**The title, authors, and abstract for this completion report are provided below.  For a copy of the completion report, please contact the GLFC via e-mail or via telephone at 734-662-3209**

 

 Estimating lake-wide relative abundance of lean trout in Lake Superior

  

Julie L. Nieland1, Jonathan J. Deroba2, and Michael J. Hansen1

1 University of Wisconsin Stevens Point, College of Natural Resources, 800 Reserve Street, Stevens Point, Wisconsin 54481, USA

2Michigan State University, Department of Fisheries and Wildlife, 13 Natural Resources Building, East Lansing, Michigan 48824, USA

  

Abstract

 

Lake trout (Salvelinus namaycush) stocks in Lake Superior collapsed in the 1950s due to over-fishing and sea lamprey (Petromyzon marinus) predation. Stocks were reestablished through stocking, sea lamprey control, and fishery regulation, but stock sustainability is of concern because lake trout are in high demand in fisheries and sea lampreys are still a significant source of mortality. Effectiveness of sea lamprey control is monitored using annual lake-wide indices of sea lamprey abundance, sea lamprey marking rates on lake trout, and lake trout relative abundance. We sought to develop the most appropriate statistical model for expressing annual lake-wide relative abundance of lean lake trout longer than 533 mm in Lake Superior during 19802005. We used catch per unit effort data from standardized gill-net surveys across Lake Superior to estimate annual lake-wide arithmetic mean, geometric mean, and model-based mean relative lake trout abundance. Temporal patterns of the annual geometric mean and model-based mean were similar, but differed from the temporal pattern of the arithmetic mean. We conclude that the geometric mean and model-based mean are both appropriate models for expressing temporal patterns in lake-wide relative abundance of lean lake trout longer than 533 mm in Lake Superior during 19802005. We recommend that the geometric mean be used as the lake-wide index of lake trout abundance in Lake Superior because this model produced similar temporal patterns to the model-based mean through a simpler approach.