Decision making and best practices for taxonomy-free eDNA metabarcoding in biomonitoring using Hill numbers

Abstract

1Environmental DNA (eDNA) metabarcoding raises expectations for biomonitoring to cover organisms 2 that have hitherto been neglected or excluded. To bypass current limitations in taxonomic assignments 3 due to incomplete or erroneous reference data bases, taxonomic-free approaches are proposed for biomon-4 itoring at the level of operational taxonomic unites (OTUs). However, this is challenging, because OTUs 5 cannot be annotated and directly compared to classically derived data. The application of good strin-6 gency treatments to infer validity of OTUs and the clear understanding of the consequences to such 7 treatments is thus especially relevant for biodiversity assessments. We investigated how common prac-8 tices of stringency filtering affect diversity estimates based on Hill numbers derived from eDNA samples. 9 We collected eDNA at 61 sites across a 740 km 2 river catchment, reflecting a spatially realistic sce-10 nario in biomonitoring. After bioinformatic processing of the data, we studied how different stringency 11 treatments affect conclusions with respect to biodiversity at the catchment and site levels. The applied 12 stringency treatments were based on the consistent appearance of OTUs across filter replicates, a relative 13 abundance cut-off and rarefaction. We detected large differences in diversity estimates when accounting 14 for presence/absence only, such that the detected diversity at the catchment scale differed by an order 15 of magnitude between the treatments. These differences disappeared between the stringency treatments 16 with increasing weighting of the OTUs' abundances. Our study demonstrated the usefulness of Hill num-17 bers for comparisons between data sets with large differences in diversity, and suggests best practice for 18 data stringency filtering for biomonitoring. 19

DNA metabarcoding captures subtle differences in forest beetle communities following disturbance

“…The lack of a significant result for the non-curated COI dataset indicates the importance of adapting bioinformatics parameters for reliable species diversity estimation (Brandt et al 2020). While we note that estimating species richness is very sensitive to bioinformatics strategy (Froslev et al 2017;Calderón-Sanou et al 2020), the similar community structure resolved with our LULU-curated datasets demonstrates a robust metric in spite of current limitations in DNA metabarcoding (Brandt et al 2020;Mächler et al 2020).…”

How to design optimal eDNA sampling strategies for biomonitoring in river networks

“…Collecting more samples at fixed downstream locations would also be beneficial because, due to a dilution effect, eDNA concentrations at the downstream sites are likely not high even in the presence of a local taxon hotspot (see Figure 3), and hence more prone to result in non‐detections. This is especially important in the context of many metabarcoding studies setting thresholds of read numbers below which the signal is no longer accepted as a true positive (Deiner et al., 2017; Mächler, Walser, & Altermatt, 2020). In this perspective, collecting larger water volumes at the downstream sites is likely to help minimize the risk of non‐detection.…”

How to design optimal eDNA sampling strategies for biomonitoring in river networks

“…Collecting more samples at fixed downstream locations would also be beneficial because, due to a dilution effect, eDNA concentrations at the downstream sites are likely not high even in the presence of a local taxon hotspot (see Figure 3), and hence more prone to result in non-detections. This is especially important in the context of many metabarcoding studies setting thresholds of read numbers below which the signal is no longer accepted as a true positive [Deiner et al, 2017;Mächler et al, 2020]. In this perspective, collecting larger water volumes at the downstream sites is likely to help minimize the risk of non-detection.…”