Integrating DNA metabarcoding and morphological analysis improves marine zooplankton biodiversity assessment

Marine copepod communities play crucial roles in ocean ecosystems. However, their accurate assessment remains challenging due to taxonomic complexities. This study combines morphological and DNA metabarcoding approaches to evaluate copepod diversity and community structure in the northern East China Sea. Zooplankton samples were collected from 10 stations along a coastal-offshore gradient in August 2019. Morphological analysis identified 34 species from 25 genera, while DNA metabarcoding detected 31 species from 20 genera. Both methods revealed distinct coastal and offshore assemblages, with Paracalanus parvus s.l. as the dominant species across all stations. A significant positive correlation was found between morphology-based individual counts and metabarcoding sequence reads (Spearman's Rho = 0.58, p < 0.001), improving at the genus level (Rho = 0.70, p < 0.001). Redundancy analysis revealed that salinity, temperature, and phytoplankton density significantly influenced copepod distribution. Although both approaches captured similar broad-scale patterns, they provided complementary insights into community structure. Morphological identification was more effective for detecting Cyclopoida diversity, whereas DNA metabarcoding had greater sensitivity for specific Calanoid species. This study underscores the value of integrating traditional and molecular methods for marine biodiversity assessment, especially in the context of global environmental changes.

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Publication Details

Journal
Scientific Reports
Published
2025-03-01
DOI
https://doi.org/10.1038/s41598-025-89684-9
Citations
4
Primary Topic
Environmental DNA in Biodiversity Studies
Type
article
Field-Weighted Citation Impact
6.87

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article

Integrating DNA metabarcoding and morphological analysis improves marine zooplankton biodiversity assessment

Chungoo Park, Ho Young Soh, Seongmin Cheon, Soyeon Kim
4 citations
Scientific Reports
Environmental DNA in Biodiversity Studies
6.87
article

Integrating DNA metabarcoding and morphological analysis improves marine zooplankton biodiversity assessment

Chungoo Park, Ho Young Soh, Seongmin Cheon, Soyeon Kim
article en
4 citations

Abstract

Marine copepod communities play crucial roles in ocean ecosystems. However, their accurate assessment remains challenging due to taxonomic complexities. This study combines morphological and DNA metabarcoding approaches to evaluate copepod diversity and community structure in the northern East China Sea. Zooplankton samples were collected from 10 stations along a coastal-offshore gradient in August 2019. Morphological analysis identified 34 species from 25 genera, while DNA metabarcoding detected 31 species from 20 genera. Both methods revealed distinct coastal and offshore assemblages, with Paracalanus parvus s.l. as the dominant species across all stations. A significant positive correlation was found between morphology-based individual counts and metabarcoding sequence reads (Spearman's Rho = 0.58, p < 0.001), improving at the genus level (Rho = 0.70, p < 0.001). Redundancy analysis revealed that salinity, temperature, and phytoplankton density significantly influenced copepod distribution. Although both approaches captured similar broad-scale patterns, they provided complementary insights into community structure. Morphological identification was more effective for detecting Cyclopoida diversity, whereas DNA metabarcoding had greater sensitivity for specific Calanoid species. This study underscores the value of integrating traditional and molecular methods for marine biodiversity assessment, especially in the context of global environmental changes.

Scientific ReportsVol. 15(1)
Chonnam National University (KR)
Chonnam National University
Life below water
Openalex Percentile: Top 4%
Environmental DNA in Biodiversity Studies
6.87
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Integrating DNA metabarcoding and morphological analysis improves marine zooplankton biodiversity assessment — Chungoo Park, Ho Young Soh, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS