Combining environmental DNA metabarcoding and specimen collections to describe fish biodiversity in the Tukakas Bay, Colombian Caribbean
DOI:
https://doi.org/10.15517/4z83mm52Keywords:
Bio Expedition “Lamuuna Neimalu’u”; Wayuu indigenous communities; La Guajira desert; Colombian Caribbean; molecular taxonomyAbstract
Introduction: Tukakas Bay, located on the border between Colombia and Venezuela, is practically unknown in terms of its marine biodiversity. This lack of knowledge generated the need to carry out an expedition to evaluate the current state of its associated biodiversity. Objective: To describe for the first time fish biodiversity in Tukakas Bay through integrated sampling methodologies. Methods: We combined environmental DNA (eDNA) from seawater with observations and morphological methods, and subsequent mitochondrial DNA barcoding (COI, 16S) to describe fish biodiversity. Water samples for eDNA analysis were concentrated in four transects along the bay and processed in laboratory. Visual censuses were carried out through scuba diving and snorkelling, and fish were collected in 17 stations. Tissue samples were subtracted and preserved for DNA barcoding. Voucher specimens were fixed and preserved for taxonomy. Both specimens and tissue samples are part of reference collections at MHNMC, and their metadata are available in the public domain. Results: We identified 481 ASVs belonging to 95 species, 68 genera, and 52 families from eDNA, visual censuses, and morphology (including DNA barcoding). Detections made with eDNA included solitary species and represented 65 % of all identified fish taxa in Tukakas Bay, from which 15 species were also observed or collected. Specimen collections were effective for the creation of 45 DNA barcodes and 164 DNA sequences, and the confirmation of taxonomic assignations obtained by the other two methods. We improved taxonomic resolution for 20 % of the taxa by combining these three survey methods. Conclusion: Integrating eDNA metabarcoding approaches to traditional fish surveys significantly improves biodiversity assessments specially on remote areas.
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