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

low probability of detection can lead to overestimates for higher level parameters, including probability of capture [47]. Additionally, many species were only detected in the shallow water sites and were detected consistently across biological replicates at these sites, further contribut- ing to a high estimate for the community mean probability of capture. Species-specific probabilities of detection varied by amplicon and by phylum. Since we did not have replication within each amplicon for each sample, the effects of amplicon are con- founded with the effects of occasion (i.e. PCR stochasticity). However, the effects of amplicon on species detectability were consistent across samples and it is very unlikely that this pattern would be observed due to PCR stochasticity alone, which is a random process. Therefore, we assume the effects we observed at the level of detectability were driven by the different ampli- cons used. Since the performance of each amplicon varies by taxonomic group (this study; [13]), including a variety of amplicons is important to detect species across the tree of life, and increasing the number of technical replicates using a single amplicon will not necessarily improve the community-wide probability of detection. Information such as this can be used to guide primer selection for future metabarcoding studies to maximize the probability of detec- tion for target taxa or to ensure broad taxonomic coverage for holistic biodiversity surveys. We used the occupancy modeling framework to estimate the species richness for the survey

area and determined that 53 species or approximately 19% of the estimated number of species present were undetected during our surveys. Similar to many ecological studies, the case study presented here included a relatively low spatial coverage (n = 8 sites), but our occupancy modelling approach allowed us to assess false absences at two different sampling levels in our study and thereby understand what portion of biodiversity was missed, which is a significant improvement from most metabarcoding surveys [11]. Understanding how biological replica- tion and technical replication affect biodiversity estimates can inform future sampling designs Fig 3. Mean detection probability estimated from occupancy model 9 (ψ(.) θ(.) p(amplicon)) for each species plotted by amplicon. The band in the middle of the box represents the median and the upper and lower edges of the box represent the upper and lower quartiles. The whiskers represent 1.5 times the inter-quartile range. https://doi.org/10.1371/journal.pone.0224119.g003 PLOS ONE Multi-species occupancy models for metabarcoding PLOS ONE | https://doi.org/10.1371/journal.pone.0224119 March 19, 2020 10 / 17