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Sampling and curation of rove beetles (Insecta, Coleoptera, Staphylinidae) for comprehensive and DNA-grade collections to enhance biodiversity exploration in Northern Eurasia

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Abstract Staphylinidae beetles form a major portion of terrestrial biodiversity globally and, in particular, in Northern Eurasia, a large area with a historically better known north temperate, subarctic and arctic… Click to show full abstract

Abstract Staphylinidae beetles form a major portion of terrestrial biodiversity globally and, in particular, in Northern Eurasia, a large area with a historically better known north temperate, subarctic and arctic biota. However, even here, rove beetles remain amongst the so-called “dark taxa” with a high fraction of taxonomically unknown lineage diversity. The propagation of DNA-based technologies in systematic entomology in recent decades has brought new opportunities for biodiversity exploration, true also for Staphylinidae. Simultaneously, new methods have revealed limitations of specimens sampled and curated by traditional practices, as existing legacy collections, whether institutional or private, unfortunately do not always qualify as a source of DNA-grade material. In addition, both legacy and newly-collected DNA-grade material of Staphylinidae remain highly biased towards Central Europe, a region with a traditionally well-developed scientific infrastructure and long-established culture for the maintenance of entomological collections. To increase the degree of biodiversity knowledge for our target organismal group across the globe, efficient sampling of DNA-grade material and, in particular, the development of comprehensive local collections in under-studied regions is highly desirable. To facilitate that, here we provide a practical guide for collecting and curation of Staphylinidae with a focus on capacity building for DNA-grade collections in Siberia and elsewhere in Northern Eurasia.

Keywords: northern eurasia; dna; dna grade; rove beetles; biodiversity; staphylinidae

Journal Title: Biodiversity Data Journal
Year Published: 2022

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