Seasonal Habitat Use by Greater Sage-Grouse (Centrocercus urophasianus) on a Landscape with Low Density Oil and Gas Development

Abstract

Fragmentation of the sagebrush (Artemisia spp.) ecosystem has led to concern about a variety of sagebrush obligates including the greater sage-grouse (Centrocercus urophasianus). Given the increase of energy development within greater sage-grouse habitats, mapping seasonal habitats in pre-development populations is critical. The North Park population in Colorado is one of the largest and most stable in the state and provides a unique case study for investigating resource selection at a relatively low level of energy development compared to other populations both within and outside the state. We used locations from 117 radio-marked female greater sage-grouse in North Park, Colorado to develop seasonal resource selection models. We then added energy development variables to the base models at both a landscape and local scale to determine if energy variables improved the fit of the seasonal models. The base models for breeding and winter resource selection predicted greater use in large expanses of sagebrush whereas the base summer model predicted greater use along the edge of riparian areas. Energy development variables did not improve the winter or the summer models at either scale of analysis, but distance to oil/gas roads slightly improved model fit at both scales in the breeding season, albeit in opposite ways. At the landscape scale, greater sage-grouse were closer to oil/gas roads whereas they were further from oil/gas roads at the local scale during the breeding season. Although we found limited effects from low level energy development in the breeding season, the scale of analysis can influence the interpretation of effects. The lack of strong effects from energy development may be indicative that energy development at current levels are not impacting greater sage-grouse in North Park. Our baseline seasonal resource selection maps can be used for conservation to help identify ways of minimizing the effects of energy development.

Greater Sage‐Grouse Response to the Physical Footprint of Energy Development

“…There is much previous research that has focused on the response of sage‐grouse to specific development types or infrastructure features, including wind turbines, conventional oil wells, natural gas wells, or transmission lines (Aldridge and Boyce 2007, Dinkins et al 2014, Rice et al 2016, Lebeau et al 2017, Gibson et al 2018). Because this was not the intent of our research, we did not isolate potential effects from exposure to specific infrastructure features.…”

Habitat specialists as conservation umbrellas: Do areas managed for greater sage‐grouse also protect pygmy rabbits?

“…Two general habitat features are associated with the year-round presence of pygmy rabbits: (1) relatively dense and tall sagebrush vegetation and (2) soil characteristics that are conducive to burrowing, such as the presence of deep, loamy soils, and features such as alluvial fans and Mima mounds (Borell and Ellis 1934, Weiss and Verts 1984, McMahon et al 2017. Unlike pygmy rabbits, sage-grouse shift habitat use across the year, and biologists often consider spring breeding, summer brood rearing, and winter habitats as distinct (Fedy et al 2014, Rice et al 2016.…”

Defining biologically relevant and hierarchically nested population units to inform wildlife management

“…We considered important candidate habitat covariates and scales identified in resource selection functions defining habitat suitability for clustering (Coates et al, 2019; Fedy et al, 2014; Rice et al, 2016; Saher et al, 2022). The continuous habitat covariate data included terrain indices (5 datasets), percent cover of shrubland vegetation communities (10 datasets; Rigge et al, 2021), and bioclimatic variables (5 datasets; O'Donnell & Ignizio, 2012).…”

“…For each covariate, we used zonal statistics to summarize the spatial data surrounding a lek within seven radii (an additional three radii were used for terrain indices) occurring between 30 m and 6400 m (7–10 datasets). Although 30‐m pixel sizes are small, this scale is commonly considered in sage‐grouse species distribution models (Coates et al, 2019; Fedy et al, 2014; Rice et al, 2016; Saher et al, 2022). The pixels associated with each lek are also summarized across all leks in a group (a minimum of 15 leks), so the combined area is larger than 30 m. We calculated arithmetic mean and coefficient of variation (standard deviation / mean) for the zonal statistics (see supplemental S2 and Tables S1 and S2 for definitions of indices, data sources, scales, and statistics).…”

“…Although 30-m pixel sizes are small, this scale is commonly considered in sage-grouse species distribution models (Coates et al, 2019;Fedy et al, 2014;Rice et al, 2016;Saher et al, 2022). The pixels associated with each lek are also summarized across all leks in a group (a minimum of 15 leks), so the combined area is larger than 30 m.…”