Sandars, D. (2015). Understanding Europe’s future ability to feed itself within an uncertain climate change and socio economic scenario space (Vol. 5).
Abstract: Europe’s ability to feed its population depends on the balance of agricultural productivity (yields and land suitability) and demand which are affected by future climate and socio-economic change (arising from changing food demand; prices; technology change etc). Land use under 2050 climate change and socio-economic scenarios can be rapidly and systematically quantified with a modelling system that has been developed from meta-models of optimal cropping and crop and forest yields derived from the outputs of the previously developed complex models (Audsley et al; 2015). Profitability of each possible land use is modelled for every soil in every grid across the EU. Land use in a grid is then allocated based on profit thresholds set for intensive agriculture extensive agriculture, managed forest and finally unmanaged forest or unmanaged land. The European demand for food as a function of population, imports, food preferences and bioenergy, is a production constraint, as is irrigation water available. The model iterates until demand is satisfied (or cannot be met at any price). Results are presented as contour plots of key variables. For example, given a 40% increase in population from the baseline socio-economic scenario, adapting by increasing crop yields by 40% will leave a 38% probability that the 2050 future climate will be such that we cannot feed ourselves – considering “all” the possible climate scenarios. No Label
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Kipling, R. P., Topp, C. F. E., Bannink, A., Bartley, D. J., Blanco-Penedo, I., Cortignani, R., et al. (2019). To what extent is climate change adaptation a novel challenge for agricultural modellers. Env. Model. Softw., 120, Unsp 104492.
Abstract: Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change.
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Del Prado, A., van den Pol-van Dasselaar, A., Chadwick, D., Misselbrook, T., Sandars, D. L., Audsley, E., et al. (2014). Synergies between mitigation and adaption to climate change in grassland-based farming systems..
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Del Prado, A., Van den Pol-van Dasselaar, A., Chadwick, D., Misselbrook, T., Sandars, D., Audsley, E., et al. (2015). Synergies between mitigation and adaptation to Climate Change in grassland-based farming systems (Vol. 6).
Abstract: Climate change mitigation and adaptation have generally been considered in separate settings for both scientific and policy viewpoints. Recently, it has been stressed (e.g. by the latest IPCC reports) the importance to consider both mitigation and adaptation from land management together. To date, although there is already large amount of studies considering climate mitigation and adaptation in relation to grassland-based systems, there are no studies that analyse the potential synergies and tradeoffs for the main climate change mitigation and adaptation measures within the current European Policy context. This paper reviews which mitigation and adaptation measures interact with each other and how, and it explores the potential limitations and strengths of the different policy instruments that may have an effect in European grassland-based livestock systems. No Label
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Sandars, D., Audsley, E., & Holman, I. (2014). Predicting the optimum land use at any location for any future scenario (CLIMSAVE/IMPRESSIONS). FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Given any socio-, techno-, economic scenario and location specific soil and climate scenario, the farm model predicts the most profitable land use at that location. This model is encapsulated within a Europe-wide interactive interface, to allow adaptation and mitigation options to be explored by any user. With 5 climate models and 19 parameters, the user can study the sensitivity of the results to the chosen scenario settings. A scenario’s land use can be classified as intensive arable, intensive grassland, extensive grassland, forestry, or abandoned depending on potential profitability.
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