Zooplankton diversity monitoring strategy for the urban coastal region using metabarcoding analysis

Abstract

Marine ecosystems in urban coastal areas are exposed to many risks due to human ac­ tivity. Thus, long-term and continuous monitoring of zooplankton diversity is necessary. High-throughput DNA metabarcoding has gained recognition as an efficient and highly sensitive approach to accurately describing the species diversity of marine zooplankton as­ semblages. In this study, We collected 30 zooplankton samples at about 2-week intervals for 1 year and monitored zooplankton diversity by DNA metabarcoding of a cytochrome c oxidase subunit I sequence. “Common” and “total” zooplankton data were compared to assess which indicator was more suitable for monitoring a broad and long-term coastal environ­ ment. Furthermore, we compared our results with the national list of marine species (NLMS) to identify candidates that pose a potential threat as early invader species or non-indige- nous species (NIS). Zooplankton diversity was lowest in spring (April) and highest in autumn (September). The cluster analysis divided the zooplankton community into four groups* spring, summer, late summer-autumn, and winter, showing a typical four seasons pattern. Of the “total” and “common” zooplankton, we assigned 267 and 64 taxa, respectively. The cluster struc此ire and seasonal diversity change pattern were rough when only the “common” zooplankton was used. In comparison, when the “total” zooplankton was used, clustering was more pronounced. Furthermore, against NLMS, it enabled the detection of 46 species that could be potential candidates for early invaders or NIS, which may threaten future ecosystem maintenance. Our study examined how to maximize the benefits of metabar­ coding for monitoring zooplankton diversity in urban coastal areas. The results suggest that to take full advantage of metabarcoding when monitoring a zooplankton community, it is necessary to carefully investigate potential ecosystem threats (early invaders or NIS) through sufficient curation rather than disregarding low-abundance operational taxonomic units.