Rodents show darker and redder coloration in warm and rainy environments
Data files
Jan 12, 2024 version files 1.54 MB
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dryad_data.zip
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README.md
Abstract
Aim: Gloger’s rule predicts that warmer and wetter areas favor more pigmented animals. Yet, the original formulation lacks differentiation between the two primary pigments: eu- and pheomelanin. We examined geographic variation in eumelanin and pheomelanin to unravel how various ecological factors influence pigment deposition, and to assess support for the complex version of Gloger’s rule.
Location: South America.
Time period: Contemporary.
Major Taxa Studied: Sigmodontine rodents.
Methods: We extracted pelage color data from 231 species and quantified the variation in eu- and pheomelanin deposition at the assemblage level. We performed linear multiple regression to investigate the influence of temperature, precipitation, predator diversity, and UVA-B radiance in eumelanin (lightness) and pheomelanin (redness).
Results: Our findings support the original formulations of Gloger’s rule. Rodents in warmer and rainier regions, which also entails greater exposure to UV radiation and a diverse range of predators, exhibit darker-colored pelage. In addition, redder rodents prevail in warmer environments. However, contrary to the rule predictions, we observe a reversal for reddish patterns in relation to precipitation, with rainier regions showcasing more intense red rodents.
Main conclusions: Our study breaks new ground by investigating previously unexplored facets of Gloger's rule in a continental mammalian group. We discovered compelling evidence that darker and redder coloration align closely with temperature and rainfall gradients. Although we found support for eumelanin-pelage predictions, expectations for pheomelanin pigmentation were only partially met. Our results might suggest that selective pressures act differently on dark and reddish coloration, revealing that coloration patterns in response to climate are more intricate than previously formulated.
README: Rodents in warm and rainy regions exhibit darker and redder coloration
This release encompasses both the code and data that underpin the conclusions as outlined in the paper. Elaborated methods can be found within the main body of the corresponding article.
Description of the data and file structure
The materials are organized into distinct folders according to their primary roles within the analyses. A concise outline of the data structure within each folder is presented below (in bold).
Color_assembly_data folder
Lightness_space.csv: Data on average lightness values in South American grid cells, determined by co-occurring species within each cell. Matrix columns: 'ID' (grid cell identification), 'RGB_mean' (average lightness from RGB species values), 'CIE_l_mean' (CIELAB colorspace lightness), 'HSV_v_mean' (HSV colorspace lightness).
Redness_space.csv: Data on average redness values in South American grid cells, determined by co-occurring species within each cell. Matrix columns: 'ID' (grid cell identification), 'Redness_mean' (average redness).
Color_species_data folder
Species_lightness.csv: Species-level pelage lightness obtained by averaging values from sampled specimens. Matrix columns: 'Species' (species name), 'Pic_num' (photos per species sampled), 'RGB_mean' and 'RGB_sd' (mean and standard deviation of species lightness in RGB, respectively), 'CIE_l_mean' and 'CIE_l_sd' (mean and standard deviation of species lightness in CIELAB colorspace, respectively), 'HSV_v_mean' and 'HSV_v_sd' (mean and standard deviation of species lightness in HSV colorspace, respectively).
Species_redness.csv: Species-level pelage redness obtained by averaging values from sampled specimens. Matrix columns: 'Species' (species name), 'Pic_num' (photos per species sampled), 'Redness_mean' and 'Redness_sd' (mean and standard deviation of species redness, respectively).
Combined_datasets_space folder
Combined_datasets.csv: Dataset containing both response variables (lightness and redness) and predictor variables (temperature, precipitation, predator diversity, and UVA-B radiance) for each grid cell. Matrix columns: 'ID' (grid cell identification), 'long' (cell longitude), 'lat' (cell latitude), 'RGB_mean' (average lightness from RGB species values), 'CIE_l_mean' (CIELAB colorspace lightness), 'HSV_v_mean' (HSV colorspace lightness), 'Redness_mean' (average redness), 'bio1' (annual mean temperature), 'bio12' (annual mean precipitation), 'UVB_UVA' (UVA/B radiance), 'Accip_rich' (Accipitriformes species richness), 'Carnivora_rich' (Carnivora species richness), 'Falc_rich' (Falconiformes species richness), 'Strig_rich' (Strigiformes species richness), 'Vip_rich' (Viperidae species richness).
Data_units.txt: Text annotator describing the units of the used variables.
Shapefiles folder
color_space.: Shapefile for mapping lightness and redness coloration across South America, with extensions including '.dbf', '.prj', '.shp', '.shx'.
south_america.: Shapefile of South American borders for visualization purposes, with extensions including '.dbf', '.prj', '.shp', '.shx', '.avl', '.xml'
Statistical_analyses_codes folder
'Statistical_analyses.R': R script encompassing the procedures for primary statistical analyses and figure reproduction as described in the main text.
Methods
Usage notes
This provided data and code are essential for reproducing the results detailed in the article. The materials are organized into specific folders, each serving a primary role in the analyses. The README file offers a succinct overview of the data structure within each folder.