Th-A-14 Stock Identification and Distribution in the Lake Michigan Lake Whitefish Commercial Fishery

Thursday, August 23, 2012: 11:30 AM
Ballroom A (RiverCentre)
Brian L. Sloss , College of Natural Resources, USGS Wisconsin Cooperative Fishery Research Unit, University of Wisconsin–Stevens Point, Stevens Point, WI
Justin A. VanDeHey , Wisconsin Cooperative Fishery Research Unit, College of Natural Resources, University of Wisconsin-Stevens Point, Stevens Point, WI
Ryan T. Andvik , Wisconsin Cooperative Fishery Research Unit, College of Natural Resources, University of Wisconsin-Stevens Point, Stevens Point, WI
Lucas R. Nathan , Wisconsin Cooperative Fishery Research Unit, College of Natural Resources, University of Wisconsin-Stevens Point, Stevens Point, WI
Scott P. Hansen , Wisconsin Department of Natural Resources, Sturgeon Bay, WI
Randall M. Claramunt , Fisheries Division, Michigan Department of Natural Resources and Environment, Charlevoix, MI
Trent M. Sutton , School of Fisheries and Ocean Sciences, University of Alaska Fairbanks, Fairbanks, AK
Stock delineation of Lake Michigan’s lake whitefish fishery has long been an area of concern because of the economic and cultural significance and the inter-jurisdictional management of the commercial fishery.  Recent studies resolved six genetic units and suggested these units were mostly consistent with contemporary commercial management zones.  Concerns over the temporal stability of these six stocks were addressed using archived (1973-1992) samples from spawning assessments.  Although some differences existed between temporal and contemporary samples, the overall consensus of six genetic units was resolved.  Understanding the distribution of these stocks in the commercial harvest is important for stock-based management.  Tagging studies have suggested significant mixing of stocks in the harvest.  Mixed stock analysis of commercially harvested fish from the 2009-2010 seasons showed spatial and temporal variations in stock contribution.  Geographic location generally predicted the predominant harvested stock but in many cases this stock comprised less than 50% of the site’s total harvest.  These data suggest contemporary lake whitefish stock-specific harvest rates are poorly understood and confirmed tagging studies showing large-scale movement of lake whitefish.  Further analyses of the stock-specific, seasonal harvest rates could provide critical data to revise statistical catch-at-age models and improve stock-based management of this important resource.