An assessment of sampling strategies for surveying introgression in watersheds

Extensive translocation and stocking of non-native fish have resulted in widespread patterns of hybridization and genomic introgression. Unfortunately, current methodologies used to survey the disruption of natural patterns of genetic variation often involve sampling from single, accessible sites in a watercourse. This leads to an overestimation of non-native admixture, as modern sampling sites are correlated with historical stocking locations where trail, road, or rail access was available. These strategies can lead to inflated, imprecise estimates of admixture and subsequently, inappropriate conservation measures. Here, we use an individual-based demographic and genetic model to simulate introgression. Then, we use iterative resampling of simulations to determine the relative importance of spatial site arrangement, number of sites, reach length along a watercourse, and number of fish sampled. Results reinforce and demonstrate expectations of statistical theory: that the most represent..., , # Data from: An assessment of sampling strategies for surveying introgression in watersheds

Dataset DOI: [10.5061/dryad.djh9w0wcr](10.5061/dryad.djh9w0wcr)

## Description of the data and file structure

#### Dataset Overview

This dataset was generated from spatial modelling (completed with Unicor and QGIS), spatial demographic modelling (completed with CDMetaPop), sampling algorithms (completed in R and STAN), and a final synthesis of outputs (completed in R). All input files are included for running on Windows or Linux OS. In addition, output files are included from Unicor, sampling algorithms, and final synthesis.

#### Directory Structure

Within the assessmentSampStrat_CJFAS2026.zip folder, the directory structure is as follows:

**Folder: Analysis**

**Folder: BowRiver**

**Folder: SprayReservoir**

**Folder: StarCreek**

#### Software

These simulations require QGIS 3.22 and UNICOR v3.0 ([https://github.com/ComputationalEcologyLab/UNICOR](https://github.com/ComputationalEcology..., ,