Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 112, Issue 7, Pages 2076-2081Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1424997112
Keywords
oyster reefs; operational taxonomic units; meiofauna; ARMS; cryptic species
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Funding
- US Army Corps of Engineers in FL [SAJ-2012-02893]
- Sant Chair and Smithsonian Tennenbaum Marine Observatories Network
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Documenting the diversity of marine life is challenging because many species are cryptic, small, and rare, and belong to poorly known groups. New sequencing technologies, especially when combined with standardized sampling, promise to make comprehensive biodiversity assessments and monitoring feasible on a large scale. We used this approach to characterize patterns of diversity on oyster reefs across a range of geographic scales comprising a temperate location [Virginia (VA)] and a subtropical location [Florida (FL)]. Eukaryotic organisms that colonized multilayered settlement surfaces (autonomous reef monitoring structures) over a 6-mo period were identified by cytochrome c oxidase subunit I barcoding (>2-mm mobile organisms) and metabarcoding (sessile and smaller mobile organisms). In a total area of similar to 15.64 m(2) and volume of similar to 0.09 m(3), 2,179 operational taxonomic units (OTUs) were recorded from 983,056 sequences. However, only 10.9% could be matched to reference barcodes in public data-bases, with only 8.2% matching barcodes with both genus and species names. Taxonomic coverage was broad, particularly for animals (22 phyla recorded), but 35.6% of OTUs detected via meta-barcoding could not be confidently assigned to a taxonomic group. The smallest size fraction (500 to 106 pm) was the most diverse (more than two-thirds of OTUs). There was little taxonomic overlap between VA and FL, and samples separated by similar to 2 m were significantly more similar than samples separated by similar to 100 m. Ground-truthing with independent assessments of taxonomic composition indicated that both presence-absence information and relative abundance information are captured by metabarcoding data, suggesting considerable potential for ecological studies and environmental monitoring.
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