At the forefront: evidence of the applicability of using environmental DNA to quantify the abundance of fish populations in natural lentic waters with additional sampling considerations
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Abstract
Environmental DNA (eDNA) sampling has proven to be a valuable tool for detecting species in aquatic ecosystems. Within this rapidly evolving field, a promising application is the ability to obtain quantitative estimates of relative species abundance based on eDNA concentration rather than traditionally labor-intensive methods. We investigated the relationship between eDNA concentration and Arctic char (Salvelinus alpinus) abundance in five well-studied natural lakes; additionally, we examined the effects of different temporal (e.g., season) and spatial (e.g., depth) scales on eDNA concentration. Concentrations of eDNA were linearly correlated with char population estimates (
= 0.78) and exponentially correlated with char densities (
= 0.96 by area; 0.82 by volume). Across lakes, eDNA concentrations were greater and more homogeneous in the water column during mixis; however, when stratified, eDNA concentrations were greater in the hypolimnion. Overall, our findings demonstrate that eDNA techniques can produce effective estimates of relative fish abundance in natural lakes. These findings can guide future studies to improve and expand eDNA methods while informing research and management using rapid and minimally invasive sampling.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | At the forefront: evidence of the applicability of using environmental DNA to quantify the abundance of fish populations in natural lentic waters with additional sampling considerations |
| Series title | Canadian Journal of Fisheries and Aquatic Sciences |
| DOI | 10.1139/cjfas-2017-0114 |
| Volume | 74 |
| Issue | 12 |
| Year Published | 2017 |
| Language | English |
| Publisher | NRC Research Press |
| Contributing office(s) | Coop Res Unit Seattle |
| Description | 5 p. |
| First page | 2030 |
| Last page | 2034 |
| Google Analytic Metrics | Metrics page |