Evaluating a Novel Approach to Remote Underwater Video Systems (RUVs) for Assessing Fish Assemblages in a Danish Fjord

Non-invasive alternative methods for assessing fish assemblages have gained increasing attention compared to traditional fishing techniques. Approaches such as Baited Remote Underwater Video systems (BRUVs), Autonomous Underwater Vehicles (AUVs) equipped with cameras, and environmental DNA (eDNA) sampling have seen substantial growth over the past decade. Despite their advantages, these methods also present specific trade-offs that must be considered in monitoring design and interpretation. Baited Remote Underwater Video systems (BRUVs) are cost effective, versatile, and provide high reproducibility but can face limitations such as reduced utility in low underwater visibility and challenges related to their weight and cumbersome deployment (Langlois et al., 2010). Additionally, the use of bait to attract fish may bias sampling outcomes, particularly when studying spatiotemporal patterns within small-scale fish assemblages (Oruç, 2025). In this study, we propose an alternative approach using Non-baited Remote Underwater Video systems (RUVs) deployed in a shallow mixed-habitat coastal zone in Vejle Fjord, Denmark. Up to seven RUV units were simultaneously deployed at random, at fifteen selected underwater sites representing diverse habitats, including transplanted eelgrass mosaics, natural eelgrass patches, artificial boulder reefs, and barren sand flats. Each deployment recorded up to 10 hours during daytime and 5 hours at night. We will compare data obtained from Non-baited Remote Underwater Video systems (RUVs) with traditional seine net catches and environmental DNA (eDNA) samples to evaluate the performance and complementarity of extended-duration RUV deployments in assessing fish assemblages. Our study aims to identify potential species biases driven by species-specific ecological traits across these different monitoring approaches. Additionally, we will explore temporal trends in species composition and relative abundance over the duration of RUV deployments.