title: Likelihood-based estimation of the effective population size using temporal changes in allele frequencies: a genealogical approach.
abstract: A new genetic estimator of the effective population size (N(e)) 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 N(e) estimator (N(eFk)) by using data from simulated populations with known N(e) and real populations. The new likelihood-based estimator (N(eLB)) showed narrower credible intervals and greater accuracy than (N(eFk)) when genetic drift was strong, but performed only slightly better when genetic drift was relatively weak. When drift was strong (e.g., N(e) = 20 for five generations), as few as approximately 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, approximately 20 loci are required for the same precision when using the classical F-statistic approach. The N(eLB) 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 N(e) than does N(eLB) and thus is less likely to erroneously suggest that a population is large and has a low extinction risk.
authors.affiliation: Laboratoire de Biologie des Populations d'Altitude, UMR CNRS 5553, Université Joseph Fourier, F38041 BP53 Cedex 9 Grenoble, France. pierre.berthier@zoo.unibe.ch
authors.forename: Pierre
authors.initials: P
authors.lastname: Berthier
authors.forename: Mark A
authors.initials: MA
authors.lastname: Beaumont
authors.forename: Jean-Marie
authors.initials: JM
authors.lastname: Cornuet
authors.forename: Gordon
authors.initials: G
authors.lastname: Luikart
mesh_terms: D000818:Animals; D005787:Gene Frequency / Q000235:genetics*; D006801:Humans; D016013:Likelihood Functions; D010375:Pedigree; D011156:Population Density