A crop model ensemble analysis of wheat yield sensitivity to changes in temperature and precipitation across a European transect

Nina Pirttioja


Impact response surfaces (IRSs) were constructed to depict the sensitivity of modelled spring and winter wheat yields to systematic changes in baseline temperature (between -2°C and +9°C)  and precipitation (-50 to +50%)  as simulated by a 26-member ensemble of process-based crop simulation models. The study was conducted across a latitudinal transect for sites in Finland, Germany and Spain.

In spite of large differences in simulated yield responses to both baseline and changed climate between models, sites, crops and years, several common messages emerged. Ensemble average yields decline with warming (3-7% per 1°C) and decreased precipitation (3-9% per 10% decrease), but benefit from increased precipitation (0-8% per 10% increase). Yields are more sensitive to temperature than precipitation changes at the Finnish site while sensitivities are mixed at the other sites. Inter-model variability is highest for baseline climate at the Spanish site but is affected little by changed climate. Model responses diverge most under warming at the Finnish and German sites for winter wheat. The IRS pattern of yield reliability tracks average yield levels.

Optimal temperatures for present-day cultivars are below the baseline at the German and Spanish sites suggesting that adoption of cultivars with higher temperature requirements might already be advantageous, and increasingly so at all sites under future warming.

The study was conducted in the CropM component of the FACCE-JPI/MACSUR project.

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Authors: Nina Pirttioja1, Timothy R. Carter1, Stefan Fronzek1, Marco Bindi2, Holger Hoffmann3, Taru Palosuo4, Margarita Ruiz-Ramos5, Fulu Tao4, Miroslav Trnka6,7, Marco Acutis8, Senthold Asseng9, Piotr Baranowski10, Bruno Basso11, Per Bodin12, Samuel Buis13, Davide Cammarano14, Paola Deligios15, Marie-France Destain16, Benjamin Dumont16, Frank Ewert3, Roberto Ferrise2, Louis François16, Thomas Gaiser3, Petr Hlavinka6,7, Ingrid Jacquemin16, Kurt Christian Kersebaum17, Chris Kollas17, Jaromir Krzyszczak10, Ignacio J. Lorite18, Julien Minet16, M. Ines Minguez5, Manuel Montesino19, Marco Moriondo20, Christoph Müller21, Claas Nendel17, Isik Öztürk22, Alessia Perego8, Alfredo Rodríguez5, Alex C. Ruane23,24, Françoise Ruget13, Mattia Sanna8, Mikhail A. Semenov25, Cezary Slawinski10, Pierre Stratonovitch25, Iwan Supit26, Katharina Waha21, Enli Wang27, Lianhai Wu28, Zhigan Zhao27,29, Reimund P. Rötter4

Affiliations: 1Finnish Environment Institute (SYKE), Finland;2University of Florence, Italy;3INRES, University of Bonn, Germany;4Natural Resources Institute Finland (Luke), Finland;5CEIGRAM-AgSystems, Universidad Politecnica de Madrid, Spain;6Institute of Agrosystems and Bioclimatology, Mendel University in Brno, Czech Republic;7Global Change Research Centre AS CR, v.v.i., Czech Republic;8University of Milan, Italy;9University of Florida, USA;10Institute of Agrophysics, Polish Academy of Sciences, Poland;11Michigan State University, USA;12Lund University, Sweden;13INRA, UMR 1114 EMMAH, France;14James Hutton Institute, Scotland;15University of Sassari, Italy;16Université de Liège, Belgium;17Leibniz Centre for Agricultural Landscape Research (ZALF), Germany;18IFAPA Junta de Andalucia, Spain;19University of Copenhagen, Denmark;20CNR-IBIMET, Italy;21Potsdam Institute for Climate Impact Research, Germany;22Aarhus University, Denmark;23NASA Goddard Institute for Space Studies, USA;24Columbia University Center for Climate Systems Research, USA;25Rothamsted Research, Harpenden, Herts, UK;26Wageningen University, The Netherlands;27CSIRO Agriculture Flagship, Australia;28Rothamsted Research, North Wyke, Okehampton, UK;29China Agricultural University, China

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