論文

査読有り
2020年10月6日

Evaluation of fish biodiversity in estuaries using environmental DNA metabarcoding

PLOS ONE
  • Hyojin Ahn
  • ,
  • Manabu Kume
  • ,
  • Yuki Terashima
  • ,
  • Feng Ye
  • ,
  • Satoshi Kameyama
  • ,
  • Masaki Miya
  • ,
  • Yoh Yamashita
  • ,
  • Akihide Kasai

15
10
開始ページ
e0231127
終了ページ
e0231127
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1371/journal.pone.0231127
出版者・発行元
Public Library of Science (PLoS)

Biodiversity is an important parameter for the evaluation of the extant environmental conditions. Here, we used environmental DNA (eDNA) metabarcoding to investigate fish biodiversity in five different estuaries in Japan. Water samples for eDNA were collected from river mouths and adjacent coastal areas of two estuaries with high degrees of development (the Tama and Miya Rivers) and three estuaries with relatively low degrees of development (the Aka, Takatsu, and Sendai Rivers). A total of 182 fish species across 67 families were detected. Among them, 11 species occurred in all the rivers studied. Rare fishes including endangered species were successfully detected in rich natural rivers. Biodiversity was the highest in the Sendai River and lowest in the Tama River, reflecting the degree of human development along each river. Even though nutrient concentration was low in both the Aka and Sendai Rivers, the latter exhibited greater diversity, including many tropical or subtropical species, owing to its more southern location. Species composition detected by eDNA varied among rivers, reflecting the distribution and migration of fishes. Our results are in accordance with the ecology of each fish species and environmental conditions of each river.

リンク情報
DOI
https://doi.org/10.1371/journal.pone.0231127
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000578473000010&DestApp=WOS_CPL
URL
https://dx.plos.org/10.1371/journal.pone.0231127
ID情報
  • DOI : 10.1371/journal.pone.0231127
  • ISSN : 1932-6203
  • eISSN : 1932-6203
  • Web of Science ID : WOS:000578473000010

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