JI, Yinqiu;
Diana, Alex;
Li, Xueyou;
Matechou, Eleni;
Griffin, Jim;
Liu, Shuwei;
Luo, Mingjie;
... Popescu, Viorel; + view all
(2025)
High quality, granular, timely, trustworthy, and efficient vertebrate species distribution data across a 30,000 km2 protected area
complex.
Ecology Letters
(In press).
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1318817.pdf - Accepted Version Access restricted to UCL open access staff until 18 April 2026. Download (16MB) |
Abstract
The routine generation of species distribution data \textit{at scale} remains a challenge. We used aquatic environmental DNA metabarcoding to sample vertebrate species across the 30,000 sqkm 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.
| Type: | Article |
|---|---|
| Title: | High quality, granular, timely, trustworthy, and efficient vertebrate species distribution data across a 30,000 km2 protected area complex |
| Publisher version: | https://onlinelibrary.wiley.com/journal/14610248 |
| Language: | English |
| Additional information: | This version is the author-accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | vertebrates, environmental DNA, monitoring, biodiversity conservation, ob24 servation error, occupancy modeling, Kunming-Montreal Global Biodiversity Frame25 work, Gaoligongshan, Three Parallel Rivers, Yunnan, China, Myanmar |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10214834 |
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