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Kipling, R.; Topp, K.; Don, A. |
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Title |
The availability of carbon sequestration data in Europe |
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2015 |
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FACCE MACSUR Reports |
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4 |
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D-L1.4.2 |
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With growing interest in the carbon sequestration potential of soils, experimental research and mapping projects have produced a wealth of datasets in this subject area. However, the coverage, quality and scope of available data vary widely across Europe, and the extent to which these data are accessible to experimental researchers and modellers is also highly variable. This report describes the availability of soil carbon data at the global and European levels, and reviews the on-line resources for accessing these data and meta-data. The extent to which researchers in the field share findings, based on institutional links in projects and on-line resources, is investigated. Future priorities for research and data accessibility relating to carbon sequestration are discussed. Many soil data resources are available online. Global and European soil data portals draw together much information from across Europe, and include the outcomes of major soil carbon mapping exercises. However, much project and national research is not accessible through these portals, and information on datasets derived from many research initiatives is difficult or impossible to locate online. Data on carbon sequestration (carbon fluxes in soils) specifically is more limited, although some such datasets are available through the general soil data resources described. Improved clarity in the presentation of research, and work to link more national and sub-national data to European and global online resources is required, with initiatives such as GSIF (Global Soil Information Facility) active in encouraging direct reporting of soil-related data at the global level. Priorities for research on SOC stocks include measuring carbon storage below the topsoil (>30cm), improving records of SOC in peatlands, improving the number and distribution of samples available for Europe-wide soil carbon mapping, and developing recognised methodological standards to allow easier comparisons of datasets. In the field of carbon sequestration research specifically, priorities include linking long-term SOC data to historical land use, developing understanding of the movement of SOC between top-soil and sub-soil and increasing dialogue between modellers and empirical researchers to improve dynamic modelling of SOC. No Label |
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MA @ admin @ |
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2214 |
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Kersebaum, K.; C |
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Title |
Model intercomparison for calibrated models |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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4 |
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D-C1.6 |
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The study ROTATIONEFFECT aims to compare the output of different models simulating field data sets with multi-year crop rotations including different treatments.Within the first Step (1a2a) data sets (comprising a total of 301 crop growth seasons) for 5 locations in Europe were distributed to 15 interested modeller groups.For this step only minimal information for calibration were provided to the modellers. In total 15 modelling teams sent their “uncalibrated” results as single-year calculations and/or continuous calculations of rotation depending on the capability of the model. Results have been evaluated and the paper submitted (European Journal of Agronomy).Now, within the 2nd step (1b2b) modellers were provided with more information on the crop for the calibration of models. Again, results of calibrated runs were collected.6 models were capable to run the rotations as continuous runs and another set of 6 models provided single year simulations.A first overview of the improvement of predictions due to calibration has been produced. Result files have been uploaded to the web platform for CropM results at Aarhus University (Work package C2 – data management). No Label |
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MA @ admin @ |
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2213 |
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Köchy, M.; Jorgenson, J.; Braunmiller, K. |
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Overview of case studies |
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2015 |
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FACCE MACSUR Reports |
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6 |
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D-H2.1 |
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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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MA @ admin @ |
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2116 |
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Hoveid, Ø. |
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Title |
Prototype of stochastic equilibrium model of the food system |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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6 |
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D-T2.5 |
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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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MA @ admin @ |
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2115 |
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Palatnik, R.R. |
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Climate-dependent yields |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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6 |
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D-T2.1 |
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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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MA @ admin @ |
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2114 |
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