Biodiversity Data Journal (Dec 2023)

Assessment of the DNA barcode libraries for the study of the poorly-known rove beetle (Staphylinidae) fauna of West Siberia

  • Valeria Krivosheeva,
  • Alexey Solodovnikov,
  • Aleksandr Shulepov,
  • Darya Semerikova,
  • Anastasiya Ivanova,
  • Maria Salnitska

DOI
https://doi.org/10.3897/BDJ.11.e115477
Journal volume & issue
Vol. 11
pp. 1 – 17

Abstract

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Staphylinidae, or rove beetles, are one of the mega-diverse and abundant families of the ground-living terrestrial arthropods that is taxonomically poorly known even in the regions adjacent to Europe where the fauna has been investigated for the longest time. Since DNA barcoding is a tool to accelerate biodiversity research, here we explored if the currently-available COI barcode libraries are representative enough for the study of rove beetles of West Siberia. This is a vast region adjacent to Europe with poorly-known fauna of rove beetles and from where not a single DNA barcode has hitherto been produced for Staphylinidae. First, we investigated the faunal similarity between the rove beetle faunas of the climatically compatible West Siberia in Asia, Fennoscandia in Europe and Canada and Alaska in North America. Second, we investigated barcodes available for Staphylinidae from the latter two regions in BOLD and GenBank, the world's largest DNA barcode libraries. We conclude that the rather different rove beetle faunas of Fennoscandia, on the one hand and Canada and Alaska on the other hand, are well covered in both barcode libraries that complement each other. We also find that even without any barcodes originating from specimens collected in West Siberia, this coverage is helpful for the study of rove beetles there due to the significant number of widespread species shared between West Siberia and Fennoscandia and due to the even larger number of shared genera amongst all three investigated regions. For the first time, we compiled a literature-based checklist for 726 species of the West Siberian Staphylinidae supplemented by their occurrence dataset submitted to GBIF. Our script written for mining unique (i.e. not redundant) barcodes for a given geographic area across global libraries is made available here and can be adopted for any other regions.

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