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1000 Titel
  • Combining modeling and stakeholder involvement to build community adaptive responses to climate change in a Mediterranean agricultural district
1000 Autor/in
  1. Roggero, Pier Paolo |
  2. Seddaiu, Giovanna |
  3. Ledda, Luigi |
  4. DORO, Luca |
  5. deligios, paola |
  6. Nguyen, Thi Phuoc Lai |
  7. Pasqui, Massimiliano |
  8. Quaresima, Sara |
  9. Lacetera, Nicola |
  10. Cortignani, Raffaele |
  11. Dono, Gabriele |
1000 Erscheinungsjahr 2014
1000 Publikationstyp
  1. Kongressschrift |
  2. Artikel |
1000 Online veröffentlicht
  • 2014-06-27
1000 Erschienen in
1000 Quellenangabe
  • 3(Supplement):CP3-2
1000 Übergeordneter Kongress
1000 Copyrightjahr
  • 2015
1000 Verlagsversion
  • https://ojs.macsur.eu/index.php/Reports/article/view/CP3-2 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • 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.
1000 Fächerklassifikation (DDC)
1000 DOI 10.4126/FRL01-006413944 |
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0002-7269-4334|https://orcid.org/0000-0001-6043-1134|https://orcid.org/0000-0001-5337-5701|https://orcid.org/0000-0003-1404-2255|https://orcid.org/0000-0001-9724-2812|https://frl.publisso.de/adhoc/creator/Tmd1eWVuLCBUaGkgUGh1b2MgTGFp|https://orcid.org/0000-0002-0926-362X|https://frl.publisso.de/adhoc/creator/UXVhcmVzaW1hLCBTYXJh|https://orcid.org/0000-0003-2088-2744|https://orcid.org/0000-0002-2685-9783|https://orcid.org/0000-0002-0272-178X
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1000 @id frl:6413944.rdf
1000 Erstellt am 2019-04-11T14:23:50.004+0200
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1000 Bearbeitet von 218
1000 Zuletzt bearbeitet Thu Jan 30 22:29:37 CET 2020
1000 Objekt bearb. Wed Jun 26 13:40:45 CEST 2019
1000 Vgl. frl:6413944
1000 Oai Id
  1. oai:frl.publisso.de:frl:6413944 |
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