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Frank, S., Witzke, P., Zimmermann, A., Havlik, P., & Ciaian, P. (2014). Climate Change Impacts on European Agriculture: A Multi Model Perspective..
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Zimmermann, A., Witzke, H. - P., & Heckelei, T. (2013). Filling gaps: AgMIP scenario results from CAPRI (Vol. 2).
Abstract: 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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Köchy, M., & Zimmermann, A. (2013). Workshop on Regional Pilot Studies, 5-7 June 2013, Braunschweig (Vol. 2).
Abstract: The workshop was called to define an overarching question to be answered by all Regional Pilot Studies and to select from the existing studies those that fit best to the aims of MACSUR. The question that evolved from the discussions is “What would be the different contributions of different European adaptation strategies to ensure global food security until 2050 at different scales (farm to EU) while keeping the GHG targets?” Workshop participants agreed to use the newest climate simulations related to Representative Concentration Pathways that were also used by the AgMIP and ISI-MIP projects. There was also agreement to use a subset of the AgMIP scenarios (S2-S6) for impact assessments, with AgMIP scenario S1 as the reference scenario, for details see Table 3 below. The selection of Regional Pilot Studies was discussed separately for European Grand Regions, but there was no concluding decision taken. The Project Steering Committee will finally decide on showcase studies at a meeting in the first week of July based on characterisations sent in by interested members. Questionnaires for characterising the Regional Pilot Studies will be sent by the Hub to the regional contact persons mentioned in Table 2 to fill in. The characterization list can be extended. The questionnaires should be filled in by the end of June. Stakeholder meetings are planned for October 2013 in each region where preliminary/sample outputs of the regional pilot studies should be presented. Results will be presented at the mid-term meeting in April 2014. The last year of MACSUR is then available to improve the studies.The geographic extent of the Regional Pilot Studies is approximately county level – representing the area of the studies they are based on. The Regional Pilot Studies will be linked within the grand regions (northern, central, southern Europe) by consistent regional and continental Representative Agricultural Pathways (RAP). These regional RAPs will feed into the RAP process underway at AgMIP. Through the common RAPs the Regional Pilot Studies will reflect the common challenges of the greater region and by having several Regional Pilot Studies the diversity of the environment, farming systems, and political systems is represented. The workshop was a first step into further planning and performing the Regional Pilot Studies that will fine-tune the results of the workshop. No Label
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Zimmermann, A. (2015). Crop yield trends and variability in the EU (Vol. 5).
Abstract: Agreeing that increased future global food demand will have to be met by production intensification rather than land use expansion (e.g. Hertel, 2011), scientists have moved to empirically analyse the causes for differences between potentially attainable yields and actually realized yields – the yield gap (e.g. van Ittersum et al., 2013, Neumann et al., 2010). In the long run, we aim at disentangling the effects of biophysical, economic and political impacts and farmers’ response to them on crop yields by analysing yield gaps at regional scale in the European Union. Apart from generally improving our understanding of yield gaps and their drivers in the EU, our analysis will contribute to the integration of economic and biophysical models at a later stage of our research. As a first step towards an advanced yield gap analysis, the current paper will give an overview of yield developments in the EU27. The overview will be based on regional yield trend and yield variability estimates derived from socioeconomic panel data from the Farm Accountancy Data Network (FADN). The analysis will continue and extend the work of Ewert et al. (2005) and Reidsma et al. (2009) in terms of drawing on single farm instead of country level/farm type data, including the new EU member states and most recent years (until 2011). The EU-wide analysis of yield trends and variability will serve as a basis for the later analysis of yield gaps. No Label
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Zimmermann, A., & Britz, W. (2016). European farms’ participation in agri-environmental measures. Land Use Policy, 50, 214–228.
Abstract: Due to their diversity and voluntariness, agri-environmental measures (AEMs) are among the Common Agricultural Policy instruments that are most difficult to assess. We provide an EU-wide analysis of AEM adoption and farm’s total AEM support over total Utilised Agricultural Area using a Heckman sample selection approach and single farm data. Our analysis covers 22 Member States over the 2000-2009 period, assesses the entire portfolio of AEMs and focuses on the relationship between AEM participation and farming system. Results show that participation in AEMs is more likely in less intensive production systems, where, however, per committed hectare AEM premiums tend to be lower. Member States group into three categories: high/low intensity farming systems with low/high AEM enrollment rates, respectively, and large high diversity countries with medium AEM enrollment rates. (C) 2015 Elsevier Ltd. All rights reserved.
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