Reconciling Inter-Agency Differences in Stock Assessment Inputs From Multiple Fishery Independent Gill Net Surveys

Wednesday, September 11, 2013: 10:40 AM
White Oak (The Marriott Little Rock)
Richard Kraus , Great Lakes Science Center, Lake Erie Biological Station, US Geological Survey, Sandusky, OH
Christopher S. Vandergoot , Division of Wildlife, Sandusky Fisheries Research Station, Ohio Department of Natural Resources, Sandusky, OH
Andy Cook , Ontario Ministry of Natural Resources, Wheatley, ON, Canada
Travis Brenden , Quantitative Fisheries Center, Michigan State University, East Lansing, MI
Mark Rogers , Lake Erie Biological Station, USGS Great Lakes Science Center, Sandusky, OH
Patrick M. Kocovsky , Lake Erie Biological Station, US Geological Survey, Sandusky, OH
Historical factors have contributed to long-term inter-agency gear differences in material and mesh sizes of fishery independent gill net surveys of Lake Erie walleye.  Despite incorporation of various weighting schemes into stock assessments, population age-structure information from these different surveys has been confounded by spatial segregation of gear deployments in each agency’s jurisdiction.  We conducted comparison deployments with three primary survey gill nets to test assumptions about size-selectivity and examine gear-specific bias in terms of the estimated size and age distribution of fish contacting the nets.  Each net exhibited a unique size selection pattern that remained constant across three years of sampling.  Spatial-temporal differences in gear deployment had a greater effect on the predicted age-distribution of walleye contacting the net than any other factor.  A comparatively smaller effect was the tendency for gears with larger mesh sizes to estimate a higher proportion of older fish.  Interestingly, specification of a fishing power scenario also had a large effect on age-distribution.  Selection curve differences driven by subjective fishing power scenarios are problematic, and the use of independent data and pond experiments holds promise for useful insights regarding fishing power.  Our results provide a straightforward approach for compiling inter-agency data for stock assessments of Lake Erie walleye.