Calibrating Environmental DNA Metabarcoding to Conventional Surveys for Measuring Fish Species Richness
The ability to properly identify species present in a landscape is foundational to ecology and essential for natural resource management and conservation. However, many species are often unaccounted for due to ineffective direct capture and visual surveys, especially in aquatic environments. Environ...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-08-01
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| Series: | Frontiers in Ecology and Evolution |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fevo.2020.00276/full |
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| author | Mary E. McElroy Terra L. Dressler Georgia C. Titcomb Emily A. Wilson Kristy Deiner Tom L. Dudley Erika J. Eliason Nathan T. Evans Steven D. Gaines Kevin D. Lafferty Kevin D. Lafferty Gary A. Lamberti Yiyuan Li David M. Lodge Milton S. Love Andrew R. Mahon Michael E. Pfrender Mark A. Renshaw Kimberly A. Selkoe Christopher L. Jerde |
| author_facet | Mary E. McElroy Terra L. Dressler Georgia C. Titcomb Emily A. Wilson Kristy Deiner Tom L. Dudley Erika J. Eliason Nathan T. Evans Steven D. Gaines Kevin D. Lafferty Kevin D. Lafferty Gary A. Lamberti Yiyuan Li David M. Lodge Milton S. Love Andrew R. Mahon Michael E. Pfrender Mark A. Renshaw Kimberly A. Selkoe Christopher L. Jerde |
| author_sort | Mary E. McElroy |
| collection | DOAJ |
| description | The ability to properly identify species present in a landscape is foundational to ecology and essential for natural resource management and conservation. However, many species are often unaccounted for due to ineffective direct capture and visual surveys, especially in aquatic environments. Environmental DNA metabarcoding is an approach that overcomes low detection probabilities and should consequently enhance estimates of biodiversity and its proxy, species richness. Here, we synthesize 37 studies in natural aquatic systems to compare species richness estimates for bony fish between eDNA metabarcoding and conventional methods, such as nets, visual census, and electrofishing. In freshwater systems with fewer than 100 species, we found eDNA metabarcoding detected more species than conventional methods. Using multiple genetic markers further increased species richness estimates with eDNA metabarcoding. For more diverse freshwater systems and across marine systems, eDNA metabarcoding reported similar values of species richness to conventional methods; however, more studies are needed in these environments to better evaluate relative performance. In systems with greater biodiversity, eDNA metabarcoding will require more populated reference databases, increased sampling effort, and multi-marker assays to ensure robust species richness estimates to further validate the approach. eDNA metabarcoding is reliable and provides a path for broader biodiversity assessments that can outperform conventional methods for estimating species richness. |
| first_indexed | 2024-12-11T02:59:02Z |
| format | Article |
| id | doaj.art-20273f73c7e64948b40f65624ecff93c |
| institution | Directory Open Access Journal |
| issn | 2296-701X |
| language | English |
| last_indexed | 2024-12-11T02:59:02Z |
| publishDate | 2020-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Ecology and Evolution |
| spelling | doaj.art-20273f73c7e64948b40f65624ecff93c2022-12-22T01:23:05ZengFrontiers Media S.A.Frontiers in Ecology and Evolution2296-701X2020-08-01810.3389/fevo.2020.00276559677Calibrating Environmental DNA Metabarcoding to Conventional Surveys for Measuring Fish Species RichnessMary E. McElroy0Terra L. Dressler1Georgia C. Titcomb2Emily A. Wilson3Kristy Deiner4Tom L. Dudley5Erika J. Eliason6Nathan T. Evans7Steven D. Gaines8Kevin D. Lafferty9Kevin D. Lafferty10Gary A. Lamberti11Yiyuan Li12David M. Lodge13Milton S. Love14Andrew R. Mahon15Michael E. Pfrender16Mark A. Renshaw17Kimberly A. Selkoe18Christopher L. Jerde19Interdepartmental Graduate Program in Marine Science, University of California, Santa Barbara, Santa Barbara, CA, United StatesDepartment of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, Santa Barbara, CA, United StatesDepartment of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, Santa Barbara, CA, United StatesBiology Department, Bakersfield College, Bakersfield, CA, United StatesInstitute of Biogeochemistry and Pollutant Dynamics, ETH Zürich, Zurich, SwitzerlandMarine Science Institute, University of California, Santa Barbara, Santa Barbara, CA, United StatesDepartment of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, Santa Barbara, CA, United StatesU.S. Fish and Wildlife Service, Carterville Fish and Wildlife Conservation Office, Wilmington, IL, United StatesBren School of Environmental Science and Management, University of California, Santa Barbara, Santa Barbara, CA, United StatesMarine Science Institute, University of California, Santa Barbara, Santa Barbara, CA, United StatesWestern Ecological Research Center, United States Geological Survey at Marine Science Institute, University of California, Santa Barbara, Santa Barbara, CA, United StatesDepartment of Biological Sciences, University of Notre Dame, Notre Dame, IN, United States0Department of Integrative Biology, The University of Texas at Austin, Austin, TX, United States1Department of Ecology and Evolutionary Biology, Cornell Atkinson Center for a Sustainable Future, Cornell University, Ithaca, NY, United StatesMarine Science Institute, University of California, Santa Barbara, Santa Barbara, CA, United States2Department of Biology, Central Michigan University, Mount Pleasant, MI, United StatesDepartment of Biological Sciences, University of Notre Dame, Notre Dame, IN, United States3Oceanic Institute, Hawai’i Pacific University, Waimanalo, HI, United States4National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, Santa Barbara, CA, United StatesMarine Science Institute, University of California, Santa Barbara, Santa Barbara, CA, United StatesThe ability to properly identify species present in a landscape is foundational to ecology and essential for natural resource management and conservation. However, many species are often unaccounted for due to ineffective direct capture and visual surveys, especially in aquatic environments. Environmental DNA metabarcoding is an approach that overcomes low detection probabilities and should consequently enhance estimates of biodiversity and its proxy, species richness. Here, we synthesize 37 studies in natural aquatic systems to compare species richness estimates for bony fish between eDNA metabarcoding and conventional methods, such as nets, visual census, and electrofishing. In freshwater systems with fewer than 100 species, we found eDNA metabarcoding detected more species than conventional methods. Using multiple genetic markers further increased species richness estimates with eDNA metabarcoding. For more diverse freshwater systems and across marine systems, eDNA metabarcoding reported similar values of species richness to conventional methods; however, more studies are needed in these environments to better evaluate relative performance. In systems with greater biodiversity, eDNA metabarcoding will require more populated reference databases, increased sampling effort, and multi-marker assays to ensure robust species richness estimates to further validate the approach. eDNA metabarcoding is reliable and provides a path for broader biodiversity assessments that can outperform conventional methods for estimating species richness.https://www.frontiersin.org/article/10.3389/fevo.2020.00276/fullbland-altman analysisLin’s concordance correlation coefficienthigh-throughput sequencingmarinefreshwatereDNA |
| spellingShingle | Mary E. McElroy Terra L. Dressler Georgia C. Titcomb Emily A. Wilson Kristy Deiner Tom L. Dudley Erika J. Eliason Nathan T. Evans Steven D. Gaines Kevin D. Lafferty Kevin D. Lafferty Gary A. Lamberti Yiyuan Li David M. Lodge Milton S. Love Andrew R. Mahon Michael E. Pfrender Mark A. Renshaw Kimberly A. Selkoe Christopher L. Jerde Calibrating Environmental DNA Metabarcoding to Conventional Surveys for Measuring Fish Species Richness Frontiers in Ecology and Evolution bland-altman analysis Lin’s concordance correlation coefficient high-throughput sequencing marine freshwater eDNA |
| title | Calibrating Environmental DNA Metabarcoding to Conventional Surveys for Measuring Fish Species Richness |
| title_full | Calibrating Environmental DNA Metabarcoding to Conventional Surveys for Measuring Fish Species Richness |
| title_fullStr | Calibrating Environmental DNA Metabarcoding to Conventional Surveys for Measuring Fish Species Richness |
| title_full_unstemmed | Calibrating Environmental DNA Metabarcoding to Conventional Surveys for Measuring Fish Species Richness |
| title_short | Calibrating Environmental DNA Metabarcoding to Conventional Surveys for Measuring Fish Species Richness |
| title_sort | calibrating environmental dna metabarcoding to conventional surveys for measuring fish species richness |
| topic | bland-altman analysis Lin’s concordance correlation coefficient high-throughput sequencing marine freshwater eDNA |
| url | https://www.frontiersin.org/article/10.3389/fevo.2020.00276/full |
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