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Genetic assignment methods use genotype likelihoods to draw inference about where individuals were or were not born, potentially allowing direct, real-time estimates of dispersal. We used simulated data sets to test the power and accuracy of Monte Carlo resampling methods in generating statistical thresholds for identifying F0 immigrants in populations with ongoing gene flow, and hence for providing direct, real-time estimates of migration rates. The identification of accurate critical values required that resampling methods preserved the linkage disequilibrium deriving from recent generations of immigrants and reflected the sampling variance present in the data set being analysed. A novel Monte Carlo resampling method taking into account these aspects was proposed and its efficiency was evaluated. Power and error were relatively insensitive to the frequency assumed for missing alleles. Power to identify F0 immigrants was improved by using large sample size (up to about 50 individuals) and by sampling all populations from which migrants may have originated. A combination of plotting genotype likelihoods and calculating mean genotype likelihood ratios (DLR) appeared to be an effective way to predict whether F0 immigrants could be identified for a particular pair of populations using a given set of markers.
Defining populations and identifying ecological and life-history characteristics affecting genetic structure is important for understanding species biology and hence, for managing threatened or endangered species or populations. In this study, populations of the world's largest indigenous Atlantic salmon (Salmo salar) stock were first inferred using model-based clustering methods, following which life-history and habitat variables best predicting the genetic diversity of populations were identified. This study revealed that natal homing of Atlantic salmon within the Teno River system is accurate at least to the tributary level. Generally, defining populations by main tributaries was observed to be a reasonable approach in this large river system, whereas in the mainstem of the river, the number of inferred populations was fewer than the number of distinct sampling sites. Mainstem and headwater populations were genetically more diverse and less diverged, while each tributary fostered a distinct population with high genetic differentiation and lower genetic diversity. Population structure and variation in genetic diversity among populations were poorly explained by geographical distance. In contrast, age-structure, as estimated by the proportion of multisea-winter spawners, was the most predictive variable in explaining the variation in the genetic diversity of the populations. This observation, being in agreement with theoretical predictions, emphasizes the essence of large multisea-winter females in maintaining the genetic diversity of populations. In addition, the unique genetic diversity of populations, as estimated by private allele richness, was affected by the ease of accessibility of a site, with more difficult to access sites having lower unique genetic diversity. Our results show that despite this species' high capacity for migration, tributaries foster relatively closed populations with little gene flow which will be important to consider when developing management strategies for the system.
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