Predicting habitat suitability of critically endangered Nepenthes sumatrana

Abstract Nepenthes sumatrana is a tropical pitcher plant endemic to Sumatra. It has been categorised as critically endangered based on the IUCN Red List. often occupies in lowland forest of Its habitat threatened by land use conversion recent decade. Due high threats wild, conservation efforts are necessarily required. not possible assess all locations that suitable for this species. In terms addressing issue, Species Distribution Modelling considered an alternative way identify regions have similar environmental conditions where species known occur. The occurrence records were derived from Global Biodiversity Information Facility and reliable scientific papers. Topography, soil, climate cover used predictors model. MaxEnt algorithm was predict suitability. produces predictive model with AUC value 0.833 indicating good performance. habitats predicted several different information about suitability would be useful prioritize protected areas Furthermore, our findings valuable discovery unknown subpopulation.