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Explore how the sea evolves under SSP future projections — visualize physical processes and biogeochemical cycles.
Visualize fish biomass, yield, and marine plastics distribution.
Assess ecosystem & community resilience through indicators.
Explore how multiple human activities and climate drivers cumulatively impact the Black Sea ecosystem.
Monitor and explore socio-economic trends in the Black Sea Blue Economy through interactive dashboards, indicators, and more.
Using a hybrid Bayesian–Neural Network, the emulator predicts phytoplankton dynamics, ecosystem responses, and stressor impacts.
REST + ERDDAP endpoints for model/data access.
Access the interactive JupyterLab environment to explore, analyze, and visualize model outputs and observation datasets directly.
Step-by-step guides to use the DTO—from map navigation and scenario simulation to data download, Jupyter notebooks, and APIs.
BRIDGE Black Sea DTO stands out as one of the pioneering digital twin ocean demonstrators, integrating real-time data from database systems and smart observation setups. It incorporates high-resolution, fully coupled sophisticated models of both the sea and the watershed, enhanced by artificial intelligence tools and socio-economic models.
It aims to enhance our comprehension of regional sea ecosystems, enabling us to predict their conditions under changing climate and environmental stressors. Moreover, it facilitates the testing of alternative socio-economic scenarios, contributing valuable insights to decision-making processes.
Digital twin utilizes integrated simulations and resilience assessments to define the ecosystem's state and associated risks. Decision support tools, employing machine learning and cumulative assessments, are then applied. These tools test various socio-economic and blue economy scenarios, with sector analyses and stakeholder input from living labs across the basin.
Visuals were specifically designed to illustrate the BRIDGE Black Sea Digital Twin Ocean Demonstrator.
A proper credit to the METU Institute of Marine Sciences is required.
DSTs are founded on the Tools4MSP modeling framework, enabling a groundbreaking ad-hoc assessment of cumulative stressor effects on Black Sea ecosystem services for the first time.
CEA employs a distinctive ensemble modeling approach, drawing upon novel insights garnered through a diverse array of modeling techniques.
Actual feedback from customers and users across the Black Sea will help you to understand market needs, refining your product or service, and making informed decisions to enhance its value and appeal.
Through CEA, BRIDGE Black Sea DTO qualifies the spatial distribution of natural and anthropogenic risks, both individually and in combination, identifying critical marine areas that are affected.
Establishing crucial linkages to core Black Sea ecosystem services, a significant contribution to the MSFD is achieved by systematically considering the 15 MSFD pressures along with GES/Target indicators.
EBM for marine space and ecosystem services involves spatial identification, understanding cause-effect relationships, and facilitating the comparison of pertinent information and products among stakeholders.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101000240.
