The distinction between the effective size of a population (Ne) and the effective size of its neighborhoods (Nn) has sometimes become blurred. Ne reflects the effect of random sampling on the genetic composition of a population of size N, whereas Nn is a measure of within-population spatial genetic structure and depends strongly on the dispersal characteristics of a species. Although Nn is independent of Ne, the reverse is not true. Using simulations of a population of annual plants, it was found that the effect of Nn on Ne was well approximated by Ne=N/(1-FIS), where FIS (determined by Nn) was evaluated population wide. Nn only had a notable influence of increasing Ne as it became smaller (⩽16). In contrast, the effect of Nn on genetic estimates of Ne 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 Ne ranged from infinity to <0.1% of the true value (defined as Ne based on 100% sampling). Estimates were never accurate unless Nn 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 Ne/N that have been published.