Early Detection of Invasive Fishes in Lake Superior Joshua Schloesser and Henry Quinlan U.S. Fish and Wildlife Service Ashland Fish and Wildlife Conservation Office Joel Hoffman U.S. Environmental Protection Agency Office of Research and Development Mid-Continent Ecology Division

Outline Lake Superior and AIS Lake Superior and AIS Development of an AIS monitoring program Development of an AIS monitoring program Theory behind detecting rare species Theory behind detecting rare species Current USFWS efforts Current USFWS efforts Initial monitoring program evaluation Initial monitoring program evaluation Thunder Bay St. Louis River Upper St. Marys

Effects of Invasive Species Significant ecological and economic damage 89 known Invasive species (The Lake Superior Work Group 2010) Decreased abundance (competition/predation) Homogenous fish communities Disturbed ecosystem = increased invasion rate

Vulnerabilities and Response Continual threat of new invasions Coordinated Science and Monitoring Initiative Coordinated Science and Monitoring Initiative Lake Superior Aquatic Invasive Species Complete Prevention Plan Lake Superior Aquatic Invasive Species Complete Prevention Plan Lake Superior Lakewide Management Plan Lake Superior Lakewide Management Plan Lake Superior Fish Community Objectives (2003) Lake Superior Fish Community Objectives (2003) Vectors Shipping/ballast exchange Recreational transport Aquarium release

Developing a Monitoring Program in St. Louis River Estuary Trebitz et al. (2009) Exploiting habitat and gear patterns for efficient detection of rare and non-native benthos and fish in Great Lakes coastal ecosystems. Aquatic Invasions. Goal is early detection! Sampling gearDepth strata (m)Gear allocationTotal sample size Fyke net0-140%20 Electrofishing1-240%20 Trawling>220%10

Species Accumulation Presence/Absence Only need to detect one Non-detection does not equate to non-presence Common species are easy to detect Much effort is required to detect the rarest species Common species Few samples Rare species Many samples

U.S. FWS Sampling , August-September , August-September Random allocation of sample locations Random allocation of sample locations Sampling gear St. Louis River Upper St. Marys/Thunder Bay # stations/year Depth strata (m) # stations/year Depth strata (m) Fyke net Electrofishing Trawling10>215>1.8

Non-Natives Detected Thunder Bay (90 samples) Total Richness = 31 Common carp Fourspine stickleback Rainbow smelt Round goby Eurasian ruffe Threespine stickleback Tubenose goby St. Louis River (100 samples) Total Richness = 40 Alewife Brook silverside Common carp Eurasian ruffe Freshwater Drum Rainbow smelt Round goby Tubenose goby Threespine stickleback White perch Upper St. Marys (90 samples) Total Richness = 31 Rainbow smelt Threespine stickleback

Gear mixtures to maximize richness? St. Louis River Upper St. Marys Thunder Bay –Randomly selected 0, 2, 4, …, 20 fyke net records and added 0, 2, 4, …, 20 electrofishing and 0, 2, 4, …, 20 trawl records to reach a total of 20 stations (66 possible gear combinations) –Plotted mean richness from 10 random draws of each gear combination

Rarefaction St. Louis River Upper St. Marys River Thunder Bay (EstimateS software)

Estimated Species Richness Parameters: total fish, singletons, doubletons (EstimateS) Chao et al. (2009) Sufficient sampling for asymptotic minimum species richness estimators. Ecology Hoffman et al. (2011) Effort and potential efficiencies for aquatic non-native species early detection. Canadian Journal of Fisheries and Aquatic Sciences Location # Species observed # Species estimated Additional Individuals Additional Samples 100%95%100%95% St. Louis River Upper St. Marys Thunder Bay

Summary of Evaluation Multi-gear approach Multi-gear approach – Current gear mixtures acceptable Effort requirements for 95% detections Effort requirements for 95% detections ~ two years of effort – Substantial effort for 100% Great community survey Great community survey We have an effective AIS monitoring program!

Continual Monitoring Efforts Adjust after final evaluation Adjust after final evaluation – St. Louis River – St. Marys River, MI/Canada – Thunder Bay, Canada Environmental DNA (e-DNA) Environmental DNA (e-DNA) – Asian carp framework Hoffman et al. (2011)

Cooperative Effort U.S. EPA, Mid-Continent Ecology Division Ontario Ministry of Natural Resources Fond du Lac Band of Lake Superior Chippewa 1854 Treaty Authority University of Minnesota-Duluth, Graduate School

Questions?