ArticleBiodiversity data journal2026
16S rRNA sequence dataset for the identification of the French hoverflies (Diptera, Syrphidae).
Article in Biodiversity data journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
With ongoing biodiversity loss, a wide range of taxa are being monitored to support the implementation of conservation measures aimed at preventing their decline. Effective monitoring requires the development of robust and scalable tools and methods. Amongst these, DNA barcoding and metabarcoding have emerged as powerful and widely adopted approaches for tracking biodiversity. To achieve high taxonomic resolution in molecular-based monitoring, the use of multiple DNA markers is often essential. In this study, we focused on Syrphidae, a family that plays a key role in ecological networks. Alongside bees, hoverflies are remarkable pollinators within the order Diptera. Furthermore, larvae of the subfamily Syrphinae are widely regarded as beneficial in agricultural contexts, contributing to the biological control of pest populations. Mainland France, with its temperate climate, is a hotspot for Syrphidae diversity, hosting 566 species whose biological and ecological traits are thoroughly documented in the Syrph the Net 2024 database. France currently holds the highest recorded number of Syrphidae species in Europe. We produced a set of 16S rRNA sequences for Syrphidae, well suited for environmental biomonitoring applications. A total of 713 specimens from the private collection of specialist entomologists, representing 352 species across 14 tribes, were sequenced. Using a customised validation workflow, 561 sequences covering 316 species were retained, representing approximately 60% of the French hoverfly fauna. For 166 species, the 16S rRNA marker successfully discriminates specimens at the species level, including morphologically challenging genera such as
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