<p class="first" id="d1734828e67">One of the lasting controversies in phylogenetic
inference is the degree to which
specific evolutionary models should influence the choice of methods. Model-based approaches
to phylogenetic inference (likelihood, Bayesian) are defended on the premise that
without explicit statistical models there is no science, and parsimony is defended
on the grounds that it provides the best rationalization of the data, while refraining
from assigning specific probabilities to trees or character-state reconstructions.
Authors who favour model-based approaches often focus on the statistical properties
of the methods and models themselves, but this is of only limited use in deciding
the best method for phylogenetic inference-such decision also requires considering
the conditions of evolution that prevail in nature. Another approach is to compare
the performance of parsimony and model-based methods in simulations, which traditionally
have been used to defend the use of models of evolution for DNA sequences. Some recent
papers, however, have promoted the use of model-based approaches to phylogenetic inference
for discrete morphological data as well. These papers simulated data under models
already known to be unfavourable to parsimony, and modelled morphological evolution
as if it evolved just like DNA, with probabilities of change for all characters changing
in concert along tree branches. The present paper discusses these issues, showing
that under reasonable and less restrictive models of evolution for discrete characters,
equally weighted parsimony performs as well or better than model-based methods, and
that parsimony under implied weights clearly outperforms all other methods.
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