Abstract: Climate-induced uncertainty in crop yields is introduced in the Norwegian sector model Jordmod. The model is comprised of a supply module in which profits for more than 300 regional farms are maximized and a market module which maximizes social welfare in the agricultural sector. In the supply module, farmers determine their plant decisions and crop input levels (N-fertilizer) subject to a discrete number of weather outcomes affecting crop yields. After that, a specific weather distribution is chosen determining crop yields. The resulting input-output mix at farm level makes up the supply side of the commodity markets which together with linear demand functions determine equilibrium levels. The procedure is repeated for each discrete weather outcome. Note that plant decisions and crop input levels remain the same for all weather outcomes as farmers face the same uncertainty during all repetitions, but crop yield will vary. Hence, equilibrium prices and quantities will vary as well allowing their representation as stochastic distributions. In a preliminary empirical application, the stochastic results are contrasted with the deterministic results based on the mean values of the weather outcomes. This comparison will shed light on the potential error made by neglecting uncertainty at the farm level.

Abstract: Wheat yields in Europe have shown stagnating trends during the last two decades, partly attributed to climate change. Such developments challenge the needs for increased production, in particular at higher latitudes, to meet increasing global demands and expected productivity reductions at lower latitudes. Climate change projections from three General Circulation Models or GCMs (UKMO-HadGEM1, INM-GM3.0 and CSIRO-Mk3.1) for the A1FI SIZES emission scenario for 2000 to 2100 were downscaled at a northern latitude location (Foulum, Denmark) using LARS-WG5.3. The scenarios accounted for changes in temperature, precipitation and atmospheric CO2 concentration. In addition, three temperature-variability scenarios were included assuming different levels of decreased temperature variability in winter and increased in summer. Crop yield was simulated for the different climate change scenarios by a calibrated version of AFRCWHEAT2 to model several combinations of genotypes (varying in crop growth, development and tolerance to water and nitrogen scarcity) and management (sowing dates and nitrogen fertilization rate). The simulations showed a slight improvement of grain yields (0.3-1.2 Mg ha(-1)) in the medium-term (2030-2050), but not enough to cope with expected increases in demand for food and feed. Optimum management added up to 1.8 Mg ha(-1). Genetic modifications regarding winter wheat crop development exhibit the greatest sensitivity to climate and larger potential for improvement (+3.8 Mg ha(-1)). The results consistently points towards need for cultivars with a longer reproductive phases (2.9-7.5% per 1 degrees C) and lower photoperiod sensitivities. Due to the positive synergies between several genotypic characteristics, multiple-target breeding programmes would be necessary, possibly assisted by model-based assessments of optimal phenotypic characteristics.