Rigorous state‐wide monitoring programs are lacking for dusky grouse Dendragapus obscurus , a North American species of forest grouse with relatively low detectability that is found in coniferous and mountainous areas in the western United States and Canada. Hierarchical models for estimating abundance show promise for overcoming issues associated cryptic forest grouse behavior and low population densities. Our objectives were to evaluate protocols (i.e. number of sites, visits, and route type) and analytical methods for producing annual unbiased and precise indices of abundance (CV 2200 unique sites) and transect‐level (> 390 unique transects) distance sampling. We used an iterative process of field data collection and simulation analyses to evaluate the performance of four different statistical estimators for abundance (N‐mixture model, hierarchical time‐removal model with distance sampling, detection‐naïve model, and hierarchical distance sampling model) for point‐counts and transects to produce unbiased and precise estimates of dusky grouse abundance. Simulations demonstrated that increasing the number of sites visited or probability of detection decreased the requisite amount of survey effort for obtaining precise abundance estimates for all estimators. Unbiased and precise estimates of abundance were unachievable under most realistic point‐based distance sampling protocols. N‐mixture protocols where point‐counts conducted during periods of high probability of detection at 80 sites visited four times per area of inference (e.g. study area or region) resulted in unbiased estimates of population size with the highest precision. Our study provides baseline information necessary for the development of state‐wide monitoring programs of dusky grouse and more broadly illustrates an approach for developing rigorous and achievable monitoring programs for other species of forest grouse.
Leipold et al. (Tue,) studied this question.