Predicting the current and future suitable habitat distribution of the medicinal tree Oroxylum indicum (L.) Kurz in India

Identifying the distributional range and climatically suitable habitat of a species are crucial for developing an effective conservation strategy. This study aims to simulate the current distribution of climatically suitable habitat for a threatened medicinal tree, Oroxylum indicum (L.) Kurz in India and predict its possible range shifts in future climate scenario. Combined with 19 bioclimatic variables from WorldClim, we used Maxent to predict the potential suitable areas for species in current climatic condition and future climate under three Representative Concentration Pathway (RCP) scenarios by integrating three General Circulation Models (GCMs) for 2050 and 2070. Furthermore, we performed change analysis to identify the precise difference between the current and future distribution of suitable areas of the species for delineating habitat range expansion (gain), habitat contraction (loss) and stable habitats. The model predicted similar to 25.47 % of the geographical area in India is presently climatically suitable for the species. The study revealed that annual precipitation, precipitation of wettest and warmest quarter, precipitation of wettest month, maximum temperature of warmest month and mean temperature of warmest quarter significantly influence the distribution of the studied species. The net habitat loss under three RCP scenarios (RCP 4.5, 6.0 and 8.5) was estimated to range from 10.51 % to 17.31 % for the year 2050, which could further increase 16.63%-20.40% by the year 2070. The finding indicates that rise in temperature could significantly reduce the potential habitat of O. indicum and hence suitable measures need to be taken to conserve this important medicinal plant.

Automated summary

The study used Maxent model to simulate the climatically suitable habitat distribution of Oroxylum indicum in India, revealing the significant influence of factors such as precipitation and temperature on its distribution, and predicted the future habitat range changes under climate change scenarios.