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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Testing for temporal variation in diversification rates when sampling is incomplete and nonrandom.

Chad D Brock1, Luke J Harmon, Michael E Alfaro

  • 1Department of Zoology, School of Biological Sciences, Washington State University, Pullman, WA 99164-4236, USA. maximaul@msn.com

Systematic Biology
|March 8, 2011
PubMed
Summary
This summary is machine-generated.

Nonrandom taxonomic sampling can distort diversification patterns in phylogenies. This study introduces a new test to correct for nonrandom sampling (NRS) effects on diversification rate analyses, improving accuracy in phylogenetic studies.

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Area of Science:

  • Evolutionary Biology
  • Phylogenetics
  • Computational Biology

Background:

  • Diversification studies often show early bursts of lineage accumulation, interpreted as adaptive radiation or density-dependent processes.
  • Incomplete taxonomic sampling can artifactually create these early-burst patterns.
  • The Monte Carlo constant rates (MCCR) test assumes random pruning of taxa, which may not hold true.

Purpose of the Study:

  • To investigate how nonrandom taxonomic sampling (NRS) affects the MCCR test for diversification rates.
  • To develop and validate new methods to correct for NRS in phylogenetic diversification analyses.
  • To provide systematists with a tool to account for sampling biases in empirical trees.

Main Methods:

  • Simulations were used to demonstrate inflated type-I error rates of the MCCR test under preferential sampling of disparate lineages.
  • Two corrected MCCR tests were proposed: proportionally deeper splits and deepest splits only.
  • A generalized test incorporating a nonrandom sampling parameter (α) was developed and applied to empirical phylogenies.

Main Results:

  • Preferential sampling of disparate lineages significantly inflates MCCR test type-I error rates, especially below 75% taxon sampling.
  • The proposed corrected tests and the generalized NRS test show improved statistical properties.
  • The generalized test effectively accounts for varying degrees of nonrandom taxonomic sampling.

Conclusions:

  • Nonrandom taxonomic sampling is a critical factor that can severely bias assessments of diversification rates using the MCCR test.
  • The new generalized test provides a robust method for systematists to evaluate and correct for NRS in phylogenetic trees.
  • Evaluating sensitivity to NRS should be standard practice in cladogenesis analyses of incompletely sampled phylogenies.