DOI: 10.5061/dryad.fttdz090p
title: Effect sizes of divergence in urban noise and song minimum frequency of grey-cheeked fulvettas Alcippe morrisonia morrisonia

description: Noise pollution, one of the most prominent features of urbanization, is an
 important factor influencing the vocal behavior of urban wildlife. Studies
 have reported that many songbirds raise their song minimum frequencies in
 response to urban noise. It has been proposed that this increased minimum
 frequency (IMF) of songs is an adaptation that allows urban populations to
 cope with the masking effect of noise pollution. However, urban
 populations of some songbirds do not exhibit significant IMF compared with
 nonurban populations; thus, the notion that IMF is an adaptation to urban
 noise has been questioned. Furthermore, the effects of IMF might be
 influenced by both noise levels and the acoustic structures of songs.
 Here, we employed dichotomous and gradient effect size approaches to
 investigate IMF regarding two distinct acoustic structures (whistled and
 harmonic) in songs of six grey-cheeked fulvetta (Alcippe morrisonia
 morrisonia) populations in Taiwan, three with high noise pollution and
 three with low noise pollution. We found that when using the dichotomous
 approach, paired populations with significant divergence in noise levels
 exhibited weak or insignificant divergence in the minimum frequencies for
 both whistled and harmonic phrases. In contrast, we found that when using
 the gradient approach, the effect size of noise-level divergence was
 strongly correlated with the effect size of divergence in the minimum
 frequency of the harmonic phrase and only moderately correlated with the
 effect size of divergence in the minimum frequency of the whistled phrase.
 These findings suggest that noise pollution has a more pronounced effect
 on the divergence in the minimum frequency of harmonic phrases used in
 short-range communication compared to the whistled phrases used in
 long-range communication. We conclude that for population comparisons on
 the IMF, adopting a gradient approach could provide insights into the
 impact of noise pollution on the acoustic structures of songs across
 various communication ranges.
description: For noise measurements: The present study aimed to investigate the
 effect of noise from a population perspective rather than an individual
 territory perspective. Thus, we measured site noise instead of territory
 noise (Derryberry and Luther 2021). To represent the site noises that the
 population had been exposed to during the study period, we conducted noise
 level sampling at six sites in 2020, the middle year of the study period.
 Measurements of the
 maximum noise levels (maximum hold function, C-weighting function on a
 Sound Level Meter TES-1350, TES, Taiwan) were collected at locations that
 were at least 100 m apart along the song-recording route (BP site: 9
 locations; CM site: 28 locations; MS site: 13 locations; NS: 11 locations;
 SM site: 10 locations; SP site: 18 locations) following the procedures
 detailed in Shieh et al. (2016). We held the sound level meter
 horizontally at approximately 1.5 m during each noise measurement. We
 turned the meter 360° in a clockwise direction to measure the noise from
 all directions and to measure the maximum noise levels within about 30
 seconds. We measured the maximum noise levels at each location three times
 and averaged the three measurements for further
 analysis. For minimum frequency
 measurements: We applied a high-pass filter originally at 2.0
 kHz and adjusted the high-pass frequency for each individual to produce
 spectrograms that minimized the unwanted noise components. From the
 recordings, we produced spectrograms with the following parameters:
 sampling frequency = 22.05 kHz, FFT = 512, Hamming window, frequency
 resolution = 43 Hz, and time resolution = 2.9 ms. We measured the minimum
 frequency of each phrase on these spectrograms using the following
 procedures. First, on the whole phrase level, we visually identified the
 syllable in each phrase with the lowest frequency and manually labeled the
 syllable on the spectrogram; if two syllables in the same phrase had close
 frequency ranges, a frequency cursor was added to the spectrogram and the
 syllable with the lowest frequency was quickly identified. Then, on the
 syllable level, the minimum frequency of the labeled syllable was
 automatically measured by the Automatic Parameter Measurements setup (peak
 frequency for the minimum parameter of entire element) in Avisoft-SASLab
 Pro v5.2.
description: # Effect sizes of divergence in urban noise and song minimum frequency of
 grey-cheeked fulvettas Alcippe morrisonia morrisonia
 [https://doi.org/10.5061/dryad.fttdz090p](https://doi.org/10.5061/dryad.fttdz090p) The dataset contains the original data of noise measurements and minimum frequency values. ## Description of the data and file structure There are two sheets in the file. The 'noise measurement' sheet is for noise measurements at six sites. The 'minimum frequency' sheet is for minimum frequency values at six sites during 2019-2021 for harmonic and whistled phrase respectively. The noise measurement unit is dB and the minimum frequency unit is Hz. H: harmonic phrase; W: whistled phrase.