| Records |
| Author |
Hoffmann, H.; Zhao, G.; van Bussel, L.G.J.; Enders, A.; Specka, X.; Sosa, C.; Yeluripati, J.; Tao, F.; Constantin, J.; Raynal, H.; Teixeira, E.; Grosz, B.; Doro, L.; Zhao, Z.; Wang, E.; Nendel, C.; Kersebaum, K.C.; Haas, E.; Kiese, R.; Klatt, S.; Eckersten, H.; Vanuytrecht, E.; Kuhnert, M.; Lewan, E.; Rötter, R.; Roggero, P.P.; Wallach, D.; Cammarano, D.; Asseng, S.; Krauss, G.; Siebert, S.; Gaiser, T.; Ewert, F. |
| Title |
Variability of effects of spatial climate data aggregation on regional yield simulation by crop models |
Type |
Journal Article |
| Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
| Volume |
65 |
Issue |
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Pages |
53-69 |
| Keywords |
spatial aggregation effects; crop simulation model; input data; scaling; variability; yield simulation; model comparison; input data aggregation; systems simulation; nitrogen dynamics; data resolution; n2o emissions; winter-wheat; scale; water; impact; apsim |
Abstract  |
Field-scale crop models are often applied at spatial resolutions coarser than that of the arable field. However, little is known about the response of the models to spatially aggregated climate input data and why these responses can differ across models. Depending on the model, regional yield estimates from large-scale simulations may be biased, compared to simulations with high-resolution input data. We evaluated this so-called aggregation effect for 13 crop models for the region of North Rhine-Westphalia in Germany. The models were supplied with climate data of 1 km resolution and spatial aggregates of up to 100 km resolution raster. The models were used with 2 crops (winter wheat and silage maize) and 3 production situations (potential, water-limited and nitrogen-water-limited growth) to improve the understanding of errors in model simulations related to data aggregation and possible interactions with the model structure. The most important climate variables identified in determining the model-specific input data aggregation on simulated yields were mainly related to changes in radiation (wheat) and temperature (maize). Additionally, aggregation effects were systematic, regardless of the extent of the effect. Climate input data aggregation changed the mean simulated regional yield by up to 0.2 t ha(-1), whereas simulated yields from single years and models differed considerably, depending on the data aggregation. This implies that large-scale crop yield simulations are robust against climate data aggregation. However, large-scale simulations can be systematically biased when being evaluated at higher temporal or spatial resolution depending on the model and its parameterization. |
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0936-577x 1616-1572 |
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| Notes |
CropM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
4694 |
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| Author |
Roggero, P.P. |
| Title |
Oristano, Sardinia, Italy: Winners and losers from climate change in agriculture: a case study in the Mediterranean basin |
Type |
Conference Article |
| Year |
2015 |
Publication |
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| Volume |
6 |
Issue |
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Pages |
Sp6-7 |
| Keywords |
CropM |
| Abstract |
Focus questions • How to support effective adaptive responses to CC and stimulate proactive attitudes of farmers, policymakers & researchers? • How to co-construct the nature of the issues about CC adaptation? The «Oristanese» case study • Very diversified agricultural district in a Mediterranean context o Irrigated and rainfed farming systems o Variety of cropping systems, intensity levels, farm size • Multiple stakeholders o Cooperative agro-food system o Producers’ organizations (rice, horticulture) o Variety of extensive pastoral systems Emerging outcome • The dairy cattle coop is developing a new win-win pathway linking hi-input dairy cattle farming with low input beef cattle grazing systems • The local government is investing in the EIP for supporting the local beef production chain to reduce meat imports and enhance pasture biodiversity and ecosystem services (eg wildfire prevention) Emerging challenges Adaptive responses as co-evolution pathways • design social learning spaces for researchers, stakeholders and policy makers • combining integrated assessment modeling and social learning facilitation |
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Brussels |
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Climate-change impacts on farming systems in the next decades — why worry when you have CAP? A FACCE MACSUR workshop for policymakers, 2015-05-06 to 2015-05-06, Brussels |
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no |
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MA @ admin @ |
Serial |
2750 |
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| Author |
Gutierrez, L.; Piras, F.; Roggero, P.P. |
| Title |
A global vector autoregression model for the analysis of wheat export prices |
Type |
Journal Article |
| Year |
2015 |
Publication |
American Journal of Agricultural Economics |
Abbreviated Journal |
American Journal of Agricultural Economics |
| Volume |
97 |
Issue |
5 |
Pages |
1494-1511 |
| Keywords |
Global dynamic models; price analysis; wheat market; lagged dependent-variables; commodity-markets; error-correction; food-prices; unit-root; regressors; tests; cointegration; dynamics; time |
| Abstract |
Food commodity price fluctuations have an important impact on poverty and food insecurity across the world. Conventional models have not provided a complete picture of recent price spikes in agricultural commodity markets, and there is an urgent need for appropriate policy responses. Perhaps new approaches are needed to better understand international spill-overs, the feedback between the real and the financial sectors, as well as the link between food and energy prices. In this article, we present the results from a new worldwide dynamic model that provides the short and long-run impulse responses of the international wheat price to various real and financial shocks. |
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0002-9092 1467-8276 |
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TradeM, ft_macsur |
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no |
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MA @ admin @ |
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4658 |
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| Author |
Hoveid, Ø. |
| Title |
Prototype of stochastic equilibrium model of the food system |
Type |
Report |
| Year |
2015 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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6 |
Issue |
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Pages |
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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no |
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MA @ admin @ |
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2115 |
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| Author |
Korhonen, P. |
| Title |
Intercomparison of timothy models in northern countries |
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2015 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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5 |
Issue |
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Pages |
Sp5-31 |
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| Abstract |
Forage-based livestock and dairy production are the economic backbone of agriculture in many northern countries. In northern Europe and eastern Canada, forage grasses are commonly grown intensively for silage and hay as a part of crop rotation. In those regions, timothy (Phleum pratense L.) is one of the most widely grown grass species. Models that simulate the development of yield and nutritive quality have been developed for timothy, but the performance of different models has not been compared so far.In this study, we compare the performance of the models BASGRA, CATIMO, and STICS for the predictions of timothy yield at 7 sites located in Finland, Norway, Sweden, and Canada. In addition to yield, model predictions of additional variables, such as leaf area index, specific leaf area, and nutritive quality are gathered on a daily basis. Observed data will be used for two distinct calibrations: 1) Cultivar-specific and 2) ”global”, using all cultivars. The performance of the models will be tested by simulating all sites and years with both the 5 cultivar-specific parameter sets and the global parameter set.The first results of the comparison will be presented with a particular emphasis on dry matter yield predictions.The results will provide information about the uncertainties related to yield predictions of different timothy models and calibrations, the strengths and weaknesses of different modelling approaches, and the sensitivity of models to cultivar-specific parameters. 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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Approved |
no |
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MA @ admin @ |
Serial |
2146 |
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