How do various maize crop models vary in their responses to climate change factors?

Autor: Federico Sau, Sjaak Conijn, Delphine Deryng, Jean-Louis Durand, Katharina Waha, Edmar Teixeira, Iurii Shcherbak, R.E.E. Jongschaap, James W. Jones, Kenneth J. Boote, Maria Virginia Pravia, Jerry L. Hatfield, Alex C. Ruane, Christian Biernath, Patricio Grassini, H.L. Boogaard, Steven Hoek, K. Christian Kersebaum, Fulu Tao, Christian Baron, David Makowski, Claas Nendel, Sebastian Gayler, Dennis Timlin, Marc Corbeels, Christoph Müller, Nadine Brisson, Jon I. Lizaso, Naresh S. Kumar, Cynthia Rosenzweig, Simona Bassu, Armen R. Kemanian, Cesar Izaurralde, Bruno Basso, Giacomo De Sanctis, Myriam Adam, Soo-Hyung Kim, Eckart Priesack
Přispěvatelé: Agronomie, AgroParisTech-Institut National de la Recherche Agronomique (INRA), Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères (P3F), Institut National de la Recherche Agronomique (INRA), Department of agronomy, University of Florida [Gainesville], Department Produccion vegetal, Fitotecnia, Universidad Politécnica de Madrid (UPM), Department of agricultural and biological engineering, GISS Climate impacts group, NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC)-NASA Goddard Space Flight Center (GSFC), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Department of geological sciences, Michigan State University [East Lansing], Michigan State University System-Michigan State University System, Department crop systems, forestry and environmental sciences, University of Basilicata, Centre for Geo-Information, ALTERRA, WUR-Plant research international, Wageningen University and Research Centre [Wageningen] (WUR), Agroécologie et Intensification Durables des cultures annuelles (Cirad-Persyst-UPR 115 AIDA), Département Performances des systèmes de production et de transformation tropicaux (Cirad-PERSYST), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), School of Environmental Sciences [Norwich], UE Agroclim (UE AGROCLIM), Water and earth system science [Tübingen] (WESS), Eberhard Karls Universität Tübingen, Department of agronomy and horticulture, University of Nebraska [Lincoln], University of Nebraska System-University of Nebraska System, Department of plant science, University of Pensylvania, Institute of Lanscape Systems Analysis, Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), School of environmental and forest sciences, University of Washington [Seattle], Centre for Environment Science and Climate Resilient Agriculture (CESCRA), Indian Agricultural Research Institute (IARI), Institute of landscape systems analysis, Institute of geographical sciences and natural resources research, Chinese Academy of Sciences [Changchun Branch] (CAS), Institut National de la Recherche Agronomique ( INRA ) -AgroParisTech, Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères ( P3F ), Institut National de la Recherche Agronomique ( INRA ), Universidad Politécnica de Madrid ( UPM ), NASA Goddard Institute for Space Studies ( GISS ), NASA Goddard Space Flight Center ( GSFC ) -NASA Goddard Space Flight Center ( GSFC ), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales ( UMR AGAP ), Institut national de la recherche agronomique [Montpellier] ( INRA Montpellier ) -Centre international d'études supérieures en sciences agronomiques ( Montpellier SupAgro ) -Centre de Coopération Internationale en Recherche Agronomique pour le Développement ( CIRAD ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ), Territoires, Environnement, Télédétection et Information Spatiale ( UMR TETIS ), Centre de Coopération Internationale en Recherche Agronomique pour le Développement ( CIRAD ) -AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ), Wageningen University and Research Centre [Wageningen] ( WUR ), Annual cropping systems, Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Tyndall Centre for climate change research and school of environmental sciences, University of East Anglia [Norwich] ( UEA ), UE Agroclim ( UE AGROCLIM ), Water and earth system science (WESS) competence cluster, University of Nebraska-Lincoln, Leibniz Centre for Agricultural Landscape Research, Centre for Environment Science and Climate Resilient Agriculture ( CESCRA ), Indian Agricultural Research Institute ( IARI ), Chinese Academy of Sciences [Changchun Branch] ( CAS ), University of Florida [Gainesville] (UF), 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), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-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), Wageningen University and Research [Wageningen] (WUR), Agroécologie et Intensification Durables des cultures annuelles (UPR AIDA), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Agroclim (AGROCLIM), Eberhard Karls Universität Tübingen = Eberhard Karls University of Tuebingen
Jazyk: angličtina
Rok vydání: 2014
Předmět:
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences
010504 meteorology & atmospheric sciences
nitrogen dynamics
Atmospheric sciences
maize
01 natural sciences
Standard deviation
F01 - Culture des plantes
wheat
Aardobservatie en omgevingsinformatica
water-use efficiency
uncertainty
[ SDV.SA ] Life Sciences [q-bio]/Agricultural sciences
General Environmental Science
agriculture
2. Zero hunger
Global and Planetary Change
elevated co2
Ecology
Geography
Phenology
U10 - Informatique
mathématiques et statistiques
Agricultura
04 agricultural and veterinary sciences
simulation
Rendement des cultures
model intercomparison
climate change
CO2
Crop simulation model
Modèle mathématique
Crops
Agricultural
simulation-model
Earth Observation and Environmental Informatics
air co2 enrichment
P40 - Météorologie et climatologie
Agmip
Climate
Maize
Model Intercomparison
Simulation
Temperature
Uncertainty
Climate change
carbon-dioxide
Models
Biological
Zea mays
Agro Water- en Biobased Economy
Environmental Chemistry
Water-use efficiency
climate
0105 earth and related environmental sciences
Changement climatique
systems simulation
Modélisation des cultures
Crop yield
Simulation modeling
Water
temperature
Modèle de simulation
Carbon Dioxide
yield
Température
Agronomy
13. Climate action
Yield (chemistry)
040103 agronomy & agriculture
AgMIP
0401 agriculture
forestry
and fisheries
Environmental science
Dioxyde de carbone
Zdroj: Global Change Biology
Global Change Biology, Wiley, 2014, 20 (7), pp.2301-2320. ⟨10.1111/gcb.12520⟩
Glob. Change Biol. 20, 2301-2320 (2014)
Global Change Biology, ISSN 1354-1013, 2013-07, Vol. 20, No. 7
Global Change Biology, Wiley, 2014, 20 (7), pp.2301-2320. 〈10.1111/gcb.12520〉
Global Change Biology, 20(7), 2301-2320
Global Change Biology 20 (2014) 7
Archivo Digital UPM
Universidad Politécnica de Madrid
ISSN: 1354-1013
1365-2486
DOI: 10.1111/gcb.12520⟩
Popis: Comments This article is a U.S. government work, and is not subject to copyright in the United States. Abstract Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha 1 per °C. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.
Databáze: OpenAIRE
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