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Strategies for improving approximate Bayesian computation tests for synchronous diversification.

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This study improves methods for estimating divergence times in co-distributed species. Sorting summary statistics enhances accuracy in phylogeography, while a new buffering method refines estimates of co-divergence events.

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Area of Science:

  • Evolutionary Biology
  • Phylogeography
  • Computational Biology

Background:

  • Comparative phylogeography aims to estimate divergence time variability in co-distributed species.
  • Hierarchical Approximate Bayesian Computation (ABC) and coalescent models are used for inferring lineage co-diversification.
  • Unresolved issues include prior selection for co-divergence events (Ψ) and data summarization strategies.

Purpose of the Study:

  • To explore the impact of summary statistic sorting and prior choice on Ψ for estimating co-divergence variability.
  • To introduce a new setting (β) to potentially improve Ψ estimation by enforcing temporal differences between co-divergence pulses.
  • To apply the new method to empirical datasets of frogs, fishes, and butterflies.

Main Methods:

  • Simulation-based cross-validation to assess strategies for sorting summary statistics and priors on Ψ.
  • Introduction and application of a new parameter (β) for estimating co-divergence pulses.
  • Analysis of empirical datasets including Panamanian frogs and fishes, and Neotropical butterflies.

Main Results:

  • The choice of prior on Ψ had minimal impact on inference.
  • Sorting summary statistics significantly improved the reliability of co-divergence variability estimates.
  • The implementation of β notably improved Ψ estimation, especially with more taxon pairs.
  • Equivocal support for synchronous co-divergence in Panamanian groups; strong support for asynchronous divergence in Neotropical butterflies.

Conclusions:

  • Sorted summary statistics improve divergence time variability estimates, while priors on Ψ have negligible effects.
  • Estimating co-divergence pulses is enhanced by a flexible buffering regime over divergence times.
  • The new method improves the correlation between Ψ and isolation time variability, enabling more accurate identification of co-divergence pulses.