Western Transportation Institute

Permanent URI for this communityhttps://scholarworks.montana.edu/handle/1/35

The Western Transportation Institute is the country's largest National University Transportation Center focused on rural transportation issues. Because we live and work in rural communities, we understand the critical roles rural transportation plays in the lives of people, in the environment and in the economy. We draw from our eight integrated research groups to create solutions that work for our clients, sponsors and rural transportation research partners. WTI focuses on rural issues, but some of our program areas also address the concerns of the urban environment. Whatever the objective, we bring innovation and expertise to each WTI transportation research project. WTI's main facility with its state-of-the-art labs is adjacent to the Montana State University campus in Bozeman, Montana. We have additional offices in Alberta, Canada, and central Washington, and a large testing facility in rural Montana near Lewistown. Contact us to find out how to address your rural transportation research needs.

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    Exploring Apex Predator Effects on Wildlife-Vehicle Collisions: A Case Study on Wolf Reintroductions in Yellowstone
    (Western Transportation Institute, 2024-09) Bell, Matthew; Huijser, Marcel P.; Kack, David
    This study investigates the impact of wolf reintroduction on wildlife-vehicle collisions (WVCs) along a segment of US-191 bordering Yellowstone National Park. Wolves were reintroduced in 1995–1996, and subsequent wolf pack establishment may have influenced the behavior and population dynamics of prey species, potentially altering WVC patterns. Using carcass data collected from 1989 to 2021, the analysis was divided into two primary phases: before wolves (1989–1996) and after wolves (1997–2021). A series of linear mixed-effects models were developed to assess changes in WVCs across these time periods. Predictor variables included average annual daily traffic (AADT), elk population estimates, and wolf counts. Results showed that WVCs significantly declined in the post-wolf period, suggesting that the presence of wolves may reduce WVCs directly by modifying prey behavior and movement patterns, or indirectly by reducing prey population densities. Further analysis revealed that while elk populations were a significant predictor of WVCs before wolves were reintroduced, this relationship weakened post-reintroduction. Traffic volume did not significantly influence WVC patterns in either period, nor did it interact significantly with wolf presence. The inclusion of wolf counts as a continuous variable showed a negative relationship with WVCs, indicating that higher wolf densities may contribute to a further reduction in collisions over time. These findings suggest that apex predators can play a role in mitigating human-wildlife conflicts, such as WVCs, by influencing prey species’ behavior and distribution. The study provides valuable insights for wildlife managers and transportation planners, highlighting the potential benefits of predator conservation for road safety and ecosystem health.
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    Patterns of Domestic Animal-Vehicle Collisions on Tribal Lands in Montana, U.S.
    (Western Transportation Institute, 2024-09) Bell, Matthew; Huijser, Marcel P.; Kack, David
    Animal-vehicle collisions (AVCs) are a significant concern for motorist safety and pose a risk to both wildlife and domestic animals. This report analyzes spatial patterns of wildlife-vehicle collisions (WVCs) and domestic animal-vehicle collisions (DAVCs) on Montana’s tribal lands to identify high-risk areas and inform mitigation strategies. Data from the Montana Department of Transportation (MDT) for large mammal carcasses (2008–2022) and reported crashes (2008–2020) were used to perform Kernel Density Estimation (KDE) and Getis-Ord Gi* (GOG) hotspot analyses for three tribal reservations with sufficient data: Blackfeet, Crow, and Flathead. The KDE results show distinct spatial patterns for DAVCs and WVCs on each reservation, with DAVC hotspots concentrated near agricultural and grazing areas, while WVC hotspots were associated with natural habitats and wildlife corridors. The GOG analysis further revealed that DAVC hotspots tend to be more temporally stable, suggesting that collisions with domestic animals are influenced by consistent factors such as livestock access points and grazing practices. In contrast, WVC hotspots were more variable, likely driven by changes in wildlife movement patterns and seasonal behavior. Overall, the findings indicate that the elevated rates of DAVCs on tribal lands, compared to non-tribal lands, are likely due to unique factors such as open range grazing practices and road infrastructure adjacent to grazing lands. This report emphasizes the need for targeted mitigation strategies on tribal roads, such as enhanced livestock fencing, road signage, and livestock underpasses in high-risk areas, to reduce collisions and improve safety for both motorists and animals. Understanding the distinct spatial and temporal patterns of DAVCs and WVCs is crucial for developing comprehensive mitigation approaches that enhance safety and connectivity on Montana’s tribal lands.
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    Identification and prioritization of road sections with a relatively high concentration of large wild mammal-vehicle collisions in Gallatin County, Montana, USA
    (2024-09) Huijser, Marcel P.; Bell, Matthew A.
    The primary objective of this project is to identify and prioritize the road sections in Gallatin County that have a relatively high concentration of collisions involving large wild mammals. These road sections may then later be evaluated for potential future mitigation measures aimed at 1. Reducing collisions with large wild mammals, and 2. Providing safe passage across roads for large wild mammals, as well as other wildlife species in the area. We acquired the 3 datasets related to large wild mammal-vehicle collisions in Gallatin County: 1. Wildlife-vehicle crash data collected by law enforcement personnel, 2. Carcass removal data collected by road maintenance personnel; and 3. Grizzly bear road mortality data by the U.S. Geological Survey. The carcass removal data and grizzly bear road mortality data were merged into one carcass database. We conducted separate analyses for the crash data and the carcass data. We conducted two different types of analyses to identify and prioritize road sections with the highest number of wildlife-vehicle crashes and carcasses: 1. Kernel Density Estimation (KDE) analysis that identifies road sections with the highest concentration of collisions, and 2. Getis-Ord Gi* analysis identifies road sections that have statistically significant spatial clusters of collisions. There was great similarity between the hotspots identified through the Kernel Density Estimation analyses for 2008-2022 and 2018-2022 for both the crash and carcass removal data. The same was true for the Getis-Ord Gi* analyses. Especially sections of I-90 and US Hwy 191 between I-90 through Four Corners to the mouth of Gallatin Canyon had the highest concentration of wild animal crashes and large wild animal carcasses. Based on the Getis-Ord Gi* analyses, these road sections generally had concentrations of crashes and carcasses that were significantly higher than expected should the crashes and carcasses have been randomly distributed. In other words, these road sections do not only have the highest concentration of crashes and carcasses, but the identification of these road sections is not based on coincidence. These road sections have a concentration of crashes and carcasses that is beyond random.
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