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

Abstract

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 o0.1% 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.

A genomic approach to inferring kinship reveals limited intergenerational dispersal in the yellow fever mosquito

“…In interpreting these values, it is essential to be clear about the distinction between NS and effective population size ( N e ). NS is a parameter representing breeding structure in an isolation‐by‐distance framework and relates directly to dispersal, while N e is dependent on local species abundance and thus habitat availability (Nunney, ). These parameters are therefore expected to estimate different numbers of individuals.…”

A genomic approach to inferring kinship reveals limited intergenerational dispersal in the yellow fever mosquito

“…In interpreting these values, it is essential to be clear about the distinction between NS and effective population size (Ne). NS is a parameter representing breeding structure in an isolation by distance framework, and relates directly to dispersal, while Ne is dependent on local species abundance and thus habitat availability (Nunney, 2016). These parameters are therefore expected to estimate different numbers of individuals.…”

Spatial population genomics of the brown rat (Rattus norvegicus) in New York City

“…The presence of localized spatial genetic structure in urban rats works to maintain high population‐wide genetic diversity as alleles drift differently in different geographic locations (Nunney, ) and ensures overall population persistence in the case of local disturbance or eradication of individual colonies (Ray, ). Gene flow among adjacent rat colonies supports a stepping‐stone model of IBD, which promotes gene flow across the entire urban landscape over many successive generations of short distance dispersal.…”