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States, road networks are extensive and motor vehicle use has datasets of varying qualities and scales. Results from this ef-
sharply increased as wild lands are progressively developed fort are intended to help agencies assess the efficacy of their
and suburbanized.21,110 Human population growth and its as- current WVC data collection and analytical techniques. The
sociated infrastructure expansion, as well as increasing work complements the growing body of research on mitigat-
wildlife populations in some areas, have led to greater safety ing road impacts for wildlife and improving highway safety.
concerns and the need to develop effective countermeasures Finally, it provides practitioners and managers with methods
to mitigate WVCs. In 2002, an estimated 1.5 million WVCs that can be quickly applied to available information and
resulted in 150 fatalities and $1.1 billion in vehicle damage in ultimately streamline the delivery of transportation projects
the United States.116 in areas where WVCs are a major concern to agencies and
Studies have demonstrated that WVCs are not random stakeholders.
occurrences but are spatially clustered.190,124,51,134 However,
few studies specifically probe the nature of WVC hotspots or
their use and application in transportation planning148,136 Research Approach: Methods and Data
and few have been spatially explicit. Most have utilized only Mapping Techniques
one method of determining hotspot locations. Many of the
studies characterizing WVCs have appeared in scientific and The objective of this research was to investigate different
management-focused journals, and often include different mapping techniques that can be used to identify WVC
conclusions or recommendations for managers to consider in hotspots. The techniques can be categorized as (1) simple
designing wildlife-friendly highways.190,124,183,158 However, lack- graphic, visual mapping exercises and (2) modeling of analyt-
ing are best management practices for identifying WVC ical techniques used to identify non-random clusters or
hotspots based on current knowledge and technology to help aggregations of WVCs. The simple plotting of WVCs can be
guide planning and decision making. done in a variety of GIS formats, for example ArcView® or
Because WVCs represent a distribution of points, clustering ArcGIS®, which currently are being used by many transporta-
techniques can be used to identify hotspots. Simple plotting of tion agencies. Simple plotting does not require statistical
WVC location points can be done in a variety of GIS formats, algorithms or metrics but is based on visual groupings of road-
for example, ArcView® or ArcGIS®77,78 currently being used by kill clusters and decision-based rules of defining hotspots.
many transportation agencies. Simple plotting does not Modeling WVCs using clustering mapping techniques is more
require statistical algorithms or metrics but is based on visual complicated. The research team evaluated the mapping
groupings of roadkill clusters and decision-based rules of techniques in the context of different scales of application
defining hotspots. Clustering of WVCs has been correlated to (project-level to state-level analysis) and transportation man-
animal distributions, abundances, and dispersal habits and agement concerns (e.g., motorist safety, endangered species
road-related factors including local topography, vegetation, management). Different mapping techniques are described
vehicle volume and speed, and fence location or type.190,4,47,51 using one dataset, WVCs in the Canadian Rocky Mountains,
In this report, the research team investigates various WVC to demonstrate how this readily available information can be
hotspot identification clustering techniques that can be used used by transportation agencies to identify collision hotspots
in a variety of landscapes, taking into account different scales at different scales of application. Then one clustering tech-
of application and transportation management concerns nique (CrimeStat®) was selected and hotspot analyses run
(e.g., motorist safety, endangered species management). using two different datasets: UVC carcass data from the
Using WVC carcass datasets from two locations in North Canadian Rocky Mountains and California Department of
America with varying wildlife communities, landscapes, and Transportation (Caltrans) deer carcass data (DVC) from
transportation planning issues, the research team demon- Northern California. The following sections describe the
strates how this information can be used to identify WVC hotspot patterns/configurations and examine how they may
hotspots at different scales of application (from project level differ by species and the two landscape types.
to state level analysis). The model-based clustering tech-
niques that are demonstrated include a linear nearest neigh-
Study Area
bor analysis used initially to measure if the WVC locations
were random and then Ripley's K statistic, nearest-neighbor Canadian Rocky Mountains. This study took place in
measurements, and density measures to identify hotspots. An the central Canadian Rocky Mountains in western Alberta
overview of software applications that facilitate these types of approximately 100 km west of Calgary (see Figure 10 in
analyses is provided. The information presented in this report Section 3.2). The area encompasses the Bow River watershed
is intended to advance understanding of the considerations and includes mountain landscapes in Banff National Park
that should be taken into account when analyzing WVC and adjacent Alberta Provincial lands in Kananaskis Country.
