Funding source and budget: US Department of the Interior, National Park Service. Total budget approximately $90,000. Project Period: October 1998 through June 2001. The effect of winter recreation on animal populations is widely debated, particularly since a recent decision by the US Department of the Interior to ban snowmobiles from National Parks. This study assesses effects of over-snow vehicle traffic on an elk (Cervus elaphus) and bison (Bison bison) population in Yellowstone National Park. We relate behavior and distribution to variation in over-snow vehicle traffic. We use immunoassays of fecal glucocorticoid levels as a noninvasive method of measuring physiological stress responses to disturbances, to relate over-snow vehicle activity to glucocorticoid levels. In preliminary results for elk, day-today variation in fecal glucocorticoid levels tracked variation in the number of snowmobiles, after controlling for effects of weather and age. Glucocorticoid concentrations were higher in response to snowmobiles than in response to wheeled vehicles, after controlling for effects of weather, age and number of vehicles. Results for bison are pending, as are behavior and distribution analyses. Despite these stress responses, there is no evidence that current levels of snowmobile activity are affecting population dynamics for either species.

Animal detection systems use high-tech equipment to detect large animals when they approach the road. Once a large animal is detected, warning signs are activated urging drivers to reduce their vehicle speed, be more alert, or both. Lower vehicle speed and increased alertness may then lead to fewer and less severe collisions with, for example, deer (Odocoileus sp.), elk (Cervus elaphus), or moose (Alces alces)). For this study, we investigated the reliability of the animal detection system installed along US Hwy 191 in Yellowstone National Park, Montana, USA. The system was designed to detect elk and stored all detection data, including the detection zone in which the detection occurred, and a date and time stamp. Interpretation of the detection data suggested that at least 47 percent of all detections were related to animals crossing the road. However, animals walking in the right-of-way or medium-sized mammals (e.g., coyotes, Canis latrans) do not generate a clear detection pattern, and were, therefore, classified as “unclear.” Therefore, the 47 percent should be regarded as a minimum estimate. The timing and direction of travel of crossing events, indicated by detections on opposite sides of the road, matched local knowledge about the behavior of the elk, suggesting that the system was able to detect large animals, specifically elk, and that the data were interpreted correctly. We also compared the spatial distribution of the crossing events with snow tracking data. The spatial distribution of the crossing events and elk tracks showed a close match, again suggesting that the system was able to detect elk, and that the data were interpreted correctly. Almost 87 percent of all elk crossings recorded through snow tracking could be linked to a crossing event detected by the system. However, medium-sized mammal species, such as coyotes and wolves (Canis lupus), were not or rarely detected. Furthermore, we identified the presence and location of blind spots (potentially 17.8% of the total length covered by the sensors). Blind spots were defined as locations where the system failed to detect a human crossing between the sensors. Most of the blind spots were due to curves and slopes that caused the detection beam to shoot too high above the ground. The total time for which the flashing warning lights would have been activated was estimated at one hour and 13 minutes per day, a marked difference compared to permanently activated warning signs. Most crossing events (72.6%) were completed within three minutes, and the median duration of a crossing event was one minute and 29 seconds. If the warning signs would be activated for three minutes after the last detection, the signs would have been continuously activated for 88.1 percent of all detection intervals (i.e., time between consecutive detections) during crossing events. Similarly, 78.1 percent of all crossing events would have had the warning signs continuously activated while the crossing was in process. We conclude that the system reliably detects large animals, especially elk, but the system does not detect all elk that cross the road, e.g., because of blind spots. In addition, a three-minute activation period for the warning signs appears to be a good balance between keeping the signs turned on while elk are in the process of crossing the road, and not presenting drivers with activated warning signs longer than necessary.

Animal-vehicle collisions are an important issue in North America. Accidents are numerous and result in human injuries and fatalities, property damage, and the death or injury of the animals concerned. Some animal species may be affected at the population level and face increased risk of local or regional extinction due to the high number of road-kills and other negative effects of roads and traffic. Systematically collected road-kill data can help quantify the magnitude of this problem and potential changes in road-kill occurrences and “hot spots” over time. Such data allows for prioritization and focusing of mitigation efforts to avoid or reduce collisions. However, not all DOT’s or DOT districts record animal-vehicle collisions and the DOT’s that do record road-kill data often use different methods. A national standard and tool for the recording of animal-vehicle collisions would not only stimulate DOT’s and other organizations to collect animal-vehicle collision data, but would also allow for more effective analyses and use of the data. The Western Transportation Institute at Montana State University (WTI-MSU) has developed software that allows for easy, standardized, and spatially precise collection of animal-vehicle collision data. The software runs on a Pocket PC that is linked to a Global Positioning System (GPS). The software distinguishes between “monitoring” and “incidental observation” modes and tracks the route of the observer. Road-kill data, including species name as well as optional parameters such as the sex of the animal, are stored in a separate file that can be uploaded to a PC and imported into standard spreadsheet or mapping software. Recording road-kill observations with this tool eliminates manual data entry and transcription. Beyond the basic data-collection software, we anticipate developing data-management and analysis software that will allow for easy merging and analyses of data from numerous sources, including cluster analyses, and linking to other spatial data in a Geographic Information System (GIS). This has the potential to allow for much faster and better feedback to plan and prioritize for mitigation to address human-safety or conservation concerns. Once mitigation measures have been put in place, the tools and procedures described above allow for proper evaluation of these measures. We expect that the tools and procedures will ultimately result in fewer animal-vehicle collisions, less work for road maintenance crews, and a reduction in the transportation and disposal costs of the carcasses. A CD-ROM that demonstrates the software is available on request. Please contact WTI-MSU if you have further questions or if your organization is interested in helping us with the testing and further development of this tool and procedures.

Construction and maintenance of transportation systems can result in direct, indirect, cumulative, and secondary effects on ecosystems and can adversely affect the long-term viability of fish and wildlife populations (National Academy of Sciences 2005; Forman et al. 2002). Typically, mitigating adverse impacts associated with highway systems occurs on a project-by-project basis and commonly attempts to restore the same affected resource near the site where the impact occurs, regardless of regional ecological conservation priorities. This piecemeal approach may fulfill regulatory requirements but greater mitigation value may be achieved for a similar investment by evaluating and prioritizing off-site mitigation opportunities important to sustaining ecosystem processes associated with water quality, sustainable resource management practices, wildlife habitat and connectivity, and other environmental assets that contribute to a high quality of life. Further, project-by-project environmental permitting practices frequently involve repetitious procedures that sometimes unpredictably delay project delivery. Agencies want more effective mitigation approaches, while streamlining planning and permitting processes for transportation programs.

A federal multi-agency team recently developed a guide to encourage agencies to consider alternative approaches for more effective ecological mitigation and efficient transportation program delivery. The guide, entitled, “Eco-Logical: An Ecosystem Approach to Developing Infrastructure Projects” (Brown 2006; referred to as “Eco-Logical”), provides a framework and examples for agencies to collaboratively and strategically plan infrastructure projects and related mitigation to conserve and connect important habitats while increasing the predictability and transparency of infrastructure planning processes. The ecosystem approach outlined in Eco-Logical encourages expedited regulatory approvals for infrastructure projects – in compliance with applicable laws – while maintaining high standards for safety, environmental health, and effective public involvement.

Following guidance outlined in Eco-Logical, an interagency working group in Montana created the “Integrated Transportation and Ecosystem Enhancements for Montana” (ITEEM) process. As the first known effort to adaptively apply the Eco-Logical guidelines, the cooperating agencies encountered and overcame challenging issues, acquiring perspectives that may be helpful to other collaborative endeavors working to establish an Eco-Logical approach for other regions.

This report summarizes events that led to piloting the suggestions in Eco-Logical. The Eco-Logical document is briefly reviewed, followed by an account of the efforts to develop the ITEEM process using the Eco-Logical guidance, including a description of challenges encountered during the development of the process. The final ITEEM process is also described. The intent of this report is to summarize the outcomes, accomplishments and recommendations of this project for the sponsors and team members. The report also seeks to help other interagency collaborative efforts seeking alternative approaches to increase efficiency of transportation project delivery while mitigating adverse impacts where the conservation efforts are most needed.

To view or download a copy of the full report, please visit: http://www.mdt.mt.gov/research/docs/research_proj/integrated_transportation.pdf

Human activities today often cause landscape habitat fragmentation and blockage of wildlife movements across landscapes and ecosystems. North American and European Union initiatives such as the Transportation Equity Act and COST-341 program have heightened the importance of mitigating the negative effects of roads, such as animal-vehicle collisions and barrier effects. Wildlife crossing structures are being incorporated into some road construction and improvement projects in an attempt to reduce negative effects on wildlife populations. Transportation and resource agencies are becoming increasingly accountable and therefore concerned as to whether highway mitigation measures are functional and perform to expected standards. However, there are presently gaps in our knowledge regarding the effectiveness of wildlife crossings structure applications. One reason for the lack of available information is that relatively few mitigation projects implement rigid monitoring programs with sufficient experimental design. Thus, results obtained from most studies remain anecdotal or descriptive at best. With sufficient lead-time, experimental study designs can provide rigorous assessments of highway impacts and wildlife crossing structure performance pre- versus post-construction. Alternative methods of post-construction assessment can be used if time does not permit for data collection during the pre-construction period. We review past and current methods used to evaluate wildlife crossing structures and examine criteria to consider when evaluating wildlife passage effectiveness. We focus on methods to monitor mammals and summarize representative studies published international journals and conference proceedings. We examine pre- and post-mitigation study designs versus evaluations that base effectiveness solely on post-mitigation monitoring. We make suggestions for conducting quality scientific evaluations that will allow transportation agencies to address the question, “Do wildlife crossing structures work?”

Animal-vehicle collisions affect human safety, property and wildlife, and the number of animal-vehicle collisions has substantially increased across much of North America over the last decades. Systematically collected animal-vehicle collision data help estimate the magnitude of the problem and help record potential changes in animal-vehicle collisions over time. Such data also allow for the identification and prioritization of locations that may require mitigation. Furthermore, systematically collected animal-vehicle collision data allow for the evaluation of the effectiveness of mitigation measures in reducing the number of animal-vehicle collisions. In the United States and Canada, animal-vehicle collision data are typically collected and managed by transportation agencies, law enforcement agencies and/or natural resource management agencies. These activities result in two types of data: data from accident reports (AR data) and data based on animal carcass counts (AC data). Here we report on a survey that examined the extent to which AR and AC data are collected across the United States and Canada. While a substantial percentage of the DOTs and DNRs collect and manage AR and/or AC data, many of them do not. Furthermore, DOTs and DNRs that do collect or manage AR or AC data typically do this for different or only partly overlapping reasons. In addition, DOTs and DNRs use different reporting thresholds, have varying search and reporting effort, and only have partial overlap in the parameters recorded. These differences also occur between DOTs and between DNRs, and oftentimes one and the same organization collects inconsistent data as certain parameters may only be recorded ‘sometimes’. These differences and inconsistencies affect the comparability and ultimately the usefulness of the data. Before an AR or AC program is initiated or improved, it is important to illustrate the needs and benefits of such data collection. We list the most important needs and benefits and provide considerations for the initiation or improvement of AR and AC data collection programs.