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Havlík, P. E. S., S. Fuss, D. Leclere, M. Obersteiner, A. Mosnier, H. Valin, N. Khabarov. (2013). Linking bio-physical, bottom-up and top-do wn economic models to analyze climate change impacts and adaptation on Austrian agriculture..
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Dumont, B., Basso, B., Bodson, B., Destain, J. - P., & Destain, M. - F. (2016). Assessing and modeling economic and environmental impact of wheat nitrogen management in Belgium. Env. Model. Softw., 79, 184–196.
Abstract: Future progress in wheat yield will rely on identifying genotypes & management practices better adapted to the fluctuating environment Nitrogen (N) fertilization is probably the most important practice impacting crop growth. However, the adverse environmental impacts of inappropriate N management (e.g., lixiviation) must be considered in the decision-making process. A formal decisional algorithm was developed to tactically optimize the economic & environmental N fertilization in wheat. Climatic uncertainty analysis was performed using stochastic weather time-series (LARS-WG). Crop growth was simulated using STICS model. Experiments were conducted to support the algorithm recommendations: winter wheat was sown between 2008 & 2014 in a classic loamy soil of the Hesbaye Region, Belgium (temperate climate). Results indicated that, most of the time, the third N fertilization applied at flag-leaf stage by farmers could be reduced. Environmental decision criterion is most of the time the limiting factor in comparison to the revenues expected by farmers. (C) 2016 Elsevier Ltd. All rights reserved.
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Harstad, O. M., Bonesmo, H. S., & Özkan, S. (2014). MACSUR – utfordringer for husdyrproduksjon i et framtidig klima (MACSUR- Challenges for livestock production in a future climate)..
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Gubbins, S. (2014). Climate, insect-borne viruses and livestock production..
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Gutierrez, L., F. Piras, P. Roggero. (2013). Short and long-run impact of climate changes on worldwide grain prices..
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