Photo collection, measurement, and analyses
To assess patterns in male and female chest redness in geladas, we used
objective color measurement methods for digital photographs taken under
natural conditions (i.e., while conducting daily activities like
resting, grazing, or grooming) and while animals were under anesthesia.
Under natural conditions, chest redness was measured from 144 digital
chest photographs of adult males (n =24) and females (n =13)
collected between 2008-2010 (range=2-16 photos per individual, mean=4).
We excluded photos taken within 10 minutes of vigorous activity because
chest redness increases with such activity in males
(Bergman et al., 2009;
DeLacey et al., 2022). We only included photos taken in March and April
of each year because: (1) this was the only dataset available for
females, and (2) previous analyses have demonstrated that males exhibit
seasonal trends in chest redness that could skew male results if
selected over multiple seasons
(Benítez, 2016). While the
animals were under anesthesia, chest redness was measured from photos
taken at the start of anesthetization for both males (n =20) and
females (n =18). For a subset of individuals (n =13 males
and n =3 females) we paired the photo taken at the start of
anesthetization with a second chest photo after a heat pack was applied
to one side of the chest. We include a visualization of the within
individual change in redness after temperature treatment in the
supplementary material (Fig. S1 ), but we did not run
statistical tests due to the small sample size.
For all photos, we also photographed a color standard, the X-Rite
ColorCheckerⓇ Classic chart (hereafter, “ColorChecker
chart”), to correct for variable light conditions by adjusting the
color in the photograph to the known color levels in the chart squares.
Although the digital camera brand and model was not consistent across
all photographs, f-stop, shutter speed, and white balance settings
remained consistent between chart and chest photos. JPEG format photos
were analyzed in Adobe Photoshop (Adobe Inc. 2022) using color profiles
in the RGB color space created in ColorChecker Camera Calibration
(v2.2.0; X-Rite Inc.) software designed for use with the ColorChecker
chart. We measured redness as the Red to Green Ratio (hereafter,
“Red/Green”) because the value in each RGB channel is only informative
relative to values in the other channels
(Bergman & Beehner, 2008).
Detailed methodology and instructions for photo measurement can be found
elsewhere (DeLacey et al.,
2022).
To determine whether males are redder than females during natural
conditions, we constructed a linear mixed-effect model (LMM) with chest
redness as the outcome variable and sex as the predictor variable while
including ID and camera brand as random effects (R packages lme4(Bates et al., 2015) andlmerTest (Kunzetsova
et al., 2017)). Next, to assess whether males have a larger range in
chest redness during natural conditions, we ran a linear regression
model with the range in chest redness within an individual (maximum R/G
- minimum R/G for each individual) as the outcome variable and the
interaction between sex and camera brand as the predictor variable.
Lastly, to determine whether males are redder than females under
anesthesia at baseline, we ran a linear regression model with chest
redness as the outcome variable and camera brand and sex as the
predictor variables.