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

• 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

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.