Aerial insectivores are highly mobile predators that feed on diverse prey items that have highly variable distributions. As such, investigating the diet, prey selection and prey availability of aerial insectivores can be challenging. In this study, we used an integrated DNA barcoding method to investigate the diet and food supply of Barn Swallows, an aerial insectivore whose North American population has declined over the past 40 yr. We tested the hypotheses that Barn Swallows are generalist insectivores when provisioning their young and select prey based on size. We predicted that the diets of nestlings would contain a range of insect taxa but would be biased towards large prey items and that the diet of nestlings would change as prey availability changed. We collected insects using Malaise traps at 10 breeding sites and identified specimens using standard DNA barcoding. The sequences from these insect specimens were used to create a custom reference database of prey species and their relative sizes for our study area. We identified insect prey items from nestling fecal samples by using high-throughput DNA sequencing and comparing the sequences to our custom reference database. Barn Swallows fed nestlings prey items from 130 families representing 13 orders but showed selection for larger prey items that were predominantly from 7 dipteran families. Nestling diet varied both within and between breeding seasons as well as between breeding sites. This dietary flexibility suggests that Barn Swallows are able to adjust their provisioning to changing prey availability on the breeding grounds when feeding their nestlings. Our study demonstrates the utility of custom reference databases for linking the abundance and size of insect prey in the habitat with prey consumed when employing molecular methods for dietary analysis.
Global biodiversity loss is unprecedented, and threats to existing biodiversity are growing. Given pervasive global change, a major challenge facing resource managers is a lack of scalable tools to rapidly and consistently measure Earth's biodiversity. Environmental genomic tools provide some hope in the face of this crisis, and DNA metabarcoding, in particular, is a powerful approach for biodiversity assessment at large spatial scales. However, metabarcoding studies are variable in their taxonomic, temporal, or spatial scope, investigating individual species, specific taxonomic groups, or targeted communities at local or regional scales. With the advent of modern, ultra-high throughput sequencing platforms, conducting deep sequencing metabarcoding surveys with multiple DNA markers will enhance the breadth of biodiversity coverage, enabling comprehensive, rapid bioassessment of all the organisms in a sample. Here, we report on a systematic literature review of 1,563 articles published about DNA metabarcoding and summarize how this approach is rapidly revolutionizing global bioassessment efforts. Specifically, we quantify the stakeholders using DNA metabarcoding, the dominant applications of this technology, and the taxonomic groups assessed in these studies. We show that while DNA metabarcoding has reached global coverage, few studies deliver on its promise of near-comprehensive biodiversity assessment. We then outline how DNA metabarcoding can help us move toward real-time, global bioassessment, illustrating how different stakeholders could benefit from DNA metabarcoding. Next, we address barriers to widespread adoption of DNA metabarcoding, highlighting the need for standardized sampling protocols, experts and computational resources to handle the deluge of genomic data, and standardized, open-source bioinformatic pipelines. Finally, we explore how technological and scientific advances will realize the promise of total biodiversity assessment in a sample—from microbes to mammals—and unlock the rich information genomics exposes, opening new possibilities for merging whole-system DNA metabarcoding with (1) abundance and biomass quantification, (2) advanced modeling, such as species occupancy models, to improve species detection, (3) population genetics, (4) phylogenetics, and (5) food web and functional gene analysis. While many challenges need to be addressed to facilitate widespread adoption of environmental genomic approaches, concurrent scientific and technological advances will usher in methods to supplement existing bioassessment tools reliant on morphological and abiotic data. This expanded toolbox will help ensure that the best tool is used for the job and enable exciting integrative techniques that capitalize on multiple tools. Collectively, these new approaches will aid in addressing the global biodiversity crisis we now face.
Environmental DNA (eDNA) metabarcoding is an increasingly popular method for rapid biodiversity assessment. As with any ecological survey, false negatives can arise during sampling and, if unaccounted for, lead to biased results and potentially misdiagnosed environmental assessments. We developed a multi-scale, multi-species occupancy model for the analysis of community biodiversity data resulting from eDNA metabarcoding; this model accounts for imperfect detection and additional sources of environmental and experimental variation. We present methods for model assessment and model comparison and demonstrate how these tools improve the inferential power of eDNA metabarcoding data using a case study in a coastal, marine environment. Using occupancy models to account for factors often overlooked in the analysis of eDNA metabarcoding data will dramatically improve ecological inference, sampling design, and methodologies, empowering practitioners with an approach to wield the high-resolution biodiversity data of next-generation sequencing platforms. OPEN ACCESS Citation: McClenaghan B, Compson ZG, Hajibabaei M (2020) Validating metabarcoding-based biodiversity assessments with multi-species occupancy models: A case study using coastal marine eDNA. PLoS ONE 15(3): e0224119. https://
The deep ocean is the largest biome on Earth and faces increasing anthropogenic pressures from climate change and commercial fisheries. Our ability to sustainably manage this expansive habitat is impeded by our poor understanding of its inhabitants and by the difficulties in surveying and monitoring these areas. Environmental DNA (eDNA) metabarcoding has great potential to improve our understanding of this region and to facilitate monitoring across a broad range of taxa. Here, we evaluate two eDNA sampling protocols and seven primer sets for elucidating fish diversity from deep sea water samples. We found that deep sea water samples (> 1400 m depth) had significantly lower DNA concentrations than surface or mid-depth samples necessitating a refined protocol with a larger sampling volume. We recovered significantly more DNA in large volume water samples (1.5 L) filtered at sea compared to small volume samples (250 mL) held for lab filtration. Furthermore, the number of unique sequences (exact sequence variants; ESVs) recovered per sample was higher in large volume samples. Since the number of ESVs recovered from large volume samples was less variable and consistently high, we recommend the larger volumes when sampling water from the deep ocean. We also identified three primer sets which detected the most fish taxa but recommend using multiple markers due the variability in detection probabilities and taxonomic resolution among fishes for each primer set. Overall, fish diversity results obtained from metabarcoding were comparable to conventional survey methods. While eDNA sampling and processing need be optimized for this unique environment, the results of this study demonstrate that eDNA metabarcoding can facilitate biodiversity surveys in the deep ocean, require less dedicated survey effort per unit identification, and are capable of simultaneously providing valuable information on other taxonomic groups.
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