scholarly journals Environmental DNA metabarcoding for biodiversity monitoring of a highly diverse tropical fish community in a coral reef lagoon: Estimation of species richness and detection of habitat segregation

2020 ◽  
Author(s):  
Shin‐ichiro Oka ◽  
Hideyuki Doi ◽  
Kei Miyamoto ◽  
Nozomi Hanahara ◽  
Tetsuya Sado ◽  
...  
Keyword(s):  
Species Richness ◽  
Coral Reef ◽  
Fish Community ◽  
Environmental Dna ◽  
Tropical Fish ◽  
Habitat Segregation ◽  
Biodiversity Monitoring ◽  
Reef Lagoon ◽  
Dna Metabarcoding ◽  
Coral Reef Lagoon

scholarly journals Environmental DNA metabarcoding for biodiversity monitoring of a highly-diverse tropical fish community in a coral-reef lagoon: Estimation of species richness and detection of habitat segregation

2020 ◽  
Author(s):  
Shin-ichiro Oka ◽  
Hideyuki Doi ◽  
Kei Miyamoto ◽  
Nozomi Hanahara ◽  
Tetsuya Sado ◽  
...  
Keyword(s):  
Species Richness ◽  
Coral Reef ◽  
Fish Species ◽  
Environmental Dna ◽  
Seagrass Beds ◽  
Biodiversity Monitoring ◽  
Reef Lagoon ◽  
Coral Reef Lagoon ◽  
Offshore Reef ◽  
Reef Edge

AbstractAn environmental DNA (eDNA) metabarcoding approach has been widely used for biodiversity monitoring of fishes, although it has rarely been applied to tropical and subtropical aquatic ecosystems, where species diversity is remarkably high. This study examined the extent to which species richness can be estimated in a small coral reef lagoon (1500 × 900 m) near Okinawa Island, southern Japan, where the surrounding waters are likely to harbor more than 1500 species of fish. During 2015–2017, a total of 16 capture-based surveys were conducted to create a faunal list of fish species, followed by eDNA metabarcoding based on seawater samples taken from 11 sites in the lagoon on a day in May 2019. We also tested whether eDNA metabarcoding could detect differences between adjacent fish communities inhabiting the offshore reef edge and shore-side seagrass beds within the lagoon. A total of 217 fish species were confirmed by the capture-based samplings, while 291 fish species were detected by eDNA metabarcoding, identifying a total of 410 species distributed across 119 families and 193 genera. Of these 410 species, only 96 (24% of the total) were commonly identified by both methods, indicating that capture-based surveys failed to collect a number of species detected by eDNA metabarcoding. Interestingly, two different approaches to estimate species richness based on eDNA data yielded values close to the 410 species, including one that suggested an additional three or more eDNA surveys from 11 sites (36 samples) would detect 90% of the 410 species. In addition, non-metric multi-dimensional scaling for fish assemblages clearly distinguished between the fish communities of the offshore reef edge and those of the shore-side seagrass beds.

scholarly journals Environmental DNA metabarcoding for fish community analysis in backwater lakes: A comparison of capture methods

PLoS ONE ◽  
2019 ◽  
Vol 14 (1) ◽  
pp. e0210357 ◽  
Author(s):  
Kazuya Fujii ◽  
Hideyuki Doi ◽  
Shunsuke Matsuoka ◽  
Mariko Nagano ◽  
Hirotoshi Sato ◽  
...  
Keyword(s):  
Fish Community ◽  
Environmental Dna ◽  
Community Analysis ◽  
Dna Metabarcoding

scholarly journals Fish community assessment with eDNA metabarcoding: effects of sampling design and bioinformatic filtering

2017 ◽  
Vol 74 (9) ◽  
pp. 1362-1374 ◽  
Author(s):  
Nathan T. Evans ◽  
Yiyuan Li ◽  
Mark A. Renshaw ◽  
Brett P. Olds ◽  
Kristy Deiner ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Species Richness ◽  
Spatial Resolution ◽  
Spatial Patterns ◽  
Water Body ◽  
Fish Community ◽  
Sampling Design ◽  
Environmental Dna ◽  
Body Type ◽  
Multiple Samples

Species richness is a metric of biodiversity that represents the number of species present in a community. Traditional fisheries assessments that rely on capture of organisms often underestimate true species richness. Environmental DNA (eDNA) metabarcoding is an alternative tool that infers species richness by collecting and sequencing DNA present in the ecosystem. Our objective was to determine how spatial distribution of samples and “bioinformatic stringency” affected eDNA-metabarcoding estimates of species richness compared with capture-based estimates in a 2.2 ha reservoir. When bioinformatic criteria required species to be detected only in a single sample, eDNA metabarcoding detected all species captured with traditional methods plus an additional 11 noncaptured species. However, when we required species to be detected with multiple markers and in multiple samples, eDNA metabarcoding detected only seven of the captured species. Our analysis of the spatial patterns of species detection indicated that eDNA was distributed relatively homogeneously throughout the reservoir, except near the inflowing stream. We suggest that interpretation of eDNA metabarcoding data must consider the potential effects of water body type, spatial resolution, and bioinformatic stringency.

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