DOI: 10.5061/dryad.qjq2bvqp4
title: Reproductive state alters vocal characteristics of female North American red squirrels (Tamiasciurus hudsonicus)

description: Female advertisement of reproductive state and receptivity has the
 potential to play a large role in the mating systems of many taxa, but
 investigations of this phenomenon are underrepresented in the literature.
 North American red squirrels (Tamiasciurus hudsonicus) are highly
 territorial and engage in scramble competition mating, with males
 converging from spatially disparate territories to engage in mating
 chases. Given the narrow estrus window exhibited in this species, the
 ubiquitous use of vocalizations to advertise territory ownership, and the
 high synchronicity of males arriving from distant territories, we
 hypothesized that female vocalizations contain cues relating to their
 estrous state.  To test this hypothesis, we examined the spectral
 and temporal properties of female territorial rattle vocalizations
 collected from females of known reproductive condition over 3 years. While
 we found no distinct changes associated with estrus specifically, we did
 identify significant changes in the spectral characteristics of rattles
 relating to both female body mass and reproductive state relative to
 parturition. To the best of our knowledge, this is the first evidence of
 changes in vocal characteristics associated with late pregnancy in a
 non-human mammal.
description: Methods listed below are from: Hare, McAdam,
 Dantzer, Lane, Boutin, and Newman (2024). Reproductive state alters vocal
 characteristics of female North American Red Squirrels (Tamiasciurus
 hudsonicus). Journal of Mammalogy (In Press).
 "Study system<br>We studied a wild population of T.
 hudsonicus associated with the Kluane Red Squirrel Project (KRSP) from
 2018 – 2020 in southwestern Yukon (61˚N, 138˚W) within the Champagne and
 Aishihik First Nations’ traditional territory (Dantzer et al. 2020). Audio
 recordings were collected from 108 individual female squirrels at 6
 separate study sites spaced 5 km apart along the Alaska Highway. Each
 individual in the study was tagged with unique alphanumeric ear tags in
 each ear (Monel #1 National Band & Tag Co., Newport, KY, USA). We
 also threaded colored wires through ear tags for visual identification
 from a distance (McAdam et al. 2007). As part of the KRSP, all individuals
 were routinely trapped and handled to establish territory ownership,
 assess body mass and reproductive condition, and determine matrilineal
 relationships (McAdam et al. 2007). All data were collected following
 guidelines in Sikes (2016).  Audio
 recording<br>Continuous audio recordings were taken in 3-day bouts
 using Zoom H2N digital audio recorders (Zoom North America, NY, USA)
 placed at the center of each female midden. In brief, recorders were fixed
 to trees at the center of each midden at the beginning of each recording
 session using bungee cables at ~1.5m height prior to squirrel emergence at
 sunrise (or 5 am when close to the solstice). Batteries and SD cards were
 changed every 24 hours. Stereo recordings were taken at a 44.1 kHz
 sampling rate in a 16-bit WAV format then mixed down to mono prior to
 analysis.   Audio analysis<br>Audio recordings
 were selected for inclusion if they took place within ± 10 days of a live
 trapping event in which individual mass was recorded in order to control
 for the effects of body size on the pitch of vocalizations (Bradbury and
 Vehrencamp 1998). This range was selected to include only recordings from
 squirrels for which we had relatively high certainty of reproductive state
 through palpation and maintain the most proximate mass measurements given
 the 2-week periodicity of regular trapping that is part of the KRSP
 trapping protocol. Selected recordings were analyzed with Kaleidoscope Pro
 bioacoustics software (Wildlife Acoustics, Maynard, MA, USA) using the
 cluster analysis function, which differentiates red squirrel rattles from
 other signals based on an existing template, as used previously (Siracusa
 et al. 2019). This process identified 2.23 million acoustic signals that
 could be red squirrel rattles from 9.85 TB of uncompressed continuous
 recordings constituting 8,214 total days of sampling. Signals were then
 run through the ‘Seewave’ package (Sueur et al. 2008) in R version 4.1.0
 (R Core Team 2022) to extract a range of spectral and temporal values from
 each respective clip (sensu Siracusa et al. 2019). To
 differentiate calls made by territory owners from those produced by
 neighbouring red squirrels, all clips identified through Kaleidoscope were
 run through a Linear Discriminant Function analysis, built using
 previously published acoustic parameters (Siracusa et al. 2019) through
 the ‘caret’ package in R (Kuhn 2008) using a ground tested dataset of
 10,650 manually identified acoustic signals (Siracusa et al. 2019). In
 short, an observer recorded continuous audio while remaining stationary on
 the territory of 49 focal squirrels, recording the time whenever a rattle
 vocalization was produced by the focal individual. Acoustic signals
 extracted from these recordings were then labelled as either an owner
 rattle, neighbour rattle, or not a rattle vocalization (Supplementary Data
 SD4). Applying this linear discriminant function reduced the sample to
 11,488 potential owner rattles at a certainty of 95% for manual
 validation. Potential owner rattles were reviewed
 manually through both visual examination of the spectrograph and aural
 examination of the audio clip. Audio clips that had been detected as owner
 rattles were selected for inclusion if they were actually a red squirrel
 rattle, had a minimum of a 3:1 signal to noise ratio, had no spectral or
 temporal clipping of the vocalization, and there were no competing signals
 within the vocalizations from conspecific, heterospecific, or
 anthropogenic sources. This manual validation produced 897 good quality
 owner rattles for use in our analysis for which we had high certainty of
 individual identity. It is worth noting, however, that these data were
 collected autonomously—we did not witness the squirrel vocalization at the
 time the recording were made. Estimating estrus
 date<br>As we were interested in the timing of acoustic changes
 relative to estrus dates, owner rattles were filtered further to include
 clips from individuals from which we could accurately estimate estrus
 date.  This was done using known parturition dates from live-trapping and
 monitoring associated with ongoing research at the KRSP (McAdam et al.
 2007), then backtracking 35 days, which is within the average reported
 gestation period for a North American Red Squirrel (Dolbeer 1973; Lair
 1985; Steele 1998).  From this point, a possible window in which a mating
 chase could occur was defined as ± 5 days, allowing for individual
 variation in gestation length, which has been documented as occurring
 between 31 to 35 days (Lair 1985; Steele 1998; Dantzer et al. 2011). Calls
 that occurred within ± 100 days of parturition were included to capture
 the full extent of changes that would occur across a reproductive cycle—a
 range that was selected to encompass meaningful reproductive changes
 across the reproductive season, omitting samples collected in the winter
 from a single individual. This filtering criterion reduced our sample size
 from 897 rattles to a final dataset of 120 owner rattles from 22
 individuals in which we were able to capture their estrus window while
 being confident of signaller identity. Using known
 parturition dates also allowed us to assign different reproductive states
 to callers with fairly high certainty. In brief, any calls included that
 were over 35 days to parturition were considered as coming from
 non-reproductive squirrels, while any calls occurring within 35 days were
 considered as coming from pregnant squirrels (Steele 1998; McAdam et al.
 2007). Finally, any calls that were collected within 71 days following
 parturition were classified as coming from lactating squirrels that had
 not yet weaned their pups (McAdam et al. 2007; Dantzer et al. 2011). Each
 of the 120 owner rattles included were assigned to one of these 3
 reproductive states for further analysis of changes across reproductive
 condition (Fig. 1). Statistical analyses<br>Each
 acoustic parameter of interest was first visually examined for normality
 and homoscedasticity before being analyzed via a generalized additive
 model (GAM) to test for differences across days to parturition using the
 ‘mgcv’ package in R (Wood, 2017). We selected GAMs to test our hypothesis
 regarding estrus because the additive nature of these models would allow
 for any pronounced changes occurring within our defined estrus window to
 be detected, while linear models would likely miss these discrete changes.
 Smoothing parameters were used on continuous variables using the
 restricted maximum likelihood (REML) method on days to parturition at
 recording and scaled individual mass at most proximate trapping. Julian
 date of recording was omitted because it displayed high concurvity with
 days to parturition across all variables of interest. Year of recording
 and field site were coded as factorial covariates. Individual age in years
 and age in years squared were included as continuous integer coefficients
 to capture any linear and quadratic effects of age. Finally, individual
 squirrel identification was included as a random intercept to control for
 individual variation. This was particularly important for our models
 because there was uneven sampling of individuals across reproductive
 states, and the inclusion of a random intercept for individual identity
 accommodated for the effects of repeated sampling of certain squirrels
 (Fig. 1). Response variables were grouped into either spectral or temporal
 variables, with spectral variables including mean frequency (Fmean),
 fundamental frequency (F0), and Shannon entropy (entropy)—while temporal
 variables included call duration (duration), rattle trill rate (rate), and
 rattle duty cycle (duty cycle; for definitions see Supplementary Data
 SD3). Trends for each response variable were examined visually using a GAM
 spline with nine knots along days to parturition, specifically looking for
 distinct changes within the ± 5-day estrus window. Nine knots were
 selected for visual inspection as this was the number of smoothing terms
 produced through the REML smoothing method.  Terms that
 exhibited statistically significant effects in our GAMs were further
 examined through post-hoc generalized linear mixed models (GLMM) to
 determine whether effects were statistically significant. Days to
 parturition was replaced with the factorial covariate reproductive
 condition as calculated relative to parturition in order to test for
 significant changes across reproductive state. The effective degrees of
 freedom (edf) calculated through GAMs were used to inform GLMM
 construction, including quadratic terms for mass when it was indicated to
 have a non-linear relationship with response variables. All statistical
 tests were run on R version 4.2.1 (R Core Team 2022) and for all tests,
 statistically significant trends were inferred at a level of significance
 of  = 0.05 following visual examination of confidence intervals. Due to
 the number of tests run, a Holm-Bonferroni correction for multiple
 comparisons was applied to any obtained P-values, then compared at our
 level of significance. For any factorial variables, parameter estimates ±
 standard errors are reported along with relevant test statistics and
 associated P-values are reported in-text when significant and otherwise
 can be found in the supplementary data (see Supplementary Data SD6, SD8,
 SD10, SD12, SD14, SD16 – SD20)."
description: # Reproductive state alters vocal characteristics of female North American
 Red Squirrels (Tamiasciurus hudsonicus) - Data
 \--------------------
 GENERAL INFORMATION \-------------------- 1\. Title of Dataset:
 Reproductive state alters vocal characteristics - Data 2\. Author
 Information ``` A. Corresponding Author Contact Information Name:
 Alexander J. Hare Institution: University of Guelph Email:
 ahare04@uoguelph.ca/alexhare1991@gmail.com B. Principle Investigator
 Information Name: Amy E.M. Newman Institution: University of Guelph Email:
 newman01@uoguelph.ca ``` 3\. Date of data collection (YYYY-MM-DD): All
 data was collected between 2018-03-14 to 2020-06-17 4\. Geographic
 location of data collection: Kluane Red Squirrel Project, located on the
 traditional territories of the Champagne and Aishihik First Nations,
 within southwestern Yukon, 61˚N, 138˚W 5\. Information about funding
 sources that supported the collection of the data: This research was
 supported by a Postgraduate and Canada Graduate Scholarship
 (PGSD3-518337-2018 to AJH), grants from the Natural Sciences and
 Engineering Research Council of Canada (RGPIN-371579e2009 and
 RGPIN-2015-04707 to A.G.M; RGPIN-2014-05400 to A.E.M.N), the Northern
 Scientific Training Program (NSTP-054667 to AJH), and the American Society
 of Mammalogists Grants-in-aid (to AJH). \---------------------------
 SHARING/ACCESS INFORMATION \--------------------------- 1\. Links to
 publications that cite or use the data: Hare, A.J., McAdam, A.G., Dantzer,
 B., Lane, J.E., Boutin, S., Newman, A.E.M. 2024. Reproductive state alters
 vocal characteristics of female North American Red Squirrels (Tamiasciurus
 hudsonicus). Journal of Mammalogy (In Press). 2\. Links/relationships to
 ancillary data sets or software packages: \- R \- R libraries: ```
 library(tidyverse) library(ggplot2) library(lubridate) library(car)
 library(lme4) library(lmerTest) library(krsp) library(dplyr) library(mgcv)
 library(wesanderson) library(mgcViz) library(cowplot) ``` 3\. Was data
 derived from another source? yes/no A. If yes, list source(s): no 4\.
 Recommended citation for this dataset: Hare, A.J. (2023). Reproductive
 state alters vocal characteristics of female North American Red Squirrels
 (Tamiasciurus hudsonicus) - Data doi:
 \---------------------
 DATA & FILE OVERVIEW \--------------------- 1\. File List A. Filename:
 Reproductive_State_Manuscript_JAN06Tidy.Rmd Short description: R script
 used for analyses of data associated with Hare et al. (2024) Journal of
 Mammalogy (In Press) B. Filename: ReproVoc_Data.csv Short description: Raw
 data used in analyses for Hare et al. (2024) Journal of Mammalogy (In
 Press) 2\. Relationship between files, if important: ReproVoc_Data.csv
 provides the necessary raw data for analysis through
 Reproductive_State_Manuscript_JAN06Tidy.Rmd script in R.
 \-----------------------------------------------------------------
 DATA-SPECIFIC INFORMATION FOR: ReproVoc_Data.csv
 \----------------------------------------------------------------- 1\.
 Number of variables: 50 2\. Number of cases/rows: 120 3\. Missing data
 codes: Code/symbol = NA 4\. Variable List: ``` A. Name: squirrel_id
 Description: Individual identification number for each squirrel B. Name:
 FOLDER Description: Folder that audio data are saved in C. Name: INDIR
 Description: File directory for audio files E. Name: IN.FILE Description:
 Audio file name F. Name: OFFSET Description: Offset from start of audio
 recording that signal occurs (samples) G. Name: DURATION Description:
 Duration of signal as calculated by Kaleidoscope (in seconds) H. Name:
 Fmin Description: Minimum frequency of signal detected (Hz) I. Name: Fmean
 Description: Mean frequency of signal detected (Hz) J. Name: Fmax
 Description: Maximum frequency of signal detected (Hz) K. Name: RMS
 Description: Root Mean Square Pressure (Measure of the sound pressure
 level across the duration of the signal) L. Name: fund.freq Description:
 Fundamental frequency of signal detected (kHz). M. Name: duration
 Description: Duration of signal detected as calculated by Sewage package.
 N. Name: entropy Description: Shannon entropy O. Name: rate Description:
 The average number of distinct syllables produced per second over the
 duration of a rattle. P. Name: dutycycle Description: The proportion of
 time over the duration of a rattle that a signal was produced versus not.
 Q. Name: Q25 Description: The frequency at which 25% of frequencies
 detected within a rattle fall under. R. Name: Q75 Description: The
 frequency at which 75% of frequencies detected within a rattle fall under.
 S. Name: IQR Description: The range of frequencies which fall between Q25
 and Q75. T. Name: centroid Description: Weighted mean of frequencies in
 rattle based on amplitude. U. Name: skewness Description: A measure of
 frequency asymmetry, centered at 0, with left skew (lower frequency skew)
 presented as &lt; 0 and right skew (higher frequency skew) presented as
 &gt; 0 V. Name: kurtosis Description: Spectral kurtosis, a measure of
 spectral asymmetry W. Name: sfm Description: spectral flatness measure X.
 Name: grid Description: References specific study site which sample was
 collected from Y. Name: midden Description: Reference location of
 individual squirrels primary midden (food cache) Z. Name: wgt Description:
 squirrel mass in grams AA. Name: repro Description: reproductive condition
 as assessed during live trapping AB. Name: julian Description: Julian date
 that recording was collected AC. Name: year Description: year that
 recording was collected AD. Name: day_to_part Description: Number of days
 relative to estimated parturition date AE. Name: Litter Description:
 Whether a female red squirrel produced a litter in the year which they
 were sampled AF. Name: id Description: mother identification number AG.
 Name: gr Description: grid copied from litter record (see X above) AH.
 Name: sex Description: anatomical sex of individual squirrel (F = female)
 F = Female M = Male AI. Name: dates Description: birth date of individual
 squirrel (YYYY-MM-DD) AJ. Name: f1 Description: first tagging fate (for
 reference see
 https://github.com/KluaneRedSquirrelProject/KRSP-Meta-Data/blob/master/KRSP%20Database%20Appendix.pdf) AK. Name: byear Description: birth year of individual squirrel AL. Name: litter_id Description: litter identification number AM. Name: dam_id Description: mother squirrel_id (see A) AN. Name: sire_id Description: father squirrel_id (see A) AN. Name: bcert Description: was birth of focal individual certified by observer? Y = Yes N - No AO. Name: newgr Description: copied column from trapping record to include if grid (see X) has changed) AP. Name: newsex Description: copied vector from trapping record to include if recorded sex has changed (see AH) AQ. Name: datee Description: Date (YYYY-MM-DD) that data was entered to long term database AR. Name: f2 Description: final trapping fate (for reference see https://github.com/KluaneRedSquirrelProject/KRSP-Meta-Data/blob/master/KRSP%20Database%20Appendix.pdf) AS. Name: locX Description: location on grid (see X) along the X axis that trapping occurred AT. Name: locY Description: location on grid (see X) along the Y axis that trapping occurred AU. Name: age Description: age of focal individual in years AV. Name: age2 Description: age^2 of focal individual in years AW. Name: ageF Description: age coded as a factor for analysis (redundant, I know) AX. Name: repro_part Description: reproductive condition of focal individual as calculated relative to parturition date ```