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Bindi, M. (2013). Identification of most important cropping systems and available models (Vol. 1).
Abstract: For each region or agro-ecological zone in Europe the major cropping systems have been identified based on their cropping area. Next, for each of the selected cropping systems the most widely applied models that fulfil a number of criteria (including their documentation in peer reviewed publications; good user guides and documentation of code; source code available) have been identified. Some possible model comparisons have been hypothesized on the basis of cropping systems and model availability. No Label
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Bindi, M., Palosuo, T., Trnka, M., & Semenov, M. A. (2015). Modelling climate change impacts on crop production for food security INTRODUCTION. Clim. Res., 65, 3–5.
Abstract: Process-based crop models that synthesise the latest scientific understanding of biophysical processes are currently the primary scientific tools available to assess potential impacts of climate change on crop production. Important obstacles are still present, however, and must be overcome for improving crop modelling application in integrated assessments of risk, of sustainability and of crop-production resilience in the face of climate change (e.g. uncertainty analysis, model integration, etc.). The research networks MACSUR and AGMIP organised the CropM International Symposium and Workshop in Oslo, on 10-12 February 2014, and present this CR Special, discussing the state-of-the-art-as well as future perspectives-of crop modelling applications in climate change risk assessment, including the challenges of integrated assessments for the agricultural sector.
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Bishop, J., & Lotze-Campen, H. (2017). XC8 Extreme events – Final report (Vol. 10).
Abstract: Following a MACSUR Workshop a joint working paper preliminary titled “More than a change in crop production: metrics and approaches to understand the impacts of extreme events on food security” is now in an advanced stage. A conference paper based on an M.Sc. thesis by Christoph Buschmann, titled “A model-based economic assessment of future climate variability impacts on global agricultural markets” has been presented and the International Conference of Agricultural Economists, 2015. We are working on a journal publication at the moment. Based on a B.Sc. thesis by Patrick Jeetze, we have submitted an abstract and held a presentation at the GlobalFood Symposium 2017, 28-29 April 2017 at Georg-August-University of Goettingen, Germany. Title: “Implications of future climate variability on food security: A model-based assessment of climate-induced crop price volatility impacts” We are currently working on a journal publication on this. Finally, we contributed one section to MACSUR's Research Gap Report (H0.1-D).
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Blanco-Penedo et al. (2016). Data driven dairy decision for farmers (Vol. 8).
Abstract: Conference poster PDF
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Bodin, P. (2015). Assessing modelling approaches for simulating the effect of high temperature stress on yield (Vol. 5).
Abstract: High temperature events can have a large negative effect on crop yields, and the effects of these events are strongly dependent on not only the maximum temperature but also on the length and timing of these heat stress events. In future climate the likelihood of these types of events are expected to increase and thus make it crucial to be able to correctly assess not only the effect of changes in mean temperature but also the effect of changes in climate extremes. Crop models are often employed to predict yield responses to a changing climate, and traditionally they have not included the effect of heat stress events. In recent years more and more models have come to include the effect of high temperature stress on crop yield. Here we implement three of these approaches (APSIM, GAEZ and CERES-Wheat) into the Crop-DGVM: LPJ-GUESS and results from an initial sensitivity analysis are presented. Results show a large difference in year to year variability in simulated yield for the different approaches, and also on differences in sensitivity in relation to temperature change. No Label
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