| Records |
| Author |
Ruane, A.C.; Hudson, N.I.; Asseng, S.; Camarrano, D.; Ewert, F.; Martre, P.; Boote, K.J.; Thorburn, P.J.; Aggarwal, P.K.; Angulo, C.; Basso, B.; Bertuzzi, P.; Biernath, C.; Brisson, N.; Challinor, &rew J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.F.; Heng, L.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, R.C.; Kersebaum, K.C.; Kumar, S.N.; Müller, C.; Nendel, C.; O’Leary, G.; Olesen, J.E.; Osborne, T.M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Rötter, R.P.; Semenov, M.A.; Shcherbak, I.; Steduto, P.; Stöckle, C.O.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J.W.; Wolf, J. |
| Title |
Multi-wheat-model ensemble responses to interannual climate variability |
Type |
Journal Article |
| Year |
2016 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
Volume  |
81 |
Issue |
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Pages |
86-101 |
| Keywords |
Crop modeling; Uncertainty; Multi-model ensemble; Wheat; AgMIP; Climate; impacts; Temperature; Precipitation; lnterannual variability; simulation-model; crop model; nitrogen dynamics; winter-wheat; large-area; systems simulation; farming systems; yield response; growth; water |
| Abstract |
We compare 27 wheat models’ yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981-2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models’ climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R-2 <= 0.24) was found between the models’ sensitivities to interannual temperature variability and their response to long-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts. Published by Elsevier Ltd. |
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English |
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1364-8152 |
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Article |
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CropM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
4769 |
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| Author |
Kollas, C.; Kersebaum, K.C.; Nendel, C.; Manevski, K.; Müller, C.; Palosuo, T.; Armas-Herrera, C.M.; Beaudoin, N.; Bindi, M.; Charfeddine, M.; Conradt, T.; Constantin, J.; Eitzinger, J.; Ewert, F.; Ferrise, R.; Gaiser, T.; Cortazar-Atauri, I.G. de; Giglio, L.; Hlavinka, P.; Hoffmann, H.; Hoffmann, M.P.; Launay, M.; Manderscheid, R.; Mary, B.; Mirschel, W.; Moriondo, M.; Olesen, J.E.; Öztürk, I.; Pacholski, A.; Ripoche-Wachter, D.; Roggero, P.P.; Roncossek, S.; Rötter, R.P.; Ruget, F.; Sharif, B.; Trnka, M.; Ventrella, D.; Waha, K.; Wegehenkel, M.; Weigel, H.-J.; Wu, L. |
| Title |
Crop rotation modelling—A European model intercomparison |
Type |
Journal Article |
| Year |
2015 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
| Volume |
70 |
Issue |
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Pages |
98-111 |
| Keywords |
Model ensemble; Crop simulation models; Catch crop; Intermediate crop; Treatment; Multi-year; long-term experiment; climate-change; wheat production; n-fertilization; systems simulation; nitrogen dynamics; tillage intensity; winter-wheat; soil carbon; growth |
| Abstract |
• First model inter-comparison on crop rotations. • Continuous simulation of multi-year crop rotations yields outperformed single-year simulation. • Low accuracy of yield predictions in less commonly modelled crops such as potato, radish, grass vegetation. • Multi-model mean prediction was found to minimise the likely error arising from single-model predictions. • The representation of intermediate crops and carry-over effects in the models require further research efforts.
Diversification of crop rotations is considered an option to increase the resilience of European crop production under climate change. So far, however, many crop simulation studies have focused on predicting single crops in separate one-year simulations. Here, we compared the capability of fifteen crop growth simulation models to predict yields in crop rotations at five sites across Europe under minimal calibration. Crop rotations encompassed 301 seasons of ten crop types common to European agriculture and a diverse set of treatments (irrigation, fertilisation, CO2 concentration, soil types, tillage, residues, intermediate or catch crops). We found that the continuous simulation of multi-year crop rotations yielded results of slightly higher quality compared to the simulation of single years and single crops. Intermediate crops (oilseed radish and grass vegetation) were simulated less accurately than main crops (cereals). The majority of models performed better for the treatments of increased CO2 and nitrogen fertilisation than for irrigation and soil-related treatments. The yield simulation of the multi-model ensemble reduced the error compared to single-model simulations. The low degree of superiority of continuous simulations over single year simulation was caused by (a) insufficiently parameterised crops, which affect the performance of the following crop, and (b) the lack of growth-limiting water and/or nitrogen in the crop rotations under investigation. In order to achieve a sound representation of crop rotations, further research is required to synthesise existing knowledge of the physiology of intermediate crops and of carry-over effects from the preceding to the following crop, and to implement/improve the modelling of processes that condition these effects. |
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Edition |
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1161-0301 |
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CropM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
4660 |
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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 |
Type |
Journal Article |
| Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
| Volume |
65 |
Issue |
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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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0936-577x 1616-1572 |
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Article |
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CropM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
4662 |
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| Author |
Liu, B.; Martre, P.; Ewert, F.; Porter, J.R.; Challinor, A.J.; Mueller, C.; Ruane, A.C.; Waha, K.; Thorburn, P.J.; Aggarwal, P.K.; Ahmed, M.; Balkovic, J.; Basso, B.; Biernath, C.; Bindi, M.; Cammarano, D.; De Sanctis, G.; Dumont, B.; Espadafor, M.; Rezaei, E.E.; Ferrise, R.; Garcia-Vila, M.; Gayler, S.; Gao, Y.; Horan, H.; Hoogenboom, G.; Izaurralde, R.C.; Jones, C.D.; Kassie, B.T.; Kersebaum, K.C.; Klein, C.; Koehler, A.-K.; Maiorano, A.; Minoli, S.; San Martin, M.M.; Kumar, S.N.; Nendel, C.; O’Leary, G.J.; Palosuo, T.; Priesack, E.; Ripoche, D.; Roetter, R.P.; Semenov, M.A.; Stockle, C.; Streck, T.; Supit, I.; Tao, F.; Van der Velde, M.; Wallach, D.; Wang, E.; Webber, H.; Wolf, J.; Xiao, L.; Zhang, Z.; Zhao, Z.; Zhu, Y.; Asseng, S. |
| Title |
Global wheat production with 1.5 and 2.0 degrees C above pre-industrial warming |
Type |
Journal Article |
| Year |
2019 |
Publication |
Global Change Biology |
Abbreviated Journal |
Glob. Chang. Biol. |
| Volume |
25 |
Issue |
4 |
Pages |
1428-1444 |
| Keywords |
1.5 degrees C warming; climate change; extreme low yields; food security; model ensemble; wheat production; Climate-Change; Crop Yield; Impacts; Co2; Adaptation; Responses; Models; Agriculture; Simulation; Growth |
| Abstract |
Efforts to limit global warming to below 2 degrees C in relation to the pre-industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2 degrees C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5 and 2.0 degrees C warming above the pre-industrial period) on global wheat production and local yield variability. A multi-crop and multi-climate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by -2.3% to 7.0% under the 1.5 degrees C scenario and -2.4% to 10.5% under the 2.0 degrees C scenario, compared to a baseline of 1980-2010, when considering changes in local temperature, rainfall, and global atmospheric CO2 concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield inter-annual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producer-India, which supplies more than 14% of global wheat. The projected global impact of warming <2 degrees C on wheat production is therefore not evenly distributed and will affect regional food security across the globe as well as food prices and trade. |
| Address |
2019-04-27 |
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English |
Summary Language |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
1354-1013 |
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Article |
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CropM, ft_macsur |
Approved |
no |
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MA @ admin @ |
Serial |
5219 |
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Waha, K.; Müller, C.; Bondeau, A.; Dietrich, J.P.; Kurukulasuriya, P.; Heinke, J.; Lotze-Campen, H. |
| Title |
Adaptation to climate change through the choice of cropping system and sowing date in sub-Saharan Africa |
Type |
Journal Article |
| Year |
2013 |
Publication |
Global Environmental Change |
Abbreviated Journal |
Glob. Environ. Change |
| Volume |
23 |
Issue |
1 |
Pages |
130-143 |
| Keywords |
multiple cropping; sequential cropping systems; crop modelling; agricultural management; adaptation options; global vegetation model; future food-production; rainy-season; west-africa; agriculture; yield; maize; soil; variability; heat |
| Abstract |
Multiple cropping systems provide more harvest security for farmers, allow for crop intensification and furthermore influence ground cover, soil erosion, albedo, soil chemical properties, pest infestation and the carbon sequestration potential. We identify the traditional sequential cropping systems in ten sub-Saharan African countries from a survey dataset of more than 8600 households. We find that at least one sequential cropping system is traditionally used in 35% of all administrative units in the dataset, mainly including maize or groundnuts. We compare six different management scenarios and test their susceptibility as adaptation measure to climate change using the dynamic global vegetation model for managed land LPJmL. Aggregated mean crop yields in sub-Saharan Africa decrease by 6-24% due to climate change depending on the climate scenario and the management strategy. As an exception, some traditional sequential cropping systems in Kenya and South Africa gain by at least 25%. The crop yield decrease is typically weakest in sequential cropping systems and if farmers adapt the sowing date to changing climatic conditions. Crop calorific yields in single cropping systems only reach 40-55% of crop calorific yields obtained in sequential cropping systems at the end of the 21st century. The farmers’ choice of adequate crops, cropping systems and sowing dates can be an important adaptation strategy to climate change and these management options should be considered in climate change impact studies on agriculture. (C) 2012 Elsevier Ltd. All rights reserved. |
| Address |
2016-10-31 |
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English |
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0959-3780 |
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CropM |
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no |
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MA @ admin @ |
Serial |
4823 |
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