Assessment of Fish Diversity in the Ma'an Archipelago Special Protected Area Using Environmental DNA

被引:4
作者
Wang, Yuqing [1 ]
Li, Xunmeng [1 ,2 ]
Zhao, Xu [1 ,2 ]
Chen, Jianqu [1 ]
Wang, Zhenhua [1 ,2 ]
Chen, Lili [1 ]
Zhang, Shouyu [1 ,2 ]
Wang, Kai [1 ,2 ]
机构
[1] Shanghai Ocean Univ, Coll Marine Ecol & Environm, Shanghai 201306, Peoples R China
[2] Shanghai Ocean Univ, Engn Technol Res Ctr Marine Ranching, Shanghai 201306, Peoples R China
来源
BIOLOGY-BASEL | 2022年 / 11卷 / 12期
基金
英国科研创新办公室; 中国国家自然科学基金;
关键词
biodiversity; environmental DNA; island ecosystem; Ma'an Archipelago; special protected area; MULTI-MESH GILLNETS; ROCKY REEF HABITAT; ARTIFICIAL REEFS; COMMUNITY; ECOSYSTEM;
D O I
10.3390/biology11121832
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Simple Summary With the development of molecular techniques, environmental DNA (eDNA) methods are increasingly being applied to assess marine fish biodiversity. Fish biodiversity survey methods have been difficult to standardize due to the diversity and complexity of reef habitats. Traditional surveys can damage island ecosystems. A rational method for surveying fish biodiversity in different habitats is urgently needed. This study aimed to investigate the practical validity of the eDNA method for evaluating the fish composition and diversity in different habitats. Additionally, compared with traditional surveys, the eDNA method includes the same results, but also includes species that would not be caught by traditional surveys due to the technical limitations of traditional surveys. This is significant for continuous biodiversity monitoring and management in protected areas. This study aimed to investigate the practical validity of the environmental DNA (eDNA) method for evaluating fish composition and diversity in different habitats. We evaluated the fish composition and diversity characteristics of seven different habitats in the Ma'an Archipelago Special Protected Area in April 2020. The results showed that a total of twenty-seven species of fishes belonging to six orders, eighteen families, and twenty-three genera of the Actinopterygii were detected in the marine waters of the Ma'an Archipelago Special Protected Area. The dominant species in each habitat were Larimichthys crocea, Paralichthys olivaceus, and Lateolabrax maculatus. The mussel culture area had the highest number of species, with 19 fish species, while the offshore bulk load shedding platform had the lowest number of species, with 12 fish species. The rest of the habitat was not significantly different. The results showed that the mussel culture area had the highest diversity index (average value of 2.352 +/- 0.161), and the offshore bulk load shedding platform had the lowest diversity index (average value of 1.865 +/- 0.127); the rest of the habitat diversity indices did not differ significantly. A comparison with historical surveys showed that the eDNA technique can detect species not collected by traditional methods such as gillnets and trawls. Our study demonstrates the role of eDNA technology in obtaining fish diversity in different habitats and provides a theoretical basis for the continuous monitoring and management of fish biodiversity in protected areas.
引用
收藏
页数:17
相关论文
共 50 条
  • [31] Assessment of littoral algal diversity from the northern Gulf of Mexico using environmental DNA metabarcoding
    Bombin, Sergei
    Wysor, Brian
    Lopez-Bautista, Juan M.
    JOURNAL OF PHYCOLOGY, 2021, 57 (01) : 269 - 278
  • [32] Stream environmental conditions are homogenised outside a protected area, but fungal beta diversity remains unchanged
    Scoarize, Matheus Maximilian Ratz
    Pinha, Gisele Daiane
    Pazianoto, Laryssa Helena Ribeiro
    Benedito, Evanilde
    MYCOLOGICAL PROGRESS, 2024, 23 (01)
  • [33] Study on Fish Species Diversity in the Pingzhai Reservoir Based on Environmental DNA Technology
    Yuan, Jingjing
    Wen, Jing
    Kong, Qiuhong
    Zhou, Xianjun
    FISHES, 2024, 9 (10)
  • [34] Quantification of mesocosm fish and amphibian species diversity via environmental DNA metabarcoding
    Evans, Nathan T.
    Olds, Brett P.
    Renshaw, Mark A.
    Turner, Cameron R.
    Li, Yiyuan
    Jerde, Christopher L.
    Mahon, Andrew R.
    Pfrender, Michael E.
    Lamberti, Gary A.
    Lodge, David M.
    MOLECULAR ECOLOGY RESOURCES, 2016, 16 (01) : 29 - 41
  • [35] Mapping differences in mammalian distributions and diversity using environmental DNA from rivers
    Broadhurst, Holly A.
    Gregory, Luke M.
    Bleakley, Emma K.
    Perkins, Joseph C.
    Lavin, Jenna, V
    Bolton, Polly
    Browett, Samuel S.
    Howe, Claire, V
    Singleton, Natalie
    Tansley, Darren
    Sales, Naiara Guimaraes
    McDevitt, Allan D.
    SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 801
  • [36] Assessing the impacts of aquaculture on local fish communities using environmental DNA metabarcoding analysis
    Suzuki, Shota
    Otomo, Yuri
    Dazai, Akihiro
    Abe, Takuzo
    Kondoh, Michio
    ENVIRONMENTAL DNA, 2024, 6 (03):
  • [37] DNA barcoding for the assessment of marine and coastal fish diversity from the Coast of Mozambique
    Muhala, Valdemiro
    Guimaraes-Costa, Auryceia
    Macate, Isadola Eusebio
    Rabelo, Luan Pinto
    Bessa-Silva, Adam Rick
    Watanabe, Luciana
    dos Santos, Gisele Damasceno
    Sambora, Luisa
    Vallinoto, Marcelo
    Sampaio, Iracilda
    PLOS ONE, 2024, 19 (02):
  • [38] Using Optimal Environmental DNA Method to Improve the Fish Diversity Survey-From Laboratory to Aquatic Life Reserve
    Li, Wen-Pan
    Liu, Zi-Fang
    Guo, Tong
    Chen, He
    Xie, Xin
    WATER, 2021, 13 (11)
  • [39] Functional diversity metrics detect spatio-temporal changes in the fish communities of a Caribbean marine protected area
    Rincon-Diaz, Martha Patricia
    Pittman, Simon J.
    Arismendi, Ivan
    Heppell, Selina S.
    ECOSPHERE, 2018, 9 (10):
  • [40] Environmental DNA enhances comprehension of the spatial and temporal dynamics of fish diversity in a coastal lagoon
    Banchi, Elisa
    Bettoso, Nicola
    Borme, Diego
    Stefanni, Sergio
    Tirelli, Valentina
    ESTUARINE COASTAL AND SHELF SCIENCE, 2024, 304