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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| Published in: | Nature climate change Vol. 6; no. 12; pp. 1130 - 1136 |
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| Main Authors: | , , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Goddard Space Flight Center
Nature Publishing Group UK
01.12.2016
Nature Publishing Group |
| Subjects: | |
| ISSN: | 1758-678X, 1758-6798 |
| Online Access: | Get full text |
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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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| 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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