2023 Early Hearing Detection & Intervention Conference
March 5-7, 2023 • Cincinnati, OH
9/26/2018 | 2:25 PM - 2:40 PM | Population Viability Analysis for Greater Sage-Grouse: Considering Hierarchical Scales Across Management Areas and Lek Clusters | Eccles Conference Center Auditorium
Population Viability Analysis for Greater Sage-Grouse: Considering Hierarchical Scales Across Management Areas and Lek Clusters
We investigated trends for Wyoming Greater Sage-grouse populations at multiple scales using population viability analysis (PVA) to determine local- and meta-population dynamics. Our objective was to use lek count data to determine population growth rates (?) by local Working Group Areas, Core Areas, Core Areas by Working Group Areas, and at nine nested scales based on lek clusters. We defined the nested, hierarchical clusters by fine- and broad-scale habitat and climate attributes relevant to sage-grouse biology. We used average peak male counts per lek annually (1993-2015) in a PVA to test density-independent and density-dependent models to determine ? for each population. Trends determined by management areas are relevant as these boundaries are used to implement management plans and limit disturbances; conversely, trends based on clusters are more likely to be correlated and yield more precise trend estimates than other population demarcations. We found that when Core Area status (Core vs. Non-Core Area) was investigated within Working Group Areas, the two populations trended similarly and agreed with the overall trend of the Working Group Area. However, at the finer scale where Core Areas were analyzed individually, Core Areas within the same Working Group Area often trended differently and a few large Core Areas drove the overall trend. Our approach of monitoring populations at different spatial scales will allow managers to focus efforts on small-scale populations that are doing the poorest and driving the larger scale population trends downward and alleviates unnecessary actions to large areas to maximize efficiency of management efforts.
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Presenters/Authors
David Edmunds
(), Colorado State University, dedmunds@rams.colostate.edu;
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Cameron Aldridge
(), United States Geological Survey, aldridgec@usgs.gov;
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Michael O'Donnell
(), USGS, odonnellm@usgs.gov;
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Adrian Monroe
(), Colorado State University, adrian.monroe@colostate.edu;
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