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A data based parsimony method of cophylogenetic analysis


Kevin P. Johnson, Devin M. Drown & Dale H. Clayton, Department of Biology, University of Utah, 257 South 1400 East, Salt Lake City, UT 84112-0840, USA

Kevin P. Johnson, present address: Illinois Natural History Survey, 607 East Peabody Drive, Champaign, IL 61820, USA.


Phylogenies of closely interacting groups, such as hosts and parasites, are seldom completely congruent. Incongruence can arise from biologically meaningful differences in the histories of the two groups, or can be generated by artifactual differences that are merely the result of incorrect phylogenies with weakly supported nodes. We present a method that distinguishes between these sources of incongruence and identifies lineages that are responsible for significant differences between phylogenies. We use the logic of conditional combination in that we first test for statistically significant incongruence using the partition homogeneity test. Then we remove all possible combinations of taxa until a non-significant result of this test is achieved. Finally, we construct a ‘combined evidence’ phylogeny and then reposition the incongruent taxa. This method produces trees for final comparison using reconciliation methods, but it includes only as many incongruence events as can be statistically justified from the data sets. We apply this method to a host–parasite (gopher–louse) data set and identify many fewer incongruence events than do topology based analyses alone. Our method is broadly applicable to comparisons of phylogenies of interacting taxa, such as hosts and parasites, or mutualists. The method should also be useful for other problems involving comparisons of phylogenies, such as multiple gene trees or cladistic biogeography.