Abstract
AbstractMitigating ongoing losses of insects and their key functions (e.g., pollination) requires accurately tracking large-scale and long-term community changes. However, doing so has been notoriously hindered by uniquely high insect species diversity that requires prohibitively high investments of time, funding, and taxonomic expertise. Here, we show that these concerns can be addressed through a comprehensive, scalable and cost-efficient DNA metabarcoding workflow. We use 1,815 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, labor and maintenance. With on average 1.4M sequence reads per sample we uncovered 10,803 validated insect species, of which 83.9% were represented by a single OTU. We estimated another 21,403 plausible species, which likely 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.
Publisher
Cold Spring Harbor Laboratory
Cited by
5 articles.
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