Sinabel, F., & Brouwer, F. (2014). TradeM theme progress overview. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: TradeM is one theme of MACSUR and the major focus is on enhancing existing economic models and inspiring researchers to further develop and use models and tools. After establishing an inventory of models at the beginning of the project the next stage was used to prepare for the analysis in regional pilot studies. Case studies for three regions in Europe (North, Centre, South) are used to showcase the state of the art of agricultural modelling of climate change and food security in specific regional contexts and policy environments. In parallel efforts stakeholder participation processes are initiated, learning workshops and capacity building. Moreover, steps are to develop and test new concepts on economics for use in integrated assessment approaches dealing with risk and uncertainty.
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Schönhart, M. (2014). Uncertainty analysis and management in the regional pilot case study ‘Mostviertel region. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: An integrated modelling framework (IMF) is developed to analyse impacts of climate andpolicy changes on farm welfare and the environment. The IMF is applied on two contrasting grassland (south) and cropland (north) dominated Austrian landscapes. The IMF combines the crop rotation model CropRota, the bio-physical process model EPIC and the bio-economic farm model FAMOS[space] and applies combined climate change and policy scenarios. Changing policies reduce farm gross margins by -36% and -5% in the two landscapes respectively. Climate change increases gross margins and farms can reach pre-reform levels on average. Climate induced intensification such as removing of landscape elements andincreasing fertilization can be moderated by an agri-environmental program (AEP). However, productivity gains from climate change increase the opportunity costs for AEP participation.
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Quaranta, G., & Salvia, R. (2014). Using indicators to inform agricultural decision making. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Most farmers carry out several types of activity of their land (different crops or livestock) and use a wide range of agricultural techniques. They often need to address one of the following questions. How would the economic returns from my various activities be affected by using production practices which have different effects on soil conservation or degradation? How would the economic returns from these activities change, if the product price and/or subsidies structure and/or input costs changed? ManPrAs is a tool for Agricultural Management Practices Assessment developed. It is a method, to assess the sustainability of different agricultural practices by combining their soil conservation index (SCI) with their economic results (Gross Margin-GM). It also simulates the impact of alternative crops and management techniques on soil degradation, farm profitability and other socio-economic aspects. ManPrAs is strongly user-orientated and is a powerful simulation tool for farmers and stakeholders involved in land management.
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Bellocchi, G., Martin, R., Shtiliyanova, A., Ben Touhami, H., & Carrère, P. (2014). Vul’Clim – Climate change vulnerability studies in the region Auvergne (France). FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The region Auvergne (France) is a major livestock territory in Europe (beef and dairy cattle with permanent grasslands), with a place in climate change regional studies assisting policy makers and actors in identifying adaptation and mitigation measures. Vul’Clim is a research grant (Bourse Recherche Filière) of the region Auvergne (February 2014-September 2015) to develop model-based vulnerability analysis approaches for a detailed assessment of climate change impacts at regional scale. Its main goal is the creation of a computer-aided platform for vulnerability assessment of grasslands, in interaction with stakeholders from a cluster of eco-enterprises. A modelling engine provided by the mechanistic, biogeochemical model PaSim (Pasture Simulation model) is the core of the platform. An action studies the changes of scales by varying the granularity of the data available at a given scale (e.g. climate data supplied by global scenarios) to let them being exploited at another scale (e.g. high-resolution pixels). Another action is to develop an assessment framework linking modelling tools to entry data and outputs, including a variety of components: data-entry manager at different spatial resolutions; automatic computation of indicators; gap-filling and data quality check; simulation kernel with the model(s) used; device to represent results as maps and integrated indicators.
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Zhao, G., Hoffmann, H., Van Bussel, L., Enders, A., Specka, X., Sosa, C., et al. (2014). Weather data aggregation’s effects on simulation of cropping systems: a model, production system and crop comparison. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Interactions of climate, soil and management practices in cropping systems can be simulated at different scales to provide information for decision making. Low resolution simulation need less effort, but important details could be lost through data aggregation effects (DAEs). This paper aims to provide a general method to assess the DAEs on weather data and the simulation of cropping systems, and further investigate how the DAEs vary with changing crop models, crops, variables and production systems. A 30-year continuous cropping system was simulated for winter wheat and silage maize and potential, water-limited and water-nitrogen-limited production situations. Climate data of 1 km resolution and aggregations to resolutions of 10 to 100 km was used as input for the simulations. The data aggregation narrowed the variation of weather data and DAEs increased with increasingly coarser spatial resolution, causing the loss of hot spots in simulated results. Spatial patterns were similar across different resolutions. Consistent with DAEs on weather data, the DAEs on simulated yield (0 to 1.2 t ha-1 for winter wheat and 0 to 1.7 t ha-1 for silage maize), evapotranspiration (3 to 45 mm yr-1 for winter wheat and 4 to 40 mm yr-1 for silage maize), and water use efficiency (0.02 to 0.25 kg m-3 for winter wheat and 0.04 to 0.4 kg m-3 for silage maize), increased with coarser spatial resolution. Thus, if spatial information is needed for local management decisions, higher resolution is needed to adequately capture the spatial heterogeneity or hot spots in the region.
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