Estimating traffic volume and road age in Wyoming to inform resource management planning: An application with wildlife-vehicle collisions

Abstract

Road networks and their associated vehicular traffic disturb many terrestrial systems, but inventories of roads used to assess these effects often focus on the ‘where’ (e.g., local road type and density) and neglect the ‘when’ (e.g., temporal disturbance) or ‘how much’ (e.g., traffic volume disturbance). We developed annual estimates of the ‘when’ (road age) and ‘how much’ (vehicular traffic volume) across 148,172 km of highways, arterials, collectors, local, and gravel/graded roads within the state of Wyoming for the years 1986 to 2020 to provide a comprehensive dataset for future ecological investigations. 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 and centrality metrics to estimate the age of each road. We then predicted traffic volume obtained from the Wyoming Department of Transportation for each year across Wyoming using a machine learning method, XGBoost, and a separate set of spatial covariates hypothesized to explain traffic patterns across large regions. We found that 132,476 km of these roads likely existed before 1986, but that 16,693 km (10.7 %) of roads have been built since 1986. Overall, our estimates of road age were 89 % accurate when assessed on a subset of 1,330 roads with high-resolution aerial imagery. Mean absolute error for predicting traffic volume ranged from 35.2 to 77.9 annual average daily traffic (aadt) for trucks and 269.2 to 516.7 aadt for all-vehicles across the 35 years. We found that mean traffic volume across the state increased by 23 % for both truck-only traffic and all vehicular traffic from 1986 to 2020. However, changes in traffic volume have varied substantially across the state (e.g., 100 % increases in volume in some areas, while other areas experienced declines of up to 1,786 %). We also illustrate a novel application of these data by predicting rates of reported wildlife-vehicle collisions (WVCs) along a subset of roads. We found evidence of a non-linear relationship that supported a threshold hypothesis for WVCs, wherein increases in traffic volume equate to increases in WVCs up to a threshold, above which increases in traffic volume result in declines in WVCs. The data provided here will enable better-informed studies of road ecology to address how roads may affect wildlife populations and key ecosystems across Wyoming.