Litcius/Paper detail

Comparing eDNA metabarcoding and conventional pelagic netting to inform biodiversity monitoring in deep ocean environments

David Côté, M B McClenaghan, Jessica E. Desforges, Nicole Fahner, Mehrdad Hajibabaei, Julek Chawarski, Subal Kumar Roul, Georg Singer, Cyril Aubry, Maxime Geoffroy

2023ICES Journal of Marine Science24 citationsDOIOpen Access PDF

Abstract

Abstract The performance of environmental DNA (eDNA) metabarcoding has rarely been evaluated against conventional sampling methods in deep ocean mesopelagic environments. We assessed the biodiversity patterns generated with eDNA and two co-located conventional methods, oblique midwater trawls and vertical multinets, to compare regional and sample-level diversity. We then assessed the concordance of ecological patterns across water column habitats and evaluated how DNA markers and the level of sampling effort influenced the inferred community. We found eDNA metabarcoding characterized regional diversity well, detecting more taxa while identifying similar ecological patterns as conventional samples. Within sampling locations, eDNA metabarcoding rarely detected taxa across more than one replicate. While more taxa were found in eDNA than oblique midwater trawls within sample stations, fewer were found compared to vertical multinets. Our simulations show greater eDNA sampling effort would improve concordance with conventional methods. We also observed that using taxonomic data from multiple markers generated ecological patterns most similar to those observed with conventional methods. Patterns observed with Exact Sequence Variants were more stable across markers suggesting they are more powerful for detecting change. eDNA metabarcoding is a valuable tool for identifying and monitoring biological hotspots but some methodological adjustments are recommended for deep ocean environments.

Topics & Concepts

Environmental DNABiodiversityPelagic zoneReplicateSampling (signal processing)EcologyTaxonDNA barcodingBiologyMesopelagic zoneComputer scienceComputer visionFilter (signal processing)MathematicsStatisticsEnvironmental DNA in Biodiversity StudiesMicrobial Community Ecology and PhysiologyIdentification and Quantification in Food