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      Using occupancy modelling to compare environmental DNA to traditional field methods for regional-scale monitoring of an endangered aquatic species.

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          Abstract

          Environmental DNA (eDNA) monitoring approaches promise to greatly improve detection of rare, endangered and invasive species in comparison with traditional field approaches. Herein, eDNA approaches and traditional seining methods were applied at 29 research locations to compare method-specific estimates of detection and occupancy probabilities for endangered tidewater goby (Eucyclogobius newberryi). At each location, multiple paired seine hauls and water samples for eDNA analysis were taken, ranging from two to 23 samples per site, depending upon habitat size. Analysis using a multimethod occupancy modelling framework indicated that the probability of detection using eDNA was nearly double (0.74) the rate of detection for seining (0.39). The higher detection rates afforded by eDNA allowed determination of tidewater goby occupancy at two locations where they have not been previously detected and at one location considered to be locally extirpated. Additionally, eDNA concentration was positively related to tidewater goby catch per unit effort, suggesting eDNA could potentially be used as a proxy for local tidewater goby abundance. Compared to traditional field sampling, eDNA provided improved occupancy parameter estimates and can be applied to increase management efficiency across a broad spatial range and within a diversity of habitats.

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          Author and article information

          Journal
          Mol Ecol Resour
          Molecular ecology resources
          Wiley-Blackwell
          1755-0998
          1755-098X
          Jul 2016
          : 16
          : 4
          Affiliations
          [1 ] Department of Fisheries Biology, Humboldt State University, One Harpst Street, Arcata, CA, 95521, USA.
          Article
          10.1111/1755-0998.12501
          26677162
          972ceffe-1d4c-4297-9105-f168f11529ea
          History

          conservation genetics,environmental DNA,fish,occupancy modelling,qPCR,tidal habitats

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