A Geospatial Approach to Improving Fish Species Detection in Maumee Bay, Lake Erie

Abstract

Maumee Bay of western Lake Erie is at high risk for invasion by aquatic invasive species due to large urban and suburban populations, commercial shipping traffic, recreational boating, and aquaculture ponds. The U.S. Fish and Wildlife Service’s Early Detection and Monitoring (EDM) program has been monitoring for new invasive species since 2013 and is continually looking to adapt sampling methods to improve efficiency to increase the chance of detecting new aquatic invasive species at low abundances. From 2013–2016, the program used a random sampling design in Maumee Bay with three gear types: boat electrofishing, paired fyke nets, and bottom trawling. Capture data from the initial three years was used to spatially explore fish species richness with the hot spot analysis (Getis-Ord Gi*) in ArcGIS. In 2017, targeted sites in areas with high species richness (hot spots) were added to the randomly sampled sites to determine if the addition of targeted sampling would increase fish species detection rates and detection of rare species. Results suggest that this hybrid sampling design improved sampling efficiency as species not detected or were rare in previous survey years were captured and species were detected at a faster rate (i.e., in less sampling effort), particularly for shallow-water gear types. Through exploring past data and experimenting with targeted sampling, the EDM program will continue to refine and adapt sampling efforts to improve efficiency and provide valuable knowledge for the early detection of aquatic invasive species. The use of geospatial techniques such as hot spot analysis is one approach fisheries researchers and managers can use to incorporate targeted sampling in a non-subjective way to improve species detection.