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

AbstractPotential 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 μmol 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.
- Moscow Aviation Institute Russian Federation
- Département Sciences sociales, agriculture et alimentation, espace et environnement France
- United States Department of the Interior United States
- Helmholtz Association of German Research Centres Germany
- University of Basilicata Italy
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, nitrogen dynamics, Plant Biology, 551, maize, Agronomy and Crop Sciences, F01 - Culture des plantes, wheat, [CO2], water-use efficiency, uncertainty, [ SDV.SA ] Life Sciences [q-bio]/Agricultural sciences, agriculture, [SDV.SA] Life Sciences [q-bio]/Agricultural sciences, elevated co2, Geography, Agricultura, Temperature, Life Sciences, Agriculture, simulation, model intercomparison, climate change, Rendement des cultures, Other Plant Sciences, CO2, Modèle mathématique, simulation-model, Crops, Agricultural, 570, air co2 enrichment, P40 - Météorologie et climatologie, Climate Change, Agmip ; Climate ; Maize ; Model Intercomparison ; Simulation ; Temperature ; Uncertainty, Horticulture, carbon-dioxide, Models, Biological, Zea mays, Agricultural Science, climate, Changement climatique, 660, U10 - Méthodes mathématiques et statistiques, systems simulation, Modélisation des cultures, ddc:550, Plant Sciences, Botany, temperature, Water, Modèle de simulation, Carbon Dioxide, Température, yield, [SDV.SA] Life Sciences/Agricultural sciences, AgMIP, Dioxyde de carbone, agrovoc: agrovoc:c_24242, agrovoc: agrovoc:c_1070, agrovoc: agrovoc:c_8504, agrovoc: agrovoc:c_7657, agrovoc: agrovoc:c_3934, agrovoc: agrovoc:c_24199, agrovoc: agrovoc:c_3081, agrovoc: agrovoc:c_9000024, agrovoc: agrovoc:c_7608, agrovoc: agrovoc:c_1302, agrovoc: agrovoc:c_1666, agrovoc: agrovoc:c_10176
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, nitrogen dynamics, Plant Biology, 551, maize, Agronomy and Crop Sciences, F01 - Culture des plantes, wheat, [CO2], water-use efficiency, uncertainty, [ SDV.SA ] Life Sciences [q-bio]/Agricultural sciences, agriculture, [SDV.SA] Life Sciences [q-bio]/Agricultural sciences, elevated co2, Geography, Agricultura, Temperature, Life Sciences, Agriculture, simulation, model intercomparison, climate change, Rendement des cultures, Other Plant Sciences, CO2, Modèle mathématique, simulation-model, Crops, Agricultural, 570, air co2 enrichment, P40 - Météorologie et climatologie, Climate Change, Agmip ; Climate ; Maize ; Model Intercomparison ; Simulation ; Temperature ; Uncertainty, Horticulture, carbon-dioxide, Models, Biological, Zea mays, Agricultural Science, climate, Changement climatique, 660, U10 - Méthodes mathématiques et statistiques, systems simulation, Modélisation des cultures, ddc:550, Plant Sciences, Botany, temperature, Water, Modèle de simulation, Carbon Dioxide, Température, yield, [SDV.SA] Life Sciences/Agricultural sciences, AgMIP, Dioxyde de carbone, agrovoc: agrovoc:c_24242, agrovoc: agrovoc:c_1070, agrovoc: agrovoc:c_8504, agrovoc: agrovoc:c_7657, agrovoc: agrovoc:c_3934, agrovoc: agrovoc:c_24199, agrovoc: agrovoc:c_3081, agrovoc: agrovoc:c_9000024, agrovoc: agrovoc:c_7608, agrovoc: agrovoc:c_1302, agrovoc: agrovoc:c_1666, agrovoc: agrovoc:c_10176
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