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Phylogenetic comparative methods complement discriminant function analysis in ecomorphology.

W Andrew Barr1, Robert S Scott

  • 1Department of Anthropology, University of Texas, Austin, TX, 78712.

American Journal of Physical Anthropology
|January 3, 2014
PubMed
Summary
This summary is machine-generated.

Discriminant Function Analysis (DFA) may overestimate functional links in ecomorphology. Phylogenetic Generalized Least Squares (PGLS) is a better tool for testing hypotheses, especially when accounting for phylogenetic signal.

Keywords:
BovidaePGLSpaleoecologypaleoenvironments

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Area of Science:

  • Ecomorphology
  • Phylogenetics
  • Statistical Modeling

Background:

  • Discriminant Function Analysis (DFA) is commonly used in ecomorphology to infer functional relationships between traits and ecology.
  • The reliability of DFA in the presence of phylogenetic signal is not well understood.

Purpose of the Study:

  • To investigate the performance of DFA versus Phylogenetic Generalized Least Squares (PGLS) in detecting ecomorphological links.
  • To assess the impact of phylogenetic signal on statistical analyses in ecomorphology.

Main Methods:

  • Simulated antelope species' traits with varying levels of phylogenetic signal and random noise.
  • Applied DFA and PGLS to assess habitat category discriminability.
  • Utilized randomized habitat assignments and False Discovery Rate (FDR) corrections.

Main Results:

  • DFA frequently yielded significant results even without true functional links, especially with phylogenetic signal.
  • PGLS, particularly with FDR correction, was more conservative and accurately identified links.
  • DFA did not indicate phylogenetic signal as a driver, while PGLS did.

Conclusions:

  • DFA can produce false positives in ecomorphological studies due to phylogenetic signal.
  • PGLS is a more robust method for testing functional hypotheses in ecomorphology.
  • Accounting for phylogenetic signal is crucial for accurate ecomorphological inference.