2020 ESA Annual Meeting (August 3 - 6)

PS 60 Abstract - Strategies and challenges in detecting non-indigenous species in the Great Lakes

Christy Meredith1, Anett S. Trebitz2, Joel C. Hoffman2, Greg S. Peterson2, Chelsea Hatzenbuhler3, Erik M. Pilgrim4, Sara Okum4 and John Martinson2, (1)Montana Department of Environmental Quality, Helena, MT, (2)Great Lakes Toxicology and Ecology Division, U.S. EPA, Duluth, MN, (3)Badger Technical Services, Duluth, MN, (4)Watershed and Ecosystem Characterization Division, U.S. EPA, Cincinnati, OH
Background/Question/Methods

Great Lakes coastal systems are vulnerable to introduction of a wide variety of non-indigenous species (NIS). To increase detection of NIS in Lake Superior, the U. S. EPA has implemented a variety of strategies including conducting high-intensity sampling, deploying a wide range of sampling gear types, and performing DNA analysis of tissue and water samples.

Results/Conclusions

Our findings illustrated the pervasiveness of NIS in areas of Lake Superior typically considered less-impacted by NIS, including numerous cases of dreissenids in the Apostle Islands and Bythotrephes longimanus (spiny water flea) at Isle Royale. In addition, we identified two fish species (Dorosoma cepedianum-gizzard shad and Morone chrysops-white bass) previously unknown to Lake Superior by using a combination of high intensity sampling of larval fish and DNA metabarcoding for identification. Despite its benefits, the challenges of incorporating DNA technology are illustrated by a recent zooplankton sampling effort in Lake Superior. While 27% more unique zooplankton taxa were identified using both traditional taxonomy and DNA metabarcoding (compared to traditional taxonomy alone), 14 of the 18 taxa not identified by DNA metabarcoding had low representation in online databases. DNA metabarcoding identified four zooplankton taxa not previously found in Lake Superior, but these could not be ruled out as false positives due to low sequence abundance. These challenges may be partly overcome in the future by adding records to DNA libraries and by implementing sampling, laboratory, and analysis techniques to better identify false-negative and false-positive occurrences.