Supervised machine learning outperforms taxonomy-based environmental DNA metabarcoding applied to biomonitoring

Molecular Ecology Resources
Tristan CordierJan Pawlowski

Abstract

Biodiversity monitoring is the standard for environmental impact assessment of anthropogenic activities. Several recent studies showed that high-throughput amplicon sequencing of environmental DNA (eDNA metabarcoding) could overcome many limitations of the traditional morphotaxonomy-based bioassessment. Recently, we demonstrated that supervised machine learning (SML) can be used to predict accurate biotic indices values from eDNA metabarcoding data, regardless of the taxonomic affiliation of the sequences. However, it is unknown to which extent the accuracy of such models depends on taxonomic resolution of molecular markers or how SML compares with metabarcoding approaches targeting well-established bioindicator species. In this study, we address these issues by training predictive models upon five different ribosomal bacterial and eukaryotic markers and measuring their performance to assess the environmental impact of marine aquaculture on independent data sets. Our results show that all tested markers are yielding accurate predictive models and that they all outperform the assessment relying solely on taxonomically assigned sequences. Remarkably, we did not find any significant difference in the performance of the models buil...Continue Reading

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Citations

Aug 12, 2020·Molecular Ecology·Luna M van der Loos, Reindert Nijland
Sep 14, 2020·Molecular Ecology·Gentile Francesco FicetolaPierre Taberlet
Jan 13, 2021·Proceedings of the National Academy of Sciences of the United States of America·Toke T HøyeJenni Raitoharju
Mar 22, 2020·The Science of the Total Environment·Maria João FeioSalomé F P Almeida
Mar 9, 2021·Computational and Structural Biotechnology Journal·Ryan B Ghannam, Stephen M Techtmann
Jun 28, 2021·Molecular Ecology·Jan PawlowskiPierre Taberlet
Jul 9, 2021·Molecular Ecology Resources·Zachary GoldPaul H Barber
May 11, 2019·Environmental Science & Technology·Jacopo AguzziJoan B Company

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