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Scollan, N., Bannink, A., Kipling, R., Saetnan, E., & Van Middelkoop, J. (2015). Livestock and feed production, especially dairy and beef. In FACCE MACSUR Reports (Vol. 6, pp. Sp6–3). Brussels.
Abstract: Improving health and welfare is an important adaptation and mitigation strategyDeveloping process based modelling, responsive to adaptationLinks to climate and land use change modelling are essential Livestock systems likely to be hit hardest by climate changeNeed to develop animal health models that respond to adaptation by farmersBringing together direct and indirect impacts of climate change vitalAdaptation and mitigation need to be considered and modelled togetherLinking models across scales is important to support policy decisionsLearning between sectors carries potential for novel solutions and methodological advancesEffective communication of outcomes to stakeholders (how?) 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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Banse, M. (2015). Climate-change impacts on farming systems in the next decades: Why worry when you have CAP? A FACCE MACSUR workshop for policymakers – Introduction. In FACCE MACSUR Reports (Vol. 6, pp. SP6–1). Brussels.
Abstract: MACSUR’s aims•To analyze the effects of climate change for farming conditions in European regions •To identify risks for farmers, to jointly develop mitigation and adaptation options•To analyze consequences of mitigation and adaptation for farming competitiveness, the environment and rural developmentMACSUR’S mission •improve and integratemodels – crop and livestock production, farms, and national & international agri-food markets•demonstrate integration and links – models for selected farming systems and regions •provide hands-on training- young and experienced researchers in integrative modelingProgramme of the workshop•Presentation of current achievements—Regional Pilots on climate adaptation —EU-level assessments •Intensive discussion with all participants—What are your knowledge needs ?—What can MACSUR-2 contribute ?—How to collaborate ?—Next steps of interaction No Label
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Saetnan, E. R. (2015). Capacity building strategy (Vol. 7).
Abstract: Introduction Raising the capacity of established researchers Capacity for cross-theme collaboration Short “Master Classes” Raising the capacity of early career researchers PhD/ECR training courses Training integrative and international modellers through a Marie Curie ITN Raising the capacity of our stakeholders MACSUR input to the Advanced Training Partnership (ATP)
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Bodirsky, B. L., Rolinski, S., Biewald, A., Weindl, I., Popp, A., & Lotze-Campen, H. (2015). Global Food Demand Scenarios for the 21st Century. PLoS One, 10(11), e0139201.
Abstract: Long-term food demand scenarios are an important tool for studying global food security and for analysing the environmental impacts of agriculture. We provide a simple and transparent method to create scenarios for future plant-based and animal-based calorie demand, using time-dependent regression models between calorie demand and income. The scenarios can be customized to a specific storyline by using different input data for gross domestic product (GDP) and population projections and by assuming different functional forms of the regressions. Our results confirm that total calorie demand increases with income, but we also found a non-income related positive time-trend. The share of animal-based calories is estimated to rise strongly with income for low-income groups. For high income groups, two ambiguous relations between income and the share of animal-based products are consistent with historical data: First, a positive relation with a strong negative time-trend and second a negative relation with a slight negative time-trend. The fits of our regressions are highly significant and our results compare well to other food demand estimates. The method is exemplarily used to construct four food demand scenarios until the year 2100 based on the storylines of the IPCC Special Report on Emissions Scenarios (SRES). We find in all scenarios a strong increase of global food demand until 2050 with an increasing share of animal-based products, especially in developing countries.
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