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Nguyen, T.P.L.; Seddaiu, G.; Tidore, C.; Roggero, P.P. |
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Title |
Adaptation to climate change of Italian agricultural systems: the analysis of explorative scenarios |
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Conference Article |
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2014 |
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Adaptation of agricultural systems to climate uncertainties requires the construction of scenarios that should take into account the complexities of socio-ecological systems of a specific local context. Adaptation scenarios of agricultural systems are not making forecasts or predictions, but prospective futures or future paths. They can facilitate our understanding of how systems work and evolve. Adaptation processes of agricultural systems involve a variety of changes in local practices and social organization. The development of adaptation scenarios at farm level entails a clear understanding of farmers’ frames that are mediated by their interests, experiences and internal and external forces. Farmers’ frames is the way in which farmers frame climate issues emphasizing vulnerabilities, uncertainties and opportunities (i.e: impacts on their farming systems) and open the window for searching adaptation strategies. This study reports on the methodologies for the development of explorative scenarios (i.e., scenarios that explore the future from a variety of perspectives) for the climate change adaptation of four agricultural systems (intensive dairy cattle, extensive dairy sheep, rice farming and horticulture) in the Oristano regional pilot study in Italy. Explorative scenarios were used to explore trends into the future from the past and present. Three research steps were followed: (i) in the first step farmers’ perceptions and prospective through semi-structured interviews and questionnaires were analysed; (ii) in the second step the evolution of the agricultural systems (i.e. temporal and spatial) was evaluated; (iii) the third step examined multiple stakeholders’ outlooks about farm-level possible adaptive strategies through interactive workshops. |
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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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MA @ admin @ |
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5050 |
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Roggero, P.P.; Pulina, A.; Baldoni, G.; Basso, B.; Berti, A.; Orlandini, S.; Danuso, F.; Pasqui, M.; Toderi, M.; Mazzoncini, M.; Grignani, C.; Tei, F.; Ventrella, D. |
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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 |
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2014 |
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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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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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MA @ admin @ |
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5086 |
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Leolini, L.; Moriondo, M.; De Cortazar-Atauri, I.; Ruiz-Ramos, M.; Nendel, C.; Roggero, P.P.; Spanna, F.; Ramos, M.C.; Costafreda-Aumedes, S.; Ferrise, R.; Bindi, M. |
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Modelling different cropping systems |
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2017 |
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FACCE MACSUR Reports |
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10 |
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C1.4-D |
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Grapevine is a worldwide valuable crop characterized by a high economic importance for the production of high quality wines. However, the impact of climate change on the narrow climate niches in which grapevine is currently cultivated constitute a great risk for future suitability of grapevine. In this context, grape simulation models are considered promising tools for their contribution to investigate plant behavior in different environments. In this study, six models developed for simulating grapevine growth and development were tested by focusing on their performances in simulating main grapevine processes under two calibration levels: minimum and full calibration. This would help to evaluate major limitations/strength points of these models, especially in the view of their application to climate change impact and adaptation assessments. Preliminary results from two models (GrapeModel and STICS) showed contrasting abilities in reproducing the observed data depending on the site, the year and the target variable considered. These results suggest that a limited dataset for model calibration would lead to poor simulation outputs. However, a more complete interpretation and detailed analysis of the results will be provided when considering the other models simulations. |
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CropM |
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MA @ admin @ |
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5033 |
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Kersebaum, K.-C.; Wallor, E.; Ventrella, D.; Cammarano, D.; Choucheney, E.; Ewert, F.; Ferrise, R.; Gaiser, T.; Garofalo, P.; Giglio, L.; Giola, P.; Hoffmann, M.; Laan, M.; Lewan, E.; Maharjan, G.R.; Moriondo, M.; Mula, L.; Nendel, C.; Pohankova, E.; Roggero, P.P.; Trnka, M.; Trombi, G. |
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Comparison of site sensitivity of crop models using spatially variable field data from Precision Agriculture |
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2017 |
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FACCE MACSUR Reports |
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10 |
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C1.1-D2 |
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Site conditions and soil properties have a strong influence on impacts of climate change on crop production. Vulnerability of crop production to changing climate conditions is highly determined by the ability of the site to buffer periods of adverse climatic situations like water scarcity or excessive rainfall. Therefore, the capability of models to reflect crop responses and water and nutrient dynamics under different site conditions is essential to assess climate impact even on a regional scale. To test and improve sensitivity of models to various site properties such as soil variability and hydrological boundary conditions, spatial variable data sets from precision farming of two fields in Germany and Italy were provided to modellers. For the German 20 ha field soil and management data for 60 grid points for 3 years (2 years wheat, 1 year triticale) were provided. For the Italian field (12 ha) information for 100 grid points were available for three growing seasons of durum wheat. Modellers were asked to run their models using a) the model specific procedure to estimate soil hydraulic properties from texture using their standard procedure and use in step b) fixed values for field capacity and wilting point derived from soil taxonomy. Only the phenology and crop yield of one grid point provided for a basic calibration. In step c) information for all grid points of the first year (yield, soil water and mineral N content for Germany, yield, biomass and LAI for Italy) were provided. First results of five out of twelve participating models are compared against measured state variables analysing their site specific response and consistency across crop and soil variables. (Main text to be published in a peer-reviewed journal) |
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CropM |
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MA @ admin @ |
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4951 |
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Pulina, A.; Bellocchi, G.; Seddaiu, G.; Roggero, P.P. |
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Scenario analysis of alternative management options on the forage production and greenhouse gas emissions in Mediterranean grasslands |
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2016 |
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116 |
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263-266 |
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LiveM; MACSUR_ACK |
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TI @ martin.koechy @ |
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2940 |
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