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Phylogenetic comparative methods can yield spurious correlations for categorical characters. Hidden Markov models (HMMs) reveal rate heterogeneity as the source of false positives, offering a statistical solution for accurate evolutionary analyses.

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Area of Science:

  • Macroevolutionary studies
  • Phylogenetic comparative methods
  • Statistical modeling in biology

Background:

  • Correlated evolution between categorical characters is often assumed to indicate significant biological relationships.
  • Maddison and FitzJohn highlighted that such correlations can be spurious, especially when driven by single, ancient evolutionary events.
  • Existing phylogenetic comparative methods may struggle to adequately address this challenge, leading to potential pseudoreplication.

Purpose of the Study:

  • To address the challenge of spurious correlations in phylogenetic tests for categorical character evolution.
  • To investigate the utility of the hidden Markov model (HMM) framework for resolving issues of correlated evolution.
  • To develop a statistical solution that accounts for rate heterogeneity and improves model adequacy.

Main Methods:

  • Utilized the hidden Markov model (HMM) framework to expand the model space for phylogenetic analyses.
  • Demonstrated that rate heterogeneity within HMMs represents single, unreplicated evolutionary events.
  • Developed and implemented a multirate independent model within the HMM framework.

Main Results:

  • Identified rate heterogeneity as the underlying cause of false correlations in phylogenetic character evolution.
  • Showed that the HMM framework can statistically resolve the problem of spurious correlations.
  • The developed multirate independent model significantly reduced support for previously inferred correlations.

Conclusions:

  • The problem of spurious correlations is better understood as model misspecification rather than a failure of comparative methods.
  • Hidden Markov models provide a robust framework for addressing rate heterogeneity and improving model adequacy in macroevolution.
  • The proposed solution offers a practical approach for more accurate phylogenetic comparative analyses, with potential extensions to other biological fields.