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On the Mkv Model with Among-Character Rate Variation.

Alessio Capobianco1,2, Sebastian Höhna1,2

  • 1GeoBio-Center LMU, Ludwig-Maximilians-Universität München, Richard-Wagner-Str. 10, 80333 Munich, Germany.

Systematic Biology
|May 16, 2025
PubMed
Summary

The study reveals that how phylogenetic models account for variable characters impacts results. Using marginal acquisition bias is recommended for morphological datasets with among-character rate variation (ACRV) to avoid biased tree length and relationships.

Keywords:
ACRVAcquisition biasRevBayesascertainment biasrate heterogeneityvariable characters

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Area of Science:

  • Evolutionary Biology
  • Phylogenetics
  • Computational Biology

Background:

  • Morphological phylogenetics models often adapt molecular models.
  • The Mkv model corrects for acquisition bias; among-character rate variation (ACRV) is commonly used.
  • The interaction between acquisition bias and ACRV has not been previously studied.

Purpose of the Study:

  • To explore the interaction between acquisition bias and ACRV in morphological phylogenetics.
  • To investigate the impact of different acquisition bias correction methods on phylogenetic inference.
  • To provide recommendations for modeling variable characters in morphological datasets.

Main Methods:

  • Investigated two distinct approaches to condition likelihood on variable characters with ACRV: joint and marginal acquisition bias.
  • Conducted simulations to assess the impact of different conditioning methods on tree length and ACRV estimation.
  • Applied the methods to an empirical case study using extant and extinct taxa.

Main Results:

  • The method of conditioning on variable characters leads to different assumptions about rate variation distribution.
  • Simulations showed systematic bias in tree length and ACRV when conditioning methods mismatched simulation.
  • The empirical study indicated potential impacts on branch lengths and phylogenetic relationships.

Conclusions:

  • The choice of acquisition bias correction significantly affects phylogenetic inference in the presence of ACRV.
  • The marginal acquisition bias approach is recommended for morphological datasets with ACRV.
  • Clarification of acquisition bias implementation in phylogenetic software is needed for accurate modeling and simulation.