Abstract1. In recent years, large-scale DNA barcoding campaigns have generated an enormous amount of COI barcodes, which are usually stored in NCBI's GenBank and the official Barcode of Life database (BOLD). BOLD data are generally associated with more detailed and better curated meta-data, because a great proportion is based on expert-verified and vouchered material, accessible in public collections. In the course of the initiative German Barcode of Life data were generated for the reference library of 2,846 species of Coleoptera from 13,516 individuals.2. Confronted with the high effort associated with the identification, verification and data validation, a bioinformatic pipeline, "TaxCI" was developed that (1) identifies taxonomic inconsistencies in a given tree topology (optionally including a reference dataset), (2) discriminates between different cases of incongruence in order to identify contamination or misidentified specimens, (3) graphically marks those cases in the tree, which finally can be checked again and, if needed, corrected or removed from the dataset. For this, "TaxCI" may use DNA-based species delimitations from other approaches (e.g. mPTP) or may perform implemented threshold-based clustering.3. The data-processing pipeline was tested on a newly generated set of barcodes, using the available BOLD records as a reference. A data revision based on the first run of the TaxCI tool resulted in the second TaxCI analysis in a taxonomic match ratio very similar to the one recorded from the reference set (92% vs. 94%). The revised dataset improved by nearly 20% through this procedure compared to the original, uncorrected one.4. Overall, the new processing pipeline for DNA barcode data allows for the rapid and easy identification of inconsistencies in large datasets, which can be dealt withThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

DNA barcoding is particularly useful for identification and species delimitation in taxa with conserved morphology. Pseudoscorpions are arachnids with high prevalence of morphological crypsis. Here, we present the first comprehensive DNA barcode library for Central European Pseudoscorpiones, covering 70% of the German pseudoscorpion fauna (35 out of 50 species). For 21 species, we provide the first publicly available COI barcodes, including the rare Anthrenochernes stellae Lohmander, a species protected by the FFH Habitats Directive. The pattern of intraspecific COI variation and interspecific COI variation (i.e., presence of a barcode gap) generally allows application of the DNA barcoding approach, but revision of current taxonomic designations is indicated in several taxa. Sequences of 36 morphospecies were assigned to 74 BINs (barcode index numbers). This unusually high number of intraspecific BINs can be explained by the presence of overlooked cryptic species and by the accelerated substitution rate in the mitochondrial genome of pseudoscorpions, as known from previous studies. Therefore, BINs may not be an appropriate proxy for species numbers in pseudoscorpions, while partitions built with the ASAP algorithm (Assemble Species by Automatic Partitioning) correspond well with putative species. ASAP delineated 51 taxonomic units from our data, an increase of 42% compared with the present taxonomy. The Neobisium carcionoides complex, currently considered a polymorphic species, represents an outstanding example of cryptic diversity: 154 sequences from our dataset were allocated to 23 BINs and 12 ASAP units.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

DNA taxonomy including barcoding and metabarcoding is widely used to explore the diversity in biodiversity hotspots. In most of these hotspot areas, chafers are represented by a multitude of species, which are well defined by the complex shape of male genitalia. Here, we explore how well COI barcode data reflect morphological species entities and thus their usability for accelerated species inventorization. We conducted dedicated field surveys in Sri Lanka to collect the species-rich and highly endemic Sericini chafers (Coleoptera: Scarabaeidae). Congruence among results of a series of protocols for de novo species delimitation and with morphology-based species identifications was investigated. Different delimitation methods, such as the Poisson tree processes (PTP) model, Statistical Parsimony Analysis (TCS), Automatic Barcode Gap Discovery (ABGD), Assemble Species by Automatic Partitioning (ASAP), and Barcode Index Number (BIN) assignments, resulted in different numbers of molecular operational taxonomic units (MOTUs). All methods showed both over-splitting and lumping of morphologically identified species. Only 18 of the observed 45 morphospecies perfectly matched MOTUs from all methods. The congruence of delimitation between MOTUs and morphospecies expressed by the match ratio was low, ranging from 0.57 to 0.67. TCS and multirate PTP (mPTP) showed the highest match ratio, while (BIN) assignment resulted in the lowest match ratio and most splitting events. mPTP lumped more species than any other method. Principal coordinate analysis (PCoA) on a match ratio-based distance matrix revealed incongruent outcomes of multiple DNA delimitation methods, although applied to the same data. Our results confirm that COI barcode data alone are unlikely to correctly delimit all species, in particular, when using only a single delimitation approach. We encourage the integration of various approaches and data, particularly morphology, to validate species boundaries.

A checklist of the Syrphidae species of the Republic of Georgia is presented. New hover fly (Diptera: Syrphidae) records from Georgia are provided as a result of field work conducted in 2018. At the same time, published syrphid records for the country are here reviewed and updated. A total of 357 species of hoverflies are now documented from Georgia, 40 of which are reported for the first time. Moreover, DNA barcodes were sequenced for 238 specimens, representing 74 species from this country.