DNA barcoding has greatly accelerated the pace of specimen identification to the species level, as well as species delineation. Whereas the application of DNA barcoding to the matching of unknown specimens to known species is straightforward, its use for species delimitation is more controversial, as species discovery hinges critically on present levels of haplotype diversity, as well as patterning of standing genetic variation that exists within and between species. Typical sample sizes for molecular biodiversity assessment using DNA barcodes range from 5 to 10 individuals per species. However, required levels that are necessary to fully gauge haplotype variation at the species level are presumed to be strongly taxon‐specific. Importantly, little attention has been paid to determining appropriate specimen sample sizes that are necessary to reveal the majority of intraspecific haplotype variation within any one species. In this paper, we present a brief outline of the current literature and methods on intraspecific sample size estimation for the assessment of COI DNA barcode haplotype sampling completeness. The importance of adequate sample sizes for studies of molecular biodiversity is stressed, with application to a variety of metazoan taxa, through reviewing foundational statistical and population genetic models, with specific application to ray‐finned fishes (Chordata: Actinopterygii). Finally, promising avenues for further research in this area are highlighted.

Estimating appropriate sample sizes to measure species abundance and richness is a fundamental problem for most biodiversity research. In this study, we explore a method to measure sampling sufficiency based on haplotype diversity in the ray-finned fishes (Animalia: Chordata: Actinopterygii). To do this, we use linear regression and hypothesis testing methods on haplotype accumulation curves from DNA barcodes for 18 species of fishes, in the statistics platform R. We use a simple mathematical model to estimate sampling sufficiency from a sample-number based prediction of intraspecific haplotype diversity, given an assumption of equal haplotype frequencies. Our model finds that haplotype diversity for most of the 18 fish species remains largely unsampled, and this appears to be a result of small sample sizes. Lastly, we discuss how our overly simple model may be a useful starting point to develop future estimators for intraspecific sampling sufficiency in studies using DNA barcodes.

Although the butterflies of North America have received considerable taxonomic attention, overlooked species and instances of hybridization continue to be revealed. The present study assembles a DNA barcode reference library for this fauna to identify groups whose patterns of sequence variation suggest the need for further taxonomic study. Based on 14,626 records from 814 species, DNA barcodes were obtained for 96% of the fauna. The maximum intraspecific distance averaged 1/4 the minimum distance to the nearest neighbor, producing a barcode gap in 76% of the species. Most species (80%) were monophyletic, the others were para- or polyphyletic. Although 15% of currently recognized species shared barcodes, the incidence of such taxa was far higher in regions exposed to Pleistocene glaciations than in those that were ice-free. Nearly 10% of species displayed high intraspecific variation (>2.5%), suggesting the need for further investigation to assess potential cryptic diversity. Aside from aiding the identification of all life stages of North American butterflies, the reference library has provided new perspectives on the incidence of both cryptic and potentially over-split species, setting the stage for future studies that can further explore the evolutionary dynamics of this group.

Assessing levels of standing genetic variation within species requires a robust sampling for the purpose of accurate specimen identification using molecular techniques such as DNA barcoding; however, statistical estimators for what constitutes a robust sample are currently lacking. Moreover, such estimates are needed because most species are currently represented by only one or a few sequences in existing databases, which can safely be assumed to be undersampled. Unfortunately, sample sizes of 5–10 specimens per species typically seen in DNA barcoding studies are often insufficient to adequately capture within-species genetic diversity. Here, we introduce a novel iterative extrapolation simulation algorithm of haplotype accumulation curves, called HACSim (Haplotype Accumulation Curve Simulator) that can be employed to calculate likely sample sizes needed to observe the full range of DNA barcode haplotype variation that exists for a species. Using uniform haplotype and non-uniform haplotype frequency distributions, the notion of sampling sufficiency (the sample size at which sampling accuracy is maximized and above which no new sampling information is likely to be gained) can be gleaned. HACSim can be employed in two primary ways to estimate specimen sample sizes: (1) to simulate haplotype sampling in hypothetical species, and (2) to simulate haplotype sampling in real species mined from public reference sequence databases like the Barcode of Life Data Systems (BOLD) or GenBank for any genomic marker of interest. While our algorithm is globally convergent, runtime is heavily dependent on initial sample sizes and skewness of the corresponding haplotype frequency distribution.

DNA barcoding has been largely successful in satisfactorily exposing levels of standing genetic diversity for a wide range of taxonomic groups through the employment of only one or a few universal gene markers. However, sufficient coverage of geographically-broad intra-specific haplotype variation within genomic databases like the Barcode of Life Data Systems (BOLD) and GenBank remains relatively sparse. As reference sequence libraries continue to grow exponentially in size, there is now the need to identify novel ways of meaningfully analyzing vast amounts of available DNA barcode data. This is an important issue to address promptly for the routine tasks of specimen identification and species discovery, which have seen broad adoption in areas as diverse as regulatory forensics and resource conservation. Here, it is demonstrated that the interpretation of DNA barcoding data is lacking in statistical rigor. To highlight this, focus is set specifically on one key concept that has become a household name in the field: the DNA barcode gap. Arguments outlined herein specifically center on DNA barcoding in animal taxa and stem from three angles: (1) the improper allocation of specimen sampling effort necessary to capture adequate levels of within-species genetic variation, (2) failing to properly visualize intra-specific and interspecific genetic distances, and (3) the inconsistent, inappropriate use, or absence of statistical inferential procedures in DNA barcoding gap analyses. Furthermore, simple statistical solutions are outlined which can greatly propel the use of DNA barcoding as a tool to irrefutably match unknowns to knowns on the basis of the barcoding gap with a high degree of confidence. Proposed methods examined herein are illustrated through application to DNA barcode sequence data from Canadian Pacific fish species as a case study.