Wildlife and Roads: Decision Guide Step 1.2
Identify Wildlife & Fisheries Issues
1.2 Identify Wildlife & Fisheries Issues: We direct the users to a series of steps which first provide a literature base on the effects of roads, and the need for permeability for wildlife. The guide then instructs the user in identifying the species, natural areas, and natural processes that may be affected by the plan/project. At the end of this step, the user will decide if there is a need for mitigation and whether to proceed with the decision guide.
1.2.1 Literature on the Effects of Roads and the Need for Permeability
- 184.108.40.206 Introduction to Road Effects and Permeability
- 220.127.116.11 Ecological Effects of Roads Selected Literature
- 18.104.22.168 Additional Literature of Road Effects and Permeability
22.214.171.124 Related Websites
Transportation, Ecological Services, and the Virtual Footprint
Historically, linking transportation and ecological services may have seemed inherently in conflict but they need not be so. One can envision roads as having a physical as well as a virtual footprint. The physical footprint is easy to see and includes the actual dimensions of the road (length and width), as well as the dimensions of associated structures, e.g., the right-of-way. The virtual footprint is much larger and includes the area where the indirect effects of roads are manifested. The roaded landscape has both direct and indirect effects on wildlife species, community biodiversity, and ecosystem health and integrity. The most prevalent direct effect is road kill. Indirect effects include reduced habitat quality, barrier effects, and loss of connectivity resulting in restricted or changed animal movement patterns. The virtual footprint, therefore, can be understood only when put into a landscape, context-sensitive perspective. Here the 'Cinderella Principle' needs to be applied; namely establishing mitigation that effectively 'shrinks' the virtual footprint to more closely resemble the physical footprint. For surface transportation, this means that highway planners and engineers need to continue to incorporate mitigation measures that restore ecological integrity and landscape connectivity, while at the same time insuring safe state-of-the-art transportation services in a cost effective manner. This is not an inherently difficult job, but it does require purposeful activity guided by informed, synthetic analyses that reflect true benefits and costs. We define transportation services to mean, among other things, safe, efficient, reliable roads, inexpensive transportation, properly constructed intersections, safe and quiet road surfaces, good visibility, safe bridges, and good signage. By ecosystem services, we mean clean water, clean air, uncontaminated soil, natural landscape processes, recreational opportunities, abundant wildlife, normal noise levels, and a connected landscape that leads to restoration and maintenance of life-sustaining ecological processes.
Currently across North America, a mismatch exists. Ecosystem services have been compromised by road construction. The virtual road footprint is too large. We suggest that the overarching principle that needs to guide future road construction, renovation, and maintenance needs to link both transportation and ecological services. That is accomplished by reestablishing connectivity across the landscape. But restoration of connectivity is the desired end. The mechanism by which connectivity is established involves moving from roaded landscapes that are nearly impermeable, to landscapes that are semi-permeable and finally, fully permeable; when accomplished, the landscape is connected, and ecological services are restored. Nearly normal hydrologic flow, facilitated animal movement, reconnection of isolated populations and gene flow are made possible. In other words, the Cinderella Principle of 'shrinking the virtual footprint' has been applied effectively, restoring landscape permeability. Ecological objectives have been met coincident with a continually effective roadway network.
Permeability: The Ultimate Goal of Smart Roads
The concept and practical application of permeability might best be understood by an example. Imagine a middle-aged couple who live in a small town or suburb. They work close to their home, and shop in the neighborhood. They have walking access to a grocery store, a church, a pharmacy, a movie theater, a medical clinic; in short, all of the amenities they need for a happy and comfortable life. Then suppose that a major road that runs through the suburb is enhanced and made into a 4 lane divided interstate highway with its accompanying fences and barriers, to accommodate the increased traffic and to provide the requisite and expected transportation services. Because of the location of the road, it now separates our imaginary couple from their work, and from the amenities that they depended on and could access easily before. The couple, who always walked to access these amenities and resources, is now blocked by the highway. The highway does, however, provide connectivity in the form of crosswalks spaced approximately 6 to 8 blocks apart. The couple has a choice. They can either use their car and bear with the heavy traffic, or walk many more blocks to access the crosswalks that would allow them to cross the road. It is unsafe for them to cross the highway in any place other then the crosswalks provided. Their cohesive neighborhood is still connected, but much less permeable. This is the critical difference between connectivity and permeability. Regardless of the choice they make, accessing the resources the couple needs for everyday life is now much more difficult and entails much longer distances and a greater time commitment. Although fanciful, this imaginary situation is analogous to what happens to ecosystem resources for wildlife when highways are built across natural landscapes. Connectivity can be maintained by crossings, but the placement, type, and configuration of the crossing will determine whether permeability is impacted. Think of crossings as a funnel that guides animals under or over roads. Then imagine a context-sensitive road design that incorporates different types and designs of crossings in appropriate locations. The result can be thought of as a 'sieve' that facilitates animal movement, rather than a 'funnel'. Connectivity evolves to permeability.
Restoring connectivity is a land-based concept and easy to understand. As can be seen by the example given above, it is not necessarily equivalent with the idea of landscape permeability, which is an animal-centered concept. The difference between the two concepts involves the idea of scale sensitive (allometric), animal-based movement. Permeability implies the ability of the animal to move across its home range or territory, (its ecological neighborhood) in a relatively unhindered manner, i.e., movement ease can be indexed by essentially a straight-line distance to resources. To put this into scientific terms, the fractal measure of the pathway less-tortuous and is of lower dimension. Anything that hinders movement or increases distance moves the landscape in the direction of impermeability. Scale-sensitivity considerations enter the picture because different animals have different movement capabilities and respond to the same landscape in very different ways. A mouse does not use or move across its home range or scale to the landscape in the same way a moose does. Hence an assessment of the local animal community that exists in the landscape that the road crosses is essential and will suggest different crossing types, configurations, and locations in order to achieve permeability in roaded landscapes. Understanding animal behavior is critical in achieving permeability.
Providing guidance on the use and effectiveness of wildlife crossings to mitigate habitat fragmentation and reduce the number of animal vehicle collisions involves thinking in a context sensitive framework that is based on sound ecological principles. Connectivity is intimately linked to permeability. Permeability is the goal of smart roads and intelligent mitigation. Our goal for this decision guide is to develop effective guidelines based on this premise: understanding and establishing landscape permeability guidelines that lead to effective landscape connectivity and the restoration of ecosystem integrity—while continuing to provide efficient and effective transportation infrastructure in a cost-effective economic manner.
Click on a citation to view annotated notes
The authors consider a comprehensive framework for considering all the impacts of roads that would enable scientists and managers to develop assessment tools that more accurately inform stakeholders and policy makers about the biological consequences of road building. The two dimensional framework recognizes the three phases of road development, and five classes of environmental impacts associated with road development. They use their analysis to look at a DEIS (Draft Environmental Impact Statement, a mandatory document to analyze the potential effects of a development project) for a proposed interstate highway to illustrate which road impacts are typically ignored. Phases of road development include: 1: Road Construction, 2: Road Presence - which are roads that pass within 1 km of a water body, 3: Urbanization. The classes of factors that affect biota are: habitat structure, water chemistry, flow regime, energy source and biotic interactions. They found the DEIS results for I-73, Vermont, which followed Federal Highways guidelines for such documents, sharply contrasted between the scope of an impact assessment based on their framework of 15 different factors and the scope of actual assessment for the proposed interstate. Many impacts, especially long-term ones were overlooked or minimized. Rectifying the problem requires fundamental changes in how road impacts are defined, measured, and incorporated into policy decisions. In particular, they state that the spatial and temporal extent of assessments must be expanded to match the scales over which the most serious biological impacts of road development are manifest.
Bissonette introduces his concept of the Cinderella principle. It is mitigation to diminish both direct and indirect effects of roads, thus shrinking the virtual footprint to more closely match its physical presence. It is essential to 'make the shoe fit' in order to restore ecological health and integrity. He lists the direct effects of roads as mortality, and the indirect effects as habitat loss, barrier effects, cumulative effects, increased fragmentation, increased edge, loss of connectivity, and reduced habitat quality. These all in turn change the behavior and movement dynamics of wildlife, the spatial structure of populations, and the underlying population dynamics.
—View this literature online.
Forman defines the "road-effect zone" as the corridor of ecological effects associated with a particular roadway. Based on studies in the Netherlands and Massachusetts, he estimates the total road-effect zone of the United States. There are 6.2 million km of public roads in the U.S., covering approximately one percent of the landscape. Excluding indirect ecological effects of transportation like air pollution, Forman assumes various roadway characteristics (such as the categorization of primary and secondary roads in urban and rural areas and their associated traffic volumes) to generate his estimate. He comes up with an estimate of 19% of the U.S. affected ecologically by roadways; considering only the lower 48, the percentage if about 22%. He then lists factors that could lower (such as excluding agricultural areas from definitions of natural landscapes) or raise (greater accessibility for humans into areas because of roads) the estimate. Conservatively, Forman estimates that a fifth of the United States experiences ecological effects of roads, but points out that the value is probably higher, especially when you include air pollution and other indirect effects. Finally, he lists potential methods to mitigate ecological effects, such as building more wildlife crossing structures and concentrating traffic in rural areas on primary roads.
Overview of ecological effects of roads. Chapters include: History and Status of the U.S. Road System, Effects of Roads on Ecological Conditions, Ameliorating the Effects of Roads, Legal Context for Planning and Policy, Planning and Assessment, Integrating Obstacles and Opportunities, Appendixes: Biographical info of committee members, spatial scale of road effects on ecological conditions, annotated bibliography, congressional declaration of National Environmental Policy Act of 1969.
An overall review on all documented ecological, geological, chemical effects of roads worldwide. The author reviewed 388 references for this database. He also documents literature databases where one can find more reviews of peer-reviewed papers and their abstracts, including: Transportation Research Board Publications, and Road-Rip Roads Bibliographic database from Wildlands CPR. He briefly reviews: Environmental costs of roads, ecological effects of secondary activities, interactions between biota and roads, impacts of traffic and tourism in new areas facilitated by new roads; effects of roads on the physical environment; structures associated with roads (rest areas, signs, electricity poles); de-icing agents; and geologic effects. He reviewed: pollution and disturbance effects on biota and ecosystems; noise and artificial lighting; dust and sand effects; heavy metals in plants, animals and ecosystems; gases from exhaust; effects on aquatic systems and biota; additional effects such as road kill and long term effects to populations; habitat fragmentation; edge effects and microclimates in forests; effects of fragmentation of forest birds; effects on small mammals; consequences for feral predators; roads, fragmentation and invasive plant species; road verges and linear habitat; traffic and dispersal of plant species; assessing risks and impacts through the different environmental documents for different countries; and readdressing the detrimental effects of roads. This is a good overall review of the literature prior to 2000, with the literature cited encompassing several pages in the end.
An overall synthesis of the published record of the effects of roads on ecological communities. They categorize 7 general effects: mortality from road construction, mortality from vehicle collisions, modification of animal behavior, alteration of the physical environment, alteration of the chemical environment, spread of exotics, and increased use of areas by humans. Documentation of other findings on how wildlife are affected, as well as riparian areas and fish also affected by roads. Termed the word, hyperfragmentation to describe the multidimensional view of ecological fragmentation and habitat loss that emerges when the consequences of roads or any habitat alteration for terrestrial and aquatic ecosystems are considered simultaneously. Article is somewhat naive about literature and research that is out there, and even in just 4 years, a bit outdated (for example, recent wolverine research has shown contrary data).
Click on a title to view annotated notes
Taken directly from Ecology Abstracts database: The authors review, develop, and differentiate among concepts associated with environmental patterning (patch, division, and heterogeneity), spatial and temporal scales of ecological processes (ecological neighborhoods), and response of organisms to environmental patterning (relative patch size, relative patch duration, relative patch isolation, and grain response).They generalize the concept of ecological neighborhoods to represent regions of activity or influence during periods of time appropriate to particular ecological processes. Therefore, there is no single ecological neighborhood for any given organism, but rather a number of neighborhoods, each related to different processes.
An update paper of Shelley Alexander's dissertation work in Banff. Basically the authors state that the Trans-Canada Highway has posed a barrier to wildlife movement and the passages for wildlife are not sufficient, even in the next planned section of road construction and passages. Through snow tracking over multiple years, the authors observed normal wildlife movement was characterized by multiple crossings over short distances. The limited crossing opportunities provided by existing mitigation on the Trans-Canada Highway (TCH) do not facilitate this kind of movement. They also examine two decision support systems for assessing crossing structure effectiveness and find both to be highly suitable for complex resources allocation decisions. They conclude that the mitigation approach employed at Banff National Park fails to approximate natural movement and does not accommodate wildlife communities. They also conclude that the next phase of highway construction (Phase IIIA) functions selectively for a narrow set of highly tolerant species and at present has exacerbated the barrier effect for sensitive species, such as lynx and wolves. Alexander and Waters state an effective strategy will require crossing structures with greater spatial extent and placed at shorter intervals. They suggest the best strategy is to bury or elevate large stretches of highway.
The authors record the results of a study begun in 1991 to see if threatened desert tortoises could be kept off a state highway in the Mojave Desert in California by erecting barrier fences, and funneling tortoises to existing culverts, Other studies suggest that desert tortoise populations are depleted within at least 0.8 km of highway edges, and may be affected as far away as 3.5 km from the highways. Boarman et al. give specifics on highway fencing, such as the height (need to consider size of animals to be excluded), depth (bury fencing according to the ability of target animal and other animals ability to dig under), opacity (leave fencing open so animals can see through so they are motivated to keep trying to get around the fence barrier and thus have a greater chance of finding the culverts), and durability and maintenance (fences have to withstand humans, vehicles, animals such as livestock, the presence of flowing water or alkalinity of the soil). Caltrans erected 24 km of fence that is 6 strands of 10 gauge galvanized steel wire used as support and 60 cm high, 1.3 cm mesh hardware cloth of galvanized steel, which is buried to a depth of 15 cm beneath ground level and extends 45 cm above the ground (figures provided in article). There are 3 strands of wire (non-barbed) at the bottom to allow medium sized animals to climb under/over, and the top 3 strands are barbed to keep humans and livestock out/off of fence. The fence is supported by 2 m metal posts spaced approximately 3 m apart and tied in with existing culverts. Tortoises have been following the fence for years, and crossing under the highway, as have kit foxes, coyotes, jackrabbits, and snakes, lizards, and rodents. An annual survey of road kill tortoises found that road kill decreased in fenced vs. unfenced areas.
Authors' abstract: This report contains a summary of ongoing work on the effects of noise on wildlife populations. There is a paucity of information on the response of invertebrates to noise, particularly the levels likely to be encountered along roads. Significant populations of some species are found along rights-of-way and appear to be unaffected by roads. Other species, e.g., some aquatic forms may be adversely affected but the mechanism is unclear. Existing albeit incomplete information suggests that fish are unlikely to be adversely affected by noise levels from road. Reptiles and amphibians show some barrier effect due to roads, but there is no clear evidence of a noise effect alone. Recent work has suggested that behavior in burrowing toads may be affected by noise and this requires further study for a definitive answer. Birds have received the most study and in some cases are negatively affected both in numbers and in breeding success by proximity to roads. In other cases the effect is the opposite and there are reports of many species using roadside habitat in some areas. Large mammals may be repelled by noise, although in most cases the effect appears to be slight to moderate. Small mammals do not appear to be adversely affected by road noise; Several species occur in significant numbers in rights-of-way. There appears to be a physical barrier effect of roads for many mammals. Recommendations for future study are included.
To compare animal movement in response to 3 contexts (the Trans-Canada Highway (TCH), natural barriers, and continuous habitat), three species of murid rodents were trans-located and their paths monitored. The modest effect of roads on small mammal movement suggests that the TCH acts as a filter rather than an absolute barrier. An experimental study was conducted where 3 different species of murid rodent were taken from their home ranges and trans-located short distances away through three different areas: 1 across the Trans Canada Highway, one area was in the natural forest median of the highway, and the third treatment was in natural vegetation on the same side of the highway where the animals were live-trapped. The three species, red-backed voles, meadow voles and deer mice exhibited different abilities to find their way back to their home ranges across the three treatments, but overall, individuals were 20% less successful crossing the TCH than natural forested barriers, and 10% less successful crossing natural barriers than continuous habitat. There were some marked differences among species. A total of 85 animals were moved to the different locations. The type of vegetation and habitat influenced the animals' ability to return to its home ranges. In general, deer mice returned to their home ranges more often, perhaps because they are generalists in their habitat preferences and are nocturnal. Red-backed voles (a forest vole) had the highest return success in the continuous forest treatment, and meadow voles the lowest. Meadow voles live in grassy meadows and returned to these areas with the highest return success. Meadow voles and red-backed voles were more successful returning in the continuous treatments (forest and grassy field) than across artificial barriers of the highway and median (44% and 31% more likely for meadow voles and red-backed voles respectively). The authors conclude that the artificial road barrier is somewhat less permeable to movement than either continuous habitat or habitat ecotones.
Traffic noise affects birds. Rheindt monitored forest dependent songbirds 100 meters and 950 meters from highway that had a traffic volume of at least 50,000 vehicles per day and saw a significant difference, with major drops in most species as distance from the road decreased from 950 meters to 100 meters from the road. He found that the species with the lowest sound frequencies (those closest to highway noise frequencies of 0-5kHz) tended to be found from the road. Birds with higher pitched song frequencies were less susceptible to traffic noise pollution and were found in greater densities near the road (taking into account habitat generalists, which were excluded from survey and analysis). Acoustic masking is one of the mechanisms by which traffic noise negatively affects passerine densities along roads.
This paper presents an overall synthesis of the effects of forest roads on elk. Although these are not typically paved and high traffic roads, the information is important for the management of elk and ecosystems as well, because elk are sensitive to human use of areas. The results may help explain why some passages do not work for elk, because of the human activity near roads. Direct impacts of roads, in addition to elk/vehicle collisions include: a) elk avoid areas near open roads; b) elk vulnerability to both legal and illegal mortality from hunter harvest increases as road density increases; and c) in areas of higher road density, elk exhibit higher levels of stress and increased movement rates. The authors reviewed many studies, including a Montana study by Hillis et al, 1991, that specified that elk security areas should be located more than 0.5 miles (0.8 km) from roads. Rowland et al. gave an important suggestion for research, namely to look at the animals' locations in relation to distance from roads rather than looking at the road density and elk use of the area. They analyzed this methodology and found a strong linear increase in selection ratios of elk as distance to roads increased. The methodology is a distance-band model. For this model, elk locations are assigned to 100 m wide bands away from roads. The authors repeatedly talk of road closures, and of true road closures where there are no ATV's and other illegal use of closed roads. They state the benefits of road closures include (but are not limited to): decreased energy expenditure by elk as a result of less frequent disturbance by motorized vehicles; increases in total amount of effective habitat for elk in areas affected by closures; decreased damage to crops and haystacks from elk on private lands, due to decreased disturbance from traffic on public land; improvements in diet quality; and decreased vulnerability of elk during hunting seasons due to fewer hunters willing to hunt without a vehicle or able to access the area.
—View this literature online.
This paper presents a regional-scale evaluation of landscape permeability for large carnivores in Washington and adjacent portions of British Columbia and Idaho. The authors developed a GIS-based landscape permeability model for wolves, lynx, wolverine, and grizzly bear. The model evaluated land cover type, road density, human population density, elevation, and slope. Singleton et al. identified portions of the Washington state highway system that passed through habitat linkages between the habitat concentration areas and areas accessible to the focal species. They used GIS weighted-distance and least-cost corridor analysis techniques. These techniques are based on the idea that each cell in a map can be attributed with a relative 'cost' or 'weighted distance' associated with moving across that cell. This analysis provides a consistent measure of estimated landscape permeability across the analysis area, which can be used to develop conservation strategies, contribute to future field survey efforts, and help identify management priorities for focal species. Found at: www.fs.fed.us/pnw/pubs/rp549/
From 2002 to 2004, these researchers looked at elk and mule deer reactions to recreationists on the Starkey research site in northeastern Oregon. They documented the cause-effect relations of All Terrain Vehicles (ATV's), people on horseback, mountain bikers, and hikers activities on deer and elk, using these off road activities as experimental treatments and periods of no human activity as experimental controls; and they used the response variables of deer and elk to estimate energetic and nutritional costs associated with each activity and the resultant effects on deer and elk survival. They state that ATV use on public lands has increased seven fold (700%) during the past 20 years (1985-2004) (U.S. Department of Agriculture Forest Service 2004). They used an automated tracking system (ATS), a Global Positioning System (GPS) -based method of tracking radio-collard/GPS collared animals. This technology was not fully explained. The tracking system can generate up to one animal location every 20 seconds, 24 hours per day, from April to December each year. The authors established a network of road transects and used teams of participants (human) who either hiked, rode mountain bikes, road horses, or ATV's down these road transects each morning and each afternoon for a 5 day treatment, followed by a 9 day control period. They did not use visual observations of animal reactions due to their high degree of inaccuracy, but rather looked at the locations of radio-collared deer (12) and elk (12) in the area and tracked their movement rates over one hour periods, both for control and treatment periods. Movement rates of elk were substantially higher during periods of all four off-road activities as compared to periods of no human activity. Elk movement rates were so tied to human movement disturbance, that when human participants took their lunch break at noon, movement rates for elk dipped to their lowest level during daylight hours. Elk movement rates were highest during ATV riding, second-highest during mountain bike riding, and lowest during hiking and horseback riding. Peak movement rates of elk were highest for ATV=21 yards/minute (19 m/minute) followed by mountain bike riding =17 yards/minute (16 m/minute), horse back riding & hiking = both about 15 yards/minute (14 m/minute). During control periods when there were no humans, peak movement rates did not exceed 9 yards/minute (8m/minute). Even when people had left the area, the animals were still on alert. Movement rates of elk at or near sunrise and sunset were higher during the 5-day treatments of mountain bike and ATV activity. When humans were nearby, the maximum probability of flight by an elk was approximately 0.65 during ATV, mountain bike, and hiking activity, and 0.55 during horseback riding. Probability of flight response declined most rapidly during hiking, with little effect when hikers were beyond 500 meters. By contrast, higher probabilities of elk flight continued beyond 750 m for horseback riders, and 1,500 m from mountain bike riders and ATV riders. Deer, in contrast, showed less change in movement rates during the four off-road activities compared to the control period. During the period of the day from 8:00 am to 15:00 (3:00 pm) when off road activities occurred, movement rates for deer during ATV riding were similar to rates during control periods. By contrast, daytime movement rates of deer were higher than control periods during mountain bike riding, horseback riding and hiking activities, especially in the morning. This led the authors to believe that the deer were not exhibiting the same tendency for flight as shown by elk in relation to off road activities. They believed the deer may have hid in heavy cover rather than leave the area of human activity. The authors suggest that when the USDA Forest Service plan to accommodate off-road recreational demands while mitigating the negative effects on species like elk, consider two related concepts: 1) off road use rates and 2) off road recreational equivalents. They define off road use rates as the number of passes per unit of time on a given linear route (primitive road or trail that they referred to as transect) traveled by an off road activity. Their results show that one pass per day by any of the four off-road activities causes increased movement rates and flight responses by elk. They go on to make more management recommendations. Although these data are based on areas that are not roads that are paved, they show just how important the activities on our public lands are affecting wildlife. These off road activities serve to stress wildlife and cause them to leave areas, thereby making them more vulnerable to possible road collisions, or nutritional deficits due to loss of foraging opportunities and increased flight responses. We add this paper to help managers evaluate the different influences on wildlife in the face of the roaded landscape.
—View this literature online.
1.2.2 Literature on Animal-Vehicle Collisions and Their Ecological and Societal Costs
Wildlife-vehicle collisions are the most significant part of the overall animal-vehicle collision problem. It is estimated that there are 1.5 million wildlife-vehicle collisions and an average of 200 human deaths from those collisions annually in the United States. The following articles and website further detail this problem and the potential alternatives.
Click on a title to view annotated notes
The magnitude and trend of the deer-vehicle crash (DVC) problem in the United States can only be grossly estimated. Data that could be used to more closely define this problem are not consistently collected. However, at least two "national" surveys have attempted to estimate the number of DVCs in the United States and their results are presented. The number of fatalities and estimated non-fatal injuries in the United States due to animal-vehicle collisions are also included. The inability to properly define the DVC problem in the United States is primarily related to the misunderstandings produced by the collection, estimation, and combination of several data sets (with varying characteristics) that can be used to describe it. DVC-related data are also collected and/or estimated by multiple governmental agencies within most states. A regional Deer-Vehicle Crash Information Clearinghouse (DVCIC) was started in 2001. During the last four years the DVCIC staff have completed a DVC data collection and management survey, and also started to collect (if available) 10 years of reported DVC, deer carcass, and deer population for a five-state region (Illinois, Iowa, Michigan, Minnesota, and Wisconsin). The survey was completed to document, compare, and/or combine the state-level DVC data collected. Representatives from the Departments of Transportation and Natural Resources were surveyed. The defining criteria, weaknesses, and strengths of their databases are discussed in this paper. Trend analyses and evaluations of the DVC data collected are ongoing and preliminary results presented. Preliminary summary data for each of the five states and the region during the last 10 years will be described. Recommendations are provided about how the DVC or animal-vehicle collision problem might be better defined in the United States. In addition, preliminary regional data trends presented and discussed. They are believed to be representative of the trends occurring throughout the United States.
—View this literature online.
The report is an extensive review of deer-vehicle crash (DVC) countermeasure. Research and/or documents related to 16 different countermeasures were reviewed and are summarized. The looked at deer whistles, roadway lighting, speed limit reduction, deicing salt alternatives, deer-flagging models, intercept feeding, deer crossings signs and technologies, roadside reflectors and mirrors, repellents, hunting and herd reduction, public information and education, roadside vegetation management, exclusionary fencing, roadway maintenance design and planning policies, and wildlife crossings. Only studies of properly installed/maintained exclusionary fencing and wildlife crossing installations have consistently shown deer-vehicle collision reductions. The deer-vehicle collision reduction capabilities of the other 14 counter measures appear to still be in question. Results can also be found in the toolbox available at deercrash.com.
—View this literature online.
They sent out a survey to all state Departments of Transportation to see how and if animal-vehicle collision data is collected, what the estimated numbers of wildlife killed each year are per state, the mitigation measures within the state, and other related questions. Forty-three agencies responded. Questions sent September 1992. They made a conservative estimate of a minimum of 500,000 a-v-c's for 1991. They showed a trend for deer road kill increases from 1982 to 1991 in 26 of 29 states that had suitable trend data. The states with the greatest numbers of deer killed along roadways were Pennsylvania (high of 43,000 in 1990), and Wisconsin (a high of 76,000 in 1989 - 1990). Wildlife passages in the form of under and overpasses were reported in 8 states: CA, CO, ID, MN, NJ, NY, UT, WY. They found there were 14 published scientific studies describing ecological relationships associated with deer-highway mortality. These studies all occurred in CA or MI or PA, or WY.
1.2.3 Determining Ecologically Important Areas Within or Near the Plan /Project Area
Considering ecological resources in the planning stages of transportation projects involves identifying data sources, information inputs from local ecological professionals, and possibly conducting field research on target species. Ecological considerations are best incorporated during the initial stages of long range planning (20 to 30 years prior to projects) because ecological resources may be heavily impacted by potential transportation projects. Late consideration may heavily impact permitting schedules, mitigation costs, and time constraints associated with project progress. If the scoping process determines that a potential project will proceed through the planning process, then the initial step in planning for wildlife needs would entail accessing several data resources. For an initial "Fast Track" approach, accessing databases such as the following will be most helpful in finding critical information:
- State Wildlife Action Plan, see below for description
- Provincial Conservation Data Centres (PDF, page5)
- State Natural Heritage Database
- State/Provincial Natural Resource Agency
- U.S. Fish and Wildlife Service National Wetlands Inventory
- USGS Regional Bird Conservation Tool for maps of Federal and Tribal lands, land cover types, and breeding bird survey routes
- USGS National Map Viewer
- USGS Landcover Database for all of North America: Federal Lands, Amphibian Research and Monitoring Initiative (ARMI), Landcover, GAP analysis resources, Water resources such as aquifers, rivers, topographic maps, and many more data layers and links
- Federal and state/provincial requirements for transportation projects such as requirements of the National Environmental Protection Act (NEPA), the Endangered Species Act (ESA), and the Canadian Fish Protection Act. See: Guide to Transportation and Wildlife Law
- Connectivity analyses conducted in that state/province or region (See step 1.2.6 Investigate If Landscape Linkages Have Been Identified in The Area for further information)
- Other regional natural resource databases
In some states and provinces, internet portals have been developed as GIS planning tools for these analyses, such as Florida's ETDM
- There are also federal, state, provincial, and regional resources that record places where existing road-related culverts and bridges impede the movement of aquatic species along rivers and lakes. Correction of these problems may be required as part of the transportation project construction activities or as part of maintenance activities. An example of this type of resources is California's CalFish website. The US Fish and Wildlife Service Fish Passage Decision Support System helps to identify existing barriers to fish movement across the United States
Wildlife Action Plans
Each state has a State Wildlife Action Plan, which identifies the species at risk and threats to wildlife within the state. While these plans are uneven in treatment of the issues, each plan is required to have certain elements that can be useful in transportation planning. For an excellent treatment of the purpose of these plans, and information on each of the state's plans, see the Teaming With Wildlife website.
Numerous other resources exist to identify the wildlife and fish communities in the project area. Each state's resource agencies will have different Geographic Information Systems (GIS) data sources, maps, aerial photos, etc. It will be necessary to work with resource professionals locally to determine the communities affected.
At this point in the process it is desirable to have a general idea of the affected species so that all involved agencies understand the situation. Specific species affected will be identified in the next step.
Additional Related Links
1.2.4 Determine Species Potentially Affected by Plan/Project
- 126.96.36.199 Fast Track Checklist for Determining Potentially Affected Species
- 188.8.131.52 Continue a More In-Depth Process
- 184.108.40.206 Further Identify Species at Risk of Transportation Project Impacts
- 220.127.116.11 Determine Types of Species at Risk and Potential for Wildlife Crossing Structures
- 18.104.22.168 Conduct Field Site Visits
- 22.214.171.124 Establish a Wildlife Monitoring Study
- 126.96.36.199 Assess Traffic Volume Effects on Wildlife
- 188.8.131.52 Incorporate Local Stakeholder Knowledge
- 184.108.40.206 Combine Data and Knowledge for a Final Evaluation
- 220.127.116.11 Pertinent Internet Sites
- 18.104.22.168 Literature
Incorporating wildlife concerns in the early stages of the planning process is critical to successful mitigation and was the number one priority in our North American survey of transportation and wildlife priorities.
Once information on transportation plans has been gathered, the work outlined below can help determine the species and other environmental effects that need consideration. The expert opinion of local biologists/ecologists is crucial in this process and incorporating local professionals into the entire transportation planning, design, construction, and maintenance process helps to insure the success of the mitigation. If any of the following investigations indicate that wildlife needs to move across the transportation corridor, the consideration process continues to the more "In Depth" approach.
- Determine if protected areas are involved (federal, state, provincial, local, native tribes, private, or a conservation easement). Check with USGS Landcover Database for all of North America Federal Lands, Amphibian Research and Monitoring Initiative (ARMI), Landcover, GAP analysis resources, water resources such as aquifers, rivers, topographic maps, and many more data layers and links. Check individual state and provincial resources for protected area information.
- Determine the presence or potential presence of state/provincial or federally listed endangered and threatened species, or species that are sensitive or of special concern. At the NatureServe website for Natural Heritage Programs for each state and Canadian province, you can find species lists and interactive maps of species distributions
- Review State Wildlife Action Plans which provide information on the most critical and some of the most common but important species in a state
- Assess for the presence of wetlands with reptile, amphibian, mammal, bird, or aquatic species' populations that need to move across the landscape and would be affected by a road or railway across their home ranges. For a start, check the U.S. Fish and Wildlife Service National Wetlands Inventory
- Check state/provincial wildlife agency for fish and aquatic organism situations; e.g., Oregon Fish & Wildlife Department Guidelines and Criteria for Stream-Road Crossings and the Maine DOT Fish Passage Policy and Design Guide
- Check regulatory requirements of state/province in terms of transportation planning. Example includes the Ontario Environmental Protection Requirements for Transportation Planning and Highway Design, Construction, Operation and Maintenance
- Evaluate project for existing fish barriers. The US Fish and Wildlife Service Fish Passage Decision Support System helps to identify existing barriers to fish movement across the United States
- Identify the presence of wildlife movement corridors or landscape linkages that may be bisected or near enough to be influenced by the transportation project. Check potential resources in Step 1.2.6, Investigating Landscape Linkages
- Contact local wildlife professionals for information on the presence of herds of ungulates (e.g., deer, elk, moose) or populations of nearby larger carnivores and/or their movement pathways
- Contact local state and federal wildlife professionals and local citizens and conservation groups to determine if local species that are also involved in wildlife-vehicle collisions have declined
- Examine current infrastructure for the lack of existing permeable connections for common wildlife to move under the transportation corridor, e.g., lack of existing culverts and bridges
- Locate research studies that may provide genetic and other scientific evidence that local wildlife populations are becoming isolated from one another in the presence of the roadway. See below for examples of literature
- Consult with wildlife professionals and land managers about the need for wildlife to move from one side of the roadway to another because of potential large scale changes in their current home ranges, such as flooding, fire, timber and mining activities, and large scale human development
If the situation warrants more information, there are several additional actions that can be taken. They include:
- Further identify species at risk of transportation impacts
- Conduct field site visits
- Establish a wildlife monitoring study
- Incorporate local stakeholder knowledge in this stage of evaluation
- Determine species at risk and potential for wildlife crossing
- Assess traffic volume effects on wildlife
Identify any terrestrial or aquatic species with policy or legal status known to occur in the project area, or that may have project impacts due to life history attributes such as long dispersal distances. Include species listed under the Endangered Species Act, globally insecure species, state listed species, or federal land management agency emphasis species (such as Forest Service sensitive species protected by agency policy).
Species with policy or legal status will take precedence over species without such protection.
Impacts to species are not limited to the highway corridor. Wide-ranging species or those that disperse long distances may be greatly affected by highway projects or existing highway conditions. Many if not most projects will require consultation under Section 7 of the Endangered Species Act, and some states have special transportation liaisons with the US Fish and Wildlife Service. These liaisons are a great resource in identifying species outside the project area boundaries that may be affected by the project.
The terrestrial and aquatic species that are not federally or state protected could also be at risk from road effects. These species can be identified in part by referring to the species types at risk in Step 22.214.171.124 below. Also refer to Foreman et al's Road Ecology (2003) for a list of species groups at risk. These species are vulnerable often because they do not have as much protection (and therefore human notice) as species with legal status. At least one objective of identifying these species is to ensure that the project will not cause greater harm than a given species can tolerate and still maintain viability. Some formerly common species can be greatly affected by highways, with greatly reduced populations. Examples include formally locally abundant salamander, frog, and turtle populations that are severely reduced or eliminated near road corridors.
Roads and railways cause several types of effects on wildlife, but the most pervasive of these are direct mortality from vehicle collisions and the barrier effect caused by intimidating and dangerous amount of vehicle traffic. The barrier effect of roads includes the loss of habitat connectivity or permeability of the landscape. Other impacts include pollution from exhaust fumes, oil and deicing agents, noise, loss of habitat from the footprint of the highway, and the disturbance during highway construction and operations. More information on impacts from highways can be found in Forman et al. (2003, see below for full citation).
Although roads cause effects other than mortality and loss of permeability, all species will tend to show these two effects if they are impacted by other less direct effects. Therefore, in this section we analyze types of species at risk in terms of mortality from collisions, including safety issues to humans, and barrier impacts. It is important to note that if mortality is an issue to a group of species, then the highway will most probably become a barrier as traffic volume increases (Mueller and Berthoud 1994, Van Langevelde and Jaarsma 2000).
Table 126.96.36.199 is intended to assist in identifying the species in a project area potentially at risk from road / railway effects, and to determine if wildlife crossing structures (WCS) would be an appropriate mitigation measure based on the type of risk (mortality, barrier, or safety).
|Species Group at Risk *||Affected by Traffic Volume (TV) or Habitat Issues (H)?||Type of Risk? Mortality (M),
|Are WCS Appropriate Mitigation?||Example Species|
|Slow, meandering, stopping||TV||M, B, S||Yes||Butterflies, reptiles, amphibians, rabbits, badgers, skunks|
|Immobilizing in response to danger||TV||M,B||Yes||Armadillos, opossum, snakes, turtles|
|Highly mobile||TV||M, B, S||Yes||Ungulates, carnivores, birds|
|Wide-ranging||TV, H||M, B, S||Yes||Ungulates, carnivores, birds|
|Low mobility||TV, H||B||If appropriate habitat is included in design||Mollusks, invertebrates, birds with limited flight capability|
|Needing seasonal/daily complementary habitat||TV, H||M, B, S||Yes||Ungulates, quail, frogs, turtles, birds|
|Attracted to clear zone or road surface||TV, H||M, B, S||Maybe (fences)||Snakes, deer, raptors, scavengers, bats, waterfowl, pheasants, amphibians, reptiles|
|Species with small, isolated habitats||H||B||Probably not||Local populations of reptiles, amphibians, low mobility species like mollusks, butterflies|
|Forest interior specialists||H||B||No||Tanagers, thrushes, winter wren|
|Species requiring dense cover||H||B||Maybe||Small mammals, snakes|
|Wary of humans or noise||TV||B||No||Grizzly bears, raptors|
|Sensitive to lights||TV||B||No||Godwits, nesting sea turtles|
|Low reproductive potential||TV||M, B||Yes||Turtles, large carnivores|
|Low density or population size||TV||M, B||Yes||Threatened & Endangered species, large carnivores|
|Sensitive to road surface or edge||H||B||Maybe||Frogs, toads, small mammals|
|Sensitive to roadside pollutants||H||M, B||No||Frogs, toads|
* References: Jackson 1999, Van Langevelde and Jaarsma 2000, Forman et al. 2003, Rich and Longcore 2005 see below for full citations.
There is no substitute for getting on the ground in an area and assessing the situation for topography, land cover, land use, riparian (stream) areas, land ownership, road geometrics, and how wildlife may be using the area. We recommend a multi-disciplinary team site visit.
The results of these analyses provide a range of options for proceeding. If there is an interest in learning more about the species that may be affected by the transportation project, it is prudent to conduct a study of the species and the area. These studies could help determine how and where species need to move, how stable their populations are, and if they are likely to be seriously affected by the proposed transportation project, even with mitigation. Directed studies would help ensure potential mitigation measures are scientifically based and may provide data for future projects. Collected data can then be used to help determine the next course of action. These include decisions about the proposed location of roadbed and predicted traffic flows. For example, if the road is predicted to have low traffic flows (average daily traffic measured in the hundreds), there may be sufficient opportunity for some species to cross the roadway unimpeded, thus minimizing the need for mitigation for these specific species. This may not be the situation, however, for all species in the area. This step necessitates working with local wildlife and highway engineering professionals.
Traffic volume is one of the good predictors of road-railway impacts to wildlife. Traffic volume affects species differently. As traffic volume increases, small and slow animals are increasingly affected by mortality, whereas larger animals may be more affected by loss of permeability. Predicting these effects is highly dependent on the species and the situation. Waller and Servheen (2005) found grizzly bear were so sensitive to traffic volume that they restricted the majority of their road crossings to night time when there were only an average of 10 vehicles per hour (which would equate to 240 vehicles per day). For the majority of large and medium-sized mammals, it is when average daily traffic volume is measured in the thousands that we begin to see major effects on populations, from mortality to almost complete avoidance of the road area. For example, Ng et al. (2005) found an inverse relationship between traffic volume and wildlife-vehicle mortality. They analyzed traffic volume on freeways in Los Angeles, California and found that a road with monthly traffic volumes of 50,000 to 100,000 vehicles (1,666 to 3,333 vehicles per day) had higher road mortalities for large and medium-sized mammals than freeways with volumes ranging from 100,000 to 200,000 vehicles per month (3,333 to 6,666 vehicles per day). The authors surmised the higher volume highways posed such impenetrable barriers to wildlife that few attempted to cross them, while the lower volume road appeared to be less hazardous to the large and medium-sized animals that attempted to cross it. This example suggests a threshold for traffic volume, above which the roadway becomes much more dangerous for wildlife.
It is prudent to assess the effects of traffic volume effects on local wildlife populations. One can begin by determining how average annual daily traffic volume (and future projections) may impact the wildlife in the area. Below we present how to determine the traffic volumes, and we list literature pertaining to studies of how traffic volume has been shown to affect wildlife. We do not give specific recommendations for thresholds of traffic volume and their effects of specific species because the relationships of volume to effects tend to site and species specific.
Generally, traffic volume effects are as follows:
- Roads with average daily volume measured in the hundreds of vehicles most greatly affect slow moving wildlife such as invertebrates, amphibians, and reptiles, and highly wary species such as grizzly bears. Other species may not find this volume a barrier, especially at night, or on specific days or seasons.
- Road with average daily volumes from 1,000 to 3,000 vehicles tend to affect most wildlife species attempting to cross and pose a barrier to movement attempts by some.
- Roads with average daily volume > 3,000 vehicles have been shown to be a barrier to some species, and cause high mortality to animals that attempt to cross the road. At some traffic level, the road becomes completely impenetrable. See references below for more formal treatments of this subject.
To address the traffic volume issue, one can determine the AADT and Functional Class of the highway(s) within the project area. Average Annual Daily Traffic (AADT), or traffic volume, is a basic metric used for many purposes by transportation departments. Traffic volume data is regularly collected and maintained at the national and state levels. It is available for larger volume roads through the national Highway Performance Monitoring System (HPMS). State Departments of Transportation and provincial Ministries of Transportation also collect traffic volume data for additional highways. It is possible to collect traffic volume data if none is available for the project in question.
The Functional Class of a highway is a shorthand way to determine the likelihood of its level of impacts to wildlife because highways are categorized according to the class of service they are intended to provide. The three major classes are arterial, collector and local. More information can be found on the Federal Highways Functional Classes website.
Once it is determined whether or not there are existing effects based on the AADT, it is useful to determine the projections of traffic volume trends and the amount of time expected to meet those projections. Many if not most highways are increasing in traffic volume but the rate over the entire U.S. is not constant. Knowledge of how many years before a critical traffic volume threshold is reached for the species of concern in a project area will help planners to know whether to include mitigation in the current project for conditions projected to occur in the near future.
Local stakeholders can be a valuable source of information on wildlife in the project area, and they are often very interested in the outcome of a planning effort. Aside from the basic responsibility of public agencies to incorporate the public in planning projects affecting them, local stakeholders can assist in garnering public or political support for mitigation.
The Interstate 90 Wildlife Bridges Coalition was a powerful force in marshalling public support and awareness for wildlife crossing structures on the Snoqualmie Pass expansion project in Washington State. Their mission was to advocate for high quality wildlife passages along the Interstate 90 Expansion. Their efforts in cooperation with the transportation and natural resource agencies can be found at the I-90 Wildlife Bridges Coalition website.
A stewardship team process can be used to incorporate local knowledge and passion. An example is the Sierraville (CA) Highway 89 Stewardship Team, which has been able to obtain one wildlife crossing underpass and is working on a long-term process to install several more. Click here to view the article (A GIS-Based Identification of Potentially Significant Wildlife Habitats Associated With Roads in Vermont (PDF, page 198).
With the assistance of the above guidelines, users of this decision guide can establish a general understanding of the wildlife and road issues in the area of concern and the potentials for mitigating the situation. The actions described here also help the user to build a contact list of people able to help evaluate wildlife movement, support a mitigation project, and who could be drawn upon for assistance during different development stages of a proposed project. Once at this point, the user(s) need to decide to proceed with mitigation ideas or if mitigation would not be appropriate. This is not a one-person decision. Wildlife professionals in state, as well as highway engineers and federal agencies are part of this decision as well. The steps we outline suggest an effective process to follow.
Forman, R. T., D. Sperling, J. A. Bissonette, A. P. Clevenger, C. D. Cutshall, V. H. Dale, L. Fahrig, R. France, C. R. Goldman, K. Heanue, J. A. Jones, F. J. Swanson, T. Turrentine, T. C. Winter. 2003. Road Ecology: Science and Solutions. Island Press, Washington, D.C., USA.
Ng, S. J., R. M. Sauvajot, S. P. D. Riley, and J. W. Dole. 2005. Inverse relationship between wildlife vehicle mortality and traffic volume. In preparation.
Rich and Longcore 2005
Van Langevelde, F. and C.F. Jaarsma. 2004. Using traffic flow theory to model traffic mortality in mammals. Landscape Ecology 19:895-907.
Waller, J. S. and C. Servheen. 2005. Effects of transportation infrastructures on grizzly bears in northwestern Montana. Journal of Wildlife Management 69:985-1000.
Traffic Volume Literature
Alexander, S.M., N.M. Waters, and P.C. Paquet. 2005. Traffic volume and highway permeability for a mammalian community in the Canadian Rocky Mountains. The Canadian Geographer 49:321-331.
Bautista, L.M, J.T. Garcia, R. G. Calmaestra, C. Palacin, C.A. Martin, M.B. Morales, R. Bonal and J. Vinuela. 2004. Effect of weekend road traffic on the use of space by raptors. Conservation Biology. 18:726-733.
Clevenger, A. P., B. Chruszcz, and K. Gunson. 2001. Drainage culverts as habitat linkages and factors affecting passage by mammals. Journal of Applied Ecology 38:1340-1349.
Jaeger, J., J. Bowman, J. Brennan, L. Fahrig, D. Bert, J. Bouchard, N. Charbonneau, K. Frank, B. Gruber, and K. Tluk,von Toschanowitz. 2005. Predicting when animal populations are at risk from roads: an interactive model of road avoidance behavior. Ecological Modeling 185:329-348.
Langevelde, F. and C. F. Jaarsma. 2004. Using traffic flow theory to model traffic mortality in mammals. Landscape Ecology. 19: 895-907.
Ng, S. J., R. M. Sauvajot, S. P. D. Riley, and J. W. Dole. 2005. Inverse relationship between wildlife vehicle mortality and traffic volume. In preparation.
Waller, J. S. and C. Servheen. 2005. Effects of transportation infrastructures on grizzly bears in northwestern Montana. Journal of Wildlife Management 69:985-1000.
Van Langevelde, F. and C.F. Jaarsma. 2004. Using traffic flow theory to model traffic mortality in mammals. Landscape Ecology 19:895-907.
Bhattacharya, M., R. B. Primack, and J. Gerwein. 2003. Are roads and railroads barriers to bumblebee movement in a temperate suburban conservation area? Biological Conservation 109:37-45.
Epps, C. W., P. J. Palsboll, J. D. Wehausen, G. K. Roderick, R. R. Ramey III, and D. R. McCullough. 2005. Highways block gene flow and cause rapid decline in genetic diversity of desert bighorn sheep. Ecology Letters 8:1029-1038.
Gerlach, G. and K. Musolf. 2000. Fragmentation of landscape as a cause for genetic subdivision in bank voles. Conservation Biology 14:1066-1074.
Mills, S. L. and R. Y. Conrey. 2003. Highways as potential barriers to movement and genetic exchange in small mammals. Final Report to Montana Department of Transportation. University of Montana, School of Forestry.
Proctor, M.F., McLellan, B.N., and C. Strobeck. 2002. Population fragmentation of grizzly bears in southeastern British Columbia, Canada. Ursus 13:153-160.
Reh, W., and A. Seitz. 1990. The influence of land use on the genetic structure of populations of the common frog (Rana temporaria). Biological Conservation 54:239-249.
Riley, S. P. D., J. Pollinger, R. M. Sauvajot, E. C. York, C. Bromley, T. K. Fuller, and R. K. Wayne. 2006. Southern California freeway is a physical and social barrier to gene flow in carnivores. Molecular Ecology 15:1733-1741.
1.2.5. Determine If There Are Any Animal-Vehicle Collisions Safety Concerns in the Plan/Project
- 188.8.131.52 GIS Mapping and Analyses
- 184.108.40.206 Database spreadsheet Analyses
- 220.127.116.11 Cluster Analyses
- 18.104.22.168 Discussions with Local Agency Personnel
- 22.214.171.124 Use of Safety Performance Functions
- 126.96.36.199 Website Resources
In some situations, there is a need for safety purposes to identify areas of higher than average wildlife-vehicle collisions. This can be done through analysis of available data for specific segments of existing roadway or a road with similar characteristics to a proposed road. While we emphasize the term wildlife-vehicle collision data, the common recording of such information is classified as animal-vehicle collisions, which may also include livestock collisions. If animal-vehicle collision data or road associated carcass data is available, several analyses can be conducted including:
- GIS Mapping and Analyses
- Database Spreadsheet Analyses
- Cluster Analyses
- Discussions with Local Agency Personnel
- Use of Safety Performance Functions.
Wildlife-vehicle collision and wildlife carcass data can be mapped separately or in combination in a GIS to determine hotspots of collisions. Accurately mapping such data is dependent on the methods used to record collision locations. If Global Positioning Systems (GPS) units are not used for site locations then they are sometimes noted to the nearest intersection or mile/kilometer post. If this is the case, then the resulting map would yield more generalized information in an area of potential conflict zones, rather than precise locations. In our NCHRP 25-27 research the magnitude and patterns of location-based wildlife-vehicle collision reports and deer carcass removal datasets from Iowa were compared qualitatively through visual GIS plots and quantitatively (e.g., frequency per mile) (See Section 3.1 in our report: Evaluation of the Use and Effectiveness of Wildlife Crossings). Police-reported wildlife-vehicle collision information, deer carcass removals, and deer salvage data were evaluated. Results showed that the number of deer carcasses removed by was approximately 1.09 times greater than the number of wildlife-vehicle collision reported to the police. The number of salvaged and un-salvaged deer carcasses, on the other hand, was approximately 1.66 times greater. Clearly, the choice of the data used impacts whether a particular roadway segment might be identified for closer consideration. The message here is that the choice of the database used to define and evaluate the wildlife-vehicle collision problem and its potential countermeasures should be considered carefully. Recommendations are provided in the NCHRP final report about how the databases might be used appropriately and how the data should be collected
If the collision or carcass data was not collected with a Global Positioning System (GPS) unit and therefore not fully geo-referenced for a straight forward GIS analysis, then a database spreadsheet analysis could be applied. Data sources for such analyses include: the Highway Safety Information System (HSIS) database for animal-vehicle collisions for certain states, state and provincial DOTs/MoTs' websites of collision data, or data available within DOT/MoTs' safety divisions. Spreadsheet analysis would entail classing specific road ways into segments (typically one-mile segments) to analyze animal-vehicle-collision or carcass data such as Kassar (2005) did for Utah. Collision hotspots could then be identified. In Utah, Page (2006) and the Utah DOT determined a stretch of road was a wildlife-vehicle hotspot if there were an average of five or more wildlife-vehicle collisions per mile (1.61 kilometers) annually. These analyses could help to determine and prioritize general areas of necessary mitigative actions.
Studies of wildlife-vehicle collisions have demonstrated that they are not random occurrences but are spatially clustered. Modeling or analytical techniques permit a more detailed assessment of where wildlife-vehicle collisions occur, their intensity, and the means to begin prioritizing highway segments for potential mitigation applications. The identification and delineation of WVC clusters, which often vary widely in length depending on distribution and intensity of collisions, facilitates between-year or multi-year analyses of the stability or dynamics of wildlife-vehicle collisions hotspot locations. The wildlife-vehicle collisions data that transportation departments currently possess are suitable for meeting the primary objective of identifying hotspot locations at a range of geographic scales, from project-level (<50 km of highway) to larger district-level or state-wide assessments on larger highway network systems. The spatial accuracy of WVCs is not of critical importance for the relatively coarse-scale analysis of where hotspots are located. Any of the analytical clustering techniques can be used when more detailed information is needed. Our research analyzed several clustering methods including: Linear Nearest Neighbor Index (a simple plotting technique) to assess whether the location of dead animals found on roads as a result of wildlife-vehicle collisions were random; Ripley's K-statistic of road-kills; Nearest-Neighbor measurements (using Crimestat® software); and Density measures (See NCHRP 25-27 reports). We found that the Nearest Neighbor (Crimestat®) approach was useful for identifying key hotspot areas on highways with many road-kills because it, in essence, filters through the road-kill data to extract where the most problematic areas lay. The Density analysis approach identified more hotspot clusters on longer sections of highway. Although the Density analysis approach appears to be less useful to management, it may be a preferred option where managers are interested in taking a broader, more comprehensive view of wildlife-vehicle conflicts within a given area. Please see our final report for a more detailed description of using cluster analyses.
Accessing department of transportation or ministry of transportation data is not the only method of identifying areas with animal-vehicle collision concerns. Local wildlife agency personnel often keep records of wildlife carcasses removed from the road. A call to the area conservation officer or other wildlife agency representatives can quickly reveal potential wildlife conflict zones in an area. A visit to the local department of transportation/ ministry of transportation maintenance facility for a discussion with road maintenance workers could also be helpful.
It is important to also consider wildlife that may not necessarily be a safety risk to drivers. Local area wildlife professionals and the citizens of a community are usually aware of ongoing road associated mortality of local populations of smaller mammals, birds, amphibians, and reptiles. Contacts should be made with biologists working for the state wildlife agency, the U.S. Fish and Wildlife Service, and public land agencies near the project in order to better understand if there are potential problems with smaller species in the area of concern that need to be considered.
Safety Performance Functions are a more sophisticated statistical technique of identifying locations along roadways with a higher than average number of wildlife-vehicle collisions. Safety Performance Functions (SPFs) are predictive models for wildlife-vehicle collisions that typically relate the response variables (animal vehicle collision data and/or roadside carcass collection data) to the explanatory variables (physical roadway and roadside characteristics; often referred to as road geometrics). Other explanatory variables that animals respond to (e.g., topography, vegetative cover, and other off-road variables) are not among these variables that are readily available within the typical DOT safety databases. Hence, this approach will result in some unexplained variation, because the safety approach limits the explanatory variables to road geometrics. Regardless, this is a valuable approach because only these lower levels of data availability may exist in some jurisdictions.
The approach is statistically correct and accounts for "regression to the mean" problems. It makes use of three different levels of road data commonly available. The first level requires data on: 1) road length; and 2) annual average daily traffic volume (ADDT). The second level adds the requirement that road segments to be classified as flat, rolling, or mountainous terrain. The third level incorporates the data used in levels 1 and 2, but includes additional roadway variables such as average lane width. The safety approach has several applications and can be used to:
- Identify crash prone locations for existing or proposed roads for all crash types combined or for specific target crash types
- Aid in the evaluation, selection and prioritization of potential mitigation measures
- Evaluate the effectiveness of mitigation measures already implemented
SPFs are introduced on the website www.safetyanalyst.org, and are reviewed in depth in our research by Persaud and Lyon in Section 3.1 of our report.
An important caveat is that the safety approach does not address any aspect of wildlife population response. As they stand, the primary application of the models is for the safety management of existing roads as opposed to design or planning applications for new or newly built roads.
Kassar, C. 2005. Wildlife-vehicle collisions in Utah: An analysis of wildlife mortality hotspots, economic impacts, and implications for mitigation and management. Thesis, Utah State University, Logan Utah.
Page, M. 2006. A toolkit for reducing wildlife and domestic animal-vehicle collisions in Utah. In Transportation Research Board 2006 Annual Meeting. CD-ROM. Transportation Research Board, National Research Council, Washington, D.C.
1.2.6 Investigate if Landscape Linkages Have Been Identified in the Area
If large scale habitat connectivity analyses exist for the project area, consider the priorities identified for protection or restoration of habitat linkage areas. States that have conducted large scale (state- or region-wide) interagency habitat connectivity analyses report that the analysis has facilitated identification and prioritization of linkage areas so that both transportation and natural resource agencies can agree on linkage areas.
Arizona, Colorado, New Mexico, Vermont, and Florida as well as other states have statewide habitat connectivity maps. See below for links to some known connectivity analysis results. Each state developed its system independently, and to date there is no mandate or standardized system to construct these maps. Nevertheless, these states now have a basis for agreeing on linkage areas as well as which linkage areas are highest priority, allowing transportation departments to have a degree of predictability in project planning, and allowing natural resource departments to choose priority areas for conservation efforts.
There are numerous ways to create a large scale connectivity map. Florida has an elaborate, detailed, and expensive system, called the 'Efficient Transportation Decision Making'. It is useful for far more than transportation planning and has been used in a number of other planning applications.
A shorter, less complex approach it a rapid assessment process that can be accomplished with relatively few resources in a short period of time. Rapid assessments have the benefit of low cost because few hours of agency personnel are used; however they still can provide a level of interagency agreement on the concepts of linkage area identification and prioritization that is useful. Once developed on a generalized basis, agencies can refine them over time as resources permit. Here is an example of a regional area in southwestern Montana rapid assessment.
If the project area does not already have an interagency team to create a habitat connectivity map, it is useful to consider creating one. Habitat connectivity analyses may exist at other scale extents (i.e., a highway segment or a portion of the state).
Other Western States
Vermont Wildlife Habitat Linkage Analysis
Carr, M., Hoctor, T., Goodison, C., Zwick, P., Green, J., Hernandez, P., McCain, C., Teisinger, J., Whitney, K., "Southeastern Ecological Framework." Final Report, Geoplan Center, Departments of Landscape Architecture, Urban and Regional Planning, and Wildlife Ecology and Conservation, University of Florida, Gainesville, FL (2002).
Penrod, K., Hunter, R. and Merrifield, M., "Missing Linkages: Restoring Connectivity to the California Landscape." Conference Co-Sponsored by California Wilderness Coalition, The Nature Conservancy, U.S. Geological Survey, Center for Reproduction of Endangered Species, and California State Parks, Proceedings (2001).
Ruediger, B., Basting, P., Becker, D., Bustick, J., Cavill, P., Claar, J., Foresman, K., Hieinz, G., Kaley, D., Kratville, S., Lloyd, J., Lucas, M., McDonald, S., Stockstad, G., Vore, J., Wall, K., Wall, R., "An Assessment of Wildlife and Fish Linkages on Highway 93 - Western Montana." Forest Service Publications #R1-04-81, USDA Forest Service, USDI Fish and Wildlife Service, confederated Salish and Kootenai Tribe, Rocky Mountain Elk Foundation, Montana Fish, Wildlife and Parks, Montana Department of Transportation, Geodata Services, The University of Montana, Missoula, MT (2004) 41 pp.
Ruediger, B. and J. Lloyd. 2003. A rapid assessment process for determining potential wildlife, fish and plant linkages for highways. In: Proceedings from the 2003 ICOET conference, Lake Placid, NY. Pp.205-222. (PDF)
Singleton, P., Gaines,W. and Lehmkuhl, J., "Landscape Permeability for Large Carnivores in Washington: A Geographic Information System Weighted-Distance and Least-Cost Corridor Assessment." USDA Research Paper PNW-RP-549, Pacific Northwest Research Station, U.S. Forest Service (2002).
1.2.7. Regulatory Reasons to Be Concerned About Wildlife
There are over one dozen federal laws in the U.S. and Canada that pertain to wildlife and transportation. In the U. S. the major laws include but are not limited to:
SAFETEA-LU the 2005 Transportation Act
Department of Transportation Act
National Environmental Protection Act
Endangered Species Act
Clean Water Act
In Canada the laws include but are not limited to:
Canada Wildlife Act
Species at Risk Act
Migratory Birds Convention Act
Ontario Endangered Species Act
Fish and Wildlife Conservation Act
The web-sites below explicitly describe the acts for both Canada and the U.S. and we leave it to the user to further explore these laws and pertinent regulations.
U.S. Federal Highways Environmental Guidebook - use "Select Topics" function to search by type of act
1.2.8 Summarize Results
At this final stage of evaluating whether the planned project may affect wildlife, the remaining step is the identification of potential future situations in the project area. Important considerations include assessment of changes over time that may increase the probability of highway effects to wildlife; e.g., within a 20-year planning timeframe. Traffic volume is one variable that is likely to change over time. Additionally, rapidly increasing development will affect transportation decisions not only on the affected road but adjacent roads as well. Transportation departments have the technical ability to project traffic increases. This information, particularly traffic volume increases, combined with local planning projections, can assist in determining if mitigation may be warranted in the current project rather than waiting for future expected growth. As a case in point, wildlife crossings are much less expensive to install in new construction than as a retrofit in an existing highway.
An important consideration is the project area's importance to large scale conservation goals. Even if an area is not pristine, its position on the landscape may mark it as important for future connectivity needs. Conversely, an area may be inevitably slated for subdivisions and commercial developments. These projections will help the project team to determine the amount and type of mitigation needed currently. If there is a high probability that an area will become useless for wildlife over the next 20-50 years, then it is possible that the appropriate choice may be to do no mitigation. This difficult decision is made in light of the understanding that priorities for habitat maintenance, protection, and restoration are best made in context with large scale ecosystem needs. If the project team decides that the project area will not be suitable for mitigation due to its probable future conditions, the remainder of the Decision Guide will have little use for the team.
At this final stage of step 1.2, users are in a position to decide if the present and projected conditions in a planned project area may affect wildlife in ways that can be mitigated with potential wildlife crossings. At this point, user(s) decide whether to proceed or not with mitigation. This is not a one-person decision. Ideally, all stakeholders are part of the decision. With this decision guide, we have provided steps to accomplish the process. If the decision is that wildlife will be affected by the proposed transportation plan and wildlife crossings may help ameliorate transportation effects, proceed to step 1.3. If Mitigation Needed: Identify Goals and Objectives.