Similar Estimates of Temperature Impacts on Global Wheat Yield by Three Independent Methods
The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce...
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| Veröffentlicht in: | Nature climate change Jg. 6; H. 12; S. 1130 - 1136 |
|---|---|
| Hauptverfasser: | , , , , , , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Goddard Space Flight Center
Nature Publishing Group UK
01.12.2016
Nature Publishing Group |
| Schlagworte: | |
| ISSN: | 1758-678X, 1758-6798 |
| Online-Zugang: | Volltext |
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| Abstract | The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify 'method uncertainty' in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security. |
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| AbstractList | The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify 'method uncertainty' in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security. The potential impact of global temperature change on global wheat production has recently been assessed with different methods, scaling and aggregation approaches. Here we show that grid-based simulations, point-based simulations, and statistical regressions produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1°C global temperature increase, global wheat yield is projected to decline by between 4.1% and 6.0%, a relatively narrow range considering the different methods used. Projected temperature impacts from different methods were very similar for major wheat producing countries China, India, USA and France, but less so for Russia. At the location scale, the point-based method simulated higher responses to temperature than the grid-based method. Specifically, the point-based method tended to predict more yield loss with increasing temperature at cooler locations and less yield loss at warmer locations. However, both point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in predicting that warmer regions are likely to suffer more yield reductions with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify 'method uncertainty' in addition to model uncertainty. Use of multi-methods model ensembles should significantly improves the accuracy of estimates of climate impacts on global food security. The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO 2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify 'method uncertainty' in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security. The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO sub(2) fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 degree C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify 'method uncertainty' in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security. The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO 2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify ‘method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security. The impact of climate change on crop yield can be estimated using a variety of methods. Here, a multi-method ensemble is used to quantify ‘method uncertainty’ and improve overall confidence in projections of climate impacts on wheat yields. The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify 'method uncertainty' in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security. |
| Audience | PUBLIC |
| Author | Lobell, David B. Liu, Bing Deryng, Delphine Wallach, Daniel Rosenzweig, Cynthia Martre, Pierre Jones, James W. Elliott, Joshua Asseng, Senthold Muller, Christoph Ewart, Frank Ruane, Alex C. |
| Author_xml | – sequence: 1 givenname: Bing surname: Liu fullname: Liu, Bing organization: Nanjing Agricultural Univ – sequence: 2 givenname: Senthold surname: Asseng fullname: Asseng, Senthold organization: Florida Univ – sequence: 3 givenname: Christoph surname: Muller fullname: Muller, Christoph organization: Potsdam-Inst. fuer Klimafolgenforschung – sequence: 4 givenname: Frank surname: Ewart fullname: Ewart, Frank organization: Bonn Univ – sequence: 5 givenname: Joshua surname: Elliott fullname: Elliott, Joshua organization: Columbia Univ – sequence: 6 givenname: David B. surname: Lobell fullname: Lobell, David B. organization: Stanford Univ – sequence: 7 givenname: Pierre surname: Martre fullname: Martre, Pierre organization: Institut National de la Recherche Agronomique – sequence: 8 givenname: Alex C. surname: Ruane fullname: Ruane, Alex C. organization: NASA Goddard Inst. for Space Studies – sequence: 9 givenname: Daniel surname: Wallach fullname: Wallach, Daniel organization: Institut National de la Recherche Agronomique – sequence: 10 givenname: James W. surname: Jones fullname: Jones, James W. organization: Florida Univ – sequence: 11 givenname: Cynthia surname: Rosenzweig fullname: Rosenzweig, Cynthia organization: NASA Goddard Inst. for Space Studies – sequence: 12 givenname: Delphine surname: Deryng fullname: Deryng, Delphine organization: Columbia Univ |
| BackLink | https://hal.science/hal-01604315$$DView record in HAL |
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| Cites_doi | 10.1002/joc.3463 10.1071/PP9940695 10.1016/j.agrformet.2012.12.008 10.1111/gcb.12768 10.1111/j.1365-2486.2010.02262.x 10.1029/2008GB003435 10.1016/j.eja.2010.07.002 10.1126/science.1185383 10.1142/9781783265640_0010 10.1038/nclimate1356 10.1073/pnas.1407302112 10.1111/j.1469-8137.2008.02500.x 10.1088/1748-9326/2/1/014002 10.1016/j.agrformet.2012.09.011 10.1111/gcb.12520 10.1016/j.fcr.2005.01.007 10.1016/j.agrformet.2013.02.010 10.1038/367133a0 10.5194/esd-4-219-2013 10.1098/rsta.2010.0246 10.1073/pnas.1415181112 10.1038/nclimate1916 10.1071/AR9890001 10.1104/pp.112.207753 10.1038/nclimate2153 10.1038/nclimate2995 10.1073/pnas.1222463110 10.1111/gcb.12830 10.1088/1748-9326/10/11/115002 10.1126/science.1164363 10.1126/science.1204531 10.1088/1748-9326/10/4/045003 10.1142/9781783265640_0009 10.3354/cr01322 10.1111/j.1365-2486.2012.02724.x 10.1038/nclimate2470 10.1017/S0021859610000675 10.1038/nclimate1043 10.1016/j.envsoft.2014.12.003 10.1016/j.fcr.2013.11.008 10.1073/pnas.0906865106 10.1016/S1161-0301(97)00022-1 10.1007/s10113-013-0418-6 10.3354/cr01212 10.1038/nclimate1585 10.1016/j.agee.2011.05.016 |
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| References | WingISMonierESternAMundraAUS major crops’ uncertain climate change risks and greenhouse gas mitigation benefitsEnviron. Res. Lett.20151011500210.1088/1748-9326/10/11/115002 RosenzweigCAssessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparisonProc. Natl Acad. Sci. USA2014111326832731:CAS:528:DC%2BC2cXjtl2isL8%3D10.1073/pnas.1222463110 BattsGMorisonJEllisRHadleyPWheelerTEffects of CO2 and temperature on growth and yield of crops of winter wheat over four seasonsEur. J. Agron.19977435210.1016/S1161-0301(97)00022-1 PirttiojaNTemperature and precipitation effects on wheat yield across a European transect: a crop model ensemble analysis using impact response surfacesClim. Res.2015658710510.3354/cr01322 BassuSHow do various maize crop models vary in their responses to climate change factors?Glob. Change Biol.2014202301232010.1111/gcb.12520 WardlawIDawsonIMunibiPFewsterRThe tolerance of wheat to high temperatures during reproductive growth. I. Survey procedures and general response patternsCrop Pasture Sci.19894011310.1071/AR9890001 XiongWHolmanIPYouLYangJWuWImpacts of observed growing-season warming trends since 1980 on crop yields in ChinaReg. Environ. Change20141471610.1007/s10113-013-0418-6 LvZFLiuXJCaoWXZhuYClimate change impacts on regional winter wheat production in main wheat production regions of ChinaAgric. Forest Meteorol.201317123424810.1016/j.agrformet.2012.12.008 FischerRAByerleeDEdmeadesGOCrop Yields and Global Food Security: Will Yield Increase Continue to Feed the World?2014 KumarSNVulnerability of wheat production to climate change in IndiaClim. Res.20145917318710.3354/cr01212 MartrePMultimodel ensembles of wheat growth: many models are better than oneGlob. Change Biol.20152191192510.1111/gcb.12768 ButlerEEHuybersPAdaptation of US maize to temperature variationsNat. Clim. Change20133687210.1038/nclimate1585 LiHJiangDWollenweberBDaiTCaoWEffects of shading on morphology, physiology and grain yield of winter wheatEur. J. Agron.20103326727510.1016/j.eja.2010.07.002 CollinsMLong-term Climate Change: Projections, Commitments and Irreversibility2013 ChallinorAJA meta-analysis of crop yield under climate change and adaptationNat. Clim. Change2014428729110.1038/nclimate2153 Food and Agriculture Organization of the United Nations (FAO, 2011); http://faostat.fao.org LobellDBSibleyAOrtiz-MonasterioJIExtreme heat effects on wheat senescence in IndiaNat. Clim. Change2012218618910.1038/nclimate1356 WilcoxJMakowskiDA meta-analysis of the predicted effects of climate change on wheat yields using simulation studiesField Crop Res.201415618019010.1016/j.fcr.2013.11.008 Alexandratos, N. & Bruinsma, J. World Agriculture Towards 2030/2050: The 2012 Revision Report No. 12-03 (FAO, 2012). LobellDBFieldCBGlobal scale climate-crop yield relationships and the impacts of recent warmingEnviron. Res. Lett.200721710.1088/1748-9326/2/1/014002 LobellDBBänzigerMMagorokoshoCVivekBNonlinear heat effects on African maize as evidenced by historical yield trialsNat. Clim. Change20111424510.1038/nclimate1043 HempelSFrielerKWarszawskiLScheweJPiontekFA trend-preserving bias correction–the ISI-MIP approachEarth Syst. Dyn.2013421923610.5194/esd-4-219-2013 LobellDBSchlenkerWCosta-RobertsJClimate trends and global crop production since 1980Science20113336166201:CAS:528:DC%2BC3MXpt1yisLs%3D10.1126/science.1204531 AssengSUncertainty in simulating wheat yields under climate changeNat. Clim. Change201338278321:CAS:528:DC%2BC3sXhtl2ksLfI10.1038/nclimate1916 GodfrayHCJFood security: the challenge of feeding 9 billion peopleScience20103278128181:CAS:528:DC%2BC3cXhslWisLo%3D10.1126/science.1185383 WallachDMearnsLORivingtonMAntleJMRuaneACHandbook of Climate Change and Agroecosystems201522325910.1142/9781783265640_0009 KristensenKScheldeKOlesenJEWinter wheat yield response to climate variability in DenmarkJ. Agric. Sci.2011149334710.1017/S0021859610000675 ThorntonPKJonesPGEricksenPJChallinorAJAgriculture and food systems in sub-Saharan Africa in a 4 °C+ worldPhil. Trans. R. Soc. A201136911713610.1098/rsta.2010.0246 WardlawIWrigleyCHeat tolerance in temperate cereals: an overviewFunct. Plant Biol.19942169570310.1071/PP9940695 GallaisAGatePOuryF-XÉvolution des rendements de plusieurs plantes de grande culture une réaction différente au réchauffement climatique selon les espècesC. R. Acad. Sci.201096416 CossaniCMReynoldsMPPhysiological traits for improving heat tolerance in wheatPlant Physiol.2012160171017181:CAS:528:DC%2BC38XhvVKmt7rM10.1104/pp.112.207753 O’LearyGJResponse of wheat growth, grain yield and water use to elevated CO under a Free-Air CO Enrichment (FACE) experiment and modelling in a semi-arid environmentGlob. Change Biol.2015212670268610.1111/gcb.12830 AinsworthEALeakeyADOrtDRLongSPFACE-ing the facts: inconsistencies and interdependence among field, chamber and modeling studies of elevated [CO2] impacts on crop yield and food supplyNew Phytol.2008179591:CAS:528:DC%2BD1cXosFWhsb8%3D10.1111/j.1469-8137.2008.02500.x AssengSRising temperatures reduce global wheat productionNat. Clim. Change2015514314710.1038/nclimate2470 BattistiDSNaylorRLHistorical warnings of future food insecurity with unprecedented seasonal heatScience20093232402441:CAS:528:DC%2BD1MXhvFelsg%3D%3D10.1126/science.1164363 ZhangTHuangYEstimating the impacts of warming trends on wheat and maize in China from 1980 to 2008 based on county level dataInt. J. Climatol.20133369970810.1002/joc.3463 LobellDBAnalysis of wheat yield and climatic trends in MexicoField Crop Res.20059425025610.1016/j.fcr.2005.01.007 EwertFScale changes and model linking methods for integrated assessment of agri-environmental systemsAgric. Ecosys. Environ.201114261710.1016/j.agee.2011.05.016 SchimelDStephensBBFisherJBEffect of increasing CO2 on the terrestrial carbon cycleProc. Natl Acad. Sci. USA20151124364411:CAS:528:DC%2BC2MXltVCh10.1073/pnas.1407302112 EwertFvan BusselLZhaoGHoffmannHGaiserTHandbook of Climate Change and Agroecosystems201526127710.1142/9781783265640_0010 AssengSFosterITurnerNCThe impact of temperature variability on wheat yieldsGlob. Change Biol.201117997101210.1111/j.1365-2486.2010.02262.x RosenzweigCThe agricultural model intercomparison and improvement project (AgMIP): protocols and pilot studiesAgric. Forest Meteorol.201317016618210.1016/j.agrformet.2012.09.011 LickerRKucharikC JDoréTLindemanM JMakowskiDClimatic impacts on winter wheat yields in Picardy, France and Rostov, Russia: 1973–2010Agric. Forest Meteorol.2013176253710.1016/j.agrformet.2013.02.010 EwertFCrop modelling for integrated assessment of risk to food production from climate changeEnviron. Model Softw.20157228730310.1016/j.envsoft.2014.12.003 PortmannF TSiebertSDöllPMIRCA2000—Global monthly irrigated and rainfed crop areas around the year 2000: a new high-resolution data set for agricultural and hydrological modelingGlob. Biogeochem. Cycles2010242013202410.1029/2008GB003435 RosenzweigCParryMLPotential impact of climate change on world food supplyNature199436713313810.1038/367133a0 DeryngDRegional disparities in the beneficial effects of rising CO2 concentrations on crop water productivityNat. Clim. Change2016678679010.1038/nclimate2995 ZhengBChenuKFernanda DreccerMChapmanSCBreeding for the future: what are the potential impacts of future frost and heat events on sowing and flowering time requirements for Australian bread wheat (Triticum aestivium) varieties?Glob. Change Biol.2012182899291410.1111/j.1365-2486.2012.02724.x SchlenkerWRobertsMJNonlinear temperature effects indicate severe damages to U. S. crop yields under climate changeProc. Natl Acad. Sci. USA200910615594155981:CAS:528:DC%2BD1MXhtFyjsLvP10.1073/pnas.0906865106 UrbanDWSheffieldJLobellDBThe impacts of future climate and carbon dioxide changes on the average and variability of US maize yields under two emission scenariosEnviron. Res. Lett.20151004500310.1088/1748-9326/10/4/045003 TackJBarkleyANalleyL LEffect of warming temperatures on US wheat yieldsProc. Natl Acad. Sci. USA2015112693169361:CAS:528:DC%2BC2MXotFCmsLk%3D10.1073/pnas.1415181112 F T Portmann (BFnclimate3115_CR51) 2010; 24 RA Fischer (BFnclimate3115_CR18) 2014 G Batts (BFnclimate3115_CR41) 1997; 7 D Wallach (BFnclimate3115_CR43) 2015 DW Urban (BFnclimate3115_CR33) 2015; 10 F Ewert (BFnclimate3115_CR14) 2015 AJ Challinor (BFnclimate3115_CR3) 2014; 4 CM Cossani (BFnclimate3115_CR47) 2012; 160 DB Lobell (BFnclimate3115_CR30) 2012; 2 W Xiong (BFnclimate3115_CR45) 2014; 14 HCJ Godfray (BFnclimate3115_CR42) 2010; 327 S Bassu (BFnclimate3115_CR28) 2014; 20 P Martre (BFnclimate3115_CR44) 2015; 21 SN Kumar (BFnclimate3115_CR6) 2014; 59 K Kristensen (BFnclimate3115_CR12) 2011; 149 DS Battisti (BFnclimate3115_CR29) 2009; 323 DB Lobell (BFnclimate3115_CR34) 2005; 94 J Tack (BFnclimate3115_CR20) 2015; 112 C Rosenzweig (BFnclimate3115_CR2) 1994; 367 BFnclimate3115_CR1 BFnclimate3115_CR23 H Li (BFnclimate3115_CR24) 2010; 33 F Ewert (BFnclimate3115_CR32) 2011; 142 ZF Lv (BFnclimate3115_CR5) 2013; 171 A Gallais (BFnclimate3115_CR21) 2010; 96 D Schimel (BFnclimate3115_CR36) 2015; 112 F Ewert (BFnclimate3115_CR4) 2015; 72 S Asseng (BFnclimate3115_CR8) 2015; 5 IS Wing (BFnclimate3115_CR13) 2015; 10 R Licker (BFnclimate3115_CR19) 2013; 176 EA Ainsworth (BFnclimate3115_CR37) 2008; 179 C Rosenzweig (BFnclimate3115_CR9) 2014; 111 DB Lobell (BFnclimate3115_CR11) 2007; 2 N Pirttioja (BFnclimate3115_CR22) 2015; 65 DB Lobell (BFnclimate3115_CR10) 2011; 333 M Collins (BFnclimate3115_CR17) 2013 B Zheng (BFnclimate3115_CR48) 2012; 18 PK Thornton (BFnclimate3115_CR7) 2011; 369 S Hempel (BFnclimate3115_CR50) 2013; 4 J Wilcox (BFnclimate3115_CR16) 2014; 156 DB Lobell (BFnclimate3115_CR27) 2011; 1 I Wardlaw (BFnclimate3115_CR39) 1989; 40 D Deryng (BFnclimate3115_CR38) 2016; 6 T Zhang (BFnclimate3115_CR49) 2013; 33 EE Butler (BFnclimate3115_CR46) 2013; 3 S Asseng (BFnclimate3115_CR31) 2011; 17 S Asseng (BFnclimate3115_CR25) 2013; 3 I Wardlaw (BFnclimate3115_CR40) 1994; 21 W Schlenker (BFnclimate3115_CR26) 2009; 106 GJ O’Leary (BFnclimate3115_CR35) 2015; 21 C Rosenzweig (BFnclimate3115_CR15) 2013; 170 |
| References_xml | – reference: AssengSFosterITurnerNCThe impact of temperature variability on wheat yieldsGlob. Change Biol.201117997101210.1111/j.1365-2486.2010.02262.x – reference: XiongWHolmanIPYouLYangJWuWImpacts of observed growing-season warming trends since 1980 on crop yields in ChinaReg. Environ. Change20141471610.1007/s10113-013-0418-6 – reference: RosenzweigCThe agricultural model intercomparison and improvement project (AgMIP): protocols and pilot studiesAgric. Forest Meteorol.201317016618210.1016/j.agrformet.2012.09.011 – reference: CossaniCMReynoldsMPPhysiological traits for improving heat tolerance in wheatPlant Physiol.2012160171017181:CAS:528:DC%2BC38XhvVKmt7rM10.1104/pp.112.207753 – reference: WallachDMearnsLORivingtonMAntleJMRuaneACHandbook of Climate Change and Agroecosystems201522325910.1142/9781783265640_0009 – reference: SchimelDStephensBBFisherJBEffect of increasing CO2 on the terrestrial carbon cycleProc. Natl Acad. Sci. USA20151124364411:CAS:528:DC%2BC2MXltVCh10.1073/pnas.1407302112 – reference: CollinsMLong-term Climate Change: Projections, Commitments and Irreversibility2013 – reference: RosenzweigCAssessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparisonProc. Natl Acad. Sci. USA2014111326832731:CAS:528:DC%2BC2cXjtl2isL8%3D10.1073/pnas.1222463110 – reference: ButlerEEHuybersPAdaptation of US maize to temperature variationsNat. Clim. Change20133687210.1038/nclimate1585 – reference: EwertFvan BusselLZhaoGHoffmannHGaiserTHandbook of Climate Change and Agroecosystems201526127710.1142/9781783265640_0010 – reference: FischerRAByerleeDEdmeadesGOCrop Yields and Global Food Security: Will Yield Increase Continue to Feed the World?2014 – reference: ZhangTHuangYEstimating the impacts of warming trends on wheat and maize in China from 1980 to 2008 based on county level dataInt. J. Climatol.20133369970810.1002/joc.3463 – reference: Food and Agriculture Organization of the United Nations (FAO, 2011); http://faostat.fao.org – reference: SchlenkerWRobertsMJNonlinear temperature effects indicate severe damages to U. S. crop yields under climate changeProc. Natl Acad. Sci. USA200910615594155981:CAS:528:DC%2BD1MXhtFyjsLvP10.1073/pnas.0906865106 – reference: EwertFCrop modelling for integrated assessment of risk to food production from climate changeEnviron. Model Softw.20157228730310.1016/j.envsoft.2014.12.003 – reference: ChallinorAJA meta-analysis of crop yield under climate change and adaptationNat. Clim. Change2014428729110.1038/nclimate2153 – reference: O’LearyGJResponse of wheat growth, grain yield and water use to elevated CO under a Free-Air CO Enrichment (FACE) experiment and modelling in a semi-arid environmentGlob. Change Biol.2015212670268610.1111/gcb.12830 – reference: UrbanDWSheffieldJLobellDBThe impacts of future climate and carbon dioxide changes on the average and variability of US maize yields under two emission scenariosEnviron. Res. Lett.20151004500310.1088/1748-9326/10/4/045003 – reference: BassuSHow do various maize crop models vary in their responses to climate change factors?Glob. Change Biol.2014202301232010.1111/gcb.12520 – reference: ZhengBChenuKFernanda DreccerMChapmanSCBreeding for the future: what are the potential impacts of future frost and heat events on sowing and flowering time requirements for Australian bread wheat (Triticum aestivium) varieties?Glob. Change Biol.2012182899291410.1111/j.1365-2486.2012.02724.x – reference: AinsworthEALeakeyADOrtDRLongSPFACE-ing the facts: inconsistencies and interdependence among field, chamber and modeling studies of elevated [CO2] impacts on crop yield and food supplyNew Phytol.2008179591:CAS:528:DC%2BD1cXosFWhsb8%3D10.1111/j.1469-8137.2008.02500.x – reference: DeryngDRegional disparities in the beneficial effects of rising CO2 concentrations on crop water productivityNat. Clim. Change2016678679010.1038/nclimate2995 – reference: BattistiDSNaylorRLHistorical warnings of future food insecurity with unprecedented seasonal heatScience20093232402441:CAS:528:DC%2BD1MXhvFelsg%3D%3D10.1126/science.1164363 – reference: GodfrayHCJFood security: the challenge of feeding 9 billion peopleScience20103278128181:CAS:528:DC%2BC3cXhslWisLo%3D10.1126/science.1185383 – reference: LvZFLiuXJCaoWXZhuYClimate change impacts on regional winter wheat production in main wheat production regions of ChinaAgric. Forest Meteorol.201317123424810.1016/j.agrformet.2012.12.008 – reference: TackJBarkleyANalleyL LEffect of warming temperatures on US wheat yieldsProc. Natl Acad. Sci. USA2015112693169361:CAS:528:DC%2BC2MXotFCmsLk%3D10.1073/pnas.1415181112 – reference: LobellDBAnalysis of wheat yield and climatic trends in MexicoField Crop Res.20059425025610.1016/j.fcr.2005.01.007 – reference: WingISMonierESternAMundraAUS major crops’ uncertain climate change risks and greenhouse gas mitigation benefitsEnviron. Res. Lett.20151011500210.1088/1748-9326/10/11/115002 – reference: KristensenKScheldeKOlesenJEWinter wheat yield response to climate variability in DenmarkJ. Agric. Sci.2011149334710.1017/S0021859610000675 – reference: EwertFScale changes and model linking methods for integrated assessment of agri-environmental systemsAgric. Ecosys. Environ.201114261710.1016/j.agee.2011.05.016 – reference: HempelSFrielerKWarszawskiLScheweJPiontekFA trend-preserving bias correction–the ISI-MIP approachEarth Syst. Dyn.2013421923610.5194/esd-4-219-2013 – reference: RosenzweigCParryMLPotential impact of climate change on world food supplyNature199436713313810.1038/367133a0 – reference: MartrePMultimodel ensembles of wheat growth: many models are better than oneGlob. Change Biol.20152191192510.1111/gcb.12768 – reference: LobellDBBänzigerMMagorokoshoCVivekBNonlinear heat effects on African maize as evidenced by historical yield trialsNat. Clim. Change20111424510.1038/nclimate1043 – reference: KumarSNVulnerability of wheat production to climate change in IndiaClim. Res.20145917318710.3354/cr01212 – reference: WardlawIDawsonIMunibiPFewsterRThe tolerance of wheat to high temperatures during reproductive growth. I. Survey procedures and general response patternsCrop Pasture Sci.19894011310.1071/AR9890001 – reference: WardlawIWrigleyCHeat tolerance in temperate cereals: an overviewFunct. Plant Biol.19942169570310.1071/PP9940695 – reference: PirttiojaNTemperature and precipitation effects on wheat yield across a European transect: a crop model ensemble analysis using impact response surfacesClim. Res.2015658710510.3354/cr01322 – reference: GallaisAGatePOuryF-XÉvolution des rendements de plusieurs plantes de grande culture une réaction différente au réchauffement climatique selon les espècesC. R. Acad. Sci.201096416 – reference: LobellDBSibleyAOrtiz-MonasterioJIExtreme heat effects on wheat senescence in IndiaNat. Clim. Change2012218618910.1038/nclimate1356 – reference: BattsGMorisonJEllisRHadleyPWheelerTEffects of CO2 and temperature on growth and yield of crops of winter wheat over four seasonsEur. J. Agron.19977435210.1016/S1161-0301(97)00022-1 – reference: AssengSRising temperatures reduce global wheat productionNat. Clim. Change2015514314710.1038/nclimate2470 – reference: LickerRKucharikC JDoréTLindemanM JMakowskiDClimatic impacts on winter wheat yields in Picardy, France and Rostov, Russia: 1973–2010Agric. Forest Meteorol.2013176253710.1016/j.agrformet.2013.02.010 – reference: WilcoxJMakowskiDA meta-analysis of the predicted effects of climate change on wheat yields using simulation studiesField Crop Res.201415618019010.1016/j.fcr.2013.11.008 – reference: AssengSUncertainty in simulating wheat yields under climate changeNat. Clim. Change201338278321:CAS:528:DC%2BC3sXhtl2ksLfI10.1038/nclimate1916 – reference: Alexandratos, N. & Bruinsma, J. World Agriculture Towards 2030/2050: The 2012 Revision Report No. 12-03 (FAO, 2012). – reference: PortmannF TSiebertSDöllPMIRCA2000—Global monthly irrigated and rainfed crop areas around the year 2000: a new high-resolution data set for agricultural and hydrological modelingGlob. Biogeochem. Cycles2010242013202410.1029/2008GB003435 – reference: LiHJiangDWollenweberBDaiTCaoWEffects of shading on morphology, physiology and grain yield of winter wheatEur. J. Agron.20103326727510.1016/j.eja.2010.07.002 – reference: LobellDBFieldCBGlobal scale climate-crop yield relationships and the impacts of recent warmingEnviron. Res. Lett.200721710.1088/1748-9326/2/1/014002 – reference: ThorntonPKJonesPGEricksenPJChallinorAJAgriculture and food systems in sub-Saharan Africa in a 4 °C+ worldPhil. Trans. R. Soc. A201136911713610.1098/rsta.2010.0246 – reference: LobellDBSchlenkerWCosta-RobertsJClimate trends and global crop production since 1980Science20113336166201:CAS:528:DC%2BC3MXpt1yisLs%3D10.1126/science.1204531 – volume: 33 start-page: 699 year: 2013 ident: BFnclimate3115_CR49 publication-title: Int. J. Climatol. doi: 10.1002/joc.3463 – volume: 21 start-page: 695 year: 1994 ident: BFnclimate3115_CR40 publication-title: Funct. Plant Biol. doi: 10.1071/PP9940695 – volume: 171 start-page: 234 year: 2013 ident: BFnclimate3115_CR5 publication-title: Agric. Forest Meteorol. doi: 10.1016/j.agrformet.2012.12.008 – volume-title: Long-term Climate Change: Projections, Commitments and Irreversibility year: 2013 ident: BFnclimate3115_CR17 – volume: 21 start-page: 911 year: 2015 ident: BFnclimate3115_CR44 publication-title: Glob. Change Biol. doi: 10.1111/gcb.12768 – volume: 17 start-page: 997 year: 2011 ident: BFnclimate3115_CR31 publication-title: Glob. Change Biol. doi: 10.1111/j.1365-2486.2010.02262.x – volume: 24 start-page: 2013 year: 2010 ident: BFnclimate3115_CR51 publication-title: Glob. Biogeochem. Cycles doi: 10.1029/2008GB003435 – volume: 33 start-page: 267 year: 2010 ident: BFnclimate3115_CR24 publication-title: Eur. J. Agron. doi: 10.1016/j.eja.2010.07.002 – volume: 327 start-page: 812 year: 2010 ident: BFnclimate3115_CR42 publication-title: Science doi: 10.1126/science.1185383 – start-page: 261 volume-title: Handbook of Climate Change and Agroecosystems year: 2015 ident: BFnclimate3115_CR14 doi: 10.1142/9781783265640_0010 – volume: 2 start-page: 186 year: 2012 ident: BFnclimate3115_CR30 publication-title: Nat. Clim. Change doi: 10.1038/nclimate1356 – volume: 112 start-page: 436 year: 2015 ident: BFnclimate3115_CR36 publication-title: Proc. Natl Acad. Sci. USA doi: 10.1073/pnas.1407302112 – volume: 179 start-page: 5 year: 2008 ident: BFnclimate3115_CR37 publication-title: New Phytol. doi: 10.1111/j.1469-8137.2008.02500.x – volume: 2 start-page: 1 year: 2007 ident: BFnclimate3115_CR11 publication-title: Environ. Res. Lett. doi: 10.1088/1748-9326/2/1/014002 – ident: BFnclimate3115_CR1 – volume: 170 start-page: 166 year: 2013 ident: BFnclimate3115_CR15 publication-title: Agric. Forest Meteorol. doi: 10.1016/j.agrformet.2012.09.011 – volume: 20 start-page: 2301 year: 2014 ident: BFnclimate3115_CR28 publication-title: Glob. Change Biol. doi: 10.1111/gcb.12520 – volume: 94 start-page: 250 year: 2005 ident: BFnclimate3115_CR34 publication-title: Field Crop Res. doi: 10.1016/j.fcr.2005.01.007 – volume: 176 start-page: 25 year: 2013 ident: BFnclimate3115_CR19 publication-title: Agric. Forest Meteorol. doi: 10.1016/j.agrformet.2013.02.010 – volume-title: Crop Yields and Global Food Security: Will Yield Increase Continue to Feed the World? year: 2014 ident: BFnclimate3115_CR18 – ident: BFnclimate3115_CR23 – volume: 96 start-page: 4 year: 2010 ident: BFnclimate3115_CR21 publication-title: C. R. Acad. Sci. – volume: 367 start-page: 133 year: 1994 ident: BFnclimate3115_CR2 publication-title: Nature doi: 10.1038/367133a0 – volume: 4 start-page: 219 year: 2013 ident: BFnclimate3115_CR50 publication-title: Earth Syst. Dyn. doi: 10.5194/esd-4-219-2013 – volume: 369 start-page: 117 year: 2011 ident: BFnclimate3115_CR7 publication-title: Phil. Trans. R. Soc. A doi: 10.1098/rsta.2010.0246 – volume: 112 start-page: 6931 year: 2015 ident: BFnclimate3115_CR20 publication-title: Proc. Natl Acad. Sci. USA doi: 10.1073/pnas.1415181112 – volume: 3 start-page: 827 year: 2013 ident: BFnclimate3115_CR25 publication-title: Nat. Clim. Change doi: 10.1038/nclimate1916 – volume: 40 start-page: 1 year: 1989 ident: BFnclimate3115_CR39 publication-title: Crop Pasture Sci. doi: 10.1071/AR9890001 – volume: 160 start-page: 1710 year: 2012 ident: BFnclimate3115_CR47 publication-title: Plant Physiol. doi: 10.1104/pp.112.207753 – volume: 4 start-page: 287 year: 2014 ident: BFnclimate3115_CR3 publication-title: Nat. Clim. Change doi: 10.1038/nclimate2153 – volume: 6 start-page: 786 year: 2016 ident: BFnclimate3115_CR38 publication-title: Nat. Clim. Change doi: 10.1038/nclimate2995 – volume: 111 start-page: 3268 year: 2014 ident: BFnclimate3115_CR9 publication-title: Proc. Natl Acad. Sci. USA doi: 10.1073/pnas.1222463110 – volume: 21 start-page: 2670 year: 2015 ident: BFnclimate3115_CR35 publication-title: Glob. Change Biol. doi: 10.1111/gcb.12830 – volume: 10 start-page: 115002 year: 2015 ident: BFnclimate3115_CR13 publication-title: Environ. Res. Lett. doi: 10.1088/1748-9326/10/11/115002 – volume: 323 start-page: 240 year: 2009 ident: BFnclimate3115_CR29 publication-title: Science doi: 10.1126/science.1164363 – volume: 333 start-page: 616 year: 2011 ident: BFnclimate3115_CR10 publication-title: Science doi: 10.1126/science.1204531 – volume: 10 start-page: 045003 year: 2015 ident: BFnclimate3115_CR33 publication-title: Environ. Res. Lett. doi: 10.1088/1748-9326/10/4/045003 – start-page: 223 volume-title: Handbook of Climate Change and Agroecosystems year: 2015 ident: BFnclimate3115_CR43 doi: 10.1142/9781783265640_0009 – volume: 65 start-page: 87 year: 2015 ident: BFnclimate3115_CR22 publication-title: Clim. Res. doi: 10.3354/cr01322 – volume: 18 start-page: 2899 year: 2012 ident: BFnclimate3115_CR48 publication-title: Glob. Change Biol. doi: 10.1111/j.1365-2486.2012.02724.x – volume: 5 start-page: 143 year: 2015 ident: BFnclimate3115_CR8 publication-title: Nat. Clim. Change doi: 10.1038/nclimate2470 – volume: 149 start-page: 33 year: 2011 ident: BFnclimate3115_CR12 publication-title: J. Agric. Sci. doi: 10.1017/S0021859610000675 – volume: 1 start-page: 42 year: 2011 ident: BFnclimate3115_CR27 publication-title: Nat. Clim. Change doi: 10.1038/nclimate1043 – volume: 72 start-page: 287 year: 2015 ident: BFnclimate3115_CR4 publication-title: Environ. Model Softw. doi: 10.1016/j.envsoft.2014.12.003 – volume: 156 start-page: 180 year: 2014 ident: BFnclimate3115_CR16 publication-title: Field Crop Res. doi: 10.1016/j.fcr.2013.11.008 – volume: 106 start-page: 15594 year: 2009 ident: BFnclimate3115_CR26 publication-title: Proc. Natl Acad. Sci. USA doi: 10.1073/pnas.0906865106 – volume: 7 start-page: 43 year: 1997 ident: BFnclimate3115_CR41 publication-title: Eur. J. Agron. doi: 10.1016/S1161-0301(97)00022-1 – volume: 14 start-page: 7 year: 2014 ident: BFnclimate3115_CR45 publication-title: Reg. Environ. Change doi: 10.1007/s10113-013-0418-6 – volume: 59 start-page: 173 year: 2014 ident: BFnclimate3115_CR6 publication-title: Clim. Res. doi: 10.3354/cr01212 – volume: 3 start-page: 68 year: 2013 ident: BFnclimate3115_CR46 publication-title: Nat. Clim. Change doi: 10.1038/nclimate1585 – volume: 142 start-page: 6 year: 2011 ident: BFnclimate3115_CR32 publication-title: Agric. Ecosys. Environ. doi: 10.1016/j.agee.2011.05.016 |
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| SubjectTerms | 704/106/694/2739 706/1143 Agricultural production Agricultural sciences Alterra - Climate change and adaptive land and water management Alterra - Klimaatverandering en adaptief land- en watermanagement Carbon dioxide China climate Climate Change Climate Change and Adaptive Land and Water Management Climate Change/Climate Change Impacts Computer Programming And Software Corn Crop yield Earth Resources And Remote Sensing Earth System Science Environment Environmental Law/Policy/Ecojustice Environmental Sciences Estimates Food security France Global Changes Global temperatures global warming grain yield India Klimaatverandering Klimaatverandering en adaptief land- en watermanagement Leerstoelgroep Aardsysteemkunde Leerstoelgroep Plantaardige productiesystemen Life Sciences Methods model uncertainty PE&RC Plant Production Systems Plantaardige Productiesystemen prediction Russia Simulation Temperature Triticum aestivum United States Vegetal Biology Wheat WIMEK |
| Title | Similar Estimates of Temperature Impacts on Global Wheat Yield by Three Independent Methods |
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