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Edited by Hans Joachim Schellnhuber, Potsdam Institute for Climate Impact Research, Potsdam, Germany, and approved June 4, 2013 (received for review January 31, 2013)
Article Figures & SI
Figures
- Fig. 1.
Mean relative yield change (%) from reference period (1980–2010) compared to local mean temperature change (°C) in 20 top food-producing regions for each crop and latitudinal band. Results shown for the 7 GGCMs (6 for rice) for all GCM combinations of RCP8.5 compared to results from IPCC AR4 (represented as orange dots and quadratic fit; 36). Quadratic least-squares fits are used to estimate the general response for the GGCMs with explicit nitrogen stress (EPIC, GEPIC, pDSSAT, and PEGASUS; red line) and for those without (GAEZ-IMAGE, LPJ-GUESS, and LPJmL; green line). The 15–85% range of all models for each ¼°C band is represented in gray. Limits of local temperature changes reflect differences in projected warming in current areas of cultivation.
- Fig. 2.
Average reference period (1980–2010) GGCM maize yield (A–F, H), rescaled to a common global average to make the spatial patterns more apparent, and historical yield M3 observation set (G) (39). Note that because some models are calibrated and others are not and because some models simulate potential rather than actual yields, it is not advisable to compare the absolute yields in the ensemble with observations.
- Fig. 3.
Median yield changes (%) for RCP8.5 (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects over all five GCMs x seven GGCMs (6 GGCMs for rice) for rainfed maize (35 ensemble members), wheat (35 ensemble members), rice (30 ensemble members), and soy (35 ensemble members). Hatching indicates areas where more than 70% of the ensemble members agree on the directionality of the impact factor. Gray areas indicate historical areas with little to no yield capacity. The bottom 8 panels show the corresponding yield change patterns over all five GCMs x four GGCMs with nitrogen stress (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15) (Left); and 3 GGCMs without nitrogen stress (15 ensemble members from GAEZ-IMAGE, LPJ-GUESS, and LPJmL).
- Fig. 4.
Relative change (%) in RCP8.5 decadal mean production for each GGCM (based on current agricultural lands and irrigation distribution) from ensemble median for all GCM combinations with (solid) and without (dashed) CO2 effects for maize, wheat, rice, and soy; bars show range of all GCM combinations with CO2 effects. GEPIC, GAEZ-IMAGE, and LPJ-GUESS only contributed one GCM without CO2 effects.
- Fig. 5.
Absolute deviation of decadal average production changes from ensemble median yield changes (as fraction of 1980–2010 reference period mean production) for all GCM × GGCM combinations in RCP2.6 (dark blue), RCP4.5 (light blue), RCP6.0 (orange), and RCP8.5 (red) for maize, wheat, rice, and soy with (Upper) and without (Lower) CO2 effects. Simulations in A with CO2 effects included five GCMs and seven GGCMs (35 members), whereas GAEZ-IMAGE, GEPIC, and LPJ-GUESS ran only a single GCM without CO2 effects, resulting in 23 members in B.
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Global multi-model crop-climate impact assessment
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