The unholy trinity: taxonomy, species delimitation and DNA barcoding

Recent excitement over the development of an initiative to generate DNA sequences for all named species on the planet has in our opinion generated two major areas of contention as to how this 'DNA barcoding' initiative should proceed. It is critical that these two issues are clarified and resolved, before the use of DNA as a tool for taxonomy and species delimitation can be universalized. The first issue concerns how DNA data are to be used in the context of this initiative; this is the DNA barcode reader problem (or barcoder problem). Currently, many of the published studies under this initiative have used tree building methods and more precisely distance approaches to the construction of the trees that are used to place certain DNA sequences into a taxonomic context. The second problem involves the reaction of the taxonomic community to the directives of the 'DNA barcoding' initiative. This issue is extremely important in that the classical taxonomic approach and the DNA approach will need to be reconciled in order for the 'DNA barcoding' initiative to proceed with any kind of community acceptance. In fact, we feel that DNA barcoding is a misnomer. Our preference is for the title of the London meetings--Barcoding Life. In this paper we discuss these two concerns generated around the DNA barcoding initiative and attempt to present a phylogenetic systematic framework for an improved barcoder as well as a taxonomic framework for interweaving classical taxonomy with the goals of 'DNA barcoding'.     

Species discovery in marine planktonic invertebrates through global molecular screening

Species discovery through large‐scale sampling of mitochondrial diversity, as advocated under DNA barcoding, has been widely criticized. Two of the primary weaknesses of this approach, the use of a single gene marker for species delineation and the possible co‐amplification of nuclear pseudogenes, can be circumvented through incorporation of multiple data sources. Here I show that for taxonomic groups with poorly characterized systematics, large‐scale genetic screening using a mitochondrial DNA marker can be a very effective approach to species discovery. Global sampling (120 locations) of 1295 individuals of 22 described species of eucalanid copepods identified 15 novel evolutionarily significant units (ESUs) within this marine holoplanktonic family. Species limits were tested under reciprocal monophyly at the mitochondrial (mt) gene 16S rRNA, and 13 of 15 lineages were reciprocally monophyletic under three phylogenetic inference methods. Five of these mitochondrial ESUs also received moderate support for reciprocal monophyly at the independently‐inherited nuclear gene, internal transcribed spacer 2 (ITS2). Additional support for the utility of mt DNA as a proxy for species boundaries in this taxon is discussed, including results from related morphological and biogeographic studies. Minimal overlap of intra‐ESU and inter‐ESU 16S rRNA genetic distances was observed, suggesting that this mt marker performs well for species discovery via molecular screening. Sampling coverage required for the discovery of new ESUs was found to be in the range of >50 individuals/species, well above the sampling intensity of most current DNA Barcoding studies. Large‐scale genetic screening can provide critical first data on the presence of cryptic species, and should be used as an approach to generate systematic hypotheses in groups with incomplete taxonomies.     

Integrating DNA barcode data and taxonomic practice: determination, discovery, and description

DNA barcodes, like traditional sources of taxonomic information, are potentially powerful heuristics in the identification of described species but require mindful analytical interpretation. The role of DNA barcoding in generating hypotheses of new taxa in need of formal taxonomic treatment is discussed, and it is emphasized that the recursive process of character evaluation is both necessary and best served by understanding the empirical mechanics of the discovery process. These undertakings carry enormous ramifications not only for the translation of DNA sequence data into taxonomic information but also for our comprehension of the magnitude of species diversity and its disappearance. This paper examines the potential strengths and pitfalls of integrating DNA sequence data, specifically in the form of DNA barcodes as they are currently generated and analyzed, with taxonomic practice.     

Evolutionary processes,dispersal limitation and climatic history shape current diversity patterns of European dragonflies

We investigated the effects of contemporary and historical factors on the spatial variation of European dragonfly diversity. Specifically, we tested to what extent patterns of endemism and phylogenetic diversity of European dragonfly assemblages are structured by 1) phylogenetic conservatism of thermal adaptations and 2) differences in the ability of post‐glacial recolonization by species adapted to running waters (lotic) and still waters (lentic). We investigated patterns of dragonfly diversity using digital distribution maps and a phylogeny of 122 European dragonfly species, which we constructed by combining taxonomic and molecular data. We calculated total taxonomic distinctiveness and mean pairwise distances across 4192 50 × 50 km equal‐area grid cells as measures of phylogenetic diversity. We compared species richness with corrected weighted endemism and standardized effect sizes of mean pairwise distances or residuals of total taxonomic distinctiveness to identify areas with higher or lower phylogenetic diversity than expected by chance. Broken‐line regression was used to detect breakpoints in diversity–latitude relationships. Dragonfly species richness peaked in central Europe, whereas endemism and phylogenetic diversity decreased from warm areas in the south‐west to cold areas in the north‐east and with an increasing proportion of lentic species. Except for species richness, all measures of diversity were consistently higher in formerly unglaciated areas south of the 0°C isotherm during the Last Glacial Maximum than in formerly glaciated areas. These results indicate that the distributions of dragonfly species in Europe were shaped by both phylogenetic conservatism of thermal adaptations and differences between lentic and lotic species in the ability of post‐glacial recolonization/dispersal in concert with the climatic history of the continent. The complex diversity patterns of European dragonflies provide an example of how integrating climatic and evolutionary history with contemporary ecological data can improve our understanding of the processes driving the geographical variation of biological diversity.     

Identifying species of moths (Lepidoptera) from Baihua Mountain,Beijing, China,using DNA barcodes

DNA barcoding has become a promising means for the identification of organisms of all life‐history stages. Currently, distance‐based and tree‐based methods are most widely used to define species boundaries and uncover cryptic species. However, there is no universal threshold of genetic distance values that can be used to distinguish taxonomic groups. Alternatively, DNA barcoding can deploy a “character‐based” method, whereby species are identified through the discrete nucleotide substitutions. Our research focuses on the delimitation of moth species using DNA‐barcoding methods. We analyzed 393 Lepidopteran specimens belonging to 80 morphologically recognized species with a standard cytochrome c oxidase subunit I (COI) sequencing approach, and deployed tree‐based, distance‐based, and diagnostic character‐based methods to identify the taxa. The tree‐based method divided the 393 specimens into 79 taxa (species), and the distance‐based method divided them into 84 taxa (species). Although the diagnostic character‐based method found only 39 so‐identifiable species in the 80 species, with a reduction in sample size the accuracy rate substantially improved. For example, in the Arctiidae subset, all 12 species had diagnostics characteristics. Compared with traditional morphological method, molecular taxonomy performed well. All three methods enable the rapid delimitation of species, although they have different characteristics and different strengths. The tree‐based and distance‐based methods can be used for accurate species identification and biodiversity studies in large data sets, while the character‐based method performs well in small data sets and can also be used as the foundation of species‐specific biochips.     

A molecular systematic framework for equine strongyles based on ribosomal DNA sequence data

In this study, molecular data sets were used to address the controversies relating to the systematics of strongyloid nematodes of equids utilising morphological data sets. DNA sequences of the first and second internal transcribed spacers (ITS-1 and ITS-2) of ribosomal DNA were determined for 30 species of equine strongyles and the systematic relationships reconstructed using phenetic and phylogenetic tree-building methods. The molecular data provided support for the hypothesis that the genera with large subglobular buccal capsules are ancestral to those with small cylindrical buccal capsules, but did not provide support for the current division of the subfamilies Strongylinae and Cyathostominae or for some taxonomic groupings (i.e. generic designations of species) within the Cyathostominea based on morphological data. Although not entirely concordant, the current molecular data provide a systematic framework for future studies of equine strongyles, which could be exploited in combination with new, phylogenetically informative morphological data sets.     

Some ‘ant’swers: Application of a layered barcode approach to problems in ant taxonomy

DNA barcoding has emerged as a routine tool in modern taxonomy. Although straightforward, this approach faces new challenges, when applied to difficult situation such as defining cryptic biodiversity. Ants are prime examples for high degrees of cryptic biodiversity due to complex population differentiation, hybridization and speciation processes. Here, we test the DNA barcoding region, cytochrome c oxidase 1 and two supplementary markers, 28S ribosomal DNA and long‐wavelength rhodopsin, commonly used in ant taxonomy, for their potential in a layered, character‐based barcoding approach across different taxonomic levels. Furthermore, we assess performance of the character‐based barcoding approach to determine cryptic species diversity in ants. We found (i) that the barcode potential of a specific genetic marker varied widely among taxonomic levels in ants; (ii) that application of a layered, character‐based barcode for identification of specimens can be a solution to taxonomical challenging groups; (iii) that the character‐based barcoding approach allows us to differentiate specimens even within locations based on pure characters. In summary, (layered) character‐based barcoding offers a reliable alternative for problematic species identification in ants and can be used as a fast and cost‐efficient approach to estimate presence, absence or frequency of cryptic species.     

In silico and empirical evaluation of twelve metabarcoding primer sets for insectivorous diet analyses

During the most recent decade, environmental DNA metabarcoding approaches have been both developed and improved to minimize the biological and technical biases in these protocols. However, challenges remain, notably those relating to primer design. In the current study, we comprehensively assessed the performance of ten COI and two 16S primer pairs for eDNA metabarcoding, including novel and previously published primers. We used a combined approach of in silico, in vivo‐mock community (33 arthropod taxa from 16 orders), and guano‐based analyses to identify primer sets that would maximize arthropod detection and taxonomic identification, successfully identify the predator (bat) species, and minimize the time and financial costs of the experiment. We focused on two insectivorous bat species that live together in mixed colonies: the greater horseshoe bat (Rhinolophus ferrumequinum) and Geoffroy's bat (Myotis emarginatus). We found that primer degeneracy is the main factor that influences arthropod detection in silico and mock community analyses, while amplicon length is critical for the detection of arthropods from degraded DNA samples. Our guano‐based results highlight the importance of detecting and identifying both predator and prey, as guano samples can be contaminated by other insectivorous species. Moreover, we demonstrate that amplifying bat DNA does not reduce the primers' capacity to detect arthropods. We therefore recommend the simultaneous identification of predator and prey. Finally, our results suggest that up to one‐third of prey occurrences may be unreliable and are probably not of primary interest in diet studies, which may decrease the relevance of combining several primer sets instead of using a single efficient one. In conclusion, this study provides a pragmatic framework for eDNA primer selection with respect to scientific and methodological constraints.     

Cryptic diversity,high host specificity and reproductive synchronization in army ant‐associated Vatesus beetles

Army ants and their arthropod symbionts represent one of the most species‐rich animal associations on Earth, and constitute a fascinating example of diverse host–symbiont interaction networks. However, despite decades of research, our knowledge of army ant symbionts remains fragmentary due to taxonomic ambiguity and the inability to study army ants in the laboratory. Here, we present an integrative approach that allows us to reliably determine species boundaries, assess biodiversity, match different developmental stages and sexes, and to study the life cycles of army ant symbionts. This approach is based on a combination of community sampling, DNA barcoding, morphology and physiology. As a test case, we applied this approach to the staphylinid beetle genus Vatesus and its different Eciton army ant host species at La Selva Biological Station, Costa Rica. DNA barcoding led to the discovery of cryptic biodiversity and, in combination with extensive community sampling, revealed strict host partitioning with no overlap in host range. Using DNA barcoding, we were also able to match the larval stages of all focal Vatesus species. In combination with studies of female reproductive physiology, this allowed us to reconstruct almost the complete life cycles of the different beetle species. We show that Vatesus beetles are highly adapted to the symbiosis with army ants, in that their reproduction and larval development are synchronized with the stereotypical reproductive and behavioural cycles of their host colonies. Our approach can now be used to study army ant‐symbiont communities more broadly, and to obtain novel insights into co‐evolutionary and ecological dynamics in species‐rich host–symbiont systems.     

Reliable,verifiable and efficient monitoring of biodiversity via metabarcoding

To manage and conserve biodiversity, one must know what is being lost, where, and why, as well as which remedies are likely to be most effective. Metabarcoding technology can characterise the species compositions of mass samples of eukaryotes or of environmental DNA. Here, we validate metabarcoding by testing it against three high‐quality standard data sets that were collected in Malaysia (tropical), China (subtropical) and the United Kingdom (temperate) and that comprised 55,813 arthropod and bird specimens identified to species level with the expenditure of 2,505 person‐hours of taxonomic expertise. The metabarcode and standard data sets exhibit statistically correlated alpha‐ and beta‐diversities, and the two data sets produce similar policy conclusions for two conservation applications: restoration ecology and systematic conservation planning. Compared with standard biodiversity data sets, metabarcoded samples are taxonomically more comprehensive, many times quicker to produce, less reliant on taxonomic expertise and auditable by third parties, which is essential for dispute resolution.     

Genetic sex assignment in wild populations using genotyping‐by‐sequencing data: A statistical threshold approach

Establishing the sex of individuals in wild systems can be challenging and often requires genetic testing. Genotyping‐by‐sequencing (GBS) and other reduced‐representation DNA sequencing (RRS) protocols (e.g., RADseq, ddRAD) have enabled the analysis of genetic data on an unprecedented scale. Here, we present a novel approach for the discovery and statistical validation of sex‐specific loci in GBS data sets. We used GBS to genotype 166 New Zealand fur seals (NZFS, Arctocephalus forsteri) of known sex. We retained monomorphic loci as potential sex‐specific markers in the locus discovery phase. We then used (i) a sex‐specific locus threshold (SSLT) to identify significantly male‐specific loci within our data set; and (ii) a significant sex‐assignment threshold (SSAT) to confidently assign sex in silico the presence or absence of significantly male‐specific loci to individuals in our data set treated as unknowns (98.9% accuracy for females; 95.8% for males, estimated via cross‐validation). Furthermore, we assigned sex to 86 individuals of true unknown sex using our SSAT and assessed the effect of SSLT adjustments on these assignments. From 90 verified sex‐specific loci, we developed a panel of three sex‐specific PCR primers that we used to ascertain sex independently of our GBS data, which we show amplify reliably in at least two other pinniped species. Using monomorphic loci normally discarded from large SNP data sets is an effective way to identify robust sex‐linked markers for nonmodel species. Our novel pipeline can be used to identify and statistically validate monomorphic and polymorphic sex‐specific markers across a range of species and RRS data sets.     

Integrated taxonomy of the <Emphasis Type="Italic">Asplenium normale</Emphasis> complex (Aspleniaceae) in China and adjacent areas

The Asplenium normale D. Don complex comprises several taxa that are either diploid or tetraploid. The tetraploids are assumed to have originated from diploid ancestors by relatively recent autopolyploidization or allopolyploidization. Some of the diploids are readily recognized morphologically but most of the taxa have until now been placed into a single species. However, phylogenetic studies have challenged this treatment and emphasized the notion that the taxonomic treatment of this complex needs to be revised. An integrative taxonomic approach was employed to delimit species in the complex using cytological, morphological, and DNA sequence data. Initially, we employed a diploid first approach to establish a robust taxonomic framework. Special efforts were made to collect and identify the diploid progenitors of each polyploid lineage identified in the plastid DNA based phylogenetic hypothesis. A total of six distinct diploid species were identified. The distinctive nature of the six diploids is strongly supported by sequence differences in plastid DNA and nuclear loci, as well as by the results of morphometric analysis. Diagnostic morphological characters were identified to distinguish the six diploid species, resulting in their revised taxonomy, which includes two novel species, namely, Asplenium normaloides and A. guangdongense. Further studies to strengthen the taxonomic classification of all of the tetraploid taxa are warranted.     

A from‐benchtop‐to‐desktop workflow for validating HTS data and for taxonomic identification in diet metabarcoding studies

The main objective of this work was to develop and validate a robust and reliable “from‐benchtop‐to‐desktop” metabarcoding workflow to investigate the diet of invertebrate‐eaters. We applied our workflow to faecal DNA samples of an invertebrate‐eating fish species. A fragment of the cytochrome c oxidase I (COI) gene was amplified by combining two minibarcoding primer sets to maximize the taxonomic coverage. Amplicons were sequenced by an Illumina MiSeq platform. We developed a filtering approach based on a series of nonarbitrary thresholds established from control samples and from molecular replicates to address the elimination of cross‐contamination, PCR/sequencing errors and mistagging artefacts. This resulted in a conservative and informative metabarcoding data set. We developed a taxonomic assignment procedure that combines different approaches and that allowed the identification of ~75% of invertebrate COI variants to the species level. Moreover, based on the diversity of the variants, we introduced a semiquantitative statistic in our diet study, the minimum number of individuals, which is based on the number of distinct variants in each sample. The metabarcoding approach described in this article may guide future diet studies that aim to produce robust data sets associated with a fine and accurate identification of prey items.     

Trait‐based risk assessment for invasive species: high performance across diverse taxonomic groups,geographic ranges and machine learning/statistical tools

Aim Trait‐based risk assessment for invasive species is becoming an important tool for identifying non‐indigenous species that are likely to cause harm. Despite this, concerns remain that the invasion process is too complex for accurate predictions to be made. Our goal was to test risk assessment performance across a range of taxonomic and geographical scales, at different points in the invasion process, with a range of statistical and machine learning algorithms. Location Regional to global data sets. Methods We selected six data sets differing in size, geography and taxonomic scope. For each data set, we created seven risk assessment tools using a range of statistical and machine learning algorithms. Performance of tools was compared to determine the effects of data set size and scale, the algorithm used, and to determine overall performance of the trait‐based risk assessment approach. Results Risk assessment tools with good performance were generated for all data sets. Random forests (RF) and logistic regression (LR) consistently produced tools with high performance. Other algorithms had varied performance. Despite their greater power and flexibility, machine learning algorithms did not systematically outperform statistical algorithms. Geographic scope of the data set, and size of the data set, did not systematically affect risk assessment performance. Main conclusions Across six representative data sets, we were able to create risk assessment tools with high performance. Additional data sets could be generated for other taxonomic groups and regions, and these could support efforts to prevent the arrival of new invaders. Random forests and LR approaches performed well for all data sets and could be used as a standard approach to risk assessment development.     

A new integrative framework for large‐scale assessments of biodiversity and community dynamics,using littoral gastropods and crabs of British Columbia,Canada

Improving our understanding of species responses to environmental changes is an important contribution ecologists can make to facilitate effective management decisions. Novel synthetic approaches to assessing biodiversity and ecosystem integrity are needed, ideally including all species living in a community and the dynamics defining their ecological relationships. Here, we present and apply an integrative approach that links high‐throughput, multicharacter taxonomy with community ecology. The overall purpose is to enable the coupling of biodiversity assessments with investigations into the nature of ecological interactions in a community‐level data set. We collected 1195 gastropods and crabs in British Columbia. First, the General mixed Yule‐coalescent (GMYC) and the Poisson Tree Processes (PTP) methods for proposing primary species‐hypotheses based on cox1 sequences were evaluated against an integrative taxonomic framework. We then used data on the geographic distribution of delineated species to test species co‐occurrence patterns for nonrandomness using community‐wide and pairwise approaches. Results showed that PTP generally outperformed GMYC and thus constitutes a more effective option for producing species‐hypotheses in community‐level data sets. Nonrandom species co‐occurrence patterns indicative of ecological relationships or habitat preferences were observed for grazer gastropods, whereas assemblages of carnivorous gastropods and crabs appeared influenced by random processes. Species‐pair associations were consistent with current ecological knowledge, thus suggesting that applying community assembly within a large taxonomical framework constitutes a valuable tool for assessing ecological interactions. Combining phylogenetic, morphological and co‐occurrence data enabled an integrated view of communities, providing both a conceptual and pragmatic framework for biodiversity assessments and investigations into community dynamics.     

Measuring beta‐diversity from taxonomic similarity

Question: The utility of beta (β‐) diversity measures that incorporate information about the degree of taxonomic (dis)similarity between species plots is becoming increasingly recognized. In this framework, the question for this study is: can we define an ecologically meaningful index of β‐diversity that, besides indicating simple species turnover, is able to account for taxonomic similarity amongst species in plots? Methods: First, the properties of existing measures of taxonomic similarity measures are briefly reviewed. Next, a new measure of plot‐to‐plot taxonomic similarity is presented that is based on the maximal common subgraph of two taxonomic trees. The proposed measure is computed from species presences and absences and include information about the degree of higher‐level taxonomic similarity between species plots. The performance of the proposed measure with respect to existing coefficients of taxonomic similarity and the coefficient of Jaccard is discussed using a small data set of heath plant communities. Finally, a method to quantify β‐diversity from taxonomic dissimilarities is discussed. Results: The proposed measure of taxonomic β‐diversity incorporates not only species richness, but also information about the degree of higher‐order taxonomic structure between species plots. In this view, it comes closer to a modern notion of biological diversity than more traditional measures of β‐di‐versity. From regression analysis between the new coefficient and existing measures of taxonomic similarity it is shown that there is an evident nonlinearity between the coefficients. This nonlinearity demonstrates that the new coefficient measures similarity in a conceptually different way from previous indices. Also, in good agreement with the findings of previous authors, the regression between the new index and the Jaccard coefficient of similarity shows that more than 80% of the variance of the former is explained by the community structure at the species level, while only the residual variance is explained by differences in the higher‐order taxonomic structure of the species plots. This means that a genuine taxonomic approach to the quantification of plot‐to‐plot similarity is only needed if we are interested in the residual system's variation that is related to the higher‐order taxonomic structure of a pair of species plots.     

A Retrospective Approach to Testing the DNA Barcoding Method

A decade ago, DNA barcoding was proposed as a standardised method for identifying existing species and speeding the discovery of new species. Yet, despite its numerous successes across a range of taxa, its frequent failures have brought into question its accuracy as a short-cut taxonomic method. We use a retrospective approach, applying the method to the classification of New Zealand skinks as it stood in 1977 (primarily based upon morphological characters), and compare it to the current taxonomy reached using both morphological and molecular approaches. For the 1977 dataset, DNA barcoding had moderate-high success in identifying specimens (78-98%), and correctly flagging specimens that have since been confirmed as distinct taxa (77-100%). But most matching methods failed to detect the species complexes that were present in 1977. For the current dataset, there was moderate-high success in identifying specimens (53-99%). For both datasets, the capacity to discover new species was dependent on the methodological approach used. Species delimitation in New Zealand skinks was hindered by the absence of either a local or global barcoding gap, a result of recent speciation events and hybridisation. Whilst DNA barcoding is potentially useful for specimen identification and species discovery in New Zealand skinks, its error rate could hinder the progress of documenting biodiversity in this group. We suggest that integrated taxonomic approaches are more effective at discovering and describing biodiversity.     

Investigating microbial associations from sequencing survey data with co‐correspondence analysis

Microbial communities, which drive major ecosystem functions, consist of a wide range of interacting species. Understanding how microbial communities are structured and the processes underlying this is crucial to interpreting ecosystem responses to global change but is challenging as microbial interactions cannot usually be directly observed. Multiple efforts are currently focused to combine next‐generation sequencing (NGS) techniques with refined statistical analysis (e.g., network analysis, multivariate analysis) to characterize the structures of microbial communities. However, most of these approaches consider a single table of sequencing data measured for several samples. Technological advances now make it possible to collect NGS data on different taxonomic groups simultaneously for the same samples, allowing us to analyse a pair of tables. Here, an analytical framework based on co‐correspondence analysis (CoCA) is proposed to study the distributions, assemblages and interactions between two microbial communities. We show the ability of this approach to highlight the relationships between two microbial communities, using two data sets exhibiting various types of interactions. CoCA identified strong association patterns between autotrophic and heterotrophic microbial eukaryote assemblages, on the one hand, and between microalgae and viruses, on the other. We demonstrate also how CoCA can be used, complementary to network analysis, to reorder co‐occurrence networks and thus investigate the presence of patterns in ecological networks.     

DNA-based species delineation in tropical beetles using mitochondrial and nuclear markers

DNA barcoding has been successfully implemented in the identification of previously described species, and in the process has revealed several cryptic species. It has been noted that such methods could also greatly assist in the discovery and delineation of undescribed species in poorly studied groups, although to date the feasibility of such an approach has not been examined explicitly. Here, we investigate the possibility of using short mitochondrial and nuclear DNA sequences to delimit putative species in groups lacking an existing taxonomic framework. We focussed on poorly known tropical water beetles (Coleoptera: Dytiscidae, Hydrophilidae) from Madagascar and dung beetles (Scarabaeidae) in the genus Canthon from the Neotropics. Mitochondrial DNA sequence variation proved to be highly structured, with >95% of the observed variation existing between discrete sets of very closely related genotypes. Sequence variation in nuclear 28S rRNA among the same individuals was lower by at least an order of magnitude, but 16 different genotypes were found in water beetles and 12 genotypes in Canthon, differing from each other by a minimum of two base pairs. The distribution of these 28S rRNA genotypes in individuals exactly matched the distribution of mtDNA clusters, suggesting that mtDNA patterns were not misleading because of introgression. Moreover, in a few cases where sequence information was available in GenBank for morphologically defined species of Canthon, these matched some of the DNA-based clusters. These findings demonstrate that clusters of close relatives can be identified readily in the sequence variation obtained in field collected samples, and that these clusters are likely to correspond to either previously described or unknown species. The results suggest that DNA-assisted taxonomy will not require more than a short fragment of mtDNA to provide a largely accurate picture of species boundaries in these groups. Applied on a large scale, this DNA-based approach could greatly improve the rate of species discovery in the large assemblages of insects that remain undescribed.