Northwest Fisheries Science Center

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Document Type: Journal Article
Center: NWFSC
Document ID: 984
Title: Landscape characteristics and coho salmon (Oncorhynchus kisutch) distributions:  explaining abundance versus occupancy
Author: E. Ashley Steel, D. W. Jensen, K. M. Burnett, K. Christiansen, J. C. Firman, Blake E. Feist, K. J. Anlauf, D. P. Larsen
Publication Year: 2012
Journal: Canadian Journal of Fisheries and Aquatic Sciences
Volume: 69
Issue: 3
Pages: 457-468
Keywords: landscape, presence/absence, modeling zeros, land-use, probability sampling, hurdle model, monitoring

Distribution of fishes, both occupancy and abundance, is often correlated with landscape-scale characteristics (e.g., geology, climate, and human disturbance).  Understanding these relationships is essential for effective conservation of depressed populations.  We used landscape characteristics to explain the distribution of coho salmon (Oncorhynchus kisutch) in the Oregon Plan data set, one of the first long-term, probabilistic salmon monitoring data sets covering the full range of potential habitats.  First we compared data structure and model performance between the Oregon Plan data set and two published data sets on coho salmon distribution.  Most of the variation in spawner abundance occurred between reaches but much also occurred between years, limiting potential model performance.  Similar suites of landscape predictors are correlated with coho salmon distribution across regions and data sets.  We then modeled coho salmon spawner distribution using the Oregon Plan data set and determined that landscape characteristics could not explain presence vs. absence of spawners, but that percentage of agriculture, winter temperature range, and intrinsic potential of the stream could explain some variation in abundance (weighted average R2 = 0.30) where spawners were present.  We conclude that the previous use of nonrandom monitoring data sets may have obscured understanding of species distribution, and we suggest minor modifications to large-scale monitoring programs.

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