* Department of Biology, Boston University
Museum of Zoology
Department of Ecology and Evolutionary Biology, University of Michigan
Correspondence: E-mail: msoren{at}bu.edu.
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Abstract |
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Key Words: Anseriformes avian systematics Galliformes Galloanserae Neoaves Opisthocomus hoazin
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Introduction |
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First, we address the sister relationship and monophyly, respectively, of Anseriformes and Galliformes. Various molecular and morphological analyses agree on the monophyly of Galloanserae (Cracraft 1981; Sibley and Ahlquist 1990; Caspers et al. 1997; Livezey 1997a; Mindell et al. 1997, 1999; Groth and Barrowclough 1999; García-Moreno and Mindell 2000; van Tuinen, Sibley, and Hedges 2000; Livezey and Zusi 2001; Braun and Kimball 2002; Paton, Haddrath, and Baker 2002), but other morphological studies (Ericson 1996, 1997) and a limited analysis of the nuclear c-myc gene (Ericson, Parsons, and Johansson 2001) failed to support this grouping. The basal position of Galloanserae within Neognathae also has been questioned on the basis of spinal cord morphology (Woodbury 1998). Olson and Feduccia (1980) argued that the fossil taxon Presbyornis provides evidence that waterfowl (Anseriformes) and flamingos (Phoenicopteriformes) were derived from ancestral shorebirds (Charadriiformes). This suggestion is inconsistent with DNA-DNA hybridization data (Sibley and Ahlquist 1990) and was explicitly tested and rejected in recent morphological analyses (Ericson 1997; Livezey 1997a), but DNA sequencing studies have not included all of the major lineages within Galloanserae or all of the other avian taxa (e.g., flamingos, charadriiforms) needed to fully test this hypothesis. Our interest in this question was stimulated also by preliminary analyses of 12S rRNA gene sequences in which screamers (Anhimidae) and magpie goose (Anseranatidae), which have long been recognized as anseriforms (Livezey 1997a, 1997b), grouped with cracids, either within the galliform clade or as a sister group to galliforms. Other recent DNA sequencing studies did not include both magpie goose and screamers (Sraml et al. 1996; Groth and Barrowclough 1999) or had too few data to resolve their relationships (Ericson, Parsons, and Johansson 2001).
Second, we address the relationships of the hoatzin (Opisthocomus hoazin). This unique South American bird has puzzled avian systematists since it was described over 200 years ago (see Sibley and Ahlquist [1990] for a historical review of its classification). Most often, the hoatzin has been placed with Galliformes (e.g., Peters 1934; Cracraft 1981), Cuculiformes (e.g., de Quieroz and Good 1988; Hedges et al. 1995; Hughes 1996) or Musophagiformes (e.g., Verheyen 1956; Hughes and Baker 1999; Hughes 2000). Sibley and Ahlquist (1973, 1990) concluded that the hoatzin is a derived cuckoo and nested it within Cuculiformes as the sister lineage of a clade comprising the New World ground cuckoos (Neomorphidae), guira cuckoo, and anis (Crotophagidae). A similar result was obtained by Hughes (1996) using behavioral and ecological characters, although a later analysis placed hoatzin with turacos (Hughes 2000).
Avise, Nelson, and Sibley (1994a), Hedges et al. (1995), and Mindell et al. (1997) analyzed DNA sequence data for the hoatzin but with limited sampling of taxa and/or characters and no clear resolution of its relationships. Johnson, Goodman, and Lanyon (2000) ruled out a placement of hoatzin within cuckoos but sampled too few outgroups to say more. In contrast, Hughes and Baker (1999) found strong support for a sister relationship between hoatzin and turacos (Musophagiformes) in a combined analysis of mitochondrial and nuclear DNA sequences and declared the hoatzin problem "resolved." Hughes (2000) obtained the same result in an osteological analysis in which she identified 19 characters uniting hoatzin and turacos. With greater taxon sampling, our analysis provides a broader test of hoatzin relationships than in other recent studies. We also provide evidence that the sequences reported by Hughes and Baker (1999) contain numerous errors that biased their analysis towards finding a sister relationship between hoatzin and turacos (see Results).
Finally, we comment on some general issues in avian ordinal systematics and include tests of the monophyly of several avian orders, including Anseriformes, Galliformes, a broadly conceived Ciconiiformes (Sibley and Ahlquist 1990), and an inclusive Cuculiformes, comprising cuckoos, turacos, and hoatzin (de Quieroz and Good 1988; Hughes 2000).
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Methods |
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Amplification and sequencing protocols were as in previous studies (Sorenson et al. 1999). We sequenced both DNA strands and reconciled forward and reverse sequences in Sequence Navigator (Applied Biosystems). Requisite precautions were taken to avoid the amplification of nuclear pseudogenes of mitochondrial origin (see Arctander 1995; Sorenson and Fleischer 1996; Zhang and Hewitt 1996), including the use of (1) muscle tissue rather than blood and (2) PCR primers with degenerate sites to prevent the preferential amplification of low copy number nuclear sequences (Sorenson and Quinn 1998). An apparent nuclear copy of the second half of ND2 in Centropus cupreicaudus did not match overlapping sequences for this taxon and contained an unusual 3-bp deletion. We obtained the mtDNA sequence for this taxon by amplifying a 2.8-kb fragment with primers L3827 and H6681 and then using this product as the template for amplification and sequencing of ND2.
Discrepancies between our sequences and those reported by Hughes and Baker (1999 [hereafter HB1999]) led us to replicate our results for hoatzin using two additional samples. We sequenced three different hoatzin samples for the mtDNA regions included in our analysis plus the regions sequenced by HB1999. The three tissues we used included the two used by HB1999 (LSUMNS B-10753 and B-10754). Additional primers used for this work were L6615, L7036, L7525, L7987, L8386, L8929, L9700, L10236, H7122, H7548, H8121, H8628, H9235, H9726, H10343, and H10884.
We also sequenced intron 9 of the nuclear phosphoenolpyruvate carboxykinase (PEPCK) gene (Cook et al. 1986; S. E. Stanley, personal communication). We used a nested PCR approach in which initial amplification using primers GTP1601F (5'-ACGAGGCCTTTAACTGGCAGCA-3') and GTP1793R (5'-CTTGGCTGTCTTTCCGGAACC-3') (S.E. Stanley, personal communication) provided the template for a second amplification using primers PEPCK9F (5'-GGAGCAGCCATGAGATCTGAAGC-3') and PEPCK 9R (5'-GTGCCATGCTAAGCCAGTGGG-3'). Products were sequenced with the latter two primers. We determined PEPCK9 sequences for all taxa except Corvus, Ciconia, and Rhea. PEPCK9 sequences for most taxa comprised 658 to 700 nucleotides (including small portions of the flanking exons), except for Neomorphus, which was 1,014 nucleotides, due to a 333-bp insertion.
Details on genetic samples, voucher specimens, and GenBank accession numbers are available on the journal's Web site as online Supplementary Material.
Phylogenetic Analyses
Phylogenetic analyses were conducted in PAUP* versions 4.0b4-b10 (Swofford 2002) and POY (Gladstein and Wheeler 1996). Most of our analyses are based on a data set of 4,789 mtDNA characters that includes 30 positions with gap characters in one or more taxa but excludes regions of ambiguous alignment. Gaps were treated as a fifth character state in parsimony analyses. The excluded "gap regions" comprised approximately 350 nucleotides and 150 gap characters per taxon. We determined bootstrap values (Felsenstein 1985) using full heuristic searches and 500 randomly resampled data sets and Bremer support indices (Bremer 1988) using the program TreeRot (Sorenson 1999).
The failure of our study to corroborate the results of HB1999 led us to evaluate whether certain classes of DNA sequence characters or different kinds of character change provided conflicting evidence with respect to a number of specific phylogenetic hypotheses. In particular, we were interested in whether a high degree of homoplasy or convergent evolution in one class of characters (e.g., third codon positions in protein-coding genes) might obscure the phylogenetic signal in a more conserved class of characters. For the full data set and for each of four character partitions, we completed a series of parsimony analyses with increasingly severe down-weighting of transitions. Three of the character partitions were first, second, and third codon positions, respectively, whereas the fourth partition combined well-aligned portions of rRNA and tRNA genes. Although the different protein-coding genes in our analysis have somewhat different rates and modes of molecular evolution, we combined codon positions across genes, reasoning that functional constraints on sequence evolution are more similar within codon positions across genes than across codon positions within genes, at least for a set of mitochondrial genes.
After finding the most parsimonious (MP) tree for each character partition and weighting scheme, we evaluated the strength of evidence for or against specific phylogenetic hypotheses in the following manner. If the clade of interest was present in the MP tree, we determined its Bremer support index (i.e., the number of extra steps required in the shortest tree without that clade [Bremer 1988]). If the specified clade was not present in the MP tree, we used a constrained parsimony search to determine the number of extra steps in the shortest tree that included the clade. This latter value has been defined as the local incongruence length difference (LILD) in the slightly different context of evaluating conflict among data partitions (Thornton and DeSalle 2000 [see also figure 6 in Johnson and Sorenson 1998]). As applied here, different data partitions in the current analysis may agree with each other, but all conflict with a previous hypothesis. Nonetheless, it is straightforward to determine for each data partition the number of extra steps required to obtain the previous hypothesis and we refer to this number as the LILD. As noted by Thornton and DeSalle (2000), Bremer support and LILD are similar and complimentary measures. A hypothesized clade has a positive Bremer value (and an LILD of 0) if it is present in the MP tree(s), whereas it has a positive LILD (and a Bremer of 0) if it is not present in the MP tree(s). Thus Bremer support and LILD, respectively, measure the strength of evidence for or against a particular clade on the same relative scale. We determined both Bremer and LILD values in the context of separate analyses for each data partition, rather than in a combined or simultaneous analysis. The latter approach is used in calculating partitioned Bremer support (Baker and DeSalle 1997). For each combination of character partition, weighting scheme, and search constraint, we completed 200 replicate heuristic searches with random addition of taxa and tree-bisection-reconnection (TBR) branch-swapping.
We completed two additional analyses to evaluate the extent to which inferred relationships varied among analyses using different approaches to tree reconstruction. First, we used optimization alignment (Wheeler 1996), as implemented in the program POY (Gladstein and Wheeler 1996), to analyze the full mtDNA data set, including regions with gaps. Although generally excluded from phylogenetic analyses, sequence regions that vary in length among taxa may contain valuable phylogenetic information (Giribet and Wheeler 1999; Simmons, Ochoterena, and Carr 2001; Sorenson and Payne 2001). Optimization alignment combines tree search and sequence alignment into a single process to find the most parsimonious combination of alignment and tree topology. We completed 100 replicate heuristic searches with random addition of taxa for both an equal weights parsimony analysis (gap cost = 1) and an analysis with transitions down-weighted by 50% (gap cost = transversion cost = 2, transition cost = 1). Other parameter settings in POY included -noquick, -slop = 5, -checkslop = 10, and -maxtrees = 5. Tree scores output by POY may slightly overestimate the actual tree length (see Sorenson and Payne 2001), so we examined all search replicates yielding trees within 10 steps of the best score for each weighting scheme.
Second, we conducted maximum-likelihood (ML) analyses in PAUP* based on well-aligned portions of the data set only and excluding 30 additional positions with a gap character in one or more taxa. We used Modeltest (Posada and Crandall 1998) to select a model of sequence evolution. The general time reversible (GTR) model, with unequal nucleotide frequencies, a proportion of invariant sites (I), and -distributed rate variation among sites (the most highly parameterized model available in PAUP*) provided the best fit to the data. Parameter estimates for this model were obtained for the MP tree with 50% down-weighting of transitions, and these values were then fixed for subsequent tree searches, thereby reducing computation time. ML parameter estimates were as follows. Base frequencies: A = 0.3803, C = 0.3858, G = 0.068, and T = 0.1659. Relative transformation rates: A-C = 0.2212, A-G = 5.7677, A-T = 0.4893, C-G = 0.2091, C-T = 5.0518, G-T = 1.0000. Proportion of invariant sites: I = 0.3575. Shape parameter for the
distribution:
= 0.3970. Forty heuristic searches with random addition of taxa were completed for the unconstrained ML analysis and 30 replicates were completed for each of several analyses constrained to find specified clades. The approximately unbiased test of Shimodaira (2002) as implemented in CONSEL (Shimodaira and Hasegawa 2001) was used to test for significant differences in likelihood between constrained and unconstrained trees.
Finally, we completed a separate parsimony analysis of the PEPCK9 sequences and a combined analysis of the PEPCK9 and mtDNA data. The PEPCK9 alignment was generally unambiguous but included numerous insertions and deletions, many of which involved multiple bases. Because contiguous gap characters may not represent independent evolutionary events (e.g., Simmons and Ochoterena 2000), we treated gap characters in the PEPCK alignment as missing data and added to the data matrix a new character for each unique indel, regardless of length. In cases where one indel was a subset of a larger indel in another taxon, we coded them as alternative character states in a single multistate character. To simplify this process, we excluded sequences of Struthio and Eudromia, which were quite divergent from other birds and more difficult to align. The alignment of two small regions (comprising from 7 to 10 and 6 to 11 nucleotides per taxon, respectively) was ambiguous, so we recoded each of these regions as a single multistate character to which we applied a step matrix specifying the number of steps required to change from one character state (i.e., unique sequence) to another (see Lutzoni et al. 2000). The PEPCK data set included 743 aligned nucleotide positions (excluding a 333-bp insertion in Neomorphus) plus 49 additional gap characters, 17 of which were parsimony informative. Double-peaks resulting from allelic variation were coded with standard IUPAC codes and treated as polymorphisms in the parsimony analysis.
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Results |
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The maximum-likelihood tree included all of the clades mentioned above, except for the sister relationship between Passerifomes and Cuculiformes (fig. 2). Relationships among taxa within Galliformes, Anseriformes, Passeriforms, and Cuculiformes, respectively, also were identical in parsimony and likelihood trees. Within Passeriformes, both oscines and subocines are monophyletic based on the taxa considered here. Within Cuculiformes, a New World ani Crotophaga and ground cuckoo Neomorphus are sister to a clade comprising a coucal Centropus, a New World nesting cuckoo Coccyzus, and an Old World brood parasite Cuculus. This topology is consistent with a comprehensive analysis of cuckoo relationships based on mtDNA 12S and ND2 sequences (Sorenson and Payne 2003) but differs from recent morphological studies (Hughes 1996, 2000). Other similarities between parsimony and likelihood analyses were a sister relationship between flamingo Phoenicopterus and two charadriiforms Burhinus and Scolopax and the failure to support Ciconiiformes as defined by Sibley and Ahlquist (1990). Also in contrast to parsimony analyses, the maximum-likelihood tree included a sister relationship between Buteo and Falco, corresponding to the infraorder Falconides in Sibley and Ahlquist (1990) or the order Falconiformes in most other classifications (e.g., Amadon and Bull 1988; Griffiths 1994). Other interordinal relationships differed among analyses.
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A separate analysis of PEPCK9 sequences yields a large number of equally parsimonious trees, the strict consensus of which includes most of the well-supported nodes in the mtDNA trees (fig. 3). Also consistent with some of the mtDNA analyses, the PEPCK9 tree includes a sister relationship between flamingo and two charadriiforms (Burhinus and Scolopax). The only results that differ from the mtDNA analyses are (1) a sister relationship between a roller Coracias and a hornbill Tockus and (2) lack of suboscine monophyly (i.e., Sayornis plus Smithornis), neither of which is strongly supported. Combined analyses of PEPCK and the much larger mtDNA data set yield results very similar to the mtDNA only analyses but with rearrangement of some basal nodes within Neoaves.
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Relationships of the Hoatzin
The position of hoatzin was variable among analyses and the alternative placements found were weakly supported (e.g., fig. 1). In parsimony analyses, hoatzin was sister either to Falco or Trogon, depending on weighting scheme. In the ML tree, hoatzin is sister to the two columbiforms we sampled (fig. 2). A sister relationship with doves also was found in 74% of the MP trees in the PEPCK analysis. In other PEPCK trees, hoatzin was sister to the owl Asio or to a clade comprising parrots and passeriforms. In no case did we find a sister relationship between hoatzin and turacos. Our results contrast with those of HB1999 in which a comparable data set indicated very strong support for a sister relationship between hoatzin and turacos (93% support value based on ML-based quartet puzzling).
We analyzed different data partitions under a range of weighting schemes to explore whether evidence of a relationship between turacos and hoatzin might be present in particular subsets of the mtDNA data or in certain kinds of character change (fig. 4). None of these partitioned analyses supported a sister relationship between hoatzin and turacos, and the number of additional steps required to obtain this result (the LILD) was relatively large in all cases, particularly for second codon positions (fig. 4a). Down-weighting transitions had little effect on the relative magnitude of the LILD, suggesting that focusing on relatively conserved transversions also provided no evidence of a relationship between hoatzin and turacos. Similarly, none of the partitioned analyses suggested a relationship between hoatzin and cuckoos (fig. 4b).
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Our failure to corroborate the results of HB1999 led us to compare cytochrome b sequences for taxa common to both data sets (cytochrome b was the only gene region sequenced in both studies). Sequences reported by HB1999 differ by at least 2.4% and by as much as 8.4% from our sequences for the same species (table 2). Differences in at least the Opisthocomus and Neomorphus sequences must reflect some form of error rather than intraspecific variation, because tissue samples from the same individual birds were used in both studies. Other sequences reported by HB1999 differ substantially from sequences reported in a variety of previous studies and show a ratio of transversion differences that is much higher than expected for intraspecific comparisons (table 2). In contrast, most of our sequences differ by less than 1% from previous sequences for the same taxa (table 2). Exceptions include Opisthocomus and Coccyzus sequences from Avise, Nelson, and Sibley (1994a), a study that was criticized for sequencing errors (Hackett et al. 1995), and Colius and Trogon sequences reported by Espinosa de los Monteros (1998, 2000). Nonetheless, our Opisthocomus and Colius sequences are more similar to sequences from these previous studies than are the sequences of HB1999. The Trogon sequences differ primarily by transitions, as would be expected for a comparison of somewhat divergent haplotypes within a species.
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Using our data set, we evaluated alternative phylogenetic hypotheses for the hoatzin using both maximum likelihood and parsimony. In general, there is a strong correlation between the ln L for a given hypothesis in the mtDNA analysis and the number of extra steps (the LILD) in parsimony analyses of either mtDNA or PEPCK sequences (table 4). Hoatzin is clearly not a galliform or a derived New World cuckoo. Whereas the number of extra steps required to unite hoatzin with turacos or cuckoos is large, neither hypothesis is significantly rejected in a likelihood framework. This is nonetheless a very different result from the bootstrap analysis of HB1999, which suggested strong support for hoatzin plus turacos and significant rejection of a hoatzin plus cuckoo clade (see their table 2). Our bootstrap analyses also suggest little or no support for placing hoatzin with either turacos or cuckoos (table 4).
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Discussion |
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Galloanserae
Within Galliformes, our analyses show strong support for a sister relationship between megapodes and all other galliforms. This differs from DNA-DNA hybridization results in which cracids and megapodes were sister taxa (Sibley and Ahlquist 1990) but is consistent with morphological studies (Livezey and Zusi 2001) and other recent DNA sequencing studies (Ericson, Parsons, and Johansson 2001; Dimcheff, Drovetski, and Mindell 2002). In contrast, monophyly of Anseriformes was weakly supported and relationships among a screamer, magpie goose, and anatids were variable among analyses. Separate analyses of RNA characters (rRNA plus tRNA) nested the screamer or screamer plus magpie goose within galliforms as the sister taxon of cracids, suggesting some conflict within the mtDNA data set. PEPCK sequences and the mtDNA ML analysis, however, both support monophyly of Anseriformes and Galliformes. Divergence of both screamers and magpie goose near the base of the anseriform radiation (fig. 2) likely contributes to the weak support for Anseriformes in our analyses.
Within Anseriformes, all analyses of the full mtDNA data set suggest a sister relationship between a screamer and magpie goose (see also Sibley and Ahlquist 1990; Mindell et al. 1997). This result conflicts with traditional classifications and recent morphological analyses in which screamers are sister to a clade comprising magpie goose and anatids (Livezey 1997a, 1997b). Nuclear gene sequences also support this traditional arrangement (Cracraft et al. 2003). Divergent base composition in Aythya (fig. 6), one of the two anatids we sampled, may account for the inconsistent mtDNA results. When Aythya is excluded, magpie goose is sister to Dendrocygna rather than the screamer Chauna in both parsimony and likelihood analyses of the mtDNA data.
Hoatzin
In reviewing the history of classification of the hoatzin, Sibley and Ahlquist (1990) made clear the need for "reason ... to supplant tradition" (p. 378) in avian systematics. Unfortunately, progress in solving the hoatzin problem seems to have been hindered both by traditional points of view about its relationships and conclusions based on insufficient or erroneous data. Although Sibley and Ahlquist's (1972, 1973) results for egg-white proteins could not be replicated by Brush (1979), the earlier result apparently influenced their interpretation of DNA-DNA hybridization data for hoatzin. The latter were of poor quality because of technical problems with the hoatzin sample and provided essentially no useful information about hoatzin relationships (F. Sheldon, personal communication). Data quality was again an issue in the DNA sequencing studies of Avise, Nelson, and Sibley (1994a [see Hackett et al. 1995]) and Hughes and Baker (1999), as shown above.
Strong support for a sister relationship between hoatzin and turacos in HB1999 can be attributed primarily to sequencing errors and perhaps to a lesser extent the more limited sample of taxa in their study. Differences between the studies are not due to the inadvertent sequencing of nuclear copies or "numts" (see Quinn 1992; Arctander 1995; Zhang and Hewitt 1996; Sorenson and Quinn 1998). This explanation would require that the many different primer pairs used in each study consistently amplified mtDNA in one study and nuclear homologs in the other. In addition, large numbers of transversion differences (tables 2 and 3) are inconsistent with expectations for intraspecific comparisons of mtDNA and numts. Sequences transposed to the nucleus experience a reduced rate of evolution such that most differences between mtDNA and numt accumulate in the mtDNA copy (Zischler et al. 1995; Sorenson and Fleischer 1996; Bensasson et al. 2001). This means numts may be more similar to ancestral sequences, which is the case for sequences reported by HB1999 (see fig. 5), but comparison of mtDNA and numts from the same species should also yield a typically high transition-transversion ratio (e.g., Lopez et al. 1994).
Errors in the HB1999 data set generally increased the similarity of their sequences, but increased disproportionately the similarity of hoatzin and turaco sequences (table 3 and fig. 5). Given very low support values for interordinal relationships within Neoaves generally (fig. 1), alternative topologies may turn on a very small number of characters. An error rate of 1.5% (i.e., 74 characters in a 4,796 character data set) easily overwhelms this kind of analysis, particularly when the errors involve transversion differences that carry more weight in model-based phylogenetic analyses. The conflicting results of our study and that of HB1999 highlight the need for accurate sequence data and replication in molecular systematicsespecially for monotypic taxa such as the hoatzin.
In our analyses, the position of hoatzin as well as other basal relationships within Neoaves were not well resolved. Although we were not able to reject all previous hypotheses for the hoatzin in a maximum-likelihood framework, neither did we find any compelling evidence that hoatzin is closely related to either turacos or cuckoos. These clades required a large number of extra steps in parsimony analyses and were never or almost never recovered in bootstrap analyses using either MP or ML (table 4). Analysis of individual data partitions across a range of transition weights also suggests the lack of any phylogenetic signal for a relationship between hoatzin and either turacos or cuckoos (fig. 4). Similarly, a recent morphological analysis of avian lice found that Osculotes, a genus specific to hoatzin, was the sister taxon of a large clade of lice, none of which occur on either cuckoos or turacos (Smith 2001).
If anything, our data suggest a sister relationship between hoatzin and doves (Columbiformes). This was the result of our ML analysis and parsimony analyses in which a few long-branched taxa (Trogon, Falco, and Buteo) were excluded. With all taxa included, a hoatzin-plus-doves clade never required more than a small number of extra steps in comparison to the MP tree (fig. 4f). Finally, a hoatzin-plus-doves clade was present in 74% of the MP trees from our analysis of PEPCK intron 9. This potential congruence of mitochondrial and nuclear data is noteworthy and suggests that a relationship between hoatzin and doves deserves further testing by both molecular and morphological systematists. After galliforms, cuckoos, and turacos, doves are mentioned most frequently in Sibley and Ahlquist's (1990) review of hoatzin systematics, presumably reflecting at least some similarity perceived by early taxonomists. Of course, our result is not strongly supported and is conditional on the taxa included in our analysisfor example, we sampled none of the diverse set of taxa included in Gruiformes by Sibley and Ahlquist (1990).
Problems and Prospects in Avian Molecular Systematics
As in other recent molecular studies (Groth and Barrowclough 1999; van Tuinen, Sibley, and Hedges 2000; van Tuinen et al. 2001; Johansson et al. 2001), we find support for Neoaves but poor resolution of relationships within this clade. Strong support for the deeper split between Neoaves and Galloanserae makes clear that this difficulty is not simply a problem of reconstructing ancient divergences. Rather, the potential to resolve relationships with molecular data is a function of internode length relative to the time depth of the divergences involved. Many avian orders clearly diverged from each other in a relatively rapid radiation, raising the question of whether the base of Neoaves represents a genuine polytomy that simply cannot be resolved (see Stanley and Cracraft 2002; Poe and Chubb, in review).
Based on our analyses, we think molecular sequence data continue to have significant utility for testing hypotheses about interordinal relationships within Neoaves. Our approach of analyzing different data partitions under various weighting schemes (i.e., fig. 3), for example, provides a fairly convincing rejection of hypotheses relating hoatzin to either cuckoos or turacos, even though these hypotheses were not statistically rejected in a ML framework. The placement of hoatzin remains uncertain, however, and this kind of result may be a recurring problem for avian ordinal systematicscertain hypotheses will be relatively easily rejected, but their alternatives may remain poorly supported. One potential positive result at the interordinal level was the sister relationship between flamingo and two charadriiforms found in both our PEPCK and our mtDNA analyses. This result is not necessarily inconsistent with van Tuinen et al. (2001), in which flamingos and grebes were strongly supported as sister taxa. The addition of a grebe to our data set would be needed to further test this interesting hypothesis.
Our analysis of data subsets with different modes of evolution is potentially valuable as a heuristic approach to testing hypotheses and discovering conflicts or systematic biases within a larger data set. This approach, however, partitions characters into classes that are still demonstrably heterogenous (see below) and fails to capture the potentially complex interaction of characters in an analysis of the full data set. A sister relationship between hoatzin and Falco, for example, is supported by the full mtDNA data set when transitions are down-weighted 40% to 70%, even though none of the individual data partitions support this result (fig. 4d). Although far more demanding computationally, this approach also could be implemented in a ML framework, calculating lnL for ML trees with and without a particular clade (see Lee and Hugall 2003). Ideally, such analyses would fit an appropriate model of sequence evolution to each data partition independently. Although consistent failure (or conversely strong support) of a particular hypothesis across data partitions is of significant interest, combined analyses of all available character data should be given priority in the development and testing of phylogenetic hypotheses (e.g., Baker and DeSalle 1997).
A continuing problem in higher-level avian systematics will be variation in base composition among lineages, a form of nonindependent character evolution that can bias phylogenetic analyses (e.g., Naylor and Brown 1998; Foster and Hickey 1999; Sorenson and Payne 2001). Convergent base composition in unrelated taxa may obscure historical relationships, whereas divergent base composition inherited from a common ancestor may inflate the apparent support for a natural group (e.g., Sefc, Payne, and Sorenson 2003). With respect to the competing hypotheses of turacos, cuckoos, or doves as the sister group of hoatzin, small differences in overall base composition (see fig. 6) seem unlikely to overwhelm all other information in the data set. Anseriforms and galliforms, for example, show a broad range of base composition, yet still form a well-supported clade, as do the four passeriforms we sampled. In contrast, the hornbill-plus-owl (Tockus-plus-Asio) clade in our mtDNA analyses and unexpected relationships within Anseriformes (see above) may be artifacts of variation in base composition among taxa.
Significant variation in base composition is evident in most data sets covering broad taxonomic samples, and failure to account for this variation is perhaps one of the most significant shortcomings of commonly used models of sequence evolution. ML methods that incorporate lineage-specific base composition have been developed (Galtier and Gouy 1995, 1998; Yang and Roberts 1995) and applied in avian studies (Haddrath and Baker 2001; Paton, Haddrath, and Baker 2002). The current implementation of this method effectively allows only the evaluation of candidate trees and not searches of tree space and therefore was impractical given the number of taxa in our analysis. Other complications in real sequence data include variation in the substitution rate matrix among nucleotide positions and lineage-specific differences in the rate matrix even within individual positions (Lopez, Casane, and Philippe 2002), as may occur in a "covarion" process in which substitution patterns at a site depend on changes in neighboring sites (Fitch 1971; Galtier 2001). In our experience with large data sets, application of model selection criteria (e.g., as implemented in Modeltest [Posada and Crandall 1998]) almost always results in selection of the most complex model tested (e.g., GTR + I + )this begs the question of how much additional complexity might be justified statistically and to what extent more complex models will affect or improve phylogenetic inference (see Sanderson and Kim 2000; Buckley and Cunningham 2002).
Recent molecular analyses of avian orders, including ours, are still quite limited in terms of the number of taxa and characters considered. Increased taxon sampling may improve the resolution of relationships within Neoaves by allowing better reconstruction of ancestral character states and in effect reducing the relative depth of divergence for basal internodes. Recent studies strongly suggest benefits from greater taxon sampling (Pollock et al. 2002; Zwickl and Hillis 2002), perhaps in part because it reduces potential biases associated with some of the complexities of sequence evolution discussed above. Unfortunately, breaking long branches is not an option for monotypic taxa such as the hoatzin, except for the addition of relevant fossil material to morphological studies.
Studies of avian relationships are shifting from mitochondrial to nuclear sequence data (e.g., Groth and Barrowclough 1999; Johansson et al. 2001; Barker, Barrowclough, and Groth 2002), presumably on the logic that more conserved nuclear genes will provide better resolution of deep divergences. We think there is a need, however, for direct comparisons of the efficacy of comparable mtDNA and nuclear data sets for much larger samples of taxa before all effort is diverted from one genome to the other. The potential to use mitochondrial and nuclear data as independent sources of character information argues for the continued collection of both. Given the magnitude of the avian orders problem, comprehensive analyses of relationships within avian families and orders may be more productive for individual researchers in the short term. If these efforts are minimally coordinated, a database of comparable mitochondrial and nuclear sequence data applicable to avian interordinal relationships will be generated.
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Acknowledgements |
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Footnotes |
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2 Present address: Max Planck Research Centre for Ornithology, Vogelwarte Radolfzell, Radolfzell, Germany.
Scott Edwards, Associate Editor
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References Cited |
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