Biodiversity assessment of tropical shelf eukaryotic communities via pelagic eDNA metabarcoding. Issue 24 (3rd December 2019) - Bakker, Judith; Wangensteen, Owen S.; Baillie, Charles; Buddo, Dayne; Chapman, Demian D.; Gallagher, Austin J.; Guttridge, Tristan L.; Hertler, Heidi; Mariani, Stefano
Abstract: Our understanding of marine communities and their functions in an ecosystem relies on the ability to detect and monitor species distributions and abundances. Currently, the use of environmental DNA (eDNA) metabarcoding is increasingly being applied for the rapid assessment and monitoring of aquatic species. Most eDNA metabarcoding studies have either focussed on the simultaneous identification of a few specific taxa/groups or have been limited in geographical scope. Here, we employed eDNA metabarcoding to compare beta diversity patterns of complex pelagic marine communities in tropical coastal shelf habitats spanning the whole Caribbean Sea. We screened 68 water samples using a universal eukaryotic COI barcode region and detected highly diverse communities, which varied significantly among locations, and proved good descriptors of habitat type and environmental conditions. Less than 15% of eukaryotic taxa were assigned to metazoans, most DNA sequences belonged to a variety of planktonic "protists, " with over 50% of taxa unassigned at the phylum level, suggesting that the sampled communities host an astonishing amount of micro‐eukaryotic diversity yet undescribed or absent from COI reference databases. Although such a predominance of micro‐eukaryotes severely reduces the efficiency of universal COI markers to investigate vertebrate and other metazoans from aqueous eDNA, the study contributes to the advancement of rapid biomonitoring methods and brings us closer to a full inventory of extant marine biodiversity. Abstract : Water samples from four Caribbean areas were sampled and subjected to universal eukaryote DNA metabarcoding. Tens of thousands of species were recovered, the vast majority being unicellular protists, most of which poorly known taxonomically and ecologically. Multivariate analyses clearly separated samples according to both region and habitat of origin.