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Rolinski, S., Weindl, I., Heinke, J., Bodirsky, B. L., Biewald, A., & Lotze-Campen, H. (2015). Pasture harvest, carbon sequestration and feeding potentials under different grazing intensities. Advances in Animal Biosciences, 6(01), 43–45.
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Bodirsky, B. L., Popp, A., Lotze-Campen, H., Dietrich, J. P., Rolinski, S., Weindl, I., et al. (2014). Reactive nitrogen requirements to feed the world in 2050 and potential to mitigate nitrogen pollution. Nat. Comm., 5, 3858.
Abstract: Reactive nitrogen (Nr) is an indispensable nutrient for agricultural production and human alimentation. Simultaneously, agriculture is the largest contributor to Nr pollution, causing severe damages to human health and ecosystem services. The trade-off between food availability and Nr pollution can be attenuated by several key mitigation options, including Nr efficiency improvements in crop and animal production systems, food waste reduction in households and lower consumption of Nr-intensive animal products. However, their quantitative mitigation potential remains unclear, especially under the added pressure of population growth and changes in food consumption. Here we show by model simulations, that under baseline conditions, Nr pollution in 2050 can be expected to rise to 102-156% of the 2010 value. Only under ambitious mitigation, does pollution possibly decrease to 36-76% of the 2010 value. Air, water and atmospheric Nr pollution go far beyond critical environmental thresholds without mitigation actions. Even under ambitious mitigation, the risk remains that thresholds are exceeded.
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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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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., 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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