Effective fishery management relies on knowing the relative contributions of distinct populations to mixed-stock harvests. Mixed-stock analyses increasingly adopt single nucleotide polymorphism (SNP) panels but could make better use of precise spatial information to improve understanding of population distributions, movements, and structure. Together with local partners, we collected and georeferenced 1051 samples of lake-migratory brook trout between 2020 and 2022 from three large lakes in Quebec (Mistassini, Mistasiniishish, Waconichi). We then used a GT-seq (Genotyping-in-Thousands by sequencing) SNP panel to infer population genetic structure and determine spatial harvest contributions of genetically distinct populations. Our results revealed population structure in two of three study lakes, with few populations (n = 1–2) contributing the majority (>80%) of mixed-stock harvest in each lake. We also detected extensive movements of brook trout within and between lakes, spatial segregation of populations in one lake, and an unknown (unsampled) population in another lake. Our results illustrate the precision afforded by combining GT-seq and georeferencing of samples to generate insights into the ecology and genetics of migratory fishes, thereby facilitating local decision-making for sustainable fisheries. [ABSTRACT FROM AUTHOR]

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