Legacy Avian Noise Research Program - 2011 FINAL Report

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L e g a c y A v i a n N o i s e R e s e a r c h P r o g r a m

FINAL REPORT

September 2011

Prepared by:

BIO-WEST, Inc.1063 West 1400 NorthLogan, Utah 84321-2291


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ABBREVIATIONS USED IN THIS DOCUMENT

AIC Akaikes information criterion

BIO-WEST BIO-WEST, Inc.

C Celsius

cm centimeter

dB decibel

GIS geographic information system

GSLE Great Salt Lake Ecosystem

HQI habitat quality index

I-15 Interstate 15

I-80 Interstate 80

I-84 Interstate 84

I-215 Interstate 215

ISSR Inland Sea Shorebird Reserve

km kilometer

LANRP Legacy Avian Noise Research Program

LEQ integrated sound level

LNP Legacy Nature Preserve

m meter

SPL sound pressure level

UDOT Utah Department of Transportation

UDWR Utah Department of Wildlife Resources

USFWS U.S. Fish and Wildlife Service

WMA Wildlife Management Area


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BIO-WEST, Inc. Legacy Avian Noise Research ProgramSeptember 2011 Final Report

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EXECUTIVE SUMMARY

The Legacy Avian Noise Research Program is a 5-year study designed to assess the impacts of

highway noise on breeding bird communities within the Great Salt Lake ecosystem. This finalreport summarizes and provides conclusions based on 4 years of data collection (20072010).

The potential impacts of highway noise on breeding bird communities were assessed at ninestudy sites throughout the Great Salt Lake ecosystem by measuring effects of noise on (1) the

abundance, diversity, and richness of breeding bird communities, and (2) nesting success of twoabundant and widespread semicolonially nesting shorebirds, the American avocet (Recurvirostraamericana; hereafter, avocet) and the black-necked stilt (Himantopus mexicanus; hereafter, stilt).

To allow for assessment of relationships between highway noise and breeding bird communities,

noise data were collected concurrently with standardized 10-minute avian point-count surveysusing distance-sampling techniques. However, highway noise could not be completely separated

from non-highway noise for any of the nine study sites. Six of the nine study sites are located

within Salt Lake International Airport airspace corridors and are adjacent to interstate highways,

industries, and a heavily trafficked transcontinental railroad corridor. Because of theselimitations, inferences made about the effect of highway noise on both species-specific densities,

as well as both diversity and richness should be treated cautiously.

The effects of highway noise on breeding bird communities within the Great Salt Lake

ecosystem were evaluated by assessing species-specific density estimates generated from these

point-count data. There was a very weak but significant relationship between highway noise andspecies diversity or richness. Additionally, highway noise did have apparent impacts on yellow-

headed blackbird (Xanthocephalus xanthocephalus) and common yellowthroat (Geothlypis

trichas) abundance. Common yellowthroat abundance was negatively correlated with highwaynoise in both wet meadow habitat and emergent marsh habitat, which suggests that highway

noise may have real and negative impacts on common yellowthroat populations. Such impactsare presumed to be the result of masking, the direct interference of sound with effectivecommunications between organisms. Yellow-headed blackbird abundance was apparently

positively related to highway noise. This positive relationship, which seems counterintuitive,

may be explained by several factors, including yellow-headed blackbirds social structure,auditory capacity, and visual displays.

To allow for assessment of relationships between highway noise and nesting success, noise data

were also collected at 1,084 stilt, avocet, and snowy plover (Charadrius alexandrinus) nestsfollowing the breeding season. From a productivity standpoint, the impacts of noise on nesting

success are less clear. Evidence for a relationship between highway noise and nesting success for

avocets, stilts, and plovers was equivocal. There was no apparent relationship between highwaynoise and apparent nest success estimators for any multiple regression model except for avocets

and distance to nearest neighbor. Conversely, noise levels at successful nests of all three species

were higher than at failed nests. This positive relationship may be manifested if highway noisechanges predator communities by excluding species that depredate avocet and plover nests.

However, although depredation was the primary cause of nest failure for all species, a clear link

between noise and depredation was not apparent.


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Considered collectively, analyses of both point-count and nest success data collected over 4

years are inconclusive regarding the impact that highway noise may have on breeding bird

communities in the Great Salt Lake ecosystem. Inferences about highway noise on the effects ofboth avian abundance and nesting success should be treated cautiously given the aforementioned

limitations in collecting noise data.


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TABLE OF CONTENTS

INTRODUCTION .......................................................................................................................... 1Study Objectives ......................................................................................................................... 1Physical Setting ........................................................................................................................... 2

METHODS ..................................................................................................................................... 3

Experimental Study Design ........................................................................................................ 3Study Sites .................................................................................................................................. 3Highway Noise............................................................................................................................ 6Highway Distance ....................................................................................................................... 6Avian Density ............................................................................................................................. 7Avian Productivity ...................................................................................................................... 7

Determining Nest Success and Fate....................................................................................... 8

DATA ANALYSIS ......................................................................................................................... 9

Highway Noise............................................................................................................................ 9Avian Density, Species Richness, and Diversity ...................................................................... 10

Species-Specific Density Estimates ..................................................................................... 10Species Richness and Diversity ........................................................................................... 10

Avian Productivity .................................................................................................................... 11Nest Success Estimates ........................................................................................................ 11Analyses of Nesting Success ............................................................................................... 11

RESULTS ..................................................................................................................................... 12Highway Noise.......................................................................................................................... 12Avian Density, Species Richness, and Diversity ...................................................................... 20Avian Density and Highway Noise ........................................................................................... 20Avian Diversity and Richness and Highway Noise .................................................................. 20Avian Productivity .................................................................................................................... 23

Nest Success ........................................................................................................................ 23Nest Success Models ........................................................................................................... 27

DISCUSSION ............................................................................................................................... 28Highway Noise.......................................................................................................................... 28Avian Density and Highway Noise ........................................................................................... 28Avian Productivity .................................................................................................................... 29

CONCLUSIONS........................................................................................................................... 31

STUDY LIMITATIONS .............................................................................................................. 32

SUGGESTIONS FOR FUTURE STUDY.................................................................................... 33

LITERATURE CITED ................................................................................................................. 34


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LIST OF TABLES

Table 1. Minimum and maximum distances from point-count stations to the nearest stateor federal highway on Legacy Avian Noise Research Program study sites. .................. 5

Table 2. Distribution of point-count stations across habitat types and study sites on LegacyAvian Noise Research Program study sites, MayJuly 20072010. .............................. 5

Table 3. Minimum, maximum, and mean noise (dB) during point counts on Legacy Avian

Noise Research Program study sites, MayJuly 20072010. ...................................... 12

Table 4. Species detected 100-m radius during standardized 10-minute point counts

on Legacy Avian Noise Research Program study sites, MayJuly 20072010,

ranked in descending order of abundance, based on total number of detections. ........ 21

Table 5. Linear regression models of all species combined, common yellowthroat, and

yellow-headed blackbird density estimates on distance to the nearest highwayat point-count stations on Legacy Avian Noise Research Program study sites,

MayJuly 20072010. .................................................................................................. 24

Table 6. Analysis of Variance models for all species combined, common yellowthroat,and yellow-headed blackbird density estimates on distance to the nearest

highway at point-count stations on Legacy Avian Noise Research Program study

sites, MayJuly 20072010. ......................................................................................... 24

Table 7. Total number of nests found, and fates for each species, pooled across all yearsand study sites on the Legacy Avian Noise Research Program, MayJuly

20072010. ................................................................................................................... 24

Table 8. Nest totals and fates for nests found and monitored on Legacy Avian Noise

Research Program study sites, MayJuly 2007-2010. ................................................. 25

Table 9. Apparent and Mayfield nest success estimates for avocets and stilts nesting

on Legacy Avian Noise Research Program study sites, MayJuly 20072010. .......... 26

Table 10. Nest failure reason by study site, for avocet, stilt, and plover nests on the LegacyAvian Noise Research Program, MayJuly 20072010. ............................................. 27

Table 11. Multiple regression models of apparent nest success for (1) all species pooled,(2) stilts, and (3) avocets, based on data collected on Legacy Avian Noise

Research Program study sites, MayJuly 20072010. ................................................. 27


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LIST OF FIGURES

Figure 1. Study site locations on Legacy Avian Noise Research Program study sites. ................. 4Figure 2. Mean noise collected at point-count stations at Locomotive Springs Wildlife

Management Area, concurrent with avian point-count surveys, MayJuly 2010. ....... 13

Figure 3. Mean noise collected at point-count stations at Public Shooting Grounds WildlifeManagement Area and Salt Creek Wildlife Management Area, concurrent with

avian point count surveys, MayJuly 20072010. ....................................................... 14

Figure 4. Mean noise collected at point-count stations at the Box Elder Creek RestorationArea, concurrent with avian point-count surveys, MayJuly 2010. ............................ 15

Figure 5. Mean noise collected at point-count stations at the Great Salt Lake ShorelandsPreserve, concurrent with avian point-count surveys, MayJuly 20072010. ............. 16

Figure 6. Mean noise collected at point-count stations at Farmington Bay WildlifeManagement Area and Legacy Nature Preserve, concurrent with avian point-countsurveys, MayJuly 20072010. .................................................................................... 17

Figure 7. Mean noise collected at point-count stations at Inland Sea Shorebird Reserve,concurrent with avian point-count surveys, MayJuly 20072010. ............................ 18

Figure 8. Mean noise collected at point-count stations at Timpie Springs WildlifeManagement Area, concurrent with avian point-count surveys, MayJuly

20072010. ................................................................................................................... 19

Figure 9. Species-specific estimates of apparent nesting success calculated for each studysite relative to mean highway noise (dB), based on data collected on Legacy AvianNoise Research Program study sites, MayJuly 20072010. Data provided only

for nests with known fates. ........................................................................................... 26


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INTRODUCTION

Over the last several decades, the Wasatch Front has experienced tremendous population growth,

with pressure from urban development extending east to the foothills of the Wasatch Mountainsand west to the Great Salt Lake. Increased traffic along the Interstate 15 (I-15) corridor in

northern Salt Lake County and southwestern Davis County is a direct result of this populationgrowth. To reduce traffic congestion in this corridor, the Utah Department of Transportation

(UDOT) constructed the Legacy Parkway, which provides a direct connection between Interstate215 (I-215) in Salt Lake City, just west of the Redwood Road interchange, and the U.S. Highway89/I-15 interchange in Farmington.

As mitigation for impacts from construction of the Legacy Parkway, UDOT created the Legacy

Nature Preserve (LNP) to protect quality wildlife habitat in perpetuity (Jones & Stokes 2004). Asadditional mitigation required under a Settlement Agreement finalized in 2006, BIO-WEST, Inc.

(BIO-WEST), was contracted to assess the potential impacts of highway noise on breeding bird

communities in the Great Salt Lake ecosystem.

Study Objectives

It has been suggested that construction of the Legacy Parkway may have resulted in cumulativehabitat loss and fragmentation, and perhaps also impacted local wildlife populations, including

migratory birds, through the introduction of highway noise (Jones & Stokes 2004). To assess the

potential impacts of highway noise on breeding bird communities in the Great Salt Lakeecosystem, BIO-WEST designed and implemented the Legacy Avian Noise Research Program

(LANRP) with the objective of assessing the cumulative impacts of highway noise on breeding

bird communities throughout the Great Salt Lake ecosystem. The potential impacts of highwaynoise were assessed by measuring differences in avian community composition (density,

diversity, and species richness) and productivity (nesting success) relative to highway noise atstudy sites throughout the Great Salt Lake ecosystem.

Background

Anthropogenic (i.e., human-created) noise can have direct and immediate effects on birds inparticular (Slabbekoorn and Peet 2003, Brumm 2004, Wood and Yezerinac 2006, Habib et al.

2007, Parris and Schneider 2009) and wildlife in general (Miller et al. 2000, Foote et al. 2004,

Parris et al. 2009). Anthropogenic noise can interfere with communication in birds by masking,and possibly distorting, songs and calls that convey information about an individuals status

(Slabbekoorn and Peet 2003, Brumm 2004, Wood and Yezerinac 2006, Habib et al. 2007, Parris

and Schneider 2009). Masking occurs when noise of sufficient intensity within a specificfrequency region overlaps with the spectral region of a species vocalizations and hearing range

to the extent that it has a detrimental effect on that species ability to detect and discriminate

among vocal signals. Although masking can occur within all spectral regions, it has a far greatereffect when it overlaps with the specific spectral region of the species in question (Dooling and

Popper 2007). Because most birds communicate primarily within the 16 kHz spectral region


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(Dooling and Popper 2007) they are apparently susceptible to anthropogenic noise in general andhighway noise in particular, both of which tend to produce low-frequency noise.

Previous research on the impacts of noise on breeding birds also has shown that noise caninterfere with songs and vocalizations (Slabbekoorn and Peet 2003, Wood and Yezerinac 2006).

Song sparrows (Melopsiza melodia) (Wood and Yezerinac 2006) and great tits (Parus major)(Slabbekoorn and Peet 2003), both of which are common residents of urban environments,modify the low-frequency components of their song to offset the potential masking of their songs

by low-frequency urban noise such as highway noise. Masking effectively reduces the quality of

an individuals territory, and can result in negative effects such as reduced pairing success

(Habib et al. 2007), or increased energetic expenditures (Brumm 2004). Masking has also beenshown to reduce an individuals ability to detect approaching predators in both wild-caught

chaffinches (Fringilla coelebs) (Quinn et al. 2006) and free-ranging California ground-squirrels

(Spermophilus beecheyi) (Rabin et al. 2006). Both species showed elevated levels of vigilance inthe presence of anthropogenic noise, suggesting that anthropogenic noise may mask noises

produced by predators as well as vocalizations given by conspecifics to convey information

about predators (Quinn et al. 2006, Rabin et al. 2006). Recent research has shown thatanthropogenic noise can result in changes in breeding bird communities through reduction in

richness of breeding bird communities and disruption of predator-prey interactions (Francis et al.

2009).

Determining the impact of highway noise on birds has proved difficult. Breeding bird densities

can be lower along highway corridors in wooded and grassland habitats, but determining the role

of highway noise within the context of this relationship has been difficult (Ferris 1979; Foppenand Reijnen 1994; Reijnen et al. 1995a, 1995b; Reijnen and Foppen 1995). Reduced habitat

quality within the immediate proximity of roads has often been implicated as the primary factorresponsible for reduced breeding bird densities (Ferris 1979; Foppen and Reijnen 1994; Reijnen

and Foppen 1995; Reijnen et al. 1995a, 1995b). Studies that have focused on the effects of

highway noise have shown that the majority of species examined exhibited reduced breedingdensities along highway corridors (Reijnen et al. 1995a, 1995b), although reductions in density

varied depending upon the species, the distance from the highway, and traffic levels (Reijnen et

al. 1995a, 1995b). In at least one instance, noise has been shown to be the most important factorreducing habitat quality and, therefore, breeding bird density (Reijnen and Foppen 1994).

Physical Setting

The Great Salt Lake is one of the largest lakes in the United States and the fourth largest terminal

lake in the world (USGS 2007). It is a remnant of Lake Bonneville, a freshwater lake that

covered approximately 52,000 square kilometers (km

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) northwest of Salt Lake City during thePleistocene epoch (Behle 1985). The Great Salt Lake exhibits considerable annual variation inboth size and depth, depending on evaporation and precipitation. Between 1850 and the present,

the lakes surface-water elevation fluctuated >6 meters (m), and its area fluctuated between

2,512 and 5,905 km2. Temperatures around the lake range from around 38C in the summer to

-18C in the winter. On average, the eastern portion of the Great Salt Lake receives


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approximately 38 centimeters (cm) of annual precipitation, while the western edge receives 25cm of annual precipitation.

The Great Salt Lake is recognized internationally for its extensive wetlands, which are criticallyimportant to migratory birds (Aldrich and Paul 2002). It provides breeding or stopover habitat

for internationally significant concentrations of at least 12 species (Paul and Manning 2002). Thelakes large size, dynamic water levels, diversity of aquatic environments, extensive wetlands,and geographic position in avian migration corridors all contribute to its importance for both

migrants and breeders alike (Aldrich and Paul 2002).

METHODS

Experimental Study Design

The experimental study design was developed through an iterative process by a project team

comprised of representatives from the Utah Division of Wildlife Resources, U.S. Fish and

Wildlife Service (USFWS), and other independent consultants including BIO-WEST. The initialplanning phase included a literature review and identification of potential study sites. A variety

of geographic information system-based habitat data were evaluated to identify appropriate

vegetation communities to sample. Habitat data evaluated included those from the Utah GapAnalysis Program at Utah State University (USGS 2004) and USFWS National Wetlands

Inventory (USFWS 2009). Variable-radius point-counts were selected, rather than line transects,

for sampling breeding bird communities. Given the highly fragmented mosaic of vegetationcommunities (particularly those proximal to major roadways), it would be difficult to position

line-transect routes within a dominant vegetation community. Employing variable-radius point-

counts allows for development of robust density estimates of breeding bird communities.

Study Sites

Six study sites were established during 2006, a seventh study site was added in 2007, and an

eighth and ninth site were added in 2010 (Figure 1). Study sites were selected because of their

proximity to highways (Table 1) (I-15, Interstate 80 [I-80], Interstate 84 [I-84], I-215, and

Legacy Parkway) and highly managed status with relatively consistent habitat conditions (e.g.,water levels).

The proximity of many sites to existing sources of ambient noise (e.g., Salt Lake InternationalAirport, a busy transcontinental railroad corridor, and industries) made it nearly impossible to

collect only highway noise. To a lesser extent, residential areas and farming also contribute to

ambient noise. Therefore, noise data collected at most study sites are confounded to a certainextent by the presence of non-highway noise sources described above.

Point-count stations (n=200 in 2007-2009 and n=111 in 2010) served as sampling locations forcollecting both avian point-count and noise data during 2007, 2008, 2009, and 2010. To achieve

a balance between survey coverage while minimizing the likelihood of counting the sameindividual birds at adjacent stations, all point-count stations were distributed within study sites so


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Figure 1. Study site locations on Legacy Avian Noise Research Program study sites.

that each station was located 400 m from the next adjacent point-count station. To control for

potential confounding differences in breeding bird communities due to habitat type, rather than

noise, each point-count station was centered within one of the four dominant habitat types, sothat 60% of the area within a 100-m radius circle of the station is classified as one of four

habitat types. This allows for direct, robust analyses of bird data with respect to habitat and noise


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Table 1. Minimum and maximum distances from point-count stations to the nearest stateor federal highway on Legacy Avian Noise Research Program study sites.

STUDY SITE CLOSEST HIGHWAYDISTANCE (kilometers)

Minimum Maximum

Box Elder Creek Restoration Area I-15 0.86 0.95

Farmington Bay WMAa

Legacy Parkway 0.81 4.01Great Salt Lake Shorelands Preserve I-15 3.73 5.47

Inland Sea Shorebird Reserve I-80 0.05 2.13

Legacy Nature Preserve Legacy Parkway 0.11 1.76

Locomotive Springs WMA I-84 23.86 24.81

Public Shooting Grounds WMA Highway 83 0.05 4.94

Salt Creek WMA Highway 102 2.06 6.01

Timpie Springs WMA I-80 0.22 2.16aWMA = Wildlife Management Area.

data. Because neither the total number of point-count stations nor locations changed between2007 and 2009, three consecutive years of both avian point-count and noise data were collectedat the same point-count stations. Based on results from the 2007, 2008, and 2009 seasons, in

2010 point-count effort was concentrated in only two of the four habitat types. Point-count

stations located in grassland or playa habitats were not surveyed in 2010, and additional

emergent marsh and wet meadow habitat point-count stations were added (Table 2).

Table 2. Distribution of point-count stations across habitat types and study sites on LegacyAvian Noise Research Program study sites, MayJuly 20072010.

STUDY SITEEMERGENT

MARSH GRASSLAND PLAYAWET

MEADOWTOTALPOINTS

Box Elder Creek Restoration Area 1 0 0 1 2

Farmington Bay WMAa

19 0 7 10 36

Great Salt Lake Shorelands Preserve 8 4 1 3 16

Inland Sea Shorebird Reserve 2 8 20 0 30

Legacy Nature Preserve 3 27 3 6 39

Locomotive Springs WMA 4 0 0 1 5

Public Shooting Grounds WMA 10 8 10 11 39

Salt Creek WMA 16 15 3 9 43

Timpie Springs WMA 0 0 12 7 19

Total 63 62 56 48 229aWMA = Wildlife Management Area.


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Highway Noise

To assess highway noise, the sound pressure level (SPL) of passing highway traffic wasmeasured in decibels (dB). The SPL (hereafter, noise) is a measure of a sounds loudness, or its

amplitude. All noise data were collected with Quest Technologies Model 2900 Sound Level

Meters (Quest Technologies, Oconomowoc, Wisconsin; hereafter, soundmeter), using a standard10-minute sampling period in the 3090 dB range, the A-weighting system, and a 3 dB exchangerate. The soundmeter was mounted on a tripod for all sampling periods. Every effort was made to

minimize the effects of non-highway noise sources, but in some cases it was impossible to

exclude other noise sources. Soundmeters were calibrated approximately weekly.

Noise data were collected concurrently with point-count surveys, as well as at nest locations.With few exceptions, noise data were collected during each of three annual point-count surveys

(see below) at all 200 point-count stations, for a total of 600 noise data samples per year in 2007-2009, and 333 noise data samples in 2010. Noise data were not collected during rare instances of

soundmeter or battery failure. Similarly, not all noise data collected were retained. If the input

for a soundmeter is too high for the specified measurement range, the soundmeter overloads.Noise data were excluded from analyses where the overload was >5.0% of the total 10-minutesampling period. In 2007 18 of 523 noise data samples collected at point-count stations were

excluded due to overload. In 2008 only 5 of 598 noise data samples were excluded due to

overload, and in 2009 and 2010, all noise data samples collected were retained. Noise data were

also confounded to a certain extent by bird vocalizations.

Noise data were also collected at most nest locations. In 2007 noise data were collected at eachnest within a colony when nests were >15 m apart. For nests spaced


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Avian Density

Breeding bird communities were assessed at each of the study sites using standardized 10-minutepoint-count surveys (Ralph et al. 1993). Point-counts were conducted at point-count stations (see

study sites). Distance sampling methods were used to allow for calculation of population

densities (Buckland et al. 1993). Density estimates provide more robust estimates of birdpopulations than relative abundance methods (Norvell et al. 2003).

All birds seen or heard at each point-count station within the 10-minute survey period were

recorded and identified to species. The majority of birds that flew over the point-count stationand did not stop were recorded as fly-overs. These were not considered to be using the habitat,

and were excluded from all analyses. However, species observed to forage by either flying low

(e.g., short-eared owl [Asio flammeus], northern harrier [Circus cyaneus], barn swallow [Hirundo

rustica]) or hovering over the ground (e.g., American kestrel [Falco sparverius]) were

considered to be using the habitat and were retained in the analyses. Point-count surveys began

within 30 minutes of local sunrise, were completed within 5 hours of local sunrise, and were not

conducted during inclement weather (e.g., heavy rain, high winds). Each point-count station wassurveyed three times each year. Point-count surveys were conducted between May 1August 2,

2007; May 2July 28, 2008; May 4July 28, 2009; and May 3July 30, 2010. The majority of

individuals detected were assumed to be representative of the breeding bird community, unlessspecies-specific life histories and the primary literature suggested otherwise. Surveys were

staggered; generally 23 weeks occurred between visits.

Avian Productivity

Monitoring nest success and productivity provides a more direct measure of population health(Martin and Geupel 1993, Ralph et al. 1993) than density (Van Horne 1983, Vickery et al. 1992)

and, therefore, serves as a robust means to assess whether environmental conditions, such ashighway noise, are influencing reproduction. To assess whether highway noise affecteddemographics, BIO-WEST searched for and monitored nests of two target species, black-necked

stilt (Himantopus mexicanus; hereafter, stilt) and American avocet (Recurvirostra americana;

hereafter, avocet) during all four years. Although assessing nest success and productivity canprovide a direct assessment of a populations demographics (and information on whether

environmental conditions, such as noise, are influencing reproduction), collection of nest-

monitoring data is very time- and labor-intensive. Stiltsand avocets were selected because they

were both relatively abundant and their nests were easy to find at most LANRP study sites.

In 2008 snowy plover (Charadrius alexandrinus; hereafter, plover) was added as a third target

species. In 2007 BIO-WEST searched for and monitored nests at six of the seven study sites.Nest-searching and monitoring did not occur at Kennecott Utah Coppers Inland Sea Shorebird

Reserve (ISSR) in 2007 because another researcher was monitoring nests at that study site and

data were not available for this report. In 2008 and 2009, BIO-WEST was granted permission tosearch for and monitor nests at ISSR, and all seven study sites were included in the productivity

study during 2008 and 2009. In 2010, avocet and stilt nests were monitored only at Salt Creek


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Wildlife Management Area (WMA) and LNP due to budget constraints. Nests were notmonitored at Box Elder Creek Restoration Area or at Locomotive Springs WMA.

Nests were located through the use of behavioral cues that indicated the presence of an activenest (Martin and Geupel 1993, Ralph et al. 1993) as well as through systematic searches of areas

where observations suggested the presence of a nest. Nests found incidentally (i.e., those locatedby flushing incubating birds or discovered in the absence of adults) were also included. Nestswere checked on a regular basis (every 35 days) until they either hatched/fledged young, failed,

or were abandoned. To allow for accurate determination of the number of nestlings for

productivity calculations, visual inspections of nest contents (i.e., number of eggs and nestlings)

(Mayfield 1961, 1975; Hensler and Nichols 1981; Martin and Geupel 1993; Ralph et al. 1993)were made. In many instances nests were concealed by vegetation and were too close to adjacent

nests of the same species for accurate monitoring from a distance. Nest checks were as brief and

unobtrusive as possible, and they were not knowingly conducted in the presence of potential nestpredators. When necessary, nest checks were made later, after potential predators left the

vicinity. With few exceptions, all nests were monitored to their final outcome. The number of

successfully fledged young was assumed to be equal to the last known clutch size, unlessevidence (e.g., evidence of partial predation, unhatched eggs) indicated otherwise.

Determining Nest Success and Fate

Avocets and stilts are precocial, which means that their young can feed and care for themselveswithin 12 hours of hatching (Robinson et al. 1997, 1999). Because these chicks often vacate the

nest within hours of hatching (Robinson et al. 1997, 1999), nest fate could not be determined

based solely on the presence or absence of chicks. Rather, determinations of nest fate were basedon a combination of egg-floating techniques, which provides information about nest age

(Alberico 1995, Mabee et al. 2006, Liebezeit et al. 2007), and the presence or absence of pip

fragments, which provides information about nest fate (Mabee 1997, Mabee et al. 2006). Pipfragments are 15 millimeter (mm) egg fragments produced when a hatching chick pips its

way out of an egg; hence, they are characteristic of a successful hatching event (Mabee 1997).

Egg floating was used to estimate the expected hatching date, which is critical for determining

nest age, and, when combined with the presence or absence of pip fragments, the fate of nests(Alberico 1995, Mabee et al. 2006, Liebezeit et al. 2007). Combining estimated hatch dates with

pip fragment presence provides a robust indication of nest fate.

Eggs were floated upon a nests initial discovery (Mabee et al. 2006, Liebezeit et al. 2007).

Previous research has shown that floating eggs does not affect egg hatchability (Alberico 1995).Half of the eggs in each clutch were floated in lukewarm water in a clear, wide-mouthed plastic

container. Using a protractor, float angle (degrees) was measured for each egg floated, the

location of the egg within the water column was noted, and the length of egg surface breakingthe surface of the water was measured (mm). These data allowed classification of nest age based

on species-specific float categories (Liebezeit et al. 2007) and thus prediction of a hatching date.

For nests with estimated hatch dates, a nest was considered to be successful if pip fragments(Mabee 1997, Mabee et al. 2006) were found in the nest near (13 days) the estimated hatch


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date. Nests were also considered successful if a fledgling was observed in or near the nest within2448 hours of hatching.

For nests with unknown hatch dates, the presence of pip fragments and eggshell membrane thatwas separated or peeling from pip fragments also indicated a successful nest. A nest was

classified as unknown if the nest was empty, there were no pip fragments, and the hatch date wasunknown. A nest was classified as failed if the nest contents (eggs or chicks) disappeared wellbefore the expected hatch date, with neither pip fragments nor adults present. Nests were also

classified as failed if nest contents were present well beyond the expected hatch date (based on

egg floating) and no adults were present.

Nests known to have failed were further classified as (1) depredated, (2) abandoned, or (3)

unknown. Depredated nests had signs of depredation including yolk, eggs opened at the end or

side only, predator scat, and/or dead chicks and/or adults. A nest was also classified asdepredated if eggs disappeared well prior to estimated hatch date. Abandoned nests had eggs for

more than 30 days that were not attended by adults and showed no sign of depredation or

hatching (e.g., no starring, not hot to touch). Nests that failed for unknown reasons wereclassified as unknown.

DATA ANALYSIS

Highway Noise

Quest Suite Professional, the data application software associated with the soundmeter,

calculated mean noise for each 10-minute recording period. Mean noise was averaged across the

three point-count surveys conducted at each of the point-count stations. Because it was notalways possible to collect noise data in the absence of other noise sources, such as trains and

airplanes, averaging noise provides a more representative measure of highway noise.

Distance to the nearest state or federal highway was used in lieu of highway noise in some of the

analyses. Although it is impossible to separate highway noise from other types of noise, it can

reasonably be assumed that highway noise will increase with decreasing distance to the highway.A point-count station close to the highway will be noisy from highway noise, and a point far

from the highway may or may not be noisy but only a small fraction of the noise present is likely

to be from the highway itself. Therefore, distance to the nearest highway is a reasonablesubstitute for actual noise levels.

The relationship between the distance to the nearest highway and the 4-year mean noise level for

each point-count station was analyzed with linear regression.


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Avian Density, Species Richness, and Diversity

Species-Specific Densi ty Estimates

Species-specific density estimates were generated for each point-count station across all three

visits (point-count surveys) within a year, using the program DISTANCE 5.0 (Thomas et al.2005). Density estimates were generated for the 10 most abundant species detected visually

within a 100-m radius of the point-count station center. Only visual detections were used toeliminate highway or other noise confounding auditory detections of birds (if ambient noise is

too loud to hear avian vocalizations, some birds present may not be counted).

Linear regression was used to assess the potential effects of highway noise (using distance to

nearest highway in place of noise) on the 10 most abundant bird species using data from 2007

2010. The potential effects of highway noise were assessed for all 10 species combined, and for

common yellowthroat (Geothlypis trichas) and yellow-headed blackbird (Xanthocephalus

xanthocephalus) individually.

Analysis of variance (ANOVA) was also used to assess the potential effects of highway noise onthe 10 most abundant species combined, as well as for common yellowthroat and yellow-headed

blackbird separately. Distance to the nearest highway was used instead of mean noise level.

Distances were split into three categories: close (less than 1,000 m from the nearest highway),medium (1,0013,000 m), and far (more than 3,001 m from the nearest highway).

Species Richness and Diversity

Both species richness and diversity were calculated for each point-count station across all threevisits for a given year, and all 4 years of data were analyzed collectively. Both measures are

relative but can be informative when assessing population diversity. Species richness wascalculated as the total number of species detected at each point across all visits. Species diversity(H) was calculated using the Shannon-Weaver Index (Shannon and Weaver 1949), which

weights each species contribution to the overall diversity index by its relative abundance, so that

species with greater relative abundance have greater weight than species with lower relativeabundance.

The potential effects of highway noise on breeding bird communities were further examined by

assessing the relationship, if any, between both species diversity and species richness, for eachpoint. Linear regression was used to model the relationship between species diversity and

distance to the nearest highway (used as a substitute for highway noise), and species richness and

distance to nearest highway.


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Avian Productivity

Nest Success Estimates

Nest success was assessed at a species-specific level for each study site by calculating nest

success using the apparent estimator (Johnson and Shaffer 1990). The apparent estimator isappropriate for colonial island-nesting species (such as the avocet and stilt) with highly

synchronized nesting attempts on small islands and highly visible nests that have high rates ofnest detectability (Johnson and Shaffer 1990). Apparent nest success is equivalent to the total

number of successful nests divided by the total number of nests of known fate (Johnson and

Shaffer 1990).

Although Mayfield (1961, 1975) estimates are the most common and widely accepted analytical

tool used to assess nest success, they assume a constant mortality rate. Examination of nesting

data revealed non-constant daily mortality rates (3 nests per site failed between visits) for all 4years. However, because true estimates of nesting success likely fall somewhere in between

estimates derived from either the apparent estimator or Mayfield estimates (Sordahl 1996),Mayfield estimates were also calculated for comparison.

Apparent nest success was calculated only for those nests with known fates, while Mayfield

estimates of nest success were calculated for all nests. The number of nests used to calculate thetwo different nest-success estimators differs because Mayfield estimates include nests with

unknown fates, while apparent estimators can be calculated only from nests with known fates.

Because apparent nesting success was significantly correlated with mean number of fledglings,mean number of fledglings were not used to assess any measure of nest success.

Analyses of Nesting Success

The potential effects of highway noise on nest success were assessed using a two-step process.

First, to assess the effects of noise on nest success, species-specific estimates of nest success and

productivity were modeled against noise, distance to highway, and distance to nearest neighbor,using linear regression.

Prior to constructing multiple regression models of apparent nest success, variables were

screened for multicollinearity. For multiple regression models of apparent nest success,multicollinearity was not evident, so all variables were retained. Apparent nest success was

therefore modeled on noise, distance to the nearest paved highway, and distance to nearest

neighbor (log base-10 transformed to meet linear regression assumptions of normality). Nearestneighbor was selected as a variable for modeling nest success because stilts and avocets are

semicolonial, and a nests location within a colony, considered along with the defensive behavior

exhibited by a conspecific, may influence a nests success.

To further assess the potential role of noise on nesting success, differences in mean noise

between failed and successful nests were tested for all species pooled, as well as for avocets,


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stilts, and plovers individually. The Mann-Whitney U-test was used because of the unequalvariances and non-normality of the noise data.

RESULTS

Highway Noise

There was a wide range in variation between noise data collected at point-count stations both

within and across study sites (Table 3). For the 2010 data alone, maximum noise data ranged

from 49.3 dB at Locomotive Springs WMA to 66.9 dB at the ISSR. Minimum noise data showedsimilar variation, ranging from 27.2 dB at Locomotive Springs WMA to 46.0 dB at the Box

Elder Creek Restoration Area. The most isolated site, Locomotive Springs WMA, located on the

northwest side of the Great Salt Lake, had the lowest mean noise. This site is more than 20 miles

from the nearest highway (I-84), and is also isolated from most other sources of anthropogenicnoise such as agriculture and residential development. Two other relatively isolated sites, Public

Shooting Grounds and Salt Creek WMA, also had low minimum and mean noise levels.

Table 3. Minimum, maximum, and mean noise (dB) during point counts on Legacy AvianNoise Research Program study sites, MayJuly 20072010.

STUDY SITEHIGHWAY NOISE

n Minimum Noise Maximum Noise Mean Noise

All study sites pooled 2038 27.2 66.9 46.199 0.151

Box Elder Creek Restoration Area 6 46.0 51.7 48.750 0.843

Farmington Bay WMAa

346 32.0 61.2 46.366 0.243

Great Salt Lake Shorelands Preserve 175 28.0 62.7 45.712 0.360

Inland Sea Shorebird Reserve 249 39.7 66.9 53.4850.379

Legacy Nature Preserve 378 36.1 62.8 48.859 0.275

Locomotive Springs WMA 14 27.2 49.3 38.100 1.715

Public Shooting Grounds WMA 342 29.6 63.0 42.930 0.378

Salt Creek WMA 359 30.8 64.4 41.709 0.317

Timpie Springs WMA 169 32.6 62.0 46.415 0.479aWMA = Wildlife Management Area.

Mean noise averaged across all visits and years for each point-count station was not necessarily

related to the distance between the point-count station and the nearest paved road (Figures 2, 3,

4, 5, 6, 7 and 8). Locomotive Springs WMA (Figure 2), Public Shooting Grounds WMA (Figure3), Box Elder Creek Restoration Area (Figure 4), Farmington Bay WMA (Figure 6), ISSR

(Figure 7), and Timpie Springs WMA (Figure 8) showed a relatively clear relationship betweennoise and distance between the point-count station and the nearest state or federal highway,

while the relationship between noise and distance for Salt Creek WMA (Figure 3), the Great Salt

Lake Shorelands Preserve (Figure 5) and LNP (Figure 6) were not clearly defined.


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Figure 2. Mean noise collected at point-count stations at Locomotive Springs Wildlife

Management Area, concurrent wi th avian point-count surveys, MayJuly 2010.


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Figure 3. Mean noise collected at point -count stations at Public Shooting Grounds Wildlife

Management Area and Salt Creek Wildlife Management Area, concurrent with avianpoint count surveys, MayJuly 20072010.


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Figure4.

Meannoisecollectedatpoin

t-countstationsattheBoxElderCreekRestorationArea,concurrent

withavianpoint-countsurveys,

MayJuly2010.


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Figure 5. Mean noise collected at point -count stations at the Great Salt Lake Shorelands

Preserve, concur rent w ith avian point-count surveys, MayJuly 20072010.


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Figure 6. Mean noise collected at point-count stations at Farmington Bay Wildlife

Management Area and Legacy Nature Preserve, concurrent w ith avian poin t-countsurveys, MayJuly 20072010.


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Figure7.


t-countstationsatInlandSeaSh

orebirdReserve,concurrentwit

havian

point-countsurveys,

MayJu

ly20072010.


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Figure8.


t-countstationsatTimpieSpringsWildlifeManagementArea,co

ncurrent

withavianpoint-countsurve

ys,

MayJuly20072010.


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Using data from 2007-2010, the relationship between distance to the nearest highway and meannoise level was significant, with mean noise level highest close to the highway and lower farther

from the highway.

Avian Density, Species Richness, and Diversity

A total of 19,284 individuals of 94 species were detected (Table 4) across all point-countstations, study sites and years, within a 100-m radius of the point-count station center. A total of

3,750 individuals of 74 species were detected across all study sites in 2007. In 2008 a total of

4,485 individuals of 68 species were detected across all study sites; in 2009 a total of 5,525individuals of 75 species were detected across all study sites; and in 2010 a total of 5,524

individuals of 78 species were detected across all study sites. A combined density estimate was

calculated for 10 of the most abundant species: red-winged blackbird (Agelaius phoeniceus),avocet, marsh wren (Cistothorus palustris), yellow-headed blackbird, stilt, common

yellowthroat, savannah sparrow (Passerculus sandwichensis), white-faced ibis (Plegadis chihi),song sparrow (Melospiza melodia), and sora (Porzana carolina). American coot (Fulica

americana) were not abundant enough to be in the top 10 species until 2010, so the species wasnot included in the analyses for the sake of consistency across years; and the vast majority of

long-billed dowitchers (Limnodromus scolopaceus) were counted on only a couple of occasions

at LNP so density estimates for this species were not calculated.

Avian Density and Highway Noise

Based on the linear regression analysis, for all 10 species combined across all 4 years of data

collection, there was no significant relationship between bird density and the distance to the

nearest highway (Table 5). From the ANOVA analysis, there was also no significant differencein combined bird density close to, a medium distance from, or far from the nearest highway

(Table 6).

The linear regressions modeling the relationship between the distance to the nearest highway and

the density of common yellowthroats and yellow-headed blackbirds (individually) were both

significant but extremely weak (the coefficient for the model terms was 0 in both cases and notrend was clear) (Table 5). The ANOVA analysis for common yellowthroats showed a

significant difference in density among the three distance to highway categories (close, medium,

far), with higher yellowthroat density farther from the highway (Table 6). The ANOVA analysis

for yellow-headed blackbirds did not show a significant difference between bird densities in thethree distance categories (Table 6).

Avian Diversity and Richness and Highway Noise

The regression describing the relationship between species diversity and highway noise was

significant (n=675, squared multiple r=0.041,p=0.000), as was the relationship between speciesrichness and noise (n=675, squared multiple r=0.053,p=0.000).


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Table 4. Species detected 100-m radius during standardized 10-minute point counts onLegacy Avian Noise Research Program study sites, MayJuly 20072010, ranked indescending order of abundance, based on total number of detections .

SPECIES

TOTALNUMBER

DETECTEDALL 4

YEARS

YEARLY TOTALS(ALL STUDY SITES)

STUDY SITE TOTALS (ALL YEARS)

2007 2008 2009 2010 BCa, b

FBc

GSLd

ISSRe

LNPf

LSg, b

PSGh

SCi

TSj

marsh wren 2770 442 509 737 1082 1 1077 333 119 138 208 394 500 0

red-winged blackbird 2086 316 685 564 521 7 430 166 89 286 123 391 515 79

American avocet 1660 572 426 515 147 0 203 95 593 99 22 315 124 209

long-billed dowitcher 1571 2 7 665 897 0 15 3 897 650 0 1 1 4

yellow-headed blackbird 1505 217 489 385 414 0 649 91 242 238 34 133 99 19

black-necked stilt 1183 223 277 463 220 0 251 41 162 143 52 272 157 105

common yellowthroat 970 176 154 215 425 2 116 45 8 52 118 395 234 0

savannah sparrow 914 159 210 293 252 2 81 73 9 160 91 142 49 307

white-faced ibis 605 174 144 150 137 0 231 26 57 80 45 102 59 5

song sparrow 520 155 82 94 189 11 267 77 35 45 3 16 66 0

American coot 354 9 38 126 181 0 31 1 149 98 2 32 41 0

sora 337 82 93 47 115 0 167 23 6 20 16 35 70 0

California gull 308 1 296 1 10 0 0 0 137 9 1 0 0 161

barn swallow 304 114 42 91 57 15 129 22 22 44 2 21 40 9

brown-headed cowbird 262 40 69 56 97 3 87 18 5 52 6 43 38 10

western meadowlark 260 78 84 86 12 0 4 25 9 117 7 27 64 7

cliff swallow 253 56 82 84 31 0 22 8 33 55 4 96 24 11

tree swallow 245 3 0 46 196 0 222 1 15 5 0 0 0 2

Wilsons phalarope 236 23 96 67 50 0 12 12 11 21 13 68 52 47

killdeer 228 41 57 87 43 0 26 10 53 51 1 41 42 4

Canada goose 212 113 20 64 15 0 55 3 42 89 0 1 15 7

European starling 178 123 49 3 3 3 0 125 0 46 0 4 0 0

Virginia rail 178 58 30 25 65 0 53 29 6 19 17 18 35 1

cinnamon teal 165 26 42 44 53 3 21 9 13 21 25 56 12 5

horned lark 164 34 52 75 3 0 0 0 41 86 0 16 16 5

Franklins gull 141 11 2 9 119 0 12 0 6 0 119 4 0 0

mallard 133 44 25 28 36 0 9 24 27 9 19 24 16 5

bank swallow 122 76 18 21 7 0 16 7 47 36 0 15 0 1

Brewers sparrow 119 21 48 50 0 0 0 0 21 55 0 29 8 6

greater yellowlegs 106 1 0 105 0 0 100 2 0 0 0 1 3 0

sandhill crane 106 47 44 13 2 0 3 5 0 1 2 24 71 0

western kingbird 106 31 38 33 4 3 1 6 3 65 0 17 11 0

snowy plover 105 43 21 41 0 0 0 0 63 0 0 21 0 21

willet 97 18 28 28 23 0 3 4 25 17 7 14 2 25

grasshopper sparrow 95 12 44 37 2 0 0 1 0 12 0 9 73 0

Forsters tern 74 1 34 19 20 0 9 2 11 7 5 13 26 1


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Table 4. (Cont.)

SPECIES

TOTALNUMBER

DETECTEDALL 4

YEARS

YEARLY TOTALS(ALL STUDY SITES)

STUDY SITE TOTALS (ALL YEARS)

2007 2008 2009 2010 B Ca, b

FBc

GSLd

ISSRe

LNPf

LSg, b

PSGh

SCi

TSj

gadwall 64 14 23 19 8 0 11 0 5 15 0 16 16 1

long-billed curlew 45 9 19 16 1 0 10 0 22 1 0 3 5 4

Brewers blackbird 36 11 11 5 9 0 8 6 0 6 0 7 3 6

cattle egret 35 30 1 1 3 0 0 0 3 32 0 0 0 0

ring-necked pheasant 26 14 9 1 2 0 6 4 0 2 0 1 13 0

bobolink 25 20 2 1 2 0 0 23 0 0 0 0 2 0

northern rough-winged swallow 25 22 1 2 0 0 1 4 0 20 0 0 0 0

sage thrasher 19 7 4 8 0 0 0 0 4 0 0 15 0 0

eastern kingbird 18 4 6 7 1 0 4 3 1 10 0 0 0 0

eared grebe 17 0 2 0 15 0 0 2 15 0 0 0 0 0

northern shoveler 17 6 5 5 1 0 1 0 0 0 1 6 9 0

pied-billed grebe 17 3 9 1 4 0 4 1 2 3 0 0 6 1

snowy egret 17 4 4 6 3 0 0 0 0 7 2 5 3 0

violet-green swallow 16 0 0 16 0 0 0 0 0 16 0 0 0 0

northern harrier 15 9 2 1 3 0 1 1 1 1 3 3 4 1

red-tailed hawk 15 2 4 7 2 0 0 0 2 7 0 6 0 0

American robin 14 3 3 5 3 2 0 7 1 3 0 0 1 0

loggerhead shrike 14 1 2 11 0 0 0 0 11 1 0 2 0 0

mourning dove 13 2 10 1 0 0 0 2 0 10 0 0 1 0

great blue heron 11 4 1 3 3 0 1 1 1 5 1 1 1 0

green-winged teal 11 0 3 4 4 0 0 4 2 4 1 0 0 0

Wilsons snipe 11 2 4 3 2 0 2 3 0 0 0 2 4 0American kestrel 10 5 4 1 0 0 1 0 0 9 0 0 0 0

black-billed magpie 9 1 1 6 1 0 1 0 0 0 0 0 8 0

lesser yellowlegs 8 3 0 2 3 0 0 0 3 2 0 2 1 0

northern pintail 8 1 0 3 4 0 1 2 4 0 0 1 0 0

Clarks grebe 7 4 0 1 2 0 0 0 0 0 1 6 0 0

common raven 7 1 6 0 0 0 0 0 2 5 0 0 0 0

house finch 6 3 0 0 3 3 0 0 0 3 0 0 0 0

western grebe 6 2 1 2 1 0 2 0 0 0 0 3 1 0

blue-winged teal 5 0 0 3 2 0 0 0 2 3 0 0 0 0

short-eared owl 5 2 0 1 2 0 0 0 0 0 1 2 2 0

spotted sandpiper 5 0 2 1 2 1 2 0 0 1 0 1 0 0

American white pelican 4 3 0 1 0 0 0 0 0 1 0 3 0 0

black-crowned night-heron 4 0 1 1 2 0 1 1 0 0 1 0 0 1

redhead 4 0 0 3 1 0 1 0 0 2 1 0 0 0

vesper sparrow 4 2 2 0 0 0 0 0 0 2 0 0 2 0


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failed, 183 (26.4%) were successful, and 158 (22.8%) were classified as unknown (Table 7). Of375 stilt nests, 214 (57.1%) failed, 95 (25.3%) were successful, and 66 nests (17.6%) were

classified as unknown (Table 7). Of 17 snowy plover nests, 5 (29.4%) failed, 9 (52.9%) were

successful, and 3 (17.6%) were classified as unknown (Table 7).

Table 5. Linear regression models of all species combined, common yellowthroat,and yellow-headed blackbird density estimates on distance to the nearest highwayat point-count stations on Legacy Avian Noise Research Program study sites,MayJuly 20072010.

SPECIES nADJUSTEDSQUARED

MULTIPLE rp

COEFFICIENTESTIMATE

all species combined 81 0 0.563 0

common yellowthroat 81 0.147 0 0

yellow-headed blackbird 81 0.061 0.015 0

Table 6. Analysis of Variance models for all species combined, common yellowthroat,and yellow-headed blackbird density estimates on distance to the nearest highwayat point-count stations on Legacy Avian Noise Research Program study sites,MayJuly 20072010.

SPECIES nSQUARED

MULTIPLE rp

all species combined 81 0.009 0.702

common yellowthroat 81 0.156 0.001

yellow-headed blackbird 81 0.061 0.085

Table 7. Total number of nests found, and fates for each species, pooled across all yearsand study si tes on the Legacy Avian Noise Research Program, MayJuly 20072010.

SPECIES FAILED SUCCESSFUL UNKNOWN TOTAL

American avocet 351 (50.7%) 183 (26.4%) 158 (22.8%) 692

black-necked stilt 214 (57.1%) 95 (25.3%) 66 (17.6%) 375

snowy plover 5 (29.4%) 9 (52.9%) 3 (17.6%) 17

Total 570 (52.6%) 287 (26.5%) 227 (20.9%) 1084

Although a slight majority of all nests failed (52.6%), nest fate ranged widely by site for allspecies (Table 8). Zero percent (0.0%) of plover nests succeeded at Farmington Bay WMA while

100.0% of plover nests succeeded at Timpie Springs WMA, LNP and Public Shooting Grounds

WMA. Avocet nesting success ranged from 10.5% at Farmington Bay WMA to 46.3% at ISSR(Table 8). Stilt nesting success ranged from 5.6% at Farmington Bay to 41.7% at Timpie


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Table 9. Apparent and Mayfield nest success estimates for avocets and stilt s nesting onLegacy Avian Noise Research Program study sites, MayJuly 20072010.

STUDY SITE SPECIES

APPARENT ESTIMATESMAYFIELD

ESTIMATES

SuccessfulNests

TotalNests

ApparentNest

Success

Numberof

Nests

MayfieldNest

Success

Farmington Bay WMAavocet 8 67 11.9% 76 1.6%

stilt 3 48 6.3% 45 2.9%

Great Salt Lake ShorelandsPreserve

avocet 11 31 35.5% 57 27.0%

stilt 6 12 50.0% 21 39.4%

Inland Sea Shorebird Reserveavocet 19 35 54.3% 39 35.5%

stilt 4 13 30.8% 15 24.3%

Legacy Nature Preserveavocet 20 60 33.3% 76 16.0%

stilt 66 128 51.6% 170 39.1%

Public Shooting Grounds WMAavocet 14 97 14.4% 117 13.4%

stilt 7 25 28.0% 32 10.9%

Salt Creek WMAavocet 28 98 28.6% 118 18.4%

stilt 27 72 37.5% 87 22.3%

Timpie Springs WMAavocet 45 114 39.5% 156 37.6%

stilt 20 41 48.8% 48 41.4%

Figure 9. Species-specific estimates of apparent nesting success calculated for each studysite relative to mean highway no ise (dB), based on data collected on Legacy AvianNoise Research Program study sites, MayJuly 20072010. Data provided onlyfor nests with known fates.


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Table 10. Nest failure reason by study site, for avocet, stilt, and plover nests on the LegacyAvian Noise Research Program, MayJuly 20072010.

STUDYSITE SPECIES DEPREDATED ABANDONED UNKNOWN TOTALFarmingtonBayWMAa

avocet 53(89.8%) 3(5.1%) 3(5.1%) 59stilt 38(84.4%) 1(2.2%) 6(13.3%) 45

plover 1(100.0%) 0(0.0%) 0(0.0%) 1GreatSaltLakeShorelandsPreserve avocet 18(90.0%) 0(0.0%) 2(10.0%) 20

stilt 6(100.0%) 0(0.0%) 0(0.0%) 6InlandSeaShorebirdReserve

avocet 11(61.1%) 1(5.56%) 6(33.3%) 18stilt 5(55.6%) 0(0.0%) 4(44.4%) 9

plover 2(50.0%) 0(0.0%) 2(50.0%) 4LegacyNaturePreserve avocet 19(47.5%) 1(2.5%) 20(50.0%) 40

stilt 60(85.7%) 1(1.4%) 9(12.9%) 70PublicShootingGrounds avocet 71(85.5%) 3(3.6%) 9(10.8%) 83

stilt 17(94.4%) 0(0.0%) 1(56.6%) 18SaltCreekWMA avocet 35(56.5%) 6(9.7%) 21(33.8%) 62

stilt 34(75.5%) 4(8.9%) 7(15.6%) 45TimpieSpringsWMA avocet 37(53.6%) 11(15.9%) 21(30.4%) 69

stilt 11(52.4%) 2(9.5%) 8(38.1%) 21Total Allspecies 418(73.3%) 33(5.8%) 119(20.9%) 570

aWMA = Wildlife Management Area.

Nest Success Models

Species-specific multiple regression models of apparent nest success did not reveal anysignificant relationship between apparent nest success rates and either noise, distance to

highway, or distance to nearest neighbor for (1) avocets, stilts, and plovers considered

collectively (adjusted multiple r=0.073,p=0.112); or (2) stilts (adjusted multiple r=0.028,

p=0.349). However, the multiple regression model for avocets was significant (adjusted multiple

r=0.360,p=0.014), revealing a significant relationship between apparent nest success and

distance to nearest neighbor (Table 11).

Table 11. Multiple regression models of apparent nest success for (1) all species pooled, (2)stilts , and (3) avocets, based on data collected on Legacy Avian Noise ResearchProgram study si tes, MayJuly 20072010.

SPECIES ADJUSTED SQUARED MULTIPLE r p

all species combined 0.073 0.112

stilts 0.028 0.349

avocets 0.36 0.014


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Mean noise (dB) was significantly greater at successful nests for all species pooled(Mann-Whitney U-test,p=0.018), as well as for avocets (p=0.006). There were no differences in mean

noise at successful versus failed nests for either stilts (p= 0.745) or plovers (p=0.440).

DISCUSSION

Highway Noise

The significant correlation between all 4 years of noise data collected at point-count stations and

the distance to the nearest highway suggest that these noise data were at least somewhatrepresentative of highway noise at most study sites. However, despite the relationship between

noise and distance to highway, highway noise could not be completely separated from non-

highway noise for any of the nine study sites. Six of the nine study sites are located within the

Salt Lake International Airport airspace corridors and are adjacent to interstate highways,industries, and a heavily trafficked transcontinental railroad corridor. For example, much of the

LNP point-count stations were located directly under the takeoff and landing approaches for the

airport, and the Great Salt Lake Shorelands Preserve experiences daily military air traffic fromHill Air Force Base. Additionally, some of the sites, such as Locomotive Springs WMA and

Great Salt Lake Shorelands Preserve are not directly adjacent to a state or federal highway.

Because of these limitations, distance to highway was used as the independent variable in severalof the analyses, with the assumption that while noise level at a point-count station may or may

not be due to highway noise level, the effects of highway noise in particular on bird density

would be stronger closer to the highway and less strong farther away from the highway.However, inferences made about the effect of distance to nearest highway and highway noise on

both combined and species-specific densities, as well as both diversity and richness should be

treated cautiously.

Avian Density and Highway Noise

The lack of a significant relationship between distance to highway and bird density (using the

combined 10 species) suggests that birds are able to inhabit areas close to highway corridors.

Whether this means that birds are not negatively impacted by highway noise is not necessarily

clear.

The negative relationship between common yellowthroat density and distance to highway

suggests that highway noise may interfere with this species communication by masking itsability to effectively transmit and receive songs and calls. Common yellowthroat songs likely

serve a variety of important roles, including mate attraction and territory defense, and may also

provide information about potential predators. In particular, low-volume songs (36.3 kHz),which may stimulate females to solicit copulation or provide information about predators (Guzy

and Ritchison 1999), may be particularly susceptible to the impacts of highway noise.

Yellowthroats may rely more on effective transmission of song than other species considered inthis study, and therefore may have been adversely impacted by increased noise associated with

construction of the adjacent Legacy Parkway. However, because the yellowthroat was notselected as a target species for nest searching efforts, accompanying productivity data are not


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available to further define this relationship. Song sparrows can modify their songs to offset thepotential masking effects by low-frequency urban noise such as highway noise that can interfere

with songs and vocalizations (Slabbekoorn and Peet 2003, Wood and Yezerinac 2006). Perhaps

yellowthroats are not able to readily modify their songs in response to masking.

The positive relationship between distance to highway and yellow-headed blackbird densityseems counterintuitive, but may be explained by several things. First of all, there is considerablevariation in both hearing ability and susceptibility to hearing damage among bird species. Few

species auditory abilities have been thoroughly studied, and there is currently no way to predict

those abilities from behavior, vocalizations or physical appearance (Dooling and Popper 2007). It

may be the case that yellow-headed blackbirds simply do not hear traffic noise as well ascommon yellowthroats. Second, yellow-headed blackbirds are very social birds and are often

found in large groups. Since birds are usually close together, vocal signals from the sender do not

usually have to travel far to reach the receiver, which could allow them to communicate moreeasily in noisy environments. Third, yellow-headed blackbirds are conspicuously colored and use

visual displays in combination with vocalizations to communicate with conspecifics. These

visual displays could also allow for easier communication near noisy roadways. Fourth, manymales, particularly second-year males do not establish breeding territories and are considered

floaters (Twedt and Crawford 1995). These birds may be forced to occupy lower-quality habitat,

such as areas adjacent to roadways, which could inflate count data from these areas without

giving an accurate reflection of the breeding segment of the population. Fifth, yellow-headedblackbirds, along with most other icterids, are fairly tolerant of human disturbance and are good

at adapting to human-altered environments. They may simply be less bothered by highway

disturbance.

Semicolonial species such as the white-faced ibis, avocet, and stilt neither sing nor defend largeterritories. These species nest close to other birds and defend only small territories around either

their nest site or perhaps around their immediate vicinity. They also use relatively open habitat

and a combination of visual and aural cues to communicate with conspecifics (Ryder and Manry1994; Robinson et al. 1997, 1999), rather than relying primarily on songs. For these species,

then, highway noise is not likely to mask or interfere with communication between individuals.

In contrast, songbirds such as marsh wrens, song sparrows, and savannah sparrows use songsand, to a lesser extent, visual displays, to both define their territories and attract mates (Twedt

and Crawford 1995, Kroodsma and Verner 1997, Guzy and Ritchison 1999). Highway noise

would, therefore, be perhaps more likely to mask or interfere with communication between

individuals of these species, with the possible end result of reduced densities.

Avian Productivity

Nest fate was determined for the majority of nests located and monitored. However, despite theuse of egg-floating techniques in conjunction with pip fragments to determine nest fate, a

significant portion of all nests (20.9%) were classified as unknown because cues were

insufficient to allow for a reliable determination of fate. It is possible that the relatively highnumber of nests classified as unknown may have reduced the number of nests that were correctly

classified as being successful. Location of pip fragments within a nest often proved difficult,


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however, and in the absences of chicks pip fragments were the only indicator of a nest beingclassified as successful.

The wide variation in estimates of nest success (both apparent and Mayfield) between study sitesis not uncommon and falls within the range of variation in nest success exhibited by both stilts

(Ohlendorf et al. 1989, Sordahl 1996, Robinson et al. 1999) and avocets (Ohlendorf et al. 1989,Sordahl 1996, Robinson et al. 1997). Depredation was the primary cause of nest failure across allspecies, study sites, and years. Of 570 failed nests, 73.3% failed due to depredation. Nest failure

due to factors other than depredation, such as abandonment (5.8%) or failure due to unknown

causes (20.9%), was relatively rare. Depredation is, in most cases, the primary cause of nest

failure for the majority of bird species, including stilts, avocets and plovers (e.g., Page et al.1995, Sordahl 1996; Robinson et al. 1997, 1999).

Evidence for a relationship between highway noise and nesting success for avocets, stilts andplovers was equivocal. The apparent lack of a relationship between highway noise and apparent

nest success estimators for all species considered collectively and for stilts individually suggests

that highway noise does not influence nesting success for these species. The multiple regressionmodel for avocets revealed a positive relationship between apparent nest success and distance to

nearest neighbor, suggesting that avocets nesting near other avocets were more successful, which

is not surprising given that avocets nest semicolonially. Mean noise was significantly greater at

successful nests when all three species were pooled together, and for avocets considered alone.This apparently positive relationship between highway noise and nesting success may be the

result of disruptions of predator-prey interactions, which can result in an increase in reproductive

success (Francis et al. 2009).

Although there is some evidence that there may be either a positive relationship betweenhighway noise and nest success, or no impact of highway noise on nest success, these results

should be treated cautiously. First of all, there exist the same problems with noise data that are

present for the point-count data. Noise levels may or may not accurately represent highwaynoise. Second, habitat data, which often explain much variation for both abundance and

productivity data, were not collected.

If highway noise in particular and anthropogenic noise in general is the primary factor

influencing nesting success for avocets, study sites characterized by higher levels of noise,

whether produced by roads or not, should also have greater levels of nesting success, while

relatively quiet study sites such as Public Shooting Grounds and Salt Creek WMA should havethe lowest levels of nesting success. While noisier sites such as ISSR, LNP, and the Great Salt

Lake Shorelands Preserve did have some of the greatest levels of apparent nesting success, other

noisy sites such as Timpie Springs WMA and Farmington Bay WMA had levels of apparentnesting success closer to relatively quiet sites such as Public Shooting Grounds and Salt Creek

WMA. Apparent levels of nesting success also were relatively similar for stilts and avocets at a

given site, yet there was no evidence of a relationship between noise and stilt nesting success.

These results suggest that while highway noise may apparently play some role in influencing

nest success for avocets and stilts, it was not likely to be the dominant factor. Nest success is


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most likely influenced by a suite of interacting factors which likely include nest sitecharacteristics, parental body conditions, weather, predator communities, and noise.

In particular, the distance, extent, and depth of water in relation to nests were likely importantfactors determining nest fate. Although spatial analyses of the location, depth, and extent of

water relative to nest sites and nest success were not conducted, our field observations suggestthat avocets and stilts experience greatest nesting success when nesting on islands and in wetmeadows, respectively. Although the extent and depth of water surrounding island colonies

varied across study sites, it apparently afforded some degree of protection. Previous research on

avocets and stilts has shown that deep water can serve as an effective barrier for mammalian

predators (Robinson et al. 1997, 1999).

CONCLUSIONS

Considered collectively, analyses of both point-count and nest success data collected over 4

years suggest that highway noise may have had both positive and negative impacts on selected

species within breeding bird communities in the Great Salt Lake ecosystem. Inferences abouthighway noise on the effects of both avian abundance and nest success should be treated

cautiously, given the aforementioned limitations on noise data.

Highway noise may have had apparent impacts on the abundance of both the yellow-headed

blackbird and the common yellowthroat. For the yellow-headed blackbird, highway noise had a

slight positive influence. Conversely, highway noise had an apparent negative impact oncommon yellowthroat abundance, presumably due to the effects of masking. However, these

relationships were weak and ill-defined.

From a productivity standpoint, the impacts of noise on nesting success are less clear. Evidence

for a relationship between highway noise and nesting success for avocets, stilts and plovers wasambiguous. There was no apparent relationship between highway noise and apparent nestsuccess for any of the multiple regression models except for avocets and distance to nearest

neighbor, but mean noise was higher at successful nests than failed nests for all species pooled

and for avocets alone. These results could potentially be explained if highway noise changespredator communities by excluding species that depredate avocets, stilts and plovers.

The potential impact of anthropogenic noise on a particular species may depend on a suite of

factors, including the spectral characteristics (frequency, magnitude, duration and timing) of aparticular species songs and calls relative to the spectral characteristics of the anthropogenic

noise. There may also be a threshold level below which anthropogenic noise does not have

immediate or tangible impacts (Foote et al. 2004). Moreover, species may fall into one of twogroups, those that can adjust the frequency and amplitude of their songs so that there is little or

no overlap with anthropogenic noise, and those that cannot. Species such as nightingales

(Luscinia megarhynchos) (Brumm 2004), great tits (Parus major) (Slabekoorn and Peet 2003),song sparrows (Melospiza melodia) (Wood and Yezerinac 2006), and house finches (Carpodacus

mexicanus) (Fernadenz-Juricic et al. 2005) may be less susceptible to masking from

anthropogenic noise because they can shift the frequency (e.g., great tits, song sparrows, house


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finches) and amplitude (e.g., nightingales) of their song in response to masking fromanthropogenic noise sources. Species which cannot adjust the frequency and amplitude of their

songs may incur greater costs in terms of reduced reproductive output (Habib et al. 2007).

The characteristics of anthropogenic noise also play an important role in determining the

presence and extent of the effects of noise on wildlife. There is an important threshold levelabove which anthropogenic noise levels have more immediate and tangible impacts (Foote et al.2004). Noise below the masking threshold apparently has no effect (Dooling and Popper 2007).

More importantly, noise that overlaps with the spectral region of a birds vocalizations has a far

greater effect on masking than noise that does not coincide with the spectral region (Dooling and

Popper 2007).

Anthropogenic noise collected for this study was characterized by a considerably lower range of

amplitudes (4065 dB) than anthropogenic noise that was shown to reduce pairing success forovenbirds (75105 dB) (Habib et al. 2007). It is possible that the masking threshold may not

have been reached for this study. Moreover, noise data collected for this study did not, for the

most part, originate from point sources, but rather from moving vehicles. Likewise, with theexception of heavy traffic associated with rush hour, noise data collected for this study were not

chronic, but characterized by pulses of noises. The apparent difference in both noise levels and

the lack of continuity associated with noise levels, may account, in part, for the apparent lack of

broad impacts by noise observed in this study.

STUDY LIMITATIONS

This study focused on assessing the impacts of highway noise on breeding bird communities as a

whole, and on nesting success for two common species found throughout the GSLE. Althoughthese results may provide important information about the effects of highway noise on breeding

bird communities, there are limitations associated with this approach.

First, although the significant correlation between noise data and distance to the nearest paved

highway suggests that noise data were representative of highway noise, at most study sites noise

data are confounded to a certain extent by the presence of existing sources of ambient noiseincluding the SLIA, a busy transcontinental railroad corridor, industries, and to a lesser extent,

residential areas and farming. The presence of these non-highway noise sources suggests that our

conclusions and inferences about the effects of highway noise on breeding bird communities are

limited in scope and should be treated cautiously.

Second, this study assessed only a subset of the breeding bird community, and focused on

assessing the effects of noise on the abundance of 10 bird species, rather than for all 94 speciesdetected over 4 years. Other species that were not abundant enough to allow for density estimates

may be more (or less) susceptible to the effects of highway noise. Similarly, the effects of

highway noise on nest success were assessed for two target species, rather than the breeding birdcommunity as a whole. There may be differences in nest success and productivity related to

highway noise for the two species that were the focus of this study. Likewise, there may be

effects of noise on parameters not assessed, such as vigilance behavior (Quinn et al. 2006, Rabin


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et al. 2006), changes in song structure (Slabbekoorn and Peet 2003, Brumm 2004, Fernndez-Juricic et al. 2005, Wood and Yezerinac 2006), or damage to avian auditory systems due to

overexposure to noise (Dooling and Popper 2007).

Third, this study used soundmeters to measure noise using decibels and the A-weighting system

to assess the effects of noise on birds. The alternative, using measurements of spectral energy inthe recommended spectral range [octave band levels at 2.0 and 4.0 kHz] requires the use ofcostprohibitive oscilloscopes. Measuring noise (dB) may not provide the most appropriate

measure for assessing the effects of noise on birds, because it may provide only a very

conservative estimate of the effects of noise on communication in birds (Dooling and Popper

2007). The most relevant measure is the spectrum level of noise in the frequency region of noisethat birds most frequently vocalize and hear in, typically, 16 kHz (Dooling and Popper 2007).

However, others (e.g., Brumm et al. 2004, Fuller et al. 2007) have also used soundmeters and the

dB A-weighting system, and have found meaningful results, suggesting that soundmeters are aviable alternative to oscilloscopes.

SUGGESTIONS FOR FUTURE STUDY1. Future studies should greatly expand the number of species studied in depth (including both

abundance and productivity data).

2. If multiple species cannot be studied in depth concurrently, study species should be those thatcan be considered indicator species for the general health of the ecosystem and/or thosespecies likely to be the most sensitive to disruption from highway noise. However, it is likely

that the most sensitive species cannot be identified beforehand, which is why studying

numerous species would be most beneficial

Documents

Legacy Avian Noise Research Program - 2011 FINAL Report