Upscaling biodiversity monitoring: Metabarcoding estimates 31,846 insect species from Malaise traps across Germany

Mitigating ongoing losses of insects and their key functions (e.g. pollination) requires tracking large-scale and long-term community changes. However, doing so has been hindered by the high diversity of insect species that requires prohibitively high investments of time, funding and taxonomic expertise when addressed with conventional tools. Here, we show that these concerns can be addressed through a comprehensive, scalable and cost-efficient DNA metabarcoding workflow. We use 1815 samples from 75 Malaise traps across Germany from 2019 and 2020 to demonstrate how metabarcoding can be incorporated into large-scale insect monitoring networks for less than 50 € per sample, including supplies, labour and maintenance. We validated the detected species using two publicly available databases (GBOL and GBIF) and the judgement of taxonomic experts. With an average of 1.4 M sequence reads per sample we uncovered 10,803 validated insect species, of which 83.9% were represented by a single Operational Taxonomic Unit (OTU). We estimated another 21,043 plausible species, which we argue either lack a reference barcode or are undescribed. The total of 31,846 species is similar to the number of insect species known for Germany (~35,500). Because Malaise traps capture only a subset of insects, our approach identified many species likely unknown from Germany or new to science. Our reproducible workflow (~80% OTU-similarity among years) provides a blueprint for large-scale biodiversity monitoring of insects and other biodiversity components in near real time.

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Publication Details

Journal
Molecular Ecology Resources
Published
2024-10-04
DOI
https://doi.org/10.1111/1755-0998.14023
Citations
39
Primary Topic
Environmental DNA in Biodiversity Studies
Type
article
Field-Weighted Citation Impact
17.90
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article

Upscaling biodiversity monitoring: Metabarcoding estimates 31,846 insect species from Malaise traps across Germany

James S. Sinclair, Peter Haase, Martin Sorg, Mark Frenzel et al.
39 citations
Molecular Ecology Resources
Environmental DNA in Biodiversity Studies
17.90
article

Upscaling biodiversity monitoring: Metabarcoding estimates 31,846 insect species from Malaise traps across Germany

James S. Sinclair, Peter Haase, Martin Sorg, Mark Frenzel, Stefan Stoll, Gerhard Zotz, Carsten Morkel, Arne J. Beermann, Yuanheng Li, Frank Dziock, Florian Leese, Martin Wilmking, Julian Enß, Dominik Buchner, Tobias Scharnweber, Steffen U. Pauls, Mark O. Gessner, Jörg C. Müller, Sönke Twietmeyer, Thomas Hörren, Ronny Richter, Michael T. Monaghan, Manfred Ayasse, Jörn Buse, Wolfgang W. Weisser, Benedikt Wiggering
article en
39 citations

Abstract

Mitigating ongoing losses of insects and their key functions (e.g. pollination) requires tracking large-scale and long-term community changes. However, doing so has been hindered by the high diversity of insect species that requires prohibitively high investments of time, funding and taxonomic expertise when addressed with conventional tools. Here, we show that these concerns can be addressed through a comprehensive, scalable and cost-efficient DNA metabarcoding workflow. We use 1815 samples from 75 Malaise traps across Germany from 2019 and 2020 to demonstrate how metabarcoding can be incorporated into large-scale insect monitoring networks for less than 50 € per sample, including supplies, labour and maintenance. We validated the detected species using two publicly available databases (GBOL and GBIF) and the judgement of taxonomic experts. With an average of 1.4 M sequence reads per sample we uncovered 10,803 validated insect species, of which 83.9% were represented by a single Operational Taxonomic Unit (OTU). We estimated another 21,043 plausible species, which we argue either lack a reference barcode or are undescribed. The total of 31,846 species is similar to the number of insect species known for Germany (~35,500). Because Malaise traps capture only a subset of insects, our approach identified many species likely unknown from Germany or new to science. Our reproducible workflow (~80% OTU-similarity among years) provides a blueprint for large-scale biodiversity monitoring of insects and other biodiversity components in near real time.

Molecular Ecology ResourcesVol. 25(1)
Carl von Ossietzky Universität Oldenburg (DE), Helmholtz Centre for Environmental Research (DE), Trier University of Applied Sciences (DE), Universität Ulm (DE), Justus-Liebig-Universität Gießen (DE), University of Würzburg (DE), Bavarian Forest National Park (DE), German Centre for Integrative Biodiversity Research (DE), Senckenberg Research Institute and Natural History Museum Frankfurt/M (DE), Universität Greifswald (DE), Leibniz Institute of Freshwater Ecology and Inland Fisheries (DE), LOEWE Centre for Translational Biodiversity Genomics (DE), Hochschule für Technik und Wirtschaft Dresden – University of Applied Sciences (DE), Technische Universität Berlin (DE), University of Duisburg-Essen (DE), Technical University of Munich (DE), Freie Universität Berlin (DE), Leipzig University (DE)
Decent work and economic growth
Openalex Percentile: Top 0%
Environmental DNA in Biodiversity Studies
17.90
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