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Ferrise, R., Moriondo, M., Pasqui, M., Toscano, P., Semenov, M. A., & Bindi, M. (2014). Using seasonal forecasts for predicting durum wheat yield over the Mediterranean Basin..
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Dono, G., Cortignani, R., Dell’Unto, D., Doro, L., Lacetera, N., Mula, L., et al. (2014). Productive and economic adaptation of Mediterranean agriculture to climate change (Produktive und wirtschaftliche Anpassung der mediterranen Landwirtschaft an den Klimawandel). In Jahrbuch der ÖGA (Vol. 24, pp. 213–222).
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Pasqui, M., Quaresima, S., Tomozeiu, R., Dono, G., Doro, L., Cortignani, R., et al. (2014). A comprehensive climate characterization of the Oristano (Sardinia) regional pilot case study. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
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.
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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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Roggero, P. P., Pulina, A., Baldoni, G., Basso, B., Berti, A., Orlandini, S., et al. (2014). IC-FAR: Linking Long Term Observatories with Crop Systems Modeling For a better understanding of Climate Change Impact, and Adaptation Strategies for Italian Cropping Systems. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The IC-FAR project (2013-2016), funded by the Italian ministry of University, Research and Education, aims to use datasets from 16 Italian long term agronomic experiments (LTEs) to assess the reliability of different cropping system models over a range of Mediterranean environments and cropping systems. The selected models will be used for scenario and uncertainty analyses vs near-future climate change. The LTEs are located in seven sites: Turin, Padua, Bologna, Ancona, Pisa, Perugia, Foggia. The project’s is linked to international projects such as MACSUR, AgMIP, ANAEE, ESFRI and GRA, and has model developer teams as associate partners. IC-FAR is structured in five WPs. WP1 is focused on building a common dataset and sampling protocols. The field data will be implemented in the WP2 to calibrate, validate and assess the performances of different models across Italian environments. An uncertainty analysis will be performed in relation to the model types, cropping system typologies and climate scenarios (WP3). WP4 and WP5 are focused on capacity building on modeling and on dissemination, including networking with other European LTE platforms (WP4), and to the project coordination (WP5). The next step of IC-FAR will be the design and realization of a special issue summarizing a selection of the most important results from the LTEs, that will be the starting point towards the full implementation of the data sharing policy of this project.
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