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Sinabell, F. (2014). Adaptation in Austrian cattle and milk production. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Climate change will pose considerable challenges to Austrian agriculture which will likely be affected by a higher frequency of extreme weather events and more volatile commodity prices. We want to analyse the spatial, economic and social dimension of this threat by exploring expected consequences for the most important agricultural activity in Austria, cattle and dairy farming. We will evaluate a broad bouquet of adaptation measures from both, the perspective of the single farm as well as from the agricultural policy perspective. By aligning scenarios on projections of climate conditions and socio-economic developments with those developed in the EU MACSUR project (www.macsur.eu), the results will be consistent with state of the art analyses on climate change in Europe. By integrating results from a well established life cycle analysis model that will be specified to the Austrian situation we will broaden the spectrum of existing knowledge substantially. The results will allow policy makers to base their decisions on evidence that is not limited to the Austrian situations but includes spillover effects to foreign countries as well. Farmers willbe able to benefit directly from results of this project because stakeholders from the farm sector are part of the analyses from the beginning. An additional benefit of the project is that it is closely integrated to the activities of the international network of researchers working on climate change and food security in Europe.
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Sinabell, F., & Brouwer, F. (2014). TradeM synergies with AGMIP. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The AgMIP network started activities on intercomparison of global economic modelling at a time when MACSUR was not yet established. The achievements made so far are highly relevant for TradeM and several partners (Wageningen University, IIASA, PIK, University Bonn) are in both networks. The MOU between MACSUR and AGMIP established formal links between the two projects and TradeM is activley working on establishing further collaboration. Preparations are underway to bring together researchers of both networks in a joint workshop to be held in Austria, September 2014. The topic will be on issues related to linking local and regional models with global ones. TradeM will actively contribute to the workshop and will host a one-day side-event.
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Schönhart, M. (2014). Spillovers between MACSUR and Austrian climate change research projects. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The Austrian regional case study in MACSUR extends the methods and builds upon the results of the CC-ILA project. CC-ILA enables cooperation between landscape planners and landscape ecologists to analyse mitigation and adaptation strategies for sustainable rural land use and landscape developments in a case study landscape. Subsequent research in MACSUR includes analysis towards rural development and the improvement of the climate impact data base for grasslands. The latter is achieved by collaborating with Crop-M partner LFZ Raumberg-Gumpenstein, who is able to utilize spill-overs within the Agromet-Monitor project.
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Saetnan, E. R., & Veneman, J. B. (2014). MitiGate: an On-line Meta-Analysis Database of Mitigation Strategies for Enteric Methane Emissions. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The animal science sector has seen a proliferation of potential mitigation strategies, aimed at tackling emissions from enteric fermentation in ruminant livestock production. By bringing together data from studies on the many mitigation options available through a structured meta-analytical approach, it is possible to evaluate the overall mitigation potential for these broad strategies as well as exploring the many factors influencing the potential of CH4 mitigation strategies. Such quantification of the different mitigation strategies will allow for better estimation of mitigation potential on different levels (animal, farm and sector scale) in modelling efforts. Also quantification is important to determine the strategies that show the best potential in lowering methane emissions and hence can be instrumental in policy recommendations. A database has been established through an initial extensive structured search of published literature on the topic. For each relevant paper identified, a range of meta-data have been extracted including information on the study design, mitigation strategy, animal husbandry, diet and methane emissions. By creating a database with multiple levels of moderator coding, we have provided a flexible platform for future meta-analyses at many levels of aggregation. Studies can then in future be aggregated at the level most appropriate for specific modelling or policy recommendations. This comprehensive database is being made available on-line through a user-friendly web interface. The web-site provides a facility for open access to the database, as well as future updates of the database as more research is published on the topic.
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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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