A hierarchical Bayesian model for estimating historical salmon escapement and escapement timing

In this paper, we present an improved methodology for estimating salmon escapements from stream count data. The new method uses a hierarchical Bayesian model that improves estimates in years when data are sparse by "borrowing strength" from counts in other years. We present a model of esca...

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Bibliographic Details
Published in:Canadian Journal of Fisheries and Aquatic Sciences
Main Authors: Su, Zhenming, Adkison, Milo D, Van Alen, Benjamin W
Format: Article in Journal/Newspaper
Language:English
Published: Canadian Science Publishing 2001
Subjects:
Aquatic Science
Ecology, Evolution, Behavior and Systematics
Oncorhynchus gorbuscha
Pink salmon
Alaska
Online Access:http://dx.doi.org/10.1139/f01-099
http://www.nrcresearchpress.com/doi/pdf/10.1139/f01-099
Description
Summary:In this paper, we present an improved methodology for estimating salmon escapements from stream count data. The new method uses a hierarchical Bayesian model that improves estimates in years when data are sparse by "borrowing strength" from counts in other years. We present a model of escapement and of count data, a hierarchical Bayesian statistical framework, a Gibbs sampling approach for evaluation of the posterior distributions of the quantities of interest, and criteria for determining when the model and inference are adequate. We then apply the hierarchical Bayesian model to estimating historical escapement and escapement timing for pink salmon (Oncorhynchus gorbuscha) returns to Kadashan Creek in Southeast Alaska.

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