Abstract: Robust projections of climate impact on crop growth and productivity by crop models are key to designing effective adaptations to cope with future climate risk. However, current crop models diverge strongly in their climate impact projections. Previous studies tried to compare or improve crop models regarding the impact of one single climate variable. However, this approach is insufficient, considering that crop growth and yield are affected by the interactive impacts of multiple climate change factors and multiple interrelated biophysical processes. Here, a new comprehensive analysis was conducted to look holistically at the reasons why crop models diverge substantially in climate impact projections and to investigate which biophysical processes and knowledge gaps are key factors affecting this uncertainty and should be given the highest priorities for improvement. First, eight barley models and eight climate projections for the 2050s were applied to investigate the uncertainty from crop model structure in climate impact projections for barley growth and yield at two sites: Jokioinen, Finland (Boreal) and Lleida, Spain (Mediterranean). Sensitivity analyses were then conducted on the responses of major crop processes to major climatic variables including temperature, precipitation, irradiation, and CO2, as well as their interactions, for each of the eight crop models. The results showed that the temperature and CO2 relationships in the models were the major sources of the large discrepancies among the models in climate impact projections. In particular, the impacts of increases in temperature and CO2 on leaf area development were identified as the major causes for the large uncertainty in simulating changes in evapotranspiration, above-ground biomass, and grain yield. Our findings highlight that advancements in understanding the basic processes and thresholds by which climate warming and CO2 increases will affect leaf area development, crop evapotranspiration, photosynthesis, and grain formation in contrasting environments are needed for modeling their impacts.

Abstract: Working with ensembles of crop models is a recent but important development in crop modeling which promises to lead to better uncertainty estimates for model projections and predictions, better predictions using the ensemble mean or median, and closer collaboration within the modeling community. There are numerous open questions about the best way to create and analyze such ensembles. Much can be learned from the field of climate modeling, given its much longer experience with ensembles. We draw on that experience to identify questions and make propositions that should help make ensemble modeling with crop models more rigorous and informative. The propositions include defining criteria for acceptance of models in a crop MME, exploring criteria for evaluating the degree of relatedness of models in a MME, studying the effect of number of models in the ensemble, development of a statistical model of model sampling, creation of a repository for MME results, studies of possible differential weighting of models in an ensemble, creation of single model ensembles based on sampling from the uncertainty distribution of parameter values or inputs specifically oriented toward uncertainty estimation, the creation of super ensembles that sample more than one source of uncertainty, the analysis of super ensemble results to obtain information on total uncertainty and the separate contributions of different sources of uncertainty and finally further investigation of the use of the multi-model mean or median as a predictor.

Abstract: In this study, we compare the relative importance of climate change to technological, management, price and policy changes on European arable farming systems. This required linking four models: the SIMPLACE crop growth modelling framework to calculate future yields under climate change for arable crops; the CAPRI model to estimate impacts on global agricultural markets, specifically product prices; the bio-economic farm model FSSIM to calculate the future changes in cropping patterns and farm net income at the farm and regional level; and the environmental model INTEGRATOR to calculate nitrogen (N) uptake and losses to air and water. First, the four linked models were applied to analyse the effect of climate change only or a most likely baseline (i.e. B1) scenario for 2050 as well as for two alternative scenarios with, respectively, strong (i.e. A1-b1) and weak economic growth (B2) for five regions/countries across Europe (i.e. Denmark, Flevoland, Midi Pyrenees, Zachodniopomorsld and Andalucia). These analyses Were repeated but assuming in addition to climate change impacts, also the effects of changes in technology and management on crop yields, the effects of changes in prices and policies in 2050, and the effects of all factors together. The outcomes show that the effects of climate change to 2050 result in higher farm net incomes in the Northern and Northern-Central EU regions, in practically unchanged farm net incomes in the Central and Central-Southern EU regions, and in much lower farm net incomes in Southern EU regions compared to those in the base year. Climate change in combination with improved technology and farm management and/or with price changes towards 2050 results in a higher to much higher farm net incomes. Increases in farm net income for the B1 and A1-b1 scenarios are moderately stronger than those for the B2 scenario, due to the smaller increases in product prices and/or yields for the B2 scenario. Farm labour demand slightly to moderately increases towards 2050 as related to changes in cropping patterns. Changes in N2O emissions and N leaching compared to the base year are mainly caused by changes in total N inputs from the applied fertilizers and animal manure, which in turn are influenced by changes in crop yields and cropping patterns, whereas NH3 emissions are mainly determined by assumed improvements in manure application techniques. N emissions and N leaching strongly increase in Denmark and Zachodniopomorski, slightly decrease to moderately increase in Flevoland and Midi-Pyrenees, and strongly decrease in Andalucia, except for NH3 emissions which zero to moderately decrease in Flevoland and Denmark. (C) 2015 Elsevier Ltd. All tights reserved.