UCLA

Environmental DNA metabarcoding (eDNA) is an evolving methodology of biodiversity monitoring. By leveraging shed and excreted DNA from organisms in a marine environment, researchers can perform DNA amplification and sequencing to identify what species were present at a site without the need for visual identification. This thesis uses eDNA to evaluate conservation efforts in Southern California as well as further establish and refine eDNA as a survey tool. In Chapter 1, I evaluate seagrass beds in three distinct geographic settings in Southern California. We demonstrate that nearly half of community composition is associated with whether seagrass was found off the mainland, off an island, or in an embayment. In addition, when compared to traditional monitoring, eDNA was able to identify roughly ~50% to 400% greater number of fish species at each site. In Chapter 2, I create a novel eDNA droplet digital PCR assay for the detection of the invasive species Caulerpa prolifera that was found in Newport Bay in 2021 and found it to have the lowest eDNA steady state of any previously tested species. We demonstrate the critical importance of benchmarking eDNA assays before their use by managers and highlight some limitations for using eDNA in species detection. In Chapter 3, we perform two years of monthly sampling of MPAs using community scientists and UCLA researchers. We find that MPAs are distinct from nonMPAs in multivariate space for both fish and metazoan communities and that metazoan communities in MPAs are more diverse and stable compared to nonMPAs. We also show the scalability that eDNA has in biodiversity monitoring through the incorporation of volunteers into field sampling. Together, these chapters better our understanding of marine conservation in Southern California and further demonstrate the utility and limitations of eDNA metabarcoding for monitoring marine biodiversity.