Abstract
How should characters and taxa be sampled to resolve efficiently the phylogeny of ancient and highly speciose groups? We addressed this question empirically in the treefrog family Hylidae, which contains >800 species and may be nonmonophyletic with respect to other anuran families. We sampled 81 species (54 hylids and 27 outgroups) for two mitochondrial genes (12S, ND1), two nuclear genes (POMC, c-myc), and morphology (144 characters) in an attempt to resolve higher-level relationships. We then added 117 taxa to the combined data set, many of which were sampled for only one gene (12S). Despite the relative incompleteness of the majority of taxa, the resulting trees placed all taxa in the expected higher-level clades with strong support, despite some taxa being >90% incomplete. Furthermore, we found no relationship between the completeness of a taxon and the support (parsimony bootstrap or Bayesian posterior probabilities) for its localized placement on the tree. Separate analysis of the data set with the most taxa (12S) gives a somewhat problematic estimate of higher-level relationships, suggesting that data sets scored only for some taxa (ND1, nuclear genes, morphology) are important in determining the outcome of the combined analysis. The results show that hemiphractine hylids are not closely related to other hylids and should be recognized as a distinct family. They also show that the speciose genus Hyla is polyphyletic, but that its species can be arranged into three monophyletic genera. A new classification of hylid frogs is proposed. Several potentially misleading signals in the morphological data are discussed.
Original language | English (US) |
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Pages (from-to) | 719-748 |
Number of pages | 30 |
Journal | Systematic biology |
Volume | 54 |
Issue number | 5 |
DOIs | |
State | Published - Oct 1 2005 |
Externally published | Yes |
Keywords
- Amphibians
- Anurans
- Combined analysis
- Hylid frogs
- Missing data
- Taxon sampling
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
- Genetics