Data from: 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 representative sampling strategies are those that use
systematically distributed sampling locations and multiple sites per
watershed. This study provides recommendations about robust sampling
design and outlines the risks of poor sampling decisions that can lead to
negative conservation outcomes. The dataset is separated into the three
watersheds that were simulated. All files required to run the simulations
and output datasets are contained within the respective folders. Technical
descriptions of the steps and parameterization for the spatial modelling
and demographic modelling are included in two separate pdfs. Data and
scripts for the final analysis of all watersheds are contained in the
Analysis folder. Note that spatial and demographic modelling was built for
the sampling strategy analysis and so may not reflect actual hydrological
or biological conditions in these watersheds.