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Sensitivity of multiple vital rates for ruffed grouse in the upper Great Lakes region

Cite this dataset

Pollentier, Christopher; Hull, Scott; MacFarland, David (2021). Sensitivity of multiple vital rates for ruffed grouse in the upper Great Lakes region [Dataset]. Dryad.


Effective management of wildlife requires a full understanding of population dynamics and knowledge of potential drivers that influence population growth.  The Ruffed Grouse (Bonasa umbellus) is a popular upland game bird widely distributed across the northern United States and Canada that has experienced population declines within portions of its range in response to forest maturation and habitat loss.  Although the species has been extensively studied, few efforts have been made to synthesize demographic data into a sensitivity analysis to guide management actions.  We reviewed the literature and compiled Ruffed Grouse vital rates from 14 field studies conducted across four decades (1982−2018) within the Upper Great Lakes region of Michigan, Minnesota, and Wisconsin, USA.  We parameterized a deterministic matrix model to evaluate population dynamics and conducted sensitivity analyses to identify vital rates projected to have the greatest influence on the finite rate of population change (λ).  Our modeling effort projected a stable but highly variable annual rate of population change (λ = 1.01; 95% CI = 0.88–1.14) for Ruffed Grouse in the Upper Great Lakes region.  Stochastic rates of population change derived from spring drumming surveys (λ = 1.01; 95% CI = 0.61–1.45) and Christmas Bird Count surveys (λ = 0.99; 95% CI = 0.62–1.76) of the corresponding regional population provided validation of stable trends over the same time period as our demographic model.  Prospective elasticities and variance-scaled sensitivities suggested λ would be greatly influenced by components of reproductive performance: nesting success, chick survival, and post-fledging juvenile survival.  Retrospective analysis indicated that much of the overall variability in λ and annual productivity was also attributed to annual variation in nesting success.  Management of this species has often focused on fall and overwinter survival, but population projection models provided little evidence that survival was the predominant factor affecting population growth of Ruffed Grouse in this region.  A suite of confounding factors and demographic processes that drive population trends can differ significantly across a species’ range.  In the Upper Great Lakes region, management efforts aimed at maximizing reproductive success would likely have the greatest potential influence on Ruffed Grouse population growth.  Other types of systematic, regional survey data can also be useful for validating population trends derived from demographic modeling studies.


We reviewed documents for estimates of Ruffed Grouse vital rates from field studies located in Michigan, Minnesota, and Wisconsin.  We searched wildlife ecology literature for vital rate data on Ruffed Grouse populations by searching primary (Ruffed Grouse, grouse, Bonasa, and Bonasa umbellus) and secondary (nesting, nest survival, clutch size, chick survival, and adult survival) keywords in electronic databases including Biological Abstracts, Google Scholar, JSTOR, Web of Science, and Wildlife and Ecology Studies Worldwide.  We also checked original references from previous demographic and life-history summaries to ensure studies were not overlooked.  We reviewed references and literature included in published peer-reviewed journal articles, graduate theses and dissertations, and agency reports with relevant vital rate data spanning a four-decade time period during the years 1982–2018.  We restricted our compilation of literature to this timeframe in an attempt to evaluate present-day Ruffed Grouse populations and to ensure that our modeling effort could account for potential stochastic processes that may occur across multiple 10-year population cycles.  In total, we synthesized available data from 14 demographic field research studies located in the Upper Great Lakes region of northern Michigan, Minnesota, and Wisconsin.

Usage notes

Population models and sensitivity analyses were built and evaluated in Program R using the package POPBIO.  Computer code is provided.


Federal Aid in Wildlife Restoration Grant, Award: W-160-P

Federal Aid in Wildlife Restoration Grant, Award: W-160-P