1.Traditional biodiversity assessment is costly in time, money and taxonomic expertise. Moreover, data are frequently collected in ways (e.g. visual bird lists) that are unsuitable for auditing by neutral parties, which is necessary for dispute resolution. 2. We present protocols for the extraction of ecological, taxonomic and phylogenetic information from bulk samples of arthropods. The protocols combine mass trapping of arthropods, mass-PCR amplification of the COI barcode gene, pyrosequencing and bioinformatic analysis, which together we call 'metabarcoding'. 3. We construct seven communities of arthropods (mostly insects) and show that it is possible to recover a substantial proportion of the original taxonomic information. We further demonstrate, for the first time, that metabarcoding allows for the precise estimation of pairwise community dissimilarity (beta diversity) and within-community phylogenetic diversity (alpha diversity), despite the inevitable loss of taxonomic information inherent to metabarcoding. 4. Alpha and beta diversity metrics are the raw materials of ecology and the environmental sciences, facilitating assessment of the state of the environment with a broad and efficient measure of biodiversity.
Summary Bee populations and other pollinators face multiple, synergistically acting threats, which have led to population declines, loss of local species richness and pollination services, and extinctions. However, our understanding of the degree, distribution and causes of declines is patchy, in part due to inadequate monitoring systems, with the challenge of taxonomic identification posing a major logistical barrier. Pollinator conservation would benefit from a high‐throughput identification pipeline.We show that the metagenomic mining and resequencing of mitochondrial genomes (mitogenomics) can be applied successfully to bulk samples of wild bees. We assembled the mitogenomes of 48 UK bee species and then shotgun‐sequenced total DNA extracted from 204 whole bees that had been collected in 10 pan‐trap samples from farms in England and been identified morphologically to 33 species. Each sample data set was mapped against the 48 reference mitogenomes.The morphological and mitogenomic data sets were highly congruent. Out of 63 total species detections in the morphological data set, the mitogenomic data set made 59 correct detections (93·7% detection rate) and detected six more species (putative false positives). Direct inspection and an analysis with species‐specific primers suggested that these putative false positives were most likely due to incorrect morphological IDs. Read frequency significantly predicted species biomass frequency (R 2 = 24·9%). Species lists, biomass frequencies, extrapolated species richness and community structure were recovered with less error than in a metabarcoding pipeline.Mitogenomics automates the onerous task of taxonomic identification, even for cryptic species, allowing the tracking of changes in species richness and distributions. A mitogenomic pipeline should thus be able to contain costs, maintain consistently high‐quality data over long time series, incorporate retrospective taxonomic revisions and provide an auditable evidence trail. Mitogenomic data sets also provide estimates of species counts within samples and thus have potential for tracking population trajectories.
Pacific salmon are a keystone resource in Alaska, generating annual revenues of well over ~US$500 million/year. Due to their anadromous life history, adult spawners distribute amongst thousands of streams, posing a huge management challenge. Currently, spawners are enumerated at just a few streams because of reliance on human counters and, rarely, sonar. The ability to detect organisms by shed tissue (environmental DNA, eDNA) promises a more efficient counting method. However, although eDNA correlates generally with local fish abundances, we do not know if eDNA can accurately enumerate salmon. Here we show that daily, and near‐daily, flow‐corrected eDNA rate closely tracks daily numbers of returning sockeye and coho spawners and outmigrating sockeye smolts. eDNA thus promises accurate and efficient enumeration, but to deliver the most robust numbers will need higher‐resolution stream‐flow data, at‐least‐daily sampling, and a focus on species with simple life histories, since shedding rate varies amongst jacks, juveniles, and adults.
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