Conservation Genetics

, Volume 15, Issue 1, pp 23–35 | Cite as

Testing single-sample estimators of effective population size in genetically structured populations

  • Clare E. Holleley
  • Richard A. Nichols
  • Michael R. Whitehead
  • Aaron T. Adamack
  • Melissa R. Gunn
  • William B. Sherwin
Research Article


The effective population size (N e ) is a key parameter in evolutionary and population genetics. Single-sample N e estimation provides an alternative to traditional approaches requiring two or more samples. Single-sample methods assume that the study population has no genetic sub-structure, which is unlikely to be true in wild populations. Here we empirically investigated two single-sample estimators (onesamp and L d N e) in replicated and controlled genetically structured populations of Drosophila melanogaster. Using experimentally controlled population parameters, we calculated the Wright–Fisher expected N e for the structured population ( Total N e ) and demonstrated that the loss of heterozygosity did not significantly differ from Wright’s model. We found that disregarding the population substructure resulted in Total N e estimates with a low coefficient of variation but these estimates were systematically lower than the expected values, whereas hierarchical estimates accounting for population structure were closer to the expected values but had a higher coefficient of variation. Analysis of simulated populations demonstrated that incomplete sampling, initial allelic diversity and balancing selection may have contributed to deviations from the Wright–Fisher model. Overall the approximate-Bayesian onesamp method performed better than L d N e (with appropriate priors). Both methods performed best when dispersal rates were high and the population structure was approaching panmixia.


Effective population size Population structure Ne onesamp  LdNe 



We acknowledge the following persons and institutions: P. G. Geerts (bioinformatic support), 2K Australia (cluster CPU time), J. Gupta (closed population Drosophila experiment and genotyping); L. Tsai, E. Ho, J. Chao, C. Gelling and W. Zhao (Drosophila maintenance); S. Middleton (statistical advice); A. Higgins, J. Shearman, Ramaciotti Centre, University of New South Wales (DNA fragment size analysis); A. Grimm and B. Gruber (assistance with R-code); O. E. Gaggiotti, A. R. Templeton, J. Wang and L. Rollins (critical revisions). This research was supported by Australian Research Council Grant DP0559363 to WBS and RAN.

Supplementary material

10592_2013_518_MOESM1_ESM.pdf (520 kb)
Supplementary material 1 (PDF 520 kb)


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Clare E. Holleley
    • 1
    • 4
  • Richard A. Nichols
    • 2
  • Michael R. Whitehead
    • 1
    • 3
  • Aaron T. Adamack
    • 4
  • Melissa R. Gunn
    • 1
  • William B. Sherwin
    • 1
  1. 1.Evolution & Ecology Research Centre and School of Biological, Earth & Environmental SciencesUniversity of New South WalesSydneyAustralia
  2. 2.School of Biological & Chemical SciencesQueen Mary University of LondonLondonUK
  3. 3.Evolution, Ecology and Genetics, Research School of BiologyAustralian National UniversityCanberraAustralia
  4. 4.Institute for Applied EcologyUniversity of CanberraCanberraAustralia

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