Th-A-15 Spatial and Temporal Genetic Variability of Lake Whitefish from the Ontario Waters of Lake Huron

Thursday, August 23, 2012: 11:45 AM
Ballroom A (RiverCentre)
Wendylee Stott , Michigan State University/USGS Great Lakes Science Center, Ann Arbor, MI
Lloyd Mohr , Upper Great Lakes Management Unit - Lake Huron, Ontario Ministry of Natural Resources, Owen Sound, ON, Canada
Mark Ebener , Chippewa Ottawa Resource Authority, Inter-Tribal Fisheries and Assessment Program, Sault Ste Marie, MI
John M. Casselman , Biology, Queen's University, Kingston, ON, Canada
Stephen Crawford , Department of Integrative Biology, University of Guelph, Guelph, ON, Canada
Great Lakes fish communities have changed over the last 200 years and will continue to face alteration due to man-made impacts, climate change, and natural fluctuations in community dynamics.  Understanding the temporal stability of population structure of individual species is an important requirement for management and a first step towards a comprehensive appreciation of ecosystem dynamics.  Lake whitefish management in the Upper Great Lakes is based on several spatially defined management units derived from life history, tagging, and some genetic data. While periodic assessments have been performed within the management units to assess temporal changes in stocks, no genetic data have been collected since initial surveys in the 1970s and 1980s.  We analyzed microsatellite DNA variation in lake whitefish from 6 sites (Blind R., Burnt Is., Inner and Outer South Bay, Owen Sound, and Southampton) in the Ontario waters of Lake Huron and compared diversity from contemporary samples to that of samples collected 30 years ago that were analyzed for allozyme variation.  Levels of heterozygosity at microsatellite DNA loci were consistent among all samples from both time periods.  Genetic differentiation was observed spatially and temporally and was greatest between contemporary samples from Georgian Bay and the main basin.  An analysis of molecular variance (AMOVA) indicated that most of the variation occurred at the population level.  Similarities and differences in the results observed with allozyme and microsatellite DNA data could be related to the relative sensitivity of the two marker types, sample size differences, and differing analytical approaches.