1. Canopy temperature for simulation of heat stress in irrigated wheat in a semi-arid environment: A multi-model comparison
- Author
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Michael J. Ottman, Jørgen E. Olesen, Ehsan Eyshi Rezaei, Mikhail A. Semenov, Giacomo De Sanctis, Bruce A. Kimball, Frank Ewert, Pierre Martre, Gerard W. Wall, Jordi Doltra, Jeffrey W. White, Heidi Webber, Belay T. Kassie, Senthold Asseng, Andrea Maiorano, Dominique Ripoche, Pierre Stratonovitch, Robert F. Grant, Rheinische Friedrich-Wilhelms-Universität Bonn, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-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), Department of Agricultural and Biological Engineering [Gainesville] (UF|ABE), Institute of Food and Agricultural Sciences [Gainesville] (UF|IFAS), University of Florida [Gainesville] (UF)-University of Florida [Gainesville] (UF), Arid-Land Agricultural Research Center, School of Plant Sciences, University of Arizona, JRC Institute for Energy and Transport (IET), European Commission - Joint Research Centre [Petten], Cantabrian Agricultural Research and Training Centre, University of Alberta, Department of Agroecology, Aarhus University [Aarhus], Agroclim (AGROCLIM), Institut National de la Recherche Agronomique (INRA), Computational and Systems Biology Department, Rothamsted Research, German Science Foundation EW 119/5-1 /FACCE JPI MACSUR 031A103B, European Project: 267196, Biotechnology and Biological Sciences Research Council (BBSRC)-Biotechnology and Biological Sciences Research Council (BBSRC), Agricultural & Biological Engineering Department, University of Florida [Gainesville], and UE Agroclim (UE AGROCLIM)
- Subjects
Canopy ,stress thermique ,[SDV.SA]Life Sciences [q-bio]/Agricultural sciences ,Yield (engineering) ,ble tendre ,010504 meteorology & atmospheric sciences ,comparaison de modèles ,Energy balance ,Soil Science ,Grain filling ,Canopy temperature ,Atmospheric sciences ,01 natural sciences ,heat stress ,high temperature ,Crop model comparison ,crop model comparison ,Atmospheric instability ,climat semi aride ,condition environnementale ,0105 earth and related environmental sciences ,semi arid climate ,2. Zero hunger ,04 agricultural and veterinary sciences ,Arid ,canopy temperature ,Heat stress ,Agronomy ,soft wheat ,13. Climate action ,Semi-arid climate ,Wheat ,040103 agronomy & agriculture ,rendement agricole ,0401 agriculture, forestry, and fisheries ,Environmental science ,haute température ,Agronomy and Crop Science ,modèle multifactoriel - Abstract
Even brief periods of high temperatures occurring around flowering and during grain filling can severely reduce grain yield in cereals. Recently, ecophysiological and crop models have begun to represent such phenomena. Most models use air temperature (T-air) in their heat stress responses despite evidence that crop canopy temperature (T-c) better explains grain yield losses. T-c can deviate significantly from T-air based on climatic factors and the crop water status. The broad objective of this study was to evaluate whether simulation of T-c improves the ability of crop models to simulate heat stress impacts on wheat under irrigated conditions. Nine process-based models, each using one of three broad approaches (empirical, EMP; energy balance assuming neutral atmospheric stability, EBN; and energy balance correcting for the atmospheric stability conditions, EBSC) to simulate To simulated grain yield under a range of temperature conditions. The models varied widely in their ability to reproduce the measured T-c with the commonly used EBN models performing much worse than either EMP or EBSC. Use of T-c to account for heat stress effects did improve simulations compared to using only T-air to a relatively minor extent, but the models that additionally use T-c on various other processes as well did not have better yield simulations. Models that simulated yield well under heat stress had varying skill in simulating T-c For example, the EBN models had very poor simulations of T-c but performed very well in simulating grain yield. These results highlight the need to more systematically understand and model heat stress events in wheat.
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