Reliable, verifiable and efficient monitoring of biodiversity via metabarcoding

Authors

  • Yinqiu Ji,

    1. State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
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    • These authors contributed equally to this study.
  • Louise Ashton,

    1. Environmental Futures Centre and Griffith School of Environment, Griffith University, Nathan, Queensland, Australia
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    • These authors contributed equally to this study.
  • Scott M. Pedley,

    1. School of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich, Norfolk, UK
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    • These authors contributed equally to this study.
  • David P. Edwards,

    1. Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, New Jersey, USA
    2. Centre for Tropical Environmental and Sustainability Science (TESS), School of Marine and Tropical Biology, James Cook University, Cairns, Queensland, Australia
    3. Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, USA
    Current affiliation:
    1. Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK
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    • These authors contributed equally to this study.
  • Yong Tang,

    1. Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Meng La, Yunnan, China
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  • Akihiro Nakamura,

    1. Environmental Futures Centre and Griffith School of Environment, Griffith University, Nathan, Queensland, Australia
    2. Queensland Museum, South Brisbane, Queensland, Australia
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  • Roger Kitching,

    1. Environmental Futures Centre and Griffith School of Environment, Griffith University, Nathan, Queensland, Australia
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  • Paul M. Dolman,

    1. School of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich, Norfolk, UK
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  • Paul Woodcock,

    1. Institute of Integrative and Comparative Biology and Faculty of Biological Sciences, University of Leeds, Leeds, West Yorkshire, UK
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  • Felicity A. Edwards,

    1. Institute of Integrative and Comparative Biology and Faculty of Biological Sciences, University of Leeds, Leeds, West Yorkshire, UK
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  • Trond H. Larsen,

    1. The Betty and Gordon Moore Center for Ecosystem Science and Economics, Conservation International, Arlington, Virginia, USA
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  • Wayne W. Hsu,

    1. Department of Ecology, Evolution, and Environmental Biology, Columbia University, New York City, New York, USA
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  • Suzan Benedick,

    1. School of Sustainable Agriculture, Universiti Malaysia Sabah, Sandakan, Sabah, Malaysia
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  • Keith C. Hamer,

    1. Institute of Integrative and Comparative Biology and Faculty of Biological Sciences, University of Leeds, Leeds, West Yorkshire, UK
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  • David S. Wilcove,

    1. Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, New Jersey, USA
    2. Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, USA
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  • Catharine Bruce,

    1. School of Biological Sciences, University of East Anglia, Norwich Research Park, Norwich, Norfolk, UK
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  • Xiaoyang Wang,

    1. State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
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  • Taal Levi,

    1. Cary Institute of Ecosystem Studies, Millbrook, New York, USA
    2. Department of Biology, University of Florida, Gainesville, Florida
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  • Martin Lott,

    1. School of Computing Sciences, University of East Anglia, Norwich Research Park, Norwich, Norfolk, NR47TJ, UK
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  • Brent C. Emerson,

    1. Island Ecology and Evolution Research Group, IPNA-CSIC, Tenerife, Canary Islands, Spain
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  • Douglas W. Yu

    Corresponding author
    1. State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
    2. School of Biological Sciences, University of East Anglia, Norwich Research Park, Norwich, Norfolk, UK
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Abstract

To manage and conserve biodiversity, one must know what is being lost, where, and why, as well as which remedies are likely to be most effective. Metabarcoding technology can characterise the species compositions of mass samples of eukaryotes or of environmental DNA. Here, we validate metabarcoding by testing it against three high-quality standard data sets that were collected in Malaysia (tropical), China (subtropical) and the United Kingdom (temperate) and that comprised 55,813 arthropod and bird specimens identified to species level with the expenditure of 2,505 person-hours of taxonomic expertise. The metabarcode and standard data sets exhibit statistically correlated alpha- and beta-diversities, and the two data sets produce similar policy conclusions for two conservation applications: restoration ecology and systematic conservation planning. Compared with standard biodiversity data sets, metabarcoded samples are taxonomically more comprehensive, many times quicker to produce, less reliant on taxonomic expertise and auditable by third parties, which is essential for dispute resolution.

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