Multimodel ensembles of wheat growth: many models are better than one
Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but suc...
| Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Wiley
2015
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/57489 |
| _version_ | 1855518288287629312 |
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| author | Martre, Pierre Wallach, Daniel Asseng, Senthold Ewert, Frank Jones, James W. Rötter, Reimund P. Boote, Kenneth J. Ruane, Alex C. Thorburn, Peter J. Cammarano, Davide Hatfield, Jerry L. Rosenzweig, Cynthia Aggarwal, Pramod K. Angulo, Carlos Basso, Bruno Bertuzzi, Patrick Biernath, Christian Brisson, Nadine Challinor, Andrew J. Doltra, Jordi Gayler, Sebastian Goldberg, Richie Grant, Robert F. Heng, Lee Hooker, Josh Hunt, Leslie A. Ingwersen, Joachim Izaurralde, Roberto César Kersebaum, Kurt-Christian Müller, Christoph Kumar, Soora Naresh Nendel, Claas O’Leary, Garry J. Olesen, Jørgen E. Osborne, Tom M. Palosuo, Taru Priesack, Eckart Ripoche, Dominique Semenov, Mikhail A. Shcherbak, Iurii Steduto, Pasquale Stöckle, Claudio O. Stratonovitch, Pierre Streck, Thilo Supit, Iwan Tao, Fulu Travasso, Maria Waha, Katharina White, Jeffrey W. Wolf, Joost |
| author_browse | Aggarwal, Pramod K. Angulo, Carlos Asseng, Senthold Basso, Bruno Bertuzzi, Patrick Biernath, Christian Boote, Kenneth J. Brisson, Nadine Cammarano, Davide Challinor, Andrew J. Doltra, Jordi Ewert, Frank Gayler, Sebastian Goldberg, Richie Grant, Robert F. Hatfield, Jerry L. Heng, Lee Hooker, Josh Hunt, Leslie A. Ingwersen, Joachim Izaurralde, Roberto César Jones, James W. Kersebaum, Kurt-Christian Kumar, Soora Naresh Martre, Pierre Müller, Christoph Nendel, Claas Olesen, Jørgen E. Osborne, Tom M. O’Leary, Garry J. Palosuo, Taru Priesack, Eckart Ripoche, Dominique Rosenzweig, Cynthia Ruane, Alex C. Rötter, Reimund P. Semenov, Mikhail A. Shcherbak, Iurii Steduto, Pasquale Stratonovitch, Pierre Streck, Thilo Stöckle, Claudio O. Supit, Iwan Tao, Fulu Thorburn, Peter J. Travasso, Maria Waha, Katharina Wallach, Daniel White, Jeffrey W. Wolf, Joost |
| author_facet | Martre, Pierre Wallach, Daniel Asseng, Senthold Ewert, Frank Jones, James W. Rötter, Reimund P. Boote, Kenneth J. Ruane, Alex C. Thorburn, Peter J. Cammarano, Davide Hatfield, Jerry L. Rosenzweig, Cynthia Aggarwal, Pramod K. Angulo, Carlos Basso, Bruno Bertuzzi, Patrick Biernath, Christian Brisson, Nadine Challinor, Andrew J. Doltra, Jordi Gayler, Sebastian Goldberg, Richie Grant, Robert F. Heng, Lee Hooker, Josh Hunt, Leslie A. Ingwersen, Joachim Izaurralde, Roberto César Kersebaum, Kurt-Christian Müller, Christoph Kumar, Soora Naresh Nendel, Claas O’Leary, Garry J. Olesen, Jørgen E. Osborne, Tom M. Palosuo, Taru Priesack, Eckart Ripoche, Dominique Semenov, Mikhail A. Shcherbak, Iurii Steduto, Pasquale Stöckle, Claudio O. Stratonovitch, Pierre Streck, Thilo Supit, Iwan Tao, Fulu Travasso, Maria Waha, Katharina White, Jeffrey W. Wolf, Joost |
| author_sort | Martre, Pierre |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24–38% for the different end‐of‐season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in‐season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e‐mean) or median (e‐median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e‐median ranked first in simulating measured GY and third in GPC. The error of e‐mean and e‐median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models. |
| format | Journal Article |
| id | CGSpace57489 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | Wiley |
| publisherStr | Wiley |
| record_format | dspace |
| spelling | CGSpace574892025-03-13T09:44:02Z Multimodel ensembles of wheat growth: many models are better than one Martre, Pierre Wallach, Daniel Asseng, Senthold Ewert, Frank Jones, James W. Rötter, Reimund P. Boote, Kenneth J. Ruane, Alex C. Thorburn, Peter J. Cammarano, Davide Hatfield, Jerry L. Rosenzweig, Cynthia Aggarwal, Pramod K. Angulo, Carlos Basso, Bruno Bertuzzi, Patrick Biernath, Christian Brisson, Nadine Challinor, Andrew J. Doltra, Jordi Gayler, Sebastian Goldberg, Richie Grant, Robert F. Heng, Lee Hooker, Josh Hunt, Leslie A. Ingwersen, Joachim Izaurralde, Roberto César Kersebaum, Kurt-Christian Müller, Christoph Kumar, Soora Naresh Nendel, Claas O’Leary, Garry J. Olesen, Jørgen E. Osborne, Tom M. Palosuo, Taru Priesack, Eckart Ripoche, Dominique Semenov, Mikhail A. Shcherbak, Iurii Steduto, Pasquale Stöckle, Claudio O. Stratonovitch, Pierre Streck, Thilo Supit, Iwan Tao, Fulu Travasso, Maria Waha, Katharina White, Jeffrey W. Wolf, Joost mathematical models simulation models wheats yields triticum aestivum modelos matemáticos modelos de simulación trigo rendimiento ecology Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24–38% for the different end‐of‐season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in‐season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e‐mean) or median (e‐median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e‐median ranked first in simulating measured GY and third in GPC. The error of e‐mean and e‐median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models. 2015-02 2015-03-12T19:29:04Z 2015-03-12T19:29:04Z Journal Article https://hdl.handle.net/10568/57489 en Limited Access Wiley Martre, Pierre; Wallach, Daniel; Asseng, Senthold; Ewert, Frank; Jones, James W.; Rötter, Reimund P.; Boote, Kenneth J.; Ruane, Alex C.; Thorburn, Peter J.; Cammarano, Davide; Hatfield, Jerry L.; Rosenzweig, Cynthia; Aggarwal, Pramod K.; Angulo, Carlos; Basso, Bruno; Bertuzzi, Patrick; Biernath, Christian; Brisson, Nadine; Challinor, Andrew J.; Doltra, Jordi; Gayler, Sebastian; Goldberg, Richie; Grant, Robert F.; Heng, Lee; Hooker, Josh; Hunt, Leslie A.; Ingwersen, Joachim; Izaurralde, Roberto C.; Kersebaum, Kurt Christian; Müller, Christoph; Kumar, Soora Naresh; Nendel, Claas; O'leary, Garry; Olesen, Jørgen E.; Osborne, Tom M.; Palosuo, Taru; Priesack, Eckart; Ripoche, Dominique; Semenov, Mikhail A.; Shcherbak, Iurii; Steduto, Pasquale; Stöckle, Claudio O.; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Travasso, Maria; Waha, Katharina; White, Jeffrey W.; Wolf, Joost. 2015. Multimodel ensembles of wheat growth : many models are better than one. Global Change Biology 21: 911-25. |
| spellingShingle | mathematical models simulation models wheats yields triticum aestivum modelos matemáticos modelos de simulación trigo rendimiento ecology Martre, Pierre Wallach, Daniel Asseng, Senthold Ewert, Frank Jones, James W. Rötter, Reimund P. Boote, Kenneth J. Ruane, Alex C. Thorburn, Peter J. Cammarano, Davide Hatfield, Jerry L. Rosenzweig, Cynthia Aggarwal, Pramod K. Angulo, Carlos Basso, Bruno Bertuzzi, Patrick Biernath, Christian Brisson, Nadine Challinor, Andrew J. Doltra, Jordi Gayler, Sebastian Goldberg, Richie Grant, Robert F. Heng, Lee Hooker, Josh Hunt, Leslie A. Ingwersen, Joachim Izaurralde, Roberto César Kersebaum, Kurt-Christian Müller, Christoph Kumar, Soora Naresh Nendel, Claas O’Leary, Garry J. Olesen, Jørgen E. Osborne, Tom M. Palosuo, Taru Priesack, Eckart Ripoche, Dominique Semenov, Mikhail A. Shcherbak, Iurii Steduto, Pasquale Stöckle, Claudio O. Stratonovitch, Pierre Streck, Thilo Supit, Iwan Tao, Fulu Travasso, Maria Waha, Katharina White, Jeffrey W. Wolf, Joost Multimodel ensembles of wheat growth: many models are better than one |
| title | Multimodel ensembles of wheat growth: many models are better than one |
| title_full | Multimodel ensembles of wheat growth: many models are better than one |
| title_fullStr | Multimodel ensembles of wheat growth: many models are better than one |
| title_full_unstemmed | Multimodel ensembles of wheat growth: many models are better than one |
| title_short | Multimodel ensembles of wheat growth: many models are better than one |
| title_sort | multimodel ensembles of wheat growth many models are better than one |
| topic | mathematical models simulation models wheats yields triticum aestivum modelos matemáticos modelos de simulación trigo rendimiento ecology |
| url | https://hdl.handle.net/10568/57489 |
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