Authors
Anaïs Marquisseau, Mélodie Ollivier, Christophe Klopp, Géraldine Pascal, André Pornon, Nathalie Escaravage, Veronique Sarthou, Jean-Pierre Sarthou, Magalie Pichon
Published in
Biodiversity data journal. Volume 14. Pages e189822. Epub Jun 15, 2026.
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 Paragus, Melanostoma and Microdon. For the remaining 150 species in the dataset, the 16S rRNA marker enables identification at the genus level, though species-level resolution would require additional specimens to be sequenced. This study represents a first step towards the development of a comprehensive multi-marker reference library for French Syrphidae.
PMID:
42344953
Bibliographic data and abstract were imported from PubMed on 25 Jun 2026.
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