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Shrestha, S. |
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Title |
Comparing the cost effectiveness of GHG mitigation options on different Scottish dairy farm groups |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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5 |
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Sp5-62 |
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Greenhouse gas (GHG) mitigation is one of the main challenges faced by agriculture sector especially under an increasing demand for food. Production expansion needs to be accompanied by reductions in the GHG emission intensity of agricultural products. However, any uptakes of mitigation options by the farmers depend on the cost effectiveness of adopting such options as well as the farm characteristics. A highly effective mitigation option might not be practical for a farmer if the associated costs are high. A list of mitigation option implemented on different farm types with their cost effectiveness on farms would therefore be very useful for farmers as well as policy makers to make a decision. This paper aims to explore the use of three GHG mitigation options on different dairy farm groups in Scotland and determine the cost effectiveness of each of the options in those farm groups. The mitigation options considered for this paper are; i) use of sexed semen, ii) installing and using anaerobic digester and iii) increasing the share of concentrate diet. Farm level data from the Scottish Farm Accountancy dataset (FAS) was used and a cluster analysis was carried on to identify different dairy farm groups. The potential reduction of GHG emission per farm, including emissions arising from inputs used on the farm, under each of the option is then calculated using the GLEAM life cycle assessment model. An optimising farm level model, ScotFarm, was used on each of the farm groups to determine the optimum farm net margins under a baseline situation (with no options implemented) and three mitigation scenarios. The cost effectiveness of all three mitigation options are then determined based on reduction in GHG emission per farm and change in farm net margins under those options. Initial results for the sexed semen scenario suggest that this option can be cost effective for both efficient dairy farms (-£6.26/tCO2e) and medium-sized dairy farms (-£12.56/tCO2e). No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2177 |
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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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2014 |
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German Journal of Agricultural Economics |
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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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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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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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1364-8152 |
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LiveM, ft_macsur |
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MA @ admin @ |
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5223 |
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Shrestha, S.; Abdalla, M.; Hennessy, T.; Forristal, D.; Jones, M.B. |
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Irish farms under climate change – is there a regional variation on farm responses? |
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2015 |
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Journal of Agricultural Science |
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J. Agric. Sci. |
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153 |
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03 |
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385-398 |
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change impacts; elevated co2; potential impacts; maize production; united-states; winter-wheat; plant-growth; adaptation; ireland; yield |
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The current paper aims to determine regional impacts of climate change on Irish farms examining the variation in farm responses. A set of crop growth models were used to determine crop and grass yields under a baseline scenario and a future climate scenario. These crop and grass yields were used along with farm-level data taken from the Irish National Farm Survey in an optimizing farm-level (farm-level linear programming) model, which maximizes farm profits under limiting resources. A change in farm net margins under the climate change scenario compared to the baseline scenario was taken as a measure to determine the effect of climate change on farms. The growth models suggested a decrease in cereal crop yields (up to 9%) but substantial increase in yields of forage maize (up to 97%) and grass (up to 56%) in all regions. Farms in the border, midlands and south-east regions suffered, whereas farms in all other regions generally fared better under the climate change scenario used in the current study. The results suggest that there is a regional variability between farms in their responses to the climate change scenario. Although substituting concentrate feed with grass feeds is the main adaptation on all livestock farms, the extent of such substitution differs between farms in different regions. For example, large dairy farms in the south-east region adopted total substitution of concentrate feed while similar dairy farms in the south-west region opted to replace only 0.30 of concentrate feed. Farms in most of the regions benefitted from increasing stocking rate, except for sheep farms in the border and dairy farms in the south-east regions. The tillage farms in the mid-east region responded to the climate change scenario by shifting arable production to beef production on farms. |
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0021-8596 1469-5146 |
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CropM, TradeM |
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MA @ admin @ |
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4542 |
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Shrestha, S.; Ciaian, P.; Himics, M.; van Doorslaer, B. |
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Title |
Impacts of climate change on EU agriculture |
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Journal Article |
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2013 |
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Review of Agricultural and Applied Economics |
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Review of Agricultural and Applied Economics |
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16 |
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2 |
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24-39 |
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climate change; agricultural productivity; adaptation; Europe |
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The current paper investigates the medium term economic impact of climate changes on the EU agriculture. The yield change data under climate change scenarios are taken from the BIOMA (Biophysical Models Application) simulation environment. We employ CAPRI modelling framework to identify the EU aggregate economic effects as well as regional impacts. We take into account supply and market price adjustments of the EU agricultural sector as well as technical adaptation of crops to climate change. Overall results indicate an increase in yields and production level in the EU agricultural sector due to the climate change. In general, there are relatively small effects at the EU aggregate. For example, the value of land use and welfare change by approximately between -2% and 0.2%. However, there is a stronger impact at regional level with some stronger effects prevailing particularly in the Central and Northern EU and smaller impacts are observed in Southern Europe. Regional impacts of climate change vary by a factor higher up to 10 relative to the aggregate EU impacts. The price adjustments reduce the response of agricultural sector to climate change in particular with respect to production and income changes. The technical adaption of crops to climate change may result in a change production and land use by a factor between 1.4 and 6 relative to no-adaptation situation. |
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TradeM, ftnotmacsur |
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MA @ admin @ |
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4615 |
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