Abstract
The identification of Afrotropical hoverflies is very difficult because of limited recent taxonomic revisions and the lack of comprehensive identification keys. In order to assist in their identification, and to improve the taxonomy of this group, we constructed a reference dataset of 513 COI barcodes of 90 of the more common nominal species from Ghana, Togo, Benin and Nigeria (W Africa) and added ten publically available COI barcodes from nine nominal Afrotropical species to this (total: 523 COI barcodes; 98 nominal species; 26 genera). The identification accuracy of this dataset was evaluated with three methods (K2P distance-based, Neighbor-Joining (NJ) / Maximum Likelihood (ML) analysis, and using SpeciesIdentifier). Results of the three methods were highly congruent and showed a high identification success. Nine species pairs showed a low (< 0.03) mean interspecific K2P distance that resulted in several incorrect identifications. A high (> 0.03) maximum intraspecific K2P distance was observed in eight species and barcodes of these species not always formed single clusters in the NJ / ML analayses which may indicate the occurrence of cryptic species. Optimal K2P thresholds to differentiate intra- from interspecific K2P divergence were highly different among the three subfamilies (Eristalinae: 0.037, Syrphinae: 0.06, Microdontinae: 0.007–0.02), and among the different general suggesting that optimal thresholds are better defined at the genus level. In addition to providing an alternative identification tool, our study indicates that DNA barcoding improves the taxonomy of Afrotropical hoverflies by selecting (groups of) taxa that deserve further taxonomic study, and by attributing the unknown sex to species for which only one of the sexes is known.
Highlights
Syrphidae is one of the most diverse, and well-known to the general public, family of Diptera, with more than 6,000 species worldwide [1]
In order to assist in their identification, and to improve the taxonomy of this group, we constructed a reference dataset of 513 c oxidase subunit I (COI) barcodes of 90 of the more common nominal species from Ghana, Togo, Benin and Nigeria (W Africa) and added ten publically available COI barcodes from nine nominal Afrotropical species to this
The identification accuracy of this dataset was evaluated with three methods (K2P distance-based, Neighbor-Joining (NJ) / Maximum Likelihood (ML) analysis, and using SpeciesIdentifier)
Summary
Syrphidae (hoverflies or flower flies) is one of the most diverse, and well-known to the general public, family of Diptera, with more than 6,000 species worldwide [1]. The identification of Afrotropical hoverflies is difficult and challenging for two major reasons. The larger the genus, the less reliable the identification, because there are greater chances that the keys will not work and it becomes more difficult to use the original descriptions for identification (since there are a greater number of choices) [8]. Many of the original descriptions are too brief or too vague for species identification, and several keys are of males only (e.g. Hull's [11] key to Eumerus). The development of an accurate and effective molecular identification system would be helpful to assist morphological identification of Afrotropical hoverflies, and ecological studies on them
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