Kipling, R. P., & Scollan, N. G. (2014). Livestock production and the feed challenge. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: It is predicted that world population will reach nine billion by 2050 (Godfray et al., 2010) with the biggest increases occurring in the developing world (Guyomard et al., 2013, Thornton, 2010). This growth is expected to dramatically increase the demand for meat and animal products (Tilman et al., 2002) with a requirement by 2050 for 73 % more meat and 58 % more milk than produced in 2010 (FAO, 2011). In order to meet this growing demand, the supply of livestock products must rise to an extent comparable with that of the ‘Green Revolution’ (Tilman et al., 2002). This must occur in the context of serious global challenges related to climate change, resource availability, inequality, and biodiversity loss. At present many European livestock production systems are heavily reliant on a small number of feed products to provide protein, with imported soya accounting for 55 % of the 2.6 million tonnes of plant-derived protein fed to animals in the UK. This reliance on a small number of imported products leaves supply vulnerable to economic and climatic change. There is increased research into alternatives to South American soybean in the European feed supply chain, including improving the nutritional and agronomic characteristics of such alternatives, and exploring the use of new sources of potential feed material. This presents an opportunity for collaboration between experimental researchers and modellers to investigate the potential impacts of alternative feeds on livestock system productivity, robustness to climate change and levels of GHG emissions.
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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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