Integrating Digital Twins into Fisheries Management: Moving Beyond Traditional Operating Models for Fisheries Management Applications

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.