Reduced sampling intensity through key sampling site selection for optimal characterization of riverine fish communities by eDNA metabarcoding

Effective conservation management of river systems requires a comprehensive understanding of local and regional biodiversity, necessitating accurate characterization of species communities. Environmental DNA (eDNA) metabarcoding has emerged as a pivotal tool for assessing aquatic organisms, especially fish communities. However, optimal sampling resolution and site positioning to obtain robust fish diversity indices across heterogeneous river systems remain inadequately understood. This study empirically evaluates the optimal number of eDNA samples needed to accurately capture diversity both locally and stream-wide across three distinct river systems, comparing eDNA metabarcoding results to traditional electrofishing data. Habitat and landscape factors were characterized to interpret the localisation of key sampling sites contributing most to the overall species richness. We detected 30 fish species via eDNA metabarcoding, compared to 28 species by electrofishing, with eDNA requiring few..., A comprehensive sampling campaign was conducted across 60 sites in the northern region of Belgium, spanning three rivers: Barbierbeek, Herk, and Berwinne. Each river was sampled on two spatial scales: ten 100-meter transects for small-scale sampling and ten 100-meter sections at 1-kilometer intervals for large-scale sampling. Per sampling site, water samples were taken, followed by electrofishing. The water samples were filtered and analysed using eDNA metabarcoding. This dataset includes the data of the eDNA metabarcoding as well as the raw fish count from the electrofishing activities. Raw metabarcoding data was deposited on the NCBI's Sequence Read Archive (SRA) under BioProject number PRJNA1165199. The bioinformatical pipeline as used on these raw read counts is available on Zenodo (https://zenodo.org/record/3731310#.Y8pdbXbMI2w). The OBITools software was used for further processing of the generated sequence data. The resulting count table as available here was used for further qua..., , # Data from: Reduced sampling intensity through key sampling site selection for optimal characterization of riverine fish communities by eDNA metabarcoding

[https://doi.org/10.5061/dryad.0cfxpnwb5](https://doi.org/10.5061/dryad.0cfxpnwb5)

## Description of the data and file structure

Dataset title: \"Data from: Reduced sampling intensity through key sampling site selection for optimal characterization of riverine fish communities by eDNA metabarcoding\"

Principle investigator: Charlotte Van Driessche ([[e-mail]](mailto:[e-mail]))

Co-investigators: Teun Everts, Io Deflem, Sabrina Neyrinck, Dries Bonte, Rein Brys

Data collection data: May, July 2023

Geographic location of data collection: Belgium, Flanders (Northern Region)

### Files and variables

#### File: Data\_VanDriesscheEtAl\_key\_sampling.xlsx

Creation data file: the 7th of October 2024

The dataset contains one tab page.

1\. Full: This is the full dataset already including elect...