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| Author |
Dono, G. |
| Title |
Most relevant aspects of climate change in hot-spot analysis |
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Report |
| Year |
2013 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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1 |
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D-T3.1 |
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WP3 develops the tools for assessing the productive and economic impact of climate change and the potential of mitigation and adaptation strategies. This is achieved by focussing, along with CropM and LiveM, on significant crossing issues in specific geographical areas, natural and human resources, and farming systems. Following, the steps for identifying the hot-spots and the basic elements of climate change are shortly described. Next, the main economic and structural characteristics of each hot-spot are described followed by a presentation of the most relevant aspects of climate change, and of their main impacts on farm sector. No Label |
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MA @ admin @ |
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2263 |
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| Author |
Dono, G. |
| Title |
The economic impact of changes in climate variability on milk production in the area of Grana Padano |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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5 |
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Sp5-18 |
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Climate variability (CV) normally influences production and farm management, and climate change (CC) has precisely the effect of changing this variability. Thus, models that estimate the economic impact of CC, integrating with climatic models, agronomic, and livestock, must represent the implications of this variability on farm management. This study describes an economic model based on Discrete Stochastic Programming (DSP) which assesses the impact of CC on milk production in the Grana Padano area. The model is based on 23 farm typologies from FADN that represent 856 farms in Piacenza and Cremona, two of the most important provinces for Grana Padano production. The results of the model were projected at the regional scale. The climate scenarios, current and future, are generated with a Regional Atmospheric Modeling System. The forage production under these scenarios is estimated with the EPIC agronomic model. Estimates on milk production and livestock mortality are based on studies conducted in the Po valley. The nutritional needs of the cattle are estimated with the CNCPS model. Probability distribution functions (PDF) express the relations between the CV and the productive variables under both climate scenarios. These PDFs represent the expectations of farmers on the productive-climate variability in the DSP model, which is PMP calibrated based on land distribution observed in a reference year. Comparing the model results in the two scenarios indicates the effects of CC, given the opportunity to adapt the use of resources and techniques of cultivation. The structure of the model, and its economic results are presented and discussed, along with the strengths and weaknesses of this approach. 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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no |
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MA @ admin @ |
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2133 |
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| Author |
Dono, G. |
| Title |
Climate change impact on production and income of Mediterranean farming systems: a case study |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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5 |
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Sp5-17 |
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Adaptation to climate change calls for local responses. The impact of a 2020-30 climate scenario was assessed on a 54,000 ha Mediterranean district characterized by a variety of farming systems (FS), ranging from low-input rainfed (42% of the district area and 16% of the district net income) to high-input irrigated. Climate was generated with a Regional Atmospheric Modelling System nested into a full coupled atmosphere-ocean global simulation model, under the A1B emission scenario. Crop responses to climate were assessed using EPIC after calibration. The Temperature Humidity Index was used to assess the impact on dairy cow milk yield. Farmer choices were simulated on 13 representative FS by an hybrid model of supply, territory and farm. The adaptive choices were simulated through Discrete Stochastic Programming, fed by probability distribution functions output of crop and animal models. The expected decrease in spring rainfall (-33%) will affect hay-crop production and the net income (NI) of rainfed livestock farms (-5 to -12%). The increased summer temperature will affect dairy cows NI up to -5.9%. Rice production is expected to increase up to +10%. Overall, the NI of irrigated and rainfed farms will be -2.1% and -5.4% of the current NI respectively, with livestock FS being the most affected and rice and horticultural FS the most resilient. Results will provide an ideal mediating object for engaging policy makers and stakeholders in designing visionary adaptive strategies. 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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no |
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MA @ admin @ |
Serial |
2132 |
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Dono, G.; Raffaele, C.; Luca, G.; Roggero, P.P. |
| Title |
Income Impacts of Climate Change: Irrigated Farming in the Mediterranean and Expected Changes in Probability of Favorable and Adverse Weather Conditions |
Type |
Journal Article |
| Year |
2014 |
Publication |
German Journal of Agricultural Economics |
Abbreviated Journal |
German Journal of Agricultural Economics |
| Volume |
63 |
Issue |
3 |
Pages |
177-186 |
| Keywords |
discrete stochastic programming; rdp measures to adapt to climate change; economic impact of climate change; irrigated agriculture and climate change; insurance tools for adaptation to climate change; water markets; risk; variability; management; systems |
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EU rural development policy (RDP) regulation 1305/2013 aims to protect farmers’ incomes from ongoing change of climate variability (CCV), and the increase in frequency of adverse climatic events. An income stabilization tool (IST) is provided to compensate drastic drops in income, including those caused by climatic events. The present study examines some aspect of its application focussing on Mediterranean irrigation area where frequent water shortages may generate significant income reductions in the current climate conditions, and may be further exacerbated by climate change. This enhanced loss of income in the future would occur due to a change in climate variability. This change would appreciably reduce the probability of weather conditions that are favourable for irrigation, but would not significantly increase either the probability of unfavourable weather conditions or the magnitude of their impact. As the IST and other insurance tools that protect against adversity and catastrophic events are only activated under extreme conditions, farmers may not consider them to be suitable in dealing with the new climate regime. This would leave a portion of the financial resources allocated by the RDP unused, resulting in less support for climate change adaptation. |
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0002-1121 |
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CropM, TradeM, ft_macsur |
Approved |
no |
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MA @ admin @ |
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4669 |
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Dono, G.; Cortignani, R.; Doro, L.; Giraldo, L.; Ledda, L.; Pasqui, M.; Roggero, P.P. |
| Title |
Adapting to uncertainty associated with short-term climate variability changes in irrigated Mediterranean farming systems |
Type |
Journal Article |
| Year |
2013 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agricultural Systems |
| Volume |
117 |
Issue |
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Pages |
1-12 |
| Keywords |
changed climate variability; dsp; epic; adaptation; water management; irrigation; simulating impacts; co2 concentration; crop production; productivity; maize; yield; growth; model; photosynthesis; agriculture |
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Short-term perspectives appear to be relevant in formulating adaptation measures to changed climate variability (CCV) as a part of the European Rural Development Policy (RDP). Indeed, short-run CCV is the variation that farmers would perceive to such an extent that a political demand would be generated for adapting support measures. This study evaluates some relevant agronomic and economic impacts of CCV as modelled in a near future time period at the catchment scale in a rural district in Sardinia (Italy). The effects of CCV are assessed in relation to the availability of irrigation water and the irrigation needs of maize. The Environmental Policy Integrated Climate (EPIC) model was used to simulate the impact of key climatic variables on the irrigation water requirements and yields of maize. A three-stage discrete stochastic programming model was then applied to simulate management and economic responses to those changes. The overall economic impact of a simulated CCV was found to be primarily caused by reduced stability in the future supply of irrigation water. Adaptations to this instability will most likely lead to a higher level of groundwater extraction and a reduction in the demand for labour. Changed climate variability will most likely reduce the income potential of small-scale farming. The most CCV-vulnerable farm typologies were identified, and the implications were discussed in relation to the development of adaptation measures within the context of the Common Agricultural Policy of European Union. (C) 2013 Elsevier Ltd. All rights reserved. |
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0308521x |
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CropM, ftnotmacsur |
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no |
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MA @ admin @ |
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4489 |
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