title: Sensitivity of phylogeny estimation to taxonomic sampling.
abstract: Recent studies have shown that addition or deletion of taxa from a data matrix can change the estimate of phylogeny. I used 29 data sets from the literature to examine the effect of taxon sampling on phylogeny estimation within data sets. I then used multiple regression to assess the effect of number of taxa, number of characters, homoplasy, strength of support, and tree symmetry on the sensitivity of data sets to taxonomic sampling. Sensitivity to sampling was measured by mapping characters from a matrix of culled taxa onto optimal trees for that reduced matrix and onto the pruned optimal tree for the entire matrix, then comparing the length of the reduced tree to the length of the pruned complete tree. Within-data-set patterns can be described by a second-order equation relating fraction of taxa sampled to sensitivity to sampling. Multiple regression analyses found number of taxa to be a significant predictor of sensitivity to sampling; retention index, number of informative characters, total support index, and tree symmetry were nonsignificant predictors. I derived a predictive regression equation relating fraction of taxa sampled and number of taxa potentially sampled to sensitivity to taxonomic sampling and calculated values for this equation within the bounds of the variables examined. The length difference between the complete tree and a subsampled tree was generally small (average difference of 0-2.9 steps), indicating that subsampling taxa is probably not an important problem for most phylogenetic analyses using up to 20 taxa.
authors.affiliation: Department of Zoology, Texas Memorial Museum, University of Texas, Austin, Texas 78712-1064, USA. stevepoe@mail.utexas.edu
authors.forename: S
authors.initials: S
authors.lastname: Poe
mesh_terms: D000818:Animals; D002965:Classification / Q000379:methods*; D007448:Invertebrates / Q000145:classification; D019684:Magnoliopsida / Q000145:classification; D008322:Mammals / Q000145:classification; D010802:Phylogeny; D012044:Regression Analysis; D015203:Reproducibility of Results; D015983:Selection Bias; D014714:Vertebrates / Q000145:classification