Abstract
<title>Abstract</title> <p> Human activities have drastically altered all ecosystems and ecological processes worldwide, significantly impacting global wilderness areas and wide-ranging predators. For the Anthropocene representative examples are species like common leopard ( <italic>Panthera pardus</italic> ) and snow leopard ( <italic>P. uncia</italic> ) and their prey, which play vital roles in ecosystem dynamics. Using a generic workflow here we quantify and investigated the prediction of habitat suitability and niche overlap of such food chains based on Nepal’s Gaurishankar Conservation Area (GCA), Central Himalaya, where over fifty hydroelectric dams and extensive commercial activities are ongoing. Based on Open Access data, Open Source GIS and Machine Learning and AI ensembles (CART, boosting TreeNet and bagging Random Forest), we developed ecological niche models (ENM) and species distribution models (SDM) workflows using an open access 'Big Data' set of 10,763 camera-days, environmental variables, prey occurrence, and human disturbance factors. Our workflow is ‘generic’, globally transferable and findings reveal substantial human induced habitat overlaps between two large felid species and prey, primarily between 3,000–4,000 m elevation. The common leopard occupies approximately 50.3% (~ 1,127 km <sup>2</sup> ) of the area, while the snow leopard’s suitable habitat is only 5.6% (~ 134 km <sup>2</sup> ). The total overlapping area is approximately 134 km2 (5.6%). Key drivers of spatial distribution include rangelands, alpine meadow, roads/trails and multi-species livestock presence. Our methods demonstrated a more complete and deeper understanding of ecological niches in the Anthropocene. Our Big Data research is more holistic, and these findings offer practical guidance for designing targeted conservation strategies in the region and similar landscapes anywhere in the world. </p>