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The delivery of consistent and accurate fine‐resolution data on biodiversity using metabarcoding promises to improve environmental assessment and research. Whilst this approach is a substantial improvement upon traditional techniques, critics note that metabarcoding data are suitable for establishing taxon occurrence, but not abundance. We propose a novel hierarchical approach to recovering abundance information from metabarcoding, and demonstrate this technique using benthic macroinvertebrates. To sample a range of abundance structures without introducing additional changes in composition, we combined seasonal surveys with fish‐exclusion experiments at Catamaran Brook in northern New Brunswick, Canada. Five monthly surveys collected 31 benthic samples for DNA metabarcoding divided between caged and control treatments. A further six samples per survey were processed using traditional morphological identification for comparison. By estimating the probability of detecting a single individual, multispecies abundance models infer changes in abundance based on changes in detection frequency. Using replicate detections of 184 genera (and 318 species) from metabarcoding samples, our analysis identified changes in abundance arising from both seasonal dynamics and the exclusion of fish predators. Counts obtained from morphological samples were highly variable, a feature that limited the opportunity for more robust comparison, and emphasizing the difficulty standard methods also face to detect changes in abundance. Our approach is the first to demonstrate how quantitative estimates of abundance can be made using metabarcoding, both among species within sites as well as within species among sites. Many samples are required to capture true abundance patterns, particularly in streams where counts are highly variable, but few studies can afford to process entire samples. Our approach allows study of responses across whole communities, and at fine taxonomic resolution. We discuss how ecological studies can use additional sampling to capture changes in abundance at fine resolution, and how this can complement broad‐scale biomonitoring using DNA metabarcoding. [ABSTRACT FROM AUTHOR]

Insect metabarcoding has been mainly based on PCR amplification of short fragments within the "barcoding region" of the gene cytochrome oxidase I (COI). However, because of the variability of this gene, it has been difficult to design good universal PCR primers. Most primers used today are associated with gaps in the taxonomic coverage or amplification biases that make the results less reliable and impede the detection of species that are present in the sample. We identify new primers for insect metabarcoding using computational approaches (ecoprimers and degeprime) applied to the most comprehensive reference databases of mitochondrial genomes of Hexapoda assembled to date. New primers are evaluated in silico against previously published primers in terms of taxonomic coverage and resolution of the corresponding amplicons. For the latter criterion, we propose a new index, exclusive taxonomic resolution, which is a more biologically meaningful measure than the standard index used today. Our results show that the best markers are found in the ribosomal RNA genes (12S and 16S); they resolve about 90% of the genetically distinct species in the reference database. Some markers in protein‐coding genes provide similar performance but only at much higher levels of primer degeneracy. Combining two of the best individual markers improves the effective taxonomic resolution with up to 10%. The resolution is strongly dependent on insect taxon: COI primers detect 40% of Hymenoptera, while 12S primers detect 12% of Collembola. Our results indicate that amplicon‐based metabarcoding of insect samples can be improved by choosing other primers than those commonly used today. [ABSTRACT FROM AUTHOR]

The first step in many community ecology studies is to produce a species list from a sample of individuals. Community ecologists now have two viable ways of producing a species list: morphological and barcode identification. In this study, we compared the taxonomic resolution gained by a combined use of both methods and tested whether a change in taxonomic resolution significantly impacted richness estimates for benthic macroinvertebrates sampled from ten lakes in Sequoia National Park, USA. Across all lakes, 77 unique taxa were identified and 42% (32) were reliably identified to species using both barcode and morphological identification. Of the 32 identified to species, 63% (20) were identified solely by comparing the barcode sequence from cytochrome oxidase I to the Barcode of Life reference library. The increased resolution using a combined identification approach compared to identifications based solely on morphology resulted in a significant increase in estimated richness within a lake at the order, family, genus and species levels of taxonomy ( P < 0.05). Additionally, young or damaged individuals that could not be identified using morphology were identified using their COI sequences to the genus or species level on average 75% of the time. Our results demonstrate that a combined identification approach improves accuracy of benthic macroinvertebrate species lists in alpine lakes and subsequent estimates of richness. We encourage the use of barcodes for identification purposes and specifically when morphology is insufficient, as in the case of damaged and early life stage specimens of benthic macroinvertebrates. [ABSTRACT FROM AUTHOR]

Insect metabarcoding has been mainly based on PCR amplification of short fragments within the "barcoding region" of the gene cytochrome oxidase I (COI). However, because of the variability of this gene, it has been difficult to design good universal PCR primers. Most primers used today are associated with gaps in the taxonomic coverage or amplification biases that make the results less reliable and impede the detection of species that are present in the sample. We identify new primers for insect metabarcoding using computational approaches (ecoprimers and degeprime) applied to the most comprehensive reference databases of mitochondrial genomes of Hexapoda assembled to date. New primers are evaluated in silico against previously published primers in terms of taxonomic coverage and resolution of the corresponding amplicons. For the latter criterion, we propose a new index, exclusive taxonomic resolution, which is a more biologically meaningful measure than the standard index used today. Our results show that the best markers are found in the ribosomal RNA genes (12S and 16S); they resolve about 90% of the genetically distinct species in the reference database. Some markers in protein-coding genes provide similar performance but only at much higher levels of primer degeneracy. Combining two of the best individual markers improves the effective taxonomic resolution with up to 10%. The resolution is strongly dependent on insect taxon: COI primers detect 40% of Hymenoptera, while 12S primers detect 12% of Collembola. Our results indicate that amplicon-based metabarcoding of insect samples can be improved by choosing other primers than those commonly used today., (© 2018 The Authors. Molecular Ecology Resources Published by John Wiley & Sons Ltd.)