• Energy Research

Climate change in France, central and southern Europe is expected to provoke more frequent and more intensesummer water deficits, with increased amplitude in temperatures, exposing the same perennial crops to frosts as well as to heat waves and severe droughts. The impacts on sown monospecific grasslands have been assessed using crop models (Durand et al. 2010) but with less accuracy in extreme situations. Since less work has been done on intraspecific genetic variability there is urgent need to investigate both ranges of climate conditions and genetic variability (Poirier et al. 2012). Phenology and plant productivity responses to water, temperature and nitrogen (N) in particular need to be re-assessed over the full range of temperatures projected in the future.

Plant species diversity regulates the productivity(1-3) and stability(2,4) of natural ecosystems, along with their resilience to disturbance(5,6). The influence of species diversity on the productivity of agronomic systems is less clear(7-10). Plant genetic diversity is also suspected to influence ecosystem function(3,11-14), although empirical evidence is scarce. Given the large range of genotypes that can be generated per species through artificial selection, genetic diversity is a potentially important leverage of productivity in cultivated systems. Here we assess the effect of species and genetic diversity on the production and sustainable supply of livestock fodder in sown grasslands, comprising single and multispecies assemblages characterized by different levels of genetic diversity, exposed to drought and non-drought conditions. Multispecies assemblages proved more productive than monocultures when subject to drought, regardless of the number of genotypes per species present. Conversely, the temporal stability of production increased only with the number of genotypes present under both drought and non-drought conditions, and was unaffected by the number of species. We conclude that taxonomic and genetic diversity can play complementary roles when it comes to optimizing livestock fodder production in managed grasslands, and suggest that both levels of diversity should be considered in plant breeding programmes designed to boost the productivity and resilience of managed grasslands in the face of increasing environmental hazards.

Significance Agricultural production is vulnerable to climate change. Understanding climate change, especially the temperature impacts, is critical if policymakers, agriculturalists, and crop breeders are to ensure global food security. Our study, by compiling extensive published results from four analytical methods, shows that independent methods consistently estimated negative temperature impacts on yields of four major crops at the global scale, generally underpinned by similar impacts at country and site scales. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops, with important implications for developing crop- and region-specific adaptation strategies to ensure future food supply of an increasing world population.

Abstract Climate change is known to impact crop yields, mainly through increased temperatures, changing rainfall patterns and increasing CO2 concentration in the atmosphere. Although the potential effects of each of these factors have been discussed in a number of separate studies, no recent synthesis has been published to provide quantitative estimates of climate change impacts on crop yields, with or without adaptation strategies. In this paper, we synthetize a broad range of experimental or modeling studies to estimate, at the global scale, crop yield changes resulting from the marginal and combined effects of temperature, CO2 concentration and precipitation, with and without adaptation strategies. Crop yield sensitivities are estimated by distinguishing between C3 and C4 crops. For C3 crops, our results show that the positive effects of adaptation (+7.25 %) and CO2 (+9% for +100 ppm) are high enough to offset the negative effects of temperature increase (-2.4 % for +1 °C), even at +4 °C. On the other hand, for maize (i.e., the only C4 plant species in our database) the somewhat low positive effect from increased CO2 concentration and the absence of a significant effect of adaptation lead to higher yield losses, in the order of -10 % for +4 °C. The minimum level of CO2 concentration increase requested to achieve a yield gain under increased temperature conditions is much higher for maize than for C3 crops, in particular for wheat. The estimated effects of adaptation are uncertain, especially for soybean and rice, but also for maize, where the absence of a significant adaptation effect is probably at least partly due to limited data availability. Our results demonstrate that CO2 effects on crop yields should not be overlooked in foresight studies on the impacts of climate change. Our analysis also highlights the importance of improving our knowledge of how effective adapation strategies are in mitigating the impact of climate change.

AbstractPotential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly −0.5 Mg ha−1 per °C. Doubling [CO2] from 360 to 720 μmol mol−1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.