Abstract

AbstractThe relative quickness and cost effectiveness of single‐pass electrofishing samples (catch per effort [CPE]) argues for their use over multiple‐pass estimates for enumerating stream fish populations. However, CPE can be an imprecise index of fish abundance and therefore may be less useful than more‐precise indices of abundance, such as those obtained from mark–recapture or depletion methods, for assessing trout populations. We evaluated the use of single‐pass electrofishing samples (catch/mi) as abundance (number/mi) predictors of adult brook trout Salvelinus fontinalis and brown trout Salmo trutta in Wisconsin streams by quantifying the relationship between electrofishing CPE and adult trout abundance. First, we tested for linearity of the relationship between CPE and adult trout abundance while accounting for measurement error. Next, we explained the residual variability in the relationship using physical and biological attributes of surveyed streams. We found that the relationship between CPE and adult trout abundance was proportional (linear) for both brook trout and brown trout. Electrofishing catchability did not differ significantly between trout species or among seasons or ecoregions. However, catchability was significantly greater for towed‐barge electrofishing (0.64; 95% confidence interval, 0.55–0.73) than backpack electrofishing (0.23; 0.09–0.59). Adult trout abundance alone explained 82% of the variation in CPE for backpack units and 87% of the variation in CPE for towed‐barge units. Stream habitat features such as stream slope, mean stream width, and pool density failed to explain additional variation in catchability. Our results indicate that CPE can provide a reliable index of adult trout abundance in Wisconsin streams, but mark–recapture methods may still be needed to obtain a more precise estimate of abundance. However, because time and effort can be reduced 50% if single‐pass CPEs are used instead of mark–recapture abundance estimates to predict adult trout abundance, managers may choose to sacrifice higher precision for reduced sampling effort.Received December 20, 2010; accepted June 17, 2011

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