Similar Estimates of Temperature Impacts on Global Wheat Yield by Three Independent Methods

• Published in: Nature climate change Vol. 6; no. 12; pp. 1130 - 1136
• Main Authors: Liu, Bing, Asseng, Senthold, Muller, Christoph, Ewart, Frank, Elliott, Joshua, Lobell, David B., Martre, Pierre, Ruane, Alex C., Wallach, Daniel, Jones, James W., Rosenzweig, Cynthia, Deryng, Delphine
• Format: Journal Article
• Language: English
• Published: Goddard Space Flight Center Nature Publishing Group UK 01.12.2016; Nature Publishing Group
• Subjects: 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; ANE, France; INW, Russia; USA; China, People's Rep; India; France; United States; China; Russia; Climate Impacts; Impact Method Cmparison; Wheat Yield; Temperature; Global Warming; Food Security; sécurité alimentaire; incertitude; simulation; statistical regression; modèle de récolte; réchauffement climatique; uncertainty; impact sur le rendement; changement climatique; comparaison de modèles; global change; wheat; régression statistique; température; blé
• ISSN: 1758-678X; 1758-6798
• DOI: 10.1038/nclimate3115

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.