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König, H. J., Helming, K., Seddaiu, G., Kipling, R., Köchy, M., Graversgaard, M., et al. Stakeholder participation in agricultural research: Who should be involved, why, and how?.
Abstract: Research in sustainable agricultural management requires appropriate participatory processes and tools enabling efficient dialogue and cooperation to allow researchers and stakeholders to co-produce knowledge. Research approaches that encourage stakeholder participation are in high demand because they allow a better understanding of human-nature interactions and interdependencies between actors. Participatory approaches also support multiple goals of agricultural management: improved productivity, food security, climate change adaptation, environmental conservation, rural development and policy decision making. Approaches to stakeholder engagement in the field of agricultural management research are manifold. Therefore, selecting the “right” approach depends on the specific purpose and contextualized issues at stake. We analyzed ten stakeholder approaches and propose a new framework with which to identify and select appropriate approaches for stakeholder engagement. The framework consists of three components: whom to engage (i.e., stakeholder type and mandate), why to engage (i.e., research purpose: consult, inform, collaborate), and how to engage (i.e., different methodological approaches). We identified different stakeholder groups (who?): farmers, agricultural actors, land users, and policymakers; different purposes (why?): facilitate engagement process, inform stakeholders, and obtain stakeholder perceptions; and different types of engagement methods (how?): participatory field experiments, desk simulations, interviews, panel discussions and different types of workshops. The framework was applied to arrange these approaches, organize them to improve understanding of their main strengths, weaknesses and supports for identifying and selecting an appropriate approach. We conclude that understanding the different facets of available approaches is crucial for selecting an appropriate stakeholder engagement approach. ;
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Kipling, R. P., Bannink, A., Bellocchi, G., Dalgaard, T., Fox, N. J., Hutchings, N. J., et al. (2016). Modeling European ruminant production systems: Facing the challenges of climate change. Agricultural Systems, 147, 24–37.
Abstract: Ruminant production systems are important producers of food, support rural communities and culture, and help to maintain a range of ecosystem services including the sequestering of carbon in grassland soils. However, these systems also contribute significantly to climate change through greenhouse gas (GHG) emissions, while intensi- fication of production has driven biodiversity and nutrient loss, and soil degradation. Modeling can offer insights into the complexity underlying the relationships between climate change, management and policy choices, food production, and the maintenance of ecosystem services. This paper 1) provides an overview of how ruminant systems modeling supports the efforts of stakeholders and policymakers to predict, mitigate and adapt to climate change and 2) provides ideas for enhancing modeling to fulfil this role. Many grassland models can predict plant growth, yield and GHG emissions from mono-specific swards, but modeling multi-species swards, grassland quality and the impact of management changes requires further development. Current livestock models provide a good basis for predicting animal production; linking these with models of animal health and disease is a prior- ity. Farm-scale modeling provides tools for policymakers to predict the emissions of GHG and other pollutants from livestock farms, and to support the management decisions of farmers from environmental and economic standpoints. Other models focus on how policy and associated management changes affect a range of economic and environmental variables at regional, national and European scales. Models at larger scales generally utilise more empirical approaches than those applied at animal, field and farm-scales and include assumptions which may not be valid under climate change conditions. It is therefore important to continue to develop more realistic representations of processes in regional and global models, using the understanding gained from finer-scale modeling. An iterative process of model development, in which lessons learnt from mechanistic models are ap- plied to develop ‘smart’ empirical modeling, may overcome the trade-off between complexity and usability. De- veloping the modeling capacity to tackle the complex challenges related to climate change, is reliant on closer links between modelers and experimental researchers, and also requires knowledge-sharing and increasing technical compatibility across modeling disciplines. Stakeholder engagement throughout the process of model development and application is vital for the creation of relevant models, and important in reducing problems re- lated to the interpretation of modeling outcomes. Enabling modeling to meet the demands of policymakers and other stakeholders under climate change will require collaboration within adequately-resourced, long-term inter-disciplinary research networks
Keywords: Food security; Livestock systems; Modeling; Pastoral systems; Policy support; Ruminants
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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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Kjeldsen, C., Sørensen, A. - M. L., Dalgaard, T., & Graversgard, M. (2015). 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 (Vol. 6).
Abstract: 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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de Visser, C., Schoorlemmer, H., Golaszewski, J., Olba-Ziety, E., Stolarski, M., Brodzinski, Z., et al. (2013). Agenda for Transnational Co-operation on energy efficiency in agriculture. Wageningen.
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