Abstract: The aim of this study is to compare the water and organic material balance, yields and other aspects estimated within crop rotations by the Hermes crop model for present and future climatic conditions in the Czech Republic. Moreover, this is a pilot study for the complex and continuous crop rotations modeling (using both single crop models and ensembles) in connection with transient climate change scenarios. For this purpose, three locations representing important agricultural regions of the Czech Republic (with different climatic conditions) were selected. The crop rotation (including spring barley, silage maize, winter wheat, winter rape, and winter wheat in the listed order) was simulated from 1981-2080. The period 1981-2010 was covered by measured meteorological data, and the period 2011-2080 was represented by a transient synthetic weather series from the weather generator M&Rfi. The generated data was based on five circulation models representing an ensemble of 18 CMIP3 global circulation models to preserve to a large degree the uncertainty of the original ensemble. Two types of crop management were compared, and the influences of soil quality, increasing atmospheric CO2 and magnitude of adaptation measure (in the form of sowing date changes) were also considered. According to the results, if a “dry” scenario (such as GFCM21) would occur, then all the C3 crops produced in drier regions would be devastated in a significant number of seasons; for example, by the 2070s, up to 19.5%, 21.5% and 47.0% of seasons with winter rape, spring barley and winter wheat, respectively, would have a yield level below 50% of the present yield. Negative impacts are likely even on premium-quality soils regardless of the use of a flexible sowing date and accounting for increasing CO2 concentrations. Moreover, in some cases, the use of catch crops can have negative impacts, exacerbating the soil water deficit for the subsequent crops. This study (submitted to Climate Research journal) will be used as a pilot for subsequent activities. In this area, following calculations (the same set of stations and updated climate scenarios) using growth models ensemble (currently includes 12 modeling approaches) started to estimate uncertainty aspects. Consequently, the analysis within wider range of conditions (across continents) and farming methods will be conducted. No Label

Abstract: Climate change poses fundamental challenges on agriculture. It triggers autonomous adaptation responses of famers and thereby impacts the success of climate change mitigation. Integrated modelling frameworks (IMF) on land use serve as decision support instruments under such conditions by considering climate signals and accounting for combined mitigation and adaptation policies. We apply an IMF at the farm level in two contrasting grassland and cropland dominated landscapes in Austria to analyze climate change impacts on land use as well as impacts from mitigation and adaptation policies on the abiotic and biotic environment and the landscape. Results show that the impacts on farm gross margins and the abiotic and biotic environment are substantial either directly from climate change (e.g. changing erosion levels) or triggered via adaptation responses (i.e. land use and management change). Average gross margins increase between 1% and 12% depending on the case study landscape, the climate change scenario, and the policy scenario. With respect to biodiversity indicators, land use changes in the adaptation scenario decrease plant species diversity on farmland by 13% on average and losses are up to 80% for some farms. These changes are driven by policies in the adaptation scenario as responses on climate change in the absence of policies are modest with minor impacts on biodiversity. Results indicate the effectiveness of climate change adaptation in increasing farm incomes and the need to coordinate mitigation and adaptation policies to manage environmental outcomes. The IMF turns out to be effective in revealing heterogeneity of climate change impacts among farms and regions and linkages among adaptation and mitigation policies. No Label