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 1.4âM 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.
Upscaling biodiversity monitoring: Metabarcoding estimates 31,846 insect species from Malaise traps across Germany.
阅读:4
作者:Buchner Dominik, Sinclair James S, Ayasse Manfred, Beermann Arne J, Buse Jörn, Dziock Frank, Enss Julian, Frenzel Mark, Hörren Thomas, Li Yuanheng, Monaghan Michael T, Morkel Carsten, Müller Jörg, Pauls Steffen U, Richter Ronny, Scharnweber Tobias, Sorg Martin, Stoll Stefan, Twietmeyer Sönke, Weisser Wolfgang W, Wiggering Benedikt, Wilmking Martin, Zotz Gerhard, Gessner Mark O, Haase Peter, Leese Florian
| 期刊: | Molecular Ecology Resources | 影响因子: | 5.500 |
| 时间: | 2025 | 起止号: | 2025 Jan;25(1):e14023 |
| doi: | 10.1111/1755-0998.14023 | ||
特别声明
1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。
2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。
3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。
4、投稿及合作请联系:info@biocloudy.com。
