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Samples from subdivided populations yield biased estimates of effective size that overestimate the rate of loss of genetic variation
Author(s) -
Ryman Nils,
Allendorf Fred W.,
Jorde Per Erik,
Laikre Linda,
Hössjer Ola
Publication year - 2014
Publication title -
molecular ecology resources
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.96
H-Index - 136
eISSN - 1755-0998
pISSN - 1755-098X
DOI - 10.1111/1755-0998.12154
Subject(s) - biology , effective population size , population size , population , sampling (signal processing) , sample size determination , gene flow , statistics , variance (accounting) , population genetics , evolutionary biology , genetic variation , econometrics , genetics , mathematics , gene , demography , computer science , accounting , filter (signal processing) , sociology , business , computer vision
Many empirical studies estimating effective population size apply the temporal method that provides an estimate of the variance effective size through the amount of temporal allele frequency change under the assumption that the study population is completely isolated. This assumption is frequently violated, and the magnitude of the resulting bias is generally unknown. We studied how gene flow affects estimates of effective size obtained by the temporal method when sampling from a population system and provide analytical expressions for the expected estimate under an island model of migration. We show that the temporal method tends to systematically underestimate both local and global effective size when populations are connected by gene flow, and the bias is sometimes dramatic. The problem is particularly likely to occur when sampling from a subdivided population where high levels of gene flow obscure identification of subpopulation boundaries. In such situations, sampling in a manner that prevents biased estimates can be difficult. This phenomenon might partially explain the frequently reported unexpectedly low effective population sizes of marine populations that have raised concern regarding the genetic vulnerability of even exceptionally large populations.