The Accuracy of Methods for Coding and Sampling Higher-Level Taxa for Phylogenetic Analysis: A Simulation Study

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93 Scopus citations


Many phylogenetic analyses, particularly morphological studies, use higher taxa (e.g., genera, families) rather than species as terminal taxa. This general approach requires dealing with interspecific variation among the species that make up the higher taxon. In this paper, I review different parsimony methods for coding and sampling higher taxa and compare their relative accuracies using computer simulations. Despite their widespread use, methods that involve coding higher taxa as terminals perform poorly in simulations, relative to splitting up the higher taxa and using species as terminals. Among the methods that use higher taxa as terminals, coding a taxon based on the most common condition among the included species (majority or modal coding) is generally more accurate than other coding methods, such as coding taxa as missing or polymorphic. The success of the majority method, and results of further simulations, suggest that in many cases "common equals primitive" within variable taxa, at least for low and intermediate rates of character change. The fixed-only method (excluding variable characters) performs very poorly, a result that is indirectly supported by analyses of published data for squamate reptiles. Sampling only a single species per higher taxon also yields low accuracy under many conditions. Along with recent studies of intraspecific polymorphism, the results of this study show the general importance of (1) including characters despite variation within taxa and (2) using methods that incorporate detailed information on the distribution of states within variable taxa.

Original languageEnglish (US)
Pages (from-to)397-413
Number of pages17
JournalSystematic biology
Issue number3
StatePublished - Sep 1998


  • Accuracy
  • Coding methods
  • Parsimony
  • Simulations
  • Squamata
  • Taxon sampling

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Genetics


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