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Environmental DNA gives comparable results to morphology-based indices of macroinvertebrates in a large-scale ecological assessment
Anthropogenic activities are changing the state of ecosystems worldwide, affecting community composition and often resulting in loss of biodiversity. Rivers are among the most impacted ecosystems. Recording their current state with regular biomonitoring is important to assess the future trajectory o...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8454941/ https://www.ncbi.nlm.nih.gov/pubmed/34547039 http://dx.doi.org/10.1371/journal.pone.0257510 |
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author | Brantschen, Jeanine Blackman, Rosetta C. Walser, Jean-Claude Altermatt, Florian |
author_facet | Brantschen, Jeanine Blackman, Rosetta C. Walser, Jean-Claude Altermatt, Florian |
author_sort | Brantschen, Jeanine |
collection | PubMed |
description | Anthropogenic activities are changing the state of ecosystems worldwide, affecting community composition and often resulting in loss of biodiversity. Rivers are among the most impacted ecosystems. Recording their current state with regular biomonitoring is important to assess the future trajectory of biodiversity. Traditional monitoring methods for ecological assessments are costly and time-intensive. Here, we compared monitoring of macroinvertebrates based on environmental DNA (eDNA) sampling with monitoring based on traditional kick-net sampling to assess biodiversity patterns at 92 river sites covering all major Swiss river catchments. From the kick-net community data, a biotic index (IBCH) based on 145 indicator taxa had been established. The index was matched by the taxonomically annotated eDNA data by using a machine learning approach. Our comparison of diversity patterns only uses the zero-radius Operational Taxonomic Units assigned to the indicator taxa. Overall, we found a strong congruence between both methods for the assessment of the total indicator community composition (gamma diversity). However, when assessing biodiversity at the site level (alpha diversity), the methods were less consistent and gave complementary data on composition. Specifically, environmental DNA retrieved significantly fewer indicator taxa per site than the kick-net approach. Importantly, however, the subsequent ecological classification of rivers based on the detected indicators resulted in similar biotic index scores for the kick-net and the eDNA data that was classified using a random forest approach. The majority of the predictions (72%) from the random forest classification resulted in the same river status categories as the kick-net approach. Thus, environmental DNA validly detected indicator communities and, combined with machine learning, provided reliable classifications of the ecological state of rivers. Overall, while environmental DNA gives complementary data on the macroinvertebrate community composition compared to the kick-net approach, the subsequently calculated indices for the ecological classification of river sites are nevertheless directly comparable and consistent. |
format | Online Article Text |
id | pubmed-8454941 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-84549412021-09-22 Environmental DNA gives comparable results to morphology-based indices of macroinvertebrates in a large-scale ecological assessment Brantschen, Jeanine Blackman, Rosetta C. Walser, Jean-Claude Altermatt, Florian PLoS One Research Article Anthropogenic activities are changing the state of ecosystems worldwide, affecting community composition and often resulting in loss of biodiversity. Rivers are among the most impacted ecosystems. Recording their current state with regular biomonitoring is important to assess the future trajectory of biodiversity. Traditional monitoring methods for ecological assessments are costly and time-intensive. Here, we compared monitoring of macroinvertebrates based on environmental DNA (eDNA) sampling with monitoring based on traditional kick-net sampling to assess biodiversity patterns at 92 river sites covering all major Swiss river catchments. From the kick-net community data, a biotic index (IBCH) based on 145 indicator taxa had been established. The index was matched by the taxonomically annotated eDNA data by using a machine learning approach. Our comparison of diversity patterns only uses the zero-radius Operational Taxonomic Units assigned to the indicator taxa. Overall, we found a strong congruence between both methods for the assessment of the total indicator community composition (gamma diversity). However, when assessing biodiversity at the site level (alpha diversity), the methods were less consistent and gave complementary data on composition. Specifically, environmental DNA retrieved significantly fewer indicator taxa per site than the kick-net approach. Importantly, however, the subsequent ecological classification of rivers based on the detected indicators resulted in similar biotic index scores for the kick-net and the eDNA data that was classified using a random forest approach. The majority of the predictions (72%) from the random forest classification resulted in the same river status categories as the kick-net approach. Thus, environmental DNA validly detected indicator communities and, combined with machine learning, provided reliable classifications of the ecological state of rivers. Overall, while environmental DNA gives complementary data on the macroinvertebrate community composition compared to the kick-net approach, the subsequently calculated indices for the ecological classification of river sites are nevertheless directly comparable and consistent. Public Library of Science 2021-09-21 /pmc/articles/PMC8454941/ /pubmed/34547039 http://dx.doi.org/10.1371/journal.pone.0257510 Text en © 2021 Brantschen et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Brantschen, Jeanine Blackman, Rosetta C. Walser, Jean-Claude Altermatt, Florian Environmental DNA gives comparable results to morphology-based indices of macroinvertebrates in a large-scale ecological assessment |
title | Environmental DNA gives comparable results to morphology-based indices of macroinvertebrates in a large-scale ecological assessment |
title_full | Environmental DNA gives comparable results to morphology-based indices of macroinvertebrates in a large-scale ecological assessment |
title_fullStr | Environmental DNA gives comparable results to morphology-based indices of macroinvertebrates in a large-scale ecological assessment |
title_full_unstemmed | Environmental DNA gives comparable results to morphology-based indices of macroinvertebrates in a large-scale ecological assessment |
title_short | Environmental DNA gives comparable results to morphology-based indices of macroinvertebrates in a large-scale ecological assessment |
title_sort | environmental dna gives comparable results to morphology-based indices of macroinvertebrates in a large-scale ecological assessment |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8454941/ https://www.ncbi.nlm.nih.gov/pubmed/34547039 http://dx.doi.org/10.1371/journal.pone.0257510 |
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