Leveraging deep learning and computer vision technologies to enhance management of coastal fisheries in the Pacific region.

This paper presents the design and development of a coastal fisheries monitoring system that harnesses artificial intelligence technologies. Application of the system across the Pacific region promises to revolutionize coastal fisheries management. The program is built on a centralized, cloud-based monitoring system to automate data extraction and analysis processes. The system leverages YoloV4, OpenCV, and ResNet101 to extract information from images of fish and invertebrates collected as part of in-country monitoring programs overseen by national fisheries authorities. As of December 2023, the system has facilitated automated identification of over six hundred nearshore finfish species, and automated length and weight measurements of more than 80,000 specimens across the Pacific. The system integrates other key fisheries monitoring data such as catch rates, fishing locations and habitats, volumes, pricing, and market characteristics. The collection of these metrics supports much needed rapid fishery assessments. The system's co-development with national fisheries authorities and the geographic extent of its application enables capacity development and broader local inclusion of fishing communities in fisheries management. In doing so, the system empowers fishers to work with fisheries authorities to enable data-informed decision-making for more effective adaptive fisheries management. The system overcomes historically entrenched technical and financial barriers in fisheries management in many Pacific island communities.

Tracing innovation pathways behind fisheries co-management in Vanuatu.

Co-management approaches have become a core part of coastal fisheries policy and planning practice in Vanuatu. With a long history of supporting community based fisheries management (CBFM), we trace its evolution in Vanuatu to understand how new structures and processes become adopted at scale. A theory of scaling for CBFM guides the analysis of regime shifts over time. We discuss planning for sustained spread under a national programme by categorising multiple drivers of change through three intervention pathways focussed, respectively, on developing (i) an enabling environment, (ii) institutional and individual capacity, and (iii) focussed innovative action in smaller targeted constituencies. Whilst we argue that local fisheries co-management institutions balance competing interests, and so differ amongst places, we also recognise the importance of connectivity and continuity. The realisation of a national programme therefore requires patchworks of siloed projects to be knitted together into coordinated programmatic approaches that strategically integrate activities.