California Energy Commission, Crude Imports By Rail into California http://energyalmanac.ca.gov/petroleum/statistics/2009_crude_by_rail.html

Summary table of crude by rail imports to California, expressed as barrels of oil 2009 2010 2011 2012 2013 2014 2015 Total Canada 155,296 193,569 3,472,049 1,520,288 5,341,202 Coloradold 30,983 500,708 146,889 678,580 New Mexico 153,318 411,725 1,159,712 792,035 2,516,790 North Dakota 3,353 496,886 1,112,665 704,207 1,348,682 1,191,758 4,857,551 Utah 933,632 190,993 1,124,625 Washington 11,155 11,155 Wyoming 441,398 694,101 308,313 1,443,812 OthersOthers 94,070 37,331 122,211 90,699 344,311 Total 45,491 496,886 1,362,031 1,088,425 6,296,773 5,737,079 1,291,341

2015 Origin Total January February March April May June July August September October November December for Railcars New Mexico 162,528 132,906 176,192 114,520 132,989 81,262 16,849 11,723 20,135 849,104 Utah 49,318 21,105 45,915 44,966 14,619 1,042 0 0 0 176,965 Wyoming 134,876 25,761 26,005 78,925 17,163 69,258 12,740 99,340 213,904 677,972 Total Imports 346,722 179,772 248,113 238,411 164,770 151,562 29,589 111,063 234,038 1,704,041

2014 Colorado 27,478 642 3,422 26,583 12,352 25,909 31,085 4,589 14,829 0 0 0 146,889 North Dakota 82,620 71,541 122,885 121,057 183,189 121,057 123,446 121,057 60,529 121,057 63,320 0 1,191,758 New Mexico 51,136 63,538 58,407 65,808 71,901 78,829 95,820 103,825 88,856 141,320 141,217 199,055 1,159,712 Utah 21,490 44,794 42,930 51,621 44,202 82,115 124,781 106,902 100,534 105,334 115,132 93,797 933,632 Wyoming 18,878 46,767 33,914 42,827 42,856 9,043 9,545 31,567 77,858 70,499 112,148 198,199 694,101 Canada 372,277 199,300 133,697 249,906 267,624 200,065 97,419 0 0 0 0 0 1,520,288 Others 9,376 10,389 124 173 173 39,074 17,110 8,532 5,748 0 0 0 90,699 Total Imports 583,255 436,971 395,378 557,975 622,298 556,093 499,207 376,472 348,354 438,210 431,817 491,051 5,737,081

2013 Colorado 5,861 13,582 34,717 67,291 87,951 69,959 73,023 54,926 14,990 ‐ 23,383 55,025 500,708 NhNorth DkDakota 119,450119 450 206 206,172 172 94 94,695 695 103 103,954 954 128 128,209 209 93 93,317 317 46 46,946 946 50 50,830 830 165 165,296 296 152 152,382 382 100 100,352 352 87 87,079 079 1,348,682 New Mexico 21,382 37,861 41,888 38,361 33,636 32,858 38,768 36,045 34,186 36,490 22,741 37,509 411,725 Wyoming ‐ 6,683 10,771 ‐‐ 7,967 5,083 12,901 19,544 96,718 53,657 228,074 441,398 Canada 4,774 23,900 58,405 126,234 185,172 206,978 306,432 354,135 222,983 597,861 676,161 709,014 3,472,049 Others 4,373 8,338 605 5,750 11,259 ‐ 11,172 738 ‐‐ 16,015 63,961 122,211 Total Imports 155,840 296,536 241,081 341,590 446,227 411,079 481,424 509,575 456,999 883,451 892,309 1,180,662 6,296,773 2012 North Dakota 16,034 25,266 70,706 29,874 48,082 47,020 91,261 134,475 100,116 42,189 36,859 62,325 704,207 New Mexico 7,196 6,362 8,987 17,176 17,758 19,924 16,522 13,866 6,578 14,052 11,970 12,927 153,318 Canada 35,755 19,616 11,124 10,543 2,248 18,831 63,163 22,969 7,646 1,674 193,569 Others 7,473 11,945 9,450 8,339 124 37,331 Totall Imports 58,985 51,244 87,166 58,174 88,328 69,192 136,064 219,843 129,663 63,887 50,627 75,252 1,088,425

2011 North Dakota 77,148 77,772 86,783 101,378 107,029 106,380 97,493 94,034 98,981 48,416 130,709 86,542 1,112,665 Canada 562 568 8,153 544 10,852 7,269 10,253 15,811 18,529 41,714 41,041 155,296 Others 3,026 28,046 28,164 34,834 94,070 TotalTotal IImportsmports 80,736 78,340 94,936 101,922 117,881 113,649 97,493 104,287 114,792 94,991 200,587 162,417 1,362 ,031

2010 North Dakota 0 0 0 0 0 6,096 63,720 66,376 91,909 82,371 96,119 90,295 496,886 Total Imports 0 0 0 0 0 6,096 63,720 66,376 91,909 82,371 96,119 90,295 496,886

2009 Colorado 2,148 14,917 5,378 5,371 3,169 30,983 North Dakota 3,353 3,353 Washington 2,890 8,265 11,155 Total Imports ‐ 2,148 14,917 5,378 5,371 3,169 ‐‐ 3,353 2,890 8,265 45,491

BOZEMAN PASS WILDLIFE PRE-AND POST-FENCE MONITORING PROJECT

April C. Craighead1

Frank L. Craighead2

Lauren Oechsli3

1 Craighead Environmental Research Institute, 201 South Wallace Avenue, Suite B2D, Bozeman MT 59715. 406-585-8705 (phone and fax). Email: [email protected] 2 Craighead Environmental Research Institute, 201 South Wallace Avenue, Suite B2D, Bozeman MT 59715. 406-585-8705 (phone and fax). Email: [email protected] 3 Craighead Environmental Research Institute, 201 South Wallace Avenue, Suite B2D, Bozeman MT 59715. 406-585-8705 (phone and fax). Email: [email protected]

1 ABSTRACT Introduction The Bozeman Pass transportation corridor between Bozeman and Livingston, Montana, includes Interstate-90, frontage roads, and a railroad. The highway supports 8,000-12,000 daily vehicles during the winter and 10,000 to 15,000 daily vehicles during the summer. The interstate has essentially become a barrier and hazard to animal movements in the Bozeman Pass area. To determine the extent of the animal-vehicle conflicts and where conflicts may best be mitigated, CERI began collecting field data on Bozeman Pass in 2001. Data analysis led to recommendations to incorporate approximately 2 miles of wildlife fencing, cattle guards and landscaping design modifications into the reconstruction of a Montana Rail Link (MRL) overpass. These recommendations were accepted by the Montana Department of Transportation (MDT) and MRL in 2005 and a wildlife fence and four jump-outs were constructed in 2007. Adding relatively low cost wildlife mitigation measures to existing highway projects are effective in increasing highway permeability and reducing animal mortality, and could be incorporated into the Obama infrastructure initiative.

Methods Data on wildlife crossings and animal-vehicle collisions (AVC) were collected before and after installation of the fencing to evaluate if the fencing reduces animal-vehicle collisions, and to determine animal movements under the highway via existing culverts and the MRL overpass. Data collection includes seven tasks, as follows: 1. Road kill surveys between Bozeman and the Jackson Creek interchange. 2. Track bed monitoring of wildlife movements under the MRL bridge. 3. Remote camera monitoring of wildlife movements at fence ends 4. Infrared counter monitoring of wildlife movements at jump outs 5. Track bed monitoring of wildlife movements at fence ends and jump outs 6. Remote camera monitoring of wildlife movements in two culverts at east end of fence. 7. Opportunistic snow tracking under MRL bridge and in fenced area. Power analyses (power = 0.8; α = 0.05) indicated three to five years of post-fencing study would be optimal in order to make reasonable quantitative comparisons between the pre- and post- fencing ungulate-vehicle collision (UVC) data. This presentation reports on 2 years of data.

Results Nearly 2000 animals have been killed along 23 miles of Interstate 90 from 2001-June 2009. Since the installation of the wildlife fence about 1.5 miles long, two white-tailed deer has been killed within the fenced area and three have been killed at the fence ends. There has not been an increase in AVC at the ends of the fence. Preliminary results indicate an increased use of underpasses and culverts by wildlife.

Discussion Costs for this project were much lower than new wildlife crossing structures since the fencing was added on to a structure replacement project for an existing underpass. More wildlife appear to travel through the rebuilt underpass as well as through other existing crossing structures (culverts and county road bridge). This suggests that fencing alone can be added to help direct animals through existing structures.

2 Conclusion Wildlife fencing leading to existing crossing structures is a cost-effective method of reducing AVC and thus reducing risk to motorists as well as increasing connectivity for wildlife.

Recommendations Design improvements in jump-outs and fence-ends will be discussed.

INTRODUCTION There is a wealth of evidence that details the mainly negative impacts that roads have on wildlife populations. When animals are confronted with roads, they potentially face direct mortality, habitat fragmentation, loss of habitat connectivity and genetic isolation (Clevenger and Wierzchowski 2006, Clevenger et.al. 2001, Corlatti et. al. Forman et. al. 2003, Forman and Alexander 1998). When humans encounter wildlife on roadways the effects can also be life- threatening. Every year approximately 200 people die from animal-vehicle collisions (AVC). The cost of wildlife related collisions are staggering with an estimated $1 billion yearly being paid out by insurance companies for automobile repairs (Robbins 2007). In an effort to decrease human and wildlife mortality, transportation planners within the past few decades began incorporating wildlife mitigation features in road construction and upgrades in the United States (Forman et. al. 2003). Methods typically include installing wildlife fencing and jump outs in conjunction with a variety of underpasses, overpasses or culverts that animals may use to traverse safely from one side of road to the other (Clevenger et. al. 2001, Forman et.al. 2003,). These structures target a wide variety of species depending on the size of the structure, ranging from amphibians, reptiles and small mammals to large ungulates and carnivores (Forman et. al. 2003) While many of these structures are effective in reducing road kill they can be very expensive, costing millions of dollars for a wildlife overpass. In some instances, the cost of mitigation can be lessened by incorporating the structures into planned upgrades and rebuilds of roads already scheduled by departments of transportation.

In 2001, the Craighead Environmental Research Institute (CERI) began the Bozeman Pass Wildlife Linkage and Highway Safety study to identify accurate road kill locations and actual wildlife movement along Interstate 90 (I-90) between Bozeman and Livingston Montana. Analysis from that project, highlighted areas of higher than average road kill within the study area near Bozeman and other areas closer to Livingston. One of these areas of high road kill was in the vicinity of the Montana Rail Link (MRL) bridge that was scheduled to be rebuilt in 2005. From this data, the Montana Department of Transportation (MDT) incorporated wildlife fencing into its bridge replacement plans. In 2003, MDT and the Western Transportation Institute (WTI) contracted with CERI to monitor the pre- and post-mitigation data that would be used to comparatively assess the effect of the mitigation (wildlife fencing, jump-outs and cattle guards) on AVC and wildlife movements from one side of the highway to another after the MRL bridge was rebuilt. The post fencing mitigation study area was limited to the area between Bozeman and Jackson Creek (milepost 309.5- 319.0). Road kill data continued to be collected throughout the entire study area to identify other areas that may serve as mitigation sites in the future.

3 THE STUDY AREA Bozeman Pass on I-90 is located in southcentral Montana approximately 88 km (55 miles) north of Yellowstone National Park. The study area in and around Bozeman Pass encompasses approximately 908 km2 and includes the cities of Bozeman and Livingston . Interstate 90 bisects the area between Bozeman on the western edge and Livingston on the eastern edge. The Montana Rail Link line runs parallel to the freeway crossing underneath at milepost 321 and 314. A frontage road also runs parallel to the freeway for a portion of that distance. The distance between Bozeman and Livingston is approximately 33.6 km (21 miles). The highway supports 8,000-12,000 daily vehicles during the winter and 10,000 to 15,000 daily vehicles during the summer. Railway traffic through this area is also a factor, with approximately 30 trains using the tracks daily, moving through the MRL underpass at approximately 48 kph (30 mph) (Dewey Lonnes, personal comm.). Figure 1.

Bozeman Pass is surrounded by a mosaic of residential, agricultural and public lands. The landscape varies from shrub-grassland communities near Bozeman and Livingston to coniferous forests in the middle section of Bozeman pass. Elevation varies from 1398 meters at its low point near Livingston to 1733 meters at the top of the pass.

Bozeman Pass supports a large amount of wildlife habitat on both public and private lands and serves as a wildlife connectivity link between the Gallatin and Absorka mountain ranges in the south and the Bridger and Bangtail Mountains in the north. The wildlife habitat in the area is somewhat fragmented by human development and transportation routes. Regionally, Bozeman Pass has been identified as an important wildlife corridor connecting wildlife habitat in the Greater Yellowstone Ecosystem in the south, through the Bridger and Big Belt Mountains, to the Northern Continental Divide Ecosystem in the north (Craighead et. al. 2001, Hardy et.al. 2006, Walker and Craighead 1997, Reudiger et. al. 1999). Interstate 90 is the most significant barrier to wildlife movement in the area and in the region.

4

Figure 1. Bozeman Pass Study area

This area is rich in wildlife including: black bears (Ursus americanus), mountain lion (Puma concolor), bobcat (Felis rufus), elk (Cervus elephas), moose (Alces alces), mule deer (Odocoileus hemionus) and white-tailed deer (O. virginianus), red fox (Vulpes vulpes), coyote (Canis latrans) and a variety of smaller mammals, reptiles, and a diversity of bird species. Many of these species utilize this area on their seasonal and daily migration movements. Grizzly bears (Ursus arctos horribilis) are occasionally seen in the area but none have been documented crossing I-90 or recorded as road-kill.

The MRL bridge is located approximately at milepost 314.1 and spans the railroad and access right-of-ways underneath Interstate 90. After the bridge was rebuilt in 2005-2006 wildlife mitigation measures were installed, specifically wildlife fencing, jump outs, Texas or cattle guards and improved grading underneath the bridge to enhance wildlife movement. Wildlife exclusion fencing (1.2 meter (8 ft.) high) was installed along 1.44 km (.9 mile) of I-90, extending east and west from the bridge that crosses over the MRL railroad. The wildlife fencing is located between milepost 313.5-314.4 along both east and west bound lanes. Four jump outs were installed within the fenced areas to allow animals that became trapped on the freeway a place to ‘jump out’ to safety. These are constructed so that animals can jump away (exit) from the roadway but cannot walk back up onto the roadway (one-way). To discourage animals from

5 making “end runs” around the end of the fences, modifications were made to include cattle guards and modified fence ends. Two sets of double cattle guards or Texas guards were installed at the western termini of the fence at the Bear Canyon interchange access ramps. These were installed to deter animals from walking to the end of the fence and then walking up the on-ramp to the freeway. The eastern wildlife fence ends encompass a large double culvert and a steep embankment before tying into the traditional barbed wire fence that runs the length of the right- of-way.

METHODS Road kill data methods Road-kill data collection began in 2001. Biologists at CERI and volunteers drove along Interstate 90 over Bozeman Pass between Bozeman and Livingston and recorded the date, location (to the closest 1/10th mile using mile markers), and species of road-kills observed. Sex was recorded for carnivores and ungulates if possible. Volunteers usually traveled Bozeman Pass during the five weekdays on their way to work, and CERI personnel drove the pass during the weekend in search of road-kills. Interesting or unusual road-kills were further investigated by CERI personnel. This survey methodology continued through 2002. A more standardized survey method began in 2003, with CERI personnel driving Interstate 90 between Bozeman and Livingston three times a week to collect road kill data. Driver speed for CERI personnel was kept between 88-105 kph (55-65 mph) during the surveys. Thru June 30, 2009, the pass has been surveyed 1066 times representing 80,631 km (50,102 miles) between milepost 309.5- 333.0. It is also important to note that many more animals are killed then ever get recorded; animals get hit and then die some distance from the roadway, people pick up road kill for personal uses and road kill become obscured by vegetation or topographical features. In some cases scavengers such as coyotes will drag carcasses away from the roadside. Road kill data from CERI and other agencies only represent an index of the actual number of animals hit. Data collection will continue until June 30, 2011 in accordance with the MDT contract.

Searches of agency records provided additional wildlife collision data. Road kill data were obtained from a variety of sources including Montana Fish Wildlife and Parks (MFWP) and Montana Department of Transportation (MDT). Typically, MDT removes dead animals from the right-of-way if the animal poses a threat to driver safety. These animals are usually picked very early in the morning before CERI personnel were able to record them. Species that fall into this category typically include moose, elk, deer and other large animals and are removed promptly. However not all species are picked up promptly and carcasses will lie on the side of the road for a period of days or weeks. Some carcasses are never picked up. Supplemental data from MDT Maintenance reports that were included in this project are: carnivores, moose and elk. Deer species (mule and white-tailed) from MDT maintenance records were not included due to the difficulty in trying to reconcile duplicate records. Accurate records contain the date, location and any other pertinent information such as sex of the animal. These data were also entered into the GIS database.

Track bed survey methods

6 To determine the number and species of animals crossing underneath the bridge, a sand track bed was constructed on the north side of the railroad tracks underneath the MRL bridge. The track bed is approximately 46 meters (150 ft) long and is 2.5 meters (8 ft) wide. Due to the configuration of the freeway and railroad passing beneath it, the track bed covers approximately two-thirds the width of the passage. Since it was not possible to census the entire area for animal movements, the track bed observations provide an index of crossing activity.

Track bed surveys began in October, 2003 and continued through April, 2005 when bridge reconstruction began. During the construction phase, equipment, materials and fill were present at the track bed site making it impossible to maintain and monitor the track bed until construction was completed. Accordingly, the track bed was rebuilt in the fall of 2006. However the fencing was not completed until the spring of 2007. Post-fencing track bed monitoring therefore commenced in May 2007.

Before construction the track bed was counted and then raked every 3-4 days on average. The number of tracks counted was then divided by the number of collection days to provide a count of tracks per day. Post-construction, an alternate method was used: surveys were conducted 4 consecutive days every other week; the bed was completely raked at the beginning of the week and then counted and raked every day for the next four days to provide a count of tracks per day. This was done to avoid any confusion due to large numbers of tracks after multiple days of collection (Hardy et. al. 2006). Due to the difficulties in conducting surveys in the winter with tracks being frozen and weather events confounding track identification, surveys were conducted between May 1- October 31, 2007 through the present.

Jump-out monitoring methods Initially the jump-outs were monitored using small track beds constructed at the top of the jump- out and supplemented with trailmaster motion-sensor counters. The counters soon proved unreliable and were replaced with RECONYX motion-sensor cameras. Jump-out track beds were surveyed in conjunction with the main track bed survey (May 1- October 31). Jump-out cameras were downloaded periodically and batteries were replaced as needed.

Remote camera monitoring methods Before construction, cameras were placed in culverts at MP 314.6, MP314.8 and MP315. Photo- monitoring was initiated in 1998. The eastern culvert at mile marker 314.6 was monitored from February 19, 1998 until January 23, 2005. The western culvert at mile marker 314.6 was monitored from January 1, 1998 until July 22, 2004. The eastern culvert at mile marker 314.8 was monitored from January 14, 2002 until November 21, 2005, but the western culvert was not monitored because it was full of deep, fast-moving water. The western culvert at mile marker 315 was monitored from July 21, 2003 until July 17, 2005. The eastern culvert was not monitored because it was full of deep, fast-moving water The MP315 culvert had a camera stolen in July 2004, whereupon a new camera was hidden outside the culvert, after which it did not work as well. On August 17, 2004, a camera was added below the Montana Rail Link bridge,

7 where it was maintained until May 4, 2005. Trailmaster cameras were used with both passive IR beam or active IR beam triggers. A trial camera was also placed at the track bed to attempt to duplicate the results of track bed counts. Cameras were operated continually until the camera at MP 315 was stolen. At that point the other cameras were removed although a second camera at MP 314.6 in the easternmost culvert was also stolen before we could remove it.

After construction RECONYX digital motion-sensor cameras were used. Cameras were placed at the eastern fence ends attached to the guardrail with security boxes. At the western fence end a single camera was attached to the bridge supports at the county road underpass. Cameras were deployed in the culverts at MP 314.5 where they were attached to the ceiling of the culvert and secured with locking cables.

Cameras were maintained for constant monitoring. They were downloaded periodically and batteries were replaced as needed. In the case of the culvert cameras, maintenence could not be done during the periods of high water in spring runoff; however batteries were usually replaced just prior to high water so that they operated throughout.

ANALYSES Road kill Power analyses were applied to the pre-fencing Ungulate-Vehicle Collision (UVC) data to determine what degree of change in UVC rates would be statistically detectable when comparing rates before and after the mitigation fences were installed (Hardy et. al. 2006). Results from the power analyses (power = .8; a = 0.05) indicated a three to five year post-fencing study would be sufficient to allow quantitative comparisons to be made (Hardy et. al. 2006). The post construction monitoring period will include three years of data collection thru June 30, 2010. Data for this paper include road kill numbers thru June 30, 2009.

Research has indicated that while wildlife fencing decreases ungulate mortality within fenced areas, a majority of animals tend to get killed at the fence ends (Clevenger et. al. 2001). To accommodate this end run effect, a buffer of 0.2 miles (322 meters) of additional roadway were added to the analysis area considered as the fenced area (Hardy et. al. 2006). All data representing the fenced area thus includes the actual fenced section plus the buffered area (fence/buff).

Pre-fencing Pre-mitigation data indicated that UVC rates were significantly higher within the proposed mitigation zone then elsewhere along the highway using 2001-2004 data (Hardy et. al. 2006). We further refined the analysis by including all pre-mitigation UVC data (2001- April 4, 2005) and compared UVC rates inside the proposed fence/buff area to those outside the fence/buff area.

8 Interim Due to the longevity of this project, UVC numbers were broken into three separate categories within the mitigation zone; pre construction included 1544 days, interim (MRL bridge reconstruction and wildlife fencing installation) 819 days, and post construction 726 days (thru June 30, 2009). During the interim period, traffic patterns were restricted to two-lanes and speeds were reduced to 56 kph (35 mph). Recorded UVC numbers dropped sharply. To determine if the disruption and changes in traffic were affecting UVC rates, we ran a comparison of pre-fencing and interim UVC means both inside and outside the fence/buff zone. If there was a significant difference in UVC means then the data for the interim period would be omitted from further analysis.

Post-fencing To determine what effect the fenced area was having on UVC within the mitigation zone, we ran a series of two- and one-tailed t-tests on UVC means both spatially and temporally. Spatial data were examined to see if the fencing was having an effect on UVC inside and outside of the fence. Temporal data were examined to see if UVC rates were different pre- and post-fencing. After the fencing was completed, we wanted to investigate these three research questions: 1) Did UVC rates significantly decrease within the fence/buff zone during the post-fence period compared with the pre-fence period. 2) Did UVC rates outside the fence/buff zone differ pre- and post-fencing. 3) Are UVC rates in the fence/buff zone different from those rates outside the fenced area during the post-fencing period.

To address these questions, we tested these three null hypotheses. 1) UVC rates post fencing in the fence/buff zone did not differ from those pre-fencing. 2) UVC rates outside the fence/buff zone did not differ pre- and post-fencing. 3) Post fencing, UVC rates in the fence/buff zone did not differ from those outside the fence/buff zone.

Track bed In addition to reducing mortality caused by the highway, the mitigation project intended to ensure connectivity or passage across the highway corridor, allowing local and regional migration movement to continue. To test this, we analyzed the tracks per day observed in the track bed data to see if use had increased after fence installation. Track bed data were broken down into pre- and post-mitigation periods. Since the survey methods were slightly different between the pre- and post-fencing periods, only those data collected in a single 24 hour period were used to compare the pre-and post fencing means.

Fence ends, jump outs and Camera Data Data for the fence ends and jump outs using remote cameras has only been collected during the post fencing period and will be summarized for animals in the vicinity of the fence ends and jump outs. There are hundreds of photos from remote cameras at the culverts at mile post 314.6

9 but due differences in camera type and survey effort we were not able to compare pre-and post- fencing images with any statistical confidence. The culvert photos are useful as an index of animals using the culverts. Species and numbers of animals utilizing these different areas are summarized in the results section.

Track bed data for jump outs Track bed data for jump outs were only collected post fencing. Currently the numbers of animals utilizing the jump outs is limited. With another year of data collection, jump out data will provide additional information regarding animals attempting to exit the freeway. A list of species and numbers of tracks are summarized in the results section.

RESULTS Since 2001, 1,997 animals, representing 49 different species of mammals, birds and reptiles, have been recorded as road kill on Bozeman Pass between Bozeman and Livingston, Montana. Table 1. The majority of animals killed were ungulates (45%, 901 animals), followed by small mammals (33%, 648 animals), birds (9.6%, 191 animals), carnivores (6.7%, 135 animals) and domestics and unknown (5.3%, 107 animals).

Table 1. Total number of road kills recorded between milepost 309.5-330.0 from January 01, 2001 thru June 30, 2009 SPECIES TOTALS Badger 11 Beaver 9 Bird (Other)1 129 Bird (Owl)2 49 Bird (Raptor)3 13 Black Bear 25 Bobcat 4 Cat (Domestic) 35 Coyote 60 Deer (Mule) 181 Deer (Unk) 273 Deer (Whitetail) 389 Dog (Domestic) 4 Elk 49 Fox 23 Marmot 19 Mink 3 Moose 9 Mountain Lion 5 Pine Marten 1 Porcupine 35 Raccoon 174 Skunk 273 Small Mammal4 147

10 Snake 5 Unidentifiable 68 Weasel 3 Wolf 1 TOTALS 1997 1. Includes pheasant, Hungarian partridge, grouse, turkey, goose, duck, heron, raven, crow, magpie, cowbird, robin, pigeon, meadowlark, towhee, tanager, and unknown. 2. Includes great horned, long-eared, and unknown species. 3. Includes red-tailed hawk and northern harrier. 4. Includes rabbit, ground squirrels, and gopher.

UVC totals across the entire study area fluctuate yearly over the span of the study with a peak in 2003 and a low in 2006. (Figure 2). Seasonally, the highest number of ungulates were killed in the fall (October) followed by a smaller summer peak (June). Winter tends to have much fewer road kills (Figure 3).

160 142 140 116 120 108 111 106 103 100 88 86 80 60 41 40 20 0 2001 2002 2003 2004 2005 2006 2007 2008 2009

Figure 2. UVC by year (milepost 309.5-333.0) January, 2001- June 30, 2009.

11

Figure 3. UVCs by month (milepost 309.5-333.0) January, 2001-December 31, 2008

Pre-fencing Within the mitigation zone, there were significantly more UVCs within the proposed fence/buff area compared with the area outside (data set January 1, 2001-April 3, 2005; two-tailed T-test, P<.00). This finding justifies the placement of the mitigation fencing on this stretch of highway.

Interim During the interim period of construction and fencing, UVC rates were greatly reduced in the mitigation zone due to lower traffic speeds and two-lane traffic patterns (Table 3). The reduction in mean number of UVCs was significant between the pre-fencing and the interim period both inside and outside the fence/buff zone (paired t-test, P < .01 (outside), P < .02 (inside)). All interim data were therefore omitted from further analyses.

Table 3. UVCs in mitigation zone calculated as UVC per mile per year Stretch Pre Interim Post Fence/buff 10.9 3.8 4.3 Outside 6.9 4.8 7.4

Post-fencing We found that the mitigation fencing significantly reduced the overall UVC rates in the fence/buff area from the pre- to post-fencing period (one-tailed t-test, P<.02). In the two years of post monitoring, UVC rates were reduced from pre-fencing high of 49 animals in the fenced area alone to only 5 animals in the fenced area. Three of the five animals killed in the fenced area

12 were killed at the fence ends. Figure 4. Additionally, the fencing had no significant effect on the UVC rates outside the fence/buff area (two-tailed t-test, P<.59). Finally, we found that post- fencing UVC rates within the fence/buff area were still higher than outside the fence/buff area within the mitigation zone, however the difference might be considered only marginally significant (two-tailed t-test, P>.11). There was no evidence of increased mortality at the fence ends however this is preliminary data and another full year of data collection may result in different conclusions.

Pre- and Post-fencing UVCs within the Fence and Buffer Zones

60 Pre (4.23 yrs) 49 50 Post (1.99 yrs)

40

30

20

10 7 4 5 4 2 0 Western Buffer Fence Eastern Buffer

Figure 4. Pre- and post-fencing UVC’s within the fence and buffer zone

Track Bed After the mitigation fencing was installed, we found the number of daily ungulate crossings underneath the MRL bridge had significantly increased (two-tailed t-test, P< .01). This, along with the significant reduction in UVCs within the fence/buff area, indicates that this mitigation strategy is beneficial to ungulates in reducing road kill while maintaining connectivity of habitat.

Remote camera data for fence ends and jump outs and culverts Post fencing data indicated that animals are reliably being photographed in the vicinity of the fence ends and jump outs. These monitoring techniques are limited in determining if animals successfully cross the freeway. Table 4. Preliminary data indicate that some mammals are trying to cross at the fence ends. In a few instances, animals are successful in finding and using the jump outs.

13 The majority of photos taken were birds including, magpies, ravens, crows and robins which tended to flock near the jump outs. A variety of other mammals were photographed at the fence ends or in the vicinity of the jump outs.

Table 4. Animal occurrences near fence ends and jump outs (January 1, 08 -March 30, 09) using remote cameras. Species Fence Ends Jump outs NE NW SE SW Birds 7 72 10 19 0 Deer 9 1 1 2 0 Coyotes 4 4 0 0 0 Marmot 1 0 0 0 0 Raccoons 0 7 0 4 0 Rabbits 3 2 0 6 0 Skunk 1 1 0 0 0 Weasel 1 0 0 0 0 Black Bear 0 1 0 1 0 Human 2 1 0 2 1 Total 28 89 11 34 1

Pre-and post fencing photograph comparisons in the culverts are not applicable in this study. However, preliminary data show that the same suite of species are utilizing the culverts to pass underneath the freeway. Animals associated with aquatic habitats tend to use the culverts more than other animals with the exception of the black bear. Table 5. The data also indicate that the eastern culvert (which has little or no water most times of the year) is used more heavily than the western culvert (which contains about 2 feet of water usually).

Table 5. Remote Camera Occurrences in Culverts (milepost 314.6) Pre-fencing Post fencing Species 314.6 E 316.4 W 314.6 E 314.6 W

Beaver 5 0 2 0 Birds 9 0 7 0 Black bear 0 1 1 3 Domestic Dog 4 2 0 0 Duck 0 1 0 0 Frog 0 1 0 0 Mink 0 0 6 0 Mustelid 7 0 0 0 Nest 3 0 0 0 Raccoon 82 1 49 5 Unknown animal 4 0 0 0 Dipper 0 0 10 0 Human 8 0 3 2 Total 122 6 78 10

14 Track bed data for jump outs Table 6. Track bed data for survey period (Aug. 2, 07 –June 20, 09) Jump outs Species NE NW SE SW Black Bear 1 0 0 0 Cat (domestic) 0 1 2 1 Canid 2 0 2 0 Deer 1 1 2 0 Marmot 9 1 5 0 Rabbits 2 0 2 0 Small mammal 1 1 0 0 Snake 1 1 0 0 Total 17 5 13 1

During the post fencing monitoring period, there have been a total of 36 different tracks recorded representing a variety of mammals and reptiles at the jump outs. The majority of tracks have occurred at the NE and SE jump outs. We have found marmots living in the vicinity of the jump outs and using them as a latrine site, which over represents their presence.

DISCUSSION Our preliminary findings indicate that the installation of wildlife fencing and jump outs has significantly reduced UVC’s in the fence/buff area near the MRL bridge. Additional monitoring of the track bed underneath the bridge has shown an increased use by ungulates indicating the effectiveness of fencing in funneling animals away from the freeway and maintaining habitat connectivity. Over time, the area underneath the bridge may see increased use as animals discover it and become more accustomed to using it. Animals still try to cross at the fence ends as road kill data and photo monitoring document but our data do not indicate a significant increase of road kills at the fence ends. Data also indicate that animals are occasionally utilizing the jump outs as an effective means of exiting the freeway. Culvert monitoring has documented the long term use of a variety of animals and people utilizing the culvert as a means to cross underneath the freeway safely.

During the post-fencing monitoring period, there has been a total of five UVC’s in the fenced area (2 within the fence, 3 at the fence ends). With another year of data collection, those numbers will change but the overall effectiveness of the fencing is clearly a benefit to animals and drivers. At this time, there has not been an overall increase in UVC’s at the fence/buff zone.

While overall UVC rates are slightly higher within the fence/buff area than outside, some of those findings may be attributed to the overall distribution of ungulates in the vicinity of the MRL bridge. Initial analysis documented high UVC’s towards the western edge of the fenced area and points further west. Therefore, the fencing seems to be only straddling this hotspot; not completely covering it. In the future, if the fence could be extended to the west then UVC rates inside the fence/buff area may be comparable with outside fence/buff area. Areas to the west

15 and east already contain culverts that could be utilized by animals to cross if fencing were extended and ended at these culverts. The length of the fence could be effectively increased by installing a test section of electric fencing that continues eastward from the east end of the current fence. This electric fence could also tie into two more sets of culverts underneath the highway and thus deflect animals away from the highway and through the culverts. At the northeast end of the electric fencing it could tie into a steep hillside where end-runs of the fence would be minimal. At the southeast end it could stop in a section where the opposite side of the highway is steep hillside and cliff which would help discourage animals from attempting to cross there. Fence ends could be blocked more effectively with the use of an electrified mat that extends from one fence end to the other across the shoulders and the highway surface (East end of fencing project).

The Bozeman Pass project highlights the effectiveness of reducing UVC through wildlife mitigation strategies such as wildlife fencing, jump outs and modified earthwork. This suggests that fencing projects alone can be added to help direct animals through existing structures. It also highlights the need for innovative monitoring techniques pre- and post-mitigation to provide quantitative measures of effectiveness.

Costs for this project were much lower than new wildlife crossing structures since the fencing was added on to a structure replacement project for an existing underpass. While the cost of these mitigation techniques is not inexpensive, working with transportation managers and planners before planned rebuilds/upgrades can lessen the cost substantially. The cost of the planned MRL bridge rebuild in 2005-2006 was approximately six to eight million dollars (Deb Wambach, pers. comm.). The cost of the wildlife fencing and jump outs was approximately $100,000 which increased the cost of the re-build by only about 1.25%. While that may seem like a large expense, it is only a fraction of the cost that insurance companies pay out yearly for reported UVC. Taking into account the average cost of repairs to drivers of an ungulate collision ($6,000-$8,000), the costs of injury treatment, the indirect costs of accidents to police and medical personnel, and the ecological costs of highway barriers to wildlife populations, the overall benefits to society have already begun to be realized.

ACKNOWLEDGEMENTS We would like to thank all of the volunteers who have provided us with road kill data over the years as they drove to and from work. These include Kevin and Shannon Podruzny and Neal Anderson. We would like to thank Deb Wambach and Pierre Jomini at MDT for their help and support.

BIOGRAPHICAL SKETCH April C. Craighead received her BA in Ecology, Evolution and Behavior (EEB) from the University of California, San Diego in 1989. She received her MS in Biological Sciences from Montana State University, Bozeman in 2000. April has been working for the Craighead Environmental Research Institute (CERI) since 2000 on a variety of projects. Currently, she

16 continues to work on Bozeman Pass and road ecology issues and climate related projects involving the American pika.

Dr. Frank Lance Craighead is the Executive Director of the Craighead Environmental Research Institute. He is an experienced field ecologist, population geneticist, and conservation planner. His current research interests are focal or umbrella species, population and metapopulation persistence, gene flow, habitat connectivity, core and protected areas, and carnivore ecology. Dr. Craighead has published numerous scientific papers, completed two book chapters, and published one book, Bears of the World, for Colin Baxter/Voyageur Press. He is a member of the IUCN World Committee on Protected Areas, the Society for Conservation Biology, The Society for Conservation GIS and the Wildlife Society. He currently serves on the Montana Department of Fish, Wildlife, and Parks Connectivity Working Group to develop connectivity science and policy for the Western Governor’s Wildlife Corridor Initiative. He also directs the Craighead Center for Landscape Conservation, a conservation research and education program centered in Bozeman, Montana. The Center is a nexus for field and community work to see that the best science is used in making conservation land-use and policy decisions. Dr. Craighead and Center colleagues develop and refine conservation science tools and apply these tools to community- based conservation projects in the Rocky Mountains, the Madison River Valley, eastern Tibet, Bozeman Pass, British Columbia and Alaska.

Lauren M. Oechsli received her BA in Biological Sciences from Columbia University, N.Y. (1992) and her MS in Biological Sciences from Montana State University, Bozeman (2000). Her Master’s work focused on the impacts of exurban development on native vegetation and wildlife diversity. As a GIS Analyst and Manager for American Wildlands (2000-2006), Lauren modeled watershed and river integrity at the local scale for most of the US portion of the Yellowstone to Yukon region. She then worked as a GIS Analyst on various Road Ecology projects at Western Transportation Institute, MSU. Currently, she conducts data analysis, GIS modeling, and mapping on wildlife habitat and connectivity projects for Craighead Environmental Research Institute in Bozerman, MT.

BIBLIOGRAPHY Clevenger, Anthony P., Bryan Chruszcz, and Kari E. Gunson. “Highway mitigation fencing reduces wildlife-vehicle collisions.” Wildlife Society Bulletin 29 (2001): 646-664.

Clevenger, Anthony, P., and Nigel Waltho. “Factors influencing the effectiveness of wildlife underpasses in Banff National Park, Alberta, Canada.” Conservation Biology 14 (2000): 47-56.

Clevenger, Anthony P., and Jack Wierzchowski. "Maintaining and Restoring Connectivity in Landscapes Fragmented by Roads." In Maintaining Connections for Nature, edited by Kevin R. Crooks and M. Sanjayan, 502-35. Cambridge: Cambridge University Press, 2006.

Corlatti, Luca, Klaus Hacklander, and Fredy Frey-Roos. “Ability of wildlife overpasses to provide connectivity and prevent genetic isolation.” Conservation Biology 23 (2009): 548-556.

17 Craighead, April C., Frank L. Craighead and Elizabeth A. Roberts. “Bozeman pass wildlife linkage and highway safety study.” Paper presented at the 2001 Proceedings for the International Conference on Ecology and Transportation. Keystone, Colorado, September 24-28, 2001.

Forman, Richard T., and L. E. Alexsander. “Roads and their major ecological effects.” Annual Review of Ecology and Systematics 29 (1998): 207-231.

Forman, Richard T., Daniel Sperling, John A. Bissonette, Anthony P. Clevenger, Carol D. Cutshall, Virginia H. Dale, Lenore Fahrig, Robert France, Charles R. Goldman, Kevin Heanue, Julia A. Jones, Frederick J. Swanson, Thomas Turrentine and Thomas C. Winter. Road Ecology, Science and Solutions. Washington, Covelo, London: Island Press, 2003.

Hardy, Amanda, Julie Fuller, Scott Lee, Laura Stanley, and Ahmed Al-Kaisy. “Bozeman Pass Wildlife Channelization ITS Project.” Report to the Montana Department of Transportation. June 2006.

Robbins, Jim. “As Cars Hit More Animals on Roads, Toll Rises.” http://www.nytimes.com/2007/12/22/22/us/22crash.html

Ruediger, Bill, James Claar, and James Gore. “Restoration of carnivore habitat connectivity in the Northern Rockies.” In Proceedings of the Third International Conference on Wildlife Ecology and Transportation. FL-ER-73-99. edited by Gary Evink, P. Garrett, and D. Ziegler. Florida Department of Transportation, Tallahassee, FL. 1999.

Walker, Richard, and Lance Craighead. “Analyzing wildlife movement corridors in Montana using GIS.” Paper presented at the 1997 Proceedings International ESRI Users Conference.

18 Derailment sends section of train into the Feather River Canyon 10/26/2015

Search

Derailment sends section of train into the Feather River Canyon

Dave Marquis, ABC10 News 3:55 p.m. PST November 26, 2014

4

1

4

Police look for 3 suspects in alleged rape attack 01:56

Who's Hiring: Oct. 26, 2015 00:16

Local A.M. forecast: October 26 01:42

CONNECT TWEET LINKEDIN COMMENT EMAIL MORE OSU crash suspect faces second degree murder charges Eleven cars of a Union Pacific freight train derailed 01:26 along Highway 70 in the Feather River Canyon, in Plumas County early Tuesday, sending loads of corn and several rail cars plunging into the canyon. Davis police investigate sexual (Photo: Jake Miille / assault 02:14 www.jakemiillephotography.com) Work began almost immediately to replace track and pull cars out of the canyon, but rail traffic had to be diverted to other routes as work continued Tuesday night. Search for gunman who shot- A small army of workers descended on the site just east of the tiny community of 13-year-old girl 02S:0t.5 Francis High School Belden, about 50 miles northeast of Oroville. rallies for homecoming State Office of Emergency Services Deputy Director Kelly Huston said the state Oct. 23, 2015, 10:32 p.m. "dodged a bullet" because the train was only carrying corn. Huston said each week a Aftershock creates traffic train carrying 1 million gallons of highly volatile crude oil from the Bakken oil field in trouble 02:00 Montana and North Dakota travels down the canyon, with plans to add a second train Winning Powerball ticket shortly. The crude oil goes to refineries in California. remains unclaimed Oct. 23, 2015, 10:11 p.m. Huston said an oil spill could have caused serious contamination in the Feather River, Adopt Sawyer and Halle from which flows into Lake Oroville -- California's second largest reservoir that supplies the Stockton Animal Shelter%21 water to the the California Water Project and millions of people. 02:49 UC Davis unveils coffee Residents also worry about the possibility of an oil spill or explosion. lab Halloween-themed donuts at Oct. 23, 2015, 9:56 p.m. "It does worry me that they need to build up the containers that they're hauling that oil "Donut Madness" in Sacramento in so that it does not fall into the river and contaminate it, you know?" Belden resident 01:54 Wayne Richard said. http://www.abc10.com/story/news/local/california/2014/11/26/train-derailment-feather-river-canyon/70133634/ 1 / 2 Derailment sends section of train into the Feather River Canyon 10/26/2015

The rail cars that carry Bakken crude oil are obsolete and even railroads say the DOT 111 rail cars need to be retrofitted or replaced completely.

There have been eight major explosions in the United States caused by oil trains since 2012.

But Huston said the hidden danger here is not the danger of a massive explosion but the threat to California's water supply "during an epic drought."

Union Pacific workers expect to have the line reopened by sometime Wednesday morning. Bulldozers are cutting a road down to the base of the canyon so derailed cars can be hauled away and the spilled corn cleaned up. That's expected to take several more days.

A train carrying corn derailed in Feather River Canyon on Tuesday, Nov. 26, 2014. News10

CONNECT TWEET LINKEDIN COMMENT EMAIL MORE

The Fastest Way To Donald Trump's Homeowners Are In For Pay Off $10,000 In Statement About A Big Surprise In 2015 Credit Card Debt America's Wealth

LendingTree Money Morning Report Lending Tree

Three bodies found north of Teen charged in crash that Tempe PD: Dad deliberately Angels Camp killed dad, daughter drove family into lake

NEWS | 5 days ago NEWS | 6 days ago NEWS | 6 days ago

http://www.abc10.com/story/news/local/california/2014/11/26/train-derailment-feather-river-canyon/70133634/ 2 / 2 Road Ecology Center UC Davis

Title: Developing Fauna-Friendly Transport Structures: Analysis of the Impact of Specific Road Engineering Structures on Wildlife Mortality and Mobility Author: Elmiger, Christof, Kaden und Partner AG, Office for Ecology and Software Engineering, Switzerland Trocmé, Marguerite, Swiss Agency for the Environment Publication Date: 05-20-2007 Series: Recent Work Publication Info: Road Ecology Center Permalink: http://escholarship.org/uc/item/6gm8h39h Additional Info: Elmiger, Christof, and Marguerite Trocmé. “Developing Fauna-Friendly Transport Structures: Analysis of the Impact of Specific Road Engineering Structures on Wildlife Mortality and Mobility”. In Proceedings of the 2007 International Conference on Ecology and Transportation, edited by C. Leroy Irwin, Debra Nelson, and K.P. McDermott. Raleigh, NC: Center for Transportation and the Environment, North Carolina State University, 2007. pp. 212-219. Keywords: barrier effect, fauna passages, wildlife hazards, habitat connectivity Abstract: The barrier effect of roads is now well documented and solutions such as fauna passages are readily imple¬mented (Trocmé et al. 2002). Less well known is the mortality caused by specific engineering structures used along roads, such as drainage systems. This research focuses on censusing wildlife hazards caused by such structures and developing solutions. Structures such as drainage systems, kerbs, gullies, culverts, noise barriers, lighting, retaining walls, were all examined. Small fauna specialists and maintenance teams were interviewed to gather information on known impacts as well as solutions found. Wildlife hazards were identified. Drainage systems with gullies often provoke high mortality for amphibians and other small fauna. Other structures such as retaining walls increase fragmentation by creating complete barriers. Designs more permeable to wildlife need to be enhanced. Certain solutions such as escape ramps from drainage systems have been tested on a local scale. After identifying the problematic structures an analysis of Swiss road standards was made underlining which ones needed to be completed or modified so as to limit the impact of transport

eScholarship provides open access, scholarly publishing services to the University of California and delivers a dynamic research platform to scholars worldwide. structures on wildlife. Further studies will be necessary so as to develop standardised solutions taking into account wildlife, maintenance and safety issues.

Copyright Information: All rights reserved unless otherwise indicated. Contact the author or original publisher for any necessary permissions. eScholarship is not the copyright owner for deposited works. Learn more at http://www.escholarship.org/help_copyright.html#reuse

eScholarship provides open access, scholarly publishing services to the University of California and delivers a dynamic research platform to scholars worldwide. Developing Fauna-Friendly Transport Structures: Analysis of the Impact of Specific Road Engineering Structures on Wildlife Mortality and Mobility Christof Elmiger (41-52-721-18-44, [email protected]), Environmental Consultant, Kaden und Partner AG, Office for Ecology and Software Engineering, CH 8300 Frauenfeld, Switzerland Marguerite Trocmé (41-31-322-80-03, [email protected]), Senior Scientist, Swiss Agency for the Environment, CH 3003 Bern, Switzerland Abstract: The barrier effect of roads is now well documented and solutions such as fauna passages are readily imple- mented (Trocmé et al. 2002). Less well known is the mortality caused by specific engineering structures used along roads, such as drainage systems. This research focuses on censusing wildlife hazards caused by such structures and developing solutions. Structures such as drainage systems, kerbs, gullies, culverts, noise barriers, lighting, retaining walls, were all examined. Small fauna specialists and maintenance teams were interviewed to gather information on known impacts as well as solutions found. Wildlife hazards were identified. Drainage systems with gullies often provoke high mortality for amphibians and other small fauna. Other structures such as retaining walls increase fragmentation by creating complete barriers. Designs more permeable to wildlife need to be enhanced. Certain solutions such as escape ramps from drainage systems have been tested on a local scale. After identifying the problematic structures an analysis of Swiss road standards was made underlining which ones needed to be completed or modified so as to limit the impact of transport structures on wildlife. Further studies will be necessary so as to develop standardised solutions taking into account wildlife, maintenance and safety issues. Engineering Structures as Obstacles to Habitat Connectivity In the past 50 years urban sprawl and fast extension and densification of transport networks have caused with the intensification of agriculture high fragmentation of open spaces and natural areas. Biodiversity continues to diminish as many natural areas are too isolated and small to sustain viable wildlife populations. In countries with transport infrastructure networks as dense as in Switzerland, the preservation of links between natural habitats and the restora- tion of ecological corridors has become a priority. Part of the negative impact of transport networks can be mitigated through specific measures. The Swiss Association of Road and Traffic Experts (VSS) has emitted a series of norms on fauna passages with the goal of restoring as best possible connectivity (VSS 2004). However fauna passages do not solve all problems. A number of annexe structures cause high mortality and also have an impact on populations. The goal of this research was to collect field knowledge on the impact of various road and rail structures on animals and suggest mitigation measures. Depending on their design such structures can have negative effects, acting as traps (gullies) or positive effects, offering refuges for animals (stone walls) or movement corridors for wildlife along transportation axes (natural verges). The research report should serve as a reference for further standard revision and as a guide for engineers so as to avoid the use of struc- tures dangerous to animals and diminish causes of indirect mortality. Research Methods The study focused on gathering as much available information as possible, collecting known data about the negative side effects of infrastructure elements of road and railway systems and investigating potential issues not described so far. The impact of the following structures was examined: avalanche galleries, central reservation, curbs, drain- age systems, verges, fences, lighting, noise barriers, overhead contact wires, retaining structures, road pavement, track ballast and rails. To gain an overview a thorough study of literature was conducted. In a second step, around 100 telephone interviews were conducted to gather more information. For this, regional environmental authorities, scientists, conservationists, were contacted, as well as road maintenance personnel who are directly confronted with the results of the conflict between fauna and infrastructure. The large quantity of information that was gathered in this process was stored and processed with the help of a database system. Field investigations were undertaken to learn more about new ideas not documented so far. Examples of Problematic Infrastructures The following paragraphs present a selection of problematic structures with a strong impact on mortality and habitat connectivity of wildlife. The complete list of infrastructures and their main impact on the fauna is given in table 1. These structures are a problem when they cross natural habitat.

Chapter 5 212 ICOET 2007 Proceedings Table 1: List of problematic structures and their main impact on wildlife

Curbs as Obstacles for Small Animals Local roads in Switzerland are often not drained over the shoulder into a ditch, but by means of curbs, sewers, and a subterranean drainage system as it is standard for roads in residential areas. As distances between villages are short, there may also be sidewalks following the road. Curbstones from sidewalks and drainage systems are strong barriers difficult or impossible to overcome for small animals (invertebrates, amphibians, reptiles, small mammals) trying to cross the road and wanting to leave the roadway on either side (Ratzel 1993). Even adult amphibians somehow feel compelled to follow the vertical structure instead of jumping over it (Ratzel 1993). Animals blocked from leaving the roadway are subject to traffic mortality, predators, climatic adversities, or may find an exit only far from the original destination.

Figure 1. This curbstone is known to guide Amphibians directly into the tunnel.

Figure 2. On this sidewalk excessive tidiness in the form of granite blocks prevents that small animals from habitat on the other side of the road can reach the meadow.

Bridging the Gaps, Naturally 213 Roadside Management and Transportation Operations Retaining Walls as Barriers Retaining walls, often built as smooth concrete walls, can pose similar problems as curbs but on a bigger scale. In natural surroundings such walls, often 2-3 m high, act as complete barriers for terrestrial wildlife. The barrier effect of the walls depends on height and length. Animals may become trapped on roads and therefore be more exposed to traffic mortality.

Figure 3. Retaining walls often Figure 4. Even low retaining border close to the roadway, structures can be a strong barrier blocking animal movements and prevent free crossing of a between habitats on either side structure by small animals. (Photo of the road. courtesy to KARCH, Neuchâtel).

Drainage Systems as Amphibian Traps Besides creating curbstone-barriers for small animals, the extensive drainage system along Swiss roads poses a second risk: small animals fall through the gully-covers when following the curb on the search for an exit. Amphibians are most threatened by this issue: searching moist shelter they intentionally let themselves drop into sewer chutes. Some wastewater treatment plants count several thousand amphibians each year, that come flushed through the drainage system (Bally 1998). These numbers are a minimal estimate as only survivors are found leaving the rest in the chute (Ratzel 1993).

Figure 5. This gully traps many Figure 6. With no direct exit possibility, amphibians each year, even though trapped toads and frogs either die in there is no curbstone guiding the chute or will, in the course of the the animals to the entrance. The next rain storm, get flushed into the animals climb into the opening, sewer system via the siphon. (Photo expecting a humid shelter. courtesy to Amphibtec, Gelfingen)

Poorly Designed Culvert Culverts, leading water underneath the transport infrastructure, are often barriers to both terrestrial and aquatic wildlife due to insufficient design. Fauna friendly culvert design is well illustrated in available publications (e.g. Iuell et al. 2003).

Chapter 5 214 ICOET 2007 Proceedings Railroad-tracks Blocking Migration Similar to curbstones, railroad-tracks too can physically hinder animals from reaching habitat on the other side of the structure. Time and vibrations from trains usually create gaps between track ballast and rails that suffice for small animals to slip through underneath the rails (Roll 2004). Maintenance crews however regularly reshape the gravel bed meticulously, closing the gaps in the process and therefore eliminating crossing possibilities for small animals. As a consequence, animals may not cross at all or need to search long distances for a gap, risking high traffic mortality and exposing themselves to predators and climatic adversities. As on roads, the problem becomes most evident when amphibians mass-migrate in spring and mortality is high.

Figure 7. Newt and toad killed on migration. The tight alignment between gravel and rail did not permit crossing. (Photo courtesy of Esther Krummenacher, Hausen) Mortality and Barrier Effects of Noise Barriers Transparent noise barriers are well known to cause high casualties among songbirds as birds in flight often do not see the glass and collide with it (Schmid & Sierro 2000). However noise barriers also act as wildlife barriers, fragmenting habitat on verges. In Switzerland, the sunny, sparsely vegetated verges of the national railway network constitute an increas- ingly important refuge for reptiles amidst a landscape of urban sprawl and intensive managed farm lands (Meyer 2005). Herpetologists are concerned that the construction of noise barriers along the railway tracks may fragment this network by hindering movement both across the verge (barrier effect of the screen) and along the verge (barrier effect of the shade).

Figure 8. Noise barrier along a railroad line. Examples of Fauna Friendly Infrastructure Design The study (Rieder et al. 2007) gives a catalogue of more than 140 proposals of adaptations of engineering structures that reduce negative impacts to animals. Some of these mitigation measures still need testing. In the following para- graphs we summarize a selection of the most promising ideas. Slanted Curbs Drainage over the shoulder of the road is the best way to avoid increasing the barrier effect of roads on small fauna. If roads in natural surroundings require a curb, then the curb should be designed slanted, ideally at an angle of no more than 45 degrees (Weber 1998). Existing vertical curbs can be levelled by pouring concrete into the corner between road surface and curb. If the curb cannot be slanted as a whole, providing slants at regular intervals can be a func- tional compromise (Ratzel 1993). A less effective, temporary mitigation measure is to let adjacent vegetation overgrow the vertical curb, providing natural shelter and exit structures.

Bridging the Gaps, Naturally 215 Roadside Management and Transportation Operations Securing Drainage Systems for Amphibians Designing slanted curbs as described above is a good measure to reduce the risk that animals follow the curb and drop into drainage chutes along the way. Modifying the covers of sewers and their positioning along the curbstone are further measures to secure the drainage system from small animals. In order to reduce the risk of accidental trappings, the openings in sewer covers should be as narrow as the necessary water throughput permits. Ratzel (1993) recom- mends slits no wider than 16 mm. Drainage openings can be offset from the curb so animals following the curb will be guided around it.

Figure 9. An urban example demonstrating that storm water must not necessarily be collected at the edge of the roadway. For roads leading through more natural surroundings, such a design could serve as a measure to reduce animal mortality in drainage chutes. In the case of amphibians, slanting the curb and offsetting the chute positioning does not fully resolve the problem because of the strong attraction the dampness of gullies exerts on those animals. In some gully systems it is possible to reduce this effect of attraction by improving the drainage of the chute (Ratzel 1993). Covering openings with a fine mesh is very effective but requires much maintenance work as the mesh usually does not last long or gets clogged easily, preventing proper drainage of the street. It is therefore only to be used as a temporary measure. In Switzerland, the best solution where amphibian habitats are concerned is the installation of exit ramps from problematic chutes. Different systems of exit ramps have shown promising results and are currently being tested more thoroughly, for functionality as well as for ease of maintenance (Schelbert pers. comm.). Permeable Railroad-tracks Railroad tracks in sensitive areas, e.g. cutting through amphibian habitats, should be maintained in a way that there are gaps present between track ballast and rails at all times, permitting small animals to cross the tracks. Studies from operating companies in Switzerland have shown, that it does not harm the stability of the rails, if at regular intervals the road bed is graded 5 cm below standard level (E. Krummenacher, pers. comm.). The result of this extra effort in maintenance is a permeable railroad line that permits annual mass migrations in spring (fig. 10) as well as individual migration throughout the year.

Figure 10. A pair of toads, slipping through the gap between rails and road bed. (Photo courtesy of Esther Krummenacher, Hausen) Fauna-Friendly Retaining Walls If space permits, a strip of natural surface should be left between the pavement and the wall. Animals unable to climb can use this strip to leave the roadway and follow the vegetation to the nearest habitat. The barrier effect of the wall itself can be further softened by using structured materials such as natural rock that facilitate climbing. Gabions filled with coarse rocks allow reptiles, mice and other small animals to climb upward as well as inward. Walls created with

Chapter 5 216 ICOET 2007 Proceedings such gabions not only reduce the overall barrier effect of the structure, but also create new habitat for plants and animals (fig. 11). By providing adequate substrate behind the gabions, the wall may even offer valuable, frost-safe shelter for reptiles in winter (KARCH 2005). Another way to make walls more permeable is to break up the linear structure as shown in figure 13. As a mitigation measure, some walls can be improved by piling up a cone of rocks or by covering parts of the wall with gabions (fig. 12).

Figure 11. This retaining wall built with gabions can be climbed by various animals, reducing the strong barrier effect such structures normally exert. The crevices of the coarse material provide habitat to small animals and plants.

Figure 12. A pile of rocks (left side) or gabions filled with rocks (right side) can improve the permeability of a wall for small animals.

Figure 13. The barrier effect of the wall can be reduced by breaking up the linear structure. What’s shown in this photo for a small structure along a railway line, can be achieved for walls with a height of several metres too. The example in the picture is currently being observed as it is not clear if it will successfully permit amphibian migration. (Photo courtesy of Esther Krummenacher, Hausen)

Bridging the Gaps, Naturally 217 Roadside Management and Transportation Operations Designing Animal Friendly Noise Barriers If noise barriers must be transparent, then the glass should be intensively patterned in order to disclose the obstacle to the birds eyes (fig. 14). Broad stripes (width of 1 or 2 cm) placed closely (gaps of 5 or 10 cm respectively) have been proven to work very effectively (note: the commonly used self-adhesive silhouettes of birds of prey do not show any effect). It is also very important that all trees and shrubs in the direct vicinity of the transparent barrier are removed to further reduce the attraction to birds (Schmid & Sierro 2000). Newly developed UV-reflecting glass may constitute a good alternative to patterned glass, but in the end, the best solution to avoid infrastructure mortality for songbirds is to renounce transparency entirely (Schmid & Sierro 2000) and work with opaque materials instead, which usually possess better acoustical characteristics and need less maintenance.

Figure 14. Example of a transparent noise barrier with a striped pattern as recommended by Schmid & Sierro (2000) to disclose the glass to birds eyes. (Photo courtesy of Joggi Rieder, Kaden und Partner AG)

Figure 15. Design study for a reptile-friendly noise barrier. A well drained trench filled with sand and coarse rubble would be permeable for reptiles and other small animals and could serve as hiding-, nesting-, or winter- habitat. (Image courtesy to KARCH, Neuchâtel) Noise barriers in sensitive areas should feature openings of some sort in order to break up the strong barrier effect of this structure for small animals. The Swiss Association for the Conservation of Reptiles and Amphibians (KARCH) has developed different ideas, how such openings could be implemented (see figure 15; Meyer 2005). The effectiveness has not yet been tested. Fauna Friendly Engineering – A New Standard? Fauna friendly engineering should no longer be an exception but become a rule. It’s important that the awareness of conflicts between traffic infrastructures and the fauna rises, not only among conservationists, but most importantly among engineers. The fauna expert group of the Swiss Association of Road and Traffic Experts (VSS) aims at improv- ing the standards for the construction of road infrastructures in promoting fauna friendly designs. The fauna expert group provides information to other expert groups and critically reviews drafts of new standards and revisions of old standards. The latest product of this collaboration is a new technical standard on the construction of curbs, that now includes considerations on the influence of curb design on habitat connectivity of small animals as well as recom- mendations on how to mitigate the negative impact (VSS 2006). Other VSS norms that need to be updated in terms of fauna friendly design are technical standards about verges, drainage systems, noise barriers, retaining structures, central reservation. Standards about fences and the renovation of culverts are currently being revised and developed under the guidance of the VSS fauna expert group.

Chapter 5 218 ICOET 2007 Proceedings Biographical Sketch: Christof Elmiger, born 1977 in Switzerland, has studied biology at the University of Zurich and the Swiss Federal Institute of Technology Zurich attaining a master’s degree with a thesis on the ecology of blennies and gobies in Switzerland. Today he is working as an environmental consultant for Kaden und Partner AG, a small company in Frauenfeld. Born in Paris in 1961, Marguerite Trocmé grew up in Canada before moving to the U.S. and received her bachelor of science degree in biology from Brown University in Providence, Rhode Island in 1983. In 1985, a master’s degree in environmental engineering from the Ecole Polytechnique Fédérale (EPFL) of Lausanne, Switzerland followed. She then worked both for the Swiss World Wildlife Fund and the Swiss Ornithological Institute before joining the Swiss Agency for the Environment, Forests, and Landscape in 1989. She is responsible for the impact appraisal of federal infrastructure projects on nature and landscape. She was vice-chairman of the European COST 341 Project. She has led and edited studies and publications in the areas of the impact of high tension lines, roads, and aviation on natural ecosystems. She is president of the VSS fauna expert group. References Iuell, B., G.J. Bekker, R. Cuperus, J. Dufek, G. Fry, C. Hicks, V. Hlavac, V. Keller, C. Rosell, T. Sangwine, N. Torslov, B. le Maire Wandall (Eds.). 2003. Wildlife and Traffic - A European Handbook for Identifying Conflicts and Designing Solutions. KNNV, Utrecht, The Netherlands. KARCH. 2005. Aménagements à reptiles. Koordinationsstelle für Amphibien- und Reptilienschutz in der Schweiz. Meyer, A. 2005. Reptilienschutz im Rahmen der Lärmsanierungsprojekte der Eisenbahnen. Koordinationsstelle für Amphibien- und Reptilienschutz in der Schweiz, Schweizerische Bundesbahnen and BLS. Ratzel, M. 1993. Strassenentwässerung - Fallenwirkung und Entschärfung unter besonderer Berücksichtigung der Amphibien. Bezirksstelle für Naturschutz und Landschaftspflege, Karlsruhe. Rieder, J., C. Elmiger, S. Schneider, R. Fankhauser. 2007. Vernetzung von Lebensräumen bei der Gestaltung von Verkehrsträgern. Eidgenössisches Departement für Umwelt, Verkehr, Energie und Kommunikation UVEK, Bern. 99 pp+CD-ROM. Roll, E. 2004. Hinweise zur ökologischen Wirkungsprognose in UVP, LBP und FFH-Verträglichkeitsprüfungen bei Aus- und Neubaumaßnahmen von Eisenbahnen des Bundes. Eisenbahn-Bundesamt, 50733 Köln. Schmid, H., A. Sierro. 2000. Test of measures to prevent bird-strikes on transparent noise-protection walls. Natur und Landschaft 75: 426-430. http://www.windowcollisions.info/e/bibliography.html. Trocmé, M., S. Cahill, H. J. G. De Vries, H. Farall, L. Folkeson, G. Fry, C. Hicks, J. Peymen (Eds.) 2002. COST 341 - Habitat Fragmentation due to Transportation Infrastructure: The European Review. European Commission Directorate General Transport. VSS. 2004. Fauna und Verkehr - Schutzmassnahmen. SN 640 694. Schweizerischer Verband der Strassen und Verkehrsfachleute, Zürich. www.vss.ch. VSS. 2006. Abschlüsse für Verkehrsflächen - Qualität, Form und Ausführung. SN 640 481. Schweizerischer Verband der Strassen und Verkehrsfachleute, Zürich. www.vss.ch. Weber, D. 1998. Einzelidee 6.07 - Schräge Randsteine. Bundesamt für Umwelt, Bern. Schriftenreihe Umwelt Nr. 280.

Bridging the Gaps, Naturally 219 Roadside Management and Transportation Operations

KAMALA D. HARRIS State of California Attorney General DEPARTMENT OF JUSTICE

Environmental Justice at the Local and Regional Level Legal Background

Cities, counties, and other local governmental entities have an important role to play in ensuring environmental justice for all of California’s residents. Under state law:

“[E]nvironmental justice” means the fair treatment of people of all races, cultures, and incomes with respect to the development, adoption, implementation, and enforcement of environmental laws, regulations, and policies.

(Gov. Code, § 65040.12, subd. (e).) Fairness in this context means that the benefits of a healthy environment should be available to everyone, and the burdens of pollution should not be focused on sensitive populations or on communities that already are experiencing its adverse effects.

Many local governments recognize the advantages of environmental justice; these include healthier children, fewer school days lost to illness and asthma, a more productive workforce, and a cleaner and more sustainable environment. Environmental justice cannot be achieved, however, simply by adopting generalized policies and goals. Instead, environmental justice requires an ongoing commitment to identifying existing and potential problems, and to finding and applying solutions, both in approving specific projects and planning for future development.

There are a number of state laws and programs relating to environmental justice. This document explains two sources of environmental justice-related responsibilities for local governments, which are contained in the Government Code and in the California Environmental Quality Act (CEQA).

Government Code

Government Code section 11135, subdivision (a) provides in relevant part:

No person in the State of California shall, on the basis of race, national origin, ethnic group identification, religion, age, sex, sexual orientation, color, or disability, be unlawfully denied full and equal access to the benefits of, or be unlawfully subjected to discrimination under, any program or activity that is conducted, operated, or administered by the state or by any state agency, is funded directly by the state, or receives any financial assistance from the state….

While this provision does not include the words “environmental justice,” in certain circumstances, it can require local agencies to undertake the same consideration of fairness in the distribution of environmental benefits and burdens discussed above. Where, for example, a general plan update is funded by or receives financial assistance from the state or a state agency, the local government should take special care to ensure that the plan’s goals, objectives, policies and implementation measures (a) foster equal access to a clean environment and public health benefits (such as parks, sidewalks, and public transportation); and (b) do not result in

concentration of polluting activities near communities that fall into the categories defined in Government Code section 11135.1 In addition, in formulating its public outreach for the general plan update, the local agency should evaluate whether regulations governing equal “opportunity to participate” and requiring “alternative communication services” (e.g., translations) apply. (See Cal. Code Regs., tit. 22, §§ 98101, 98211.)

Government Code section 11136 provides for an administrative hearing by a state agency to decide whether a violation of Government Code section 11135 has occurred. If the state agency determines that the local government has violated the statute, it is required to take action to “curtail” state funding in whole or in part to the local agency. (Gov. Code, § 11137.) In addition, a civil action may be brought in state court to enforce section 11135. (Gov. Code, § 11139.)

California Environmental Quality Act (CEQA)

Under CEQA, “public agencies should not approve projects as proposed if there are feasible alternatives or feasible mitigation measures available which would substantially lessen the significant environmental effects of such projects ….” (Pub. Res. Code, § 21002.) CEQA does not use the term “environmental justice.” Rather, CEQA centers on whether a project may have a significant effect on the physical environment. Under CEQA, human beings are an integral part of the “environment.” An agency is required to find that a “project may have a ‘significant effect on the environment’” if, among other things, “[t]he environmental effects of a project will cause substantial adverse effects on human beings, either directly or indirectly[.]” (Pub. Res. Code, § 21083, subd. (b)(3); see also CEQA Guidelines,2 § 15126.2 [noting that a project may cause a significant effect by bringing people to hazards].) As set out below, by following well- established CEQA principles, local governments can help achieve environmental justice.

CEQA’s Purposes

The importance of a healthy environment for all of California’s residents is reflected in CEQA’s purposes. In passing CEQA, the Legislature determined:

• “The maintenance of a quality environment for the people of this state now and in the future is a matter of statewide concern.” (Pub. Res. Code, § 21000, subd. (a).)

• We must “identify any critical thresholds for the health and safety of the people of the state and take all coordinated actions necessary to prevent such thresholds from being reached.” (Id. at subd. (d).)

1 To support a finding that such concentration will not occur, the local government likely will need to identity candidate communities and assess their current burdens. 2 The CEQA Guidelines (Cal. Code Regs., tit. 14, §§ 15000, et seq.) are available at http://ceres.ca.gov/ceqa/.

Office of the California Attorney General – Environmental Justice – Updated: 05/8/12 Page 2 of 6

• “[M]ajor consideration [must be] given to preventing environmental damage, while providing a decent home and satisfying living environment for every Californian.” (Id. at subd. (g).)

• We must “[t]ake all action necessary to provide the people of this state with clean air and water, enjoyment of aesthetic, natural, scenic, and historic environmental qualities, and freedom from excessive noise.” (Pub. Res. Code, § 21001, subd. (b).)

Specific provisions of CEQA and its Guidelines require that local lead agencies consider how the environmental and public health burdens of a project might specially affect certain communities. Several examples follow.

Environmental Setting and Cumulative Impacts

There are a number of different types of projects that have the potential to cause physical impacts to low-income communities and communities of color. One example is a project that will emit pollution. Where a project will cause pollution, the relevant question under CEQA is whether the environmental effect of the pollution is significant. In making this determination, two long- standing CEQA considerations that may relate to environmental justice are relevant – setting and cumulative impacts.

It is well established that “[t]he significance of an activity depends upon the setting.” (Kings County Farm Bureau v. City of Hanford (1990) 221 Cal.App.3d 692, 718 [citing CEQA Guidelines, § 15064, subd. (b)]; see also id. at 721; CEQA Guidelines, § 15300.2, subd. (a) [noting that availability of listed CEQA exceptions “are qualified by consideration of where the project is to be located – a project that is ordinarily insignificant in its impact on the environment may in a particularly sensitive environment be significant.”]) For example, a proposed project’s particulate emissions might not be significant if the project will be located in a sparsely populated area, but may be significant if the project will be located in the air shed of a community whose residents may be particularly sensitive to this type of pollution, or already are experiencing higher-than-average asthma rates. A lead agency therefore should take special care to determine whether the project will expose “sensitive receptors” to pollution (see, e.g., CEQA Guidelines, App. G); if it will, the impacts of that pollution are more likely to be significant.3

In addition, CEQA requires a lead agency to consider whether a project’s effects, while they might appear limited on their own, are “cumulatively considerable” and therefore significant. (Pub. Res. Code, § 21083, subd. (b)(3).) “‘[C]umulatively considerable’ means that the incremental effects of an individual project are considerable when viewed in connection with the effects of past projects, the effects of other current projects, and the effects of probable future projects.” (Id.) This requires a local lead agency to determine whether pollution from a

3 “[A] number of studies have reported increased sensitivity to pollution, for communities with low income levels, low education levels, and other biological and social factors. This combination of multiple pollutants and increased sensitivity in these communities can result in a higher cumulative pollution impact.” Office of Environmental Health Hazard Assessment, Cumulative Impacts: Building a Scientific Foundation (Dec. 2010), Exec. Summary, p. ix, available at http://oehha.ca.gov/ej/cipa123110.html.

Office of the California Attorney General – Environmental Justice – Updated: 05/8/12 Page 3 of 6

proposed project will have significant effects on any nearby communities, when considered together with any pollution burdens those communities already are bearing, or may bear from probable future projects. Accordingly, the fact that an area already is polluted makes it more likely that any additional, unmitigated pollution will be significant. Where there already is a high pollution burden on a community, the “relevant question” is “whether any additional amount” of pollution “should be considered significant in light of the serious nature” of the existing problem. (Hanford, supra, 221 Cal.App.3d at 661; see also Los Angeles Unified School Dist. v. City of Los Angeles (1997) 58 Cal.App.4th 1019, 1025 [holding that “the relevant issue … is not the relative amount of traffic noise resulting from the project when compared to existing traffic noise, but whether any additional amount of traffic noise should be considered significant in light of the serious nature of the traffic noise problem already existing around the schools.”])

The Role of Social and Economic Impacts Under CEQA

Although CEQA focuses on impacts to the physical environment, economic and social effects may be relevant in determining significance under CEQA in two ways. (See CEQA Guidelines, §§ 15064, subd. (e), 15131.) First, as the CEQA Guidelines note, social or economic impacts may lead to physical changes to the environment that are significant. (Id. at §§ 15064, subd. (e), 15131, subd. (a).) To illustrate, if a proposed development project may cause economic harm to a community’s existing businesses, and if that could in turn “result in business closures and physical deterioration” of that community, then the agency “should consider these problems to the extent that potential is demonstrated to be an indirect environmental effect of the proposed project.” (See Citizens for Quality Growth v. City of Mt. Shasta (1988) 198 Cal.App.3d 433, 446.)

Second, the economic and social effects of a physical change to the environment may be considered in determining whether that physical change is significant. (Id. at §§ 15064, subd. (e), 15131, subd. (b).) The CEQA Guidelines illustrate: “For example, if the construction of a new freeway or rail line divides an existing community, the construction would be the physical change, but the social effect on the community would be the basis for determining that the effect would be significant.” (Id. at § 15131, subd. (b); see also id. at § 15382 [“A social or economic change related to a physical change may be considered in determining whether the physical change is significant.”])

Alternatives and Mitigation

CEQA’s “substantive mandate” prohibits agencies from approving projects with significant environmental effects if there are feasible alternatives or mitigation measures that would substantially lessen or avoid those effects. (Mountain Lion Foundation v. Fish and Game Commission (1997) 16 Cal.4th 105, 134.) Where a local agency has determined that a project may cause significant impacts to a particular community or sensitive subgroup, the alternative and mitigation analyses should address ways to reduce or eliminate the project’s impacts to that community or subgroup. (See CEQA Guidelines, § 15041, subd. (a) [noting need for “nexus” between required changes and project’s impacts].)

Depending on the circumstances of the project, the local agency may be required to consider alternative project locations (see Laurel Heights Improvement Assn. v. Regents of University of California (1988) 47 Cal.3d 376, 404) or alternative project designs (see Citizens of Goleta

Office of the California Attorney General – Environmental Justice – Updated: 05/8/12 Page 4 of 6

Valley v. Board of Supervisors (1988) 197 Cal.App.3d 1167, 1183) that could reduce or eliminate the effects of the project on the affected community.

The lead agency should discuss and develop mitigation in a process that is accessible to the public and the affected community. “Fundamentally, the development of mitigation measures, as envisioned by CEQA, is not meant to be a bilateral negotiation between a project proponent and the lead agency after project approval; but rather, an open process that also involves other interested agencies and the public.” (Communities for a Better Environment v. City of Richmond (2010) 184 Cal.App.4th 70, 93.) Further, “[m]itigation measures must be fully enforceable through permit conditions, agreements, or other legally binding instruments.” (CEQA Guidelines, § 15126.4, subd. (a)(2).)

As part of the enforcement process, “[i]n order to ensure that the mitigation measures and project revisions identified in the EIR or negative declaration are implemented,” the local agency must also adopt a program for mitigation monitoring or reporting. (CEQA Guidelines, § 15097, subd. (a).) “The purpose of these [monitoring and reporting] requirements is to ensure that feasible mitigation measures will actually be implemented as a condition of development, and not merely adopted and then neglected or disregarded.” (Federation of Hillside and Canyon Assns. v. City of Los Angeles (2000) 83 Cal.App.4th 1252, 1261.) Where a local agency adopts a monitoring or reporting program related to the mitigation of impacts to a particular community or sensitive subgroup, its monitoring and reporting necessarily should focus on data from that community or subgroup.

Transparency in Statements of Overriding Consideration

Under CEQA, a local government is charged with the important task of “determining whether and how a project should be approved,” and must exercise its own best judgment to “balance a variety of public objectives, including economic, environmental, and social factors and in particular the goal of providing a decent home and satisfying living environment for every Californian.” (CEQA Guidelines, § 15021, subd. (d).) A local agency has discretion to approve a project even where, after application of all feasible mitigation, the project will have unavoidable adverse environmental impacts. (Id. at § 15093.) When the agency does so, however, it must be clear and transparent about the balance it has struck.

To satisfy CEQA’s public information and informed decision making purposes, in making a statement of overriding considerations, the agency should clearly state not only the “specific economic, legal, social, technological, or other benefits, including region-wide or statewide environmental benefits” that, in its view, warrant approval of the project, but also the project’s “unavoidable adverse environmental effects[.]” (Id. at subd. (a).) If, for example, the benefits of the project will be enjoyed widely, but the environmental burdens of a project will be felt particularly by the neighboring communities, this should be set out plainly in the statement of overriding considerations.

Office of the California Attorney General – Environmental Justice – Updated: 05/8/12 Page 5 of 6

* * * *

The Attorney General’s Office appreciates the leadership role that local governments have played, and will continue to play, in ensuring that environmental justice is achieved for all of California’s residents. Additional information about environmental justice may be found on the Attorney General’s website at http://oag.ca.gov/environment.

Office of the California Attorney General – Environmental Justice – Updated: 05/8/12 Page 6 of 6 Copyright © 2009 by the author(s). Published here under license by the Resilience Alliance. Fahrig, L., and T. Rytwinski. 2009. Effects of roads on animal abundance: an empirical review and synthesis. Ecology and Society 14(1): 21. [online] URL: http://www.ecologyandsociety.org/vol14/iss1/ art21/

Synthesis, part of a Special Feature on Effects of Roads and Traffic on Wildlife Populations and Landscape Function Effects of Roads on Animal Abundance: an Empirical Review and Synthesis

Lenore Fahrig 1 and Trina Rytwinski 1

ABSTRACT. We attempted a complete review of the empirical literature on effects of roads and traffic on animal abundance and distribution. We found 79 studies, with results for 131 species and 30 species groups. Overall, the number of documented negative effects of roads on animal abundance outnumbered the number of positive effects by a factor of 5; 114 responses were negative, 22 were positive, and 56 showed no effect. Amphibians and reptiles tended to show negative effects. Birds showed mainly negative or no effects, with a few positive effects for some small birds and for vultures. Small mammals generally showed either positive effects or no effect, mid-sized mammals showed either negative effects or no effect, and large mammals showed predominantly negative effects. We synthesized this information, along with information on species attributes, to develop a set of predictions of the conditions that lead to negative or positive effects or no effect of roads on animal abundance. Four species types are predicted to respond negatively to roads: (i) species that are attracted to roads and are unable to avoid individual cars; (ii) species with large movement ranges, low reproductive rates, and low natural densities; and (iii and iv) small animals whose populations are not limited by road-affected predators and either (a) avoid habitat near roads due to traffic disturbance or (b) show no avoidance of roads or traffic disturbance and are unable to avoid oncoming cars. Two species types are predicted to respond positively to roads: (i) species that are attracted to roads for an important resource (e.g., food) and are able to avoid oncoming cars, and (ii) species that do not avoid traffic disturbance but do avoid roads, and whose main predators show negative population-level responses to roads. Other conditions lead to weak or non-existent effects of roads and traffic on animal abundance. We identify areas where further research is needed, but we also argue that the evidence for population- level effects of roads and traffic is already strong enough to merit routine consideration of mitigation of these effects in all road construction and maintenance projects.

Key Words: environmental impact; landscape connectivity; mortality; population density; road network; road density; road effect zone; road mitigation; species distribution; species richness; traffic density; traffic volume

INTRODUCTION and traffic at the population level,” and in support of this statement they cite a review paper published In their research agenda for road ecology, in 1991. So, the claim that there are only a few road Roedenbeck et al. (2007) identify the most pressing ecology studies at the population level (Roedenbeck research question as: “Under what circumstances et al. 2007) is based on reviews and assertions that do roads affect population persistence?” They argue are now 8–17 years old. that this question remains unanswered because “very few studies evaluate the effects of roads at the Meanwhile, over the past 10 years “road ecology” population level.” In support of this claim, has emerged as a bona fide subdiscipline within Roedenbeck et al. (2007) cite review papers ecology, as evidenced by road-ecology sessions at published in 2000 and earlier. In one of these review ecology conferences and transportation conferences, papers, Underhill and Angold (2000) state that “[h] a dedicated biennial road-ecology scientific ard information is still lacking for the effect of roads meeting (International Conference on Ecology and

1Carleton University, Geomatics and Landscape Ecology Laboratory, Department of Biology Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

Transportation), the emergence of road-ecology habitat is effectively lost to the species. Car research centers (e.g., Road Ecology Center, avoidance, on the other hand, allows the animal to University of California at Davis; Center for cross the road without being killed on it. An Transportation and the Environment, North additional behavioral response to roads is attraction Carolina State University; Western Transportation to the road, which increases the frequency with Institute, Montana State University), and a textbook which animals enter the road and, therefore, on road ecology (Forman et al. 2003). This interest increases the mortality risk (Forman et al. 2003). in the ecological effects of roads has increased along with the ever-expanding transportation network. Hypotheses in the second set argue that larger The main concern among conservationists and animals are more vulnerable to roads because they environmental planners is that roads and traffic may are more mobile, have lower reproductive rates, and be reducing or even eliminating wildlife populations occur naturally at lower densities than do small (Trombulak and Frissell 2000, Forman et al. 2003). animals (Gibbs and Shriver 2002). Individuals of Is this concern backed up by empirical evidence? A highly mobile species, i.e., species that move current review of the state of population-level frequently and/or over large distances, are more research into road effects is clearly needed. likely to interact with a given road network, thus Therefore, the first objective of this paper is to increasing the chance of road mortality (Carr and conduct a complete review of the empirical Fahrig 2001). Because of their lower reproductive literature on effects of roads on animal population rates and lower natural densities (larger home abundance and distribution, to provide an up-to-date ranges), populations of large animals are less able summary of the state of knowledge in this area. than populations of small animals to rebound from low numbers resulting from road mortality, or to Our second objective is to develop a set of working persist at low numbers due to the animal’s avoidance hypotheses and predictions in answer to of areas with high road density (Gibbs and Shriver Roedenbeck et al.’s (2007) question above: under 2002). In addition, roads could indirectly cause what circumstances do roads affect population increases in populations of smaller animals, if these persistence? Our approach was to compare the animals are prey for larger animals whose findings of our literature review with hypotheses populations are reduced by roads, i.e., the road effect that have been proposed as explanations for road could cause release from predation (Rytwinski and effects. These hypotheses fall into two main sets: Fahrig 2007). hypotheses based on species behavioral responses to roads and traffic and hypotheses based on species In this paper, we review the empirical literature on attributes that are correlated with body size. effects of roads and traffic on animal abundance and distribution. In addition, we synthesize this In the first set, Jaeger et al. (2005) proposed that information, in the context of the ideas above, to there are three behavioral responses to roads and develop what we believe to be the state-of-the- traffic: (i) avoidance of the road surface, (ii) science on the circumstances under which roads avoidance of traffic emissions and disturbance affect population abundance and distribution. (noise, lights, chemical emissions), and (iii) the ability of the animal to move out of the path of an oncoming vehicle (labeled “car avoidance” by METHODS Jaeger et al. (2005)). Avoidance of the road surface reduces animal mortality on roads but also reduces The purpose of the literature review was to collect accessibility of habitats and other resources. Note and synthesize all published empirical information that road-surface avoidance also includes situations on the effects of roads and traffic on animal where the animal may not behaviorally avoid the abundance. We used “animal abundance” as a rather road, but the road design represents a physical general term to include population size (or relative barrier to animal movement (e.g., a fenced road). size), population density (or relative density), Jaeger and Fahrig (2004) referred to complete road species presence or absence, or species richness (i. avoidance as the “fence effect,” emphasizing its e., species presence or absence summed across functional equivalency to a physical barrier. species). The studies in our review fall into three Avoidance of traffic disturbance and emissions general categories. The first category includes reduces habitat quality within the vicinity of roads; studies that document animal abundances at the higher the amount of traffic on the road, the more different distances from a road. Some of these Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

studies considered only two distances: adjacent to The studies included animals from a wide range of the road vs. farther from the road. The second taxa (invertebrates, herptiles, birds, and mammals), general category includes studies comparing animal trophic levels (herbivores, carnivores, omnivores, abundances in different landscapes or regions with and scavengers) and habitats (forests, grasslands, different road densities. Studies that compare road and wetlands). Studies were located predominantly densities within individual animals’ territories in Europe and North America, but there were also (presence) with road densities in areas outside studies in Australia, Africa, and India. animal territories (absence) are a subset within this category. The third general category includes Some general patterns are evident from Table 1. studies that document the effects of roads and traffic First, the number of documented negative effects of on animal reproduction or mortality, along with roads on animal abundance outnumbered the calculations of the consequences of these effects for number of positive effects by a factor of 5; overall, animal abundance. 114 responses were negative, 22 were positive, and 56 showed no effect. Note, in some cases, there was We attempted a complete literature review, with the more than one result for a particular species because following restrictions. First, the papers had to some species were included in more than one study present a quantitative analysis relating animal (Table 1). Second, there were some clear differences abundance to roads and traffic. We did not include among the groups in Table 1. Amphibians and studies of road or traffic effects on animal mortality, reptiles tended to show negative effects. Birds reproduction, movement, or genetic differentiation, showed mainly negative or no effects, with a few unless the authors quantitatively demonstrated the positive effects for some small birds and for impact of the effect(s) on animal abundance. For vultures. Small mammals generally showed either example, Hels and Buchwald (2001) estimated that positive effects or no effect, mid-sized mammals 5%–25% of some frog populations are killed by showed either negative effects or no effect, and large traffic mortality. However, as they did not mammals showed predominantly negative effects. determine the effect of this mortality on population General patterns for invertebrates were not abundance, we did not include the study in our apparent, because of the small number of studies for review. We included all studies showing negative this group. or positive effects of roads and traffic on animal abundance except when the road effect and habitat In the following three sections, we synthesize the were completely confounded. For example, studies information in Table 1 into a set of hypotheses of species that preferentially live in or on road verges predicting species responses to roads and traffic. and studies comparing population sizes in grassy This is based on the patterns in Table 1 and roadside verges vs. neighboring forest patches information on: (i) species behavioral responses to completely confound a habitat effect with the road roads and traffic, (ii) species reproductive rates, effect, so were not included. Note, however, that movement ranges, and natural densities, and (iii) many of the studies included in our review did trophic interactions. contain correlations or likely correlations between roads and traffic and other variables that could have been fully or partly responsible for the patterns REASONS FOR NEGATIVE ROAD attributed to roads, or could have masked real effects EFFECTS of roads. We discuss the implications of these correlations in the Discussion. We included studies There are two general categories of species or showing no effect of roads or traffic on animal species groups showing negative effects of roads on abundance, except when statistical power was very animal abundance: species that are vulnerable to low, i.e., very low sample sizes or very high variance traffic disturbances (noise, lights, pollution, traffic around abundance estimates. motion) and species that are vulnerable to road mortality. Vulnerability to traffic disturbance likely explains many of the bird responses and some of the RESULTS mid- and large-sized mammal responses in Table 1. Traffic noise seems to be a problem for Altogether we found 79 studies, with results for 131 communication among songbirds (Reijnen et al. species and 30 species groups, documenting effects 1996, Forman et al. 2002, Rheindt 2003), possibly of roads and traffic on animal abundance (Table 1). leading to low abundances near roads, and direct Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

Table 1. Documented effects of roads and traffic on animal abundance.

Species or Species Group Direction of Road Reference(s) or Traffic Effect

Invertebrates invertebrate order diversity neutral Luce and Crowe (2001) butterfly species richness negative White and Kerr (2007) neutral Munguira and Thomas (1992) butterfly total abundance neutral Munguira and Thomas (1992) carabid species richness negative Koivula and Vermeulen (2005)

carabid total abundance negative Koivula and Vermeulen (2005) Calathus micropterus negative Koivula and Vermeulen (2005) Carabus nemoralis neutral Koivula and Vermeulen (2005) Pterostichus melanarius neutral Koivula and Vermeulen (2005) Herptiles herptile species richness negative Findlay and Bourdages (2000) Amphibians amphibian species richness negative Findlay and Houlahan (1997) Parris (2006) Houlahan and Findlay (2003) neutral Loehle et al. (2005) amphibian total abundance negative Houlahan and Findlay (2003) anuran species richness negative Eigenbrod et al. (2008a) anuran total abundance negative Fahrig et al. (1995) neutral Fahrig et al. (1995) salamander relative species richness negative Porej et al. (2004) salamander total abundance negative Semlitsch et al. (2007) deMaynadier and Hunter (2000) American toad (Bufo americanus) negative Eigenbrod et al. (2008a) Trenham et al. (2003) treefrog (Hyla arborea) negative Pellet et al. (2004a, b) Cope's gray tree frog (Hyla chrysoscelis) neutral Trenham et al. (2003)

gray treefrog (Hyla versicolor) negative Houlahan and Findlay (2003) neutral Eigenbrod et al. (2008a) Trenham et al. (2003)

(con'd) Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

spadefoot toad (Pelobates fuscus) negative Nyström et al. (2007) neutral Nyström et al. (2002) spring peeper (Pseudacris crucifer) negative Houlahan and Findlay (2003) neutral Eigenbrod et al. (2008a) Trenham et al. (2003) western chorus frog (Pseudacris triseriata) neutral Trenham et al. (2003) moor frog (Rana arvalis) negative Vos and Chardon (1998) green frog (Rana clamitans) negative Houlahan and Findlay (2003) neutral Eigenbrod et al. (2008a) Trenham et al. (2003) Carr and Fahrig (2001) leopard frog (Rana pipiens) negative Eigenbrod et al. (2008a) Carr and Fahrig (2001) neutral Trenham et al. (2003) mink frog (Rana septentrionalis) negative Houlahan and Findlay (2003) wood frog (Rana sylvatica) negative Houlahan and Findlay (2003) neutral Eigenbrod et al. (2008a) Porej et al. (2004) Skidds et al. (2007) positive Trenham et al. (2003) spotted salamander (Ambystoma neutral Porej et al. (2004) maculatum) Skidds et al. (2007) smallmouth salamander (Ambystoma neutral Porej et al. (2004) texanum) Jefferson's salamander (Ambystoma neutral Porej et al. (2004) jeffersonianum) tiger salamander (Ambystoma tigrinum negative Porej et al. (2004) tigrinum) blue-spotted salamander (Ambystoma negative Houlahan and Findlay (2003) laterale) Appalachian seal salamander (Desmognathus negative Ward et al. (2008) monticola) mountain dusky salamander (Desmognathus negative Ward et al. (2008) ochrophaeus) northern two-lined salamander (Eurycea positive Ward et al. (2008) bislineata) southern gray-cheeked salamander negative Semlitsch et al. (2007) (Plethodon metcalfi) red-spotted newt (Notophthalmus negative Porej et al. (2004) viridescens viridescens)

(con'd) Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

Reptiles reptile species richness neutral Loehle et al. (2005) snake total abundance negative Rudolph et al. (1999) neutral Sullivan (2000) turtle total abundance negative Gibbs and Shriver (2002) large-bodied turtle total abundance negative Gibbs and Shriver (2002) small-bodied turtle total abundance neutral Gibbs and Shriver (2002) eastern diamondback rattlesnake (Crotalus positive Steen et al. (2007) adamanteus) timber rattlesnake (Crotalus horridus) negative Steen et al. (2007)

black ratsnake (Elaphe obsoleta) negative Row et al. (2007) Galápagos lava lizard (Microlophus negative Tanner and Perry (2007) albemarlensis) painted turtle (Chrysemys picta bellii) negative Fowle (1990) desert tortoise (Gopherus agassizii) negative Boarman and Sazaki (2006) Birds bird species richness negative Findlay and Bourdages (2000) Findlay and Houlahan (1997) Small birds small bird summed density negative Reijnen et al. (1996) grassland bird presence negative Forman et al. (2002) grassland passerines total abundance neutral Warner (1992) Yellow Thornbill (Acanthiza nana) positive* Pocock and Lawrence (2005) Skylark (Alauda arvensis) negative Reijnen et al. (1996) Meadow Pipit (Anthus pratensis) negative Reijnen et al. (1996) Florida Scrub Jay (Aphelocoma negative Mumme et al. (2000) coerulescens) Linnet (Carduelis cannabina) negative Peris and Pescador (2004) Goldfinch (Carduelis carduelis) neutral Peris and Pescador (2004) Greenfinch (Carduelis chloris) neutral Peris and Pescador (2004) Short-toed Treecreeper (Certhia neutral Peris and Pescador (2004) brachydactyla) Bobolink (Delichonyx oryzivorus) negative Forman et al. (2002)

(con'd) Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

Galah (Eolophus roseicapillus) negative* Pocock and Lawrence (2005) Pied Flycatcher (Ficedula hypoleuca) negative Kuitunen et al. (2003) Chafffinch (Fringilla coelebs) neutral Peris and Pescador (2004) Crested Lark (Galerida cristata) neutral Peris and Pescador (2004) Oystercatcher (Haematopus ostralegus) negative Reijnen et al. (1996) neutral van der Zande et al. (1980) Woodchat Shrike (Lanius senator) negative Peris and Pescador (2004) Yellow-Tufted Honeyeater (Lichenostomus negative* Pocock and Lawrence (2005) melanops) Fuscous Honeyeater (Lichenostomus fuscus) negative* Pocock and Lawrence (2005)

Black-tailed Godwit (Limosa limosa) negative Reijnen et al. (1996) van der Zande et al. (1980) Woodlark (Lullula arborea) negative Peris and Pescador (2004) Superb Fairy-Wren (Malurus cyaneus) positive* Pocock and Lawrence (2005) Corn Bunting (Miliaria calandra) positive Peris and Pescador (2004) Yellow Wagtail (Motacilla flava) neutral/negative Reijnen et al. (1996) Wheatear (Oenanthe oenanthe) negative Peris and Pescador (2004) Striated Pardalote (Pardalotus striatus) negative* Pocock and Lawrence (2005) Blue Tit (Parus caeruleus) neutral Peris and Pescador (2004) Great Tit (Parus major) neutral Peris and Pescador (2004) House Sparrow (Passer domesticus) positive Peris and Pescador (2004) Rock Sparrow (Passer petronia) positive Peris and Pescador (2004) Black Redstart (Phoenicurus ochrurus) neutral Peris and Pescador (2004) Iberian Chiffchaff (Phylloscopus brehmii) negative Peris and Pescador (2004) Serin (Serinus serinus) neutral Peris and Pescador (2004) Nuthatch (Sitta europaea) neutral Peris and Pescador (2004) Eastern Meadowlark (Sturnella magna) negative Forman et al. (2002) Starling (Sturnus unicolor) neutral Peris and Pescador (2004) Blackbird (Turdus merula) negative Peris and Pescador (2004) Lapwing (Vanellus vanellus) negative Reijnen et al. (1996) van der Zande et al. (1980)

(con'd) Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

Large birds Shoveler (Anas clypeata) negative Reijnen et al. (1996) Mallard (Anas platyrhynchos) neutral/negative Reijnen et al. (1996) Tufted Duck (Aythya fuligula) neutral/negative Reijnen et al. (1996) Turkey Vulture (Cathartes aura) positive Coleman and Fraser (1989) Black Vulture (Coragyps atratus) positive Coleman and Fraser (1989) Mute Swan (Cygnus olor) neutral/negative Reijnen et al. (1996) Coot (Fulica atra) negative Reijnen et al. (1996) Sandhill Crane (Grus canadensis) negative Norling et al. (1992)

Bald Eagle (Haliaeetus leucocephalus) negative Anthongy and Isaacs (1989) Paruk (1987) Redshank (Tringa tetanus) neutral/negative Reijnen et al. (1996) Mammals mammal species richness neutral/negative Findlay and Houlahan (1997) Small mammals small mammal species richness neutral Garland and Bradley (1984) small mammal total abundance neutral Garland and Bradley (1984) positive* Rosa and Bissonette (2007) Adams and Geis (1983) white-tailed antelope squirrel (Ammospermo- neutral Garland and Bradley (1984) philus leucurus) black-tailed prairie dog (Cynomys positive Johnson and Collinge (2004) ludovicianus) Merriam's kangaroo rat (Dipodomys neutral Garland and Bradley (1984) merriami) kangaroo rat (Dipodomys microps) positive* Rosa and Bissonette (2007) prairie vole (Microtus ochrogaster) neutral/positive Adams and Geis (1983) California vole (Microtus californicus) neutral/positive Adams and Geis (1983) house mouse (Mus musculus) positive Garland and Bradley (1984) woodrat (Notoma lepida) neutral Garland and Bradley (1984) golden mouse (Ochrotomys nuttalli) neutral/positive Adams and Geis (1983)

long-tailed pocket mouse (Perognathus neutral Garland and Bradley (1984) formosus) brush mouse (Peromyscus boylii) neutral/negative* Rosa and Bissonette (2007)

(con'd) Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

white-footed mouse (Peromyscus leucopus) neutral McGregor et al. (2008) neutral/positive Adams and Geis (1983) positive Rytwinski and Fahrig (2007) deer mouse (Peromyscus maniculatus) neutral/positive Adams and Geis (1983) ship rat (Rattus rattus) neutral Garland and Bradley (1984) eastern chipmunk (Tamias striatus) positive McGregor et al. (2008) Medium-sized mammals chacoan peccary (Catagonus wagneri) negative Altrichter and Boaglio (2004) hedgehog (Erinaceus europaeus) negative Huijser and Bergers (2000) brown hare (Lepus europaeus) negative Roedenbeck and Voser (2008)

American marten (Martes americana) neutral Mowat (2006) badger (Meles meles) negative van der Zee et al. (1992) Roedenbeck and Köhler (2006) koala (Phascolarctos cinereus) negative McAlpine et al. (2006) white-lipped peccary (Tayassu pecari) neutral Altrichter and Boaglio (2004) collared peccary (Tayassu tajacu) neutral Altrichter and Boaglio (2004) red fox (Vulpes vulpes) negative Roedenbeck and Köhler (2006) Large mammals impala (Aepyceros melampus) neutral Newmark et al. (1996) moose (Alces alces) neutral Kunkel and Pletscher (2000) wolf (Canis lupus) negative Fuller (1989) Mech et al. )1988) Thiel (1985) Jedrzejewski et al. (2004) Karlsson et al. (2007) eastern timber wolf (Canis lupus lycaon) negative Jensen et al. (1986) Mladenoff et al. (1995) black-backed jackal (Canis mesomelas) negative Newmark et al. (1996) roe deer (Capreolus capreolus) negative Roedenbeck and Köhler (2006) elk (Cervus canadensis) negative Rost and Bailey (1979) wildebeest (Connochaetes taurinus) neutral/negative Newmark et al. (1996) zebra (Equus quagga) neutral/negative Newmark et al. (1996)

giraffe (Giraffa camelopardalis) neutral Newmark et al. (1996) African elephant (Loxondonta africana) negative Newmark et al. (1996) Barnes et al. (1991)

(con'd) Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

bobcat (Lynx rufus) negative Lovallo and Anderson (1996) Eurasian lynx (Lynx lynx) negative Niedzialkowska et al. (2006) Iberian lynx (Lynx pardinus) negative Palma et al. (1999) Mule Deer (Odocoileus hemionus) negative Rost and Bailey (1979) Amur tiger (Panthera tigris altaica) negative Kerley et al. (2002) warthog (Phacochoerus africanus) neutral Newmark et al. (1996) cougar (Puma concolor) negative van Dyke et al. (1986) Dickson and Beier (2002) woodland caribou (Rangifer tarandus negative Dyer et al. (2001) caribou)

bohor reedbuck (Redunca redunca) negative Newmark et al. (1996) wild boar (Sus scrofa) negative Roedenbeck and Köhler (2006) eland (Taurotragus oryx) negative Newmark et al. (1996) brown bear (Ursus arctos) negative Suring et al. (2006) grizzly bear (Ursus arctos horribilis) negative Ciarniello et al. (2007) Mace et al. (1996) McLellan and Shackleton (1988)

*based on our analyses of data presented in paper

observations and radiotelemetry studies of large 2006). Other studies have found that some frogs and mammals have documented behavioral avoidance snakes, although not necessarily attracted to roads, of roads for some species (Brody and Pelton 1989, do not behaviorally avoid them (Row et al. 2007; J. Lovallo and Anderson 1996, Dyer et al. 2002). Bouchard, A. T. Ford, F. Eigenbrod, and L. Fahrig, unpublished manuscript). Therefore, these animals Vulnerability to road mortality likely explains most are likely to enter the road surface and, in of the amphibian and reptile responses, as well as combination with their need for seasonal migrations some of the mid-sized and large mammal responses. between breeding and overwintering sites, as well Several factors combine to make a species as their slow movement across the road, experience vulnerable to road mortality. Species that are either very high mortality rates (Hels and Buchwald 2001; attracted to roads or do not avoid roads, and that J. Bouchard, A. T. Ford, F. Eigenbrod, and L. show low car avoidance (e.g., slow-moving species) Fahrig, unpublished manuscript). Further exacerbating are particularly vulnerable (van Langevelde and this low car avoidance is the fact that some species, Jaarsma 2005). This combination is most likely including frogs (Mazerolle et al. 2005), actually responsible for the frequent negative effects of roads respond to traffic on the road by stopping, thus and traffic on abundances of amphibians and increasing the time spent on the road and making reptiles. For example, some snakes use the road them even more likely to be killed. surface for thermoregulation (Sullivan 1981), some turtles lay their eggs in gravel roads or road As discussed above, a second group of species that shoulders (Aresco 2005, Steen et al. 2006; pers. obs., is particularly vulnerable to road mortality are Fig. 1), and natterjack toads (Bufo calamita) species that have large movement ranges and low apparently equate roads with open sandy habitats to reproductive rates, and do not avoid roads or traffic which they are naturally attracted (Stevens et al. (Gibbs and Shriver 2002, Forman et al. 2003). These Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

Fig. 1. A. Snapping turtle (Chelydra serpentina) digging a nest on the shoulder of a paved road. B. Snapping turtle killed by traffic on the same road. (Photos courtesy of Ewen Eberhardt.)

attributes interact with the animal’s behavioral areas, which depresses the populations, or because responses to roads to affect animal abundances. If animals avoid these locations because of the traffic animals with very large movement ranges do not disturbance. Higher mortality rates in roaded areas avoid roads, their high frequency of road crossing would support the former (e.g., Fahrig et al. 1995), leads to a high overall probability of being killed at and analyses of movement paths showing deviations some point. Because animals with large movement away from roads would support the latter (e.g., ranges typically have low reproductive rates (e.g., Whittington et al. 2004). Note that Roedenbeck et large carnivores), they cannot quickly compensate al. (2007) state that distinguishing between these is for higher mortality through higher reproduction, so a priority for road-ecology research: their fourth the mortality leads to population declines. For research question is “What is the relative example, in California, Dickson and Beier (2002) importance of the different mechanisms by which showed that cougars readily cross roads within their roads affect population persistence?” territories, i.e., they do not avoid roads. However, cougar territories contain lower road densities than areas without cougars. In Florida, it was shown that REASONS FOR POSITIVE ROAD EFFECTS road mortality killed over 20% of all cougars OR NO ROAD EFFECT (Florida panthers (Puma concolor)) (Land and Lotz 1996). Therefore, it seems likely that cougars are When animals are attracted to roads for a resource absent from areas of high road density because of but have the cognitive ability and movement speed the high probability of mortality in those areas. to allow them to avoid being killed by vehicles (i. e., car avoidance), there can be a net positive effect It is important to note that to determine whether a of roads on animal abundance. For example, some particular negative effect of roads on animal vultures have high densities near roads, presumably abundance is due to mortality or traffic disturbance, because of the availability of food (road-killed we need information on per capita traffic mortality animals) (Table 1) and their ability to lift themselves rates and/or behavioral responses to roads and off the road in time to avoid oncoming traffic (pers. traffic (preferably both). If we only have obs.). information on the distribution of animals with respect to roads, we cannot distinguish between Species showing no effect of roads on abundance these two causes. Animal numbers may be low near are those with the inverse of the factors above roads and/or in landscapes with high road density (“Reasons for negative effects”). Species that avoid either because the mortality rate is high in these going onto roads but are not disturbed by road Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

traffic, and have small movement ranges, small Strong positive effects of roads on animal territory sizes, and high reproductive rates are abundance are predicted in two situations. First, unlikely to be affected by roads because road roads should produce a net increase in abundance mortality is low and viable populations can exist for species that are attracted to roads for an within areas bounded by roads. This combination important resource (e.g., food) and are able to avoid of conditions likely explains the lack of effect or oncoming cars. Second, roads should produce a net weak effects for several small birds and small increase in abundance for species that do not avoid mammals (Table 1). traffic disturbance or emissions (low habitat loss) but do avoid roads (low road mortality), and whose Finally, if such a species is prey for other species main predators show negative population-level that are negatively affected by roads, the abundance responses to roads (predator release). of the prey species may actually be positively related to roads, due to the release from predation in roaded The four conditions leading to negative road effects areas. This combination of factors is most likely the are likely much more common than the two cause of the predominantly positive effects of roads conditions leading to positive road effects, which on small mammal abundances in Table 1. Several most likely is the reason that there are five times as studies have shown that small mammals avoid going many recorded negative road effects as positive road onto roads, presumably because of the lack of effects (Table 1). Note, however, that this estimate protective cover (Ford and Fahrig 2008, McGregor may be biased if researchers purposefully select et al. 2008), and several predators of small mammals study species and situations in which they expect a have been shown to be negatively affected by roads, negative effect of roads a priori. The remaining four including foxes, badgers, and snakes (Table 1). (of 10) conditions in Fig. 2 lead to either no effect or only a weak positive or negative effect of roads. We hypothesize that this is the reason for the 35% SYNTHESIS of effects in Table 1 that are neutral or weak. The results of the literature review (Table 1) and the information and ideas discussed above are DISCUSSION summarized in Fig. 2. This figure represents a set of predictions of the conditions that lead to strong Probably the most surprising result of this study, at or weak negative or positive effects or no effect of least to us, is the very large number of studies, 79 roads and traffic on animal abundance. in all, that quantified the relationships between animal abundance and roads or traffic. Before Strong negative effects of roads are predicted in four completing this review, we had been under the situations. First, any species that is attracted to roads apparently mistaken impression that very few such and is unable to avoid individual cars (e.g., species studies existed. There are several reasons for this that are too slow moving) should be negatively discrepancy. First, 71% (56 of 79) of the studies affected by roads. Second, all species with large were published within the last 8 years (since 2000; movement ranges, low reproductive rates, and low Table 1), so the impression that there are few natural densities should be negatively affected by population-level studies (see Introduction) is simply roads and traffic, irrespective of their behavioral outdated. Second, many of the studies we found response to roads. Those that do not avoid roads and were not primarily “about” road effects. Roads were traffic are susceptible to high mortality effects and included in a set of possible predictor variables, but those that do avoid roads or traffic disturbance or the author(s) did not focus on roads as the main emissions are susceptible to habitat loss, i.e., “story” in the paper, so these papers are not widely otherwise suitable habitat becomes inaccessible or known among road ecologists. We found these underused. Third, smaller animals whose papers mainly by reading papers that cited well- populations are not limited by road-affected known, older road-ecology papers. It is possible that predators but who avoid habitat near roads are there are still more papers in this category that we negatively affected by roads through habitat loss. have missed in our review. The third reason for the Finally, small animals whose populations are not discrepancy is that, although papers showing a lack limited by road-affected predators, have no road or of animals in roaded areas are in fact evidence for traffic avoidance, and are not able to avoid effects of roads on animal abundance, the authors oncoming cars show negative responses to roads sometimes do not present the work in this way. due to traffic mortality. Rather, it is fairly common to interpret such studies Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

Fig. 2. Summary of the factors affecting the size and direction of road effects on animal abundance, with 10 possible cases. Each case is defined by all the conditions leading to it through the arrows above. “neg,” “pos,” and “neut” refer to negative, positive, and neutral effects of roads on abundance (respectively). “m,” “h,” and “p” refer to the mechanisms creating road effects on the populations: mortality, habitat loss or increase, and predation release (respectively). Mortality and habitat loss are negative effects, and habitat increase and predation release are positive effects of roads on animal abundance. Examples of species in each case are: some turtles and snakes (A), vultures (B), large mammals, some mid-sized mammals, and some large birds (C), some small birds (D and E), small mammals (F, G, H, I), and amphibians (J). Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

as evidence for a behavioral avoidance of roads by two approaches are termed “mensurative these animals. As discussed above, this inference is experiments.” The final and arguably best solution not valid; the mechanism (mortality or avoidance) is to conduct a full “before–after–control–impact” for reduced abundance cannot be inferred without (BACI) experiment in which animal abundance is additional information. Finally, it may not be widely studied for several years both before and after road appreciated that studies of road density in animal construction, at both control and road construction territories are actually studies of road effects on sites (Roedenbeck et al. 2007). This sort of study is animal abundance: if territories have lower road extremely rare; we are aware of a few before–after densities than control areas, the corollary is that studies of animal use of road mitigation structures, areas with high road densities have lower but we are not aware of any road BACI studies on abundances (or lower probability of occurrence) animal abundance. Therefore, despite the large than areas with low road densities. number of studies in Table 1, there is still an urgent need for well-designed studies of road effects on Although our literature review revealed many more animal abundance. studies than we anticipated, the evidence for population-level effects of roads in many of these Although derived from the existing literature, the studies is compromised because of weaknesses in predictions in Fig. 2 still need to be tested with study design. Studies where road effects were not independent data. This requires obtaining not only the main interest of the author were typically not information on road effects on population designed a priori with the intention of quantifying abundance, but also information on the species’ the effects of roads independent of other variables. movement range and its behavioral responses to Roads or areas of high road density are, therefore, roads, traffic emissions, and oncoming vehicles, and frequently correlated with other variables. For in some cases, information on the population example, if areas of high road density typically have responses of its major predators to roads and traffic. lower habitat amounts, it is not possible to state Although some of this information is available for conclusively that the negative effects of roads are some species, usually the full set is not available for real, i.e., they could be effects of habitat loss. This a particular species. In addition, we emphasize that problem is recognized by some authors (e.g., information on behavioral responses to roads needs Houlahan and Findlay 2003, Roedenbeck and to be clearly distinguished from information on road Köhler 2006), and is bound to occur in any study in mortality (Karlsson et al. 2007). For example, which the sample sites are selected randomly or deMaynadier and Hunter (2000) showed reduced systematically in space, without attention to the salamander movements and Noordijk et al. (2006) distribution of possible confounding variables. showed reduced ground beetle movements across Such correlations are one of the main reasons that roads, but their sampling methods did not allow road-ecology research generally has low inferential them to determine whether this reduction was due strength (Roedenbeck et al. 2007). to mortality or avoidance, so this information cannot be used in testing predictions in Fig. 2. There are three possible solutions to this problem. The first is to select sites while controlling for On first reading, it may seem that our synthesis and possible confounding variables. For example, in our the predictions in Fig. 2 miss one of the main study of effects of road density on small mammal mechanisms proposed for negative population-level abundance, we selected landscapes ranging in road effects of roads, namely the movement barrier density, but with the constraint that small mammal effect, or reduction in landscape connectivity. If habitat variables had to be constant across sites and roads are a barrier to animal movement, they should landscapes (Rytwinski and Fahrig 2007). A second reduce animal abundance by fragmenting habitat, approach is to select sites such that road density thus increasing local extinction rate and reducing varies independently of possible confounding colonization rate, and by reducing animal access to variables. For example, Eigenbrod et al. (2008a) critical resources (Jaeger et al. 2005). These purposefully selected landscapes varying widely in processes are actually subsumed within the main traffic density and forest cover such that there was effects of mortality and traffic disturbance because no correlation across landscapes between these two both of these processes result in an underutilization variables. This was accomplished by searching for of the available habitat. In fact, Eigenbrod et al. landscapes with unusual combinations such as both (2008b) showed that “accessible habitat,” defined high traffic density and high forest cover. These first as the habitat available to pond-dwelling Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

amphibians without individuals needed to cross a Responses to this article can be read online at: major road, was a better predictor of amphibian http://www.ecologyandsociety.org/vol14/iss1/art21/ species richness than simply the amount of habitat responses/ within some distance of the ponds. This reduction in species richness is likely caused by lack of immigration to ponds with low amounts of Acknowledgments: accessible habitat, where the low immigration may be due to either mortality of individuals attempting This work was supported by the Natural Sciences to cross the road, or avoidance of the road due to and Engineering Research Council of Canada traffic noise or other emissions. Note again that (NSERC) and the Canada Foundation for when the road presents a physical barrier to Innovation. We thank two anonymous reviewers for movement, e.g., because of fencing along the road, their helpful suggestions. the effect on the population is equivalent to the animal showing an extremely strong behavioral avoidance of the road itself.

In conclusion, our review of the empirical literature LITERATURE CITED revealed many more population-level studies on road effects than we were initially expecting based Adams, L. W., and A. D. Geis. 1983. Effects of on statements in the literature (Underhill and roads on small mammals. Journal of Applied Angold 2000, Roedenbeck et al. 2007). Studies have Ecology 20:403–415. been conducted on a wide range of taxa, and overall there is strong evidence for negative effects of roads Altrichter, M., and G. I. Boaglio. 2004. at the population level. Although more research in Distribution and relative abundance of peccaries in this area is still needed because of the issues the Argentine Chaco: associations with human discussed above, it seems the evidence is certainly factors. Biological Conservation 116:217–225. strong enough to merit routine consideration of mitigation of these effects in road construction and Anthongy, R. G., and F. B. Isaacs. 1989. maintenance projects. The synthesis in Fig. 2 Characteristics of bald eagle nest sites in Oregon. suggests that appropriate mitigation will depend on Journal of Wildlife Management 53:148–159. whether the species of concern in a particular instance are affected mainly through road mortality Aresco, M. J. 2005. The effect of sex-specific or through traffic disturbance. Fencing and wildlife terrestrial movements and roads on the sex ratio of crossings (ecopassages) can be used to mitigate road freshwater turtles. Biological Conservation effects for species affected mainly through mortality 123:37–44. (amphibians, reptiles, some mammals), whereas road and traffic effects on species affected mainly Barnes, R. F. W., K. L. Barnes, P. T. Alers, and through traffic disturbance (birds, some large A. Blom. 1991. Man determines the distribution of mammals) can likely only be mitigated by reducing elephants in the rain forests of north-eastern Gabon. road and traffic density in the landscape. Finally, African Journal of Ecology 29:54–63. we note that the large base of research on population-level effects is sufficient to justify Boarman, W. I., and M. Sazaki. 2006. A highway's increased research attention to the other questions road-effect zone for desert tortoises (Gopherus raised in the Rauischholzhausen agenda (Roedenbeck agassizii). Journal of Arid Environments 65:94– et al. 2007) such as: what is the relative importance 101. of road effects vs. other impacts on population persistence (e.g., Eigenbrod et al. 2008a) and under Brody, A. J., and M. R. Pelton. 1989. Effects of what circumstances can road effects be mitigated roads on black bear movements in western North (van der Ree et al. 2007)? Carolina. Wildlife Society Bulletin 17:5–10. Carr, L. W., and L. Fahrig. 2001. Effect of road traffic on two amphibian species of differing vagility. Conservation Biology 15:1071–1078. Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

Ciarniello, L. M., M. S. Boyce, D. C. Heard, and Ford, A. T. and L. Fahrig. 2008. Movement D. R. Seip. 2007. Components of grizzly bear patterns of eastern chipmunks (Tamias striatus) near habitat selection: density, habitats, roads, and roads. Journal of Mammalogy 89:895–903. mortality risk. Journal of Wildlife Management 71:1446–1457. Forman R. T. T., B. Reineking, and A. M. Hersperger. 2002. Road traffic and nearby Coleman, J. S., and J. D. Fraser. 1989. Habitat use grassland bird patterns in a suburbanizing and home ranges of black and turkey vultures. landscape. Environmental Management 29:782– Journal of Wildlife Management 53:782–792. 800. de Maynadier, P. G., and M. L. Hunter. 2000. Forman, R. T. T., D. Sperling, J. A. Bissonette, A. Road effects on amphibian movements in a forested P. Clevenger, C. D. Cutshall, V. H. Dale, L. landscape. Natural Areas Journal 20:56–65. Fahrig, R. France, C. R. Goldman, K. Heanue, J. A. Jones, F. J. Swanson, T. Turrentine, and T. Dickson, B. G., and P. Beier. 2002. Home-range C. Winter. 2003. Road ecology: science and and habitat selection by adult cougars in southern solutions. Island Press, Washington, D.C., USA. California. Journal of Wildlife Management 66:1235–1245. Fowle, S. C. 1990. The painted turtle in the Mission Valley of western Montana. Dissertation, University Dyer, S. J., J. P. O’Neill, S. M. Wasel, and S. of Montana, Missoula, Montana, USA. Boutin. 2001. Avoidance of industrial development by woodland caribou. Journal of Wildlife Fuller, T. K. 1989. Population dynamics of wolves Management 65:531–542. in North-central Minnesota. Wildlife Monographs 105:1–41. Dyer, S. J., J. P. O’Neill, S. M. Wasel, and S. Boutin. 2002. Quantifying barrier effects of roads Garland, T., and W. G. Bradley. 1984. Effects of and seismic lines on movements of female a highway on Mojave Desert rodent populations. woodland caribou in northeastern Alberta. American Midland Naturalist 111:47–56. Canadian Journal of Zoology 80:839–845. Gibbs, J. P., and W. G. Shriver. 2002. Estimating Eigenbrod, F., S. J. Hecnar, and L. Fahrig. 2008a. the effects of road mortality on turtle populations. The relative effects of road traffic and forest cover Conservation Biology 16:1647–1652. on anuran populations. Biological Conservation 141:35–46. Hels, T., and E. Buchwald. 2001. The effect of road kills on amphibian populations. Biological Eigenbrod, F., S. J. Hecnar, and L. Fahrig. 2008b. Conservation 99:331–340. Accessible habitat: an improved measure of the effects of habitat loss and roads on wildlife Houlahan, J. E., and C. S. Findlay. 2003. The populations. Landscape Ecology 23:159–168. effects of adjacent land use on wetland amphibian species richness and community composition. Fahrig, L., J. H. Pedlar, S. E. Pope, P. D. Taylor Canadian Journal of Fisheries and Aquatic and J. F. Wegner. 1995. Effect of road traffic on Sciences 60:1078–1094. amphibian density. Biological Conservation 73:177–182. Huijser, M. P., and P. J. M. Bergers. 2000. The effect of roads and traffic on hedgehogs (Erinaceus Findlay, C. S., and J. Bourdages. 2000. Response europaeus) populations. Biological Conservation time of wetland biodiversity to road construction on 95:111–116. adjacent lands. Conservation Biology 14:86–94. Jaeger, J. A. G., J. Bowman, J. Brennan, L. Findlay, C. S., and J. Houlahan. 1997. Fahrig, D. Bert, J. Bouchard, N. Charbonneau, Anthropogenic correlates of species richness in K. Frank, B. Gruber, and K. Tluk von southeastern Ontario wetlands. Conservation Toschanowitz. 2005. Predicting when animal Biology 11:1000–1009. populations are at risk from roads: an interactive Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

model of road avoidance behavior. Ecological Land, D., and M. Lotz. 1996. Wildlife crossing Modeling 185:329–348. designs and use by Florida panthers and other wildlife in southwest Florida. In G. L. Evink, P. Jaeger, J. A. G., and L. Fahrig. 2004. Under what Garrett, D. Zeigler, and J. Berry, editors. conditions do fences reduce the effects of roads on Proceedings of the 1996 International Conference population persistence? Conservation Biology on Wildlife Ecology and Transportation. State of 18:1651–1657. Florida Department of Transportation Environmental Management Office, Tallahassee, Florida, USA. Jedrzejewski, W., M. Niedzialkowska, S. Nowak, [online] URL: http://www.icoet.net/ICOWET/96pr and B. Jedrzejewska. 2004. Habitat variables oceedings.asp. associated with wolf (Canis lupus) distribution and abundance in northern Poland. Diversity and Loehle, C., T. B. Wigley, P. A. Shipman, S. F. Fox, Distributions 10:225–233. S. Rutzmoser, R. E. Thill, and M. A. Melchiors. 2005. Herpetofaunal species richness responses to Jensen, W. F., T. K. Fuller, and W. L. Robinson. forest landscape structure in Arkansas. Forest 1986. Wolf (Canis lupus) distribution on the Ecology and Management 209:293–308. Ontario–Michigan border near Sault Ste. Marie. Canadian Field-Naturalist 100:363–366. Lovallo, M. J., and E. M. Anderson. 1996. Bobcat movements and home ranges relative to roads in Johnson, W. C., and S. K. Collinge. 2004. Wisconsin. Wildlife Society Bulletin 24:71–76. Landscape effects on black-tailed prairie dog colonies. Biological Conservation 115:487–497. Luce, A., and M. Crowe. 2001. Invertebrate terrestrial diversity along a gravel road on Barrie Karlsson J., H. Brøseth, H. Sand, and H. Andrén. Island, Ontario, Canada. Great Lakes Entomologist 2007. Predicting occurrence of wolf territories in 34:55–60. Scandinavia. Journal of Zoology 272:276–283. Mace, R. D., J. S. Waller, T. L. Manley, L. J. Lyon, Kerley, L. L., J. M. Goodrich, D. G. Miquelle, E. and H. Zurring. 1996. Relationships among N. Smirnov, H. B. Quigley, and M. G. Hornocker. grizzly bears, roads, and habitat in the Swan 2002. Effects of roads and human disturbance on Mountains, Montana. The Journal of Applied Amur tigers. Conservation Biology 16:97–108. Ecology 33:1395–1404. King, C. M., J. G. Innes, M. Flux, M. O. Mazerolle, M. J., M. Huot, and M. Gravel. 2005. Kimberley, J. R. Leathwick, and D. S. Williams. Behavior of amphibians on the road in response to 1996. Distribution and abundance of small car traffic. Herpetologica 61:380–388. mammals in relation to habitat in Pureora Forest Park. New Zealand Journal of Ecology 20:215–240 McAlpine, C. A., J. R. Rhodes, J. G. Callaghan, M. E. Bowen, D. Lunney, D. L. Mitchell, D. V. Koivula, M. J., and H. J. W. Vermeulen. 2005. Pullar, and H. P. Possingham. 2006. The Highways and forest fragmentation—effects on importance of forest area and configuration relative carabid beetles (Coleoptera, Carabidae). Landscape to local habitat factors for conserving forest Ecology 20:911–926. mammals: a case study of koalas in Queensland, Australia. Biological Conservation 132:153–165. Kuitunen, M. T., J. Viljanen, E. Rossi, and A. Stenroos. 2003. Impact of busy roads on breeding McGregor, R. L., D. J. Bender, and L. Fahrig. success in pied flycatchers Ficedula hypoleuca. 2008. Do small mammals avoid roads because of Environmental Management 31:79–85. the traffic? Journal of Applied Ecology 45:117–123. Kunkel, K. E., and D. H. Pletscher. 2000. Habitat McLellan, B. N., and D. M. Shackleton. 1988. factors affecting vulnerability of moose to predation Grizzly bears and resource-extraction industries: by wolves in southeastern British Columbia. effects of roads on behavior, habitat use and Canadian Journal of Zoology 78:150–157. demography. Journal of Applied Ecology 25:451– 460. Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

Sundstedt, C. Reslow, and A. Broström. 2007. A Mech, L. D., S. H. Fritts, G. L. Radde, and W. J. documented amphibian decline over 40 years: Paul. 1988. Wolf distribution and road density in possible causes and implications for species Minnesota. Wildlife Society Bulletin 16:85–87. recovery. Biological Conservation 138:399–411. Mladenoff, D. J., T. A. Sickley, R. G. Haight, and Palma, L., P. Beja, and M. Rodrigues. 1999. The A. P. Wydeven. 1995. A regional landscape analysis use of sighting data to analyse Iberian lynx habitat and prediction of favourable Gray Wolf habitat in and distribution. Journal of Applied Ecology the northern Great-Lakes region. Conservation 36:812–824. Biology 9:279–294. Parris, K. M. 2006. Urban amphibian assemblages Mowat, G. 2006. Winter habitat associations of as metacommunities. Journal of Animal Ecology 75:757– American martens Martes americana in interior 764. wet-belt forests. Wildlife Biology 12:51–61. Paruk, J. D. 1987. Habitat utilization by bald eagles Mumme, R. L., S. J. Schoech, G. E. Woolfenden, wintering along the Mississippi River (USA). and J. W. Fitzpatrick. 2000. Life and death in the Transactions of the Illinois State Academy of fast line: demographic consequences of road Science 80:333–342. mortality in the Florida Scrub-Jay. Conservation Biology 14:501–512. Pellet, J., A. Guisan, and N. Perrin. 2004a. A concentric analysis of the impact of urbanization on Munguira, M. L., and J. A. Thomas. 1992. Use of the threatened European tree frog in an agricultural road verges by butterfly and burnet populations, and landscape. Conservation Biology 18:1599–1606. the effect of roads on adult dispersal and mortality. Journal of Applied Ecology 29:316–329. Pellet, J., S. Hoehn, and N. Perrin. 2004b. Multiscale determinants of tree frog (Hyla arborea Newmark, W. D., J. I. Boshe, H. I. Sariko, and L.) calling ponds in western Switzerland. G. K. Makumbule. 1996. Effects of a highway on Biodiversity and Conservation 13:2227–2235. large mammals in Mikumi National Park, Tanzania. African Journal of Ecology 34:15–31. Peris, S. J., and M. Pescador. 2004. Effects of traffic noise on passerine populations in Niedzialkowska, M., W. Jedrzejewski, R. W. Mediterranean wooded pastures. Applied Acoustics Myslajek, S. Nowak, B. Jedrzejewska, and K. 65:357–366. Schmidt. 2006. Environmental correlates of Eurasian lynx occurrence in Poland—large scale Pocock, Z., and R. E. Lawrence. 2005. How far census and GIS mapping. Biological Conservation into a forest does the effect of a road extend? 133:63–69. Defining road edge effect in eucalyupt forests of south-eastern Australia. Pages 397–405 in C. L. Noordijk, J., D. Prins, M. de Jonge, and R. Irwin, P. Garrett, and K. P. McDermott, editors. Vermeulen. 2006. Impact of a road on the Proceedings of the 2005 International Conference movements of two ground beetle species on Ecology and Transportation. Center for (Coleoptera: Carabidae). Entomologica Fennica Transportation and Environment, North Carolina 17:276–283. State University, Raleigh, North Carolina, USA. Norling, B. S., S. H. Anderson, and W. A. Hubert. Porej, D., M. Micacchion, and T. E. 1992. Roost sites used by Sandhill Crane staging Hetherington. 2004. Core terrestrial habitat for along the Platte River, Nebraska. Great Basin conservation of local populations of salamanders Naturalist 52:253–261. and wood frogs in agricultural landscapes. Biological Conservation 120:399–409. Nyström, P., L. Birkedal, C. Dahlberg, and C. Brönmark. 2002. The declining spadefoot toad Reijnen, R., R. Foppen, and H. Meeuwsen. 1996. Pelobates fuscus: calling site choice and The effects of traffic on the density of breeding birds conservation. Ecography 25: 488–498. in dutch agricultural grasslands. Biological Conservation 75:255–260. Nyström, P., J. Hansson, J. Månsson, M. Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

Rheindt, F. E. 2003. The impact of roads on birds: Rytwinski, T., and L. Fahrig. 2007. Effect of road does song frequency play a role in determining density on abundance of white-footed mice. susceptibility to noise pollution? Journal für Landscape Ecology 22:1501–1512. Ornithologie 144: 295–306. Semlitsch, R. D., T. J. Ryan, K. Hamed, M. Roedenbeck, I. A., L. Fahrig, C. S. Findlay, J. E. Chatfield, B. Drehman, N. Pekarek, M. Spath, Houlahan, J. A. G. Jaeger, N. Klar, S. Kramer- and A. Watland. 2007. Salamander abundance Schadt, and E. A. van der Grift. 2007. The along road edges and within abandoned logging Rauischholzhausen agenda for road ecology. roads in Appalachian forests. Conservation Biology Ecology and Society 12(1): 11. [online] URL: http: 21:159–167. //www.ecologyandsociety.org/vol12/iss1/art11/. Skidds, D. E., F. C. Golet, P. W. C. Paton, and J. Roedenbeck, I. A., and W. Köhler. 2006. Effekte C. Mitchell. 2007. Habitat correlates of der Landschaftszerschneidung auf die Unfallhäufigkeit reproductive effort in wood frogs and spotted und Bestandsdichte von Wildtierpopulationen. salamanders in an urbanizing watershed. Journal of 2006. Naturschutz und Landschaftsplanung Herpetology 41:439–450. 38:314–322. Steen, D. A., M. J. Aresco, S. G. Beilke, B. W. Roedenbeck, I. A., and P. Voser. 2008. Effects of Compton, E. P. Condon, C. K. Dodd, H. roads on spatial distribution, abundance and Forrester, J. W. Gibbons, J. L. Greene, G. mortality of brown hare (Lepus europaeus) in Johnson, T. A. Langen, M. J. Oldham, D. N. Switzerland. European Journal of Wildlife Research Oxier, R. A. Saumure, F. W. Schueler, J. M. 54:425–437. Sleeman, L. L. Smith, J. K. Tucker, and J. P. Gibbs. 2006. Relative vulnerability of female Rosa, S., and J. Bissonette. 2007. Roads and desert turtles to road mortality. Animal Conservation small mammal communities: positive interaction? 9:269–273. Pages 562–566 in C. L. Irwin, D. Nelson, and K. P. McDermott, editors. Proceedings of the 2007 Steen, D. A., L. L. Smith, L. M. Conner, J. C. International Conference on Ecology and Brock, and S. K. Hoss. 2007. Habitat use of Transportation. Center for Transportation and sympatric rattlesnake species within the Gulf Environment, North Carolina State University, Coastal Plain. Journal of Wildlife Management Raleigh, North Carolina, USA. 71:759–764. Rost, G. R., and J. A. Bailey. 1979. Distribution of Stevens, V. M., E. Leboulengé, R. A. Wesselingh, mule deer and elk in relation to roads. Journal of and M. Baguette. 2006. Quantifying functional Wildlife Management 43:634–641. connectivity: experimental assessment of boundary permeability for the natterjack toad (Bufo calamita). Row, J. R., G. Blouin-Demers, and P. J. Oecologia 150:161–171. Weatherhead. 2007. Demographic effects of road mortality in black ratsnakes (Elaphe obsoleta). Sullivan, B. K. 1981. Observed differences in body Biological Conservation 137:117–124. temperature and associated behaviour of four snake species. Journal of Herpetology 15:245–246. Rudolph, D. C., S. J. Burgdorf, R. N. Conner, and R. R. Schaefer. 1999. Preliminary evaluation of the Sullivan, B. K. 2000. Long-term shifts in snake impact of roads and associated vehicular traffic on populations: a California site revisited. Biological snake populations in eastern Texas. In G. L. Evink, Conservation 94:321–325. P. Garrett, and D. Ziegler, editors. Proceedings of the Third International Conference on Wildlife Suring, L. H., S. D. Farley, G. V. Hilderbrand, Ecology and Transportation, FL-ER-73-99. Florida M. I. Goldstein, S. Howlin, and W. P. Erickson. Department of Transportation, Tallahassee, Florida, 2006. Patterns of landscape use by female brown USA. [online] URL: http://www.icoet.net/ICOWET bears on the Kenia Peninsula, Alaska. Journal of /99proceedings.asp. Wildlife Management 70:1580–1587. Ecology and Society 14(1): 21 http://www.ecologyandsociety.org/vol14/iss1/art21/

Tanner, D., and J. Perry. 2007. Road effects on van Langevelde, F., and C. F. Jaarsma. 2005. abundance and fitness of Galápagos lava lizards Using traffic flow theory to model traffic mortality (Microlophus albemarlensis). Journal of Environmental in mammals. Landscape Ecology 19:895–907. Management 85:270–278. Vos, C. C., and J. P. Chardon. 1998. Effects habitat Thiel, R. P. 1985. Relationship between road fragmentation and of road density on the densities and wolf habitat suitability in Wisconsin. distribution pattern of the moor frog Rana arvalis. The American Midland Naturalist 113:404–407. Journal of Applied Ecology 35:44–56. Trenham, P. C., W. D. Koenig, M. J. Mossman, Ward, R. L., J. T. Anderson, and J. T. Petty. 2008. S. L. Stark, and L. A. Jagger. 2003. Regional Effects of road crossings on stream and streamside dynamics of wetland-breeding frogs and toads: salamanders. Journal of Wildlife Management turnover and synchrony. Ecological Applications 72:760–771. 13:1522–1532. Warner, R. E. 1992. Nest ecology of grassland Trombulak, S. C., and C. A. Frissell. 2000. Review passerines on road rights-of-way in central Illinois. of ecological effects of roads on terrestrial and Biological Conservation 59:1–7. aquatic communities. Conservation Biology 14:18– 30. White, P. J. T., and J. T. Kerr. 2007. Human impacts on environment–diversity relationships: Underhill, J. E., and P. G. Angold. 2000. Effects evidence for biotic homogenization from butterfly of roads on wildlife in an intensively modified species richness patterns. Global Ecology and landscape. Environmental Reviews 8:21–39. Biogeography 16: 290–299. van der Ree, R., E. van der Grift, C. Mata, and Whittington, J., C. C. St. Clair, and G. Mercer. F. Suarez. 2007. Overcoming the barrier effect of 2004. Path tortuosity and the permeability of roads roads—how effective are mitigation strategies? An and trails to wolf movement. Ecology and Society international review of the use and effectiveness of 9(1):4. [online] URL: http://www.ecologyandsociety. underpasses and overpasses designed to increase the org/vol9/iss1/art4/. permeability of roads for wildlife. Pages 423–431 in C. L. Irwin, D. Nelson, and K. P. McDermott, editors. Proceedings of the 2007 International Conference on Ecology and Transportation. Center for Transportation and Environment, North Carolina State University, Raleigh, North Carolina, USA. van der Zande, A. N., W. J. ter Keurs, and W. J. van der Weijden. 1980. The impact of roads on the densities of four bird species in an open field habitat —evidence of a long-distance effect. Biological Conservation 18:299–321. van der Zee, F. F., J. Wiertz, C. J. F. ter Braak, and R. C. Apeldoorn. 1992. Landscape change as a possible cause of the badger Meles meles L. decline in the Netherlands. Biological Conservation 61:17–22. van Dyke, F. G., R. H. Brocke, and H. G. Shaw. 1986. Use of road track counts as indices of mountain lion presence. Journal of Wildlife Management 50:102–109. Downloaded from rspb.royalsocietypublishing.org on December 11, 2013

Noise pollution alters ecological services: enhanced pollination and disrupted seed dispersal

Clinton D. Francis, Nathan J. Kleist, Catherine P. Ortega and Alexander Cruz

Proc. R. Soc. B 2012 279, doi: 10.1098/rspb.2012.0230 first published online 21 March 2012

Supplementary data "Data Supplement" http://rspb.royalsocietypublishing.org/content/suppl/2012/03/15/rspb.2012.0230.DC1.h tml References This article cites 39 articles, 6 of which can be accessed free http://rspb.royalsocietypublishing.org/content/279/1739/2727.full.html#ref-list-1

Article cited in: http://rspb.royalsocietypublishing.org/content/279/1739/2727.full.html#related-urls Subject collections Articles on similar topics can be found in the following collections

ecology (1477 articles) environmental science (236 articles) Receive free email alerts when new articles cite this article - sign up in the box at the top Email alerting service right-hand corner of the article or click here

To subscribe to Proc. R. Soc. B go to: http://rspb.royalsocietypublishing.org/subscriptions Downloaded from rspb.royalsocietypublishing.org on December 11, 2013

Proc. R. Soc. B (2012) 279, 2727–2735 doi:10.1098/rspb.2012.0230 Published online 21 March 2012

Noise pollution alters ecological services: enhanced pollination and disrupted seed dispersal Clinton D. Francis1,*, Nathan J. Kleist2, Catherine P. Ortega3 and Alexander Cruz2 1NESCent: the National Evolutionary Synthesis Center, 2024 West Main Street, Suite A200, Durham, NC 27705, USA 2Ecology and Evolutionary Biology, University of Colorado, Boulder, CO 80309, USA 3San Juan Institute of Natural and Cultural Resources, Fort Lewis College, Durango, CO 81301, USA Noise pollution is a novel, widespread environmental force that has recently been shown to alter the behaviour and distribution of birds and other vertebrates, yet whether noise has cumulative, commu- nity-level consequences by changing critical ecological services is unknown. Herein, we examined the effects of noise pollution on pollination and seed dispersal and seedling establishment within a study system that isolated the effects of noise from confounding stimuli common to human-altered landscapes. Using observations, vegetation surveys and pollen transfer and seed removal experiments, we found that effects of noise pollution can reverberate through communities by disrupting or enhancing these eco- logical services. Specifically, noise pollution indirectly increased artificial flower pollination by hummingbirds, but altered the community of animals that prey upon and disperse Pinus edulis seeds, potentially explaining reduced P. edulis seedling recruitment in noisy areas. Despite evidence that some ecological services, such as pollination, may benefit indirectly owing to noise, declines in seedling recruit- ment for key-dominant species such as P. edulis may have dramatic long-term effects on ecosystem structure and diversity. Because the extent of noise pollution is growing, this study emphasizes that investigators should evaluate the ecological consequences of noise alongside other human-induced environmental changes that are reshaping human-altered landscapes worldwide. Keywords: anthropogenic noise; birds; ecological service; human disturbance; pollination; seed dispersal

1. INTRODUCTION processes. A few studies have shown that predators Human activities have altered over 75 per cent of the avoid noisy areas [7,14–16], presumably because noise Earth’s land surface [1,2]. Concomitant with these surface impairs predators’ abilities to locate prey. These studies changes is a pervasive increase in anthropogenic noise, or provide us with insights on how noise may directly noise pollution, caused by expanding dendritic transpor- affect predator–prey interactions, but do not provide tation networks, urban centres and industrial activities information on whether noise may have cumulative, indir- [3]. The geographical extent of noise exposure varies by ect consequences for other interactions and organisms region and scale, but estimates suggest that one-fifth of that are not impacted by noise directly. the United States’ land area is impacted by traffic noise Our goal was to investigate whether noise pollution can directly [4] and over 80 per cent of some rural landscapes reverberate through ecological communities by affecting are exposed to increased noise levels owing to energy species that provide functionally unique ecological services. extraction activities [5]. Despite the potentially substantial We focused our efforts on ecological services provided pri- scale of noise exposure across the globe, surprisingly little marily by birds because they are considered to be especially is known about how these ecologically novel acoustic sensitive to noise pollution owing to their reliance on acous- conditions affect natural populations and communities. tic communication [11]. However, because not all species We are beginning to understand the impacts of respond uniformly to noise exposure [6,7,10,17], we can increased noise exposure on the behaviours of individuals evaluate how different responses by functionally unique and the distributions of species [6–10], and several recent species impact other organisms indirectly and trigger reviews outline potential and some known effects of noise further changes to community structure. We studied [3,11–13]. Despite this recent attention given to the ecological services provided by Archilochus alexandri effects of noise, we still have limited knowledge of how (black-chinned hummingbird) and Aphelocoma californica these impacts scale to community and ecosystem-level (western scrub-jay), which serve as mobile links for pollina- tion and Pinus edulis (pin˜on) seed dispersal services, respectively [18–20]. Because A. alexandri preferentially * Author for correspondence ([email protected]). nests in noisy environments and A. californica avoids Electronic supplementary material is available at http://dx.doi.org/ noisy areas [5, 7], we proposed that their noise-dependent 10.1098/rspb.2012.0230 or via http://rspb.royalsocietypublishing.org. distributions could result in a higher rate of pollination

Received 31 January 2012 Accepted 28 February 2012 2727 This journal is q 2012 The Royal Society Downloaded from rspb.royalsocietypublishing.org on December 11, 2013

2728 C. D. Francis et al. Noise alters ecological services

(a) figure 2a +

+ figure 2b,c +

figure 3e figure 3a – + figure 3c – – figure 3b

figure 3d +

(b) (c) (d)

250 m

Figure 1. (a) Pathway by which noise alters pollination and seed dispersal services. Solid and dashed arrows denote direct and indirect interactions, respectively. Signs refer to effect direction, and support for each effect is indicated by figure number. See main text for results and citations supporting the dependence of I. aggregata on A. alexandri (arrow labelled figure 2a) and for the functional quality of Peromyscus mice and A. californica as P. edulis seed dispersers (arrows labelled figure 3c,d). (b) Active gas wells located at the end of access roads served as (c) noisy treatment sites owing to the presence of noise-generating gas well compressors (white arrow) or (d) quiet control sites. for hummingbird-pollinated plants and disrupt P. edulis figure S1) [5–7]. Additionally, human activity at wells and seed dispersal services in noisy areas and potentially affect major vegetation features in the woodlands surrounding seedling recruitment (figure 1a). wells do not differ between wells with (noisy treatment sites) To test these predictions, we used a unique study and without noise-generating compressors (quiet control system that isolates the influence of noise exposure from sites, figure 1c,d)[7], providing an opportunity to evaluate many confounding factors common to noisy areas, such the indirect effect of noise on supporting ecological services as vegetation heterogeneity, edge effects and the presence in the absence of many confounding stimuli common to of humans and moving vehicles (see below). We used most human-altered landscapes. observations, vegetation surveys and pollen transfer and seed-removal experiments on pairs of treatment and (a) Pollination experiment control sites to determine how ecological interactions To determine whether hummingbird-pollinated flowers differ in noisy and quiet areas and whether noise indirectly benefit from noise, we used a field experiment indirectly affects plants that depend on functionally controlling for the density and the spatial arrangement of unique avian mobile links. hummingbird nectar resources with patches of artificial flowers that mimicked a self-incompatible, hummingbird-pollinated plant common to our study area: Ipomopsis aggregata (electro- 2. MATERIAL AND METHODS nic supplementary material, figures S2 and S3a). In May 2010, Our study took place in the Rattlesnake Canyon Habitat we established seven pairs of treatment and control sites within Management Area (RCHMA), located in northwestern New RCHMA for the pollination experiments. Sites were paired Mexico. Study area and site details can be found elsewhere geographically to minimize potential differences in vegetation [5–7]. Briefly, RCHMA is dominated by woodland consisting features within each pair; however, to ensure that back- of P. edulis and Juniperus osteosperma (juniper) and has a high ground noise levels were significantly different between density of natural gas wells (figure 1b). Many wells are coupled paired sites, sites were greater than or equal to 500 m apart with compressors that run continuously and generate noise at and resulted in relatively quiet conditions at control sites. high amplitudes (greater than 95 dB(A) at a distance of 1 m), The resulting distance between treatment-control pairs was and, like most anthropogenic noise, compressor noise has 767 m (+57 s.e.m., minimum ¼ 520 m, maximum ¼ 954 m). substantial energy at low frequencies and diminishes towards Artificial flower patches were established 125 m from either higher frequencies (electronic supplementary material, the wellhead or compressor on control and treatment sites,

Proc. R. Soc. B (2012) Downloaded from rspb.royalsocietypublishing.org on December 11, 2013

Noise alters ecological services C. D. Francis et al. 2729 respectively (electronic supplementary material, figure S2a). between treatment and control sites. Individual sites and The direction of the first patch relative to the wellhead or com- geographically paired sites were treated as random effects. pressor was determined randomly and the second patch was Following focal observations, on 28 May 2010, we established 40 m from the first and also at 125 m from the well- returned to all patches between 07.00 and 12.00 to refill all head or compressor. Prior to the experiment, at each patch, we artificial flowers with the sucrose reward and uniquely measured background noise amplitude as A-weighted decibels marked one plant per patch with either yellow or red fluor- (dB(A)) for 1 min to confirm that noise levels were signifi- escent powder (Day-Glo Color Corporation, Cleveland, cantly higher at treatment patches relative to control patches. Ohio, USA) such that plants within the same site but at In all cases, measurements on paired treatment and control different patches received a unique coloured powder. Use sites were completed on the same day and at approximately of fluorescent powder as a proxy for pollen transfer is a tech- the same time. We measured amplitude as the equivalent nique widely used in pollination studies because the transfer continuous noise level (Leq, fast response time) with Casella of powder is strongly correlated with the transfer of pollen convertible sound dosimeter/sound pressure metres (model [27,28]. Each patch was permitted 24 h of exposure for pol- CEL 320 and CEL 1002 converter). We used 95 mm acousti- linator visits before we collected each plant for subsequent cal windscreens, and we did not take measurements when wind examination for powder transfer in the laboratory. conditions were categorized three or above on the Beaufort In the laboratory, we used an ultraviolet lamp under dark Wind Scale (approx. 13–18 km h21), or when sounds other conditions to record the presence or absence of powder on than compressor noise (i.e. bird vocalizations and aircraft each inflorescence, noting whether the powder was from noise) could bias measurements. the marked plant within the same patch or the patch located Artificial flowers are frequently used in pollination studies at 40 m. We then used Poisson GLMMs to examine within- [21,22] and those used in our experiment were constructed patch and between-patch pollen transfer with number of from 0.6 ml microcentrifuge tubes. This microcentrifuge tube individual flowers per patch with transferred pollen as size had been used previously in pollination experiments with response variables. We treated each site and geographically A. alexandri [23]. To mimic the appearance of I. aggregata, paired treatment and control site as random effects in we wrapped each microcentrifuge tube with red electrical all models. tape (electronic supplementary material, figure S3). Addi- tionally, we attached three small pieces of yellow yarn to (b) Pinus edulis seed-removal experiment provide a substrate for marking flowers with fluorescent dye We conducted P.edulis seed-removal experiments throughout and subsequent transfer and deposition on other flowers by RCHMA to determine whether and how seed-removal rates pollinators. Each artificial plant consisted of three flowers and the community of seed predators and dispersers respond attached to a 53 cm long metal rod with green electrical tape to noise exposure. Pinus edulis trees within a region typically (electronic supplementary material, figure S3b). Patches of synchronize production of large-cone crops every 5–7 years plants were arranged in a 3 m2 area with four plants marking [20]. As cones gradually dry and open in September, seeds each corner and one at the centre (electronic supplementary not harvested by corvids from cones in the canopy fall to material, figure S2a). the ground where rodents, corvids and other bird species Plant patches were established simultaneously or one consume and harvest seeds for several months [20]. Monitor- immediately after another (less than or equal to 30 min) on ing rates of autumn seed removal from the ground can be paired sites. Because I. aggregata nectar is 20–25% sucrose problematic as seeds continue to fall from trees; therefore, [24,25], we filled each flower with a reward of 0.4 ml 25 we conducted our experiments in June–July when no other per cent sucrose solution with pipettes and calibrated plastic P. edulis seeds were available, similar to other studies that droppers, returning each day at approximately the same time have examined P. edulis seed removal and dispersal during to refill the flower with the sucrose reward so that pollinators summer months [29]. learned to use the flowers as a foraging resource. Only rarely We used six pairs of treatment and control sites that were did we encounter a single artificial flower completely geographically coupled. Sites met those same criteria depleted of the reward between visits to replenish the described for the pollination experiment. The mean distance reward, but never all three flowers on the same plant. between treatment-control pairs was 821 m (+51 s.e.m., We conducted observations to determine pollinator visita- minimum ¼ 642 m, maximum ¼ 1029 m). At each site, we tion rates at 11 (79%) of 14 pairs of treatment and control established seed stations at 10 locations within 150 m of patches. Because the establishment of our patches took sev- each well or compressor (electronic supplementary material, eral days, prior to our observations, four pairs of patches figure S2b). Locations were selected randomly provided that were refilled for 4 days, two patches were refilled for 3 days the distance between each station was greater than or equal and five patches were refilled for 2 days and all observed to 40 m, and each station was located on the ground under patches had been established for greater than 38 h prior to a reproductively mature P. edulis tree. observation. We then conducted observations at patches on Seed-removal experiments lasted for 72 h with visits to pairs of control and treatment sites simultaneously or one each station every 24 h to quantify the daily rate of seed immediately after the other. We watched flowers at focal removal. At the beginning of each 24 h period, we simulated patches for 15 min and tallied the number of visits to natural seed fall by scattering 20 P.edulis seeds on the ground each plant from a distance of 5 m, using binoculars when in a 0.125 m2 area. We then returned 24 h later to document necessary to identify arthropods visiting the flowers. All the number of removed seeds, determine whether there was non-hummingbird pollinators were separated into their evidence for in situ seed predation by carefully searching orders (Hymenoptera, Diptera and Lepidoptera) and we the immediate area (approx. 2 m2) for newly opened used Poisson generalized linear-mixed models (GLMM) P. edulis seeds (usually conspicuous as a clumped collection within the lme4 package in R [26] to examine whether of seed-coat fragments from several seeds) and to again patch visitations by A. alexandri or other pollinators differed scatter 20 seeds at the station. Evidence of seed predation

Proc. R. Soc. B (2012) Downloaded from rspb.royalsocietypublishing.org on December 11, 2013

2730 C. D. Francis et al. Noise alters ecological services at a station was defined as whether recently opened (and established relatively recently and under the same acoustic empty) seed coats were detected during any of the three conditions that were present in 2007. We assumed seedlings visits used to quantify seed-removal rate. All seeds were col- less than or equal to 20 cm had been dispersed and estab- lected locally within RCHMA and were handled with latex lished within the previous 6 years because 1 year-old gloves so that human scent was not transferred to the P. edulis seedlings were measured to have an average height seeds. During one of the four visits to each station, we of 5.3 cm [30] and because the closely related Pinus measured background noise amplitude following the cembroides reaches a height of 1 m at around 5 years old methods described above for the pollination experiment. [31]. Thus, our assumptions should be considered conserva- To document the identity of animals removing seeds, we tive. We analysed seedling recruitment with the number of paired each station with a motion-triggered digital camera seedlings per plot as the response variable using Poisson (Wildview Xtreme II). Cameras were mounted on a trunk GLMMs. Predictor variables included plot location on either or a branch of an adjacent tree within 1–3 m from the seed a treatment or control site, but also plot-level features that station for a clear view, yet positioned in a relatively incon- may influence seedling establishment and recruitment, such spicuous location to avoid drawing additional attention to as the number of shrubs, P.edulis and J. osteosperma trees, the the station. Cameras remained on each station for the amount of canopy cover, leaf litter depth and the proportion entire 72 h period and documented both diurnal and noctur- of ground cover classified as living material, dead matter or nal seed removal. A positive detection of a species removing bare ground. Site identity was treated as a random effect. We seeds was recorded only when an individual was documented followed the same model selection procedure described removing or consuming seeds. above for seed removal and seed predation. Data for seedling The number of seeds removed per 24 h period was used to recruitment, plus data from the seed removal and pollination calculate a daily mean proportion of seeds removed, which experiments have been deposited at Dryad (www.datadryad. we arcsine square-root transformed to meet assumptions of org; doi:10.5061/dryad.6d2ps7s7). normality and homogeneity of variance. We used linear- mixed models (LMMs) to examine whether the proportion of seeds removed differed between treatment and control 3. RESULTS seed stations or owing to the presence or absence of individual (a) Pollination species. We used binomial GLMMs to determine how the Noise amplitude values were significantly higher (approx. presence of individual species explained in situ seed predation, 12 dB(A)) at treatment patches relative to control patches 2 evidenced by the presence of newly opened P.edulis seed coats. (LMM: x1 ¼ 25.550, p , 0.001, electronic supplementary For the models in which we examined the influence of individ- material, figure S2c) and similar to those experienced ual species on seed removal or predation, we started with approximately 500 m from motorways [32,33]. Focal models containing all documented species as predictor vari- observations at a subset of patches revealed that several ables and proceeded to remove each non-significant variable taxa visited artificial flowers supplied with a nectar reward one at a time based on the highest p-value until only significant (electronic supplementary material, table S1), yet only effects remained. We used Poisson and binomial GLMMs to A. alexandri visits differed between treatment and control examine whether species richness of the seed removing com- sites. Archilochus alexandri visits were five times more munity and detections of individual species differed at common at treatment patches than control patches 2 treatment and control seed stations, respectively. For all (Poisson GLMM: x1 ¼ 6.859, p ¼ 0.009, figure 2a). models, we treated each site and geographically paired treat- Consistent with more A. alexandri visits to plants in noisy ment and control sites as random effects. Some models areas, within-patch pollen transfer occurred for 5 per cent of evaluating detections of individual species on treatment and control site flowers, but 18 per cent of treatment site flowers 2 control sites would not converge; therefore, for these cases, (Poisson GLMM: x1 ¼ 15.518, p , 0.001, figure 2b)and we used x2-tests to determine whether there was a difference between-patch pollen transfer occurred for 1 per cent of between the total number of detections on control and treat- control site flowers and 5 per cent of treatment site flowers 2 ment sites. (Poisson GLMM: x1 ¼ 6.120, p ¼ 0.013, figure 2c). Analyses using the presence or absence of transferred (c) Seedling recruitment surveys pollen at the patch level revealed the same pattern 2 In 2007, we completed 129 random vegetation surveys on (within-patch binomial GLMM: x1 ¼ 8.800, p ¼ 0.003; 2 25 m diameter vegetation plots (approx. 490 m2) located between-patch binomial GLMM: x1 ¼ 5.608, p ¼ 0.018). on nine treatment and eight control sites, some of which were not the same sites used in the seed-removal exper- (b) Pinus edulis seed removal iments, which included only six pairs of sites (12 total). Noise amplitude values were consistently higher (approx. Ten treatment sites were surveyed in 2007, but we excluded 14 dB(A)) at treatment seed stations relative to control 2 vegetation plots from one site from this analysis because seed stations (LMM: x1 ¼ 19.084, p , 0.001, electronic the compressor was installed in 2006, thus confounding the supplementary material, figure S2d), yet neither seed- 2 acoustic conditions during which many seedlings may have removal rate (LMM: x1 ¼ 2.209, p ¼ 0.137), nor been established (see below). Compressors on all other documented species richness per seed station differed treatment sites had been in place for at least 6 years, but between sites with and without noise (Poisson GLMM: 2 over 10 years for several sites. x1 ¼ 0.461, p ¼ 0.497). Because our fieldwork in previous years had documented The majority of animals detected with motion-triggered an avoidance of noise by A. californica [7], in 2007, we cameras removing seeds from stations were easily identified counted all P. edulis seedlings per vegetation plot. We to species; however, for two groups, Peromyscus mice and restricted counts of seedlings to those less than or equal to Sylvilagus rabbits, we were not always able to identify indi- 20 cm to make sure that they had been dispersed and viduals to species; therefore, they were assigned to their

Proc. R. Soc. B (2012) Downloaded from rspb.royalsocietypublishing.org on December 11, 2013

Noise alters ecological services C. D. Francis et al. 2731

Mice were detected at 63 per cent of treatment seed pollination (a) stations and only 45 per cent of control stations (binomial 2 3 GLMM: x1 ¼ 4.023, p ¼ 0.045; figure 3a). By contrast, A. californica was detected removing seeds exclusively 2 at control stations (x1 ¼ 5.486, p ¼ 0.019; figure 3b). Peromyscus mice and A. californica were also the only taxa 2 with strong effects on seed removal and, along with Tamias minimus, were taxa with strong influences on pat- terns of seed predation at the seed station (i.e. presence 1 of opened seed coats). Seed removal rates were approxi-

visits per patch mately 30 per cent higher at stations where Peromyscus mice or A. californica were documented removing seeds 0 compared with stations where they were not detected 2 (LMM: x2 ¼ 35.775, p , 0.001; figure 3c,d). Seed preda- tion was positively affected by the presence of Peromyscus control treatment mice (bmouse ¼ 0.841 + 0.412 s.e.) and T. minimus (bchipmunk ¼ 1.199 + 0.544 s.e.), both typically considered seed predators [20], but negatively affected by the presence of A. calilfornia (bscrub-jay ¼ 22.031 + 1.005 s.e.; binomial (b)(c) 2 GLMM: x3 ¼ 13.748, p ¼ 0.003). Indeed, most stations where Peromyscus mice (74%) and T. minimus (81%) were detected also had evidence of seed predation, but only 33 6 per cent of stations where A. california was detected were there signs of seed predation.

4 (c) Pinus edulis seedling recruitment Consistent with the difference in animals removing seeds in 2 noisy and quiet areas, P. e d u l i s seedlings were four times more abundant on control sites relative to treatment sites (bTreatment ¼ 21.543 + 0.240 s.e.; figure 3e), but number pollinated flowers per patch pollinated flowers 0 of J. osteosperma trees (bJuniper ¼ 0.036 + 0.016 s.e.) and the proportion of dead organic ground cover (bDead ¼ control treatment control treatment 0.023 + 0.008 s.e.) had small, positive effects on 2 seedling abundance (Poisson GLMM: x3 ¼ 38.583, Figure 2. Evidence from pollination experiment. (a) Archilochus p , 0.001). However, neither of these variables, nor alexandri visited artificial flowers on noisy treatment patches number of P. e d u l i s trees, differed between treatment and more than quiet control site patches. The values displayed reflect control sites (juniper LMM: x2 ¼ 0.726, p ¼ 0.394; dead the sum of visits per site (14 sites total with two patches per site, 1 ground cover LMM: x2 ¼ 0, p ¼ 1.0; P. e d u l i s LMM: five plants per patch and three flower per plant). (b,c) Pollination 1 2 ¼ ¼ of individual flowers was higher on treatment sites relative to x1 2.560, p 0.110), suggesting that other habitat fea- control sites both (b) within and (c) between patches. Values tures can be excluded as alternative explanations for displayed reflect the sum of pollinated flowers in both patches P.edulis seedling recruitment on treatment and control sites. per site. (a-c) Lines link geographically paired sites.

4. DISCUSSION respective genera. In total, we document 11 taxa removing Elevated noise levels affected pollination rates by hum- seeds, nine of which were considered seed predators (elec- mingbirds and P. edulis seed dispersal and seedling tronic supplementary material, table S2). Cameras failed to recruitment, but the direction of each effect was different. detect the identity of animals that removed seeds at Noise exposure had an indirect positive effect on pollina- approximately one station per site, primarily owing to bat- tion by hummingbirds, but an indirect negative effect on tery failure. However, there was no difference in the P.edulis seedling establishment by altering the composition number of camera failures between treatment and control of animals preying upon or dispersing seeds. These results sites that would suggest our detections were biased towards extend our knowledge of the consequences of noise 2 one site type over the other (binomial GLMM: x1 ¼ 0.240, exposure, which has primarily focused on vocal responses p ¼ 0.624); therefore, any relative differences in detections to noise [8,34,35], somewhat on species distributions and between treatment and control sites should reflect actual reproductive success [7,10,32,36] and very little on species differences between noisy and quiet areas. interactions [7,14–16]. In an example of the latter, traffic Of the nine seed predators documented removing seeds, noise negatively affects bat (Myotis myotis) foraging effi- only one, Pipilo maculatus, was detected more frequently on ciency by impairing its ability to locate prey by listening control sites relative to treatment sites (binomial GLMM: to sounds generated from prey movement [14]. Here, 2 x1 ¼ 4.133, p ¼ 0.042); a pattern consistent with previous our data demonstrate that the frequency of species inter- findings that P.maculatus avoids noise in its nest placement actions can change without a direct effect of noise on the [7]. We also documented seed removal by Peromyscus mice interaction itself, suggesting that noise exposure may and A. californica, considered to be primarily seed preda- trigger changes to numerous ecological interactions and tors and important seed dispersers, respectively [20]. reverberate through communities.

Proc. R. Soc. B (2012) Downloaded from rspb.royalsocietypublishing.org on December 11, 2013

2732 C. D. Francis et al. Noise alters ecological services

(a)(b) seed 1.0 0.3 removal 1.8 and seedling 0.2 recruitment 1.6 1.4 0.1 1.2

0 0

proportion of stations per site control treatment control treatment

(c)(d)(e)

20 8 15 6 10 4 5 2 piñon seedlings seed removal rate seed removal 0 0 absent present absent present control treatment Figure 3. (a) Peromyscus mice were detected more frequently at treatment seed stations relative to control stations. (b) A. cali- fornica removed seeds exclusively on control sites. Values displayed in (a) and (b) reflect the proportion of seed stations per site where mice or jays were detected. (c,d) Seed removal rates (per 24 h) were higher when (c) Peromyscus mice or (d) A. californica were detected at a seed station. (e) Pinus edulis seedling recruitment was significantly higher on control sites relative to treatment sites. Box plots indicate the median value (solid black line), 25th and 75th percentiles (box), and whiskers denote 1.5 the interquartile range. Outliers are denoted by open circles.

Increases in pollination rates were in line with our with protein-rich animal prey [41], individuals at our prediction based on the positive responses to noise by study area may have been foraging primarily on animal A. alexandri, both in terms of nest-site selection [7] and prey rather than P. edulis seeds during our experiments. abundances determined from surveys [17]. Our exper- Second, our use of seed stations on the ground did not imental design and use of artificial flowers were account for seed removal from cones in the canopy by advantageous because we could control for variation in other important seed dispersers, such as Gymnorhinus density and the spatial arrangement of nectar resources cyanocephalus (pin˜on jay); a species that occurs in that can influence pollination patterns [37]. However, RCHMA, but also avoids noisy areas [7,42].Thedegreeto this approach precluded us from determining whether which these factors contribute to reduced seedling recruit- increases in pollination in noisy areas results in greater ment in noisy areas is unknown, but provides an interesting seed and fruit production. This is probable for I. aggregata avenue of research for future study. because it can be pollen limited throughout its range Although, A. californica and Peromyscus mice had the [38–40] and fruit set is strongly correlated with pollinator greatest influence on seed-removal rates, we were unable (e.g. hummingbird) abundance [18]. Therefore, noise- to track the fate of individual seeds. Nevertheless, these dependent increases in A. alexandri abundances [7,17] species influenced patterns of seed predation in a coupled with increases in visits to artificial flowers in this manner consistent with knowledge of how these species study is suggestive that I. aggregata plants exposed to elev- differ as mobile links for P. edulis seed dispersal and seed- ated noise levels may have greater reproductive output ling establishment. Evidence of seed predation was less relative to individuals in quiet areas. common at seed stations visited by A. californica, poten- Seed removal, seed predation and seedling recruitment tially reflecting its role as an important disperser of data were consistent with one another and our expec- P. edulis seeds. For example, one A. californica individual tations, suggesting that noise has the potential to may cache up to 6000 P. edulis seeds in locations favour- indirectly affect woodland structure. It is plausible that able for germination during a single autumn [43]. Many the suite of species removing seeds may differ in June seeds are relocated and consumed, but many go unre- and July when we conducted our study from that found covered and germinate [20]. By contrast, although in the autumn when seeds are typically available. Yet, all Peromyscus mice might function as conditional dispersers species documented removing seeds are year-round resi- under some circumstances [44,45], here their presence dents and their relative abundances are unlikely to at a seed station was a strong predictor of seed predation, fluctuate between treatment and control sites throughout reflecting their primary role as seed predators [20]. Pre- the year. Instead, it is more likely that we underestimated vious research using experimental enclosures to study the magnitude of the difference in seed dispersal quality caching behaviour in the field supports our findings between noisy and quiet areas for two main reasons. [29,44]. Peromyscus mice consume a large proportion First, because A. californica typically provision young (approx. 40%) of encountered seeds and typically cache

Proc. R. Soc. B (2012) Downloaded from rspb.royalsocietypublishing.org on December 11, 2013

Noise alters ecological services C. D. Francis et al. 2733 many encountered seeds that are not immediately con- initial changes in stand structure could have gone un- sumed [44]. Yet, cached seeds are often recovered and detected for decades. Such long-term changes may have eaten (greater than 80%) along with seeds cached by important implications for the woodland community as other individuals or species [29]. Thus, the reduced den- a whole by prolonging the negative consequences of sity of seedlings in noisy areas could be explained not only noise exposure. That is, noise may not only result in by fewer seeds entering the seed bank as a result of large declines in diversity during exposure by causing reduced densities of important avian seed dispersers site abandonment or reduced densities by many species that cache many thousands of seeds, but because seeds [7,10], but diversity may suffer long after noise sources present within the seed bank experience elevated rates are gone because fewer P.edulis trees will provide less criti- of predation via cache pilfering associated with noise- cal habitat for the many hundreds of species that depend dependent increases in Peromyscus mice. on them for survival [48]. Despite the concordance between our findings and These separate experiments highlight that noise pol- the literature regarding the roles of A. californica and lution is a strong environmental force that may alter key Peromyscus mice on P. edulis seed dispersal and predation, ecological processes and services. Over a decade ago, seedling mortality caused by key seedling predators, such Forman [4] estimated that approximately one-fifth of as Odocoileus hemionus (mule deer) and Cervus canadensis the land area in the United States is affected by traffic (elk), could potentially explain the higher density of seed- noise, yet the actual geographical extent of noise exposure lings in quiet relative to noisy areas. However, ungulates is undoubtedly greater when other sources are con- such as C. canadensis appear to avoid areas exposed to sidered. Additionally, this spatial footprint of noise, the noise from high traffic volume [46], suggesting that seed- anthropogenic soundscape, will only increase because ling mortality owing to browsing ungulates should be sources of noise pollution are growing at a faster rate greater in areas with less noise and leading to a pattern than the human population [3]. These data suggest that opposite from that which we observed. Still needed are anthropogenic soundscapes have or will encompass confirmatory studies that track the fate of cached seeds nearly all terrestrial habitat types, potentially impacting and document patterns of seedling predation within innumerable species interactions both directly and noisy and quiet areas. indirectly. It is critical that we identify which other func- Despite the downstream consequences of species- tionally unique species abandon or preferentially settle in specific response to noise exposure, the mechanistic other noisy areas around the world. Early detection of reasons for species-specific responses are still not clear. altered species distributions and the resulting disrupted Aphelocoma californica may avoid noisy areas because or enhanced ecological services will be key to understand- noise can mask their vocal communication. Larger birds ing the trajectory of the many populations and with lower frequency vocalizations are more sensitive to communities that outwardly appear to persist despite noise than smaller species with higher frequency vocaliza- our industrial rumble. tions because their vocalizations overlap low-frequencies This study was completed in compliance with the University where noise has more acoustic energy [17]. Aphelocoma of Colorado Animal Care and Use Committee. californica is also the main nest predator in the study area [7,16] and it is possible that noise masks acoustic We thank our many research assistants, plus C. Quintero, cues used to locate prey at nests (e.g. nestling and J. Paritsis and S. Wagner for their help with pollination parent calls). It is also possible that these forms of acous- experiments. We also thank C.A. Botero, C.R. McClain and tic interference may lead to elevated stress levels that the anonymous referees for useful suggestions and comments on earlier versions of this manuscript. This work was primarily could influence patterns of habitat use [13], but research supported by NSF DDIG (no. IOS 0910092), United States on this potential link is currently lacking. Bureau of Land Management, ConocoPhillips, Williams In contrast to the direct effect noise may have on Energy and U. Colorado Department of Ecology and A. californica communication and foraging, positive Evolutionary Biology. C.D.F was supported by the National responses to noise by A. alexandri and Peromyscus mice Evolutionary Synthesis Center (NESCent; NSF EF-0905606). probably reflect indirect responses to noise. Noisy areas may represent refugia from predators and key competitors REFERENCES that typically avoid noisy areas, including jays. For 1 Ellis, E. C. 2011 Anthropogenic transformation of example, A. alexandri may preferentially settle in noisy the terrestrial biosphere. Phil. Trans. R. Soc. A 369, areas in response to cues indicative of lower nest preda- 1010–1035. (doi:10.1098/rsta.2010.0331) tion pressure from A. californica. Similarly, Peromyscus 2 Ellis, E. C. & Ramankutty, N. 2008 Putting people in the mice populations may increase in noisy areas not only map: anthropogenic biomes of the world. Front. Ecol. because of reduced competition with A. californica and Environ. 6, 439–447. (doi:10.1890/070062) other jays for key-foraging resources, but also in response 3 Barber, J. R., Crooks, K. R. & Fristrup, K. M. 2010 The to reduced predation by nocturnal acoustic predators that costs of chronic noise exposure for terrestrial organisms. may avoid noise [14], such as owls. Trends Ecol. Evol. 25, 180–189. (doi:10.1016/j.tree. That noise may alter patterns of seedling recruitment 2009.08.002) adds important insights to our earlier work where we 4 Forman, R. T. T. 2000 Estimate of the area affected ecolo- gically by the road system in the United States. Conserv. found neither P. edulis tree density, nor 12 other habitat Biol. 14, 31–35. (doi:10.1046/j.1523-1739.2000.99299.x) features differed between treatment and control sites 5 Francis, C. D., Paritsis, J., Ortega, C. P. & Cruz, A. 2011 [7]. This, however, may be slowly changing. Reduced Landscape patterns of avian habitat use and nest success P.edulis seedling recruitment in noisy areas may eventually are affected by chronic gas well compressor noise. translate into fewer mature trees, yet because P. edulis is Landscape Ecol. 26, 1269–1280. (doi:10.1007/S10980- slow growing and has long generation times [47], these 011-9609-Z)

Proc. R. Soc. B (2012) Downloaded from rspb.royalsocietypublishing.org on December 11, 2013

2734 C. D. Francis et al. Noise alters ecological services

6 Francis, C. D., Ortega, C. P. & Cruz, A. 2011 Vocal 25 Waser, N. M. & McRobert, J. A. 1998 Hummingbird frequency change reflects different responses to anthro- foraging at experimental patches of flowers: evidence pogenic noise in two suboscine tyrant flycatchers. for weak risk-aversion. J. Avian Biol. 29, 305–313. Proc. R. Soc. B 278, 2025–2031. (doi:10.1098/rspb. 26 R Core Development Team 2010 R: a language and 2010.1847) environment for statistical computing. Vienna, Austria: R 7 Francis, C. D., Ortega, C. P. & Cruz, A. 2009 Noise Foundation for Statistical Computing. pollution changes avian communities and species inter- 27 Dudash, M. R. 1991 Plant size effects on female and male actions. Curr. Biol. 19, 1415–1419. (doi:10.1016/j.cub. function in hermaphroditic Sabatia angularis (Gentianaceae). 2009.06.052) Ecology 72, 1004–1012. (doi:10.2307/1940600) 8 Francis, C. D., Ortega, C. P. & Cruz, A. 2011 Different 28 Kearns, C. A. & Inouye, D. W. 1993 Techniques for polli- behavioural responses to anthropogenic noise by two clo- nation biologists. Niwot, CO: University of Colorado sely related passerine birds. Biol. Lett. 7, 850–852. Press. (doi:10.1098/rsbl.2011.0359) 29 Vander Wall, S. B. 2000 The influence of environmental 9 Halfwerk, W. & Slabbekoorn, H. 2009 A behavioural conditions on cache recovery and cache pilferage by mechanism explaining noise-dependent frequency use yellow pine chipmunks (Tamias amoenus) and deer mice in urban birdsong. Anim. Behav. 78, 1301–1307. (Peromyscus maniculatus). Behav. Ecol. 11, 544–549. (doi:10.1016/j.anbehav.2009.09.015) (doi:10.1093/beheco/11.5.544) 10 Bayne, E. M., Habib, L. & Boutin, S. 2008 Impacts of 30 Harrington, M. G. 1987 Characteristics of 1-year-old chronic anthropogenic noise from energy-sector activity on natural pinyon seedlings. Research Note RM-477. Fort abundance of songbirds in the boreal forest. Conserv. Biol. Collins, CO: U.S.D.A. Forest Service, Rocky Mountain 22,1186–1193.(doi:10.1111/j.1523-1739.2008.00973.x) Research Station. 11 Slabbekoorn, H. & Ripmeester, E. A. P. 2008 Birdsong 31 Segura, G. & Snook, L. C. 1992 Stand dynamics and and anthropogenic noise: implications and applications regeneration patterns of a pinyon pine forest in east cen- for conservation. Mol. Ecol. 17, 72–83. (doi:10.1111/j. tral Mexico. Forest Ecol. Manag. 47, 175–194. (doi:10. 1365-294X.2007.03487.x) 1016/0378-1127(92)90273-C) 12 Patricelli, G. L. & Blickley, J. L. 2006 Avian communi- 32 Halfwerk, W., Holleman, L. J. M., Lessells, C. M. & cation in urban noise: causes and consequences of vocal Slabbekoorn, H. 2011 Negative impact of traffic adjustment. Auk 123, 639–649. (doi:10.1642/0004- noise on avian reproductive success. J. Appl. Ecol. 48, 8038(2006)123[639:ACIUNC]2.0.CO;2) 210–219. (doi:10.1111/j.1365-2664.2010.01914.x) 13 Kight, C. R. & Swaddle, J. P. 2011 How and why 33 Summers, P. D., Cunnington, G. M. & Fahrig, L. 2011 environmental noise impacts animals: an integrative, Are the negative effects of roads on breeding birds mechanistic review. Ecol. Lett. 14, 1052–1061. (doi:10. caused by traffic noise? J. Appl. Ecol. 48, 1527–1534. 1111/J.1461-0248.2011.01664.X) (doi:10.1111/j.1365-2664.2011.02041.x) 14 Siemers, B. M. & Schaub, A. 2011 Hunting at the high- 34 Gross, K., Pasinelli, G. & Kunc, H. P. 2010 Behavioral way: traffic noise reduces foraging efficiency in acoustic plasticity allows short-term adjustment to a novel environ- predators. Proc. R. Soc. B 278, 1646–1652. (doi:10. ment. Am. Nat. 176, 456–464. (doi:10.1086/655428) 1098/rspb.2010.2262) 35 Halfwerk, W., Bot, S., Buikx, J., van der Velde, M., 15 Schaub, A., Ostwald, J. & Siemers, B. M. 2008 Foraging Komdeur, J., Ten Cate, C. & Slabbekoorn, H. bats avoid noise. J. Exp. Biol. 211, 3174–3180. (doi:10. 2011 Low-frequency songs lose their potency in 1242/jeb.022863) noisy urban conditions. Proc. Natl Acad. Sci. USA 108, 16 Francis, C. D., Ortega, C. P., Kennedy, R. I. & Nylander, 14 549–14 554. (doi:10.1073/pnas.1109091108) P. J. In press. Are nest predators absent from noisy areas 36 Habib, L., Bayne, E. M. & Boutin, S. 2007 Chronic or unable to locate nests? Ornithol. Monogr. industrial noise affects pairing success and age structure 17 Francis, C. D., Ortega, C. P. & Cruz, A. 2011 Noise of ovenbirds Seiurus aurocapilla. J. Appl. Ecol. 44, pollution filters bird communities based on vocal fre- 176–184. (doi:10.1111/j.1365-2664.2006.01234.x) quency. PloS ONE 6, e27052. (doi:10.1371/journal. 37 Feinsinger, P., Iii, H. M. T. & Young, B. E. 1991 Do pone.0027052) tropical bird-pollinated plants exhibit density-dependent 18 Paige, K. N. & Whitham, T. G. 1987 Flexible life-history interactions? Field experiments. Ecology 72, 1953–1963. traits: shifts by scarlet gilia in response to pollinator abun- (doi:10.2307/1941550) dance. Ecology 68, 1691–1695. (doi:10.2307/1939861) 38 Hainsworth, F. R., Wolf, L. L. & Mercier, T. 1985 Pollen 19 Vander Wall, S. B. & Balda, R. P. 1981 Ecology and evol- limitation in a monocarpic species, Ipomopsis aggregata. ution of food-storage behavior in conifer-seed-caching J. Ecol. 73, 263–270. corvids. Z. Tierpsychol. 56, 217–242. (doi:10.1111/j. 39 Campbell, D. R. & Halama, K. J. 1993 Resource and 1439-0310.1981.tb01298.x) pollen limitations to lifetime seed production in a natural 20 Chambers, J. C., Vander Wall, S. B. & Schupp, E. W. plant population. Ecology 74, 1043–1051. (doi:10.2307/ 1999 Seed and seedling ecology of pinon and juniper 1940474) species in the pygmy woodlands of western North Amer- 40 Juenger, T. & Bergelson, J. 1997 Pollen and resource ica. Bot. Rev. 65, 1–38. (doi:10.1007/BF02856556) limitation of compensation to herbivory in scarlet gilia, 21 Hurly, T.A. 1996 Spatial memory in rufous hummingbirds: Ipomopsis aggregata. Ecology 78, 1684–1695. (doi:10. memory for rewarded and non-rewarded sites. Anim. 1890/0012-9658(1997)078[1684:PARLOC]2.0.CO;2) Behav. 51, 177–183. (doi:10.1006/anbe.1996.0015) 41 Curry, R. L., Peterson, A. T. & Langen, T. A. 2002 22 Hurly, T.A., Franz, S. & Healy, S. D. 2010 Do rufous hum- Western scrub-jay (Aphelocoma californica), no. 712. In mingbirds (Selasphorus rufus)usevisualbeacons?Anim. The birds of North America (ed. A. Poole), pp. 1–36. Cogn. 13,377–383.(doi:10.1007/s10071-009-0280-6) Ithaca, NY: Cornell Laboratory of Ornithology. 23 Baum, K. A. & Grant, W. E. 2001 Hummingbird for- 42 Ortega, C. P. & Francis, C. D. In press. Effects of gas well aging behavior in different patch types: simulation of compressor noise on ability to detect birds during surveys alternative strategies. Ecol. Model. 137, 201–209. in northwest New Mexico. Ornithol. Monogr. (doi:10.1016/S0304-3800(00)00436-1) 43 Balda, R. P. 1987 Avian impact on pinyon-juniper 24 Pleasants, J. M. 1983 Nectar production patterns in Ipomop- woodland. In Proc. pinyon-juniper Conf., General Technical sis aggregata (Polemoniaceae). Am.J.Bot.70, 1468–1475. Report INT-215 (ed. R. L. Everett), pp. 526–533.

Proc. R. Soc. B (2012) Downloaded from rspb.royalsocietypublishing.org on December 11, 2013

Noise alters ecological services C. D. Francis et al. 2735

Ogden, UT: Intermountain Forest and Range distribution and highway crossings in Arizona. J. Wildl. Experiment Station. Manage. 71, 2318–2323. (doi:10.2193/2006-224) 44 Pearson, K. M. & Theimer, T. C. 2004 Seed-caching 47 Floyd, M. L., Colyer, M., Hanna, D. D. & responses to substrate and rock cover by two Peromyscus Romme, W. H. 2003 Gnarly old trees: canopy character- species: implications for pinyon pine establishment. istics of old-growth pin˜on-juniper woodlands. In Ancient Oecologia 141,76–83.(doi:10.1007/s00442-004-1638-8) pin˜on-juniper woodlands (ed. M. L. Floyd), pp. 11–29. 45 Theimer, T. C. 2005 Rodent seed dispersers as con- Boulder, CO: University of Colorado Press. ditional mutualists. In Seed fate: predation, dispersal and 48 Mueller, R. C., Scudder, C. M., Porter, M. E., seedling establishment (eds P.-M. Forget, J. E. Lambert, Trotter, R. T., Gehring, C. A. & Whitham, T. G. P. E. Hulme & S. B. Vander Wall), pp. 283–296. 2005 Differential tree mortality in response to severe Cambridge, MA: CABI Press. drought: evidence for long-term vegetation shifts. 46 Gagnon, J. W., Theimer, T. C., Boe, S., Dodd, N. L. & J. Ecol. 93, 1085–1093. (doi:10.1111/j.1365-2745. Schweinsburg, R. E. 2007 Traffic volume alters elk 2005.01042.x)

Proc. R. Soc. B (2012) REVIEWS REVIEWS REVIEWS A framework for understanding noise impacts on wildlife: an urgent conservation priority

Clinton D Francis1*† and Jesse R Barber2†

Anthropogenic noise is an important environmental stressor that is rapidly gaining attention among biologists, resource managers, and policy makers. Here we review a substantial literature detailing the impacts of noise on wildlife and provide a conceptual framework to guide future research. We discuss how several likely impacts of noise exposure have yet to be rigorously studied and outline how behavioral responses to noise are linked to the nature of the noise stimulus. Chronic and frequent noise interferes with animals’ abilities to detect important sounds, whereas intermittent and unpredictable noise is often perceived as a threat. Importantly, these effects can lead to fitness costs, either directly or indirectly. Future research should consider the range of behavioral and physiological responses to this burgeoning pollutant and pair measured responses with metrics that appro- priately characterize noise stimuli. This will provide a greater understanding of the mechanisms that govern wildlife responses to noise and help in identifying practical noise limits to inform policy and regulation.

Front Ecol Environ 2013; doi:10.1890/120183

n emerging aim in applied ecology and conservation its ability to inform conservation policy. As more attention Abiology is to understand how human-generated noise and resources are invested in understanding the full eco- affects taxonomically diverse organisms in both marine (eg logical effects of noise, it is important that investigators Slabbekoorn et al. 2010; Ellison et al. 2012) and terrestrial design research questions and protocols in light of the (eg Patricelli and Blickley 2006; Barber et al. 2010; Kight many possible costs associated with noise exposure and also and Swaddle 2011) environments. Noise is a spatially that they properly link responses to several relevant fea- extensive pollutant and there is growing evidence to sug- tures of noise, such as intensity, frequency, or timing, that gest that it may have highly detrimental impacts on nat- could explain wildlife responses (Panel 1). ural communities; yet efforts to address this issue of emerg- Here we introduce a framework using a mechanistic ing conservation concern lack a common framework for approach for how noise exposure can impact fitness at the understanding the ecological consequences of noise. A level of the individual organism as a result of changes in conceptual scaffold is critical to scientific progress and to behavior, and identify several acoustic characteristics that are relevant to noise exposure and ecological integrity. We provide representative examples of noise impacts, primar- In a nutshell: ily from terrestrial systems; however, these issues are • Noise is an intense, widespread pollutant, relevant to conser- equally applicable to organisms in aquatic environments. vation efforts worldwide We stress that various responses to noise exposure are less • Using the number of animals present in environments obvious than those that have typically been studied to exposed to anthropogenic noise as the sole metric of noise impacts can be deceiving because there are many hidden date, such as signal modifications (eg changes in vocal fre- costs of noise exposure (eg compromising predator/prey quency, amplitude, or vocalization timing) and decreases detection or mating signals, altering temporal or movement in site occupancy (eg Bayne et al. 2008; Francis et al. patterns, increasing physiological stress) 2011b). Importantly, probable behavioral responses to • To ensure that conservation initiatives (and efforts to estab- noise that merit further scientific study might be detrimen- lish regulatory limits) are relevant, investigators must prop- erly characterize a suite of noise features tal to individual fitness and may have severe population- • Reducing noise exposure and incorporating sound measure- level consequences. As we show below, the presence of a ment into environmental planning will quickly benefit eco- species in a noisy area cannot be interpreted as an indica- logical systems tion that it is not being impacted by elevated sound levels, because there are many potential costs associated with noise exposure that have not been rigorously studied. 1National Evolutionary Synthesis Center, Durham, NC; current address: Biological Sciences Department, California Polytechnic ! Variation in responses to the same noise stimulus State University, San Luis Obispo, CA *([email protected]); 2Department of Biological Sciences, Boise State University, Boise, Species differ in their sensitivities to noise exposure ID; †the authors contributed equally to this work (Bayne et al. 2008; Francis et al. 2009, 2011a); however,

© The Ecological Society of America www.frontiersinecology.org Understanding noise impacts on wildlife CD Francis and JR Barber

(a) impacts in terms of pairing success, number of offspring, physiological stress, or other measures of fitness (Figure 1). Because the various responses may range from linear to threshold functions of noise exposure, investigators should take an integrative approach that incor- porates several different metrics (eg density, pairing success, number of offspring), rather than using a single metric to describe how noise influences their study organism. But which alterations in behavior are most likely to occur and which are the most detrimental? These are important questions because funding and logis- tical constraints ensure that measuring all of the (b) (c) (d) potential impacts of noise is impossible. Fortunately, the nature of sound stimuli can guide investigators toward likely behavioral changes that may influence fitness.

! Characterizing noise and the disturbance–interference continuum Figure 1. Responses to the same noise stimulus can take a variety of shapes. (a) The sound pressure level (SPL) of noise (red) decreases with increasing Determining whether a particular noise stimu- distance from the source but may not reach “baseline” ambient levels until lus is within an organism’s sensory capabilities is ~1 km away (this distance will vary depending on noise source and the foremost in importance; if a sound consists of environment). Response curves for species occupancy (blue solid line) and frequencies that are outside of an organism’s pairing rates (blue dashed line) in response to noise may have unique shapes, hearing range, it will not have a direct effect as might other measures of species responses to noise stimuli. The (Panel 1; Figure 2). Provided that an organism relationship between SPL and distance is from Francis et al. (2011c) and can hear the noise stimulus, its acoustic energy Francis (unpublished data) with noise generated from gas well compressors. could cause permanent or temporary hearing Behavioral responses are hypothetical but based on responses in Francis et loss, but this might only occur when the animal al. (2011c). (b) Spatial propagation of elevated noise levels from a point is extremely close to the source of the noise source (such as a single car or an oil/gas compressor station), which decays (Dooling and Popper 2007). at a spreading loss of 6 dB or more per doubling of distance, due to the Instead, sounds may have their greatest influ- geometry of the spherical wave front. It is important to note that line sources ence on behavior, which then translates into fit- (such as a busy highway; not shown) lose only 3 dB per doubling of distance ness costs, but how and why noise elicits a due to their cylindrical wave front. Clearly, knowledge of the geometry of response can vary greatly (Figures 2 and 3). At anthropogenic noise stimuli is essential to understanding the scale of one extreme, noise stimuli that startle animals exposure. (c and d) Spatial representation of (c) species occupancy and (d) are perceived as threats and generate self-preser- pairing success surrounding a point source of noise. vation responses (eg fleeing, hiding), which are similar to responses to real predation risk or non- the degree to which individuals vary in sensitivity to lethal human disturbance (ie the risk–disturbance noise during each life-history stage or due to behavioral hypothesis, which posits that animal responses to human context has been underappreciated. For example, oven- activities are analogous to their responses to real predation bird (Seiurus aurocapilla) habitat occupancy appears unin- risk; Frid and Dill 2002). Noise stimuli at this end of the fluenced by noise exposure (Habib et al. 2007; Bayne et al. continuum are often infrequent, but are abrupt and unpre- 2008; Goodwin and Shriver 2011), yet males defending dictable. At the other end of the continuum, noise can noisy territories are less successful in attracting mates impair sensory capabilities by masking biologically rele- (Habib et al. 2007). Reed buntings (Emberiza schoeniclus) vant sounds used for communication, detection of threats also show reduced pairing success in noisy areas (Gross et or prey, and spatial navigation. These noise stimuli tend to al. 2010). Such examples should serve as a warning to be frequent or chronic and their spectral (ie frequency) biologists, land managers, and policy makers: the same content overlaps with biologically relevant sounds. noise stimulus can affect various response metrics in dif- Increases in noise intensity (loudness or amplitude) will ferent ways. An organism might show little to no increase the severity of the impacts, regardless of whether response to noise in terms of habitat occupancy or forag- it is perceived as a threat or masks biologically relevant ing rate, for example, but may experience strong negative sounds. An important supplement to this dichotomy is www.frontiersinecology.org © The Ecological Society of America CD Francis and JR Barber Understanding noise impacts on wildlife that limited stimulus processing capacity could be in spatial distributions or movements, (3) decreases in responsible for some detrimental effects. Noise stimuli foraging or provisioning efficiency coupled with of various kinds might act as a distraction, drawing the increased vigilance and anti-predator behavior, and (4) animal’s attention to a sound source and thereby impair- changes in mate attraction and territorial defense (Figure ing its ability to process information perceived through 3). As demonstrated below, these disturbance-, distrac- other sensory modalities (Chan et al. 2010). Alter- tion-, and masking-mediated behavioral changes could natively, noise may reduce auditory awareness, trigger directly impact individual survival and fitness or lead to increased visual surveillance, and compromise visually physiological stress that may then compromise fitness. mediated tasks. The mechanistic details and ecological importance of such distractions still need to be fully Changes in temporal patterns explored. Regardless, the conservation implications of understanding the importance of noise as a distractor Sound stimuli that are perceived as threats can alter tem- are not trivial; if distraction is a fundamental route poral patterns; for example, red foxes (Vulpes vulpes) cross for noise impacts, our concern might spread beyond busy roads when traffic rates are lower, suggesting noise those frequencies that overlap with biologically relevant cues might be affecting the timing of their movements signals. (Figure 3b; Baker et al. 2007). Similarly, noise from boat traffic disrupts the timing of foraging by West Indian ! Behavioral changes manatees (Trichechus manatus), potentially influencing foraging efficiency and energy budgets (Figure 3m; Although a limited number of laboratory studies have Miksis-Olds et al. 2007). Noise can also change behavior suggested that noise may affect gene expression, physio- due to interference with cue detection. European robins logical stress, and immune function directly (Figure 3a; (Erithacus rubecula) avoid acoustic interference from Kight and Swaddle 2011), most noise-related impacts urban noise by singing at night, when noise levels are appear to involve behavioral responses across four cate- lower than during daylight hours (Figure 3c; Fuller et al. gories: (1) changes in temporal patterns, (2) alterations 2007). Although this example may appear to be an

Panel 1. Sound features relevant to noise-impact studies

In the main text we discuss how the spectral (frequency) compo- assumed, which may be inappropriate for many animals. sition of noise is related to an organism’s hearing range and its In contrast, quantification of chronic noise can best be served

ability to detect relevant sounds. For these reasons, it is critical with time-averaged values such as Leq (WebFigure 1b). Leq is typi- that researchers collect sound-level data with an appropriate fre- cally calculated over 24 hours; however, many studies fail to report

quency-weighting filter. For instance, the “A” filter on many over what time period Leq values were integrated and a 24-hr inte- sound-level meters is based on equal loudness contours for gration is assumed, which may not be appropriate for many eco- human hearing; this filter provides a conservative estimate of bird logical questions. For example, for a species that is sensitive to hearing and is the best readily-available weighting for bird studies traffic noise, such as the white-breasted nuthatch (Sitta carolinensis; (Dooling and Popper 2007). However, whether working with WebFigure 1b; Goodwin and Shriver 2011), it may be best to trun- birds or other taxa, it is best to simultaneously record and mea- cate the time interval to the hours of biological interest, such as sure the noise using a “flat” frequency filter, then truncate the during dawn chorus. Limiting frequency analyses to the hearing or resulting spectral output to the most relevant frequency range for vocal range of the target species or community may also be bene- each species of interest (see below). ficial (eg Halfwerk et al. 2011b). Future studies should aim to use Investigators should also avoid the temptation to characterize a biologically relevant integration times and report these details. noise stimulus as a single decibel value, whether weighted or not, Best practices will include simultaneous acquisition of high-qual- as other metrics that describe the noise are equally important ity audio recordings along with multiple sound level measurements (Figure 2). Time-averaged values, such as equivalent continuous to offer unconstrained opportunities to investigate alternative

sound level (Leq), can be extremely informative to describe sounds spectral filtering, time integration, and additional measurements, that are chronic or frequent; however, these integration times do such as order statistics indicating the percentage of time above a not properly characterize sounds that occur once, infrequently, or certain decibel level or metrics reflective of the sound event’s pre- more regularly. Instead, measurements integrated over several dictability (Figure 2). Carefully considering how these temporal, hours will mischaracterize short, abrupt sounds that could be intensity, and frequency features (Figure 2b) interact will help inves- viewed as disturbances, such as noise events created by infrequent tigators identify where along the disturbance–interference contin- and loud military jet overflights that alter the behavior and time uum (Figure 2a) the stimulus is most likely to fall and will help iden- budgets of harlequin ducks (Histrionicus histrionicus; WebFigure 1; tify the most likely behavioral responses (Figure 3). Goudie 2006). For disturbance sounds, exposure metrics that Above all, to maximize interpretability of results, facilitate com-

capture each sound event’s maximum power (Lmax; WebFigure 1a) parisons among studies, and provide meaningful data for conserva- and the rate at which power rises from the lowest detectable tion measures, it is critical to explicitly report the acoustic metrics

level to its maximum are important (ie onset; Figure 2). Lmax used in each study to describe species responses. Additional values are often reported without stating the frequency weight- sound metric and terminology details can be found in Barber et al. ing; in these cases, A-weighting (a human-centric curve) is (2011) and Pater et al. (2009).

© The Ecological Society of America www.frontiersinecology.org Understanding noise impacts on wildlife CD Francis and JR Barber

investigator’s ability to measure responses to noise. (a) Cue (b) Predictability masking For example, increases in continuous noise of 5–10 High Low decibels (dB, A-weighted; Panel 1) above baseline Onset can reduce bird numbers during standard bird sur- Slow Sudden veys by one-half, greatly biasing measures of site occupancy and abundance (Ortega and Francis Amplitude above ambient values 2012). If not carefully considered, this detection problem could bias subsequent interpretations and Low High management efforts. Despite the known effects of noise on popula- Overlap with biologically relevant sounds tion sizes, there is still considerable evidence to None/low Complete suggest that animals may abandon areas when fre- Overlap with organism’s hearing capabilities quent or chronic noise stimuli interfere with cue detection or when more variable sounds are per-

Frequency Intensity Temporal Intensity Frequency None/low High

Disturbance–interference continuum Disturbance–interference ceived as threats (Bayne et al. 2008; Goodwin and

Acute/infrequentNone/low Chronic/frequent High Shriver 2011; Blickley et al. 2012a). Birds with low-frequency vocalizations experience more Startle Potential severity of noise impact response acoustic interference from chronic low-frequency anthropogenic noise and therefore exhibit Figure 2. (a) The disturbance–interference continuum can range from stronger negative responses to noise in their habi- acute or infrequent noise stimuli that will likely trigger startle or hide tat use than birds with high-frequency vocaliza- responses to frequent or chronic noises that interfere with cue detection. tions that experience less acoustic interference (b) The severity of an impact from a noise stimulus will depend on the (Figure 3e; Francis et al. 2011a). These masking temporal, intensity, and frequency features of the stimulus. effects can be spatially extensive, potentially impairing communication at distances ranging important behavioral adaptation that permits this species from 0.5 to 1.0 km or farther from the noise source to overcome unfavorable acoustic conditions, the conse- (Blickley and Patricelli 2012). Furthermore, changes in quences of shifting the timing of song delivery are spatial distributions due to noise’s effect on cue detection unknown. The effects of signal timing on mate attraction are not restricted to intraspecific communication; for or territorial defense may be just as important to fitness as instance, greater mouse-eared bats (Myotis myotis), other signal features (eg frequency, syntax). Changes in which locate terrestrial prey based on sounds they gener- the timing of song delivery of less than one hour can ate when walking, also avoid hunting in noisy areas break down signaler–receiver coordination so that con- (Figure 3f; Schaub et al. 2008). In addition to disrupting specific males do not recognize species-specific signals cue detection at the intra- and interspecific level, ambi- (Luther 2008). If signaler–receiver coordination is dis- ent noise may also interfere with cue detection used for rupted between singing males and responsive females, the movement at larger spatial scales. Some frog species use behavioral flexibility that permits shifts in signal timing conspecific calls to locate appropriate breeding habitat, in response to noise may possibly be maladaptive. while some newt species use heterospecific calls for the Sleep is an important factor and follows a strong tem- same purpose (reviewed in Slabbekoorn and Bouton poral profile. Although a substantial body of research has 2008). Whether noise exposure impedes animals from investigated the impact of noise on sleep in humans, using such acoustic beacons to locate critical resources scant information is available regarding its effects in (eg water, food, habitat) is unknown and should be a other animals (reviewed in Kight and Swaddle 2011). focus of future research. Understanding the importance of sleep disruption on Site abandonment or decreases in population numbers overall fitness is critical as we might expect detrimental can also occur in response to unpredictable, erratic, or influences even for species not typically described as sudden sounds, which are perceived as threats (Figure dependent upon hearing (eg visually oriented predators 3d). For example, greater sage grouse (Centrocercus such as raptors). urophasianus) lek attendance declines at a higher rate in response to experimentally introduced intermittent road Alterations in spatial distributions or movements noise than to continuous noise (Blickley et al. 2012a), suggesting that sage grouse site occupancy may depend Among the most obvious responses to noise are site aban- more on perceived risk than on masking of acoustic cues. donment and decreases in spatial abundance. These met- Nevertheless, masking of communication may have other rics may also be easiest and least costly to quantify, which consequences (Figure 1). perhaps explains why there are many such examples in Species undoubtedly differ in their sensitivities to dis- the literature (eg Bayne et al. 2008; Eigenbrod et al. 2008; ruptive sounds, but individuals within a population also Francis et al. 2009). However, noise itself can affect an show such differences (Bejder et al. 2006). Individuals can www.frontiersinecology.org © The Ecological Society of America CD Francis and JR Barber Understanding noise impacts on wildlife

a – Kight and Swaddle (2011)

b –Baker et al. (2007)

c – Fuller et al. (2007)

d – Blickley et al. (2012a)

e – Francis et al. (2011a) Flee/hide Distraction Communication response f – Schaub et al. (2008) Soundscape Predator/prey g – Leonard and Horn (2012) orientation interactions h – Siemers and Schaub (2011)

i – Chan et al. (2010)

j – Quinn et al. (2006) Changes in spatial k – Gavin and Komers (2006) distributions or movements Increases in l – Halfwerk et al. (2011a) vigilance rates and anti-predator m – Miksis-Olds et al. (2007) Decreases in behavior Changes in foraging or mate n – Schaub et al. (2008) Changes in attraction or temporal provisioning efficiency territory o – Quinn et al. (2006) patterns defense* (and sleep) Gavin and Komers (2006)

p – Kight and Swaddle (2011)

Blickley et al. (2012b)

Increased stress, q – Bonier et al. (2009) decreased immune Survival and response r – Habib et al. (2007) reproductive success Halfwerk et al. (2011b)

Figure 3. Conceptual framework for understanding how noise stimuli – perceived as a threat or interfering with cue detection (the disturbance–interference continuum) – can elicit behavioral responses that have direct consequences for fitness or via a physiological stress response, which can also feed back to behavioral changes. Startle/hide responses are more likely to occur in response to noise stimuli that are perceived as a threat (acute, erratic, or sudden sounds). Problems arising from a failure to detect cues are more likely to occur when noise stimuli are chronic and overlap with biologically relevant cues used for communication, orientation, and predator/prey detection. Problems arising from distraction may occur as a result of sounds with features ranging from those that interfere with cue detection to those that are perceived as threats. Lowercase letters indicate studies (listed on the right) providing evidence for the link made for each arrow. Dashed arrows signify a link that we predict as important but for which no current evidence exists. The asterisk denotes that which could result from a change in behavior or a failure to change behavior in response to noise. vary greatly in their behavioral responses to stimuli, tive) and risk-prone (bold) behaviors can be heritable which may explain the variations in their ability to cope (Dingemanse et al. 2002). with environmental change (Sih et al. 2004). The redis- Site abandonment and changes in abundance provide tribution of sensitive and tolerant individuals across the only a limited understanding of how noise can impact landscape may not appear to be a problem. However, in wildlife populations and communities. Importantly, the case of social animals, where group living provides abundance can also be misleading because areas where protection from predation, the loss of sensitive individu- individuals are abundant do not always translate into als from the group through site abandonment could high fitness for those individuals (eg Johnson and increase predation risk for the group as a whole through Temple 1986). Using such evidence to conclude that the removal of the most vigilant group members. These noise has no impact is problematic; individuals may not sensitive individuals, who are now isolated from the have alternative areas to occupy or other responses (sur- group, lose the benefit of safety in numbers. Depending vival, mating success, reproductive output) may be neg- on population structure and the scale at which these indi- atively affected by noise even when abundance is high viduals are displaced by noise, genetic diversity may be (Figure 1a). These possibilities are especially likely reduced because traits that govern risk-averse (shy/sensi- when a noise stimulus is new and demographic processes

© The Ecological Society of America www.frontiersinecology.org Understanding noise impacts on wildlife CD Francis and JR Barber have not had time to impact population size or when represent a metabolic expense (relevant to survival and the population in an area that is exposed to noise is sup- reproductive success) will help to reveal the hidden plemented by individuals from elsewhere (ie source– costs of noise exposure. sink dynamics). Changes in mate attraction and territorial defense Decreases in foraging or provisioning efficiency and increased vigilance and anti-predator behavior The most direct way in which noise may alter an individ- ual’s ability to attract mates or defend its territory is Noise can impair foraging and provisioning rates directly through energetic masking, in which potential receivers (Figure 3, g and h) or indirectly as a consequence of are simply unable to hear another individual’s acoustic sig- increased vigilance and anti-predator behavior (Figure 3, nals through noise that is frequent or continuous during i–k, o). When noise is perceived as a threat, an organism important temporal signaling windows. Changes made to may miss foraging opportunities (“missed opportunity acoustic signals appear to be an adaptive behavioral cost”; Brown 1999) while hiding or as a result of main- adjustment that permits individuals to communicate taining increased vigilance (Figure 3k; Gavin and Komers under noisy conditions (eg Fuller et al. 2007; Gross et al. 2006). Missed opportunities can also occur when noise 2010; Francis et al. 2011b), yet these shifts could also incur interferes with cue detection. For instance, nestling tree a cost. In noisy areas, female great tits (Parus major) more swallows (Tachycineta bicolor) exposed to noise beg less in readily detect male songs sung at higher frequencies than response to recorded playbacks of parents arriving at nests females typically prefer (Halfwerk et al. 2011a). However, (eg calls, movement, sounds) than nestlings in quiet con- males who sing predominately at higher frequencies expe- ditions, presumably because the ambient noise masks par- rience higher rates of cuckoldry (Figure 3l). Great tits ent-arrival sounds (Figure 3g; Leonard and Horn 2012). breeding in noisy areas also have smaller clutches and Unfortunately, this study did not determine whether fewer fledglings (Halfwerk et al. 2011b); similarly, eastern missed provisioning opportunities translated into costs, bluebirds (Sialia sialis) experience decreased productivity such as reduced nestling mass or fledging success. when nesting in areas with elevated noise levels (Kight et Noise that interferes with cue detection can also al. 2012). Paired with patterns of decreased pairing success hamper predators’ hunting abilities. For example, in noisy areas (Habib et al. 2007; Gross et al. 2010), these among greater mouse-eared bats, search time for prey studies suggest that short-term signal adjustments in was shown to increase and hunting success to decrease response to anthropogenic noise might function as evolu- with exposure to experimental traffic noise (Figure 3h; tionary traps (eg Schlaepfer et al. 2002) in which behav- Siemers and Schaub 2011). This decrease in foraging ioral responses to novel acoustic stimuli could be maladap- success may explain why some predators avoid noisy tive. That is, behavioral shifts to be heard in noisy areas areas (Figure 3n; eg Schaub et al. 2008; Francis et al. may come with the cost of compromising the attractive- 2009). Noise also impairs foraging in three-spined ness of the signal to potential mates. This possibility sticklebacks (Gasterosteus aculeatus), resulting in more remains to be tested against other potential explanations unsuccessful hunting attempts (Purser and Radford for declines in pairing or reproductive success, but empha- 2011). Noise also possibly interferes with the ability of sizes why investigators should measure aspects of fitness in prey species to hear approaching predators, which noise-impact studies rather than simply documenting could impact fitness directly. Although likely, elevated changes in site occupancy or abundance. predation risk due to noise has yet to be demonstrated, Finally, although the list of species known to shift their but some evidence does suggest that animals exposed to signals in response to noise is growing, there is at least noise behave as though they are at greater risk of preda- one frog species and some bird species that do not alter tion. For example, in the chaffinch (Fringilla coelebs), their vocalizations in response to noise (eg Hu and continuous noise impairs auditory surveillance, trigger- Cardoso 2010; Love and Bee 2010; Francis et al. 2011b). ing increased visual surveillance, as a result of which More work is needed to provide a thorough understand- the birds spend less time foraging (Figure 3j; Quinn et ing of the phylogenetic distribution of noise-dependent al. 2006). Noise that serves as a distraction may also vocal change and researchers should strive to publish lead to an increased latency in predator-escape negative results, as knowledge of the apparent absence of response (Figure 3i; Chan et al. 2010), potentially com- these behavioral modifications is just as important as promising survival. Both distraction and elevated vigi- knowledge of their presence. lance could also cause a decrease in foraging rates and success (ie a trade-off; Figure 3o; Gavin and Komers ! Linking behavioral changes, physiological 2006; Quinn et al. 2006). Collectively, these studies responses, and fitness costs suggest that both interference noise and noise per- ceived as a threat decrease the rate and frequency at The behavioral changes mentioned above can have which organisms obtain food. Studies aimed at under- direct consequences for fitness (Figure 3r), such as standing the extent to which these behavioral shifts reduced pairing success (Habib et al. 2007) or reduced www.frontiersinecology.org © The Ecological Society of America CD Francis and JR Barber Understanding noise impacts on wildlife reproductive success (Halfwerk et al. 2011b). However, Nevertheless, additional investigations will be needed to behavior can influence, and be influenced by, physiologi- understand why species respond to sound stimuli as they cal responses (Figure 3p; Kight and Swaddle 2011), do. Settlement patterns may not hinge on the intensity of which in turn can affect fitness (Figure 3q; Bonier et al. noise, but are perhaps due to the presence or absence of 2009). Kight and Swaddle (2011) reviewed many links cues indicating the presence of predators and heterospe- between noise, physiological stress, and behavioral cific competitors (Francis et al. 2009). These other species change, so we only briefly mention them here. (ie predators or competitors) may have unique settlement It is well known that increased physiological stress patterns in response to noise and will complicate efforts affects fitness (Figure 3q); yet, to our knowledge, a direct to measure how noise directly affects the species of inter- link between increased physiological stress due to noise est. Disentangling these interactions will also be essential and decreased survival or reproductive success has not to understanding the consequences of noise exposure for been shown in wild animals. The best evidence for this organisms that are not directly impacted by noise, such as potential link comes from two studies. In one, Blickley et plants that depend on noise-sensitive faunal taxa (Francis al. (2012b) found that greater sage grouse on leks exposed et al. 2012) or animals whose hearing range is not tuned to experimental playback of continuous natural gas to a particular frequency that makes up a sound stimulus. drilling noise or intermittent road noise had higher fecal glucocorticoid metabolites (fGMs) than individuals on ! Conclusions control leks. The authors suggested that masking of cues likely resulted in elevated stress levels, inhibiting social Both policy and scientific literature have often oversim- interactions or leading to a heightened perception of pre- plified the effects of noise on wild animals, typically sug- dation risk. In the other, Hayward et al. (2011) showed gesting that species either are sensitive and abandon that experimental exposure to motorcycle traffic and noisy areas or are not and remain. In our experience with motorcycle noise increased fGMs in northern spotted stakeholders, habituation is an oft-cited reason for persis- owls (Strix occidentalis caurina). In an observational com- tence and an absence of noise impacts, yet research on ponent of the same study, spotted owls nesting in areas other stressors indicates that acclimation to a stressor with higher levels of traffic noise fledged fewer offspring, might not release an organism from costs to fitness even though they did not have elevated fGMs, suggesting (Romero et al. 2009). Additionally, we have shown how that the effects of road noise may have been offset by behavioral modifications among individuals confronted greater prey availability in noisy areas. These two studies with noise – even those individuals that outwardly appear demonstrate that noise may lead to decreased fitness in to habituate – can lead to decreased fitness. Challenging sage grouse and spotted owls, and also clearly indicate the assumption that habituation to noise equals “no that more research is needed to determine how noise impact” will be difficult, but it will also be a critical com- exposure, physiological stress, and fitness are linked in ponent in revealing how a range of behavioral mecha- wild populations. nisms link noise exposure to fitness costs. Ideally, we need to predict which combination of noise characteristics and ! Scaling up behavioral responses behavioral contexts are most detrimental and under what circumstances behavioral changes affect fitness directly Here, we have focused on effects of noise exposure at the or indirectly. This will require an array of experimental level of the individual; however, studies that integrate and observational approaches and frameworks that com- individual behavior, population responses among multi- plement the conceptual structure presented here (Figure ple species, and species interactions are critical to under- 3). Other promising frameworks include the risk–distur- standing the cumulative, community-level consequences bance hypothesis (Frid and Dill 2002), which provides an of noise. Measures of species richness are a good starting avenue for understanding energetic costs associated with point, but may be misleading because species may wildlife responses to noise disturbances that are perceived respond negatively, positively, or not at all to sound stim- as threats. Studies evaluating aspects of habitat selection uli (Bayne et al. 2008; Francis et al. 2009), individuals and acoustic communication in response to noise may within a single species may respond differently to the find it useful to frame questions in terms of ecological and same stimulus (Sih et al. 2004), and individuals that evolutionary traps (Schlaepfer et al. 2002). Furthermore, remain in noisy areas may suffer from one or more of the investigators should strive to measure responses along a fitness costs discussed above. This variation within and range of noise exposure levels to reveal the shape of among species in response to noise guarantees that com- response curves (eg threshold, linear) because these munities in noisy areas will not always be subsets of the details will be indispensable to resource managers and pol- species that make up communities in comparable quiet icy makers when establishing and modifying regulatory areas. Researchers should couple standard measures of limits that reflect the ecological effects of noise exposure. richness and alpha (local) diversity with beta-diversity An increase in anthropogenic noise levels is only one metrics that reflect variations in the composition of of many threats to biodiversity on which ecologists and species within communities and among sites. policy makers should focus their attention. However, rel-

© The Ecological Society of America www.frontiersinecology.org Understanding noise impacts on wildlife CD Francis and JR Barber ative to other conservation problems, noise may also offer Bonier F, Moore IT, Martin PR, and Robertson RJ. 2009. The rela- readily available solutions, which, if implemented, could tionship between fitness and baseline glucocorticoids in a lead to major, measurable improvements for both wildlife passerine bird. Gen Comp Endocr 163: 208–13. Brown JS. 1999. Vigilance, patch use and habitat selection: forag- and people. For example, use of noise-attenuating walls ing under predation risk. Evol Ecol Res 1: 49–71. could reduce the area of a landscape exposed to elevated Chan AAYH, Stahlman WD, Garlick D, et al. 2010. Increased noise levels from natural gas extraction activities by as amplitude and duration of acoustic stimuli enhance distraction. much as 70% (Francis et al. 2011c) and similar solutions Anim Behav 80: 1075–79. exist for mitigating noise from roadways and cities (Code Code of Federal Regulations. 2010. Procedures for abatement of of Federal Regulations 2010). These mitigation efforts highway traffic noise and construction noise. Washington, DC: US Government Printing Office. 23 CFR §772.17. www.ecfr. could come with drawbacks; for instance, noise-attenuat- gov/cgi-bin/text-idx?c=ecfr&SID=cd313d7dd374014a ing walls near roads could restrict the movement of 6041944112b4456b&rgn=div5&view=text&node=23:1.0.1.8. wildlife and impede gene flow. Nevertheless, as we 44&idno=23#23:1.0.1.8.44.0.1.9. Viewed on 29 Mar 2013. develop a better understanding of the ecological effects of Dingemanse NJ, Both C, Drent PJ, et al. 2002. Repeatability and noise, implementation of mitigation efforts can begin in heritability of exploratory behaviour in great tits from the wild. Anim Behav 64: 929–38. many well-studied and high-priority systems (eg oil and Dooling RJ and Popper AN. 2007. The effects of highway noise on gas developments in natural areas, transportation net- birds. Sacramento, CA: California Department of Trans- works in national parks), where benefits outweigh the portation. potential costs. In addition to protecting contiguous nat- Eigenbrod F, Hecnar SJ, and Fahrig L. 2008. The relative effects of ural habitat, reducing noise exposure in and around road traffic and forest cover on anuran populations. Biol developed areas will not only benefit wildlife populations Conserv 141: 35–46. Ellison WT, Southall BL, Clark CW, and Frankel AS. 2012. A new and diversity, but will also provide adjacent human popu- context-based approach to assess marine mammal behavioral lations with the suite of physiological benefits afforded by responses to anthropogenic sounds. Conserv Biol 26: 21–28. living in a quieter community. Francis CD, Kleist NJ, Ortega CP, and Cruz A. 2012. Noise pollu- tion alters ecological services: enhanced pollination and dis- rupted seed dispersal. P Roy Soc B–Biol Sci 279: 2727–35. ! Acknowledgements Francis CD, Ortega CP, and Cruz A. 2009. Noise pollution changes avian communities and species interactions. Curr Biol 19: We thank J Bunkley, K Fristrup, A Keener, N Kleist, B 1415–19. Leavell, T Mason, C McClure, and H Ware for comments Francis CD, Ortega CP, and Cruz A. 2011a. Noise pollution filters on earlier versions of this manuscript. CDF thanks the bird communities based on vocal frequency. PLoS ONE 6: National Evolutionary Synthesis Center (NSF EF- e27052. 0905606) for support and JRB acknowledges support from Francis CD, Ortega CP, and Cruz A. 2011b. Vocal frequency change reflects different responses to anthropogenic noise in the Natural Sounds and Night Skies Division of the two suboscine tyrant flycatchers. P Roy Soc B–Biol Sci 278: National Park Service (CESU H8R07060001). 2025–31. Francis CD, Paritsis J, Ortega CP, and Cruz A. 2011c. Landscape ! References patterns of avian habitat use and nest success are affected by Baker PJ, Dowding CV, Molony SE, et al. 2007. Activity patterns of chronic gas well compressor noise. Landscape Ecol 26: 1269–80. urban red foxes (Vulpes vulpes) reduce the risk of traffic- Frid A and Dill LM. 2002. Human-caused disturbance stimuli as a induced mortality. Behav Ecol 18: 716–24. form of predation risk. Conserv Ecol 6: 11. Barber JR, Crooks KR, and Fristrup KM. 2010. The costs of chronic Fuller RA, Warren PH, and Gaston KJ. 2007. Daytime noise pre- noise exposure for terrestrial organisms. Trends Ecol Evol 25: dicts nocturnal singing in urban robins. Biol Lett 3: 368–70. 180–89. Gavin SD and Komers PE. 2006. Do pronghorn (Antilocapra ameri- Barber J, Burdett C, Reed S, et al. 2011. Anthropogenic noise cana) perceive roads as a predation risk? Can J Zool 84: exposure in protected natural areas: estimating the scale of eco- 1775–80. logical consequences. Landscape Ecol 26: 1281–95. Goodwin SH and Shriver WG. 2011. Effects of traffic noise on Bayne EM, Habib L, and Boutin S. 2008. Impacts of chronic occupancy patterns of forest birds. Conserv Biol 25: 406–11. anthropogenic noise from energy-sector activity on abundance Goudie RI. 2006. Multivariate behavioural response of harlequin of songbirds in the boreal forest. Conserv Biol 22: 1186–93. ducks to aircraft disturbance in Labrador. Environ Conserv 33: Bejder L, Samuels A, Whitehead H, and Gales N. 2006. 28–35. Interpreting short-term behavioural responses to disturbance Gross K, Pasinelli G, and Kunc HP. 2010. Behavioral plasticity within a longitudinal perspective. Anim Behav 72: 1149–58. allows short-term adjustment to a novel environment. Am Nat Blickley JL and Patricelli GL. 2012. Potential acoustic masking of 176: 456–64. greater sage-grouse display components by chronic industrial Habib L, Bayne EM, and Boutin S. 2007. Chronic industrial noise noise. Ornithol Monogr 74: 23–35. affects pairing success and age structure of ovenbirds Seiurus Blickley JL, Blackwood D, and Patricelli GL. 2012a. Experimental aurocapilla. J Appl Ecol 44: 176–84. evidence for the effects of chronic anthropogenic noise on Halfwerk W, Bot S, Buikx J, et al. 2011a. Low-frequency songs lose abundance of greater sage-grouse at leks. Conserv Biol 26: their potency in noisy urban conditions. P Natl Acad Sci USA 461–71. 108: 14549–54. Blickley JL, Word KR, Krakauer AH, et al. 2012b. Experimental Halfwerk W, Holleman LJM, Lessells CM, and Slabbekoorn H. chronic noise is related to elevated fecal corticosteroid metabo- 2011b. Negative impact of traffic noise on avian reproductive lites in lekking male greater sage-grouse (Centrocercus success. J Appl Ecol 48: 210–19. urophasianus). PLoS ONE 7: e50462. Hayward LS, Bowles AE, Ha JC, and Wasser SK. 2011. Impacts of www.frontiersinecology.org © The Ecological Society of America CD Francis and JR Barber Understanding noise impacts on wildlife

acute and long-term vehicle exposure on physiology and repro- for improved assessment of noise impacts on wildlife. J Wildlife ductive success of the northern spotted owl. Ecosphere 2: 65. Manage 73: 788–95. Hu Y and Cardoso GC. 2010. Which birds adjust the frequency of Patricelli GL and Blickley JL. 2006. Avian communication in vocalizations in urban noise? Anim Behav 79: 863–67. urban noise: causes and consequences of vocal adjustment. Auk Johnson RG and Temple SA. 1986. Assessing habitat quality for 123: 639–49. birds nesting in fragmented tallgrass prairies. In: Verner J, Purser J and Radford AN. 2011. Acoustic noise induces attention Morrison ML, and Ralph CJ (Eds). Wildlife 2000: modeling shifts and reduces foraging performance in three-spined stickle- habitat relationships of terrestrial vertebrates. Madison, WI: backs (Gasterosteus aculeatus). PLoS ONE 6: e17478. University of Wisconsin Press. Quinn JL, Whittingham MJ, Butler SJ, and Cresswell W. 2006. Kight CR and Swaddle JP. 2011. How and why environmental Noise, predation risk compensation and vigilance in the noise impacts animals: an integrative, mechanistic review. Ecol chaffinch Fringilla coelebs. J Avian Biol 37: 601–08. Lett 14: 1052–61. Romero LM, Dickens MJ, and Cyr NE. 2009. The reactive scope Kight CR, Saha MS, and Swaddle JP. 2012. Anthropogenic noise is model – a new model integrating homeostasis, allostasis, and associated with reductions in the productivity of breeding east- stress. Horm Behav 55: 375–89. ern bluebirds (Sialia sialis). Ecol Appl 22: 1989–96. Schaub A, Ostwald J, and Siemers BM. 2008. Foraging bats avoid Leonard ML and Horn AG. 2012. Ambient noise increases missed noise. J Exp Biol 211: 3174–80. detections in nestling birds. Biol Lett 8: 530–32. Schlaepfer MA, Runge MC, and Sherman PW. 2002. Ecological Love EK and Bee MA. 2010. An experimental test of noise-depen- and evolutionary traps. Trends Ecol Evol 17: 474–80. dent voice amplitude regulation in Cope’s grey treefrog, Hyla Siemers BM and Schaub A. 2011. Hunting at the highway: traffic chrysoscelis. Anim Behav 80: 509–15. noise reduces foraging efficiency in acoustic predators. P Roy Luther DA. 2008. Signaller: receiver coordination and the timing Soc B–Biol Sci 278: 1646–52. of communication in Amazonian birds. Biol Lett 4: 651–54. Sih A, Bell A, and Johnson JC. 2004. Behavioral syndromes: an eco- Miksis-Olds JL, Donaghay PL, Miller JH, et al. 2007. Noise level logical and evolutionary overview. Trends Ecol Evol 19: 372–78. correlates with manatee use of foraging habitats. J Acoust Soc Slabbekoorn H and Bouton N. 2008. Soundscape orientation: a Am 121: 3011–20. new field in need of sound investigation. Anim Behav 76: Ortega CP and Francis CD. 2012. Effects of gas well compressor E5–E8. noise on ability to detect birds during surveys in northwest Slabbekoorn H, Bouton N, van Opzeeland I, et al. 2010. A noisy New Mexico. Ornithol Monogr 74: 78–90. spring: the impact of globally rising underwater sound levels on Pater LL, Grubb TG, and Delaney DK. 2009. Recommendations fish. Trends Ecol Evol 25: 419–27.

© The Ecological Society of America www.frontiersinecology.org CD Francis and JR Barber et al. – Supplemental information (a) US Air Force and USFWS (b) USFWS and E Francis E and USFWS (b) USFWS and Force Air US (a) WebFigure 1. Example of two acoustic metrics that employ different time-weighting functions. (a) Infrequent noise events from aircraft alter harlequin duck behavior. These types of distinct noise disturbances should be quantified using Lmax, which represents the loudest sound level occurring within a specified period (illustrated below photo in the waveform). (b) White-breasted nuthatches avoid chronic traffic noise. To characterize chronic noise it can be better to utilize Leq, which represents a time-averaged value during a specified period (illustrated below photos as a dashed line in the waveform).

© The Ecological Society of America www.frontiersinecology.org Traffic Volume Alters Elk Distribution and Highway Crossings in Arizona Author(s): JEFFREY W. GAGNON, TAD C. THEIMER, NORRIS L. DODD, SUSAN BOE, and RAYMOND E. SCHWEINSBURG Source: Journal of Wildlife Management, 71(7):2318-2323. Published By: The Wildlife Society DOI: http://dx.doi.org/10.2193/2006-224 URL: http://www.bioone.org/doi/full/10.2193/2006-224

BioOne (www.bioone.org) is a nonprofit, online aggregation of core research in the biological, ecological, and environmental sciences. BioOne provides a sustainable online platform for over 170 journals and books published by nonprofit societies, associations, museums, institutions, and presses. Your use of this PDF, the BioOne Web site, and all posted and associated content indicates your acceptance of BioOne’s Terms of Use, available at www.bioone.org/page/terms_of_use. Usage of BioOne content is strictly limited to personal, educational, and non-commercial use. Commercial inquiries or rights and permissions requests should be directed to the individual publisher as copyright holder.

BioOne sees sustainable scholarly publishing as an inherently collaborative enterprise connecting authors, nonprofit publishers, academic institutions, research libraries, and research funders in the common goal of maximizing access to critical research. Research Article Traffic Volume Alters Elk Distribution and Highway Crossings in Arizona

JEFFREY W. GAGNON,1 Arizona Game and Fish Department, Research Branch, 2221 W. Greenway Road, Phoenix, AZ 85023, USA TAD C. THEIMER, Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ 86011, USA NORRIS L. DODD, Arizona Game and Fish Department, Research Branch, Pinetop, AZ 85935, USA SUSAN BOE, Arizona Game and Fish Department, Research Branch, 2221 W. Greenway Road, Phoenix, AZ 85023, USA RAYMOND E. SCHWEINSBURG, Arizona Game and Fish Department, Research Branch, Phoenix, AZ 85023, USA

ABSTRACT We used 38,709 fixes collected from December 2003 through June 2006 from 44 elk (Cervus elaphus) fitted with Global Positioning System collars and hourly traffic data recorded along 27 km of highway in central Arizona, USA, to determine how traffic volume affected elk distribution and highway crossings. The probability of elk occurring near the highway decreased with increasing traffic volume, indicating that elk used habitat near the highway primarily when traffic volumes were low (,100 vehicles/hr). We used multiple logistic regression followed by model selection using Akaike’s Information Criterion to identify factors influencing probability of elk crossings. We found that increasing traffic rates reduced the overall probability of highway crossing, but this effect depended on both season and the proximity of riparian meadow habitat. Elk crossed highways at higher traffic volumes when accessing high quality foraging areas. Our results indicate that 1) managers assessing habitat quality for elk in areas with high traffic-volume highways should consider that habitat near highways may be utilized at low traffic volumes, 2) in areas where highways potentially act as barriers to elk movement, increasing traffic volume decreases the probability of highway crossings, but the magnitude of this effect depends on both season and proximity of important resources, and 3) because some highway crossings still occurred at the high traffic volumes we recorded, increasing traffic alone will not prevent elk–vehicle collisions. Managers concerned with elk–vehicle collisions could increase the effectiveness of wildlife crossing structures by placing them near important resources, such as riparian meadow habitat. (JOURNAL OF WILDLIFE MANAGEMENT 71(7):2318–2323; 2007) DOI: 10.2193/2006-224

KEY WORDS Arizona, Cervus elaphus, collisions, elk, highway, permeability, roads, traffic, ungulate, wildlife–vehicle.

Roads can negatively impact wild ungulates by altering temporal fluctuations. For example, elk in Oregon, USA, habitat use (Lyon 1979, Rost and Bailey 1979, Rowland et showed a consistent diurnal pattern of movement relative al. 2000), restricting movements and thereby genetically to low traffic-volume forest roads that were open to traffic, subdividing populations (Forman et al. 2003, Epps et al. moving closer at night and farther away during the day 2005) and increasing mortality through collisions with (Ager et al. 2003). Likewise, most highway crossings by vehicles (Groot Bruinderink and Hazebroek 1996, Forman grizzly bears (Ursus arctos) in Montana, USA, occurred at et al. 2003). The magnitude of all of these factors likely night when traffic counters documented traffic volume was increases with increasing traffic volume. For example, elk lowest (Waller and Servheen 2005). These studies under- (Cervus elaphus) more strongly avoid areas near forest roads score the need to link how animals respond to highways with higher traffic levels (Perry and Overly 1976, Witmer with temporal fluctuations in traffic. and deCalesta 1985, Rowland et al. 2000, Wisdom et al. Although several studies have documented elk response to 2005), leading to the hypothesis that increased traffic should relatively low traffic-volume roads (Hershey and Leege result in decreasing habitat effectiveness (Lyon 1979, Lyon 1976, Perry and Overly 1976, Rowland et al. 2000, Wisdom and Christensen 1992). Likewise, increasing rates of et al. 2005) previous studies have not examined the ungulate–vehicle collisions are often correlated with in- potentially greater effects of varying traffic levels on elk creasing traffic volume (Allen and McCullough 1976, Groot distributions and movements along highways (Ruediger et Bruinderink and Hazebroek 1996, Romin and Bissonette al. 2006). Furthermore, previous studies compared elk 1996), though the relationship is often not linear, suggesting distributions among different areas of roadway or using complex interactions with behavior, ungulate population road type as a surrogate for increasing traffic levels (Rost and density, and landscape-level phenomena (Groot Bruinder- Bailey 1979, Witmer and deCalesta 1985), potentially ink and Hazebroek 1996, Seiler 2004). Finally, several confounding the effect of traffic with differences in habitat, recent theoretical models (Iuell et al. 2003, Jaeger et al. resource type and availability, and human disturbance. In 2005) assume that the potential for traffic to act as an this study, we examined the effects of fluctuating hourly impermeable moving fence (Bellis and Graves 1978) traffic rates on the distribution and movements of elk in increases with traffic volume. central Arizona along a relatively high traffic-volume Traffic volume on any roadway varies seasonally, weekly, highway. We explored 1) how elk distribution relative to and with time of day, and animals may respond to these the highway varied at differing traffic volumes, and 2) how traffic volume interacted with other factors to determine the 1 E-mail: [email protected] probability of elk crossing the highway.

2318 The Journal of Wildlife Management 71(7) STUDY AREA sides of the highway (crossing occurred). We defined a Our study focused on 27 km of State Route (SR) 260, noncrossing movement as those instances when the 2 approximately 15 km east of Payson, Arizona, USA. The successive GPS relocations indicated elk entered the 250- Mogollon Rim escarpment was the dominant land feature in m zone adjacent to the highway from beyond that distance the area. The study area rose gradually from 1,590 m to but did not cross the highway. We chose the 250-m zone 2,000 m, and vegetation type changed accordingly with based on the mean movement of elk during crossing events. pinyon (Pinus edulis)–juniper (Juniperus spp.) and chaparral Because the upper limit of the 99% confidence interval for (Arctostaphylos spp.) at lower elevations giving way to highway crossings by all elk during this study was ,600 m, ponderosa pine (P. ponderosa) and pockets of Douglas fir we assumed ,1% of elk could enter this 600-m zone (Pseudotsuga menziesii) at the upper end of the study area (250 m on each side of the 100-m highway footprint) from (Brown 1994). At several points, the highway ran along either direction and cross the highway without being riparian areas that supported wet meadows favored by elk as detected. foraging areas (Dodd et al. 2007a). This roadway has Our primary focus in this analysis was determining the effect produced high numbers of elk–vehicle collisions with some that varying traffic volumes had on the probability of elk sections experiencing as many as 10 collisions/km per year crossing SR 260. In addition to traffic, we identified 4 other since 1993 (Dodd et al. 2006). factors that potentially influence elk movement near roads or are associated with higher elk–vehicle collision rates based on METHODS prior studies. 1) Previous studies have demonstrated that elk We estimated traffic volume using a permanent traffic respond to presence of riparian meadow habitat adjacent to counter programmed to record mean hourly traffic volumes. roadways (Ward 1976; Dodd et al. 2006, 2007a;Manzo We installed the traffic counter in December 2003 at the 2006). We considered wet meadows and areas along streams center of the study area. No major roads branched off the within 1 km of the highway as adjacent. 2) Frequency and highway along the length we studied and vehicles could patterns of elk movements to and from feeding areas and move from either end of the study area to the traffic counter seasonal use areas can vary across the year (Groot Bruinderink in no more than 10 minutes. We assumed that traffic volume and Hazebroek 1996, Gunson and Clevenger 2003, Dodd et recorded by the counter accurately represented levels present al. 2006). We defined 4 seasons based on local climatic along that stretch of highway during any 1-hour interval. conditions and elk behavior as winter (Dec–Feb), spring We obtained Global Positioning System (GPS) reloca- (Mar–May), summer (Jun–Aug), and fall (Sep–Nov). 3) Due tions from 44 elk (7 M, 37 F) radiocollared with store-on- to differing reproductive and nutritional drives, sexes may board collars (model TGW-3600; Telonics, Inc., Mesa, AZ) differ in their response to traffic (Marcum and Edge 1991, from 2001 through 2006 (Dodd et al. 2007a). We recovered Gunson and Clevenger 2003, McCorquodale 2003, Dodd et all of our collars by June 2006, providing approximately 30 al. 2006). 4) Although we limited our analysis to the hours months of data concurrent with operation of our traffic between dusk and dawn, activity patterns can vary with time of counter. We accrued GPS fixes at 2-hour intervals, and were night (Groot Bruinderink and Hazebroek 1996, Haikonen 6 accurate to 10 m (Dodd et al. 2006). We only used fixes and Summala 2001, Dodd et al. 2006). We defined 3 time recorded during 1700–0800 hours because this was the periods during which elk motivation to move from one area to period elk were most active and ,3% of highway crossings another could potentially vary: 1) evening, 1700–2159 hours, occurred outside of this period (Gagnon 2006). We to include dusk, sunset, and the hours immediately following combined traffic and GPS data by assigning traffic volumes sunset; 2) night, 2200–0259 hours; and 3) morning, 0300– for the previous hour to each GPS location using ArcGIS 0800 hours to include twilight, sunrise, and time immediately Version 9.1. following sunrise. We examined how the proportion of elk relocations at We used Akaike’s Information Criterion (AIC; Burnham different distances from the highway varied with traffic and Anderson 2002) to select the most parsimonious model volume by calculating the percentage of relocations in each 100-m distance band, out to a maximum of 600 m (similar among a suite of 23 models (Table 1). A model was D , to Rowland et al. 2005). To avoid bias due to differences in considered a candidate if it had a AIC 10. We used a the number of relocations for individual elk, we used the goodness-of-fit test to check fit of the selected model(s) proportion of relocations occurring in each distance band for versus the saturated model (Agresti 1996). Once we selected each elk as the sample unit, rather than total relocations. We the best possible model(s) and tested for adequate fit, for then calculated a mean proportion across all 44 elk within ease of interpretation, we converted the log odds models each 100-m distance band at varying traffic volumes. into probabilities using:  To investigate how traffic volume influenced the proba- expða þ bx þ ...Þ bility of elk crossing the highway, we used a multiple logistic probability ¼ : 1 þ expða þ bx þ ...Þ regression approach (Agresti 1996) and assigned a binomial response to 2 different behaviors: 1) movement near the We then used these equations to create a graphical model of highway in which crossing was not detected, and 2) the probability of elk crossing the highway under these movement that resulted in successive relocations on opposite scenarios.

Gagnon et al. Effect of Traffic on Elk 2319 Table 1. Results of model selection for 23 candidate models using Akaike’s vehicle/hour to 1,514 vehicles/hour and averaged 300 Information Criterion (AIC) that describe the probability of 40 elk crossing vehicles/hour (95% CI ¼ 296, 304). State Route 260 in Arizona, USA, 2003–2006. Each model is listed with its number of parameters (K), AIC, AIC difference (DAIC), and Akaike We based our distribution analysis on 38,709 GPS weights (wi). relocations recorded within 600 m of the highway between 1700 hours and 0800 hours. Frequency distributions of Model K AIC DAIC wi combined probabilities showed a shift in distribution away Traffic þ season þ meadow 4 6,225 0 0.9997 from the highway at increasing traffic volume, with the Traffic þ time þmeadow 4 6,241 16 0.0003 Traffic þ meadow 3 6,245 20 ,0.001 mean probability of an elk occurring within 200 m of the Traffic þ meadow þ sex 4 6,245 20 ,0.001 highway approximately 40% at ,100 vehicles/hour and Meadow þ season þ time 4 6,245 20 ,0.001 dropping to less than 20% when traffic was 600 vehicles/ Traffic þ season þ time 4 6,253 28 ,0.001 hour (Fig. 1). Traffic þ season 3 6,257 32 ,0.001 Traffic þ season þ sex 4 6,257 32 ,0.001 We based our highway crossing probability analysis on Meadow þ season 3 6,262 37 ,0.001 15,608 movements that occurred within 250 m of the Meadow þ time 3 6,268 43 ,0.001 highway, yielding 2,177 crossings. Forty of the 44 elk Traffic þ time 3 6,275 50 ,0.001 Traffic þ sex þ time 4 6,275 50 ,0.001 crossed the highway at least once and were included in the Traffic 2 6,279 54 ,0.001 analysis. Elk traveled almost twice the distance during Season þ time 3 6,279 54 ,0.001 crossings (x¯ ¼ 467 m, 95% CI ¼ 448, 486) than during Traffic þ sex 3 6,279 54 ,0.001 noncrossing movements (x¯ ¼ 253 m, 95% CI ¼ 248,258). Sex þ time 3 6,279 54 ,0.001 Meadow 2 6,284 59 ,0.001 Our AIC model selection process yielded only one model Meadow þ sex 3 6,284 59 ,0.001 that was supported under the AIC criteria (DAIC , 10); Season 2 6,295 70 ,0.001 this model included traffic volume, riparian meadow habitat, Season þ sex 3 6,295 70 ,0.001 and season (Table 1). Model fit was adequate for continued Time 2 6,303 78 ,0.001 2 Null 1 6,319 94 ,0.001 analysis (v ¼ 3579, df ¼ 3583, P ¼ 0.51). Using coefficients Sex 2 6,319 94 ,0.001 derived from this model (Table 2), we created graphs representing the probability of crossing for each traffic– meadow–season combination (Agresti 1996; Fig. 2). RESULTS Although in each case the probability of crossing decreased Total monthly traffic for December 2003–June 2006 ranged with increasing traffic volume, the probability of crossing at from 120,129 vehicles to 330,011 vehicles and totaled any given traffic volume was highest during the spring and 6,470,211 vehicles. Hourly traffic volumes during the peak fall seasons in areas where riparian meadow habitat was elk movement period of 1700–0800 hours ranged from 1 present, followed in decreasing order by winter and summer

Figure 1. Mean probability that radiocollared elk (n ¼ 44) occurred within each 100-m distance band from the highway at varying traffic volumes, State Route 260, Arizona, USA, 2003–2006: (a) ,100 vehicles/hour, (b) .100–200 vehicles/hour, (c) .200–300 vehicles/hour, (d) .300–400 vehicles/hour, (e) .400–500 vehicles/hour, (f) .500 vehicles/hour.

2320 The Journal of Wildlife Management 71(7) Table 2. Logistic regression output obtained following model selection for the probability of 40 elk crossing State Route 260, Arizona, USA, 2003– 2006. Each model is listed with its coefficient (b), standard error, Wald chi- square, degrees of freedom, P values, and odds.

Variable b SE v2 df P Odds

Traffic volumea 0.001 0.0001 75.49 1 ,0.001 0.99 Meadow, present 0.58 0.067 66.99 1 ,0.001 1.79 Season Winter 0.16 0.047 10.99 1 ,0.001 0.85 Spring 0.17 0.04 18.92 1 ,0.001 1.18 Summer 0.15 0.04 12.25 1 ,0.001 0.86 Fall 0.14 0.037 13.23 1 ,0.001 1.15 Intercept 1.09 0.07 237.11 1 ,0.001 0.34

a Continuous variable, all others categorical. Figure 2. Probability that elk would cross the highway at varying traffic volumes under different scenarios, derived from the best possible model seasons in areas with meadows present, spring and fall selected using Akaike’s Information Criterion, along State Route 260, seasons with no meadow present, and winter and summer Arizona, USA, 2003–2006. (a) spring or fall, meadow present; (b) winter or summer, meadow present; (c) spring or fall, no meadow present; (d) winter seasons in areas with no meadow present. or summer, no meadow present. DISCUSSION Traffic Volume and Elk Distribution season and proximity to riparian meadow habitat. We Although negative responses of elk to low traffic-volume hypothesize that the influence of these 2 factors is due to roads (Lyon 1979, Witmer and deCalesta 1985, Rowland et their effect on the motivation for animals to cross the al. 2000, Wisdom et al. 2005) suggested that ‘‘persistent highway and therefore their tendency to tolerate higher road-mediated disturbance may lead to permanent shifts in traffic volumes while crossing. Riparian meadow habitats are habitat use by elk’’ (Rowland et al. 2000:681), we did not heavily used by elk in this area, particularly in the spring find a permanent shift away from the highway even though when forage growth is most vigorous (Dodd et al. 2006). As traffic levels were nearly 10-fold greater than in these other a result, part of the interaction between season and traffic studies. Instead, elk responded to fluctuations in traffic volume may have been due to increased attractiveness of volume by shifting away from the highway at high traffic meadows in spring. In addition, some of the elk in our study volumes and returning to utilize areas near the highway crossed the highway during migratory movements between when traffic volume was relatively low, similar to responses summer and winter ranges in both fall and spring. The documented on lower volume forest roads (Morgantini and elevational gradient across our study area is extremely steep, Hudson 1979, Ager et al. 2003). This pattern is broadly so migrational movements can be relatively short, with consistent with models of roads resulting in reduced habitat animals summering on one side of the highway and effectiveness (Lyon 1979, 1983), defined as ‘‘percentage of wintering on the other, and yet remaining relatively close available habitat that is usable by elk outside the hunting to the highway throughout the year. Other animals we season’’ (Lyon and Christensen 1992:4). As a result, tracked did not show these migratory movements, and the modeling of habitat effectiveness near highways with traffic low probability of crossing during winter and summer likely volumes like those we studied should consider elk responses reflect the combination of the absence of strong unidirec- to traffic volume fluctuations, as has been suggested for tional movements by migrants and the tendency of resident lower volume roadways (Wisdom et al. 2005). Two factors animals to be just as likely to move along either side of the may explain why elk in our study showed only temporary highway as to cross it. movement away from the highway: 1) elk that live near Although males have been documented to have higher roadways with higher traffic may have a higher tolerance for sensitivity to roads than females (Marcum and Edge 1991, traffic volumes, and 2) the riparian meadow habitat and McCorquodale 2003), our analysis did not indicate that sex water sources along this highway may be of greater was an important factor in predicting crossing probabilities. importance to elk at our site due to the relative rarity of This difference may have been due to the close proximity of these resources in the arid southwestern United States the highway to the riparian meadow habitat apparently so (Dodd et al. 2006, 2007a; Manzo 2006). important to elk in our study area. For example, Dodd et al. (2006, 2007a) found that although riparian meadow habitat Traffic Volume, Probability of Highway Crossing, and made up only 4% of the available habitat in our study area, Highway Permeability roughly 50% of bull locations occurred in these habitats As traffic volume increased from zero to 1,500 vehicles/ during certain times of year. hour, the probability of highway crossings declined by Overall, our data indicate that the effect of traffic volume approximately 20%. However, the effect of traffic volume on the probability of highway crossing varied with landscape on crossing probability was strongly influenced by both context; animals accessing rich foraging areas like riparian

Gagnon et al. Effect of Traffic on Elk 2321 meadows or making seasonal movements were more likely permeability to elk must consider the larger landscape to cross at higher traffic volumes. As a result, the effect of context. Both the tendency for elk to shift closer to the highways with similar traffic volumes may differ depending highway at lower traffic volumes and to cross the highway at on how the location of the highway interacts with important higher traffic volumes during migratory periods or near resources and movement corridors. Traffic volume on a meadows could increase the potential for elk–vehicle highway that intersects movement corridors between winter collisions. Therefore, placing wildlife crossing structures and summer seasonal ranges, for example, may reach higher near meadows could allow elk to pass safely to and from levels before elk cease crossing compared to a highway that these areas in both migratory and nonmigratory seasons. lies parallel to the corridor. A counter-intuitive prediction from this hypothesis is that highway impermeability would ACKNOWLEDGMENTS be reached at lower traffic volumes on highways that appear This study was funded by a grant from Arizona Department to have the smallest impact on elk access to important of Transportation (ADOT) Transportation Research Cen- resources. ter and by the Federal Aid Wildlife in Restoration Act, Project W-78-R. Additional funding was provided by Elk Distribution and Collisions Tonto National Forest. We thank D. Eberline, M. Catch- The spatial response of elk to traffic volume we documented pole, J. Garrison, and D. Buskirk of ADOT Transportation indicated that elk were more likely to use resources near the Planning Division for support and consultation of traffic highway when traffic volumes were lower, thus potentially data collection. E. Kombe, B. Eilerts, and S. Nordhaugen of increasing the probability of collisions with vehicles. It was ADOT, and T. Brennan, R. Ingram, and E. Kline of the not uncommon in our study to see elk feeding in the median Tonto National Forest were instrumental to the success of or directly alongside the road where plant growth was this project. Thanks to P. Beier and S. Rosenstock for their enhanced by water runoff and artificial seeding to control input and editing on earlier drafts. A. Manzo and S. erosion. This may partly explain why collisions between elk Sprague assisted with data collection and analysis. and vehicles on this highway occurred more frequently on weekdays, when traffic volume was low, compared to weekends (Dodd et al. 2006). This pattern contrasts with LITERATURE CITED studies of elk (Gunson and Clevenger 2003) and white- Ager, A. A., B. K. Johnson, J. W. Kern, and J. G. Kie. 2003. Daily and tailed deer (Odocoileus virginianus; Allen and McCullough seasonal movements and habitat use by female Rocky Mountain elk and 1976) in which the number of collisions was highest on mule deer. Journal of Mammalogy 84:1076–1088. weekends when traffic volume was higher. In these cases, Agresti, A. 1996. An introduction to categorical data analysis. Wiley and the most effective mitigation measure may be fencing (Falk Sons, New York, New York, USA. Allen, R. E., and D. R. McCullough. 1976. Deer car accidents in southern et al. 1978, Clevenger et al. 2001, Farrell et al. 2002). Michigan. Journal of Wildlife Management 40:317–325. While collisions during relatively low traffic-volume Bellis, E. D., and H. B. Graves. 1978. Highway fences as deterrents to periods may be due to elk that moved nearer the highway vehicle–deer collisions. Transportation Research Record 674:53–58. to forage along the shoulder or median, collisions during Brown, D. E. 1994. Biotic communities: southwestern United States and northwestern Mexico. University of Utah Press, Salt Lake City, USA. high traffic volume periods may be more likely either during Burnham, K. P., and D. R. Anderson. 2002. Model selection and migration or when elk that have moved farther from the multimodel inference: a practical information-theoretic approach. Second highway to avoid higher traffic volumes make long-distance, edition. Springer-Verlag, New York, New York, USA. directed movements to access the riparian meadows Clevenger, A. P., B. Chruszcz, and K. Gunson. 2001. Highway mitigation fencing reduces wildlife–vehicle collisions. Wildlife Society Bulletin 29: common along this stretch of highway. Given the potential 646–653. for wildlife crossing structures to safely convey animals Clevenger, A. P., and N. Waltho. 2005. Performance indices to identify across highway corridors (Foster and Humphrey 1995, attributes of highway crossing structures facilitating movement of large Clevenger and Waltho 2005, Gagnon et al. 2006, Dodd et mammals. Biological Conservation 121:453–464. Dodd, N. L., J. W. Gagnon, S. Boe, and R. E. Schweinsburg. 2006. al. 2007b), our data indicate that placing these structures Characteristics of elk–vehicle collisions and comparison to GPS- near meadows could allow elk to pass safely to and from determined highway crossing patterns. Pages 461–477 in Proceedings these areas in both migratory and nonmigratory seasons, of the 2005 International Conference on Ecology and Transportation, 29 thereby reducing the probability of elk–vehicle collisions at August–2 September 2005, San Diego, California, USA. North Carolina Center for Transportation and the Environment, North Carolina State high traffic volumes. University, Raleigh, USA. Dodd, N. L., J. W. Gagnon, S. Boe, and R. E. Schweinsburg. 2007a. MANAGEMENT IMPLICATIONS Assessment of elk highway permeability by using Global Positioning Elk use of areas near a relatively high traffic-volume System telemetry. Journal of Wildlife Management 71: 1107–1117. Dodd, N. L., J. W. Gagnon, A. L. Manzo, and R. E. Schweinsburg. 2007b. highway depended on traffic volume; therefore, models of Video surveillance to assess highway underpass use by elk in Arizona. habitat effectiveness for elk living near highways should Journal of Wildlife Management 71:637–645. consider both the temporal pattern of traffic volume and Epps, C. W., P. J. Palsboll, J. D. Wehausen, G. K. Roderick, R. R. Ramry, how elk respond to those traffic fluctuations. Traffic volume, II, and D. R. McCullough. 2005. Highways block gene flow and cause season, and proximity to meadows interacted to determine rapid decline in genetic diversity of desert bighorn sheep. Ecology Letters 8:1029–1038. the probability of highway crossing by elk, therefore Falk, N. W., H. B. Graves, and E. D. Bellis. 1978. Highway right-of-way modeling the impact of traffic volume on highway fences as deer deterrents. Journal of Wildlife Management 42:646–650.

2322 The Journal of Wildlife Management 71(7) Farrell, J. E., L. R. Irby, and P. T. McGowen. 2002. Strategies for Proceedings Elk Vulnerability Symposium, 10–12 April 1991. Montana ungulate–vehicle collision mitigation. Intermountain Journal of Science State University, Bozeman, USA. 8:1–18. McCorquodale, S. M. 2003. Sex-specific movements and habitat use by elk Forman, R. T. T., D. Sperling, J. A. Bissonette, A. P. Clevenger, C. D. in the Cascade Range of Washington. Journal of Wildlife Management Cutshall, V. H. Dale, L. Fahrig, R. France, C. R. Goldman, K. Heanue, 67:729–741. J. A. Jones, F. J. Swanson, T. Turrentine, and T. C. Winter. 2003. Road Morgantini, L. E., and R. J. Hudson. 1979. Human disturbance and habitat ecology: science and solutions. Island Press, Washington, D.C., USA. selection in elk. Pages 132–139 in M. S. Boyce and L. D. Hayden-Wing, Foster, M. L., and S. R. Humphrey. 1995. Use of highway underpasses by editors. North American elk: ecology, behavior and management. Florida panthers and other wildlife. Wildlife Society Bulletin 23:95–100. University of Wyoming, Lramie, USA. Gagnon, J. W. 2006. Effect of traffic on elk distribution, highway crossings, Perry, C., and R. Overly. 1976. Impacts of roads on big game distributions and wildlife underpass use in Arizona. Thesis, Northern Arizona in portions of the Blue Mountains of Washington. Pages 62–68 in University, Flagstaff, USA. Proceedings of the Elk-Logging-Roads Symposium 16–17 December Gagnon, J. W., N. L. Dodd, R. Schweinsburg, and A. L. Manzo. 2006. 1976, Forest, Wildlife and Range Experiment Station, University of Comparison of wildlife underpass usage along State Route 260 in central Idaho, Moscow, USA. Arizona. Pages 534–544 in Proceedings of the International Conference Romin, L. A., and J. A. Bissonette. 1996. Temporal and spatial distribution on Ecology and Transportation, 29 August–2 September 2005, Sand of highway mortality of mule deer on newly constructed roads at Diego, California, USA. North Carolina Center for Transportation and Jordanelle Reservoir, Utah. Great Basin Naturalist. 56:1–11. the Environment, North Carolina State University, Raleigh, USA. Rost, G. R., and J. A. Bailey. 1979. Distribution of mule deer and elk in Groot Bruinderink, G. W. T. A, and E. Hazebroek. 1996. Ungulate traffic relation to roads. Journal of Wildlife Management 43:634–641. collisions in Europe. Conservation Biology 10:1059–1067. Rowland, M. M., M. J. Wisdom, B. K. Johnson, and J. G. Kie. 2000. Elk Gunson, K. E., and A. P. Clevenger. 2003. Large animal–vehicle collisions distribution and modeling in relation to roads. Journal of Wildlife in the central Canadian Rocky Mountains: patterns and characteristics. Management 64:672–684. Rowland, M. M, M. J. Wisdom, B. K. Johnson, and M. A. Penninger. Pages 355–366 in Proceedings of the International Conference on Ecology and Transportation, 24–29 August 2005, Lake Placid, New 2005. Effects of roads on elk: implications for management in forested ecosystems. Pages 42–52 M. J. Wisdom, editor. The Starkey Project: a York, USA. North Carolina Center for Transportation and the in synthesis of long-term studies of elk and mule deer. Reprinted from the Environment, North Carolina State University, Raleigh, USA. 2004 Transactions of the North American Wildlife and Natural Haikonen, H., and H. Summala. 2001. Deer–vehicle crashes, extensive Resources Conference, Alliance Communications Group, Lawrence, peak at 1 hour after sunset. American Journal of Preventive Medicine 21: Kansas, USA. 209–213. Ruediger, W. C., K. Wall, and R. Wall. 2006. Effects of highways on elk Hershey, T. J., and T. A. Leege. 1976. Influences of logging on elk summer (Cervus elaphus) habitat in the western United States and proposed range in north-central Idaho. Pages 73–80 in Proceedings of the Elk- mitigation approaches. Pages 269–278 in Proceedings of the Interna- Logging-Roads Symposium. Forest, Wildlife and Range Experiment tional Conference on Ecology and Transportation, 29 August–2 Station, University of Idaho, 16–17 December 1975, Moscow, USA. September 2005, San Diego, California, USA. North Carolina Center Iuell, B., H. Becker, R. Cuperus, J. Dufek, G. Fry, C. Hicks, V. Hlavac, J. for Transportation and the Environment, North Carolina State Keller, B. B. le Marie Wandall, C. Rosell, T. Sangwine, and N. Torslov, University, Raleigh, USA. editors. 2003. Wildlife and Traffic—a European handbook for identify- Seiler, A. 2004. Trends and spatial patterns in ungulate–vehicle collisions in ing conflicts and designing solutions. Prepared by COST 341—Habitat Sweden. Wildlife Biology 10:301–313. Fragmentation due to Transportation Infrastructure. Ministry of Trans- Waller, J. S., and C. Servheen. 2005. Effects of transportation infrastructure port, Public Works and Water Management, Road and Hydraulic on grizzly bears in northwestern Montana. Journal of Wildlife Manage- Engineering Division, Delft, The Netherlands. ment 69:985–1000. Jaeger, J. A. G., J. Bowman, J. Brennan, L. Fahrig, D. Bert, J. Bouchard, N. Ward, A. L. 1976. Elk behavior in relation to timber harvest operations and Charbonneau, K. Frank, B. Gruber, and K. Tluk von Toschanowitz. traffic on the Medicine Bow Range in south-central Wyoming. Pages 2005. Predicting when animal populations are at risk from roads: 32–43 in Proceedings of the Elk-Logging-Roads Symposium. Forest, interactive model of road avoidance. Ecological Modeling 185:329–348. Wildlife and Range Experiment Station, University of Idaho, 16–17 Lyon, L. J. 1979. Habitat effectiveness for elk as influenced by roads and December 1975, Moscow, USA. cover. Journal of Forestry 79:658–660. Wisdom, M. J., N. J. Cimon, B. K. Johnson, E. O. Garton, and J. W. Lyon, L. J. 1983. Road density models for describing habitat effectiveness Thomas. 2005. Spatial partitioning by mule deer and elk in relation to for elk. Journal of Forestry 81:592–595. traffic. Pages 53–66 in M. J. Wisdom, editor. The Starkey Project: a Lyon, L. J., and A. G. Christensen. 1992. A partial glossary of elk synthesis of long-term studies of elk and mule deer. Reprinted from the management terms. U.S. Department of Agriculture, Forest Service, 2004 Transactions of the North American Wildlife and Natural General Technical Report INT-GTR-288, Portland, Oregon, USA. Resources Conference, Alliance Communications Group, Lawrence, Manzo, A. L. 2006. An ecological analysis of environmental parameters Kansas, USA. influencing Rocky Mountain elk crossings of an Arizona highway. Witmer, G. W., and D. S. deCalesta. 1985. Effect of forest roads on habitat Thesis, Northern Arizona University, Flagstaff, USA. use by Roosevelt elk. Northwest Science 59:122–125. Marcum, C. L., and W. D. Edge. 1991. Sexual differences in distribution of elk relative to roads and logged areas of Montana. Pages 142–148 in Associate Editor: McCorquodale.

Gagnon et al. Effect of Traffic on Elk 2323 University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln USDA National Wildlife Research Center - Staff Wildlife Damage Management, Internet Center for Publications

1-1-2009 A review of mitigation measures for reducing wildlife mortality on roadways David J. Glista Indiana Department of Transportation,

Travis L. DeVault USDA Wildlife Services, Brewerton, NY, [email protected]

J. Andrew DeWoody Purdue University

Follow this and additional works at: http://digitalcommons.unl.edu/icwdm_usdanwrc Part of the Environmental Sciences Commons

Glista, David J.; DeVault, Travis L.; and DeWoody, J. Andrew, "A review of mitigation measures for reducing wildlife mortality on roadways" (2009). USDA National Wildlife Research Center - Staff Publications. Paper 846. http://digitalcommons.unl.edu/icwdm_usdanwrc/846

This Article is brought to you for free and open access by the Wildlife Damage Management, Internet Center for at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in USDA National Wildlife Research Center - Staff ubP lications by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. Landscape and Urban Planning 91 (2009) 1–7

Contents lists available at ScienceDirect

Landscape and Urban Planning

journal homepage: www.elsevier.com/locate/landurbplan

Review A review of mitigation measures for reducing wildlife mortality on roadways

David J. Glista a, Travis L. DeVault b,∗, J. Andrew DeWoody c a Indiana Department of Transportation, Office of Environmental Services, Ecology Unit, 100 North Senate Avenue, IGCN, Room N642, Indianapolis, IN 46204, USA b United States Department of Agriculture, Wildlife Services, National Wildlife Research Center, 5757 Sneller Road, Brewerton, NY 13029, USA c Department of Forestry and Natural Resources, Purdue University, 195 Marsteller Street, West Lafayette, IN 47907, USA article info abstract

Article history: A growing literature in the field of road ecology suggests that vehicle/wildlife collisions are important to Received 9 October 2007 biologists and transportation officials alike. Roads can affect the quality and quantity of available wildlife Received in revised form 15 April 2008 habitat, most notably through fragmentation. Likewise, vehicular traffic on roads can be direct sources of Accepted 3 November 2008 wildlife mortality and in some instances, can be catastrophic to populations. Thus, connectivity of habi- Available online 17 December 2008 tat and permeability of road systems are important factors to consider when developing road mortality mitigation systems. There are a variety of approaches that can be used to reduce the effects of roads and Keywords: road mortality on wildlife populations. Here, we briefly review wildlife-crossing structures, summarize Mitigation Wildlife previous wildlife road mortality mitigation studies, describe common mitigation measures, and discuss Roads factors that influence the overall effectiveness of mitigation strategies. Because there are very few road Habitat mortality studies “before” and “after” the installation of wildlife-crossing structures, their efficiency is Movements nearly impossible to evaluate. However, simple and relatively inexpensive measures reviewed herein can Mortality almost certainly reduce the number of collisions between wildlife and automobiles. Published by Elsevier B.V.

Contents

1. Introduction ...... 1 2. Types of crossing structures ...... 2 3. Factors influencing the effectiveness of crossing structures ...... 4 4. Nonstructural methods ...... 5 5. Mitigation for birds ...... 5 6. Conclusions ...... 5 Acknowledgements...... 5 References ...... 5

1. Introduction soils, and water have been identified, with effects varying in dis- tance outward from meters to kilometers (Ellenberg et al., 1991; Although roads provide some ecological benefits, such as main- Forman, 1995). “Road-effect zones” impact an estimated 15–20% of tenance of grassland plants in intense agricultural areas (Forman, the land mass in the United States (Forman and Alexander, 1998). 2000), they also can act as both physical and biological barriers Collisions with automobiles are a major source of direct to many wildlife species (Forman and Alexander, 1998; Jackson, mortality in some animal populations (Romin and Bissonette, 2000). Roads can affect the quality and quantity of available wildlife 1996; Trombulak and Frissell, 2000; Gibbs and Shriver, 2002; habitat, most notably through fragmentation. Likewise, vehicu- Glista et al., 2008). Lalo (1987) estimated vertebrate mortal- lar traffic on roads can be direct sources of wildlife mortality, ity on roads in the United States at 1 million individuals per and in some instances, can be catastrophic to animal populations day. A variety of mitigation approaches are used to reduce the (Langton, 1989a). Many other ecological effects of roads on species, effects of roads and road mortality on wildlife populations. In general, these approaches fall into one of two categories: the modification of motorist behavior and/or the modification of ani- ∗ Corresponding author. Tel.: +1 315 698 0940; fax: +1 315 698 0943. mal behavior. Modification of motorist behavior often involves E-mail address: [email protected] (T.L. DeVault). speed limits, lights, and signs, whereas modification of animal

0169-2046/$ – see front matter. Published by Elsevier B.V. doi:10.1016/j.landurbplan.2008.11.001 2 D.J. Glista et al. / Landscape and Urban Planning 91 (2009) 1–7 behavior often involves habitat alterations and/or installation of wildlife-crossing structures (Romin and Bissonette, 1996; Forman et al., 2003). Wildlife-crossing structures range from exclusion fences and culverts to overpass/underpass systems (Romin and Bissonette, 1996). Many structures are designed to reduce large animal–vehicle collisions (Forman et al., 2003). Such structures should be designed to allow safe passage for animals, pro- mote habitat connectivity, be accessible, and encourage natural movements. Unfortunately, the frequency at which road mortality mitigation measures are implemented does not correlate with their perceived effectiveness; the most promising measures often are the least used. For example, Romin and Bissonette (1996) reported that many U.S. states used wildlife-crossing signs and public awareness pro- grams to reduce automobile collisions with large animals, although most state natural resource agencies admitted that the effective- Fig. 1. Amphibian tunnel for mitigating road mortality (Federal Highway ness of such measures was largely unknown to them. Conversely, Administration, 2002). relatively few U.S. states used fences, overpasses, and underpasses to reduce collisions, even though most agencies that used them reported that these structures were effective. Undoubtedly, eco- using purpose-built fauna culverts in combination with exclu- nomic factors often dictate the choice of road mortality mitigation sion fencing under the Pacific Highway. Of all wildlife-crossing measures that are implemented. Moreover, evaluations of miti- structures, culverts may be one of the most economical. Further- gation success often are based on opinion rather than research more, with some modification (e.g., the addition of drift fences, (Forman et al., 2003). Poor road mortality mitigation designs do habitat modification at entrances, incorporation of dry ledges in little to minimize road effects on wildlife and are generally a waste culverts frequently inundated with water), preexisting culverts of time and money. Furthermore, poorly designed structures can often may be used as crossings. A drawback to some culverts is interrupt natural processes that can lead to various ecological prob- that their size may not promote use by larger animals. Also, care lems such as overgrazing, increased erosion, or population declines must be taken to ensure that culverts remain open for animals to (Forman et al., 2003). use. A growing literature in the field of road ecology suggests that Wildlife underpasses, also known as wildlife bridges, are large vehicle/wildlife collisions can be major sources of vertebrate mor- underpasses that provide a relatively unconfined passage for tality and thus potentially limit wildlife populations (Aresco, 2005). wildlife (Jackson and Griffin, 2000). Where roads cross over water For example, one recent study documented nearly 10,000 mortality or other roads, underpasses can provide a passageway for many events over 17 months at a single site (Glista et al., 2008). Miti- wildlife species, especially those that use riparian corridors. In sit- gation measures that potentially reduce such collisions have been uations where underpasses hold excessive amounts of water, ledges developed, and transportation officials should be aware of meth- can be incorporated into their designs to allow animal passage. ods to reduce wildlife mortality on roadways. In this review, we Veenbaas and Brandjes (1999) reported that mammals used all summarize previous wildlife road mortality mitigation monitoring (100%) existing highway underpasses along waterways, and 75% studies, describe some of the most common mitigation measures of underpasses were used by amphibians. Underpasses with the employed, and discuss factors that lead to the overall effectiveness largest diameters were used most frequently by mammals; this of road mortality mitigation measures (Table 1). relationship did not hold for amphibians. Passages with extended banks were used by more species overall. Some advantages to underpasses are that they can utilize natural terrain features to pro- 2. Types of crossing structures mote animal crossings and can accommodate a greater variety of species. Unfortunately, underpasses can be expensive due to con- Pipe culverts are relatively small structures (0.3–2 m diameter) struction costs, such as in instances where they must span large made of concrete, smooth steel, or corrugated metal designed to riparian areas. carry water under roads. Europe has led the way in implementing Overpasses for wildlife are primarily designed for larger ani- smaller pipe-style culverts, also referred to as “amphibian tun- mals such as large carnivores and ungulates. They can range in nels” (Forman et al., 2003; Fig. 1). Box culverts, generally larger width from 30 to 50 m to over 200 m on each end (Jackson and than pipe culverts, also are used to allow water to pass under Griffin, 2000; Forman et al., 2003). Overpasses are sometimes roads. Unlike pipe culverts, they usually remain dry except in referred to as “green bridges”, a term used to describe wildlife periods of heavy runoff. Culverts may be used by a variety of overpasses with relatively large strips of natural vegetation cross- wildlife species to cross roads (Yanes et al., 1995; Rodriguez et al., ing over roads (Bekker et al., 1995). “Landscape connectors” are 1996; Clevenger and Waltho, 2000). Kaye et al. (2005) reported especially wide overpasses that maintain the connectivity of hori- that spotted turtles (Clemmys guttata, a state threatened species) zontal ecological flows across the landscape (Forman et al., 1997). used a box culvert under a highway improvement project to move Wildlife overpasses accommodate a larger variety of species than between two habitats in MA, United States. The use of a sys- do underpasses (Jackson and Griffin, 2000). tem consisting of a retaining well, box culverts, and pipe culverts Van Wieren and Worm (2001) reported that a wildlife overpass reduced wildlife road mortality by 93.5% in the Paynes Prairie in the central Netherlands was used frequently by large mam- State Preserve, FL, United States (Dodd et al., 2004). Clevenger et mals, specifically red deer (Cervus elaphus) and wild boar (Sus al. (2001) monitored 36 culverts along the Trans-Canada highway scrofa). They also noted that animal crossings had increased almost and found a total of 618 crossings by a minimum of 9 species, threefold since previous monitoring in 1989 and suggested that with an average of 2.8 species at each culvert. In Australia, Taylor the increase was due to habituation of red deer to the structure. and Goldingay (2004) recorded 17 different vertebrate species Keller (1999) also noted that ungulates, most notably roe deer D.J. Glista et al. / Landscape and Urban Planning 91 (2009) 1–7 3 toads Elk mammals mammals deer 74 days in late winter/early spring Weasels 2000October 1990–April 1993 Weasels Unspecified February 2001–May 2001 Water frogs, common November 1996–June 1998 Unspecified Unspecified Roe deer Unspecified 2 years Mammals mammals frogs, agile frogs mammals devils France, and Netherlands France, Netherlands Montes de Toledo, Spain None September 1991–July 1992 Small mammals ). Forman et al., 2003 CulvertsCulvertsOverpasses MT, USA Switzerland, MA, Germany, USA Small mammals January 2001-August 2001 Spotted turtles Unspecified April 2004–July 2004 Unspecified Underpasses and overpassesCulvertsUnderpassesCulverts Alberta, CanadaAmphibian tunnels VA, USA FL, Large USA mammals Vancouver, Canada MA, USAAmphibian tunnels November 1997–August 2000Various under-road passages Amphibians andAmphibian small tunnels Large mammals Unspecified NY, USA Deer England Spotted salamanders France June 2004–May 2005 March 2001–March 2002 Spring 1998 Unspecified Amphibians White-tailed deer Southern leopard frogs Common toad, water March 2002–April 2002 Spotted salamanders Unspecified Raccoons Common toad UnderpassesDrift fence and culvertsUnspecifiedBridges and culvertsUnderpasses and overpassesDry drainage culvertsUnderpasses and FL, culverts USA Alberta, Canada New South Wales, Australia TX, USA Alberta, Upper Canada Rhine, France Alberta, Canada UnspecifiedUnderpasses UnspecifiedTunnels Reptiles and Unspecified amphibians Small- andDrift medium-sized Large fences mammals and tunnels BobcatsReflectors, ramps, and pipes 9 months in April 1997 2000–November 2003 FL, January USA 1998–December 1998 TasmaniaUnderpasses MA, USA 9 months in 1985 January 1995–March 1996, New South Wales, Reptiles Australia and amphibians Large mammals August 1997–May 1999 Unspecified Overpasses UnspecifiedUnderpasses Florida FL, Eastern panthers quolls, USA Tasmanian Culverts, underpasses, and Spotted salamanders Ungulates overpasses Underpasses Bobcats UnderpassesCulverts 2 months inOverpasses 1987 1988 Switzerland,Various Germany, types 2 of months, passages 16 days inUnderpasses 1995Culverts WY, USA Florida panthers FL, Netherlands USA Catalonia, Spain Medium- to large-sized Small- to Netherlands medium-sized New South Wales, Australia Alberta, Canada Unspecified Deer Unspecified Central Spain Spotted salamanders Unspecified Unspecified Black bears Mammals Unspecified Spring/summer 2000 None 11 months Unspecified Raccoons, in white-tailed 1997 2 years December 1994–December 1995 3 1989, years 1994, 1995 Rabbits Bandicoots Unspecified Four seasonal periods over 1 year Mice, voles Red Ungulates deer Small mammals Ungulates Various types of passages Hungary Amphibians Unspecified Unspecified . a a a a a a a a a a a a a a a a Forman et al. (2003) Cited in a Pfister et al. (1997) Clevenger and Waltho (2000) Foresman (2001) Foster and Humphrey (1995) Kaye et al. (2005) Keller (1999) Land and Lotz (1996) Clevenger and Waltho (2005) Dodd et al. (2004) Donaldson (2005) Fitzgibbon (2001) Hunt et al. (1987) Jackson (1996) Jackson and Tyning (1989) Langton (2002) LaPoint et al. (2003) Lesbarreres et al. (2004) Aresco (2005) Ballon (1985) Cain et al. (2003) Clevenger (1998) Clevenger and Waltho (1999) Jones (2000) Rodriguez et al. (1996) Roof and Wooding (1996) Rosell et al. (1997) Taylor and Goldingay (2004) Van Wieren and Worm (2001) Veenbaas and Brandjes (1999) Woods (1990) Yanes et al. (1995) Puky and Vogel (2003) Reed et al. (1975) Table 1 Wildlife passage monitoring studies (modified from StudyAMBS Consulting (1997) Mitigation measure(s) Location Target species (or group) Monitoring duration Species encountered 4 D.J. Glista et al. / Landscape and Urban Planning 91 (2009) 1–7

(Capreolus capreolus), were the most frequent users of wildlife over- (Hunt et al., 1987; Rodriguez et al., 1996; Clevenger and Waltho, passes in Switzerland, Germany, France, and the Netherlands. At 1999), but deter other species like deer and other ungulates if it two overpass structures in Banff National Park, Canada, along the restricts their vision (Pedevillano and Wright, 1987; Clevenger and Trans-Canada Highway, Clevenger and Waltho (2005) reported that Waltho, 2000). elk (Cervus elaphus) and deer (Odocoileus spp.) were large mam- The use of fencing and/or barrier walls in conjunction with mals that most frequently used the structures. Some advantages of passages can help prevent animal access to roads and facilitate overpasses are that they are less confining, quieter, maintain ambi- movement of animals towards crossing structures (Ratcliffe, 1983; ent conditions of rainfall, temperature, and light, and can serve as Feldhamer et al., 1986; Jackson and Tyning, 1989; Jackson, 1996; both passageways for wildlife and intermediate habitats for smaller AMBS Consulting, 1997; Bissonette and Hammer, 2000; Jackson animals (e.g., small mammals, reptiles, and amphibians) (Jackson and Griffin, 2000; Dodd et al., 2004). A barrier wall in conjunction and Griffin, 2000). One of the drawbacks of overpasses is that they with a culvert system was effective in reducing wildlife road mor- often are the most expensive option due to their large size and tality 93.5% in the Paynes Prairie State Preserve, Florida (Dodd et construction costs. al., 2004). For many larger species, fencing is necessary because of their inherent avoidance of passages. Many ungulates avoid under- passes unless there is no other way to cross a road (Ward, 1982) 3. Factors influencing the effectiveness of crossing and mountain lions traveling along streams are known to leave structures the stream and cross over highways rather than use under-road culverts (Beier, 1995). Fencing in the absence of crossing struc- Several factors affect the ability of a crossing structure to facil- tures, however, can be detrimental, because it can act as a barrier itate wildlife movements. Location of crossing structures is very to natural movements and contribute to habitat fragmentation important and may be the most important factor predicting effec- (Jaeger and Fahrig, 2004). Fencing should extend far enough to tiveness (Podloucky, 1989; Foster and Humphrey, 1995; Yanes et al., either side of a crossing structure to promote guidance to the struc- 1995; Land and Lotz, 1996; Rodriguez et al., 1996; Clevenger and ture. The length of fencing often is dictated by the target species Waltho, 2000). Location is especially vital for smaller, less mobile and the surrounding terrain. Because there is no universal design species such as reptiles and amphibians (Jackson and Griffin, 2000). that works well for all roads, we recommend that transporta- Rodriguez et al. (1996) suggested that crossing structures should be tion officials work with wildlife biologists to customize fencing placed in areas of suitable habitat and that passages implemented regimes. near continual disturbance (e.g., excessive human presence) were Moisture, temperature, light, substrate, and noise (disturbance) less frequently used by several wildlife species (e.g., carnivores and all can influence whether animals will use wildlife passages ungulates). (Langton, 1989b; Mansergh and Scotts, 1989; Beier, 1995; Yanes The dimensions of structures are also important in designing et al., 1995; Jackson, 1996). Amphibians generally require moist passageways for vertebrates (Ulbrich, 1984; Ballon, 1985 [as cited conditions during migration, thus designing passages to allow in Yanes et al., 1995]). The size and shape of a particular struc- rain to moisten the passage may be important (Jackson, 1996). ture may be the determining factor for crossing success (Reed et Langton (1989b) reported that temperature differences between al., 1975; Ballon, 1985; Cain et al., 2003; Clevenger and Waltho, the interior and exterior of culverts may dissuade use by some 2005). In Europe, hourglass-shaped overpasses are used regularly amphibian species. The ability of air to flow freely through a by wild boar, but not by red deer that become unnerved or fright- passage (e.g., by using grate tops rather than solid tops) may ened by the constriction at the center (Vassant et al., 1993 [as cited help negate temperature differences and allow freer use by a in Forman et al., 2003]). For some species, the relative openness wider range of species. Moreover, open tops will allow more in a passage may be more important than overall size (Foster and ambient light to enter crossing structures. Jackson and Tyning Humphrey, 1995; Clevenger and Waltho, 2005). Structures along (1989) noted that increased natural light in tunnels accelerated the Trans-Canada Highway with high openness ratios (short in the rate at which spotted salamanders (Ambystoma macula- length, high and wide) were used most often by grizzly bears (Ursus tum) would cross. Conversely, artificial light often may deter arctos horribilis), wolves (Canis lupus), elk, and deer, whereas more animals from using a crossing structure (Reed, 1981; Jackson, constrictive structures were used more often by black bears (Ursus 2000). americanus) and cougars (Felis concolor)(Clevenger and Waltho, The inclusion of a natural substrate within a crossing struc- 2005). Tunnels that allow animals to see the other end were pos- ture can provide continuity of habitat and may encourage animals itively correlated with use by some species (Rosell et al., 1997 to pass (Yanes et al., 1995; Jackson, 2000). In controlled experi- [as cited in Jackson and Griffin, 2000]). Conversely, some studies ments between bare concrete tunnels, soil-lined tunnels, and open (Rodriguez et al., 1996; Clevenger and Waltho, 1999) have suggested grass, Lesbarreres et al. (2004) found that water frogs (Rana escu- that smaller passages may be better for some small mammals. lenta) and common toads (Bufo bufo) preferred the tunnels to the There is some evidence that predators use crossing structures to grass, whereas agile frogs (Rana dalmatina) preferred grass. Use and increase prey capture (Hunt et al., 1987; Foster and Humphrey, crossing success were both higher in the soil-lined tunnel. Mougey 1995), which can limit the use of crossing structures by prey (1996) suggested that frogs are deterred from bare concrete due to species. Culverts and underpasses that are exposed, restricted, or its alkalinity. Juvenile western toads (Bufo boreas) and red-legged narrow may reduce the effectiveness of escape mechanisms of frogs (Rana aurora) showed greater movement in culverts with sub- prey species (Reed et al., 1975; Yanes et al., 1995; Clevenger et al., strate as opposed to culverts without (Bernard, 2000 [as cited in 2001). Fitzgibbon, 2001]). Approaches to structures also can affect their use by animals Noise levels (e.g., traffic) can influence animal use of crossing (Veenbaas and Brandjes, 1999; Clevenger and Waltho, 2000). The structures (Clevenger and Waltho, 2000, 2005; Jackson, 2000). In availability of cover (or lack thereof) at the approach to a cross- Banff National Park, Canada, carnivore and ungulate movements ing structure can determine whether a particular species will use through passages near the town of Banff were significantly affected it. Natural vegetation can enhance the “attractiveness” of cross- by human activity and noise (Clevenger and Waltho, 2000). As such, ing structures to animals and allow a continuity of habitat. Cover planners should consider the use of noise-reducing materials dur- may influence the use of crossings by small to mid-sized mammals ing construction of crossing structures. D.J. Glista et al. / Landscape and Urban Planning 91 (2009) 1–7 5

4. Nonstructural methods 6. Conclusions

Financial considerations are often a major concern when con- Everyone (transportation officials, wildlife biologists, the gen- sidering the implementation of wildlife road mortality mitigation eral populace) can agree that collisions between vehicles and measures. Cost can be extremely variable depending on the method wildlife are undesirable. Unfortunately, the reduction of such colli- chosen, availability of materials, and scale of the project. Usu- sions is difficult and nuanced because of many factors, including ally, however, nonstructural methods are less expensive than economics, human attitudes, and wildlife biology. The inher- structural methods. Bank et al. (2002) reported on a variety ent problem when designing effective wildlife-crossing structures of nonstructural methods of road mortality mitigation currently concerns the need to accommodate high priority species while being researched in Europe. These include: (1) olfactory repellents maintaining an economic and structurally sound building plan. whereby scented foam is sprayed on vegetation and structures When possible, target sites for road mortality mitigation should along the road, (2) ultrasound, (3) road lighting (which may be identified a priori in consultation with transportation planners have negative consequences for nesting birds), (4) population and wildlife biologists, but more often are identified a posteriori. control (e.g., hunting), and (5) habitat modification, used pri- Either way, mitigation approaches usually are targeted for a par- marily to keep animals away from roads or increase driver and ticular species or group of organisms. Although many studies have animal visibility. Development of less expensive alternatives to reported on the use of various structures for reducing road mor- expensive structures (e.g., overpasses) would allow wider use and tality, relatively few have measured the success of such structures. promote permeability of road corridors (Forman et al., 2003). As such, more research is needed concerning the effectiveness of Biological consequences of nonstructural methods are not well various road mortality mitigation programs. Although specific rec- understood, and more research is needed to ascertain their effec- ommendations are best made in consultations among planners, tiveness. engineers, and local biologists, we provide below some general Although it is impossible to predict exactly where and when recommendations regarding wildlife collision reduction: animals will appear on roads, motorists who are aware of the potential for animal crossings can sometimes help mitigate wildlife (1) Preconstruction planning is generally more economical than road mortality. The use of signs and/or speed bumps to reduce retrofitting existing roads and potentially could be considered speed and enhancing speed limit enforcement may help reduce during environmental impact assessments. road mortality of wildlife in areas of known animal crossings. (2) Connectivity of habitat and permeability of road systems are High-speed traffic is often considered one of the main causes of important factors. wildlife–vehicle collisions (Pojar et al., 1975; Case, 1978). Wildlife- (3) Financial considerations may dictate nonstructural approaches crossing signs also can be installed in areas of intense animal to collision reduction, but structural methods are probably activity to help make drivers more aware of wildlife presence, more effective (and more expensive). although their effectiveness is questionable (Pojar et al., 1975; (4) Finally, the efficiency of road mortality mitigation approaches Aberg, 1981 [as cited in Groot Briunderink and Hazebroek, 1996]). should be determined via a post-implementation monitoring Even stuffed mule deer (Odocoileus hemionus) placed in road program. rights-of-way failed to evoke a reaction from many drivers (D.F. Reed, personal communication [as cited in Groot Briunderink Acknowledgements and Hazebroek, 1996]), suggesting that traffic control is one of the most difficult options in wildlife road mortality mitiga- We would like to thank the Joint Transportation Research Pro- tion. gram of the Indiana Department of Transportation and Purdue University for funding our research. We also would like to thank O.E. Rhodes, Jr. and H.P. Weeks for their reviews of earlier versions 5. Mitigation for birds of the manuscript.

Although most wildlife road mortality mitigation measures References focus on mammals, reptiles, and amphibians, roads also can affect birds through fragmentation, isolation, and direct mortal- Aberg, L., 1981. The human factor in game–vehicle accidents: a study of driver’s ity. Although most birds possess the ability to fly over roads information acquisition. Acta Universitatis Upsalienis, Studia Psychologica Upsaliensia 6, Uppsala, Finland. rather than walk or run across them, they also have some AMBS Consulting, 1997. Fauna usage of three underpasses beneath the F3 freeway unique problems. Birds often define territories by the use of between Sydney and Newcastle. Final report to New South Wales Roads and songs, and if those songs cannot be heard over (or are dis- Traffic Authority, Sydney, Australia. Aresco, M.J., 2005. Mitigation measures to reduce highway mortality of turtles and torted by) vehicular traffic noise, males may find it difficult to other herpetofauna at a north Florida lake. Journal of Wildlife Management 69, attract and keep mates (Ferris, 1979; Reijnen et al., 1995). Traffic 549–560. noise could potentially force males to conduct wider searches for Ballon, P., 1985. Premieres observations sur l’efficacite des passages a gibier sur l’autoroute A36. In: Routes et faune sauvage. Service d’Etudes Techniques de females and bring them closer to roads. Many migrating species Routes et Autoroutes, Bagneaux, France, pp. 311–316. rely on starlight navigation (Emlen, 1975), thus light pollution Bank, F.G., Irwin, C.L., Evink, G.L., Gray, M.E., Hagood, S., Kinar, J.R., Levy, A., Paul- from a variety of sources, including highway lighting, may cause son, D., Ruediger, B., Sauvajot, R.M., Scott, D.J., White, P., 2002. Wildlife habitat birds to become disoriented, resulting in collisions with auto- connectivity across European highways. Technical Report FWHA-PL-02-011. U.S. Department of Transportation, Washington, DC. mobiles (Ogden and Evans, 1996). Non- or low-flying birds (e.g., Beier, P., 1995. Dispersal of juvenile cougars in fragmented habitat. Journal of Wildlife quail, turkeys, owls), birds that forage at ground level, and scav- Management 59, 228–237. engers are even more susceptible to road mortality because of Bekker, H., van den Hengel, B., van Bohemen, H., van der Sluijs, H., 1995. Natuur over wegen. Ministry of Transport, Public Works and Water Management, Delft, their habits (Stoner, 1925). Therefore, birds present several road Netherlands. mortality mitigation challenges compared to other vertebrates. Bernard, D., 2000. Unpublished environmental monitor’s report submitted to the Jacobson (2005) addressed several of these problems and suggested Vancouver Island highway project. Ministry of Transportation and Highways. Victoria, British Columbia, Canada. possible solutions, including the reduction of noise and light pol- Bissonette, J., Hammer, M., 2000. Comparing the effectiveness of earthen escape lution. ramps with one-way gates in Utah. Unpublished. USGS Utah cooperative Fish 6 D.J. Glista et al. / Landscape and Urban Planning 91 (2009) 1–7

and Wildlife Research Unit, Department of Fisheries and Wildlife, College of Jackson, S.D., Griffin, C.R., 2000. A strategy for mitigating highway impacts on Natural Resources, Utah State University, Logan, UT. wildlife. In: Messmer, T.A., West, B. (Eds.), Wildlife and Highways: Seeking Cain, A.T., Tuovila, V.R., Hewitt, D.G., Tewes, M.E., 2003. Effects of a highway and Solutions to an Ecological and Socio-economic Dilemma. The Wildlife Society, mitigation projects on bobcats in southern Texas. Biological Conservation 114, Bethesda, MD, pp. 143–159. 189–197. Jackson, S.D., Tyning, T.F., 1989. Effectiveness of drift fences and tunnels for mov- Case, R.M., 1978. Interstate highway road-killed animals: a data source for biologists. ing spotted salamanders Ambystoma maculatum under roads. In: Langton, T.E.S. Wildlife Society Bulletin 6, 8–13. (Ed.), Amphibians and Roads, Proceedings of the Toad Tunnel Conference. ACO Clevenger, A.P., 1998. Permeability of the Trans-Canada highway to wildlife in Banff Polymer Products Ltd., Bedfordshire, England, pp. 93–99. National Park: importance of crossing structures and factors influencing their Jacobson, S.L., 2005. Mitigation measures for highway-caused impacts to birds. PSW- effectiveness. In: Evink, G.L., Garrett, P., Zeigler, D., Berry, J. (Eds.), Proceedings GTR-191. USDA Forest Service General Technical Report. of the International Conference on Wildlife Ecology and Transportation. FL-ER- Jaeger, J.A.G., Fahrig, L., 2004. Effects of road fencing on population persistence. 69-98. Florida Department of Transportation, Tallahassee, FL, pp. 109–119. Conservation Biology 18, 1651–1657. Clevenger, A.P., Chruszcz, B., Gunson, K., 2001. Drainage culverts as habitat link- Jones, M., 2000. Road upgrade, road mortality, and remedial measures: impacts ages and factors affecting passage by mammals. Journal of Applied Ecology 38, on a population of eastern quolls and Tasmanian devils. Wildlife Research 27, 1340–1349. 289–296. Clevenger, A.P., Waltho, N., 1999. Dry drainage culvert use and design considerations Kaye, D.R., Walsh, K.M., Ross, C.C., 2005. Spotted turtle use of a culvert for small- and medium-sized mammal movement across a major transportation under relocated Route 44 in Carver, Massachusetts. In: Proceedings of the corridor. In: Evink, G.L., Garrett, P., Zeigler, D., Berry, J. (Eds.), Proceedings of the International Conference of Ecology and Transportation, San Diego, CA, International Conference on Wildlife Ecology and Transportation. FL-ER-69-98. pp. 426–432. Florida Department of Transportation, Tallahassee, FL, pp. 263–277. Keller, V., 1999. The use of wildlife overpasses by mammals: results from infra- Clevenger, A.P., Waltho, N., 2000. Factors influencing the effectiveness of wildlife red video surveys in Switzerland, Germany, France, and the Netherlands. In: underpasses in Banff National Park, Alberta, Canada. Conservation Biology 14, Proceedings of the 5th Infra Eco Network Europe conference, Budapest, Hungary. 47–56. Lalo, J., 1987. The problem of roadkill. American Forests 50, 50–52. Clevenger, A.P., Waltho, N., 2005. Performance indices to identify attributes of high- Land, D., Lotz, M., 1996. Wildlife crossing designs and use by Florida panthers and way crossing structures facilitating movement of large mammals. Biological other wildlife in Southwest Florida. In: Evink, G.L., Garrett, P., Zeigler, D., Berry, Conservation 121, 453–464. J. (Eds.), Proceedings of the International Conference on Wildlife Ecology and Dodd Jr., C.K., Barichivich, W.J., Smith, L.L., 2004. Effectiveness of a barrier wall and Transportation. FL-ER-69-98. Florida Department of Transportation, Tallahassee, culverts in reducing wildlife mortality on a heavily traveled highway in Florida. FL, pp. 323–328. Biological Conservation 118, 619–631. Langton, T.E.S., 1989a. Reasons for preventing amphibian mortality on roads. In: Donaldson, B.M., 2005. Use of highway underpasses by large mammals and other Langton, T.E.S. (Ed.), Amphibians and Roads, Proceedings of the Toad Tunnel wildlife in Virginia and factors influencing their effectiveness. In: Proceedings Conference. ACO Polymer Products Ltd., Bedfordshire, England. of the International Conference of Ecology and Transportation, San Diego, CA, Langton, T.E.S., 1989b. Tunnels and temperature: results from a study of a drift pp. 433–441. fence and tunnel system at Henley-on-Thames, Buckinghamshire, England. In: Ellenberg, H., Muller, K., Stottele, T., 1991.Strassen-Okologie. In: Okologie und strasse. Langton, T.E.S. (Ed.), Amphibians and Roads, Proceedings of the Toad Tunnel Broschurenreihe de Deutschen Strassenliga, Bonn, Germany, pp. 19–115. Conference. ACO Polymer Products Ltd., Bedfordshire, England. Emlen, S.T., 1975. Migration: orientation and navigation. In: Farmer, D.S., King, J.R. Langton, T.E.S., 2002. Measures to protect amphibians and reptiles from road traffic. (Eds.), Avian Biology, vol. 5. Academic Press, New York, pp. 129–219. In: Sherwood, B., Cutler, D., Burton, J. (Eds.), Wildlife and Roads: The Ecological Federal Highway Administration, 2002. FHWA website. http://www.fhwa.dot.gov/ Impact. Imperial College Press, London, England, pp. 223–248. environment/greenerroadsides/sum02p3.htm. LaPoint, S.D., Kays, R.W., Ray, J.C., 2003. Animals crossing the Northway: are existing Feldhamer, G.A., Gates, J.E., Harman, D.M., Loranger, A.J., Dixon, K.R., 1986. Effects culverts useful? Adirondack Journal of Environmental Studies Spring/Summer, of interstate highway fencing on white-tailed deer activity. Journal of Wildlife 11–17. Management 50, 497–503. Lesbarreres, D., Lode, T., Merila, J., 2004. Short communication: what type of amphib- Ferris, C.R., 1979. Effects of Interstate 95 on breeding birds in northern Maine. Journal ian tunnel could reduce road kills? Oryx 38, 220–223. of Wildlife Management 43, 421–427. Mansergh, I.M., Scotts, D.J., 1989. Habitat continuity and social organization of the Fitzgibbon, K., 2001. An evaluation of corrugated steel culverts as transit corridors for mountain pygmy-possum restored by tunnel. Journal of Wildlife Management amphibians and small mammals at two Vancouver Island wetlands and compar- 53, 701–707. ative culvert trials. Thesis, Royal Roads University, Vancouver, British Columbia, Mougey, T., 1996. Des tunnels pour batraciens. Le Courier de la Nature 155, 22–28. Canada. Ogden, L., Evans J., 1996. Collision course: the hazards of lighted structures and Foresman, K.R., 2001. Small mammal use of modified culverts on the Lolo South windows to migrating birds. Report published by World Wildlife Fund Canada project of western Montana. In: Proceedings of the International Conference of and Fatal Light Awareness Program. Ecology and Transportation, Keystone, CO. Pedevillano, C., Wright, R.G., 1987. The influence of visitors on mountain goat activ- Forman, R.T.T., 1995. Land Mosaics: The Ecology of Landscapes and Regions. Cam- ities in Glacier National Park, Montana. Biological Conservation 39, 1–11. bridge University Press, Cambridge, United Kingdom. Pfister, H.P., Keller, V., Reck, H., Georgii, B., 1997. Bio-Ecological Effectiveness Forman, R.T.T., 2000. Estimate of the area affected ecologically by the road system of Wildlife Overpasses or “Green Bridges” Over Roads and Railway Lines. in the United States. Conservation Biology 14, 31–35. Herausgegeben vom Bundesministerium fur Verkehr Abeteilung Strassenbau. Forman, R.T.T., Alexander, L.E., 1998. Roads and their major ecological effects. Annual Bonn-Bad Godesberg, Germany. Review of Ecology and Systematics 29, 207–231. Podloucky, R., 1989. Protection of amphibians on roads: examples and experiences Forman, R.T.T., Freidman, D.S., Fitzhenry, D., Martin, J.D., Chen, A.S., Alexander, from Lower Saxony. In: Langton, T.E.S. (Ed.), Amphibians and Roads, Proceed- L.E., 1997. Ecological effects of roads: toward three summary indices and an ings of the Toad Tunnel Conference. ACO Polymer Products Ltd., Bedfordshire, overview for North America. In: Canters, K. (Ed.), Habitat Fragmentation and England, pp. 15–28. Infrastructure. Ministry of Transport, Public Works and Water Management, Pojar, T.M., Prosence, R.A., Reed, D.F., Woodard, T.N., 1975. Effectiveness of a lighted, Delft, Netherlands, pp. 40–54. animated deer crossing sign. Journal of Wildlife Management 39, 87–91. Forman, R.T.T., Sperling, D., Bissonette, J.A., Clevenger, A.P., Cutshall, C.D., Dale, V.H., Puky, M., Vogel, Z., 2003. Amphibian mitigation measures on Hungarian roads: Fahrig, L., France, R., Goldman, C.R., Heanue, K., Jones, J.A., Swanson, F.J., Tur- design, efficiency, problems, and possible improvement, need for a coordi- rentine, T., Winter, T.C., 2003. Road Ecology; Science and Solutions. Island Press, nated European environmental education strategy. Habitat fragmentation due Washington DC. to transportation infrastructure. In: Proceedings of the 9th Infra Eco Network Foster, M.L., Humphrey, S.R., 1995. Use of highway underpasses by Florida panthers Europe conference, Brussels, Belgium. and other wildlife. Wildlife Society Bulletin 23, 95–100. Ratcliffe, J., 1983. Why did the toad cross the road? Wildlife August, 304–307. Gibbs, J.P., Shriver, G., 2002. Estimating the effects of road mortality on turtle popu- Reed, D.F., 1981. Mule deer behavior at a highway underpass exit. Journal of Wildlife lations. Conservation Biology 16, 1647–1652. Management 45, 542–543. Glista, D.J., DeVault, T.L., DeWoody, J.A., 2008. Vertebrate road mortality pre- Reed, D.F., Woodard, T.N., Pojar, T.M., 1975. Behavioral response of mule deer to a dominately impacts amphibians. Herpetological Conservation and Biology 3, highway underpass. Journal of Wildlife Management 39, 361–367. 77–87. Reijnen, R., Foppen, R., Braak, C.T., Thissen, J., 1995. The effects of car traffic on Groot Briunderink, G.W.T.A., Hazebroek, E., 1996. Ungulate traffic collisions in breeding bird populations in woodland. III. Reductions of density in relation Europe. Conservation Biology 10, 1059–1067. to proximity of main roads. Journal of Applied Ecology 32, 187–202. Hunt, A., Dickens, J., Whelan, R.J., 1987. Movement of mammals through tunnels Rodriguez, A., Crema, G., Delibes, M., 1996. Use of non-wildlife passages across a under railway lines. Australian Zoologist 24, 89–93. high-speed railway by terrestrial vertebrates. Journal of Applied Ecology 33, Jackson, S.D., 1996. Underpass systems for amphibians. In: Evink, G.L., Garrett, P., Zei- 1527–1540. gler, D., Berry, J. (Eds.), Proceedings of the International Conference on Wildlife Romin, L.A., Bissonette, J.A., 1996. Deer-vehicle collisions: status of state monitoring Ecology and Transportation. FL-ER-69-98. Florida Department of Transportation, activities and mitigation efforts. Wildlife Society Bulletin 24, 276–283. Tallahassee, FL, pp. 240–244. Roof, J., Wooding, J., 1996. Evaluation of the S.R. 46 wildlife crossing in Lake Jackson, S.D., 2000. Overview of transportation related wildlife problems. In: Evink, County, Florida. In: Evink, G.L., Garrett, P., Zeigler, D., Berry, J. (Eds.), G.L., Garrett, P., Zeigler, D., Berry, J. (Eds.), Proceedings of the International Confer- Proceedings of the International Conference on Wildlife Ecology and Trans- ence on Wildlife Ecology and Transportation. FL-ER-69-98. Florida Department portation. FL-ER-69-98. Florida Department of Transportation, Tallahassee, FL, of Transportation, Tallahassee, FL, pp. 1–4. pp. 329–336. D.J. Glista et al. / Landscape and Urban Planning 91 (2009) 1–7 7

Rosell, C., Parpal, J., Campeny, R., Jove, S., Pasquina, A., Velasco, J.M., 1997. Mitigation Vassant, J., Brandt, S., Jullien, J.M., 1993. Influence du passage de l’autoroute A5 sur of barrier effect of linear infrastructures on wildlife. In: Canters, K. (Ed.), Habi- les populations cert et sanglier du Massif d’Arc-en-Banois: 1er partie. Bulletin tat Fragmentation and Infrastructure. Ministry of Transport, Public Works and de l’Office National de la Chasse 183, 15–25. Water Management, Delft, Netherlands, pp. 367–372. Veenbaas, G., Brandjes, J., 1999. Use of fauna passages along waterways under high- Stoner, D., 1925. The toll of the automobile. Science 61, 56–57. ways. In: Evink, G.L., Garrett, P., Zeigler, D., Berry, J. (Eds.), Proceedings of the Taylor, B.D., Goldingay, R.L., 2004. Wildlife road-kills on three major roads in north- International Conference on Wildlife Ecology and Transportation. FL-ER-69-98. eastern New South Wales. Wildlife Research 31, 83–91. Florida Department of Transportation, Tallahassee, FL, pp. 253–258. Trombulak, S.C., Frissell, C.A., 2000. Review of ecological effects of roads on terrestrial Ward, A.L., 1982. Mule deer behavior in relation to fencing and underpasses on and aquatic communities. Conservation Biology 14, 18–30. Interstate 80 in Wyoming. Transportation Research Record 859, 8–13. Ulbrich, P., 1984. Untersuchung der wirksamkeit von wildwarnreflektoren und Woods, J.G., 1990. Effectiveness of fences and underpasses on the Trans-Canada der eignung von wilddurchschlassen. Zeitschrift Fur Jagdwissenschaft 30, Highway and their impact on ungulate populations. Report to Banff National 101–116. Park Warden Service. Banff, Alberta, Canada. Van Wieren, S.E., Worm, P.B., 2001. The use of a motorway wildlife overpass by large Yanes, M., Velasco, J., Suarez, F., 1995. Permeability of roads and railways to verte- mammals. Netherlands Journal of Zoology 51, 97–105. brates: the importance of culverts. Biological Conservation 71, 217–222. Research Note

Effects of Traffic Noise on Occupancy Patterns of Forest Birds

SARAH E. GOODWIN∗ AND W. GREGORY SHRIVER Department of Entomology and Wildlife Ecology, University of Delaware, Newark, DE 19716-2103, U.S.A.

Abstract: Noise may drive changes in the composition and abundance of animals that communicate vocally. Traffic produces low-frequency noise (<3 kHz) that can mask acoustic signals broadcast within the same frequency range. We evaluated whether birds that sing within the frequency range of traffic noise are affected by acoustic masking (i.e., increased background noise levels at the same frequency of vocalizations reduce detection of vocalization) and are less abundant in areas where traffic noise is loud (44–57 dB). We estimated occupancy, the expected probability that a given site is occupied by a species, and detection probabilities of eight forest-breeding birds in areas with and without traffic noise as a function of noise and three measures of habitat quality: percent forest cover, distance from plot center to the edge of forest, and the number of standing dead trees or snags. For the two species that vocalize at the lowest peak frequency (the frequency with the most energy) and the lowest overall frequency (Yellow-billed Cuckoo [Coccyzus americanus] and White-breasted Nuthatch [Sitta carolinensis]), the presence of traffic noise explained the greatest proportion of variance in occupancy, and these species were 10 times less likely to be found in noisy than in quiet plots. For species that had only portions of their vocalizations overlapped by traffic noise, either forest cover or distance to forest edge explained more variation in occupancy than noise or no single variable explained occupancy. Our results suggest that the effects of traffic noise may be especially pronounced for species that vocalize at low frequencies.

Keywords: avian communication, masking, roads, song, urban Efectos del Ruido de Tr´afico sobre los Patrones de Ocupacion´ de Aves de Bosque Resumen. El ruido puede producir cambios en la composicion´ y abundancia de animales que se comuni- can vocalmente. El trafico´ produce ruido de baja frecuencia (<3 kHz) que puede enmascarar la transmision´ de senales˜ acusticas´ en el mismo rango de frecuencia. Evaluamos s´ı las aves que cantan en el rango de frecuencia del ruido de trafico´ son afectadas por el enmascaramiento acustico´ (i.e., el incremento en los niveles de ruido de fondo con la misma frecuencia de las vocalizaciones reduce la deteccion´ de vocalizacion)´ y son menos abundantes en areas´ donde el ruido de trafico´ es alto (44–57 dB). Estimamos la ocupacion,´ la probabilidad esperada de que un sitio determinado sea ocupado por una especie, y las probabilidades de deteccion´ de 8 especies de aves de bosque en areas´ con y sin ruido de trafico´ como una funcion´ del ruido y 3 medidas de calidad de habitat:´ porcentaje de cobertura forestal, distancia del centro de la parcela al borde del bosque y el numero´ de arboles´ muertos en pie. Para las especies que vocalizan en el pico menor de frecuencia (la frecuencia con mayor energ´ıa) y en la menor frecuencia total (Coccyzus ameri- canus y Sitta carolinensis), la presencia de ruido de trafico´ explico´ la mayor proporcion´ de varianza en la ocupacion,´ y fue 10 veces menos probable encontrar estas especies en parcelas ruidosas que en parcelas silen- ciosas. Para especies cuyas vocalizaciones se traslaparon parcialmente con el ruido de trafico,´ la variacion´ en la ocupacion´ fue explicada mas´ por la cobertura vegetal o la distancia al borde del bosque que por el ruido o ninguna variable individual explico´ la ocupacion.´ Nuestros resultados sugieren que los efectos

∗Current address: Organismic and Evolutionary Biology Program, University of Massachusetts, 219 Morrill Science, Amherst, MA 01003, U.S.A., email [email protected] Paper submitted April 15, 2010; revised manuscript accepted June 21, 2010. 406 Conservation Biology, Volume 25, No. 2, 406–411 C 2010 Society for Conservation Biology DOI: 10.1111/j.1523-1739.2010.01602.x Goodwin & Shriver 407 del ruido de trafico´ pueden ser especialmente pronunciados para especies que vocalizan en frecuencias bajas.

Palabras Clave: caminos, canto, comunicacion´ de aves, enmascaramiento, urbano

Introduction of Washington, D.C. Both parks have large volumes of traffic (annual average daily traffic of 59,000 along Route Avian communities generally decrease in diversity as ur- 29 in Manassas and 41,000 along Route 234 at the bound- banization increases, with a peak in species richness, ary of Prince William). Shannon diversity, and biomass at moderately urbanized In each park we established 30 study plots in forested sites (Emlen 1974; Blair 1996). This pattern is largely areas that were separated by at least 250 m. Plots were shaped by changes in vegetation cover, composition, and 175 × 175 m, and we marked 25-m intervals in each to patch configuration (e.g., Friesen et al. 1995; Villard et al. create a grid. Fifteen plots were within 250 m of roads 1999; Debinski & Holt 2000). Anthropogenic noise may with heavy traffic (noisy plots), and 15 other plots were also influence species composition wherever noise lev- farther than 700 m from roads with heavy traffic (quiet els are high, for example in urbanized areas. Physiological plots). We measured sound pressure levels (in decibels) and behavioral responses to noise have been documented with an Extech 407730 handheld sound-level meter (Ex- in a variety of animals, including cetaceans (Nowacek tech, Waltham, Massachusetts) set to A-weight and slow et al. 2007), anurans (Sun & Narins 2005), and chiropter- response. Sound pressure level is the logarithmic measure ans (Schaub et al. 2008), and for an increasing variety of sound relative to the threshold of human hearing. We of birds (e.g., Brumm & Todt 2002; Slabbekoorn & Peet recorded minimum and maximum sound pressure levels 2003; Fuller et al. 2007). Vocalizations of birds have been at the center and corners of each plot for 30 s between optimized over evolutionary time (Wiley 1991), and novel dawn and 5 h after dawn, which is the daily peak of avian anthropogenic noise may decrease their effectiveness. singing activity. We averaged these values for each plot There is evidence that noise alters singing behavior (e.g., (Table 1). All noisy plots had a higher average maximum Brumm & Todt 2002; Slabbekoorn & Peet 2003; Wood & sound pressure level than all the quiet sites (t28 = 3.76, Yezerinac 2006), decreases abundance near roads (e.g., p < 0.001). We categorized plots as noisy or quiet be- Reijnen et al. 1996; Forman et al. 2002; Benitez-Lopez cause it is difficult to determine a static sound pressure et al. 2010), and alters patterns of abundance that de- level from a highly variable source of noise, such as pend on song frequency (Rheindt 2003; Hu & Cardoso traffic. 2009). Traffic noise is low frequency, primarily ≤3 kHz We estimated the percent of forest cover within 200 m (Warren et al. 2006; Wood & Yezerinac 2006). Species of plot centers and distance to forest edge from plot that vocalize within this frequency range may be affected centers with the 2001 National Land Cover Dataset in Ar- by acoustic masking, whereby signals in the same fre- cGIS 9.2 (ESRI 2004). We counted snags or standing dead quency range as background noise are more difficult to wood >10 cm diameter at breast height (dbh) within detect (Klump 1996; Patricelli & Blickley 2006). Acoustic 30 m of plot centers as a metric of forest composition as masking could therefore decrease some species’ use of cavity-nesting birds rely on snags for reproduction. We noisy areas. limited the number of site measurements to 3 because the We evaluated occupancy patterns, the expected avian data set was relatively small (Anderson & Burnham probability that a site is occupied, of eight forest bird 2002). species in noisy and quiet areas. We also evaluated as- Plots were surveyed once a week for 10 weeks be- sociations between occupancy patterns and measures of tween dawn and 5 h after dawn on days with no pre- forest cover, composition, and configuration, which are cipitation and little wind. During each visit, a trained more traditional measures of habitat quality.

Table 1. Site characteristics across quiet (n = 15) and noisy (n = 15) plots located in Prince William Forest National Park and Methods Manassas National Battlefield, Virginia. Quiet Noisy We collected data from 25 May through 25 July 2009 in Prince William County in northern Virginia at two na- Site characteristic average SE average SE tional parks: Prince William Forest Park (Prince William) Forest cover (%) 94.17 1.84 85.63 3.06 and Manassas National Battlefield (Manassas). Prince Distance to edge (m) 255.12 58.80 125.68 12.22 William is 6800 ha of forest and is 50 km south of Snags 7.40 1.59 6.20 1.06 Washington, D.C. Manassas (2000 ha) is a mixture Maximum noise (dB) 52.07 0.70 56.88 3.67 Minimum noise (dB) 40.98 0.34 44.57 0.58 of maintained grasslands and forest patches 30 km west

Conservation Biology Volume 25, No. 2, 2011 408 Birds and Traffic Noise

Table 2. Estimated peak, minimum, maximum, and total range of frequency (kHz) of territorial vocalizations of eight forest birds (SE).

Species Peak frequency∗ Minimum frequency Maximum frequency Frequency range

Yellow-billed Cuckoo 0.676 (0.022) 0.433 (0.029) 0.971 (0.058) 0.538 White-breasted Nuthatch 1.442 (0.413) 1.365 (0.120) 2.779 (0.173) 1.337 Carolina Wren 2.606 (0.107) 1.864 (0.199) 4.421 (0.278) 2.557 Great Crested Flycatcher 2.748 (0.162) 1.964 (0.092) 4.244 (0.189) 2.280 Scarlet Tanager 2.907 (0.076) 2.097 (0.045) 4.014 (0.148) 1.917 Wood Thrush 3.292 (0.264) 1.924 (0.129) 6.784 (0.755) 4.860 Ovenbird 4.739 (0.561) 2.943 (0.080) 8.515 (0.269) 5.572 Acadian Flycatcher 5.332 (0.551) 2.337 (0.238) 6.451 (0.044) 4.114 ∗Frequency with greatest power. observer systematically walked the 175 m × 175 m grid of snags, excluding noise. We used models that assumed of each plot, recorded all birds detected by sight and constant detection or occupancy rates as reference mod- sound, and noted their approximate location within the els. We used a global model of detection rate to identify flagged grid (spot mapping) (International Bird Census statistically significant detection covariates and included Committee 1970). The average duration of a survey was only those covariates in our occupancy models. These 31 min, and multiple plots were surveyed each morning. detection covariates were survey specific and were ob- server, date of survey, start time of survey (minutes past dawn), and time spent surveying. We used Akaike’s information criterion (AIC) to rank Data Analyses models and calculated AIC weights in PRESENCE 2.2 (Burnham & Anderson 2002; Hines 2006). We used the We estimated occupancy and detection rates for eight most parsimonious model (lowest AIC value) to estimate breeding bird species: Acadian Flycatcher (Empidonax occupancy and detection parameters. Where there was virescens), Carolina Wren (Thryothorus ludovicianus), no best model (AIC < 2), we used model averaging Great Crested Flycatcher (Myiarchus crinitus), Oven- to estimate the parameters (Burnham & Anderson 2002). bird (Seiurus aurocapilla), Scarlet Tanager (Piranga We used detection probabilities to assess the minimum olivacea), White-breasted Nuthatch (Sitta carolinen- number of visits necessary to establish whether a species sis), Wood Thrush (Hylocichla mustelina), and Yellow- was absent as opposed to not detected (Pellet & Schmidt billed Cuckoo (Coccyzus americanus). We analyzed five 2005). We used the estimated β coefficients to assess the recordings of territorial vocalizations for each species strength of association of each covariate with occupancy (provided by the Macaulay Library of Natural Sounds at and calculated an odds ratio to determine the magnitude the Cornell Lab of Ornithology, Ithaca, New York) to de- of the effect when appropriate (Hosmer & Lemeshow termine the degree of song overlap with anthropogenic 2000). noise. We used recordings made in Maryland, Washing- ton, D.C., or Virginia to ensure that we analyzed bird dialects from our region of study. We measured peak, minimum, and maximum frequency of songs (Table 2) Results with the acoustic analysis program Signal 4.0 (Beeman 2002). We determined peak frequency (i.e., frequency Quiet plots had greater percent forest cover and were with greatest power) of each bird’s song by plotting farther from a forest edge than noisy plots. Quiet plots power against frequency (i.e., the power spectra) and also had a lower minimum and maximum sound pressure determining the apex of this graph. We also measured level than noisy plots (Table 1). The number of snags did minimum and maximum frequencies to assess the total not differ among plot types (Table 1). All species were rel- range of frequency use in vocalizations from power spec- atively common, with na¨ıve estimates of plot-level occu- tra. We measured these values as −24db to the left of pancy ranging from 0.53 (Yellow-billed Cuckoo) to 0.90 the peak frequency and toward lower frequencies (the (Carolina Wren). minimum) or −24db to the right of the peak and toward The model that best explained occupancy patterns var- higher frequencies (maximum). ied by species (Table 3). A model that included only For each plot, we estimated bird detection and occu- noise best explained the occupancy of White-breasted pancy rates with a likelihood-based approach (MacKenzie Nuthatch and Yellow-billed Cuckoo, and both species et al. 2002). We modeled each of the four site covariates were less likely to occur in noisy plots than in quiet (noise, forest cover, distance to forest edge, and number plots (Fig. 1). Beta coefficients for the noise parameter of snags) separately and modeled “all habitat” as an addi- in the noise models were −2.37 (SE 0.84) and −2.83 tive model of forest cover, distance to edge, and number (SE 1.24) for Yellow-billed Cuckoo and White-breasted

Conservation Biology Volume 25, No. 2, 2011 Goodwin & Shriver 409

Table 3. Results of occupancy model selection for eight forest breeding birds.a

Yellow- White- Great billed breasted Carolina Crested Scarlet Wood Acadian Modelb Cuckoo Nuthatch Wren Flycatcher Tanager Thrush Ovenbird Flycatcher

(noise), p(covs) 0.000c 0.000c 1.800 4.530 0.820 1.990 11.120 1.790 (forest cover), p(covs) 5.700 4.800 0.980 3.130 1.760 0.370 0.000c 2.020 (distance to edge), p(covs) 7.140 4.770 2.150 0.000c 1.600 1.620 5.700 0.000 (snags), p(covs) 6.990 4.680 0.000 4.960 1.550 1.440 26.630 1.610 (allhabitat), p(covs) 8.940 8.520 2.660 3.410 5.000 3.920 3.530 2.380 (.), p(covs) 5.450 2.870 0.180 3.530 0.000 0.000 9.720 . (.), p(global) 11.230 3.270 5.310 4.480 2.600 2.390 13.020 5.900 (.), p(.) 11.790 5.310 0.210 30.640 18.710 13.110 48.090 0.030 aValues are change in Akaike information criterion (AIC). bKey: ψ, occupancy covariates; p, detection covariates; covs, significant detection covariates included; allhabitat, additive function of all habitat variables excluding noise; global, all detection covariates included; (.), constant model as reference. cBest model.

Nuthatch, which indicates these species were approxi- generated by traffic noise. Occupancy patterns of low- mately 10 times less likely to be present in noisy plots frequency vocalizers, the Yellow-billed Cuckoo and the than in quiet plots. The vocalizations of these species White-breasted Nuthatch, were best explained by traffic had the lowest average frequencies (Table 2) and over- noise even when measures of vegetation were consid- lapped the most with the frequency of traffic noise ered simultaneously. Although the songs of other species (Fig. 1). Great Crested Flycatcher occupancy patterns in our analyses were partly masked by traffic noise, some were associated most strongly with distance to edge elements of their songs had frequencies that were greater (β =−0.732, SE 0.437), and occupancy patterns of Oven- than traffic noise; thus, they were released from acous- birds were associated most strongly with percent for- tic masking. Stronger evidence to evaluate our hypothe- est cover (β = 15.068, SE 5.499). There was no best sis would include a larger sample size of birds that sing model for the remaining species, and we applied model- at both low and high frequencies and data on the rela- averaging techniques to estimate detection and occu- tive amplitude of traffic noise versus bird song (Dooling pancy rates. Detection rates varied from 26% to 66%, 1982). and 10 visits were sufficient to infer absence for all Occupancy of Great Crested Flycatcher, a forest gen- species. eralist that forages in edges (Brennan & Schnell 2007), was strongly associated with the distance to forest edge. Great Crested Flycatchers also had higher rates of occu- Discussion pancy in noisy plots (Fig. 1), which were often adjacent to roads at the edge of forest. The percentage of forest Our results suggest that traffic noise influences the pres- cover was most strongly associated with occupancy pat- ence of bird species that vocalize in the frequency range terns for Ovenbirds, a forest interior species (VanHorn

Figure 1. Estimates of bird occupancy (1 SE) in quiet (white bar) and noisy (gray bar) plots, and spectrograms of bird vocalizations or a portion of a vocalization (black) and frequency range of traffic noise (gray).

Conservation Biology Volume 25, No. 2, 2011 410 Birds and Traffic Noise et al. 1995). Forest cover is an established predictor of Debinski, D. M., and R. D. Holt. 2000. A survey and overview of habitat distribution and abundance of Ovenbirds (VanHorn et al. fragmentation experiments. Conservation Biology 14:342–355. 1995) and their song frequency range is not masked by Dooling, R. J. 1982. Auditory perception in birds. Kroodsma. Pages 95–130 in D. E., and E. H. Miller, editors. Acoustic communication traffic noise. in birds. Volume 1. Academic Press, New York. The four site variables we examined represent only Emlen, J. 1974. Urban bird community in Tucson, Arizona – derivation, a few of all possible variables relevant to site use and structure, regulation. Condor 76:184–197. selection, and species for which we did not identify best ESRI (Environmental Systems Research Institute). 2004. ArcGIS. Version models were likely responding to unmeasured habitat 9.0. ESRI, Redlands, California. Forman, R. T. T., B. Reineking, and A. M. Hersperger. 2002. Road traffic characteristics or other factors that we did not examine. and nearby grassland bird patterns in a suburbanizing landscape. Our work adds to a growing body of literature that Environmental Management 29:782–800. suggests noise has adverse effects on natural systems. Friesen, L. E., P. F. J. Eagles, and R. J. Mackay. 1995. Effects of residen- Abundance of some species of birds is thought to decline tial development on forest-dwelling neotropical migrant songbirds. 9: in response to traffic noise (e.g., Reijnen & Foppen 1995; Conservation Biology 1408–1414. Fuller, R. A., P. H. Warren, and K. J. Gaston. 2007. Daytime noise pre- Reijnen et al. 1995; Rheindt 2003); however, we are the dicts nocturnal singing in urban robins. Biology Letters 3:368–370. first to evaluate the importance of traffic noise relative Hines, J. E. 2006. Presence 2.2. USGS-Patuxent Wildlife Research Cen- to vegetation across multiple species. On the basis of ter, Laurel, Maryland. our results for Yellow-billed Cuckoos and White-breasted Hosmer, D. W., and S. Lemeshow. 2000. Applied logistic regression. Nuthatches, we suggest that birds that sing at the frequen- 2nd edition. John Wiley & Sons, New York. Hu, Y., and G. C. Cardoso. 2009. Are bird species that vocalize at higher cies of traffic noise may be strongly affected by the noise frequencies preadapted to inhabit noisy urban areas? Behavioral of urbanization and infrastructure development beyond Ecology 20:1268–1273. urbanized areas. International Bird Census Committee. 1970. An international stan- dard for a mapping method in bird census work recommended by the International Bird Census Committee. Audubon Field Notes 24:722–726. Acknowledgments Klump, G. A. 1996. Bird communication in the noisy world. Pages 321–338 in D. E. Kroodsma, and E. H. Miller, editors. Ecology and We thank J. Harmening for field assistance and the Univer- evolution of acoustic communication in birds. Comstock Publishing, sity of Delaware, College of Agriculture and Natural Re- Ithaca, New York. sources, Department of Entomology and Wildlife Ecology MacKenzie, D. I., J. D. Nichols, G. B. Lachman, S. Droege, J. A. for logistical and administrative support. J. L. Bowman, S. Royle, and C. A. Langtimm. 2002. Estimating site occupancy rates 83: L. Carter, C. K. Williams, and two anonymous reviewers when detection probabilities are less than one. Ecology 2248– 2255. provided valuable comments on earlier versions of this Nowacek, D. P., L. H. Thorne, D. W. Johnston, and P. L. Tyack. 2007. manuscript and are warmly acknowledged. We also thank Response of cetaceans to anthropogenic noise. Mammal Review the Podos Lab at the University of Massachusetts Amherst 37:81–115. for song analysis suggestions and helpful feedback. This Patricelli, G. L., and J. L. Blickley. 2006. Avian communication in research was funded by the National Park Service (NPS) urban noise: causes and consequences of vocal adjustment. Auk 123:639–649. National Capital Region Inventory and Monitoring Net- Pellet, J., and B. R. Schmidt. 2005. Monitoring distributions using call work, and J. P. Campbell and NPS staff made this project surveys: estimating site occupancy, detection probabilities and in- possible. ferring absence. Biological Conservation 123:27–35. Reijnen, R., and R. Foppen. 1995. The effects of car traffic on breeding bird populations in woodland. 4. Influence of population-size on the Literature Cited reduction of density close to a highway. Journal of Applied Ecology 32:481–491. Anderson, D. R., and K. P. Burnham. 2002. Avoiding pitfalls when us- Reijnen, R., R. Foppen, C. Terbraak, and J. Thissen. 1995. The effects of ing information-theoretic methods. Journal of Wildlife Management car traffic on breeding bird populations in woodland. Reduction of 66:912–918. density in relation to the proximity of main roads. Journal of Applied Beeman, K. 2002. SIGNAL 4.0. Engineering Design, Belmont, Mas- Ecology 32:187–202. sachusetts. Reijnen, R., R. Foppen, and H. Meeuwsen. 1996. The effects of traffic Benitez-Lopez, A., R. Alkemade, and P. A. Verweij. 2010. The impacts on the density of breeding birds in Dutch agricultural grasslands. of roads and other infrastructure on mammal and bird populations: Biological Conservation 75:255–260. a meta-analysis. Biological Conservation 143:1307–1316. Rheindt, F. E. 2003. The impact of roads on birds: does song frequency Blair, R. 1996. Land use and avian species diversity along an urban play a role in determining susceptibility to noise pollution? Journal gradient. Ecological Applications 6:506–519. of Ornithology 144:295–306. Brennan, S. P., and G. D. Schnell. 2007. Multiscale analysis of tyran- Slabbekoorn, H., and M. Peet. 2003. Ecology: birds sing at a higher pitch nid abundances and landscape variables in the Central Plains, USA. in urban noise – great tits hit the high notes to ensure that their Wilson Journal of Ornithology 119:631–647. mating calls are heard above the city’s din. Nature 424:267–267. Brumm, H., and D. Todt. 2002. Noise-dependent song amplitude regu- Schaub, A., J. Ostwald, and B.M. Siemers. 2008. Foraging bats avoid lation in a territorial songbird. Animal Behaviour 63:891–897. noise. Journal of Experimental Biology 211:3174–3180. Burnham, K. P., and D. R. Anderson. 2002. Model selection and Sun, J. W. C., and P. M. Narins. 2005. Anthropogenic sounds multi-model inference: a practical information-theoretic approach. differentially affect amphibian call rate. Biological Conservation Springer Science and Business Media, New York. 121:419–427.

Conservation Biology Volume 25, No. 2, 2011 Goodwin & Shriver 411

VanHorn, M. A., R. M. Gentry, and J. Faaborg. 1995. Patterns of ovenbird Warren P. S., M. Katti, M. Ermann, and A. Brazel. 2006. Urban bioacous- (Seiurus aurocapillus) pairing success in Missouri forest tracts. Auk tics: it’s not just noise. Animal Behaviour 71:491–502. 112:98–106. Wiley, R. H. 1991. Associations of song properties with habitats for Villard M. A., M. K. Trzcinski, and G. Merriam. 1999. Fragmenta- territorial oscine birds of eastern North-America. The American Nat- tion effects on forest birds: relative influence of woodland cover uralist 138:973–993. and configuration on landscape occupancy. Conservation Biology Wood, W. E., and S. M. Yezerinac. 2006. Song sparrow (Melospiza 13:774–783. melodia) song varies with urban noise. Auk 123:650–659.

Conservation Biology Volume 25, No. 2, 2011 Biodivers Conserv (2008) 17:1685–1699 DOI 10.1007/s10531-008-9374-8

ORIGINAL PAPER

Response of carnivores to existing highway culverts and underpasses: implications for road planning and mitigation

Clara Grilo Æ John A. Bissonette Æ Margarida Santos-Reis

Received: 14 June 2007 / Accepted: 13 March 2008 / Published online: 26 March 2008 Ó Springer Science+Business Media B.V. 2008

Abstract Roads with high traffic volumes are a source of animal mortality, can disrupt normal animal movements and dispersal, and may represent a potentially serious threat to wildlife population stability and viability. Retrofitting existing structures built for other purposes (e.g., drainage culverts or small below-grade access roads) to facilitate wildlife crossing by animals and to reduce mortality may be expensive if modifications to the existing structures themselves were involved. However, the environmental context sur- rounding these structures may influence the willingness of animals to cross, and management of some of these attributes may enhance the attractiveness of these structures. Culverts and underpasses are two common structures along roads in Portugal. We quan- tified the response of small and medium-sized carnivores to the presence of both types of existing passages by determining: (1) frequency of use; (2) whether use differed by type of passage, and if so; (3) by examining if associated environmental attributes might explain the differences observed. We surveyed 57 different passages along 252 km of highway with a total sampling effort of 2,330 passage trap-days. The mean passage rate for car- nivores combined was 0.7 complete passages per crossing structure per day. Crossings by weasel, polecat, otter, and wildcat were infrequent or absent. Red fox, badger, genet and Egyptian mongoose used the crossing structures regularly and without obvious preference; stone marten preferred underpasses. Regression analyses showed the frequency of use by carnivores varied with structural, landscape, road-related features, and human disturbance with 17 of 26 (65%) attributes being significant. Larger passages with vegetation close to the passage entrances, favorable habitat in the surrounding area, and low disturbance by humans were important key features to regular use by the guild of species studied. Miti- gation planning in areas with ecological significance for carnivores will be beneficial. Structural attributes and human disturbances are more difficult or expensive to change,

C. Grilo (&) Á M. Santos-Reis Departamento de Biologia Animal/Centro de Biologia Ambiental, Faculdade de Cieˆncias, Universidade de Lisboa, C2 5° Piso, 1749-016 Lisboa, Portugal e-mail: [email protected]

J. A. Bissonette USGS Utah Cooperative Fish and Wildlife Research Unit, Department of Wildland Resources, College of Natural Resources, Utah State University, Logan, UT 84322-5290, USA 123 1686 Biodivers Conserv (2008) 17:1685–1699 even though related significantly to crossing use. Management of vegetation at passage entrances and restricting human use near passages in carnivore suitable areas may sub- stantially improve crossing attractiveness for the guild of carnivore species.

Keywords Carnivores Á Conservation Á Habitat connectivity Á Non-wildlife passages Á Road design

Introduction

Increasing road density has emerged recently as a major conservation issue (Noss et al. 1996; Trombulak and Frissel 2000; Forman et al. 2003). Wide roads with high traffic volumes represent a serious threat to wildlife by introducing an additional source of mortality (Forman and Alexander 1998; Gerlach and Musolf 2000; Trombulak and Frissel 2000; Iuell et al. 2003; Epps et al. 2005). Furthermore, roads can disrupt animal movement and dispersal, creating effective barriers and resulting in the loss of landscape connectivity. Highways, in particular, often are avoided by wildlife as a consequence of increasing urbanization (Ruediger 1998; Hlava´cˇ and Ande˘l 2002; Whittington et al. 2005). In some mammalian carnivores there is evidence of vulnerability to road network expansions (Ferreras et al. 1992; Haas 2000; Cain et al. 2003; Percy 2003; Kramer-Schadt et al. 2004) because of their relatively large ranges and low densities (Sunquist and Sunquist 2001). Some carnivores face threats of extinction in some regions. For example, Van der Zee et al. (1992) explicitly linked badger population declines in the Netherlands during the late 1980s to high road density; Thiel (1985) found that wolves disappeared when road den- sities exceeded 0.6 km km-2. According to Chruszcz et al. (2003), in Banff National Park, Canada, grizzly bears were found closer to roads with low traffic volumes. In Spain, road density impacted fox and stone marten movements (Blanco 1988; Lope´z-Martin et al. 1997) resulting in home range changes. Similarly, Whittington et al. (2004) reported that roads increased the tortuosity of wolf movement pathways in areas of high road density. Given these data, it is clear that barrier effects in particular, have emerged as a significant threat to the viability of some carnivore populations world-wide. Thus, an opportunity to minimize barrier effects includes the adaptation of existing transportation infrastructures to facilitate passage and restore large-scale habitat connectivity. Passages designed specifically to increase road permeability have been constructed for some groups of vertebrates (Foster and Humphrey 1995; Keller and Pfister 1997; Cle- venger and Waltho 2000) but they are not common in Portugal. However, because existing structures built for other purposes (e.g., drainage culverts, and below-grade local access roads) are numerous and may often coincide with preferential crossing locations, they have received increasing attention as potential valuable alternatives to mitigate barrier effects (Hunt et al. 1987; Yanes et al. 1995; Rodriguez et al. 1996; Clevenger et al. 2001; Cain et al. 2003; Mata et al. 2005). The use of existing passages by carnivores is relatively well- described (Foster and Humphrey 1995; Clevenger et al. 2001; Gloyne and Clevenger 2001; Cain et al. 2003; Dodd et al. 2004; Clevenger and Waltho 2005). There is evidence that carnivores do not cross highways at random, but rather focus their crossing activity in locations that vary with passage characteristics, road-related attributes, surrounding habitat characteristics, and human disturbance levels (Barnum 2003; Rodriquez et al. 1997; Cle- venger and Waltho 2000; Mata et al. 2005). Therefore, managing the habitat surrounding in existing crossing structures may well be a cost effective way of increasing their use (Iuell et al. 2003). 123 Biodivers Conserv (2008) 17:1685–1699 1687

In the Mediterranean region, a world biodiversity hotspot (Myers et al. 2000), some studies have investigated the role of existing structures and their importance in restoring landscape permeability for some small and medium-sized carnivores (Yanes et al. 1995; Rosell et al. 1997; Rodriguez et al. 1997; Mata et al. 2005; Ascensa˜o and Mira 2007). However, there is little consensus on whether the type of passage significantly influences crossing rates. Rosell et al. (1997) found no significant differences related to size of passage; Mata et al. (2005) reported that most carnivores in Spain (except weasels) pre- ferred larger structures; Yanes et al. (1995) and Ascensa˜o and Mira (2007) found some carnivore species used smaller culverts regularly. To examine the importance of passage size on restoring carnivore habitat connectivity, we collected quantitative data on the response of small and medium-sized carnivores to the most common existing structures along selected highways in Portugal: culverts and underpasses. Culverts are small-sized circular or rectangular tubes that allow for water flow from surrounding drainages, whereas underpasses are larger passages usually built for passage by farm vehicles. We first sought to determine how often carnivores used crossing structures. Second, we were interested in whether differences in passage use were related to structure size, or to measurable envi- ronmental variables associated with each structure. We expected a regular use of existing passages by carnivores but different crossing rates for each type of passage. Specifically, we predicted that both fossorial (fox and badger) and ground-dwelling (mongoose) species would use the culverts more often whereas arboreal (stone marten and genet) species would use the larger underpasses. Additionally, we expected that cover would explain some of the variance in passages use.

Study area and methods

Study area

The study was conducted along 252 km of two highways (A2—94 km and A6—158 km) in Alentejo province, southern Portugal between March and September 2004. Both high- ways are four-lane roads and are bordered on both sides by unburied livestock exclusion fences (1.5 m high, 10 cm mesh size). Between 1998 and 2001, reconstructed stretches of both highways were opened to traffic. Currently A2 and A6 have an average daily traffic volume of *13,000 and *6,000 vehicles/day, respectively. The densities of the different crossing structures were similar for both highways and averaged: 1.22 circular culverts/km (1 9 1 and 1.5 9 1.5 m), 0.34 box culverts/km (2 9 2, 3 9 3, 4 9 4 and 5 9 5 m), and 0.47 underpasses/km (5 m height and 8 m width). Mean distance between crossing structures was *390 m, and ranged from 5 to 1,566 m. The study area was characterized by its vast plains, with elevations ranging from *200 to 500 m, and by its Mediterranean climate. The region was originally covered by woodlands and scrublands, but has been modified by human activity for centuries, and especially since the 1930s. The resulting landscape is highly fragmented, with about half of the area occupied by cropland. The remaining area is dominated by cork oak (Quercus suber) woods in the west and holm oak (Quercus ilex) woods in the east. Primary human activities include cork extraction, livestock, agriculture, and hunting. Three Natura 2000 sites (Sado, Cabrela, and Monfurado) are located in the province. Human population density is *43 inhabitants km-2 (INE 2002) and the road network density averages 0.25 km km-2, about half of the mean national road network density of 0.49 km km-2 (IgeoE 1999). 123 1688 Biodivers Conserv (2008) 17:1685–1699

The carnivore community in the study area is diverse and comprised of nine species (Santos-Reis and Petrucci-Fonseca 1999): fox (Vulpes vulpes), weasel (Mustela nivalis), polecat (Mustela putorius), stone marten (Martes foina), badger (Meles meles), otter (Lutra lutra), genet (Genetta genetta), Egyptian mongoose (Herpestes ichneumon) and wildcat (Felis silvestris). The wildcat is legally classified as threatened (Vulnerable), while the polecat is classified as Data Deficient (Cabral et al. 2005). The otter, although classed as Least Concern in Portugal (Cabral et al. 2005) is of conservation concern in Europe (Near Threatened, IUCN 2006).

Crossing structures and monitoring

A sample of 57 crossing structures was selected for monitoring of carnivore use along the A2 and A6 highways (Fig. 1), and included two structural designs: (1) 44 circular culverts (1 and 1.5 m of diameter) and 13 underpasses (5 m high, 8 m wide). On average, the minimum distance between crossings selected for this study was 2 km (roughly equivalent to the average diameter of carnivore home range, as documented by Palomares and Delibes 1994; Rosalino et al. 2004; Santos-Reis et al. 2004; Rondinini et al. 2006) in order to minimize the effects of spatial autocorrelation and help insure independence of observa- tions (Guisan and Zimmermann 2000). Field work took place during the driest period of the year when passages were least likely to be flooded. We used marble dust to detect tracks during 20 consecutive days in spring and 20 days in summer, 2004. A dust plot 1 m wide and 3–10 mm deep was put on the ground at both ends of each culvert and in the middle of the underpass, checked every 5 days, and carnivore tracks identified (Lawrence and Brown 1973; Blanco 1998; Pin˜ero 2002). On average, we checked each crossing eight times during the monitoring periods. Adverse weather conditions and livestock and human activities occasionally prevented clear identification of tracks, hence we only recorded data when a correct assessment of

Fig. 1 Study area and passages location along the A2 and A6 highways 123 Biodivers Conserv (2008) 17:1685–1699 1689 animal sign was possible. Each record included species ID, number of tracks, and whether the tracks completely or partially crossed through the passage). In selected passages, infra-red digital CamtrackÒ cameras were used at both entrances to validate track identifications.

Data analysis

To calculate the crossing rate, we summed the number of times a given species used the passage (complete passage) and divided by the number of operative days the passage was sampled for each season. We also quantified partial passage, which occurred when the tracks were not found in both passage entrances in the same direction and infra-red cameras detect enter and exit of the same species in a short period of time. In general, crossing rates tended to be higher in spring than in other seasons, with significant differences between spring and summer (Wilcoxon test, P \ 0.05), hence for the analysis, we compared the mean crossing rates between the two seasons. To evaluate the effect of passage size on number of crossings, we removed the con- founding effects of the surrounding landscape by using two approaches: (1) we analyzed 26 crossing structures (13 circular culverts plus 13 underpasses) placed along both highways; and (2) we compared six paired culverts and underpasses. Mann–Whitney U-tests (P \ 0.05) were conducted to test for significant differences in use of passages based on size and Wilcoxon signed rank tests for differences in use for six paired passages. To assess the influence of environmental variables on passage use, we used all sampled crossing structures (n = 57); each was characterized according to 32 independent variables (Table 1). Structural variables included crossing structure dimensions: width, height, and an openness ratio (Yanes et al. 1995), distance from highway to passage, and year of construction. Landscape attributes at a micro-scale included percentage of five land use types measured within a 500 m radius of the crossing structure: urban, intensive agricul- ture, extensive agriculture, oak woodlands, and production forest (Pinus spp.; Eucalyptus spp.). In order to evaluate the influence of landscape variables on the passages use, we also estimated the proportion of the five habitat cover types mentioned above within a circle with a radius equivalent to the carnivores’ home range around each passage. We used the home range size of 300 ha for stone marten, genet and mongoose data (see Palomares and Delibes 1991, 1993; Santos-Reis et al. 2004), and 500 ha for fox and badgers (see Rosalino et al. 2004). Distances from passage to the nearest forest cover, as well as the proportion and average height of shrubs within 10 m were also measured. In order to evaluate the role of streams and associated vegetation, streams were characterized by width, direction, and distance to the highway. Road-related attributes included: number of additional existing structures in a 1,000 m buffer around each passage, distance to the next nearest crossing structure, and average distance from each structure to the nearest two structures. Human disturbance attributes included 2004 daily average traffic volume (BRISA, unpublished data), intensity of human activity, minimum distance to other roads and average distance to urban areas. Because of the proportional nature of the response variable (species crossing rates), we assumed that errors followed a binomial distribution (Zuur et al. 2007). Therefore, gen- eralized linear models with a logarithmic function were fitted to the data to investigate the influence of environmental attributes near passages on species crossing rates (Faraway 2004). Only variables that yielded significant results (P \ 0.10) for species-specific crossing rates in the bivariate regression analysis were used as predictors for subsequent 123 1690 Biodivers Conserv (2008) 17:1685–1699

Table 1 Names, definitions, mode and range of values of variables used in the analysis Variables Definition Mode Range values

Structural Width Crossing structure width (m) 1 1–9 Height Crossing structure height (m) 1 1–6.2 Openness Crossing structure openness 0.03 0.03–1.33 (= width 9 length/height) Landscape Urban_500 m Urban within 500 m radius (%) 0 0–10 Intensive agriculture_500 m Intensive agriculture within 500 m radius 0 0–50 (%) Extensive agriculture_500 m Extensive agriculture within 500 m radius 0 0–100 (%) Oak woodland_500 m Oak woodland within 500 m radius (%) 0 0–100 Production forest_500 m Production forest within 500 m radius (%) 0 0–20 Urban_hr Urban within home range areaa (%) 0 0–7 Intensive agriculture_hr Intensive agriculture within home range 0 0–100 areaa (%) Extensive agriculture_hr Extensive agriculture within home range 0 0–95 areaa (%) Oak woodland_hr Oak woodland within home range areaa 0 0–98 (%) Production forest_hr Production forest within home range areaa 0 0–7 (%) % Shrub cover_500 m Shrub cover measured within 500 m radius 0 0–100 (%) Distance to forest cover Minimum distance from the passage to 0 0–2,000 forest cover (m) Density of vegetation 0 = absent; 1 = sparse; 2 = dense 0 0–2 at the entrance Height vegetation Average height of vegetation within 10 m 0 0–1.25 of both entrances (m) Stream width Stream width (m) 0 0–8 Distance to streams Distance to streams (m) 2,000 0–2,000 Stream direction 0 = absent; 1 = parallel, 0 0–2 2 = perpendicular Type of riparian vegetation 0 = absent, 1 = shrubs, 2 = gallery 0 0–2 Structure of riparian vegetation 0 = absent, 1 = open, 2 = closed 0 0–2 Road-related Highway—passage distance Distance from the passage entrance to 7 1–21 highway edge (m) Year of construction Year of construction of the highway (year) 1998 1995–2001 Distance to the nearest passage Distance to the nearest crossing structure 100 1–580 (m) Distance to the two nearest Average distance to the nearest crossing 250 75–875 passages structure at both sides of the passage (m) Number passages Number passages in within 1,000 m radius 6 1–12 from the passage

123 Biodivers Conserv (2008) 17:1685–1699 1691

Table 1 continued

Variables Definition Mode Range values

Human disturbance Traffic volume Mean 2004 average daily traffic volume 9,404 3,000–18,000 (no vehicles/day) Human use 0 = absent; 1 = irregular; 2 = regular 0 0–2 Distance to roads Minimum distance to linear infra 349 109–519 structures (other roads) (m) Distance to cities Average distance to cities within 1,000 m 250 0–4,031 radius (m) Road density_hr Sum of road length within home range 2,514 2,247–8,591 areaa (m) a 300 ha for stone marten, genet and mongoose and 500 ha for fox and badger

multiple regression analysis. We applied a stepwise selection procedure to retain signifi- cant variables and their interactions. Suitable transformations on the dependent and independent variables were conducted to reduce the effect of outliers (Chaterjee and Price 1991). In addition, we constructed a correlation matrix and excluded correlated variables to minimize multicollinearity. All statistical analyses were conducted using the Brodgar 2.5.1 (Zuur et al. 2007) and SPSS 14 v. (SPSS 2003) software programs.

Results

Which species used the crossings?

Eight carnivore species used the crossing structures over 2,330 trap-days: red fox, weasel, polecat, stone marten, badger, otter, genet, and Egyptian mongoose. Although present in the study area (Pinto and Fernandes 2001; Fernandes 2004), no wildcats were recorded. A total of 1,940 carnivore tracks were recorded; 1,649 (85%) were complete passages. The average crossing rate was 0.7 complete passages per structure per day (Table 2). Egyptian mongoose (28%) and badger (27%) crossed most frequently, followed by fox (18%), stone marten (12%), genet (12%) and otter (2%). Weasels (n = 2) and polecats (n = 1) crossed least frequently. The average number of species detected at a crossing structure was 3.32 (SD = 1.17). Absence of wildcat records and the small number of weasel, polecat, and otter records precluded statistical analysis. We focused on complete crossings by the five species that used the passages the most (red fox, stone marten, badger, genet, and Egyptian mongoose).

Did passage size make a difference?

Even though there was a tendency to use the larger underpasses (Fig. 2), only stone marten showed a statistically significant preference (U = 40.5, 0.01 \ P \ 0.05). When use of paired culverts and underpasses was conducted, we found similar results: selection was random except for stone marten, which preferred underpasses (Z =-1.782, 0.01 \ P \ 0.05). 123 62BoiesCnev(08 17:1685–1699 (2008) Conserv Biodivers 1692 123

Table 2 Movements through crossing structures expressed in number of tracks per day Typea Fox Weasel Polecat Stone marten Badger Otter Genet Mongoose

CP PP CP PP CP PP CP PP CP PP CP PP CP PP CP PP

Spring 0.085 0.014 0.000 0.001 0.001 0.000 0.117 0.028 0.212 0.025 0.013 0.001 0.104 0.021 0.188 0.060 Summer 0.151 0.015 0.000 0.000 0.001 0.000 0.053 0.017 0.162 0.015 0.013 0.003 0.065 0.006 0.207 0.043

a CP, complete passage; PP, partial passage Biodivers Conserv (2008) 17:1685–1699 1693

0.8

0.7 underpasses circular culverts 0.6

0.5

0.4

0.3

0.2 number ofnumber passages/day 0.1

0.0 fox stone marten badger genet mongoose

Fig. 2 Mean crossing rates for the culverts and underpasses and standard deviation respectively (n = 26)

Table 3 Deviance explained with their slope (± slope value) and level of significance and numbers (1–9) indicating variable importance rank for each species Variables Fox Stone marten Badger Genet Mongoose

Structural Width +0.09** 1 +0.22** 1 +0.100** 5 +0.06* 5 ns Height +0.08** 2 +0.18** 2 +0.080** 7 +0.04* 6 ns Openness +0.07** 3 +0.16** 4 0.060** 9 +0.06* 5 ns Landscape Extensive agriculture_500 m ns 0.08** 6 -0.18** 1 -0.09* 2 ns Oak woodland_500 m +0.08** 2 +0.17** 3 +0.11** 4 +0.07** 4 +0.04* 5 % Shrub cover_500 m ns ns ns ns +0.07** 4 Intensive agriculture_hr ns -0.17* 3 ns ns ns Oak woodland_hr ns 0.12* 5 0.07* 8 ns ns Distance to forest cover ns -0.08** 7 -0.17** 2 -0.06* 5 ns Height of vegetation +0.07** 3 ns ns ns +0.14** 1 Stream direction ns ns +0.04* 10 ns +0.11** 2 Type of riparian vegetation ns ns +0.09** 6 ns +0.07** 4 Structure of riparian vegetation ns ns ns ns +0.07** 4 Road-related Distance to the nearest passage ns -0.09** 6 ns ns -0.08** 3 Highway—passage distance ns +0.08* 7 ns ns ns Human disturbance Traffic volume ns ns +0.06** 8 ns ns Human use ns ns -0.08** 7 -0.08* 3 ns Distance to roads +0.07** 3 +0.06** 8 +0.12** 3 +0.10** 1 ns Distance to cities ns ns +0.04* 10 ns ns Road density_hr ns ns ns -0.09* ns—not significant; * 0.05 [ P \ 0.10; ** 0.00 [ P \ 0.05 123 1694 Biodivers Conserv (2008) 17:1685–1699

What environmental variables influenced passage use?

Regression analyses showed that the frequency of use by carnivores varied with structural, landscape, road-related features, and human disturbance variables (Table 3); 19 of 32 (59%) attributes were significant. Structural attributes (width, height, and openness) had high explanatory power; with the exception of mongoose, carnivores were less likely to use smaller passages. Landscape attributes also influenced crossing rate. All carnivores tended to use passages within oak woodland areas. High vegetation height at crossing entrances was important for fox and mongoose; distance to forest cover was important for all car- nivores. Mongoose crossings were correlated with stream direction, as well as the type and structure of riparian vegetation. Stone marten and mongoose passage use was negatively correlated with distance to the next nearest existing structure. Intensive agriculture and forest production, density of vegetation at the entrance, stream width, and distance to streams, as well as road related descriptors such as the number of passages in a 1,000 m buffer and year of highway construction, were not significantly related to crossing use. Five species-specific models were developed (Table 4). The proportion of variance (R2) explained by the models developed for each carnivore had values that ranged from 0.15 to 0.40, suggesting other unmeasured variables were responsible for crossing behavior. Some structural attributes, habitat features, road-related attributes, and human disturbance were

Table 4 Variables retained in the stepwise regression model for each carnivore species, coefficients (B), standard error, significances, P-value (t test) and deviance explained (D) Species Variables B Std Error P-value D

Foxa (Constant) -2.03 0.037 0.000 0.146 Oak woodland_500 m 0.01 0.004 0.010 Height vegetation 0.09 0.04 0.030 Stone martena (Constant) -3.04 0.501 0.000 0.311 Width (1) 0.09 0.430 0.040 Width (2) 1.2 0.380 0.002 Oak woodland_500 m 0.01 0.005 0.010 Badgera (Constant) -2.61 0.640 0.001 0.395 Oak woodland_500 m 0.01 0.003 0.010 Distance to roads 0.00 0.001 0.003 Cover distance -0.31 0.120 0.010 Type of riparian vegetation (1) 0.78 0.260 0.005 Type of riparian vegetation (2) 0.16 0.300 0.590 Geneta (Constant) -3.11 0.770 0.000 0.245 Distance to roads 0.01 0.001 0.010 Oak woodland_500 m 0.00 0.004 0.010 Human use (1) -0.69 0.330 0.040 Human use (2) -0.83 0.450 0.070 Mongoosea (Constant) -1.20 0.230 0.000 0.195 % Shrub cover_500 m 0.01 0.003 0.008 Stream direction (1) 0.26 0.320 0.410 Stream direction (2) 0.90 0.290 0.003 a The data used for these species were square root transformed 123 Biodivers Conserv (2008) 17:1685–1699 1695 important model components for carnivores, although their influence varied by species. Except for mongoose, the presence of oak woodland forest was the most important variable in the models. Distance to other roads was positively related to badger and genet crossing rates, whereas human use was negatively correlated with genet crossings. Passage width was a predictor of stone marten crossings. Vegetation height and % shrub cover helped to explain fox and mongoose crossing rates, respectively.

Discussion

The most common habitat-generalists (fox, stone marten, badger, genet and mongoose) used large and small passages regularly, but specific attributes influenced species differ- ently in determining the effectiveness of a passage. Our findings suggest that structure size is important especially for the arboreal stone marten which preferred larger passages. In general, crossing rates were two times higher in passages 1.5 m wide or larger. These results differ from those reported by Rodriguez et al. (1997) who did not find any pref- erence or avoidance by fox or wildcat; however, their passages ranged from 1.2 to 3.5 m while our passages ranged from 1 to 8 m, suggesting a threshold response. In general, larger passages with vegetation close to the passage entrances, favorable habitat in the surroundings, and low disturbance by humans were important key attributes. The presence of vegetation [0.5 m high at the passages entrances was associated with higher fox, stone marten, and mongoose crossing rates. When the proportion of oak woodland forest cover was [75%, we found higher values of crossing rates for all car- nivores. Both features contributed to masking passage structure and provide greater protection and security for animals. Human disturbances in the vicinity of passages limited their use (Clevenger and Waltho 2000; Ng et al. 2004; Ascensa˜o and Mira 2007). We observed a significant increase in fox, stone marten, badger, and genet crossing rates when distance to other roads was 500 m or greater. Where we found absence of human activity, the crossing rates doubled for badger and genet. When the distance to urban centers was greater than 2,000 m, badger crossing rates increased significantly. We documented that when stream flow passed through a passage, mongoose crossing rates were two times higher than when the stream paralleled the crossing. Streams with riparian vegetation provide travel corridors providing shelter and food, and anti-predator cover (Simberloff and Cox 1987; Hobbs 1992; Palomares and Delibes 1993; Virgo´s 2001), and influence the moving pattern of the mongoose, a largely diurnal species that avoids open areas (Palo- mares and Delibes 1991). Both culverts and underpasses play an important role in maintaining landscape con- nectivity for carnivores in general, but the existing structures appear to be selectively permeable. Species-specific habitat preferences contribute to the observed differences in permeability and may act cumulatively. Otters, polecats and wildcats are habitat special- ists. Otters are water-obligate (Beja 1992), and because we specifically chose the driest season to avoid water in the passages, their lower frequency of crossing does not reflect their high abundance in Portugal (Trindade et al. 1998; Cabral et al. 2005). Polecats, although not strictly water dependent, show a high association with aquatic environments (Lode 1994; Zabala et al. 2005) for the higher availability and diversity of prey (e.g., amphibians and crayfish). For wildcats, as forest-dependent and highly persecuted species (Fernandes 2004), the need for undisturbed old growth forest patches may not apply to the road-related environments, at least at the scale of analysis of this study. Weasels, on the contrary, do not show strict habitat preference (King 1975; Santos-Reis 1989; Blanco 123 1696 Biodivers Conserv (2008) 17:1685–1699

1998; Klemola et al. 1999) but are rodent-specialists and this largely influences their demography with populations showing strong fluctuations that in some cases may lead to almost local extinctions (Santos-Reis 1989). The 2 year drought preceding and during the study was the driest period during the last 75 years and influenced plant productivity and rodent numbers, and weasel populations were very low. Regardless, weasels avoid open areas and use linear corridors such as stone walls or vegetation strips (King 1975); structures not normally present in the passages. The variability found on passages use frequency was also related to differences in population densities. The occurrence of a particular species in the vicinity of a passage and fluctuations in its local abundance and activity patterns may explain the large amount of crossing rate variance (Yanes et al. 1995; Rodriguez et al. 1996; Clevenger et al. 2001; Hlava´cˇ and Ande˘l 2002). Rodriguez et al. (1997) found that for foxes and wildcats the variance explained by passage attributes was much lower (0.06–0.16) than that explained by patterns of the species abundance (0.23–0.53). Undoubtedly, shelter and food resources exert an important role. We found an increase in crossing rates in oak woodland where relative abundances were higher. Overall, our results indicate that culverts and underpasses facilitate the crossing of highways by carnivores. These structures appear to be important for landscape connec- tivity. To increase the likelihood of passage use by the carnivores guild we suggest some guidelines for highway managers: (1) promote the construction of large passages; (2) prioritize mitigative measures in areas with ecological significance for carnivores, e.g., forested areas of natural woods and where streams associated with riparian vegetation run through or close to the passages; (3) plant vegetation at passage entrances to guide animals towards the existing structure; (4) restrict human use of passages and (5) maintenance of natural vegetation structure inside the passage (soil, logs, rocks, woody debris) will help encourage use by more sensitive species (weasel and polecat) to artificial structures. An integrated approach using combined mitigation measures should reduce the impact of roads. Additional work on other methodologies that account for seasonal and yearly variations as well as effective monitoring to evaluate the effectiveness of these measures will be beneficial. Further information is needed to clarify the relationship between species density and crossing rates. Less common species are important components of the ecosystem and their inclusion will be important. Consideration of adequate gene flow and connected populations will enable decisions regarding the effectiveness of passages and the restoration and mainte- nance of basic ecological processes and functions.

Acknowledgments C. Grilo was supported by a Ph.D. grant (SFRH/BD/10600/2002) from the Fundac¸a˜o para a Cieˆncia e a Tecnologia. Additional funding was provided by Brisa Auto-Estradas de Portugal S.A. We also would like to thank Joana Roque de Pinho and Fernando Ascensa˜o for valuable comments on the earlier drafts of the manuscript and Eric Gese and Henrique Cabral for the final critical comments on the manuscript. We also thank one anonymous reviewer for their helpful comments on this manuscript.

References

Ascensa˜o F, Mira A (2007) Factors affecting culvert use by vertebrates along two stretches of road in Southern Portugal. Ecol Res 22:57–66 Barnum SA (2003) Identifying the best locations along highways to provide safe crossing opportunities for wildlife. Final report, Colorado Department of Transportation Research Branch Beja P (1992) Effects of freshwater availability on the summer distribution of otters Lutra lutra on the Southwest Coast of Portugal. Ecography 15:273–278 123 Biodivers Conserv (2008) 17:1685–1699 1697

Blanco JC (1988) Estudio ecolo´gico del zorro (Vulpes vulpes L. 1758) en la Sierra de Gaudarrama. Ph.D. Thesis, University of Oviedo Blanco JC (1998) Mamı´feros de Espan˜a. Insectivoros, Quiro´pteros, Primates, Carnı´voros de la Peninsula Iberica, Baleares y Canarias. Geoplaneta, Barcelona Cabral MJ, Almeida J, Almeida PR, Dellinger T, Ferrand de Almeida N, Oliveira ME, Palmeirim JM, Queiroz AI, Rogado L, Santos-Reis M (eds) (2005) Livro Vermelho dos Vertebrados de Portugal. Instituto da Conservac¸a˜o da Natureza, Lisboa Cain AT, Tuovila VR, Hewitt DG, Tewes ME (2003) Effects of a highway and mitigation projects on bobcats in Southern Texas. Biol Conserv 114:189–197 Chaterjee S, Price B (1991) Regression analysis by examples. Wiley, New York Chruszcz B, Clevenger A, Gunson K, Gibeau M (2003) Relationships among grizzly bears, highways and habitat in the Banff-Bow Valley, Alberta, Canada. Can J Zool 81:1378–1391 Clevenger AP, Waltho N (2000) Factors influencing the effectiveness of wildlife underpasses in Banff National Park, Alberta, Canada. Conserv Biol 14(1):47–56 Clevenger AP, Waltho N (2005) Performance indices to identify attributes of highway crossing structures facilitating movement of large mammals. Biol Conserv 121:453–464 Clevenger AP, Chruszcz B, Gunnison K (2001) Drainage culverts as habitat linkages and factors affecting passage by mammals. J Appl Ecol 38:1340–1349 Dodd K, Barichivich W, Smith L (2004) Effectiveness of a barrier wall and culverts in reducing wildlife mortality on a heavily travelled highway in Florida. Biol Conserv 118:619–631 Epps CW, Palsbøll P, Wehausen JD, Roderick G, Ramey R II, McCullough DR (2005) Highways block gene flow and cause a rapid decline in genetic diversity of desert bighorn sheep. Ecol Lett 8:1029–1038 Faraway JJ (2004) Linear models with R. Chapman & Hall/CRC, USA Fernandes ML (2004) Gato-bravo no nordeste transmontano. Patrimo´nio Natural Transmontano. Roger Lopes, Mirandela Ferreras P, Aldama JJ, Beltra´n JF, Delibes M (1992) Rates and causes of mortality in a fragmented population of Iberian lynx Felis pardina Temminck 1824. Biol Conserv 61:197–202 Forman RTT, Alexander LE (1998) Roads and their major ecological effects. Annu Rev Ecol Syst 29:207– 231 Forman RTT, Sperling D, Bissonette J, Clevenger A, Cutshall C, Dale V, Fahrig L, France R, Goldman C, Heanue K, Jones J, Swanson F, Turrentine T, Winter T (2003) Road ecology: science and solutions. Island Press, Washington Foster ML, Humphrey SR (1995) Use of highway underpasses by Florida panthers and other wildlife. Wildl Soc Bull 23:95–100 Gerlach G, Musolf K (2000) Fragmentation of landscape as a cause for genetic subdivision in bank voles. Conserv Biol 14(4):1066–1074 Gloyne CC, Clevenger AP (2001) Cougar Puma concolor use of wildlife crossing structures on the Trans- Canada highway in Banff National Park, Alberta. Wildl Biol 7:117–124 Guisan A, Zimmermann N (2000) Predictive habitat distribution models in ecology. Ecol Modell 135:147– 186 Haas CD (2000) Distribution, relative abundance, and roadway underpass responses of carnivores throughout the Puente-Chino Hills. Master Thesis, Faculty of California Polytechnic University Hlava´cˇ V, Ande˘l P (2002) On the permeability of the roads for wildlife. A handbook. Agency for Nature Conservation and Landscape Protection of Czech Republic, Praha Hobbs RJ (1992) The role of corridors in conservation: solution or bandwagon? Trends Ecol Evol 7:389–392 Hunt A, Dickens HJ, Whelan RJ (1987) Movements of mammal through tunnels under railway lines. Aust Zool 24:89–93 IgeoE (1999) Carta militar itinera´ria de Portugal 1/500 000. Instituto Geogra´fico do Exe´rcito, Lisboa INE (2002) Censos 2001—Resultados definitivos—Portugal. Instituto Nacional de Estatı´stica, Lisboa IUCN (2006) 2006 IUCN red list of threatened species. http://www.iucnredlist.org Iuell B, Bekker GJ, Cuperus R, Dufek J, Fry G, Hicks C, HlavA´ cˇ V, Keller VB, Rossel C, Sangwine T, Torslov N, le Maire Wandall B (eds) (2003) Wildlife and traffic: an European handbook for identifying conflicts and designing solutions. KNNV publishers, UK Keller V, Pfister HR (1997) Wildlife passages as a means of mitigating effects of habitat fragmentation by roads and railway lines. In: Canters K (ed) Habitat fragmentation and infrastructure, Maastricht, The Hague, Ministry of Transport, Public Works and Water Management, Delft, pp 17–21 King CM (1975) The home range of the weasel (Mustela nivalis) in an English woodland. J Anim Ecol 44(2):639–668 Klemola T, Korpimaki E, Norrdahl K, Tanhuanpaa M, Koivula M (1999) Mobility and habitat utilization of small mustelids in relation to cyclically fluctuating prey abundances. Ann Zool Fenn 36:75–82

123 1698 Biodivers Conserv (2008) 17:1685–1699

Kramer-Schadt S, Revilla E, Wiegand T, Breitenmoser U (2004) Fragmented landscapes, road mortality and patch connectivity: modelling influences on the dispersal of Eurasian lynx. J Appl Ecol 41:711–723 Lawrence MJ, Brown RW (1973) Mammals of Britain their tracks, trails and signs. Blandford Press, London Lode T (1994) Environmental factors influencing habitat exploitation by the polecat Mustela putorius in western France. J Zool Lond 234:75–88 Lope´z-Martin JM, Lampreave G, Ruiz-Olmo J (1997) Seleccio´n de habitat de la gardun˜a (Martes foina): importancia de las islas de vegetacio´n en ecosistemas mediterra´neos alterados. In: Abstracts of the III Jornadas SECEM—I Jornadas Ibe´ricas sobre la Nutria. Castello´ de Empu´ries, Girona, 5–7 December 1997 Mata C, Herva´s I, Herranz J, Sua´rez F, Malo JE (2005) Complementary use by vertebrates of crossing structures along a fenced Spanish motorway. Biol Conserv 124:397–405 Myers N, Mittermeier RA, Mittermeier CG, Fonseca GAB, Kent J (2000) Biodiversity hotspots for con- servation priorities. Nature 403:853–858 Ng SJ, Dale JW, Sauvajot RM, Riley SPD, Valone T (2004) Use of highway undercrossings by wildlife in Southern California. Biol Conserv 115:499–507 Noss RF, Quigley HB, Hornocker MG, Merril T, Paquet P (1996) Conservation biology and carnivore conservation in the Rocky Mountains. Conserv Biol 10:949–963 Palomares F, Delibes M (1991) Assessing three methods to estimate daily activity patterns in radio-trakked mongooses. J Wildl Manage 55(4):698–700 Palomares F, Delibes M (1993) Key habitats for Egyptian mongooses in Donˇana National Park, south- western Spain. J Appl Ecol 30:752–758 Palomares F, Delibes M (1994) Spatial-temporal ecology and behaviour of European genets in southwestern Spain. J Mammal 75(3):714–724 Percy MP (2003) Spatio-temporal movement and road crossing patterns of wolves, black bears and grizzly bears in the bow river valley of Banff National Park. M.Sc. Thesis, University of Alberta Pin˜ero JR (2002) Mamı´feros carnı´voros ibe´ricos. Lynx edicions, Barcelona Pinto B, Fernandes M (2001) Abordagem preliminar a` distribuic¸a˜o do gato-bravo em Portugal. DHE/ICN, Lisboa Rodriguez A, Crema G, Delibes M (1996) Use of non-wildlife passages across a high speed railway by terrestrial vertebrates. J Appl Ecol 33:1527–1540 Rodriguez A, Crema G, Delibes M (1997) Factors affecting crossing of red foxes and wildcats through non- wildlife passages across a high-speed railway. Ecography 20:287–294 Rondinini C, Ercoli V, Boitani L (2006) Habitat use and preference by polecats (Mustela putorius L.) in a Mediterranean agricultural landscape. J Zool 269:213–219 Rosalino LM, Macdonald DW, Santos-Reis M (2004) Spatial structure and land-cover use in a low-density Mediterranean population of Eurasian badgers. Can J Zool 82(9):1493–1502 Rosell C, Parpal J, Campeny R, Jove´ S, Pasquina A, Velasco JM (1997) Mitigation of barrier effect of linear infrastructures on wildlife. In: Canters K (ed) Proceedings of the international conference on habitat fragmentation, infrastructure and the role of ecological engineering, Maastricht and the Hague Ruediger B (1998) Rare carnivores and highways—moving into the 21st century. In: Evink GL, Garret P, Zeigler D, Berry J (eds) Proceedings of the international conference on wildlife ecology and trans- portation, Tallahasse, pp 10–16 Santos-Reis M (1989) As doninhas ibe´ricas (Carnivora: Mustela) um estudo taxono´mico e ecolo´gico. Ph.D. Thesis, University of Lisbon Santos-Reis M, Petrucci-Fonseca F (1999) Carnı´voros. In: ICN/CBA (eds) Mamı´feros terrestres de Portugal Continental, Madeira e Ac¸ores. Instituto de Conservac¸a˜o da Natureza/Centro de Biologia Ambiental, Lisboa Santos-Reis M, Santos MJ, Lourenc¸o S, Marques T, Pereira I, Pinto B (2004) Relationships between stone martens, genets and cork oak woodlands in Portugal. In: Harrison DJ, Fuller AK, Proulx G (eds) Marten and fishers in human altered landscapes: an international perspective. Kluwer Academic Publishers, Massachusetts Simberloff D, Cox J (1987) Consequences and costs of conservation corridors. Conserv Biol 1:63–71 SPSS (2003) SPSS statistical software—version 12.0 for windows. SPSS Inc., Chicago Sunquist ME, Sunquist FC (2001) Changing landscapes: consequences for carnivores. In: Gittleman JL, Funk SM, MacDonald DW, Wayne RK (eds) Carnivore conservation. Conservation biology 5. Cambridge University Press, pp 399–418 Thiel RP (1985) Relationship between road densities and wolf habitat suitability in Wisconsin. Am Midl Nat 113(2):404–407 Trindade A, Farinha N, Floreˆncio E (1998) A Distribuic¸a˜o da Lontra Lutra lutra em Portugal—situac¸a˜oem 1995. Estudos de Biologia e Conservac¸a˜o da Natureza, 28. ICN, Lisboa

123 Biodivers Conserv (2008) 17:1685–1699 1699

Trombulak SC, Frissel CA (2000) Review of ecological effects of roads on terrestrial and aquatic com- munities. Conserv Biol 14(1):18–30 Van der Zee FF, Wiertz J, Ter Braak CJF, Apeldoorn RC (1992) Landscape change as a possible cause of the badger Meles meles L. decline in the Netherlands. Biol Conserv 61:17–22 Virgo´s E (2001) Relative value of riparian woodlands in landscapes with different forest cover for medium- sized Iberian carnivores. Biodivers Conserv 10:1039–1049 Whittington J, St Clair CC, Mercer G (2004) Path tortuosity and the permeability of roads and trails to wolf movement. Ecol Soc 9(1):4. http://www.ecologyandsociety.org/vol9/iss1/art4/ Whittington J, St Clair CC, Mercer G (2005) Spatial responses of wolves to roads and trails in mountain valleys. Ecol Appl 15(2):543–553 Yanes M, Velasco J, Suare´z F (1995) Permeability of roads and railways to vertebrates: the importance of culverts. Biol Conserv 71:217–222 Zabala J, Zuberogoitia ÆI, Martı´nez-Climent ÆJA (2005) Site and landscape features ruling the habitat use and occupancy of the polecat (Mustela putorius) in a low density area: a multiscale approach. Eur J Wildl Res 51:157–162 Zuur A, Ieno E, Graham S (2007) Analysing ecological data. Springer, UK

123

Journal of Applied Blackwell Publishing Ltd Ecology 2007 Chronic industrial noise affects pairing success and 44, 176–184 age structure of ovenbirds Seiurus aurocapilla

LUCAS HABIB, ERIN M. BAYNE and STAN BOUTIN Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2E9

Summary 1. Anthropogenic noise is rapidly increasing in wilderness areas as a result of industrial expansion. While many road studies have attempted to assess the effects of industrial noise on birds, conflicting factors such as edge effects often inhibit the ability to draw strong conclusions. 2. We assessed pairing success and age distribution of male ovenbirds Seiurus aurocapilla in the boreal forest of Alberta, Canada, in areas around noise-generating compressor stations compared with areas around habitat-disturbed, but noiseless, wellpads. This allowed us to control for edge effects, human visitation and other factors that are not controlled for in studies of noise generated by roads. Generalized estimating equations (GEE) were used to assess the impacts of noise on ovenbird pairing success, age structure and body morphology. 3. We found a significant reduction in ovenbird pairing success at compressor sites (77%) compared with noiseless wellpads (92%). These differences were apparent regardless of territory quality or individual male quality. Significantly more inexperienced birds breeding for the first time were found near noise-generating compressor stations than noiseless wellpads (48% vs. 30%). 4. While there are multiple proximate explanations for these results, the ultimate cause of the changes seems to be noise pollution. We hypothesize that noise interferes with a male’s song, such that females may not hear the male’s song at greater distances and/or females may perceive males to be of lower quality because of distortion of song characteristics. 5. Synthesis and applications. This work demonstrates that chronic background noise could be an important factor affecting bird populations. It can impact upon pairing success and age structure of passerines; in boreal Alberta this could pose a problem for certain species as energy development expands rapidly. Key-words:age structure, compressor stations, industrial impacts, noise, ovenbird, pairing success Journal of Applied Ecology (2007) 44, 176–184 doi: 10.1111/j.1365-2664.2006.01234.x

of young fledged are highest (Holmes, Marra & Sherry Introduction 1996). Physical changes to habitat caused by human Many factors contribute to the ability of male birds to activity can reduce the quality of habitat for many birds attract a female during the breeding season. Individual by decreasing nest success, reducing food supply and ‘quality’ is usually measured by age, size or body condi- decreasing survival. These effects may interact to create tion; these attributes and how they influence song quality a situation whereby lower-quality males settle in disturbed are often identified as key determinants of the attrac- habitats and as such are less likely to attract a mate tiveness of males to females (Breitwisch 1989; Holmes, because of female avoidance of disturbed habitats Marra & Sherry 1996). High-quality individuals are and/or the ‘lower quality’ of males that settle there often found in habitats where nesting success and number (Villard, Martin & Drummond 1993; Reijnen & Foppen © 2006 The Authors. 1994; Van Horn, Gentry & Faaborg 1995; Lambert & Journal compilation Correspondence: Erin Bayne, Department of Biological Hannon 2000; Bayne & Hobson 2001). While most © 2006 British Sciences, University of Alberta, Edmonton, Alberta, Canada research on how avian pairing success is affected by Ecological Society T6G 2E9 (fax +780 492 9234; e-mail [email protected]). anthropogenic impacts deals with physical factors such

177 as edge and landscape condition, it is possible that non- tion in amplitude (Bolstad Engineering Associates Chronic noise and physical anthropogenic impacts may also diminish 1978; Brenowitz 1982). ovenbird pairing the ability of male birds to attract females. As birds The range of noise intensity produced by compressor success communicate primarily by sound, loud ambient noise stations is similar to those in studies that have found caused by human activities could inhibit communica- negative effects on birds as a result of purported ‘road tion between conspecifics, potentially reducing pairing noise’. At compressor stations, however, many of the success. Birds in forests typically have songs characterized confounding variables associated with roads are absent by low frequencies (c. 1·5–4·0 kHz). These frequencies or can be more effectively controlled for. Vehicle traffic seem to provide optimal long-distance song transmission to compressor stations in forests is typically minimal, range in complex forest structures (Brenowitz 1982; having only a few vehicles visiting per day. Compressor Slabbekoorn, Ellers & Smith 2002). As a result, much stations in forest environments are associated with bird song lies in the same part of the frequency spectrum a significant amount of edge habitat, as are roads. This occupied by many types of mechanical noise (Binek correlation between noise and edge makes it difficult to 1996; ATCO Noise Management 2003). Because of this separate the impacts on birds of noise relative to edge. overlap, industrial noise may interfere with bird Simply comparing bird responses at distances away communication occurring via song. If the ability to from compressor stations confounds noise effects with communicate with females is influenced by anthropogenic edge effects, an issue that has not been well addressed noise, then we might expect males in high noise areas to by road noise studies. However, associated with pipelines be less likely to attract a mate. are wellpads. Like compressor stations, wellpads are The limited research on the effects of chronic anthro- clearings of 1- to 2-ha of forest habitat that are linked via pogenic noise and birds has indirectly examined the narrow linear features such as pipelines and single-lane effects of traffic noise on bird populations near high- road access. However, wellpads, unlike compressor ways. Many species of bird have been found to exhibit stations, produce no chronic noise and thus provide an reduced breeding densities in areas around roads, with effective control for separating the effects of edge rela- noise assumed to play a larger role in that reduction than tive to noise. either visibility of cars or traffic mortality (Reijnen et al. The objective of this study was to test whether noise 1995; Kuitunen, Rossi & Stenroos 1998). A few studies decreases habitat quality in the breeding range for the have also shown that birds have reduced breeding neotropical migrant ovenbird Seiurus aurocapilla (Linnaeus success (i.e. a lower probability of mating or successfully 1766) by examining pairing success close to compres- rearing young) near roads (Reijnen & Foppen 1994; sor stations relative to wellpads. By capturing birds and Burke & Nol 2000; Kuitunen et al. 2003). However, it obtaining information on individual attributes we were has never been demonstrated conclusively that the noise also able to examine some of the proximate mechanisms generated by roads is the factor that results in reduced that influence the ability of a male bird to attract a female breeding activity in birds; the myriad of other potential in noisy vs. quiet environments. The ovenbird was selected impacts of roads (e.g. edge effects and traffic-caused as the study species because of a male-dominated sex bias mortality) have not been effectively controlled for. in most populations, its apparent sensitivity to habitat Boreal Alberta is one of North America’s most intense disturbance caused by anthropogenic activity, the fact oil and natural gas production areas. Throughout the that it is a ground-dweller, making it relatively easy to region, a network of pipeline systems connects gathering capture and track, and its high density in the western sites to processing facilities and ultimately transport boreal forest (Villard, Martin & Drummond 1993; Van terminals. Along these pipeline systems lie compressor Horn, Gentry & Faaborg 1995; Lambert & Hannon 2000; stations, which function to boost pressure in the pipelines Bayne & Hobson 2001). In addition, the ovenbird has and help maintain the flow of natural gas and oil from an inflexible song relative to other species (Lein 1981), wells. A typical compressor station consists of one to suggesting little ability of males to adapt their song to three motors cooled by an equal number of large fan be heard above anthropogenic noise. Ovenbird song units; the machinery is housed in an aluminium shed in frequency (with a minimum frequency of c. 2 kHz) also a 1- to 2-ha cleared area in the forest. These motors and overlaps with that of compressor station noise. fans run continuously other than for infrequent maintenance, and typically produce chronic noise levels Methods of 75–90 dB(A) near the source (Bolstad Engineering Associates 1978; ATCO Noise Management 2003)   but can reach 105 dB(A) (MacDonald, Ewanek & Tilley 1996). Under ‘free field’ conditions, noise is reduced by Our research was conducted in two regions of northern © 2006 The Authors. 6 dB(A) for every doubling of distance from the source Alberta, Canada, between 54° and 59° latitude and 110° Journal compilation (ATCO Noise Management 2003); this loss is accelerated and 119° longitude. The region has significant energy © 2006 British in forested systems, dependent on the type of forest sector development, with roads, industrial sites and Ecological Society, Journal of Applied and understorey structure (Huisman & Attenborough seismic lines being the prominent form of human Ecology, 44, 1991). However, low-frequency mechanical noise can disturbance. The study area contains c. 900 compressor 176–184 be transmitted far from the source despite this reduc- stations in an approximately 10-million ha area.

178 > 3 km away from other sites to ensure that no noise L. Habib, contamination from one site would reach another. E. M. Bayne & Control sites were occasionally < 3 km away from each S. Boutin other for logistical reasons; however, as no noise was emitted from these sites noise contamination was not a concern. While forestry is a major industry in the study areas, no study sites were located within 1 km of existing clearcuts or within 2 km of ongoing forestry operations at the time of the study.

Fig. 1. Study design for ovenbird capture in northern Alberta, Canada, in 2004 and 2005. One ovenbird was captured on   each side of an energy industry-created clearing (territories Male ovenbirds were captured in the spring of 2004 and indicated by grey polygons). Compressor sites had a noise- generating compressor station (house icon) at the centre of 2005. We captured birds in approximately equal numbers the clearing, while control sites had a noiseless wellhead at compressor sites and control sites (hereafter compressor (diamond icon) at the centre. and control birds, respectively). All captures were con- ducted between 24 May and 22 June, with the majority of birds captured before 9 June. Birds captured after Forests in the region consist of boreal mixed wood and that date were usually replacements that had assumed peatland vegetation (Strong & Leggat 1992). Lowland the territory of birds that had been ringed but who vegetation is dominated by black spruce Picea mariana had vacated the area post-capture. These ‘missing’ birds (Mill.), bogs and fens, while upland areas are dominated were presumed not to have permanently settled in the by trembling aspen Populus tremuloides (Michx.) and territory and were excluded from all analyses. Capture white spruce Picea glauca (Moench). attempts were focused on the early morning (04:00– 10:00) but during the peak capture period birds were   caught at all times of day. To locate birds on which to evaluate pairing status, Birds were observed at two types of sites, compressor we walked the perimeter of the cleared pad listening stations and wellpads (hereafter compressor sites and for male ovenbirds singing near the forest’s edge. If an control sites). All sites were rectangular clearings in ovenbird was heard, and estimated to be < 200 m from the forest that had been created for energy industry the clearing edge, we targeted it for capture. If during a operations. Clearings measured c. 200–400 m side−1. walk of the perimeter no ovenbirds were heard, we would Compressor sites had a compressor station with one to repeat the walk while playing recordings of male oven- three fan units at the centre of the cleared pad. Control bird songs from speakers. It is possible that locating birds sites were pads of a similar size. Most of these had by playback resulted in birds moving closer to the edge wellheads at the centre, although some had meter than they would have been found otherwise; however, stations or other small facilities that produced no noise. it is reasonable to assume that ovenbirds responding to While some wells and meter stations occasionally the playback of a rival male’s song would remain within produced a very quiet and periodic hissing sound, the the boundary of their territories. Therefore, all birds caught only chronic noise at control sites was wind-generated. were likely to be the closest inhabitants to the edge. Both types of site had similar physical disturbances such We used mist-nets together with male ovenbird song as pipelines and road access (Fig. 1). playback to draw birds into the net. Once captured, birds Site selection was carried out using ArcGIS 9·0 (ESRI were sexed based on the presence of a cloacal protuber- Inc., Redlands, CA) using Alberta Vegetation Inventory ance (Pyle et al. 1987); female birds were released. Each (AVI) data, energy facility data and road data obtained male bird received a Canadian Wildlife Service (Ottawa, from Alberta Pacific Forest Industries (Boyle, Canada), Canada) aluminium ring and three coloured-plastic leg Tolko Forest Industries (High Level, Canada) and rings to form a unique ring combination. We measured Daishowa-Marubeni International Ltd (Peace River, unflattened right wing chord (mm), tail length (mm), Canada). Our research was conducted entirely in mature, right tarsal length (mm) and mass (g) of each bird (Pyle 60–90-year-old aspen forest (the primary habitat of et al. 1987). We derived a condition index by dividing mass breeding ovenbirds) to reduce the effects of vegetation by wing chord (Burke & Nol 2001). We also plucked the structure as a factor influencing habitat quality for birds. third right rectrix in order to age the bird. Following the All sites selected in the GIS were ground-truthed to ensure capture procedure, the bird was released; pairing obser- © 2006 The Authors. that the energy facility was appropriate and vegetation type vations did not commence until at least the next day. Journal compilation was accurate. Within the pool of sites having appropriate © 2006 British forest cover, site selection was constrained by the follow- Ecological Society,   Journal of Applied ing criteria: all selected sites were truck-accessible, and Ecology, 44, sites were close enough together to make travel between Each ringed ovenbird was identified based on its colour 176–184 sites practical on a daily basis. Compressor sites were bands, and followed to determine whether or not it

179 was able to pair successfully with a female. Our pairing    Chronic noise and success protocol followed those of Lambert & Hannon ovenbird pairing (2000) and Bayne & Hobson (2001). Birds were fol- We conducted a vegetation survey in the estimated success lowed for up to 90 min over the breeding season or territory of each ringed male ovenbird via four 1-m wide, until a sign of pairing was observed. Signs of pairing 25-m long transects orientated along a random bearing. included observing: (i) the male in the vicinity of a Transects were spaced 10 m apart and were based female; (ii) the male carrying food; (iii) the male or around the centre of the territory, as defined by the female with nesting material; (iv) the male or female with cumulative observations of that bird’s behaviour. We young; or (v) an active nest within the male’s territory measured diameter at breast height (d.b.h.) of all trees (Bayne & Hobson 2001). As ovenbirds are mono- that intercepted the transect. We used a ‘bird-centric’ morphic, a non-singing individual tolerated by a male definition of tree. Any vegetation > 5 m in height was within a 5-m radius or emitting a series of ‘tsip’ notes classified as a tree, and all stems emerging from the was considered its female mate, as females often make same individual plant were measured separately. While those vocalizations in response to their mate’s song walking transects, we recorded the number of downed (Lein 1980). woody material (DWM) pieces > 8 cm in diameter that Birds were tracked for a maximum of 30 min−1 day, the transect intercepted. with track time being accumulated when the bird was in Along each transect, five 0·25-m2 plots were placed sight or in continuous song within 30 m of the observer. at 5-m intervals. In each plot, we measured shrub Tracking days were spread out over the breeding season; species, density (number of stems of each species) and all efforts were made to have a minimum of one 30-min height category (0·5–2 m or > 2 m). We also measured tracking period during the prime courting and nest- the leaf litter depth at the centre of each plot with a metal building period (c. 27 May−9 June). For birds who were metre stick, and estimated percentage cover of forbs, not determined to be paired before c. 9 June, a second moss and grass in each plot based on five categories (0, tracking period was attempted during the female’s none present; 1, 1–25% cover; 2, 26–50% cover; 3, 51–75% nesting period when the male is feeding the young cover; 4, 76–100% cover). For analysis, all vegetation (until c. 19 June), and a third after the chicks had left measurements were averaged for each ovenbird’s terri- the nest (beginning c. 20 June), ensuring that birds tory. Shrub density was transformed into two variables, that may have acquired mates late in the season had density of short shrubs and density of tall shrubs. Tree adequate track time. data were summarized into density of hardwood and softwood trees.     By measuring the tip angle of the third right rectrix, it is possible to classify an ovenbird as either a second- To evaluate whether ovenbirds at compressor sites year (SY) bird or an after-second-year (ASY) bird had lower pairing success than at control sites, we used (Donovan & Stanley 1995). SY birds are inexperienced a generalized estimating equation (GEE) with a breeders breeding for the first time (hereafter young binomial error structure and a logit link within STATA birds), while ASY birds had potentially bred the year 9·1 (STATA Corp., College Station, TX). GEE are a before (hereafter old birds). Ageing birds in this manner modification of generalized linear models that account is possible because ovenbirds retain their juvenile tail for the nested structure in an experimental design, feathers through their first winter season and do not whereby each individual occurs at a site with the site moult them until after their first breeding season (Pyle being the primary sampling unit (Hardin & Hilbe 2003). et al. 1987). These feathers are often tapered, compared Within the GEE framework, the pairing status of the with the paddle shape of post-moult rectrices present in multiple birds sampled at each site is assumed to be ASY individuals (Pyle et al. 1987). Feathers were scanned correlated to an extent that is estimated by the model. into a computer and images expanded by a constant By estimating the exchangeable correlation in pairing size. Images were printed in greyscale and the angle of status of individuals within the same site, estimates of the feather tip calculated using transparent grid paper standard errors are robust to any lack of independence. and a small ruler. Birds having a rectrix tip angle of < A priori we predicted that noise would reduce pairing 84° were classified as SY; those having tip angles > 84° success, so our tests for noise effects were all one-tailed. were classified as ASY (Bayne & Hobson 2001). With This study was designed to minimize any variation in this criterion we were able to age all individuals, habitat quality as a result of vegetation structure. How- albeit with some uncertainty. Donovan & Stanley (1995) ever, variation in habitat quality for attributes that were © 2006 The Authors. demonstrated that birds with tip angles > 90° were ASY not effectively described by AVI data could have been a Journal compilation and < 78° were SY with 99% certainty. During analysis, confounding factor in our design. To control for any © 2006 British we used both criteria for ageing. Feathers were classi- vegetation effects, we used principal components analysis Ecological Society, Journal of Applied fied blindly by bird identification number without (PCA) in STATA 9·1 to summarize the variation in Ecology, 44, knowledge of which treatment group that individual vegetation structure for all territories. All vegetation 176–184 belonged to. variables were standardized to zero mean and unit

180 Table 1. Summary of male ovenbirds captured and ringed per treatment per year, and the number of birds on which pairing L. Habib, observations were made. Compressor sites (n = 20) had a noise-generating compressor station at the centre of a forest clearing, E. M. Bayne & while control sites (n = 21) had a noiseless wellhead at the centre. The study was conducted in northern Alberta, Canada, in 2004 and 2005 S. Boutin 2004 2005 Total number Captured Missing Captured Missing of birds used

Control 47 8 26 7 58 Compressor 44 7 31 13 55 Total 91 15 57 20 113

variance prior to PCA. PCA of DWM, forb cover, moss Table 2. Contingency table illustrating ovenbird pairing cover, grass cover, litter depth, high shrub density, low success and age distribution between treatments. SY birds are shrub density, hardwood tree density and softwood first-year breeders, while ASY birds are in at least their second breeding season. Compressor sites had a noise-generating tree density resulted in two principal component axes compressor station at the centre of a forest clearing, while that together explained 40% of the variation in the control sites had a noiseless wellhead at the centre. The study original data set. The first factor represented territories was conducted in northern Alberta, Canada, in 2004 and 2005 with large trees, higher shrub density and more DWM (positive loading on component 1, hereafter territory Compressor Control Treatment structure). The second factor represented territories Status Paired Unpaired Paired Unpaired Total that varied in the proportion of deciduous to conifer trees (positive loading for deciduous tree density, hereafter Age territory composition). Territory structure and territory SY 20 6 17 0 43 composition were included in the GEE model to ensure ASY 23 4 34 4 65 Unaged 1 0 1 0 2 that any confounding effects of vegetation as a measure Total 44 10 52 4 110 of territory quality were controlled for when assessing the effects of noise. As vegetation factors were simply nuisance variables with no a priori predictions regarding direction, we report their statistical significance as two- Results tailed tests. Male quality as measured by age and body morphology   has been shown to be an important determinant of pairing success in other studies (Saether 1990; Bayne & A total of 148 birds was captured over the 2004 and 2005 Hobson 2001). If there is no effect of noise on oven- breeding seasons at 20 compressor sites and 19 control birds, then a priori we predicted that there should be no sites. Data were pooled across years for all analyses. differences in age structure or body morphology of Summary data are presented in Table 1. All birds that birds between compressor and control sites. How- had gone missing and were not relocated (n = 35) were ever, if noise does affect pairing success it may do so by excluded from all analyses. A contingency table analysis influencing the quality of the individuals that settle with a chi-square test demonstrated no significant at compressor vs. control sites. A GEE was used to test difference in the number of birds that went missing whether the frequency of occurrence of old vs. young birds between the two treatments (χ2 = 0·77, d.f. = 1, P = 0·38). differed between these sites. We tested this hypothesis There was also no difference in the number of birds that using both the 84° tip angle criterion and the more went missing between age categories (χ2 = 1·76, d.f. = 1, stringent 78°/90° rule. We also tested whether bigger P = 0·18). We were unable to amass 90 min of pairing birds or those in better condition were less likely to observations, or observe a conclusive pairing sign, on settle at compressor vs. control sites. GEE were used to three birds (two control birds and one compressor bird). analyse these data with respect to noise treatment. In These birds were also excluded from analyses. this analysis we assumed a Gaussian error structure and For the remaining 110 birds we identified 92% of identity link. Vegetation structure within territories control birds as paired compared with 77% of com- was controlled for in all analyses. A priori we predicted pressor birds (Table 2). Controlling for territory structure that larger and older birds in better condition would be and composition, we found that pairing success was more likely to settle at controls than at compressors so significantly lower for compressor birds than control © 2006 The Authors. these statistical tests are one-tailed. birds (OR = 0·31, z = −2·11, P = 0·02). Territory struc- Journal compilation All results are reported as odds-ratios (OR) or slope ture was also a significant predictor of pairing suc- © 2006 British coefficients (α). Statistical tests are reported as z-scores cess (OR = 1·49, z = 2·2, P = 0·03), while territory Ecological Society, − Journal of Applied from GEE unless otherwise stated, with probability composition was not (OR = 0·87, z = 0·63, P = 0·53). Ecology, 44, values derived as discussed above. All tests were con- The within-site correlation estimated by the GEE was 176–184 sidered significant at P = 0·05. r = −0·12.

181   males having high-quality territories. Our results suggest Chronic noise and that females are selecting high-quality (i.e. quiet) ovenbird pairing Again, all birds that were categorized as missing were territories rather than older or bigger males. Admit- success excluded from analyses. Among the remaining birds tedly, however, the small sample size of unpaired males (n = 111), 70% of birds at control sites (n = 57) were makes age and body morphology effects difficult to classified as ASY compared with 52% at compressor detect. Noise level from industrial activity seems to be sites (n = 54), using the 84° rule. If we discounted one habitat factor that females use when deciding all birds whose tip angles were between 78° and 90° how to choose a mate, as we found a 15% difference (n = 31), 79% of birds at control sites were classified as in pairing success between ovenbirds at sites having ASY (n = 33) compared with 53% at compressor sites industrial background noise and those without. (n = 20), an even greater difference. Because of this, we A probable explanation for the reduction in likelihood chose the more conservative 84° rule for further analyses. of male–female mating encounters is that intersex For birds whose pairing status was determined (n = 108), ovenbird communication is being reduced by chronic there was a significant difference in age structure between background noise. If noise interferes with a male’s treatments (OR = 0·50, z = −1·68, d.f. = 1, P = 0·046). song it may not be audible to females over as great a Age was not a significant determinant of pairing distance, thereby reducing the pool of females who may success, however (OR = 1·26, d.f. = 1, z = 0·41, P = 0·69). potentially respond to his song. Alternatively, females The discrepancy in sample size was because of two may perceive males as being of lower quality than they birds from which tail feathers were not collected so actually are because of distortion of song characteristics. ageing was not possible. The within-site correlation Ovenbirds have a high-amplitude song relative to most for age structure was very low at r = 0·001. wood warblers in North America yet they still exhibit a reduction in pairing success, suggesting that other   species with quieter songs may be similarly affected. Alternatively, other forms of communication may be Estimates of wing, tail and mass were available for 107 impacted by industrial noise. Predator detection individuals for whom pairing success was determined. may be inhibited, resulting in increased mortality of There was no relationship between bird age and tail length females. This risk may be particularly high for female (α = 0·94, z = 1·44, d.f. = 1, P = 0·07), mass (α = 0·12, ovenbirds as they nest on the ground and are the sole z = 0·55, d.f. = 1, P = 0·29) or body condition (α = incubators. Male and female ovenbirds have a con- 0·01, z = 0·95, d.f. = 1, P = 0·17), although wing chord was siderable repertoire of quiet call notes (Lein 1980) that significantly longer in older birds (α = 1·09, z = 2·48, they use when directly communicating with their mate d.f. = 1, P = 0·007). After controlling for age, there was (e.g. signalling when the female leaves the nest) that also no significant difference in any of the four body variables may be more difficult to hear in noisy environments. between compressor and control sites (all P > 0·05). While nesting success was not addressed in this study, begging calls from nestlings may also be drowned   .   out, leading to increased chick mortality. Finally, Villard, Martin & Drummond (1993) proposed that female A model containing habitat structure, habitat com- passerines are more likely to settle in sites having a high position, noise status, individual age and individual male density. In a related experiment, detectability- morphology was created to determine the relative adjusted point-count densities of singing male oven- importance of individual quality vs. habitat quality birds were greater at control sites than at compressor as factors influencing pairing success. In this model, sites (Habib 2006). Lower densities of ovenbird males the only two variables that were statistically significant at compressor sites may reduce the probability that were noise status (OR = 0·30, z = −2·1, d.f. = 1, P = 0·02) females will settle there. and territory structure (OR = 2·1, z = 2·3, d.f. = 1, While little work has been done on the specific issue P = 0·02). of noise and bird pairing success, research comparing ovenbird pairing success in continuous vs. fragmented forests has found differences ranging from 10% to Discussion 50% (Villard, Martin & Drummond 1993; Van Horn,   Gentry & Faaborg 1995; Bayne & Hobson 2001). The difference of 15% found in this study is at the low end of Competition to attract females seems to be intense for this range. However, whether differential pairing success male ovenbirds across their range, as almost all studies influences population dynamics is unclear. Unmated © 2006 The Authors. have found pairing success to be < 100% (Villard, males are common in many passerine species, which Journal compilation Martin & Drummond 1993; Van Horn, Gentry & suggests that forest songbird populations naturally © 2006 British Faaborg 1995; Lambert & Hannon 2000; Bayne & have inherent sex biases. If the mechanisms causing a Ecological Society, Journal of Applied Hobson 2001). This indicates that a biased sex ratio differential sex bias in a population are driven by habitat- Ecology, 44, exists in ovenbird populations, which seems to result in specific female survival or recruitment, then variable 176–184 strong selection by females for high-quality males or pairing success between high- and low-quality habitats 182 may be indicative of a negative demographic effect. optimal sites. Our expectation was that this difference L. Habib, Alternatively, females may simply be more reluctant to use in age structure would explain the differences in pairing E. M. Bayne & one habitat over another. If all females in a population success we observed. That we did not find a direct S. Boutin breed, and tend to do so in the best-quality habitats, then relationship between age and pairing success at the the effects of habitat-specific pairing success on popula- individual level could be the result of the limited number tion dynamics may be negligible. of unpaired males available to test for age effects and/ The structure of vegetation in the territories of paired or inaccuracies in ageing birds. Alternatively, females vs. unpaired birds played a role in determining male may use song characteristics to identify young or low- pairing success. We found that pairing success increased quality males and, in background noise, their ability to in areas having more complex territory structure. While do so accurately is impaired. More work is required to Howell et al. (2000) found a negative association of test the generality of age-related variation in habitat ovenbird density with mean tree d.b.h., Van Horn & selection in forest songbirds. Donovan (1994) state that ovenbirds prefer habitats One prediction of ideal–despotic behaviour is that having large trees. This discrepancy probably comes sites that are high quality will tend to be reoccupied from different definitions of what is meant by large in subsequent years by males that return to sites where trees, as studies in Missouri have found mean tree size they were previously successful (Bayne & Hobson 2002). is greater in territories of paired than unpaired males We attempted to assess if young or unsuccessful breeders (Van Horn & Donovan 1994). Van Horn & Donovan from 2004 would return to the same territory in 2005. (1994) emphasized the importance of litter depth in This would have provided an indication of whether determining pairing success. Unreported models using birds move away from noisy territories when settling litter depth as a measure of territory quality were not the following year. In the first week of June 2005, we significant in our study. Habitat structure can influence returned to all the locations where ovenbirds were the transmission of sound (Huisman & Attenborough captured in 2004. Using playbacks to attract the birds 1991), so it is possible that birds with territories that in the forested periphery of the cleared site where they have more habitat complexity are less impacted by noise had been caught the preceding year, we attempted to because of greater attenuation. If this were the case, we determine if there was a difference in return rate to expected the interaction between habitat structure and the control vs. compressor sites. However, only one bird noise level to be significant. In unreported analyses, we was resighted in 2005, at a compressor site. This low found no evidence for this, but a limited sample size of return rate is in distinct contrast to work by Porneluzi unpaired males makes such effects difficult to detect. & Faaborg (1999), Burke & Nol (2001) and Bayne & At the individual level, we found no evidence that age Hobson (2002), who found that c. 40% of male oven- or body morphology influenced pairing success. This is birds return to the same territory from year to year in in contrast to previous work that has shown that older contiguous forest. One explanation for this extremely birds have greater pairing success than younger birds low return rate could be that ovenbirds at wellpads (Saether 1990; Bayne & Hobson 2001). A connection and compressor stations were universally affected by between age and pairing status in the presence of noise some other factor (e.g. high predation at edges) and was found by Reijnen & Foppen (1994): within 200 m of subsequently never returned to either one of these a highway, young males willow warblers Phylloscopus anthropogenically disturbed areas. This phenomenon trochilus were 25% less successful at attracting mates warrants further study. than older males, while farther from the road there were If the pattern of age-related habitat selection were to no differences in pairing success between age classes. manifest itself in females, the implications for ovenbird This pattern could be explained by older birds being more population dynamics could be more substantial. Young experienced singers, which females may be attracted to females attempting to breed for the first time often despite the background noise. have lower reproductive output than older individuals having previous breeding experience (Holmes, Marra     & Sherry 1996). In areas where young females are dominant, population sinks may form. Populations in Although we did not find an effect of individual age sink habitats may only persist via immigration from on pairing success, we did find that the age structure other areas having less human disturbance (Robinson of ovenbirds near compressor sites was different from et al. 1995). Managers need to recognize that the controls overall. How biased age structures form between presence of birds like the ovenbird near compressor habitats is not clear. Holmes, Marra & Sherry (1996) sites and other industrial sites does not necessarily suggested that older black-throated blue warbler indicate that local populations are self-sustaining. © 2006 The Authors. Dendroica caerulescens males occupy higher quality Journal compilation sites than younger males because older males outcompete © 2006 British   younger birds for these areas. By claiming the highest Ecological Society, Journal of Applied quality territories early in the breeding season, older As of September 2005, there are more than 5600 com- Ecology, 44, males may exclude younger males from good-quality pressor stations in Alberta’s boreal forest (IHS Energy, 176–184 habitats, thereby forcing younger males to use sub- Calgary, Canada). However, there are also many other 183 types of noise-generating energy industry facilities, Nielsen for assistance in the field. Shawna Pelech, Chronic noise and including gas plants, dehydration facilities and pump- Darroch Whitaker, Simon Thirgood and an anonymous ovenbird pairing jacks. Currently these disturbances exist in a region referee provided valuable comments on an earlier success about three times the size of England. The proliferation version of this manuscript. Thanks to Alberta Pacific of energy facilities is set to increase dramatically in this Forest Industries, Tolko Forest Industries, Daishowa- region over the next 5 years as a $100-billion influx of Marubeni International Ltd and IHS Energy for AVI energy sector development is planned. The reduction and facility GIS data layers. This research was conducted in habitat amount as well as reduced breeding success as part of the Natural Sciences and Engineering Research in areas impacted by industrial noise could result in a Council of Canada (NSERC) Industrial Research Chair large decrease in the amount of high-quality breeding in Integrated Landscape Management held by S. habitat available for ovenbirds and other passerines. Boutin. Additional funding was provided by the The effect may be particularly problematic in the eastern Canadian Circumpolar Institute, Alberta Sport, portion of Alberta, a region subject to extraction of Recreation, Parks and Wildlife Foundation and the bitumen by mining and steam-assisted gravity drainage Alberta Conservation Association Challenge Grants (SAGD) procedures, which involve a substantial number in Biodiversity. Personal funding to L. Habib was of noise-generating facilities. provided by NSERC, Alberta Ingenuity Fund and the Compressor station clearings typically range from 1 Alberta Society of Professional Biologists. to 4 ha in size. In the eastern portion of our study area, there are approximately 650 compressor station-type References facilities. Assuming a conservative average cleared area of 2 ha pad−1, this translates to 1300 ha of direct ovenbird Alberta Energy & Utilities Board (1999) Guide 38: Noise Control Directive User Guide. Alberta Energy & Utilities habitat area lost to tree removal for compressor pads Board, Calgary, Canada. (including wellpads in this estimate would drastically ATCO Noise Management (2003) Environmental Noise Control. increase the figure by more than 50 000 ha). If we assume ATCO Noise Management, Calgary, Canada. that one ovenbird territory on each side of the perimeter Bayne, E.M. & Hobson, K.A. (2001) Effects of habitat of the compressor station pad has additional negative fragmentation on pairing success of ovenbirds: importance of male age and floater behavior. Auk, 118, 380–388. behavioural effects consistent with our findings, it results Bayne, E.M. & Hobson, K.A. (2002) Apparent survival of in an additional impacted area of nearly 13 000 ha. Adding male ovenbirds in fragmented and forested boreal landscapes. ‘impacted area’ buffers around other noise-generating Ecology, 83, 1307–1316. facilities would increase this figure considerably. Impor- Binek, J. (1996) Some important considerations in the design tantly, technology to decrease noise levels at industrial of a quiet compressor station. Proceedings of the Spring Environmental Noise Conference: Innovations in Noise Control sites by c. 30 dB(A) does exist (ATCO Noise Management for the Energy Industry. Alberta Energy Utility Board, Red 2003). However, the financial costs to fit compressor Deer, AB. stations with noise reduction technologies in wilderness Bolstad Engineering Associates Ltd (1978) Compressor areas has been deemed unnecessary because of the lack of Station and Gas Plant Noise Emission: An Engineering Report. impact on human residences (Alberta Energy & Utilities Bolstad Engineering Associates Ltd, Edmonton, Canada. Breitwisch, R. (1989) Mortality patterns, sex ratios, and parental Board 1999). Our study demonstrates that noise per se investment in monogamous birds. Current Ornithology, 6, does have an impact on breeding forest songbirds and 1–50. that more careful assessment of noise effects is needed Brenowitz, E.A. (1982) Long-range communication of species for future energy developments. identity by song in the red-winged blackbird. Behavioral While previous studies looking at effects of roads Ecology Sociobiology, 10, 29–38. Burke, D. & Nol, E. (2000) Landscape and fragment size on breeding birds (Reijnen & Foppen 1994; Reijnen effects on reproductive success of forest-breeding birds in et al. 1995; Reijnen, Foppen & Veenbaas 1997) have Ontario. Ecological Applications, 10, 1749–1761. postulated noise as the cause of altered behavioural Burke, D. & Nol, E. (2001) Age ratios and return rates of adult patterns, researchers have been unable to isolate it from male ovenbirds in contiguous and fragmented forests. confounding factors. This study provides the strongest Journal of Field Ornithology, 72, 433–438. Donovan, T.M. & Stanley, C.M. (1995) A new method of support that chronic noise is an important factor determining ovenbird age on the basis of rectrix shape. influencing habitat quality. Our result supports the Journal of Field Ornithology, 66, 247–252. conclusions from road avoidance studies, which argue Habib, L.D. (2006) Effects of chronic industrial noise distur- that noise is the key factor influencing birds in such bance on boreal forest songbirds. MSc Thesis. University of environments. Consequently, adding busy roads to the Alberta, Edmonton, Canada. Hardin, J.W. & Hilbe, J.M. (2003) Generalized Estimating list of noise-generating sites in Alberta and elsewhere in the Equations. Chapman & Hall/CRC, Boca Raton, FL. world dramatically increases impacted area estimates. Holmes, R.T., Marra, P.P. & Sherry, T.W. (1996) Habitat- © 2006 The Authors. specific demography of breeding black-throated blue warblers Journal compilation (Dendroica caerulescens): implications for population dynamics. © 2006 British Acknowledgements Journal of Animal Ecology, 65, 183–195. Ecological Society, Howell, C.A., Latta, S.C., Donovan, T.M., Porneluzi, P.A., Journal of Applied Thanks to Cris Gray, Doug Pueschel, Erin Cameron, Parks, G.R. & Faaborg, J. (2000) Landscape effects mediate Ecology, 44, Adam Blake, Martin Lankau, Maria Cecilia Arienti, breeding bird abundance in midwestern forests. Landscape 176–184 Heather Clarke, Mark Conboy, Tanya Hope and Scott Ecology, 15, 547–562. 184 Huisman, W.H.T. & Attenborough, K. (1991) Reverberation Reijnen, R., Foppen, R., Terbraak, C. & Thissen, J. (1995) L. Habib, and attenuation in a pine forest. Journal of the Acoustical The effects of car traffic on breeding bird populations in E. M. Bayne & Society of America, 90, 2664–2677. woodland. III. Reduction of density in relation to the Kuitunen, M., Rossi, E. & Stenroos, A. (1998) Do highways proximity of main roads. Journal of Applied Ecology, 32, S. Boutin influence density of land birds? Environmental Management, 187–202. 22, 297–302. Reijnen, R., Foppen, R. & Veenbaas, G. (1997) Disturbance Kuitunen, M.T., Viljanen, J., Rossi, E. & Stenroos, A. (2003) by traffic of breeding birds: evaluation of the effect and Impact of busy roads on breeding success in pied flycatchers considerations in planning and managing road corridors. Ficedula hypoleuca. Environmental Management, 31, 79–85. Biodiversity and Conservation, 6, 567–581. Lambert, J.D. & Hannon, S.J. (2000) Short-term effects of timber Robinson, S., Thompson, F. III, Donovan, T., Whitehead, D. harvest on abundance territory characteristics, and pairing & Faaborg, J. (1995) Regional forest fragmentation and success of ovenbirds in riparian buffer strips. Auk, 117, 687–698. the nesting success of migratory birds. Science, 267, 1987– Lein, M.R. (1980) Display behavior of ovenbirds (Seiurus 1990. aurocapillus). I. Non-song vocalizations. Wilson Bulletin, Saether, B.-E. (1990) Age-specific variation in reproductive 92, 312–329. performance of birds. Current Ornithology, 7, 251–283. Lein, M.R. (1981) Display behaviour of ovenbirds (Seiurus Slabbekoorn, H., Ellers, J. & Smith, T.B. (2002) Birdsong and aurocapillus). II. Song variation and singing behaviour. sound transmission: the benefits of reverberations. Condor, Wilson Bulletin, 93, 21–41. 104, 564–573. MacDonald, J. (1996) Trapping and suppressing compressor Strong, W.L. & Leggat, K.R. (1992) Ecoregions of Alberta. axial fan intake noise. Proceedings of the Spring Environ- Alberta Forestry, Lands & Wildlife, Edmonton, Canada. mental Noise Conference: Innovations in Noise Control for Van Horn, M.A. & Donovan, T.M. (1994) Ovenbird (Seiurus the Energy Industry. Alberta Energy Utility Board, Red aurocapillus). The Birds of North America, Vol 88 (eds A. Deer, AB. Poole and F. Gill). Philadelphia: The Academy of Natural Porneluzi, P. & Faaborg, J. (1999) Season-long fecundity, Sciences; Washington, D.C.: The American Ornithologists’ survival, and viability of ovenbirds in fragmented and unfrag- Union. mented landscapes. Conservation Biology, 13, 1151–1161. Van Horn, M.A., Gentry, R.M. & Faaborg, J. (1995) Patterns Pyle, P., Howell, S.N.G., Yunick, R.P. & DeSante, D.F. (1987) of ovenbird (Seiurus aurocapillus) pairing success in Missouri Identification Guide to North American Passerines. Slate forest tracts. Auk, 112, 98–106. Creek Press, Bolinas, CA. Villard, M.A., Martin, P.R. & Drummond, C.G. (1993) Reijnen, R. & Foppen, R. (1994) The effects of car traffic on Habitat fragmentation and pairing success in the ovenbird breeding bird populations in woodland. I. Evidence of (Seiurus aurocapillus). Auk, 110, 759–768. reduced habitat quality for willow warblers (Phylloscopus trochilus) breeding close to a highway. Journal of Applied Received 10 February 2006; final copy received 5 July 2006 Ecology, 31, 85–94. Editor: William Montevecchi

© 2006 The Authors. Journal compilation © 2006 British Ecological Society, Journal of Applied Ecology, 44, 176–184 Journal of Applied Ecology 2011, 48, 210–219 doi: 10.1111/j.1365-2664.2010.01914.x Negative impact of traffic noise on avian reproductive success

Wouter Halfwerk1*, Leonard J. M. Holleman2, C(Kate). M. Lessells2 and Hans Slabbekoorn1

1Behavioural Biology, Institute of Biology, Leiden University, 2333 BE Leiden, The Netherlands; and 2Netherlands Institute of Ecology (NIOO-KNAW), 6666 ZG Heteren, The Netherlands

Summary 1. Traffic affects large areas of natural habitat worldwide. As a result, the acoustic signals used by birds and other animals are increasingly masked by traffic noise. Masking of signals important to territory defence and mate attraction may have a negative impact on reproductive success. Depend- ing on the overlap in space, time and frequency between noise and vocalizations, such impact may ultimately exclude species from suitable breeding habitat. However a direct impact of traffic noise on reproductive success has not previously been reported. 2. We monitored traffic noise and avian vocal activity during the breeding season alongside a busy Dutch motorway. We measured variation in space, time and spectrum of noise and tested for nega- tive effects on avian reproductive success using long-term breeding data on great tits Parus major. 3. Noise levels decreased with distance from the motorway, but we also found substantial spatial variation independent of distance. Noise also varied temporally with March being noisier than April, and the daytime being noisier than night-time. Furthermore, weekdays were clearly noisier than weekends. Importantly, traffic noise overlapped in time as well as acoustic frequency with avian vocalization behaviour over a large area. 4. Traffic noise had a negative effect on reproductive success with females laying smaller clutches in noisier areas. Variation in traffic noise in the frequency band that overlaps most with the lower fre- quency part of great tit song best explained the observed variation. 5. Additionally, noise levels recorded in April had a negative effect on the number of fledglings, independent of clutch size, and explained the observed variation better than noise levels recorded in March. 6. Synthesis and applications. We found that breeding under noisy conditions can carry a cost, even for species common in urban areas. Such costs should be taken into account when protecting threa- tened species, and we argue that knowledge of the spatial, temporal and spectral overlap between noise and species-specific acoustic behaviour will be important for effective noise management. We provide some cost-effective mitigation measures such as traffic speed reduction or closing of roads during the breeding season. Key-words: anthropogenic noise, clutch size, great tit, Parus major, reproductive success, traffic noise fluctuations

camp 1998; Brumm & Slabbekoorn 2005). As a consequence, Introduction animals living in areas exposed to anthropogenic noise may Anthropogenic noise currently affects large areas of natural suffer reduced reproductive success, which may ultimately lead habitat worldwide (Forman 2000; Barber, Crooks & Fristrup to the exclusion of species from otherwise suitable habitat 2009). Masking by noise interferes with the use of the acoustic (Slabbekoorn & Ripmeester 2008). signals critical to many animal species (Bradbury & Vehren- The majority of areas affected by noise are situated along major transport links, such as motorways and railways (For- man 2000; Barber, Crooks & Fristrup 2009). The impact of *Correspondence author. E-mail: [email protected] traffic noise has been explored in a diverse range of taxa (frogs;

2010 The Authors. Journal of Applied Ecology 2010 British Ecological Society Traffic noise and avian reproductive success 211

Bee & Swanson 2007; bats; Schaub, Ostwald & Siemers 2008), The great tit Parus major (Linneaus 1758) is a common but has been studied most intensively in birds (e.g. Reijnen species that is currently not under threat, but the availability et al. 1995; Stone 2000). Many studies have shown a reduction of long-term data from a population bordering a major in breeding numbers in the vicinity of motorways (e.g. van der motorway provides a rare opportunity to investigate whether Zande, ter Keurs & van der Weijden 1980; Reijnen & Foppen noise has more subtle effects than simply excluding birds 1991), but no study to date has been able to exclude confound- from otherwise suitable habitat. This species prefers artificial ing factors associated with roads and thus identify traffic noise nest-boxes to natural cavities (Kluyver 1951) even when they as the key threat to birds (Warren et al. 2006). are situated in suboptimal habitat. This is probably one rea- An impact of anthropogenic noise on breeding numbers son why great tits breed in substantial numbers in areas (Bayne, Habib & Boutin 2008) and species richness (Francis, adjacent to motorways (Junker-Bornholdt et al. 1998), Ortega & Cruz 2009) without confounding factors has been allowing collection of breeding data in noisy areas. Great tit demonstrated in the vicinity of noisy gas compressor stations. singing behaviour has been repeatedly related to noise at However, extrapolating these findings to motorway noise is both the population (Slabbekoorn & den Boer-Visser 2006; far from straightforward. For instance, noise at gas compres- Mockford & Marshall 2009) and individual level (Slabbeko- sor stations is constant in amplitude throughout the day and orn & Peet 2003). We know that relatively low frequency year (Francis, Ortega & Cruz 2009), whereas most anthropo- songs are detected less well when there is traffic-like noise genic noise levels show strong daily, weekday versus weekend, (Pohl et al. 2009), and great tits can switch between song and seasonal variation (Bautista et al. 2004; Warren et al. types when exposed to experimental noise (Halfwerk & Slab- 2006). bekoorn 2009). However, it is unknown whether such The negative effect of traffic noise on birds depends on the behavioural flexibility prevents any negative effects of temporal and spectral overlap with relevant acoustic sounds anthropogenic noise. (Brumm & Slabbekoorn 2005). Birds use a variety of vocal- We studied spatial, temporal and spectral variation in the izations throughout the day but many species restrict the use loudness of traffic noise and bird acoustic behaviour in a nest- of song, which is important in both territorial defence and box population of great tits adjacent to a Dutch motorway with female attraction, to the period around dawn (Catchpole & a heavy traffic load. Traffic noise and bird song were recorded Slater 2008). The overlap between dawn song and peaks in during two important breeding stages: March, when territories traffic activity (e.g. the rush hour) may be an important factor are formed, and April, when eggs are laid and incubated. We in determining negative effects, and depends primarily on used these data, together with habitat and long-term breeding the time of year in combination with longitude and latitude data to explore the following questions: How does traffic noise (Warren et al. 2006). Assessing temporal variation in noise in habitat adjacent to a motorway vary in space? To what levels is therefore an important step in understanding when extent do traffic noise and bird vocal activity overlap in time noise overlaps most with the vocal activity of birds (Slabbeko- and frequency, and does the amount of overlap differ between orn & Ripmeester 2008; Barber, Crooks & Fristrup 2009). breeding stages? Is there an impact of traffic noise levels on Spectral overlap is most dramatic for birds vocalizing at low breeding success? Does seasonal variation in traffic noise affect frequencies (e.g. cuckoos, owls, woodpeckers and grouse) as particular breeding stages? And does spectral overlap between traffic noise is typically loudest at lower frequencies (Pohl great tit song and traffic noise play a role in the effect on repro- et al. 2009) and low sounds attenuate less with distance and ductive success? Answers to these questions will be valuable in vegetation density (Wiley & Richards 1978; Padgham 2004). identifying conservation measures and applying effective noise Furthermore, fluctuations in low frequency transmission can management in natural areas polluted by traffic noise. change dramatically with weather conditions (Ovenden, Shaf- fer & Fernando 2009) resulting in unpredictable overlap lev- Materials and methods els. Even when there is clear temporal and spectral overlap STUDY SITE AND SPECIES between traffic noise and birdsong, assessing whether there is a negative impact on reproductive success in the field is not We collected data from a nest-box population of great tits Parus straightforward. The effect on breeding numbers may underes- major breeding at the Buunderkamp (0545¢ E; 5201¢ N) in the Neth- erlands (Fig. 1a). The area is bounded in the north by a four-lane timate the impact and provides little insight into the mecha- ) motorway and in the south by a railway line (about 20 trains h 1). nisms by which birds are affected. For example, breeding The habitat is mixed woodland consisting of plots of varying sizes, success and welfare may be impaired, but breeding densities and age and species of trees, with Pinus sylvestris and Quercus rubra remain high because of compensating effects of noise on preda- dominant (see Drent 1987 for further description of the area). tion rates (Francis, Ortega & Cruz 2009) or competition for The great tit is a hole-nesting passerine that sings in the frequency food (Slabbekoorn & Halfwerk 2009). Furthermore, inexperi- range of 2–9 kHz (Halfwerk & Slabbekoorn 2009). Territory enced or low quality birds may be more likely to occupy noisy defence starts in mid-January and peaks towards the end of March areas (Reijnen & Foppen 1991; Habib, Bayne & Boutin 2007). (Kluyver 1951). Egg-laying in the study population starts in April Therefore, understanding the mechanisms underlying the neg- and is accompanied by a strong increase in dawn singing activity. ative effects of noise is best achieved by focusing on individual We used long-term breeding data on great tits for the period 1995– life history traits that are components of reproductive success. 2009 during which no major changes have been made in the area

2010 The Authors. Journal of Applied Ecology 2010 British Ecological Society, Journal of Applied Ecology, 48, 210–219 212 W. Halfwerk et al.

(a) (b)

! ! " " " " " " " ! " " ! " " " " " " " " " " " " " " " " " " " " " " " " " " " " " 3 " " ! " " " " " " " ! ! " " " " " ! ! ! ! " " " ! " " " " " ! ! " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " ! " " ! ! ! ! ! " " " " ! ! ! " " " " " " " " ! " " " " " " " " " " " " " " " " " " " " " " " " " " " " " ! ! " " " ! " " ! ! " ! ! ! " " ! ! " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " " ! ! ! ! " " ! ! " ! ! ! " " " ! " " " " " " " " " " " " " " " " " ! " ! " " " " ! " " ! ! " " " ! ! " ! ! ! " " " " " " " " " " " " " " " " " " " " " " ! " " 1 ! ! ! " " ! ! " ! 2 " " " " " ! " ! ! " " " " " " " " " " " " " " " " " " " " " " " " " N " " " " "

" " " " " " " " " " " " " " " " " " " " ! " " " ! 4 " " " " ! " " " " " ! " " ! " " " " " ! " ! " " " " ! " " !

" ! " 100 m ! " " !

(c)

> 65 dB > 62 dB > 59 dB > 56 dB > 53 dB > 50 dB > 47 dB > 44 dB

1 km

Fig. 1. Maps of the Buunderkamp area showing nest-boxes, sampling locations and noise levels. Motorway (triple line) and railway (dashed line) are shown. a) nest-box distribution (small dots). Only breeding data from nest-boxes within the rectangle was used. b) sampling locations (filled rectangles) along 10 transects (open rectangles, 2 of them shown). Numbers refer to locations of example recordings used in Fig. 2. c) GIS-map showing spatial variation in sound levels. Traffic noise shows a strong decrease with distance from the motorway (absolute range at sampling locations 46Æ5–67Æ8 dB SPL, A-weighted), but there is substantial spatial variation in this decline. that would have affected the spatial spread of noise coming from of the area, but we used two additional SongMeters to monitor the the motorway. remaining area. Recorders were attached to large trees (>40 cm in diameter) at 2 m above the ground with the recording microphone directed towards the motorway. Recording levels for the micro- NOISE DATA ACQUISITION phones were adjusted to a sensitivity ranging from 0Æ0to1Æ5 We made sound recordings between March and May 2008, before dBV pa)1 (reaching full scale between 92Æ5and94Æ0dBSPL)and major leafing of the deciduous trees. We sampled sound levels along amplitude levels were adjusted according to the effective sensitivity ten transects perpendicular to the motorway (Fig. 1b), with auto- of each individual Song Meter recorder. Recorders were randomly matic SongMeter recorders (16 bit, 24 kHz sample rate; Wildlife swapped between sampling locations to control for any remaining Acoustics Inc., Concorde, MA, USA). Exact sampling locations variation in recording levels. Recorders were scheduled to record for were determined with a GPS (Garmin 60CSx, Olathe, KS, USA). 30 s at 30 min intervals, day and night. The sampling transects started 100 m from the mid-line of the We analysed sound recordings in the computer program Matlab motorway and six sampling locations at approximately 100 m inter- (Mathworks Inc., Natick, MA, USA). We measured overall sound vals were chosen within each transect. The transects were spaced levels (using an A-weighted filter), and also sound levels in four 80–100 m apart and two transects were sampled simultaneously for adjacent octave-bands, centred at frequencies of 0Æ5, 1Æ0, 2Æ0, and 3–5 consecutive days. Transects were each sampled twice in a ran- 4Æ0 kHz. Sound measurements were averaged over either 30-min or dom order, once between 8th and 30th of March, and once between 24-h intervals, and ⁄ or sampling locations, depending on the type of 31st of March and 1st of May. The sampling grid encompassed most analysis.

2010 The Authors. Journal of Applied Ecology 2010 British Ecological Society, Journal of Applied Ecology, 48,210–219 Traffic noise and avian reproductive success 213

We used 76 sampling locations to visualize spatial variation in Institute (KNMI) at de Bilt (situated ±50 km to the west of the Bu- noise levels for the Buunderkamp in the computer program ArcGis underkamp). (version 9Æ0, ESRI). Sixty locations from the sampling transects and 16 additional sampling locations were plotted onto a geo-annotated STATISTICAL ANALYSIS reference map from which noise maps were derived with the Spatial Analyst toolbox. Spatial resolution was set at 5 m and raster values We analysed all data using SPSS (version 17Æ0) and log-transformed between sampling locations were calculated with a weighted distance variables when necessary to meet model assumptions. Temporal interpolation tool (IDW). Additionally we calculated distances for all variation in daily and seasonal sound levels were explored using nest boxes and sampling locations to the nearest mid-point on the repeated measures anovas with sound level grouped by sampling motorway. location as the dependent variable and time of day or date as an We assessed the temporal overlap between traffic noise and vocal explanatory variable. Additionally, we compared recordings made bird activity throughout the season and at different times of day. At on weekdays with recordings from weekends with type of day as a our study site most of the non-anthropogenic sound comes from fixed factor. vocalizing birds with the majority of acoustic energy in the range of We examined the effect of daily weather conditions on the propaga- 2–8 kHz. We selected a subset of sampling locations at distances over tion of noise with full factorial linear mixed models. To test for the 400 m from the motorway where there is little traffic noise present in effect of wind direction we discriminated between days with northerly the 4 kHz octave band so temporal variation in sound levels was (coming from the direction of the motorway) and southerly winds mainly related to the vocal activity by birds. For these locations, we (going towards the direction of the motorway). Wind direction was compared sound levels, averaged over 1 or 24 h intervals, in the included as a fixed factor, and sample location as a random factor. 1 kHz band (mainly due to traffic noise) with those in the 4 kHz band Distance to the motorway, wind speed, and daily temperature were (mainly due to bird activity, including great tits). included as covariates. We constructed a set of linear mixed models for each life history trait and compared them using a model selection approach based on LONG-TERM BREEDING DATA Akaike’s information criterion (Burnham & Anderson 2002). Models Great tit breeding data were collected between 1995 and 2009 by the always included nest-box type (large or small), sampling location and Netherlands Institute of Ecology (NIOO-KNAW). We used data breeding year as random factors. Depending on the model, we also from both large and small nest-boxes within the sampling grid included other reproductive traits as explanatory variables (cf. Wilkin (Fig 1a) on laying date, clutch size, number of hatchlings, number of et al. 2006). For instance, clutch size can correlate with laying date fledglings and fledging mass (average weight of chicks for the brood and an effect of noise on clutch size could be indirectly caused by an when chicks are 15 days old) for all first great tit clutches over this effect of noise on laying date. Including laying date in the clutch size period, except for 2007 and 2008 when data were excluded because of model therefore allows us to test for a direct effect of noise. For the an unrelated experiment. Additional data on female identity, female number of hatchlings we included clutch size and for the number of age and fledging mass were only available for 1995–1999, 2001 and fledglings we included number of hatchlings in the models. For the 2009. fledging mass model we included both clutch size and laying date as For analysis of breeding performance we used only first clutches these factors are known to have a large effect on fledging mass (e.g. (categorised using female identity or because laying date was within Wilkin et al. 2006). 30 days of the first laying date for a given year). For analyses of In a first analysis we compared models that included overall noise laying date we used only clutches for which this could be reliably levels, distance to the motorway, tree density, tree diameter and per- calculated. We were interested in the mechanisms underlying breed- centage deciduous trees as explanatory factors only. Models con- ing success and therefore focused on life history traits that reflected tained single factors or in combination with other factors as main decisions made by the birds. For the analysis of clutch size we effects as we had no a priori knowledge that interactions among fac- therefore excluded clutches that were not incubated, because tors would be of importance. The total set contained 32 models to be including nests that were abandoned (either through a decision by compared for each trait, including the Null model. We calculated for the parents, or predation of the parents) would introduce unwanted each explanatory factor the probability that it would be in the best heterogeneity in the data. Similarly, we excluded nests where no approximating model using Akaike weights (see e.g. Whittingham chicks hatched or fledged from the analyses of the number of et al. 2005; Garamszegi et al. 2009). We used the subset of models hatchlings and fledglings, respectively, because it was usually with a delta-AIC < 4Æ0 from the top model to get model-averaged unknown whether failure was caused by death of all the embryos estimates and standard errors for each factor (cf. Burnham & Ander- or chicks, abandonment by the parents or predation of the parents son 2002). In a second analysis we focused on temporal overlap (away from the nest). between noise sampling period and breeding stage. We used the mod- els with delta-AIC < 4Æ0 from the previous analysis and only exchanged the overall noise with noise levels sampled either in March WEATHER DATA AND HABITAT MEASUREMENTS or in April. In a third analysis, we repeated this procedure, but We assessed habitat characteristics, including tree density, tree diame- focused on the spectral overlap with song and explored whether noise ter and species composition, at the level of woodland plots (0Æ2– in a certain frequency range (0Æ5, 1Æ0, 2Æ0, or 4Æ0 octave band, or over- 1Æ0 ha). We measured tree density and diameter and noted tree species all noise) better explained variation of the data. at each of the 60 sampling locations, and at the 2 nest boxes nearest to Breeding performance is known to be age-dependent (Kluyver these locations. We calculated the percentage of deciduous trees per 1951; Wilkin et al. 2006) and we therefore re-ran analyses for which plot and averaged tree density and diameter over all locations within we found strong support using the subset of data for which female a plot. We used weather data on daily wind direction and speed, and age was known. Female identity was added as a random factor and temperature, recorded by the Royal Netherlands Meteorological female age (first year or older) as a fixed factor.

2010 The Authors. Journal of Applied Ecology 2010 British Ecological Society, Journal of Applied Ecology, 48, 210–219 214 W. Halfwerk et al.

distancesfromthemotorway.Forinstance,at700mfromthe Results motorway, sound levels below 1 kHz could increase by over 10 dB SPL on cold days or days with northerly winds SPATIAL PATTERNS IN NOISE LEVELS (Fig. 2c,d). Overall sound levels gradually decreased with distance from the motorway (F5,54 =200Æ5, P <0Æ001) with an average TEMPORAL FLUCTUATIONS IN TRAFFIC NOISE LEVELS drop of 20 dB SPL (A-weighted) over less than 500 m AND THE OVERLAP WITH BIRD ACTIVITY (Fig. 1c). Furthermore, high frequencies attenuated faster than low frequencies (F3,59 =12Æ03, P <0Æ001; Fig. 2a). There Traffic noise levels changed throughout the season (F1,59 = was substantial spatial variation in traffic noise, independent 7Æ57 P =0Æ008) with March being noisier and more variable of distance to the motorway (Fig. 1c): different locations at than April (Fig. 3a). Additionally, noise levels on weekdays medium (>300 m) to large (>700 m) distances from the were significantly higher than at the weekend (F1,59 =4Æ87 motorway differed by more than 9 dB SPL (A-weighted) in P =0Æ032; Fig. 3). Noise levels showed a strong daily pattern noise level (Fig. 1c). Train noise can be very loud (see e.g. (F1,59 =8Æ776 P =0Æ005), with a clear drop between 0:00 and Fig. 2b) but, in contrast to motorway noise, is transient and 4:00 AM, but no distinct rush-hour peaks (Fig. 3b). average daily noise levels near the railway line were among the Screening of recordings revealed that, at distances over lowest (Fig. 1c). 400 m from the motorway, variation in sound levels in the 4 kHz band was indeed mainly influenced by bird vocal activ- ity, and we therefore used recordings at these distances to WEATHER-DEPENDENT NOISE LEVELS assess seasonal and daily overlap of traffic noise and bird vocal Wind direction, wind speed and daily temperature all had an behaviour. Bird vocal activity as measured at the peak of the effect on overall sound levels (see Table 1). Furthermore, wind dawn chorus increased throughout the season (4 kHz-band; direction and temperature interacted with distance to the F1,59 =7Æ88, P <0Æ001) whereas traffic noise during this time motorway (Table 1). We reanalysed a subset of recordings period decreased (1 kHz-band; F1,59 =5Æ13, P <0Æ001; made at distances of 400–700 m from the motorway to explore Fig. 3a). Bird vocal behaviour showed a temporal shift the effect of weather conditions on sounds in different octave between early March and late April due to changes in the time bands. Both temperature (F1,59 =27Æ78; P <0Æ0001) and of sunrise, but despite this, the temporal overlap with traffic wind direction (F1,59 =5Æ27; P =0Æ001) interacted with fre- noise remained remarkably high on weekdays (Fig. 3b), prob- quency, with the strongest effect at lower frequencies and large ably due to the change from winter to summer time (i.e. clock

70 Near 3 70 (b) Train 4 (a) Far 1 No train 4 D 60 April 21, 2008 D 60 April 21, 2008 20:00 19:30 50 50

40 40

30 30

20 20 Fig. 2. Variation in sound profiles across dif- ferent environmental conditions. a) power- 10 10 spectrographic example comparing sound 0125 34 6 0123456 profiles near to (±100 m), and far from (±700 m), the motorway. At larger dis- 60 Cold 1 60 Northern 2 B C tances, the high-frequency components of (c) April 16, 2008 (d) April 18, 2008 16:00;6·4 °C 16:00 traffic noise are more attenuated and even

Noise level (dB SPL) 50 50 disappear above ±3 kHz. b) recordings 2 Warm 1 Southern made near the railway (±100 m from the E A 40 April 25, 2008 40 March 31, 2008 track and ±1 km from the motorway) 16:00;12·6 °C 16:00 shortly before and during the passage of a 30 30 train. c) comparison of sound profiles on days with different temperatures, but similar 20 20 wind conditions illustrates large effect of weather conditions on noise levels. d) com- 10 10 parison of sound profiles on days with oppo- site wind directions, but similar temperature 0 0 and wind speed. Small numbers refer to loca- 0123456 012 345 6 tions illustrated in Fig. 1. Capital letters refer Frequency (kHz) to recording days illustrated in Fig. 3.

2010 The Authors. Journal of Applied Ecology 2010 British Ecological Society, Journal of Applied Ecology, 48,210–219 Traffic noise and avian reproductive success 215

Table 1. Results from mixed model showing effect of weather and 3) and virtually no support in the remaining life history condition on overall noise levels. Sampling location (N = 60) was models. added as random factor. Only first order interactions are reported Overall noise levels had an independent negative effect on Source d.f. F P clutch size, with females laying on average about 10% fewer eggs across a noise gradient of 20 dB SPL (A-weighted) Distance 5 6Æ61 <0Æ001 (Table 3). Reanalysing the top clutch size model to include Wind direction (N vs. S) 1 10Æ92 0Æ001 female identity and age confirmed the effect of noise Daily temperature 1 9Æ65 0Æ002 (F1,268 =7Æ82, P =0Æ007),butfailedtoshowaneffectof Wind speed* 1 29Æ30 <0Æ001 female age on clutch size (F =0Æ20, P =0Æ82). Noise lev- Distance · Wind direction 5 3Æ81 0Æ002 1,268 Distance · Daily temperature 5 2Æ73 0Æ019 els had a negative effect on fledging mass (Table 3), but in none Distance · Wind speed* 5 1Æ75 0Æ12 of the top models was the effect significant (all P >0Æ2). Wind direction · Daily temperature 1 1Æ32 0Æ25 Wind direction · Wind speed* 1 10Æ38 0Æ001 Daily temperature · Wind speed* 1 11Æ26 0Æ001 TEMPORAL AND SPECTRAL VARIATION IN NOISE PREDICTS SMALLER CLUTCHES AND FEWER *log-transformed. FLEDGLINGS time advancing by 1 h on 30 March). Peak activity of avian Refining the models with noise sampled either in March or in vocal behaviour showed the least overlap with traffic noise dur- April did not change the level of support, except for the num- ing the weekends, especially in late April (Fig. 3b). ber of fledglings model (Tables 4 and 5). Noise sampled in April was about seven times more likely to explain variation of the data compared to noise sampled in March (Table 5). NEGATIVE EFFECT OF TRAFFIC NOISE ON BREEDING Higher noise levels in April correlated with lower numbers of PERFORMANCE fledglings (Table 5). We re-ran the top model to include clutch Overall noise levels received strong support in the model selec- size instead of the number of fledglings as fixed factor. Clutch tion procedure for clutch size and fledging mass models and size had a large effect on the number of fledglings moderate support for the number of fledglings model (Tables 2 (B =0Æ57 ± 0Æ070; F1,364 =65Æ51, P <0Æ0001), but we and 3). Tree diameter and tree density received strong support found noise sampled in April to have an additional negative ) in all life history models (Tables 2 and 3), but the effect was not effect (B = 0Æ061 ± 0Æ027; F1,364 =5Æ09, P =0Æ028) as consistent across models and the variance was high (Table 3). well. Distance to the highway and percentage deciduous trees Finally, we found that variation in noise levels in the 2 kHz received weak support in the fledging mass model (Tables 2 octave band best explained variation in clutch size, although

60 (a) Traffic noise Bird sounds Weekend 50

40

A B C D E 30 March April

60 Week60 Weekend 60 Week 60 Weekend (b)

Noise level (dB SPL) 50 50 50 50

40 40 40 40

30 30 30 30

20 20 20 20 0 2 4 6 8 1012141618202224 0 2 4 6 8 1012141618202224 02468 1012141618202224 0 2 4 6 8 10 12 14 16 18 20 22 24 Time of day (h)

Fig. 3. Temporal patterns in traffic noise levels and bird vocal activity. Recordings made at distances of 400–700 m from the motorway, averaged over 1 or 24 h intervals. We compared amplitude fluctuations in the 1 and 4 kHz band, which are mainly influenced by traffic and bird vocal activity respectively. a) seasonal pattern in sound levels between March and May 2008. Recordings made at dawn during peak singing activity. Traffic noise levels decrease throughout the season, but show substantial variation due to changes in traffic activity (week days being noisier than weekend days) and changes in weather conditions. Bird vocal activity increases throughout the season. b) daily pattern in traffic noise and bird sound levels during either the period of great tit territory defense (8–16 of March, left two graphs) or egg-laying (19–27 of April, right two graphs), on weekdays or at the weekend.

2010 The Authors. Journal of Applied Ecology 2010 British Ecological Society, Journal of Applied Ecology, 48, 210–219 216 W. Halfwerk et al.

Table 2. Life history model selection Akaike procedure based on traffic noise, distance Dependent trait Model AIC D AIC weight and ⁄ or habitat features using Akaike’s information criterion. Overall noise level Laying date (N = 542) d+t 3523Æ81 0Æ00 0Æ52 (Noise), distance to the highway (dH), tree d 3525Æ61 1Æ80 0Æ21 diameter (d), tree density (t) and percentage Noise+d+t 3526Æ86 3Æ06 0Æ11 of deciduous trees (%d) were entered as main Clutch size (N = 505) Noise+d 1727Æ51 0Æ00 0Æ32 effects in mixed models. Only models with a Noise+d+t 1727Æ92 0Æ41 0Æ26 D AIC < 4Æ0 are shown for each life history Noise 1729Æ43 1Æ92 0Æ12 trait d 1730Æ05 2Æ54 0Æ09 d+t 1730Æ41 2Æ90 0Æ07 Noise+t 1730Æ41 2Æ90 0Æ07 Number of hatchlings (N = 470) d 917Æ53 0Æ00 0Æ36 d+t 917Æ71 0Æ18 0Æ33 Null 920Æ18 2Æ65 0Æ10 t 921Æ05 3Æ53 0Æ06 Noise+d 921Æ19 3Æ66 0Æ06 Noise+d+t 921Æ38 3Æ85 0Æ05 Number of fledglings (N = 387) d 1956Æ24 0Æ00 0Æ29 d+t 1956Æ65 0Æ42 0Æ24 Noise+d 1957Æ61 1Æ37 0Æ15 Noise+d+t 1958Æ08 1Æ85 0Æ12 Null 1958Æ98 2Æ74 0Æ07 t 1959Æ22 2Æ99 0Æ07 Fledging mass (N = 215) Noise+d+t+%d 2070Æ29 0Æ00 0Æ52 Noise+d+t 2072Æ26 1Æ96 0Æ19 Noise+d+t+dH+%d 2072Æ86 2Æ57 0Æ14

overall noise and noise in the 0Æ5and1Æ0 kHz band also Table 3. Results from model selection procedure showing selection received moderate support (Table 6a). Noise in the 2 kHz probabilities (calculated across the whole model set) and parameter estimates (using a subset of the models with D AIC < 4Æ0 and model band frequency range overlaps the lower part of great tit song averaging procedures; see text and Table 2). Only factors that were in our study population and had a negative effect on the num- used for model averaging are shown ber of eggs laid by females (Table 6b).

Dependent trait ⁄ independent Selection parameter probability B SE Discussion

Laying date We recorded high traffic noise levels in forest bird breeding Tree diameter 0Æ92 )107 392 habitat related to the proximity of a motorway. However, we Tree density 0Æ70 0Æ34 0Æ93 also found spatial variation in noise levels independent of Noise 0Æ18 0Æ044 0Æ075 distance to the motorway that allowed us to demonstrate a Clutch size negative relationship between noise levels and the reproductive Noise 0Æ80 )0Æ053 0Æ021 success of great tits. Furthermore, noise levels varied substan- Tree diameter 0Æ75 0Æ18 1Æ23 tially with the time of day, season and weather conditions, and Tree density 0Æ42 0Æ17 0Æ25 both temporal and spectral overlap with vocalizing birds is Number of hatchlings high under a wide range of conditions. Finally, we found noise Tree diameter 0Æ81 0Æ72 1Æ64 levels in April to have a negative effect on the number of fledg- Tree density 0Æ46 )0Æ05 0Æ35 Noise 0Æ14 )0Æ039 0Æ030 lings, while noise variation in the frequency with most spectral overlap with great tit song best predicted a negative effect on Number of fledglings Tree diameter 0Æ80 )0Æ75 0Æ83 clutch size. Tree density 0Æ45 )0Æ18 0Æ15 Noise 0Æ33 )0Æ044 0Æ020 EXPLAINING NOISE IMPACT ON REPRODUCTIVE Fledging mass SUCCESS Tree diameter 0Æ99 145Æ1 151Æ7 Tree density 0Æ99 )10Æ87 26Æ96 We found an impact of traffic noise on avian reproductive suc- ) Noise 0Æ93 3Æ14 2Æ67 cess manifest by smaller clutches and fewer fledged chicks in Distance to highway 0Æ22 0Æ005 0Æ11 the noisier areas. We also explored relationships between Percentage deciduous 0Æ16 0Æ56 0Æ39 breeding traits and temporal and spectral overlap of noise,

2010 The Authors. Journal of Applied Ecology 2010 British Ecological Society, Journal of Applied Ecology, 48,210–219 Traffic noise and avian reproductive success 217

Table 4. Results from model selection procedure focusing on temporal variation in noise. Models as used in Table 2 were adjusted to include noise levels recorded either in March or April

Dependent trait Model AIC D AIC Akaike weight

Laying date (N = 542) d+t 3523Æ81 0 0Æ52 d 3525Æ61 1Æ80 0Æ21 Noise April+d+t 3527Æ03 3Æ23 0Æ10 Noise March+d+t 3527Æ30 3Æ49 0Æ09 Noise April+d 3528Æ85 5Æ05 0Æ04 Noise March+d 3529Æ14 5Æ34 0Æ04 Clutch size (N = 505) Noise March+d 1725Æ97 0 0Æ25 Noise April+d 1726Æ20 0Æ23 0Æ22 Noise April+d+t 1726Æ56 0Æ59 0Æ19 Noise March+d+t 1726Æ79 0Æ82 0Æ17 Noise March 1728Æ05 2Æ08 0Æ09 Noise April 1728Æ11 2Æ14 0Æ09 Number of hatchlings (N = 470) d 917Æ53 0 0Æ36 d+t 917Æ71 0Æ18 0Æ33 Null 920Æ18 2Æ65 0Æ09 t 921Æ05 3Æ53 0Æ06 Number of fledglings (N = 387) Noise April+d 1955Æ34 0 0Æ32 Noise April+d+t 1956Æ08 0Æ74 0Æ22 d 1956Æ24 0Æ89 0Æ21 d+t 1956Æ65 1Æ31 0Æ17 Fledging mass (N = 215) Noise April+d+t+%d 2070Æ16 0 0Æ39 Noise Marchl+d+t+%d 2071Æ12 0Æ96 0Æ24 Noise April+d+t 2072Æ30 2Æ14 0Æ13 Noise March+d+t 2073Æ01 2Æ85 0Æ09 Noise April+d+t+dH+%d 2073Æ13 2Æ97 0Æ09 Noise March+d+t+dH+%d 2073Æ84 3Æ68 0Æ06

Table 5. Temporal variation in noise is related to breeding The first explanation is related to interference with acoustic performance. Selection probabilities and parameter estimates of assessment of mate quality. Female birds are known to rely on noise recorded either in March or April from model selection song in assessment of male quality and subsequent investment procedures are shown (see text and Table 4) decisions (Holveck & Riebel 2009). High noise levels could Noise reduce perceived song quality and cause females to breed later, parameter allocate less energy to the eggs or provide less maternal care to (sampling Selection the chicks. Our data show that spectral overlap between noise Dependent trait period) probability B SE and great tit song best predicts patterns in clutch size, suggest- Laying date March 0Æ13 0,007 0,050 ing that noise may indeed interfere with song-based assessment April 0Æ14 0,024 0,059 of male quality and subsequently lower female investment. The second explanation for the effect of traffic noise on Clutch size March 0Æ50 )0,038 0,020 April 0Æ50 )0Æ040 0Æ020 reproductive success could be related to the non-random dis- tribution of individuals across the habitat. Birds may per- Number of hatchlings March 0Æ07 )0Æ027 0Æ027 April 0Æ09 )0Æ032 0Æ029 ceive a noisy territory as being of lesser quality (Slabbekoorn & Ripmeester 2008) and therefore try to avoid these areas. Number of fledglings March 0Æ08 )0Æ033 0Æ019 For instance, both Reijnen & Foppen (1991) and Habib, April 0Æ55 )0Æ051 0Æ019 Bayne & Boutin (2007) found less experienced birds breeding ) Fledging mass March 0Æ39 1Æ97 1Æ80 in more noisy territories. We did not find traffic noise or April 0Æ61 )3Æ16 2Æ48 clutch size to covary with female age and we have no insight into distribution and performance of lower quality individu- als (e.g. immigrants, who are known to produce smaller which could provide some insight into the mechanisms by clutches; Kluyver 1951), but it is likely that noise may play which birds are affected. We believe there are at least four an important role at the time that individuals are settling possible mechanisms, all related to signal masking to some and defending territories. degree, which could explain how anthropogenic noise has a The third explanation is that increased noise levels could negative impact on avian reproductive success. also cause physiological stress due to reduced foraging

2010 The Authors. Journal of Applied Ecology 2010 British Ecological Society, Journal of Applied Ecology, 48, 210–219 218 W. Halfwerk et al.

Table 6. Spectral overlap between noise and song predicts clutch size. study reveals a high level of heterogeneity at a local scale that a) model selection using clutch size models with strong support in should be taken into account when trying to understand the previous analysis (see text and Table 2). Only models with a D impact of noise on bird breeding populations. AIC < 4Æ0 are shown. b) Selection probabilities for noise in different frequency ranges and parameter estimates after model averaging. In addition to revealing the pattern of noise heterogeneity, Only results for noise variables are shown we were able to provide some insight into the causal explana- tions for the noise variation in space, time, and frequency. We a) found substantial spatial variation throughout our study area that was not related to the distance to the motorway. The effect Akaike Model (Noise frequency range) AIC D AIC weight was most pronounced at a few hundred metres from the motorway, with nearby areas differing by over 9 dB in mean 2 kHz band+d+t 1726Æ59 0 0Æ28 noise levels. Transmission of traffic noise is known to depend overall (A-weighted)+d+t 1727Æ92 1Æ33 0Æ15 on motorway architecture, and ground and vegetation struc- 0Æ5 kHz band+d+t 1728Æ14 1Æ54 0Æ13 ture (Bucur 2006). However, the architecture of the motorway 1 kHz band+d+t 1728Æ62 2Æ02 0Æ10 does not vary over the length adjacent to our study area and 4 kHz band+d+t 1729Æ57 2Æ98 0Æ06 2 kHz band+d 1730Æ27 3Æ67 0Æ05 the spatial noise heterogeneity that we found is most likely to b) be caused by variation in tree densities in the areas close to the motorway (Padgham 2004). Noise levels close to the motorway Selection source are known to depend on traffic load (Parris & Schneider probability Noise frequency range BSE 2009) which can vary between day and night, and between weekdays and the weekend (Bautista et al. 2004). Noise ampli- 2 kHz band 0Æ38 )0Æ058 0Æ016 overall (A-weighted) 0Æ20 )0Æ053 0Æ021 tude is also strongly related to traffic speed (Makarewicz & Ko- 0Æ5 kHz band 0Æ18 )0Æ070 0Æ022 kowski 2007), which is probably why we did not detect a clear 1 kHz band 0Æ15 )0Æ064 0Æ018 rush-hour peak in noise, because traffic during the rush-hour is 4 kHz band 0Æ09 )0Æ069 0Æ027 often much slower or even stationary. Finally, we not only con- firmed that lower frequency sounds were transmitted over a larger area than higher frequency sounds but that relatively low frequencies were also more influenced by changing opportunities, because prey are less easy to detect (Schaub, weather conditions. Ostwald & Siemers 2008), or because more time has to be spent scanning for predators (Quinn et al. 2006). Individuals living Conclusions in noisy areas may therefore have less energy to invest in their eggs and offspring. We have shown that traffic noise levels in roadside forest vary And finally, the fourth explanation could be that noise can substantially in space, time and frequency, which allowed us to have an impact on parent-offspring communication and adults reveal a negative relationship with reproductive success in a may therefore not be able to meet their chicks’ demands (Leon- common species. Great tit females laid fewer eggs and pairs ard & Horn 2008). We did not find a significant effect on fledg- fledged fewer young in noisier areas. As the impact of noise is ing mass, but we did find that high noise levels in April have a potentially even higher for species vocalizing at lower frequen- negative effect on the number of fledglings, independent of cies than great tits our data could have significance for the con- clutch size. Whether this is related to higher stress levels, servation of species that are less abundant or under threat. reduced foraging or decreased communication is difficult to Consequently, we believe that integration of data on species- disentangle, but it does suggest that noise interference could specific acoustic behaviour with noise prediction models and affect food provisioning to the chicks. actual field measurements could be a useful approach in exploring ways to protect threatened birds in noise-polluted wildlife sanctuaries. EXPLAINING TRAFFIC NOISE HETEROGENEITY Mitigation measures to reduce the negative impact of noise The opportunity to test for an impact of traffic noise on avian on breeding birds could include sound barriers (Slabbekoorn & reproductive success relied on the heterogeneity of noise levels Ripmeester 2008), alternative, more sound-efficient transport independent of distance to the motorway. Many earlier studies by buses through nature reserves (Laube & Stout 2000) or clos- have designed ways to predict spatial and temporal variation ing roads during acoustically critical phases in the breeding of traffic noise, using a combination of field data and theoreti- cycle (Groot Bruinderink et al. 2002). Traffic noise could also cal modelling (Steele 2001). However, these models have be reduced by introducing a ‘noise tax’ for a given time of day or tended to focus either on noise data at the source (taking traffic season based on the type of car or tyres and the average vehicle and road variables into account; e.g. Li et al. 2002; Parris & speed – factors that are known to affect noise levels (Mak- Schneider 2009) or on transmission data (e.g. Ovenden, Shaffer arewicz & Kokowski 2007). It is clear that the trade-off between & Fernando 2009). The few models that have integrated these ecological and economic values will play a crucial role in the aspects have assumed that the areas adjacent to motorways are implementation of these kinds of applications. Furthermore, environmentally homogeneous (Steele 2001). In contrast, our sufficient insight into species-specific acoustic behaviour and

2010 The Authors. Journal of Applied Ecology 2010 British Ecological Society, Journal of Applied Ecology, 48,210–219 Traffic noise and avian reproductive success 219 noise distribution data is typically still lacking. Nevertheless, we Laube, M.M. & Stout, R.W. (2000) Grand Canyon National Park – assessment hope our results help to raise awareness of the potentially nega- of transportation alternatives. Transit: Planning, Intermodal Facilities, Man- agement, and Marketing, 1735, 59–69. tive impact of anthropogenic noise on breeding birds in general. Leonard, M.L. & Horn, A.G. (2008) Does ambient noise affect growth and beg- ging call structure in nestling birds? Behavioral Ecology, 19, 502–507. Li, B.G., Tao, S., Dawson, R.W., Cao, J. & Lam, K. (2002) A GIS based road Acknowledgements traffic noise prediction model. Applied Acoustics, 63, 679–691. Makarewicz, R. & Kokowski, P. (2007) Prediction of noise changes due to traf- We thank C. ten Cate, H. Kunc and three anonymous referees for critically fic speed control. Journal of the Acoustical Society of America, 122,2074– reviewing previous versions of the manuscript. This study was funded through 2081. a NWO grant (no. 817Æ01Æ003) to H.S and material support from the ‘Dobberke Mockford, E.J. & Marshall, R.C. (2009) Effects of urban noise on song and stichting’ to W.H. response behaviour in great tits. Proceedings of the Royal Society B-Biologi- cal Sciences, 276, 2979–2985. Ovenden, N.C., Shaffer, S.R. & Fernando, H.J.S. (2009) Impact of meteorolog- References ical conditions on noise propagation from freeway corridors. Journal of the Acoustical Society of America, 126, 25–35. Barber, J.R., Crooks, K.R. & Fristrup, K.M. (2009) The costs of chronic noise Padgham, M. (2004) Reverberation and frequency attenuation in forests–impli- exposure for terrestrial organisms. Trends in Ecology & Evolution, 25,180– cations for acoustic communication in animals. Journal of the Acoustical 189. Society of America, 115, 402–410. Bautista, L.M., Garcia, J.T., Calmaestra, R.G., Palacin, C., Martin, C.A., Parris, K.M. & Schneider, A. (2009) Impacts of traffic noise and traffic volume Morales, M.B., Bonal, R. & Vinuela, J. (2004) Effect of weekend road traffic on birds of roadside habitats. Ecology and Society, 14,29. on the use of space by raptors. Conservation Biology, 18, 726–732. Pohl, N.U., Slabbekoorn, H., Klump, G.M. & Langemann, U. (2009) Effects Bayne, E.M., Habib, L. & Boutin, S. (2008) Impacts of Chronic Anthropogenic of signal features and environmental noise on signal detection in the great tit, Noise from Energy-Sector Activity on Abundance of Songbirds in the Boreal Parus major. Animal Behaviour, 78, 1293–1300. Forest. Conservation Biology, 22, 1186–1193. Quinn, J.L., Whittingham, M.J., Butler, S.J. & Cresswell, W. (2006) Noise, pre- Bee, M.A. & Swanson, E.M. (2007) Auditory masking of anuran advertisement dation risk compensation and vigilance in the chaffinch Fringilla coelebs. calls by road traffic noise. Animal Behaviour, 74, 1765–1776. Journal of Avian Biology, 37, 601–608. Bradbury, J.W. & Vehrencamp, S.L. (1998) Principles of Animal Communica- Reijnen, R. & Foppen, R. (1991) Effect of road traffic on the breeding site tion. Sinauer Associates, Sunderland, MA. tenacity of male willow warblers (Phylloscopus trochilus). Journal Fur Orni- Brumm, H. & Slabbekoorn, H. (2005) Acoustic communication in noise. thologie, 132, 291–295. Advances in the Study of Behavior, Vol 35 (eds P.J.B. Slater, C.T. Snowdown, Reijnen, R., Foppen, R., Terbraak, C. & Thissen, J. (1995) The effects of car traf- H.J. Brockmann & M. Naguib), pp. 151–209. Elsevier Academic Press, San fic on breeding bird populations in woodland. 3. Reduction of density in rela- Diego, USA. tion to the proximity of main roads. Journal of Applied Ecology, 32, 187–202. Bucur, V. (2006) Urban Forest Acoustics. Springer-Verlag, Berlin, Heidelberg. Schaub, A., Ostwald, J. & Siemers, B.M. (2008) Foraging bats avoid noise. Burnham, K.P. & Anderson, D.R. (2002) Model Selection and Multimodel Journal of Experimental Biology, 211, 3174–3180. Inference: A Practical-Theoretic Approach, 2nd edn. Springer-Verlag, Berlin. Slabbekoorn, H. & den Boer-Visser, A. (2006) Cities change the songs of birds. Catchpole, C.K. & Slater, P.J.B. (2008) Bird Song: Biological Themes and Vari- Current Biology, 16, 2326–2331. ations. Cambridge University Press, Cambridge. Slabbekoorn, H. & Halfwerk, W. (2009) Behavioural ecology: noise annoys at Drent, P.J. (1987) The importance of nestboxes for territory settlement, sur- community level. Current Biology, 19,R693–R695. vival and density of the great tit. ARDEA, 75,59–71. Slabbekoorn, H. & Peet, M. (2003) Ecology: birds sing at a higher pitch in Forman, R.T.T. (2000) Estimate of the area affected ecologically by the road urban noise. Nature, 424, 267–267. system in the United States. Conservation Biology, 14, 31–35. Slabbekoorn, H. & Ripmeester, E.A.P. (2008) Birdsong and anthropogenic Francis, C.D., Ortega, C.P. & Cruz, A. (2009) Cumulative consequences of noise: implications and applications for conservation. Molecular Ecology, noise pollution: noise changes avian communities and species interactions. 17, 72–83. Current Biology, 19, 1415–1419. Steele, C. (2001) A critical review of some traffic noise prediction models. Garamszegi, L.Z., Calhim, S., Dochtermann, N., Hegyi, G., Hurd, P.L., Jor- Applied Acoustics, 62, 271–287. gensen, C., Kutsukake, N., Lajeunesse, M.J., Pollard, K.A., Schielzeth, H., Stone, E. (2000) Separating the noise from the noise: a finding in support of the Symonds, M.R.E. & Nakagawa, S. (2009) Changing philosophies and tools ‘‘Niche Hypothesis,’’ that birds are influenced by human-induced noise in for statistical inferences in behavioral ecology. Behavioral Ecology, 20,1363– natural habitats. Anthrozoos, 13, 225–231. 1375. Warren, P.S., Katti, M., Ermann, M. & Brazel, A. (2006) Urban bioacoustics: Groot Bruinderink, G.W.T.A., Brandjes, G.J., van Eekelen, R., Niewold, it’s not just noise. Animal Behaviour, 71, 491–502. F.J.J., ten Den, P.G.A. & Waardenburg, H.W. (2002) Faunabeheerplan Na- Whittingham, M.J., Swetnam, R.D., Wilson, J.D., Chamberlain, D.E. & tionaal Park Sallandse Heuvelrug i.o. Alterra, Research Instituut voor de Freckleton, R.P. (2005) Habitat selection by yellowhammers Emberiza citri- Groene Ruimte, Wageningen. nella on lowland farmland at two spatial scales: implications for conserva- Habib, L., Bayne, E.M. & Boutin, S. (2007) Chronic industrial noise affects tion management. Journal of Applied Ecology, 42, 270–280. pairing success and age structure of ovenbirds Seiurus aurocapilla. Journal of Wiley, R.H. & Richards, D.G. (1978) Physical constraints on acoustic commu- Applied Ecology, 44, 176–184. nication in atmosphere – implications for evolution of animal vocalizations. Halfwerk, W. & Slabbekoorn, H. (2009) A behavioural mechanism explaining Behavioral Ecology and Sociobiology, 3, 69–94. noise-dependent frequency use in urban birdsong. Animal Behaviour, 78, Wilkin, T.A., Garant, D., Gosler, A.G. & Sheldon, B.C. (2006) Density effects 1301–1307. on life-history traits in a wild population of the great tit Parus major:analy- Holveck, M.J. & Riebel, K. (2009) Low-quality females prefer low-quality ses of long-term data with GIS techniques. Journal of Animal Ecology, 75, males when choosing a mate. Proceedings of the Royal Society B-Biological 604–615. Sciences, 277, 153–160. van der Zande, A.N., ter Keurs, W.J. & van der Weijden, W.J. (1980) The Junker-Bornholdt, R., Wagner, M., Zimmermann, M., Simonis, S., Schmidt, impact of roads on the densities of four bird species in an open field habitat – K.H. & Wiltschko, W. (1998) The impact of a motorway in construction and evidence of a long-distance effect. Biological Conservation, 18, 299–321. after opening to traffic on the breeding biology of Great Tit (Parus major) and Blue Tit (P. caeruleus). Journal Fur Ornithologie, 139, 131–139. Received 8 July 2010; accepted 2 November 2010 Kluyver, H.N. (1951) The population ecology of the great tit, Parus major L. Handling Editor: Mark Whittingham ARDEA, 39,1–135.

2010 The Authors. Journal of Applied Ecology 2010 British Ecological Society, Journal of Applied Ecology, 48, 210–219

Mitigation Measures for Highway-caused Impacts to Birds1

Sandra L. Jacobson2 ______Abstract Highways cause significant impacts to birds in four (Keller et al. 1996). However, highway impacts to ways: direct mortality, indirect mortality, habitat frag- birds occur in four major ways, some of which are mentation, and disturbance. In this paper I discuss unique to birds: by fragmentation, disturbance, and highway-related impacts, and suggest solutions from a direct and indirect mortality. These impacts could have highway management perspective. Non-flying birds considerable negative effects on populations, especially (either behaviorally or structurally) such as gallina- when considered in combination with other sources of ceous birds and ducklings; waterbirds such as terns; mortality and habitat loss. The mitigation measures owls; ground-nesters; scavengers; Neotropical over- reviewed here have the potential to reduce impacts to water migrants; frugivorous birds; and birds attracted birds from all four categories. to salt are often killed from highway-related causes. Suggested solutions include highway crossing struc- Many mitigation techniques reviewed in this paper tures, diversion poles on bridges or medians, modified have been developed for other taxa, particularly ungu- right-of-way mowing regimes, road kill removal, lates and large carnivores, but are applicable to birds as appropriate median vegetation, and modified deicing well. Further information on the projects from which agents. Indirect mortalities caused by highway con- these suggested solutions are drawn can be found at the struction or maintenance include habitat loss and USDA Forest Service’s ‘Wildlife Crossings Toolkit’ at decreased quality; predator attraction or bridges to http://www.wildlifecrossings.info. This database is the nesting habitat; increased incidence of invasive spe- most complete compilation available of case histories cies; increased associated lethal structures; and main- of highway impact mitigation for all taxa. It includes a tenance practices that disrupt reproduction. Suggested glossary for biologists unfamiliar with highway infra- 3 solutions include highway management strategies that structure terminology . consider avian needs. Several publications have reviewed highway impacts to birds, with most focusing on direct mortality and few offering suggestions for mitigation. A thorough review Key words: birds, direct mortality, disturbance, frag- of impacts of linear developments, including highways, mentation, highway, indirect mortality, mitigation, to birds and other wildlife is found in Jalkotzy et al. vehicle-animal collision, wildlife crossing structure. (1997); suggested mitigation measures focus on large mammals. Forman and Hersperger (1996) review miti- gation measures for most taxa, but include relatively little information on measures effective for birds. A re- view of the impact of forest roads on wildlife, including Introduction some information on birds, is in Gucinski et al. (2000). As the most mobile of terrestrial wildlife, birds are not The current transportation paradigm dictates that high- often considered significantly affected by highways ways will continue to be built and expanded to meet increasing transportation needs, and impacts to birds ______and other wildlife will continue as a result. No mitiga-

1 tion by itself or in combination with others can totally A version of this paper was presented at the Third Interna- remove the impacts to wildlife. Several methods sug- tional Partners in Flight Conference, March 20-24, 2002, Asilomar Conference Grounds, California. gested here might reduce impacts to birds, however, 2USDA Forest Service, Redwood Sciences Laboratory, Pacific and are based on successes with other taxa. Expensive Southwest Research Station, 1700 Bayview Drive, Arcata, CA structural mitigation techniques such as wildlife over- 95521. E-mail: [email protected]. crossings are unlikely to be initiated to mitigate avian 3 The purpose of the website is to provide a database of known impacts alone, but additional benefits to birds might mitigation techniques for terrestrial wildlife for use by profes- raise the benefit/cost ratio. The first step to reducing sional biologists and highway engineers. The Wildlife Crossings Toolkit was developed by a partnership of the USDA Forest the impacts of highways on birds through improved Service’s San Dimas Technology and Development Center, Utah highway design and retroactive mitigations is to under- State University’s College of Natural Resources. Montana State stand how highways affect birds. In this paper I review University-Bozeman’s Western Transportation Institute, and the Federal Highway Administration.

USDA Forest Service Gen. Tech. Rep. PSW-GTR-191. 2005 1043 Impacts of Highways on Birds - Jacobson the current state of knowledge regarding these impacts Planning the location of a highway to avoid environ- and effective mitigations. mental as well as construction costs may be the simplest but least considered solution. If the lands crossed are public lands, then an environmental analysis might develop an alternative that keeps habitat Fragmentation patches intact over one that bisects them. The public’s Highways can fragment bird populations and habitats role as stakeholders in this process is very important in three ways: loss of large carnivores, habitat dissec- because many public land managers are still awakening tion, and the isolation of less mobile species (table 1). to the avoidable impacts of highway design. Loss of Large Carnivores Crossing structures can be a tool to reduce impacts. Structures that are high, wide and open tend to retain When highways fragment large carnivore populations, the most functional ecosystems (Ruediger 2002). birds can suffer increased depredation from smaller Causeways, viaducts, and expanded bridges provide carnivores such as bobcats, skunks and weasels the most opportunities for birds to cross under a high- (Crooks and Soulé 1999). Many structural designs for way because of their openness and the surrounding encouraging large carnivores to cross highways have vegetation is usually continuous under the structure. In been developed, and are being increasingly if not uni- Europe, woodland bird species use wildlife over- versally considered in appropriate highway projects. crossings with planted vegetation significantly more to Large underpasses or extended bridges are used suc- cross highways than direct overflights, and in some cessfully for such species as Florida panthers (Puma cases have incorporated the over-crossing into territo- concolor coryi), black bears (Ursus americanus), and ries (Keller et al. 1996). wolves (Canis spp.) (Foster and Humphrey 1995; Roof and Wooding 1996; Clevenger and Waltho 2000). In Isolation most cases, barrier fencing is needed to encourage these highly mobile species to use the prepared Highways can isolate small populations or individuals crossing. because of habitat dissection. Isolation is a variant of habitat dissection, but it also includes those situations Habitat Dissection where a portion of a daily or annual habitat is difficult or dangerous to access because of the presence of a Highways are designed to minimize costs. These routes highway. The tendency of Mountain (Oreortyx picta) are often the shortest distance between two points, in and California (Lophortyx californica) quail to avoid areas without human development to avoid the cost of large openings (Gutierrez 1980) may make seasonal land acquisition and to avoid noise effects to homes, habitat virtually unavailable if multiple-lane, high vol- and with minimal elevation changes. This may result in ume highways bisect seasonal or daily movements, and rare habitats such as wetlands being disproportionately their low flight and tight flocking behavior may in- affected by highway development (FHWA 2000). crease the risk of mortality when crossing highways. Habitat dissection may result in patches of habitat too small to complete a territory. Woodland species are Correctly locating crossing structures is critical to their more affected by habitat dissection than grassland effectiveness. Although many wildlife travel along species, which appear to be more willing to cross ridges and drainages, some animals, such as Mountain highways as part of their territories (Keller et al. 1996). Quail, might have consistent but less obvious cross- ings. Knowing the location of frequent crossings can help situate the most effective structure.

Table 1— Fragmentation impacts to birds from highways.

Impact Problem Suggested solution Loss of large carnivores Increased small carnivores prey Highway crossing structures for large disproportionately on birds. carnivores. Habitat dissection Habitat parcels are too small to Avoid dissection by highway placement. contain complete territories. Use causeways or viaducts to maintain small scale habitat continuity. Isolation Highways are barriers to less Overall connectivity strategy. mobile or reclusive birds. Use open-span bridges, viaducts or wildlife over-crossings.

USDA Forest Service Gen. Tech. Rep. PSW-GTR-191. 2005 1044 Impacts of Highways on Birds - Jacobson

Disturbance public lands by considering road surface design when constructing or upgrading highways. Disturbance from highways may be most pronounced during the breeding season, but can also affect other Lights life history periods (table 2). One method of migrant navigation is by reference to Noise stars (Emlen 1975). Light pollution from all sources reduces the visibility of stars, and may entrap migrating Territorial song is only effective if it is heard by other birds in dangerous environments especially during birds, and noise from traffic can be so loud that bird inclement weather, causing collision, apparent confu- song may be distorted, resulting in difficulties in at- sion, and mortality (Ogden 1996). Highway lighting tracting and keeping females (Reijnen and Foppen standards are based on the Illuminating Engineering 1994). While the mechanism causing decreased num- Society of North America’s (IES) standards, and newer bers of woodland breeding birds next to highways designs are available that meet the IES standards but (Riejnen and Foppen 1994) is not clearly understood, have reduced light pollution effects. Lower wattage flat noise can disturb birds and render otherwise suitable lens fixtures on highways and city streets direct light habitat next to highways less effective (Reijnen et al. down and reduce glare, thus reducing light pollution. 1995, Stone 2000). Increased predation may also occur They are currently being used in a major retrofitting due to the inability of birds to hear predators project in Calgary, Alberta to reduce light pollution and (Scherzinger 1973). to save money and energy (City of Calgary 2002). Most noise from highways is produced by engines and Increasing the reflectivity of signs and road striping tires as they contact the surface, with noise varying by (retro-reflectivity) is a method of increasing the visibil- tire and surface qualities (FHWA 2000). Noise can be ity of roads to drivers while reducing the need for mitigated by providing a barrier to the source of noise, electrical lighting (Hasson 2000). or reducing the source itself. Because most of the noise derives from the road surface, a change in elevation of the road surface may reduce noise, and cuts and fills Direct Mortality can be used to advantage. Noise barriers are commonly used in city situations and can be seen as large cement Direct mortality is the impact most people likely associ- block walls along city highways. While this effectively ate with highways. Birds are listed as killed most fre- reduces noise in lower vegetation layers, it also elimi- quently in most multiple taxa road mortality studies nates permeability for most essentially non-flying spe- (Forman et al. 2003). One estimate of bird mortalities cies, and is expensive. A variant of the common city from all causes lists vehicle deaths as the fourth or fifth sound wall can be created by less dense material such most numerous at 60 million or more per year in the as wood, vegetation, or fabric. United States, after pesticides and high-power transmis- sion lines (U.S. Fish and Wildlife Service 2002), both of The Federal Highway Administration (FHWA) has which can be associated with highways and cause commissioned much research on environmental noise cumulative impacts. The extent of mortality from high- reduction. Smooth surfaces have been developed to ways is underestimated (as it is in most studies of mor- reduce noise while retaining safe traction control; in tality from man-made structures) because scavengers addition, some tires are much less noisy than others. pick up small bird carcasses rapidly, often within min- Land management agencies could reduce noise through utes (Morris 2002). Bird mortality from vehicle colli- sions affects some groups more than others (table 3).

Table 2— Disturbance impacts to birds from highways.

Impact Problem Suggested solution Noise Noise disrupts song or intimidates shy species. Noise barriers. Reduce noise sources such as tires and road surfaces. Lights Migrants can’t see stars to navigate. Coordinate light-pollution reduction. Ensure lights are necessary before installation. Use lower wattage flat lens fixtures on highways, retroreflective elements on signs and pavement.

USDA Forest Service Gen. Tech. Rep. PSW-GTR-191. 2005 1045 Impacts of Highways on Birds - Jacobson

Table 3— Direct mortality from highways.

Impact Problem Suggested solution Walking birds Non-flying birds incur greater mortality Crossing structures with large openness ratios risk. (underpasses) or wildlife over-crossings. Water birds Winds over bridges can slam flying Diversion poles on bridge decks. birds into vehicles. Owls Owls hunt at headlight height. Diversion poles or short fences along highway medians and rights-of-way. Ground nesters Mowing rights-of-way kills nesters. Mow after August 1. Scavengers Corvids or raptors are killed while Reduce roadkill. foraging on roadkill. Remove roadkill from road. Attracted scavengers reduce productivity adjacent to highways. Migrant landfalls Exhausted cross-gulf migrants fly into Low temporary fences to encourage higher flight vehicles. across roads. Frugivores Fruiting median plants attracts birds Plant non-fruiting varieties. across traffic. Remove fruiting varieties. Winter finches Deicing salt or sand attracts birds to Velocity spreaders. road surface. Road temperature sensors to reduce quantities. Concentrate runoff appropriately. Public education program.

Ground-Dwelling Birds cluded Common Loons (Gavia immer), Peregrine Fal- cons (Falco peregrinus), and Brown Pelicans. Signs Birds that fly infrequently because of morphology, for- warning of the danger of pelican collisions on the aging behavior or age are at greater risk of vehicle col- bridge may not be effective at reducing mortalities (G. lisions because they spend longer time on the roadway, and S. Colley, pers. comm.). and often have a shallow escape flight trajectory. Spe- cies affected include gallinaceous birds, juvenile ana- Owls tids, and Melanerpes woodpeckers foraging on road- killed insects (Stoner 1925). Crossing structures such Several species of owls, particularly Barn Owls (Tyto as open bridges, large V-shaped underpasses, viaducts alba), Great Horned Owls (Bubo virginianus), and or causeways with vegetation maintained beneath high- Short-eared Owls (Asio flammeus), often forage near ways can be used to mitigate impacts to these species. roads at about the same height as vehicle windshields Causeways elevated on pilings or other intermittent and are common victims of vehicle collisions. In the supports across wetlands maintain ecological function Central Valley of California, juvenile Barn Owls suffer better than causeways built on dikes because they al- heavy mortality from vehicles along Interstate 5 and low water flow and uninterrupted movement of marsh- smaller county roads (Moore and Mangel 1996). No land species of all taxa. mitigation has been attempted in this case, however, a concept similar to the Sebastian Inlet State Park barrier Water Birds poles may be effective for owls as well. If so, a low fence or fence material such as plastic construction When bridges are approximately perpendicular to wind fence or closely spaced, frangible reflective highway direction they can cause downdrafts that increase the markers may be effective if installed along highway risk of collisions between birds and traffic or bridge verges and medians. structures. At Sebastian Inlet State Park, Florida, Royal Terns (Sterna maxima) and Brown Pelicans (Pelecanus Ground Nesters occidentalis) suffered mortality particularly during northeasterly winds. In one case, a semi truck killed Birds nesting in highway rights-of-way are vulnerable several Brown Pelicans at once (A. Bard, pers. comm.). to direct mortality due to mowing practices. Most states The installation of aluminum fence poles spaced at mow rights-of-way to maintain sight distances and for intervals along the edge of the bridge created an appar- esthetic reasons. The most vigorous spring growth and ent barrier that caused birds to fly higher, resulting in onset of mowing in May or June coincides with nesting significantly fewer mortalities (Bard et al. 2002). On season. Mowing affects primarily grassland species or Queen Isabella Causeway on South Padre Island, Tex- waterfowl by directly killing eggs, fledglings or adults as, avian mortalities during certain wind directions in- attending nests. An estimated 4,500 ducks are killed on

USDA Forest Service Gen. Tech. Rep. PSW-GTR-191. 2005 1046 Impacts of Highways on Birds - Jacobson highway rights-of-way each year in the prairie pothole traffic, in a manner similar to the Sebastian Inlet State region of North Dakota because about a third of nesting Park approach. ducks have not hatched by the early July mowing (Cook and Daggett 1995). Illinois Department of Frugivores Transportation currently delays mowing until August 1 to protect nesting birds (Cook and Daggett 1995). Frugivores such as Cedar Waxwings (Bombycilla ced- Mowing for esthetic purposes instead of vegetation rorum) and thrushes are attracted to fruiting plants control may be possible to forego. Highway users in grown in highway medians as barriers to vehicles. In several states supported unmowed verges when the many eastern states, thorny eleagnus (Elaeagnus pun- environmental ramifications were explained (Harper- gens) has been planted in medians, causing the attrac- Lore 2000). In addition, naïve fledglings of many tion and death by collision of hundreds of waxwings, species nesting near roadways are vulnerable to American Robins (Turdus migratorius) and Common collisions with passing vehicles. Grackles (Quiscalus quiscula) (Watts and Paxton 2001). Removal of thorny eleagnus is being accom- Scavengers plished in Virginia as a result of the identification of the problem and effective negotiations with the Scavengers such as corvids and raptors are at risk of Virginia DOT. being hit by vehicles as they forage on other road killed carcasses (Mumme 2000). At the same time, because Winter Finches road kills are a reliable source of food, the same avian and mammalian scavengers patrol highways for food, Deicing highways in snow country costs transportation and thus are at higher densities along highways. These agencies considerable expense and time. Solutions to scavengers may then turn to adjacent habitat for other this safety concern are continually being sought. Both foraging opportunities, including nesting birds. In most sand and salt as deicing agents are deadly for gregari- states, the state Department of Transportation (DOTs) ous winter finches such as Pine Siskins (Carduelis is responsible for removing road kills (Cook and pinus) and crossbills (Loxia spp.) when ingested. Salt is Daggett 1995). Where this is the case, it may be helpful highly toxic to birds and causes lethargy or passive es- to encourage agencies to expeditiously follow the pol- cape reactions to vehicles; the combination of salt and icy to remove large animal carcasses, or create one sand sometimes causes massive mortality (Environ- where no policy exists. ment Canada 2001). Solutions are complex but may include continued research into better deicing agents, Migrant Landfalls velocity spreaders, and temperature sensors in road- ways to minimize application rates. In Glacier and Exhausted cross-Gulf migrants can congregate by the Mount Revelstoke National Parks in Canada, visitors thousands at first landfall. Some of these locations are are given a brochure explaining the issue and advising now prime oceanfront real estate with developments motorists to honk their horns at congregated birds to that include highways. In 1996, many cross-Gulf give them time to escape (Morris 2002). migrants were blown off course and landed in the Florida Keys. Florida State Park road kill records indicate a huge number of warblers and vireos that year (Fahrig et al. 2002), suggesting a situation likely to be Indirect Mortality repeated at many other locations. Some normal land- Habitat Loss and Habitat Sinks falls such as the Mississippi and Alabama coastline contain highways immediately adjacent to the nearest Habitat loss to highway development is huge and in- vegetation after shoreline, thus concentrating birds near sidious because highways may facilitate further devel- a high mortality risk (B. Sargent, pers. comm.). While opment. Highways cover about 1 percent of the land land use planning to maintain habitat adjacent to the base of the United States, or an area about the size of shoreline is the ultimate solution, some areas known to South Carolina (Forman 2000). Land use planning, and be mortality hotspots, such as Highway 180 near Fort transportation options such as mass transit, intermodal Morgan, Alabama (B. Sargent, pers. comm.), may need transportation (transportation between public and pri- to be monitored after heavy flights (predictable by vate modes), and intelligent transportation systems are radar images broadly available over the Internet) and urgently needed. It is probably safe to assume that at extraordinary measures taken to prevent birds from least some percentage of that highway growth forever attempting low flights across highways while still alters valuable bird habitat. exhausted. In some of these locations, it might be pos- sible to erect temporary fences or other barriers that en- Highway medians and rights-of-way do provide some courage migrants to fly at some height over passing habitat for species in heavily developed areas, particu- larly grassland species in the eastern states, but it is still

USDA Forest Service Gen. Tech. Rep. PSW-GTR-191. 2005 1047 Impacts of Highways on Birds - Jacobson unknown whether or not these small, linear habitats Act active nests containing eggs or young, or colonies function as overall population sinks or as sources. with at least one such nest, are protected; intermitted take sometimes occurs regardless. On a bridge in Mon- Predator Bridges tana, DOT officials removed Cliff Swallow nests prior to the breeding season and applied a sticky repellent. Land-filled bridges across open waterways can allow The repellent was removed after maintenance was predators to access previously predator-free island sea- completed, limiting the loss of productivity to at most bird nesting colonies. Following the construction of a one year (Wabash et al. 2002). new highway in Norway, foxes, martens and badgers were able to cross to the island of Tuatara on rocky fill Table 4 is a summary of these indirect sources of mor- below the highway. Remedial measures such as noise- tality to birds from highways, associated structures, and makers and an open-grid drawbridge have been unsuc- maintenance activities. cessful to date (Quell 2001). Avoidance of these situations is the best policy. Brood Parasitism and Noxious Species Conclusion There are few data regarding the impacts of highways The expansion of Brown-headed Cowbirds (Molothrus on birds and fewer on the effectiveness of the relatively ater) and several species of noxious plants and animals is few mitigation measures devised to reduce those ef- facilitated by the cleared line of sight along highways, fects. Nationwide, estimates of direct mortality from particularly where these species had been limited by bird-car collisions range from 10 to 380 million (see blocks of unsuitable habitat. Line of sight clearing is a Erickson et al. this volume). These are based on extra- safety measure that normally is a minimum of 10 m (30 polations from local studies, none of which corrected ft). Where cowbird brood parasitism is a concern, large for the unquestionably large bias from carcass sca- blocks of minimally cleared rights-of-way may be part of vengers and searcher efficiency. There are no estimates a suite of mechanisms used to control this species. for the sub chronic effects on populations from habitat Lethal Associated Structures loss, fragmentation, disturbance and other indirect effects of highway construction. Thus, there is a need When associated with highways, powerlines, railroads for systematic efforts to assess these impacts locally and canals are a few structures cumulatively more haz- and nationwide. Without these data, it is difficult to ardous to birds. Vehicle traffic may cause birds to fly promote effective mitigations to highway planners. higher to avoid cars only to collide with parallel power- There might be little to be done to minimize impacts lines. Raptors continue to be electrocuted on power- along the majority of the roughly 4 million miles of lines, possibly in greater numbers along highways roadway in the United States, but protective measures because of the attraction of roadkill scavenging oppor- addressed in this paper and other innovative solutions tunities. Gallinaceous species are attracted to canals in should be attempted along certain highly vulnerable desert areas only to become vehicle mortalities (or locations, e.g. next to wetlands, over rivers, through drowned). Some of these structures can be buried, re- riparian areas, and along migration corridors or fallout located or made safer if planners are aware of the locations. cumulative impacts to birds because of their proximity to highways. The guidelines recommended by the Avi- an Power Line Interactions Committee to minimize electrocutions and collisions should be followed when- Literature Cited ever possible (APLIC 1994, 1996). Avian Power Line Interaction Committee (APLIC). 1994. Mitigating bird collisions with power lines: The state of the art in 1994. Washington, DC: Edison Electric Institute; Maintenance Practices 78 p.

Peregrine Falcons and Cliff Swallows (Hirundo Avian Power Line Interaction Committee (APLIC). 1996. Sug- pyrrhonota), among others, may use bridges as nesting gested practices for raptor protection on power lines: habitat. Bridge maintenance, however, typically occurs The state of the art in 1996. Washington, DC: Edison in warmer seasons, so it can conflict with successful Electric Institute/Raptor Research Foundation; 125 p. nesting. Washington DOT developed specific and strict Bard, A. 2001. Personal communication. Florida Department of protocols to minimize impacts to Peregrine Falcons, Environmental Protection, Apopka, Florida. formerly a State- and Federally-listed endangered spe- cies (Carey 1998). Under the Migratory Bird Treaty

USDA Forest Service Gen. Tech. Rep. PSW-GTR-191. 2005 1048 Impacts of Highways on Birds - Jacobson

Table 4— Indirect mortality from highways.

Impact Problem Suggested solution Habitat loss Highways facilitate development. Land use planning; Mass transit or other change in transportation paradigm. Habitat sink Suitable habitat near highway increases Make habitat unsuitable; mortality. Haze birds away; Reduce mortality through above methods. Predator bridges Bridges or land causeways allow Design to avoid predator crossings; access to nesting islands. Drawbridge or open grid deck on bridge; Noise. Brood parasitism Cowbirds increase along cleared rights- Reduce line-of-sight clearing; of-way. Other cowbird control mechanisms to break continuous pathway. Noxious species Highways facilitate noxious species Plants: herbicides, biological controls; travel. Work with local DOTs to emphasize control. Lethal structures Birds fly into associated structures; Follow APLIC guidelines; Additional structures increase distance Attach visibility markers; to cross. Bury telephone/power lines; Require raptor-safe power poles; Consider cumulative impact of railroads, power lines, canals, frontage roads. Maintenance practices Maintenance often occurs during Maintenance protocols; nesting season. Timing restrictions; Acceptance of one year loss of productivity.

Bard, A. M., H. T. Smith, T. V. Harbor, G. W. Stewart, J. S. Crooks, K. R. and M. E. Soulé. 1999. Mesopredator release Weeks, M. M. Browne, and S. D. Ensile. 2002. Road-killed and avifaunal extinctions in a fragmented system. Nature Royal Terns (Sterna maxima) recovered at Sebastian 400: 563-566. Inlet State Park, Florida, USA: a 23-year analysis of banding data. In: Proceedings of the International Emlen, S. T. 1975. Migration: Orientation and navigation. In: Conference on Ecology and Transportation, 2001 D. S. Farner and J. R. King, eds. Avian Biology, Vol. 5. September 24-28; Keystone, CO. Raleigh, NC: Center for New York, NY: Academic Press; 129-219. Transportation and the Environment, North Carolina State Environment Canada. 2001. Canadian Environmental Protect- University; 386-389. ion Act, 1999: Priority substances list assessment report: Carey, M. 1998. Peregrine Falcons and the Washington state Road salts. Hull, Quebec: Minister of Public Works and Department of Transportation. In: G. L. Evink, P. Government Services. Report available at http://www. Garrett, D. Ziegler, and J. Berry, editors. Proceedings of the ec.gc.ca/substances/ese/eng/psap/final/main.cfm. International Conference on Wildlife Ecology and Trans- Erickson, Wallace, Gregory D. Johnson, and David P. Young, Jr. portation, FL-ER-69-98. Tallahassee, FL: Florida Depart- This volume. A summary and comparison of bird ment of Transportation; 121-125. mortality from anthropogenic causes with an emphasis City of Calgary. 2002. Calgary sheds new light on environ- on collision mortality. mental stewardship: Launch of Envirosmart Streetlights Fahrig, L., K. E. Neill, and J. G. Duquesnel. 2002. Interpret- Retrofit Project. Press release. March 26, 2002. Calgary, ation of joint trends in traffic volume and traffic-related Alberta, Canada. wildlife mortality: A case study from Key Largo, Clevenger, A. P. and N. Waltho. 2000. Factors influencing the Florida. In: Proceedings of the International Conference on effectiveness of wildlife underpasses in Banff National Ecology and Transportation; 2001 September 24-28; Park, Alberta, Canada. Conservation Biology 14: 47-56. Keystone, CO. Raleigh, NC: Center for Transportation and the Environment, North Carolina State University; 518-521. Colley, G. and S. Colley. 2002. Personal communication with Randall Raeder in unpublished (online) Wildlife Crossings Federal Highway Administration (FHWA). 2000. Highway traf- Toolkit (http://www.wildlifecrossings.info), “South Padre fic noise in the U.S.: Problem and response. Washington Island Brown Pelican Flashing Light Signs,” Forest Service, DC: FHWA Department of Transportation; 16 p. plus U.S. Department of Agriculture. appendix. Cook, K. E. and P.-M. Daggett. 1995. Highway roadkill, safety, Forman, R. T. T. 2000. Estimate of the area affected ecol- and associated issues of safety and impact on highway ogically by the road system in the United States. ecotones. Unreviewed report for Task Force on Natural Conservation Biology 14(1): 31-35. Resources, (A1F52), Transportation Research Board, National Research Council; 26 p.

USDA Forest Service Gen. Tech. Rep. PSW-GTR-191. 2005 1049 Impacts of Highways on Birds - Jacobson

Forman, R. T. T. and A. M. Hersperger. 1996. Road ecology Demographic consequences of road mortality in the and road density in different landscapes, with inter- Florida Scrub-Jay. Conservation Biology 14 (2): 501-512. national planning and mitigation solutions. In: G. L. Evink, P. Garrett, D. Ziegler, and J. Berry, editors. Trends Ogden, L. and J. Evans. 1996. Collision course: The hazards of in addressing transportation related wildlife mortality. lighted structures and windows to migrating birds. Publication FL-ER-58-96. Tallahassee, Florida: Florida Toronto, Canada: Report published by the World Wildlife Department of Transportation; 263 p. Fund Canada and Fatal Light Awareness Program; 46 p. Forman, R. T. T., D. Sperling, J. A. Bissonette, A. P. Clevenger, Reijnen, R., R. Foppen, C. T. Braak, and J. Thissen. 1995. The C. D. Cutshall, V. H. Dale, L. Fahrig, R. France, C. R. effects of car traffic on breeding bird populations in Goldman, K. Heanue, J. A. Jones, F. J. Swanson, T. woodland, III. Reductions of density in relation to Turrentine, T. C. Winter. 2003. Road ecology: Science and proximity of main roads. Journal of Applied Ecology 32: solutions. Washington DC: Island Press; (not paginated), 187-202. 481 p. Reijnen, R. 1995. Disturbance by car traffic as a threat to Foster, M. L. and S. R. Humphrey. 1995. Use of highway breeding birds in The Netherlands. Leiden, The underpasses by Florida panthers and other wildlife. Netherlands: Rijksuniversiteit van Leiden. Ph. D. Thesis. Wildlife Society Bulletin 23(1): 95-100. Roof, J. and J. Wooding. 1996. Evaluation of the S.R. 46 Gucinski, H., M. J. Furniss, R. R. Ziemer, and M. H. Brookes. wildlife crossing in Lake County, Florida. In: G. L. 2000. Forest roads: A synthesis of scientific information. Evink, P. Garrett, D. Zeigler and J. Berry, editors. Trends in Gen. Tech. Rep. PNW-GTR-509. Portland, OR: Pacific addressing transportation related wildlife mortality. Public- Northwest Research Station, Forest Service U.S. Depart- ation FL-ER-58-96. Tallahassee, Florida: Florida Depart- ment of Agriculture; 117 p. ment of Transportation. Gutierrez, R J. 1980. Comparative ecology of the Mountain Ruediger, B. 2002. High, wide and handsome: Designing more and California Quail in the Carmel Valley, California. effective wildlife and fish crossings for roads and Living Bird 18: 71-93. highways. In: Proceedings of the International Conference on Ecology and Transportation; 2001 September 24-28; Key- Harper-Lore, B. 2000. Incorporating grasses into clear zones. In: stone, CO. Raleigh, NC: Center for Transportation and the B. Harper-Lore and M. Wilson, eds. Roadside use of native Environment, North Carolina State University; 509-516. plants. U.S. Department of Transportation, Federal Highway Administration, sponsor. Covelo, CA: Island Press. Sargent, R.. 2003. Personal communication. Director, Hummer/ Bird Study Group, Inc. bird-banding station at Fort Morgan, Hasson, P. 2000. Bringing the nighttime road to life. WST2: Alabama. Washington State Technology Transfer, WSDOT Issue 68. Available at: http://www.usroads.com/journals/rmej/0109/ Scherzinger, W. 1979. Zum Feindverhalten des Haselhuhnes rm010902.htm. Banasia bonasia. Die Vogelwelt 100: 205-217 as cited in Reijnen, Rien. 1995. Disturbance by car traffic as a threat to Iuell, B. 2002. Prevention of unwanted species immigrating to breeding birds in The Netherlands. Rijksuniversiteit van islands on strait crossings. In: Proceedings of the Leiden. Ph. D. Thesis. International Conference on Ecology and Transportation; September 24-28, 2001; Keystone, CO. Raleigh, NC: Stone, E. 2000. Separating the noise from the noise: A finding Center for Transportation and the Environment, North in support of the "Niche Hypothesis," that birds are Carolina State University; 376-384. influenced by human-induced noise in natural habitats. Anthrozoos 13(4): 225-231. Jalkotszy, M. G., P. I. Ross, and M. D. Nasserden. 1997. The effects of linear developments on wildlife: A review of Stoner, D. 1925. The toll of the automobile. Science 61: 56-57. selected scientific literature. Prepared for Canadian U. S. Fish and Wildlife Service (USFWS). 2002. Migratory Association of Petroleum Producers. Calgary, Canada: Arc bird mortality: Many human-caused threats afflict our Wildlife Services, Ltd.; 115 p. bird populations. Brochure. Arlington, VA: Division of Keller, V., H.-G. Bauer, H.-W. Ley, and H. P. Pfister. 1996. The Migratory Bird Management, Fish and Wildlife Service, significance of wildlife overpasses for birds. Der Ornith- U.S. Department of the Interior; 2 p. ologische Beobachter 93: 249-258. Wambach, D. A., M. A. Traxler, and K. Eakin. 2002. Montana Moore, T. G. and M. Mangel. 1996. Traffic related mortality Department of Transportation: A fine feathered friend. and the effects on local populations of Barn Owls, Tyto In: Proceedings of the International Conference on Ecology alba. In: G. L. Evink, P. Garrett, D. Ziegler, and J. Berry, and Transportation; 2001 September 24-28; Keystone, CO. editors. Trends in addressing transportation related wildlife Raleigh, NC: Center for Transportation and the Environ- mortality. Publication FL-ER-58-96. Tallahassee, Florida: ment, North Carolina State University; 546-548. Florida Department of Transportation; (not paginated) 263 Watts, B. D. and B. J. Paxton. 2001. The influence of thorny p. eleagnus on automobile-induced bird mortality. Virginia Morris, M. 2002. Grill bird alert. Parks Canada. (Brochure on Transportation Research Council publication VTCR 01- avoiding birds attracted to highways by salt and sand.) CR2. Williamsburg, VA: Center for Conservation Biology, College of William and Mary. Mumme, R. L., S. J. Schoech, G. E. Woolfenden, and J. W. Fitzpatrick. 2000. Life and death in the fast lane: Wildlife Crossings Toolkit website: http://www.wildlifecrossings. info. Last accessed 21 June 2004.

USDA Forest Service Gen. Tech. Rep. PSW-GTR-191. 2005 1050 bs_bs_bannerJournal of Zoology

Journal of Zoology. Print ISSN 0952-8369 Avoidance of roads by large herbivores and its relation to disturbance intensity M. Leblond1, C. Dussault2 & J. –P. Ouellet1

1 Département de Biologie, Chimie & Géographie, Université du Québec à Rimouski, Rimouski, QC, Canada 2 Service de la faune terrestre et de l’avifaune, Ministère des Ressources naturelles et de la Faune du Québec, Québec, QC, Canada

Keywords Abstract anthropogenic disturbance; habitat fragmentation; human activity; road ecology; Avoidance of roads has been demonstrated for many animal species, but little is road-effect zone; traffic. known about the relationship between anthropogenic disturbance levels and the degree of avoidance by animals. We investigated the hypothesis that the strength Correspondence of road-avoidance behaviour increases with the intensity of the disturbance for a Mathieu Leblond, Département de Biologie, large, disturbance-sensitive herbivore: the forest-dwelling caribou Rangifer taran- Chimie et Géographie, Université du dus caribou. We assessed the behaviour of 53 global positioning system-collared Québec à Rimouski, 300 Allée des caribou monitored during the gradual modification of a highway over a 7-year Ursulines, Rimouski, QC, Canada, G5L3A1. period, while controlling for potentially confounding factors. We studied caribou Tel: + 418 723 1986 #1968; Fax: + 418 724 movements, resource selection and distribution before, during and after road 1525; Email: [email protected] modifications at multiple scales. We expected that the degree of avoidance would be positively related to road width, traffic density and the presence of active Editor: Virginia Hayssen construction sites. The proportion of individuals that excluded the highway from their home range increased as highway modifications progressed. A lower propor- Received 26 March 2012; revised 28 June tion of caribou locations was found in a 5000 m road-effect zone during and after 2012; accepted 12 July 2012 highway modifications compared with before. Within that zone, caribou avoided habitat types that were selected at the home range scale. Caribou displayed higher doi:10.1111/j.1469-7998.2012.00959.x movement rates in the vicinity of the highway, especially when traffic density was high. Our data support the hypothesis that avoidance of roads by large herbivores is positively related to disturbance intensity. Our results shed light on the behav- ioural mechanisms determining avoidance of human infrastructure by large her- bivores, and suggest that increased human activity may affect behaviour at multiple scales. Conservation efforts in areas where roads are constructed or modified should be directed towards maintaining access to critical habitat resources, while also restoring habitat quantity and quality.

Introduction able to road effects (Rytwinski & Fahrig, 2011), because their populations are less able to recover from high mortality rates Many human infrastructures influence the survival (Gibbs & caused by roads, both directly (e.g. road collisions) and indi- Shriver, 2002), reproduction (Gerlach & Musolf, 2000), dis- rectly (e.g. increased predation risk). persal (Shepard et al., 2008), predator–prey interactions Many studies have highlighted negative impacts of human (Rogala et al., 2011) and behaviour (May et al., 2006) of infrastructure on the behaviour of large herbivores. Caribou animals. The North American road network, for example, Rangifer tarandus consistently avoid paved and forestry roads covers more than 8 million km, and its development shows no (Leblond et al., 2011), seismic lines (Dyer et al., 2001) and sign of slowing (Forman et al., 2002). Each year, roads are tourist resorts (Vistnes & Nellemann, 2008) by several kilome- improved worldwide to allow for greater traffic densities, and tres. Mountain goats Oreamnos americanus were unable to new roads are created in previously pristine wildlife habitats. cross a highway in Montana at high traffic densities, and Roads may be complete barriers to small animals (Shepard showed behaviours indicative of fear (e.g. running, erected tail et al., 2008), and certain road widths (Smith-Patten & Patten, and hair) even in the absence of vehicles (Singer, 1978). Moose 2008) or traffic densities (Gagnon et al., 2007) may partially Alces alces in Québec had higher movement rates in the vicin- disrupt movements for larger species. Large animals are more ity of a highway, up to 3 h before and after crossing (Dussault likely to be negatively affected by roads, because their vagility et al., 2007). The level of disturbance associated with human and use of large home ranges increase their probability of infrastructure, however, is difficult to assess and their frequent interacting with roads (Gibbs & Shriver, 2002). Long-lived association with other features (e.g. buildings are found near species with low reproductive rates are also the most vulner- access roads) may confound our ability to disentangle their

32 Journal of Zoology 289 (2013) 32–40 © 2012 The Authors. Journal of Zoology © 2012 The Zoological Society of London M. Leblond, C. Dussault and J.-P. Ouellet Avoidance of roads and disturbance intensity individual impacts on animal behaviour. Although the avoid- 2002), after the enlargement of the highway, and when traffic ance of human infrastructure by large herbivores has been densities were high (Gagnon et al., 2007). demonstrated in many systems, we know little about the rela- tionship between disturbance levels associated with these infrastructures and their relative degree of avoidance by Materials and methods animals. Such knowledge would be of paramount importance to implement suitable mitigation and conservation measures Study area of human activities for large herbivore populations. Our study area (approximately 7250 km2) was located north We investigated the hypothesis that the strength of road- of Québec City in the Laurentides Wildlife Reserve (between avoidance behaviour by animals increases with disturbance 47°10’ and 48°00’ N, and 70°30’ and 71°50’ W), Québec, intensity associated with the road. We studied a species that Canada (Fig. 1). It received a heavy annual snowfall (average repeatedly demonstrates strong reactions to anthropogenic >350 cm) and was characterized by a mixture of coniferous disturbances, the forest-dwelling caribou R. t. caribou. and mixed forest stands, typical of the boreal region. Balsam Throughout its range, forest-dwelling caribou are subject to fir Abies balsamea and black spruce Picea mariana dominated several sources of disturbance, of which roads have among the at higher altitudes, whereas valleys and low-lying sectors were strongest adverse impacts on their distribution and behaviour covered with mixed and deciduous stands. The study area was (Dyer et al., 2002; Leblond et al., 2011). Caribou may avoid the approximately 56% forested, and 37% was covered by dis- road surface, but also a road-effect zone (sensu Forman et al., turbed habitats, mostly clearcuts of different ages and roads. 2002) of at least 1250 m around paved roads (Leblond et al., 2011), possibly because of avoidance of traffic noises (Jaeger et al., 2005). Near roads, caribou reduce their food acquisition Sampling design and increase their energy expenditure, and they tend to have The study area was intersected by Highway 175, of which higher movement rates and increased vigilance (Murphy & 95.5 km crossed the caribou range. Modifications of the Curatolo, 1987). Although caribou react strongly to humans highway began as early as May 2006 and as late as June 2009, and human infrastructure, they were also found to be sensitive and lasted between 100 and 900 days (depending on local to low-disturbance human footprints in the landscape, such as terrain conditions, Table 1). Within this period, the highway abandoned seismic lines in Alberta (Dyer et al., 2001). was widened from approximately 25 to 90 m. Construction To relate the strength of avoidance of caribou to various sites within the caribou range averaged 7 km in length. There levels of a disturbance, we studied a long span of spatio- was activity on construction sites during both day and night, temporally changing highway, therefore controlling for poten- and throughout most of the year, with short stops during tially confounding factors such as the surrounding habitat. holidays or because of adverse weather conditions. All Highway 175 in Québec, Canada, has undergone significant highway modifications were completed by the end of 2010. changes between 2006 and 2010, changing from a two-lane to Hence, within a given year, caribou could interact with the a four-lane highway, more than three times wider than before. highway before, during, and/or after its modification. This highway intersects the Charlevoix caribou range, a threatened forest-dwelling caribou population of less than 85 individuals. We used a long-term telemetry programme per- Caribou capture and telemetry formed throughout the gradual modification of the highway to assess caribou behaviour before, during and after highway Between April 2004 and March 2010, we captured 53 adult modifications. We thus considered the highway as a dynamic caribou (37 F and 16 M) by net-gunning from a helicopter, disturbance of varying intensity. We used highway width, and fitted them with global positioning system telemetry human activity on construction sites and traffic density as collars (models TGW 3600 and 4600, Telonics Inc., Mesa, AZ, surrogates of disturbance intensity, expecting that a larger USA) programmed to collect locations every 3 or 7 h depend- highway, higher traffic densities and the presence of active ing upon the collar model. Capture and handling procedures construction sites (with workers, large trucks and blasting) were approved by Animal Welfare Committees (Ministère des would result in stronger avoidance (or a wider road-effect Ressources naturelles et de la Faune du Québec and Univer- zone) by caribou. sité du Québec à Rimouski). We recaptured caribou at 1- or We predicted that the highway would have specific effects 2-year intervals to download location data and replace battery on caribou behaviour; caribou would cross the highway less packs. Collars were equipped with a timer release mechanism than expected when compared with random movements and were programmed to drop at the end of the study. across the landscape (Dyer et al., 2002), and caribou would travel through the road-effect zone at a higher movement rate Spatio-temporal data (Dussault et al., 2007) because they would perceive this area as a risky environment (Frid & Dill, 2002). We also predicted We used digital forest maps (minimum mapping unit size = 4ha that as the intensity of highway disturbance increased, the for forest stands, 2 ha for non-forested areas) to determine number of caribou crossings would decrease, and that the land-cover types using ArcGIS 9.3 (ESRI Inc., Redlands, CA, width of the road-effect zone for caribou would increase in USA). These vector maps were derived from aerial photo- the vicinity of active construction sites (Mahoney & Schaefer, graphs taken in 1998 at the scale of 1: 20 000. We updated maps

Journal of Zoology 289 (2013) 32–40 © 2012 The Authors. Journal of Zoology © 2012 The Zoological Society of London 33 Avoidance of roads and disturbance intensity M. Leblond, C. Dussault and J.-P. Ouellet

Figure 1 Map of the study area showing Highway 175 crossing the forest-dwelling caribou range in the Charlevoix region, Québec, Canada. Québec National park boundaries and caribou locations (n = 364 100) obtained with the global positioning system telemetry programme between 2004 and 2010 are shown.

Table 1 Length of Highway 175 segments crossing the forest-dwelling old; 10.5%), regenerating stands (generally 20–30 years after caribou range in the Charlevoix region, Québec, Canada, by highway disturbance; 25.6%), open lichen woodlands (1.0%), wetlands status and year (2.3%), powerlines (0.4%), and others (e.g. lakes, unproductive Highway status length (km) open lands; 4.2%). We used a digital elevation model with a Before highway During highway After highway 50-m resolution to measure local elevation and slope. We Year modifications modifications modifications updated the map of the highway fortnightly to account for the 2004 95.5 0.0 0.0 spatio-temporal evolution of highway modifications and 2005 95.5 0.0 0.0 assigned a status to each 1-km road segment, that is either 2006 80.4 15.1 0.0 before, during or after road modifications. 2007 80.4 15.1 0.0 We developed a mean hourly traffic index based on 2008 23.2 61.7 10.6 summary reports provided by the Ministère des Transports du 2009 0.0 80.4 15.1 Québec, which collected data using an electromagnetic traffic 2010 0.0 36.6 58.9 counter placed on the highway near the centre of our study area. We used a composite index based on the mean hourly Highway modifications began in 2006. χ traffic for the whole year, i (i.e. 24 different values of hour,1 for each hour), which we modified to consider relative varia- each year to include new clearcuts, and combined available tions in traffic density between months, j (12 different average habitat types into 10 vegetation classes, including old mature values), and weekdays, k (7 different average values). We cal- conifer-dominated forests (conifer and mixed stands Ն90 years culated the index using the equation: old; availability = 11.5% of the landscape), young mature χ χ Traffic density =×χ month j ×weekdayk conifer-dominated forests (conifer and mixed stands 50–90 houri χmonth χweekday years old; 31.0%), mature deciduous forests (>50 years old; 2.8%), recent clearcuts or natural disturbances (Յ5 years The resulting index, varying between 18 and 786 vehicles old; 10.7%), old clearcuts or natural disturbances (6–20 years per·hour, was assigned to every caribou location based on

34 Journal of Zoology 289 (2013) 32–40 © 2012 The Authors. Journal of Zoology © 2012 The Zoological Society of London M. Leblond, C. Dussault and J.-P. Ouellet Avoidance of roads and disturbance intensity date and time. Because our index was collected on a single To determine if caribou avoided the highway within their highway, it was independent from road width. This allowed us home range, we measured the minimal distance between each to overcome a bias often found in other disturbance studies caribou location and the highway. We included this distance, comparing roads of different traffic densities (i.e. large roads along with 10 vegetation classes, elevation and slope, in a are likely to have high traffic and vice versa). mixed-effect resource selection function (RSF) model (Manly et al., 2002). RSFs contrasted habitat features at observed locations with those found at a similar number of random Data analysis locations drawn within the annual home range of caribou. We performed collinearity diagnostics and found that collinearity Impacts of the highway on caribou behaviour was low in our dataset (variance inflation value < 2). We set individual (year) as a random intercept to account for differ- To determine if caribou crossed the highway less frequently ences in sample size among caribou and for variation in selec- than expected by chance, we simulated 1000 random highways tion among years. We included a second-order polynomial by translating and rotating the actual highway in our study term for elevation, which was also centred on the mean to area to a new location within the caribou range (highway improve model fit. We used the predominant vegetation class, sections that fell outside of the range were deleted). A poste- young mature conifer forests, as the reference category. We riori analyses revealed that the environment next to the real employed k-fold cross-validation to evaluate the robustness of highway was not different from the environment around our RSF (Boyce et al., 2002), and reported the average rS random roads. We counted the number of crossings of the resulting from 10 iterations. We included vegetation classes random highway made by caribou along their movement and topography as covariates because previous studies have paths, and performed one-sample t-tests comparing the mean outlined their importance to forest-dwelling caribou (see annual number of random highway crossings per km to the Leblond et al., 2011 for more details). observed annual number of crossings per km. Although we predicted that the reaction of caribou would To determine if caribou increased their movement rate in gradually increase with the intensity of highway disturbance, the vicinity of the highway, we compared the movement rate we also expected that this gradual response would be more (m h-1) of caribou while crossing the highway (T0) to their easily observed within a given distance from the highway, movement rate a few hours before (five time-steps preceding likely determined by the perception range of caribou (Olden T0, T-1 to T-5) and after (five time-steps following T0, T+1to et al., 2004). Consequently, we assessed the impacts of distur- T+5) crossing (Dussault et al., 2007). We also created a con- bance level on caribou behaviour by constraining our analyses tinuous time variable increasing from 1 to 11 for each time- to a small fraction of caribou home ranges located in the step, to take the non-independance of time series into vicinity of the highway. To do so, we used different road- consideration. We used a mixed effects linear regression model buffer zones potentially representative of the perception range with movement rate as the dependent variable, time-step as of caribou: 1250, 2500 and 5000 m. We explored larger road- the fixed effect independent variable, and crossing event (n = buffer zones during preliminary analyses and obtained similar 93), individual (n = 12), time, and time2 (i.e. based on our results with widths >5000 m and the global analysis using all prediction that movement rate would increase near the caribou locations. By narrowing some of our analyses to the highway) as random factors. We computed the least squares area close to the highway (our finest scale of analysis), we means of fixed effects and we performed multiple post hoc focused on the behaviour of individuals that did not exclude comparisons between the different time-steps using the the highway from their home range. To determine if avoidance Tukey’s adjustment. by caribou was higher near active construction sites and the larger highway compared with the unmodified highway, we Impacts of increasing highway disturbance evaluated RSF models of the same form as the global model using only the locations (observed and random) within the intensity on caribou behaviour 1250-, 2500- or 5000-m road-buffer zones, and included inter- To determine if caribou avoided the highway, we assessed action terms between minimum distance to the highway and habitat selection by caribou at different spatial scales (i.e. highway status (before, during or after road modifications). In landscape, home range and road vicinity). Our first step was to this analysis, we could not consider individual and year as assess if caribou changed the location of their home range in random effects because of small sample sizes. the landscape according to the intensity of disturbance. To do Although our RSF assessed the relative probability of so, we assessed the correlation between year (used as an caribou occurrence in relation to the highway, we wanted to approximation of increasing highway disturbance intensity) evaluate the impact of disturbance intensity on the proportion and highway density (km·km-2) in annual home ranges (deter- of caribou locations within different road-buffer zones. We mined using the 100% minimum convex polygon) of individu- performed log-linear regressions to determine if the propor- als that included the highway at least 1 year. Similarly, we tion of caribou locations within the 1250-, 2500- and 5000-m performed a Spearman correlation between the number of road-buffer zones was influenced by traffic density (with low crossings per km per·individual of the highway and year to and high values set below or above the median of 186 vehicles determine whether the number of caribou crossings decreased per·hour, respectively) or highway status (before, during or as highway modifications progressed. after highway modifications). We also performed a linear

Journal of Zoology 289 (2013) 32–40 © 2012 The Authors. Journal of Zoology © 2012 The Zoological Society of London 35 Avoidance of roads and disturbance intensity M. Leblond, C. Dussault and J.-P. Ouellet

Table 2 Annual number of crossings per km and crossings of Highway 175 by forest-dwelling caribou in the Charlevoix region, Québec, Canada, for each highway status

Mean number of crossings Number of crossings per km (and crossings) of the highway per km of the 1000 random Before highway During highway After highway highways Ϯ standard Year modifications modifications modifications Total deviation t-value 2004 0.14 (13) –a – 0.14 (13) 1.00 Ϯ 2.13 12.83** 2005 0.21 (20) – – 0.21 (20) 1.19 Ϯ 2.68 11.61** 2006 0.06 (5) 0.07 (1) – 0.06 (6) 1.50 Ϯ 2.93 15.47** 2007 0.16 (13) 0.07 (1) – 0.15 (14) 1.87 Ϯ 2.26 24.09** 2008 0.04 (1) 0.26 (16) 0.38 (4) 0.22 (21) 2.98 Ϯ 3.89 22.44** 2009 – 0.01 (1) 0.07 (1) 0.02 (2) 2.16 Ϯ 3.38 19.99** 2010 – 0 0.29 (17) 0.18 (17) 2.84 Ϯ 3.91 21.53** Total (52) (19) (22) 0.97 (93) 14.17 Ϯ 16.99 24.57**

The observed number of crossings per km was compared with the number of crossings of 1000 simulated (random) highways using t-tests. aHighway status unavailable. **P < 0.001.

regression with movement rate as the dependent variable, traffic density as the independent variable and individual caribou (n = 12 caribou that crossed the highway) as a random factor, to assess if the movement rate was influenced by increased traffic density. We performed all statistical analyses using SAS 9.2 (SAS Institute Inc., Cary, NC, USA).

Results

Impacts of the highway on caribou behaviour Only 12 (8 F and 4 M) of the 53 (23%) caribou crossed the highway at least once between 2004 and 2010, and only 93 of the 364 100 (<0.03 %) caribou locations were the end point of a movement step that crossed the highway. The annual rate of caribou crossings was much lower on the real highway than Figure 2 Adjusted least-squares mean movement rate [m h-1 + stand- on random roads (Table 2). We observed a negative trend ard error (SE) ] of forest-dwelling caribou during crossing of Highway between the number of crossings per km per individual and 175 (T0), as well as five time-steps before (T-1 to T-5) and five time- year (n = 7 years; r =-0.68; P = 0.09). steps after (T+1toT+5), in the Charlevoix region, Québec, Canada, from The movement rate of caribou was higher during crossings 2004 to 2010. Bars sharing the same letter did not differ significantly. of the highway (1011 m h-1 on average) than during time-steps Յ -1 just preceding or following crossing ( 683mh , Fig. 2). The years changed the location of their home range to avoid the movement rate of caribou was also higher during the two highway at a large scale during (n = 3) or after (n = 5) its time-steps preceding (T-1 and T-2, 7.5 h before crossing on modification. average) and the time-step immediately following the crossing The RSF model using all caribou locations (Table 3) (T+1, 3.5 h after crossing on average) compared with move- revealed that caribou avoided the highway at the home-range ment rates recorded at every other preceding and succeeding scale. Only 1713 (0.47%), 6974 (1.92%), and 16 067 (4.41%) time-steps. locations were within the 1250-, 2500- and 5000-m road-buffer zones, respectively, which was 1.3–2.3 times less than random Impacts of increasing highway disturbance locations. Results from the RSF models focusing on the road- buffer zones showed that caribou generally avoided the intensity on caribou behaviour highway even when they were in its vicinity (Table 3). Within The correlation between highway density in caribou home these zones, they avoided all vegetation classes except power- ranges and year was negative (r =-0.17, P = 0.03). Eight out of lines and wetlands within 5000 m. nine individuals whose home range included the highway at Caribou crossed the highway at a significantly higher move- least once during the study and that we monitored for Ն 2 ment rate when traffic density was high [1.60 Ϯ 0.77 (standard

36 Journal of Zoology 289 (2013) 32–40 © 2012 The Authors. Journal of Zoology © 2012 The Zoological Society of London M. Leblond, C. Dussault and J.-P. Ouellet Avoidance of roads and disturbance intensity

Table 3 Selection coefficients (b) and associated 95% CL of models of resource selection by forest-dwelling caribou in the Charlevoix region, Québec, Canada, from 2004 to 2010

Within 1250 m Within 2500 m Within 5000 m of the highway of the highway of the highway All caribou locations (n = 1713) (n = 6974) (n = 16 067) (n = 364 100) b (95% CL) b (95% CL) b (95% CL) b (95% CL) Vegetation classa Old mature conifer -1.11 (-1.37:-0.85) -1.15 (-1.27:-1.03) -0.48 (-0.55:-0.42) 0.31 (0.15:0.47) Open lichen woodland -1.04 (-1.80:-0.28) 1.90 (1.68:2.12) Wetland -0.23 (-0.57:0.12) -0.25 (-0.49:-0.01) 1.01 (0.91:1.12) 0.90 (0.77:1.04) Deciduous -1.29 (-1.62:-0.96) -0.77 (-0.94:-0.59) 0.43 (-0.07:0.93) Young disturbance (<5 years) -0.56 (-0.81:-0.31) -0.55 (-0.69:-0.40) -0.16 (-0.23:-0.08) 1.37 (1.18:1.56) Old disturbance (6–20 years) -1.28 (-1.82:-0.74) -0.40 (-0.59:-0.22) -0.41 (-0.52:-0.30) 0.34 (0.17:0.51) Regenerating (>20 years) -2.38 (-2.77:-1.99) -2.10 (-2.28:-1.92) -1.90 (-2.02:-1.78) -0.87 (-1.04:-0.71) Other -3.27 (-3.82:-2.72) -2.89 (-3.34:-2.44) -0.80 (-0.95:-0.65) -0.61 (-0.76:-0.46) Powerline 2.29 (1.98:2.60) 2.46 (2.21:2.72) 2.23 (2.01:2.44) 4.28 (3.89:4.67) Topography Elevation (km) -5.86 (-7.51:-4.20) -1.43 (-2.57:-0.30) 2.86 (2.42:3.31) 2.12 (0.69:3.56) Elevation2 130.05 (108.46:151.63) 75.95 (63.06:88.85) 17.11 (12.24:21.98) 5.80 (-0.61:12.22) Slope (°) -0.02 (-0.04: < 0.01) 0.05 (0.04:0.06) 0.04 (0.03:0.04) -0.03 (-0.04:-0.02) Distance to the highway Minimum distance to the highway (km) 0.57 (0.29:0.85) 0.82 (0.73:0.91) 0.04 (0.01:0.06) 0.03 (0.01:0.05) Interaction between the minimum distance to the highway (km) and highway statusb During highway modifications -0.81 (-1.35:-0.28) -0.14 (-0.27:-0.01) 0.05 (0.01:0.09) After highway modifications -2.07 (-2.59:-1.54) -2.95 (-3.30:-2.60) -0.18 (-0.24:-0.12) Random effect [individual (year)] 0.11 (-0.08:0.31)

Validation (Spearman rS ) 0.854 0.955 0.935 0.961

Models were first ran using all caribou locations (n = 364 100) and then using caribou locations within the road-buffer zones (1250, 2500 and 5000 m). Open lichen woodlands within 1250 and 2500 m, and deciduous stands within 1250 m were removed from the models because no caribou locations were observed in these classes. Results of model validation (Spearman’s correlation rS values) are provided. aReference category = young mature conifer-dominated stands. bReference category = before highway modifications. CL, confidence limits.

Table 4 Parameter estimates (b) and associated 95% CL of the log-linear regression analyses assessing the influence of the interaction between traffic density or highway status and distance to the highway on the proportion of caribou locations within 1250-, 2500- and 5000-m road-buffer zones by forest-dwelling caribou in the Charlevoix region, Québec, Canada, from 2004 to 2010

Within 1250 m of the highway Within 2500 m of the highway Within 5000 m of the highway b 95% CL b 95% CL b 95% CL Traffic density (reference category = low) High 0.25 0.16:0.35 -0.03 -0.08:0.01 <-0.01 -0.04:0.03 Highway status (reference category = before highway modifications) During highway modifications -0.78 -0.91:-0.66 0.02 -0.03:0.07 -0.05 -0.08:-0.01 After highway modifications -0.17 -0.29:-0.05 -1.48 -1.59:-1.37 -1.45 -1.55:-1.41

High and low traffic densities were set above and below the median value of 186 vehicles per hour of the traffic index, respectively. CL, confidence limits.

error), P = 0.04]. Moreover, a higher proportion of caribou Discussion locations were found within 1250 m of the highway when traffic density was high, compared with when it was low We investigated caribou reactions towards a single gradually (Table 4). We did not find a similar trend within 2500 and modified highway, thereby controlling for potentially con- 5000 m of the highway. Caribou also used road-buffer zones founding factors, and our data support the hypothesis that less during and after highway modifications compared with avoidance of roads by large herbivores is positively related to before (although not significantly within 2500 m, Table 4). disturbance intensity. The increased intensity of disturbance

Journal of Zoology 289 (2013) 32–40 © 2012 The Authors. Journal of Zoology © 2012 The Zoological Society of London 37 Avoidance of roads and disturbance intensity M. Leblond, C. Dussault and J.-P. Ouellet resulting from the wider highway, the presence of active con- Animals generally mitigate the effects of the factors most struction sites, and higher traffic densities led to stronger detrimental to their fitness by avoiding them at broad scales behavioural reactions by caribou at several scales. The (Rettie & Messier, 2000). As such, the highway was a deter- impacts of human activity on animal behaviour and distribu- mining feature for caribou when establishing their home range tion have been studied extensively in recent years (e.g. Heb- in the landscape (May et al., 2006). For caribou, this may be a blewhite & Merrill, 2008; Rogala et al., 2011). However, to good strategy to increase survival: only three caribou–vehicle our knowledge, we are the first to relate the strength of avoid- collisions occurred in our study area during our 7-year study. ance shown by a mammal species towards a human infrastruc- Our results suggest that the high disturbance levels found in ture with the level of disturbance associated with that the vicinity of the highway decreased habitat suitability up to infrastructure. at least 5000 m from it. As found with moose (Dussault et al., At a broad scale, the few individuals that used the 2007), caribou showed increased movement rates many hours highway before road modifications gradually modified their before and after crossing, suggesting that a large disturbance space use to exclude it from their home range as the modi- zone around the road was perceived as risky, unsuitable fications progressed. The low number of annual highway habitat. This also suggests that, for most caribou, the per- crossings by caribou showed a decreasing trend (P = 0.09, ceived benefits of using resources up to 5 km away from the low sample size) during the course of the study. At a finer road were not strong enough to offset the perceived risks. scale, we found a lower proportion of caribou locations in Despite the negative reactions we observed at the popula- the road-buffer zones during and after highway modifica- tion level, some individuals may have benefited from living tions as compared with before, showing that increased road near the highway. For example, a few individuals may have disturbance resulted in stronger avoidance behaviour by selected sites to feed in the open terrain under powerlines caribou. Within these road-buffer zones, caribou avoided the adjacent to the highway, where abundant shrubs and herba- habitat types that they selected elsewhere in their home ceous plants can be found. Proximity to the road may also range. The proportion of caribou locations in road-buffer result in lower predation risk for caribou (Muhly et al., 2011). zones did not decrease with increasing traffic density, as In the Greater Yellowstone Ecosystem (USA), Berger (2007) reported for other ungulate populations (e.g. Gagnon et al., found that moose used the vicinity of roads to shelter from 2007), but rather translated into higher movement rates by their traffic-averse predators. Given that individuals using the caribou, which we also interpret as a reaction of caribou to road-buffer zones reacted to increased disturbance, the per- increased disturbance. Although we considered the relative ceived risks of living near roads for large herbivores could impacts of road width, human activity on construction sites, therefore surpass the former benefits following road enhance- and traffic density separately, we underscore that these ment projects or increased traffic levels. effects may occur simultaneously and act synergistically to Our study showed that the avoidance behaviour of a large, influence the behaviour of large herbivores living in human- disturbance-sensitive herbivore is related to disturbance inten- modified landscapes, thereby degrading habitat quality and sity. It may help to understand why sensitive species slowly landscape connectivity. disappear from fragmented, human-altered landscapes, Caribou were already found to avoid infrastructure usually adding to the global biodiversity decline. Conservation efforts associated with little to no human activity, such as forestry in areas where roads are constructed or modified should be roads, seismic lines, dams and pipeline corridors (e.g. Vistnes directed towards maintaining access to critical resources and & Nellemann, 2008). Our results indicate that, even if caribou restoring habitat quantity and quality. Although connectivity were reacting to increased disturbance levels, most individuals across the highway could be increased by constructing wildlife were using areas away from the highway before its modifica- crossing structures (Olsson, Widen & Larkin, 2008), the tions, suggesting that road disturbance had already shaped strong avoidance behaviour shown by sensitive species like caribou distribution (May et al., 2006). Individuals establish- caribou could limit their effectiveness. In the case of a large or ing their home range far from the highway likely showed the busy road, the wide road-effect zone might prevent individuals strongest road-avoidance. Therefore, the minimal disturbance from finding and using the passages. To facilitate the adapta- intensity we measured (i.e. the unmodified two-lane highway tion of sensitive species to wildlife passages, we recommend to with lowest traffic density) likely exceeded the threshold initi- limit the intensity of human disturbances in their surround- ating a behavioural reaction for most caribou. ings (e.g. by limiting human presence and vehicle noises; Clev- Animals face a conflicting trade-off when encountering a enger & Waltho, 2005). road: the strong incentive to access resources found on the Our results suggest that the negative impacts of roads and other side of the road may be overcome by the perceived risks increasing disturbance levels may affect animal behaviour associated with vehicles and human activity. We found that over a wide range of scales. It may take several years after 77% (41/53) of caribou did not cross the highway. It is likely road modifications are completed to further evaluate their full that the individuals most sensitive to road disturbances were impacts on animal behaviour. Time lags are common in not able to access resources potentially available on the oppo- studies assessing long-term impacts of human disturbances site side of the highway (including suitable areas protected by (Ewers & Didham, 2006), and forest-dwelling caribou were national parks). This represents a potential loss of 52–61% of shown to display such delayed responses (Vors et al., 2007). In the caribou range, for individuals west or east of the highway, the case of the Charlevoix caribou, if the wider four-lane respectively. highway eventually becomes a complete barrier to caribou

38 Journal of Zoology 289 (2013) 32–40 © 2012 The Authors. Journal of Zoology © 2012 The Zoological Society of London M. Leblond, C. Dussault and J.-P. Ouellet Avoidance of roads and disturbance intensity movements, the population could be subdivided into two Gerlach, G. & Musolf, K. (2000). Fragmentation of landscape smaller groups, each having a greater risk of local extinction as a cause for genetic subdivision in bank voles. Conserv. because of stochastic events (Hanski & Ovaskainen, 2003). We Biol. 14, 1066–1074. encourage further studies on road-avoidance behaviour to Gibbs, J.P. & Shriver, W.G. (2002). Estimating the effects of investigate whether behavioural impacts of human distur- road mortality on turtle populations. Conserv. Biol. 16, bances on wildlife may translate to impacts on population 1647–1652. dynamics. Hanski, I. & Ovaskainen, O. (2003). Metapopulation theory for fragmented landscapes. Theor. Popul. Biol. 64, 119–127. Acknowledgements Hebblewhite, M. & Merrill, E. (2008). Modelling wildlife– human relationships for social species with mixed-effects We thank B. Baillargeon, L. Breton, P. Dubois, J.-G. Fren- J. Appl. Ecol. 45 ette, S. Gravel, D. Grenier, R. McNicol, M. Poulin, S. Rivard resource selection models. , 834–844. and S. St-Onge. We also thank three anonymous reviewers for Jaeger, J.A.G., Bowman, J., Brennan, J., Fahrig, L., Bert, D., their suggestions. Funding was provided by the Ministère des Bouchard, J., Charbonneau, N., Frank, K., Gruber, B. & Ressources naturelles et de la Faune and the Ministère des von Toschanowitz, K.T. (2005). Predicting when animal Transports du Québec. M. L. received a graduate scholarship populations are at risk from roads: an interactive model of from the Fonds québécois de recherche sur la nature et les road avoidance behaviour. Ecol. Model. 185, 329–348. technologies. Leblond, M., Frair, J., Fortin, D., Dussault, C., Ouellet, J.-P. & Courtois, R. (2011). Assessing the influence of resource References covariates at multiple spatial scales: an application to forest-dwelling caribou faced with intensive human activity. Berger, J. (2007). Fear, human shields and the redistribution Landsc. Ecol. 26, 1433–1446. of prey and predators in protected areas. Biol. Lett. 3, 620– Mahoney, S.P. & Schaefer, J.A. (2002). Hydroelectric devel- 623. opment and the disruption of migration in caribou. Biol. Boyce, M.S., Vernier, P.R., Nielsen, S.E. & Schmiegelow, Conserv. 107, 147–153. F.K.A. (2002). Evaluating resource selection functions. Manly, B.F.J., McDonald, L.L., Thomas, D.L., McDonald, Ecol. Model. 157, 281–300. T.L. & Erickson, W.P. (2002). Resource selection by animals: Clevenger, A.P. & Waltho, N. (2005). Performance indices to statistical design and analysis for field studies. 2nd edn. identify attributes of highway crossing structures facilitat- Dordrecht, The Netherlands: Kluwer Academic Publishers. ing movement of large mammals. Biol. Conserv. 121, May, R., Landa, A., van Dijk, J., Linnell, J.D.C. & Andersen, 453–464. R. (2006). Impact of infrastructure on habitat selection of Dussault, C., Ouellet, J., Laurian, C., Courtois, R., Poulin, wolverines Gulo gulo. Wildl. Biol. 12, 285–295. M. & Breton, L. (2007). Moose movement rates along high- Muhly, T.B., Semeniuk, C., Massolo, A., Hickman, L. & ways and crossing probability models. J. Wildl. Manage. Musiani, M. (2011). Human activity helps prey win the 71, 2338–2345. predator–prey space race. PLoS ONE 6, e17050. Dyer, S.J., O’Neill, J.P., Wasel, S.M. & Boutin, S. (2001). Murphy, S.M. & Curatolo, J.A. (1987). Activity budgets and Avoidance of industrial development by woodland caribou. movement rates of caribou encountering pipelines, roads, J. Wildl. Manage. 65, 531–542. and traffic in northern Alaska. Can. J. Zool. 65, 2483–2490. Dyer, S.J., O’Neill, J.P., Wasel, S.M. & Boutin, S. (2002). Olden, J.D., Schooley, R.L., Monroe, J.B. & Poff, N.L. Quantifying barrier effects of roads and seismic lines on (2004). Context-dependent perceptual ranges and their rel- movements of female woodland caribou in northeastern evance to animal movements in landscapes. J. Anim. Ecol. Alberta. Can. J. Zool. 80, 839–845. 73, 1190–1194. Ewers, R.M. & Didham, R.K. (2006). Confounding factors in Olsson, M.P.O., Widen, P. & Larkin, J.L. (2008). Effective- the detection of species responses to habitat fragmentation. ness of a highway overpass to promote landscape connec- Biol. Rev. 81, 117–142. tivity and movement of moose and roe deer in Sweden. Forman, R.T.T., Sperling, D., Bissonette, J.A., Clevenger, Landsc. Urban Plan. 85, 133–139. A.P., Cutshall, C.D., Dale, V.H., Fahrig, L., France, R., Rettie, W.J. & Messier, F. (2000). Hierarchical habitat selec- Goldman, C.R., Heanue, K., Jones, J.A., Swanson, F.J., tion by woodland caribou: its relationship to limiting Turrentine, T. & Winter, T.C. (2002). Road ecology: science factors. Ecography 23, 466–478. and solutions. Washington: Island Press. Rogala, J.K., Hebblewhite, M., Whittington, J., White, C.A., Frid, A. & Dill, L. (2002). Human-caused disturbance stimuli Coleshill, J. & Musiani, M. (2011). Human activity differ- as a form of predation risk. Conserv. Ecol. 6, 11. entially redistributes large mammals in the Canadian Gagnon, J.W., Theimer, T.C., Dodd, N.L., Boe, S. & Rockies National Parks. Ecol. Soc. 16, 16. Schweinsburg, R.E. (2007). Traffic volume alters elk Rytwinski, T. & Fahrig, L. (2011). Reproductive rate and distribution and highway crossings in Arizona. J. Wildl. body size predict road impacts on mammal abundance. Manage. 71, 2318–2323. Ecol. Appl. 21, 589–600.

Journal of Zoology 289 (2013) 32–40 © 2012 The Authors. Journal of Zoology © 2012 The Zoological Society of London 39 Avoidance of roads and disturbance intensity M. Leblond, C. Dussault and J.-P. Ouellet

Shepard, D.B., Kuhns, A.R., Dreslik, M.J. & Phillips, C.A. Vistnes, I. & Nellemann, C. (2008). The matter of spatial and (2008). Roads as barriers to animal movement in frag- temporal scales: a review of reindeer and caribou response mented landscapes. Anim. Conserv. 11, 288–296. to human activity. Polar Biol. 31, 399–407. Singer, F.J. (1978). Behaviour of mountain goats in relation Vors, L.S., Schaefer, J.A., Pond, B.A., Rodgers, A.R. & to U.S. Highway 2, Glacier National Park Montana. Patterson, B.R. (2007). Woodland caribou extirpation and J. Wildl. Manage. 42, 591–597. anthropogenic landscape disturbance in Ontario. J. Wildl. Smith-Patten, B.D. & Patten, M.A. (2008). Diversity, season- Manage. 71, 1249–1256. ality, and context of mammalian roadkills in the southern great plains. Environ. Manage. 41, 844–852.

40 Journal of Zoology 289 (2013) 32–40 © 2012 The Authors. Journal of Zoology © 2012 The Zoological Society of London

Evaluation of Best Management Practices for Mitigating Impacts of Highways on Stream and Wildlife Ecology

(First Progress Report)

Ruiqiang Liu (GRA) and Don Zhao (PI)

Department of Civil Engineering Auburn University, Auburn, AL 36849

July 11, 2003

[Abstract]

Transportation, like many other human activities, affects the environment such as air and water quality as well as wildlife habitat. Serious environment problems may arise when a road/highway intercepts the natural pathways of streams or wetlands, which play critical roles in accommodating regional habitats for both aquatic and terrestrial wildlife and in facilitating biological life cycles. Disruption of streams by transportation activities often results in upsetting the existing processes that maintain regional populations and ecological balances. Published field data show that highway operations have caused unprecedented habitat loss and degradation, habitat fragmentation and road kills.

Over the last thirty years, new laws and regulations have emerged to mitigate the impacts of transportation projects on the ecosystem. Powered by the Clean Air Act (CAA) and Clean Water Act (CWA), more and more stringent legislations have been promulgated to regulate specific environmental issues associated with transportation. In light of ever tightening environmental regulations, selection of best management practice (BMP) is no longer dictated solely by practical feasibility. Overall environmental soundness including wildlife ecology and environmental sustainability is also influencing the permitting process.

Engineered animal passage structures have been widely employed to facilitate the movement of certain terrestrial and amphibian species across highways and thus to mitigate the adverse impacts of highway activities on the wildlife ecology. This report summarizes and examines various engineered passage structures such as wildlife overpass, wildlife underpass, upland culvert, oversized stream culvert and bridge, viaduct, and fencing. Discussion pertaining to their suitability, design and dimensions was offered. Environmental factors such as location, noise, temperature, light and moisture, which may affect the effectiveness of these passage systems, are also discussed in this report.

For aquatic species, our study indicated three fish passage design options: no slope option, hydraulic design option and stream simulation option. Design guidelines for bridges were also discussed.

Preliminary cost analysis revealed that some of the most effective techniques for facilitating wildlife movement (e.g. overpasses) are also quite expensive. A practical strategy for mitigating highway impacts on wildlife movement may dictate that expensive elements be reserved for areas that are identified as important travel corridors or connection between areas of significant habitats, while inexpensive elements be used at appropriate areas throughout the highway alignment.

The information will help road designers with selecting BMPs for mitigating transportation impacts on the environment.

[Key Word] BMP, highway, ecology, fragmentation, mitigation, overpass, road kill, underpass, wildlife.

1 1. Introduction

Roads and numbers of motorized vehicles increased enormously during the twentieth century. In 2000, it was estimated that United States contained 6.36 millions km of roads occupying 8.1 millions hectares (Highway Statistics, 2001) and these numbers for Canada in 1995 were 0.9 millions km and 1.2 millions hectares; In 1990, the European Commission presented a major plan for improving so-called Trans-Europe Network (TEN), this program entailed an enormous expansion of motorway, waterway and high-speed railway links, the total length of motorway was scheduled to grow from 43,00 0 km to 58,000 km (Bekker, 1998). By 1998, Australia had built approximately 870,000 km of roads and yielded more than 3.1 million of its rural area to roads (Straker, 1998). Total length of roads in the Great Britain was approximately 371,914 km by 1999. The total area of land taken up by these roads in 1991 was about 0.32 millions hectares, about 1.4% of its total land area (Spellerberg, 2002).

As more and more roads are constructed, the associated impacts on the human and environmental health become increasingly an environmental concern. Highway activities can cause severe human’s health and safety problems such as traffic accidents, air pollution from exhaust, noise pollution, water contamination, soil pollution. In addition, highway projects also directly or indirectly damage the stream and wildlife ecology near highways. Studies in Canada, for example, indicate a correlation between traffic intensity and lower density of calling anurans and between the density of paved roads within 1-2 km of wetland and the diversity of wildlife in that wetland (Fahrig, 1995).

Various new laws and regulations have emerged to mitigate the impacts of transportation projects on the ecosystem during the last thirty years. The following environmental laws/regulations are among the most encountered and should be aware of by transportation designers and practitioners:

• National Environmental Policy Act (NEPA), Public Law No. 91-190. 1970 • Clean Water Act of 1977, Section 401 and 404. • Endangered Species Act of 1973, as amended, 16 USC 1531 et seq. • Coastal Zone Act Reauthorization Amendments of 1990-section 6217. • Coastal Resources Management program-October 1987. • Federal Coastal Zone Management Act of 1972, P.L. 92-583, as amended. • Section 4(f) Evaluation and Approvals for Federally- Aided Highway Projects with Minor Involvement with Public Parks, Recreations Lands, Wildlife and Waterfowl Refuges and historic Sites, December 23, 1986-49 USC303. • Migratory Bird Treaty Act. • Fish and Wildlife Coordination Act

Since Congress adopted the National Environmental Policy Act (NEPA) in 1969, the Federal Highway Administration (FHWA) has established various policies and procedures to help meet its social, economic, and environmental responsibilities while accomplishing its transportation mission. The FHWA Environmental Policy Statement (EPS) is a formal expression of FHWA’s commitment to protection and enhancement of the environment. The FHWA provides the policy

2 grounds and associated procedures for development of environmentally sound projects. It is clear from the FHWA environmental policy that environmentally sound transportation system is the ultimate goal, and it is the responsibility of state transportation agencies to meet these standards.

Powered by the National Environmental Policy Act (NEPA), Clean Water Act (CWA) and Clean Air Act (CAA), more and more stringent legislations have been promulgated to regulate specific environmental issues associated with transportation. For instance, the Fish and Wildlife Coordination Act (FWCA) requires conservation, maintenance, and management of wildlife resources for any project that involves impoundment, diversion, channel deepening or other modification of a stream or other water bodies. In light of ever tightening environmental regulations, selection of a BMP is no longer driven only by practical feasibility. Overall environmental soundness including wildlife ecology is also influencing the permitting process.

Although various engineered structures such as wildlife overpasses, underpasses, and upland culverts have been practiced, an integrated guideline regarding their application and performance is lacking. Some of the most effective techniques for facilitating wildlife movement (e.g. overpasses) are also quite expensive. To maximize the use of limited resources in transportation agencies and to help agencies comply with regulatory requirements, an improved decision- making process is needed to guide state DOT designers and practitioners on selecting the most economical and effective mitigating strategies.

The objectives of this project are:

• To update our knowledge base on the BMPs used for mitigating transportation impacts on the stream and wildlife ecology, and • To present recommendations/guidelines for transportation designers and practitioners on selecting the BMPs.

2. Impacts of Highway on Wildlife

A large body of literature data has revealed the tremendous impacts of massive road constructions and heavy highway operations on the wildlife ecology. Some most well documented effects are summarized as follows.

2.1. Direct habitat loss

The most direct damage of road development to wildlife is occupation of land or area, which serves as the habitat of animals and plants. Wildlife was forced to find a new place for habitat and foods, which often results in large quantities of death. In the Netherlands, the loss of habitat during 1980-1993 due to construction of rural sealed roads was 0.18 million hectares, constituting an annual loss of 0.04% of rural land (Cuperus et al.,1999). A recent study by the National Research Council (1997) estimates that approximately 20 million acres or 8.1 million hectares of natural habitat has been converted to US highways, streets, and adjacent rights-of- way. This represents approximately 1% of the contiguous United States or an area about the size of South Carolina. The number did not include private roads, parking areas and driveways.

3 The variability in habitat delineation across the nation makes it very difficult to follow wildlife trends. However, using a macro-habitat perspective of landscape features, Flather et al. (1999) described the decreasing trend in wildlife associated with the habitat loss in the United States. Landscape structure that influences the distribution and abundance of wildlife is primarily affected by vegetation cover and how the land is used by humans (Forman 1995; Janetos 1997). Vitous et al. (1997) identified human land use as the primary force changing biological diversity. The cumulative effect of the land-use change has resulted in a number of critically endangered ecosystems (where the presettlement extent of system is reduced by more than 98%) (Noss and Petter, 1995). Of the studied habitats, six were in the Rocky mountain region, seven in the northern and pacific coastal regions, and nine in the south. May (1990) concluded that this has resulted in efforts to save the few remaining individuals of endangered species to avoid extinction, as reflected by the Endangered Species Act of 1973.

The impacts of direct habitat loss on wildlife may vary with the area that a highway transects. Some habitats such as “critical habitats” for endangered species could be more important than disturbed habitats in urban setting. Uniqueness and importance for wildlife are factors that need to be considered early in transportation planning to avoid and/or minimize impacts to wildlife. Special cautions should be exercised to include habitat loss as a significant part of environmental studies when road projects pass through public lands such as park, wildlife refuge, forests and wilderness area (Harper-Lore, 2002).

2.2. Degradation of habitat quality

Road development can cause serious deterioration in quality of both terrestrial and aquatic habitats. Erosion from poorly constructed or rehabilitated sites can lead to slope movement causing downstream siltation, thereby ruining spawning beds for fish; Constriction of flows at water crossings can make the current too fast for some species; Alterations of flood cycles, tidal flows, and water levels can upset trophic dynamics by affecting the life cycle of plankton, and have corresponding damaging effects on the rest of the food chain. The cumulative effects of modification of aquatic habitats through impoundment, channlization, dredges along with sediments and water pollution has resulted in dramatic declines of the North America naiad fauna in last century (UN, 1999).

The presence of motor vehicles often causes contamination of the soil, air and water adjacent to the road. In the case of surface water, well beyond the immediate surroundings, chronic contamination can be a serious problem for animal species, especially those at top of the food chain because of bioaccumulation of the pollutants generated thought various road development activities (WHO, 1993).

Noise associated with road development and usage can also impact wildlife habitats. Forest interior birds, ovenbird, redheaded woodpecker, cuckoo, owl and hawks have specific habitat requirement that can be affected by highway noise (Forman and Deblinger, 1998). Rejjenn et al (1995b) showed evidence that in woodland, noise is probably the most critical factor in causing reduced density of birds close to road and also the most critical factor in open land. For example, the population of meadow birds, which are of international importance, in the western part of the

4 Netherlands was estimated to have decreased by 16% because of the denser network of extremely crowded main roads near their habitat.

In addition to direct land occupation, the pollution and other general disturbance by highway operation may extend to 30 m, sometimes even 100 m, from the road edge. Recent research showed that some of the adverse environmental effects may extend several hundreds of meters away from the road. Forman and Deblinger (1998) described a so-called “road effect zone”, whose size and extent may vary from area to area. They estimated that such effect zones may account for 15 to 20% of the land in the United States.

2.3. Fragmentation of habitat and population

Highways often constrain or destroy the living activities of both terrestrial and aquatic animals and result in fragmentation of habitat and population due to following facts:

• Highway structures (median strip, fences, etc.) can split existing habitat or population into fragments; • Road development alters the habitat topography, deteriorating habitat living conditions for animals; • Heavy traffic volume virtually exacerbates the barrier function of highways. Studies indicated that an average daily traffic (ADT) of 10,000 could completely block animal movement for a number of species (FHWA-PL-02-011).

Highway fragmentation of vital habitat can jeopardize the local population of wildlife. For instance, in Glacier National Park in Montana, construction of US Highway 2 interrupted the habitat of mountain goats that have to cross the highway to access to an important mineral lick (Singer and Doherty, 1985). During wet seasons/years when much of their habitat is flooded, wildlife to the south of I-75 in the Big Cypress Swamp and adjacent environs in Florida has to rely on the wildlife crossing to move into the dry habitat to the north of the highway (Evink 1990, Evink 1996). Fowle (1996) observed that by separating aquatic habitat and upland nesting habitat for turtles, or terrestrial habitat and aquatic breeding sites for amphibians, highway could pose significant adverse impacts on local population of those species. Diaz et al.(2000) hypothesized that the combined effects of fragmentation and predation in small remnants of forests had led to extinction of the forest lizard Psammodramus algirus in fragments smaller than about 90 hectares. Recolonization seemed to be prevented by the very limited dispersal abilities of these lizards.

Wildlife populations suffer when fragmented by roads. Dispersal of individuals between populations is important for gene flow, movement of individuals to maintain small populations, and decolonization of areas where species has been extirpated (Shaffer 1985; Dodd 1990; Gibbs 1993; Fahrig and Merriam 1994).

Road crossing can also fragment habitat for fish and other aquatic animals (Furniss et al. 1991; Ruediger and Ruediger 1999). Such separation can result in the inability of individuals to find each other for reproduction. This is especially true for species that are shy of roads or do not cross high traffic roads, such as the wolf and grizzly bear (Gibeau 1996; Paquett and Callahan 1996). Pronghorn antelope (Bruns 1997) and mountain lions (Van Dyke et al. 1986) have also shown reluctance to cross roads. In Germany, genetic difference was observed in common frogs in places where roads were barriers (Reh and Seitz 1990).

5 Wildlife species composition changes due to avoidance of roadway by some animals (Lyon 1983). Most recent research indicates that road avoidance has been demonstrated for bobcats (Lovallo and Anderson 1996), wolves (Thber et al., 1994), grizzly bear (MeLellan and Shackleton 1988), and black bears (Brody and Pelton 1998). In western North Carolina, a study of black bears by Brody and Pelton (1989) found that these bears almost never crossed an interstate highway. Of the roads the bears did cross, those of low traffic density were crossed more frequently. Avoidance of areas adjacent to roads was apparent in a study of bird breeding and nesting in Netherlands (Illner 1992; Reijnen 1995; Reijnen and Thissen 1997). Species, which are most vulnerable to local and regional extinction following habitat fragmentation, include naturally rare species, wide-ranging species, interior species, and species with low reproductive capacity (Meffe and Carroll, 1994).

2.4. Road kill

Road-related mortality represents the most visible and direct effect on wildlife. Road mortality has impacted significantly some species such as white-tailed deer, black bear, Florida panther and so on. Additionally, wildlife-vehicle collisions are a serious safety problem for human in North America, Europe and Japan. Cook & Paggett (1995) estimated the cost at $ 1.2 million per year nationwide in property damage and human injury associated with deer vehicle collision (DVC).

Recent studies indicate that road mortality (motorist safety and wildlife species impacts) has been a global concern.

In Australia, for example, the number of frogs and reptiles killed annually on roads has been estimated at around five millions. A wildlife information and rescue service has estimated that up to 12 million native animals are killed on Australian roads each year. In the Netherlands, Jonkers and De Vries (1977) estimated that the yearly average number of animal traffic casualties at 653,000 birds and 159,000 mammals. In the UK, an estimated 10 million of birds were killed on roads every year (Spellerberg, 2002). Deer are particularly at risk. Romin and Bissonette’s report (1996a) provided a comprehensive account of deer mortality on highway (Table 1). Table 1 also shows that between 1982 and 1991 the number roadkills has increased considerably in most states.

Road kill is perhaps the greatest, directly human related source of wildlife mortality throughout the United States and worldwide. For some species its impacts are significant at population level (Natasha 1998). Farhrig et al (1995) after a detailed study of effects of traffic on amphibian density concluded that road kills could be contributing to worldwide declines in amphibian population. For some endangered species, road kills are also thought to be an important contributing factor to mortality (Spellerberg, 2002).

6 Table 1: State–wise changes in deer mortality on USA highways from 1982-1991 (from Romin and Bissonette, 1996)

State No. deer killed (year) Actual Percenta Lowest year Highest year Count made? Change

Alabama no data Alaskab 57-77/year Arizona no response Arkansas 3,603(1990) 4,200 (1989) no (14) California 15,000/year no Colorado 5,202(1983) 7,296 (1991) no 40 Connecticut 1,429(1982) 2,423(1986) yes 70 Delaware 103(1982) 268(1991) yes 160 Florida no data Georgia 50,000/year no Hawaii no response Idaho no data Illinois 2,797(1982) 15,560(1991) yes 456 Indiana 2,858(1982) 12,671(1991) yes 343 Iowa 4,805(1982) 9,248(1988) yes 92 Kansas 2,492(1982) 3,536(1991) yes 41 Kentucky 1,490(1982) 4,677(1990) yes 214 Louisiana 1,500/year no Maine 2,000(1080’s) 3,000(1990’s) no 75 Maryland no response Massachusetts no data Michigan 18,045(1982) 44,374(1991) no 146 Minnesota 11,471(1982) 16,280(1991) yes 42 Mississippi no data Missouri 4,779(1982) 9,519(1987) yes 99 Montana no data Nebraska 1,261(1982) 3,341(1991) yes 42 Nevada no response New Hampshire 455(1982) 1,000(1990) yes 120 New Jerseyc 455(1982) 10,496(1986) yes 20,202 New Mexico no data New York 7,269(1984) 10,978(1991) yes 51 North Carolina 5,000-8,000/year no

7 Table 1(contd.)

State No. deer killed (year) Actual Percenta Lowest year Highest year Count made? Change

North Dakota 2,500(1980’s) 3,000(1990’s) no 20 Ohio 8,587(1982) 20,215(1991) yes 135 Oklahomad 450(1985) 495(1983) yes (9) Oregon no data Pennsylvania 24,648(1983) 43,002(1990) yes 75 Rhode Island no response South Carolina 840(1982) 3,689(1991) yes 339 South Dakota 2,166(1982) 3,363(1991) yes 55 Tennessee no response Texas (19,000/year) Utah 1,826(1980-81) 5,502 (1988-89) yes 201 Vermont 1,105(1982-83) 1,514(1990-91) yes 37 Virginia 1,446(1982) 3,427(1990) yes 137 Washington no response West Virginia 3,844(1985) 9,515 (1991) yes 148 Wisconsin 28,878(1982-82) 76,626(1989-90) yes 165 Wyoming 987(1988) 1,756(1982) yes (44)

a. Values in parentheses are decreases. b. Highest yearly estimate was use to calculate total deer killed in 1990. c. Actual counts through 1988-1989, estimated 10,000 deer/year from 1989-1992. d. Record keeping discontinued after 1985 due to unreliable efforts.

3. Engineered Mitigation Strategies

To mitigate the habitat fragmentation and road kills caused by highway construction, various wildlife passages have been constructed across the highway to connect the habitat and facilitate the movement of wild species across the highway. For example, various engineered tunnels have been widely used to help mitigate the fragmentation of habitat in Europe, Australia, Canada and the USA. Some of the most commonly used engineered structures are summarized and discussed as follows.

3.1. Wildlife Overpasses

The overpass approach has been considered quite successful for the largest spectrum of animals (USDOT and FHA, 2002). Figures 1-2 show two common overpasses used in New Jersey (TRB, 2002) and Germany (TRB, 2002). The presence of habitat and structure on overpasses allows for use by everything from insects to large carnivores. The most effective overpasses range in width from 50 m wide on each end narrowing to 8-35 m in the center, to structure up to 200m wide. Pfister et al (1999) observed that structures at least 60 m (196.8 ft) wide were more effective than overpasses narrower than 50 m (164 ft), especially for larger mammals. It was noted that animal

8 behavior on the overpasses was more normal on the wider structures. Soil on these overpasses ranging in depth from 0.5 – 2 m, allows for the growth of herbaceous vegetation, shrubs and small trees. As guidance for soil depth for plants on overpasses, the Germans use 1/3 m for grass, 2/3 m for shrubs, and 1.5 to 2 m for trees (USDOT and FHA, 2002). Some overpasses contain small ponds fed by rainwater. Sometimes board fence are used along the edge of an overpass to prevent traffic noise and lights from disturbing wildlife.

Figure 1. Overpass being used by deer and Figure 2. Vegetated overpass in German Other wildlife in New Jersey (91.46m wide) approximately 50 m wide.

Primary advantages of overpasses relative to underpasses are that they are less confining, quieter, maintain ambient conditions of rainfall, temperature and light, and can serve both as passage ways for wildlife and inter mediate habitat for small animals such as reptiles, amphibians and small mammals. They are probably less effective for semi-aquatic species, such as muskrats (Ondatra zibethica), beavers (Caster canadensis) and alligators (Alligator mississippiensis). By providing intermediate habitat, overpasses may provide the only feasible means for allowing various species of animals to cross highways. The major drawback is that they are rather expensive.

France was the first European country to use overpasses (USDOT and FHA, 2002). In 1991, France had 125 overpasses in place and continues to use them as principal structures for habitat connectivity and motorist safety. Some overpasses are quite large, such as the 800-m-wide overpass at Forest Hardelot (France). Germany had 32 overpasses, with 8 additional ones under construction and 20 more planned in 2002, with a width ranging from 8.5m to 870 m. The Switzerland had more than 20 overpasses with widths from 3.4 m to 200 m by 2002, and is continuing to build new overpasses (USDOT and FHA, 2002).

Although wildlife overpasses has been largely a European phenomenon, application in the U.S. has been growing. Table 2 listed a number of major structures in Florida, Hawaii, New Jersey and Utah. The New Jersey overpasses, among the first in the United States, were completed in 1985 at a cost of $12 million. The two overpasses were designed to provide connectivity across I-78 (a six-lane highway) at an approximately 2-mile stretch that crossed the Watchung Reservation in Union Country. Although no formal research has been conducted, deer have been observed using the crossing and the health of local population indicates the success of the overpasses (TRB, 2002).

9 Table 2. State use of structural measures for wildlife (NCHRP, Synthesis 305, 2002, pp30-31)

10 Table2 (Continued)

11 3.2. Wildlife Underpasses

Wildlife underpasses are constructed through bridges (up to 30 m wide, 3-5 m high) and/or large culverts over dry land and sometimes land and water as shown in Figures 3-4. The target species of this structure are medium-sized and large mammals although smaller animals can also use it. The length and height of these large culverts and bridges varies with the wildlife expected to use them. Vegetations, stump and piles of debris often provided under large crossing structure as cover for smaller animals. These structures provide relatively unconfined passage for wildlife with plenty of light and air movement, but generally too dry for some species of amphibians. Wildlife underpasses with open median provide a certain amount of intermediate habitat for small mammals, reptiles and amphibians. However, open median design is much noisier than continuous bridges and may be less suitable for species that are sensitive to human disturbance. While less expensive than overpasses, wildlife underpasses are also fairly costly.

Twenty-three states reported using underpasses for wildlife (Table 2). Some species being addressed included bobcat and coyote in San Bernardino, California; Deer in most states and goats at Glacier national Park, Montana (Figure 3).

Figure 3. Snowslide gulch bridge for goats on Figure 4. One of 23 wildlife underpasses on I-75 Highway 2 near Glacier national Park, Montana (Alligator Alley) in Southern Florida California (3m high x 3m wide x11m long) (36.5m high x 2.44m high)

Florida used 2.44m high and 7.32m wide box culverts for a variety of species in central and south Florida (TRB, 2002). Depending on the remoteness of the area of use, these concrete boxes can be either cast in place or pre-cast for shipment to the site. Fencing associated with these crossing was 3.04 m in height with three strands of barbed wire on an outrigger. A wide variety of species use the culverts, including the Florida panther and black bear (Land and Lotz 1996; Roof and wooding 1996).

Wyoming conducted a research on a wildlife crossing (6.08 m wide, 9.12 m long and 3.35 m high) on US-30 through Nugget Canyon between Kemmerer and Cokeville and found that approximately 2,000 animals (elk, mule deer and antelope) had used the crossing (Gordon, 2002B). North Carolina is constructing three underpasses for black bears at a new location, US-64 near Outer Banks in Washington County. The dimensions will be approximately 38 m wide, 2.4-3 m high and 100 m long (Van Manen et al. 2002).

12 3.3. Upland Culverts

A culvert is a closed conduit primarily used to convey water from one area to another, usually from one side of road to the other side. Culverts can be divided into two functional types: Stream Culvert (also called Stream Crossing) and Upland Culvert (also called Runoff Management).The first culvert type, stream culvert, is required where the roadway crosses a stream channel to allow pass downstream. The second type culvert, upland culvert, is the one that is strategically placed to manage and route roadway runoff along, under, and away from roadway. However here in section 3.3 and 3.4, upland culvert and stream culvert will be used as animal passages.

Not all species of wildlife readily use stream or river corridors for travel routes. Therefore, a comprehensive approach to the maintenance of habitat connectivity must include structures allowing overland movement between wetlands and uplands. Figures 5 shows one of the upland culverts incorporated with fine mesh fence for amphibians in the Netherlands. Figure 6 shows one of the culverts designed for small and medium-sized mammals in Banff National Park. Movements to and from wetlands are particularly important for amphibians, reptiles and other small animals. Wildlife overpasses and underpasses (see above) may provide upland passage for larger species. Relatively small amphibian and reptile tunnels may be a cost effective means for mitigating highway impacts where roads and highways are located between wetland and upland habitats. Box culverts are generally preferable over pipes. Larger culvert will generally accommodate more species than smaller ones. Open-top culverts can be expected to provide more light and moisture, and will be more effective for facilitating amphibian’s movements. Although there is evidence that amphibian and reptile tunnels are effective when used with two-lane roads, it is not known how effective they will be for facilitating passage beneath highways of four or more lanes. Guidance structures are usually needed to direct target animals to culvert under the roads (see details in Fencing below)

Upland culvert systems were observed in most of the European countries and culverts are placed in known areas of amphibian movement to alleviate mortality on roadways. The Dutch, for example, are using concrete pipes, metal pipes, or rectangular concrete tunnels approximately 0.4 to 2.0 m in diameter in conjunction with fine mesh fencing for amphibians and reptiles, as well as other small animals.

Figure 5. Fine mesh fence and culvert for Figure 6. Box culvert used by wildlife in Banff small mammals in Europe. National Park

13 Table 2 reports that a number of states in the US are using culverts in different applications for a variety of species. Florida, Montana, New Hampshire, Texas, and Wisconsin are using culverts for reptiles and amphibians. Nebraska and South Carolina are using them for turtles.

3.4. Oversize Stream Culverts and Bridges

Where roads and highways cross rivers and streams, expanded bridges that can provide upland corridors adjacent to waterway can provide passageways for many species of riverine wildlife, as well as other species that may utilize stream corridors for travel. Higher bridges with wider areas for passage underneath tend to be more successful than low bridges and culverts

Where culverts are used to cross-streams and small rivers, oversize culverts, large enough to allow for wildlife passage, maybe used. Again, box culverts generally provide more room for travel than large pipes. Efforts to provide natural substrate, including large flat rocks as cover for small animals, will enhance their use by some species. Construction of benches on one or both sides of stream to allow dry passage during normal high water periods will also enhance these structures. The optimum size for this structure is not known but, generally, the larger the more effective. Given sufficient height, these culverts can even allow larger mammals, such as deer, bear and other species that ordinarily follow riparian corridors for movement, to pass safely under roads. Proper sizing of the culvert depends on site-specific considerations and hydraulics, but including the natural streambed and as much adjacent upland as possible proves most successful. Culverts are less expensive than expanded bridges, but also less effective.

A number of states reported uses of specialized culverts and bridges in streams for uninterrupted or improved fish passage (Table 2). In Washington, there are 4,463 sites where state highways cross fish-bearing streams. Of these locations, more than 500 “problem sites” were identified. These were sites where the drop of the culvert’s outfall was too high, existing water velocities are too great, or water depth was too shallow for adequate upstream fish passage. The state transportation agency is fixing these culverts using a “priority Index System”, which considers potential habitat improvements. These efforts have been documented by Carey and Wagner (1996). Oregon has a similar program to retrofit culverts to increase the value and accessibility of upstream habitat.

Stream restoration is also becoming a part of transportation projects. Harman and Jennings (2002) describe restoration project in North Carolina that used the natural channel in the design technique. The project was to improve water quality and habitat, reduce stream bank erosion, and enhance floodplain functions. Enhancement to stream was provided during Maine Turnpike construction for two high-quality trout stream crossings to improve productive habitat and the carrying capacity of the streams. Log flow deflectors were provided to increase the depth and velocity of the main channel, create pools, scour fine sediments, and divert water flow from eroding banks. Submerged woody debris and boulders were placed to provide additional habitat. Log bank undercut structures were provided to stabilize stream banks (Farrell and Simmons 2002).

Fish passage structures in urban streams are also becoming better understood. Hegberg et al. (2002A and B) discussed related hydrologic and resource issues and presented approaches on the hydraulic design and analysis. Recommendations for evaluation of target fish species characteristics, site-

14 specific base flow hydrology, and hydraulics of structures are provided. They also present a list of procedures for design of the passage structures. To address the specifics of culvert design and placement, the Pacific Northwest National Laboratory in the state of Washington started a culvert testing for juvenile salmonid passage (Pearson et al. 2002). Full-scale models will be used to look at hydraulic conditions (velocity, turbulence, and water depth) associated with various culvert designs under various slopes and flow regimes.

States are also considering freshwater mussels in construction of bridges and culverts. Savidge(1998) described erosion control measures, elimination of direct drainage from bridges, and structural features on several projects in North Carolina that were the result of protected mussel species. Reutter and Patrick (2002) reported on measures taken for mussels in a bridge replacement on Allegheny River 80.5 km north of Pittsburgh, Pennsylvania. The assessment included a construction/ demolition option evaluation, hydraulic and hydrologic analyses, and the development and implementation of a mussel relocation program with subsequent monitoring of success.

3.5. Viaducts

Viaducts are areas of elevated roadway that span valleys and gorges. Figures 7 and 8 provide a general view of two viaduct structures (TRB, 2002). They are different from bridges in that they are typically higher and cross-streams and rivers as well as adjacent valley habitats. Viaducts provide relatively unrestricted passage for riverine wildlife and species that utilize riparian areas for movement. The height of viaducts allows for maintenance of vegetated habitat beneath the structure and provides a sense of openness that is required for many species.

Most existing viaducts were constructed because it was the best or most esthetic way to cross a valley or ravine from an engineering standpoint rather than to accommodate wildlife. However, consideration and design for wildlife are increasing, especially in Europe. There are three viaducts (593m, 160m and 265m in length, respectively) used in Slovenia on the Ljubljana-Trieste highway. These viaducts are being successfully used by brown bear, wolf and a number of ungulates.

Based on the survey in Table 2, none of the states reported using this concept for wildlife connectivity. Although there are numerous viaducts in the United States and Europe, wildlife movement was not the primary motive in their development. However, wildlife connectivity could be one of the multiple considerations resulting in a viaduct.

Figure 7. Viaduct on Highway 241 Figure 8. Viaduct on the Ljublijana- in southern California Trieste Highway in Slovenia

15 3.6. Fencing

Fencing for large and medium-sized mammals is required for underpass and overpass system to be effective. Standard fencing may not be effective for some species (black bear, coyotes), but manipulations of wildlife trails and vegetation can also be used to guide animals to passage ways and learning may enhance their effectiveness for these species over time. Fencing for large animals must also include one-way gates or earthen ramps to prevent animals that get onto roadways from being trapped between fences on both sides of road. Fencing for small mammals, reptile and amphibians must be specifically designed to prevent animals from climbing over and through, or tunneling under the fencing. Short retaining walls (Figure 9) can provide relative maintenance-free barriers for reptiles, amphibians and small mammals (USDOT and FHA, 2002). Table 2 shows that 28 of 34 responding states use all kinds of fences to protect different animals from highway disturbing.

Figure 9. Short wall to keep reptiles and amphibians from road

4. Design Guidelines

4.1. Design considerations

Placement. Placement of passage structures can be very important for some species, even relatively mobile species. Travel distance (to reach a passage way) is especially important for small animals. Mammals are generally capable of learning to use underpass or overpass system and may transfer that knowledge to succeeding generation (Ford 1980, Singer and Doherty 1985, Land and Lotz 1996, Paquet and Callaghan 1996). This is unlikely to be the case with reptiles and amphibians. The learning ability may result in improving mitigation success over time for more mobile species even for underpass that is not placed at traditional crossing points. Even so, many people consider placement to be the single most important factor affecting the success of passage structure (Podlucky 1989, Foster and Humphrey 1995, Rodriguez et al.1996, Rosell et al. 1997). However, few methodological approaches to determine the placement of mitigation passages along road corridors have been explored. The following three methods are most often used in passage structure design:

(1). The location of wildlife passage is derived from information on the spatial distribution of wildlife-vehicle collisions primarily where road kill density are highest (Evink, 1996). Databases such as Wars200-Wildlife Accident Reporting System (Sielecki, 2000) and the Washington State DOT deer kill database (Carey, 2002) are being developed by transportation agencies to identify

16 wildlife accident prone locations and wildlife accident trends, direct wildlife accident mitigation effort and evaluate the effectiveness of wildlife accident mitigation techniques.

(2). The other method for locating passages might utilize data obtained from radio-monitoring of animal movements or tracking surveys along roads (Kohbler and Adamic 1999, Scheick&Junes 1999). Florida and Montana DOTs are financing these radio-telemetry studies for important species in important ecological areas of their states (Waller and Servheen ,1999; Eason and McCown, 2002). But not all transportation planners and land managers have the luxury of possessing data on animal movements, their crossing location and road-kill location or the time to initiate studying to acquire these data because infrastructure-planning decisions are usually made over a short period of time.

(3). Modeling habitat linkages with a geographic information system (GIS) is another means of determining optical placement of wildlife crossing structures because basically, this method associates characteristic of topography (e.g. Elevation, slope, greenness, wetness and so on) with activity of an animal (Clevenger et al, 2002). Briefly, this method relates the frequency of the activity of a certain animal to the combination of various topographical characteristics of its surroundings based on field observation and literature. The highway area which has the same or similar topography with highest activity frequency of the animal will has the highest probability for this animal to cross. In planning mitigation passages for this kind of animals, the wildlife habitat linkage placement can be easily identified by comparing the topography of planning area with the conclusion. This method represents a useful tools for resource and transportation planners charged with determining the location of mitigation passage for wildlife when baseline information is lacking and when time constraints do not allow for data collection before construction.

Size. It is difficult to determine critical size thresholds fro passage structures because these size thresholds undoubtedly vary from species and species. For some species openness-the size of underpasses is more important than absolute size (Foster and Humphrey, 1995). Tunnel layouts that allow animals to see the opposite end of a wildlife passage were positively correlated with utilization for some species (Rosell, 1997). In general, bigger is better. However, some species such as old world badgers and some small mammals may prefer small underpasses. Based on studies of ecoducts in Europe, some have recommended that wildlife overpass be at least 50m wide (Keller and Pfister, 1997).

Light. Some species are hesitant to enter underpasses that lack sufficient ambient light (Jackson,1996). Conversely, there is evidence that species that are sensitive to human avoid areas that are artificially lit (Beier, 1995). Maintenance of natural lighting through the use of overpasses, large underpasses or open-top (grated) underpasses may help address these concerns.

Moisture. Maintenance of wet substrate is important for some amphibian’s species. Shrews are often more active (or more mobile) on rainy nights and also may prefer wet substrates for traveling. Underpasses at stream crossings will probably suffice for species that utilize riverine or riparian habitat. However, many amphibian species do not use riparian or riverine areas for migration and the presence of flowing water may deter usage by these species. Open-top (grated or slotted) underpasses do provide sufficient moisture for crossings that lack flowing water. Alternatively, innovative storm water systems might be designed for closed-top systems that would provide enough water to maintain moist travel conditions without creating flooded or stream-like conditions. Proper

17 drainage is important, because some wildlife species are less likely to use structures when they contain standing water (Rosell et al 1997, Santolini et al 1997).

Temperature. Small underpasses may create temperature disparities (inside vs. outside) that can deter use by amphibians (Langton 1989b). Large underpasses or open-top systems that allow more airflow may help address this concern.

Noise. Traffic noise can be a problem for some mammals, especially those sensitive to human disturbance. Certain underpasses designs (those with expansion joints and those with uncovered medians) can be quite noisy (Foster and Humphrey 1995, Santolini et al 1997). Open-top designs would be inappropriate for species that are sensitive to traffic noise. Overpass systems that incorporate tree and shrub buffers along the edges appear to be much quieter than underpass systems.

Substrate. Some animals feel more secure utilizing crossing systems if they provides sufficient cover. For example, rows of stumps in an underpass appear to facilitate use by small mammals (Linden 1997). Maintaining or replicating streambed conditions within over-sized culverts may facilitate use by salamanders, frogs, small mammals and aquatic invertebrates, thereby maintaining habitat continuity in the area of stream crossings. Certain species (e.g. Mountain pygmy possums, Burramys parvus) with very specific substrate requirements may require special attention at wildlife crossing (Manserrgh and Scotts 1989).

Approaches. Characteristics of the approaches to underpasses or overpasses may affect their use by some species. Forested species, such as black bears (Ursus americanus), prefer well vegetated approaches Other species, such as mountain goats, appear to prefer approaches that provide good visibility. At Glacier National Park, mountain goats have apparently shifted movement patterns away from a traditional crossing point rather than utilize an underpass that offers poor visibility on the approaches (Pedevillano and wright 1987). The presence of covers on the approaches, in the form of vegetation, rocks and logs, may enhance use by a variety of small and mid-sized mammals (Rodriguez et al 1996, Rosell et al 1997, Santolini et al 1997). However, vegetation at the entrance of an underpass may deter some mammals that are wary of conditions that provide ambush opportunities for predators.

Fencing. Although some species may utilize underpasses or overpasses systems without fencing. Some forms of fencing do appear to be necessary for most species. Fences help guide animals to passage systems and prevent wildlife from circumventing the system. Mountain lions moving along stream corridors have been observed to leave stream valleys and cross over highways rather than utilize large culverts (Beier, 1995). This has also been observed for two species of turtles in Massachusetts. Ungulates commonly seek to avoid underpasses and will generally use them only if other access cross the highway is barred (Ward, 1982). In Banff national Park an elaborate system of multiple arched fences is used to deter wildlife from walking around fences. However, some species are relatively good at circumventing fences by climbing over (black bears) or digging under (coyotes, Canis latrans, and badgers) standard fencing. Standard fencing is also ineffective for small animals.

If mitigation objectives are defined too narrowly, mitigation projects can create as many problems as they solve. An obvious example of this is the use of fencing along highways to reduce wildlife road

18 mortality, often for human safety reasons. When these fences are installed without crossing structures, they can compound the fragmentation effects of highway on populations and habitat. In designing wildlife passages, it is important to remember that different structures are not designed for use by a broad range of wildlife, a project that that facilitates passage for one species might constitute an absolute barrier for another.

Wildlife overpass, underpass, upland culvert and viaduct are passage structures for terrestrial and amphibian species. As discussed above, these structures are widely used in North America, Europe and Australia for mitigating highway impacts on the wildlife ecology. However, there have not been standard design criteria for these passage structures so far (Spellerberg, 2002) because different species of animal may need different passage structure and no study of comprehensive effectiveness of passage structure was conducted so far.

4.2. Design of fish passages

Fish passage design is very important and complicated because:

• Well-designed fish passage is necessary for life cycle of some migrating fish species such as wild salmon and sea-run trout, which need upstream habitat for spawning. Poorly-designed passage, for example, will wash them back downstream because of the stream velocity in the culvert or outfall drop is too high.

• Fish passage design involves more disciplines including engineering, hydrology and biology.

Selected structures for fish passage are summarized as follows.

4.2.1. Road-Crossing Culverts

The Washington Department of Fish and Wildlife (1999) provided a manual for the design of permanent new, retrofit, or replacement road crossing culverts that will not block the migration of salmonids. Passage design for other fishes can also consult this manual. There are three design options provided in this manual. A general flow chart of the culvert-design process for fish passage is shown in Figure 10.

The no-slope design option results in reasonably sized culverts without requiring much in the way of calculations. The hydraulic design option requires hydrologic and open channel hydraulic calculations, but it usually results in smaller culverts being required than no-slope design option. Smaller culverts may trap more debris, however, so a factor of safety must be applied. The hydraulic design option is based on velocity, depth and maximum-turbulence requirement for a target species and age class. The stream–simulation design option involves constructing an artificial stream channel inside culvert, thereby providing passage for any fish that would be migrating through the reach. It is difficult in most situations, if not impossible, to comply with velocity criteria for juvenile fish passage using the hydraulic design option. The no-slope and stream-simulation design, on the other hand, are assumed to be satisfactory for adult and juvenile passage: thus, they tend to be used more at sites where juvenile fish passage is required. Application of the no-slope design option is most effective for relatively short culverts at low-gradient sites. Following is a brief

19 introduction to no-slope design option. More about hydraulic design and stream –simulation design option might be found at www.wa.gov/wdfw/hab/engineer/cm/ (Design of road culvert for fish passage, 2003)

No Slope Hydraulic Design Stream Simulation

WcB=Wch WcB=1.2Wch +2’ Zero slope L •channel slope<.2D Culvert length Slope up to 1.25 • channel slope

Countersink fish Countersink

Check inlet fish passage design flow Specify bed, downstream Bed stability control Max. velocity Size,slope,and roughness

Set elevation: Countersink at low flow Match tailwater at high flow

Correct channel profile

Check flood capacity

Final design or other option

Figure 10 Culvert design process

(Note: W cB= Width of culvert bed Wch=Bankful width of channel L= Length of culvert D= Diameter of culvert )

No-Slope Design Option. Successful fish passage can be expected if the culvert is sufficiently large and is installed flat, allowing the natural movement of bedload to form a stable bed inside the culvert. The No-Slope Design Option creates just such a scenario. A no-slope option is defined by a culvert with:

• Width equal to or greater than the average channel bed width at the elevation the culvert meets the streambed. • A flat gradient, • The downstream invert is countersunk below the channel bed by a minimum of 20% of the culvert diameter or rise, • The upstream invert is countersunk below the channel bed by a maximum of 40% of the culvert diameter or rise, • The possibility of upstream headcut has been taken into account and, • There is adequate flood capacity.

20 Generally, the no-slope design option might be applied in the following situations

• New and replacement culvert installations, • Simple installations: low to moderate natural gradient or culvert length (generally, 3% slope), • Passage required for all species, • No species design expertise or survey information required.

Information needed for the no-slope option includes:

• The average natural channel bed width, • The natural channel slope, • The elevation of natural channel bed at the culvert outlet, • The evaluation of potential headcut impacts upstream of the culvert.

A reasonable upper limit of no-slope design option is to use it at sites where the product of channel slope (ft/ft) and the culvert length (ft) doesn’t exceed 20% of the culvert diameter or rise. It should be noted that this limitation can be overcome by understanding and accounting for the implications of constricting the upstream end of the culvert with accreted bed or by installing a larger culvert. Any culvert shape can be used (round, pipe-arch or elliptical), but it must be countersunk a minimum of 20 % at downstream end and a maximum of 40 % at upstream end (see Figure 11).

The no-slope design option is, therefore, limited by slope and length. If a site does not comply with this limitation, the size of culvert (D) can be increased: the slope (S) can be decreased, or another design option should be used.

1. Culvert bed width 2. Culvert level equal to channel bed width

3. Downstream countersink 4. Upstream countersink 20% of rise of rise maximum

Figure 11. No Slope Option

4.2.2. Bridges

Where the design process leads away from a culvert as a viable crossing structure, bridges should be considered. This is particularly the case where the stream width exceeds 20 feet or stream slope is greater than about six percent, or when the movement of large debris is frequent. Crossing that is subject to debris flows needs special consideration. Alternatives in such a situation include fords, temporary bridges, bridges with high clearance and moving the road to where its crossing is less problematic.

21 While general considerations regarding the use of bridges at crossing are discussed in this design guideline (www.wa.gov/wdfw/hab/engineer/cm/), their actual design details are not provided. An experienced bridge design engineer is required for such an undertaking.

For the purpose of this guideline, a bridge is any crossing that has separate structural elements for the span and its abutments. Unencumbered by the dimensional limitations of culverts, a bridge can be large enough that the structure does not significantly affect the flood hydraulic profile. Piers and abutments can be drilled or buried deeply enough that there is very little risk of failure.

Like culverts, however, bridge designs must also comply with regulations; in this case, regulations addressing water crossings and the creation of new channels (WAC220-110-070 and 220-110-0800). And, just as in the case of culverts, bridge design must begin with consideration for habitat impact. Properly designed bridges are superior to culverts in terms of habitat preservation and restoration; however, mitigation measures may still be necessary to compensate for impacts from construction, bank armoring or other habitat losses caused by the presence of the bridge.

The channel created or restored beneath the bridge must have a gradient, width, floodplain and configuration similar to the natural existing natural channel upstream or downstream of the crossing. Where possible, habitat components normally present in these channels should also be included. In high-gradient situations, the stream-simulation width criteria may be used to determine channel width under the bridge.

Bridge-span calculations should begin with a consideration of required channel width and floodplain requirements and proceed to side-slope. Abutments should be placed at an angle that leads to natural stability. Large riprap retaining walls that encroach on the channel should be avoided. Wac220-110- 070 states that abutments, piers, piling, sills, approach fills, etc. should not constrict the flow so as to cause any appreciable increase (not exceed 0.2 feet) in backwater elevation (calculated at the 100- year flood) or channel wide scour and should be aligned to cause the least effect on hydraulics of water course. The purpose of the criteria is to limit the effect of bridge on the upstream channel, especially in channels with significant gravel bedload.

When an undersized culvert is removed and replaced with a bridge, some upstream channel instability is likely. This can be due to stored sediment above the culvert and /or channel incisions below the culvert. The result is excessive drop through the area of the crossing. The designer should carefully consider the channel headcut and regrade factors (see the discussion addressing channel regrade in chapter 7, Channel Profile at www.wa.gov/wdfw/hab/engineer/cm/). Some sort of grade control, temporary or permanent, may be necessary to ensure channel and habitat integrity.

5. Toward a Practical Strategy

To mitigate highway impacts on wildlife we must focus on reducing the impact of roadways on local populations and preserving ecological processes related to landscape continuity and metapopulation dynamics. Mitigation strategies that focus too much on preserving local populations may be too expensive to be fully implemented, given the large numbers of species involved. A practical strategy for mitigating highway impacts should fist focus on the landscape level, using the most effective techniques available to maintain landscape continuity and metapopulation dynamics within the

22 designated “connectivity zones”. In addition to the maintenance of some level of ecosystem function, cost-effective techniques should be practically employed throughout the highway alignment to maintain local wildlife populations.

According to Jackson et al (1998), a practical strategy for mitigating highway impacts on wildlife should include:

• Avoidance of highway fencing and Jersey barriers when not used in association with wildlife passage structures. • Use of small (e.g.2’x2’ minimum) amphibian and reptile passages wherever roadways pass along the boundary between wetlands and uplands. • Use of oversized stream culverts and bridges at stream crossings. • Selective use of viaducts instead of bridges at important stream or river crossing. • Use of landscape-based analyses to identify “connectivity zones” where mitigation efforts can be concentrated to maintain ecosystem processes. • Selective use of wildlife overpasses and larger underpasses within “connectivity zones.” • Monitoring and maintenance plans to ensure that mitigation system continue to function over time and that knowledge gained from these projects can be used to further refine our mitigation techniques.

6. Concluding Remarks

Traditionally, highway impacts to wildlife have been viewed in terms of road mortality and threats to selected populations of animals. Viewing this issue from a landscape ecology perspective, it is clear that highways have the potential to undermine ecological process through the fragmentation of wildlife populations, restriction of wildlife movements, and the disruption of gene flow and metapopulation dynamics.

Due to the complex nature associated with the natural ecological systems, selection and design of engineered structures are rather complicated. With the growing application of engineered structures worldwide, our knowledge base is also growing. This report provides up-to-the-date knowledge pertaining to selected key structures widely used to protect the wildlife ecology for both terrestrial and aquatic animals. The information provided herewith should be helpful to transportation designers to select BMPs for mitigating road impacts on ecological integrity.

7. Literature Cited

Adams, LW. and A.D. Geis, 1983. Effects of roads on small mammals. Journal of Applied Ecology 20:403-415 Anthony P. Clevenger et al. 2002. GIS-Generated, Expert-Based Models for Identifying Wildlife Habitat linkages and Planning Mitigation Passages. Conservation Biology 16(2): 503-514 Beier, P.1993. Determining minimum habitat areas and habitat corridors for cougars. Conservation Biology. 7(1): 94-108

23 Bishop, R.A., R.C.Nomsen, and R.E. Andrews. 1977. A look at Iowa’s Hungarian partridge. In: GD. Kobridger,ed., Peridix I: Hungarian partridge workshop. Central Mtns.and plains Sec. And North Dakota Chapter The wildlife Society , Dickinson, ND. 10-28. Brody, A.J. and M.R. Pelton 1989. Effects of roads on black bear movements in west North Carolina. Wildlife Society Bulletin.17:5-10. Bruns, E.H.1997. Winter behavior of pronghorns in relation to habitat. Journal of wildlife Management. 41:560-571 Carroll, j.P. 1987. Gray partridge ecology in North Dakota. In: R.o. Kimmel, J.w. Schulz, and G.J. Michell. Eds., Perdix IV: gray partridge workshop. Minn.Dep. Nat Resour., Madelia: 123. Carey, M. 2002. Addressing wildlife mortality on highway in Washington. In Proceedings of The International Conference on Ecology and Transportation. Center For Transportation and Environment, Raleigh, N.C., 2002. Cook, K.E., and P.M. Daggett. 1995. Highway roadkill; associated issues of safety and impacts on highway ectones. Task force on natural resources, Transportation Research Board. National Research Council, Washington D.C., USA. Dodds,C.K. 1990. Effect of habitat fragmentation on a stream dwelling species, the flattened musk turtle sternotherus depressus. Biological Conservation, 54, 1990, pp 33-45. Eason, T.H. and J. W. McCown, 2002. Black bear movements and habitat use relative to roads in Ocala National Forest, Florida. In Proceedings of The International Conference on Ecology and Transportation. Center For Transportation and Environment, Raleigh, N.C., 2002 Evink,G.L., 1990. Wildlife crossing of Florida I-75, Transportation Research Record 1279, Transportation Research Board, National Research Council, Washington, D.C., 1990, pp 54-59 Evink,G.L., 1996. Florida department of transportation initiative related to wildlife mortality. Trends in Addressing Transportation Related wildlife Mortality, proceedings of the transportation related wildlife mortality seminar. State of Florida Department of Transportation, Tallahassee, FL. FL-ER-58-96. Fahrig,L. and G. Merriam, 1995. Conservation of fragmented populations. Conservation Biology, 73:177- 82 Findlay. C.S. and J. Haulahan. 1997 Correlates of species richness in southeastern Ontario wet land. Biological Conservation. 11:1000-1009. Flather,C.H., S.J. Brady, and M.S. Knowles, 2000. Wildlife Resource Trends in the United States: A technical Document Supporting the 2000 USDA Forest Service RPA Assessment, Gen. Tech. Rep. RMRS-33, U.S. department of Agriculture, Forest service, Rocky Mountain Research Station, Fort Collins, Colo.,1999. Ford, S.G. 1980. Evaluation of highway deer kill mitigation on SIE/LAS-395. U.S Department of Transportation Report No. FHWA/CA/TP-80/01 Forman, R.T.T., 1995. Land Mosaics: The Ecology of landscapes in Regions, Cambridge University Press, New York, 1995. Forman, R.T.T., and R.D. Deblinger, 1998. The ecological road-effect zone for transportation planning and Massachusetts highway example. In: proceedings of the international conference on wildlife ecology and transportation. February 10-12, 1998. Fort Myers, Florida.78-96

24 Foster, M.L. and S.R. Humphrey. 1995. Use of highway underpasses by Florida panthers and Other wildlife. Wildlife Society Bulletin 23(1): 95-100. Fowle, S.C. 1996. Effect of roadkill mortality on the western painted turtles. 14pp. In G.L. Evink, et al (eds) Trends in Addressing Transportation Related wildlife Mortality, proceedings of the transportation related wildlife mortality seminar. State Of Florida Department of Transportation, Tallahassee, FL.FL-ER-58-96. Furniss,M.J., T.D. Rolrloffs, and C.S.Yee, 1991. Road construction and maintenance. Influence of Forest and Rangeland Management on Salmonid Fishes and Their Habitats, Special Publication No.19, American Fisheries Society, Bethesda, Md., 1991. Gibbs,J.P., 1993. Importance of small wetlands for the persistence of local population of wetland-associated animals. Wetlands, Vol. 13 (1),1993, pp 25-31 Gibeau, M. L. 1996. Effects of transportation corridors on large carnivores in the Bow Valley, Alberta. pp 75-90. In G.L. Evink, et al (eds) Trends in Addressing Transportation Related wildlife Mortality, proceedings of the transportation related wildlife mortality seminar. State Of Florida Department of Transportation, Tallahassee, FL.FL-ER-58-96. Hans Bekker, 1998. Habitat fragmentation and infrastructure in the Netherlands and Europe. In: proceedings of the international conference on wildlife ecology and transportation. February 10-12, 1998. Fort Myers, Florida, 151-165. Harper-Lore, B.L., 2002. Where the forest meets the roadside. In Proceedings of The International Conference on Ecology and Transportation. Center For Transportation and Environment, Raleigh, N.C., 2002. Highway Statistics 2001, www.fhwa.dot.gov/ohim/hs01/hm40.htm and www.fhwa.dot.gov/ohim/hs01/aspublished/im.htm Illner, H.1992. Effect of roads with heavy traffic on grey partridge density. Gibier Faune Sauvag. 9:467-490 Jackson, S.D. 1996. Underpass system for amphibians. 4pp. In G.L. Evink, et al (eds) Trends in Addressing Transportation Related wildlife Mortality, proceedings of the Transportation related wildlife mortality seminar. State of Florida Department of Transportation, Tallahassee, FL.FL-ER-58-96 Janetos,A.C., 1996. ”Do We Still Need Nature? The Importance of biological Diversity” Consequences, Vol.32, 1996, pp 969-974 Jonkers, D.A. and De Vries, G.W. 1977. Verkeersslachtoffers onder de Fauna. Nederlandse Vereniging tot Bescherming van Vogels. Zeist. Keller,V. and HP.Pfister. 1997. Wildlife passages as a means of mitigating effects of Habitat fragmentation by roads and railway lines.pp70-80 In Kcanters (ed.) Habitat fragment&infrastructure, proceedings of the international conference on Habitat fragmentation, infrastructure and the role of ecological engineerings .Ministry of Transport, Public Works and water management, Delft, The Netherlands Kerry, A.G., Mark, J.B. and Hillary, L.R. 1998. Factors influencing the frequency of Road-killed wildlife in Yellowstone national Park. In: proceedings of the International conference on wildlife ecology and transportation February 10-12, 1998. Fort Myers, Florida. 171-180 Land, D. and M. Lotz. 1996. Wildlife crossing designs and use by Florida panthers and Other wildlife in southwest Florida. 6pp. In G.L. Evink, et al (eds) Trends in Addressing Transportation Related wildlife Mortality, proceedings of the Transportation related

25 wildlife mortality seminar. State of Florida Department of Transportation, Tallahassee, FL.FL-ER-58-96. Langton, T. E. S. 1989b. Tunnels and temperature results: from a study of a drift fence and tunnel system at Henley –on-Thames, Buckinghamshire, England. Pp.145-152 In T.E.S. Langton (ed.) Amphibians and Roads, proceedings of the toad tunnel conference. ACO Polymer Products, Shefford, England. Lenore Fahrig, John H. P., Shealagh E. P., Philip D. T. and John F. W.1995 Effects of road traffic on amphibian density. Biological Conservation.73:177-182. Linden, P. J. H. van der, 1997. A wall of tree-stumps as a fauna-corridor.pp.409-417 In .Canters (ed.) Habitat fragment&infrastructure, proceedings of the international conference on habitat fragmentation, infrastructure and the role of ecological engineering. Ministry of Transport, Public Works and water management, Delft, The Netherlands. Lovallo,M. J. and E.M. Anderson. 1996 Bobact movement and home ranges relative to roads in Wisconsin . Wildlife Society Bulletin.24:71-76. Lyon, L. J. 1983. Road density models describing habitat effectiveness for elk. Journal of Forestry. 81:592-595. Mansergh,I.M. and D.J.Scotts, 1989. Habitat continuity and social organization of the moutain pygmy-possum restored by tunnel. Journal of Wildlife Management.53(3):701-707. Marcel, P. H., Hans, J. G. and Piet J. M. 1998. Hedgehog traffic victims: how to quantify effects on the population level and the prospects for mitigation. In: proceedings of the international conference on wildlife ecology and transportation February 10-12, 1998. Fort Myers, Florida. 171-180. Mark ,B.T. 1995. Arizona’s General Hitchcock Highway: balancing safety and the environment . Public Roads. 58:30-36. May,R.M. 1990. How many species. Philosophical Transactions of the Royal society of Landon, Series B, Vol. 330, 1990, pp 293-304. MeLellan, B.N. and D. M. Shackleton. 1988. Grizzly bears and resource-extraction industries: effects of roads on behavior, habitat use and demography. Journal of Applied Ecology. 25:451-456. Natasha, C.K. and Don E.S. 1998. Quantifying wildlife road mortality in Saguaro National Park. In: proceedings of the international conference on wildlife ecology and Transportation. February 10-12, 1998. Fort Myers, Florida. 23-27. Noss,R.F. and R.L. Petters, 1995. Status report on America’s Vanishing Habitat and Wildlife, Defender of Wildlife, Washington, D.C., 1995. Oetting, R.B. and J.F. Cassel. 1971. Waterfowl nesting on interstate highway right of way in North Dakota. Journal of Wildlife Management. 35:774-781. Paquet,P.C. and C.Callaghan.1996. Effects of linear developments on winter movements of gray wolves in the bow riveer valley of Banff National Park, Albert. 21pp. In G.L. Evink, et al (eds) Trends in Addressing Transportation Related wildlife Mortality, proceedings of the transportation related wildlife mortality seminar. State of Florida Department of Transportation, Tallahassee, FL.FL-ER-58-96. Pedevillano, C and RG. Wright. 1987. The influence of visitors on mountain goat activities in Glacier National Park , Montana Biological Conservation. 39; 1-11. Podlucky,R. 1989. Protection of amphibians on roads: examples and experiences from Lower Saxony. Pp15-28. In G.L. Evink, et al (eds) Trends in Addressing Transportation Related wildlife Mortality, proceedings of the transportation related wildlife

26 mortality seminar. State of Florida Department of Transportation, Tallahassee, FL.FL-ER-58-96. Reh,W and A. Seitz. 1990. The influence of land use on the genetic structure of populationa of the common frog Rana temporia. Biological Conservation.54:239-249. Reijnen,R. and Foppen, R. 1994. The effects of car traffic on breeding bird populations in woodland. I. Evidence of reduced habitat quality for willow warblers breeding close to a highway. Journal of Applied Ecology. 32, 187-202. Reijnen, R. Foppen, R. ter Braak, C. and Thissen, J. 1995. The effects of car traffic on breeding birds populations in woodland III Reduction of density in relation to the proximity of main roads. Journal of Applied Ecology:32; 18l-202 Reijnen , R and Thissen, J. 1997. Effects of road traffic on breeding bird populations in woodlands. Annual Report 1996, Research Institute for Nature management, Leersum, The Netherlands. pp 121-132 Romin, L.A. and J.A. Bissonette.1996. Deer-vehicle collisions: status of state monitoring activities and mitigation efforts. Wildlife Society Bulletin 24:276-283 Rodriguez, A.,G. Crema and M. Delibes. 1996. Use of non-wildlife passages across a high speed railway by terrestrial vertebrate Journal of Applied Ecology33:1527-1540 Rosell, C., Jarpal, R. Campeny, Sjove, A. Pasquina and J.M. Velasco.1997 mitigation of barrier effect of linear infrastructure on wildlife. pp.367-372 In K.Canters (ed.) Habitat fragment&infrastructure, proceedings of the international conference on habitat fragmentation, infrastructure and the role of ecologoical engineerings .Ministry of Transport, Public Works and water management, Delft, The Netherlands Ruediger, B. and B. Ruediger. 1996. The effects of highways on trout and salmon rivers and streams in the western U.S. pp 151-160. In G.L. Evink, et al (eds) Trends in Addressing Transportation Related wildlife Mortality, proceedings of the transportation related wildlife mortality seminar. State of Florida Department of Transportation, Tallahassee, FL.FL-ER-58-96. Räty, M.1979. Effect of highway traffic on tetraonid densities. Ornis. Fennica 56:169-170. Scott, D.J. And Curtice, R.G. 1998. Towards a practical strategy for mitigation highway impacts on wildlife . In: proceedings of the international conference on wildlife ecology and transportation February 10-12, 1998. Fort Myers, Florida. 17-22. Shaffer, M. L. and F. B. Samson, 1985. Population size and extinction: a norte on determining critical population size. America Naturralist. Vol.125, 1985, pp144-152. Sielecki, L. 2000. Wars 2000-wildllife accident reporting system, Ministry of Transportation, Victoria, B.C., Canada. Singer,F.J and J.L., Poherty. 1985. Managing mountain goats at a highway crossing. Wildlife Society Bulletin ,13:469-477. Santolini, R., G. Sauli, S. Malcevschi, and F. Perco, 1997. The relationship between infrastructure and wildlife problems, possible solutions and finished works in Italy pp.202-212 In K.Canters (ed.) Habitat fragment&infrastructure, proceedings of the international conference on habitat fragmentation, infrastructure and the role of ecologoical engineering. Ministry of Transport, Public Works and water management, Delft, The Netherlands Thurber,J.M., R.O. Peterson, T.D. Drummer and S.A. Thomasma.1994 Gray wolf response to refuge boundaries and roads in Alaska. Wildlife Society Bulletin.22:61-67.

27 Spellerberg, Ian F., 2002. Ecological Effects of Roads. pp 124-129. United Nations, 1999. Road development and the environment: Methodologies for minimizing environmental damage New York:16-22. Straker, A. 1998. Management of roads as biolinks and habitat zones in Australia. In: Proceedings of the international conference on wildlife ecology and transportation February 10-12, 1998. Fort Myers, Florida. 181-188 USDOT and FHWA, 2002. US Department of Transportation and Federal Highway Administration (International technology Exchange Program.report No. FHWA-PL- 02-011) 2002 Wildlife habitat connectivity across European highways, pp19-20. Va Der Zande, A.N., Ter keurs,W.J. and Van der Weijden, W.J. 1980. The impact of roads on the densities of four bird species in an open field habitat: evidence of a long distance effect Biological Conservation 18,299-321. Van Dyke, F.G., R.H. Brocke, and H.G. Shaw. 1986. Use of road track counts as indices of mountain lion presence. Journal of Wildlife Management.50:102-109. Vitousek, P.M., H.A. Mooney, and J.Lubchenco, 1997. Human Domination of Earth’s Ecosystems. Science, Vol. 227, 1997, pp.494-499. Waller, J. and C. Servheen. 1999. Documenting grizzly bear highway crossing patterns using GSP technology. In; Proceedings of the Third International Conference on Wildlife Ecollogy and Transportation, FL-ER-73-99, Florida Department of Transportation, Tallahassee, 1999 , pp 21-24. WHO 1993. Assessment of source of air, water and land pollution: a guide to rapid source inventory techniques and their use in formulating environmental control strategies. Part 1 and part 2. World Health Organization, Geneva.

28 Journal of Environmental Management 144 (2014) 51e57

Contents lists available at ScienceDirect

Journal of Environmental Management

journal homepage: www.elsevier.com/locate/jenvman

Dry paths effectively reduce road mortality of small and medium-sized terrestrial vertebrates

* Milla Niemi a, , Niina C. Ja€askel€ ainen€ b, Petri Nummi a, Tiina Makel€ a€ a, Kai Norrdahl b a Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014, University of Helsinki, Finland b Department of Biology, University of Turku, FI-20014, University of Turku, Finland article info abstract

Article history: Wildlife passages are widely used mitigation measures designed to reduce the adverse impacts of roads Received 17 October 2013 on animals. We investigated whether road kills of small and medium-sized terrestrial vertebrates can be Received in revised form reduced by constructing dry paths adjacent to streams that pass under road bridges. The study was 9 May 2014 carried out in southern Finland during the summer of 2008. We selected ten road bridges with dry paths Accepted 13 May 2014 and ten bridges without them, and an individual dry land reference site for each study bridge on the Available online 9 June 2014 basis of landscape and traffic features. A total of 307 dead terrestrial vertebrates were identified during the ten-week study period. The presence of dry paths decreased the amount of road-killed terrestrial Keywords: < Corridor vertebrates (Poisson GLMM; p 0.001). That was true also when considering amphibians alone < Wildlife passage (p 0.001). The evidence on road-kills on mammals was not such clear. In the mammal model, a lack of River-side dry paths increased the amount of carcasses (p ¼ 0.001) whereas the number of casualties at dry path Road-kill bridges was comparable with dry land reference sites. A direct comparison of the dead ratios suggests an average efficiency of 79% for the dry paths. When considering amphibians and mammals alone, the computed effectiveness was 88 and 70%, respectively. Our results demonstrate that dry paths under road bridges can effectively reduce road-kills of small and medium-sized terrestrial vertebrates, even without guiding fences. Dry paths seemed to especially benefit amphibians which are a threatened species group worldwide and known to suffer high traffic mortality. © 2014 Elsevier Ltd. All rights reserved.

1. Introduction shown that mortality or other disturbances related to roads can have negative impacts on populations (Gibbs and Shriver, 2002; Roads and traffic have many ecological and environmental ef- van der Ree et al., 2009). Examples include population decline fects, and their impacts on animals are mostly negative (e.g. (e.g. van der Zee et al., 1992), and gene flow reductions between Forman and Alexander, 1998; Trombulak and Frissell, 2000; Fahrig populations (e.g. Garcia-Gonzalez et al., 2012). and Rytwinski, 2009). Major concerns stemming from an expand- Wildlife passages are the most widely recommended design ing road network include the destruction and deterioration of solution for reducing the adverse impacts of roads on animals (but habitats and the loss of landscape connectivity (Forman, 1998). see also Lovich et al., 2011). Passages reduce the barrier effect of Traffic-related animal mortality is often acknowledged, as it is roads by making them more permeable to animal movements highly visible: every year an enormous number of animals die on (Mansergh and Scotts, 1989; van der Ree et al., 2009), thus helping roads (Case, 1978; Seiler et al., 2004). In USA, for example, the daily to maintain landscape connectivity. Crossing structures can also estimate of road-killed animals is approximately one million in- reduce animal mortality caused by traffic(Clevenger et al., 2003; dividuals (Forman and Alexander, 1998). Traffic can be a significant Dodd et al., 2004; Aresco, 2005). Crossing structures have usually cause of mortality for common and abundant species, but may been equipped with wildlife fences or other barrier structures, nevertheless not threaten population persistence (e.g. Seiler et al., leading animals towards passages (e.g. Clevenger and Waltho, 2004). On the other hand, a considerable number of studies have 2000; Dodd et al., 2004; McCollister and van Manen, 2010). How- ever, it is not always clear if fences reduce animal road mortality (Villalva et al., 2013). * Corresponding author. Department of Forest Sciences, P.O. Box 27, Latokarta- Many terrestrial vertebrate groups are known to utilize passages nonkaari 7, FI-00014, University of Helsinki, Finland. Tel.: 358 (0)9 191 þ í 58366, þ358 40 724 0330; fax: þ358 (0)9 191 58100. (Hunt et al., 1987; Yanes et al., 1995; Rodr guez et al., 1996; Veenbaas E-mail address: milla.niemi@helsinki.fi (M. Niemi). and Brandjes,1999; Lesbarreres et al., 2004; Nget al., 2004). However, http://dx.doi.org/10.1016/j.jenvman.2014.05.012 0301-4797/© 2014 Elsevier Ltd. All rights reserved. 52 M. Niemi et al. / Journal of Environmental Management 144 (2014) 51e57 some species or species groups can have their own demands con- the country. Several divided highways and main roads run through cerning, for example, the structural characteristics of the passages. the study area, which also contains a dense network of minor roads. Small-sized mammals are more likely to cross roads across small Landscape structures in the study area range from the mosaic of structures (Rodriguez et al., 1996; McDonald and St Clair, 2004), settlement and cultivated areas found at the southern coast, to rural whereas larger animals, such as roe deer (Capreolus capreolus)orwild areas and forest with watercourses in the western and northern boars (Sus scrofa) avoid narrow culvert-type passages (Mata et al., parts. The eastern part is dominated by cultivated land with a few 2008). Medium-sized carnivores also prefer larger structures (Grilo lakes. et al., 2008). The presence of human use in passages or high We selected 10 DPBs and 10 NPBs (Fig. 1; Appendices A and C) amounts of traffic could reduce passage usage by carnivores with as similar characteristics as possible based on landscape maps, (Clevenger and Waltho, 2000; Clevenger et al., 2001) and ungulates data from a bridge register maintained by the Finnish Road (Olsson et al., 2008), while increasing traffic volumes could Administration (FRA), and field visits. All selected bridges were encourage some species, e.g. hares, to utilize passages more situated along two-lane (one lane in each direction) paved roads frequently (Clevenger et al., 2001). The bottom material of the without median strips and crossed a stream or narrow river (width structures is not irrelevant either; amphibians prefer tunnels lined of the watercourse excluding river banks ca. 2e20 m) with with soil (Lesbarreres et al., 2004; Woltz et al., 2008), andwater inside continuous river-side vegetation stretching at least 1 km in both passages can reduce the usage of structures (Serronha et al., 2013). directions from the selected bridges. The maximum width of the Landscape factors and vegetation near structures can also affect studied dry paths varied between 1.5 m and 16.0 m (including the passage usage. Species favoring covered habitats are less likely to entire bank) and the maximum height (from the ground to the use passages located in the middle of farmland (Rodríguez et al., underside of the bridge) between 1.5 m and 8.0 m. Average bridge 1996). Vegetation near passage entrances provides a cover for age was 36 years. One NPB was reconstructed two years before our small mammals (Hunt et al., 1987; McDonald and St Clair, 2004), data collection and major repairs had been carried out on one DPB but some medium-sized species e.g. hares could benefit from and one NPB during the preceding three years. None of the study adjacent vegetation as well (Clevenger et al., 2001). bridges were originally constructed as animal passages. Still, all dry It is important to appropriately locate passages to ensure that paths remained usable during the entire study period, and NPBs they are available for animals, especially when the target species could not be passed under even during low water levels. has a limited capability for movement (McDonald and St Clair, Despite selecting bridges with as similar characteristics as 2004); small animals are unlikely to find and use distant pas- possible, it was not possible to find DPB-NPB pairs situated in fully sages. River crossings are potential structure sites in many areas. comparable environments and with identical traffic features. So, For example, riversides are known to be ecological corridors (e.g. instead of a direct comparison between DPBs and NPBs, we used a Hoctor et al., 2000), and they are often preserved, even in urban study design including individual dry land reference site for each environments. In addition to semi-aquatic animals, many terrestrial bridge to minimize the impact of landscape and traffic features on mammals also move along river and stream corridors (Spackman our conclusions. We selected a reference road section for every and Hughes, 1995; Hilty and Merenlender, 2004; Matos et al., study bridge, with comparable landscape and traffic features but no 2009). Riverside habitats are road-kill hotspots, e.g. for semi- stream or river running in the middle of it. To ensure that road- and aquatic European otters (Lutra lutra)(Philcox et al., 1999; Guter traffic-related features such as traffic amount were comparable et al., 2005), raccoon dogs (Nyctereutes procyonoides)(Saeki and within studyereference pairs, reference sections were selected MacDonald, 2004), white-tailed deer (Odocoileus virginianus) along the same road as the study bridge (but not closer than 2 km). (Finder et al., 1999; Hubbard et al., 2000), and for small and We matched the proportion of different landscape classes (agri- medium-sized terrestrial vertebrates in general (Niemi et al., 2007). cultural areas, forests, infrastructure, treeless wetlands, water Several studies show that animals use catwalks or concrete bodies) within a 1-km radius circle around the bridge and its shelves above the culvert floor and artificial ledges (Cain et al., reference site. The 1-km scale was selected based on the assump- 2003; Foresman, 2003; Meaney et al., 2007; Villalva et al., 2013), tion that most potential dry path users in our study area would be and passages along watercourses with extended banks or dry small or medium-sized species (cf. Veenbaas and Brandjes, 1999), connections (hereafter referred to as dry paths) (Veenbaas and whose home ranges typically ranged from less than a hectare to a Brandjes, 1999). However, in addition to passage usage, it is few km2 (Lindstedt et al., 1986; Swihart et al., 1988). important that structures are also effective (van der Ree et al., The distance between DPBs and their matched reference sites 2007), i.e. that they mitigate the barrier effect of roads, reduce ranged from 2.6 km to 31.8 km (average 11.6 km). For NPBs, the road-kills or have other positive effects on animals, for example by corresponding range was 2.1 kme24.3 km (average 8.8 km). enhancing the demographic connection between populations (see All landscape variables used as covariates in our statistical Sawaya et al., 2013). So far, only a few studies have tried to evaluate models (Table 1) were extracted from the Finnish national version the effectiveness of wildlife passages (see van der Ree et al., 2007; of the CORINE Land Cover 2006 database, where land use in Finland Lesbarreres and Fahrig, 2012) and, to our knowledge, none of them is presented with a pixel size of 25 25 m (Finnish Environment concentrate on passages at watercourses. Institute, 2009). Landscape data was processed using ArcMap Our study examined whether dry paths under bridges crossing version 9.3 (ESRI, 2009). Road-related variables, the amount of watercourses reduce the traffic mortality of animals. We tested the traffic (cars/day) and speed limit (kilometers/hour), were provided hypothesis that there are fewer road-killed animals near road bridges by the FRA. with dry paths under them (dry path bridge; DPB; Appendix A) than near bridges without such dry paths (non-path bridge; NPB). 2.2. Data collection 2. Methods We surveyed a 400-m stretch of the road at each site, with the 2.1. Study area and design middle point located in the center of the bridge or reference site without a bridge (total distance being 800 m including both sides of We carried out our study in southern Finland (Fig. 1, Appendix the road). The carcasses of small and medium-sized animals are B), which is the most densely populated and fragmented part of normally not removed from road areas in Finland, but road M. Niemi et al. / Journal of Environmental Management 144 (2014) 51e57 53

Fig. 1. Simplified map of the study area, showing the examined study bridge sites (squares) and their reference sites (circles). Solid symbols refer to dry path bridges (DPBs) and their reference sites, open symbols to non-path bridges (NPBs) and their reference sites. Only major roads are shown. (Road data: ©Finnish Road Agency, Country borders: ©Eurostat). operators were still instructed not to collect road-killed animals 2.3. Modeling during our study. Fieldwork was carried out during a 10-week period in We first identified possible collinearities between the explana- JulyeSeptember 2008. The study period was selected based on the tory variables (Table 1) using Spearman rank correlation co- season when hibernating species e.g. the raccoon dog and am- efficients (Zuur et al., 2009). As the variables ‘forest’ and phibians are active and weather conditions are suitable for field- ‘agriculture’ were highly negatively correlated (r > 0.8), the var- work (e.g. enough daylight available, no risk of snowing). iable ‘agriculture’ was omitted from further analysis. We counted and identified mammals (excluding bats), am- Statistical analyses were made using generalized linear mixed phibians, and reptiles killed along the study and reference sections. models (GLMM) with Poisson distribution, where the total amount Roads were examined by walking along one side at a time. We of road-killed small and medium-sized terrestrial vertebrates per noted carcasses on the lanes, and also on the verges of the roads. site was used as a dependent variable. Poisson distribution is The location was noted and every carcass was marked with spray suitable for count data and GLMM enables the use of specific paint to avoid double observations; we assume the risk of paint random intercept (Zuur et al., 2009), which makes it possible to attracting some scavengers to be minute. We surveyed each group independent samples, or in our case, take the paired dispo- studyereference pair ten times in total (approximately once per sition of the data into account. week). As the carcass disappearing rate of some animal groups is The status of each site (DPB; NPB; reference) and all landscape high (Santos et al., 2011), studyereference pairs were checked al- or road variables (Table 1) were evaluated as fixed effects. The ways within the same day and immediately one after the other. number of the studyereference pair was used as a random effect.

Table 1 A summary of variables used as covariates in the generalized linear mixed effect model analysis of road-killed animals (mean, minimum and maximum values are presented). Landscape variables were combined from the national CORINE Land Cover 2006 database and the proportion of each landscape type was calculated from a 1 km- radius circle was drawn around the study bridges and central points of the reference sections.

Variable DPBs DPB references NPBs NPB references

Mean Min Max Mean Min Max Mean Min Max Mean Min Max

Speed limit (km/hour) 93 70 100 91 60 100 89 80 100 96 80 100 Traffic (cars/day) 7901 5871 13,514 8225 2876 13,161 8556 5923 15,754 8863 4923 15,754 Agriculture (%) 36.0 4.9 85.6 32.5 9.5 80.5 36.7 8.6 57.7 37.1 14.3 55.7 Forest (%) 42.3 4.5 81.2 51.1 12.7 83.1 43.6 23.1 83.4 46.2 25.1 60.3 Infrastructure (%) 19.5 7.3 35.2 14.7 4.5 48.0 16.0 5.6 30.2 13.2 7.3 20.0 Other habitats (%) 0.8 0 4.8 0.5 0 1.5 1.8 0 10.4 1.3 0 5.9 Water bodies (%) 1.5 0 5.3 1.2 0 9.3 1.8 0 13.5 2.2 0 12.8 54 M. Niemi et al. / Journal of Environmental Management 144 (2014) 51e57

Because of a relatively small data set, we decided not to use any We found 44 road-killed small or medium-sized terrestrial interactions, but main terms only. Thus, the simplified model was vertebrates at the DPBs, and 114 carcasses on their reference sites defined as: (Table 2). When considering amphibians separately, there were fewer carcasses at the DPBs than at their reference sites. In the e m Yij Poisson ij paired comparisons (Fig. 2), the number of crushed amphibians was lower at DPBs than at their reference sites in six pairs out of ten (or where Y is the expected number of carcasses (covering the whole 8 excluding sites without carcasses). The pattern was similar in study period), i is the factor status (DPB; NPB; reference), and j is mammals, although the difference was not as clear; there were the number of the studyereference pair (1e20), and Yij is assumed fewer mammal carcasses at the DPBs than at reference sites. In to follow the Poisson distribution with mean mij. paired comparisons, the number of road-killed mammals was We used three models in total: first a general model based on all lower at the DPBs than at their reference sites in seven pairs out of the road-killed small and medium-sized terrestrial vertebrates we ten. found, and thereafter separate models for amphibians and mam- Contrary to the DPBs, there were more road-killed animals near mals. To determine the final models we used backward elimination NPBs than at their reference sections (Table 2). For amphibians, the of non-significant variables. The modeling was performed using R number of recorded carcasses at the NPBs and their reference sites software (R Core Team, 2012), with package lme4 (Bates et al., were 44 and 24, respectively. The ratio was approximately the same 2012). for mammals; there were more carcasses at NPBs than at their reference sites. In the paired comparisons there were more 2.4. Computing effectiveness mammal carcasses at NBPs in six pairs out of ten (or 8 excluding sites without carcasses). To evaluate the impact of dry paths, we calculated an estimate for their effectiveness, based on the ratio of carcasses found at the 3.2. The effect of dry paths bridges and at their reference sites. The calculation was based on the total number of carcasses found on road sections of different Two of our three models (Table 3A) strongly supported the status (DPBs; NPBs; references): prediction that fewer carcasses would occur at bridges with dry = = paths, as suggested by our hypotheses. The effect was evident for all 100 ½ðCarcassesDPBs CarcassesDPBReferencesÞ small and medium-sized terrestrial vertebrates combined and for ðCarcasses =Carcasses Þ*100 NPBs NPBReferences amphibians alone. In the mammalian model a lack of dry paths Effectiveness was calculated for all small and medium-sized increased the amount of carcasses whereas the number of casu- terrestrial vertebrates combined and for amphibians and mam- alties at dry path bridges was comparable with dry land reference mals separately. sites. The proportion of infrastructure in the landscape was nega- tively related to the amount of road-killed mammals. e 2.5. Track counting The variance of the random effect (study reference pair) was largest in the amphibian model (Table 3B), indicating that We searched for animal tracks under bridges with dry paths amphibian road mortality is more likely to aggregate in certain during the carcass counts. We did not carry out a systematic follow- places than the road-kills of the other species groups. up with artificial track beds, but utilized the soft and muddy shore When calculating the estimate for dry path effectiveness based zone for observations. Tracks were identified to the species level on the ratio of carcasses found at bridges and their reference sites, fi when possible, or otherwise to the species group. we found an average ef ciency of 79% for the dry paths. When considering amphibians and mammals alone, the computed effectiveness was 88% and 70%, respectively. 3. Results

3.1. Carcass distribution 4. Discussion

We counted a total of 307 dead small or medium-sized 4.1. How effective are dry paths? terrestrial vertebrates (155 mammals, 142 amphibians, 10 rep- tiles) from our study and reference sites. Mammals and reptiles Our main finding was that there were significantly fewer road- were identified to the species level. As it was not possible to killed small and medium-sized terrestrial vertebrates near bridges reliably separate crushed common frogs (Rana temporaria) from with dry paths than bridges without underpasses. This was also moor frogs (R. arvalis), these species were combined as ‘frogs’.We true when modeling amphibians separately. In the mammalian concurrently recorded 15 species (excluding humans) or species model bridges without dry paths increased the number of road- groups that had used dry paths under bridges during the study killed mammals, which is in line with studies where rivers and period (Appendix D). streams are found to be hotspot areas for road-kills (Philcox et al.,

Table 2 The number of road-killed small or medium-sized terrestrial vertebrates found in the study bridges and their reference sites during our study period. The class “all terrestrial vertebrates” includes all wingless mammals (i.e. not bats), amphibians, and reptiles. SD is the standard deviation.

Dry path bridges (DPBs) DPBs reference sites Non-path bridges (NPBs) NPBs reference sites

Total Mean SD Range Total Mean SD Range Total Mean SD Range Total Mean SD Range

Mammals 30 3.0 2.4 0e7 51 5.1 3.8 1e14 49 4.9 5.2 0e18 25 2.5 2.8 0e10 Amphibians 13 1.3 1.8 0e5 61 6.1 5.8 0e14 44 4.4 7.8 0e25 24 2.4 3.9 0e12 All terrestrial 44 4.4 3.6 0e11 114 11.4 8.0 1e28 96 9.6 13.2 0e45 53 5.3 7.6 0e26 vertebrates M. Niemi et al. / Journal of Environmental Management 144 (2014) 51e57 55

50 Table 3B 45 A A summary of a generalized mixed linear model analysis of road-killed animals as a DPBs 40 function of studyereference pair (N ¼ 20), which was used as a random effect in our 35 Reference sections model. SD is the standard deviation. 30 Estimates, Estimates, Estimates, 25 general model amphibian mammal model 20 model 15 10

Number of carcasses Random effect Variance SD Variance SD Variance SD 5 0 Pair number 0.785 0.886 1.864 1.365 0.335 0.579 (Intercept) 1 5 6 8 10 11 16 17 18 20 Number of study-reference pair

50 fi 45 traf c mortality by up to 93% (or 65% when including hylid tree- B NPBs 40 frogs, known to be skilled climbers). Aresco (2005) observed the 35 Reference sections road crossing rates of turtles before and after a drift fence was 30 installed near drainage culverts and concluded that mitigation 25 measures reduced traffic mortality by 98%. The effectiveness re- 20 15 ported in both studies was comparable with our observations 10 although our study bridges had no guiding fences. Interestingly, Number of carcasses 5 Villalva et al. (2013) reported culvert fencing only having a scarce 0 effect on mammalian road-kills. Thus, it is possible that the benefits 2 3 4 7 9 12 13 14 15 19 of installing guiding fences near passages could be very site- and/or Number of study-reference pair species-specific and should be studied in more detail in the future. Fig. 2. The number of road-killed terrestrial vertebrates at dry path bridges (DPBs) and their reference sections (upper panel; A), and at non-path bridges (NPBs) and their 4.2. Road-killed species and species responses to dry paths reference sections (lower panel; B). Traffic can be a substantial source of mortality for amphibians (Hels and Buchwald, 2001; Orlowski, 2007; Coelho et al., 2012). 1999; Hubbard et al., 2000; Saeki and MacDonald, 2004; Niemi Roads and traffic can reduce anuran populations (Carr and Fahrig, et al., 2007). Concurrently, the number of road-killed mammals 2001; Eigenbrod et al., 2008) and even minor roads can act as a did not differ between bridges with dry paths and their dry land barrier for amphibians (Garcia-Gonzalez et al., 2012; but see reference sites. This suggests that a dry path under a bridge is Bouchard et al., 2009). Our study indicated that dry paths would enough to neutralize the increased risk of mammalian road mor- considerably reduce amphibian traffic mortality, although a lack of tality at bridges crossing watercourses. amphibian population size estimates in our area mean that we As the amount of infrastructure in the landscape seemed to cannot directly infer an effect of reduced mortality on long-term affect the number of mammalian road-kills, further research population size or population persistence. On the other hand, am- focusing on mammals is needed to confirm our preliminary phibians are a threatened species group worldwide (Stuart et al., conclusions. 2004), and any mitigation measures (e.g. dry paths) that reduce The use of passages has often been seen as an indicator of their their mortality and maintain wetland connectivity should be effectiveness (e.g. Clevenger and Waltho, 2000). However, in considered in their conservation. addition to mere usage, it is important to consider the actual We recorded 15 species or species groups that had used dry effectiveness of passages in mitigating the negative effects of roads paths. All examined paths except one had been used by raccoon (van der Ree et al., 2007; Lesbarreres and Fahrig, 2012). As we had dogs, which also move in riparian areas in urban environments no possibility of using population-level data, we calculated theo- (Va€an€ anen€ et al., 2007). Small mammals are known to use various retical percentages for the impact of dry paths on the amount of types of fauna underpasses (Yanes et al., 1995; Rodríguez et al., road-killed animals. The computed effectiveness was better for 1996; McDonald and St Clair, 2004), so it was not surprising that amphibians (88%) than mammals (70%), indicating that amphibians we observed rat, mice, vole, and shrew tracks on dry paths. Other may benefit from dry paths more than mammals. Most mammals animals we recorded were also species known to use underpasses are faster than frogs and therefore are able to cross roads relatively (Rodríguez et al., 1996; Veenbaas and Brandjes, 1999; Clevenger quickly, which may partly explain why frogs seemed to be more et al., 2001). vulnerable than mammals for road mortality at bridge structures Most of the road-killed mammals we recorded were common lacking underpasses. species in Finland. Traffic mortality of common animals does not In line with our findings, Dodd et al. (2004) reported that the necessarily pose a threat to population viability, despite the large combination of a barrier wall and culverts can reduce vertebrate number of annually killed individuals (e.g. Seiler et al., 2004).

Table 3A A summary of a generalized mixed linear model analysis of road-killed animals as a function of site status (dry path bridge DPB; non-path bridge NPB; reference site) and landscape variables, which were used as fixed effects in our model. b is the coefficient, SE is the standard error and p-value denotes the level of significance.

Estimates, general model Estimates, amphibian model Estimates, mammal model

Fixed effects b SE p-value b SE p-value b SE p-value

(Intercept) 1.762 0.218 0.712 0.342 0.958 0.190 Dry path bridge 0.900 0.178 <0.001 1.496 0.307 <0.001 0.035 0.252 0.889 Non path bridge 0.491 0.161 0.002 0.490 0.240 0.041 0.565 0.217 0.001 Infrastructure 0.524 0.156 <0.001 56 M. Niemi et al. / Journal of Environmental Management 144 (2014) 51e57

From a conservation perspective, the most noteworthy mammal Reviewers for comments on our manuscript. Our study was funded species using paths under bridges was the European otter, which is by the Finnish Road Administration and the Finnish Cultural known to suffer from relatively high traffic mortality (Philcox et al., Foundation. 1999; Hauer et al., 2002; Guter et al., 2005). The otter has a special position in road planning in many countries (e.g. Sierla et al., 2004; Appendix A. Supplementary data Vagverket,€ 2005), and have been reported to use underpasses at least occasionally (Grilo et al., 2008). Supplementary data related to this chapter can be found at http://dx.doi.org/10.1016/j.jenvman.2014.05.012. 4.3. Practical implications: a road planner's perspective

Decisions on the efficient placement of passages should be References based on detailed information concerning movement routes in the Aresco, M.J., 2005. Mitigation measures to reduce highway mortality of turtles and landscape (see van Manen et al., 2001). In practice, obtaining such other herpetofauna at a North Florida Lake. J. Wildl. Manag. 69, 549e560 http:// information may demand more time and funding than can be dx.doi.org/10.2193/0022-541X(2005)069[0549:MMTRHM]2.0.CO;2. allocated for the purpose. In such cases, we suggest that passages Bates, D., Maechler, M., Bolker, B., 2012. lme4: Linear Mixed Models Using S4 Classes. R package version 0.999999-0. http://CRAN.R-project.org/ along watercourses that are usually also ecological corridors (e.g. package¼lme4 (accessed May 2013). Hoctor et al., 2000) are the next best solution. However, the exis- Bouchard, J., Ford, A.T., Eigenbrod, F.E., Fahrig, L., 2009. Behavioral responses of tence of a next best solution does not replace the need for collab- Northern leopard frogs (Rana pipiens) to roads and traffic: implications for population persistence. Ecol. Soc. 14 (23). http://ecologyandsociety.org/vol14/ oration between wildlife researchers and road planners when iss2/art23/. planning wildlife passages and evaluating their effectiveness Cain, A.T., Tuovila, V.R., Hewitt, D.G., Tewes, M.E., 2003. Effects of a highway and (Lesbarreres and Fahrig, 2012). mitigation projects on bobcats in. South. Tex. Biol. Cons. 114, 189e197. http://dx. doi.org/10.1016/S0006-3207(03)00023-5. The dry paths observed in our study were originally constructed Carr, L.W., Fahrig, L., 2001. Effect of road traffic on two amphibian species of to assist in occasional bridge maintenance and repair, but as we differing vagility. Conserv. Biol. 15, 1071e1078. http://www.jstor.org/stable/ have shown here they are fully capable of also assisting in animal 3061326. movements. They can also enable human crossings of busy roads, Case, R.M., 1978. Interstate highway road-killed animals: a data source for bi- ologists. Wild. Soc. Bull. 6, 8e13. although a high level of human activity is known to reduce passage Clevenger, A.P., Waltho, N., 2000. Factors influencing the effectiveness of wildlife utilization by some animal species (Rodríguez et al., 1997; underpasses in Banff National Park, Alberta, Canada. Conserv. Biol. 14, 47e56. Clevenger and Waltho, 2000). Dry paths functioning in multipur- http://dx.doi.org/10.1046/j.1523-1739.2000.00099-085.x. Clevenger, A.P., Chruszcz, B., Gunson, K., 2001. Drainage culverts as habitat linkages pose ways may be an attractive choice because in these cases the and factors affecting passage by mammals. J. Appl. Ecol. 38, 1340e1349. http:// cost-benefit ratio of dry paths is relatively good compared to cases dx.doi.org/10.1046/j.0021-8901.2001.00678.x. where the structure's only purpose is to facilitate animal move- Clevenger, A.P., Chruszcz, B., Gunson, K., 2003. Spatial patterns and factors influ- e fi encing small vertebrate fauna road-kill aggregations. Biol. Cons. 109, 15 26. ments (Bridge engineer Timo Tirkkonen, Finnish Traf c Agency, http://dx.doi.org/10.1016/. personal communication). However, the costs of passage structures Coelho, I.P., Teixeira, F.Z., Colombo, P., Coelho, A.V., Kindel, A., 2012. Anuran road- are always very site-specific, so economical calculations should be kills neighboring a peri-urban reserve in the Atlantic Forest. Braz. J. Environ. Manage. 112, 17e26. http://dx.doi.org/10.1016/j.jenvman.2012.07.004. conducted before construction. Dodd Jr., C.K., Barichivich, W.J., Smith, L.L., 2004. Effectiveness of a barrier wall and culverts in reducing wildlife mortality on a heavily travelled highway in Florida. 5. Conclusions Biol. Cons 118, 619e631. http://dx.doi.org/10.1016/j.biocon.2003.10.011. Eigenbrod, F., Hecnar, S.J., Fahrig, L., 2008. The relative effects of road traffic and forest cover on anuran populations. Biol. Cons. 141, 35e46. http://dx.doi.org/10. Our results demonstrate that dry paths under road bridges 1016/j.biocon.2007.08.025. crossing streams and small rivers significantly reduced the traffic ESRI, 2009. Redlands. Environmental Systems Research Institute Inc, CA, USA. mortality of small and medium-sized terrestrial vertebrates even Fahrig, L., Rytwinski, T., 2009. Effects of roads on animal abundance: an empirical review and synthesis. Ecol. Soc. 14 (21). http://ecologyandsociety.org/vol14/ without guiding fences. The hypothesis of animals crossing roads iss1/art21/. under bridges via dry paths, leading to lower road mortality, was Finder, R.A., Roseberry, J.L., Woolf, A., 1999. Site and landscape conditions at white- e corroborated by the track observations representing several tailed deer/vehicle collision locations in Illinois. Landsc. Urban Plan. 44, 77 85. http://dx.doi.org/10.1016/S0169-2046(99)00006-7. different species under DPBs. We thus argue that dry paths are a Finnish Environmental Institute, 2009. CLC2006 Finland. Finnish Environmental useful method for maintaining landscape connectivity by providing Institute, Helsinki, Finland. Final technical report. http://ymparisto.fi/download. safer road crossing options for animals. asp?contentid¼118299&lan¼fi. Foresman, K.R., 2003. Small mammal use of modified culverts on the Lolo south Environmental issues are often neglected in road planning project of western Montana - an update. In: Irwin, C.L., Garret, P., processes (see Malakoff, 2011), but dry paths have features which McDermott, K.P. (Eds.), Proceedings of the 2003 International Conference on could increase their popularity among decision makers; dry paths Ecology and Transportation. Center for Transportation and the Environment, North Carolina State University, Raleigh, North Carolina, USA, pp. 342e343. are relatively low-cost alternatives compared to wider passage Forman, R.T.T., 1998. Road ecology: a solution for the giant embracing us. Landsc. structures and are also easy to plan when building new bridges or Ecol. 13 (4) iiiev. repairing old ones (Bridge engineer Timo Tirkkonen, Finnish Traffic Forman, R.T.T., Alexander, L.E., 1998. Road and their major ecological effects. Annu. Rev. Ecol. Evol. Syst. 29, 207e231. http://dx.doi.org/10.1146/annurev.ecolsys.29. Agency, personal communication). We recommend that bridges 1.207. equipped with dry paths should be considered standard practice Garcia-Gonzalez, C., Campo, D., Pola, I.G., Garcia-Vazquez, E., 2012. Rural road instead of drainage culverts or concrete bridges without passage networks as barriers to gene flow for amphibians: species-dependent mitiga- fi e possibilities when guiding water flow beneath roads. These miti- tion by traf c calming. Landsc. Urban Plan. 104, 171 180. http://dx.doi.org/10. 1016/j.landurbplan.2011.10.012. gation measures effectively reduce the traffic mortality of animals Gibbs, J.P., Shriver, W.G., 2002. Estimating the effects of road mortality on turtle and facilitate their movements in landscapes fragmented by a road populations. Conserv. Biol. 16, 1652e1674. http://dx.doi.org/10.1046/j.1523- network. 1739.2002.01215.x. Grilo, C., Bissonette, J.A., Santos-Reis, M., 2008. Response of carnivores to existing highway culverts and underpasses: implications for road planning and miti- Acknowledgements gation. Biodivers. Conserv. 17, 1685e1699. http://dx.doi.org/110.1007/s10531- 008-9374-8. Guter, A., Dolev, A., Saltz, D., Kronfeld-Schor, N., 2005. Temporal and spatial in- We thank H. Rita and J. Isotalo for help with our study design fluences on road mortality in otters: conservation implications. Isr. J. Zool. 51, and L. Fahrig, D. Simmons, W. Branch, S. Sirkia,€ and two anonymous 199e207. http://dx.doi.org/110.1560/3TF7-7B74-QWKC-6WV1. M. Niemi et al. / Journal of Environmental Management 144 (2014) 51e57 57

Hauer, S., Ansorge, H., Zinke, O., 2002. Mortality patterns of otters (Lutra lutra) from R Core Team, 2012. R: a Language and Environment for Statistical Computing. R eastern Germany. J. Zool. (Lond.) 256, 361e368. http://dx.doi.org/10.1017/ Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0. S0952836902000390. http://R-project.org/ (accessed December 2012). Hels, T., Buchwald, E., 2001. The effect of road kills on amphibian populations. Biol. Ree, R., van der, Gulle, Holland, N., Grift, K., van der, E., Mata, C., Suarez, F., 2007. Cons. 99, 331e340. http://dx.doi.org/10.1016/S0006-3207(00)00215-9. Overcoming the barrier effect of roads e how effective are mitigation strate- Hilty, J.A., Merenlender, A.M., 2004. Use of riparian corridors and vineyards by gies? In: Irwin, C.L., Nelson, D., McDermott, K.P. (Eds.), Proceedings of the In- mammalian predators in northern California. Conserv. Biol. 18, 126e135. http:// ternational Conference on Ecology and Transportation. Center for dx.doi.org/10.1111/j.1523-1739.2004.00225.x. Transportation and the Environment, North Carolina State University, Raleigh, Hoctor, T.S., Carr, M.H., Zwick, P.D., 2000. Identifying a linked reserve system using a North Carolina, Arkansas, USA, pp. 423e431. regional landscape approach: the Florida ecological network. Purch. Biol. 14, Ree, R., van der, Heinze, D., McCarthy, M., Mansergh, I., 2009. Wildlife tunnel en- 984e1000. http://dx.doi.org/10.1046/j.1523-1739.2000.99075.x. hances population viability. Ecol. Soc. 14 (7). http://ecologyandsociety.org/ Hubbard, M.W., Danielson, B.J., Schmitz, R.A., 2000. Factors influencing the location vol14/iss2/art7/. of deer-vehicle accidents in Iowa. J. Wildl. Manag. 64, 707e713. http://dx.doi. Rodríguez, A., Crema, G., Delibes, M., 1996. Use of non-wildlife passages across a org/10.2307/3802740. high speed railway by terrestrial vertebrates. J. Appl. Ecol. 33, 1527e1540. Hunt, A., Dickens, H.J., Whelan, R.J., 1987. Movement of mammals through tunnels http://jstor.org/stable/2404791. under railway lines. Aust. Zool. 24, 89e93. Rodríguez, A., Crema, G., Delibes, M., 1997. Factors affecting crossing of red foxes and Lesbarreres, D., Fahrig, L., 2012. Measures to reduce population fragmentation by wildcats through non-wildlife passages across a high-speed railway. Ecography roads: what has worked and how do we know? Trends Ecol. Evol. 27, 374e380. 20, 287e294. http://dx.doi.org/10.1111/j.1600-0587.1997.tb00373.x. http://dx.doi.org/10.1016/j.tree.2012.01.015. Saeki, M., Macdonald, D.W., 2004. The effects of traffic on the raccoon dog (Nyc- Lesbarreres, D., Lode, T., Merila,€ J., 2004. What type of amphibian tunnel could tereutes procyonoides viverrinus) and other mammals in Japan. Biol. Cons 118, reduce road kills? Oryx 38, 220e223. http://dx.doi.org/10.1017/ 559e571. http://dx.doi.org/10.1016/j.biocon.2003.10.004. S0030605304000389. Santos, S.M., Carvalho, F., Mira, A., 2011. How long do the dead survive on the road? Lindstedt, S.L., Miller, B.J., Buskirk, S.W., 1986. Home range, time, and body size in Carcass persistence probability and implications for road-kill monitoring sur- mammals. Ecology 67, 413e418. http://dx.doi.org/10.2307/1938584. veys. PLoS ONE 6. http://dx.doi.org/10.1371/journal.pone.0025383. Lovich, J.E., Ennen, J.R., Madrak, S., Grover, B., 2011. Turtles, culverts and alternative Sawaya, M.A., Clevenger, A.P., Kalinowski, S.T., 2013. Demographic connectivity for energy development: an unreported but potentially significant mortality threat ursid populations at wildlife crossing structures in Banff National Park. Conserv. to the desert tortoise (Gopherus agassizii). Chelonian Conserv. Biol. 10, 124e129. Biol. 27, 721e730. http://dx.doi.org/10.1111/cobi.12075. http://dx.doi.org/10.2744/CCB-0864.1. Seiler, A., Helldin, J.-O., Seiler, C., 2004. Road mortality in Swedish mammals: results Malakoff, D., 2011. Research projects could be roadkill in revision of massive of a drivers’ questionnaire. Wildl. Biol. 10, 183e191. highway bill. Science 334 (884). http://dx.doi.org/10.1126/science.334.6058. Serronha, A.M., Mateus, A.R.A., Santos-Reis, M., Grilo, C., 2013. Towards effect 884. culvert design: monitoring seasonal use and behavior by Mediterranean mes- Manen, F.T. van, Jones, M.D., Kindall, J.L., Thompson, L.M., Scheick, B.K., 2001. ocarnivores. Environ. Monit. Assess. 185, 6235e6246. http://dx.doi.org/10.1007/ Determining the potential mitigation effects of wildlife passageways on black s10661-012-3020-3. bears. In: Irwin, C.L., Garret, P., McDermott, K.P. (Eds.), Proceedings of the In- Sierla, L., Lammi, E., Mannila, J., Nironen, M., 2004. Direktiivilajien huomioon ternational Conference on Ecology and Transportation. Center for Trans- ottaminen suunnittelussa (English summary: How species listed in EU di- portation and the Environment, North Carolina State University, Raleigh, North rectives should be considered in planning processes). Suomen ymparist€ o€ 742. Carolina, USA, pp. 435e446. Finnish Ministry of the Environment, Helsinki. Mansergh, I.A., Scotts, D.J., 1989. Habitat continuity and social organization of the Spackman, S.C., Hughes, J.W., 1995. Assessment of minimum stream corridor width mountain pygmy-possum restored by tunnel. J. Wildl. Manag. 53, 701e707. for biological conservation: species richness and distribution along mid-order http://jstor.org/stable/3809200. streams in Vermont, USA. Biol. Cons. 71, 325e332. http://dx.doi.org/10.1016/ Mata, C., Hervas, I., Herranz, J., Suarez, F., Malo, J.E., 2008. Are motorway wildlife 0006-3207(94)00055-U. passages worth building? Vertebrate use of road-crossing structures on a Stuart, S.N., Chanson, J.S., Cox, N.A., Young, B.E., Rodrigues, A.S.L., Fischman, D.L., Spanish motorway. J. Environ. Manage. 88, 407e415. http://dx.doi.org/10.1016/j. Wallers, R.W., 2004. Status and trends of amphibian declines and extinctions jenvman.2007.03.014. worldwide. Science 306, 1783e1786. http://dx.doi.org/10.1126/science.1103538. Matos, H.M., Santos, M.J., Palomares, F., Santos-Reis, M., 2009. Does riparian habitat Swihart, R.K., Slade, N.A., Bergstrom, B.J., 1988. Relating body size to the rate of condition influence mammalian carnivore abundance in Mediterranean eco- home range use in mammals. Ecology 69, 393e399. http://jstor.org/stable/ systems? Biodivers. Conserv. 18, 373e386. http://dx.doi.org/10.1007/s10531- 1940437. 008-9493-2. Trombulak, S.C., Frissell, C.A., 2000. Review of ecological effects of roads on McCollister, M.F., van Manen, F.T., 2010. Effectiveness of wildlife underpasses and terrestrial and aquatic communities. Conserv. Biol. 14, 18e30. http://dx.doi.org/ fencing to reduce wildlife-vehicle collisions. J. Wildl. Manag. 74, 1722e1731 10.1046/j.1523-1739.2000.99084.x. http://dx.doi.org/doi - 10.2193/2009-535. Veenbaas, G., Brandjes, J., 1999. Use of fauna passages along waterways under McDonald, W., St Clair, C.C., 2004. Elements that promote highway crossing struc- highways. In: Evink, G.L., Garret, P., Zeigler, D. (Eds.), Proceedings of the Third ture use by small mammals in Banff National Park. J. Appl. Ecol. 41, 82e93. International Conference on Wildlife Ecology and Transportation. Florida http://dx.doi.org/10.1111/j.1365-2664.2004.00877.x. Department of Transportation, Tallahassee, Florida, USA, pp. 253e258. Meaney, C., Bakeman, M., Reed-Eckert, M., Wostl, E., 2007. Effectiveness of Ledges in Villalva, P., Reto, D., Santos-Reis, M., Revilla, E., Grilo, C., 2013. Do dry ledges reduce Culverts for Small Mammal Passage (Report No. CDOT-2007-9). Colorado the barrier effect of roads? Ecol. Eng. 57, 143e148. http://dx.doi.org/10.1016/j. Department of Transportation Research Branch, Denver. http://www. ecoleng.2013.04.005. coloradodot.info/programs/research/pdfs/2007/smallmammal.pdf. Vagverket,€ 2005. Uttrar och vagar.€ Swedish Transport Administration, Borlange.€ Ng, S.J., Dole, J.W., Sauvajot, R.M., Riley, S.P.D., Valone, T.J., 2004. Use of highway http://publikationswebbutik.vv.se/upload/872/88869_Uttrar_och_vagar.pdf. undercrossings by wildlife in southern. Calif. Biol. Cons. 115, 499e507. http://dx. Va€an€ anen,€ V.M., Nummi, P., Rautiainen, A., Asanti, T., Huolman, I., Mikkola-Roos, M., doi.org/10.1016/S0006-3207(03)00166-6. Nurmi, J., Orava, R., Rusanen, P., 2007. Vieraspeto kosteikolla e vaikuttaako Niemi, M., Grenfors, E., Martin, A., Nummi, P., Tanner, J., 2007. Tie tappaa e mihin supikoira vesilintujen ja kahlaajien poikueiden ma€ar€ a€an?€ (English summary: elaimille€ tarkoitetut kulkureittiratkaisut kannattaa rakentaa? ((English sum- The effect of raccoon dog Nyctereutes procyonoides removal on waterbird mary: Road kills of small vertebrates e can we do something?)), 53 Suomen breeding success), 53 Suomen Riista, pp. 49e63. Riista, pp. 89e103. http://www.helsinki.fi/metsatieteet/tutkimus/hankkeet/ Woltz, H.W., Gibbs, J.P., Ducey, P.K., 2008. Road crossing structures for amphibians riistahankkeet/pdf/SR53_89103.pdf. and reptiles: informing design through behavioral analysis. Biol. Cons. 141, Olsson, M.P.O., Widen, P., Larkin, J.L., 2008. Effectiveness of a highway overpass to 1745e2750. http://dx.doi.org/10.1016/j.biocon.2008.08.010. promote landscape connectivity and movement of moose and roe deer in Yanes, M., Velasco, J.M., Suarez, F., 1995. Permeability of roads and railways to Sweden. Landsc. Urban Plan. 85, 133e139. http://dx.doi.org/10.1016/j. vertebrates: the importance of culverts. Biol. Cons. 71, 217e222. http://dx.doi. landurbplan.2007.10.006. org/10.1016/0006-3207(94)00028-O. Orlowski, G., 2007. Spatial distribution and seasonal pattern in road mortality of the Zee, F.F., van der, Wiertz, J., Ter Braak, C.J.F., Apeldoorn, R.C., van, 1992. Landscape common toad Bufo bufo in an agricultural landscape of south-western Poland. change as a possible cause of the badger Meles meles L. decline in The Amphibia-Reptilia 28, 25e31. http://dx.doi.org/10.1163/156853807779799045. Netherlands. Biol. Cons. 61, 17e22. http://dx.doi.org/10.1016/0006-3207(92) Philcox, C.K., Grogan, A.L., MacDonald, D.W., 1999. Patterns of otter Lutra lutra road 91203-5. mortality in Britain. J. Appl. Ecol. 36, 748e762. http://dx.doi.org/10.1046/j.1365- Zuur, A.F., Ieno, E.N., Walker, N.J., Saveliev, A.A., Smith, G.M., 2009. Mixed Effects 2664.1999.00441.x. Models and Extensions in Ecology with R. Springer, New York. Obama Signs Bill Delaying Deadline for Train-Safety Equipment Installation - The New York Times

NATIONAL BRIEFING | WASHINGTON Ending Obama Signs Bill Delaying Deadline for The Disciple Strikes Back: Questions and Answers od Train-Safety Equipment Installation Rubio Bests Bush in a Key About Veteran Suicides Moment

U.S. | NATIONAL BRIEFING | WASHINGTON Obama Signs Bill Delaying Deadline for Train-Safety Equipment Installation

By THE ASSOCIATED PRESS OCT. 29, 2015

President Obama on Thursday signed a Email bill that gave railroads at least three more years to install safety technology known Share as positive train control. Railroads, which had been given seven years by Congress Tweet to install the technology, sought the delay, saying they were likely to miss a Save year-end deadline. They now have until Dec. 31, 2018, to complete the upgrade or More seek a waiver. The measure also extends until Nov. 20 the government’s authority to spend money on transportation programs in an effort to buy time for Congress to pass a long-term bill. Federal investigators say positive train control would have prevented an Amtrak derailment in Philadelphia in May that killed eight people and injured about 200 others. (AP)

A version of this brief appears in print on October 30, 2015, on page A14 of the New York edition with the headline: Obama Signs Bill Delaying Deadline For Train-Safety Equipment Installation . Order Reprints | Today's Paper | Subscribe

More in U.S. » TRENDING

http://www.nytimes.com/2015/10/30/us/obama-signs-bill-delaying-deadline-for-train-safety-equipment-installation.html?_r=0[10/29/2015 8:14:17 PM] Date of Incident Origin City Origin State Destination City Destination State Incident City Incident County Incident State Carrier/Reporter Name Commodity Short Name 2/3/2015 THOREAU NEW MEXICO BAKERSFIELD CALIFORNIA Barstow SAN BERNARDINO CA BNSF RAILWAY COMPANY PETROLEUM CRUDE OIL 10/17/2014 WELLINGTON UTAH LONG BEACH CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 10/17/2014 BIG SPRING TEXAS PARAMOUNT CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 10/9/2014 FARMINGTON UTAH LONG BEACH CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 9/19/2014 EGBERT WYOMING LONG BEACH CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 9/19/2014 EGBERT WYOMING LONG BEACH CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 9/19/2014 EGBERT WYOMING LONG BEACH CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 7/16/2014 HELPER UTAH LONG BEACH CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 7/1/2014 THOREAU NEW MEXICO LONG BEACH CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 6/8/2014 JAMESTOWN NEW MEXICO BAKERSFIELD CALIFORNIA Barstow SAN BERNARDINO CA BNSF RAILWAY COMPANY PETROLEUM CRUDE OIL 6/4/2014 ALBUQUERQUE NEW MEXICO BAKERSFIELD CALIFORNIA Barstow SAN BERNARDINO CA BNSF RAILWAY COMPANY PETROLEUM CRUDE OIL 6/3/2014 FARMINGTON UTAH LONG BEACH CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 5/16/2014 SAN ARDO CALIFORNIA WILMINGTON CALIFORNIA Carson LOS ANGELES CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 5/14/2014 DOUGLAS WYOMING LONG BEACH CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 5/13/2014 THOREAU NEW MEXICO LONG BEACH CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 5/12/2014 FARMINGTON UTAH VERNON CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 5/11/2014 THOREAU NEW MEXICO LONG BEACH CALIFORNIA Barstow SAN BERNARDINO CA BNSF RAILWAY COMPANY PETROLEUM CRUDE OIL 4/21/2014 LONG BEACH CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 4/9/2014 JAMESTOWN NEW MEXICO BAKERSFIELD CALIFORNIA Barstow SAN BERNARDINO CA BNSF RAILWAY COMPANY PETROLEUM CRUDE OIL 3/29/2014 JAMESTOWN NEW MEXICO BAKERSFIELD CALIFORNIA Barstow SAN BERNARDINO CA BNSF RAILWAY COMPANY PETROLEUM CRUDE OIL 3/10/2014 CARSON CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 3/6/2014 CARSON CALIFORNIA BLOOMINGTON SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 3/6/2014 CARSON CALIFORNIA BLOOMINGTON SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 2/3/2014 LONG BEACH CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 2/3/2014 LONG BEACH CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 1/27/2014 CARSON CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 1/27/2014 FARMINGTON UTAH LONG BEACH CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 1/20/2014 CARSON CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 1/20/2014 FARMINGTON UTAH LONG BEACH CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 1/8/2014 WILMINGTON CALIFORNIA ROSEVILLE PLACER CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 1/8/2014 WILMINGTON CALIFORNIA ROSEVILLE PLACER CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 1/8/2014 WILMINGTON CALIFORNIA ROSEVILLE PLACER CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 1/8/2014 WILMINGTON CALIFORNIA ROSEVILLE PLACER CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 1/8/2014 WILMINGTON CALIFORNIA ROSEVILLE PLACER CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 1/7/2014 CARSON CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 1/7/2014 WILMINGTON CALIFORNIA Roseville PLACER CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 1/7/2014 LONG BEACH CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 1/7/2014 CARSON CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 1/3/2014 LONG BEACH CALIFORNIA BLOOMINGTON SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 1/3/2014 LONG BEACH CALIFORNIA BLOOMINGTON SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 1/3/2014 LONG BEACH CALIFORNIA BLOOMINGTON SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL 1/3/2014 LONG BEACH CALIFORNIA Bloomington SAN BERNARDINO CA UNION PACIFIC RAILROAD COMPANY INC PETROLEUM CRUDE OIL Water Air Soil Pollut (2011) 218:333–345 DOI 10.1007/s11270-010-0645-0

Railway transportation as a serious source of organic and inorganic pollution

B. Wiłkomirski & B. Sudnik-Wójcikowska & H. Galera & M. Wierzbicka & M. Malawska

Received: 7 May 2010 /Accepted: 24 September 2010 /Published online: 8 October 2010 # The Author(s) 2010. This article is published with open access at Springerlink.com

Abstract Polycyclic aromatic hydrocarbons and railway junction showed a very significant increase of heavy metal (Pb, Cd, Cu, Zn, Hg, Fe, Co, Cr, Mo) the PAHs level since 1995. It was found that the heavy contents were established in soil and plant samples metal contamination was also very high. Pb, Zn, Hg collected in different areas of the railway junction and Cd were established at the highest levels in the Iława Główna, Poland. Soil and plant samples were railway siding area, whereas Fe concentration was the collected in four functional parts of the junction, i.e. highest in the platform area. A significant increase in the loading ramp, main track within platform area, mercury content was observed in the cleaning bay area. rolling stock cleaning bay and the railway siding. It The investigations proved very significant increase of was found that all the investigated areas were strongly contamination with PAHs and similar heavy metals contaminated with polycyclic aromatic hydrocarbons contamination in comparison with the concentration (PAHs). The PAH contamination of the soil was the determined in the same areas 13 years ago. highest in the railway siding and in the platform area (59,508 and 49,670 μgkg−1, respectively). In the Keywords Railway. Soil . Plants . Contamination . loading ramp and cleaning bay, the PAH concentra- Heavy metals . PAHs tion in soil was lower but still relatively very high (17,948 and 15,376 μgkg−1, respectively). The contamination in the railway siding exceeded the 1 Introduction average control level up to about 80 times. In the soil of all the investigated areas, four- and five-ring PAHs The railway is one of the most fundamental (apart prevailed. The concentrations of PAHs were determined from roads) means of transportation. In Poland, the in four dominating species of plants found at the rail has used some areas for more than 150 years. It junction. The highest concentration was found in the has been commonly thought that rail transportation is aerial parts of Taraxacum officinale (22,492 μgkg−1) much less harmful to the environment than road growing in the cleaning bay. The comparison of the traffic. However, the specificity of rail causes some soil contamination with PAHs in the investigated typical organic and inorganic contamination (Malawska and Wiłkomirski 1999, 2000, 2001; Lacey and Cole ł * : : B. Wi komirski: ( ) B. Sudnik-Wójcikowska: 2003; Liu et al. 2009), resulting mostly from used H. Galera M. Wierzbicka M. Malawska lubricate oils and condenser fluids, transportation of oil Institute of Botany, University of Warsaw, derivatives, metal ores, fertilizers and different chemicals, Al. Ujazdowskie 4, 00-478 Warsaw, Poland as well as from application of herbicides. The two most e-mail: [email protected] important types of pollutants connected with railway 334 Water Air Soil Pollut (2011) 218:333–345 transport are polycyclic aromatic hydrocarbons (PAHs) environmental pollution. After World War II, the very and heavy metals. Besides high toxicity, significant old railway junction Iława Główna (built in 1870) stability and a cumulative effect in the environment became an important junction in Polish Railway PAHs have a peculiar feature, which is the carcinogenic Network. Very heavy passenger and goods traffic is and mutagenic effect on living organisms (IARC 1983). concentrated in the area of the junction because Iława The main source of PAHs in railway areas derives from Główna is situated at the crossing of a few important substances used for rolling stock exploitation such as railway routes. The railway junction covers an area of machine grease, fuel oils and transformers oils. Another almost 2 km2 within which the different functional important source of PAHs is creosote, which is a parts are situated. Our investigations were carried out common impregnation agent for outdoor wood structures, at four sites of the junction: including railway ties (Brooks 2004; Moret et al. 2007; 1. The railway siding (in tables and figures referred Thierfelder and Sandström 2008). Heavy metals are to as “siding”) which consists of many tracks amongst the most frequently found and intensively where goods trains wait for unloading. The studied chemical substances that contaminate the envi- sampling area was situated in the most frequently ronment. Railway areas are thought to be sites of used track of the railway siding (53°34′67.5″ N; intensive heavy metal emission, and there are some 19°34′34.0″ E) interesting articles dealing with this problem (Chillrud et 2. The loading station (referred to as “loading”) al. 2005;Bukowieckietal.2007; Liu et al. 2009). The which is the track located close to the loading rail rolling stock construction material abrasion, fuel platform where different goods (at present mostly combustion in diesel-electric locomotives, action of coal) are reloaded from hopper wagons to heavy pantographs on trolley wires and cargo leakage emit lorries (53°35′09.4″ N; 19°34′39.7″ E) particles containing heavy metals into the air and 3. Track no. 7 (referred to as “platform”) which is subsequently deposit them into the plant and soil through located in the passenger part of the junction and dry and wet deposition. focuses main stream of local and long distance The first aim of this work is to present information trains (53°34′55.0″ N; 19°34′26.1″ E) concerning the pollution level of soil and plants with 4. The rolling stock cleaning bay (referred to as heavy metals (Pb, Cd, Cu, Zn, Hg, Fe, Co, Cr, Mo) “cleaning”) which is the separated and unsecured and 17 PAHs in the area of four functional parts of the railway track with no facilities preventing the railway junction Iława Główna (Poland). Similar leakage (53°34′49.0″ N; 19°34′20.1″ E) investigations were performed 13 years ago (Malawska and Wiłkomirski 2001); hence, the second aim is to compare the presents results with previous findings 2.2 Soil and plant sampling and to provide evidence that railway transport is the source of the above contamination. At each of the four investigated sites, a surface covering a total of 120 m2 was established. The surface consisted of two subsurfaces (60 m2 each): the 2 Materials and methods first covering a fragment of the tracks situated between the rails (rail gauge) and the second one 2.1 Study area located outside both rails up to the end of railway ties. This allowed us to find the potential differences The investigations were carried out in the area of the between the level of contamination inside and outside railway junction Iława Główna located in northern rails. The diagram illustrating the method of soil Poland about 200 km north of Warsaw on the sampling in each investigated area is presented in Warsaw–Gdańsk railway route in the western part of Fig. 1. the Mazurian Lake Region. This region covered Soil samples were collected in predetermined mostly by forests and lakes is relatively clean, since investigation areas in September 2008. The railway no heavy industry is concentrated there. The junction basement soil collected from the depth of 0–20 cm having such location is the relevant place to investi- was sieved (5 mm sieve) directly at the sampling area. gate the influence of railway transportation on Each time, 15–20 individual samples were taken Water Air Soil Pollut (2011) 218:333–345 335

Fig. 1 Method of soil sampling

thereby providing a mean mixed sample of about 1 kg fluoranthene, pyrene, benzo[a]anthracene, chrysene, benzo of the soil representing ballast bed either from the [b]fluoranthene, benzo[k]fluoranthene, benzo[e]pyrene, subsurface located between the rails or outside rails. benzo[a]pyrene, perylene, indeno[123-cd]pyrene, dibenzo Dried soil samples were sieved (1 mm sieve) in the [ah]anthracene and benzo[ghi]perylene. laboratory and used for further analysis. The entire analytical procedure underwent quality The reference soil samples were collected at three control checks. Analyses of blanks were performed points: (1) the vicinity of a small factory about 500 m for every eight samples. PAH concentrations in all southwest of the railway junction (53°34′44.6″ N; 19° blank values were below the detection limit. 34′13.1″ E), (2) hilly field about 500 m southeast of Heavy metal analyses were carried out after the railway junction (53°34′43.2″ N; 19°34′33.4″ E) mineralization using nitric acid and microwaves for and (3) field in the suburb town of Iława about 2 km east plant samples and aqua regia in open system for soil of the railway junction (53°34′52.4″ N; 19°35′05.7″ E). samples. The mercury content was established by the total mercury assessment technique with an AMA 254 2.3 Determination of PAHs and heavy metals analyser. The other heavy metal contents (Pb, Cd, Cu, Zn, Fe, Co, Cr, Mo) were established by the The extraction of plant and soil samples was inductively coupled plasma (ICP) mass spectroscopy performed with the use of dichloromethane. Further technique for plants and ICP-optical emission spec- purification was carried out on Florisil. The PAH trometry technique for soil samples. The quality content analysis in plant and soil material was assurance and quality control was performed by performed using a gas chromatograph equipped with analyzing the standard samples of known composi- a mass detector (GC/MSD Agilent Technologies tion. All the analyses (PAHs and heavy metals) were 6890 N/5973) and a non-polar capillary column HP- carried out in Central Chemical Laboratory of Polish 5MS (length 50 m, diameter 0.2 mm, 0.3 μm Geological Institute which possesses accreditation diphenyl–95% dimethylpolysiloxane film). Tempera- certificate AB 283. ture programming was applied: 70°C±10°C min−1 to 200°C, ±2°C min−1 to 300°C (2 min). The detector temperature was 280°C. The temperature of injection 3 Results and discussion port was 250°C. The quantitative analysis was performed using the external standard method where The levels of PAHs were determined in soil samples the certified PM-612 standard (Ultra Scientific Ltd) and selected plants. The PAH contents in the soil was applied for PAHs except benzo[e]pyrene and collected from the four functional parts of the perylene for which certified standard 15 RM-612 junction, i.e. “siding”, “loading”, “platform” and (LGC Standard) was applied. The carrier gas was “cleaning”, are presented in Table 1. The results helium—flow rate 1 ml/min. obtained from each study area are represented by two The following 17 PAHs were determined: acenaphthy- values, i.e. A (between rails—rail gauge) and B lene, acenaphthene, fluorene, phenanthrene, anthracene, (shoulder outside rails). Control values represented 336 Water Air Soil Pollut (2011) 218:333–345

Table 1 Content of PAHs in soil samples taken from Compounds Siding Loading Platform Cleaning Control the railway junction Iława Główna depending on place ABABABAB123 (micrograms per kilogram) Acenaphthylene 240 352 106 65 333 172 125 92 2 4 2 Acenaphthene 443 347 53 51 480 326 65 27 1 2 2 Fluorene 396 349 86 76 455 418 69 43 1 3 2 Phenanthrene 5,000 4,500 1,318 1,186 5,700 4,300 1,149 666 39 64 35 Anthracene 1,584 1,558 427 287 1,023 866 530 289 7 6 3 Fluoranthene 8,900 7,400 2,650 2,450 8,100 6,800 2,380 1,188 135 133 69 Pyrene 7,600 6,200 2,640 2,180 6,700 5,700 2,170 1,189 114 101 54 Benzo[a]anthracene 4,900 5,300 1,275 1,142 3,300 2,970 1,047 511 60 48 24 Chrysene 4,400 4,700 1,359 1,183 3,500 2,860 1,181 565 70 73 32 Benzo[b]fluoranthene 5,900 6,300 2,160 1,626 4,700 3,700 1,719 791 92 83 35 Benzo[k]fluoranthene 2,650 2,900 871 715 1,976 1,630 686 341 49 42 18 Benzo[e]pyrene 2,290 2,510 841 659 1,939 1,484 668 361 75 64 28 Benzo[a]pyrene 5,300 5,800 1,348 1,192 3,500 3,200 1,085 537 85 59 28 Perylene 869 937 228 204 551 509 187 99 21 13 5 Indeno[123-cd]pyrene 4,300 4,700 1,265 1,061 3,400 2,850 1,026 562 83 73 25 Dibenzo[ah]anthracene 936 1,032 211 218 713 601 220 116 15 12 5 Benzo[ghi]perylene 3,800 4,100 1,110 940 3,300 2,640 1,069 609 83 70 24 results obtained from the three described reference the junction, the lowest contamination was detected in areas, respectively. the cleaning bay area, reaching 15,376 and Whilst analyzing the total PAHs found in soil in 7,986 μgkg−1 (A and B, respectively). Figure 2 different parts of the railway junction Iława Główna, presented the comparison of total PAHs content in rail the highest concentrations of these substances were gauge (A) and shoulder (B). In all the investigated detected in the platform and railway siding areas areas, the total PAHs content is slightly higher in reaching in siding 59,508 and 58,985 μgkg−1 (A and transect A than in transect B. All amounts are B, respectively) and in platform 49,670 and significantly higher than the amount of PAHs in 41,026 μgkg−1 (A and B, respectively). The concen- control areas. tration of PAHs in the loading ramp was placed at the The PAHs concentration in soil of the three level 17,948 and 41,026 μgkg−1 (A and B, respec- reference areas varied from 391 to 932 μgkg−1.In tively). Amongst the investigated functional parts of all the investigated areas, the level of PAHs in the rail

Fig. 2 The comparison of 70000 total PAH content in soil sum of 17 PAHs 59508 58985 of transect A and transect B 60000 depending on place 49670 (micrograms per kilogram) 50000 41026 40000

30000

20000 17948 15170 15376

10000 7986 932 850 391 0 AAAA1B B B B 2 3 siding loading platform cleaning control Water Air Soil Pollut (2011) 218:333–345 337

Fig. 3 The percentage con- 6 ring tent of three-, four-, five- and 5 ring six-ring PAHs in railway 4 ring ł ł 100% junction I awa G ówna 3 ring depending on place 90%

80%

70%

60%

50%

40%

30%

20%

10%

0% AAAA1B B B B 2 3 siding loading platform cleaning control gauge was slightly higher than in the shoulder. Such a groups of hydrocarbons in soil of all the parts of the pattern of PAH levels indicates that soil contamination is junction were four- and five-ring PAHs. mostly created either by very intensive train movement The tracks of all the investigated parts of the (platform) or by rolling stock remaining in one place for a junction were covered by plants, although in different long time (siding). In the loading ramp and the cleaning degree. The plant cover on track which is very heavily bay where traffic is not heavy and rolling stock remains used within platform area was very poor. A slightly for a relatively short time, the PAH level is less increased bigger plant cover was observed in the loading ramp, compared with the formerly described parts of the whereas in the railway siding and the cleaning bay, junction. The same distribution of contamination was the plant cover was relatively more abundant but still observed in the past (Malawska and Wiłkomirski 2001), rather scanty. but currently the contamination level is much higher. In all the investigated areas, 120 plant species were Figure 3 presented the percentage content of three-, found (Galera et al., submitted for publication). four-, five- and six-ring PAHs in railway junction However, the prevailing number of them was represented Iława Główna. It proved that the most abundant by one or a few specimens. Four species occurring in

25000 22492

20000 17371 15523 15182 15461 14896 15000 12302 13359 13159

10000 7615 7640 7687 5843 5000 3936

0 AP* R AP* R AP* R AP* R AP* R AP* R AP* R Daucus carota Sonchus oleraceus Pastinaca sative Sonchus oleraceus Taraxacum sp. Daucus carota Taraxacum sp. siding loading platform cleaning bay

*AP-aerial parts; R-roots

Fig. 4 The comparison of the total PAH content in different plants in railway junction Iława Główna depending on place (micrograms per kilogram) 338 Water Air Soil Pollut (2011) 218:333–345

Table 2 Content of PAHs in plant samples (aerial parts and roots) in railway junction Iława Główna depending on place (micrograms per kilogram)

Compounds Siding Loading Platform Cleaning bay

Daucus Sonchus Pastinaca Sonchus Taraxacum Daucus Taraxacum carota oleraceus sativa oleraceus sp. carota sp.

AP R AP R AP R AP R AP R AP R AP R

Acenaphthylene 161 120 38 126 196 123 26 89 23 28 98 177 135 130 Acenaphthene 840 66 63 63 1,213 150 56 95 99 49 167 54 62 40 Fluorene 1,484 122 137 117 1,344 207 119 284 114 71 216 98 111 81 Phenanthrene 5,600 1,225 1,363 1,238 1,000 1,685 936 2,170 1,125 760 1,938 769 1,476 923 Anthracene 200 342 305 373 460 311 109 456 126 114 155 483 443 412 Fluoranthene 4,200 1,758 2,600 1,786 7,800 2,510 672 1,404 1,285 891 1,929 1,102 6,600 2,610 Pyrene 1,463 1,470 1,375 1,524 2,870 1,890 498 1,458 996 721 861 1,382 4,100 1,960 Benzo[a]anthracene 184 898 236 900 295 1,014 194 777 482 380 230 500 763 582 Chrysene 327 1,068 426 1,089 818 1,055 239 752 557 391 368 619 3,300 1,469 Benzo[b]fluoranthene 294 2,040 350 2,130 504 1,511 326 1,364 857 576 482 2,430 2,260 1,776 Benzo[k]fluoranthene 122 851 133 868 195 619 113 438 308 250 187 936 899 660 Benzo[e]pyrene 117 835 117 856 168 575 124 530 260 242 197 947 787 664 Benzo[a]pyrene 184 1,576 175 1,567 161 1,015 186 785 539 388 266 1,409 445 503 Perylene 30 304 26 300 30 179 27 128 84 68 45 260 73 97 Indeno[123-cd]pyrene 147 1,204 129 1,209 155 969 135 680 377 417 257 1,044 529 592 Dibenzo[ah]anthracene 34 250 31 248 29 203 36 146 70 64 53 236 98 101 Benzo[ghi]perylene 136 1,053 111 1,067 133 880 140 746 338 433 238 913 411 559

AP aerial parts, R roots

100%

90%

80%

70%

60% 6 ring 5 ring 50% 4 ring 40% 3 ring 30%

20%

10%

0% AP RAPRAPRAPRAPRAPRAPR Daucus carota Sonchus oleraceus Pastinaca sative Sonchus oleraceus Taraxacum sp. Daucus carota Taraxacum sp. siding loading platform cleaning bay

Fig. 5 The percentage content of three-, four-, five- and six-ring PAHs in aerial parts and roots of selected species growing in different parts of Iława Główna junction Water Air Soil Pollut (2011) 218:333–345 339

Fig. 6 The comparison of 60000 55186 14 PAHs content in soil in sum of 14 PAHs four functional parts of the 50000 railway junction Iława ł G ówna in 1995 and 38861 2008 years (micrograms per 40000 kilogram) 30000

14307 20000

10000 7434 2178.3 2249 1097.5 910.4 384 356 0 1995 2008 1995 2008 1995 2008 1995 2008 1995 2008 siding loading platform cleaning control relatively higher abundance were selected for PAHs Table 2 shows the PAH content in the aerial parts analysis, although in the loading ramp and platform areas and roots of a selected plant in the investigated areas only one species could be collected in the amount which of the junction. makes chemical analysis possible. The selected species The percentage content of PAHs possessing different included three perennials (Daucus carota, Pastinaca numbers of rings in the molecule in aerial parts and roots sativa and Taraxacum officinale) and one annual plant of selected species growing in different parts of Iława (Sonchus oleraceus). All the collected plant specimens Główna junction was presented in Fig. 5. The most were divided into aerial parts and roots. abundant group of PAHs present in plants in the The comparison of PAH total content in different investigated areas is represented by four-ring PAHs. plants in railway junction Iława Główna is presented Plants of three species growing in the railway siding in Fig. 4. The highest level of PAHs (22,492 μgkg−1) differ from other investigated plants by a much smaller was observed in T. officinale growing in the cleaning amount of five- and six-ring PAHs in aerial parts. bay. The highest PAH accumulation in roots was The present study was carried out in September observed in plants growing in railway siding area and 2008. Thirteen years ago in the same study area, the reached 15,182, 15,461 and 14,896 μgkg−1 in D. following 14 PAHs were determined: acenaphthene, carota, S. oleraceus and P. sativa, respectively. fluorene, phenanthrene, anthracene, fluoranthene, pyrene,

Fig. 7 The comparison of 25000 the 14 PAHs content in aerial parts of different sum of 14 PAHs 21497 plants from the area 20000 of Iława Główna railway junction in 1995 and 16977 2008 (micrograms per 15215 kilogram) 15000

10000 7434 7273 7347

3756 5000

846 722.3 640.7 393.6 65.4 118.5 0 T.o** D.c P.s S.o. T.o. S.o. T.o T.o T.o T.o D.c. T.o. T.o 1995 2008 1995 2008 1995 2008 1995 2008 1995 2008 siding loading platform cleanning control bay 340 Water Air Soil Pollut (2011) 218:333–345 Fig. 8 a The percentage sum of 6 ring sum of 4 ring content of three-, four-, a five- and six-ring PAHs in sum of 5 ring sum of 3 ring soil collected in 1995 and 100% 2008 depending on place. b The percentage content of 90% three-, four-, five- and six-ring PAHs in plants 80% collected in 1995 and 2008 depending on place 70%

60%

50%

40%

30%

20%

10%

0% 1995 2008 1995 2008 1995 2008 1995 2008 1995 2008 siding loading platform cleaning control

b 3 ring 4 ring 5 ring 6 ring 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% T.o D.c P.s S.o. T.o. S.o. T.o T.o T.o T.o D.c. T.o. T.o 1995 2008 1995 2008 1995 2008 1995 2008 1995 2008 platform loading siding cleanning bay control benzo(a)anthracene, chrysene, benzo(b)fluoranthene, of 14 investigated PAHs in the soil of the different parts benzo(k)fluoranthene, benzo(a)pyrene, indeno(123-cd) of the junction (in 1995 and 2008) is presented in Fig. 6. pyrene, dibenzoanthracene and bezo(ghi)perylene According to the data obtained from Polish Rail (Malawska and Wiłkomirski 2001). The comparison of Regional Head Office in Olsztyn, the different parts earlier findings with the results indicating the total level of the railway junction Iława Główna were renovated of the same 14 PAHs determined in the present study (including the replacement of ballast bed and railway showed a very significant increase of PAHs content in all ties): cleaning bay in 1978, track no. 7 in 1977, the functional parts of the railway junction Iława loading ramp in 1984 and railway siding in 1991. Główna. At the same time, the PAH level in the control Between our former investigations and the present areas did not change. The comparison of the total level study, no other renovation was carried out. Hence, the Water Air Soil Pollut (2011) 218:333–345 341

Table 3 Content of heavy metals in soil samples collected in the railway junction Iława Główna depending on place (milligrams per kilogram)

Heavy metals Siding Loading Platform Cleaning Control

Soil Soil Soil Soil Soil Soil Soil Soil Soil Soil Soil ABABA BAB123

Lead 448 494 75 84 193 177 134 204 8 11 6 Cadmium 5.4 5.1 7.4 0.8 2.5 1.3 1.3 1.9 n.d. n.d. n.d. Copper 191 161 33 37 480 326 105 418 4 4 4 Zinc 1,264 1,223 206 228 1,438 897 357 563 23 23 18 Mercury 0.573 0.969 0.066 0.046 0.165 0.144 0.678 0.757 0.014 0.050 0.013 Iron 44,800 39,700 14,600 11,900 112,900 59,700 24,900 34,300 4,400 4,500 5,000 Cobalt 9 8 3 3 14 656112 Chromium 67 58 14 11 208 62 23 33 5 6 8 Molybdenum 2 2 n.d. n.d. 8 4 1 1 n.d. n.d. 1

13 years of intensive railway use led to the substantial The levels of nine heavy metals (Pb, Cd, Cu, Zn, increase of the PAHs level in soil. Hg, Fe, Co, Cr, Mo) were established. The highest Similar analysis also indicated a remarkably high level of lead, which exceeded the control level contamination of plants with PAHs compared with approximately 50-fold, was determined in the siding previous investigations. The control made for T. area. In other parts of the junction, the lead level was officinale did not show the increase of the contami- lower and exceeded the control value by ca. tenfold, nation. These results are presented in Fig. 7. Very 22-fold and 20-fold, respectively. The cadmium level interesting results are presented in Fig. 8 showing the is rather low in all the investigated areas. However, in proportion between PAHs possessing different number the area of siding and in railway gauge of the loading of rings in the molecule. ramp, the level of cadmium is higher than in other The significant percentage of five- and six-ring parts of the junction. The highest concentration of PAHs in the soil (ranging from about 25% to about copper was detected in the platform area, what is easy 50%) is very characteristic. This percentage is to understand due to the intensive action of panto- different in the case of plants. The lack of five- and graphs on trolley wires (track 7 is intensively used by six-ring PAHs in plants growing in control areas and passenger trains and some of them do not stop at the the small percentage of these compounds in plants station, passing through with a high velocity). growing within railway junction suggested that The whole area of the junction contains elevated railway transport is a source of serious pollution with concentration of zinc. The highest concentration of PAHs. It seems that the content of “heavy” PAHs in this metal was observed on the siding, exceeding the the soil is associated with the permanent and long control level approximately 60-fold. A significant cumulative deposit, whereas plants reflect rather increase in mercury content was observed in the current deposit connected with railway emission. This cleaning bay area and in the railway siding. In both is in accordance with the observations concerning the areas, the average mercury concentration exceeded different uptake pathways of contaminants into plants the control level about 30 times. (Trapp 1995;Barberetal.2004). The smaller Cobalt and molybdenum concentrations in the soil percentage of the “light” PAHscouldalsobe of all the investigated areas were relatively low. Iron connected with their evaporation from the soil. Such contamination of soil is high in all the functional parts tendencies were observed both in 1995 and 2008. of the junction, especially in the platform area where The levels of the investigated heavy metals were in the railway gauge its level reached ca. 11%, determined in soil samples and selected plants. The justifying the common name of the railway. Chromium heavy metal contents in soil are presented in Table 3. contamination varied reaching the highest level in the rail 342 Table 4 Content of heavy metals in aerial parts and root of selected plants collected in railway junction Iława Główna depending on place (milligrams per kilogram dry weight)

Heavy metals Siding Loading Platform Cleaning

Daucus carota Sonchus oleraceus Pastinaca sativa Sonchus oleraceus Taraxacum sp. Daucus carota Taraxacum sp. Taraxacum sp.

Ap R Ap R Ap R Ap R Ap R Ap R Ap R Ap R

Lead 13.39 68.42 11.69 74.81 7.49 80.75 13.41 55.26 19.44 29.98 11.29 32.91 14.97 43.69 14.97 43.69 Cadmium 0.73 1.5 0.73 1.32 0.32 1.43 1 1.23 0.85 0.85 1.18 1.62 1.00 1.11 1.00 1.11 Copper 22.12 62.26 22.94 85.9 18.92 44.83 29.04 39.82 123.19 154.43 46.89 72.91 53.88 107.42 53.88 107.42 Zinc 100 243 122 260 85 248 224 153 102 120 192 153 158 203 158 203 Mercury 0.03 0.16 0.03 0.1 0.03 0.090 0.026 0.048 0.033 0.040 0.046 0.107 0.118 0.406 0.118 0.406 Iron 4,695 11,644 3,528 15,062 2,985 8,590 2,075 5,199 18,819 20,361 5,119 9,178 5,274 12,405 5,274 12,405 Cobalt 0.89 2.57 0.64 3.3 0.55 2.33 0.69 2.38 2.65 2.77 0.81 1.65 0.91 2.36 0.91 2.36 Chromium 19 142 20 226 36 92 35 37 57 72 25 67 26 110 26 110 Molybdenum 2.25 1.8 2.14 2.38 2.07 1.06 0.97 1.1 2.01 3.92 1.61 1.6 4.53 2.12 4.53 2.12

AP aerial parts, R roots

Table 5 The comparison of heavy metal contents in the soil from the area of Iława Główna railway junction in 1995 and 2008 depending on place (milligrams per kilogram dry weight)

Heavy metal Siding Loading Platform Cleaning Control

1995 2008 1995 2008 1995 2008 1995 2008 1995 2008

Lead 506 494 62 84 55 177 273 204 22 11 6 8 218:333 (2011) Pollut Soil Air Water Cadmium 5.2 5.1 0.7 0.8 nd 1.3 2.8 1.9 nd n.d. n.d. nd Copper 115 161 25 37 24 326 113 418 6 4 4 4 Zinc 704 1,223 95 228 84 897 1,244 563 45 23 18 23 Mercury 0.26 0.97 0.02 0.046 0.01 0.144 2.28 0.76 0.04 0.05 0.01 0.01 Iron 50,600 39,700 10,800 11,900 11,600 59,700 40,000 34,300 5,300 4,500 5,000 4,400 Cobalt 682326861121 Chromium 81 58 10 11 14 62 32 33 5 6 8 5 Molybdenum 3 2 nd n.d. nd 4 2 1 nd n.d. 1 nd – 345 Water Air Soil Pollut (2011) 218:333–345 343

gauge in the platform area. Generally, the contamination of soil with all the heavy metals, except mercury, was higher in the railway siding and platform area and lower Taraxacum officinale in the loading ramp and cleaning bay. With regard to the railway studies, Liu et al. (2009) reported the levels of heavy metals alongside mountain

Taraxacum officinale railway in China. These concentrations were comparable to our results. The heavy metal contents in roots and aerial parts of selected plants collected in different

Daucus carota functional parts of the junction are presented in Table 4. In nearly all the investigated plants, the contents of heavy metals were higher in roots than in aerial parts. A different tendency was demonstrated only in the

Taraxacum officinale case of molybdenum. The concentration of PAHs in the area of railway junction significantly increased from 1995 to 2008. The heavy metal concentration did not change Taraxacum officinale considerably during this period. We assumed that this was connected with the railway ballast permeability making the leaching of soluble contamination possible. ówna railway junction in 1995 and 2008 (milligrams per kilogram dry weight)

ł The comparisons of heavy metal contents in 1995 and Taraxacum officinale 2008 in soil and plants are presented in Tables 5 and 6, awa G ł respectively. The statistical analysis showing the dependence

Taraxacum officinale between contents of contaminants in plants and soil is presented in Table 7. The obtained results show:

1. High positive dependence between Cu, Fe and Hg Sonchus oleraceus (lower) contents in soil and the amount of these metals in aerial parts of plants 2. High positive dependence between Pb, Cu, Fe and Hg (lower) contents in soil and the amount of Taraxacum officinale these metals in roots of plants 3. High positive dependence between Cu, Hg and Fe contents in aerial parts and roots Sonchus oleraceus

The described values indicate that these elements

Pastinaca sativa are absorbed by the root system from the soil and transported to leaves. The high dependence between Pb content in soil and roots and lack of such

Daucus carota dependence between Pb content in soil and aerial parts indicate that lead is absorbed from the soil and deposited in roots. The dependences between Cd

1995Taraxacum 2008sp. 1995 2008 1995content 2008 in soil 1995 and roots 2008 as well as in 1995 soil and 2008 aerial parts are not observed, although the relationship The comparison of heavy metal content in aerial parts of different plants from the area of I between the content of this element in roots and aerial parts is highly positive which suggest mobility LeadCadmiumCopper 1 43ZincMercury 49Iron 13.39 0.73 0.06 255Cobalt 7.49 22.12Chromium 0.32 380 0.03Molybdenum 18.92 100 107 3 1.8 11.69 0.73 0.03 22.94 85 4,695 19 22 2.25 0.89 1 29,885 0.03 55 122 2.07 36 0.55 3,528 13.41 0.07 2.14 0.64 1 190 290 29.04 20 28 0.03 98 1.5 3 224 2,075 89 1 0.07 19.44 320 0.97 123.19 162 0.69 35 56 0.85 0.03 52 2.5 18,819 4 102 87 1 1.94 14.97 430 2.01 53.88 480 2.65 11.29 0.12 57 5,274 46.89 1 1.5 18 158 21 3 0.05 5,119 66 4.53 1.18 210 0.02 nd 192 nd 0.91 nd 26 88 1.61 nd nd 1.5 0.81 nd 25 nd 2 nd 65 nd nd Table 6 Heavy metal Siding Loadingof Platform cadmium. The Cleaning bay content of each heavy Control metal in the 344 Water Air Soil Pollut (2011) 218:333–345

Table 7 The correlation coefficient between heavy Pb Cd Cu Zn Hg Fe The sum of PAHs metals and PAH contents in aerial parts and roots of Soil vs AP −0.5 −0.5 0.8 −0.9 0.5 0.9 0.3 plants and soil (P<0.005) Soil vs R 0.8 −0.2 0.8 0.4 0.6 0.9 −0.1 AP vs R −0.7 0.8 0.9 −0.5 0.9 0.8 0.3 soil of all the investigated parts of the railway type (class 5°). The only exception is surface B junction exceeded the average amount of these (outside the rails) in the cleaning bay, where the level elements in Poland’s soils (Kabata-Pendias and of PAH contamination places the soil in class 4°. Pendias 1999). According to the Ministry Regulation, all the parts No relationship between the total content of PAHs of the investigated railway junction are covered by the in soil and plants was found, which indicates that polluted soil. According to the Dutch List, the soil these compounds are deposited from the atmosphere from the area of the railway siding and platform are and are not absorbed by the root system. In Poland, too heavily polluted (class 3°) and the soil from the the assessment of soil quality is carried out based on area of loading ramp and cleaning bay is polluted different classifications, i.e. National Research Institute (class 2°) (Institute of Soil Science and Plant Cultivation, ISSPC) system (sum of 13 PAHs), Ministry Regulation (sum of nine PAHs) and Dutch List (sum of ten PAHs). Table 8 4 Conclusions shows the comparison of PAHs content and soil assessment. In order to summarise the above results, it should be The Institute of Soil Science and Plant Cultivation stated that railway transport may be an important in Pulawy proposed the classification of agricultural threat to the natural environment. This concerns soil contaminated with PAHs, which is often used in especially PAH contamination. Since the PAH level Poland. According to this classification, PAH content is much higher in the area of all the functional parts of in agricultural soil below 200 μgkg−1 can be the junction than in the surrounding areas, it seems considered as “background level”, whereas the range necessary to monitor the level of contamination in all from 200 to 600 μgkg−1 is characteristic of the intensively used railway infrastructure. The unpolluted soil with slightly increased PAH content. determination of extremely high level of contamina- The sum of PAHs (600–10,000 μgkg−1) corresponds tion should be a signal for renovation including the to the contaminated soil with different levels of change of ballast bed and railway wooden ties for contamination, and the content of these compounds concrete ones. This is especially important in the exceeding 10,000 μgkg−1 corresponds to very railway siding where trains remain in one place for a heavily contaminated soils where reclamation is long time and in platform area where the train needed. movement is very intensive. The heavy metal con- The soil from all the investigated parts of the centration in the area of railway junction is also high, railway junction Iława Główna is heavily polluted although not so extreme as in the case of PAHs. The

Table 8 Standard limiting PAH content in the soil surface layer (micrograms per kilogram)

Class 1 2 3 3 4 5

ISSPC 0–200 unpolluted 200–600 unpolluted 600–1,000 slightly 1,000–5,000 5,000–10,000 up to >10,000 (13 PAHs) (natural content) (increased content) polluted polluted heavily polluted very heavily polluted Ministry of <1,000 unpolluted >1,000 polluted >40,000 Environment (9 PAHs) Dutch List <1,000 unpolluted 1,000–40,000 Heavily polluted (10 PAHs) polluted Water Air Soil Pollut (2011) 218:333–345 345 railway siding and the platform area are the places evaluation of the carcinogenic risk of chemicals to humans. highly contaminated with heavy metals. Vol. 32. Lyon: International Agency for Research on Cancer. Kabata-Pendias, A., & Pendias, H. (1999). Biogeochemistry of trace elements (in Polish). Warszawa: Wydawnictwo Acknowledgements We wish to acknowledge our indebtedness Naukowwe PWN. to the Ministry of Science and Higher Education for grant no. Lacey, R. F., & Cole, J. A. (2003). Estimating water pollution N305 076 32/2694 which made this work possible. We are also risks arising from road and railway accidents. Quarterly very grateful to Polish Rail Regional Head Office in Olsztyn for Journal of Engineering Geology and Hydrogeology, 36(2), ł ł permission to investigate the railway junction I awa G ówna and 185–192. for essential information about exploitation of particular functional Liu, H., Chen, L. P., Ai, Y. W., Yang, X., Yu, Y. H., & Zuo, Y. parts of the junction. B. (2009). Heavy metal contamination in soil alongside mountain railway in Sichuan, China. Environmental Open Access This article is distributed under the terms of the Monitoring and Assessment, 152,25–33. Creative Commons Attribution Noncommercial License which Moret, S., Purcaro, G., & Conte, L. S. (2007). Polycyclic permits any noncommercial use, distribution, and reproduction in aromatic hydrocarbon (PAH) content of soil and olives any medium, provided the original author(s) and source are credited. collected in areas contaminated with creosote released from old railway ties. The Science of the Total Environment, 386,1–8. ł References Malawska, M., & Wi komirski, B. (1999). An analysis of polychlorinated biphenyls (PCBs) content in soil and plant leaves (Taraxacum officinale) in the area of the railway Barber,J.L.,Thomas,G.O.,Kerstiens,G.,&Jones,K.C.(2004). junction. Iława Główna, 70, 509–515. Current issues and uncertainties in the measurement and Malawska, M., & Wiłkomirski, B. (2000). Soil and plant modeling of air-vegetation exchange and within-plant processing contamination with heavy metals in the area of the old of POPs. Environmental Pollution, 128,99–138. railway junction Tarnowskie Góry and near two main Brooks, K. M. (2004). Polycyclic aromatic hydrocarbon migration railway routes. Roczniki Państwowego Zakładu Higieny, from creosote-treated railway ties into ballast and adjacent 51(3), 259–268. wetlands. Research Paper FLP-RP-617. Madison: Department Malawska, M., & Wiłkomirski, B. (2001). An analysis of of Agriculture, Forest Service, Forest Products Laboratory. soil and plant (Taraxacum officinale) contamination Bukowiecki, N., Gehrig, R., Hill, M., Lienemann, B., Zwicky, with heavy metals and polycyclic aromatic hydrocar- C. N., Buchmann, B., et al. (2007). Iron, manganese and bons (PAHs) in the area of the railway junction Iława copper emitted by cargo and passenger trains in Zurich Główna, Poland. Water, Air, and Soil Pollution, 127, (Switzerland): Size-segregated mass concentrations in 339–349. ambient air. Atmospheric Environment, 41, 878–889. Thierfelder, T., & Sandström, E. (2008). The creosote content Chillrud, S. N., Grass, D., Ross, J. M., Coulibaly, D., of used railway crossties as compared with European Slavkovich, V., Epstein, D., et al. (2005). Steel dust in stipulations for hazardous waste. The Science of the Total the New York City subway system as a source of Environment, 402, 106–112. manganese, chromium and iron exposures for transit Trapp, S. (1995). Model for uptake of xenobiotics into plants. workers. Journal of Urban Health, 82,33–42. In S. Trapp & J. C. McFarlane (Eds.), Plant contamination IARC. (1983). Polynuclear aromatic compounds. Part I, chemical, modelling and simulation of organic chemical processes environmental and experimental data, monographs on the (pp. 107–151). London: Lewis.