4.5 Article

Comparing anesthetic stations and environmental DNA sampling to determine community composition of cryptobenthic coral reef fishes of Vava'u, Kingdom of Tonga

Journal

CORAL REEFS
Volume 42, Issue 3, Pages 785-797

Publisher

SPRINGER
DOI: 10.1007/s00338-023-02375-7

Keywords

Biodiversity; Metabarcoding; COI

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Comparing eDNA sequences from water samples with anesthetic stations, it was found that eDNA sampling cannot effectively characterize the community composition of cryptobenthic reef fishes (CRF) due to their low biomass, low detectable DNA abundance in eDNA samples, large number of non-targeted metazoan reads drowning the detections of CRF sequences, and lack of complete taxonomic information in public databases representing CRF's high level of endemism.
Cryptobenthic reef fishes (CRF) are an important component of coral reef communities that are often overlooked, as their cryptic nature and very small size make them difficult to assess using visual methods. The prevailing method for quantifying communities of CRF is to use enclosures and anesthetics to collect fishes from within the reef. Environmental DNA (eDNA) sampling of water around reefs may be an alternative or supplemental way to quantify CRF communities. Here, we compare the ability to characterize CRF communities using eDNA sequences from water samples collected from within the interstices of the reef, with corresponding anesthetic stations from the same microhabitat. A total of 676 CRF from 33 species were collected from anesthetic stations, whereas only four species of CRF were detected from the eDNA samples taken at the same locations. Main factors contributing to these results may have been: (1) low standing biomass of CRF, thus low abundance of detectable DNA in the eDNA water samples; (2) large number of non-targeted metazoan reads that drowned the detections of specific CRF sequences; and (3) lack of sequences available in public databases that represent the high level of endemism present in CRF and a need for more complete taxonomic inventory.

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