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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This work was supported by the National High-Tech Research and Development Program of China (2013AA100404), the National Natural Science Foundation of China (31271616, 31611130182, 41571088 and 31561143003), the National Research Foundation for the Doctoral Program of Higher Education of China (20120097110042), the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), and the China Scholarship Council. We would like to acknowledge support provided by IFPRI through the Global Futures and Strategic Foresight project, the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), the CGIAR Research Program on Wheat and the Agricultural Model Intercomparison and Improvement Project (AgMIP).
The authors declare no competing financial interests.
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Liu, B., Asseng, S., Müller, C. et al. Similar estimates of temperature impacts on global wheat yield by three independent methods. Nature Clim Change 6, 1130–1136 (2016). https://doi.org/10.1038/nclimate3115
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