Multimodel ensembles of wheat growth: many models are better than one
Pierre Martre
(1)
,
Daniel Wallach
(2)
,
Senthold Asseng
(3)
,
Frank Ewert
(4)
,
James W. Jones
(3)
,
Reimund P. Rotter
(5)
,
Kenneth J. Boote
(3)
,
Alex C. Ruane
(6)
,
Peter J. Thorburn
(7)
,
Davide Cammarano
(3)
,
Jerry L. Hatfield
(8)
,
Cynthia Rosenzweig
(6)
,
Pramod K. Aggarwal
(9)
,
Carlos Angulo
(4)
,
Bruno Basso
(10, 11)
,
Patrick Bertuzzi
(12)
,
Christian Biernath
(13)
,
Nadine Brisson
(14)
,
Andrew J. Challinor
(15, 16)
,
Jordi Doltra
(17)
,
Sebastian Gayler
(18)
,
Richie Goldberg
(6)
,
Robert F. Grant
(19)
,
Lee Heng
(20)
,
Josh Hooker
(21)
,
Leslie A. Hunt
(22)
,
Joachim Ingwersen
(23)
,
Roberto C. Izaurralde
(24)
,
Kurt Christian Kersebaum
(25)
,
Christoph Mueller
(26)
,
Soora Naresh Kumar
(27)
,
Claas Nendel
(25)
,
Garry O'Leary
(28)
,
Jorgen E. Olesen
(29)
,
Tom M. Osborne
(30)
,
Taru Palosuo
(5)
,
Eckart Priesack
(31)
,
Dominique Ripoche
(12)
,
Mikhail A. Semenov
(32)
,
Iurii Shcherbak
(11, 10)
,
Pasquale Steduto
(33)
,
Claudio O. Stoeckle
(34)
,
Pierre Stratonovitch
(32)
,
Thilo Streck
(35)
,
Iwan Supit
(36)
,
Fulu Tao
(37)
,
Maria Travasso
(38)
,
Katharina Waha
(26)
,
Jeffrey W. White
(39)
,
Joost Wolf
(36)
1
GDEC -
Génétique Diversité et Ecophysiologie des Céréales
2 ARCHE - Agrosystèmes Cultivés et Herbagers
3 UF|ABE - Department of Agricultural and Biological Engineering [Gainesville]
4 Institute of Crop Science and Resource Conservation [Bonn]
5 Plant Production Research
6 GISS - NASA Goddard Institute for Space Studies
7 Ecosystem Sciences
8 National Laboratory for Agriculture and Environment
9 Consultative Group on International Agricultural Research, Research Program on ClimateChange, Agriculture and Food Security
10 Department of Geological Sciences
11 KBS - W. K. Kellogg Biological Station
12 AGROCLIM - Agroclim
13 Institute of Soil Ecology, German Research Center for Environmental Health
14 Agronomie
15 CGIAR-ESSP Program on Climate Change,Agriculture and Food Security
16 SEE - School of Earth and Environment [Leeds]
17 Cantabrian Agricultural Research and Training Centre
18 Water & Earth System Science Competence Cluster
19 Department of Renewable Resources
20 IAEA - International Atomic Energy Agency [Vienna]
21 School of Agriculture, Policy and Development
22 Department of Plant Agriculture
23 Institute of Soil Science and Land Evaluation
24 Department of Geographical Sciences
25 Institute of Landscape Systems Analysis
26 PIK - Potsdam Institute for Climate Impact Research
27 CESCRA - Centre for Environment Science and Climate Resilient Agriculture
28 Department of Primary Industries, Landscape & Water Sciences
29 Department of Agroecology
30 National Centre for Atmospheric Science, Department of Meteorology
31 Institute of Soil Ecology German Research Center for Environmental Health
32 Computational and Systems Biology Department
33 FAO - Food and Agriculture Organization of the United Nations [France]
34 WSU - Washington State University
35 Institute of Soil Science and Land Evaluation
36 WUR - Wageningen University and Research [Wageningen]
37 Institute Geographical Sciences and Natural Resources Research
38 CIRN, Institute forClimate and Water
39 Arid-Land Agricultural Research Center
2 ARCHE - Agrosystèmes Cultivés et Herbagers
3 UF|ABE - Department of Agricultural and Biological Engineering [Gainesville]
4 Institute of Crop Science and Resource Conservation [Bonn]
5 Plant Production Research
6 GISS - NASA Goddard Institute for Space Studies
7 Ecosystem Sciences
8 National Laboratory for Agriculture and Environment
9 Consultative Group on International Agricultural Research, Research Program on ClimateChange, Agriculture and Food Security
10 Department of Geological Sciences
11 KBS - W. K. Kellogg Biological Station
12 AGROCLIM - Agroclim
13 Institute of Soil Ecology, German Research Center for Environmental Health
14 Agronomie
15 CGIAR-ESSP Program on Climate Change,Agriculture and Food Security
16 SEE - School of Earth and Environment [Leeds]
17 Cantabrian Agricultural Research and Training Centre
18 Water & Earth System Science Competence Cluster
19 Department of Renewable Resources
20 IAEA - International Atomic Energy Agency [Vienna]
21 School of Agriculture, Policy and Development
22 Department of Plant Agriculture
23 Institute of Soil Science and Land Evaluation
24 Department of Geographical Sciences
25 Institute of Landscape Systems Analysis
26 PIK - Potsdam Institute for Climate Impact Research
27 CESCRA - Centre for Environment Science and Climate Resilient Agriculture
28 Department of Primary Industries, Landscape & Water Sciences
29 Department of Agroecology
30 National Centre for Atmospheric Science, Department of Meteorology
31 Institute of Soil Ecology German Research Center for Environmental Health
32 Computational and Systems Biology Department
33 FAO - Food and Agriculture Organization of the United Nations [France]
34 WSU - Washington State University
35 Institute of Soil Science and Land Evaluation
36 WUR - Wageningen University and Research [Wageningen]
37 Institute Geographical Sciences and Natural Resources Research
38 CIRN, Institute forClimate and Water
39 Arid-Land Agricultural Research Center
Pierre Martre
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Frank Ewert
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James W. Jones
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Davide Cammarano
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Andrew J. Challinor
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Claas Nendel
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- ORCID : 0000-0001-7608-9097
Mikhail A. Semenov
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- ORCID : 0000-0002-1561-7113
Iurii Shcherbak
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Résumé
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.