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Dono, G., Raffaele Cortignani, Paola Deligios, Luca Doro, Luca Giraldo, Luigi Ledda, Graziano Mazzapicchio, Massimiliano Pasqui, Pier Paolo Roggero. (2013). Economic assessment of the impact of uncertainty associated with short-run change in climate variability in Mediterranean farming systems..
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Dono, G. (2013). Storylines regarding climate change and scenarios (Vol. 1).
Abstract: 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 storylines regarding climate change and scenarios in the hot-spots. No Label
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Dono, G. (2013). Most relevant aspects of climate change in hot-spot analysis (Vol. 1).
Abstract: 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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Dono, G. (2015). The economic impact of changes in climate variability on milk production in the area of Grana Padano (Vol. 5).
Abstract: 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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Dono, G. (2015). Climate change impact on production and income of Mediterranean farming systems: a case study (Vol. 5).
Abstract: 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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