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Approximate Bayesian computation for modular inference problems with many parameters: the example of migration rates.

S Aeschbacher1, A Futschik, M A Beaumont

  • 1Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, EH9 3JT, UK. simon.aeschbacher@univie.ac.at

Molecular Ecology
|January 11, 2013
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Summary
This summary is machine-generated.

This study introduces a two-step method for estimating population migration rates using approximate Bayesian computation (ABC). The approach found limited gene flow in Alpine ibex populations, with minimal evidence of substantial migration between demes.

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Area of Science:

  • Population Genetics
  • Computational Biology
  • Evolutionary Biology

Background:

  • Estimating migration rates is crucial for understanding population structure and gene flow.
  • Complex demographic models often involve numerous parameters, posing inference challenges.
  • Previous work estimated global parameters for Alpine ibex populations.

Purpose of the Study:

  • To develop and validate a two-step approximate Bayesian computation (ABC) framework for estimating multiple migration rates.
  • To assess the efficacy of pairwise versus joint estimation for migration rates in large population clusters.
  • To investigate gene flow patterns in reintroduced Alpine ibex populations.

Main Methods:

  • A two-step ABC procedure was employed, building on prior estimation of global parameters.
  • Migration rates were estimated independently for clusters of demes, with pairwise estimation assessed via simulation.
  • ABC-type model comparison was used to differentiate between low and zero migration rates.

Main Results:

  • Pairwise estimation of migration rates can be a valid alternative to joint estimation, with accuracy depending on the number of parameters.
  • The approach was applied to microsatellite data from Alpine ibex.
  • Substantial gene flow was largely absent, with evidence of migration found only between one specific pair of demes in a single direction.

Conclusions:

  • The proposed two-step ABC method effectively estimates multiple migration rates, even with complex demographic models.
  • The study provides insights into the genetic connectivity of Alpine ibex populations, indicating limited historical gene flow.
  • The findings highlight the utility of ABC for inferring population genetic parameters in conservation biology.