Abstract: Data of diverse crop rotations from five locations across Europe were distributed to modelers to investigate the capability of models to handle complex crop rotations and management interactions. Crop rotations comprise various main crops (winter/spring wheat, winter/spring barley, rye, oat, maize, sugar beet, oil seed rape and potatoes) plus several catch crops. The experimental setup of the datasets included treatments such as modified soils, crops exchanged within the rotations, irrigation/rainfed, nitrogen fertilization, residue management, tillage and atmospheric CO2 concentration. 19 modeling teams registered to model either the whole rotation or single crops. Models which are capable to run the whole rotation should provide transient as well as single year simulations with a reset of initial conditions. In the first step only initial soil conditions (water and soil mineral N) of the first year and key phenological stages were provided to the modelers. For calibration, crop yields and biomass were provided for selected years but not for all seasons. In total the combination of treatments and seasons results in 301 years of simulation. Results were analyzed to evaluate the effect of transient simulation versus single-year simulation regarding crop yield, biomass, water and nitrogen balance components. Model results will be evaluated crop-specifically to identify crops with highest uncertainty and potential for model improvement. Full data will be provided to modelers for model-improvement and results will provide insights into model capabilities to reproduce treatments and crops. Further, the question of error propagation along the transient simulation of crop rotations will be addressed.

Abstract: Priorities in addressing research gaps and challenges should follow the order of im­por­tance, which in itself would be a matter of defining goals and metrics of importance, e.g. the extent, impact and likelihood of occurrence. For improving assessments of cli­mate change impacts on agriculture for achieving food security and other sustainable develop­ment goals across the European continent, the most important research gaps and challen­ges appear to be the agreement on goals with a wide range of stakeholders from policy, science, producers and society, better reflection of political and societal prefer­ences in the modelling process, and the reflection of economic decisions in farm manage­ment within models. These and other challenges could be approached in phase 3 of MACSUR.

Abstract: Adaptation can reduce climate change risks to crop production and is best analyzed at local scales considering regional specificities. Uncertainty inherent in modelling adaptation options is due to climate projections, downscaling and imperfections of crop models. The challenge of making effective adaptation decisions requires powerful approaches for exploiting the potential of genotype by environment by management interactions, and for generating projections informed with uncertainty.Here we present a methodology that constructs impact response surfaces (IRSs) from an ensemble of crop models and applies these to explore the adaptation potential of rainfed winter wheat at Lleida (NE Spain) in a water-limited environment. The simulation experiment includes: 1) a systematic sensitivity analysis to changes to baseline temperature and precipitation (1981-2010) through a delta change approach that accounts for seasonal differences, 2) three levels of CO2 representing present-day and future conditions until 2050 (A1B scenario), and 3) soil profiles representative for the variable conditions around Lleida. The adaptation simulations represent adjusted management practices about sowing, supplementary irrigation, and the thermal and vernalisation requirements of cultivars used.A pre-selection of the adaptation options was done iteratively, in ranges supported by literature review of crop adaptation in the Mediterranean (e.g. shifts from current sowing date between -30 and +45 days). This procedure allowed to identify a limited number of effective and feasible adaptations to be evaluated combining IRSs and probabilistic projections of climate change. No Label