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Taking phylogenetics beyond pattern analysis: can models of genome dynamics guide predictions about homoplasy in morphological and behavioral data sets?

Research paper by J C JC Masters

Indexed on: 17 Apr '07Published on: 17 Apr '07Published in: Journal of Human Evolution



Abstract

Despite the considerable amount of interest in phylogeny reconstruction, patterns of homoplasy in morphological and behavioral data have received only limited attention to date, whereas the patterns of homoplasy in molecular data are relatively well understood. First, because the number of alternative molecular character states is strictly limited (particularly for nucleotide sequence data), higher rates of substitution generate higher levels of homoplasy. Second, depending on the relative proportions of constrained and unconstrained sites, each molecular data set has a time frame of applicability outside of which resolution becomes ambiguous. There is good evidence to suggest that numbers of alternative character states for morphological and even behavioral data may be similarly limited and that higher rates of evolution are often linked to higher rates of homoplasy. Like molecular data sets, morphological and behavioral data sets contain rapidly evolving characters as well as more conservative elements. Morphologies and behaviors related to sexual recognition and reproduction show low levels of intraspecific variation, but high levels of lability between species, making them crucial for species identification but often poor as markers of relationship at greater time depths. The organization theory of speciation derived by Carson is a model based on genome dynamics, and it predicts exactly this window of applicability for characters related to sexual reproduction. Nonsexual characters related to environmental adaptation should be applicable at greater phylogenetic depths. A better understanding of patterns of homoplasy enables a more sophisticated approach to the assessment of the relative reliabilities of alternative tree topologies.