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Bellocchi, G., & Ma, S. (2014). Results of uncalibrated grassland model runs (Vol. 3).
Abstract: 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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Bellocchi, G., Rivington, M., & Acutis, M. (2014). Protocol for model evaluation (Vol. 3).
Abstract: This deliverable focuses on the development of methods for model evaluation in order to have unambiguous indications derived from the use of several evaluation metrics. The information about model quality is aggregated into a single indicator using a fuzzy expert system that can be applied to a wide range of model estimates where suitable test data are available. This is a cross-cutting activity between CropM (C1.4) and LiveM (L2.2). No Label
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Köchy, M., Jorgenson, J., & Braunmiller, K. (2015). Overview of case studies (Vol. 6).
Abstract: MACSUR comprises 18 regional case studies for analysing the effects of climate change on agriculture with integrated inter-disciplinary models. Three case studies in Finland, Austria, and Italy have been selected as pilot studies because of their advancement in integration and representation of European farming systems and regions. No Label
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Hoveid, Ø. (2015). Prototype of stochastic equilibrium model of the food system (Vol. 6).
Abstract: Food security is an issue of risk. If climate change is not responded to with diet, technology and/or policy changes, it may lead to reduced food security for the world population, in particular the poorer part which in longer periods may not afford to purchase food in sufficient quantity and quality. In order to improve the situation, certain policy changes may be required. In some cases are policy recommendations relatively obvious, while in other cases a deeper insight in the stochastic dynamics of food supply and storage is required to assess the consequences of policy proposals. The relatively obvious part is that farmers need be responsive in periods of low total production, so that sufficient supply restores quickly. Moreover, trade should allow local shortages to be covered. Many national policies with the goal of self-sufficiency aim in the opposite direction with stable prices and production and relatively less flexibility in production. The stochastic dynamics of food supply can be analysed in more detail with a dynamic stochastic general equilibrium model (DSGE). Although agriculture by nature is about taking decisions under uncertainty, quantitative stochastic dynamic models for policy analysis in agriculture have not yet emerged. The contribution in MACSUR is a formalization of a class of DSGE-s based on representation of biological processes managed with regard to outcomes due to uncertain nature. No Label
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Palatnik, R. R. (2015). Climate-dependent yields (Vol. 6).
Abstract: In this report we summarize the contributions made by four groups to the subject of climate dependent yields. The first is by Waldemar Bojar, Leszek Knopik, Jacek Zarski, Cezary Slawinski, Piotr Baranowski and Wojciech Zarski on the subject of “the impact of extreme climate changes on the forecasted agriculture production”. It presents general characteristics of resources and outputs of agriculture in the Kujawsko-Pomorskie (K&P) and Lubelskie regions, based on statistical databases and the literature review. In this study, some statistically significant dependencies between the climatic parameters and yields of selected important crops in the abovementioned regions were worked out on the basis of empirical survey conducted in the University of Technology and Life Sciences and Institute of Agrophysics in Lublin. Efforts were taken to make integrated assessments of forecasted agricultural outputs influenced by climate extreme phenomena on the basis of the found dependencies’ yields – precipitation and the data coming from wide area model regional outputs such as prices, areas of farmland and yields. The second contribution is by Bojar W., Knopik L. and Zarski J. on the subject of “integrated assessment of business crop productivity and profitability to use in food supply forecasting”. It examines the proposals to build a model describing the amount of precipitation and taking into account periods without rain. This model is based on a mixture of gamma distribution and one point-distribution. The third contribution is by Iddo Kan on the Vegetative Agricultural Land Use Economic (VALUE) model. It discusses the sub-task with respect to crops of statistically estimating with statistical methods predictions of expected crop-yield contingent on climate, soil and production cost for use in existing trade models, or refined versions thereof, and how VALUE can contribute to this sub-task. The fourth contribution was made by Christoph Muller and Richard D. Robertson on the subject of “projecting future crop productivity for global economic modelling”. It supplies a set of climate impact scenarios on agricultural land productivity derived from two climate models and two biophysical crop growth models to account for some of the uncertainty inherent in climate and impact models. No Label
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