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Dalgaard, T.; Kjeldsen, C.; Graversgard, M. |
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Review of regional scale models in the EU and methods commonly used when modelling outcomes of the implementation of the climate change mitigation policies |
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2015 |
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FACCE MACSUR Reports |
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6 |
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D-L4.1 |
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Management of Nitrogen (N) losses and the related greenhouse gas emissions is one of the most important environmental issues related to agriculture. This report shows examples of an integrated model tool, developed to quantify the N-dynamics at the complex interface between agriculture and the environment, and quantify effects of different management practices. Based on results from the EU funded research projects NitroEurope (www.NitroEurope.eu) and MEAscope (www.MEA-scope.org), examples from the quantification of farm N-losses in European agricultural landscapes are demonstrated. Applications of the dynamic whole farm model FASSET (www.FASSET.dk), and the Farm-N tool (www.farm-N.dk/FarmNTool) to calculate farm N balances, and distribute the surplus N between different types of N-losses (volatilisation, denitrification, leaching), and the related greenhouse gas emissions, show significant variation between landscapes and management practices. Moreover, significant effects of the nonlinearities, appearing when integrating over time, and scaling up from farm to landscape, are demonstrated. Finally, perspectives for stakeholder involvement is included and general recommendations for landscape level management of farm related nitrogen and greenhouse gas fluxes are made, and discussed in relation to ongoing research in the European research projects. No Label |
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MA @ admin @ |
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2110 |
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Hoffmann, H.; Ewert, F. |
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Review on scaling methods for crop models |
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2015 |
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FACCE MACSUR Reports |
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6 |
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D-C3.1 |
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Agricultural systems cover a range of organisational levels and spatial and temporal scales. To capture multi-scale problems of sustainable management in agricultural systems, Integrated assessment modelling (IAM) including crop models is often applied which require methods of scale changes (scaling methods). Scaling methods, however, are often not well understood and are therefore sources of uncertainty in models. The present report summarizes scaling methods as developed and applied in recent years (e.g. in SEAMLESS-IF and MACSUR) in a classification scheme based on Ewert et al. (2011, 2006). Scale changes refer to different spatial, temporal and functional scales with changes in extent, resolution, and coverage rate. Accordingly, there are a number of different scaling methods that can include data extrapolation, aggregation and disaggregation, sampling and nested simulation. Comparative quantitative analysis of alternative scaling methods are currently under way and covered by other reports in MACSUR and several publications (e.g. Ewert et al., 2014; Hoffmann et al., 2015; Zhao et al., 2015). The following classification of scaling methods assists to structure such analysis. Improved integration of scaling methods in IAM may help to overcome modelling limitations that are related to high data demand, complexity of models and scaling methods considered. No Label |
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MA @ admin @ |
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2094 |
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Carter, T. |
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Scenarios and related data for MACSUR2 Timothy Carter Finnish Environment |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-11 |
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Framing scenario selection (RCP/SSP)Ongoing scenario development in FP7 IMPRESSIONSSome examples of sources of data and scenarios No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2126 |
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Zander, P. |
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Scenarios of regional agricultural land use under climate change for 4 case study regions in Northern Germany |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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5 |
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Sp5-73 |
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Agricultural land use in Northern Germany is characterized by a gradient of decreasing precipitation from west to east. Climate change is expected to increase temperature and decrease summer precipitation. In the context of a nationally funded project we aim to analyze climate change adaptation strategies for agricultural land use. The research is focused in 4 study regions from Eastern to Western Germany. The presented modelling approach analyses agricultural land use under climate change and for three policy scenarios (business as usual, biodiversity and climate protection). The biodiversity and climate protection scenarios each reserve area for specific scenario objectives: 10% for specific biodiversity measures and 20% for N-fixing legumes in case of the climate protection scenario. All scenarios are executed for three time steps representing year 2010, 2020 and 2030 with a constant yield increase, extrapolated from past observations. Building on IACS data for a farm typology and expert assessments of current and future land use options, we applied a linear programming farm model. Prices are exogenous and derived from CAPRI model runs for 2020 and 2030. First preliminary results show strong impacts of price assumptions and yield assessments. This results in 2020 in lower gross margins for a number of crops and finally to higher set aside areas in eastern Germany. For 2030 input–output price relations are more favourable for farmers and thus lead to lower set aside areas. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2188 |
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Lacetera, N. |
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Season and temperature humidity index related changes of productive and health parameters in dairy cows and pigs |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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5 |
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Sp5-33 |
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The work described herein was based on construction and query of four different large databases which included multiannual (5-7 years) meteorological, productive and health data from the field. Productive data were referred to dairy cows and included milk yield and composition (total bacterial count, fat and protein percentages) whereas health data were relative both to dairy cows (milk somatic cell counts and mortality data) and pigs (mortality data during transport and at lairage). The analysis pointed out significant seasonal variations of parameters under study. In synthesis, summer/hot season was associated with significant worsening of cows’ milk composition and with significant higher risk of death in pigs. The analysis also permitted to establish the themperature humidity index values above which a significant decline of performance and health of dairy cows or pigs has to expected. These results may help to predict the consequences of climate change in economically important sectors of the livestock industry, to identify and target adaptation options that are appropriate for specific contexts and that can contribute to environmental sustainability as well as to economic development. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2148 |
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