Assessing fish diversity in small streams and ponds of the Peruvian Amazon using environmental DNA metabarcoding.

The Amazon basin harbors exceptional fish diversity, with more than 3,500 species reported. However, this biodiversity is increasingly threatened by anthropogenic activities and climate change. The Peruvian Amazon alone is home to nearly 1,000 freshwater fish species - approximately one-third of the entire Amazon - yet significant gaps remain in our understanding of their distribution, ecology, and conservation status. Molecular approaches, particularly environmental DNA (eDNA) metabarcoding, have emerged as promising alternatives for rapid and accurate biodiversity assessment. In this study, a metabarcoding workflow targeting a fragment of the 12S gene to eDNA samples collected from small streams and ponds near Iquitos, Peru, was applied to evaluate the applicability of this approach for local fish community inventories. Water from 12 sites was filtered, and DNA was extracted, amplified, and sequenced using high-throughput Illumina technology. Bioinformatic analyses included MOTU clustering, haplotype identification, and taxonomic assignment using the Lowest Common Ancestor (LCA) algorithm. A total of 226 amplicon sequence variants (ASVs) were identified, 95 of which were assigned to fish taxa and clustered into 44 MOTUs across four orders: Characiformes, Gymnotiformes, Siluriformes, and Cichliformes. The study highlights the effectiveness of eDNA metabarcoding in detecting both common and elusive species, while also highlighting current limitations due to incomplete DNA barcode reference libraries. These findings underscore the need to expand barcode databases to fully harness the potential of eDNA for monitoring Amazonian fish biodiversity and support its use as a valuable tool for inventorying fish communities in sensitive and understudied environments.