DOI: 10.5061/dryad.stqjq2c6s
title: Data for: Zebra finch song ecology: monitoring of breeding, observational transects, focal and year-round acoustic recordings, and a large-scale simultaneous playback experiment

description: Male songbirds sing to establish territories and to attract mates.
 However, increasing reports of singing in non-reproductive contexts and by
 females show that song use is more diverse than previously considered.
 Therefore, alternative functions of song, such as social cohesion and
 synchronisation of breeding, by and large were overlooked even in such
 well-studied species as the zebra finch (Taeniopygia guttata). In these
 social songbirds only the males sing and pairs breed synchronously in
 loose colonies following aseasonal rain events in their arid habitat. As
 males are not territorial, and pairs form long-term monogamous bonds early
 in life, conventional theory predicts that zebra finches should not sing
 much at all; yet they do and their song is the focus of hundreds of
 lab-based studies. We hypothesise that zebra finch song functions to
 maintain social cohesion and to synchronise breeding. Here we test this
 idea using data from five years of field studies, including observational
 transects, focal and year-round audio recordings, and a large-scale
 playback experiment. We show that zebra finches frequently sing while in
 groups, that breeding status influences song output at the nest and at
 aggregations, that they sing year-round, and that they predominantly sing
 when with their partner, suggesting that song remains important after pair
 formation. Our playback reveals that song actively features in social
 aggregations as it attracts conspecifics. Together, these results
 demonstrate that birdsong has important functions beyond territoriality
 and mate choice, illustrating its importance in coordination and cohesion
 of social units within larger societies.
description: This dataset contains data from several collection methods which
 together give an integrated perspective on wild zebra finch song ecology.
 The data was collected from 2016 to 2020 in UNSW Fowlers Gap Arid Zone
 Research Station in New South Wales, Australia, home to a well-studied
 population of wild zebra finches. The methods
 are: <strong>a) Nest box
 monitoring</strong> <br>We routinely checked nest boxes from
 2016 to 2020, usually from August till December (in 2020 already from June
 onwards due to drought-breaking rain), when most breeding activity in this
 population is observed. We combined the resulting clutches laid with the
 rainfall data for our field site for 2016 to 2020 from the Australian
 Bureau of Meteorology. <strong>b) Observational
 transects</strong><br>In the spring of 2018, 2019 and 2020, we
 walked 1 km transects to standardise encounters with zebra finches at our
 field site. During these transects, for every zebra finch observation we
 scored the group size and presence of song.
 <strong>c) Focal, hand-held acoustic
 recordings</strong><br>In 2018, we opportunistically recorded
 wild zebra finch songs using directional microphones. Afterwards, using
 spectrograms made in Audacity, we scored for each recorded song which
 individual produced it and the specific social context in which it was
 produced. <strong>d) Acoustic recordings at
 active nest boxes</strong> <br>In 2016, we installed
 time-programmable audio recorders near 63 active nest boxes, in various
 stages of breeding. We analysed one day (it was 26th October) from each
 nest using Audacity to score the start and end times of each singing bout,
 while also noting the quality (low, medium or high) as an indication of
 distance from the nest. We attributed each song to an individual by
 comparing spectrograms. We also assigned an owner for each nest based on
 song output and quality. For each nest, we had the breeding stage due to
 nest monitoring. <strong>e) Year-round acoustic
 recording at activity hotspots</strong> <br>We placed
 time-programmable audio recorders (Song Meters 3 and 4, Wildlife
 Acoustics) that were active from sunrise to sunset every four days. For
 sound analysis, we selected the day of the month with the lowest average
 wind speeds per month for October 2018 – October 2019. We obtained these
 low wind days using a python script to link the recording timestamps to
 the half-hourly wind speed data from the local weather station (Australian
 Bureau of Meteorology) with the half hour closest to the start time of the
 recording used as indication of wind speed for that recording. Then, we
 calculated the average wind speed on the recording days and selected the
 day of the month with the lowest average wind speeds. We selected the four
 recorders on which we expected the highest chance of obtaining zebra finch
 activity, which were situated at feeders (3x) and an artificial water site
 (1x). Using sound spectrograms in Audacity we scored per 1-hour recording
 the presence of song and the vocal activity level, which considers that
 zebra finches regularly vocalise. This activity score was a 0 – 4
 Likert-scale resembling the amount of vocal activity (0: no activity, 1:
 quiet overall, &lt; 5 min of vocalisations, 2: not busy, 5 - 15 min,
 3: quite busy, 15 - 30 min, 4: very busy, &gt; 30 min). We also scored
 whether we heard any calls (less precise than the activity score) or zebra
 finches flying over (flying zebra finches do not sing).
 <strong>f) Playback experiments which were
 filmed</strong> <br>We conducted a large-scale playback
 experiment from the 5th to 10th October 2017 that consisted of automated
 simultaneous playbacks with three treatments: zebra finch song,
 nightingale song (heterospecific control) and silence (additional
 control). Playback setups consisted of a nest box attached to a steel post
 next to a tree where a loudspeaker was placed. To control for local
 variation in zebra finch presence, treatments were organised in triplets
 (N = 23), with the three simultaneous treatments in the same general
 location. On a given day three or four triplet experiments were conducted
 at the same time in different areas of the study site, resulting in a
 total of 23 sites, of which 19 received visits by zebra finches. Played
 sound files consisted of two minutes of either zebra finch or nightingale
 song followed by 13 minutes of silence, resulting in a 15-minute loop
 playback. Playback experiments started between 06:45 and 10:05 in the
 morning and lasted about 7.5 hours. All treatments were filmed
 continuously and we scored the videos by noting the timestamp for all
 visits to the bush or nest box. We also scored foraging movements (birds
 only on the ground) or visits that happened after there were already birds
 present (these visitors might have been attracted by the birds instead of
 the playback). We also scored the sex and group size (pair or flock) of
 arriving birds. Additionally, we scored whether arriving males were
 singing although this was not always possible. We calculated for each
 arrival the visit latency, that is, how many seconds passed since the
 playback ended, scoring a zero if the visit was during playback.
 For further details on how the data was collected, we refer to
 the (open access) related article.
description: All the uploaded datasets are csv
 files. The readme contains information on datasets and software, but the
 (open-source) software elements (R 4.1.1 analysis script; python 3.7.0
 script linking wind speeds to audio files) are uploaded to
 Zenodo.