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Why do crop models diverge substantially in climate impact projections? A comprehensive analysis based on eight barley crop models

Authors :
Kurt Christian Kersebaum
Frank Ewert
Carlos Gregorio Hernández Díaz-Ambrona
Pierre Martre
Fulu Tao
Tapio Salo
Camilla Dibari
Xenia Specka
Lucía Rodríguez
Roberto Ferrise
Amit Kumar Srivastava
G. Padovan
Taru Palosuo
Davide Cammarano
Margarita Ruiz-Ramos
M. Ines Minguez
Alan H. Schulman
Mikhail A. Semenov
Thomas Gaiser
Claas Nendel
Reimund P. Rötter
Jukka Höhn
Viikki Plant Science Centre (ViPS)
Institute of Biotechnology
Natural Resources Institute Finland (LUKE)
Georg-August-University [Göttingen]
Centre for Biodiversity and Sustainable Land Use (CBL)
Universidad Politécnica de Madrid (UPM)
Rothamsted Research
Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF)
Department of Agronomy
Purdue University [West Lafayette]
Crop Science Group, INRES
Rheinische Friedrich-Wilhelms-Universität Bonn
Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI)
Écophysiologie des Plantes sous Stress environnementaux (LEPSE)
Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)
Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
University of Helsinki
FACCE-MACSUR knowledge hub (031A103B)
Academy of Finland through projects AI-CropPro (decision no. 316172)
DivCSA (decision no. 316215)
Natural Resources Institute Finland through strategic projects ClimSmartAgri and Boost-IA
German Federal Ministry of Education and Research
‘Limpopo Living Landscapes’ project within the SPACES program (grant number 01LL1304A)
IMPAC^3 project funded by the German Federal Ministry of Education and Research (FKZ 031A351A)
MULCLIVAR CGL2012-38923-C02-02 from MINECO and by MACSUR01-UPM from INIA within FACCE-JPI
German Federal Ministry of Food and Agriculture (BMEL) through the Federal Office for Agriculture and Food (BLE), (2851ERA01J)
German Ministry of Education and Research (BMBF), 031B0039C
FACCE-MACSUR project (031A103B) through the metaprogramme on Adaptation of Agriculture and Forests to Climate Change (AAFCC) of the French National Institute for Agricultural Research (INRA)
FACCE-JPI project ClimBar (Academy of Finland decision 284987)
JPI FACCE MACSUR2 through the Italian Ministry for Agricultural, Food, and Forestry Policies
Biotechnology and Biological Sciences Research Council (BBSRC) Designing Future Wheat project (BB/P016855/1).
European Project: 613556,EC:FP7:KBBE,FP7-KBBE-2013-7-single-stage,WHEALBI(2014)
Georg-August-University = Georg-August-Universität Göttingen
Biotechnology and Biological Sciences Research Council (BBSRC)
Università degli Studi di Firenze = University of Florence (UniFI)
Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro
Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
Helsingin yliopisto = Helsingfors universitet = University of Helsinki
Source :
Agricultural and Forest Meteorology, Agricultural and Forest Meteorology, Elsevier Masson, 2020, 281, ⟨10.1016/j.agrformet.2019.107851⟩, Agricultural and Forest Meteorology, 2020, 281, ⟨10.1016/j.agrformet.2019.107851⟩
Publication Year :
2020

Abstract

International audience; Robust projections of climate impact on crop growth and productivity by crop models are key to designing effective adaptations to cope with future climate risk. However, current crop models diverge strongly in their climate impact projections. Previous studies tried to compare or improve crop models regarding the impact of one single climate variable. However, this approach is insufficient, considering that crop growth and yield are affected by the interactive impacts of multiple climate change factors and multiple interrelated biophysical processes. Here, a new comprehensive analysis was conducted to look holistically at the reasons why crop models diverge substantially in climate impact projections and to investigate which biophysical processes and knowledge gaps are key factors affecting this uncertainty and should be given the highest priorities for improvement. First, eight barley models and eight climate projections for the 2050s were applied to investigate the uncertainty from crop model structure in climate impact projections for barley growth and yield at two sites: Jokioinen, Finland (Boreal) and Lleida, Spain (Mediterranean). Sensitivity analyses were then conducted on the responses of major crop processes to major climatic variables including temperature, precipitation, irradiation, and CO2, as well as their interactions, for each of the eight crop models. The results showed that the temperature and CO2 relationships in the models were the major sources of the large discrepancies among the models in climate impact projections. In particular, the impacts of increases in temperature and CO2 on leaf area development were identified as the major causes for the large uncertainty in simulating changes in evapotranspiration, above-ground biomass, and grain yield. Our findings highlight that advancements in understanding the basic processes and thresholds by which climate warming and CO2 increases will affect leaf area development, crop evapotranspiration, photosynthesis, and grain formation in contrasting environments are needed for modeling their impacts.

Details

Language :
English
ISSN :
01681923
Database :
OpenAIRE
Journal :
Agricultural and Forest Meteorology, Agricultural and Forest Meteorology, Elsevier Masson, 2020, 281, ⟨10.1016/j.agrformet.2019.107851⟩, Agricultural and Forest Meteorology, 2020, 281, ⟨10.1016/j.agrformet.2019.107851⟩
Accession number :
edsair.doi.dedup.....0edd8f600e781a70b021515221a46c54
Full Text :
https://doi.org/10.1016/j.agrformet.2019.107851⟩