Prediction of the distribution pattern

The GPS coordinates were employed for ENM to predict the potential distribution of populations determining suitable niches for the species. For confirmation of the result both, BioClim and MaxEnt based models were applied as the assembling and comparing the results from different models can give robust projection^49,50. The BioClim algorithm was applied using the envelope method as implemented in program DIVA-GIS v7.5⁴⁷ for baseline and predicted bioclimatic variables. MaxEnt model was applied through program MaxEnt v3.4.1^50–52 to evaluate the response of niches to the bioclimatic variables for baseline and predicted climatic regimes. For training with threshold-depended sensitivity model (threshold = 0.5), default parameters in program setting were preferred with 50 replications and 500 iterations doing jackknife and to measure variable importance. The results obtained for two different models for two climatic regimes were correlated and the proportion of overlapping niches was determined through program ENMtools v1.8⁵³ applying relative rank statistics⁵⁴. Based on the significant correlation among the bioclimatic variables obtained through program ENMtools v1.8, finally climatic variables viz. minimum temperature (T_MIN), maximum temperature (T_MAX), temperature range (T_RANGE), isothermality (I), and mean annual precipitation (MAP) were tested to find out the limiting factor for the species distribution.