High Quality, Granular, Timely, Trustworthy and Efficient Vertebrate Species Distribution Data Across a 30,000 km 2 Protected Area Complex

Abstract

The routine generation of species distribution data at scale remains a challenge. We used aquatic environmental DNA metabarcoding to sample vertebrate species across the 30,000 km 2 Gaoligongshan region along the China–Myanmar border. In just 56 calendar days (33 researcher‐field‐days + 69 researcher‐lab‐days), we detected 389 vertebrate species, of which 35 are Red‐Listed. We introduce the ‘eDNA‐aware’ OccPlus occupancy model, which accounts for false‐negative and false‐positive error in the field and lab. OccPlus leverages the taxonomic breadth of eDNA datasets by using ordination to estimate species occupancies. 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 can obtain high‐quality, granular, timely, trustworthy and efficient species distribution data to facilitate nature conservation and restoration.

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