Data from: Quantifying relative fish abundance with eDNA: a promising tool for fisheries management
Lacoursière-Roussel, Anaïs; Côté, Guillaume; Leclerc, Véronique; Bernatchez, Louis (2016), Data from: Quantifying relative fish abundance with eDNA: a promising tool for fisheries management, Dryad, Dataset, https://doi.org/10.5061/dryad.6g53s
Assessment and monitoring of exploited fish populations are challenged by costs, logistics and negative impacts on target populations. These factors therefore limit large-scale effective management strategies. Evidence is growing that the quantity of eDNA may be related not only to species presence/absence, but also to species abundance. In this study, the concentrations of environmental DNA (eDNA) from a highly prized sport fish species, Lake Trout Salvelinus namaycush (Walbaum 1792), were estimated in water samples from 12 natural lakes and compared to abundance and biomass data obtained from standardized gillnet catches as performed routinely for fisheries management purposes. To reduce environmental variability among lakes, all lakes were sampled in spring, between ice melt and water stratification. The eDNA concentration did not vary significantly with water temperature, dissolved oxygen, pH and turbidity, but was significantly positively correlated with relative fish abundance estimated as catch per unit effort (CPUE), whereas the relationship with biomass per unit effort (BPUE) was less pronounced. The value of eDNA to inform about local aquatic species distribution was further supported by the similarity between the spatial heterogeneity of eDNA distribution and spatial variation in CPUE measured by the gillnet method. Synthesis and applications. Large-scale empirical evidence of the relationship between the eDNA concentration and species abundance allows for the assessment of the potential to integrate eDNA within fisheries management plans. As such, the eDNA quantitative method represents a promising population abundance assessment tool that could significantly reduce the costs associated with sampling and increase the power of detection, the spatial coverage and the frequency of sampling, without any negative impacts on fish populations.