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

Area of Science:

• Ichthyology
• Molecular Ecology
• Environmental DNA (eDNA) analysis

Background:

• The Amazon basin boasts immense fish diversity, with over 3,500 species, but faces threats from human activities and climate change.
• The Peruvian Amazon, hosting nearly 1,000 freshwater fish species, has significant knowledge gaps regarding distribution, ecology, and conservation status.
• Environmental DNA (eDNA) metabarcoding offers a rapid and accurate method for biodiversity assessment.

Purpose of the Study:

• To evaluate the applicability of eDNA metabarcoding for local fish community inventories in the Peruvian Amazon.
• To assess the effectiveness of a 12S gene metabarcoding workflow for detecting fish species in small streams and ponds.

Main Methods:

• Collected water samples from 12 sites near Iquitos, Peru.
• Extracted, amplified, and sequenced eDNA using a 12S gene target and Illumina technology.
• Performed bioinformatic analyses including MOTU clustering, haplotype identification, and taxonomic assignment via LCA.

Main Results:

• Identified 226 amplicon sequence variants (ASVs), with 95 assigned to fish taxa.
• Clustered fish ASVs into 44 molecular operational taxonomic units (MOTUs) across four orders: Characiformes, Gymnotiformes, Siluriformes, and Cichliformes.
• Demonstrated eDNA metabarcoding's capability to detect both common and elusive fish species.

Conclusions:

• eDNA metabarcoding is effective for fish community inventories in understudied Amazonian environments.
• Current limitations include incomplete DNA barcode reference libraries, highlighting the need for database expansion.
• eDNA metabarcoding is a valuable tool for monitoring Amazonian fish biodiversity, supporting conservation efforts.