ESCAPING FROM THE FELSENSTEIN ZONE BY DETECTING LONG BRANCHES IN PHYLOGENETIC DATA

Long branches in a true phylogeny tend to disrupt hierarchical charact er covariation (phylogenetic signal) in the distribution of traits amo ng organisms, The distortion of hierarchical structure in character-st ate matrices can lead to errors in the estimation of phylogenetic rela tionships and inconsistency of methods of phylogenetic inference. Exam ination of trees distorted by long-branch attraction will not reveal t he identities of problematic taxa, in part because the distortion can mask long branches by reducing inferred branch lengths and through err ors in branching order. Here we present a simple method for the detect ion of taxa whose placement in evolutionary trees is made difficult by the effects of long-branch attraction. The method is an extension of a tree-independent conceptual framework of phylogenetic data explorati on (RASA), Taxa that are likely to attract are revealed because long b ranches leave distinct footprints in the distribution of character sta tes among taxa, and these traces can be directly observed in the error structure of the RASA regression. Problematic taxa are identified usi ng a new diagnostic plot called the taxon variance plot, in which the apparent cladistic and phenetic variances contributed by individual ta xa are compared. The procedure for identifying long edges employs algo rithms solved in polynomial time and can be applied to morphological, molecular, and mixed characters. The efficacy of the method is demonst rated using simulated evolution and empirical evidence of long branche s in a set of recently published sequences. We show that the accuracy of evolutionary trees can be improved by detecting and combating the p otentially misleading influences of long-branch taxa. (C) 1997 Academi c Press.