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Zimmermann, A.; Witzke, H.-P.; Heckelei, T. |
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Filling gaps: AgMIP scenario results from CAPRI |
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2013 |
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FACCE MACSUR Reports |
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2 |
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D-T1.4 |
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Climate change impacts on food production, socioeconomic changes (population and income growth in large parts of the world) and biofuel policies affecting demand quantities have risen scientific, political and public interest in long-term forecasts on food security. Whereas first quantitative analyses from global economic models are starting to appear (e.g. (von Lampe et al., under review)), similar studies on smaller regional scales are not yet available. However, acknowledging that climate change affects crop yields differently across scales and regions (e.g. (Reidsma et al., 2007)) and considering the specific political setting given through the Common Agricultural Policy (CAP) in Europe, the MACSUR project focuses on the impact of climate change and socioeconomic changes on European agriculture and its contribution to global food security. We present a Europe-wide analysis of the effect of selected climate and socioeconomic scenarios on food security in terms of food prices using the Common Agricultural Policy Regionalised Impact modelling system (CAPRI). No Label |
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MA @ admin @ |
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2246 |
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Barnes, A.; Moran, D. |
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Title |
Modelling Food Security and Climate Change: Scenario Analysis |
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2013 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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1 |
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D-T1.2 |
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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 |
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MA @ admin @ |
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2262 |
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Bojar, W. |
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Title |
Factsheets of the models |
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2013 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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1 |
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D-T1.1 |
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The exploration of adaptation and mitigation measures in the context of global challenges like climate change, food security and expected demographic boom is an field of research of growing importance. Over the last decades many research groups have been developing economic-trade models to analyse consequences on farm welfare, market supply and trade, some of them also address food security and other global concerns. There are many different ways to tackle these issues and the specific advantages and limitations of alternative modelling strategies are not yet well understood. The objective of the WP1 T1.1 task within TradeM theme of MACSUR is to use the results of a survey on trade and economic models of MACSUR Consortium partners to show which topics are currently addressed in the different models, which methods are used and how well these tools are prepared for an integration with other models like climate, crop and livestock models. This work was co-financed by NCBiR, Contract no. FACCE JPI/04/2012 – P100 PARTNER No Label |
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MA @ admin @ |
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2261 |
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Bellocchi, G.; Ma, S.; Köchy, M.; Braunmiller, K. |
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Datasets classification and criteria for data requirements |
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2013 |
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FACCE MACSUR Reports |
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2 |
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D-L2.1.2 |
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This deliverable focuses on the collation, screening, and consolidation of data for selected grassland sites in Europe and peri-Mediterranean regions. No Label |
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MA @ admin @ |
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2245 |
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Bellocchi, G.; Ma, S.; Köchy, M.; Braunmiller, K. |
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Identified grassland-livestock production systems and related models |
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2013 |
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FACCE MACSUR Reports |
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2 |
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D-L2.1.1 |
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This report describes grassland-livestock production systems, as selected for model-basedstudies. A list of grassland models was identified for evaluation against such datasets(WP2) and application at reference farm (WP3) and regions (WP4) across Europe and peri-European countries. No Label |
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MA @ admin @ |
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2244 |
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