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Bojar, W., Knopik, L., & Zarski, J. (2015). Application of Markov chains approach for expecting extreme precipitation changes having impact on food supply (Vol. 4).
Abstract: This work was co-financed by NCBiR, Contract no. FACCE JPI/04/2012 – P100 PARTNER No Label
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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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Kipling, R., Topp, K., & Don, A. (2014). Appropriate meta-data for modellers (Vol. 3).
Abstract: Report D-L1.4.1 provided an overview of the data and related resources available online and through EU funded projects, relating to soil organic carbon (SOC), and carbon sequestration in grasslands in particular. Building on D-L1.4.1, the report presented here discusses how meta-data describing these types of data (and experimental data more generally) can best be presented in an online resource useful to grassland modellers requiring data to use in their modelling work. Identifying the useful categories of meta-data is a necessary precursor to providing such a resource, which could facilitate better communication between modelling and experimental research groups, allowing researchers to more efficiently locate relevant data and to link up with other scientists working on similar topics. A survey among grassland modelling teams and an assessment of online meta-data resources was used to produce recommendations about the meta-data categories that should be included in an online resource. The categories are generic, so that the recommendations can be followed in the design of meta-data resources for the more general agricultural modelling community. No Label
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Saetnan, E. (2015). Are we building a better connected community (Vol. 5).
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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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