Schönhart, M., Schauppenlehner, T., Kuttner, M., & Schmid, E. (2015). Integrated Assessment of Climate Change Mitigation and Adaptation Impacts at Landscape level: Mostviertel, Austria. In FACCE MACSUR Reports (Vol. 6, SPp. 6). Brussels.
Abstract: ConclusionsIncreasing productivity can increase intensification pressuresThreatened permanent (extensive) grasslands and landscape elements, butsubject to resource constraints, costs and prices andfuture production potential to increase global food supplyFuture RDP and environmental policy design (e.g. WFD) should take changing productivity into accountHeterogeneity matters at farm and regional levelChanging relative competitiveness of farmsFuture research: analyze uncertainties No Label
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Ewert, F., Rötter, R., & Brüser, K. (2015). CropM: Understanding and Modelling Impacts of Climate Change on Crop Production. In FACCE MACSUR Reports (Vol. 6, pp. SP6–2). Brussels.
Abstract: Key ambition:To developa shared comprehensive information system on the impacts of climate change on European crop production and food securityfirst shared pan-continental assessments and tools(Full) range of important crops and important crop rotationsImproved management and analysis of dataModel improvement (stresses and factors not yet accounted for)Advanced scaling methodsAdvanced link to farm and sector modelsComprehensive uncertainty assessment and reportingTo train integrative crop modelerData. for better understanding and modelling climate change impactEvaluation of data quality (platinum, gold, silver)Quantify data gaps for modellingEmpirical analysis of crop responses to past climate variability and changeObserved adaptation options and their efficacyEffect of extreme events (past analysis and projections)Climate change scenariosConcept for data management, data journalUncertaintyMethodology & protocols for uncertainty analysisMethodology for standardized model evaluationLocal-scale climate scenarios & uncertainties in climate projectionsBasic methodology for probabilistic assessment of CC impacts using impact response surfacesMethodology for probabilistic evaluation of alternative adaptation options Main aims in MACSUR2:Improve crop model to better capture extremesComplement knowledge from crop models with empirical crop-weather analysisConsider management variables in simulationsFull range of methods for analysing uncertainty in climate impact assessmentsEvaluate potential adaptation optionsContributing to cross-cutting issues and case studies.Further the links with other modelling activitiesLink local to European and global responses No Label
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Bojar, W., Dzieza, G., Sikora, M., Spiewak, J., Wyszkowska, Z., Januszewski, A., et al. (2014). Wybrane metody ograniczania dzialania czynników ryzyka w rolnictwie w swietle wspólczesnych wyzwan (Selected methods of limiting of risk factors in agriculture in a view of contemporary challenges) Y ograniczania dzialania czynników ryzyka w rolnictwie. Roczniki naukowe ekonomii rolnictwa i rozwoju obszarów wiejskich, 101(4), 7–18.
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Graef, F., Sieber, S., Mutabazi, K., Asch, F., Biesalski, H. K., Bitegeko, J., et al. (2014). Framework for participatory food security research in rural food value chains. Global Food Security, 3(1), 8–15.
Abstract: Enhancing food security for poor and vulnerable people requires adapting rural food systems to various driving factors. Food security-related research should apply participatory action research that considers the entire food value chain to ensure sustained success. This article presents a research framework that focusses on determining, prioritising, testing, adapting and disseminating food securing upgrading strategies across the multiple components of rural food value chains. These include natural resources, Food production, processing, markets, consumption and waste management. Scientists and policy makers jointly use tools developed for assessing potentials for enhancing regional food security at multiple spatial and temporal scales. The research is being conducted in Tanzania as a case study for Sub-Saharan countries and is done in close collaboration with local, regional and national stakeholders, encompassing all activities across all different food sectors. (C) 2014 Elsevier B.V. All rights reserved.
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Virkajärvi, P., Jing, Q., Bélanger, G., Baron, V., Bonesmo, H., & Young, D. (2013). Modeling grassland with CATIMO – focus on the second cut. (Vol. 9(1), pp. 9–13).
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