Abstracts (first author)

Poster 

How good is good enough? An investigation of tree-based analyses using paleontological phylogenies

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Author(s): Soul LC, Friedman M

Summary:

Many tree-based methods now available for macroevolutionary analyses can include extinct taxa. Unfortunately, many of the groups for which we have abundant and diverse fossils have not been subjected to cladistic analysis. It is therefore important to understand the sensitivity of tree-based analyses to uncertainty in relationships, and whether taxonomic information can be a useful substitute for an explicit phylogenetic hypothesis where one does not exist. With this in mind, I collected data for 20 animal clades (vertebrate and invertebrate) that include fossil taxa, for which a recent cladogram and pre-cladistic taxonomies were available. I measured a series of phylogenetically explicit parameters (e.g. phylogenetic clustering of extinction [Fritz and Purvis’ D], phylogenetic conservatism [Blomberg’s K], inferred divergence times) and determined the degree to which they co-varied for taxonomic and cladistic trees. Results show that pairwise distances between taxa in taxonomies match those for formal solutions very well (R2 > 0.9 for all clades). With the exception of measures of phylogenetic clustering of extinction — which are sensitive to differences in tree topology — when taxonomic information is used, results of analyses are strongly correlated with those obtained using the formal solution and are therefore unlikely to be misleading relative to this standard. The particular analysis performed and the quality of the taxonomic information used must be carefully considered, but under some circumstances taxonomies are ‘good enough’ to be used in place of formal cladistic solutions.



Contacts

Chairman: Octávio S. Paulo
Tel: 00 351 217500614 direct
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email: mail@eseb2013.com

Address

XIV Congress of the European Society for Evolutionary Biology

Organization Team
Department of Animal Biology (DBA)
Faculty of Sciences of the University of Lisbon
P-1749-016 Lisbon
Portugal

Website

Computational Biology & Population Genomics Group 
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