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Cladistic estimates of evolutionary rates focused on palaeontological datasets using TNT.

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Title: Cladistic estimates of evolutionary rates focused on palaeontological datasets using TNT.
Authors: Pol, Diego1,2 (AUTHOR) dpol@mef.org.ar, Ezcurra, Martín D.1,2,3 (AUTHOR)
Source: Cladistics. Feb2025, Vol. 41 Issue 1, p28-54. 27p.
Subjects: Missing data (Statistics), Scripts, Ambiguity, Trees, Parsimonious models, Calibration
Abstract: We describe a protocol for estimating evolutionary rates from phylogenetic trees based on parsimony character optimization. The rate estimation is conducted through a TNT script and the results are analysed in a script for the software environment R. The TNT script allows analysing multiple optimal topologies, considering optimization ambiguity, and alternative time‐calibrations or pre‐calibrated trees. The R script summarizes estimated rates on a consensus tree and plots the variation of evolutionary rates through time, jointly with the phylogenetic diversity and a new metric (clade completeness index) that measures the distribution of missing data along the tree. We present results for simulated and empirical analyses, and evaluate the impact of missing data and alternative calibration methods in rate estimates. We found that while missing data can lower the nominal values of evolutionary rates, the overall pattern of rate variation through time remained robust. Empirical cases highlight different scenarios, such as datasets in which peaks of evolutionary rates can be coupled or decoupled from diversification dynamics (phylogenetic diversity) and cases in which missing data may influence the variation of estimated evolutionary rates. We conclude with recommendations for using this protocol and interpreting the results of parsimony‐based rate estimates. [ABSTRACT FROM AUTHOR]
Copyright of Cladistics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Cladistic estimates of evolutionary rates focused on palaeontological datasets using TNT.
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  Data: <searchLink fieldCode="AR" term="%22Pol%2C+Diego%22">Pol, Diego</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> dpol@mef.org.ar</i><br /><searchLink fieldCode="AR" term="%22Ezcurra%2C+Martín+D%2E%22">Ezcurra, Martín D.</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Cladistics%22">Cladistics</searchLink>. Feb2025, Vol. 41 Issue 1, p28-54. 27p.
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  Data: <searchLink fieldCode="DE" term="%22Missing+data+%28Statistics%29%22">Missing data (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Scripts%22">Scripts</searchLink><br /><searchLink fieldCode="DE" term="%22Ambiguity%22">Ambiguity</searchLink><br /><searchLink fieldCode="DE" term="%22Trees%22">Trees</searchLink><br /><searchLink fieldCode="DE" term="%22Parsimonious+models%22">Parsimonious models</searchLink><br /><searchLink fieldCode="DE" term="%22Calibration%22">Calibration</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: We describe a protocol for estimating evolutionary rates from phylogenetic trees based on parsimony character optimization. The rate estimation is conducted through a TNT script and the results are analysed in a script for the software environment R. The TNT script allows analysing multiple optimal topologies, considering optimization ambiguity, and alternative time‐calibrations or pre‐calibrated trees. The R script summarizes estimated rates on a consensus tree and plots the variation of evolutionary rates through time, jointly with the phylogenetic diversity and a new metric (clade completeness index) that measures the distribution of missing data along the tree. We present results for simulated and empirical analyses, and evaluate the impact of missing data and alternative calibration methods in rate estimates. We found that while missing data can lower the nominal values of evolutionary rates, the overall pattern of rate variation through time remained robust. Empirical cases highlight different scenarios, such as datasets in which peaks of evolutionary rates can be coupled or decoupled from diversification dynamics (phylogenetic diversity) and cases in which missing data may influence the variation of estimated evolutionary rates. We conclude with recommendations for using this protocol and interpreting the results of parsimony‐based rate estimates. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Cladistics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1111/cla.12608
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      – Code: eng
        Text: English
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        PageCount: 27
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      – SubjectFull: Missing data (Statistics)
        Type: general
      – SubjectFull: Scripts
        Type: general
      – SubjectFull: Ambiguity
        Type: general
      – SubjectFull: Trees
        Type: general
      – SubjectFull: Parsimonious models
        Type: general
      – SubjectFull: Calibration
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      – TitleFull: Cladistic estimates of evolutionary rates focused on palaeontological datasets using TNT.
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            NameFull: Pol, Diego
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              M: 02
              Text: Feb2025
              Type: published
              Y: 2025
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              Value: 41
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