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Hide ‘n seq: direct versus indirect metabarcoding of coral reef cryptic communities

Cite this dataset

Nichols, Patrick; Timmers, Molly; Marko, Peter (2021). Hide ‘n seq: direct versus indirect metabarcoding of coral reef cryptic communities [Dataset]. Dryad.


Ecological patterns in biodiversity are primarily based on conspicuous organisms. Few methods are used to survey the taxonomically rich cryptobiome, which is made up of inhabitants from within microhabitats. One way that cryptic marine biodiversity can be non-invasively surveyed is by analyzing environmental DNA (eDNA) present in seawater. Using coral reefs as a model system, here we compare estimates of cryptic diversity among community biomass and eDNA metabarcoding sampling methods with a broad eukaryotic marker (COI). First, contributions to eDNA were investigated across cryptobiomes through a comparison of community metabarcoded biomass from standardized autonomous reef monitoring structures (ARMS) to eDNA acquired from seawater in which individual ARMS were soaked. Second, we compared these results to those from eDNA samples taken from within reef crevices and the ambient water column. Metabarcoding of community biomass from ARMS and eDNA from the two types of water samples revealed significantly different communities of cryptic coral reef habitat with little overlap between methods. Taxa that were unique to metabarcoding of ARMS biomass were predominantly from chitinous and calcifying groups (polychaetes, palaemonid shrimp, molluscs, brittle stars, and red algae), which suggests that these taxa are underrepresented in eDNA surveys. Other than the corals themselves, sponges and red algae were significant drivers of reef crevice community differences, while ambient seawater samples detected mostly planktonic organisms and reef fishes. Our data indicate that both eDNA and ARMS provide incomplete accounting of cryptic diversity. Direct sampling of biomass is best suited for building taxonomies and improving databases, whereas eDNA methods offer rapid insights into the composition of cryptobiomes. Because each method likely captures different taxa, multiple targeted assays can be used to provide the greatest estimates of metazoan and macroalgal richness.