ArticleInsects2024
DNA Barcoding of German Cuckoo Wasps (Hymenoptera: Chrysididae) Suggests Cryptic Species in Several Widely Distributed Species.
Article in Insects, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Computer Vision for Monitoring Wild Bees and Wasps: A Structured Literature Review.Ecology and evolution · 2026Review
- Exploration of Wolbachia strains in Amrasca biguttula Ishida (Hemiptera: Cicadellidae) and its egg parasitoid Trichogramma chilonis (Hymenoptera: Trichogrammatidae).BMC microbiology · 2026Article
- New species and barcode analysis ofZooKeys · 2025Article
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Authors and funding
4 authors.
Funding
Abstract
Germany is home to a rich cuckoo wasp fauna (Hymenoptera: Chrysididae) with about 108 species. However, several nomenclatural changes, the lack of identification keys, and the discovery of cryptic species difficult to identify based on external morphology have made the identification of several species a challenge. COI barcoding has been instrumental in the identification of some cuckoo wasp species and could help alleviate some of the above problems, but a reliable large reference database containing the cuckoo wasp barcodes is lacking. We present the COI barcodes of more than 800 specimens of 101 cuckoo wasp species native to Germany to lay the foundation for the barcode-based identification of German species. An analysis of the COI barcode sequences suggested groups that are largely consistent with the current taxonomy of the group. We found a few cases of over- or undersplitting of taxa. In some common species, the high degree of barcode divergence suggests the presence of cryptic species that need to be further assessed by integrative approaches. Our library of cuckoo wasp reference barcodes will enhance researchers' ability to reliably identify species within this fascinating group of insects, in particular for identifying life stages that offer few or no morphological features for species-level identification.
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