Hutchings, N. (2017). Farm-scale model linkage for ruminant systems (Vol. 10).
Abstract: This report describes the findings of the first workshop and associated actions of task L1.4. The findings detailed below, along with the outputs of a second workshop (L1.4-D2) are currently being synthesized into an article for submission as a peer reviewed paper. The work presented here addresses the scientific/conceptual issues related to model linkage.
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Hutchings, N., Weindl, I., Topp, C. F. E., Snow, V. O., Rotz, A., Raynal, H., et al. (2017). Does collaborative farm-scale modelling address current challenges and future opportunities (Vol. 10).
Abstract: Resources required increasing, resources available decreasing Farm-scale modellers will need to make strategic decisions Single-owner models May continue with additional resources Risk of ‘succession’ problem Community modelling is an alternative Need to continue building a community of farm modellers
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Topp, K., Eory, V., Bannink, A., Bartley, D. J., Blanco-Penedo, I., Cortignani, R., et al. (2017). Modelling climate change adaptation in European agriculture: Definitions and Current Modelling (Vol. 10).
Abstract: Confidential content, in preparation for a peer-reviewed publication.
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Hutchings, N., & Kipling, R. (2014). Inventory of farm-scale models within LiveM (Vol. 3).
Abstract: The aim of WP3 is to improve the assessment of the impact of climate change on livestock and grassland systems at the farm-scale. The first step in this process is to understand the current state of the art in farm-scale modelling, and the resources available within the MACSUR knowledge hub. Here, an inventory of the farm-scale models available within LiveM is presented, along with a summary of the types of model represented. Thirteen farm-scale models were identified, three of which focus on environmental aspects of farm systems (GHG emissions etc.) and ten of which focus on management strategies (productivity, economics etc.).
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Hutchings, N. (2015). A comparison of farm-scale models to estimate greenhouse gas emissions from dairy farms in Europe (Vol. 5).
Abstract: Farm-scale models quantify the cycling of nitrogen (N) and carbon (C) so are powerful tools for assessing the impact of management-related decisions on greenhouse gas (GHG) emissions, especially on dairy cattle farms, where the internal cycling is particularly important. Farm models range in focus (economic, environmental) and the detail with which they represent C and N cycling. We compared four models from this range in terms of on-farm production and emissions of GHGs, using standardized scenarios. The models compared were SFarMod, DairyWise, FarmAC and HolosNor. The scenarios compared were based on two soil types (sandy clay versus heavy clay), two roughage systems (grass only versus grass and maize), and two climate types (Eindhoven versus Santander). Standard farm characteristics were; area (50 ha), milk yield (7000 kg/head/year), fertiliser (275 kg N and 150 kg N/ha/year for grass and maize, respectively). Potential yields for grass 10t dry matter (DM)/ha/year in both areas, maize 14 t DM/ha/ year in Eindhoven and 18t DM/ha/ year in Santander. The import of animal feed and the export/import manure and forages was minimized. Similar total farm direct GHG emissions for all models disguised a variation between models in the contribution of the different on-farm sources. There were large differences between models in the predictions of indirect GHG emission from nitrate leaching. Results could be explained by differences between models in the assumptions made and detail with which underlying processes were represented. We conclude that the choice of an appropriate farm model is highly dependent upon the role it should play and the context within which it will operate, so the current diversity of farm models will continue into the future. No Label
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