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Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change

Authors :
Fronzek, Stefan
Pirttioja, Nina
Carter, Timothy R.
Bindi, Marco
Hoffmann, Holger
Palosuo, Taru
Ruiz-Ramos, Margarita
Tao, Fulu
Trnka, Miroslav
Acutis, Marco
Asseng, Senthold
Baranowski, Piotr
Basso, Bruno
Bodin, Per
Buis, Samuel
Cammarano, Davide
Deligios, Paola
Destain, Marie France
Dumont, Benjamin
Ewert, Frank
Ferrise, Roberto
François, Louis
Gaiser, Thomas
Hlavinka, Petr
Jacquemin, Ingrid
Kersebaum, Kurt Christian
Kollas, Chris
Krzyszczak, Jaromir
Lorite, Ignacio J.
Minet, Julien
Minguez, M.I.
Montesino, Manuel
Moriondo, Marco
Müller, Christoph
Nendel, Claas
Öztürk, Isik
Perego, Alessia
Rodríguez, Alfredo
Ruane, Alex C.
Ruget, Françoise
Sanna, Mattia
Semenov, Mikhail A.
Slawinski, Cezary
Stratonovitch, Pierre
Supit, Iwan
Waha, Katharina
Wang, Enli
Wu, Lianhai
Zhao, Zhigan
Rötter, Reimund P.
Fronzek, Stefan
Pirttioja, Nina
Carter, Timothy R.
Bindi, Marco
Hoffmann, Holger
Palosuo, Taru
Ruiz-Ramos, Margarita
Tao, Fulu
Trnka, Miroslav
Acutis, Marco
Asseng, Senthold
Baranowski, Piotr
Basso, Bruno
Bodin, Per
Buis, Samuel
Cammarano, Davide
Deligios, Paola
Destain, Marie France
Dumont, Benjamin
Ewert, Frank
Ferrise, Roberto
François, Louis
Gaiser, Thomas
Hlavinka, Petr
Jacquemin, Ingrid
Kersebaum, Kurt Christian
Kollas, Chris
Krzyszczak, Jaromir
Lorite, Ignacio J.
Minet, Julien
Minguez, M.I.
Montesino, Manuel
Moriondo, Marco
Müller, Christoph
Nendel, Claas
Öztürk, Isik
Perego, Alessia
Rodríguez, Alfredo
Ruane, Alex C.
Ruget, Françoise
Sanna, Mattia
Semenov, Mikhail A.
Slawinski, Cezary
Stratonovitch, Pierre
Supit, Iwan
Waha, Katharina
Wang, Enli
Wu, Lianhai
Zhao, Zhigan
Rötter, Reimund P.
Source :
ISSN: 0308-521X
Publication Year :
2018

Abstract

Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (-2 to +9°C) and precipitation (-50 to +50%). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses.The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern.The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description.Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their

Details

Database :
OAIster
Journal :
ISSN: 0308-521X
Notes :
application/pdf, Agricultural Systems 159 (2018), ISSN: 0308-521X, ISSN: 0308-521X, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1200324513
Document Type :
Electronic Resource