Identifying sources of uncertainty in wheat production projections with consideration of crop climatic suitability under future climate.

• Assessing impacts of climate change on wheat production in climate-suitable area. • Quantifying projected uncertainty of wheat production under future climate change. • SDM dominated projected uncertainty of wheat production in climate-suitable area. • CM was more certain when projecting future wheat production in climate-suitable area. Climate change poses a great challenge to global food security. Recently the combination of crop models (CMs), global climate models (GCMs), and species distribution models (SDMs) has been applied to assess the impacts of climate change on crop production with consideration of changes of crop climate-suitable regions. However, little is known about the uncertainty sources in the wheat production projections with consideration of crop climatic suitability under future climate. In this study, an integration method based on multiple CMs, SDMs, and GCMs was adopted to assess the impacts of climate change on winter wheat production in the Loess Plateau of China. A comprehensive analysis of different uncertainty sources (i.e. CM, GCM, SDM, Emission Scenario or Scen , and their interactions) was conducted through the ANOVA (Analysis of variance) method. Based on the projections of CM ensemble and ensemble-SDMs driven by 27 GCMs, multi-model mean winter wheat production would increase by 14.6% and 19.7% in 2041–2060 and 4.9% and 3.5% in 2081–2100 under SSP245 and SSP585, respectively. We found that the changes in climate-suitable areas of winter wheat caused larger changes in winter wheat production than the changes of per unit yield. SDM was the largest uncertainty contributor among the four main factors of CM, GCM, SDM, and Scen in the projections of winter wheat production under future climate in the Loess Plateau, accounting for about 20.3% of total uncertainty. At the same time, CM was the lowest uncertainty contributor and accounted for only about 3.0% of total uncertainty. Thus, CM was proved more certain in future projections of winter wheat production when considering the changes of crop climate-suitable areas. The efforts in this study could help to rationally integrate the crop modeling, species distribution modeling, and climate models on the projections of global wheat production under future global climate change. [ABSTRACT FROM AUTHOR]