Hierarchical population monitoring of greater sage-grouse (<em>Centrocercus urophasianus</em>) in Nevada and California—Identifying populations for management at the appropriate spatial scale

Abstract

For more information on the USGS-the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment-visit https://www.usgs.gov/ or call 1-888-ASK-USGS (1-888-275-8747).For an overview of USGS information products, including maps, imagery, and publications, visit https:/store.usgs.gov.Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.Suggested citation Coates, P.S., Prochazka, B.G., Ricca, M.A., Wann, G.T., Aldridge, C.L., Hanser, S.E., Doherty, K.E., O'Donnell, M.S., Edmunds, D.R., and, Espinosa, S.P., 2017, Hierarchical population monitoring of greater sage-grouse (Centrocercus urophasianus) in Nevada and California-Identifying populations for management at the appropriate spatial scale: U.S. Geological Survey Open-File Report 2017-1089, 49 p., https://doi.org/10.3133/ofr20171089. ISSN 2331ISSN -1258 iii Preface This study was conducted to provide timely scientific information to establish an adaptive monitoring framework and modeling approach for greater sage-grouse (Centrocercus urophasianus) population trends at multiple spatial scales in northeastern California and Nevada. These findings fill a prominent information gap, and heighten understanding of sage-grouse population trends at nested spatial and temporal scales. Importantly, this study highlights an example of an 'early warning system' that can be carried out annually to identify where and when management action could be applied to benefit declining populations of sage-grouse at the appropriate scale. The rules of this framework can be modified to identify populations responding positively to management actions, and could ultimately be implemented across the geographic range of sage-grouse. This report is also intended to provide timely scientific information and inform newly established State and Federal monitoring programs, particularly those of the Bureau of Land Management and U.S. Forest Service. AbstractPopulation ecologists have long recognized the importance of ecological scale in understanding processes that guide observed demographic patterns for wildlife species. However, directly incorporating spatial and temporal scale into monitoring strategies that detect whether trajectories are driven by local or regional factors is challenging and rarely implemented. Identifying the appropriate scale is critical to the development of management actions that can attenuate or reverse population declines. We describe a novel example of a monitoring framework for estimating annual rates of population change for greater sage-grouse (Centrocercus urophasianus) within a hierarchical and spatially nested structure. Specifically, we conducted Bayesian analyses on a 17-year dataset (2000)(2001)(2002)(2003)(...

Bridging the research-management gap: landscape science in practice on public lands in the western United States

“…Scientists and managers have leveraged insights from this research to develop a hierarchical framework that agencies can use to monitor greater sage-grouse (BLM and U.S. Forest Service 2014) that addresses broadand mid-scales, and a framework that agencies can use to assess sage-grouse habitat (Stiver et al 2015) which identifies specific assessment methods and metrics at scales from rangewide to individual sites. These products and approaches are being applied rangewide to assess population changes (Coates et al 2017;Edmunds et al 2018a, b;O'Donnell et al 2019), and to evaluate sage-grouse population responses to temporally varying vegetation characteristics (see Rigge et al 2019), climate, fire, cheatgrass invasion, and energy development to inform future management actions within the sage-grouse range.…”

Designing multi‐scale hierarchical monitoring frameworks for wildlife to support management: a sage‐grouse case study

“…For example, spatial variability and quality of available resources can affect local population success and result in different population growth rates among population units (Coates et al. , Edmunds et al. , b).…”

“…Using each cluster level, one could query survey sites and associated demographic data to analyze population trends (Coates et al. ). We could also use any newly discovered leks and associated demographic data with our framework and similar queries without having to develop a new hierarchical framework, unless the structure of connectivity significantly changed (e.g., a periphery population).…”

“…However, the smaller sampling units allow us to assess local population trends and thus a tradeoff between possible movements between finestscaled clusters and ability to evaluate local population trends. Using each cluster level, one could query survey sites and associated demographic data to analyze population trends (Coates et al 2017). We could also use any newly discovered leks and associated demographic data with our framework and similar queries without having to develop a new hierarchical framework, unless the structure of connectivity significantly changed (e.g., a periphery population).…”

“…These resulted in a single clustered polygon, and therefore, there are no competing covariates to evaluate. population growth rates among population units (Coates et al 2017, Edmunds et al 2018a. Further, stressors acting at different scales and extents often affect species like sage-grouse, influencing patterns of abundance and source-sink dynamics (Aldridge and Boyce 2007, Kirol et al 2015, Heinrichs et al 2017.…”