© 2006 Society of Systematic Biologists
The Effect of Combining Molecular and Morphological Data in Published Phylogenetic Analyses
Edited by Rod Page: Associate Editor
1 Department of Plant Sciences, University of Oxford South Parks Road, Oxford, OX1 3RB, UK E-mail: robert.scotland{at}plants.ox.ac.uk (R.W.S.)
Received April 23, 2005; Revised December 11, 2005; Accepted May 3, 2006 Understanding the natural world is not possible without an extensive knowledge of organismal morphology. The encyclopedia of life (Wilson, 2003) would be an empty, sterile list without detailed information about the full range of morphological diversity. Morphology plays a pivotal role in our understanding of life cycles, geographical distributions, identification, conservation status, evolution, development, and species delimitation (Buzgo et al., 2004; Endress, 2000; Kaplan, 2001; Scotland et al., 2003a). Nonetheless, there remains considerable debate about the precise role of morphology in one particular area of biology—computer-based phylogenetic inference (Baker and Gatesy, 2002; Hillis and Wiens, 2000; Jenner, 2004; Scotland et al., 2003b; Smith and Turner, 2005; Wortley and Scotland, 2006; Wiens, 2004).
One widespread contemporary use of morphological data in phylogeny reconstruction is in combined analysis with molecular sequence data (recent examples include Aagesen and Sanso, 2003; Cameron and Williams, 2003; Cohen et al., 2004; Dorchin et al., 2004; Hebsgaard et al., 2004; Lundberg and Bremer, 2003; Michelangeli et al., 2003; Near et al., 2003; Pedersen et al., 2003; Zrzav
, 2003). Despite the methodological, conceptual, and philosophical issues surrounding combined analyses of independent data partitions (Ballard, 1996; Ballard et al., 1998; Brower et al., 1996; Bull et al., 1993; De Queiroz et al., 1995; Farris, 2000; Huelsenbeck et al., 1996; Kluge, 1998; Levasseur and Lapointe, 2001; Nixon and Carpenter, 1996; Page, 1996; Pupko et al., 2002), the number of combined analyses conducted recently demonstrates that this is a popular way of integrating morphological data into phylogenetic analyses.
Recent empirical studies have both questioned (e.g., Gaubert et al., 2005) and defended (e.g., Wahlberg et al., 2005) the role of morphology in phylogenetic analysis, with equal vigor. Although individual studies such as these can be highly informative and compelling, it is doubtful whether they can effectively reflect general trends. In 1998, Baker et al. investigated the contribution of morphological data sets to combined analyses with molecular data across a range of studies and found that the support contributed by morphological data was substantial, and often greater than that provided by molecular data. Since then, molecular sequence data sets have dramatically increased in size (from an average of 156 parsimony-informative characters across the 15 molecular data sets studied in Baker et al. (1998) to an average of 391 parsimony-informative characters across the 26 data sets analyzed in this paper), whereas morphological data sets have remained approximately the same (from an average of 40 parsimony-informative characters in Baker et al., 1998, to 47 parsimony-informative characters here). Since the first phylogenetic analyses using molecular data, more than 20 years ago (e.g., Curtis and Clegg, 1984; Hillis, 1987; Rogers and Bendick, 1985), the composition of molecular data sets has also changed. Molecular data sets can include amplified fragment length polymorphisms (AFLPs), restriction fragment length polymorphisms (RFLPs), protein and DNA sequences, coded gaps, and secondary chemicals. At the time of Baker et al.'s (1998) study, only two-thirds of "molecular" analyses considered comprised DNA sequence data. Today, the vast majority of analyses of molecular data comprise DNA sequences (all of the molecular data sets studied in this paper included DNA sequence, 24 out of 26 exclusively). Changes in the size and composition of molecular data sets used in phylogenetic analysis imply that the relative contribution of morphological data to combined analyses with molecular data may also have changed significantly in recent years.
In the context of the ongoing debate surrounding molecular and morphological data in phylogenetic studies, there is a need for a broad survey to assess this development, and in particular to determine the effect of adding morphological data to molecular sequence data in combined analysis today. This has the potential to provide important general insights about current practice that individual, taxon-specific analyses do not. Two important parameters to consider are the degree of resolution provided by a data set and the level of support for the groups resolved, because improvements in resolution and support are frequently cited as the motivation for conducting combined analyses. In this paper we conduct a survey specifically to test the hypothesis that phylogenetic analyses of combined morphological and molecular sequence data sets yield significantly increased levels of resolution and support compared to analyses of molecular data alone.
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Selection of Studies
The Web of Knowledge citation database (http://wok.mimas.ac.uk/) is the most comprehensive database of peer-reviewed scientific literature. It was searched for all combined analyses of molecular sequence and morphological data published between 1998 and 2004. This period was chosen because studies published during recent years are most likely to reflect the current situation.
The sample was then narrowed down according to a set of criteria designed to ensure the valid comparison of phylogenies within and between studies. Because support values obtained using different search methods (such as parsimony bootstrap and Bayesian posterior probability) are not directly comparable (Alfaro et al., 2003), comparisons were restricted to studies using the same method of analysis. Bayesian methods are becoming increasingly prevalent and are now being used to analyse combined data in a likelihood framework (e.g., Nylander et al., 2004); however, parsimony is still by far the most commonly used method for combined analyses of molecular and morphological data, and therefore parsimony analyses provide the largest possible set of studies for this investigation.
Studies were excluded if they reported only the results of a combined phylogenetic analysis, because this did not allow for a direct comparison of the combined analysis with separate analyses of molecular or morphological data for the same taxa. Similarly, those studies that used different sets of taxa in separate and combined analyses (due to the availability of certain data sets for some taxa and not others) were excluded, since the phylogenies could not directly be compared. Finally, studies that used different methods, such as maximum likelihood for molecular data and parsimony for morphological and combined analyses, were excluded for the same reason.
Measures of Comparison
A wide range of metrics has been used to compare separate and combined analyses, both in single studies (e.g., Wahlberg et al., 2005) and broader surveys (Baker et al., 1998). These include the number of most parsimonious trees found, degree of resolution in consensus trees, tree statistics such as consistency and retention indices (Farris, 1989; Kluge and Farris, 1969) and, most often, measures of support such as jack-knife, bootstrap, and decay values (Bremer, 1994; Felsenstein, 1985). The most meaningful measures of the relative success of any phylogenetic analysis are accuracy (representation of true evolutionary relationships), resolution (number of branching events recovered), and support (confidence) for the relationships recovered (Bremer et al., 1999; Hillis, 1995; Huelsenbeck, 1995; Lecointre et al., 1993). The first of these, accuracy, cannot be determined without knowledge of the underlying phylogeny. This paper therefore concentrates on resolution and support.
Resolution was measured using the consensus fork index (CFI), calculated by dividing the number of nodes found in a strict consensus tree by the total number of possible nodes (Colless, 1980, 1981). The support measure most frequently presented in the studies used here was the nonparametric bootstrap, which provides statistical support for individual clades. This was translated into support for each tree as a whole by counting the number of clades found to attain a value of at least 50% (the usual minimum reported in phylogenetic studies) and the number attaining at least 95% (often taken as indicating strong support for a clade) in bootstrap analyses.
To conform, and allow comparison, with previous studies, the following statistics were also extracted from the studies: number of taxa, total number of characters, number of parsimony-informative characters, consistency index, and retention index. The percentage contribution of molecular and morphological data sets to the total number of parsimony-informative characters was also calculated.
A two-tailed, paired t-test was used to assess whether there was a significant difference in resolution or support upon adding molecular or morphological data. The distribution of data points was near enough normal to justify the use of this parametric test. A paired version of the t-test was used because the sets of samples to be tested were not independent, comprising analyses of the same taxa with or without an additional data set. Because we could not be certain that the effect of adding data would be positive and wished also to detect any negative effect, we tested the nondirectional null hypothesis "adding a data set makes no difference to resolution and support." Nondirectional hypotheses are most appropriately tested using a two-tailed t-test, which also has the benefit of being a more conservative test than the one-tailed and therefore providing more convincing evidence should a significant difference be found.
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Twenty-six data sets fulfilled the criteria described above (Table 1, Appendix 1). The data sets ranged in size from 10 to 103 terminal taxa and covered mosses and flowering plants, vertebrates and invertebrates. Molecular data sets ranged from 246 to 6972 aligned characters, of which 57 to 2093 were parsimony informative. Morphological data sets ranged from 12 to 119 characters in size, of which 12 to 119 were parsimony informative. On average, morphological data sets contributed 11% (ranging from 2% to 35%) and molecular data sets 89% (65% to 98%) of the parsimony-informative characters in the combined analysis.
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When morphological and molecular data were analyzed separately, morphological data almost always gave lower support and resolution than molecular data for the same taxa: fewer nodes were resolved and fewer clades found to be supported at both 50% and 95% bootstrap levels (Table 2). In one instance (Zrzav
, 2003), morphological data provided more resolution than molecular data, and in one other (Marvaldi et al., 2002), greater support.
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When morphology was added to molecular data in combined analysis, there was most often an increase in resolution compared to molecular data alone (Fig. 1A). Fourteen studies showed an increase in CFI, three a decrease and seven remained unchanged (these tended to be studies where complete resolution was attained both with and without morphological data). When molecular data was added to morphological data, the change in resolution was always positive (Fig. 1B). Using a two-tailed t-test, the addition of morphology to a molecular data set was found to make a significant difference to resolution (P = 0.01). The effect of adding molecular data to morphological data was also statistically significant (P < 0.001).
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In terms of support, with the addition of morphological to molecular data, 10 studies showed an increase in the number of clades supported at the 50% level, three showed a decrease and four remained the same (Fig. 2A). At the 95% level, nine studies showed an increase, four a decrease, and four were unchanged (Fig. 3A). With the addition of molecular to morphological data, eight studies showed an increase in the number of clades supported at the 50% level and one showed a decrease (Fig. 2B). At the 95% level, all nine studies where bootstrap values were reported showed an increase (Fig. 3B). Using a two-tailed t-test, no significant difference was found between the level of support for molecular and combined phylogenies (P = 0.61 for the 50% level; P = 0.50 for 95%). By contrast, the difference between morphology alone and combined analysis (i.e., the effect of adding molecular data) was significant (P = 0.05 for the 50% level, P = 0.03 for 95%). When support values were scaled by the total number of nodes in the phylogeny, the same patterns were seen (graphs not shown). No relationship was found between patterns of support or resolution and the type of taxon (plant or animal, vertebrate or invertebrate) or level of analysis (intergeneric, interfamilial, interphylum, interkingdom).
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The aim of this survey was to analyze current phylogenetic practice in order to determine whether combined analyses of morphological and molecular data, as recommended in, and implemented by, recent papers, have yielded significantly increased levels of resolution and support compared to analyses of molecular data alone (e.g., Aagesen and Sanso, 2003; Cameron and Williams, 2003; Edgecombe et al., 2002; Giribet et al., 2002; Jenner, 2004; Lundberg and Bremer, 2003; Meier and Wiegmann, 2002; Schulmeister et al., 2002; Smith and Turner, 2005; Stach and Turbeville, 2002; Virtanen, 2003; Wahlberg and Nylin, 2003; Wiens, 2004). In the sample of studies examined, the inclusion of morphological data was found to have had a significant, positive effect upon resolution in combined analyses. For the same sample, the inclusion of morphological data did not have a statistically significant effect upon support as measured by the number of nodes attaining a given bootstrap value.
The molecular data sets studied usually contained an order of magnitude more characters than the morphological ones with which they were combined (Table 1). However, morphological data sets contributed an appreciable proportion (on average 11%) of the parsimony-informative characters in each combined analysis. They therefore might be expected to have a significant effect on the results of phylogenetic analysis, even if not as large as the effect of molecular data. In terms of resolution, the results clearly indicate this positive effect of adding morphology in combined analyses. Resolution is an important aspect of phylogenetic analysis. However, in the absence of support resolution is of limited value and difficult to evaluate (Sanderson, 1995). In terms of support, although the result for this sample masks a great deal of variability, the effect of adding morphological data in combined analysis was not significant.
Baker et al. (1998) conducted a similar survey of 15 phylogenetic analyses from 1989 to 1997, focusing on the relative contribution of morphological and molecular data within a combined analysis using partitioned Bremer support (PBS). There is a stark difference between their conclusion—that "the inclusion of morphology has a substantial influence on the support in a simultaneous [combined] analysis" (Baker et al., 1998:434)—and ours. One possible reason for this is the dramatic increase in size of molecular data sets since 1997, during which time they have more than doubled in terms of their average number of parsimony-informative characters, whereas the size of morphological data sets has remained approximately the same (from the data sets presented in these two studies). This means that, although morphology may have had the same absolute effect on analyses conducted between 1998 and 2004 (this study) as it did between 1989 and 1997 (Baker et al., 1998), the relative additional impact it has had when combined with molecular data is now smaller, because molecular data provide a larger amount of support and resolution.
More recently, Wahlberg et al. (2005) suggested that combining molecular and morphological data sets can sometimes result in synergistic improvements in support (measured as decay values) that are greater than the total support expected from the sum of the individual partitions. Our study found that morphology did not have a statistically significant effect upon support, despite increasing the number of supported clades in a majority of studies. This may be because, in some of the studies examined here, the added morphological data sets conflicted with the molecular ones to decrease support at some nodes (Aagesen and Sanso, 2003). Thus, within individual studies, a relatively conservative change in overall resolution or support could mask different positive or negative effects on individual clades. It may also be because, for each individual study, the change in support values was relatively small, and therefore could be attributed to chance due to sampling error. However, this is not to say that in any particular study the impact of morphological data upon combined analysis will never be important. For instance, in Carpenter and Wheeler's (1999) study of Hymenoptera, combined analyses recovered 33 nodes in strict consensus, compared to only 21 using molecular data alone. Similarly Marvaldi et al.'s (2002) combined molecular and morphological analysis of Coleoptera found dramatically more supported nodes (47 at 50% bootstrap support) than molecular data alone (20). In contrast, in Littlewood et al.'s (1999) analysis of platyhelminthes, adding morphological data resulted in a decrease from 52 to 27 nodes supported at 50% bootstrap, and in Meier and Wiegmann's (2002) study of Diptera it caused a decrease from 11 to six nodes at 95% bootstrap. These examples show that selective citing of individual studies can be used to support almost any point of view on the impact of morphological data in combined analysis. To get a more complete picture of the role of morphological data, its average impact across an objective sample of studies must be compared.
The relatively small number of studies that fulfilled our criteria raises the possibility of inadvertent bias in the sample. However, the studies cover a range of taxa from bryophytes (Pedersen et al., 2003) to flowering plants (Aagesen and Sanso, 2003; Cannon and Manos, 2001; Farmer and Schilling, 2002; Fernández et al., 2001; GPWG, 2001; Mansano et al., 2004; Meerow et al., 2002; Meerow and Snijman, 2001; Michelangeli et al., 2003; Renner, 1999) and platyhelminthes (Littlewood et al., 1999) to vertebrates (Wiley et al., 1998) and a variety of taxonomic levels, from genera to kingdoms. If there is any bias in the sample, it is most likely to overestimate the potential role of morphological data in phylogenetic analysis, because in taxonomic groups where morphological data are likely to have less to contribute (such as prokaryotes), morphological data sets tend not to be published at all.
Another way to investigate this question would be to extract and reanalyze the data sets using a standard search protocol, for better comparability between the results of individual studies. The alternative approach adopted here was motivated by the question of whether the inclusion of morphological data in combined phylogenetic analyses has actually resulted in a significant difference to support and resolution in recent published studies; this was successfully investigated by comparing published CFI and bootstrap values. One potential drawback of any such survey lies in the simple dichotomy drawn between molecular and morphological data sets: in many of the studies considered, the molecular data set actually comprised sequences drawn from a number of different gene regions, and was thus itself a "combined" data set, within which different phylogenetic signals may have been present. However, the morphological data sets were similar in composition, comprising combinations of separate data sets drawn from adult and larval morphology, anatomy, palynology, karyology, ecology, life history, and biochemistry. Thus, although the distinction between molecular and morphological data sets is crude, it did not result in a bias against one type of data or another.
Our findings have implications for focusing future phylogenetic research. When planning and initiating a phylogenetic study, there are a number of different factors to be considered and balanced against one another. These include which data sets will provide the most strongly supported, resolved, and accurate phylogeny, and how much investment in terms of research time and resources are needed to generate them. Although this study cannot predict the contribution of a particular data set for a given set of taxa, it can help to estimate the probability that adding a data set will have a positive effect. In general, it is likely that adding a morphological data set to an existing molecular one will have a significant impact on resolution but not on support, whereas a molecular data set is likely to improve both parameters relative to analysis of morphological data alone. It is important to remember that this study focused upon resolution and support, as two of the primary goals of contemporary phylogenetic analysis, but cannot reflect the crucial issue of phylogenetic accuracy, which would ideally need to be determined to provide a full assessment of the performance of phylogenetic methods and data sets. Resolution and support have little meaning if they relate to incorrect clades.
The debate surrounding the role of morphological data still shows no sign of abating (Jenner, 2004; Lee, 2004; Olmstead and Scotland, 2005; Scotland et al., 2003b; Stuessy et al., 2003; Wiens, 2004; Wortley and Scotland, 2006), and continued adaptation of new techniques of phylogenetic analysis to enable them to be used with morphological and combined data implies that there is still a demand for such research (Lewis, 2001; Nylander et al., 2004). In its most widespread application, in combination with molecular sequence data, recent studies have shown that morphology may be either convergent and misleading (Gaubert et al., 2005) or provide important, synergistic support for new clades (Wahlberg et al., 2005). We set out to test the hypothesis that phylogenetic analyses of combined morphological and molecular sequence data sets yield significantly increased levels of resolution and support compared to analyses of molecular data alone. Our results show that the hypothesis has been verified for resolution but not proven with regard to support.
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The authors would like to thank P. Forey, L. Lohmann, N. MacLeod, R. Page, K. Pryer, H. Schneider, M. Wilkinson, and an anonymous reviewer for comments on an earlier draft of this manuscript. A. Grafen and D. Bebber provided help with statistical analysis.
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2 Present Address: Royal Botanic Garden Edinburgh, 20A Inverleith Row, Edinburgh, EH3 5LR, UK
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