Genetic assignment methods for the direct, real‐time estimation of migration rate: a simulation‐based exploration of accuracy and power

TLDR

Genetic assignment methods use genotype likelihoods to infer natal origins, enabling direct, real‑time estimates of dispersal. The study tests and proposes a novel Monte Carlo resampling approach to generate statistical thresholds for identifying F₀ immigrants and directly estimating migration rates in populations with ongoing gene flow. The authors employed simulated datasets and Monte Carlo resampling that preserves linkage disequilibrium and sampling variance to derive accurate critical values for detecting F₀ immigrants. The method’s power was largely unaffected by missing allele frequency, increased with sample size up to about 50 individuals and comprehensive source sampling, and was effectively predicted by plotting genotype likelihoods and mean likelihood ratios.

Abstract

Abstract 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 F 0 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 F 0 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 ( D LR ) appeared to be an effective way to predict whether F 0 immigrants could be identified for a particular pair of populations using a given set of markers.