A hierarchical dependent double-observer method for estimating waterfowl breeding pairs abundance from helicopters

We applied a dependent double-observer method for helicopter surveys and developed a hierarchical Bayesian model as a means to adjust counts of waterfowl for incomplete detection. We conducted our study using 52 plots in Labrador, Canada. A designated pair of primary observers reported counts and location of all waterfowl flocks that they detected to a pair of secondary observers, including details regarding the species, age and sex of observed birds. Secondary observers then reported any additional flocks observed by them but missed by the primary observers. The pairs of observers alternated between primary and secondary roles during the course of the survey, as well as position (front or back) within the helicopter. We used hierarchical Bayesian models to estimate detection probabilities of waterfowl flocks, as well as derive species-specific detection-corrected abundance and sex composition estimates of flocks. The hierarchical model output allowed us to derive estimates of indicated...