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Ewert, F., Rötter, R. P., Bindi, M., Webber, H., Trnka, M., Kersebaum, K., et al. (2015). Crop modelling for integrated assessment of risk to food production from climate change (Vol. 6).
Abstract: The complexity of risks posed by climate change and possible adaptations for crop production has called for integrated assessment and modelling (IAM) approaches linking biophysical and economic models. This paper attempts to provide an overview of the present state of crop modelling to assess climate change risks to food production and to which extent crop models comply with IAM demands. Considerable progress has been made in modelling effects of climate variables, where crop models best satisfy IAM demands. Demands are partly satisfied for simulating commonly required assessment variables. However, progress on the number of simulated crops, uncertainty propagation related to model parameters and structure, adaptations and scaling are less advanced and lagging behind IAM demands. The limitations are considered substantial and apply to a different extent to all crop models. Overcoming these limitations will require joint efforts, and consideration of novel modelling approaches. No Label
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Barbier-Brygoo, H., Chilliard, Y., Durand, J. - L., Elmayan, T., Goldringer, I., & Porter, J. R. (2014). Rapport du groupe de traveil sur la Propriétè Intellectuelle dans le végétal, du conseil scientifique nationale de l’INRA. Paris, France.
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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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Montesino-San Martin, M., Wallach, D., Olesen, J. E., & Porter, J. R. Quantifying data requirements in crop models; applying the learning curve approach to winter wheat phenology models.
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Porter, J. R., Durand, J. L., & Elmayan, T. (2016). Edited plants should not be patented. Nature, 530, 33.
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