.1007/978-3-030-58211-12, DOI 10.1007/978-3-030-58211-1_2, 10.1007/978-3-030-58211-1_2]
   Comte D., 1991, Natural Hazards, V4, P23, DOI 10.1007/BF00126557
   Contreras J, 2018, EUR J SUSTAIN DEV, V7, P435, DOI 10.14207/ejsd.2018.v7n4p435
   Contreras L, 2007, ENVIRON POLLUT, V145, P75, DOI 10.1016/j.envpol.2006.03.051
   Cuba D., 2022, Coasts, V2, P259, DOI DOI 10.3390/COASTS2040013
   Darimont CT, 2009, P NATL ACAD SCI USA, V106, P952, DOI 10.1073/pnas.0809235106
   Dawson E.Y., 1964, Beihefte Nova Hedwigia, V13, P1
   de Bettignies T, 2013, LIMNOL OCEANOGR, V58, P1680, DOI 10.4319/lo.2013.58.5.1680
   Des M, 2020, MAR ENVIRON RES, V161, DOI 10.1016/j.marenvres.2020.105074
   Duarte CM, 2022, GLOBAL ECOL BIOGEOGR, V31, P1422, DOI 10.1111/geb.13515
   EDDING M, 1990, HYDROBIOLOGIA, V204, P361, DOI 10.1007/BF00040257
   Edding Mario E., 1994, P407
   EDDING ME, 1993, HYDROBIOLOGIA, V261, P231
   Edding ME, 2003, AQUAC RES, V34, P507, DOI 10.1046/j.1365-2109.2003.00827.x
   Eger AM, 2023, NAT COMMUN, V14, DOI 10.1038/s41467-023-37385-0
   Eger AM, 2022, BIOL REV, V97, P1449, DOI 10.1111/brv.12850
   El Peruano, 2019, RESOLUCION PRESIDENC
   ENFEN, 2012, DEFINICION OPERACION
   Erlania, 2023, SCI TOTAL ENVIRON, V890, DOI 10.1016/j.scitotenv.2023.164430
   Ernande B, 2004, P ROY SOC B-BIOL SCI, V271, P415, DOI 10.1098/rspb.2003.2519
   Escudero L., 2020, B I MAR, V35, P257
   Ferduose F, 2018, GLOBEFISH RES PROGRA, V124
   Fernandez E., 1999, REV PERUANA BIOL, V6, P47, DOI [10.15381/rpb.v6i3.8430, DOI 10.15381/RPB.V6I3.8430]
   Filbee-Dexter K, 2022, J PHYCOL, V58, P198, DOI 10.1111/jpy.13239
   Filbee-Dexter K, 2020, ONE EARTH, V2, P398, DOI 10.1016/j.oneear.2020.05.004
   Filbee-Dexter K, 2019, GLOBAL PLANET CHANGE, V172, P1, DOI 10.1016/j.gloplacha.2018.09.005
   Filbee-Dexter K, 2018, BIOSCIENCE, V68, P64, DOI 10.1093/biosci/bix147
   Fischell E., 2018, J ACOUST SOC AM, V144, P1806, DOI [10.1121/1.5067972, DOI 10.1121/1.5067972]
   Flores E, 2022, BIOGEOSCIENCES, V19, P1395, DOI 10.5194/bg-19-1395-2022
   Foster MS., 1985, Biological Report, V85
   Getirana A, 2018, REMOTE SENS ENVIRON, V217, P366, DOI 10.1016/j.rse.2018.08.030
   Gevaert F, 2008, J SEA RES, V60, P215, DOI 10.1016/j.seares.2008.06.006
   Gil-Kodaka P, 2002, 1 JORN CIENT BAS EC, P154
   GOMEZ A, 2023, B INVEST MAR COST, V52, P125, DOI DOI 10.25268/bimc.invemar.2023.52.2.1218
   González AV, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0169182
   González AV, 2015, PHYCOLOGIA, V54, P283, DOI 10.2216/14-105.1
   González CP, 2018, MAR POLLUT BULL, V135, P694, DOI 10.1016/j.marpolbul.2018.07.072
   Gonzalez-Aragon D, 2024, ECOL EVOL, V14, DOI 10.1002/ece3.10901
   Gouraguine A, 2021, MAR BIOL, V168, DOI 10.1007/s00227-021-03870-7
   Guillemin M., 2016, Seaweed Phylogeography, P251, DOI DOI 10.1007/978-94-017-7534-2_10
   HAYASHIDA F, 1977, B JPN SOC SCI FISH, V43, P1043
   Hermosillo-Núñez BB, 2020, HYDROBIOLOGIA, V847, P739, DOI 10.1007/s10750-019-04134-8
   Hernandez Oyarzun JE, 2018, THESIS U CHILE
   Howe M.A., 1914, Memoirs of the Torrey Botanical Club, V15, P1
   Huovinen P, 2020, SCI TOTAL ENVIRON, V703, DOI 10.1016/j.scitotenv.2019.135531
   Hurd CL, 2022, J PHYCOL, V58, P347, DOI 10.1111/jpy.13249
   Hurtado A.Q., 2022, Genetic resources for farmed seaweeds-thematic background study
   IMARPE, 2022, ESTUDIO BIOLOGICO PO
   INGEMMET, 2021, BATHYMETRIC DATASET
   Japan Blue Economy, 2022, METHODOLOGY QUANTIFY
   Jayathilake DRM, 2021, BIOL CONSERV, V257, DOI 10.1016/j.biocon.2021.109099
   JOHNSTON CS, 1977, HELGOLAND WISS MEER, V30, P527, DOI 10.1007/BF02207859
   JUPP BP, 1974, J EXP MAR BIOL ECOL, V15, P185, DOI 10.1016/0022-0981(74)90044-6
   KIRKMAN H, 1984, J EXP MAR BIOL ECOL, V76, P119, DOI 10.1016/0022-0981(84)90060-1
   Kosek K, 2023, MAR POLLUT BULL, V196, DOI 10.1016/j.marpolbul.2023.115655
   Krause-Jensen D, 2016, NAT GEOSCI, V9, P737, DOI [10.1038/NGEO2790, 10.1038/ngeo2790]
   KREMER BP, 1984, J PLANT PHYSIOL, V117, P233, DOI 10.1016/S0176-1617(84)80005-X
   Krumhansl KA, 2012, MAR ECOL PROG SER, V467, P281, DOI 10.3354/meps09940
   Leonardi PI, 1999, HYDROBIOLOGIA, V399, P375
   Levin LA, 2001, ANNU REV ECOL SYST, V32, P51, DOI 10.1146/annurev.ecolsys.32.081501.114002
   Lleelish J, 2001, SUSTENTABILIDAD BIOD, P331
   Lucero S, 2019, INF I MAR PERU, V46, P34
   LUNING K, 1969, MAR BIOL, V3, P282, DOI 10.1007/BF00360961
   MANN KH, 1973, SCIENCE, V182, P975, DOI 10.1126/science.182.4116.975
   MANN KH, 1972, MAR BIOL, V12, P1
   MaqueraLS Herrera, 2019, THESIS NATL U MOQUEG
   Marquez Raul, 2020, European Review of Latin American and Caribbean Studies, P101, DOI 10.32992/erlacs.10590
   Martin P, 2011, THESIS TE HERENGA WA
   Martin P, 2012, PHYCOL RES, V60, P276, DOI 10.1111/j.1440-1835.2012.00658.x
   Martínez EA, 2003, J PHYCOL, V39, P504, DOI 10.1046/j.1529-8817.2003.02191.x
   McKinley E, 2019, ENVIRON DEV SUSTAIN, V21, P2253, DOI 10.1007/s10668-018-0133-z
   MINAM, 2022, 3 NAT COMM PER UN FR
   Mora-Soto A, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12040694
   Moreno B., 2021, S SUSTAINABILITY, V2, pe038, DOI [10.21142/SS-0202-2021-m001, DOI 10.21142/SS-0202-2021-M001]
   Murúa P, 2013, PHYCOL RES, V61, P145, DOI 10.1111/pre.12013
   Nardelli AE, 2023, J APPL PHYCOL, V35, P1485, DOI 10.1007/s10811-023-02968-3
   NEWELL RC, 1982, MAR ECOL PROG SER, V8, P103, DOI 10.3354/meps008103
   NOAA, 2023, DATABASE TEMPERATURE
   OEFA, 2014, RESOLUCION DIRECTORA
   OEFA, 2019, OEFA ORD SHOUG PAR I
   Ortiz M, 2020, 304863770 FICATACAMA
   Ortiz M, 2008, ECOL MODEL, V216, P31, DOI 10.1016/j.ecolmodel.2008.04.006
   Ortiz M, 2010, AQUAT CONSERV, V20, P494, DOI 10.1002/aqc.1126
   Oyarzo-Miranda C, 2023, FRONT MAR SCI, V9, DOI 10.3389/fmars.2022.1062481
   Palanques A, 2002, J MAR RES, V60, P347, DOI 10.1357/00222400260497525
   Palkovacs EP, 2018, FRONT ECOL ENVIRON, V16, P20, DOI 10.1002/fee.1743
   Pedersen MF, 2020, OECOLOGIA, V192, P227, DOI 10.1007/s00442-019-04573-z
   Perreault MC, 2014, J EXP MAR BIOL ECOL, V453, P22, DOI 10.1016/j.jembe.2013.12.021
   Pessarrodona A, 2023, BIOL REV, V98, P1945, DOI 10.1111/brv.12990
   Pessarrodona A, 2022, SCI DATA, V9, DOI 10.1038/s41597-022-01554-5
   Pessarrodona A, 2021, GLOBAL CHANGE BIOL, V27, P5262, DOI 10.1111/gcb.15759
   Pessarrodona A, 2018, GLOBAL CHANGE BIOL, V24, P4386, DOI 10.1111/gcb.14303
   Reed DC., 2009, The management of natural coastal carbon sinks, P30
   Rodríguez D, 2014, J APPL PHYCOL, V26, P1115, DOI 10.1007/s10811-013-0121-5
   Ross FWR, 2023, SCI TOTAL ENVIRON, V885, DOI 10.1016/j.scitotenv.2023.163699
   Sagawa T, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11101155
   Salomon AK, 2008, ECOL APPL, V18, P1874, DOI 10.1890/07-1777.1
   Santos IR, 2021, ESTUAR COAST SHELF S, V255, DOI 10.1016/j.ecss.2021.107361
   Scheffer M, 2001, NATURE, V413, P591, DOI 10.1038/35098000
   Schiel D. R., 2015, The biology and ecology of giant kelp forests, DOI [10.1525/california/9780520278-868.003.0010, DOI 10.1525/CALIFORNIA/9780520278-868.003.0010]
   Schimel ACG, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12091371
   Scrosati R, 2005, PHYCOL RES, V53, P224
   SEARLES RB, 1978, BRIT PHYCOL J, V13, P361, DOI 10.1080/00071617800650421
   Segovia NI, 2015, MAR ECOL-EVOL PERSP, V36, P1107, DOI 10.1111/maec.12206
   Shao H, 2017, J MAR SCI TECH-TAIW, V25, P343, DOI 10.6119/JMST-016-1229-1
   Sjotun K, 1998, EUR J PHYCOL, V33, P337, DOI 10.1017/S0967026298001838
   Smale DA, 2020, NEW PHYTOL, V225, P1447, DOI 10.1111/nph.16107
   Smale DA, 2016, MAR ECOL PROG SER, V542, P79, DOI 10.3354/meps11544
   Smale DA, 2013, P ROY SOC B-BIOL SCI, V280, DOI 10.1098/rspb.2012.2829
   Starko S, 2019, MOL PHYLOGENET EVOL, V136, P138, DOI 10.1016/j.ympev.2019.04.012
   Steneck RS, 2013, B MAR SCI, V89, P31, DOI 10.5343/bms.2011.1148
   Stenius I, 2022, SENSORS-BASEL, V22, DOI 10.3390/s22135064
   Tala F, 2004, NEW ZEAL J MAR FRESH, V38, P255, DOI 10.1080/00288330.2004.9517235
   Tala F, 2007, PHYCOL RES, V55, P66, DOI 10.1111/j.1440-1835.2006.00447.x
   Tanaka H., 2023, MOVING NET ZERO CARB, P107, DOI [10.1007/978-3-031-24545-97, DOI 10.1007/978-3-031-24545-97]
   Tarazona J, 1988, RECURSOS DYNAMICA EC, P115
   Tejada A, 2018, INF I MAR PERU, V45, P194
   Tejada A, 2019, INFORME INSTITUTO MA, V46, P52
   Thiel M, 2007, OCEANOGR MAR BIOL, V45, P195
   Torres N, 2023, REV DERECHO PUBLICO, V3, P831
   UNFCCC, 2022, COMMON METRICS
   United Nations Environment Programme and Norwegian Blue Forests Network, 2023, Into the blue: securing a sustainable future for kelp forests
   Uribe R, 2015, THESIS U ANATOFAGAST
   Uribe RA, 2022, ESTUAR COAST SHELF S, V269, DOI 10.1016/j.ecss.2022.107813
   Valiente O, 2013, B INVEST I TECNOL PR, V11, P91
   Valles-Maravi P., 2022, S SUSTAINABILITY, V3, pe045, DOI [10.21142/SS-0301-2022-e045, DOI 10.21142/SS-0301-2022-E045]
   Valqui J, 2021, ESTUAR COAST SHELF S, V250, DOI 10.1016/j.ecss.2020.107142
   Vásquez JA, 1999, HYDROBIOLOGIA, V399, P217, DOI 10.1023/A:1017054517382
   Vasquez JA, 1989, DOCTORAL DISSERTATIO, P261
   Vasquez JA, 2012, INF I MAR PERU, P5
   Vasquez JA, 2004, NINO NINA 1997 2000, P119
   Vásquez JA, 2006, J APPL PHYCOL, V18, P505, DOI 10.1007/s10811-006-9056-4
   Vasquez Julio A., 1996, Hydrobiologia, V326-327, P327, DOI 10.1007/BF00047826
   Vásquez JA, 2014, J APPL PHYCOL, V26, P1081, DOI 10.1007/s10811-013-0173-6
   Vega JMA, 2005, REV CHIL HIST NAT, V78, P33
   Vega-Abad GA, 2020, THESIS U NACL AGRARI
   Velazco F, 2015, IN SITU MAR PERU INF, V42, P526
   Velazco F, 2017, INF I MAR PERU, V44, P198
   VENEGAS M, 1993, BOT MAR, V36, P47, DOI 10.1515/botm.1993.36.1.47
   Villegas MJ, 2008, HELGOLAND MAR RES, V62, pS33, DOI 10.1007/s10152-007-0096-1
   VILLOUTA E, 1986, PHYCOLOGIA, V25, P81, DOI 10.2216/i0031-8884-25-1-81.1
   Walkley A, 1934, SOIL SCI, V37, P29, DOI 10.1097/00010694-193401000-00003
   Webb P, 2023, GLOB FOOD SECUR-AGR, V37, DOI 10.1016/j.gfs.2023.100686
   Wernberg T, 2005, AQUAT BOT, V82, P168, DOI 10.1016/j.aquabot.2005.04.003
   Wernberg T, 2019, WORLD SEAS: AN ENVIRONMENTAL EVALUATION, VOL III: ECOLOGICAL ISSUES AND ENVIRONMENTAL IMPACTS, 2ND EDITION, P57, DOI 10.1016/B978-0-12-805052-1.00003-6
   Wernberg T, 2010, ECOL LETT, V13, P685, DOI 10.1111/j.1461-0248.2010.01466.x
   Westermeier R, 2006, AQUAC RES, V37, P164, DOI 10.1111/j.1365-2109.2005.01414.x
   Westermeier R, 2017, J APPL PHYCOL, V29, P2267, DOI 10.1007/s10811-016-1019-9
   Westermeier R, 2016, J APPL PHYCOL, V28, P2969, DOI 10.1007/s10811-016-0827-2
   Wiktor JM Jr, 2022, FRONT MAR SCI, V9, DOI 10.3389/fmars.2022.1021675
   Wilkinson M., 2020, COLLECTING IDENTIFYI
   Wilmers CC, 2012, FRONT ECOL ENVIRON, V10, P409, DOI 10.1890/110176
   Zavala J., 2010, INF I MAR, V42, P510
   Zhou XL, 2021, NAT PLANTS, V7, DOI 10.1038/s41477-020-00815-8
NR 179
TC 0
Z9 0
U1 8
U2 10
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0921-8971
EI 1573-5176
J9 J APPL PHYCOL
JI J. Appl. Phycol.
PD OCT
PY 2024
VL 36
IS 5
BP 3057
EP 3076
DI 10.1007/s10811-024-03269-z
EA JUN 2024
PG 20
WC Biotechnology & Applied Microbiology; Marine & Freshwater Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biotechnology & Applied Microbiology; Marine & Freshwater Biology
GA I2Y7M
UT WOS:001247220700005
DA 2025-01-10
ER

PT J
AU Ishiyama, N
   Sueyoshi, M
   Molinos, JG
   Iwasaki, K
   Negishi, JN
   Koizumi, I
   Nagayama, S
   Nagasaka, A
   Nagasaka, Y
   Nakamura, F
AF Ishiyama, Nobuo
   Sueyoshi, Masanao
   Molinos, Jorge Garcia
   Iwasaki, Kenta
   Negishi, Junjiro N.
   Koizumi, Itsuro
   Nagayama, Shigeya
   Nagasaka, Akiko
   Nagasaka, Yu
   Nakamura, Futoshi
TI Underlying geology and climate interactively shape climate change
   refugia in mountain streams
SO ECOLOGICAL MONOGRAPHS
LA English
DT Article
DE climate-change refugia; connectivity; freshwater biodiversity;
   geodiversity; habitat fragmentation; microclimate
ID TEMPERATURE; GROUNDWATER; TROUT; RIVERS; HETEROGENEITY; CATCHMENT;
   SCENARIOS; COMMUNITY; HOKKAIDO; RANGE
AB Identifying climate-change refugia is a key adaptation strategy for reducing global warming impacts. Knowledge of the effects of underlying geology on thermal regime along climate gradients and the ecological responses to the geology-controlled thermal regime is essential to plan appropriate climate adaptation strategies. In the present study, the dominance of volcanic rocks in the watershed is used as a landscape-scale surrogate for cold groundwater inputs to clarify the importance of underlying geology in stream ecosystems along climate gradients. First, using hundreds of monitoring stations distributed across multiple catchments, we explored the relationship between watershed geology and the mean summer water temperature of mountain streams along climate gradients in the Japanese archipelago. Mean summer water temperature was explained by the interaction between the watershed geology and climate in addition to independent effects. The cooling effect supported by volcanic rocks reached up to 3.3? among study regions, which was more pronounced in streams with less summer precipitation or lower air temperatures. Next, we examined the function of volcanic streams as cold refugia under contemporary and future climatic conditions. Community composition analyses revealed that volcanic streams hosted distinct stream communities composed of more cold-water species compared with nonvolcanic streams. Scenario analyses based on multiple global climate models and Representative Concentration Pathways (RCPs) revealed a geology-related pattern of thermal habitat loss for cold-water species. Nonvolcanic streams rapidly declined in thermally suitable habitats for lotic sculpins even under the lowest emission scenario (RCP 2.6). In contrast, most volcanic streams will be sustained below the thermal threshold, especially for low- and mid-level emission scenarios (RCP 2.6, 4.5). However, the distinct stream community in volcanic streams and geology-dependent habitat loss for lotic sculpins was not uniform and were more pronounced in streams with less summer precipitation or lower air temperatures. These findings highlight that underlying geology, climate variability, and their interaction should be considered simultaneously for the effective management of climate-change refugia in mountain streams.
C1 [Ishiyama, Nobuo; Nagasaka, Akiko; Nagasaka, Yu] Hokkaido Res Org, Forest Res Inst, Bibai, Japan.
   [Sueyoshi, Masanao; Nagayama, Shigeya] Publ Works Res Inst, Aqua Restorat Res Ctr, Kakamigahara, Japan.
   [Molinos, Jorge Garcia] Hokkaido Univ, Arctic Res Ctr, Sapporo, Japan.
   [Iwasaki, Kenta] Hokkaido Res Org, Forestry Res Inst, Doto Stn, Shintoku, Japan.
   [Negishi, Junjiro N.; Koizumi, Itsuro] Hokkaido Univ, Fac Environm Earth Sci, Sapporo, Japan.
   [Nakamura, Futoshi] Hokkaido Univ, Grad Sch Agr, Dept Forest Sci, Sapporo, Japan.
   [Sueyoshi, Masanao] Natl Inst Environm Studies, Tsukuba, Japan.
   [Iwasaki, Kenta] Forestry & Forest Prod Res Inst, Ctr Forest Damage & Risk Management, Tsukuba, Japan.
   [Nagayama, Shigeya] Gifu Univ, Reg Adaptat Res Ctr, Gifu, Japan.
C3 PWRI: Public Works Research Institute; Hokkaido University; Hokkaido
   University; Hokkaido University; National Institute for Environmental
   Studies - Japan; Forestry & Forest Products Research Institute - Japan;
   Gifu University
RP Ishiyama, N (corresponding author), Hokkaido Res Org, Forest Res Inst, Bibai, Japan.
EM night7mare@gmail.com
RI Nagayama, Shigeya/HPG-7065-2023; Koizumi, Itsuro/D-4222-2009; Ishiyama,
   Nobuo/ITF-6469-2023; Iwasaki, Kenta/AAB-6506-2021; NEGISHI,
   JUNJIRO/HMV-8630-2023; Garcia Molinos, Jorge/C-9252-2015
OI Sueyoshi, Masanao/0000-0002-5517-0256; Nagasaka,
   Akiko/0000-0001-6356-4450; Iwasaki, Kenta/0000-0002-7344-920X; Nagayama,
   Shigeya/0000-0003-0398-7827; Garcia Molinos, Jorge/0000-0001-7516-1835
FU Environmental Restoration and Conservation Agency of Japan
   [JPMEERF20202004]; JSPS KAKENHI [18K18221, 19H04314, 22H03796]; Ministry
   of Land, Infrastructure, Transport, and Tourism (MLIT); Grants-in-Aid
   for Scientific Research [23K25050, 22H03796] Funding Source: KAKEN
FX Environmental Restoration and Conservation Agency of Japan, Grant/Award
   Number: JPMEERF20202004; JSPS KAKENHI, Grant/Award Numbers: 18K18221,
   19H04314, 22H03796; Ministry of Land, Infrastructure, Transport, and
   Tourism (MLIT)
CR Ackerly DD, 2020, FRONT ECOL ENVIRON, V18, P288, DOI 10.1002/fee.2204
   Armstrong JB, 2021, NAT CLIM CHANGE, V11, P354, DOI 10.1038/s41558-021-00994-y
   Arthington AH, 2006, ECOL APPL, V16, P1311, DOI 10.1890/1051-0761(2006)016[1311:TCOPEF]2.0.CO;2
   Barbarossa V, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-21655-w
   Barrows CW, 2020, FRONT ECOL ENVIRON, V18, P298, DOI 10.1002/fee.2205
   Barton K, 2022, MUMIN PACKAGE MULTIM
   Boulton AJ, 2006, AUST J BOT, V54, P133, DOI 10.1071/BT05074
   Brewitt KS, 2014, ECOSPHERE, V5, DOI 10.1890/ES14-00036.1
   BRITTAIN JE, 1991, AUST J MAR FRESH RES, V42, P107
   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
   Caissie D, 2006, FRESHWATER BIOL, V51, P1389, DOI 10.1111/j.1365-2427.2006.01597.x
   Chessman BC, 2009, GLOBAL CHANGE BIOL, V15, P2791, DOI 10.1111/j.1365-2486.2008.01840.x
   CLARKE KR, 1993, AUST J ECOL, V18, P117, DOI 10.1111/j.1442-9993.1993.tb00438.x
   Comte L, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2011639118
   Comte L, 2013, ECOGRAPHY, V36, P1236, DOI 10.1111/j.1600-0587.2013.00282.x
   Cornu JF, 2013, HYDROGEOL J, V21, P949, DOI 10.1007/s10040-013-0984-1
   Dallas HF, 2012, HYDROBIOLOGIA, V679, P61, DOI 10.1007/s10750-011-0856-4
   De Caceres M., 2022, indicspecies: relationship between species and groups of sites
   De Cáceres M, 2009, ECOLOGY, V90, P3566, DOI 10.1890/08-1823.1
   De Frenne P, 2021, GLOBAL CHANGE BIOL, V27, P2279, DOI 10.1111/gcb.15569
   Dobrowski SZ, 2011, GLOBAL CHANGE BIOL, V17, P1022, DOI 10.1111/j.1365-2486.2010.02263.x
   Ehbrecht M, 2019, FOREST ECOL MANAG, V432, P860, DOI 10.1016/j.foreco.2018.10.008
   Fujimoto M, 2016, HYDROL PROCESS, V30, P558, DOI 10.1002/hyp.10558
   Geological Survey of Japan, 2013, 1 200000 SEAML DIG G
   Geospatial Information Authority of Japan, 2016, 10 M DIG EL MOD
   Grant EHC, 2007, ECOL LETT, V10, P165, DOI 10.1111/j.1461-0248.2006.01007.x
   Gray M, 2021, P GEOLOGIST ASSOC, V132, P605, DOI 10.1016/j.pgeola.2021.09.001
   Haesen S, 2021, GLOBAL CHANGE BIOL, V27, P6307, DOI 10.1111/gcb.15892
   Hare DK, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-21651-0
   Hatakeyama R., 2018, AQUACULTURE SCI, V66, P123
   Herrera-R GA, 2020, GLOBAL CHANGE BIOL, V26, P5509, DOI 10.1111/gcb.15285
   Hilderbrand RH, 2014, ENVIRON MANAGE, V54, P14, DOI 10.1007/s00267-014-0272-4
   Inoue M, 2009, CAN J FISH AQUAT SCI, V66, P1423, DOI 10.1139/F09-088
   Isaak DJ, 2017, WATER RESOUR RES, V53, P9181, DOI 10.1002/2017WR020969
   Isaak DJ, 2016, P NATL ACAD SCI USA, V113, P4374, DOI 10.1073/pnas.1522429113
   Isaak DJ, 2013, GLOBAL CHANGE BIOL, V19, P742, DOI 10.1111/gcb.12073
   Ishiyama N, 2018, CONSERV BIOL, V32, P1403, DOI 10.1111/cobi.13137
   Ishizaki NN, 2020, SOLA, V16, P80, DOI 10.2151/sola.2020-014
   Iwagami S, 2010, HYDROL PROCESS, V24, P2771, DOI 10.1002/hyp.7690
   Iwasaki K, 2021, WATER RESOUR RES, V57, DOI 10.1029/2021WR029641
   Japan Aerospace Exploration Agency, 2021, ALOS AVNIR 2 HIGH RE
   Jucker T, 2018, GLOBAL CHANGE BIOL, V24, P5243, DOI 10.1111/gcb.14415
   Kanno Y, 2014, RIVER RES APPL, V30, P745, DOI 10.1002/rra.2677
   Karger DN, 2017, SCI DATA, V4, DOI 10.1038/sdata.2017.122
   Kawai H, 2013, ECOL FRESHW FISH, V22, P645, DOI 10.1111/eff.12069
   Kawai T., 2005, Aquatic insects of Japan: manual with keys and illustrations
   Knudson C, 2018, NAT CLIM CHANGE, V8, P678, DOI 10.1038/s41558-018-0188-8
   Kurylyk BL, 2013, HYDROL EARTH SYST SC, V17, P2701, DOI 10.5194/hess-17-2701-2013
   Lusardi RA, 2021, WATER-SUI, V13, DOI 10.3390/w13121652
   Macek M, 2019, LANDSCAPE ECOL, V34, P2541, DOI 10.1007/s10980-019-00903-x
   Masson-Delmotte V, 2021, CLIMATE CHANGE 2021, DOI DOI 10.1017/9781009157896
   Matthews HD, 2022, SCIENCE, V376, P1404, DOI 10.1126/science.abo3378
   McDonnell TC, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0134757
   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
   Muñoz-Villers LE, 2012, WATER RESOUR RES, V48, DOI 10.1029/2011WR011316
   Musiake K, 1981, P JAPAN SOC CIVIL EN, V309, P51, DOI [10.2208/jscej1969.1981.309_51, DOI 10.2208/JSCEJ1969.1981.309_51]
   Nagasaka A, 1999, LANDSCAPE ECOL, V14, P543, DOI 10.1023/A:1008164123102
   Nakagawa S, 2017, J R SOC INTERFACE, V14, DOI 10.1098/rsif.2017.0213
   Nakagawa S, 2013, METHODS ECOL EVOL, V4, P133, DOI 10.1111/j.2041-210x.2012.00261.x
   Nakajima S, 2021, HEREDITY, V127, P413, DOI 10.1038/s41437-021-00468-z
   Nakamura F., 2022, GREEN INFRASTRUCTURE, P189, DOI [10.1007/978, DOI 10.1007/978-981-16-6791-6_12]
   Nakamura F, 2020, RIVER RES APPL, V36, P921, DOI 10.1002/rra.3576
   Natsumeda T, 2010, NIPPON SUISAN GAKK, V76, P169, DOI 10.2331/suisan.76.169
   Neter J., 1996, Applied linear statistical models, VFourth edition
   Ohno H., 2016, Climate in Biosphere, V16, P71, DOI [10.2480/cib.J-16-028, DOI 10.2480/CIB.J-16-028]
   Oksanen J, 2022, R package version 2.6-2, DOI DOI 10.4135/9781412971874.N145
   Onda Y, 2006, J HYDROL, V331, P659, DOI 10.1016/j.jhydrol.2006.06.009
   R Development Core Team, 2009, R: a language and environment for statistical computing
   Richardson CM, 2020, WATER RESOUR RES, V56, DOI 10.1029/2019WR026577
   Rodhouse TJ, 2017, ECOL EVOL, V7, P1514, DOI 10.1002/ece3.2763
   Sanderson BM, 2015, J CLIMATE, V28, P5171, DOI 10.1175/JCLI-D-14-00362.1
   SATO H, 1994, J GEOPHYS RES-SOL EA, V99, P22261, DOI 10.1029/94JB00854
   Scheffers BR, 2016, SCIENCE, V354, DOI 10.1126/science.aaf7671
   Schmidt-Kloiber A, 2015, ECOL INDIC, V53, P271, DOI 10.1016/j.ecolind.2015.02.007
   Schwalm CR, 2020, P NATL ACAD SCI USA, V117, P19656, DOI 10.1073/pnas.2007117117
   Selong JH, 2001, T AM FISH SOC, V130, P1026, DOI 10.1577/1548-8659(2001)130<1026:EOTOGA>2.0.CO;2
   SHIMIZU T, 1980, Bulletin for the Forestry and Forest Products Research Institute, P109
   Snyder CD, 2015, ECOL APPL, V25, P1397, DOI 10.1890/14-1354.1
   Suzuki H, 2022, WATER-SUI, V14, DOI 10.3390/w14142166
   Suzuki K, 2021, WATER-SUI, V13, DOI 10.3390/w13070975
   Tague C, 2004, WATER RESOUR RES, V40, DOI 10.1029/2003WR002629
   Tague C, 2007, HYDROL PROCESS, V21, P3288, DOI 10.1002/hyp.6538
   Takeshita N., 2017, J HIGH ENERGY PHYS, V65, P51
   Thomas CD, 2004, NATURE, V427, P145, DOI 10.1038/nature02121
   Vieira N.K., 2006, US Geological Survey Data Series, V187, P1, DOI DOI 10.3133/DS187
   Warren R, 2018, SCIENCE, V360, P791, DOI 10.1126/science.aar3646
   Wilkening JL, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0119327
   Yamada T, 2020, ZOOL SCI, V37, P429, DOI 10.2108/zs190149
   Yukimoto S, 2012, J METEOROL SOC JPN, V90A, P23, DOI 10.2151/jmsj.2012-A02
NR 91
TC 8
Z9 8
U1 6
U2 26
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0012-9615
EI 1557-7015
J9 ECOL MONOGR
JI Ecol. Monogr.
PD MAY
PY 2023
VL 93
IS 2
DI 10.1002/ecm.1566
EA MAR 2023
PG 20
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA E3PW1
UT WOS:000944099900001
DA 2025-01-10
ER

PT J
AU Hubner, V
   Böhm, C
   Eysel-Zahl, G
   Kudlich, W
   Kursten, E
   Lamersdorf, N
   Meixner, CA
   Morhart, C
   Peschel, T
   Tsonkova, P
   Wiesmeier, M
AF Hubner, Von Rico
   Boehm, Christian
   Eysel-Zahl, Georg
   Kudlich, Wolfram
   Kursten, Ernst
   Lamersdorf, Norbert
   Meixner, Christoph A.
   Morhart, Christopher
   Peschel, Tobias
   Tsonkova, Penka
   Wiesmeier, Martin
TI Carbon certification trough agroforestry?! Potential, accounting and
   recommendations
SO BERICHTE UBER LANDWIRTSCHAFT
LA German
DT Article
ID SOIL ORGANIC-CARBON; SEQUESTRATION; SYSTEMS; STOCKS; EMISSIONS; BIOMASS;
   METAANALYSIS; FOREST; SINKS
AB Agroforestry has long been appreciated for having a great potential for increasing and, above all, permanently storing carbon in the biomass and the soil. The Intergovernmental Panel on Climate Change (IPCC), the German Advisory Council on Global Change (WBGU), the European Commission and Parliament recognise agroforestry as a very suitable option in the fight against the climate crisis and in adaptation to its impacts. Of recent interest is financing such climate adaption with market-based instrument like climate- or carbon certificates. In light of the upcoming EU Carbon Farming-Directive, the Fit-for-55-debate as well as the revision of the CAP and LULUCF-mechanisms, there is an urgent need for some guidelines for climate certificates within agroforestry measures and which role these may play in the future.
   The carbon reduction potential and accounting principles in agroforestry outlined in this article cover four sectors - comparable to other land use-based strategies. 1) above-ground biomass, 2) belowground biomass, 3) the soil, and 4) the up- and downstream sector. The recommendations cover ten frequently discussed topics and concerns, namely 1) additionally, 2) quantifiability, 3) displacement effects, 4) contribution to food security, 5) additional emissions, 6) longevity and durability, 7) traceability, 8) transaction and opportunity costs, 9) synergies and compromises with other goals, and 10) security, trust and transparency.
   If the recommendations developed are taken into account, the authors conclude that the climate protecting and mitigation services of agroforestry in the form of carbon reduction potential can and should be rewarded by climate or carbon certificates. On the one hand, this could be seen as an innovative and promising way of financing future agroforestry systems; on the other hand, it must be ensured that the measures meet minimum scientific and social requirements. If planned scientifically sound, reliable, transparent and ethically just, there is a good chance to create with climate certificates for agroforestry some contributing solutions for EUs ambitious climate target plan, a 55 percent greenhouse gas reduction by 2030 compared to 1990.
C1 [Hubner, Von Rico] Tech Univ Munchen TUM, Lehrstuhl Strategie & Management Landschaftsentwi, Emil Ramann Str 6, D-85354 Freising Weihenstephan, Germany.
   [Boehm, Christian; Tsonkova, Penka] Brandenburg Tech Univ Cottbus Senftenberg BTU, Lehrstuhl Bodenschutz & Rekultivierung, Konrad Wachsmann Allee 6, D-03046 Cottbus, Germany.
   [Eysel-Zahl, Georg] VRD Stiftung Erneuerbare Energien, Heinrich Fuchs Str 94, D-69126 Heidelberg, Germany.
   [Kudlich, Wolfram] WALD21 GmbH, Friedrich Ebert Str 13, D-97215 Uffenheim, Germany.
   [Kursten, Ernst] 3N Dienstleistungen GmbH, Papenstucken 2, D-30455 Hannover, Germany.
   [Lamersdorf, Norbert] Georg August Univ Gottingen, Busgen Inst Okopedol Gemaigten Zonen, Busgenweg 2, D-37077 Gottingen, Germany.
   [Meixner, Christoph A.] Triebwerk Regenerat Land & Agroforstwirtschaft, Rothenbach 49, D-37290 Meissner, Germany.
   [Morhart, Christopher] Albert Ludwigs Univ Freiburg, Waldwachstum & Dendrookol, Tennenbacher Str 4, D-79106 Freiburg, Germany.
   [Peschel, Tobias] Lignovis GmbH, Tietzestr 29, D-22587 Hamburg, Germany.
   [Wiesmeier, Martin] Inst Agrarokol Okol Landbau & Bodenschutz IAB, Bayer Landesanstalt Landwirtschaft LfL, Emil Ramann Str 2, D-85354 Freising Weihenstephan, Germany.
C3 Technical University of Munich; University of Gottingen; University of
   Freiburg
RP Hubner, V (corresponding author), Tech Univ Munchen TUM, Lehrstuhl Strategie & Management Landschaftsentwi, Emil Ramann Str 6, D-85354 Freising Weihenstephan, Germany.
EM rico.huebner@tum.de; boehmc@btu.de; gez@vrd-stiftung.org;
   kudlich@wald21.com; ek@wood-report.de; nlamers@gwdg.de;
   christoph.meixner@relawi.org; Christopher.Morhart@iww.uni-freiburg.de;
   tobias.peschel@lignovis.com; penka.tsonkova@b-tu.de;
   martin.wiesmeier@lfl.bayern.de
RI Morhart, Christopher/F-6718-2014; Böhm, Christian/HDN-5925-2022;
   Wiesmeier, Martin/N-3066-2014
CR Aertsens J, 2013, LAND USE POLICY, V31, P584, DOI 10.1016/j.landusepol.2012.09.003
   Albrecht A, 2003, AGR ECOSYST ENVIRON, V99, P15, DOI 10.1016/S0167-8809(03)00138-5
   [Anonymous], 2007, CLIMATE CHANGE IMPAC
   [Anonymous], 2011, LEITFADEN AGROFORSTS
   [Anonymous], 2006, GUIDELINES NATL GREE, V2
   [Anonymous], 1939, HOLZ ALS ROHSTOFF
   Axe MS, 2017, AGR ECOSYST ENVIRON, V250, P81, DOI 10.1016/j.agee.2017.08.008
   Bambrick AD, 2010, AGROFOREST SYST, V79, P343, DOI 10.1007/s10457-010-9305-z
   Bindoff N. L., 2019, IPCC SPECIAL REPORT, P447
   Bohm C., 2020, AUFWERTEN LOSEBLATTS
   Bohm C., 2020, BAUME ALS BEREICHERU
   Bohm C., 2020, Konzept zur Forderung von Agroforstflachen als Agrarumweltund Klimamassnahme (AUKM) im Rahmen des Kulturlandschaftsprogramms (KULAP) des Landes Brandenburg
   Boinot S, 2019, AGR ECOSYST ENVIRON, V285, DOI 10.1016/j.agee.2019.106630
   Burger F, 2018, AGRARHOLZ SCHNELLWAC
   BURSCHEL P, 1993, ROLLE WALD FORSTWIRT
   Cardinael R, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aaeb5f
   Cardinael R, 2017, AGR ECOSYST ENVIRON, V236, P243, DOI 10.1016/j.agee.2016.12.011
   Cardinael R, 2015, PLANT SOIL, V391, P219, DOI 10.1007/s11104-015-2422-8
   Chatterjee N, 2018, AGR ECOSYST ENVIRON, V266, P55, DOI 10.1016/j.agee.2018.07.014
   COWI Ecologic Institute & IEEP, 2021, CLIMAC3ETU2018007 CO
   D'Hervilly C, 2021, PLANT SOIL, V463, P537, DOI 10.1007/s11104-021-04932-x
   De Stefano A, 2018, AGROFOREST SYST, V92, P285, DOI 10.1007/s10457-017-0147-9
   Dieter M, 2002, FORSTWISS CENTRALBL, V121, P195, DOI 10.1046/j.1439-0337.2002.02030.x
   Drexler S, 2021, REG ENVIRON CHANGE, V21, DOI 10.1007/s10113-021-01798-8
   European Commission-DG CLIMA, 2020, AGR WOOD LANDSC FEAT
   European Parliament, 2022, COM20210554C90320202
   Feliciano D, 2018, AGR ECOSYST ENVIRON, V254, P117, DOI 10.1016/j.agee.2017.11.032
   Fiege C, 2022, RUCKBAU KURZUMTRIEBS
   Germon A, 2016, PLANT SOIL, V401, P409, DOI 10.1007/s11104-015-2753-5
   Gholizadeh A, 2021, SOIL TILL RES, V211, DOI 10.1016/j.still.2021.105017
   Gold Standard Foundation (, 2021, US
   Grote R, 2003, FORSTWISS CENTRALBL, V122, P287, DOI 10.1007/s10342-003-0006-2
   Gunther D, 2021, BERICHTERSTATTUNG UN
   Hackenberg J, 2014, FORESTS, V5, P1069, DOI 10.3390/f5051069
   Hartmann T, 2011, INVESTIEREN WALDKLIM
   Hawken P., 2018, Drawdown: the most comprehensive plan ever proposed to reverse global warming
   Hellebrand HJ, 2008, ATMOS ENVIRON, V42, P8403, DOI 10.1016/j.atmosenv.2008.08.006
   Hubner R, 2021, WALD AUFS FELD HOLEN
   Hubner R., 2021, AUFWERTEN LOSEBLATTS
   Hübner R, 2021, AGR ECOSYST ENVIRON, V315, DOI 10.1016/j.agee.2021.107437
   Jacobs A, 2020, LANDBAUFORSCHUNG-GER, V70, P31, DOI 10.3220/LBF1605778405000
   Kaeser A, 2010, ART BERICHT, P736
   Kanzler M, 2021, AGROECOL SUST FOOD, V45, P868, DOI 10.1080/21683565.2021.1871697
   Kay S, 2019, LAND USE POLICY, V83, P581, DOI 10.1016/j.landusepol.2019.02.025
   Kern J, 2018, AGRARHOLZ SCHNELLWAC
   Kim DG, 2016, AGR ECOSYST ENVIRON, V226, P65, DOI 10.1016/j.agee.2016.04.011
   Klemmt H.-J., 2011, LWF AKTUELL, V81, P25
   Kramer H., 1982, LEITFADEN DENDROMETR
   Kuhne S., 2018, HECKEN RAINE AGRARLA
   KURSTEN E, 1993, WATER AIR SOIL POLL, V70, P533, DOI 10.1007/BF01105020
   Lehmann LM, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12135429
   Leifeld J, 2019, AGRARFORSCH SCHWEIZ+, V10, P346
   Lorenz K, 2014, AGRON SUSTAIN DEV, V34, P443, DOI 10.1007/s13593-014-0212-y
   Ma ZL, 2020, GLOBAL ECOL BIOGEOGR, V29, P1817, DOI 10.1111/geb.13145
   Mayer S, 2022, AGR ECOSYST ENVIRON, V323, DOI 10.1016/j.agee.2021.107689
   Mcdonald H.., 2021, Carbon Farming Making Agriculture Fit for 2030 Policy Department for Economic, Scientific and Quality of Life Policies Directorate-General for Internal Policies
   Millar N., 2013, Quantifying N2O emissions reductions in US agricultural crops through N fertilizer rate reduction
   Mokany K, 2006, GLOBAL CHANGE BIOL, V12, P84, DOI 10.1111/j.1365-2486.2005.001043.x
   Montagnini F, 2004, AGROFOREST SYST, V61-2, P281, DOI 10.1023/B:AGFO.0000029005.92691.79
   Nabuurs GJ, 2017, FOREST POLICY ECON, V75, P120, DOI 10.1016/j.forpol.2016.10.009
   Nair P. K. R., 2012, AGROFORESTRY THE FUT
   Nair PKR, 2009, J PLANT NUTR SOIL SC, V172, P10, DOI 10.1002/jpln.200800030
   Nyssens C., 2021, Carbon farming for climate, nature, and farmers: Policy recommendations
   Offenthaler I. V. O., 2006, Centralblatt fur das gesamte Forstwesen, V123, P65
   Powlson DS, 2011, EUR J SOIL SCI, V62, P42, DOI 10.1111/j.1365-2389.2010.01342.x
   Pretzsch H., 2019, GRUNDLAGEN WALDWACHS
   Reyes F, 2021, AGRICULTURE-BASEL, V11, DOI 10.3390/agriculture11040356
   Roedl A, 2010, INT J LIFE CYCLE ASS, V15, P567, DOI 10.1007/s11367-010-0195-0
   Rohle H., 2010, AGROWOOD KURZUMTRIEB
   Ruter S., 2016, CLIM WOOD 2030 CLIMA
   Ruter S., 2017, BEITRAG STOFFLICHEN
   Sathre R, 2010, ENVIRON SCI POLICY, V13, P104, DOI 10.1016/j.envsci.2009.12.005
   Schlamadinger B, 1996, BIOMASS BIOENERG, V10, P275, DOI 10.1016/0961-9534(95)00113-1
   Schoeneberger MM, 2009, AGROFOREST SYST, V75, P27, DOI 10.1007/s10457-008-9123-8
   Seserman DM, 2019, AGRICULTURE-BASEL, V9, DOI 10.3390/agriculture9070147
   Shi LL, 2018, LAND DEGRAD DEV, V29, P3886, DOI 10.1002/ldr.3136
   Stavi I, 2013, AGRON SUSTAIN DEV, V33, P81, DOI 10.1007/s13593-012-0081-1
   Torralba M, 2016, AGR ECOSYST ENVIRON, V230, P150, DOI 10.1016/j.agee.2016.06.002
   Tsonkova P, 2019, AGROFORESTRY STRENGT
   Twistel G, 2000, ERFASSUNG POTENZIALS
   WBAE, 2019, EFF GEST AGR KLIM RA
   WBGU, 2020, Landwende im Anthropozan: Von der Konkurrenz zur Integration
   Weisser D, 2007, ENERGY, V32, P1543, DOI 10.1016/j.energy.2007.01.008
   Wiesmeier M., 2021, ARBEITSFELD PFLANZEN
   Wiesmeier M., 2020, CO2 CERTIFICATES CAR, DOI 10.20387/bonares-ne0g-ce98
   Wiesmeier M, BONARES SERIES
   Wiesmeier M, 2020, GEODERMA, V369, DOI 10.1016/j.geoderma.2020.114333
   Wiesmeier M, 2015, SCI TOTAL ENVIRON, V536, P1045, DOI 10.1016/j.scitotenv.2015.07.064
   Wiesmeier M, 2014, GLOBAL CHANGE BIOL, V20, P653, DOI 10.1111/gcb.12384
   Wilhelm Eckehard-G., 2015, Naturschutz und Landschaftsplanung, V47, P37
   Wolters S., 2018, FREIWILLIGE CO2 KOMP
   Zepp S, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13163141
   Zukunftskommission Landwirtschaft, 2021, Zukunft Landwirtschaft. Eine gesamtgesellschaftliche Aufgabe
NR 93
TC 0
Z9 0
U1 0
U2 22
PU BUNDESMINISTERIUM ERNAHRUNG LANDWIRTSCHAFT
PI BPMM
PA DEICHMANNS AUE 29, BPMM, 53179, GERMANY
SN 2196-5099
J9 BER LANDWIRTSCH
JI Ber. Landwirtsch.
PD AUG
PY 2022
VL 100
IS 2
PG 34
WC Agriculture, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA 3T9VA
UT WOS:000840617800001
DA 2025-01-10
ER

PT J
AU Venter, ZS
   Krog, NH
   Barton, DN
AF Venter, Zander S.
   Krog, Norun Hjertager
   Barton, David N.
TI Linking green infrastructure to urban heat and human health risk
   mitigation in Oslo, Norway
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Ecosystem services; Landsat; Surface temperature; Heat-associated
   illness; Remote sensing
ID LAND-SURFACE TEMPERATURE; AIR-TEMPERATURE; VEGETATION INDEX;
   PUBLIC-HEALTH; ISLAND; MORTALITY; CLIMATE; IMPROVEMENT; RESOLUTION;
   RETRIEVAL
AB The predicted extreme temperatures of globalwarming aremagnified in cities due to the urban heat island effect. Even if the target for average temperature increase in the Paris Climate Agreement is met, temperatures during the hottest month in a northern city like Oslo are predicted to rise by over 5 degrees C by 2050. We hypothesised that heat-related diagnoses for heat-sensitive citizens (75+) in Oslo are correlated to monthly air temperatures, and that green infrastructure such as tree canopy cover reduces extreme land surface temperatures and thus reduces health risk from heat exposure. Monthly air temperatures were significantly correlated to the number of skin-related diagnoses at the city level, but were unrelated to diagnoses under circulatory, nervous system, or general categories. Satellite-derived spatially-explicit measures revealed that on one of the hottest days during the summer of 2018, landscape units composed of paved, midrise or lowrise buildings gave off the most heat (39 degrees C), whereas units composed of complete tree canopy cover, ormixed (i.e. tree and grass) vegetation maintained temperatures of between 29 and 32 degrees C. Land surface temperatureswere negatively correlated to tree canopy cover (R-2= 0.45) and vegetation greenness (R-2= 0.41). In a scenario inwhich each city tree was replaced by the most common non-tree cover in its neighbourhood, the area of Oslo exceeding a 30 degrees C health risk threshold during the summerwould increase from 23 to 29%. Combining modelling results with population at risk at census tract level, we estimated that each tree in the city currently mitigates additional heat exposure of one heatsensitive person by one day. Our results indicate that maintaining and restoring tree cover provides an ecosystem service of urban heat reduction. Our findings have particular relevance for health benefit estimation in urban ecosystem accounting and municipal policy decisions regarding ecosystem-based climate adaptation. (C) 2019 The Authors. Published by Elsevier B.V.
C1 [Venter, Zander S.; Barton, David N.] Norwegian Inst Nat Res NINA, Terr Ecol Sect, N-0349 Oslo, Norway.
   [Krog, Norun Hjertager] NIPH, Div Infect Control & Environm Hlth, Sect Air Pollut & Noise, POB 222, N-0213 Oslo, Norway.
C3 Norwegian Institute Nature Research; Norwegian Institute of Public
   Health (NIPH)
RP Venter, ZS (corresponding author), Norwegian Inst Nat Res NINA, Terr Ecol Sect, N-0349 Oslo, Norway.
EM alexander.venter@nina.no
RI Krog, Norun Hjertager/HJA-5692-2022; Barton, David/KGM-8862-2024
OI Venter, Zander/0000-0003-2638-7162
FU URBAN EEA project - Experimental Ecosystem Accounting for Greater Oslo
   (URBAN EEA); MILJOFORSK programme; Research Council of Norway [255156]
FX The researchwas carried outwith support of the URBAN EEA project -
   Experimental Ecosystem Accounting for Greater Oslo (URBAN EEA),
   MILJOFORSK programme, The Research Council of Norway, contract #255156.
   Thank you to Megan Nowell for generating the training dataset for the
   land cover classification.
CR Akbari H., 2005, Energy Saving Potentials and Air Quality Benefits of Urban Heat IslandMitigation
   Akbari H, 2012, ENERG BUILDINGS, V55, P2, DOI 10.1016/j.enbuild.2012.02.055
   Ali I, 2016, J PLANT ECOL, V9, P649, DOI 10.1093/jpe/rtw005
   Aminipouri M, 2019, BUILD ENVIRON, V158, P226, DOI 10.1016/j.buildenv.2019.05.022
   [Anonymous], POP DIV UN
   [Anonymous], 2006, 86 AMS ANN M
   [Anonymous], 2013, GREEN INFR ENH EUR N
   [Anonymous], ECOL EC
   [Anonymous], POP STAT ANN EST FIG
   [Anonymous], 2013, WORLD POP AG 2013
   [Anonymous], GEOGR B
   [Anonymous], 2001, Machine Learning
   [Anonymous], 2017, STAT
   [Anonymous], REPORT EUROPEAN ENV
   [Anonymous], LOV NATUROMRADER OSL
   Astrom DO, 2020, SCAND J PUBLIC HEALT, V48, P428, DOI 10.1177/1403494818801615
   Bastin JF, 2019, PLOS ONE, V14, DOI 10.1371/journal.pone.0217592
   Bates D., 2014, arXiv Prepr. arXiv1406.5823
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   Bunker A, 2016, EBIOMEDICINE, V6, P258, DOI 10.1016/j.ebiom.2016.02.034
   Cadenasso ML, 2007, FRONT ECOL ENVIRON, V5, P80, DOI 10.1890/1540-9295(2007)5[80:SHIUER]2.0.CO;2
   Carlsen HK, 2019, INT J ENV RES PUB HE, V16, DOI 10.3390/ijerph16020286
   Carrasco L, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11030288
   Chand P. K., 2008, Regional Health Forum, V12, P43
   Chapman L, 2017, INT J CLIMATOL, V37, P3597, DOI 10.1002/joc.4940
   Cohen P, 2012, BUILD ENVIRON, V51, P285, DOI 10.1016/j.buildenv.2011.11.020
   Coronel AS, 2015, AIMS ENVIRON SCI, V2, P803, DOI 10.3934/environsci.2015.3.803
   Crum SM, 2017, J ENVIRON MANAGE, V200, P295, DOI 10.1016/j.jenvman.2017.05.077
   D'Amato G, 2013, MULTIDISCIP RESP MED, V8, DOI 10.1186/2049-6958-8-12
   Dhakal KP, 2017, J ENVIRON MANAGE, V203, P171, DOI 10.1016/j.jenvman.2017.07.065
   Escobedo FJ, 2019, URBAN FOR URBAN GREE, V37, P3, DOI 10.1016/j.ufug.2018.02.011
   Fang YJ, 1997, REMOTE SENS ENVIRON, V59, P407, DOI 10.1016/S0034-4257(96)00163-0
   Feyisa GL, 2014, LANDSCAPE URBAN PLAN, V123, P87, DOI 10.1016/j.landurbplan.2013.12.008
   Gago EJ, 2013, RENEW SUST ENERG REV, V25, P749, DOI 10.1016/j.rser.2013.05.057
   Gascon M, 2016, ENVIRON INT, V86, P60, DOI 10.1016/j.envint.2015.10.013
   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
   Hall-Spencer JM, 2008, NATURE, V454, P96, DOI 10.1038/nature07051
   Hamstead ZA, 2016, ECOL INDIC, V70, P574, DOI 10.1016/j.ecolind.2015.10.014
   Hanssen F., 2019, MAPPING URBAN TREE C
   Harlan SL, 2013, ENVIRON HEALTH PERSP, V121, P197, DOI 10.1289/ehp.1104625
   Harrison XA, 2018, PEERJ, V6, DOI 10.7717/peerj.4794
   Hidalgo I, 2019, J MED FOOD, V22, P567, DOI 10.1089/jmf.2018.0210
   Hoshiko S, 2010, INT J PUBLIC HEALTH, V55, P133, DOI 10.1007/s00038-009-0060-8
   HUETE AR, 1988, REMOTE SENS ENVIRON, V25, P295, DOI 10.1016/0034-4257(88)90106-X
   Hyyppä J, 2008, INT J REMOTE SENS, V29, P1339, DOI 10.1080/01431160701736489
   Jenerette GD, 2018, LANDSCAPE ECOL, V33, P1655, DOI 10.1007/s10980-018-0708-y
   Jiang ZY, 2008, REMOTE SENS ENVIRON, V112, P3833, DOI 10.1016/j.rse.2008.06.006
   Jiménez-Muñoz JC, 2009, IEEE T GEOSCI REMOTE, V47, P339, DOI 10.1109/TGRS.2008.2007125
   Johnson Helen, 2005, Health Stat Q, P6
   Kalnay E, 1996, B AM METEOROL SOC, V77, P437, DOI 10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2
   Karlessi T, 2009, SOL ENERGY, V83, P538, DOI 10.1016/j.solener.2008.10.005
   Kestens Y, 2011, INT J HEALTH GEOGR, V10, DOI 10.1186/1476-072X-10-7
   Kotzeva Mariana., 2016, Urban Europe. Statistics on cities
   Kovats RS, 2006, EUR J PUBLIC HEALTH, V16, P592, DOI 10.1093/eurpub/ckl049
   Kownacki KL, 2019, INT J ENV RES PUB HE, V16, DOI 10.3390/ijerph16040560
   Laaidi K, 2012, ENVIRON HEALTH PERSP, V120, P254, DOI 10.1289/ehp.1103532
   Lee JS, 2014, INDOOR BUILT ENVIRON, V23, P62, DOI 10.1177/1420326X12474483
   Lin S, 2012, ENVIRON HEALTH PERSP, V120, P1571, DOI 10.1289/ehp.1104728
   Liu H, 2012, REMOTE SENS ENVIRON, V117, P57, DOI 10.1016/j.rse.2011.06.023
   Luther M, 2016, INT J ENV RES PUB HE, V13, DOI 10.3390/ijerph13080753
   Marando F, 2019, ECOL MODEL, V392, P92, DOI 10.1016/j.ecolmodel.2018.11.011
   McCarthy MP, 2010, GEOPHYS RES LETT, V37, DOI 10.1029/2010GL042845
   Michelogiannakis G, 2011, INT SYMP MICROARCH, P83
   Mirzaei PA, 2015, SUSTAIN CITIES SOC, V19, P200, DOI 10.1016/j.scs.2015.04.001
   Morabito M, 2018, REMOTE SENS-BASEL, V10, DOI 10.3390/rs10010026
   Nyelele C, 2019, URBAN FOR URBAN GREE, V42, P10, DOI 10.1016/j.ufug.2019.04.018
   OKE TR, 1982, Q J ROY METEOR SOC, V108, P1, DOI 10.1002/qj.49710845502
   Ossola A, 2018, SCI TOTAL ENVIRON, V612, P940, DOI 10.1016/j.scitotenv.2017.08.103
   Peng SJ, 2019, ECOL INDIC, V96, P127, DOI 10.1016/j.ecolind.2018.08.059
   Phelan PE, 2015, ANNU REV ENV RESOUR, V40, P285, DOI 10.1146/annurev-environ-102014-021155
   Pichierri M, 2012, REMOTE SENS ENVIRON, V127, P130, DOI 10.1016/j.rse.2012.08.025
   Pirard P, 2005, Euro Surveill, V10, P153
   Public Health England, 2018, HEATW PLAN ENGL
   Rahman MA, 2017, BUILD ENVIRON, V114, P118, DOI 10.1016/j.buildenv.2016.12.013
   Rong F., 2006, Impact Of "urban sprawl" On U. S. Residential Energy Use"
   Rosenthal JK, 2014, HEALTH PLACE, V30, P45, DOI 10.1016/j.healthplace.2014.07.014
   Roy S, 2012, URBAN FOR URBAN GREE, V11, P351, DOI 10.1016/j.ufug.2012.06.006
   Schwarz N, 2012, ECOL INDIC, V18, P693, DOI 10.1016/j.ecolind.2012.01.001
   Shahmohamadi P, 2011, PROCEDIA ENGINEER, V20, DOI 10.1016/j.proeng.2011.11.139
   Sheng L, 2017, ECOL INDIC, V72, P738, DOI 10.1016/j.ecolind.2016.09.009
   Shiflett SA, 2017, SCI TOTAL ENVIRON, V579, P495, DOI 10.1016/j.scitotenv.2016.11.069
   Sobrino JA, 2004, REMOTE SENS ENVIRON, V90, P434, DOI 10.1016/j.rse.2004.02.003
   Suárez JC, 2005, COMPUT GEOSCI-UK, V31, P253, DOI 10.1016/j.cageo.2004.09.015
   Takebayashi H, 2007, BUILD ENVIRON, V42, P2971, DOI 10.1016/j.buildenv.2006.06.017
   Tan K, 2017, FRONT EARTH SCI-PRC, V11, P20, DOI 10.1007/s11707-016-0570-7
   TUCKER CJ, 1979, REMOTE SENS ENVIRON, V8, P127, DOI 10.1016/0034-4257(79)90013-0
   UN, 2017, SEEA EXP EC ACC TECH
   Vyberci D, 2018, THEOR APPL CLIMATOL, V133, P925, DOI 10.1007/s00704-017-2224-4
   Weng QH, 2014, REMOTE SENS ENVIRON, V145, P55, DOI 10.1016/j.rse.2014.02.003
   World Population Review, 2020, World population review. minimum wage by country 2020
   Xu H, 2008, INT J REMOTE SENS, V29, P4269, DOI 10.1080/01431160802039957
   Zardo L, 2017, ECOSYST SERV, V26, P225, DOI 10.1016/j.ecoser.2017.06.016
   Zhang YJ, 2017, LANDSCAPE URBAN PLAN, V165, P162, DOI 10.1016/j.landurbplan.2017.04.009
   Zhu Z, 2015, REMOTE SENS ENVIRON, V159, P269, DOI 10.1016/j.rse.2014.12.014
   Ziter CD, 2019, P NATL ACAD SCI USA, V116, P7575, DOI 10.1073/pnas.1817561116
NR 96
TC 106
Z9 110
U1 13
U2 127
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 20
PY 2020
VL 709
AR 136193
DI 10.1016/j.scitotenv.2019.136193
PG 10
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA KJ8BS
UT WOS:000512281700116
PM 31887497
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Suska-Malawska, M
   Kot, M
   Grezak, A
   Metrak, M
   Khudjanazarov, M
   Szymczak, K
AF Suska-Malawska, Malgorzata
   Kot, Malgorzata
   Grezak, Anna
   Metrak, Monika
   Khudjanazarov, Mukhiddin
   Szymczak, Karol
TI Potential impact of Holocene climate changes on camel breeding practices
   of Neolithic pastoralists in the Central Asian drylands: A preliminary
   assessment
SO HOLOCENE
LA English
DT Article
DE paleoclimate; arid regions; fatty acids; stable isotopes; camel
   domestication; Central Asia
ID ARID CENTRAL-ASIA; CENTRAL TIAN-SHAN; FATTY-ACID; MULTI-PROXY;
   KYRGYZSTAN; PALEOLIMNOLOGY; BACTRIANUS; XINJIANG; RECORDS; MILK
AB Archaeological findings from the Neolithic open-air location Ayakagytma 'The Site', situated in the south-eastern part of the Kyzyl-kum Desert in Uzbekistan, can potentially shed new light on the camel domestication process in the Central Asian drylands and help to connect it to regional changes of paleoclimate. Detailed analyses of composition and C-13 isotopic ratios of fatty acids performed on potsherds from an archaeological horizon of a Keltaminar culture dated at 3000-4000 cal BC combined with analogical analyses of modern camel and horse milk samples from Uzbekistan indicated a plausible possibility that camels were kept and milked by stockbreeders of Ayakagytma during this time period. The observed herding practices based almost exclusively on camel husbandry, as opposed to earlier more balanced herds of cattle, horses and camels, were probably an adaptation to climate transition from relatively humid to relatively dry, and the following changes in vegetation. Such climatic shift did not correspond with the general trend of Holocene moisture changes over the Westerlies-dominated Central Asia. However, it was in accordance with wet-to-dry climate transitions recorded in sediments of several lakes in the same region at around 4000 cal BP. The observed changes in Neolithic stockbreeding practices, as other inconsistencies in Holocene moisture evolution over a massive area of arid Central Asia, may have resulted from local manifestations of globally-forced climate changes and/or from local hydrographic alterations unrelated to paleoclimate.
C1 [Suska-Malawska, Malgorzata; Metrak, Monika] Univ Warsaw, Fac Biol, Biol & Chem Res Ctr, Zwirki & Wigury 101, PL-02089 Warsaw, Poland.
   [Suska-Malawska, Malgorzata] Tottori Univ, Int Platform Dryland Res & Educ, Tottori, Japan.
   [Kot, Malgorzata; Grezak, Anna; Szymczak, Karol] Univ Warsaw, Inst Archaeol, Warsaw, Poland.
   [Khudjanazarov, Mukhiddin] Uzbek Acad Sci, Inst Archaeol Res, Tashkent, Uzbekistan.
C3 University of Warsaw; Tottori University; University of Warsaw; Academy
   of Sciences of Uzbekistan; Institute of Archaeological Studies Named
   After Y. Gulyamov
RP Metrak, M (corresponding author), Univ Warsaw, Fac Biol, Biol & Chem Res Ctr, Zwirki & Wigury 101, PL-02089 Warsaw, Poland.
EM m.metrak@uw.edu.pl
RI Mętrak, Monika/HMO-6034-2023; Suska-Malawska, Małgorzata/AAT-9188-2021;
   Kot, Malgorzata/E-7540-2013
OI Metrak, Monika/0000-0002-6069-6041; Suska-Malawska,
   Malgorzata/0000-0002-5400-9508; Kot, Malgorzata/0000-0001-5277-0283
FU Polish National Science Centre [2017/25/B/HS3/00520]; Polish State
   Committee for Scientific Research [1HO1G01112 -Gr/795, 2HO1H03622
   -Gr/1681]; Faculty of Biology, University of Warsaw
   [501-D114-01-1140900]
FX The author(s) disclosed receipt of the following financial support for
   the research, authorship and/or publication of this article: This study
   was supported by the Polish National Science Centre (Grant No
   2017/25/B/HS3/00520). The field and laboratory research in Ayakagytma
   `The Site' was financed by the Polish State Committee for Scientific
   Research (Grant Nos 1HO1G01112 -Gr/795 and 2HO1H03622 -Gr/1681). Lipid
   analyses were financed by the statutory research of the Faculty of
   Biology, University of Warsaw (501-D114-01-1140900).
CR Barnard H, 2007, J ARCHAEOL SCI, V34, P28, DOI 10.1016/j.jas.2006.03.010
   Bocherens H, 2006, J ARCHAEOL SCI, V33, P253, DOI 10.1016/j.jas.2005.07.010
   Boomer I, 2000, QUATERNARY SCI REV, V19, P1259, DOI 10.1016/S0277-3791(00)00002-0
   B┬u├ek┬u├enyi S., 2000, ARCHAEOZOOLOGY NEAR, Vvol.32, P116
   Burger PA, 2019, ANIM GENET, V50, P598, DOI 10.1111/age.12858
   Chen FH, 2008, QUATERNARY SCI REV, V27, P351, DOI 10.1016/j.quascirev.2007.10.017
   Chen FH, 2016, QUATERNARY SCI REV, V146, P134, DOI 10.1016/j.quascirev.2016.06.002
   Cheng H, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2011GL050202
   Compagnoni B., 1978, APPROACHES FAUNAL AN, Vvol.2, P91
   Copley MS, 2003, P NATL ACAD SCI USA, V100, P1524, DOI 10.1073/pnas.0335955100
   Doreau M, 2006, EAAP PUBLIC, P77
   Dunne J, 2012, NATURE, V486, P390, DOI 10.1038/nature11186
   Endo K., 2012, WORKSH P SUST SOC CE, P77
   Evershed RP, 2008, WORLD ARCHAEOL, V40, P26, DOI 10.1080/00438240801889373
   Ferronskii V.I., 2003, WATER RESOUR, V30, P252, DOI DOI 10.1023/A:1023826011601
   Gintzburger G., 2003, Rangelands of the arid and semi-arid zones in Uzbekistan
   Gregg MW, 2009, J ARCHAEOL SCI, V36, P937, DOI 10.1016/j.jas.2008.09.009
   Grillo KM, 2020, P NATL ACAD SCI USA, V117, P9793, DOI 10.1073/pnas.1920309117
   Harris David., 2010, ORIGINS AGR W CENTRA, DOI [10.9783/9781934536513.53, DOI 10.9783/9781934536513]
   Hendy J, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-06335-6
   Hoch E., 1979, South Asian archaeology 1977, P589
   Huang XT, 2014, QUATERNARY SCI REV, V103, P134, DOI 10.1016/j.quascirev.2014.09.012
   Jiang QF, 2007, CHINESE SCI BULL, V52, P1970, DOI 10.1007/S11434-007-0245-6
   Johansson KSL, 2016, LIMNOL OCEANOGR, V61, P1563, DOI 10.1002/lno.10296
   Kang SG, 2020, QUATERNARY SCI REV, V246, DOI 10.1016/j.quascirev.2020.106553
   Kapustina LA, 2000, US FOR SERV RMRS-P, P98
   Khujanazarov M., 2014, INNOVATIONS SUSTAINA, P65
   Kohl P.L., 1992, CHRONOLOGIES OLD WOR, P179
   Konuspayeva G, 2008, DAIRY SCI TECHNOL, V88, P327, DOI 10.1051/dst:2008005
   Kottek M, 2006, METEOROL Z, V15, P259, DOI 10.1127/0941-2948/2006/0130
   Kuzmina, 2015, PREHISTORY SILK ROAD
   Lan JH, 2021, EARTH-SCI REV, V217, DOI 10.1016/j.earscirev.2021.103645
   Lasota-Moskalewska A., 2012, RICERCHE ATTIVITA CO, P23
   Lasota-Moskalewska A., 2009, HORSE MAN EUROPEAN A, P14
   Lauterbach S, 2014, HOLOCENE, V24, P970, DOI 10.1177/0959683614534741
   Liu SZ, 2015, SCI REP-UK, V5, DOI 10.1038/srep08001
   Miller ARV, 2020, SCI TECHNOL ARCHAEOL, V6, P41, DOI 10.1080/20548923.2020.1759316
   Orlando L, 2016, P NATL ACAD SCI USA, V113, P6588, DOI 10.1073/pnas.1606340113
   Outram AK, 2011, ANTIQUITY, V85, P116, DOI 10.1017/S0003598X00067478
   Outram AK, 2009, SCIENCE, V323, P1332, DOI 10.1126/science.1168594
   Patalano R., 2020, CURRENT PROTOCOLS PL, V5
   Peters J, 1997, J ZOOL, V242, P651, DOI 10.1111/j.1469-7998.1997.tb05819.x
   Pumpelly Raphael., 1908, EXPLORATIONS TURKEST, VI.
   Ran M, 2014, ORG GEOCHEM, V73, P47, DOI 10.1016/j.orggeochem.2014.05.006
   Rasmussen KA., 2001, PAGES NEWS, V9, P5, DOI [DOI 10.22498/PAGES.9.2.5, 10.22498/pages.9.2.5]
   Regert M, 2011, MASS SPECTROM REV, V30, P177, DOI 10.1002/mas.20271
   Ricketts RD, 2001, PALAEOGEOGR PALAEOCL, V176, P207, DOI 10.1016/S0031-0182(01)00339-X
   Roffet-Salque M, 2017, ARCHAEOL ANTHROP SCI, V9, P1343, DOI 10.1007/s12520-016-0357-5
   Rudenko, 2015, BASELINE SURVEY KARA
   Sachse D, 2004, GEOCHIM COSMOCHIM AC, V68, P4877, DOI 10.1016/j.gca.2004.06.004
   Sala Renato., 2017, Journal of Arid Land Studies Special Reports: Camel Husbandry in Central Asia, V26, P205, DOI DOI 10.14976/JALS.26.4_205
   Salvatori Sandro., 2005, South Asian Archaeology 2001, P281
   Sarianidi W., 2005, GONURDEPE TURKMENIST, P321
   Schwarz A, 2017, QUATERNARY SCI REV, V177, P340, DOI 10.1016/j.quascirev.2017.10.009
   Steinhilber F, 2009, GEOPHYS RES LETT, V36, DOI 10.1029/2009GL040142
   Szymczak, 2011, WIATOWIT, V8, P9
   Szymczak K., 2009, BLISKO DALEKO KSI GA, P89
   Szymczak K., 2006, SITEOTHER COLLECTION, V11
   Tan LC, 2021, SCI BULL, V66, P603, DOI 10.1016/j.scib.2020.10.011
   Trinks Alexandra, 2012, P79
   Uerpmann Margarethe, 2012, P109
   Wang W, 2013, QUATERN INT, V311, P54, DOI 10.1016/j.quaint.2013.07.034
   Warinner C, 2014, SCI REP-UK, V4, DOI 10.1038/srep07104
   Wilkin S, 2020, NAT ECOL EVOL, V4, P346, DOI 10.1038/s41559-020-1120-y
   Wolff C, 2017, HOLOCENE, V27, P142, DOI 10.1177/0959683616652711
   Xu H, 2019, GEOLOGY, V47, P255, DOI 10.1130/G45686.1
   Zhang DL, 2020, SCI TOTAL ENVIRON, V735, DOI 10.1016/j.scitotenv.2020.139545
   Zorya S., 2019, Farm Restructuring in Uzbekistan: How Did It Go and What Is Next?
NR 68
TC 1
Z9 1
U1 1
U2 14
PU SAGE PUBLICATIONS LTD
PI LONDON
PA 1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND
SN 0959-6836
EI 1477-0911
J9 HOLOCENE
JI Holocene
PD NOV
PY 2022
VL 32
IS 11
BP 1132
EP 1143
DI 10.1177/09596836221114289
EA JUL 2022
PG 12
WC Geography, Physical; Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Physical Geography; Geology
GA 4U8UL
UT WOS:000832732800001
OA hybrid
DA 2025-01-10
ER

PT J
AU Gubler, S
   Rossa, A
   Avalos, G
   Brönnimann, S
   Cristobal, K
   Croci-Maspoli, M
   Dapozzo, M
   van der Elst, A
   Escajadillo, Y
   Flubacher, M
   Garcia, T
   Imfeld, N
   Konzelmann, T
   Lechthaler, F
   Liniger, M
   Quevedo, K
   Ramos, H
   Rohrer, M
   Schwierz, C
   Sedlmeier, K
   Spirig, C
   de Ventura, S
   Wüthrich, B
AF Gubler, Stefanie
   Rossa, Andrea
   Avalos, Grinia
   Bronnimann, Stefan
   Cristobal, Katy
   Croci-Maspoli, Mischa
   Dapozzo, Marlene
   van der Elst, Andrea
   Escajadillo, Yury
   Flubacher, Moritz
   Garcia, Teresa
   Imfeld, Noemi
   Konzelmann, Thomas
   Lechthaler, Filippo
   Liniger, Mark
   Quevedo, Karim
   Ramos, Hugo
   Rohrer, Mario
   Schwierz, Cornelia
   Sedlmeier, Katrin
   Spirig, Christoph
   de Ventura, Sara
   Wuthrich, Brigitte
TI Twinning SENAMHI and MeteoSwiss to co-develop climate services for the
   agricultural sector in Peru
SO CLIMATE SERVICES
LA English
DT Article
DE Climate services; Twinning; Global Framework for Climate Services;
   SENAMHI Peru
ID IMPACT; PRECIPITATION; SEAS5
AB The development and dissemination of weather and climate information is crucial to improve people's resilience and adaptability to climate variability and change. The impacts of climate variability and change are generally stronger for disadvantaged population groups due to their limited adaptive and coping capacities. For instance, smallholder farmers living in remote areas such as the southern Peruvian Andes suffer strongly from adverse weather and climatic events such as droughts or frost. The project Climandes aimed at providing high-quality climate services in support of the agricultural sector in southern Peru by implementing the guidelines of the Global Framework for Climate Services (GFCS).
   In Climandes, a two-fold challenge was tackled: the co-development of climate services by building up a continuous dialogue between the information provider (in this case the Peruvian national meteorological and hydrological service (NMHS)) and potential users; and the production of climate services through international cooperation. To this end, the NMHSs of Peru (SENAMHI) and Switzerland (MeteoSwiss) worked closely together to tackle issues ranging from the treatment of climate data to ensure the provision of reliable information to establishing continuous interaction with different user groups. In this paper, we postulate that this approach of close collaboration, the so-called twinning of the two NMHSs, was key for the projects' success and contributed to strengthening the Peruvian NMHS institutionally and procedurally. This project overview guides its reader through the approach, main achievements, and conclusions regarding successes and challenges of the project, and reflects on some potential improvements for future initiatives.
C1 [Gubler, Stefanie; Rossa, Andrea; Croci-Maspoli, Mischa; van der Elst, Andrea; Flubacher, Moritz; Imfeld, Noemi; Konzelmann, Thomas; Liniger, Mark; Schwierz, Cornelia; Sedlmeier, Katrin; Spirig, Christoph; de Ventura, Sara] Fed Off Meteorol & Climatol MeteoSwiss, Zurich, Switzerland.
   [Avalos, Grinia; Cristobal, Katy; Dapozzo, Marlene; Escajadillo, Yury; Garcia, Teresa; Quevedo, Karim; Ramos, Hugo] SENAMHI, Serv Nacl Meteorol & Hidrol Peru, Lima, Peru.
   [Bronnimann, Stefan; Imfeld, Noemi] Univ Bern, Oeschger Ctr Climate Changes Res, Bern, Switzerland.
   [Bronnimann, Stefan; Imfeld, Noemi] Univ Bern, Inst Geog, Bern, Switzerland.
   [Lechthaler, Filippo] Bern Univ Appl Sci, Sch Agr Forest & Food Sci, Zollikofen, Switzerland.
   [Lechthaler, Filippo] Swiss Trop & Publ Hlth Inst, Basel, Switzerland.
   [Lechthaler, Filippo] Swiss Fed Inst Technol, Zurich, Switzerland.
   [Ramos, Hugo] Univ Nacl Agr La Molina, Lima, Peru.
   [Rohrer, Mario] Meteodat GmbH, Zurich, Switzerland.
   [Sedlmeier, Katrin] Deutsch Wetterdienst, Munich, Germany.
   [Wuthrich, Brigitte] Jurg Sauter GmbH Partner, Schaffhausen, Switzerland.
C3 Federal Office of Meteorology & Climatology (MeteoSwiss); Servicio
   Nacional de Meteorologia Hidrologia del Peru (SENAMHI); University of
   Bern; University of Bern; University of Basel; Swiss Tropical & Public
   Health Institute; Swiss Federal Institutes of Technology Domain; ETH
   Zurich; Universidad Nacional Agraria La Molina
RP Gubler, S (corresponding author), Fed Off Meteorol & Climatol MeteoSwiss, Zurich, Switzerland.
RI Brönnimann, Stefan/A-5737-2008; Spirig, Christoph/D-2471-2014; Liniger,
   Mark/K-7757-2013
OI Escajadillo, Yury/0000-0002-9536-213X; Quevedo,
   Karim/0000-0003-0419-2962; Ramos Inca Roca, Hugo
   Oswaldo/0000-0002-8592-8208; Sedlmeier, Katrin/0000-0002-0400-5517;
   Bronnimann, Stefan/0000-0001-9502-7991; Croci-Maspoli,
   Mischa/0009-0002-3946-1210; Avalos Roldan, Grinia
   Jesus/0000-0002-6163-5806
FU World Meteorological Organization (WMO) [7F-08453.01]
FX We thank two anonymous reviewers for very constructive comments that
   helped shape the content of this publication. Further, we acknowledge
   the continuous support by Guillermo Podesta. Then, we thank the World
   Meteorological Organization (WMO) for their support of the project
   Servicios Climaticos con ' enfasis en los Andes en apoyo a las
   Decisiones (Climandes), project no. 7F-08453.01 between the Swiss Agency
   for Development and Cooperation (SDC) and the WMO.
CR [Anonymous], 2018, GLOBAL WARMING 15 C
   [Anonymous], **DATA OBJECT**, DOI DOI 10.7916/D8668DCW
   [Anonymous], 2011, CLIM KNOWL ACT GLOB
   [Anonymous], 2014, Climate change 2014: synthesis report
   Aybar C, 2020, HYDROLOG SCI J, V65, P770, DOI 10.1080/02626667.2019.1649411
   Baigorria G, 2019, USO INFORM METEOROLO
   Barros VR, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1133
   Carr ER, 2018, CLIM RISK MANAG, V22, P82, DOI 10.1016/j.crm.2017.03.002
   Doblas-Reyes FJ, 2006, GEOPHYS RES LETT, V33, DOI 10.1029/2005GL025061
   Domínguez-Castro F, 2018, INT J CLIMATOL, V38, P5459, DOI 10.1002/joc.5739
   Garcia T, 2020, IMPLEMENTING BLENDED
   Gerlak A. K., 2017, MIDTERM REV GLOBAL F
   Gray B., 2013, Sustainability through partnerships: Capitalizing on collaboration
   Gubler S, 2020, WEATHER FORECAST, V35, P561, DOI 10.1175/WAF-D-19-0106.1
   Huerta A, 2018, PISCO TEMPERATURE V1
   Imfeld N, 2021, INT J CLIMATOL, V41, P679, DOI 10.1002/joc.6645
   Imfeld N, 2019, INT J CLIMATOL, V39, P4497, DOI 10.1002/joc.6087
   Johnson SJ, 2019, GEOSCI MODEL DEV, V12, P1087, DOI 10.5194/gmd-12-1087-2019
   Karl TR, 1999, CLIMATIC CHANGE, V42, P3, DOI 10.1023/A:1005491526870
   LeClerc J, 2015, RISK ANAL, V35, P385, DOI 10.1111/risa.12336
   Lewicki RoyJ., 2003, MAKING SENSE INTRACT
   MeteoSwiss / SENAMHI, 2018, DES US DRIV CLIM SER
   MINAM, 2010, PER CAMB CLIM 2 COM
   MINAM, 2015, ESTR NAC ANT CAMB CL
   Minvielle M, 2011, J CLIMATE, V24, P4577, DOI 10.1175/JCLI-D-11-00051.1
   Molteni F., 2011, ECMWF Technical Memoranda
   Neukom R, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/8/084017
   Peterson T.C., 2001, REPORT ACTIVITIES WO
   Pezo D., 2019, Intervenciones y tecnologias ambientalmente racionales (TAR) para la adaptacion al cambio climatico del sector agropecuario de America Latina y el Caribe
   Rabatel A, 2013, CRYOSPHERE, V7, P81, DOI 10.5194/tc-7-81-2013
   Ramírez IJ, 2017, INT J DISAST RISK SC, V8, P489, DOI 10.1007/s13753-017-0151-8
   Rodríguez-Morata C, 2019, CLIM DYNAM, V52, P5605, DOI 10.1007/s00382-018-4466-y
   Rosas G., 2016, Climate Services, V4, P30, DOI 10.1016/j.cliser.2016.10.001
   Rossa A, 2020, HDB CLIMATE SERVICES
   Roulston MS, 2004, WEATHER FORECAST, V19, P391, DOI 10.1175/1520-0434(2004)019<0391:TBWCWR>2.0.CO;2
   Salzmann N, 2013, CRYOSPHERE, V7, P103, DOI 10.5194/tc-7-103-2013
   Schleussner CF, 2016, EARTH SYST DYNAM, V7, P327, DOI 10.5194/esd-7-327-2016
   UNFCCC, 2017, CLIM ACT NOW SUMM PO
   UNFCCC, 2015, C PART AD PAR AGR, P1
   UNFCCC, 2012, National Adaptation Plans. Technical Guidelines for the National Adaptation Plan Process
   UNISDR, 2015, SENDAI FRAMEWORK DIS
   United Nations, 2015, No.A/RES/70/1.
   Vargas P., 2009, El cambio climatico y sus efectos en el Peru
   WEF, 2018, WEF GLOB RISK REP 20, V13th
   WMO, 2017, WMO INT GLOB OBS SYS
   WMO, 2013, WMO SPECIAL B, P62
   Worldbank, 2014, PPCR TECHN WORKSH EN
   Ziervogel G, 2005, AGR SYST, V83, P1, DOI 10.1016/j.agsy.2004.02.009
NR 48
TC 3
Z9 3
U1 2
U2 10
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2405-8807
J9 CLIM SERV
JI Clim. Serv.
PD DEC
PY 2020
VL 20
AR 100195
DI 10.1016/j.cliser.2020.100195
PG 13
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 PH1SK
UT WOS:000600201200003
OA Green Published, gold, Green Accepted
DA 2025-01-10
ER

PT J
AU Klemm, T
   McPherson, RA
AF Klemm, Toni
   McPherson, Renee A.
TI Assessing Decision Timing and Seasonal Climate Forecast Needs of Winter
   Wheat Producers in the South-Central United States
SO JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY
LA English
DT Article
DE Social Science; North America; Seasonal forecasting; Agriculture;
   Communications; decision making
ID OKLAHOMA MESONET; PREDICTION; INFORMATION; WEATHER; PRECIPITATION;
   AGRICULTURE; TEMPERATURE; MANAGEMENT; SUPPORT; FARMERS
AB Agricultural decision-making that adapts to climate variability is essential to global food security. Crop production can be severely impacted by drought, flood, and heat, as seen in recent years in parts of the United States. Seasonal climate forecasts can help producers reduce crop losses, but many nationwide, publicly available seasonal forecasts currently lack relevance for agricultural producers, in part because they do not reflect their decision needs. This study examines the seasonal forecast needs of winter wheat producers in the southern Great Plains to understand what climate information is most useful and what lead times are most relevant for decision-making. An online survey of 119 agricultural advisers, cooperative extension agents in Oklahoma, Kansas, Texas, and Colorado, was conducted and gave insights into producers' preferences for forecast elements, what weather and climate extremes have the most impact on decision-making, and the decision timing of major farm practices. The survey participants indicated that winter wheat growers were interested not only in directly modeled variables, such as total monthly rainfall, but also in derived elements, such as consecutive number of dry days. Moreover, these agricultural advisers perceived that winter wheat producers needed seasonal climate forecasts to have a lead time of 0-2.5 monthsthe planning lead time for major farm practices, like planting or harvesting. A forecast calendar and monthly rankings for forecast elements were created that can guide forecasters and advisers as they develop decision tools for winter wheat producers and that can serve as a template for other time-sensitive decision tools developed for stakeholder communities.
C1 [Klemm, Toni] Univ Oklahoma, Dept Geog & Environm Sustainabil, Norman, OK 73019 USA.
   South Cent Climate Adaptat Sci Ctr, Norman, OK USA.
C3 University of Oklahoma System; University of Oklahoma - Norman
RP Klemm, T (corresponding author), Univ Oklahoma, Dept Geog & Environm Sustainabil, Norman, OK 73019 USA.
EM toni-klemm@tamu.edu
RI Klemm, Toni/GVS-2040-2022; McPherson, Renee/H-6256-2016
OI McPherson, Renee/0000-0002-1497-9681
FU Oklahoma EPSCoR project through the Oklahoma State Regents for Higher
   Education; National Science Foundation under NSF [OIA-1301789];
   University of Oklahoma (OU)
FX We thank the USDA Cooperative Extension Services of Texas, Oklahoma,
   Kansas, and Colorado, and the state climatologist of Texas for
   participating in this survey and for their invaluable help pretesting
   and distributing it. Thanks also to Drs. Mike Langston and Jean Steiner
   for connecting us to the extension community and to Al Sutherland and
   Gary McManus for their feedback on early versions of the survey. We also
   thank Drs. Derek Rosendahl, Duncan Wilson, Elinor Martin, Esther
   Mullens, Jason Slemons, Joe Ripberger, and Travis Gliedt, as well as
   Benjamin Ignac and Braden Owsley for their help with our analysis and
   visualization. Finally, we thank three anonymous reviewers for their
   excellent comments and suggestions, which made this a much stronger
   paper. This work was funded by the Oklahoma EPSCoR project through the
   Oklahoma State Regents for Higher Education and the National Science
   Foundation under NSF Grant OIA-1301789, with additional support from the
   Office of the Vice President for Research of the University of Oklahoma
   (OU) through the South Central Climate Adaptation Science Center and the
   Dean of the College of Atmospheric and Geographic Sciences through the
   OU Department of Geography and Environmental Sustainability.
CR [Anonymous], 2014, Internet, phone, mail, and mixed-mode surveys: The tailored design method, DOI DOI 10.1002/9781394260645
   [Anonymous], 2014, BASICS SOCIAL RES
   BALMASEDA MA, 1995, J CLIMATE, V8, P2705, DOI 10.1175/1520-0442(1995)008<2705:DASDOE>2.0.CO;2
   BARNSTON AG, 1994, B AM METEOROL SOC, V75, P2097, DOI 10.1175/1520-0477(1994)075<2097:LLSFDW>2.0.CO;2
   Beraki AF, 2014, J CLIMATE, V27, P1719, DOI 10.1175/JCLI-D-13-00275.1
   Bonhomme R, 2000, EUR J AGRON, V13, P1, DOI 10.1016/S1161-0301(00)00058-7
   Borgers N, 2004, QUAL QUANT, V38, P17, DOI 10.1023/B:QUQU.0000013236.29205.a6
   Cabrera V. E., 2006, 06001 SE CLIM CONS
   Cabrera VE, 2007, AGR SYST, V93, P25, DOI 10.1016/j.agsy.2006.04.005
   Carberry P, 2000, ATMOS OCEAN SCI LIB, V21, P167
   Changnon SA, 2004, WEATHER FORECAST, V19, P606, DOI 10.1175/1520-0434(2004)019<0606:CUOCPI>2.0.CO;2
   Changnon SA, 1988, J CLIMATE, V1, P757, DOI 10.1175/1520-0442(1988)001<0757:ACIUIA>2.0.CO;2
   Crane TA, 2010, WEATHER CLIM SOC, V2, P44, DOI 10.1175/2009WCAS1006.1
   Frisvold GB, 2013, WEATHER CLIM SOC, V5, P55, DOI 10.1175/WCAS-D-12-00022.1
   Haigh T, 2015, CLIM RISK MANAG, V7, P20, DOI 10.1016/j.crm.2015.01.004
   Han WG, 2012, COMPUT ELECTRON AGR, V84, P111, DOI 10.1016/j.compag.2012.03.005
   Hunger B., 2012, CR7088 OKL STAT U
   Jia LW, 2016, J CLIMATE, V29, P4121, DOI 10.1175/JCLI-D-15-0471.1
   Jia LW, 2015, J CLIMATE, V28, P2044, DOI 10.1175/JCLI-D-14-00112.1
   Jones JW, 2000, AGR ECOSYST ENVIRON, V82, P169, DOI 10.1016/S0167-8809(00)00225-5
   Kirtman BP, 2014, B AM METEOROL SOC, V95, P585, DOI 10.1175/BAMS-D-12-00050.1
   Klemm T, 2017, AGR FOREST METEOROL, V232, P384, DOI 10.1016/j.agrformet.2016.09.005
   Klockow KE, 2010, WEATHER CLIM SOC, V2, P224, DOI 10.1175/2010WCAS1034.1
   Lau KM, 2002, GEOPHYS RES LETT, V29, DOI 10.1029/2001GL014263
   Mavi H. S., 2004, AGROMETEOROLOGY PRIN
   McCrea R, 2005, INT J CLIMATOL, V25, P1127, DOI 10.1002/joc.1164
   McPherson RA, 2007, J ATMOS OCEAN TECH, V24, P301, DOI 10.1175/JTECH1976.1
   Meinke H, 2005, CLIMATIC CHANGE, V70, P221, DOI 10.1007/s10584-005-5948-6
   Meinke H., 2003, CAN CLIMATE KNOWLEDG
   NADEAU R, 1995, PUBLIC OPIN QUART, V59, P323, DOI 10.1086/269480
   National Agricultural Statistics Service, 2018, 2016 WINT WHEAT PROD
   Nulty DD, 2008, ASSESS EVAL HIGH EDU, V33, P301, DOI 10.1080/02602930701293231
   O'Lenic EA, 2008, WEATHER FORECAST, V23, P496, DOI 10.1175/2007WAF2007042.1
   Peairs F., 2010, Wheat Production and Pest Management for the Great Plains Region
   Prokopy LS, 2013, WEATHER CLIM SOC, V5, P162, DOI 10.1175/WCAS-D-12-00036.1
   RASINSKI KA, 1989, PUBLIC OPIN QUART, V53, P388, DOI 10.1086/269158
   ROPELEWSKI CF, 1986, MON WEATHER REV, V114, P2352, DOI 10.1175/1520-0493(1986)114<2352:NAPATP>2.0.CO;2
   Saha S, 2014, J CLIMATE, V27, P2185, DOI 10.1175/JCLI-D-12-00823.1
   Schneider JM, 2009, J SOIL WATER CONSERV, V64, p100A, DOI 10.2489/jswc.64.3.100A
   Sherman-Morris K., 2005, Environ Hazards, V6, P201, DOI [10.1016/j.hazards.2006.10.002, DOI 10.1016/J.HAZARDS.2006.10.002]
   Shroyer J.P., 1997, Wheat Production Handbook
   SONKA ST, 1992, B AM METEOROL SOC, V73, P1999, DOI 10.1175/1520-0477(1992)073<1999:HAUCPI>2.0.CO;2
   Takle ES, 2014, EARTH INTERACT, V18, DOI 10.1175/2013EI000541.1
   Templeton SR, 2014, REG ENVIRON CHANGE, V14, P645, DOI 10.1007/s10113-013-0522-7
   U.S. Department of Agriculture, 2012, AC12A51 USDA
   USDA, 2018, FED CROP INS CORP SU
   van den Dool H.M., 1994, P 19 ANN CLIM DIAGN, P405
   Vecchi GA, 2014, J CLIMATE, V27, P7994, DOI 10.1175/JCLI-D-14-00158.1
   Warnecke RB, 1997, ANN EPIDEMIOL, V7, P334, DOI 10.1016/S1047-2797(97)00030-6
   Wen CH, 2012, J CLIMATE, V25, P5689, DOI 10.1175/JCLI-D-11-00556.1
   WMO, 2015, GLOB PROD CTR LONG R
NR 51
TC 10
Z9 11
U1 1
U2 26
PU AMER METEOROLOGICAL SOC
PI BOSTON
PA 45 BEACON ST, BOSTON, MA 02108-3693 USA
SN 1558-8424
EI 1558-8432
J9 J APPL METEOROL CLIM
JI J. Appl. Meteorol. Climatol.
PD SEP
PY 2018
VL 57
IS 9
BP 2129
EP 2140
DI 10.1175/JAMC-D-17-0246.1
PG 12
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Meteorology & Atmospheric Sciences
GA GT1IM
UT WOS:000444222600001
OA Bronze
DA 2025-01-10
ER

PT J
AU Liu, CC
   He, NP
   Zhang, JH
   Li, Y
   Wang, QF
   Sack, L
   Yu, GR
AF Liu, Congcong
   He, Nianpeng
   Zhang, Jiahui
   Li, Ying
   Wang, Qiufeng
   Sack, Lawren
   Yu, Guirui
TI Variation of stomatal traits from cold temperate to tropical forests and
   association with water use efficiency
SO FUNCTIONAL ECOLOGY
LA English
DT Article
DE community; phylogeny; plant functional group; stomata; water use
   efficiency
ID LATITUDINAL VARIATION; LEAF PHYSIOLOGY; CANOPY POSITION; DENSITY; PLANT;
   CO2; MORPHOLOGY; DIVERSITY; ANATOMY; LEAVES
AB Stomata control carbon and water vapour exchange between leaves and the atmosphere, thus it can influence water use efficiency (WUE) and reflect plant adaptation to climate. However, the spatial patterns of leaf stomatal traits and relationships between stomatal trait and WUE across natural communities remain unclear. We measured stomatal density, stomatal size and stomatal area fraction for 737 plant species from nine forests ranging from tropical to cold temperate forests. Stomatal density, stomatal size and stomatal area fraction were all log-normally distributed, and different across species, plant functional groups (trees, shrubs, and herbs), and communities. At the regional scale, variation in stomatal traits was primarily related to species, followed by climate and soil types. The community-weighted mean of stomatal size increased linearly with latitude, whereas those of stomatal density and stomatal area fraction showed humpbacked relationship. The community-weighted mean of stomatal area fraction was correlated with climatic aridity, consistent with the adaptation strategies of plant species to achieve high maximum rates of gas exchange in arid regions when water is available. Further, community-weighted mean of stomatal area fraction was positively correlated with WUE in natural forest communities, indicating that plants have lower stomatal conductance in order to adapt greater aridity conditions. These findings highlight the strong associations of stomatal traits with plant functional group and climate at a regional scale, representing the adaptation strategies of stomatal traits across natural forest communities to climate.
   A is available for this article.
C1 [Liu, Congcong; He, Nianpeng; Zhang, Jiahui; Li, Ying; Wang, Qiufeng; Yu, Guirui] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing, Peoples R China.
   [Liu, Congcong; He, Nianpeng; Wang, Qiufeng; Yu, Guirui] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China.
   [He, Nianpeng] Northeast Normal Univ, Inst Grassland Sci, Changchun, Jilin, Peoples R China.
   [He, Nianpeng] Minist Educ, Key Lab Vegetat Ecol, Changchun, Jilin, Peoples R China.
   [Sack, Lawren] Univ Southern Calif, Dept Ecol & Evolutionary Biol, Los Angeles, CA USA.
C3 Chinese Academy of Sciences; Institute of Geographic Sciences & Natural
   Resources Research, CAS; Chinese Academy of Sciences; University of
   Chinese Academy of Sciences, CAS; Northeast Normal University - China;
   University of Southern California
RP He, NP (corresponding author), Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing, Peoples R China.; He, NP (corresponding author), Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China.
EM henp@igsnrr.ac.cn
RI wang, qiufeng/C-1654-2013; Zhang, Jiahui/GPT-1640-2022; Yu,
   Guirui/C-1768-2014; Sack, Lawren/A-5492-2008
OI Yu, Guirui/0000-0002-1859-8966; he, nianpeng/0000-0002-0458-5953; Liu,
   Congcong/0000-0003-3949-4194; Sack, Lawren/0000-0002-7009-7202
FU National Key R&D Program of China [2016YFC0500202]; National Natural
   Science Foundation of China [31290221, 41571130043]; STS of Chinese
   Academy of Sciences [KFJ-SW-STS-167]; Youth Innovation Research Team
   Project [LENOM2016Q0005]
FX National Key R&D Program of China, Grant/Award Number: 2016YFC0500202;
   National Natural Science Foundation of China, Grant/Award Number:
   31290221 and 41571130043; STS of Chinese Academy of Sciences,
   Grant/Award Number: KFJ-SW-STS-167; Youth Innovation Research Team
   Project, Grant/Award Number: LENOM2016Q0005;
CR Al Afas N, 2007, ANN FOREST SCI, V64, P521, DOI 10.1051/forest:2007029
   BEERLING DJ, 1993, ANN BOT-LONDON, V71, P431, DOI 10.1006/anbo.1993.1056
   Boyer J.S., 1995, WATER RELATIONS PLAN
   Carins Murphy MR, 2014, PLANT CELL ENVIRON, V37, P124, DOI 10.1111/pce.12136
   Casson SA, 2010, CURR OPIN PLANT BIOL, V13, P90, DOI 10.1016/j.pbi.2009.08.005
   Choat B, 2007, NEW PHYTOL, V175, P686, DOI 10.1111/j.1469-8137.2007.02137.x
   Cornelissen JHC, 2003, J VEG SCI, V14, P311, DOI 10.1111/j.1654-1103.2003.tb02157.x
   De Martonne E, 1926, Bulletin de lAssociation de Gographes Franais, V9, P3, DOI DOI 10.3406/BAGF.1926.6321
   Engineer CB, 2014, NATURE, V513, P246, DOI 10.1038/nature13452
   Franks PJ, 2015, NEW PHYTOL, V207, P188, DOI 10.1111/nph.13347
   Franks PJ, 2009, PLANT CELL ENVIRON, V32, P1737, DOI [10.1111/j.1365-3040.2009.002031.x, 10.1111/j.1365-3040.2009.02031.x]
   Franks PJ, 2009, P NATL ACAD SCI USA, V106, P10343, DOI 10.1073/pnas.0904209106
   Fraser LH, 2009, ANN BOT-LONDON, V103, P769, DOI 10.1093/aob/mcn252
   Garnier E, 2012, AGRON SUSTAIN DEV, V32, P365, DOI 10.1007/s13593-011-0036-y
   Grime JP, 1998, J ECOL, V86, P902, DOI 10.1046/j.1365-2745.1998.00306.x
   Grubb Peter J., 1998, Perspectives in Plant Ecology Evolution and Systematics, V1, P3, DOI 10.1078/1433-8319-00049
   Haworth M, 2011, J EXP BOT, V62, P2419, DOI 10.1093/jxb/err086
   Hetherington AM, 2003, NATURE, V424, P901, DOI 10.1038/nature01843
   Hultine KR, 2000, OECOLOGIA, V123, P32, DOI 10.1007/s004420050986
   Lavorel S, 2012, J ECOL, V100, P128, DOI 10.1111/j.1365-2745.2011.01914.x
   Lawson T, 1998, J EXP BOT, V49, P1397, DOI 10.1093/jexbot/49.325.1397
   Liu C, 2017, DRYAD DIGITAL REPOSI
   Luo JX, 2006, FOREST ECOL MANAG, V221, P285, DOI 10.1016/j.foreco.2005.10.004
   Luomala EM, 2005, PLANT CELL ENVIRON, V28, P733, DOI 10.1111/j.1365-3040.2005.01319.x
   Maximov N.A., 1931, SCIENCE, V73, P422
   McElwain JC, 2016, NEW PHYTOL, V209, P94, DOI 10.1111/nph.13579
   OBERBAUER SF, 1986, AM J BOT, V73, P409, DOI 10.2307/2444084
   Reddy KR, 1998, ENVIRON EXP BOT, V39, P117, DOI 10.1016/S0098-8472(97)00028-2
   Reichstein M, 2014, P NATL ACAD SCI USA, V111, P13697, DOI 10.1073/pnas.1216065111
   Sack L, 2003, PLANT CELL ENVIRON, V26, P1343, DOI 10.1046/j.0016-8025.2003.01058.x
   Sack L, 2016, PLANT PHYSIOL, V171, P2358, DOI 10.1104/pp.16.00476
   Salisbury EJ, 1928, PHILOS T R SOC LON B, V216, P1, DOI 10.1098/rstb.1928.0001
   Scoffoni C, 2015, NEW PHYTOL, V207, P43, DOI 10.1111/nph.13346
   Taylor SH, 2012, NEW PHYTOL, V193, P387, DOI 10.1111/j.1469-8137.2011.03935.x
   Wang RL, 2016, J GEOGR SCI, V26, P15, DOI 10.1007/s11442-016-1251-x
   Wang RL, 2015, SCI REP-UK, V5, DOI 10.1038/srep14454
   Wright IJ, 2001, FUNCT ECOL, V15, P423, DOI 10.1046/j.0269-8463.2001.00542.x
   Xu Z, 2008, J EXP BOT, V59, P3317, DOI 10.1093/jxb/ern185
   Yu GR, 2008, NEW PHYTOL, V177, P927, DOI 10.1111/j.1469-8137.2007.02316.x
   Zhao N, 2016, GLOBAL ECOL BIOGEOGR, V25, P359, DOI 10.1111/geb.12427
NR 40
TC 107
Z9 134
U1 19
U2 208
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0269-8463
EI 1365-2435
J9 FUNCT ECOL
JI Funct. Ecol.
PD JAN
PY 2018
VL 32
IS 1
SI SI
BP 20
EP 28
DI 10.1111/1365-2435.12973
PG 9
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA FS0WN
UT WOS:000419494600003
OA Bronze
DA 2025-01-10
ER

PT J
AU Wang, J
   Wang, Y
   Wang, SJ
AF Wang, Jun
   Wang, Yang
   Wang, Shiji
TI Biophysical and socioeconomic drivers of the dynamics in snow hazard
   impacts across scales and over heterogeneous landscape in Northern Tibet
SO NATURAL HAZARDS
LA English
DT Article
DE Snow hazard impacts; Drivers; Statistical modeling; Herder communities;
   Northern Tibet
ID PANEL-DATA; ADAPTIVE CAPACITY; CLIMATE-CHANGE; ADAPTATION;
   VULNERABILITY; LIVELIHOODS; FRAMEWORK
AB Understanding the dynamics of snow hazard impacts on the Tibetan Plateau is significant and prerequisite for decision making in mitigating the negative impacts of snow hazards and facilitating social adaptation to climate variability and change. In this study, we adopted the framework of vulnerability analysis to analyze the drivers of the dynamics in snow hazard impacts indicated by livestock mortality rate in Northern Tibet. We selected Nagqu Prefecture, a remote pastoral area of Northern Tibet, as the case study area to analyze the drivers of the dynamics in snow hazard impacts between 1982 and 2010. We applied panel data models and geographically weighted regressions to diagnose the drivers of the dynamics in snow hazard impacts across two administrative scales and over heterogeneous landscape in Nagqu Prefecture. The results showed that the contributions of biophysical and socioeconomic factors to explaining the annual dynamics of livestock mortality rate varied between Nagqu Prefecture scale and Nagqu County scale. The modeling results using geographically weighted regressions showed that the statistical relationships between livestock mortality rate and various explanatory variables varied across geographic space due to spatial heterogeneity of local grassland social-ecological systems. Insights gained through this study help to improve our understanding of the drivers of snow hazard impacts across different administrative scales and over heterogeneous landscape in Northern Tibet. The findings of this study also have important implications for snow hazard management and building adaptive capacity for future climate change in the pastoral areas of Northern Tibet.
C1 [Wang, Jun] Peking Univ, Shenzhen Grad Sch, Key Lab Human & Environm Sci & Technol, Shenzhen 518055, Peoples R China.
   [Wang, Yang] China Meteorol Adm, Natl Climate Ctr, Beijing 100081, Peoples R China.
   [Wang, Shiji] Chinese Acad Sci, Cold & Arid Regions Environm & Engn Res Inst, State Key Lab Cryospher Sci, Lanzhou 730000, Gansu, Peoples R China.
C3 Peking University; China Meteorological Administration; Chinese Academy
   of Sciences; Cold & Arid Regions Environmental & Engineering Research
   Institute, CAS
RP Wang, Y (corresponding author), China Meteorol Adm, Natl Climate Ctr, Beijing 100081, Peoples R China.
EM wangy8610@gmail.com
FU National Science Foundation of China [41401215]; State Key Laboratory of
   Cryospheric Sciences, Cold and Arid Regions Environment and Engineering
   Research Institute, China [SKLCS-OP-2014-10]; Laboratory for Climate
   Studies Open Funds for Young Scholars, China
FX This work was conducted with financial support from National Science
   Foundation of China (41401215), the State Key Laboratory of Cryospheric
   Sciences, Cold and Arid Regions Environment and Engineering Research
   Institute, China (SKLCS-OP-2014-10), and Laboratory for Climate Studies
   Open Funds for Young Scholars, China (2015).
CR Adger WN, 2006, GLOBAL ENVIRON CHANG, V16, P268, DOI 10.1016/j.gloenvcha.2006.02.006
   [Anonymous], 1991, NOMADIC PEOPLES
   [Anonymous], ERDKUNDE, DOI DOI 10.3112/ERD
   Armstrong RL., 2005, Global monthly EASE-Grid snow water equivalent climatology
   Brooks N, 2005, GLOBAL ENVIRON CHANG, V15, P151, DOI 10.1016/j.gloenvcha.2004.12.006
   Brunsdon C, 1996, GEOGR ANAL, V28, P281, DOI 10.1111/j.1538-4632.1996.tb00936.x
   Carpenter S, 2001, ECOSYSTEMS, V4, P765, DOI 10.1007/s10021-001-0045-9
   Elhorst J.P., 2010, Handbook of Applied Spatial Analysis: Software Tools, Methods and Applications, P377
   Elhorst J.P., 2010, 4 WORLD C SPAT EC AS
   Elhorst JP, 2003, INT REGIONAL SCI REV, V26, P244, DOI 10.1177/0160017603253791
   Fernández-Giménez ME, 2012, GLOBAL ENVIRON CHANG, V22, P836, DOI 10.1016/j.gloenvcha.2012.07.001
   Filed C, 2012, MANAGING RISKS EXTRE
   Folke C, 2006, GLOBAL ENVIRON CHANG, V16, P253, DOI 10.1016/j.gloenvcha.2006.04.002
   Frees E. W., 2004, LONGITUDINAL PANEL D
   Fu Y, 2012, ENVIRON MANAGE, V50, P607, DOI 10.1007/s00267-012-9918-2
   [高懋芳 GAO Maofang], 2011, [干旱区资源与环境, Journal of Arid Land Resources and Environment], V25, P101
   Goldstein M, 2012, PASTORAL PRACTICES H, P257
   Holling CS, 2001, ECOSYSTEMS, V4, P390, DOI 10.1007/s10021-001-0101-5
   Hsiao C., 2003, Analysis of panel data, V2nd, DOI [10.1017/CBO9780511754203, DOI 10.1017/CBO9780511754203]
   Kreutzmann Hermann, 2011, PASTORALISM RANGELAN
   Lee LF, 2010, ECONOMET THEOR, V26, P564, DOI 10.1017/S0266466609100099
   Liu XD, 2000, INT J CLIMATOL, V20, P1729, DOI 10.1002/1097-0088(20001130)20:14<1729::AID-JOC556>3.0.CO;2-Y
   Long R, 2011, PASTORALISM RANGELAN, P239
   McDowell JZ, 2012, GLOBAL ENVIRON CHANG, V22, P342, DOI 10.1016/j.gloenvcha.2011.11.002
   Morss RE, 2011, ANNU REV ENV RESOUR, V36, P1, DOI 10.1146/annurev-environ-060809-100145
   Smit B, 2006, GLOBAL ENVIRON CHANG, V16, P282, DOI 10.1016/j.gloenvcha.2006.03.008
   Smith B, 2000, CLIMATIC CHANGE, V45, P223, DOI 10.1023/A:1005661622966
   Stow D, 2003, INT J REMOTE SENS, V24, P1111, DOI 10.1080/0143116021000020144
   Turner BL, 2003, P NATL ACAD SCI USA, V100, P8074, DOI 10.1073/pnas.1231335100
   Waldron S, 2010, CHINA AGR ECON REV, V2, P298, DOI 10.1108/17561371011078435
   Wang J, 2013, GLOBAL ENVIRON CHANG, V23, P1673, DOI 10.1016/j.gloenvcha.2013.08.014
   Wang W, 2013, NAT HAZARD EARTH SYS, V13, P1411, DOI 10.5194/nhess-13-1411-2013
   Wang Y, 2014, ECOL SOC, V19, DOI 10.5751/ES-06803-190408
   Yeh ET, 2014, HUM ECOL, V42, P61, DOI 10.1007/s10745-013-9625-5
   Yu JH, 2008, J ECONOMETRICS, V146, P118, DOI 10.1016/j.jeconom.2008.08.002
NR 35
TC 11
Z9 12
U1 0
U2 36
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 2016
VL 81
IS 3
BP 1499
EP 1514
DI 10.1007/s11069-015-2142-7
PG 16
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 DG7TC
UT WOS:000372285600006
DA 2025-01-10
ER

PT J
AU Motsholapheko, MR
   Kgathi, DL
   Vanderpost, C
AF Motsholapheko, M. R.
   Kgathi, D. L.
   Vanderpost, C.
TI An assessment of adaptation planning for flood variability in the
   Okavango Delta, Botswana
SO MITIGATION AND ADAPTATION STRATEGIES FOR GLOBAL CHANGE
LA English
DT Article
DE Adaptation planning; Flood variability; Institutions; Livelihoods
ID HOUSEHOLD ADAPTATION; RURAL LIVELIHOODS; LAKE NGAMI; DESICCATION;
   MANAGEMENT; DROUGHT
AB In the Okavango Delta, Botswana, household adaptation to climatic variability hinges upon access to wetland resources. Household adaptation may be effective for current flood variability, but inadequate for future climate variability. Government interventions through adaptation planning for flood variability may also be inadequate. This study aimed to improve knowledge on adaptation planning in the Okavango Delta and similar areas in the world. The specific objectives were to determine household exposure, adaptive capacity and sensitivity to flood-related shocks, identify and assess government interventions for flood variability, and determine the effect of these interventions on household adaptation to flood variability in the Okavango Delta. Informed by the institutional analysis and development framework, the study used data from a survey of 623 households in five villages, some qualitative methods and secondary data sources. The results indicate that households are inherently sensitive to shocks, due to their dependence on natural resource-based livelihood activities, and that most households had sick members (53 %), and were food insecure (74 %). More households were more affected by river desiccation (84 %) than by flooding (23 %). Adaptation planning was implicitly undertaken in the form of disaster risk reduction, and mainstream development and poverty reduction programmes. These effectively contributed to household adaptation to flood variability but inhibited local institutional learning and innovation. Moreover, they were neither participatory nor conformant to local norms and therefore not sustainable in the long term. There is a need to adopt explicit, flexible and participatory approaches to planning to promote autonomous adaptation to flood variability in the Okavango Delta.
C1 [Motsholapheko, M. R.; Kgathi, D. L.; Vanderpost, C.] Univ Botswana, Okavango Res Inst, Maun, Botswana.
C3 University of Botswana
RP Motsholapheko, MR (corresponding author), Univ Botswana, Okavango Res Inst, P Bag 285, Maun, Botswana.
EM rmoseki@orc.ub.bw
RI Motsholapheko, Moseki/AAM-9815-2021
FU Carnegie-RISE; Office for Research and Development, University of
   Botswana
FX This paper forms part of a study undertaken by Moseki R. Motsholapheko
   for PhD Natural Resources Management at the Okavango Research Institute,
   University of Botswana. It was financially supported by Carnegie-RISE
   and Office for Research and Development, University of Botswana. We
   thank Dr M. Murray-Hudson, Professor J.E. Mbaiwa and Professor L. Swatuk
   for insightful comments, and Mr M. Dhliwayo for technical assistance.
CR Agrawal Arun., 2008, ROLE LOCAL I ADAPTAT, DOI [10.1596/28274, 10.1007/978-0-387-75217-4_1]
   [Anonymous], 2000, Linking social and ecological systems: management practices and social mechanisms for building resilience
   [Anonymous], 1999, ELINOR OSTROM BLOOMI
   [Anonymous], 2011 POP HOUS CENS P
   [Anonymous], BOTSW MILL DEV GOALS
   [Anonymous], 2001, Introduction to quantitative research methods: An investigative approach
   [Anonymous], GLOBAL CHANGE PROCES
   [Anonymous], 2008, STAT INF REP SIRI
   Bendsen H, 2003, P ENV MON TROP SUBTR
   Bernard T, 2005, J ARID ENVIRON, V63, P256, DOI 10.1016/j.jaridenv.2005.02.001
   Birkmann J, 2010, SUSTAIN SCI, V5, P171, DOI 10.1007/s11625-010-0108-y
   Botswana Institute of Development Policy Analysis, 2003, REP REV REM AR DEV P
   Bouwer LM, 2006, DISASTERS, V30, P49, DOI 10.1111/j.1467-9523.2006.00306.x
   Department of Animal Production, 2010, LIV MAN INFR DEV LIM
   Dessai S, 2009, UNCERTAINTY CLIMATE
   Dube OP, 2008, CLIMATE ADAPTATION
   Ellis F., 2000, Rural Livelihood and Diversity in Developing Countries
   Ellis Frank., 2009, Social Protection in Africa, DOI DOI 10.4337/9781848446014
   Foley C., 2007, Mozambique: A case study in the role of the affected state in humanitarian action
   Food and Agricultural Organisation [FAO], 2008, DIS RISK MAN SYST AN
   Gergis A., 1999, BIDPA Working Paper No. 22
   Gupta J, 2010, ENVIRON SCI POLICY, V13, P459, DOI 10.1016/j.envsci.2010.05.006
   Hahn MB, 2009, GLOBAL ENVIRON CHANG, V19, P74, DOI 10.1016/j.gloenvcha.2008.11.002
   HOLM JD, 1985, J MOD AFR STUD, V23, P463, DOI 10.1017/S0022278X00057189
   International Poverty Centre [IPC] and Botswana Institute for Development and Policy Analysis [BIDPA], 2005, POV STAT REP BOTSW I
   Kennedy J., 2008, Journal of Contingencies and Crisis Management, V16, P24, DOI [10.1111/j.1468-5973.2008.00529.x, DOI 10.1111/J.1468-5973.2008.00529.X]
   Kerapeletswe CK, 2001, POVERTY REDUCTION WH
   Kgathi D. L., 2007, Development Southern Africa, V24, P289, DOI 10.1080/03768350701327186
   Koontz TM, 2005, POLICY STUD J, V33, P459, DOI 10.1111/j.1541-0072.2005.00125.x
   Lengwe- Katumbela M., 1998, Journal o f Social Development in Africa, V13, P55
   Magole L., 2005, Botsw. Notes Rec, V7, P125
   Magole L, 2009, DEV SO AFR, V26, P611, DOI 10.1080/03768350903181399
   McCarthy TS, 1998, S AFR J GEOL, V101, P101
   McCarthy TS, 2000, S AFR J SCI, V96, P25
   Mercer J, 2010, J INT DEV, V22, P247, DOI 10.1002/jid.1677
   Ministry of Finance and Development Planning, 1997, NAT DEV PLAN 8 1997
   Mitchell Tom., 2008, Convergence of Disaster Risk Reduction and Climate Change Adaptation
   Mmopelwa G., 2011, IMPACT ENV CHANGE EC
   Mosepele M, 2012, COMMUNICATION
   Moser C.A., 1971, Survey Methods in Social Investigation, V1st, DOI DOI 10.4324/9781315241999
   Motsholapheko MR, 2012, AGREKON, V51, P41, DOI 10.1080/03031853.2012.741204
   Motsholapheko MR, 2011, PHYS CHEM EARTH, V36, P984, DOI 10.1016/j.pce.2011.08.004
   Motsholapheko MR, 2012, J WATER CLIM CHANGE, V3, P300, DOI 10.2166/wcc.2012.048
   National Disaster Management Office, 2009, NAT DIS MAN PLAN
   Omari K., 2010, Climate Change Vulnerability andAdaptation Preparedness in Southern Africa -A Case Study of Botswana
   Osman-Elasha B., 2007, Lessons learned in preparing national adaptation programmes of action in Eastern and Southern Africa
   Ostrom E, 2005, UNDERSTANDING INSTITUTIONAL DIVERSITY, P1
   Ostrom E, 2011, POLICY STUD J, V39, P7, DOI 10.1111/j.1541-0072.2010.00394.x
   Peters Pauline., 1994, DIVIDING COMMONS POL
   Republic of Botswana, 2003, NAT DEV PLAN 9 2003
   Rowntree K, 2008, ECOSYSTEM SERVICES P
   Rudd MA, 2004, ECOL ECON, V48, P109, DOI 10.1016/j.ecolecon.2003.10.002
   Seleka T.B., 2005, 27 BIDPA
   Shaw P., 1983, Botswana Notes and Records, V15, P79
   Smit B, 2001, CLIMATE CHANGE 2001: IMPACTS, ADAPTATION, AND VULNERABILITY, P877
   Statistics Botswana, 2011, BOTSW COR WELF IND P
   Tearfund Institute of Development Studies, 2006, 1 TEARF I DEV STUD
   Tsheko R, 2003, WATER SA, V29, P389
   Vanderpost C, 2006, POPUL ENVIRON, V27, P285, DOI 10.1007/s11111-006-0022-5
   Wolski P, 2006, S AFR J SCI, V102, P173
   World Bank, 2012, World Development Report 2012: Gender Equality and Development
NR 61
TC 5
Z9 6
U1 1
U2 32
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 2015
VL 20
IS 2
BP 221
EP 239
DI 10.1007/s11027-013-9488-5
PG 19
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA AZ0RN
UT WOS:000347952400003
DA 2025-01-10
ER

PT J
AU Kuss, AJM
   Gurdak, JJ
AF Kuss, Amber Jean M.
   Gurdak, Jason J.
TI Groundwater level response in US principal aquifers to ENSO, NAO, PDO,
   and AMO
SO JOURNAL OF HYDROLOGY
LA English
DT Article
DE Groundwater; Climate variability; ENSO; NAO; PDO; AMO
ID ATMOSPHERE TELECONNECTION PATTERNS; HYDROLOGIC TIME-SERIES;
   CLIMATE-CHANGE; UNITED-STATES; INTERANNUAL VARIABILITY; WINTER
   PRECIPITATION; CHANGE IMPACTS; HIGH-PLAINS; WATER; WAVELET
AB Groundwater will play an important role in society's adaptation to climate variability and change. Therefore, it is particularly important to understand teleconnections in groundwater with interannual to multidecadal climate variability because of the tangible and near-term implications for water-resource management. Here we use singular spectrum analysis (SSA), wavelet coherence analysis, and lag correlation to quantify the effects of the El Nino Southern Oscillation (ENSO) (2-7 year cycle), North Atlantic Oscillation (NAO) (3-6 year cycle), Pacific Decadal Oscillation (PDO) (15-25 year cycle), and Atlantic Multidecadal Oscillation (AMO) (50-70 year cycle) on precipitation and groundwater levels across the regionally extensive Central Valley, Basin and Range, and North Atlantic Coastal Plain principal aquifers (PAs) of the United States (U.S.). Results are compared to recent findings from a similar climate variability study of the High Plains aquifer to provide the first national-scale assessment of the effects of interannual to multidecadal climate variability on groundwater resources in U.S. PAs. The results indicate that groundwater levels are partially controlled by interannual to multidecadal climate variability and are not solely a function of temporal patterns in pumping. ENSO and PDO have a greater control than NAO and AMO on variability in groundwater levels across the U.S., particularly in the western and central PAs. Findings and methods presented here expand the knowledge and usable toolbox of innovative approaches that can be used by managers and scientists to improve groundwater resource planning and operations under future climate uncertainty. (C) 2014 Elsevier B.V. All rights reserved.
C1 [Kuss, Amber Jean M.] Univ Calif Santa Cruz, Dept Environm Studies, Santa Cruz, CA 95064 USA.
   [Gurdak, Jason J.] San Francisco State Univ, Dept Earth & Climate Sci, San Francisco, CA 94732 USA.
C3 University of California System; University of California Santa Cruz;
   California State University System; San Francisco State University
RP Gurdak, JJ (corresponding author), San Francisco State Univ, Dept Earth & Climate Sci, 1600 Holloway Ave, San Francisco, CA 94732 USA.
EM akuss@ucsc.edu; jgurdak@sfsu.edu
FU National Science Foundation (NSF) Hydrologic Sciences program
   [EAR-1316553]; Directorate For Geosciences; Division Of Earth Sciences
   [1316553] Funding Source: National Science Foundation
FX Funding for this research was provided by the National Science
   Foundation (NSF) Hydrologic Sciences program under the award #
   EAR-1316553. Discussion and comments by Tim Janssen and John Monteverde
   (San Francisco State University), Randy Hanson (USGS), Jesse Dickinson
   (USGS), and an anonymous reviewer greatly improved the manuscript.
CR Allen MR, 1996, J CLIMATE, V9, P3373, DOI 10.1175/1520-0442(1996)009<3373:MCSDIO>2.0.CO;2
   Anderson WP, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL036054
   [Anonymous], 1749 US GEOL SURV
   [Anonymous], NINO HIST PALEOCLIMA
   [Anonymous], INTERHEMISPHERIC CLI
   [Anonymous], PRINC AQ 48 CONT US
   [Anonymous], NAT WAT INF SYST NAT
   [Anonymous], 1991, Professional Paper 1401-a.
   [Anonymous], 2012, CLIMATE CHANGE EFFEC
   [Anonymous], CLIM RAD DAT INV 192
   [Anonymous], 1977, Exploratory Data Analysis
   [Anonymous], 4A9 US GEOL SURV TEC
   [Anonymous], 20075009 US GEOL SUR
   [Anonymous], THESIS SAN FRANCISCO
   [Anonymous], CTR LAND OCEAN ATMOS
   [Anonymous], 1992, 1404G US GEOL SURV
   [Anonymous], 2005, 1279 US GEOL SURV
   Brown DP, 2004, GEOPHYS RES LETT, V31, DOI 10.1029/2003GL018726
   Clark B.R., 2011, U.S. Geological Survey Professional paper 1785
   Venencio MD, 2011, J HYDROL, V409, P62, DOI 10.1016/j.jhydrol.2011.07.039
   Dettinger M.D., 1995, EOS T AM GEOPHYS UN, V76, P12
   DETTINGER MD, 1995, J CLIMATE, V8, P606, DOI 10.1175/1520-0442(1995)008<0606:LSAFOR>2.0.CO;2
   Dickinson JE, 2004, WATER RESOUR RES, V40, DOI 10.1029/2003WR002650
   Earman S, 2011, J WATER CLIM CHANGE, V2, P213, DOI 10.2166/wcc.2011.034
   Enfield DB, 2006, INT J CLIMATOL, V26, P885, DOI 10.1002/joc.1293
   Enfield DB, 2001, GEOPHYS RES LETT, V28, P2077, DOI 10.1029/2000GL012745
   Faunt C.C., 2009, GROUNDWATER AVAILABI
   Figura S, 2011, GEOPHYS RES LETT, V38, DOI 10.1029/2011GL049749
   Fisher LH, 2008, J ENVIRON QUAL, V37, P1051, DOI 10.2134/jeq2006.0561
   Fleming SW, 2006, GROUND WATER, V44, P595, DOI 10.1111/j.1745-6584.2006.00187.x
   Furtado JC, 2011, J CLIMATE, V24, P3049, DOI 10.1175/2010JCLI3584.1
   Ghil M, 2002, REV GEOPHYS, V40, DOI 10.1029/2000RG000092
   Ghil M., 2002, ENCY GLOBAL ENV CHAN, P544
   Green TR, 2011, J HYDROL, V405, P532, DOI 10.1016/j.jhydrol.2011.05.002
   Grinsted A, 2004, NONLINEAR PROC GEOPH, V11, P561, DOI 10.5194/npg-11-561-2004
   Gurdak J., 2008, Ground-Water Vulnerability: Nonpoint-source Contamination, Climate Variability, and the High Plain Aquifer
   Gurdak J.J., 2009, Effects of Climate Variability and Change on Groundwater Resources of the United States (No. 2327-6932)
   Gurdak JJ, 2007, VADOSE ZONE J, V6, P533, DOI 10.2136/vzj2006.0087
   Gutzler DS, 2002, WEATHER FORECAST, V17, P1163, DOI 10.1175/1520-0434(2002)017<1163:MOEBLL>2.0.CO;2
   Hanson RT, 2006, HYDROGEOL J, V14, P1122, DOI 10.1007/s10040-006-0067-7
   Hanson RT, 2012, WATER RESOUR RES, V48, DOI 10.1029/2011WR010774
   Hanson RT, 2005, J AM WATER RESOUR AS, V41, P517, DOI 10.1111/j.1752-1688.2005.tb03752.x
   Hanson RT, 2004, J HYDROL, V287, P252, DOI 10.1016/j.jhydrol.2003.10.006
   Helsel D.R., 2002, BOOK 4 HYDROLOGIC AN, DOI DOI 10.3133/TWRI04A3
   Holman IP, 2006, HYDROGEOL J, V14, P637, DOI 10.1007/s10040-005-0467-0
   Holman IP, 2009, HYDROL PROCESS, V23, P3123, DOI 10.1002/hyp.7466
   Holman IP, 2011, HYDROGEOL J, V19, P1269, DOI 10.1007/s10040-011-0755-9
   HURRELL JW, 1995, SCIENCE, V269, P676, DOI 10.1126/science.269.5224.676
   Hurrell JW, 1997, CLIMATIC CHANGE, V36, P301, DOI 10.1023/A:1005314315270
   Hurrell JW., 2003, GEOPHYS MONOGR SER, V134, P1, DOI 10.1029/134GM01
   Ionita M, 2012, J HYDROMETEOROL, V13, P172, DOI 10.1175/JHM-D-11-063.1
   Kerr RA, 2000, SCIENCE, V288, P1984, DOI 10.1126/science.288.5473.1984
   Kiladis GN, 1989, J CLIMATE, V2, P1069, DOI 10.1175/1520-0442(1989)002<1069:GCAAWE>2.0.CO;2
   Klove B, 2014, J HYDROL, V518, P250, DOI 10.1016/j.jhydrol.2013.06.037
   Kurtzman D, 2007, WATER RESOUR RES, V43, DOI 10.1029/2007WR005863
   Labat D, 2000, J HYDROL, V238, P149, DOI 10.1016/S0022-1694(00)00322-X
   Labat D, 2005, J HYDROL, V314, P275, DOI 10.1016/j.jhydrol.2005.04.003
   Labat D, 2008, ADV WATER RESOUR, V31, P109, DOI 10.1016/j.advwatres.2007.07.004
   Labat D, 2010, J HYDROL, V385, P269, DOI 10.1016/j.jhydrol.2010.02.029
   Lapp SL, 2012, INT J CLIMATOL, V32, P1423, DOI 10.1002/joc.2364
   Mantua NJ, 1997, B AM METEOROL SOC, V78, P1069, DOI 10.1175/1520-0477(1997)078<1069:APICOW>2.0.CO;2
   Mantua NJ, 2002, J OCEANOGR, V58, P35, DOI 10.1023/A:1015820616384
   McCabe GJ, 2004, P NATL ACAD SCI USA, V101, P4136, DOI 10.1073/pnas.0306738101
   McMahon PB, 2011, HYDROGEOL J, V19, P779, DOI 10.1007/s10040-011-0722-5
   McMahon PB, 2006, WATER RESOUR RES, V42, DOI 10.1029/2005WR004417
   McNeeley SM, 2012, B AM METEOROL SOC, V93, P477, DOI 10.1175/BAMS-D-11-00221.1
   Milly PCD, 2008, SCIENCE, V319, P573, DOI 10.1126/science.1151915
   Newman M, 2003, J CLIMATE, V16, P3853, DOI 10.1175/1520-0442(2003)016<3853:EVOTPD>2.0.CO;2
   Ottersen G, 2001, OECOLOGIA, V128, P1, DOI 10.1007/s004420100655
   Peings Y, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/3/034018
   Perez-Valdivia C, 2012, WATER RESOUR RES, V48, DOI 10.1029/2011WR010930
   Perez-Valdivia C, 2011, DENDROCHRONOLOGIA, V29, P41, DOI 10.1016/j.dendro.2010.09.001
   Planert M., 1995, GROUND WATER ATLAS U
   Polsky C, 2000, CLIMATE RES, V14, P161
   Pool DR, 2005, WATER RESOUR RES, V41, DOI 10.1029/2004WR003255
   ROPELEWSKI CF, 1986, MON WEATHER REV, V114, P2352, DOI 10.1175/1520-0493(1986)114<2352:NAPATP>2.0.CO;2
   Sheppard PR, 2002, CLIM RES, V21, P219, DOI 10.3354/cr021219
   Stoll S, 2011, HYDROL EARTH SYST SC, V15, P3861, DOI 10.5194/hess-15-3861-2011
   THOMPSON L.G., 1992, El Nino: historical and paleoclimatic aspects of the Southern Oscillation, P295
   Torrence C, 1998, B AM METEOROL SOC, V79, P61, DOI 10.1175/1520-0477(1998)079<0061:APGTWA>2.0.CO;2
   Trapp H., 1997, Groundwater Atlas of the United States, Hydrologic Investigations Atlas 730-L
   Treidel H., 2012, Climate change effects on groundwater resources: a global synthesis of findings and recommendations
   Tremblay L, 2011, J HYDROL, V410, P178, DOI 10.1016/j.jhydrol.2011.09.013
   VAUTARD R, 1992, PHYSICA D, V58, P95, DOI 10.1016/0167-2789(92)90103-T
   Vicente-Serrano SM, 2011, J GEOPHYS RES-ATMOS, V116, DOI 10.1029/2011JD016039
   Wada Y, 2010, GEOPHYS RES LETT, V37, DOI 10.1029/2010GL044571
   Walvoord MA, 2003, SCIENCE, V302, P1021, DOI 10.1126/science.1086435
   Wolter K, 2011, INT J CLIMATOL, V31, P1074, DOI 10.1002/joc.2336
NR 88
TC 108
Z9 120
U1 5
U2 89
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 27
PY 2014
VL 519
BP 1939
EP 1952
DI 10.1016/j.jhydrol.2014.09.069
PN B
PG 14
WC Engineering, Civil; Geosciences, Multidisciplinary; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Engineering; Geology; Water Resources
GA AX6FH
UT WOS:000347018100058
DA 2025-01-10
ER

PT J
AU Shen, JB
   Cui, ZL
   Miao, YX
   Mi, GH
   Zhang, HY
   Fan, MS
   Zhang, CC
   Jiang, RF
   Zhang, WF
   Li, HG
   Chen, XP
   Li, XL
   Zhang, FS
AF Shen, Jianbo
   Cui, Zhenling
   Miao, Yuxin
   Mi, Guohua
   Zhang, Hongyan
   Fan, Mingsheng
   Zhang, Chaochun
   Jiang, Rongfeng
   Zhang, Weifeng
   Li, Haigang
   Chen, Xinping
   Li, Xiaolin
   Zhang, Fusuo
TI Transforming agriculture in China: From solely high yield to both high
   yield and high resource use efficiency
SO GLOBAL FOOD SECURITY-AGRICULTURE POLICY ECONOMICS AND ENVIRONMENT
LA English
DT Article
DE Agricultural transformation; Intensification; Food security; Resource
   use efficiency; Environmental protection; Crop-soil management
   technology
ID NITROGEN-USE EFFICIENCY; REDUCING ENVIRONMENTAL RISK; NUTRIENT USE
   EFFICIENCY; CROP SYSTEM MANAGEMENT; ON-FARM EVALUATION; FOOD SECURITY;
   SOIL; PRODUCTIVITY; QUALITY; MAIZE
AB The challenges facing agriculture in China are probably more severe than ever before. We have developed an integrated technology system in which the focus is on achieving both high crop productivity and high resource use efficiency ("double high" technology system) to ensure food security and environmental sustainability. The components comprise (1) significantly increased grain yield through high-yield crop management, i.e. an optimal cropping system design and management well adapted to climate conditions; (2) greatly increased nutrient-use efficiency through root/rhizosphere management to optimize the nutrient supply intensity and composition in the root zone to maximize root/rhizosphere efficiency; (3) improved soil quality to ensure long-term food security by managing soil organic matter and eliminating soil physical, chemical and biological constrains and (4) enhanced agricultural sustainability through resource and environment management by increasing resource use efficiency, reducing nutrient losses and greenhouse gas emissions and minimizing negative ecological footprints. In our work in major agricultural regions of China, this system has been successfully tested and demonstrated through well-organized farmer associations, enterprises with improved products and government extension networks. The new "double high" concept has the potential to become an effective agricultural development path to ensure food security and improve environmental quality, especially in China and other rapidly developing economies where agricultural intensification must achieve and must be transformed from low-efficiency systems to achieving high yields with high resource use efficiency. (C) 2013 Elsevier B.V. All rights reserved.
C1 [Shen, Jianbo; Cui, Zhenling; Miao, Yuxin; Mi, Guohua; Zhang, Hongyan; Fan, Mingsheng; Zhang, Chaochun; Jiang, Rongfeng; Zhang, Weifeng; Li, Haigang; Chen, Xinping; Li, Xiaolin; Zhang, Fusuo] China Agr Univ, Dept Plant Nutr, Ctr Resources Environm & Food Secur, 2 Yuan Ming Yuan West Rd, Beijing 100193, Peoples R China.
C3 China Agricultural University
RP Zhang, FS (corresponding author), China Agr Univ, Dept Plant Nutr, Ctr Resources Environm & Food Secur, 2 Yuan Ming Yuan West Rd, Beijing 100193, Peoples R China.
EM zhangfs@cau.edu.cn
RI Li, Xiaolin/O-5795-2015; Zhang, Fusuo/AAV-4517-2021; Xinping,
   Chen/F-7305-2013; Cui, Zhenling/HZH-5349-2023; Shen, Jianbo/Y-3591-2019
OI Shen, Jianbo/0000-0001-8943-948X
FU National Basic Research Program of China [2009CB118600]; National
   Natural Science Foundation of China [30890130, 30925024]; NSFC
   [31121062]
FX This research was supported by the National Basic Research Program of
   China (2009CB118600), the National Natural Science Foundation of China
   (30890130, 30925024), and the innovative group grant of the NSFC
   (31121062). We give special thanks to Dr. Achim Dobermann in
   International Rice Research Institute (IRRI) for his comments and
   linguistic revisions.
CR [Anonymous], CHIN AGR STAT YB
   [Anonymous], FAOSAT STAT DAT
   [Anonymous], CHIN STAT YB
   [Anonymous], LAND DEGRADATION DEV
   [Anonymous], EXPLORATION MODERN A
   [Anonymous], SOIL NITROGEN CHINES
   [Anonymous], THESIS CHINA AGR U
   [Anonymous], CHIN WAT RES B
   [Anonymous], 2009, REPORTS AGR WATER US
   Campbell CA, 1995, FERT RES, V42, P277, DOI 10.1007/BF00750521
   Cassman KG, 2002, AMBIO, V31, P132, DOI 10.1639/0044-7447(2002)031[0132:ANUEAN]2.0.CO;2
   Cassman KG, 1996, FIELD CROP RES, V47, P1, DOI 10.1016/0378-4290(95)00101-8
   Cassman KG, 1999, P NATL ACAD SCI USA, V96, P5952, DOI 10.1073/pnas.96.11.5952
   Cassman KG, 2003, ANNU REV ENV RESOUR, V28, P315, DOI 10.1146/annurev.energy.28.040202.122858
   Chen Jie, 2002, Journal of Geographical Sciences, V12, P243
   Chen XP, 2011, P NATL ACAD SCI USA, V108, P6399, DOI 10.1073/pnas.1101419108
   Cui ZL, 2008, AGRON J, V100, P517, DOI 10.2134/agronj2007.0194
   Cui ZL, 2008, FIELD CROP RES, V105, P48, DOI 10.1016/j.fcr.2007.07.008
   Cui ZL, 2010, AMBIO, V39, P376, DOI 10.1007/s13280-010-0076-6
   Cui ZL, 2010, FIELD CROP RES, V116, P140, DOI 10.1016/j.fcr.2009.12.004
   Dobermann A, 2005, SCI CHINA SER C, V48, P745, DOI 10.1360/062005-268
   Dobermann A., 2007, INT WORKSH FERT BEST
   Dobermann A., 2000, RICE NUTR DISORDERS
   Fan MS, 2012, J EXP BOT, V63, P13, DOI 10.1093/jxb/err248
   Guo JH, 2010, SCIENCE, V327, P1008, DOI 10.1126/science.1182570
   Huang Y, 2006, CHINESE SCI BULL, V51, P1785, DOI 10.1007/s11434-006-2056-6
   Janzen HH, 2006, SOIL BIOL BIOCHEM, V38, P419, DOI 10.1016/j.soilbio.2005.10.008
   Jiao L, 2010, SCIENCE, V328, P1462, DOI 10.1126/science.328.5985.1462-a
   Jing J, 2012, FIELD CROP RES, V133, P176, DOI 10.1016/j.fcr.2012.04.009
   Jing J, 2010, FIELD CROP RES, V119, P355, DOI 10.1016/j.fcr.2010.08.005
   Ju XT, 2009, P NATL ACAD SCI USA, V106, P3041, DOI 10.1073/pnas.0813417106
   Ladha JK., 2005, Adv Agron, V87, P86, DOI DOI 10.1016/S0065-2113(05)87003-8
   Le C, 2010, ENVIRON MANAGE, V45, P662, DOI 10.1007/s00267-010-9440-3
   Lindert PeterH., 2000, SHIFTING GROUND CHAN
   Meng QF, 2013, FIELD CROP RES, V143, P91, DOI 10.1016/j.fcr.2012.09.023
   [潘根兴 Pan Genxing], 2005, [地球科学进展, Advance in Earth Sciences], V20, P384
   Peng SB, 2010, AGRON SUSTAIN DEV, V30, P649, DOI 10.1051/agro/2010002
   Qiu J, 2010, NATURE, V466, P308, DOI 10.1038/466308a
   Shen JB, 2013, J EXP BOT, V64, P1181, DOI 10.1093/jxb/ers342
   Shen JB, 2011, PLANT PHYSIOL, V156, P997, DOI 10.1104/pp.111.175232
   Tilman D, 2002, NATURE, V418, P671, DOI 10.1038/nature01014
   Tilman D, 2011, P NATL ACAD SCI USA, V108, P20260, DOI 10.1073/pnas.1116437108
   Tso TC, 2004, NATURE, V428, P215, DOI 10.1038/428215a
   Zhang FS, 2012, ADV AGRON, V116, P1, DOI 10.1016/B978-0-12-394277-7.00001-4
   Zhang FS, 2011, J ENVIRON QUAL, V40, P1051, DOI 10.2134/jeq2010.0292
   Zhang FS, 2010, ADV AGRON, V107, P1, DOI 10.1016/S0065-2113(10)07001-X
   Zhang FuSuo Zhang FuSuo, 2008, Acta Pedologica Sinica, V45, P915
   Zheng X., 2004, GlobalBiogeochemicalCycles18, pB2018
   Zwart SJ, 2004, AGR WATER MANAGE, V69, P115, DOI 10.1016/j.agwat.2004.04.007
NR 49
TC 105
Z9 129
U1 10
U2 163
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 2211-9124
J9 GLOB FOOD SECUR-AGR
JI Glob. Food Secur.-Agric.Policy
PD MAR
PY 2013
VL 2
IS 1
BP 1
EP 8
DI 10.1016/j.gfs.2012.12.004
PG 8
WC Food Science & Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Food Science & Technology
GA V42DK
UT WOS:000209594300001
DA 2025-01-10
ER

PT C
AU Olsson, O
   Bauer, M
   Ikramova, M
   Froebrich, J
AF Olsson, Oliver
   Bauer, Melanie
   Ikramova, Malika
   Froebrich, Jochen
BE Qi, J
   Evered, KT
TI THE ROLE OF THE AMU DARYA DAMS AND RESERVOIRS IN FUTURE WATER SUPPLY IN
   THE AMU DARYA BASIN
SO ENVIRONMENTAL PROBLEMS OF CENTRAL ASIA AND THEIR ECONOMIC, SOCIAL AND
   SECURITY IMPACTS
SE NATO Science for Peace and Security Series C-Environmental Security
LA English
DT Proceedings Paper
CT NATO Advanced Research Workshop on Environmental Problems of Central
   Asia and their Economic, Social and Security Impacts
CY OCT 01-05, 2007
CL Tashkent, UZBEKISTAN
SP NATO Sci Peace & Secur Program
DE Amu Darya basin; role of dams and reservoirs; water supply; enhanced
   reservoir operation; water quality; water quantity
AB Central Asia still remains as an area of substantial water stress problems caused by climate change, over-consumption of water resources and soil salinization. The rapid recession of glaciers along with a Concurrent increasing frequency and intensity of extreme droughts has led to a progressive reduction of the already scarce resources. As in many other arid and semi-arid zones, surface waters in Central Asia are heavily regulated by extended river-reservoir systems, which affect both the quantity and the quality of water. The large dams and reservoirs of the Amu Darya basin should not only be a matter of international dispute, but also considered as an option to adapt to climate and global change and to the future water shortage in the region. With the Nurek and Rogun darns in the upstream part of the Amu Darya basin and the downstream dam system, the Tuyamuyun Hydroengineering Complex (THC), the region already has a high potential for improving the future water supply by adapting the management of the dams according to site specifications. The main scope of this study is to introduce this potential as all applicable instrument for implementing a sustainable water management strategy in the Amu Darya basin. Although this potential or the opportunities dams provide is not always obvious, the results herein received make clear that the management of large darns and reservoirs is an effective measure to improve the resulting water quality and to contribute towards a safe water supply through a modified use of already existing infrastructure.
C1 [Olsson, Oliver; Bauer, Melanie] Bauer Olsson GbR Engn, Water Management Ctr, Am Kleinen Felde 30, Hannover, Germany.
   [Ikramova, Malika] Ctr Asian Sci Res Inst Irrigat SANIIRI, Tashkent 700187, Uzbekistan.
   [Froebrich, Jochen] Wageningen UR, Ctr Water & Climate CWK, NL-6700 AA Wageningen, Netherlands.
C3 Wageningen University & Research
RP Olsson, O (corresponding author), Bauer Olsson GbR Engn, Water Management Ctr, Am Kleinen Felde 30, Hannover, Germany.
EM o.olsson@wmc-engincers.eu
RI Olsson, Oliver/C-2710-2014; Ikramova, Malika/AAB-8451-2020
OI Ikramova, Malika/0000-0001-5360-8536
CR Ahmad Masood., 2004, Water Resource Development in Northern Afghanistan and Its Implications for Amu Darya Basin
   Froebrich J, 2004, NATO SCI S SS IV EAR, V36, P49
   GIESE E, 2004, DISCUSSION PAPERS CT, V18
   ICG (International Crisis Group), 2002, 34 ICG
   KAYUMOV O, 1997, UZBEKISTAN AGR, V2
   *MIN EN, 2004, ANN REP MIN EN
   *REP UZB CLIM CHAN, 1999, IN COMM REP UZB UN F
   Schmidt R, 2006, PROC MONOGR ENG WATE, P405
   SHERMAN S, 1992, POWER TECHNOLOGY ENG, V25, P668
   SMITH DR, 1995, POST-SOV GEOGR, V36, P351, DOI 10.1080/10605851.1995.10640997
   Spoor M., 2003, Perspectives on Global Development and Technology, V2, P593, DOI 10.1163/156915003322986415
   *TACIS, 1995, WAT RES MAN AGR PROD, V4
   Tanton TW, 1999, J WATER RES PL-ASCE, V125, P363, DOI 10.1061/(ASCE)0733-9496(1999)125:6(363)
   *UN, 2004, WAT RES MAN ENV PERF, pCH8
   Wegerich K, 2007, ENERG POLICY, V35, P3815, DOI 10.1016/j.enpol.2007.01.024
   *WORLD BANK, 2005, 32603TJ WORLD BANK
NR 16
TC 6
Z9 8
U1 0
U2 16
PU SPRINGER
PI DORDRECHT
PA PO BOX 17, 3300 AA DORDRECHT, NETHERLANDS
SN 1871-4668
BN 978-1-4020-8958-9
J9 NATO SCI PEACE SECUR
JI NATO Sci. Peace Secur. Ser. C- Environ. Secur.
PY 2008
BP 277
EP +
DI 10.1007/978-1-4020-8960-2_20
PG 4
WC Economics; Environmental Sciences; Environmental Studies; Geography;
   Geography, Physical
WE Conference Proceedings Citation Index - Science (CPCI-S); Conference Proceedings Citation Index - Social Science &amp; Humanities (CPCI-SSH)
SC Business & Economics; Environmental Sciences & Ecology; Geography;
   Physical Geography
GA BIM31
UT WOS:000260774600020
OA Bronze
DA 2025-01-10
ER

PT J
AU Charlet, LD
   Armstrong, JS
   Hein, GL
AF Charlet, LD
   Armstrong, JS
   Hein, GL
TI Sunflower stem weevil and its larval parasitoids in the Central and
   Northern Plains of the USA
SO BIOCONTROL
LA English
DT Article
DE sunflower; Helianthus; biological control; natural enemies; parasitoids;
   weevils; Hymenoptera
ID CYLINDROCOPTURUS-ADSPERSUS COLEOPTERA; GREAT-PLAINS; BIOLOGICAL-CONTROL;
   INSECT FAUNA; CURCULIONIDAE; DAKOTA; HYMENOPTERA; HELIANTHUS; ABUNDANCE
AB The sunflower stem weevil, Cylindrocopturus adspersus (LeConte) (Coleoptera: Curculionidae), is a pest of cultivated sunflower (Helianthus annuus L) from the southern to the northern Great Plains. The incidence of weevil infestation in fields from the six different states sampled during 1996 and 1997 ranged from 33% (Minnesota) to 100% (Kansas, Colorado, Nebraska). Weevil populations in the fields sampled were statistically greater in the central Plains (Colorado, Kansas, Nebraska) with a mean of 12.3 and 19.5 larvae per stalk compared with the northern Plains (North and South Dakota, Minnesota) of 0.7 and 1.3 larvae per stalk in 1996 and 1997, respectively. Parasitization of weevils varied from field to field ranging from 1 to 100%, but was usually less than 20%. The nine species of larval parasitoids recovered were all Hymenoptera and included: Nealiolus curculionis (Fitch), N. collaris (Brues), Bracon sp. (Braconidae); Neocatolaccus tylodermae (Ashmead), Chlorocytus sp., Pteromalus sp. (Pteromalidae); Quadrastichus ainsliei Gahan (Eulophidae), Eurytoma tylodermatis Ashmead (Eurytomidae); and Eupelmus sp. (Eupelmidae). Nealiolus curculionis was the most prevalent parasitoid reared from C. adspersus, and it was recovered from all states sampled. Parasitoid species richness was greatest in the central Plains. The reduced number of parasitoid species found attacking C. adspersus in the northern Plains may be caused by low host population levels, slow migration by parasitoids into the region, or lack of adaptation to climatic conditions. Additional work to understand the population dynamics of the parasitoid complex associated with C. adspersus may result in improved biological control of the sunflower stem weevil in cultivated sunflower.
C1 USDA ARS, No Crop Sci Lab, Fargo, ND 58105 USA.
   Texas Tech Univ, Dept Plant & Soil Sci, Lubbock, TX 79409 USA.
   Univ Nebraska, Panhandle Res & Extens Ctr, Scottsbluff, NB 69361, Canada.
C3 United States Department of Agriculture (USDA); Texas Tech University
   System; Texas Tech University
RP Charlet, LD (corresponding author), USDA ARS, No Crop Sci Lab, Fargo, ND 58105 USA.
CR Armstrong JS, 1997, J KANSAS ENTOMOL SOC, V70, P258
   Armstrong JS, 1996, P 18 SUNFL RES WORKS, P49
   ARTHUR AP, 1990, CAN ENTOMOL, V112, P387
   Beacher John H., 1947, ANN ENT SOC AMERICA, V40, P530, DOI 10.1093/aesa/40.3.530
   Bugbee R. E., 1967, Proceedings of the United States National Museum, V118, P433
   CASALSBUSTOS P, 1976, THESIS N DAKOTA STAT, P108
   Charlet Laurence D., 1997, Agronomy (Madison), V35, P183
   CHARLET LD, 1983, ENVIRON ENTOMOL, V12, P1526, DOI 10.1093/ee/12.5.1526
   CHARLET LD, 1985, J ECON ENTOMOL, V78, P1347, DOI 10.1093/jee/78.6.1347
   CHARLET LD, 1992, ENVIRON ENTOMOL, V21, P493, DOI 10.1093/ee/21.3.493
   CHARLET LD, 1984, J KANSAS ENTOMOL SOC, V57, P526
   CHARLET LD, 1994, ANN ENTOMOL SOC AM, V87, P831, DOI 10.1093/aesa/87.6.831
   CHARLET LD, 1994, BIOL CONTROL, V4, P26, DOI 10.1006/bcon.1994.1005
   CHARLET LD, 1983, ENVIRON ENTOMOL, V12, P888, DOI 10.1093/ee/12.3.888
   CHARLET LD, 1987, CAN ENTOMOL, V119, P1131, DOI 10.4039/Ent1191131-12
   Charlet LD, 1999, THOM SAY P, P91
   CHARLET LD, 1983, ENVIRON ENTOMOL, V12, P1286, DOI 10.1093/ee/12.4.1286
   CHARLET LD, 1984, P SUNFL RES WORKSH B, P18
   GOEDEN RD, 1970, J ECON ENTOMOL, V63, P827, DOI 10.1093/jee/63.3.827
   GOEDEN RD, 1976, ENVIRON ENTOMOL, V5, P1169, DOI 10.1093/ee/5.6.1169
   GOEDEN RD, 1975, ENVIRON ENTOMOL, V4, P301, DOI 10.1093/ee/4.2.301
   Hawkins B.A., 1994, PATTERN PROCESS HOST
   Krombein KV., 1979, CATALOG HYMENOPTERA, P1198
   Mitchell J. D., 1911, Proceedings of the Entomological Society of Washington DC, V13
   Müller CB, 1999, J ANIM ECOL, V68, P346, DOI 10.1046/j.1365-2656.1999.00288.x
   NEWTON JH, 1921, 12 ANN REPT STA ENTO, V35, P37
   Pierce W. B., 1916, Proceedings of the Entomological Society of Washington, V18
   PSCHORNWALCHER H, 1977, ANNU REV ENTOMOL, V22, P1, DOI 10.1146/annurev.en.22.010177.000245
   Rogers C. E, 1980, TEX AGR EXP STA MISC, V1457, P30
   ROGERS CE, 1982, ENVIRON ENTOMOL, V11, P154, DOI 10.1093/ee/11.1.154
   ROGERS CE, 1979, J ECON ENTOMOL, V72, P529, DOI 10.1093/jee/72.4.529
   SAS Institute, 1990, SAS STAT US GUID VER
   SCHULZ JT, 1978, AGRON SER AM SOC AGR, V19, P505
   [No title captured]
NR 34
TC 11
Z9 11
U1 1
U2 5
PU KLUWER ACADEMIC PUBL
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 1386-6141
J9 BIOCONTROL
JI Biocontrol
PD OCT
PY 2002
VL 47
IS 5
BP 513
EP 523
DI 10.1023/A:1016567930895
PG 11
WC Entomology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Entomology
GA 578RZ
UT WOS:000177133900003
DA 2025-01-10
ER

PT J
AU Liu, GX
   Xiang, AC
   Wan, ZW
   Zhang, LQ
   Wu, J
   Xie, Z
AF Liu, Guangxu
   Xiang, Aicun
   Wan, Zhiwei
   Zhang, Longqi
   Wu, Jie
   Xie, Zheng
TI Quantitative characterization, spatiotemporal evolution, and analysis of
   driving factors of daily dry-wet abrupt alternation: A case study of the
   Ganjiang River Basin
SO JOURNAL OF HYDROLOGY-REGIONAL STUDIES
LA English
DT Article
DE Dry-Wet Abrupt Alternation; Quantitative characterization;
   Spatiotemporal evolution characteristics; Extreme precipitation; The
   Ganjiang River Basin
ID CIRCULATION; ENSO; PRECIPITATION; DROUGHT; CHINA; PART
AB Study Region: This study focuses on the Ganjiang River Basin, a major tributary of the Poyang Lake located in southern China. Study Focus: With the growing frequency of extreme weather events driven by climate change, there is increased attention on compound disasters such as Dry-Wet Abrupt Alternation (DWAA). This study aims to quantify and define DWAA in the Ganjiang River Basin by developing and applying a DWAA Index (DWAAI) using a percentile threshold method. The objective is to investigate the spatiotemporal characteristics and patterns of DWAA in the region. Precipitation data from 12 meteorological stations were analyzed to track these events from 1970 to 2019. New Hydrological Insights For the region: The results of this study provide new insights into DWAA dynamics in the Ganjiang River Basin. Key findings include: (i) The DWAAI effectively captures the extremes of Dry-Wet Abrupt Alternations, especially at the 1st and 99th percentiles; (ii) The basin experienced 37-48 dry-to-wet events (DtWs) during the study period, with higher frequencies observed in the central-eastern, western, and northern mountainous areas, and lower frequencies in the southern regions; (iii) Wet-to-dry events (WtDs) were less common than DtWs and exhibited a distinct spatial and temporal shift from the southern mountains toward the central basin; (iv) Temperature was identified as the dominant factor influencing DWAAI changes, while large-scale atmospheric patterns such as AO, ENSO, PDO, and Sunspot activity showed insignificant correlations. These findings offer critical insights for improving water resource management and climate adaptation efforts in the region.
C1 [Liu, Guangxu; Xiang, Aicun; Wan, Zhiwei; Wu, Jie; Xie, Zheng] Gannan Normal Univ, Sch Geog & Environm Engn, Ganzhou 341000, Peoples R China.
   [Zhang, Longqi] Changsha Univ Sci & Technol, Sch Traff & Transportat Engn, Changsha, Peoples R China.
   [Zhang, Longqi] Changsha Univ Technol, Survey & Mapping Remote Sensing Lab, Changsha, Peoples R China.
C3 Gannan Normal University; Changsha University of Science & Technology
RP Liu, GX (corresponding author), Gannan Normal Univ, Sch Geog & Environm Engn, Ganzhou 341000, Peoples R China.
EM liuguangxu@gnnu.edu.cn
FU Jiangxi Province Social Science Planning Project [23GL19]; Humanities
   and Social Science Research Planning Project for Universities of Jiangxi
   Province [GL20116]; Science and Technology Project of Jiangxi Department
   of Education [GJJ201419]; National Natural Science Foundation of China
   [42361011]
FX This study was financially supported by the Jiangxi Province Social
   Science Planning Project, grant number 23GL19; the Humanities and Social
   Science Research Planning Project for Universities of Jiangxi Province,
   grant number GL20116; Science and Technology Project of Jiangxi
   Department of Education, grant number GJJ201419; and National Natural
   Science Foundation of China, grant number 42361011.
CR Ahmad I, 2015, ADV METEOROL, V2015, DOI 10.1155/2015/431860
   [Anonymous], 2014, A Chronicle of Permutation Statistical Methods
   Ansari R, 2022, NAT HAZARD EARTH SYS, V22, P287, DOI 10.5194/nhess-22-287-2022
   Bai XY, 2023, FRONT EARTH SC-SWITZ, V11, DOI 10.3389/feart.2023.1203603
   Barbu N, 2016, THEOR APPL CLIMATOL, V126, P273, DOI 10.1007/s00704-015-1579-7
   Cai Z., 2013, J. Nat. Disasters, V2, P144
   Cañón J, 2007, J HYDROL, V333, P252, DOI 10.1016/j.jhydrol.2006.08.015
   Casmir Chidiebere O., 2015, SCI J APPL MATH STAT, V3, P165, DOI [10.11648/j.sjams.20150303.20, DOI 10.11648/J.SJAMS.20150303.20]
   Cazelles B, 2008, OECOLOGIA, V156, P287, DOI 10.1007/s00442-008-0993-2
   Chinanews, 2022, Drought disaster has affected 4.814 million people in Jiangxi, and more than 200,000 people need living assistance due to drought
   Chui C.K., 1992, An Introduction to Wavelets
   Dai AG, 2018, CURR CLIM CHANGE REP, V4, P301, DOI 10.1007/s40641-018-0101-6
   DAleo J., 2016, Evidence-Based Climate Science, P263
   Daubechies I, 1992, 10 LECT WAVELETS
   Gallegati M, 2018, CLIMATIC CHANGE, V148, P325, DOI 10.1007/s10584-018-2172-8
   Gershunov A, 1998, B AM METEOROL SOC, V79, P2715, DOI 10.1175/1520-0477(1998)079<2715:IMOET>2.0.CO;2
   Gong L, 2023, ANTHROPOCENE, V41, DOI 10.1016/j.ancene.2023.100368
   He J., 2006, Chin. Sci. Bull., V51, P1717
   Held IM, 2006, J CLIMATE, V19, P5686, DOI 10.1175/JCLI3990.1
   Hu YiHong Hu YiHong, 2017, Transactions of the Chinese Society of Agricultural Engineering, V33, P107
   Jian H., 2021, Water Resour. Power, V39, P6
   [金凯 Jin Kai], 2020, [地理学报, Acta Geographica Sinica], V75, P961
   Li TR, 2015, J TROP METEOROL, V21, P161
   Liu F, 2017, GEOMORPHOLOGY, V293, P24, DOI 10.1016/j.geomorph.2017.05.007
   Liu W., 2003, Further modifications to the Palmer drought model and its applications
   Lu E, 2009, GEOPHYS RES LETT, V36, DOI 10.1029/2009GL038817
   Lu XR, 2018, WATER-SUI, V10, DOI 10.3390/w10070887
   Ma ZG, 2007, CHINESE SCI BULL, V52, P2130, DOI 10.1007/s11434-007-0284-z
   Maheras P, 1999, THEOR APPL CLIMATOL, V64, P189, DOI 10.1007/s007040050122
   Mallat S., 1999, A wavelet tour of signal processing
   McKenna CM, 2022, GEOPHYS RES LETT, V49, DOI 10.1029/2022GL099083
   Meyer Y., 1993, Phila. Soc. Ind. Appl. Math.
   MORLET J, 1982, GEOPHYSICS, V47, P203, DOI 10.1190/1.1441328
   NOAA, 2023, Products By Category
   [潘静 Pan Jing], 2010, [气象科学, Scientia Meteorologlca Sinica], V30, P574
   Peng Y, 2022, REG ENVIRON CHANGE, V22, DOI 10.1007/s10113-022-01936-w
   Rezvani R, 2023, J HYDROL, V624, DOI 10.1016/j.jhydrol.2023.129906
   Rimbu N, 2021, INT J CLIMATOL, V41, pE644, DOI 10.1002/joc.6715
   Shan LJ, 2018, J GEOGR SCI, V28, P1039, DOI 10.1007/s11442-018-1540-7
   Shen BZ, 2012, ACTA PHYS SIN-CH ED, V61, DOI 10.7498/aps.61.109202
   Shi WZ, 2021, J HYDROL, V597, DOI 10.1016/j.jhydrol.2021.126179
   SILSO, 2023, Sunspot Index and Long-term Solar Observations
   Sun P., 2012, Pearl River, V33, P29
   [孙卫国 Sun Weiguo], 2008, [应用气象学报, Journal of Applied Meteorolgical Science], V19, P479
   Tao X. e, 2019, Ecol. Environ. Monit. Three Gorges, V4, P52
   Thompson DWJ, 2000, J CLIMATE, V13, P1000, DOI 10.1175/1520-0442(2000)013<1018:AMITEC>2.0.CO;2
   Trenberth KE, 2011, CLIM RES, V47, P123, DOI 10.3354/cr00953
   [王胜 WANF Sheng], 2009, [中国农业气象, Chinese Journal of Agrometeorology], V30, P31
   [王春林 Wang Chunlin], 2012, [气候变化研究进展, Progressus Inquisitiones de Mutatione Climatis], V8, P157
   [王岱 Wang Dai], 2020, [气候变化研究进展, Progressus Inquisitiones de Mutatione Climatis], V16, P70
   Wang J., 2013, Encyclopedia of Systems Biology, P1634
   [王璐璐 Wang Lulu], 2016, [中山大学学报. 自然科学版, Acta Scientiarum Naturalium Universitatis Sunyatseni], V55, P123
   Wang X., 2006, Research on dry and wet climate transition in Northwest China
   Wang Y., 2019, JILIN PROV WATER CON, V11, P55
   [杨家伟 Yang Jiawei], 2019, [地理学报, Acta Geographica Sinica], V74, P2358
   Zhang Shuifeng, 2012, Hupo Kexue, V24, P679
   [张雯 Zhang Wen], 2020, [大气科学, Chinese Journal of Atmospheric Sciences], V44, P390
NR 57
TC 0
Z9 0
U1 20
U2 20
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 DEC
PY 2024
VL 56
AR 102030
DI 10.1016/j.ejrh.2024.102030
PG 15
WC Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Water Resources
GA K4T5N
UT WOS:001343816800001
OA gold
DA 2025-01-10
ER

PT J
AU Zhang, WC
   Wu, W
   Liu, HB
AF Zhang, Wei-Chun
   Wu, Wei
   Liu, Hong-Bin
TI Planting Year- and Climate-Controlled Soil Aggregate Stability and Soil
   Fertility in the Karst Region of Southwest China
SO AGRONOMY-BASEL
LA English
DT Article
DE soil fertility index; water stable aggregates; long-term monocropping
   system; fertilization
ID ORGANIC-CARBON; INDICATORS; AMENDMENT
AB The effects of long-term monocropping systems combined with climate on soil water aggregate stability (WSA) and soil fertility in the karst region of Southwest China (KRSWC) are unclear. Our research was conducted in the KRSWC, wherein tobacco (Nicotiana tabacum) production is characterized by heavy fertilization and continuous monocropping. The tobacco fields in the study area have similar soil types and fertilization and tillage practices and are spread over an area of 11,500 km2. A total of 568 topsoil samples were collected in 2021. Soil fertility was reflected using the soil fertility index (SFI), which was calculated using the minimum data set method with six soil fertility-related factors, namely, soil pH, soil organic matter, cation exchange capacity, available nitrogen, available phosphorus, and available potassium. Results showed that long-term planting generally promoted soil fertility levels and WSA content. WSA and SFI had inconsistent spatial distribution patterns likely due to different climate-driven effects. WSA variability was greatly controlled by precipitation (Spearman correlation coefficient [r] = -0.49, p < 0.01), whereas SFI variability was mostly dominated by temperature (r = -0.36, p < 0.01). The levels of SFI and WSA were optimal under conditions of low temperature and precipitation and poor under conditions of high temperature and precipitation. Moreover, long-term planting could alleviate the negative effects of climate on SFI and WSA in the KRSWC. The results of this study could provide valuable information on fertilization and climate-adapted strategies for tobacco fields in the KRSWC.
C1 [Zhang, Wei-Chun; Liu, Hong-Bin] Southwest Univ, Coll Resources & Environm, Chongqing 400716, Peoples R China.
   [Wu, Wei] Southwest Univ, Coll Comp & Informat Sci, Chongqing 400716, Peoples R China.
C3 Southwest University - China; Southwest University - China
RP Liu, HB (corresponding author), Southwest Univ, Coll Resources & Environm, Chongqing 400716, Peoples R China.
EM zhang_weichun1996@163.com; wuwei_star@163.com; lhbin@swu.edu.cn
OI Liu, HongBin/0000-0002-3892-1636
FU Chongqing Key Laboratory of Digital Agriculture (China)
FX We thank the local farmers for their help during the sample collection.
CR Abdi H, 2010, WIRES COMPUT STAT, V2, P433, DOI 10.1002/wics.101
   Amézketa E, 1999, J SUSTAIN AGR, V14, P83, DOI 10.1300/J064v14n02_08
   [Anonymous], 2016, DZ/T 0295-2016, P1
   ANSELIN L, 1995, GEOGR ANAL, V27, P93, DOI 10.1111/j.1538-4632.1995.tb00338.x
   Ballabio C, 2019, GEODERMA, V355, DOI 10.1016/j.geoderma.2019.113912
   Bashir MA, 2022, J INTEGR AGR, V21, P3356, DOI 10.1016/j.jia.2022.08.062
   Bronick CJ, 2005, GEODERMA, V124, P3, DOI 10.1016/j.geoderma.2004.03.005
   Chen J, 2020, INT J AGRIC BIOL, V24, P645, DOI 10.17957/IJAB/15.1481
   Chen P, 2023, PLANT SOIL, DOI 10.1007/s11104-023-05973-0
   Chen YJ, 2020, J SOIL SCI PLANT NUT, V20, P192, DOI 10.1007/s42729-019-00118-8
   Chinese National Soil Survey Office (CNSSO), 1997, China Soil Data from Census
   Dai PG, 2021, AGRONOMY-BASEL, V11, DOI 10.3390/agronomy11112135
   Sá JCD, 2009, SOIL TILL RES, V104, P56, DOI 10.1016/j.still.2008.11.007
   DORAN JW, 1994, SSSA SPEC PUBL, P3
   He C, 2022, APPL SOIL ECOL, V174, DOI 10.1016/j.apsoil.2022.104397
   Hobley E, 2015, PLANT SOIL, V390, P111, DOI 10.1007/s11104-015-2380-1
   Hu TW, 2010, TOB CONTROL, V19, P58, DOI 10.1136/tc.2009.031799
   Institute of Soil Science Chinese Academy of Sciences (ISSCAS), 1978, Physical and Chemical Analysis Methods of Soils, P7
   Jenny H., 1941, Factors of Soil Formation: A System of Quantitative Pedology, DOI 10.1097/00010694-194111000-00009
   Jin HF, 2021, ECOL INDIC, V130, DOI 10.1016/j.ecolind.2021.108013
   Jobbágy EG, 2000, ECOL APPL, V10, P423, DOI 10.2307/2641104
   Kemper W.D., 1965, Methods of soil analysis, V9th, P499, DOI [DOI 10.2134/AGRONMONOGR9.1.C39, 10.2134/agronmonogr9.1.c39]
   Le Bissonnais Y, 2016, EUR J SOIL SCI, V67, P11, DOI 10.1111/ejss.4_12311
   Li P, 2021, GEODERMA, V403, DOI 10.1016/j.geoderma.2021.115197
   Li YJ, 2023, SCI TOTAL ENVIRON, V892, DOI 10.1016/j.scitotenv.2023.164649
   Liu FT, 2021, SCI TOTAL ENVIRON, V794, DOI 10.1016/j.scitotenv.2021.148795
   Ma R, 2022, J CLEAN PROD, V369, DOI 10.1016/j.jclepro.2022.133305
   Plaza C, 2016, AGR ECOSYST ENVIRON, V225, P150, DOI 10.1016/j.agee.2016.04.014
   Qi YB, 2009, GEODERMA, V149, P325, DOI 10.1016/j.geoderma.2008.12.015
   Qu MK, 2013, SOIL SCI SOC AM J, V77, P2182, DOI 10.2136/sssaj2013.05.0177
   Ramos MF, 2022, SOIL TILL RES, V219, DOI 10.1016/j.still.2022.105324
   Rezácová V, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-91653-x
   Singh S, 2022, CHEMOSPHERE, V287, DOI 10.1016/j.chemosphere.2021.131889
   Singh S, 2019, GEODERMA REG, V18, DOI 10.1016/j.geodrs.2019.e00233
   Six J, 2004, SOIL TILL RES, V79, P7, DOI 10.1016/j.still.2004.03.008
   Song XD, 2020, GEODERMA, V363, DOI 10.1016/j.geoderma.2019.114145
   Su Y, 2022, FRONT MICROBIOL, V13, DOI 10.3389/fmicb.2022.818956
   Thomaz E, 2022, ARCH AGRON SOIL SCI, V68, P719, DOI 10.1080/03650340.2020.1852550
   Wang KL, 2019, LANDSCAPE ECOL, V34, P2743, DOI 10.1007/s10980-019-00912-w
   Wang SQ, 2020, CATENA, V191, DOI 10.1016/j.catena.2020.104578
   Wang T, 2023, REMOTE SENS-BASEL, V15, DOI 10.3390/rs15082118
   Wiesmeier M, 2019, GEODERMA, V333, P149, DOI 10.1016/j.geoderma.2018.07.026
   Wilding L. P., 1985, Soil spatial variability, P166
   Wu K, 2014, BIOL FERT SOILS, V50, P961, DOI 10.1007/s00374-014-0916-9
   Wu RJ, 2023, SOIL USE MANAGE, V39, P1109, DOI 10.1111/sum.12926
   Ye LP, 2019, SOIL TILL RES, V192, P1, DOI 10.1016/j.still.2019.03.009
   Ye LP, 2018, SOIL TILL RES, V179, P71, DOI 10.1016/j.still.2018.01.012
   Zeraatpisheh M, 2021, GEODERMA REG, V27, DOI 10.1016/j.geodrs.2021.e00440
   Zhang S, 2022, PLANT SOIL, V481, P63, DOI 10.1007/s11104-022-05616-w
   Zhang WC, 2023, CATENA, V228, DOI 10.1016/j.catena.2023.107170
   Zhang YT, 2016, ENVIRON SCI POLLUT R, V23, P5442, DOI 10.1007/s11356-015-5673-2
   Zheng XB, 2020, J SOIL SCI PLANT NUT, V20, P293, DOI 10.1007/s42729-019-00108-w
   Zou CM, 2018, GEODERMA, V325, P49, DOI 10.1016/j.geoderma.2018.03.017
NR 53
TC 3
Z9 3
U1 4
U2 17
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4395
J9 AGRONOMY-BASEL
JI Agronomy-Basel
PD DEC
PY 2023
VL 13
IS 12
AR 2962
DI 10.3390/agronomy13122962
PG 14
WC Agronomy; Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Plant Sciences
GA DL5Z3
UT WOS:001132224300001
OA gold
DA 2025-01-10
ER

PT J
AU Schünemann, C
   Ziemann, A
   Goldberg, V
AF Schuenemann, Christoph
   Ziemann, Astrid
   Goldberg, Valeri
TI Spatially resolved indoor overheating evaluation using microscale
   meteorological simulation as input for building simulation -
   opportunities and limitations
SO CITY AND ENVIRONMENT INTERACTIONS
LA English
DT Article
DE Toolchain; Urban microscale meteorological simulation; Building
   performance simulation; Heat stress; Climate adaptation; Overheating
   assessment
ID ATMOSPHERIC BOUNDARY-LAYER; THERMAL COMFORT; SOIL-WATER; URBAN; CLIMATE;
   SURFACE; IMPACT; RISK; CITY
AB To assess the spatial heat resilience of buildings in urban development we test the suitability of a toolchain approach from microscale meteorological simulations, resolving the spatial influences on local urban climate, to building performance simulations, evaluating the indoor overheating risk in buildings. This approach makes it possible to investigate how much microscale effects (e.g. buildings, trees e.g. roads) in open space influence the overheating intensity in a building depending on its location within a district. In this context, the question arises how realistic the microscale meteorological simulation is to be used as input for indoor overheating evaluation. In this context, we applied a 3D urban climate model (ENVI-met) and a 1D boundary layer model (HIRVAC) for two urban districts in Germany as meteorological input for an indoor thermal comfort evaluation of two representative buildings. The results demonstrate that ENVI-met simulations without using measured temperature data create unrealistically low diurnal variations in outdoor air temperature despite an overestimated solar irradiance. The implementation to building simulation leads to a significant underestimation of the heat resilience for both buildings and to wrong conclusions about the efficacy of passive heat adaptation measures. In contrast, the HIRVACsimulations show a more realistic representation of the meteorological variables (when measured data is used for calibration) but are not able to resolve urban 3D structures. Our findings point out that an adjusted boundary layer representation in microscale meteorological simulations is crucial to provide meteorological input suitable for realistic spatially resolved indoor overheating analysis.
C1 [Schuenemann, Christoph] Leibniz Inst Ecol Urban & Reg Dev, Weberpl 1, D-01217 Dresden, Germany.
   [Ziemann, Astrid; Goldberg, Valeri] Tech Univ Dresden, Chair Meteorol, Pienner Str 23, D-01737 Tharandt, Germany.
C3 Leibniz Institut fur okologische Raumentwicklung; Technische Universitat
   Dresden
RP Schünemann, C (corresponding author), Leibniz Inst Ecol Urban & Reg Dev, Weberpl 1, D-01217 Dresden, Germany.
EM c.schuenemann@ioer.de
OI Ziemann, Astrid/0000-0002-6686-3736; Schunemann,
   Christoph/0000-0002-1214-8593; Goldberg, Valeri/0000-0002-9477-1652
FU Federal Ministry of Education and Research (BMBF) [01LR1724A,
   01LR1724D]; Leibniz Institute of Ecological and Regional Development
   (IOER)
FX This research was mainly funded by the Federal Ministry of Education and
   Research (BMBF) in the joint project "HeatResilientCity" (subproject
   grant number: 01LR1724A and 01LR1724D) . The promoter of this project is
   the DLR project management agency (DLR-PT) . In addition, the study was
   carried out with basic funding from the Leibniz Institute of Ecological
   and Regional Development (IOER) within the scope of the project
   "Heat-Resilient Buildings-interaction of heat adaptation measures in
   buildings and open space, indicator-based overheating assessment,
   implementation dynamics and health aspects".
CR Ali-Toudert F, 2006, BUILD ENVIRON, V41, P94, DOI 10.1016/j.buildenv.2005.01.013
   [Anonymous], 2021, DIN-EN-16798-1
   [Anonymous], 2007, EN_15242
   Baums AB, 2005, METEOROL Z, V14, P211, DOI 10.1127/0941-2948/2005/0024
   Berardi U, 2020, SCI TOTAL ENVIRON, V747, DOI 10.1016/j.scitotenv.2020.141300
   Brotas L, 2017, ARCHIT SCI REV, V60, P180, DOI 10.1080/00038628.2017.1300762
   Bruse M, 1998, ENVIRON MODELL SOFTW, V13, P373, DOI 10.1016/S1364-8152(98)00042-5
   DWD, 2020, Climate Data Center DWD
   Emmanuel R, 2007, INT J CLIMATOL, V27, P1995, DOI 10.1002/joc.1609
   EQUA, 2018, IDA Indoor Climate and Energy 4.8 SP1
   Fahmy M, 2011, BUILD SERV ENG RES T, V32, P73, DOI 10.1177/0143624410394536
   Fischer B, 2008, ECOL MODEL, V214, P75, DOI 10.1016/j.ecolmodel.2008.02.037
   Franck U, 2013, Meteorologische Zeitschrift (Berlin), P22
   Gamero-Salinas JC, 2020, BUILD ENVIRON, V171, DOI 10.1016/j.buildenv.2020.106664
   Goldberg V, 2001, ANN GEOPHYS, V19, P581, DOI 10.5194/angeo-19-581-2001
   Goldberg V, 2013, METEOROL Z, V22, P739, DOI 10.1127/0941-2948/2013/0463
   Hamdy M, 2017, BUILD ENVIRON, V122, P307, DOI 10.1016/j.buildenv.2017.06.031
   Head K, Report of the systematic review on the effect of indoor heat on health (WHO Housing and health guidelines-Web Annex D)
   Huttner S., 2012, Further development and application of the 3D microclimate simulation ENVI-met
   Jenkins DP, 2011, ENERG BUILDINGS, V43, P1723, DOI 10.1016/j.enbuild.2011.03.016
   Katzschner L, 2011, Urban Climate Strategies Against Future Heat Stress Conditions
   Kunze S, 2020, P 26 INT SUST DEV RE
   Laouadi A, 2020, J BUILD PERFORM SIMU, V13, P301, DOI 10.1080/19401493.2020.1727954
   Liu ZX, 2021, BUILD ENVIRON, V200, DOI 10.1016/j.buildenv.2021.107939
   Liu ZX, 2018, ATMOSPHERE-BASEL, V9, DOI 10.3390/atmos9050198
   Lomas KJ, 2017, BUILD RES INF, V45, P1, DOI 10.1080/09613218.2017.1256136
   Manoli G, 2019, NATURE, V573, P55, DOI 10.1038/s41586-019-1512-9
   Mavrogianni A, 2015, BUILD RES INF, V43, P316, DOI 10.1080/09613218.2015.991515
   Mix W., 1994, METEOROL Z, V3, P187, DOI 10.1127/metz/3/1994/187
   Mohajerani A, 2017, J ENVIRON MANAGE, V197, P522, DOI 10.1016/j.jenvman.2017.03.095
   Mourkos K, 2020, BUILD ENVIRON, V181, DOI 10.1016/j.buildenv.2020.107070
   Pacifici M, 2019, Dissertation (PhD of Science)
   Petrou G, 2019, BUILD SERV ENG RES T, V40, P492, DOI 10.1177/0143624419847621
   Roberts B, 2019, BUILD SERV ENG RES T, V40, P512, DOI 10.1177/0143624419847349
   Santamouris M, 2020, ENERG BUILDINGS, V207, DOI 10.1016/j.enbuild.2019.109482
   Schiela D, 2021, INT J BUILT ENV SUST, V8, P121, DOI 10.11113/ijbes.v8.n3.852
   Schünemann C, 2022, INT J ENERGY ENVIR E, V13, P889, DOI 10.1007/s40095-022-00476-7
   Schünemann C, 2021, BUILDINGS-BASEL, V11, DOI 10.3390/buildings11060242
   Schünemann C, 2020, BUILD CITIES, V1, P36, DOI 10.5334/bc.12
   Schunemann C, 2020, P 26 INT SUST DEV RE
   Schunemann C, P IABSE S WROCL 2020
   Schünemann C, 2021, BUILD ENVIRON, V202, DOI 10.1016/j.buildenv.2021.107987
   Simon H., C PASS LOW EN ARCH P
   Soutullo S, 2020, ENERGIES, V13, DOI 10.3390/en13010237
   Steeneveld GJ, 2011, J GEOPHYS RES-ATMOS, V116, DOI 10.1029/2011JD015988
   Taylor J, 2014, BUILD ENVIRON, V76, P81, DOI 10.1016/j.buildenv.2014.03.010
   Toparlar Y, 2017, RENEW SUST ENERG REV, V80, P1613, DOI 10.1016/j.rser.2017.05.248
   Toulemon L, 2008, POP STUD-J DEMOG, V62, P39, DOI 10.1080/00324720701804249
   VDI2078, 2015, VDI 2078
   Vellei M, 2016, P 9 WINDSOR C MAK CO
   Vieira CB, 2018, CHEMENGINEERING, V2, DOI 10.3390/chemengineering2010012
   YAMADA T, 1975, J ATMOS SCI, V32, P2309, DOI 10.1175/1520-0469(1975)032<2309:ASOTWA>2.0.CO;2
   Ziemann A, 1998, METEOROL Z, V7, P120, DOI 10.1127/metz/7/1998/120
   Zuvela-Aloise M, 2016, CLIMATIC CHANGE, V135, P425, DOI 10.1007/s10584-016-1596-2
NR 54
TC 1
Z9 1
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 DEC
PY 2023
VL 20
AR 100122
DI 10.1016/j.cacint.2023.100122
EA OCT 2023
PG 16
WC Environmental Sciences; Environmental Studies; Meteorology & Atmospheric
   Sciences
WE Emerging Sources Citation Index (ESCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA W8XD7
UT WOS:001094394500001
OA gold
DA 2025-01-10
ER

PT J
AU Wang, MQ
   Liang, SF
   Zhao, SL
   Gao, W
   Li, ZQ
AF Wang, Muqun
   Liang, Shaofeng
   Zhao, Shuangliang
   Gao, Wei
   Li, Zequan
TI Facile Preparation of a Low-Cost Liquid Interlayer Material with
   Intelligent UV-NIR-Shielding Function for Smart Windows
SO ACS APPLIED MATERIALS & INTERFACES
LA English
DT Article
DE smart materials; optical properties; carbondots; UV-NIR shielding
ID CARBON DOTS; HYDROGEL; LUMINESCENCE; COMPOSITE; EMISSION; BLOCKING;
   BEHAVIOR; WATER; RED
AB High-performance interlayer materials have garnered considerable interest owing to their low manufacturing costs and applicability in smart windows. In this study, a novel smart-window interlayer material capable of selective shielding against both near-infrared (NIR) and ultraviolet (UV) radiation is developed based on the light transmittance control mechanism. An excellent thermoresponsive liquid, denoted as CDs@TRL (viz., carbon quantum dots at thermal-responsive liquid), is synthesized by compositing biomass-based fluorescent carbon quantum dots (CDs) and poly(N-isopropylacrylamide) (pNIPAM) at natural ambient temperature and in an aqueous phase. Due to the characteristics of CDs and synergistic effect of hydrogen bonds, CDs@TRL exhibits a high specific heat capacity (4.41 kJ kg(-1) K-1), large thermal storage capacity (264.6 kJ kg(-1)), and better UV-NIR-blocking properties, compared to pure pNIPAM, as well as improves the sensitivity of thermal response. When injected into a window as a liquid interlayer, CDs@TRL can intelligently adjust the light transmittance according to ambient light intensity to achieve an intelligent response. The shielding rate of a 10 mm-thick CDs@TRL composite liquid against UV radiation (200-400 nm) was more than 95% in an overcast environment with insufficient light and close to 100% in a well-lighted environment. In addition, CDs@TRL is a cost-effective material that can be prepared from a wide range of raw material sources using a simple preparation process and exhibits excellent mobility and recyclability. Because of these features, it is considered to be a promising candidate for developing energy-saving and climate-adapted smart windows.
C1 [Wang, Muqun; Liang, Shaofeng; Zhao, Shuangliang; Gao, Wei; Li, Zequan] Guangxi Univ, State Key Lab Featured Met Mat & Life Cycle Safet, Nanning 530004, Peoples R China.
   [Wang, Muqun; Liang, Shaofeng; Zhao, Shuangliang; Gao, Wei; Li, Zequan] Guangxi Engn & Technol Res Ctr High Qual Struct P, Nanning 530004, Guangxi, Peoples R China.
   [Wang, Muqun] Guangxi Univ, Sch Civil Engn & Architecture, Nanning 530004, Guangxi, Peoples R China.
   [Liang, Shaofeng; Gao, Wei; Li, Zequan] Guangxi Univ, Sch Resources Environm & Mat, Nanning 530004, Guangxi, Peoples R China.
   [Zhao, Shuangliang] Guangxi Univ, Coll Chem & Chem Engn, Nanning 530004, Guangxi, Peoples R China.
C3 Guangxi University; Guangxi University; Guangxi University; Guangxi
   University
RP Zhao, SL; Gao, W (corresponding author), Guangxi Univ, State Key Lab Featured Met Mat & Life Cycle Safet, Nanning 530004, Peoples R China.; Zhao, SL; Gao, W (corresponding author), Guangxi Engn & Technol Res Ctr High Qual Struct P, Nanning 530004, Guangxi, Peoples R China.; Gao, W (corresponding author), Guangxi Univ, Sch Resources Environm & Mat, Nanning 530004, Guangxi, Peoples R China.; Zhao, SL (corresponding author), Guangxi Univ, Coll Chem & Chem Engn, Nanning 530004, Guangxi, Peoples R China.
EM szhao@gxu.edu.cn; galaxy@gxu.edu.cn
RI Gao, Wei/AAQ-8992-2021; Li, Zequan/JDW-8193-2023; Zhao,
   Shuangliang/KBD-1515-2024; Zhao, Shuangliang/B-6139-2017
OI Zhao, Shuangliang/0000-0002-9547-4860; Liu, Haibo/0000-0002-4213-2883;
   Gao, Wei/0000-0002-4353-6599
FU Natural Science Foundation of China [21878078]; Key R&D projects in
   Guangxi [AB22080040, AB21196033]; Guangxi Science and Technology Program
   [AD23026201]; Industry-university Research Cooperation Fund of Guangxi
   Hongkai Furniture Co., Ltd [20200782]; Guangxi University [20200782]
FX This work was financially supported by the Natural Science Foundation of
   China (no. 21878078), the Key R&D projects in Guangxi (AB22080040), the
   Guangxi Science and Technology Program (AD23026201), Industry-university
   Research Cooperation Fund of Guangxi Hongkai Furniture Co., Ltd &
   Guangxi University (20200782), and the Key R&D projects in Guangxi
   (AB21196033).
CR Baker SN, 2010, ANGEW CHEM INT EDIT, V49, P6726, DOI 10.1002/anie.200906623
   Barman BK, 2020, APPL SURF SCI, V510, DOI 10.1016/j.apsusc.2020.145405
   Cao D, 2018, SOL RRL, V2, DOI 10.1002/solr.201700219
   Casini M, 2018, RENEW ENERG, V119, P923, DOI 10.1016/j.renene.2017.12.049
   Cayuela A, 2015, SENSOR ACTUAT B-CHEM, V207, P596, DOI 10.1016/j.snb.2014.10.102
   Cheng CY, 2021, NANO ENERGY, V90, DOI 10.1016/j.nanoen.2021.106575
   Chun SY, 2021, NANO ENERGY, V82, DOI 10.1016/j.nanoen.2020.105721
   Cui YY, 2018, JOULE, V2, P1707, DOI 10.1016/j.joule.2018.06.018
   Ding H, 2016, ACS NANO, V10, P484, DOI 10.1021/acsnano.5b05406
   Eskalen H, 2020, IND CROP PROD, V147, DOI 10.1016/j.indcrop.2020.112209
   Feng X, 2017, CARBOHYD POLYM, V161, P253, DOI 10.1016/j.carbpol.2017.01.030
   Hess SC, 2017, J MATER CHEM A, V5, P5187, DOI 10.1039/c7ta00397h
   Hu RX, 2017, CARBON, V111, P133, DOI 10.1016/j.carbon.2016.09.038
   Hu YW, 2019, CARBON, V152, P511, DOI 10.1016/j.carbon.2019.06.047
   Huang QS, 2022, POLYM CHEM-UK, V13, P2178, DOI 10.1039/d1py01657a
   Jain K, 2015, POLYM CHEM-UK, V6, P6819, DOI 10.1039/c5py00998g
   Jiang K, 2015, ANGEW CHEM INT EDIT, V54, P5360, DOI 10.1002/anie.201501193
   KERR RA, 1992, SCIENCE, V255, P797, DOI 10.1126/science.255.5046.797
   Kim HN, 2020, ADV FUNCT MATER, V30, DOI 10.1002/adfm.201902597
   Kim KW, 2020, NPG ASIA MATER, V12, DOI 10.1038/s41427-020-00257-w
   Kreuzer LP, 2021, LANGMUIR, V37, P9179, DOI 10.1021/acs.langmuir.1c01342
   Kreuzer LP, 2020, MACROMOLECULES, V53, P2841, DOI 10.1021/acs.macromol.0c00046
   Lei H, 2019, J MATER CHEM A, V7, P6720, DOI 10.1039/c8ta11753e
   Li D, 2021, ACS APPL MATER INTER, V13, P61196, DOI 10.1021/acsami.1c19273
   Li JN, 2021, ADV FUNCT MATER, V31, DOI 10.1002/adfm.202102350
   Li KM, 2020, ACS APPL MATER INTER, V12, P42193, DOI 10.1021/acsami.0c12710
   Li XH, 2019, JOULE, V3, P290, DOI 10.1016/j.joule.2018.10.019
   Liang SF, 2021, CARBON TRENDS, V4, DOI 10.1016/j.cartre.2021.100063
   Liang X, 2018, J MATER CHEM C, V6, P7054, DOI 10.1039/c8tc01274a
   Liu S, 2021, APPL ENERG, V297, DOI 10.1016/j.apenergy.2021.117207
   Ma YS, 2019, CHEM ENG J, V374, P787, DOI 10.1016/j.cej.2019.06.016
   Oh SW, 2021, ACS APPL MATER INTER, V13, P5028, DOI 10.1021/acsami.0c19015
   Owusu-Nkwantabisah S, 2017, MACROMOLECULES, V50, P3671, DOI 10.1021/acs.macromol.7b00355
   Panagiotidou M, 2021, SOL ENERGY, V230, P675, DOI 10.1016/j.solener.2021.10.060
   Piper SL, 2022, GREEN CHEM, V24, P102, DOI 10.1039/d1gc03420k
   Shi Y, 2015, ADV FUNCT MATER, V25, P1219, DOI 10.1002/adfm.201404247
   Silverstein KAT, 2000, J AM CHEM SOC, V122, P8037, DOI 10.1021/ja000459t
   Smith AT, 2020, MATTER-US, V2, P680, DOI 10.1016/j.matt.2019.12.006
   Song XY, 2019, MACROMOLECULES, V52, P3869, DOI 10.1021/acs.macromol.8b02323
   Tian J, 2015, NANO ENERGY, V11, P419, DOI 10.1016/j.nanoen.2014.10.025
   Tian J, 2021, COMPOS PART A-APPL S, V149, DOI 10.1016/j.compositesa.2021.106538
   Wang JL, 2021, NANO LETT, V21, P9976, DOI 10.1021/acs.nanolett.1c03438
   Wang SC, 2021, SCIENCE, V374, P1501, DOI 10.1126/science.abg0291
   Wang SC, 2018, APPL ENERG, V211, P200, DOI 10.1016/j.apenergy.2017.11.039
   Wang SN, 2022, COMPOS PART A-APPL S, V154, DOI 10.1016/j.compositesa.2021.106757
   Wang Y, 2020, IND ENG CHEM RES, V59, P21012, DOI 10.1021/acs.iecr.0c04029
   Wang Y, 2018, IND ENG CHEM RES, V57, P12801, DOI 10.1021/acs.iecr.8b02692
   Wu MC, 2018, ACS APPL MATER INTER, V10, P39819, DOI 10.1021/acsami.8b15574
   Yang CH, 2020, ADV OPT MATER, V8, DOI 10.1002/adom.201901536
   Yang J, 2021, ACS APPL MATER INTER, V13, P20689, DOI 10.1021/acsami.1c03085
   Yuan KJ, 2020, ADV FUNCT MATER, V30, DOI 10.1002/adfm.201904228
   Yue J, 2019, ACS APPL MATER INTER, V11, P44566, DOI 10.1021/acsami.9b13737
   Zhang SL, 2020, ADV MATER, V32, DOI 10.1002/adma.202004686
   Zhou Y, 2020, J MATER CHEM A, V8, P10007, DOI 10.1039/d0ta00849d
   Zhou Y, 2014, J MATER CHEM A, V2, P13550, DOI 10.1039/c4ta02287d
NR 55
TC 3
Z9 3
U1 15
U2 48
PU AMER CHEMICAL SOC
PI WASHINGTON
PA 1155 16TH ST, NW, WASHINGTON, DC 20036 USA
SN 1944-8244
EI 1944-8252
J9 ACS APPL MATER INTER
JI ACS Appl. Mater. Interfaces
PD OCT 3
PY 2023
VL 15
IS 41
BP 48673
EP 48682
DI 10.1021/acsami.3c10909
EA OCT 2023
PG 10
WC Nanoscience & Nanotechnology; Materials Science, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics; Materials Science
GA U1HU2
UT WOS:001077677600001
PM 37788155
DA 2025-01-10
ER

PT J
AU Torres, FC
   Almenar, JB
   Rugani, B
AF Torres, Francesco Cruz
   Almenar, Javier Babi
   Rugani, Benedetto
TI Photovoltaic-green roof energy communities can uphold the European Green
   Deal: Probabilistic cost-benefit analyses help discern economically
   convenient scenarios
SO JOURNAL OF CLEANER PRODUCTION
LA English
DT Article
DE Energy effi ciency; Exploratory modelling; Robust decision making;
   Scenario discovery; Uncertainty
ID PERFORMANCE; LIMITATIONS
AB The new roadmap of the European Union (EU), the European Green Deal, aims at tackling climate adaptation, energy, biodiversity, and pollution challenges. To contribute to such aim, the latest EU Renewable Energy Directive defines for the first time renewable energy communities. Among them, Photovoltaic-Green roof Energy Communities (PGECs) emerge as a potential option in urban areas. This paper investigates whether and under which conditions PGECs are capable to meet the objectives of the European Green Deal in an economically convenient manner. Since some conditions are context-specific, this research is showcased using a case study (Luxembourg). First, European legislation was reviewed to determine the suitable legal model for PGECs. Second, a systematic literature review helped identifying lifecycle costs and benefits of photovoltaic-green roofs and their value ranges. Third, a model for probabilistic social and private cost-benefit analyses was developed and tailored to Luxembourg. Lastly, Scenario Discovery was used to identify the ranges of input values leading to desirable net present values. Results show that PGECs can contribute to achieving multiple objectives of the European Green Deal in an economically convenient manner. From the societal perspective, PGECs are found to be economically convenient for any cost, benefit, and discount rate in the case study. From the private perspective, PGECs remain convenient in 62% of the scenarios, with green roofs' installation cost and electricity generation benefit playing pivotal roles. This paper presents a rare combination of probabilistic cost-benefit analyses and scenario discovery, It supports policymakers designing incentive schemes for PGECs, and can be replicated in other countries.
C1 [Torres, Francesco Cruz; Almenar, Javier Babi; Rugani, Benedetto] Luxembourg Inst Sci & Technol LIST, Environm Res & Innovat ERIN Dept, RDI Unit Environm Sustainabil Assessment & Circul, Maison Innovat, 5 Ave Hauts Fourneaux, L-4362 Esch sur Alzette, Luxembourg.
   [Torres, Francesco Cruz] Delft Univ Technol, Fac Technol Policy & Management, NL-2628 BX Delft, Netherlands.
   [Torres, Francesco Cruz] Politecn Milan, Dept Energy, I-20156 Milan, Italy.
   [Almenar, Javier Babi] Politecn Milan, Dept Elect Informat & Bioengn, I-20133 Milan, Italy.
C3 Luxembourg Institute of Science & Technology; Delft University of
   Technology; Polytechnic University of Milan; Polytechnic University of
   Milan
RP Torres, FC (corresponding author), Delft Univ Technol, Fac Technol Policy & Management, NL-2628 BX Delft, Netherlands.; Torres, FC (corresponding author), Politecn Milan, Dept Energy, I-20156 Milan, Italy.; Almenar, JB (corresponding author), Politecn Milan, Dept Elect Informat & Bioengn, I-20133 Milan, Italy.
EM francesco.cruz@polimi.it; javier.babialmenar@polimi.it
RI Babi Almenar, Javier/AAA-2199-2019; RUGANI, Benedetto/E-8074-2017
OI Babi Almenar, Javier/0000-0001-5980-5899; Cruz Torres,
   Francesco/0000-0002-1825-7061; RUGANI, Benedetto/0000-0002-3525-1382
FU National Biodiversity Future Centre; National Re-covery and Resilience
   Plan (NRPP) , Mission 4, Component 2 [CN_00000033, 3175]; European
   Union-NextGenerationEU; National Biodiversity Future~Centre (NBFC) under
   National Recovery and Resilience Plan (NRPP) [CN_00000033]; Italian
   Ministry of University and Research - European Union - NextGenerationEU
   [3175]
FX We would like to warmly thank Dr. Servaas Storm and Dr. Ir. Jan Kwakkel
   from Technical University of Delft for the fruitful exchange of thoughts
   and the thorough comments we received on this work. We would also like
   to thank Dr. Claudio Petucco from the Luxembourg Institute of Science
   and Technology for his insightful comments on an initial version of our
   research work. Finally, we would like to thank seven anonymous reviewers
   for their precious comments, constructive criticisms, and suggestions
   oriented to improve the quality of our study. JBA acknowledges the
   support of the National Biodiversity Future & nbsp;Centre (NBFC) to
   Politecnico di Milano, funded under the National Recovery and Resilience
   Plan (NRPP), Mission 4, Component 2, Investment 1.4, Project Code
   CN_00000033. Call for tender No. 3138 of 16 December 2021, rectified by
   Decree n. 3175 of 18 December 2021 of Italian Ministry of University and
   Research funded by the European Union - NextGenerationEU.
CR AGORA, 2019, QUART ALZ
   Almenar JB, 2021, LAND USE POLICY, V100, DOI 10.1016/j.landusepol.2020.104898
   [Anonymous], 2019, REGULATION EU 2019 9
   [Anonymous], 2015, Regulation (EU) 2018/1999 of the European Parliament and of the Council of 11 December 2018 on the Gover- nance of the Energy Union and Climate Action, amending Regulations (EC) No 663/2009 and (EC) No 715/2009 of the European Parliament and of the Council, Directives 94/22/EC, 98/70/EC, 2009/31/EC, 2009/73/EC, 2010/31/EU, 2012/27/EU and 2013/30/EU of the European Parliament and of the Council, Council Directives 2009/119/EC and (EU) 2015/652 and repealing Regulation (EU) No 525/2013 of the European Parliament and of the Council, Pub. L. No. 32018R1999, 328 OJ L (2018).
   [Anonymous], 2020, LEGGE 28 FEBBRAIO 20
   [Anonymous], 2018, Directive (EU) 2018/ 2001 of the European parliament and of the council on the promotion of the use of energy from renewable sources: RED II
   [Anonymous], 2019, Housing prices (indicator), DOI DOI 10.1787/63008438-EN
   [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
   [Anonymous], 2019, Directive (EU) 2019/944 of the European Parliament and of the Council of 5 June 2019 on common rules for the internal market for electricity and amending Directive 2012/27/EU (recast) (Text with EEA relevance.)
   [Anonymous], 2019, The European environment - state and outlook 2020 - Knowledge for transition to a sustainable Europe
   [Anonymous], 2021, DEL GOV REC DIR EUR
   [Anonymous], 2021, Communication from the Commission to the European Parliament and the Council: Business Taxation for the 21st Century
   Bankes S.C., 2013, ENCY OPERATIONS RES, V3rd, P532, DOI [DOI 10.1007/978-1-4419-1153-7314, 10.1007/978- 1- 4419- 1153- 7_314]
   Berardi U, 2014, APPL ENERG, V115, P411, DOI 10.1016/j.apenergy.2013.10.047
   Bianchini F, 2012, BUILD ENVIRON, V58, P152, DOI 10.1016/j.buildenv.2012.07.005
   BIL, 2019, OV LUX HOUS MARK
   Blasch J, 2021, ENERGY RES SOC SCI, V82, DOI 10.1016/j.erss.2021.102276
   Bocken N, 2019, J CLEAN PROD, V208, P1498, DOI 10.1016/j.jclepro.2018.10.159
   Bryant BP, 2010, TECHNOL FORECAST SOC, V77, P34, DOI 10.1016/j.techfore.2009.08.002
   Caramizaru A., 2020, Energy Communities: An Overview of Energy and Social Innovation
   Chan S.C., 2011, P JOINT S 2011 INT B
   Chemisana D, 2014, APPL ENERG, V119, P246, DOI 10.1016/j.apenergy.2013.12.027
   Egusquiza A, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su132111931
   Enserink B., 2010, Policy Analysis of Multi-Actor Systems
   European Commission, 2021, Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions Europes Media in the Digital Decade: An Action Plan to Support Recovery and Transformation
   European Commission, 2012, SWD20120398 EUR COMM
   European Commission, 2020, Biodiversity Strategy for 2030
   Friedman JH, 1999, STAT COMPUT, V9, P123, DOI 10.1023/A:1008894516817
   Gwak JH, 2017, J ENVIRON MANAGE, V189, P125, DOI 10.1016/j.jenvman.2016.12.022
   Hannoset A, 2019, ENERGY COMMUNITIES E
   Harris JonathanM., 2022, Environmental and Natural Resource Economics: A Contemporary Approach, VFifth
   Hinsch A., 2021, POLICY BRIEF 1 RENEW
   Jim CY, 2011, BUILD ENVIRON, V46, P1263, DOI 10.1016/j.buildenv.2010.12.013
   Kalra N., 2014, 6906 POL RES WORLD B
   Kim S, 2021, ENERGIES, V14, DOI 10.3390/en14175443
   Kwakkel JH, 2017, ENVIRON MODELL SOFTW, V96, P239, DOI 10.1016/j.envsoft.2017.06.054
   La Notte A, 2017, ECOL INDIC, V74, P392, DOI 10.1016/j.ecolind.2016.11.030
   Lamnatou C, 2015, RENEW SUST ENERG REV, V43, P264, DOI 10.1016/j.rser.2014.11.048
   Legge 17, 2020, LUGL 2020 N 77 REC M
   Lempert R., 2003, Shaping the next one hundred years: New methods for quantitative, long-term policy analysis (MR-1626-CR)
   Lempert RJ, 2014, J BENEFIT-COST ANAL, V5, P487, DOI 10.1515/jbca-2014-9006
   Liberalesso T, 2020, LAND USE POLICY, V96, DOI 10.1016/j.landusepol.2020.104693
   Lowitzsch, 2019, EN TRANS FIN CONS CO, DOI [10.1007/978-3-319-93518-8, DOI 10.1007/978-3-319-93518-8]
   Lowitzsch J, 2020, RENEW SUST ENERG REV, V122, DOI 10.1016/j.rser.2019.109489
   Lugo-Laguna D, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13063238
   Manso M, 2021, RENEW SUST ENERG REV, V135, DOI 10.1016/j.rser.2020.110111
   Meister T, 2020, ENERGY SUSTAIN SOC, V10, DOI 10.1186/s13705-020-00248-3
   Memorial A, LOI 2021 3 FEVRIER 2, P94
   Nash C, 2016, ISR J ECOL EVOL, V62, P74, DOI 10.1080/15659801.2015.1045791
   Nassar K., 2006, Cost Engineering, V48, P13
   Nesshöver C, 2017, SCI TOTAL ENVIRON, V579, P1215, DOI 10.1016/j.scitotenv.2016.11.106
   OECD, 2023, PURCHASING POWER PAR, DOI [10.1787/1290-e5a-en, DOI 10.1787/1290-E5A-EN]
   Petucco C., 2018, NATURE BASED SOLUTIO
   Publications Office of the European Union, 2021, EUR LEX WWW DOC EUR
   Romijn G., 2013, General Guidance for Cost-Benefit Analysis
   RSE, 2020, Gli schemi di Autoconsumo Collettivo e le Comunita dell'Energia 2020
   Santamouris M, 2007, ENERGY, V32, P1781, DOI 10.1016/j.energy.2006.11.011
   Sartori D., 2015, Guide to Cost-Benefit Analysis of Investment Projects
   Sattler S, 2020, APPL SCI-BASEL, V10, DOI 10.3390/app10051791
   Schindler BY, 2018, J ENVIRON MANAGE, V225, P288, DOI 10.1016/j.jenvman.2018.08.017
   Shafique M, 2020, SOL ENERGY, V202, P485, DOI 10.1016/j.solener.2020.02.101
   Shin E, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11123319
   Shin E, 2015, J ASIAN ARCHIT BUILD, V14, P315, DOI 10.3130/jaabe.14.315
   Sproul J, 2014, ENERG BUILDINGS, V71, P20, DOI 10.1016/j.enbuild.2013.11.058
   Tyllianakis E, 2016, J ENVIRON MANAGE, V182, P531, DOI 10.1016/j.jenvman.2016.08.012
   Verde S., 2020, FUTURE RENEWABLE ENE
   Vijayaraghavan K, 2016, RENEW SUST ENERG REV, V57, P740, DOI 10.1016/j.rser.2015.12.119
   World Bank, 2021, GDP DEFL BAS YEAR VA
   Xing YJ, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13094678
   Zhao MJ, 2012, J CENT SOUTH UNIV, V19, P639, DOI 10.1007/s11771-012-1050-1
NR 70
TC 11
Z9 11
U1 4
U2 17
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 AUG 15
PY 2023
VL 414
AR 137428
DI 10.1016/j.jclepro.2023.137428
EA JUN 2023
PG 18
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 M1FQ6
UT WOS:001027681600001
OA hybrid, Green Published
DA 2025-01-10
ER

PT J
AU Becker, JN
   Grozinger, J
   Sarkar, A
   Reinhold-Hurek, B
   Eschenbach, A
AF Becker, Joscha N.
   Grozinger, Janis
   Sarkar, Abhijit
   Reinhold-Hurek, Barbara
   Eschenbach, Annette
TI Effects of cowpea (<i>Vigna unguiculata</i>) inoculation on nodule
   development and rhizosphere carbon and nitrogen content under simulated
   drought
SO PLANT AND SOIL
LA English
DT Article
DE Rhizodeposition; Soil-plant interaction; Soil organic carbon; Mineral N;
   Biological nitrogen fixation; Nodulation
ID N-2 FIXATION; DELTA-N-15 SIGNATURES; CROPPING SYSTEMS; SP NOV.; SOIL;
   LEGUME; ROOT; RHIZOBIA; AFRICA; ESTABLISHMENT
AB AimsInoculation with climate-adapted rhizobia is able to increase legume productivity in drought-prone regions of Sub-Saharan Africa. Enhanced nodulation might additionally affect plant-soil interactions and control rhizosphere carbon (C) and nitrogen (N) pools.MethodsWe investigated inoculation effects on nodulation and biological N-2 fixation (BNF) of Vigna unguiculata and consequent effects on C and N pools in two Namibian soils. Three treatments (Bradyrhizobium sp.1-7 inoculant, non-inoculated, N-fertilised with 50 kg N ha(-1)) were applied in rhizoboxes at 45% and 20% maximum water holding capacity. Nodule development was photo-documented, and rhizobia-DNA sequences were identified. BNF was assessed by delta N-15 enrichment, and organic C and N pools were analysed in bulk and root adherent soil.ResultsPlant growth initially enhanced mineral N losses from the rhizosphere at flowering stage (6 weeks growth), but led to a re-increase of N, and organic C contents after ripening (10 weeks). Inoculation had no effect on nodulation and soil C and N pools, indicating that both soils contained sufficient indigenous rhizobia to allow effective nodulation. However, the inoculant strain was more competitive in establishing itself in the root nodules, depending on the local conditions, showing a need for regional adjustment of inoculation strategies.ConclusionWater stress was the main limitation for nodulation and, in combination with soil type, substantially affected rhizosphere and bulk soil C and N contents. The temporally enhanced rhizodeposition after ripening could be able to maintain soil C and N pools after legume cultivation.
C1 [Becker, Joscha N.; Grozinger, Janis; Eschenbach, Annette] Univ Hamburg, Inst Soil Sci, CEN Ctr Earth Syst Res & Sustainabil, Allende Pl 2, D-20146 Hamburg, Germany.
   [Sarkar, Abhijit; Reinhold-Hurek, Barbara] Univ Bremen, Fac Biol & Chem, Ctr Biomol Interact Bremen, Dept Mol Plant Microbiol, Leobener Str 5, D-28359 Bremen, Germany.
C3 University of Hamburg; University of Bremen
RP Becker, JN (corresponding author), Univ Hamburg, Inst Soil Sci, CEN Ctr Earth Syst Res & Sustainabil, Allende Pl 2, D-20146 Hamburg, Germany.
EM joscha.becker@uni-hamburg.de
RI Becker, Joscha/HHS-0056-2022
OI Becker, Joscha N./0000-0002-3210-3632; Sarkar,
   Abhijit/0009-0005-6256-683X
FU National Commission on Research, Science and Technology Namibia
   [RPIV00092018]; Federal Ministry of Education and Research Germany
   [01DG17004B, 01DG17004A-1]; Deutsche Forschungsgemeinschaft (DFG, German
   Research Foundation) under Germany's Excellence Strategy [390683824, EXC
   2037]
FX We thank Prof. Dr. Percy Chimwamurombe (Namibia University of Science
   and Technology) and Prof. Dr. Fisseha Itanna (National University of
   Lesotho) for their expertise and providing resources and facilities for
   our field sites. Further, we thank Elisa Toth (Universitat Hamburg) for
   helping with image analyses, as well as Deborah Harms and Sumita Rui for
   laboratory work. This research was supported by the National Commission
   on Research, Science and Technology Namibia (Permit RPIV00092018) and
   funded by the Federal Ministry of Education and Research Germany (grants
   #01DG17004B and #01DG17004A-1), as well as 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 Universitaet Hamburg.
CR Alami Y, 2000, APPL ENVIRON MICROB, V66, P3393, DOI 10.1128/AEM.66.8.3393-3398.2000
   Amusan AO, 2011, NUTR CYCL AGROECOSYS, V90, P321, DOI 10.1007/s10705-011-9432-6
   Andres JA., 2012, Bacteria in agrobiology: stress management, P77, DOI DOI 10.1007/1978-1003-1642-23465-23461_23465
   AWONAIKE KO, 1990, FIELD CROP RES, V24, P163, DOI 10.1016/0378-4290(90)90035-A
   Batista L, 2015, BIOL FERT SOILS, V51, P11, DOI 10.1007/s00374-014-0946-3
   Belane AK, 2009, SYMBIOSIS, V48, P47, DOI 10.1007/BF03179984
   Concha C, 2020, J EXP BOT, V71, P3902, DOI 10.1093/jxb/eraa198
   Dakora FD, 1997, SOIL BIOL BIOCHEM, V29, P809, DOI 10.1016/S0038-0717(96)00225-8
   Dakora FD, 2002, PLANT SOIL, V245, P35, DOI 10.1023/A:1020809400075
   de Blécourt M, 2019, J ARID ENVIRON, V165, P88, DOI 10.1016/j.jaridenv.2019.02.006
   De Notaris C, 2020, NUTR CYCL AGROECOSYS, V116, P1, DOI 10.1007/s10705-019-10026-z
   Dhakal Y, 2016, LEGUME RES, DOI [10.18805/lr.v0iOF.9435, DOI 10.18805/LR.V0IOF.9435]
   Drinkwater LE, 1998, NATURE, V396, P262, DOI 10.1038/24376
   Edgar RC, 2004, NUCLEIC ACIDS RES, V32, P1792, DOI 10.1093/nar/gkh340
   Fustec J, 2010, AGRON SUSTAIN DEV, V30, P57, DOI 10.1051/agro/2009003
   Getachew Gebrehana Z., 2020, Environmental Systems Research, V9, P14, DOI DOI 10.1186/S40068-020-00174-5
   Gogoi N., 2018, Legumes for Soil Health and Sustainable Management, P511
   Groenemeyer Jann, 2013, Biodiversity Ecol, V5, P287, DOI 10.7809/b-e.00282
   Grönemeyer JL, 2014, APPL ENVIRON MICROB, V80, P7244, DOI 10.1128/AEM.02417-14
   Grönemeyer JL, 2018, FRONT MICROBIOL, V9, DOI 10.3389/fmicb.2018.02194
   Grönemeyer JL, 2015, INT J SYST EVOL MICR, V65, P4886, DOI 10.1099/ijsem.0.000666
   Groengroeft A., 2013, Biodiversity Ecol, V5, P105, DOI 10.7809/b-e.00259
   Gronemeyer JL, 2016, INT J SYST EVOL MICR, V66, P62, DOI 10.1099/ijsem.0.000674
   HAMDI Y A, 1971, Soil Biology and Biochemistry, V3, P121, DOI 10.1016/0038-0717(71)90004-6
   Hassen A, 2017, REG ENVIRON CHANGE, V17, P1713, DOI 10.1007/s10113-017-1131-7
   He MZ, 2014, NEW PHYTOL, V204, P924, DOI 10.1111/nph.12952
   Henneron L, 2020, NEW PHYTOL, V228, P1269, DOI 10.1111/nph.16760
   Herridge DF, 2008, PLANT SOIL, V311, P1, DOI 10.1007/s11104-008-9668-3
   Horn LN, 2020, ANN AGR SCI-CAIRO, V65, P83, DOI 10.1016/j.aoas.2020.03.002
   Irisarri P, 2019, FRONT MICROBIOL, V10, DOI 10.3389/fmicb.2019.00768
   IUSS Working Group WRB, 2015, World Soil Resources Reports, V106, DOI DOI 10.1017/S0014479706394902
   Jürgens N, 2012, ENVIRON MONIT ASSESS, V184, P655, DOI 10.1007/s10661-011-1993-y
   Kasper S, 2019, AGRICULTURE-BASEL, V9, DOI 10.3390/agriculture9100209
   Kebede E, 2021, FRONT SUSTAIN FOOD S, V5, DOI 10.3389/fsufs.2021.728014
   Kermah M, 2018, AGR ECOSYST ENVIRON, V261, P201, DOI 10.1016/j.agee.2017.08.028
   Kerr RB, 2007, EXP AGR, V43, P437, DOI 10.1017/S0014479707005339
   Khadka J, 2006, PLANT PROD SCI, V9, P115, DOI 10.1626/pps.9.115
   Kokkoris V, 2019, SCI TOTAL ENVIRON, V660, P1135, DOI 10.1016/j.scitotenv.2019.01.100
   Kumar S, 2018, LEGUMES SOIL HLTH SU
   Kumar S, 2016, MOL BIOL EVOL, V33, P1870, DOI [10.1093/molbev/msw054, 10.1093/molbev/msv279]
   Kurdali F, 2002, J PLANT NUTR, V25, P355, DOI 10.1081/PLN-100108841
   Laguerre G, 1996, APPL ENVIRON MICROB, V62, P2029, DOI 10.1128/AEM.62.6.2029-2036.1996
   Lal R, 2015, J SOIL WATER CONSERV, V70, P329, DOI 10.2489/jswc.70.6.329
   Lal R, 2015, SUSTAINABILITY-BASEL, V7, P5875, DOI 10.3390/su7055875
   Larkin MA, 2007, BIOINFORMATICS, V23, P2947, DOI 10.1093/bioinformatics/btm404
   Leenaars J.G.B., 2015, Root Zone Plant-Available Water Holding Capacity of the Sub-Saharan Africa soil
   Liu Y, 2022, SOIL BIOL BIOCHEM, V165, DOI 10.1016/j.soilbio.2021.108541
   Luchen C. C., 2018, J. Plant Pathol. Microbiol, V9, DOI [10.4172/2157-7471.1000456, DOI 10.4172/2157-7471.1000456]
   Lynch J M, 2012, RHIZOSPHERE-NETH
   Makgato MJ, 2020, AGRONOMY-BASEL, V10, DOI 10.3390/agronomy10111675
   Maltais-Landry G, 2015, PLANT SOIL, V394, P139, DOI 10.1007/s11104-015-2518-1
   Manzoni S, 2012, ECOLOGY, V93, P930, DOI 10.1890/11-0026.1
   Delamuta JRM, 2013, INT J SYST EVOL MICR, V63, P3342, DOI 10.1099/ijs.0.049130-0
   Masson-Delmotte PZ V., 2018, GLOBAL WARMING 1 5 C
   Meena B.L., 2018, Legumes for Soil Health and Sustainable Management, P387
   Meier IC, 2017, SOIL BIOL BIOCHEM, V106, P119, DOI 10.1016/j.soilbio.2016.12.004
   Mendoza-Suarez M, 2021, FRONT PLANT SCI, V12, DOI 10.3389/fpls.2021.690567
   Naylor D, 2018, FRONT PLANT SCI, V8, DOI 10.3389/fpls.2017.02223
   Nyaga JW, 2020, FRONT AGRON, V2, DOI 10.3389/fagro.2020.606293
   O'Dea JK, 2015, NUTR CYCL AGROECOSYS, V102, P179, DOI 10.1007/s10705-015-9687-4
   PARARAJASINGHAM S, 1990, CAN J PLANT SCI, V70, P163, DOI 10.4141/cjps90-018
   Parkin TB, 2002, PLANT SOIL, V243, P187, DOI 10.1023/A:1019949727575
   Parte AC, 2014, NUCLEIC ACIDS RES, V42, pD613, DOI 10.1093/nar/gkt1111
   Paul BK, 2020, AGRON SUSTAIN DEV, V40, DOI 10.1007/s13593-020-00626-3
   Pausch J, 2018, GLOBAL CHANGE BIOL, V24, P1, DOI 10.1111/gcb.13850
   Raats M. M., 1992, Food Quality and Preference, V3, P89, DOI 10.1016/0950-3293(91)90028-D
   Rehman HM, 2019, PLANT CELL ENVIRON, V42, P52, DOI 10.1111/pce.13368
   Reinhold-Hurek B, 2015, ANNU REV PHYTOPATHOL, V53, P403, DOI 10.1146/annurev-phyto-082712-102342
   Reinprecht Y, 2020, FRONT PLANT SCI, V11, DOI 10.3389/fpls.2020.01172
   Saima Hamid Saima Hamid, 2016, Journal of the Saudi Society of Agricultural Sciences, V15, P127, DOI 10.1016/j.jssas.2014.08.002
   Salgado GC, 2021, AGRICULTURE-BASEL, V11, DOI 10.3390/agriculture11080690
   Sammauria R, 2018, LEGUMES SOIL HLTH SU
   Smaling EMA, 2008, AGR ECOSYST ENVIRON, V128, P185, DOI 10.1016/j.agee.2008.06.005
   Soumare A, 2020, PLANTS-BASEL, V9, DOI 10.3390/plants9081011
   Sugiyama A., 2012, SECRETIONS EXUDATES, P27, DOI DOI 10.1007/978-3-642-23047-9_2
   THIES JE, 1991, APPL ENVIRON MICROB, V57, P19, DOI 10.1128/AEM.57.1.19-28.1991
   UnitedNations, 2019, World Population Prospects 2019: Highlights
   Vanlauwe B, 2019, AGR ECOSYST ENVIRON, V284, DOI 10.1016/j.agee.2019.106583
   Villarino SH, 2021, SCI ADV, V7, DOI 10.1126/sciadv.abd3176
   Virk AL, 2022, ADV AGRON
   Vlassak KM, 1997, CRIT REV PLANT SCI, V16, P163, DOI 10.1080/713608146
   Wall P. C., 2014, Conservation agriculture: global prospects and challenges, P263, DOI 10.1079/9781780642598.0263
   Wanek W, 2002, J EXP BOT, V53, P1109, DOI 10.1093/jexbot/53.371.1109
   Webb J, 2003, SOIL SCI SOC AM J, V67, P928, DOI 10.2136/sssaj2003.0928
   Willems A, 2003, SYST APPL MICROBIOL, V26, P203, DOI 10.1078/072320203322346056
   Willems A, 2001, INT J SYST EVOL MICR, V51, P111, DOI 10.1099/00207713-51-1-111
   Wongphatcharachai M, 2015, J APPL MICROBIOL, V118, P1152, DOI 10.1111/jam.12771
NR 87
TC 3
Z9 3
U1 2
U2 12
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 JUL
PY 2024
VL 500
IS 1-2
SI SI
BP 33
EP 51
DI 10.1007/s11104-023-06051-1
EA MAY 2023
PG 19
WC Agronomy; Plant Sciences; Soil Science
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Plant Sciences
GA ZH8M7
UT WOS:000984769700003
OA hybrid
DA 2025-01-10
ER

PT J
AU Traore, B
   Moussa, AA
   Traore, A
   Nassirou, YSA
   Ba, MN
   Tabo, R
AF Traore, Bouba
   Moussa, Abdourazak Alio
   Traore, Amadou
   Nassirou, Yahaya Seydou Abdel
   Ba, Malick N.
   Tabo, Ramadjita
TI Pearl Millet (<i>Pennisetum glaucum</i>) Seedlings Transplanting as
   Climate Adaptation Option for Smallholder Farmers in Niger
SO ATMOSPHERE
LA English
DT Article
DE food security; crop failure; mineral fertilization; crop management;
   Sahel
ID PLANTING DATES; GRAIN-YIELD; VARIABILITY; FERTILIZATION; AFRICA; GROWTH;
   MAIZE; L.
AB Pearl millet is the most widely grown cereal crop in the arid and semi-arid regions of Africa, and in Niger in particular. To determine an optimized management strategy for smallholder farmers in southern Niger to cope with crop production failure and improve cropping performance in the context of climate change and variability, multi-site trials were conducted to evaluate the impacts of transplanting on pearl millet growth and productivity. Eight treatments viz. T1-0NPK (100% transplanting without NPK), T1-NPK (100% transplanting + NPK), T2-0NPK (100% transplanting of empty hills without NPK), T2-NPK (100% transplanting of empty hills + NPK), T3-0NPK (50% transplanting of empty hills without NPK), T3-NPK (50% transplanting of empty hills + NPK), T4-0NPK (farmer practice without NPK), and T4-NPK (farmer practice + NPK) were included in the experiment. Compared to farmer practice, transplanting significantly reduced time to tillering, flowering, and maturity stages by 15%, 27%, and 11%, respectively. The results also revealed that T1-NPK significantly increased panicle weight, total biomass, grain yield, and plant height by 40%, 38%, 27%, and 23%, respectively. Farmers' evaluations of the experiments supported these findings, indicating three substantial advantages of transplanting, including higher yield (37.50% of responses), larger, more vigorous and more panicles (34.17% of responses), and good tillering (28.33% of responses). An economic profitability analysis of the system revealed that biomass gain (XOF 359,387/ha) and grain gain (XOF 324,388/ha) increased by 34% and 22%, respectively, with T1-NPK. Therefore, it can be inferred that transplanting is a promising strategy for adapting millet cultivation to climate change and variability in southern Niger.
C1 [Traore, Bouba; Moussa, Abdourazak Alio; Nassirou, Yahaya Seydou Abdel; Ba, Malick N.; Tabo, Ramadjita] Int Crops Res Inst Semi Arid Trop, BP 12404, Niamey, Niger.
   [Traore, Bouba; Traore, Amadou] Inst Econ Rurale IER Mali, BP 28, Koutiala, Mali.
C3 CGIAR; International Crops Research Institute for the Semi-Arid-Tropics
   (ICRISAT)
RP Traore, B (corresponding author), Int Crops Res Inst Semi Arid Trop, BP 12404, Niamey, Niger.; Traore, B (corresponding author), Inst Econ Rurale IER Mali, BP 28, Koutiala, Mali.
EM b.traore@cgiar.org; abdoulrazakalio@gmail.com; traoreamadou73@yahoo.fr;
   ay02121990@gmail.com; b.malick@cgiar.org; r.tabo@cgiar.org
RI Moussa, Abdourazak/AAT-1848-2021; Ba, Malick/I-8557-2012
OI Ba, Malick/0000-0001-7323-8739; Traore, Bouba/0000-0002-4458-6440
FU USAID Development Food Security Assistance program (DFSA/GIRMA) of
   Catholic Relief Services (CRS) under the ICRISAT agreement
   [72DFFP18CA00003, NE.19.SUBCONT.8563.672.P0410.01.00]
FX This research has been funded by the USAID Development Food Security
   Assistance program (DFSA/GIRMA) of Catholic Relief Services (CRS) (grant
   number: 72DFFP18CA00003) under the ICRISAT agreement (grant number:
   NE.19.SUBCONT.8563.672.P0410.01.00); however, the views expressed do not
   necessarily reflect the US government's official policies.
CR Ado AM, 2019, ENVIRON DEV SUSTAIN, V21, P2963, DOI 10.1007/s10668-018-0173-4
   Agbaje G. O., 2002, Tropicultura, V20, P217
   AJAYI O, 1990, ANN APPL BIOL, V117, P487, DOI 10.1111/j.1744-7348.1990.tb04815.x
   Alhassane Agali, 2013, Secheresse (Montrouge), V24, P282, DOI 10.1684/sec.2013.0400
   Alvar-Beltrán J, 2020, ATMOSPHERE-BASEL, V11, DOI 10.3390/atmos11080827
   [Anonymous], 2016, Agriculture Food Security, DOI [10.1186/s40066-016-0075-3, DOI 10.1186/S40066-016-0075-3]
   Assefa D., 2007, 48 DCG
   Bationo A., 1989, Soil, crop, and water management systems for rainfed agriculture in the Sudano-Sahelian zone., P159
   Ben Mohamed A, 2002, CLIMATIC CHANGE, V54, P327, DOI 10.1023/A:1016189605188
   Bielders CL, 2015, FIELD CROP RES, V171, P165, DOI 10.1016/j.fcr.2014.10.008
   Biswas S., 2020, INT J ENV CLIM CHANG, V10, P24, DOI [10.9734/ijecc/2020/v10i530198, DOI 10.9734/IJECC/2020/V10I530198]
   Chouhan M, 2015, BIOSCAN, V10, P1295
   Coulibaly A, 2019, AGRONOMY-BASEL, V9, DOI 10.3390/agronomy9100664
   Devkota M, 2020, AGR SYST, V185, DOI 10.1016/j.agsy.2020.102946
   Djanaguiraman M, 2018, PLANT CELL ENVIRON, V41, P993, DOI 10.1111/pce.12931
   Fairhurst T, 2015, MANUEL GESTION INTEG
   Fanadzo M, 2009, AFR J AGR RES, V4, P689
   Gudadhe NN, 2020, MAYDICA, V65
   Ingram KT, 2002, AGR SYST, V74, P331, DOI 10.1016/S0308-521X(02)00044-6
   Kamara AY, 2009, AGRON J, V101, P91, DOI 10.2134/agronj2008.0090
   Khairwal I, 2007, Pearl millet crop management and seed production manual
   Krishnan R, 2018, J FOOD SCI TECH MYS, V55, P3362, DOI 10.1007/s13197-018-3305-9
   Lawali M.N., 2018, CAMEROON J BIOL BIOC, V26, P6
   Maman N, 2017, AGRON J, V109, P2333, DOI 10.2134/agronj2017.03.0139
   Mapfumo S, 2002, THESIS U ZIMBABWE HA
   Marshall E., 2009, Make money by growing mushrooms
   Moussa S., 2020, RESEARCHGATE
   Nicou R.=, 1994, SORGHUM TROPICAL AGR
   Nwajei Sunday Ebonka, 2019, Acta Agriculturae Slovenica, V114, P169, DOI 10.14720/aas.2019.114.2.3
   Obwocha EB, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14020765
   Olabanji O. G., 1996, International Sorghum and Millets Newsletter, P61
   Oswald A, 2001, WEED SCI, V49, P346, DOI 10.1614/0043-1745(2001)049[0346:TMASRS]2.0.CO;2
   Pal M., 1976, Indian Farming, V25, P21
   Sehgal D, 2012, BMC PLANT BIOL, V12, DOI 10.1186/1471-2229-12-9
   Silungwe FR, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11164330
   Singh D., 2017, J MULTIDISCIP ADV RE, V6, P149
   Sissoko K, 2011, REG ENVIRON CHANGE, V11, pS119, DOI 10.1007/s10113-010-0164-y
   Sogoba B, 2020, AGRICULTURE-BASEL, V10, DOI 10.3390/agriculture10060214
   Soler CMT, 2008, J AGR SCI-CAMBRIDGE, V146, P445, DOI 10.1017/S0021859607007617
   Taye M, 2019, ENVIRONMENTS, V6, DOI 10.3390/environments6110118
   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
   Upadhyay PN, 2001, INDIAN J AGRON, V46, P126
   van Ittersum MK, 2016, P NATL ACAD SCI USA, V113, P14964, DOI 10.1073/pnas.1610359113
   Young E.M., 2003, Transplanting sorghum and millet as a means of increasing food security in semi-arid low-income countries
NR 46
TC 3
Z9 3
U1 0
U2 1
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4433
J9 ATMOSPHERE-BASEL
JI Atmosphere
PD JUL
PY 2022
VL 13
IS 7
AR 997
DI 10.3390/atmos13070997
PG 15
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA 3G9MK
UT WOS:000831669900001
OA Green Accepted, gold
DA 2025-01-10
ER

PT J
AU Curran-Groome, W
   Hino, M
   BenDor, TK
   Salvesen, D
AF Curran-Groome, William
   Hino, Miyuki
   BenDor, Todd K.
   Salvesen, David
TI Complexities and costs of floodplain buyout implementation
SO LAND USE POLICY
LA English
DT Article
DE Floodplain buyouts; Climate adaptation; Hazard mitigation; Environmental
   finance; Flood policy; Fiscal impacts
AB Public acquisitions of floodplain properties, or "buyouts," whereby governments purchase properties at risk of flooding from willing sellers and convert them to open space, are a widely used strategy for reducing risk. Since 1990, the U.S. Federal Emergency Management Agency (FEMA) has provided funding for more than 40,000 properties. Yet, little is known about the costs of buyout implementation, even though federal funding re-quirements mandate a complex set of activities undertaken by local, state, and federal government staff. This lack of understanding of buyout activity costs hinders development of evidence-based policy recommendations. To address this gap, we surveyed local and state government officials and consultants who have worked on floodplain buyout projects. Our survey results provide the first systematic, activity-level financial documentation of buyout projects in the U.S. Local and state government respondents reported median per-property activity costs of $14,428 and $8,161 (or 9.64% and 6.95% of property purchase costs), respectively. Respondents also reported significant variation in the activities undertaken as part of each project; community engagement strategies were particularly diverse, suggesting some households may not be adequately informed as a result of insufficient funding, time, or technical capacity for these activities. The varied and complex structures of buyout projects, as well as the attendant activity costs, pose barriers to implementation for local governments. Our results suggest both that: a) additional support and flexibility may be needed for critical activities that improve the experience of buyout participants; and b) reducing other activity costs may produce significant savings, which in turn could be used to improve the quality and expand the scope of buyout projects.
C1 [Curran-Groome, William; Hino, Miyuki; BenDor, Todd K.] Univ North Carolina Chapel Hill, Dept City & Reg Planning, New East Bldg,Campus Box 3140, Chapel Hill, NC 27599 USA.
   [Salvesen, David] Univ North Carolina Chapel Hill, Inst Environm, 100 Europa Dr,Suite 490, Chapel Hill, NC 27517 USA.
C3 University of North Carolina; University of North Carolina Chapel Hill;
   University of North Carolina School of Medicine; University of North
   Carolina School of Medicine; University of North Carolina; University of
   North Carolina Chapel Hill
RP BenDor, TK (corresponding author), Univ North Carolina Chapel Hill, Dept City & Reg Planning, New East Bldg,Campus Box 3140, Chapel Hill, NC 27599 USA.
EM bendor@unc.edu
RI BenDor, Todd/E-1375-2016
FU North Carolina Policy Collaboratory and through the U.S. National
   Science Foundation [1427188, 1660450]; Division Of Environmental
   Biology; Direct For Biological Sciences [1427188] Funding Source:
   National Science Foundation
FX This paper is based on work graciously supported by the North Carolina
   Policy Collaboratory and through the U.S. National Science Foundation
   under Coastal SEES Grant No. 1427188 and Geography and Spatial Sciences
   Grant No. 1660450.
CR Adaptation Clearinghouse, 2020, UN REL ASS REAL PROP
   [Anonymous], 2004, COGNITIVE INTERVIEWI
   BenDor TK, 2020, NAT HAZARDS REV, V21, DOI 10.1061/(ASCE)NH.1527-6996.0000380
   Binder SB, 2020, DISASTER PREV MANAG, V29, P497, DOI 10.1108/DPM-09-2019-0298
   BLS, 2019, EMPL COSTS EMPL COMP
   Brady A.F., 2015, Buyouts and beyonds: politics, planning, and the future of Staten Island's East Shore after superstorm Sandy (Doctoral dissertation, Massachusetts Institute of Technology)
   Brody SD, 2017, LANDSCAPE URBAN PLAN, V167, P225, DOI 10.1016/j.landurbplan.2017.07.003
   Climate Central & Zillow, 2019, OC DOOR NEW HOM RIS
   Condylios Steve, 2021, **DATA OBJECT**
   Curran-Groome W, 2021, CLIMATIC CHANGE, V168, DOI 10.1007/s10584-021-03178-x
   Davenport FV, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2017524118
   de Vries DH, 2017, HUM ECOL, V45, P437, DOI 10.1007/s10745-017-9915-4
   Elliott JR, 2020, SOCIUS, V6, DOI 10.1177/2378023120905439
   FEMA, 2015, HAZ MIT ASS GUID 201
   FEMA, 2020, FREQUENTLY ASKED QUE
   FEMA, 2021, OpenFEMA dataset: hazard mitigation assistance mitigated properties - V2
   GAO, 2021, FEMA SHOULD TAK ADD
   Grace-McCaskey CA, 2021, J ENVIRON STUD SCI, V11, P341, DOI 10.1007/s13412-021-00701-5
   Greer A, 2017, HOUS POLICY DEBATE, V27, P372, DOI 10.1080/10511482.2016.1245209
   Hulse K, 2020, HOUSING STUD, V35, P981, DOI 10.1080/02673037.2019.1644297
   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
   Kraan CM, 2021, J ENVIRON STUD SCI, V11, P481, DOI 10.1007/s13412-021-00688-z
   Loughran K, 2019, POPUL ENVIRON, V41, P52, DOI 10.1007/s11111-019-00324-7
   Mach KJ, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aax8995
   Marino E, 2018, GLOBAL ENVIRON CHANG, V49, P10, DOI 10.1016/j.gloenvcha.2018.01.002
   NC Office of State Budget and Management, 2007, N CAR DIS REC GUID
   Peterson K, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su122310112
   Qualtrics, 2020, QUALTR COMP PROGR VE
   Raats M. M., 1992, Food Quality and Preference, V3, P89, DOI 10.1016/0950-3293(91)90028-D
   Siders AR, 2019, CLIMATIC CHANGE, V152, P239, DOI 10.1007/s10584-018-2272-5
   United States Government Accountability Office, 2018, BLUEPRINT BUYOUT BLU
   USGCRP, 2018, OUR CHANGING CLIMATE
   Weber A., 2019, Going Under: Long wait times for post-flood buyouts leave homeowners underwater
   Weber Anna, BLUEPRINT BUYOUT CHA
   Zavar E, 2016, DISASTER PREV MANAG, V25, P360, DOI 10.1108/DPM-01-2016-0021
NR 36
TC 6
Z9 11
U1 0
U2 7
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 JUL
PY 2022
VL 118
AR 106128
DI 10.1016/j.landusepol.2022.106128
EA APR 2022
PG 9
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA 1I6HG
UT WOS:000797328500011
OA Bronze
DA 2025-01-10
ER

PT J
AU Wang, R
   Wu, H
   Chiles, R
AF Wang, Rui
   Wu, Hong
   Chiles, Robert
TI Ecosystem Benefits Provision of Green Stormwater Infrastructure in
   Chinese Sponge Cities
SO ENVIRONMENTAL MANAGEMENT
LA English
DT Article
DE Public perception; Ecosystem benefit; Green stormwater infrastructure;
   Sponge city development; Co-benefits approach
ID URBAN CLIMATE ADAPTATION; WILLINGNESS-TO-PAY; PUBLIC PERCEPTION;
   MANAGEMENT; SERVICES; GOVERNANCE; CITY; IMPLEMENTATION; EDUCATION; RANKS
AB The Sponge City Development (SCD) concept was initiated in 2012 to address severe urban flooding and water quality challenges in China. Green stormwater infrastructure (GSI) such as rain gardens have been adopted as critical stormwater management tools. Existing GSI research has focused primarily on their environmental performance, overlooking the human dimensions. The co-benefits of GSI have been particularly underinvestigated. We used social surveys (n = 607) and expert interviews (n = 11) to explore public perception of SCD and GSI in four pilot sponge cities, examining flood experience, stormwater concerns, GSI familiarity, institutional trust, and GSI benefit perception. The survey found high exposure to flooding, medium GSI familiarity, and strong institutional trust. The public showed greater concern on stormwater impacts on their quality-of-life than the water environment, rating the less-intended aesthetic and health values as the best-perceived benefits. Experience, familiarity, concern, trust, age, and city significantly affected GSI benefit perception. In contrast, the experts spoke more positively about the environmental benefits while indicating the inadequacy of public participation. The case of GSI in SCD offers broad implications for environmental governance and expert-public relationships in an era of rapid social, technological, and environmental change. Refining policies and regulations to incorporate social goals, bringing the public into the SCD process, and building up the GSI industry's capacity in planning, design, construction, and maintenance are critical to enhancing GSI benefits provision. Adopting the co-benefits approach will be essential to utilizing GSI as a place-making tool to create more sustainable and livable communities.
C1 [Wang, Rui; Wu, Hong] Penn State Univ, Dept Landscape Architecture, University Pk, PA 16802 USA.
   [Chiles, Robert] Penn State Univ, Rock Eth Inst, Dept Food Sci, Dept Agr Econ Sociol & Educ, University Pk, PA 16802 USA.
C3 Pennsylvania Commonwealth System of Higher Education (PCSHE);
   Pennsylvania State University; Pennsylvania State University -
   University Park; Pennsylvania Commonwealth System of Higher Education
   (PCSHE); Pennsylvania State University; Pennsylvania State University -
   University Park
RP Wu, H (corresponding author), Penn State Univ, Dept Landscape Architecture, University Pk, PA 16802 USA.
EM huw24@psu.edu
RI wang, rui/JAC-6240-2023
OI Wu, Hong/0000-0002-9728-8455; WANG, RUI/0000-0002-5268-6839
FU China Scholarship Council [201808030006]; Pennsylvania State
   University's College of Arts and Architecture
FX This study is part of a Ph.D. dissertation co-funded by the China
   Scholarship Council [Grant No. 201808030006] and the Pennsylvania State
   University's College of Arts and Architecture.
CR Anguelovski I, 2014, GLOBAL ENVIRON CHANG, V27, P156, DOI 10.1016/j.gloenvcha.2014.05.010
   Apostolaki S, 2006, WATER PRACT TECHNOL, V1, DOI 10.2166/WPT.2006009
   Asah ST, 2014, ECOSYST SERV, V10, P180, DOI 10.1016/j.ecoser.2014.08.003
   Baptiste AK, 2014, COMMUNITY DEV, V45, P337, DOI 10.1080/15575330.2014.934255
   Baptiste AK, 2015, LANDSCAPE URBAN PLAN, V136, P1, DOI 10.1016/j.landurbplan.2014.11.012
   Barclay N, 2019, J ENVIRON MANAGE, V251, DOI 10.1016/j.jenvman.2019.109620
   Barnhill K, 2012, ENVIRON PRAC, V14, P6, DOI 10.1017/S1466046611000470
   Benedict M., 2006, GREEN INFRASTRUCTURE
   Byrne JA, 2015, LANDSCAPE URBAN PLAN, V138, P132, DOI 10.1016/j.landurbplan.2015.02.013
   Chan FKS, 2018, LAND USE POLICY, V76, P772, DOI 10.1016/j.landusepol.2018.03.005
   Chizhou Municipal Commission of Housing and Rural and Urban Construction, 2017, ANHUI ARCHITECTURE, P14
   Choi C, 2021, J ENVIRON MANAGE, V291, DOI 10.1016/j.jenvman.2021.112583
   Church SP, 2015, LANDSCAPE URBAN PLAN, V134, P229, DOI 10.1016/j.landurbplan.2014.10.021
   Corder G.W., 2009, NONPARAMETRIC STAT N, DOI DOI 10.1111/J.1751-5823.2010.00122_6.X
   Cousins JJ, 2017, CITIES, V66, P44, DOI 10.1016/j.cities.2017.03.005
   Dai LP, 2018, INT J WATER RESOUR D, V34, P578, DOI 10.1080/07900627.2017.1373637
   Dar MUD, 2021, J CLEAN PROD, V318, DOI 10.1016/j.jclepro.2021.128474
   DeMaris A., 2004, REGRESSION SOCIAL DA
   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
   Dhakal KP, 2016, ENVIRON MANAGE, V57, P1112, DOI 10.1007/s00267-016-0667-5
   Dietz ME, 2004, ENVIRON MANAGE, V34, P684, DOI 10.1007/s00267-003-0238-4
   Ding L, 2019, CITIES, V93, P13, DOI 10.1016/j.cities.2019.04.007
   Echols Stuart., 2008, LANDSCAPE J, V27, P268, DOI DOI 10.3368/LJ.27.2.268
   Elliott RM, 2020, AMBIO, V49, P569, DOI 10.1007/s13280-019-01223-9
   Friedman M, 1937, J AM STAT ASSOC, V32, P675, DOI 10.2307/2279372
   Gao YL, 2018, J ENVIRON MANAGE, V223, P478, DOI 10.1016/j.jenvman.2018.06.059
   Giacalone K, 2010, J CONTEMP WAT RES ED, V146, P92, DOI 10.1111/j.1936-704X.2010.00395.x
   Gong X, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9040575
   [宫永伟 Gong Yongwei], 2018, [中国给水排水, China Water & Wastewater], V34, P1
   Guba EG., 1994, Handbook of qualitative research, P105, DOI DOI 10.1093/INTQHC/MZM042
   Hansen R, 2014, AMBIO, V43, P516, DOI 10.1007/s13280-014-0510-2
   Hendricks MD, 2018, SUSTAIN CITIES SOC, V38, P265, DOI 10.1016/j.scs.2017.12.039
   Henstra D, 2020, J ENVIRON PLANN MAN, V63, P1077, DOI 10.1080/09640568.2019.1634015
   Huang, 2017, CONSTRUCTION SCI TEC, V1, P35, DOI [10.16116/j.cnki.jskj.2017.01.006, DOI 10.16116/J.CNKI.JSKJ.2017.01.006]
   Hughes S, 2020, NAT CLIM CHANGE, V10, P1085, DOI 10.1038/s41558-020-00953-z
   Jia HF, 2017, FRONT ENV SCI ENG, V11, DOI 10.1007/s11783-017-0984-9
   Kati V, 2016, LAND USE POLICY, V50, P537, DOI 10.1016/j.landusepol.2015.09.031
   KRUSKAL WH, 1952, J AM STAT ASSOC, V47, P583, DOI 10.1080/01621459.1952.10483441
   Li H, 2017, WATER-SUI, V9, DOI 10.3390/w9090594
   Li X., 2018, RES PRACTICE SPONGE
   Li Y, 2007, CHINESE HYDRAULIC EN, P77
   Liang X, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10030669
   Manning J., 2017, The international encyclopedia of communication research methods, DOI 10.1002/9781118901731.iecrm0270
   MHURD, 2019, EXC SPONG PIL CIT 1
   MHURD, 2014, STRAT PLAN URB GROWT
   Miles M. B., 1994, QUALITATIVE DATA ANA
   Miller SM, 2019, ECOSYST SERV, V37, DOI 10.1016/j.ecoser.2019.100928
   Mol APJ, 2006, DEV CHANGE, V37, P29, DOI 10.1111/j.0012-155X.2006.00468.x
   National Bureau of Statistics, 2020, REP 2019 PERS INC EX
   Pohontsch NJ, 2019, REHABILITATION, V58, P413, DOI 10.1055/a-0801-5465
   Porse EC, 2013, WATER-SUI, V5, P29, DOI 10.3390/w5010029
   Pradhananga AK, 2017, LANDSCAPE URBAN PLAN, V168, P1, DOI 10.1016/j.landurbplan.2017.10.001
   Prudencio L, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aaa81a
   Qiao XJ, 2020, SUSTAIN CITIES SOC, V53, DOI 10.1016/j.scs.2019.101963
   Ren NQ, 2017, FRONT ENV SCI ENG, V11, DOI 10.1007/s11783-017-0960-4
   Sañudo-Fontaneda LA, 2019, LAND USE POLICY, V89, DOI 10.1016/j.landusepol.2019.104251
   Scott AB, 2017, SCI TOTAL ENVIRON, V592, P738, DOI 10.1016/j.scitotenv.2017.01.201
   Serra-Llobet A, 2016, WATER-SUI, V8, DOI 10.3390/w8100445
   Shandas V, 2020, J ENVIRON PLANN MAN, V63, P959, DOI 10.1080/09640568.2019.1620708
   Shen J., 2019, ARCHITECTURE, V26, P81, DOI [10.14085/j.fjyl.2019.03.0081.06, DOI 10.14085/J.FJYL.2019.03.0081.06]
   Nguyen TT, 2020, J ENVIRON MANAGE, V253, DOI 10.1016/j.jenvman.2019.109689
   United States Environmental Protection Agency (USEPA n.d.), WHAT IS GREEN INFR
   Veerkamp CJ, 2021, ECOSYST SERV, V52, DOI 10.1016/j.ecoser.2021.101367
   Venkataramanan V, 2020, SCI TOTAL ENVIRON, V720, DOI 10.1016/j.scitotenv.2020.137606
   Wang Y, 2020, J CLEAN PROD, V256, DOI 10.1016/j.jclepro.2020.120479
   Wang YT, 2017, RESOUR CONSERV RECY, V122, P11, DOI 10.1016/j.resconrec.2017.02.002
   Wang ZX, 2005, INT REV SOCIOL, V15, P155, DOI 10.1080/03906700500038876
   Williams JB, 2019, LANDSCAPE URBAN PLAN, V190, DOI 10.1016/j.landurbplan.2019.103610
   Wong SM, 2020, WATER RESOUR RES, V56, DOI 10.1029/2019WR027008
   Yang B, 2016, LANDSCAPE RES, V41, P314, DOI 10.1080/01426397.2015.1077944
   Yang Y, 2014, PROBL POST-COMMUNISM, V61, DOI 10.2753/PPC1075-8216610304
   Zhang SY, 2018, WATER-SUI, V10, DOI 10.3390/w10060766
   Zhao, 2015, GARDEN, V7, P26, DOI [10.3969/j.issn.1000-0283.2015.07.005, DOI 10.3969/J.ISSN.1000-0283.2015.07.005]
   Zhong Y, 2014, PROBL POST-COMMUNISM, V61, DOI 10.2753/PPC1075-8216610303
   Zinda JA, 2018, CURR SOCIOL, V66, P867, DOI 10.1177/0011392118778098
NR 76
TC 20
Z9 22
U1 9
U2 110
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 0364-152X
EI 1432-1009
J9 ENVIRON MANAGE
JI Environ. Manage.
PD MAR
PY 2022
VL 69
IS 3
BP 558
EP 575
DI 10.1007/s00267-021-01565-9
EA JAN 2022
PG 18
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA ZB4QM
UT WOS:000741857700001
PM 35020029
DA 2025-01-10
ER

PT J
AU Rangwala, I
   Moss, W
   Wolken, J
   Rondeau, R
   Newlon, K
   Guinotte, J
   Travis, WR
AF Rangwala, Imtiaz
   Moss, Wynne
   Wolken, Jane
   Rondeau, Renee
   Newlon, Karen
   Guinotte, John
   Travis, William Riebsame
TI Uncertainty, Complexity and Constraints: How Do We Robustly Assess
   Biological Responses under a Rapidly Changing Climate?
SO CLIMATE
LA English
DT Article
DE natural resource management; conservation; climate adaptation; climate
   change; ecological transformation; biodiversity; ecosystems; regional
   projections; uncertainty; complexity; scenario planning; ecological
   impact assessment; wildlife; expert elicitation
ID SPECIES DISTRIBUTION MODELS; NO-ANALOG COMMUNITIES; LAND-USE; ECOLOGICAL
   RESPONSES; EXPERT KNOWLEDGE; ENVELOPE MODELS; CHANGE IMPACTS;
   CONSERVATION; FOREST; PREDICT
AB How robust is our assessment of impacts to ecosystems and species from a rapidly changing climate during the 21st century? We examine the challenges of uncertainty, complexity and constraints associated with applying climate projections to understanding future biological responses. This includes an evaluation of how to incorporate the uncertainty associated with different greenhouse gas emissions scenarios and climate models, and constraints of spatiotemporal scales and resolution of climate data into impact assessments. We describe the challenges of identifying relevant climate metrics for biological impact assessments and evaluate the usefulness and limitations of different methodologies of applying climate change to both quantitative and qualitative assessments. We discuss the importance of incorporating extreme climate events and their stochastic tendencies in assessing ecological impacts and transformation, and provide recommendations for better integration of complex climate-ecological interactions at relevant spatiotemporal scales. We further recognize the compounding nature of uncertainty when accounting for our limited understanding of the interactions between climate and biological processes. Given the inherent complexity in ecological processes and their interactions with climate, we recommend integrating quantitative modeling with expert elicitation from diverse disciplines and experiential understanding of recent climate-driven ecological processes to develop a more robust understanding of ecological responses under different scenarios of future climate change. Inherently complex interactions between climate and biological systems also provide an opportunity to develop wide-ranging strategies that resource managers can employ to prepare for the future.
C1 [Rangwala, Imtiaz; Moss, Wynne; Wolken, Jane; Travis, William Riebsame] Univ Colorado, North Cent Climate Adaptat Sci Ctr, Boulder, CO 80309 USA.
   [Rangwala, Imtiaz; Moss, Wynne; Wolken, Jane; Travis, William Riebsame] Univ Colorado, Cooperat Inst Res Environm Sci, Boulder, CO 80309 USA.
   [Moss, Wynne] Conservat Sci Partners, Truckee, CA 96161 USA.
   [Rondeau, Renee] Colorado State Univ, Colorado Nat Heritage Program, Ft Collins, CO 80523 USA.
   [Newlon, Karen; Guinotte, John] US Fish & Wildlife Serv, Lakewood, CO 80228 USA.
   [Travis, William Riebsame] Univ Colorado, Dept Geog, Boulder, CO 80309 USA.
C3 University of Colorado System; University of Colorado Boulder;
   University of Colorado System; University of Colorado Boulder; Colorado
   State University; United States Department of the Interior; US Fish &
   Wildlife Service; University of Colorado System; University of Colorado
   Boulder
RP Rangwala, I (corresponding author), Univ Colorado, North Cent Climate Adaptat Sci Ctr, Boulder, CO 80309 USA.; Rangwala, I (corresponding author), Univ Colorado, Cooperat Inst Res Environm Sci, Boulder, CO 80309 USA.
EM imtiaz.rangwala@colorado.edu; wynne@csp-inc.org;
   Jane.Wolken@colorado.edu; renee.rondeau@colostate.edu;
   karen_newlon@fws.gov; john_guinotte@fws.gov; william.travis@colorado.edu
OI Moss, Wynne/0000-0002-2813-1710; RANGWALA, IMTIAZ/0000-0002-4313-9374
CR Albano CM, 2021, CLIMATIC CHANGE, V164, DOI 10.1007/s10584-021-02985-6
   Alexander JM, 2018, GLOBAL CHANGE BIOL, V24, P563, DOI 10.1111/gcb.13976
   Andrews T, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2012GL051607
   Angilletta MJ, 2009, BIO HABIT, P1, DOI 10.1093/acprof:oso/9780198570875.001.1
   [Anonymous], 2012, RMRSGTR277WWW FAQ
   Austin MP, 2011, J BIOGEOGR, V38, P1, DOI 10.1111/j.1365-2699.2010.02416.x
   Bachelet D, 2015, GLOBAL CHANGE BIOL, V21, P4548, DOI 10.1111/gcb.13048
   Barros V, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, pIX
   Barsugli J.J., 2013, Eos Trans. Am. Geophys. Union, V94, P424, DOI DOI 10.1002/2013EO460005
   Barsugli JJ, 2020, EARTHS FUTURE, V8, DOI 10.1029/2020EF001537
   Batllori E, 2020, P NATL ACAD SCI USA, V117, P29720, DOI 10.1073/pnas.2002314117
   Beaumont LJ, 2008, ECOL LETT, V11, P1135, DOI 10.1111/j.1461-0248.2008.01231.x
   Beeton TA, 2019, CLIM RISK MANAG, V23, P50, DOI 10.1016/j.crm.2018.09.002
   Berner LT, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-18479-5
   Bertrand R, 2011, NATURE, V479, P517, DOI 10.1038/nature10548
   Bode M, 2017, METHODS ECOL EVOL, V8, P1012, DOI 10.1111/2041-210X.12703
   Bonan GB, 2018, SCIENCE, V359, P533, DOI 10.1126/science.aam8328
   Bozinovic F, 2015, ECOL EVOL, V5, P1025, DOI 10.1002/ece3.1403
   Bridle J, 2020, SCIENCE, V367, P626, DOI 10.1126/science.aba6432
   Buckley LB, 2008, AM NAT, V171, pE1, DOI 10.1086/523949
   Buma B, 2015, ECOSPHERE, V6, DOI 10.1890/ES15-00058.1
   Burgess MG, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abcdd2
   Burkett VR, 2005, ECOL COMPLEX, V2, P357, DOI 10.1016/j.ecocom.2005.04.010
   Case MJ, 2015, BIOL CONSERV, V187, P127, DOI 10.1016/j.biocon.2015.04.013
   Chakraborty D, 2021, GEOSCI DATA J, V8, P121, DOI 10.1002/gdj3.110
   Chan SC, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/9/094024
   Chapin FS, 1996, ECOLOGY, V77, P822, DOI 10.2307/2265504
   Comte L, 2013, ECOGRAPHY, V36, P1236, DOI 10.1111/j.1600-0587.2013.00282.x
   Coops NC, 2009, ECOL MODEL, V220, P1787, DOI 10.1016/j.ecolmodel.2009.04.029
   Cramer W, 2001, GLOBAL CHANGE BIOL, V7, P357, DOI 10.1046/j.1365-2486.2001.00383.x
   Crausbay SD, 2020, ONE EARTH, V3, P337, DOI 10.1016/j.oneear.2020.08.019
   Cross MS, 2012, ENVIRON MANAGE, V50, P341, DOI 10.1007/s00267-012-9893-7
   Cuena-Lombraña A, 2018, INT J BIOMETEOROL, V62, P1283, DOI 10.1007/s00484-018-1533-3
   D'Amen M, 2017, BIOL REV, V92, P169, DOI 10.1111/brv.12222
   Daniel CJ, 2016, METHODS ECOL EVOL, V7, P1413, DOI 10.1111/2041-210X.12597
   Davis AJ, 1998, NATURE, V391, P783, DOI 10.1038/35842
   Davis EL, 2020, CLIMATIC CHANGE, V162, P1365, DOI 10.1007/s10584-020-02743-0
   Dawson TP, 2011, SCIENCE, V332, P53, DOI 10.1126/science.1200303
   Deutsch CA, 2018, SCIENCE, V361, P916, DOI 10.1126/science.aat3466
   Díaz S, 2019, SCIENCE, V366, P1327, DOI 10.1126/science.aax3100
   Doblas-Reyes F. J., 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, P1363, DOI [10.1017/9781009157896.012, DOI 10.1017/9781009157896.012]
   Dullinger S, 2004, J ECOL, V92, P241, DOI 10.1111/j.0022-0477.2004.00872.x
   Easterling D R, 2017, PRECIPITATION CHANGE, P207, DOI [10.7930/J0H993CC, DOI 10.7930/J0H993CC]
   Elith J, 2009, ANNU REV ECOL EVOL S, V40, P677, DOI 10.1146/annurev.ecolsys.110308.120159
   Ficklin DL, 2017, J GEOPHYS RES-ATMOS, V122, P2061, DOI 10.1002/2016JD025855
   Fink M., 2014, COLORADO NATURAL HER
   Fisichelli N, 2014, OIKOS, V123, P1331, DOI 10.1111/oik.01349
   Flynn M, 2018, ENVIRON SCI POLICY, V79, P45, DOI 10.1016/j.envsci.2017.10.012
   Fordham DA, 2020, SCIENCE, V369, P1072, DOI 10.1126/science.abc5654
   Fowler HJ, 2007, INT J CLIMATOL, V27, P1547, DOI 10.1002/joc.1556
   Fowler HJ, 2021, NAT REV EARTH ENV, V2, P107, DOI 10.1038/s43017-020-00128-6
   Franklin J, 2013, GLOBAL CHANGE BIOL, V19, P473, DOI 10.1111/gcb.12051
   Fraser LH, 2013, FRONT ECOL ENVIRON, V11, P147, DOI 10.1890/110279
   Fuentes M. M. P. B., 2009, Endangered Species Research, V9, P33, DOI 10.3354/esr00224
   Garcia RA, 2014, SCIENCE, V344, P486, DOI 10.1126/science.1247579
   Germain SJ, 2020, CLIMATIC CHANGE, V163, P579, DOI 10.1007/s10584-020-02868-2
   Grosse G, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/4/040201
   Guisan A, 2005, ECOL LETT, V8, P993, DOI 10.1111/j.1461-0248.2005.00792.x
   Harris RMB, 2018, NAT CLIM CHANGE, V8, P579, DOI 10.1038/s41558-018-0187-9
   Harsch MA, 2011, GLOBAL ECOL BIOGEOGR, V20, P582, DOI 10.1111/j.1466-8238.2010.00622.x
   Hausfather Z, 2020, NATURE, V577, P618, DOI 10.1038/d41586-020-00177-3
   Hawkins E, 2009, B AM METEOROL SOC, V90, P1095, DOI 10.1175/2009BAMS2607.1
   Heikkinen RK, 2007, GLOBAL ECOL BIOGEOGR, V16, P754, DOI 10.1111/j.1466-8238.2007.00345.x
   Heino J, 2021, BIOL REV, V96, P89, DOI 10.1111/brv.12647
   Held H., 2021, Hamburg Climate Futures Outlook 2021: Assessing the Plausibility of Deep Decarbonization by 2050, P21
   Helmuth B., 2014, Clim. Chang. Responses, V1, P6, DOI [10.1186/s40665-014-0006-0, DOI 10.1186/S40665-014-0006-0]
   Henry GHR, 1997, GLOB CHANGE BIOL, V3, P1, DOI 10.1111/j.1365-2486.1997.gcb132.x
   Herr A, 2016, ENVIRON MODELL SOFTW, V76, P95, DOI 10.1016/j.envsoft.2015.10.023
   Hijmans RJ, 2006, GLOBAL CHANGE BIOL, V12, P2272, DOI 10.1111/j.1365-2486.2006.01256.x
   Hobbins M., 2019, Extreme Hydrology and Climate Variability, P325
   Hughes TP, 2018, SCIENCE, V359, P80, DOI 10.1126/science.aan8048
   IPCC, 2013, CLIMATE CHANGE 2013, DOI DOI 10.1017/CBO9781107415324
   Jackson ST, 2021, SCIENCE, V373, P1085, DOI 10.1126/science.abj6777
   Jennings KS, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-03629-7
   Jenouvrier S, 2009, P NATL ACAD SCI USA, V106, P1844, DOI 10.1073/pnas.0806638106
   Jentsch A, 2008, CR GEOSCI, V340, P621, DOI 10.1016/j.crte.2008.07.002
   Joyce Linda A., 2020, General Technical Report - Rocky Mountain Research Station, USDA Forest Service, DOI 10.2737/RMRS-GTR-413
   Kayler ZE, 2015, FRONT ECOL ENVIRON, V13, P219, DOI 10.1890/140174
   Kendon EJ, 2012, J CLIMATE, V25, P5791, DOI 10.1175/JCLI-D-11-00562.1
   Knapp AK, 2015, GLOBAL CHANGE BIOL, V21, P2624, DOI 10.1111/gcb.12888
   Knutti R, 2008, PHILOS T R SOC A, V366, P4647, DOI 10.1098/rsta.2008.0169
   Kotamarthi R., 2016, Use of Climate Information for Decision-Making and Impacts Research: State of Our Understanding
   Krivtsov V, 2004, ECOL MODEL, V174, P37, DOI 10.1016/j.ecolmodel.2003.12.042
   Lavergne S, 2010, ANNU REV ECOL EVOL S, V41, P321, DOI 10.1146/annurev-ecolsys-102209-144628
   Lawrence DJ, 2021, CLIMATIC CHANGE, V167, DOI 10.1007/s10584-021-03169-y
   Lempert R, 2013, CLIMATIC CHANGE, V117, P627, DOI 10.1007/s10584-012-0574-6
   Lepetz V, 2009, BIODIVERS CONSERV, V18, P3185, DOI 10.1007/s10531-009-9636-0
   Liu CH, 2017, CLIM DYNAM, V49, P71, DOI 10.1007/s00382-016-3327-9
   Liu HY, 2018, P NATL ACAD SCI USA, V115, P4051, DOI 10.1073/pnas.1700299114
   Macias-Fauria M, 2018, BIOL LETTERS, V14, DOI 10.1098/rsbl.2017.0702
   Mair L, 2018, DIVERS DISTRIB, V24, P1416, DOI 10.1111/ddi.12771
   Marcot BG, 2001, FOREST ECOL MANAG, V153, P29, DOI 10.1016/S0378-1127(01)00452-2
   Martin K, 2000, CONDOR, V102, P503, DOI 10.1650/0010-5422(2000)102[0503:RDADRI]2.0.CO;2
   Martin TG, 2012, CONSERV BIOL, V26, P29, DOI 10.1111/j.1523-1739.2011.01806.x
   Masson-Delmotte V., 2021, Climate Change 2021: The Physical Science Basis, P41
   Maxwell SL, 2019, DIVERS DISTRIB, V25, P613, DOI 10.1111/ddi.12878
   McLaughlin BC, 2012, GLOBAL CHANGE BIOL, V18, P2301, DOI 10.1111/j.1365-2486.2011.02630.x
   Millar CI, 2015, SCIENCE, V349, P823, DOI 10.1126/science.aaa9933
   Miller BW, 2017, ECOSPHERE, V8, DOI 10.1002/ecs2.2020
   Miller BW, 2014, ECOL SOC, V19, DOI 10.5751/ES-06813-190341
   Moraitis ML, 2019, SCI TOTAL ENVIRON, V667, P16, DOI 10.1016/j.scitotenv.2019.02.338
   Morgan MG, 2001, CLIMATIC CHANGE, V49, P279, DOI 10.1023/A:1010651300697
   Mote P., 2011, Eos Trans. AGU, V92, P257, DOI DOI 10.1029/2011EO310001
   Mouquet N, 2015, J APPL ECOL, V52, P1293, DOI 10.1111/1365-2664.12482
   Nabhan GP, 2010, J ETHNOBIOL, V30, P1, DOI 10.2993/0278-0771-30.1.1
   Nobre CA, 2016, P NATL ACAD SCI USA, V113, P10759, DOI 10.1073/pnas.1605516113
   Nogués-Bravo D, 2018, TRENDS ECOL EVOL, V33, P765, DOI 10.1016/j.tree.2018.07.005
   Nolan C, 2018, SCIENCE, V361, P920, DOI 10.1126/science.aan5360
   O'Neill SJ, 2008, J APPL ECOL, V45, P1649, DOI 10.1111/j.1365-2664.2008.01552.x
   Ockendon N, 2014, GLOBAL CHANGE BIOL, V20, P2221, DOI 10.1111/gcb.12559
   Ogden AE, 2009, ECOL SOC, V14
   Pacifici M, 2015, NAT CLIM CHANGE, V5, P215, DOI 10.1038/NCLIMATE2448
   Pearson RG, 2003, GLOBAL ECOL BIOGEOGR, V12, P361, DOI 10.1046/j.1466-822X.2003.00042.x
   Navarro MAP, 2019, ECOSYSTEMS, V22, P77, DOI 10.1007/s10021-018-0254-0
   Perret DL, 2019, GLOBAL ECOL BIOGEOGR, V28, P429, DOI 10.1111/geb.12862
   Peterson GD, 2003, CONSERV BIOL, V17, P358, DOI 10.1046/j.1523-1739.2003.01491.x
   Platts PJ, 2015, AFR J ECOL, V53, P103, DOI 10.1111/aje.12180
   Raffini F, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12114508
   Rangwala I., 2015, HIGH MOUNTAIN CRYOSP, P9
   Redmond KT, 2002, B AM METEOROL SOC, V83, P1143, DOI 10.1175/1520-0477-83.8.1143
   Roe GH, 2007, SCIENCE, V318, P629, DOI 10.1126/science.1144735
   Rondeau R., 2012, THESIS COLORADO STAT
   Rondeau R, 2017, PINYON JUNIPER LANDS
   Rowland E.R., 2014, CONSIDERING MULTIPLE
   Runyon A.N., 2021, CLIMATE CHANGE SCENA
   Runyon AN, 2020, Parks Stewardship Forum, V36, DOI [10.5070/p536146402, DOI 10.5070/P536146402]
   Rupp D. E., 2016, U.S. Geological Survey OpenFile Report, V1047, DOI [10.3133/ofr20161047, DOI 10.3133/ofr20161047]
   Rupp DE, 2013, J GEOPHYS RES-ATMOS, V118, P10884, DOI 10.1002/jgrd.50843
   Sandercock BK, 2005, ECOLOGY, V86, P2176, DOI 10.1890/04-0563
   Santini L, 2016, GLOBAL CHANGE BIOL, V22, P2415, DOI 10.1111/gcb.13271
   Schuurman G.W., 2020, NPSNRSSCCRPNRR202022
   Seglund A., 2018, UNPUB
   Shepherd TG, 2019, P ROY SOC A-MATH PHY, V475, DOI 10.1098/rspa.2019.0013
   Slavich E, 2014, DIVERS DISTRIB, V20, P952, DOI 10.1111/ddi.12216
   Smith DR, 2018, J FISH WILDL MANAG, V9, P302, DOI 10.3996/052017-JFWM-041
   Smith MD, 2011, J ECOL, V99, P656, DOI 10.1111/j.1365-2745.2011.01798.x
   Smith SDP, 2019, ECOL INDIC, V101, P203, DOI 10.1016/j.ecolind.2019.01.010
   Sofaer HR, 2017, GLOBAL CHANGE BIOL, V23, P2537, DOI 10.1111/gcb.13653
   Star J, 2016, CLIM RISK MANAG, V13, P88, DOI 10.1016/j.crm.2016.08.001
   Stein B A., 2014, Climate-Smart Conservation: Putting Adaptation Principles into Practice
   Stewart RIA, 2013, ADV ECOL RES, V48, P71, DOI 10.1016/B978-0-12-417199-2.00002-1
   Sully S, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-09238-2
   Suttle KB, 2007, SCIENCE, V315, P640, DOI 10.1126/science.1136401
   Svenning JC, 2013, AM J BOT, V100, P1266, DOI 10.3732/ajb.1200469
   Symstad AJ, 2017, CLIM RISK MANAG, V17, P78, DOI 10.1016/j.crm.2017.07.002
   Tewksbury JJ, 2014, BIOSCIENCE, V64, P300, DOI 10.1093/biosci/biu032
   Thomas CD, 2004, NATURE, V427, P145, DOI 10.1038/nature02121
   Thorne JH, 2020, FRONT ECOL ENVIRON, V18, P281, DOI 10.1002/fee.2208
   Turner MG, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0105
   Tylianakis JM, 2008, ECOL LETT, V11, P1351, DOI 10.1111/j.1461-0248.2008.01250.x
   Ulbrich U, 2009, THEOR APPL CLIMATOL, V96, P117, DOI 10.1007/s00704-008-0083-8
   Ummenhofer CC, 2017, PHILOS T R SOC B, V372, DOI 10.1098/rstb.2016.0135
   Urban MC, 2016, SCIENCE, V353, P1113, DOI 10.1126/science.aad8466
   Urban MC, 2012, P ROY SOC B-BIOL SCI, V279, P2072, DOI 10.1098/rspb.2011.2367
   USFWS, 2020, SPEC STAT ASS REP SO
   USFWS, 2021, SPEC STAT ASS REP CO
   van de Pol M, 2017, PHILOS T R SOC B, V372, DOI 10.1098/rstb.2016.0134
   Vial J, 2013, CLIM DYNAM, V41, P3339, DOI 10.1007/s00382-013-1725-9
   Vinyeta K., 2013, Exploring the role of traditional ecological knowledge in climate change initiatives
   Wadgymar SM, 2018, NEW PHYTOL, V218, P517, DOI 10.1111/nph.15029
   Wann G.T., 2017, THESIS COLORADO STAT
   Weeks D., 2011, Park Science, V28, P26
   Weigel AP, 2010, J CLIMATE, V23, P4175, DOI 10.1175/2010JCLI3594.1
   Weiskopf SR, 2020, SCI TOTAL ENVIRON, V733, DOI 10.1016/j.scitotenv.2020.137782
   Wethey DS, 2011, J EXP MAR BIOL ECOL, V400, P132, DOI 10.1016/j.jembe.2011.02.008
   Williams AP, 2013, NAT CLIM CHANGE, V3, P292, DOI [10.1038/NCLIMATE1693, 10.1038/nclimate1693]
   Williams JW, 2007, FRONT ECOL ENVIRON, V5, P475, DOI 10.1890/070037
   Williams JW, 2021, NAT ECOL EVOL, V5, P17, DOI 10.1038/s41559-020-01344-5
   Yates KL, 2018, TRENDS ECOL EVOL, V33, P790, DOI 10.1016/j.tree.2018.08.001
NR 169
TC 17
Z9 17
U1 0
U2 10
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2225-1154
J9 CLIMATE
JI Climate
PD DEC
PY 2021
VL 9
IS 12
AR 177
DI 10.3390/cli9120177
PG 28
WC Meteorology & Atmospheric Sciences
WE Emerging Sources Citation Index (ESCI)
SC Meteorology & Atmospheric Sciences
GA XX0RS
UT WOS:000736015100001
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Mahon, R
   Petrie, JA
   Trotman, A
   Eyzaguirre, J
   Burrowes, R
   Matthews, L
   Van Meerbeeck, CJ
   Charles, A
AF Mahon, Roche
   Petrie, Jodi-Ann
   Trotman, Adrian
   Eyzaguirre, Jimena
   Burrowes, Ravidya
   Matthews, Lindsay
   Van Meerbeeck, Cedric J.
   Charles, Amanda
TI Climate services for tourism: Insights from Caribbean Small Island
   Developing States
SO CLIMATE SERVICES
LA English
DT Article
DE Climate services; Climate adaptation; Tourism; Global Framework for
   Climate Services; Small Island Developing States; Caribbean
ID COASTAL TOURISM; INFORMATION BROKERS; DESTINATION CHOICE;
   DECISION-MAKING; FORECASTS; WEATHER; IMPACT; VULNERABILITY; CHALLENGES;
   MANAGEMENT
AB Peer reviewed literature on the availability and use of climate services in the operations and management of tourism is scarce. Using a multi-method approach, we provide insights on both basic and specialised climate information utilised by a range of public and private sector tourism decision-makers in the most tourismdependent region in the world - the Caribbean. We also examined whether existing climate information meets tourism destination planning, marketing and operational decision-making needs and how the tourism industry could more effectively and efficiently integrate climate information to enhance sector performance. Results from research with 47 Caribbean hoteliers and tourism policy-makers show that short-term destination and source market weather information are widely consulted, but the use of historical climate information and longer-term climate forecasts is comparatively lower. There are few tailored climate information products and services, and uptake of the few that exist is low. Current climate information inadequately fulfills decision-makers' needs due to a number of challenges, including a short history of engagement between the climate and tourism communities, along with a partial understanding of the needs and preferences of tourism stakeholders. Evidence suggests that a new generation of specialised climate information products can enhance climate risk management amongst tourism suppliers. Further research and relationship building will be needed to support the coproduction and uptake of tailored climate information for the Caribbean tourism sector. Tourism-dependent Small Island Developing States in other regions interested in pursuing climate services for tourism can learn from the experience and approach used in the Caribbean.
C1 [Mahon, Roche; Petrie, Jodi-Ann; Trotman, Adrian; Van Meerbeeck, Cedric J.] Caribbean Inst Meteorol & Hydrol, Husbands, St James, Barbados.
   [Eyzaguirre, Jimena; Burrowes, Ravidya] ESSA Technol Ltd, Ottawa, ON, Canada.
   [Matthews, Lindsay] Environm & Climate Change Canada, Canadian Ctr Ctr Climate Serv, Gatineau, PQ, Canada.
   [Charles, Amanda] Caribbean Tourism Org, St Michael, Barbados.
C3 Environment & Climate Change Canada
RP Mahon, R (corresponding author), Caribbean Inst Meteorol & Hydrol, Husbands, St James, Barbados.
EM rmahon@cimh.edu.bb
RI Van Meerbeeck, Cedric/D-1231-2010; Burrowes, Ravidya/JDD-2789-2023;
   Eyzaguirre, Jimena/IAM-6627-2023
FU United States Agency for International Development's (USAID) Programme
   for Building Regional Climate Capacity in the Caribbean (BRCCC
   Programme) [AID-538-10-14-00001]; Caribbean Tourism Organization (CTO)
   under the African Caribbean Pacific-European Union-Caribbean Development
   Bank-Natural Disaster Risk Management in CARIFORUM Countries programme
   (NDRM) [GA 177/REG]
FX This research was funded by the United States Agency for International
   Development's (USAID) Programme for Building Regional Climate Capacity
   in the Caribbean (BRCCC Programme) (USAID, Grant ID:
   AID-538-10-14-00001) with the generous support of the American people.
   The three-year BRCCC Programme was executed by the WMO and implemented
   by the CIMH (BRCCC Programme: rcc.cimh.edu.bb/brccc). Additional support
   for this study was provided by the Caribbean Tourism Organization (CTO)
   under the African Caribbean Pacific-European Union-Caribbean Development
   Bank-Natural Disaster Risk Management in CARIFORUM Countries programme
   (NDRM) (Grant ID: GA 177/REG -Supporting a Climate Smart and Sustainable
   Caribbean Tourism Industry Project). Funding agencies had no involvement
   in study design; in the collection, analysis and interpretation of data;
   in the writing of the report; and in the decision to submit the article
   for publication. Any opinions, findings, and conclusion or
   recommendations expressed in this material are those of the authors and
   do not necessarily reflect the view of their institutions, including
   Environment and Climate Change Canada or the Canadian government. We
   thank Ms. Loreto Duffy-Mayers and Dr. Shelly-Ann Cox for their
   assistance in carrying out this research; as well as Dr. David Farrell
   and two anonymous reviewers for their comments that have improved the
   manuscript.
CR Agrawala S, 2001, SCI TECHNOL HUM VAL, V26, P454, DOI 10.1177/016224390102600404
   Albright R, 2010, P NATL ACAD SCI USA, V107, P20400, DOI 10.1073/pnas.1007273107
   Alvarez-Díaz M, 2010, CLIM RES, V43, P207, DOI 10.3354/cr00931
   [Anonymous], 2012, WMO Bull., DOI 10.1016/C2016-0-01594-2
   [Anonymous], 2002, KSG WORKING PAPERS S
   [Anonymous], 2021, Jamaica Gleaner
   [Anonymous], 2011, CLIMATE CHANGES IMPA
   Asrar GR, 2012, CURR OPIN ENV SUST, V4, P88, DOI 10.1016/j.cosust.2012.01.003
   Ayscue EP, 2015, TOURISM GEOGR, V17, P603, DOI 10.1080/14616688.2015.1053974
   Bigano A, 2006, CLIMATIC CHANGE, V76, P389, DOI 10.1007/s10584-005-9015-0
   BURTON I, 1964, NAT RESOUR J, V3, P412
   Cambers G, 2009, AQUAT ECOSYST HEALTH, V12, P168, DOI 10.1080/14634980902907987
   Cashman A, 2012, TOUR REV, V67, P17, DOI 10.1108/16605371211259803
   Changnon D, 2004, B AM METEOROL SOC, V85, P601, DOI 10.1175/BAMS-85-4-601
   CIMH CARDI CWWA CDEMA CARPHA CCREEE CTO CHTA, 2015, LETT AGR CONS REG SE
   CIMH CARDI CWWA CDEMA CARPHA CCREEE CTO CHTA, 2020, STRENGTH CLIM SERV C
   CIMH CARDI CWWA CDEMA CARPHA CCREEE CTO CHTA, 2015, TERMS REF CONS REG S
   Clayton A, 2009, WORLDW HOSP TOUR THE, V1, P212, DOI 10.1108/17554210910980576
   Climate Studies Group Mona, 2020, STAT CAR CLIM SOCC R
   Coelho CAS, 2010, CURR OPIN ENV SUST, V2, P317, DOI 10.1016/j.cosust.2010.09.002
   Creswell J. W., 2015, A concise introduction to mixed methods research
   Damm Andrea, 2017, Climate Services, V7, P31, DOI 10.1016/j.cliser.2016.07.003
   Damm A, 2020, CLIM SERV, V17, DOI 10.1016/j.cliser.2019.02.001
   de Freitas CR, 2017, INT J BIOMETEOROL, V61, pS107, DOI 10.1007/s00484-017-1389-y
   de Freitas CR, 2003, INT J BIOMETEOROL, V48, P45, DOI 10.1007/s00484-003-0177-z
   Dilling L, 2011, GLOBAL ENVIRON CHANG, V21, P680, DOI 10.1016/j.gloenvcha.2010.11.006
   Donner SD, 2007, P NATL ACAD SCI USA, V104, P5483, DOI 10.1073/pnas.0610122104
   Edwards J., 2018, UTILIZATION REGIONAL
   Emmanuel K, 2009, WORLDW HOSP TOUR THE, V1, P252, DOI 10.1108/17554210910980594
   Eugenio-Martin JL, 2010, TOURISM MANAGE, V31, P744, DOI 10.1016/j.tourman.2009.07.015
   Forster J, 2012, CLIMATIC CHANGE, V114, P745, DOI 10.1007/s10584-012-0433-5
   Gable F.J., 1997, J COASTAL RES, V24, P49
   Gerlak A. K., 2017, MIDTERM REV GLOBAL F
   Gledhill DK, 2008, J GEOPHYS RES-OCEANS, V113, DOI 10.1029/2007JC004629
   Granvorka C, 2013, TOURISM ECON, V19, P1401, DOI 10.5367/te.2013.0238
   Guido Z, 2016, WEATHER CLIM SOC, V8, P285, DOI 10.1175/WCAS-D-15-0076.1
   Hall AJ, 2009, WORLDW HOSP TOUR THE, V1, P269, DOI 10.1108/17554210910980602
   Hamilton JM, 2005, CONTEMP GEOGR LEIS T, P229
   Hyman TA, 2014, J SUSTAIN TOUR, V22, P1197, DOI 10.1080/09669582.2013.855220
   IPCC, 2007, SYNTHESIS REPORT, P56
   Kossin James P, 2020, Proc Natl Acad Sci U S A, V117, P11975, DOI 10.1073/pnas.1920849117
   Laframboise N., 2014, WP14229 IMF
   Lemos MC, 2014, CLIM RISK MANAG, V4-5, P32, DOI 10.1016/j.crm.2014.08.001
   Lemos MC, 2012, NAT CLIM CHANGE, V2, P789, DOI [10.1038/NCLIMATE1614, 10.1038/nclimate1614]
   Li HY, 2018, J TRAVEL RES, V57, P178, DOI 10.1177/0047287516687409
   Lorde T, 2016, J TRAVEL RES, V55, P946, DOI 10.1177/0047287515592852
   Ma SY, 2020, TOURISM MANAGE, V80, DOI 10.1016/j.tourman.2020.104105
   Mackay EA, 2017, WORLDW HOSP TOUR THE, V9, P44, DOI 10.1108/WHATT-11-2016-0069
   MAHON R., 2018, Social and Economic Studies, P239
   Mahon R, 2019, CLIM SERV, V13, P14, DOI 10.1016/j.cliser.2019.01.002
   Martinez R., 2012, IMPROVING CLIMATE RI
   Matthews L, 2021, CURR ISSUES TOUR, V24, P1576, DOI 10.1080/13683500.2020.1816928
   Matthews L, 2021, INT J BIOMETEOROL, V65, P749, DOI 10.1007/s00484-019-01799-7
   Matzarakis A, 2006, TOUR PLAN DEV, V3, P99, DOI 10.1080/14790530600938279
   McNie EC, 2007, ENVIRON SCI POLICY, V10, P17, DOI 10.1016/j.envsci.2006.10.004
   Méndez-Lázaro PA, 2014, ECOL SOC, V19, DOI 10.5751/ES-06380-190211
   Moghal Z, 2015, CLIMATE CHANGE VULNE
   Moore W.R., 2010, The supply side effects of climate change on tourism
   Moore WR, 2010, CURR ISSUES TOUR, V13, P495, DOI 10.1080/13683500903576045
   Nalau J, 2017, WEATHER CLIM SOC, V9, P377, DOI 10.1175/WCAS-D-16-0078.1
   Nerem RS, 2018, P NATL ACAD SCI USA, V115, P2022, DOI 10.1073/pnas.1717312115
   Ochieng R., 2017, Open Access Libr, V4, P1, DOI [10.4236/oalib.1103826, DOI 10.4236/OALIB.1103826]
   Oduber M., 2017, Journal of Tourism Research & Hospitality, V2017, DOI [10.4172/2324-8807.1000159, DOI 10.4172/2324-8807.1000159]
   Pagano TC, 2002, CLIMATE RES, V21, P259, DOI 10.3354/cr021259
   Rayner S, 2005, CLIMATIC CHANGE, V69, P197, DOI 10.1007/s10584-005-3148-z
   Ridderstaat J, 2014, TOURISM MANAGE, V41, P245, DOI 10.1016/j.tourman.2013.09.005
   Rosselló J, 2020, TOURISM MANAGE, V79, DOI 10.1016/j.tourman.2020.104080
   Rutty M, 2013, CLIM RES, V57, P259, DOI 10.3354/cr01183
   Rutty M, 2021, INT J BIOMETEOROL, V65, P639, DOI 10.1007/s00484-020-02070-0
   Rutty M, 2020, ATMOSPHERE-BASEL, V11, DOI 10.3390/atmos11040412
   Rutty M, 2014, TOURISM GEOGR, V16, P346, DOI 10.1080/14616688.2014.932833
   Scott D, 2010, PROCEDIA ENVIRON SCI, V1, P146, DOI 10.1016/j.proenv.2010.09.011
   Scott D, 2019, ANN TOURISM RES, V77, P49, DOI 10.1016/j.annals.2019.05.007
   Scott D, 2012, J SUSTAIN TOUR, V20, P883, DOI 10.1080/09669582.2012.699063
   Scott DJ, 2011, CLIM RES, V47, P111, DOI 10.3354/cr00952
   Soares MB, 2016, CLIMATIC CHANGE, V137, P89, DOI 10.1007/s10584-016-1671-8
   Soares MB, 2015, CLIM RISK MANAG, V10, P8, DOI 10.1016/j.crm.2015.07.001
   Sookram S., 2009, Caribbean Development Report, V2, P204
   Sookram S., ECLAC PROJECT DOCUME, V2, P204
   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]
   Vaughan Catherine, 2016, Climate Services, V4, P65, DOI 10.1016/j.cliser.2016.11.004
   Weijerman M, 2018, J APPL ECOL, V55, P1823, DOI 10.1111/1365-2664.13105
   World Meteorological Organization-WMO, 2016, CLIM SERV SUPP CLIM
   World Travel and Tourism Council (WTTC), 2020, TRAV TOUR EC IMP 202
NR 84
TC 15
Z9 15
U1 10
U2 31
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 100262
DI 10.1016/j.cliser.2021.100262
EA NOV 2021
PG 13
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 YE2EY
UT WOS:000740944100004
OA gold
DA 2025-01-10
ER

PT J
AU Brown, A
   Dowdy, A
AF Brown, Andrew
   Dowdy, Andrew
TI Severe Convective Wind Environments and Future Projected Changes in
   Australia
SO JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
LA English
DT Article
DE climate; convection; thunderstorms; wind; reanalysis; projections
ID SEVERE THUNDERSTORM ENVIRONMENTS; HIGH-SHEAR; CLIMATOLOGY; MODEL;
   PARAMETERS; DOWNBURST; TRENDS; EVENT; GUSTS; STORM
AB Thunderstorms can produce severe convective winds (SCWs) that damage buildings and other infrastructure such as electricity transmission towers. Understanding the climatology of SCWs is therefore important for planning and risk management. An archive of observed SCWs is used to examine a diverse set of diagnostics for indicating SCW environments based on reanalysis data. These diagnostics are then applied to climate model data to examine projections of future climate change for Australia. A diagnostic based on logistic regression is found to provide a better representation of observed SCW occurrences than other diagnostics. Projections for the future based on that diagnostic indicate increases and decreases between -16% and 34% in the occurrence frequency of regionally averaged SCW environments, based on the 10th and 90th percentile estimates of annual mean changes from a 12-member ensemble of global climate models. Projections based on other severe weather diagnostics indicate a wider range of future changes, including increases and decreases of up to 50% in magnitude, with regional and seasonal variations through Australia. Changes in the frequency of SCW environments appears to be largely driven by increased low level moisture concentrations which can lead to increased convective available potential energy, countered in some cases by a stabilization of the mid-troposphere temperature lapse rate. These results represent the most comprehensive estimate to date for constraining the range of uncertainty in projected future changes in convective environments for Australia, including severe thunderstorms and associated SCWs, noting that this has significant implications for risk management and climate adaptation purposes.
C1 [Brown, Andrew; Dowdy, Andrew] Bur Meteorol, Melbourne, Vic, Australia.
C3 Bureau of Meteorology - Australia
RP Brown, A (corresponding author), Bur Meteorol, Melbourne, Vic, Australia.
EM andrew.brown@bom.gov.au
RI Dowdy, Andrew/AAI-6395-2020; Brown, Andrew/LFV-3050-2024; Dowdy,
   Andrew/J-3414-2016
OI Dowdy, Andrew/0000-0003-0720-4471; Brown, Andrew/0000-0001-7354-295X
FU Energy Sector Climate Information (ESCI) project of the Australian
   Government; ESCC Hub of the Australian Government's National
   Environmental Science Program (NESP)
FX This work was supported by the Energy Sector Climate Information (ESCI)
   project of the Australian Government and the ESCC Hub of the Australian
   Government's National Environmental Science Program (NESP). Comments on
   earlier drafts by Acacia Pepler and Justin Peter from the Bureau of
   Meteorology are gratefully acknowledged. Curation of a replica MERRA-2
   data set on the Australian National Computing Infrastructure by Paola
   Petrelli is gratefully acknowledged.
CR Allen J.T., 2018, CLIMATE CHANGE SEVER, DOI [10.1093/acrefore/9780190228620.001.0001/acrefore-9780190228620-e-62, DOI 10.1093/ACREFORE/9780190228620.001.0001/ACREFORE-9780190228620-E-62]
   Allen JT, 2016, ATMOS RES, V178, P347, DOI 10.1016/j.atmosres.2016.03.011
   Allen JT, 2014, J CLIMATE, V27, P3848, DOI 10.1175/JCLI-D-13-00426.1
   Allen JT, 2014, J CLIMATE, V27, P3827, DOI 10.1175/JCLI-D-13-00425.1
   Allen JT, 2014, INT J CLIMATOL, V34, P81, DOI 10.1002/joc.3667
   Allen JT, 2011, AUST METEOROL OCEAN, V61, P143, DOI 10.22499/2.6103.001
   [Anonymous], 2015, Merra-2: 3d,3-hourly,instantaneous,pressure-level,assimilation, DOI DOI 10.5067/QBZ6MG944HW0
   Azorin-Molina C, 2021, J CLIMATE, V34, P3103, DOI 10.1175/JCLI-D-20-0590.1
   Azorin-Molina C, 2019, INT J CLIMATOL, V39, P2260, DOI 10.1002/joc.5949
   Blumberg WG, 2017, B AM METEOROL SOC, V98, P1625, DOI 10.1175/BAMS-D-15-00309.1
   Brooks HE, 2013, ATMOS RES, V123, P129, DOI 10.1016/j.atmosres.2012.04.002
   Brooks HE, 2003, ATMOS RES, V67-8, P73, DOI 10.1016/S0169-8095(03)00045-0
   Brown A., 2019, 034 BUR RES
   Brown A, 2021, J SO HEMISPH EARTH, V71, P30, DOI 10.1071/ES19052
   Coniglio MC, 2006, J ATMOS SCI, V63, P1231, DOI 10.1175/JAS3681.1
   CSIRO  & Bureau of Meteorology, 2015, CLIMATE CHANGE AUSTR
   De Meutter P, 2015, MON WEATHER REV, V143, P742, DOI 10.1175/MWR-D-14-00290.1
   Doswell CA, 2003, ATMOS RES, V67-8, P117, DOI 10.1016/S0169-8095(03)00047-4
   DOSWELL CA, 1990, WEATHER FORECAST, V5, P576, DOI 10.1175/1520-0434(1990)005<0576:OSMOSI>2.0.CO;2
   Dowdy A.J., 2015, P MOD SIM SOC AUSTR, DOI [10.36334/modsim.2015.g4.dowdy, DOI 10.36334/MODSIM.2015.G4.DOWDY]
   Dowdy AJ, 2020, CLIM DYNAM, V54, P3041, DOI 10.1007/s00382-020-05167-9
   Geerts B, 2001, WEATHER FORECAST, V16, P261, DOI 10.1175/1520-0434(2001)016<0261:EDRMSW>2.0.CO;2
   Gelaro R, 2017, J CLIMATE, V30, P5419, DOI 10.1175/JCLI-D-16-0758.1
   Gensini VA, 2018, NPJ CLIM ATMOS SCI, V1, DOI 10.1038/s41612-018-0048-2
   Grose MR, 2020, EARTHS FUTURE, V8, DOI 10.1029/2019EF001469
   Hawbecker P, 2017, WIND ENERGY, V20, P1803, DOI 10.1002/we.2122
   Hersbach H, 2020, Q J ROY METEOR SOC, V146, P1999, DOI 10.1002/qj.3803
   Holmes J.D., 2002, AUST J STRUCT ENG, V4, P29
   Holzworth RH, 2021, GEOPHYS RES LETT, V48, DOI 10.1029/2020GL091366
   Kuchera EL, 2006, WEATHER FORECAST, V21, P595, DOI 10.1175/WAF931.1
   Kunkel KE, 2013, B AM METEOROL SOC, V94, P499, DOI 10.1175/BAMS-D-11-00262.1
   Ladds M, 2017, INT J DISAST RISK RE, V21, P419, DOI 10.1016/j.ijdrr.2017.01.004
   Ladwig William, 2017, CISL RDA
   Mason SJ, 2002, Q J ROY METEOR SOC, V128, P2145, DOI 10.1256/003590002320603584
   May R., 2016, METPY PYTHON PACKAGE, DOI DOI 10.5065/D6WW7G29
   Middelmann M., 2007, Natural Hazards in Australia: Identifying Risk Analysis Requirements
   Miller PW, 2018, NAT HAZARD EARTH SYS, V18, P1261, DOI 10.5194/nhess-18-1261-2018
   Miller R.C., 1972, NOTES ANAL SEVERE ST
   Mills GA, 1998, WEATHER FORECAST, V13, P1078, DOI 10.1175/1520-0434(1998)013<1078:OPOSTE>2.0.CO;2
   Mohr S, 2017, NAT HAZARD EARTH SYS, V17, P957, DOI 10.5194/nhess-17-957-2017
   Niall S, 2005, INT J CLIMATOL, V25, P1933, DOI 10.1002/joc.1233
   Pacey GP, 2021, WEATHER FORECAST, V36, P237, DOI 10.1175/WAF-D-20-0075.1
   Pryor KL, 2015, WEATHER FORECAST, V30, P1182, DOI 10.1175/WAF-D-14-00106.1
   Púcik T, 2017, J CLIMATE, V30, P6771, DOI 10.1175/JCLI-D-16-0777.1
   Rädler AT, 2018, J APPL METEOROL CLIM, V57, P569, DOI 10.1175/JAMC-D-17-0132.1
   Richter H, 2014, MON WEATHER REV, V142, P3038, DOI 10.1175/MWR-D-13-00405.1
   Romanic D, 2020, MON WEATHER REV, V148, P3747, DOI 10.1175/MWR-D-19-0312.1
   Seabold Skipper, 2010, P 9 PYTH SCI C AUST, V57, P10, DOI DOI 10.25080/MAJORA-92BF1922-011
   Sherburn KD, 2016, WEATHER FORECAST, V31, P1899, DOI 10.1175/WAF-D-16-0086.1
   Sherburn KD, 2014, WEATHER FORECAST, V29, P854, DOI 10.1175/WAF-D-13-00041.1
   SHERMAN DJ, 1987, MON WEATHER REV, V115, P1193, DOI 10.1175/1520-0493(1987)115<1193:TPOAWT>2.0.CO;2
   Smith A., 2020, 2010-2019: A landmark decade of us. billion-dollar weather and climate disasters
   Smith BT, 2013, WEATHER FORECAST, V28, P229, DOI 10.1175/WAF-D-12-00096.1
   Spassiani A.C, 2020, THESIS U QUEENSLAND, DOI [10.14264/UQL.2020.901, DOI 10.14264/UQL.2020.901]
   Spassiani AC, 2021, J WIND ENG IND AEROD, V210, DOI 10.1016/j.jweia.2021.104529
   Stocker, 2014, CLIMATE CHANGE 2013
   Su CH, 2019, GEOSCI MODEL DEV, V12, P2049, DOI 10.5194/gmd-12-2049-2019
   Taszarek M, 2020, J CLIMATE, V33, P10263, DOI 10.1175/JCLI-D-20-0346.1
   Taszarek M, 2017, MON WEATHER REV, V145, P1511, DOI 10.1175/MWR-D-16-0384.1
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Thompson RL, 2007, WEATHER FORECAST, V22, P102, DOI 10.1175/WAF969.1
   Timbal B, 2010, J CLIMATE, V23, P2440, DOI 10.1175/2009JCLI3456.1
   Trapp RJ, 2009, GEOPHYS RES LETT, V36, DOI 10.1029/2008GL036203
   van Vuuren DP, 2011, CLIMATIC CHANGE, V109, P1, DOI 10.1007/s10584-011-0157-y
   Virts KS, 2013, B AM METEOROL SOC, V94, P1381, DOI 10.1175/BAMS-D-12-00082.1
   WAKIMOTO RM, 1985, MON WEATHER REV, V113, P1131, DOI 10.1175/1520-0493(1985)113<1131:FDMAOT>2.0.CO;2
NR 66
TC 16
Z9 16
U1 1
U2 13
PU AMER GEOPHYSICAL UNION
PI WASHINGTON
PA 2000 FLORIDA AVE NW, WASHINGTON, DC 20009 USA
SN 2169-897X
EI 2169-8996
J9 J GEOPHYS RES-ATMOS
JI J. Geophys. Res.-Atmos.
PD AUG 20
PY 2021
VL 126
IS 16
AR e2021JD034633
DI 10.1029/2021JD034633
PG 17
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA UF6UJ
UT WOS:000688706700012
OA hybrid
DA 2025-01-10
ER

PT J
AU Guan, XX
   Zhang, JY
   Bao, ZX
   Liu, CS
   Jin, JL
   Wang, GQ
AF Guan, Xiaoxiang
   Zhang, Jianyun
   Bao, Zhenxin
   Liu, Cuishan
   Jin, Junliang
   Wang, Guoqing
TI Past variations and future projection of runoff in typical basins in 10
   water zones, China
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE 10 water zones; Climate change; Runoff variation and projection; Climate
   elasticity method; Effects quantification
ID CLIMATE-CHANGE; REFERENCE EVAPOTRANSPIRATION; PRECIPITATION; ELASTICITY;
   STREAMFLOW; CATCHMENT; CMIP6
AB Understanding the historical and future changing characteristics of key climatic variables and runoff in 10 major river zones in China is essential for water resources evaluation and management. To this end, the historical and future changing trends of key hydrometeorological variables, including precipitation, potential evapotranspiration, and runoff were analyzed in detail for each water zone across China. The climate elasticity method was also established to quantify the impacts of climate change and human activities on historical runoff variations. The results indicate that the characteristics and causes of runoff variations in China were generally spatially heterogeneous. The runoff in water-scarce river basins of northern China decreased significantly during the period of 1961-2018, variations of which were more sensitive to human activities. For southern water zones in China, the runoff showed no significant trend and climate change was the main influencing factor. On basis of 9 Coupled Model Intercomparison Project Phase 6 (CMIP6) climate model ensemble simulations under three different shared socioeconomic pathways (ssp126, ssp245 and ssp585), the future runoff in 10 typical basins of the water zones were projected and the results suggested an increasing trend of runoff over China, thanks to increasing precipitation in the rest 21 century. While under ssp585, the rising air temperature tends to evaporate more water and offset the effect of precipitation increase to some extent, resulting in that the increments of runoff under ssp585 are not necessarily greater than those under ssp245 and ssp126. Overall, our study could be used as a basis to support climate adaptation strategies and policies to cope with future water resources conditions. (c) 2021 Elsevier B.V. All rights reserved.
C1 [Guan, Xiaoxiang] Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China.
   [Guan, Xiaoxiang; Zhang, Jianyun; Bao, Zhenxin; Liu, Cuishan; Jin, Junliang; Wang, Guoqing] Minist Water Resources, Res Ctr Climate Change, Nanjing 210029, Peoples R China.
   [Guan, Xiaoxiang; Zhang, Jianyun; Bao, Zhenxin; Jin, Junliang; Wang, Guoqing] Yangtze Inst Conservat & Dev, Nanjing 210098, Peoples R China.
   [Zhang, Jianyun; Bao, Zhenxin; Liu, Cuishan; Jin, Junliang; Wang, Guoqing] Nanjing Hydraul Res Inst, Slate Key Lab Hydrol Water Resources & Hydraul En, Nanjing 210029, Peoples R China.
C3 Hohai University; Nanjing Hydraulic Research Institute
RP Wang, GQ (corresponding author), Nanjing Hydraul Res Inst, 223 Guangzhou Rd, Nanjing 210029, Jiangsu, Peoples R China.
EM gqwang@nhri.cn
RI Bao, Zhenxin/LWZ-8554-2024; WANG, GUOQING/AAP-8796-2020; zhang,
   jianyun/X-7292-2018
OI Guan, Xiaoxiang/0000-0002-5791-6867
FU National Key Research and Development Programs of China [2016YFA0601501,
   2017YFA0605002, 2017YFA0605004]; National Natural Science Foundation of
   China [41830863, 51879164, 41961124007]
FX This study was financially supported by the National Key Research and
   Development Programs of China (Grants: 2016YFA0601501, 2017YFA0605002,
   2017YFA0605004) and the National Natural Science Foundation of China
   (Grants: 41830863, 51879164, 41961124007).
CR Allen R.G., 1998, FAO Irrigation and Drainage Paper
   Arora VK, 2002, J HYDROL, V265, P164, DOI 10.1016/S0022-1694(02)00101-4
   Bao ZX, 2020, J WATER CLIM CHANGE, V11, P1551, DOI 10.2166/wcc.2019.095
   Berghuijs WR, 2014, NAT CLIM CHANGE, V4, P583, DOI [10.1038/nclimate2246, 10.1038/NCLIMATE2246]
   Berti A, 2014, AGR WATER MANAGE, V140, P20, DOI 10.1016/j.agwat.2014.03.015
   Budyko M. I., 1974, CLIMATE LIFE
   Chen HP, 2020, SCI BULL, V65, P1415, DOI 10.1016/j.scib.2020.05.015
   [陈洁 Chen Jie], 2019, [自然资源学报, Journal of Natural Resources], V34, P2440
   Dey P, 2017, J HYDROL, V548, P278, DOI 10.1016/j.jhydrol.2017.03.014
   [丁加丽 DING Jiali], 2007, [河海大学学报. 自然科学版, Journal of Hohai University. Natural Sciences], V35, P633
   Donohue RJ, 2012, J HYDROL, V436, P35, DOI 10.1016/j.jhydrol.2012.02.033
   Ficklin DL, 2009, J HYDROL, V374, P16, DOI 10.1016/j.jhydrol.2009.05.016
   Fu B.P., 1981, Sci. Atmos. Sin, V5, P23, DOI DOI 10.3878/J.ISSN.1006-9895.1981.01.03
   Gillett NP, 2016, GEOSCI MODEL DEV, V9, P3685, DOI 10.5194/gmd-9-3685-2016
   Guan X., 2018, J N CHINA U WATER RE, V39, P51, DOI DOI 10.3969/J.ISSN.1002-5634.2018.02.008
   Guan XX, 2021, METEOROL ATMOS PHYS, V133, P97, DOI 10.1007/s00703-020-00741-6
   Guo DL, 2017, WATER RESOUR RES, V53, P435, DOI 10.1002/2016WR019627
   [郭晓英 Guo Xiaoying], 2016, [中国水土保持科学, Science of Soil and Water Conservation], V14, P88
   Hargreaves G.H., 1985, APPL ENG AGRIC, V1, DOI [10.13031/2013.26773, DOI 10.13031/2013.26773]
   [何大明 He Daming], 2016, [水科学进展, Advances in Water Science], V27, P928
   [胡豪然 Hu Haoran], 2015, [西南大学学报. 自然科学版, Journal of Southwest University. Natural Science Edition], V37, P146
   Hu Y., CLIM CHANG RES
   Jiang DB, 2020, ADV ATMOS SCI, V37, P1102, DOI 10.1007/s00376-020-2034-y
   Jiang SH, 2011, HYDROL PROCESS, V25, P2492, DOI 10.1002/hyp.8002
   Kumar S, 2016, WATER RESOUR RES, V52, P3127, DOI 10.1002/2016WR018607
   Li HB, 2010, J GEOPHYS RES-ATMOS, V115, DOI 10.1029/2009JD012882
   Li ZL, 2020, SCI TOTAL ENVIRON, V716, DOI 10.1016/j.scitotenv.2020.137072
   [刘凯 Liu Kai], 2020, [地球科学进展, Advance in Earth Sciences], V35, P1113
   Lv XZ, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-51115-x
   Montanari A, 2013, HYDROLOG SCI J, V58, P1256, DOI 10.1080/02626667.2013.809088
   Montenegro A, 2010, HYDROL PROCESS, V24, P2705, DOI 10.1002/hyp.7825
   Nash JE., 1970, Journal of Hydrology, V10, P282, DOI [DOI 10.1016/0022-1694(70)90255-6, 10.1016/0022-1694(70)90255-6]
   O'Neill BC, 2017, GLOBAL ENVIRON CHANG, V42, P169, DOI 10.1016/j.gloenvcha.2015.01.004
   O'Neill BC, 2014, CLIMATIC CHANGE, V122, P387, DOI 10.1007/s10584-013-0905-2
   Pettitt A. N., 1979, Applied Statistics, V28, P126, DOI 10.2307/2346729
   [任国玉 Ren Guoyu], 2015, [水科学进展, Advances in Water Science], V26, P451
   Sankarasubramanian A, 2001, WATER RESOUR RES, V37, P1771, DOI 10.1029/2000WR900330
   Schaake J. C., 1990, Climate change and US water resources., P177
   [施雅风 Shi Yafeng], 2003, [第四纪研究, Quaternary Sciences], V23, P152
   [施雅风 Shi Yafeng], 2002, [冰川冻土, Journal of Glaciology and Geocryology], V24, P219
   Sivapalan M, 2003, HYDROL PROCESS, V17, P3163, DOI 10.1002/hyp.5155
   Stocker, 2014, CLIMATE CHANGE 2013
   Tang X., 2016, T CSAE, V32, P63, DOI DOI 10.11975/J.ISSN.1002-6819.2016.Z1.010
   Ul Islam S, 2019, HYDROL EARTH SYST SC, V23, P811, DOI 10.5194/hess-23-811-2019
   Verstraeten G, 2006, J GEOPHYS RES-ATMOS, V111, DOI 10.1029/2006JD007169
   Vetter T, 2017, CLIMATIC CHANGE, V141, P419, DOI 10.1007/s10584-016-1794-y
   Wang G.Q., 2020, ADV WATER SCI, V31, P313, DOI [10.14042/j.cnki.32.1309.2020.03.001, DOI 10.14042/J.CNKI.32.1309.2020.03.001]
   Wang GQ, 2016, WATER-SUI, V8, DOI 10.3390/w8060267
   Wang K., 2020, Clim. Chang. Res, V16, P306, DOI [10.12006/j.issn.1673-1719.2019.103, DOI 10.12006/J.ISSN.1673-1719.2019.103]
   Wang ZL, 2017, J HYDROL, V544, P97, DOI 10.1016/j.jhydrol.2016.11.021
   Xin XG, 2020, INT J CLIMATOL, V40, P6423, DOI 10.1002/joc.6590
   Xing WQ, 2018, GLOBAL PLANET CHANGE, V162, P120, DOI 10.1016/j.gloplacha.2018.01.006
   Yang X, 2018, J HYDROMETEOROL, V19, P609, DOI 10.1175/JHM-D-17-0180.1
   Yang XL, 2021, ADV ATMOS SCI, V38, P817, DOI 10.1007/s00376-021-0351-4
   Yang YH, 2009, J HYDROL, V374, P373, DOI 10.1016/j.jhydrol.2009.06.040
   Yao Y, 2021, WATER-SUI, V13, DOI 10.3390/w13081053
   Yin YY, 2020, EARTHS FUTURE, V8, DOI 10.1029/2020EF001492
   Yin YH, 2010, CHINESE SCI BULL, V55, P3329, DOI 10.1007/s11434-010-3289-y
   Yuan Z, 2018, MITIG ADAPT STRAT GL, V23, P27, DOI 10.1007/s11027-016-9727-7
   [张建云 Zhang Jianyun], 2020, [水科学进展, Advances in Water Science], V31, P153
   [张建云 ZHANG Jianyun], 2007, [水科学进展, Advances in Water Science], V18, P230
   Zheng HX, 2009, WATER RESOUR RES, V45, DOI 10.1029/2007WR006665
   Zheng J., 2018, RES RUNOFF EVOLUTION
   Zhu HH, 2020, ADV ATMOS SCI, V37, P1119, DOI 10.1007/s00376-020-9289-1
NR 64
TC 40
Z9 44
U1 12
U2 217
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 2021
VL 798
AR 149277
DI 10.1016/j.scitotenv.2021.149277
EA JUL 2021
PG 15
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA UY9LU
UT WOS:000701837400016
PM 34340074
OA Bronze
DA 2025-01-10
ER

PT J
AU Zielinski, T
   Bolzacchini, E
   Evans, K
   Ferrero, L
   Gregorczyk, K
   Kijewski, T
   Kotynska-Zielinska, I
   Mrowiec, P
   Oleszczuk, B
   Pakszys, P
   Piechowska, E
   Piwowarczyk, J
   Sobieszczanski, J
   Wichorowski, M
AF Zielinski, Tymon
   Bolzacchini, Ezio
   Evans, Karen
   Ferrero, Luca
   Gregorczyk, Klaudia
   Kijewski, Tomasz
   Kotynska-Zielinska, Izabela
   Mrowiec, Patrycja
   Oleszczuk, Barbara
   Pakszys, Paulina
   Piechowska, Ewa
   Piwowarczyk, Joanna
   Sobieszczanski, Jan
   Wichorowski, Marcin
TI Abundance of Environmental Data vs. Low Public Interest in Climate and
   Ocean Issues. Where Is the Missing Link?
SO FRONTIERS IN MARINE SCIENCE
LA English
DT Article
DE climate and ocean change; climate adaptation and mitigation;
   environmental data and observations; integrated knowledge sharing;
   climate and ocean literacy
ID EXPERIENCES; CONFIDENCE; KNOWLEDGE
AB Climate change and associated modification of the ocean is a fact, however, it seems to be the most undervalued and little understood "pandemic" challenge of this century. We live in a world where environmental data is increasingly being amassed and models are generating finer scale and increasingly dense numbers of outputs, resulting in the production of high level scientific information on climate and ocean. However, the knowledge generated is often inaccessible, incomprehensible and misunderstood by society. Given that society has access to many levels of information through various forms of media, how do we better share this knowledge, and improve understanding of how society is impacting their immediate and remote surroundings and what behavioral changes are needed for reducing those impacts? In this paper, we assess the level of environmental and ocean awareness among young learners. We argue that, despite the wide range of environmental data available and a common use of a broad range of media, this group is not aware of or interested in climate related issues. This paper highlights the challenges in bringing researchers, data managers and educators together to provide consistent, up-to-date messages that can appeal to and can be understood by modern societies. It also highlights insufficiencies in environmental school education, including those concerning the "uncertainty" concept, which is a fundamental part of any scientific process. In identifying these challenges, we propose a pathway for improving societal knowledge on climate and ocean changes that takes advantage of the technological abilities for environmental data collection, storage and processing, global and regional research, as well as good practices in ocean literacy and climate and ocean education.
C1 [Zielinski, Tymon; Gregorczyk, Klaudia; Kijewski, Tomasz; Oleszczuk, Barbara; Pakszys, Paulina; Piechowska, Ewa; Piwowarczyk, Joanna; Wichorowski, Marcin] Polish Acad Sci, Inst Oceanol, Sopot, Poland.
   [Bolzacchini, Ezio; Ferrero, Luca] Univ Milano Bicocca, Dept Earth & Environm Sci, GEMMA & POLARIS Res Ctr, Milan, Italy.
   [Evans, Karen] CSIRO, Canberra, NSW, Australia.
   [Kotynska-Zielinska, Izabela] Today We Have, Sopot, Poland.
   [Mrowiec, Patrycja; Sobieszczanski, Jan] Storware, Warsaw, Poland.
C3 Polish Academy of Sciences; Institute of Oceanology of the Polish
   Academy of Sciences; University of Milano-Bicocca; Commonwealth
   Scientific & Industrial Research Organisation (CSIRO)
RP Zielinski, T (corresponding author), Polish Acad Sci, Inst Oceanol, Sopot, Poland.; Mrowiec, P (corresponding author), Storware, Warsaw, Poland.
EM tymon@iopan.pl; p.mrowiec@storware.eu
RI evans, karen/D-7110-2012; Pakszys, Paulina/V-5150-2017
OI Kotynska-Zielinska, Izabela/0000-0002-7099-8692; Kijewski,
   Tomasz/0000-0002-3643-9483; Pakszys, Paulina/0000-0001-6098-8215;
   Zielinski, Tymon/0000-0003-4712-8899; Piwowarczyk,
   Joanna/0000-0001-6864-5073; Wichorowski, Marcin/0000-0002-1498-9492
CR [Anonymous], 2014, MILL DEV GOALS REP 2
   [Anonymous], 2002, WORLD SUMM SUST DEV
   Bawden D, 2009, J INF SCI, V35, P180, DOI 10.1177/0165551508095781
   Beck S, 2011, REG ENVIRON CHANGE, V11, P297, DOI 10.1007/s10113-010-0136-2
   Cambridge International Examinations 2015, 2017, CAMBR INT AS A LEV I
   Cinner JE, 2016, NATURE, V535, P416, DOI 10.1038/nature18607
   Donert K., 2018, HDB RES ED DESIGN CL
   Evans K, 2019, FRONT MAR SCI, V6, DOI 10.3389/fmars.2019.00298
   Fauville G, 2018, MAR POLICY, V91, P85, DOI 10.1016/j.marpol.2018.01.034
   Ferrero L, 2015, INT J ENVIRON SCI TE, V12, P2777, DOI 10.1007/s13762-014-0680-2
   Ferrero L, 2013, ENVIRON SCI TECHNOL, V47, P3856, DOI 10.1021/es304790f
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fischer H, 2019, NAT CLIM CHANGE, V9, P776, DOI 10.1038/s41558-019-0563-0
   Gaines SD, 2018, SCI ADV, V4, DOI 10.1126/sciadv.aao1378
   González RD, 2019, KEY CHAL GEOGR, P1, DOI 10.1007/978-3-030-04750-4_1
   Gordon Foundation, 2015, RETH TOP WORLD ARCT, DOI [10.1126/sciadv.aao1378, DOI 10.1126/SCIADV.AAO1378]
   Heddy BC, 2017, SCI EDUC, V101, P765, DOI 10.1002/sce.21292
   HEDLUND G, 1994, STRATEGIC MANAGE J, V15, P73
   Holliman R., 2009, Investigating science communication in the information age: Implications for public engagement and popular media, P35
   Hulme M, 2010, PROG PHYS GEOG, V34, P705, DOI 10.1177/0309133310373719
   Jensen EA, 2020, FRONT COMMUN, V4, DOI 10.3389/fcomm.2019.00078
   Kahila J, 2020, GAMES CULT, V15, P685, DOI 10.1177/1555412019845592
   Kollmuss A., 2002, Environ Educ Res, V8, P239, DOI [10.1080/13504620220145401, DOI 10.1080/13504620220145401]
   Kopke K, 2019, FRONT MAR SCI, V6, DOI 10.3389/fmars.2019.00060
   Kotynska-Zielinska I, 2020, OCEANOLOGIA, V62, P576, DOI 10.1016/j.oceano.2020.03.006
   McCauley V, 2019, ENVIRON EDUC RES, V25, P280, DOI 10.1080/13504622.2018.1553234
   McKinley E, 2012, MAR POLICY, V36, P839, DOI 10.1016/j.marpol.2011.11.001
   Orr E., 2019, SESS REPORT 2018 SVA
   Patterson J, 2017, ENVIRON INNOV SOC TR, V24, P1, DOI 10.1016/j.eist.2016.09.001
   Pendleton L, 2020, P NATL ACAD SCI USA, V117, P9652, DOI 10.1073/pnas.2005485117
   Peters MA, 2020, EDUC PHILOS THEORY, V52, P1, DOI 10.1080/00131857.2019.1593033
   Rubio-Iglesias JM, 2020, FRONT CLIM, V2, DOI 10.3389/fclim.2020.600998
   Serban A., 2002, OVERVIEW KNOWLEDGE M
   Sibbel A., 2009, International Journal of Sustainability in Higher Education, V10, P68, DOI DOI 10.1108/14676370910925262
   Stoll-Kleemann S, 2019, FRONT MAR SCI, V6, DOI 10.3389/fmars.2019.00273
   Sundblad EL, 2009, ENVIRON BEHAV, V41, P281, DOI 10.1177/0013916508314998
   Terorotua H, 2020, FRONT MAR SCI, V7, DOI 10.3389/fmars.2020.00160
   UN, 2017, FIRST GLOBAL INTEGRA
   UN, 2017, 1 GLOB INT MAR ASS O
   United Nations, 2019, PROGR PERF REP 2018
   United Nations, 2018, REV ROADM UN DEC OC
   Van den Heuvel F., 2020, SESS REPORT 2019 SVA
   Vedder-Weiss D, 2011, J RES SCI TEACH, V48, P199, DOI 10.1002/tea.20398
   Williamson P, 2016, NATURE, V540, P171, DOI 10.1038/540171a
   Wisz MS, 2020, FRONT MAR SCI, V7, DOI 10.3389/fmars.2020.00576
   Zins C, 2007, J AM SOC INF SCI TEC, V58, P479, DOI 10.1002/asi.20508
   Zusho A, 2003, INT J SCI EDUC, V25, P1081, DOI 10.1080/0950069032000052207
NR 47
TC 4
Z9 5
U1 1
U2 13
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 FEB 22
PY 2021
VL 8
DI 10.3389/fmars.2021.619638
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 QR2ZZ
UT WOS:000625083900001
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Lakoba, VT
   Barney, JN
AF Lakoba, Vasiliy T.
   Barney, Jacob N.
TI Home climate and habitat drive ecotypic stress response differences in
   an invasive grass
SO AOB PLANTS
LA English
DT Article
DE Agricultural weeds; climate adaptation; ecotype; invasive plants; plant
   stress; rapid adaptation
ID LOCAL ADAPTATION; SORGHUM-HALEPENSE; PHENOTYPIC PLASTICITY;
   DROUGHT-RESISTANCE; BIOMASS ALLOCATION; RAPID EVOLUTION; ATMOSPHERIC
   CO2; LAND-USE; SOIL; ROOT
AB Invasive plants and agricultural weeds are a ubiquitous and ever-expanding threat to biosecurity, biodiversity and ecosystem services. Many of these species are known to succeed through rapid adaptation to biotic and abiotic stress regimes, often in highly disturbed systems. Given the current state of evidence for selection of weedy genotypes via primary physiological stresses like drought, flooding, heat, cold and nutrient deficiency, we posit that adaptation to land management regimes which comprise suites of these stresses can also be expected. To establish this link, we tested adaptation to water and nutrient stresses in five non-agricultural and five agricultural populations of the invader Johnsongrass (Sorghum halepense) sampled across a broad range of climates in the USA. We subjected seedlings from each population to factorial drought and nutrient stresses in a common garden greenhouse experiment. Agricultural and non-agricultural ecotypes did not respond differently to experimentally applied stresses. However, non-agricultural populations from more drought-prone and nutrient-poor locations outperformed their agricultural counterparts in shoot allocation and chlorophyll production, respectively. We also found evidence for root allocation adaptation to hotter climates, in line with other C4 grasses, while greater adaptation to drought treatment was associated with soil organic carbon (SOC)-rich habitats. These findings imply that adaptation to land-use types can interact with other macrohabitat parameters, which will be fluctuating in a changing climate and resource-needy world. We see that invasive plants are poised to take on novel habitats within their introduced ranges, leading to complications in the prevention and management of their spread.
C1 [Lakoba, Vasiliy T.; Barney, Jacob N.] Virginia Tech, Sch Plant & Environm Sci, Blacksburg, VA 24061 USA.
C3 Virginia Polytechnic Institute & State University
RP Lakoba, VT (corresponding author), Virginia Tech, Sch Plant & Environm Sci, Blacksburg, VA 24061 USA.
EM vtlakoba@vt.edu
RI Barney, Jacob/C-2412-2008
OI Lakoba, Vasiliy/0000-0003-4688-3067
FU Virginia Tech College of Agriculture and Life Sciences; National
   Institute of Food and Agriculture Global Food Security CAP
   [2015-68004-23492]
FX This work was supported by the Virginia Tech College of Agriculture and
   Life Sciences and the National Institute of Food and Agriculture Global
   Food Security CAP (2015-68004-23492 to J.N.B.).
CR Abbas AM, 2019, S AFR J BOT, V123, P228, DOI 10.1016/j.sajb.2019.03.018
   Acciaresi HA, 2010, WEED RES, V50, P481, DOI 10.1111/j.1365-3180.2010.00794.x
   Alirzayeva E, 2017, ENVIRON POLLUT, V220, P1024, DOI 10.1016/j.envpol.2016.11.041
   Cardoso JA, 2015, AOB PLANTS, V7, DOI 10.1093/aobpla/plv107
   Armbruster WS, 2014, AOB PLANTS, V6, DOI 10.1093/aobpla/plu003
   Atwater DZ, 2018, J PLANT ECOL, V11, P189, DOI 10.1093/jpe/rtw124
   Atwater DZ, 2016, ECOGRAPHY, V39, P894, DOI 10.1111/ecog.02031
   Ball C., 1902, USDA BUREAU PLANT IN, V11, P3
   Baruch Z, 2005, OECOLOGIA, V145, P522, DOI 10.1007/s00442-005-0153-x
   Battles AC, 2019, GLOBAL CHANGE BIOL, V25, P562, DOI 10.1111/gcb.14509
   Berger JD, 2014, J EXP BOT, V65, P6219, DOI 10.1093/jxb/eru006
   BURT GW, 1974, WEED SCI, V22, P59, DOI 10.1017/S0043174500036523
   Carvajal DE, 2017, PERSPECT PLANT ECOL, V29, P12, DOI 10.1016/j.ppees.2017.10.001
   Catford JA, 2012, PERSPECT PLANT ECOL, V14, P231, DOI 10.1016/j.ppees.2011.12.002
   Cavero J, 2009, AGRON J, V101, P854, DOI 10.2134/agronj2008.0224x
   Chapin F. S. III, 1987, Genetic aspects of plant mineral nutrition  Developments in Plant and Soil Sciences, 27., P15
   Cheng WG, 2016, SOIL SCI PLANT NUTR, V62, P212, DOI 10.1080/00380768.2016.1155169
   CLARK RB, 1991, PLANT SOIL, V130, P97, DOI 10.1007/BF00011862
   Crooks JA, 2011, BIOL INVASIONS, V13, P165, DOI 10.1007/s10530-010-9799-3
   Davidson AM, 2011, ECOL LETT, V14, P419, DOI 10.1111/j.1461-0248.2011.01596.x
   Decker KL, 2012, INVAS PLANT SCI MANA, V5, P108, DOI 10.1614/IPSM-D-11-00007.1
   Delêtre M, 2017, EVOL APPL, V10, P498, DOI 10.1111/eva.12472
   Dimkpa CO, 2020, SCI TOTAL ENVIRON, V722, DOI 10.1016/j.scitotenv.2020.137808
   Ehleringer JR, 1997, OECOLOGIA, V112, P285, DOI 10.1007/s004420050311
   Engel Katharina, 2011, Communicative & Integrative Biology, V4, P247, DOI 10.4161/cib.4.3.14885
   Espeland EK, 2013, J ARID LAND, V5, P268, DOI 10.1007/s40333-013-0163-1
   Eziz A, 2017, ECOL EVOL, V7, P11002, DOI 10.1002/ece3.3630
   Fahey C, 2018, ECOLOGY, V99, P2692, DOI 10.1002/ecy.2536
   Filippou P, 2014, ENVIRON EXP BOT, V97, P1, DOI 10.1016/j.envexpbot.2013.09.010
   Funk JL, 2008, J ECOL, V96, P1162, DOI 10.1111/j.1365-2745.2008.01435.x
   Gaertner M, 2017, BIOL INVASIONS, V19, P3461, DOI 10.1007/s10530-017-1598-7
   Gao SB, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-21557-w
   Garrido E, 2012, NEW PHYTOL, V193, P445, DOI 10.1111/j.1469-8137.2011.03923.x
   Gervasi DDL, 2017, NAT COMMUN, V8, DOI 10.1038/ncomms14691
   Gitelson AA, 1999, REMOTE SENS ENVIRON, V69, P296, DOI 10.1016/S0034-4257(99)00023-1
   Gorton AJ., 2018, P ROY SOC B-BIOL SCI, P1
   Hengl T, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0105992
   Henn JJ, 2018, FRONT PLANT SCI, V9, DOI 10.3389/fpls.2018.01548
   Johnson NC, 2010, P NATL ACAD SCI USA, V107, P2093, DOI 10.1073/pnas.0906710107
   Kausar Abida, 2019, Journal of Applied Biology & Biotechnology, V7, P53, DOI 10.7324/JABB.2019.70310
   Kawecki TJ, 2004, ECOL LETT, V7, P1225, DOI 10.1111/j.1461-0248.2004.00684.x
   Kour D, 2020, BIOCATAL AGR BIOTECH, V23, DOI 10.1016/j.bcab.2020.101501
   Kueffer C, 2013, NEW PHYTOL, V200, P615, DOI 10.1111/nph.12415
   Lavergne S, 2010, ANN BOT-LONDON, V105, P109, DOI 10.1093/aob/mcp271
   Leguizamón ES, 2011, CAN J PLANT SCI, V91, P1011, DOI [10.4141/CJPS10202, 10.4141/cjps10202]
   Leimu R, 2008, PLOS ONE, V3, DOI 10.1371/journal.pone.0004010
   Li QQ, 2008, PLANT PROD SCI, V11, P161, DOI 10.1626/pps.11.161
   Liu YN, 2019, ECOL INDIC, V101, P249, DOI 10.1016/j.ecolind.2019.01.029
   Lowry DB, 2014, AM NAT, V183, P682, DOI 10.1086/675760
   Lustenhouwer N, 2019, J ECOL, V107, P396, DOI 10.1111/1365-2745.13045
   Malíková L, 2016, EVOL ECOL, V30, P861, DOI 10.1007/s10682-016-9845-4
   Matesanz S, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0044955
   MCWHORTER CG, 1971, WEED SCI, V19, P496, DOI 10.1017/S0043174500050517
   Molina-Montenegro MA, 2018, FRONT PLANT SCI, V9, DOI 10.3389/fpls.2018.00208
   Oduor AMO, 2016, J ECOL, V104, P957, DOI 10.1111/1365-2745.12578
   Papafilippaki A, 2020, SCI HORTICULTURAE, V261, P1
   Park W, 2012, SOIL SCI PLANT NUTR, V58, P334, DOI 10.1080/00380768.2012.684643
   Postma FM, 2016, P NATL ACAD SCI USA, V113, P7590, DOI 10.1073/pnas.1606303113
   Qi YL, 2019, GLOB ECOL CONSERV, V18, DOI 10.1016/j.gecco.2019.e00606
   Rajakaruna N, 2018, BOT REV, V84, P39, DOI 10.1007/s12229-017-9193-2
   Razgour O, 2019, P NATL ACAD SCI USA, V116, P10418, DOI 10.1073/pnas.1820663116
   Reich PB, 2014, P NATL ACAD SCI USA, V111, P13721, DOI 10.1073/pnas.1216053111
   Rout ME, 2013, AM J BOT, V100, P1726, DOI 10.3732/ajb.1200577
   Sakaguchi S, 2019, J ECOL, V107, P418, DOI 10.1111/1365-2745.13034
   Salas RA, 2016, PEST MANAG SCI, V72, P864, DOI 10.1002/ps.4241
   Sanchez AC, 2002, PLANT MOL BIOL, V48, P713, DOI 10.1023/A:1014894130270
   Schneider LC, 2006, J LAT AM GEOGR, V5, P91, DOI 10.1353/lag.2006.0028
   Schwinning S, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0176042
   Sezen UU, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0164584
   te Beest M, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0068274
   THORNLEY JH, 1972, ANN BOT-LONDON, V36, P431, DOI 10.1093/oxfordjournals.aob.a084602
   Turner KG, 2014, NEW PHYTOL, V202, P309, DOI 10.1111/nph.12634
   van Boheemen LA, 2019, NEW PHYTOL, V222, P614, DOI 10.1111/nph.15564
   Vetter VMS, 2020, GLOBAL CHANGE BIOL, V26, P3539, DOI 10.1111/gcb.15025
   WARWICK SI, 1983, CAN J PLANT SCI, V63, P997, DOI 10.4141/cjps83-125
   WARWICK SI, 1986, WEED RES, V26, P381, DOI 10.1111/j.1365-3180.1986.tb00721.x
   Washburn JD, 2013, BIOENERG RES, V6, P822, DOI 10.1007/s12155-013-9305-8
   Bin W, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0141567
   Whitney KD, 2008, DIVERS DISTRIB, V14, P569, DOI 10.1111/j.1472-4642.2008.00473.x
   Wilsey BJ, 2006, OECOLOGIA, V150, P300, DOI 10.1007/s00442-006-0515-z
   WILSON JB, 1988, ANN BOT-LONDON, V61, P433, DOI 10.1093/oxfordjournals.aob.a087575
   Xia HB, 2011, NEW PHYTOL, V191, P1119, DOI 10.1111/j.1469-8137.2011.03766.x
   Yang RY, 2007, BOT STUD, V48, P453
   Yuan X., 2018, PLOS ONE, V13, P1
   Zeng XT, 2013, PLOS ONE, V8, DOI [10.1371/journal.pone.0079074, 10.1371/journal.pone.0083135]
   Zhou HR, 2018, P NATL ACAD SCI USA, V115, P12057, DOI 10.1073/pnas.1718988115
NR 86
TC 5
Z9 5
U1 2
U2 13
PU OXFORD UNIV PRESS
PI OXFORD
PA GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND
SN 2041-2851
J9 AOB PLANTS
JI Aob Plants
PD NOV 24
PY 2020
VL 12
IS 6
AR plaa062
DI 10.1093/aobpla/plaa062
PG 9
WC Plant Sciences; Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences; Environmental Sciences & Ecology
GA PR3GE
UT WOS:000607126700001
PM 33408848
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Willems, JJ
   Molenveld, A
   Voorberg, W
   Brinkman, G
AF Willems, Jannes J.
   Molenveld, Astrid
   Voorberg, William
   Brinkman, Geert
TI Diverging Ambitions and Instruments for Citizen Participation across
   Different Stages in Green Infrastructure Projects
SO URBAN PLANNING
LA English
DT Article
DE climate adaptation; community involvement; green infrastructure;
   participation; policy instruments; urban water management
ID POLICY INSTRUMENTS; PUBLIC-PARTICIPATION; CLIMATE-CHANGE; GOVERNANCE;
   ADAPTATION; COPRODUCTION; MANAGEMENT; INNOVATION; FRAMEWORK; DESIGN
AB Both theory and practice increasingly argue that creating green infrastructure in order to make cities climate-proof requires joint public service delivery across the green infrastructure's lifecycle. Accordingly, citizen participation in each green infrastructure project stage is required, but the type of participation may differ. So far, limited research has been conducted to detangle how participation in green infrastructure projects is operationalised along the different project stages. This article, therefore, presents a comparative case study of nine European green infrastructure projects, in which we aim to determine: (1) how participatory ambitions may differ across green infrastructure project phases; and (2) which instruments are used to realise the participatory ambitions for each phase and whether these instruments differ across stages. The cases demonstrate different participation ambitions and means in the three project phases distinguished in this article (i.e., design, delivery, and maintenance). The design and maintenance stages resulted in high participation ambitions using organisational instruments (e.g., living labs, partnerships with community groups) and market-based instruments (e.g., open calls). In the delivery phase, participation ambitions decreased significantly in our cases, relying on legal instruments (e.g., statutory consultation) and communicative instruments (e.g., community events). Altogether, our exploratory study helps to define participation across the green infrastructure lifecycle: Early stages focus on creating shared commitment that legitimises the green infrastructure, while later stages are also driven by instrumental motives (lowering management costs). Although theory argues for profound participation in the delivery stage as well, our cases show the contrary. Future research can assess this discrepancy.
C1 [Willems, Jannes J.; Molenveld, Astrid; Voorberg, William; Brinkman, Geert] Erasmus Univ, Erasmus Sch Behav & Social Studies, Dept Publ Adm & Sociol, NL-3000 DR Rotterdam, Netherlands.
   [Molenveld, Astrid] Univ Antwerp, Fac Social Sci, Dept Polit Sci, Res Grp Polit & Publ Governance, B-2000 Antwerp, Belgium.
C3 Erasmus University Rotterdam - Excl Erasmus MC; Erasmus University
   Rotterdam; University of Antwerp
RP Willems, JJ (corresponding author), Erasmus Univ, Erasmus Sch Behav & Social Studies, Dept Publ Adm & Sociol, NL-3000 DR Rotterdam, Netherlands.
EM willems@essb.eur.nl; molenveld@essb.eur.nl; voorberg@essb.eur.nl;
   brinkman@essb.eur.nl
RI Voorberg, William/IUO-3659-2023
OI Willems, Jannes/0000-0002-3318-9706; Brinkman, Geert/0009-0005-1089-4700
FU European Interreg Project BEGIN (Blue-Green Infrastructure through
   Social Innovation)
FX The authors gratefully acknowledge the input received from city-partners
   that participated in this research. This study is made possible with
   funding from the European Interreg Project BEGIN (Blue-Green
   Infrastructure through Social Innovation). The authors would also like
   to thank the three reviewers for their feedback, which has greatly
   improved the manuscript.
CR ARNSTEIN SR, 1969, J AM I PLANNERS, V35, P216, DOI 10.1080/01944366908977225
   Benedict M. A., 2002, Renewable Resources Journal, V20, P12
   Bouckaert G, 2010, PUB SECTOR ORGAN, P1, DOI 10.1057/9780230275256
   Brandsen T, 2017, INT REV ADM SCI, V83, P676, DOI 10.1177/0020852315592467
   Brown R, 2011, WATER RESOUR MANAG, V25, P4037, DOI 10.1007/s11269-011-9886-y
   Burton P, 2013, URBAN POLICY RES, V31, P399, DOI 10.1080/08111146.2013.778196
   Capano G, 2017, POLICY SCI, V50, P269, DOI 10.1007/s11077-016-9267-8
   Dai LP, 2018, INT J WATER RESOUR D, V34, P652, DOI 10.1080/07900627.2017.1372273
   Dunleavy P, 2006, J PUBL ADM RES THEOR, V16, P467, DOI 10.1093/jopart/mui057
   Dunston R, 2009, AUST J PUBL ADMIN, V68, P39, DOI 10.1111/j.1467-8500.2008.00608.x
   Faehnle M, 2014, LANDSCAPE URBAN PLAN, V130, P171, DOI 10.1016/j.landurbplan.2014.07.012
   Feldman RonJ., 2002, The Tools of Government: A Guide to the New Governance, P186
   Fletcher TD, 2015, URBAN WATER J, V12, P525, DOI 10.1080/1573062X.2014.916314
   Frantzeskaki N, 2019, ENVIRON SCI POLICY, V93, P101, DOI 10.1016/j.envsci.2018.12.033
   Hartley J, 2005, PUBLIC MONEY MANAGE, V25, P27
   Henstra D, 2016, CLIM POLICY, V16, P496, DOI 10.1080/14693062.2015.1015946
   Hood C., 1983, The Tools of Government
   Howlett M, 2000, CAN PUBLIC ADMIN, V43, P412, DOI 10.1111/j.1754-7121.2000.tb01152.x
   Hyde P, 2004, HUM RELAT, V57, P1407, DOI 10.1177/0018726704049415
   Innes J. E., 2004, Planning Theory & Practice, V5, P419, DOI DOI 10.1080/1464935042000293170
   Jerome G, 2017, ENVIRON RES, V158, P399, DOI 10.1016/j.envres.2017.05.037
   Kabisch N, 2016, ECOL SOC, V21, DOI 10.5751/ES-08373-210239
   Kassim H, 2010, WEST EUR POLIT, V33, P1, DOI 10.1080/01402380903354031
   Kotze T., 2003, Quality Assurance in Education, V11, P186, DOI DOI 10.1108/09684880310501377
   Krause RM, 2019, PUBLIC ADMIN REV, V79, P477, DOI 10.1111/puar.13025
   Lovell ST, 2013, LANDSCAPE ECOL, V28, P1447, DOI 10.1007/s10980-013-9912-y
   Mees HLP, 2019, ENVIRON POLICY GOV, V29, P198, DOI 10.1002/eet.1847
   Mees HLP, 2014, ECOL SOC, V19, DOI 10.5751/ES-06639-190258
   Osborne SP, 2006, PUBLIC MANAG REV, V8, P377, DOI 10.1080/14719030600853022
   Osborne SP, 2015, BRIT J MANAGE, V26, P424, DOI 10.1111/1467-8551.12094
   Osborne SP, 2013, AM REV PUBLIC ADM, V43, P135, DOI 10.1177/0275074012466935
   Porter D.O., 2013, New public governance, the third sector, and co-production, P163
   Rhodes RAW, 1996, POLIT STUD-LONDON, V44, P652, DOI 10.1111/j.1467-9248.1996.tb01747.x
   Rydin Y., 2000, LOCAL ENVIRON, V5, P153, DOI 10.1080/13549830050009328
   Scholl C, 2016, URBAN PLAN, V1, P89, DOI 10.17645/up.v1i4.749
   Sharp L., 2017, Reconnecting People and Water. Public Engagement and Sustainable Urban Water Management
   Uittenbroek CJ, 2019, J ENVIRON PLANN MAN, V62, P2529, DOI 10.1080/09640568.2019.1569503
   van Popering-Verkerk J, 2017, J CLEAN PROD, V169, P225, DOI 10.1016/j.jclepro.2017.04.141
   Vedung EO, 2011, Carrots, Sticks and Sermons. Policy Instruments & Their Evaluation, DOI DOI 10.4324/9781315081748
   Verhoest K., 2003, SAMENWERKING AFSTEMM
   Voorberg WH, 2015, PUBLIC MANAG REV, V17, P1333, DOI 10.1080/14719037.2014.930505
   Wilker J, 2016, PLAN PRACT RES, V31, P229, DOI 10.1080/02697459.2016.1158065
   Zidar K, 2017, URBAN PLAN, V2, P56, DOI 10.17645/up.v2i3.1038
NR 43
TC 17
Z9 19
U1 8
U2 59
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 2020
VL 5
IS 1
BP 22
EP 32
DI 10.17645/up.v5i1.2613
PG 11
WC Urban Studies
WE Emerging Sources Citation Index (ESCI)
SC Urban Studies
GA KU2VF
UT WOS:000519565300004
OA Green Published, gold
DA 2025-01-10
ER

PT J
AU Sánchez-García, D
   Bienvenido-Huertas, D
   Tristancho-Carvajal, M
   Rubio-Bellido, C
AF Sanchez-Garcia, Daniel
   Bienvenido-Huertas, David
   Tristancho-Carvajal, Monica
   Rubio-Bellido, Carlos
TI Adaptive Comfort Control Implemented Model (ACCIM) for Energy
   Consumption Predictions in Dwellings under Current and Future Climate
   Conditions: A Case Study Located in Spain
SO ENERGIES
LA English
DT Article
DE adaptive comfort; climate change; performance simulation; energy
   consumption; dwellings
ID THERMAL COMFORT; OFFICE BUILDINGS; DEMAND; IMPACT; TEMPERATURE;
   NETHERLANDS; PERFORMANCE; GUIDELINE; DESIGN
AB Currently, the knowledge of energy consumption in buildings of new and existing dwellings is essential to control and propose energy conservation measures. Most of the predictions of energy consumption in buildings are based on fixed values related to the internal thermal ambient and pre-established operation hypotheses, which do not reflect the dynamic use of buildings and users' requirements. Spain is a clear example of such a situation. This study suggests the use of an adaptive thermal comfort model as a predictive method of energy consumption in the internal thermal ambient, as well as several operation hypotheses, and both conditions are combined in a simulation model: the Adaptive Comfort Control Implemented Model (ACCIM). The behavior of ACCIM is studied in a representative case of the residential building stock, which is located in three climate zones with different characteristics (warm, cold, and mild climates). The analyses were conducted both in current and future scenarios with the aim of knowing the advantages and limitations in each climate zone. The results show that the average consumption of the current, 2050, and 2080 scenarios decreased between 23% and 46% in warm climates, between 19% and 25% in mild climates, and between 10% and 29% in cold climates by using such a predictive method. It is also shown that this method is more resilient to climate change than the current standard. This research can be a starting point to understand users' climate adaptation to predict energy consumption.
C1 [Sanchez-Garcia, Daniel; Tristancho-Carvajal, Monica; Rubio-Bellido, Carlos] Univ Seville, Dept Bldg Construct 2, E-41012 Seville, Spain.
   [Bienvenido-Huertas, David] Univ Seville, Dept Graph Express & Bldg Engn, E-41012 Seville, Spain.
C3 University of Sevilla; University of Sevilla
RP Rubio-Bellido, C (corresponding author), Univ Seville, Dept Bldg Construct 2, E-41012 Seville, Spain.
EM sangardaniel@gmail.com; jbienvenido@us.es; monicatristcar@gmail.com;
   carlosrubio@us.es
RI Rubio-Bellido, Carlos/K-1861-2014; Sanchez Garcia, Daniel/T-2234-2017;
   Bienvenido Huertas, Jose David/I-2976-2018
OI Rubio-Bellido, Carlos/0000-0001-6719-8793; Sanchez Garcia,
   Daniel/0000-0002-3080-0821; Bienvenido Huertas, Jose
   David/0000-0003-0716-8589
CR American National Standards Institute/American Society of Heating Refrigerating and Air Conditioning Engineers (ANSI/ASHRAE), 2014, ASHRAE GUID 14 2014, P146
   American National Standards Institute/American Society of Heating Refrigerating and Air Conditioning Engineers (ANSI/ASHRAE), 2013, 552013 ANSIASHRAE
   [Anonymous], 2007, 152512007 INDOOR ENV
   [Anonymous], BUILD DES CONSTR FOR
   [Anonymous], 2002, Off J Eur Union, P65, DOI [10.1039/ap9842100196, DOI 10.1039/AP9842100196]
   Barbadilla-Martín E, 2018, ENERG BUILDINGS, V167, P281, DOI 10.1016/j.enbuild.2018.02.033
   Barbadilla-Martín E, 2017, BUILD ENVIRON, V123, P163, DOI 10.1016/j.buildenv.2017.06.042
   Bienvenido-Huertas D, 2019, ENERGIES, V12, DOI 10.3390/en12071197
   Bienvenido-Huertas D, 2019, APPL ENERG, V233, P1, DOI 10.1016/j.apenergy.2018.10.052
   BIENVENIDOHUERTAS, 2018, ENERGIES, V11, DOI DOI 10.3390/EN11092222
   Boerstra AC, 2015, ARCHIT SCI REV, V58, P24, DOI 10.1080/00038628.2014.971702
   Castano-Rosa R., 2018, INDOOR BUILT ENVIRON, DOI [10.1177/1420326X18764783, DOI 10.1177/1420326X18764783]
   Cellura M, 2018, ENERGY SUSTAIN DEV, V45, P46, DOI 10.1016/j.esd.2018.05.001
   Di Pilla L, 2016, ENERG BUILDINGS, V112, P21, DOI 10.1016/j.enbuild.2015.11.050
   European Commission, 2011, ROADMAP TRANSFORMING, P1
   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]
   Horne R, 2008, J HOUS BUILT ENVIRON, V23, P119, DOI 10.1007/s10901-008-9105-1
   Hoyt T, 2015, BUILD ENVIRON, V88, P89, DOI 10.1016/j.buildenv.2014.09.010
   Isaac M, 2009, ENERG POLICY, V37, P507, DOI 10.1016/j.enpol.2008.09.051
   Jentsch M.F., 2013, CLIMATE CHANGE WORLD
   Kalvelage K, 2014, ENERG BUILDINGS, V76, P373, DOI 10.1016/j.enbuild.2014.03.009
   Karimpour M, 2015, ENERG BUILDINGS, V87, P142, DOI 10.1016/j.enbuild.2014.10.064
   Kramer R, 2017, BUILD ENVIRON, V118, P14, DOI 10.1016/j.buildenv.2017.03.028
   Kurtz F, 2015, INF CONSTR, V67, DOI 10.3989/ic.14.062
   Lowe R, 2007, BUILD RES INF, V35, P412, DOI 10.1080/09613210701238268
   Naspi F, 2018, J SENSORS, V2018, DOI 10.1155/2018/2756542
   Page J, 2008, ENERG BUILDINGS, V40, P83, DOI 10.1016/j.enbuild.2007.01.018
   Park KS, 2017, ENERGIES, V10, DOI 10.3390/en10101506
   Pérez-Andreu V, 2018, ENERGY, V165, P63, DOI 10.1016/j.energy.2018.09.015
   Pérez-Fargallo A, 2018, ENERG BUILDINGS, V178, P94, DOI 10.1016/j.enbuild.2018.08.030
   Pérez-Lombard L, 2008, ENERG BUILDINGS, V40, P394, DOI 10.1016/j.enbuild.2007.03.007
   Ren ZG, 2018, APPL ENERG, V210, P152, DOI 10.1016/j.apenergy.2017.10.110
   Roaf S., 2009, ADAPTING BUILDINGS C, V2nd
   Rubel F, 2010, METEOROL Z, V19, P135, DOI 10.1127/0941-2948/2010/0430
   Rubio-Bellido C, 2016, ENERGY, V114, P569, DOI 10.1016/j.energy.2016.08.021
   Sánchez-García D, 2019, ENERG BUILDINGS, V187, P173, DOI 10.1016/j.enbuild.2019.02.002
   Sánchez-García D, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10103507
   Sánchez CSG, 2017, BUILD ENVIRON, V114, P344, DOI 10.1016/j.buildenv.2016.12.029
   Spyropoulos GN, 2011, ENERG BUILDINGS, V43, P770, DOI 10.1016/j.enbuild.2010.12.015
   The Government of Spain, 2015, COD TECN ED DOC BAS
   Theodoridou I, 2011, ENERG BUILDINGS, V43, P2779, DOI 10.1016/j.enbuild.2011.06.036
   Tushar W, 2017, ENERG BUILDINGS, V134, P105, DOI 10.1016/j.enbuild.2016.10.027
   van der Linden AC, 2006, ENERG BUILDINGS, V38, P8, DOI 10.1016/j.enbuild.2005.02.008
   Wan KKW, 2011, ENERGY, V36, P1404, DOI 10.1016/j.energy.2011.01.033
   World Wildlife Fund, 2014, LIV PLAN REP 2014 SP, V1
   ,, 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 46
TC 33
Z9 33
U1 0
U2 10
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 1996-1073
J9 ENERGIES
JI Energies
PD APR 2
PY 2019
VL 12
IS 8
AR 1498
DI 10.3390/en12081498
PG 22
WC Energy & Fuels
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Energy & Fuels
GA HX9XP
UT WOS:000467762600091
OA Green Submitted, Green Published, gold
DA 2025-01-10
ER

PT J
AU Tesfaye, K
   Khatri-Chhetri, A
   Aggarwal, PK
   Mequanint, F
   Shirsath, PB
   Stirling, CM
   Jat, ML
   Rahut, DB
   Erenstein, O
AF Tesfaye, K.
   Khatri-Chhetri, A.
   Aggarwal, P. K.
   Mequanint, F.
   Shirsath, P. B.
   Stirling, C. M.
   Jat, M. L.
   Rahut, D. B.
   Erenstein, O.
TI Assessing climate adaptation options for cereal-based systems in the
   eastern Indo-Gangetic Plains, South Asia
SO JOURNAL OF AGRICULTURAL SCIENCE
LA English
DT Article
DE Climate change; climate smart agriculture; crop modelling; cropping
   systems; rice; wheat
ID RICE-WHEAT SYSTEMS; FARMERS MANAGING CLIMATE; CONSERVATION AGRICULTURE;
   CROPPING SYSTEM; SMALLHOLDER FARMERS; WATER-USE; SUSTAINABLE
   INTENSIFICATION; MODEL PREDICTIONS; FOOD-PRODUCTION; USE EFFICIENCY
AB New farming systems and management options are needed in South Asia as the intensive rice-wheat production system is set to become increasingly unsustainable under climate change. In the current study, six cropping systems options/treatments varying in tillage, crop establishment method, residue management, crop sequence and fertilizer and water management were evaluated using a cropping systems model under current (1980-2009) and future (2030 and 2050) climate scenarios in the state of Bihar, India. The treatments were current farmers' practice (CP), best fertilizer and water management practices, zero tillage (ZT) with no crop residue retention, ZT with partial crop residue retention (ZTPR), future conservation agriculture-based rice-wheat intensive cropping system (FCS-1) and future conservation agriculture-based maize-wheat intensive cropping system (FCS-2). The results indicate that climate change is likely to reduce rice-wheat system productivity under CP by 4% across Bihar. All the crop management options studied increased yield, water productivity and net returns over that of the CP under the current and future climate scenarios. However, the ZTPR treatment gave significantly higher relative yield, lower annual yield variability and a higher benefit-cost-ratio than the other treatments across cropping system components and climate periods. Although all the new cropping system treatments had a positive yield implication under the current climate (compared to CP), they did not contribute to adaptation under the future climate except FCS-2 in wheat. It is concluded that adaptation to future climate must integrate both cropping system innovations, and genetic improvements in stress tolerance.
C1 [Tesfaye, K.] Int Maize & Wheat Improvement Ctr CIMMYT, Addis Ababa, Ethiopia.
   [Khatri-Chhetri, A.; Aggarwal, P. K.; Shirsath, P. B.] Int Maize & Wheat Improvement Ctr CIMMYT, CGIAR Res Program Climate Change Agr & Food Secur, BISA, New Delhi, India.
   [Mequanint, F.] EIAR, Addis Ababa, Ethiopia.
   [Stirling, C. M.; Rahut, D. B.; Erenstein, O.] Int Maize & Wheat Improvement Ctr CIMMYT, Texcoco, Mexico.
   [Jat, M. L.] Int Maize & Wheat Improvement Ctr CIMMYT, New Delhi, India.
   [Stirling, C. M.] Cocoa Life Crop Sci Technol Platform Mondelez UK, Birmingham, W Midlands, England.
C3 CGIAR; International Maize & Wheat Improvement Center (CIMMYT); CGIAR;
   International Maize & Wheat Improvement Center (CIMMYT); Ethiopian
   Institute of Agricultural Research (EIAR); CGIAR; International Maize &
   Wheat Improvement Center (CIMMYT); CGIAR; International Maize & Wheat
   Improvement Center (CIMMYT)
RP Tesfaye, K (corresponding author), Int Maize & Wheat Improvement Ctr CIMMYT, Addis Ababa, Ethiopia.
EM K.tesfayefantaye@cgiar.org
RI Jat, ML/O-2824-2019; Mequanint, Fasil/ABM-1601-2022; Rahut, Dil
   Bahadur/AAD-8370-2022
OI Erenstein, Olaf/0000-0002-7491-5786; Rettie, Fasil
   Mequanint/0000-0001-6049-1794; Tesfaye, Kindie/0000-0002-7201-8053
FU CGIAR Trust Fund
FX This work was implemented as part of 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. The
   views expressed in this publication are those of the authors and cannot
   be taken to reflect the official opinions of the associated and/or
   supporting institutions. The usual disclaimer applies.
CR Aggarwal PK, 2002, CLIMATIC CHANGE, V52, P331, DOI 10.1023/A:1013714506779
   Andales AA, 2000, AGR SYST, V66, P69, DOI 10.1016/S0308-521X(00)00037-8
   [Anonymous], 2012, Annals of Agricultural Research New Series
   [Anonymous], 2304 CSIRO
   [Anonymous], 2014, DECISION SUPPORT SYS
   [Anonymous], 2013, Carbon Clim. Law Rev
   Aryal JP, 2016, AGR ECOSYST ENVIRON, V233, P325, DOI 10.1016/j.agee.2016.09.013
   Aryal JP, 2015, FOOD SECUR, V7, P725, DOI 10.1007/s12571-015-0460-y
   Aryal JP, 2015, EXP AGR, V51, P1, DOI 10.1017/S001447971400012X
   Asseng S, 2015, NAT CLIM CHANGE, V5, P143, DOI [10.1038/nclimate2470, 10.1038/NCLIMATE2470]
   Balkovic J, 2014, GLOBAL PLANET CHANGE, V122, P107, DOI 10.1016/j.gloplacha.2014.08.010
   Balwinder-Singh, 2015, FIELD CROP RES, V173, P81, DOI 10.1016/j.fcr.2014.11.019
   Balwinder-Singh, 2011, FIELD CROP RES, V121, P209, DOI 10.1016/j.fcr.2010.12.005
   Bates D, 2013, J STAT SOFTW, V52, P1, DOI 10.18637/jss.v052.i05
   Batjes NH, 2009, SOIL USE MANAGE, V25, P124, DOI 10.1111/j.1475-2743.2009.00202.x
   Batjes N.H., 2012, ISRIC WISE DERIVED S
   Boote KJ, 2013, PLANT CELL ENVIRON, V36, P1658, DOI 10.1111/pce.12119
   Caviglia OP, 2013, FIELD CROP RES, V149, P300, DOI 10.1016/j.fcr.2013.05.003
   Challinor AJ, 2009, J EXP BOT, V60, P2775, DOI 10.1093/jxb/erp062
   Chattopadhyay N, 2011, CLIMATE CHANGE AND FOOD SECURITY IN SOUTH ASIA, P229, DOI 10.1007/978-90-481-9516-9_15
   Corbeels M, 2016, EUR J AGRON, V76, P41, DOI 10.1016/j.eja.2016.02.001
   Das TK, 2016, J AGR SCI-CAMBRIDGE, V154, P1327, DOI 10.1017/S0021859615001264
   Davis KF, 2017, NAT GEOSCI, V10, P919, DOI 10.1038/s41561-017-0004-5
   DES, 2015, COST CULT PROD REL D
   DoA (Department of Agriculture), 2018, BIH AGR STAT GLANC
   Dubash NK, 2013, WIRES CLIM CHANGE, V4, P191, DOI 10.1002/wcc.210
   Erenstein O, 2008, SOIL TILL RES, V100, P1, DOI 10.1016/j.still.2008.05.001
   Erenstein O, 2011, AGR SYST, V104, P42, DOI 10.1016/j.agsy.2010.09.004
   Erenstein O, 2010, APPL GEOGR, V30, P112, DOI 10.1016/j.apgeog.2009.05.001
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Fofana B, 2005, NUTR CYCL AGROECOSYS, V71, P227, DOI 10.1007/s10705-004-5084-0
   Garnett T, 2013, SCIENCE, V341, P33, DOI 10.1126/science.1234485
   Gathala MK, 2015, FIELD CROP RES, V172, P85, DOI 10.1016/j.fcr.2014.12.003
   Gathala MK, 2013, AGR ECOSYST ENVIRON, V177, P85, DOI 10.1016/j.agee.2013.06.002
   Gathala MK, 2011, AGRON J, V103, P961, DOI 10.2134/agronj2010.0394
   Gijsman AJ, 2002, AGRON J, V94, P462, DOI 10.2134/agronj2002.4620
   GoB, 2015, Bihar State Action Plan on Climate Change
   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
   Guan K, 2017, AGR FOREST METEOROL, V232, P291, DOI 10.1016/j.agrformet.2016.07.021
   Gupta, 2003, ADDR RES CONS ISS RI, P95
   Gupta PK, 2004, CURR SCI INDIA, V87, P1713
   Hasegawa H, 1999, FIELD CROP RES, V63, P255, DOI 10.1016/S0378-4290(99)00043-X
   Hasegawa H, 2000, FIELD CROP RES, V67, P239, DOI 10.1016/S0378-4290(00)00099-X
   Hati KM, 2016, J AGR PHYS, V14, P121
   Hellin J, 2015, INT FOOD AGRIBUS MAN, V18, P151
   Hochman Z, 2017, AGR SYST, V151, P61, DOI 10.1016/j.agsy.2016.11.007
   Hochman Z, 2017, AGR SYST, V150, P54, DOI 10.1016/j.agsy.2016.10.001
   Humphreys E, 2010, ADV AGRON, V109, P155, DOI 10.1016/S0065-2113(10)09005-X
   Hundal SS, 2007, CURR SCI INDIA, V92, P506
   Jagtap SS, 1999, AGR SYST, V60, P77, DOI 10.1016/S0308-521X(99)00019-0
   Jat RK, 2014, FIELD CROP RES, V164, P199, DOI 10.1016/j.fcr.2014.04.015
   Johansen C, 2000, LEGUMES RICE WHEAT C
   Jones JW, 2003, EUR J AGRON, V18, P235, DOI 10.1016/S1161-0301(02)00107-7
   Keil A, 2016, FOOD SECUR, V8, P1011, DOI 10.1007/s12571-016-0611-9
   Keil A, 2015, FOOD SECUR, V7, P983, DOI 10.1007/s12571-015-0492-3
   Khatri-Chhetri A, 2016, CURR SCI INDIA, V110, P1251
   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., 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, P45
   Ladha J.K., 2003, ASA SPECIAL PUBLICAT, V65
   Ladha JK, 2016, GLOBAL CHANGE BIOL, V22, P1054, DOI 10.1111/gcb.13143
   Liu B, 2016, NAT CLIM CHANGE, V6, P1130, DOI 10.1038/NCLIMATE3115
   Liu HL, 2011, NUTR CYCL AGROECOSYS, V89, P313, DOI 10.1007/s10705-010-9396-y
   Lobell DB, 2014, GLOB FOOD SECUR-AGR, V3, P72, DOI 10.1016/j.gfs.2014.05.002
   Luo QY, 2011, CLIMATIC CHANGE, V109, P583, DOI 10.1007/s10584-011-0028-6
   Marta AD, 2018, J AGR SCI-CAMBRIDGE, V156, P575, DOI 10.1017/S002185961800076X
   Matthews RB, 2013, GLOB FOOD SECUR-AGR, V2, P24, DOI 10.1016/j.gfs.2012.11.009
   Mishra A, 2013, SCI TOTAL ENVIRON, V468, pS132, DOI 10.1016/j.scitotenv.2013.05.080
   Mosier AR, 1998, CLIMATIC CHANGE, V40, P39, DOI 10.1023/A:1005338731269
   Ngwira AR, 2014, SOIL TILL RES, V143, P85, DOI 10.1016/j.still.2014.05.003
   Parry ML, 2004, GLOBAL ENVIRON CHANG, V14, P53, DOI 10.1016/j.gloenvcha.2003.10.008
   Piani C, 2010, J HYDROL, V395, P199, DOI 10.1016/j.jhydrol.2010.10.024
   Porter C.H., 2010, OPER RES INT J, V10, P247, DOI [10.1007/s12351-009-0059-1, DOI 10.1007/S12351-009-0059-1, 10.1007/ s12351-009-0059-1]
   Prabhjyot-Kaur, 2010, NATURAL AND ANTHROPOGENIC DISASTERS: VULNERABILITY, PREPAREDNESS AND MITIGATION, P413, DOI 10.1007/978-90-481-2498-5_18
   Reynolds MP, 2016, GLOB FOOD SECUR-AGR, V8, P9, DOI 10.1016/j.gfs.2016.02.002
   Ritchie JT, 2009, SOIL SCI SOC AM J, V73, P792, DOI 10.2136/sssaj2007.0325
   Ruane AC, 2013, AGR FOREST METEOROL, V170, P132, DOI 10.1016/j.agrformet.2011.10.015
   Saharawat Y. S., 2012, Journal of Soil Science and Environmental Management, V3, P9
   Sapkota TB, 2015, J INTEGR ENVIRON SCI, V12, P31, DOI 10.1080/1943815X.2015.1110181
   Saseendran SA, 2007, GEODERMA, V140, P297, DOI 10.1016/j.geoderma.2007.04.013
   Scopel E, 2004, AGRONOMIE, V24, P383, DOI 10.1051/agro:2004029
   Shiferaw B, 2011, FOOD SECUR, V3, P475, DOI 10.1007/s12571-011-0153-0
   Smith P, 2008, PHILOS T R SOC B, V363, P789, DOI 10.1098/rstb.2007.2184
   Soldevilla-Martinez M, 2013, SPAN J AGRIC RES, V11, P820, DOI 10.5424/sjar/2013113-3747
   Tesfaye K, 2018, CLIM RISK MANAG, V19, P106, DOI 10.1016/j.crm.2017.10.001
   Tesfaye K, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9111998
   Tesfaye K, 2017, THEOR APPL CLIMATOL, V130, P959, DOI 10.1007/s00704-016-1931-6
   Thaler S, 2012, J AGR SCI-CAMBRIDGE, V150, P537, DOI 10.1017/S0021859612000093
   Tilman D, 2011, P NATL ACAD SCI USA, V108, P20260, DOI 10.1073/pnas.1116437108
   Timsina J, 2006, AGR SYST, V90, P5, DOI 10.1016/j.agsy.2005.11.007
   Tongwane M, 2016, ENVIRON DEV, V19, P23, DOI 10.1016/j.envdev.2016.06.004
   Verhulst N, 2011, FIELD CROP RES, V124, P347, DOI 10.1016/j.fcr.2011.07.002
   Walker NJ, 2006, PHYS CHEM EARTH, V31, P995, DOI 10.1016/j.pce.2006.08.012
   Yu Q, 2006, AGR SYST, V89, P457, DOI 10.1016/j.agsy.2005.10.009
   Zhao C, 2017, P NATL ACAD SCI USA, V114, P9326, DOI 10.1073/pnas.1701762114
NR 95
TC 10
Z9 10
U1 2
U2 30
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 APR
PY 2019
VL 157
IS 3
BP 189
EP 210
AR PII S0021859619000492
DI 10.1017/S0021859619000492
PG 22
WC Agriculture, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA JA2MJ
UT WOS:000487650500001
DA 2025-01-10
ER

PT J
AU Veraart, JA
   Klostermann, JEM
   van Slobbe, EJJ
   Kabat, P
AF Veraart, J. A.
   Klostermann, J. E. M.
   van Slobbe, E. J. J.
   Kabat, P.
TI Scientific knowledge use and addressing uncertainties about climate
   change and ecosystem functioning in the Rhine-Meuse-Scheldt estuaries
SO ENVIRONMENTAL SCIENCE & POLICY
LA English
DT Article
DE Uncertainties; Freshwater; Climate change; Knowledge; Adaptation;
   Problem framing
ID ADAPTATION; VULNERABILITY; MANAGEMENT; ATTENTION; IGNORANCE; LESSONS;
   LAKE
AB This paper analyses how scientists, policy makers and water users engage with scientific knowledge and uncertainties during a lengthy and complex decision-making process (2000-2014) about water quality, freshwater resources and climate adaptation in the Rhine-Meuse-Scheldt estuaries. The research zooms in on lake Volkerak-Zoom. Interviews confirm that 'negotiated knowledge', shaped by the agricultural sector, NGO's and water managers can lead to strategies to improve water quality problems. One such a strategy, based on negotiated knowledge, is to create an inlet to allow limited tides and inflow of saline waters in Lake Volkerak-Zoom. Meanwhile, during negotiations, monitoring showed an autonomous decline in the annually returning algal blooms, leading to new uncertainties and disrupting the negotiations. At another negotiation arena, water users and policy makers repeatedly disputed scientific assessments about costs and benefits regarding additional freshwater supply for agriculture and the knowledge underlying proposed decisions was still considered uncertain in 2014. Several strategies have been observed to deal with uncertainties in decision making, such as deconstruction of certainties, creation of deadlines for decisions and selection of preferred solutions based upon the No-regret principle'. The risk of a lengthy decision making process can be reduced when the responsible authorities recognize, acknowledge and give an equal role to these behavioural strategies to address uncertainties. Tailor-made strategies are needed to make knowledge use more efficient, for example, joint-factfinding (in case of disputed knowledge and ambiguity), additional research and monitoring (in case of epistemic uncertainty) or commissioning research whereby temporarily a protected environment is created to allow research without political interference (in case of ontic/structural uncertainty).
C1 [Veraart, J. A.; Klostermann, J. E. M.] Wageningen Univ & Res Ctr, Wageningen Environm Res, POB 47, NL-6700 AA Wageningen, Netherlands.
   [van Slobbe, E. J. J.; Kabat, P.] Wageningen Univ & Res Ctr, Water Syst & Global Change Grp, POB 47, NL-6700 AA Wageningen, Netherlands.
   [Kabat, P.] IIASA, Schlosspl 1, A-2361 Laxenburg, Austria.
C3 Wageningen University & Research; Wageningen University & Research;
   International Institute for Applied Systems Analysis (IIASA)
RP Veraart, JA (corresponding author), Wageningen Univ & Res Ctr, Wageningen Environm Res, POB 47, NL-6700 AA Wageningen, Netherlands.
EM jeroen.veraart@wur.nl
RI Kabat, Pavel/AAJ-2245-2020
OI van Slobbe, Erik/0000-0003-0499-2281; Veraart,
   Jeroen/0000-0001-6463-2056
FU Ministry of Agriculture Nature and Food Quality [BO-43-021.03-002];
   foundation "Knowledge for Climate" [HSZD01]
FX We thank the Ministry of Agriculture Nature and Food Quality (Grant ID:
   BO-43-021.03-002) and the foundation "Knowledge for Climate" (Grant ID:
   HSZD01) for commissioning the project. We are grateful towards the
   programme office Southwest Delta for the given opportunity to
   participate within the Delta programme.
CR Adger WN, 2001, DEV CHANGE, V32, P681, DOI 10.1111/1467-7660.00222
   Adler PatriciaA., 1987, Membership Roles in Field Research, V6
   [Anonymous], HOE ZOUT WORDT ZOETE
   [Anonymous], DELT 2015 WERK AAN D
   [Anonymous], ESTUARY CHANGED FRES
   [Anonymous], NAT HAZARDS EARTH SY
   [Anonymous], 1372014 KVK
   [Anonymous], 2511 ALT WAG UR
   [Anonymous], INGENIEUR
   [Anonymous], 1994, HDB QUALITATIVE RES
   [Anonymous], VRAAG AANBOD ZOETWAT
   [Anonymous], ACTIEF BIOL BEHEER N
   [Anonymous], ASSESSMENT SECURITY
   [Anonymous], INT REV LANDSC ARCHI
   [Anonymous], MIRT VERK GREV BESL
   [Anonymous], EFFECT ZOUT VOLKERAK
   [Anonymous], VERB TOEK PERSP GREV
   [Anonymous], DELT TIM CLIM CHANG
   [Anonymous], EUR POLIT SCI
   [Anonymous], UITVOERINGSSTRATEGIE
   [Anonymous], EERST ZOET DAN ZOUT
   [Anonymous], H2O MAGAZINE
   [Anonymous], MIL WAT VOLK ZOOMM O
   [Anonymous], 2200 ALT
   [Anonymous], HET DELTAPLAN
   [Anonymous], STICHT LEV DELT
   [Anonymous], PBL PUBLICATIE
   [Anonymous], DELT 2016 WERK AAN D
   [Anonymous], P475 HYDR
   [Anonymous], TOEKOMSTBESTENDIGHEI
   [Anonymous], WAT VOLK ZOOMM
   [Anonymous], ZOETWATERVOORZIENING
   [Anonymous], THESIS
   [Anonymous], 2016, PUBLIC MANAG REV, DOI DOI 10.1080/14719037.2015.1028974
   [Anonymous], INGENIEUR
   [Anonymous], E P 36 IAHR WORLD C
   [Anonymous], 10117 LEI
   [Anonymous], ATLAS TI 6 USER GUID
   [Anonymous], ZOETWATERVOORZIENING
   [Anonymous], SAM MET WAT LAND DAT
   [Anonymous], CLIMATE CHANGE CHANG
   [Anonymous], JOINT FACT FINDING Z
   [Anonymous], ZOETWATERVOORZIENING
   [Anonymous], ROL ONZEKERHEID KENN
   [Anonymous], ZOUTWATERVREES ZEKER
   [Anonymous], MEER ONTWIKKELING EV
   [Anonymous], KLIMAATVERANDERING V
   [Anonymous], NAT GROT WAT 2050 VE
   [Anonymous], 2 FASE LANGE TERMIJN
   [Anonymous], W0627 IVM I ENV STUD
   [Anonymous], ICID 2011 DELT EUR G
   [Anonymous], CIVIL JUSTICE RES ON
   [Anonymous], INDICATIE INKOMENS V
   [Anonymous], OPEN BRIEF NATL
   [Anonymous], 1205970000 DELT
   [Anonymous], VULNERABILITY ASSESS
   [Anonymous], PLANNING UNCERTAINTY
   [Anonymous], ZOETWATER RAPPORTAGE
   [Anonymous], MORPHOLOGY E SCHELDT
   [Anonymous], NADER ONDERZOEK EXTR
   [Anonymous], 2014, EVOL APPL, DOI DOI 10.1111/eva.12137
   [Anonymous], 2012, Applications of case study research
   [Anonymous], SYNTH ZUIDW DELT ACH
   [Anonymous], 1132 ALT
   [Anonymous], UNCERTAIN SCI UNCERT
   [Anonymous], 2510 ALT
   [Anonymous], DEEL 4 PLAN KERNB RU
   [Anonymous], 2018, Knowledge, power, and participation in environmental policy analysis
   [Anonymous], NADERE VERKENNING AL
   [Anonymous], W1019 I ENV STUD
   BANNINK BA, 1984, NETH J SEA RES, V18, P179, DOI 10.1016/0077-7579(84)90001-2
   Berkhout F, 2014, REG ENVIRON CHANGE, V14, P879, DOI 10.1007/s10113-013-0519-2
   Bertolini L., 2010, The Ashgate research companion to planning theory: Conceptual challenges for spatial planning, P413
   Boeije H.R., 2016, ANAL KWALITATIEF OND
   Breukers CPM, 1997, HYDROBIOLOGIA, V342, P367, DOI 10.1023/A:1017043524394
   Brugnach M, 2011, J ENVIRON MANAGE, V92, P78, DOI 10.1016/j.jenvman.2010.08.029
   Bruijin J.A., 1999, Science and Public Policy, V26, P179, DOI DOI 10.3152/147154399781782428
   Byers W, 2011, BLIND SPOT: SCIENCE AND THE CRISIS OF UNCERTANITY, P1
   Correljé A, 2015, J FLOOD RISK MANAG, V8, P99, DOI 10.1111/jfr3.12087
   de Boer J, 2010, GLOBAL ENVIRON CHANG, V20, P502, DOI 10.1016/j.gloenvcha.2010.03.003
   Dessai S, 2004, CLIMATIC CHANGE, V64, P11, DOI 10.1023/B:CLIM.0000024781.48904.45
   Dewulf A, 2015, J WATER CLIM CHANGE, V6, P759, DOI 10.2166/wcc.2015.117
   Edelenbos J, 2011, ENVIRON SCI POLICY, V14, P675, DOI 10.1016/j.envsci.2011.04.004
   Eelkema M, 2013, COAST ENG J, V55, DOI 10.1142/S0578563413500101
   Flyvbjerg B, 2006, QUAL INQ, V12, P219, DOI 10.1177/1077800405284363
   Ford JD, 2010, WIRES CLIM CHANGE, V1, P374, DOI 10.1002/wcc.48
   Gross M, 2008, SOTSIOL ISSLED+, P13
   Ha-Duong M, 2007, GLOBAL ENVIRON CHANG, V17, P8, DOI 10.1016/j.gloenvcha.2006.12.003
   Hajer M.A., 1996, The politics of environmental discourse
   Hommes S, 2009, WATER RESOUR MANAG, V23, P1641, DOI 10.1007/s11269-008-9345-6
   IPCC, 2018, GLOB WARM 1 5C SUMM
   Jay S, 2007, ENVIRON IMPACT ASSES, V27, P287, DOI 10.1016/j.eiar.2006.12.001
   Jeuken A, 2015, J WATER CLIM CHANGE, V6, P711, DOI 10.2166/wcc.2014.141
   Kabat P, 2005, NATURE, V438, P283, DOI 10.1038/438283a
   Kabat P, 2009, NAT GEOSCI, V2, P450, DOI 10.1038/ngeo572
   Karl HA, 2007, ENVIRONMENT, V49, P20, DOI 10.3200/ENVT.49.1.20-34
   Kelly George A, 1991, PSYCHOL PERSONAL CON
   Klosterman JEM, 2007, J CLEAN PROD, V15, P1573, DOI 10.1016/j.jclepro.2006.07.031
   Koppenjan J., 2004, MAKING POLICY HAPPEN, DOI [10.4324/9781003060697-5, DOI 10.4324/9781003060697-5]
   Kunseler EM, 2017, ENVIRON SCI POLICY, V67, P1, DOI 10.1016/j.envsci.2016.10.001
   Kwakkel Jan H., 2010, International Journal of Technology, Policy and Management, V10, P299, DOI 10.1504/IJTPM.2010.036918
   Meire P, 2005, HYDROBIOLOGIA, V540, P1, DOI 10.1007/s10750-005-0896-8
   MERTON RK, 1987, ANNU REV SOCIOL, V13, P1, DOI 10.1146/annurev.so.13.080187.000245
   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'Toole K, 2013, COAST MANAGE, V41, P561, DOI 10.1080/08920753.2013.848747
   Paavola J, 2006, ECOL ECON, V56, P594, DOI 10.1016/j.ecolecon.2005.03.015
   Restemeyer B, 2017, J ENVIRON PLANN MAN, V60, P920, DOI 10.1080/09640568.2016.1189403
   Runhaar HAC, 2016, ENVIRON SCI POLICY, V55, P467, DOI 10.1016/j.envsci.2015.09.002
   Seijger C, 2013, ENVIRON SCI POLICY, V29, P103, DOI 10.1016/j.envsci.2013.02.007
   Spradley J.P., 2016, The ethnographic interview
   Stocking SH, 1998, SCI COMMUN, V20, P165, DOI 10.1177/1075547098020001019
   Swart R, 2009, CLIMATIC CHANGE, V92, P1, DOI 10.1007/s10584-008-9444-7
   Thomas G, 2011, QUAL INQ, V17, P511, DOI 10.1177/1077800411409884
   van der Heide T, 2007, ECOSYSTEMS, V10, P1311, DOI 10.1007/s10021-007-9099-7
   Van Dijk J.M., 2008, Water and Environment in Decision-Making: Water Assessment, Environmental Impact Assessment, and Strategic Environmental Assesment in Dutch Planning - A Comparison
   van Katwijk MM, 2009, MAR POLLUT BULL, V58, P179, DOI 10.1016/j.marpolbul.2008.09.028
   Veraart JA, 2014, REG ENVIRON CHANGE, V14, P851, DOI 10.1007/s10113-013-0567-7
   Verkerk J, 2015, POLICY POLIT, V43, P579, DOI 10.1332/030557312X655909
   Verweij M, 2006, PUBLIC ADMIN, V84, P817, DOI 10.1111/j.1540-8159.2005.09566.x-i1
   Vink MJ, 2013, ENVIRON SCI POLICY, V30, P90, DOI 10.1016/j.envsci.2012.10.010
   Vinke-de Kruijf J., 2010, Irrigation and Drainage Systems, V24, P249, DOI 10.1007/s10795-010-9097-3
   VRANKEN M, 1990, HYDROBIOLOGIA, V195, P13, DOI 10.1007/BF00026810
   Yin R.K., 2014, Applications of case study research, V2nd
   Zegwaard A, 2014, WATER ALTERN, V7, P464
   Zegwaard A, 2015, CLIMATIC CHANGE, V132, P433, DOI 10.1007/s10584-014-1259-0
NR 126
TC 5
Z9 6
U1 0
U2 9
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
PD DEC
PY 2018
VL 90
BP 148
EP 160
DI 10.1016/j.envsci.2018.09.009
PG 13
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA HA6IL
UT WOS:000450383100016
OA hybrid
DA 2025-01-10
ER

PT J
AU Carter, EK
   Riha, SJ
   Melkonian, J
   Steinschneider, S
AF Carter, Elizabeth K.
   Riha, Susan J.
   Melkonian, Jeff
   Steinschneider, Scott
TI Yield response to climate, management, and genotype: a large-scale
   observational analysis to identify climate-adaptive crop management
   practices in high-input maize systems
SO ENVIRONMENTAL RESEARCH LETTERS
LA English
DT Article
DE acclimation; climate variability; collinearity; crop management;
   rainfed; maize; observational data
ID PLANT-DENSITY; KERNEL SET; DROUGHT; SENSITIVITY; HYBRIDS; TOLERANCE
AB Sustaining food security under climate conditions expected for the 21st century will require that existing crop production systems simultaneously increase both productivity and resiliency to warmer and more variable climate conditions. In this study, we analyzed observational rainfedmaize (Zeamays L.) yield data from major maize production areas of theUSCorn Belt. These data included detailed information on crop management and genetics not typically available in observational studies, allowing us to better understand maize yield response to climate under variable management. Spatial variability in management variables across the study domain is coincident with spatial climate gradients. Regularized global and geographically weighted regression models were used to exploremaize yield response to climate, management, genetics, and their interactions, while accounting for collinearity among them associated with corresponding scales of spatial variability. In contrast with recent analyses suggesting increased susceptibility to drought stress under higher plant populations inmaize production, our analyses indicated that under moisture limitation, higher yields were achieved when high planting rates were coupled with delayed planting date. Maize genetic families that performed best with adequate moisture saw greater yield penalties under moisture limited conditions, while positive response to increased radiation was consistentamong family lines. Themagnitude of yield response to climate, management, and their interactions was also variable across the study domain, suggesting that information on crop management in spatial yield data can be used to better tailor localmanagement practices to changes in yield potential resulting fromagronomic advancements and changing local climate.
C1 [Carter, Elizabeth K.; Steinschneider, Scott] Cornell Univ, Dept Biol & Environm Engn, Ithaca, NY 14853 USA.
   [Riha, Susan J.] Cornell Univ, Dept Earth & Atmospher Sci, Ithaca, NY 14853 USA.
   [Melkonian, Jeff] Cornell Univ, Sch Integrat Plant Sci, Sect Soil & Crop Sci, Ithaca, NY 14853 USA.
C3 Cornell University; Cornell University; Cornell University
RP Carter, EK (corresponding author), Cornell Univ, Dept Biol & Environm Engn, Ithaca, NY 14853 USA.
EM ekc76@cornell.edu
OI Steinschneider, Scott/0000-0002-8882-1908; Carter,
   Elizabeth/0000-0002-4920-0973
FU State University of New York Diversity Fellowship; United States
   Department of Agriculture National Institute for Food and Agriculture
   Hatch Program [NYC-124400]; section of Soil and Crop Sciences in the
   School of Integrative Plant Sciences, Cornell University; United States
   Department of Agriculture National Institute for Food and Agriculture
   Predoctoral Fellowship Program [2017-06913]
FX This research received financial support from the State University of
   New York Diversity Fellowship, the section of Soil and Crop Sciences in
   the School of Integrative Plant Sciences, Cornell University, the United
   States Department of Agriculture National Institute for Food and
   Agriculture Hatch Program/Project number: NYC-124400, and the United
   States Department of Agriculture National Institute for Food and
   Agriculture Predoctoral Fellowship Program/Award number: 2017-06913. The
   authors also wish to thank the National Corn Growers Association
   (http://ncga.com) for providing the maize data, the High Plains Regional
   Climate Center and the University of Missouri for providing the climate
   data, and DuPont Pioneer for information on 'family-level'
   identification of NCGA cultivars, and specifically Dr Jeffery Schussler,
   for technical assistance.
CR Allen R. G., 1998, FAO Irrigation and Drainage Paper
   Assefa Y, 2016, CROP SCI, V56, P2802, DOI 10.2135/cropsci2016.04.0215
   Barker T, 2005, PL BRED RE, V25, P173
   Boyer JS, 2013, GLOB FOOD SECUR-AGR, V2, P139, DOI 10.1016/j.gfs.2013.08.002
   Butler EE, 2013, NAT CLIM CHANGE, V3, P68, DOI [10.1038/NCLIMATE1585, 10.1038/nclimate1585]
   Carter EK, 2018, AGR FOREST METEOROL, V256, P242, DOI 10.1016/j.agrformet.2018.02.029
   Carter EK, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/9/094012
   ChallinorA J, 2015, CHANGE BIOL, V21, P1679
   Ciampitti I., 2015, Corn seeing rate recommendations
   Cooper M, 2014, J EXP BOT, V65, P6191, DOI 10.1093/jxb/eru064
   Duvick DN, 2005, ADV AGRON, V86, P83, DOI 10.1016/S0065-2113(05)86002-X
   Gaffney J, 2015, CROP SCI, V55, P1608, DOI 10.2135/cropsci2014.09.0654
   Gollini I, 2013, J STAT SOFTW, V63, P1548
   Hammer GL, 2009, CROP SCI, V49, P299, DOI 10.2135/cropsci2008.03.0152
   Harris P, 2017, SPAT STAT-NETH, V21, P241, DOI 10.1016/j.spasta.2017.07.006
   Hsiao TC, 2009, AGRON J, V101, P448, DOI 10.2134/agronj2008.0218s
   Larson EJ, 1999, J PROD AGRIC, V12, P400, DOI 10.2134/jpa1999.0400
   Li X, 2011, AGR SYST, V104, P348, DOI 10.1016/j.agsy.2010.12.006
   Lobell DB, 2014, SCIENCE, V344, P516, DOI 10.1126/science.1251423
   Mansfield BD, 2014, CROP SCI, V54, P157, DOI 10.2135/cropsci2013.04.0252
   Meng QF, 2016, SCI REP-UK, V6, DOI 10.1038/srep19605
   Mueller ND, 2017, J CLIMATE, V30, P7505, DOI 10.1175/JCLI-D-17-0096.1
   Ort DR, 2014, SCIENCE, V344, P483, DOI 10.1126/science.1253884
   Pruitt JD, 2016, THESIS
   Roberts MJ, 2013, AM J AGR ECON, V95, P236, DOI 10.1093/ajae/aas047
   Schlenker W, 2009, P NATL ACAD SCI USA, V106, P15594, DOI 10.1073/pnas.0906865106
   SCHUSSLER JR, 1995, CROP SCI, V35, P1074, DOI 10.2135/cropsci1995.0011183X003500040026x
   SCHUSSLER JR, 1991, CROP SCI, V31, P1196, DOI 10.2135/cropsci1991.0011183X003100050024x
   Shapiro CA, 2006, AGRON J, V98, P529, DOI 10.2134/agronj2005.0137
   Tao FL, 2010, EUR J AGRON, V33, P103, DOI 10.1016/j.eja.2010.04.002
   Tokatlidis IS, 2004, FIELD CROP RES, V88, P103, DOI 10.1016/j.fcr.2003.11.013
   USDA-NASS, 2007, CORN OBJ YIELD SURV
   Westgate ME, 2011, CROP ADAPTATION TO CLIMATE CHANGE, P314
   Zou H, 2005, J R STAT SOC B, V67, P301, DOI 10.1111/j.1467-9868.2005.00503.x
NR 34
TC 8
Z9 11
U1 1
U2 23
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 NOV
PY 2018
VL 13
IS 11
AR 114006
DI 10.1088/1748-9326/aae7a8
PG 11
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA GZ2CI
UT WOS:000449184500001
OA gold
DA 2025-01-10
ER

PT J
AU Dunnett, A
   Shirsath, PB
   Aggarwal, PK
   Thornton, P
   Joshi, PK
   Pal, BD
   Khatri-Chhetri, A
   Ghosh, J
AF Dunnett, A.
   Shirsath, P. B.
   Aggarwal, P. K.
   Thornton, P.
   Joshi, P. K.
   Pal, B. D.
   Khatri-Chhetri, A.
   Ghosh, J.
TI Multi-objective land use allocation modelling for prioritizing
   climate-smart agricultural interventions
SO ECOLOGICAL MODELLING
LA English
DT Article
DE Climate-smart agriculture; Optimization; Adaptation; Mitigation;
   Prioritization; Climate change
ID FOOD SECURITY; ADAPTATION; FRAMEWORK; CROP; TOOL
AB Climate-smart interventions in agriculture have varying costs and environmental and economic impacts. Their implementation requires appropriate investment decisions by policy makers that are relevant for current as well as future scenarios of agro-ecology, climate and economic development. Decision support tools are therefore needed to assist different stakeholders to prioritize and hence implement appropriate strategic interventions. These interventions transform agriculture ecosystems to climate-resilient, adaptive and efficient. This paper outlines the mathematical modelling framework of one such, the Climate Smart Agricultural Prioritization (CSAP) toolkit. This toolkit employs a dynamic, spatially-explicit multi-objective optimization model to explore a range of agricultural growth pathways coupled with climate-adaptation strategies to meet agricultural development and environmental goals. The toolkit consists of three major components: (i) land evaluation including assessment of resource availability, land suitability, yield and input-output estimation for all promising crop production practices and technologies for key agro-ecological units; (ii) formulation of scenarios based on policy views and development plans; and (iii) land-use optimization in the form of linear programming models. Climate change and socio-economic drivers condition the land evaluation, technological input-output relations, and specification of optimization objectives that define modelled scenarios. By integrating detailed bottom-up biophysical, climate impact and agricultural-emissions models, CSAP is capable of supporting multi-objective analysis of agricultural production goals in relation to food self-sufficiency, incomes, employment and mitigation targets, thus supporting a wide range of analyses ranging from food security assessment to environmental impact assessment to preparation of climate smart development plans.
C1 [Dunnett, A.] CGIAR Res Program Climate Change Agr & Food Secur, New Delhi 110012, India.
   [Shirsath, P. B.; Aggarwal, P. K.; Khatri-Chhetri, A.] Inamat Maize & Wheat Improvement Ctr CIMMYT, BISA, CGIAR Res Program Climate Change Agr & Food Secur, New Delhi 110012, India.
   [Thornton, P.] Int Livestock Res Inst, CGIAR Res Program Climate Change Agr & Food Secur, POB 30709, Nairobi 00100, Kenya.
   [Joshi, P. K.; Pal, B. D.; Ghosh, J.] Int Food Policy Res Inst IFPRI South Asia, New Delhi 110012, India.
C3 CGIAR; CGIAR; CGIAR; International Livestock Research Institute (ILRI);
   CGIAR; International Food Policy Research Institute (IFPRI)
RP Shirsath, PB (corresponding author), Inamat Maize & Wheat Improvement Ctr CIMMYT, BISA, CGIAR Res Program Climate Change Agr & Food Secur, New Delhi 110012, India.
EM p.bhaskar@cgiar.org
RI Thornton, Philip/AAB-8806-2020
OI Thornton, Philip/0000-0002-1854-0182; Pal, Barun Deb/0000-0002-2584-6155
FU CGIAR Fund Council, Australia (ACIAR); Irish Aid; European Union;
   International Fund for Agricultural Development (IFAD), Netherlands;
   International Fund for Agricultural Development (IFAD), New Zealand;
   International Fund for Agricultural Development (IFAD), Switzerland;
   International Fund for Agricultural Development (IFAD), UK; USAID
FX We acknowledge the CGIAR Fund Council, Australia (ACIAR), Irish Aid,
   European Union, International Fund for Agricultural Development (IFAD),
   Netherlands, New Zealand, Switzerland, UK, USAID and Thailand for
   funding to the CGIAR Research Program on Climate Change, Agriculture and
   Food Security (CCAFS)".
CR Aggarwal P. K., 2001, LAND USE ANAL PLANNI, P167
   Agrell PJ, 2004, EUR J OPER RES, V158, P194, DOI 10.1016/S0377-2217(03)00355-2
   Andrieu N, 2017, AGR SYST, V154, P13, DOI 10.1016/j.agsy.2017.02.008
   [Anonymous], 2006, Population Projection Report for India and States 2001-2026
   [Anonymous], WORLD POP PROSP
   Berardy A, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa5e6d
   Brandt P, 2017, AGR SYST, V151, P234, DOI 10.1016/j.agsy.2015.12.011
   Campbell BM, 2016, GLOB FOOD SECUR-AGR, V11, P34, DOI 10.1016/j.gfs.2016.06.002
   Cross MS, 2012, ENVIRON MANAGE, V50, P341, DOI 10.1007/s00267-012-9893-7
   FAO, 2016, Climate-Smart Agriculture SourcebookModule 1: Why Climate-Smart Agriculture, Fisheries and Forestry
   Feltmate B., 2012, Climate change adaptation: a priorities plan for Canada
   Hillier J, 2011, ENVIRON MODELL SOFTW, V26, P1070, DOI 10.1016/j.envsoft.2011.03.014
   Ilori C., 2015, ADAPTATION PROBLEM D, P29
   Jones PG, 2015, AGR SYST, V139, P93, DOI 10.1016/j.agsy.2015.07.003
   Jones PG, 2013, AGR SYST, V114, P1, DOI 10.1016/j.agsy.2012.08.002
   Khatri-Chhetri A, 2017, AGR SYST, V151, P184, DOI 10.1016/j.agsy.2016.10.005
   Lipper L, 2014, NAT CLIM CHANGE, V4, P1068, DOI [10.1038/NCLIMATE2437, 10.1038/nclimate2437]
   Lobell DB, 2008, SCIENCE, V319, P607, DOI 10.1126/science.1152339
   Long TB, 2016, J CLEAN PROD, V112, P9, DOI 10.1016/j.jclepro.2015.06.044
   MCKAY MD, 1979, TECHNOMETRICS, V21, P239, DOI 10.2307/1268522
   Mehmood Y., 2017, INT J SUST DEV WORLD, V24, P532, DOI [10.1080/13504509.2016.1254689, DOI 10.1080/13504509.2016.1254689]
   Mizina S.V., 1999, MITIG ADAPT STRATEG, V4, P25, DOI [DOI 10.1023/A:1009626526883, 10.1023/A:1009626526883]
   Mwongera C, 2017, AGR SYST, V151, P192, DOI 10.1016/j.agsy.2016.05.009
   Niang-Diop I., 2004, FORMULATING ADAPTION, P190
   Parry M., 2009, ASSESSING COSTS ADAP
   Prabhakar S. V. R. K., 2014, ADAPTATION DECISION
   Praduman Kumar Praduman Kumar, 2011, Agricultural Economics Research Review, V24, P1
   Sanneh ES, 2014, MITIG ADAPT STRAT GL, V19, P1163, DOI 10.1007/s11027-013-9465-z
   Sapkota TB, 2018, MITIG ADAPT STRAT GL, V23, P621, DOI 10.1007/s11027-017-9752-1
   Shirsath PB, 2017, AGR SYST, V151, P174, DOI 10.1016/j.agsy.2016.09.018
   Steenwerth KL., 2014, Agric Food Secur, V3, P1, DOI [10.1186/2048-7010-3-11, DOI 10.1186/2048-7010-3-11]
   Taneja G., 2014, Farmers preferences for climate-smart agriculture: an assessment in the Indo-Gangetic Plain, V1337
   Tanure S, 2013, AGR SYST, V115, P104, DOI 10.1016/j.agsy.2012.08.008
   Thornton P., 2014, 01340 IFPRI, DOI [10.2139/ssm.2423763, DOI 10.2139/SSM.2423763]
   Thornton P. K., 2018, Climate Smart Agriculture: Building Resilience to Climate Change, Natural Resource Management and Policy, DOI [10.1007/978-3-319-61194-5, DOI 10.1007/978-3-319-61194-5, 10.1007/978-3-319-61194-517, DOI 10.1007/978-3-319-61194-517]
   Thornton PK, 2017, AGR SYST, V151, P149, DOI 10.1016/j.agsy.2016.12.007
   Vermeulen SJ, 2012, ENVIRON SCI POLICY, V15, P136, DOI 10.1016/j.envsci.2011.09.003
   Webber H, 2014, AGR SYST, V127, P161, DOI 10.1016/j.agsy.2013.12.006
   Willows R. I., CLIMATE ADAPTATION R
NR 39
TC 43
Z9 48
U1 4
U2 81
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0304-3800
EI 1872-7026
J9 ECOL MODEL
JI Ecol. Model.
PD AUG 10
PY 2018
VL 381
BP 23
EP 35
DI 10.1016/j.ecolmodel.2018.04.008
PG 13
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA GJ1TY
UT WOS:000435052000003
OA hybrid
DA 2025-01-10
ER

PT J
AU Liu, Y
   He, NP
   Wen, XF
   Xu, L
   Sun, XM
   Yu, GR
   Liang, LY
   Schipper, LA
AF Liu, Yuan
   He, Nianpeng
   Wen, Xuefa
   Xu, Li
   Sun, Xiaomin
   Yu, Guirui
   Liang, Liyin
   Schipper, Louis A.
TI The optimum temperature of soil microbial respiration: Patterns and
   controls
SO SOIL BIOLOGY & BIOCHEMISTRY
LA English
DT Article
DE Soil respiration; Optimum temperature; Adaption; Substrate; Microbe;
   Forest
ID ORGANIC-MATTER DECOMPOSITION; CARBON DECOMPOSITION; SENSITIVITY;
   DEPENDENCE; COMMUNITIES; RESPONSES; BACTERIAL; GRADIENT; FORESTS; MODEL
AB The temperature response of soil microbial respiration (R-h) is of significance, with the optimum temperature of R-h being the key parameter for accurately modeling how it responds to temperature change under climate warming scenarios. However, knowledge about T-opt in natural ecosystems remains limited, especially at large scales, which increases the uncertainty of climate projections. Here, we collected 25 soils from tropical to cold temperate forests in the northern hemisphere to quantify regional variation in T-opt and the controls underlying this variation. R-h was measured at high frequency using a novel system under the mode, with temperature gradually increasing from 5 to 50 degrees C. The results showed that T-opt ranged from 38.5 to 46.0 degrees C (mean: 42.4 degrees C). Of note, this study is the first to demonstrate that T-opt is far higher than the assumed value used in models (35 degrees C), varying greatly across different climatic zones and increasing with latitude from tropical to cold-temperate forest soils. To some extent, our results supported the substrate supply hypothesis, and contrast with the climate adaption hypothesis. In addition, climate, nutrient, and soil microorganisms jointly regulate regional variation in T-opt together explaining 53% of variation in T-opt. The higher T-opt in northern regions indicated that these regions have a greater potential to release more CO2 from soil, which might lead to a positive feedback to global warming. In conclusion, process-based models should incorporate the high variability of T-opt across regions to improve predictions of the carbon dynamics of terrestrial ecosystems under climate warming scenarios.
C1 [Liu, Yuan; He, Nianpeng; Wen, Xuefa; Xu, Li; Sun, Xiaomin; Yu, Guirui] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China.
   [Liu, Yuan; He, Nianpeng; Wen, Xuefa; Sun, Xiaomin; Yu, Guirui] Univ Chinese Acad Sci, Coll Resources & Environment, Beijing 100049, Peoples R China.
   [He, Nianpeng] Northeast Normal Univ, Inst Grassland Sci, Changchun 130024, Jilin, Peoples R China.
   [He, Nianpeng] Minist Educ, Key Lab Vegetat Ecol, Changchun 130024, Jilin, Peoples R China.
   [Liang, Liyin; Schipper, Louis A.] Univ Waikato, Sch Sci, Private Bag 3105, Hamilton, New Zealand.
C3 Chinese Academy of Sciences; Institute of Geographic Sciences & Natural
   Resources Research, CAS; Chinese Academy of Sciences; University of
   Chinese Academy of Sciences, CAS; Northeast Normal University - China;
   University of Waikato
RP He, NP (corresponding author), Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.
EM henp@igsnrr.ac.cn
RI Liu, Yuan/P-3172-2019; Xu, Ligang/HHZ-1943-2022; Liang,
   Liyin/G-4503-2015; Schipper, Louis/F-1605-2010; Yu, Guirui/C-1768-2014;
   Liu, Yuan/GSI-7550-2022
OI Liang, Liyin/0000-0001-9831-4793; he, nianpeng/0000-0002-0458-5953;
   Schipper, Louis/0000-0001-9899-1276; Yu, Guirui/0000-0002-1859-8966;
   Liu, Yuan/0000-0001-8350-5773
FU Natural Science Foundation of China [31770655, 41571130043]; National
   Key R&D Program of China [2016YFC0500202]; program of Youth Innovation
   Research Team Project [LENOM2016Q0005]
FX This work was supported by the Natural Science Foundation of China
   (31770655 and 41571130043), the National Key R&D Program of China
   (2016YFC0500202), and the program of Youth Innovation Research Team
   Project (LENOM2016Q0005). The original data are available from the
   corresponding author upon request (henp@igsnrr.ac.cn). We thank the
   comments from the professor of Institute of Botany, CAS (Xingguo Han).
CR Ågren GI, 2007, SOIL BIOL BIOCHEM, V39, P1794, DOI 10.1016/j.soilbio.2007.02.007
   Allison SD, 2010, NAT GEOSCI, V3, P336, DOI 10.1038/NGEO846
   Angilletta MJ, 2009, BIO HABIT, P181
   [Anonymous], Z PFLANZENERNAHRUNG
   [Anonymous], TOTAL CARBON ORGANIC
   Ascar L, 2008, CHEMOSPHERE, V72, P1548, DOI 10.1016/j.chemosphere.2008.04.056
   Bååth E, 2003, SOIL BIOL BIOCHEM, V35, P955, DOI 10.1016/S0038-0717(03)00154-8
   Balser TC, 2005, BIOGEOCHEMISTRY, V73, P395, DOI 10.1007/s10533-004-0372-y
   Balser TC, 2009, GLOBAL CHANGE BIOL, V15, P2935, DOI 10.1111/j.1365-2486.2009.01946.x
   Bárcenas-Moreno G, 2009, GLOBAL CHANGE BIOL, V15, P2950, DOI 10.1111/j.1365-2486.2009.01882.x
   Bradford MA, 2013, FRONT MICROBIOL, V4, DOI 10.3389/fmicb.2013.00333
   Cheng WX, 1996, SOIL BIOL BIOCHEM, V28, P1283, DOI 10.1016/S0038-0717(96)00138-1
   Daniel R. M., 2007, NEW PARAMETERS CONTR
   Daniel RM, 2008, EXTREMOPHILES, V12, P51, DOI 10.1007/s00792-007-0089-7
   Daniel RM, 2010, TRENDS BIOCHEM SCI, V35, P584, DOI 10.1016/j.tibs.2010.05.001
   Davidson EA, 2006, NATURE, V440, P165, DOI 10.1038/nature04514
   Erhagen B, 2015, SOIL BIOL BIOCHEM, V80, P45, DOI 10.1016/j.soilbio.2014.09.021
   Fang C, 2001, SOIL BIOL BIOCHEM, V33, P155, DOI 10.1016/S0038-0717(00)00125-5
   Fenner N, 2005, SOIL BIOL BIOCHEM, V37, P1814, DOI 10.1016/j.soilbio.2005.02.032
   Fissore C, 2013, SOIL BIOL BIOCHEM, V67, P306, DOI 10.1016/j.soilbio.2013.09.007
   Friedlingstein P, 2006, J CLIMATE, V19, P3337, DOI 10.1175/JCLI3800.1
   FROSTEGARD A, 1993, SOIL BIOL BIOCHEM, V25, P723, DOI 10.1016/0038-0717(93)90113-P
   Gershenson A, 2009, GLOBAL CHANGE BIOL, V15, P176, DOI 10.1111/j.1365-2486.2008.01827.x
   Hamdi S, 2013, SOIL BIOL BIOCHEM, V58, P115, DOI 10.1016/j.soilbio.2012.11.012
   He NP, 2018, FUNCT ECOL, V32, P10, DOI 10.1111/1365-2435.12934
   He NP, 2013, ECOL EVOL, V3, P5045, DOI 10.1002/ece3.881
   Hobbs JK, 2013, ACS CHEM BIOL, V8, P2388, DOI 10.1021/cb4005029
   Holland EA, 2000, GLOBAL BIOGEOCHEM CY, V14, P1137, DOI 10.1029/2000GB001264
   Ise T, 2006, BIOGEOCHEMISTRY, V80, P217, DOI 10.1007/s10533-006-9019-5
   JENKINSON DS, 1991, NATURE, V351, P304, DOI 10.1038/351304a0
   Kirschbaum MUF, 2010, GLOBAL CHANGE BIOL, V16, P2117, DOI 10.1111/j.1365-2486.2009.02093.x
   Kirschbaum MUF, 2006, SOIL BIOL BIOCHEM, V38, P2510, DOI 10.1016/j.soilbio.2006.01.030
   KIRSCHBAUM MUF, 1995, SOIL BIOL BIOCHEM, V27, P753, DOI 10.1016/0038-0717(94)00242-S
   Knies JL, 2010, AM NAT, V176, P227, DOI 10.1086/653662
   Ley RE, 2002, SOIL BIOL BIOCHEM, V34, P989, DOI 10.1016/S0038-0717(02)00032-9
   Li J, 2017, SOIL BIOL BIOCHEM, V106, P18, DOI 10.1016/j.soilbio.2016.12.002
   Liu Y, 2017, GLOBAL CHANGE BIOL, V23, P3393, DOI 10.1111/gcb.13613
   LLOYD J, 1994, FUNCT ECOL, V8, P315, DOI 10.2307/2389824
   PARKER LW, 1983, SOIL BIOL BIOCHEM, V15, P303, DOI 10.1016/0038-0717(83)90075-5
   PARTON WJ, 1987, SOIL SCI SOC AM J, V51, P1173, DOI 10.2136/sssaj1987.03615995005100050015x
   Pietikäinen J, 2005, FEMS MICROBIOL ECOL, V52, P49, DOI 10.1016/j.femsec.2004.10.002
   Richardson J, 2012, SOIL BIOL BIOCHEM, V46, P89, DOI 10.1016/j.soilbio.2011.11.008
   Rinnan R, 2009, GLOBAL CHANGE BIOL, V15, P2615, DOI 10.1111/j.1365-2486.2009.01959.x
   Robinson JM, 2017, BIOGEOCHEMISTRY, V133, P101, DOI 10.1007/s10533-017-0314-0
   Rousk J, 2011, FEMS MICROBIOL ECOL, V78, P17, DOI 10.1111/j.1574-6941.2011.01106.x
   Santrucková H, 2003, GLOBAL CHANGE BIOL, V9, P1106, DOI 10.1046/j.1365-2486.2003.00596.x
   Schipper LA, 2014, GLOBAL CHANGE BIOL, V20, P3578, DOI 10.1111/gcb.12596
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Tuomi M, 2008, ECOL MODEL, V211, P182, DOI 10.1016/j.ecolmodel.2007.09.003
   Wang J, 2017, FUNCTIONAL ECOLOGY, P1, DOI [DOI 10.1002/jcla.22185, 10.1109/ICOCN.2017.8121187]
   Wen D, 2016, ECOL INDIC, V61, P960, DOI 10.1016/j.ecolind.2015.10.054
   Zhao N, 2016, GLOBAL ECOL BIOGEOGR, V25, P359, DOI 10.1111/geb.12427
NR 52
TC 72
Z9 81
U1 5
U2 172
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0038-0717
J9 SOIL BIOL BIOCHEM
JI Soil Biol. Biochem.
PD JUN
PY 2018
VL 121
BP 35
EP 42
DI 10.1016/j.soilbio.2018.02.019
PG 8
WC Soil Science
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA GG7ND
UT WOS:000432884100007
DA 2025-01-10
ER

PT J
AU Dojana, N
   Cotor, G
   Codreanu, I
   Raita, S
   Balaceanu, RA
   Budica, C
AF Dojana, N.
   Cotor, G.
   Codreanu, I.
   Raita, S.
   Balaceanu, R. A.
   Budica, C.
TI Investigation into the effect of season on oestrus in gilts over two
   years of climate adaptation
SO SOUTH AFRICAN JOURNAL OF ANIMAL SCIENCE
LA English
DT Article
DE Age of puberty; climate conditions; length of oestrus; weaning to
   oestrus interval
ID REPRODUCTIVE-PERFORMANCE; SOWS; OVULATION; LANDRACE; AGE; STRESS
AB This study examined the changes in age at first oestrus, the weaning-to-oestrus interval (WEI), and duration of oestrus (DE) in a Yorkshire sow population during two years of adaptation from a northern (55 degrees 48'N, 9 degrees 13'W) European region to a southern (44 degrees 03'N, 23 degrees 35'W) one. The adaptation process induced a grouping effect of gilts around the mean age of the onset of puberty. Autumn and spring were characterized by the most enhanced gilt grouping effect at 201 to 210 days of age. The same effect was found for oestrus duration, which declined from a 12- to 96-hour range in the first year to an 18- to 90-hour range in the second year. The mean age of first oestrus was 0.8 days significantly lower in the second year compared with the first; the maximal lowering (1.7 days) occurred in the winter season. The WEI decreased significantly from the first to the second year in all four seasons, by a mean annual value of 0.88 days (15.9%). DE increased by 6.5 hours (significantly for all seasons) from the first year to the next. DE showed an ascending evolution from winter to spring and descending from summer to autumn, during each monitored year. Adaptation influences the oestrus in sows. The age to puberty and WEI tended to decrease, while DE tended to increase, with a simultaneous decrease in the variability of these oestrus parameters.
C1 [Dojana, N.; Cotor, G.; Codreanu, I.; Raita, S.; Balaceanu, R. A.; Budica, C.] Univ Agron Sci & Vet Med Bucharest, Fac Vet Med, 105 Splaiu Independentei Str, Bucharest 050097, Romania.
C3 University of Agronomic Science & Veterinary Medicine - Bucharest
RP Dojana, N (corresponding author), Univ Agron Sci & Vet Med Bucharest, Fac Vet Med, 105 Splaiu Independentei Str, Bucharest 050097, Romania.
EM nicolaedojana@fmvb.ro
RI Stefania, Raita/LWI-7890-2024
CR Anderson L. L., 1993, P343
   Bernabucci U, 2010, ANIMAL, V4, P1167, DOI 10.1017/S175173111000090X
   Chokoe TC, 2009, S AFR J ANIM SCI, V39, P45
   Einarsson S, 2008, ACTA VET SCAND, V50, DOI 10.1186/1751-0147-50-48
   FAILLACE LS, 1994, J REPROD FERTIL, V100, P353, DOI 10.1530/jrf.0.1000353
   Gaustad-Aas AH, 2004, ANIM REPROD SCI, V80, P291, DOI 10.1016/j.anireprosci.2003.08.001
   Gourdine JL, 2006, ASIAN AUSTRAL J ANIM, V19, P1111, DOI 10.5713/ajas.2006.1111
   HURTGEN JP, 1980, J AM VET MED ASSOC, V176, P119
   Hutchens L.K, 1978, ANIMAL SCI RES REPOR
   Kemp B, 1996, J ANIM SCI, V74, P944
   Knox R.V., 2002, EFFECT FREQUENCY BOA, P144
   Knox RV, 2001, J ANIM SCI, V79, P2957
   Koketsu Y, 1997, THERIOGENOLOGY, V47, P1445, DOI 10.1016/S0093-691X(97)00135-0
   Kraeling RR, 2015, J ANIM SCI BIOTECHNO, V6, DOI 10.1186/2049-1891-6-3
   Mabry J.W., 2006, J SWINE HEALTH PROD, V4, P185
   Peltoniemi OAT, 2000, ANIM REPROD SCI, V60, P173, DOI 10.1016/S0378-4320(00)00092-0
   Prunier A, 1997, LIVEST PROD SCI, V52, P123, DOI 10.1016/S0301-6226(97)00137-1
   Quesnel H, 2005, PROD ANIM, V18, P101
   SAS (Statistical Analysis System), 2002, US GUID STAT
   SOMADE B, 1985, Beitraege zur Tropischen Landwirtschaft und Veterinaermedizin, V23, P339
   Suriyasomboon A, 2006, THERIOGENOLOGY, V65, P606, DOI 10.1016/j.theriogenology.2005.06.005
   Tast A., 2002, ENDOCRINOLOGICAL BAS
   Tummaruk P, 2000, ANIM REPROD SCI, V63, P241, DOI 10.1016/S0378-4320(00)00184-6
   Tummaruk P, 2007, ANIM REPROD SCI, V99, P167, DOI 10.1016/j.anireprosci.2006.05.004
   Tummaruk P, 2004, J VET MED SCI, V66, P477, DOI 10.1292/jvms.66.477
NR 25
TC 3
Z9 3
U1 0
U2 3
PU SOUTH AFRICAN JOURNAL OF ANIMAL SCIENCES
PI HATFIELD
PA C/O ESTIE KOSTER, PO BOX 13884, HATFIELD 0028, SOUTH AFRICA
SN 0375-1589
J9 S AFR J ANIM SCI
JI South Afr. J. Anim. Sci.
PY 2017
VL 47
IS 2
BP 187
EP 193
DI 10.4314/sajas.v47i2.10
PG 7
WC Agriculture, Dairy & Animal Science
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA EO7AZ
UT WOS:000396844900010
OA Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Luo, XB
   Peng, YD
AF Luo, Xiaobo
   Peng, Yidong
TI Scale Effects of the Relationships between Urban Heat Islands and Impact
   Factors Based on a Geographically-Weighted Regression Model
SO REMOTE SENSING
LA English
DT Article
DE urban heat island; SAVI; IBI; NDSI; geographically weighted regression;
   scale effect
ID LAND-SURFACE-TEMPERATURE; VARYING RELATIONSHIPS; VEGETATION INDEX;
   NEURAL-NETWORK; URBANIZATION; CLIMATE; NONSTATIONARY; HOUSTON; COVER;
   AREA
AB Urban heat island (UHI) effect, the side effect of rapid urbanization, has become an obstacle to the further healthy development of the city. Understanding its relationships with impact factors is important to provide useful information for climate adaptation urban planning strategies. For this purpose, the geographically-weighted regression (GWR) approach is used to explore the scale effects in a mountainous city, namely the change laws and characteristics of the relationships between land surface temperature and impact factors at different spatial resolutions (30-960 m). The impact factors include the Soil-adjusted Vegetation Index (SAVI), the Index-based Built-up Index (IBI), and the Soil Brightness Index (NDSI), which indicate the coverage of the vegetation, built-up, and bare land, respectively. For reference, the ordinary least squares (OLS) model, a global regression technique, is also employed by using the same dependent variable and explanatory variables as in the GWR model. Results from the experiment exemplified by Chongqing showed that the GWR approach had a better prediction accuracy and a better ability to describe spatial non-stationarity than the OLS approach judged by the analysis of the local coefficient of determination (R-2), Corrected Akaike Information Criterion (AICc), and F-test at small spatial resolution (< 240 m); however, when the spatial scale was increased to 480 m, this advantage has become relatively weak. This indicates that the GWR model becomes increasingly global, revealing the relationships with more generalized geographical patterns, and then spatial non-stationarity in the relationship will tend to be neglected with the increase of spatial resolution.
C1 [Luo, Xiaobo; Peng, Yidong] Chongqing Univ Posts & Telecommun, Inst Comp Sci & Technol, 2 Chongwen Rd, Chongqing 400065, Peoples R China.
   [Luo, Xiaobo] Chongqing Inst Meteorol Sci, Chongqing 401147, Peoples R China.
C3 Chongqing University of Posts & Telecommunications
RP Luo, XB (corresponding author), Chongqing Univ Posts & Telecommun, Inst Comp Sci & Technol, 2 Chongwen Rd, Chongqing 400065, Peoples R China.; Luo, XB (corresponding author), Chongqing Inst Meteorol Sci, Chongqing 401147, Peoples R China.
EM luoxb@cqupt.edu.cn; eadonlife@yahoo.com
FU Program for National Natural Science Foundation of China [61272195];
   Scientific and Technological Research Program of Chongqing Municipal
   Education Commission [KJ120517]
FX This work is supported by the Program for National Natural Science
   Foundation of China (61272195) and the Scientific and Technological
   Research Program of Chongqing Municipal Education Commission (KJ120517).
   The authors wish to thank the Institute of Remote Sensing and Digital
   Earth Chinese Academic of Sciences for the availability of the satellite
   data, and the NASA for the atmospheric correction tool.
CR [Anonymous], 2009, ACTA GEOGRAPHICA SIN
   Callejas IJA, 2011, J APPL REMOTE SENS, V5, DOI 10.1117/1.3666044
   Ashtiani A, 2014, ENERG BUILDINGS, V76, P597, DOI 10.1016/j.enbuild.2014.03.018
   Barsi J.A., 2005, P SPIE INT SOC OPTIC
   Brown S, 2012, ENVIRON MODEL ASSESS, V17, P241, DOI 10.1007/s10666-011-9289-8
   Brunsdon C, 1996, GEOGR ANAL, V28, P281, DOI 10.1111/j.1538-4632.1996.tb00936.x
   Brunsdon C, 2001, INT J CLIMATOL, V21, P455, DOI 10.1002/joc.614
   Buyantuyev A, 2010, LANDSCAPE ECOL, V25, P17, DOI 10.1007/s10980-009-9402-4
   Carlson TN, 2000, GLOBAL PLANET CHANGE, V25, P49, DOI 10.1016/S0921-8181(00)00021-7
   Chander G, 2003, IEEE T GEOSCI REMOTE, V41, P2674, DOI 10.1109/TGRS.2003.818464
   Chen XL, 2006, REMOTE SENS ENVIRON, V104, P133, DOI 10.1016/j.rse.2005.11.016
   Finley AO, 2011, METHODS ECOL EVOL, V2, P143, DOI 10.1111/j.2041-210X.2010.00060.x
   Foody GM, 2003, REMOTE SENS ENVIRON, V88, P283, DOI 10.1016/j.rse.2003.08.004
   Fotheringham A., 2002, Geographically Weighted Regression: The Analysis of Spatially Varying Relationships
   Gao JB, 2011, APPL GEOGR, V31, P292, DOI 10.1016/j.apgeog.2010.06.003
   HUETE A R, 1988, Remote Sensing of Environment, V25, P295, DOI 10.1016/0034-4257(88)90106-X
   Hurvich CM, 1998, J ROY STAT SOC B, V60, P271, DOI 10.1111/1467-9868.00125
   Imhoff ML, 2010, REMOTE SENS ENVIRON, V114, P504, DOI 10.1016/j.rse.2009.10.008
   Javi ST, 2014, ENVIRON MONIT ASSESS, V186, P3123, DOI 10.1007/s10661-013-3605-5
   Jin ML, 2005, J CLIMATE, V18, P1551, DOI 10.1175/JCLI3334.1
   Jusuf SK, 2007, HABITAT INT, V31, P232, DOI 10.1016/j.habitatint.2007.02.006
   Lamptey BL, 2005, GLOBAL PLANET CHANGE, V49, P203, DOI 10.1016/j.gloplacha.2005.10.001
   Lee YY, 2016, ENERG BUILDINGS, V110, P353, DOI 10.1016/j.enbuild.2015.11.013
   LEVIN SA, 1992, ECOLOGY, V73, P1943, DOI 10.2307/1941447
   Li SC, 2010, ENVIRON MODELL SOFTW, V25, P1789, DOI 10.1016/j.envsoft.2010.06.011
   Longley PA, 2004, ANN ASSOC AM GEOGR, V94, P503, DOI 10.1111/j.1467-8306.2004.00411.x
   Mennis JL, 2005, ANN ASSOC AM GEOGR, V95, P249, DOI 10.1111/j.1467-8306.2005.00459.x
   Mirzaei PA, 2015, SUSTAIN CITIES SOC, V19, P403, DOI 10.1016/j.scs.2015.07.008
   Mirzaei PA, 2015, SUSTAIN CITIES SOC, V19, P200, DOI 10.1016/j.scs.2015.04.001
   Ogashawara I, 2012, REMOTE SENS-BASEL, V4, P3596, DOI 10.3390/rs4113596
   Oke T.R., 1997, Applied Climatology: Principles Practices, P273
   PRICE JC, 1984, J GEOPHYS RES-ATMOS, V89, P7231, DOI 10.1029/JD089iD05p07231
   Propastin PA, 2009, REMOTE SENS ENVIRON, V113, P2234, DOI 10.1016/j.rse.2009.06.007
   Qin Z.H., 2004, REMOTE SENS LAND RES, V16, p2832, 36, 41, DOI [DOI 10.3969/J.ISSN.1001-070X.2004.03.007, 10.6046/gtzyyg.2004.03.07, DOI 10.6046/GTZYYG.2004.03.07]
   Shi H, 2006, ECOL MODEL, V190, P171, DOI 10.1016/j.ecolmodel.2005.04.007
   Streutker DR, 2003, REMOTE SENS ENVIRON, V85, P282, DOI 10.1016/S0034-4257(03)00007-5
   Streutker DR, 2002, INT J REMOTE SENS, V23, P2595, DOI 10.1080/01431160110115023
   Su YF, 2012, LANDSCAPE URBAN PLAN, V107, P172, DOI 10.1016/j.landurbplan.2012.05.016
   Tayanc M, 1997, CLIMATIC CHANGE, V35, P501, DOI 10.1023/A:1005357915441
   Tian F, 2012, IEEE J-STARS, V5, P687, DOI 10.1109/JSTARS.2012.2190978
   Tu J, 2008, SCI TOTAL ENVIRON, V407, P358, DOI 10.1016/j.scitotenv.2008.09.031
   Voogt JA., 2002, CAUSES CONSEQUENCES, V3, P660
   Weng QH, 2004, REMOTE SENS ENVIRON, V89, P467, DOI 10.1016/j.rse.2003.11.005
   Weng QH, 2011, IEEE T GEOSCI REMOTE, V49, P4080, DOI 10.1109/TGRS.2011.2128874
   Xie H, 2014, J APPL REMOTE SENS, V8, DOI 10.1117/1.JRS.8.085098
   Xu H, 2008, INT J REMOTE SENS, V29, P4269, DOI 10.1080/01431160802039957
   [徐建春 Xu Jianchun], 2002, [遥感学报, Journal of Remote Sensing], V6, P142
   Yu DL, 2006, ANN REGIONAL SCI, V40, P173, DOI 10.1007/s00168-005-0038-2
   Yuan F, 2007, REMOTE SENS ENVIRON, V106, P375, DOI 10.1016/j.rse.2006.09.003
   Zhang CS, 2009, ENVIRON POLLUT, V157, P3083, DOI 10.1016/j.envpol.2009.05.044
   Zhao ZQ, 2015, THEOR APPL CLIMATOL, V120, P507, DOI 10.1007/s00704-014-1188-x
NR 51
TC 38
Z9 43
U1 3
U2 86
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2072-4292
J9 REMOTE SENS-BASEL
JI Remote Sens.
PD SEP
PY 2016
VL 8
IS 9
AR 760
DI 10.3390/rs8090760
PG 19
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 DY9XB
UT WOS:000385488000070
OA Green Submitted, gold
DA 2025-01-10
ER

PT J
AU Perry, LG
   Reynolds, LV
   Beechie, TJ
   Collins, MJ
   Shafroth, PB
AF Perry, Laura G.
   Reynolds, Lindsay V.
   Beechie, Timothy J.
   Collins, Mathias J.
   Shafroth, Patrick B.
TI Incorporating climate change projections into riparian restoration
   planning and design
SO ECOHYDROLOGY
LA English
DT Article; Proceedings Paper
CT Restoring Functional Riparian Ecosystems - Concepts and Applications
   Symposium at the 5th World Conference on Ecological Restoration
CY 2013
CL Madison, WI
DE climate adaptation; global change; hydrology; ecological restoration;
   riparian ecosystems; river management; streamflow
ID SCALE FLOW EXPERIMENTS; FRESH-WATER; ENVIRONMENTAL FLOWS; STREAM-FLOW;
   PHENOLOGICAL RESPONSE; MANAGEMENT DECISIONS; PASSIVE RESTORATION;
   INVASIVE PLANT; UNITED-STATES; RIVER-BASINS
AB Climate change and associated changes in streamflow may alter riparian habitats substantially in coming decades. Riparian restoration provides opportunities to respond proactively to projected climate change effects, increase riparian ecosystem resilience to climate change, and simultaneously address effects of both climate change and other human disturbances. However, climate change may alter which restoration methods are most effective and which restoration goals can be achieved. Incorporating climate change into riparian restoration planning and design is critical to long-term restoration of desired community composition and ecosystem services. In this review, we discuss and provide examples of how climate change might be incorporated into restoration planning at the key stages of assessing the project context, establishing restoration goals and design criteria, evaluating design alternatives, and monitoring restoration outcomes. Restoration planners have access to numerous tools to predict future climate, streamflow, and riparian ecology at restoration sites. Planners can use those predictions to assess which species or ecosystem services will be most vulnerable under future conditions, and which sites will be most suitable for restoration. To accommodate future climate and streamflow change, planners may need to adjust methods for planting, invasive species control, channel and floodplain reconstruction, and water management. Given the considerable uncertainty in future climate and streamflow projections, riparian ecological responses, and effects on restoration outcomes, planners will need to consider multiple potential future scenarios, implement a variety of restoration methods, design projects with flexibility to adjust to future conditions, and plan to respond adaptively to unexpected change. Copyright (c) 2015 John Wiley & Sons, Ltd.
C1 [Perry, Laura G.; Reynolds, Lindsay V.] Colorado State Univ, Dept Biol, Ft Collins, CO 80523 USA.
   [Perry, Laura G.; Reynolds, Lindsay V.; Shafroth, Patrick B.] US Geol Survey, Ft Collins Sci Ctr, Ft Collins, CO USA.
   [Beechie, Timothy J.] NOAA, Natl Marine Fisheries Serv, NW Fisheries Sci Ctr, Fish Ecol Div, Seattle, WA 98115 USA.
   [Collins, Mathias J.] NOAA, Natl Marine Fisheries Serv, Restorat Ctr, Gloucester, MA USA.
C3 Colorado State University; United States Department of the Interior;
   United States Geological Survey; National Oceanic Atmospheric Admin
   (NOAA) - USA; National Aeronautics & Space Administration (NASA);
   National Oceanic Atmospheric Admin (NOAA) - USA
RP Perry, LG (corresponding author), Colorado State Univ, Dept Biol, Ft Collins, CO 80523 USA.
EM perryl@usgs.gov
RI Perry, Laura/AAG-2719-2020
OI Reynolds, Lindsay V/0000-0001-9973-9312; Perry,
   Laura/0000-0003-2796-868X; Collins, Mathias/0000-0003-4238-2038
CR Acreman M, 2014, FRONT ECOL ENVIRON, V12, P466, DOI 10.1890/130134
   Adam JC, 2008, J CLIMATE, V21, P1807, DOI 10.1175/2007JCLI1535.1
   Addor N, 2014, WATER RESOUR RES, V50, P7541, DOI 10.1002/2014WR015549
   [Anonymous], 2013, STREAM WATERSHED RES
   [Anonymous], ISSUES GEOGRAPHY GEO
   [Anonymous], 20135080 US GEOL SUR
   [Anonymous], REGIONAL CLIMATE T 9
   [Anonymous], ECOSPHERE
   [Anonymous], 2014, CLIMATE CHANGE 2014, V80, P1
   [Anonymous], IACWD B B
   [Anonymous], BIOSCIENCE
   [Anonymous], COARSE SEDIMENT MANA
   [Anonymous], CLIMATE CHANGE 2007
   Araújo MB, 2012, ECOLOGY, V93, P1527, DOI 10.1890/11-1930.1
   Armstrong WH, 2014, HYDROLOG SCI J, V59, P1636, DOI 10.1080/02626667.2013.862339
   Arora VK, 2001, J GEOPHYS RES-ATMOS, V106, P3335, DOI 10.1029/2000JD900620
   Auble GT, 2005, WETLANDS, V25, P143, DOI 10.1672/0277-5212(2005)025[0143:UOISRA]2.0.CO;2
   Barnett TP, 2005, NATURE, V438, P303, DOI 10.1038/nature04141
   Beauchamp VB, 2011, ECOL APPL, V21, P465, DOI 10.1890/09-1638.1
   Beechie T, 2008, N AM J FISH MANAGE, V28, P891, DOI 10.1577/M06-174.1
   Beechie T, 2013, RIVER RES APPL, V29, P939, DOI 10.1002/rra.2590
   Beechie T., 2013, Stream and Watershed Restoration: A Guide to Restoring Riverine Processes and Habitats, P50
   Beechie TJ, 2006, GEOMORPHOLOGY, V78, P124, DOI 10.1016/j.geomorph.2006.01.030
   Beechie TJ, 2010, BIOSCIENCE, V60, P209, DOI 10.1525/bio.2010.60.3.7
   Benito-Garzón M, 2013, GLOBAL ECOL BIOGEOGR, V22, P1141, DOI 10.1111/geb.12075
   Benjankar R, 2011, J ENVIRON MANAGE, V92, P3058, DOI 10.1016/j.jenvman.2011.07.017
   Bernhardt ES, 2005, SCIENCE, V308, P636, DOI 10.1126/science.1109769
   Boyles JG, 2011, INTEGR COMP BIOL, V51, P676, DOI 10.1093/icb/icr053
   Bradley BA, 2010, TRENDS ECOL EVOL, V25, P310, DOI 10.1016/j.tree.2009.12.003
   Bravard JP, 1999, INCISED RIVER CHANNELS: PROCESSES, FORMS, ENGINEERING, AND MANAGEMENT, P303
   Breed MF, 2013, CONSERV GENET, V14, P1, DOI 10.1007/s10592-012-0425-z
   Brierley G, 2010, SCI TOTAL ENVIRON, V408, P2025, DOI 10.1016/j.scitotenv.2010.01.038
   Burke EJ, 2011, J HYDROMETEOROL, V12, P1378, DOI 10.1175/2011JHM1386.1
   Capon SJ, 2013, ECOSYSTEMS, V16, P359, DOI 10.1007/s10021-013-9656-1
   Carey M, 2014, J HYDROL, V518, P60, DOI 10.1016/j.jhydrol.2013.11.006
   Caskey ST, 2015, EARTH SURF PROC LAND, V40, P586, DOI 10.1002/esp.3651
   Catford JA, 2014, NEW PHYTOL, V204, P19, DOI 10.1111/nph.12951
   Catford JA, 2014, DIVERS DISTRIB, V20, P1084, DOI 10.1111/ddi.12225
   Catford JA, 2013, ECOSYSTEMS, V16, P382, DOI 10.1007/s10021-012-9566-7
   Chambers LE, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0075514
   Chen IC, 2011, SCIENCE, V333, P1024, DOI 10.1126/science.1206432
   Clewell A., 2005, GUIDELINES DEV MANAG, V2nd
   Condon LE, 2015, HYDROL EARTH SYST SC, V19, P159, DOI 10.5194/hess-19-159-2015
   Cooper DJ, 2012, RIVER RES APPL, V28, P204, DOI 10.1002/rra.1452
   Corbin JD, 2012, INVAS PLANT SCI MANA, V5, P117, DOI 10.1614/IPSM-D-11-00005.1
   Dai AG, 2011, WIRES CLIM CHANGE, V2, P45, DOI 10.1002/wcc.81
   Déry SJ, 2009, WATER RESOUR RES, V45, DOI 10.1029/2008WR006975
   Dettinger MD, 2004, CLIMATIC CHANGE, V62, P283, DOI 10.1023/B:CLIM.0000013683.13346.4f
   Douglas EM, 2011, J HYDROL ENG, V16, P203, DOI 10.1061/(ASCE)HE.1943-5584.0000303
   Doyle MW, 2007, J HYDRAUL ENG-ASCE, V133, P831, DOI 10.1061/(ASCE)0733-9429(2007)133:7(831)
   Dufour S, 2013, KNOWL MANAG AQUAT EC, DOI 10.1051/kmae/2013068
   Dukes JS, 1999, TRENDS ECOL EVOL, V14, P135, DOI 10.1016/S0169-5347(98)01554-7
   Fitzpatrick FA, 2009, GEOL SOC AM SPEC PAP, V451, P23, DOI 10.1130/2009.2451(02)
   Flanagan NE, 2015, ECOL APPL, V25, P753, DOI 10.1890/14-0767.1
   Flessa Karl W., 2013, Eos, Transactions American Geophysical Union, V94, P485, DOI 10.1002/2013EO500001
   Florsheim JL, 2008, BIOSCIENCE, V58, P519, DOI 10.1641/B580608
   Folke C, 2004, ANNU REV ECOL EVOL S, V35, P557, DOI 10.1146/annurev.ecolsys.35.021103.105711
   Formann E, 2014, LANDSC ECOL ENG, V10, P323, DOI 10.1007/s11355-013-0228-5
   Freudiger D, 2014, HYDROL EARTH SYST SC, V18, P2695, DOI 10.5194/hess-18-2695-2014
   Fuller MM, 2008, ECOL APPL, V18, P711, DOI 10.1890/06-0838.1
   García-Ruiz JM, 2011, EARTH-SCI REV, V105, P121, DOI 10.1016/j.earscirev.2011.01.006
   Githui F, 2009, INT J CLIMATOL, V29, P1823, DOI 10.1002/joc.1828
   del Tánago MG, 2012, ENVIRON MANAGE, V50, P123, DOI 10.1007/s00267-012-9862-1
   Grady KC, 2011, GLOBAL CHANGE BIOL, V17, P3724, DOI 10.1111/j.1365-2486.2011.02524.x
   Graf WL, 2006, GEOMORPHOLOGY, V79, P336, DOI 10.1016/j.geomorph.2006.06.022
   Gregory KJ, 2006, GEOMORPHOLOGY, V79, P172, DOI 10.1016/j.geomorph.2006.06.018
   Grill G, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/1/015001
   Güneralp I, 2014, INT J APPL EARTH OBS, V33, P119, DOI 10.1016/j.jag.2014.05.004
   Hällfors MH, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0102979
   Hammersmark CT, 2008, RIVER RES APPL, V24, P735, DOI 10.1002/rra.1077
   Harris JA, 2006, RESTOR ECOL, V14, P170, DOI 10.1111/j.1526-100X.2006.00136.x
   Harris R, 1997, RESTOR ECOL, V5, P34, DOI 10.1111/j.1526-100X.1997.00034.x
   Hay LE, 2011, EARTH INTERACT, V15, DOI 10.1175/2010EI370.1
   Hayhoe K, 2007, CLIM DYNAM, V28, P381, DOI 10.1007/s00382-006-0187-8
   Hegland SJ, 2009, ECOL LETT, V12, P184, DOI 10.1111/j.1461-0248.2008.01269.x
   Hering D, 2004, RIVER RES APPL, V20, P445, DOI 10.1002/rra.759
   Hodgkins GA, 2006, GEOPHYS RES LETT, V33, DOI 10.1029/2005GL025593
   Hodgkins GA, 2011, WATER RESOUR RES, V47, DOI 10.1029/2010WR009109
   Holmes PM, 2008, S AFR J BOT, V74, P538, DOI 10.1016/j.sajb.2008.01.182
   Horner GJ, 2009, GLOBAL CHANGE BIOL, V15, P2176, DOI 10.1111/j.1365-2486.2009.01915.x
   Hough-Snee N, 2013, ECOL ENG, V58, P371, DOI 10.1016/j.ecoleng.2013.07.042
   Howe HF, 2014, BOT SCI, V92, P459
   Hughes FMR, 1997, PROG PHYS GEOG, V21, P501, DOI 10.1177/030913339702100402
   Hughes L, 2003, AUSTRAL ECOL, V28, P423, DOI 10.1046/j.1442-9993.2003.01300.x
   Ikeda DH, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0107037
   James JJ, 2010, INVAS PLANT SCI MANA, V3, P229, DOI 10.1614/IPSM-D-09-00027.1
   Januschke K, 2014, ECOL INDIC, V38, P243, DOI 10.1016/j.ecolind.2013.10.031
   Johnson WC, 2015, ECOHYDROLOGY, V8, P765, DOI 10.1002/eco.1534
   Johnson WC, 2012, BIOSCIENCE, V62, P123, DOI 10.1525/bio.2012.62.2.6
   Kauffman JB, 1997, FISHERIES, V22, P12, DOI 10.1577/1548-8446(1997)022<0012:AEPORA>2.0.CO;2
   Kim J, 2005, CLIMATIC CHANGE, V68, P153, DOI 10.1007/s10584-005-4787-9
   Kirby JM, 2014, J HYDROL, V518, P120, DOI 10.1016/j.jhydrol.2014.01.024
   Koirala S, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/6/064017
   Kominoski JS, 2013, FRONT ECOL ENVIRON, V11, P423, DOI 10.1890/120056
   Kondolf GM, 1998, AQUAT CONSERV, V8, P39, DOI 10.1002/(SICI)1099-0755(199801/02)8:1<39::AID-AQC250>3.0.CO;2-9
   Konrad CP, 2008, RIVER RES APPL, V24, P355, DOI 10.1002/rra.1070
   Konrad CP, 2011, BIOSCIENCE, V61, P948, DOI 10.1525/bio.2011.61.12.5
   Kristensena EA, 2014, ECOL ENG, V66, P141, DOI 10.1016/j.ecoleng.2013.10.001
   Kundzewicz ZW, 2014, HYDROLOG SCI J, V59, P1, DOI 10.1080/02626667.2013.857411
   Kunkel KE, 2013, B AM METEOROL SOC, V94, P499, DOI 10.1175/BAMS-D-11-00262.1
   Laghari AN, 2012, HYDROLOG SCI J, V57, P103, DOI 10.1080/02626667.2011.637040
   Laizé CLR, 2014, RIVER RES APPL, V30, P299, DOI 10.1002/rra.2645
   Lawler JJ, 2009, ANN NY ACAD SCI, V1162, P79, DOI 10.1111/j.1749-6632.2009.04147.x
   Lester RE, 2008, ENVIRON MANAGE, V42, P310, DOI 10.1007/s00267-008-9151-1
   Liu DD, 2015, HYDROL PROCESS, V29, P2112, DOI 10.1002/hyp.10360
   Liu GL, 2014, ENVIRON EARTH SCI, V71, P4579, DOI 10.1007/s12665-013-2850-9
   Magdaleno F, 2011, RIVER RES APPL, V27, P374, DOI 10.1002/rra.1368
   Mahoney JM, 1998, WETLANDS, V18, P634, DOI 10.1007/BF03161678
   Mantua N, 2010, CLIMATIC CHANGE, V102, P187, DOI 10.1007/s10584-010-9845-2
   Marchetti MP, 2001, ECOL APPL, V11, P530, DOI 10.1890/1051-0761(2001)011[0530:EOFROF]2.0.CO;2
   Matalas NC, 2012, J WATER RES PLAN MAN, V138, P311, DOI 10.1061/(ASCE)WR.1943-5452.0000215
   McKay SF, 2006, RIVER RES APPL, V22, P1023, DOI 10.1002/rra.958
   Meli P, 2013, RESTOR ECOL, V21, P163, DOI 10.1111/j.1526-100X.2012.00934.x
   Menzel A, 2006, GLOBAL CHANGE BIOL, V12, P1969, DOI 10.1111/j.1365-2486.2006.01193.x
   Merritt DM, 2012, ECOL APPL, V22, P1973, DOI 10.1890/12-0303.1
   Merritt DM, 2010, FRESHWATER BIOL, V55, P206, DOI 10.1111/j.1365-2427.2009.02206.x
   Merritt DM, 2000, REGUL RIVER, V16, P543, DOI 10.1002/1099-1646(200011/12)16:6<543::AID-RRR590>3.0.CO;2-N
   Miller DE, 1999, WILDLAND HYDROLOGY, PROCEEDINGS, P293
   Milly PCD, 2008, SCIENCE, V319, P573, DOI 10.1126/science.1151915
   Montgomery D.R., 1998, River Ecology and Management, P13, DOI DOI 10.1007/978-1-4612-1652-0_2
   Moore CE, 2014, J AM WATER RESOUR AS, V50, P1033, DOI 10.1111/jawr.12155
   Mote PW, 2003, CLIMATIC CHANGE, V61, P45, DOI 10.1023/A:1026302914358
   Murray JV, 2012, GLOBAL CHANGE BIOL, V18, P1738, DOI 10.1111/j.1365-2486.2011.02621.x
   Naiman R.J., 2005, RIPARIA ECOLOGY CONS
   Nilsson C, 2013, ECOSYSTEMS, V16, P401, DOI 10.1007/s10021-012-9622-3
   Norman L, 2014, ECOL ENG, V70, P241, DOI 10.1016/j.ecoleng.2014.05.012
   O'Brien NL, 2014, J HYDROL, V519, P2040, DOI 10.1016/j.jhydrol.2014.09.041
   O'Connor TG, 2010, AUSTRAL ECOL, V35, P778, DOI 10.1111/j.1442-9993.2009.02084.x
   Olden JD, 2014, FRONT ECOL ENVIRON, V12, P176, DOI 10.1890/130076
   Ollero A, 2010, GEOMORPHOLOGY, V117, P247, DOI 10.1016/j.geomorph.2009.01.015
   Olsen JR, 1999, J AM WATER RESOUR AS, V35, P1509, DOI 10.1111/j.1752-1688.1999.tb04234.x
   Opperman JJ, 2010, J AM WATER RESOUR AS, V46, P211, DOI 10.1111/j.1752-1688.2010.00426.x
   Palmer MA, 2005, J APPL ECOL, V42, P208, DOI 10.1111/j.1365-2664.2005.01004.x
   Palmer M, 2007, RESTOR ECOL, V15, P472, DOI 10.1111/j.1526-100X.2007.00243.x
   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
   Parmesan C, 2007, GLOBAL CHANGE BIOL, V13, P1860, DOI 10.1111/j.1365-2486.2007.01404.x
   Parmesan C, 2006, ANNU REV ECOL EVOL S, V37, P637, DOI 10.1146/annurev.ecolsys.37.091305.110100
   Parsons M, 2006, RIVER RES APPL, V22, P187, DOI 10.1002/rra.905
   Pastorok RA, 1997, ECOL ENG, V9, P89, DOI 10.1016/S0925-8574(97)00036-0
   Patten DT, 2001, ECOL APPL, V11, P635, DOI 10.1890/1051-0761(2001)011[0635:AMFOTC]2.0.CO;2
   Pechony O, 2010, P NATL ACAD SCI USA, V107, P19167, DOI 10.1073/pnas.1003669107
   Perry LG, 2012, GLOBAL CHANGE BIOL, V18, P821, DOI 10.1111/j.1365-2486.2011.02588.x
   Poff NL, 2007, P NATL ACAD SCI USA, V104, P5732, DOI 10.1073/pnas.0609812104
   Poff NL, 2010, FRESHWATER BIOL, V55, P147, DOI 10.1111/j.1365-2427.2009.02204.x
   Polvi LE, 2013, BIOSCIENCE, V63, P439, DOI 10.1525/bio.2013.63.6.6
   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]
   Prudhomme C, 2010, J HYDROL, V390, P198, DOI 10.1016/j.jhydrol.2010.06.043
   Regonda SK, 2005, J CLIMATE, V18, P372, DOI 10.1175/JCLI-3272.1
   Rice KJ, 2003, FRONT ECOL ENVIRON, V1, P469, DOI 10.1890/1540-9295(2003)001[0469:MMRITF]2.0.CO;2
   Richardson DM, 2007, DIVERS DISTRIB, V13, P126, DOI 10.1111/j.1366-9516.2006.00314.x
   Rivaes RP, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0110200
   Rood SB, 2005, FRONT ECOL ENVIRON, V3, P193, DOI 10.1890/1540-9295(2005)003[0193:MRFTRF]2.0.CO;2
   Rood SB, 2003, TREE PHYSIOL, V23, P1113, DOI 10.1093/treephys/23.16.1113
   Rosgen D.L., 1996, Applied River Morphology
   Rosner A, 2014, WATER RESOUR RES, V50, P1928, DOI 10.1002/2013WR014561
   Rout TM, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0075814
   Ruwanza S, 2013, S AFR J BOT, V88, P132, DOI 10.1016/j.sajb.2013.06.022
   Sabo JL, 2005, ECOLOGY, V86, P56, DOI 10.1890/04-0668
   Sabo JL, 2010, P NATL ACAD SCI USA, V107, P21263, DOI 10.1073/pnas.1009734108
   Salas JD, 2014, J HYDROL ENG, V19, P554, DOI 10.1061/(ASCE)HE.1943-5584.0000820
   Saxe H, 2001, NEW PHYTOL, V149, P369, DOI 10.1046/j.1469-8137.2001.00057.x
   Schilthuizen M, 2014, EVOL APPL, V7, P56, DOI 10.1111/eva.12116
   Schnitzler A, 2007, BIOL CONSERV, V138, P146, DOI 10.1016/j.biocon.2007.04.010
   Schumm S., 1973, FLUVIAL GEOMORPHOLOG, V6, P69
   Schwartz MW, 2012, BIOL CONSERV, V155, P149, DOI 10.1016/j.biocon.2012.06.011
   Seastedt TR, 2008, FRONT ECOL ENVIRON, V6, P547, DOI 10.1890/070046
   Seavy N. E., 2009, Ecological Restoration, V27, P330, DOI 10.3368/er.27.3.330
   Sgrò CM, 2011, EVOL APPL, V4, P326, DOI 10.1111/j.1752-4571.2010.00157.x
   Shafroth PB, 2010, FRESHWATER BIOL, V55, P68, DOI 10.1111/j.1365-2427.2009.02271.x
   Shafroth PB, 2005, ENVIRON MANAGE, V35, P231, DOI 10.1007/s00267-004-0099-5
   Shaw JR, 2008, J HYDROL, V350, P68, DOI 10.1016/j.jhydrol.2007.11.030
   Shields FD, 2003, J HYDRAUL ENG-ASCE, V129, P575, DOI 10.1061/(ASCE)0733-9429(2003)129:8(575)
   Skidmore Peter., 2013, Stream and Watershed Restoration: a guide to restoring riverine processes and habitats, V1st, P215
   Spencer LJ, 2014, RESTOR ECOL, V22, P397, DOI 10.1111/rec.12074
   Stahl K, 2010, HYDROL EARTH SYST SC, V14, P2367, DOI 10.5194/hess-14-2367-2010
   Stainforth DA, 2007, PHILOS T R SOC A, V365, P2163, DOI 10.1098/rsta.2007.2073
   Start AN, 2002, AUST J BOT, V50, P465, DOI 10.1071/BT01060
   Steinfeld CMM, 2013, RIVER RES APPL, V29, P206, DOI 10.1002/rra.1583
   Stewart IT, 2005, J CLIMATE, V18, P1136, DOI 10.1175/JCLI3321.1
   Stohlgren TJ, 1999, ECOL MONOGR, V69, P25, DOI 10.1890/0012-9615(1999)069[0025:EPSIHS]2.0.CO;2
   Stromberg JC, 2007, DIVERS DISTRIB, V13, P70, DOI 10.1111/j.1472-4642.2006.00295.x
   Stromberg JC, 2010, RIVER RES APPL, V26, P712, DOI 10.1002/rra.1272
   Tank AMGK, 2003, J CLIMATE, V16, P3665, DOI 10.1175/1520-0442(2003)016<3665:TIIODT>2.0.CO;2
   Taylor JP, 2004, WEED TECHNOL, V18, P1278, DOI 10.1614/0890-037X(2004)018[1278:RSASTS]2.0.CO;2
   Thackeray SJ, 2010, GLOBAL CHANGE BIOL, V16, P3304, DOI 10.1111/j.1365-2486.2010.02165.x
   Trabucchi M, 2014, ENVIRON MANAGE, V53, P1132, DOI 10.1007/s00267-014-0264-4
   Van Driesche RG, 2010, BIOL CONTROL, V54, pS2, DOI 10.1016/j.biocontrol.2010.03.003
   Veloz SD, 2013, ECOSPHERE, V4, DOI 10.1890/ES12-00341.1
   Verhoeven JTA, 2014, ECOL ENG, V66, P6, DOI 10.1016/j.ecoleng.2013.03.006
   Visser ME, 2005, P ROY SOC B-BIOL SCI, V272, P2561, DOI 10.1098/rspb.2005.3356
   Wahid A, 2007, ENVIRON EXP BOT, V61, P199, DOI 10.1016/j.envexpbot.2007.05.011
   WARD JV, 1995, REGUL RIVER, V11, P105, DOI 10.1002/rrr.3450110109
   Ward MN, 2013, CLIMATIC CHANGE, V118, P307, DOI 10.1007/s10584-012-0616-0
   Warfe DM, 2014, FRESHWATER BIOL, V59, P2064, DOI 10.1111/fwb.12407
   Weisberg PJ, 2013, RESTOR ECOL, V21, P12, DOI 10.1111/j.1526-100X.2012.00907.x
   West JM, 2009, ENVIRON MANAGE, V44, P1001, DOI 10.1007/s00267-009-9345-1
   Westra S, 2014, WATER RESOUR RES, V50, P5090, DOI 10.1002/2013WR014719
   Wheeler S, 2014, J HYDROL, V518, P28, DOI 10.1016/j.jhydrol.2013.09.019
   Wilby RL, 2010, HYDROLOG SCI J, V55, P1090, DOI 10.1080/02626667.2010.513212
   Wilby RL, 2010, SCI TOTAL ENVIRON, V408, P4150, DOI 10.1016/j.scitotenv.2010.05.014
   Williams GP, 1984, 1286 US GEOL SURV
   Wohl E, 2005, WATER RESOUR RES, V41, DOI 10.1029/2005WR003985
NR 203
TC 44
Z9 55
U1 22
U2 221
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1936-0584
EI 1936-0592
J9 ECOHYDROLOGY
JI Ecohydrology
PD JUL
PY 2015
VL 8
IS 5
SI SI
BP 863
EP 879
DI 10.1002/eco.1645
PG 17
WC Ecology; Environmental Sciences; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED); Conference Proceedings Citation Index - Science (CPCI-S)
SC Environmental Sciences & Ecology; Water Resources
GA CN6IR
UT WOS:000358538800011
DA 2025-01-10
ER

PT J
AU Bari, MN
   Jahan, M
   Islam, KS
AF Bari, M. N.
   Jahan, M.
   Islam, K. S.
TI Effects of Temperature on the Life Table Parameters of <i>Trichogramma
   zahiri</i> (Hymenoptera: Trichogrammatidae), an Egg Parasitoid of
   <i>Dicladispa armigera</i> (Chrysomelidae: Coleoptera)
SO ENVIRONMENTAL ENTOMOLOGY
LA English
DT Article
DE parasitoid; Trichogramma zahiri; temperature; effect; life table
ID EPHESTIA-KUEHNIELLA; COMPARATIVE BIOLOGY; PRETIOSUM; CONSTANT;
   GELECHIIDAE; LEPIDOPTERA; EVANESCENS; JACKKNIFE; CACOECIAE; ACACIOI
AB The influence of different temperatures on biological parameters of native strains of Trichogramma zahiri Polaszek (Hymenoptera: Trichogrammatidae), an egg parasitoid of rice hispa, Dicladispa armigera (Olivier) (Chrysomelidae: Coleoptera), was evaluated in the laboratory on its host. The key biological parameters of the parasitoid T. zahiri in relation to temperature were investigated to find out its candidature as a potential biological control agent of rice hispa. The highest number of eggs parasitized by T. zahiri was 15.7 eggs per female at 26 degrees C, which differed significantly from those at 18, 22, 30, and 34 degrees C (P < 0.05). Development duration and longevity of T. zahiri decreased as temperature increased. Fecundity differed significantly at all constant temperatures. Emergence rates decreased at both high (34 degrees C) and low ( < 26 degrees C) temperatures. Female-biased sex ratio ranged from 54 to 70% at all constant temperatures. The lower temperature threshold for T. zahiri was 6.2 degrees C for males and 6.95 degrees C for females. The upper threshold temperatures were 35.82 and 35.87 degrees C for males and females, respectively. Net reproductive rate (R-0) was highest at 26 degrees C compared with other temperatures. Mean cohort generation time (t(G)) and population doubling time (t(D)) decreased as temperature increased from 18 to 30 degrees C. The daily intrinsic rate of increase (r(m)) and finite rate of increase (lambda) were positively correlated with temperatures ranging from 18 to 30 degrees C and then decreased at 34 degrees C. The relevance of our results is discussed in the context of climatic adaptation and biological control.
C1 [Bari, M. N.] BRRI, Div Entomol, Gazipur 1701, Bangladesh.
   [Jahan, M.; Islam, K. S.] BAU, Dept Entomol, Mymensingh 2202, Bangladesh.
C3 Bangladesh Rice Research Institute (BRRI); Bangladesh Agricultural
   University (BAU)
RP Bari, MN (corresponding author), BRRI, Div Entomol, Gazipur 1701, Bangladesh.
EM mn_bari@yahoo.com
FU National Agricultural Technology Project (NATP), Phase 1, Bangladesh
   Agricultural Research Council (BARC), Farmgate, Dhaka, Bangladesh
FX The present research was supported by National Agricultural Technology
   Project (NATP), Phase 1, Bangladesh Agricultural Research Council
   (BARC), Farmgate, Dhaka, Bangladesh. We are grateful to Mr. Md. Panna
   Ali, Doctoral Course Student, Laboratory of Biotechnology, Department of
   Bioscience, Graduate School of Science and Technology, Shizuoka
   University, Shizuoka, Japan, for his kind help with data analysis,
   figures preparation, and revising the manuscript. Thanks are also given
   to Nur Ahmed, Principal Scientific Officer, Entomology Division, BRRI,
   Gazipur, Bangladesh, and PhD fellow, Department of Agro Systems, SLU,
   Alnarp, Sweden, for different data analysis and valuable suggestions for
   preparing the manuscript.
CR [Anonymous], 1998, MEMOIRS ENTOMOLOGICA
   [Anonymous], 1988, BOL SAN VEG PLAGAS
   Baitha Arun, 1998, Indian Journal of Entomology, V60, P250
   Bari M. N, 2013, THESIS BANGLADESH AG
   Bari MN, 2005, BANGLADESH J ENTOMO, V15, P45
   BIRCH LC, 1948, J ANIM ECOL, V17, P15, DOI 10.2307/1605
   Botto EN, 2004, BIOCONTROL SCI TECHN, V14, P449, DOI 10.1080/09583150410001683510
   Choudhury D.A.M, 2002, THESIS U LONDON
   CONSOLI FL, 1995, J APPL ENTOMOL, V119, P415, DOI 10.1111/j.1439-0418.1995.tb01310.x
   Dadpour Moghanlou H, 2002, THESIS TARBIAT MODAR
   Gotoh T, 2003, APPL ENTOMOL ZOOL, V38, P7, DOI 10.1303/aez.2003.7
   Gotoh T, 2010, EXP APPL ACAROL, V52, P239, DOI 10.1007/s10493-010-9362-z
   Haghani M. L., 2004, J AGR SCI NATURAL RE, V10, P117
   Haile AT, 2002, J APPL ENTOMOL, V126, P287, DOI 10.1046/j.1439-0418.2002.00631.x
   Hansen LS, 2000, ENTOMOL EXP APPL, V96, P185, DOI 10.1023/A:1004069716921
   HARRISON WW, 1985, ENVIRON ENTOMOL, V14, P118, DOI 10.1093/ee/14.2.118
   Ikemoto T, 2000, ENVIRON ENTOMOL, V29, P671, DOI 10.1603/0046-225X-29.4.671
   Ikemoto T, 2005, ENVIRON ENTOMOL, V34, P1377, DOI 10.1603/0046-225X-34.6.1377
   Ikemoto T, 2003, APPL ENTOMOL ZOOL, V38, P487, DOI 10.1303/aez.2003.487
   Ikemoto T, 2008, J MED ENTOMOL, V45, P963, DOI 10.1603/0022-2585(2008)45[963:TMDNMH]2.0.CO;2
   Ikemoto T, 2013, INSECT SCI, V20, P420, DOI 10.1111/j.1744-7917.2012.01525.x
   Islam S, 1997, THESIS SCH ENV RESOU
   Islam Z., 2009, Outlooks on Pest Management, V20, P37, DOI 10.1564/20feb12
   Islam Z., 2003, BANGLADESH J ENTOMOL, V13, P1
   Kalyebi A, 2005, BIOL CONTROL, V32, P164, DOI 10.1016/j.biocontrol.2004.09.006
   Khan A. R., 1989, P 1 SEM HYDR POT DEE, P3
   Maia AHN, 2000, J ECON ENTOMOL, V93, P511, DOI 10.1603/0022-0493-93.2.511
   McDougall SJ, 1997, ENTOMOL EXP APPL, V83, P195, DOI 10.1023/A:1002903720301
   MEYER JS, 1986, ECOLOGY, V67, P1156, DOI 10.2307/1938671
   NELDER JA, 1965, COMPUT J, V7, P308, DOI 10.1093/comjnl/7.4.308
   Omer AD, 1996, BIOL CONTROL, V6, P29, DOI 10.1006/bcon.1996.0004
   Özder N, 2010, BIOCONTROL SCI TECHN, V20, P245, DOI 10.1080/09583150903497880
   Park K. Y., 2000, J ASIA-PAC ENTOMOL, V3, P65
   PARRA J R P, 1987, Memorias do Instituto Oswaldo Cruz, V82, P153
   Pavlik J., 1990, C INRA, V56, P85
   Polaszek A, 2002, B ENTOMOL RES, V92, P529, DOI 10.1079/BER2002197
   Pratissoli D, 2000, PESQUI AGROPECU BRAS, V35, P1281, DOI 10.1590/S0100-204X2000000700001
   Pratissoli D, 2004, ANN ENTOMOL SOC AM, V97, P729, DOI 10.1603/0013-8746(2004)097[0729:FLTOTP]2.0.CO;2
   Pratissoli D, 2004, PESQUI AGROPECU BRAS, V39, P193, DOI 10.1590/S0100-204X2004000200014
   Pratissoli D, 2000, J APPL ENTOMOL, V124, P339, DOI 10.1046/j.1439-0418.2000.00477.x
   Reznik S. Ya, 1995, Entomologicheskoe Obozrenie, V74, P507
   Sabelis M.W., 1985, P265
   Samara R, 2011, PHYTOPARASITICA, V39, P109, DOI 10.1007/s12600-010-0142-4
   Samara RY, 2008, BIOCONTROL SCI TECHN, V18, P75, DOI 10.1080/09583150701749789
   Schöller M, 2001, ENTOMOL EXP APPL, V98, P35, DOI 10.1023/A:1018700408113
   SCHOOLFIELD RM, 1981, J THEOR BIOL, V88, P719, DOI 10.1016/0022-5193(81)90246-0
   SHARPE PJH, 1977, J THEOR BIOL, V64, P649, DOI 10.1016/0022-5193(77)90265-X
   Shi PJ, 2011, ENVIRON ENTOMOL, V40, P462, DOI 10.1603/EN10265
   Ullah MS, 2011, EXP APPL ACAROL, V54, P1, DOI 10.1007/s10493-010-9420-6
   VANHUIS A, 1994, ENTOMOL EXP APPL, V70, P41, DOI 10.1007/BF02380630
   vanLenteren JC, 1997, BIOL CONTROL, V10, P143, DOI 10.1006/bcon.1997.0548
   Zhang WQ, 2001, Z PFLANZENK PFLANZEN, V108, P413
NR 52
TC 18
Z9 22
U1 0
U2 45
PU OXFORD UNIV PRESS INC
PI CARY
PA JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA
SN 0046-225X
EI 1938-2936
J9 ENVIRON ENTOMOL
JI Environ. Entomol.
PD APR
PY 2015
VL 44
IS 2
BP 368
EP 378
DI 10.1093/ee/nvu028
PG 11
WC Entomology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Entomology
GA CF6DK
UT WOS:000352646700020
PM 26313191
DA 2025-01-10
ER

PT J
AU Frieler, K
   Meinshausen, M
   Mengel, M
   Braun, N
   Hare, W
AF Frieler, Katja
   Meinshausen, Malte
   Mengel, Matthias
   Braun, Nadine
   Hare, William
TI A Scaling Approach to Probabilistic Assessment of Regional Climate
   Change
SO JOURNAL OF CLIMATE
LA English
DT Article
ID GREENHOUSE-GAS; FOREST DIEBACK; PROJECTIONS; ATMOSPHERE; MODEL;
   PRECIPITATION; TEMPERATURE; OCEAN; 21ST-CENTURY; UNCERTAINTY
AB A new approach to probabilistic projections of regional climate change is introduced. It builds on the already established quasi-linear relation between global-mean temperature and regional climate change found in atmosphere-ocean general circulation models (AOGCMs). The new approach simultaneously 1) takes correlations between temperature- and precipitation-related uncertainty distributions into account, 2) enables the inclusion of predictors other than global-mean temperature, and 3) checks for the interscenario and interrun variability of the scaling relationships. This study tests the effectiveness of SOx and black carbon emissions and greenhouse gas forcings as additional predictors of precipitation changes. The future precipitation response is found to deviate substantially from the linear relationship with global-mean temperature change in some regions; thereby, the two main limitations of a simple linear scaling approach, namely having to rely on exogenous aerosol experiments (or ignoring their regional effect), and ignoring changes in scaling coefficients when approaching equilibrium conditions, are addressed. The additional predictors can markedly improve the emulation of AOGCM simulations. In some regions, variations in hydrological sensitivity (the percentage change of precipitation per degree of warming) across different scenarios can be reduced by more than 50%. Coupled to probabilistic projections of global-mean temperatures and greenhouse gas forcings, bidimensional distributions of regional temperature and precipitation changes accounting for multiple uncertainties are derived. Based on 20 Fourth Assessment Report AOGCMs (AR4 AOGCMs), probabilistic projections are provided for two representative concentration pathway (RCP) scenarios and 31 world regions (online database at www.pik-potsdam.de/primap/regional_temp_and_precip). As an example application of the projections for climate adaptation and vulnerability studies, future changes in the surface mass balance of the Greenland Ice Sheet are computed.
C1 [Frieler, Katja; Meinshausen, Malte; Mengel, Matthias] Potsdam Inst Climate Impact Res, D-14412 Potsdam, Germany.
   [Braun, Nadine] Ecofys, Cologne, Germany.
   [Hare, William] Climate Analyt, Potsdam, Germany.
C3 Potsdam Institut fur Klimafolgenforschung
RP Frieler, K (corresponding author), Potsdam Inst Climate Impact Res, Telegrafenberg A26, D-14412 Potsdam, Germany.
EM katja.frieler@pik-potsdam.de
RI Meinshausen, Malte/AAG-6505-2019; Meinshausen, Malte/A-7037-2011
OI Mengel, Matthias/0000-0001-6724-9685; Frieler,
   Katja/0000-0003-4869-3013; Hare, William/0000-0003-1242-8250;
   Meinshausen, Malte/0000-0003-4048-3521
FU UFOPLAN by the German Federal Environment Agency [FKZ 370841103]
FX KF and MM were supported by the UFOPLAN project (FKZ 370841103) by the
   German Federal Environment Agency. We thank Reto Knutti and Julie
   Arblaster for initial NCL code examples to diagnose the AOGCM data,
   which were the early basis for our R-based diagnostics routines. We
   thank Tom Wigley for his collaboration on MAGICC and SCENGEN. We
   acknowledge the modeling groups, the Program for Climate Model Diagnosis
   and Intercomparison (PCMDI) and the WCRP's Working Group on Coupled
   Modelling (WGCM), for their roles in making available the WCRP CMIP3
   multimodel dataset. Support of this dataset is provided by the Office of
   Science, U.S. Department of Energy.
CR ALBRECHT BA, 1989, SCIENCE, V245, P1227, DOI 10.1126/science.245.4923.1227
   Allen MR, 2002, NATURE, V419, P224, DOI 10.1038/nature01092
   Allen MR, 2009, NATURE, V458, P1163, DOI 10.1038/nature08019
   Andrews T, 2010, GEOPHYS RES LETT, V37, DOI 10.1029/2010GL043991
   Andrews T, 2009, J CLIMATE, V22, P2557, DOI 10.1175/2008JCLI2759.1
   [Anonymous], 1990, 47 M PLANCK I MET
   [Anonymous], CLIMATE CHANGE 2007
   [Anonymous], 2011, SUMMARY CMIP5 EXPT D
   Bala G, 2010, CLIM DYNAM, V35, P423, DOI 10.1007/s00382-009-0583-y
   Betts RA, 2004, THEOR APPL CLIMATOL, V78, P157, DOI 10.1007/s00704-004-0050-y
   Brohan P, 2006, J GEOPHYS RES-ATMOS, V111, DOI 10.1029/2005JD006548
   Cox PM, 2004, THEOR APPL CLIMATOL, V78, P137, DOI 10.1007/s00704-004-0049-4
   Dessai S, 2005, J GEOPHYS RES-ATMOS, V110, DOI 10.1029/2005JD005919
   Domingues CM, 2008, NATURE, V453, P1090, DOI 10.1038/nature07080
   Dong BW, 2009, J CLIMATE, V22, P3079, DOI 10.1175/2009JCLI2652.1
   Forster PMD, 2006, J CLIMATE, V19, P6181, DOI 10.1175/JCLI3974.1
   Friedlingstein P, 2006, J CLIMATE, V19, P3337, DOI 10.1175/JCLI3800.1
   Frieler K, 2011, GEOPHYS RES LETT, V38, DOI 10.1029/2010GL045953
   Furrer R, 2007, ENVIRON ECOL STAT, V14, P249, DOI 10.1007/s10651-007-0018-z
   Giorgi F, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL024288
   Giorgi F, 2008, J CLIMATE, V21, P1589, DOI 10.1175/2007JCLI1763.1
   Gregory JM, 2006, PHILOS T R SOC A, V364, P1709, DOI 10.1098/rsta.2006.1796
   Harris GR, 2010, NAT HAZARD EARTH SYS, V10, P2009, DOI 10.5194/nhess-10-2009-2010
   Hulme Michael., 2000, Using a climate scenario generator for vulnerability and adaptation assessments: MAGICC and SCENGEN: version 2.4 workbook: Climatic Research Unit
   Huntingford C, 2000, CLIM DYNAM, V16, P575, DOI 10.1007/s003820000067
   Ineson S, 2009, NAT GEOSCI, V2, P32, DOI 10.1038/NGEO381
   Jones A, 2009, ATMOS CHEM PHYS, V9, P6055, DOI 10.5194/acp-9-6055-2009
   Lambert FH, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL034838
   Mearns LO, 2001, CLIMATE CHANGE 2001: THE SCIENTIFIC BASIS, P739
   Meehl GA, 2007, B AM METEOROL SOC, V88, P1383, DOI 10.1175/BAMS-88-9-1383
   Meehl GA, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P747
   Meinshausen M, 2011, ATMOS CHEM PHYS, V11, P1417, DOI 10.5194/acp-11-1417-2011
   Meinshausen M, 2009, NATURE, V458, P1158, DOI 10.1038/nature08017
   Mitchell JFB, 1999, CLIMATIC CHANGE, V41, P547, DOI 10.1023/A:1005466909820
   Mitchell TD, 2003, CLIMATIC CHANGE, V60, P217, DOI 10.1023/A:1026035305597
   Muller CJ, 2011, NAT CLIM CHANGE, V1, P266, DOI 10.1038/NCLIMATE1169
   Nakicenvoic N., 2000, Special report on emissions scenarios: A special report of working group iii of the intergovernmental panel on climate change
   Pennell C, 2011, J CLIMATE, V24, P2358, DOI 10.1175/2010JCLI3814.1
   Pinheiro J. C., 2009, Mixed-effects models in S and S-Plus, DOI DOI 10.1007/BF01313644
   Ramanathan V, 2001, SCIENCE, V294, P2119, DOI 10.1126/science.1064034
   Schlesinger ME, 2000, TECHNOL FORECAST SOC, V65, P167, DOI 10.1016/S0040-1625(99)00114-6
   SCHWARZ G, 1978, ANN STAT, V6, P461, DOI 10.1214/aos/1176344136
   Solomon S, 2009, P NATL ACAD SCI USA, V106, P1704, DOI 10.1073/pnas.0812721106
   Stainforth DA, 2005, NATURE, V433, P403, DOI 10.1038/nature03301
   Tebaldi C, 2009, J R STAT SOC A STAT, V172, P83, DOI 10.1111/j.1467-985X.2008.00545.x
   TWOMEY S, 1977, J ATMOS SCI, V34, P1149, DOI 10.1175/1520-0469(1977)034<1149:TIOPOT>2.0.CO;2
   van den Broeke M, 2009, SCIENCE, V326, P984, DOI 10.1126/science.1178176
   van Vuuren DP, 2011, CLIMATIC CHANGE, V109, P5, DOI [10.1007/s10584-011-0148-z, 10.1007/s10584-011-0157-y]
   Watterson IG, 2008, J GEOPHYS RES-ATMOS, V113, DOI 10.1029/2007JD009254
   Wigley TML, 2001, SCIENCE, V293, P451, DOI 10.1126/science.1061604
   Wu PL, 2010, GEOPHYS RES LETT, V37, DOI 10.1029/2010GL043730
NR 51
TC 49
Z9 51
U1 0
U2 30
PU AMER METEOROLOGICAL SOC
PI BOSTON
PA 45 BEACON ST, BOSTON, MA 02108-3693, UNITED STATES
SN 0894-8755
EI 1520-0442
J9 J CLIMATE
JI J. Clim.
PD MAY
PY 2012
VL 25
IS 9
BP 3117
EP 3144
DI 10.1175/JCLI-D-11-00199.1
PG 28
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA 939OV
UT WOS:000303822700004
OA hybrid
DA 2025-01-10
ER

PT J
AU Li, CY
   Junttila, O
   Heino, P
   Palva, ET
AF Li, CY
   Junttila, O
   Heino, P
   Palva, ET
TI Low temperature sensing in silver birch (<i>Betula pendula</i> Roth)
   ecotypes
SO PLANT SCIENCE
LA English
DT Article
DE abscisic acid; cold acclimation; freezing tolerance; dormancy release
ID FREEZING TOLERANCE; ABSCISIC-ACID; COLD-ACCLIMATION; SEASONAL-CHANGES;
   BUD DORMANCY; ABA; GROWTH; RESISTANCE; PUBESCENS; RELEASE
AB Non-freezing low temperature (LT) is the main factor controlling cold acclimation and dormancy release of woody plants in the cold and temperate regions. Through evolution many tree species have developed different ecotypes, which are closely adapted to the local climatic conditions. In order to elucidate the physiological basis of climatic adaptation involved in LT sensing in the northern tree species, we investigated responses of the northern and southern ecotypes of silver birch (Betula pendula Roth) to a range of decreasing temperatures. Development of freezing tolerance, determined by the electrolyte leakage, and bud dormancy release were monitored. A range of decreasing temperatures triggered cold acclimation and development of freezing tolerance in actively growing plants, and enhanced freezing tolerance and released bud dormancy in the dormant plants in both ecotypes tested. However, there were significant ecotypic differences in LT-induced cold acclimation and bud dormancy release. The northern ecotype was more responsive to a range of decreasing temperatures than the southern ecotype, resulting in more rapid cold acclimation and development of freezing tolerance in actively growing plants, and earlier enhancement of freezing tolerance and bud dormancy release in the dormant plants. Development of freezing tolerance and dormancy release induced by LT was accompanied by changes in ABA levels. Alterations in ABA levels paralleled with development of freezing tolerance and preceded bud dormancy release in both ecotypes tested, but these alterations in ABA levels were ecotype-dependent, the northern ecotype reacting more strongly to LT. (C) 2004 Elsevier Ireland Ltd. All rights reserved.
C1 Chinese Acad Sci, Chengdu Inst Biol, Chengdu 610041, Peoples R China.
   Univ Helsinki, Viikki Bioctr, Div Genet, Dept Biosci, FIN-00014 Helsinki, Finland.
   Univ Tromso, Dept Biol, N-9037 Tromso, Norway.
   Univ Helsinki, Dept Appl Biol, FIN-00014 Helsinki, Finland.
C3 Chinese Academy of Sciences; Chengdu Institute of Biology, CAS;
   University of Helsinki; UiT The Arctic University of Tromso; University
   of Helsinki
RP Chinese Acad Sci, Chengdu Inst Biol, POB 416, Chengdu 610041, Peoples R China.
EM licy@cib.ac.cn; tapio.palva@helsinki.fi
RI li, chun yang/D-6254-2013
OI li, chun yang/0000-0003-2895-2786
CR Baldwin BD, 1998, PHYSIOL PLANTARUM, V102, P201, DOI 10.1034/j.1399-3054.1998.1020207.x
   Bewley JD, 1994, SEEDS PHYSL DEV GERM, P199, DOI 10.1007/978-1-4899-1002-8_5
   Browse J, 2001, CURR OPIN PLANT BIOL, V4, P241, DOI 10.1016/S1369-5266(00)00167-9
   Davies W.J., 1991, Abscisic acid: Physiology and biochemistry
   Fladung M, 1997, J PLANT PHYSIOL, V150, P420, DOI 10.1016/S0176-1617(97)80092-2
   GIRAUDAT J, 1994, PLANT MOL BIOL, V26, P1557, DOI 10.1007/BF00016490
   Hughes MA, 1996, J EXP BOT, V47, P291, DOI 10.1093/jxb/47.3.291
   Lee H, 1999, PLANT J, V17, P301, DOI 10.1046/j.1365-313X.1999.00375.x
   LEVITT J, 1980, RESPONSES PLANTS ENV, V1, P19
   Li CY, 2003, TREE PHYSIOL, V23, P481, DOI 10.1093/treephys/23.7.481
   Li CY, 2003, TREES-STRUCT FUNCT, V17, P127, DOI 10.1007/s00468-002-0214-2
   Li CY, 2003, PHYSIOL PLANTARUM, V117, P206, DOI 10.1034/j.1399-3054.2003.00002.x
   Li CY, 2002, PHYSIOL PLANTARUM, V116, P478, DOI 10.1034/j.1399-3054.2002.1160406.x
   MYKING T, 1995, TREE PHYSIOL, V15, P697, DOI 10.1093/treephys/15.11.697
   MYKING T, 1997, THESIS AGR U NORWAY
   NUOTIO S, 2001, CROP RESPONSES ADAPT, P151
   Palva ET, 1997, PLANT COLD HARDINESS, P3
   POWELL LE, 1987, HORTSCIENCE, V22, P845
   QAMARUDDIN M, 1993, PHYSIOL PLANTARUM, V87, P203, DOI 10.1111/j.1399-3054.1993.tb00143.x
   RINNE P, 1994, PHYSIOL PLANTARUM, V90, P451, DOI 10.1111/j.1399-3054.1994.tb08801.x
   RINNE P, 1994, TREE PHYSIOL, V14, P549, DOI 10.1093/treephys/14.6.549
   Rinne P, 1998, PLANT CELL ENVIRON, V21, P601, DOI 10.1046/j.1365-3040.1998.00306.x
   Rinne PLH, 2001, PLANT J, V26, P249, DOI 10.1046/j.1365-313X.2001.01022.x
   SAKAI A, 1987, FORST SURVIVAL PLANT
   STUSHNOFF C, 1986, POLAR BIOL, V5, P129, DOI 10.1007/BF00441691
   SUKUMARAN N P, 1972, Hortscience, V7, P467
   SUTTLE JC, 1994, PLANT PHYSIOL, V105, P891, DOI 10.1104/pp.105.3.891
   Thomashow MF, 1999, ANNU REV PLANT PHYS, V50, P571, DOI 10.1146/annurev.arplant.50.1.571
   WEISER CJ, 1970, SCIENCE, V169, P1269, DOI 10.1126/science.169.3952.1269
   Welling A, 1997, PHYSIOL PLANTARUM, V100, P119, DOI 10.1034/j.1399-3054.1997.1000112.x
   WRIGHT STC, 1975, J EXP BOT, V26, P161, DOI 10.1093/jxb/26.2.161
   Xin Z, 2000, PLANT CELL ENVIRON, V23, P893, DOI 10.1046/j.1365-3040.2000.00611.x
NR 32
TC 15
Z9 19
U1 0
U2 16
PU ELSEVIER IRELAND LTD
PI CLARE
PA ELSEVIER HOUSE, BROOKVALE PLAZA, EAST PARK SHANNON, CO, CLARE, 00000,
   IRELAND
SN 0168-9452
J9 PLANT SCI
JI Plant Sci.
PD JUL
PY 2004
VL 167
IS 1
BP 165
EP 171
DI 10.1016/j.plantsci.2004.03.015
PG 7
WC Biochemistry & Molecular Biology; Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biochemistry & Molecular Biology; Plant Sciences
GA 824HM
UT WOS:000221677300021
DA 2025-01-10
ER

PT J
AU Meier, S
   Campos, P
   Morales, A
   Jobet, C
   López-Olivari, R
   Palma-Millanao, R
   Matus, I
   Aponte, H
   Cartes, P
   Khan, N
   Lavanderos, L
   Seguel, A
AF Meier, Sebastian
   Campos, Pedro
   Morales, Arturo
   Jobet, Claudio
   Lopez-Olivari, Rafael
   Palma-Millanao, Ruben
   Matus, Ivan
   Aponte, Humberto
   Cartes, Paula
   Khan, Naser
   Lavanderos, Laura
   Seguel, Alex
TI Genotypic responses to phosphorus and water management in winter wheat:
   Strategies to increase resource use efficiency and productivity
SO AGRICULTURAL WATER MANAGEMENT
LA English
DT Article
DE Genotypic difference; Phosphorus deficit; Drought; Grain quality
ID GRAIN-YIELD; NUTRIENT MANAGEMENT; ROOT RESPONSE; STRESS; ACQUISITION;
   NITROGEN; QUALITY; FIELD; CHALLENGES; COMPONENTS
AB The phosphorus (P) addition can be helpful in the mitigation of the adverse effects of water deficit stress. However, the efficiency of wheat in utilizing both components has not been assessed in field conditions. This research aims to assess the effects of P and water addition on phosphorus use efficiency (PUE) and water productivity (WP) in field conditions for select wheat cultivars co-adapted to climate-induced agronomic challenges. Three wheat cultivars were selected based on their PUE and water WP from a previous experiment. The trials were conducted in field conditions over two consecutive years, from 2020 to 2021 (Season 1) and 2021 - 2022 (Season 2). The plants were grown on an andisol with a soil P concentration of 10 mg P kg -1 and 30 mg P kg -1 . Two irrigation treatments were imposed: Well-watered (+W) and dryland (-W). The plants were sampled at three stages: tillering (Z25), anthesis (Z65), and ripening (Z95). At the end of the phenological cycle, grain yield components, grain yield, grain quality, PUE, and WP were evaluated. Phosphorus addition promotes plant growth, especially in the early vegetative stages, by enhancing tiller development and nutrient and water uptake. These effects were critical during the anthesis and ripening stages, enhancing yield components and higher grain production. Differential responses were observed across cultivars, underscoring the genotype-specificity in PUE and WP. Seasonal water deficit stress modulated these effects, highlighting a more complex genotypeenvironment-nutrient interaction. The water addition promoted PUE and WP, suggesting a synergy between the two components. Among the cultivars, Chevignon outperformed in grain yield, PUE, and WP. However, while phosphorus, water, and environmental factors influenced grain quality, the genetic background of the cultivar was the primary determinant of these components. This study advocates for implementing individual nutrient management strategies tailored to the specific cultivar and adaptable to environmental conditions under climate change.
C1 [Meier, Sebastian; Campos, Pedro; Morales, Arturo; Jobet, Claudio; Lopez-Olivari, Rafael] INIA Carillanca, Inst Invest Agr, Casilla Postal 929, Temuco, Chile.
   [Meier, Sebastian] Univ Mayor, Escuela Agron, Fac Ciencias Ingn & Tecnol, Temuco, Chile.
   [Palma-Millanao, Ruben] Univ La Frontera, Vicerrectoria Invest & Postgrad, Temuco, Chile.
   [Matus, Ivan] INIA Quilamapu, Inst Invest Agr, Av Vicente Mendez 515, Chillan, Chile.
   [Aponte, Humberto] Univ OHiggins, Lab Soil Microbiol & Biogeochem, Campus Colchagua, Rancagua, Chile.
   [Cartes, Paula] Univ La Frontera, BIOREN UFRO, Sci & Technol Bioresource Nucleus, POB 54-D, Temuco, Chile.
   [Khan, Naser] Univ Adelaide, Sch Chem Engn, Adelaide, SA 5000, Australia.
   [Lavanderos, Laura] Univ La Frontera, Fac Ciencias Agr & Medioambiente, Carrera Agron, POB 54-D, Temuco 4811230, Chile.
   [Seguel, Alex] Univ La Frontera, Fac Ciencias Agr & Medioambiente, Dept Ciencias Agron & Recursos Nat, Temuco, Chile.
C3 Instituto de Investigacion Agropecuaria (INIA); Universidad Mayor;
   Universidad de La Frontera; Universidad de O'Higgins; Universidad de La
   Frontera; University of Adelaide; Universidad de La Frontera;
   Universidad de La Frontera
RP Meier, S (corresponding author), INIA Carillanca, Inst Invest Agr, Casilla Postal 929, Temuco, Chile.; Seguel, A (corresponding author), Univ La Frontera, Fac Ciencias Agr & Medioambiente, Dept Ciencias Agron & Recursos Nat, Temuco, Chile.
EM sebastian.meier@inia.cl; alex.seguel@ufrontera.cl
RI Campos, Pedro/AAD-3433-2020
OI de Souza Campos, Pedro/0000-0002-7749-6863; Lavanderos Kehr,
   Laura/0000-0002-9458-6596; Palma-Millanao, Ruben/0000-0002-1317-4689
FU FONDECYT [1220190, 1201257, 1211387]; Subsecretaria de Agricultura,
   Gobierno de Chile [503605-71]; Subsecretaria de Agricultura, Gobierno de
   Chile, Programa de Recursos Geneticos [30-501453-70]
FX Sebastian Meier, Paula Cartes, and Alex Seguel acknowledge the FONDECYT
   project numbers 1220190, 1201257, and 1211387, respectively. Sebastian
   Meier also acknowledges Subsecretaria de Agricultura, Gobierno de Chile,
   number 503605-71 Pedro de Souza Campo acknowledges Subsecretaria de
   Agricultura, Gobierno de Chile, Programa de Recursos Geneticos number
   30-501453-70.
CR Acuña TB, 2015, CROP PASTURE SCI, V66, P419, DOI 10.1071/CP14308
   Ahmadi A, 2001, J AGR SCI-CAMBRIDGE, V136, P257, DOI 10.1017/S0021859601008772
   Alewell C, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-18326-7
   Allen R. G., 1998, FAO Irrigation and Drainage Paper
   Aziz H.A., 2017, Arch Clin Biomed Res.
   Balemi T, 2012, J SOIL SCI PLANT NUT, V12, P547, DOI 10.4067/S0718-95162012005000015
   Barraclough PB, 2010, EUR J AGRON, V33, P1, DOI 10.1016/j.eja.2010.01.005
   Bashir S., 2015, Methods, V5
   Blum A, 2005, AUST J AGR RES, V56, P1159, DOI 10.1071/AR05069
   Bovill WD, 2013, CROP PASTURE SCI, V64, P179, DOI 10.1071/CP13135
   Brennan RF, 2009, CROP PASTURE SCI, V60, P566, DOI 10.1071/CP08401
   Brouwer C., 1985, Training Manual
   Chen XX, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-53000-z
   CIREN, 2002, Publicacion CIREN N 122
   Condon AG, 2004, J EXP BOT, V55, P2447, DOI 10.1093/jxb/erh277
   Cong WF, 2020, TRENDS PLANT SCI, V25, P967, DOI 10.1016/j.tplants.2020.04.013
   Covacevich F, 2007, APPL SOIL ECOL, V35, P1, DOI 10.1016/j.apsoil.2006.06.001
   del Pozo A, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-019-57116-0
   Deng Y, 2018, FRONT PLANT SCI, V9, DOI 10.3389/fpls.2018.01614
   Etchevers B.J.D., 2007, Nutr. oN. De. Cultiv., V438
   Famiglietti JS, 2013, SCIENCE, V340, P1300, DOI 10.1126/science.1236460
   FAO, 2020, 1 FAO UN, DOI DOI 10.4060/CA8032EN
   Farooq M, 2014, CRIT REV PLANT SCI, V33, P331, DOI 10.1080/07352689.2014.875291
   Forero LE, 2019, FRONT ENV SCI-SWITZ, V7, DOI 10.3389/fenvs.2019.00184
   Giunta F., 1993, Field Crops Res.
   Gorden E., 2018, Breeding for Phosphorus Use Efficiency in Wheat (Triticum aestivum L.), P127
   Gutierrez-Boem FH, 1998, AGRON J, V90, P166, DOI 10.2134/agronj1998.00021962009000020008x
   HANSON WC, 1950, J SCI FOOD AGR, V1, P172, DOI 10.1002/jsfa.2740010604
   Hatfield JL, 2019, FRONT PLANT SCI, V10, DOI 10.3389/fpls.2019.00103
   Ho MD, 2005, FUNCT PLANT BIOL, V32, P737, DOI 10.1071/FP05043
   Ionescu V., 2010, Comparative evaluation of wet gluten quantity and quality through different methods Functional composites based on whey protein and vegetable extracts for food applications
   Jin J, 2005, SOIL SCI PLANT NUTR, V51, P953, DOI 10.1111/j.1747-0765.2005.tb00133.x
   Johnston AE, 2014, ADV AGRON, V123, P177, DOI 10.1016/B978-0-12-420225-2.00005-4
   Lambers H, 2006, ANN BOT-LONDON, V98, P693, DOI 10.1093/aob/mcl114
   Lázaro L, 2010, J AGR SCI-CAMBRIDGE, V148, P83, DOI 10.1017/S0021859609990402
   López-Olivari R, 2021, IRRIGATION SCI, V39, P173, DOI 10.1007/s00271-020-00693-0
   Lynch JP, 2007, AUST J BOT, V55, P493, DOI 10.1071/BT06118
   Meena RP, 2019, AGR WATER MANAGE, V223, DOI 10.1016/j.agwat.2019.105709
   Meier S, 2023, RHIZOSPHERE-NETH, V25, DOI 10.1016/j.rhisph.2022.100631
   Meier S, 2022, AGR WATER MANAGE, V263, DOI 10.1016/j.agwat.2022.107481
   Meier S, 2021, AGR WATER MANAGE, V248, DOI 10.1016/j.agwat.2021.106765
   MOLL RH, 1982, AGRON J, V74, P562, DOI 10.2134/agronj1982.00021962007400030037x
   Nagy R, 2006, PLANT BIOLOGY, V8, P186, DOI 10.1055/s-2005-873052
   Ozturk A, 2004, J AGRON CROP SCI, V190, P93, DOI 10.1046/j.1439-037X.2003.00080.x
   PASSIOURA JB, 1977, J AUST I AGR SCI, V43, P117
   Pouri K, 2019, CEREAL RES COMMUN, V47, P383, DOI 10.1556/0806.47.2019.05
   Roberts TL, 2015, RESOUR CONSERV RECY, V105, P275, DOI 10.1016/j.resconrec.2015.09.013
   Rodriguez D., 1999, Effects of phosphorus nutrition on tiller emergence in wheat
   Rose TJ, 2013, FRONT PLANT SCI, V4, DOI 10.3389/fpls.2013.00444
   Rosegrant MW, 2003, SCIENCE, V302, P1917, DOI 10.1126/science.1092958
   Sadras V.O., 2010, SOLAW Background Thematic Report TR07 42
   Sadras V.O., 2012, Grains Res. Dev. Corp., P1
   Sadzawka A., 2006, Metodos de Analisis Recomendados para los Suelos de Chile Revision 2006
   Salazar-Gutierrez M.R., 2013, Article in International Journal of Plant Production
   Sandaña P, 2014, J SOIL SCI PLANT NUT, V14, P973
   Sandaña P, 2016, EUR J AGRON, V76, P95, DOI 10.1016/j.eja.2016.02.003
   Sandoval M., 2012, Publicaciones Departamento de Suelos y Recursos Naturales, V5, P80
   Sharma B.R., 2015, Curr. Situat. Trends
   Shen JY, 2021, SUSTAIN PROD CONSUMP, V28, P736, DOI 10.1016/j.spc.2021.07.002
   Slafer GA, 2014, FIELD CROP RES, V157, P71, DOI 10.1016/j.fcr.2013.12.004
   Syers J.K., 2008, FAO fertilizer and plant nutrition bulletin, V18, P1
   Teng W, 2017, FRONT PLANT SCI, V8, DOI 10.3389/fpls.2017.00543
   Teng W, 2013, J EXP BOT, V64, P1403, DOI 10.1093/jxb/ert023
   Tóth B, 2020, J CEREAL SCI, V91, DOI 10.1016/j.jcs.2019.102867
   Vance CP, 2003, NEW PHYTOL, V157, P423, DOI 10.1046/j.1469-8137.2003.00695.x
   Wang XR, 2010, PLANT SCI, V179, P302, DOI 10.1016/j.plantsci.2010.06.007
   Waraich EA, 2011, ACTA AGR SCAND B-S P, V61, P291, DOI 10.1080/09064710.2010.491954
   Waraich EA, 2010, J PLANT NUTR, V33, P640, DOI 10.1080/01904160903575881
   Zhao YJ, 2021, PLANT CELL TISS ORG, V147, P545, DOI 10.1007/s11240-021-02146-8
   Zhu XK, 2012, J INTEGR AGR, V11, P1103, DOI 10.1016/S2095-3119(12)60103-8
NR 70
TC 1
Z9 1
U1 8
U2 9
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 APR 30
PY 2024
VL 295
AR 108762
DI 10.1016/j.agwat.2024.108762
EA MAR 2024
PG 16
WC Agronomy; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Water Resources
GA QQ1O2
UT WOS:001222245200001
OA hybrid
DA 2025-01-10
ER

PT J
AU Tanyi, CB
   Ngosong, C
   Ntonifor, NN
AF Tanyi, Clovis B.
   Ngosong, Christopher
   Ntonifor, Nelson N.
TI Effects of climate variability on insect pests of cabbage: adapting
   alternative planting dates and cropping pattern as control measures
SO CHEMICAL AND BIOLOGICAL TECHNOLOGIES IN AGRICULTURE
LA English
DT Article
DE Climate change; Diamondback moth; Intercropping; Piper botanical;
   Planting date
ID DIAMONDBACK MOTH LEPIDOPTERA; AGRICULTURAL PRODUCTIVITY; RESISTANCE;
   CONSEQUENCES; PLUTELLIDAE; EFFICACY; CAMEROON
AB Background: Considering the potential impact of climate change on the ecology of insect pests, different planting dates and cropping patterns were investigated as farm-level adaption to control insect pests of cabbage and improve productivity.
   Methods: This is a 3 x 4 factorial experiment setup in randomized complete block design including three planting dates (early, normal and late) and four cropping patterns (control-sole cabbage or tomato, tomato intercrop, Piper emulsion and insecticide) with four replications each.
   Results: Cabbage infestation ranged from 1 to 29 and correlated negatively with planting dates or treatments, which differed (P < 0.001) significantly across planting dates, treatments and their interaction, with the highest during early planting. Diamondback moth larvae correlated negatively with planting dates or treatments, ranging from 0 to 13 that differed significantly (P < 0.001) across planting dates, treatments and their interaction. Looper larvae correlated negatively with treatments, ranging from 0 to 8 that differed significantly (P < 0.001) across planting dates, treatments and their interaction, with highest during normal planting and lowest during late planting. Webworm larvae correlated negatively with planting dates or treatments, ranging from 0 to 13 that differed significantly (P < 0.001) across planting dates, treatments and their interaction. The number of sprouted plants ranged from 0 to 6 and differed significantly (P < 0.001) across planting dates, treatments and their interaction, with the highest in early planting for control that differed significantly from late planting. Cabbage yield correlated positively with planting dates and ranged from 2.8 to 6.0 tons per hectare that differed significantly (P < 0.001) across planting dates, treatments and their interaction, with the highest during normal and late planting dates.
   Conclusion: The interaction of planting dates and Piper emulsion or intercropping treatments can be effectively used as control measure for insect pests of cabbage leading to greater yield, with late planting as viable farm-level adaptation to climate variability.
C1 [Tanyi, Clovis B.; Ngosong, Christopher; Ntonifor, Nelson N.] Univ Buea, Fac Agr & Vet Med, Dept Agron & Appl Mol Sci, POB 63, Buea, South West Regi, Cameroon.
RP Tanyi, CB (corresponding author), Univ Buea, Fac Agr & Vet Med, Dept Agron & Appl Mol Sci, POB 63, Buea, South West Regi, Cameroon.
EM tanyi.clovis@yahoo.com
RI Ngosong, Christopher/O-8274-2018
OI Tanyi, Clovis/0000-0003-1279-2773
FU Faculty of Agriculture and Veterinary Medicine, University of Buea;
   Ministry of Higher Education-MINESUP Cameroon
FX We extend gratitude to the Faculty of Agriculture and Veterinary
   Medicine, University of Buea, and the Ministry of Higher
   Education-MINESUP Cameroon for Research Grants.
CR Abril S, 2010, J INSECT SCI, V10, DOI 10.1673/031.010.9701
   Arong G.A., 2011, WORLD J SCI TECHNOL, V1, P14
   Asare-Bediako E., 2010, American Journal of Food Technology, V5, P269, DOI 10.3923/ajft.2010.269.274
   Bagamba F., 2012, African Crop Science Journal, V20, P303
   Bale JS, 2002, GLOBAL CHANGE BIOL, V8, P1, DOI 10.1046/j.1365-2486.2002.00451.x
   Das D.K., 2011, J. Agric. Phys, V11, P13
   Datta S., 2013, International J. of Sci., V2, P661
   de Paula VF, 2000, PEST MANAG SCI, V56, P168
   ENDERSBY NM, 1991, BIOL AGRIC HORTIC, V8, P33, DOI 10.1080/01448765.1991.9754574
   Estay SA, 2009, J APPL ENTOMOL, V133, P491, DOI 10.1111/j.1439-0418.2008.01380.x
   Fraser P.J., 1998, Climate of the Mount Cameroon region, Long and Medium Term rainfall, Temperature and Sunshine Data, P56
   Gornall J, 2010, PHILOS T R SOC B, V365, P2973, DOI 10.1098/rstb.2010.0158
   Jamieson MA, 2012, PLANT PHYSIOL, V160, P1719, DOI 10.1104/pp.112.206524
   John P., 2007, W AFRICA PLANT ECOL, V192, P251, DOI DOI 10.1007/S11258-007-9326-5
   Kemausuor F., 2011, Journal of Agricultural and Biological Science, V6, P26
   Kerchev PI, 2012, PLANT CELL ENVIRON, V35, P441, DOI 10.1111/j.1365-3040.2011.02399.x
   Kotir Julius H., 2011, Environment Development and Sustainability, V13, P587, DOI 10.1007/s10668-010-9278-0
   Laux P, 2010, AGR FOREST METEOROL, V150, P1258, DOI 10.1016/j.agrformet.2010.05.008
   Lobell DB, 2008, SCIENCE, V319, P607, DOI 10.1126/science.1152339
   Menendez Rosa, 2007, Tijdschrift voor Entomologie, V150, P355
   Mirza MMQ, 2003, CLIM POLICY, V3, P233, DOI 10.1016/S1469-3062(03)00052-4
   Mochiah MB., 2011, J ENTOMOLOGY NEMATOL, V3, P85
   Mohammad FD, 2014, J AGR FISH, V3, P171, DOI DOI 10.11648/J.AFF.20140303.15
   Ngondjeb YD, 2013, AFR J SCI TECHNOL IN, V5, P85, DOI 10.1080/20421338.2013.782151
   Okonkwo C. O., 2013, Journal of Chemical and Pharmaceutical Research, V5, P370
   Olesen JE, 2002, EUR J AGRON, V16, P239, DOI 10.1016/S1161-0301(02)00004-7
   Pane C, 2015, CHEM BIOL TECHNOL AG, V2, DOI 10.1186/s40538-014-0026-9
   PORTER JH, 1991, AGR FOREST METEOROL, V57, P221, DOI 10.1016/0168-1923(91)90088-8
   Sarfraz M, 2005, J APPL ENTOMOL, V129, P149, DOI 10.1111/j.1439-0418.2005.00930.x
   Sayyed AH, 2008, J ECON ENTOMOL, V101, P1658, DOI 10.1603/0022-0493(2008)101[1658:GBAPCO]2.0.CO;2
   Scott IM, 2004, J ECON ENTOMOL, V97, P1390, DOI 10.1603/0022-0493-97.4.1390
   SHELTON AM, 1993, J ECON ENTOMOL, V86, P11, DOI 10.1093/jee/86.1.11
   Shelton AM, 2000, J ECON ENTOMOL, V93, P931, DOI 10.1603/0022-0493-93.3.931
   Shukla A, 2005, ADV INT ENTOMON PR S, V1, P229
   StatSoft, 2010, STAT 9 1 WIND
   Stireman JO, 2005, P NATL ACAD SCI USA, V102, P17384, DOI 10.1073/pnas.0508839102
   Susila W, 2003, J ISSAAS, V9, P132
   Syed T. S., 2003, Journal of South China Agricultural University, V24, P87
   Tanyi C., 2017, J. Agric. Ecol. Res, V13, P1, DOI [10.9734/JAERI/2017/38815, DOI 10.9734/JAERI/2017/38815]
   Tingem M, 2008, CLIM RES, V36, P65, DOI 10.3354/cr00733
   Van Damme V, 2015, J PEST SCI, V88, P533, DOI 10.1007/s10340-014-0636-9
   Xu QC, 2010, J FOOD AGRIC ENVIRON, V8, P1037
NR 57
TC 8
Z9 10
U1 2
U2 16
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
EI 2196-5641
J9 CHEM BIOL TECHNOL AG
JI Chem. Biol. Technol. Agric.
PD DEC 10
PY 2018
VL 5
AR 25
DI 10.1186/s40538-018-0140-1
PG 11
WC Agriculture, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA HD7YH
UT WOS:000452769600001
OA gold
DA 2025-01-10
ER

PT J
AU Yang, YZ
   Cheng, ZJ
   Li, WY
   Yao, L
   Li, ZY
   Luo, WH
   Yuan, ZJ
   Zhang, J
   Zhang, JZ
AF Yang YuZhang
   Cheng ZhiJie
   Li WeiYa
   Yao Ling
   Li ZhanYang
   Luo WuHong
   Yuan ZengJian
   Zhang Juan
   Zhang JuZhong
TI The emergence, development and regional differences of mixed farming of
   rice and millet in the upper and middle Huai River Valley, China
SO SCIENCE CHINA-EARTH SCIENCES
LA English
DT Article
DE Upper and middle Huai River; Neolithic; Mixed farming of rice and
   millet; Agricultural development and transformation; Regional
   differences
ID STARCH; IDENTIFICATION; PHYTOLITH; GRAINS
AB Mixed farming of rice and millet is one of the basic agricultural modes in the upper and middle Huai River Valley (HRV). According to the latest data, this agricultural mode appeared during the middle and late Peiligang Culture (7.8-7.0 ka BP) in the upper HRV, and then became a common subsistence economy in the end of the Neolithic (5.0-4.0 ka BP) in both the upper and middle HRV. However, it is still not clear how this mixed farming developed in the upper HRV after its occurrence, nor are the regional differences in the development of mixed farming between the upper and middle HRV during the Neolithic completely understood. In this paper, flotation and starch analyses were conducted on samples from eight archaeological sites in the upper and middle HRV. The results indicate that the mixed farming of rice and millet first appeared in the later phase of the middle Neolithic in the regions of the Peiligang Culture, then developed quite rapidly in the late Neolithic (6.8-5.0 ka BP), finally becoming the main subsistence economy at the end of the Neolithic in the upper HRV. However, there are obvious differences in the emergence and development of agriculture between the middle and upper HRV. Rice farming was the only agricultural system during the middle Neolithic, lasting until the end of the Neolithic, when mixed farming appeared in the middle HRV. Furthermore, although mixed farming appeared in both the upper and middle HRV during the end of the Neolithic, the roles of rice, foxtail millet and broomcorn millet in the subsistence economy were not the same. In general, millet was more widely cultivated than rice in the upper HRV, but rice occupied the same or a slightly more prominent position in the middle HRV at the end of the Neolithic. These results are significant for understanding the process of agricultural development and transformation, as well as human adaptation to climatic and cultural variability duringthe Neolithic.
C1 [Yang YuZhang; Cheng ZhiJie; Li WeiYa; Yao Ling; Luo WuHong; Yuan ZengJian; Zhang Juan; Zhang JuZhong] Univ Sci & Technol China, Dept Hist Sci & Sci Archaeol, Hefei 230026, Peoples R China.
   [Li WeiYa] Leiden Univ, Fac Archaeol, NL-2333 CC Leiden, Netherlands.
   [Li ZhanYang] Henan Prov Inst Cultural Relics & Archaeol, Zhengzhou 450000, Peoples R China.
C3 Chinese Academy of Sciences; University of Science & Technology of
   China, CAS; Leiden University - Excl LUMC; Leiden University
RP Luo, WH; Zhang, JZ (corresponding author), Univ Sci & Technol China, Dept Hist Sci & Sci Archaeol, Hefei 230026, Peoples R China.
EM wh0551@mail.ustc.edu.cn; juzhzh@ustc.edu.cn
RI zhou, yang/JED-3951-2023; Zhang, Jiacheng/HTS-3961-2023; Zhou,
   Boyan/HJI-4278-2023; Zhang, Juan/GRX-2638-2022
OI Li, Weiya/0000-0001-7040-8472
FU Strategic Priority Research Program of the Chinese Academy of Sciences
   [XDA05130503]; National Basic Research Program of China [2015CB953802];
   National Natural Science Foundation of China [41472148, 41502164];
   Ministry of Education [15YJA780003]
FX This work was supported by the Strategic Priority Research Program of
   the Chinese Academy of Sciences (Grant No. XDA05130503), National Basic
   Research Program of China (Grant No. 2015CB953802), the National Natural
   Science Foundation of China (Grant Nos. 41472148 & 41502164) and the
   Philosophy and Social Science Planning Project of the Ministry of
   Education (Grant No. 15YJA780003).
CR Anhui Provincial Institute of Culture Relics and Archaeology Bengbu Municipal Museum, 2008, EXC REP NEOL SIT SHU, P684
   [Anonymous], 2005, J Zhengzhou Univ
   Bar-Yosef O, 2011, CURR ANTHROPOL, V52, pS175, DOI 10.1086/659784
   Chen W W, 2012, HUAXIA ARCHAEOL, P54
   [程至杰 Cheng Zhijie], 2016, [第四纪研究, Quaternary Sciences], V36, P302
   Childe V G, 1951, MAN MAKES HIMSELF, P191
   Department of archeology in Peking University Zhumadian Municipal Institution of Cultural Relics Protection., 1998, ZHUM YANGZH CULT REL, P91
   Dong Z., 2013, THESIS
   [董珍 Dong Zhen], 2014, [第四纪研究, Quaternary Sciences], V34, P114
   Gao G R, 2005, J ZHENGZHOU U PHILOS, V38, P5
   [葛威 Ge Wei], 2010, [第四纪研究, Quaternary Sciences], V30, P377
   Guan G Q, 2000, IDENTIFICATION WEED, P358
   Guo Q X, 1998, IDENTIFICATION WEED, P176
   Henan Provincial Institute of Cultural Relics and Archaeology, 1987, HUAXIA ARCHAEOL, P3
   Henan Provincial Institute of Cultural Relics and Archaeology, 1999, JIAH WUYANG COUNT, P883
   Henan Provincial Institute of Cultural Relics and Archaeology, 1995, ACTA ARCHAEOL SIN, P39
   Henan Provincial Institute of Cultural Relics and Archaeology Department for the History of Science and Scientific Archaeology in University of Science and technology of China, 2015, JIAHU WUYANG COUNTY, P743
   [黄润 Huang Run], 2005, [地理学报, Acta Geographica Sinica], V60, P742
   [李占扬 Li Zhanyang], 2014, [人类学学报, Acta Anthropologica Sinica], V33, P285
   Lin L.G., 2014, ACTA ARCHAEOL SIN, V4, P519
   Liu L., 2014, ARCHAEOL CULT RELICS, V3, P109
   Liu L, 2014, J ARCHAEOL SCI, V52, P421, DOI 10.1016/j.jas.2014.09.008
   Liu L, 2013, P NATL ACAD SCI USA, V110, P5380, DOI 10.1073/pnas.1217864110
   Liu L, 2010, ANTIQUITY, V84, P816, DOI 10.1017/S0003598X00100249
   Lu HY, 2009, PLOS ONE, V4, DOI 10.1371/journal.pone.0004448
   Luan F S, 2005, J ZHENGZHOU U, V38, P10
   Meteorological Bureau of Anhui Province, 1983, CLIM ANH PROV, P122
   Meteorological Bureau of Henan Province, 1980, CLIM ANH PROV, P121
   No.1 Team of Institute of Archaeology of CASS, 1984, ACTA ARCHAEOL SIN, P23
   Perry L, 2011, PLAINS ANTHROPOL, V56, P109, DOI 10.1179/pan.2011.011
   Piperno DR, 2004, NATURE, V430, P670, DOI 10.1038/nature02734
   Qin L, 2010, QUAT SCI, V30, P246
   Ren S., 2005, ACAD EXPLORATION, V6, P110
   School of Archaeology and Museology of Peking University, 2007, PREL ARCH REP INV UP, P916
   Shida N, 2004, SEEDS WILD PLANTS JA, P261
   Torrence R., 2006, ANCIENT STARCH RES, P256
   [万智巍 Wan Zhiwei], 2011, [第四纪研究, Quaternary Sciences], V31, P736
   Wang J, 1984, AGR ARCHAEOLOGY, P276
   Wang Y., 2011, ARCHAEOLOGY, P3
   Wang Z L, 1998, ARCHAEOLOGY, P87
   Wei Cun-xu, 2008, Zhongguo Shuidao Kexue, V22, P377
   Wu Y, 2014, J ARCHAEOL SCI, V49, P326, DOI 10.1016/j.jas.2014.06.001
   Yan W M, 2000, ORIGINS AGR RISE CIV, P388
   Yang XY, 2013, J ARCHAEOL SCI, V40, P3170, DOI 10.1016/j.jas.2013.04.004
   Yang XY, 2012, P NATL ACAD SCI USA, V109, P3726, DOI 10.1073/pnas.1115430109
   [杨晓燕 Yang Xiaoyan], 2010, [第四纪研究, Quaternary Sciences], V30, P364
   [杨晓燕 Yang Xiaoyan], 2009, [第四纪研究, Quaternary Sciences], V29, P153
   [杨玉璋 Yang Yuzhang], 2015, [第四纪研究, Quaternary Sciences], V35, P229
   Yin D., 2013, YUHUICUN SITE BENGBU, P250
   Zhang J. Z., 2004, E ARCHAEOLOGY, P198
   Zhang J, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0030181
   [张永辉 Zhang Yonghui], 2011, [第四纪研究, Quaternary Sciences], V31, P891
   Zhao Z., 2009, Kaogu, V2009, P84
   Zhao Z.J., 2010, PALEOETHNOBOTANY THE, P109
   Zhao ZJ, 1998, ECON BOT, V52, P134, DOI 10.1007/BF02861201
   Zhao ZJ., 2007, Huaxia Kaogu (Huaxia Archaeol.), V2, P78
NR 56
TC 33
Z9 44
U1 1
U2 45
PU SCIENCE PRESS
PI BEIJING
PA 16 DONGHUANGCHENGGEN NORTH ST, BEIJING 100717, PEOPLES R CHINA
SN 1674-7313
EI 1869-1897
J9 SCI CHINA EARTH SCI
JI Sci. China-Earth Sci.
PD SEP
PY 2016
VL 59
IS 9
BP 1779
EP 1790
DI 10.1007/s11430-015-5340-3
PG 12
WC Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI); Arts &amp; Humanities Citation Index (A&amp;HCI)
SC Geology
GA DV1GX
UT WOS:000382669900007
DA 2025-01-10
ER

PT J
AU Bennie, J
   Kubin, E
   Wiltshire, A
   Huntley, B
   Baxter, R
AF Bennie, Jonathan
   Kubin, Eero
   Wiltshire, Andrew
   Huntley, Brian
   Baxter, Robert
TI Predicting spatial and temporal patterns of bud-burst and spring frost
   risk in north-west Europe: the implications of local adaptation to
   climate
SO GLOBAL CHANGE BIOLOGY
LA English
DT Article
DE Betula pubescens; bud-burst; climate change; downy birch; Fennoscandia;
   Finland; frost risk; growing degree days; growing season; phenology
ID MOUNTAIN BIRCH; GROWING-SEASON; BOREAL TREES; PHENOLOGY; BUDBURST;
   TEMPERATE; GROWTH; MODEL; VARIABILITY; RESPONSES
AB The timing of spring bud-burst and leaf development in temperate, boreal and Arctic trees and shrubs fluctuates from year to year, depending on meteorological conditions. Over several generations, the sensitivity of bud-burst to meteorological conditions is subject to selection pressure. The timing of spring bud-burst is considered to be under opposing evolutionary pressures; earlier bud-burst increases the available growing season (capacity adaptation) but later bud-burst decreases the risk of frost damage to actively growing parts (survival adaptation). The optimum trade-off between these two forms of adaptation may be considered an evolutionarily stable strategy that maximizes the long-term ecological fitness of a phenotype under a given climate. Rapid changes in climate, as predicted for this century, are likely to exceed the rate at which trees and shrubs can adapt through evolution or migration. Therefore the response of spring phenology will depend not only on future climatic conditions but also on the limits imposed by adaptation to current and historical climate. Using a dataset of bud-burst dates from twenty-nine sites in Finland for downy birch (Betula pubescens Ehrh.), we parameterize a simple thermal time bud-burst model in which the critical temperature threshold for bud-burst is a function of recent historical climatic conditions and reflects a trade-off between capacity and survival adaptation. We validate this approach with independent data from eight independent sites outside Finland, and use the parameterized model to predict the response of bud-burst to future climate scenarios in north-west Europe. Current strategies for budburst are predicted to be suboptimal for future climates, with bud-burst generally occurring earlier than the optimal strategy. Nevertheless, exposure to frost risk is predicted to decrease slightly and the growing season is predicted to increase considerably across most of the region. However, in high-altitude maritime regions exposure to frost risk following bud-burst is predicted to increase.
C1 [Bennie, Jonathan; Wiltshire, Andrew; Huntley, Brian; Baxter, Robert] Univ Durham, Sch Biol & Biomed Sci, Ctr Ecosyst Sci, CLASSIC, Durham DH1 3LE, England.
   [Kubin, Eero] Finnish Forest Res Inst, Muhos Res Unit, FI-91500 Muhos, Finland.
C3 Durham University; Natural Resources Institute Finland (Luke)
RP Bennie, J (corresponding author), Univ Durham, Sch Biol & Biomed Sci, Ctr Ecosyst Sci, CLASSIC, South Rd, Durham DH1 3LE, England.
EM j.j.bennie@exeter.ac.uk
RI Bennie, Jonathan/A-6526-2010; Wiltshire, Andy/C-2848-2008; Baxter,
   Robert/C-7688-2012
OI Baxter, Robert/0000-0002-7504-6797; Bennie, Jonathan/0000-0003-4394-2041
FU Climate Land atmosphere Interaction Centre (CLASSIC), UK Natural
   Environment Research Council Centres of Excellence in Earth Observation
   [F14/G6/116]; NERC [NE/F010222/1, earth010002] Funding Source: UKRI
FX This study was supported by grant F14/G6/116 (Climate Land atmosphere
   Interaction Centre (CLASSIC), a component of the UK Natural Environment
   Research Council Centres of Excellence in Earth Observation. The authors
   would like to thank the anonymous reviewers of this and a previous
   version of the manuscript for their insightful comments.
CR Ahas R, 2002, INT J CLIMATOL, V22, P1727, DOI 10.1002/joc.818
   Ahl DE, 2006, REMOTE SENS ENVIRON, V104, P88, DOI 10.1016/j.rse.2006.05.003
   [Anonymous], 2000, SPECIAL REPORT EMISS
   [Anonymous], [No title captured]
   [Anonymous], ACT FOR FEN
   [Anonymous], 2001, DESCRIPTION TRIFFID
   Aono Y, 2008, INT J CLIMATOL, V28, P905, DOI 10.1002/joc.1594
   Badeck FW, 2004, NEW PHYTOL, V162, P295, DOI 10.1111/j.1469-8137.2004.01059.x
   BILLINGTON HL, 1991, FUNCT ECOL, V5, P403, DOI 10.2307/2389812
   Botta A, 2000, GLOBAL CHANGE BIOL, V6, P709, DOI 10.1046/j.1365-2486.2000.00362.x
   CANNELL MGR, 1986, J APPL ECOL, V23, P177, DOI 10.2307/2403090
   Chuine I, 2000, J THEOR BIOL, V207, P337, DOI 10.1006/jtbi.2000.2178
   Dalen L, 2005, ARCT ANTARCT ALP RES, V37, P284, DOI 10.1657/1523-0430(2005)037[0284:DRTDIT]2.0.CO;2
   Doi H, 2008, GLOBAL ECOL BIOGEOGR, V17, P556, DOI 10.1111/j.1466-8238.2008.00398.x
   Doi H, 2008, AGR FOREST METEOROL, V148, P512, DOI 10.1016/j.agrformet.2007.10.002
   Eriksson G, 1986, SCAND J FOREST RES, V1, P421, DOI 10.1080/02827588609382434
   Fisher JI, 2007, GLOBAL CHANGE BIOL, V13, P707, DOI 10.1111/j.1365-2486.2006.01311.x
   Fisher JI, 2006, REMOTE SENS ENVIRON, V100, P265, DOI 10.1016/j.rse.2005.10.022
   Gansert D, 1999, J ECOL, V87, P382, DOI 10.1046/j.1365-2745.1999.00354.x
   Givnish TJ, 2002, SILVA FENN, V36, P703, DOI 10.14214/sf.535
   HANNINEN H, 1991, PLANT CELL ENVIRON, V14, P449, DOI 10.1111/j.1365-3040.1991.tb01514.x
   Heide OM, 2003, TREE PHYSIOL, V23, P931, DOI 10.1093/treephys/23.13.931
   Howe GT, 2003, CAN J BOT, V81, P1247, DOI [10.1139/b03-141, 10.1139/B03-141]
   HUNTER AF, 1992, J APPL ECOL, V29, P597, DOI 10.2307/2404467
   Johns TC, 2006, J CLIMATE, V19, P1327, DOI 10.1175/JCLI3712.1
   Jylhä K, 2004, BOREAL ENVIRON RES, V9, P127
   Karlsen SR, 2008, INT J APPL EARTH OBS, V10, P253, DOI 10.1016/j.jag.2007.10.005
   Karlsen SR, 2007, INT J BIOMETEOROL, V51, P513, DOI 10.1007/s00484-007-0091-x
   Karlsen SR, 2006, GLOBAL ECOL BIOGEOGR, V15, P416, DOI 10.1111/j.1466-822x.2006.00234.x
   Karlsson PS, 2003, ECOGRAPHY, V26, P617, DOI 10.1034/j.1600-0587.2003.03607.x
   KRAMER K, 1995, PLANT CELL ENVIRON, V18, P93, DOI 10.1111/j.1365-3040.1995.tb00356.x
   Kucharik CJ, 2006, ECOL MODEL, V196, P1, DOI 10.1016/j.ecolmodel.2005.11.031
   LECHOWICZ MJ, 1984, AM NAT, V124, P821, DOI 10.1086/284319
   Leinonen I, 2002, SILVA FENN, V36, P695, DOI 10.14214/sf.534
   Linkosalo T, 2008, TREE PHYSIOL, V28, P1873, DOI 10.1093/treephys/28.12.1873
   Linkosalo T, 2006, TREE PHYSIOL, V26, P1249, DOI 10.1093/treephys/26.10.1249
   Linkosalo T, 2006, TREE PHYSIOL, V26, P1165, DOI 10.1093/treephys/26.9.1165
   LOCKHART JA, 1983, OECOLOGIA, V60, P34, DOI 10.1007/BF00379317
   Menzel A, 2001, GLOBAL CHANGE BIOL, V7, P657, DOI 10.1046/j.1365-2486.2001.00430.x
   Menzel A, 2000, INT J BIOMETEOROL, V44, P76, DOI 10.1007/s004840000054
   Menzel A, 2006, GLOBAL CHANGE BIOL, V12, P1969, DOI 10.1111/j.1365-2486.2006.01193.x
   Mjaaseth RR, 2005, OECOLOGIA, V145, P53, DOI 10.1007/s00442-005-0089-1
   MURRAY MB, 1989, J APPL ECOL, V26, P693, DOI 10.2307/2404093
   MYKING T, 1995, TREE PHYSIOL, V15, P697, DOI 10.1093/treephys/15.11.697
   Myneni RB, 1997, NATURE, V386, P698, DOI 10.1038/386698a0
   Nordli O, 2008, INT J BIOMETEOROL, V52, P625, DOI 10.1007/s00484-008-0156-5
   Piao SL, 2006, GLOBAL CHANGE BIOL, V12, P672, DOI 10.1111/j.1365-2486.2006.01123.x
   Picard G, 2005, GLOBAL CHANGE BIOL, V11, P2164, DOI 10.1111/j.1365-2486.2005.01055.x
   Potter CS, 1999, GLOBAL ECOL BIOGEOGR, V8, P473, DOI 10.1046/j.1365-2699.1999.00152.x
   Prozherina N, 2003, NEW PHYTOL, V159, P623, DOI 10.1046/j.1469-8137.2003.00828.x
   Pudas E, 2008, INT J BIOMETEOROL, V52, P251, DOI 10.1007/s00484-007-0126-3
   Rigby JR, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL033955
   Ruohomaki K, 1997, ECOLOGY, V78, P2105, DOI 10.1890/0012-9658(1997)078[2105:LVEODT]2.0.CO;2
   Schwartz MD, 2006, GLOBAL CHANGE BIOL, V12, P343, DOI 10.1111/j.1365-2486.2005.01097.x
   Shutova E, 2006, INT J BIOMETEOROL, V51, P155, DOI 10.1007/s00484-006-0042-y
   Siljamo P, 2008, GLOBAL ECOL BIOGEOGR, V17, P489, DOI 10.1111/j.1466-8238.2008.00383.x
   SKRE O, 1993, NATO ADV SCI INST SE, V244, P65
   Slayback DA, 2003, GLOBAL CHANGE BIOL, V9, P1, DOI 10.1046/j.1365-2486.2003.00507.x
   Stöckli R, 2004, INT J REMOTE SENS, V25, P3303, DOI 10.1080/01431160310001618149
   Tanja S, 2003, GLOBAL CHANGE BIOL, V9, P1410, DOI 10.1046/j.1365-2486.2003.00597.x
   Tape K, 2006, GLOBAL CHANGE BIOL, V12, P686, DOI 10.1111/j.1365-2486.2006.01128.x
   Taulavuori KMJ, 2004, NEW PHYTOL, V162, P427, DOI 10.1111/j.1469-8137.2004.01042.x
   Thompson R, 2006, INT J BIOMETEOROL, V50, P312, DOI 10.1007/s00484-005-0017-4
   Weih M, 2001, MAN BIOSPH, V27, P143
   Wesolowski T, 2006, FOREST ECOL MANAG, V237, P387, DOI 10.1016/j.foreco.2006.09.061
   White MA, 2006, REMOTE SENS ENVIRON, V104, P43, DOI 10.1016/j.rse.2006.04.014
   Wielgolaski FE, 2003, INT J BIOMETEOROL, V47, P213, DOI 10.1007/s00484-003-0178-y
   Zar HJ, 1996, Biostatistical analysis, V3rd
NR 68
TC 128
Z9 149
U1 1
U2 129
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 2010
VL 16
IS 5
BP 1503
EP 1514
DI 10.1111/j.1365-2486.2009.02095.x
PG 12
WC Biodiversity Conservation; Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA 583RG
UT WOS:000276696100007
OA Bronze
DA 2025-01-10
ER

PT J
AU Yoshida, H
   Horie, T
AF Yoshida, Hiroe
   Horie, Takeshi
TI A process model for explaining genotypic and environmental variation in
   growth and yield of rice based on measured plant N accumulation
SO FIELD CROPS RESEARCH
LA English
DT Article
DE Crop model; Genotype-by-environment interaction; Sink-source balance;
   Nitrogen use efficiency
ID RESPIRATION COEFFICIENTS; ONTOGENETIC CHANGES; BIOMASS GROWTH;
   PHOTOSYNTHESIS; TEMPERATURE; REPRESSION; INHIBITION; STERILITY; SORGHUM;
   CO2
AB The objective of this study was to develop a mechanistic model for simulating the genotypic and environmental variation in rice growth and yield based on measured plant N accumulation. The model calibrations and evaluations were conducted for rice growth and yield data obtained from a cross-locational experiment on 9 genotypes at 7 climatically different locations in Asia. The rough dry grain yield measured in the experiment ranged from 71 to 1044 g m(-2) over the genotypes and locations. An entire process model was developed by integrating sub-models for simulating the processes of leaf-area index development, partitioning of nitrogen within plant organs, vegetative biomass growth, spikelet number determination, and yield. The entire process model considered down-regulation of photosynthesis caused by limited capacity for end-product utilization in growing sink organs by representing canopy photosynthetic rate as a function of sugar content per unit leaf nitrogen content. The model well explained the observed genotypic and environmental variation in the dynamics of above-ground biomass growth (for validation dataset, R-2 = 95), leaf area index development (R-2 = 0.82) and leaf N content (R-2 = 0.85), and spikelet number per unit area (R-2 = 0.67) and rough grain yield (R-2 = 0.66), simultaneously. The model calibrations for each sub-model and the entire process model against observed data identified 10 genotype-specific model parameters as important traits for determining genotypic differences in the growth attributes. Out of the 10 parameters, 5 were related to the processes of phenological development and spikelet sterility, considered to be major determinants of genotypic adaptability to climate. The other 5 parameters of stomatal conductance, radiation extinction coefficient, nitrogen use efficiency in spikelet differentiation, critical leaf N causing senescence, and potential single grain mass had significant influence on the yield potential of genotypes under given climate conditions. (C) 2009 Elsevier B.V. All rights reserved.
C1 [Yoshida, Hiroe; Horie, Takeshi] Natl Agr & Food Res Org, Tsukuba, Ibaraki 3058517, Japan.
C3 National Agriculture & Food Research Organization - Japan
RP Horie, T (corresponding author), Natl Agr & Food Res Org, Kannondai 3-1-1, Tsukuba, Ibaraki 3058517, Japan.
EM horiet@affrc.go.jp
CR Ainsworth EA, 2005, NEW PHYTOL, V165, P351, DOI 10.1111/j.1469-8137.2004.01224.x
   [Anonymous], POTENTIAL PRODUCTIVI
   [Anonymous], 2006, Working with Crop ModelsEvaluation, Analysis, Parameterization and Applications
   BAGNALL DJ, 1988, PLANTA, V175, P348, DOI 10.1007/BF00396340
   BATTEN GD, 1993, PLANT SOIL, V155, P243, DOI 10.1007/BF00025029
   BOURNAN BAM, 2001, ORYZA2000 MODELING L, P1
   Dingkuhn M, 1996, AGR SYST, V52, P383, DOI 10.1016/0308-521X(95)00078-J
   Haga T., 1980, REGRESSION ANAL PRIN
   Horie T., 1987, Southeast Asian Studies, V25, P62
   Horie T., 2003, JPN J CROP SCI, V72, P88
   Horie T., 1995, Modeling the Impact of Climate Change on Rice Production in Asia, P51
   IWAKI H, 1975, JIBP SYNTHESIS, V11, P105
   KABAKI N, 1982, JPN J CROP SCI, V51, P82, DOI 10.1626/jcs.51.82
   KING RW, 1967, PLANTA, V77, P261, DOI 10.1007/BF00385296
   KROPFF MJ, 1994, SARP RES P LOS BAN A, P1
   MATSUSHIMA S, 1958, JPN J CROP SCI, V27, P6
   MCCREE KJ, 1988, CROP SCI, V28, P114, DOI 10.2135/cropsci1988.0011183X002800010025x
   Moore BD, 1999, PLANT CELL ENVIRON, V22, P567, DOI 10.1046/j.1365-3040.1999.00432.x
   Paul MJ, 1997, PLANT CELL ENVIRON, V20, P110, DOI 10.1046/j.1365-3040.1997.d01-17.x
   PAUL MJ, 1991, J EXP BOT, V42, P845, DOI 10.1093/jxb/42.7.845
   PENNINGDEVRIES FWT, 1975, ANN BOT-LONDON, V39, P77
   SATAKE T, 1983, JPN J CROP SCI, V52, P207, DOI 10.1626/jcs.52.207
   SATAKE T, 1978, JPN J CROP SCI, V47, P6, DOI 10.1626/jcs.47.6
   SATAKE T, 1970, Proceedings of the Crop Science Society of Japan, V39, P468
   SETTER TL, 1980, PLANT PHYSIOL, V65, P884, DOI 10.1104/pp.65.5.884
   SHEEN J, 1990, PLANT CELL, V2, P1027, DOI 10.1105/tpc.2.10.1027
   SIVASAMY R, 1994, NITROGEN EC IRRIGATE, P31
   STAHL RS, 1988, CROP SCI, V28, P111, DOI 10.2135/cropsci1988.0011183X002800010024x
   Stitt M, 1999, PLANT CELL ENVIRON, V22, P583, DOI 10.1046/j.1365-3040.1999.00386.x
   Thornley JHM, 2000, ANN BOT-LONDON, V85, P55, DOI 10.1006/anbo.1999.0997
   Ueda T., 2000, JPN J CROP SCI, V69, P112
   Wada G., 1969, Bull. natn. Inst. agric. Sci., Tokyo, VA16, P27
   Wada M., 1981, Bulletin of the Kyushu National Agricultural Experiment Station, V21, P113
   YIN X, 2005, CROP SYSTEMS DYNAMIC, P1
   Yoshida H, 2006, FIELD CROP RES, V97, P337, DOI 10.1016/j.fcr.2005.11.004
   Yoshida H, 2008, FIELD CROP RES, V108, P222, DOI 10.1016/j.fcr.2008.05.004
   Yoshida H, 2007, FIELD CROP RES, V102, P228, DOI 10.1016/j.fcr.2007.04.006
NR 37
TC 28
Z9 30
U1 3
U2 44
PU ELSEVIER SCIENCE BV
PI AMSTERDAM
PA PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
SN 0378-4290
EI 1872-6852
J9 FIELD CROP RES
JI Field Crop. Res.
PD SEP 4
PY 2009
VL 113
IS 3
BP 227
EP 237
DI 10.1016/j.fcr.2009.05.010
PG 11
WC Agronomy
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA 486KD
UT WOS:000269194000005
DA 2025-01-10
ER

PT J
AU Beever, EA
   Westover, ML
   Smith, AB
   Gerraty, FD
   Billman, PD
   Smith, FA
AF Beever, Erik A.
   Westover, Marie L.
   Smith, Adam B.
   Gerraty, Francis D.
   Billman, Peter D.
   Smith, Felisa A.
TI Combining past and contemporary species occurrences with ordinal species
   distribution modeling to investigate responses to climate change
SO ECOGRAPHY
LA English
DT Article; Early Access
DE Distributional declines; geographic range retraction; logistic
   regression; ordinal regression; ordinal response; temporal
   interpretation
ID OCHOTONA-PRINCEPS; AMERICAN PIKA; OCCUPANCY ESTIMATION; RANGE EXPANSION;
   MULTIPLE STATES; POPULATION; DISPERSAL; PATTERNS; COLONIZATION;
   EXTIRPATION
AB Many organisms leave evidence of their former occurrence, such as scat, abandoned burrows, middens, ancient eDNA or fossils, which indicate areas from which a species has since disappeared. However, combining this evidence with contemporary occurrences within a single modeling framework remains challenging. Traditional binary species-distribution modeling reduces occurrence to two temporally coarse states (present/absent), so thus cannot leverage the information inherent in temporal sequences of evidence of past occurrence. In contrast, ordinal modeling can use the natural time-varying order of states (e.g. never occupied versus previously occupied versus currently occupied) to provide greater insights into range shifts. We demonstrate the power of ordinal modeling for identifying the major influences of biogeographic and climatic variables on current and past occupancy of the American pika Ochotona princeps, a climate-sensitive mammal. Sampling over five years across the species' southernmost, warm-edge range limit, we tested the effects of these variables at 570 habitat patches where occurrence was classified either as binary or ordinal. The two analyses produced different top models and predictors - ordinal modeling highlighted chronic cold as the most-important predictor of occurrence, whereas binary modeling indicated primacy of average summer-long temperatures. Colder wintertime temperatures were associated in ordinal models with higher likelihood of occurrence, which we hypothesize reflect longer retention of insulative and meltwater-provisioning snowpacks. Our binary results mirrored those of other past pika investigations employing binary analysis, wherein warmer temperatures decrease likelihood of occurrence. Because both ordinal- and binary-analysis top models included climatic and biogeographic factors, results constitute important considerations for climate-adaptation planning. Cross-time evidences of species occurrences remain underutilized for assessing responses to climate change. Compared to multi-state occupancy modeling, which presumes all states occur in the same time period, ordinal models enable use of historical evidence of species' occurrence to identify factors driving species' distributions more finely across time.
C1 [Beever, Erik A.] US Geol Survey, Northern Rocky Mt Sci Ctr, Bozeman, MT USA.
   [Beever, Erik A.] Montana State Univ, Bozeman, MT USA.
   [Westover, Marie L.; Smith, Felisa A.] Univ New Mexico, Dept Biol, Albuquerque, NM USA.
   [Westover, Marie L.] Rios Community Coll Dist, Sacramento, CA USA.
   [Smith, Adam B.] Ctr Conservat & Sustainable Dev, Missouri Bot Garden, St Louis, MO 63110 USA.
   [Gerraty, Francis D.] Univ Calif Santa Cruz, Dept Ecol & Evolutionary Biol, Santa Cruz, CA USA.
   [Billman, Peter D.] Univ Connecticut, Dept Ecol & Evolutionary Biol, Storrs, CT USA.
C3 United States Department of the Interior; United States Geological
   Survey; Montana State University System; Montana State University
   Bozeman; University of New Mexico; Missouri Botanical Gardens;
   University of California System; University of California Santa Cruz;
   University of Connecticut
RP Smith, AB (corresponding author), Ctr Conservat & Sustainable Dev, Missouri Bot Garden, St Louis, MO 63110 USA.
EM Adam.Smith@mobot.org
RI Smith, Adam/H-6906-2019; Smith, Felisa/ABE-6160-2021; Smith,
   Adam/L-5111-2013
OI Smith, Adam/0000-0002-6420-1659; Gerraty, Francis
   (Frankie)/0000-0001-9989-4953; Beever, Erik/0000-0002-9369-486X
CR Agresti Alan., 2010, Wiley Series in Probability and Statistics, V2nd, DOI DOI 10.1002/9780470594001
   Alexander JM, 2018, GLOBAL CHANGE BIOL, V24, P563, DOI 10.1111/gcb.13976
   [Anonymous], 2012, Regression for categorical data
   Beever E. A., 2024, Data from: Combining past and contemporary species occurrences with ordinal species distribution modeling to investigate responses to climate change, DOI [10.5061/dryad.z612jm6n0, DOI 10.5061/DRYAD.Z612JM6N0]
   Beever EA, 2003, J MAMMAL, V84, P37, DOI 10.1644/1545-1542(2003)084<0037:POAEAI>2.0.CO;2
   Beever EA, 2023, BIOL CONSERV, V282, DOI 10.1016/j.biocon.2023.109942
   Beever EA, 2016, J MAMMAL, V97, P1495, DOI 10.1093/jmammal/gyw128
   Beever EA, 2013, ECOLOGY, V94, P1563, DOI 10.1890/12-2174.1
   Beever EA, 2011, GLOBAL CHANGE BIOL, V17, P2054, DOI 10.1111/j.1365-2486.2010.02389.x
   Beever EA, 2010, ECOL APPL, V20, P164, DOI 10.1890/08-1011.1
   Bennie J, 2013, ECOL LETT, V16, P921, DOI 10.1111/ele.12129
   Billman PD, 2023, FRONT ECOL EVOL, V11, DOI 10.3389/fevo.2023.1202610
   Billman PD, 2021, GLOBAL CHANGE BIOL, V27, P4498, DOI 10.1111/gcb.15793
   Burnham K. P., 2002, Model selection and inference: a practical informationtheoretic approach, VSecond edition
   Calkins MT, 2012, ECOGRAPHY, V35, P780, DOI 10.1111/j.1600-0587.2011.07227.x
   Cao J, 2021, FRONT MAR SCI, V8, DOI 10.3389/fmars.2021.736462
   Castillo JA, 2016, ECOL APPL, V26, P1660, DOI 10.1890/15-1452.1
   Daly C, 2002, CLIM RES, V22, P99, DOI 10.3354/cr022099
   Erb LP, 2011, ECOLOGY, V92, P1730, DOI 10.1890/11-0175.1
   Fordham DA, 2020, SCIENCE, V369, P1072, DOI 10.1126/science.abc5654
   Galbreath KE, 2009, EVOLUTION, V63, P2848, DOI 10.1111/j.1558-5646.2009.00803.x
   Giam XL, 2016, METHODS ECOL EVOL, V7, P388, DOI 10.1111/2041-210X.12492
   Guisan A, 2000, J VEG SCI, V11, P617, DOI 10.2307/3236568
   Guisan A., 2017, Habitat Suitability and Distribution Models: With Applications in R
   Jackson ST, 2005, J BIOGEOGR, V32, P1085, DOI 10.1111/j.1365-2699.2005.01251.x
   Johnston AN, 2019, ECOLOGY, V100, DOI 10.1002/ecy.2638
   Jones R, 2023, LANDSCAPE ECOL, V38, P3003, DOI 10.1007/s10980-023-01776
   Kittle AM, 2008, OECOLOGIA, V157, P163, DOI 10.1007/s00442-008-1051-9
   Klingler KB, 2023, PEERJ, V11, DOI 10.7717/peerj.15962
   Mackenzie DI, 2009, ECOLOGY, V90, P823, DOI 10.1890/08-0141.1
   MacKenzie DI, 2003, ECOLOGY, V84, P2200, DOI 10.1890/02-3090
   MacKenzie DI., 2018, OCCUPANCY ESTIMATION, V2nd
   Maclean IMD, 2023, NAT CLIM CHANGE, V13, P484, DOI 10.1038/s41558-023-01650-3
   Martin J, 2009, BIOL CONSERV, V142, P2726, DOI 10.1016/j.biocon.2009.06.027
   McNellie MJ, 2019, APPL VEG SCI, V22, P361, DOI 10.1111/avsc.12437
   Meik JM, 2018, ECOL EVOL, V8, P928, DOI 10.1002/ece3.3658
   Millar CI, 2014, ECOL APPL, V24, P1748, DOI 10.1890/13-0520.1
   Nadeau CP, 2017, GLOBAL CHANGE BIOL, V23, P12, DOI 10.1111/gcb.13475
   NAGELKERKE NJD, 1991, BIOMETRIKA, V78, P691, DOI 10.1093/biomet/78.3.691
   Nichols JD, 2008, J APPL ECOL, V45, P1321, DOI 10.1111/j.1365-2664.2008.01509.x
   Nichols JD, 2007, ECOLOGY, V88, P1395, DOI 10.1890/06-1474
   Noruis M. J., 2011, Ordinal regression. IBM SPSS Statistics 19 advanced statistical procedures companion
   Oldfather MF, 2020, GLOBAL CHANGE BIOL, V26, P1055, DOI 10.1111/gcb.14897
   Pagel J, 2020, P NATL ACAD SCI USA, V117, P3663, DOI 10.1073/pnas.1908684117
   Peacock MM, 1997, OECOLOGIA, V112, P524, DOI 10.1007/s004420050341
   Ray C, 2016, ECOSPHERE, V7, DOI 10.1002/ecs2.1379
   Rubenstein MA, 2023, ENVIRON EVID, V12, DOI 10.1186/s13750-023-00296-0
   Schwalm D, 2016, GLOBAL CHANGE BIOL, V22, P1572, DOI 10.1111/gcb.13189
   SMITH A T, 1990, Mammalian Species, P1, DOI 10.2307/3504319
   Smith AB, 2019, NAT CLIM CHANGE, V9, P787, DOI 10.1038/s41558-019-0584-8
   SMITH AT, 1983, BEHAV ECOL SOCIOBIOL, V13, P37, DOI 10.1007/BF00295074
   SMITH AT, 1978, ECOLOGY, V59, P133, DOI 10.2307/1936639
   SMITH AT, 1974, ECOLOGY, V55, P1368, DOI 10.2307/1935464
   Smith F. A., 2021, Mammalian paleoecology: using the past to study the present
   Smith FA, 2009, GLOBAL PLANET CHANGE, V65, P122, DOI 10.1016/j.gloplacha.2008.10.015
   Stewart JAE, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0181834
   Stewart JAE, 2015, J BIOGEOGR, V42, P880, DOI 10.1111/jbi.12466
   Tapper S.C., 1973, SPATIAL ORG PIKAS OC
   Thompson William., 2017, Investigating occupancy and density of American pikas (Ochotona princeps) across precipitation gradients in the intermountain West, USA
   Tingley MW, 2009, TRENDS ECOL EVOL, V24, P625, DOI 10.1016/j.tree.2009.05.009
   Valle D, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-39377-x
   Venables W. N., 2002, Modern Applied Statistics with S, DOI 10.1007/978-0-387-21706-2
   Zhu LK, 2019, NAT CLIM CHANGE, V9, P886, DOI 10.1038/s41558-019-0588-4
NR 63
TC 0
Z9 0
U1 4
U2 4
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 0906-7590
EI 1600-0587
J9 ECOGRAPHY
JI Ecography
PD 2024 NOV 27
PY 2024
DI 10.1111/ecog.07382
EA NOV 2024
PG 14
WC Biodiversity Conservation; Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA N4A6W
UT WOS:001363789900001
OA gold
DA 2025-01-10
ER

PT J
AU Marley, CL
   Fychan, R
   Davies, JW
   Scott, M
   Crotty, F
   Sanderson, R
   Scullion, J
AF Marley, Christina L.
   Fychan, Rhun
   Davies, John W.
   Scott, Mark
   Crotty, Felicity, V
   Sanderson, Ruth
   Scullion, John
TI Grasslands and flood mitigation - Contrasting forages improve surface
   water infiltration rates
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Clovers; Forbs; Climate change resilience; Earthworms; Roots
ID CHICORY CICHORIUM-INTYBUS; PLANTAIN PLANTAGO-LANCEOLATA; ECOSYSTEM
   SERVICES; SOIL; GROWTH; PERFORMANCE; MANAGEMENT; PASTURE; IMPACT; DAIRY
AB Grasslands globally deliver many ecosystem services, including water management to alleviate flood risk reduction. Two replicated field experiments were conducted to study how agricultural forage species with diverse rooting systems, sown as single species, affected rooting, soil structure and earthworm populations, and consequently water infiltration to understand how they each might influence flood risk from grasslands. Experiment One showed soils under red clover (Trifolium pratense), white clover (Trifolium repens) and chicory (Cichorium intybus) had higher infiltration rates three years after establishment, compared to perennial ryegrass (Lolium perenne). Higher red clover and chicory root biomass or increased earthworm abundance under white clover may have caused these effects. Experiment Two monitored infiltration at intervals over several years post establishment to understand the timeframe for changes in rates; plantain (Plantago lanceolata) was sown as an additional forage. Infiltration declined post establishment, the timing and extent of decline varying with forages; forage effects were significant after 27 months (P < 0.05). Infiltration rates were higher under red and white clover compared to ryegrass, with chicory and plantain intermediate (P < 0.05). Forages again differed in likely mechanisms delivering higher water infiltration, notably between the two clover species. White clover had higher earthworm biomass (P < 0.05), whereas red clover had a higher average root diameter compared to the other forages (P < 0.05). Drivers of intermediate benefits of chicory and plantain also differed: chicory had higher earthworm abundance (month 38) compared to plantain, which had higher average root diameter compared to ryegrass (month 41); 30 months post-establishment soil bulk density was lower under both forages compared to ryegrass and red clover, with white clover intermediate (P < 0.05); bulk density and penetration resistance did not relate to infiltration. Findings demonstrate that a shift from perennial ryegrass-dominated pastures to swards with more contrasting forages provides an ecohydrological approach to mitigating flood risk and climate adaptation.
C1 [Marley, Christina L.] Aberystwyth Univ, Inst Biol Environm & Rural Sci IBERS, Gogerddan SY23 3EE, Ceredigion, Wales.
   [Crotty, Felicity, V] Ricardo Energy & Environm, Agr & Land Team, Gemini Bldg,Fermi Ave, Didcot OX11 0QR, England.
C3 Aberystwyth University; UK Research & Innovation (UKRI); Biotechnology
   and Biological Sciences Research Council (BBSRC); Institute of
   Biological, Environmental, Rural & Sciences (IBERS)
RP Marley, CL (corresponding author), Aberystwyth Univ, Inst Biol Environm & Rural Sci IBERS, Gogerddan SY23 3EE, Ceredigion, Wales.
EM cvm@aber.ac.uk; arf@aber.ac.uk; jtd@aber.ac.uk; mds@aber.ac.uk;
   rts@aber.ac.uk; jos@aber.ac.uk
FU Welsh Government Rural Communities-Rural Development Programme 2014-2020
   - European Agricultural Fund for Rural Development [81334]; Welsh
   Government; BBSRC; UKRI
FX The authors sincerely thank Vince Theobald, Huw Powell, Naomi Gordon,
   Jan Newman and all staff in analytical chemistry at IBERS for their
   assistance with this research. The PROSOILplus project (81334) received
   funding through the Welsh Government Rural Communities-Rural Development
   Programme 2014-2020, which is funded by the European Agricultural Fund
   for Rural Development and the Welsh Government. IBERS receives strategic
   funding from BBSRC, UKRI.
CR AHDB, 2023, Nutrient Management Guide (RB209). Section 3 Grass and Forage Crops
   Alaoui A, 2018, J HYDROL, V557, P631, DOI 10.1016/j.jhydrol.2017.12.052
   Alifu H, 2022, SCI REP-UK, V12, DOI 10.1038/s41598-022-25182-6
   Amami R, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13063155
   Baird D.B., 2022, Introduction to Genstat for Windows TM, V22nd
   Bengtsson J, 2019, ECOSPHERE, V10, DOI 10.1002/ecs2.2582
   Blanco-Canqui H, 2017, SOIL TILL RES, V170, P38, DOI 10.1016/j.still.2017.03.001
   Bommarco R, 2013, TRENDS ECOL EVOL, V28, P230, DOI 10.1016/j.tree.2012.10.012
   Bouche M B., 1971, La Vie dans les Sols, Aspects Nouveaux, Etudes Experimentales, P187
   Bouche MB, 1997, SOIL BIOL BIOCHEM, V29, P441, DOI 10.1016/S0038-0717(96)00272-6
   Brown H. E., 2003, Legumes for dryland pastures. Proceedings of a New Zealand Grassland Association (Inc.) Symposium held at Lincoln University, 18-19 November, 2003, P91
   CARADUS JR, 1990, ADV AGRON, V43, P1
   Carretta L, 2021, CATENA, V197, DOI 10.1016/j.catena.2020.104972
   Cheng L, 2017, J AGR SCI-CAMBRIDGE, V155, P669, DOI 10.1017/S0021859616001076
   CLEMENT CR, 1966, J SOIL SCI, V17, P133, DOI 10.1111/j.1365-2389.1966.tb01460.x
   Cranston LM, 2016, J AGRON CROP SCI, V202, P13, DOI 10.1111/jac.12129
   Cresswell A, 1999, ANN BOT-LONDON, V84, P359, DOI 10.1006/anbo.1999.0928
   Crotty FV, 2015, SOIL BIOL BIOCHEM, V91, P119, DOI 10.1016/j.soilbio.2015.08.036
   Crotty F.V., 2020, The Changing Status of Arable Habitats in Europe, P123, DOI [10.1007/978-3-030-59875-49, DOI 10.1007/978-3-030-59875-49]
   Cui Z, 2022, SCI TOTAL ENVIRON, V819, DOI 10.1016/j.scitotenv.2021.151985
   Curry JP, 2007, PEDOBIOLOGIA, V50, P463, DOI 10.1016/j.pedobi.2006.09.001
   Deru JGC, 2018, APPL SOIL ECOL, V125, P26, DOI 10.1016/j.apsoil.2017.12.011
   Eekeren N. van, 2010, Proceedings of the 19th World Congress of Soil Science: Soil solutions for a changing world, Brisbane, Australia, 1-6 August 2010. Symposium 4.1.1 Valuing the soil's natural capital, P27
   Environment Agency, 2021, Report to Ministers under the Climate Change Act 2021
   Evans JR, 2020, J EXP BOT, V71, P2211, DOI 10.1093/jxb/eraa110
   EVANS PS, 1977, NEW ZEAL J AGR RES, V20, P331, DOI 10.1080/00288233.1977.10427343
   Ferreira CSS, 2022, SCI TOTAL ENVIRON, V805, DOI 10.1016/j.scitotenv.2021.150106
   Freeman C, 2023, SCI TOTAL ENVIRON, V879, DOI 10.1016/j.scitotenv.2023.163063
   Gibbs R.J., 1986, Changes in Soil Structure under Different Cropping Systems, P131
   Gregory J. H., 2005, Applied Turfgrass Science, P1
   He QS, 2024, RESOUR CONSERV RECY, V203, DOI 10.1016/j.resconrec.2024.107428
   Jacques W. A., 1943, NEW ZEALAND JOUR SCI AND TECH, V25A, P91
   Keesstra S, 2018, SCI TOTAL ENVIRON, V610, P997, DOI 10.1016/j.scitotenv.2017.08.077
   Kendon EJ, 2023, NAT COMMUN, V14, DOI 10.1038/s41467-023-36499-9
   Kleijn D, 2019, TRENDS ECOL EVOL, V34, P154, DOI 10.1016/j.tree.2018.11.002
   Lane SN, 2017, WIRES WATER, V4, DOI 10.1002/wat2.1211
   Lemaire G, 2011, GRASSLAND PRODUCTIVITY AND ECOSYSTEM SERVICES, P1, DOI 10.1079/9781845938093.0000
   Li CJ, 2011, ALLELOPATHY J, V27, P43
   Marchi L, 2010, J HYDROL, V394, P118, DOI 10.1016/j.jhydrol.2010.07.017
   Marley CL, 2007, GRASS FORAGE SCI, V62, P1, DOI 10.1111/j.1365-2494.2007.00556.x
   Marley CL, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0086259
   Marley CL, 2003, VET PARASITOL, V112, P147, DOI 10.1016/S0304-4017(02)00412-0
   Milazzo F, 2023, AGR ECOSYST ENVIRON, V348, DOI 10.1016/j.agee.2023.108443
   MITCHELL AR, 1995, COMMUN SOIL SCI PLAN, V26, P2655, DOI 10.1080/00103629509369475
   Morrison J., 2005, Experimental Agriculture, V42, P254
   Muhandiram NPK, 2020, FOOD ENERGY SECUR, V9, DOI 10.1002/fes3.227
   MYTTON LR, 1993, GRASS FORAGE SCI, V48, P84, DOI 10.1111/j.1365-2494.1993.tb01840.x
   O'Connell E, 2007, HYDROL EARTH SYST SC, V11, P96, DOI 10.5194/hess-11-96-2007
   O'Mara FP, 2012, ANN BOT-LONDON, V110, P1263, DOI 10.1093/aob/mcs209
   PARKER ER, 1945, SOIL SCI, V60, P353, DOI 10.1097/00010694-194511000-00002
   Peñuela A, 2016, EARTH SURF PROC LAND, V41, P1595, DOI 10.1002/esp.3938
   Phukubye K, 2022, GEODERMA REG, V28, DOI 10.1016/j.geodrs.2021.e00479
   Porqueddu C, 2016, GRASS FORAGE SCI, V71, P1, DOI 10.1111/gfs.12212
   Prosdocimi M, 2016, EARTH-SCI REV, V161, P191, DOI 10.1016/j.earscirev.2016.08.006
   Sánchez-Rodríguez AR, 2019, SOIL BIOL BIOCHEM, V129, P153, DOI 10.1016/j.soilbio.2018.11.019
   Reid JB, 2015, ANN APPL BIOL, V167, P327, DOI 10.1111/aab.12228
   Robinson DA, 2022, SCI TOTAL ENVIRON, V852, DOI 10.1016/j.scitotenv.2022.158506
   Robinson M, 2013, T I BRIT GEOGR, V38, P451, DOI 10.1111/j.1475-5661.2012.00534.x
   SCULLION J, 1988, AGR ECOSYST ENVIRON, V20, P289, DOI 10.1016/0167-8809(88)90165-X
   Self-Davis ML, 2003, J SOIL WATER CONSERV, V58, P349
   Sherlock E., 2018, Key to the Earthworms of the UK and Ireland, V2nd
   Shi XQ, 2021, GEODERMA, V403, DOI 10.1016/j.geoderma.2021.115363
   SHIPITALO MJ, 1988, SOIL BIOL BIOCHEM, V20, P233, DOI 10.1016/0038-0717(88)90042-9
   Shnel A., 2021, IGC P 1993 2023, V4
   Somasiri SC, 2015, SMALL RUMINANT RES, V127, P20, DOI 10.1016/j.smallrumres.2015.04.005
   Stolte J., 2015, Soil Threats in Europe. Status, Methods, Drivers and Effects on Ecosystem Services, A Review Report, Deliverable 2.1 of the RECARE Project, DOI DOI 10.2788/828742
   Taylor N.L., 1996, Current Plant Science and Biotechnology, V28, P228
   van de Logt R, 2023, EUR J SOIL BIOL, V119, DOI 10.1016/j.ejsobi.2023.103545
   van Eekeren N, 2009, APPL SOIL ECOL, V42, P254, DOI 10.1016/j.apsoil.2009.04.006
   Vanmaercke M, 2011, SCI TOTAL ENVIRON, V409, P1715, DOI 10.1016/j.scitotenv.2011.01.034
   Violle C, 2015, SCI TOTAL ENVIRON, V534, P43, DOI 10.1016/j.scitotenv.2015.03.141
   Wedderburn ME, 2010, NEW ZEAL J AGR RES, V53, P377, DOI 10.1080/00288233.2010.514927
   Weiler M, 2003, HYDROL PROCESS, V17, P477, DOI 10.1002/hyp.1136
   Zaller JG, 2021, ENVIRON SCI EUR, V33, DOI 10.1186/s12302-021-00492-0
   Zangerlé A, 2011, GEODERMA, V167-68, P303, DOI 10.1016/j.geoderma.2011.09.004
   Zhang MX, 2023, SCI TOTAL ENVIRON, V899, DOI 10.1016/j.scitotenv.2023.165675
   Zhang YH, 2018, CAN J SOIL SCI, V98, P604, DOI 10.1139/cjss-2018-0046
NR 77
TC 1
Z9 1
U1 7
U2 7
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 2024
VL 951
AR 175598
DI 10.1016/j.scitotenv.2024.175598
EA AUG 2024
PG 10
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA E6J9H
UT WOS:001304058500001
PM 39159691
OA hybrid
DA 2025-01-10
ER

PT J
AU Zha, FK
   Lu, LL
   Wang, R
   Zhang, SC
   Cao, SS
   Baqa, MF
   Li, QT
   Chen, F
AF Zha, Fukang
   Lu, Linlin
   Wang, Ran
   Zhang, Shuangcheng
   Cao, Shisong
   Baqa, Muhammad Fahad
   Li, Qingting
   Chen, Fang
TI Understanding fine-scale heat health risks and the role of green
   infrastructure based on remote sensing and socioeconomic data in the
   megacity of Beijing, China
SO ECOLOGICAL INDICATORS
LA English
DT Article
DE Heat Health Risk Index; Urban green space; SDG11.7; Nature -based
   solutions
ID EXTREME HEAT; VULNERABILITY INDEX; CLIMATE-CHANGE; ECOSYSTEM SERVICES;
   HOT WEATHER; URBAN; MORTALITY; IMPACT; DEATHS; EVENTS
AB The frequency and intensity of extreme heat events have been increasing due to the combined effects of global climate change and urbanization. Urban green infrastructure, including urban green and blue space, has been recognized as an effective measure to mitigate urban heat. However, the effects of green infrastructure on heat health risk were insufficiently addressed. To address this gap, we conducted a comprehensive assessment in the megacity of Beijing with a rapidly aging population. Various data sources were collected, including remote sensing images, meteorological data from weather stations, point of interest(POI) data, and social statistics. Following the risk triangle theory, the hazard, population exposure, and social vulnerability components of heat health risk were evaluated at the census tract level. The weights of vulnerability indicators were determined using Principal Component Analysis. Moran's I and Getis-Ord Gi* statistics were used to identify risk hotspot areas. To evaluate the effects of green infrastructure on heat health risk, a Green Infrastructure Index (GII) was created to quantitatively measure the abundance and accessibility of green infrastructure. The analysis, using a spatially-explicit Heat Health Risk Index (HHRI), indicated that the HHRI in the central urban area inhabited by high-income population groups is 2.66 times that of its suburban counterpart. The primary driving factors of heat health risk were identified as high population density and elevated temperatures. Census tracts with abundant green infrastructure exhibited a low likelihood of becoming high-risk areas, with a probability of less than 2%, while regions with limited green infrastructure had a 54.26% probability of becoming high-risk areas. This highlights the significance of expanding the coverage of green spaces and water areas to reduce heat health risk. The findings provide valuable insights for the development of risk mitigation measures enhancing urban thermal resilience through nature-based climate adaptation.
C1 [Zha, Fukang; Zhang, Shuangcheng] Changan Univ, Coll Geol Engn & Geomat, Xian, Peoples R China.
   [Zha, Fukang; Lu, Linlin] China Meteorol Adm, Key Lab Urban Meteorol, Beijing, Peoples R China.
   [Zha, Fukang; Lu, Linlin; Baqa, Muhammad Fahad; Chen, Fang] Int Res Ctr Big Data Sustainable Dev Goals, Beijing, Peoples R China.
   [Zha, Fukang; Lu, Linlin; Baqa, Muhammad Fahad; Chen, Fang] Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, Beijing, Peoples R China.
   [Wang, Ran] Nankai Univ, Coll Econ & Social Dev, Tianjin, Peoples R China.
   [Cao, Shisong] Beijing Univ Civil Engn & Architecture, Sch Geomat & Urban Spatial Informat, Beijing, Peoples R China.
   [Baqa, Muhammad Fahad] Univ Chinese Acad Sci, Beijing, Peoples R China.
   [Li, Qingting] Chinese Acad Sci, Aerosp Informat Res Inst, Airborne Remote Sensing Ctr, Beijing, Peoples R China.
C3 Chang'an University; China Meteorological Administration; Chinese
   Academy of Sciences; International Research Center of Big Data for
   Sustainable Development Goals; Chinese Academy of Sciences; Aerospace
   Information Research Institute, CAS; Nankai University; Beijing
   University of Civil Engineering & Architecture; Chinese Academy of
   Sciences; University of Chinese Academy of Sciences, CAS; Chinese
   Academy of Sciences; Aerospace Information Research Institute, CAS
RP Lu, LL; Chen, F (corresponding author), Int Res Ctr Big Data Sustainable Dev Goals, Beijing, Peoples R China.
EM lull@radi.ac.cn; chenfang@radi.ac.cn
RI Baqa, Muhammad/AAT-8212-2021; Zhang, Yulong/HLQ-2846-2023; Chen,
   Fang/AAU-7638-2020; Lu, Linlin/P-9200-2018
OI Chen, Fang/0000-0002-4410-7040; Lu, Linlin/0000-0003-1647-1950
FU Open research fund of the Key Laboratory of Urban Meteorology, China
   Meteorological Administration [LUM-2023-16]; National Natural Science
   Foundation of China [41901292, 42071321]; National Key Research &
   Development Program of China [2022YFC3800700]
FX We would like to thank the editors and the anonymous reviewers for their
   suggestions and comments. This work was supported by the Open research
   fund of the Key Laboratory of Urban Meteorology, China Meteorological
   Administration (LUM-2023-16) , the National Natural Science Foundation
   of China (41901292 and 42071321) , and the National Key Research &
   Development Program of China (2022YFC3800700) .
CR Anderson GB, 2011, ENVIRON HEALTH PERSP, V119, P210, DOI 10.1289/ehp.1002313
   Åström DO, 2011, MATURITAS, V69, P99, DOI 10.1016/j.maturitas.2011.03.008
   Bai L, 2016, ENVIRON HEALTH-GLOB, V15, DOI 10.1186/s12940-015-0081-0
   Ballester J, 2023, NAT MED, V29, P1857, DOI 10.1038/s41591-023-02419-z
   Bradford K, 2015, ENVIRON SCI TECHNOL, V49, P11303, DOI 10.1021/acs.est.5b03127
   Braga ALF, 2002, ENVIRON HEALTH PERSP, V110, P859, DOI 10.1289/ehp.02110859
   Cai Z, 2022, J ENVIRON MANAGE, V324, DOI 10.1016/j.jenvman.2022.116263
   Campbell S, 2018, HEALTH PLACE, V53, P210, DOI 10.1016/j.healthplace.2018.08.017
   Cao Q, 2018, ENVIRON INT, V112, P134, DOI 10.1016/j.envint.2017.12.027
   Chapman S, 2017, LANDSCAPE ECOL, V32, P1921, DOI 10.1007/s10980-017-0561-4
   Chen B, 2022, SUSTAIN CITIES SOC, V81, DOI 10.1016/j.scs.2022.103831
   Chen B, 2021, SCI TOTAL ENVIRON, V768, DOI 10.1016/j.scitotenv.2021.145052
   Chen HQ, 2022, SCI BULL, V67, P1340, DOI 10.1016/j.scib.2022.05.006
   Chen Q, 2018, INT J HEALTH GEOGR, V17, DOI 10.1186/s12942-018-0135-y
   Chen X, 2019, URBAN FOR URBAN GREE, V43, DOI 10.1016/j.ufug.2019.126368
   Cheng J, 2019, ENVIRON RES, V177, DOI 10.1016/j.envres.2019.108610
   Crichton D., 1999, Nat Disaster Manag, P102
   Depietri Y, 2018, NAT HAZARD EARTH SYS, V18, P3363, DOI 10.5194/nhess-18-3363-2018
   Diep L, 2022, NATURE, V606, P653, DOI 10.1038/d41586-022-01698-9
   Dong JQ, 2020, LANDSCAPE URBAN PLAN, V203, DOI 10.1016/j.landurbplan.2020.103907
   Dong WH, 2014, SUSTAINABILITY-BASEL, V6, P7334, DOI 10.3390/su6107334
   Ebi KL, 2021, LANCET, V398, P698, DOI 10.1016/S0140-6736(21)01208-3
   Eggermont H, 2015, GAIA, V24, P243, DOI 10.14512/gaia.24.4.9
   El-Zein A, 2015, ECOL INDIC, V48, P207, DOI 10.1016/j.ecolind.2014.08.012
   Escobedo FJ, 2019, URBAN FOR URBAN GREE, V37, P3, DOI 10.1016/j.ufug.2018.02.011
   Estoque RC, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-15218-8
   Fuhrmann CM, 2016, J COMMUN HEALTH, V41, P146, DOI 10.1007/s10900-015-0080-7
   Gasparrini A, 2017, LANCET PLANET HEALTH, V1, pE360, DOI 10.1016/S2542-5196(17)30156-0
   GETIS A, 1992, GEOGR ANAL, V24, P189, DOI 10.1111/j.1538-4632.1992.tb00261.x
   Gronlund CJ, 2015, ENVIRON RES, V136, P449, DOI 10.1016/j.envres.2014.08.042
   Guo X, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11202358
   Gupta AK, 2020, ECOL INDIC, V109, DOI 10.1016/j.ecolind.2019.105787
   Gupta AK, 2019, ECOL INDIC, V106, DOI 10.1016/j.ecolind.2019.105512
   Hajat S, 2010, J EPIDEMIOL COMMUN H, V64, P753, DOI 10.1136/jech.2009.087999
   Harlan SL, 2013, ENVIRON HEALTH PERSP, V121, P197, DOI 10.1289/ehp.1104625
   Ho HC, 2018, APPL GEOGR, V95, P61, DOI 10.1016/j.apgeog.2018.04.015
   Ho HC, 2015, INT J ENV RES PUB HE, V12, P16110, DOI 10.3390/ijerph121215046
   Hu KJ, 2019, SCI TOTAL ENVIRON, V647, P1044, DOI 10.1016/j.scitotenv.2018.08.095
   Hu KJ, 2017, ENVIRON SCI TECHNOL, V51, P1498, DOI 10.1021/acs.est.6b04355
   Hua J., 2021, Sustainable Cities and Society, P64
   Huang HJ, 2023, ECOL INDIC, V153, DOI 10.1016/j.ecolind.2023.110449
   Huang HC, 2021, URBAN FOR URBAN GREE, V62, DOI 10.1016/j.ufug.2021.127154
   Inostroza L, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0162464
   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
   Jaafari S, 2020, ENVIRON MONIT ASSESS, V192, DOI 10.1007/s10661-020-08377-0
   Jay O, 2021, LANCET, V398, P709, DOI 10.1016/S0140-6736(21)01209-5
   Jenerette GD, 2011, ECOL APPL, V21, P2637, DOI 10.1890/10-1493.1
   Johnson DP, 2012, APPL GEOGR, V35, P23, DOI 10.1016/j.apgeog.2012.04.006
   Kabisch N, 2016, ECOL INDIC, V70, P586, DOI 10.1016/j.ecolind.2016.02.029
   Kiarsi M, 2023, J THERM BIOL, V116, DOI 10.1016/j.jtherbio.2023.103588
   Li D, 2013, J APPL METEOROL CLIM, V52, P2051, DOI 10.1175/JAMC-D-13-02.1
   Li JJ, 2009, ECOL COMPLEX, V6, P413, DOI 10.1016/j.ecocom.2009.02.002
   Lu LL, 2023, SUSTAIN CITIES SOC, V92, DOI 10.1016/j.scs.2023.104505
   Lu LL, 2019, SCI TOTAL ENVIRON, V684, P567, DOI 10.1016/j.scitotenv.2019.05.344
   Marando F, 2019, ECOL MODEL, V392, P92, DOI 10.1016/j.ecolmodel.2018.11.011
   Mora C, 2017, NAT CLIM CHANGE, V7, P501, DOI [10.1038/nclimate3322, 10.1038/NCLIMATE3322]
   Mushore TD, 2018, J SPAT SCI, V63, P173, DOI 10.1080/14498596.2017.1290558
   Navarro-Estupiñan J, 2020, URBAN CLIM, V31, DOI 10.1016/j.uclim.2019.100576
   Nayak SG, 2018, PUBLIC HEALTH, V161, P127, DOI 10.1016/j.puhe.2017.09.006
   Nieuwenhuijsen MJ, 2021, ANNU REV PUBL HEALTH, V42, P317, DOI 10.1146/annurev-publhealth-090419-102511
   Perkins-Kirkpatrick SE, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-16970-7
   Reid CE, 2012, ENVIRON HEALTH PERSP, V120, P715, DOI 10.1289/ehp.1103766
   Reid CE, 2009, ENVIRON HEALTH PERSP, V117, P1730, DOI 10.1289/ehp.0900683
   Seneviratne S. I., 2021, Climate Change 2021-The Physical Science Basis, P1513, DOI [DOI 10.1017/9781009157896.013, 10.1017/9781009157896.013]
   Shi Y, 2018, SCI TOTAL ENVIRON, V618, P891, DOI 10.1016/j.scitotenv.2017.08.252
   Shih W.-Y, 2022, Landsc. Urban Plan., V226
   Song JL, 2020, SCI TOTAL ENVIRON, V718, DOI 10.1016/j.scitotenv.2020.137226
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Su BB, 2023, J AM MED DIR ASSOC, V24, P206, DOI 10.1016/j.jamda.2022.10.002
   Su XK, 2022, INT J DISAST RISK SC, V13, P987, DOI 10.1007/s13753-022-00449-8
   Su YX, 2020, AGR FOREST METEOROL, V280, DOI 10.1016/j.agrformet.2019.107765
   Thompson R, 2018, PUBLIC HEALTH, V161, P171, DOI 10.1016/j.puhe.2018.06.008
   Tieskens KF, 2022, SCI TOTAL ENVIRON, V845, DOI 10.1016/j.scitotenv.2022.157283
   Tomlinson CJ, 2011, INT J HEALTH GEOGR, V10, DOI 10.1186/1476-072X-10-42
   United Nations, 2015, Transforming our world: The 2030 Agenda for Sustainable Development
   United Nations Department of Economic and Social Affairs Population Division, 2019, World Population Prospects 2019: Highlights; 2019
   Venter ZS, 2020, SCI TOTAL ENVIRON, V709, DOI 10.1016/j.scitotenv.2019.136193
   Voogt JA, 2003, REMOTE SENS ENVIRON, V86, P370, DOI 10.1016/S0034-4257(03)00079-8
   Wang D, 2017, BMJ OPEN, V7, DOI 10.1136/bmjopen-2016-015794
   Weber S, 2015, APPL GEOGR, V63, P231, DOI 10.1016/j.apgeog.2015.07.006
   Wong NH, 2021, NAT REV EARTH ENV, V2, P166, DOI 10.1038/s43017-020-00129-5
   Wu SB, 2023, LANDSCAPE URBAN PLAN, V233, DOI 10.1016/j.landurbplan.2023.104701
   Xiao Y, 2023, SUSTAIN CITIES SOC, V98, DOI 10.1016/j.scs.2023.104817
   [谢盼 Xie Pan], 2015, [地理科学进展, Progress in Geography], V34, P165
   Yan CH, 2020, BUILD ENVIRON, V169, DOI 10.1016/j.buildenv.2019.106541
   Yin ZT, 2023, ECOL INDIC, V154, DOI 10.1016/j.ecolind.2023.110765
   Yu JS, 2021, ENVIRON HEALTH-GLOB, V20, DOI 10.1186/s12940-021-00708-z
   Yu ZW, 2019, SCI TOTAL ENVIRON, V674, P242, DOI 10.1016/j.scitotenv.2019.04.088
   Zepp H, 2020, URBAN FOR URBAN GREE, V49, DOI 10.1016/j.ufug.2020.126603
   Zhang W, 2019, SCI TOTAL ENVIRON, V663, P852, DOI 10.1016/j.scitotenv.2019.01.240
   Zhang YQ, 2017, ENVIRON POLLUT, V225, P700, DOI 10.1016/j.envpol.2017.02.066
NR 91
TC 11
Z9 11
U1 53
U2 75
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 1470-160X
EI 1872-7034
J9 ECOL INDIC
JI Ecol. Indic.
PD MAR
PY 2024
VL 160
AR 111847
DI 10.1016/j.ecolind.2024.111847
EA MAR 2024
PG 15
WC Biodiversity Conservation; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA OB3V5
UT WOS:001204770200001
OA gold
DA 2025-01-10
ER

PT J
AU Song, XY
   Lei, XP
   Ma, R
   Hou, JZ
   Liu, WB
AF Song, Xiaoyan
   Lei, Xiaoping
   Ma, Rui
   Hou, Jingzhi
   Liu, Wenbin
TI Spatiotemporal variation and multivariate controls of short-cycle
   drought-flood abrupt alteration: A case in the Qinling-Daba Mountains of
   China
SO INTERNATIONAL JOURNAL OF CLIMATOLOGY
LA English
DT Article
DE multiple wavelet coherence; Qinling-Daba Mountains; R-SDFAI; short-cycle
   drought-flood abrupt alteration; wavelet transform coherence
ID MULTIPLE-WAVELET COHERENCE; STREAMFLOW VARIABILITY; ALTERNATION; BASIN;
   ENSO
AB A comprehensive understanding of the patterns of drought and flood alternation in adjacent months is essential for enabling climate adaptation and mitigation strategies. However, there is a paucity of knowledge regarding short-cycle drought-flood abrupt alteration (s-DFAA) and its responses to multiple environmental factors at various timescales. This is because of the inadequate formula construction of the existing short-cycle drought-flood abrupt alteration index (SDFAI), such as the inability to introduce drought standards. To accurately capture the s-DFAA's characteristics in the Qinling-Daba Mountains (Qinba Mountains), we proposed a revised SDFAI (R-SDFAI), which incorporates the standardized precipitation index (SPI) and allows for the customization of drought standards. Next, we used wavelet transform coherence and multiple wavelet coherence to investigate the timescale relationships between s-DFAA events and their influence factors such as relative humidity, sunshine duration, temperature, evaporation, Arctic Oscillation (AO), Nino3.4 SSTA Index (Nino3.4), Total Sunspot Number Index (TSNI) and Pacific Decadal Oscillation Index (PDO). Our results showed that the R-SDFAI outperformed traditional SDFAI in capturing s-DFAA events and characterizing their severity. Furthermore, s-DFAA events identified by R-SDFAI at different levels (i.e., mild, moderate, severe, extreme and total) displayed insignificant downward trends. Spatially, there were more s-DFAA events in the east than the west. Wavelet analysis indicated that meteorological factors and teleconnections significantly impact s-DFAA events at large timescales, though their driving mechanisms differed substantially. Among meteorological factors, single relative humidity and its related combinations exhibited relatively high percent area of significant coherence (PASC, ranging from 17.47 to 29.46). Each teleconnection and its combinations are irreplaceable, with PASC values always increasing with the number of variables. The PASC ranges from 8.3 to 10.29 for one factor, 12.38 to 18.65 for two factors, 24.02 to 30.58 for three factors and 40.88 for four factors, respectively.
C1 [Song, Xiaoyan; Lei, Xiaoping; Ma, Rui; Hou, Jingzhi] Northwest A&F Univ, Key Lab Agr Soil & Water Engn Arid & Semiarid Area, Minist Educ, Yangling, Peoples R China.
   [Liu, Wenbin] Inst Geog Sci & Nat Resources Res, Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Beijing, Peoples R China.
   [Song, Xiaoyan] Northwest A&F Univ, Coll Water Resource & Architectural Engn, Weihui Rd 23, Yangling 712100, Peoples R China.
   [Liu, Wenbin] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, 11A Datun Rd, Beijing 100101, Peoples R China.
C3 Northwest A&F University - China; Chinese Academy of Sciences; Institute
   of Geographic Sciences & Natural Resources Research, CAS; Northwest A&F
   University - China; Chinese Academy of Sciences; Institute of Geographic
   Sciences & Natural Resources Research, CAS
RP Song, XY (corresponding author), Northwest A&F Univ, Coll Water Resource & Architectural Engn, Weihui Rd 23, Yangling 712100, Peoples R China.; Liu, WB (corresponding author), Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, 11A Datun Rd, Beijing 100101, Peoples R China.
EM xiaoyansong@nwsuaf.edu.cn; liuwb@igsnrr.ac.cn
RI ma, rui/JGE-4890-2023; Lei, Xiaoping/AAW-8870-2021; Liu,
   Wenbin/AAB-2665-2021
FU Second Tibetan Plateau Scientific Expedition and Research Program
   [2019QZKK0406]; National Key Research and Development Program of China
   [2019YFA0606903]; National Natural Science Foundation of China
   [42022005]; National Science and Technology Basic Resource Investigation
   Program [2017FY100904]; Program for the "Kezhen-Bingwei" Youth Talents
   [2020RC004]
FX Second Tibetan Plateau Scientific Expedition and Research Program,
   Grant/Award Number: 2019QZKK0406; National Key Research and Development
   Program of China, Grant/Award Number: 2019YFA0606903; National Natural
   Science Foundation of China, Grant/Award Number: 42022005; National
   Science and Technology Basic Resource Investigation Program, Grant/Award
   Number: 2017FY100904; Program for the "Kezhen-Bingwei" Youth Talents,
   Grant/Award Number: 2020RC004
CR [毕吴瑕 Bi Wuxia], 2021, [水资源保护, Water Resources Protection], V37, P40
   Bi WX, 2019, INT J ENV RES PUB HE, V16, DOI 10.3390/ijerph16050691
   Case JL, 2016, RESULTS PHYS, V6, P1183, DOI 10.1016/j.rinp.2016.11.012
   Das D, 2018, ECON LETT, V164, P100, DOI 10.1016/j.econlet.2018.01.013
   Feng Y, 2023, ATMOS RES, V283, DOI 10.1016/j.atmosres.2022.106553
   Feng Y, 2022, INT J CLIMATOL, V42, P2935, DOI 10.1002/joc.7399
   Feng Y, 2021, INT J CLIMATOL, V41, pE1085, DOI 10.1002/joc.6755
   Grinsted A, 2004, NONLINEAR PROC GEOPH, V11, P561, DOI 10.5194/npg-11-561-2004
   [何慧 He Hui], 2016, [地理学报, Acta Geographica Sinica], V71, P130
   Hu W, 2016, HYDROL EARTH SYST SC, V20, P3183, DOI 10.5194/hess-20-3183-2016
   Hu YiHong Hu YiHong, 2017, Transactions of the Chinese Society of Agricultural Engineering, V33, P107
   Huang QZ, 2017, GLOBAL PLANET CHANGE, V155, P1, DOI 10.1016/j.gloplacha.2017.05.010
   [吉中会 Ji Zhonghui], 2015, [长江流域资源与环境, Resources and Environment in the Yangtze Basin], V24, P1793
   Liu WB, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/ac188f
   [陆福志 Lu Fuzhi], 2019, [地理学报, Acta Geographica Sinica], V74, P875
   Mann HB, 1945, ECONOMETRICA, V13, P245, DOI 10.2307/1907187
   Nalley D, 2019, J HYDROL, V574, P288, DOI 10.1016/j.jhydrol.2019.04.024
   Nalley D, 2016, J HYDROL, V536, P426, DOI 10.1016/j.jhydrol.2016.02.049
   [闪丽洁 Shan Lijie], 2018, [地理学报, Acta Geographica Sinica], V73, P25
   [闪丽洁 Shan Lijie], 2015, [长江流域资源与环境, Resources and Environment in the Yangtze Basin], V24, P2100
   Shi WZ, 2021, J HYDROL, V597, DOI 10.1016/j.jhydrol.2021.126179
   Su L, 2019, J GEOPHYS RES-ATMOS, V124, P4932, DOI 10.1029/2018JD029842
   Sun P, 2017, NAT HAZARDS, V89, P963, DOI 10.1007/s11069-017-3002-4
   Sutanto SJ, 2020, ENVIRON INT, V134, DOI 10.1016/j.envint.2019.105276
   Tian HW, 2022, GEODERMA, V409, DOI 10.1016/j.geoderma.2021.115600
   Tian R, 2016, GEOMAT NAT HAZ RISK, V7, P287, DOI 10.1080/19475705.2014.897654
   Torrence C, 1998, B AM METEOROL SOC, V79, P61, DOI 10.1175/1520-0477(1998)079<0061:APGTWA>2.0.CO;2
   Wang LY, 2021, ATMOS RES, V252, DOI 10.1016/j.atmosres.2020.105429
   Wang Rong, 2020, Hupo Kexue, V32, P207, DOI 10.18307/2020.0120
   Wu ZW, 2006, CHINESE SCI BULL, V51, P2027, DOI 10.1007/s11434-006-2060-x
   Xiong QQ, 2019, PHYSIOL PLANTARUM, V167, P564, DOI 10.1111/ppl.12901
   [杨家伟 Yang Jiawei], 2019, [地理学报, Acta Geographica Sinica], V74, P2358
   Yang P, 2022, ATMOS RES, V270, DOI 10.1016/j.atmosres.2022.106087
   [杨星星 Yang Xingxing], 2019, [自然灾害学报, Journal of Natural Disasters], V28, P192
   [张百平 Zhang Baiping], 2019, [地理科学进展, Progress in Geography], V38, P305
   Zhang Q, 2016, THEOR APPL CLIMATOL, V126, P631, DOI 10.1007/s00704-015-1593-9
   Zhang S.Y., 2022, ACTA SCI CIRCUMST, V42, P1, DOI [10.13671/j.hjkxxb.2021.0474, DOI 10.13671/J.HJKXXB.2021.0474]
   Zhang Shuifeng, 2012, Hupo Kexue, V24, P679
   Zhang Yun-fan, 2021, Engineering Journal of Wuhan University, V54, P887, DOI 10.14188/j.1671-8844.2021-10-002
   Zhu HF, 2021, CATENA, V207, DOI 10.1016/j.catena.2021.105695
   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 42
TC 0
Z9 0
U1 28
U2 84
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 2023
VL 43
IS 10
BP 4756
EP 4769
DI 10.1002/joc.8115
EA JUN 2023
PG 14
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA N8OG1
UT WOS:001003254800001
DA 2025-01-10
ER

PT J
AU Khairallah, L
   Chedid, M
   Jaber, L
   Martiniello, G
   Hamadeh, SK
AF Khairallah, Lamisse
   Chedid, Mabelle
   Jaber, Lina
   Martiniello, Giuliano
   Hamadeh, Shady K.
TI Traditional dairy goat value chain in Lebanon: an uneven distribution of
   values
SO JOURNAL OF AGRIBUSINESS IN DEVELOPING AND EMERGING ECONOMIES
LA English
DT Article
DE Small ruminants; Goat dairy value chain; Small-scale farmers; Goat dairy
   processing; Traditional dairy goat products; Q12
ID QUALITY; SYSTEMS; BEKAA; SHEEP; MILK
AB Purpose Small-scale goat farming and dairy goat productions are significant constituents in the livelihoods of marginal Lebanese rural communities. Reviving and supporting that sector is instrumental in creating value for rural communities to build sustainable livelihoods and safeguard climate-adapted value chains (VCs). The paper aims to describe the dairy goat VC in the Shouf and West Bekaa (WB) areas of Lebanon, which are traditionally popular for caprine production. Design/methodology/approach A socio-economic approach was employed to determine the perceived challenges, opportunities and context of goat farmers and dairy processor in the Shouf and WB casas as case studies, using the Heifer International's toolkit for goat value chains. Questionnaires were developed for the five actors of the VC: farmer, milk collector, processor, retailer and consumer. The data were analyzed quantitatively, using simple statistical analysis, and qualitatively through observation, gathering, coding and thematically organizing the responses. Findings In the Shouf, the chain is shorter, consisting of a farmer, processor and consumer, while in the WB the VC includes a milk collector and larger dairy factories. The value is unequally and unfairly distributed among the actors putting the small-scale farmers and processors in subordinate positions. In terms of enabling environment, the role of the state, authorities and organizations remains minimal in supporting the sector. The challenges facing this sector are economic, regulatory, operational, social and hygienic as perceived by the participants. Research limitations/implications The economic, political and social instability of the country hinders the performance of the sector. Originality/value Limited research is available on the small ruminants' VC in Lebanon, addressing the socio-economic status of goat farmers and opportunities available in the sector. On the other hand, the demand for traditional dairy products is increasing amid rising concerns related to intensive livestock systems and negative association of livestock systems with climate change. Accordingly, basic assessment and research on the existing small ruminant dairy chains is important as a first step for the sustainable development of the sector.
C1 [Khairallah, Lamisse; Hamadeh, Shady K.] Amer Univ Beirut, Environm & Sustainable Dev Unit, Fac Agr & Food Sci, Beirut, Lebanon.
   [Chedid, Mabelle] Livestock Sustainabil, Montpellier, France.
   [Jaber, Lina] Amer Univ Beirut, Dept Agr, Fac Agr & Food Sci, Beirut, Lebanon.
   [Martiniello, Giuliano] Univ Int Rabat, Coll Law & Polit & Social Sci, Sale, Morocco.
   [Martiniello, Giuliano] Amer Univ Beirut, Fac Food & Agr Sci, Beirut, Lebanon.
C3 American University of Beirut; American University of Beirut; Universite
   Internationale de Rabat; American University of Beirut
RP Chedid, M (corresponding author), Livestock Sustainabil, Montpellier, France.
EM lamisse.kh@gmail.com; mabelle.chedid@gmail.com; lj01@aub.edu.lb;
   giuliano.martiniello@uir.ac.ma; shamadeh@aub.edu.lb
OI Khairallah, Lamisse/0000-0002-5017-2674; Hamadeh,
   Shady/0000-0002-5977-9878
FU American University of Beirut Research Board [103601]
FX The authors are thankful to the American University of Beirut Research
   Board (award number: 103601) for funding this project.
CR Abdul-Rahaman A, 2020, J AGRIBUS DEV EMERG, V10, P511, DOI 10.1108/JADEE-07-2019-0095
   Balaa R. El, 2008, SECURITY, P6
   Barua P., 2021, Mod. Supply Chain Res. Appl, V3, P98, DOI [10.1108/MSCRA-07-2020-0020, DOI 10.1108/MSCRA-07-2020-0020]
   Boyazoglu J, 2001, SMALL RUMINANT RES, V40, P1, DOI 10.1016/S0921-4488(00)00203-0
   Chedid M., 2018, Journal of Food Research, V7, P16, DOI 10.5539/jfr.v7n5p16
   Chedid M, 2018, SMALL RUMINANT RES, V167, P16, DOI 10.1016/j.smallrumres.2018.07.025
   Darwich S., 2017, ETUDE AGR FAMILIALE
   Devaux A, 2018, J AGRIBUS DEV EMERG, V8, P99, DOI 10.1108/JADEE-06-2017-0065
   Dick C.I., 2008, 8 EUR IFSA S
   Donovan J, 2015, J AGRIBUS DEV EMERG, V5, P2, DOI 10.1108/JADEE-07-2013-0025
   Dubeuf JP, 2011, SMALL RUMINANT RES, V98, P3, DOI 10.1016/j.smallrumres.2011.03.008
   Dubeuf JP, 2004, SMALL RUMINANT RES, V51, P165, DOI 10.1016/j.smallrumres.2003.08.007
   ESDU, 2020, OV LOC AGR FOOD HER
   Feenstra G. W., 1997, American Journal of Alternative Agriculture, V12, P28, DOI 10.1017/S0889189300007165
   Ghattas H, 2013, J NUTR, V143, P1666, DOI 10.3945/jn.113.176388
   Haddad E., 2014, CIHEAM IAMM ANIMA
   Hamade K., 2020, Lebanon's Food Insecurity and the Path toward Agricultural Reform
   Hamadeh S., 2006, RES DEV DRY ARAB REG
   Hamadeh SK, 1996, SMALL RUMINANT RES, V21, P173, DOI 10.1016/0921-4488(95)00831-4
   Hamadeh SK, 2001, SMALL RUMINANT RES, V40, P41, DOI 10.1016/S0921-4488(00)00210-8
   Heifer International, 2014, SCAL UP SUCC PRACT S
   Hilali M, 2011, SMALL RUMINANT RES, V101, P92, DOI 10.1016/j.smallrumres.2011.09.029
   Hosri C., 2004, MEDITERRANEAN OPTI A
   Hosri C., 2016, MEDITERRANEAN OPTI A
   IDAL, 2017, OV CHOUF DISTR
   ILO, 2011, COOPERATIVES SUSTAIN
   ILO I, 2018, COOP SECT LEB ROL FU
   Kaplinsky R., 2000, A handbook for value chain research, V113
   Kassie GT, 2019, J AGRIBUS DEV EMERG, V9, P220, DOI 10.1108/JADEE-02-2018-0024
   Matveeva A, 2017, Impacts of Climate Change on Farming Systems and Livelihoods in the Near East and North-Africa Regional Initiative on Small-Scale Family Farming for the Near East and North Africa
   McCullough F. S. W., 2003, British Food Journal, V105, P239, DOI 10.1108/00070700310477031
   McMichael P, 2013, THIRD WORLD Q, V34, P671, DOI 10.1080/01436597.2013.786290
   Morand-Fehr P, 2004, SMALL RUMINANT RES, V51, P175, DOI 10.1016/j.smallrumres.2003.08.013
   Ortega DL, 2017, J AGRIBUS DEV EMERG, V7, P21, DOI 10.1108/JADEE-12-2014-0045
   Salameh C., 2015, SEM FAT CIHEAM SUB N
   Semaan Hajj E., 2011, LEBAN SCI J, V12, P21
   Serhan M., 2017, GOAT SCI
   Tabet E, 2016, SMALL RUMINANT RES, V140, P13, DOI 10.1016/j.smallrumres.2016.05.011
   van der Ploeg J.D., 2008, The New Peasantries: Struggle for autonomy and sustainability in an era of empire and glogalization
   van der Ploeg JD, 2012, J PEASANT STUD, V39, P133, DOI 10.1080/03066150.2011.652619
   Zurayk R., 2008, AKKAR AMEL LEBANONS, P90
NR 41
TC 0
Z9 0
U1 2
U2 8
PU EMERALD GROUP PUBLISHING LTD
PI BINGLEY
PA HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND
SN 2044-0839
EI 2044-0847
J9 J AGRIBUS DEV EMERG
JI J. Agribus. Dev. Emerg. Econ.
PD JUL 7
PY 2023
VL 13
IS 4
BP 555
EP 569
DI 10.1108/JADEE-06-2021-0144
EA FEB 2022
PG 15
WC Agricultural Economics & Policy; Economics
WE Emerging Sources Citation Index (ESCI)
SC Agriculture; Business & Economics
GA L4LK3
UT WOS:000762137600001
DA 2025-01-10
ER

PT J
AU Hlásny, T
   Zimová, S
   Bentz, B
AF Hlasny, T.
   Zimova, S.
   Bentz, B.
TI Scientific response to intensifying bark beetle outbreaks in Europe and
   North America
SO FOREST ECOLOGY AND MANAGEMENT
LA English
DT Article
DE European spruce bark beetle; Mountain pine beetle; Climate change;
   Forest management; Forest policy; Systematic literature review
ID MOUNTAIN PINE-BEETLE; ADAPTING FOREST MANAGEMENT; NORWAY SPRUCE FORESTS;
   CLIMATE-CHANGE; NATURAL DISTURBANCES; IPS-TYPOGRAPHUS; TREE MORTALITY;
   BIOTIC DISTURBANCES; ECOSYSTEM SERVICES; BRITISH-COLUMBIA
AB Tree-killing bark beetles are globally the most destructive forest pests and their impacts have increased in recent decades. Such an increase has been consistently reported from Europe and North America, and it is, with high confidence, driven by climate change. We investigated how the scientific community in both continents responded to this situation by conducting a comprehensive search of the Scopus database from 1970 to 2020. Studies that investigated interactions between climate change and two prominent bark beetles in Europe and North America, the European spruce bark beetle Ips typographus (ESBB) and the mountain pine beetle Dendroctonus ponderosae (MPB), were identified. We used several hierarchical search criteria, starting from general aspects of pest - climate change interactions, to studies with clear implications for management and policies.
   We found that authors investigating the two bark beetle species mentioned climate change in publications beginning in 1998, and have constituted 8.9 and 13.8 % of all studies on ESBB (N = 987) and MPB (N = 1479) recorded in Scopus. However, only part of these studies addressed climate change as a fundamental or integral part of their research design (59.1 % in ESBB and 38.7 % in MPB). We identified 30 studies on ESBB and 50 studies on MPB which informed efforts towards improving bark beetle management strategies to address climate change-affected ecosystem dynamics. Publications on both insects consistently highlighted the importance of vegetation management aiming to reduce the risk and severity of outbreaks and prevent large-scale population expansion. Only a minor portion of studies placed their findings into the context of relevant policies and legislation, and this connection was particularly lacking in studies on MPB.
   We conclude that research on bark beetle management under climate change has received inadequate attention and it lags behind observed and foreseen global-scale impacts. We suggest that focused and applied research with clear management implications is needed to develop new climate-adapted and evidence-based management strategies.
C1 [Hlasny, T.; Zimova, S.] Czech Univ Life Sci Prague, Fac Forestry & Wood Sci, Kamycka 129, Prague 16521 6, Czech Republic.
   [Bentz, B.] US Forest Serv, USDA, Rocky Mt Res Stn, 860 North 1200 East, Logan, UT 84321 USA.
C3 Czech University of Life Sciences Prague; United States Department of
   Agriculture (USDA); United States Forest Service
RP Hlásny, T (corresponding author), Czech Univ Life Sci Prague, Fac Forestry & Wood Sci, Kamycka 129, Prague 16521 6, Czech Republic.
EM hlasny@fld.czu.cz
RI Zimová, Soňa/AAB-3375-2021; Hlásny, Tomáš/AAE-5476-2019
OI Senfeldova, Sona/0009-0002-3690-3909
FU OP RDE [CZ.02.1.01/0.0/0.0/16_019/0000803]; USDA Forest Service Rocky
   Mountain Research Station
FX This study was supported by the grant "EVA4.0", No.
   CZ.02.1.01/0.0/0.0/16_019/0000803 financed by OP RDE, and the USDA
   Forest Service Rocky Mountain Research Station.
CR Abrams J, 2018, ENVIRON SCI POLICY, V90, P102, DOI 10.1016/j.envsci.2018.09.019
   Allen CD, 2015, ECOSPHERE, V6, DOI 10.1890/ES15-00203.1
   Anderegg WRL, 2015, NEW PHYTOL, V208, P674, DOI 10.1111/nph.13477
   [Anonymous], 2020, FOR CHANG AD TOOLS
   [Anonymous], 2021, MOUNTAIN PINE BEETLE
   [Anonymous], 2017, USDA FOREST SERVICE
   Arora VK, 2016, GEOPHYS RES LETT, V43, P2590, DOI 10.1002/2015GL067532
   Audley JP, 2020, FOREST ECOL MANAG, V475, DOI 10.1016/j.foreco.2020.118403
   Augustynczik ALD, 2021, LANDSCAPE URBAN PLAN, V209, DOI 10.1016/j.landurbplan.2020.104035
   Bednarek AT, 2018, SUSTAIN SCI, V13, P1175, DOI 10.1007/s11625-018-0550-9
   Bentz B., 2005, BARK BEETL S
   Bentz BJ, 2019, FRONT FOR GLOB CHANG, V2, DOI 10.3389/ffgc.2019.00001
   Bentz BJ, 2010, BIOSCIENCE, V60, P602, DOI 10.1525/bio.2010.60.8.6
   Biedermann PHW, 2019, TRENDS ECOL EVOL, V34, P914, DOI 10.1016/j.tree.2019.06.002
   Björkman C, 2015, CABI CLIM CHANGE SER, V7, P248, DOI 10.1079/9781780643786.0248
   Boucher D, 2018, ECOL APPL, V28, P1245, DOI 10.1002/eap.1724
   Bramer WM, 2017, SYST REV-LONDON, V6, DOI 10.1186/s13643-017-0644-y
   Carnicer J, 2011, P NATL ACAD SCI USA, V108, P1474, DOI 10.1073/pnas.1010070108
   Christiansen E., 1988, P479
   Cohen J, 2016, ENVIRON RESOUR ECON, V63, P613, DOI 10.1007/s10640-014-9856-y
   Cole W.E., 1980, GEN TECHNICAL REPORT
   Collins BJ, 2012, FOREST ECOL MANAG, V284, P260, DOI 10.1016/j.foreco.2012.07.027
   Cooke BJ, 2017, FOREST ECOL MANAG, V396, P11, DOI 10.1016/j.foreco.2017.04.008
   Cottrell S, 2020, SUSTAIN SCI, V15, P555, DOI 10.1007/s11625-019-00736-2
   Cvitanovic C, 2015, MAR POLICY, V52, P38, DOI 10.1016/j.marpol.2014.10.026
   Dhar A, 2016, CAN J FOREST RES, V46, P987, DOI 10.1139/cjfr-2016-0137
   Di Gregorio M, 2017, ENVIRON SCI POLICY, V67, P35, DOI 10.1016/j.envsci.2016.11.004
   Dobor L, 2020, ECOL EVOL, V10, P12233, DOI 10.1002/ece3.6854
   Dobor L, 2020, J ENVIRON MANAGE, V254, DOI 10.1016/j.jenvman.2019.109792
   Dobor L, 2020, J APPL ECOL, V57, P67, DOI 10.1111/1365-2664.13518
   Dowle EJ, 2017, MOL ECOL, V26, P6071, DOI 10.1111/mec.14342
   Dymond CC, 2014, CAN J FOREST RES, V44, P1196, DOI 10.1139/cjfr-2014-0146
   Embrey S, 2012, AM J PUBLIC HEALTH, V102, P818, DOI 10.2105/AJPH.2011.300520
   European Forest Institute Forest Europe Liaison Unit Bratislava, 2019, CREAT EUR FOR RISK F
   Faccoli M., 2008, DAMAGE THRESHOLDS, V15, P44, DOI [10.1111/j.1439-0418.2004.00848.307, DOI 10.1111/J.1439-0418.2004.00848.307]
   FAO, 2020, COUNTR
   Fettig CJ, 2019, FOREST ECOL MANAG, V432, P164, DOI 10.1016/j.foreco.2018.09.006
   Fettig CJ, 2014, FOREST SCI, V60, P450, DOI 10.5849/forsci.13-032
   Fettig CJ, 2014, FORESTS, V5, P822, DOI 10.3390/f5040822
   Forrest JRK, 2016, CURR OPIN INSECT SCI, V17, P49, DOI 10.1016/j.cois.2016.07.002
   Galko J, 2016, CENT EURO FOR J, V62, P207, DOI 10.1515/forj-2016-0027
   Garnas JR, 2018, CURR OPIN INSECT SCI, V29, P93, DOI 10.1016/j.cois.2018.07.013
   Gillette NE, 2014, FOREST SCI, V60, P527, DOI 10.5849/forsci.13-040
   Gregoire J.C., 2015, Bark beetles biology and ecology of native and invasive species, P585, DOI [DOI 10.1016/B978-0-12-417156-5.00015-0, 10.1016/B978-0-12-417156-5.00015-0]
   Grimes DR, 2018, ROY SOC OPEN SCI, V5, DOI 10.1098/rsos.171511
   Grodzki W, 2004, ENVIRON POLLUT, V130, P73, DOI 10.1016/j.envpol.2003.10.022
   Guston DH, 2001, SCI TECHNOL HUM VAL, V26, P399, DOI 10.1177/016224390102600401
   Halofsky J.E., 2018, RMRSGTR374 USDA FOR
   Halofsky JE, 2018, FOREST ECOL MANAG, V421, P84, DOI 10.1016/j.foreco.2018.02.037
   Halofsky JE, 2016, ATMOSPHERE-BASEL, V7, DOI 10.3390/atmos7030046
   Hessburg PF, 2019, FRONT ECOL EVOL, V7, DOI 10.3389/fevo.2019.00239
   Hl  asny T., 2019, SCI POLICY
   Hlásny T, 2021, FOREST ECOL MANAG, V490, DOI 10.1016/j.foreco.2021.119075
   Hlasny T., CURR FORESTRY REP
   Hlásny T, 2013, ANN FOREST SCI, V70, P481, DOI 10.1007/s13595-013-0279-7
   Holusa J, 2017, FOREST ECOL MANAG, V404, P165, DOI 10.1016/j.foreco.2017.08.019
   Honkaniemi J, 2020, LANDSCAPE ECOL, V35, P591, DOI 10.1007/s10980-019-00964-y
   Hood PR, 2017, FOREST ECOL MANAG, V390, P80, DOI 10.1016/j.foreco.2017.01.003
   Jactel H, 2009, ANN FOREST SCI, V66, DOI 10.1051/forest/2009054
   Jakoby O, 2019, GLOBAL CHANGE BIOL, V25, P4048, DOI 10.1111/gcb.14766
   Jandl R, 2019, ANN FOREST SCI, V76, DOI 10.1007/s13595-019-0827-x
   Janes JK, 2014, MOL BIOL EVOL, V31, P1803, DOI 10.1093/molbev/msu135
   Kautz M, 2017, GLOBAL ECOL BIOGEOGR, V26, P533, DOI 10.1111/geb.12558
   Keskitalo ECH, 2016, FOREST POLICY ECON, V65, P59, DOI 10.1016/j.forpol.2015.10.011
   kland B., 2015, EURASIAN SPRUCE BARK
   Knapp EE, 2021, FOREST ECOL MANAG, V479, DOI 10.1016/j.foreco.2020.118595
   Kolb TE, 2016, FOREST ECOL MANAG, V380, P321, DOI 10.1016/j.foreco.2016.04.051
   Leverkus AB, 2021, FOREST ECOL MANAG, V481, DOI 10.1016/j.foreco.2020.118721
   Leverkus AB, 2020, FRONT ECOL ENVIRON, V18, P391, DOI 10.1002/fee.2219
   Lieffers VJ, 2020, CAN J FOREST RES, V50, P855, DOI 10.1139/cjfr-2019-0422
   Logan JA, 1999, ENVIRON ENTOMOL, V28, P924, DOI 10.1093/ee/28.6.924
   Logan JA, 2010, ECOL APPL, V20, P895, DOI 10.1890/09-0655.1
   Marini L, 2017, ECOGRAPHY, V40, P1426, DOI 10.1111/ecog.02769
   McCright AM, 2016, ENERGY RES SOC SCI, V21, P180, DOI 10.1016/j.erss.2016.08.003
   McDaniels T, 2012, RISK ANAL, V32, P2098, DOI 10.1111/j.1539-6924.2012.01822.x
   McDowell NG, 2020, SCIENCE, V368, P964, DOI 10.1126/science.aaz9463
   Meddens AJH, 2012, ECOL APPL, V22, P1876, DOI 10.1890/11-1785.1
   Messier C, 2019, FOR ECOSYST, V6, DOI 10.1186/s40663-019-0166-2
   Mezei P, 2017, AGR FOREST METEOROL, V242, P85, DOI 10.1016/j.agrformet.2017.04.004
   Morris JL, 2018, FRONT ECOL ENVIRON, V16, pS34, DOI 10.1002/fee.1754
   Morris JL, 2017, J APPL ECOL, V54, P750, DOI 10.1111/1365-2664.12782
   Müller J, 2008, BIODIVERS CONSERV, V17, P2979, DOI 10.1007/s10531-008-9409-1
   Nelson H, 2007, CAN J AGR ECON, V55, P459, DOI 10.1111/j.1744-7976.2007.00102.x
   Ogris N, 2010, ECOL MODEL, V221, P290, DOI 10.1016/j.ecolmodel.2009.05.015
   Posner SM, 2019, ENVIRON SCI POLICY, V92, P141, DOI 10.1016/j.envsci.2018.11.006
   Progar RA, 2014, FOREST SCI, V60, P414, DOI 10.5849/forsci.13-010
   Raffa KF, 2008, BIOSCIENCE, V58, P501, DOI 10.1641/B580607
   Ravindranath M., [No title captured]
   Rayner T., 2016, Oxford Research Encyclopedia of Climate Science, DOI [10.1093/acrefore/9780190228620.013.47, DOI 10.1093/ACREFORE/9780190228620.013.47]
   Régnière J, 2007, J INSECT PHYSIOL, V53, P559, DOI 10.1016/j.jinsphys.2007.02.007
   Rose DC, 2015, CONSERV BIOL, V29, P748, DOI 10.1111/cobi.12444
   Rouault G, 2006, ANN FOREST SCI, V63, P613, DOI 10.1051/forest:2006044
   Safranyik L., 2006, The mountain pine beetle: a synthesis of biology, management and impacts on lodgepole pine, P3
   Schelhaas MJ, 2003, GLOBAL CHANGE BIOL, V9, P1620, DOI 10.1046/j.1365-2486.2003.00684.x
   Schuck A., 2015, STRATEGY BUSINESS PL, V95
   SciVerse Scopus, 2020, SCOPUS DOCUMENT SEAR
   Seidl R, 2017, NAT CLIM CHANGE, V7, P395, DOI [10.1038/NCLIMATE3303, 10.1038/nclimate3303]
   Seidl R, 2016, J APPL ECOL, V53, P530, DOI 10.1111/1365-2664.12540
   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, 2011, GLOBAL CHANGE BIOL, V17, P2842, DOI 10.1111/j.1365-2486.2011.02452.x
   Senf C., 2020, INCREASES CANOPY MOR
   Senf C, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-07539-6
   Senf C, 2018, GLOBAL CHANGE BIOL, V24, P1201, DOI 10.1111/gcb.13897
   Settele J, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P271
   Seybold SJ, 2018, ANNU REV ENTOMOL, V63, P407, DOI 10.1146/annurev-ento-020117-043339
   Siders AR, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.573
   Sims C, 2014, P NATL ACAD SCI USA, V111, P16718, DOI 10.1073/pnas.1407381111
   Soderberg DN, 2021, ECOL MONOGR, V91, DOI 10.1002/ecm.1437
   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
   Stanturf JA, 2020, BURL DODDS AGR SCI, V71, P515, DOI 10.19103/AS.2019.0057.19
   Stritih A, 2021, FOREST ECOL MANAG, V484, DOI 10.1016/j.foreco.2021.118950
   Swanston CW., 2016, Forest Adaptation Resources: climate change tools and approaches for land managers, V2nd, DOI DOI 10.2737/NRS-GTR-87-2
   Thom D, 2016, BIOL REV, V91, P760, DOI 10.1111/brv.12193
   Thom D, 2013, FOREST ECOL MANAG, V307, P293, DOI 10.1016/j.foreco.2013.07.017
   Thorn S, 2018, J APPL ECOL, V55, P279, DOI 10.1111/1365-2664.12945
   Thorn S, 2017, FOREST ECOL MANAG, V388, P113, DOI 10.1016/j.foreco.2016.06.006
   Timberlake TJ, 2021, J ENVIRON PLANN MAN, V64, P1291, DOI 10.1080/09640568.2020.1817730
   Tkacz B., 2011, NATL ROADMAP RESPOND
   Weed AS, 2013, ECOL MONOGR, V83, P441, DOI 10.1890/13-0160.1
   Wermelinger B, 2004, FOREST ECOL MANAG, V202, P67, DOI 10.1016/j.foreco.2004.07.018
   Zhou YT, 2019, FORESTS, V10, DOI 10.3390/f10100860
   Zimová S, 2020, FOREST ECOL MANAG, V475, DOI 10.1016/j.foreco.2020.118408
NR 124
TC 13
Z9 15
U1 2
U2 52
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 NOV 1
PY 2021
VL 499
AR 119599
DI 10.1016/j.foreco.2021.119599
EA AUG 2021
PG 10
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Forestry
GA UR5NO
UT WOS:000696796200005
OA Bronze
DA 2025-01-10
ER

PT J
AU Arafeh-Dalmau, N
   Brito-Morales, I
   Schoeman, DS
   Possingham, HP
   Klein, CJ
   Richardson, AJ
AF Arafeh-Dalmau, Nur
   Brito-Morales, Isaac
   Schoeman, David S.
   Possingham, Hugh P.
   Klein, Carissa J.
   Richardson, Anthony J.
TI Incorporating climate velocity into the design of climate-smart networks
   of marine protected areas
SO METHODS IN ECOLOGY AND EVOLUTION
LA English
DT Article
DE climate adaptation; conservation planning; marine reserves; marine
   spatial planning; post-2020 conservation targets; spatial prioritization
ID SPATIAL CONSERVATION PRIORITIZATION; COST
AB Climate change is redistributing terrestrial and marine biodiversity and altering fundamental ecological interactions. To conserve biodiversity and promote its long-term persistence, protected areas should account for the ecological implications of species' redistribution. Data paucity across many systems means that achieving this goal requires generic metrics that act as proxies for likely responses of multiple taxa to climate change. Climate velocity is one such metric, representing the potential speed and direction of species' range shifts. Here, we explore three approaches for incorporating climate velocity into the design of marine protected areas and demonstrate their application in the Mediterranean Sea. Our methods are designed to meet the climate-smart adaptation strategy of protecting climate refugia by selecting slow-moving climate velocity areas. For our case study, we found that incorporating climate velocity as a cost measure in Marxan best selects slower moving areas, which are robust indicators of climate refugia. However, this approach is unable to accommodate socio-economic cost data and is thus impractical. Incorporating climate velocity as a boundary or as a feature selects slower moving areas with a lower socio-economic cost. We recommend incorporating velocity as a boundary, where possible because it is a more flexible approach. The boundary approach considers the climate velocity of all planning units, rather than being limited to a subjective classification of 'slow-moving' planning units when treated as a feature. However, further assessment is required. For different planning scales and for grid structures other than squares, the relative performance of incorporating climate velocity as a boundary or as a feature might vary among case studies. This work presents simple and practical ways of including climate velocity in conservation plans to achieve the key climate-smart objective of protecting climate refugia, thereby enhancing ecological resilience. Our methods are widely applicable, encouraging researchers and practitioners to advance the field and deliver networks of climate-smart protected areas by 2030.
C1 [Arafeh-Dalmau, Nur; Possingham, Hugh P.; Klein, Carissa J.] Univ Queensland, Ctr Biodivers & Conservat Sci, Sch Biol Sci, St Lucia, Qld, Australia.
   [Arafeh-Dalmau, Nur; Brito-Morales, Isaac; Klein, Carissa J.] Univ Queensland, Sch Earth & Environm Sci, St Lucia, Qld, Australia.
   [Brito-Morales, Isaac; Richardson, Anthony J.] CSIRO, Oceans & Atmosphere BioSci Precinct QBP, St Lucia, Qld, Australia.
   [Schoeman, David S.] Univ Sunshine Coast, Sch Sci Technol & Engn, Global Change Ecol Res Grp, Maroochydore, Qld, Australia.
   [Schoeman, David S.] Nelson Mandela Univ, Ctr African Conservat Ecol, Dept Zool, Ggeberha, South Africa.
   [Possingham, Hugh P.] Nature Conservancy, Arlington, VA USA.
   [Richardson, Anthony J.] Univ Queensland, Ctr Applicat Nat Resource Math, Sch Math & Phys, St Lucia, Qld, Australia.
C3 University of Queensland; University of Queensland; Commonwealth
   Scientific & Industrial Research Organisation (CSIRO); University of the
   Sunshine Coast; Nelson Mandela University; Nature Conservancy;
   University of Queensland
RP Arafeh-Dalmau, N (corresponding author), Univ Queensland, Sch Earth & Environm Sci, St Lucia, Qld, Australia.
EM n.arafehdalmau@uq.net.au
RI POSSINGHAM, HUGH/R-8310-2019; Brito-Morales, Isaac/L-2071-2019; Klein,
   Carissa/F-1632-2011; Richardson, Anthony/B-3649-2010; Brito Morales,
   Isaac/C-3104-2019; Arafeh-Dalmau, Nur/D-4223-2019; Possingham,
   Hugh/B-1337-2008
OI Richardson, Anthony/0000-0002-9289-7366; Brito Morales,
   Isaac/0000-0003-0073-2431; Arafeh-Dalmau, Nur/0000-0001-9053-0037;
   Possingham, Hugh/0000-0001-7755-996X; Schoeman,
   David/0000-0003-1258-0885
FU Advanced Human Capital Program of the Chilean National Research and
   Development Agency [72170231]; Fundacion Bancaria 'la Caixa'
   Postgraduate Fellowship [LCF/BQ/AA16/11580053]; ARC Future Fellowship
   [FT200100314]; Australian Research Council [FT200100314] Funding Source:
   Australian Research Council
FX Advanced Human Capital Program of the Chilean National Research and
   Development Agency, Grant/Award Number: 72170231; Fundacion Bancaria `la
   Caixa' Postgraduate Fellowship, Grant/Award Number: LCF/BQ/
   AA16/11580053; ARC Future Fellowship, Grant/Award Number: FT200100314
CR Alvarez-Romero JG, 2018, BIOL CONSERV, V227, P369, DOI 10.1016/j.biocon.2018.06.027
   Arafeh-Dalmau N, 2019, FRONT MAR SCI, V6, DOI 10.3389/fmars.2019.00499
   Arafeh-Dalmau N, 2017, FRONT MAR SCI, V4, DOI 10.3389/fmars.2017.00150
   Ball I. R., 2009, SPATIAL CONSERVATION, P185
   Ban NC, 2009, CONSERV LETT, V2, P206, DOI 10.1111/j.1755-263X.2009.00071.x
   Bates AE, 2019, BIOL CONSERV, V236, P305, DOI 10.1016/j.biocon.2019.05.005
   Beger M, 2010, CONSERV LETT, V3, P359, DOI 10.1111/j.1755-263X.2010.00123.x
   Brito-Morales I, 2020, NAT CLIM CHANGE, V10, P576, DOI 10.1038/s41558-020-0773-5
   Brito-Morales I, 2018, TRENDS ECOL EVOL, V33, P441, DOI 10.1016/j.tree.2018.03.009
   Burrows MT, 2014, NATURE, V507, P492, DOI 10.1038/nature12976
   Burrows MT, 2011, SCIENCE, V334, P652, DOI 10.1126/science.1210288
   Cahill AE, 2013, P ROY SOC B-BIOL SCI, V280, DOI 10.1098/rspb.2012.1890
   Carroll C, 2017, GLOBAL CHANGE BIOL, V23, P4508, DOI 10.1111/gcb.13679
   CBD, 2021, OP END WORK GROUP PO
   Cramer W, 2018, NAT CLIM CHANGE, V8, P972, DOI 10.1038/s41558-018-0299-2
   Daigle RM, 2020, METHODS ECOL EVOL, V11, P570, DOI 10.1111/2041-210X.13349
   Diaz RJ, 2008, SCIENCE, V321, P926, DOI 10.1126/science.1156401
   Duarte CM, 2020, NATURE, V580, P39, DOI 10.1038/s41586-020-2146-7
   Edgar GJ, 2014, NATURE, V506, P216, DOI 10.1038/nature13022
   Fredston-Hermann A, 2018, ANN NY ACAD SCI, V1429, P5, DOI 10.1111/nyas.13597
   Garcia Molinos Jorge, 2016, Nature Climate Change, V6, P83, DOI 10.1038/nclimate2769
   Giorgi F, 2006, GEOPHYS RES LETT, V33, DOI 10.1029/2006GL025734
   Gray CL, 2016, NAT COMMUN, V7, DOI 10.1038/ncomms12306
   Haight J, 2020, BIOL CONSERV, V241, DOI 10.1016/j.biocon.2019.108258
   Hansen L, 2010, CONSERV BIOL, V24, P63, DOI 10.1111/j.1523-1739.2009.01404.x
   Harris RMB, 2014, WIRES CLIM CHANGE, V5, P621, DOI 10.1002/wcc.291
   Hiddink JG, 2012, GLOBAL CHANGE BIOL, V18, P2161, DOI 10.1111/j.1365-2486.2012.02698.x
   Jones KR, 2016, BIOL CONSERV, V194, P121, DOI 10.1016/j.biocon.2015.12.008
   Kaschner K., 2016, AQUAMAPS PREDICTED R
   Keppel G, 2015, FRONT ECOL ENVIRON, V13, P106, DOI 10.1890/140055
   Klein CJ, 2015, SCI REP-UK, V5, DOI 10.1038/srep17539
   Kroeker KJ, 2013, GLOBAL CHANGE BIOL, V19, P1884, DOI 10.1111/gcb.12179
   LANDIS JR, 1977, BIOMETRICS, V33, P159, DOI 10.2307/2529310
   Lawler JJ, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0117
   Lejeusne C, 2010, TRENDS ECOL EVOL, V25, P250, DOI 10.1016/j.tree.2009.10.009
   Loarie SR, 2009, NATURE, V462, P1052, DOI 10.1038/nature08649
   Lotze HK, 2019, P NATL ACAD SCI USA, V116, P12907, DOI 10.1073/pnas.1900194116
   Maxwell SL, 2019, GLOB ECOL CONSERV, V18, DOI 10.1016/j.gecco.2019.e00649
   Mazor T, 2014, ECOL APPL, V24, P1115, DOI 10.1890/13-1249.1
   McHugh ML, 2012, BIOCHEM MEDICA, V22, P276, DOI 10.11613/bm.2012.031
   Micheli F, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0040832
   Moilanen A., 2009, Spatial conservation prioritization: Quantitative methods and computational tools, P196
   Molinos JG, 2019, METHODS ECOL EVOL, V10, P2195, DOI 10.1111/2041-210X.13295
   Nagelkerken I, 2020, SCIENCE, V369, P829, DOI 10.1126/science.aax0621
   O'Neill BC, 2017, GLOBAL ENVIRON CHANG, V42, P169, DOI 10.1016/j.gloenvcha.2015.01.004
   O'Neill BC, 2014, CLIMATIC CHANGE, V122, P387, DOI 10.1007/s10584-013-0905-2
   Oliver ECJ, 2019, FRONT MAR SCI, V6, DOI 10.3389/fmars.2019.00734
   Pecl GT, 2017, SCIENCE, V355, DOI 10.1126/science.aai9214
   Reside AE, 2018, BIODIVERS CONSERV, V27, P1, DOI 10.1007/s10531-017-1442-5
   Roberts CM, 2017, P NATL ACAD SCI USA, V114, P6167, DOI 10.1073/pnas.1701262114
   Robinson LM, 2011, GLOBAL ECOL BIOGEOGR, V20, P789, DOI 10.1111/j.1466-8238.2010.00636.x
   Ruiz-Frau A, 2015, OCEAN COAST MANAGE, V103, P86, DOI 10.1016/j.ocecoaman.2014.11.012
   Sala E, 2021, NATURE, V592, DOI 10.1038/s41586-021-03371-z
   Sandel B, 2011, SCIENCE, V334, P660, DOI 10.1126/science.1210173
   Sequeira AMM, 2018, METHODS ECOL EVOL, V9, P1250, DOI 10.1111/2041-210X.12998
   Smale DA, 2019, NAT CLIM CHANGE, V9, P306, DOI 10.1038/s41558-019-0412-1
   Stein B A., 2014, Climate-Smart Conservation: Putting Adaptation Principles into Practice
   Stewart RR, 2005, ENVIRON MODEL ASSESS, V10, P203, DOI 10.1007/s10666-005-9001-y
   Stralberg D, 2020, CONSERV LETT, V13, DOI 10.1111/conl.12712
   Stralberg D, 2018, GLOBAL ECOL BIOGEOGR, V27, P690, DOI 10.1111/geb.12731
   Tittensor DP, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aay9969
   Vargas-Yáñez M, 2008, GLOBAL PLANET CHANGE, V63, P177, DOI 10.1016/j.gloplacha.2007.09.001
   Venegas-Li R, 2018, METHODS ECOL EVOL, V9, P773, DOI 10.1111/2041-210X.12896
   West JM, 2017, ENVIRON MANAGE, V59, P102, DOI 10.1007/s00267-016-0774-3
   Wilson KL, 2020, GLOBAL CHANGE BIOL, V26, P3251, DOI 10.1111/gcb.15094
   Yates KL, 2018, TRENDS ECOL EVOL, V33, P790, DOI 10.1016/j.tree.2018.08.001
NR 66
TC 33
Z9 36
U1 5
U2 64
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 2041-210X
EI 2041-2096
J9 METHODS ECOL EVOL
JI Methods Ecol. Evol.
PD OCT
PY 2021
VL 12
IS 10
BP 1969
EP 1983
DI 10.1111/2041-210X.13675
EA AUG 2021
PG 15
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA WB5NH
UT WOS:000684517400001
OA Bronze
DA 2025-01-10
ER

PT J
AU Wang, Y
   Guo, CH
   Zhuang, SR
   Chen, XJ
   Jia, LQ
   Chen, ZY
   Xia, ZL
   Wu, Z
AF Wang, Yao
   Guo, Chi-hui
   Zhuang, Shu-rong
   Chen, Xi-jie
   Jia, Li-qiong
   Chen, Ze-yu
   Xia, Zi-long
   Wu, Zhen
TI Major contribution to carbon neutrality by China's geosciences and
   geological technologies
SO CHINA GEOLOGY
LA English
DT Article
DE Carbon neutrality; Carbon peaking; Carbon emissions; Carbon
   sequestration; Key minerals; Renewable energy; Climate change;
   Geosciences; Geological technology; China
ID NATURAL-GAS HYDRATE; HOT DRY ROCK; SOUTH CHINA; SHENHU AREA; ENERGY;
   MECHANISM; CLIMATE; SYSTEM; BASIN
AB In the context of global climate change, geosciences provide an important geological solution to achieve the goal of carbon neutrality, China's geosciences and geological technologies can play an important role in solving the problem of carbon neutrality. This paper discusses the main problems, opportunities, and challenges that can be solved by the participation of geosciences in carbon neutrality, as well as China's response to them. The main scientific problems involved and the geological work carried out mainly fall into three categories: (1) Carbon emission reduction technology (natural gas hydrate, geothermal, hot dry rock, nuclear energy, hydropower, wind energy, solar energy, hydrogen energy); (2) carbon sequestration technology (carbon capture and storage, underground space utilization); (3) key minerals needed to support carbon neutralization (raw materials for energy transformation, carbon reduction technology). Therefore, geosciences and geological technologies are needed: First, actively participate in the development of green energy such as natural gas, geothermal energy, hydropower, hot dry rock, and key energy minerals, and develop exploration and exploitation technologies such as geothermal energy and natural gas; the second is to do a good job in geological support for new energy site selection, carry out an in-depth study on geotechnical feasibility and mitigation measures, and form the basis of relevant economic decisions to reduce costs and prevent geological disasters; the third is to develop and coordinate relevant departments of geosciences, organize and carry out strategic research on natural resources, carry out theoretical system research on global climate change and other issues under the guidance of earth system science theory, and coordinate frontier scientific information and advanced technological tools of various disciplines. The goal of carbon neutrality provides new opportunities and challenges for geosciences research. In the future, it is necessary to provide theoretical and technical support from various aspects, enhance the ability of climate adaptation, and support the realization of the goal of carbon peaking and carbon neutrality. (C) 2021 China Geology Editorial Office.
C1 [Wang, Yao; Chen, Xi-jie; Jia, Li-qiong] Dev & Res Ctr China Geol Survey, Beijing 100037, Peoples R China.
   [Guo, Chi-hui] China Univ Geosci Beijing, Beijing 100083, Peoples R China.
   [Zhuang, Shu-rong; Xia, Zi-long] East China Normal Univ, Shanghai 200241, Peoples R China.
   [Chen, Ze-yu] China Inst Water Resources & Hydropower Res, Beijing 100038, Peoples R China.
   [Wu, Zhen] Nanjing Univ, Nanjing 210000, Peoples R China.
C3 China Geological Survey; Development & Research Center of China
   Geological Survey; China University of Geosciences; East China Normal
   University; China Institute of Water Resources & Hydropower Research;
   Nanjing University
RP Wang, Y (corresponding author), Dev & Res Ctr China Geol Survey, Beijing 100037, Peoples R China.
EM 565601371@qq.com
RI chen, xijie/ABD-4916-2021; Zilong, Xia/GSD-3261-2022
OI Wu, Zhen/0000-0003-2235-825X; Chen, Xijie/0000-0003-4109-9134
FU China Geological Survey [DD20211413]
FX This study was supported by the project of China Geological Survey on a
   systematic assessment of ecological protection and natural resources
   utilization (DD20211413)
CR Agostini A, 2021, APPL ENERG, V281, DOI 10.1016/j.apenergy.2020.116102
   Bai WLYS, 2020, INT J HYDROGEN ENERG, V45, P34354, DOI 10.1016/j.ijhydene.2019.12.198
   Budt M, 2016, APPL ENERG, V170, P250, DOI 10.1016/j.apenergy.2016.02.108
   Chen JH, 2020, DAZHONG DAILY 1103
   Chen JW, 2016, P 2016 CHIN NONM MIN, P81, DOI [10.26914/c.cnkihy.2016.002238, DOI 10.26914/C.CNKIHY.2016.002238]
   Chen K, 2020, SCI SURVEYING MAPPIN, V4, P199, DOI [10.16251/j.cnki.1009-2307.2020.04.028, DOI 10.16251/J.CNKI.1009-2307.2020.04.028]
   Chen XS, 2011, SINOGLOBAL ENERGY, V9, P1
   Cheng LJ, 1992, INT S DEV UT HIGH TE, P14
   China Geological Survey, 2021, FOREIGN GEOLOGICAL S, P5
   Duan H, 2019, CONSERVATION UTILIZA, V39, P99, DOI [10.13779/j.cnki.issn1001- 0076.2019.04.017, DOI 10.13779/J.CNKI.ISSN1001-0076.2019.04.017]
   Fan JJ, 2021, CHINA NATURAL RESOUR
   Faqin Dong, 2015, Materials Science Forum, V814, P583, DOI 10.4028/www.scientific.net/MSF.814.583
   Feng YF, 2018, CHINA GEOL, V1, P331, DOI 10.31035/cg2018043
   Gong YH, 2010, NATURAL GAS IND, V10, P103
   Gu WD, 2006, MACROECONOMICS, V4, P44, DOI [10.16304/j.cnki.11-3952/ f.2006.04.009, DOI 10.16304/J.CNKI.11-3952/F.2006.04.009]
   Hashim JH, 2016, ASIA-PAC J PUBLIC HE, V28, p8S, DOI 10.1177/1010539515599030
   Hayashi D, 2020, ENERGY RES SOC SCI, V70, DOI 10.1016/j.erss.2020.101644
   [何梅兴 He Meixing], 2020, [中国地质, Geology of China], V47, P173
   Hu QY, 2017, RESOURCES IND, V19, P5
   Jiang MQ, 2020, J NATURAL RESOURCES, V11, P2585
   Jiang SY, 2020, ENERGY CHINA, V1, P4
   Jin RS, 2020, CHINA GEOL, V3, P52, DOI 10.31035/cg2020002
   Li C, 2019, GEOLOGY CHINA, V3, P482
   Li JL, 2020, RENEW SUST ENERG REV, V132, DOI 10.1016/j.rser.2020.110002
   Li JF, 2018, CHINA GEOL, V1, P5, DOI 10.31035/cg2018003
   Liang XC, 2006, ECOLOGICAL EC, V11, P105
   Liu B, 2005, HUNAN SOCIAL SCI, P104, DOI [10.3969/j.issn.1009-5675.2005.01.025, DOI 10.3969/J.ISSN.1009-5675.2005.01.025]
   [刘东盛 Liu Dongsheng], 2020, [地球学报, Acta Geoscientia Sinica], V41, P807
   [刘东盛 Liu Dongsheng], 2020, [地球学报, Acta Geoscientia Sinica], V41, P759
   Liu GR, 1992, GEOLOGY CHINA, V9, P8
   Liu J., 2012, Geol. Surv. Res, V35, P67
   Liu Mingjie., 2021, 2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS), P1, DOI [DOI 10.19851/J.CNKI.CN11-1010/F.2021.02.06, 10.19851/j.cnki.cn11-1010/f.2021.02.06]
   Liu Z., 2015, CHEM MINER GEOL, V37, P171
   Long C, 2019, SMALL METHODS, V3, DOI 10.1002/smtd.201800369
   Lu YB, 2009, EXPLORATION ENG ROCK, V36, P1
   Lu ZQ, 2020, CHINA GEOL, V3, P511, DOI 10.31035/cg2020075
   Mah AXY, 2019, INT J HYDROGEN ENERG, V44, P5661, DOI 10.1016/j.ijhydene.2019.01.077
   [梅生伟 Mei Shengwei], 2017, [电网技术, Power System Technology], V41, P3392
   Mock JE, 1997, ANNU REV ENERG ENV, V22, P305, DOI 10.1146/annurev.energy.22.1.305
   [庞忠和 Pang Zhonghe], 2020, [地学前缘, Earth Science Frontiers], V27, P134
   [庞忠和 Pang Zhonghe], 2017, [中国科学院院刊, Bulletin of the Chinese Academy of Sciences], V32, P1224
   Paulo C, 2021, APPL GEOCHEM, V129, DOI 10.1016/j.apgeochem.2021.104955
   Qin XW, 2020, CHINA GEOL, V3, P210, DOI 10.31035/cg2020038
   Qiu XF, 2008, MOUNTAIN RES, V2, P185
   Runyon J., 2020, CONSTRUCTION BEGINS
   Ryu BJ, 2013, MAR PETROL GEOL, V47, P1, DOI 10.1016/j.marpetgeo.2013.07.007
   [沙志彬 Sha Zhibin], 2019, [海洋地质前沿, Marine Geology Letters], V35, P1
   Shen DC, 2009, SOL ENERGY, V3, P11
   Shen J, 2018, GEOLOGICAL SURVEY CH, V5, P25, DOI [10.19388/j.zgdzdc.2018.02.04, DOI 10.19388/J.ZGDZDC.2018.02.04]
   Shepherd JG, 2012, PHILOS T R SOC A, V370, P4166, DOI 10.1098/rsta.2012.0186
   Sherif S.A., 2005, The Electricity Journal, V18, P62, DOI [10.1016/j.tej.2005.06.003, DOI 10.1016/J.TEJ.2005.06.003]
   Solomon AA, 2014, APPL ENERG, V134, P75, DOI 10.1016/j.apenergy.2014.07.095
   Stephenson M, 2018, EN CLIM CHANG, P91
   Sun L, 2018, CHINA GEOL, V1, P425, DOI 10.31035/cg2018044
   [孙涛 Sun Tao], 2014, [中国地质, Geology of China], V41, P1986
   Tang CC, 2019, CHIN J GEOMECH, V25, P501, DOI DOI 10.12090/J.ISSN.1006-6616.2019.25.04.048
   Teske S, 2019, ACHIEVING THE PARIS CLIMATE AGREEMENT GOALS: GLOBAL AND REGIONAL 100% RENEWABLE ENERGY SCENARIOS WITH NON-ENERGY GHG PATHWAYS FOR +1.5(DEGREE)C AND +2(DEGREE)C, P1, DOI 10.1007/978-3-030-05843-2
   [佟新华 Tong Xinhua], 2020, [中国人口·资源与环境, China Population Resources and Environment], V30, P26
   United States Geological Survey (USGS), 2020, RAR EARTH STAT INF
   Wan ZJ, 2005, RENEW ENERG, V30, P1831, DOI 10.1016/j.renene.2005.01.016
   Wang G, 2013, P 38 WORKSHOP GEOTHE
   Wang GL, 2020, CHINA GEOL, V3, P173, DOI 10.31035/cg2020013
   Wang GL, 2018, CHINA GEOL, V1, P273, DOI 10.31035/cg2018021
   [王贵玲 Wang Guiling], 2020, [地学前缘, Earth Science Frontiers], V27, P1
   [王贵玲 Wang Guiling], 2017, [中国地质, Geology of China], V44, P1074
   Wang JS, 2020, EARTH SCI FRONTIERS, V1, P17, DOI [10.13745/j.esf.2020.1.3, DOI 10.13745/J.ESF.2020.1.3]
   Wang JS, 2004, J GEOLOGICAL HAZARDS, V4, P5
   Wang L, PET GEOL EXP, V43, P208, DOI CNKI:SUN:SYSD.0.2021-02-003
   Wang Q, 2019, CHINA GEOL, V2, P563, DOI 10.31035/cg2018136
   [王绍武 Wang Shaowu], 2010, [地球科学进展, Advance in Earth Sciences], V25, P656
   Wang XJ, 2014, MAR GEOL, V357, P272, DOI 10.1016/j.margeo.2014.09.040
   [王学求 Wang Xueqiu], 2020, [地球学报, Acta Geoscientia Sinica], V41, P739
   [魏合龙 Wei Helong], 2016, [海洋地质与第四纪地质, Marine Geology & Quaternary Geology], V36, P1
   [文冬光 Wen Dongguang], 2014, [中国地质, Geology of China], V41, P1716
   World Bank, 2021, CO2 EM STAT COUNTR
   Wu NY, 2010, P OFFSH TECHN C, DOI [10.4043/20485-MS, DOI 10.4043/20485-MS]
   [吴时国 Wu Shiguo], 2018, [科学通报, Chinese Science Bulletin], V63, P2
   Xiao ZH, 2020, CHINA GEOL, V3, P411, DOI 10.31035/cg2020040
   [徐步朝 Xu Buchao], 2010, [资源科学, Resources Science], V32, P2186
   [许天福 Xu Tianfu], 2016, [吉林大学学报. 地球科学版, Journal of Jilin University. Earth Science Edition], V46, P1139
   Xue H, 2020, CHINA GEOL, V3, P524, DOI 10.31035/cg2020037
   [闫强 Yan Qiang], 2010, [地球学报, Acta Geoscientia Sinica], V31, P759
   Yang, 2018, ENERGY CHINA, V40, P25
   Yang PQ, 2007, NW HYDROPOWER, V4, P17
   Ye JL, 2018, CHINA GEOL, V1, P202, DOI 10.31035/cg2018029
   Yeh TK, 2019, TERR ATMOS OCEAN SCI, V30, P151, DOI 10.3319/TAO.2018.12.22.01
   Zhang DC, 2012, CHINA NONMETALLIC MI, V5, P4
   [张二勇 Zhang Eryong], 2012, [水文地质工程地质, Hydrogeology & Engineering Geology], V39, P131
   Zhang GX, 2018, CHINA GEOL, V1, P459, DOI 10.31035/cg2018060
   Zhang MH, 2020, ENERGY, V206, DOI 10.1016/j.energy.2020.118165
   Zhang QX, 2011, TRANSFORMATION CHINE, P22
   [张森琦 Zhang Senqi], 2018, [中国地质, Geology of China], V45, P1087
   Zhang SF, 2014, ENERG POLICY, V67, P903, DOI 10.1016/j.enpol.2013.12.063
   Zhang YW, 2001, REMOTE SENSING LAND, V1, P19
   Zhou D., 2018, SINO GLOBAL ENERGY, V23, P38
   Zhu YH, 2021, CHINA GEOL, V4, P17, DOI 10.31035/cg2021025
NR 96
TC 28
Z9 37
U1 9
U2 164
PU CHINA GEOLOGY EDITORIAL OFFICE
PI BEIJING
PA NO 45 FUWAL ST, XICHENG DISTRICT, BEIJING, 100037, PEOPLES R CHINA
SN 2096-5192
J9 CHINA GEOL
JI China Geol.
PD JUN
PY 2021
VL 4
IS 2
BP 329
EP 352
DI 10.31035/cg2021037
EA JUL 2021
PG 24
WC Geosciences, Multidisciplinary
WE Emerging Sources Citation Index (ESCI)
SC Geology
GA TQ3DS
UT WOS:000678164900012
OA gold
DA 2025-01-10
ER

PT J
AU Yu, ZW
   Zhang, JU
   Yang, GY
   Schlaberg, J
AF Yu, Zhaowu
   Zhang, Jinguang
   Yang, Gaoyuan
   Schlaberg, Juliana
TI Reverse Thinking: A New Method from the Graph Perspective for Evaluating
   and Mitigating Regional Surface Heat Islands
SO REMOTE SENSING
LA English
DT Article
DE urban heat island; graph theory; morphological spatial pattern analysis;
   habitat availability indices; land surface temperature; climate adaption
ID LOCAL CLIMATE ZONES; RAPID URBANIZATION; SPATIAL-PATTERNS; GREEN SPACE;
   TEMPERATURE RETRIEVAL; THERMAL ENVIRONMENT; URBAN EXPANSION; HABITAT
   PATCHES; CONNECTIVITY; TECHNOLOGIES
AB Accurately locating key nodes and corridors of an urban heat island (UHI) is the basis for effectively mitigating a regional surface UHI. However, we still lack appropriate methods to describe it, especially considering the interaction between UHIs and the role of connectivity (network). Specifically, previous studies paid much attention to the raster and vector perspective-based on standard landscape configuration metrics that only provide an overall statistic over the entire study area without further indicating locations where different types of pattern and fragmentation occur. Therefore, by reverse thinking, here we attempt to propose a new method from the graph perspective which integrates morphological spatial pattern analysis (MSPA)-which is used to characterize binary patterns with emphasis on connections between their parts as measured at varying analysis scales, and habitat availability indices to evaluate and mitigate regional surface UHI. We selected the Pearl River Delta Metropolitan Region (PRDR), one of the most rapidly urbanized regions in the world as the case study (1995-2015). The results of the case study showed: (1) the core (UHI) type accounts for the vast majority of the MSPA model, with the relative land surface temperature (LST) rises, the proportion of the core type will increase, and it could influence the edge (UHI) type significantly; (2) the branch, bridge, and islet (UHI) types have similar results to the lower temperature (4 < Relative LST <= 6) area and account for the majority, indicating that these types are more susceptible to their surrounding environment; (3) the importance and extreme importance area (node) from 1995 to 2015 have increased significantly and mainly distributed in the urbanized areas, which means cooling measures need to be implemented in these areas in order of priority. Shifting the research logic of UHI evaluation and mitigation from "patch" to "network", we hold the point that the method (reverse thinking) has significant theoretical and practical implications for mitigating regional UHI and urban climate-resilience.
C1 [Yu, Zhaowu] Fudan Univ, Dept Environm Sci & Engn, Songhu Rd 2005, Shanghai 200438, Peoples R China.
   [Zhang, Jinguang; Yang, Gaoyuan] Univ Copenhagen, Dept Geosci & Nat Resource Management, Fac Sci, Rolighedsvej 23, DK-1958 Copenhagen, Denmark.
   [Schlaberg, Juliana] Tech Univ Dresden, Fac Environm Sci, D-01062 Dresden, Germany.
C3 Fudan University; University of Copenhagen; Technische Universitat
   Dresden
RP Yu, ZW (corresponding author), Fudan Univ, Dept Environm Sci & Engn, Songhu Rd 2005, Shanghai 200438, Peoples R China.
EM zhaowu_yu@fudan.edu.cn; jizh@ign.ku.dk; gy@ign.ku.dk;
   juliana.schlaberg@mallbox.tu-dresden.de
RI Zhang, Jinguang/JAN-7365-2023; Gaoyuan, Yang/HKO-4087-2023; Yu,
   Zhaowu/E-8032-2016
OI Zhang, Jinguang/0000-0003-4696-5652; Yu, Zhaowu/0000-0003-4576-4541;
   Yang, Gaoyuan/0000-0001-9735-6529
FU Open Foundation of the State Key Laboratory of Urban and Regional
   Ecology of China [SKLURE2019-2-6]
FX This research was funded by the Open Foundation of the State Key
   Laboratory of Urban and Regional Ecology of China (grant no.
   SKLURE2019-2-6).
CR Akbari H, 2016, ENERG BUILDINGS, V133, P834, DOI 10.1016/j.enbuild.2016.09.067
   Bechtel B, 2015, ISPRS INT J GEO-INF, V4, P199, DOI 10.3390/ijgi4010199
   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
   Churkina G, 2017, ENVIRON SCI TECHNOL, V51, P6120, DOI 10.1021/acs.est.6b06514
   Deilami K, 2018, INT J APPL EARTH OBS, V67, P30, DOI 10.1016/j.jag.2017.12.009
   Estoque RC, 2017, SCI TOTAL ENVIRON, V577, P349, DOI 10.1016/j.scitotenv.2016.10.195
   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
   Forman RTT, 2014, URBAN ECOLOGY: SCIENCE OF CITIES, P1
   Gao J, 2019, ECOL INDIC, V107, DOI 10.1016/j.ecolind.2019.105579
   Gorelick N, 2017, REMOTE SENS ENVIRON, V202, P18, DOI 10.1016/j.rse.2017.06.031
   Hoag H, 2015, NATURE, V524, P402, DOI 10.1038/524402a
   Jiménez-Muñoz JC, 2014, IEEE GEOSCI REMOTE S, V11, P1840, DOI 10.1109/LGRS.2014.2312032
   Li HD, 2018, SCI TOTAL ENVIRON, V624, P262, DOI 10.1016/j.scitotenv.2017.11.360
   Liu JY, 2010, J GEOGR SCI, V20, P483, DOI 10.1007/s11442-010-0483-4
   Luan XL, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12030391
   Manoli G, 2019, NATURE, V573, P55, DOI 10.1038/s41586-019-1512-9
   Montgomery MR, 2008, SCIENCE, V319, P761, DOI 10.1126/science.1153012
   Oke T. R., 2017, Urban Climates, DOI [10.1017/9781139016476, DOI 10.1017/9781139016476]
   Pascual-Hortal L, 2008, EUR J FOREST RES, V127, P23, DOI 10.1007/s10342-006-0165-z
   Pascual-Hortal L, 2006, LANDSCAPE ECOL, V21, P959, DOI 10.1007/s10980-006-0013-z
   Peng J, 2018, SCI TOTAL ENVIRON, V644, P781, DOI 10.1016/j.scitotenv.2018.06.292
   Peng J, 2016, REMOTE SENS ENVIRON, V173, P145, DOI 10.1016/j.rse.2015.11.027
   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
   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
   Saura S, 2011, FOREST ECOL MANAG, V262, P150, DOI 10.1016/j.foreco.2011.03.017
   Seto KC, 2012, P NATL ACAD SCI USA, V109, P16083, DOI 10.1073/pnas.1211658109
   Shi XM, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10124649
   Sobstyl JM, 2018, PHYS REV LETT, V120, DOI 10.1103/PhysRevLett.120.108701
   Soille P, 2009, PATTERN RECOGN LETT, V30, P456, DOI 10.1016/j.patrec.2008.10.015
   Stewart ID, 2012, B AM METEOROL SOC, V93, P1879, DOI 10.1175/BAMS-D-11-00019.1
   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 Y, 2014, NAT CLIM CHANGE, V4, P1082, DOI 10.1038/NCLIMATE2410
   TAYLOR PD, 1993, OIKOS, V68, P571, DOI 10.2307/3544927
   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
   Vogt P, 2007, LANDSCAPE ECOL, V22, P171, DOI 10.1007/s10980-006-9013-2
   Ward K, 2016, SCI TOTAL ENVIRON, V569, P527, DOI 10.1016/j.scitotenv.2016.06.119
   Wickham JD, 2010, LANDSCAPE URBAN PLAN, V94, P186, DOI 10.1016/j.landurbplan.2009.10.003
   Xiong YZ, 2012, REMOTE SENS-BASEL, V4, P2033, DOI 10.3390/rs4072033
   Yang GY, 2020, SUSTAIN CITIES SOC, V53, DOI 10.1016/j.scs.2019.101932
   Yu WJ, 2017, REMOTE SENS-BASEL, V9, DOI 10.3390/rs9010045
   Yu XL, 2014, REMOTE SENS-BASEL, V6, P9829, DOI 10.3390/rs6109829
   Yu ZW, 2020, URBAN FOR URBAN GREE, V49, DOI 10.1016/j.ufug.2020.126630
   Yu ZW, 2020, APPL ENERG, V264, DOI 10.1016/j.apenergy.2020.114724
   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
   Zeng C, 2016, HABITAT INT, V55, P46, DOI 10.1016/j.habitatint.2016.02.006
   Zhang YJ, 2017, LANDSCAPE URBAN PLAN, V165, P162, DOI 10.1016/j.landurbplan.2017.04.009
   Zhou DC, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11010048
   Zhou DC, 2018, SCI TOTAL ENVIRON, V628-629, P415, DOI 10.1016/j.scitotenv.2018.02.074
   Zhou DC, 2015, SCI REP-UK, V5, DOI 10.1038/srep11160
   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
NR 61
TC 35
Z9 39
U1 16
U2 173
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 2021
VL 13
IS 6
AR 1127
DI 10.3390/rs13061127
PG 19
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 SE3SG
UT WOS:000651989900001
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Wadsworth, CB
   Okada, Y
   Dopman, EB
AF Wadsworth, Crista B.
   Okada, Yuta
   Dopman, Erik B.
TI Phenology-dependent cold exposure and thermal performance of <i>Ostrinia
   nubilalis</i> ecotypes
SO BMC EVOLUTIONARY BIOLOGY
LA English
DT Article
DE Thermal tolerance; Seasonal timing; Phenology; Cold-hardiness; Climate
   adaptation; Diapause; Adaptation by time
ID EUROPEAN CORN-BORER; SYMPATRIC SPECIATION; OVERWINTERING LARVAE;
   SPATIAL-DISTRIBUTION; PHEROMONE STRAINS; GENETIC ISOLATION; FLOWERING
   TIME; LEPIDOPTERA; DIVERGENCE; POPULATION
AB Background Understanding adaptation involves establishing connections between selective agents and beneficial population responses. However, relatively little attention has been paid to seasonal adaptation, in part, because it requires complex and integrative knowledge about seasonally fluctuating environmental factors, the effects of variable phenology on exposure to those factors, and evidence for temporal specialization. In the European corn borer moth, Ostrinia nubilalis, sympatric pheromone strains exploit the same host plant (Zea mays) but may genetically differ in phenology and be reproductively "isolated by time." Z strain populations in eastern North America have been shown to have a prolonged larval diapause and produce one annual mating flight (July), whereas E strain populations complete an earlier (June) and a later (August) mating flight by shortening diapause duration. Here, we find evidence consistent with seasonal "adaptation by time" between these ecotypes. Results We use 12 years of field observation of adult seasonal abundance to estimate phenology of ecotype life cycles and to quantify life-stage specific climatic conditions. We find that the observed reduction of diapause duration in the E strain leads their non-diapausing, active life stages to experience a similar to 4 degrees C colder environment compared to the equivalent life stages in the Z strain. For a representative pair of populations under controlled laboratory conditions, we compare life-stage specific cold tolerance and find non-diapausing, active life stages in the E strain have as much as a 60% greater capacity to survive rapid cold shock. Enhanced cold hardiness appears unrelated to life-stage specific changes in the temperature at which tissues freeze. Conclusions Our results suggest that isolation by time and adaptation by time may both contribute to population divergence, and they argue for expanded study in this species of allochronic populations in nature experiencing the full spectrum of seasonal environments. Cyclical selective pressures are inherent properties of seasonal habitats. Diverse fluctuating selective agents across each year (temperature, predation, competition, precipitation, etc.) may therefore be underappreciated drivers of biological diversity.
C1 [Wadsworth, Crista B.; Okada, Yuta; Dopman, Erik B.] Tufts Univ, Dept Biol, 200 Boston Ave,Suite 4700, Medford, MA 02155 USA.
   [Wadsworth, Crista B.] Rochester Inst Technol, Thomas H Gosnell Sch Life Sci, 85 Lomb Mem Dr, Rochester, NY 14623 USA.
C3 Tufts University; Rochester Institute of Technology
RP Wadsworth, CB; Dopman, EB (corresponding author), Tufts Univ, Dept Biol, 200 Boston Ave,Suite 4700, Medford, MA 02155 USA.; Wadsworth, CB (corresponding author), Rochester Inst Technol, Thomas H Gosnell Sch Life Sci, 85 Lomb Mem Dr, Rochester, NY 14623 USA.
EM cbwsbi@rit.edu; erik.dopman@tufts.edu
OI Dopman, Erik/0000-0002-8633-5527
FU United States Department of Agriculture [2010-65106-20610]; National
   Science Foundation [DEB1257251, 2011116050]; NIFA [580982,
   2010-65106-20610] Funding Source: Federal RePORTER
FX The study was funded by the United States Department of Agriculture
   (2010-65106-20610 to EBD) and the National Science Foundation
   (DEB1257251 to EBD; 2011116050 to CBW).
CR Ågren J, 2017, EVOLUTION, V71, P550, DOI 10.1111/evo.13126
   ALEXANDER RD, 1960, EVOLUTION, V14, P334, DOI 10.1111/j.1558-5646.1960.tb03095.x
   Andreadis SS, 2008, PHYSIOL ENTOMOL, V33, P365, DOI 10.1111/j.1365-3032.2008.00642.x
   BALE JS, 1987, J INSECT PHYSIOL, V33, P899, DOI 10.1016/0022-1910(87)90001-1
   BARNES D, 1956, J ECON ENTOMOL, V49, P19, DOI 10.1093/jee/49.1.19
   Beck S.D., 1987, Agricultural Zoology Reviews, V2, P59
   BENJAMINI Y, 1995, J R STAT SOC B, V57, P289, DOI 10.1111/j.2517-6161.1995.tb02031.x
   Bergland AO, 2014, PLOS GENET, V10, DOI 10.1371/journal.pgen.1004775
   Berlocher SH, 2002, ANNU REV ENTOMOL, V47, P773, DOI 10.1146/annurev.ento.47.091201.145312
   Bethenod MT, 2005, HEREDITY, V94, P264, DOI 10.1038/sj.hdy.6800611
   Bolnick DI, 2007, ANNU REV ECOL EVOL S, V38, P459, DOI 10.1146/annurev.ecolsys.38.091206.095804
   Boughman JW, 2017, EVOLUTION, V71, P6, DOI 10.1111/evo.13089
   CALVIN DD, 1991, ENVIRON ENTOMOL, V20, P441, DOI 10.1093/ee/20.2.441
   Coates BS, 2019, J ECON ENTOMOL, V112, P2007, DOI 10.1093/jee/toz078
   Derron JO, 2009, REV SUISSE AGRIC, V41, P179
   Gaitán-Espitia JD, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0070662
   Dopman EB, 2005, P NATL ACAD SCI USA, V102, P14706, DOI 10.1073/pnas.0502054102
   Dopman EB, 2004, GENETICS, V167, P301, DOI 10.1534/genetics.167.1.301
   Dopman EB, 2010, EVOLUTION, V64, P881, DOI 10.1111/j.1558-5646.2009.00883.x
   ECKENRODE CJ, 1983, ENVIRON ENTOMOL, V12, P393, DOI 10.1093/ee/12.2.393
   Egan SP, 2015, ECOL LETT, V18, P817, DOI 10.1111/ele.12460
   FEDER JL, 1994, P NATL ACAD SCI USA, V91, P7990, DOI 10.1073/pnas.91.17.7990
   Filchak KE, 2000, NATURE, V407, P739, DOI 10.1038/35037578
   Fisher R.A., 1922, Philos. Trans. R. Soc. Lond. Ser. A Contain. Pap. Math. Phys. Char., V222, P309, DOI [10.1098/rsta.1922.0009, DOI 10.1098/RSTA.1922.0009]
   GLOVER TJ, 1992, ARCH INSECT BIOCHEM, V20, P107, DOI 10.1002/arch.940200203
   GLOVER TJ, 1991, ENVIRON ENTOMOL, V20, P1356, DOI 10.1093/ee/20.5.1356
   Goto M, 2001, J INSECT PHYSIOL, V47, P157, DOI 10.1016/S0022-1910(00)00099-8
   GRUBORLAJSIC G, 1991, CRYOLETTERS, V12, P177
   Hall MC, 2006, EVOLUTION, V60, P2466, DOI 10.1554/05-688.1
   HANEC W, 1960, J INSECT PHYSIOL, V5, P169, DOI 10.1016/0022-1910(60)90002-0
   HENDERSON CF, 1955, J ECON ENTOMOL, V48, P157, DOI 10.1093/jee/48.2.157
   Hendry AP, 2005, MOL ECOL, V14, P901, DOI 10.1111/j.1365-294X.2005.02480.x
   Hood GR, 2015, P NATL ACAD SCI USA, V112, pE5980, DOI 10.1073/pnas.1424717112
   HUDON M, 1986, PHYTOPROTECTION, V67, P39
   Ikten C, 2011, ANN ENTOMOL SOC AM, V104, P567, DOI 10.1603/AN09149
   Keller I, 2012, MOL ECOL, V21, P782, DOI 10.1111/j.1365-294X.2011.05397.x
   KLUN JA, 1975, ENVIRON ENTOMOL, V4, P891, DOI 10.1093/ee/4.6.891
   Kozak GM, 2019, CURR BIOL, V29, P3501, DOI 10.1016/j.cub.2019.08.053
   Kozak GM, 2017, MOLECOL, V11, pe1005141
   Lamichhaney S, 2015, NATURE, V518, P371, DOI 10.1038/nature14181
   Lehmann P, 2017, PHYSIOL ENTOMOL, V42, P232, DOI 10.1111/phen.12188
   Length R, 2015, LSMEANS LEAST SQUARE, P1
   Mason CE, 1996, N CENT REG EXT PUBL, P1
   MATTESON JW, 1965, J ECON ENTOMOL, V58, P344, DOI 10.1093/jee/58.2.344
   MAYR E, 1982, EVOLUTION, V36, P1119, DOI 10.1111/j.1558-5646.1982.tb05483.x
   McCarthy J, 2015, DES THINK DES THEOR, P1
   MCLEOD DGR, 1976, CAN ENTOMOL, V108, P1403, DOI 10.4039/Ent1081403-12
   Michaud MR, 2004, INT CONGR SER, V1275, P32, DOI 10.1016/j.ics.2004.08.059
   NORDIN JH, 1984, J INSECT PHYSIOL, V30, P563, DOI 10.1016/0022-1910(84)90084-2
   O'Rourke ME, 2010, ECOL APPL, V20, P1228, DOI 10.1890/09-0067.1
   Ohlberger J, 2008, FUNCT ECOL, V22, P501, DOI 10.1111/j.1365-2435.2008.01391.x
   Pegoraro M, 2014, PLOS GENET, V10, DOI 10.1371/journal.pgen.1004603
   PICKETT A. D., 1940, SCI AGRIC [OTTAWA], V20, P551
   Ponsard S, 2004, CAN J ZOOL, V82, P1177, DOI [10.1139/z04-075, 10.1139/Z04-075]
   R Core Team, R A Language and Environment for Statistical Computing
   Ravinet M, 2016, MOL ECOL, V25, P287, DOI 10.1111/mec.13332
   Ritz C, 2005, J STAT SOFTW, V12, P1
   Santos H, 2011, J EVOLUTION BIOL, V24, P1897, DOI 10.1111/j.1420-9101.2011.02318.x
   Santos H, 2007, P ROY SOC B-BIOL SCI, V274, P935, DOI 10.1098/rspb.2006.3767
   Santos HM, 2013, ECOL EVOL, V3, P5098, DOI 10.1002/ece3.865
   Saunders DS, 2014, ENTOMOL SCI, V17, P25, DOI 10.1111/ens.12059
   Sinclair BJ, 1999, EUR J ENTOMOL, V96, P157
   Sulloway F.J., 1979, Studies in the History of Biology, V3, P23
   Tauber M.J., 1986, SEASONAL ADAPTATIONS, P1
   Taylor RS, 2017, MOL ECOL, V26, P3330, DOI 10.1111/mec.14126
   Teets NM, 2013, PHYSIOL ENTOMOL, V38, P105, DOI 10.1111/phen.12019
   Teixeira LAF, 2005, ENVIRON ENTOMOL, V34, P47, DOI 10.1603/0046-225X-34.1.47
   Trnka M, 2007, ECOL MODEL, V207, P61, DOI 10.1016/j.ecolmodel.2007.04.014
   Wadsworth CB, 2015, HEREDITY, V114, P593, DOI 10.1038/hdy.2014.128
   Wadsworth CB, 2013, J EVOLUTION BIOL, V26, P2359, DOI 10.1111/jeb.12227
   Wellenreuther M, 2018, TRENDS ECOL EVOL, V33, P427, DOI 10.1016/j.tree.2018.04.002
   YI SX, 1987, J INSECT PHYSIOL, V33, P523, DOI 10.1016/0022-1910(87)90117-X
   2015, REF ORTH SCOTL ESS, P1
NR 73
TC 12
Z9 13
U1 2
U2 17
PU BMC
PI LONDON
PA CAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND
SN 1471-2148
J9 BMC EVOL BIOL
JI BMC Evol. Biol.
PD MAR 6
PY 2020
VL 20
IS 1
AR 34
DI 10.1186/s12862-020-1598-6
PG 14
WC Evolutionary Biology; Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Evolutionary Biology; Genetics & Heredity
GA KT5KH
UT WOS:000519052800001
PM 32138649
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Steinacher, M
   Joos, F
AF Steinacher, M.
   Joos, F.
TI Transient Earth system responses to cumulative carbon dioxide emissions:
   linearities, uncertainties, and probabilities in an
   observation-constrained model ensemble
SO BIOGEOSCIENCES
LA English
DT Article
ID CLIMATE-CHANGE; OCEAN ACIDIFICATION; ATMOSPHERIC CO2; SOIL RESPIRATION;
   TEMPERATURE; CYCLE; PROJECTIONS; SENSITIVITY; DYNAMICS; IMPACT
AB Information on the relationship between cumulative fossil CO2 emissions and multiple climate targets is essential to design emission mitigation and climate adaptation strategies. In this study, the transient response of a climate or environmental variable per trillion tonnes of CO2 emissions, termed TRE, is quantified for a set of impact-relevant climate variables and from a large set of multi-forcing scenarios extended to year 2300 towards stabilization. An similar to 1000-member ensemble of the Bern3D-LPJ carbon-climate model is applied and model outcomes are constrained by 26 physical and biogeochemical observational data sets in a Bayesian, Monte Carlo-type framework. Uncertainties in TRE estimates include both scenario uncertainty and model response uncertainty. Cumulative fossil emissions of 1000 Gt C result in a global mean surface air temperature change of 1.9 degrees C (68% confidence interval (c.i.): 1.3 to 2.7 degrees C), a decrease in surface ocean pH of 0.19 (0.18 to 0.22), and a steric sea level rise of 20 cm (13 to 27 cm until 2300). Linearity between cumulative emissions and transient response is high for pH and reasonably high for surface air and sea surface temperatures, but less pronounced for changes in Atlantic meridional overturning, Southern Ocean and tropical surface water saturation with respect to biogenic structures of calcium carbonate, and carbon stocks in soils. The constrained model ensemble is also applied to determine the response to a pulse-like emission and in idealized CO2-only simulations. The transient climate response is constrained, primarily by long-term ocean heat observations, to 1.7 degrees C (68% c.i.: 1.3 to 2.2 degrees C) and the equilibrium climate sensitivity to 2.9 degrees C (2.0 to 4.2 degrees C). This is consistent with results by CMIP5 models but inconsistent with recent studies that relied on short-term air temperature data affected by natural climate variability.
C1 [Steinacher, M.; Joos, F.] Univ Bern, Inst Phys, Climate & Environm Phys, CH-3012 Bern, Switzerland.
   [Steinacher, M.; Joos, F.] Univ Bern, Oeschger Ctr Climate Change Res, CH-3012 Bern, Switzerland.
C3 University of Bern; University of Bern
RP Steinacher, M (corresponding author), Univ Bern, Inst Phys, Climate & Environm Phys, CH-3012 Bern, Switzerland.; Steinacher, M (corresponding author), Univ Bern, Oeschger Ctr Climate Change Res, CH-3012 Bern, Switzerland.
EM steinacher@climate.unibe.ch
RI Steinacher, Marco/J-1527-2012; Joos, Fortunat/B-4118-2018
OI Joos, Fortunat/0000-0002-9483-6030; Steinacher,
   Marco/0000-0002-4795-1749
FU Swiss National Science Foundation; European Project CARBOCHANGE -
   European Commission's Seventh Framework Programme [264879];
   International Space Science Institute (ISSI)
FX This study was funded by the Swiss National Science Foundation and the
   European Project CARBOCHANGE (264879), which received funding from the
   European Commission's Seventh Framework Programme (FP7/20072013). We
   also acknowledge the support from the International Space Science
   Institute (ISSI). This publication is an outcome of the ISSI's Working
   Group on "Carbon Cycle Data Assimilation: How to consistently assimilate
   multiple data streams".
CR Allen MR, 2014, NAT CLIM CHANGE, V4, P23, DOI 10.1038/NCLIMATE2077
   Allen MR, 2009, NATURE, V458, P1163, DOI 10.1038/nature08019
   [Anonymous], 1992, UNFCCC/INFORMAL/84 GE.05-62220 (E) 200705
   [Anonymous], 2011, GLOBALVIEW CO2 COOP
   [Anonymous], 2010, GEOPHYS RES LETT, DOI DOI 10.1029/2010GL043584
   [Anonymous], CONTRIBUTION WORKING, DOI [DOI 10.1017/CBO9781107415324, 10.1017/CBO9781107415324]
   Archer D, 1998, GLOBAL BIOGEOCHEM CY, V12, P259, DOI 10.1029/98GB00744
   Bartelink HH, 1998, TREE PHYSIOL, V18, P91
   Batjes NH, 1996, EUR J SOIL SCI, V47, P151, DOI [10.1111/j.1365-2389.1996.tb01386.x, 10.1111/ejss.12114_2]
   Bhat KS, 2012, ENVIRONMETRICS, V23, P345, DOI 10.1002/env.2149
   Bodman R, 2013, NAT CLIM CHANGE, V3, P725, DOI [10.1038/nclimate1903, 10.1038/NCLIMATE1903]
   Bozbiyik A, 2011, CLIM PAST, V7, P319, DOI 10.5194/cp-7-319-2011
   Brohan P, 2006, J GEOPHYS RES-ATMOS, V111, DOI 10.1029/2005JD006548
   Calvin K, 2012, ENERG ECON, V34, pS251, DOI 10.1016/j.eneco.2012.09.003
   Canadell JG, 2007, P NATL ACAD SCI USA, V104, P18866, DOI 10.1073/pnas.0702737104
   Charman DJ, 2013, BIOGEOSCIENCES, V10, P929, DOI 10.5194/bg-10-929-2013
   COLLATZ GJ, 1990, PLANT CELL ENVIRON, V13, P219, DOI 10.1111/j.1365-3040.1990.tb01306.x
   Conway T., 2011, Trends in atmospheric carbon dioxide
   Deutsch C, 2015, SCIENCE, V348, P1132, DOI 10.1126/science.aaa1605
   Dickson A., 2002, HDB METHODS ANAL VAR
   Edwards N, 2005, CLIM DYNAM, V24, P415, DOI 10.1007/s00382-004-0508-8
   Etheridge DM, 1996, J GEOPHYS RES-ATMOS, V101, P4115, DOI 10.1029/95JD03410
   FARQUHAR GD, 1980, PLANTA, V149, P78, DOI 10.1007/BF00386231
   Flato G., 2013, CLIMATE CHANGE 2013, P741, DOI DOI 10.1017/CBO9781107415324.020
   Forster P, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P129
   Friedlingstein P, 2011, NAT CLIM CHANGE, V1, P457, DOI 10.1038/NCLIMATE1302
   Frölicher TL, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/7/075002
   Frölicher TL, 2014, NAT CLIM CHANGE, V4, P40, DOI [10.1038/NCLIMATE2060, 10.1038/nclimate2060]
   Gangsto R, 2008, BIOGEOSCIENCES, V5, P1057, DOI 10.5194/bg-5-1057-2008
   Garcia H.E., 2010, NOAA ATLAS NESDIS 71, V4, P398
   Gattuso JP, 2015, SCIENCE, V349, DOI 10.1126/science.aac4722
   Gerber M, 2013, OCEAN MODEL, V64, P29, DOI 10.1016/j.ocemod.2012.12.012
   Gerber M, 2010, GLOBAL BIOGEOCHEM CY, V24, DOI 10.1029/2009GB003531
   Gerber M, 2009, GLOBAL BIOGEOCHEM CY, V23, DOI 10.1029/2008GB003247
   Gillett NP, 2013, J CLIMATE, V26, P6844, DOI 10.1175/JCLI-D-12-00476.1
   Global Soil Data Task Group, 2000, GRIDD SURF SEL SOIL, DOI [10.3334/ORNLDAAC/569, DOI 10.3334/ORNLDAAC/569]
   Gobron N, 2006, J GEOPHYS RES-ATMOS, V111, DOI 10.1029/2005JD006511
   Gregory JM, 2009, J CLIMATE, V22, P5232, DOI 10.1175/2009JCLI2949.1
   Gruber N, 2012, SCIENCE, V337, P220, DOI 10.1126/science.1216773
   Grübler A, 2007, TECHNOL FORECAST SOC, V74, P873, DOI 10.1016/j.techfore.2006.07.009
   Hallgren WS, 2000, GLOBAL CHANGE BIOL, V6, P483, DOI 10.1046/j.1365-2486.2000.00325.x
   Harris GR, 2013, CLIM DYNAM, V40, P2937, DOI 10.1007/s00382-012-1647-y
   Hartmann DL, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P159
   Hawkins E, 2009, B AM METEOROL SOC, V90, P1095, DOI 10.1175/2009BAMS2607.1
   Haxeltine A, 1996, FUNCT ECOL, V10, P551, DOI 10.2307/2390165
   Heinze C, 2004, GEOPHYS RES LETT, V31, DOI 10.1029/2004GL020613
   Herrington T, 2014, EARTH SYST DYNAM, V5, P409, DOI 10.5194/esd-5-409-2014
   Holden PB, 2013, BIOGEOSCIENCES, V10, P339, DOI 10.5194/bg-10-339-2013
   Holden PB, 2015, J APPL STAT, V42, P2038, DOI 10.1080/02664763.2015.1016412
   Holden PB, 2010, CLIM DYNAM, V35, P785, DOI 10.1007/s00382-009-0630-8
   Howes EL, 2015, FRONT MAR SCI, V2, DOI 10.3389/fmars.2015.00036
   Huang BY, 2003, J CLIMATE, V16, P3344, DOI 10.1175/1520-0442(2003)016<3344:OHUITC>2.0.CO;2
   Huber M, 2014, NAT GEOSCI, V7, P651, DOI [10.1038/ngeo2228, 10.1038/NGEO2228]
   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
   IPCC, 1995, CLIM CHANG 1994 RAD, P11
   JENKINSON DS, 1990, PHILOS T R SOC B, V329, P361, DOI 10.1098/rstb.1990.0177
   Joos F, 2013, ATMOS CHEM PHYS, V13, P2793, DOI 10.5194/acp-13-2793-2013
   Joos F, 1999, SCIENCE, V284, P464, DOI 10.1126/science.284.5413.464
   Joos F, 2001, GLOBAL BIOGEOCHEM CY, V15, P891, DOI 10.1029/2000GB001375
   Joos F, 1996, TELLUS B, V48, P397, DOI 10.1034/j.1600-0889.1996.t01-2-00006.x
   Joos F., 2011, OCEAN ACIDIFICATION, P319
   Karl TR, 2015, SCIENCE, V348, P1469, DOI 10.1126/science.aaa5632
   Keeling C.D., 2005, ATMOSPHERIC CO2 RECO
   Keith H, 2009, P NATL ACAD SCI USA, V106, P11635, DOI 10.1073/pnas.0901970106
   Kergoat L, 1998, J HYDROL, V212, P268, DOI 10.1016/S0022-1694(98)00211-X
   Key RM, 2004, GLOBAL BIOGEOCHEM CY, V18, DOI 10.1029/2004GB002247
   Knutti R, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL023294
   Knutti R, 2003, CLIM DYNAM, V21, P257, DOI 10.1007/s00382-003-0345-1
   Knutti R, 2002, NATURE, V416, P719, DOI 10.1038/416719a
   Knutti R, 2008, NAT GEOSCI, V1, P735, DOI 10.1038/ngeo337
   Krasting JP, 2014, GEOPHYS RES LETT, V41, P2520, DOI 10.1002/2013GL059141
   Kummer JR, 2014, GEOPHYS RES LETT, V41, P3565, DOI 10.1002/2014GL060046
   Kwon EY, 2009, NAT GEOSCI, V2, P630, DOI 10.1038/NGEO612
   LEVERENZ JW, 1988, PHYSIOL PLANTARUM, V74, P332, DOI 10.1111/j.1399-3054.1988.tb00639.x
   Levitus S, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2012GL051106
   Little CM, 2013, NAT CLIM CHANGE, V3, P654, DOI [10.1038/nclimate1845, 10.1038/NCLIMATE1845]
   LLOYD J, 1994, FUNCT ECOL, V8, P315, DOI 10.2307/2389824
   Locarnini R.A., 2010, World Ocean Atlas 2009, Volume 1: Temperature, V1, P1
   Luyssaert S, 2007, GLOBAL CHANGE BIOL, V13, P2509, DOI 10.1111/j.1365-2486.2007.01439.x
   Lyman JM, 2010, NATURE, V465, P334, DOI 10.1038/nature09043
   Magnani F, 1998, PLANT CELL ENVIRON, V21, P867, DOI 10.1046/j.1365-3040.1998.00328.x
   Maier-Reimer E., 1987, CLIM DYNAM, V2, P63
   Marotzke J, 2015, NATURE, V517, P565, DOI 10.1038/nature14117
   Matthews HD, 2009, NATURE, V459, P829, DOI 10.1038/nature08047
   MCKAY MD, 1979, TECHNOMETRICS, V21, P239, DOI 10.2307/1268522
   McNeil BI, 2007, TELLUS B, V59, P191, DOI 10.1111/j.1600-0889.2006.00241.x
   Meinshausen M, 2011, CLIMATIC CHANGE, V109, P213, DOI 10.1007/s10584-011-0156-z
   Meinshausen M, 2009, NATURE, V458, P1158, DOI 10.1038/nature08017
   Moss RH, 2010, NATURE, V463, P747, DOI 10.1038/nature08823
   Müller SA, 2008, GLOBAL BIOGEOCHEM CY, V22, DOI 10.1029/2007GB003065
   Müller SA, 2006, J CLIMATE, V19, P5479, DOI 10.1175/JCLI3911.1
   Murphy JM, 2004, NATURE, V430, P768, DOI 10.1038/nature02771
   Myhre G, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P659
   Nieves V, 2015, SCIENCE, V349, P532, DOI 10.1126/science.aaa4521
   Olson R J., 2001, NPP Multi- Biome: NPP and Driver Data for Ecosystem Model-Data Intercomparison
   Olson R, 2012, J GEOPHYS RES-ATMOS, V117, DOI 10.1029/2011JD016620
   Orr J.C., 2011, Ocean Acidification, P41
   Orr JC, 2005, NATURE, V437, P681, DOI 10.1038/nature04095
   Otto A, 2013, NAT GEOSCI, V6, P415, DOI 10.1038/ngeo1836
   Parekh P, 2008, PALEOCEANOGRAPHY, V23, DOI 10.1029/2007PA001531
   Peters GP, 2013, NAT CLIM CHANGE, V3, P4, DOI 10.1038/nclimate1783
   Pfister PL, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/1/014010
   Plattner GK, 2001, TELLUS B, V53, P564, DOI 10.1034/j.1600-0889.2001.530504.x
   Portner H.-O., 2011, OCEAN ACIDIFICATION, P154
   Prentice IC, 2001, CLIMATE CHANGE 2001: THE SCIENTIFIC BASIS, P183
   RAICH JW, 1992, TELLUS B, V44, P81, DOI 10.1034/j.1600-0889.1992.t01-1-00001.x
   Ritz SP, 2011, QUATERNARY SCI REV, V30, P3728, DOI 10.1016/j.quascirev.2011.09.021
   Ritz SP, 2011, J CLIMATE, V24, P349, DOI 10.1175/2010JCLI3351.1
   Roberts CD, 2015, NAT CLIM CHANGE, V5, P337, DOI 10.1038/nclimate2531
   Roemmich D, 2015, NAT CLIM CHANGE, V5, P240, DOI [10.1038/NCLIMATE2513, 10.1038/nclimate2513]
   Rogelj J, 2011, NAT CLIM CHANGE, V1, P413, DOI 10.1038/NCLIMATE1258
   Schleussner CF, 2014, CLIMATIC CHANGE, V127, P579, DOI 10.1007/s10584-014-1265-2
   Schmittner A, 2009, GLOBAL BIOGEOCHEM CY, V23, DOI 10.1029/2008GB003421
   Schwartz SE, 2012, SURV GEOPHYS, V33, P745, DOI 10.1007/s10712-012-9180-4
   Sherwood SC, 2010, P NATL ACAD SCI USA, V107, P9552, DOI 10.1073/pnas.0913352107
   Shindell D, 2014, NAT CLIM CHANGE, V4, P742, DOI 10.1038/nclimate2346
   Shindell DT, 2014, NAT CLIM CHANGE, V4, P274, DOI [10.1038/NCLIMATE2136, 10.1038/nclimate2136]
   Shine KP, 2005, CLIMATIC CHANGE, V68, P281, DOI 10.1007/s10584-005-1146-9
   SIEGENTHALER U, 1978, SCIENCE, V199, P388, DOI 10.1126/science.199.4327.388
   Sitch S, 2003, GLOBAL CHANGE BIOL, V9, P161, DOI 10.1046/j.1365-2486.2003.00569.x
   Spahni R, 2013, CLIM PAST, V9, P1287, DOI 10.5194/cp-9-1287-2013
   Stainforth DA, 2014, NAT CLIM CHANGE, V4, P248, DOI 10.1038/nclimate2172
   Steinacher M, 2009, BIOGEOSCIENCES, V6, P515, DOI 10.5194/bg-6-515-2009
   Steinacher M, 2013, NATURE, V499, P197, DOI 10.1038/nature12269
   Stocker BD, 2014, TELLUS B, V66, DOI 10.3402/tellusb.v66.23188
   Stocker TF, 2013, SCIENCE, V339, P280, DOI 10.1126/science.1232468
   Strassmann KM, 2008, TELLUS B, V60, P583, DOI 10.1111/j.1600-0889.2008.00340.x
   Strassmann KM, 2009, CLIM DYNAM, V33, P737, DOI 10.1007/s00382-008-0505-4
   Tarnocai C, 2009, GLOBAL BIOGEOCHEM CY, V23, DOI 10.1029/2008GB003327
   Tarnocai C., 2007, NORTHERN CIRCUMPOLAR
   Trumbore S, 2000, ECOL APPL, V10, P399, DOI 10.1890/1051-0761(2000)010[0399:AOSOMA]2.0.CO;2
   United Nations, 2015, FCCCCP2015L9 UN
   United Nations, 2010, FCCCCP20107ADD1 UN
   van der Werf GR, 2014, EARTH SYST DYNAM, V5, P375, DOI 10.5194/esd-5-375-2014
   Van Vuuren DP, 2008, P NATL ACAD SCI USA, V105, P15258, DOI 10.1073/pnas.0711129105
   von Schuckmann K, 2011, OCEAN SCI, V7, P783, DOI 10.5194/os-7-783-2011
   Weyant JR, 2006, ENERG J, P1
   Wigley TML, 2001, SCIENCE, V293, P451, DOI 10.1126/science.1061604
   Williamson D, 2013, CLIM DYNAM, V41, P1703, DOI 10.1007/s00382-013-1896-4
   Wong PP, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P361
   Zaehle S, 2005, GLOBAL BIOGEOCHEM CY, V19, DOI 10.1029/2004GB002395
   Zickfeld K, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2011GL050205
   Zickfeld K, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/3/031001
   Zickfeld K, 2009, P NATL ACAD SCI USA, V106, P16129, DOI 10.1073/pnas.0805800106
NR 144
TC 36
Z9 38
U1 1
U2 32
PU COPERNICUS GESELLSCHAFT MBH
PI GOTTINGEN
PA BAHNHOFSALLEE 1E, GOTTINGEN, 37081, GERMANY
SN 1726-4170
EI 1726-4189
J9 BIOGEOSCIENCES
JI Biogeosciences
PY 2016
VL 13
IS 4
BP 1071
EP 1103
DI 10.5194/bg-13-1071-2016
PG 33
WC Ecology; Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Geology
GA DG4ZR
UT WOS:000372082200013
OA Green Published, gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Butts, M
   Drews, M
   Larsen, MAD
   Lerer, S
   Rasmussen, SH
   Grooss, J
   Overgaard, J
   Refsgaard, JC
   Christensen, OB
   Christensen, JH
AF Butts, Michael
   Drews, Martin
   Larsen, Morten A. D.
   Lerer, Sara
   Rasmussen, Soren H.
   Grooss, Jesper
   Overgaard, Jesper
   Refsgaard, Jens C.
   Christensen, Ole B.
   Christensen, Jens H.
TI Embedding complex hydrology in the regional climate system - Dynamic
   coupling across different modelling domains
SO ADVANCES IN WATER RESOURCES
LA English
DT Article
DE Climate change; Water resources management; Dynamic model coupling;
   Groundwater-atmosphere interaction; Atmospheric feedback; Adaptation
ID EUROPEAN CLIMATE; SURFACE; ENERGY; IMPACT; PERFORMANCE; ENSEMBLE; SHE;
   PARAMETERIZATION; REPRESENTATION; SIMULATIONS
AB To improve our understanding of the impacts of feedback between the atmosphere and the terrestrial water cycle including groundwater and to improve the integration of water resource management modelling for climate adaption we have developed a dynamically coupled climate-hydrological modelling system. The OpenMI modelling interface is used to couple a comprehensive hydrological modelling system, MIKE SHE running on personal computers, and a regional climate modelling system, HIRHAM running on a high performance computing platform. The coupled model enables two-way interaction between the atmosphere and the groundwater via the land surface and can represent the lateral movement of water in both the surface and subsurface and their interactions, not normally accounted for in climate models. Meso-scale processes are important for climate in general and rainfall in particular. Hydrological impacts are assessed at the catchment scale, the most important scale for water management. Feedback between groundwater, the land surface and the atmosphere occurs across a range of scales. Recognising this, the coupling was developed to allow dynamic exchange of water and energy at the catchment scale embedded within a larger meso-scale modelling domain. We present the coupling methodology used and describe the challenges in representing the exchanges between models and across scales. The coupled model is applied to one-way and two-way coupled simulations for a managed groundwater-dominated catchment, the Skjern River, Denmark. These coupled model simulations are evaluated against field observations and then compared with uncoupled climate and hydrological model simulations. Exploratory simulations show significant differences, particularly in the summer for precipitation and evapotranspiration the coupled model including groundwater and the RCM where groundwater is neglected. However, the resulting differences in the net precipitation and the catchment runoff in this groundwater dominated catchment were small. The need for further decadal scale simulations to understand the differences and insensitivity is highlighted. (C) 2014 Elsevier Ltd. All rights reserved.
C1 [Butts, Michael; Lerer, Sara; Grooss, Jesper; Overgaard, Jesper] DHI, DK-2970 Horsholm, Denmark.
   [Drews, Martin; Rasmussen, Soren H.; Christensen, Ole B.; Christensen, Jens H.] Danish Meteorol Inst, DK-2100 Copenhagen, Denmark.
   [Larsen, Morten A. D.] Univ Copenhagen, Dept Geosci & Nat Resource Management, DK-1350 Copenhagen, Denmark.
   [Refsgaard, Jens C.] Geol Survey Denmark & Greenland GEUS, DK-1350 Copenhagen K, Denmark.
   [Drews, Martin; Larsen, Morten A. D.] Tech Univ Denmark, Dept Engn Management, DK-4000 Roskilde, Denmark.
   [Lerer, Sara] Tech Univ Denmark, Dept Environm Engn, DK-2800 Lyngby, Denmark.
   [Rasmussen, Soren H.] EnviDan, DK-2770 Kastrup, Denmark.
C3 Danish Hydraulic Institute (DHI); Danish Meteorological Institute DMI;
   University of Copenhagen; Geological Survey Of Denmark & Greenland;
   Technical University of Denmark; Technical University of Denmark
RP Butts, M (corresponding author), DHI, Agern Alle 5, DK-2970 Horsholm, Denmark.
EM mib@dhigroup.com; mard@dtu.dk; madla@dtu.dk; smrl@env.dtu.dk;
   shr@envidan.dk; jgr@dhigroup.com; jov@dhigroup.com; jcr@geus.dk;
   obc@dmi.dk; jhc@dmi.dk
RI Butts, Michael/JZE-3703-2024; Christensen, Ole/E-4417-2013; Larsen,
   Morten/HSG-6811-2023; Christensen, Jens Hesselbjerg/C-4162-2013; Larsen,
   Morten Andreas Dahl/F-5185-2015; Drews, Martin/E-8081-2017; Refsgaard,
   Jens Christian/G-5274-2011
OI Butts, Michael/0000-0003-1234-3580; Christensen, Jens
   Hesselbjerg/0000-0002-9908-8203; Larsen, Morten Andreas
   Dahl/0000-0002-7478-5416; Drews, Martin/0000-0002-3532-4780; Refsgaard,
   Jens Christian/0000-0003-0420-349X
FU DHI; Danish Meteorological Institute; Technical University of Denmark;
   Danish Strategic Research Council [DSF-EnMi 2104-07-0008, HYACINTS-521];
   Centre for Regional Change in the Earth System (CRES) [DSF-EnMi
   09-066868]
FX The present study was funded with the support from DHI, the Danish
   Meteorological Institute, the Technical University of Denmark and from
   the Danish Strategic Research Council for the project 520 HYdrological
   Modelling for Assessing Climate Change Impacts at differeNT Scales
   (HYACINTS-521 www.hyacints.dk) under Contract No: DSF-EnMi 2104-07-0008
   and partly through its support of the Centre for Regional Change in the
   Earth System (CRES;www.cres-centre.dk) under Contract No. DSF-EnMi
   09-066868. The authors would like to acknowledge the valuable assistance
   of Jacob Gudbjerg in coding the links between OpenMI and HIRHAM.
CR ABBOTT MB, 1986, J HYDROL, V87, P61, DOI 10.1016/0022-1694(86)90115-0
   ABBOTT MB, 1986, J HYDROL, V87, P45, DOI 10.1016/0022-1694(86)90114-9
   [Anonymous], P IAHR INT GROUNDW S
   [Anonymous], THESIS DTU
   [Anonymous], QUANTIFICATION REDUC
   [Anonymous], 2012, CHINA WATER RESOUR
   [Anonymous], 964 DMI
   [Anonymous], 2004, USER MANUAL
   [Anonymous], CALIBRATION DI UNPUB
   [Anonymous], IAHS PUBL
   [Anonymous], 459 NCAR
   [Anonymous], 1969, Journal of Hydrology, v
   [Anonymous], 349 MPIM
   [Anonymous], RESULTS FULL C UNPUB
   [Anonymous], 2006, 0617 DMI
   Bates B., 2008, Climate change and water, DOI DOI 10.1029/90EO00112
   BERGKAMP G, 2003, ADAPTATION WATER MAN
   Best MJ, 2011, GEOSCI MODEL DEV, V4, P677, DOI 10.5194/gmd-4-677-2011
   Betts AK, 2009, J ADV MODEL EARTH SY, V1, DOI 10.3894/JAMES.2009.1.4
   Blyth E., 2006, Global Change Newsletter, P9
   Boberg F, 2010, CLIM DYNAM, V35, P1509, DOI 10.1007/s00382-009-0683-8
   Boberg F, 2009, CLIM DYNAM, V32, P1097, DOI 10.1007/s00382-008-0446-y
   Bovolo CI, 2009, ENVIRON RES LETT, V4, DOI 10.1088/1748-9326/4/3/035001
   Butts M., 2010, Innovations in Watershed Management under Land Use and Climate Change. Proceedings of the 2010 Watershed Management Conference, Madison, Wisconsin, USA, 23-27 August 2010, P1002
   Butts MB, 2004, J HYDROL, V298, P242, DOI 10.1016/j.jhydrol.2004.03.042
   Christensen JH, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL035694
   Christensen JH, 2007, CLIMATIC CHANGE, V81, P7, DOI 10.1007/s10584-006-9210-7
   Craig AP, 2005, INT J HIGH PERFORM C, V19, P309, DOI 10.1177/1094342005056117
   Davin EL, 2011, CLIM DYNAM, V37, P1889, DOI 10.1007/s00382-011-1019-z
   Dee DP, 2011, Q J ROY METEOR SOC, V137, P553, DOI 10.1002/qj.828
   Famiglietti J. S., 1990, Land surface-atmosphere interactions for climate modeling: observations, models and analysis., P179
   Feyen L, 2009, J GEOPHYS RES-ATMOS, V114, DOI 10.1029/2008JD011438
   Fowler HJ, 2007, INT J CLIMATOL, V27, P1547, DOI 10.1002/joc.1556
   Giorgi F, 1997, REV GEOPHYS, V35, P413, DOI 10.1029/97RG01754
   Gochis D.J., 2013, The WRF-Hydro model technical description and user's guide
   Goodall JL, 2013, ENVIRON MODELL SOFTW, V46, P250, DOI 10.1016/j.envsoft.2013.03.019
   Graham DN, 2006, WATERSHED MODELS, P245
   Graham LP, 2004, AMBIO, V33, P235, DOI 10.1639/0044-7447(2004)033[0235:CCEORF]2.0.CO;2
   Green TR, 2011, J HYDROL, V405, P532, DOI 10.1016/j.jhydrol.2011.05.002
   Gregersen JB, 2007, J HYDROINFORM, V9, P175, DOI 10.2166/hydro.2007.023
   Gregersen J.B., 2005, Advances in Geosciences, V4, P37, DOI DOI 10.5194/ADGEO-4-37-2005
   Greve MH, 2007, GEOGR TIDSSKR-DEN, V107, P1
   Henriksen HJ, 2008, J HYDROL, V348, P224, DOI 10.1016/j.jhydrol.2007.09.056
   Hohenegger C, 2008, METEOROL Z, V17, P383, DOI 10.1127/0941-2948/2008/0303
   Hojberg AL, 2013, ENVIRON MODELL SOFTW, V40, P202, DOI 10.1016/j.envsoft.2012.09.010
   Holt TR, 2006, MON WEATHER REV, V134, P113, DOI 10.1175/MWR3057.1
   Hughes JD, 2008, GROUND WATER, V46, P797, DOI 10.1111/j.1745-6584.2008.00500.x
   Jensen KH, 2011, VADOSE ZONE J, V10, P1, DOI 10.2136/vzj2011.0006
   Kendon EJ, 2012, J CLIMATE, V25, P5791, DOI 10.1175/JCLI-D-11-00562.1
   Kjellström E, 2010, CLIM RES, V44, P135, DOI 10.3354/cr00932
   Larsen MAD, 2013, CLIM DYNAM, V40, P2903, DOI 10.1007/s00382-012-1513-y
   Larson J, 2005, INT J HIGH PERFORM C, V19, P277, DOI 10.1177/1094342005056115
   Lucas-Picher P, 2012, J GEOPHYS RES-ATMOS, V117, DOI 10.1029/2011JD016267
   Lucas-Picher P, 2011, J HYDROMETEOROL, V12, P849, DOI 10.1175/2011JHM1327.1
   Maxwell RM, 2008, NAT GEOSCI, V1, P665, DOI 10.1038/ngeo315
   Maxwell RM, 2007, ADV WATER RESOUR, V30, P2447, DOI 10.1016/j.advwatres.2007.05.018
   Maxwell RM, 2011, MON WEATHER REV, V139, P96, DOI 10.1175/2010MWR3392.1
   Michalakes J., 2001, Developments in Teracomputing, P269, DOI [10.1142/97898127996850024, DOI 10.1142/97898127996850024]
   Mölders N, 2002, ATMOS RES, V63, P3, DOI 10.1016/S0169-8095(02)00002-9
   Nikulin G, 2012, J CLIMATE, V25, P6057, DOI 10.1175/JCLI-D-11-00375.1
   Overgaard J, 2006, BIOGEOSCIENCES, V3, P229, DOI 10.5194/bg-3-229-2006
   Rasmussen SH, 2012, J HYDROL, V426, P63, DOI 10.1016/j.jhydrol.2012.01.014
   Redler R, 2010, GEOSCI MODEL DEV, V3, P87, DOI 10.5194/gmd-3-87-2010
   Refsgaard JC, 2014, CLIMATIC CHANGE, V122, P271, DOI 10.1007/s10584-013-0990-2
   Ridler ME, 2012, J HYDROL, V436, P1, DOI 10.1016/j.jhydrol.2012.01.047
   Rihani JF, 2010, WATER RESOUR RES, V46, DOI 10.1029/2010WR009111
   Ringgaard R, 2011, VADOSE ZONE J, V10, P54, DOI 10.2136/vzj2009.0181
   Seaby LP, 2013, J HYDROL, V486, P479, DOI 10.1016/j.jhydrol.2013.02.015
   SELLERS PJ, 1992, J GEOPHYS RES-ATMOS, V97, P18345, DOI 10.1029/92JD02111
   SHUTTLEWORTH WJ, 1985, Q J ROY METEOR SOC, V111, P839, DOI 10.1256/smsqj.46909
   Solomon S, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P1
   Stieglitz M, 1997, J CLIMATE, V10, P118, DOI 10.1175/1520-0442(1997)010<0118:AEATMT>2.0.CO;2
   Stisen S, 2012, HYDROL EARTH SYST SC, V16, P4157, DOI 10.5194/hess-16-4157-2012
   Stisen S, 2011, J HYDROL, V409, P337, DOI 10.1016/j.jhydrol.2011.08.030
   Stisen S, 2011, VADOSE ZONE J, V10, P37, DOI 10.2136/vzj2010.0001
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Stoll S, 2011, HYDROL EARTH SYST SC, V15, P21, DOI 10.5194/hess-15-21-2011
   Taylor RG, 2013, NAT CLIM CHANGE, V3, P322, DOI [10.1038/nclimate1744, 10.1038/NCLIMATE1744]
   Unden P., 2002, The, HIRLAM-5 Scientific Documentation
   Valcke S, 2013, GEOSCI MODEL DEV, V6, P373, DOI 10.5194/gmd-6-373-2013
   Van der Linden P., 2009, ENSEMBLES; Climate change and its impacts: Summary ofresearch and results from the ENSEMBLES project, P160
   van Roosmalen L, 2010, J HYDROL, V380, P406, DOI 10.1016/j.jhydrol.2009.11.014
   Wang CG, 2013, Q J ROY METEOR SOC, V139, P1964, DOI 10.1002/qj.2081
   Warner JC, 2008, ENVIRON MODELL SOFTW, V23, P1240, DOI 10.1016/j.envsoft.2008.03.002
   Zampieri M, 2012, J HYDROL, V420, P72, DOI 10.1016/j.jhydrol.2011.11.041
NR 85
TC 35
Z9 37
U1 0
U2 51
PU ELSEVIER SCI LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
SN 0309-1708
EI 1872-9657
J9 ADV WATER RESOUR
JI Adv. Water Resour.
PD DEC
PY 2014
VL 74
BP 166
EP 184
DI 10.1016/j.advwatres.2014.09.004
PG 19
WC Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Water Resources
GA AU3PE
UT WOS:000345525000014
DA 2025-01-10
ER

PT J
AU Hao, SG
   Liu, CX
   Ma, C
   Guo, W
   Kang, L
AF Hao, Shuguang
   Liu, Chunxiang
   Ma, Chuan
   Guo, Wei
   Kang, Le
TI Embryonic Development of Grasshopper Populations Along Latitudinal
   Gradients Reveal Differential Thermoaccumulation for Adaptation to
   Climate Warming
SO FRONTIERS IN ECOLOGY AND EVOLUTION
LA English
DT Article
DE Chorthippus dubius; embryonic development; diapause; climate warming;
   mitochondrial DNA
ID GEOGRAPHIC-VARIATION; DEVELOPMENT TIME; BERGMANNS RULE; BODY-SIZE;
   GROWTH; TEMPERATURE; RESPONSES; ORTHOPTERA; CONSERVATION; ECTOTHERMS
AB Climate warming has a remarkable effect on the distribution, phenology, and development of insects. Although the embryonic development and phenology of non-diapause grasshopper species are more susceptible to warming than those of diapause species, the responses of developmental traits in conspecifically different populations to climate warming remain unknown. Here, we compared the mtDNA sequences and embryonic development of eight populations of grasshopper species (Chorthippus dubius) in field-based manipulated warming and laboratory experiments. The mtDNA sequences showed a significant genetic differentiation of the southernmost population from the other seven populations on the Mongolian Plateau. The embryonic development of the southernmost population was significantly slower than those of the northern populations at the same incubation temperatures. Interestingly, laboratory experiments showed that a significant difference exists in the effective accumulated degree days (EADD) but not in the lower development threshold temperatures (LDTT) among the different populations. The high-latitude populations required less EADD than the low-latitude populations. The warming treatments significantly accelerated the embryonic development in the field and decreased duration from embryos to hatchlings of all eight populations in the incubation. In addition, warming treatments in field significantly increased EADD requirement per stage in the incubation. Linear regression model confirmed that the embryonic development characteristics of eight populations were correlated with the annual mean temperature and total precipitation of embryonic development duration. The results indicated that grasshopper species have evolved a strategy of adjusting their EADD but not their LDTT to adapt to temperature changes. The variations in the EADD among the different populations enabled the grasshopper eggs to buffer the influences of higher temperatures on development and preserve their univoltine nature in temperate regions while encountering warmer climatic conditions. Thus, the findings of this study is valuable for our understanding species variation and evolution, and as such has direct implication for modeling biological response to climate warming.
C1 [Hao, Shuguang; Liu, Chunxiang; Ma, Chuan; Guo, Wei; Kang, Le] Chinese Acad Sci, Inst Zool, State Key Lab Integrated Management Pest Insects, Beijing, Peoples R China.
   [Guo, Wei; Kang, Le] Univ Chinese Acad Sci, CAS Ctr Excellence Biot Interact, Beijing, Peoples R China.
   [Kang, Le] Chinese Acad Sci, Beijing Inst Life Sci, Beijing, Peoples R China.
C3 Chinese Academy of Sciences; Institute of Zoology, CAS; Chinese Academy
   of Sciences; University of Chinese Academy of Sciences, CAS; Chinese
   Academy of Sciences
RP Guo, W; Kang, L (corresponding author), Chinese Acad Sci, Inst Zool, State Key Lab Integrated Management Pest Insects, Beijing, Peoples R China.; Guo, W; Kang, L (corresponding author), Univ Chinese Acad Sci, CAS Ctr Excellence Biot Interact, Beijing, Peoples R China.; Kang, L (corresponding author), Chinese Acad Sci, Beijing Inst Life Sci, Beijing, Peoples R China.
EM guowei@ioz.ac.cn; lkang@ioz.ac.cn
RI Kang, Le/ABD-1116-2022
OI Kang, Le/0000-0003-4262-2329
FU National Natural Science Foundation of China [31572459]; Knowledge
   Innovation Program in the Chinese Academy of Sciences
FX Funding This work was supported by the National Natural Science
   Foundation of China (Grant No. 31572459) and Knowledge Innovation
   Program in the Chinese Academy of Sciences (Grant No. KSCX2-YW-Z-1021).
CR Aragón P, 2010, ANIM CONSERV, V13, P363, DOI 10.1111/j.1469-1795.2009.00343.x
   Bale JS, 2002, GLOBAL CHANGE BIOL, V8, P1, DOI 10.1046/j.1365-2486.2002.00451.x
   Bey-Bienko GY., 1951, LOCUSTS GRASSHOPPERS
   Blanckenhorn WU, 2004, INTEGR COMP BIOL, V44, P413, DOI 10.1093/icb/44.6.413
   Bonebrake TC, 2012, ECOLOGY, V93, P449, DOI 10.1890/11-1187.1
   Buckley LB, 2015, P ROY SOC B-BIOL SCI, V282, DOI 10.1098/rspb.2015.0441
   Childebaev MK, 2001, TETHYS ENTOMOL RES, V3, P5
   De Frenne P, 2013, J ECOL, V101, P784, DOI 10.1111/1365-2745.12074
   Deutsch CA, 2008, P NATL ACAD SCI USA, V105, P6668, DOI 10.1073/pnas.0709472105
   DINGLE H, 1994, OECOLOGIA, V97, P179, DOI 10.1007/BF00323147
   Duffy GA, 2015, CURR OPIN INSECT SCI, V11, P84, DOI 10.1016/j.cois.2015.09.013
   Excoffier L, 2010, MOL ECOL RESOUR, V10, P564, DOI 10.1111/j.1755-0998.2010.02847.x
   García-Robledo C, 2016, P NATL ACAD SCI USA, V113, P680, DOI 10.1073/pnas.1507681113
   Gardner JL, 2011, TRENDS ECOL EVOL, V26, P285, DOI 10.1016/j.tree.2011.03.005
   GROETERS FR, 1992, EVOLUTION, V46, P245, DOI [10.2307/2409819, 10.1111/j.1558-5646.1992.tb01999.x]
   Guo K, 2009, GLOBAL CHANGE BIOL, V15, P2539, DOI 10.1111/j.1365-2486.2009.01861.x
   Hagen SB, 2007, ECOGRAPHY, V30, P299, DOI [10.1111/j.2007.0906-7590.04981.x, 10.1111/j.0906-7590.2007.04981.x]
   Hao SG, 2004, ENVIRON ENTOMOL, V33, P1528, DOI 10.1603/0046-225X-33.6.1528
   Hao SG, 2004, J APPL ENTOMOL, V128, P95, DOI 10.1046/j.1439-0418.2003.00810.x
   Harrington R, 2001, AGR FOREST ENTOMOL, V3, P233, DOI 10.1046/j.1461-9555.2001.00120.x
   Hassall C, 2014, GLOBAL CHANGE BIOL, V20, P475, DOI 10.1111/gcb.12340
   Kang Le, 1995, Entomologia Sinica, V2, P265
   Laugen AT, 2003, OECOLOGIA, V135, P548, DOI 10.1007/s00442-003-1229-0
   Leigh JW, 2015, METHODS ECOL EVOL, V6, P1110, DOI 10.1111/2041-210X.12410
   Li Hong-Chang, 2007, Acta Entomologica Sinica, V50, P361
   Librado P, 2009, BIOINFORMATICS, V25, P1451, DOI 10.1093/bioinformatics/btp187
   Liefting M, 2009, EVOLUTION, V63, P1954, DOI 10.1111/j.1558-5646.2009.00683.x
   Ma C, 2012, MOL ECOL, V21, P4344, DOI 10.1111/j.1365-294X.2012.05684.x
   Millien V, 2006, ECOL LETT, V9, P853, DOI 10.1111/j.1461-0248.2006.00928.x
   Niewiarowski PH, 2008, FUNCT ECOL, V22, P895, DOI 10.1111/j.1365-2435.2008.01441.x
   Nilsson-Örtman V, 2013, ECOL MONOGR, V83, P491, DOI 10.1890/12-1383.1
   Nilsson-Örtman V, 2013, ECOL LETT, V16, P64, DOI 10.1111/ele.12013
   Nilsson-Örtman V, 2012, ECOLOGY, V93, P1340
   Ohlberger J, 2013, FUNCT ECOL, V27, P991, DOI 10.1111/1365-2435.12098
   Parmesan C, 1999, NATURE, V399, P579, DOI 10.1038/21181
   Parmesan C, 2007, GLOBAL CHANGE BIOL, V13, P1860, DOI 10.1111/j.1365-2486.2007.01404.x
   Parmesan C, 2006, ANNU REV ECOL EVOL S, V37, P637, DOI 10.1146/annurev.ecolsys.37.091305.110100
   Parmesan C, 2013, ECOL LETT, V16, P58, DOI 10.1111/ele.12098
   Posada D, 2008, MOL BIOL EVOL, V25, P1253, DOI 10.1093/molbev/msn083
   Rasmann S, 2014, FUNCT ECOL, V28, P46, DOI 10.1111/1365-2435.12135
   RHYMER JM, 1992, J EVOLUTION BIOL, V5, P289, DOI 10.1046/j.1420-9101.1992.5020289.x
   Stefanescu C, 2003, GLOBAL CHANGE BIOL, V9, P1494, DOI 10.1046/j.1365-2486.2003.00682.x
   Teplitsky C, 2008, P NATL ACAD SCI USA, V105, P13492, DOI 10.1073/pnas.0800999105
   van Asch M, 2013, NAT CLIM CHANGE, V3, P244, DOI [10.1038/NCLIMATE1717, 10.1038/nclimate1717]
   VANHORN SN, 1966, J MORPHOL, V120, P83, DOI 10.1002/jmor.1051200105
   Wu TJ, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0041764
   Yamahira K, 2002, ECOLOGY, V83, P1252, DOI 10.1890/0012-9658(2002)083[1252:IVILVI]2.0.CO;2
   Yamahira K, 2007, EVOLUTION, V61, P1577, DOI 10.1111/j.1558-5646.2007.00130.x
   Yin X.C, 1984, INSECTS QINGHAI TIBE
   Zera AJ, 2001, ANNU REV ECOL SYST, V32, P95, DOI 10.1146/annurev.ecolsys.32.081501.114006
   Zheng Z, 1998, ORTHOPTERA ACRIDOIDA
NR 51
TC 1
Z9 2
U1 2
U2 15
PU FRONTIERS MEDIA SA
PI LAUSANNE
PA AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND
SN 2296-701X
J9 FRONT ECOL EVOL
JI Front. Ecol. Evol.
PD NOV 23
PY 2021
VL 9
AR 736456
DI 10.3389/fevo.2021.736456
PG 12
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA XK7OD
UT WOS:000727649200001
OA gold
DA 2025-01-10
ER

PT J
AU Ansley, RJ
   Boutton, TW
   Jacoby, PW
AF Ansley, R. J.
   Boutton, T. W.
   Jacoby, P. W.
TI Root Biomass and Distribution Patterns in a Semi-Arid Mesquite Savanna:
   Responses to Long-Term Rainfall Manipulation
SO RANGELAND ECOLOGY & MANAGEMENT
LA English
DT Article
DE carbon isotope ratio; carbon sequestration; climate change; leaf water
   potential; root-to-shoot ratio; woody plant encroachment
ID WOODY PLANT ENCROACHMENT; HONEY MESQUITE; SOIL-MOISTURE;
   PROSOPIS-GLANDULOSA; WATER RELATIONS; DESERT SHRUBS; LAND-USE; GRASS;
   GROWTH; CARBON
AB Expansion of woody plants in North American grasslands and savannas is facilitated in part by root system adaptation to climatic extremes. Climatic extremes are predicted to become more common with global climate change and, as such, may accelerate woody expansion and/or infilling rates. We quantified root biomass and distribution patterns of the invasive woody legume, honey mesquite (Prosopis glandulosa), and associated grasses following a long-term rainfall manipulation experiment in a mixed grass savanna in the southern Great Plains (United States). Root systems of mature trees were containerized with vertical barriers installed to a depth of 270 cm, and soil moisture was manipulated with irrigation (Irrigated) or rainout shelters (Rainout). Other treatments included containerized, precipitation-only (Control) and noncontainerized, precipitation-only (Natural) trees. After 4 yr of treatment, soil cores to 270 cm depth were obtained, and mesquite root length density (RLD) and root mass, and grass root mass were quantified. Mesquite in the Rainout treatment increased coarse-root (>2 mm diameter) RLD and root mass at soil depths between 90 cm and 270 cm. In contrast, mesquite in the Irrigated treatment increased fine-root (<2 mm diameter) RLD and root mass between 30 cm and 270 cm depths, but did not increase total root mass (fine+coarse) compared to the Control. Mesquite root-to-shoot mass ratio was 2.8 to 4.6 times greater in Rainout than the other treatments. Leaf water stress was greatest in the Rainout treatment in the first year, but not in subsequent years, possibly the result of increased root growth. Leaf water use efficiency was lowest in the Irrigated treatment. The increase in coarse root growth during extended drought substantially increased mesquite belowground biomass and suggests an important mechanism by which woody plant encroachment into grasslands may alter below ground carbon stocks under climate change scenarios predicted for this region.
C1 [Ansley, R. J.] Texas A&M AgriLife Res, Vernon, TX 76385 USA.
   [Ansley, R. J.] Texas A&M Univ, Dept Ecosyst Sci & Management, College Stn, TX 76384 USA.
   [Boutton, T. W.] Texas A&M Univ, Dept Ecosyst Sci & Management, College Stn, TX 77843 USA.
   [Jacoby, P. W.] Washington State Univ, Dept Crop & Soil Sci, Pullman, WA 99164 USA.
C3 Texas A&M University System; Texas A&M University College Station; Texas
   A&M AgriLife Research; Texas A&M University System; Texas A&M University
   College Station; Texas A&M University System; Texas A&M University
   College Station; Washington State University
RP Ansley, RJ (corresponding author), Texas A&M AgriLife Res, POB 1658,11708 Highway 70 S, Vernon, TX 76385 USA.
EM jansley@ag.tamu.edu
RI Boutton, Thomas/C-5821-2016
OI Boutton, Thomas/0000-0002-7522-5728
FU University Lands-Surface Interests; University of Texas System, Midland,
   TX; Waggoner Foundation, Vernon, TX
FX Research was funded in part by the University Lands-Surface Interests,
   University of Texas System, Midland, TX and the Waggoner Foundation,
   Vernon, TX. The W. T. Waggoner Estate, Vernon, TX provided land area for
   the project.
CR [Anonymous], STABLE ISOTOPES ECOL
   Ansley RJ, 2007, US FOR SERV RMRS-P, P96
   Ansley RJ, 2010, GCB BIOENERGY, V2, P26, DOI 10.1111/j.1757-1707.2010.01036.x
   ANSLEY RJ, 1992, J ARID ENVIRON, V22, P147, DOI 10.1016/S0140-1963(18)30588-3
   Ansley RJ, 1998, J RANGE MANAGE, V51, P345, DOI 10.2307/4003421
   ANSLEY RJ, 1990, J RANGE MANAGE, V43, P436, DOI 10.2307/3899008
   ARCHER S, 1995, CLIMATIC CHANGE, V29, P91, DOI 10.1007/BF01091640
   Archer S., 2001, Global biogeochemical cycles in the climate system, P115, DOI [DOI 10.1016/B978-012631260-7/50011-X, 10.1016/B978-012631260-7/50011-X]
   Asner GP, 2003, GLOBAL CHANGE BIOL, V9, P316, DOI 10.1046/j.1365-2486.2003.00594.x
   Asner GP, 2004, ANNU REV ENV RESOUR, V29, P261, DOI 10.1146/annurev.energy.29.062403.102142
   Bai WM, 2010, GLOBAL CHANGE BIOL, V16, P1306, DOI 10.1111/j.1365-2486.2009.02019.x
   BELSKY AJ, 1994, ECOLOGY, V75, P922, DOI 10.2307/1939416
   Bohm W., 1979, Methods of studying root systems.
   Bond WJ, 2000, GLOBAL CHANGE BIOL, V6, P865, DOI 10.1046/j.1365-2486.2000.00365.x
   Boutton TW, 2010, J GEOPHYS RES-BIOGEO, V115, DOI [10.1029/2009JG0011R4, 10.1029/2009JG001184]
   BOUTTON T W, 1991, P155
   Boutton T.W., 2009, Soil Carbon Sequestration and the Greenhouse Effect, P181
   Boutton TW, 1999, RAPID COMMUN MASS SP, V13, P1263, DOI 10.1002/(SICI)1097-0231(19990715)13:13<1263::AID-RCM653>3.0.CO;2-J
   Canadell J, 1996, Oecologia, V108, P583, DOI 10.1007/BF00329030
   CASTELLANOS J, 1991, PLANT SOIL, V131, P225, DOI 10.1007/BF00009452
   Chew R.M., 1965, ECOL MONOGR, V35, P355
   Collins DBG, 2007, WATER RESOUR RES, V43, DOI 10.1029/2006WR005541
   Coplen T.B, 1996, GEOCHIM COSMOCHIM AC, V60, P3359, DOI [10.1016/0016-7037(96)00263-3, DOI 10.1016/0016-7037(96)00263-3]
   Dai X, 2006, J ENVIRON QUAL, V35, P1620, DOI 10.2134/jeq2005.0260
   Dawson TE, 1996, OECOLOGIA, V107, P13, DOI 10.1007/BF00582230
   FERNANDEZ OA, 1975, J ECOL, V63, P703, DOI 10.2307/2258746
   Gibbens RP, 2001, J ARID ENVIRON, V49, P221, DOI 10.1006/jare.2000.0784
   Gile LH, 1997, J ARID ENVIRON, V35, P39, DOI 10.1006/jare.1996.0157
   HARRIS GA, 1989, AGRON J, V81, P935, DOI 10.2134/agronj1989.00021962008100060017x
   HEITSCHMIDT RK, 1988, J RANGE MANAGE, V41, P227, DOI 10.2307/3899173
   HODGKINSON KC, 1978, OECOLOGIA, V34, P353, DOI 10.1007/BF00344912
   Hughes RF, 2006, GLOBAL CHANGE BIOL, V12, P1733, DOI 10.1111/J.1365-2486.2006.01210.x
   Jackson RB, 1997, P NATL ACAD SCI USA, V94, P7362, DOI 10.1073/pnas.94.14.7362
   Jackson RB, 1996, OECOLOGIA, V108, P389, DOI 10.1007/BF00333714
   JACOBY PW, 1988, J RANGE MANAGE, V41, P83, DOI 10.2307/3898797
   JOHNSON HB, 1990, OECOLOGIA, V84, P176, DOI 10.1007/BF00318269
   Karl T. R., 2009, Global climate change impacts in the United States
   Kramp BA, 1998, SOUTHWEST NAT, V43, P300
   LEE CA, 1994, AM MIDL NAT, V132, P117, DOI 10.2307/2426206
   LEROUX X, 1995, OECOLOGIA, V104, P147, DOI 10.1007/BF00328579
   Ludwig JA., 1977, COLORADO STATE U SER, P85
   Maestre FT, 2009, ECOL LETT, V12, P930, DOI 10.1111/j.1461-0248.2009.01352.x
   McCulley RL, 2004, OECOLOGIA, V141, P620, DOI 10.1007/s00442-004-1687-z
   Midwood AJ, 1998, PLANT SOIL, V205, P13, DOI 10.1023/A:1004355423241
   National Assessment Synthesis Team, 2001, CLIM CHANG IMP US FD
   Ogle K, 2004, OECOLOGIA, V141, P282, DOI 10.1007/s00442-004-1507-5
   Padilla FM, 2007, FUNCT ECOL, V21, P489, DOI 10.1111/j.1365-2435.2007.01267.x
   Padilla FM, 2009, PLANT ECOL, V204, P261, DOI 10.1007/s11258-009-9589-0
   Parmesan C., 2004, OBSERVED IMPACT GLOB
   Reynolds JF, 1999, ECOL MONOGR, V69, P69, DOI 10.1890/0012-9615(1999)069[0069:IODODS]2.0.CO;2
   RICHARDS D, 1975, AUST J AGR RES, V26, P173, DOI 10.1071/AR9750173
   Robinson D, 2007, P ROY SOC B-BIOL SCI, V274, P2753, DOI 10.1098/rspb.2007.1012
   *SAS I, 2003, SAS STAT VERS 9 1 WI
   Schenk HJ, 2005, GEODERMA, V126, P129, DOI 10.1016/j.geoderma.2004.11.018
   Schenk HJ, 2002, J ECOL, V90, P480, DOI 10.1046/j.1365-2745.2002.00682.x
   Schenk HJ, 2002, ECOL MONOGR, V72, P311, DOI 10.1890/0012-9615(2002)072[0311:TGBOR]2.0.CO;2
   SCHLESINGER WH, 1990, SCIENCE, V247, P1043, DOI 10.1126/science.247.4946.1043
   Scholes RJ, 1997, ANNU REV ECOL SYST, V28, P517, DOI 10.1146/annurev.ecolsys.28.1.517
   Schwinning S, 2004, OECOLOGIA, V141, P191, DOI 10.1007/s00442-004-1683-3
   Seager R, 2007, SCIENCE, V316, P1181, DOI 10.1126/science.1139601
   Shelford V. E., 1963, The Ecology of North America
   Snyman HA, 2009, AGR ECOSYST ENVIRON, V130, P100, DOI 10.1016/j.agee.2008.12.003
   Tape K, 2006, GLOBAL CHANGE BIOL, V12, P686, DOI 10.1111/j.1365-2486.2006.01128.x
   TURNER NC, 1981, PLANT SOIL, V58, P339, DOI 10.1007/BF02180062
   Van Auken OW, 2009, J ENVIRON MANAGE, V90, P2931, DOI 10.1016/j.jenvman.2009.04.023
   Van Auken OW, 2000, ANNU REV ECOL SYST, V31, P197, DOI 10.1146/annurev.ecolsys.31.1.197
   VANVEGTEN JA, 1984, VEGETATIO, V56, P3
   Volder A., 2010, Global Change Biology, V16, P3349, DOI 10.1111/j.1365-2486.2009.02152.x
   Walter H., 1954, Vegetatio, V5-6, P6, DOI 10.1007/BF00299544
   Wigley BJ, 2010, GLOBAL CHANGE BIOL, V16, P964, DOI 10.1111/j.1365-2486.2009.02030.x
   Wilcox CS, 2004, J ARID ENVIRON, V56, P129, DOI 10.1016/S0140-1963(02)00324-5
   YODER CK, 1995, SOUTHWEST NAT, V40, P273
   Zou CB, 2005, OECOLOGIA, V145, P32, DOI 10.1007/s00442-005-0110-8
NR 73
TC 33
Z9 43
U1 5
U2 173
PU SOC RANGE MANAGEMENT
PI LAKEWOOD
PA 445 UNION BLVD, STE 230, LAKEWOOD, CO 80228-1259 USA
SN 1550-7424
EI 1551-5028
J9 RANGELAND ECOL MANAG
JI Rangel. Ecol. Manag.
PD MAR
PY 2014
VL 67
IS 2
BP 206
EP 218
DI 10.2111/REM-D-13-00119.1
PG 13
WC Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA AD4PI
UT WOS:000333232600010
DA 2025-01-10
ER

PT C
AU Calcagni, L
   Hensel, DS
   Hensel, MU
   Battisti, A
AF Calcagni, Livia
   Hensel, Defne Sunguroglu
   Hensel, Michael Ulrich
   Battisti, Alessandra
BE Ikoma, T
   Tabeta, S
   Lim, SH
   Wang, CM
TI A Performance-Based Design Framework for Floating Architecture.
   Trade-Offs and Correlations Between Requirements for Multiple Criteria
   Decision-Making Optimization
SO PROCEEDINGS OF THE THIRD WORLD CONFERENCE ON FLOATING SOLUTIONS, WCFS
   2023
SE Lecture Notes in Civil Engineering
LA English
DT Proceedings Paper
CT 3rd World Conference on Floating Solutions (WCFS)
CY AUG 28-29, 2023
CL Tokyo, JAPAN
DE Performance-based design; Floating architecture; Adaptation measures;
   Multiple criteria decision-making; Coastal areas
ID SEA-LEVEL RISE
AB Compared to inland settlements, coastal cities concentrate a large proportion of the global population and economic activity, while being exposed and vulnerable to a range of climate- and ocean-compounded hazards driven by climate change. Given the urgency of identifying efficient and sustainable climate adaptation strategies and designing climate-proof models of urban development, the research focuses on floating urban clusters as plug-in extensions of coastal cities. In particular, the study focuses on the identification of the requirements that make up the performancebased design framework (PBDF) for floating architecture. The PBDF is conceived as a meta-design tool for architects, urban planners, and policymakers, for advancing multiple criteria decision-making for floating architecture. Floating urban development is likely to take place in the context of coastal areas. The hypothesis is that the needs and design criteria are more similar to those related to the built environment than to those related to the offshore or naval industry. Therefore, the identification and categorization of performance requirements takes the urban-architectural prescriptive and performance-based norms as the starting point, while addressing the missing aspects from the perspective of offshore and shipping regulatory frameworks. First of all, an evidence-based assessment of performance guidelines and regulatory systems that are effective in different countries around the world is carried out. The PBDF is further integrated, weighted, and validated through a case study analysis to merge as much as possible theory and practice. Ultimately, the paper outlines the trade-offs and correlations between different performance requirements, as the PBDF is meant to emphasize the logical interaction between the different potential choices for the identification of different scenarios. Overall, this paper highlights how floating architecture and floating urban development of coastal cities can provide a viable adaptation strategy to the problem of rising sea levels, if appropriately addressed through a structured system of guidelines in accordance with Blue Economy principles and the Agenda 2030.
C1 [Calcagni, Livia; Battisti, Alessandra] Sapienza Univ Rome, Dept Panning Design & Technol Architecture, Via Flaminia 72, I-00196 Rome, Italy.
   [Calcagni, Livia; Hensel, Michael Ulrich] Vienna Univ Technol, Dept Digital Architecture & Planning, Karlspl 13, A-1040 Vienna, Austria.
   [Hensel, Defne Sunguroglu] Southeast Univ Nanjing, Sch Architecture, 2 Sipailou, Nanjing 210096, Peoples R China.
C3 Sapienza University Rome; Technische Universitat Wien; Southeast
   University - China
RP Calcagni, L (corresponding author), Sapienza Univ Rome, Dept Panning Design & Technol Architecture, Via Flaminia 72, I-00196 Rome, Italy.
EM livia.calcagni@uniroma1.it; defne.hensel@tum.de;
   michael.hensel@tuwien.ac.at; alessandra.battisti@uniroma1.it
RI Hensel, Defne/AAS-8536-2020; Calcagni, Livia/AAT-2080-2021
CR [Anonymous], 2019, IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, P321, DOI [10.1017/9781009157964.006, DOI 10.1017/9781009157964.006]
   [Anonymous], Queensland Development Code MP 3.1 Floating buildings of 16 November 2007 online
   Barbier EB, 2015, ESTUAR COAST SHELF S, V165, pA1, DOI 10.1016/j.ecss.2015.05.035
   Barker R, 2015, Aquatecture. Buildings and cities designed to live and work with water
   Battisti A, 2023, Equity in health and health promotion in urban areas, green energy and technology, DOI [10.1007/978-3-031-16182-713, DOI 10.1007/978-3-031-16182-713]
   Baumeister J, 2022, Cities+ 1m: urban development solutions for sea level rise
   Bednar-Friedl B., 2023, Climate Change 2022Impacts, Adaptation and Vulnerability, P1817, DOI DOI 10.1017/9781009325844.015
   Berman I, 2010, ARCHIT DESIGN, P66
   Ciampoli M, 2010, EARTH SPACE 2010 ENG, P2063
   Columbia B, 1993, Float home standard
   Dallinga R.P., 2010, CRUISE SHIP SEAKEEPI
   El-Shihy AA, 2019, ALEX ENG J, V58, P507, DOI 10.1016/j.aej.2019.05.003
   Flesche F, 2005, Water house
   Foka E, 2014, Water quality impact of floating houses: a study on the effects of dissolved oxygen levels
   Giurgiu Ioana Corina, 2022, WCFS2020: Proceedings of the Second World Conference on Floating Solutions. Lecture Notes in Civil Engineering (158), P423, DOI 10.1007/978-981-16-2256-4_26
   Groat Linda, 2013, Architectural research methods, V2nd
   Gromicko N, 2015, Inspecting floating homes
   Habibi S, 2015, Architectural Engineering Technology, DOI [10.4172/2168-9717.1000142, DOI 10.4172/2168-9717.1000142]
   Hensel M, 2013, PERFORMANCE-ORIENTED ARCHITECTURE: RETHINKING ARCHITECTURAL DESIGN AND THE BUILT ENVIRONMENT, P1, DOI 10.1002/9781118640630
   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
   IRCC, 2010, ABOUT US
   Kishore S, 2013, IEEE: the expertise to make smart grid a reality
   Lattke F, 2009, TES EnergyFacade-prefabricated timber based building system for improving the energy efficiency of the building envelope
   Losasso M, 2018, TECHNE, V15, P16, DOI 10.13128/Techne-23195
   Magni F., 2019, Climate proof planning
   Meacham B, 2005, BUILD RES INF, V33, P91, DOI 10.1080/0961321042000322780
   Meyer BC, 2010, LANDSCAPE URBAN PLAN, V98, P139, DOI 10.1016/j.landurbplan.2010.08.012
   Moon CH, 2014, 30 INT PLEA C 16 18
   Penning-Rowsell E, 2020, LANDSCAPE RES, V45, P395, DOI 10.1080/01426397.2019.1694881
   Piatek L, 2016, Displacing architecture? From floating houses to ocean habitats: expanding the building typology. Education for research, research for creativity, P273
   Picon A, 2013, Performalism: form and performance in digital architecture, P15
   Schwab K, 2019, Floating cities once seemed like sci-fi. Now the UN is getting on board
   Seattle Municipal Code, 2022, 23.60A.204- Floating structures and standards for house barges
   Space@Sea, 2019, A Catalogue of Technical Requirements and Best Practices for the Design
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Stopp H, 2010, Architecture Civil Engineering Environment, No. 4/2010, P81
   Storbjörk S, 2021, OCEAN COAST MANAGE, V210, DOI 10.1016/j.ocecoaman.2021.105732
   Thiebault S, 2018, The Mediterranean region under climate change: a scientific update
   UCCRN, 2018, UCRN technical report, P36
   UNDESA Program, 2018, World urbanization prospects: the 2018 revision
   Venhuizen H, 2000, Amfibisch Wonen. Amphibious living
   Wang KF, 2021, An investigation into environment-floating buildings in relation to sustainability indicators for planning and design process
   Watson CS, 2015, NAT CLIM CHANGE, V5, P565, DOI 10.1038/nclimate2635
   WHO, 2010, No.WHO/WKC/WHD/2010.1
   Wylson Anthony., 1986, Aquatecture: Architecture and Water
NR 45
TC 0
Z9 0
U1 0
U2 0
PU SPRINGER-VERLAG SINGAPORE PTE LTD
PI SINGAPORE
PA 152 BEACH ROAD, #21-01/04 GATEWAY EAST, SINGAPORE, 189721, SINGAPORE
SN 2366-2557
EI 2366-2565
BN 978-981-97-0497-2; 978-981-97-0495-8; 978-981-97-0494-1
J9 LECT NOTES CIVIL ENG
PY 2024
VL 465
BP 185
EP 208
DI 10.1007/978-981-97-0495-8_12
PG 24
WC Construction & Building Technology; Green & Sustainable Science &
   Technology; Engineering, Civil; Regional & Urban Planning
WE Conference Proceedings Citation Index - Science (CPCI-S); Conference Proceedings Citation Index - Social Science &amp; Humanities (CPCI-SSH)
SC Construction & Building Technology; Science & Technology - Other Topics;
   Engineering; Public Administration
GA BX4PD
UT WOS:001293054700012
DA 2025-01-10
ER

PT J
AU Wang, GF
   Guo, QY
   Zhou, XS
   Zhang, F
AF Wang, Guofeng
   Guo, Qinyang
   Zhou, Xinsheng
   Zhang, Fan
TI Spatial correlation network characteristics of embodied carbon transfer
   in global agricultural trade
SO ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
LA English
DT Article
DE Agricultural trade; Input-output model; Social network analysis; Block
   model; Climate adaptation
ID CHINA; NEUTRALITY
AB Agricultural carbon emission is an important cause of climate change, and the carbon transfer caused by agricultural trade is a key area related to carbon emissions of all countries. Based on the Eora database, this paper aims to constructs a multi-region input-output database of 185 countries or regions, analyzes a spatial correlation network of embodied net carbon transfer in global agricultural trade by using UCINET, selects multi-dimensional network measurement indicators, and comprehensively studies the global evolution characteristics and functional features of network plate role of embodied carbon transfer in the global agricultural trade. The result shows that the embodied net carbon transfer network of global agricultural trade is densely connected, the spatial correlation spillover effect is significant, and the edge of the network core structure is clear. On the one hand, the top four countries or regions in terms of embodied carbon outflow in agricultural trade are the USA, Australia, Vietnam, and China. On the other hand, the top four countries or regions of embodied carbon inflow are Malaysia, Central Africa, Singapore, and Serbia. From the perspective of outdegree, indegree, proximity centrality, and intermediary centrality, Cambodia, the Netherlands, Vietnam, Ghana, and South Africa, with the high frequency of the shortest path of the globally embodied net carbon transfer network, have a strong influence and linking facility in spatial correlation and have a strong control ability to the spatial correlation of other countries or regions. The embodied carbon emission network of global agricultural trade can be divided into four sectors: main spillover, two-way spillover, broker, and main benefit. The main spillover segment, constituted by the USA, India, Germany, and China, has significant embodied carbon spillover effects on the internal segment and other segments. It is the main embodied carbon spillover sector of embodied net carbon transfer of global agricultural trade. Countries should reasonably allocate the responsibility of carbon reduction according to the trading embodied carbon transfer and made efforts to optimize the export structure of agricultural products.
C1 [Wang, Guofeng; Guo, Qinyang; Zhou, Xinsheng] Shanxi Univ Finance & Econ, Fac Int Trade, Taiyuan 030006, Peoples R China.
   [Zhang, Fan] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China.
C3 Shanxi University Finance & Economics; Chinese Academy of Sciences;
   Institute of Geographic Sciences & Natural Resources Research, CAS
RP Zhang, F (corresponding author), Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China.
EM zhangf.ccap@igsnrr.ac.cn
RI Fan, Zhang/AAZ-3509-2021
OI Zhang, Fan/0000-0003-3453-0512
FU National Natural Science Foundation of China [72003111, 71903117]
FX This research was funded by the National Natural Science Foundation of
   China, grant numbers 72003111 and 71903117.
CR Abbasi KR, 2022, RENEW ENERG, V187, P390, DOI 10.1016/j.renene.2022.01.066
   Balogh J.M., 2020, INT J ENERGY EC POLI, V10, P401, DOI [10.32479/ijeep.8859, DOI 10.32479/IJEEP.8859]
   Balogh J M., 2017, Int. J. Energy Econ. Policy, V7/5, P217
   Beghin JC, 2021, APPL ECON PERSPECT P, V43, P500, DOI 10.1002/aepp.13124
   Cabernard L, 2021, SCI TOTAL ENVIRON, V755, DOI 10.1016/j.scitotenv.2020.142587
   Cao LJ, 2021, CHINA AGR ECON REV, V13, P1, DOI 10.1108/CAER-05-2020-0079
   Cui LB, 2019, COMPUT IND ENG, V128, P1040, DOI 10.1016/j.cie.2018.04.029
   De la Peña L, 2022, RESOUR CONSERV RECY, V177, DOI 10.1016/j.resconrec.2021.105957
   Deng XZ, 2017, J CLEAN PROD, V142, P758, DOI 10.1016/j.jclepro.2016.05.057
   Deng XZ, 2016, J GEOGR SCI, V26, P953, DOI 10.1007/s11442-016-1309-9
   FAO, 2020, The State of Agricultural Commodity Markets 2020, The State of Agricultural Commodity Markets 2020
   Hao Y, 2021, SCI TOTAL ENVIRON, V763, DOI 10.1016/j.scitotenv.2020.144183
   Irfan M, 2022, PERS INDIV DIFFER, V188, DOI 10.1016/j.paid.2021.111450
   Irfan M, 2021, TRANSPORT RES D-TR E, V100, DOI 10.1016/j.trd.2021.103049
   Irfan M, 2021, J CLEAN PROD, V292, DOI 10.1016/j.jclepro.2021.126008
   Irfan M, 2021, SUSTAIN PROD CONSUMP, V27, P312, DOI 10.1016/j.spc.2020.10.031
   Irfan M, 2020, ENERGY STRATEG REV, V32, DOI 10.1016/j.esr.2020.100540
   Jiang Si-Jian, 2020, Journal of Agro-Environment Science, V39, P762, DOI 10.11654/jaes.2020-0114
   Lun F, 2021, GLOBAL ENVIRON CHANG, V69, DOI 10.1016/j.gloenvcha.2021.102282
   Lynn J, 2021, CLIMATIC CHANGE, V169, DOI 10.1007/s10584-021-03233-7
   Müller-Casseres E, 2021, ENERGY, V237, DOI 10.1016/j.energy.2021.121547
   Muradov K., 2021, J EC STRUCT, V10, P1, DOI [10.1186/s40008-021-00245-5, DOI 10.1186/S40008-021-00245-5]
   Summary for Policymakers, 2001, CLIMATE CHANGE 2001, P2
   Wang GP, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12041451
   Wang GF, 2019, CHINA ECON REV, V56, DOI 10.1016/j.chieco.2019.101313
   Wang Q, 2021, TECHNOL FORECAST SOC, V169, DOI 10.1016/j.techfore.2021.120805
   Wood R, 2020, CLIM POLICY, V20, pS39, DOI 10.1080/14693062.2019.1639489
   Xu HL, 2020, J ENVIRON MANAGE, V270, DOI 10.1016/j.jenvman.2020.110893
   Yang CX, 2021, STRUCT CHANGE ECON D, V59, P442, DOI 10.1016/j.strueco.2021.06.017
   Zhang, 2021, CHINA SCI TOTAL ENV, P784, DOI [10.1016/j.scitotenv.2021a.147285, DOI 10.1016/J.SCITOTENV.2021A.147285]
   Zhang SH, 2021, LANCET PLANET HEALTH, V5, pE808, DOI 10.1016/S2542-5196(21)00252-7
   Zhao X, 2022, RESOUR CONSERV RECY, V176, DOI 10.1016/j.resconrec.2021.105959
   Zheng D, 2017, J CLEAN PROD, V141, P295, DOI 10.1016/j.jclepro.2016.09.091
   Zhou Y, 2021, POL J ENVIRON STUD, V30, P2445, DOI 10.15244/pjoes/127414
NR 34
TC 10
Z9 10
U1 15
U2 104
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 JAN
PY 2023
VL 30
IS 1
BP 2315
EP 2328
DI 10.1007/s11356-022-22337-w
EA AUG 2022
PG 14
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA H4UK6
UT WOS:000836535800009
PM 35930151
OA Bronze, Green Published
DA 2025-01-10
ER

PT J
AU Romanello, N
   Lourenco, JD
   Barioni, W
   Brandao, FZ
   Marcondes, CR
   Pezzopane, JRM
   Pantoja, MHD
   Botta, D
   Giro, A
   Moura, ABB
   Barreto, AD
   Garcia, AR
AF Romanello, Narian
   Lourenco Junior, Jose de Brito
   Barioni Junior, Waldomiro
   Brandao, Felipe Zandonadi
   Marcondes, Cintia Righetti
   Macedo Pezzopane, Jose Ricardo
   de Andrade Pantoja, Messy Hannear
   Botta, Daniela
   Giro, Alessandro
   Bossois Moura, Ana Beatriz
   Barreto, Andrea do Nascimento
   Garcia, Alexandre Rossetto
TI Thermoregulatory responses and reproductive traits in composite beef
   bulls raised in a tropical climate
SO INTERNATIONAL JOURNAL OF BIOMETEOROLOGY
LA English
DT Article
DE Tropical livestock; Thermoregulation; Animal welfare; Homeothermy;
   Infrared thermography; Semen quality
ID HEAT-STRESS; BOS-TAURUS; SPERM CHROMATIN; FEED-INTAKE; INFRARED
   THERMOGRAPHY; ENVIRONMENTAL-FACTORS; RECTAL TEMPERATURE; SCROTAL
   INSULATION; THYROID-HORMONES; SEMINAL QUALITY
AB It is believed that increased livestock production is limited by tropical climate. Thermal imbalance in bulls can lead to hyperthermia and alter testicular metabolism, causing subfertility or infertility. Therefore, the thermoregulation of composite Canchim bulls (5/8 Charolais x 3/8 Zebu) raised in tropical climate as well as their consequences in the physiological, hematological, hormonal, and andrological parameters were evaluated monthly. The bulls (n = 18; 30.0 +/- 1.5 months; 503.8 +/- 23.0 kg) were kept on pasture, in a single group, from August 2015 to March 2016, comprising the winter, spring, and summer seasons. Biometeorological variables were continuously monitored, and the Temperature and Humidity Index (THI) was calculated. A greater thermal challenge occurred in spring and summer (THI >= 72.0). Nevertheless, the bulls exhibited normothermia (38.6 to 38.9 degrees C) in these seasons. The cortisol did not vary between seasons (7.0 vs. 8.7 vs. 6.8 ng/mL; P > 0.05) and remained within the physiological patterns. Independent of the seasons, stress leukogram was also not observed, refitting the incidence of acute or chronic thermal stress. It is noteworthy that T3 and testosterone increased (P < 0.0001, P < 0.05) in spring and summer, the time that coincides with the breeding season, when there is increased metabolic requirement from the bulls. The progressive thermal challenge increase did not affect the scrotal thermoregulatory capacity, and in general, scrotal temperature remained at 5.2 degrees C below the internal body temperature. In summer, there was a 5% reduction in the minor sperm defects (P < 0.05) and DNA fragmentation in 2.4% of spermatozoa, a compatible value for high fertility bulls. The results show that the studied composite bulls can be considered as climatically adapted and constitute a viable alternative to be used in production systems in a tropical climate, even if the breeding seasons occur during the most critical thermal condition periods of the year.
C1 [Romanello, Narian; Lourenco Junior, Jose de Brito; de Andrade Pantoja, Messy Hannear; Botta, Daniela; Giro, Alessandro; Barreto, Andrea do Nascimento] Fed Univ Para, Av Univ S-N, BR-68746360 Castanhal, Brazil.
   [Barioni Junior, Waldomiro; Marcondes, Cintia Righetti; Macedo Pezzopane, Jose Ricardo; Garcia, Alexandre Rossetto] Brazilian Agr Res Corp, Lab Biotechnol & Anim Reprod, Embrapa Livestock Southeast, Km 234, BR-13560970 Sao Carlos, SP, Brazil.
   [Brandao, Felipe Zandonadi; Bossois Moura, Ana Beatriz] Fluminense Fed Univ, Rua Vital Brazil 64, BR-24230340 Niteroi, RJ, Brazil.
C3 Universidade Federal do Para; Empresa Brasileira de Pesquisa
   Agropecuaria (EMBRAPA); Universidade Federal Fluminense
RP Garcia, AR (corresponding author), Brazilian Agr Res Corp, Lab Biotechnol & Anim Reprod, Embrapa Livestock Southeast, Km 234, BR-13560970 Sao Carlos, SP, Brazil.
EM narian.r_@hotmail.com; joselourencojr@yahoo.com.br;
   waldomiro.barioni@embrapa.br; fzbrandao@id.uff.br;
   cintia.marcondes@embrapa.br; jose.pezzopane@embrapa.br;
   messy.andrade@yahoo.com.br; dani_botta@hotmail.com;
   giro.aless@gmail.com; anabeatriz.bossois@gmail.com;
   andreadnb91@gmail.com; alexandre.garcia@embrapa.br
RI Moura, Ana Beatriz/KYM-0023-2024; de Andrade Pantoja, Messy/Z-4309-2019;
   Barioni Jr, Waldomiro/AFK-0489-2022; Marcondes, Cintia/D-9904-2013;
   Brandão, Felipe/W-5261-2018; Pezzopane, José Ricardo/AAG-7792-2021;
   GARCIA, ALEXANDRE/G-1477-2012
OI Barioni Jr, Waldomiro/0000-0001-5970-6591; GARCIA,
   ALEXANDRE/0000-0002-3354-1474; Pezzopane, Jose/0000-0001-5462-6090;
   Marcondes, Cintia/0000-0002-1444-8514; Bossois Moura, Ana
   Beatriz/0000-0002-4992-7996; de Andrade Pantoja, Messy
   Hannear/0000-0002-4325-1841
FU Embrapa-Brazilian Agricultural Research Corporation [BIOTEC Network]
   [0113060010504]; Embrapa-Brazilian Agricultural Research Corporation
   [ADAPT+] [0212020080003]; Federal University of Para; CNPq-National
   Council for Scientific and Technological Development
FX This project was financially supported by the Embrapa-Brazilian
   Agricultural Research Corporation [BIOTEC Network (grant no.
   0113060010504) and ADAPT+ (grant no. 0212020080003)], by the Federal
   University of Para, and by the CNPq-National Council for Scientific and
   Technological Development.
CR Ahmad E, 2011, TROP ANIM HEALTH PRO, V43, P159, DOI 10.1007/s11250-010-9668-1
   ANDERSSON M, 1992, ANIM REPROD SCI, V27, P107, DOI 10.1016/0378-4320(92)90050-N
   Bailey TL, 1998, THERIOGENOLOGY, V49, P581, DOI 10.1016/S0093-691X(98)00009-0
   Barros DV, 2016, ARQ BRAS MED VET ZOO, V68, P422, DOI 10.1590/1678-4162-8327
   Beletti ME, 2004, THERIOGENOLOGY, V62, P398, DOI 10.1016/j.theriogenology.2003.10.016
   Berry DP, 2011, THERIOGENOLOGY, V75, P172, DOI 10.1016/j.theriogenology.2010.08.002
   Bloom E., 1973, NORD VET MED, V15, P283
   Bochenek M, 2001, THERIOGENOLOGY, V56, P557, DOI 10.1016/S0093-691X(01)00588-X
   CBRA-Colegio Brasileiro de Reproduca~o Animal, 2013, MANUAL EXAME ANDROL, Vthird, P104
   CHRISTOPHERSON RJ, 1979, CAN J ANIM SCI, V59, P655, DOI 10.4141/cjas79-085
   Church JS, 2014, RES VET SCI, V96, P220, DOI 10.1016/j.rvsc.2013.11.006
   Collier RJ, 2015, ANNU REV ANIM BIOSCI, V3, P513, DOI 10.1146/annurev-animal-022114-110659
   Curley KO, 2008, HORM BEHAV, V53, P20, DOI 10.1016/j.yhbeh.2007.08.005
   Curtis AK, 2017, J THERM BIOL, V63, P104, DOI 10.1016/j.jtherbio.2016.11.015
   Dogan S, 2015, BIOL REPROD, V92, DOI 10.1095/biolreprod.114.124255
   EMBRAPA-Empresa Brasileira de pesquisa Agropecuaria, 2016, COND MET EST EMBRAPA
   FAO, 2021, OECD-FAO Agricultural Outlook 20212030, DOI [10.1787/19991142, DOI 10.1787/19991142]
   Fernandes CE, 2008, THERIOGENOLOGY, V70, P1560, DOI 10.1016/j.theriogenology.2008.07.005
   Ferreira F, 2006, ARQ BRAS MED VET ZOO, V58, P732, DOI 10.1590/S0102-09352006000500005
   Fortes MRS, 2012, THERIOGENOLOGY, V78, P326, DOI 10.1016/j.theriogenology.2012.02.007
   Garcia A. R., 2017, Revista Brasileira de Reproducao Animal, V41, P33
   Garcia AR, 2004, THESIS
   Gifford CA, 2015, PHYSIOL BEHAV, V138, P118, DOI 10.1016/j.physbeh.2014.10.025
   Godfray HCJ, 2010, SCIENCE, V327, P812, DOI 10.1126/science.1185383
   Gulia S, 2010, TROP ANIM HEALTH PRO, V42, P1143, DOI 10.1007/s11250-010-9538-x
   Hillman PE, 2001, ASABE ANN M
   Hoffmann G, 2013, VET RES COMMUN, V37, P91, DOI 10.1007/s11259-012-9549-3
   Jensen KL, 2008, REPROD DOMEST ANIM, V43, P760, DOI 10.1111/j.1439-0531.2007.00991.x
   Kahwage PR, 2017, INT J BIOMETEOROL, V61, P1819, DOI 10.1007/s00484-017-1367-4
   Kamal R, 2016, INDIAN J ANIM SCI, V86, P75
   Karoui S, 2012, J ANIM SCI, V90, P2437, DOI 10.2527/jas.2011-4492
   Kastelic JP, 2012, REPROD DOMEST ANIM, V47, P45, DOI 10.1111/j.1439-0531.2012.02042.x
   Kastelic JP, 1997, ANIM REPROD SCI, V45, P255, DOI 10.1016/S0378-4320(96)01587-4
   Kastelic JP, 2001, CAN J VET RES, V65, P111
   Kilkenny C, 2010, PLOS BIOL, V8, DOI 10.1371/journal.pbio.1000412
   Kottek M, 2006, METEOROL Z, V15, P259, DOI 10.1127/0941-2948/2006/0130
   Kraft W.U. M. Durr., 2005, Klinische Labordiagnostik in der Tiermedizin, V6
   LCI, 1970, PATT TRANS LOSS
   Lockwood SA, 2017, THERIOGENOLOGY, V89, P140, DOI 10.1016/j.theriogenology.2016.10.019
   Lucio AC, 2016, THERIOGENOLOGY, V86, P924, DOI 10.1016/j.theriogenology.2016.03.015
   Mader TL, 2006, J ANIM SCI, V84, P712, DOI 10.2527/2006.843712x
   Maia ASC, 2005, INT J BIOMETEOROL, V50, P17, DOI 10.1007/s00484-005-0267-1
   Maibam U, 2014, TROP ANIM HEALTH PRO, V46, P1155, DOI 10.1007/s11250-014-0620-7
   McManus C, 2009, TROP ANIM HEALTH PRO, V41, P95, DOI 10.1007/s11250-008-9162-1
   MINTON JE, 1981, J ANIM SCI, V53, P1551, DOI 10.2527/jas1982.5361551x
   Montanholi YR, 2008, J THERM BIOL, V33, P468, DOI 10.1016/j.jtherbio.2008.09.001
   Nichi M, 2006, THERIOGENOLOGY, V66, P822, DOI 10.1016/j.theriogenology.2006.01.056
   OHASHI OM, 1988, PESQUI VET BRASIL, V8, P31
   Menegassi SRO, 2015, INT J BIOMETEOROL, V59, P357, DOI 10.1007/s00484-014-0847-z
   Peel MC, 2007, HYDROL EARTH SYST SC, V11, P1633, DOI 10.5194/hess-11-1633-2007
   Pereira AMF, 2008, INT J BIOMETEOROL, V52, P199, DOI 10.1007/s00484-007-0111-x
   Radostits OM, 2007, CLIN VET TRATADO DOE
   Rahman MB, 2011, THERIOGENOLOGY, V76, P1246, DOI 10.1016/j.theriogenology.2011.05.031
   REVELL SG, 1994, ANIM REPROD SCI, V36, P77, DOI 10.1016/0378-4320(94)90055-8
   Rhoads RP, 2013, J ANIM SCI, V91, P2492, DOI 10.2527/jas.2012-6120
   Robin E., 2014, COMPLEX VISIBLES OUT, P559
   Roland L, 2014, J VET DIAGN INVEST, V26, P592, DOI 10.1177/1040638714546490
   Saacke RG, 2008, THERIOGENOLOGY, V70, P473, DOI 10.1016/j.theriogenology.2008.04.012
   SAS, 2011, BAS SAS 9 3 PROC GUI
   Schaefer AL, 2012, RES VET SCI, V93, P928, DOI 10.1016/j.rvsc.2011.09.021
   Silanikove N, 2000, LIVEST PROD SCI, V67, P1, DOI 10.1016/S0301-6226(00)00162-7
   Silva LKX, 2018, ANDROLOGIA, V50, DOI 10.1111/and.12836
   Srikandakumar A, 2004, TROP ANIM HEALTH PRO, V36, P685, DOI 10.1023/B:TROP.0000042868.76914.a9
   Strong RA, 2015, J DAIRY SCI, V98, P7771, DOI 10.3168/jds.2015-9591
   Thom EC., 1959, Weatherwise, V12, P57, DOI [10.1080/00431672.1959.9926960, DOI 10.1080/00431672.1959.9926960]
   TOELLE VD, 1985, J ANIM SCI, V60, P89, DOI 10.2527/jas1985.60189x
   USDA-United States Department of Agriculture, 2014, AGR PROJ 2023
   Van Engen NK, 2014, J ANIM SCI, V92, P498, DOI 10.2527/jas.2013-6857
   VanCamp SD, 1997, VET CLIN N AM-FOOD A, V13, P203, DOI 10.1016/S0749-0720(15)30336-4
   Vencato J, 2014, REPROD DOMEST ANIM, V49, P481, DOI 10.1111/rda.12315
   Villanueva I, 2013, OXID MED CELL LONGEV, V2013, DOI 10.1155/2013/218145
NR 71
TC 25
Z9 25
U1 0
U2 11
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 0020-7128
EI 1432-1254
J9 INT J BIOMETEOROL
JI Int. J. Biometeorol.
PD SEP
PY 2018
VL 62
IS 9
BP 1575
EP 1586
DI 10.1007/s00484-018-1557-8
PG 12
WC Biophysics; Environmental Sciences; Meteorology & Atmospheric Sciences;
   Physiology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biophysics; Environmental Sciences & Ecology; Meteorology & Atmospheric
   Sciences; Physiology
GA GR7FQ
UT WOS:000442854500003
PM 29732473
DA 2025-01-10
ER

PT J
AU Tsarouhas, V
   Gullberg, U
   Lagercrantz, U
AF Tsarouhas, V
   Gullberg, U
   Lagercrantz, U
TI Mapping of quantitative trait loci (QTLs) affecting autumn freezing
   resistance and phenology in <i>Salix</i>
SO THEORETICAL AND APPLIED GENETICS
LA English
DT Article
ID FALL FROST-RESISTANCE; COASTAL DOUGLAS-FIR; BIOMASS PRODUCTION; CLIMATIC
   ADAPTATION; PINUS-SYLVESTRIS; GENETIC-ANALYSIS; COLD-HARDINESS; SCOTS
   PINE; TOLERANCE; WILLOWS
AB Quantitative trait locus (QTL) analysis was performed at different time points during cold-acclimation of a tetraploid F-2 Salix pedigree. The pedigree (n=92) was derived from a cross between a frost-susceptible diploid female clone 'Jorunn' (Salix viminalis) and a frost resistant hexaploid male clone 'SW901290' (Salix dasyclados). Freezing resistance, height growth increment and number of new leaves were assessed at days 0, 12, 20, 24, 31 and 42 of a short day-low temperature (SD-LT) hardening regime, while the initiation of shoot tip abscission and shoot tip abscission were measured daily. Height increment, dry-to-fresh weight ratio and number of new leaves were also measured in a replicated field trial. Freezing resistance was determined from electrolyte leakage of leaf tissues and from visual injuries on stem segments, after exposure to a predetermined freeze-thaw stress. Using a genetic map of the F-2 composed of 432 single-dose AFLP markers, a total of 19 genomic regions controlling freezing resistance (10) and phenological traits (9) before and during cold-acclimation (SD-LT) were identified. The magnitude of the phenotypic variation explained by each freezing resistance locus varied over acclimation time (0-45%), and there was no time point at which all the QTLs could be detected. The single QTL detected for non-acclimated freezing resistance did not reach significance at any time point during cold-acclimation, suggesting an independent genetic relationship between non-acclimated and acclimated resistance to freezing in Salix. Five of the loci associated with freezing resistance shared common intervals with loci controlling phenological traits. Of the 14 QTLs controlling autumn freezing resistance and/or phenological traits in the indoors experiment, six (43%) were associated with autumn phenology-related traits, i.e. height increment, dry-to-fresh weight ratio and number of new leaves, measured in the field. A major locus with multi-trait association in both indoor and outdoor experiments was detected.
C1 Swedish Univ Agr Sci, Dept Plant Biol & Forest Genet, S-75007 Uppsala, Sweden.
C3 Swedish University of Agricultural Sciences
RP Stockholm Univ, Wenner Gren Inst, Dept Dev Biol, S-10691 Stockholm, Sweden.
EM Vasilios@devbio.su.se
RI Tsarouhas, Vasilios/AAG-8226-2020
OI Tsarouhas, Vasilios/0000-0002-2933-1351
CR Aitken SN, 1996, CAN J FOREST RES, V26, P1828, DOI 10.1139/x26-208
   [Anonymous], ECOLOGICAL STUDIES
   BASTEN CJ, 2000, QTL CARTOGRAPHER V1
   Beavis WD., 1994, P 49 ANN CORN SORGH
   Byrne M, 1997, THEOR APPL GENET, V95, P975, DOI 10.1007/s001220050650
   Deans JD, 1996, FORESTRY, V69, P5, DOI 10.1093/forestry/69.1.5
   Doerge RW, 2000, P NATL ACAD SCI USA, V97, P7951, DOI 10.1073/pnas.97.14.7951
   GALIBA G, 1995, THEOR APPL GENET, V90, P1174, DOI 10.1007/BF00222940
   HAYES PM, 1993, THEOR APPL GENET, V87, P392, DOI 10.1007/BF01184929
   HOWE GT, 1995, PHYSIOL PLANTARUM, V93, P695, DOI 10.1111/j.1399-3054.1995.tb05119.x
   Howe GT, 2000, THEOR APPL GENET, V101, P632, DOI 10.1007/s001220051525
   Hurme P, 2000, GENETICS, V156, P1309
   Hurme P, 1997, CAN J FOREST RES, V27, P716, DOI 10.1139/cjfr-27-5-716
   Jermstad KD, 2001, THEOR APPL GENET, V102, P1152, DOI 10.1007/s001220000506
   *JMP, 1994, STAT SOFTW MAC V3 0
   Junttila O, 1990, SCAND J FOREST RES, V5, P195, DOI 10.1080/02827589009382605
   Larsson S, 1998, BIOMASS BIOENERG, V15, P23, DOI 10.1016/S0961-9534(98)80003-2
   Lerceteau E, 2000, MOL BREEDING, V6, P451, DOI 10.1023/A:1026548716320
   Li Paul H., 1984, Horticultural Reviews, V6, P373, DOI 10.1002/9781118060797.ch10
   Ma CX, 2002, GENOME RES, V12, P1974, DOI 10.1101/gr.320202
   Manly KF, 2001, MAMM GENOME, V12, P930, DOI 10.1007/s00335-001-1016-3
   Nilsson JE, 1986, SCAND J FOREST RES, V1, P205, DOI 10.1080/02827588609382412
   Ögren E, 1999, TREE PHYSIOL, V19, P755
   Ögren E, 1999, TREE PHYSIOL, V19, P749
   PAN A, 1994, THEOR APPL GENET, V89, P900, DOI 10.1007/BF00224516
   Ronnberg-Wastljung A. C., 2003, Forest Genetics, V10, P185
   Rönnberg-Wästljung AC, 1999, THEOR APPL GENET, V98, P531, DOI 10.1007/s001220051101
   SAKAI A, 1970, ECOLOGY, V51, P485, DOI 10.2307/1935383
   STONE JM, 1993, P NATL ACAD SCI USA, V90, P7869, DOI 10.1073/pnas.90.16.7869
   SUTINEN ML, 1992, TREE PHYSIOL, V11, P241, DOI 10.1093/treephys/11.3.241
   TEUTONICO RA, 1995, MOL BREEDING, V1, P329, DOI 10.1007/BF01248410
   Thibault J, 1998, CAN J BOT, V76, P157, DOI 10.1139/cjb-76-1-157
   Thomashow MF, 1998, PLANT PHYSIOL, V118, P1, DOI 10.1104/pp.118.1.1
   Tsarouhas V, 2001, SILVAE GENET, V50, P54
   Tsarouhas V, 2000, BIOMASS BIOENERG, V19, P165, DOI 10.1016/S0961-9534(00)00030-1
   TSAROUHAS V, 2002, THESIS SWEDISH U AGR
   von Fircks H. A., 1994, THESIS SWEDISH U AGR
   WEISER C J, 1970, Hortscience, V5, P403
NR 38
TC 32
Z9 43
U1 1
U2 11
PU SPRINGER
PI NEW YORK
PA 233 SPRING ST, NEW YORK, NY 10013 USA
SN 0040-5752
EI 1432-2242
J9 THEOR APPL GENET
JI Theor. Appl. Genet.
PD MAY
PY 2004
VL 108
IS 7
BP 1335
EP 1342
DI 10.1007/s00122-003-1544-1
PG 8
WC Agronomy; Plant Sciences; Genetics & Heredity; Horticulture
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Plant Sciences; Genetics & Heredity
GA 814QE
UT WOS:000220988400017
PM 14747916
DA 2025-01-10
ER

PT J
AU Li, XX
   Huang, LY
   Peng, SB
   Wang, F
AF Li, Xiaoxiao
   Huang, Liying
   Peng, Shaobing
   Wang, Fei
TI Inter-annual climate variability constrains rice genetic improvement in
   China
SO FOOD AND ENERGY SECURITY
LA English
DT Article
DE grain yield; Green super rice; nighttime temperature; NUE
ID NITROGEN-USE EFFICIENCY; HIGH NIGHT TEMPERATURE; GRAIN-YIELD;
   PROTEIN-CONTENT; CROP PRODUCTION; EATING-QUALITY; HYBRID RICE; INCREASE;
   GROWTH; PHOTOSYNTHESIS
AB Yield potential has been significantly increased through hybrid rice breeding in the past, however, the genetic gain in grain yield is becoming marginal in recent years, especially in farmers' field. The increase in climate variability is one potential reason for the stagnant rice grain yield. Moreover, overuse of nitrogen fertilizer and poor grain quality of hybrid rice reduce its advantage over inbred rice. The present study evaluated seventy-eight elite hybrid varieties in 2014-2018 aiming to determine the climate variability and its influences on grain yield, nitrogen use efficiency (NUE), and grain protein content of the newly bred rice hybrid varieties simultaneously. It was found that daily maximum and minimum temperature, daily radiation varied significantly across planting years. The extreme differences for T-max, T-min, and radiation were 2.0 degrees C, 1.5 degrees C, and 3.6 MJ m(-2) d(-1), respectively. Overall, grain yield of 22 varieties was significantly increased in comparison to that of the control cultivar Yangliangyou6 (YLY6), which was closely dependent on the planting year. Grain yield of these elite varieties ranged from 9.69 to 11.97 t ha(-1), and NUE for grain production (NUEg) from 47.3 to 60.9 kg kg(-1). The inter-annual variation in grain yield, NUEg, and grain protein content was significantly related to the average daily minimum temperature (T-min), due to its effects on grain filling percentage and harvest index. Moreover, these three properties are mutually correlated for all varieties across five years: grain yield positively correlated with NUEg (R-2 = 0.46) and negatively correlated with protein content (R-2 = 0.32), whereas NUEg negatively related to protein content (R-2 = 0.49). These results suggest that enhancing the adaptation to climate variability in hybrid rice breeding is essential and urgent for sustainable rice production in China.
C1 [Li, Xiaoxiao; Peng, Shaobing; Wang, Fei] Huazhong Agr Univ, Coll Plant Sci & Technol, Natl Key Lab Crop Genet Improvement, MARA Key Lab Crop Ecophysiol & Farming Syst Middl, Wuhan, Peoples R China.
   [Huang, Liying] Yangtze Univ, Coll Agr, Jingzhou, Peoples R China.
C3 Huazhong Agricultural University; Yangtze University
RP Wang, F (corresponding author), Huazhong Agr Univ, Coll Plant Sci & Technol, Natl Key Lab Crop Genet Improvement, MARA Key Lab Crop Ecophysiol & Farming Syst Middl, Wuhan, Peoples R China.
EM fwang@mail.hzau.edu.cn
RI Sun, Haipeng/AAM-4474-2021; Wang, Fei/HLQ-5605-2023
OI Li, Xiaoxiao/0000-0002-3635-2636; Wang, Fei/0000-0002-5021-2904
FU National Key Research and Development Program of China
   [2017YFD0301401-3]; National Natural Science Foundation of China
   [32071948]
FX the National Key Research and Development Program of China, Grant/Award
   Number: 2017YFD0301401-3; National Natural Science Foundation of China,
   Grant/Award Number: 32071948
CR Bailey-Serres J, 2019, NATURE, V575, P109, DOI 10.1038/s41586-019-1679-0
   Cao ZZ, 2017, PLANT GROWTH REGUL, V81, P477, DOI 10.1007/s10725-016-0225-4
   Cao ZhenZhen Cao ZhenZhen, 2012, Acta Agronomica Sinica, V38, P99
   Cassman KG, 2003, ANNU REV ENV RESOUR, V28, P315, DOI 10.1146/annurev.energy.28.040202.122858
   Challinor AJ, 2014, NAT CLIM CHANGE, V4, P287, DOI [10.1038/nclimate2153, 10.1038/NCLIMATE2153]
   Deng NY, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-09447-9
   Donat MG, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2012GL052459
   Evans LT, 1999, CROP SCI, V39, P1544, DOI 10.2135/cropsci1999.3961544x
   Food and Agriculture Organization (FAO), 2018, FAOSTAT DAT AGR PROD
   Gourdji SM, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/2/024041
   Hu B, 2015, NAT GENET, V47, P834, DOI 10.1038/ng.3337
   Huang LY, 2019, FIELD CROP RES, V233, P49, DOI 10.1016/j.fcr.2019.01.005
   Huang LY, 2018, FIELD CROP RES, V216, P150, DOI 10.1016/j.fcr.2017.11.019
   Iizumi T, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/3/034003
   Impa SM, 2021, PLANT CELL ENVIRON, V44, P2049, DOI 10.1111/pce.14028
   Ito S, 2009, J AGRON CROP SCI, V195, P368, DOI 10.1111/j.1439-037X.2009.00376.x
   Kanno K, 2009, SOIL SCI PLANT NUTR, V55, P124, DOI 10.1111/j.1747-0765.2008.00343.x
   Kwak Jieun, 2018, Korean Journal of Crop Science / Hanguk Jakmul Hakhoe Chi, V63, P77, DOI 10.7740/kjcs.2018.63.2.077
   Laza MRC, 2015, AGR FOREST METEOROL, V209, P69, DOI 10.1016/j.agrformet.2015.04.029
   Liang ChengGang Liang ChengGang, 2010, Chinese Journal of Rice Science, V24, P398
   Ling Xiao-Xia, 2019, Acta Agronomica Sinica, V45, P323, DOI 10.3724/SP.J.1006.2019.82044
   Liu QH, 2019, J AGRON CROP SCI, V205, P188, DOI 10.1111/jac.12313
   Liu QH, 2013, AGRON J, V105, P446, DOI 10.2134/agronj2012.0164
   Lobell DB, 2014, SCIENCE, V344, P516, DOI 10.1126/science.1251423
   Lobell DB, 2011, SCIENCE, V333, P616, DOI [10.1126/science.1206376, 10.1126/science.1204531]
   Lobell DB, 2008, ENVIRON RES LETT, V3, DOI 10.1088/1748-9326/3/3/034007
   Lu Shi, 2019, Chinese Journal of Rice Science, V33, P541, DOI 10.16819/j.1001-7216.2019.9022
   [马启林 MA Qilin], 2008, [湖北农业科学, Hubei Agricultural Sciences], V47, P1228
   Matsue Y, 1997, JPN J CROP SCI, V66, P189, DOI 10.1626/jcs.66.189
   Matsue Y, 2001, PLANT PROD SCI, V4, P71, DOI 10.1626/pps.4.71
   Mohammed AR, 2013, CROP SCI, V53, P2603, DOI 10.2135/cropsci2013.01.0060
   Morita S, 2005, ANN BOT-LONDON, V95, P695, DOI 10.1093/aob/mci071
   Ohdaira Y, 2010, PLANT PROD SCI, V13, P132, DOI 10.1626/pps.13.132
   Peng SB, 2004, P NATL ACAD SCI USA, V101, P9971, DOI 10.1073/pnas.0403720101
   Peng SB, 2008, FIELD CROP RES, V108, P32, DOI 10.1016/j.fcr.2008.04.001
   Peng ShaoBing Peng ShaoBing, 2002, Agricultural Sciences in China, V1, P776
   Peraudeau S, 2015, FIELD CROP RES, V171, P67, DOI 10.1016/j.fcr.2014.11.004
   Qiu XL, 2019, AGRONOMY-BASEL, V9, DOI 10.3390/agronomy9120794
   Ray DK, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms6989
   Sadok W, 2020, TRENDS PLANT SCI, V25, P644, DOI 10.1016/j.tplants.2020.02.003
   Satapathy SS, 2014, EUR J AGRON, V54, P21, DOI 10.1016/j.eja.2013.11.010
   Schauberger B, 2017, NAT COMMUN, V8, DOI 10.1038/ncomms13931
   Shi WJ, 2016, FIELD CROP RES, V190, P18, DOI 10.1016/j.fcr.2015.10.006
   Shi WJ, 2013, NEW PHYTOL, V197, P825, DOI 10.1111/nph.12088
   Sreenivasulu N, 2015, J EXP BOT, V66, P1737, DOI 10.1093/jxb/eru544
   Tao FL, 2013, GLOBAL CHANGE BIOL, V19, P3200, DOI 10.1111/gcb.12250
   Tao FL, 2013, J APPL METEOROL CLIM, V52, P531, DOI 10.1175/JAMC-D-12-0100.1
   Tao YY, 2014, FIELD CROP RES, V168, P101, DOI 10.1016/j.fcr.2014.08.014
   Tester M, 2010, SCIENCE, V327, P818, DOI 10.1126/science.1183700
   Tilman D, 2011, P NATL ACAD SCI USA, V108, P20260, DOI 10.1073/pnas.1116437108
   Urban D, 2012, CLIMATIC CHANGE, V112, P525, DOI 10.1007/s10584-012-0428-2
   van Ittersum MK, 2013, FIELD CROP RES, V143, P4, DOI 10.1016/j.fcr.2012.09.009
   Wang DP, 2016, FIELD CROP RES, V198, P303, DOI 10.1016/j.fcr.2016.05.008
   Wang F, 2017, J INTEGR AGR, V16, P1000, DOI 10.1016/S2095-3119(16)61561-7
   Wing RA, 2018, NAT REV GENET, V19, P505, DOI 10.1038/s41576-018-0024-z
   Wu C, 2016, SCI REP-UK, V6, DOI 10.1038/srep34978
   Wu LL, 2016, FRONT PLANT SCI, V7, DOI 10.3389/fpls.2016.01024
   Xu J, 2021, PHYTOCHEM ANALYSIS, V32, P785, DOI 10.1002/pca.3024
   Yamakawa H, 2010, PLANT CELL PHYSIOL, V51, P795, DOI 10.1093/pcp/pcq034
   Yuan L., 1994, Hybrid Rice Technology: New Developments and Future Prospects, P143
   Zhang QF, 2007, P NATL ACAD SCI USA, V104, P16402, DOI 10.1073/pnas.0708013104
   Zhang TY, 2012, J SCI FOOD AGR, V92, P1643, DOI 10.1002/jsfa.5523
   Zhao C, 2017, P NATL ACAD SCI USA, V114, P9326, DOI 10.1073/pnas.1701762114
   Zhu GL, 2016, SCI REP-UK, V6, DOI 10.1038/srep21049
NR 64
TC 6
Z9 7
U1 2
U2 38
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 2048-3694
J9 FOOD ENERGY SECUR
JI Food Energy Secur.
PD NOV
PY 2021
VL 10
IS 4
AR e299
DI 10.1002/fes3.299
EA JUN 2021
PG 11
WC Agronomy; Food Science & Technology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Food Science & Technology
GA WY2LQ
UT WOS:000656924000001
OA gold
DA 2025-01-10
ER

PT J
AU El Yaacoubi, A
   Oukabli, A
   Legave, JM
   Ainane, T
   Mouhajir, A
   Zouhair, R
   Hafidi, M
AF El Yaacoubi, Adnane
   Oukabli, Ahmed
   Legave, Jean-Michel
   Ainane, Tarik
   Mouhajir, Abdelmounaim
   Zouhair, Rachid
   Hafidi, Majida
TI Response of almond flowering and dormancy to Mediterranean temperature
   conditions in the context of adaptation to climate variations
SO SCIENTIA HORTICULTURAE
LA English
DT Article
DE Almond; Flowering; Dormancy; Chill requirements; Heat requirements
ID PRUNUS-ARMENIACA L.; HEAT REQUIREMENTS; FRUIT-TREES; BUD DORMANCY;
   FLORAL PHENOLOGY; SWEET CHERRY; APPLE; CULTIVARS; CHILL; DEPENDENCE
AB Determining the flowering and the dormancy phases in fruit trees is a crucial process because of their substantial role in some agricultural practices and crop managements. However, few of these studies were conducted on almond flowering and dormancy, particularly in mild climate areas. This study aimed to simulate the dormancy phases, closely involved in the determination of flowering time of almond species in response to temperature variations. To reach this objective, Partial Least Squares analysis was used. In this regard, climatic and flowering data were collected from Ain Taoudjate in Morocco during the period from 1974 to 2014. In fact, a significant temperature increase was highlighted, inducing a decrease in amounts of chill during the studied period. Using Partial Least Squares analysis, a good fit of data was obtained, particularly using mean and maximal tempera. tures. Two relevant periods controlling the flowering process were highlighted in Tuono cultivar, in concordance with the sequential model in prediction of flowering times. The first long chilling period started from October 01st to January 11th. During this period, temperatures correlated positively with flowering dates, inducing consequently a delayed flowering dates because of low and slow accumulation of chilling requirements. However, the second short forcing period extended from January 18th to March 09th, during which flowering dates were negatively correlated with temperatures. In fact, the accumulation of certain threshold of Growing Degree Hours and Chill Portions during the two periods respectively could delay flowering, particularly in the context of chilling privation in the coming future, causing a serious problem for fruit trees. Significantly, temperatures during the chilling period seemed to affect effectively the flowering dates of almond than temperatures during the forcing period. In this investigation, we demonstrated that Partial Least Squares showed a good fit in explanation of the flowering process and can be used for prediction of dormancy phases and flowering process.
C1 [El Yaacoubi, Adnane; Ainane, Tarik] Univ Sultan Moulay Slimane, Higher Sch Technol Khenifra, PB 170, Khenifra, Morocco.
   [Oukabli, Ahmed] INRA, Plant Breeding & Genet Resources, Reg Agr Res Ctr Meknes, Box 578, Meknes, Morocco.
   [Legave, Jean-Michel] INRA UMR 1334 AGAP, F-34398 Montpellier, France.
   [Mouhajir, Abdelmounaim; Zouhair, Rachid; Hafidi, Majida] Univ Moulay Ismail, Fac Sci, Dept Biol, BP 11 201 Zitoune, Meknes 50000, Morocco.
C3 Sultan Moulay Slimane University of Beni Mellal; Moulay Ismail
   University of Meknes; INRAE; Moulay Ismail University of Meknes
RP El Yaacoubi, A (corresponding author), Univ Sultan Moulay Slimane, Higher Sch Technol Khenifra, PB 170, Khenifra, Morocco.
EM a.elyaacoubi@usms.ma
RI Ainane, Tarik/AEI-6594-2022; Yaacoubi, Adnane/U-5291-2019; tarik,
   ainane/G-4483-2015
OI Mouhajir, Abdelmounaim/0000-0002-3170-4057; tarik,
   ainane/0000-0001-6743-2666; EL YAACOUBI, Adnane/0000-0003-2076-1563
FU Agricultural Research for Development Program [PRAD 11-08]
FX This study was carried out with the support of the Agricultural Research
   for Development Program (PRAD 11-08) that we thank for its financial
   support. We also thank Professor Mohamed Zeriouh for editing the
   language of this paper and we equally express our sincere
   acknowledgements to the editor and the reviewers for their contribution
   to improve this paper.
CR Abu-Asab MS, 2001, BIODIVERS CONSERV, V10, P597, DOI 10.1023/A:1016667125469
   Alburquerque N, 2008, ENVIRON EXP BOT, V64, P162, DOI 10.1016/j.envexpbot.2008.01.003
   Alonso JM, 2005, J AM SOC HORTIC SCI, V130, P308, DOI 10.21273/JASHS.130.3.308
   Segura JMA, 2017, SCI HORTIC-AMSTERDAM, V224, P61, DOI 10.1016/j.scienta.2017.05.036
   Anderson J. L., 1986, Acta Horticulturae, P71
   Andreini L, 2014, AGR FOREST METEOROL, V184, P210, DOI 10.1016/j.agrformet.2013.10.005
   Andreini L, 2012, TREES-STRUCT FUNCT, V26, P919, DOI 10.1007/s00468-011-0668-1
   Atkinson CJ, 2013, ENVIRON EXP BOT, V91, P48, DOI 10.1016/j.envexpbot.2013.02.004
   Baldocchi D, 2008, CLIMATIC CHANGE, V87, pS153, DOI 10.1007/s10584-007-9367-8
   Bartolini S, 2019, SCI HORTIC-AMSTERDAM, V244, P399, DOI 10.1016/j.scienta.2018.09.070
   Benmoussa H, 2017, AGR FOREST METEOROL, V239, P34, DOI 10.1016/j.agrformet.2017.02.030
   Campoy JA, 2011, S AFR J BOT, V77, P618, DOI 10.1016/j.sajb.2010.12.006
   Campoy JA, 2012, EUR J AGRON, V37, P43, DOI 10.1016/j.eja.2011.10.004
   Chmielewski FM, 2004, AGR FOREST METEOROL, V121, P69, DOI 10.1016/S0168-1923(03)00161-8
   Chuine I, 1998, PLANT CELL ENVIRON, V21, P455, DOI 10.1046/j.1365-3040.1998.00299.x
   Cook NC, 2017, SCI HORTIC-AMSTERDAM, V226, P307, DOI 10.1016/j.scienta.2017.08.028
   Darbyshire R, 2017, AGR FOREST METEOROL, V240, P67, DOI 10.1016/j.agrformet.2017.03.021
   Darbyshire R, 2014, INT J BIOMETEOROL, V58, P1119, DOI 10.1007/s00484-013-0705-4
   Darbyshire R, 2011, AGR FOREST METEOROL, V151, P1074, DOI 10.1016/j.agrformet.2011.03.010
   Egea J, 2003, ENVIRON EXP BOT, V50, P79, DOI 10.1016/S0098-8472(03)00002-9
   El Yaacoubi A, 2016, INT J BIOMETEOROL, V60, P1695, DOI 10.1007/s00484-016-1160-9
   El Yaacoubi A, 2014, SCI HORTIC-AMSTERDAM, V180, P243, DOI 10.1016/j.scienta.2014.10.041
   FISHMAN S, 1987, J THEOR BIOL, V126, P309, DOI 10.1016/S0022-5193(87)80237-0
   FISHMAN S, 1987, J THEOR BIOL, V124, P473, DOI 10.1016/S0022-5193(87)80221-7
   Fujisawa M, 2010, GLOBAL CHANGE BIOL, V16, P2651, DOI 10.1111/j.1365-2486.2009.02126.x
   Gannouni TA, 2017, SCI HORTIC-AMSTERDAM, V219, P272, DOI 10.1016/j.scienta.2017.03.013
   Grab S, 2011, AGR FOREST METEOROL, V151, P406, DOI 10.1016/j.agrformet.2010.11.001
   Guo L, 2013, AGR FOREST METEOROL, V180, P164, DOI 10.1016/j.agrformet.2013.06.004
   Lalanne-Tisne G., 2017, Acta Horticulturae, P349, DOI 10.17660/actahortic.2017.1172.65
   LANG GA, 1987, HORTSCIENCE, V22, P817
   Legave JM, 2013, INT J BIOMETEOROL, V57, P317, DOI 10.1007/s00484-012-0551-9
   Legave JM, 2015, FRONT PLANT SCI, V6, DOI 10.3389/fpls.2015.01054
   Luedeling E, 2013, INT J BIOMETEOROL, V57, P679, DOI 10.1007/s00484-012-0594-y
   Luedeling E, 2012, AGR FOREST METEOROL, V158, P43, DOI 10.1016/j.agrformet.2011.10.020
   Maulión E, 2014, SCI HORTIC-AMSTERDAM, V177, P112, DOI 10.1016/j.scienta.2014.07.042
   Mazer SJ, 2015, ECOSPHERE, V6, DOI 10.1890/ES14-00433.1
   Meier U., 1997, Growth Stages of Mono-and Dicotyledonous Plants
   Menzel A, 2006, GLOBAL CHANGE BIOL, V12, P1969, DOI 10.1111/j.1365-2486.2006.01193.x
   Nava GA, 2009, SCI HORTIC-AMSTERDAM, V122, P37, DOI 10.1016/j.scienta.2009.03.021
   Oukabli A., 2012, CARACTERISATION PHEN, P125
   RICHARDSON E A, 1974, Hortscience, V9, P331
   Sakar E, 2019, ERWERBS-OBSTBAU, V61, P103, DOI 10.1007/s10341-018-0401-y
   Sakar E, 2017, INT J FRUIT SCI, V17, P415, DOI 10.1080/15538362.2017.1345671
   Sparks TH, 2000, INT J BIOMETEOROL, V44, P82, DOI 10.1007/s004840000049
   TROMP J, 1976, SCI HORTIC-AMSTERDAM, V5, P331, DOI 10.1016/0304-4238(76)90128-X
   Vitasse Y, 2018, AGR FOREST METEOROL, V248, P60, DOI 10.1016/j.agrformet.2017.09.005
   Viti R., 2013, Advances in Horticultural Science, V27, P5
   Viti R, 2010, ACTA HORTIC, V862, P257
   Viti R, 2010, SCI HORTIC-AMSTERDAM, V124, P217, DOI 10.1016/j.scienta.2010.01.001
   YOUNG E, 1992, J AM SOC HORTIC SCI, V117, P271, DOI 10.21273/JASHS.117.2.271
NR 50
TC 11
Z9 13
U1 1
U2 33
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0304-4238
EI 1879-1018
J9 SCI HORTIC-AMSTERDAM
JI Sci. Hortic.
PD NOV 17
PY 2019
VL 257
AR 108687
DI 10.1016/j.scienta.2019.108687
PG 9
WC Horticulture
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture
GA IY0SS
UT WOS:000486103700025
DA 2025-01-10
ER

PT J
AU Subroto, S
   Datta, R
AF Subroto, Sujoy
   Datta, Ranjan
TI Perspectives of racialized immigrant communities on adaptability to
   climate disasters following the UN Roadmap for Sustainable Development
   Goals (SDGs) 2030
SO SUSTAINABLE DEVELOPMENT
LA English
DT Article
DE anti-racist climate solutions; climate change disasters;
   community-driven adaptation strategies; compounded vulnerability;
   intersectionality; systematic marginalization; Western Canada
ID NATURAL DISASTERS; RISK REDUCTION; RESILIENCE; VULNERABILITY;
   INTERSECTIONALITY; METHODOLOGIES; CAPACITY; GENDER; HEALTH; IMPACT
AB Climate Change-induced risk events intensify vulnerability and disproportionately affect regions and racialized immigrant communities. Understanding the multiple dimensions of disaster and risk, especially how these are embedded in a broader social-political context, and translated into risk management strategies, have now been identified as priority areas under Sendai Framework for Disaster Risk Reduction 2015-2030 and UN Research Roadmap for achieving Sustainable Development Goals (SDGs) 2030. Drawing on a relational intersectional approach, this study explores the meanings of climate change disasters and risk reduction strategies from a racialized immigrant community's (i.e., Bangladeshi-Canadian) lived experiences in Calgary, Canada. From our relational research, we learned that extreme climate events (such as forest fires/wildfires, heat waves, flash floods, severe colds, hailstorms, etc.) are the most common stressors unevenly impacting the household economy, physical health, and mental and psychological wellbeing of the racialized immigrant community in Calgary. The community's compounded vulnerability to disaster risks is further aggravated due to their intersectional positionality and structural inequality (systematic marginalization) rooted in the lack of explicit anti-racist policy guidelines in Canada. The community members adapt diverse strategies (mostly reactive) based on their family income, severity and frequency of the exposure to risks, social support system, geographic location (residence), cultural practices, and involvement with community networks. While proposing solutions, they suggested that community-engaged tailored disaster intervention strategy could play an instrumental role in addressing social vulnerability (determinants) and enhancing adaptive capacity at the local level. Moreover, this study calls for a more holistic account of the differential vulnerability context to better understand the structural root causes and emphasizes that upscaling land-based practices and knowledge transmission, ensuring deliberate participation of visible minorities, fostering collective action and integrating local community associations into all stages of disaster management should be the priority for the state agencies to support long-term resilience.
C1 [Subroto, Sujoy] Univ Calgary, Dept Geog, Calgary, AB, Canada.
   [Datta, Ranjan] Mt Royal Univ, Dept Humanities, Calgary, AB, Canada.
   [Datta, Ranjan] Mt Royal Univ, Dept Humanities, Calgary, AB T3E 6K6, Canada.
C3 University of Calgary; Mount Royal University; Mount Royal University
RP Datta, R (corresponding author), Mt Royal Univ, Dept Humanities, Calgary, AB T3E 6K6, Canada.
EM rdatta@mtroyal.ca
RI Datta, Ranjan/AAA-5934-2021
FU Canada Research Chair Grant [CRC-2019-00338]
FX We acknowledge the contributions of the members of the
   Bangladeshi-Canadian diaspora for sharing their time, wisdom, and
   insightful perceptions. This research was conducted with the support of
   a Canada Research Chair Grant (CRC-2019-00338).
CR Adger WN, 2006, GLOBAL ENVIRON CHANG, V16, P268, DOI 10.1016/j.gloenvcha.2006.02.006
   Ajubade I., 2010, SECURITY CANADA CANA, P20
   [Anonymous], 2015, AUST J EMERG MANAG, V30, P9
   Antronico L, 2020, INT J DISAST RISK RE, V46, DOI 10.1016/j.ijdrr.2020.101529
   Benevolenza MA, 2019, J HUM BEHAV SOC ENVI, V29, P266, DOI 10.1080/10911359.2018.1527739
   Berberian AG, 2022, CURR ENV HLTH REP, V9, P451, DOI 10.1007/s40572-022-00360-w
   Berkes F, 2013, SOC NATUR RESOUR, V26, P5, DOI 10.1080/08941920.2012.736605
   Brown K, 2011, ANNU REV ENV RESOUR, V36, P321, DOI 10.1146/annurev-environ-052610-092905
   Buikstra E., 2011, Continuity versus creative response to challenge: The primacy of resilience and resourcefulness in life and therapy, P273
   Calgary Economic Development, 2020, CALG DEM
   Canada and United Nations, 2022, US
   Cardona OD, 2012, MANAGING THE RISKS OF EXTREME EVENTS AND DISASTERS TO ADVANCE CLIMATE CHANGE ADAPTATION, P65
   Carmen E, 2022, AMBIO, V51, P1371, DOI 10.1007/s13280-021-01678-9
   Caxaj CS, 2015, GLOB QUALIT NURS RES, V2, DOI 10.1177/2333393615580764
   Chisty M. A., 2021, Continuity & Resilience Review, V3, P119, DOI [10.1108/CRR-03-2021-0007, DOI 10.1108/CRR-03-2021-0007]
   Crenshaw K., 1989, University of Chicago Legal Forum, V1989
   Cutter SL, 2016, GEOGR J, V182, P110, DOI 10.1111/geoj.12174
   Datta R, 2023, POLAR GEOGR, V46, P3, DOI 10.1080/1088937X.2022.2141905
   Datta R, 2018, AM INDIAN CULT RES J, V42, P115, DOI 10.17953/aicrj.42.1.datta
   Datta R, 2015, LOCAL ENVIRON, V20, P102, DOI 10.1080/13549839.2013.818957
   Dewan C, 2022, ETHNOS, V87, P538, DOI 10.1080/00141844.2020.1788109
   Donner W, 2008, SOC FORCES, V87, P1089
   Engle NL, 2011, GLOBAL ENVIRON CHANG, V21, P647, DOI 10.1016/j.gloenvcha.2011.01.019
   Esteves AM, 2021, BUS STRATEG ENVIRON, V30, P1423, DOI 10.1002/bse.2706
   Fisher S, 2010, VIOLENCE AGAINST WOM, V16, P902, DOI 10.1177/1077801210377649
   Gillborn D, 2015, QUAL INQ, V21, P277, DOI 10.1177/1077800414557827
   Government of Canada, 2020, CAN UN
   Greaves W, 2021, INT J-TORONTO, V76, P183, DOI 10.1177/00207020211019325
   Greaves Wilfrid., 2012, Natural Resources and Social Conflict. Towards Critical Environmental Security, P63, DOI DOI 10.1177/0967010616665957
   Griffith DM, 2013, AM J MENS HEALTH, V7, p19S, DOI 10.1177/1557988313480227
   Hansen A, 2013, GLOBAL HEALTH ACTION, V6, P1, DOI 10.3402/gha.v6i0.21364
   Hasan MR, 2019, INT J DISAST RISK RE, V41, DOI 10.1016/j.ijdrr.2019.101324
   Held MBE, 2019, INT J QUAL METH, V18, DOI 10.1177/1609406918821574
   Hulme M., 2013, ORISIS, V26, P506
   Imperiale AJ, 2021, SUSTAIN DEV, V29, P891, DOI 10.1002/sd.2182
   Imperiale AJ, 2019, DISASTER PREV MANAG, V28, P434, DOI 10.1108/DPM-01-2018-0030
   Joerin J, 2012, INT J DISAST RISK RE, V1, P44, DOI 10.1016/j.ijdrr.2012.05.006
   Kaijser A, 2014, ENVIRON POLIT, V23, P417, DOI 10.1080/09644016.2013.835203
   Klein JA, 2019, ENVIRON SCI POLICY, V94, P143, DOI 10.1016/j.envsci.2018.12.034
   Kuran CHA, 2020, INT J DISAST RISK RE, V50, DOI 10.1016/j.ijdrr.2020.101826
   Kustatscher M., 2015, FAMILIES INTERGENERA, P1
   Leichenko R, 2014, WIRES CLIM CHANGE, V5, P539, DOI 10.1002/wcc.287
   Lin KHE, 2016, GEOGR J, V182, P135, DOI 10.1111/geoj.12141
   Lincoln YS, 2008, QUAL INQ, V14, P784, DOI 10.1177/1077800408318304
   Mearns R., 2010, SOCIAL DIMENSIONS CL, DOI [10.1596/978-0-8213-7887-8, DOI 10.1596/978-0-8213-7887-8]
   Neumayer E, 2007, ANN ASSOC AM GEOGR, V97, P551, DOI 10.1111/j.1467-8306.2007.00563.x
   Nightingale AJ, 2016, AREA, V48, P41, DOI 10.1111/area.12195
   Norris FH, 2008, AM J COMMUN PSYCHOL, V41, P127, DOI 10.1007/s10464-007-9156-6
   Okoliko DA, 2021, J MEDIA ETHICS, V36, P36, DOI 10.1080/23736992.2020.1856666
   Osborne N, 2015, PLAN THEOR, V14, P130, DOI 10.1177/1473095213516443
   Paprocki K., 2015, Himal Southasian, V28, P54
   Pelling M, 2008, ENVIRON PLANN A, V40, P867, DOI 10.1068/a39148
   Ragavan MI, 2020, PEDIATRICS, V145, DOI 10.1542/peds.2019-3169
   Räsänen A, 2020, INT J DISAST RISK RE, V45, DOI 10.1016/j.ijdrr.2020.101485
   Sanyal S, 2016, INT J DISAST RISK RE, V19, P101, DOI 10.1016/j.ijdrr.2016.08.010
   Sauchyn D., 2017, PRAIRIE PROVINCES CH
   Shepherd M, 2015, GEOGR COMPASS, V9, P579, DOI 10.1111/gec3.12244
   Shonkoff SB, 2011, CLIMATIC CHANGE, V109, P485, DOI 10.1007/s10584-011-0310-7
   Smith LindaTuhiwai., 2012, Decolonizing Methodologies: Research and Indigenous Peoples, V2nd
   Taylor M., 2013, POLITICAL ECOLOGY CL, DOI [10.23943/princeton/9780691148472.001.0001, DOI 10.23943/PRINCETON/9780691148472.001.0001]
   Thomas K, 2019, WIRES CLIM CHANGE, V10, DOI 10.1002/wcc.565
   Touza J, 2021, ENVIRON MANAGE, V68, P505, DOI 10.1007/s00267-021-01500-y
   Uddin MS, 2021, DISASTER PREV MANAG, V30, P94, DOI 10.1108/DPM-03-2020-0069
   Vaismoradi M, 2013, NURS HEALTH SCI, V15, P398, DOI 10.1111/nhs.12048
   Versey HS, 2021, POL INS BEH BRAIN SC, V8, P67, DOI 10.1177/2372732220982628
   Versey HS, 2016, SOC SCI RES, V57, P99, DOI 10.1016/j.ssresearch.2015.12.012
NR 66
TC 5
Z9 5
U1 7
U2 25
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 APR
PY 2024
VL 32
IS 2
SI SI
BP 1386
EP 1400
DI 10.1002/sd.2676
EA JUL 2023
PG 15
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 MP4G9
UT WOS:001040718900001
DA 2025-01-10
ER

PT J
AU Ng, K
   Borges, P
   Phillips, MR
   Medeiros, A
   Calado, H
AF Ng, Kiat
   Borges, Paulo
   Phillips, Michael Robert
   Medeiros, Antonio
   Calado, Helena
TI An integrated coastal vulnerability approach to small islands: The
   Azores case
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Coastal hazards; Coastal planning; Coastal adaptation; Resilience;
   Coastal vulnerability index (CVI); Sustainable coastal development
ID SAO-MIGUEL ISLAND; SEA-LEVEL RISE; ADAPTIVE CAPACITY; ADAPTATION;
   RESILIENCE; INDEX; ASSESSMENTS; TOPOGRAPHY; SYSTEMS; FUTURE
AB Coastal development in small islands needs adapting to climate and ecosystem changes in the Anthropocene era. Understanding variability of coastal vulnerability along the entire coastline informs coastal planning and management at an island-wide scale as some coastal stretches are more appropriate for big-scale development, while others require additional coastal protection and/or ecosystem conservation. To date, few researches focused on developing macro-scale coastal vulnerability index at an island or archipelagic-scale. This paper fills a knowledge gap by developing an integrated coastal vulnerability index (ICVI) for nine small islands in the Azores archipelago. Considering that degree of vulnerability varies according to human-environment traits of each coastal stretch, this paper characterises integrated coastal vulnerability according to three broad attributes, i.e. exposure to external stressors, biophysical features and socioeconomic characteristics. Using field work, semi-quantitative analysis and GIS, ICVI is a simple and relatively quick approach that provides a broad overview of coastal vulnerability in small island context. A set of six accessible and representative parameters was employed as indicators for this vulnerability assessment, i.e. type of cliff; type of beach; coastal defences; exposure to swell/storm waves; outcrop flooded and land-use. The entire coastline of each island was divided into segments according to their geomorphic compartments and subsequently assigned with a relative ICVI value. Each segment was ranked into five classes ranging from very low to very high based on its relative degree of vulnerability. While majority of the coasts are of moderate relative vulnerability in the Azores, vulnerability varies broadly along the coast between low, moderate and high. The ICVI approach serves as a useful decision support tool to facilitate effective planning and management for the Azores small islands and the methodology has the flexibility of being scaled deep by adding more indicators where necessary and available or scaled out to other small islands. (C) 2019 Elsevier B.V. All rights reserved.
C1 [Ng, Kiat] Univ Porto, Interdisciplinary Ctr Marine & Environm Res CIIMA, Fac Engn, Rua Dr Roberto Frias, P-4200465 Porto, Portugal.
   [Borges, Paulo; Medeiros, Antonio] Univ Acores, Fac Ciencias & Tecnol, Rua Mae Deus, P-9500321 Ponta Delgada, Acores, Portugal.
   [Phillips, Michael Robert] Univ Wales Trinity St David, Coastal & Marine Res Grp, Swansea SA16ED, W Glam, Wales.
   [Calado, Helena] Univ Acores, MARE Ctr Ciencias Mar & Ambiente, Fac Ciencias & Tecnol, Rua Mae Deus, P-9501855 Ponta Delgada, Acores, Portugal.
C3 Universidade do Porto; Universidade dos Acores; University of Wales
   Trinity St David; Universidade dos Acores
RP Ng, K (corresponding author), Univ Porto, Interdisciplinary Ctr Marine & Environm Res CIIMA, Fac Engn, Rua Dr Roberto Frias, P-4200465 Porto, Portugal.
EM kiatng@fe.up.pt; paulo.js.borges@uac.pt; mike.phillips@uwtsd.ac.uk;
   antonio.m.medeiros@uac.pt; helena.mg.calado@uac.pt
RI Borges, Paulo/M-7265-2013; Calado, Helena/L-7810-2013; Phillips,
   Michael/D-6720-2011
OI Calado, Helena/0000-0002-4043-4466; Phillips,
   Michael/0000-0001-5037-7023
FU Fundacao para a Ciencia e a Tecnologia (FCT, Portugal) postdoctoral
   fellowship [SFRH/BPD/120394/2016]; Fundação para a Ciência e a
   Tecnologia [SFRH/BPD/120394/2016] Funding Source: FCT
FX This research was supported by Fundacao para a Ciencia e a Tecnologia
   (FCT, Portugal) postdoctoral fellowship (SFRH/BPD/120394/2016).
CR Abuodha Pamela A. O., 2010, Journal of Coastal Conservation, V14, P189, DOI 10.1007/s11852-010-0097-0
   Adger WN, 2005, CR GEOSCI, V337, P399, DOI 10.1016/j.crte.2004.11.004
   Adger WN, 2005, SCIENCE, V309, P1036, DOI 10.1126/science.1112122
   Andrade C, 2008, HOLOCENE, V18, P745, DOI 10.1177/0959683608091794
   Barnett J, 2010, EARTHSCAN CLIM, P1
   Barnett J., 2016, The Palgrave handbook of international development, P731, DOI DOI 10.1057/978-1-137-42724-3-40
   Berkes F., 1998, LINKING SOCIAL ECOLO
   Beutel RG, 2014, INSECT MORPHOLOGY AND PHYLOGENY: A TEXTBOOK FOR STUDENTS OF ENTOMOLOGY, P117
   Bijlsma L., 1996, Climate Change 1995-Impacts, P289
   Borges M.de F., 2009, Ecosystems and Human Well-Being: Portuguese Assessment of the Millennium Ecosystem Assessment [in Portuguese], P437
   Borges P, 2002, J COASTAL RES, P89
   Borges P, 2014, J COASTAL RES, P385, DOI 10.2112/SI70-065.1
   Borges P., 2003, THESIS
   Borges P., 1999, STORM CHARACTE UNPUB
   Brooks N., 2003, Tyndall Centre for Climate Change Research, DOI DOI 10.1086/379713
   Calado H, 2011, NAT HAZARDS, V58, P427, DOI 10.1007/s11069-010-9676-5
   Cohen PJ, 2016, AMBIO, V45, pS309, DOI 10.1007/s13280-016-0831-4
   COS, 2007, CART OC SOL REG AUT
   DAVIES WTR, 2012, THESIS
   De Souza RM, 2018, RESILIENCE: THE SCIENCE OF ADAPTATION TO CLIMATE CHANGE, P143, DOI 10.1016/B978-0-12-811891-7.00011-6
   Duvat VKE, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.478
   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
   Folke C., 2016, Oxford Research Encyclopedia of Environmental Science, DOI [10.1093/acrefore/9780199389414.013.8, DOI 10.1093/ACREFORE/9780199389414.013.8]
   Forbes DL, 2013, SUSTAIN SCI, V8, P327, DOI 10.1007/s11625-013-0218-4
   Gallopin GC, 2006, GLOBAL ENVIRON CHANG, V16, P293, DOI 10.1016/j.gloenvcha.2006.02.004
   GORNITZ V, 1991, GLOBAL PLANET CHANGE, V89, P379, DOI 10.1016/0921-8181(91)90118-G
   Gornitz V.M., 1994, J. Coast. Res, V12, P327
   Gutierrez B.T., 2007, U.S. Geological Survey Open-File Report 2007-1278
   INE, 2011, CENS 2011 POP RES PO
   Kantamaneni K, 2018, OCEAN COAST MANAGE, V158, P164, DOI 10.1016/j.ocecoaman.2018.03.039
   Koroglu A, 2019, OCEAN COAST MANAGE, V178, DOI 10.1016/j.ocecoaman.2019.05.001
   Lavell A, 2014, ENVIRON HAZARDS-UK, V13, P267, DOI 10.1080/17477891.2014.935282
   McLaughlin S, 2010, ENVIRON HAZARDS-UK, V9, P233, DOI 10.3763/ehaz.2010.0052
   Mimura N, 1999, CLIM RES, V12, P137, DOI 10.3354/cr012137
   Ng K, 2014, SCI TOTAL ENVIRON, V481, P142, DOI 10.1016/j.scitotenv.2014.01.067
   Ng K, 2013, APPL GEOGR, V44, P99, DOI 10.1016/j.apgeog.2013.07.013
   Nguyen TTX, 2016, OCEAN COAST MANAGE, V123, P18, DOI 10.1016/j.ocecoaman.2015.11.022
   Nurse LA, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1613
   Palmer BJ, 2011, J COASTAL RES, P1390
   Pelling M., 2001, Environmental Hazards, V3, P49
   Pendleton E.A., 2010, Coastal vulnerability assessment of the Northern Gulf of Mexico to sea-level rise and coastal change: U.S. Geological Survey Open-File Report 2010-1146
   Pethick JS, 2000, ENVIRON CONSERV, V27, P359
   Phillips MR, 2018, J COASTAL RES, P1411, DOI 10.2112/SI85-283.1
   Rusu E, 2016, RENEW ENERG, V85, P687, DOI 10.1016/j.renene.2015.07.042
   Rusu L, 2012, RENEW ENERG, V45, P183, DOI 10.1016/j.renene.2012.02.027
   SGPA, 2015, UNPUB
   Smit B, 2006, GLOBAL ENVIRON CHANG, V16, P282, DOI 10.1016/j.gloenvcha.2006.03.008
   Smith W. H. F., 1997, Science, V277, P1956, DOI 10.1126/science.277.5334.1956
   Soares MB, 2012, INT J CLIM CHANG STR, V4, P6, DOI 10.1108/17568691211200191
   Srinivasan UT, 2010, CLIM POLICY, V10, P298, DOI 10.3763/cpol.2009.0652
   Tompkins E.L., 2005, Surviving climate change in small islands: A guidebook
   Walker B, 2004, ECOL SOC, V9
   Woodroffe CD, 2008, GLOBAL PLANET CHANGE, V62, P77, DOI 10.1016/j.gloplacha.2007.11.001
   Yamano H, 2007, GLOBAL PLANET CHANGE, V57, P407, DOI 10.1016/j.gloplacha.2007.02.007
   Young OR, 2006, GLOBAL ENVIRON CHANG, V16, P304, DOI 10.1016/j.gloenvcha.2006.03.004
NR 56
TC 28
Z9 30
U1 0
U2 75
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 2019
VL 690
BP 1218
EP 1227
DI 10.1016/j.scitotenv.2019.07.013
PG 10
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA IT0QC
UT WOS:000482549900110
PM 31470484
DA 2025-01-10
ER

PT J
AU Locatelli, JL
   Popin, GV
   Santos, RS
   Bieluczyk, W
   Cipriani, LT
   Cherubin, MR
   Cerri, CEP
AF Locatelli, Jorge Luiz
   Popin, Gustavo Vicentini
   Santos, Rafael Silva
   Bieluczyk, Wanderlei
   Cipriani, Leticia Thomaz
   Cherubin, Mauricio Roberto
   Cerri, Carlos Eduardo Pellegrino
TI A comprehensive assessment of greenhouse gas emissions research in the
   Cerrado region, Brazil
SO CATENA
LA English
DT Article
DE Climate change; Conservation agriculture; Tropical agriculture; Soil
   organic matter; Carbon balance; Climate adaptation
ID LAND-USE CHANGE; NITROUS-OXIDE EMISSIONS; ORGANIC-CARBON STOCKS; SOIL
   CO2 EMISSION; N FERTILIZATION; N2O EMISSIONS; COVER CROPS; SUGARCANE;
   FLUXES; TILLAGE
AB The increasing demand for food, fiber, and (bio)energy boosted by population growth has accentuated agricultural expansion, increasing global greenhouse gas (GHG) emissions. This scenario is valid in Brazil, where agriculture accounts for the largest part of the nation's GHG emissions, primarily associated with the expansion of agriculture over areas of native vegetation, especially in the Cerrado region. However, despite the contribution of this sector to GHG emissions, there is a limited understanding of how different systems affect these emissions, as well as the current state of the art on this topic. Therefore, we performed a comprehensive literature review to synthesize the information about GHG emissions in the region, including cropping systems where GHG was measured, methodological procedures, and the main results achieved. Our review shows that the subject of "GHG" has been poorly investigated, with a huge discrepancy compared to other related topics such as soil organic matter. Most studies (31 % of 236) only mentioned GHG-related terms but did not measure them. The studies that measured GHG (n = 39) were conducted mainly in the south-central part of the region and were mostly limited to short-term experiments (< 5 years) or monitoring periods (< 1 year), using manual static chambers. The analysis of the available GHG data indicated that converting Cerrado into agriculture increases N2O emissions by 0.45 kg ha(-1) year(-1) while decreasing CH4 influx by 3 kg ha(-1) year(-1). Despite that, notillage combined with cover crops effectively reduces N2O emissions ( -0.3 kg ha(-1) year(-1)). Our findings reveal a significant gap in monitoring GHG fluxes in the Cerrado region, particularly in the northern part where Brazil's new agricultural frontier, the Matopiba region, is located. Efforts should prioritize generating comprehensive GHG data for Cerrado agriculture by employing more robust monitoring protocols. This would help guide producers, researchers, and policymakers to enhance agricultural management practices toward greater sustainability.
C1 [Locatelli, Jorge Luiz; Popin, Gustavo Vicentini; Cipriani, Leticia Thomaz; Cherubin, Mauricio Roberto; Cerri, Carlos Eduardo Pellegrino] Univ Sao Paulo, Luiz De Queiroz Coll Agr, Dept Soil Sci, Ave Padua Dias 11, BR-13418900 Piracicaba, SP, Brazil.
   [Santos, Rafael Silva] Colorado State Univ, Nat Resource Ecol Lab, Univ Ave 307, Ft Collins, CO 80521 USA.
   [Bieluczyk, Wanderlei] Univ Sao Paulo, Ctr Nucl Energy Agr, Isotop Ecol Lab, Ave Centenario 303, BR-13416000 Piracicaba, SP, Brazil.
   [Cherubin, Mauricio Roberto; Cerri, Carlos Eduardo Pellegrino] Univ Sao Paulo, Ctr Carbon Res Trop Agr CCARBON, Padua Dias Ave 11, BR-13418900 Piracicaba, SP, Brazil.
C3 Universidade de Sao Paulo; Colorado State University; Universidade de
   Sao Paulo; Universidade de Sao Paulo
RP Locatelli, JL (corresponding author), Univ Sao Paulo, Luiz De Queiroz Coll Agr, Dept Soil Sci, Ave Padua Dias 11, BR-13418900 Piracicaba, SP, Brazil.
EM jorgellocatelli@usp.br
RI Bieluczyk, Wanderlei/G-8142-2014; Cherubin, Mauricio/A-6896-2016;
   Locatelli, Jorge/AAH-3790-2019
OI Cherubin, Mauricio Roberto/0000-0001-7920-8362
FU Sao Paulo Research Foundation (FAPESP) [2021/14989-0, 2022/15778-6,
   2021/10573-4, 2020/15230-5]; FAPESP [2019/25988-5, 2023/18333-8];
   National Council for Scientific and Technological Development (CNPq)
   [311787/2021-5]; Research Centre for Greenhouse Gas Innovation (RCGI);
   Center for Carbon Research in Tropical Agriculture (CCARBON); Bayer Ag
   Company
FX J.L.L. thanks the Sao Paulo Research Foundation (FAPESP) for the
   research grants #2021/14989-0 and #2022/15778-6. G.V.P. thanks FAPESP
   for the research grant #2019/25988-5. W.B. thanks FAPESP for the
   post-doctoral scholarship (grant #2023/18333-8) . M.R.C. thanks the
   National Council for Scientific and Technological Development (CNPq) for
   the Research Productivity Fellowship (grant #311787/2021-5) .Funding:
   This work was supported by the Sao Paulo Research Foundation (FAPESP)
   (grants #2021/10573-4 and #2020/15230-5) , the Research Centre for
   Greenhouse Gas Innovation (RCGI), the Center for Carbon Research in
   Tropical Agriculture (CCARBON) , and Bayer Ag Company.
CR Abdalla M, 2019, GLOBAL CHANGE BIOL, V25, P2530, DOI 10.1111/gcb.14644
   Alvares CA, 2013, METEOROL Z, V22, P711, DOI 10.1127/0941-2948/2013/0507
   Alvarez DO, 2023, MOL ECOL, V32, P3257, DOI 10.1111/mec.16912
   Amelung W, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-18887-7
   [Anonymous], 2004, Mapa de Biomas do Brasil. Primeira Aproximacao. Escala 1:5.000.000
   Azevedo T., 2020, Tech
   Batlle-Bayer L, 2010, AGR ECOSYST ENVIRON, V137, P47, DOI 10.1016/j.agee.2010.02.003
   Bayer C, 2016, SOIL TILL RES, V161, P86, DOI 10.1016/j.still.2016.03.011
   Beillouin D, 2021, GLOBAL CHANGE BIOL, V27, P4697, DOI 10.1111/gcb.15747
   Bieluczyk W, 2023, J ENVIRON MANAGE, V344, DOI 10.1016/j.jenvman.2023.118573
   Blanco-Canqui H, 2020, SOIL SCI SOC AM J, V84, P1527, DOI 10.1002/saj2.20129
   Blanco-Canqui H, 2015, AGRON J, V107, P2449, DOI 10.2134/agronj15.0086
   Bodelier PLE, 2004, FEMS MICROBIOL ECOL, V47, P265, DOI 10.1016/S0168-6496(03)00304-0
   Brito L.C.R., 2023, Engenharia Agricola, V43, DOI [10.1590/1809-4430-Eng.Agric.v43n2, DOI 10.1590/1809-4430-ENG.AGRIC.V43N2]
   Campanha MM, 2019, SCI TOTAL ENVIRON, V692, P1165, DOI 10.1016/j.scitotenv.2019.07.315
   Canteral KFF, 2023, ENVIRON SCI POLLUT R, V30, P61052, DOI 10.1007/s11356-023-26824-6
   Carvalho A.M., 2006, Emissao de oxidos de nitrogenio associada a aplicacao de ureia sob plantio convencional e direto, P679
   Carvalho A.M., 2022, Land (Basel), V11, DOI [10.3390/ land11091535, DOI 10.3390/LAND11091535]
   Carvalho JLN, 2009, SOIL TILL RES, V103, P342, DOI 10.1016/j.still.2008.10.022
   Cherubin MR, 2016, GEODERMA, V267, P156, DOI 10.1016/j.geoderma.2016.01.004
   CONAB, 2022, Acompanhamento Da Safra Brasileira de Gros, VVolume 10
   Corrêa RS, 2016, PESQUI AGROPECU BRAS, V51, P1148, DOI [10.1590/s0100-204x2016000900014, 10.1590/S0100-204X2016000900014]
   da Silva JF, 2017, AGR ECOSYST ENVIRON, V246, P55, DOI 10.1016/j.agee.2017.05.019
   Oliveira DMD, 2016, AGR ECOSYST ENVIRON, V228, P38, DOI 10.1016/j.agee.2016.05.005
   Damian M, 2021, CATENA, V202, DOI 10.1016/j.catena.2021.105238
   de Carvalho AM, 2021, ENVIRON TECHNOL INNO, V22, DOI 10.1016/j.eti.2021.101470
   de Carvalho AM, 2017, NUTR CYCL AGROECOSYS, V108, P69, DOI 10.1007/s10705-017-9823-4
   de Carvalho AM, 2016, PESQUI AGROPECU BRAS, V51, P1213, DOI [10.1590/S0100-204X2016000900021, 10.1590/s0100-204x2016000900021]
   Carvalho MTD, 2013, PESQUI AGROPECU BRAS, V48, P478, DOI 10.1590/S0100-204X2013000500003
   de Oliveira AD, 2023, J ENVIRON MANAGE, V348, DOI 10.1016/j.jenvman.2023.119295
   de Oliveira AD, 2021, SCI AGR, V78, DOI [10.1590/1678-992X-2018-0355, 10.1590/1678-992x-2018-0355]
   Dias LCP, 2016, GLOBAL CHANGE BIOL, V22, P2887, DOI 10.1111/gcb.13314
   Don A, 2011, GLOBAL CHANGE BIOL, V17, P1658, DOI 10.1111/j.1365-2486.2010.02336.x
   dos Santos IL, 2016, AGR ECOSYST ENVIRON, V233, P111, DOI 10.1016/j.agee.2016.08.027
   Velazco SJE, 2019, DIVERS DISTRIB, V25, P660, DOI 10.1111/ddi.12886
   Cruvinel EBF, 2011, AGR ECOSYST ENVIRON, V144, P29, DOI 10.1016/j.agee.2011.07.016
   Fialho RC, 2019, FLORESTA AMBIENTE, V26, DOI 10.1590/2179-8087.067917
   Gibbs HK, 2015, SCIENCE, V347, P377, DOI 10.1126/science.aaa0181
   Gmach MR, 2018, GEODERMA REG, V14, DOI 10.1016/j.geodrs.2018.e00178
   Gomes LC, 2019, GEODERMA, V340, P337, DOI 10.1016/j.geoderma.2019.01.007
   Gosling SN, 2016, CLIMATIC CHANGE, V134, P371, DOI 10.1007/s10584-013-0853-x
   Grace PR, 2020, J ENVIRON QUAL, V49, P1126, DOI 10.1002/jeq2.20124
   Green VS, 2007, SOIL TILL RES, V92, P114, DOI 10.1016/j.still.2006.01.004
   Gregorich E, 2015, ADV AGRON, V132, P39, DOI 10.1016/bs.agron.2015.02.004
   Guo LB, 2002, GLOBAL CHANGE BIOL, V8, P345, DOI 10.1046/j.1354-1013.2002.00486.x
   Hales S., 2014, QUANTITATIVE RISK AS
   Harvey MJ, 2020, J ENVIRON QUAL, V49, P1110, DOI 10.1002/jeq2.20129
   Henderson B., 2022, SOIL CARBON SEQUESTRATION BY AGRICULTURE POLICY OPTIONS Soil Carbon Sequestration by Agriculture: Policy Options
   Hensen A, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/2/025022
   Hong CP, 2021, NATURE, V589, P554, DOI 10.1038/s41586-020-03138-y
   Huddell A, 2021, AGROSYS GEOSCI ENV, V4, DOI 10.1002/agg2.20169
   IBGE, 2017, Censo Agropecuario-resultados definitivos
   IPCC, 2019, Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories
   Kaschuk G, 2011, PLANT SOIL, V338, P467, DOI 10.1007/s11104-010-0559-z
   Lahsen M, 2016, ENVIRONMENT, V58, P4, DOI 10.1080/00139157.2016.1229537
   Lange M, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms7707
   Leip A, 2018, ATMOS ENVIRON, V174, P237, DOI 10.1016/j.atmosenv.2017.12.006
   Lessa ACR, 2014, AGR ECOSYST ENVIRON, V190, P104, DOI 10.1016/j.agee.2014.01.010
   Li YZ, 2020, SOIL TILL RES, V204, DOI 10.1016/j.still.2020.104721
   Locatelli JL, 2023, AGRONOMY-BASEL, V13, DOI 10.3390/agronomy13010071
   Locatelli JL, 2022, GEODERMA REG, V28, DOI 10.1016/j.geodrs.2021.e00474
   Lopes AS, 2016, ADV AGRON, V137, P1, DOI 10.1016/bs.agron.2015.12.004
   Mahama GY, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12114403
   Maier M, 2022, J PLANT NUTR SOIL SC, V185, P447, DOI 10.1002/jpln.202200199
   Manlay RJ, 2007, AGR ECOSYST ENVIRON, V119, P217, DOI 10.1016/j.agee.2006.07.011
   MapBiomas, 2022, MapBiomas-Colecao 7.1 Uso e Cobertura do Solo WWW Document
   Martins MR, 2015, SOIL TILL RES, V151, P75, DOI 10.1016/j.still.2015.03.004
   [Masson-Delmotte V. IPCC IPCC], 2021, Summary for Policy Makers
   McDaniel MD, 2019, ECOSYSTEMS, V22, P1424, DOI 10.1007/s10021-019-00347-z
   McManus C, 2021, SCIENTOMETRICS, V126, P801, DOI 10.1007/s11192-020-03762-5
   Mello FFC, 2014, NAT CLIM CHANGE, V4, P605, DOI [10.1038/nclimate2239, 10.1038/NCLIMATE2239]
   Metay A, 2007, GEODERMA, V141, P78, DOI 10.1016/j.geoderma.2007.05.010
   Minasny B, 2017, GEODERMA, V292, P59, DOI 10.1016/j.geoderma.2017.01.002
   Moitinho MR, 2018, SUGAR TECH, V20, P658, DOI 10.1007/s12355-018-0595-1
   Muhammad I, 2022, FRONT MICROBIOL, V13, DOI 10.3389/fmicb.2022.868862
   Nader HB, 2022, SCIENCE, V378, P931, DOI 10.1126/science.adf9526
   Carvalho JLN, 2014, AGR ECOSYST ENVIRON, V183, P167, DOI 10.1016/j.agee.2013.11.014
   Oliveira DMS, 2024, GEODERMA REG, V37, DOI 10.1016/j.geodrs.2024.e00796
   Paustian K, 2016, NATURE, V532, P49, DOI 10.1038/nature17174
   Petherick A., 2017, Nature, V548, P249
   Petter FA, 2016, J ENVIRON MANAGE, V169, P27, DOI 10.1016/j.jenvman.2015.12.020
   Pinto AD, 2006, EARTH INTERACT, V10, DOI 10.1175/EI146.1
   Poeplau C, 2015, AGR ECOSYST ENVIRON, V200, P33, DOI 10.1016/j.agee.2014.10.024
   Rada N, 2013, FOOD POLICY, V38, P146, DOI 10.1016/j.foodpol.2012.11.002
   Ramos MLG, 2024, AGRONOMY-BASEL, V14, DOI 10.3390/agronomy14061257
   Ribeiro FP, 2023, PLANTS-BASEL, V12, DOI 10.3390/plants12142751
   Tavanti RFR, 2020, CATENA, V194, DOI 10.1016/j.catena.2020.104702
   Rodrigues GG, 2023, FORESTRY, V96, P618, DOI 10.1093/forestry/cpad001
   Salton JC, 2014, AGR ECOSYST ENVIRON, V190, P70, DOI 10.1016/j.agee.2013.09.023
   Santos RS, 2021, GEODERMA, V400, DOI 10.1016/j.geoderma.2021.115149
   Sato JH, 2019, EUR J SOIL SCI, V70, P1183, DOI 10.1111/ejss.12819
   Sato JH, 2017, NUTR CYCL AGROECOSYS, V108, P55, DOI 10.1007/s10705-017-9822-5
   Sattolo TMS, 2021, SOIL SCI SOC AM J, V85, P1799, DOI 10.1002/saj2.20306
   Serrano-Silva N., 2014, Methanogenesis and Methanotrophy in Soil: A Review, V1
   Shcherbak I, 2014, P NATL ACAD SCI USA, V111, P9199, DOI 10.1073/pnas.1322434111
   Silva JF, 2006, J BIOGEOGR, V33, P536, DOI 10.1111/j.1365-2699.2005.01422.x
   Silva WMD, 2022, AGRICULTURE-BASEL, V12, DOI 10.3390/agriculture12020163
   Neto MS, 2011, REV BRAS CIENC SOLO, V35, P63, DOI 10.1590/S0100-06832011000100006
   Siqueira-Neto M, 2021, EUR J SOIL SCI, V72, P1431, DOI 10.1111/ejss.13059
   Smith KA, 2018, EUR J SOIL SCI, V69, P10, DOI 10.1111/ejss.12539
   Smith P, 2008, NUTR CYCL AGROECOSYS, V81, P169, DOI 10.1007/s10705-007-9138-y
   Souza CM, 2020, REMOTE SENS-BASEL, V12, DOI 10.3390/rs12172735
   Spera S, 2017, TROP CONSERV SCI, V10, DOI 10.1177/1940082917720662
   Spera SA, 2016, GLOBAL CHANGE BIOL, V22, P3405, DOI 10.1111/gcb.13298
   Steffen W, 2015, SCIENCE, V347, DOI 10.1126/science.1259855
   STEUDLER PA, 1991, BIOTROPICA, V23, P356, DOI 10.2307/2388252
   Tanabe K., 2006, 2006 IPCC Guidelines for National Greenhouse Gas Inventories
   Team RC, 2021, R LANGUAGE ENV STAT
   Teixeira RD, 2020, LAND DEGRAD DEV, V31, P909, DOI 10.1002/ldr.3480
   Teodoro PE, 2024, J CLEAN PROD, V434, DOI 10.1016/j.jclepro.2023.139983
   van Eck NJ, 2010, SCIENTOMETRICS, V84, P523, DOI 10.1007/s11192-009-0146-3
   Varella RF, 2004, ECOL APPL, V14, pS221, DOI 10.1890/01-6014
   Veloso MG, 2019, SOIL TILL RES, V190, P139, DOI 10.1016/j.still.2019.03.003
   Vicentini ME, 2019, PLANT SOIL, V444, P193, DOI 10.1007/s11104-019-04262-z
   Virk AL, 2022, AGR ECOSYST ENVIRON, V335, DOI 10.1016/j.agee.2022.108010
   Vizioli B, 2021, SOIL TILL RES, V209, DOI 10.1016/j.still.2021.104935
   Wang C, 2021, AGRONOMY-BASEL, V11, DOI 10.3390/agronomy11040770
   Wiesmeier M, 2019, GEODERMA, V333, P149, DOI 10.1016/j.geoderma.2018.07.026
   WMO W.M.O., 2022, The State of Greenhouse Gases in the Atmosphere Based on Global Observations through 2021
   World Bank, 2023, Research and development expenditure (% of GDP) WWW Document
   You LC, 2022, SOIL BIOL BIOCHEM, V165, DOI 10.1016/j.soilbio.2021.108523
   Zamudio KR, 2018, SCIENCE, V361, P1322, DOI 10.1126/science.aav3296
NR 122
TC 0
Z9 0
U1 4
U2 4
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0341-8162
EI 1872-6887
J9 CATENA
JI Catena
PD DEC
PY 2024
VL 247
AR 108538
DI 10.1016/j.catena.2024.108538
EA NOV 2024
PG 15
WC Geosciences, Multidisciplinary; Soil Science; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology; Agriculture; Water Resources
GA M3L9Z
UT WOS:001356602900001
DA 2025-01-10
ER

PT J
AU Schneider, R
   Koch, J
   Troldborg, L
   Henriksen, HJ
   Stisen, S
AF Schneider, Raphael
   Koch, Julian
   Troldborg, Lars
   Henriksen, Hans Jorgen
   Stisen, Simon
TI Machine-learning-based downscaling of modelled climate change impacts on
   groundwater table depth
SO HYDROLOGY AND EARTH SYSTEM SCIENCES
LA English
DT Article
ID HIGH-RESOLUTION; RANDOM FOREST
AB There is an urgent demand for assessments of climate change impacts on the hydrological cycle at high spatial resolutions. In particular, the impacts on shallow groundwater levels, which can lead to both flooding and drought, have major implications for agriculture, adaptation, and urban planning. Predicting such hydrological impacts is typically performed using physically based hydrological models (HMs). However, such models are computationally expensive, especially at high spatial resolutions. This study is based on the Danish national groundwater model, set up as adistributed, integrated surface-subsurface model at a 500 m horizontalresolution. Recently, a version at a higher resolution of 100 m was created, amongst others, to better represent the uppermost groundwater table and to meet end-user demands for water management and climate adaptation. However, the increase in resolution of the hydrological model also increases computational bottleneck. To evaluate climate change impacts, a large ensemble of climate models was run with the 500 m hydrological model, while performing the same ensemble run with the 100 m resolution nationwide model was deemed infeasible. The desired outputs at the 100 m resolution were produced by developing a novel, hybrid downscaling method based on machine learning (ML). Hydrological models for five subcatchments, covering around 9 % of Denmark and selected to represent a range of hydrogeological settings, were run at 100 m resolutions with forcings from a reduced ensemble of climate models. Random forest (RF) algorithms were established using the simulated climate change impacts (future - present) on water table depth at 100 m resolution from those submodels as training data. The trained downscaling algorithms were then applied to create nationwidemaps of climate-change-induced impacts on the shallow groundwater table at 100 m resolutions. These downscaled maps were successfully validated against results from a validation submodel at a 100 m resolution excluded from training the algorithms, and compared to the impact signals from the 500 m HM across Denmark. The suggested downscaling algorithm also opens for the spatial downscalingof other model outputs. It has the potential for further applications where, for example, computational limitations inhibit running distributedHMs at fine resolutions.
C1 [Schneider, Raphael; Koch, Julian; Troldborg, Lars; Henriksen, Hans Jorgen; Stisen, Simon] Geol Survey Denmark & Greenland GEUS, Dept Hydrol, DK-1350 Copenhagen K, Denmark.
C3 Geological Survey Of Denmark & Greenland
RP Schneider, R (corresponding author), Geol Survey Denmark & Greenland GEUS, Dept Hydrol, DK-1350 Copenhagen K, Denmark.
EM rs@geus.dk
RI Schneider, Raphael/H-7499-2018; Stisen, Simon/Q-2832-2017; Koch,
   Julian/D-2509-2015; troldborg, lars/G-8754-2018
OI Henriksen, Hans Jorgen/0000-0003-4821-5310; Stisen,
   Simon/0000-0001-6695-8412; Koch, Julian/0000-0002-7732-3436; Schneider,
   Raphael/0000-0001-9628-0809; troldborg, lars/0000-0002-7366-1438
FU HIP4Plus project
FX This research has been supported by the HIP4Plus project, funded as part
   of the Danish Digital Strategy 2016-2020, initiative 6.1 common data on
   topography, climate and water (Den Faellesoffentlige
   Digitaliseringsstrategi Initiativ 6.1, Faelles data om terraen, klima og
   vand, FODS6.1).
CR ABBOTT MB, 1986, J HYDROL, V87, P45, DOI 10.1016/0022-1694(86)90114-9
   Addor N, 2018, WATER RESOUR RES, V54, P8792, DOI 10.1029/2018WR022606
   Anderson MC, 2021, REMOTE SENS ENVIRON, V252, DOI 10.1016/j.rse.2020.112189
   Anderson MC, 2004, J HYDROMETEOROL, V5, P343, DOI 10.1175/1525-7541(2004)005<0343:AMRSMF>2.0.CO;2
   Beven K. J., 1979, HYDROL SCI B, V24, P43, DOI DOI 10.1080/02626667909491834
   Breiman L, 2001, MACH LEARN, V45, P5, DOI 10.1023/A:1010933404324
   Cheng JX, 2020, IEEE ACCESS, V8, P39623, DOI 10.1109/ACCESS.2020.2974785
   DHI, 2020, MIKE SHE US GUID REF
   Doherty J., 2015, WATERMARK NUMERICAL, DOI DOI 10.1111/GWAT.12360
   Fan Y, 2013, SCIENCE, V339, P940, DOI 10.1126/science.1229881
   Ghiggi G, 2019, EARTH SYST SCI DATA, V11, P1655, DOI 10.5194/essd-11-1655-2019
   Gleeson T, 2016, NAT GEOSCI, V9, P161, DOI 10.1038/NGEO2590
   Gonzalez RQ, 2021, ISPRS INT J GEO-INF, V10, DOI 10.3390/ijgi10110792
   Guzinski R, 2019, REMOTE SENS ENVIRON, V221, P157, DOI 10.1016/j.rse.2018.11.019
   Halsnaes K., SAMFUNDSOKONOMISKE K
   Henriksen H. J., 2020, SAMMENFATNINGSRAPPOR, DOI [10.22008/gpub/38112, DOI 10.22008/GPUB/38112]
   Henriksen H. J., 2018, FODS 6.1 Fasttrack metodeudvikling, P1, DOI DOI 10.22008/GPUB/32582
   Henriksen H. J., 2021, DOKUMENTATIONSRAPPOR, DOI [10.22008/gpub/38113, DOI 10.22008/GPUB/38113]
   Henriksen HJ, 2003, J HYDROL, V280, P52, DOI 10.1016/S0022-1694(03)00186-0
   Hojberg AL, 2013, ENVIRON MODELL SOFTW, V40, P202, DOI 10.1016/j.envsoft.2012.09.010
   Im J, 2016, ENVIRON EARTH SCI, V75, DOI 10.1007/s12665-016-5917-6
   Jacob D, 2014, REG ENVIRON CHANGE, V14, P563, DOI 10.1007/s10113-013-0499-2
   Jakobsen P. R., 2015, DANMARKS DIGITALE JO, DOI [10.22008/gpub/30680, DOI 10.22008/GPUB/30680]
   Koch J, 2022, GEUS B, V49, DOI 10.34194/geusb.v49.8292
   Koch J, 2021, FRONT WATER, V3, DOI 10.3389/frwa.2021.701726
   Koch J, 2019, HYDROL EARTH SYST SC, V23, P4603, DOI 10.5194/hess-23-4603-2019
   Koch J, 2019, WATER RESOUR RES, V55, P1451, DOI 10.1029/2018WR023939
   Mai J, 2021, J HYDROL ENG, V26, DOI [10.1061/(ASCE)HE.1943-5584.0002097, 10.1061/(asce)he.1943-5584.0002097]
   Meyer H, 2021, METHODS ECOL EVOL, V12, P1620, DOI 10.1111/2041-210X.13650
   Moller AB, 2018, GEODERMA, V320, P30, DOI 10.1016/j.geoderma.2018.01.018
   Motarjemi SK, 2021, J HYDROL-REG STUD, V36, DOI 10.1016/j.ejrh.2021.100839
   Nearing GS, 2021, WATER RESOUR RES, V57, DOI 10.1029/2020WR028091
   Nijzink RC, 2016, HYDROL EARTH SYST SC, V20, P1151, DOI 10.5194/hess-20-1151-2016
   Noorduijn SL, 2021, J HYDROL, V603, DOI 10.1016/j.jhydrol.2021.126796
   Olesen S. E., 2009, KORTLAEGNING POTENTI
   Pasten-Zapata E, 2019, GEOL SURV DEN GREENL, V43, DOI 10.34194/GEUSB-201943-01-02
   Read JS, 2019, WATER RESOUR RES, V55, P9173, DOI 10.1029/2019WR024922
   Refsgaard JC, 2016, HYDROLOG SCI J, V61, P2312, DOI 10.1080/02626667.2015.1131899
   Rodell M, 2018, NATURE, V557, P650, DOI 10.1038/s41586-018-0123-1
   Rodriguez-Galiano V, 2014, SCI TOTAL ENVIRON, V476, P189, DOI 10.1016/j.scitotenv.2014.01.001
   Samaniego L, 2019, B AM METEOROL SOC, V100, P2451, DOI 10.1175/BAMS-D-17-0274.1
   Scharling M, 9912 DAN MET I
   Schneider R, 2022, HUNTING INFORM STREA, V14, P110, DOI [10.3390/w14010110, DOI 10.3390/W14010110]
   Soltani M, 2021, J HYDROL, V603, DOI 10.1016/j.jhydrol.2021.127026
   Soylu ME, 2022, IEEE J-STARS, V15, P89, DOI 10.1109/JSTARS.2021.3124892
   Stisen S., 2019, NATL WATER RESOURCE, DOI [10.22008/gpub/32631, DOI 10.22008/GPUB/32631]
   Stisen S, 2011, VADOSE ZONE J, V10, P37, DOI 10.2136/vzj2010.0001
   Sun AY, 2020, FRONT WATER, V2, DOI 10.3389/frwa.2020.536743
   Tesoriero AJ, 2017, WATER RESOUR RES, V53, P7316, DOI 10.1002/2016WR020197
   The Danish Agency for Data Supply and Infrastructure (SDFI), 2021, HIP HYDR INF PROGN
   Thejll PA., 2021, METHODS USED DANISH
   Tran H, 2021, WATER-SUI, V13, DOI 10.3390/w13233393
   Tyralis H, 2019, WATER-SUI, V11, DOI 10.3390/w11050910
   van Roosmalen L, 2007, VADOSE ZONE J, V6, P554, DOI 10.2136/vzj2006.0093
   van Vuuren DP, 2011, CLIMATIC CHANGE, V109, P5, DOI [10.1007/s10584-011-0148-z, 10.1007/s10584-011-0157-y]
   Wood EF, 2011, WATER RESOUR RES, V47, DOI 10.1029/2010WR010090
   Wunsch A, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-28770-2
   Yang YB, 2017, REMOTE SENS-BASEL, V9, DOI 10.3390/rs9080789
   Zhang JX, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13030523
NR 59
TC 10
Z9 10
U1 1
U2 15
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 23
PY 2022
VL 26
IS 22
BP 5859
EP 5877
DI 10.5194/hess-26-5859-2022
PG 19
WC Geosciences, Multidisciplinary; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Geology; Water Resources
GA 6M0EN
UT WOS:000888550800001
OA gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Sinha, S
   Mondal, SK
   Mondal, S
   Hansda, S
   Patra, UK
AF Sinha, Subhajit
   Mondal, Sushanta Kumar
   Mondal, Subhronil
   Hansda, Sonu
   Patra, Uttam Kumar
TI Deciphering grain size populations and hydromorphological
   characteristics of the beach-dune system of East Coast of India:
   implications to coastal resilience and hazard mitigation
SO ENVIRONMENTAL EARTH SCIENCES
LA English
DT Article
DE End-member modelling analysis (EMMA); Grain size distributions; Coastal
   resilience; Erosion-accretion; East coast of India
ID SHORELINE CHANGE; LAKE-SEDIMENTS; PHOSPHORUS; IMPACT; RIVER
AB Beach-dune complexes are dynamic systems and fluctuations in its hydrodynamic conditions facilitate the exchange of sediments between onshore and offshore seasonally. The present study focuses on sediment texture within the beach-dune systems corresponding to an arcuate and a straight beach of Bakkhali and Talsari region, respectively. Multivariate statistical approach has been used to identify the end members and their proportion contributing to the grain size composition of the beach-dune system. To support the end members with a meaningful geological significance, discriminant analysis for depositional environments and CM plot for its dynamics are substantiated. The beach-dune system of Bakkhali shows appreciable homogenization of samples as compared to the Talsari region. In the Bakkhali beach an average of 0.238 m/year erosion and average rate of accretion is 0.423 m/year while in Talsari beach it is 0.238 m/year and 0.302 m/year, respectively. The end-member (EM) modelling showed relatively high contributions of medium- to fine-sand (ranging similar to 2.0 to 3.5 Phi) along with a minor amount of fines. Our study clarifies that grain size population exerts the primary control on erosion-accretion whilst hydraulic effects of wave and wind contribute to its spatial distribution. Since the particular size is lost from the system which needs to be replenished otherwise it disturbs the beach equilibrium. This study also bears its importance for beach nourishment as the end member analysis serves as a guide to replenish a beach with the required types of sediment grain sizes and search for its specific source areas. This work will also pave the way for advanced coastal resilience programs and climate adaptation planning and provide a platform for policymakers, technological innovators, the industry and researchers for coastal hazard mitigation and will ensure decision-makers regarding the execution of the plans on the ground.
C1 [Sinha, Subhajit; Mondal, Subhronil; Hansda, Sonu] Univ Calcutta, Dept Geol, 35 Ballygunge Circular Rd, Kolkata 700019, W Bengal, India.
   [Mondal, Sushanta Kumar] Sidho Kanho Birsha Univ, Dept Phys, Ranchi Rd, Purulia 723104, W Bengal, India.
   [Mondal, Subhronil] Indian Inst Sci Educ & Res IISER, Dept Earth Sci, Kolkata 741246, W Bengal, India.
   [Patra, Uttam Kumar] JK Coll, Dept Geog, Purulia 723101, W Bengal, India.
C3 University of Calcutta; Indian Institute of Science Education & Research
   (IISER) - Kolkata
RP Sinha, S (corresponding author), Univ Calcutta, Dept Geol, 35 Ballygunge Circular Rd, Kolkata 700019, W Bengal, India.
EM subho.ecstasy@gmail.com
RI Mondal, Subhronil/V-7796-2019
OI patra, uttam kumar/0000-0002-2840-1530
CR [Anonymous], EMMAGEO END MEMBER M
   BANKS R, 1979, CONTRIB MINERAL PETR, V70, P237, DOI 10.1007/BF00375353
   BEST TC, 1991, COASTAL SEDIMENTS 91, VOL 2, P2262
   Blott SJ, 2001, EARTH SURF PROC LAND, V26, P1237, DOI 10.1002/esp.261
   Boggs S., 2006, PRINCIPLES SEDIMENTO, V4th, P662
   Chatterjee N, 2015, J COASTAL SCI, V2, P54
   Christiansen C., 1986, GEOGR TIDSSKR-DEN, V86, P28, DOI [10.1080/00167223.1986.10649225, DOI 10.1080/00167223.1986.10649225]
   Church JA, 2001, CLIMATE CHANGE 2001: THE SCIENTIFIC BASIS, P639
   Collins JD, 2017, ARCHAEOMETRY, V59, P331, DOI 10.1111/arcm.12243
   CROWELL M, 1991, J COASTAL RES, V7, P839
   Dietze E, 2012, SEDIMENT GEOL, V243, P169, DOI 10.1016/j.sedgeo.2011.09.014
   Doctor DH, 2006, HYDROGEOL J, V14, P1171, DOI 10.1007/s10040-006-0031-6
   DOUGLAS BC, 1991, J GEOPHYS RES-OCEANS, V96, P6981, DOI 10.1029/91JC00064
   Elsherif EA., 2020, Egypt. J. Aquat. Biol. Fish., V24, P349, DOI [10.21608/ejabf.2020.70860, DOI 10.21608/EJABF.2020.70860]
   Friedman G.M., 1961, J SEDIMENT PETROL, V31, P514, DOI DOI 10.1306/74D70BCD-2B21-11D7-8648000102C1865D
   GHOSH SK, 1994, SEDIMENT GEOL, V89, P181, DOI 10.1016/0037-0738(94)90093-0
   Gowthaman R, 2015, INT J NAV ARCH OCEAN, V7, P939, DOI 10.1515/ijnaoe-2015-0065
   Hannigan RE, 2001, CHEM GEOL, V175, P397, DOI 10.1016/S0009-2541(00)00335-1
   Hartmann K, 2009, QUATERN INT, V194, P28, DOI 10.1016/j.quaint.2007.06.037
   Hicks DM, 1985, THESIS U CALIFORNIA, P210
   Integrated Coastal Zone Management (ICZM) Project, 2010, INT COAST ZON MAN IC, P1
   Jana A, 2013, J INDIAN SOC REMOTE, V41, P675, DOI 10.1007/s12524-012-0251-2
   Kaminsky GM, 2010, MAR GEOL, V273, P96, DOI 10.1016/j.margeo.2010.02.006
   Kantamaneni K, 2019, WATER-SUI, V11, DOI 10.3390/w11020393
   Klovan J.E., 1971, MATH GEOL, V3, P61, DOI DOI 10.1007/BF02047433
   KLOVAN JE, 1966, J SEDIMENT PETROL, V36, P115
   Kunte PD, 2001, INDIAN J MAR SCI, V30, P57
   LanFond EC, 1957, P IND ACAD SCI, VXLVI, P1
   MIESCH AT, 1980, J INT ASS MATH GEOL, V12, P523, DOI 10.1007/BF01034742
   Mohanty P. K., 2008, P50, DOI 10.1007/978-1-4020-6646-7_5
   Moore LJ, 2000, J COASTAL RES, V16, P111
   NATH BN, 1989, MAR GEOL, V87, P301, DOI 10.1016/0025-3227(89)90067-4
   Passe T, 1997, SEDIMENTOLOGY, V44, P1011
   PASSEGA R, 1969, SEDIMENTOLOGY, V13, P233, DOI 10.1111/j.1365-3091.1969.tb00171.x
   PASSEGA R., 1964, Jour. Sediment. Res, V34, P830, DOI DOI 10.1306/74D711A4-2B21-11D7-8648000102C1865D
   Passega R, 1957, AAPG B, V41, P1984
   Patch KB, 2006, DEV SAND BUDGE UNPUB
   Paterson GA, 2015, GEOCHEM GEOPHY GEOSY, V16, P4494, DOI 10.1002/2015GC006070
   Paul, 2006, ISSUESS COASTAL ZONE
   Phillips DL, 2001, OECOLOGIA, V127, P171, DOI 10.1007/s004420000578
   POTEMRA JT, 1991, J GEOPHYS RES-OCEANS, V96, P12667, DOI 10.1029/91JC01045
   Purkait B, 2002, J SEDIMENT RES, V72, P367, DOI 10.1306/091001720367
   Purkait B, 2019, ARAB J GEOSCI, V12, DOI 10.1007/s12517-019-4456-3
   Purkait B, 2014, SEDIMENT GEOL, V308, P53, DOI 10.1016/j.sedgeo.2014.05.001
   Putro AHS, 2020, J MAR SCI ENG, V8, DOI 10.3390/jmse8100749
   Riotte J, 2014, GEOCHIM COSMOCHIM AC, V145, P116, DOI 10.1016/j.gca.2014.09.015
   Román-Sierra J, 2013, SEDIMENTOLOGY, V60, P1484, DOI 10.1111/sed.12040
   Rúa A, 2016, J COASTAL RES, V32, P397, DOI 10.2112/JCOASTRES-D-14-00216.1
   Ruggiero P, 2003, J COASTAL RES, P57
   SAHU B.K., 1964, JOUR SEDIMENT PETROL, V34, P73, DOI DOI 10.1306/74D70FCE-2B21-11D7-8648000102C1865D
   Schoonees T, 2019, ESTUAR COAST, V42, P1709, DOI 10.1007/s12237-019-00551-z
   Sewell RBS., 1937, OUTLINE FIELD SCI IN, P17
   Sierra JP, 2014, CLIMATIC CHANGE, V124, P861, DOI 10.1007/s10584-014-1120-5
   Sinha Subhajit, 2021, Arabian Journal of Geosciences, V14, DOI 10.1007/s12517-020-06249-y
   Stauble DK, 1991, II29 CETN US ARM ENG, P10
   Staudt F, 2021, J COAST CONSERV, V25, DOI 10.1007/s11852-021-00801-y
   WALKER TW, 1976, GEODERMA, V15, P1, DOI 10.1016/0016-7061(76)90066-5
   Weltje GJ, 2007, SEDIMENT GEOL, V202, P409, DOI 10.1016/j.sedgeo.2007.03.007
   Weltje GJ, 2003, SEDIMENT GEOL, V162, P39, DOI 10.1016/S0037-0738(03)00235-5
   Weltje GJ, 1997, MATH GEOL, V29, P503, DOI 10.1007/BF02775085
   Xiao JL, 2009, HOLOCENE, V19, P899, DOI 10.1177/0959683609336574
   Zavisic A, 2016, SOIL BIOL BIOCHEM, V98, P127, DOI 10.1016/j.soilbio.2016.04.006
NR 62
TC 3
Z9 3
U1 1
U2 14
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 1866-6280
EI 1866-6299
J9 ENVIRON EARTH SCI
JI Environ. Earth Sci.
PD MAR
PY 2022
VL 81
IS 5
AR 147
DI 10.1007/s12665-022-10276-1
PG 20
WC Environmental Sciences; Geosciences, Multidisciplinary; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Geology; Water Resources
GA ZE4SI
UT WOS:000758874100004
DA 2025-01-10
ER

PT J
AU Perry, A
   Wachowiak, W
   Beaton, J
   Iason, G
   Cottrell, J
   Cavers, S
AF Perry, Annika
   Wachowiak, Witold
   Beaton, Joan
   Iason, Glenn
   Cottrell, Joan
   Cavers, Stephen
TI Identifying and testing marker-trait associations for growth and
   phenology in three pine species: Implications for genomic prediction
SO EVOLUTIONARY APPLICATIONS
LA English
DT Article
DE common garden trial; genetic variation; local adaptation; marker-trait
   association; predictive model; quantitative trait; Scots pine; SNP array
ID CONTROLLING ADAPTIVE TRAITS; COASTAL DOUGLAS-FIR; SCOTS PINE; WIDE
   ASSOCIATION; COMPLEX TRAITS; SNP DISCOVERY; GENETIC DIFFERENTIATION;
   POPULUS-TRICHOCARPA; CLIMATIC ADAPTATION; POPULATION
AB In tree species, genomic prediction offers the potential to forecast mature trait values in early growth stages, if robust marker-trait associations can be identified. Here we apply a novel multispecies approach using genotypes from a new genotyping array, based on 20,795 single nucleotide polymorphisms (SNPs) from three closely related pine species (Pinus sylvestris, Pinus uncinata and Pinus mugo), to test for associations with growth and phenology data from a common garden study. Predictive models constructed using significantly associated SNPs were then tested and applied to an independent multisite field trial of P. sylvestris and the capability to predict trait values was evaluated. One hundred and eighteen SNPs showed significant associations with the traits in the pine species. Common SNPs (MAF > 0.05) associated with bud set were only found in genes putatively involved in growth and development, whereas those associated with growth and budburst were also located in genes putatively involved in response to environment and, to a lesser extent, reproduction. At one of the two independent sites, the model we developed produced highly significant correlations between predicted values and observed height data (YA, height 2020: r = 0.376, p < 0.001). Predicted values estimated with our budburst model were weakly but positively correlated with duration of budburst at one of the sites (GS, 2015: r = 0.204, p = 0.034; 2018: r = 0.205, p = 0.034-0.037) and negatively associated with budburst timing at the other (YA: r = -0.202, p = 0.046). Genomic prediction resulted in the selection of sets of trees whose mean height was taller than the average for each site. Our results provide tentative support for the capability of prediction models to forecast trait values in trees, while highlighting the need for caution in applying them to trees grown in different environments.
C1 [Perry, Annika; Cavers, Stephen] UK Ctr Ecol & Hydrol Edinburgh, Penicuik EH26 0QB, Midlothian, Scotland.
   [Wachowiak, Witold] Adam Mickiewicz Univ, Fac Biol, Inst Environm Biol, Poznan, Poland.
   [Beaton, Joan; Iason, Glenn] James Hutton Inst, Aberdeen, Scotland.
   [Cottrell, Joan] Northern Res Stn, Forest Res, Roslin, Midlothian, Scotland.
C3 UK Centre for Ecology & Hydrology (UKCEH); Adam Mickiewicz University;
   James Hutton Institute
RP Perry, A (corresponding author), UK Ctr Ecol & Hydrol Edinburgh, Penicuik EH26 0QB, Midlothian, Scotland.
EM annt@ceh.ac.uk
RI Perry, Annika/F-6784-2014; Cavers, Stephen/B-7806-2010
OI Perry, Annika/0000-0002-7889-7597; Cavers, Stephen/0000-0003-2139-9236
FU GAPII - NERC [NE/K012177/1]; PROTREE - BBSRC [BB/L012243/1]; PROTREE -
   DEFRA [BB/L012243/1]; PROTREE - ESRC [BB/L012243/1]; PROTREE - Forestry
   Commission [BB/L012243/1]; PROTREE - NERC [BB/L012243/1]; PROTREE -
   Scottish Government under the Tree Health and Plant Biosecurity
   Initiative [BB/L012243/1]; B4EST - European Union [773383]; BBSRC
   [BB/L012227/1, BB/L012243/1] Funding Source: UKRI; NERC [NE/K012177/1,
   NE/H003959/1] Funding Source: UKRI
FX This work was financially supported by the following grants: GAPII
   (NE/K012177/1), funded by NERC; PROTREE (BB/L012243/1), funded jointly
   by BBSRC, DEFRA, ESRC, the Forestry Commission, NERC and the Scottish
   Government, under the Tree Health and Plant Biosecurity Initiative;
   B4EST (773383) funded by the European Union's Horizon 2020 research and
   innovation program. Dave Sim and Sheila Reid are gratefully acknowledged
   for their fieldwork assistance. Numerous placement students and casual
   workers are also thanked for their contribution to fieldwork.
   Constructive comments from four anonymous reviewers and the Associate
   Editor greatly improved the manuscript.
CR Ahrazem O, 2019, BMC GENOMICS, V20, DOI 10.1186/s12864-019-5666-5
   Aitken SN, 2001, TREE PHYSIOL SER, V1, P23
   [Anonymous], 2006, Plant Growth and Climate Change, DOI DOI 10.1002/9780470988695.CH3
   [Anonymous], 2024, Package 'Hmisc'
   Avia K, 2014, NEW PHYTOL, V204, P159, DOI 10.1111/nph.12901
   BALOCCHI CE, 1993, FOREST SCI, V39, P231
   Bartholomé J, 2016, BMC GENOMICS, V17, DOI 10.1186/s12864-016-2879-8
   Beaulieu J, 2014, HEREDITY, V113, P343, DOI 10.1038/hdy.2014.36
   Beaulieu J, 2011, GENETICS, V188, P197, DOI 10.1534/genetics.110.125781
   Blanca J, 2012, BMC GENOMICS, V13, DOI 10.1186/1471-2164-13-280
   Bogdan S, 2004, SILVAE GENET, V53, P198, DOI 10.1515/sg-2004-0036
   Boshnakov Georgi N, 2023, CRAN
   Bradbury PJ, 2007, BIOINFORMATICS, V23, P2633, DOI 10.1093/bioinformatics/btm308
   Budde KB, 2014, NEW PHYTOL, V201, P230, DOI 10.1111/nph.12483
   Calleja-Rodriguez A, 2020, BMC GENOMICS, V21, DOI 10.1186/s12864-020-07188-4
   Capblancq T, 2020, ANNU REV ECOL EVOL S, V51, P245, DOI 10.1146/annurev-ecolsys-020720-042553
   Chancerel E, 2011, BMC GENOMICS, V12, DOI 10.1186/1471-2164-12-368
   Cooke JEK, 2012, PLANT CELL ENVIRON, V35, P1707, DOI 10.1111/j.1365-3040.2012.02552.x
   Cooper HF, 2019, GLOBAL CHANGE BIOL, V25, P187, DOI 10.1111/gcb.14494
   Cornell MJ, 2007, GENOME RES, V17, P1809, DOI 10.1101/gr.6531807
   Crossa J, 2017, TRENDS PLANT SCI, V22, P961, DOI 10.1016/j.tplants.2017.08.011
   Dougherty P.M., 1994, Ecological Bulletins, V43, P64
   DUNN OJ, 1961, J AM STAT ASSOC, V56, P52, DOI 10.2307/2282330
   Durán R, 2019, TREES-STRUCT FUNCT, V33, P1505, DOI 10.1007/s00468-019-01875-w
   Eckert AJ, 2015, TREE GENET GENOMES, V11, DOI 10.1007/s11295-015-0863-0
   Eckert AJ, 2009, GENETICS, V183, P289, DOI 10.1534/genetics.109.103895
   Endelman JB, 2011, PLANT GENOME-US, V4, P250, DOI 10.3835/plantgenome2011.08.0024
   Evans LM, 2018, NAT GENET, V50, P737, DOI 10.1038/s41588-018-0108-x
   Evans LM, 2014, NAT GENET, V46, P1089, DOI 10.1038/ng.3075
   Franklin J, 2016, P NATL ACAD SCI USA, V113, P3725, DOI 10.1073/pnas.1519911113
   Geraldes A, 2011, MOL ECOL RESOUR, V11, P81, DOI 10.1111/j.1755-0998.2010.02960.x
   Goddard ME, 2009, NAT REV GENET, V10, P381, DOI 10.1038/nrg2575
   Goudet J, 2005, MOL ECOL NOTES, V5, P184, DOI 10.1111/j.1471-8286.2004.00828.x
   GRATANI L, 2014, ADV BOT, V2014, P1, DOI [10.1155/2014/208747, DOI 10.1155/2014/208747]
   Grotkopp E, 2004, EVOLUTION, V58, P1705, DOI 10.1111/j.0014-3820.2004.tb00456.x
   Gyllenstrand N, 2007, PLANT PHYSIOL, V144, P248, DOI 10.1104/pp.107.095802
   Herbert R., 1999, USING LOCAL STOCK PL, P10
   Holliday JA, 2010, NEW PHYTOL, V188, P501, DOI 10.1111/j.1469-8137.2010.03380.x
   Howe GT, 2003, CAN J BOT, V81, P1247, DOI [10.1139/b03-141, 10.1139/B03-141]
   Hurme P, 2000, GENETICS, V156, P1309
   Hurme P, 1997, CAN J FOREST RES, V27, P716, DOI 10.1139/cjfr-27-5-716
   Isabel N, 2020, EVOL APPL, V13, P3, DOI 10.1111/eva.12902
   Isik F, 2016, PLANT SCI, V242, P108, DOI 10.1016/j.plantsci.2015.08.006
   Jermstad KD, 2003, GENETICS, V165, P1489
   Jermstad KD, 2001, THEOR APPL GENET, V102, P1142, DOI 10.1007/s001220000505
   Kanninen M., 2010, Plantation forests: global perspectives
   Korte A, 2013, PLANT METHODS, V9, DOI 10.1186/1746-4811-9-29
   Kumar S, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0036674
   Laube J, 2014, GLOBAL CHANGE BIOL, V20, P170, DOI 10.1111/gcb.12360
   Lee S., 1999, INFORM NOTE
   Leebens-Mack JH, 2019, NATURE, V574, P679, DOI 10.1038/s41586-019-1693-2
   Lewandowski A, 2000, PLANT SYST EVOL, V221, P15, DOI 10.1007/BF01086377
   Liu JJ, 2014, BMC PLANT BIOL, V14, DOI 10.1186/s12870-014-0380-6
   Lu MM, 2017, TREE GENET GENOMES, V13, DOI 10.1007/s11295-017-1140-1
   Mackay TFC, 2001, ANNU REV GENET, V35, P303, DOI 10.1146/annurev.genet.35.102401.090633
   Mahony CR, 2020, EVOL APPL, V13, P116, DOI 10.1111/eva.12871
   McLean P., 2019, WOOD PROPERTIES USES
   Meuwissen THE, 2001, GENETICS, V157, P1819
   Minamikawa MF, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-05100-x
   Muranty H, 2015, HORTIC RES-ENGLAND, V2, DOI 10.1038/hortres.2015.60
   Neale DB, 2008, CURR OPIN PLANT BIOL, V11, P149, DOI 10.1016/j.pbi.2007.12.004
   Paradis E, 2019, BIOINFORMATICS, V35, P526, DOI 10.1093/bioinformatics/bty633
   Parchman TL, 2012, MOL ECOL, V21, P2991, DOI 10.1111/j.1365-294X.2012.05513.x
   Parchman TL, 2010, BMC GENOMICS, V11, DOI 10.1186/1471-2164-11-180
   Pellegrini M, 1999, P NATL ACAD SCI USA, V96, P4285, DOI 10.1073/pnas.96.8.4285
   Perry A, 2020, MOL ECOL RESOUR, V20, P1697, DOI 10.1111/1755-0998.13223
   Plomion C, 1996, THEOR APPL GENET, V93, P849, DOI 10.1007/BF00224085
   Polturak G, 2018, MOL PLANT, V11, P189, DOI 10.1016/j.molp.2017.12.002
   Prunier J, 2016, NEW PHYTOL, V209, P44, DOI 10.1111/nph.13565
   Prunier J, 2013, BMC GENOMICS, V14, DOI 10.1186/1471-2164-14-368
   Raats M. M., 1991, Food Quality and Preference, V3, P89, DOI 10.1016/0950-3293(91)90028-D
   Repo T, 2000, TREES-STRUCT FUNCT, V14, P456, DOI 10.1007/s004680000059
   Resende MFR, 2012, GENETICS, V190, P1503, DOI 10.1534/genetics.111.137026
   Resende MDV, 2012, NEW PHYTOL, V194, P116, DOI 10.1111/j.1469-8137.2011.04038.x
   Salmela MJ, 2011, FOREST ECOL MANAG, V262, P1020, DOI 10.1016/j.foreco.2011.05.037
   SCHLICHTING CD, 1986, ANNU REV ECOL SYST, V17, P667, DOI 10.1146/annurev.es.17.110186.003315
   Scotti-Saintagne C, 2004, THEOR APPL GENET, V109, P1648, DOI 10.1007/s00122-004-1789-3
   Segura V, 2012, NAT GENET, V44, P825, DOI 10.1038/ng.2314
   Silva OB, 2015, NEW PHYTOL, V206, P1527, DOI 10.1111/nph.13322
   Stevens KA, 2016, GENETICS, V204, P1613, DOI 10.1534/genetics.116.193227
   Stocks JJ, 2019, NAT ECOL EVOL, V3, P1686, DOI 10.1038/s41559-019-1036-6
   Thistlethwaite FR, 2017, BMC GENOMICS, V18, DOI 10.1186/s12864-017-4258-5
   Trick M, 2009, PLANT BIOTECHNOL J, V7, P334, DOI 10.1111/j.1467-7652.2008.00396.x
   van Kleunen M, 2014, BASIC APPL ECOL, V15, P1, DOI 10.1016/j.baae.2013.10.006
   Vázquez-González C, 2021, FOREST ECOL MANAG, V482, DOI 10.1016/j.foreco.2020.118843
   Vivas M, 2020, FOREST ECOL MANAG, V460, DOI 10.1016/j.foreco.2020.117909
   Wachowiak W, 2009, TREE GENET GENOMES, V5, P117, DOI 10.1007/s11295-008-0188-3
   Wachowiak W, 2018, TREE GENET GENOMES, V14, DOI 10.1007/s11295-018-1296-3
   Wachowiak W, 2018, ECOL EVOL, V8, P655, DOI 10.1002/ece3.3690
   Wachowiak W, 2015, BMC GENOMICS, V16, DOI 10.1186/s12864-015-1401-z
   Wachowiak W, 2013, BOT J LINN SOC, V172, P225, DOI 10.1111/boj.12049
   Wachowiak W, 2011, MOL ECOL, V20, P1729, DOI 10.1111/j.1365-294X.2011.05037.x
   Wang MY, 2019, HEREDITY, V123, P287, DOI 10.1038/s41437-019-0205-3
   Westbrook JW, 2020, EVOL APPL, V13, P31, DOI 10.1111/eva.12886
   Westbrook JW, 2013, NEW PHYTOL, V199, P89, DOI 10.1111/nph.12240
   Yang JA, 2011, AM J HUM GENET, V88, P76, DOI 10.1016/j.ajhg.2010.11.011
   Young AI, 2018, NAT GENET, V50, P1304, DOI 10.1038/s41588-018-0178-9
   Zimin A, 2014, GENETICS, V196, P875, DOI 10.1534/genetics.113.159715
   Zimin AV, 2017, GIGASCIENCE, V6, DOI 10.1093/gigascience/giw016
NR 99
TC 5
Z9 5
U1 1
U2 22
PU WILEY
PI HOBOKEN
PA 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
SN 1752-4571
J9 EVOL APPL
JI Evol. Appl.
PD FEB
PY 2022
VL 15
IS 2
BP 330
EP 348
DI 10.1111/eva.13345
EA FEB 2022
PG 19
WC Evolutionary Biology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Evolutionary Biology
GA ZG5VE
UT WOS:000753798000001
PM 35233251
OA Green Published, Green Accepted
DA 2025-01-10
ER

PT J
AU Elsen, PR
   Saxon, EC
   Simmons, BA
   Ward, M
   Williams, BA
   Grantham, HS
   Kark, S
   Levin, N
   Perez-Hammerle, KV
   Reside, AE
   Watson, JEM
AF Elsen, Paul R.
   Saxon, Earl C.
   Simmons, B. Alexander
   Ward, Michelle
   Williams, Brooke A.
   Grantham, Hedley S.
   Kark, Salit
   Levin, Noam
   Perez-Hammerle, Katharina-Victoria
   Reside, April E.
   Watson, James E. M.
TI Accelerated shifts in terrestrial life zones under rapid climate change
SO GLOBAL CHANGE BIOLOGY
LA English
DT Article
DE biodiversity; climate adaptation; conservation; ecosystem change; global
   change; Holdridge life zones; sustainable development; terrestrial
   ecoregions
ID ADAPTATION STRATEGIES; GLOBAL PATTERNS; ECOSYSTEMS; IMPACTS; FUTURE;
   WATER; VULNERABILITY; CONSERVATION; SENSITIVITY; MANAGEMENT
AB Rapid climate change is impacting biodiversity, ecosystem function, and human well-being. Though the magnitude and trajectory of climate change are becoming clearer, our understanding of how these changes reshape terrestrial life zones-distinct biogeographic units characterized by biotemperature, precipitation, and aridity representing broad-scale ecosystem types-is limited. To address this gap, we used high-resolution historical climatologies and climate projections to determine the global distribution of historical (1901-1920), contemporary (1979-2013), and future (2061-2080) life zones. Comparing the historical and contemporary distributions shows that changes from one life zone to another during the 20th century impacted 27 million km(2) (18.3% of land), with consequences for social and ecological systems. Such changes took place in all biomes, most notably in Boreal Forests, Temperate Coniferous Forests, and Tropical Coniferous Forests. Comparing the contemporary and future life zone distributions shows the pace of life zone changes accelerating rapidly in the 21st century. By 2070, such changes would impact an additional 62 million km(2) (42.6% of land) under "business-as-usual" (RCP8.5) emissions scenarios. Accelerated rates of change are observed in hundreds of ecoregions across all biomes except Tropical Coniferous Forests. While only 30 ecoregions (3.5%) had over half of their areas change to a different life zone during the 20th century, by 2070 this number is projected to climb to 111 ecoregions (13.1%) under RCP4.5 and 281 ecoregions (33.2%) under RCP8.5. We identified weak correlations between life zone change and threatened vertebrate richness, levels of vertebrate endemism, cropland extent, and human population densities within ecoregions, illustrating the ubiquitous risks of life zone changes to diverse social-ecological systems. The accelerated pace of life zone changes will increasingly challenge adaptive conservation and sustainable development strategies that incorrectly assume current ecological patterns and livelihood provisioning systems will persist.
C1 [Elsen, Paul R.; Grantham, Hedley S.] Wildlife Conservat Soc, Global Conservat Program, Bronx, NY 10460 USA.
   [Elsen, Paul R.] Univ Wisconsin, Dept Forest & Wildlife Ecol, Madison, WI USA.
   [Saxon, Earl C.; Ward, Michelle; Williams, Brooke A.; Perez-Hammerle, Katharina-Victoria; Reside, April E.; Watson, James E. M.] Univ Queensland, Ctr Biodivers & Conservat Sci, Brisbane, Qld, Australia.
   [Saxon, Earl C.; Levin, Noam] Hebrew Univ Jerusalem, Dept Geog, Jerusalem, Israel.
   [Simmons, B. Alexander] Boston Univ, Global Dev Policy Ctr, Boston, MA 02215 USA.
   [Simmons, B. Alexander] Queensland Univ Technol, Inst Future Environm, Brisbane, Qld, Australia.
   [Ward, Michelle] WWF Australia, Brisbane, Qld, Australia.
   [Ward, Michelle; Williams, Brooke A.; Watson, James E. M.] Univ Queensland, Sch Earth & Environm Sci, Brisbane, Qld, Australia.
   [Kark, Salit] Univ Queensland, Ctr Biodivers & Conservat Sci, Sch Biol Sci, NESP Threatened Species Recovery Hub,Biodivers Re, Brisbane, Qld, Australia.
   [Levin, Noam] Univ Queensland, Remote Sensing Res Ctr, Sch Earth & Environm Sci, Brisbane, Qld, Australia.
   [Perez-Hammerle, Katharina-Victoria] Univ Queensland, Sch Biol Sci, Brisbane, Qld, Australia.
C3 Wildlife Conservation Society; University of Wisconsin System;
   University of Wisconsin Madison; University of Queensland; Hebrew
   University of Jerusalem; Boston University; Queensland University of
   Technology (QUT); World Wildlife Fund; University of Queensland;
   University of Queensland; University of Queensland; University of
   Queensland
RP Elsen, PR (corresponding author), Wildlife Conservat Soc, Global Conservat Program, Bronx, NY 10460 USA.
EM pelsen@wcs.org
RI Saxon, Earl/LSK-4986-2024; Williams, Brooke/AAW-1658-2020; Simmons,
   Blake/J-6564-2019; Elsen, Paul/H-9567-2019; Ward,
   Michelle/HGA-8862-2022; Kark, Salit/C-6795-2016; Reside,
   April/H-4940-2011; Simmons, Blake/N-6022-2016; Watson,
   James/D-8779-2013; Levin, Noam/D-2180-2013
OI Elsen, Paul/0000-0002-9953-7961; Kark, Salit/0000-0002-7183-3988;
   Reside, April/0000-0002-0760-9527; Grantham, Hedley/0000-0002-8933-807X;
   Simmons, Blake/0000-0002-1332-1810; Williams,
   Brooke/0000-0002-0692-7507; Watson, James/0000-0003-4942-1984; Ward,
   Michelle/0000-0002-0658-855X; Perez-Hammerle,
   Katharina-Victoria/0000-0002-2434-5594; Levin, Noam/0000-0002-9434-7501;
   Simmons, Blake/0000-0002-1918-3463
FU Wildlife Conservation Society; University of Queensland; Forest Inform
   Pty Ltd
FX Wildlife Conservation Society; University of Queensland; Forest Inform
   Pty Ltd
CR Adger WN, 2013, NAT CLIM CHANGE, V3, P112, DOI [10.1038/NCLIMATE1666, 10.1038/nclimate1666]
   Allen CD, 1998, P NATL ACAD SCI USA, V95, P14839, DOI 10.1073/pnas.95.25.14839
   Batllori E, 2017, GLOBAL CHANGE BIOL, V23, P3219, DOI 10.1111/gcb.13663
   Baumann M, 2017, GLOBAL CHANGE BIOL, V23, P1902, DOI 10.1111/gcb.13521
   Beaumont LJ, 2011, P NATL ACAD SCI USA, V108, P2306, DOI 10.1073/pnas.1007217108
   Beck HE, 2018, SCI DATA, V5, DOI 10.1038/sdata.2018.214
   Bellard C, 2012, ECOL LETT, V15, P365, DOI 10.1111/j.1461-0248.2011.01736.x
   Belote RT, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-27721-6
   Bergengren JC, 2011, CLIMATIC CHANGE, V107, P433, DOI 10.1007/s10584-011-0065-1
   Bernstein L., 2008, IPCC 2007 CLIMATE CH
   Bond WJ, 2005, J VEG SCI, V16, P261, DOI 10.1658/1100-9233(2005)016[0261:LPOTWA]2.0.CO;2
   Box EO, 1996, J VEG SCI, V7, P309, DOI 10.2307/3236274
   Brown SC, 2020, NAT CLIM CHANGE, V10, P244, DOI 10.1038/s41558-019-0682-7
   Burrows MT, 2011, SCIENCE, V334, P652, DOI 10.1126/science.1210288
   Carroll ML, 2009, INT J DIGIT EARTH, V2, P291, DOI 10.1080/17538940902951401
   CBD (Convention on Biological Diversity), 2011, COP 10 DEC X 2 STRAT
   Chen J, 2015, ISPRS J PHOTOGRAMM, V103, P7, DOI 10.1016/j.isprsjprs.2014.09.002
   CIESIN, 2018, Gridded Population of the World, Version 4 (GPWv4): Population count, Revision 11
   Cuo L, 2013, J HYDROL, V502, P37, DOI 10.1016/j.jhydrol.2013.08.003
   Daru BH, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-15921-6
   Dee DP, 2011, Q J ROY METEOR SOC, V137, P553, DOI 10.1002/qj.828
   Dinerstein E, 2017, BIOSCIENCE, V67, P534, DOI 10.1093/biosci/bix014
   Dowdy AJ, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-46362-x
   Droogers P., 2002, Irrigation and Drainage Systems, V16, P33, DOI 10.1023/A:1015508322413
   Ellis EC, 2015, ECOL MONOGR, V85, P287, DOI 10.1890/14-2274.1
   Elsen PR, 2020, SCI ADV, V6, DOI 10.1126/sciadv.aay0814
   Elsen PR, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-15881-x
   Elsen PR, 2018, P NATL ACAD SCI USA, V115, P6004, DOI 10.1073/pnas.1720141115
   Feng Y, 2021, NAT SUSTAIN, V4, P892, DOI 10.1038/s41893-021-00738-y
   Gonzalez P, 2010, GLOBAL ECOL BIOGEOGR, V19, P755, DOI 10.1111/j.1466-8238.2010.00558.x
   Gorelick N, 2017, REMOTE SENS ENVIRON, V202, P18, DOI 10.1016/j.rse.2017.06.031
   Guerin GR, 2015, BIODIVERS CONSERV, V24, P2877, DOI 10.1007/s10531-015-0977-6
   Guerin GR, 2015, METHODS ECOL EVOL, V6, P845, DOI 10.1111/2041-210X.12361
   Hanewinkel M, 2013, NAT CLIM CHANGE, V3, P203, DOI [10.1038/NCLIMATE1687, 10.1038/nclimate1687]
   Hanson JO, 2020, NATURE, V580, P232, DOI 10.1038/s41586-020-2138-7
   Harris I, 2020, SCI DATA, V7, DOI 10.1038/s41597-020-0453-3
   Hayhoe K., 2017, CLIMATE SCI SPECIAL, VI, P133, DOI [DOI 10.7930/J0WH2N54, 10.7930/J0WH2N54]
   Heller NE, 2009, BIOL CONSERV, V142, P14, DOI 10.1016/j.biocon.2008.10.006
   Hirota M, 2011, SCIENCE, V334, P232, DOI 10.1126/science.1210657
   Holdridge L. R., 1967, Life zone ecology.
   HOLDRIDGE LR, 1947, SCIENCE, V105, P367, DOI 10.1126/science.105.2727.367
   Huang JP, 2016, NAT CLIM CHANGE, V6, P166, DOI [10.1038/NCLIMATE2837, 10.1038/nclimate2837]
   Iglesias A, 2015, AGR WATER MANAGE, V155, P113, DOI 10.1016/j.agwat.2015.03.014
   IUCN, 2016, The IUCN Red List of Threatened Species
   Karger DN, 2017, SCI DATA, V4, DOI 10.1038/sdata.2017.122
   Keith D. A, 2020, IUCN Global Ecosystem Typology 2.0: descriptive profiles for biomes and ecosystem functional groups, DOI [10.2305/IUCN.CH.2020.13.en, DOI 10.2305/IUCN.CH.2020.13.EN]
   Kier G, 2009, P NATL ACAD SCI USA, V106, P9322, DOI 10.1073/pnas.0810306106
   Kreft H, 2007, P NATL ACAD SCI USA, V104, P5925, DOI 10.1073/pnas.0608361104
   Kröpelin S, 2008, SCIENCE, V320, P765, DOI 10.1126/science.1154913
   Laffan SW, 2003, J BIOGEOGR, V30, P511, DOI 10.1046/j.1365-2699.2003.00875.x
   Latham J., 2014, Global Land Cover SHARE, P1
   Lawler JJ, 2009, ECOLOGY, V90, P588, DOI 10.1890/08-0823.1
   Lehmann N, 2013, AGR SYST, V117, P55, DOI 10.1016/j.agsy.2012.12.011
   Lenoir J, 2010, ECOGRAPHY, V33, P295, DOI 10.1111/j.1600-0587.2010.06279.x
   Li DL, 2018, GLOBAL CHANGE BIOL, V24, P4095, DOI 10.1111/gcb.14327
   Loarie SR, 2009, NATURE, V462, P1052, DOI 10.1038/nature08649
   Lugo AE, 1999, J BIOGEOGR, V26, P1025, DOI 10.1046/j.1365-2699.1999.00329.x
   Martin TG, 2016, NAT CLIM CHANGE, V6, P122, DOI 10.1038/nclimate2918
   Maxwell SL, 2020, NATURE, V586, P217, DOI 10.1038/s41586-020-2773-z
   Miller-Rushing AJ, 2008, GLOBAL CHANGE BIOL, V14, P1959, DOI 10.1111/j.1365-2486.2008.01619.x
   Monsarrat S, 2019, PHILOS T R SOC B, V374, DOI 10.1098/rstb.2019.0219
   Morelli TL, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0159909
   Morueta-Holme N, 2015, P NATL ACAD SCI USA, V112, P12741, DOI 10.1073/pnas.1509938112
   MuimbaKankolongo A, 2018, FOOD CROP PRODUCTION BY SMALLHOLDER FARMERS IN SOUTHERN AFRICA: CHALLENGES AND OPPORTUNITIES FOR IMPROVEMENT, P1
   Neilson RP, 2005, BIOSCIENCE, V55, P749, DOI 10.1641/0006-3568(2005)055[0749:FRTGPM]2.0.CO;2
   Niang I, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT B: REGIONAL ASPECTS, P1199
   Nolan C, 2018, SCIENCE, V361, P920, DOI 10.1126/science.aan5360
   Olson DM, 2001, BIOSCIENCE, V51, P933, DOI 10.1641/0006-3568(2001)051[0933:TEOTWA]2.0.CO;2
   Pan Y, 2003, INT J REMOTE SENS, V24, P1009, DOI 10.1080/01431160110115816
   Pausas JG, 2012, CLIMATIC CHANGE, V110, P215, DOI 10.1007/s10584-011-0060-6
   Pecl GT, 2017, SCIENCE, V355, DOI 10.1126/science.aai9214
   Rehm EM, 2015, ECOGRAPHY, V38, P1167, DOI 10.1111/ecog.01050
   Reside AE, 2018, BIODIVERS CONSERV, V27, P1, DOI 10.1007/s10531-017-1442-5
   Root TL, 2003, NATURE, V421, P57, DOI 10.1038/nature01333
   Sanderson BM, 2015, J CLIMATE, V28, P5171, DOI 10.1175/JCLI-D-14-00362.1
   Saxon Earl, 2008, BIODIVERSITY-OTTAWA, V9, P5
   Scheffers BR, 2016, SCIENCE, V354, DOI 10.1126/science.aaf7671
   Seddon AWR, 2016, NATURE, V531, P229, DOI 10.1038/nature16986
   Sheridan JA, 2011, NAT CLIM CHANGE, V1, P401, DOI 10.1038/NCLIMATE1259
   Sinclair ARE, 2007, CONSERV BIOL, V21, P580, DOI 10.1111/j.1523-1739.2007.00699.x
   Sisneros R, 2011, PROCEDIA COMPUT SCI, V4, P1582, DOI 10.1016/j.procs.2011.04.171
   Smith JR, 2018, NAT ECOL EVOL, V2, P1889, DOI 10.1038/s41559-018-0709-x
   Smithers J, 1997, GLOBAL ENVIRON CHANG, V7, P129, DOI 10.1016/S0959-3780(97)00003-4
   Tatli H, 2016, INT J CLIMATOL, V36, P3864, DOI 10.1002/joc.4600
   Tilman D, 2011, P NATL ACAD SCI USA, V108, P20260, DOI 10.1073/pnas.1116437108
   Vitousek PM, 1997, SCIENCE, V277, P494, DOI 10.1126/science.277.5325.494
   Ward M, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-18457-x
   Ward M, 2020, NAT ECOL EVOL, V4, P1321, DOI 10.1038/s41559-020-1251-1
   Watson JEM, 2013, NAT CLIM CHANGE, V3, P989, DOI [10.1038/NCLIMATE2007, 10.1038/nclimate2007]
   Williams JW, 2007, FRONT ECOL ENVIRON, V5, P475, DOI 10.1890/070037
   Woodward FI, 2004, PHILOS T ROY SOC B, V359, P1465, DOI 10.1098/rstb.2004.1525
   Xu C, 2020, P NATL ACAD SCI USA, V117, P11350, DOI 10.1073/pnas.1910114117
   Xu JC, 2009, CONSERV BIOL, V23, P520, DOI 10.1111/j.1523-1739.2009.01237.x
   Zabel F, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0107522
   Zorner RJ, 2008, AGR ECOSYST ENVIRON, V126, P67, DOI 10.1016/j.agee.2008.01.014
NR 95
TC 33
Z9 33
U1 5
U2 67
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 2022
VL 28
IS 3
BP 918
EP 935
DI 10.1111/gcb.15962
EA NOV 2021
PG 18
WC Biodiversity Conservation; Ecology; Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biodiversity & Conservation; Environmental Sciences & Ecology
GA YC1QF
UT WOS:000718080500001
PM 34719077
OA Green Submitted
DA 2025-01-10
ER

PT J
AU He, YY
   Zhou, CC
   Ahmed, T
AF He, Yueyue
   Zhou, Changchun
   Ahmed, Tanveer
TI Vulnerability assessment of rural social-ecological system to climate
   change: a case study of Yunnan Province, China
SO INTERNATIONAL JOURNAL OF CLIMATE CHANGE STRATEGIES AND MANAGEMENT
LA English
DT Article
DE Vulnerability; Adaptability; Climate change; Exposure; Sensitivity;
   Social-ecological system
ID ADAPTATION; FRAMEWORK; COMMUNITIES; RISKS; INDICATORS; RESILIENCE;
   INDUSTRY
AB Purpose
   The purpose of this paper is to quantitatively measure the vulnerability level of the whole rural social-ecological system in Yunnan Province and to analyze the spatial differences of the vulnerability in different regions.
   Design/methodology/approach
   Based on the "exposure-sensitivity-adaptability" vulnerability assessment framework, this paper establishes the index system of rural social-ecological system vulnerability to climate change. Combined with the questionnaire survey and meteorological data, the entropy method was used to measure and analyze the vulnerability level and influencing factors of the overall rural social-ecological system in Yunnan Province. At the same time, the vulnerability level of social-ecological system in Yunnan Province is divided into five levels, and the spatial differences of vulnerability level of 16 states (cities) in Yunnan Province are analyzed.
   Findings
   The results show that: the social-ecological system has high exposure to climate change (0.809), strong sensitivity (0.729), moderate adaptability (0.297) and overall system vulnerability is at a medium level (0.373). Yunnan Province is divided into five levels of social-ecological system vulnerable areas. The areas of extreme, severe, moderate, mild and slight vulnerability account for 21.45%, 24.65%, 36.82%, 13.18% and 3.90% of the whole province, respectively. The geographical division and vulnerability division of Yunnan Province are basically consistent in space.
   Originality/value
   Comprehensive evaluation of the vulnerability of the social-ecological system of Yunnan Province to climate change is the scientific basis for the country to formulate countermeasures against climate change, and it is also the need to improve the adaptability of the social and economic system of the fragile area, reduce the vulnerability and realize the sustainable development of national social economy. The research results can provide a basis for decision-making of climate adaptation in Yunnan and other regions and provide methods and indicators for the assessment of social-ecological system vulnerability under the background of climate change.
C1 [He, Yueyue; Zhou, Changchun; Ahmed, Tanveer] Kunming Univ Sci & Technol, Fac Management & Econ, Kunming, Yunnan, Peoples R China.
C3 Kunming University of Science & Technology
RP Zhou, CC (corresponding author), Kunming Univ Sci & Technol, Fac Management & Econ, Kunming, Yunnan, Peoples R China.
EM kmlgdxgjxy@126.com
RI , CC. Zhou/AGI-1229-2022; Ahmed, Tanveer/ABC-2863-2021
OI He, Yueyue/0000-0003-2893-5804
FU National Natural Science Foundation of China [71940015]; Achievements of
   Key Projects of Yunnan Philosophy and Social Science Planning
   [ZDZZD201907]; Scientific Research Fund Project of Yunnan Provincial
   Department of Education [2020Y0093]
FX This research was funded by National Natural Science Foundation of China
   (Grant No. 71940015), Achievements of Key Projects of Yunnan Philosophy
   and Social Science Planning (Grant No. ZDZZD201907) and Scientific
   Research Fund Project of Yunnan Provincial Department of Education
   (Grant No. 2020Y0093). The authors thank the journal editors and the
   anonymous reviewers for the in-depth review and comments that have
   greatly improved this paper.
CR Adger WN, 2005, GLOBAL ENVIRON CHANG, V15, P77, DOI [10.1016/j.gloenvcha.2005.03.001, 10.1016/j.gloenvcha.2004.12.005]
   Ahsan MN, 2014, INT J DISAST RISK RE, V8, P32, DOI 10.1016/j.ijdrr.2013.12.009
   Amos E, 2015, ENVIRON DEV SUSTAIN, V17, P887, DOI 10.1007/s10668-014-9580-3
   Armatas C, 2017, SUSTAIN SCI, V12, P105, DOI 10.1007/s11625-016-0369-1
   Aryal S, 2018, ENVIRON DEV, V25, P73, DOI 10.1016/j.envdev.2017.09.001
   Bardsley DK, 2012, GLOBAL ENVIRON CHANG, V22, P713, DOI 10.1016/j.gloenvcha.2012.04.003
   Barreteau O, 2020, ECOL SOC, V25, DOI 10.5751/ES-11402-250203
   Below TB, 2012, GLOBAL ENVIRON CHANG, V22, P223, DOI 10.1016/j.gloenvcha.2011.11.012
   Biggs D, 2011, ECOL SOC, V16
   Binita KC, 2015, APPL GEOGR, V62, P62, DOI 10.1016/j.apgeog.2015.04.007
   Chen J, 2018, J GEOGR SCI, V28, P152, DOI 10.1007/s11442-018-1465-1
   Cumming GS, 2005, ECOSYSTEMS, V8, P975, DOI 10.1007/s10021-005-0129-z
   Ding WQ, 2014, RANGELAND J, V36, P535, DOI 10.1071/RJ13051
   Fedele G, 2019, ENVIRON SCI POLICY, V101, P116, DOI 10.1016/j.envsci.2019.07.001
   Ford JD, 2004, ARCTIC, V57, P389, DOI 10.14430/arctic516
   Frazier TG, 2014, APPL GEOGR, V51, P158, DOI 10.1016/j.apgeog.2014.04.004
   Hagenlocher M, 2018, SCI TOTAL ENVIRON, V631-632, P71, DOI 10.1016/j.scitotenv.2018.03.013
   Hahn MB, 2009, GLOBAL ENVIRON CHANG, V19, P74, DOI 10.1016/j.gloenvcha.2008.11.002
   Jena R, 2020, IOP C SER EARTH ENV, V540, DOI 10.1088/1755-1315/540/1/012079
   Li A, 2019, WEATHER CLIM SOC, V11, P577, DOI 10.1175/WCAS-D-18-0093.1
   Li B, 2019, CHINESE GEOGR SCI, V29, P1052, DOI 10.1007/s11769-019-1076-5
   Luers AL, 2003, GLOBAL ENVIRON CHANG, V13, P255, DOI 10.1016/S0959-3780(03)00054-2
   Maikhuri RK, 2017, INT J DISAST RISK RE, V25, P111, DOI 10.1016/j.ijdrr.2017.09.002
   McDowell G, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/3/033001
   Mendoza MET, 2014, J ENVIRON SCI MANAG, V17, P78
   Müller S, 2019, AGRON SUSTAIN DEV, V39, DOI 10.1007/s13593-019-0586-y
   Morzaria-Luna HN, 2014, MAR POLICY, V45, P182, DOI 10.1016/j.marpol.2013.10.013
   Naylor LA, 2019, REG ENVIRON CHANGE, V19, P1835, DOI 10.1007/s10113-019-01530-7
   Pandey R, 2017, ECOL INDIC, V79, P338, DOI 10.1016/j.ecolind.2017.03.047
   Pandey R, 2015, APPL GEOGR, V64, P74, DOI 10.1016/j.apgeog.2015.09.008
   [Parry Martin. IPCC. Intergovernmental Panel on Climate Change IPCC. Intergovernmental Panel on Climate Change], 2007, WORKING GROUP 2 CONT
   Perera ENC, 2019, MODEL EARTH SYST ENV, V5, P1635, DOI 10.1007/s40808-019-00615-w
   Pielke RA, 2005, POPUL ENVIRON, V26, P255, DOI 10.1007/s11111-005-1877-6
   Preston BL, 2011, SUSTAIN SCI, V6, P177, DOI 10.1007/s11625-011-0129-1
   Shinn JE, 2019, S AFR GEOGR J, V101, P121, DOI 10.1080/03736245.2018.1562365
   Thiault L, 2018, MAR POLICY, V88, P213, DOI 10.1016/j.marpol.2017.11.027
   Thomalla F, 2006, DISASTERS, V30, P39, DOI 10.1111/j.1467-9523.2006.00305.x
   Turner BL, 2003, P NATL ACAD SCI USA, V100, P8074, DOI 10.1073/pnas.1231335100
   Winkler KJ, 2018, LAND USE POLICY, V79, P137, DOI 10.1016/j.landusepol.2018.06.034
   Withanachchi SS, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10093062
   Zhang L., 2019, J SERV SCI MANAG, V12, P116, DOI [10.4236/jssm.2019.122007, DOI 10.4236/JSSM.2019.122007]
   Zhu J, 2018, CHINESE GEOGR SCI, V28, P600, DOI 10.1007/s11769-018-0977-z
   Zúñiga-Upegui P, 2019, SCI TOTAL ENVIRON, V695, DOI 10.1016/j.scitotenv.2019.133874
NR 43
TC 17
Z9 19
U1 13
U2 114
PU EMERALD GROUP PUBLISHING LTD
PI BINGLEY
PA HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND
SN 1756-8692
EI 1756-8706
J9 INT J CLIM CHANG STR
JI Int. J. Clim. Chang. Strateg. Manag.
PD JUN 25
PY 2021
VL 13
IS 2
BP 162
EP 180
DI 10.1108/IJCCSM-08-2020-0094
EA MAY 2021
PG 19
WC Environmental Studies
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA TB9UN
UT WOS:000647812500001
OA gold
DA 2025-01-10
ER

PT J
AU de Gracia, A
   Tarragona, J
   Crespo, A
   Fernández, C
AF de Gracia, Alvaro
   Tarragona, Joan
   Crespo, Alicia
   Fernandez, Cesar
TI Smart control of dynamic phase change material wall system
SO APPLIED ENERGY
LA English
DT Article
DE Phase change material (PCM); Smart control; Tabu search; Model
   predictive control (MPC); Dynamic system; Climatic adaptable building
   shells (CABS)
ID MODEL-PREDICTIVE CONTROL; VENTILATED FACADE; ENERGY-STORAGE; BUILDINGS;
   PCM; SAVINGS
AB This work presents two different smart control algorithms to manage a novel phase change material system integrated into building walls and roofs. This system is able to move a phase change material layer with respect to the insulation layer inside the building component. With this ability, the system can increase solar benefits in winter and take profit from night free cooling in summer. During the heating season, the system places the phase change material facing outdoors during sunny hours to melt it, and it moves the phase change material back facing indoors to provide space heating when desired. In the cooling season, the phase change material is moved to the outer face of insulation at night time to enhance its solidification process, and it is moved back to face indoors during cooling peak hours. An appropriate control system, referring to the schedule of operation and placement of phase change material layer with respect to the insulation (when phase change material is facing outdoors or indoors) is critical to achieve savings and avoid malfunctioning of the system. In this work, we have developed and numerically compared two different control algorithms based on weather forecast data for space heating and cooling applications. Experimentation has been done under four different climate conditions: Athens, Madrid, Strasbourg, and Helsinki. One of the control algorithms, based on local search (Tabu), provided the set of activations of the dynamic system for a 24 h period. The other algorithm is based on model predictive control with an horizon of 2.5 and 5 h. Results proved the feasibility of the two smart control methods, as well as their capacity to improve the energy benefits of the dynamic phase change material system in days with suitable weather conditions. Moreover, the two control algorithms successfully avoided activating the system in days with non-appropriate weather conditions.
C1 [de Gracia, Alvaro; Tarragona, Joan; Crespo, Alicia; Fernandez, Cesar] Univ Lleida, INSPIRES Res Ctr, GREiA Res Grp, Pere Cabrera S-N, Lleida 25001, Spain.
   [Tarragona, Joan] CIRIAF Interuniv Res Ctr Pollut & Environm Mauro, Via G Duranti 63, I-06125 Perugia, Italy.
C3 Universitat de Lleida
RP de Gracia, A (corresponding author), Univ Lleida, INSPIRES Res Ctr, GREiA Res Grp, Pere Cabrera S-N, Lleida 25001, Spain.
EM alvaro.degracia@udl.cat
RI de Gracia, Alvaro/AAF-3152-2019; Tarragona, Joan/AAD-6121-2021
OI Crespo Gutierrez, Alicia/0000-0003-4616-0221; de Gracia,
   Alvaro/0000-0002-8208-5487; Tarragona, Joan/0000-0001-6776-4273
FU Ministerio de Ciencia, Innovacion y Universidades de Espana
   [RTI2018-093849-B-C31, TIN2015-71799-C2-2-P]; Agencia Estatal de
   Investigacion (AEI) [RED2018-102431-T]; Government of Catalonia [2017
   SGR 1537]; ICREA
FX This work was partially funded by the Ministerio de Ciencia, Innovacion
   y Universidades de Espana (RTI2018-093849-B-C31 and
   TIN2015-71799-C2-2-P) and the Agencia Estatal de Investigacion (AEI)
   (RED2018-102431-T). The authors would like to thank the Catalan
   Government for the quality accreditation given to their research group
   (2017 SGR 1537). GREiA is a certified TECNIO agent in the category of
   technology developers from the Government of Catalonia. This work is
   partially supported by ICREA under the ICREA Academia programme.
CR Afram A, 2014, BUILD ENVIRON, V72, P343, DOI 10.1016/j.buildenv.2013.11.016
   [Anonymous], 2016, TECHNICAL REPORTS PV
   Bottou L, 2004, LECT NOTES ARTIF INT, V3176, P146
   Castell A, 2010, ENERG BUILDINGS, V42, P534, DOI 10.1016/j.enbuild.2009.10.022
   de Gracia A, 2019, APPL SCI-BASEL, V9, DOI 10.3390/app9183688
   de Gracia A, 2019, APPL ENERG, V235, P1245, DOI 10.1016/j.apenergy.2018.11.061
   de Gracia A, 2016, ENERG BUILDINGS, V130, P821, DOI 10.1016/j.enbuild.2016.09.007
   de Gracia A, 2015, ENERG BUILDINGS, V106, P234, DOI 10.1016/j.enbuild.2015.06.045
   de Gracia A, 2015, ENERG BUILDINGS, V103, P414, DOI 10.1016/j.enbuild.2015.06.007
   de Gracia A, 2013, APPL THERM ENG, V61, P372, DOI 10.1016/j.applthermaleng.2013.07.035
   Fiorentini M, 2017, APPL ENERG, V187, P465, DOI 10.1016/j.apenergy.2016.11.041
   Gholamibozanjani G, 2018, APPL ENERG, V231, P959, DOI 10.1016/j.apenergy.2018.09.181
   Gleixner A., 2018, 1826 ZIB
   GLOVER F, 1986, COMPUT OPER RES, V13, P533, DOI 10.1016/0305-0548(86)90048-1
   Glover F., 1997, Tabu Search
   Izquierdo-Barrientos MA, 2012, APPL THERM ENG, V47, P73, DOI 10.1016/j.applthermaleng.2012.02.038
   Kazmi H, 2018, ENERGY, V144, P159, DOI 10.1016/j.energy.2017.12.019
   Kottek M, 2006, METEOROL Z, V15, P259, DOI 10.1127/0941-2948/2006/0130
   Lago J, 2019, IFAC PAPERSONLINE, V52, P488, DOI 10.1016/j.ifacol.2019.08.258
   Lamberg P, 2004, INT J THERM SCI, V43, P277, DOI 10.1016/j.ijthermalsci.2003.07.001
   Liu SM, 2006, ENERG BUILDINGS, V38, P142, DOI 10.1016/j.enbuild.2005.06.002
   Mandilaras I, 2013, BUILD ENVIRON, V61, P93, DOI 10.1016/j.buildenv.2012.12.007
   Navarro L, 2015, ENERG EFFIC, V8, P895, DOI 10.1007/s12053-015-9330-x
   Oldewurtel F, 2012, ENERG BUILDINGS, V45, P15, DOI 10.1016/j.enbuild.2011.09.022
   Omrany H, 2016, RENEW SUST ENERG REV, V62, P1252, DOI 10.1016/j.rser.2016.04.010
   Rawlings J. B., 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251), P662, DOI 10.1109/ACC.1999.782911
   Ruelens F, 2018, IEEE T SMART GRID, V9, P3792, DOI 10.1109/TSG.2016.2640184
   Sahinidis NV, 2019, OPTIM ENG, V20, P301, DOI 10.1007/s11081-019-09438-1
   Siroky J, 2011, APPL ENERG, V88, P3079, DOI 10.1016/j.apenergy.2011.03.009
   Stamatiaou M, 2009, P 11 INT C THERM EN, V1
   Tarragona J, 2020, ENERGY, V197, DOI 10.1016/j.energy.2020.117229
   Thieblemont H, 2017, ENERG BUILDINGS, V153, P485, DOI 10.1016/j.enbuild.2017.08.010
   Vázquez-Canteli J, 2017, ENRGY PROCED, V122, P415, DOI 10.1016/j.egypro.2017.07.429
   Wilcox S, 2008, USERS MANUAL TMY3 DA, DOI [10.2172/928611, DOI 10.2172/928611]
   Zhao Y, 2015, ENERG BUILDINGS, V86, P415, DOI 10.1016/j.enbuild.2014.10.019
NR 35
TC 25
Z9 25
U1 0
U2 20
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 DEC 1
PY 2020
VL 279
AR 115807
DI 10.1016/j.apenergy.2020.115807
PG 10
WC Energy & Fuels; Engineering, Chemical
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Energy & Fuels; Engineering
GA OY2YA
UT WOS:000594115700008
DA 2025-01-10
ER

PT J
AU Karrasch, L
   Klenke, T
   Kleyer, M
AF Karrasch, Leena
   Klenke, Thomas
   Kleyer, Michael
TI Land-use elements and attributed ecosystem services: an archetype
   approach to land-use evaluation at the German North Sea coast
SO ECOLOGY AND SOCIETY
LA English
DT Article
DE archetype approach; ecosystem-based management; ecosystem services;
   land-use management; stakeholder participation
ID DECISION-MAKING; TRADE-OFFS; ADAPTATION; LANDSCAPES; GOVERNANCE;
   CHALLENGES; SUPPORT; SCALE
AB The ecosystem services concept has been introduced as a decisive approach to include ecosystem functioning in land-use planning and stakeholder-driven sustainable development. Early integration of stakeholders in participatory processes in the nexus of ecosystem services, climate adaption, and land-use management is still a demanding challenge. This investigation followed a cognitive approach to archetype analysis. We defined cognitive archetypes as recurrent patterns in individual perceptions of social-ecological relations. Our aim was to identify cognitive archetypes based on stakeholders' perceived relation between land-use elements and ecosystem services as exemplified in a German North Sea coastal region. Land-use elements were spatially explicit and delivered a variety of different ecosystem services. The stakeholders were regional decision makers and experts who represented key societal sectors, i.e., water management, agriculture, nature conservation, regional policy, and tourism. Within a participatory process, these stakeholders individually evaluated a matrix of 19 land-use elements and 18 ecosystem services. In terms of archetype analysis, the stakeholders were considered as different cases, and the evaluation of relationships between land-use elements and ecosystem services built the attributions to identify archetypes. They independently agreed on the relevance of close to one-third of 342 attributions, whereas there was disagreement on approximately two-thirds of the possible attributions. By identifying agreements across different sectors, 2 archetypes in land-use element-ecosystem service attributions were identified. The first archetype built on monofunctional attributions, i.e., one land-use element was relevant for the provision of one ecosystem service. The second archetype described land-use elements attributed to bundles of ecosystem services, indicating multifunctionality of land-use elements. Disagreement can result primarily from sector or individual viewpoints. In the case of disagreements, land-use-ecosystem relationships can reveal archetypical mutually exclusive interests, the third archetype. We found that disagreements were mainly individual and not sector specific. This indicated that individual knowledge on service outputs of multiple land uses differed strongly among the stakeholders, particularly with respect to regulatory services.
C1 [Karrasch, Leena] Carl von Ossietzky Univ Oldenburg, Ecol Econ, Oldenburg, Germany.
   [Karrasch, Leena; Klenke, Thomas] Carl von Ossietzky Univ Oldenburg, COAST Ctr Environm & Sustainabil Res, Oldenburg, Germany.
   [Kleyer, Michael] Carl von Ossietzky Univ Oldenburg, Landscape Ecol Grp, Inst Biol & Environm Sci, Oldenburg, Germany.
C3 Carl von Ossietzky Universitat Oldenburg; Carl von Ossietzky Universitat
   Oldenburg; Carl von Ossietzky Universitat Oldenburg
RP Karrasch, L (corresponding author), Carl von Ossietzky Univ Oldenburg, Ecol Econ, Oldenburg, Germany.; Karrasch, L (corresponding author), Carl von Ossietzky Univ Oldenburg, COAST Ctr Environm & Sustainabil Res, Oldenburg, Germany.
OI Karrasch, Leena/0000-0002-7722-1720; Klenke, Thomas/0000-0001-7190-8495
FU German Federal Ministry of Education and Research [01LL0911]
FX The authors would like to thank the stakeholders who took an active part
   in our study. Their insights and knowledge were invaluable for our
   research. Our special thanks go to Marcel Kuhmann for his contributions
   to the statistical analysis. This project was part of the collaborative
   research project "Sustainable coastal land management: trade-offs in
   ecosystem services" (COMTESS), supported by the German Federal Ministry
   of Education and Research (grant number 01LL0911).
CR Albert C, 2014, LANDSCAPE ECOL, V29, P1301, DOI [10.1007/s10980-014-9990-5, 10.1007/s10980-014-0085-0]
   [Anonymous], 2003, ECOSYSTEMS HUMAN WEL
   [Anonymous], 2007, P MACHINE LEARNING R
   [Anonymous], OJ L, P7
   Bossard M., 2000, CORINE LAND COVER TE
   Brandt J, 2004, ADV ECOL SCI, V14, P3
   Burkhard B., 2009, Landscape Online
   Carpenter SR, 2006, SCIENCE, V314, P257, DOI 10.1126/science.1131946
   Cebrián-Piqueras MA, 2017, ECOSYST SERV, V23, P108, DOI 10.1016/j.ecoser.2016.11.009
   Cebrian-Piqueras Miguel A., 2017, International Journal of Biodiversity Science Ecosystem Services & Management, V13, P53, DOI 10.1080/21513732.2017.1289245
   Cullum C, 2017, PROG PHYS GEOG, V41, P95, DOI 10.1177/0309133316671103
   Daily GC, 2008, P NATL ACAD SCI USA, V105, P9455, DOI 10.1073/pnas.0804960105
   Dale VH, 2007, ECOL ECON, V64, P286, DOI 10.1016/j.ecolecon.2007.05.009
   de Groot RS, 2010, ECOL COMPLEX, V7, P260, DOI 10.1016/j.ecocom.2009.10.006
   Döring M, 2018, AREA, V50, P169, DOI 10.1111/area.12382
   Dunford R, 2018, ECOSYST SERV, V29, P499, DOI 10.1016/j.ecoser.2017.10.014
   Eisenack K, 2012, Human/nature interactions in the Anthropocene: Potentials of social-ecological systems analysis, P107
   Eisenack K., 2018, 2 RES WORKSH ARCH AN
   Fedele G, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0195895
   Fish RD, 2011, PROG PHYS GEOG, V35, P671, DOI 10.1177/0309133311420941
   Fuerst Christine, 2017, International Journal of Biodiversity Science Ecosystem Services & Management, V13, P412, DOI 10.1080/21513732.2017.1396257
   Kandziora M, 2013, ECOL INDIC, V28, P54, DOI 10.1016/j.ecolind.2012.09.006
   Karrasch L, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9091668
   Karrasch L, 2016, RES HANDB IMPACT ASS, P86
   Kaur S, 2017, FRONT CHEM, V5, DOI 10.3389/fchem.2017.00043
   Koschke L, 2012, ECOL INDIC, V21, P54, DOI 10.1016/j.ecolind.2011.12.010
   Langerwisch F, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aa954d
   Lavorel S, 2017, REG ENVIRON CHANGE, V17, P2251, DOI 10.1007/s10113-017-1207-4
   Levers C, 2018, REG ENVIRON CHANGE, V18, P715, DOI 10.1007/s10113-015-0907-x
   Lim-Camacho L, 2017, REG ENVIRON CHANGE, V17, P93, DOI 10.1007/s10113-016-0976-5
   Maes J, 2012, ECOSYST SERV, V1, P31, DOI 10.1016/j.ecoser.2012.06.004
   Manuel-Navarrete D, 2015, ECOL SOC, V20, DOI 10.5751/ES-07720-200326
   Merino MV, 2019, CLIM DEV, V11, P418, DOI 10.1080/17565529.2018.1442804
   Müller F, 2012, ECOSYST SERV, V1, P26, DOI 10.1016/j.ecoser.2012.06.001
   Muller F., 2010, Landscape Online, P1
   Oberlack C, 2016, GLOBAL ENVIRON CHANG, V41, P153, DOI 10.1016/j.gloenvcha.2016.10.001
   Oberlack C, 2014, GLOBAL ENVIRON CHANG, V24, P349, DOI 10.1016/j.gloenvcha.2013.08.016
   Opdam Paul., 2013, Landscape Ecology for Sustainable Environment and Culture, P77, DOI DOI 10.1007/978-94-007-6530-6_5
   Peña L, 2015, ECOSYST SERV, V13, P108, DOI 10.1016/j.ecoser.2014.12.008
   Plieninger T, 2015, ECOL SOC, V20, DOI 10.5751/ES-07443-200205
   Potschin M, 2013, LANDSCAPE ECOL, V28, P1053, DOI 10.1007/s10980-012-9756-x
   Primmer E, 2012, ECOSYST SERV, V1, P85, DOI 10.1016/j.ecoser.2012.07.008
   Raudsepp-Hearne C, 2010, Proc Natl Acad Sci U S A, V107, P5242, DOI 10.1073/pnas.0907284107
   Rauken T, 2015, LOCAL ENVIRON, V20, P408, DOI 10.1080/13549839.2014.880412
   Rodríguez JP, 2006, ECOL SOC, V11
   Schleyer C, 2015, ECOSYST SERV, V16, P174, DOI 10.1016/j.ecoser.2015.10.014
   Schultz L, 2015, P NATL ACAD SCI USA, V112, P7369, DOI 10.1073/pnas.1406493112
   Seppelt R, 2016, BIOSCIENCE, V66, P890, DOI 10.1093/biosci/biw004
   Sietz D, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa768b
   SIMPSON EH, 1949, NATURE, V163, P688, DOI 10.1038/163688a0
   Stürck J, 2017, LANDSCAPE ECOL, V32, P481, DOI 10.1007/s10980-016-0459-6
   Václavík T, 2016, ENVIRON RES LETT, V11, DOI 10.1088/1748-9326/11/9/095002
   Václavík T, 2013, GLOBAL ENVIRON CHANG, V23, P1637, DOI 10.1016/j.gloenvcha.2013.09.004
   Van der Biest K, 2014, ECOL INDIC, V37, P252, DOI 10.1016/j.ecolind.2013.04.006
   Verhagen W, 2018, ECOL INDIC, V89, P397, DOI 10.1016/j.ecolind.2018.01.019
   Verhagen W, 2016, LANDSCAPE ECOL, V31, P1457, DOI 10.1007/s10980-016-0345-2
   Vrebos D, 2015, ECOSYST SERV, V13, P28, DOI 10.1016/j.ecoser.2014.11.005
   Wamsler C, 2015, ECOL SOC, V20, DOI 10.5751/ES-07489-200230
   Wardropper CB, 2016, ECOL SOC, V21, DOI 10.5751/ES-08384-210212
   Witte S, 2016, WETLANDS, V36, P121, DOI 10.1007/s13157-015-0722-7
   1992, OFFICIAL J L, V206, P7
NR 61
TC 16
Z9 17
U1 3
U2 44
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 JUL
PY 2019
VL 24
IS 2
AR 13
DI 10.5751/ES-10744-240213
PG 13
WC Ecology; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology
GA IT2VT
UT WOS:000482712400007
OA Green Accepted, gold, Green Submitted
DA 2025-01-10
ER

PT J
AU Mazza, G
   Monteverdi, MC
   Altieri, S
   Battipaglia, G
AF Mazza, Gianluigi
   Monteverdi, Maria Cristina
   Altieri, Simona
   Battipaglia, Giovanna
TI Climate-driven growth dynamics and trend reversal of Fagus sylvatica L.
   and Quercus cerris L. in a low-elevation beech forest in Central Italy
SO SCIENCE OF THE TOTAL ENVIRONMENT
LA English
DT Article
DE Climate -growth relationships; Tree -rings analysis; Dendroecology;
   Carbon stable isotope; Climate warming
ID CARBON-ISOTOPE DISCRIMINATION; WATER-USE EFFICIENCY; EUROPEAN BEECH;
   RANGE CORE; DROUGHT; TREES; RESPONSES; LIMIT; OAK; DENDROCHRONOLOGY
AB In highly climate-change-sensitive regions, such as the Mediterranean, increasing knowledge of climate-driven growth dynamics is required for habitat conservation and forecasting species adaptability under future climate change. In this study, we test a high spectrum of climatic signals, not only monthly and seasonal but also on a multi-year scale and include the single tree analysis to answer this issue, focusing on a low-elevation thermophilic old-growth beech forest surrounding the Bracciano Lake in Central Italy. Through a dendroecological and isotope analysis, we evaluate both short- and long-term sensitivity of F. sylvatica and the coexisting better-drought-adapted species Q. cerris to climatic and hydrological variability in terms of growth reduction and delta 13C responses. After the 1990s, beech trees showed a climate-driven decrease in growth compared to oak, especially after 2003 (-20 % of basal area increment), with a significant growth trend reversal between the species. For F. sylvatica, the significant correlations with precipitation decreased, whereas for Q. cerris, they increased, with a higher number of trees positively influenced. However, the temperature highlighted more clearly the contrasting climate-growth correlation pattern between the two species. In F. sylvatica after the '90s, the negative effect of temperatures has significantly intensified, as shown by past summer values up to four years previously, involving about half of the trees. Surprisingly, the water-level fluctuations showed a highly significant influence on tree-ring growth in both species. Nevertheless, it reduced after the '90s. Finally, Q. cerris trees showed a significantly higher ability to recover their growth levels after extreme droughts (+55 %). The growth trend reversal and the shift in iWUE of the last years may point to potential changes in the future species composition, raising the need for climate-adaptive silviculture (e.g., selective thinning) to reduce growth decline, enhance resilience and favour the natural regeneration of the target species for habitat conservation.
C1 [Mazza, Gianluigi; Monteverdi, Maria Cristina] CREA Res Ctr Forestry & Wood, Arezzo, Italy.
   [Altieri, Simona; Battipaglia, Giovanna] Univ Naples 2, Dept Environm Biol & Pharmaceut Sci & Technol, Caserta, Italy.
C3 Universita della Campania Vanvitelli
RP Mazza, G (corresponding author), CREA Res Ctr Forestry & Wood, Arezzo, Italy.
EM gianluigi.mazza@crea.gov.it
RI Altieri, Simona/AAN-9284-2021; Mazza, Gianluigi/C-8955-2013; Monteverdi,
   Maria Cristina/C-9687-2016
OI Monteverdi, Maria Cristina/0000-0003-1786-4713
FU Project "LakeFagus", funded by the Regional Natural Park of
   Bracciano-Martignano (Lazio region, Italy)
FX This work was supported by the Project "LakeFagus", funded by the
   Regional Natural Park of Bracciano-Martignano (Lazio region, Italy) .
   The authors would like to thank the Director and the personnel from the
   Regional Natural Park of Bracciano-Martignano, especially Dr. Salvatore
   Mineo, for field assistance and collaboration. We also wish to thank our
   colleague Dr. Ugo Chiavetta from CREA for helping with field work. We
   also wish to thank two anonymous reviewers for their useful comments and
   suggestions that helped to improve the article.
CR Altieri S, 2015, TREES-STRUCT FUNCT, V29, P1593, DOI 10.1007/s00468-015-1242-z
   Babst F, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aat4313
   Battipaglia G, 2009, FOREST ECOL MANAG, V257, P820, DOI 10.1016/j.foreco.2008.10.015
   Battipaglia G, 2020, GLOB ECOL CONSERV, V24, DOI 10.1016/j.gecco.2020.e01274
   Battipaglia G, 2014, PLANT CELL ENVIRON, V37, P382, DOI 10.1111/pce.12160
   Bert D, 2022, DENDROCHRONOLOGIA, V72, DOI 10.1016/j.dendro.2022.125939
   Biondi F, 2008, TREE-RING RES, V64, P81, DOI 10.3959/2008-6.1
   Bontemps JD, 2011, DENDROCHRONOLOGIA, V29, P99, DOI 10.1016/j.dendro.2010.09.002
   Bose AK, 2021, SCI TOTAL ENVIRON, V784, DOI 10.1016/j.scitotenv.2021.147222
   Bosela M, 2016, AGR FOREST METEOROL, V222, P21, DOI 10.1016/j.agrformet.2016.03.005
   Bréda N, 2006, ANN FOREST SCI, V63, P625, DOI 10.1051/forest:2006042
   Bricca A, 2022, PERSPECT PLANT ECOL, V56, DOI 10.1016/j.ppees.2022.125675
   Brinkmann N, 2019, PLANT BIOLOGY, V21, P71, DOI 10.1111/plb.12907
   Bunn AG, 2008, DENDROCHRONOLOGIA, V26, P115, DOI 10.1016/j.dendro.2008.01.002
   Bunn AG, 2010, DENDROCHRONOLOGIA, V28, P251, DOI 10.1016/j.dendro.2009.12.001
   BUTTNER V, 1994, FOREST ECOL MANAG, V70, P11, DOI 10.1016/0378-1127(94)90071-X
   Linares JC, 2011, OECOLOGIA, V167, P847, DOI 10.1007/s00442-011-2012-2
   Cavin L, 2017, GLOBAL CHANGE BIOL, V23, P362, DOI 10.1111/gcb.13366
   Cavin L, 2013, FUNCT ECOL, V27, P1424, DOI 10.1111/1365-2435.12126
   Cherubini P, 2021, CURR FOR REP, V7, P69, DOI 10.1007/s40725-021-00137-8
   Cook ER, 2001, ECOL APPL, V11, P883, DOI 10.1890/1051-0761(2001)011[0883:IFGOTI]2.0.CO;2
   del Castillo EM, 2022, COMMUN BIOL, V5, DOI 10.1038/s42003-022-03107-3
   Di Filippo A, 2007, J BIOGEOGR, V34, P1873, DOI 10.1111/j.1365-2699.2007.01747.x
   Di Iorio A, 2007, TREE PHYSIOL, V27, P407, DOI 10.1093/treephys/27.3.407
   Dorman M, 2015, OECOLOGIA, V177, P1025, DOI 10.1007/s00442-015-3229-2
   Drobyshev I, 2010, FOREST ECOL MANAG, V259, P2160, DOI 10.1016/j.foreco.2010.01.037
   FARQUHAR GD, 1989, ANNU REV PLANT PHYS, V40, P503, DOI 10.1146/annurev.pp.40.060189.002443
   Francey RJ, 1999, J GEOPHYS RES-ATMOS, V104, P23631, DOI 10.1029/1999JD900357
   Frelich Lee E., 2003, Environmental Reviews, V11, pS9, DOI 10.1139/a03-011
   Fyllas NM, 2009, GLOBAL ECOL BIOGEOGR, V18, P64, DOI 10.1111/j.1466-8238.2008.00419.x
   Gärtner H, 2010, DENDROCHRONOLOGIA, V28, P85, DOI 10.1016/j.dendro.2009.09.002
   Genet H, 2010, TREE PHYSIOL, V30, P177, DOI 10.1093/treephys/tpp105
   Gessler A, 2007, TREES-STRUCT FUNCT, V21, P1, DOI 10.1007/s00468-006-0107-x
   Gillner S, 2013, FOREST ECOL MANAG, V302, P372, DOI 10.1016/j.foreco.2013.03.032
   Giorgi F, 2002, CLIM DYNAM, V18, P675, DOI 10.1007/s00382-001-0204-x
   Grime J.P., 2012, The Evolutionary Strategies that Shape Ecosystems
   Hacket-Pain AJ, 2016, EUR J FOREST RES, V135, P897, DOI 10.1007/s10342-016-0982-7
   Hacket-Pain AJ, 2017, DENDROCHRONOLOGIA, V44, P22, DOI 10.1016/j.dendro.2017.02.005
   Hacket-Pain AJ, 2015, TREE PHYSIOL, V35, P319, DOI 10.1093/treephys/tpv007
   Hampe A, 2011, ANNU REV ECOL EVOL S, V42, P313, DOI 10.1146/annurev-ecolsys-102710-145015
   Hartl-Meier C, 2014, TREES-STRUCT FUNCT, V28, P819, DOI 10.1007/s00468-014-0994-1
   Harvey JE, 2020, GLOBAL CHANGE BIOL, V26, P2505, DOI 10.1111/gcb.14966
   Jump AS, 2006, GLOBAL CHANGE BIOL, V12, P2163, DOI 10.1111/j.1365-2486.2006.01250.x
   Jump AS, 2010, J ENVIRON MONITOR, V12, P1791, DOI 10.1039/b923773a
   Kasper J, 2022, FOREST ECOL MANAG, V506, DOI 10.1016/j.foreco.2021.119892
   Kasper J, 2021, ANN FOREST SCI, V78, DOI 10.1007/s13595-021-01081-0
   King GM, 2013, OECOLOGIA, V173, P1587, DOI 10.1007/s00442-013-2696-6
   Kirfel K, 2019, FOREST ECOL MANAG, V444, P256, DOI 10.1016/j.foreco.2019.04.022
   Knapp AK, 2015, GLOBAL CHANGE BIOL, V21, P2624, DOI 10.1111/gcb.12888
   Korner C., 2012, ALPINE TREELINES FUN
   Kramer K, 2010, FOREST ECOL MANAG, V259, P2213, DOI 10.1016/j.foreco.2009.12.023
   Kulla L, 2023, FOREST ECOL MANAG, V529, DOI 10.1016/j.foreco.2022.120633
   Latte N, 2015, DENDROCHRONOLOGIA, V33, P69, DOI 10.1016/j.dendro.2015.01.002
   Lendzion J, 2008, FOREST ECOL MANAG, V256, P648, DOI 10.1016/j.foreco.2008.05.008
   Leuschner C, 2001, FOREST ECOL MANAG, V149, P33, DOI 10.1016/S0378-1127(00)00543-0
   Leuschner C, 2020, PERSPECT PLANT ECOL, V47, DOI 10.1016/j.ppees.2020.125576
   Lloret F, 2011, OIKOS, V120, P1909, DOI 10.1111/j.1600-0706.2011.19372.x
   Marín SD, 2023, FOR ECOSYST, V10, DOI 10.1016/j.fecs.2023.100097
   Mazza G, 2021, ECOL INDIC, V130, DOI 10.1016/j.ecolind.2021.108109
   Mazza G, 2021, TREES-STRUCT FUNCT, V35, P1697, DOI 10.1007/s00468-021-02151-6
   Mazza G, 2020, AGR FOREST METEOROL, V291, DOI 10.1016/j.agrformet.2020.108036
   Mazza G, 2018, FOREST ECOL MANAG, V425, P9, DOI 10.1016/j.foreco.2018.05.029
   McCarroll D, 2017, TREE PHYSIOL, V37, P1021, DOI 10.1093/treephys/tpx030
   Meier IC, 2018, ECOSYSTEMS, V21, P280, DOI 10.1007/s10021-017-0148-6
   Müller-Haubold H, 2013, ECOSYSTEMS, V16, P1498, DOI 10.1007/s10021-013-9698-4
   Niccoli F, 2023, DENDROCHRONOLOGIA, V79, DOI 10.1016/j.dendro.2023.126086
   Ogle K, 2015, ECOL LETT, V18, P221, DOI 10.1111/ele.12399
   Packham JR, 2012, J ECOL, V100, P1557, DOI 10.1111/j.1365-2745.2012.02017.x
   Peltier DMP, 2018, J ECOL, V106, P613, DOI 10.1111/1365-2745.12878
   Peñuelas J, 2008, GLOBAL CHANGE BIOL, V14, P1076, DOI 10.1111/j.1365-2486.2008.01563.x
   Pesaresi S, 2017, J MAPS, V13, P955, DOI 10.1080/17445647.2017.1413017
   Piovesan G, 2005, J VEG SCI, V16, P13, DOI 10.1111/j.1654-1103.2005.tb02334.x
   Piovesan G, 2008, GLOBAL CHANGE BIOL, V14, P1265, DOI 10.1111/j.1365-2486.2008.01570.x
   R Core Team, 2020, R: A Language and Environment for Statistical Computing
   Rezaie N, 2018, TREE PHYSIOL, V38, P1110, DOI 10.1093/treephys/tpy025
   Sala A, 2012, TREE PHYSIOL, V32, P764, DOI 10.1093/treephys/tpr143
   Saurer M, 2004, GLOBAL CHANGE BIOL, V10, P2109, DOI 10.1111/j.1365-2486.2004.00869.x
   Schweingruber F.H, 1989, Tree Rings: Basics and Applications of Dendrochronology, P273
   Tardif J, 2003, ECOL MONOGR, V73, P241, DOI 10.1890/0012-9615(2003)073[0241:SVITGI]2.0.CO;2
   Taviani S, 2015, HYDROGEOL J, V23, P1481, DOI 10.1007/s10040-015-1271-0
   Tegel W, 2014, EUR J FOREST RES, V133, P61, DOI 10.1007/s10342-013-0737-7
   Timofeeva G, 2017, TREE PHYSIOL, V37, P1028, DOI 10.1093/treephys/tpx041
   Vacchiano G, 2017, NEW PHYTOL, V215, P595, DOI 10.1111/nph.14600
   Vanhellemont M, 2019, SCI TOTAL ENVIRON, V650, P3017, DOI 10.1016/j.scitotenv.2018.10.054
   Vicente-Serrano SM, 2010, J CLIMATE, V23, P1696, DOI 10.1175/2009JCLI2909.1
   Vilà-Cabrera A, 2019, ECOL LETT, V22, P1439, DOI 10.1111/ele.13329
   Zimmermann J, 2015, ECOSYSTEMS, V18, P560, DOI 10.1007/s10021-015-9849-x
NR 87
TC 5
Z9 5
U1 7
U2 32
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 15
PY 2024
VL 908
AR 168250
DI 10.1016/j.scitotenv.2023.168250
EA NOV 2023
PG 12
WC Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA Z1QH8
UT WOS:001109893200001
PM 37926261
DA 2025-01-10
ER

PT J
AU Elbeltagi, A
   Srivastava, A
   Deng, JS
   Li, ZB
   Raza, A
   Khadke, L
   Yu, ZL
   El-Rawy, M
AF Elbeltagi, Ahmed
   Srivastava, Aman
   Deng, Jinsong
   Li, Zhibin
   Raza, Ali
   Khadke, Leena
   Yu, Zhoulu
   El-Rawy, Mustafa
TI Forecasting vapor pressure deficit for agricultural water management
   using machine learning in semi-arid environments
SO AGRICULTURAL WATER MANAGEMENT
LA English
DT Article
DE Agricultural Water Management; Meteorological Data; Machine Learning
   Random Subspace; REPTree; Partial auto-correlation function
ID RANDOM SUBSPACE METHOD; EVAPORATIVE DEMAND; REFERENCE
   EVAPOTRANSPIRATION; SURFACE HUMIDITY; NEURAL-NETWORKS; USE EFFICIENCY;
   UNITED-STATES; RANDOM FOREST; CLIMATE; TEMPERATURE
AB Precise evapotranspiration (ET) estimation is critical for agricultural water management, particularly in waterstressed developing countries. Vapor Pressure Deficit is one of the ET parameters that has a significant impact on its calculation (VPD). This paper forecasts VPD using ensemble learning-based modeling in eight different regions (Dakahliyah, Gharbiyah, Kafr Elsheikh, Dumyat, Port Said, Ismailia, Sharqiyah, and Qalubiyah) in Egypt. In this study, six machine learning algorithms were used: Linear Regression (LR), Additive regression trees (ART), Random SubSpace (RSS), Random Forest (RF), Reduced Error Pruning Tree (REPTree), and Quinlan's M5 algorithm (M5P). Monthly vapor pressure data were obtained from the Japanese 55-year Reanalysis JRA-55 from 1958 to 2021. The dateset has been divided into two segments: the training stage (1958-2005) and the testing stage (2006-2021). Five statistical measures were used to evaluate the model performances: Correlation Coefficient (CC), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Relative absolute error (RAE), and Root Relative Squared Error (RRSE), across both training and testing stages. RF model outperformed the rest of the models [CC = 0.9694; MAE = 0.0967; RMSE = 0.1252; RAE (%) = 21.7297 and RRSE (%) = 24.0356], followed closely by REPTree and RSS models. On the other hand, M5P model performance remained moderate and both LR and AR model were the worst. During the testing stage, RF outperformed the rest of the models in terms of (which statistic), followed closely by REPTree and RSS models. On the other hand, M5P performance remained moderate and both LR and AR models were the worst. This study recommended using the RF model for future hydro-climatological studies in general, and vapor pressure deficit modeling and prediction in particular. This study enables future magnitudes to be predicted, alerting the authorities and administrators involved to focus their policy-making on more specific pathways toward climate adaptation.
C1 [Elbeltagi, Ahmed; Deng, Jinsong; Li, Zhibin; Yu, Zhoulu] Zhejiang Univ, Coll Environm & Resources Sci, Hangzhou 310058, Zhejiang, Peoples R China.
   [Elbeltagi, Ahmed; Deng, Jinsong] Zhejiang Ecol Civilizat Acad, Zhejiang 313300, Peoples R China.
   [Elbeltagi, Ahmed] Mansoura Univ, Fac Agr, Agr Engn Dept, Mansoura 35516, Egypt.
   [Srivastava, Aman] Indian Inst Technol IIT Kharagpur, Dept Civil Engn, Kharagpur 721302, West Bengal, India.
   [Li, Zhibin] Univ Chinese Acad Sci, Beijing, Peoples R China.
   [Raza, Ali] Jiangsu Univ, Sch Agr Engn, Zhenjiang 212013, Peoples R China.
   [Khadke, Leena] Indian Inst Technol IIT Bombay, Dept Civil Engn, Mumbai 400076, Maharashtra, India.
   [El-Rawy, Mustafa] Minia Univ, Fac Engn, Civil Engn Dept, Al Minya 61111, Egypt.
   [El-Rawy, Mustafa] Shaqra Univ, Coll Engn, Civil Engn Dept, Dawadmi 11911, Saudi Arabia.
C3 Zhejiang University; Egyptian Knowledge Bank (EKB); Mansoura University;
   Indian Institute of Technology System (IIT System); Indian Institute of
   Technology (IIT) - Kharagpur; Chinese Academy of Sciences; University of
   Chinese Academy of Sciences, CAS; Jiangsu University; Indian Institute
   of Technology System (IIT System); Indian Institute of Technology (IIT)
   - Bombay; Egyptian Knowledge Bank (EKB); Minia University; Shaqra
   University
RP Deng, JS; Yu, ZL (corresponding author), Zhejiang Univ, Coll Environm & Resources Sci, Hangzhou 310058, Zhejiang, Peoples R China.
EM jsong_deng@zju.edu.cn; yuzl@zju.edu.cn
RI Raza, Ali/IZD-7266-2023; El-Rawy, Mustafa/G-6605-2018; Deng,
   Jinsong/A-9301-2015; Srivastava, Aman/HPH-0177-2023; Elbeltagi,
   Ahmed/P-4614-2018
OI Elbeltagi, Ahmed/0000-0002-5506-9502; Khadke, Leena/0000-0002-9149-4696;
   Raza, Ali/0000-0001-9207-5779
FU National Science and Technology Support Projects of China
   [2020YFC1807501]
FX Funding This research was funded by the National Science and Technology
   Support Projects of China (No. 2020YFC1807501) .
CR Abdelaty E.F., 2015, J AGR ENV SCI DAM U, V14, P17
   Ahmar S, 2020, INT J MOL SCI, V21, DOI 10.3390/ijms21072590
   Allen R. G., 1998, FAO Irrigation and Drainage Paper
   [Anonymous], 2014, INT J ADV RES COMPUT
   Baudoin W., 2020, 217 FAO UN
   Blaifi SA, 2018, SOL ENERGY, V163, P405, DOI 10.1016/j.solener.2018.01.071
   BOLTON D, 1980, MON WEATHER REV, V108, P1046, DOI 10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2
   Bramer I, 2018, ADV ECOL RES, V58, P101, DOI 10.1016/bs.aecr.2017.12.005
   Breiman L, 2001, MACH LEARN, V45, P5, DOI 10.1023/A:1010933404324
   CAPMAS, 2022, Central Agency for Public Mobilization & Statistics Annual Bulletin of Statistical Crop Area and Plant Production, 2019/ 2020.
   Carins Murphy MR, 2014, PLANT CELL ENVIRON, V37, P124, DOI 10.1111/pce.12136
   Carnicer J, 2013, FRONT PLANT SCI, V4, DOI 10.3389/fpls.2013.00409
   Chen W, 2019, J HYDROL, V575, P864, DOI 10.1016/j.jhydrol.2019.05.089
   Chipman HA, 2010, ANN APPL STAT, V4, P266, DOI 10.1214/09-AOAS285
   André GD, 2022, SCI REP-UK, V12, DOI 10.1038/s41598-022-12863-5
   Dai A, 2006, J CLIMATE, V19, P3589, DOI 10.1175/JCLI3816.1
   Dai AG, 2018, CURR CLIM CHANGE REP, V4, P301, DOI 10.1007/s40641-018-0101-6
   de Cárcer PS, 2018, GLOBAL CHANGE BIOL, V24, P1108, DOI 10.1111/gcb.13973
   Devasena CL., 2014, INT J COMPUT APPL, V975, P30
   Devi MJ, 2016, PHYSIOL PLANTARUM, V156, P387, DOI 10.1111/ppl.12378
   Devi MJ, 2018, ENVIRON EXP BOT, V155, P509, DOI 10.1016/j.envexpbot.2018.07.024
   Ding JZ, 2018, GEOPHYS RES LETT, V45, P2852, DOI 10.1002/2017GL076803
   Du QJ, 2018, PLANT SOIL ENVIRON, V64, P13, DOI 10.17221/701/2017-PSE
   El-Rawy M, 2020, REGION GEOL REV, P687, DOI 10.1007/978-3-030-15265-9_18
   Elbeltagi A, 2022, APPL WATER SCI, V12, DOI 10.1007/s13201-022-01667-7
   Elbeltagi A, 2022, STOCH ENV RES RISK A, V36, P3311, DOI 10.1007/s00477-022-02196-0
   Emami M, 2022, WATER-SUI, V14, DOI 10.3390/w14121937
   Feng Y, 2019, GEODERMA, V338, P67, DOI 10.1016/j.geoderma.2018.11.044
   Ficklin DL, 2017, J GEOPHYS RES-ATMOS, V122, P2061, DOI 10.1002/2016JD025855
   Fletcher AL, 2007, ENVIRON EXP BOT, V61, P145, DOI 10.1016/j.envexpbot.2007.05.004
   Gavilán P, 2007, AGR WATER MANAGE, V89, P275, DOI 10.1016/j.agwat.2007.01.014
   Gong XW, 2020, AGR WATER MANAGE, V235, DOI 10.1016/j.agwat.2020.106154
   Grossiord C, 2020, NEW PHYTOL, V226, P1550, DOI 10.1111/nph.16485
   Guichard S, 2005, J PLANT GROWTH REGUL, V24, P201, DOI 10.1007/s00344-005-0040-z
   Hammad M, 2021, STOCH ENV RES RISK A, V35, P2213, DOI 10.1007/s00477-021-02013-0
   Ho TK, 1998, IEEE T PATTERN ANAL, V20, P832, DOI 10.1109/34.709601
   Huntington T, 2020, BIOFUEL BIOPROD BIOR, V14, P566, DOI 10.1002/bbb.2087
   IPCC, 2013, CLIM CHANG 2013B PHY, V33
   IPCC, 2013, CLIM CHANG 2013A PHY
   Iribarne J.V., 1981, ATMOSPHERIC THERMODY, P65
   Islam AMT, 2022, SUSTAINABILITY-BASEL, V14, DOI 10.3390/su14095233
   Jung M, 2010, NATURE, V467, P951, DOI 10.1038/nature09396
   Khan MT, 2021, WATER-SUI, V13, DOI 10.3390/w13243528
   Khosravi A, 2021, HORTICULTURAE, V7, DOI 10.3390/horticulturae7100349
   Khosravi K, 2019, COMPUT ELECTRON AGR, V167, DOI 10.1016/j.compag.2019.105041
   Kimball JS, 1997, AGR FOREST METEOROL, V85, P87, DOI 10.1016/S0168-1923(96)02366-0
   Kobayashi S, 2015, J METEOROL SOC JPN, V93, P5, DOI 10.2151/jmsj.2015-001
   Konings AG, 2017, NAT GEOSCI, V10, P284, DOI [10.1038/ngeo2903, 10.1038/NGEO2903]
   Leuschner C, 2002, FLORA, V197, P262, DOI 10.1078/0367-2530-00040
   Li Y, 2022, J HYDROL, V610, DOI 10.1016/j.jhydrol.2022.127788
   Liu WB, 2017, J HYDROMETEOROL, V18, P977, DOI [10.1175/jhm-d-16-0204.1, 10.1175/JHM-D-16-0204.1]
   Lobell DB, 2014, SCIENCE, V344, P516, DOI 10.1126/science.1251423
   Maulud D., 2020, Journal of Applied Science and Technology Trends, V1, P140, DOI [10.38094/jastt1457, DOI 10.38094/JASTT1457]
   Mert A, 2016, EXPERT SYST, V33, P275, DOI 10.1111/exsy.12149
   Mokhtar A, 2021, COMPUT ELECTRON AGR, V191, DOI 10.1016/j.compag.2021.106501
   Nguyen DH, 2022, J HYDROL, V606, DOI 10.1016/j.jhydrol.2022.127445
   Novick KA, 2016, NAT CLIM CHANGE, V6, P1023, DOI [10.1038/nclimate3114, 10.1038/NCLIMATE3114]
   Onyari E.K., 2013, International Journal of Innovation, Management and Technology, P11, DOI DOI 10.7763/IJIMT.2013.V4.347
   Otieno D, 2012, WETLANDS, V32, P895, DOI 10.1007/s13157-012-0322-8
   Paredes P, 2018, THEOR APPL CLIMATOL, V134, P1115, DOI 10.1007/s00704-017-2329-9
   Perry Dr Chris, 2018, IMPROVING IRRIGATION
   Pierce DW, 2013, HYDROL EARTH SYST SC, V17, P1833, DOI 10.5194/hess-17-1833-2013
   Qiu RJ, 2020, PLANT J, V101, P543, DOI 10.1111/tpj.14553
   Qiu RJ, 2019, AGR WATER MANAGE, V224, DOI 10.1016/j.agwat.2019.105755
   Quinlan J. R., 1992, Proceedings of the 5th Australian Joint Conference on Artificial Intelligence. AI '92, P343
   QUINLAN JR, 1987, INT J MAN MACH STUD, V27, P221, DOI 10.1016/S0020-7373(87)80053-6
   Rahimikhoob A, 2010, THEOR APPL CLIMATOL, V101, P83, DOI 10.1007/s00704-009-0204-z
   Rahman M, 2021, J ENVIRON MANAGE, V295, DOI 10.1016/j.jenvman.2021.113086
   Rana G, 2000, EUR J AGRON, V13, P125, DOI 10.1016/S1161-0301(00)00070-8
   RAWSON HM, 1977, PLANTA, V134, P5, DOI 10.1007/BF00390086
   Raza A, 2021, FRESEN ENVIRON BULL, V30, P7490
   Raza A, 2020, PURE APPL GEOPHYS, V177, P4479, DOI 10.1007/s00024-020-02473-5
   Raza A, 2020, THEOR APPL CLIMATOL, V139, P1459, DOI 10.1007/s00704-019-03007-3
   Restaino CM, 2016, P NATL ACAD SCI USA, V113, P9557, DOI 10.1073/pnas.1602384113
   Rhein M, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P255
   Schoppach R, 2016, J EXP BOT, V67, P2847, DOI 10.1093/jxb/erw125
   Sellin A, 2019, J PLANT RES, V132, P369, DOI 10.1007/s10265-019-01106-w
   Shamshirband S, 2020, ENG APPL COMP FLUID, V14, P339, DOI 10.1080/19942060.2020.1715844
   Shen Rong, 2018, MATEC Web of Conferences, V176, DOI 10.1051/matecconf/201817601033
   Shi T, 2006, J COMPUT GRAPH STAT, V15, P118, DOI 10.1198/106186006X94072
   Shoaib M, 2018, WATER RESOUR MANAG, V32, P83, DOI 10.1007/s11269-017-1796-1
   Simmons AJ, 2010, J GEOPHYS RES-ATMOS, V115, DOI 10.1029/2009JD012442
   Skurichina M, 2002, PATTERN ANAL APPL, V5, P121, DOI 10.1007/s100440200011
   Smidt SJ, 2016, SCI TOTAL ENVIRON, V566, P988, DOI 10.1016/j.scitotenv.2016.05.127
   Sparks JP, 1999, TREE PHYSIOL, V19, P453
   Su XG, 2012, WIRES COMPUT STAT, V4, P275, DOI 10.1002/wics.1198
   Tan YV, 2019, STAT MED, V38, P5048, DOI 10.1002/sim.8347
   Trajkovic S, 2009, J IRRIG DRAIN ENG, V135, P443, DOI 10.1061/(ASCE)IR.1943-4774.0000094
   Vicente-Serrano SM, 2018, EARTH SYST DYNAM, V9, P915, DOI 10.5194/esd-9-915-2018
   Nhu VH, 2020, ISPRS INT J GEO-INF, V9, DOI 10.3390/ijgi9080479
   Vincent L. A, 2004, B AM METEOROL SOC, P4633
   Wada Y, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/10/104003
   Wang JZ, 2022, WATER-SUI, V14, DOI 10.3390/w14101666
   Wang KC, 2012, J CLIMATE, V25, P8353, DOI 10.1175/JCLI-D-11-00492.1
   Willett KM, 2014, CLIM PAST, V10, P1983, DOI 10.5194/cp-10-1983-2014
   Willett KM, 2008, J CLIMATE, V21, P5364, DOI 10.1175/2008JCLI2274.1
   Williams AP, 2013, NAT CLIM CHANGE, V3, P292, DOI [10.1038/NCLIMATE1693, 10.1038/nclimate1693]
   Williams LE, 2007, AM J ENOL VITICULT, V58, P173
   Yoo C, 2019, ISPRS J PHOTOGRAMM, V157, P155, DOI 10.1016/j.isprsjprs.2019.09.009
   Yuan WP, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aax1396
   Zhang BZ, 2016, AGR FOREST METEOROL, V216, P1, DOI 10.1016/j.agrformet.2015.09.015
   Zhang DL, 2018, HORTSCIENCE, V53, P1784, DOI [10.21273/HORTSCI13129-18, 10.21273/hortsci13129-18]
   Zounemat-Kermani M, 2021, J HYDROL, V598, DOI 10.1016/j.jhydrol.2021.126266
NR 103
TC 14
Z9 14
U1 7
U2 20
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 JUN 1
PY 2023
VL 283
AR 108302
DI 10.1016/j.agwat.2023.108302
EA APR 2023
PG 15
WC Agronomy; Water Resources
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Water Resources
GA F4ET8
UT WOS:000981901300001
OA hybrid
DA 2025-01-10
ER

PT J
AU Weithmann, G
   Paligi, SS
   Schuldt, B
   Leuschner, C
AF Weithmann, Greta
   Paligi, Sharath Shyamappa
   Schuldt, Bernhard
   Leuschner, Christoph
TI Branch xylem vascular adjustments in European beech in response to
   decreasing water availability across a precipitation gradient
SO TREE PHYSIOLOGY
LA English
DT Article
DE branch age; drought acclimation; hydraulic conductivity; precipitation;
   soil moisture; tree height; vessel diameter
ID FAGUS-SYLVATICA L.; CAVITATION RESISTANCE; WOOD ANATOMY; HYDRAULIC
   CONDUCTIVITY; VESSEL SIZE; TRADE-OFFS; VULNERABILITY; TREE; ANGIOSPERM;
   TRAITS
AB Crucial for the climate adaptation of trees is a xylem anatomical structure capable of adjusting to changing water regimes. Although species comparisons across climate zones have demonstrated anatomical change in response to altered water availability and tree height, less is known about the adaptability of tree vascular systems to increasing water deficits at the intraspecific level. Information on the between-population and within-population variability of xylem traits helps assessing a species' ability to cope with climate change. We investigated the variability of wood anatomical and related hydraulic traits in terminal branches of European beech (Fagus sylvatica L.) trees across a precipitation gradient (520-890 mm year(-1)) and examined the influence of climatic water balance (CWB), soil water capacity (AWC), neighborhood competition (CI), tree height and branch age on these traits. Furthermore, the relationship between xylem anatomical traits and embolism resistance (P-50) was tested. Within-population trait variation was larger than between-population variation. Vessel diameter, lumen-to-sapwood area ratio and potential conductivity of terminal branches decreased with decreasing CWB, but these traits were not affected by AWC, whereas vessel density increased with an AWC decrease. In contrast, none of the studied anatomical traits were influenced by variation in tree height (21-34 m) or CI. Branch age was highly variable (2-22 years) despite equal diameter and position in the flow path, suggesting different growth trajectories in the past. Vessel diameter decreased, and vessel density increased, with increasing branch age, reflecting negative annual radial growth trends. Although vessel diameter was not related to P-50, vessel grouping index and lumen-to-sapwood area ratio showed a weak, though highly significant, positive relationship to P-50. We conclude that the xylem anatomy of terminal tree-top branches in European beech is modified in response to increasing climatic aridity and/or decreasing soil water availability, independent of a tree height effect.
C1 [Weithmann, Greta; Paligi, Sharath Shyamappa; Schuldt, Bernhard; Leuschner, Christoph] Univ Goettingen, Albrecht von Haller Inst Plant Sci, Plant Ecol, Untere Karspule 2, D-37073 Gottingen, Germany.
   [Schuldt, Bernhard] Univ Wurzburg, Julius von Sachs Inst Biol Sci, Ecophysiol & Vegetat Ecol, Julius von Sachs Pl, D-97082 Wurzburg, Germany.
   [Leuschner, Christoph] Univ Goettingen, Ctr Biodivers & Sustainable Land Use CBL, D-37075 Gottingen, Germany.
C3 University of Gottingen; University of Wurzburg; University of Gottingen
RP Weithmann, G (corresponding author), Univ Goettingen, Albrecht von Haller Inst Plant Sci, Plant Ecol, Untere Karspule 2, D-37073 Gottingen, Germany.
EM greta.weithmann@uni-goettingen.de; cleusch@gwdg.de
RI Schuldt, Bernhard/O-4172-2015
FU Federal Ministries of Food and Agriculture (BMEL); Environment, Nature
   Conservation and Nuclear Safety (BMU) through the Waldklimafonds [FKZ:
   22WC415001]
FX We thank Ana Sapoznikova for her help with the anatomical analyses and
   several student assistants for their support in collecting the samples.
   This study is part of the project 'Beechlimits'. The financial support
   from the Federal Ministries of Food and Agriculture (BMEL) and
   Environment, Nature Conservation and Nuclear Safety (BMU) through the
   Waldklimafonds (FKZ: 22WC415001) is gratefully acknowledged. We thank
   the Nordwestdeutsche Forstliche Versuchsanstalt, the Landesforsten of
   Brandenburg, Hamburg, Mecklenburg-Vorpommern and Schleswig-Holstein and
   the forest officers of the different study sites for the permission to
   sample the trees and for the support with stand-related information.
CR ALONI R, 1983, DIFFERENTIATION, V24, P203, DOI 10.1111/j.1432-0436.1983.tb01320.x
   Aloni R, 2001, J PLANT GROWTH REGUL, V20, P22, DOI 10.1007/s003440010001
   Aloni R, 2015, TREES-STRUCT FUNCT, V29, P1, DOI 10.1007/s00468-014-1070-6
   Anfodillo T, 2006, NEW PHYTOL, V169, P279, DOI 10.1111/j.1469-8137.2005.01587.x
   Anfodillo T, 2013, IAWA J, V34, P352, DOI 10.1163/22941932-00000030
   Aranda I, 2017, TREE PHYSIOL, V37, P938, DOI 10.1093/treephys/tpx058
   Awad H, 2010, PHYSIOL PLANTARUM, V139, P280, DOI 10.1111/j.1399-3054.2010.01367.x
   BAAS P, 1983, IAWA BULL, V4, P141, DOI 10.1163/22941932-90000407
   Bates D, 2015, J STAT SOFTW, V67, P1, DOI 10.18637/jss.v067.i01
   Borghetti M, 2017, TREE PHYSIOL, V37, P4, DOI 10.1093/treephys/tpw087
   Burgess SSO, 2006, PLANT CELL ENVIRON, V29, P229, DOI 10.1111/j.1365-3040.2005.01415.x
   Cabon A, 2020, NEW PHYTOL, V225, P209, DOI 10.1111/nph.16146
   CARLQUIST S, 1977, ANN MO BOT GARD, V64, P627, DOI 10.2307/2395258
   Carrer M, 2015, TREE PHYSIOL, V35, P27, DOI 10.1093/treephys/tpu108
   Chenlemuge T, 2015, TREES-STRUCT FUNCT, V29, P623, DOI 10.1007/s00468-014-1131-x
   Christman MA, 2009, NEW PHYTOL, V182, P664, DOI 10.1111/j.1469-8137.2009.02776.x
   Cochard H, 2005, PHYSIOL PLANTARUM, V124, P410, DOI 10.1111/j.1399-3054.2005.00526.x
   Fajardo A, 2020, NEW PHYTOL, V225, P2347, DOI 10.1111/nph.16287
   Fan ZX, 2009, IAWA J, V30, P1, DOI 10.1163/22941932-90000198
   Fichot R, 2010, PLANT CELL ENVIRON, V33, P1553, DOI 10.1111/j.1365-3040.2010.02164.x
   Fonti P, 2013, PLANT BIOLOGY, V15, P210, DOI 10.1111/j.1438-8677.2012.00599.x
   Gartner BL, 1997, WOOD FIBER SCI, V29, P10
   Gleason SM, 2018, NEW PHYTOL, V218, P1360, DOI 10.1111/nph.15116
   Hacke UG, 2006, TREE PHYSIOL, V26, P689, DOI 10.1093/treephys/26.6.689
   Hacke UG, 2017, PLANT CELL ENVIRON, V40, P831, DOI 10.1111/pce.12777
   Hajek P, 2016, FRONT PLANT SCI, V7, DOI 10.3389/fpls.2016.00791
   Hajek P, 2015, FOREST ECOL MANAG, V348, P108, DOI 10.1016/j.foreco.2015.03.019
   Hajek P, 2014, TREE PHYSIOL, V34, P744, DOI 10.1093/treephys/tpu048
   HALLE F, 1978, P441
   Hatton TJ, 1997, FUNCT ECOL, V11, P665, DOI 10.1046/j.1365-2435.1997.00159.x
   Hegyi F., 1974, GROWTH MODELS TREE S, P74
   Herbette S, 2010, TREE PHYSIOL, V30, P1448, DOI 10.1093/treephys/tpq079
   Jansen S, 2009, AM J BOT, V96, P409, DOI 10.3732/ajb.0800248
   Jump AS, 2007, MOL ECOL, V16, P925, DOI 10.1111/j.1365-294X.2006.03203.x
   Kaack L, 2021, NEW PHYTOL, V230, P1829, DOI 10.1111/nph.17282
   Kirfel K, 2017, FRONT PLANT SCI, V8, DOI 10.3389/fpls.2017.01194
   Kuznetsova A, 2017, J STAT SOFTW, V82, P1, DOI 10.18637/jss.v082.i13
   Lachenbruch B, 2011, TREE PHYSIOL-NETH, V4, P121, DOI 10.1007/978-94-007-1242-3_5
   LAMBERS H, 2019, PLANT PHYSIOLOGICAL, P1
   Leal S, 2007, WOOD SCI TECHNOL, V41, P339, DOI 10.1007/s00226-006-0112-7
   Lechthaler S, 2019, TREE PHYSIOL, V39, P495, DOI 10.1093/treephys/tpy110
   Lemaire C., 2020, BIORXIV, V2020
   Lens F, 2011, NEW PHYTOL, V190, P709, DOI 10.1111/j.1469-8137.2010.03518.x
   Leuschner C, 2020, PERSPECT PLANT ECOL, V47, DOI 10.1016/j.ppees.2020.125576
   LEWIS AM, 1995, AM J BOT, V82, P1112, DOI 10.2307/2446063
   Li S, 2019, FORESTS, V10, DOI 10.3390/f10080662
   Li S, 2016, IAWA J, V37, P152, DOI 10.1163/22941932-20160128
   Liang XY, 2019, AGR FOREST METEOROL, V271, P83, DOI 10.1016/j.agrformet.2019.02.043
   Link R.M., 2020, corrmorant: Flexible Correlation Matrices Based on 'ggplot2'. R package version 0.0.0.9007
   Liu H, 2019, SCI ADV, V5, DOI 10.1126/sciadv.aav1332
   Loepfe L, 2007, J THEOR BIOL, V247, P788, DOI 10.1016/j.jtbi.2007.03.036
   Lübbe T, 2017, TREE PHYSIOL, V37, P456, DOI 10.1093/treephys/tpw095
   Maherali H, 2004, ECOLOGY, V85, P2184, DOI 10.1890/02-0538
   Martínez-Vilalta J, 2009, NEW PHYTOL, V184, P353, DOI 10.1111/j.1469-8137.2009.02954.x
   Nakagawa S, 2017, J R SOC INTERFACE, V14, DOI 10.1098/rsif.2017.0213
   Nonweiler T., 1975, Encyclopedia of Plant Physiology, P474
   Ogasa M, 2013, TREE PHYSIOL, V33, P335, DOI 10.1093/treephys/tpt010
   Olson M, 2020, ECOL MONOGR, V90, DOI 10.1002/ecm.1410
   Olson ME, 2021, NEW PHYTOL, V229, P1877, DOI 10.1111/nph.16961
   Olson ME, 2018, P NATL ACAD SCI USA, V115, P7551, DOI 10.1073/pnas.1721728115
   Olson ME, 2014, ECOL LETT, V17, P988, DOI 10.1111/ele.12302
   Petit G, 2018, NEW PHYTOL, V218, P1383, DOI 10.1111/nph.15118
   Petit G, 2010, NEW PHYTOL, V187, P1146, DOI 10.1111/j.1469-8137.2010.03304.x
   Pfautsch S, 2016, ECOL LETT, V19, P240, DOI 10.1111/ele.12559
   Piedallu C, 2013, GLOBAL ECOL BIOGEOGR, V22, P470, DOI 10.1111/geb.12012
   R Core Team, 2022, R: A Language and Environment for Statistical Computing
   Rodriguez-Zaccaro FD, 2019, PLANT CELL ENVIRON, V42, P1816, DOI 10.1111/pce.13528
   Rosell JA, 2017, CURR FOR REP, V3, P46, DOI 10.1007/s40725-017-0049-0
   SASS U, 1995, TREES-STRUCT FUNCT, V9, P247, DOI 10.1007/BF00202014
   Schaap MG, 2001, J HYDROL, V251, P163, DOI 10.1016/S0022-1694(01)00466-8
   Schreiber SG, 2015, FUNCT ECOL, V29, P1392, DOI 10.1111/1365-2435.12455
   Schuldt B, 2020, BASIC APPL ECOL, V45, P86, DOI 10.1016/j.baae.2020.04.003
   Schuldt B, 2016, NEW PHYTOL, V210, P443, DOI 10.1111/nph.13798
   Schumann K, 2019, TREES-STRUCT FUNCT, V33, P1475, DOI 10.1007/s00468-019-01874-x
   SPERRY JS, 1994, ECOLOGY, V75, P1736, DOI 10.2307/1939633
   Stojnic S, 2018, TREE PHYSIOL, V38, P173, DOI 10.1093/treephys/tpx128
   Van Genuchten M.T., 1991, Environmental Protection Agency. EPA/600/2-91/065
   VANGENUCHTEN MT, 1980, SOIL SCI SOC AM J, V44, P892, DOI 10.2136/sssaj1980.03615995004400050002x
   von Arx G, 2014, DENDROCHRONOLOGIA, V32, P290, DOI 10.1016/j.dendro.2013.12.001
   Walthert L, 2021, SCI TOTAL ENVIRON, V753, DOI 10.1016/j.scitotenv.2020.141792
   Weithmann G, 2022, OECOLOGIA, V198, P629, DOI 10.1007/s00442-022-05124-9
   West GB, 1999, NATURE, V400, P664, DOI 10.1038/23251
   WHEELER EA, 1993, PALEOBIOLOGY, V19, P487, DOI 10.1017/S009483730001410X
   Wickham H., 2019, JOSS, V4, DOI [DOI 10.21105/JOSS.01686, 10.21105/joss.01686., 10.21105/joss.01686]
   Wiemann MC, 1998, PALAEOGEOGR PALAEOCL, V139, P83, DOI 10.1016/S0031-0182(97)00100-4
   Woodruff DR, 2004, PLANT CELL ENVIRON, V27, P229, DOI 10.1111/j.1365-3040.2003.01141.x
   Wortemann R, 2011, TREE PHYSIOL, V31, P1175, DOI 10.1093/treephys/tpr101
   Zhao XP, 2015, J FOREST RES-JPN, V20, P175, DOI 10.1007/s10310-014-0458-x
   Zimmermann J, 2021, TREES-STRUCT FUNCT, V35, P919, DOI 10.1007/s00468-021-02090-2
   Zimmermann M. H., 1983, Xylem structure and the ascent of sap.
NR 90
TC 9
Z9 9
U1 10
U2 63
PU OXFORD UNIV PRESS
PI OXFORD
PA GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND
SN 0829-318X
EI 1758-4469
J9 TREE PHYSIOL
JI Tree Physiol.
PD NOV 8
PY 2022
VL 42
IS 11
BP 2224
EP 2238
DI 10.1093/treephys/tpac080
EA AUG 2022
PG 15
WC Forestry
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Forestry
GA 6C5ON
UT WOS:000847759200001
PM 35861677
DA 2025-01-10
ER

PT J
AU Durbin, HJ
   Lu, D
   Yampara-Iquise, H
   Miller, SP
   Decker, JE
AF Durbin, Harly J.
   Lu, Duc
   Yampara-Iquise, Helen
   Miller, Stephen P.
   Decker, Jared E.
TI Development of a genetic evaluation for hair shedding in American Angus
   cattle to improve thermotolerance
SO GENETICS SELECTION EVOLUTION
LA English
DT Article
ID DEER CERVUS-ELAPHUS; BEEF-CATTLE; HEAT-STRESS; TALL FESCUE; PERFORMANCE;
   LACTATION; GROWTH; COWS; MECHANISMS; ERGOVALINE
AB Background Heat stress and fescue toxicosis caused by ingesting tall fescue infected with the endophytic fungusEpichloe coenophialarepresent two of the most prevalent stressors to beef cattle in the United States and cost the beef industry millions of dollars each year. The rate at which a beef cow sheds her winter coat early in the summer is an indicator of adaptation to heat and an economically relevant trait in temperate or subtropical parts of the world. Furthermore, research suggests that early-summer hair shedding may reflect tolerance to fescue toxicosis, since vasoconstriction induced by fescue toxicosis limits the ability of an animal to shed its winter coat. Both heat stress and fescue toxicosis reduce profitability partly via indirect maternal effects on calf weaning weight. Here, we developed parameters for routine genetic evaluation of hair shedding score in American Angus cattle, and identified genomic loci associated with variation in hair shedding score via genome-wide association analysis (GWAA). Results Hair shedding score was moderately heritable (h(2) = 0.34 to 0.40), with different repeatability estimates between cattle grazing versus not grazing endophyte-infected tall fescue. Our results suggest modestly negative genetic and phenotypic correlations between a dam's hair shedding score (lower score is earlier shedding) and the weaning weight of her calf, which is one metric of performance. Together, these results indicate that economic gains can be made by using hair shedding score breeding values to select for heat-tolerant cattle. GWAA identified 176 variants significant at FDR < 0.05. Functional enrichment analyses using genes that were located within 50 kb of these variants identified pathways involved in keratin formation, prolactin signalling, host-virus interaction, and other biological processes. Conclusions This work contributes to a continuing trend in the development of genetic evaluations for environmental adaptation. Our results will aid beef cattle producers in selecting more sustainable and climate-adapted cattle, as well as enable the development of similar routine genetic evaluations in other breeds.
C1 [Durbin, Harly J.; Yampara-Iquise, Helen; Decker, Jared E.] Univ Missouri, Columbia, MO 65211 USA.
   [Lu, Duc; Miller, Stephen P.] Angus Genet Inc, St Joseph, MO 64506 USA.
C3 University of Missouri System; University of Missouri Columbia
RP Decker, JE (corresponding author), Univ Missouri, Columbia, MO 65211 USA.
EM DeckerJE@missouri.edu
RI Decker, Jared/H-2730-2019
OI Miller, Stephen/0000-0001-5273-352X; Rowan, Harly/0000-0001-6400-368X
FU Agriculture and Food Research Initiative Competitive from the USDA
   National Institute of Food and Agriculture [2016-68004-24827]; Angus
   Genetics Inc.; American Angus Association Foundation
FX This project was supported by Agriculture and Food Research Initiative
   Competitive Grant no. 2016-68004-24827 from the USDA National Institute
   of Food and Agriculture. HJD was supported as an intern through funding
   from Angus Genetics Inc. The American Angus Association Foundation
   supported North Carolina State University and Mississippi State
   University in collection of the AGI dataset.
CR Aguilar I, 2011, J ANIM BREED GENET, V128, P422, DOI 10.1111/j.1439-0388.2010.00912.x
   Aiken G. E., 2011, Professional Animal Scientist, V27, P336
   AZZAM SM, 1990, J ANIM SCI, V68, P5
   BAUMAN DE, 1980, J DAIRY SCI, V63, P1514, DOI 10.3168/jds.S0022-0302(80)83111-0
   Baumgard LH, 2017, J DAIRY SCI, V100, P10353, DOI 10.3168/jds.2017-13242
   Baumgard L. H., 2015, Revista Brasileira de Reproducao Animal, V39, P173
   Beltran RS, 2018, P ROY SOC B-BIOL SCI, V285, DOI 10.1098/rspb.2018.0318
   Berry I.L., 1964, T ASABE, V7, P329, DOI [10.13031/2013.40772, DOI 10.13031/2013.40772]
   Bindea G, 2009, BIOINFORMATICS, V25, P1091, DOI 10.1093/bioinformatics/btp101
   Bradford HL, 2016, J ANIM SCI, V94, P4143, DOI 10.2527/jas.2016-0707
   Burnight ER, 2014, GENE THER, V21, P662, DOI 10.1038/gt.2014.39
   Cannon ME, 2018, AM J HUM GENET, V103, P637, DOI 10.1016/j.ajhg.2018.10.001
   Carabaño MJ, 2019, ANIM FRONT, V9, P62, DOI 10.1093/af/vfy033
   Carvalheiro R, 2019, GENET SEL EVOL, V51, DOI 10.1186/s12711-019-0470-x
   CLAY K, 1988, ECOLOGY, V69, P10, DOI 10.2307/1943155
   Coppieters F, 2010, HUM MUTAT, V31, P1097, DOI 10.1002/humu.21337
   Cundiff LV, 2018, 9 BEEF IMPR FED
   Déry F, 2019, ECOL EVOL, V9, P2920, DOI 10.1002/ece3.4970
   Dikmen S, 2014, J DAIRY SCI, V97, P5508, DOI 10.3168/jds.2014-8087
   Falconer D. S., 1996, INTRO QUANTITATIVE G, P464
   FALCONER DS, 1952, AM NAT, V86, P293, DOI 10.1086/281736
   Freetly HC, 2006, J ANIM SCI, V84, P2157, DOI 10.2527/jas.2005-534
   FRIBOURG HA, 1991, AGRON J, V83, P777, DOI 10.2134/agronj1991.00021962008300050001x
   Gray KA, 2011, LIVEST SCI, V140, P68, DOI 10.1016/j.livsci.2011.02.009
   Guerre P, 2015, TOXINS, V7, P773, DOI 10.3390/toxins7030773
   Habvey N. E., 1958, Australian Journal of Biological Sciences, V11, P187
   Hazlerigg DG, 2006, TRENDS ENDOCRIN MET, V17, P83, DOI 10.1016/j.tem.2006.02.004
   HEYDON MJ, 1995, J EXP ZOOL, V273, P12, DOI 10.1002/jez.1402730103
   Hoff JL, 2019, BMC GENOMICS, V20, DOI 10.1186/s12864-019-5941-5
   Hoveland CS, 2009, AGRONOMY MONOGRAPHS, P1
   KAY RNB, 1978, J ZOOL, V185, P505
   Klotz JL, 2009, J ANIM SCI, V87, P2437, DOI 10.2527/jas.2008-1692
   Koltes JE, 2018, TRANSL ANIM SCI, V2, P319, DOI 10.1093/tas/txy061
   Lee C, 1998, ASIAN AUSTRAL J ANIM, V11, P441, DOI 10.5713/ajas.1998.441
   Lee C, 2002, ASIAN AUSTRAL J ANIM, V15, P1222, DOI 10.5713/ajas.2002.1222
   Lee C, 2002, J ANIM SCI, V80, P316
   Legarra A, 2018, GENET SEL EVOL, V50, DOI 10.1186/s12711-018-0426-6
   Littlejohn MD, 2014, NAT COMMUN, V5, DOI 10.1038/ncomms6861
   Matika O, 2013, ANIM GENET, V44, P742, DOI 10.1111/age.12070
   MEYER K, 1995, LIVEST PROD SCI, V44, P125, DOI 10.1016/0301-6226(95)00067-4
   Miller SP, 1999, J ANIM SCI, V77, P1155
   Misztal I, 2014, BLUPF90 FAMILY PROGR
   NAY T, 1954, AUST J BIOL SCI, V7, P361, DOI 10.1071/BI9540361
   Neibergs HL, 2014, BMC GENOMICS, V15, DOI 10.1186/1471-2164-15-1164
   Pauling RC, 2018, J ANIM SCI, V96, P3599, DOI 10.1093/jas/sky262
   Peirson SN, 2018, J NEUROSCI METH, V300, P26, DOI 10.1016/j.jneumeth.2017.04.007
   PETERS CW, 1992, J ANIM SCI, V70, P1550, DOI 10.2527/1992.7051550x
   Rhoads ML, 2009, J DAIRY SCI, V92, P1986, DOI 10.3168/jds.2008-1641
   Robinson TP, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0096084
   Rowan TN, 2020, BIORXIV, DOI [10.1101/2020.03.11.988121, DOI 10.1101/2020.03.11.988121]
   Rowan TN, 2019, GENET SEL EVOL, V51, DOI 10.1186/s12711-019-0519-x
   RYDER ML, 1966, ANIM PROD, V8, P289, DOI 10.1017/S000335610003467X
   Santana ML, 2013, ANIMAL, V7, P202, DOI 10.1017/S1751731112001711
   Sargolazei M., 2014, SNP1101 Users Guide Version 1.0
   Sargolzaei M, 2014, BMC GENOMICS, V15, DOI 10.1186/1471-2164-15-478
   SCHONS D, 1985, J ANIM SCI, V61, P44, DOI 10.2527/jas1985.61144x
   Smith JL, 2019, BMC GENOMICS, V20, DOI 10.1186/s12864-019-6231-y
   St-Pierre NR, 2003, J DAIRY SCI, V86, pE52, DOI 10.3168/jds.S0022-0302(03)74040-5
   STRICKLAND JR, 1993, VET HUM TOXICOL, V35, P454
   Strickland JR, 1996, J ANIM SCI, V74, P1664
   Szklarczyk D, 2015, NUCLEIC ACIDS RES, V43, pD447, DOI 10.1093/nar/gku1003
   TURNER H. G., 1960, AUSTRALIAN JOUR AGRIC RES, V11, P645, DOI 10.1071/AR9600645
   VanRaden PM, 2008, J DAIRY SCI, V91, P4414, DOI 10.3168/jds.2007-0980
   YEATES N. T. M., 1955, AUSTRALIAN JOUR AGRIC RES, V6, P891, DOI 10.1071/AR9550891
   Zhang Y, 2014, HUM MOL GENET, V23, P40, DOI 10.1093/hmg/ddt394
   Zimin AV, 2009, GENOME BIOL, V10, DOI 10.1186/gb-2009-10-4-r42
NR 66
TC 13
Z9 18
U1 0
U2 6
PU BMC
PI LONDON
PA CAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND
SN 0999-193X
EI 1297-9686
J9 GENET SEL EVOL
JI Genet. Sel. Evol.
PD OCT 21
PY 2020
VL 52
IS 1
AR 63
DI 10.1186/s12711-020-00584-0
PG 14
WC Agriculture, Dairy & Animal Science; Genetics & Heredity
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Genetics & Heredity
GA OE5MJ
UT WOS:000580574000001
PM 33087048
OA gold, Green Published
DA 2025-01-10
ER

PT J
AU Thorne, JH
   Choe, H
   Boynton, RM
   Lee, DK
AF Thorne, James H.
   Choe, Hyeyeong
   Boynton, Ryan M.
   Lee, Dong Kun
TI Open space networks can guide urban renewal in a megacity
SO ENVIRONMENTAL RESEARCH LETTERS
LA English
DT Article
DE urban renewal; megacity; open space networks; connectivity; urban green
   area; street tree; urban park; redevelopment; Omniscape
ID GREEN-SPACE; HEAT-ISLAND; CHALLENGES; HEALTH; CITIES; INFRASTRUCTURE;
   TEMPERATURE; RESILIENCE; FRAMEWORK; ECOLOGY
AB As human populations move into cities they are increasingly isolated from the natural world, with associated negative impacts on health and well-being. However, as cities renew themselves through urban redevelopment and climate-adaptation, opportunities arise to improve people's access to urban green areas that can be informed by modeling the network of urban open spaces. Recent research identified the need for multi-criteria indices of access to urban green spaces. Including open spaces such as empty lots, ground- and air-spaces surrounding buildings, and spaces associated with roads and other linear features can improve planning for urban greenspaces by identifying areas of opportunity for additional greening. Further, the gradient of interconnections among open spaces can be used to prioritize urban greening locations to build green networks. We modelled all open-space connections across 605 km(2)in Seoul, population 10.3 million, using Omniscape, a landscape connectivity model. We combined the resulting open-space connectivity map with distance-based indices for existing urban parks and street trees. Combining these criteria permits rank-prioritization of locations where new green spaces would most improve residents' access. We found 2910 of 3375 (86.2%) locations where urban green spaces already exist within 300 m for city residents. Of the remaining 465 locations, 276 are in areas with the lowest-open space connections. For urban street trees, 44.3% of the 2588 km of the city's major roads are already planted with street trees. Of the remainder, 210 km (8.1%) are located in the areas with the least connections to green spaces. Nine new urban parks would provide relief for the most highly-impacted areas, where the flow of open space is lowest and where no green spaces are available within 300 m. The integration of a spatial model typically used for conservation assessments with city planning provides useful additional context for building urban health.
C1 [Thorne, James H.; Boynton, Ryan M.] Univ Calif Davis, Dept Environm Sci & Policy, Davis, CA 95616 USA.
   [Choe, Hyeyeong] Kangwon Natl Univ, Dept Ecol Landscape Architecture Design, Chunchon 24341, South Korea.
   [Boynton, Ryan M.; Lee, Dong Kun] Seoul Natl Univ, Coll Agr & Life Sci, Dept Landscape Architecture, Seoul 08826, South Korea.
C3 University of California System; University of California Davis; Kangwon
   National University; Seoul National University (SNU)
RP Choe, H (corresponding author), Kangwon Natl Univ, Dept Ecol Landscape Architecture Design, Chunchon 24341, South Korea.
EM jhthorne@ucdavis.edu; hychoe@kangwon.ac.kr
OI Choe, Hyeyeong/0000-0003-2130-1622; Boynton, Ryan/0000-0002-3952-2573
FU National Research Foundation of Korea (NRF) - Korean government (MSIT)
   [2019R1G1A1005770]
FX The authors thank Dr Brad McRae and Dr Carrie Schloss at The Nature
   Conservancy for use of their codes. We also thank two anonymous referees
   for constructive comments on the initial manuscript. This work was
   supported by the National Research Foundation of Korea (NRF) grant
   funded by the Korean government (MSIT) (No. 2019R1G1A1005770).
CR Ahern J, 2013, LANDSCAPE ECOL, V28, P1203, DOI 10.1007/s10980-012-9799-z
   [Anonymous], 2019, ArcGIS Desktop: Release 10.8
   Aronson MFJ, 2017, FRONT ECOL ENVIRON, V15, P189, DOI 10.1002/fee.1480
   Bowler DE, 2010, LANDSCAPE URBAN PLAN, V97, P147, DOI 10.1016/j.landurbplan.2010.05.006
   Childers DL, 2015, SUSTAINABILITY-BASEL, V7, P3774, DOI 10.3390/su7043774
   Choe H, 2019, LANDSC ECOL ENG, V15, P245, DOI 10.1007/s11355-019-00377-8
   Choe H, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0190754
   Choe H, 2017, J APPL ECOL, V54, P1742, DOI 10.1111/1365-2664.12865
   Choe H, 2017, FORESTS, V8, DOI 10.3390/f8090321
   Dickson BG, 2019, CONSERV BIOL, V33, P239, DOI 10.1111/cobi.13230
   Du YX, 2018, SUSTAIN CITIES SOC, V42, P314, DOI 10.1016/j.scs.2018.08.001
   Ekkel ED, 2017, LANDSCAPE URBAN PLAN, V157, P214, DOI 10.1016/j.landurbplan.2016.06.008
   Estoque RC, 2017, SCI TOTAL ENVIRON, V577, P349, DOI 10.1016/j.scitotenv.2016.10.195
   Fintikakis N, 2011, SUSTAIN CITIES SOC, V1, P54, DOI 10.1016/j.scs.2010.12.001
   Frank LD, 2010, BRIT J SPORT MED, V44, P924, DOI 10.1136/bjsm.2009.058701
   Georgescu M, 2014, P NATL ACAD SCI USA, V111, P2909, DOI 10.1073/pnas.1322280111
   Giacomoni MH, 2017, J WATER RES PLAN MAN, V143, DOI 10.1061/(ASCE)WR.1943-5452.0000812
   Google, 2018, DIGITALGLOBE
   Gu M, 2004, J WIND ENG IND AEROD, V92, P1147, DOI 10.1016/j.jweia.2004.06.004
   Haaland C, 2015, URBAN FOR URBAN GREE, V14, P760, DOI 10.1016/j.ufug.2015.07.009
   Han YW, 2019, URBAN FOR URBAN GREE, V41, P354, DOI 10.1016/j.ufug.2019.04.015
   Hobbie SE, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0124
   James Peter, 2015, Curr Epidemiol Rep, V2, P131
   Kang W, 2019, ENVIRON MONIT ASSESS, V191, DOI 10.1007/s10661-019-7520-2
   Keeley ATH, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aacb85
   Kim G, 2018, SUSTAIN CITIES SOC, V36, P144, DOI 10.1016/j.scs.2017.09.014
   Korea National Park Service, 2020, NUMB VIS NAT PARKS E
   Lee ACK, 2011, J PUBLIC HEALTH-UK, V33, P212, DOI 10.1093/pubmed/fdq068
   Lee D, 2011, J URBAN PLAN D-ASCE, V137, P425, DOI 10.1061/(ASCE)UP.1943-5444.0000090
   Li JK, 2017, WATER RESOUR MANAG, V31, P4745, DOI 10.1007/s11269-017-1776-5
   Littlefield CE, 2017, CONSERV BIOL, V31, P1397, DOI 10.1111/cobi.12938
   Liu JG, 2015, SCIENCE, V347, DOI 10.1126/science.1258832
   McRae B., 2016, CONSERVING NATURES S
   McRae B. H., 2013, Circuitscape 4 User Guide
   Ministry of the Interior and Safety, 2019, NAT STAND NOD LINK
   Mullaney J, 2015, LANDSCAPE URBAN PLAN, V134, P157, DOI 10.1016/j.landurbplan.2014.10.013
   Nielsen TS, 2007, HEALTH PLACE, V13, P839, DOI 10.1016/j.healthplace.2007.02.001
   Norton BA, 2015, LANDSCAPE URBAN PLAN, V134, P127, DOI 10.1016/j.landurbplan.2014.10.018
   Park CY, 2020, SCI TOTAL ENVIRON, V698, DOI 10.1016/j.scitotenv.2019.134259
   Park CY, 2018, BUILD ENVIRON, V141, P298, DOI 10.1016/j.buildenv.2018.05.058
   Park JH, 2017, SUSTAINABILITY-BASEL, V9, DOI 10.3390/su9020185
   Plastrik P., 2018, LIFE CARBON NEXT GLO
   Reklaitiene R, 2014, SCAND J PUBLIC HEALT, V42, P669, DOI 10.1177/1403494814544494
   Rovai M, 2014, ADV ENG FORUM, V11, P338, DOI 10.4028/www.scientific.net/AEF.11.338
   Seoul Metropolitan Council, 2015, PARKS VIS US SAT SUR
   Seoul Metropolitan Government, 2012, SEOUL STREET TREES I
   Seoul Metropolitan Government, 2015, SEOUL BIOT MAP
   Seoul Metropolitan Government, 2018, SEOUL STAT YB
   South Korean Ministry of Environment, 2016, DEV LAND COV MAP 7 I
   Thacker S, 2019, NAT SUSTAIN, V2, P324, DOI 10.1038/s41893-019-0256-8
   Thompson CW, 2012, LANDSCAPE URBAN PLAN, V105, P221, DOI 10.1016/j.landurbplan.2011.12.015
   TIAN YH, 2017, SUSTAINABILITY-BASEL, V9, DOI DOI 10.3390/su9091653
   Triguero-Mas M, 2015, ENVIRON INT, V77, P35, DOI 10.1016/j.envint.2015.01.012
   United Nations (UN), 2013, SUST DEV CHANG WORLD
   Yang CB, 2017, FORESTS, V8, DOI 10.3390/f8050153
   Yoon EJ, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/aaf0cf
   Zhang YJ, 2017, LANDSCAPE URBAN PLAN, V165, P162, DOI 10.1016/j.landurbplan.2017.04.009
NR 57
TC 14
Z9 15
U1 18
U2 131
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 SEP
PY 2020
VL 15
IS 9
AR 094080
DI 10.1088/1748-9326/ab9fad
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 NQ2SC
UT WOS:000570714200001
OA gold
DA 2025-01-10
ER

PT J
AU Aparecido, LED
   de Moraes, JRDC
   Rolim, GD
   Martorano, LG
   Soares, SD
   de Meneses, KC
   Costa, CTS
   Mesquita, DZ
   Barbosa, AMD
   do Amaral, EF
   Bardales, NG
AF de Oliveira Aparecido, Lucas Eduardo
   da Silva Cabral de Moraes, Jose Reinaldo
   Rolim, Glauco de Souza
   Martorano, Lucieta Guerreiro
   Soares, Sabrina dos Santos
   de Meneses, Kamila Cunha
   Silva Costa, Cicero Teixeira
   Mesquita, Daniel Zimmermann
   da Silva Barbosa, Aline Michelle
   do Amaral, Eufran Ferreira
   Bardales, Nilson Gomes
TI Neural networks in spatialization of meteorological elements and their
   application in the climatic agricultural zoning of bamboo
SO INTERNATIONAL JOURNAL OF BIOMETEOROLOGY
LA English
DT Article
DE Modeling; Crop zoning; Multilayer perceptron; Training algorithm;
   Climatology
ID PHYLLOSTACHYS-EDULIS; FORESTS
AB Bamboo has an important role in international commerce due to its diverse uses, but few studies have been conducted to evaluate its climatic adaptability. Thus, the objective of this study was to construct an agricultural zoning for climate risk (ZARC) for bamboo using meteorological elements spatialized by neural networks. Climate data included air temperature (T-AIR, degrees C) and rainfall (P) from 4947 meteorological stations in Brazil from the years 1950 to 2016. Regions were considered climatically apt for bamboo cultivation when T-AIR varied between 18 and 35 degrees C, and P was between 500 and 2800 mm year(-1), or P-WINTER was between 90 and 180 mm year(-1). The remainder of the areas was considered marginal or inapt for bamboo cultivation. A multilayer perceptron (MLP) neural network with a multilayered backpropagation training algorithm was used to spatialize the territorial variability of each climatic element for the whole area of Brazil. Using the overlapping of the T-AIR, P, and P-WINTER maps prepared by MLP, and the established climatic criteria of bamboo, we established the agricultural zoning for bamboo. Brazil demonstrates high seasonal climatic variability with T-AIR varying between 14 and 30 degrees C, and P varying between < 400 and 4000 mm year(-1). The ZARC showed that 87% of Brazil is climatically apt for bamboo cultivation. The states that were classified as apt in 100% of their territories were Mato Grosso do Sul, Goias, Tocantins, Rio de Janeiro, Espirito Santo, Sergipe, Alagoas, Ceara, Piaui, MaranhAo, Rondonia, and Acre. The regions that have restrictions due to low T-AIR represent just 11% of Brazilian territory. This agroclimatic zoning allowed for the classification of regions based on aptitude of climate for bamboo cultivation and showed that 71% of the total national territory is considered to be apt for bamboo cultivation. The regions that have restrictions are part of southern Brazil due to low values of T-AIR and portions of the northern region that have high levels of P which is favorable for the development of diseases.
C1 [de Oliveira Aparecido, Lucas Eduardo; da Silva Cabral de Moraes, Jose Reinaldo; Soares, Sabrina dos Santos; Silva Costa, Cicero Teixeira; Mesquita, Daniel Zimmermann] Fed Inst Educ Sci & Technol Mato Grosso Sul, Campus Navirai, Navirai, MS, Brazil.
   [Rolim, Glauco de Souza; de Meneses, Kamila Cunha; da Silva Barbosa, Aline Michelle] Sao Paulo State Univ, Dept Exact Sci, BR-14884900 Jaboticabal, SP, Brazil.
   [Martorano, Lucieta Guerreiro; do Amaral, Eufran Ferreira; Bardales, Nilson Gomes] Embrapa Eastern Amazon, Trav Dr Eneas Pinheiro S-N, Belem, Para, Brazil.
C3 Universidade Estadual Paulista; Empresa Brasileira de Pesquisa
   Agropecuaria (EMBRAPA)
RP Aparecido, LED (corresponding author), Fed Inst Educ Sci & Technol Mato Grosso Sul, Campus Navirai, Navirai, MS, Brazil.
EM lucas-aparecido@outlook.com
RI DE OLIVEIRA APARECIDO, LUCAS/Y-3502-2019; de Meneses,
   Kamila/AAK-9546-2020; Martorano, Lucieta/O-4719-2018; Aparecido, Lucas
   Eduardo de Oliveira/N-4883-2015; Moraes, Jose Reinaldo da Silva Cabral
   de/T-9508-2017
OI Barbosa, Aline Michelle da Silva/0000-0001-8336-2645; Aparecido, Lucas
   Eduardo de Oliveira/0000-0002-4561-6760; Moraes, Jose Reinaldo da Silva
   Cabral de/0000-0002-8567-4893; Cunha de Meneses,
   Kamila/0000-0001-9200-5260
CR Alvares CA, 2013, METEOROL Z, V22, P711, DOI 10.1127/0941-2948/2013/0507
   Angelocci L. R., 2002, AGROMETEOROLOGIA FUN
   [Anonymous], 2010, J BAMBOO RES, DOI DOI 10.3969/J.ISSN.1000-6567.2010.01.004
   Basumatary A, 2018, J FORESTRY RES, V29, P1379, DOI 10.1007/s11676-017-0535-z
   Camargo A. P. de, 2000, Bragantia, V59, P125, DOI 10.1590/S0006-87052000000200002
   Chen SL, 2018, FOREST ECOL MANAG, V409, P1, DOI 10.1016/j.foreco.2017.11.008
   de Oliveira AS, 2012, REV BRAS ENG AGR AMB, V16, P1223, DOI 10.1590/S1415-43662012001100011
   Aparecido LED, 2018, BRAGANTIA, V77, P193, DOI 10.1590/1678-4499.2016527
   Aparecido LED, 2018, J SCI FOOD AGR, V98, P1280, DOI 10.1002/jsfa.8575
   Santos DRD, 2016, SCI FOR, V44, P751, DOI 10.18671/scifor.v44n111.21
   FAO, 2010, Global Forest Resource Assessment Report: Country Report Uganda
   Felisberto MHF, 2017, FOOD RES INT, V101, P96, DOI 10.1016/j.foodres.2017.08.058
   Fu J., 2001, Bamboo, V22, P5
   Gelcer E, 2018, AGR FOREST METEOROL, V248, P316, DOI 10.1016/j.agrformet.2017.10.002
   IPCC, 2018, GLOB WARM 1 5C SUMM
   Jin Jia-Xin, 2013, Chinese Journal of Plant Ecology, V37, P631, DOI 10.3724/SP.J.1258.2013.00065
   Martins E., 2015, Coffee Science, V10, P499
   Pereira MA, 2016, CANAL16
   Song XZ, 2017, AGR FOREST METEOROL, V247, P467, DOI 10.1016/j.agrformet.2017.09.001
   Song ZL, 2018, SCI TOTAL ENVIRON, V615, P1, DOI 10.1016/j.scitotenv.2017.09.253
   Taiz L., 2009, Plant Physiology, V5th
   Takano KT, 2017, ECOL EVOL, V7, P9848, DOI 10.1002/ece3.3471
   Xu L, 2017, FORESTS, V8, DOI 10.3390/f8100371
NR 23
TC 2
Z9 3
U1 0
U2 15
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 0020-7128
EI 1432-1254
J9 INT J BIOMETEOROL
JI Int. J. Biometeorol.
PD NOV
PY 2018
VL 62
IS 11
BP 1955
EP 1962
DI 10.1007/s00484-018-1596-1
PG 8
WC Biophysics; Environmental Sciences; Meteorology & Atmospheric Sciences;
   Physiology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Biophysics; Environmental Sciences & Ecology; Meteorology & Atmospheric
   Sciences; Physiology
GA GV5WP
UT WOS:000446176400003
PM 30121896
DA 2025-01-10
ER

PT J
AU Sida, TS
   Baudron, F
   Kim, H
   Giller, KE
AF Sida, Tesfaye Shiferaw
   Baudron, Frederic
   Kim, Haekoo
   Giller, Ken E.
TI Climate-smart agroforestry: <i>Faidherbia albida</i> trees buffer wheat
   against climatic extremes in the Central Rift Valley of Ethiopia
SO AGRICULTURAL AND FOREST METEOROLOGY
LA English
DT Article
DE Climate change; Local adaptation; Competition; Facilitation; Heat
   stress; Crop physiology
ID PARKLAND SYSTEM; USE EFFICIENCY; CROP YIELD; WATER; MILLET; VARIABILITY;
   CHALLENGES; SAHEL; LIGHT
AB Faidherbia albida parklands cover a large area of the Sudano-Sahelian zone of Africa, a region that suffers from soil fertility decline, food insecurity and climate change. The parklands deliver multiple benefits, including fuelwood, soil nutrient replenishment, moisture conservation, and improved crop yield underneath the canopy. Its microclimate modification may provide an affordable climate adaptation strategy which needs to be explored. We carried out an on-farm experiment for three consecutive seasons in the Ethiopian Central Rift Valley with treatments of Faidherbia trees with bare soil underneath, wheat grown beneath Faidherbia and wheat grown in open fields. We tested the sensitivity of wheat yield to tree-mediated variables of photosynthetically active radiation (PAR), air temperature and soil nitrogen, using APSIM-wheat model. Results showed that soil moisture in the sub-soil was the least for wheat with tree, intermediate for sole tree and the highest for open field. Presence of trees resulted in 35-55% larger available N close to tree crowns compared with sole wheat. Trees significantly reduced PAR reaching the canopy of wheat growing underneath to optimum levels. Midday air temperature was about 6 degrees C less under the trees than in the open fields. LAI, number of grains spike(-1), plant height, total aboveground biomass and wheat grain yield were all significantly higher (P < 0.001) for wheat associated with F. albida compared with sole wheat. Model-based sensitivity analysis showed that under moderate to high rates of N, wheat yield responded positively to a decrease in temperature caused by F. albida shade. Thus, F. albida trees increase soil mineral N, wheat water use efficiency and reduce heat stress, increasing yield significantly. With heat and moisture stress likely to be more prevalent in the face of climate change, F. albida, with its impact on microclimate modification, maybe a starting point to design more resilient and climate-smart farming systems.
C1 [Sida, Tesfaye Shiferaw; Kim, Haekoo] Int Maize & Wheat Improvement Ctr CIMMYT Ethiopia, ILRI, Shola Campus,POB 5689, Addis Ababa, Ethiopia.
   [Baudron, Frederic] Int Maize & Wheat Improvement Ctr CIMMYT, Southern Africa Reg Off, POB MP 163,12-5 Km Peg Mazowe Rd, Harare, Zimbabwe.
   [Sida, Tesfaye Shiferaw; Giller, Ken E.] Wageningen Univ, Plant Prod Syst, POB 430, NL-6700 AK Wageningen, Netherlands.
C3 CGIAR; International Livestock Research Institute (ILRI); International
   Maize & Wheat Improvement Center (CIMMYT); Wageningen University &
   Research
RP Sida, TS (corresponding author), Wageningen Univ, Plant Prod Syst, POB 430, NL-6700 AK Wageningen, Netherlands.
EM tesfaye.sida@wur.nl
RI Sida, Tesfaye/R-9651-2019; Giller, Ken/K-2799-2012; Sida, Tesfaye
   Shiferaw/H-4643-2014
OI Baudron, Frederic/0000-0002-5648-2083; Sida, Tesfaye
   Shiferaw/0000-0001-6482-2669
FU Australian Centre for International Agricultural Research (ACIAR)
   [FSC/2012/014]; CRP WHEAT
FX This work was implemented by CIMMYT and Wageningen University as part of
   the project 'Trees for Food Security' (FSC/2012/014), made possible by
   the generous support of the Australian Centre for International
   Agricultural Research (ACIAR) and CRP WHEAT (www.wheat.org). Any
   opinions, findings, conclusion, or recommendations expressed in this
   publication are those of the authors and do not necessarily reflect the
   view of ACIAR and CRP MAIZE. We acknowledge the Ethiopian Institute of
   Agricultural Research (EIAR) for supporting the implementation on-farm
   experiments.
CR Acreche MM, 2009, FIELD CROP RES, V110, P98, DOI 10.1016/j.fcr.2008.07.006
   [Anonymous], 2013, 3 NAT PLATF M LAND W
   [Anonymous], IMPACT USE NEW TECHN
   [Anonymous], 2014, WATER RESOUR RES, DOI DOI 10.1002/2013WR015197
   [Anonymous], US MAN PROF PROB TYP
   [Anonymous], PHENOLOGICAL DEV YIE
   [Anonymous], AGROFOR SYST
   [Anonymous], 9 ISRIC
   [Anonymous], US MAN TIN TEMP LOGG
   [Anonymous], INTEGRATING CLIMATE
   [Anonymous], 1999, AGROFORESTRY PARKLAN
   [Anonymous], REG GOV OR LUM WOR B
   Anwar MR, 2015, AGR SYST, V132, P133, DOI 10.1016/j.agsy.2014.09.010
   Asseng S, 2011, GLOBAL CHANGE BIOL, V17, P997, DOI 10.1111/j.1365-2486.2010.02262.x
   Bayala J, 2006, NUTR CYCL AGROECOSYS, V76, P193, DOI 10.1007/s10705-005-1547-1
   Bayala J, 2015, AGR ECOSYST ENVIRON, V205, P25, DOI 10.1016/j.agee.2015.02.018
   Bayala J, 2014, CURR OPIN ENV SUST, V6, P28, DOI 10.1016/j.cosust.2013.10.004
   Black C, 2000, AGR FOREST METEOROL, V104, P25, DOI 10.1016/S0168-1923(00)00145-3
   Canham CA, 2012, OECOLOGIA, V170, P909, DOI 10.1007/s00442-012-2381-1
   Challinor AJ, 2014, NAT CLIM CHANGE, V4, P287, DOI [10.1038/nclimate2153, 10.1038/NCLIMATE2153]
   Craufurd PQ, 2009, J EXP BOT, V60, P2529, DOI 10.1093/jxb/erp196
   Fischer RA, 2011, CROP PASTURE SCI, V62, P95, DOI 10.1071/CP10344
   García-Baquero G, 2016, J VEG SCI, V27, P219, DOI 10.1111/jvs.12353
   Gelaw AM, 2015, LAND DEGRAD DEV, V26, P690, DOI 10.1002/ldr.2261
   Giller K. E., 2001, NITROGEN FIXATION TR, DOI [10.1079/9780851994178.0000, DOI 10.1079/9780851994178.0000]
   Guendouz A., 2016, EKIN, Journal of Crop Breeding and Genetics, V2, P82
   Iiyama M, 2017, AGROFOREST SYST, V91, P271, DOI 10.1007/s10457-016-9926-y
   Kassie BT, 2014, J AGR SCI-CAMBRIDGE, V152, P58, DOI 10.1017/S0021859612000986
   Kho RM, 2001, AGROFOREST SYST, V52, P219, DOI 10.1023/A:1011820412140
   Lin BB, 2007, AGR FOREST METEOROL, V144, P85, DOI 10.1016/j.agrformet.2006.12.009
   Lin BB, 2010, AGR FOREST METEOROL, V150, P510, DOI 10.1016/j.agrformet.2009.11.010
   Lobell DB, 2012, NAT CLIM CHANGE, V2, P186, DOI [10.1038/NCLIMATE1356, 10.1038/nclimate1356]
   Lott JE, 2009, AGR FOREST METEOROL, V149, P1140, DOI 10.1016/j.agrformet.2009.02.002
   Ludwig F, 2004, PLANT ECOL, V170, P93, DOI 10.1023/B:VEGE.0000019023.29636.92
   Matus F, 2014, CATENA, V120, P102, DOI 10.1016/j.catena.2014.04.008
   Mbow C, 2014, CURR OPIN ENV SUST, V6, P61, DOI 10.1016/j.cosust.2013.10.014
   Mokgolodi Neo C., 2011, Forestry Studies in China, V13, P123, DOI 10.1007/s11632-011-0202-y
   Motzo R, 2013, EUR J AGRON, V44, P87, DOI 10.1016/j.eja.2012.09.002
   New M., 2011, Four degrees and beyond: the potential for a global temperature increase of four degrees and its implications
   Ngigi SN, 2006, PHYS CHEM EARTH, V31, P910, DOI 10.1016/j.pce.2006.08.006
   R Core Team, 2015, R LANG ENV STAT COMP
   Rickards L, 2012, CROP PASTURE SCI, V63, P240, DOI 10.1071/CP11172
   Sanou J, 2012, EXP AGR, V48, P283, DOI 10.1017/S0014479712000014
   Schmidhalter U, 2005, J PLANT NUTR SOIL SC, V168, P432, DOI 10.1002/jpln.200520521
   Sileshi GW, 2016, J ARID ENVIRON, V132, P1, DOI 10.1016/j.jaridenv.2016.03.002
   Sinare H, 2015, AGR ECOSYST ENVIRON, V200, P186, DOI 10.1016/j.agee.2014.11.009
   Smith DM, 1997, J HYDROL, V198, P140, DOI 10.1016/S0022-1694(96)03311-2
   Van Halsema GE, 2011, IRRIG DRAIN, V60, P622, DOI 10.1002/ird.613
   van Noordwijk M, 2015, TREE-CROP INTERACTIONS: AGROFORESTRY IN A CHANGING CLIMATE, 2ND EDITION, P221, DOI 10.1079/9781780645117.0221
   Wahl CT, 2013, INT J AGR SUSTAIN, V11, P382, DOI 10.1080/14735903.2013.812607
   Webb N., 2013, User manual for the SunScan Canopy Analysis System, type SS1, P83
   Zhao G, 2014, ECOL MODEL, V279, P1, DOI 10.1016/j.ecolmodel.2014.02.003
NR 52
TC 86
Z9 91
U1 2
U2 100
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 JAN 15
PY 2018
VL 248
BP 339
EP 347
DI 10.1016/j.agrformet.2017.10.013
PG 9
WC Agronomy; Forestry; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Agriculture; Forestry; Meteorology & Atmospheric Sciences
GA FP5KZ
UT WOS:000417659700029
DA 2025-01-10
ER

PT J
AU Laport, RG
   Hatem, L
   Minckley, RL
   Ramsey, J
AF Laport, Robert G.
   Hatem, Layla
   Minckley, Robert L.
   Ramsey, Justin
TI Ecological niche modeling implicates climatic adaptation, competitive
   exclusion, and niche conservatism among <i>Larrea tridentata</i>
   cytotypes in North American deserts
SO JOURNAL OF THE TORREY BOTANICAL SOCIETY
LA English
DT Article
DE ecological speciation; edaphic endemic; genome duplication; polyploidy;
   range boundary; species distribution modeling
ID ALGODONES DUNES; PLANT MORTALITY; POLYPLOIDY; SOIL; ESTABLISHMENT;
   DISTRIBUTIONS; SPECIATION; NUMBERS; SONORAN; PLOIDY
AB Larrea tridentata is a dominant and widespread shrub of North American warm deserts. The species comprises three "chromosomal races," including diploids (Chihuahuan Desert), tetraploids (Sonoran Desert), hexaploids (Mojave and western Sonoran Deserts), as well as the geographically restricted tetraploid L. tridentata var. arenaria. Creosote bush is a recent arrival to the North American continent, and it is hypothesized that its geographic dispersion reflects rapid ecological divergence mediated by polyploidization. Here we use species distribution modeling to quantitatively evaluate alternate hypotheses for cytotype distributions, based on comprehensive field sampling of creosote bush populations over four years. Using ecological niche models and analyses of field-collected soils, we test whether (1) the climatic niche of the three cytotypes are differentiated; (2) there is evidence for strong climatic gradients at the distributional boundaries of the cytotypes; and (3) cytotype ranges are distinguished by edaphic features. Quantitative tests of niche equivalence indicated that distribution models for all cytotypes were significantly different from one other, suggesting that cytotype races occupy unique and distinctive habitats. However, tests of niche similarity suggest a pattern of niche conservatism, wherein cytotypes tend to occur in climatically similar regions of their respective deserts. Moreover, the modeled diploid distribution was projected to intrude into the geographic range of tetraploids, and the modeled tetraploid distribution was projected to intrude into the range of hexaploids, suggesting that intercytotype competition is a factor influencing cytotype distributions. The range boundary between the dune endemic L. tridentata var. arenaria and hexaploid L. tridentata was noteworthy for exhibiting a strong climatic gradient and striking differences in soil texture (increased sand, decreased gravel). More generally, soil texture differed statistically between sites occupied by diploid, tetraploid, and hexaploid L. tridentata, albeit with considerable overlap across the geographic ranges of the three cytotypes. Taken together, our findings suggest that multiple factors affect the distribution of creosote bush chromosome races, including but not limited to ecological divergence.
C1 [Laport, Robert G.; Hatem, Layla; Minckley, Robert L.; Ramsey, Justin] Univ Rochester, Dept Biol, Rochester, NY 14627 USA.
C3 University of Rochester
RP Laport, RG (corresponding author), Univ Rochester, Dept Biol, River Campus, Rochester, NY 14627 USA.
EM rob.laport@gmail.com
RI Minckley, Robert/AAF-9011-2020
OI Laport, Robert/0000-0001-5672-0929
FU NSF DDIG grant [DEB-1010738]; Torrey Botanical Society fellowship;
   Botanical Society of America student research grant; NSF CAREER grant
   [DEB-0953551]; Direct For Biological Sciences; Division Of Environmental
   Biology [0953551, 1010738] Funding Source: National Science Foundation
FX This research was supported by an NSF DDIG grant (DEB-1010738), a Torrey
   Botanical Society fellowship, and a Botanical Society of America student
   research grant to R. Laport, and an NSF CAREER grant (DEB-0953551) to J.
   Ramsey.
CR Ackerman EA, 1941, GEOGR REV, V31, P105, DOI 10.2307/210420
   [Anonymous], 1935, HEREDITAS
   [Anonymous], 2001, TAXON
   Bahre Conrad J., 1995, P230
   BARBOUR MG, 1969, AM MIDL NAT, V81, P54, DOI 10.2307/2423651
   Benson L., 1981, Trees and Shrubs of the South- western Deserts
   Bouyoucos GJ, 1936, SOIL SCI, V42, P225, DOI 10.1097/00010694-193609000-00007
   Bowers JE, 2004, PLANT ECOL, V172, P107, DOI 10.1023/B:VEGE.0000026026.34760.1b
   BRETAGNOLLE F, 1995, EUPHYTICA, V84, P197, DOI 10.1007/BF01681812
   Brochmann C, 2004, BIOL J LINN SOC, V82, P521, DOI 10.1111/j.1095-8312.2004.00337.x
   Brown J. S, 1923, 497 US GEOL SURV
   Buggs RJA, 2007, EVOLUTION, V61, P125, DOI 10.1111/j.1558-5646.2007.00010.x
   Casper BB, 1997, ANNU REV ECOL SYST, V28, P545, DOI 10.1146/annurev.ecolsys.28.1.545
   Chew R.M., 1965, ECOL MONOGR, V35, P355
   DANFORTH BN, 1994, PAN-PAC ENTOMOL, V70, P283
   De Kovel CGF, 2000, J EVOLUTION BIOL, V13, P561, DOI 10.1046/j.1420-9101.2000.00211.x
   EHLERINGER JR, 1988, OECOLOGIA, V76, P562, DOI 10.1007/BF00397870
   FELBER F, 1991, J EVOLUTION BIOL, V4, P195, DOI 10.1046/j.1420-9101.1991.4020195.x
   FELGER R.S., 2000, Flora of the Gran Desierto and Rio Colorado of Northwestern Mexico, P465
   GATES DH, 1956, ECOL MONOGR, V26, P155, DOI 10.2307/1943288
   Glennon KL, 2012, EVOL ECOL, V26, P909, DOI 10.1007/s10682-011-9539-x
   Glor RE, 2011, EVOLUTION, V65, P673, DOI 10.1111/j.1558-5646.2010.01177.x
   Godsoe W, 2013, AM J BOT, V100, P496, DOI 10.3732/ajb.1200275
   Graham CH, 2004, EVOLUTION, V58, P1781, DOI 10.1554/03-274
   GREENFIELD MD, 1987, ECOLOGY, V68, P828, DOI 10.2307/1938354
   Hamerlynck EP, 2010, J ARID ENVIRON, V74, P1569, DOI 10.1016/j.jaridenv.2010.06.001
   Hamerlynck ER, 2008, J ARID ENVIRON, V72, P1793, DOI 10.1016/j.jaridenv.2008.05.002
   Hamerlynck EP, 2002, ECOLOGY, V83, P768, DOI 10.1890/0012-9658(2002)083[0768:EROTMD]2.0.CO;2
   HENRICKSON J.R., 1976, A Gazeteer of the Chihuahuan Desert Flora
   Hijmans RJ, 2003, EUPHYTICA, V130, P47, DOI 10.1023/A:1022344327669
   Hijmans RJ, 2005, INT J CLIMATOL, V25, P1965, DOI 10.1002/joc.1276
   Hijmans RJ, 2012, ECOLOGY, V93, P679, DOI 10.1890/11-0826.1
   Holt RD, 2005, OIKOS, V108, P18, DOI 10.1111/j.0030-1299.2005.13147.x
   Hunter KL, 2001, GLOBAL ECOL BIOGEOGR, V10, P521, DOI 10.1046/j.1466-822X.2001.00254.x
   HUNZIKER J.H., 1977, Creosote bush: biology and chemistry of Larrea in New World Deserts, P10
   HUNZIKER JH, 1972, ANN MO BOT GARD, V59, P224, DOI 10.2307/2394755
   HURD P. D., 1975, PRINCIPAL LARREA BEE, V193
   Husband BC, 1998, AM J BOT, V85, P1688, DOI 10.1046/j.1469-8137.2004.00998.x
   Ignace DD, 2009, J ARID ENVIRON, V73, P626, DOI 10.1016/j.jaridenv.2009.01.009
   Kozak KH, 2008, TRENDS ECOL EVOL, V23, P141, DOI 10.1016/j.tree.2008.02.001
   Kozak KH, 2006, EVOLUTION, V60, P2604, DOI 10.1111/j.0014-3820.2006.tb01893.x
   KRAMER CY, 1956, BIOMETRICS, V12, P307, DOI 10.2307/3001469
   Laport R., 2013, USDA Forest Service Proceedings, P218
   Laport RG, 2012, SYST BOT, V37, P153, DOI 10.1600/036364412X616738
   Levin D. A., 1975, Taxon, V24, P35, DOI 10.2307/1218997
   LEVIN DA, 1983, AM NAT, V122, P1, DOI 10.1086/284115
   Levin DA, 2004, NEW PHYTOL, V161, P91, DOI 10.1046/j.1469-8137.2003.00921.x
   Lewis W. H., 1980, POLYPLOIDY BIOL RELE
   LUCKENBACH RA, 1983, J APPL ECOL, V20, P265, DOI 10.2307/2403392
   MACEWEN R., 2005, Proceedings, P525
   Maherali H, 2009, NEW PHYTOL, V184, P721, DOI 10.1111/j.1469-8137.2009.02997.x
   Martin SL, 2009, J ECOL, V97, P913, DOI 10.1111/j.1365-2745.2009.01543.x
   McAuliffe JR, 2010, J ARID ENVIRON, V74, P885, DOI 10.1016/j.jaridenv.2010.01.001
   MCAULIFFE JR, 1994, ECOL MONOGR, V64, P111, DOI 10.2307/2937038
   McIntyre PJ, 2012, AM J BOT, V99, P655, DOI 10.3732/ajb.1100466
   MCLAUGHLIN SP, 1986, GREAT BASIN NAT, V46, P46
   Morafka D.J., 1977, P437
   NORRIS RM, 1961, GEOL SOC AM BULL, V72, P605, DOI 10.1130/0016-7606(1961)72[605:ADOSC]2.0.CO;2
   Oberhauser K, 2003, P NATL ACAD SCI USA, V100, P14063, DOI 10.1073/pnas.2331584100
   Ogle K, 2004, OECOLOGIA, V141, P282, DOI 10.1007/s00442-004-1507-5
   Papes M, 2007, DIVERS DISTRIB, V13, P890, DOI 10.1111/j.1472-4642.2007.00392.x
   Pearson RG, 2007, J BIOGEOGR, V34, P102, DOI 10.1111/j.1365-2699.2006.01594.x
   Peterson AT, 2001, BIOSCIENCE, V51, P363, DOI 10.1641/0006-3568(2001)051[0363:PSIUEN]2.0.CO;2
   Peterson AT, 1999, SCIENCE, V285, P1265, DOI 10.1126/science.285.5431.1265
   Phillips SJ, 2006, ECOL MODEL, V190, P231, DOI 10.1016/j.ecolmodel.2005.03.026
   Ramsey J, 2002, ANNU REV ECOL SYST, V33, P589, DOI 10.1146/annurev.ecolsys.33.010802.150437
   Ramsey J, 2011, P NATL ACAD SCI USA, V108, P7096, DOI 10.1073/pnas.1016631108
   RICE WR, 1989, EVOLUTION, V43, P223, DOI 10.1111/j.1558-5646.1989.tb04220.x
   RICKLEFS RE, 1992, AM NAT, V139, P1305, DOI 10.1086/285388
   Riddle BR, 2000, P NATL ACAD SCI USA, V97, P14438, DOI 10.1073/pnas.250413397
   Riddle BR, 1998, ECOGRAPHY, V21, P437, DOI 10.1111/j.1600-0587.1998.tb00409.x
   Rodriguez DJ, 1996, AM NAT, V147, P33, DOI 10.1086/285838
   Roura-Pascual N, 2004, P ROY SOC B-BIOL SCI, V271, P2527, DOI 10.1098/rspb.2004.2898
   ROZEN J.G., 1992, Am. Mus. Novit, V3046, P1
   Russell R, 1931, DRY CLIMATES US
   SCHMIDT RH, 1979, J ARID ENVIRON, V2, P243, DOI 10.1016/S0140-1963(18)31774-9
   Segraves KA, 1999, EVOLUTION, V53, P1114, DOI 10.1111/j.1558-5646.1999.tb04526.x
   SHREVE F., 1942, BOT REV, V8, P195, DOI 10.1007/BF02882228
   Shreve Forrest., 1951, VEGETATION FLORA SON, VI
   Smith SA, 2010, SYST BIOL, V59, P322, DOI 10.1093/sysbio/syq011
   Sobel JM, 2010, EVOLUTION, V64, P295, DOI 10.1111/j.1558-5646.2009.00877.x
   SOLBRIG O.T., 1977, Creosote bush: biology and chemistry of Larrea in New World deserts, P1
   Soltis DE, 2007, TAXON, V56, P13, DOI 10.2307/25065732
   Soltis DE, 2009, AM J BOT, V96, P336, DOI 10.3732/ajb.0800079
   THOMPSON JD, 1992, TRENDS ECOL EVOL, V7, P302, DOI 10.1016/0169-5347(92)90228-4
   Tukey J.W., 1953, COLLECTED WORKS JW T, V8
   Turner R.M., 1995, Sonoran Desert Plants: An Ecological Atlas
   Turner RM., 1994, Biotic Communities: Southwestern United States and Northwestern Mexico, P157
   Van Dam AR, 2008, ANN ENTOMOL SOC AM, V101, P411, DOI 10.1603/0013-8746(2008)101[411:IOOVUO]2.0.CO;2
   Warren DL, 2008, EVOLUTION, V62, P2868, DOI 10.1111/j.1558-5646.2008.00482.x
   WELLS PV, 1976, ANN MO BOT GARD, V63, P843, DOI 10.2307/2395251
   Wiens JJ, 2005, ANNU REV ECOL EVOL S, V36, P519, DOI 10.1146/annurev.ecolsys.36.102803.095431
   Wood DA, 2013, DIVERS DISTRIB, V19, P722, DOI 10.1111/ddi.12022
   Wood TE, 2009, P NATL ACAD SCI USA, V106, P13875, DOI 10.1073/pnas.0811575106
   YANG T W, 1970, Journal of the Arizona Academy of Science, V6, P41, DOI 10.2307/40022846
   YANG T W, 1968, Madrono, V19, P161
   YANG TW, 1967, AM J BOT, V54, P1041, DOI 10.2307/2440729
NR 97
TC 37
Z9 45
U1 0
U2 67
PU TORREY BOTANICAL SOC
PI LAWRENCE
PA 810 E 10TH ST, LAWRENCE, KS 66044 USA
SN 1095-5674
EI 1940-0616
J9 J TORREY BOT SOC
JI J. Torrey Bot. Soc.
PD SEP
PY 2013
VL 140
IS 3
BP 349
EP 363
DI 10.3159/TORREY-D-13-00009.1
PG 15
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA AM2CH
UT WOS:000339655700010
DA 2025-01-10
ER

PT J
AU Gibbon, A
   Silman, MR
   Malhi, Y
   Fisher, JB
   Meir, P
   Zimmermann, M
   Dargie, GC
   Farfan, WR
   Garcia, KC
AF Gibbon, Adam
   Silman, Miles R.
   Malhi, Yadvinder
   Fisher, Joshua B.
   Meir, Patrick
   Zimmermann, Michael
   Dargie, Greta C.
   Farfan, William R.
   Garcia, Karina C.
TI Ecosystem Carbon Storage Across the Grassland-Forest Transition in the
   High Andes of Manu National Park, Peru
SO ECOSYSTEMS
LA English
DT Article
DE Peru; Manu National Park; treeline; puna; upper tropical montane cloud
   forest; carbon stocks
ID TROPICAL MOUNTAIN FORESTS; MONTANE FOREST; PRIMARY PRODUCTIVITY; BIOMASS
   ALLOCATION; PINE PLANTATIONS; ORGANIC-CARBON; CLIMATE-CHANGE; WATER
   YIELD; AFFORESTATION; VEGETATION
AB Improved management of carbon storage by terrestrial biomes has significant value for mitigating climate change. The carbon value of such management has the potential to provide additional income to rural communities and provide biodiversity and climate adaptation co-benefits. Here, we quantify the carbon stores in a 49,300-ha landscape centered on the cloud forest-grassland transition of the high Andes in Manu National Park, Peru. Aboveground carbon densities were measured across the landscape by field sampling of 70 sites above and below the treeline. The forest near the treeline contained 63.4 +/- A 5.2 Mg C ha(-1) aboveground, with an additional 13.9 +/- A 2.8 Mg C ha(-1) estimated to be stored in the coarse roots, using a root to shoot ratio of 0.26. Puna grasslands near the treeline were found to store 7.5 +/- A 0.7 Mg C ha(-1) in aboveground biomass. Comparing our result to soil data gathered by Zimmermann and others (Ecosystems 13:62-74, 2010), we found the ratio of belowground:aboveground carbon decreased from 15.8 on the puna to 8.6 in the transition zone and 2.1 in the forest. No significant relationships were found between carbon densities and slope, altitude or fire disturbance history, though grazing (for puna) was found to reduce aboveground carbon densities significantly. We scaled our study sites to the study region with remote sensing observations from Landsat. The carbon sequestration potential of improved grazing management and assisted upslope treeline migration was also estimated. Afforestation of puna at the treeline could generate revenues of US $1,374 per ha over the project lifetime via commercialization of the carbon credits from gains in aboveground carbon stocks. Uncertainties in the fate of the large soil carbon stocks under an afforestation scenario exist.
C1 [Gibbon, Adam; Malhi, Yadvinder; Fisher, Joshua B.] Univ Oxford, Environm Change Inst, Sch Geog & Environm, Oxford OX1 3QY, England.
   [Silman, Miles R.; Farfan, William R.; Garcia, Karina C.] Wake Forest Univ, Dept Biol, Winston Salem, NC 27106 USA.
   [Meir, Patrick; Zimmermann, Michael; Dargie, Greta C.] Univ Edinburgh, Sch Geosci, Edinburgh EH8 9XP, Midlothian, Scotland.
   [Farfan, William R.; Garcia, Karina C.] Univ Nacl San Antonio Abad, Cuzco, Peru.
C3 University of Oxford; Wake Forest University; University of Edinburgh;
   Universidad Nacional de San Antonio Abad del Cusco
RP Gibbon, A (corresponding author), Univ Oxford, Environm Change Inst, Sch Geog & Environm, S Parks Rd, Oxford OX1 3QY, England.
EM a.e.gibbon@gmail.com
RI Meir, Patrick/J-8344-2012; Malhi, Yadvinder/I-4668-2012; Fisher,
   Joshua/AFM-8914-2022; FARFAN-RIOS, WILLIAM/J-9881-2015; Zimmermann,
   Michael/F-7547-2010
OI Fisher, Joshua/0000-0003-4734-9085; FARFAN-RIOS,
   WILLIAM/0000-0002-3196-0317; Zimmermann, Michael/0000-0002-5162-2008
FU Blue Moon Fund; NERC [NE/F010680/1, NE/G018278/1] Funding Source: UKRI
FX We thank the Blue Moon Fund for support. We especially thank Manu
   National Park and the Peruvian Instituto Nacional de Recusos National
   (INRENA) and the Amazon Conservation Association (ACCA) for permission
   to work in Manu National Park and at the Wayquecha field station,
   respectively. The guards at Manu National Park and Luis Imunda provided
   essential logistical support and advice. Five hard-working undergraduate
   students from Wake Forest University and Flor Zamora, Percy Chambi and
   Nelson Cahuana from Universidad Nacional de San Antonio Abad del Cusco,
   were essential for the completion of this project.
CR Adler PB, 1999, J RANGE MANAGE, V52, P471, DOI 10.2307/4003774
   [Anonymous], 1987, CLOUD FORESTS HUMID
   [Anonymous], 2006, IDRISI ANDES GUIDE G
   Braun G, 2002, MOUNTAIN BIODIVERSITY: A GLOBAL ASSESSMENT, P75
   Brown S., 1997, Estimating biomass and biomass change of tropical forests: a primer, V134
   Bruijnzeel LA, 1998, ECOLOGY, V79, P3, DOI 10.1890/0012-9658(1998)079[0003:CCATMF]2.0.CO;2
   BRUIJNZEEL LA, 1995, ECOL STU AN, V110, P38
   Bubb P., 2004, Cloud forest agenda, P34
   Bush MB, 2002, GLOBAL ECOL BIOGEOGR, V11, P463, DOI 10.1046/j.1466-822X.2002.00305.x
   Bush MB, 2004, SCIENCE, V303, P827, DOI 10.1126/science.1090795
   Becerra JAB, 2007, INT J ENVIRON SUSTAI, V6, P357, DOI 10.1504/IJESD.2007.016240
   Buytaert W, 2007, FOREST ECOL MANAG, V251, P22, DOI 10.1016/j.foreco.2007.06.035
   Cairns MA, 1997, OECOLOGIA, V111, P1, DOI 10.1007/s004420050201
   Campbell J.B., 1997, Cartographica, V34, P70
   CAVELIER J, 1995, ECOL STU AN, V110, P125
   Chave J, 2004, PHILOS T R SOC B, V359, P409, DOI 10.1098/rstb.2003.1425
   Chave J, 2003, J ECOL, V91, P240, DOI 10.1046/j.1365-2745.2003.00757.x
   Chave J, 2005, OECOLOGIA, V145, P87, DOI 10.1007/s00442-005-0100-x
   Chave J, 2006, ECOL APPL, V16, P2356, DOI 10.1890/1051-0761(2006)016[2356:RAPVOW]2.0.CO;2
   CONGALTON RG, 1991, REMOTE SENS ENVIRON, V37, P35, DOI 10.1016/0034-4257(91)90048-B
   De Castro EA, 1998, J TROP ECOL, V14, P263, DOI 10.1017/S0266467498000212
   del Castillo RF, 2007, BIODIVERSITY LOSS AND CONSERVATION IN FRAGMENTED FOREST LANDSCAPES: THE FORESTS OF MONTANE MEXICO AND TEMPERATE SOUTH AMERICA, P158, DOI 10.1079/9781845932619.0158
   Delaney M, 1997, J TROP ECOL, V13, P697, DOI 10.1017/S0266467400010877
   Denman KL, 2007, AR4 CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS, P499
   DYMOND JR, 1992, INT J REMOTE SENS, V13, P1735, DOI 10.1080/01431169208904223
   EDWARDS PJ, 1977, J ECOL, V65, P943, DOI 10.2307/2259387
   Farley KA, 2005, GLOBAL CHANGE BIOL, V11, P1565, DOI 10.1111/j.1365-2486.2005.01011.x
   Farley KA, 2004, ECOSYSTEMS, V7, P729, DOI 10.1007/s10021-004-0047-5
   Fehse J, 2002, FOREST ECOL MANAG, V163, P9, DOI 10.1016/S0378-1127(01)00535-7
   Flombaum P, 2007, J ARID ENVIRON, V69, P352, DOI 10.1016/j.jaridenv.2006.09.008
   Foody GM, 2002, REMOTE SENS ENVIRON, V80, P185, DOI 10.1016/S0034-4257(01)00295-4
   Foster P, 2001, EARTH-SCI REV, V55, P73, DOI 10.1016/S0012-8252(01)00056-3
   Glenday J, 2006, FOREST ECOL MANAG, V235, P72, DOI 10.1016/j.foreco.2006.08.014
   GOLICHER D, 2007, FRAGMENTED FOREST LA, P200
   González-Espinosa M, 2007, BIODIVERSITY LOSS AND CONSERVATION IN FRAGMENTED FOREST LANDSCAPES: THE FORESTS OF MONTANE MEXICO AND TEMPERATE SOUTH AMERICA, P335, DOI 10.1079/9781845932619.0335
   Guo LB, 2002, GLOBAL CHANGE BIOL, V8, P345, DOI 10.1046/j.1354-1013.2002.00486.x
   Hamilton K., 2009, Fortifying the Foundation: State of the Voluntary Carbon Markets 2009
   Hofstede RGM, 2002, MT RES DEV, V22, P159, DOI 10.1659/0276-4741(2002)022[0159:IOPPOS]2.0.CO;2
   Holl KD, 2000, RESTOR ECOL, V8, P339, DOI 10.1046/j.1526-100x.2000.80049.x
   Houghton RA, 1998, GLOBAL BIOGEOCHEM CY, V12, P25, DOI 10.1029/97GB02729
   *INRENA, 2002, I NAC REC NAT PLAN M
   *IUCN, 2008, PROT AR WORLD HER PE
   Jackson RB, 2002, NATURE, V418, P623, DOI 10.1038/nature00910
   Jarvis A., 2006, Hole-filled seamless SRTM data V3
   Jenness JS, 2004, WILDLIFE SOC B, V32, P829, DOI 10.2193/0091-7648(2004)032[0829:CLSAFD]2.0.CO;2
   Kitayama K, 2002, J ECOL, V90, P37, DOI 10.1046/j.0022-0477.2001.00634.x
   Leuschner C, 2007, BASIC APPL ECOL, V8, P219, DOI 10.1016/j.baae.2006.02.004
   Malhi Y, 2000, TRENDS ECOL EVOL, V15, P332, DOI 10.1016/S0169-5347(00)01906-6
   Malhi Y, 2009, GLOBAL CHANGE BIOL, V15, P1255, DOI 10.1111/j.1365-2486.2008.01780.x
   Mokany K, 2006, GLOBAL CHANGE BIOL, V12, P84, DOI 10.1111/j.1365-2486.2005.001043.x
   Moser G., 2008, V198, P229
   Paul KI, 2002, FOREST ECOL MANAG, V168, P241, DOI 10.1016/S0378-1127(01)00740-X
   Pucheta E, 1998, ACTA OECOL, V19, P97, DOI 10.1016/S1146-609X(98)80013-1
   Raich JW, 1997, ECOLOGY, V78, P707
   Ramsay PM, 2001, MT RES DEV, V21, P161, DOI 10.1659/0276-4741(2001)021[0161:AAOANP]2.0.CO;2
   Robertson K, 2004, ENVIRON SCI POLICY, V7, P465, DOI 10.1016/j.envsci.2004.07.003
   Sarmiento FO, 2002, MT RES DEV, V22, P278, DOI 10.1659/0276-4741(2002)022[0278:ACFTL]2.0.CO;2
   Schuman GE, 2002, ENVIRON POLLUT, V116, P391, DOI 10.1016/S0269-7491(01)00215-9
   Scurlock JMO, 1998, GLOBAL CHANGE BIOL, V4, P229, DOI 10.1046/j.1365-2486.1998.00151.x
   Still CJ, 1999, NATURE, V398, P608, DOI 10.1038/19293
   TERBORGH J, 1977, ECOLOGY, V58, P1007, DOI 10.2307/1936921
   van der Werf GR, 2003, GLOBAL CHANGE BIOL, V9, P547, DOI 10.1046/j.1365-2486.2003.00604.x
   WEAVER PL, 1990, BIOTROPICA, V22, P69, DOI 10.2307/2388721
   Wilcke W, 2005, FOREST ECOL MANAG, V205, P139, DOI 10.1016/j.foreco.2004.10.044
   Williams MS, 2000, CAN J FOREST RES, V30, P306, DOI 10.1139/cjfr-30-2-306
   Young KR, 2007, PHILOS T R SOC B, V362, P263, DOI 10.1098/rstb.2006.1986
   Young KR, 2000, MT RES DEV, V20, P208, DOI 10.1659/0276-4741(2000)020[0208:BCIPSE]2.0.CO;2
   Zimmermann M, 2010, ECOSYSTEMS, V13, P62, DOI 10.1007/s10021-009-9300-2
NR 68
TC 85
Z9 101
U1 2
U2 122
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 1432-9840
EI 1435-0629
J9 ECOSYSTEMS
JI Ecosystems
PD NOV
PY 2010
VL 13
IS 7
BP 1097
EP 1111
DI 10.1007/s10021-010-9376-8
PG 15
WC Ecology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology
GA 661BY
UT WOS:000282699200011
DA 2025-01-10
ER

PT C
AU Khabou, W
AF Khabou, W
BE Vitagliano, C
   Martelli, GP
TI The effect of orthotropic and plagiotropic shoots on semi-hard wood
   cuttings rhizogenesis of some Tunisian olive cultivars
SO PROCEEDINGS OF THE FOURTH INTERNATIONAL SYMPOSIUM ON OLIVE GROWING, VOLS
   1 AND 2
SE ACTA HORTICULTURAE
LA English
DT Proceedings Paper
CT 4th International Symposium on Olive Growing
CY SEP 25-30, 2000
CL VALENZANO, ITALY
SP Int Soc Hort Sci, Univ Bari, DPPAM, CIHEAM
DE olive tree; semi-hardwood cutting; growth promoter; plagiotropic and
   orthotropic shoot; proximal and distal cutting
AB Tunisian olive industry is characterized by the presence of a number of native varieties with diversified edaphic and climatic adaptation. Preservation of this precious germplasm would be facilitated if vegetative propagation by cuttings were generally applicable. To extend this type of propagation to as many genotypes as possible, attempts were made to improve the rooting ability of some recalcitrant varieties by using 11 different growth promoter combinations, denoted T1 to T11, which were compared with the untreated control TO,without hormones. Hormones were applied to proximal and distal cuttings with four or six apical leaves, collected from orthotropic or plagiotropic shoots. Cultivars under trial were Chemiali, Meski, Chemchali and Oueslati. Results showed that the rooting rate of all cuttings was influenced by factors such a selection of shoots (plagiotropic or orthotropic), position of the cuttings on the shoot, and combination of growth promoter. In particular: (i) cv. Chemlali. The best rooting rate (60%) was obtained with proximal cuttings containing four leaves, collected from plagiotropic shoot and treated with T5 (IBA 2000 ppm). Distal cuttings with four or six leaves from orthotropic shoots and treated with T4 (IBA 2000+NAA500+IAA500ppm) showed a rooting rate of 40%; (ii) cv.Meski. The best rooting rate (80% and 60%)was shown by orthotropic cuttings with four leaves, treated respectively with T1(IBA4000 ppm), T2 (IBA 3000 + NAA 500+IAA500 ppm), T3 (IBA 2000+NAA1000 +IAA 1000 ppm) and T5 (IBA 2000 ppm). With the same cultivar, plagiotropic cuttings with four or six leaves gave a rooting rate of 82% with T6 (IBA 2000+NAA 500 ppm); (iii)cv.Chemchali registered the highest percentage of rooting (75%)when orthotropic cuttings with four leaves and plagiotropic cuttings with six leaves were treated with T5(IBA 2000 ppm); (iv) cuttings of cv. Oueslati yielded 73% rooting when they were selected from orthotropic shoots with four leaves, treated with T1(IBA 4000ppm) and T3 (IBA 2000+NAA 1000+IAA 1000ppm), or were from plagiotropic shoots with six leaves, treated with T4 (IBA 2000 + NAA500+IAA 500ppm).
C1 Inst Olivier, Sfax 3029, Tunisia.
C3 Institut de l'Olivier; Universite de Sfax
RP Khabou, W (corresponding author), Inst Olivier, BP 1087, Sfax 3029, Tunisia.
CR BARTOLINI G, 1984, RIV ORTOFLOROFRUTTIC
   CHAARI A, 1995, 9 CONS RES COOP INT, P33
   DELRIO C, 1991, J HORTIC SCI, V66, P301, DOI 10.1080/00221589.1991.11516157
   Ede FJ, 1997, J HORTIC SCI, V72, P179, DOI 10.1080/14620316.1997.11515504
   Howard BH, 1996, J HORTIC SCI BIOTECH, V71, P591
   KHABOU W, 1994, MEMOIRE 3 C INAT
   KHABOU W, 1997, CONTRIBUTION ETUDE A
NR 7
TC 2
Z9 3
U1 0
U2 2
PU INTERNATIONAL SOCIETY HORTICULTURAL SCIENCE
PI LEUVEN 1
PA PO BOX 500, 3001 LEUVEN 1, BELGIUM
SN 0567-7572
BN 90-6605-756-4
J9 ACTA HORTIC
PY 2002
IS 586
BP 887
EP 890
DI 10.17660/ActaHortic.2002.586.193
PG 4
WC Agricultural Engineering; Agronomy
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Agriculture
GA BV88J
UT WOS:000180301200193
DA 2025-01-10
ER

PT J
AU Liu, J
   Chen, YN
   Wang, BL
   Wu, XY
   Na, Y
AF Liu, Jian
   Chen, Yini
   Wang, Baolong
   Wu, Xuyong
   Na, Yi
TI Simulation and Experimental Study of Light and Thermal Environment of
   Photovoltaic Greenhouse in Tropical Area Based on Design Builder
SO APPLIED SCIENCES-BASEL
LA English
DT Article
DE photovoltaic greenhouse; light and thermal environment; Design Builder
   simulation; tropical area
AB In order to study the adaptability of photovoltaic greenhouses to climate in tropical areas, a photovoltaic greenhouse model (photovoltaic panel coverage rate: 76.9%) was built in this study according to a 1:1 proportion. The distribution law of the indoor illuminance, temperature, and humidity were studied simultaneously in the photovoltaic greenhouse by actual measurements and simulation. The filed data are shown as follows: (1) Illuminance: in limited rain winter, the average illuminance and light transmittance were 7.02 kLux and 25.77%, respectively (10:00-16:00); but in different weather conditions during summer, the average illuminance and light transmittance were 15.47 kLux and 32.35%, respectively (9:00-16:00). (2) Temperature and humidity: the indoor temperatures of the greenhouse were between 22.1 and 29.3 & DEG;C in limited rain winter, with a relative small temperature difference between indoor and outdoor environments; the relative humidity values were between 69% and 97%; but in summer, the temperatures at all indoor test site were higher than outdoor sites, with an average temperature difference of 2.7 & DEG;C and relative humidity values between 46% and 94%. According to the simulation by Design Builder, the average light transmittances were 33.09% in winter and 37.54% in summer, the temperature difference between winter and summer was less than 1 & DEG;C, and the relative humidity decreased with the increase of temperature, which basically coincided with the filed data. The results of the analysis showed that the illuminance, temperature and humidity of the photovoltaic greenhouse can satisfy the production requirements of shade-enduring and neutral crops. At the same time, by comparing the illumination, temperature and humidity of the photovoltaic greenhouse with that of an ordinary greenhouse, the former had good adaptability to climate in tropical areas, which can achieve the goal of photovoltaic generation and agricultural production synchronously.
C1 [Liu, Jian; Chen, Yini; Wang, Baolong; Wu, Xuyong; Na, Yi] Hainan Univ, Sch Hort, Haikou 570228, Hainan, Peoples R China.
   [Liu, Jian; Chen, Yini; Wang, Baolong; Wu, Xuyong; Na, Yi] Key Lab Qual Regulat Trop Hort Hainan Prov, Haikou 570228, Hainan, Peoples R China.
C3 Hainan University
RP Wang, BL (corresponding author), Hainan Univ, Sch Hort, Haikou 570228, Hainan, Peoples R China.; Wang, BL (corresponding author), Key Lab Qual Regulat Trop Hort Hainan Prov, Haikou 570228, Hainan, Peoples R China.
EM liujian99@hainanu.edu.cn; mickymin0427@163.com;
   wangbaolong@hainanu.edu.cn; 21220951310177@hainanu.edu.cn;
   nygreeny@163.com
RI zhang, ying/HJB-1230-2022
FU Hainan Provincial Natural Science Foundation of China [520RC551]; Hainan
   University Scientific Research Fund [KYQD(ZR)20054];  [20054]
FX Funding This research was funded by Hainan Provincial Natural Science
   Foundation of China (grant number: 520RC551) and Hainan University
   Scientific Research Fund (grant number: KYQD(ZR)20054).
CR [Anonymous], 2012, GB50797 2012 COD DES, P101
   Blanco JM, 2016, ENERG BUILDINGS, V111, P326, DOI 10.1016/j.enbuild.2015.11.053
   Dong W., 2015, Agric. Eng., V5, P44
   Ezzaeri K, 2020, SOL ENERGY, V198, P275, DOI 10.1016/j.solener.2020.01.057
   Fan Y., 2020, P 2020 INT C GREEN B, P321
   Fatnassi H, 2015, SOL ENERGY, V120, P575, DOI 10.1016/j.solener.2015.07.019
   Hassanien RHE, 2018, RENEW ENERG, V121, P377, DOI 10.1016/j.renene.2018.01.044
   Li D., 2014, HEILONGJIANG AGR SCI, V10, P168, DOI [10.3969/j.issn.1002-2767.2014.10.053, DOI 10.3969/J.ISSN.1002-2767.2014.10.053]
   Liu J., 2015, China Patent, Patent No. [201320738494.4, 2013207384944]
   Qi JuanXia Qi JuanXia, 2017, Acta Agriculturae Zhejiangensis, V29, P414
   Shu S., 2017, PHOTOSYNTH QUAL PAKC, V4, P44, DOI 10.ssss/j.issn.1000-6346.2017.4.007
   Song T., 2018, ARCHIT ENG TECHNOL D, V2, P531, DOI [10.3969/j.issn.2095-6630.2018.02.508, DOI 10.3969/J.ISSN.2095-6630.2018.02.508]
   Wang Changan, 2011, J HAINAN NORM U NAT, V24, P168
   Yan D., 2020, AGR ENG TECHNOL, V40, P57, DOI [10.16815/j.cnki.11-5436/s.2020.16.009, DOI 10.16815/J.CNKI.11-5436/S.2020.16.009]
   Zhang Y., 2017, AGR ENG TECHNOL, V37, P31, DOI [10.16815/j.cnki.11-5436/s.2017.22.004, DOI 10.16815/J.CNKI.11-5436/S.2017.22.004]
   Zhang Y., 2000, SHANGHAI VEG, V1, P32
   Zhao Xue Zhao Xue, 2013, Journal of Northwest A & F University - Natural Science Edition, V41, P93
   Zhou C., 2013, AGR ENG TECHNOL GREE, V11, P40, DOI [10.16815/j.cnki.11-5436/s.2013.11.003, DOI 10.16815/J.CNKI.11-5436/S.2013.11.003]
   Zhou C., 2019, AGR ENG TECHNOL, V39, P36
   Zhou C., 2018, AGR ENG TECHNOL, V38, P39
NR 20
TC 4
Z9 4
U1 5
U2 36
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 NOV
PY 2021
VL 11
IS 22
AR 10785
DI 10.3390/app112210785
PG 19
WC Chemistry, Multidisciplinary; Engineering, Multidisciplinary; Materials
   Science, Multidisciplinary; Physics, Applied
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Chemistry; Engineering; Materials Science; Physics
GA XH1QT
UT WOS:000725217400001
OA gold
DA 2025-01-10
ER

PT J
AU Xu, DS
   Li, YF
   Li, JX
   Zhong, H
   Li, JM
   Huang, YB
AF Xu, Desheng
   Li, Yanfeng
   Li, Jiaxin
   Zhong, Hua
   Li, Junmei
   Huang, Youbo
TI Climate-adaptive fire smoke ventilation strategies for atrium-type metro
   stations: A NSGA-II multi-objective optimisation study
SO ENERGY
LA English
DT Article
DE Multi-objective optimisation; Fire safety; Climate change; Ventilation
   system; Energy consumption
ID HYBRID VENTILATION; EMERGENCY VENTILATION; NUMERICAL-SIMULATION; TRAIN
   FIRE; SUBWAY; MODE; PLATFORM; SYSTEM
AB This study explores the impact of climate variability on the operation of sustainable ventilation systems in urban infrastructure, with a focus on smoke movement in metro stations under varied external climatic conditions. Smoke characteristics and ventilation strategies in an atrium-type metro station are investigated using numerical simulations. The simulations reveal the influence of external climate on smoke movement through the atrium and roof windows, with particular attention to outdoor temperature and wind velocity. The study designs different ventilation strategies for smoke control that incorporate meteorological data, evaluating smoke visibility, CO distribution, and smoke extraction efficiency. The findings indicate that under severe external climates of low temperatures and high wind velocities, smoke extraction from roof window outlets is challenging. The adverse effects of external climate decrease the natural smoke extraction efficiency, increase the CO concentration, and reduce the safe visibility area. However, improved ventilation measures, such as the platform make-up air system and roof mechanical extraction system, can significantly enhance smoke control performance and facilitate safe evacuation. The study also employs the NSGA-II multi-objective optimisation method to obtain optimal ventilation strategies for different climates, balancing three optimisation objectives of operating energy consumption, safe visibility area, and smoke extraction efficiency. The outcomes show that the recommended values of V-p are 20%-30 % (0 degrees C <= T-o <= 40 degrees C) and 40 % (-40 degrees C <= T-o<0 degrees C), v(r) are 0.3 (10 degrees C <= T-o <= 40 degrees C) and 0.4 (-40 degrees C <= T-o < -10 degrees C), and V-c are all lower than 4 %. As wind velocity increases, the recommended values need to be enhanced. This research contributes to sustainable urban development by offering a framework for managing public safety and energy efficiency in the context of climate variability.
C1 [Xu, Desheng; Li, Yanfeng; Li, Jiaxin; Li, Junmei] Beijing Univ Technol, Beijing Key Lab Green Built Environm & Energy Effi, Beijing, Peoples R China.
   [Zhong, Hua] London South Bank Univ, Sch Built Environm & Architecture, 103 Borough Rd, London SE1 0AA, England.
   [Huang, Youbo] Chongqing Univ Sci & Technol, Coll Safety Engn, Chongqing, Peoples R China.
C3 Beijing University of Technology; London South Bank University;
   Chongqing University of Science & Technology
RP Li, YF (corresponding author), Beijing Univ Technol, Beijing Key Lab Green Built Environm & Energy Effi, Beijing, Peoples R China.; Zhong, H (corresponding author), London South Bank Univ, Sch Built Environm & Architecture, 103 Borough Rd, London SE1 0AA, England.
EM liyanfeng@bjut.edu.cn; hua.zhong@lsbu.ac.uk
RI Huang, Youbo/IVH-1868-2023; Desheng, Xu/IVV-4174-2023; zhong,
   hua/AAC-9831-2022
OI Xu, Desheng/0000-0002-6629-4561; zhong, hua/0000-0001-9604-4523
FU Beijing Natural Science Foundation [8222002]; National Natural Science
   Foundation of China [52104185]
FX This work was supported by the Beijing Natural Science Foundation (Grant
   No: 8222002) ,National Natural Science Foundation of China (Grant No:
   51378040) ,and National Natural Science Foundation of China (Grant No.
   52104185)
CR [Anonymous], 2009, NFPA92B
   [Anonymous], 2022, GB50736
   [Anonymous], 2015, Feasibility study Report on Project of Beijing urban Rail traffic Airport line: Part of ventilation and air conditioning, P9
   [Anonymous], 2017, GB51251
   [Anonymous], 2018, NFPA 204
   [Anonymous], 2012, 507362012 GB
   [Anonymous], 2018, NFPA92, Standard for Smoke Control Systems
   [Anonymous], 2018, GB51298
   [Anonymous], 2010, NFPA130
   [Anonymous], 2022, GB55036
   Aram M, 2023, J CLEAN PROD, V405, DOI 10.1016/j.jclepro.2023.136996
   Bilyaz S, 2021, FIRE SAFETY J, V126, DOI 10.1016/j.firesaf.2021.103446
   Binbin W., 2011, Procedia Engineering, V26, P1065, DOI DOI 10.1016/J.PROENG.2011.11.2275
   Chen JF, 2023, BUILD ENVIRON, V242, DOI 10.1016/j.buildenv.2023.110553
   Chen JF, 2023, CASE STUD THERM ENG, V41, DOI 10.1016/j.csite.2022.102666
   Chen JF, 2022, J WIND ENG IND AEROD, V228, DOI 10.1016/j.jweia.2022.105133
   Chen T, 2024, THERM SCI ENG PROG, V47, DOI 10.1016/j.tsep.2023.102306
   China Railway First Survey and Design Institude Group Co LTD, 2013, FEASIBILITY STUDY RE, P10
   China Urban Railway Transit Association, 2023, Annual statistics and analysis report on urban rail traffic in 2022
   Chow WK, 1995, FIRE SAFETY J, V25, P337, DOI 10.1016/0379-7112(96)00001-X
   Deb K, 2002, IEEE T EVOLUT COMPUT, V6, P182, DOI 10.1109/4235.996017
   Fan CG, 2017, APPL THERM ENG, V117, P254, DOI 10.1016/j.applthermaleng.2017.02.017
   Gao R, 2015, SAFETY SCI, V80, P94, DOI 10.1016/j.ssci.2015.07.015
   Gao R, 2012, TUNN UNDERGR SP TECH, V31, P128, DOI 10.1016/j.tust.2012.04.013
   Gao R, 2012, ENERG BUILDINGS, V45, P280, DOI 10.1016/j.enbuild.2011.11.018
   García-Izquierdo O, 2024, APPL ENERG, V367, DOI 10.1016/j.apenergy.2024.123369
   Guan BW, 2023, SUSTAIN CITIES SOC, V99, DOI 10.1016/j.scs.2023.104928
   He L, 2021, J WIND ENG IND AEROD, V212, DOI 10.1016/j.jweia.2021.104588
   Hu LH, 2014, BUILD SIMUL-CHINA, V7, P137, DOI 10.1007/s12273-013-0143-6
   Hurley MJ., 2016, SFPE HDB FIRE PROTEC
   Ivanov ML, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13137406
   Jang YJ, 2022, TUNN UNDERGR SP TECH, V121, DOI 10.1016/j.tust.2021.104321
   Jeon GY, 2011, BUILD ENVIRON, V46, P1094, DOI 10.1016/j.buildenv.2010.11.010
   Ji J, 2013, INT J HEAT MASS TRAN, V66, P531, DOI 10.1016/j.ijheatmasstransfer.2013.07.057
   Ji J, 2011, TUNN UNDERGR SP TECH, V26, P490, DOI 10.1016/j.tust.2011.02.001
   Lei WJ, 2022, SAFETY SCI, V153, DOI 10.1016/j.ssci.2022.105807
   Leng JW, 2021, ENERG BUILDINGS, V245, DOI 10.1016/j.enbuild.2021.111068
   Li JX, 2021, TUNN UNDERGR SP TECH, V112, DOI 10.1016/j.tust.2021.103897
   Li JX, 2021, BUILD ENVIRON, V204, DOI 10.1016/j.buildenv.2021.108226
   Lin D, 2024, TUNN UNDERGR SP TECH, V143, DOI 10.1016/j.tust.2023.105373
   Liu C, 2019, BUILD ENVIRON, V147, P267, DOI 10.1016/j.buildenv.2018.10.022
   Liu F, 2020, TUNN UNDERGR SP TECH, V96, DOI 10.1016/j.tust.2019.103177
   Liu YQ, 2021, INT J THERM SCI, V165, DOI 10.1016/j.ijthermalsci.2021.106937
   Long Z, 2021, BUILD SIMUL-CHINA, V14, P779, DOI 10.1007/s12273-020-0692-4
   Long Z, 2020, TUNN UNDERGR SP TECH, V103, DOI 10.1016/j.tust.2020.103508
   Lozinsky CH, 2023, J BUILD ENG, V70, DOI 10.1016/j.jobe.2023.106320
   Luo N, 2014, TUNN UNDERGR SP TECH, V43, P140, DOI 10.1016/j.tust.2014.05.001
   McGrattan K., 2018, Fire Dynamics Simulator User's Guide, VSixth
   Meng N, 2014, TUNN UNDERGR SP TECH, V40, P151, DOI 10.1016/j.tust.2013.09.014
   Peixoto JPJ, 2023, SUSTAIN CITIES SOC, V97, DOI 10.1016/j.scs.2023.104713
   Peng YL, 2021, BUILD ENVIRON, V206, DOI 10.1016/j.buildenv.2021.108408
   Qin TX, 2009, BUILD ENVIRON, V44, P56, DOI 10.1016/j.buildenv.2008.01.014
   Sayyaadi H, 2012, ENERGY, V38, P362, DOI 10.1016/j.energy.2011.11.048
   Song CN, 2024, J MANUF PROCESS, V120, P895, DOI 10.1016/j.jmapro.2024.05.016
   Tan DL, 2024, ENERGY, V286, DOI 10.1016/j.energy.2023.129582
   Tan TT, 2021, FIRE SAFETY J, V120, DOI 10.1016/j.firesaf.2020.103136
   Wang K, 2021, PROCESS SAF ENVIRON, V147, P146, DOI 10.1016/j.psep.2020.09.033
   Wang K, 2016, PROCESS SAF ENVIRON, V103, P46, DOI 10.1016/j.psep.2016.06.026
   Wang Q, 2023, TUNN UNDERGR SP TECH, V142, DOI 10.1016/j.tust.2023.105419
   Wang XY, 2024, ELECTR POW SYST RES, V232, DOI 10.1016/j.epsr.2024.110385
   Wang ZL, 2019, TUNN UNDERGR SP TECH, V88, P98, DOI 10.1016/j.tust.2019.02.006
   Xu DS, 2024, ENERGY, V287, DOI 10.1016/j.energy.2023.129570
   Xu DS, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su131910584
   Xu Y, 2024, THIN WALL STRUCT, V200, DOI 10.1016/j.tws.2024.111918
   Xu YZ, 2021, BUILD ENVIRON, V204, DOI 10.1016/j.buildenv.2021.108142
   Zhang X, 2021, BUILD ENVIRON, V194, DOI 10.1016/j.buildenv.2021.107671
   Zhao PJ, 2017, TRANSPORT RES A-POL, V99, P46, DOI 10.1016/j.tra.2017.03.003
   Zhou Z, 2024, INT J HYDROGEN ENERG, V68, P297, DOI 10.1016/j.ijhydene.2024.04.233
NR 68
TC 1
Z9 1
U1 12
U2 12
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 OCT 15
PY 2024
VL 306
AR 132390
DI 10.1016/j.energy.2024.132390
EA JUL 2024
PG 19
WC Thermodynamics; Energy & Fuels
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Thermodynamics; Energy & Fuels
GA A2B5F
UT WOS:001280636700001
OA hybrid
DA 2025-01-10
ER

PT J
AU Wang, T
   Fan, GH
   Zhang, H
   Shen, XJ
AF Wang, Ting
   Fan, Gaohua
   Zhang, Hui
   Shen, Xiangjin
TI Temporal and Spatial Variability of Ground Frost Indices in Northeast
   China
SO ATMOSPHERE
LA English
DT Article
DE ground frost indices; last spring frost (LSF); first fall frost (FFF);
   frost-free period (FFP); climate change; Northeast China
ID SOLAR-RADIATION; SPATIOTEMPORAL VARIATIONS; FREE PERIOD; TEMPERATURE;
   PHENOLOGY; TRENDS; REGION; MAIZE; DATES; PRECIPITATION
AB Frost is one of the most frequent, intense, and influential agrometeorological disasters that occurs frequently in Northeast China. The study of the spatiotemporal changes of ground frost is of great significance for farmers and policymakers in Northeast China, as it can inform decisions related to crop selection, planting schedules, and the development of regional climate adaptation plans. In this study, the spatiotemporal changes of frost indices (last spring frost (LSF), first fall frost (FFF), and frost-free period (FFP)) in Northeast China were analyzed from 1961 to 2020. Then, we investigated the mutation characteristics of the frost indices and their correlation with geographical factors. The results revealed that (1) the LSF, FFF, and FFP in Northeast China were concentrated at 120-140 DOY, 260-280 DOY, and 110-170 days, respectively. The spatial distribution of frost indices exhibited significant spatial heterogeneity. (2) The LSF, FFF, and FFP showed significant trends of advancement, delay, and extension, with trends of -1.94 days/10 a, 1.72 days/10 a, and 4.21 days/10 a, respectively. (3) More than 80% of the LSF, FFF, and FFP of the sites showed trends of advancement, delay, and extension, with greater variability in the central part of Heilongjiang Province. (4) The FFF and FFP experienced an abrupt change in the late 1990s. (5) The correlation between latitude and LSF, FFF, and FFP was the strongest, with correlation coefficients of 0.77, -0.79, and -0.78, respectively. This study provides a comprehensive understanding of the changing characteristics of ground frost indices that impact agricultural production in Northeast China against the backdrop of climate change. The findings hold significant scientific value in guiding the adaptation of agricultural production layouts in Northeast China to the evolving climatic conditions.
C1 [Wang, Ting] Taiyuan Univ Technol, Coll Ecol, Taiyuan 030024, Peoples R China.
   [Fan, Gaohua] Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China.
   [Zhang, Hui] Jilin Normal Univ, Geog Sci & Tourism Coll, Siping 136000, Peoples R China.
   [Zhang, Hui] Univ Sains Malaysia, Ctr Global Sustainabil Studies, George Town 11800, Malaysia.
   [Shen, Xiangjin] Chinese Acad Sci, Northeast Inst Geog & Agroecol, Changchun 130102, Peoples R China.
C3 Taiyuan University of Technology; Chinese Academy of Sciences; Institute
   of Botany, CAS; Jilin Normal University; Universiti Sains Malaysia;
   Chinese Academy of Sciences; Northeast Institute of Geography &
   Agroecology, CAS
RP Shen, XJ (corresponding author), Chinese Acad Sci, Northeast Inst Geog & Agroecol, Changchun 130102, Peoples R China.
EM wangting03@tyut.edu.cn; fangaohua@ibcas.ac.cn; 1911004@jlnu.edu.cn;
   shenxiangjin@iga.ac.cn
OI Gaohua, Fan/0000-0001-6043-8467
FU National Natural Science Foundation of China [42371070]; Key Research
   Program of Frontier Sciences, CAS [ZDBS-LY-7019]; Natural Science
   Foundation of Jilin Province [20210101104JC]; Youth Innovation Promotion
   Association, CAS [Y2023069]
FX This research was funded by National Natural Science Foundation of China
   (42371070), Key Research Program of Frontier Sciences, CAS
   (ZDBS-LY-7019), Natural Science Foundation of Jilin Province
   (20210101104JC), and Youth Innovation Promotion Association, CAS
   (Y2023069).
CR Anandhi A, 2013, HYDROL PROCESS, V27, P3094, DOI 10.1002/hyp.9937
   Anandhi A, 2013, CLIMATIC CHANGE, V120, P169, DOI 10.1007/s10584-013-0794-4
   Augspurger CK, 2013, ECOLOGY, V94, P41, DOI 10.1890/12-0200.1
   Biazar SM, 2020, THEOR APPL CLIMATOL, V141, P907, DOI 10.1007/s00704-020-03248-7
   Brázdil R, 2021, INT J CLIMATOL, V41, P3881, DOI 10.1002/joc.7048
   Charalampopoulos I, 2022, ATMOSPHERE-BASEL, V13, DOI 10.3390/atmos13091407
   Charalampopoulos I, 2021, ATMOSPHERE-BASEL, V12, DOI 10.3390/atmos12060671
   Chen RW, 2023, EUR J AGRON, V142, DOI 10.1016/j.eja.2022.126642
   Chmielewski FM, 2004, AGR FOREST METEOROL, V121, P69, DOI 10.1016/S0168-1923(03)00161-8
   Dai X, 2023, SCI TOTAL ENVIRON, V864, DOI 10.1016/j.scitotenv.2022.161045
   Drepper B, 2022, AGR FOREST METEOROL, V315, DOI 10.1016/j.agrformet.2022.108822
   Du JZ, 2017, ATMOS CHEM PHYS, V17, P4931, DOI 10.5194/acp-17-4931-2017
   Erlat E, 2016, CLIM RES, V69, P155, DOI 10.3354/cr01397
   Ezaz GT, 2022, GLOBAL PLANET CHANGE, V208, DOI 10.1016/j.gloplacha.2021.103712
   Gabbrielli M, 2022, ITAL J AGRON, V17, DOI 10.4081/ija.2022.2046
   García-Martín A, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13158491
   Gaumont-Guay D, 2003, TREE PHYSIOL, V23, P301, DOI 10.1093/treephys/23.5.301
   Girardin MP, 2022, P NATL ACAD SCI USA, V119, DOI 10.1073/pnas.2117464119
   Graczyk D, 2020, AGRONOMY-BASEL, V10, DOI 10.3390/agronomy10111835
   Guan XJ, 2021, INT J DISAST RISK RE, V64, DOI 10.1016/j.ijdrr.2021.102504
   Haggag M, 2023, NAT HAZARDS, V116, P3645, DOI 10.1007/s11069-023-05829-x
   [韩荣青 Han Rongqing], 2010, [地理学报, Acta Geographica Sinica], V65, P525
   Helali J, 2022, THEOR APPL CLIMATOL, V149, P1405, DOI 10.1007/s00704-022-04124-2
   Helali J, 2021, METEOROL ATMOS PHYS, V133, P1203, DOI 10.1007/s00703-021-00804-2
   Kad P, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac9c74
   Kozminski C, 2021, AGRICULTURE-BASEL, V11, DOI 10.3390/agriculture11070573
   Kukal MS, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-25212-2
   Kunkel KE, 2004, GEOPHYS RES LETT, V31, DOI 10.1029/2003GL018624
   Lamichhane JR, 2021, NAT CLIM CHANGE, V11, P554, DOI 10.1038/s41558-021-01090-x
   Li HY, 2022, REMOTE SENS-BASEL, V14, DOI 10.3390/rs14102400
   Li Y, 2021, FRONT EARTH SC-SWITZ, V9, DOI 10.3389/feart.2021.789523
   Li ZG, 2014, REG ENVIRON CHANGE, V14, P39, DOI 10.1007/s10113-013-0503-x
   Liu BH, 2008, J GEOPHYS RES-ATMOS, V113, DOI 10.1029/2007JD009259
   Lu MG, 2021, SCI TOTAL ENVIRON, V781, DOI 10.1016/j.scitotenv.2021.146774
   MA L, 2022, FRONT EARTH SCI-PRC, V16, P846, DOI 10.1007/s11707-021-0950-5
   Ma R, 2022, FRONT PLANT SCI, V13, DOI 10.3389/fpls.2022.899800
   Malinovic-Milicevic S, 2018, GEOGR ANN A, V100, P44, DOI 10.1080/04353676.2017.1369048
   Masaki Y, 2022, THEOR APPL CLIMATOL, V147, P473, DOI 10.1007/s00704-021-03834-3
   Masaki Y, 2021, THEOR APPL CLIMATOL, V145, P411, DOI 10.1007/s00704-021-03637-6
   Masson-Delmotte V, 2021, CLIMATE CHANGE 2021, DOI DOI 10.1017/9781009157896
   McCabe GJ, 2015, INT J CLIMATOL, V35, P4673, DOI 10.1002/joc.4315
   Meehl GA, 2004, CLIM DYNAM, V23, P495, DOI 10.1007/s00382-004-0442-9
   Meng CC, 2021, THEOR APPL CLIMATOL, V145, P295, DOI 10.1007/s00704-021-03618-9
   Meng QF, 2013, FIELD CROP RES, V143, P91, DOI 10.1016/j.fcr.2012.09.023
   Nikolova N., 2020, J. Environ. Manag, V22, P85
   Ning XJ, 2017, J GEOGR SCI, V27, P23, DOI 10.1007/s11442-017-1362-z
   Papagiannaki K, 2014, NAT HAZARD EARTH SYS, V14, P2375, DOI 10.5194/nhess-14-2375-2014
   Parker LE, 2022, AGRONOMY-BASEL, V12, DOI 10.3390/agronomy12010205
   Pérez J, 2021, ECOL INDIC, V121, DOI 10.1016/j.ecolind.2020.106984
   Potop V, 2014, NAT HAZARDS, V71, P1, DOI 10.1007/s11069-013-0894-5
   Qin ZX, 2019, THEOR APPL CLIMATOL, V138, P1767, DOI 10.1007/s00704-019-02932-7
   Rahimi M, 2007, INT J CLIMATOL, V27, P349, DOI 10.1002/joc.1405
   Ru XY, 2023, SCI HORTIC-AMSTERDAM, V308, DOI 10.1016/j.scienta.2022.111604
   Sangüesa-Barreda G, 2021, SCI TOTAL ENVIRON, V775, DOI 10.1016/j.scitotenv.2021.145860
   Scheifinger H, 2003, THEOR APPL CLIMATOL, V74, P41, DOI 10.1007/s00704-002-0704-6
   Shang LJ, 2022, INT J BIOMETEOROL, V66, P545, DOI 10.1007/s00484-021-02215-9
   Shen XJ, 2024, GLOBAL CHANGE BIOL, V30, DOI 10.1111/gcb.17097
   Shen XJ, 2022, J CLIMATE, V35, P5103, DOI 10.1175/JCLI-D-21-0325.1
   Shen XJ, 2022, GLOBAL BIOGEOCHEM CY, V36, DOI 10.1029/2022GB007396
   Shen XJ, 2021, SCI CHINA EARTH SCI, V64, P1115, DOI 10.1007/s11430-020-9778-7
   Skvareninova J, 2022, ECOL INDIC, V145, DOI 10.1016/j.ecolind.2022.109688
   Sun WX, 2022, INT J CLIMATOL, V42, P10464, DOI 10.1002/joc.7927
   Tait A, 2003, J APPL METEOROL, V42, P193, DOI 10.1175/1520-0450(2003)042<0193:MFOUSD>2.0.CO;2
   Tang JX, 2023, ECOL INDIC, V146, DOI 10.1016/j.ecolind.2023.109912
   Thibeault JM, 2010, J GEOPHYS RES-ATMOS, V115, DOI 10.1029/2009JD012718
   Tonelli E, 2023, SCI TOTAL ENVIRON, V857, DOI 10.1016/j.scitotenv.2022.159239
   Vitasse Y, 2019, GLOBAL CHANGE BIOL, V25, P3781, DOI 10.1111/gcb.14803
   Vitasse Y, 2014, FRONT PLANT SCI, V5, DOI 10.3389/fpls.2014.00541
   Wang KC, 2015, J GEOPHYS RES-ATMOS, V120, P6500, DOI 10.1002/2015JD023420
   Wang KC, 2013, P NATL ACAD SCI USA, V110, P14877, DOI 10.1073/pnas.1311433110
   Wang T, 2021, TERR ATMOS OCEAN SCI, V32, P483, DOI 10.3319/TAO.2021.10.18.01
   Wang XJ, 2022, EARTH SPACE SCI, V9, DOI 10.1029/2022EA002587
   Wypych A, 2017, INT J CLIMATOL, V37, P3340, DOI 10.1002/joc.4920
   Xu XM, 2021, NAT HAZARDS, V109, P827, DOI 10.1007/s11069-021-04858-8
   Xu XM, 2021, SCI TOTAL ENVIRON, V785, DOI 10.1016/j.scitotenv.2021.147247
   Yan YP, 2020, CLIM DYNAM, V55, P2405, DOI 10.1007/s00382-020-05386-0
   Yang WC, 2023, IRRIGATION SCI, V41, P321, DOI 10.1007/s00271-022-00813-y
   Yang YX, 2022, INT J CLIMATOL, V42, P5342, DOI 10.1002/joc.7536
   Yesilirmak E, 2022, THEOR APPL CLIMATOL, V150, P1233, DOI 10.1007/s00704-022-04229-8
   Yu LJ, 2014, INT J CLIMATOL, V34, P3499, DOI 10.1002/joc.3923
   Yu YR, 2021, IEEE J-STARS, V14, P1783, DOI 10.1109/JSTARS.2020.3048823
   Yue ZY, 2022, ATMOSPHERE-BASEL, V13, DOI 10.3390/atmos13071087
   Zhang Z, 2014, J GEOGR SCI, V24, P387, DOI 10.1007/s11442-014-1095-1
   [张志高 Zhang Zhigao], 2022, [干旱区地理, Arid Land Geography], V45, P1685
   Zhao J, 2016, CLIMATIC CHANGE, V137, P29, DOI 10.1007/s10584-016-1652-y
   Zhao JF, 2015, AGR ECOSYST ENVIRON, V207, P79, DOI 10.1016/j.agee.2015.04.006
   Zhao Q, 2021, LANCET PLANET HEALTH, V5, pE415, DOI 10.1016/S2542-5196(21)00081-4
   Zhu LH, 2022, THEOR APPL CLIMATOL, V147, P1713, DOI 10.1007/s00704-021-03889-2
   Zong XZ, 2023, INT J CLIMATOL, V43, P2975, DOI 10.1002/joc.8011
NR 89
TC 1
Z9 1
U1 11
U2 11
PU MDPI
PI BASEL
PA ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
EI 2073-4433
J9 ATMOSPHERE-BASEL
JI Atmosphere
PD JUL
PY 2024
VL 15
IS 7
AR 817
DI 10.3390/atmos15070817
PG 17
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA ZQ3Y1
UT WOS:001276733300001
OA gold
DA 2025-01-10
ER

PT J
AU Markovic, L
   Fasko, P
AF Markovic, Ladislav
   Fasko, Pavel
TI Regional frequency analysis for maximum 5-day precipitation totals using
   L-moments approach in Slovakia
SO THEORETICAL AND APPLIED CLIMATOLOGY
LA English
DT Article
ID EXTREME PRECIPITATION; RAINFALL; VARIABILITY; WATERSHEDS; EVENTS
AB This study presents a comprehensive Regional Frequency Analysis (RFA) of maximum 5-day precipitation totals (Rx5D) in Slovakia using the L-moments approach. The analysis utilized data from 419 precipitation stations across Slovakia, operating continuously from 1951 to 2020. The main objectives were to identify homogeneous regions based on Rx5D, estimate regional frequency distributions, calculate maximum Rx5D for return periods of 5, 10, 20, 50, 100, and 200 years, and map these estimates for Slovakia. The cluster analysis, employing index-flood procedure and Ward's method, identified 14 reasonably homogeneous clusters. Homogeneity and discordancy tests further refined these clusters. The regional frequency distribution for each Rx5D region was determined using L-moment ratio diagrams, ZDist\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${Z}<^>{Dist}$$\end{document} measure and Anderson-Darling tests, resulting in the selection of Gumbel (GUM), Generalized Pareto (GPA), and Generalized Logistic (GLO) as the best-fit distributions for different regions. Specifically, GUM was selected as the best fit only for mountainous regions, highlighting the variability in distribution characteristics across different geographical areas. The analysis revealed significant spatial variability in the Rx5D patterns across Slovakia. Our results indicate that, design Rx5D values expected once every 100 years in lowland regions could occur as frequently as once every 25 years in mountainous areas. The most extreme design Rx5D values exceeding 200 mm were observed in the high-elevation mountainous regions, underscoring the heightened risk of extreme precipitation events in these areas. By exposing these spatial variations, our study contributes to a deeper understanding of precipitation extremes in Slovakia and provides a robust framework for informing water resource management and climate adaptation strategies in the region.
C1 [Markovic, Ladislav; Fasko, Pavel] Slovak Hydrometeorol Inst, Climatol Serv, Bratislava, Slovakia.
   [Markovic, Ladislav] Comenius Univ, Fac Math Phys & Informat, Bratislava, Slovakia.
C3 Comenius University Bratislava
RP Markovic, L (corresponding author), Slovak Hydrometeorol Inst, Climatol Serv, Bratislava, Slovakia.; Markovic, L (corresponding author), Comenius Univ, Fac Math Phys & Informat, Bratislava, Slovakia.
EM ladislav.markovic@shmu.sk
OI Markovic, Ladislav/0000-0001-7272-0494
FU Slovak Research and Development Agency [APVV-19-0340]
FX This work was supported by the Slovak Research and Development Agency
   under the Contract no. APVV-19-0340.
CR Adamowski K, 2000, J HYDROL, V229, P219, DOI 10.1016/S0022-1694(00)00156-6
   Amiri MA, 2021, THEOR APPL CLIMATOL, V146, P645, DOI 10.1007/s00704-021-03743-5
   Amiri MA, 2019, THEOR APPL CLIMATOL, V137, P2905, DOI 10.1007/s00704-019-02787-y
   BURN DH, 1990, WATER RESOUR RES, V26, P2257, DOI 10.1029/WR026i010p02257
   Ceman R, 2003, ZEMEPISNY ATLAS SLOV
   D'Agostino RB., 1986, GOODNESS OF FIT TECH, P367
   Dalrymple T, 1960, 1543A US GEOL SURV, DOI [10.3133/wsp1543A, DOI 10.3133/WSP1543A]
   Dezfuli AK, 2011, THEOR APPL CLIMATOL, V104, P57, DOI 10.1007/s00704-010-0321-8
   Dinpashoh Y, 2004, J HYDROL, V297, P109, DOI 10.1016/j.jhydrol.2004.04.009
   ESRI, 2011, ArcGIS Desktop: Release 10
   FOVELL RG, 1993, J CLIMATE, V6, P2103, DOI 10.1175/1520-0442(1993)006<2103:CZOTCU>2.0.CO;2
   Gaal L, 2004, C P INT BIOCL WORKSH
   Gaal L., 2002, CONTRIB GEOPHYS GEOD, V32, P197
   Gocic M, 2021, PURE APPL GEOPHYS, V178, P1499, DOI 10.1007/s00024-021-02688-0
   Gocic M, 2021, EARTH SCI INFORM, V14, P633, DOI 10.1007/s12145-020-00543-9
   GREENWOOD JA, 1979, WATER RESOUR RES, V15, P1049, DOI 10.1029/WR015i005p01049
   GUTTMAN NB, 1993, J CLIMATE, V6, P2309, DOI 10.1175/1520-0442(1993)006<2309:TUOLMI>2.0.CO;2
   Haddad K, 2011, STOCH ENV RES RISK A, V25, P815, DOI 10.1007/s00477-010-0443-7
   Hosking J.R. M., 1995, Recent advances in life-testing and reliability, P545
   Hosking J.R.M., 1997, Regional Frequency Analysis: An Approach Based on L-Moments, DOI [10.1017/CBO9780511529443, DOI 10.1017/CBO9780511529443]
   HOSKING JRM, 1992, AM STAT, V46, P186, DOI 10.2307/2685210
   HOSKING JRM, 1990, J ROY STAT SOC B MET, V52, P105
   HOSKING JRM, 1993, WATER RESOUR RES, V29, P271, DOI 10.1029/92WR01980
   Isik S, 2008, J HYDROL ENG, V13, P824, DOI 10.1061/(ASCE)1084-0699(2008)13:9(824)
   Jain AK, 1999, ACM COMPUT SURV, V31, P264, DOI 10.1145/331499.331504
   Jurova S., 2002, ACTA HYDROL SLOVACA, V3, P165
   Kar K.K., 2017, Geoenviron Disasters, V4, P18, DOI [10.1186/s40677-017-0082-0, DOI 10.1186/S40677-017-0082-0]
   Kottegoda NT., 1997, STAT PROBABILITY REL, P216
   Kvetak S, 1983, ZBORN PRAC SLOV HYDR, P95
   Kysely J, 2007, CLIM RES, V33, P243, DOI 10.3354/cr033243
   Laio F, 2004, WATER RESOUR RES, V40, DOI 10.1029/2004WR003204
   Lapin M., 2001, VSEOBECNA REGIONALNA
   Lapin M, 2004, SEM EXTR POC PODN BR
   Malekinezhad H, 2011, J AGR SCI TECH-IRAN, V13, P1183
   Malekinezhad H, 2014, ATMOSFERA, V27, P411, DOI 10.1016/S0187-6236(14)70039-6
   Markovic L, 2021, ACTA HYDROL SLOVACA, V22, P2644, DOI [10.31577/ahs-2021-0022.02.0033, DOI 10.31577/AHS-2021-0022.02.0033]
   Markovic L, 2019, METEOROLOGICKY CASOP, V22, P31
   Markovic L, 2017, THESIS COMENIUS U BR, P73
   Mogotsi I. C., 2010, Information Retrieval, V13, P192, DOI [10.1007/s10791-009-9115-y, DOI 10.1007/S10791-009-9115-Y, 10.1007/ s10791-009-9115-y]
   Nicholson SE, 2013, J CLIMATE, V26, P45, DOI 10.1175/JCLI-D-11-00653.1
   Norbiato D, 2007, J HYDROL, V345, P149, DOI 10.1016/j.jhydrol.2007.07.009
   Núñez JH, 2011, J HYDROL, V405, P352, DOI 10.1016/j.jhydrol.2011.05.035
   Oliver M. A., 1990, International Journal of Geographical Information Systems, V4, P313, DOI 10.1080/02693799008941549
   Ostapowicz K., 2013, CARPATHIANS INTEGRAT, P131, DOI [10.1007/978-3-642-12725-0_10, DOI 10.1007/978-3-642-12725-0_10, 10.1007/978-3-642-12725-010]
   Peel MC, 2001, HYDROLOG SCI J, V46, P147, DOI 10.1080/02626660109492806
   R Core Team, 2020, R: A Language and Environment for Statistical Computing
   Rao AR, 2006, J HYDROL, V318, P37, DOI 10.1016/j.jhydrol.2005.06.003
   Remiasova R, 2011, MONOGRAFIE
   RStudio Team, 2020, RSTUDIO INT DEV ENV
   SCHAEFER MG, 1990, WATER RESOUR RES, V26, P119, DOI 10.1029/WR026i001p00119
   SCHOLZ FW, 1987, J AM STAT ASSOC, V82, P918, DOI 10.2307/2288805
   Siman C, 2017, METEOROLOGICK ASOPIS, V20, P11
   Stedinger J. R., 1993, Handbook of Hydrology
   STEDINGER JR, 1995, STOCH HYDROL HYDRAUL, V9, P49, DOI 10.1007/BF01581758
   Stehlova K, 2001, ACTA HYDROLOGICA SLO, P167
   Sveinsson OGB, 2001, WATER RESOUR RES, V37, P2733, DOI 10.1029/2001WR000321
   Viglione A, 2007, WATER RESOUR RES, V43, DOI 10.1029/2006WR005095
   Wallis JR, 2007, HYDROL EARTH SYST SC, V11, P415, DOI 10.5194/hess-11-415-2007
   WARD JH, 1963, J AM STAT ASSOC, V58, P236, DOI 10.2307/2282967
NR 59
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 JUL
PY 2024
VL 155
IS 7
BP 5679
EP 5693
DI 10.1007/s00704-024-04970-2
EA APR 2024
PG 15
WC Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Meteorology & Atmospheric Sciences
GA C2P4X
UT WOS:001203366600001
DA 2025-01-10
ER

PT J
AU Gholamnia, M
   Sajadi, P
   Khan, S
   Sannigrahi, S
   Ghaffarian, S
   Shahabi, H
   Pilla, F
AF Gholamnia, Mehdi
   Sajadi, Payam
   Khan, Salman
   Sannigrahi, Srikanta
   Ghaffarian, Saman
   Shahabi, Himan
   Pilla, Francesco
TI Assessment and Modeling of Green Roof System Hydrological Effectiveness
   in Runoff Control: A Case Study in Dublin
SO IEEE ACCESS
LA English
DT Article
DE Green products; Rain; Air pollution; Meteorology; Urban areas; Sensors;
   Distance measurement; Temperature sensors; Green buildings; Wind speed;
   Green roof; machine learning; rainfall hyetographs; rainfall-runoff
   modeling; runoff hydrograph; water retention
ID SUPPORT VECTOR MACHINES; CLIMATE-CHANGE IMPACTS; WATER-RETENTION;
   URBAN-GROWTH; PERFORMANCE; SUBSTRATE; REDUCTION; ENSEMBLE; CITY
AB Green roofs are essential for urban greening and climate adaptation, especially in densely populated areas. Analyzing runoff reduction parameters is crucial for effectively designing and implementing these systems. This study enhances traditional assessments using advanced sensors to gather meteorological and hydrological data from four green roof installations at University College Dublin (UCD) in Dublin, Ireland. The comprehensive dataset enabled detailed modeling of runoff hydrograph parameters using rainfall hyetographs, which were subsequently analyzed through sophisticated machine learning algorithms. This research introduces an innovative approach by identifying the optimal combination of variables for modeling key runoff characteristics, including Water Retention Amount (WRA), Total RUnoff Volume (TRUV), Peak Runoff Discharge (PRD), and Peak Flow Reduction (PFR). The findings are compelling, with Support Vector Regression (SVR) achieving R-2 values ranging from 0.67 to 0.82 and RMSE values ranging from 0.37 to 1.51 millimeters for WRA, TRUV, PRD, and PFR. XGBoost (XGB) demonstrated superior performance, with R-2 values ranging from 0.77 to 0.84 and RMSE values ranging from 0.28 to 1.26 millimeters for the same parameters. Random Forest Regression (RF) also showed robust results, with R-2 values ranging from 0.76 to 0.84 and RMSE values ranging from 0.31 to 1.29 millimeters. Overall, the green roof system demonstrated a water retention rate of 55.69% for the studied events. The study identifies Cumulative Rainfall Volume (CRV) and Peak Rainfall Intensity (PRI) as crucial for modeling runoff, highlighting green roofs' potential as sustainable urban infrastructure and offering key insights for their design and optimization.
C1 [Gholamnia, Mehdi; Sajadi, Payam; Khan, Salman; Pilla, Francesco] Univ Coll Dublin, Sch Architecture Planning & Environm Policy, Dublin 4, Ireland.
   [Sannigrahi, Srikanta] Univ Coll Dublin, Sch Geog, Dublin 4, Ireland.
   [Ghaffarian, Saman] UCL, Inst Risk & Disaster Reduct, London WC1E 6BT, England.
   [Shahabi, Himan] Silesian Tech Univ, Inst Phys, Div Geochronol & Environm Isotopes, PL-44100 Gliwice, Poland.
   [Shahabi, Himan] Univ Kurdistan, Fac Nat Resources, Dept Geomorphol, Sanandaj 6617715175, Iran.
RP Gholamnia, M (corresponding author), Univ Coll Dublin, Sch Architecture Planning & Environm Policy, Dublin 4, Ireland.
EM mehdi.gholamnia@ucd.ie
FU Climate Action Regional Offices (CARO); National Challenge Fund, Science
   Foundation Ireland (SFI) [22/NCF/OT/11263]
FX This work was supported in part by the Climate Action Regional Offices
   (CARO, https://www.caro.ie/); and in part by the National Challenge
   Fund, Science Foundation Ireland (SFI), under Grant 22/NCF/OT/11263.
CR Abdalla EMH, 2021, HYDROL EARTH SYST SC, V25, P5917, DOI 10.5194/hess-25-5917-2021
   Abelev B, 2013, PHYS LETT B, V719, P18, DOI 10.1016/j.physletb.2012.12.066
   Adnan RM, 2021, NAT HAZARDS, V105, P2987, DOI 10.1007/s11069-020-04438-2
   [Anonymous], 1998, STAT LEARNING THEORY
   Basu AS, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su132313231
   Behzad M, 2009, EXPERT SYST APPL, V36, P7624, DOI 10.1016/j.eswa.2008.09.053
   Belgiu M, 2016, ISPRS J PHOTOGRAMM, V114, P24, DOI 10.1016/j.isprsjprs.2016.01.011
   Bhatta B, 2010, ADV GEOGR INFORM SCI, P17, DOI 10.1007/978-3-642-05299-6_2
   Blignaut J, 2014, ECOL ENG, V65, P54, DOI 10.1016/j.ecoleng.2013.09.003
   Brandao C, 2017, ECOL ENG, V102, P596, DOI 10.1016/j.ecoleng.2017.02.025
   Breiman L, 2001, MACH LEARN, V45, P5, DOI 10.1023/A:1010933404324
   Carter TL, 2006, J AM WATER RESOUR AS, V42, P1261, DOI 10.1111/j.1752-1688.2006.tb05611.x
   Chen B, 2015, J HYDROL, V523, P97, DOI 10.1016/j.jhydrol.2015.01.049
   Chen PY, 2024, ECOHYDROL HYDROBIOL, V24, P112, DOI 10.1016/j.ecohyd.2023.12.002
   Chen T., 2015, R Pack Vers, V1, P1
   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
   Cherkassky V, 2007, Learning from Data: Concepts, Theory, and Methods
   Man CD, 2018, INT J REMOTE SENS, V39, P1243, DOI 10.1080/01431161.2017.1399477
   Coda S, 2019, J HYDROL, V569, P470, DOI 10.1016/j.jhydrol.2018.11.074
   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]
   Bui DT, 2012, MATH PROBL ENG, V2012, DOI 10.1155/2012/974638
   Dinh TLA, 2022, GEOSCI MODEL DEV, V15, P3519, DOI 10.5194/gmd-15-3519-2022
   Feyen L, 2009, WATER AND URBAN DEVELOPMENT PARADIGMS, P217
   Firozjaei MK, 2020, REMOTE SENS ENVIRON, V242, DOI 10.1016/j.rse.2020.111751
   Firozjaei MK, 2019, CITIES, V93, P120, DOI 10.1016/j.cities.2019.05.001
   Firozjaei MK, 2018, ECOL INDIC, V91, P155, DOI 10.1016/j.ecolind.2018.03.052
   Friedman JH, 2001, ANN STAT, V29, P1189, DOI 10.1214/aos/1013203451
   Fu YC, 2019, SCI TOTAL ENVIRON, V666, P274, DOI 10.1016/j.scitotenv.2019.02.178
   Garzón A, 2022, WATER RESOUR RES, V58, DOI 10.1029/2021WR031808
   Getter KL, 2006, HORTSCIENCE, V41, P1276, DOI 10.21273/HORTSCI.41.5.1276
   Graceson A, 2013, ECOL ENG, V61, P328, DOI 10.1016/j.ecoleng.2013.09.030
   Guo YH, 2021, WIRES WATER, V8, DOI 10.1002/wat2.1487
   Hakimdavar R, 2014, ECOL ENG, V73, P494, DOI 10.1016/j.ecoleng.2014.09.080
   Hosseinalizadeh M, 2019, GEODERMA, V342, P1, DOI 10.1016/j.geoderma.2019.01.050
   Huong HTL, 2013, HYDROL EARTH SYST SC, V17, P379, DOI 10.5194/hess-17-379-2013
   Keck Thomas., 2016, CoRR
   Le LT, 2019, APPL SCI-BASEL, V9, DOI 10.3390/app9132714
   Lhomme S., 2019, Cybergeo, Eur ...  Geogr.  ..., V651, P1
   Li JN, 2022, PR MACH LEARN RES
   Li XX, 2018, LAND DEGRAD DEV, V29, P3628, DOI 10.1002/ldr.3102
   Li X, 2019, HYDROLOG SCI J, V64, P1857, DOI 10.1080/02626667.2019.1680846
   Liu W, 2020, HYDROL RES, V51, P635, DOI 10.2166/nh.2020.167
   Liu W, 2019, J HYDROL, V569, P230, DOI 10.1016/j.jhydrol.2018.11.066
   Marjanovic M, 2011, ENG GEOL, V123, P225, DOI 10.1016/j.enggeo.2011.09.006
   Mentens J, 2006, LANDSCAPE URBAN PLAN, V77, P217, DOI 10.1016/j.landurbplan.2005.02.010
   Metselaar K, 2012, RESOUR CONSERV RECY, V64, P49, DOI 10.1016/j.resconrec.2011.12.009
   Micheletti N, 2014, MATH GEOSCI, V46, P33, DOI 10.1007/s11004-013-9511-0
   Mienye ID, 2022, IEEE ACCESS, V10, P99129, DOI 10.1109/ACCESS.2022.3207287
   Moguerza JM, 2006, STAT SCI, V21, P322, DOI 10.1214/088342306000000493
   Moran A. C., 2003, P WORLD WAT ENV RES
   Morgan S, 2013, J ENVIRON ENG, V139, P471, DOI 10.1061/(ASCE)EE.1943-7870.0000589
   Mountrakis G, 2011, ISPRS J PHOTOGRAMM, V66, P247, DOI 10.1016/j.isprsjprs.2010.11.001
   Mukonza SS, 2022, 2022 IEEE MEDITERRANEAN AND MIDDLE-EAST GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (M2GARSS), P134, DOI 10.1109/M2GARSS52314.2022.9840135
   Nawaz R, 2015, ECOL ENG, V82, P66, DOI 10.1016/j.ecoleng.2014.11.061
   Nielsen D., 2016, ''Tree boosting with Xgboost-why does Xgboost win 'every' machine learning competition?
   Palermo SA, 2019, WATER-SUI, V11, DOI 10.3390/w11071378
   Palla A, 2011, WATER SCI TECHNOL, V64, P766, DOI 10.2166/wst.2011.171
   Pappas EA, 2008, CATENA, V72, P146, DOI 10.1016/j.catena.2007.05.001
   Paranunzio R, 2022, J MAR SCI ENG, V10, DOI 10.3390/jmse10111715
   Pilla F, 2019, SCI TOTAL ENVIRON, V650, P144, DOI 10.1016/j.scitotenv.2018.08.439
   Poë S, 2015, J HYDROL, V523, P356, DOI 10.1016/j.jhydrol.2015.02.002
   Pourghasemi HR, 2016, ENVIRON EARTH SCI, V75, DOI 10.1007/s12665-015-4950-1
   Qin YH, 2020, WATER-SUI, V12, DOI 10.3390/w12123579
   Rennie J.D., 2003, On The Value of Leave-One-Out Cross-Validation Bounds
   Roehr D, 2010, CAN WATER RESOUR J, V35, P53, DOI 10.4296/cwrj3501053
   Sagi O, 2018, WIRES DATA MIN KNOWL, V8, DOI 10.1002/widm.1249
   Schreider SY, 2000, CLIMATIC CHANGE, V47, P91, DOI 10.1023/A:1005621523177
   Shafique M, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10041231
   Shuster W. D., 2005, Urban Water J, V2, P263, DOI [DOI 10.1080/15730620500386529, 10.1080/15730620500386529]
   Solomon DD, 2023, DIAGNOSTICS, V13, DOI 10.3390/diagnostics13152610
   Soulis KX, 2012, HYDROL EARTH SYST SC, V16, P1001, DOI 10.5194/hess-16-1001-2012
   Soulis KX, 2017, ECOL ENG, V102, P80, DOI 10.1016/j.ecoleng.2017.01.031
   Speak AF, 2013, SCI TOTAL ENVIRON, V461, P28, DOI 10.1016/j.scitotenv.2013.04.085
   Sreedharan R., 2023, Ethical Issues in AI for Bioinformatics and Chemoinformatics, P56
   Stovin V, 2015, ECOL ENG, V85, P159, DOI 10.1016/j.ecoleng.2015.09.076
   Stovin V, 2013, J ENVIRON MANAGE, V131, P206, DOI 10.1016/j.jenvman.2013.09.026
   Stovin V, 2012, J HYDROL, V414, P148, DOI 10.1016/j.jhydrol.2011.10.022
   Stovin V, 2010, WATER ENVIRON J, V24, P192, DOI 10.1111/j.1747-6593.2009.00174.x
   Tehrany MS, 2014, J HYDROL, V512, P332, DOI 10.1016/j.jhydrol.2014.03.008
   Versini PA, 2016, URBAN WATER J, V13, P372, DOI 10.1080/1573062X.2014.993993
   Wan SA, 2009, KNOWL-BASED SYST, V22, P580, DOI 10.1016/j.knosys.2009.07.008
   Wong GKL, 2014, ECOL ENG, V70, P366, DOI 10.1016/j.ecoleng.2014.06.025
   Wu S., 2008, Tech. Paper VI
   Xiang YH, 2021, REMOTE SENS-BASEL, V13, DOI 10.3390/rs13142831
   Xie HW, 2022, WATER RESOUR MANAG, V36, P1107, DOI 10.1007/s11269-022-03076-6
   Xu C, 2020, J CLEAN PROD, V262, DOI 10.1016/j.jclepro.2020.121421
   Yang Y, 2021, HYDROL EARTH SYST SC, V25, P5839, DOI 10.5194/hess-25-5839-2021
   Yao X, 2008, GEOMORPHOLOGY, V101, P572, DOI 10.1016/j.geomorph.2008.02.011
   Yu Li, 2019, 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), P982, DOI 10.1109/IAEAC47372.2019.8997825
   Zhu H., 2019, Int. J. Transp. Sci. Technol, V8, P373, DOI [DOI 10.1016/J.IJTST.2018.12.001, 10.1016/j.ijtst.2018.12.001]
NR 90
TC 0
Z9 0
U1 0
U2 0
PU IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
PI PISCATAWAY
PA 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
SN 2169-3536
J9 IEEE ACCESS
JI IEEE Access
PY 2024
VL 12
BP 189689
EP 189709
DI 10.1109/ACCESS.2024.3516313
PG 21
WC Computer Science, Information Systems; Engineering, Electrical &
   Electronic; Telecommunications
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Computer Science; Engineering; Telecommunications
GA P9Y7U
UT WOS:001381377200049
OA gold
DA 2025-01-10
ER

PT J
AU Bunbury, MME
   Austvoll, KI
   Jorgensen, EK
   Nielsen, SV
   Kneisel, J
   Weinelt, M
AF Bunbury, Magdalena Maria Elisabeth
   Austvoll, Knut Ivar
   Jorgensen, Erlend Kirkeng
   Nielsen, Svein Vatsvag
   Kneisel, Jutta
   Weinelt, Mara
TI Understanding climate resilience in Scandinavia during the Neolithic and
   Early Bronze Age
SO QUATERNARY SCIENCE REVIEWS
LA English
DT Article
DE Holocene Thermal Maximum; 4.2 ka BP climate shift; Climate adaptation;
   Settlement archaeology; Summed probability distributions; Bayesian
   statistics; Aoristic patterns; Southern Norway; Arctic Norway; Southern
   Scandinavia
ID POPULATION-DYNAMICS; RADIOCARBON-DATES; VARIABILITY; NORWAY; EVENT;
   RECONSTRUCTION; COLONIZATION; TEMPERATURE; DEMOGRAPHY; EXAMPLES
AB Mid and late-Holocene climate shifts are considered to have profoundly shaped demographic developments and adaptive responses of communities globally. Yet their onset, duration, and impact on Neolithic and Early Nordic Bronze Age communities in the high-latitude ranges of southern and north-western Scandinavia remain a major research gap. Here, we built on an emerging body of archaeological and paleoclimate data, encompassing 20,908 anthropogenic 14C dates and 49 climate records from the Holocene. Additionally, we gathered and correlated a new archaeological dataset of 3649 houses from southern Scandinavia and southern Norway. In this study, we utilised 6268 reliable 14C dates and 2519 dwellings to generate time series and socio-economic trends from-4100 to 1100 BCE. Our study revealed three key findings: (1) A distinct lateral zonation, with variations in the duration and timing of the Holocene Thermal Maximum (-7050-2050 BCE). In Southern Scandinavia, a warmer climate may have facilitated the spread of crop cultivation (3820-3790 BCE), coinciding with significant population growth. Neolithic communities settled in permanent two-aisled houses 90-160 years later (3700-3660 BCE). (2) The 2250 BCE (4.2 ka BP) cooling trend marked the beginning of a climate regime shift with varying duration and timing (-3450-1450 BCE). This period coincided with demographic growth, migration, crop cultivation diversity, and the development of houses with crop storage facilities (2290-2215 BCE). (3) Severe abrupt cooling periods (-1850-1450 BCE) corresponded to short-term demographic decline including disruptions in trade networks with continental Europe. However, repopulation and redistribution of wealth (-1450 BCE), along with the development of stable three-aisled houses (1475-1450 BCE), underscore the resilience of food-producing economies in mitigating environmental disturbances.
C1 [Bunbury, Magdalena Maria Elisabeth; Kneisel, Jutta; Weinelt, Mara] Univ Kiel, Cluster Excellence ROOTS Social Environm & Cultura, Kiel, Germany.
   [Bunbury, Magdalena Maria Elisabeth] James Cook Univ, Coll Arts Soc & Educ, ARC Ctr Excellence Australian Biodivers & Heritage, Cairns, Australia.
   [Austvoll, Knut Ivar] Univ Oslo, Dept Archaeol Conservat & Hist, Oslo, Norway.
   [Jorgensen, Erlend Kirkeng] Norwegian Inst Cultural Heritage Res, NIKU High North Dept, Framsenteret, N-9296 Tromso, Norway.
   [Nielsen, Svein Vatsvag] Univ Stavanger, Dept Archaeol Excavat & Nat Sci, Museum Archaeol, Stavanger, Norway.
   [Kneisel, Jutta; Weinelt, Mara] Univ Kiel, Inst Pre & Protohist Archaeol, Kiel, Germany.
C3 University of Kiel; James Cook University; University of Oslo;
   Universitetet i Stavanger; University of Kiel
RP Bunbury, MME (corresponding author), Univ Kiel, Cluster Excellence ROOTS Social Environm & Cultura, Kiel, Germany.
EM magdalena.bunbury@jcu.edu.au
RI Weinelt, Mara/AAD-5295-2020
OI Austvoll, Knut Ivar/0000-0001-5878-5494; Weinelt,
   Mara/0000-0001-5438-4546; Bunbury, Magdalena M.E./0000-0003-3114-3138;
   Jorgensen, Erlend Kirkeng/0000-0002-8573-4489
FU Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) [EXC
   2150-390870439]; Australian Research Council through a Centre of
   Excellence grant [CE170100015]; Swedish Research Council (2020-01097_VR)
   : Modelling Bronze Age Societies in Southern Scandinavia; Riksbankens
   Jubileumsfond [M21-0018]
FX We thank Jan Piet Brozio for supplying a dataset of NE Germany houses.
   We also thank Julian Laabs and Jens Winther Johannsen for their useful
   comments on the paper, as well as Julien Schirrmacher and Ralph
   Grossmann for discussions regarding 14C data collection. MMEB conducted
   this research as a postdoctoral fellow within the Cluster of Excellence
   'ROOTS-Social, Environmental, and Cultural Connectivity in Past
   Societies' funded by the Deutsche Forschungsgemeinschaft (DFG, German
   Research Foundation) under Germany's Excellence Strategy - EXC
   2150-390870439. The paper was finalised while MMEB was funded by the
   Australian Research Council through a Centre of Excellence grant
   (CE170100015) . KIA's contribution was funded through the Swedish
   Research Council (2020-01097_VR) : Modelling Bronze Age Societies in
   Southern Scandinavia, and Riksbankens Jubileumsfond (M21-0018) :
   Maritime Encounters.
CR Andersson M., 2004, Riksantikvarieambetet
   Andersson M., 2016, J NEOLITHIC ARCHAEOL, V18, P23, DOI [10.12766/jna.v18i0.118, DOI 10.12766/jna.v18i0.118]
   Andreasen M.H., 2009, Kuml, V2009, P9, DOI [/10.7146/kuml.v58i58.26388, DOI 10.7146/KUML.V58I58.26388]
   [Anonymous], 1955, Univ. Oldsaksamlingen Arb.
   [Anonymous], 2014, Iberia. Protohistory of the Far West of Europe: From Neolithic to Roman Conquest
   [Anonymous], 1994, Fangstfolk Og Bonder I Fjellet. Bidrag Til Hardangerviddas Forhistorie 8500-2500 Ar For Natid
   [Anonymous], 2016, Studies in Rural Settlement and Farming in Norway
   [Anonymous], 2012, Agrarsamfundenes Ekspansion I Nord
   [Anonymous], 2015, The Bell Beaker Transition in Europe. Mobility and Local Evolution during the 3rd Millennium BC
   [Anonymous], 2005, Viking
   [Anonymous], 2012, Agrarsamfundenes Ekspansion I Nord
   [Anonymous], 1971, Norwegian Archaeological Review, DOI [10.1080/00293652.1971.9965136, DOI 10.1080/00293652.1971.9965136]
   [Anonymous], 1979, Norweg. Archaeol. Rev., DOI DOI 10.1080/00293652.1979.9965311
   [Anonymous], 2013, The Border of Farming Shetland and Scandinavia-Neolithic and Bronze Age Farming, Papers from the Symposium in Copenhagen September 19th Til the 21st2012
   Apel J., 2001, Doctoral dissertation
   Arntzen J.E., 2010, rapport nr 39
   Arntzen J.E., 2012, Jordbruksboplasser fra bronsealder og forromersk jernalder i NordNorge: veien videre, P184
   Arntzen J.E., 2015, FENNOSCANDIA ARCHAEO, V32, P3
   Artursson M., 2009, Gothenburg Archaeological Thesis,, V73
   Artursson M., 2015, The Bell Beaker Transition in Europe. Mobility and Local Evolution during the 3rd Millennium BC, P69
   Austvoll K.I., 2019, Constructing Identities. Structure and Practice in the Early Bronze Age-Southwest Norway, V60
   Austvoll K.I., 2021, New Directions in Anthropological Archaeology
   Berglund B., 2018, Arbok for Helgeland 2018, P56
   Bergsvik KA, 2021, QUATERNARY SCI REV, V259, DOI 10.1016/j.quascirev.2021.106898
   Bertelsen R., 2005, Utmark"- the Outfield as Industry and Ideology in the Iron Age and the Middle Ages
   Bevan A, 2017, P NATL ACAD SCI USA, V114, pE10524, DOI 10.1073/pnas.1709190114
   Bini M, 2019, CLIM PAST, V15, P555, DOI 10.5194/cp-15-555-2019
   Bird D, 2022, SCI DATA, V9, DOI 10.1038/s41597-022-01118-7
   Bocquet-Appel JP, 2008, NEOLITHIC DEMOGRAPHIC TRANSITION AND ITS CONSEQUENCES, P35, DOI 10.1007/978-1-4020-8539-0_3
   Bonsall C., 2002, EUR J ARCHAEOL, V5, P9, DOI DOI 10.1179/EJA.2002.5.1.9
   Borner W., 2004, ENTER THE E WAY 4 DI, V1227, P448
   Borup P., 2019, Journal of Neolithic Archaeology, V20, P83, DOI [10.12766/jna.2018.3, DOI 10.12766/JNA.2018.3]
   Brink K, 2013, EUR J ARCHAEOL, V16, P433, DOI 10.1179/1461957113Y.0000000033
   Bronk Ramsey C., 2020, OXCAL V4 2 2
   Brozio JP, 2019, HOLOCENE, V29, P1558, DOI 10.1177/0959683619857227
   Bunbury MME, 2022, P NATL ACAD SCI USA, V119, DOI 10.1073/pnas.2207609119
   Butruille C, 2017, HOLOCENE, V27, P63, DOI 10.1177/0959683616652701
   Cheng H, 2015, GEOPHYS RES LETT, V42, P8641, DOI 10.1002/2015GL065397
   Crema ER, 2022, J ARCHAEOL METHOD TH, V29, P1387, DOI 10.1007/s10816-022-09559-5
   Crema ER, 2017, J ARCHAEOL SCI, V87, P1, DOI 10.1016/j.jas.2017.09.007
   Crema ER, 2021, RADIOCARBON, V63, P23, DOI 10.1017/RDC.2020.95
   Cullen HM, 2000, GEOLOGY, V28, P379, DOI 10.1130/0091-7613(2000)28<379:CCATCO>2.0.CO;2
   Damm CB, 2020, QUATERN INT, V549, P52, DOI 10.1016/j.quaint.2019.02.032
   Dollar S.R., 2012, Archaologie in Schleswig, V14, P39
   Donat P., 2018, Hauser der Bronze-und Eisenzeit im mittleren Europa
   Earle T.K., 2002, BRONZE AGE EC BEGINN
   Engedal O., 2010, Unpublished dr. philos. dissertation
   Ethelberg P., 2000, Det Sonderjyske Landbrugs Historie: StenOg Bronzealder
   Ethelberg P., 2000, Skrifterudgivet Af Historisk Samfund for Sonderjylland, V81, P135
   Feeser I, 2019, HOLOCENE, V29, P1596, DOI 10.1177/0959683619857223
   Feeser I, 2016, HOLOCENE, V26, P947, DOI 10.1177/0959683615622550
   Finstad E., 2018, J. Glacial Archaeol., V3, P43, DOI [10.1558/jga.33147, DOI 10.1558/JGA.33147]
   Fitzhugh B, 2019, J ARCHAEOL SCI-REP, V23, P1077, DOI 10.1016/j.jasrep.2018.03.016
   Gallopin GC, 2006, GLOBAL ENVIRON CHANG, V16, P293, DOI 10.1016/j.gloenvcha.2006.02.004
   Gjerde J.M., 2010, Unpublished PhD Thesis
   Glykou A., 2016, Neustadt LA 156-Ein submariner Fundplatz des spaten Mesolithikums und des fruhesten Neolithikums in Schleswig-Holstein. Untersuchungen zur Subsistenzstrategie der letzten Jager, Sammler und Fischer an der norddeutschen Ostseekuste
   Gron KJ, 2018, ANTIQUITY, V92, P958, DOI 10.15184/aqy.2018.71
   Haughton M, 2024, J ARCHAEOL METHOD TH, V31, P227, DOI 10.1007/s10816-023-09603-y
   Hinz M., 2019, J. Neolithic Archaeol., V21, P1, DOI DOI 10.12766/JNA.2019.1
   Hinz M, 2012, J ARCHAEOL SCI, V39, P3331, DOI 10.1016/j.jas.2012.05.028
   Hjelle KL, 2006, ENVIRON ARCHAEOL, V11, P147, DOI 10.1179/174963106x123188
   Hogestol M, 2006, ENVIRON ARCHAEOL, V11, P19, DOI 10.1179/174963106x97034
   Holberg E., 2000, Unpublished M (Phil. Thesis).
   Holst MK, 2001, ANTIQUITY, V75, P126, DOI 10.1017/S0003598X00052820
   Hubner E., 2005, Nordiske Fortidsminder. Serie B, V24, P1
   Hufthammer A.K., 2015, Exploitation of Outfield Resources - Joint Research at the University Museums of Norway, P231
   Hultgreen T., 1985, Viking, V48, P83
   Iversen R., 2015, An Eastern Danish Perspective on the 3rd Millennium BC, V88
   Iversen R., 2020, J. Neolithic Archaeol., P119, DOI [10.12766/jna.2020.4, DOI 10.12766/JNA.2020.4]
   Jackson R., 2017, Towards a New Social Contract for Archaeology and Climate Change Adaptation, V25
   Jarriel K, 2021, QUATERN INT, V597, P118, DOI 10.1016/j.quaint.2020.08.010
   Jensen C.E., 2020, Archaeobotanical Studies of Past Plant Cultivation in Northern Europe, V5, P69
   JOHANSEN OS, 1986, RADIOCARBON, V28, P739, DOI 10.1017/S0033822200007979
   Jorgensen EK, 2023, QUATERNARY SCI REV, V299, DOI 10.1016/j.quascirev.2022.107825
   Jorgensen EK, 2021, J ARCHAEOL METHOD TH, V28, P333, DOI 10.1007/s10816-020-09458-7
   Jorgensen EK, 2019, HOLOCENE, V29, P1782, DOI 10.1177/0959683619862036
   Jorgensen EK, 2020, QUATERN INT, V549, P36, DOI 10.1016/j.quaint.2018.05.014
   Kaniewski D, 2018, CLIM PAST, V14, P1529, DOI 10.5194/cp-14-1529-2018
   Kanstrup M, 2014, J ARCHAEOL SCI, V51, P115, DOI 10.1016/j.jas.2013.04.018
   Kaufman D, 2020, SCI DATA, V7, DOI 10.1038/s41597-020-0445-3
   Kintigh KW, 2018, J ARCHAEOL SCI, V89, P25, DOI 10.1016/j.jas.2017.09.006
   Kirleis W, 2014, VEG HIST ARCHAEOBOT, V23, pS81, DOI 10.1007/s00334-014-0440-8
   Kirleis W, 2012, VEG HIST ARCHAEOBOT, V21, P221, DOI 10.1007/s00334-011-0328-9
   Kneisel J., 2022, The Baltic in the Bronze Age. Regional Patterns, Interactions and Boundaries, P189
   Kneisel J., 2012, Collapse or Continuity? Enviroment and Development of Bronze Age Human Landscapes. Universitatsforschungen zur prahistorischen Archaologie 205, P209
   Kneisel J, 2019, HOLOCENE, V29, P1607, DOI 10.1177/0959683619857237
   Krause-Kyora B, 2013, NAT COMMUN, V4, DOI 10.1038/ncomms3348
   Kristiansen K., 2006, ECOLOGY EC STONE AGE, P171
   Kristiansen K, 2010, FUND ISSUE ARCHAEOL, P169, DOI 10.1007/978-1-4419-6300-0_7
   Larsson L., 1992, Papers of the Archaeological Institute University of Lund, P5
   Lawrence D, 2021, PLOS ONE, V16, DOI 10.1371/journal.pone.0244871
   Ling J., 2022, Trade before Civilization: Long Distance Exchange and the Rise of Social Complexity, V53
   Ling J, 2018, CURR ANTHROPOL, V59, P488, DOI 10.1086/699613
   Longo WM, 2020, QUATERNARY SCI REV, V242, DOI 10.1016/j.quascirev.2020.106438
   Madsen M., 2019, Houses for the Living: Two-Aisled Houses from the Neolithic and Early Bronze Age in Denmark, P81
   Marcott SA, 2013, SCIENCE, V339, P1198, DOI 10.1126/science.1228026
   Marston JM, 2011, J ANTHROPOL ARCHAEOL, V30, P190, DOI 10.1016/j.jaa.2011.01.002
   Matthews J.A., 2013, Encyclopedia of Quaternary Science, Vsecond, P257
   Meier D., 2013, Studien zur nordeuropaischen Bronzezeit,, V1, P91
   Melheim A.L., 2016, Comparative Perspectives on Past Colonisation, Maritime Interaction and Cultural Integration, P189
   Mikkelsen M., 2013, Siedlungen der alteren Bronzezeit, P33
   Moen A., 1999, NATL ATLAS NORWAY VE
   Mulder MB, 2009, SCIENCE, V326, P682, DOI 10.1126/science.1178336
   Nielsen P.O., 2019, Sparrevohn et al, V1, P9
   Nielsen SV, 2023, J ARCHAEOL SCI-REP, V51, DOI 10.1016/j.jasrep.2023.104139
   Nielsen SV, 2019, J ANTHROPOL ARCHAEOL, V53, P82, DOI 10.1016/j.jaa.2018.11.004
   Nielsen Svein Vatsvag, 2021, Journal of Neolithic Archaeology, V23, P83, DOI 10.12766/jna.2021.4
   Olsen J, 2010, J PALEOLIMNOL, V43, P323, DOI 10.1007/s10933-009-9334-7
   Pääkkönen M, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-19409-8
   Palmisano A, 2021, QUATERNARY SCI REV, V252, DOI 10.1016/j.quascirev.2020.106739
   Palmisano A, 2017, J ARCHAEOL SCI, V87, P59, DOI 10.1016/j.jas.2017.10.001
   Prescott C., 2018, WATER POWER SOC, P177
   Prescott C., 2020, FARMERS FRONTIER PAN, P381
   Prescott C., 2005, AMS-Varia, V43, P127
   Prosch-Danielsen L., 2000, The Deforestation Patterns and the Establishment of the Coastal Heathland of Southern Norway
   Prosch-Danielsen L, 2020, J ARCHAEOL SCI-REP, V32, DOI 10.1016/j.jasrep.2020.102443
   Prosch-Danielsen L, 2018, PRAEHIST Z, V93, P48, DOI 10.1515/pz-2018-0002
   Railsback LB, 2018, QUATERNARY SCI REV, V186, P78, DOI 10.1016/j.quascirev.2018.02.015
   Ramsey CB, 2009, RADIOCARBON, V51, P337, DOI 10.1017/S0033822200033865
   Reimer PJ, 2020, RADIOCARBON, V62, P725, DOI 10.1017/RDC.2020.41
   Renssen H, 2012, QUATERNARY SCI REV, V48, P7, DOI 10.1016/j.quascirev.2012.05.022
   RICK JW, 1987, AM ANTIQUITY, V52, P55, DOI 10.2307/281060
   Risebrobakken B, 2011, PALEOCEANOGRAPHY, V26, DOI 10.1029/2011PA002117
   Sarauw T., 2006, Bericht der Romisch-Germanischen Kommission, P213
   Sarauw T, 2008, EUR J ARCHAEOL, V11, P23, DOI 10.1177/1461957108101240
   Schafer Di-Maida S., 2023, Unter Hugeln: Bronzezeitliche Transformationsprozesse in Schleswig-Holstein am Beispiel des Fundplatzes von Mang de Bargen (Bornhoved, Kr. Segeberg)
   Schirrmacher J, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0243662
   Schmid MME, 2019, RADIOCARBON, V61, P629, DOI 10.1017/RDC.2018.129
   Schmid MME, 2018, QUAT GEOCHRONOL, V48, P64, DOI 10.1016/j.quageo.2018.07.015
   Schmid Magdalena Maria E., 2018, Published PhD thesis.
   Schmidt J.-P., 2013, Studien zur nordeuropaischen Bronzezeit, V1, P119
   Seppä H, 2009, CLIM PAST, V5, P523, DOI 10.5194/cp-5-523-2009
   Shennan S, 2013, NAT COMMUN, V4, DOI 10.1038/ncomms3486
   Simonsen J., 2017, Daily life at the turn of the Neolithic
   Skjolsvold A., 1977, Museum of Archaeology, V2
   Skoglund P., 2005, Vardagens Landskap: Lokala Perspektiv Pa Bronsalderns Materiella Kultur, V49
   Solheim S, 2018, J ARCHAEOL SCI-REP, V19, P334, DOI 10.1016/j.jasrep.2018.03.007
   Sorensen L., 2013, PNM: Stud. in Arch. & Hist, V22, P463
   Sorensen L., 2014, Acta Archaeol., V85, P73
   Sorensen L, 2014, J ARCHAEOL SCI, V51, P98, DOI 10.1016/j.jas.2012.08.042
   Sorensen LB, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su132413556
   Stoddart S, 2019, HOLOCENE, V29, P761, DOI 10.1177/0959683619826696
   Tallavaara M, 2012, HOLOCENE, V22, P215, DOI 10.1177/0959683611414937
   Team R.C., 2019, R: a Language and Environment for Statistical Computing, V2013
   Timpson A, 2014, J ARCHAEOL SCI, V52, P549, DOI 10.1016/j.jas.2014.08.011
   Topping P., 1996, Neolithic houses in northwest Europe and beyond, P157
   Tveito O.E., 2001, DNMI report, V6
   Vandkilde H., 2017, METAL HOARD PILE SCA, DOI [10.2307/j.ctv62hgr5, DOI 10.2307/J.CTV62HGR5]
   Vandkilde H., 2001, P INT C RIV GARD, VI, P333
   Vandkilde H, 2014, EUR J ARCHAEOL, V17, P602, DOI 10.1179/1461957114Y.0000000064
   Vollan K.W.B., 2022, STONE AGE C BERGEN 2, V12, P13
   Vorren KD, 2007, BOREAS, V36, P253, DOI 10.1080/03009480601061152
   Walker MJC, 2014, SPR GEOL, P983, DOI 10.1007/978-3-319-04364-7_186
   Warden L, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-14353-5
   Weinelt M, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abd8a8
   Weninger B, 2015, WORLD ARCHAEOL, V47, P543, DOI 10.1080/00438243.2015.1064022
   Williams AN, 2012, J ARCHAEOL SCI, V39, P578, DOI 10.1016/j.jas.2011.07.014
NR 157
TC 3
Z9 3
U1 1
U2 4
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0277-3791
EI 1873-457X
J9 QUATERNARY SCI REV
JI Quat. Sci. Rev.
PD DEC 15
PY 2023
VL 322
AR 108391
DI 10.1016/j.quascirev.2023.108391
EA NOV 2023
PG 20
WC Geography, Physical; Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Physical Geography; Geology
GA AM4E9
UT WOS:001118861800001
OA Green Accepted, Green Published, hybrid
DA 2025-01-10
ER

PT J
AU Olutumise, AI
AF Olutumise, Adewale Isaac
TI Intensity of adaptations to heat stress in poultry farms: A behavioural
   analysis of farmers in Ondo state, Nigeria
SO JOURNAL OF THERMAL BIOLOGY
LA English
DT Article
DE Adaptation strategies; Behavioural factors; Climate change; Heat stress;
   Poultry farms; Nigeria
ID CLIMATE-CHANGE; AGRICULTURAL PRACTICES; GROWTH-RATE; STRATEGIES;
   MANAGEMENT; RESPONSES; BROILERS; ADOPTION; PERCEPTION; CHICKENS
AB The detrimental consequences of heat stress due to high ambient temperatures, particularly in the poultry in-dustry, have led to the invention of several adaptation strategies. However, there is still limited information on the intensity of adaptations and the likely behavioural factors that influence farmers' decisions. Thus, under-standing the practical adaptation behaviours of poultry farmers would improve our knowledge of the funda-mental mechanisms for developing effective interventions. To fill this void, using a count data model, the study empirically examines the farmers' behavioural factors and the intensity of heat stress adaptation strategies' adoption among poultry farmers in Ondo State, Nigeria. The data were drawn from a survey of 150 poultry farmers using a multistage sampling procedure. The empirical results show that the majority of the farmers perceived an increase in temperature, frequently experienced heat stress, and believed that heat stress is induced by climate change. An average of six adaptation strategies were simultaneously adopted to mitigate heat stress in the area. The results of the count regression model reveal that farm-level factors such as permanent water sources, the quantity of feed, and bird stock density exert a significant effect on the intensity of adaptations. Climate-related factors such as access to climate information, training participation, perceived increases in temperature, attitudes toward climate change, and motives for adoption have a significant behavioural effect on the intensity of adaptations. Likewise, variables such as poultry farming experience, educational status, and access to credit are accounted for as socioeconomic behavioural factors that influence the intensity of adopting heat stress adaptation strategies in the area. This concludes that behavioural factors are crucial in addressing heat stress adaptations and assisting in improving environmental management, which would form a key variable in the policy interventions.
C1 [Olutumise, Adewale Isaac] Adekunle Ajasin Univ, Dept Agr Econ, PMB 001, Akungba Akoko, Ondo, Nigeria.
   [Olutumise, Adewale Isaac] Walter Sisulu Univ, Dept Econ & Business Sci, Mthatha, South Africa.
C3 Walter Sisulu University
RP Olutumise, AI (corresponding author), Adekunle Ajasin Univ, Dept Agr Econ, PMB 001, Akungba Akoko, Ondo, Nigeria.
EM adewale.olutumise@aaua.edu.ng
RI Olutumise, Adewale/M-4644-2018
OI Olutumise, Adewale Isaac/0000-0003-4600-9265
CR Abedin MA, 2019, INT J DISAST RISK SC, V10, P28, DOI 10.1007/s13753-018-0211-8
   Abioja M.O., 2021, AFRICAN HDB CLIMATE, P1
   Adeagbo OA, 2021, HELIYON, V7, DOI 10.1016/j.heliyon.2021.e06231
   AFO (Annual Flood Outlook), 2021, ANN PUBL NIG HYDR SE
   Afsal A., 2018, INT J VET ANIM MED, V2, P1, DOI [10.31021/ijvam.20181108, DOI 10.31021/IJVAM.20181108]
   Alam MA, 2019, AQUACULT ECON MANAG, V23, P359, DOI 10.1080/13657305.2019.1641568
   Ali MF, 2021, ENVIRON SCI POLLUT R, V28, P14844, DOI 10.1007/s11356-020-11472-x
   Altan Ö, 2000, BRIT POULTRY SCI, V41, P489, DOI 10.1080/713654965
   [Anonymous], 1986, Market. Sci.
   Aryal JP, 2018, NAT RESOUR FORUM, V42, P141, DOI 10.1111/1477-8947.12152
   Ayanlade A, 2017, WEATHER CLIM EXTREME, V15, P24, DOI 10.1016/j.wace.2016.12.001
   Ayo J O, 2011, ISRN Vet Sci, V2011, P838606, DOI 10.5402/2011/838606
   Belay Abrham., 2017, Agriculture Food Security, V6, P24, DOI [10.1186/s40066-017-0100-1, DOI 10.1186/S40066-017-0100-1]
   Bhadauria P., 2017, MANAGEMENT HEAT STRE
   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
   Cameron A. C., 2013, REGRESSION ANAL COUN, V53, DOI DOI 10.1017/CBO9781139013567
   Caviglia-Harris JL, 2003, ECON DEV CULT CHANGE, V52, P23, DOI 10.1086/380137
   Chowdhury VS, 2012, J POULT SCI, V49, P212, DOI 10.2141/jpsa.011071
   DAVIS FD, 1989, MIS QUART, V13, P319, DOI 10.2307/249008
   Deeb N, 2002, POULTRY SCI, V81, P1454, DOI 10.1093/ps/81.10.1454
   Deressa T.T., 2008, WORLD BANK POLICY RE, P4342
   Deressa TT, 2009, GLOBAL ENVIRON CHANG, V19, P248, DOI 10.1016/j.gloenvcha.2009.01.002
   Dhanya P, 2016, J INTEGR ENVIRON SCI, V13, P1, DOI 10.1080/1943815X.2015.1062031
   Ding Z, 2020, CHINA AGR ECON REV, V12, P215, DOI 10.1108/CAER-08-2019-0149
   Ding Z, 2018, CHINA AGR ECON REV, V10, P462, DOI [10.1108/CAER-02-2017-0022, 10.1108/caer-02-2017-0022]
   Fahad S, 2018, LAND USE POLICY, V79, P301, DOI 10.1016/j.landusepol.2018.08.018
   Farnell MB, 2001, AVIAN DIS, V45, P479, DOI 10.2307/1592992
   Fatuase A., 2014, Gaziosmanpașa Universitesi Ziraat Fakultesi Dergisi, V31, P100
   Fatuase AI, 2017, THEOR APPL CLIMATOL, V129, P939, DOI 10.1007/s00704-016-1825-7
   Gbetibouo G.A., 2009, IFPRI DISCUSSION PAP, DOI DOI 10.1068/A312017
   Gogoi S, 2021, J THERM BIOL, V97, DOI 10.1016/j.jtherbio.2021.102840
   Gowe RS, 2008, POULTRY PRODUCTION IN HOT CLIMATES: 2ND EDITION, P13, DOI 10.1079/9781845932589.0013
   Green DonaldP., 1996, Pathologies of rational choice theory: A critique of applications in political science
   Green S.L., 2002, BAYLOR U FACULTY DEV, P1
   Gujarati D.N., 2012, ECONOMETRICS EXAMPLE, V1
   Hassan R, 2008, AFR J AGRIC RESOUR E, V2, P83
   Havenstein GB, 2003, POULTRY SCI, V82, P1500, DOI 10.1093/ps/82.10.1500
   He SP, 2018, WORLD POULTRY SCI J, V74, P647, DOI 10.1017/S0043933918000727
   Huffman WE, 2020, APPL ECON PERSPECT P, V42, P92, DOI 10.1002/aepp.13010
   Humphrey T, 2006, BRIT POULTRY SCI, V47, P379, DOI 10.1080/00071660600829084
   Igbokwe N. A., 2018, Nigerian Veterinary Journal, V39, P101
   Irshad A., 2012, Journal of Animal Production Advances, V3, P177
   Islam MM, 2013, BMC PUBLIC HEALTH, V13, DOI 10.1186/1471-2458-13-11
   Jahejo A. R., 2016, Sindh University Research Journal -Science Series, V48, P829
   Kadim I. T., 2008, International Journal of Poultry Science, V7, P655
   Kumar M, 2021, J THERM BIOL, V97, DOI 10.1016/j.jtherbio.2021.102867
   Lara Lucas J, 2013, Animals (Basel), V3, P356, DOI 10.3390/ani3020356
   Lin H, 2004, BRIT POULTRY SCI, V45, P476, DOI 10.1080/00071660400001173
   Loyau T, 2013, J ANIM SCI, V91, P3674, DOI 10.2527/jas.2013-6445
   Ma Wanglin, 2022, SN Bus Econ, V2, P41, DOI 10.1007/s43546-022-00214-5
   Ma WL, 2020, AUST J AGR RESOUR EC, V64, P1087, DOI 10.1111/1467-8489.12390
   Mack LA, 2013, POULTRY SCI, V92, P285, DOI 10.3382/ps.2012-02589
   Mugenyi A, 2021, PLOS NEGLECT TROP D, V15, DOI 10.1371/journal.pntd.0009820
   Nardone A, 2010, LIVEST SCI, V130, P57, DOI 10.1016/j.livsci.2010.02.011
   Nawab A, 2018, J THERM BIOL, V78, P131, DOI 10.1016/j.jtherbio.2018.08.010
   Nawaz AH, 2021, FRONT VET SCI, V8, DOI 10.3389/fvets.2021.699081
   NBS (National Bureau of Statistics), 2016, POP NIG 2016 SOC STA
   Nienaber JA, 2007, INT J BIOMETEOROL, V52, P149, DOI 10.1007/s00484-007-0103-x
   NOAA (National Oceanic and Atmospheric Administration), 2022, ASS GLOB CLIM 2021
   Nyoni NMB, 2019, CLIM DEV, V11, P83, DOI 10.1080/17565529.2018.1442792
   Ogunleye A, 2021, HELIYON, V7, DOI 10.1016/j.heliyon.2021.e08624
   Ojo TO, 2020, LAND USE POLICY, V95, DOI 10.1016/j.landusepol.2019.04.007
   Oloyo A, 2018, POULTRY SCI J, V6, P1, DOI 10.22069/psj.2018.13880.1284
   Olutumise AI, 2021, INT J BIOMETEOROL, V65, P951, DOI 10.1007/s00484-021-02079-z
   Pereira WF, 2020, COMPUT ELECTRON AGR, V170, DOI 10.1016/j.compag.2020.105257
   Ramirez O.A., 2000, Journal of Agricultural and Applied Economics, V32, P21, DOI DOI 10.1017/S1074070800027796
   Rathore SS, 2017, SOFT COMPUT, V21, P7417, DOI 10.1007/s00500-016-2284-x
   Renaudeau D, 2012, ANIMAL, V6, P707, DOI 10.1017/S1751731111002448
   Rostagno MH, 2009, FOODBORNE PATHOG DIS, V6, P767, DOI 10.1089/fpd.2009.0315
   Saeed M, 2019, J THERM BIOL, V84, P414, DOI 10.1016/j.jtherbio.2019.07.025
   Safdar A.H., 2014, EUR J EXP BIOL, V4, P625
   Sejian V, 2018, ANIMAL, V12, pS431, DOI 10.1017/S1751731118001945
   Settar P, 1999, POULTRY SCI, V78, P1353, DOI 10.1093/ps/78.10.1353
   Shahzad MF, 2021, APPL ECON, V53, P1013, DOI 10.1080/00036846.2020.1820445
   Sohail MU, 2012, POULTRY SCI, V91, P2235, DOI 10.3382/ps.2012-02182
   Stocker, 2014, CLIMATE CHANGE 2013
   Tanimonure VA, 2021, RESOUR ENVIRON SUST, V5, DOI 10.1016/j.resenv.2021.100029
   Vandana GD, 2021, INT J BIOMETEOROL, V65, P163, DOI 10.1007/s00484-020-02023-7
   Zaboli G, 2019, POULTRY SCI, V98, P1551, DOI 10.3382/ps/pey399
NR 80
TC 2
Z9 2
U1 0
U2 1
PU PERGAMON-ELSEVIER SCIENCE LTD
PI OXFORD
PA THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
SN 0306-4565
EI 1879-0992
J9 J THERM BIOL
JI J. Therm. Biol.
PD JUL
PY 2023
VL 115
AR 103614
DI 10.1016/j.jtherbio.2023.103614
EA JUN 2023
PG 10
WC Biology; Zoology
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Life Sciences & Biomedicine - Other Topics; Zoology
GA N5DK5
UT WOS:001037214200001
PM 37336113
OA hybrid
DA 2025-01-10
ER

PT J
AU Ravanbakhsh, M
   Babakhani, B
   Ghasemnezhad, M
   Serpooshan, F
   Biglouie, MH
AF Ravanbakhsh, Mokarram
   Babakhani, Babak
   Ghasemnezhad, Mahmood
   Serpooshan, Fariba
   Biglouie, Mohamad Hassan
TI Acer velutinum Bioss. (velvet maple) seedlings are more tolerant to
   water deficit than Alnus subcordata CA Mey. (Caucasian alder) seedlings
SO ACTA BOTANICA CROATICA
LA English
DT Article
DE Alnus subcordata; Acer velutinum; antioxidant enzymes; biomass; growth;
   water deficit
ID DROUGHT STRESS; BIOCHEMICAL RESPONSES; USE EFFICIENCY; GROWTH;
   VARIETIES; PROLINE; TRAITS; FOREST; PLANTS; SHOW
AB - Drought stress is a major environmental factor limiting plant growth. Selection of drought-tolerant plants is of critical importance in vegetation restoration and forestation programs. Alnus subcordata and Acer velutinum are two valuable, dominant, and endemic species in the Hyrcanian forests. There are fast-growing species and significant diffuse-porous hardwood in afforestation and reforestation. One-year old seedlings of both species were exposed to four water shortage treatments (100, 75, 50 and 25% of field capacity (FC) chosen as control, mild, moderate, and severe) for 12 weeks. Thereafter, their morphological characteristics such as height and basal area, total and organ biomass (root, stem, and leaf), leaf area (LA), specific leaf area (SLA), leaf area ratio (LAR), as well as physiological and biochemical characteristics such as relative water content (RWC), content of chlorophyll, free proline and malondialdehyde (MDA), and superoxide dismutase (SOD) and peroxidase (POD) activity were measured. The results showed that when exposed to reduced water availability, plant height, basal diameter, total and organ biomass, LA, LAR, RWC and chlorophyll content decreased, but their proline concentration, MDA content, SOD, and POD activity increased in both species. The root to shoot ratio (R/S) and root mass ratio (RMR) increased at 50 and 25% FC treatments in A. subcordata, whereas no significant difference was found in A. velutinum under drought treatments. SLA increased significantly at 50% FC in A. velutinum and decreased in A. subcordata under drought treatments compared to control treatment. A. velutinum showed more proline content, RWC, POD, and lower increase in MDA content than A. subcordata under moderate treatment. Therefore, A. velutinum appears to possess a better mechanism to cope with drought stress. The drought tolerance of A. velutinum may enhance its potential for climatic adaptations under drier conditions with the ongoing climatic change.
C1 [Ravanbakhsh, Mokarram; Babakhani, Babak; Ghasemnezhad, Mahmood; Serpooshan, Fariba; Biglouie, Mohamad Hassan] Islamic Azad Univ, Dept Biol, Tonekabon Branch, Tonekabon, Iran.
   [Ghasemnezhad, Mahmood] Univ Guilan, Fac Agr Sci, Dept Hort Sci, Rasht, Iran.
   [Biglouie, Mohamad Hassan] Univ Guilan, Fac Agr Sci, Dept Water Engn, Rasht, Iran.
C3 Islamic Azad University; University of Guilan; University of Guilan
RP Babakhani, B (corresponding author), Islamic Azad Univ, Dept Biol, Tonekabon Branch, Tonekabon, Iran.
EM babakhani_babak@yahoo.com
RI Ghasemnezhad, Mahmood/HJY-7068-2023; Serpooshan, Fariba/AAN-9867-2021
OI Ghasemnezhad, Mahmood/0000-0002-7615-2639
CR Abdolahi A., 2017, IRANIAN J FOREST POP, V25, P275
   Abid M, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-21441-7
   Allahyari MS, 2016, CLIMATE, V4, DOI 10.3390/cli4040058
   Anjum SA, 2011, AFR J AGR RES, V6, P2026
   [Anonymous], 2012, ACTA ECOLOGICA SINIC, DOI DOI 10.1016/J.CHNAES.2012.05.001
   [Anonymous], 2018, Iran. J. For.
   Ashraf M, 2013, PHOTOSYNTHETICA, V51, P163, DOI 10.1007/s11099-013-0021-6
   Ashrafi M, 2018, PLANT PHYSIOL BIOCH, V132, P391, DOI 10.1016/j.plaphy.2018.09.009
   Attarod P., 2017, IRAN J FOREST, V9, P171
   Bangar P, 2019, TURK J BIOL, V43, P58, DOI 10.3906/biy-1801-64
   Barros V, 2020, PLANT PHYSIOL BIOCH, V147, P181, DOI 10.1016/j.plaphy.2019.12.018
   BATES LS, 1973, PLANT SOIL, V39, P205, DOI 10.1007/BF00018060
   Bhusal N, 2020, FOREST ECOL MANAG, V465, DOI 10.1016/j.foreco.2020.118099
   Chakhchar A, 2015, J PLANT INTERACT, V10, P252, DOI 10.1080/17429145.2015.1068386
   Dias MC, 2014, PLANT PHYSIOL BIOCH, V75, P123, DOI 10.1016/j.plaphy.2013.12.014
   Díaz-López L, 2012, AGR WATER MANAGE, V105, P48, DOI 10.1016/j.agwat.2012.01.001
   Du LS, 2019, ECOL EVOL, V9, P9948, DOI 10.1002/ece3.5536
   Du N, 2010, ACTA PHYSIOL PLANT, V32, P839, DOI 10.1007/s11738-010-0468-z
   Dulai S, 2014, J PLANT PHYSIOL, V171, P509, DOI 10.1016/j.jplph.2013.11.015
   Farooq M, 2009, SUSTAINABLE AGRICULTURE, P153, DOI 10.1051/agro:2008021
   Gallé A, 2007, PHYSIOL PLANTARUM, V131, P412, DOI 10.1111/j.1399-3054.2007.00972.x
   Ge YJ, 2014, ACTA PHYSIOL PLANT, V36, P1241, DOI 10.1007/s11738-014-1502-3
   Geng DL, 2019, J INTEGR AGR, V18, P1280, DOI 10.1016/S2095-3119(19)62571-2
   Ghaffari H, 2019, ACTA PHYSIOL PLANT, V41, DOI 10.1007/s11738-019-2815-z
   Ghorbani M, 2018, FOREST ECOL MANAG, V409, P890, DOI 10.1016/j.foreco.2017.11.016
   GIANNOPOLITIS CN, 1977, PLANT PHYSIOL, V59, P309, DOI 10.1104/pp.59.2.309
   Guo X, 2019, FLORA, V257, DOI 10.1016/j.flora.2019.151423
   Guo X, 2013, ACTA PHYSIOL PLANT, V35, P1149, DOI 10.1007/s11738-012-1154-0
   Guo YY, 2018, RUSS J PLANT PHYSL+, V65, P244, DOI 10.1134/S1021443718020127
   Jourgholami M, 2020, NEW FOREST, V51, P349, DOI 10.1007/s11056-019-09738-5
   Khaleghi A, 2019, SCI REP-UK, V9, DOI 10.1038/s41598-019-55889-y
   Lei YB, 2006, PHYSIOL PLANTARUM, V127, P182, DOI 10.1111/j.1399-3054.2006.00638.x
   LICHTENTHALER HK, 1987, METHOD ENZYMOL, V148, P350
   Liu BH, 2019, SCI HORTIC-AMSTERDAM, V250, P230, DOI 10.1016/j.scienta.2019.02.056
   Medeiros DB, 2013, THEOR EXP PLANT PHYS, V25, P213, DOI 10.1590/S2197-00252013000300006
   Meng GT, 2013, J PLANT GROWTH REGUL, V32, P542, DOI 10.1007/s00344-013-9319-7
   Mohammadkhani N, 2008, TURK J BIOL, V32, P23
   Naghdi R, 2016, EUR J FOREST RES, V135, P949, DOI 10.1007/s10342-016-0986-3
   Naji HR, 2016, IFOREST, V9, P325, DOI 10.3832/ifor1333-008
   PLEWA MJ, 1991, MUTAT RES, V247, P57, DOI 10.1016/0027-5107(91)90033-K
   Rahimi D., 2016, Journal of Forest Science (Prague), V62, P269, DOI 10.17221/15/2016-JFS
   Sjöman H, 2021, DENDROBIOLOGY, V85, P39, DOI 10.12657/denbio.085.005
   Tariq A, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-24038-2
   Tavankar F, 2017, CROAT J FOR ENG, V38, P73
   Toscano S, 2016, FRONT PLANT SCI, V7, DOI 10.3389/fpls.2016.00645
   Wang SC, 2012, PLANT PHYSIOL BIOCH, V51, P81, DOI 10.1016/j.plaphy.2011.10.014
   Wu FZ, 2008, ENVIRON EXP BOT, V63, P248, DOI 10.1016/j.envexpbot.2007.11.002
   Wu JW, 2017, ACTA PHYSIOL PLANT, V39, DOI 10.1007/s11738-017-2380-2
   Wu M, 2013, RUSS J PLANT PHYSL+, V60, P681, DOI 10.1134/S1021443713030151
   Yang F, 2010, SILVA FENN, V44, P23, DOI 10.14214/sf.160
   Ying YQ, 2015, FRONT PLANT SCI, V6, DOI 10.3389/fpls.2015.00361
   Zhang YY, 2019, GLOB ECOL CONSERV, V19, DOI 10.1016/j.gecco.2019.e00660
NR 52
TC 1
Z9 1
U1 2
U2 13
PU UNIV ZAGREB, FAC SCIENCE, DIV BIOLOGY
PI ZAGREB
PA C/O DAMIR VILICIC, EDITOR-IN-CHIEF, DEPARTMENT OF BOTANY, ROOSEVELTOV
   TRG 6, ZAGREB, CROATIA
SN 0365-0588
EI 1847-8476
J9 ACTA BOT CROAT
JI Acta Bot. Croat.
PD MAR
PY 2023
VL 82
IS 1
BP 60
EP 70
DI 10.97427/botcro-2022-029
PG 11
WC Plant Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Plant Sciences
GA C8KG1
UT WOS:000964335900008
DA 2025-01-10
ER

PT J
AU Crona, BI
   Wassénius, E
   Jonell, M
   Koehn, JZ
   Short, R
   Tigchelaar, M
   Daw, TM
   Golden, CD
   Gephart, JA
   Allison, EH
   Bush, SR
   Cao, L
   Cheung, WWL
   DeClerck, F
   Fanzo, J
   Gelcich, S
   Kishore, A
   Halpern, BS
   Hicks, CC
   Leape, JP
   Little, DC
   Micheli, F
   Naylor, RL
   Phillips, M
   Selig, ER
   Springmann, M
   Sumaila, UR
   Troell, M
   Thilsted, SH
   Wabnitz, CCC
AF Crona, Beatrice I.
   Wassenius, Emmy
   Jonell, Malin
   Koehn, J. Zachary
   Short, Rebecca
   Tigchelaar, Michelle
   Daw, Tim M.
   Golden, Christopher D.
   Gephart, Jessica A.
   Allison, Edward H.
   Bush, Simon R.
   Cao, Ling
   Cheung, William W. L.
   DeClerck, Fabrice
   Fanzo, Jessica
   Gelcich, Stefan
   Kishore, Avinash
   Halpern, Benjamin S.
   Hicks, Christina C.
   Leape, James P.
   Little, David C.
   Micheli, Fiorenza
   Naylor, Rosamond L.
   Phillips, Michael
   Selig, Elizabeth R.
   Springmann, Marco
   Sumaila, U. Rashid
   Troell, Max
   Thilsted, Shakuntala H.
   Wabnitz, Colette C. C.
TI Four ways blue foods can help achieve food system ambitions across
   nations
SO NATURE
LA English
DT Article
ID SMALL-SCALE FISHERIES; ENVIRONMENTAL IMPACTS; NUTRITIOUS FOODS; MEAT
   CONSUMPTION; CLIMATE-CHANGE; RED MEAT; FISH; AQUACULTURE; HEALTH; DEMAND
AB Blue foods, sourced in aquatic environments, are important for the economies, livelihoods, nutritional security and cultures of people in many nations. They are often nutrient rich(1), generate lower emissions and impacts on land and water than many terrestrial meats(2), and contribute to the health(3), wellbeing and livelihoods of many rural communities(4). The Blue Food Assessment recently evaluated nutritional, environmental, economic and justice dimensions of blue foods globally. Here we integrate these findings and translate them into four policy objectives to help realize the contributions that blue foods can make to national food systems around the world: ensuring supplies of critical nutrients, providing healthy alternatives to terrestrial meat, reducing dietary environmental footprints and safeguarding blue food contributions to nutrition, just economies and livelihoods under a changing climate. To account for how context-specific environmental, socio-economic and cultural aspects affect this contribution, we assess the relevance of each policy objective for individual countries, and examine associated co-benefits and trade-offs at national and international scales. We find that in many African and South American nations, facilitating consumption of culturally relevant blue food, especially among nutritionally vulnerable population segments, could address vitamin B-12 and omega-3 deficiencies. Meanwhile, in many global North nations, cardiovascular disease rates and large greenhouse gas footprints from ruminant meat intake could be lowered through moderate consumption of seafood with low environmental impact. The analytical framework we provide also identifies countries with high future risk, for whom climate adaptation of blue food systems will be particularly important. Overall the framework helps decision makers to assess the blue food policy objectives most relevant to their geographies, and to compare and contrast the benefits and trade-offs associated with pursuing these objectives.
C1 [Crona, Beatrice I.; Wassenius, Emmy; Jonell, Malin; Short, Rebecca; Daw, Tim M.] Stockholm Univ, Stockholm Resilience Ctr, Stockholm, Sweden.
   [Crona, Beatrice I.; Wassenius, Emmy; Jonell, Malin; Troell, Max] Royal Swedish Acad Sci, Global Econ Dynam & Biosphere, Stockholm, Sweden.
   [Koehn, J. Zachary; Tigchelaar, Michelle; Leape, James P.; Micheli, Fiorenza; Selig, Elizabeth R.; Wabnitz, Colette C. C.] Stanford Univ, Stanford Ctr Ocean Solut, Stanford, CA USA.
   [Golden, Christopher D.] Harvard TH Chan Sch Publ Hlth, Dept Nutr, Boston, MA USA.
   [Golden, Christopher D.] Harvard TH Chan Sch Publ Hlth, Dept Environm Hlth, Boston, MA USA.
   [Golden, Christopher D.] Harvard TH Chan Sch Publ Hlth, Dept Global Hlth & Populat, Boston, MA USA.
   [Gephart, Jessica A.] Amer Univ, Dept Environm Sci, Washington, DC USA.
   [Allison, Edward H.; Phillips, Michael; Thilsted, Shakuntala H.] WorldFish, Bayan Lepas, Malaysia.
   [Bush, Simon R.] Wageningen Univ & Res, Wageningen, Netherlands.
   [Cao, Ling] Shanghai Jiao Tong Univ, Sch Oceanog, Shanghai, Peoples R China.
   [Cheung, William W. L.; Sumaila, U. Rashid; Wabnitz, Colette C. C.] Univ British Columbia, Inst Oceans & Fisheries, Vancouver, BC, Canada.
   [DeClerck, Fabrice] EAT, Oslo, Norway.
   [Fanzo, Jessica] Johns Hopkins Univ, Berman Inst Bioeth, Bloomberg Sch Publ Hlth, Washington, DC USA.
   [Fanzo, Jessica] Johns Hopkins Univ, Nitze Sch Adv Int Studies, Washington, DC USA.
   [Gelcich, Stefan] Pontificia Univ Catolica Chile, Inst Milenio Socio Ecol Costera, Santiago, Chile.
   [Gelcich, Stefan] Pontificia Univ Catolica Chile, Ctr Appl Ecol & Sustainabil, Santiago, Chile.
   [Kishore, Avinash] Int Food Policy Res Inst IFPRI, New Delhi, India.
   [Halpern, Benjamin S.] UC Santa Barbara, Natl Ctr Ecol Anal & Synth, Santa Barbara, CA USA.
   [Halpern, Benjamin S.] UC Santa Barbara, Bren Sch Environm Sci & Management, Santa Barbara, CA USA.
   [Hicks, Christina C.] Univ Lancaster, Lancaster Environm Ctr, Lancaster, England.
   [Little, David C.] Univ Stirling, Inst Aquaculture, Stirling, Scotland.
   [Micheli, Fiorenza] Stanford Univ, Oceans Dept, Hopkins Marine Stn, Pacific Grove, CA USA.
   [Naylor, Rosamond L.] Stanford Univ, Dept Earth Syst Sci, Stanford, CA USA.
   [Naylor, Rosamond L.] Stanford Univ, Ctr Food Secur & Environm, Stanford, CA USA.
   [Springmann, Marco] Univ Oxford, Oxford Martin Programme Future Food, Oxford, England.
   [Springmann, Marco] Univ Oxford, Nuffield Dept Populat Hlth, Oxford, England.
   [Sumaila, U. Rashid] Univ British Columbia, Sch Publ Policy & Global Affairs, Vancouver, BC, Canada.
   [Troell, Max] Royal Swedish Acad Sci, Beijer Inst Ecol Econ, Stockholm, Sweden.
C3 Stockholm University; Royal Swedish Academy of Sciences; Global Economic
   Dynamics & Biosphere - The Erling-Persson Family Academy Program;
   Stanford University; Harvard University; Harvard T.H. Chan School of
   Public Health; Harvard University; Harvard T.H. Chan School of Public
   Health; Harvard University; Harvard T.H. Chan School of Public Health;
   American University; CGIAR; Worldfish; Wageningen University & Research;
   Shanghai Jiao Tong University; University of British Columbia; Johns
   Hopkins University; Johns Hopkins Bloomberg School of Public Health;
   Johns Hopkins University; Pontificia Universidad Catolica de Chile;
   Pontificia Universidad Catolica de Chile; CGIAR; International Food
   Policy Research Institute (IFPRI); National Center for Ecological
   Analysis & Synthesis; University of California System; University of
   California Santa Barbara; University of California System; University of
   California Santa Barbara; Lancaster University; University of Stirling;
   Stanford University; Stanford University; Stanford University;
   University of Oxford; University of Oxford; University of British
   Columbia; Royal Swedish Academy of Sciences; Beijer Institute of
   Ecological Economics
RP Crona, BI (corresponding author), Stockholm Univ, Stockholm Resilience Ctr, Stockholm, Sweden.; Crona, BI (corresponding author), Royal Swedish Acad Sci, Global Econ Dynam & Biosphere, Stockholm, Sweden.
EM beatrice.crona@su.se
RI Troell, Max/I-1724-2019; Fanzo, Jessica/HCH-3533-2022; Hicks,
   Christina/M-6182-2015; Gephart, Jessica/HCH-3165-2022; Gelcich,
   Stefan/LSL-2212-2024; Cheung, William/F-5104-2013; Allison,
   Edward/JAC-5655-2023; Halpern, Benjamin/J-6141-2014; Wassénius,
   Emmy/AAK-3042-2021; Thilsted, Shakuntala/JPU-9977-2023; Crona,
   Beatrice/HHZ-3183-2022; Golden, Christopher/JPA-5431-2023; Sumaila,
   U./ABE-6475-2020
OI Micheli, Fiorenza/0000-0002-6865-1438; Golden,
   Christopher/0000-0002-2258-7493; Allison, Edward/0000-0003-4663-1396;
   Wassenius, Emmy/0000-0002-8756-1649; Crona,
   Beatrice/0000-0003-1617-4067; Springmann, Marco/0000-0001-6028-5712;
   Fanzo, Jessica/0000-0002-6760-1359; Thilsted,
   Shakuntala/0000-0002-4041-1651; Daw, Tim M./0000-0001-6635-9153;
   Tigchelaar, Michelle/0000-0001-7964-229X
FU Builders Initiative; MAVA Foundation; Oak Foundation; Walton Family
   Foundation; Erling Persson Family Foundation
FX This paper is part of the Blue Food Assessment
   (https://www.bluefood.earth), a comprehensive examination of the role of
   aquatic foods in building healthy, sustainable and equitable food
   systems. The assessment was supported by the Builders Initiative, the
   MAVA Foundation, the Oak Foundation and the Walton Family Foundation. We
   thank all scientific leaders of the Blue Food Assessment for their
   intellectual input on this paper, as well as S.?Maniatakou and
   G.?Parlato for research assistance. B.C. also acknowledges the generous
   support of the Erling Persson Family Foundation.
CR Abdelhamid AS, 2018, COCHRANE DB SYST REV, DOI 10.1002/14651858.CD003177.pub4
   Ainsworth R., 2021, FAO Fisheries and Aquaculture Circular, DOI 10.4060/cb2827en
   Allison EH, 2012, FISH FISH, V13, P14, DOI 10.1111/j.1467-2979.2011.00405.x
   [Anonymous], 2020, NATURE, V577, P293, DOI 10.1038/d41586-020-00086-5
   [Anonymous], 2012, WORLD DEV IND
   [Anonymous], OECD FAO AGR OUTLOOK
   [Anonymous], 2018, Continuous update project expert report 2018: diet, nutrition, physical activity and colorectal cancer
   Arthur RI, 2022, FISH FISH, V23, P109, DOI 10.1111/faf.12602
   Barange M, 2014, NAT CLIM CHANGE, V4, P211, DOI [10.1038/nclimate2119, 10.1038/NCLIMATE2119]
   Belton B, 2021, MAR POLICY, V129, DOI 10.1016/j.marpol.2021.104523
   Belton B, 2020, NAT SUSTAIN, V3, P677, DOI 10.1038/s41893-020-0540-7
   Bene C, 2015, FOOD SECUR, V7, P261, DOI 10.1007/s12571-015-0427-z
   Béné C, 2010, DEV POLICY REV, V28, P325, DOI 10.1111/j.1467-7679.2010.00486.x
   Bennett A, 2021, AMBIO, V50, P981, DOI 10.1007/s13280-020-01451-4
   Bergner D, 2009, CH CRC DATA MIN KNOW, P19
   Blake CE, 2021, GLOB FOOD SECUR-AGR, V28, DOI 10.1016/j.gfs.2021.100503
   Bogard JR, 2017, PLOS ONE, V12, DOI 10.1371/journal.pone.0175098
   Byrd KA, 2021, MATERN CHILD NUTR, V17, DOI 10.1111/mcn.13192
   Cheung WWL, 2018, GLOBAL CHANGE BIOL, V24, P5149, DOI 10.1111/gcb.14390
   Cisneros-Montemayor AM, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0166681
   Clapp J, 2021, NAT FOOD, V2, P404, DOI 10.1038/s43016-021-00297-7
   Clark MA, 2019, P NATL ACAD SCI USA, V116, P23357, DOI 10.1073/pnas.1906908116
   Clarke TM, 2021, DIVERS DISTRIB, V27, P65, DOI 10.1111/ddi.13181
   Cohen PJ, 2019, FRONT MAR SCI, V6, DOI 10.3389/fmars.2019.00171
   Cole SM, 2020, GEND TECHNOL DEV, V24, P48, DOI 10.1080/09718524.2020.1729480
   Dey MM, 2008, AUST J AGR RESOUR EC, V52, P321, DOI 10.1111/j.1467-8489.2008.00418.x
   Dubois P, 2014, AM ECON REV, V104, P832, DOI 10.1257/aer.104.3.832
   Fakhri M., 2020, SECRETARY UN GEN ASS
   FAO, 2022, The state of World Fisheries and Aquaculture 2022. Towards Blue Transformation, DOI [10.4060/ca9229en, 10.4060/cc0461en, DOI 10.4060/CC0461EN, DOI 10.4060/CA9229EN]
   Farmery AK, 2022, REV FISH BIOL FISHER, V32, P101, DOI 10.1007/s11160-021-09663-x
   Farmery AK, 2021, ONE EARTH, V4, P28, DOI 10.1016/j.oneear.2020.12.002
   Ferguson CE, 2022, MAR POLICY, V137, DOI 10.1016/j.marpol.2022.104954
   Fesenfeld LP, 2020, NAT FOOD, V1, DOI 10.1038/s43016-020-0047-4
   Fishery and Aquaculture Statistics, 2021, GLOB CAPT PROD 1950
   Gallet Craig A., 2009, Aquaculture Economics and Management, V13, P235, DOI 10.1080/13657300903123985
   Gephart Jessica A, 2021, Nature, V597, P360, DOI 10.1038/s41586-021-03889-2
   Gephart JA, 2020, REV FISH SCI AQUAC, V29, P122, DOI 10.1080/23308249.2020.1782342
   Gephart JA, 2017, GLOBAL ENVIRON CHANG, V42, P24, DOI 10.1016/j.gloenvcha.2016.11.003
   Golden C, 2016, NATURE, V534, P317, DOI 10.1038/534317a
   Golden CD, 2021, NATURE, V598, P315, DOI 10.1038/s41586-021-03917-1
   Guasch-Ferré M, 2019, CIRCULATION, V139, P1828, DOI 10.1161/CIRCULATIONAHA.118.035225
   Halpern BS, 2019, P NATL ACAD SCI USA, V116, P18152, DOI 10.1073/pnas.1913308116
   HAMBY DM, 1994, ENVIRON MONIT ASSESS, V32, P135, DOI 10.1007/BF00547132
   Hamilton-Hart N, 2016, MAR POLICY, V63, P166, DOI 10.1016/j.marpol.2015.03.020
   Hanich Q, 2018, MAR POLICY, V88, P279, DOI 10.1016/j.marpol.2017.11.011
   Heltberg R, 2009, GLOBAL ENVIRON CHANG, V19, P89, DOI 10.1016/j.gloenvcha.2008.11.003
   Henriksson PJG, 2021, ONE EARTH, V4, P1220, DOI 10.1016/j.oneear.2021.08.009
   Herforth A., 2020, 309369 FAO AGR DEV E
   Herrero M, 2021, LANCET PLANET HEALTH, V5, pE50, DOI 10.1016/S2542-5196(20)30277-1
   Hicks CC, 2022, NAT FOOD, V3, P851, DOI 10.1038/s43016-022-00618-4
   Hicks CC, 2019, NATURE, V574, P95, DOI 10.1038/s41586-019-1592-6
   Hilborn R, 2018, FRONT ECOL ENVIRON, V16, P329, DOI 10.1002/fee.1822
   Hua K, 2019, ONE EARTH, V1, P316, DOI 10.1016/j.oneear.2019.10.018
   Hulme M, 2020, ONE EARTH, V2, P309, DOI 10.1016/j.oneear.2020.03.005
   Kent G., 2003, FISH TRADE FOOD SECU
   Kittinger JN, 2021, CONSERV SCI PRACT, V3, DOI 10.1111/csp2.386
   Koehn JZ, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac3954
   Koehn JZ, 2020, J AGRIC FOOD SYST CO, V10, P171, DOI [0.5304/jafscd.2020.101.027, 10.5304/jafscd.2020.101.027]
   Koehn JZ, 2022, FISH FISH, V23, P125, DOI 10.1111/faf.12603
   Lam VWY, 2020, NAT REV EARTH ENV, V1, P440, DOI 10.1038/s43017-020-0071-9
   Leslie P, 2013, CURR ANTHROPOL, V54, P114, DOI 10.1086/669563
   Loring PA, 2019, MARE PUBL SER, V21, P55, DOI 10.1007/978-3-319-94938-3_4
   Mamun AA, 2021, FRONT SUSTAIN FOOD S, V5, DOI 10.3389/fsufs.2021.713140
   Manson JE, 2019, NEW ENGL J MED, V380, P23, DOI 10.1056/NEJMoa1811403
   McCay BJ, 2014, MAR POLICY, V44, P49, DOI 10.1016/j.marpol.2013.08.001
   Miller V, 2022, JAMA NETW OPEN, V5, DOI 10.1001/jamanetworkopen.2021.46705
   Moberg E, 2021, NAT FOOD, V2, P282, DOI 10.1038/s43016-021-00261-5
   Myers RA, 2003, NATURE, V423, P280, DOI 10.1038/nature01610
   Naylor RL, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-021-25516-4
   Naylor RL, 2021, NATURE, V591, P551, DOI 10.1038/s41586-021-03308-6
   Nutrition and Food Systems, 2017, REP HIGH LEV PAN EXP
   Ota Y, 2021, AQUAT CONSERV, V31, P1925, DOI 10.1002/aqc.3568
   Oyinlola MA, 2022, GLOBAL CHANGE BIOL, V28, P1315, DOI 10.1111/gcb.15991
   Parker RWR, 2018, NAT CLIM CHANGE, V8, P333, DOI 10.1038/s41558-018-0117-x
   Pomeroy RS, 2011, SMALL-SCALE FISHERIES MANAGEMENT: FRAMEWORKS AND APPROACHES FOR THE DEVELOPING WORLD, P1, DOI 10.1079/9781845936075.0000
   Poore J, 2018, SCIENCE, V360, P987, DOI 10.1126/science.aaq0216
   Popkin BM, 2004, INT J OBESITY, V28, pS2, DOI [10.1038/sj.ijo.0802804, 10.1038/sj.ijo.0802557]
   Richi EB, 2015, INT J VITAM NUTR RES, V85, P70, DOI 10.1024/0300-9831/a000224
   Robinson JPW, 2022, FISH FISH, V23, P800, DOI 10.1111/faf.12649
   Roda M.A. Perez, 2019, A third assessment of global marine fisheries discards, P78
   Roos E, 2021, POLICY OPTIONS SUSTA
   Roos N, 2007, J NUTR, V137, P1106, DOI 10.1093/jn/137.4.1106
   Ryckman T, 2021, NUTR REV, V79, P35, DOI 10.1093/nutrit/nuaa137
   Ryckman T, 2021, NUTR REV, V79, P52, DOI 10.1093/nutrit/nuaa139
   Selig ER, 2019, CONSERV LETT, V12, DOI 10.1111/conl.12617
   Shepon A, 2022, RESOUR CONSERV RECY, V181, DOI 10.1016/j.resconrec.2022.106260
   Short RE, 2021, NAT FOOD, V2, P733, DOI 10.1038/s43016-021-00363-0
   Song AM, 2019, MAR POLICY, V103, P19, DOI 10.1016/j.marpol.2019.02.017
   Sprague M, 2016, SCI REP-UK, V6, DOI 10.1038/srep21892
   Springmann M, 2020, BMJ-BRIT MED J, V370, DOI 10.1136/bmj.m2322
   Springmann M, 2018, LANCET PLANET HEALTH, V2, pE451, DOI [10.1016/S2542-5196(18)30206-7, 10.1016/s2542-5196(18)30206-7]
   Starling P, 2015, NUTRIENTS, V7, P2001, DOI 10.3390/nu7032001
   Stoll JS, 2018, FRONT MAR SCI, V5, DOI 10.3389/fmars.2018.00239
   Sumaila UR, 2020, FRONT MAR SCI, V7, DOI 10.3389/fmars.2020.00523
   Teh LCL, 2013, FISH FISH, V14, P77, DOI 10.1111/j.1467-2979.2011.00450.x
   Tezzo X, 2021, AGR HUM VALUES, V38, P73, DOI 10.1007/s10460-020-10037-5
   Thilsted SH, 2016, FOOD POLICY, V61, P126, DOI 10.1016/j.foodpol.2016.02.005
   Tigchelaar M, 2021, NAT FOOD, V2, P673, DOI 10.1038/s43016-021-00368-9
   Tlusty MF, 2019, GLOBAL ENVIRON CHANG, V59, DOI 10.1016/j.gloenvcha.2019.101991
   Tlusty MF, 2011, SUSTAINABILITY-BASEL, V3, P957, DOI 10.3390/su3070957
   Troell M, 2014, P NATL ACAD SCI USA, V111, P13257, DOI 10.1073/pnas.1404067111
   United Nations, 2015, No.A/RES/70/1.
   Van Anrooy R., 2006, REV CURRENT STATE WO
   van Putten I, 2019, FISH RES, V209, P14, DOI 10.1016/j.fishres.2018.09.007
   von Braun J, 2021, NATURE, V597, P28, DOI 10.1038/d41586-021-02331-x
   Weeratunge N, 2014, FISH FISH, V15, P255, DOI 10.1111/faf.12016
   Willett W, 2019, LANCET, V393, P447, DOI 10.1016/S0140-6736(18)31788-4
   Wolk A, 2017, J INTERN MED, V281, P106, DOI 10.1111/joim.12543
   Zeng LX, 2019, J ACAD NUTR DIET, V119, P1085, DOI 10.1016/j.jand.2019.04.004
NR 109
TC 47
Z9 48
U1 41
U2 189
PU NATURE PORTFOLIO
PI BERLIN
PA HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY
SN 0028-0836
EI 1476-4687
J9 NATURE
JI Nature
PD APR 6
PY 2023
VL 616
IS 7955
BP 104
EP +
DI 10.1038/s41586-023-05737-x
EA FEB 2023
PG 25
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA X3LD8
UT WOS:000940612400003
PM 36813964
OA Green Published, hybrid
HC Y
HP N
DA 2025-01-10
ER

PT J
AU Okumus, DE
   Terzi, F
AF Okumus, Deniz Erdem
   Terzi, Fatih
TI Reconsidering Urban Densification for Microclimatic Improvement:
   Planning and Design Strategies for Istanbul
SO ICONARP INTERNATIONAL JOURNAL OF ARCHITECTURE AND PLANNING
LA English
DT Article
DE Istanbul; spatial planning; urban density; urban design; urban heat
   island
ID LAND-SURFACE TEMPERATURE; HEAT-ISLAND; CLIMATE-CHANGE; BUILDING HEIGHT;
   CANYON GEOMETRY; COVER PATTERN; DENSITY; IMPACT; CITY; ENERGY
AB One of the key issues of the urban planning agenda is how urban density be decided in the spatial configurations of future neighbourhoods to overcome complex challenges such as urban warming. This paper aims to reconsider urban density as a spatial planning instrument to develop effective densification policies, planning and design strategies in terms of surface urban heat island (SUHI) mitigation in Istanbul. The quantitative research embraced a four-stage methodology including grid-based sampling design, decoding the taxonomy of urban density-matrix (UDM), land surface temperature mapping, and ANOVA tests. Tests were conducted on the UDM consisting of nine building typologies representing the horizontal and vertical urban density. The research indicated that the impact of urbanisation on SUHI can be mitigated by controlling densities and urban forms based on quantitative findings. The highest temperatures were recorded in areas with high-coverage-mid-rise and mid-coverage-mid-rise development. The different levels of SUHI in different building typologies having the same density indicated the mitigation potentials of the built-form in Istanbul's local urban warming. Low coverage and high-rise building forms were an optimal solution for mitigating SUHI in densely populated urban areas. The research gives insight into an ongoing debate among urban professionals in Istanbul concerning the impacts of density and the urban form for climate adaptation. It enables professionals to understand the impact of urban planning decisions on microclimate and integrate them into the operational processes. Considering quantitative research findings as a strong foundation for developing policy recommendations and using them as a guideline may create new opportunities for researchers, practitioners, and policymakers. The study has an original value for exploring design strategies to improve microclimate and promoting sustainable urban development.
C1 [Okumus, Deniz Erdem] Yildiz Tech Univ, City & Reg Planning Dept, Istanbul, Turkey.
   [Terzi, Fatih] Istanbul Tech Univ, Urban & Reg Planning Dept, Istanbul, Turkey.
C3 Yildiz Technical University; Istanbul Technical University
RP Okumus, DE (corresponding author), Yildiz Tech Univ, City & Reg Planning Dept, Istanbul, Turkey.
EM denizer@yildiz.edu.tr; terzifati@itu.edu.tr
RI Terzi, Fatih/O-1756-2013; Erdem Okumus, Deniz/AAZ-6710-2020
OI Terzi, Fatih/0000-0002-1292-576X; Erdem Okumus,
   Deniz/0000-0003-2671-0126
FU Scientific Research Projects Department of Istanbul Technical
   University, Istanbul, Turkey [42088]; Scientific and Technological
   Research Council of Turkey (TUBITAK)
FX This paper was produced from the PhD thesis conducted by the
   corresponding author under the supervision of the second author. The
   study conception and design were supported by the Scientific Research
   Projects Department of Istanbul Technical University, Istanbul, Turkey
   [grant number 42088]. The final manuscript has been completed by the
   support of the Scientific and Technological Research Council of Turkey
   (TUBITAK), 2214-A International Research Fellowship Program for Ph.D.
   Students.
CR ALEXANDER ER, 1993, J ARCHIT PLAN RES, V10, P181
   [Anonymous], 1993, KENTLESME POLITIKASI
   ARNFIELD AJ, 1990, PHYS GEOGR, V11, P220, DOI 10.1080/02723646.1990.10642404
   Arnfield AJ, 2003, INT J CLIMATOL, V23, P1, DOI 10.1002/joc.859
   ARNFIELD AJ, 1990, ENERG BUILDINGS, V14, P117, DOI 10.1016/0378-7788(90)90031-D
   Balçik FB, 2014, ENVIRON MONIT ASSESS, V186, P859, DOI 10.1007/s10661-013-3427-5
   Barsi JA, 2014, REMOTE SENS-BASEL, V6, P11607, DOI 10.3390/rs61111607
   Basar U. G., 2008, EVALUATION URBAN HEA, P37
   Blazejczyk K, 2013, GEOGR POL, V86, P5, DOI 10.7163/GPol.2013.1
   Bolen F., 2004, ITU A|Z, V1, P14
   C.S.B, 2018, IST IL 2017 YIL CEVR
   Chow WTL, 2012, B AM METEOROL SOC, V93, P517, DOI 10.1175/BAMS-D-11-00011.1
   Chun B, 2014, LANDSCAPE URBAN PLAN, V125, P76, DOI 10.1016/j.landurbplan.2014.01.016
   Corburn J, 2009, URBAN STUD, V46, P413, DOI 10.1177/0042098008099361
   Dihkan M, 2015, OCEAN COAST MANAGE, V118, P309, DOI 10.1016/j.ocecoaman.2015.03.008
   Ezber Y, 2007, INT J CLIMATOL, V27, P667, DOI 10.1002/joc.1420
   Feng X, 2016, BUILD ENVIRON, V95, P346, DOI 10.1016/j.buildenv.2015.09.019
   Gago EJ, 2013, RENEW SUST ENERG REV, V25, P749, DOI 10.1016/j.rser.2013.05.057
   Giridharan R, 2007, BUILD ENVIRON, V42, P3669, DOI 10.1016/j.buildenv.2006.09.011
   Guha S, 2018, EUR J REMOTE SENS, V51, P667, DOI 10.1080/22797254.2018.1474494
   Guo GH, 2016, ENVIRON MODELL SOFTW, V84, P427, DOI 10.1016/j.envsoft.2016.06.021
   Hamin EM, 2009, HABITAT INT, V33, P238, DOI 10.1016/j.habitatint.2008.10.005
   He BJ, 2020, SUSTAIN CITIES SOC, V60, DOI 10.1016/j.scs.2020.102289
   He BJ, 2020, SUSTAIN CITIES SOC, V55, DOI 10.1016/j.scs.2020.102028
   Hu YP, 2016, PROCEDIA ENGINEER, V169, P166, DOI 10.1016/j.proeng.2016.10.020
   I.B.B, 2018, IST BUYUKS BEL IST I
   Jiménez-Muñoz JC, 2006, REMOTE SENS ENVIRON, V103, P474, DOI 10.1016/j.rse.2006.04.012
   Jiménez-Muñoz JC, 2009, SENSORS-BASEL, V9, P768, DOI 10.3390/s90200768
   Kaya S, 2012, EKOLOJI, V21, P107, DOI 10.5053/ekoloji.2012.8412
   Kleerekoper L, 2012, RESOUR CONSERV RECY, V64, P30, DOI 10.1016/j.resconrec.2011.06.004
   Knuth S, 2020, URBAN GEOGR, V41, P1335, DOI 10.1080/02723638.2020.1850024
   Liao W, 2021, ENERG BUILDINGS, V244, DOI 10.1016/j.enbuild.2021.111027
   Lin PY, 2017, LANDSCAPE URBAN PLAN, V168, P48, DOI 10.1016/j.landurbplan.2017.09.024
   M.G.M, 2022, GEN STAT DAT PROV
   Masoumi HE, 2019, CITIES, V85, P170, DOI 10.1016/j.cities.2018.09.005
   Masson-Delmotte V, 2021, CLIMATE CHANGE 2021, DOI DOI 10.1017/9781009157896
   Metz B, 2002, CLIM POLICY, V2, P211, DOI 10.1016/S1469-3062(02)00037-2
   Mirzaei PA, 2010, BUILD ENVIRON, V45, P2192, DOI 10.1016/j.buildenv.2010.04.001
   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, 1987, BOUNDARY LAYER CLIMA, DOI [10.4324/9780203407219, DOI 10.4324/9780203407219]
   Okumus DE, 2021, SUSTAIN CITIES SOC, V73, DOI 10.1016/j.scs.2021.103128
   Pomponi F, 2021, NPJ URBAN SUSTAIN, V1, DOI 10.1038/s42949-021-00034-w
   Quattrochi D. A., 1995, REMOTE SENSING REV, V12, P255
   Salvati A, 2017, ENERG BUILDINGS, V146, P38, DOI 10.1016/j.enbuild.2017.04.025
   Santamouris M, 2013, RENEW SUST ENERG REV, V26, P224, DOI 10.1016/j.rser.2013.05.047
   Santamouris M., 2019, Decarbonising the Built Environment, P337, DOI DOI 10.1007/978-981-13-7940-6
   SCHEFFE H, 1953, BIOMETRIKA, V40, P87, DOI 10.1093/biomet/40.1-2.87
   SCHEFFE H., 1999, The analysis of variance, V72
   Shishegar Nastaran, 2013, Journal of Clean Energy Technologies, V1, P52, DOI 10.7763/JOCET.2013.V1.13
   Sobrino JA, 2004, REMOTE SENS ENVIRON, V90, P434, DOI 10.1016/j.rse.2004.02.003
   Song JC, 2020, LANDSCAPE URBAN PLAN, V198, DOI 10.1016/j.landurbplan.2020.103794
   Stewart ID, 2012, B AM METEOROL SOC, V93, P1879, DOI 10.1175/BAMS-D-11-00019.1
   Stromann-Andersen J, 2011, ENERG BUILDINGS, V43, P2011, DOI 10.1016/j.enbuild.2011.04.007
   Sun YW, 2019, REMOTE SENS-BASEL, V11, DOI 10.3390/rs11080959
   Suter G, 2022, INTEGR ENVIRON ASSES, V18, P1117
   Swart R, 2003, CLIM POLICY, V3, pS19, DOI 10.1016/j.clipol.2003.10.010
   Terzi F, 2012, URBAN STUD, V49, P1229, DOI 10.1177/0042098011410334
   Terzi F, 2009, EUR PLAN STUD, V17, P1559, DOI 10.1080/09654310903141797
   U.N.D.P, 2015, SURD KALK AM
   United Nations, 2015, No.A/RES/70/1.
   United Nations Habitat, 2019, STRAT PLAN 2020 2023
   USGS, 2019, NAS, V8, P97
   Voogt J.A., 1995, Thermal Remote Sensing of Urban Surface Temperatures
   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
   Voogt JA, 1997, J APPL METEOROL, V36, P1117, DOI 10.1175/1520-0450(1997)036<1117:CUST>2.0.CO;2
   Weng QH, 2004, REMOTE SENS ENVIRON, V89, P467, DOI 10.1016/j.rse.2003.11.005
   Weng QH, 2009, ISPRS J PHOTOGRAMM, V64, P335, DOI 10.1016/j.isprsjprs.2009.03.007
   Wong NH, 2011, SOL ENERGY, V85, P57, DOI 10.1016/j.solener.2010.11.002
   Xu HQ, 2004, J ENVIRON SCI-CHINA, V16, P276
   Yang F, 2010, BUILD ENVIRON, V45, P115, DOI 10.1016/j.buildenv.2009.05.010
   Yang J, 2019, SUSTAIN CITIES SOC, V47, DOI 10.1016/j.scs.2019.101487
   Yang JY, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12051737
   Yang XY, 2015, BUILD ENVIRON, V90, P146, DOI 10.1016/j.buildenv.2015.03.037
   Yilmaz S, 2022, BUILD ENVIRON, V219, DOI 10.1016/j.buildenv.2022.109210
   Yilmaz S, 2021, ENVIRON SCI POLLUT R, V28, P63837, DOI 10.1007/s11356-020-12009-y
   Yin CH, 2018, SCI TOTAL ENVIRON, V634, P696, DOI 10.1016/j.scitotenv.2018.03.350
   Zhao C., 2018, ISPRS ANN PHOTOGRAMM, V4
   Zheng Z, 2019, PHYS CHEM EARTH, V110, P149, DOI 10.1016/j.pce.2019.01.008
   Zhou WQ, 2011, LANDSCAPE URBAN PLAN, V102, P54, DOI 10.1016/j.landurbplan.2011.03.009
NR 82
TC 3
Z9 3
U1 3
U2 15
PU KONYA TECHNICAL UNIV, FAC ARCHITECTURE & DESIGN
PI KONYA
PA YENI ISTANBUL CAD NO 235-1 SELCUKLU, KONYA, Turkiye
SN 2147-9380
J9 ICONARP INT J ARCHIT
JI ICONARP Int. J. Archit. Plann.
PD DEC
PY 2022
VL 10
IS 2
BP 660
EP 687
DI 10.15320/ICONARP.2022.220
PG 28
WC Architecture
WE Emerging Sources Citation Index (ESCI)
SC Architecture
GA 7N1UN
UT WOS:000907131500011
OA gold
DA 2025-01-10
ER

PT J
AU Gabriele, M
   Brumana, R
   Previtali, M
   Cazzani, A
AF Gabriele, Marzia
   Brumana, Raffaella
   Previtali, Mattia
   Cazzani, Alberta
TI A combined GIS and remote sensing approach for monitoring climate
   change-related land degradation to support landscape preservation and
   planning tools: the Basilicata case study
SO APPLIED GEOMATICS
LA English
DT Article
DE Desertification; Land degradation; Agricultural landscape; Remote
   sensing; Marginal areas; Landscape conservation and planning
ID DESERTIFICATION RISK; SENSITIVE AREAS; TM IMAGERY; REGION; COVER;
   SOUTHERN; SOILS; URBAN; QUANTIFICATION; BIODIVERSITY
AB Monitoring landscapes in times of climate change patterns is a crucial issue, moreover, in the analyzed Mediterranean area, one of the major global candidates to develop land degradation stresses and consequential desertification phenomena. The research presented here is developed in the Mediterranean Basin, specifically in the Basilicata Region (southern Italy). The region is characterized by a very long history of intensive anthropization endowed by the high diversity of relatively geologically young soil types that consequentially created a vastity of spatial mosaics, which contributed to the composition of its archeolandscapes and endorsed some specific characteristics of the Mediterranean region, that evolved to respond to the human impact, including grazing, cultivation, and fires. Those key elements lead to the crucial issues of the region investigated here as soil erosion, salinization, loss of organic carbon, loss of biodiversity, and landslides, which together with deforestations, depopulation, and wildfires, define the exact framework of degradation and marginality. The evaluation of the sensitivity to degradation was performed (i) firstly at the regional scale, through a MEDALUS (Kosmas et al. 1999) approach, by implementing 6 main indicators (Soil Quality Index, Climate Quality Index, Vegetation Quality Index, Management Quality Index, Landslide Risk Index, Water Availability Index), and (ii) secondly at the mid-regional scale, through remote sensing by evaluation of the NDVI differencing thresholds in time intervals, covering a 20 years' time span going from 2000 to 2020. The study helped to define the in-progress land degradation trends and scenarios of the region, which must be the evidence-based foundation of integrated landscape planning strategies in marginal territories, implemented through a Decision Support System (DSS) based both on ecological, climate-adaptive, and environmental indicators, and on social, cultural, and economic development co-creation strategies.
C1 [Gabriele, Marzia; Brumana, Raffaella; Previtali, Mattia] Politecn Milan, Dept ABC, Via Giuseppe Ponzio 31, I-20133 Milan, Italy.
   [Cazzani, Alberta] Politecn Milan, Dept DaStU, Piazza Leonardo da Vinci 26, I-20133 Milan, Italy.
C3 Polytechnic University of Milan; Polytechnic University of Milan
RP Gabriele, M (corresponding author), Politecn Milan, Dept ABC, Via Giuseppe Ponzio 31, I-20133 Milan, Italy.
EM marzia.gabriele@polimi.it; raffaella.brumana@polimi.it;
   mattia.previtali@polimi.it; alberta.cazzani@polimi.it
OI gabriele, marzia/0000-0002-2357-9049
CR Agnoletti M., 2010, PAESAGGI RURALI STOR
   Agnoletti M, 2019, SUSTAINABILITY-BASEL, V11, DOI 10.3390/su11010235
   [Anonymous], PPR 2011 2021 PIANO
   [Anonymous], 2016, World Heritage and Tourism in a Changing Climate
   [Anonymous], 2000, European Landscape Convention
   [Anonymous], 2007, ATLANTE NAZIONALE AR
   [Anonymous], 1996, Remote Sensing of the Environment, DOI DOI 10.1080/02757259609532305
   Bakr N, 2012, ECOL INDIC, V15, P271, DOI 10.1016/j.ecolind.2011.09.034
   Becerril-Piña R, 2016, HUM ECOL RISK ASSESS, V22, P1323, DOI 10.1080/10807039.2016.1169914
   Canora F, 2015, J MAPS, V11, P745, DOI 10.1080/17445647.2014.980857
   Ceccarelli T., 2006, APAT CRA CNLSD MANUA, V40, P1
   Cherlet M., 2018, World Atlas of Desertification: Rethinking Land Degradation and Sustainable Land Management, DOI [10.2760/9205, DOI 10.2760/9205]
   Colantoni A, 2015, ECOL INDIC, V48, P599, DOI 10.1016/j.ecolind.2014.09.031
   Coluzzi R, 2019, GEOMAT NAT HAZ RISK, V10, P168, DOI 10.1080/19475705.2018.1513872
   Contador JFL, 2009, LAND DEGRAD DEV, V20, P129, DOI 10.1002/ldr.884
   Coppin P, 2004, INT J REMOTE SENS, V25, P1565, DOI 10.1080/0143116031000101675
   Cowling RM, 1996, TRENDS ECOL EVOL, V11, P362, DOI 10.1016/0169-5347(96)10044-6
   Crutzen PJ, 2002, NATURE, V415, P23, DOI 10.1038/415023a
   D'Emilio M, 2018, ENVIRON EARTH SCI, V77, DOI 10.1007/s12665-017-7206-4
   Desclée B, 2006, REMOTE SENS ENVIRON, V102, P1, DOI 10.1016/j.rse.2006.01.013
   Dunjó G, 2003, CATENA, V52, P23, DOI 10.1016/S0341-8162(02)00148-0
   Duscher K, 2015, HYDROGEOL J, V23, P1867, DOI 10.1007/s10040-015-1296-4
   Eastman JR, 2013, REMOTE SENS-BASEL, V5, P4799, DOI 10.3390/rs5104799
   Ferrara A., 2010, FOREST, V7, P133, DOI [10.3832/efor0627-007, DOI 10.3832/EFOR0627-007]
   Ferrara A, 2020, LAND DEGRAD DEV, V31, P1593, DOI 10.1002/ldr.3559
   Fontana F, 2004, RIFORMA FONDIARIA TR
   Francaviglia R, 2011, DESERTIFICAZIONE CON
   Freire S, 2009, J COASTAL RES, P1499
   Gabriele M, 2020, P 2020 3 INT C GEOIN, P62, DOI [10.1145/3397056.3397079, DOI 10.1145/3397056.3397079]
   Gambino R, 2010, RI VISTA, V14
   Gambino R., 1997, Conservare - Innovare. Paesaggio, Ambiente, Territorio
   Gassert F., 2014, AQUEDUCT GLOBAL MAPS
   Gokceoglu C, 1996, ENG GEOL, V44, P147, DOI 10.1016/S0013-7952(97)81260-4
   GREEN K, 1994, PHOTOGRAMM ENG REM S, V60, P331
   Grenon M., 1989, FUTURES MEDITERRANEA
   Haberl H, 2007, P NATL ACAD SCI USA, V104, P12942, DOI 10.1073/pnas.0704243104
   Hayes DJ, 2001, PHOTOGRAMM ENG REM S, V67, P1067
   Heywood VH, 1993, CONNAISSANCE CONSERV
   Hobbs RJ, 1996, RESTOR ECOL, V4, P93, DOI 10.1111/j.1526-100X.1996.tb00112.x
   Hoekstra AY, 2014, SCIENCE, V344, P1114, DOI 10.1126/science.1248365
   Howard A.D., 1994, Geomorphology of Desert Environments, P213, DOI [10.1007/978-94-015-8254-4_9, DOI 10.1007/978-94-015-8254-4_9]
   IGRAC (International Groundwater Resources Assessment Centre) UNESCO-IHP (UNESCO International Hydrological Programme), 2015, TRANSB AQ WORLD
   INEA, 1999, CONT SCEN SVIL AGR R
   Jakob M., 2009, Il paesaggio
   Jensen JR, 1996, INTRO DIGITAL IMAGE, V2
   Karamesouti M, 2018, CATENA, V167, P266, DOI 10.1016/j.catena.2018.04.042
   Kayser B, 1958, THESIS PARIS
   King R, 1990, GEOGR
   Kosmas C, 2000, CATENA, V40, P3, DOI 10.1016/S0341-8162(99)00061-2
   Kosmas C, 2014, ENVIRON MANAGE, V54, P951, DOI 10.1007/s00267-013-0109-6
   Kosmas C., 1999, MEDALUS PROJECT MEDI, P31
   Kundu A, 2017, NAT HAZARDS, V86, P297, DOI 10.1007/s11069-016-2689-y
   Lacava P, 1903, BASILICATA LETTERA A
   Ladisa G, 2012, PHYS CHEM EARTH, V49, P103, DOI 10.1016/j.pce.2011.05.007
   Lamqadem AA, 2018, SENSORS-BASEL, V18, DOI 10.3390/s18072230
   Latham J., 2014, Global Land Cover SHARE, P1
   Le Houerou HN, 1981, ECOSYSTEMS WORLD
   Lee EJ, 2019, FOR SCI TECHNOL, V15, P210, DOI 10.1080/21580103.2019.1667880
   Lu DS, 2004, PHOTOGRAMM ENG REM S, V70, P723, DOI 10.14358/PERS.70.6.723
   Lyon JG, 1998, PHOTOGRAMM ENG REM S, V64, P143
   Macleod RD, 1998, PHOTOGRAMM ENG REM S, V64, P207
   Mancino G, 2013, IFOREST, V7, P75, DOI 10.3832/ifor0909-007
   Martinez-Austria P.F., 2018, Extreme Weather. IntechOpen, DOI DOI 10.5772/INTECHOPEN.75559
   Mas JF, 1999, INT J REMOTE SENS, V20, P139, DOI 10.1080/014311699213659
   Mendelsohn R, 2003, LAND ECON, V79, P328, DOI 10.2307/3147020
   Montanarella L, 2008, 15 INT C INT SOIL CO, V18
   MUCHONEY DM, 1994, PHOTOGRAMM ENG REM S, V60, P1243
   NAVEH Z, 1990, MANS ROLE IN THE SHAPING OF THE EASTERN MEDITERRANEAN LANDSCAPE, P43
   OLDEMAN LR, 1993, GEODERMA, V60, P309, DOI 10.1016/0016-7061(93)90033-H
   Pachauri AK, 1998, ENVIRON GEOL, V36, P325, DOI 10.1007/s002540050348
   Pan JH, 2013, NAT HAZARDS, V68, P915, DOI 10.1007/s11069-013-0665-3
   Paskoff R, 1999, OCEAN COAST MANAGE, V42, P105, DOI 10.1016/S0964-5691(98)00048-9
   Phillips CP, 1998, APPL GEOGR, V18, P243, DOI 10.1016/S0143-6228(98)00005-8
   Piccarreta M, 2006, CATENA, V65, P138, DOI 10.1016/j.catena.2005.11.005
   Ponce-Hernandez R., 2004, Methodological Framework for Land Degradation Assessment in Drylands (LADA)
   Pravalie R, 2017, CATENA, V158, P309, DOI 10.1016/j.catena.2017.07.006
   Pravalie R, 2017, CATENA, V153, P114, DOI [10.1016/j.catena.2017.02.011, 10.1016/j.catena2017.02.011]
   Prenzel B, 2004, PROG PLANN, V61, P281, DOI 10.1016/S0305-9006(03)00065-5
   Prince SD, 2016, SPRING EARTH SYST SC, P225, DOI 10.1007/978-3-642-16014-1_9
   Pu R, 2008, ENVIRON MONIT ASSESS, V140, P15, DOI 10.1007/s10661-007-9843-7
   Rendell HM., 1986, DESERTIFICATION EURO, P184, DOI 10.1007/978-94-009-4648-4_19
   Revetria R, 2019, 2019 SPRING SIMULATION CONFERENCE (SPRINGSIM), DOI 10.23919/springsim.2019.8732917
   Reynolds J.F., 2002, Global Desertification: Do Humans Cause Deserts?, P1
   Reynolds JF, 2007, SCIENCE, V316, P847, DOI 10.1126/science.1131634
   Rouget M, 2003, BIOL CONSERV, V112, P63, DOI 10.1016/S0006-3207(02)00395-6
   Rouse J.W., 1974, Monitoring vegetation systems in the great plains with ERTS
   Sala OE, 2000, SCIENCE, V287, P1770, DOI 10.1126/science.287.5459.1770
   Salvati L, 2013, APPL ECOL ENV RES, V11, P611, DOI 10.15666/aeer/1104_611627
   Salvati L, 2008, IRRIG DRAIN, V57, P507, DOI 10.1002/ird.380
   Salvati L, 2011, APPL GEOGR, V31, P223, DOI 10.1016/j.apgeog.2010.04.006
   Salvati L, 2010, ECOL ECON, V69, P511, DOI 10.1016/j.ecolecon.2009.08.025
   Salvia R, 2019, LAND-BASEL, V8, DOI 10.3390/land8120191
   SARKAR S, 1995, MT RES DEV, V15, P301, DOI 10.2307/3673806
   SCHLESINGER WH, 1990, SCIENCE, V247, P1043, DOI 10.1126/science.247.4946.1043
   Schwartz MW, 2006, BIOL CONSERV, V127, P282, DOI 10.1016/j.biocon.2005.05.017
   Sereni Emilio., 1961, Storia del paesaggio agrario italiano
   Serra P, 2014, APPL GEOGR, V55, P71, DOI 10.1016/j.apgeog.2014.09.005
   Singh A., 1986, Remote Sensing and Tropical Land Management, V44, P273, DOI DOI 10.1080/10106048809354188
   Sonnino A, 1998, ATT 2 FOR INT POL EU
   Spinoni J, 2015, INT J CLIMATOL, V35, P2210, DOI 10.1002/joc.4124
   Steinfeld H., 2006, Renewable Resources Journal, V24, P15
   Sulla-Menashe D, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aa9b88
   Symeonakis E, 2016, LAND DEGRAD DEV, V27, P1562, DOI 10.1002/ldr.2285
   Tanrivermis H, 2003, J ARID ENVIRON, V54, P553, DOI 10.1006/jare.2002.1078
   Tavares JDP, 2015, CATENA, V128, P214, DOI 10.1016/j.catena.2014.10.005
   Tengberg A., 2002, LAND DEGRADATION ASS
   Trotta C, 2015, REND LINCEI-SCI FIS, V26, pS421, DOI 10.1007/s12210-014-0362-5
   United Nations Convention to Combat Desertification (Secretariat), 1999, UN CONV COMB DES THO
   Vieira RMSP, 2015, SOLID EARTH, V6, P347, DOI 10.5194/se-6-347-2015
   Wachal D. J., 2000, GeoJournal, V51, P245, DOI 10.1023/A:1017524604463
   Wilson G. A., 2005, Unravelling desertification: policies and actor networks in Southern Europe
   Zambon I, 2017, AGRICULTURE-BASEL, V7, DOI 10.3390/agriculture7070056
   Zdruli P, 2017, ANTHROP POL ECON SOC, V15, P13, DOI 10.1007/978-3-319-45035-3_2
   [曾永年 ZENG YongNian], 2006, [地理科学, Scientia Geographica Sinica], V26, P75
NR 114
TC 19
Z9 20
U1 0
U2 8
PU SPRINGER HEIDELBERG
PI HEIDELBERG
PA TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
SN 1866-9298
EI 1866-928X
J9 APPL GEOMAT
JI Appl. Geomat.
PD SEP
PY 2023
VL 15
IS 3
SI SI
BP 497
EP 532
DI 10.1007/s12518-022-00437-z
EA JUL 2022
PG 36
WC Remote Sensing
WE Emerging Sources Citation Index (ESCI)
SC Remote Sensing
GA R5CG1
UT WOS:000830369000001
OA hybrid
DA 2025-01-10
ER

PT J
AU Bradford, MA
   Wood, SA
   Addicott, ET
   Fenichel, EP
   Fields, N
   González-Rivero, J
   Jevon, F
   Maynard, DS
   Oldfield, EE
   Polussa, A
   Ward, EB
   Wieder, WR
AF Bradford, Mark A.
   Wood, Stephen A.
   Addicott, Ethan T.
   Fenichel, Eli P.
   Fields, Nicholas
   Gonzalez-Rivero, Javier
   Jevon, Fiona, V
   Maynard, Daniel S.
   Oldfield, Emily E.
   Polussa, Alexander
   Ward, Elisabeth B.
   Wieder, William R.
TI Quantifying microbial control of soil organic matter dynamics at
   macrosystem scales
SO BIOGEOCHEMISTRY
LA English
DT Article
DE Forecasting; Functional redundancy; Jensen&#8217; s Inequality; Logical
   inference fallacies; Multilevel models; Soil carbon
ID LEAF-LITTER DECOMPOSITION; EARTH SYSTEM MODELS; BACTERIAL COMMUNITIES;
   TEMPERATURE ADAPTATION; VEGETATION MODEL; CARBON STORAGE; SPECIES POOLS;
   CLIMATE; DIVERSITY; ECOLOGY
AB Soil organic matter (SOM) stocks, decomposition and persistence are largely the product of controls that act locally. Yet the controls are shaped and interact at multiple spatiotemporal scales, from which macrosystem patterns in SOM emerge. Theory on SOM turnover recognizes the resulting spatial and temporal conditionality in the effect sizes of controls that play out across macrosystems, and couples them through evolutionary and community assembly processes. For example, climate history shapes plant functional traits, which in turn interact with contemporary climate to influence SOM dynamics. Selection and assembly also shape the functional traits of soil decomposer communities, but it is less clear how in turn these traits influence temporal macrosystem patterns in SOM turnover. Here, we review evidence that establishes the expectation that selection and assembly should generate decomposer communities across macrosystems that have distinct functional effects on SOM dynamics. Representation of this knowledge in soil biogeochemical models affects the magnitude and direction of projected SOM responses under global change. Yet there is high uncertainty and low confidence in these projections. To address these issues, we make the case that a coordinated set of empirical practices are required which necessitate (1) greater use of statistical approaches in biogeochemistry that are suited to causative inference; (2) long-term, macrosystem-scale, observational and experimental networks to reveal conditionality in effect sizes, and embedded correlation, in controls on SOM turnover; and (3) use of multiple measurement grains to capture local- and macroscale variation in controls and outcomes, to avoid obscuring causative understanding through data aggregation. When employed together, along with process-based models to synthesize knowledge and guide further empirical work, we believe these practices will rapidly advance understanding of microbial controls on SOM and improve carbon cycle projections that guide policies on climate adaptation and mitigation.
C1 [Bradford, Mark A.; Wood, Stephen A.; Addicott, Ethan T.; Fenichel, Eli P.; Fields, Nicholas; Gonzalez-Rivero, Javier; Jevon, Fiona, V; Oldfield, Emily E.; Polussa, Alexander; Ward, Elisabeth B.] Yale Univ, Yale Sch Environm, 195 Prospect St, New Haven, CT 06511 USA.
   [Wood, Stephen A.] Nature Conservancy, 1815 N Lynn St, Arlington, VA USA.
   [Maynard, Daniel S.] Swiss Fed Inst Technol, Inst Integrat Biol, Univ Str 16, CH-8006 Zurich, Switzerland.
   [Wieder, William R.] Natl Ctr Atmospher Res, Climate & Global Dynam Lab, POB 3000, Boulder, CO 80307 USA.
   [Wieder, William R.] Univ Colorado, Inst Arctic & Alpine Res, Boulder, CO 80309 USA.
C3 Yale University; Nature Conservancy; Swiss Federal Institutes of
   Technology Domain; ETH Zurich; National Center Atmospheric Research
   (NCAR) - USA; University of Colorado System; University of Colorado
   Boulder
RP Bradford, MA (corresponding author), Yale Univ, Yale Sch Environm, 195 Prospect St, New Haven, CT 06511 USA.
EM mark.bradford@yale.edu
RI Jevon, Fiona/ABB-9955-2020; Wieder, William/AAY-3338-2020; Addicott,
   Ethan/JQI-8784-2023; Wood, Stephen/A-1928-2017; Bradford,
   Mark/G-3850-2012
OI Maynard, Daniel/0000-0003-0142-9100; WIEDER,
   WILLIAM/0000-0001-7116-1985; Bradford, Mark/0000-0002-2022-8331
FU U.S. National Science Foundation [DEB-1926482, DEB-1926413]; U.S.
   Department of Energy [BSS DE-SC0016364]
FX MAB, AP, SAW, WRW, NF, JGR and FJ were supported by the U.S. National
   Science Foundation's Macrosystem Biology and NEON-Enabled Science
   program grants DEB-1926482 and DEB-1926413. WRW was supported by the
   U.S. Department of Energy under award number BSS DE-SC0016364.
CR Abramoff R, 2018, BIOGEOCHEMISTRY, V137, P51, DOI 10.1007/s10533-017-0409-7
   Abramoff RZ, 2019, GLOBAL BIOGEOCHEM CY, V33, P761, DOI 10.1029/2018GB006001
   Adhikari K, 2020, GEODERMA, V375, DOI 10.1016/j.geoderma.2020.114472
   Aerts R, 1997, OIKOS, V79, P439, DOI 10.2307/3546886
   AGREN GI, 1991, ECOL APPL, V1, P118, DOI 10.2307/1941806
   Albright MBN, 2020, FEMS MICROBIOL ECOL, V96, DOI 10.1093/femsec/fiaa135
   Allison SD, 2008, P NATL ACAD SCI USA, V105, P11512, DOI 10.1073/pnas.0801925105
   [Anonymous], 2002, Biochemical Adaptation
   Anthony MA, 2020, ONE EARTH, V2, P349, DOI 10.1016/j.oneear.2020.03.006
   Arnqvist G, 2020, TRENDS ECOL EVOL, V35, P329, DOI 10.1016/j.tree.2019.12.004
   Arora VK, 2013, J CLIMATE, V26, P5289, DOI 10.1175/JCLI-D-12-00494.1
   Averill C, 2016, GLOBAL CHANGE BIOL, V22, P1957, DOI 10.1111/gcb.13219
   Ayres E, 2009, SOIL BIOL BIOCHEM, V41, P606, DOI 10.1016/j.soilbio.2008.12.022
   Bárcenas-Moreno G, 2009, GLOBAL CHANGE BIOL, V15, P2950, DOI 10.1111/j.1365-2486.2009.01882.x
   Baumberger C, 2017, WIRES CLIM CHANGE, V8, DOI 10.1002/wcc.454
   Baym M, 2016, SCIENCE, V353, P1147, DOI 10.1126/science.aag0822
   Berhe AA, 2018, ANNU REV EARTH PL SC, V46, P521, DOI [10.1146/annurev-earth-082517-010018, 10.1146/annurev-earth-082517010018]
   Bestelmeyer BT, 2011, ECOSPHERE, V2, DOI 10.1890/ES11-00216.1
   Betancourt Michael, 2017, ARXIV
   Blankinship JC, 2018, BIOGEOCHEMISTRY, V140, P1, DOI 10.1007/s10533-018-0478-2
   Bolnick DI, 2011, TRENDS ECOL EVOL, V26, P183, DOI 10.1016/j.tree.2011.01.009
   Bonan GB, 2002, GLOBAL BIOGEOCHEM CY, V16, DOI 10.1029/2000GB001360
   Bonan GB, 2013, GLOBAL CHANGE BIOL, V19, P957, DOI 10.1111/gcb.12031
   BOND WJ, 1989, BIOL J LINN SOC, V36, P227, DOI 10.1111/j.1095-8312.1989.tb00492.x
   Bradford MA, 2006, SCALING AND UNCERTAINTY ANALYSIS IN ECOLOGY: METHODS AND APPLICATIONS, P109, DOI 10.1007/1-4020-4663-4_6
   Bradford MA, 2019, NAT ECOL EVOL, V3, P223, DOI 10.1038/s41559-018-0771-4
   Bradford MA, 2017, NAT ECOL EVOL, V1, P1836, DOI 10.1038/s41559-017-0367-4
   Bradford MA, 2016, NAT CLIM CHANGE, V6, P751, DOI [10.1038/NCLIMATE3071, 10.1038/nclimate3071]
   Bradford MA, 2016, J ECOL, V104, P229, DOI 10.1111/1365-2745.12507
   Bradford MA, 2014, NAT CLIM CHANGE, V4, P625, DOI [10.1038/NCLIMATE2251, 10.1038/nclimate2251]
   Buchkowski RW, 2017, ECOL LETT, V20, P231, DOI 10.1111/ele.12712
   Bünemann EK, 2018, SOIL BIOL BIOCHEM, V120, P105, DOI 10.1016/j.soilbio.2018.01.030
   Burnham KP, 2004, SOCIOL METHOD RES, V33, P261, DOI 10.1177/0049124104268644
   Buzzard V, 2019, NAT ECOL EVOL, V3, P1298, DOI 10.1038/s41559-019-0954-7
   Cash DW, 2006, ECOL SOC, V11
   Chadwick KD, 2020, METHODS ECOL EVOL, V11, P1492, DOI 10.1111/2041-210X.13463
   Veen GF, 2019, FRONT ENV SCI-SWITZ, V7, DOI 10.3389/fenvs.2019.00168
   Clark AT, 2020, J ECOL, V108, P774, DOI 10.1111/1365-2745.13316
   Clark JS, 2010, SCIENCE, V327, P1129, DOI 10.1126/science.1183506
   Cline LC, 2014, ENVIRON MICROBIOL, V16, P1538, DOI 10.1111/1462-2920.12281
   Cornwell WK, 2008, ECOL LETT, V11, P1065, DOI 10.1111/j.1461-0248.2008.01219.x
   Cotrufo MF, 2019, NAT GEOSCI, V12, P989, DOI 10.1038/s41561-019-0484-6
   Crowther TW, 2019, SCIENCE, V365, P772, DOI 10.1126/science.aav0550
   Crowther TW, 2015, P NATL ACAD SCI USA, V112, P7033, DOI 10.1073/pnas.1502956112
   Crowther TW, 2014, FRONT MICROBIOL, V5, DOI 10.3389/fmicb.2014.00579
   Currie WS, 2010, GLOBAL CHANGE BIOL, V16, P1744, DOI 10.1111/j.1365-2486.2009.02086.x
   Dacal M, 2019, NAT ECOL EVOL, V3, P232, DOI 10.1038/s41559-018-0770-5
   Deeks JJ., 2020, COCHRANE HDB SYSTEMA
   Delgado-Baquerizo M, 2017, SCI ADV, V3, DOI 10.1126/sciadv.1602008
   Denny M, 2017, J EXP BIOL, V220, P139, DOI 10.1242/jeb.140368
   Dickie IA, 2012, ECOL LETT, V15, P133, DOI 10.1111/j.1461-0248.2011.01722.x
   Doetterl S, 2015, NAT GEOSCI, V8, P780, DOI [10.1038/ngeo2516, 10.1038/NGEO2516]
   Domeignoz-Horta LA, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-17502-z
   Evans S. E., 2012, Biogeochemistry, V109, P101, DOI 10.1007/s10533-011-9638-3
   Evans SE, 2014, ECOLOGY, V95, P110, DOI 10.1890/13-0500.1
   Evans SE, 2014, ECOL LETT, V17, P155, DOI 10.1111/ele.12206
   Faber J, 2018, SOIL BIOL BIOCHEM, V123, P250, DOI 10.1016/j.soilbio.2018.05.010
   Fei SL, 2016, LANDSCAPE ECOL, V31, P1, DOI 10.1007/s10980-015-0315-0
   Ferraro PJ, 2019, P NATL ACAD SCI USA, V116, P5311, DOI 10.1073/pnas.1805563115
   Firn J, 2019, NAT ECOL EVOL, V3, P400, DOI 10.1038/s41559-018-0790-1
   Fisher RA, 2015, GEOSCI MODEL DEV, V8, P3593, DOI 10.5194/gmd-8-3593-2015
   Fisher RA, 2020, J ADV MODEL EARTH SY, V12, DOI 10.1029/2018MS001453
   Fisher RA, 2018, GLOBAL CHANGE BIOL, V24, P35, DOI 10.1111/gcb.13910
   Fitch AA, 2020, FRONT FOR GLOB CHANG, V3, DOI 10.3389/ffgc.2020.569945
   Friedlingstein P, 2006, J CLIMATE, V19, P3337, DOI 10.1175/JCLI3800.1
   Fukami T, 2015, ANNU REV ECOL EVOL S, V46, P1, DOI 10.1146/annurev-ecolsys-110411-160340
   Funk JL, 2017, BIOL REV, V92, P1156, DOI 10.1111/brv.12275
   Geisen S, 2021, ISME J, V15, P618, DOI 10.1038/s41396-020-00792-y
   Gelman A, 2007, Q J POLIT SCI, V2, P345, DOI 10.1561/100.00006026
   Gerber, 2020, ECOLOGY
   German DP, 2012, GLOBAL CHANGE BIOL, V18, P1468, DOI 10.1111/j.1365-2486.2011.02615.x
   German DP, 2011, ECOLOGY, V92, P1471, DOI 10.1890/10-2028.1
   Gholz HL, 2000, GLOBAL CHANGE BIOL, V6, P751, DOI 10.1046/j.1365-2486.2000.00349.x
   Glassman SI, 2018, P NATL ACAD SCI USA, V115, P11994, DOI 10.1073/pnas.1811269115
   Hamil KAD, 2016, LANDSCAPE ECOL, V31, P7, DOI 10.1007/s10980-015-0288-z
   Hättenschwiler S, 2005, P NATL ACAD SCI USA, V102, P1519, DOI 10.1073/pnas.0404977102
   Hawkes CV, 2020, SOIL BIOL BIOCHEM, V143, DOI 10.1016/j.soilbio.2020.107752
   Heffernan JB, 2014, FRONT ECOL ENVIRON, V12, P5, DOI 10.1890/130017
   Hodapp D, 2018, ECOL LETT, V21, P1364, DOI 10.1111/ele.13102
   Hoffman MD, 2014, J MACH LEARN RES, V15, P1593
   HOLLAND PW, 1986, J AM STAT ASSOC, V81, P945, DOI 10.2307/2289064
   Isaac NJB, 2020, TRENDS ECOL EVOL, V35, P56, DOI 10.1016/j.tree.2019.08.006
   JENKINSON DS, 1977, SOIL SCI, V123, P298, DOI 10.1097/00010694-197705000-00005
   Jian JS, 2018, GLOBAL CHANGE BIOL, V24, P4143, DOI 10.1111/gcb.14301
   Jian SY, 2020, NAT COMMUN, V11, DOI 10.1038/s41467-020-19428-y
   Jobbágy EG, 2000, ECOL APPL, V10, P423, DOI 10.2307/2641104
   Kearney MR, 2020, METHODS ECOL EVOL, V11, P38, DOI 10.1111/2041-210X.13330
   Keiser AD, 2016, ECOSYSTEMS, V19, P50, DOI 10.1007/s10021-015-9917-2
   Keiser AD, 2014, J ECOL, V102, P603, DOI 10.1111/1365-2745.12220
   Keuskamp JA, 2013, METHODS ECOL EVOL, V4, P1070, DOI 10.1111/2041-210X.12097
   Knutti R, 2013, NAT CLIM CHANGE, V3, P369, DOI [10.1038/nclimate1716, 10.1038/NCLIMATE1716]
   Koven CD, 2013, NAT GEOSCI, V6, P452, DOI [10.1038/ngeo1801, 10.1038/NGEO1801]
   Kraft NJB, 2015, FUNCT ECOL, V29, P592, DOI 10.1111/1365-2435.12345
   Kuppler J, 2020, GLOBAL ECOL BIOGEOGR, V29, P992, DOI 10.1111/geb.13077
   Lancaster LT, 2020, P NATL ACAD SCI USA, V117, P13580, DOI 10.1073/pnas.1918162117
   Laubmeier AN, 2020, TRENDS ECOL EVOL, V35, P1090, DOI 10.1016/j.tree.2020.08.006
   LAUENROTH WK, 1992, ECOL APPL, V2, P397, DOI 10.2307/1941874
   Lehmann J, 2020, NAT GEOSCI, V13, P529, DOI 10.1038/s41561-020-0612-3
   Lembrechts JJ, 2020, GLOBAL CHANGE BIOL, V26, P337, DOI 10.1111/gcb.14942
   Lennon JT, 2012, ECOLOGY, V93, P1867, DOI 10.1890/11-1745.1
   LEVIN SA, 1992, ECOLOGY, V73, P1943, DOI 10.2307/1941447
   Loescher H, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0083216
   Luo ZK, 2013, ECOL APPL, V23, P408, DOI 10.1890/12-0672.1
   Lustenhouwer N, 2020, P NATL ACAD SCI USA, V117, P11551, DOI [10.1073/pnas.1909166117, 10.1073/pnas.1909166117/-/DCSupplemental.]
   Mac Nally R, 2018, J APPL ECOL, V55, P1441, DOI 10.1111/1365-2664.13060
   Malik AA, 2020, ISME J, V14, P1, DOI 10.1038/s41396-019-0510-0
   Manski Charles F, 2008, IDENTIFICATION PREDI
   Martiny JBH, 2006, NAT REV MICROBIOL, V4, P102, DOI 10.1038/nrmicro1341
   Maynard DS, 2019, NAT MICROBIOL, V4, P846, DOI 10.1038/s41564-019-0361-5
   Maynard DS, 2017, P NATL ACAD SCI USA, V114, P11464, DOI 10.1073/pnas.1712211114
   McGill BJ, 2019, GLOBAL ECOL BIOGEOGR, V28, P6, DOI 10.1111/geb.12855
   Meyer KM, 2010, BASIC APPL ECOL, V11, P563, DOI 10.1016/j.baae.2010.08.001
   Milcu A, 2018, NAT ECOL EVOL, V2, P279, DOI 10.1038/s41559-017-0434-x
   Moher D, 2010, INT J SURG, V8, P336, DOI [10.1371/journal.pmed.1000097, 10.1136/bmj.b2700, 10.1016/j.ijsu.2010.02.007, 10.1136/bmj.i4086, 10.1136/bmj.b2535, 10.1016/j.ijsu.2010.07.299, 10.1186/2046-4053-4-1]
   Moorcroft PR, 2001, ECOL MONOGR, V71, P557, DOI 10.1890/0012-9615(2001)071[0557:AMFSVD]2.0.CO;2
   Morrissey EM, 2019, NAT ECOL EVOL, V3, P1064, DOI 10.1038/s41559-019-0918-y
   Mouquet N, 2015, J APPL ECOL, V52, P1293, DOI 10.1111/1365-2664.12482
   Munafò MR, 2018, NATURE, V553, P399, DOI 10.1038/d41586-018-01023-3
   Naeem S, 2001, COM ECO SYS, P223
   Naylor D, 2020, ANNU REV ENV RESOUR, V45, P29, DOI 10.1146/annurev-environ-012320-082720
   Neal AL, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-67631-0
   Nunan N, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0249
   Oldfield EE, 2019, SOIL-GERMANY, V5, P15, DOI 10.5194/soil-5-15-2019
   Oster E, 2019, J BUS ECON STAT, V37, P187, DOI 10.1080/07350015.2016.1227711
   PARTON WJ, 1987, SOIL SCI SOC AM J, V51, P1173, DOI 10.2136/sssaj1987.03615995005100050015x
   Pavlick R, 2013, BIOGEOSCIENCES, V10, P4137, DOI 10.5194/bg-10-4137-2013
   Peay KG, 2012, MOL ECOL, V21, P4122, DOI 10.1111/j.1365-294X.2012.05666.x
   Peters DPC, 2007, ECOSYSTEMS, V10, P790, DOI 10.1007/s10021-007-9055-6
   Pioli S, 2020, SOIL BIOL BIOCHEM, V144, DOI 10.1016/j.soilbio.2020.107778
   Poulter B, 2015, GEOSCI MODEL DEV, V8, P2315, DOI 10.5194/gmd-8-2315-2015
   Prosser JI, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0240
   Rasmussen C, 2018, BIOGEOCHEMISTRY, V137, P297, DOI 10.1007/s10533-018-0424-3
   RASTETTER EB, 1992, ECOL APPL, V2, P55, DOI 10.2307/1941889
   Reich PB, 2014, J ECOL, V102, P275, DOI 10.1111/1365-2745.12211
   Rinnan R, 2009, GLOBAL CHANGE BIOL, V15, P2615, DOI 10.1111/j.1365-2486.2009.01959.x
   Robinson WS, 1950, AM SOCIOL REV, V15, P351, DOI 10.1093/ije/dyn357
   Rose KC, 2017, ECOL LETT, V20, P147, DOI 10.1111/ele.12717
   Rousk J, 2012, GLOBAL CHANGE BIOL, V18, P3252, DOI 10.1111/j.1365-2486.2012.02764.x
   Rudgers JA, 2018, ECOLOGY, V99, P576, DOI 10.1002/ecy.2136
   Ruel JJ, 1999, TRENDS ECOL EVOL, V14, P361, DOI 10.1016/S0169-5347(99)01664-X
   Sarkar Sahotra., 2016, The Stanford Encyclopedia of Philosophy
   Schimel JP, 2012, FRONT MICROBIOL, V3, DOI 10.3389/fmicb.2012.00348
   Schmidt MWI, 2011, NATURE, V478, P49, DOI 10.1038/nature10386
   Schmitz 0.J., 2010, Resolving ecosystem complexity
   Shiffrin RM, 2016, P NATL ACAD SCI USA, V113, P7308, DOI 10.1073/pnas.1608845113
   Shiklomanov AN, 2020, ECOL APPL, V30, DOI 10.1002/eap.2064
   Sierra CA, 2011, BIOGEOSCIENCES, V8, P951, DOI 10.5194/bg-8-951-2011
   Smith GR, 2020, NEW PHYTOL, V226, P292, DOI 10.1111/nph.16432
   Soranno PA, 2019, ECOL LETT, V22, P1587, DOI 10.1111/ele.13346
   Soranno PA, 2014, FRONT ECOL ENVIRON, V12, P65, DOI 10.1890/120366
   Sorensen JW, 2020, PHILOS T R SOC B, V375, DOI 10.1098/rstb.2019.0255
   Spake R, 2021, ECOL LETT, V24, P374, DOI 10.1111/ele.13641
   SPRUGEL DG, 1989, AM NAT, V133, P465, DOI 10.1086/284930
   Strickland MS, 2015, BIOGEOCHEMISTRY, V122, P165, DOI 10.1007/s10533-014-0065-0
   Sulman BN, 2018, BIOGEOCHEMISTRY, V141, P109, DOI 10.1007/s10533-018-0509-z
   Talbot JM, 2014, P NATL ACAD SCI USA, V111, P6341, DOI 10.1073/pnas.1402584111
   Tang JY, 2015, NAT CLIM CHANGE, V5, P56, DOI [10.1038/NCLIMATE2438, 10.1038/nclimate2438]
   Tarnocai C, 2009, GLOBAL BIOGEOCHEM CY, V23, DOI 10.1029/2008GB003327
   Tenney FG, 1929, SOIL SCI, V28, P55, DOI 10.1097/00010694-192907000-00005
   Todd-Brown KEO, 2012, BIOGEOCHEMISTRY, V109, P19, DOI 10.1007/s10533-011-9635-6
   Tomczyk NJ, 2020, ECOSPHERE, V11, DOI 10.1002/ecs2.3050
   Transtrum MK, 2015, J CHEM PHYS, V143, DOI 10.1063/1.4923066
   Tredennick AT, 2021, ECOLOGY, V102, DOI 10.1002/ecy.3336
   Urban MC, 2012, P ROY SOC B-BIOL SCI, V279, P2072, DOI 10.1098/rspb.2011.2367
   van der Plas F, 2020, NAT ECOL EVOL, V4, P1602, DOI 10.1038/s41559-020-01316-9
   Vaughan E, 2019, GEODERMA, V354, DOI 10.1016/j.geoderma.2019.06.044
   Vervoort JM, 2012, ECOL SOC, V17, DOI 10.5751/ES-05098-170424
   von Fromm SF., 2020, SOIL DISCUSS REV
   Wadoux AMJC, 2020, EARTH-SCI REV, V210, DOI 10.1016/j.earscirev.2020.103359
   Wagner T, 2016, ECOSPHERE, V7, DOI 10.1002/ecs2.1417
   Waring BG, 2020, GLOBAL CHANGE BIOL, V26, P6631, DOI 10.1111/gcb.15365
   Waring BG, 2016, NEW PHYTOL, V209, P845, DOI 10.1111/nph.13654
   Wasserstein RL, 2019, AM STAT, V73, P1, DOI 10.1080/00031305.2019.1583913
   Weissgerber TL, 2015, PLOS BIOL, V13, DOI 10.1371/journal.pbio.1002128
   Wieder WR, 2019, GEOPHYS RES LETT, V46, P14486, DOI 10.1029/2019GL085543
   Wieder WR, 2018, GLOBAL CHANGE BIOL, V24, P1563, DOI 10.1111/gcb.13979
   Wieder WR, 2015, GLOBAL BIOGEOCHEM CY, V29, P1782, DOI 10.1002/2015GB005188
   Wieder WR, 2013, NAT CLIM CHANGE, V3, P909, DOI [10.1038/nclimate1951, 10.1038/NCLIMATE1951]
   Wiesmeier M, 2019, GEODERMA, V333, P149, DOI 10.1016/j.geoderma.2018.07.026
   Wright JP, 2012, FUNCT ECOL, V26, P1390, DOI 10.1111/1365-2435.12001
   Wutzler T, 2020, GEOSCI INSTRUM METH, V9, P239, DOI 10.5194/gi-9-239-2020
   Xie HW, 2020, BIOGEOSCIENCES, V17, P4043, DOI 10.5194/bg-17-4043-2020
   Ye JS, 2019, GLOBAL CHANGE BIOL, V25, P3354, DOI 10.1111/gcb.14738
   Zellweger F, 2020, SCIENCE, V368, P772, DOI 10.1126/science.aba6880
   Zhang HC, 2020, GLOBAL CHANGE BIOL, V26, P2668, DOI 10.1111/gcb.14994
   Ziliak ST, 2019, AM STAT, V73, P281, DOI 10.1080/00031305.2018.1514325
NR 186
TC 42
Z9 48
U1 3
U2 80
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0168-2563
EI 1573-515X
J9 BIOGEOCHEMISTRY
JI Biogeochemistry
PD OCT
PY 2021
VL 156
IS 1
SI SI
BP 19
EP 40
DI 10.1007/s10533-021-00789-5
EA APR 2021
PG 22
WC Environmental Sciences; Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Geology
GA US3ZC
UT WOS:000644290100001
DA 2025-01-10
ER

EF