Changes in Avian Vocalization Occurrence and Frequency Range During the Winter

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Amy I. Oden University of Nebraska - Lincoln, [email protected]

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Oden, Amy I., "Changes in Avian Vocalization Occurrence and Frequency Range During the Winter" (2013). Dissertations & Theses in Natural Resources. 69. https://digitalcommons.unl.edu/natresdiss/69

This Article is brought to you for free and open access by the Natural Resources, School of at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Dissertations & Theses in Natural Resources by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. CHANGES IN AVIAN VOCALIZATION OCCURRENCE AND FREQUENCY RANGE DURING THE WINTER

Amy I. Oden

A THESIS

Presented to the Faculty of

The Graduate College at the University of Nebraska

In Partial Fulfillment of Requirements

For the Degree of Master of Science

Major: Natural Resource Sciences

Under the Supervision of Professor James R. Brandle

Lincoln, Nebraska

August, 2013

CHANGES IN AVIAN VOCALIZATION OCCURRENCE AND FREQUENCY RANGE DURING THE WINTER

Amy I. Oden, M. S.

University of Nebraska, 2013

Advisor: James R. Brandle

Human population expansion has led to an increase in vehicle traffic and therefore vehicle noise. Traffic and traffic noise has been shown to affect avian abundance, breeding success, density and species diversity on the landscape. Documented changes in avian vocalizations due to traffic noise include shifts in amplitude, frequency, rate, timing, and duration of vocalizations along with a number of behavioral adaptations.

During the winters of 2011–2012 and 2012–2013, we recorded and measured the “chick- a-dee” vocalization of Black-capped Chickadees (Poecile atricapillus) and the “po-ta-to- chip” vocalization of American Goldfinches (Spinus tristis) to determine if bird vocalizations near high traffic noise had higher minimum and maximum frequencies than bird vocalizations near low traffic noise. We found that both the Black-capped Chickadee and American Goldfinch vocalizations have a higher minimum frequency near high traffic noise while the maximum frequency showed no change. This suggests that these species will alter the part of their vocalization that is acoustically masked by traffic noise in order to better transmit the vocalization. However, costs of altering vocalizations include the inability to attract a mate, poor vocal performance, not sounding like conspecifics, and being more easily heard by predators. Chickadees also alter how often they vocalize based on their flock composition. Chickadees vocalize more in mixed-

species flocks with other satellite members than in flocks that contained juncos or in single-species flocks of chickadees. Also, single species flocks of Black-capped

Chickadees tended to be smaller in size and mixed-species flocks of Dark-eyed Juncos plus individual satellite members tended to be larger in size.

ACKNOWLEDGEMENTS

I would like to thank Dr. John Quinn for not only sparking my love of birds, but for giving me the chance to complete a Master’s degree. I appreciate all the input, advice, edits (oh how many edits), and information you sent, and continue to send, my way.

I would like to thank Dr. James R. Brandle for guiding me these past two years and allowing me earn my keep as a teaching assistant. I have learned so much teaching others and am thankful for the opportunity you have given me.

I would like to thank Dr. Mary Bomberger Brown for being there for a good talk when I needed it and for all the amazing edits on my thesis.

I would like to thank Dr. Mark Burbach for taking on a thesis that is a little outside of your expertise and still being able to provide excellent feedback.

I would like to thank my husband, Cameron Oden, and our dog Vixen for putting up with every stop I made on our walks so I could listen to and photograph the birds. Your support and love is amazing. Also, to my family and friends, I know you may not fully understand what I do, but I love that you care enough to repeatedly ask.

TABLE OF CONTENTS Page TITLE PAGE ...... i

ABSTRACT ...... ii

ACKNOWLEDGEMENTS ...... iv

LIST OF TABLES ...... vii

LIST OF FIGURES ...... viii

LIST OF APENDECIES ...... ix

CHAPTERS

1. THE EFFECTS OF TRAFFIC NOISE ON AVIAN VOCALIZATION AND COMMUNICATION: A REVIEW Abstract ...... 1 Introduction ...... 2 Methods ...... 2 Birds communication and traffic ...... 3 Proximate outcomes of acoustic masking ...... 4 Mechanisms of response to change ...... 7 Is traffic noise the biggest driver? ...... 8 Proximate outcomes from impacts of traffic quantity ...... 9 Ultimate outcomes of acoustic masking and traffic quantity ...... 10 Need for future research: proximate and ultimate outcomes of acoustic masking . . . . 11 Traffic noise vs traffic volume ...... 13 Applied research and mitigation ...... 13 Conclusion ...... 14 Literature Cited ...... 15

2. AVIAN VOCALIZATIONS DURING THE WINTER CHANGE IN RESPONSE TO HIGH LEVELS OF TRAFFIC NOISE

Abstract ...... 20 Introduction ...... 20 vi

Methods ...... 25 Results ...... 27 Discussion ...... 29 Conclusion ...... 31 Literature Cited ...... 32

3. BEHAVIORAL DYNAMICS OF SINGLE- AND MIXED-SPECIES WINTER FLOCKS IN EASTERN NEBRASKA Abstract ...... 35 Introduction ...... 36 Methods ...... 39 Results ...... 42 Discussion ...... 44 Conclusion ...... 46 Literature Cited ...... 48

TABLES ...... 50

FIGURES ...... 54

APPENDICES ...... 61

vii

LIST OF TABLES Table Page

1. Mitigation efforts to reduce the impacts of traffic and traffic noise on avian species...... 50

2. Number of vocalizations obtained for Black-capped Chickadees and American Goldfinches at each study site ...... 51

3. Results from the generalized linear regression model on flock size as a function of flock composition ...... 52

4. Results from the generalized linear regression model on chickadee vocalizations as a function of flock composition ...... 53

viii

LIST OF FIGURES Figure Page

1. Years of publication for studies that relate to traffic effects on avian species. Papers obtained from the Web of Science following a key word search for the terms avian, communication, vocalization, traffic, roads, and noise...... 54

2. Map of eastern Nebraska showing all 20 study sites ...... 55

3. Noise data from the Nebraska Department of Roads shows that significant noise levels drop off around 450 meters from the center of the outside lane of I-80. 56

4. Sonograms from Song Scope showing (a) “chick-a-dee” call in high traffic noise. (b) “chick-a-dee” call in low traffic noise. (c) “po-ta-to-chip” call in high traffic noise. (d) “po-ta-to-chip” call in low traffic noise ...... 57

5. (a) Maximum frequency ranges of American Goldfinch vocalizations in high and low traffic noise areas. (b) Maximum frequency ranges of Black-capped Chickadee vocalizations in high and low traffic noise areas. (c) Minimum frequency ranges of American Goldfinch vocalizations in high and low traffic noise areas. (d) Minimum frequency ranges of Black-capped Chickadee vocalizations in high and low traffic noise areas ...... 58

6. Estimated flock size as a function of flock composition. All refers to flocks of chickadees, juncos, and satellite members. BCCHonly refers to flocks with only chickadees or lone chickadees. BCCHwsat refers to chickadees with only satellite members, no juncos. DEJUonly refers to flocks of juncos only or lone juncos. DEJUwsat refers to flocks of juncos with satellite members, no chickadees . . 59

7. Estimated number of vocalizations as a function of flock composition. All refers to flocks of chickadees, juncos, and satellite members. BCCHonly refers to flocks with only chickadees or lone chickadees. BCCHwsat refers to chickadees with only satellite members, no juncos ...... 60

LIST OF APPENDICES

Appendix Page

1. Description and GPS coordinates of study sites for Chapter 2 ...... 61

2. Description and GPS coordinates of study sites for Chapter 3 ...... 64

CHAPTER 1 THE EFFECTS OF TRAFFIC NOISE ON AVIAN VOCALIZATION AND COMMUNICATION: A REVIEW

ABSTRACT

Human population expansion has led to an increase in the number and mileage of roadways across the landscape with a consequent increase in vehicle traffic. A growing body of literature has demonstrated that many birds alter the way they vocalize in order to be heard by their own and different species due to the noise generated by traffic and other human activity. This review evaluates the growing literature that describes the effects of traffic noise on birds. The issue of traffic quantity and/or traffic noise has been shown to be among the most significant drivers of change in bird behavior. Traffic and traffic noise has been shown to affect abundance, breeding success, density and species diversity on the landscape. Documented changes in vocalizations due to traffic noise include shifts in amplitude, frequency, rate, timing, and duration of vocalizations along with a number of behavioral adaptations. Costs of altering vocalizations include the inability to attract a mate, poor vocal performance, not sounding like conspecifics, and being more easily heard by predators. Future research needs in this area include 1) controlling for different variables that could be affecting avian species distributions along roadways, 2) vocal responses during the winter, 3) responses to acoustic masking (e.g., inability to protect a territory or faulty parent-offspring communication), and 4) applied research on mitigation efforts.

INTRODUCTION

All environments are noisy as sound is a perpetual and dynamic property of landscapes

(Slabbekoorn & Ripmeester 2008; Pijanowski et al. 2011). However, humans have altered much of the world’s acoustic characteristics with anthropogenic sounds–sounds that are different in pitch, amplitude, acoustic structure, distribution, and often more continuous than sounds produced in natural environments (Wood & Yezerinac 2006;

Slabbekoorn & Ripmeester 2008; Pijanowski et al. 2011). Roads and associated traffic, in particular, have a broad acoustic impact, affecting nearly one-fifth of the total land area in the United States (Forman et al. 2002). The resulting acoustic impacts from traffic may be broad, extending outwards as far as 450m into the environment adjacent to roadways (Slabbekoorn & Ripmeester 2008; Summers et al. 2011) and may affect how birds communicate. In addition, roads can interrupt natural processes (e.g., flowing water, spreading fires) (Forman & Alexander 1998) and create smaller habitat patches (Faaborg et al. 2010).

METHODS

To summarize the growing literature on impacts of traffic noise on bird vocalizations

(Figure 1) and to identify key gaps in knowledge we searched the Web of Science for key words avian, communication, vocalization, traffic, roads, and noise. The identified papers fell into two major themes presented here under 1) proximate and 2) ultimate responses to acoustic masking. Proximate responses were divided by: changes in frequency, amplitude, timing, structure, learning, behavior and mechanisms of change. In order to 3 address what some say is the most significant environmental issue associated with roads, avian responses to traffic quantity was also discussed.

BIRDS COMMUNICATION AND TRAFFIC

Birds have among the most elaborate and complex acoustic signals in the animal kingdom (Marler 2004); they communicate primarily through songs and calls. Birds will occupy nearly all available spaces and available acoustic niches, even if it means inhabiting less-than-ideal patches along roadways (Farina et al. 2011). Calls are simpler and shorter than songs and can convey a variety of messages (Marler 2004). Songs are longer, more melodic, and are mainly used for attracting females and deterring rivals

(Marler 2004). Most vocalizations from birds range between 1 kHz and 9 kHz (Rheindt

2003). Since traffic noise is characterized by a low frequency band of noise between 0–4 kHz (Patricelli & Blickley 2006; Nemeth & Brumm 2010), the lower frequencies of bird vocalizations may overlap with traffic noise (acoustic masking). Acoustic masking occurs when one sound masks, or drowns out, another sound. Acoustic masking of bird vocalizations has the potential to negatively affect bird communication and reproductive fitness (Rheindt 2003). As verbal communications can only be beneficial and able to receive a response if the vocalization is detected (Ryan & Brenowitz 1985), acoustic masking of vocalizations by traffic noise has proximate and ultimate implications.

Because traffic noise is a predominantly low frequency, there are different levels of sensitivity of bird species to traffic noise (Rheindt 2003). In particular, those species with lower frequency vocalizations (1–2 kHz) will have greater acoustic interference, or masking, than those with higher frequency vocalizations (higher than 4 kHz) that are 4 above typical traffic noise levels (Wood & Yezerinac 2006; Parris & Schneider 2009;

Luther & Baptista 2010). Hence, it is essential that we better recognize the impacts of increased noise on animal communication.

PROXIMATE OUTCOMES OF ACOUSTIC MASKING

Frequency. The most common response of birds to traffic noise is to vocalize at a higher frequency, or pitch, which includes: increasing their minimum frequency (Slabbekoorn & den Boer-Visser 2006; Wood & Yezerinac 2006; Luther & Baptista 2010; Dowling et al.

2011), changing their maximum frequency (Dowling et al. 2011), shifting the entire vocalization to a higher frequency (Rheindt 2003; Parris & Schneider 2009; Francis et al.

2011; Halfwerk et al. 2011a), or to change the relative amplitude of different frequency components (Wood & Yezerinac 2006; Nemeth & Brumm 2010). Shifting a vocalization up in pitch allows for fewer low pitch notes that could potentially be masked by anthropogenic noise (Slabbekoorn & den Boer-Visser 2006).

Species with lower pitch calls are more likely to shift their vocalizations. Parris and

Schneider (2008) showed that the lower pitch singing Grey Shrike-thrush (Colluicincla harmonica) sang at a higher frequency when near traffic noise. In contrast, the higher singing Grey Fantail (Rhipidura fuliginosa) did not change its song in the presence of traffic noise. The differences in type of shift are demonstrated by both Great Tits (Parus major) and Common Blackbirds (Turdus merula). While both species sing at higher pitches in urban areas; Common Blackbirds shift their whole song upwards in frequency while Great Tits only increase their minimum frequency (Slabbekoorn & Peet 2003; 5

Nemeth & Brumm 2010). If a male has to sing at a higher frequency to be heard it could possibly reduce the attractiveness of the song (Halfwerk et al. 2011a). For example, female Great Tits (Parus major) may cheat on their mates if the male does not sing a low pitch song (Halfwerk et al. 2011a).

Amplitude. Birds adjust and adapt the amplitude, or energy, of their vocalizations daily

(Brumm & Todt 2002; Brumm 2004a; Nemeth & Brumm 2010). Increasing amplitude in response to an increase in ambient noise is known as the Lombard effect (Lombard

1911). The Lombard effect is usually accompanied by a change in pitch of the vocalization since lower frequency vocalizations (1–4 kHz) tend to have less energy

(Wood & Yezerinac 2006; Nemeth & Brumm 2010). It has been suggested that amplitude is the key factor in exchanging verbal information and that amplitude has a larger, stronger effect on communication distance than frequency (Nemeth & Brumm 2010).

Nemeth and Brumm (2010) studied Great Tits in cities dominated by traffic noise and found birds that increased their amplitude could communicate further distances, even in the presence of increased traffic noise. Lowry et al. (2012) found that the Noisy Miner

(Manorina melanocephala) will call more loudly at noisier locations near busy roads than near quieter residential streets.

Timing. Birds can change the timing of their vocalizations to avoid competing with their neighbors, to take advantage of small gaps in ambient noise, or to not sing when predators are more active or a mate is not near (Ficken et al. 1974; Popp 1989). Ficken et al. (1974) showed that Least Flycatchers (Empidonax minimus) will sing between the 6 songs of Red-eyed Vireos (Vireo olivaceus) so as to not have overlap of the two species’ songs. In response to traffic, the European Robin (Erithacus rubecula), has been shown to change the time of day they vocalize by singing at night when traffic noise levels are low (Fuller et al. 2007).

Vocalization structure. Species may vary vocalization structure by changing rate or rhythm, increasing the length, or increasing redundancy in a song or call before switching to another song or call type (Brumm & Slater 2006; Mockford & Marshall 2009).

Changing the rate and/or rhythm of a song or call can include temporal structures, note timing, or syllable timing in the vocalization (Patricelli & Blickley 2006). While this change may allow a bird to be heard it could also increase the risk of having a poorer vocal performance that may not be as attractive to females (Byers 2007). Brumm and

Slater (2006) found that Chaffinches (Fringilla coelebs) use serial redundancy in order to make sure their message was received when in noisy areas.

Learning. Vocalizations that are masked by background noise may be copied incorrectly or never learned (Slabbekoorn & Ripmeester 2008); copying imprecision may result from a bird hearing, and therefore only learning, part of a song. Those bird species that are able to learn multiple songs may be at an advantage in areas of high traffic noise. If a certain song does not elicit a response, those birds with multiple songs in their repertoire are able to drop that song and still have others to choose from (Slabbekoorn & Ripmeester 2008).

With an increase in repertoire size, it is possible that the Song Sparrows (Melospiza 7 melodia) can pick and choose which songs from their repertoire to sing that will be heard best over traffic and urban park noise (Wood & Yezerinac 2006).

Behavior. Birds may also alter behaviors associated with vocalizations in order to have their vocalizations heard. Dooling (2005) suggests that birds, like humans, may get closer to the receiver or turn their heads more so their vocalization is sent in the direction of the receiver.

MECHANISM OF RESPONSE TO CHANGE

Vocalization Plasticity. No bird species has only one call or one song (Robbins 2007).

A majority of birds learn their songs and calls from listening to others of their species that are around them, their parents, neighbors, or birds in their flock. Within these species, some are able to modify their songs multiple times throughout their life, while others stop developing that ability early in life. This is due to a plastic period of vocal development where learning after a certain point cannot happen (Slabbekoorn & Peet 2003). Song

Sparrows could be age-limited song learners since the songs in their repertoire are identical year after year (Nordby et al. 2002). Some species are born with innate vocalizations and are unable to modify them during their life. Species unable to modify their vocalizations include the Willow Flycatcher (Empidonax traillii) and Alder

Flycatcher (Empidonax alnorum) (Kroodsma 1984). Noisy territories do not hinder birds with innately higher spectral capacities or for birds that learn to restrict vocal output to a frequency range that overcomes the masking effect of ambient noise. Those birds with 8 vocal plasticity may not be able to avoid acoustic masking and may have to search for more suitable, quiet habitat.

Anatomy. Some birds may have anatomical or physiological limits in their ability to vocalize at higher frequency ranges to be heard over traffic noise. This could include the angle they can hold their head, how wide they can open their beak, their beak shape, and their body size. Typically, the frequencies that birds are able to produce are related to their body size. The larger the body size, the lower the frequency of the bird’s songs or call; and, the smaller the body size, the higher the frequency of the vocalization (Ryan &

Brenowitz 1985). There is also an association between body size and amplitude (Brumm

2004a).The larger the body is, the greater the amplitude and vice versa. A bird cannot change the vocal mechanisms in their throats that allow for certain characteristics of a song to be produced (Podos et al. 2004). Having an anatomical or physiological limit for making a vocalization could cause birds to avoid areas with high levels of traffic noise.

IS TRAFFIC NOISE THE BIGGEST DRIVER?

While the focus of this review is on the effect of traffic noise on bird vocalizations, suggested by many as the largest impact of roads on birds (Reijnen & Foppen 1994;

Reijnen et al. 1995; Reijnen & Foppen 1997; Forman et al. 2002; Parris & Schneider

2009; Halfwerk et al. 2011b), others suggest that negative impacts on birds (e.g., reduction in avian density, richness, abundance, diversity, breeding success, and reproductive success) in habitats adjoining roads may be due to factors other than traffic noise (Foppen & Reijnen 1994; Reijnen & Foppen 1994; Reijnen & Foppen 1995; 9

Reijnen et al. 1995; Fernandez-Juricic 2001; Forman et al. 2002; Rheindt 2003; Miller et al. 2003; Francis et al. 2009; Goodwin & Shriver 2010; Halfwerk et al. 2011b; Herrera-

Montes & Aide 2011; Summers et al. 2011). Other negative impacts of roadways include: air pollutants, microclimatic modification, visibility of cars, road kill, and predators attracted to road vicinity. These drivers may not extend outward enough to explain the change in bird behavior, but their effects should not be discounted.

PROXIMATE OUTCOMES FROM IMPACTS OF TRAFFIC QUANTITY

Traffic affects large areas of natural habitat worldwide, the exact cause is still unknown

(Halfwerk et al. 2011b). Traffic volume may cause a reduction in habitat quality near roads (Reijnen & Foppen 1995). The increase in the number of vehicles may cause an increase in the distance or range the impact of those vehicles has on birds, ranging from meters in forests up to a kilometer or more in grasslands (Reijnen & Foppen 1994).

Traffic emits pollutants in the form of gases, liquids, and solids (Goosem 2007).

Pollution from cars can affect the abundance and size of insects that birds feed on, up to

50m from the road (Przybylski 1979). The presence of vehicles can cause avoidance of roadside areas for foraging and nesting which would lead to lower rates of occupancy or reduced breeding success near roads (Reijnen et al. 1995; Forman et al. 2002). Vehicles on the road may create visual disturbances such as movement, flashing headlights, and reflection of the sunlight up to 25m from the road (Goosem 2007; Parris & Schneider

2009). As the number of vehicles increase, the chance of a fatal collision with a bird increases as well. It is suggested that this mortality may be the main reason for species richness abundance reduction near roads (Summers et al. 2011). 10

Some species are not vulnerable to the negative impacts of living near roads, such as the

House Finch (Carpodacus mexicanus) (Francis et al. 2009) and the Blue Tit (Cyanistes caeruleus) whose abundance was shown to be greater near roads (Rheindt 2003). This could be due to their level of stress tolerance, human associated food sources, lower interspecific competition pressure, less predation risk since predators may avoid noisy areas, or predators that may not be able to locate nests using acoustic cues (Rheindt 2003;

Francis et al. 2009; Slabbekoorn & Halfwerk 2009).

ULTIMATE OUTCOMES OF ACOUSTIC MASKING AND TRAFFIC QUANTITY

Bird vocalizations, like all attributes of living organisms, can evolve due to a changing environment. The acoustic properties of the environment, and their masking effects, can influence the evolution of vocal signals (Brumm 2004a; Slabbekoorn & den Boer-Visser

2006; Pijanowski et al. 2011). Song learning altered by traffic noise is at least partly responsible for the song divergence between populations of species living in cities and forests (Slabbekoorn & den Boer-Visser 2006). Copying imprecision can lead to variation in songs which can then lead to the development of dialects that are easier to detect over the noise (Podos et al. 2004; Slabbekoorn & den Boer-Visser 2006; Luther &

Baptista 2010). Reproductive isolation of species can be due to divergence between urban and nonurban songs, urban songs being higher pitched than nonurban songs (Slabbekoorn

& Ripmeester 2008).

Divergence of species may also be caused by roadways fragmenting a habitat, causing greater edge habitats and smaller interior habitats. Those species that are sensitive to 11 edges may show changes in abundance, richness, and diversity (Delgado et al. 2009) and decreases in these may lead to reduction in genetic diversity. High mortality rates near roads may be a cause for a reduction in genetic diversity (Jackson & Fahrig 2011).

NEEDS FOR FUTURE RESEARCH:

PROXIMATE AND ULTIMATE OUTCOMES OF ACOUSTIC MASKING

Territory guarding. Males changing their territorial songs to overcome acoustic masking is a predicted response of traffic noise that has not been tested yet. If a male near traffic noise sings normally he risks possibly not having his song heard. If he alters his song, the message may not be received correctly. If the song is not heard or understood, it could lead to having to fight off intruding males to keep them from encroaching into his territory, which would detract from the time spent singing for females (Slabbekoorn & den Boer-Visser 2006; Mockford & Marshall 2009). There are studies on traffic noise affecting mate fidelity and choice, but information is needed to see if traffic noise could cause males that have changed their songs to lose their territory during the breeding season or to suffer reduced fitness.

Inter- and intra- flock communication. Changes in communications between and among species are another predicted response of traffic noise whose effects remain understudied. Vocalizations can inform the receiver of the whereabouts, identity, and distance of the sender in order to keep in contact with a mate, a flock mate, or a social group (Slabbekoorn & Halfwerk 2009). Parents and their offspring also use acoustic signals to recognize and communicate with each other (Beecher 1990; Kilner et al. 1999). 12

The young must beg for food and attention from their parents with distinguished vocal sounds (Marler 2004). If the vocalizations are not heard, or the sender has made the vocalization sound different, information may not be transferred correctly. Studies are needed on how traffic noise could potentially interrupt parent-offspring communication, conspecific communications, intra-flock communications, or inter-species communications and the consequences of those interruptions.

Winter. Migratory birds have four parts of their migration cycle: spring migration, summer breeding, fall migration, and over-wintering. Research and management for birds has focused on the breeding season and their migration patterns (Faaborg et al. 2010).

There is a lack of information and research during the wintering season. Winter months are important for migrating birds as they build nutrient reserves for the spring migration

(Faaborg et al. 2010). For non-migrating birds, the winter season provides security and time to acclimate to the resources and hiding places in a bird’s home range. Also, for some non-migrating species, the winter months allow them to form mate pairs and gain territory for breeding come spring (Smith 1984). More information is needed on how traffic noise interrupts birds’ communication in the winter when the focus is not on mating and territory but rather food location, predators, and contact calls. Interruption of winter vocalizations can cause identity confusion, disrupt food information transfer, and cause predator warnings to me misinterpreted or not heard.

TRAFFIC NOISE VS TRAFFIC VOUME

Further research that better controls other stimuli associated with noise such as physical alteration of habitat or visual disturbance presented by moving traffic is needed

(Slabbekoorn & Ripmeester 2008; Francis et al. 2009; Nemeth & Brumm 2010; Summers et al. 2011). To say traffic noise is the only factor contributing to negative effects on birds, researchers must design a study that blocks visual disturbances from traffic, keeps birds from colliding with traffic, have no pollution or food coming from the cars, and find a way to not have a habitat edge near the traffic noise. Or, researchers can bring traffic noise into an area with no previous anthropogenic noise. In order to show that other variables besides traffic noise contribute most to the negative effects on birds, a roadway with all of its pollution and flashing lights must be used, but it must be silent. Also, more specific information on why certain species thrive near traffic is needed.

APPLIED RESEARCH AND MITIGATION

Many methods have been proposed to reduce the impacts of traffic and traffic noise on avian communities (Table 1) (as suggested by Reijnen et al. 1995; Forman et al. 2002;

Miller et al. 2003; Maekawa 2004; Slabbekoorn & Ripmeester 2008; Parris & Schneider

2009; Halfwerk et al. 2011b; Summers et al. 2011). However, most of these solutions are costly (Parris & Schneider 2009). Also, they would not solve the issue of habitat fragmentation caused by the presence of road, and some mitigation efforts might increase fragmentation, cause a loss of interior habitats, and increase population isolation leading to genetic consequences (Forman & Alexander 1998; Fernandez-Juricic 2001).

Although many researchers have suggested these methods, there is a need for studies to be conducted to test their efficacy in reducing the negative impacts on birds. Finding cost-efficient mitigation techniques for traffic noise may help ameliorate noise pollution and therefore reduce the consequences of acoustic masking.

Mitigating the effects of traffic will not only benefit bird species, but humans as well

(Slabbekoorn & Ripmeester 2008). Any effort we make to keep birds from colliding with cars will also prevent birds from hitting and damaging our cars. Any effort we make to keep sound from affecting the birds will also keep sound from affecting the human population that live near roads.

CONCLUSION

It is clear that the effects of traffic and traffic noise on birds are not fully understood.

New research methods are needed in order to control variables that could alter the results on what is specifically impacting avian species. Research needs to be done to look at predicted responses of traffic noise and the effects during non-breeding times of the year.

Despite gaps in our knowledge, we can conclude that traffic is having a negative impact on certain avian species and we need to begin implementing mitigation measures to prevent this problem from worsening.

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Halfwerk, W., Holleman, L. J. M., Lessells, C. M., & Slabbekoorn, H. 2011b: Negative impact of traffic noise on avian reproductive success. Journal of Applied Ecology 48, 210-219. 17

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Luther, D. & Baptista, L. 2010: Urban noise and the cultural evolution of bird songs. Proceedings of the Royal Society B 277, 469-473.

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CHAPTER 2 AVIAN VOCALIZATIONS DURING THE WINTER CHANGE IN RESPONSE TO HIGH LEVELS OF TRAFFIC NOISE

ABSTRACT

Low frequency (pitch) traffic noise may cause acoustic masking of avian vocalizations.

This constant background noise may cause birds to shift or otherwise alter the frequencies of their vocalizations in order to be heard. During the winters of 2011–2012 and 2012–2013, we recorded and measured the “chick-a-dee” vocalization of Black- capped Chickadees (Poecile atricapillus) and the “po-ta-to-chip” vocalization of

American Goldfinches (Spinus tristis) to determine if bird vocalizations near high traffic noise had higher minimum and maximum frequencies than bird vocalizations near low traffic noise. We found that both the Black-capped Chickadee and American Goldfinch vocalizations have a higher minimum frequency near high traffic noise while the maximum frequency showed no change in either species. This suggests that these species will alter the part of their vocalization that is acoustically masked by traffic noise in order to better transmit the vocalization. However, changing parts of a vocalization may result in a poorer vocal performance or the message in the vocalization being received incorrectly, both of which could cause harm to the sender and the receiver.

INTRODUCTION Sound is an attribute of every landscape (Slabbekoorn & Ripmeester 2008;

Pijanowski et al. 2011). With the increase in human population and their encroachment 21 into wilderness areas, the acoustic characteristics of many landscapes have been changed by anthropogenic sounds that are different in pitch, amplitude, and acoustic structure from natural sounds. Moreover, these sounds are generally more continuous in quality than sounds produced naturally in the environment (Wood & Yezerinac 2006;

Slabbekoorn & Ripmeester 2008; Pijanowski et al. 2011). Traffic noise is one of the main anthropogenic sounds added to the landscape; the area that roads and traffic sounds have an effect on cover almost 20% of the entire land mass in the United States (Forman &

Alexander 1998). In humans, traffic noise can increase stress and reduce concentration

(Ouis 2001). Birds in areas near traffic noise are at risk for lower breeding success and fitness due to acoustic interference (Halfwerk et al. 2011b).

Birds produce some of the most complex and elaborate vocal signals in the entire animal kingdom (Marler 2004). Birds are able to sing at many different pitches, or frequencies, ranging between 1 kHz and 9 kHz (Rheindt 2003). Traffic noise associated with roads is of a lower frequency, generally falling between 0 kHz and 4 kHz (Patricelli

& Blickley 2006; Nemeth & Brumm 2010). The lower frequency components of bird vocalizations may overlap with traffic noise causing acoustic interference, or masking.

Those species that have components of their vocalizations falling in the lower frequency spectrum will experience greater acoustic masking than those species with vocalization components at higher frequencies (Wood & Yezerinac 2006; Parris & Schneider 2009;

Luther & Baptista 2010). 22

The possible impacts of acoustic masking on bird vocalizations are numerous with most research to date focused on impacts occurring during the breeding season. For example, if a male bird’s vocalizations are masked and not heard by others, that male might encounter other males attempting to encroach into his territory, which would distract him from singing to attract mates (Slabbekoorn & den Boer-Visser 2006;

Mockford & Marshall 2009). If a pair is formed and the male does not sing at the correct pitch, the female may leave that male for another with a better quality song (Halfwerk et al. 2011a). Beyond the breeding season, other evolutionary responses may arise from acoustic masking. Imprecision in vocal copying by a juvenile or an adult, caused by traffic noise masking part of a vocalization, can lead to variation in vocalizations. This variation may then lead to the development of dialects that are easier to detect over the noise or may lead to song divergence between populations of species living in urban and nonurban areas (Podos et al. 2004; Slabbekoorn & den Boer-Visser 2006; Luther &

Baptista 2010). Continued divergence between these different populations could lead to reproductive isolation (Slabbekoorn & Ripmeester 2008).

Birds have developed a variety of ways to overcome or avoid this acoustic masking. The most common response of birds to traffic noise is to vocalize at a higher frequency, which can be done by increasing the minimum frequency, the maximum frequency, or the entire vocalization (Rheindt 2003; Dowling et al. 2011). Some species will vocalize louder by increasing amplitude in areas that are close to noisy roads (Lowry et al. 2012); or some species may change the relative amplitude of different frequency 23 components (Wood & Yezerinac 2006). Other species will change the time of day they vocalize in an attempt to not compete with high traffic noise (Fuller et al. 2007). Some species may vary their vocalization structure by changing rate or rhythm, increasing the length, or increasing redundancy in one vocalization before switching to another vocalization type (Brumm & Slater 2006; Mockford & Marshall 2009). Others may alter behaviors associated with vocalizations, moving closer or turning their head towards the receiver, in order to have a better chance of their vocalization being heard (Dooling

2005).

As noted above, most studies on avian vocalizations have been done during the summer months when birds sing in order to attract mates and defend a territory.

However, it is important we understand if traffic noise continues to make an impact on avian vocalizations through the winter, when communication does not directly influence breeding success and birds tend to flock in tight groups rather than compete for territories. Vocalizations during the winter, non-breeding season, occur for different purposes than during the summer breeding season. One main reason for winter vocalizations is to share the location of quality food sources (Freeberg & Lucas 2002).

Food can be scarce after a harsh winter storm and it is beneficial to have every member of a flock healthy in order to look for predators and be able to give warning calls.

Vocalizations during the winter are also used for individual and flock recognition

(Mammen & Nowicki 1981).

This study focuses on two species that vocalize frequently throughout the winter in Nebraska: Black-capped Chickadees (Poecile atricapillus) and American Goldfinches

(Spinus tristis). Little is known about vocal learning in Black-capped Chickadees; however, there is evidence for vocal learning in the development of the “chick-a-dee” call

(Hughes et al. 1998). The “chick-a-dee” call is more common during the winter, nonbreeding months (Ficken et al. 1978) and both males and females give this call.

During these months, the acoustic structure of the “chick-a-dee” call is similar among flock members, giving each flock a flock-specific acoustic signature. That acoustic structure then varies significantly between different flocks (Nowicki 1989). The “chick- a-dee” call is also used for individual recognition (Mammen & Nowicki 1981). Besides recognition, chickadees use this call for mild alarm, food location, contact calls, and to coordinate flock movements (Nowicki 1989). The “chick” part of the call can have different meanings based on its structure when viewed in a sonagram. A chevron-shaped

“chick” can be for used for mobbing or while patrolling a territory (Hurd 1996). A

“chick” without the chevron can be used to indicate the location or availability of food sources (Freeberg & Lucas 2002). More “chick” notes in a call can mean a bird has had first contact with a new seed source, or it could mean a larger, lower threat predator is around (Freeberg & Lucas 2002; Soard & Ritchison 2009). Smaller, higher threat predators are signaled with few or no “chick” notes and significantly more “dee” notes

(Soard & Ritchison 2009).

There have not been many studies conducted on American Goldfinch vocalizations outside of the breeding season when they are known to vocalize for individual recognition. American Goldfinch females recognize individual males by their individually distinctive flight calls (Mundinger 1970). Both males and females give a flight call (“po-ta-to-chip”) when flying alone or in a flock. Male and females that fly in pairs will develop pair-specific flight calls due to vocal imitation (Mundinger 1979). This call may also be given while the bird is perched, usually just before or after flight

(Mundinger 1970). It has been found that each male possesses one to three versions of the flight call, with at least one of those calls being distinctive to that male. Individuals may also change their in-flight call repertoires as a result of learning (Mundinger 1970).

In this study we asked if Black-capped Chickadees and American Goldfinches vocalizing during the nonbreeding season in eastern Nebraska change the minimum and/or maximum frequencies of their vocalizations in the presence of traffic noise.

METHODS

Study design – We recorded vocalizations during the winter, non-breeding season between November and February. We sampled at 12 sites in 2011–2012 with an additional 8 sites in 2012–2013 in eastern Nebraska, between Omaha and Lincoln,

Nebraska (Figure 2, Appendix 1). Recordings started at 8:00 A.M. and ended at 5:00

P.M. for 10 minutes at the start of each hour. 26

Study sites – All study sites had linear, mixed conifer/deciduous woodlands (Appendix

1). Prairies, urban areas, and agriculture fields were the most abundant land cover surrounding the woodland areas. Ten sites were located within 450m of Interstate I-80 corresponding to the highest noise levels within 450m of the interstate (NE Department of Roads 2011; Figures 2 and 3). Ten sites were located within 450m of a less-traveled country road.

Study species – Due to their distinct vocalizations, their abundance in Nebraska during the winter, and their tendency to vocalize multiple times, we chose two species for this study: the Black-capped Chickadee and the American Goldfinch (Table 2). We focused on the “chick-a-dee” call of the Black-capped Chickadee (Figure 4a,b) and the “po-ta-to- chip” call of the American Goldfinch (Figure 4c,d).

Materials – We used Song Meter SM2 automated recording units (ARU) (Wildlife

Acoustics Inc. 2013) to record vocalizations, allowing for concurrent sampling across study sites; this design allowed for sufficient sampling despite low detection probabilities. We attached each ARU to a tree, four to six feet off the ground. Once a month, we changed the batteries and memory card in each recorder. We uploaded the recordings and used Song Scope (Wildlife Acoustics Inc. 2013) to sort and analyze the recordings. We measured, for each vocalization, the minimum and maximum frequency, in Hertz. 27

Data analysis – We compared the minimum and maximum frequencies in the vocalizations between sites with high traffic noise and sites with low traffic noise for each species with a Kruskal-Wallis rank sum test using an alpha value of 0.05. All analyses were done with Program R V3.0 (R Core Team 2013).

RESULTS

A total of 3,208 vocalizations were separated from over 26,000 10-minute sound files. 1227 were American Goldfinch calls and 1,981 were Black-capped Chickadee calls.

1297 vocalizations came from the first field season (2011 – 2012) and 1,911 were from the second field season (2012 – 2013). The average frequency of ambient background noise in sites with low traffic was 766Hz (range = 132Hz–1437Hz). The ambient background noise on the sites with high traffic had an average frequency of 2556Hz

(range = 1437Hz–3687Hz).

Frequency measurements of Black-capped Chickadee vocalizations

A total of 1981 Black-capped chickadee “chick-a-dee” calls were analyzed.

Overall, Black-capped Chickadee vocalizations ranged from 2250–5250Hz. In areas near high traffic noise, the vocalization frequencies ranged from 2562–4750Hz. The minimum frequency of these vocalizations ranged from 2562–4000 Hz and the maximum frequency ranged from 3562–4750Hz. In areas near low traffic noise, the vocalization 28 frequencies ranged from 2250–5250 Hz. The minimum frequency of these vocalizations ranged from 2250–3625Hz and the maximum frequency ranged from 3652–5250Hz. The average maximum frequency of the “chick-a-dee” call between both high and low traffic is 4168Hz and the average minimum frequency is 3056 Hz.

There was no significant difference between the maximum frequencies of chickadee vocalizations near high traffic noise and low traffic noise (Kruskal-Wallis χ2 =

0.1249, df = 1, p = 0.724). However, there was a significant increase in minimum frequencies under high traffic noise (Kruskal-Wallis χ2 = 6.7856, df = 1, p = 0.009)

(Figure 5b, d).

Frequency measurements of American Goldfinch vocalizations

A total of 1,227 American Goldfinch “po-ta-to-chip” calls were analyzed.

American Goldfinch vocalizations ranged from 2187–5500Hz. In areas near high traffic noise, the vocalization frequencies ranged from 2187–5500Hz. The minimum frequency of these vocalizations ranged from 2187–4187Hz and the maximum frequency ranged from 3437–5500Hz. In areas near low traffic noise, the vocalization frequencies ranged from 2187–5312Hz. The minimum frequency of these vocalizations ranged from 2187–

4652Hz and the maximum frequency ranged from 3437–5312Hz. The average maximum frequency of the “po-ta-to-chip” call between both high and low traffic is 4348Hz and the average minimum frequency is 3036 Hz. 29

There was no significant difference between the maximum frequencies of goldfinch vocalizations near high traffic noise and low traffic noise (Kruskal-Wallis χ2 =

3.604, df = 1, p = 0.0576). However, there was a significant different between minimum frequencies in high and low traffic noise (Kruskal-Wallis χ2 = 4.6851, df = 1, p = 0.030)

(Figure 4a, c).

DISCUSSION

Our results show that under high levels of traffic noise, the vocalization frequencies of wintering Black-capped Chickadee and American Goldfinch compress; specifically, the minimum frequencies shift higher. The Black-capped Chickadee “chick- a-dee” call’s minimum frequency shifted almost 190Hz higher (6%) while the American

Goldfinch “po-ta-to-chip” call’s minimum frequency shifted about 50Hz higher (1.6%).

The maximum frequency for both species’ vocalizations did not shift.

The frequency shifts of the minimum frequencies is expected since the lower frequency parts of vocalizations risk overlapping with traffic noise and therefore will suffer from acoustic masking. Birds may attempt to avoid acoustic masking since it can negatively affect both communication attempts and fitness (Rheindt 2003). Vocalizing with a higher minimum frequency is one solution to avoid acoustic masking, and other studies have shown this shift (Slabbekoorn & den Boer-Visser 2006; Wood & Yezerinac

2006; Luther & Baptista 2010). However, these studies did not report on the maximum 30 frequency so it is unclear whether the vocalizations they studied were compressed or if the whole vocalization shifted to a higher frequency.

As shown here, birds are capable of modifying the frequency of their vocalizations in response to traffic noise. It is advantageous to have a vocalization that is heard clearly. Since the maximum frequency of vocalizations by chickadees and goldfinches are outside the frequency range of traffic noise, it is not surprising that the maximum frequencies showed no shift. Not changing the maximum frequency may help maintain the quality of the vocalization and therefore help transmit the correct message

(Nowicki et al. 2002; Wood & Yezerinac 2006; Mockford & Marshall 2009).

Sending clear auditory signals is necessary when foraging in dense cover as many wintering flocks do. Even in a fairly tight flock, it may not be easy to maintain visual contact (Mammen & Nowicki 1981). Vocalizations can inform the receiver of the whereabouts and identity of the sender in order to keep in contact with a mate or flock

(Slabbekoorn & Halfwerk 2009). If part of a vocalization is masked by traffic noise, it may be harder to detect and recognize conspecifics or alarm calls. Males may find it difficult to keep non-flock members outside of the territory without physical interactions

(Mockford & Marshall 2009). Having vocalizations that are clear ensures the correct message is transferred, therefore saving time and energy.

Shifts in vocalization frequencies during the winter may result in identification errors among flock mates, territory intrusions, and the development of dialects.

Vocalization shifts may alter within-flock and between-flock interactions. During the winter months, the chickadees’ “chick-a-dee” calls converge with the rest of their flock in order to recognize one another more quickly (Nowicki 1989). With chickadee flocks, this could possibly lead to a divergence of flocks or harassing a flock mate that has the

‘wrong’ vocalization. It would be valuable for future research to address if convergence rates differ between loud and quiet sites. For sites near low traffic noise, a controlled experiment could be conducted bringing in high traffic noise to see if frequencies shift with the change in anthropogenic noise.

CONCLUSION

For Black-capped Chickadee and American Goldfinches that winter near high traffic noise in Nebraska, our results show a compression of their vocalizations caused by an increase in the minimum frequencies. We suggest this observed change is the result of avoidance of acoustic masking by traffic noise. Since changes in vocalizations may cause complications in identification, flock unification, predator response, and information sharing, more research is needed during the winter months looking at consequences of vocalization shifts within flocks and between flocks.

LITERATURE CITED

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CHAPTER 3 BEHAVIORAL DYNAMICS OF SINGLE- AND MIXED-SPECIES WINTER FLOCKS IN EASTERN NEBRASKA

ABSTRACT

Little is known about the behavioral dynamics of mixed-species flocks of birds during the winter, particularly in the Great Plains. We studied the composition of single- and mixed- species winter flocks to better understand 1) differences in flock species composition, 2) number of vocalizations made based on flock composition, and 3) differences in habitat use by flock member species. Black-capped Chickadees (Poecile atricapillus) and Dark- eyed Juncos (Junco hyemalis) commonly form single- and mixed-species flocks during the winter. We focused on flocks of chickadees and juncos associated with different satellite flock member species. Chickadees form the core of the mixed species flocks while juncos don’t neatly fall into either category: core or satellite. Therefore the species we called satellite species included: White-breasted Nuthatches (Sitta carolinensis),

Downy Woodpeckers (Picoides pubescens), American Robins (Turdus migratorius),

Northern Cardinals (Cardinalis cardinalis), Northern Flickers (Colaptes auratus), and

Blue Jays (Cyanocitta cristata). Approximately 85% of mixed species flocks of chickadees and juncos had satellite species. We found that single species flocks of Black- capped Chickadees tended to be smaller in size and mixed-species flocks of Dark-eyed

Juncos plus individual satellite members tended to be larger in size. Chickadees vocalize more in mixed-species flocks with other satellite members than in flocks that contained 36 juncos or in single-species flocks. There was no significant difference in habitat use by chickadees and juncos occupying single or mixed species flocks.

INTRODUCTION During the winter, many bird species will form single-species flocks within a familiar home range; these flocks will often remain together throughout the winter

(Greenberg 2000). This flocking behavior brings two primary benefits to flock members: reduced predation risk and higher foraging efficiency. Individuals that form flocks may experience reduced per capita predation risks due to 1) enhanced detection of predators through the presence of more observers, 2) a reduced likelihood of falling victim to predation via a “dilution effect”, or 3) flock members successfully mob or distract the predator(s) (Moynihan 1962; Hamilton 1971; Brown & Brown 1996). Members of flocks consequently are able to spend less time scanning for predators and more time foraging with larger flocks being more efficient than smaller flocks (Balph 1979; Caraco 1979;

Brown & Brown 1996). Members of a flock may also share information with one another about the location of food resources; this information can lead to an increase in feeding efficiency resulting in higher rates of survival in flocks compared to individuals (Berner and Grubb 1985; Brown & Brown 1996; Sridhar et al. 2009).

Mixed-species flocks are widely ranging groups of individuals formed by two or more species that forage and associate together (Sridhar et al. 2009). They are usually found in well-defined and defended areas with a relatively small number of individuals of 37 each species per flock (Smith 1984; Greenberg 2001). These mixed-species flocks consist of a gregarious core species that appears to facilitate flock formation, usually one of the

Paridae (tits, chickadees or titmice; chickadees, in this study) and various satellite species

(Austin & Smith 1972; Dolby & Grubb 1999). Satellite species include woodpeckers, nuthatches, jays, and robins. Dark-eyed Juncos fit part of the description of a core species by being small and drab, however there are no studies showing they facilitate flock movement. They are also unlike satellite species since they flock together in single-species flocks. The natural histories of the different species within mixed-species flocks typically are different enough so that mixed-species competition and aggressive interactions are infrequent (Smith 1967; Morse 1970). Birds that do not join a winter flock, or that leave a winter flock, may have a reduced probability of surviving the winter

(Fretwell 1969).

Even in fairly small flocks, it can be difficult to maintain visual contact while foraging in dense cover. Therefore, auditory cues are needed to maintain flock recognition and cohesion (Mammen & Nowicki 1981). Black-capped Chickadees

(Poecile atricapillus) rely heavily on their vocal signals. The “chick-a-dee” vocalization can convey a variety of messages: alarm, flock cohesion, mobbing, food sources, and individual recognition (Ficken et al. 1978; Mammen & Nowicki 1981; Hurd 1996). If, for example, when viewed on a sonogram, the “chick” part of the call is chevron-shaped, it can indicate the individual is patrolling a territory or ready to show mobbing behavior

(Hurd 1996). A “chick” without the chevron can give information about food sources to 38 others (Freeberg & Lucas 2002). More “chick” notes can convey the finding of a new food source, or that a low-threat predator is near, while few or no “chick” notes and more

“dee” notes warns of a higher-threat predator (Freeberg & Lucas 2002; Soard &

Ritchison 2009). Some satellite species may be attracted to the vocalizations of chickadees (Dolby and Grubb 1999) and benefit from the mobbing calls and display anti- predator behavior (Ficken et al. 1978; Sullivan 1984; Hurd 1996). The structure of the

“chick-a-dee” call is similar among the chickadees in a single-species flock but may vary significantly between different chickadee flocks (Nowicki 1989). Chickadees in a mixed species flock may align their calls in order to more easily identify their own flock members. This becomes advantageous in encounters with neighboring flocks as social interaction may be less conspicuous to predators and may allow more time for feeding

(Mammen & Nowicki 1981). Dark-eyed Juncos (Junco hyemalis) in single-species flocks will use multiple vocalizations to 1) increase their inter-individual distance, 2) assess dominance, 3) offer appeasement, 4) in-flight contact, and 5) separation from the flock (Balph 1977). In a flock, they give distinctive “tsip” calls as they take flight in response to a ground predator. These “tsip” calls may serve to draw the birds together and co-ordinate flock movements during escape (Balph 1977).

Chickadees and juncos appear to facilitate flock size within their mixed-species flocks. Flocks may reduce in size if food resources become limiting, for example, during inclement weather (Gottfried & Franks 1975; Balph 1977; Goldman 1980). When resources are abundant, flocks may merge with adjacent flocks for a short period to form 39 larger flocks that are able to feed more efficiently than single birds or smaller groups

(Goldman 1980; Gottfried & Franks 1975). Different species appear to have their own habitat niches within mixed-species flocks. Chickadees and juncos prefer different habitats within their environment. Chickadee flocks prefer open deciduous or mixed forest habitats and are rarely found on the ground (Smith 1967). Juncos will feed intensively on the ground in the morning and late afternoon. High snow accumulation, high winds, or low temperatures, may modify this behavior. Junco flocks roost in conifers for protection and favor areas near cover and water (Gottfried & Franks 1975; Davis

2013).

In this study we investigated single and mixed-species flock dynamics of Black- capped Chickadees and Dark-eyed Juncos at 10 sites in and around Lincoln, Lancaster

County, Nebraska over the winter of 2012–2013. Our first objective was to determine if single-and mixed-species flock size is a function of flock species composition. Our second objective was to determine if the number of Black-capped Chickadee vocalizations is a function of flock species composition. Our third objective was to determine if habitat use of Black-capped Chickadees and Dark-eyed Juncos changes as a function of flock composition.

METHODS

Study sites – We observed single- and mixed-species flock dynamics on trails in

Lancaster County, Nebraska (Appendix 2) from December 2012 to the end of February 40

2013. All of our study sites consisted of trails through linear, mixed conifer/deciduous woodlands. Adjacent to these woodlands were: tallgrass prairie, urban areas, roads, or agriculture fields with no winter harvest.

Study species – The primary study species were the Black-capped Chickadee and Dark- eyed Junco. During the winter, these species are commonly found in forested areas and form both single- and mixed-species flocks. Secondary study species (satellite flock species) were: White-breasted Nuthatches (Sitta carolinensis), Downy Woodpeckers

(Picoides pubescens), American Robins (Turdus migratorius), Northern Cardinals

(Cardinalis cardinalis), Northern Flickers (Colaptes auratus), and Blue Jays (Cyanocitta cristata).

Materials - We used an Olympus LS10, linear PCM recorder with a Sennheiser ME55 short shotgun microphone to record vocalizations and take notes of species present and habitat use along the trails. Sonograms of recordings were viewed using Song Scope from

Wildlife Acoustics (Wildlife Acoustics Inc. 2013).

Methods - We sampled between the hours of 08:00 and 17:00. On each site we walked from 0.5 – 3 miles of trail. If it was snowing, raining, had winds above 15mph, or temperatures below 20 degrees Fahrenheit, we did not collect data. We began recording 41 when a flock of Black-capped Chickadees, a flock of Dark-eyed Juncos, a flock with a mix of the two species, or single individuals of each species was identified. We gathered data for 10 minutes, or until the birds moved out of the field of vision. We recorded the numbers of each species per flock, how frequently Black-capped Chickadees vocalized, when Dark-eyed Juncos vocalized, where in the habitat each species was located, and what other species was in the immediate area (assumed to be satellite members of the flock). Habitat use was divided into tree tops, lower portions of trees, bush tops, low in bushes, and ground. Once we found a flock in an area, we did not return to that area in order to eliminate the bias of recording the same flock multiple times.

Data analysis – We analyzed the number of species per single- and mixed-species flocks with a generalized linear regression (GLM) with Poisson distribution to determine if certain flock compositions favored more or fewer members. We analyzed the number of vocalizations of Black-capped Chickadees with a generalized linear regression (GLM) with Poisson distribution to determine if the number of vocalizations varied based on flock composition. Different flock compositions included: a single-species flock of

Black-capped Chickadees, a mixed-species flock with Black-capped Chickadees and

Dark-eyed Juncos only, a mixed-species flock with Black-capped Chickadees and any other species besides Dark-eyed Juncos, and a mixed-species flock consisting of any species. Dark-eyed Juncos only vocalized after being disturbed and while flying away.

Since multiple juncos would be vocalizing at once, their vocalizations could not be analyzed. Due to a small sample size, we used a Fisher’s exact test to determine if 42 habitat use between single-species flocks of Black-capped Chickadees, single-species flocks of Dark-eyed Juncos, and mixed-species flocks containing both these species differed. Satellite flock species were not included in the analysis of habitat use. All analyses were done with Program R V3.0 (R Core Team 2013).

RESULTS

Flock composition

There were 54 total encounters with single- and mixed-species flocks of Black- capped Chickadees and Dark-eyed Juncos. In any combination of flock with more than one species, satellite species were present in 85% of the occurrences. Satellite members included: White-breasted Nuthatches (Sitta carolinensis), Downy Woodpeckers (Picoides pubescens), American Robins (Turdus migratorius), Northern Cardinals (Cardinalis cardinalis), Northern Flickers (Colaptes auratus), and Blue Jays (Cyanocitta cristata).

Estimated abundance was lowest in flocks of only chickadees and increased as satellite members joined the flock. Flocks with chickadees were smaller than flocks with juncos. As the mixed species flocks of the two gained satellite members, abundance increased. When chickadees and juncos were in the same flock with satellite members, the estimated abundance was similar to flocks of only juncos (Table 3, Figure 6).

Vocalizations

Single-species flocks of Black-capped Chickadees produced the fewest vocalizations. Flocks composed of Black-capped Chickadees, Dark-eyed Juncos, and satellite species produced more chickadee vocalizations. Flocks of Black-capped

Chickadees without Dark-eyed Juncos but with other satellite species had the most chickadee vocalizations (Table 4, Figure 7).

Habitat Use

We found no significant differences in habitat use between single-species flocks of chickadees, single-species flocks of juncos, or mixed-species flocks of the two (p- values > 0.1). Single Dark-eyed Juncos and those in single-species flocks were always in the lower portions of trees and bushes, or more commonly (70% of occurrences), on the ground. Juncos flocking with chickadees were always found below the chickadees in low branches of trees and bushes or on the ground. Chickadees were found most often in the upper portion of trees or high in thick bushes. There was no occurrence of chickadees being on the ground.

DISCUSSION

Flock Composition

We found the numbers of individuals in single- and mixed-species flocks in our study area to be lower than previous studies in other parts of the species’ ranges. For

Black-capped Chickadees, the average flock size was two birds with a maximum of four.

Typical wintering flocks of Black-capped Chickadees in Wisconsin contain four to 10 individuals with an average between six and nine (Ficken et al.1981). Dark-eyed Junco flocks in our study area averaged six individuals with a maximum of 35. Flocks studied by Gottfried and Franks (1975) in Illinois showed groups of 11–13 birds breaking up into smaller groups of two to four birds.

Food depletion rates increase with a larger group size. This may cause dominant individuals within the flock to reduce flock size to maintain high resource (food) availability (Caraco 1979). Austin and Smith (1972) gathered data from several sources, including their own research, to conclude that flocks with 10–17 birds is the optimum size for maximum efficiency in utilizing resources. Our results show a lower average flock size than this within mixed-species flocks. This could be due to resource limitations or a small sample size of mixed flocks (n = 13). There is a need for more information on flocking behavior and territory overlaps between the mixed-species flocks and satellite members.

Vocalizations

We found that chickadees would vocalize significantly less when they were alone or with conspecifics. Vocalizing alarm calls when alone may make it easier for the predator to locate the caller than if multiple birds were vocalizing. Members of single- species flocks of chickadees were seen within close proximity to one another, while juncos and satellite species were usually found in different niches. It could be possible that this close proximity of chickadees to one another is cause for less vocal communication in single species flocks while more vocalizations are needed in mixed species flocks. Chickadees vocalized most around satellite species, not including juncos.

This could be because satellite species do not have potential flock mates to convey information to while juncos have their own communication and may not need to rely on chickadee vocalizations. We are unable to address if these differences are a sampling effect or behavioral effect since sometimes one chickadee was vocalizing with other chickadees around and sometimes more than one chickadee was vocalizing at a time.

Their vocalizations need to be studied more in-depth to determine if different vocalizations occur more or less frequently based on flock composition. The most frequently heard vocalization from the Dark-eyed Juncos was their “tsip” calls as they took flight in response to human or dog presence. These “tsip” calls co-ordinate flock movements in response to predators (Balph 1977). Multiple members of the flock made this vocalization at once; therefore we were unable to analyze their vocalizations as a function of flock composition.

Habitat

There was no significant difference in habitat use based on flock composition of single- or mixed-species flocks of chickadees and juncos. However, we did find habitat use of different species in the flocks to be consistent with previous research. Previous studies show chickadees are found in trees approximately 97% of the time (21% in coniferous and 76.4% in deciduous) and rarely found on the ground (2.6%) (Smith 1967).

Our results show chickadees were always found in trees when alone or in single-species flocks and in trees almost 73% of the time when in mixed-species flocks with juncos.

We never found chickadees on the ground. Juncos can be found in trees and shrubs adjacent to fields during their midday, non-feeding time (Gottfried & Franks 1975).

While feeding, they will look for seeds on the ground, except when there is high snow accumulation (Gottfried & Franks 1975). Dark-eyed Juncos were almost always found in bushes or on the ground. Three out of the five instances a junco was in a tree, there was deep snow covering the ground preventing the birds from utilizing their usual foraging niche. While in mixed species flocks, chickadees and juncos maintain their individual habitat niches and therefore avoid interference.

CONCLUSION

Our results show individual differences in number of birds per species based on flock composition, as well as differences in the number of chickadee vocalizations based on flock composition. There was no significant difference of habitat use based on flock 47 composition. Our results support the idea that satellite flock species use Black-capped

Chickadee vocalizations, most likely for the benefits of predator defense and food information. A more in-depth analysis of the wide variety of chickadee vocalizations is necessary in order to understand the differences in occurrence of each vocalization type within single- and mixed-species flocks.

LITERATURE CITED

Austin, G. T. & Smith, E. L. 1972: Winter foraging ecology of mixed insectivorous bird flocks in oak woodland in southern Arizona. The Condor 74, 17-24. Balph, M. H. 1997: Winter social behavior of Dark-eyed Juncos: communication, social organization, and ecological implications. Animal Behaviour 25, 859-864. Balph, M. H. 1979: Flock stability in relation to social dominance and agnostic behavior in wintering Dark-eyed Juncos. Auk 96, 714-722. Berner, T. O. & Grubb Jr., T. C. 1985: An experimental analysis of mixed-species flocking in birds of deciduous woodland. Ecology 66, 1229-1236. Brown, C.R. & Brown, M. B. 1996: Coloniality in the Cliff Swallow: the effect of group size on social behavior. University of Chicago Press, Chicago, IL. Caraco, T. 1979: Time budgeting and group size: a theory. Ecology 60, 611-617. Dolby, A. S. & Grubb Jr., T. C. 1999: Functional roles in mixed-species foraging flocks: a field manipulation. Auk 116, 557-559. Ficken, M. S., Ficken, R. W., & Witkin, S. R. 1978: Vocal repertoire of the Black- capped Chickadee. Auk 95, 34-48. Ficken, M. S., Witkin, S. R., & Weise, C. M. 1981: Associations among members of a Black-capped Chickadee flock. Behavioral Ecology and Sociobiology 8, 245-249. Freeberg, T. M. & Lucas, J. R. 2002: Receivers respond differently to chick-a-dee calls varying in note composition in Carolina chickadees (Poecile carolinensis). Animal Behavior 63, 837-845. Fretwell, S. 1969: Dominance behavior and winter habitat distribution in juncos (Junco hyemalis). Bird Banding 40, 1-25. Goldman, P. 1980: Flocking as a possible predator defense in Dark-eyed Juncos. Wilson Bulletin 92, 88-95. Gottfried, B. M. & Franks, E. C. 1975: Habitat use and flock activity of Dark-eyed Juncos in winter. The Wilson Bulletin 87, 374-383. Greenberg, R. 2001: Birds of many feathers: the formation and structure of mixed-species flocks of forest birds. In: Boinski, On the move: how and why animals travel in groups. (S. and Garber, P. A. eds.), pp. 521-558. University of Chicago Press, Chicago, IL. Hamilton, W.D. 1971: Geometry for the selfish herd. Journal of Theoretical Biology. 31, 295-311. 49

Hurd, C. R. 1996: Interspecific attraction to the mobbing calls of Black-capped Chickadees (Parus atricapillus). Behavioral Ecology and Sociobiology 38, 287- 292. Mammen, D. L. & Nowicki, S. 1981: Individual differences and within-flock convergence in chickadee calls. Behavioral Ecology and Sociobiology 9, 179-186. Morse, D. H. 1970: Ecological aspects of some mixed-species foraging flocks of birds. Ecological Monographs 40, 119-168. Moynihan, M. 1962: The organization and probable evaluation of some mixed species flock of Neotropical birds. Smithsonian Miscellaneous Collections 143, 1-140. Nowicki, S. 1989: Vocal plasticity in captive black-capped chickadees: the acoustic basis and rate of call convergence. Animal Behavior 37, 64-73. Smith, S. M. 1967: An ecological study of winter flocks of Black-capped and Chestnut backed Chickadees. The Wilson Bulletin 79, 200-207. Smith, S. M. 1984: Flock switching in chickadees: why be a winter floater? The American Naturalist 123, 81-98. Soard, C. M. & Ritchison, G. 2009: ‘Chick-a-dee’ calls of Carolina Chickadees convey information about degree of threat posed by avian predators. Animal Behaviour 78, 1447-1453. Sridhar, H., Beauchamp, G., & Shanker, K. 2009: Why do birds participate in mixed-species foraging flocks? A large-scale synthesis. Animal Behaviour 78, 337-347. Sullivan, K. A. 1984: Information exploitation by downy woodpeckers in mixed-species flocks. Behaviour 91, 294-311. Wildlife Acoustics Inc. 2013: 970 Sudbury Road Concord, MA 01742-4939. www.wildlifeacoustics.com.

Table 1. List of different mitigation efforts to reduce the impacts of traffic and traffic noise on avian species.

Mitigation Techniques

On Cars Better engine features Quieter mufflers Quieter vehicle aerodynamics Different tires New brake systems On Roadways Road barriers Depressed highways Elevated highways Underground tunnels Speed limitations and restrictions Alternate road routes Key road closures during breeding season Near Roadways Screens to keep birds away from roads Barriers to force birds to fly over roads Land buffers next to roads Soil berms Planning Better urban planning on roads Noise tax based on season, type of car, tires, and speed

Table 2. Number of vocalizations obtained for Black-capped Chickadees and American Goldfinches at each study site.

Site and number of vocalizations saved for each species

American Site Goldfinch Black-capped Chickadee

Near I-80 (high traffic noise)

AUK 33 510

OAK 21 29

HFS 18 81

OPPD 2 56

WARNER 39 54

TWIN 29 32

UNL 100 32

CAW 55 26

WAV 60 87

DAKOTA 19 0

Away From I-80 (low traffic noise)

MEAD 110 58

LIZ 30 26

MO 51 33

JB 90 250

CZECK 0 9

PP 133 347

NMP 131 57

SMM 83 0

CGF 164 181

WW 59 113

Table 3. Results from the generalized linear regression model on flock size as a function of flock composition.

Flock size as a function of species composition Estimate SE Z- Value Pr(>|Z|) Single species flocks of chickadees -1.80 0.283 -6.375 0.00 Single species flocks of juncos -0.38 0.148 -2.544 0.01 Mixed species flocks with chickadees and satellite -0.74 0.156 -4.756 0.00 members (no juncos)

Mixed species flocks with juncos and satellite 1.48 0.149 9.900 0.00 members (no chickadees)

Mixed species flocks with chickadees, juncos, and 2.14 0.094 22.595 0.00 satellite members

Table 4. Results from the generalized linear regression model on chickadee vocalizations as a function of flock composition.

Chickadee vocalizations as a function of flock composition Estimate SE Z Value Pr(>|Z|) Single species flock of chickadees -2.03 0.17 -11.78 0.00

Mixed species flock with chickadees, juncos, and satellite members -1.56 0.15 -10.24 0.00

Mixed species flock with chickadees and satellite members (excluding juncos) -0.80 0.14 -5.85 0.00

Figure 1. Years of publication for studies that relate to traffic effects on avian species. Papers obtained from the Web of Science following a key word search for the terms avian, communication, vocalization, traffic, roads, and noise.

Figure 2. Aerial map of eastern Nebraska showing all 20 study sites. Red line is Interstate 80. White lines are minor roads.

Figure 3. Noise data from the Nebraska Department of Roads shows that significant noise levels drop off around 450 meters from the center of the outside lane of I-80.

Figure 4. Sonograms showing (a) “chick-a-dee” call in high traffic noise. (b) “chick-a- dee” call in low traffic noise. (c) “po-ta-to-chip” call in high traffic noise. (d) “po-ta-to- chip” call in low traffic noise.

a b

c d

Figure 5. (a) Maximum frequency ranges of American Goldfinch vocalizations in high and low traffic noise areas. (b) Maximum frequency ranges of Black-capped Chickadee vocalizations in high and low traffic noise areas. (c) Minimum frequency ranges of American Goldfinch vocalizations in high and low traffic noise areas. (d) Minimum frequency ranges of Black-capped Chickadee vocalizations in high and low traffic noise areas.

Figure 6. Estimated flock size as a function of flock composition. All refers to flocks of chickadees, juncos, and satellite members. BCCHonly refers to flocks with only chickadees or lone chickadees. BCCHwsat refers to chickadees with only satellite members, no juncos. DEJUonly refers to flocks of juncos only or lone juncos. DEJUwsat refers to flocks of juncos with satellite members, no chickadees.

Figure 7. Estimated number of vocalizations as a function of flock composition. All refers to flocks of chickadees, juncos, and satellite members. BCCHonly refers to flocks with only chickadees or lone chickadees. BCCHwsat refers to chickadees with only satellite members, no juncos.

Appendix 1. Description and GPS coordinates of study sites for Chapter 2

Study sites near I-80 include:

AUK: This privately owned backyard is located in Omaha, south-east of Pacific Street and I-80, in Douglas County. The neighborhood has a wide riparian area with hardwood trees that extends through the backyards of multiple properties.

Oak Hills Country Club (OAK): A golf course in Omaha, in Douglas County, this site is located on the north side of I-80. Most of the area is covered in mowed grass patches with linear oaks (Quercus sp.) and conifers next to the interstate. Scattered around the area are small patches of oaks and other deciduous trees as well as a small lake. 41°11’27.87”N 96°06’06.19”W

Holy Family Shrine (HFS): This site is in Sarpy County on the south side of I-80. The property is dominated by upland tallgrass prairie with a large patch of riparian deciduous woodland on the east side. This woodland mainly has Eastern Cottonwood (Populus deltoides), elm (Ulmus sp.), Green Ash (Fraxinus pennsylvanica), and Boxelder (Acer negundo) with woody vegetation in the understory. 41°04’41.81”N 96°16’42.23”W

OPPD Arboretum (OPPD): This 26-acre accredited Arboretum is located in Omaha, in Douglas County on the west side of I-80. It was constructed in 1992 to help the public learn proper planting of trees and shrubs near power lines. In total there are 208 different species of trees as well as 201 species of shrubs. 41°16’44.79”N 96°04’37.03”W

Warner WMA (WARNER): This site in Lancaster County is dominated by upland tallgrass prairie with pockets of both deciduous and coniferous trees. Near the western edge is a thick, deciduous woodland with Eastern Red Cedars (Juniperus virginiana) mixed in. This site was added the second year of the study. 40°53’58.47”N 96°35’13.82”W

Twin Lakes WMA (TWIN): This site in Seward County is dominated by thick woodlands with species such as: Eastern Red Cedar, Green Ash, Red Mulberry (Morus rubra), Siberian Elm (Ulmus pumila), and dogwood (Cornus sp.). The grass within the woodlands is Smooth Brome (Bromus inermis) and Reed Canary Grass (Phalaris arundinacea). 40°49’20.53”N 96°58’03.89”W

University of Nebraska- Lincoln Technology Park (UNL): This site in Lincoln, in Lancaster County, is located on the north side of I-80. It has a Smooth Brome (Bromus inermis) field that leads into a mix of tallgrass and deciduous trees near a lake. Near the western side of the site, the trees become a thick deciduous woodland with scattered conifers. 40°51’16.87”N 96°43’34.38”W

Camp-A-Way RV and Camping Area (CAW): This site in Lincoln, in Lancaster County, is on the south side of I-80. It is crisscrossed by multiple roadways leading to different RV camping areas. Between the roads is mowed grass and along the edges of the site are deciduous trees and a small creek. 40°51’33.33”N 96°43’06.04”W

WAV: This site is private lands on the outskirts of Waverly in Lancaster County. Mixed in with sparse housing are bare agriculture fields, mowed grass, and linear hardwood tree lines. This site was added the second year of the study.

Dakota Springs WMA (DAKOTA): This site in Lancaster County is dominated by upland tallgrass prairie with pockets of Green Ash, American Elm (Ulmus americana), Eastern Cottonwood, Common Hackberry (Celtis occidentalis), Red Mulberry, dogwood, and Eastern Red Cedar. It is next to private agriculture fields with no winter harvest. This site was added the second year of the study. 41°53’35.57”N 96°40’11.32”W

Study sites off of I-80 include:

Mead (MEAD): This site is a University of Nebraska – Lincoln research area located in Saunders County. The south-west corner is an old seed orchard with oaks, walnuts (Juglans sp.), White Poplar (Populus alba), Sycamore (Platanus occidentalis), Green Ash, Honey Locust (Gleditsia triacanthos), and Black Cherry (Prunus serotina). Surrounding this area is unplanted agriculture lands broken up by windbreaks of Scotch Pine (Pinus sylvestris), Eastern Red Cedar, Green Ash, and Austrian Pine (Pinus nigra). This site was added the second year of the study. 41°08’51.07”N 96°30’01.59”W

LIZ: This site is a private organic farm located 2.5 miles north-west of Abie in Butler County. South of the road is a row of dogwoods mixed with deciduous trees with another row of coniferous trees to the south. There is a grazed field to the south of the conifers. To the north of the road is unplanted agriculture land.

MO: This site is a private organic farm located .75 miles outside Prague in Saunders County. It has linear deciduous woodlands next to unplanted agriculture fields.

JB: This site is a private organic farm 1 mile outside Weeping Water in Cass County. The surrounding area is mainly agriculture lands with no winter harvest and small pockets of riparian areas and woody shrubs.

Czeckland Lake (CZECK): This site in Saunders County has upland tall grass prairie with linear rows of dogwood shrubs, deciduous riparian trees, and conifers. This site was added the second year of the study. 41°20’09.99”N 96°49’35.50”W

Prairie Pines (PP): This site is in Lincoln in Lancaster County. It has a mix of upland tallgrass prairie with deciduous riparian woodlands. The site has a large number of conifers and is surrounded by agriculture lands with no winter harvest. 40°50’39.80”N 96°34’02.15”W

Nine-Mile Prairie (NMP): This site is a 230-acre upland tallgrass prairie in Lancaster County and is owned by the University of Nebraska Foundation. Extending into the prairie are riparian woodlands composed of elm, ash (Fraxinus sp.), and Eastern Cottonwood. This site was added the second year of the study. 40°52’07.68”N 96°48’31.21”W

Frank Shoe-maker Marsh (SMM): This site is located in Lincoln in Lancaster County. It is predominantly upland tallgrass prairie with large patches of deciduous woodlands with trees such as: Green Ash, American Elm, Eastern Cottonwood, Boxelder, Common Hackberry, Red Mulberry, Black Cherry, dogwood, Honey Locust, buckthorn (Rhamnus sp.), and Eastern Red Cedar. This site was added the second year of the study. 40°54’40.48”N 96°40’55.32”W

Common Good Farm (CGF): This site is a private organic farm 1.5 miles outside of Raymond in Lancaster County. It is mainly agriculture and grazed lands with no winter harvest with linear hardwood and conifer windbreaks 2-3 trees thick.

Wildwood Lake WMA (WW): This site is in Lancaster County. Surrounding the lake are linear strips of deciduous riparian woodlands, agriculture lands with no winter harvest, and mowed grass paths. This site was added the second year of the study. 41°02’44.14”N 96°50’51.58”W

Appendix 2. Description and GPS coordinates of study sites for Chapter 3

2 miles of the Mopac Trail: This concrete trail runs east-west through the center of

Lincoln. The 2 mile section in the study is between 40th and 66th Streets. The trail is surrounded on either side by a thin line of deciduous trees with buildings, residential, or parks beyond that.

40°49’23.87”N 96°39’37.27”W

5 miles of trails around Branched Oak State Recreation Area: This site, north-west of Lincoln, has dirt paths on the south-west side of Branched Oak Lake that meander in and out of mixed coniferous/deciduous woodlands.

40°57’32.01”N 96°53’07.50”W

Nine Mile Prairie: This site is a 230-acre upland tallgrass prairie in Lancaster County and is owned by the University of Nebraska Foundation. There are mowed grass paths that follow the contour of elm, ask, and cottonwood riparian woodlands as well as paths along the perimeter of the prairie.

40°52’07.68”N 96°48’31.21”W

Trails within the Nature Center and parts of Pioneers Park: Pioneers Park is located on the south-west corner of W. Van Dorn Street and S. Coddington Avenue in Lincoln.

It has pockets of conifers as well as pockets of deciduous trees with concrete streets running through it. The Nature Center is in the south-west corner of the park. The Nature

Center has woodchip paths that wind through a mixed conifer/deciduous woodland and plant/animal exhibits.

40°46’25.38”N 96°46’32.34”W 65

Frank Shoemaker Marsh: This site is located in north Lincoln and has dirt and grass trails throughout. It is predominantly upland tallgrass prairie with large patches of deciduous woodlands.

40°54’40.48”N 96°40’55.32”W

Bluestem Lake State Recreation Area: This site, south-west of Lincoln, has concrete roads around Bluestem Lake with multiple parking lots surrounded by mixed conifer/deciduous woodlands and woody underbrush.

40°32’36.62”N 96°47’56.37”W

10 miles of the Jamaica North Trail: The Jamaica North Trail runs north-south along the west side of Lincoln. We chose multiple sections of this white rock trail near Van

Dorn Street, Old Cheney Road, and Saltillo Road. Surrounding the trail on the west side is a thin line of deciduous trees with thicker, up to half of a mile, patches of woodland with bare agriculture fields beyond that. The east side has a mix of any of the following: bare agriculture fields, residential, business parks, or up to half a mile of deciduous woodland.

Old Cheney Road 40°45’17.50”N 96°42’49.40”W

Saltillo Road 40°41’50.35”N 96°41’18.64”W

Van Dorn Street 40°47’04.73”N 96°43’10.77”W