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Cortignani, R., & Dono, G. (2015). Simulation of the impact of greening measures in an agricultural area of the southern Italy. Land Use Policy, 48, 525–533.
Abstract: Together, sustainable management of natural resources and climate action form one of the three objectives of the 2014-2020 Common Agricultural Policy. This objective is being addressed by replacing the existing direct payments under Pillar 1 with a basic payment, combined with an additional payment conditional on farmers undertaking agricultural practices beneficial for the climate and the environment, a policy referred to as greening. In this study, the impact of greening was assessed using a hybrid model calibrated using positive mathematical programming. The model describes the macro-types of farm production in a Mediterranean agricultural area. The results show that greening was not beneficial throughout the study area and only some farm types have been particularly affected. However, greening appears to have a positive impact on curtailing the use of chemicals, particularly nitrogen, and on crop diversity. (C) 2015 Elsevier Ltd. All rights reserved.
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Humblot, P., Jayet, P. A., Clerino, P., Leconte-Demarsy, D., Szopa, S., & Castell, J. F. (2013). Assessment of ozone impacts on farming systems: a bio-economic modeling approach applied to the widely diverse French case. Ecol. Econ., 85, 50–58.
Abstract: As a result of anthropogenic activities, ozone is produced in the surface atmosphere, causing direct damage to plants and reducing crop yields. By combining a biophysical crop model with an economic supply model we were able to predict and quantify this effect at a fine spatial resolution. We applied our approach to the very varied French case and showed that ozone has significant productivity and land-use effects. A comparison of moderate and high ozone scenarios for 2030 shows that wheat production may decrease by more than 30% and barley production may increase by more than 14% as surface ozone concentration increases. These variations are due to the direct effect of ozone on yields as well as to modifications in land use caused by a shift toward more ozone-resistant crops: our study predicts a 16% increase in the barley-growing area and an equal decrease in the wheat-growing area. Moreover, mean agricultural gross margin losses can go as high as 2.5% depending on the ozone scenario, and can reach 7% in some particularly affected regions. A rise in ozone concentration was also associated with a reduction of agricultural greenhouse gas emissions of about 2%, as a result of decreased use of nitrogen fertilizers. One noteworthy result was that major impacts, including changes in land use, do not necessarily occur in ozone high concentration zones, and may strongly depend on farm systems and their adaptation capability. Our study suggests that policy makers should view ozone pollution as a major potential threat to agricultural yields. (C) 2012 Elsevier B.V. All rights reserved.
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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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Vosough Ahmadi, B., Shrestha, S., Thomson, S. G., Barnes, A. P., & Stott, A. W. (2015). Impacts of greening measures and flat rate regional payments of the Common Agricultural Policy on Scottish beef and sheep farms. J. Agric. Sci., 153(04), 676–688.
Abstract: The latest Common Agricultural Policy (CAP) reforms could bring substantial changes to Scottish farming communities. Two major components of this reform package, an introduction of environmental measures into the Pillar 1 payments and a move away from historical farm payments towards regionalized area payments, would have a significant effect on altering existing support structures for Scottish farmers, as it would for similar farm types elsewhere in Europe where historic payments are used. An optimizing farm-level model was developed to explore how Scottish beef and sheep farms might be affected by the greening and flat rate payments under the current CAP reforms. Nine different types of beef and sheep farms were identified and detailed biophysical and financial farm-level data for these farm types were used to parameterize the model. Results showed that the greening measures of the CAP did not have much impact on net margins of most of the beef and sheep farm businesses, except for ‘Beef Finisher’ farm types where the net margins decreased by 3%. However, all farm types were better off adopting the greening measures than not qualifying for the greening payments through non-compliance with the measures. The move to regionalized farm payments increased the negative financial impact of greening on most of the farms but it was still substantially lower than the financial sacrifice of not adopting greening measures. Results of maximizing farm net margin, under a hypothetical assumption of excluding farm payments, showed that in most of the mixed (sheep and cattle) and beef suckler cattle farms the optimum stock numbers predicted by the model were lower than actual figures on farm. When the regionalized support payments were allocated to each farm, the proportion of the mixed farms that would increase their stock numbers increased whereas this proportion decreased for beef suckler farms and no impact was predicted in sheep farms. Also under the regionalized support payments, improvements in profitability were found in mixed farms and sheep farms. Some of the specialized beef suckler farms also returned a profit when CAP support was added.
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