Abstract: Developing scenarios is a common interest within MACSUR researchers. This report  outlines the main results of a survey of TRADE-M participants with respect to the  scenarios used within modelling, the time frame and the importance of factors in  their development. Most researchers are generating their own regionally defined  scenarios, though some are basing these on IPCC scenarios. Generally, they adopt  a short-term time frame of up to 2020 to estimate impacts. Most see food  production as the main driver behind the scenarios followed by climate change  mitigation and adaptation. The main weakness seems to be lack of interest in  modelling variability due to weather effects, these may be an argument for  stronger cross-collaboration between different MACSUR consortia within the crops  and animals groups. No Label

Abstract: As models become increasingly complex and integrated, uncertainty among model  parameters, variables and processes become critical for evaluating model outcomes and  predictions. A framework for understanding uncertainty in climate modelling has been  developed by the IPCC and EEA which provides a framework for discussion of uncertainty  in models in general. Here we report on a review of this framework along with the results  of a survey of sources of uncertainty in livestock and grassland models. Along with the  identification of key sources of uncertainty in livestock and grassland modelling, the  survey highlighted the need for a development of a common typology for uncertainty.  When collaborating across traditionally separate research fields, or when communicating  with stakeholders, differences in understanding, interpretation or emphasis can cause  confusion. Further work in MACSUR should focus on improving model intercomparison  methods to better understand model uncertainties, and improve availability of high  quality datasets which can reduce model uncertainties. No Label

Abstract: Modelling of climate effects on agriculture and food security at the European scale requires a harmonized spatially, explicit database of European land use. It can be used for scaling results of point models to an area. A recent review of land cover maps focused on the global scale (Köchy, 2010). European land use as a subset of global land use is contained in the product GlobCover representing the year 2009 with a resolution of 0.3 km. A European product is the CORINE data set with a resolution of 100 m and a minimum mapping unit of 25 ha representing the year 2006 (version 16, European Environmental Agency, 2012). For scaling the results obtained for individual points to larger regions one needs fine-grained maps using the same categories as represented by the sample points. The CORINE map of pasture cover (Fig. 1) has the advantage of being very fine-grained and the classification being supervised. The visual differences to coarser maps of cover matched to census (Fig. 4), however, indicate, that none of the existing maps is reflecting reality perfectly. Since MACSUR will likely work with official national statistics it may be preferable to use one of the census-calibrated maps. For a better match, official EU spatial reporting schemes may be used at a grain that ensures data privacy of the land owners. No Label