Objective Sponsors Final Agenda Proceedings Conference Facility Participants

The 2005 International Conference
on Ecology & Transportation
San Diego, CA

August 29 – September 2, 2005
Theme: “On The Road To Stewardship”

On The Road To Stewardship

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Abstracts: Wildlife-Vehicle Collisions

Coming Up Next: ICOET 2007 in Little Rock, AR!

Prevention and Reduction Strategies

Characteristics of Elk-Vehicle Collisions and Comparison to GPS-Determined Highway Crossing Patterns

Norris L. Dodd (Phone: 928-367-5675, Email: doddnbenda@cybertrails.com), Jeffrey W. Gagnon, Susan Boe and Raymond E. Schweinsburg, Arizona Game and Fish Department, Research Branch, 2221 West Greenway Road, Phoenix, AZ 85023

We assessed spatial and temporal patterns of elk (Cervus elaphus nelsoni) collisions with vehicles from 1994-2004 (n = 456) along a 30-km stretch of highway in central Arizona, currently being reconstructed in five sections with 11 wildlife underpasses, 6 bridges, and associated ungulate-proof fencing. We used Global Positioning System (GPS) telemetry to assess spatial and temporal patterns of elk highway crossings and compare to elk-vehicle collision (EVC) patterns. Annual EVC were related to traffic volume and elk population levels (r2 = 0.750). EVC occurred in a non-random pattern. Mean before-construction EVC (4.5/year) were lower than EVC on sections under construction (12.4 EVC/year). On the only completed section, EVC did not differ among before-, during-, and after-construction classes, even though mean traffic volume increased 67 percent from before- to after-construction levels, pointing to the benefit of three passage structures and fencing. On one section under construction, EVC increased 2.5x when fencing associated with seven passage structures was incomplete; EVC dropped dramatically once fencing was completed. We accrued 101,506 fixes from 33 elk (25 females, 8 males) fitted with GPS collars May 2002-April 2004. Elk crossed the highway 3,057 times (mean = 92.6/elk) in a non-random pattern. We compared EVC and crossings at five scales; the strongest relationship was at the highway section scale (r2 = 0.942). Strength of the relationship and management utility were optimized at the 1.0-km scale (r2 = 0.701). EVC frequency was associated with proximity to riparian-meadow habitats adjacent to the highway at the section (r2 = 0.962) and 1.0 km (r2 = 0.596) scales. Though both fall EVC and crossings exceeded expected levels, the proportion of EVC in September-November (49%) exceeded the proportion of crossings and coincided with the breeding season, migration of elk from summer, and high use of riparian-meadow habitats adjacent to the highway. The proportion of EVC and crossings by day did not differ; both reflected avoidance of crossing the highway during periods of highest traffic volume. Though traffic volume was highest from Thursday-Saturday, the proportion of EVC was below expected. A higher proportion of EVC (59%) occurred relative to crossings (33%) in the evening hours (17:00-23:00); 34 percent of EVC occurred within a one-hour departure of sunset, and 55.5 percent within a two-hour departure. EVC data are valuable in developing strategies to maintain permeability and increase highway safety including selecting locations of passage structures.

Effects of Gender and Season on Spatial and Temporal Patterns of Deer-Vehicle Collisions

Uma Ramakrishnan (Phone: 814-641-3436, Email: Ramakrishnan@juniata.edu), Laura Daugherty (Phone: 570-954-8125, Email: DaughLa2@juniata.edu), and Neil W. Pelkey (Phone: 814-641-3589, Email: Pelkey@juniata.edu), Juniata College, 1700 Moore Street, Huntingdon, PA, 16652; and Scott C. Williams (Phone: 203-974-8527, Email: Scott.Williams@uconn.edu), University of Connecticut, Department of Natural Resources Management and Engineering, 1376 Storrs Road, Storrs, CT 06269

White-tailed deer (Odocoileus virginianus) are a serious accident hazard, especially in suburban communities with high deer densities. Such areas are becoming more common as deer populations continue to grow throughout the northeastern United States. This study analyzed deer-vehicle collision data collected from police reports in Connecticut for 2000, 2001 and 2002. The purpose of this project was to integrate the use of standard crime mapping tools, multi-temporal remotely sensed vegetation imagery, human infrastructure, and the behavioral aspect of white-tailed deer to create a spatially explicit model of gender-specific deer-vehicle accident probabilities. We found marked differences between number, location, and seasonality of male and female accidents. Through most of the year, the number of males and females involved in accidents were relative to their proportion in the population. However, during the breeding season, there were a higher proportion of males involved in accidents. The spatial distribution of accidents involving deer also varied by season and sex – outside of the breeding season, accidents involving male deer were concentrated in a few key locations in the state. The difference in the spatial location of male and female accidents could be the result of resource partitioning exhibited by the species, with males occupying broader ranges in peripheral habitats. This model can be used to predict high risk areas as they change over the different seasons and design warning programs and adaptive education to these target areas.

Evaluation of a Highway Improvement Project on Florida Key Deer

Anthony W. Braden (Email: anthonybraden@hotmail.com), Roel R. Lopez (Phone: 979-845-5777, Email: roel@tamu.edu), Clay W. Roberts, and Nova J. Silvy, Department of Wildlife and Fisheries Sciences, Texas A&M University, College Station, TX 77843; Catherine B. Owen (Phone: 305-470-5399, Email: catherine.owen@dot.state.fl.us), Florida Department of Transportation, Environmental Management Office, Miami, FL 33172; Philip A. Frank, U.S. Fish and Wildlife Service, National Key Deer Refuge, Big Pine Key, FL 33043; and Donald S. Davis, Department of Veterinary Pathobiology, Texas A&M University, College Station, TX 77843

Deer-vehicle collisions (DVCs) are a concern in the recovery of the endangered Florida Key deer (Odocoileus virginianus clavium) on Big Pine Key, Florida. Since the 1960s, nearly half of the total deer mortality has been attributed to DVCs; the majority of these mortalities occurring along the United States Highway 1 (US 1) corridor. In 2002, the Florida Department of Transportation completed modifications to a 2.6-km segment of the US 1 corridor that included fencing, experimental deer guards, and underpasses designed to prevent deer entry into the roadway and minimize DVCs. We evaluated the effectiveness of highway modifications in reducing Key deer-vehicle collisions pre- and post-project using long-term mortality data. Overall US 1 DVCs remained unchanged due to DVC increases along the unfenced section of US 1 on Big Pine Key; even though highway modifications (i.e., deer guards, fencing, and underpasses) reduced Key deer-vehicle collisions by 83–95 percent both post-project years. Experimental deer guards minimized deer crossings to six deer crossings the first post-project year and three crossings the second year. As a result, we recommend experimental deer guards in combination with fencing (and underpasses when applicable) can benefit wildlife in urban/suburban settings while maintaining human safety.

OPTIFLUX: A Tool for Measuring Wild Animal Population Fluxes for the Optimization of Road Infrastructures

Dr. Philippe Thiévent (Phone: 0033 / 01 30 48 44 97, Email: p.thievent@scetauroute.fr), SCETAUROUTE, Environment Department, EGIS Group, Guyancourt 78286 France

In West European countries natural habitats are often fragmented. In those countries fragmentation is both characterized by an increase in the number of habitat fragments and a decrease in their size, leading to animal population isolation. The geometry of linear infrastructures (e.g., roads, railways) is not so much a cause of destruction of animal habitats, but rather it acts more as a barrier between fragments. If we consider linear infrastructure as a barrier in landscapes, it is important to study biological fluxes between landscape features before deciding the final route of such infrastructures. OptiFlux development is based on the "resistance concept," developed by G. Pain for his Ph.D. (2001) for SCETAUROUTE and the French Ministry of Environment and the Ministry of Transport.

OptiFlux is an automatic GIS space analysis device. It is designed for the prediction and identification of the effects of linear infrastructure on the territorial occupation and viability of the animal populations concerned. OptiFlux can also be used to assess the relevance of fauna passages and, consequently, to optimize their final location and quantities. OptiFlux is crossing land use and environmental data, correlated with the ecological requirements of the species studied. OptiFlux is based on a population viability analysis, applying the SCETAUROUTE Arc View GIS standard. The innovative aspect of OptiFlux is its automated diagnostic approach, with the cross-relation of space and biological data. There are three direct applications for the tool:

  • Identification of routes having least impact on wild animal population flows
  • Optimization of the number/location of fauna passages for the benefit of wild animals
  • Simulation of the positive effect of the fauna passages proposed

OptiFlux provides a preliminary approach for a quick identification of the critical areas to be taken into account for design and estimation of the infrastructure. However, it does not eliminate the need for expertise and verification of the results obtained by a field biologist. OptiFlux is a project optimization instrument, helping with the decision making process, concerning the necessity and relevance of the improvements retained. It is also a tool that provides images of future scenarios once the project is realized.

OptiFlux has been tested on many species, such as Mustela lutreola, Osmoderma eremita, species of major importance in terms of the European wildlife heritage (threatened species), and Capreolus capreolus, Cervus elaphus, Sus scrofa, species encountered in the majority of projects. Several organizations have already expressed interest in this tool, such as the ONCFS (French National Hunting and Wildlife Authority), various French motorway companies, the IAURIF (Ile de France Regional Urban Planning and Development Institute), and the Direction Régionale de l'Equipement du Nord Pas de Calais.

Probabilistic Measure of Road Lethality

John S. Waller (Phone: 406-888-7829, Email: john_waller@nps.gov), Glacier National Park, West Glacier, MT 59936, Fax: 406-888-7946; Christopher Servheen (Phone: 406-243-4903, Email: grizz@umontana.edu), U.S. Fish and Wildlife Service, College of Forestry and Conservation, University Hall, Room 309, University of Montana, Missoula, MT 59812; and David A. Patterson, Department of Mathematics, University of Montana, Missoula, MT 59812

Throughout the world, the effects of highways and railroads on wildlife have been of great concern to scientists, land and wildlife managers, and the public, for over 80 years. Through these years, many researchers have sought to understand and mitigate the negative impacts of roads through theoretical and empirical research. However, to our knowledge, no one has investigated the underlying probability theory that likely governs the extent to which linear transportation features result in wildlife mortality. One reason may be that the number of factors potentially influencing observed patterns of road mortality can be quite large and can quickly become intractable. Our objective here was to suggest that the lethality of linear transportation features to wildlife is governed primarily by two factors: traffic volume and time spent on the roadway. Using a simple Poisson model of expected vehicle arrival times, we estimated the probabilities of animals successfully crossing roads under different traffic volume and animal mobility constraints. We used actual vehicle counts from two study areas as examples, and used a study of grizzly bears along a major railroad and highway to illustrate these concepts. We discuss the usefulness of this approach to conservation problems, and place it in context with other efforts to quantify the occurrence of wildlife mortality due to highways. Our hope is that these ideas will clarify and advance the search for solutions to what previously has been an intractable problem.

Reliability of the Animal Detection System Along US HWY 191 in Yellowstone National Park, Montana, USA

Marcel P. Huijser (Phone: 406-543-2377, Email: mhuijser@coe.montana.edu), Whisper Camel, and Amanda Hardy, Western Transportation Institute, Montana State University, P.O. Box 174250, Bozeman, MT 59717-4250

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.

Upgrading a 144-km Section of Highway in Prime Moose Habitat: Where, Why, and How to Reduce Moose-Vehicle Collisions

Yves Leblanc (Phone: 418-871-2452, Email: yves.leblanc@tecsult.com) and François Bolduc (418-809-1105, Email: francois.bolduc@foramec.qc.ca), Tecsult Inc., 4700, boul. Wilfrid-Hamel, Québec City, Québec G1P 2J9, Canada; and Donald Martel (Phone:418-695-7916, Email: dmartel@mtq.gouv.qc.ca), Direction Saguenay-Lac-St-Jean-Chibougamau, Ministère des Transports du Québec, 3950, boul. Harvey 1er étage, Jonquière, Québec G7X 8L6 Canada

In Quebec, as throughout North America, the number of vehicles on roads and the daily distances travelled increase continuously. At the same time, populations of moose (Alces alces) and white-tailed deer (Odocoileus virginianus) have reached unprecedented levels in this province. For example, the moose population increased from 60,000 to 100,000 animals in Quebec between 1990 and 2002. Hence, moose-vehicle collisions have increased and caused numerous human injuries and fatalities in recent years in Quebec. The main objective of our study was to identify roadway, habitat, and moose population features that correlated with the reported number of moose-vehicle collisions (MVCs) and propose measures to reduce risks to motorists. Our study was implemented in the context of a planned project to upgrade a two-lane primary artery to a four-lane divided highway, located north of Québec City that bisects a wide forested area, the Laurentides Wildlife Reserve (LWR). Moose population and habitat variables were obtained from harvest, aerial inventory data, and aerial photos. Other variables were also measured from digital data layers using the ArcView GIS. Habitat suitability was computed using digital layers from ecoforestry maps and ArcView Spatial Analysis. Roadway variables were collected in the field or extracted and computed from digital layers with AutoCad and InRoads software packages. Moose-track surveys were also conducted monthly from June to September 2004 along the major conflict zone.

Moose densities varied between 1.0 moose/10 km2 in the center of the 144-km Highway 175 to 8 individuals/10 km2 in its southern and northern portions. We estimated that between 573 and 860 moose were roaming within 5 km on each side of the highway in 2004. A controlled hunt and high quality habitats following forest exploitation and natural perturbations occurring within the LWR are likely to be major contributors to this growing population. Our data analysis using AIC showed that four variables explained most variations in the number of MVCs among 1-km sections. These variables were (1) the slope complexity of the adjacent landscape, (2) the total length of rivers, streams, and brooks located within a 250-m buffer zone on each side, (3) the habitat suitability for forage within a buffer zone of 1 km on both sides, and (4) the proportion of steep (> 3-m high) road cuts. During fall and early winter habitat features were strongly related to the number and location of MVCs, whereas the influence of slope complexity was greater during summer. However, annual and seasonal models explained a limited amount of the variance in the number of MVCs (R2 < 0.288) and could not be used efficiently to identify conflicting sections and set management priority. The longest and the most hazardous section tallied 25 km, which was surrounded by high-quality moose habitat. Track surveys in the summer of 2004 showed frequent movements across the highway, but little clustering. Because we could not find strong relationships between MVCs and road and habitats features, we used the numbers of recorded MVCs to delineate 5-km sections and establish actions to be taken to reduce risks. The top priority hazardous zone, which encompasses 25 km, will be fenced during the upgrading project and combined with two major underpasses.

Use of Video Surveillance to Assess Wildlife Behavior and Use of Wildlife Underpasses in Arizona

Jeffrey W. Gagnon (Phone: 928-522-8164, Email: jeff_gagnon@yahoo.com) and Raymond E. Schweinsburg, Arizona Game and Fish Department, Research Branch, 2221 West Greenway Road, Phoenix, AZ 85023; Norris L. Dodd, Arizona Game and Fish Department, Research Branch, P.O. Box 2326, Pinetop, AZ 85935; and Amanda L. Manzo, Arizona Game and Fish Department, Research Branch, 3500 South Lake Mary Road, Flagstaff, AZ 86001

We used integrated, four-camera video surveillance systems to assess and compare wildlife use of five open span bridged wildlife underpasses along a 30-km stretch of reconstructed highway in central Arizona. We determined passage rates (proportion of animals approaching and crossing through underpasses) and categorized behavioral responses exhibited during underpass approaches and crossings. Two underpasses have been monitored for over 2-1/2 years; both open into the same meadow/riparian complex, are only 225 m apart, but have different below-span characteristics and dimensions, providing an excellent opportunity to compare use by wildlife. Four underpasses, in place for 18 months, have been monitored for over one year; two of these allowed for monitoring before ungulate-proof fencing was erected in association with the underpasses. This allowed us to record pre- and post-fencing passage rates and behavior to assess the role of fencing in funneling animals to underpasses and influencing passage rates. At the two adjacent underpasses monitored over 2-1/2 years (December 2002-June 2005), we recorded eight species of wildlife totaling 3,914 animals, including 3,548 elk (Cervus elaphus nelsoni), 216 white-tailed deer (Odocoileus virginianus cousei), and 6 species of carnivores including 4 mountain lions (Puma concolor). Overall, elk passage rates averaged 0.62, while only 15 deer crossed the underpasses (0.075 passage rate). We detected significant differences in passage rate and behaviors indicative of resistance to crossing. One underpass with earthen 2:1 sloped sides has been used more by elk (1,908 elk) displaying less resistant behaviors and delay in crossing compared to one with concrete walls (598 elk). This information was used in an adaptive management context to minimize concrete walls and pursue alternatives to soil stabilization at a wildlife underpass currently under construction. At the three recently completed underpasses, monitored February 2004-June 2005, we recorded 10 species of wildlife totaling 1,703 animals, including 860 elk, 367 white-tailed deer, 194 mule deer (O. hemionus), and 7 species of carnivores. Elk passage rates to date averaged 0.35, with the passage rate at two underpasses exceeding 0.50 and two below 0.27. Both white-tailed and mule deer regularly used the newer underpasses with passage rates of 0.40 and 0.29, respectively. Ungulate-proof fencing was completed through the underpasses in December 2004, and we continue to monitor wildlife response and changes in passage rates since this fencing was erected. Video surveillance constitutes a valuable tool in quantifying wildlife use of underpasses and assessing the effectiveness of underpasses and fencing. Continued monitoring will allow us to assess long-term use of passage structure.

What Features of the Landscape and Highway Influence Ungulate Vehicle Collisions in the Watersheds of the Central Canadian Rocky Mountains? A Fine-Scale Perspective

Kari E. Gunson (Phone: 403-760 1371, Email: kari.gunson@pc.gc.ca) and Bryan Chruszcz (Email: bryan.chruszcz@pc.gc.ca), Parks Canada, Box 900, Banff, Alberta T1L 1K2, Canada; and Anthony P. Clevenger, Ph.D. (Phone: 403-760-1371, Email: tony.clevenger@pc.gc.ca), Western Transportation Institute, P.O. Box 174250, Montana State University, Bozeman, Montana 59717

Wildlife-vehicle collisions represent an additive source of mortality to wildlife populations, in addition to other mortality, such as predation and disease. The trends of increasing traffic volumes and road densities will only magnify the mortality impacts of roads on large mammals and other vertebrates. In this study, we examined the descriptive and spatial aspects of ungulate-vehicle collisions (UVCs) in the Central Canadian Rocky Mountains (CCRMs). We then specifically addressed the landscape and highway characteristics associated with the UVCs in four major watersheds: the Bow Valley, Kananaskis Valley, Kicking Horse Valley, and Kootenay Valley, each with differing road-types, topography, and habitat. We grouped the factors associated with vehicle collisions into three groups: combined, landscape-animal, and highway-vehicular-animal. The combined model included all variables, the landscape-animal model included factors that influence whether an animal makes it to the roadway, and the road-vehicular model included factors that influence the probability of an interaction between the animal and the vehicle. Between 1999 and 2003 all kill sites were initially measured with a Global Positioning System (GPS) (accuracy <3 m) and later revisited to measure all field measurements. Many other studies have looked at the factors associated with wildlife vehicle collisions; however, our study is unique in that we were able to revisit exact collision sites (accuracy <10 m). There were a total of 546 ungulate mortalities on all highways in the watershed with the majority occurring in the Bow Valley followed by the Kicking Horse Valley, and Kananaskis Valley, and the least occurring in Kootenay Valley. The distribution of kills was correlated with the traffic volumes on each road-type. Further, UVC distributions differed significantly from random distributions along all road types in each watershed. Type of habitat was the most important variable in explaining UVCs in the combined, landscape and Bow watershed models. UVCs were less likely to occur in open water, rock, and closed coniferous forest relative to open habitat. The proportion of open vegetation in the Bow Valley positively influenced wildlife mortality, while in the Kicking Horse watershed it negatively influenced mortality. Width and traffic volume were significantly positively correlated with the occurrence of UVCs in the combined model and Bow model, respectively. Elevation was a significant factor in the combined, landscape, Bow, and Kootenay watersheds, having a negative correlation on ungulate mortality. The proportion of open habitat positively contributed to kills in the Bow; whereas, it negatively influenced kills in the Kicking Horse. The three grouped models were ranked differently in their ability to predict the observed likelihood for UVCs. The combined model was the most important model in predicting the occurrence of UVCs, followed by the landscape model, and lastly the road-vehicular-animal model. Our findings show that kills do not occur randomly in the landscape. Different scales of analysis, i.e., ecoregion or watershed perspective, can influence which variables are important in contributing to the spatial distribution of UVCs. Further, different groups of variables, i.e., roads and motorist related factors, or landscape and animal behavior factors, may contribute differently to the spatial occurrence of UVCs. The factors contributing to UVCs along each landscape and highway are critical for developing knowledge-based mitigation for reducing effects of vehicle collisions on large animal populations and increasing public safety on highways.

Wildlife and High Speed Rail

California High Speed Rail Proposal: "High Speed Rail and Wildlife"

Cynthia Wilkerson, M.S. (Phone: 916-313-5800 ext. 110, Email: cwilkerson@defenders.org), California Representative, Defenders of Wildlife, 1303 J Street, Suite 270, Sacramento, CA 95814 (Supplemental materials provided by Dan Leavitt, California High Speed Rail Authority)

The California High Speed Rail (HSR) Proposal is in the initial planning phase. In response to increasing population and an overtaxed transportation network, a 700-mile HSR proposal has been proposed to link major metropolitan areas in the state. The HSR proposed would be devised of state-of-the-art technology, travel at a maximum speed of 220 miles, a 50-foot right of way, and include at-grade, aerial, and tunnel alignments. The entire length of the at-grade alignments would be fenced. Due to sophisticated communications systems, trains would be frequent, with options for local as well as long-distance use. Travel times are comparable to, and in some cases surpass, door-to-door travel times for driving or flying alternatives.

The Final Environmental Impact Report/Statement (FEIR/S), which was released in August 2005, concludes that the HSR option leads to decreased energy consumption, reduced air pollutant emissions and improved air quality, uses less land, and has fewer overall impacts to sensitive habitats and water resources than either the option to continue with currently planned transportation projects or to expand existing highways and airports. A major concern in terms of wildlife is the impact of the fencing on wildlife movement and migration corridors. The California HSR Authority has decided to relegate the analysis of this impact to the project-level environmental documents. There is a recognized concern that this approach will fail to provide the landscape-level analysis necessary to accommodate the wildlife movement needs.

The environmental review process revealed several areas of controversy. For the northern mountain crossing connecting the Bay Area to the Central Valley, there was a concern that the Altamont Pass alignment, which tracks I-580, was not included as an option. As a result, the HSR Authority will be working with groups in the Bay Area on an additional EIR/S to specifically choose the alignment on this crossing.

A second area of controversy is the southern mountain crossing, which connects the Bakersfield to Los Angeles stations. Seismic and tunneling constraints caused the southern mountain crossing to be chosen, which cuts east into the West Mojave Desert with a station in Palmdale instead of following I-5 directly south. This decision was made despite major concerns of direct and growth-inducing impacts to the West Mojave Desert. Those with a desire to decrease impacts to public lands or to expand the growth in the city of Palmdale were in support of this option.

The third area of controversy concerned impacts on parks, wildlife areas, and recreational resources. As a result, no alignments were chosen through Henry Coe State Park, Don Edwards San Francisco Bay Wildlife Refuge, or San Luis State Recreation Area. Additionally, alignments which occur adjacent to state parks will occur on existing rail corridors, and other concerns will be considered at the project level.

The final area of controversy was the growth-inducing impact of the stations themselves. All stations are required to serve as multi-modal sites.

Identified environmental impacts will be avoided, minimized, and mitigated. Nearly 70 percent of the alignments will occur on existing transportation corridors and rail lines. Only 24 percent of the alignment will be at-grade in new corridors. Underpasses and overpasses will be designed during the project-level analysis, and tunneling will occur in mountainous habitat in major portions of the undeveloped alignments. Mitigation will be determined at the project-level but may include project-design changes, contribution to a conservation bank or natural management area, relocation of sensitive species, and construction of wildlife underpasses, bridges, and/ or culverts. The FEIR/S also outlines specific mitigation strategies to be employed at the project level for plant communities, biological resources management plans, sensitive plan species, invasive species, wildlife movement and migration corridors, and jurisdictional waters and wetlands.