Climate-driven spatial patterns of diversity, phenology, and habitat suitability in Pyrenaria (Theaceae) across Northeast India

Forests of Northeast India, a global biodiversity hotspot, are increasingly threatened by climate change and human disturbances, placing narrowly distributed plant species at risk of extinction. The genus Pyrenaria (Theaceae), which includes several endemic and poorly studied species, lacks comprehensive ecological and distributional assessments necessary for evidence-based conservation planning. This study integrates extensive field surveys and MaxEnt modeling to assess the diversity, population structure, phenology, and habitat suitability of six Pyrenaria taxa across five states in Northeast India. A total of 40 occurrence points and 167 individuals (47 seedlings, 21 saplings, 99 adults) were recorded, revealing poor regeneration linked to disturbances like logging, agricultural expansion, mining and fire. Habitat suitability was modeled using the MaxEnt algorithm with eleven environmental predictors derived from WorldClim, including elevation after removing correlated variables (r > 0.8). The model showed high predictive accuracy, with Area Under the Curve (AUC) values ranging from 0.850 to 0.999 and True Skill Statistic (TSS) values from 0.50 to 0.998. Habitat suitability analysis revealed large potential distributions for most species, except for the endemic P. cherrapunjeana, which showed a highly restricted suitable habitat of only 1,633 km². Mean diurnal temperature range, precipitation, and elevation emerged as key factors influencing species distribution. By combining field-based ecological data with spatial modeling, this study identifies priority conservation areas and potential reintroduction sites, providing a framework for safeguarding Pyrenaria under ongoing environmental change.