Rötter, R. P. (2014). Cross-cutting uncertainties in MACSUR impact projections. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Projections into the future, such as climate change impact projections on crop production for a given region, or, on global food prices and trade are inherently uncertain. Uncertainty does not fall within a single discipline but is dealt with by a wide variety of disciplines, themes and problem domains. Model uncertainty pertaining to the impact modelling chain from climate via crop and livestock to economic and trade modelling is only part of the overall uncertainty*. There is also scenario uncertainty and many other known and unknown “unknowns”1 to be considered in efforts such as MACSUR and its themes (CropM, LiveM, TradeM) to advance model-based integrated assessment of climate change risk assessment for agriculture and food security. Propagation of uncertainties along the climate change impact modelling chain has been portrayed as “uncertainty cascade” 2. We will present different basic approaches for evaluating uncertainty in models. So far, studies addressing quantification and reporting of uncertainties in impact projections still largely focus on two major sources, i.e. the shares originating from climate modelling and from crop modelling. However, a more comprehensive treatment of uncertainty and how it is reported is urgently needed.
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Jorgenson, J. S. (2014). Data format standards and variable mapping. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Short report on work being done tools used for standardising data formats, including variable name mapping.
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Bellocchi, G., Rivington, M., & Acutis, M. (2014). Deliberative processes for comprehensive evaluation of agro-ecological models. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Biophysical models are acknowledged for examining interactions of agro-ecological systems and fostering communication between scientists, managers and the public. As the role of models grows in importance, there is an increase in the need to assess their quality and performance (Bellocchi et al., 2010). However, the heterogeneity of factors influencing model outputs makes it difficult a full assessment of model features. Where models are used with or for stakeholders then model credibility depends not only on the outcomes of well-structured statistical evaluation but also less tangible factors may need to be addressed using complementary deliberative processes. To expand our horizons in the evaluation of crop and grassland models, approaches have been reviewed with emphasis on using combined metrics. Comprehensive evaluation of simulation models was developed to integrate expectations of stakeholders via a weighting system where lower and upper fuzzy bounds are applied to a set of evaluation metrics. A questionnaire-based survey helped understanding the multi-faceted knowledge and experience required and the substantial challenges posed by the deliberative process. MACSUR knowledge hub holds potential to advance in good modelling practice in relation with model evaluation (including access to appropriate software tools), an activity which is frequently neglected in the context of time-limited projects.
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Persson, T., Kværnø, S., & Höglind, M. (2014). Determining the impact of soil regionalization and climate change on wheat and timothy grass yield in southeastern Norway. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Southeastern Norway is characterized by variable soils, which affect its agricultural productivity. The region is dominated by cereal production, but livestock farming with forage crops has increased the latest years. Climate and socio-economic changes could entail a shift from the current production areas of cereal and forage crops. In this study we used the mechanistic models CSM-CERES and LINGRA to evaluate impacts of climate change and soil variability on wheat and timothy yields in Akerhus and Østfold Counties in Southeastern Norway. The models were run for historical (1961-90) and projected future (2046-2065) climatic conditions, and for four soil regionalizations of different resolution (1, 5, 16 and 76 representative soil profiles). The extrapolation of soil characteristics was based on similarities in texture, organic matter, layering and water holding capacity. Across the whole region, there were small differences in both spring wheat and timothy yield between the different soil regionalization resolutions. However, within certain districts within the region the differences in wheat grain yield and timothy biomass yield among the soil resolutions were up to 20 percent. These results indicate that a relatively detailed resolution of the soil proporties is preferred to better understand the impact of shifts in production between cereals and forage grasses on yield level if spatial variability within regions is considered. The climate change scenario used indicated increased yields of both crop types in a future climate. Further steps could include a weighting of the wheat and timothy production across soils according to economic analyses.
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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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