Open Collections

Description

<b>Abstract</b><br/>

<em>Setophaga townsendi </em>is a species of wood-warbler (family Parulidae) in northwestern North America that has a geographic structure in the mitochondrial and nuclear genomes: while interior populations have differentiated mitonuclear ancestry from the sister species <em>S. occidentalis</em>, coastal populations have a mix of inland and <em>S. occidentalis </em>mitonuclear ancestries. This coastal-to-inland transition in genomic ancestry raises the possibility of similar geographic structure in phenotypic traits, especially those involved in mate choice. Using qualitative and multivariate approaches, we investigated whether there is a sharp transition between coastal and inland populations in both songs and nuclear DNA. We find there is a shallow geographic cline in the Type I song but not in the Type II song. Nuclear DNA shows a gradient between the coast and inland. There is little correlation between variation in song and the isolation-by-distance pattern in the nuclear DNA. The learned songbird song is shaped by both genetic and cultural processes. There has been a debate on whether song learning promotes or slows down population differentiation. By comparing the within-species variation in song and genetic structures, we can expand our understanding of the dynamic interplay between mating signals and population differentiation.</p>; <b>Methods</b><br />

<strong>Data collection</strong></p>

Song recordings were collected at 30 locations across British Columbia from May to July of 2017, using a Marantz PMD660 digital recorder and an Audio-Technica 815a Shotgun microphone. Recordings were typically eight to ten minutes long and consisted of ten to forty songs. For songs recorded after June 25th, a playback of song recordings was used to encourage birds to sing. We designed playbacks to consist of three song variants from different regions of the <em>S. townsendi</em> range, to avoid playback matching. </p>

This dataset consists of songs of 249 birds (180 from field recordings, 39 from Xeno-Canto, and 30 from Macaulay Library). For each bird, songs were characterized into types based on visual similarity and the results of Janes and Ryker (2016) and Janes (2017). We classified the clear song as the Type I song (i.e., used more in female attraction), and the buzzy song as the Type II song (i.e., used more in territorial defense).</p>

We randomly selected three numbers from the total in each recording. These three songs were analyzed as follows: Spectrograms were visualized in Raven Pro 1.4 using Hann spectrogram windows with 512 samples, discrete Fourier transform (DFT) size of 512 samples, hop size of 5.6 ms, sampling frequency of 44.1 kHz, and a time resolution of 11.6 ms. The boundaries of each selection were conducted using the power spectrum as outlined in Zollinger <em>et al.</em> (2012). </p>

This dataset shows the following for 3 songs per bird per song type (Type I song n = 195; Type II song n =74):</p> <ul> <li>Twenty-one variables were measured from each song using Raven Pro 1.4(Figure 1): total number of notes, number of unique notes, duration, minimum and maximum frequencies, bandwidth, and aggregate entropy of the whole song and parts 1 and 2 of the song.</li> </ul>

The scores for these songs were analyzed in a PCA and then the mean and standard deviation of each variable were calculated for the three songs of each type.</p>