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Roggero, P. P., Seddaiu, G., Ledda, L., Doro, L., Deligios, P., Nguyen, T. P. L., et al. (2014). Combining modeling and stakeholder involvement to build community adaptive responses to climate change in a Mediterranean agricultural district. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The case study area (54,000 ha) is located at Oristano, Italy. The main cropping systems are based on forages (silage maize, Italian ryegrass and alfalfa under irrigation, winter cereals and grasslands under rainfed conditions), rainfed cereals (durum wheat, barley), vegetables (e.g. artichokes), rice, citrus, olives and vineyards. Some 36,000 ha are served by irrigation. The area includes the dairy cows cooperative system of Arborea (30,000 cows, 5500 ha, nitrate vulnerable zone). The rainfed dairy sheep includes 372,000 sheep and a number of small milk processing plants. The research aims to support adaptive responses to climate change through the combination of modeling approaches and stakeholder engagement. Present (2000-2010) and future (2020-2030) climatic scenarios were developed by combining global climate models with Regional Atmospheric Modelling Systems to produce calibrated time series of daily temperature and precipitation for the case study. The EPIC model was calibrated to simulate the impact of climate scenarios on the main cropping systems. The impact of THIndex on milk yield, milk quality and mortality was also simulated for dairy cows. A territorial farm-type Discrete Stochastic Programming model was implemented to simulate choices for thirteen farming typologies as influenced by crop yields and water consumptions. Participatory activities, including field experiments, interviews, focus groups and interactive workshops, involved farmers and other stakeholders in the most critical phases of the research. The assessment of uncertainties and opportunities were proposed as a basis for discussion with policy makers to identify priorities for agro-climatic measures in 2014-2020.
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Dono, G., Cortignani, R., Dell’Unto, D., Deligios, P., Doro, L., Lacetera, N., et al. (2016). Winners and losers from climate change in agriculture: Insights from a case study in the Mediterranean basin. Agricultural Systems, 147, 65–75.
Abstract: The Mediterranean region has always shown a marked inter-annual variability in seasonal weather, creating uncertainty in decisional processes of cultivation and livestock breeding that should not be neglected when modeling farmers’ adaptive responses. This is especially relevant when assessing the impact of climate change (CC), which modifies the atmospheric variability and generates new uncertainty conditions, and the possibility of adaptation of agriculture. Our analysis examines this aspect reconstructing the effects of inter-annual climate variability in a diversified farming district that well represents a wide range of rainfed and irrigated agricultural systems in the Mediterranean area. We used a Regional Atmospheric Modelling System and a weather generator to generate 150 stochastic years of the present and near future climate. Then, we implemented calibrated crop and livestock models to estimate the corresponding productive responses in the form of probability distribution functions (PDFs) under the two climatic conditions. We assumed these PDFs able to represent the expectations of farmers in a discrete stochastic programming (DSP) model that reproduced their economic behaviour under uncertainty conditions. The comparison of the results in the two scenarios provided an assessment of the impact of CC, also taking into account the possibility of adjustment allowed by present technologies and price regimes. The DSP model is built in blocks that represent the farm typologies operating in the study area, each one with its own resource endowment, decisional constraints and economic response. Under this latter aspect, major differences emerged among farm typologies and sub-zones of the study area. A crucial element of differentiation was water availability, since only irrigated C3 crops took full advantage from the fertilization effect of increasing atmospheric CO2 concentration. Rainfed crop production was depressed by the expected reduction of spring rainfall associated to the higher temperatures. So, a dualism emerges between the smaller impact on crop production in the irrigated plain sub-zone, equipped with collective water networks and abundant irrigation resources, and the major negative impact in the hilly area, where these facilities and resources are absent. However intensive dairy farming was also negatively affected in terms of milk production and quality, and cattle mortality because of the increasing summer temperatures. This provides explicit guidance for addressing strategic adaptation policies and for framing farmers’ perception of CC, in order to help them to develop an awareness of the phenomena that are already in progress, which is a prerequisite for effective adaptation responses.
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Dono, G., Cortignani, R., Doro, L., Giraldo, L., Ledda, L., Pasqui, M., et al. (2013). Adapting to uncertainty associated with short-term climate variability changes in irrigated Mediterranean farming systems. Agricultural Systems, 117, 1–12.
Abstract: 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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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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Dono, G., Cortignani, R., Doro, L., Giraldo, L., Ledda, L., Pasqui, M., et al. (2013). An integrated assessment of the impacts of changing climate variability on agricultural productivity and profitability in an irrigated Mediterranean catchment. Water Resource Manage., 27(10), 3607–3622.
Abstract: Climate change is likely to have a profound effect on many agricultural variables, although the extent of its influence will vary over the course of the annual farm management cycle. Consequently, the effect of different and interconnected physical, technical and economic factors must be modeled in order to estimate the effects of climate change on agricultural productivity. Such modeling commonly makes use of indicators that summarize the among environmental factors that are considered when farmers plan their activities. This study uses net evapotranspiration (ETN), estimated using EPIC, as a proxy index for the physical factors considered by farmers when managing irrigation. Recent trends suggest that the probability distribution function of ETN may continue to change in the near future due to changes in the irrigation needs of crops. Also, water availability may continue to vary due to changes in the rainfall regime. The impacts of the uncertainties related to these changes on costs are evaluated using a Discrete Stochastic Programming model representing an irrigable Mediterranean area where limited water is supplied from a reservoir. In this context, adaptation to climate change can be best supported by improvements to the collective irrigation systems, rather than by measures aimed at individual farms such as those contained within the rural development policy.
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