@article{170711, author = {Lyndon D. Estes and Hein Beukes and Bethany A. Bradley and Stephanie R. Debats and Michael Oppenheimer and Alex C. Ruane and Roland Schulze and Mark Tadross}, title = {Projected climate impacts to South African maize and wheat production in 2055: a comparison of empirical and mechanistic modeling approaches}, abstract = { Crop model-specific biases are a key uncertainty affecting our understanding of climate change impacts to agriculture. There is increasing research focus on intermodel variation, but comparisons between mechanistic (MM s) and empirical models (EM s) are rare despite both being used widely in this field. We combined MM s and EM s to project future (2055) changes in the potential distribution (suitability) and productivity of maize and spring wheat in S outh A frica under 18 downscaled climate scenarios (9 models run under 2 emissions scenarios). EM s projected larger yield losses or smaller gains than MM s. The EM s{\textquoteright} median-projected maize and wheat yield changes were -3.6\% and 6.2\%, respectively, compared to 6.5\% and 15.2\% for the MM . The EM projected a 10\% reduction in the potential maize growing area, where the MM projected a 9\% gain. Both models showed increases in the potential spring wheat production region (EM ~=~48\%, MM ~=~20\%), but these results were more equivocal because both models (particularly the EM ) substantially overestimated the extent of current suitability. The substantial water-use efficiency gains simulated by the MM s under elevated CO ₂ accounted for much of the EM -MM difference, but EM s may have more accurately represented crop temperature sensitivities. Our results align with earlier studies showing that EM s may show larger climate change losses than MM s. Crop forecasting efforts should expand to include EM -MM comparisons to provide a fuller picture of crop{\textendash}climate response uncertainties. }, year = {2013}, journal = {Global Change Biology}, volume = {vol. 19 }, language = {eng}, }