AN EMPIRICAL-TEST OF BOOTSTRAPPING AS A METHOD FOR ASSESSING CONFIDENCE IN PHYLOGENETIC ANALYSIS

Bootstrapping is a common method for assessing confidence in phylogene tic analyses. Although bootstrapping was first applied in phylogenetic s to assess the repeatability of a given result, bootstrap results are commonly interpreted as a measure of the probability that a phylogene tic estimate represents the true phylogeny. Here we use computer simul ations and a laboratory-generated phylogeny to test bootstrapping resu lts of parsimony analyses, both as measures of repeatability (i.e., th e probability of repeating a result given a new sample of characters) and accuracy (i.e., the probability that a result represents the true phylogeny). Our results indicate that any given bootstrap proportion p rovides an unbiased but highly imprecise measure of repeatability, unl ess the actual probability of replicating the relevant result is nearl y one. The imprecision of the estimate is great enough to render the e stimate virtually useless as a measure of repeatability. Under conditi ons thought to be typical of most phylogenetic analyses, however, boot strap proportions in majority-rule consensus trees provide biased but highly conservative estimates of the probability of correctly inferrin g the corresponding clades. Specifically, under conditions of equal ra tes of change, symmetric phylogenies, and internodal change of less-th an-or-equal-to 20% of the characters, bootstrap proportions of greater -than-or-equal-to 70% usually correspond to a probability of greater-t han-or-equal-to 95% that the corresponding clade is real. However, und er conditions of very high rates of internodal change (approaching ran domization of the characters among taxa) or highly unequal rates of ch ange among taxa, bootstrap proportions >50% are overestimates of accur acy.