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| Author |
Kjeldsen, C.; Sørensen, A.-M.L.; Dalgaard, T.; Graversgard, M. |
| Title |
Report on cross-cutting approaches for the assessment of climate change adaption on selected EU sites or hotspots and potentials for adaption and mitigation in the dairy sector |
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Report |
| Year |
2015 |
Publication |
FACCE MACSUR Reports |
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6 |
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D-L4.3 |
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Adaption to climate change in the context of agriculture involves collaborative planning and development of practices which is deemed more sustainable than preceeding practices. It is however not given that sustainable development will be the outcome of such efforts. In some cases, even motivated participants experience that despite good intentions, high levels of knowledge, feasible models, appropriate technologies and many other factors present, they still might not succeed bringing about the desired change. The reasons for this can not easily be reduced to just one factor, but is very likely to be the outcome of highly complex interactions between social, technological, institutional, or even personal factors. The report documents attempts to understand the complexities of climate change adaption in a Danish water catchment, Lundgaards Bæk, which is dominated by dairy farming. As part of the EU projects AQUARIUS and MACSUR, a local action group was formed which was composed of local farmers, local agricultural advisors, advisors from the national agricultural advisory service, environmental planners from the local municipality, and environmental planners from the national environmental agency in Denmark. The action group was supposed to develop specific measures, which were supposed to lead to an overall reduction in nitrogen loading of the neighboring fjord, Mariager Fjord. The report addresses three related research themes: (1) how do the stakeholders in question interact during the process of climate change adaption, (2) when do the stakeholders encounter opportunities and barriers during the process, and finally (3) does the adaption process in question lead to the desired outcomes? The empirical background of the report is a detailed process study of dynamics within a group of stakeholders, including farmers and extension officers, who were supposed to develop sustainable management practices in order to reduce nitrogen leaching to the Mariager Fjord. The study is based on the assumption that in order for research and policy to contribute to sustainable practices, deeper understanding of complex dynamics within stakeholder partnerships is needed. Based on a theoretical framework derived from social learning, adaptive co-management and Andrew Pickering’s notion of ‘the mangle’, different in-depth explanations to why sustainable development did not occur, are offered. One explanation concerns social-psychological dynamics of knowledge. Another explanation concerns the mechanisms by which social and material forces affect outcomes of the adaption process. The report concludes by exploring the study’s relevance in relation to policy, research and practice, followed by suggestions for further in-depth case studies and experimentation in practice. No Label |
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Christen, B.; Kjeldsen, C.; Dalgaard, T.; Martin-Ortega, J. |
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Can fuzzy cognitive mapping help in agricultural policy design and communication? |
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Journal Article |
| Year |
2015 |
Publication |
Land Use Policy |
Abbreviated Journal |
Land Use Policy |
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45 |
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64-75 |
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Agricultural policy; Agro-environmental measures; Fuzzy cognitive mapping (FCM); General Binding Rules; Stakeholder communication; Scottish agriculture |
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Highlights •Fuzzy cognitive mapping (FCM)can help to improve agricultural policy design. •We analyse the views on regulation between farmers and non-farmers. •We demonstrate the utility of FCM in disentangling reasons for non-compliance. •Non-compliance is a result of dis-alignment of views rather than unwillingness. •FCM offers a critical, reflexive approach to how a regulatory process is conceived. Agricultural environmental regulation often fails to deliver the desired effects because of farmers adopting the related measures incorrectly or not at all. This is due to several barriers to the uptake of the prescribed environmentally beneficial farm management practices, most of which have been well established by social science research. Yet it is unclear why these barriers remain so difficult to overcome despite numerous and persistent attempts at the design, communication and enforcement of related agricultural policies. This paper examines the potential of fuzzy cognitive mapping (FCM) as a tool to disentangle the underlying reasons of this persistent problem. We present the FCM methodology as adapted to the application in a Scottish case study on how environmental regulation affects farmers and farming practice and what factors are important for compliance or non-compliance with this regulation. The study compares the views of two different stakeholder groups on this matter using FCM network visualizations that were validated by interviews and a workshop session. There was a farmers group representing a typical mix of Scottish farming systems and a non-farmers group, the latter comprising professionals from the fields of design, implementation, administration, consulting on and enforcement of agricultural policies. Between the two groups, the FCM process reveals a very different perception of importance and interaction of factors and strongly suggests that the problem lies in an institutional failure rather than in a simple unwillingness of farmers to obey the rules. FCM allows for a structured process of identifying areas of conflicting perceptions, but also areas where strongly differing groups of stakeholders might be able to gain common ground. In this way, FCM can help to identify anchoring points for targeted policy development and has the potential of becoming a useful tool in agricultural policy design and communication. Our results show the utility of FCM by pointing out how Scottish environmental regulation could be altered to increase compliance with the rules and where the reasons for the identified institutional failure might be sought. |
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LiveM, ftnotmacsur |
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MA @ admin @ |
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4620 |
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Dalgaard, T. |
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LiveM WP4: 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 |
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2014 |
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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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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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5097 |
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Dalgaard, T.; Hutchings, N.; Noe, E. |
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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 |
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Conference Article |
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2014 |
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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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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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5102 |
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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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Report |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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6 |
Issue |
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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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