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Estimation and Modeling of Electrofishing Capture Efficiency for Fishes in Wadeable Warmwater Streams
Author(s) -
Price Alison L.,
Peterson James T.
Publication year - 2010
Publication title -
north american journal of fisheries management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 72
eISSN - 1548-8675
pISSN - 0275-5947
DOI - 10.1577/m09-122.1
Subject(s) - electrofishing , sampling (signal processing) , streams , abundance (ecology) , fishery , environmental science , fish <actinopterygii> , statistics , ecology , biology , computer science , mathematics , computer network , filter (signal processing) , computer vision
Abstract Stream fish managers often use fish sample data to inform management decisions affecting fish populations. Fish sample data, however, can be biased by the same factors affecting fish populations. To minimize the effect of sample biases on decision making, biologists need information on the effectiveness of fish sampling methods. We evaluated single‐pass backpack electrofishing and seining combined with electrofishing by following a dual‐gear, mark–recapture approach in 61 blocknetted sample units within first‐ to third‐order streams. We also estimated fish movement out of unblocked units during sampling. Capture efficiency and fish abundances were modeled for 50 fish species by use of conditional multinomial capture–recapture models. The best‐approximating models indicated that capture efficiencies were generally low and differed among species groups based on family or genus. Efficiencies of single‐pass electrofishing and seining combined with electrofishing were greatest for Catostomidae and lowest for Ictaluridae. Fish body length and stream habitat characteristics (mean cross‐sectional area, wood density, mean current velocity, and turbidity) also were related to capture efficiency of both methods, but the effects differed among species groups. We estimated that, on average, 23% of fish left the unblocked sample units, but net movement varied among species. Our results suggest that (1) common warmwater stream fish sampling methods have low capture efficiency and (2) failure to adjust for incomplete capture may bias estimates of fish abundance. We suggest that managers minimize bias from incomplete capture by adjusting data for site‐ and species‐specific capture efficiency and by choosing sampling gear that provide estimates with minimal bias and variance. Furthermore, if block nets are not used, we recommend that managers adjust the data based on unconditional capture efficiency.