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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.

Crop models are essential tools for assessing the threat of climate change to local and global food production(1). Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature(2). Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 degrees C to 32 degrees C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each degrees C of further temperature increase and become more variable over space and time.

Projections of climate change impacts on crop performances are inherently uncertain. However, multimodel uncertainty analysis of crop responses is rare because systematic and objective comparisons among process-based crop simulation models are difficult. Here we report on the Agricultural Model Intercomparison and Improvement Project ensemble of 30 wheat models tested using both crop and climate observed data in diverse environments, including infra-red heating field experiments, for their accuracy in simulating multiple crop growth, N economy and yield variables. The relative error averaged over models in reproducing observations was 24-38% for the different end-of-season variables. Clusters of wheat models organized by their correlations with temperature, precipitation, and solar radiation revealed common characteristics of climatic responses; however, models are rarely in the same cluster when comparing across sites. We also found that the amount of information used for calibration has only a minor effect on model ensemble climatic responses, but can be large for any single model. When simulating impacts assuming a mid-century A2 emissions scenario for climate projections from 16 downscaled general circulation models and 26 wheat models, a greater proportion of the uncertainty in climate change impact projections was due to variations among wheat models rather than to variations among climate models. Uncertainties in simulated impacts increased with atmospheric [CO2] and associated warming. Extrapolating the model ensemble temperature response (at current atmospheric [CO2]) indicated that warming is already reducing yields at a majority of wheat-growing locations. Finally, only a very weak relationship was found between the models’ sensitivities to interannual temperature variability and their response to long-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs. In conclusion, uncertainties in prediction of climate change impacts on crop performance can be reduced by improving temperature and CO2 relationships in models and are better quantified through use of impact ensembles.

Previous studies of photosynthetic acclimation to elevated CO2 have focused on the most recently expanded, sunlit leaves in the canopy. We examined acclimation in a vertical profile of leaves through a canopy of wheat (Triticum aestivum L.). The crop was grown at an elevated CO2 partial pressure of 55 Pa within a replicated field experiment using free-air CO2 enrichment. Gas exchange was used to estimate in vivo carboxylation capacity and the maximum rate of ribulose-1,5-bisphosphate-limited photosynthesis. Net photosynthetic CO2 uptake was measured for leaves in situ within the canopy. Leaf contents of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco), light-harvesting-complex (LHC) proteins, and total N were determined. Elevated CO2 did not affect carboxylation capacity in the most recently expanded leaves but led to a decrease in lower, shaded leaves during grain development. Despite this acclimation, in situ photosynthetic CO2 uptake remained higher under elevated CO2. Acclimation at elevated CO2 was accompanied by decreases in both Rubisco and total leaf N contents and an increase in LHC content. Elevated CO2 led to a larger increase in LHC/Rubisco in lower canopy leaves than in the uppermost leaf. Acclimation of leaf photosynthesis to elevated CO2 therefore depended on both vertical position within the canopy and the developmental stage.

Spring wheat was grown from emergence to grain maturity in two partial pressures of CO2 (pCO2): ambient air of nominally 37 Pa and air enriched with CO2 to 55 Pa using a free-air CO2 enrichment (FACE) apparatus. This experiment was the first of its kind to be conducted within a cereal field without the modifications or disturbance of microclimate and rooting environment that accompanied previous studies. It provided a unique opportunity to examine the hypothesis that continuous exposure of wheat to elevated pCO2 will lead to acclimatory loss of photosynthetic capacity. The diurnal courses of photosynthesis and conductance for upper canopy leaves were followed throughout the development of the crop and compared to model-predicted rates of photosynthesis. The seasonal average of midday photosynthesis rates was 28% greater in plants exposed to elevated pCO2 than in contols and the seasonal average of the daily integrals of photosynthesis was 21% greater in elevated pCO2 than in ambient air. The mean conductance at midday was reduced by 36%. The observed enhancement of photosynthesis in elevated pCO2 agreed closely with that predicted from a mechanistic biochemical model that assumed no acclimation of photosynthetic capacity. Measured values fell below predicted only in the flag leaves in the mid afternoon before the onset of grain-filling and over the whole diurnal course at the end of grain-filling. The loss of enhancement at this final stage was attributed to the earlier senescence of flag leaves in elevated pCO2. In contrast to some controlled-environment and field-enclosure studies, this field-scale study of wheat using free-air CO2 enrichment found little evidence of acclimatory loss of photosynthetic capacity with growth in elevated pCO2 and a significant and substantial increase in leaf photosynthesis throughout the life of the crop.\ud \ud