Using an ensemble modeling approach to predict the potential distribution for the Kashmir gray langur (Semnopithecus ajax)

Accurate species distribution data is vital for assessing threats and planning conservation. Many primates, especially in remote & challenging areas, are understudied. The endemic Kashmir gray langur, a shy, arboreal folivore in the North-Western Himalayas, is elusive due to its steep, high-altitude habitat. Using ensemble modeling with 35 environmental variables and 144 occurrence points, we predicted its distribution and identified key influencing factors. The model (mean AUC=0.926; TSS=0.78) identified suitable habitats as forested, moderately sloped, mid-elevation areas with low human disturbance, aligning with observed locations. Key factors were pronounced precipitation seasonality, moderate slopes, and optimal diurnal temperature—conditions of threatened temperate forests. We recommend integrating these findings into conservation strategies and enhancing population monitoring for long-term protection.