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

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

Abstract: Maize (Zea mays L) is one of the most important food crops and very common in all parts of sub-Saharan Africa. In 2010 53 million tons of maize were produced in sub-Saharan Africa on about one third of the total harvested cropland area (similar to 33 million ha). Our aim is to identify the limiting agroclimatic variable for maize growth and development in sub-Saharan Africa by analyzing the separated and combined effects of temperature and precipitation. Under changing climate, both climate variables are projected to change severely, and their impacts on crop yields are frequently assessed using process-based crop models. However it is often unclear which agroclimatic variable will have the strongest influence on crop growth and development under climate change and previous studies disagree over this question. We create synthetic climate data in order to study the effect of large changes in the length of the wet season and the amount of precipitation during the wet season both separately and in combination with changes in temperature. The dynamic global vegetation model for managed land LPJmL is used to simulate maize yields under current and future climatic conditions for the two 10-year periods 2056-2065 and 2081-2090 for three climate scenarios for the A1b emission scenario but without considering the beneficial CO2 fertilization effect. The importance of temperature and precipitation effects on maize yields varies spatially and we identify four groups of crop yield changes: regions with strong negative effects resulting from climate change (<-33% yield change), regions with moderate (-33% to -10% yield change) or slight negative effects (-10% to +6% yield change), and regions with positive effects arising from climate change mainly in currently temperature-limited high altitudes (>+6% yield change). In the first three groups temperature increases lead to maize yield reductions of 3 to 20%, with the exception of mountainous and thus cooler regions in South and East Africa. A reduction of the wet season precipitation causes decreases in maize yield of at least 30% and prevails over the effect of increased temperatures in southern parts of Mozambique and Zambia, the Sahel and parts of eastern Africa in the two projection periods. This knowledge about the limiting abiotic stress factor in each region will help to prioritize future research needs in modeling of agricultural systems as well as in drought and heat stress breeding programs and to identify adaption options in agricultural development projects. On the other hand the study enhances the understanding of temperature and water stress effects on crop yields in a global vegetation model in order to identify future research and model development needs. (C) 2013 Elsevier B.V. All rights reserved.