N-mix for fish: estimating riverine salmonid habitat selection via N-mixture models

Canadian Journal of Fisheries and Aquatic Sciences
By: , and 

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Abstract

Models that formulate mathematical linkages between fish use and habitat characteristics are applied for many purposes. For riverine fish, these linkages are often cast as resource selection functions with variables including depth and velocity of water and distance to nearest cover. Ecologists are now recognizing the role that detection plays in observing organisms, and failure to account for imperfect detection can lead to spurious inference. Herein, we present a flexible N-mixture model to associate habitat characteristics with the abundance of riverine salmonids that simultaneously estimates detection probability. Our formulation has the added benefits of accounting for demographics variation and can generate probabilistic statements regarding intensity of habitat use. In addition to the conceptual benefits, model application to data from the Trinity River, California, yields interesting results. Detection was estimated to vary among surveyors, but there was little spatial or temporal variation. Additionally, a weaker effect of water depth on resource selection is estimated than that reported by previous studies not accounting for detection probability. N-mixture models show great promise for applications to riverine resource selection.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title N-mix for fish: estimating riverine salmonid habitat selection via N-mixture models
Series title Canadian Journal of Fisheries and Aquatic Sciences
DOI 10.1139/cjfas-2017-0027
Volume 75
Issue 7
Year Published 2018
Language English
Publisher Canadian Science Publishing
Contributing office(s) Western Fisheries Research Center
Description 11 p.
First page 1048
Last page 1058