DOI: 10.5061/dryad.2z34tmppn
title: Red coloration and the evolution of aposematism in arboreal sciurids

description: An animal's coloration is associated with a variety of processes and
 is therefore subjected to multiple selective pressures. Mammals,
 especially, are typically inconspicuously colored, or cryptic, to avoid
 detection by predators. Alternatively, an animal may use conspicuous
 coloration to advertise the presence of an anti-predator defense. The
 association between signal and defense is called aposematism. Conspicuous
 black and white coloration has recently been associated with a range of
 defenses in mammals, including body size (Howell et al. 2021), however red
 coloration as a potentially aposematic signal has yet to be investigated
 in mammals. Squirrels, like most mammals, are unable to perceive red for
 use as a social signal. Here we use a comparative framework to test
 whether redness could be a means of background matching, serve a
 thermoregulatory function or be an honest warning of anti-predator
 defenses across a global distribution of tree squirrels which vary in size
 from 16g to 2.2kg in this study. We measured redness of the dorsum, the
 venter and of red accents of study skin specimens of 57 tree squirrel
 species (N=257) representing 25 genera. We then associated these
 phenotypic variables with environmental variables using phylogenetic
 generalized least squares regression.  We find that increasing
 dorsal redness is associated with more humid environments and closed
 canopies, consistent with prior work that coloration on this body region
 under selection for crypsis (Sheets and Chavez 2020). However, we find
 that ventral redness and maximum redness is associated with large body
 sizes. Our findings suggest that crypsis and aposematism are not mutually
 exclusive, and that aposematism may be more widespread in mammals than is
 currently appreciated.
description: <strong>Phenotypic
 Data.</strong> We measured
 redness color from 318 study skin specimens at the Smithsonian National
 Museum of Natural History (NMNH, Washington, D.C.) representing 73 of the
 148 recognized tree squirrel speciesand across 33 generawithin Sciuridae .
 Up to five individuals were selected per species(µ=4.1, ∂=0.14), if available, which maximized
 representation of available color morphs and subspecies for each species.
 We photographed the dorsal and ventral side of each specimen using a
 digital camera (Sony Alpha a5000) beneath a diffused light from two ESDDI
 85 W 5500K Day Light Florescent bulbs. The specimens were collected from a
 range of years, between 1880 and 2018. 
 We extracted
 the mean A* channel pixel value from the digital images to acquire redness
 color from each study skin specimen. We did this by converting each image
 to CIE LAB colorspace using scikit-image
 in Python. Dorsal redness was measured as the mean
 A* channel pixel value across the entire visible dorsal surface of the
 study skin specimen. Ventral redness (mean A* channel pixel value) was
 focused solely on the single, contiguous monochromatic patch of color
 found in the ventral region of squirrels, and not from other visible areas
 of the body outside of this ventral patch. Both dorsal and ventral redness
 were averaged across all individuals within a
 species.   
 We also measured the maximum redness of
 the dorsum and ventrum from each study skin to capture potentially
 relevant chroma-based signal that is not constrained by averaging redness
 across either the dorsum or ventral patch. We measured a maximum value of
 chromaticity because the salience of a visual signal is dependent on both
 it’s chromaticity and apparent color patch size (would be good to find a
 citation CITE). . To do this, we set a minimum patch size of 10% of the
 visible surface (DORSAL OR VENTRAL OR BOTH??) of the study skin that still
 allowed a large enough patch to be perceived by a receiving animal. We
 convolved the A* channel values with a box linear filter, which is done by
 replacing the A* channel value of each pixel with the mean A* channel
 value of its neighbors plus itself. The size of the filter was set to be
 the smallest square with an area of at least 10% of the surface of the
 specimen visible in the photograph. Pixels that did not belong to the
 specimen and were part of the photo background were masked to a value of
 zero prior to the convolution. The highest A* channel value from the
 resulting convolution was recorded for each specimen’s dorsum and ventrum,
 not just the ventral patch as mentioned for the average A* channel values.
 We then chosethe maximum redness of each species as the maximum convolved
 A* channel value of any individual study skin from each
 species.  
 <strong>Body mass.</strong>
 Body mass data for 58 species was
 sourced from Thorington et al (2012). For another six species, body mass
 was sourced from Pantheria (Jones et al 2009). Finally, body mass for the
 remaining nine species was imputed using <em>Rphylopars
 </em>(Goolsby et
 al 2021) from body length measurements (Thorington et al 2012), first
 molar area (Smith et al 2018) and jaw size (Zelditch et al 2017) assuming
 a Brownian motion model of evolution and the phylogenetic tree produced by
 Menendez et al (2020). We then manually assessed imputations for
 reliability.   
 <strong>Environmental
 Data. </strong> We generated
 climatic data for the species used in this study using geographic
 information science approaches. Polygons representing extant ranges for
 these species were sourced from the IUCN Red List database. Raster files
 with high resolution data on spatial humidity and mean annual temperature
 were sourced from the NASA MODIS website (https://neo.sci.gsfc.nasa.gov). Raster files representing canopy closure were sourced from Hansen et al (2013). Climatic variables for each species range were calculated using the ‘clip’ function in the R package <em>raster </em>(Higmans 2020).