Quantifying singing behaviour
We generated a waveform and spectrogram (Hamming window, FFT = 512
samples, 87.5% overlap) for all 15-min recordings using Raven Pro sound
analysis software (v1.5; Cornell Laboratory of Ornithology, Ithaca, NY).
On each spectrogram, we drew cursor boxes (hereafter, “annotated”)
around vireo songs that were visible on the spectrogram and waveform
(i.e., clear pulses in amplitude). In some instances, songs from
non-focal males could be seen and heard in the background of the
recording, but these were easily distinguished from the subject’s songs
either because they were relatively faint or because they did not match
the known vocal repertoire of the subject. We defined songs as
vocalizations comprising one or more elements, where elements of the
same song are separated by < 0.5 s and those of different
songs are separated by ≥ 0.5 s (Mejías et al. 2020, Mejías et al. 2021).
Our song definition did not hinder our ability to identify discrete
songs and rambling songs (Figure 2), as defined by Bradley (1980:
Figures 1B, 2A, B, and C). In total, we annotated 17,682 vireo songs
from 430 15-min recordings. To make our 15-min measure of vocal activity
comparable to previous studies, we multiplied the number of discrete and
rambling songs in each recording session by four to obtain hourly rates.