**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 1980–2005. 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 1980–2005. 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.