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Author Köchy, M.; Bishop, J.; Lehtonen, H.; Scollan, N.; Webber, H.; Zimmermann, A.; Bellocchi, G.; Bannink, A.; Biewald, A.; Ferrise, R.; Helming, K.; Kipling, R.P.; Milford, A.; Özkan Gülzari, Ş.; Ruiz-Ramos, M.; Curth-van Middelkoop, J.
Title Challenges and research gaps in the area of integrated climate change risk assessment for European agriculture and food security Type Report
Year 2017 Publication FACCE MACSUR Reports Abbreviated Journal
Volume 10 Issue Pages (up) H0.1-D
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Abstract Priorities in addressing research gaps and challenges should follow the order of im­por­tance, which in itself would be a matter of defining goals and metrics of importance, e.g. the extent, impact and likelihood of occurrence. For improving assessments of cli­mate change impacts on agriculture for achieving food security and other sustainable develop­ment goals across the European continent, the most important research gaps and challen­ges appear to be the agreement on goals with a wide range of stakeholders from policy, science, producers and society, better reflection of political and societal prefer­ences in the modelling process, and the reflection of economic decisions in farm manage­ment within models. These and other challenges could be approached in phase 3 of MACSUR.
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Call Number MA @ admin @ Serial 4950
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Author Barnes, A.; Moran, D.
Title Modelling Food Security and Climate Change: Scenario Analysis Type Report
Year 2013 Publication FACCE MACSUR Reports Abbreviated Journal
Volume 1 Issue Pages (up) D-T1.2
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Abstract 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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Call Number MA @ admin @ Serial 2262
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Author Bojar, W.
Title Factsheets of the models Type Report
Year 2013 Publication FACCE MACSUR Reports Abbreviated Journal
Volume 1 Issue Pages (up) D-T1.1
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Abstract 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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Call Number MA @ admin @ Serial 2261
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Author Rolinski, S.; Sætnan, E.
Title Uncertainties in climate change prediction and modelling Type Report
Year 2013 Publication FACCE MACSUR Reports Abbreviated Journal
Volume 1 Issue Pages (up) D-L1.5
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Abstract As models become increasingly complex and integrated, uncertainty among model  parameters, variables and processes become critical for evaluating model outcomes and  predictions. A framework for understanding uncertainty in climate modelling has been  developed by the IPCC and EEA which provides a framework for discussion of uncertainty  in models in general. Here we report on a review of this framework along with the results  of a survey of sources of uncertainty in livestock and grassland models. Along with the  identification of key sources of uncertainty in livestock and grassland modelling, the  survey highlighted the need for a development of a common typology for uncertainty.  When collaborating across traditionally separate research fields, or when communicating  with stakeholders, differences in understanding, interpretation or emphasis can cause  confusion. Further work in MACSUR should focus on improving model intercomparison  methods to better understand model uncertainties, and improve availability of high  quality datasets which can reduce model uncertainties. No Label
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Call Number MA @ admin @ Serial 2259
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Author Braunmiller, K.; Köchy, M.
Title Grassland datasets Type Report
Year 2013 Publication FACCE MACSUR Reports Abbreviated Journal
Volume 1 Issue Pages (up) D-L1.3
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Abstract In the MACSUR project, there are several grassland models in use that were designed for and adjusted with data from different climatic regions. To be able to run these modelsfor a wide geographical range, there is a need to validate and calibrate them on the same basis.Therefore, a high-quality dataset is needed, which includes a wide range of climatic conditions, management systems and other variables.Through this search 23 grassland related institutes from eleven countries were found and contacted, where 12 of them responded to the request. Nine institutes from cooler (e.g. Finland) and warmer regions (e.g. Israel) are now willing to provide their experimental data. One contributor is even planning to join the project bringing its own grassland model.These new grassland datasets cover in addition to already available ones (Fig. 1) a wide range of climatic regions for a substantiated calibration and validation of the models. Data supplied by the institutes have been checked for internal consistency and cast into a common format. The data have been passed on to WP L2 (Model intercomparison on climate change in relation to livestock and grassland). No Label
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Call Number MA @ admin @ Serial 2258
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