ANNUAL REPORT 2025
Socio-ecological analysis and models for digital twin ocean (SEADITO)
SEADITO is a project focused on the development of analytical methods and tools aimed at supporting the deployment of the EU Digital Twin Ocean (DTO), by integrating socio-ecological models to create a comprehensive decision support platform.
1. CHALLENGE
In response to the growing pressures from the increased use of maritime spaces, the need for an approach that considers the interaction of multiple disciplines, such as ecological and economic perspectives, without ignoring the human component, becomes key. SEADITO seeks to strengthen the transdisciplinary capabilities of socio-ecological models by updating and integrating them to improve Ecosystem-based Management. To this end, case studies are developed in the Baltic Sea, the North Sea and the Mediterranean, in addition to a pan-European case study on which IHCantabria focuses its contribution. These studies provide the context for multi-stakeholder participatory processes aimed at identifying community needs.
2. SOLUTION
SEADITO integrates the knowledge of multiple actors and sectors, from conventional fisheries to governance and the scientific community, using open data at the European scale. These data have been processed and homogenized to build an index for an integrated understanding of the social, ecological and economic effects of activities such as fishing, offshore wind energy development or aquaculture, as well as their interaction with climate change. This approach allows us to analyze holistically and based on quantitative data how coastal communities will be affected.
3. RESULTS
The project generated a set of interoperable, spatially explicit, DTO-compatible components for socio-ecological decision support. Outputs include scalable, multi-level models, integrated quantitative and qualitative indicators, and workflows that incorporate cultural and behavioral aspects. The components will be available on an interactive spatial platform, the SEADITO Explorer, which will feature visual applications of socio-ecological models and the option to study multiple future scenarios. In addition, training materials will be developed for researchers, decision-makers and the general public.
Funded by:
Funded by the European Union under the Grant Agreement 101157243. The views expressed are solely those of the author(s) and do not necessarily reflect those of the European Union or CINEA. Neither the European Union nor the funding entity can be held responsible for them.
More information about this project, through the following link
Project partners:
