Towards Digital Twins of the Ocean: New Technologies and Automation for Integrated Ecosystem Assessment

The sustainable management of marine ecosystems is increasingly challenged by the scale, complexity, and rapid dynamics of coupled socio-ecological systems, requiring a paradigm shift in ocean observing, data integration, and modelling frameworks. Recent advances in autonomous sensing platforms, marine robotics, high-resolution remote sensing, and biogeochemical observations are transforming ocean monitoring by enabling sustained, cost-effective, and multi-scale data collection across littoral, coastal and open ocean regions. In parallel, advances in automation, artificial intelligence, and hybrid modelling are reshaping data processing pipelines, ecological modelling, and ecosystem indicator development, allowing heterogeneous observations to be integrated with process-based models.

Together, these developments are boosting the development of Digital Twins of the Ocean (DTO), i.e., dynamic, data-assimilative virtual representations that support near-real-time ecosystem assessment, scenario analysis, and adaptive decision-making.



This Research Topic aims to bring together contributions that advance the scientific and operational integration of emerging ocean sensing technologies, automated workflows, and hybrid and novel end-to-end process-based modelling approaches to strengthen quantitative Integrated Ecosystem Assessments and accelerate progress toward operational DTO, supporting ecosystem-based management, marine spatial planning, sustainable blue economy strategies, and evidence-informed marine governance.



We welcome original research, methods, perspectives, and review articles that contribute to advancing theory, technology, and applications at the interface of ocean observation, modelling, and decision support for the operationalisation of an integrated approach to marine management.



Possible topics include (but are not limited to):

• Autonomous and robotic ocean observing systems (e.g., gliders, floats, surface vehicles, ROVs, AUVs) with associated data management and transmission workflows

• Integration of in situ, remote sensing, and biogeochemical observations for ecosystem assessment

• Automated data processing, quality control, indicator extraction and risks and vulnerability analyses for ecosystem based management

• Hybrid modelling approaches for marine ecosystems, combining process-based models and machine learning

• Data assimilation and real-time updating of ecosystem models

• Development and application of Digital Twins of the Ocean for ecosystem assessment

• Scenario testing and forecasting of cumulative human and climate impacts

• Operational tools for ecosystem-based management and marine spatial planning

• Digital twin applications supporting sustainable blue economy and policy frameworks

• Challenges, uncertainties, and governance aspects of operational ocean digital twins

Topic Editor Dr. Julie Robidart holds a licence for the RoCSI eDNA autosampler technology, commercialised through the National Oceanography Centre with McLane Laboratories. The other Topic Editors report no competing interests related to this Research Topic.