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Holman, I. (2016). How do models treat climate change adaptation?. Rotterdam (Netherlands).
Abstract: Presentation SC 8.4 Impact indicators & models. How do models treat climate change adaptation?, Ian Holman, Cranfield University, United Kingdom (2016). Presented at the international conference Adaptation Futures 2016, Rotterdam, the Netherlands. No Label
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Höglind, M., Persson T. (2013). Yields and harvest security in Nordic forage production in the future – examples from simulation studies using the LINGRA model..
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Höglind, M. (2014). Europeisk landbruk i et klima i endring (MACSUR)..
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Höglind, M., Persson, T., & van Oijen, M. (2013). Identifying target traits for forage grass breeding under a changing climate in Norway using the BASGRA model..
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Savary, S., Jouanin, C., Félix, I., Gourdain, E., Piraux, F., Brun, F., et al. (2016). Assessing plant health in a network of experiments on hardy winter wheat varieties in France: patterns of disease-climate associations. Eur. J. Plant Pathol., 146, 741–755.
Abstract: A data set generated by a multi-year (2003–2010) and multi-site network of experiments on winter wheat varieties grown at different levels of crop management is analysed in order to assess the importance of climate on the variability of wheat health. Wheat health is represented by the multiple pathosystem involving five components: leaf rust, yellow rust, fusarium head blight, powdery mildew, and septoria tritici blotch. An overall framework of associations between multiple diseases and climate variables is developed. This framework involves disease levels in a binary form (i.e. epidemic vs. non-epidemic) and synthesis variables accounting for climate over spring and early summer. The multiple disease-climate pattern of associations of this framework conforms to disease-specific knowledge of climate effects on the components of the pathosystem. It also concurs with a (climate-based) risk factor approach to wheat diseases. This report emphasizes the value of large scale data in crop health assessment and the usefulness of a risk factor approach for both tactical and strategic decisions for crop health management.
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