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Effective/census population size ratio estimation: a compendium and appraisal.

Friso P Palstra1, Dylan J Fraser

  • 1CNRS UMR 7206 Eco-anthropologie et Ethnobiologie, Equipe "Génétique des populations humaines", Muséum National d'Histoire Naturelle CP 139, 57 rue Cuvier, F-75231, Paris Cedex 05, France.

Ecology and Evolution
|November 10, 2012
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Summary

Estimating effective population size (N(e)) and census population size (N) ratios is crucial for conservation. However, many studies fail to link N(e) and N correctly, impacting conservation inferences.

Keywords:
Conservation geneticseffective population sizeempirical estimationgenetic stochasticity

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Area of Science:

  • Ecology and Evolutionary Biology
  • Conservation Genetics

Background:

  • The ecological-evolutionary perspective is vital for managing endangered species.
  • Genetic estimation of effective population size (N(e)) is increasingly used in conservation.
  • Accurate N(e) estimation is critical for understanding population viability.

Purpose of the Study:

  • To assess how often effective population size (N(e)) is linked to census population size (N) in empirical studies.
  • To evaluate the accuracy of N(e)/N ratio calculations.
  • To determine the extent to which uncertainty in N(e) and N estimates is addressed.

Main Methods:

  • Comprehensive analysis of empirical literature over the past two decades.
  • Categorization of studies based on linking N(e) to N.
  • Evaluation of the reporting of confidence intervals for N(e) and N.

Main Results:

  • Only 20% of N(e) estimates explicitly linked N(e) to N.
  • Of those linked, only 31% did so correctly.
  • Only 7% of N(e)/N ratios reported confidence intervals for both N(e) and N, with significant uncertainty often spanning orders of magnitude.

Conclusions:

  • The estimation of N(e)/N ratios in natural populations requires significant improvement.
  • Addressing uncertainty in N(e) and N is crucial for reliable conservation assessments.
  • Future research should focus on refining N(e)/N estimation methods.