The effect of neighborhood size on effective population size in theory and in practice

The distinction between the effective size of a population (N-e) and the effective size of its neighborhoods (N-n) has sometimes become blurred. N-e reflects the effect of random sampling on the genetic composition of a population of size N, whereas N-n is a measure of within-population spatial genetic structure and depends strongly on the dispersal characteristics of a species. Although N-n is independent of N-e, the reverse is not true. Using simulations of a population of annual plants, it was found that the effect of N-n on N-e was well approximated by N-e = N/(1 - F-IS), where F-IS (determined by N-n) was evaluated population wide. N-n only had a notable influence of increasing N-e as it became smaller (<= 16). In contrast, the effect of N-n on genetic estimates of N-e was substantial. Using the temporal method (a standard two-sample approach) based on 1000 single-nucleotide polymorphisms (SNPs), and varying sampling method, sample size (2-25% of N) and interval between samples (T = 1-32 generations), estimates of N-e ranged from infinity to <0.1% of the true value (defined as N-e based on 100% sampling). Estimates were never accurate unless N-n and T were large. Three sampling techniques were tested: same-site resampling, different-site resampling and random sampling. Random sampling was the least biased method. Extremely low estimates often resulted when different-site resampling was used, especially when the population was large and the sample fraction was small, raising the possibility that this estimation bias could be a factor determining some very low N-e/N that have been published.