Document Type

Article

Publication Date

2022

Publication Title

Metabarcoding and Metagenomics

Abstract

The karst aquifer of the Yucatán Peninsula (YP) in southeastern Mexico is a unique ecosystem in which water-filled sinkholes, locally known as cenotes, connect subterranean waters with the surface. This system is home to around 20 species of freshwater fishes, including several that are endemic and/or threatened. Studies on this unique ichthyofauna have been partially hampered by the technical difficulties associated with sampling these habitats, particularly submerged caves. In this proof-of-concept study, we use environmental DNA (eDNA) metabarcoding to survey the diversity of freshwater fishes associated with the YP karst aquifer by sampling six cenotes from across the Ring of Cenotes region in northwestern Yucatán, a 180-km-diameter semicircular band of abundant karst sinkholes. Through a combination of conventional sampling (direct observation, fishing) and eDNA metabarcoding, we detected eight species of freshwater fishes across the six sampled cenotes. Overall, our eDNA metabarcoding approach was effective at detecting the presence of fishes from cenote water samples, including one of the two endemic cave-dwelling fish species restricted to the subterranean section of the aquifer. Although our study was focused on detecting fishes via eDNA, we also recovered DNA from several other vertebrate groups, particularly bats. These results suggest that the eDNA metabarcoding approach represents a promising and largely noninvasive method to assay aquatic biodiversity in these vulnerable habitats, allowing more effective, frequent, and wide-ranging surveys. Our detection of DNA from aerial and terrestrial vertebrate fauna implies that eDNA from cenotes, besides being a means to survey aquatic fauna, may also offer an effective way to quickly survey non-aquatic biodiversity associated with these persistent water bodies.

Comments

Published in Metabarcoding and Metagenomics by Pensoft Publishers. Available via doi: 10.3897/mbmg.6.89857.

This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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