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Evaluating single-pass catch as a tool for identifying spatial pattern in fish distribution

January 1, 2005

We evaluate the efficacy of single-pass electrofishing without blocknets as a tool for collecting spatially continuous fish distribution data in headwater streams. We compare spatial patterns in abundance, sampling effort, and length-frequency distributions from single-pass sampling of coastal cutthroat trout (Oncorhynchus clarki clarki) to data obtained from a more precise multiple-pass removal electrofishing method in two mid-sized (500–1000 ha) forested watersheds in western Oregon. Abundance estimates from single- and multiple-pass removal electrofishing were positively correlated in both watersheds, r = 0.99 and 0.86. There were no significant trends in capture probabilities at the watershed scale (P > 0.05). Moreover, among-sample variation in fish abundance was higher than within-sample error in both streams indicating that increased precision of unit-scale abundance estimates would provide less information on patterns of abundance than increasing the fraction of habitat units sampled. In the two watersheds, respectively, single-pass electrofishing captured 78 and 74% of the estimated population of cutthroat trout with 7 and 10% of the effort. At the scale of intermediate-sized watersheds, single-pass electrofishing exhibited a sufficient level of precision to be effective in detecting spatial patterns of cutthroat trout abundance and may be a useful tool for providing the context for investigating fish-habitat relationships at multiple scales.

Publication Year 2005
Title Evaluating single-pass catch as a tool for identifying spatial pattern in fish distribution
DOI 10.1080/02705060.2005.9664974
Authors Douglas S. Bateman, Robert E. Gresswell, Christian E. Torgersen
Publication Type Article
Publication Subtype Journal Article
Series Title Journal of Freshwater Ecology
Index ID 70031496
Record Source USGS Publications Warehouse
USGS Organization Forest and Rangeland Ecosystem Science Center; Northern Rocky Mountain Science Center