Ecological risks of shale oil and gas development to wildlife, aquatic resources and their habitats.

Technological advances in hydraulic fracturing and horizontal drilling have led to the exploration and exploitation of shale oil and gas both nationally and internationally. Extensive development of shale resources has occurred within the United States over the past decade, yet full build out is not expected to occur for years. Moreover, countries across the globe have large shale resources and are beginning to explore extraction of these resources. Extraction of shale resources is a multistep process that includes site identification, well pad and infrastructure development, well drilling, high-volume hydraulic fracturing and production; each with its own propensity to affect associated ecosystems. Some potential effects, for example from well pad, road and pipeline development, will likely be similar to other anthropogenic activities like conventional gas drilling, land clearing, exurban and agricultural development and surface mining (e.g., habitat fragmentation and sedimentation). Therefore, we can use the large body of literature available on the ecological effects of these activities to estimate potential effects from shale development on nearby ecosystems. However, other effects, such as accidental release of wastewaters, are novel to the shale gas extraction process making it harder to predict potential outcomes. Here, we review current knowledge of the effects of high-volume hydraulic fracturing coupled with horizontal drilling on terrestrial and aquatic ecosystems in the contiguous United States, an area that includes 20 shale plays many of which have experienced extensive development over the past decade. We conclude that species and habitats most at risk are ones where there is an extensive overlap between a species range or habitat type and one of the shale plays (leading to high vulnerability) coupled with intrinsic characteristics such as limited range, small population size, specialized habitat requirements, and high sensitivity to disturbance. Examples include core forest habitat and forest specialists, sagebrush habitat and specialists, vernal pond inhabitants and stream biota. We suggest five general areas of research and monitoring that could aid in development of effective guidelines and policies to minimize negative impacts and protect vulnerable species and ecosystems: (1) spatial analyses, (2) species-based modeling, (3) vulnerability assessments, (4) ecoregional assessments, and (5) threshold and toxicity evaluations.

Landscape characteristics influencing the genetic structure of greater sage-grouse within the stronghold of their range: a holistic modeling approach.

Given the significance of animal dispersal to population dynamics and geographic variability, understanding how dispersal is impacted by landscape patterns has major ecological and conservation importance. Speaking to the importance of dispersal, the use of linear mixed models to compare genetic differentiation with pairwise resistance derived from landscape resistance surfaces has presented new opportunities to disentangle the menagerie of factors behind effective dispersal across a given landscape. Here, we combine these approaches with novel resistance surface parameterization to determine how the distribution of high- and low-quality seasonal habitat and individual landscape components shape patterns of gene flow for the greater sage-grouse (Centrocercus urophasianus) across Wyoming. We found that pairwise resistance derived from the distribution of low-quality nesting and winter, but not summer, seasonal habitat had the strongest correlation with genetic differentiation. Although the patterns were not as strong as with habitat distribution, multivariate models with sagebrush cover and landscape ruggedness or forest cover and ruggedness similarly had a much stronger fit with genetic differentiation than an undifferentiated landscape. In most cases, landscape resistance surfaces transformed with 17.33-km-diameter moving windows were preferred, suggesting small-scale differences in habitat were unimportant at this large spatial extent. Despite the emergence of these overall patterns, there were differences in the selection of top models depending on the model selection criteria, suggesting research into the most appropriate criteria for landscape genetics is required. Overall, our results highlight the importance of differences in seasonal habitat preferences to patterns of gene flow and suggest the combination of habitat suitability modeling and linear mixed models with our resistance parameterization is a powerful approach to discerning the effects of landscape on gene flow.