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Watson, J., Challinor, A. J., Fricker, T. E., & Ferro, C. A. T. (2015). Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model. Clim. Change, 132(1), 93–109.
Abstract: Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve.
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Shrestha, S. (2015). Comparing the cost effectiveness of GHG mitigation options on different Scottish dairy farm groups (Vol. 5).
Abstract: Greenhouse gas (GHG) mitigation is one of the main challenges faced by agriculture sector especially under an increasing demand for food. Production expansion needs to be accompanied by reductions in the GHG emission intensity of agricultural products. However, any uptakes of mitigation options by the farmers depend on the cost effectiveness of adopting such options as well as the farm characteristics. A highly effective mitigation option might not be practical for a farmer if the associated costs are high. A list of mitigation option implemented on different farm types with their cost effectiveness on farms would therefore be very useful for farmers as well as policy makers to make a decision. This paper aims to explore the use of three GHG mitigation options on different dairy farm groups in Scotland and determine the cost effectiveness of each of the options in those farm groups. The mitigation options considered for this paper are; i) use of sexed semen, ii) installing and using anaerobic digester and iii) increasing the share of concentrate diet. Farm level data from the Scottish Farm Accountancy dataset (FAS) was used and a cluster analysis was carried on to identify different dairy farm groups. The potential reduction of GHG emission per farm, including emissions arising from inputs used on the farm, under each of the option is then calculated using the GLEAM life cycle assessment model. An optimising farm level model, ScotFarm, was used on each of the farm groups to determine the optimum farm net margins under a baseline situation (with no options implemented) and three mitigation scenarios. The cost effectiveness of all three mitigation options are then determined based on reduction in GHG emission per farm and change in farm net margins under those options. Initial results for the sexed semen scenario suggest that this option can be cost effective for both efficient dairy farms (-£6.26/tCO2e) and medium-sized dairy farms (-£12.56/tCO2e). No Label
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Tsutsumi, Y. (2015). Comparing bio-economic farm models: evaluating uncertainty of impacts of climate and socio-economic changes on arable farming in Flevoland (the Netherlands). M.Sc., M.Sc.. Master's thesis, Wageningen University, Wageningen.
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Rivington, M., & Wallach, D. (2015). Communication strategy, including design of tools for more effective communication of uncertainty (Vol. 6).
Abstract: Communication is the key link between the generation of information by MACSUR about the uncertainty of climate change impacts on future food security and how information is used by decision makers. It is therefore important to make available the common tools for reporting uncertainty, with a discussion of the advantages or difficulties of each. That is the purpose of this report. No Label
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Kipling, R. (2015). Communicating Modelling (Vol. 4).
Abstract: No abstract. No Label
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