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Article Dans Une Revue Nature Plants Année : 2017

The uncertainty of crop yield projections is reduced by improved temperature response functions

1 Agriculture and Food
2 LEPSE - Écophysiologie des Plantes sous Stress environnementaux
3 CAU - China Agricultural University
4 Institute of Crop Science and Resource Conservation [Bonn]
5 ZALF - Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research
6 Georg-August-University = Georg-August-Universität Göttingen
7 Arid-Land Agricultural Research Center
8 The School of Plant Sciences
9 Global Wheat Program
10 CGIAR Research Program on Climate Change
11 WSU - Washington State University
12 Department of Earth and Environmental Sciences and W.K. Kellogg Biological Station
13 BIOP - Institute of Biochemical Plant Pathology
14 UF|ABE - Department of Agricultural and Biological Engineering [Gainesville]
15 University of Leeds
16 CCAFS - CGIAR Research Program on Climate Change, Agriculture and Food Security
17 EFSA - European Food Safety Authority
18 CIFA - Catabrian Agricultural Research and Training Center
19 Dep. Agronomia
20 CSIC - Consejo Superior de Investigaciones Cientificas [España] = Spanish National Research Council [Spain]
21 Institute of Soil Science and Land Evaluation
22 AgWeatherNet Program
23 Department of Plant Agriculture
24 Department of Geographical Sciences
25 Texas A and M AgriLife Research
26 Department of Agroecology
27 Jiangsu Collaborative Innovation Center for Modern Crop Production
28 PIK - Potsdam Institute for Climate Impact Research
29 CESCRA - Centre for Environment Science and Climate Resilient Agriculture
30 Landscape and Water Sciences
31 LUKE - Natural Resources Institute Finland
32 AGROCLIM - Agroclim
33 GISS - NASA Goddard Institute for Space Studies
34 Computational and Systems Biology Department
35 Biological Systems Engineering
36 PPS and WSG &CALM
37 CAAS - Chinese Academy of Agricultural Sciences
38 CSIRO - Commonwealth Scientific and Industrial Research Organisation [Canberra]
39 AGIR - AGroécologie, Innovations, teRritoires
40 College of Agronomy and Biotechnology
41 National Engineering and Technology Center for Information Agriculture
Enli Wang
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Gerrit Hoogenboom
Dominique Ripoche
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Iwan Supit
  • Fonction : Auteur
Daniel Wallach
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Joost Wolf
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Résumé

Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections.

Dates et versions

hal-02629102 , version 1 (27-05-2020)

Identifiants

Citer

Enli Wang, Pierre Martres, Zhigan Zhao, Frank Ewert, Andrea Maiorano, et al.. The uncertainty of crop yield projections is reduced by improved temperature response functions. Nature Plants, 2017, 3 (10), pp.833-833. ⟨10.1038/s41477-017-0032-6⟩. ⟨hal-02629102⟩
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