Combining Data with Different Distributions of Among-Site Rate Variation

Abstract

As the number of molecular studies continues to grow, so does the problem of how to analyze multiple data sets. The importance of this problem is indicated by the flurry of recent papers (reviewed by de Queiroz et alv 1995) addressing philosophical and practical considerations facing systematists fortunate enough to have several pertinent data sets on hand. Perhaps the most rigorous practical treatment was that of Bull et al. (1993), who argued against combining data when there is demonstrable heterogeneity among the different data sets in the processes governing character evolution. These authors showed that combining simulated data sets generated from the same topology but with different rates of evolution leads to less accurate estimation of phylogeny than does analysis of the more slowly evolving data set alone. Although the validity of these results is not in question for the models tested, the models used in these simulations may not be very realistic. Specifically, Bull et al. used two single-rate models to generate data sets, one with a uniform high rate and one with a uniform low rate of evolution. Chippindale and Wiens (1994) demonstrated that down-weighting rapidly evolving characters resulted in increased accuracy in combined analyses of