The genomic revolution has fundamentally changed how we survey biodiversity on earth. High‐throughput sequencing (“HTS”) platforms now enable the rapid sequencing of DNA from diverse kinds of environmental samples (termed “environmental DNA” or “eDNA”). Coupling HTS with our ability to associate sequences from eDNA with a taxonomic name is called “eDNA metabarcoding” and offers a powerful molecular tool capable of noninvasively surveying species richness from many ecosystems. Here, we review the use of eDNA metabarcoding for surveying animal and plant richness, and the challenges in using eDNA approaches to estimate relative abundance. We highlight eDNA applications in freshwater, marine and terrestrial environments, and in this broad context, we distill what is known about the ability of different eDNA sample types to approximate richness in space and across time. We provide guiding questions for study design and discuss the eDNA metabarcoding workflow with a focus on primers and library preparation methods. We additionally discuss important criteria for consideration of bioinformatic filtering of data sets, with recommendations for increasing transparency. Finally, looking to the future, we discuss emerging applications of eDNA metabarcoding in ecology, conservation, invasion biology, biomonitoring, and how eDNA metabarcoding can empower citizen science and biodiversity education.

Identifying the floral composition of honey provides a method for investigating the plants that honey bees visit. We compared melissopalynology, where pollen grains retrieved from honey are identified morphologically, with a DNA metabarcoding approach using the rbcL DNA barcode marker and 454-pyrosequencing. We compared nine honeys supplied by beekeepers in the UK. DNA metabarcoding and melissopalynology were able to detect the most abundant floral components of honey. There was 92% correspondence for the plant taxa that had an abundance of over 20%. However, the level of similarity when all taxa were compared was lower, ranging from 22–45%, and there was little correspondence between the relative abundance of taxa found using the two techniques. DNA metabarcoding provided much greater repeatability, with a 64% taxa match compared to 28% with melissopalynology. DNA metabarcoding has the advantage over melissopalynology in that it does not require a high level of taxonomic expertise, a greater sample size can be screened and it provides greater resolution for some plant families. However, it does not provide a quantitative approach and pollen present in low levels are less likely to be detected. We investigated the plants that were frequently used by honey bees by examining the results obtained from both techniques. Plants with a broad taxonomic range were detected, covering 46 families and 25 orders, but a relatively small number of plants were consistently seen across multiple honey samples. Frequently found herbaceous species were Rubus fruticosus, Filipendula ulmaria, Taraxacum officinale, Trifolium spp., Brassica spp. and the non-native, invasive, Impatiens glandulifera. Tree pollen was frequently seen belonging to Castanea sativa, Crataegus monogyna and species of Malus, Salix and Quercus. We conclude that although honey bees are considered to be supergeneralists in their foraging choices, there are certain key species or plant groups that are particularly important in the honey bees environment. The reasons for this require further investigation in order to better understand honey bee nutritional requirements. DNA metabarcoding can be easily and widely used to investigate floral visitation in honey bees and can be adapted for use with other insects. It provides a starting point for investigating how we can better provide for the insects that we rely upon for pollination.

Identification of the species origin of pollen has many applications, including assessment of plant–pollinator networks, reconstruction of ancient plant communities, product authentication, allergen monitoring, and forensics. Such applications, however, have previously been limited by microscopy-based identification of pollen, which is slow, has low taxonomic resolution, and has few expert practitioners. One alternative is pollen DNA barcoding, which could overcome these issues. Recent studies demonstrate that both chloroplast and nuclear barcoding markers can be amplified from pollen. These recent validations of pollen metabarcoding indicate that now is the time for researchers in various fields to consider applying these methods to their research programs. In this paper, we review the nascent field of pollen DNA barcoding and discuss potential new applications of this technology, highlighting existing limitations and future research developments that will improve its utility in a wide range of applications.

We present the first national DNA barcode resource that covers the native flowering plants and conifers for the nation of Wales (1143 species). Using the plant DNA barcode markers rbcL and matK, we have assembled 97.7% coverage for rbcL, 90.2% for matK, and a dual-locus barcode for 89.7% of the native Welsh flora. We have sampled multiple individuals for each species, resulting in 3304 rbcL and 2419 matK sequences. The majority of our samples (85%) are from DNA extracted from herbarium specimens. Recoverability of DNA barcodes is lower using herbarium specimens, compared to freshly collected material, mostly due to lower amplification success, but this is balanced by the increased efficiency of sampling species that have already been collected, identified, and verified by taxonomic experts. The effectiveness of the DNA barcodes for identification (level of discrimination) is assessed using four approaches: the presence of a barcode gap (using pairwise and multiple alignments), formation of monophyletic groups using Neighbour-Joining trees, and sequence similarity in BLASTn searches. These approaches yield similar results, providing relative discrimination levels of 69.4 to 74.9% of all species and 98.6 to 99.8% of genera using both markers. Species discrimination can be further improved using spatially explicit sampling. Mean species discrimination using barcode gap analysis (with a multiple alignment) is 81.6% within 10×10 km squares and 93.3% for 2×2 km squares. Our database of DNA barcodes for Welsh native flowering plants and conifers represents the most complete coverage of any national flora, and offers a valuable platform for a wide range of applications that require accurate species identification.

Understanding which flowers honey bees (Apis mellifera) use for forage can help us to provide suitable plants for healthy honey bee colonies. Accordingly, honey DNA metabarcoding provides a valuable tool for investigating pollen and nectar collection. We investigated early season (April and May) floral choice by honey bees provided with a very high diversity of flowering plants within the National Botanic Garden of Wales. There was a close correspondence between the phenology of flowering and the detection of plants within the honey. Within the study area there were 437 genera of plants in flower during April and May, but only 11% of these were used. Thirty-nine plant taxa were recorded from three hives but only ten at greater than 1%. All three colonies used the same core set of native or near-native plants, typically found in hedgerows and woodlands. The major plants were supplemented with a range of horticultural species, with more variation in plant choice between the honey bee colonies. We conclude that during the spring, honey bees need access to native hedgerows and woodlands to provide major plants for foraging. Gardens provide supplementary flowers that may increase the nutritional diversity of the honey bee diet.

Pollination by insects is a key ecosystem service and important to wider ecosystem function. Most species‐level pollination networks studied have a generalised structure, with plants having several potential pollinators, and pollinators in turn visiting a number of different plant species. This is in apparent contrast to a plant's need for efficient conspecific pollen transfer. The aim of this study was to investigate the structure of pollen transport networks at three levels of biological hierarchy: community, species and individual. We did this using hoverflies in the genus Eristalis, a key group of non‐Hymenopteran pollinators. We constructed pollen transport networks using DNA metabarcoding to identify pollen. We captured hoverflies in conservation grasslands in west Wales, UK, removed external pollen loads, sequenced the pollen DNA on the Illumina MiSeq platform using the standard plant barcode rbcL, and matched sequences using a pre‐existing plant DNA barcode reference library. We found that Eristalis hoverflies transport pollen from 65 plant taxa, more than previously appreciated. Networks were generalised at the site and species level, suggesting some degree of functional redundancy, and were more generalised in late summer compared to early summer. In contrast, pollen transport at the individual level showed some degree of specialisation. Hoverflies defined as “single‐plant visitors” varied from 40% of those captured in early summer to 24% in late summer. Individual hoverflies became more generalised in late summer, possibly in response to an increase in floral resources. Rubus fruticosus agg. and Succisa pratensis were key plant species for hoverflies at our sites Our results contribute to resolving the apparent paradox of how generalised pollinator networks can provide efficient pollination to plant species. Generalised hoverfly pollen transport networks may result from a varied range of short‐term specialised feeding bouts by individual insects. The generalisation and functional redundancy of Eristalis pollen transport networks may increase the stability of the pollination service they deliver.