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Singing silver-haired bats (Lasionycteris noctivagans)

Cite this dataset

Lausen, Cori et al. (2023). Singing silver-haired bats (Lasionycteris noctivagans) [Dataset]. Dryad.


Characterizing sounds produced by animals can lead to better understanding of their behavioral ecology and conservation. While considerable focus has been on signals used by bats for echolocation, there has been less emphasis on nonecholocation sounds. We describe songs (i.e., acoustic vocalizations with distinctive syllable types in series or in complex motifs) produced by silver‐haired bat (Lasionycteris noctivagans). Songs, characterized by a sequence (song phrase) of 3 distinct vocalization types, were confirmed by observing free‐flying, silver‐haired bats at mine hibernacula in British Columbia, Canada. The song patterns were relatively consistent with each song phrase consisting of a lead call, followed by a droplet call, and finishing with a series of multiple chirp calls. The function of the songs is unknown, however, as other bat species produce songs for mating, we propose silver‐ aired bat songs may similarly be associated with courtship or mating. Alternative functions cannot be ruled out, particularly because we recorded some songs outside of the accepted mating period. Other research has determined peak mating of silver‐haired bats occurs in fall, and spring mating has been documented. Here we additionally provide evidence of winter mating in British Columbia. The proportion of silver‐haired bat songs recorded relative to echolocation recordings varied across locations and seasons. While we recorded songs in all months of the year, more than half of the songs were produced during winter, and 93.4% (of 1,857) were produced outside of summer months. Song production in summer could be associated with other behaviors such as learning or practice, establishing or maintaining social bonds, or male‐male competition. To provide landscape and temporal context, we summarize acoustic datasets from numerous locations in western North America where recordings were made between 2005 and 2022.


These recordings are samples of songs produced by silver-haired bats.
Files have been made publicly available courtesy of Wildlife Conservation Society Canada, Montana Natural Heritage Program, British Columbia Ministry of Environment, Colorado Bureau of Land Management, Utah USDA Forest Service, and Idaho USDA Forest Service.

To view .wav files (full spectrum recordings) the following free software can be used:
Kaleiodscope (Wildlife Acoustics) - specific to viewing bat recordings
Raven Lite (Cornell University)

Fee-based software that could be used and is specific to viewing bat acoustic recordings:
Anabat Insight (Titley Scientific)

Recordings that end in something other than .wav (i.e., #, zc) are zero-crossing files and can be viewed in free software AnalookW (available: select first option in list), or fee-based Anabat Insight (Titley Scientific)

IMPORTANT NOTE: Metadata is not necessarily accurate, and should not be used. When these files are automatically identified to species in AutoID software, the species can be (and often is) incorrect -- this is because these social calls are not part of the underpinning libraries of autoID software.


Methods from the manuscript:

Study Species

In Canada, silver‐haired bats are considered migratory, moving south for winter months (Naughton 2012) however, in British Columbia (BC) and parts of the northwestern U.S. (including Washington, Idaho and Montana), silver‐ haired bats are recorded year‐round, flying in winter during hibernal arousals (Schowalter et al. 1978, Falxa 2007, Lausen et al. 2022). Banding records provide evidence that at least some silver‐haired bats reside year‐round at some mines in British Columbia (Lausen et al. 2022).

 Study Area

Our recordings spanned several U.S. states and areas of BC. We recorded bats at 23 acoustic detector sites across western U.S. and Canada, each with varying degrees of forested/rocky terrain (Table S1, available in Supporting Information; Figure 1): California (4), Colorado (1), Idaho (3), Utah (2), Montana (2), Washington (one main active monitoring area), and British Columbia (BC, 10). At the Washington site, overwintering roosts of silver‐haired bats were observed in bat boxes, under Douglas‐fir and Western red cedar tree bark, and in small crevices on building exteriors. At 20 of the stationary recording sites, we had no knowledge of whether the sites were used by silver‐ haired bats for roosting. Two of the 10 monitored sites in BC were mine sites in forested areas where silver‐haired bats hibernate and have been documented year‐round (CA‐9, CA‐10; Figure 1, Table 1, S1). The CA‐10 mine is an inaccessible and deep abandoned mine complex with many large (>16 m2) openings and a central pit roughly 100 m in diameter. The CA‐9 mine is an accessible (but gated) shallow (~50 m) mine with 2 large (>20 m2) openings immediately adjacent to each other. Silver‐haired bats use the CA‐9 mine in both summer and winter and have been radiotracked to day roosts (summer and winter) in trees surrounding the mine (Lausen et al. 2022). Mist‐net capture in winter of silver‐haired bats flying in or out of each mine also facilitated examination of bats to determine sex, signs of breeding, etc. (Lausen et al. 2022).

Upon first recording these songs during the 2011 season, we were uncertain whether they were produced by big brown or silver‐haired bats, because the echolocation calls that preceded or followed song phrases were ambiguous and could be attributed to either species (Betts 1998). We therefore conducted capture inventories at both mines, mist‐netting and harp‐trapping bats flying in and out of the entrances to identify species. To understand potential reasons for winter flight and song production, we also examined genitalia to assess any signs of mating activities.

Acoustic recording
We recorded bats passively using Anabat (models SD1 and SD2, Titley Scientific, city, Australia), SM2Bat (model Plus, Wildlife Acoustics, Maynard, MA, USA), Anabat Swift (Titley Scientific, Australia), SM4Bat (Wildlife Acoustics, primarily in a lowland mixed‐conifer wooded park (Squaxin Park) in Olympia, WA (Figure 1). Bats were recorded primarily near forest edge adjacent to water features, roads, or other open nonforested landscapes in all seasons, and in particular active recordings were typically in November, when silver‐ aired bats were the only non‐Myotis bats recorded (Falxa 2007). These active recordings were associated with silver‐haired bats by observing a bat's flight pattern and foraging behaviors; during these recordings, bats producing low frequencies (low‐frequency bats) were observed flying in slow, straight lines over open areas and along canopy edges while echolocation calls and songs of silver‐haired bat were recorded. Some song‐containing files were recorded in close proximity (1–50 m) to known silver‐haired bat roosts. All passive bat detectors were programmed to trigger on bat ultrasound and record up to a maximum duration of 15 s before beginning a new sound file. Adhering to standardized acoustic terminology (Loeb et al. 2015), we refer to single file (recording) as a bat pass, and we define a call as a single burst (pulse) of sound, whether it is echolocation or social in nature. A sequence of calls is any series of pulses, whether they are echolocation or social. To differentiate pulses produced in songs versus those typical of echolocation, we refer to pulses making up a song as syllables. Different types of syllables vary in frequency and duration parameters. A distinct sequence consisting of different types of syllables which is repeated to produce a song, we refer to as a phrase. Generally, a song will consist of one or more phrases, however, if only part of a phrase was recorded, as long as the syllables present are clearly attributable to a phrase, then we refer to this as a partial song. In some cases, such as when a bat is only in the detection volume of a bat detector for a very short period of time, only partial songs (i.e., less than one complete phrase) were recorded. We processed acoustic recordings using a variety of methods, with larger datasets first being processed with either Kaleidoscope Pro (Wildlife Acoustics, MA, USA) or SonoBat (California State Polytechnic University, Humboldt, CA, USA) for auto-identification prior to manually vetting; some smaller datasets were examined without auto‐ identification as a first step. We manually vetted files using either Kaleidoscope Pro, SonoBat, AnalookW (C. Corben,, MO) or Anabat Insight (Titley Scientific, Brisbane, Australia). Recordings from BC were largely zero-crossing format, and all other datasets were recorded in full spectrum format. British Columbia datasets were manually vetted using a combination of AnalookW and Anabat Insight. Washington and Mendocino County California datasets were manually reviewed using Kaleidoscope Pro. Recordings collected in Montana, Idaho, Utah, Colorado, and Lassen Volcanic National Park (California) were manually reviewed using SonoBat. Active recordings from Washington were reviewed by one of us (G. Falxa) manually to identify songs using both Sonobat3 and Kaleidoscope Pro. Files were manually analyzed in real‐time (uncompressed) mode in order to ensure visualization of a song pattern; compressed mode can obscure the diagnostic song pattern if some song pulses are of low intensity. For larger datasets that underwent automated classification, we determined that silver‐haired bat songs were often misclassified as big brown bat, Brazilian free‐tailed bat, pallid bat (Antrozous pallidus), Townsend's big‐eared bat (Corynorhinus townsendii), western red bat (Lasiurus blossevillii), hoary bat, or long‐eared myotis (Myotis evotis). Thus, files automatically classified as any of the above species were manually vetted to search for silver‐haired bat songs. To avoid reporting extraneous results, we present silver‐haired bat activity only in the context of low‐ frequency bat passes (minimum frequency <30 kilohertz [kHz], where one recorded file = pass), as silver‐haired bat songs are most likely to be confused with echolocation calls of low‐ frequency bat species. We refer to call parameters (measured in AnalookW, Anabat Insight and/or Kaleidoscope Pro) as follows: call body is the flattest part of the call (Figure 2A), with Sc being the slope of that call body in octaves per second (OPS); time between calls (TBC) is the amount of time between pulses/calls; and minimum (Fmin)/maximum (Fmax) frequencies refer to the lowest/highest frequency produced in one call/pulse. Generally, echolocation pulses of North American bats (low duty cycle) are frequency modulated (FM) and thus start high in frequency and end lower, having bandwidth greater than zero (Russo et al. 2018). If the call body is flat or nearly flat, bandwidth approaches zero and this is referred to as a quasi‐constant frequency (QCF) component of a call. The rate of change of frequencies can vary as the call is produced (i.e., the slope changes over time) and may be gradual or sudden. In the latter, this change of slope creates a bend in the call, often called a knee (Figure 2A). The slope of the call from its start at Fmax, to the knee, is measured as S1 (OPS), and the slope from the knee to the Fmin, is generally the call body and is the Sc as discussed above. We measured call duration (time from start to end of a pulse, measured in milliseconds [ms]). All parameters were measured in zero‐crossing format using AnalookW. Spectrograms in the figures are shown in True Time (x‐axis shows the real time elapsed) unless specified (x‐ axis in Compressed Time shows only the time within each pulse in real time, with the time between the pulses largely removed, for display purposes). All spectrograms display a logarithmic frequency (y axis). 

To assess the auto‐identification treatment of songs, we processed all full spectrum song files using both Kaleidoscope Pro (classifier version North America 5.4.0) and SonoBat (versions 4.4.0 and 4.4.5 Great Basin classifier) including the following species (Kaleidoscope Pro): big brown bat; Brazilian free‐tailed bat; California myotis, Myotis californicus; canyon bat, Parastrellus hesperus; fringed myotis, M. thysanodes; hoary bat; little brown myotis, M. lucifugus; long‐eared myotis; long‐legged myotis, M. volans; pallid bat; silver‐ haired bat; spotted bat, Euderma maculatum; Townsend's big‐eared bat; western red bat; western small‐footed myotis, M. ciliolabrum; and Yuma myotis, M. yumanensis. The Montana classifier set included eastern red bat (Lasiurus borealis) instead of western red bat, and additionally included northern myotis (M. septentrionalis). We used default settings for each software package (Kaleidoscope Pro Balanced; SonoBat 0.7 call quality, 0.9 sequence decision threshold). We examined each recording to ensure the software was triggering on the song pulses, and thus considering them in the auto‐identification process. We calculated the percentage of misclassifications.

Usage notes

Files that end in .wav can be opened with Sonobat, Kaleidoscope, or Anabat Insight. They can also be opened with free acoustic software that permit visualization such as Raven Lite. Note that Kaleidoscope (from Wildlife Acoustics) is free to download and use to visualize any of the recordings in this dataset. Insight must be purchased. Sonobat must be purchased and can only be used to view the .wav files. Files that end in something other than .wav (i.e., # or zc) are zero-crossing format and will require the free software download AnalookW or the fee-based Anabat Insight (both software links available on website of Titley Scientific).