Continuous Track Analysis: A New Phylogenetic and Biogeographic Method

Continuous track analysis (CTA) can depict reticulate evolutionary patterns in phylogenetics and biogeography. A reticulate connection implies convergence, hybridization, or introgression in an evolutionary graph of taxa and implies dispersal in an evolutionary graph of biogeographic areas. CTA finds graphs that (1) have a minimal number of connections and (2) imply that most character states or taxa have distributions or tracks across taxa or areas (objects) that are continuous, i.e., can be traced across the connections among the objects including that state without traveling through any other objects. Continuous tracks imply either that character states in phylogenies have unique evolutionary origins or that taxa in biogeographic analyses are monophyletic. Relatively simple graphs usually cannot imply completely continuous tracks. There? fore, CTA graphs seek to minimize the number of track fragments, which are locally continuous parts of a track; tracks with more than one fragment are discontinuous. Minimizing fragments is the same as minimizing character-state transitions only if there are no reticulations. Because hy? pothetical ancestors do little to reduce the number of fragments, CTA tends to place known taxa or areas at internal nodes. A heuristic algorithm analogous to tree bisection-reconnection is used to find highly parsimonious CTA graphs. In phylogenetic analyses, CTA employs a special com? plementary binary coding convention that serendipitously solves the missing characters/missing data problem. Although the problem of ancestors "inheriting" states from hybrid descendants is irrelevant if reticulations merely represent convergence patterns, CTA includes an optional algo? rithm that avoids such instances by explicitly identifying ancestors and descendants. CTA was compared with standard parsimony analysis using a data set of 17 Neogene species of North American fossil hipparionine horses. CTA separates the three major clades and illustrates their convergent features with reticulations, whereas standard parsimony analysis groups the three in an unresolved polytomy. CTA also minimizes the number of hypothetical, unsampled ancestors and lineages. [Ancestors; biogeographic methods; dispersal; homology; Hipparionini; hybridiza? tion; phylogenetic methods; reticulation. ] Reticulate evolution and biogeographic dispersal are two of evolutionary biology's greatest methodological puzzles. In this paper, a new means of analyzing the pat? terns created by either of these superficial? ly dissimilar processes is introduced. A unified approach is possible because both reticulating phylogenetic hypotheses and dispersal hypotheses imply more than the smallest possible number of evolutionary connections among taxa or areas. Al-, though this fact has been noted by other authors (e.g., Nelson, 1983), the method presented here is the first to base an ex? plicit parsimony criterion on the idea of minimizing the number of connections. The implications of this criterion are com? plex and require detailed discussion. Phylogenetic reticulation has inspired 1 E-mail; jack@homebrew.geo. arizona.edu. rel tively little debate since a symposium on the topic in 1981 (Platnick and Funk, 1983). Several different approaches to the problem were described (Humphries, 1983; Nelson, 1983; Wagner, 1983; Wanntorp, 1983), and the stage seemed set for a synthetic approach. However, even the ex? isting methods have attracted little atten? tio since then (but see Humphries and Funk, 1984; Funk, 1985). The only related developments are in the field of molecular systematics, where several methods are us d to recognize ambiguous nodes. How? ever, the split decomposition method of Bandelt and Dress (1992) identifies alter? native taxonomic bipartitions, not reticu? lations, and the cladogram estimation pro? cedure of Templeton et al. (1992) is nar? rowly applicable to haplotype data, makes restrictive probabilistic assumptions about the evolutionary process, and treats addi-