Intercalibration of Research Survey Vessels on Lake Erie

Abstract

AbstractFish abundance indices obtained from annual research trawl surveys are an integral part of fisheries stock assessment and management in the Great Lakes. It is difficult, however, to administer trawl surveys using a single vessel−gear combination owing to the large size of these systems, the jurisdictional boundaries that bisect the Great Lakes, and changes in vessels as a result of fleet replacement. When trawl surveys are administered by multiple vessel−gear combinations, systematic error may be introduced in combining catch‐per‐unit‐effort (CPUE) data across vessels. This bias is associated with relative differences in catchability among vessel−gear combinations. In Lake Erie, five different research vessels conduct seasonal trawl surveys in the western half of the lake. To eliminate this systematic bias, the Lake Erie agencies conducted a side‐by‐side trawling experiment in 2003 to develop correction factors for CPUE data associated with different vessel−gear combinations. Correcting for systematic bias in CPUE data should lead to more accurate and comparable estimates of species density and biomass. We estimated correction factors for the 10 most commonly collected species age‐groups for each vessel during the experiment. Most of the correction factors (70%) ranged from 0.5 to 2.0, indicating that the systematic bias associated with different vessel−gear combinations was not large. Differences in CPUE were most evident for vessels using different sampling gears, although significant differences also existed for vessels using the same gears. These results suggest that standardizing gear is important for multiple‐vessel surveys, but there will still be significant differences in catchability stemming from the vessel effects and agencies must correct for this. With standardized estimates of CPUE, the Lake Erie agencies will have the ability to directly compare and combine time series for species abundance.