Abstract: Agricultural elements have been covered in the scenario process on shared socio-economic  pathways (SSPs) incompletely and pathways have not been specified for the future  development of the European Union. We will therefore devise a general framework on  European Representative Agricultural Pathways (EU-RAPs), where we cover different  aspects of agricultural development, as for example European and domestic agricultural and  environmental policies, or different livestock and crop management systems, and describe  future developments of the confederation of the countries of the European Union. For the  agricultural elements we distinguish between elements that can be derived from the  definitions in the Shared Socioeconomic Pathways, as for example irrigation efficiencies  which are linked to technological development, and elements that have to be newly devised  such as the development of the Common Agricultural Policy. For the future of the European  Union we develop five different worlds which correspond to the SSPs. Finally both  frameworks are combined.

Abstract: This paper addresses protein crop production in Europe. European food and feed industries highly depend on imported protein crops and derived products and climate change is likely to affect domestic protein crop production and thus the import dependency. The recent reform of EU agricultural policy reform aims at promoting climate friendly agricultural practices and stimulating the production of protein crops. We choose three contrasting climate change scenarios as well as specifications of the recent CAP reform in order to investigate how farmers might adapt to changing land use restrictions and climate conditions. Output response, land allocation and nitrogen use are the main variables of interest. Exemplified for Austrian cropland, we apply an integrated modeling framework consisting of a statistical climate change model, a crop rotation model, the bio-physical process model EPIC, and the economic bottom-up land use optimization model BiomAT. This model maximizes total gross margins by optimizing for land use and crop management practices for different scenarios of climate change and market conditions. Results obtained at a 1 km grid are aggregated to the national level. The model results indicate that changes in policy conditions, cropland use, and flexibility in crop management practices may have stronger effects on total protein crop production than climate change in the next decades. An expansion of current protein crop production leads to an increase in marginal opportunity costs, reduces mineral fertilizer input demand, and mainly replaces maize in the crop rotations. No Label

Abstract: Ruminant production systems are important producers of food, support rural communities and culture, and help to maintain a range of ecosystem services including the sequestering of carbon in grassland soils. However, these systems also contribute significantly to climate change through greenhouse gas (GHG) emissions, while intensi- fication of production has driven biodiversity and nutrient loss, and soil degradation. Modeling can offer insights into the complexity underlying the relationships between climate change, management and policy choices, food production, and the maintenance of ecosystem services. This paper 1) provides an overview of how ruminant systems modeling supports the efforts of stakeholders and policymakers to predict, mitigate and adapt to climate change and 2) provides ideas for enhancing modeling to fulfil this role. Many grassland models can predict plant growth, yield and GHG emissions from mono-specific swards, but modeling multi-species swards, grassland quality and the impact of management changes requires further development. Current livestock models provide a good basis for predicting animal production; linking these with models of animal health and disease is a prior- ity. Farm-scale modeling provides tools for policymakers to predict the emissions of GHG and other pollutants from livestock farms, and to support the management decisions of farmers from environmental and economic standpoints. Other models focus on how policy and associated management changes affect a range of economic and environmental variables at regional, national and European scales. Models at larger scales generally utilise more empirical approaches than those applied at animal, field and farm-scales and include assumptions which may not be valid under climate change conditions. It is therefore important to continue to develop more realistic representations of processes in regional and global models, using the understanding gained from finer-scale modeling. An iterative process of model development, in which lessons learnt from mechanistic models are ap- plied to develop ‘smart’ empirical modeling, may overcome the trade-off between complexity and usability. De- veloping the modeling capacity to tackle the complex challenges related to climate change, is reliant on closer links between modelers and experimental researchers, and also requires knowledge-sharing and increasing technical compatibility across modeling disciplines. Stakeholder engagement throughout the process of model development and application is vital for the creation of relevant models, and important in reducing problems re- lated to the interpretation of modeling outcomes. Enabling modeling to meet the demands of policymakers and other stakeholders under climate change will require collaboration within adequately-resourced, long-term inter-disciplinary research networks