Evaluates sampling strategies that inform conservation efforts by minimizing genetic admixture estimations in watersheds, indicating best practices for fish management.
Extensive translocation and stocking of non-native fish has 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.
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Sullivan et al. (2026) studied this question.
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