Climate change is causing species range shifts and changing species compositions, altering the trophodynamics of ecosystems. Yet, while approaches such as species distribution models can be used to project assemblage change, there is limited knowledge of the consequences for ecosystem functioning. We developed the ‘Temporal Ecological Disruption Index’ as a framework for assessing potential shifts in ecosystem functioning that are quantified over time and can be compared between ecosystems or climate scenarios. The aim is to provide a simple and easy-to-interpret index that builds on existing efforts on quantifying functional diversity and has useful properties such as comparability and interpretability. We demonstrate this index by projecting changes in species assemblages for the present-day and end-century under two climate scenarios in two protected seascape sites in eastern Canada, illustrating how species composition shifts can be translated into potential ecological disruption, and are affected by different carbon emission trajectories. The approach provides a foundation for exploring the functional consequences of species range shifts due to climate change and identifying areas at greater risk. It can be used to link projected shifts from species distribution models to potential ecological disruption, thus helping to inform efforts to build ecological resilience in a warming world.

How to cite: Irvine, A., Reygondeau, G., Stanley, R., and Tittensor, D.: The Temporal Ecological Disruption Index: Assessing climate change impacts on ecosystem functioning  , One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-128, https://doi.org/10.5194/oos2025-128, 2025.

The mesopelagic zone, located between 20-100m in depth, represents 20% of the ocean’s volume. The substantial biomass of organisms inhabiting these zones, estimated at 5-15 billion tons, has recently attracted the attention of states, raising the question of the possibility of sustainable exploitation. In the Northeast Atlantic, Maurolicus muelleri and Benthosema glaciale, the most abundant and well-studied mesopelagic fish species, stand out. Nevertheless, these species are still largely unknown, and stock assessments remain riddled with considerable uncertainties.

As part of the European H2020 MEESO project, three models were compared to better evaluate these uncertainties. This presentation will focus mainly on the SEAPODYM-LMTL (Low and Mid Trophic Levels) model. It is a spatio-temporal population dynamics model that explicitly simulates the vertical migration behaviours of mesopelagic species, grouped into six categories. Physical (temperature, current) and biogeochemical (net primary production) forcings are integrated across three layers (epipelagic, upper mesopelagic, and lower mesopelagic). The thickness of these layers is determined by the depth of the euphotic zone. Horizontal passive transport movements, as well as random water mass movements, are modelled using advection-diffusion equations. The model was adapted for Maurolicus and Benthosema by spatially restricting the recruitment zone. Maurolicus performs diel vertical migrations between the surface and the upper mesopelagic layer, while Benthosema migrates deeper, to the lower mesopelagic layer. These species are not currently exploited by any fisheries, and their stocks are considered to be at the equilibrium. Two fishing scenarios were tested: a harvest rate of 5% and 25%.

The spatial distribution of the two species remains stable over the period 1998-2022, with a total biomass of around 9.106 tons for Maurolicus and 6.5.107 tons for Benthosema. Neither exploitation scenario leads to a population collapse. Comparisons with the two other models confirm this result. However, the nearly one-order-of-magnitude difference in total biomass between models calls for great caution should exploitation be considered.

How to cite: Mérillet, L., Speirs, D., Dolmaire, E., Skogen, M., Conchon, A., Health, M., Strand, E., Titaud, O., and Vastenhoud, B.: Could harvesting mesopelagic fish be sustainable? Results from population and ecosystem models in the Northeastern Atlantic, One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-338, https://doi.org/10.5194/oos2025-338, 2025.

The SWIO 30*30 project is a social-ecological initiative focused on identifying priority marine conservation areas across the South West Indian Ocean (SWIO) region to meet the Kunming-Montreal Global Biodiversity Framework goal of protecting 30% of terrestrial and marine areas by 2030. SWIO marine ecosystems, while hosting exceptional biodiversity, face high ecological pressure from overfishing, pollution, and habitat loss. Despite these challenges, the coverage of Marine Protected Areas (MPAs) across this region remains low, with most countries far from the 30% protection target. This situation highlights the urgent need for strategic conservation planning that is tailored to SWIO’s unique ecological and socio-economic contexts. This project is built on our previous successful Peru 30*30 project, which provided promising results for expanding Peruvian protected areas through a combination of scientific methods and local stakeholder engagement. The current objective is to provide a framework for conservation planning in SWIO marine areas (for Madagascar, Mozambique, Mayotte, Reunion, Comoros) that not only promotes biodiversity but also enhances ecosystem services essential for local communities, such as carbon storage, food provision, and cultural values. To answer the project’s core research questions—namely, identifying priority areas for marine conservation and understanding how to balance various conservation factors—the SWIO 30*30 project adopts a transdisciplinary approach that involves three main methodological components. First, it integrates diverse data, combining information on biodiversity, ecosystem services, and socio-economic factors. These data can be sourced from both space/in situ earth observation agencies (e.g. ESA, CNES) and environmental marine monitoring programs (e.g. CMEMS Copernicus), ensuring that the conservation planning process is informed by high-quality, contextually relevant data. Second, it applies advanced artificial intelligence techniques, including mathematical optimization methods, to address the multi-objective complexity of marine conservation planning. These AI tools allow for more sophisticated prioritization of conservation areas by handling the high combinatorial demands of multi-factor decisions. Third, the project follows a stakeholder co-production model, involving local communities and decision-makers throughout the process. This collaboration increases the transparency, acceptance, and practical utility of conservation recommendations, improving the chances that the proposed MPAs will be adopted and managed effectively at the national level. To adapt conservation strategies to the specific regional needs, the project evaluates four different scenarios: (1) a Biodiversity scenario, focused solely on preserving biodiversity; (2) a Socio-ecological scenario that adds ecosystem services such as carbon storage, food provision, and cultural values; (3) a Pragmatic scenario that incorporates human impacts (e.g., fishing, sea transport) alongside ecological considerations; and (4) an Integrated scenario that combines all previous factors with an emphasis on ecological connectivity. These scenarios will allow decision-makers to weigh conservation trade-offs and synergies and identify the best path forward for MPAs. By offering a context-sensitive and data-driven framework, SWIO 30*30 aims to contribute not only to SWIO biodiversity and ecosystem services conservation but also pave the way to broader global efforts, potentially serving as a model for other biodiverse yet under-protected marine regions worldwide.

How to cite: Deléglise, H., Palomo, I., and Brasseur, P.: SWIO 30*30: A social-ecological approach to identify marine priority areas for conservation under the Kunming-Montreal Global Biodiversity Framework in the South West Indian Ocean region., One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-524, https://doi.org/10.5194/oos2025-524, 2025.

The proliferation of pelagic Sargassum in the tropical Atlantic since 2011 has become a significant environmental and socioeconomic issue. To better understand and predict this phenomenon, a combination of remote sensing observations and numerical modeling has been employed. By integrating satellite data with a biophysical model (NEMO-Sarg), we have investigated the factors driving Sargassum blooms, their seasonal variability, and their potential impact on coastal regions. Our findings highlight the role of the North Atlantic Oscillation in initiating the regime shift in 2010 and the nutrient fluxes sustaining subsequent blooms. Additionally, we demonstrate the feasibility of seasonal Sargassum forecasts with up to 7-month of anticipation, providing valuable insights for coastal communities to mitigate the adverse effects of Sargassum inundation. By quantifying the amount of Sargassum accumulating on coastlines and developing vulnerability indices, we identify regions most at risk and inform targeted management strategies. These advancements in our understanding and predictive capabilities are crucial for addressing the challenges posed by Sargassum blooms and safeguarding coastal ecosystems.

How to cite: Jouanno, J., Morvan, G., Benshila, R., Aumont, O., Berthet, S., Thouvenin-Masson, C., Berline, L., Sheinbaum, J., Ménard, F., Almar, R., Muller-Karger, F., van Tussenbroek, B., Sosa-Gutierrez, R., Asquier, J., Pitek, L., Brilouet, P.-E., Appeaning Addo, K., and Marchesiello, P.: Understanding and Predicting Sargassum Blooms: A Coupled Modeling and Remote Sensing Approach, One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-539, https://doi.org/10.5194/oos2025-539, 2025.

Approximately 40% of the global population resides within 100 kilometers of the coastline, making these regions highly vulnerable to the impacts of climate change. Increasing risks of coastal erosion, flooding, and biodiversity loss necessitate robust monitoring and effective protection strategies. Nature-Based Solutions (NBS), particularly those involving coastal vegetation such as seagrass, salt marshes, and mangroves, offer sustainable approaches to mitigate these threats. NBS not only reduce erosion and wave energy but also enhance carbon sequestration and support biodiversity, aligning with climate adaptation and mitigation goals.

This study presents an innovative Digital Twin (DT) application that integrates advanced hydrodynamic, wave, and morphodynamic models with artificial intelligence components. This DT application serves as a virtual representation of coastal environments, enabling dynamic simulations of complex interactions between natural processes and human interventions.  Integrated observational, coupled modelling framework and artificial intelligence facilitates the forecasting of prospective risks for oceanic regions and the evaluation of potential mitigation strategies. However, these systems are dependent on the input of expert technical knowledge. The introduction of the DT as a methodology for addressing environmental challenges provides a novel instrument that serves as a virtual replica of the ocean. By conducting comprehensive "What-If" scenarios, the DT assesses the effectiveness of NBS under varying climate conditions and informs coastal management strategies.

Our demonstration focuses on the German Bight, using scenario analysis to evaluate the risk reduction capabilities of seagrass meadows. The simulations reveal significant changes in hydrodynamic properties, including reductions in wave heights and bottom stress, which help to stabilize sediments and lower erosion risks.

The containerized DT application, integrated within platforms like EDITO-Infra, provides a user-friendly interface for stakeholders, allowing them to explore and assess NBS measures without requiring specialized technical expertise. This tool empowers decision-makers to evaluate and implement sustainable coastal protection strategies effectively, offering a scalable solution adaptable to diverse coastal regions.

The findings show the critical role of Digital Twins in advancing the implementation of Nature-Based Solutions, supporting a shift towards more resilient and adaptive coastal management practices.  Through various WIS, this DT approach offers actionable insights for optimizing ecosystem services, reducing erosion risks, and enhancing the resilience of coastal communities in the face of climate change.

How to cite: Jacob, B., Chen, W., Yuan, B., Dammak, N., and Staneva, J.: Digital Twins for Enhancing Coastal Resilience Through Nature-Based Solutions, One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-612, https://doi.org/10.5194/oos2025-612, 2025.

The Southwest Indian Ocean (SWIO) is characterized by diverse dynamic regimes, with intense energy fluxes and intricate atmospheric interactions (Phillips et al., 2021). The Mascarene area, to the east of Madagascar, is influenced by the South Equatorial Current and the Indian subtropical gyre, the Mozambique Channel presents numerous mesoscale eddies, which play an important role in the biogeochemical dynamics, and the Equatorial zone is affected by the inversion of seasonal Monsoon circulation. Modeling such complex systems requires the consideration of multiple sources of uncertainty. In the context of global warming and climate projections, it is essential to simulate these uncertainties in order to obtain a more accurate representation and understanding of the SWIO ocean dynamics. The objective of this project is to identify and analyze the dominant sources of uncertainty affecting surface circulation in the SWIO. To address this issue, a probabilistic approach is integrated into the CROCO model (Coastal and Regional Ocean Community), following three key steps. Firstly, a realistic model configuration for the SWIO region is developed, which is forced and validated by CMEMS and ECMWF operational and satellite products. Then, a stochastic perturbation generator (referred to as STOGEN and originally developed in the NEMO model, Brankart et al., 2015) is implemented into CROCO, associated with an ensemble generator. Finally, stochastic processes with varying correlation structures in space and time are generated in the defined regional setting. This allows to test the cumulative effect of different sources of uncertainty associated with surface ocean circulation. We starts with the simulation of an ensemble by perturbing the wind stress. Then, three additional ensemble simulations will be generated by perturbing the vertical mixing, the initial conditions to analyze the intrinsic ocean variability, and the open boundary conditions. These ensemble experiments describing prior uncertainties and the associated modeling testbed will then be used for 4D inversions (Popov et al., 2024) exploiting high-resolution spatial (real or simulated) altimetry, surface currents, high-resolution temperature and ocean colour data to reduce uncertainties in surface ocean Lagrangian transport. The integration of stochastic methodologies within CROCO may facilitate scenario exploration and uncertainty quantification, providing a basis for informed decision-making and collaborations with ocean actors in the SWIO region.

Phillips, H. E., Tandon, A., Furue, R., Hood, R., Ummenhofer, C. C., Benthuysen, J. A., ... & Wiggert, J. (2021). Progress in understanding of Indian Ocean circulation, variability, air–sea exchange, and impacts on biogeochemistry.

Brankart, J.-M., Candille, G., Garnier, F., Calone, C., Melet, A., Bouttier, P. A., Brasseur, P., Verron, J. (2015). A generic approach to explicit simulation of uncertainty in the NEMO ocean model.

Popov, M., Brankart, J.-M., Capet, A., Cosme, E., Brasseur, P. (2024). Ensemble analysis and forecast of ecosystem indicators in the North Atlantic using ocean colour observations and prior statistics from a stochastic NEMO-PISCES simulator.

How to cite: Weiss, L., Brankart, J.-M., Jamet, Q., and Brasseur, P.: Probabilistic modeling of the Southwest Indian Ocean dynamics to quantify uncertainties in surface currents, One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-613, https://doi.org/10.5194/oos2025-613, 2025.

The strandings of common dolphin (Delphinus delphis) have been significantly increasing along the French coast since 2016, putting at risk the whole population. These strandings occur especially in winter, despite the temporal variability remains high. Therefore, it is essential to understand the distribution of this species on a fine scale to propose solutions to reduce accidental captures. The suite of models SEAPODYM was used to map the spatio-temporal distribution of dolphins and their preys.

Highly mobile, dolphins respond to environmental variations and move towards conditions that best match their physiology and the presence of their prey. Using biophysical data (CMEMS) as an input of the SEAPODYM-LMTL (Low and Mid trophic Levels) model, we have modelled the spatio-temporal distribution of the dolphins’ preferred prey: sardines (Sardina pilchardus), anchovies (Engraulis encrasicolus), mackerel (Scomber scombrus), horse mackerel (Trachurus trachurus) as well as a mesopelagic fish, Kroyeri’s lanterfish (Notoscopelus kroyeri). Then we modelled dolphin’s habitat with SEAPODYM-MASS (Migratory Aged Structured Stock) model, function of the presence of the preys and their accessibility. The density energy of the prey was taken into account, as it varies across seasons, to compute the preferred habitat of dolphins.

Besides modelling the spatial distribution of the common dolphin in the Bay of Biscay, it is crucial to understand the distribution of the fleet's effort using fishing gears that are implicated in the strandings to identify the areas where dolphins are the most at risk to interact with fishing gears at concern. To achieve this goal, we trained machine learning algorithms to recognize fishing activities along trajectories of vessels using those gears. For each fishing occurrence identified by our algorithm, environmental conditions like the type of sediment, sea temperatures at various depth, currents or phytoplankton concentration are extracted and compared to the conditions over the entire Bay of Biscay through a Species Distribution Model (SDM). During the training process, SDM performance are evaluated by cross-validation. Once trained, the SDM can predict the probability of fishing activity across the entire region given the current environmental conditions. The output of the SDM being maps of probabilities it can overlapped with the dolphin habitat maps to characterize in near real time the risk of interaction between dolphin populations and fishing activities.

Key words: mechanistic habitat modelling, small pelagic, mesopelagic fish, energy density, fishing effort distribution.

How to cite: Conchon, A., Merillet, L., Saccareau, T., Magon de la Giclais, S., Lalire, M., and Titaud, O.: Mapping risk of common dolphin (Delphinus delphis) bycatch in the Bay of Biscay, One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-674, https://doi.org/10.5194/oos2025-674, 2025.

Digital ocean twins represent a transformative tool for integrating marine ecosystem models, observational data, and direct stakeholder input to develop robust management strategies. Here, we introduce one of the first digital twins for the Black Sea—a pioneering model designed to deepen our understanding of this unique ecosystem, forecast its response to climate change and environmental stressors, and evaluate alternative socio-economic scenarios to support informed decision-making.

The Black Sea digital twin includes a comprehensive ensemble of integrated simulations and resilience assessments, offering insights into ecosystem states and the risks to the valuable services they provide. Utilizing machine learning and Cumulative Effects Assessment (CEA) methodologies, it functions as a sophisticated decision-support system. This model tests a variety of socio-economic and blue economy scenarios, incorporating analyses of critical sectors and feedback from stakeholders through basin-wide living labs.

Through this innovative digital twin, we aim to define a "safe operating space" for the Black Sea—where ecosystem services are preserved and understood, enabling resilient and sustainable coastal societies. The model not only enhances our capacity to predict future changes but also serves as a foundation for adaptive management in a region undergoing rapid environmental shifts.

How to cite: Salihoglu, B., Fach, B., Arkin, S., Yucel, M., Uygurer, P., Tezcan, D., Guittard, A., St. John, M., Mariani, P., Niiranen, S., Barbanti, A., Menagon, S., and Herpers, F.: "Towards Resilient Coastal Societies: The Black Sea Digital Twin as a Model for Ecosystem and Socio-Economic Scenario Planning", One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-712, https://doi.org/10.5194/oos2025-712, 2025.

The UN Decade Programme "Digital Twins of the Ocean" (DITTO) is dedicated to creating a comprehensive digital framework to support the UN Ocean Decade’s Challenge 8: developing a global digital ocean map for free and open access. DITTO strengthens science and evidence-based decision-making through extensive community engagement and the development of accessible and transferable community interfaces to prioritise user-friendly and trustworthy digital twin frameworks. By promoting these community-centric approaches, DITTO is championing sustainable and extensible practices that help ensure that decisions are grounded by the best possible understanding of potential risks, both now and in the future. The aspiration is for a collaborative and transparent framework where science consistently informs responsible and sustainable ocean practices, enabling effective engagement and proactive management that safeguards marine habitats and biodiversity, helping to support UN Sustainable Development Goals.

DITTO provides a focal point for users, developers and stakeholders to ensure that digital twin technologies are accessible and fit-for-purpose for policymakers, researchers, industry leaders and local communities. By championing best practice and helping communities establish shared standards for digital twin development, DITTO is helping to ensure that digital twins are interoperable and scientifically robust, contributing to a unified global ocean knowledge system. These trusted foundations are essential for making informed, impactful decisions that align with the UN Ocean Decade’s vision.

As part of its mission, DITTO is actively collaborating with other Decade actions and initiatives to maximise the impact of digital twin technologies at global and regional scales. This includes establishing community interfaces that enable and promote common resources, standards, interoperability, and coordinated responses to ocean challenges within and between ocean communities.  DITTO also fosters inclusive and broadscale community engagement in the co-development of digital twin models that ensures that local knowledge and concerns are incorporated, making digital twins more comprehensive and relevant to specific regions and user needs. Through workshops, training, and open-access tools, and soliciting feedback on their use, DITTO is empowering communities to engage with ocean data directly, bridging the gap between scientific insights and decision-making.

How to cite: Palmer, M., Hermsen, A., Staneva, J., Mehra, A., Ramsewak, D., Blower, J., and Tintore, J.: Establishing Community Interfaces To Optimise Outcomes And Maximise Impacts From Digital Twins Of The Ocean, One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-972, https://doi.org/10.5194/oos2025-972, 2025.

With climate change and rising sea levels, coastal hazards, such as erosion and flooding are increasing in intensity and frequency, posing significant threats to coastal areas. Traditional protection strategies including the construction of seawalls, breakwaters, and revetments have been adopted over the years. However, these approaches present challenges such as the high cost of construction and negative environmental impacts. Consequently, there is a drive towards the adoption of Nature-based Solutions (NBS), such as the use of mangroves. With the use of Digital Twin of the Ocean (DTO), the effectiveness of such NBS can be simulated through advanced models. In this study, we explore the What-if Scenarios (WiS) using mangroves as NBS to curb coastal erosion. This research explores WiS by testing mangroves as NBS for mitigating coastal erosion in the Volta Delta region, an area that is particularly lacking in comprehensive observational data. The integration of the DTO framework helps bridge this data gap by providing high-resolution simulations and predictive capabilities. Instead of relying on simplified modeling approaches, this study employs a robust model chain integrated within the DTO to simulate different configurations and densities of mangroves, The work explored three (3) WiS which include: the beach without mangroves, mangroves positioned at the back of the shoreline, and mangroves placed within the intertidal zone. The model validation against measured coastal profiles shows strong agreement with observed erosion trends, providing accurate predictions of sediment volume changes. The results demonstrate a significant reduction in erosion, with mangroves at varying densities offering protection between 18% and 100%. In scenarios with high densities of mangroves introduced in the intertidal zone; the shoreline was fully stabilized. The results of these simulations demonstrate the potential of mangroves as a dynamic coastal defense strategy, with DTO applications providing a valuable tool for testing and optimizing NBS interventions. This study contributes to the ongoing development of mangroves as an NBS for coastal defense strategy demonstrating how DTO applications can effectively test and optimize intervention. By addressing the scarcity of observational data, the DTO framework enhances our understanding and predictive capacity for coastal dynamics. These findings support the broader goals of the UN Ocean Decade by aligning with global efforts to enhance resilience through sustainable, data-driven coastal management strategies and inclusive science-policy-society interfaces.

How to cite: Jayson-Quashigah, P.-N., Staneva, J., Chen, W., and Djath, B.: Mangroves as coastal defense: A model assessment , One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-974, https://doi.org/10.5194/oos2025-974, 2025.

The Balearic Islands, a biodiversity hotspot facing growing pressure from climate change and human activities, are a key area for developing and implementing effective management strategies for marine ecosystems. This is especially crucial in light of the European Union’s goal to protect 30% of its seas by 2030, with particular emphasis on areas like the Cabrera Archipelago Maritime-Terrestrial National Park, a major Mediterranean protected area. 

To help achieve this goal, the Balearic Islands Coastal Observing and Forecasting System (SOCIB) has developed a suite of user-oriented tools in the Mediterranean Sea that translate scientific knowledge into accessible information for stakeholders. These tools, built upon open access data provided by regional research infrastructures and available in the European marine data portals (e.g. Copernicus Marine Service, EMODNet), integrate historical and near real-time data from multi-platform observations (e.g. satellites, buoys, profiling floats and gliders) with regional ocean models. This allows for continuous and timely monitoring of essential ocean variables (e.g. temperature, salinity, chlorophyll-a concentration, sea level, currents, winds) as well as key derived indicators (e.g. anomalies, gradients, ocean heat content, mixed layer properties, transports). This information is provided for all sub-regions of the Mediterranean Sea, enabling comprehensive assessment of ocean state, variability, and change across various spatial and temporal scales, from open to coastal and near-shore ocean waters, and from the surface to deep waters. Specifically, these tools enable detecting extreme ocean events (such as marine heatwaves, harmful algal blooms, sea level maxima or storms) in real-time and provide 10-day forecasts as well as estimating long-term variations in response to climate change, from local to regional scales. By facilitating the access and visualization to relevant information for users, these applications support evidence-based decision-making for climate change adaptation. 

The increasing capability of the ocean observing and forecasting systems integrated into science-based tools are an important step towards improving the capabilities and the development of regional Digital Twins of the Ocean, allowing more effective management and conservation of valuable marine ecosystems and supporting the European's ambitious marine protection targets.

How to cite: Juza, M., Soriano González, J., Reyes, E., Mora-Fernández, À., Navarro, G., Caballero, I., de Alfonso, M., Zarokanellos, N., Rodríguez, R., García, A., and Tintoré, J.: Towards a regional Digital Twin of the Balearic Sea for sustainable ocean management, One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-1179, https://doi.org/10.5194/oos2025-1179, 2025.

The Iliad Digital Twins of the Ocean project [1] is a large (55 partners) European Green Deal Project which aims at the development of an architecture and set of components, tools and services for the creation of digital twins of the ocean.  The approach aims to support the emerging European Digital Twins of the Ocean (EU DTO) initative including interoperability with associated projects like EDITO Infra and EDITO Model lab and the overall Destination Earth (DestinE) initiative and also taking advantage of the evolving European Common Data Spaces including the Green Deal Data Space, the Copernicus Data Space and the EOSC cross domain Data Space.  The approach of Iliad digital twin interoperability architecture based on four steps of a digital twin pipeline.

The four digital twin pipeline steps are:  Digital Twin Data Acquisition/Collection,  Digital Twin Data Representation, Digital Twin Hybrid and Cognitive/AI Analytics Models  and Digital Twin Visualisation and Control.  The Iliad project has idenified these four steps as main architectural pipeline areas from an interoperability perspective, as described in the following. The architecture is system of systems based and the figure also shows the existence of potential multiple digital twins interactions.

The first Digital Twin step focuses on Data acquisition and collection from various sources including collection of realtime see\nsor data, for input to the Digital Twin. This is supported by various Data Spaces and also through a direct Stream Handler. This includes both streaming data and data extraction from relevant external data sources and sensors.  It includes support for handling all relevant data types and also relevant data protection handling for this step. In the Digital Twin sensor context this includes the full Observation Pyramid from remote sensing through airborne sensors to surface and subsea sensors and in-situ and IoT sensors.

The second Digital Twin step focuses on Digital Twin Data Representation. The data availability for the digital twins is supported by various Digital Twin Data Lakes – connected to Data Spaces and also potentially directly to streaming observations from the previous step.

The third Digital Twin step focuses on Digital Twin Hybrid and Cognitive/AI Analytics Models.  The processing execution for the models is supported by various Digital Twin Engines.   

The fourth Digital Twin step focuses on Digital Twin Visualisation and Control.  This is being supported by various types of 2D/3D/4D visualisations, and immersive visualisations and further evolutions towards the GeoVerse perspective on MetaVerse.

The Iliad project is providing a framework with tools and services for these four digital twin pipeline steps aiming at technical and semantic interoperability with, and portability to, the EU DTO ecosystem of digital twins of the ocean.

[1] Iliad – Digital Twins of the Ocean project,  https://ocean-twin.eu/ 

How to cite: Berre, A., Sarmento, P., Sylaios, G., Agorogiannis, E., Oliveira, M., Mayer, I., and Ipektsidis, B.: Iliad Digital Twins of the Ocean Interoperability Architecture, One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-1376, https://doi.org/10.5194/oos2025-1376, 2025.

The European Digital Twin Ocean is a central component of the Digital Ocean Knowledge System under the EU Mission "Restore our Ocean and Waters." The EU Digital Twin Ocean aims to make ocean knowledge accessible to all—from international policymakers, national governments, and researchers to businesses, entrepreneurs, activists, and citizens. It provides a comprehensive set of user-driven, interactive, and decision-making tools, all supported by scientific data.
The European Commission launched the DTO's development at the One Ocean Summit in February 2022. To support this, EDITO-Infra project was launched to develop the EU Digital Twin Ocean platform prototype, creating a unified, cloud-optimized gateway to Europe’s marine information assets, including EMODnet and Copernicus Marine. The platform is equipped with cutting-edge tools, marine models, and applications that enable users to build "what-if" scenarios, facilitating informed decision-making.
Closely aligned with EU policies under the European Green Deal, the platform contributes to initiatives such as the Marine Strategy Framework Directive, the Biodiversity Strategy to 2030, and other key environmental policies. Through advanced data integration and cloud computing, EDITO-Infra is driving digital transformation in ocean science, positioning the EU Digital Twin Ocean as a vital asset for the sustainable management and protection of Europe’s marine environments.
In 2025, the project will enter its second phase, transitioning from a prototype to an operational platform with enhanced capabilities. The platform aspires to provide broad public access to an extensive range of ocean observations and data, models, cloud and high-performance computing resources, and a collaborative environment where users can integrate their own data and models, as well as develop their own applications.
The EU DTO platform is designed in accordance with international standards, enabling interoperability with other digital twins and supporting the integration of digital twins developed by a diverse range of communities. This is made possible through contributions to and participation in international initiatives such as the Digital Twins of the Ocean (DITTO) under the UN Decade Programme.

How to cite: Tonani, M., Arnaud, A., Tyberghein, L., Gaudel, Q., Gasperi, J., Vera, J., Delaney, C., and Leclercq, F.: European Digital Twin Ocean platform: an innovative platform for making ocean knowledge readily available , One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-1545, https://doi.org/10.5194/oos2025-1545, 2025.

Digital twin technology, originally developed for industrial applications, is gaining increased attention in ocean governance and multilateral negotiations. While existing research gives insights into the scope of digital ocean twin applications for environmental governance and associated technical challenges, they do not sufficiently explore how their development and use takes place across politically contentious spaces in which various public and private actors operate. To address this gap, our paper pursues two research questions: ‘Who develops and uses digital twins of the oceans and for which purposes?’  and ‘Which promises and risks are associated with digital ocean twins in the context of multilateral negotiations?’. The paper is based on empirical bibliometric research into academic literature, patents, and policy documents to identify political, scientific, and corporate actors involved in developing and applying digital ocean twins and to map their discourses. By offering a holistic view of how digital twins are, or could be, applied in ocean governance, this paper aims to contribute to the development of effective, technology-driven, but also politically sensible approaches environmental governance.

How to cite: Dunshirn, P. and Vadrot, A.: Mapping actors and discourses in the use of digital ocean twins for environmental governance, One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-605, https://doi.org/10.5194/oos2025-605, 2025.

The ocean offers a plethora of vital services and intrinsic values, covering many different sectors. Decision-making to optimize and safeguard these values requires data and information that reflects the complexity. Digital twins of the ocean represent powerful tools for both decision-makers and scientists. The Iliad project builds on the assets resulting from two decades of investments in policies and infrastructures for the blue economy and aims at establishing interoperable, data-intensive, and cost-effective digital twins of the ocean. It capitalizes on the explosion of new data provided by many different Earth observation resources, auxiliary data,  advanced computing infrastructures (cloud computing, HPC, Internet of Things, Big Data, social networking, and more) in an inclusive, virtual/augmented, and engaging fashion to address all Earth data challenges. To meet the needs of decision-makers and scientists Iliad has developed a set of thematic and local digital twins covering a variety of sectors on locations in Europe, Middle-East and Africa. An overview of the thematic and local twins and examples of use of various data and technologies to meet the needs of decision-makers and scientists will be presented. This will contribute to enhancing and sustaining the ecosystem of digital twins of the ocean, its data, technology and knowledge.

How to cite: Bye, B. L., Berre, A. J., Sylaios, G., Brönner, U., van Dam, S., Keeble, S., and Ipektisidis, C.: Thematic and local twins of the ocean, One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-1348, https://doi.org/10.5194/oos2025-1348, 2025.

In the light of time pressure, persisting data gaps, and challenges to the implementation of global sustainability goals for ocean protection, the European Commission is currently building a prototype digital twin of the ocean (DTO). The EU DTO is part of a larger set of substantial global and national efforts to develop highly accurate digital models of the ocean for ‘better decision-making’ and an emerging high-tech knowledge infrastructure that turns various types of ocean data into prediction tools for public and private actors. However, as this paper argues, DTOs are a political issue in themselves. Firstly, DTOs run the risk of perpetuating global inequalities because the capacities to develop, access, and use ocean data are unequally distributed. Secondly, DTOs may create an array of legal and political uncertainties regarding data access, ownership, security, and sharing. Thirdly, DTOs should be embedded into a set of norms, rules, and values to prevent abuse and misuse in practice — a neglected aspect in the current ‘twin rush’. This paper re-conceptualizes digital twins as socio-technical relations operating under a specific set of institutional, political, and economic conditions and within a hybrid research, data, and observation environment and explores how they may shape multilateral environmental negotiations in the future.

How to cite: Vadrot, A.: Can digital ocean twins shape the future of multilateral environmental negotiations?, One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-316, https://doi.org/10.5194/oos2025-316, 2025.

Digital Twining involves creating a virtual, dynamic replica of physical systems—in this case, the ocean—integrated with real-time data and advanced simulations to represent, analyze, and predict changes in the marine environment. Thus, Digital Twins of the Ocean (DTO) open new possibilities for fostering inclusive, collaborative science-policy-society interfaces and can serve as vibrant platforms for advancing ocean sustainability. Through the Iliad project’s DTOs, we explore how such digital models can enhance our understanding of ocean systems and drive informed decision-making to address complex challenges.

DTOs can play a pivotal role in bridging the gap between scientific research, policy development, and societal engagement. By providing detailed, real-time visualizations and predictive capabilities, they enable stakeholders—including scientists, policymakers, industries, and communities—to access actionable insights that inform and guide sustainable ocean management. Through citizen science, citizens, communities, and businesses can also contribute to improving environmental monitoring,  forecasting, and ensuring the sustainability of marine ecosystems. This is particularly vital in the context of global initiatives like the European Green Deal and the Mission Restore Our Ocean and Waters by 2030, which focuses on reversing the degradation of marine ecosystems. DTOs can also contribute to the UN Decade of the Ocean’s overarching goal of promoting sustainable ocean governance, by ensuring that data and decision-making are inclusive, transparent, and grounded in real-time environmental information.

In this presentation, we will showcase specific examples of how the Iliad DTOs have been developed and applied in real-world scenarios. These digital models integrate oceanographic data, satellite observations, and environmental sensors to simulate complex marine processes, from fisheries management to ship routing marine to biodiversity conservation. By embedding these simulations within policy-making frameworks, DTOs provide a powerful decision-support tool, facilitating evidence-based strategies that align with global sustainability goals.

Moreover, DTOs help overcome barriers to inclusive decision-making by democratizing access to ocean data. They offer a platform for diverse stakeholders—including policymakers, businesses, and civil society—to collaborate on solutions in a way that is transparent, interactive, and adaptive. Through open-access interfaces, local communities and indigenous groups can contribute their knowledge, creating a more holistic approach to ocean governance. The real-time nature of DTOs ensures that policies and actions can be responsive to ongoing changes in the marine environment, fostering adaptive governance practices that are crucial in an era of rapid environmental shifts.

Ultimately, Digital Twins of the Ocean represent a groundbreaking tool in the pursuit of ocean sustainability, enhancing the capacity of science, policy, and society to work together in a multisectoral approach to tackle  the pressing challenges facing our oceans today. By demonstrating the real-world impact of DTOs in ocean governance, this presentation aims to inspire further innovation and collaboration in support of global ocean action.

How to cite: Kazanjian, G., Bye, B. L., and Guezguez, D.: Navigating the Future: Empowering Ocean Action with Digital Twins, One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-1339, https://doi.org/10.5194/oos2025-1339, 2025.

As we move into the digital age, the concept of a digital twin of the ocean - a virtual replica that integrates real-time data, environmental conditions and ecosystem dynamics - holds transformative potential for ocean science and resource management. Digital twins promise to provide unprecedented insight into ocean processes, supporting real-time scenario testing, predictive modelling and adaptive management. However, while their value for marine resource management is compelling, the integration of digital twins into fisheries management applications, such as Management Strategy Evaluation (MSE), presents a number of technical and operational challenges.

MSE is a critical framework for evaluating and optimising fisheries management strategies, but the operating models (OMs) on which it is based are often simplified single-species population models with limited, if any, environmental feedback. Due to constraints on data availability, computational resources, and the need for transparency and stakeholder engagement, these OMs are typically built to prioritise practicality over complexity. Ecosystem models remain underused in MSE due to these constraints, and Models of Intermediate Complexity are somewhat more applicable as they can be fitted to data in a similar way to single-species models. Therefore, the full potential of sophisticated digital twins, even when they become technologically feasible, may be difficult to realise immediately in MSE and related fisheries management applications.

This presentation will examine the technical and operational barriers to adopting Digital Twins of the Ocean for fisheries management applications such as MSE, highlighting the significant requirements for expertise, data integration, computational power and model transparency. We discuss key areas for development, including simplification and modularisation of Digital Twins to make them suitable for fisheries-focused applications, as well as the need for training, standardisation and stakeholder engagement. In conclusion, while Digital Twins of the Ocean hold great promise, their immediate adoption in fisheries management is limited by practical and technological barriers. Overcoming these challenges will require cross-disciplinary collaboration, investment in computational infrastructure, and a roadmap for bridging current OMs with emerging digital frameworks. The path to integrating digital twins into fisheries management must therefore balance ambition with a pragmatic approach, preparing the field for the eventual realisation of fully integrated, adaptive digital management tools.

How to cite: Oliveros-Ramos, R.: Integrating Digital Twins into Fisheries Management: Moving Beyond Traditional Operating Models for Fisheries Management Applications, One Ocean Science Congress 2025, Nice, France, 3–6 Jun 2025, OOS2025-1504, https://doi.org/10.5194/oos2025-1504, 2025.