Table 2. Biodiversity-related attributes used to rank the cells.

For each variable, the subscript k indexes a grid cell that is being ranked against the other cells. These data are available in raster format at https://doi.org/10.5066/P95LH274.

Description
Index of Plant Biodiversity (Sk,plant)—We used SDMs for 138 plant species that were developed by The Nature Conservancy using a maximum entropy (MaxEnt) approach [35, 36]. The continuous probabilities of presence were converted to binary scores (1 = suitable, 0 = unsuitable) using thresholds that maximized the recovery of both true positives and true negatives for each species in testing data [37]. The binary scores for the 138 plant species were summed to compute predicted plant species richness. Reference: [36]
Index of Reptile and Amphibian (herpetofauna) Biodiversity (Sk,herp)—We used SDMs (random forest or generalized additive models) developed by Franklin et al. [38] for 24 reptiles and 5 amphibians. The probability of presence for the 29 species was summed to yield predicted herpetofauna species richness. Reference: [38]
Index of Bird Biodiversity (S k,bird)—We used SDMs (partitioned Mahalanobis D2 models) developed by KLP for 6 bird species. Habitat similarity index scores from 0 (low suitability) to 1 (high suitability) were summed to yield predicted bird species richness. Reference: Unpublished
Index of Mammal Biodiversity (Sk,mamm)—We used SDMs for 18 mammal species ranging from small mammals to mountain lions developed by JED and ST using ecological niche factor analysis, implemented in Biomapper [39]. The resulting suitability scores were rescaled on 0.0 to 1.0 and summed to yield predicted mammal richness. Reference: [40]
Mean Genetic Diversity (Gk,divers)—We used previously developed raster models of intra-population sequence diversity averaged across 14 small animal species (invertebrates, amphibians, reptiles, birds and mammals). We interpolated continuous rasters from average sequence diversity measured within populations for the 14 species (S1 Appendix) for which mtDNA sequence data were collected throughout southern California. These were averaged into a single raster depicting regional hotspots of intrapopulation genetic diversity for the species assemblage. Reference: [28]
Mean Genetic Divergence (Gk,diverg)—A similar approach was used to create a raster depicting regional hotspots of average genetic divergence for 21 small animal species (invertebrates, amphibians, reptiles, birds and mammals). Sequence divergence between pairs of populations was mapped to the geographic midpoints between populations and interpolated into continuous rasters the 21 species (S1 Appendix) and averaged into a single layer. Reference: [28]