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Janssen, S.; Houtkamp, J.; De Groot, H.; Schils, R. |
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Title |
Online web tool for data visualization |
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Report |
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2015 |
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FACCE MACSUR Reports |
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6 |
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D-C2.6 |
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This deliverable lays out the work as done as part of MACSUR CropM on data, with the focus on providing a web tool for visualization of model output. It was decided early on that not a specific MACSUR web tool would be developed as part of MACSUR for phase 1, and mostly results would be visualized in other available tools, such as the Global Yield Gap Atlas, which are recognised resources for visualizations. Only in relationship to the MACSUR Geonetwork data catalog hosted at Aarhus University some developments where started. Operationally speaking, most data was still being generated during phase 1, so there was not enough to visualize on specific websites and partners did not commit financial resources to their development, and only in kind was available. No Label |
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MA @ admin @ |
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2093 |
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Ewert, F.; Rötter, R.P.; Bindi, M.; Webber, H.; Trnka, M.; Kersebaum, K.; Christian,; Olesen, J.E.; Van Ittersum, M.K.; Janssen, S.; Rivington, M.; Semenov, M.A.; Wallach, D.; Porter, J.R.; Stewart, D.; Verhagen, J.; Gaiser, T.; Palosuo, T.; Tao, F.; Nendel, C.; Roggero, P.P.; Bartošová, L.; Asseng, S. |
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Crop modelling for integrated assessment of risk to food production from climate change |
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2015 |
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FACCE MACSUR Reports |
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6 |
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D-C0.3 |
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The complexity of risks posed by climate change and possible adaptations for crop production has called for integrated assessment and modelling (IAM) approaches linking biophysical and economic models. This paper attempts to provide an overview of the present state of crop modelling to assess climate change risks to food production and to which extent crop models comply with IAM demands. Considerable progress has been made in modelling effects of climate variables, where crop models best satisfy IAM demands. Demands are partly satisfied for simulating commonly required assessment variables. However, progress on the number of simulated crops, uncertainty propagation related to model parameters and structure, adaptations and scaling are less advanced and lagging behind IAM demands. The limitations are considered substantial and apply to a different extent to all crop models. Overcoming these limitations will require joint efforts, and consideration of novel modelling approaches. No Label |
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MA @ admin @ |
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2089 |
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Ewert, F.; Rötter, R.P.; Bindi, M.; Webber, H.; Trnka, M.; Kersebaum, K.C.; Olesen, J.E.; van Ittersum, M.K.; Janssen, S.; Rivington, M.; Semenov, M.A.; Wallach, D.; Porter, J.R.; Stewart, D.; Verhagen, J.; Gaiser, T.; Palosuo, T.; Tao, F.; Nendel, C.; Roggero, P.P.; Bartošová, L.; Asseng, S. |
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Crop modelling for integrated assessment of risk to food production from climate change |
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2015 |
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Environmental Modelling & Software |
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Env. Model. Softw. |
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72 |
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287-303 |
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uncertainty; scaling; integrated assessment; risk assessment; adaptation; crop models; agricultural land-use; change adaptation strategies; farming systems simulation; agri-environmental systems; enrichment face experiment; high-temperature stress; change impacts; nitrogen dynamics; atmospheric co2; spring wheat |
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The complexity of risks posed by climate change and possible adaptations for crop production has called for integrated assessment and modelling (IAM) approaches linking biophysical and economic models. This paper attempts to provide an overview of the present state of crop modelling to assess climate change risks to food production and to which extent crop models comply with IAM demands. Considerable progress has been made in modelling effects of climate variables, where crop models best satisfy IAM demands. Demands are partly satisfied for simulating commonly required assessment variables. However, progress on the number of simulated crops, uncertainty propagation related to model parameters and structure, adaptations and scaling are less advanced and lagging behind IAM demands. The limitations are considered substantial and apply to a different extent to all crop models. Overcoming these limitations will require joint efforts, and consideration of novel modelling approaches. |
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English |
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1364-8152 |
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CropM, ft_macsur |
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MA @ admin @ |
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4521 |
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Rosenzweig, C.; Jones, J.W.; Hatfield, J.L.; Ruane, A.C.; Boote, K.J.; Thorburn, P.; Antle, J.M.; Nelson, G.C.; Porter, C.; Janssen, S.; Asseng, S.; Basso, B.; Ewert, F.; Wallach, D.; Baigorria, G.; Winter, J.M. |
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The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and pilot studies |
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2013 |
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Agricultural and Forest Meteorology |
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Agricultural and Forest Meteorology |
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170 |
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166-182 |
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0168-1923 |
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CropM, ftnotmacsur, IPCC-AR5 |
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MA @ admin @ |
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4927 |
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Acharya, T.; Fanzo, J.; Gustafson, D.; Ingram, J.; Schneeman, B.; Allen, L.; Boote, K.; Drewnowski, A.; Ewert, F.; Hall, S.; Hendley, P.; Howden, M.; Janssen, S.; Jones, J.; Latulippe, M.; Lotze-Campen, H.; McDermott, J.; Meijl, H.V.; Nelson, G.; Newsome, R.; Roulin, A.; Scholes, B.; Tanumihardjo, S.; Tavill, G.; van der Mensbrugghe, D.; Wiebe, K. |
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Title |
Assessing Sustainable Nutrition Security: The Role of Food Systems: Working Paper |
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2014 |
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ftnotmacsur |
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Washington, D.C., U.S.A. |
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ILSI Research Foundation: Center for Integrated Modeling of Sustainable Agriculture and Nutrition Security |
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TradeM |
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MA @ admin @ |
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4995 |
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