Data Sets , Partitions , and Characters : Philosophies and Procedures for Analyzing Multiple Data Sets

Ð W e compared four approaches for analyzing three data sets derived from staphylinoid beetles, a superfamily whose known species diversity is roughly comparable to that of vertebrates. O ne data set is derived from adult morphology and the two molecular data sets are from 12S ribosomal RNA and cytochrome b mitochondrial DNA. We found that taxonomic congruence following conditional data combination, herein called compatible evidence (CE), resolved more nodes compatible with an initial conservative hypothesis than did total evidence (TE), conditional data combination (CDC), or taxonomic congruence (TC). CE sets a base of nodes obtained by CDC analysis and then investigates what further agreement may arise in a universe where these nodes are accepted as given. W e suggest that CE75-75 may be appropriate for future studies that aim to both generate a well-corroborated tree and investigate con ̄ icts between data sets, partitions, and characters. CE75-75 is a 75% bootstrap consensus CDC tree followed by combinable-component consensus of a 75% bootstrap consensus of each homogeneous set of partitions having hierarchical structure. [Beetles; compatible evidence; conditional data combination; Staphylinidae; taxonomic congruence; total evidence. ] The growth of systematics and the availability of independent data sets raises the question of how these data sets should be analyzed. Kluge (1989) suggested that all data sets should be analyzed simultaneously according to a total evidence (TE) or simultaneous analysis (Nixon and Carpenter, 1993) procedure to maximize informativeness. This approach seeks a single best-® tting hypothesis that, in cladistics, involves maximizing character congruence. However, each data set may have di erent levels of hierarchical structure (Faith and Cranston, 1991), be subject to distinct biological forces (Bull et al., 1993), and be informative at di erent divergence levels (Friedlander et al., 1994). As a result, no single criterion or model may be applicable to all sets of evolutionary processes. Chippindale and Wiens (1994) argued that di erences in character evolution can be accommodated by di erential character weighting in a combined analysis of all data. They acknowledged, however, that the appropriate weighting scheme is as unknown as the true phylogeny. A step toward the resolution of this quandary is to de® ne data partitions a priori. It may be argued that partitions recognized by evolutionary biologists do not conform to natural sets of characters but are merely artifacts of tradition and technology. The naturalness of di erent partitions can be defended by relating their existence to the concept of evolutionary processes de® ned by Bull et al. (1993). These authors de® ned process partitions as subsets of characters that are evolving under demonstrably di erent rules. There are at least three reasons why partitions may appear to evolve di erently : (1) The signal in one or more partitions may be swamped by homoplasy, (2) distinct and con ̄ icting processes may be operating, or (3) methods for investigating whether process partitions should be combined may be inadequate. Faith and Cranston (1991) developed the combined hierarchical evidence (CHE) procedure (Faith, personal communication) to address the potential problem of signal being swamped by homoplasy. In CHE the data are partitioned, each independent partition is tested for structure using the permutation probability (PTP) test, and a tree is constructed from partitions with hierarchical structure 367 D ow naded rom http/academ ic.p.com /sysbio/articlact/47/3/367/1703689 by gest on 06 D ecem er 2018 (Archie, 1989; Faith, 1990). Employing this procedure, Faith and Cranston (1991) showed that excluding data sets without PTP structure may resolve a higher number of nodes than including data sets both with and without PTP structure. Second, distinct and con ̄ icting patterns may result from such phenomena as introgression or selection. Bull et al. (1993) developed the conditional data combination (CDC) procedure to address this issue. Chippindale and Wiens (1994) refer to this approach as prior agreement. In CDC the data are partitioned into process partitions, each independent partition is tested for homogeneity, and combinable partitions are pooled and a tree constructed (Bull et al., 1993; de Q ueiroz, 1993; Rodrigo et al., 1993). Consider the nonmonophyly of the two mitochondrial haplotypes of Drosophila mauritiana with respect to the D. simulans mitochondrial haplotypes (Satta and Takahata, 1990). Alternative explanations for the observed nonmonophyly are the retention of ancestral polymorphisms or introgression. Inspection of Satta and Takahata’s (1990) sequence data show D. mauritiana maI di ers from the D. simulans siIII haplotype by a single substitution. Moreover, the mtDNA of D. mauritiuna maI and that of D. simulans siIII have no restriction site length polymorphism di erences (Solignac and M onnerot, 1986). This suggests that there has been introgression of D. simulans siIII mtDNA into D. mauritiana . Laboratory crosses of D. mauritiana (males) and D. simulans (females) result in sterile males and fertile females (Robertson, 1983), supporting the feasibility of introgression. Third, methods for investigating whether process partitions should be combined may be inadequate. Sullivan (1996) showed that, in deer mice and grasshopper mice, portions of 12S ribosomal RNA and cytochrome b have con ̄ icting signals but a combined parsimony analysis with equal weights recovered a wellcorroborated hypothesis. O ne explanation for this apparent contradiction is that the phylogenetic signal from the di erent loci with different evolutionary processes was additive when it was analyzed under a homogeneous model. An alternative method for analyzing multiple data sets, taxonomic congruence (TC), was proposed by Mickevich (1978). This method involves partitioning data into discrete process partitions, analyzing the characters in each partition separately, and constructing a consensus tree that summarizes the topological features shared by trees from the separate analyses ( Jones et al., 1993). The TC approach has many methodological advantages because each data set is treated independently, separate analyses can corroborate speci® c assemblages, and con ̄ icts between process partitions can be directly investigated (Lanyon, 1985; Miyamoto and Fitch, 1995). However, consensus methods may endorse trees that contradict the tree obtained from the pooled data. Barrett et al. (1991) suggested that these situations `̀ may not be rare’’ and in such circumstances the consensus trees should not be regarded as the `̀ best’’ inference to make from the available data. We investigated a new approach to the analysis of multiple data sets, herein called compatible evidence (CE). This procedure can be broken down into six steps and involves a series of familiar elements of systematic analysis (Fig. 1). CE sets a base of nodes obtained by CDC analysis and then investigates what further agreement may arise in a universe where these nodes are treated as given. The process is consistent with the tenets of metaanalysis and combines the philosophy of CDC with the methodology of TC. M eta-analysis originally was de® ned as statistical analysis of a large collection of individual data sets for the purpose of integrating the results (Glass, 1976). However, the term is often used more restrictively (e.g., Hedges and O lkin 1985; Dickersin and Berlin, 1992). In restrictive meta-analysis, a weighted combined analysis of all data from all studies is statistically compared to the separate analysis of each individual study. Consistent with meta-analysis, Hillis (1987) suggested that the best estimate of a phylogeny is obtained from a combined analysis, but that congruence among data sets is evidence that the underlying phylogeny is correctly estimated. We constructed an initial conservative hypothesis and compared the TE, TC, CDC, and CE approaches by analyzing three independently derived data sets from staphylinoid beetles. O ne data set is derived from adult morphology and the other two data sets are from 368 SYSTEM ATIC BIO LO GY VO L. 47 D ow naded rom http/academ ic.p.com /sysbio/articlact/47/3/367/1703689 by gest on 06 D ecem er 2018 12S ribosomal RNA (12S rRNA) and cytochrome b mitochondrial DNA (mtDNA). In this study we compare the number of well-supported nodes generated by the four techniques and prefer the method that supports the highest number of such nodes that are congruent with the a priori hypothesis (M iyamoto et al., 1994; Wheeler, 1995). CE resolved a higher number of nodes compatible with the initial conservative hypothesis than did any other procedure. Further, CE facilitates investigation of con ̄ icts between data sets, partitions, and characters. However, CE may accept a tree that is not the most parsimonious and may generate a biased estimator of nodal support. M ATERIALS AND M ETHO DS