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Author Pasqui, M.; Quaresima, S.; Tomozeiu, R.; Dono, G.; Doro, L.; Cortignani, R.; Ledda, L.; Roggero, P.P. url  openurl
  Title A comprehensive climate characterization of the Oristano (Sardinia) regional pilot case study Type Conference Article
  Year 2014 Publication Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract In order to assess probability distributions of critical response variables in a full crop modelling system, a complete climate characterization has been implemented to identify principal variability components in the Oristano (Sardinia) regional pilot study area with a particular emphasis on current vs near future climate.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title FACCE MACSUR Mid-term Scientific Conference  
  Series Volume (down) 3(S) Sassari, Italy Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy  
  Notes Approved no  
  Call Number MA @ admin @ Serial 5046  
Permanent link to this record
 

 
Author Roggero, P.P.; Seddaiu, G.; Ledda, L.; Doro, L.; Deligios, P.; Nguyen, T.P.L.; Pasqui, M.; Quaresima, S.; Lacetera, N.; Cortignani, R.; Dono, G. url  openurl
  Title Combining modeling and stakeholder involvement to build community adaptive responses to climate change in a Mediterranean agricultural district Type Conference Article
  Year 2014 Publication Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  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.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title FACCE MACSUR Mid-term Scientific Conference  
  Series Volume (down) 3(S) Sassari, Italy Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy  
  Notes Approved no  
  Call Number MA @ admin @ Serial 5065  
Permanent link to this record
 

 
Author Dono, G.; Cortignani, R.; Doro, L.; Roggero, P.P. url  openurl
  Title The adaptation of farm and awareness of ongoing climate change (CC) Type Conference Article
  Year 2014 Publication Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Farm planning is based on awareness of climate variability, here assumed to depend on experience gained over the years, and to generate expectations on climatic variables. Expectations are based on probability distributions (pdfs) estimated on climate data and used to generate managing choices by means of Discrete Stochastic Programming. The model simulates the income losses in case farmers do not recognize the ongoing CC, and continue to plan assuming climate stability. In particular, the use of resources in 2010 is simulated based on the pdfs of the early 2000s, despite CC has changed the probabilities of the various states of nature. The model, calibrated with Positive Mathematical Programming, generates a 0.9% income increase when is allowed to adapt to 2010 climate pdfs. The model is also calibrated according to pdfs of 2010, i.e. recognizing CC: in this case income falls of 0.7% when farmers are simulated to use their soil mistakenly based of the 2000 pdfs. Given the short period of CC, the differences represent an appreciable error that farmers may be already committing. Properly specifying with the CC at local level can help building farmers’ awareness on it, and to properly manage their resources, recovering profitability.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title FACCE MACSUR Mid-term Scientific Conference  
  Series Volume (down) 3(S) Sassari, Italy Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy  
  Notes Approved no  
  Call Number MA @ admin @ Serial 5131  
Permanent link to this record
 

 
Author Cortignani, R.; Dono, G. url  doi
openurl 
  Title Simulation of the impact of greening measures in an agricultural area of the southern Italy Type Journal Article
  Year 2015 Publication Land Use Policy Abbreviated Journal Land Use Policy  
  Volume 48 Issue Pages 525-533  
  Keywords agricultural policy; supply analysis; mathematical programming; maximum-entropy; level; models  
  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.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume (down) Series Issue Edition  
  ISSN 0264-8377 ISBN Medium Article  
  Area Expedition Conference  
  Notes TradeM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4746  
Permanent link to this record
 

 
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. url  doi
openurl 
  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 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.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume (down) 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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