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Using eDNA to elucidate distribution of fish species in a complex river system
Citation:
Hatzenbuhler, C., W. Chadderton, J. Hoffman, S. Okum, B. Olds, E. Pilgrim, A. Trebitz, A. Tucker, AND M. Renshaw. Using eDNA to elucidate distribution of fish species in a complex river system. St. Louis River Summit, Superior, WI, March 05 - 06, 2019.
Impact/Purpose:
This collaborative research project, involving EPA/ORD and researchers from academia and the Nature Conservancy, aims to advance methods for estimating fish distribution on the basis of eDNA, which is genetic material that organisms shed into the aqueous environment. Surveys based on eDNA offer the potential for efficient biological monitoring, but first require work to refine sampling and data analysis protocols and to understand how results compare to traditional organism-collection data. We accomplish the former through structured inter-lab and inter-method comparisons, and the latter by leveraging existing EPA/ORD fish distribution data sets.
Description:
Environmental DNA (eDNA) analysis is a non-invasive genetic tool that can improve efficiency and reduce costs associated with species detection in aquatic systems. eDNA methods are widely used to assess presence/absence of target species and have recently demonstrated potential for estimating biodiversity in controlled environments. We applied eDNA methods to estimate distribution of fish species in a large and complex river system. The St. Louis River Estuary provides a suitable study area because fish diversity and species distribution are well documented, thanks to past and ongoing fishery assessments and invasive species early detection monitoring. We collected water samples from 240 randomly selected sites extending over 30 river km in June and October 2016. At 30 sites, an additional water sample was collected for an inter-lab comparison. Composition and spatial distribution patterns derived from eDNA data were compared to traditional adult and larval fish survey data to understand the different perspectives they give. Results from our study provide insight into the efficacy of eDNA methods for estimating fish distribution in large, complex aquatic systems and begin to inform us about how these methods can be operationalized for use by management agencies.