Mitigation effectiveness for improving nesting success of greater sage-grouse influenced by energy development

Effectiveness of Wyoming's Sage-Grouse Core Areas: Influences on Energy Development and Male Lek Attendance

Greater sage-grouse (Centrocercus urophasianus) populations have declined across their range due to human-assisted factors driving large-scale habitat change. In response, the state of Wyoming implemented the Sage-grouse Executive Order protection policy in 2008 as a voluntary regulatory mechanism to minimize anthropogenic disturbance within defined sage-grouse core population areas. Our objectives were to evaluate areas designated as Sage-grouse Executive Order Core Areas on: (1) oil and gas well pad development, and (2) peak male lek attendance in core and non-core sage-grouse populations. We conducted our evaluations at statewide and Western Association of Fish and Wildlife Agencies management zone (MZ I and MZ II) scales. We used Analysis of Covariance modeling to evaluate change in well pad development from 1986-2014 and peak male lek attendance from 958 leks with consistent lek counts within increasing (1996-2006) and decreasing (2006-2013) timeframes for Core and non-core sage-grouse populations. Oil and gas well pad development was restricted in Core Areas. Trends in peak male sage-grouse lek attendance were greater in Core Areas compared to non-core areas at the statewide scale and in MZ II, but not in MZ I, during population increase. Trends in peak male lek attendance did not differ statistically between Core and non-core population areas statewide, in MZ I, or MZ II during population decrease. Our results provide support for the effectiveness of Core Areas in maintaining sage-grouse populations in Wyoming, but also indicate the need for increased conservation actions to improve sage-grouse population response in MZ I.

The influence of mitigation on sage-grouse habitat selection within an energy development field

Growing global energy demands ensure the continued growth of energy development. Energy development in wildlife areas can significantly impact wildlife populations. Efforts to mitigate development impacts to wildlife are on-going, but the effectiveness of such efforts is seldom monitored or assessed. Greater sage-grouse (Centrocercus urophasianus) are sensitive to energy development and likely serve as an effective umbrella species for other sagebrush-steppe obligate wildlife. We assessed the response of birds within an energy development area before and after the implementation of mitigation action. Additionally, we quantified changes in habitat distribution and abundance in pre- and post-mitigation landscapes. Sage-grouse avoidance of energy development at large spatial scales is well documented. We limited our research to directly within an energy development field in order to assess the influence of mitigation in close proximity to energy infrastructure. We used nest-location data (n = 488) within an energy development field to develop habitat selection models using logistic regression on data from 4 years of research prior to mitigation and for 4 years following the implementation of extensive mitigation efforts (e.g., decreased activity, buried powerlines). The post-mitigation habitat selection models indicated less avoidance of wells (well density β = 0.18 ± 0.08) than the pre-mitigation models (well density β = -0.09 ± 0.11). However, birds still avoided areas of high well density and nests were not found in areas with greater than 4 wells per km² and the majority of nests (63%) were located in areas with ≤ 1 well per km². Several other model coefficients differed between the two time periods and indicated stronger selection for sagebrush (pre-mitigation β = 0.30 ± 0.09; post-mitigation β = 0.82 ± 0.08) and less avoidance of rugged terrain (pre-mitigation β = -0.35 ± 0.12; post-mitigation β = -0.05 ± 0.09). Mitigation efforts implemented may be responsible for the measurable improvement in sage-grouse nesting habitats within the development area. However, we cannot reject alternative hypotheses concerning the influence of population density and intraspecific competition. Additionally, we were unable to assess the actual fitness consequences of mitigation or the source-sink dynamics of the habitats. We compared the pre-mitigation and post-mitigation models predicted as maps with habitats ranked from low to high relative probability of use (equal-area bins: 1 – 5). We found more improvement in habitat rank between the two time periods around mitigated wells compared to non-mitigated wells. Informed mitigation within energy development fields could help improve habitats within the field. We recommend that any mitigation effort include well-informed plans to monitor the effectiveness of the implemented mitigation actions that assess both habitat use and relevant fitness parameters.