Large‐scale integrative taxonomy of Swedish grass flies (Diptera, Chloropidae) reveals hitherto unknown complexity of a dark taxon

The study of biodiversity is fundamental to preserving life on Earth but a challenging endeavour due to the taxonomic neglect associated with hyperdiverse lineages. To overcome this problem, we have implemented for the first time a Large‐scale integrative taxonomic (LIT) approach on the hyperdiverse...

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Bibliographic Details
Published inZoologica scripta Vol. 53; no. 5; pp. 614 - 631
Main Authors Riccardi, Paula Raile, Hartop, Emily
Format Journal Article
LanguageEnglish
Published Oslo Wiley Subscription Services, Inc 01.09.2024
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Summary:The study of biodiversity is fundamental to preserving life on Earth but a challenging endeavour due to the taxonomic neglect associated with hyperdiverse lineages. To overcome this problem, we have implemented for the first time a Large‐scale integrative taxonomic (LIT) approach on the hyperdiverse insect family Chloropidae. This lineage of flies is a great fit for implementing emerging protocols such as LIT due to their ecological relevance, abundance and global distribution, poorly known genetic diversity and challenging taxonomy. In this study, we test cost‐effective barcoding workflows on nonoptimally preserved chloropid flies from Sweden and then apply targeted morphological validation to accelerate the species recognition process. Our dataset yielded DNA barcodes of 63 species that represent almost one‐third of the species diversity from Sweden and 15% of the European diversity. Applying LIT allowed us to uncover two new species and address for the first time three troublesome species complexes through a comprehensive framework. We also provide previously unknown DNA barcodes for 35% of the described species found and address distribution patterns with a focus on grassland environments. We have thus contributed significantly to overcoming the taxonomic neglect of this hyperdiverse lineage by tackling the diversity of chloropids using complementary sources of data, scalable techniques and quickly translating multiple sources of evidence into named species.
ISSN:0300-3256
1463-6409
DOI:10.1111/zsc.12663