A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration - GIP Bretagne Environnement Accéder directement au contenu
Article Dans Une Revue Agricultural and Forest Meteorology Année : 2015

A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration

David Makowski (1) , S. Asseng (2) , F. Ewert (3) , Simona Bassu (1) , Jean-Louis Durand (4) , T. Li (5, 6) , Pierre Martres (7) , M. Adam (8) , P. K. Aggarwal (9) , C. Angulo (10) , C. Baron (11) , B. Basso (12, 13) , Patrick Bertuzzi (14) , C. Biernath (15) , H. Boogaard (16) , K. J. Boote (17) , B. Bouman (5, 6) , S. Bregaglio (18) , Nadine Brisson (1, 14) , Samuel Buis (19) , D. Cammarano (20) , A. J. Challinor (21, 22) , R. Confalonieri (23) , J. G. Conijn (24) , M. Corbeels (25, 26) , D. Deryng (27) , G. de Sanctis (28) , J. Doltra (29) , T. Fumoto (30) , D. Gaydon (31) , S. Gayler (32) , R. Goldberg (33) , R. F. Grant (34) , P. Grassini (35) , J. L. Hatfield (36) , T. Hasegawa (30) , L. Heng (37) , S. Hoek (38) , J. Hooker (39) , L. A. Hunt (40) , J. Ingwersen (41) , R. C. Izaurralde (42, 43) , R. E. E. Jongschaap (25, 26) , J. W. Jones (2) , R. A. Kemanian (44) , K. C. Kersebaum (45) , S. -H. Kim (46) , J. Lizaso (47) , M. Marcaida (5) , C. Müller (48) , H. Nakagawa (49) , S. Naresh Kumar (50) , C. Nendel (51) , G. J. O'Leary (52) , J. E. Olesen (53) , P. Oriol (8) , T. M. Osborne (54) , T. Palosuo (55) , M. V. Pravia (44, 56) , E. Priesack (57) , Dominique Ripoche (14) , C. Rosenzweig (33) , A. C. Ruane (33) , Francoise Ruget (19) , F. Sau (58) , M. A. Semenov (59) , I. Shcherbak (60) , B. Singh (61) , U. Singh (62) , H. K. Soo (63) , P. Steduto (64) , C. Stöckle (65) , P. Stratonovitch (59) , T. Streck (41) , I. Supit (66) , L. Tang (67) , F. Tao (55) , E. I. Teixeira (68) , P. Thorburn (31) , D. Timlin (69) , M. Travasso (70) , R.P. Rötter (55) , K. Waha (48, 71) , Daniel Wallach (72) , J. W. White (73) , P. Wilkens (62) , J. R. Williams (74) , J. Wolf (66) , X. Yin (75) , H. Yoshida (49) , Zhongkai Zhang (76) , Y. Zhu (67)
1 Agronomie
2 UF|ABE - Department of Agricultural and Biological Engineering [Gainesville]
3 INRES - Institute of Crop Science and Resource Conservation [Bonn]
4 P3F - Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères
5 IRRI - International Rice Research Institute [Philippines]
6 Int Rice Res Inst, Los Banos, Philippines
7 GDEC - Génétique Diversité et Ecophysiologie des Céréales
8 UMR AGAP - Amélioration génétique et adaptation des plantes méditerranéennes et tropicales
9 International Water Management Institute, Research Program on Climate Change, Agriculture and Food Security
10 Institute of Crops Science and Resource Conservation INRES
11 UMR TETIS - Territoires, Environnement, Télédétection et Information Spatiale
12 Department of Geological Sciences and W. K. Kellogg Biological Station
13 Department of Geological Sciences [East Lansing]
14 AGROCLIM - Agroclim
15 German Research Center for Environmental Health, Institute of Soil Ecololgy
16 Center for Geo-information
17 Department of Agronomy
18 Cassandra Lab
19 EMMAH - Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes
20 The James Hutton Institute
21 CGIAR ESSP Program on Climate Change, Agriculture and Food Security
22 SEE - School of Earth and Environment [Leeds]
23 Cassandra Lab
24 Plant Research International
25 Embrapa Cerrados
26 UPR AIDA - Agroécologie et Intensification Durables des cultures annuelles
27 Tyndall Centre for Climate Change Research, School of Environmental Science
28 JRC - European Commission - Joint Research Centre [Ispra]
29 Cantabrian Agricultural Research and Training Centre
30 Tsukuba
31 Agriculture Flagship
32 WESS Water and Earth System Science Competence Cluster
33 GISS - NASA Goddard Institute for Space Studies
34 Departement of Renewable Resources
35 Department of Agronomy and Horticulture
36 National Laboratory for Agriculture and Environment
37 IAEA - International Atomic Energy Agency [Vienna]
38 Centre for Geo-Information
39 Agriculture Department
40 Department of Plant Agriculture
41 Institute of Soil Science and Land Evaluation
42 Department of Geographical Sciences
43 AGIR - AGroécologie, Innovations, teRritoires
44 INIA - Instituto Nacional de Investigación Agropecuaria
45 Institute of Landscape System Analysis
46 College of the Environment, School of Environmental and Forest Sciences
47 Department Produccion Vegetal, Fitotecnia
48 PIK - Potsdam Institute for Climate Impact Research
49 NARO - National Agriculture and Food Research Organization
50 CESCRA - Centre for Environment Science and Climate Resilient Agriculture
51 Institute of Landscape Systems Analysis
52 Department of Economic Development Jobs, Transport and Resources
53 Department of Agroecology
54 Walker Institute, NCAS Climate
55 LUKE - Natural Resources Institute Finland
56 Department of Plant Science
57 German Research Center for Environmental Health, Institute of Soil Ecology
58 Department Biologia Vegetal
59 Computational and Systems Biology Department
60 Department of Geological Sciences and W.K. Kellogg Biological Station,
61 CIMMYT - International Maize and Wheat Improvement Centre [Inde]
62 IFDC - International Fertilizer Development Center
63 College of the Environment, School of Environmental and Forest Science
64 FAO - FAO Sub-regional Office for Eastern Africa [Addis Ababa, Ethiopie]
65 Biological Systems Engineering
66 Plant Production Systems and Earth System Science
67 National Engineering and Technology Center for Information Agriculture
68 Sustainable Production
69 ARS Crop Systems and Global Change Laboratory
70 CIRN, Institute for Climate and Water
71 Agriculture
72 ARCHE - Agrosystèmes Cultivés et Herbagers
73 Arid-Land Agricultural Research Center
74 Texas AgriLife Research and Extension
75 Centre for Crop Systems Analysis
76 State Key Laboratory of Earth Surface Processes and Resource Ecology
David Makowski
Simona Bassu
  • Fonction : Auteur
Patrick Bertuzzi
  • Fonction : Auteur
S. Bregaglio
  • Fonction : Auteur
Nadine Brisson
  • Fonction : Auteur
R. Confalonieri
  • Fonction : Auteur
T. Fumoto
  • Fonction : Auteur
D. Gaydon
  • Fonction : Auteur
T. Hasegawa
  • Fonction : Auteur
J. Hooker
  • Fonction : Auteur
Dominique Ripoche
  • Fonction : Auteur
P. Thorburn
  • Fonction : Auteur

Résumé

Ensembles of process-based crop models are increasingly used to simulate crop growth for scenarios of temperature and/or precipitation changes corresponding to different projections of atmospheric CO2 concentrations. This approach generates large datasets with thousands of simulated crop yield data. Such datasets potentially provide new information but it is difficult to summarize them in a useful way due to their structural complexities. An associated issue is that it is not straightforward to compare crops and to interpolate the results to alternative climate scenarios not initially included in the simulation protocols. Here we demonstrate that statistical models based on random-coefficient regressions are able to emulate ensembles of process-based crop models. An important advantage of the proposed statistical models is that they can interpolate between temperature levels and between CO2 concentration levels, and can thus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without rerunning the original complex crop models. Our approach is illustrated with three yield datasets simulated by 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to these datasets, and are then used to analyze the variability of the yield response to [CO2] and temperature. Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effect of a temperature increase of +2 degrees C in the considered sites. Compared to wheat, required levels of [CO2] increase are much higher for maize, and intermediate for rice. For all crops, uncertainties in simulating climate change impacts increase more with temperature than with elevated [CO2]. (C) 2015 Elsevier B.V. All rights reserved.

Dates et versions

hal-01245201 , version 1 (16-12-2015)

Identifiants

Citer

David Makowski, S. Asseng, F. Ewert, Simona Bassu, Jean-Louis Durand, et al.. A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration. Agricultural and Forest Meteorology, 2015, 214-215, pp.483-493. ⟨10.1016/j.agrformet.2015.09.013⟩. ⟨hal-01245201⟩
1145 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More