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SFS Annual Meeting

Poster Details

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Accurately estimating the distribution of a species is important for managing sustainable populations of fishes. The yellow perch (Perca flavescens) is one of the most abundant fishes in Great Lakes coastal wetlands, which they commonly use for spawning and nursery habitat. Many management decisions are based on results from sampling, but these methods rarely account for incomplete detection (i.e., presence of a species that is not detected by sampling). We applied the method of occupancy modeling, which takes incomplete detection into account, to yellow perch presence/absence data from coastal wetlands across all five Great Lakes. We used occupancy models with environmental variables to predict the detection probability of fyke-net sampling and the occupancy of yellow perch under different environmental conditions. We found that both detection probability and occupancy of yellow perch varied among all five Great Lakes and with changes in other environmental variables. The best models included wetland class, vegetation, and Great Lake basin, and yellow perch occupancy was predicted to be highest in Lake Superior, areas with submerged aquatic vegetation (SAV) or bulrush, and riverine wetlands. Our results predict which coastal wetland habitats were preferred by yellow perch.

Kaitlyn Dykstra (Primary Presenter/Author), Annis Water Resources Institute, Grand Valley State University,;

Carl R. Ruetz III (Co-Presenter/Co-Author), Grand Valley State University,;

Matthew Cooper (Co-Presenter/Co-Author), Burke Center for Freshwater Innovation, Northland College,;

Donald Uzarski (Co-Presenter/Co-Author), Institute for Great Lakes Research, Central Michigan University,;