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Barnes, A.; Shrestha, S.; Thomson, S.; Toma, L.; Mathews, K.; Sutherland, L.A. |
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Comparing visions for CAP reforms post 2015: Farmer intentions and farm bio-economic modelling |
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2014 |
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FACCE MACSUR Reports |
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3 |
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Sp3-2 |
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This paper illustrates the impacts of two of the potential CAP reform post 2015 scenarios using an optimising farm level model and compares results with farmers’ perception about the policy changes, captured in a farmer intentions survey. The model results suggest that beef farms suffer a loss in farm net margins under fully decoupled (up to -21%) as well as under partially decoupled scenario (up to -19%) compared to current historical single farm payments. The model also shows that farm respond by reducing the number of beef animals on farm by up to 5%. However, under a partial decoupled scenario, beef farms increase calf numbers by 15% to benefit from coupled calf payment. A survey of 1,400 beef producers with respect to their intentions toward 2020 was conducted in the Summer of 2013. A set of hypothetical payment scenarios was used to test self-reported response to a number of scenarios related to expanding and extensifying. These were compared with the modelling results and found a range of responses which could, we argue, be used for future calibration and ‘sense-checking’ of results within future modelling strategies. No Label |
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MA @ admin @ |
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2219 |
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Bartley, D. |
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Identification of datasets on climate change in relation to livestock productivity (production and fitness traits) and livestock infectious disease |
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2013 |
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FACCE MACSUR Reports |
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1 |
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D-L1.1 |
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Datasets from Germany and the United Kingdom containing information on geographic (European Union 27 countries), climatic, meteorological, host and infectious agents’ parameters (figure 2) have been completed and are now available for preliminary analysis relating to data quality and consistency. Data set information will continue to be added over the next 12 months. No Label |
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MA @ admin @ |
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2255 |
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Bellocchi, G. |
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Fuzzy-logic based multi-site crop model evaluation |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-5 |
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The most common way to evaluate simulation models is to quantify the agreement between observations and simulations via statistical metrics such as the root mean squared error and the linear regression coefficient of determination. It is agreed that the aggregation of metrics of different nature intro integrated indicators offers a valuable way to assess models. Expanded notions of model evaluation that have recently emerged, based on the trade-off between properties of the model and agreement between predictions and actual data under contrasting conditions, integrate sensitivity analysis measures and information criteria for model selection, as well as concepts of model robustness, and point to expert judgments to explore the importance of different metrics. As a FACCE MACSUR CropM-LiveM action, a composite indicator (MQIm: Model Quality Indicator for multi-site assessment) was elaborated, by a group of specialists, on metrics commonly used to evaluate crop models (with extension to grassland models) while also integrating aspects of model complexity and stability of performances. The indicator, based on fuzzy bounds applied to a set of weighed metrics, was first revised by a broader group of modellers and then assessed via questionnaire survey of scientists and end-users. We document a crop model evaluation in Europe and assess to what extent the MQIm reflects the main components of model quality and supports inferences about model performances. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2120 |
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Bellocchi, G., B.; Brilli, L.; Ferrise, R.; Dibari, C.; Bindi, M. |
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Model comparison and improvement: Links established with other consortia |
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2017 |
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FACCE MACSUR Reports |
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10 |
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XC1.3-D |
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XC1 has established links to other research activities and consortia on model comparison and improvement. They include the global initiatives AgMIP (http://www.agmip.org ) and GRA (http://www.globalresearchalliance.org), and the EU-FP7 project MODEXTREME (http://modextreme.org ). These links have allowed sharing and communication of recent results and methods, and have created opportunities for future research calls. |
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MA @ admin @ |
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4941 |
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Bellocchi, G.; Ma, S. |
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Results of uncalibrated grassland model runs |
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2014 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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3 |
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D-L2.3 |
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This deliverable focuses on the some illustrative results obtained with the grassland models selected (D-L2.1.1) to simulate biomass and flux data from grassland sites in Europe and peri-Mediterranean regions (D-L2.1.1 and D-L2.1.2). This is a blind exercise, carried out without model calibration. The complete set of results will include simulations from calibrated models. The results shown are illustrative of the methodology adopted for grassland model intercomparison in MACSUR. The insights gained from this ongoing study are relevant for some crop and vegetation models, which in some cases proved comparable to grassland-specific models to simulate biomass data from managed grasslands. The results reported here cannot be considered conclusive. Additional results will be published as they become available together with calibration results, as well as the comprehensive evaluation of models with fuzzy logic-based indicators. No Label |
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MA @ admin @ |
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2234 |
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