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Hoffmann, H., Zhao, G., Asseng, S. A. U. -,, Bindi, M., Cammarano, D., Constantin, J., et al. (2016). Analysing data aggregation effects on large-scale yield simulations.. Berlin (Germany).
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Ruiz-Ramos, M., Ferrise, R., Rodríguez, A., Lorite, I. J., Tao, F., Pirttioja, N., et al. (2016). An ensemble of projections of wheat adaptation to climate change in europe analyzed with impact response surfaces.. Berlin (Germany).
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Tao, F., & Zhang, Z. (2013). Climate Change, High-Temperature Stress, Rice Productivity, and Water Use in Eastern China: A New Superensemble-Based Probabilistic Projection. J. Appl. Meteor. Climatol., 52(3), 531–551.
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Ruiz-Ramos, M., Ferrise, R., Rodríguez, A., Lorite, I. J., Bindi, M., Carter, T. R., et al. (2017). Applying adaptation response surfaces for managing wheat under perturbed climate and elevated CO2 in a Mediterranean environment (Vol. 1ß).
Abstract: This study developed Adaptation Response Surfaces and applied them to a study case in North East Spain on winter crops adaptation, using rainfed winter wheat as reference crop. Crop responses to perturbed temperature, precipitation and CO2 were simulated by an ensemble of crop models. A set of combined changes on cultivars (on vernalisation requirements and phenology) and management (on sowing date and irrigation) were considered as adaptation options and simulated by the crop model ensemble. The discussion focused on two main issues: 1) the recommended adaptation options for different soil types and perturbation levels, and 2) the need of applying our current knowledge (AOCK) when building a crop model ensemble. The study has been published Agricultural Systems (Available online 25 January 2017, https://doi.org/10.1016/j.agsy.2017.01.009 ), and the text below consists on extracts from that paper.
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