BackgroundCurrently there is a critical need for accurate and standardized wildlife-vehicle collision data, because it is the underpinning of mitigation projects that protect both drivers and wildlife. Gathering data can be challenging because wildlife-vehicle collisions occur over broad areas, during all seasons of the year, and in large numbers. Collecting data of this magnitude requires an efficient data collection system. Presently there is no widely adopted system that is both efficient and accurate.Methodology/Principal FindingsOur objective was to develop and test an integrated smartphone-based system for reporting wildlife-vehicle collision data. The WVC Reporter system we developed consisted of a mobile web application for data collection, a database for centralized storage of data, and a desktop web application for viewing data. The smartphones that we tested for use with the application produced accurate locations (median error = 4.6–5.2 m), and reduced location error 99% versus reporting only the highway/marker. Additionally, mean times for data entry using the mobile web application (22.0–26.5 s) were substantially shorter than using the pen/paper method (52 s). We also found the pen/paper method had a data entry error rate of 10% and those errors were virtually eliminated using the mobile web application. During the first year of use, 6,822 animal carcasses were reported using WVC Reporter. The desktop web application improved access to WVC data and allowed users to easily visualize wildlife-vehicle collision patterns at multiple scales.Conclusions/SignificanceThe WVC Reporter integrated several modern technologies into a seamless method for collecting, managing, and using WVC data. As a result, the system increased efficiency in reporting, improved accuracy, and enhanced visualization of data. The development costs for the system were minor relative to the potential benefits of having spatially accurate and temporally current wildlife-vehicle collision data.

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As roads continue to be built and expanded, it is important that managers understand the effects that vehicle-related mortality can have on the population dynamics of wildlife. Our objective was to examine the frequency of mule deer (Odocoileus hemionus) vehicle collisions to determine if different demographic groups showed differential susceptibility to mortality when compared with their proportion in the population. We also compared vehicle collision rates of mule deer, elk (Cervus canadensis), and moose (Alces alces) to determine their relative vulnerability to vehicle collisions. We found that 65% of mule deer involved in vehicle collisions were female; of those, 40% were adult does ≥2 yrs. When we compared the proportion of bucks, does, and fawns killed in vehicle collisions to surveys of live deer, we found that bucks were killed at rate of 2.1–3.0 times their proportion in the population. Additionally, when we compared vehicle collision rates for 2010 and 2011, we found that mule deer were 7.4–8.7 times more likely to be involved in collisions than elk and 1.2–2.0 times more likely than moose. However, we were unable to detect a negative correlation (P=0.55) between mule deer abundance and increasing traffic volume.

Understanding how deer move in relationship to roads is critical, because deer are in vehicle collisions, and collisions cause vehicle damage, as well as human injuries and fatalities. In temperate climates, mule deer Odocoileus hemionus have distinct movement patterns that aff ect their spatial distribution in relationship to roads. In this paper, we analyzed deer movements during two consecutive winter seasons with vastly diff erent conditions to determine how deer -vehicle collision rates responded. We predicted that deer -vehicle collision rates would be higher when precipitation and snow depth were higher. We used meteorological data from local weather stations to describe temperature, precipitation and snow depth. We monitored deer movements with global positioning system telemetry to document distance of deer to roads, elevation use and road crossing rates. We also documented changes in deer abundance and traffi c volumes, which were potentially confounding variables. We found that precipitation decreased 50% and snow depth decreased 48% between winters. In response, deer used habitats that were 16% higher in elevation and that were 213% farther from roads with high traffi c volumes. Consequently, crossing rates also decreased as much as 96% on roads with high traffi c volumes. Reduced crossing rates were likely responsible for much of the 75% decrease in deer -vehicle collisions that occurred during the second winter. Abundance and traffi c volume also can be important factors aff ecting deer -vehicle collisions rates. However, it is unlikely they were the major drivers of variation in deer -vehicle collisions during our study, because traffi c volumes did not change between years and deer abundance only decreased 7%. Our data suggest a mechanism by which variation in winter conditions can contribute to diff erences in deer -vehicle collision rates between years. h ese fi ndings have signifi cant management implications for deer -vehicle collision mitigation.