An analysis of avian vocal performance at the note and song levels

AbstractSexual displays that require extreme feats of physiological performance have the potential to reliably indicate the signaller’s skill or motivation. We tested for evidence of performance constraints in Adelaide’s warblers (Setophaga adelaidae) songs. At the note level, we identified three trade-offs with well-defined limits. At the song level, we identified two trade-offs, but their limits were less well-defined than the note-level limits. Trade-offs at both levels suggest that song structure is constrained by limits to the speed of both frequency modulation (while vocalizing and between notes) and respiration.  Performance metrics derived from the observed limits to performance varied moderately among individuals and strongly among song types. Note-level performance metrics were positively skewed, as predicted by the hypothesis that performance is constrained. We conclude that physiological limits on frequency modulation and respiration constrain song structure in male Adelaide’s warblers. Further work is needed to determine whether receivers respond to natural levels of variation in performance, and whether performance correlates with singer quality or motivation.
MethodsStudy species Adelaide’s warbler is a socially monogamous insectivore endemic to Puerto Rico and Vieques. Mated pairs maintain all-purpose territories throughout the year (Toms 2010). Male songs are frequency modulated trills (Fig. 2). Individual males sing repertoires of song types (avg. ≈ 23 songs), many of which are shared with other males (Staicer 1991; Kaluthota et al. 2019). Each male’s repertoire comprises two categories, A and B, which are characterized by distinct times of delivery, song rates, and song switching frequencies (Staicer 1991; Kaluthota et al. 2019). The individual notes comprising songs are structurally simple, with almost all of the energy concentrated in the fundamental frequency. There exists considerable among-note variation in duration, frequency, and frequency modulation (Fig. 2). Ethics This research was approved by the Institutional Animal Care and Use Committee at the University of Puerto Rico, Mayagüez (17 September, 2010). It adheres to the ASAB/ABS Guidelines for the use of animals in research. Birds were captured under D.M.L.’s federal bird banding permit (no. 23696). The U.S. Fish and Wildlife Service granted permission to work at the Cabo Rojo Wildlife Refuge (permit 2012-01). Recording and scoring We recorded nine mated male Adelaide’s Warblers at the Cabo Rojo National Wildlife Refuge (US Fish and Wildlife Service) during the breeding season between March and June, 2012. All subjects wore unique combinations of coloured leg bands, allowing recordists to unambiguously identify individuals. Each male was recorded on four days, from 45 minutes before sunrise until 2 hours and 45 minutes after sunrise. Consecutive recordings of a given male were separated by at least four days, except on two occasions when recordings were made on consecutive days because of logistical constraints. Recordings were made with Marantz PMD 661 digital recorders and Sennheisser ME67 shotgun microphones (file format = wav, sampling rate = 44.1KHz, bit depth = 16 bits). This is the same set of recordings used in a previous study of short-term variation in song performance (Schraft et al. 2017), a methods paper on song sequences (Hedley et al. 2018), and an analysis of singing modes (Kaluthota et al. 2019). We visualized recordings as sound spectrograms in Syrinx PC v.2.6 (J. Burt, Seattle, WA; Settings: Blackman window, transform size = 1024 points). Each song recording from a focal male was assessed for recording quality. One person (D.M.L.) assigned song recordings to song types. A previous study that used the same recordings estimated the inter-rater reliability of song type scoring to be 100% within an individual bird, and 87% among individuals (Kaluthota et al. 2019). We only used high-quality recordings (high signal-to-noise ratio, minimal overlap with other sounds) for song measurements. High quality song recordings were analysed in Luscinia v2.14 (max. freq. = 10kHz, frame length = 5ms, time step = 1ms, dynamic range = 35 dB, dynamic equalization = 100ms, de-reverberation = 100%, de-reverberation range = 100ms, high pass threshold = 1.0kHz, noise removal = 10dB; Lachlan 2007). We loosely outlined the trace of each note with a stylus on a touchscreen monitor, and Luscinia’s algorithms identified the signal and rejected background noise. The following note-level acoustic variables were output to a spreadsheet: start time, end time, maximum peak frequency, and minimum peak frequency. Luscinia offers several frequency metrics. We chose peak frequency because visual inspection of spectrograms showed that it tracked the fundamental frequency better than the fundamental frequency metric. Analysis: trade-offs The note-level analysis omitted the one or two low-amplitude notes that began some songs and the final note...