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Bojar, W.; Knopik, L.; Żarski, J.; Sławiński, C.; Baranowski, P.; Żarski, W. |
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Title |
Impact of extreme climate changes on the forecasted agriculture production |
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Journal Article |
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Year |
2014 |
Publication |
Acta Agrophysica |
Abbreviated Journal |
Acta Agrophysica |
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21 |
Issue |
4 |
Pages |
415-431 |
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Keywords |
agricultural economics; agriculture; climate change; crop production; integrating assessments |
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The paper presents general characteristics of resources and outputs of agriculture in the Kujawsko-Pomorskie and Lubelskie Regions, based on statistical databases and literature review. Some specific features of the regions, with special consideration for the predicted extreme climate changes, are also included. Next, 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, Bydgoszcz, and the Institute of Agrophysics in Lublin. Creating an appropriate method of forecasting long series of ten days without precipitation was necessary to find the desired dependencies. Third, some efforts were taken to make integrated assessments of forecast agricultural outputs influenced by climate extreme phenomena on the basis of the yield-precipitation relations obtained and on the data coming from wide area model regional outputs such as prices of farmland and produce. |
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CropM, TradeM, ft_macsur |
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MA @ admin @ |
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4619 |
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Rolinski, S.; Weindl, I.; Heinke, J.; Bodirsky, B.L.; Biewald, A.; Lotze-Campen, H. |
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Pasture harvest, carbon sequestration and feeding potentials under different grazing intensities |
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2015 |
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Advances in Animal Biosciences |
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Advances in Animal Biosciences |
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6 |
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01 |
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43-45 |
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global dynamic vegetation model; LPJmL; grasslands; livestock production |
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CropM, LiveM, ft_macsur |
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MA @ admin @ |
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4541 |
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Gomara, I.; Bellocchi, G.; Martin, R.; Rodriguez-Fonseca, B.; Ruiz-Ramos, M. |
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Title |
Influence of climate variability on the potential forage production of a mown permanent grassland in the French Massif Central |
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Journal Article |
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2020 |
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Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
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280 |
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107768 |
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climate variability; grasslands; potential yield; climate services; forage production forecasts; french massif central; pasture simulation-model; dry-matter production; atmospheric; circulation; crop yield; SST anomalies; maize yield; managed grasslands; storm track; ENSO; impacts |
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Climate Services (CS) provide support to decision makers across socio-economic sectors. In the agricultural sector, one of the most important CS applications is to provide timely and accurate yield forecasts based on climate prediction. In this study, the Pasture Simulation model (PaSim) was used to simulate, for the period 1959–2015, the forage production of a mown grassland system (Laqueuille, Massif Central of France) under different management conditions, with meteorological inputs extracted from the SAFRAN atmospheric database. The aim was to generate purely climate-dependent timeseries of optimal forage production, a variable that was maximized by brighter and warmer weather conditions at the grassland. A long-term increase was observed in simulated forage yield, with the 1995–2015 average being 29% higher than the 1959–1979 average. Such increase seems consistent with observed rising trends in temperature and CO2, and multi-decadal changes in incident solar radiation. At interannual timescales, sea surface temperature anomalies of the Mediterranean (MED), Tropical North Atlantic (TNA), equatorial Pacific (El Niño Southern Oscillation) and the North Atlantic Oscillation (NAO) index were found robustly correlated with annual forage yield values. Relying only on climatic predictors, we developed a stepwise statistical multi-regression model with leave-one-out cross-validation. Under specific management conditions (e.g., three annual cuts) and from one to five months in advance, the generated model successfully provided a p-value<0.01 in correlation (t-test), a root mean square error percentage (%RMSE) of 14.6% and a 71.43% hit rate predicting above/below average years in terms of forage yield collection. This is the first modeling study on the possible role of large-scale oceanic–atmospheric teleconnections in driving forage production in Europe. As such, it provides a useful springboard to implement a grassland seasonal forecasting system in this continent. |
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2020-06-08 |
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LiveM, ft_macsur |
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MA @ admin @ |
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5233 |
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Pulina, A.; Lai, R.; Salis, L.; Seddaiu, G.; Roggero, P.P.; Bellocchi, G. |
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Title |
Modelling pasture production and soil temperature, water and carbon fluxes in Mediterranean grassland systems with the Pasture Simulation Model |
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2018 |
Publication |
Grass and Forage Science |
Abbreviated Journal |
Grass Forage Sci. |
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73 |
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2 |
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272-283 |
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grassland production; Mediterranean pastures; model calibration; PaSim; sheep grazing systems; soil respiration |
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Grasslands play important roles in agricultural production and provide a range of ecosystem services. Modelling can be a valuable adjunct to experimental research in order to improve the knowledge and assess the impact of management practices in grassland systems. In this study, the PaSim model was assessed for its ability to simulate plant biomass production, soil temperature, water content, and total and heterotrophic soil respiration in Mediterranean grasslands. The study site was the extensively managed sheep grazing system at the Berchidda‐Monti Observatory (Sardinia, Italy), from which two data sets were derived for model calibration and validation respectively. A new model parameterization was derived for Mediterranean conditions from a set of eco‐physiological parameters. With the exception of heterotrophic respiration (Rh), for which modelling efficiency (EF) values were negative, the model outputs were in agreement with observations (e.g., EF ranging from ~0.2 for total soil respiration to ~0.7 for soil temperature). These results support the effectiveness of PaSim to simulate C cycle components in Mediterranean grasslands. The study also highlights the need of further model development to provide better representation of the seasonal dynamics of Mediterranean annual species‐rich grasslands and associated peculiar Rh features, for which the modelling is only implicitly being undertaken by the current PaSim release. |
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LiveM, ft_macsur |
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MA @ admin @ |
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4973 |
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Schönhart, M.; Mitter, H.; Schmid, E.; Heinrich, G.; Gobiet, A. |
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Integrated analysis of climate change impacts and adaptation measures in Austrian agriculture |
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Year |
2014 |
Publication |
German Journal of Agricultural Economics |
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German Journal of Agricultural Economics |
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63 |
Issue |
3 |
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156-176 |
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land use; modelling; climate change impact; adaptation; integrated analysis; epic; pasma; crop production; land-use; management-practices; model projections; central-europe; soil-erosion; water; variability; strategies; region |
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An integrated modelling framework (IMF) has been developed and applied to analyse climate change impacts and the effectiveness of adaptation measures in Austrian agriculture. The IMF couples the crop rotation model CropRota, the bio-physical process model EPIC and the bottom-up economic land use model PASMA at regional level (NUTS-3) considering agri-environmental indicators. Four contrasting regional climate model (RCM) simulations represent climate change until 2050. The RCM simulations are applied to a baseline and three adaptation and policy scenarios. Climate change increases crop productivity on national average in the IMF. Changes in average gross margins at national level range from 0% to + 5% between the baseline and the three adaptation and policy scenarios. The impacts at NUTS-3 level range from -5% to + 7% between the baseline and the three adaptation and policy scenarios. Adaptation measures such as planting of winter cover crops, reduced tillage and irrigation are effective in reducing yield losses, increasing revenues, or in improving environmental states under climate change. Future research should account for extreme weather events in order to analyse whether average productivity gains at the aggregated level suffice to cover costs from expected higher climate variability. |
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0002-1121 |
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TradeM, ft_macsur |
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MA @ admin @ |
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4652 |
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