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

occupancy, capture, and detection probabilities. Given the high stakes for documenting and understanding biodiversity that is under increasing anthropogenic threat [60] and declining [61] globally, new tools are imperative for rapid bioassessment [7,62,63]; yet, like any emergent technology, there is the potential to misuse these tools [64], which can have unforeseen conse- quences (e.g. [65]). In the case of DNA metabarcoding, neglecting to assess imperfect detection at key points along the sample collection and processing pipeline could lead to failure to detect species of interest, biased estimates of species richness, and miscalculations of species distribu- tions, all of which have consequences for conservation and management [24,66,67]. We rec- ommend incorporating multi-scale, multi-species occupancy modeling into the design and analysis of future metabarcoding studies. Supporting information S1 Table. Literature review of occupancy modeling for metabarcoding data. List of studies (n = 5) that have examined occupancy models in the context of DNA metabarcoding. To obtain this list of publications, we performed the following systematic, Boolean search using the Web of Science: “�DNA” AND "metabarcoding" AND "occupancy model�". (DOCX) S2 Table. Species-specific parameter estimates from multi-species, multi-scale occupancy model. Species-specific estimates of occupancy, capture and detection using mean covariates values (water depth (m) and sequencing depth) from a multi-scale, multi-species occupancy model for eDNA metabarcoding data from Conception Bay, Newfoundland.

(DOCX) S1 File. Model assessment calculations for multi-species, multi-scale occupancy models. Calculations presented for likelihood, Bayesian p-value, WAIC, CPO, Brier score and log score for model assessment and comparison. (DOCX) S2 File. Model structure in BUGS language. BUGS model structure presented for the most complex model ψ(water depth) θ(.) p(sequencing depth, amplicon), the best model ψ(water depth) θ(.) p(sequencing depth) with data augmentation and the ψ(.) θ(.) p(amplicon) model with a group-level effect (phylum). (DOCX) S3 File. Diagnostic plots to asses fit of ψ(water depth) θ(.) p(sequencing depth) model. Plots of residual deviance for each species, site and covariate from a multi-species, multi-scale occupancy model based on eDNA metabarcoding data collected from Conception Bay, New- foundland. (DOCX) Acknowledgments We would like to thank Nicole Fahner, Joshua Barnes, Avery McCarthy, Greg Singer, Hoda Rajabi, and Emily Porter for their assistance in sample collection, processing and bioinformatics. Author Contributions Conceptualization: Beverly McClenaghan, Mehrdad Hajibabaei. Formal analysis: Beverly McClenaghan. PLOS ONE Multi-species occupancy models for metabarcoding PLOS ONE | https://doi.org/10.1371/journal.pone.0224119 March 19, 2020 13 / 17