Figure 1From: An autoregressive model for global vertebrate richness rankings: long-distance dispersers may have stronger spatial structures Illustration of the color extraction and classification procedures. The procedures in the present study were used for generating species richness ranks of grid cells from a hypothetical richness map. The core of this procedure was to convert the color from each of the grid cells in the map into red, green, and blue (RGB) channels with numeric values ranging 0 ~ 255. The k-means clustering method was then applied to the resultant RGB color channel matrices to reconstruct clusters of groups for the RGB numeric data. Finally, a naked-eye check of the numeric data grouping was carried out to match the richness classes in the original and hypothetical richness maps. After the visual check, a richness rank was assigned to each of the grid cells to obtain the resultant richness rank map, which was used for the subsequent autoregressive analyses.Back to article page