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Author Dono, G.; Cortignani, R.; Dell’Unto, D.; Deligios, P.; Doro, L.; Lacetera, N.; Mula, L.; Pasqui, M.; Quaresima, S.; Vitali, A.; Roggero, P.P.
Title Winners and losers from climate change in agriculture: Insights from a case study in the Mediterranean basin Type Journal Article
Year 2016 Publication Agricultural Systems Abbreviated Journal Agricultural Systems
Volume (down) 147 Issue Pages 65-75
Keywords Adaptation of farms to CC; Mediterranean region; Discrete Stochastic Programming; Regional Atmospheric Modelling System; Crop models; Livestock models
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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Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0308521x ISBN Medium Article
Area Expedition Conference
Notes CropM, LiveM, TradeM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4756
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Author Nguyen, T.P.L.; Seddaiu, G.; Virdis, S.G.P.; Tidore, C.; Pasqui, M.; Roggero, P.P.
Title Perceiving to learn or learning to perceive? Understanding farmers’ perceptions and adaptation to climate uncertainties Type Journal Article
Year 2016 Publication Agricultural Systems Abbreviated Journal Agricultural Systems
Volume (down) 143 Issue Pages 205-216
Keywords climate variability; socio-cognitive learning process; adaptation strategies; mediterranean agricultural systems; agricultural land-use; adaptive capacity; farming systems; variability; knowledge; risk; drought; africa; future; rain
Abstract Perception not only shapes knowledge but knowledge also shapes perception. Humans adapt to the natural world through a process of learning in which they interpret their sensory impressions in order to give meaning to their environment and act accordingly. In this research, we examined how farmers’ decision making is shaped in the context of changing climate. Using empirical data (face-to-face semi-structured interviews and questionnaires) on four Mediterranean farming systems from a case study located in Oristano (Sardinia, Italy) we sought to understand farmers’ perception of climate change and their behaviors in adjustment of farming practices. We found different perceptions among farmer groups were mainly associated with the different socio-cultural and institutional settings and perceived relationships between climate factors and impacts on each farming systems. The research findings on different perceptions among farmer groups can help to understand farmers’ current choices and attitudes of adaptation for supporting the development of appropriate adaptation strategies. In addition, the knowledge of socio-cultural and economic factors that lead to biases in climate perceptions can help to integrate climate communication into adaptation research for making sense of climate impacts and responses at farm level.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0308-521x ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4707
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Author 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 (down) 117 Issue 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
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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Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0308521x ISBN Medium Article
Area Expedition Conference
Notes CropM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 4489
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Author Ferrise, R.; Toscano, P.; Pasqui, M.; Moriondo, M.; Primicerio, J.; Semenov, M.A.; Bindi, M.
Title Monthly-to-seasonal predictions of durum wheat yield over the Mediterranean Basin Type Journal Article
Year 2015 Publication Climate Research Abbreviated Journal Clim. Res.
Volume (down) 65 Issue Pages 7-21
Keywords yield predictions; seasonal forecasts; analogue forecasts; stochastic weather generator; empirical forecasting models; durum wheat; crop modelling; mediterranean basin; general-circulation model; scale climate indexes; crop yield; grain-yield; forecasts; simulation; region; precipitation; australia; europe
Abstract Uncertainty in weather conditions for the forthcoming growing season influences farmers’ decisions, based on their experience of the past climate, regarding the reduction of agricultural risk. Early within-season predictions of grain yield can represent a great opportunity for farmers to improve their management decisions and potentially increase yield and reduce potential risk. This study assessed 3 methods of within-season predictions of durum wheat yield at 10 sites across the Mediterranean Basin. To assess the value of within-season predictions, the model SiriusQuality2 was used to calculate wheat yields over a 9 yr period. Initially, the model was run with observed daily weather to obtain the reference yields. Then, yield predictions were calculated at a monthly time step, starting from 6 mo before harvest, by feeding the model with observed weather from the beginning of the growing season until a specific date and then with synthetic weather constructed using the 3 methods, historical, analogue or empirical, until the end of the growing season. The results showed that it is possible to predict durum wheat yield over the Mediterranean Basin with an accuracy of normalized root means squared error of <20%, from 5 to 6 mo earlier for the historical and empirical methods and 3 mo earlier for the analogue method. Overall, the historical method performed better than the others. Nonetheless, the analogue and empirical methods provided better estimations for low-yielding and high-yielding years, thus indicating great potential to provide more accurate predictions for years that deviate from average conditions.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0936-577x 1616-1572 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4696
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Author Dono, G.; Cortignani, R.; Doro, L.; Giraldo, L.; Ledda, L.; Pasqui, M.; Roggero, P.P.
Title An integrated assessment of the impacts of changing climate variability on agricultural productivity and profitability in an irrigated Mediterranean catchment Type Journal Article
Year 2013 Publication Water Resource Management Abbreviated Journal Water Resource Manage.
Volume (down) 27 Issue 10 Pages 3607-3622
Keywords discrete stochastic programming; climate change variability; adaptation to climate change; net evapotranspiration and irrigation requirements; water availability; epic crops model; economic impact of climate change; precipitation; uncertainty; region; series; yield; model; scale; wheat; gis
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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Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0920-4741 ISBN Medium Article
Area Expedition Conference
Notes TradeM Approved no
Call Number MA @ admin @ Serial 4487
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