Modeling the Current and Future Distribution of (Roxb.) Suksathan & Borchs.: A Monotypic Plant Endemic to the Western Ghats-Sri Lanka Biodiversity Hotspot.

Species distribution modeling (SDM) is an essential tool in ecology and conservation for predicting species distributions based on species presence/absence data and environmental variables. The present study aimed to understand the distribution pattern and habitat suitability of under current and future climate change scenarios (2050 and 2070) using and tools. The study also intended to identify key environmental predictors of distribution. Species occurrence data were collected from various sources, including herbarium (online and physical), field surveys, and online databases, yielding 105 unique locations in the Western Ghats (WG) of India and Sri Lanka. We used 19 bioclimatic variables and elevation data sourced from WorldClim for modeling. The and models showed excellent performance in predicting the distribution of , with area under the curve values of 0.958 (± 0.002) and 0.93, respectively. In modeling, Temperature Seasonality (bio4) was the most significant environmental parameter, followed by the Precipitation of the Coldest Quarter (bio19). In contrast, the Annual Mean Temperature (bio1), Temperature Seasonality (bio4), and Annual Precipitation (bio12) were among the key contributors in . Both the models predicted relatively lesser areas in the species' distribution range as highly suitable habitats (HSH) in India and Sri Lanka. We found divergent trends in predicting distributions using and , particularly for future projections. Nevertheless, both models predicted significant habitat loss under future climate change scenarios, especially under RCP85, with varying degrees of suitability across India and Sri Lanka. Overall, our findings on expected habitat loss under future climate change scenarios highlight the importance of conserving , which has already been declared critically endangered (CR) in Sri Lanka.