The Species Concept as a Cognitive Tool for Biological Anthropology

Taxonomy is caught between the search for the “perfect” theory and an elusive biological variability. The lack of major advances in issues related to how “species” and other taxonomic categories are defined suggests that perhaps we should avoid excessively rigid formalism in this regard. The risk is a separation between elegant but useless theories and confusing applications of the taxonomic tools. Communication is one of the main functions of taxonomy, and stability one of the main parameters that taxonomy users should be sensitive to. An excess of stability may generate anachronistic consequences while continuous revisions may make the tool of taxonomy scarcely practical. The current tendency pushes toward more and more fragmentation of biologically valid taxa. While taxonomy specialists enjoy such challenges, many taxonomy users feel a bit nervous and discouraged when trying to use a tool that is constantly changing. Debates over taxonomy would seem particularly unrewarding for fields with limited samples and scarce biological diversity, such as palaeoanthropology. In this context, where the information available is rarely sufficient to supply consistent taxonomical evidence, there are frequently excessive efforts to create debate on species separations. The risk is that we maintain the debate on a purely theoretical level, or else we distrust a reliable use of taxonomy. A compromise (and recommended) choice between these two extremes would be to rely on shared and reasonable interpretations of homogeneous evolutionary units, without diving into fine‐grained issues that will remain, however, unresolved. Taxonomy should be a tool, not the goal, of the evolutionary biologist. Our mind needs discrete and recognizable objects to structure our perception of reality. There is no reason to expect that nature works the same way. Am. J. Primatol. 75:10‐15, 2013. © 2012 Wiley Periodicals, Inc.     

Effect of marker choice and thermal cycling protocol on zooplankton DNA metabarcoding studies

DNA metabarcoding is a promising approach for rapidly surveying biodiversity and is likely to become an important tool for measuring ecosystem responses to environmental change. Metabarcoding markers need sufficient taxonomic coverage to detect groups of interest, sufficient sequence divergence to resolve species, and will ideally indicate relative abundance of taxa present. We characterized zooplankton assemblages with three different metabarcoding markers (nuclear 18S rDNA, mitochondrial COI, and mitochondrial 16S rDNA) to compare their performance in terms of taxonomic coverage, taxonomic resolution, and correspondence between morphology‐ and DNA‐based identification. COI amplicons sequenced on separate runs showed that operational taxonomic units representing >0.1% of reads per sample were highly reproducible, although slightly more taxa were detected using a lower annealing temperature. Mitochondrial COI and nuclear 18S showed similar taxonomic coverage across zooplankton phyla. However, mitochondrial COI resolved up to threefold more taxa to species compared to 18S. All markers revealed similar patterns of beta‐diversity, although different taxa were identified as the greatest contributors to these patterns for 18S. For calanoid copepod families, all markers displayed a positive relationship between biomass and sequence reads, although the relationship was typically strongest for 18S. The use of COI for metabarcoding has been questioned due to lack of conserved primer‐binding sites. However, our results show the taxonomic coverage and resolution provided by degenerate COI primers, combined with a comparatively well‐developed reference sequence database, make them valuable metabarcoding markers for biodiversity assessment.     

Taxonomic versus allometric constraints on non‐linear interaction strengths

Recently, the importance of body mass and allometric scaling for the structure and dynamics of ecological networks has been highlighted in several ground‐breaking studies. However, advances in the understanding of generalities across ecosystem types are impeded to a considerable extent by a methodological dichotomy contrasting a considerable portion of marine ecology on the one hand opposite to traditional community ecology on the other hand. Many marine ecologists are bound to the taxonomy‐neglecting size spectrum approach when describing and analysing community patterns. In contrast, the mindset of the other school is focused on taxonomies according to the Linnean system at the cost of obscuring information due to applying species or population averages of body masses and other traits. Following other pioneering studies, we addressed this lingering gap, and studied non‐linear interaction strengths (i.e. functional responses) between two taxonomically‐distinct terrestrial arthropod predators (centipedes and spiders) of varying individual body masses and their prey. We fitted three non‐linear functional response models to the data: (1) a taxonomic model not accounting for variance in body masses amongst predator individuals, (2) an allometric model ignoring taxonomic differences between predator individuals, and (3) a combined model including body mass and taxonomic effects. Ranked according to their AICs, the combined model performs better than the allometric model, which provides a superior fit to the data than the taxonomic model. These results strongly indicate that the body masses of predator and prey individuals were responsible for most of the variation in non‐linear interaction strengths. Taxonomy explained some specific patterns in allometric exponents between groups and revealed mechanistic insights in predation efficiencies. Reconciling quantitative allometric models as employed by the marine size‐spectrum approach with taxonomic information may thus yield quantitative results that are generalized across ecosystem types and taxonomic groups. Using these quantitative models as novel null models should also strengthen subsequent taxonomic analyses.     

Biogeographic patterns in major marine realms: function not taxonomy unites fish assemblages in reef,seagrass and mangrove systems

We examine the effects of different biogeographic histories on assemblage composition in three major marine habitats in two biogeographically distinct marine realms. Specifically, we quantify the taxonomic and functional composition of fish assemblages that characterise coral reef, seagrass and mangrove habitats, to explore the potential effects of biogeographic history and environment on assemblage composition. The three habitats were surveyed in the Caribbean and on the Great Barrier Reef using a standardised underwater visual census method to record fish size and abundance data. The taxonomic composition of assemblages followed biogeographic expectations, with realm‐specific family‐level compositions. In marked contrast, the functional composition of assemblages separated habitats regardless of their biogeographic locations. In essence, taxonomy characterises biogeographic realms while functional groups characterise habitats. The Caribbean and Indo‐West Pacific have been separated for approximately 15 million years. The two realms have different taxonomic structures which reflect this extended separation, however, the three dominant shallow‐water marine habitats all retain distinct functional characteristics: seagrass fishes are functionally similar regardless of their taxonomic composition or biogeographic location. Likewise, for coral reefs and mangroves. The results emphasise the advantages and limitations of taxonomic vs. functional metrics in evaluating patterns. Taxonomy primarily reflects biogeographic and evolutionary history while functional characteristics may better reflect ecological constraints.     

Rapid and accurate taxonomic classification of insect (class Insecta) cytochrome c oxidase subunit 1 (COI) DNA barcode sequences using a naïve Bayesian classifier

Current methods to identify unknown insect (class Insecta) cytochrome c oxidase (COI barcode) sequences often rely on thresholds of distances that can be difficult to define, sequence similarity cut‐offs, or monophyly. Some of the most commonly used metagenomic classification methods do not provide a measure of confidence for the taxonomic assignments they provide. The aim of this study was to use a naïve Bayesian classifier (Wang et al. Applied and Environmental Microbiology, 2007; 73: 5261) to automate taxonomic assignments for large batches of insect COI sequences such as data obtained from high‐throughput environmental sequencing. This method provides rank‐flexible taxonomic assignments with an associated bootstrap support value, and it is faster than the blast ‐based methods commonly used in environmental sequence surveys. We have developed and rigorously tested the performance of three different training sets using leave‐one‐out cross‐validation, two field data sets, and targeted testing of Lepidoptera, Diptera and Mantodea sequences obtained from the Barcode of Life Data system. We found that type I error rates, incorrect taxonomic assignments with a high bootstrap support, were already relatively low but could be lowered further by ensuring that all query taxa are actually present in the reference database. Choosing bootstrap support cut‐offs according to query length and summarizing taxonomic assignments to more inclusive ranks can also help to reduce error while retaining the maximum number of assignments. Additionally, we highlight gaps in the taxonomic and geographic representation of insects in public sequence databases that will require further work by taxonomists to improve the quality of assignments generated using any method.     

A DNA barcode library for 5,200 German flies and midges (Insecta: Diptera) and its implications for metabarcoding‐based biomonitoring

This study summarizes results of a DNA barcoding campaign on German Diptera, involving analysis of 45,040 specimens. The resultant DNA barcode library includes records for 2,453 named species comprising a total of 5,200 barcode index numbers (BINs), including 2,700 COI haplotype clusters without species‐level assignment, so called “dark taxa.” Overall, 88 out of 117 families (75%) recorded from Germany were covered, representing more than 50% of the 9,544 known species of German Diptera. Until now, most of these families, especially the most diverse, have been taxonomically inaccessible. By contrast, within a few years this study provided an intermediate taxonomic system for half of the German Dipteran fauna, which will provide a useful foundation for subsequent detailed, integrative taxonomic studies. Using DNA extracts derived from bulk collections made by Malaise traps, we further demonstrate that species delineation using BINs and operational taxonomic units (OTUs) constitutes an effective method for biodiversity studies using DNA metabarcoding. As the reference libraries continue to grow, and gaps in the species catalogue are filled, BIN lists assembled by metabarcoding will provide greater taxonomic resolution. The present study has three main goals: (a) to provide a DNA barcode library for 5,200 BINs of Diptera; (b) to demonstrate, based on the example of bulk extractions from a Malaise trap experiment, that DNA barcode clusters, labelled with globally unique identifiers (such as OTUs and/or BINs), provide a pragmatic, accurate solution to the “taxonomic impediment”; and (c) to demonstrate that interim names based on BINs and OTUs obtained through metabarcoding provide an effective method for studies on species‐rich groups that are usually neglected in biodiversity research projects because of their unresolved taxonomy.     

Metabarcoding for stomach‐content analyses of Pygmy devil ray (Mobula kuhlii cf. eregoodootenkee): Comparing tissue and ethanol preservative‐derived DNA

The application of high‐throughput sequencing to retrieve multi‐taxon DNA from different substrates such as water, soil, and stomach contents has enabled species identification without prior knowledge of taxon compositions. Here we used three minibarcodes designed to target mitochondrial COI in plankton, 16S in fish, and 16S in crustaceans, to compare ethanol‐ and tissue‐derived DNA extraction methodologies for metabarcoding. The stomach contents of pygmy devilrays (Mobula kuhlii cf. eregoodootenkee) were used to test whether ethanol‐derived DNA would provide a suitable substrate for metabarcoding. The DNA barcoding assays indicated that tissue‐derived operational taxonomic units (OTUs) were greater compared to those from extractions performed directly on the ethanol preservative. Tissue‐derived DNA extraction is therefore recommended for broader taxonomic coverage. Metabarcoding applications should consider including the following: (i) multiple barcodes, both taxon specific (e.g., 12S or 16S) and more universal (e.g., COI or 18S) to overcome bias and taxon misidentification and (ii) PCR inhibitor removal steps that will likely enhance amplification yields. However, where tissue is limited or no longer available, but the ethanol‐preservative medium is still available, metabarcoding directly from ethanol does recover the majority of common OTUs, suggesting the ethanol‐retrieval method could be applicable for dietary studies. Metabarcoding directly from preservative ethanol may also be useful where tissue samples are limited or highly valued; bulk samples are collected, such as for rapid species inventories; or mixed‐voucher sampling is conducted (e.g., for plankton, insects, and crustaceans).     

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.     

Evaluating hybridization capture with RAD probes as a tool for museum genomics with historical bird specimens

Laboratory techniques for high‐throughput sequencing have enhanced our ability to generate DNA sequence data from millions of natural history specimens collected prior to the molecular era, but remain poorly tested at shallower evolutionary time scales. Hybridization capture using restriction site‐associated DNA probes (hyRAD) is a recently developed method for population genomics with museum specimens. The hyRAD method employs fragments produced in a restriction site‐associated double digestion as the basis for probes that capture orthologous loci in samples of interest. While promising in that it does not require a reference genome, hyRAD has yet to be applied across study systems in independent laboratories. Here, we provide an independent assessment of the effectiveness of hyRAD on both fresh avian tissue and dried tissue from museum specimens up to 140 years old and investigate how variable quantities of input DNA affect sequencing, assembly, and population genetic inference. We present a modified bench protocol and bioinformatics pipeline, including three steps for detection and removal of microbial and mitochondrial DNA contaminants. We confirm that hyRAD is an effective tool for sampling thousands of orthologous SNPs from historic museum specimens to describe phylogeographic patterns. We find that modern DNA performs significantly better than historical DNA better during sequencing but that assembly performance is largely equivalent. We also find that the quantity of input DNA predicts %GC content of assembled contiguous sequences, suggesting PCR bias. We caution against sampling schemes that include taxonomic or geographic autocorrelation across modern and historic samples.     

Geminivirus classification and nomenclature: progress and problems

During the last few years there has been some confusion among geminivirologists about how to determine the taxonomic status of a geminivirus and provide appropriate names for newly discovered viruses. The Seventh Report of the International Committee on Taxonomy of Viruses (ICTV) published in 2000, that provides guidelines for classification within the family Geminiviridae, is rapidly becoming obsolete, due mainly to the large number of complete genomic sequences that have become available. These sequences have provided a wealth of information with which to establish a coherent and durable taxonomic system, although the realisation that frequent inter‐species recombination events occur has introduced an additional level of complexity. This has resulted in a number of individual initiatives that were not fully compatible with current classification. The Geminiviridae Study Group of the ICTV exploited the last two International Geminivirus Workshops, held in Puerto Rico (1998) and Norwich, UK (2001), to debate some of the issues arising, allowing taxonomic proposals to be formulated that are in the process of being accepted by the ICTV for publication in the Eighth Report due in 2004. The present paper reviews these established principles and provides a reference with which to name and classify geminiviruses appropriately.     

Decoupling of taxonomic diversity and morphological disparity during decline of the Cambrian trilobite family Pterocephaliidae

Although discordance between taxonomic diversity and morphological disparity is common, little is known about the underlying dynamics that drive this decoupling. Early in the history of the Cambrian trilobite family Pterocephaliidae, there was an increase in taxonomic diversity and morphological diversity. As taxonomic diversity declined in the later history of the clade, range of variation stayed high and disparity continued to increase. However, per‐branch rates of morphological evolution estimated from a recent phylogeny decreased with time. Neither within‐trait nor within‐species variation increased or decreased, suggesting that the declining rates of morphological evolution were more likely related to ecological opportunity or niche partitioning, rather than increasing intrinsic constraints. This is further supported by evidence for increased biofacies associations throughout the time period. Thus, the high disparity seen at low taxonomic diversity late in the history of this clade was due to extinction – either random or targeting mean forms – rather than increased rates of morphological evolution. This pattern also provides a scenario that could account for instances of low taxonomic diversity but high morphological disparity in modern groups.     

Towards a taxonomy of Bacteria and Archaea based on interactive and cumulative data repositories

Taxonomy in the second decade of the 21st century is benefiting from technological advances in molecular microbiology, especially those related to genomics. Gene and genome databases are significantly increasing due to intense research activities in the field of molecular ecology and genomics. Taxa, and especially species, are tailored by means of the recognition of a phylogenetic, genomic and phenotypic coherence that reveal their uniqueness in the classification schema. Phylogenetic coherence is mainly revealed by means of 16S rRNA gene analyses for which curated databases such as EzTaxon and LTP provide a valuable tool for tree reconstruction to taxonomy users. On the other hand, in silico full or partial genomic sequence comparisons are called on to substitute cumbersome techniques such as DNA-DNA hybridization (DDH) to genomically circumscribe species. DDH similarity values around 70% would be equivalent to ANI values of 96%. Finally, finding an exclusive phenotypic property for the taxa to be classified is of paramount relevance to producing an operative and predictive classification system. The current methods used for taxonomic classification require significant laboratory experimentation, and generally will not produce interactive databases. The new high-throughput metabolomic technologies, such as ICR-FT and MALDI-TOF mass spectrometry methods, open the door to the construction of metabolic databases for taxonomic purposes. It is to be foreseen that, in the future, taxonomists will benefit significantly from public databases speeding up the classification process. However, serious effort will be needed to harmonize them and to prevent inaccurate material.     

Genomic data reveal deep genetic structure but no support for current taxonomic designation in a grasshopper species complex

Taxonomy has traditionally relied on morphological and ecological traits to interpret and classify biological diversity. Over the last decade, technological advances and conceptual developments in the field of molecular ecology and systematics have eased the generation of genomic data and changed the paradigm of biodiversity analysis. Here we illustrate how traditional taxonomy has led to species designations that are supported neither by high throughput sequencing data nor by the quantitative integration of genomic information with other sources of evidence. Specifically, we focus on Omocestus antigai and Omocestus navasi, two montane grasshoppers from the Pyrenean region that were originally described based on quantitative phenotypic differences and distinct habitat associations (alpine vs. Mediterranean‐montane habitats). To validate current taxonomic designations, test species boundaries, and understand the factors that have contributed to genetic divergence, we obtained phenotypic (geometric morphometrics) and genome‐wide SNP data (ddRADSeq) from populations covering the entire known distribution of the two taxa. Coalescent‐based phylogenetic reconstructions, integrative Bayesian model‐based species delimitation, and landscape genetic analyses revealed that populations assigned to the two taxa show a spatial distribution of genetic variation that do not match with current taxonomic designations and is incompatible with ecological/environmental speciation. Our results support little phenotypic variation among populations and a marked genetic structure that is mostly explained by geographic distances and limited population connectivity across the abrupt landscapes characterizing the study region. Overall, this study highlights the importance of integrative approaches to identify taxonomic units and elucidate the evolutionary history of species.     

Integrating DNA data and traditional taxonomy to streamline biodiversity assessment: an example from edaphic beetles in the Klamath ecoregion, California, USA

Conservation and land management decisions may be misguided by inaccurate or misinterpreted knowledge of biodiversity. Non‐systematists often lack taxonomic expertise necessary for an accurate assessment of biodiversity. Additionally, there are far too few taxonomists to contribute significantly to the task of identifying species for specimens collected in biodiversity studies. While species level identification is desirable for making informed management decisions concerning biodiversity, little progress has been made to reduce this taxonomic deficiency. Involvement of non‐systematists in the identification process could hasten species identification. Incorporation of DNA sequence data has been recognized as one way to enhance biodiversity assessment and species identification. DNA data are now technologically and economically feasible for most scientists to apply in biodiversity studies. However, its use is not widespread and means of its application has not been extensively addressed. This paper illustrates how such data can be used to hasten biodiversity assessment of species using a little‐known group of edaphic beetles. Partial mitochondrial cytochrome oxidase I was sequenced for 171 individuals of feather‐wing beetles (Coleoptera: Ptiliidae) from the Klamath ecoregion, which is part of a biodiversity hotspot, the California Floristic Province. A phylogram of these data was reconstructed via parsimony and the strict consensus of 28,000 equally parsimonious trees was well resolved except for peripheral nodes. Forty‐two voucher specimens were selected for further identification from clades that were associated with many synonymous and non‐synonymous nucleotide changes. A ptiliid taxonomic expert identified nine species that corresponded to monophyletic groups. These results allowed for a more accurate assessment of ptiliid species diversity in the Klamath ecoregion. In addition, we found that the number of amino acid changes or percentage nucleotide difference did not associate with species limits. This study demonstrates that the complementary use of taxonomic expertise and molecular data can improve both the speed and the accuracy of species‐level biodiversity assessment. We believe this represents a means for non‐systematists to collaborate directly with taxonomists in species identification and represents an improvement over methods that rely solely on parataxonomy or sequence data.     

Environmental metabarcodes for insects: in silico PCR reveals potential for taxonomic bias

Studies of insect assemblages are suited to the simultaneous DNA‐based identification of multiple taxa known as metabarcoding. To obtain accurate estimates of diversity, metabarcoding markers ideally possess appropriate taxonomic coverage to avoid PCR‐amplification bias, as well as sufficient sequence divergence to resolve species. We used in silico PCR to compare the taxonomic coverage and resolution of newly designed insect metabarcodes (targeting 16S) with that of existing markers [16S and cytochrome oxidase c subunit I (COI)] and then compared their efficiency in vitro. Existing metabarcoding primers amplified in silico <75% of insect species with complete mitochondrial genomes available, whereas new primers targeting 16S provided >90% coverage. Furthermore, metabarcodes targeting COI appeared to introduce taxonomic PCR‐amplification bias, typically amplifying a greater percentage of Lepidoptera and Diptera species, while failing to amplify certain orders in silico. To test whether bias predicted in silico was observed in vitro, we created an artificial DNA blend containing equal amounts of DNA from 14 species, representing 11 insect orders and one arachnid. We PCR‐amplified the blend using five primer sets, targeting either COI or 16S, with high‐throughput amplicon sequencing yielding more than 6 million reads. In vitro results typically corresponded to in silico PCR predictions, with newly designed 16S primers detecting 11 insect taxa present, thus providing equivalent or better taxonomic coverage than COI metabarcodes. Our results demonstrate that in silico PCR is a useful tool for predicting taxonomic bias in mixed template PCR and that researchers should be wary of potential bias when selecting metabarcoding markers.     

Bushmeat genetics: setting up a reference framework for the DNA typing of African forest bushmeat

The bushmeat trade in tropical Africa represents illegal, unsustainable off‐takes of millions of tons of wild game – mostly mammals – per year. We sequenced four mitochondrial gene fragments (cyt b, COI, 12S, 16S) in >300 bushmeat items representing nine mammalian orders and 59 morphological species from five western and central African countries (Guinea, Ghana, Nigeria, Cameroon and Equatorial Guinea). Our objectives were to assess the efficiency of cross‐species PCR amplification and to evaluate the usefulness of our multilocus approach for reliable bushmeat species identification. We provide a straightforward amplification protocol using a single ‘universal’ primer pair per gene that generally yielded >90% PCR success rates across orders and was robust to different types of meat preprocessing and DNA extraction protocols. For taxonomic identification, we set up a decision pipeline combining similarity‐ and tree‐based approaches with an assessment of taxonomic expertise and coverage of the GENBANK database. Our multilocus approach permitted us to: (i) adjust for existing taxonomic gaps in GENBANK databases, (ii) assign to the species level 67% of the morphological species hypotheses and (iii) successfully identify samples with uncertain taxonomic attribution (preprocessed carcasses and cryptic lineages). High levels of genetic polymorphism across genes and taxa, together with the excellent resolution observed among species‐level clusters (neighbour‐joining trees and Klee diagrams) advocate the usefulness of our markers for bushmeat DNA typing. We formalize our DNA typing decision pipeline through an expert‐curated query database – DNAbushmeat – that shall permit the automated identification of African forest bushmeat items.     

Beyond DNA barcoding: The unrealized potential of genome skim data in sample identification

Genetic tools are increasingly used to identify and discriminate between species. One key transition in this process was the recognition of the potential of the ca 658bp fragment of the organelle cytochrome c oxidase I (COI) as a barcode region, which revolutionized animal bioidentification and lead, among others, to the instigation of the Barcode of Life Database (BOLD), containing currently barcodes from >7.9 million specimens. Following this discovery, suggestions for other organellar regions and markers, and the primers with which to amplify them, have been continuously proposed. Most recently, the field has taken the leap from PCR‐based generation of DNA references into shotgun sequencing‐based “genome skimming” alternatives, with the ultimate goal of assembling organellar reference genomes. Unfortunately, in genome skimming approaches, much of the nuclear genome (as much as 99% of the sequence data) is discarded, which is not only wasteful, but can also limit the power of discrimination at, or below, the species level. Here, we advocate that the full shotgun sequence data can be used to assign an identity (that we term for convenience its “DNA‐mark”) for both voucher and query samples, without requiring any computationally intensive pretreatment (e.g. assembly) of reads. We argue that if reference databases are populated with such “DNA‐marks,” it will enable future DNA‐based taxonomic identification to complement, or even replace PCR of barcodes with genome skimming, and we discuss how such methodology ultimately could enable identification to population, or even individual, level.