Urban expansion has increased pollution including both physical (e.g., exhaust, litter) and sensory (e.g., anthropogenic noise) components. Urban avian species tend to increase the frequency and/or amplitude of songs to reduce masking by low frequency noise. Nevertheless, song propagation to the receiver can also be constrained by the environment. We know relatively little about how this propagation may be altered across species that (1) vary in song complexity and (2) inhabit areas along an urbanization gradient. We investigated differences in song amplitude, attenuation, and active space, or the maximum distance a receiver can detect a signal, in two human-commensal species: the house sparrow (Passer domesticus) and house finch (Haemorhous mexicanus). We described urbanization both discretely and quantitatively to investigate the habitat characteristics most responsible for propagation changes. We found mixed support for our hypothesis of urban-specific degradation of songs. Urban songs propagated with higher amplitude; however, urban song fidelity was species-specific and showed lowered active space for urban house finch songs. Taken together, our results suggest that urban environments may constrain the propagation of vocal signals in species-specific manners. Ultimately this has implications for the ability of urban birds to communicate with potential mates or kin.

This data was collected for the manuscript titled "Urbanization alters the song propagation of two human-commensal songbird species."

Data were originally .wav files collected during a propagation study. The .wav files were clipped so that each file contained a single exemplar with 0.1 seconds of silence before and after the exemplar. Each single-song .wav file was imported into Raven Pro to calculate active space using the "batch correlator" function. Within each site and exemplar, we cross correlated the song at 1m to the song at each consecutive distance. We also corss correlated the song at 1m to the background noise at each site. To determine active space from the cross correlations, we created a linear line of best fit between the cross correlation value and distance (5m-100m) for each stimulus. We then determined the distance that the regression line intersected with the background noise (a horizontal line over distance). We defined the distance of the intersection point as active space. 

The single-song .wav files were also imported into Praat to calculate amplitude. Before calculation, songs were filtered so that any sound more than 100 Hz below the minumum frequency of the song was removed. Then, amplitude was calculated in Praat using the "get intensity" function. We calculated attenuation in excel as the difference in amplitude at 1m (the reference signal) to each consecutive distance (5m, 10m-100m in 10m increments).