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Relating Stomatal Conductance to Leaf Functional Traits
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A multispecies coalescent model for quantitative traits.

Fábio K Mendes1, Jesualdo A Fuentes-González1,2, Joshua G Schraiber3,4,5

  • 1Department of Biology, Indiana University, Bloomington, United States.

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Summary
This summary is machine-generated.

This study introduces a new model for quantitative traits that accounts for genetic inconsistencies between species. This approach improves evolutionary inferences and corrects biases in estimating trait evolution and phylogenetic signals.

Keywords:
evolutionary biologygenealogical discordancehemiplasynonequantitative traits

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Area of Science:

  • Evolutionary biology
  • Quantitative genetics
  • Phylogenetics

Background:

  • Quantitative traits are influenced by multiple genes and evolutionary processes.
  • Genealogical discordance, arising from incomplete lineage sorting, can complicate evolutionary analyses.
  • Existing models may not adequately account for discordance in trait evolution.

Purpose of the Study:

  • To develop a multispecies coalescent model for quantitative traits that incorporates genealogical discordance.
  • To enable accurate evolutionary inferences at both micro- and macroevolutionary scales.
  • To identify conditions where different analytical methods perform optimally and to suggest ways to mitigate discordance effects.

Main Methods:

  • Development of a novel multispecies coalescent model.
  • Simulation studies to assess the impact of genealogical discordance on trait covariance.
  • Analysis of how discordance affects evolutionary rate estimation, phylogenetic signal, and shifts in mean trait values.

Main Results:

  • Genealogical discordance reduces trait covariance between closely related species.
  • Unaccounted discordance leads to overestimation of evolutionary rates and decreased phylogenetic signal.
  • The number of loci controlling a trait does not influence these discordance effects, which also impact threshold traits.

Conclusions:

  • The proposed model effectively incorporates genealogical discordance for improved evolutionary inferences.
  • Understanding discordance is crucial for accurate analyses of quantitative trait evolution.
  • The findings provide guidance on selecting appropriate methods and developing new approaches to address genealogical discordance.