ArticlePloS one2020
Validating metabarcoding-based biodiversity assessments with multi-species occupancy models: A case study using coastal marine eDNA.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed.
- Leveraging artificial intelligence to enhance marine biosecurity.Bioscience · 2026Review
- Making eDNA more digestible: A pizza analogy for understanding false negatives and occupancy modeling.Bioscience · 2026Review
- Environmental DNA metabarcoding facilitates integrative conservation assessments and species rediscoveries in tropical biodiversity hotspots.Scientific reports · 2026Article
- Article
- Harnessing environmental DNA to reveal biogeographical patterns of non-indigenous species for improved co-governance of the marine environment in Aotearoa New Zealand.Scientific reports · 2023Article
- Optimal sample type and number vary in small shallow lakes when targeting non-native fish environmental DNA.PeerJ · 2023Article
- The community ecology perspective of omics data.Microbiome · 2022Article
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- Article
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
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