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Similar Estimates of Temperature Impacts on Global Wheat Yield by Three Independent MethodsThe 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.
Document ID
20160011401
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Liu, Bing (Nanjing Agricultural Univ. China)
Asseng, Senthold (Florida Univ. Gainesville, FL, United States)
Muller, Christoph (Potsdam-Inst. fuer Klimafolgenforschung Potsdam, Germany)
Ewart, Frank (Bonn Univ. Germany)
Elliott, Joshua (Columbia Univ. New York, NY, United States)
Lobell, David B. (Stanford Univ. Stanford, CA, United States)
Martre, Pierre (Institut National de la Recherche Agronomique Montpellier, France)
Ruane, Alex C. (NASA Goddard Inst. for Space Studies New York, NY, United States)
Wallach, Daniel (Institut National de la Recherche Agronomique Montpellier, France)
Jones, James W. (Florida Univ. Gainesville, FL, United States)
Rosenzweig, Cynthia (NASA Goddard Inst. for Space Studies New York, NY, United States)
Deryng, Delphine (Columbia Univ. New York, NY, United States)
Date Acquired
September 21, 2016
Publication Date
September 12, 2016
Publication Information
Publication: Nature Climate Change
Volume: 6
Subject Category
Earth Resources and Remote Sensing
Computer Programming and Software
Report/Patent Number
GSFC-E-DAA-TN35739
Distribution Limits
Public
Copyright
Other
Keywords
Climate impacts
Food security
Wheat yield
Impact method cmparison
Temperature
Global warming