A BAYESIAN-APPROACH TO CLASSIFICATION CRITERIA FOR SPECTACLED EIDERS

To facilitate decisions to classify species according to risk of extin ction, we used Bayesian methods to analyze trend data for the Spectacl ed Elder an arctic sea duck. Trend data from three independent surveys of the Yukon-Kuskokwim Delta were analyzed individually and in combin ation to yield posterior distributions for population growth rates. We used classification criteria developed by the recovery team for Spect acled Elders that seek to equalize errors of under- or overprotecting the species. We conducted both a Bayesian decision analysis and a freq uentist (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 nonscientist s. With the exception of the aerial survey analysis of the 10 most rec ent years, both Bayesian and frequentist methods indicated that an end angered classification is warranted. The discrepancy between surveys w arrants further research, Although the trend data are abundance indice s, 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 abund ance highlight the need for models that apply to declining and then re covering species.