Greater sage-grouse (Centrocercus urophasianus; hereinafter sage-grouse) is a sagebrush obligate species and widely considered an indicator species for sagebrush ecosystems and other sagebrush-dependent species (Hanser and Knick, 2011; Prochazka and others, 2023). Sagebrush ecosystems are threatened by a wide range of disturbances and anthropogenic factors, including climate change, severe drought, altered wildfire regimes, expansion of invasive species, and anthropogenic development. Collectively, these threats have led to reduced ecological integrity and sage-grouse habitat quality within the sagebrush biome (Doherty and others, 2022). Steady and long-term declines in sage-grouse populations have led to large-scale efforts to improve population performance and prevent additional loss of habitat for sage-grouse and other sagebrush-dependent species (Coates and others, 2021). Due to their complex space use and habitat selection patterns during different life stages, requirements for large intact tracts of sagebrush, declining population trends, and status as a proposed protected species, sage-grouse have become integral to land management and conservation policy throughout the western United States (Western Association of Fish and Wildlife Agencies, 2015; Doherty and others, 2022). References cited: Coates, P.S., Prochazka, B.G., Aldridge, C.L., O’Donnell, M.S., Edmunds, D.R., Monroe, A.P., Hanser, S.E., Wiechman, L.A., and Chenaille, M.P., 2023, Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)-Updated 1960-2022: U.S. Geological Survey Data Report 1175, 17 p., accessed December 7, 2023, at [Available at https://doi.org/10.3133/dr1175.] Doherty, K., Theobald, D.M., Bradford, J.B., Wiechman, L.A., Bedrosian, G., Boyd, C.S., Cahill, M., Coates, P.S., Creutzburg, M.K., Crist, M.R., Finn, S.P., Kumar, A.V., Littlefield, C.E., Maestas, J.D., Prentice, K.L., Prochazka, B.G., Remington, T.E., Sparklin, W.D., Tull, J.C., Wurtzebach, Z., and Zeller, K.A., 2022, A sagebrush conservation design to proactively restore America’s sagebrush biome: U.S. Geological Survey Open-File Report 2022-1081, 38 p., accessed December 6, 2023, at https://doi.org/10.3133/ofr20221081. Hanser, S.E., and Knick, S.T., 2011, Greater sage-grouse as an umbrella species for shrubland passerine birds-A multiscale assessment, chap. 19 in Knick, S.T., eds., Greater sage grouse-Ecology and conservation of a landscape species and its habitats: University of California Press, p. 474-487. [Available at https://doi.org/10.1525/california/9780520267114.003.0020.] Prochazka, B.G., Coates, P.S., O’Donnell, M.S., Edmunds, D.R., Monroe, A.P., Ricca, M.A., Wann, G.T., Hanser, S.E., Wiechman, L.A., Doherty, K.E., Chenaille, M.P., and Aldridge, C.L., 2023, A targeted annual warning system developed for the conservation of a sagebrush indicator species: Ecological Indicators, v. 148. [Available at https://doi.org/10.1016/j.ecolind.2023.110097.] Western Association of Fish and Wildlife Agencies, 2015, Greater sage-grouse population trends: an analysis of lek count databases 1965-2015: Cheyenne, Wyo., Western Association of Fish and Wildlife Agencies, 55 p., accessed 07 12, 2023, at https://ir.library.oregonstate.edu/concern/technical_reports/ng451p621

Greater sage-grouse (Centrocercus urophasianus; hereinafter sage-grouse) is a sagebrush obligate species and widely considered an indicator species for sagebrush ecosystems and other sagebrush-dependent species (Hanser and Knick, 2011; Prochazka and others, 2023). Sagebrush ecosystems are threatened by a wide range of disturbances and anthropogenic factors, including climate change, severe drought, altered wildfire regimes, expansion of invasive species, and anthropogenic development. Collectively, these threats have led to reduced ecological integrity and sage-grouse habitat quality within the sagebrush biome (Doherty and others, 2022). Steady and long-term declines in sage-grouse populations have led to large-scale efforts to improve population performance and prevent additional loss of habitat for sage-grouse and other sagebrush-dependent species (Coates and others, 2021). Due to their complex space use and habitat selection patterns during different life stages, requirements for large intact tracts of sagebrush, declining population trends, and status as a proposed protected species, sage-grouse have become integral to land management and conservation policy throughout the western United States (Western Association of Fish and Wildlife Agencies, 2015; Doherty and others, 2022). References cited: Coates, P.S., Prochazka, B.G., Aldridge, C.L., O’Donnell, M.S., Edmunds, D.R., Monroe, A.P., Hanser, S.E., Wiechman, L.A., and Chenaille, M.P., 2023, Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)-Updated 1960-2022: U.S. Geological Survey Data Report 1175, 17 p., accessed December 7, 2023, at [Available at https://doi.org/10.3133/dr1175.] Doherty, K., Theobald, D.M., Bradford, J.B., Wiechman, L.A., Bedrosian, G., Boyd, C.S., Cahill, M., Coates, P.S., Creutzburg, M.K., Crist, M.R., Finn, S.P., Kumar, A.V., Littlefield, C.E., Maestas, J.D., Prentice, K.L., Prochazka, B.G., Remington, T.E., Sparklin, W.D., Tull, J.C., Wurtzebach, Z., and Zeller, K.A., 2022, A sagebrush conservation design to proactively restore America’s sagebrush biome: U.S. Geological Survey Open-File Report 2022-1081, 38 p., accessed December 6, 2023, at https://doi.org/10.3133/ofr20221081. Hanser, S.E., and Knick, S.T., 2011, Greater sage-grouse as an umbrella species for shrubland passerine birds-A multiscale assessment, chap. 19 in Knick, S.T., eds., Greater sage grouse-Ecology and conservation of a landscape species and its habitats: University of California Press, p. 474-487. [Available at https://doi.org/10.1525/california/9780520267114.003.0020.] Prochazka, B.G., Coates, P.S., O’Donnell, M.S., Edmunds, D.R., Monroe, A.P., Ricca, M.A., Wann, G.T., Hanser, S.E., Wiechman, L.A., Doherty, K.E., Chenaille, M.P., and Aldridge, C.L., 2023, A targeted annual warning system developed for the conservation of a sagebrush indicator species: Ecological Indicators, v. 148. [Available at https://doi.org/10.1016/j.ecolind.2023.110097.] Western Association of Fish and Wildlife Agencies, 2015, Greater sage-grouse population trends: an analysis of lek count databases 1965-2015: Cheyenne, Wyo., Western Association of Fish and Wildlife Agencies, 55 p., accessed 07 12, 2023, at https://ir.library.oregonstate.edu/concern/technical_reports/ng451p621

The distance within which populations respond to features in a landscape (scale of effect) can indicate how disturbance and management may affect wildlife. Using annual counts of male Greater Sage-grouse (Centrocercus urophasianus) attending 584 leks in southwest Wyoming (2003-2019) and estimates of sagebrush cover from the Rangeland Condition Monitoring Assessment and Projection (RCMAP), we used a scale selection approach to jointly estimate the scale of effect and the effect of sagebrush cover in the surrounding landscape for sage-grouse population trends. We estimated these parameters using a state-space model fit with a Bayesian approach. Data formatting necessary for this analysis produced data stored in two lists, one for model constants (nimbleconstants_sg_wlci.txt, including number of years, number of sites [leks], number of scales, number of visits, indicators for site and year, and number of detection parameters) and one for model data (nimbledata_sg_wlci.txt, including lek counts/surveys in both long- and array-format, a matrix for detection covariates, an array for sagebrush cover [scaled], and unscaled arrays for sagebrush, ordinal date, and time since sunrise).

The distance within which populations respond to features in a landscape (scale of effect) can indicate how disturbance and management may affect wildlife. Using annual counts of male Greater Sage-grouse (Centrocercus urophasianus) attending 584 leks in southwest Wyoming (2003-2019) and estimates of sagebrush cover from the Rangeland Condition Monitoring Assessment and Projection (RCMAP), we used a scale selection approach to jointly estimate the scale of effect and the effect of sagebrush cover in the surrounding landscape for sage-grouse population trends. We estimated these parameters using a state-space model fit with a Bayesian approach. Data formatting necessary for this analysis produced data stored in two lists, one for model constants (nimbleconstants_sg_wlci.txt, including number of years, number of sites [leks], number of scales, number of visits, indicators for site and year, and number of detection parameters) and one for model data (nimbledata_sg_wlci.txt, including lek counts/surveys in both long- and array-format, a matrix for detection covariates, an array for sagebrush cover [scaled], and unscaled arrays for sagebrush, ordinal date, and time since sunrise).

nv_lvl1_finescale: Nevada hierarchical cluster level 1 (fine-scale) for Greater sage-grouse We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different population growth rates among smaller clusters. Equally so, the spatial structure and ecological organization driving scale-dependent systems in a fragmented landscape affects dispersal behavior, suggesting inclusion in population monitoring frameworks. Studies that compare conditions among spatially explicit hierarchical clusters may elucidate the cause of differing growth rates, indicating the appropriate location and spatial scale of a management action. The data presented here reflect the results from developing a hierarchical monitoring framework and then applying these methods to Greater Sage-grouse in Nevada and Wyoming, US. When using these data for evaluating population changes or when identifying a spatially balanced sampling protocol, all cluster levels are designed to work together and therefore we recommend evaluating multiple cluster levels prior to selecting a single cluster level, if a single scale is desired, when analyzing population growth rates or other analyses, as these data are intended for multi-scale efforts. In other words, let your data decide which scale(s) are appropriate for the given species. These cluster levels are specific to Greater Sage-grouse but they may be appropriate for other sagebrush obligate species, but the user will need to make this determination. The products from this study aim to support multiple research and management needs. However, these data represent an interim data product because there may be errors associated with clusters along the edges of the state boundaries (due to the lack of lek data in neighboring states). We are planning to release new data that we will develop for the Greater sage-grouse range. We recommend using the new data products once available instead of these data products. These data will remain online as they are associated with the following citation, which provides a detailed explanation of the methods used to develop these data: O’Donnell, Michael S., David R. Edmunds, Cameron L. Aldridge, Julie A. Heinrichs, Peter S. Coates, Brian G. Prochazka, and Steve E. Hanser. 2019. Designing multi-scale hierarchical monitoring frameworks for wildlife with high site fidelity to support conservation: a sage-grouse case study. Ecosphere

This dataset provides summary statistics of multiple sage-grouse microhabitat characteristics of the Great Basin. These data support the following publication: Coates, P.S., Brussee, B.E., Ricca, M.A., Dudko, J.E., Prochazka, B.G., Espinosa, S.P., Casazza, M.L., and Delehanty, D.J., 2017, Greater sage-grouse (Centrocercus urophasianus) nesting and brood-rearing microhabitat in Nevada and California—Spatial variation in selection and survival patterns: U.S. Geological Survey Open-File Report 2017-1087, 79 p., https://doi.org/10.3133/ofr20171087.

This dataset provides summary statistics of multiple sage-grouse microhabitat characteristics of the Great Basin. These data support the following publication: Coates, P.S., Brussee, B.E., Ricca, M.A., Dudko, J.E., Prochazka, B.G., Espinosa, S.P., Casazza, M.L., and Delehanty, D.J., 2017, Greater sage-grouse (Centrocercus urophasianus) nesting and brood-rearing microhabitat in Nevada and California—Spatial variation in selection and survival patterns: U.S. Geological Survey Open-File Report 2017-1087, 79 p., https://doi.org/10.3133/ofr20171087.

We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different population growth rates among smaller clusters. Equally so, the spatial structure and ecological organization driving scale-dependent systems in a fragmented landscape affects dispersal behavior, suggesting inclusion in population monitoring frameworks. Studies that compare conditions among spatially explicit hierarchical clusters may elucidate the cause of differing growth rates, indicating the appropriate location and spatial scale of a management action. The data presented here reflect the results from developing a hierarchical monitoring framework and then applying these methods to Greater Sage-grouse in Nevada and Wyoming, US. When using these data for evaluating population changes or when identifying a spatially balanced sampling protocol, all cluster levels are designed to work together and therefore we recommend evaluating multiple cluster levels prior to selecting a single cluster level, if a single scale is desired, when analyzing population growth rates or other analyses, as these data are intended for multi-scale efforts. In other words, let your data decide which scale(s) are appropriate for the given species. These cluster levels are specific to Greater Sage-grouse but they may be appropriate for other sagebrush obligate species, but the user will need to make this determination. The products from this study aim to support multiple research and management needs. However, these data represent an interim data product because there may be errors associated with clusters along the edges of the state boundaries (due to the lack of lek data in neighboring states). We are planning to release new data that we will develop for the Greater sage-grouse range. We recommend using the new data products once available instead of these data products. These data will remain online as they are associated with the following citation, which provides a detailed explanation of the methods used to develop these data: O’Donnell, Michael S., David R. Edmunds, Cameron L. Aldridge, Julie A. Heinrichs, Peter S. Coates, Brian G. Prochazka, and Steve E. Hanser. 2018. Designing hierarchically nested and biologically relevant monitoring frameworks to study populations across scales. Ecosphere

We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different population growth rates among smaller clusters. Equally so, the spatial structure and ecological organization driving scale-dependent systems in a fragmented landscape affects dispersal behavior, suggesting inclusion in population monitoring frameworks. Studies that compare conditions among spatially explicit hierarchical clusters may elucidate the cause of differing growth rates, indicating the appropriate location and spatial scale of a management action. The data presented here reflect the results from developing a hierarchical monitoring framework and then applying these methods to Greater Sage-grouse in Nevada and Wyoming, US. When using these data for evaluating population changes or when identifying a spatially balanced sampling protocol, all cluster levels are designed to work together and therefore we recommend evaluating multiple cluster levels prior to selecting a single cluster level, if a single scale is desired, when analyzing population growth rates or other analyses, as these data are intended for multi-scale efforts. In other words, let your data decide which scale(s) are appropriate for the given species. These cluster levels are specific to Greater Sage-grouse but they may be appropriate for other sagebrush obligate species, but the user will need to make this determination. The products from this study aim to support multiple research and management needs. However, these data represent an interim data product because there may be errors associated with clusters along the edges of the state boundaries (due to the lack of lek data in neighboring states). We are planning to release new data that we will develop for the Greater sage-grouse range. We recommend using the new data products once available instead of these data products. These data will remain online as they are associated with the following citation, which provides a detailed explanation of the methods used to develop these data: O’Donnell, Michael S., David R. Edmunds, Cameron L. Aldridge, Julie A. Heinrichs, Peter S. Coates, Brian G. Prochazka, and Steve E. Hanser. 2018. Designing hierarchically nested and biologically relevant monitoring frameworks to study populations across scales. Ecosphere

We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different population growth rates among smaller clusters. Equally so, the spatial structure and ecological organization driving scale-dependent systems in a fragmented landscape affects dispersal behavior, suggesting inclusion in population monitoring frameworks. Studies that compare conditions among spatially explicit hierarchical clusters may elucidate the cause of differing growth rates, indicating the appropriate location and spatial scale of a management action. The data presented here reflect the results from developing a hierarchical monitoring framework and then applying these methods to Greater Sage-grouse in Nevada and Wyoming, US. When using these data for evaluating population changes or when identifying a spatially balanced sampling protocol, all cluster levels are designed to work together and therefore we recommend evaluating multiple cluster levels prior to selecting a single cluster level, if a single scale is desired, when analyzing population growth rates or other analyses, as these data are intended for multi-scale efforts. In other words, let your data decide which scale(s) are appropriate for the given species. These cluster levels are specific to Greater Sage-grouse but they may be appropriate for other sagebrush obligate species, but the user will need to make this determination. The products from this study aim to support multiple research and management needs. However, these data represent an interim data product because there may be errors associated with clusters along the edges of the state boundaries (due to the lack of lek data in neighboring states). We are planning to release new data that we will develop for the Greater sage-grouse range. We recommend using the new data products once available instead of these data products. These data will remain online as they are associated with the following citation, which provides a detailed explanation of the methods used to develop these data: O’Donnell, Michael S., David R. Edmunds, Cameron L. Aldridge, Julie A. Heinrichs, Peter S. Coates, Brian G. Prochazka, and Steve E. Hanser. 2018. Designing hierarchically nested and biologically relevant monitoring frameworks to study populations across scales. Ecosphere