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A Comparison of Electrofishing and Visual Surveying Methods for Estimating Fish Community Structure in Temperate Rivers
- Source :
- River Research and Applications. 31:1040-1051
- Publication Year :
- 2014
- Publisher :
- Wiley, 2014.
-
Abstract
- Studies attempting to describe fish community structure in shallow riverine environments typically rely on electrofishing and/or visual (snorkelling) surveys, but few have addressed the relative efficiencies of these two methods at estimating fish density and biomass across wide ranges of geography, taxonomy and life history stages. Multiple paired electrofishing and visual surveys were conducted in 18 temperate Canadian rivers in order to obtain community-wide density and biomass estimates from both methods. Partial canonical multivariate analyses were applied to the paired fish community matrices comparing the results of both surveying methods at the taxonomic levels of family, genus and species, as well as size classes within families and species, to assess the particular effectiveness of each sampling method. Although electrofishing estimates of family and species richness were generally greater, snorkelling surveys tended to generate higher density and biomass estimates for different size classes of many salmonid and cyprinid species. Moreover, mean river biomass estimates derived from visual surveying matched those obtained from our best mean river biomass estimates arising from the two methods combined. This study provides empirical evidence that electrofishing and visual survey methods generate different types of information when assessing fish community structure at the family level or by size classes. Our results provide ample background information for determining the most accurate sampling method for a particular fish community assemblage, which is fundamental to fisheries management and research. Copyright © 2014 John Wiley & Sons, Ltd.
Details
- ISSN :
- 15351459
- Volume :
- 31
- Database :
- OpenAIRE
- Journal :
- River Research and Applications
- Accession number :
- edsair.doi...........56c72040c5251b6bc5cefdb217f85a17