Spatial patterns of phylogenetic diversity and endemism in the Western Ghats, India: a case study using ancient predatory arthropods

The Western Ghats (WG) mountain chain in peninsular India is a global biodiversity hotspot, one in which patterns of phylogenetic diversity and endemism remain to be documented across taxa. We used a well-characterized community of ancient soil predatory arthropods from the WG to understand diversity gradients, identify hotspots of endemism and conservation importance, and highlight poorly-studied areas with unique biodiversity. We compiled an occurrence dataset for 19 species of scolopendrid centipedes, which was used to predict areas of habitat suitability using bioclimatic and geomorphological variables in Maxent. We used predicted distributions and a time-calibrated species phylogeny to calculate taxonomic and phylogenetic indices of diversity, endemism and turnover. We observed a decreasing latitudinal gradient in taxonomic and phylogenetic diversity in the WG, which supports expectations from the latitudinal diversity gradient. The southern WG had the highest phylogenetic diversity and endemism, and was represented by lineages with long branch lengths as observed from relative phylogenetic diversity/endemism. These results indicate the persistence of lineages over evolutionary time in the southern WG and are consistent with predictions from the southern WG refuge hypothesis. The northern WG, despite having low phylogenetic diversity, had high values of phylogenetic endemism represented by distinct lineages as inferred from relative phylogenetic endemism. The distinct endemic lineages in this sub-region might be adapted to life in lateritic plateaus characterized by poor soil conditions and high seasonality. Sites across an important biogeographic break, the Palghat Gap, broadly grouped separately in comparisons of species turnover along the WG. The southern WG and Nilgiris, adjoining the Palghat Gap, harbour unique centipede communities, where the causal role of climate or dispersal barriers in shaping diversity remains to be investigated. Our results highlight the need to use phylogeny and distribution data while assessing diversity and endemism patterns in the WG.ReadMe: README_1Sep21.docx: details of each R script (code1 - code8) including input and output files Data files: biasMap.tif - sampling bias layer, which is the prediction of a Maxent model which uses all species occurrences as presence locations and all the WorldClim layers plus a soil type layer as predictors biasBg.csv - coordinates of background locations used for Maxent species distribution modeling obtained from a sampling bias layer (biasMap.tif) gps_9Jun20.csv - coordinates of occurrence locations used for Maxent species distribution modeling supp_table_locations - coordinates of occurrence locations used for Maxent species distribution modeling (some formatting differences as compared to gps_9Jun20.csv in terms of species names), used for plotting Figure 1 results_summary_4Apr21.csv - summary of results from Maxent species distribution modeling giving indices of model transferability and performance, and top two predictor variables in terms of permutation importance, used for plotting figures in Appendix S2 biodiverse_16Mar21.csv - input site by species matrix used as input in Biodiverse 3.1 threegenera.tre - phylogenetic tree used for calculations of phylogenetic diversity, endemism and turnover tiplabels.csv - mapping of tip labels to species names in threegenera.tre threegenera_results_16Mar21.csv - results of diversity and endemism indices (taxonomic, phylogenetic, relative phylogenetic) calculated in Biodiverse 3.1 threergenera_struc_randomization_results_16Mar21.csv - results of randomizations of diversity and endemism indices obtained in Biodiverse 3.1 R scripts: Scripts available at https://github.com/bhartidk/centipede_diversity_endemism code1-code4, code6-code8 - details of analysis workflow available in README_1Sep21.docx code5 - instructions for running Biodiverse3.1 GU