DOI: 10.5061/dryad.3bk3j9kzf
title: eDNA metabarcoding to monitor fish communities in a large river floodplain

description: 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.
description: # eDNA metabarcoding to monitor fish communities in a large river
 floodplain Dataset DOI: [10.5061/dryad.3bk3j9kzf](10.5061/dryad.3bk3j9kzf)
 ## Description of the data and file structure The data were collected as
 part of an experimental and field-based study comparing fish community
 composition assessed through environmental DNA (eDNA) metabarcoding and
 electrofishing surveys across a large river floodplain. Sampling included
 the collection of water samples for eDNA extraction and sequencing,
 concurrent electrofishing surveys for comparison, and the recording of
 environmental variables to evaluate potential drivers of community
 variation. ### Files and variables #### File: edna_env.csv
 **Description:** Environmental variables associated with eDNA samples.
 ##### Variables * station: Sampling sites code names * year: Year of
 sampling * landuse: Land use at the sampling sites * manag: Land
 management at the sampling site * region: Sector the sampling sites are
 located into * Date: Sampling date * UTM_X: UTM geographical cootdinates *
 UTM_Y: UTM geographical cootdinates * Turbidity: Water turbidity recorded
 at sampling site (FNU) * Water_Level: Water level at each sampling site
 was modeled as the difference between GPS-derived altitude and modeled
 water level, with negative values indicating that water covered the site
 (i.e., water level above GPS altitude) * Mean_NDVI: Mean Normalized
 Difference Vegetation Index (NDVI) values at each sampling site for the
 year preceding sampling #### File: elec_env.csv
 **Description:** Environmental variables associated with electrofishing
 samples. ##### Variables * station: Sampling sites code names * year: Year
 of sampling * landuse: Land use at the sampling sites * region: Sector the
 sampling sites are located into * Date: Sampling date * UTM_X: UTM
 geographical cootdinates * UTM_Y: UTM geographical cootdinates *
 Turbidity: Water turbidity recorded at sampling site (FNU) * Water_Level:
 Water level at each sampling site was modeled as the difference between
 GPS-derived altitude and modeled water level, with negative values
 indicating that water covered the site (i.e., water level above GPS
 altitude). * Mean_NDVI: Mean Normalized Difference Vegetation Index (NDVI)
 values at each sampling site for the year preceding sampling #### File:
 edna_lg_clean.csv **Description:** A long format fish abundance table
 derived from eDNA sampling after bioinformatic processing ##### Variables
 * site: Sampling sites code names * round: In 2022, two sampling rounds
 were conducted; this variable indicates the corresponding sampling round.
 * region: Sector the sampling sites are located into * landuse: Land use
 at the sampling sites * year: Year of sampling * CODE_BDRSI: Fish species
 codes * count: Number of sequence * rel_ab: Relative number of sequence at
 each site and dates #### File: elec_long.csv **Description:** A long
 format fish abundance table derived from electrofiching sampling #####
 Variables * station: Sampling sites code names * year: Year of sampling *
 CODE_BDRSI: Fish species codes * count: Abundance * rel_ab: Relative
 abundance at each site and dates #### File: fish_codes.csv
 **Description:** Species names associated with fish species codes #####
 Variables * Family: * Genus: * Species: * CODE_BDRSI: Fish species codes
 #### File: raw_seq.zip **Description:** Raw sequences derived from
 Illumina sequencing. One forder for each sampling year. File names contain
 information as follows: * 2019: filter-site code-year-marker_illumina
 ids_R1 or R2_001.fastq.gz * 2022: marker-site code-round of
 samplingfilter_illumina ids_R1 or R2_001.fastq.gz