Highlights
We present scenarios for European agriculture and food systems: the Eur-Agri-SSPs.
The five Eur-Agri-SSPs describe plausible and consistent developments until 2050.
We followed a nine-step protocol to ensure a systematic and transparent process.
European stakeholders provided regional and thematic details and valuable feedback.
The Eur-Agri-SSPs can inform integrated assessments, education, and policy making.
This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.agsy.2016.05.007Ruminant 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 intensification 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 priority. 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 applied to develop ?smart? empirical modeling, may overcome the trade-off between complexity and usability. Developing 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 related 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.authorsversionPeer reviewe
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AbstractThe Common Agricultural Policy (CAP) was fundamentally reformed in 2003. From 2005 on, farmers will receive decoupled income support payments instead of production premiums if basic standards for environment, food safety, animal health and welfare are met. Farmers will likely adjust production and management practices to the new policy framework. We describe how this reform fits into the EU strategy of making agricultural production more environmentally friendly by concentrating on financial aspects. Using an agricultural sector model for Austria, we show that the reform will further decrease agricultural outputs, reduce farm inputs, lessen nitrogen surpluses and make environmentally friendly management practices more attractive for farmers.JEL classification: Q12, Q18, Q24, Q28
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