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.
