This project will look at the relationship between governance, power and knowledge structures and how these influence behaviour, actions and decision taking for sustainable ecosystems. It will link several social science techniques (e.g. social network analysis and agent-based modelling) to comprehensively map all relevant social and ecological knowledge flows regarding ecosystems in two substantive areas where there is pressure on ecosystem services. With our local partners, we will look at two cases in the western Indian Ocean (Kenya) and the Bay of Bengal (Bangladesh) regarding coastal zone resource uses and management. The purpose is to generate more generic data across comparative studies about how decisions for policy and for action are taken at local levels. We will look at the networks that individuals use to help them make decisions regarding their livelihoods. These will be understood within the context of the global economy and other decision networks impacting upon the social-ecological interrelationships at the local level. Our own understanding will be framed within the literature around social-ecological complexity and complex adaptive management. The project will substantively focus on strengthening the sustainable management of coastal ecosystems with a process focus on the political economy for poverty reduction and to understand better how livelihoods can be maintained and ecosystem services valued and preserved. The project is asking for funds for two UK partners (The University of York and the Stockholm Environment Institute, Oxford) to work with six partners in Bangladesh and in Kenya in close collaboration with policy makers and practitioners there in order to develop an understanding of sustainable norms for decision making in the use of coastal ecosystem services for poverty reduction. Put most simply, we are going to talk to relevant people in Kenya and Bangladesh to see where and from whom they get information, about what, and present this as a knowledge network map. We will then work with those stakeholders to see if it is the right information for their needs (i.e. to make the decisions that they need to make). We will deepen our and their understanding of what needs to happen by the use of agent based models of the systems. This will also bring together the social understanding of the milieu within which information is passed around and used with a more technical analysis of that information itself and its utility. Our work tasks are mapped to the knowledge gaps identified in the ESPA call (page 7). However, we propose that degradation and sustainability drivers should be considered as a part of the same complex system. Little is known about the way in which multiple drivers interact, feedback upon, or balance each other so it is currently very difficult to attribute individual drivers to patterns of degradation or sustainability. To capture this complexity we propose 4 tasks: A) Investigate multiple drivers across a range of disciplines (biophysical, social, political and economic). B) Map the horizontal and vertical networks and knowledge diffusion patterns. C) Use socio-ecological models to analyse and model interactions among drivers. D) Reflectively link the impact of the WD-NACE project (see also Impact Plan). Our chosen criteria of success will be by means of an assessment of post-workshop feedback, but we shall also agree a criterion of success with each research collaborator and with our partner organisation. These criteria can then be used as the touchstone of impact. It is an expected outcome of WD-NACE that the conceptual framework linking ecosystem and livelihoods domains, knowledge networks and decision-making structures will be developed and improved. In developing such a model, we would expect that it could be applied to a range of settings such as by policy-making institutions and international development organizations as well as by more local users.

The FAIR2Adapt is a multidisciplinary project geared towards transforming data into actionable knowledge to shape climate adaptation strategies. By leveraging and collaborating with EOSC, we fully tap into the EOSC's wide range of services, the FAIR Implementation Framework Catalogue of Resources, and align with the EOSC interoperability framework. We adopt FAIR Digital Objects (FDOs) by using RO-Crate and nanopublications as key implementation tools. We use semantic bridging strategies, such as the I-ADOPT framework, and tailored FDO services to build a collaborative, user-friendly FAIR and open data sharing framework. Rich case studies will co-develop FAIR Supporting Resources in alignment with the FAIRification framework and demonstrate the impact of FAIR and open data sharing on climate change adaptation, and strategically support the EU Mission’s objective of enhancing climate resilience in European regions and communities. Through transfer cases and collaboration with other initiatives, FAIR2Adapt extends its reach to additional contexts, showcasing its scalability, sustainability and applicability beyond the project’s completion. A significant aspect of the FAIR2Adapt project is stakeholder engagement and capacity-building activities, which will be instrumental in raising awareness and devising customised solutions. By transforming data into flexible, practical, and resilient climate adaptation strategies, FAIR2Adapt constructs a scalable and extensible model for data sharing that can be adapted to multiple climate adaptation scenarios. The impact of FAIR2Adapt will span across scientific advancement, economic resilience, social-environmental wellbeing, and responsive policy development, fostering multidisciplinary cooperation, enhancing trust in science, and stimulating a climate-smart economy. Ultimately, FAIR2Adapt intends to build a more resilient, inclusive and knowledge-based society capable of efficiently tackling the challenges of climate change.