This $10,000 funding request is part of a larger Sea Grant California-funded project aimed at monitoring the fish community in Marine Protected Areas (MPAs) to assess their success. BRUVs are one of the methods used in this monitoring effort. The funding will support the purchase and validation of MaxN AI software for BRUV video analysis, helping determine if AI can improve time efficiency, standardization, and accuracy in marine biodiversity monitoring

• AI Software - $3275: Covers MaxN plugin for EventMeasure to automate fish species detection and evaluate AI’s efficiency vs. manual review, helping standardize analysis
• Researcher/Video Analyzer (200 hrs) - $5240: Researcher will validate MaxN’s performance by comparing AI results with manual analysis, assessing its ability to process large footage volumes more efficiently
• Fringe - $555: Payroll taxes (worker’s comp, unemployment, Social Security, Medicare)
• Miscellaneous - $930: Unexpected costs (hardware, software upgrades, storage)

Additional Information

Marine Protected Areas (MPAs) are established in ecologically significant areas that support critical stages of the life histories of various organisms. Because of this, non-invasive sampling techniques are preferred by researchers studying marine species associated with MPAs. Baited Remote Underwater Videos (BRUVs) represent a low-impact method for gathering data on species diversity and abundance in marine and aquatic environments. This technique is particularly conducive to sampling areas where delicate or endangered species may be present, minimizing disruption to the ecosystem. However, BRUV sampling produces numerous hours of video footage which requires rigorous attention from the observer to extract meaningful data. Researchers working with BRUV footage often spend many hours analyzing the footage, sometimes without recording any species.

This project, funded by Sea Grant California and conducted by staff in the Department of Fisheries at Cal Poly Humboldt, focuses on studying the fish community in the sandy beach surf zone along the Northern California coast. The project has been ongoing for five years and is set to continue for at least two more, allowing for the collection of long-term data on MPAs. The study employs BRUVs to document and monitor the fish species in this dynamic environment. By using BRUVs, researchers are able to capture video footage of fish interactions with baited camera traps, providing insights into species composition, behavior, and abundance. This non-invasive method allows for detailed observations without disrupting the delicate coastal ecosystem, offering valuable data for the management and conservation of MPAs in the region.

This research is not only important for commercial and recreational fisheries in the area, but also valuable for the underserved communities in the region. Many of the fish species in the sandy beach surf zone are essential to the cultural and subsistence practices of local Indigenous tribes. By using non-invasive BRUV sampling, this project optimizes data collection while minimizing disruption to the marine ecosystem. The continuation of this work will provide valuable insights to guide the management of MPAs, supporting the protection of both marine biodiversity and the commercial, recreational, and cultural resources central to local communities.

To enhance the efficiency of data analysis, we are seeking funding for the MaxN AI plugin for EventMeasure software, developed by SeaGIS. The MaxN plugin will allow us to rapidly process large volumes of BRUV video data, accurately detecting fish presence with high consistency. Through EventMeasure, the AI program timestamps fish and other species in the footage, enabling researchers to focus only on frames where organisms are identified. This will significantly reduce the time spent analyzing hours of footage, improve consistency, and lower the costs associated with future monitoring efforts. It is expected that by adopting this innovative approach to video analysis, AI will increase time efficiency, increase consistency, and reduce expenses for future monitoring projects in MPAs and other sensitive aquatic habitats in which BRUVs are utilized.