Validating metabarcoding-based biodiversity assessments with multi-species occupancy models: A case study using coastal marine eDNA

McClenaghan, Beverly; Compson, Zacchaeus G.; Hajibabaei, Mehrdad

doi:10.1371/journal.pone.0224119

Cited by 41 publications

(45 citation statements)

References 61 publications

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“…In previous studies of eDNA metabarcoding, multispecies site occupancy models have been applied by aggregating sequence reads into binary detection/non-detection data (Doi et al 2019, Bush et al 2020, McClenaghan et al 2020, McColl-Gausden et al 2020. In such an approach, sequence read counts are not explicitly modeled, making it difficult to adequately decompose the combined effects of throughput and relative frequency of species sequences on the probability of species detection.…”

Section: Discussionmentioning

confidence: 99%

“…To address these issues, we developed a novel extension of the multispecies site occupancy modeling framework (Dorazio & Royle 2005, Dorazio et al 2006. Multispecies site occupancy models account for the imperfect detection of species in a metacommunity and have recently been applied in eDNA metabarcoding (Doi et al 2019, Bush et al 2020, McClenaghan et al 2020, McColl-Gausden et al 2020. However, to apply these models to eDNA metabarcoding data, the original sequence read counts must be aggregated into binary detection and non-detection indicators.…”

Section: Introductionmentioning

confidence: 99%

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Multispecies site occupancy modeling and study design for spatially replicated environmental DNA metabarcoding

Fukaya

Kondo

Matsuzaki

et al. 2021

Preprint

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Environmental DNA (eDNA) metabarcoding has become widely applied to gauge biodiversity in a noninvasive and cost-efficient manner. The detection of species using eDNA metabarcoding is, however, imperfect owing to various factors that can cause false negatives in the inherent multi-stage workflow. Imperfect detection in the multi-stage workflow of eDNA metabarcoding also raises an issue of study design: namely, how available resources should be allocated among the different stages to optimize survey efficiency. Here, we propose a variant of the multispecies site occupancy model for eDNA metabarcoding studies where samples are collected at multiple sites within a region of interest. This model describes the variation in sequence reads, the unique output of the high-throughput sequencers, in terms of the hierarchical workflow of eDNA metabarcoding and interspecific heterogeneity, allowing the decomposition of the sources of variation in the detectability of species throughout the different stages of the workflow. We also introduced a Bayesian decision analysis framework to identify the study design that optimizes the efficiency of species detection with a limited budget. An application of the model to freshwater fish communities in the Lake Kasumigaura watershed, in Japan, highlighted a remarkable inhomogeneity in the detectability of species, indicating a potential risk of the biased detection of specific species. Species with lower site occupancy probabilities tended to be difficult to detect as they had lower capture probabilities and lower dominance of the sequences. The expected abundance of sequence reads was predicted to vary by up to 23.5 times between species. An analysis of the study design suggested that ensuring multiple within-site replications of the environmental samples is preferred in order to achieve better species detection efficiency, provided that a throughput of tens of thousands of sequence reads was secured. The proposed framework makes the application of eDNA metabarcoding more error-tolerant, allowing ecologists to monitor ecological communities more efficiently.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multispecies site occupancy modeling and study design for spatially replicated environmental DNA metabarcoding

Fukaya

Kondo

Matsuzaki

et al. 2021

Preprint

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“…Up to now, most occupancy models used in an eDNA context have been applied to single-species data, with multispecies approaches starting to be developed more recently (Doi et al, 2019;McClenaghan et al, 2020). Such multispecies metabarcoding-based assessments have the major advantage of providing information on biodiversity and community composition.…”

Section: Occupancy Modelsmentioning

confidence: 99%

“…Recently developed multispecies occupancy models for eDNA data (Doi et al, 2019;McClenaghan et al, 2020) are an important advancement but do not account for species interactions in their model structure. The other end of the spectrum is represented by joint distribution models, which incorporate complex interactions among species or functional groups but which are often highly complex and data hungry (Pollock et al, 2014).…”

Section: Computational "Add-ons" To Occupancy Modelsmentioning

confidence: 99%

Improving the reliability of eDNA data interpretation

Burian

Mauvisseau

Bulling

et al. 2021

Molecular Ecology Resources

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Since the beginning of the last century, global species extinctions have occurred at unprecedented rates and currently over a million species are at risk (IPBES, 2019). Rapid transformations of natural ecosystems and habitat degradation highlight the urgent need for effective conservation strategies to mitigate further biodiversity losses. A prerequisite for the development of such strategies is the provision of comprehensive, reliable and frequently updated monitoring data, recording distribution changes of vulnerable, endangered and invasive species.A promising approach that is currently gaining momentum and fulfils such monitoring objectives relies on the detection of genetic traces left by organisms, also referred to as environmental DNA (or eDNA). Substantial advantages of eDNA-based methods are higher cost and time effectiveness compared to many traditional survey methods (Evans et al., 2017), their noninvasive nature (Cristescu & Hebert, 2018), and high specificity and sensitivity (Wilcox et al., 2013). However, eDNA-based methods have only been applied for about a decade in conservation management, and method reliability and accuracy are still being refined (Cristescu & Hebert, 2018).

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“…Environmental DNA (eDNA) is increasingly used within biodiversity assessments (McClenaghan et al, 2020). The method relies on the detection of DNA released from source organisms into aquatic or terrestrial environments.…”

Section: Introductionmentioning

confidence: 99%

An Rshiny app for modelling environmental DNA data: accounting for false positive and false negative observation error

Diana

Matechou

Griffin

et al. 2020

Preprint

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Environmental DNA (eDNA) surveys have become a popular tool for assessing the distribution of species. However, it is known that false positive and false negative observation error can occur at both stages of eDNA surveys, namely the field sampling stage and laboratory analysis stage.We present an RShiny app that implements the Griffin et al. (2019) statistical method, which accounts for false positive and false negative errors in both stages of eDNA surveys. Following Griffin et al. (2019), we employ a Bayesian approach and perform efficient Bayesian variable selection to identify important predictors for the probability of species presence as well as the probabilities of observation error at either stage.We demonstrate the RShiny app using a data set on great crested newts collected by Natural England in 2018 and we identify water quality, pond area, fish presence, macrophyte cover, frequency of drying as important predictors for species presence at a site.The state-of-the-art statistical method that we have implemented is the only one that has specifically been developed for the purposes of modelling false negatives and false positives in eDNA data. Our RShiny app is user-friendly, requires no prior knowledge of R and fits the models very efficiently. Therefore, it should be part of the tool-kit of any researcher or practitioner who is collecting or analysing eDNA data.

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Validating metabarcoding-based biodiversity assessments with multi-species occupancy models: A case study using coastal marine eDNA

Cited by 41 publications

References 61 publications

Multispecies site occupancy modeling and study design for spatially replicated environmental DNA metabarcoding

Multispecies site occupancy modeling and study design for spatially replicated environmental DNA metabarcoding

Improving the reliability of eDNA data interpretation

An Rshiny app for modelling environmental DNA data: accounting for false positive and false negative observation error

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