Likelihood-Based Estimation of the Effective Population Size Using Temporal Changes in Allele Frequencies: A Genealogical Approach

Abstract

Abstract A new genetic estimator of the effective population size (Ne) is introduced. This likelihood-based (LB) estimator uses two temporally spaced genetic samples of individuals from a population. We compared its performance to that of the classical F-statistic-based Ne estimator () by using data from simulated populations with known Ne and real populations. The new likelihood-based estimator () showed narrower credible intervals and greater accuracy than () when genetic drift was strong, but performed only slightly better when genetic drift was relatively weak. When drift was strong (e.g., Ne = 20 for five generations), as few as ~10 loci (heterozygosity of 0.6; samples of 30 individuals) are sufficient to consistently achieve credible intervals with an upper limit <50 using the LB method. In contrast, ~20 loci are required for the same precision when using the classical F-statistic approach. The estimator is much improved over the classical method when there are many rare alleles. It will be especially useful in conservation biology because it less often overestimates Ne than does and thus is less likely to erroneously suggest that a population is large and has a low extinction risk.