Predictive distribution modeling of Swertia bimaculata in Darjeeling-Sikkim Eastern Himalaya using MaxEnt: current and future scenarios

Abstract

Abstract Background As global temperatures continue to rise, species distribution modeling is a suitable tool for identifying rare and endangered species most at risk of extinction, along with tracking shifting geographical range. Methods The present study investigates the potential distribution of Swertia bimaculata in the Darjeeling-Sikkim region of Eastern Himalaya in current and future climate scenarios of GFDL-CM3 (Geophysical Fluid Dynamics Laboratory-Climate Model 3) for the year 2050 and year 2070 through MaxEnt presence data modeling. Two sets of variables were used for modeling current scenario. The models were evaluated using AUC (area under the curve) values and TSS (true skill statistic). Results Habitat assessment of the species shows low and sporadic distribution within the study area. A significant decrease is observed in the possible range of the species in the future climate scenario with the habitat decreasing from 869.48 to 0 km2. Resultant maps from the modeling process show significant upward shifting of the species range along the altitudinal gradient. Still, results should be taken with caution given the low number of occurrences used in the modeling. Conclusions The results thus highlight the vulnerability of the species towards extinction in the near future.

Keywords

• Distribution modeling
• Swertia bimaculata
• MaxEnt
• Eastern Himalaya