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Understanding environmental DNA detection probabilities: A case study using a stream-dwelling char Salvelinus fontinalis

January 1, 2016

Environmental DNA sampling (eDNA) has emerged as a powerful tool for detecting aquatic animals. Previous research suggests that eDNA methods are substantially more sensitive than traditional sampling. However, the factors influencing eDNA detection and the resulting sampling costs are still not well understood. Here we use multiple experiments to derive independent estimates of eDNA production rates and downstream persistence from brook trout (Salvelinus fontinalis) in streams. We use these estimates to parameterize models comparing the false negative detection rates of eDNA sampling and traditional backpack electrofishing. We find that using the protocols in this study eDNA had reasonable detection probabilities at extremely low animal densities (e.g., probability of detection 0.18 at densities of one fish per stream kilometer) and very high detection probabilities at population-level densities (e.g., probability of detection > 0.99 at densities of ≥ 3 fish per 100 m). This is substantially more sensitive than traditional electrofishing for determining the presence of brook trout and may translate into important cost savings when animals are rare. Our findings are consistent with a growing body of literature showing that eDNA sampling is a powerful tool for the detection of aquatic species, particularly those that are rare and difficult to sample using traditional methods.

Publication Year 2016
Title Understanding environmental DNA detection probabilities: A case study using a stream-dwelling char Salvelinus fontinalis
DOI 10.1016/j.biocon.2015.12.023
Authors Taylor Wilcox, Kevin S. Mckelvey, Michael K. Young, Adam J. Sepulveda, Bradley B. Shepard, Stephen F Jane, Andrew R. Whiteley, Winsor H. Lowe, Michael K. Schwartz
Publication Type Article
Publication Subtype Journal Article
Series Title Biological Conservation
Index ID 70162270
Record Source USGS Publications Warehouse
USGS Organization Northern Rocky Mountain Science Center