| Records |
| Author |
Kersebaum, K.C.; Kollas, C.; Bindi, M.; Palosuo, T.; Wu, L.; Sharif, B.; Öztürk, I.; Trnka, M.; Hlavinka, P.; Nendel, C.; Müller, C.; Waha, K.; Armas-Herrera, C.; Olesen, J.E.; Eitzinger, J.; Roggero, P.P.; Conradt, T.; Martre, P.; Ferrise, R.; Moriondo, M.; Ruiz-Ramos, M.; Ventrella, D.; Rötter, R.P.; Wegehenkel, M.; Eckersten, H.; Lorite Torres, I.J.; Hernandez, C.G.; Launay, M.; De Wit, A.; Hoffmann, H.; Weigel, H.-J.; Manderscheid, R.; Beaudoin, N.; Constantin, J.; Garcia de Cortazar-Atauri, I.; Mary, B.; Ripoche, D.; Ruget, F. |
| Title |
Model inter-comparison on crop rotation effects – an intermediate report |
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Conference Article |
| Year |
2014 |
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Data of diverse crop rotations from five locations across Europe were distributed to modelers to investigate the capability of models to handle complex crop rotations and management interactions. Crop rotations comprise various main crops (winter/spring wheat, winter/spring barley, rye, oat, maize, sugar beet, oil seed rape and potatoes) plus several catch crops. The experimental setup of the datasets included treatments such as modified soils, crops exchanged within the rotations, irrigation/rainfed, nitrogen fertilization, residue management, tillage and atmospheric CO2 concentration. 19 modeling teams registered to model either the whole rotation or single crops. Models which are capable to run the whole rotation should provide transient as well as single year simulations with a reset of initial conditions. In the first step only initial soil conditions (water and soil mineral N) of the first year and key phenological stages were provided to the modelers. For calibration, crop yields and biomass were provided for selected years but not for all seasons. In total the combination of treatments and seasons results in 301 years of simulation. Results were analyzed to evaluate the effect of transient simulation versus single-year simulation regarding crop yield, biomass, water and nitrogen balance components. Model results will be evaluated crop-specifically to identify crops with highest uncertainty and potential for model improvement. Full data will be provided to modelers for model-improvement and results will provide insights into model capabilities to reproduce treatments and crops. Further, the question of error propagation along the transient simulation of crop rotations will be addressed. |
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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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MA @ admin @ |
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5104 |
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Kersebaum, C.; Kollas, C.; Bindi, M.; Nendel, C.; Ferrise, R.; Moriondo, M.; Olesen, J.E.; Sharif, B.; Öztürk, I.; Hoffmann, H.; Launay, M.; Ripoche, D.; Ruget, F.; Bertuzzi, P.; Cortazar, I.G.D.; Beaudoin, N.; Armas-Herrera, C.; Mary, B.; Müller, C.; Waha, K.; Ventrella, D.; Palosuo, T.; Rötter, R.; Trnka, M.; Hlavinka, P.; Wu, L.; Wegehenkel, M.; Mirschel, W.; Conradt, T.; Wechsung, F.; Weigel, H.-J.; Manderscheid, R.; Eitzinger, J. |
| Title |
Modelling complex crop rotations and management across sites in Europe with an ensemble of models |
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Conference Article |
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2014 |
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CropM |
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ASA-CSSA-SSSA Int. Annual Meeting, Long Beach, CA, 2-5 November 2014, 2014-11-02 to 2014-11-05 |
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MA @ admin @ |
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2526 |
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Ma, S.; Acutis, M.; Barcza, Z.; Ben, T., H.; Doro, L.; Hidy, D.; Köchy, M.; Minet, J.; Lellei-Kovács, E.; Perego, A.; Rolinski, S.; Ruget, F.; Seddaiu, G.; Wu, L.; Bellocchi, G. |
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The grassland model intercomparison of the MACSUR (Modelling European Agriculture with Climate Change for Food Security) European knowledge hub |
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Conference Article |
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2014 |
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LiveM |
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7th International Congress on Environmental Modelling and Software, 2014-06-15 to 2014-06-19 |
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MA @ admin @ |
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2618 |
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Sándor, R.; Ehrhardt, F.; Basso, B.; Bellocchi, G.; Bhatia, A.; Brilli, L.; Migliorati, M.D.A.; Doltra, J.; Dorich, C.; Doro, L.; Fitton, N.; Giacomini, S.J.; Grace, P.; Grant, B.; Harrison, M.T.; Jones, S.; Kirschbaum, M.U.F.; Klumpp, K.; Laville, P.; Léonard, J.; Liebig, M.; Lieffering, M.; Martin, R.; McAuliffe, R.; Meier, E.; Merbold, L.; Moore, A.; Myrgiotis, V.; Newton, P.; Pattey, E.; Recous, S.; Rolinski, S.; Sharp, J.; Massad, R.S.; Smith, P.; Smith, W.; Snow, V.; Wu, L.; Zhang, Q.; Soussana, J.F. |
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C and N models Intercomparison – benchmark and ensemble model estimates for grassland production |
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Journal Article |
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2016 |
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Advances in Animal Biosciences |
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Advances in Animal Biosciences |
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7 |
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03 |
Pages |
245-247 |
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2040-4700 |
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LiveM, ft_macsur |
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no |
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MA @ admin @ |
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4868 |
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Pirttioja, N.; Carter, T.R.; Fronzek, S.; Bindi, M.; Hoffmann, H.; Palosuo, T.; Ruiz-Ramos, M.; Tao, F.; Trnka, M.; Acutis, M.; Asseng, S.; Baranowski, P.; Basso, B.; Bodin, P.; Buis, S.; Cammarano, D.; Deligios, P.; Destain, M.F.; Dumont, B.; Ewert, F.; Ferrise, R.; François, L.; Gaiser, T.; Hlavinka, P.; Jacquemin, I.; Kersebaum, K.C.; Kollas, C.; Krzyszczak, J.; Lorite, I.J.; Minet, J.; Minguez, M.I.; Montesino-San Martin, M.; Moriondo, M.; Müller, C.; Nendel, C.; Öztürk, I.; Perego, A.; Rodríguez, A.; Ruane, A.C.; Ruget, F.; Sanna, M.; Semenov, M.A.; Slawinski, C.; Stratonovitch, P.; Supit, I.; Waha, K.; Wang, E.; Wu, L.; Zhao, Z.; Rötter, R.P. |
| Title |
Temperature and precipitation effects on wheat yield across a European transect: a crop model ensemble analysis using impact response surfaces |
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Journal Article |
| Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
| Volume |
65 |
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Pages |
87-105 |
| Keywords |
climate; crop model; impact response surface; IRS; sensitivity analysis; wheat; yield; climate-change impacts; uncertainty; 21st-century; projections; simulation; growth; region |
| Abstract |
This study explored the utility of the impact response surface (IRS) approach for investigating model ensemble crop yield responses under a large range of changes in climate. IRSs of spring and winter wheat Triticum aestivum yields were constructed from a 26-member ensemble of process-based crop simulation models for sites in Finland, Germany and Spain across a latitudinal transect. The sensitivity of modelled yield to systematic increments of changes in temperature (-2 to +9°C) and precipitation (-50 to +50%) was tested by modifying values of baseline (1981 to 2010) daily weather, with CO2 concentration fixed at 360 ppm. The IRS approach offers an effective method of portraying model behaviour under changing climate as well as advantages for analysing, comparing and presenting results from multi-model ensemble simulations. Though individual model behaviour occasionally departed markedly from the average, ensemble median responses across sites and crop varieties indicated that yields decline with higher temperatures and decreased precipitation and increase with higher precipitation. Across the uncertainty ranges defined for the IRSs, yields were more sensitive to temperature than precipitation changes at the Finnish site while sensitivities were mixed at the German and Spanish sites. Precipitation effects diminished under higher temperature changes. While the bivariate and multi-model characteristics of the analysis impose some limits to interpretation, the IRS approach nonetheless provides additional insights into sensitivities to inter-model and inter-annual variability. Taken together, these sensitivities may help to pinpoint processes such as heat stress, vernalisation or drought effects requiring refinement in future model development. |
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English |
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0936-577x 1616-1572 |
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CropM, ft_macsur |
Approved |
no |
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MA @ admin @ |
Serial |
4662 |
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