Prediction models using maximum entropy for suitable habitats in the present and future scenarios for rare and endemic Codonopsis affinis in Darjeeling eastern Himalaya

Recent climate research has revealed that climate change will impact biodiversity, particularly in mountainous regions. Furthermore, species that are endemic and rare will be more significantly impacted. Codonopsis affinis (Campanulaceae) is a rare and endemic twiner in the Darjeeling eastern Himalaya. The present study is focused on species distribution modeling of C. affinis using the MaxEnt algorithm. Models were generated by first collecting occurrence points within the study area, followed by model generation. The modeling throws light on the current and future distribution and range shift of the species with respect to climate change. Modeling was performed with six occurrence points and nine uncorrelated bioclimatic and topographic variables. All the generated models performed well, with AUC value of 0.992, and TSS value of 0.904. The main variable that impacts the species distribution happens to be altitude. The current habitat area is 274.5 sq km after applying the 0.61 minimum training presence threshold. Overall, a sharp decline in the probable suitable habitat is observed in the future models compared to the current one, reducing from 8.83% of the total habitat to about 0 to 1.35% in the future. This indicates that future climate change could negatively impact this endemic species. Furthermore, the taxon is also impacted by other anthropogenic factors, such as changes in land use. This implies urgency for prioritizing this neglected species, and hence, it would be ideal to take measures to conserve this rare species either through ex-situ or in-situ approaches.