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Dalgaard, T., Kjeldsen, C., Meyer-Aurich, A., Özkan, S., Rolinski, S., Köchy, M., et al. (2014). Farming systems models for regional scale impact assessment in Europe – case studies of N-losses and greenhouse gas emissions..
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Dalgaard, T., Kjeldsen, C., & Graversgard, M. (2015). Review of regional scale models in the EU and methods commonly used when modelling outcomes of the implementation of the climate change mitigation policies (Vol. 6).
Abstract: 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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Christen, B., Kjeldsen, C., Dalgaard, T., & Martin-Ortega, J. (2015). Can fuzzy cognitive mapping help in agricultural policy design and communication? Land Use Policy, 45, 64–75.
Abstract: 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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