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Song perception in communication networks

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Abstract
Communication is a cornerstone of animal behavior and mediates myriad interactions pertaining to survival and reproduction. For animals that communicate acoustically, signals are carried to multiple receivers in what is described as communication networks. In my dissertation, I explore how songbirds and their songs are perceived and used in networks. First, I examine a dilemma many animals face when communicating in a network – how do animals contend with overlapping, conspecific noise? Using a playback experiment in the field, I document Black-capped Chickadees (Poecile atricapillus) shifting the frequency of their song in the presence of overlapping noise. Next, I examine song function in communication networks, and evidence for social eavesdropping. Using Chipping Sparrows (Spizella passerina), I first explored what song parameters territorial males find salient. I found residents are attentive to variation in trill rate or how quickly notes are repeated per unit time. In a parallel experiment, I found no evidence that males attended to a related song parameter – the total frequency range covered in a song, although I did find evidence these two parameters trade-off. In further work, I found males are attentive to the song performance of their neighbors, and occasionally cooperate to help expel intruders. My work reveals that males cooperate under specific circumstances; when the resident under attack has a relatively slow song, and the simulated intruder has a comparatively fast song. These field studies suggest neighbor-turned-allies are most likely to help nearby residents when the intruder is relatively threatening, and suggests males may eavesdrop on their neighbors. Finally, I surveyed Chipping Sparrow neighborhoods throughout Western Massachusetts and was unable to detect any effect of social factors on territory choice. Together, my work describes some disadvantages and advantages songbirds face in communicating in networks, and contributes to our understanding of the importance of networks in signal evolution.
Type
dissertation
Date
2016-05
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