Across populations, animals that inhabit areas with high anthropogenic noise produce vocalizations that differ from those inhabiting less noisy environments. Such patterns may be due to individuals rapidly adjusting their songs in response to changing noise, but individual variation is seldom explored. We tested the hypothesis that male house wrens (Troglodytes aedon) immediately adjust their songs according to changing noise, and that social context further modifies responses. We recorded songs, quantified noise, and defined social context within pairs as female fertile status and between males as number of conspecific neighbors. We used a reaction norm approach to compare song trait intercepts (between-male effects) and slopes (within-male effects) as a function of noise. Individuals immediately adjusted song duration in response to changing noise. How they achieved adjustments varied: some sang shorter and others longer songs with greater noise, and individuals varied in the extent to which they adjusted song duration. Variation in song duration could be affected by competition, as between-male noise levels interacted with number of neighbors to affect syllable duration. Neither within- nor between-male noise effects were detected for frequency traits. Rather males with fertile mates sang lower frequency songs and increased peak frequency with more neighbors. Among males, social context but not noise affected song frequency, whereas temporal structure varied between and within individuals depending on noise and social factors. Not all males adjusted signals the same way in response to noise and selection could favor different levels of variation according to noise.
Audio recordings of focal males were made at their nest boxes using Wildlife Acoustics Song Meter 2 units (SM2; Maynard, MA; 44.1 kHz sample frequency, 16-bit, .wav format), by attaching a microphone (Wildlife Acoustics: SMX-II model) directly to the nest box pole and connecting the microphone to SM2 unit with a 3-m cord. Units were pre-programmed to begin recording one hour before sunrise (Eastern Standard Time, EST) and to continue recording for five hours. We used Avisoft SASLab Pro v5.2 (R. Specht, Glienicke/Nordbahn, Germany) to label 25 songs from 36 males (Flat top window, 512 FFT length, 93.75% overlap, 0.725 ms time resolution). We used the automated parameter window (-20 dB threshold) to extract minimum frequency (Hz), maximum frequency (Hz), peak frequency (Hz), bandwidth (Hz), and song duration (s) from each song, song section, and syllable.