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Gaussian process models for geographic controls in phylogenetic trees.

Frederik Hartmann1, Gerhard Jäger2

  • 1Department of Linguistics, University of North Texas, Denton, Texas, 7620, USA.

Open Research Europe
|May 23, 2024
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Summary

This study introduces a new method to distinguish language evolution from geographical proximity. The approach identifies language contact zones, improving phylogenetic tree accuracy.

Keywords:
Gaussian processesPhylogeneticscontrol for language contactgeospatial confounding

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Area of Science:

  • Computational linguistics
  • Phylogenetic modeling
  • Geospatial analysis

Background:

  • Geographical confounding is a persistent challenge in phylogenetic inference.
  • Distinguishing common genetic descent from language contact effects is difficult for current models.

Purpose of the Study:

  • To develop a novel approach for detecting and accounting for geographical biases in phylogenetic inference.
  • To improve the accuracy of language family tree topologies by addressing spatial effects.

Main Methods:

  • Introduced a distance-based Gaussian process model incorporating latent phylogenetic distances.
  • Developed methods to detect potential geographic contact zones.
  • Quantified the influence of contact zones on tree-level (clade support) and language-level (pairwise distances) metrics.

Main Results:

  • The proposed approach successfully identifies potential high-contact areas between languages.
  • The method quantifies the impact of geographical proximity on phylogenetic relationships.
  • Demonstrated the ability to differentiate between shared ancestry and language contact.

Conclusions:

  • The Gaussian process approach effectively mitigates geographical confounding in phylogenetic inference.
  • This method enhances the reliability of reconstructed language histories.
  • Provides a robust framework for analyzing language contact and its impact on linguistic diversity.