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Development of optimized methods for unbiased dusky grouse population monitoring using real and simulated data

dc.contributor.authorLeipold, Elizabeth A.
dc.contributor.authorGower, Claire N.
dc.contributor.authorMcNew, Lance B.
dc.date.accessioned2026-06-23T20:38:45Z
dc.date.issued2026-02
dc.description.abstractRigorous 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%) 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. 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.
dc.identifier.citationLeipold, E.A., Gower, C. and McNew, L.B. (2026), Development of optimized methods for unbiased dusky grouse population monitoring using real and simulated data. Wildlife Biology e01506. https://doi.org/10.1002/wlb3.01506
dc.identifier.doi10.1002/wlb3.01506
dc.identifier.issn1903-220X
dc.identifier.urihttps://scholarworks.montana.edu/handle/1/19948
dc.language.isoen_US
dc.publisherWiley
dc.rightscc-by
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectAbundance (ecology)
dc.subjectDistance sampling
dc.subjectTransect
dc.subjectAbundance estimation
dc.subjectSampling (signal processing)
dc.subjectGrouse
dc.subjectPopulation
dc.subjectEstimator
dc.titleDevelopment of optimized methods for unbiased dusky grouse population monitoring using real and simulated data
dc.typeArticle
mus.citation.extentfirstpage1
mus.citation.extentlastpage22
mus.citation.journaltitleWildlife Biology
mus.relation.collegeCollege of Agriculture
mus.relation.departmentAnimal & Range Sciences
mus.relation.universityMontana State University - Bozeman

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