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Ewert, F., & Rötter, R. (2014). MACSUR CropM – progress overview. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Activities in the first 1 ½ years of CropM were related to key issues identified as critical at the beginning of the FACCE MACSUR the knowledge Hub. These include: Model intercomparisonGeneration of new data for model improvementMethods for scaling and model linkingUncertainty analysisBuilding research capacity Climate scenario data for crop models The key ambition of CropM has been to develop scientific excellence on methods for a comprehensive assessment of climate change impact, adaptation and policy on European crop production, agriculture and food security. Much progress has been made in developing a first shared continental assessment and tool for: A range of important cropsImportant crop rotationsAdvanced scaling methodsAdvanced link to farm and sector modelsNovel impact uncertainty assessment and reportingState-of-the-art scenario construction A number of concrete studies towards this aim have been launched in CropM workpackages (WPs): WP1-2: Two multi-facetted studies on crop rotation, launched in summer 2013 WP3: comprehensive scaling exercises, launched in March 2013WP4: Studies on (a) Climate scenario development, (b) impact response surface method and (c) Extremes, launched in summer 2013WP5: Analysis of transect across Europe with temperature effect (Space for Time) In addition, extended activities related to capacity building including several PhD courses (WP5) workshops (in WPs1-4) and an International Symposium (10-12 Feb, Oslo, Norway) have been organized. Present and future work is and will be focused on framing and advancing crop modelling as integrated part of comprehensive climate risk assessment and modelling of agricultural systems for food security from farm to supra-national level.
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Spanna, F., Cassardo, C., Cavalletto, S., La Iacona, T., Vitali, M., & Balanzino, A. (2014). MACSUR Project – The case study of vineyards. Eco-physiological and biophysical modeling applied to the growth and productivity of vineyards in northwestern Italy. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Viticulture in Italy is one of the economically most important agricultural sectors. Recent research allows eco-physiological and biophysical models to develop tools able to provide support to the crop management, in terms of optimizing production performance and limiting environmental impacts. The ability to check on a daily basis the activities of vegetative and productive phases of vines is certainly a fundamental tool for the vineyard organization and management, and for linking the trends of growth and productivity with the quality of the final product: the wine. Since some years, some researches are taking place in the vineyards of northwestern Italy, with the aim of modeling the eco-physiological behavior of the vines, using and valorizing all available historical field data related to the vegetative and productive behavior of the vines, as well as laboratory qualitative data. At the same time, our team is evaluating two different modeling approaches: one biophysical, using the land surface scheme UTOPIA (University of TOrino land Process Interaction in Atmosphere), and another one eco-physiological. The case-study vineyards, referred to the northwestern Italian territory, is part of a wider working program involving several integrated teams from Italy, Spain and Germany. The objectives are: to improve the use of the models used by different groups; to compare the results obtained by different modeling tools; to create a common database of field measurements; to study the relationships between vegetative-productive behaviors and quality of productions.
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Curnel, Y. R. W. (2014). Meteorological risks as drivers of environmental innovation in agro-ecosystem management. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The extreme weather events, projected to increase both in frequency and magnitude with climate change have significant impact on agro-ecosystem services and pose severe limitations to sustainable agricultural land management. The proposed activities start from the hypothesis that these meteorological risks act as drivers of environmental innovation in agro-ecosystem management. These activities deal with risks associated with extreme weather phenomena and with risks of biological origin (e.g. pests and diseases). In order to reach this objective, the following elements of the chain of risk should be considered: • Hazard (assessment of the likely frequency and magnitude of extreme meteorological events)• Impact (analysis of the potential bio-physical and socio-economic impact of extreme weather events on agro-ecosystems)• Vulnerability (identification of the most vulnerable agro-ecosystems)• Risk Management (uncovering innovative risk management and adaptation options)These activities will concentrate on promoting a robust and flexible framework by demonstrating its performance across Belgian agro-ecosystems, and by ensuring its relevance to policy makers and practitioners. Impacts developed from physically based models will not only provide information on the state of the damage at any given time, but also assist in understanding the links between different factors causing damage and determining bio-physical vulnerability. Socio-economic impacts will enlarge the basis for vulnerability mapping, risk management and adaptation options. A strong expert and end-user network will be established to help exploiting project results to meet user needs
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Dalgaard, T., Hutchings, N., & Noe, E. (2014). Methods for regional scale farming systems modelling and uncertainty assessment – sustainability assessment case studies of production, nutrient losses and greenhouse gas emissions from grassland based systems. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: In the EU Joint-Programming-Initiative: Modelling European Agriculturewith Climate Change for Food Security (MACSUR, LiveM: http://www.macsur.eu/index.php/livestock-modelling) we develop a research frameworkfor the modelling and sustainability assessment of livestock and grasslandbased farming systems at farm and regional scales.Based on results from related research and model development in Denmark,methodologies used for regional scaling, the description of data requirementsand sources, and methods to predict the effect and effectiveness of climate-and environment related policy measures are developed. In this study we present results from farm modelling in a study areaaround Viborg, Western Denmark using the http://www.Farm-N.dk/ model (Env.Pol. 159 3183-3192), including thedistribution of N-surpluses into different types of losses, and a comparisonwith empirical studies of farm nitrogen balances in the Danish study and fiveadditional European landscapes (Biogeosciences 9, 5303–5321). Based on this,methods and development needs for the mapping and uncertainty assessment ofnutrient losses and greenhouse gas emissions are discussed, referring to the presentdevelopment of the Farm-AC model and ongoing scenario studies in e.g. the www.dNmark.org project. In these scenarios, regional-scale policy measures areimplemented via the responses of a range of stakeholders, such as farmers,public interest groups, regulators and politicians. When modelling the outcomeof the policy measures implementation, it is often assumed that stakeholdersrespond as economically rational entities. However, social and cultural factorsare also known to play a role and modelling methods that permit these factorsto be taken into account will also be discussed.
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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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