eDNA metabarcoding to monitor fish communities in a large river floodplain

This dataset contains raw and processed environmental DNA (eDNA) metabarcoding and electrofishing data used to compare fish community composition across the floodplain of Lake St. Pierre, the largest floodplain habitat along the St. Lawrence River (Québec, Canada). The study aimed to evaluate the effectiveness of eDNA metabarcoding relative to traditional electrofishing for biomonitoring fish diversity in a hydrologically dynamic and heterogeneous floodplain system. Sampling was conducted across multiple floodplain sectors encompassing a gradient of land uses, from natural wetlands to annual crop agriculture.

The dataset includes: (1) raw Illumina sequence files from eDNA samples, (2) processed read tables generated following stringent bioinformatic filtering and taxonomic assignment, (3) site-level electrofishing catch data including species identity, abundance, and biomass, and (4) associated environmental metadata (e.g., sector, land use classification, geographic coordinates).

These data underpin analyses demonstrating that eDNA metabarcoding detects a broader range of species than electrofishing, while both methods reliably capture the most abundant taxa. The dataset further supports findings that eDNA-derived fish community composition is more strongly associated with spatial structuring across floodplain sectors than with variation in land use. The deposited files can be reused to explore species-specific detection patterns, method congruence, and spatial drivers of fish diversity in large river floodplains, and to inform future methodological comparisons in freshwater biomonitoring.