Order Lepidoptera Linnaeus, 1758. In : Zhang, Z.-Q. (Ed.) Animal biodiversity: An outline of higher-level classification and survey of taxonomic richness

The proliferation of DNA data is revolutionizing all fields of systematic research. DNA barcode sequences, now available for millions of specimens and several hundred thousand species, are increasingly used in algorithmic species delimitations. This is complicated by occasional incongruences between species and gene genealogies, as indicated by situations where conspecific individuals do not form a monophyletic cluster in a gene tree. In two previous reviews, non-monophyly has been reported as being common in mitochondrial DNA gene trees. We developed a novel web service “Monophylizer” to detect non-monophyly in phylogenetic trees and used it to ascertain the incidence of species non-monophyly in COI (a.k.a. cox1) barcode sequence data from 4977 species and 41,583 specimens of European Lepidoptera, the largest data set of DNA barcodes analyzed from this regard. Particular attention was paid to accurate species identification to ensure data integrity. We investigated the effects of tree-building method, sampling effort, and other methodological issues, all of which can influence estimates of non-monophyly. We found a 12% incidence of non-monophyly, a value significantly lower than that observed in previous studies. Neighbor joining (NJ) and maximum likelihood (ML) methods yielded almost equal numbers of non-monophyletic species, but 24.1% of these cases of non-monophyly were only found by one of these methods. Non-monophyletic species tend to show either low genetic distances to their nearest neighbors or exceptionally high levels of intraspecific variability. Cases of polyphyly in COI trees arising as a result of deep intraspecific divergence are negligible, as the detected cases reflected misidentifications or methodological errors. Taking into consideration variation in sampling effort, we estimate that the true incidence of non-monophyly is ∼23%, but with operational factors still being included. Within the operational factors, we separately assessed the frequency of taxonomic limitations (presence of overlooked cryptic and oversplit species) and identification uncertainties. We observed that operational factors are potentially present in more than half (58.6%) of the detected cases of non-monophyly. Furthermore, we observed that in about 20% of non-monophyletic species and entangled species, the lineages involved are either allopatric or parapatric—conditions where species delimitation is inherently subjective and particularly dependent on the species concept that has been adopted. These observations suggest that species-level non-monophyly in COI gene trees is less common than previously supposed, with many cases reflecting misidentifications, the subjectivity of species delimitation or other operational factors.

This study provides a first, comprehensive, diagnostic use of DNA barcodes for the Canadian fauna of noctuoids or “owlet” moths (Lepidoptera: Noctuoidea) based on vouchered records for 1,541 species (99.1% species coverage), and more than 30,000 sequences. When viewed from a Canada-wide perspective, DNA barcodes unambiguously discriminate 90% of the noctuoid species recognized through prior taxonomic study, and resolution reaches 95.6% when considered at a provincial scale. Barcode sharing is concentrated in certain lineages with 54% of the cases involving 1.8% of the genera. Deep intraspecific divergence exists in 7.7% of the species, but further studies are required to clarify whether these cases reflect an overlooked species complex or phylogeographic variation in a single species. Non-native species possess higher Nearest-Neighbour (NN) distances than native taxa, whereas generalist feeders have lower NN distances than those with more specialized feeding habits. We found high concordance between taxonomic names and sequence clusters delineated by the Barcode Index Number (BIN) system with 1,082 species (70%) assigned to a unique BIN. The cases of discordance involve both BIN mergers and BIN splits with 38 species falling into both categories, most likely reflecting bidirectional introgression. One fifth of the species are involved in a BIN merger reflecting the presence of 158 species sharing their barcode sequence with at least one other taxon, and 189 species with low, but diagnostic COI divergence. A very few cases (13) involved species whose members fell into both categories. Most of the remaining 140 species show a split into two or three BINs per species, while Virbia ferruginosa was divided into 16. The overall results confirm that DNA barcodes are effective for the identification of Canadian noctuoids. This study also affirms that BINs are a strong proxy for species, providing a pathway for a rapid, accurate estimation of animal diversity.

Noctuidae are one of the world’s most diverse, ecologically successful, and economically important animal lineages with over 12,000 species in ~1,150 genera. We inferred a phylogeny using eight protein-coding genes for the global fauna, greatly expanding upon previous attempts to stabilize Noctuidae higher classification by sampling 341 genera (nearly half represented by their type species) representing 70/76 widely recognized family-group taxa: 20/21 subfamilies, 32/35 tribes, and 18/20 subtribes. We evaluated 17 subfamily-level taxa in detail, discussing adult and larval morphology, life histories, and taxonomic implications of our results. We significantly alter concepts of Acontiinae, Condicinae, Eustrotiinae, Metoponiinae, and Stiriinae. Our results supported recognition of two new subfamilies: Cobubathinae Wagner & Keegan, 2021 subf. nov. and Cropiinae Keegan & Wagner, 2021 subf. nov. Other nomenclatural changes we made are as follows. We moved: ‘Acontia’ viridifera (Hampson, 1910), ‘Azenia’ virida Barnes and McDunnough, 1916, Aleptinoides, Austrazenia, Chalcoecia, Megalodes, and Trogotorna to Chamaecleini in Acontiinae; Apaustis to, and reinstated Emmelia as a valid genus in Acontiinae; Allophyes and Meganephria to Cuculliinae; ‘Plagiomimicus’ navia (Harvey, 1875), Airamia, Alvaradoia, Hypoperigea, Neotarache, and Mesotrosta to Condicinae; Axenus, Azenia, Metaponpneumata, Sexserrata, and Tristyla to Metoponiinae; ‘Paramiana’ canoa (Barnes, 1907) to Noctuinae; Aucha, Cobubatha, and Tripudia to Cobubathinae; Anycteola and Supralathosea to Oncocnemidinae; Cropia to Cropiinae; Desmoloma to Dyopsinae; Eviridemas and Gloanna to Bryophilinae; Fota and Stilbia to Stiriinae; and Copibryophila, Homolagoa, and Tyta to Noctuidae incertae sedis. We conclude with discussion of instances where current understanding of noctuid biogeography and life histories were changed by our results.