Abstract: Stakeholder engagement in research projects can take a number of forms according to the scope of the project and the purpose of the interaction. L4.2. has focused on comparing different approaches to stakeholder engagement in collaborative projects. This report presents a synthesis of the experiences and lessons learnt through the stakeholder engagement activities of LiveM researchers within MACSUR, within an Italian (Oristano) case study, and within the SOLID (Sustainable, Organic and Low Input Dairying) project. An overview of these examples, and some of the lessons drawn from them, can also be found in the MACSUR paper on stakeholder engagement methods being developed by researchers from all three MACSUR themes (Koenig et al. under production). The first part of this report describes the stakeholder engagement strategy within the SOLID project. Stakeholder engagement methods are analysed through observations of activities and using semi-structured interviews with researchers and stakeholders. Two aspects of the SOLID approach are described – the stakeholder panel and the Future Dairying workshop. Transcripts of the workshop and the contribution of the stakeholder panel to the SOLID annual meeting in Helsinki are included (Appendices 1 and 2), as a contribution to the analysis of workshop outcomes being undertaken within the SOLID project. As part of a wider suite of stakeholder engagement activities, the SOLID stakeholder panel provided an example of how ongoing oversight of scientific outputs and direction by stakeholders can be effective in identifying weaknesses in approach and communication, and in suggesting relevant and effective directions for research activities. The stakeholder workshop demonstrated a useful structure for the exploration of stakeholder concerns, their view of ideal states and their solutions for reaching them. Low participation levels demonstrated the need to understand the motivations that drive stakeholders to engage in such projects, and highlighted the value of developing long-term relationships between stakeholders and researchers that allow scientific research to become an accepted part of practical problem-solving. The second part of the report describes stakeholder engagement activities carried out in the context of one of the MACSUR regional pilot studies (Oristanese case study in Sardinia, Italy). The Oristanese case study demonstrates the potentialities and constraints of participatory methodologies in relation to the different categories of stakeholder involved. It highlights the importance of creating new spaces for dialogue between farmers, researchers and policy makers in order to promote the generation of “hybrid knowledge” (Nguyen et al. 2013) for the emergence of more sustainable and longer-lasting strategies to adapt to CC. This would require the promotion of open knowledge generation platforms where multiple stakeholders are encouraged to participate and make their views heard. These approaches are designed in order to overcome the misalignment between scientists’ suggestions and policy implementation. In the third part of the report, the outcomes of a “learning event” held in Sassari (MACSUR mid-term meeting) with decision makers from different EU countries, are discussed. Finally, some reflections are presented on the importance of involving local stakeholders and decision makers in research projects, of sharing views and knowledge between scientists and stakeholders, and on the pros and cons of different methodologies at the different scales of stakeholder engagement, drawing on all three examples of practice. The research approach analysed includes two important components, which are represented by “transdisciplinarity” (to be included in the macro area of “scientific knowledge”) and “local knowledge”, as fundamental elements to fill the Science and Policy Gap. No Label

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

Abstract: Grassland-based ruminant production systems are integral to sustainable food production in Europe, converting plant materials indigestible to humans into nutritious food, while providing a range of environmental and cultural benefits. Climate change poses significant challenges for such systems, their productivity and the wider benefits they supply. In this context, grassland models have an important role in predicting and understanding the impacts of climate change on grassland systems, and assessing the efficacy of potential adaptation and mitigation strategies. In order to identify the key challenges for European grassland modelling under climate change, modellers and researchers from across Europe were consulted via workshop and questionnaire. Participants identified fifteen challenges and considered the current state of modelling and priorities for future research in relation to each. A review of literature was undertaken to corroborate and enrich the information provided during the horizon scanning activities. Challenges were in four categories relating to: 1) the direct and indirect effects of climate change on the sward 2) climate change effects on grassland systems outputs 3) mediation of climate change impacts by site, system and management and 4) cross-cutting methodological issues. While research priorities differed between challenges, an underlying theme was the need for accessible, shared inventories of models, approaches and data, as a resource for stakeholders and to stimulate new research. Developing grassland models to effectively support efforts to tackle climate change impacts, while increasing productivity and enhancing ecosystem services, will require engagement with stakeholders and policy-makers, as well as modellers and experimental researchers across many disciplines. The challenges and priorities identified are intended to be a resource 1) for grassland modellers and experimental researchers, to stimulate the development of new research directions and collaborative opportunities, and 2) for policy-makers involved in shaping the research agenda for European grassland modelling under climate change.