A bayesian approach to classification criteria for spectacled eiders

Ecological Applications
By: , and 

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Abstract

To facilitate decisions to classify species according to risk of extinction, we used Bayesian methods to analyze trend data for the Spectacled Eider, an arctic sea duck. Trend data from three independent surveys of the Yukon-Kuskokwim Delta were analyzed individually and in combination to yield posterior distributions for population growth rates. We used classification criteria developed by the recovery team for Spectacled Eiders that seek to equalize errors of under- or overprotecting the species. We conducted both a Bayesian decision analysis and a frequentist (classical statistical inference) decision analysis. Bayesian decision analyses are computationally easier, yield basically the same results, and yield results that are easier to explain to nonscientists. With the exception of the aerial survey analysis of the 10 most recent years, both Bayesian and frequentist methods indicated that an endangered classification is warranted. The discrepancy between surveys warrants further research. Although the trend data are abundance indices, we used a preliminary estimate of absolute abundance to demonstrate how to calculate extinction distributions using the joint probability distributions for population growth rate and variance in growth rate generated by the Bayesian analysis. Recent apparent increases in abundance highlight the need for models that apply to declining and then recovering species.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title A bayesian approach to classification criteria for spectacled eiders
Series title Ecological Applications
DOI 10.2307/2269592
Volume 6
Issue 4
Year Published 1996
Language English
Publisher Wiley
Contributing office(s) Alaska Science Center
Description 13 p.
First page 1077
Last page 1089
Country United States
State Alaska
Other Geospatial Yukon-Kuskokwim Delta