Disentangling the components of coastal fish biodiversity in southern Brittany by applying an environmental DNA approach

Abstract

The global biodiversity crisis from anthropogenic activities significantly weakens the functioning of marine ecosystems and jeopardizes their ecosystem services. Increasing monitoring of marine ecosystems is crucial to understand the breadth of the changes in biodiversity, ecosystem functioning and propose more effective conservation strategies. Such strategies should not only focus on maximizing the number of species (i.e., taxonomic diversity) but also the diversity of phylogenetic histories and ecological functions within communities. To support future conservation decisions, multicomponent biodiversity monitoring can be combined with high-throughput species assemblage detection methods such as environmental DNA (eDNA) metabarcoding. Here, we used eDNA to assess fish biodiversity along the coast of southern Brittany (France, Iroise Sea). We filtered surface marine water from 17 sampling stations and applied an eDNA metabarcoding approach targeting Actinopterygii and Elasmobranchii taxa.We documented three complementary biodiversity components-taxonomic, phylogenetic, and functional diversity-and three diversity facets-richness, divergence and regularity. We identified a north/south contrast with higher diversity for the three facets of the biodiversity components in the northern part of the study area. The northern communities showed higher species richness, stronger phylogenetic overdispersion and lower functional clustering compared to the ones in the southern part, due to the higher diversity of habitats (reefs, rocky shores) and restricted access for fishing. Moreover, we also detected a higher level of taxonomic, phylogenetic, and functional uniqueness in many offshore stations compared to more coastal ones, with the presence of species typically living at greater depths (> 300 m), which suggests an influence of hydrodynamic structures and currents on eDNA dispersion and hence sample composition. eDNA metabarcoding can, therefore, be used as an efficient sampling method to reveal fine-scale community compositions and in combination with functional and phylogenetic information to document multicomponent biodiversity gradients in coastal marine systems.

Environmental DNA recovers fish composition turnover of the coral reefs of West Indian Ocean islands

“…Our results suggest that eDNA metabarcoding can be used to identify an ecological signal of habitat selection by fish species and MOTUs across the transition from coral reefs to pelagic habitat. Rather than suggesting a broad diffusion of eDNA, our approach indicates that eDNA is detected only over small spatial distances from where it originated, as already demonstrated in numerous studies (Lafferty et al, 2021;Murakami et al, 2019;Nguyen et al, 2020;Rozanski et al, 2022). As expected, we detected species belonging to the Scombridae family with greater probability in their pelagic habitat (Colette & Nauen, 1983).…”

“…Moreover, seawater salinity affects eDNA preservation and eDNA could be diluted during transport, which could be advantageous because faster degradation leads to more localised eDNA detection (Harrison et al, 2019). In line with this, a highly localised spatial resolution of eDNA in marine environments has been reported frequently (e.g., Minamoto et al, 2017;O'Donnell et al, 2017;Port et al, 2016;Rozanski et al, 2022;Stat et al, 2019), despite the potential for oceanic currents, eddies and waves to disperse eDNA over long distances (Barnes & Turner, 2015). By virtue of their isolation and simplified shoreline gradients, islands can be excellent model systems to better understand the diffusion of the eDNA signal.…”

Arctic char occurrence and abundance using environmental DNA

“…This mixing and merging can potentially increase the signal by aggregating same‐species eDNA material or dilute the signal my mixing with other species material or other environmental material (e.g., water, soil). It is therefore essential to include adequate spatial sampling to ensure capturing of genetic material across the study area and to assess the spatial distribution of the genetic material in the sampled environment (Lawson Handley et al, 2019; Rozanski et al, 2022). Secondly, the ecology of the study species should be considered as even within small waterways there will be environmental and habitat heterogeneity, which will influence the amount of time different species will spend foraging, hiding, resting, or breeding which will influence the spatial patterns of eDNA accumulation in a given environment (Wang et al, 2021).…”

“…conservation, eDNA, fisheries, quantitative polymerase chain reaction, salmonid, Salvelinus alpinus soil). It is therefore essential to include adequate spatial sampling to ensure capturing of genetic material across the study area and to assess the spatial distribution of the genetic material in the sampled environment (Lawson Handley et al, 2019;Rozanski et al, 2022).…”

New deep learning‐based methods for visualizing ecosystem properties using environmental DNA metabarcoding data

“…Recently, our ability to rapidly generate comprehensive biodiversity inventories has been enhanced by the development of environmental DNA (eDNA) metabarcoding, which allows the retrieval and analysis of DNA naturally shed by organisms in their environment (Deiner et al, 2017; Miya, 2022). eDNA metabarcoding is now operational in many ecosystems for a wide range of micro‐ and macroorganisms (Cantera et al, 2022; Cordier et al, 2021; Kjær et al, 2022; Mathon et al, 2022), providing information on their taxonomic, functional, but also phylogenetic affiliations (Marques, Castagné, et al, 2021; Marques, Milhau, et al, 2021; Rozanski et al, 2022). Given its limited field effort and ecosystem disturbance (Muff et al, 2023), even in the most remote locations, and the decrease in sequencing cost over the recent years, this approach can be scaled up to monitor many sites at high temporal frequency (Agersnap et al, 2022).…”