Sciurids have one of the greatest diversities of color patterns and hues among mammalian families, but whether these color patterns conform to Gloger’s Rule has not been investigated. Gloger’s rule is the ecogeographic trend that describes the tendency of animals’ pelage to be darker in warmer and wetter environments. Several mechanisms have been proposed explain this trend that relate to various environmental variables. However, these variables frequently correlate with each other which can cause increased Type I error rates in conventional analyses with a single dependent variable. Here we use a new phylogenetic comparative method that implements path analysis to produce a hypothesized series of cause and effect relationships between predictor variables to form a path model. This multi-regression approach allows for the simultaneous exploration of the effects of numerous predictor variables. Our path analysis results using 137 Sciurid species show that squirrel pelage luminance conforms to Gloger’s rule and that there is a significant evolutionary relationship between precipitation and pelage luminance. Also significant were that other commonly found variables (humidity, temperature, and vegetation cover) did not have strong relationships with pelage luminance. Our findings demonstrate that utility of path analysis in phylogenetic comparative studies in studying a trait influenced by several covarying variables.

Luminance Data from Museum Study Skins

To obtain color measurements of the 135 squirrels used in our phylogenetic analysis, we photographed the dorsal profile of museum study skins from the Division of Mammals at the Smithsonian National Museum of Natural History. We used a Sony Alpha 5000 to take digital photographs of specimens against a gray matte background. Two light-boxes containing ESDDI 85W 5500K Day Light Florescent bulbs were positioned at opposing ends of the specimen stage in an interior room without windows. All images had their backgrounds masked by standard image editing software. We then loaded masked images into a custom python script that converted the image data to CIE LAB colorspace. Average luminance was then recorded for the entire dorsal region of the study skin for each species. Higher luminance values indicate brighter pelage color.

Environmental Data

We obtained environmental data for nine predictor variables for all 135 squirrel species from multiple databases. First, we acquired precipitation and temperature values for each species from the Pantheria database (Kate et al, 2009). We obtained canopy-closure data as a proxy measure for lightness of the environment from Hansen et al (2013). Due to memory constraints, the resolution of this dataset was reduced by a factor of 5 using the “aggregate” function in the raster package in R (R Core Team 2013; Hijmans 2014). We also downloaded soil-carbon content and soil density raster data at a 5-km resolution from the ISRIC Soil Grids web app (Batjes et al. 2019). The remaining environmental data (water vapor, net primary productivity, fire frequency, and insolation) were obtained from the NASA MODIS satellite hosted on NASA Earth Observations (https://neo.sci.gsfc.nasa.gov). These data were available for each month for approximately the past 20 years. We downloaded these data at a 11 km by 11 km resolution and averaged them into a single raster file. With all of the downloaded environmental data (except the Pantheria data), we only used data for each species that fell within their species range. To determine this, we downloaded shapefiles of extent range maps of all 135 species from the IUCN (http://www.iucnredlist.org) and then clipped the environmental data based on these map using the raster and rgdal packages in R (Bivand et al. 2013; R Core Team 2013; Hijmans 2014).

Accession Numbers

GenBank accession numbers corresponding to sequences used in the study.