Rötter, R. P., & Semenov, M. A. (2014). Development of methods for the probabilistic assessment of climate change impacts on crop production (Vol. 3).
Abstract: Various attempts have been made to determine the relative importance of uncertainties in climate change impact assessments stemming from climate projections and crop models, respectively, and to analyse yield outputs probabilistically. For example, in the ENSEMBLES project, probabilistic climate projections (Harris et al. 2010) have been applied in conjunction with impact response surfaces (IRS), constructed by using impact models, to estimate the future likelihood (risk) of exceeding critical thresholds of crop yield impact (see, Fronzek et al., 2011, for an explanation of the method). In this task, we aimed to further develop and operationalize these methods and testing them in different case study regions in Europe. The method combines results of a sensitivity analysis of (one or more) impact model(s) with probabilistic projections of future temperature and precipitation (Fronzek et al., 2011). Such an overlay is one way of portraying probabilistic estimates of future impacts. By further accounting for the uncertainties in crop and biophysical parameters (using perturbed parameter approaches), the outcome represents an ensemble of impact risk estimates, encapsulating both climate and crop model uncertainties. No Label
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Dáder, B., Winters, A., Moreno, A., Fereres, A., & Gwynn-Jones, D. (2014). Differences in plant chemistry and crop growth under specific wavelengths of the UV region..
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Schönhart, M., & Nadeem, I. (2014). Direct climate change impacts on cattle in Austria indicated by THI-models..
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Sanz-Cobena, A., García-Marco, S., Quemada, M., Gabriel, J. L., Almendros, P., & Vallejo, A. (2014). Do cover crops enhance N2O, CO2 or CH4 emissions from soil in Mediterranean arable systems? Science of the Total Environment, 466-467, 164–174.
Abstract: This study evaluates the effect of planting three cover crops (CCs) (barley, Hordeum vulgare L.; vetch, Vicia villosa L.; rape, Brassica napus L.) on the direct emission of N(2)O, CO(2) and CH(4) in the intercrop period and the impact of incorporating these CCs on the emission of greenhouse gas (GHG) from the forthcoming irrigated maize (Zea mays L.) crop. Vetch and barley were the CCs with the highest N(2)O and CO(2) losses (75 and 47% increase compared with the control, respectively) in the fallow period. In all cases, fluxes of N(2)O were increased through N fertilization and the incorporation of barley and rape residues (40 and 17% increase, respectively). The combination of a high C:N ratio with the addition of an external source of mineral N increased the fluxes of N(2)O compared with -Ba and -Rp. The direct emissions of N(2)O were lower than expected for a fertilized crop (0.10% emission factor, EF) compared with other studies and the IPCC EF. These results are believed to be associated with a decreased NO(3)(-) pool due to highly denitrifying conditions and increased drainage. The fluxes of CO(2) were in the range of other fertilized crops (i.e., 1118.71-1736.52 kg CO(2)-Cha(-1)). The incorporation of CC residues enhanced soil respiration in the range of 21-28% for barley and rape although no significant differences between treatments were detected. Negative CH(4) fluxes were measured and displayed an overall sink effect for all incorporated CC (mean values of -0.12 and -0.10 kg CH(4)-Cha(-1) for plots with and without incorporated CCs, respectively).
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Bartley, D. (2014). Do modellers dream of electric sheep? – Practical to mathematical and back again. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Disease agents, whether viral, bacterial or parasitic, infecting grazing domestic animals represent a significant threat to livestock health and welfare and to food security, globally. In addition, inefficiency in production due to sub-clinical disease adds significantly to a farm’s environmental footprint. Projected climatic changes over the short-medium term have implications for livestock pests and pathogens, both directly and indirectly, and will result in changing disease patterns e.g. incidence, seasonality and geographic spread. An area where interdisciplinary collaboration is mutually beneficial, and essential in order to gain a better understanding of the interactions between climatic change, pathogen dissemination and livestock productivity is between ‘fundamental’ or ‘practical’ livestock researchers and modellers. To facilitate this collaboration, there needs to be a dialogue between both parties on the data depth, quality and format required to populate different models to ensure relevant and appropriate outputs. An example of where this type of collaboration has been used is work using an Intergovernmental Panel on Climate Change (IPCC)-compliant model (CPLANv2) to calculate greenhouse gases (GHG) associated with fattening lambs over five consecutive grazing seasons. The results demonstrated that effective control of sub-clinical/clinical parasitic gastroenteritis resulted in a ~10% reduction in GHG emissions/kg live weight gain (Kenyon et al., 2013).
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