The computer program Modeltest (Posada and
Crandall, 1998) was used to assess the model of evolution
that best fit the combined data. The parameters
corresponding to the model selected were treated as
unknown variables with equal a priori probability and
estimated as part of the analysis based on Bayesian inference.
Four MCMC (Markov Chain Monte Carlo)
chains (one cold and three heated) were run simultaneously
on random starting trees for 1.5_106 generations
with results sampled every 100 (printed every 1000)
generations. The )ln of the trees was plotted against
generations to determine the number of generations required
to achieve stability of the results and the trees
obtained in generations below the stability value were
discarded as ‘‘burn-in.’’