Comparison of fish detections, community diversity, and relative abundance using environmental DNA metabarcoding and traditional gears

Abstract

Background: Detecting species at low abundance, including aquatic invasive species (AIS), is critical for making informed management decisions. Environmental DNA (eDNA) methods have become a powerful tool for rare or cryptic species detection; however, many eDNA assays offer limited utility for community-level analyses due to their use of species-specific (presence/absence) 'barcodes'. Metabarcoding methods provide information on entire communities based on sequencing of all taxon-specific barcodes within an eDNA sample.Aims: Evaluate measures of fish species detections, community diversity, and estimates of relative abundance based on eDNA metabarcoding and traditional fisheries sampling approaches in the context of fish community characterization and AIS survellience. Materials and Methods:In 2016, eight limnologically diverse lakes (surface area range: 13 -1,728 ha) in Michigan, USA were sampled using a variety of traditional fisheries gears to characterize fish community composition. Environmental DNAs from surface (33 ± 6, mean ± 1 SD) and benthic (14 ± 2) water samples from each lake were isolated and amplified for two metabarcoding markers (mitochondrial 12S and 16S rDNA loci) using fish-specific primers. Fish species detected within each lake were determined by comparing the sequencing data to a database of sequences from native Michigan fish species and 19 AIS on the Michigan's Watch List.Results: Analysis of species accumulation curves indicated multi-locus eDNA metabarcoding assays can enhance species detection capacities and characterize 95% of a fish community in fewer sampling efforts than traditional gear (range: 2 -62, median: 14). In addition, all AIS detected in traditional gear samples were also detected by eDNA, while some AIS detected by eDNA assays were absent from traditional gear samples. | 369SARD et Al.

eDNA metabarcoding outperforms traditional fisheries sampling and reveals fine-scale heterogeneity in a temperate freshwater lake

“…Ethanol was allowed to evaporate from the half-filters for 24 hours before extraction. We followed the extraction methods outlined in Sard et al (2019) and Laramie et al (2015), using a combination of the Qiagen DNeasy Blood & Tissue Kit and the Purification of Total DNA from Animal Tissues Spin-Column Protocol (ThermoFisher). We performed two elutions of 100 μl each using Buffer AE warmed to 70℃.…”

“…Our positive control was DNA extracted from a caudal fin clip of Pygocentrus natterei , a tropical fish not found in our study system, which we included to visualize any potential cross contamination between wells. We then amplified extracted DNA at two mitochondrial genes, 12S and 16S, using primers also used by Sard et al (2019) in their study on similar freshwater systems in Michigan. For 12S, the universal primers were originally developed by Riaz et al (2011): Forward: 5’-ACTGGGATTAGATACCCC-3’, Reverse: 5’- TAGAACAGGCTCCTCTAG-3’.…”

“…Afzali et al, 2020; Civade et al, 2016; Olds et al, 2016; Yamamoto et al, 2017; Zou et al, 2020). Additionally, Sard et al (2019) demonstrated that eDNA metabarcoding could characterize 95% of a fish community with less sampling effort than traditional gear, and that eDNA detected aquatic invasive species that were not observed in some nets.…”

Read counts from environmental DNA (eDNA) metabarcoding reflect fish abundance and biomass in drained ponds

“…site occupancy or read counts) and fish abundance or biomass (as deduced by established surveys e.g. gill-netting) have been demonstrated in natural environments (Thomsen et al, 2012;Hänfling et al, 2016;Lawson Handley et al, 2019;Sard et al, 2019).…”

“…The ease of eDNA collection also makes this approach suitable for remote location sampling, and the molecular identification of the genetic material does not require taxonomic expertise. eDNA metabarcoding has been shown to outperform established methods for the assessment of freshwater fish community composition (Civade et al, 2016;Hӓnfling et al, 2016;Valentini et al, 2016;Pont et al, 2018;Sard et al, 2019).…”