Temporal and hierarchical spatial components of animal occurrence: conserving seasonal habitat for greater sage-grouse

Developing strategies for sustainable management of landscapes requires research that bridges regionally important ecological and socioeconomic issues, and that aims to provide solutions to sustainability problems. We integrated Global Positioning Systems (GPS) telemetry and statistical modeling to quantify hierarchical spatial and temporal components of occurrence among greater sage-grouse (Centrocercus urophasianus; n = 87), a species of conservation concern, with the larger goal of developing spatially-explicit guidance for conservation of important winter habitat in a Wyoming, USA landscape undergoing development for energy resources. The pattern of occurrence at the landscape level (second-order) and within seasonal use areas (third-order) included selection for shrub vegetation with a prominent sagebrush (Artemisia spp.) component, and avoidance of rough terrain, mesic areas, and human activity. A change in resource selection behavior across the diel cycle was not an apparent component of the higher-order selection process; however, at the finer scale of investigation sage-grouse shifted behavior across the diel cycle in ways likely related to risk aversion or maintaining a favorable thermal environment (i.e., day-time-only avoidance of natural gas wells and night-time-only selection for taller shrubs). At both spatial scales there was considerably more variation among individuals in the sign of their association with anthropogenic features than with vegetation and terrain. The final spatially-explicit model, which depicted lower-order selection (local, patch-level, and seasonal use area) across the diel cycle constrained by selection processes at a higher order (second-order), validated well, offering specific guidance for managing human activity and sage-grouse conservation in the study area, and general guidance in developing sustainable landscape management strategies when animal occurrence reflects multiple spatial and temporal processes.