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.