DOI: 10.5061/dryad.vt4b8gtpm
title: Vocalizations of the squirrel family

description: The dataset Squirrel_Calls is a collection of vocal records (defined as
 primary literature that numerically describes the vocalization of at least
 1 squirrel species) where each row corresponds to a single call type of
 one species. The details of the row include a summary of the literature
 metadata, categorical descriptions of the call and the caller as well as
 numerical values of the call frequencies. The dataset
 Squirrel_Ecological_Traits is a corresponding set of ecological traits for
 all the species listed in the Squirrel_Calls dataset. The traits listed
 (mass, time partitioning, gliding capabilities, habitat, and sociality)
 reflect hypotheses and predictions explored in the associated article. At
 the end of this document, there is a complete list of the literature
 references used to assemble these datasets. Squirrel_Script is the R
 script used to produce the statistics and models used in the corresponding
 paper. Squirrel_Tree is a nexus file compiling the data of 1000 trees
 downloaded from VertLife.org which were subsetted from their published
 mammalian supertree. The nexus file was used in the R script.
description: We developed a database beginning with a list of publications
 that described the vocalizations of squirrels. The minimum requirement for
 each publication was the description of at least one call with either a
 spectrographic analysis or numerical data, though the majority of
 publications described multiple calls per species or described multiple
 species per publication (493 calls from 72 species represented in 89
 publications). The databases used to search for these publications were
 Google Scholar, JSTOR, Web of Science, and Wiley Online Library. We used
 the keywords acoustics, acoustic repertoire, calls, frequency, Hz,
 vocalizations, and ultrasound paired with Sciuridae, squirrel, or an
 exhaustive list of currently valid and invalid genera (the most updated
 nomenclature was taken from the Integrated Taxonomic Information System
 http://www.itis.gov/).
 For each call described in the selected publication, the following
 characteristics were taken: the fundamental frequency
 (F<sub>0</sub>: the mean frequency of the primary vibrational
 frequency of the vocal membrane; kHz), dominant frequency
 (F<sub>Dom</sub>: the frequency with the greatest energy,
 power or amplitude; kHz), minimum frequency (F<sub>Min</sub>:
 the minimum frequency of the fundamental frequency; kHz), maximum
 frequencies (F<sub>Max</sub>: the maximum frequency of the
 fundamental frequency (or of harmonic on which F<sub>Dom</sub>
 is measured); kHz), and the highest visible harmonic
 (F<sub>Harm</sub>: mean frequency of the highest complete
 harmonic visible on the spectrograph; kHz). Once our
 review of vocalization publications was complete, we searched for the body
 mass (g), diel activity pattern (diurnal or nocturnal), social complexity,
 and habitat openness of the dominant habitat (open or closed) of each
 species from the relevant vocalization papers. If not provided, other
 resources including Mammalian Species accounts, PanTHERIA (Jones et al.
 2009), and the Animal Diversity Web (Myers et al. 2020) were reviewed.
 Both male and female body masses were initially recorded, but male body
 size could not be found for <i>Spermophilus taurensis</i>.
 Male and female body mass were strongly correlated (<i>r</i> =
 0.98, <i>p </i>&lt; 0.001), therefore female body mass was
 chosen to represent squirrel body size. Because we could only assign an
 adult female body mass to all species, calls that are exclusively produced
 by males or pups were removed from the dataset before analysis. We pooled
 all other calls (calls produced by both sexes or females only as well as
 calls produced by juveniles and adults) as there is little evidence to
 suggest that juveniles and adults produce acoustically distinct calls
 across the family (Matrosova et al. 2007, 2011; Schneiderová 2012;
 Volodina, Matrosova, and Volodin 2010; but see: Nikol’skii 2007). While
 the initial database included a five-tiered social classification ranging
 from solitary to colonial (based on the social grades of ground squirrels
 described by Matějů et al. (2016)), social classes were reduced to social
 or solitary living to reduce model parameters. Species that exhibit
 dynamic social structures, such as flying squirrels that engage in social
 nesting to a greater extent during one portion of the year (Garroway,
 Bowman, and Wilson 2013), were treated as socially living. Two subspecies
 (<i>Marmota baibacina centralis </i>and <i>Tamias
 dorsalis dorsalis</i>) could not be used in the subsequent analyses
 because ecological data and body mass-specific to each subspecies could
 not be found; similarly, the species <i>Spermophilus pallidicauda
 </i>could not be included as body mass for either sex could not be
 found. <i>Phylogeny</i>
 VertLife, an online resource that allows the user to extract
 pruned trees from vertebrate supertrees, was used to produce 100 pruned
 trees from the Mammalian supertree (Upham, Esselstyn, and Jetz 2019).
 Three subspecies had to be incorporated under their parent species, so
 branch tips were broken in two and subspecies were treated as equivalent
 to parent species, with branch lengths identical between the parent and
 subspecies (the addition of a subspecies did not create any polytomies in
 the tree). Three species are represented by subspecies only:
 <i>Sciurus aberti kaibensis, Sciurus niger rufiventer, </i>and
 <i>Callosciurus erythraeus thaiwanensis</i>.
 <i>Statistical Analysis</i>
 Phylogenetic generalized least square (PGLS) modelling was used
 to account for the variation in acoustic repertoire that may be explained
 by phylogenetic relatedness. PGLS models produce a lambda
 parameter,<i> λ</i>, that represents the degree to which the
 variance of traits is explained by the phylogenetic relationships in the
 model. The <i>λ </i>parameter varies between 0 and 1, with 0
 representing no phylogenetic trace and 1 representing absolute Brownian
 motion (Freckleton, Harvey, and Pagel 2002; Martin et al. 2016).
 PGLS modelling restricts each species to a single observation
 (i.e., no subsampling of species permitted). Therefore, the numerous data
 entries per species had to be reduced. For the fundamental, dominant,
 maximum, and highest harmonic frequencies, the absolute maximum value for
 each characteristic reported among all publications was chosen. Likewise,
 for minimum frequency, the absolute minimum reported frequency was chosen.
 We use maximum and minimum values rather than the median for a more
 rigorous test of our hypothesis about method limits.
 Body mass and all frequency characteristics were log-transformed
 to achieve normal distributions. Additive models were built for each
 frequency type (β<sub>0</sub> + body mass
 (β<sub>Mass)</sub> + diel activity pattern
 (β<sub>Diel</sub>) + sociality
 (β<sub>Sociality</sub>) + habitat openness
 (β<sub>Open</sub>) + method limits
 (β<sub>Lim</sub>)) using the caper package in R (ver 3.6.2).
 We reported the test statistics of the regression to evaluate significance
 and effect size (<i>F-</i>statistic,
 <i>p-</i>value, and adjusted
 R<sup>2</sup>).