Delineating and prioritizing areas where wildlife occur on a seasonal basis is critical for successful conservation and management of at-risk populations. Many local populations of greater sagegrouse (Centrocercus urophasianus) are of conservation concern in western North America because of continuing habitat loss and degradation caused by changing land use. To manage populations, wildlife managers need accurate, high-resolution maps of different seasonal habitats, guidelines for managing habitat at landscape scales, and quantitative tools to inform habitat prioritization and management. We conducted population-level, multi-scale, resource selection function (RSF) analyses with generalized estimating equations (GEE) using locations from 2006 to 2010 to model and map greater sage-grouse seasonal habitats in the Parachute-Piceance-Roan population in northwestern Colorado. Areas selected by greater sage-grouse in all seasons had a mix of habitats with a sagebrush component, less rugged topography, and less nonsagebrush habitat. Selection or avoidance of most vegetation classes was best supported at the 100-m or 400-m scale in all seasons. Birds selected sagebrush and sagebrush-grassland at intermediate elevations during breeding and winter and more diverse sagebrush habitats at higher elevations in summer and fall. Absolute validation index (AVI) analyses indicated that although most use locations were concentrated within a highly restricted portion of the study area in each season, a much larger proportion of the study area was required to encompass seasonal use locations for most individuals in the population. Our study illustrates the utility of multi-scale RSF analyses with GEE for accurately mapping habitat and AVI analyses for informing prioritization efforts for populations of greater sage-grouse. Ó

The identification of core habitat areas and resulting prediction maps are vital tools for land managers. Often, agencies have large datasets from multiple studies over time that could be combined for a more informed and complete picture of a species. Colorado Parks and Wildlife has a large database for greater sage‐grouse (Centrocercus urophasianus) including 11 radio‐telemetry studies completed over 12 years (1997–2008) across northwestern Colorado. We divided the 49,470‐km2 study area into 1‐km2 grids with the number of sage‐grouse locations in each grid cell that contained at least 1 location counted as the response variable. We used a generalized linear mixed model (GLMM) using land cover variables as fixed effects and individual birds and populations as random effects to predict greater sage‐grouse location counts during breeding, summer, and winter seasons. The mixed effects model enabled us to model correlations that may exist in grouped data (e.g., correlations among individuals and populations). We found only individual groupings accounted for variation in the summer and breeding seasons, but not the winter season. The breeding and summer seasonal models predicted sage‐grouse presence in the currently delineated populations for Colorado, but we found little evidence supporting a winter season model. According to our models, about 50% of the study area in Colorado is considered highly or moderately suitable habitat in both the breeding and summer seasons. As oil and gas development and other landscape changes occur in this portion of Colorado, knowledge of where management actions can be accomplished or possible restoration can occur becomes more critical. These seasonal models provide data‐driven, distribution maps that managers and biologists can use for identification and exploration when investigating greater sage‐grouse issues across the Colorado range. Using historic data for future decisions on species management while accounting for issues found from combining datasets allows land managers the flexibility to use all information available. © 2013 The Wildlife Society.