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Data and scripts from: Development of optimized methods for unbiased dusky grouse population monitoring using real and simulated data

Leipold, Elizabeth1

Published Jun 26, 2026; Updated Aug 06, 2026 on Dryad. https://doi.org/10.5061/dryad.m63xsj4dm

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Jun 26, 2026 version files 1.29 MB
Aug 06, 2026 version files 1.29 MB

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Abstract

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 < 15%) of dusky grouse to inform a statewide monitoring program. During 2019–2022, we designed and implemented multiple survey protocols throughout western Montana, USA, including spring point-counts (> 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. 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.