U.S. Geological Survey, Fort Collins Science Center Fort Collins, Colorado, United States
Abstract: Road networks and their associated vehicular traffic negatively impact populations of many terrestrial species by causing habitat degradation, functional habitat loss, and direct mortality. Inventories of roads used to assess these impacts often focus on the ‘where’ (e.g., spatial disturbance) but neglect the ‘when’ (e.g., temporal disturbance) or ‘how much’ (e.g., dynamic traffic disturbance). Knowing these characteristics is critical for assessing the cumulative impact of roads and their associated vehicular traffic on ecosystems. We developed annual estimates of road age and vehicular traffic volume across 147,108 km of highways, arterials, collectors, local, and gravel/graded roads within the state of Wyoming for the years 1986 to 2020. We leveraged a suite of ancillary data on surface disturbances (e.g., oil & gas drilling operations, wind turbines, and open pit mines) with known establishment dates and combined them using graph theory to estimate the age of each road. We then predicted traffic volume for each year across Wyoming using XGBoost, a novel machine learning method, to relate ongoing traffic monitoring by the Wyoming Department of Transportation with a separate set of spatial covariates hypothesized to explain traffic patterns across large regions. We use these estimates of traffic volume to assess how traffic has impacted Greater sage-grouse (Centrocercus urophasianus) population growth rates across the state. Declines and extirpation of Greater sage-grouse have been documented at lek sites near major highways and other transportation infrastructure since the 1950s but are not well studied. Recent decades have also seen increased traffic associated with energy development such as oil and gas drilling, which can elevate stress hormones, change lekking behavior, and increase mortality. The cumulative and long-term impacts of vehicular traffic on sage-grouse populations are largely unknown, yet very little sage-grouse habitat in Wyoming remains untouched by road infrastructure. We used the estimates of traffic volume in a multi-scale Bayesian hierarchical modeling framework to 1) assess how traffic has impacted sage-grouse population growth rates, 2) identify the spatial scales at which these effects are most evident, and 3) identify what levels of traffic result in sage-grouse population declines. We find that effects of traffic volume tend to be detrimental to population growth rates, and that these effects are local. Areas that experienced rapid growth in development also experienced the greatest declines in sage-grouse population abundance.