Assessing recovery of spectacled eiders using a Bayesian decision analysis.

Area of Science:

• Wildlife conservation
• Population dynamics
• Ecological modeling

Background:

• Endangered Species Act (ESA) listing decisions require accurate species status assessments.
• Misclassification errors, underprotection or overprotection, pose risks to conservation efforts.
• Spectacled eider populations in Alaska show signs of recovery, necessitating a review of their federal listing status.

Purpose of the Study:

• To estimate population metrics and project future abundance for Alaskan spectacled eiders.
• To assess the risk of quasi-extinction for spectacled eider populations.
• To apply decision analysis to evaluate misclassification errors in species status assessments.

Main Methods:

• State-space models were used to estimate population metrics for Alaskan breeding spectacled eiders.
• Population abundance was projected over 50 years using posterior estimates and process variation.
• A decision analysis framework, incorporating a loss function, was used to map quasi-extinction risk.

Main Results:

• The Yukon Kuskokwim Delta breeding population has met recovery criteria.
• The Arctic Coastal Plain breeding population has not met recovery criteria.
• The applied methods quantify misclassification error risks for decision-makers.

Conclusions:

• Accurate species status assessment is crucial for effective conservation under the ESA.
• Decision analysis and abundance thresholds improve the transparency and defensibility of listing decisions.
• The study provides a robust framework for evaluating species recovery and informing conservation management.