A groundbreaking study led by Prof. Douglas W. Yu at the Kunming Institute of Zoology, Chinese Academy of Sciences, has ushered in a new era for biodiversity monitoring in complex mountain ecosystems. Published in Ecology Letters, the research demonstrates how environmental DNA (eDNA) metabarcoding can deliver high-quality, large-scale species distribution data efficiently—addressing a critical global challenge for achieving the Kunming-Montreal Global Biodiversity Framework goals.

In the Gaoligong Mountains—a unique convergence of three global biodiversity hotspots and a vital ecological barrier in Southwest China—the team surveyed a 30,000 km² area, detecting 389 vertebrate species with just 33 fieldwork days and 69 lab days. This unprecedented efficiency uncovered rare and endangered species, including the critically endangered Malayan pangolin (Manis javanica), the endangered dhole (Cuon alpinus), Shortridge’s langur (Trachypithecus shortridgei), and the Chinese red panda (Ailurus styani), as well as nationally protected species such as the Gaoligong takin (Budorcas taxicolor) and Sclater’s monal (Lophophorus sclateri).

The key innovation, "OccPlus"—a new multi-species occupancy model—accurately filters eDNA contamination, ensuring reliable distributions. For instance, it correctly identified false positives for the takin in southern sites, reconstructing its true northern-only range, which traditional models failed to do.

Findings include a clear north-to-south increase in freshwater fish richness, revealing that protected areas limit invasives mainly through natural barriers like high elevation. Crucially, OccPlus pinpointed human-driven invasion hotspots in Bingzhongluo Town, linked to tourism and aquaculture, underscoring anthropogenic pressures. The study also provided molecular evidence of protected areas' success: native terrestrial vertebrates showed significantly higher occupancy inside reserves than outside.

This scalable "gold standard" method empowers global conservation in rugged terrains, offering timely, trustworthy data for policy and management.