Beyond traditional surveys: assessing reef fish diversity in a Marine Protected Area using BRUV and eDNA
Description
The effectiveness of Marine Protected Areas often suffers from a lack of continuous monitoring, which is crucial for biodiversity conservation. In this context, alternative approaches to biodiversity assessment that take advantage of current technologies can be valuable tools for monitoring protected areas. Our research evaluated the potential of environmental DNA (eDNA) metabarcoding and Baited Remote Underwater Video (BRUV) as complementary monitoring tools for assessing fish assemblages and biodiversity patterns in a fully submerged marine park. The study was conducted on tropical reefs (18–30 m depth) in the Southwestern Atlantic across two management zones: Preservation (no-take area) and Conservation (sustainable use). We utilized water filtration for eDNA analysis (12S rRNA metabarcoding with MiFish primers) and BRUV deployment (MaxN counts) to evaluate species richness and community structure. Together, eDNA and BRUV detected 68 reef fish species (51% of known local richness), including eight endangered species and two new regional records. BRUV identified 43 species, while eDNA identified 20, with 49.3% of eDNA amplicon sequence variants remaining unclassified due to significant gaps in South Atlantic genetic reference libraries. This highlights the critical need for sequencing Southwestern fish species to improve the resolution of eDNA applications. Within BRUV dataset, statistical analyses revealed that the Pedra do Mar reef (Preservation Zone), exhibited significantly higher richness and diversity compared to reefs in the Conservation Zone. These findings demonstrate that BRUV and eDNA are effective complementary tools for rapidly and accurately assessing reef biodiversity and analyzing ecological differences among management zones within marine protected areas. Here are deposited the raw sequences of eDNA metabarcoding of the 20 sampling points of the four reefs studied, and also the MaxN counts for fish species from BRUV dataset.
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Institutions
- Universidade Federal do CearáCeará, Fortaleza