2025/04/08 by Yinqiu Ji, Alex Diana, Xueyou Li +17 · 1 voice
Environmental Science · #Species Distribution and Climate Change #Wildlife Ecology and Conservation
paper · pdf · doi:10.22541/au.174412107.76832286/v1
openalex publication_date 2025/04/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/19
The Kunming-Montreal Global Biodiversity Framework needs copious data on species distributions to achieve its targets, but generating such data at scale remains challenging. We used aquatic eDNA (environmental DNA) metabarcoding to sample vertebrate species across the 30,000 km\textsuperscript2 Gaoligongshan protected-area complex along the China-Myanmar border. In just 33 researcher-days, we detected 397 vertebrate species, including 35 Red-Listed species. We introduce the ‘eDNA-aware’ OccPlus occupancy model, which accounts for false-negative and false-positive error at two stages of the eDNA pipeline, field and lab. OccPlus leverages the taxonomic breadth of eDNA datasets by using ordination to estimate species occupancies, even for low-detection species. We recover known biogeographic patterns and find that native terrestrial and fish species have higher occupancies inside protected areas while domesticated species and non-native fishes have higher occupancies outside them. Our study demonstrates how eDNA metabarcoding provides a scalable method for obtaining high-quality, granular, timely, and trustworthy biodiversity data.