Topographic constraints appear to concentrate energy infrastructure in areas with gentler topography that also have the highest GrSG use. Three land cover classes most affected by energy infrastructure were also those strongly selected by GrSG. By 2015, anthropogenic infrastructure covered 2.70% of occupied range and 2.93% of GrSG habitat, and energy infrastructure covered 2.50% and 10.79% of two priority habitat management area zones in the PPR. Pipelines comprised 74-80% of reclaimed surface and roads comprised 54-69% of disturbed surface across years.
facilities, roads, pipelines) rather than well pads, with an average of 2.24 ± 0.52 SE ha of supporting infrastructure per ha of well pad. The majority of energy infrastructure present each year (77-84%) was supporting infrastructure (i.e. In contrast, non-energy infrastructure decreased to 532 ha (-8.3%). During that time, the footprint of energy infrastructure more than doubled to 3,275 ha (+108.6%), including 195 new well pads, 930 ha of new pipelines, and 230 km of new roads. We mapped the annual distribution, surface type, and activity level of energy and non-energy infrastructure in the Parachute-Piceance-Roan (PPR), a small, peripheral greater sage-grouse population in Colorado with expanding oil and gas development, from 2005 to 2015. Increasing energy development within GrSG range has prompted the need to quantify and predict impacts of energy infrastructure on their habitat and populations. and Canada and the focus of widespread conservation and management efforts. The greater sage-grouse (Centrocercus urophasianus GrSG) is a species of concern in sagebrush ecosystems of the western U.S.
Quantifying the effects of energy infrastructure on land cover and wildlife habitat is essential for informing land-use policy, developing wildlife conservation strategies, and projecting impacts of future development.
New technologies and increasing energy demand have contributed to rapid expansion of unconventional oil and gas development in the U.S. Journal of Wildlife Management published by Wiley Periodicals, Inc. 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.
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. 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. Selection or avoidance of most vegetation classes was best supported at the 100-m or 400-m scale in all seasons. Areas selected by greater sage-grouse in all seasons had a mix of habitats with a sagebrush component, less rugged topography, and less non-sagebrush habitat. 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. 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. Many local populations of greater sage-grouse (Centrocercus urophasianus) are of conservation concern in western North America because of continuing habitat loss and degradation caused by changing land use. Delineating and prioritizing areas where wildlife occur on a seasonal basis is critical for successful conservation and management of at-risk populations.
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