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Eory, V.; MacLeod, M.; Shrestha, S.; Roberts, D. |
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Title  |
Linking an economic and a life-cycle analysis biophysical model to support agricultural greenhouse gas mitigation policy |
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Journal Article |
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Year |
2014 |
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German Journal of Agricultural Economics |
Abbreviated Journal |
German Journal of Agricultural Economics |
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63 |
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133-142 |
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Greenhouse gas (GHG) mitigation is one of the main challenges facing agriculture, exacerbated by the increasing demand for food, in particular for livestock products. Production expansion needs to be accompanied by reductions in the GHG emission intensity of agricultural products, if significant increases in emissions are to be avoided. Suggested farm management changes often have systemic effects on farm, therefore their investigation requires a whole farm approach. At the same time, changes in GHG emissions arising offfarm in food supply chains (pre- or post-farm) can also occur as a consequence of these management changes. A modelling framework that quantifies the whole-farm, life-cycle effects of GHG mitigation measures on emissions and farm finances has been developed. It is demonstrated via a case study of sexed semen on Scottish dairy farms. The results show that using sexed semen on dairy farms might be a costeffective way to reduce emissions from cattle production by increasing the amount of lower emission intensity ‘dairy beef’ produced. It is concluded that a modelling framework combining a GHG life cycle analysis model and an economic model is a useful tool to help designing targeted agri-environmental policies at regional and national levels. It has the flexibility to model a wide variety of farm types, locations and management changes, and the LCA-approach adopted helps to ensure that GHG emission leakage does not occur in the supply chain. |
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TradeM |
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MA @ admin @ |
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4670 |
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Ahmadi, B.V.; Thomson, S.; Shrestha, S.; Stott, A.W. |
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Title |
Predicting the implications of CAP reform using a bio-economic modelling approach |
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2013 |
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133rd EAAE seminar Developing Integrated and Reliable Modeling Tools for Agricultural and Environmental Policy Analysis, Crete, Greece, 2013-06-15 to 2013-06-16 |
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MA @ admin @ |
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2274 |
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Shrestha, S.; Ahmadi, B.V.; Thomson, S.A.; Barnes, A. |
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Title |
Scottish beef and sheep farms – will they be affected under greening of the CAP |
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2013 |
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LiveM |
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133rd EAAE seminar Developing Integrated and Reliable Modeling Tools for Agricultural and Environmental Policy Analysis, Crete, Greece, 2013-06-15 to 2013-06-16 |
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MA @ admin @ |
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2833 |
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Kipling, R.P.; Topp, C.F.E.; Bannink, A.; Bartley, D.J.; Blanco-Penedo, I.; Cortignani, R.; del Prado, A.; Dono, G.; Faverdin, P.; Graux, A.-I.; Hutchings, N.J.; Lauwers, L.; Gulzari, S.O.; Reidsma, P.; Rolinski, S.; Ruiz-Ramos, M.; Sandars, D.L.; Sandor, R.; Schoenhart, M.; Seddaiu, G.; van Middelkoop, J.; Shrestha, S.; Weindl, I.; Eory, V. |
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Title |
To what extent is climate change adaptation a novel challenge for agricultural modellers |
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2019 |
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Environmental Modelling & Software |
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Env. Model. Softw. |
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120 |
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Unsp 104492 |
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Adaptation; Agricultural modelling; Climate change; Research challenges; greenhouse-gas emissions; farm-level adaptation; land-use; food; security; adapting agriculture; livestock production; decision-making; change impacts; dairy farms; crop |
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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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2020-02-14 |
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English |
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1364-8152 |
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LiveM, ft_macsur |
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MA @ admin @ |
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5223 |
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