The analysis of DNA barcode sequences with varying techniques for cluster recognition provides an efficient approach for recognizing putative species (operational taxonomic units, OTUs). This approach accelerates and improves taxonomic workflows by exposing cryptic species and decreasing the risk of synonymy. This study tested the congruence of OTUs resulting from the application of three analytical methods (ABGD, BIN, GMYC) to sequence data for Australian hypertrophine moths. OTUs supported by all three approaches were viewed as robust, but 20% of the OTUs were only recognized by one or two of the methods. These OTUs were examined for three criteria to clarify their status. Monophyly and diagnostic nucleotides were both uninformative, but information on ranges was useful as sympatric sister OTUs were viewed as distinct, while allopatric OTUs were merged. This approach revealed 124 OTUs of Hypertrophinae, a more than twofold increase from the currently recognized 51 species. Because this analytical protocol is both fast and repeatable, it provides a valuable tool for establishing a basic understanding of species boundaries that can be validated with subsequent studies.

Gelechioidea are one of the most species rich and least studied superfamilies of Lepidoptera. We examine the interrelationships within the superfamily using the densest taxon sampling to date, combined with the most extensive ever morphological and molecular character data. We perform partitioned and combined analyses using maximum likelihood, Bayesian and parsimony approaches. The combined dataset consists of 155 exemplar species of Gelechioidea, representing nearly all subfamilies recognized in recent classifications. Parsimony analyses are performed with a dataset including 28 additional terminal taxa with only morphological data available. We use eight genes with a total of 6127 bp, and morphological data with 253 characters derived from larval, pupal, and adult morphology. The analyses of combined data yield more resolved trees and significantly better-supported groupings than either dataset when analysed alone. The recurrent monophyletic groupings in all our modelbased analyses support a revision of the family classification. Deeper relationships vary between analyses and data partitions, leaving them ambiguous. The place of the root remains a challenge for future research. We propose a revised classification and suggest the division of Gelechioidea into 16 families. We redefine Depressariidae Meyrick, 1883 for a monophylum that includes Acriinae, Aeolanthinae, Cryptolechiinae, Depressariinae, Ethmiinae, Hypercalliinae, Hypertrophinae, Peleopodinae, Oditinae, Stenomatinae, Carcina, and a diversity of predominantly New World taxa previously excluded from Lypusidae (Amphisbatidae s. authors) but left without family position. A monophyletic Oecophoridae s. s., including Deuterogoniinae and Pleurotinae, is obtained for the first time with significant support. Elachistidae s. l. is found to be polyphyletic, and Elachistidae is restricted to comprise Agonoxeninae, Elachistinae, and Parametriotinae. Batrachedridae are polyphyletic, with several genera pending further study. Apart from the core Batrachedra, the taxa previously included in this family are grouped in an expanded Pterolonchidae, together with Coelopoetinae and Syringopainae. Lypusidae s. s. and Chimabachidae form a monophylum; Chimabachinae is united with Lypusidae as a subfamily, stat. n. Our results contradict the subfamily classifications of several families, notably Lecithoceridae and Autostichidae, but due to insufficient sampling of taxa we refrain from comprehensive taxonomic conclusions on the subfamily level, and encourage focused studies to resolve these groups.

The accelerating loss of biodiversity has created a need for more effective ways to discover species. Novel algorithmic approaches for analyzing sequence data combined with rapidly expanding DNA barcode libraries provide a potential solution. While several analytical methods are available for the delineation of operational taxonomic units (OTUs), few studies have compared their performance. This study compares the performance of one morphology-based and four DNA-based (BIN, parsimony networks, ABGD, GMYC) methods on two groups of gelechioid moths. It examines 92 species of Finnish Gelechiinae and 103 species of Australian Elachistinae which were delineated by traditional taxonomy. The results reveal a striking difference in performance between the two taxa with all four DNA-based methods. OTU counts in the Elachistinae showed a wider range and a relatively low (ca. 65%) OTU match with reference species while OTU counts were more congruent and performance was higher (ca. 90%) in the Gelechiinae. Performance rose when only monophyletic species were compared, but the taxon-dependence remained. None of the DNA-based methods produced a correct match with non-monophyletic species, but singletons were handled well. A simulated test of morphospecies-grouping performed very poorly in revealing taxon diversity in these small, dull-colored moths. Despite the strong performance of analyses based on DNA barcodes, species delineated using single-locus mtDNA data are best viewed as OTUs that require validation by subsequent integrative taxonomic work.