Phylogeny and Character Behavior in the Family Lemuridae

Molecular Phylogenetics and Evolution Vol. 15, No. 1, April, pp. 124–134, 2000 doi:10.1006/mpev.1999.0723, available online at http://www.idealibrary.com on

Phylogeny and Character Behavior in the Family Lemuridae Yael Wyner,*,† Rob DeSalle,† and Robin Absher† *Department of Biology, New York University, Washington Square, New York, New York 10003; and †Molecular Laboratories, American Museum of Natural History, 79th Street at Central Park West, New York, New York 10024 Received May 17, 1999; revised August 10, 1999

A phylogenetic analysis of the family Lemuridae was accomplished using multiple gene partitions and morphological characters. The results of the study suggest that several nodes in the lemurid phylogeny can be robustly resolved; however, the relationships of the species within the genus Eulemur are problematically nonrobust. The genus Varecia is strongly supported as the basal genus in the family. Hapalemur and Lemur catta are strongly supported as sister taxa and together are the sister group to the genus Eulemur. E. mongoz is the most basal species in the genus Eulemur. E. fulvus subspecies form a monophyletic group with three distinct lineages. E. coronatus is strongly supported as the sister taxon to E. macaco. The relationships of E. rubriventer, E. fulvus, and the E. macaco–E. coronatus pair are unresolved. Our combined molecular and morphological analysis demonstrates the lack of influence that morphology has on the simultaneous analysis tree when these two kinds of data are given equal weight. The effects of several extreme weighting schemes (removal of transitions and of third positions in protein-coding regions) and maximum-likelihood analysis were also explored. We suggest that these other forms of inference add little to resolving the problematic relationships of the species in the genus Eulemur. r 2000 Academic Press

INTRODUCTION Several molecular studies have examined the systematic relationships of Malagasy primates in general and the family Lemuridae in particular (Yoder et al., 1996a,b; Stanger-Hall and Cunningham, 1998; Yoder and Irwin, 1999). Most of these studies have begun to converge on the same set of hypotheses concerning the systematics of taxa in the family Lemuridae. In addition, morphological data have also been examined in detail for many of the species in the Lemuridae (Tattersall and Schwartz, 1974; Eaglen, 1983; Groves and Eaglen, 1988; Simons and Rumpler, 1988; Tattersall and Schwartz, 1991; Yoder, 1994; Stanger-Hall, 1997). The quality and utility of these morphological characters have been assessed and for some comparisons there is topological incongruence between molecules and mor1055-7903/00 $35.00 Copyright r 2000 by Academic Press All rights of reproduction in any form reserved.

phology (Yoder and Irwin, 1999; Baker et al., 1998). Yoder and Irwin (1999) and Stanger-Hall and Cunningham (1998), using molecular approaches, and StangerHall (1997), using morphological characters, have shown that inferences concerning relationships of species within the genus Eulemur are somewhat weak. Related to this lack of robustness at nodes within Eulemur are issues concerning character weighting. Both Yoder and Irwin (1999) and Stanger-Hall and Cunningham (1997) suggest character weighting as a means of overcoming the incongruence of molecular data within Eulemur. In this communication we present a phylogenetic analysis using an expanded data set for the Lemuridae that includes a complete species-level sampling of the taxa in the Lemuridae and comprises multiple data partitions (12S, cyt-b, d-loop, casein kinase II, morphology, and behavior). In addition, we include at least two exemplars of each species in our analyses. We also use these data in a simultaneous analysis framework to examine the congruence of molecules and morphology for these taxa and examine issues of robustness of the phylogenetic hypotheses that we generate. MATERIALS AND METHODS Taxa and Data Matrices The samples that we examined in this study are listed in Table 1. Previous studies have used other character partitions for a smaller taxonomic sampling that partially overlaps ours (Table 2). We therefore decided to construct two data matrices. The first matrix included all of the specimens listed in Table 1 for five partitions (cyt-b, 12S, d-loop, casein kinase II, and morphology). The second matrix included a reduced taxon sampling nearly identical to that used by Yoder and Irwin (1999), except that instead of using Microcebus as an outgroup we inserted Daubentonia as an outgroup. This matrix has seven partitions (cyt-b, 12S, d-loop, casein kinase II (present study), COII, IRBP (Yoder et al., 1996a; Yoder and Irwin, 1999), and morphology). Daubentonia was coded as missing for the IRBP sequences. Morphological characters were taken from Table 1 of Stanger-Hall (1997).

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TABLE 1 Samples Used in This Study Sample

Abbreviations

Location of origin

Source

GenBank cyt-b

GenBank 12S

GenBank d-loop

GenBank casein kinase II

Eulemur coronatus 1 Eulemur coronatus 2 Eulemur macaco flavifrons 1 Eulemur macaco flavifrons 2 Eulemur macaco macaco 1 Eulemur macaco macaco 2 Eulemur fulvus collaris 1 Eulemur fulvus collaris 2 Eulemur fulvus albocollaris 1 Eulemur fulvus albocollaris 2 Eulemur fulvus fulvus 1 Eulemur fulvus fulvus 2 Eulemur fulvus sanfordi 1 Eulemur fulvus sanfordi 2 Eulemur fulvus albifrons 1 Eulemur fulvus rufus 1 Eulemur fulvus rufus 2 Eulemur rubriventer 1 Eulemur rubriventer 2 Eulemur mongoz 1 Eulemur mongoz 2 Lemur catta1 Lemur catta 2 Hapalemur simus 1 Hapalemur simus 2 Varecia variegata variegata 1 Varecia variegata rubra 1 Propithecus tattersalli Propithecus tattersalli Daubentonia

Ecor1 Ecor2 Emflav1 Emflav2 Emmac1 Emmac2 Efcol1 Efcol2 Efalbo1 Efalbo2 Efful1 Efful2 Efsan1 Efsan2 Efalb1 Efruf1 Efruf2 Erub1 Erub2 Emon1 Emon2 Lcat1 Lcat2 Hap1 Hap2 Vvvar1 Vvrub1 Prop1 Prop2 Daub

Analamahitsy Sakaramy Maromandia Maromandia * * Fort Dauphain Near Berenty Vevembe Vevembe * * Mt d’Ambre * Masoala Ranomafana Ranomafana Northern range Ranomafana Moheli Island Moheli Island * * Karianga Karianga * * Antsahalalina Antsahalalina Mananara Region

DUPC DUPC DUPC DUPC DUPC DUPC DUPC DUPC Wild Wild DUPC DUPC DUPC DUPC DUPC DUPC DUPC DUPC DUPC DUPC DUPC DUPC DUPC Wild Wild DUPC DUPC DUPC DUPC DUPC

AF175831 AF175832 AF175836 AF175835 AF175837 AF175849 AF175833 AF175834 AF175857 AF175858 AF175841 AF175842 AF175845 AF175846 AF175856 AF175854 AF175855 AF175847 AF175848 AF175843 AF175844 AF175838 AF175839 AF175859 AF175860 AF175851 AF175850 AF175853 AF175852 AF175840

AF175772 AF175773 AF175777 AF175776 AF175778 AF175790 AF175774 AF175775 AF175798 AF175799 AF175782 AF175783 AF175786 AF175787 AF175797 AF175795 AF175796 AF175788 AF175789 AF175785 AF175784 AF175779 AF175780 AF175800 AF175801 AF175792 AF175791 AF175794 AF175793 AF175781

AF175861 AF175862 AF175866 AF175865 AF175867 AF175879 AF175863 AF175864 AF175887 AF175888 AF175871 AF175872 AF175875 AF175876 AF175886 AF175884 AF175885 AF175877 AF175878 AF175874 AF175873 AF175868 AF175869 AF175889 AF175890 AF175881 AF175880 AF175882 AF175883 AF175870

AF175802 AF175803 AF175807 AF175806 AF175808 AF175820 AF175804 AF175805 AF175827 AF175828 AF175812 AF175813 AF175816 AF175817 AF175826 AF175824 AF175825 AF175818 AF175819 AF175815 AF175814 AF175809 AF175810 AF175829 AF175830 AF175822 AF175821 AF175823 AF175811

* Sample from unknown origin.

DNA Isolation, PCR, and Sequencing DNA was isolated from blood samples shown in Table 1 using the method outlined in DeSalle et al. (1993). Polymerase chain reaction (PCR) was performed in ABI 486 and 9600 Thermal Cyclers. Table 3 shows the primer sequences and reaction conditions for each primer pair for which we generated new sequences (cyt-b, 12S, d-loop, and casein kinase II). DNA sequencing was done by manual methods using USB dideoxy chain terminating methods and S35. Automated sequences were generated on an ABI 373 automated sequencer using ABI dye termination technology. All samples were sequenced in both directions and automated sequences were compiled and corrected using Sequencher software. All sequences have been deposited in GenBank under Accession Nos. AF175772– AF175890. Alignment and Phylogenetic Analysis Two matrices (a full matrix and a reduced matrix as described above) were generated. We used Daubentonia and Propithecus as outgroups in analyses of both matrices. Alignments for 12S and d-loop were per-

formed using MALIGN (Wheeler and Gladstein, 1996) with gap:change costs of 2, 4, 6, and 8. Alignmentambiguous regions were removed using the CULL method outlined in Gatesy et al. (1993). Analyses using a gap:change cost of 4 were also generated. Since the results of the analyses in which alignment-ambiguous regions were removed were identical to those using the single alignment gap:change cost of 4, we arbitrarily chose to report here the results of the analyses using the gap:change cost of 4. Gaps were scored as characters. We explored the range of character weighting by doing three analyses with each of the two matrices. The first analysis treated all characters as equally weighted, the second analysis removed third codon positions in cyt-b and COII, and the third analysis removed transitions from the analysis for all DNA sequences. All trees reported in this paper are strict consensus trees (except for the bootstrap trees). Parsimony, likelihood, and bootstrap analyses were accomplished with PAUP4.0 (Swofford, 1999). Bootstrap analyses were accomplished with 100 replicates of 10 random addition heuristic searches per replicate. Only those nodes with greater than 50% support are reported here. Likelihood

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of incongruence were calculated with the Partition Homogeneity option in PAUP4.0. Partitioned Bremer support was calculated as outlined in Baker and DeSalle (1997).

TABLE 2 Taxon Sampling in Molecular Studies of the Lemuridae

Taxa

Sa

Y1 a

Y2 a

Wa

V. v. varieagata Hapalemur L. catta E. macaco E. mongoz E. coronatus E. f. rufus E. f. albifrons E. f. collaris

V. v. varieagata Hapalemur L. catta E. f. rufus E. f. collaris

V. v. varieagata V. v. rubra Hapalemur L. catta E. m. macaco E. m. flavifrons E. mongoz E. f. rufus E. f. albifrons E. f. collaris E. rubriventer

V. v. varieagata V. v. rubra Hapalemur L. catta E. m. macaco E. m. flavifrons E. mongoz E. f. rufus E. f. albifrons E. f. collaris E. f. albocollaris E. f. fulvus E. f. sanfordi E. rubriventer E. coronatus

COII cyt-b

d-loop COII cyt-b IRBP MORPH

d-loop cyt-b 12S casein MORPH

Genes b 16S COII cyt-b

a S, Stanger-Hall and Cunningham, 1998; Y1, Yoder et al., 1996a; Y2, Yoder and Irwin, 1999; W, present study. b cyt-b, mt cytochrome b partition, 180 bp; 12S, mt 12S rDNA partition, 230 bp; d-loop, mt control region partition, 273 bp; casein, nuclear casein kinase II intron partition, 511 bp; MORPH, morphological partition. IRBP (938 bp) and COII (684 bp) were examined for an even smaller subset using single representatives of Eulemur, Varecia, Hapalemur, and Lemur.

analyses used heuristic searches with the imposition of a variety of models that are discussed in the text. Bremer support for nodes were calculated using AUTODECAY (Erikson, 1994; Bremer, 1988, 1994). Incongruence length differences (ILDs) and tests of significance TABLE 3 Primers Used Primer dlp5 a (d-loop) (Baker et al., 1993) dlp1.5 a (d-loop) GCA-CCC-AAA-GCT-GARRTT-CTA cyt-b1 a (Irwin et al., 1992) cyt-b2 a (Irwin et al., 1992) 12Sa a (Kocher et al., 1989) 12Sb a (Kocher et al., 1989) CasN2f b (casein kinase II) CTC-ACT-GGA-CTCAAT-GAG-CAG-G CasN3ra b (casein kinase II) TCA-AGC-TCT-TCATCT-GAA-ACA-C

Fragment size (bp) ⬃500 ⬃500 180 180 230 230 511 511

a Reaction conditions of 94°C for 1 min, 47°C for 1 min, 72°C for 1 min 30 s for 35 cycles. b Reaction conditions of 94°C for 45 s, 54°C for 45 s, 72°C for 1 min for 40 cycles.

RESULTS A Phylogenetic Hypothesis for the Lemuridae We chose three ‘‘extreme’’ weighting schemes to explore the robustness of the phylogenetic hypotheses that we obtained. We also chose these three weighting schemes to explore the range of effects of weighting on phylogenetic inferences for this group. In all of these analyses gave equal weight to morphological and molecular characters. Figure 1 shows the results of parsimony analysis using the reduced taxon data set for these three weighting schemes. The major difference among these three schemes is that the equally weighted analysis recovered E. mongoz as sister to all other Eulemur taxa with relatively high bootstrap and Bremer support (Fig. 1). Both transversion parsimony and removing third positions recovered similar topologies with weak support for the placement of E. mongoz. This result suggests that character information from transitions and third positions in codons are the major source of support for E. mongoz as the basal taxon in the genus Eulemur in the equally weighted simultaneous analysis tree. Figure 2 shows the results of phylogenetic analysis using the expanded taxon data set. The overall results of this analysis are similar to those reported in Fig. 1 in that transversion parsimony and removing third codon positions deresolve the relationships of E. mongoz with respect to other Eulemur species. In addition, the weighting schemes also deresolve the position of E. rubriventer, although the position of both E. mongoz and E. rubriventer are not strongly supported in the equally weighted analysis. E. coronatus is observed in two of the analyses as the sister taxon to E. macaco subspecies with high bootstrap and Bremer support (Fig. 2). All six subspecies of E. fulvus are observed as a monophyletic group in all three analyses. Wyner et al. (1999) suggested that E. fulvus could actually be considered three separate units and the current unweighted analysis supports this suggestion (Fig. 2). In particular, we observe two well-supported clades that agree with the previous analysis with a much larger sample size of E. fulvus specimens in Wyner et al. (1999). E. f. collaris and E. f. albocollaris form a well-supported clade and are rather well differentiated from each other, but the other E. fulvus subspecies do not form distinct sister pairings. The remaining four subspecies (E. f. albifrons, E. f. sanfordi, E. f. fulvus, and E. f. rufus) form a strong monophyletic group (Bremer support of 5 and 86% bootstrap support) that is sister to the E. f. albocollaris–E. f. collaris pair (Bremer support of 8 and 94% bootstrap support). As in other molecular-based studies, L. catta and Hapalemur are observed with high

FIG. 1. Parsimony trees for three ‘‘extreme’’ weighting schemes of the reduced taxon data set. TV parsimony and 3rd position parsimony gave a single tree while the equal weighting tree is a consensus of two trees. Nodes are numbered 1–8 for the eight nodes that are common in all three trees. Nodes a and b are problematic in all three trees. Bremer support is given above the line and bootstrap proportion is given below the line. The maximum-likelihood topology discussed in the text is identical to the equally weighted parsimony tree shown in this figure. The equally weighted tree, although shown fully resolved here, is one of two equally parsimonious trees. A consensus of these two equally weighted parsimony trees would collapse node b to give an unresolved trichotomy for E. fulvus, E. macaco, and E. rubriventer. Tree statistics are Equal Weighted, Steps ⫽ 1467, CI ⫽ 0.58, RI ⫽ 0.59; 3rd Position Parsimony, Steps ⫽ 938, CI ⫽ 0.63, RI ⫽ 0.62; and TV Parsimony, Steps ⫽ 508, CI ⫽ 0.66, RI ⫽ 0.73.

PHYLOGENY OF LEMURIDAE

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FIG. 2. Parsimony trees for the three ‘‘extreme’’ weighting schemes of the expanded taxon sampling data set. Taxon designations are as in Table 1. Nodes are numbered in four classes. Lower-case Roman numerals indicate nodes relevant to subspecies classification. Lower-case letters indicate nodes where species designations are relevant. Upper-case letters indicate nodes that have been strongly supported in other studies while upper-case Roman numerals indicate problematic nodes in other studies. All trees are labeled with Bremer support and bootstrap proportions. Bremer support is given above the line and bootstrap proportion is given below the line for the equal weighting tree. For the TV parsimony tree and the 3rd position parsimony tree, Bremer support is listed before the slash and bootstrap proportion is listed after the slash. Tree statistics are Equal Weighted, Steps ⫽ 984, CI ⫽ 0.61, RI ⫽ 0.76; 3rd Position Parsimony, Steps ⫽ 841, CI ⫽ 0.63, RI ⫽ 0.77; and TV Parsimony, Steps ⫽ 428, CI ⫽ 0.67, RI ⫽ 0.83.

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support (Bremer support of 10 and 95% bootstrap support) as sister taxa. In addition, this pair is strongly supported as the sister group to the genus Eulemur. The two Varecia subspecies are, not surprisingly, observed as monophyletic in all analyses but are also strongly supported as the most basal ingroup taxon (Bremer support of 13 and 100% bootstrap support) in all parsimony analyses. Likelihood analyses recovered one of the two parsimony trees (Fig. 1). This tree is identical to the equally weighted tree in Fig. 1 but also places E. rubriventer as sister to E. macaco, which is an unresolved node in the equally weighted parsimony analysis. All likelihood models (JC, K2P, F84, and GTR), whether or not site-specific rate heterogeneity was incorporated into the model, recovered this single topology. It should be noted that the poorly supported nodes in our analysis are also the nodes that Yoder and Irwin (1999) observed as problematic. In particular, Yoder and Irwin (1999) recognized that the placement of E. rubriventer and E. mongoz was problematic in both parsimony analysis and maximum-likelihood analysis. Molecules and Morphology We first examined the degree of congruence between morphology and various molecular character partitions. Table 4 shows the results of using the ILD test of Farris et al. (1994, 1995) as implemented in the partition homogeneity test in PAUP. In all comparisons, regardless of weighting scheme or data matrix (reduced matrix or expanded matrix), significant incongruence between the morphological partition and the molecular partition could not be detected, indicating that morphological characters are in general congruent with molecular characters. In addition, the ILD measures are all uniformly about 1% (except for comparisons of nuclear partitions with morphology, which are 5%), indicating that there is an increase of only 1% in tree length in the simultaneous analysis tree due to combining the morphological data with the molecular data (Mickevich and Farris, 1981). We conclude that although the morphological tree (Stanger-Hall, 1997) is topologically different from TABLE 4 ILD Values and Tests for Significant Incongruence

Reduced matrix Equal TV pars. 3rd pos. pars. Full matrix Equal TV pars. 3rd pos. pars.

Mt vs Nuc

Mt vs Mor

Nuc vs Mor

Mol vs Mor

0.003 0.005 0.005

0.005 0.011 0.008

0.010 0.011 0.010

0.004 0.011 0.006

0.010 0.009 0.011

0.009 0.013 0.024

0.050 0.051 0.051

0.006 0.006 0.012

Note. Abbreviations: Mt, mitochondrial partition; Nuc, nuclear gene partition; Mor, morphological partition; Mol, total molecular partition. None of the values in this table are statistically significant.

TABLE 5 Distribution of Partitioned Bremer Support Values for the Three Weighting Schemes Employed in This Paper for the Reduced Matrix Node Weighting scheme

1

Equal COII 5 cyt-b 0 12S 1 d-loop 1 casein 0 IRBP 0 Morph 0 Transversion parsimony COII 0 cyt-b 0 12S 0 d-loop 2 casein 0 IRBP 0 Morph 1 Third positions removed COII 0 cyt-b 0 12S 1 d-loop 1 casein 0 IRBP ⫺1 Morph 1

2

3

4

5

6

6 18 2 0 1 8 ⫺2 ⫺3 1 12 0 1 3 1 3 ⫺1 3 11 14 4 3 1 0 1 0 ⫺1 3 3 ⫺1 1 2 2 ⫺1 ⫺3 2 2 0 3 0 0 1

7

8

a

24 3 5 8 3 5 8 1 0 20 4 ⫺4 11 ⫺2 0 14 ⫺1 0 1 0 0

b

0 0 0 0 0 0 0

Tot PI

58 180 32 55 18 26 52 119 14 25 17 33 2 11

8 1 3 7 6 0 ⫺1 ⫺1 25 162 0 1 0 8 0 0 0 0 11 48 0 1 0 3 2 0 ⫺1 ⫺1 5 23 1 6 8 3 10 5 3 3 44 104 0 0 1 0 4 ⫺1 0 0 4 25 1 2 ⫺1 0 5 0 0 0 7 31 2 ⫺2 0 ⫺1 1 0 0 0 2 11

0 5 ⫺1 ⫺1 ⫺1 1 1 ⫺1 0 8 ⫺1 2 4 1 4 7 ⫺2 8 9 2 0 1 ⫺2 1 0 ⫺1 4 4 0 1 1 2 2 0 ⫺3

8 1 0 ⫺2 9 36 9 0 0 ⫺1 17 17 10 1 1 0 23 26 19 4 ⫺1 4 51 119 11 ⫺2 0 0 9 25 1 ⫺1 1 0 8 33 ⫺2 0 0 0 1 11

Note. Last column (PI) lists phylogenetically informative sites. Nodes are as numbered in Fig. 1. Numbered nodes are those that exist in all three trees in Fig. 1. Nodes a and b are the two nodes that change from weighting scheme to weighting scheme. cyt-b, cytochrome b partition; 12S, 12S rDNA partition; d-loop, control region partition; casein, casein kinase II intron partition.

the simultaneous analysis tree that we report here, there are too few characters in the morphological matrix to show significant conflict with the molecular characters. An examination of the level of support of morphological characters on the simultaneous analysis tree can be accomplished using the partitioned Bremer support (PBS) of Baker and DeSalle (1997). This method allows one to apportion the total Bremer support for individual nodes to the various data partitions that exist in a matrix. We calculated PBS for all nodes in the reduced data set analysis for all three weighting schemes and for the equally weighted analysis in the expanded taxon sampling matrix (reduced analysis in Table 5; expanded analysis in Table 6). These analyses demonstrate the small but overall positive contribution of the morphological characters to the simultaneous analysis and also point to several nodes (those with negative PBS values) where the morphological characters are at odds with the simultaneous analysis. When the larger taxon sampling matrix is used in phylogenetic analysis, the effect of morphology on the

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TABLE 6 Distribution of the Partitioned Bremer Support Values for the Equally Weighted Analysis of the Expanded Matrix Node

cyt-b

12S

d-loop

casein

Morph

ii iii iv v vi vii vii a b c d e f g h i j k A B C D E I II III PI

5 0 ⫺1.7 ⫺2 ⫺0.5 2 1 1 ⫺2 2.5 2 7 0 0 13 9 19 2.5 ⫺2.5 ⫺2 ⫺2 1 2 4 ⫺1 4 76

0 0 0 0 0 1 2 0 1 0 0 5 5 7 3 8 11 1.5 4.5 3 2 1 1 1 0 1 38

4.5 0.5 6.7 3 0.5 4 6 6 4 3 3 3 3 7 6 17 26 0.7 0 9 3 10 2 0 2.5 ⫺4 146

0 0.5 0 0 0 ⫺1 0 1 0 0.5 1 5 0 9 ⫺2 12 0 0.3 0 2 3 1 1 0 0.5 0 46

0 0 0 0 0 0 0 1 1 0 0 3 2 2 3 1 2 0 0 ⫺2 2 0 0 0 0 0 18

Note. Last row (PI) indicates number of phylogenetically informative sites for the different data partitions. Nodes are numbered as in Fig. 2. Lowercase Roman numerals indicate nodes relevant to subspecies classification. Lower-case letters indicate nodes where species designations are relevant. Uppercase letters indicate nodes that have been strongly supported in other studies. Upper-case Roman numerals indicate problematic nodes in other studies. cyt-b, cytochrome b partition; 12S, 12S rDNA partition; d-loop, control region partition; casein, casein kinase II intron partition; Morph, morphological partition.

simultaneous analysis tree increases (Table 6). This increase occurs as a result of adding exemplars of morphologically distinct taxa for which the morphological data add strongly to the phylogenetic inference for the nodes defining that taxon (note that all nodes in the a–k class of nodes in Table 6 are positive or zero). In the reduced taxon analysis, morphology contributes between 1 and 2% of the total Bremer support while in the expanded taxon analysis the morphological contribution to the total Bremer support for the tree is 6%. Character Behavior in Simultaneous Analysis We chose two approaches to examining character change and support in a simultaneous analysis framework. First, we examined character support change related to weighting scheme using the reduced data matrix. In this analysis we examine the degree of

support that each data partition imparts to the simultaneous analysis tree as a function of weighting. We also examine the degree of support that problematic nodes have as a function of weighting. This latter approach is helpful in determining which character partitions and which weighting schemes impart the greatest character support for certain nodes. Second, we examined character support at different taxonomic levels using the expanded data matrix. This analysis allows us to determine the source of character support at different taxonomic levels and might also allow us to assess which character partitions or kinds of character partitions would address further phylogenetic hypothesis testing in this family of primates. Since character weighting has been suggested as an important element in resolving the relationships of taxa in the family (Stanger-Hall and Cunningham, 1997; Yoder and Irwin, 1999), we decided to examine the behavior of characters in the simultaneous analysis trees for the reduced taxon data set. We used the PBS at each node for the seven partitions to examine the effect of different weighting schemes on character support at these nodes (Table 5). This analysis demonstrates that substantial decrease in support occurs for all character partitions, except for the d-loop partition, when transversion parsimony and third positions are removed from the analysis. Total support for the simultaneous analysis hypothesis for all other character partitions drops when the transversion parsimony and third position removal weighting schemes are imposed. This result is not surprising, as these kinds of weighting schemes reduce the number of characters in an analysis. In addition to the drop in total support for these well-corroborated nodes, the problematic nodes identified in Yoder and Irwin (1999) are also affected by character weighting. In particular, nodes a and b (in Fig. 1) show very low support after implementation of transversion parsimony and removal of third positions, whereas in equal weighting one problematic node (a in the equal weighted tree in Fig. 1) is observed as strongly supported and the other (b in the equal weighted tree in Fig. 1) has no total Bremer support (Fig. 1) nor Bremer support for any of the individual partitions (Table 5). Likewise, in the expanded analysis, transversion parsimony and removal of third positions weakens problematic nodes further (Fig. 2). It is also important to discuss the effect of likelihood analysis on these data. The ML approach gave a fully resolved tree with which the equally weighted parsimony consensus tree is consistent. In fact, the ML tree is identical to one of the two parsimony trees (Fig. 1). The likelihood approach in the present case simply chooses among one of the equally weighted parsimony trees and resolves relationships among E. rubriventer, E. macaco, and E. fulvus. As we discuss later, we feel that although resolving this node in a robust manner is probably the last remaining task in establishing the

PHYLOGENY OF LEMURIDAE

systematics of these taxa, a more reasonable solution to the problem is to focus efforts on collecting more character data. The expanded analysis (Table 6) shows that character support for diagnosis of well-supported taxa is high in all five character partitions. It appears that d-loop contributes greatest to these nodes, followed by cyt-b, 12S, casein kinase II, and morphology in that order (nodes a–k in Table 6). We have divided the rest of the nodes in Fig. 2 into three further classes: nodes that have been described as well supported in other studies (A–E in Table 6), nodes that involve subspecies designations (nodes ii–viii in Table 6), and nodes that have been earmarked as problematic in other studies as well as in our reduced analysis (i.e., nodes a and b in Fig. 1). The dynamics of support for the first type of nodes indicate that cyt-b actually disagrees with the simultaneous analysis inferences for these nodes (A–E in Table 6) in that several of the PBS values for cyt-b are negative. D-loop and 12S contribute strongly and consistently to the robustness of these nodes, as does the nuclear gene partition casein kinase II. The subspecies nodes (ii–viii in Table 6) are defined mostly on the basis of the information from the d-loop partition. The cyt-b partition actually contributes negatively to this class of nodes. 12S, casein kinase II, and morphology have very little to contribute to these nodes. The three problematic nodes (I–III in Table 6) are short internodes at intermediate taxonomic levels that define relationships among species or species pairs. Two partitions are involved in imparting support to these nodes (cyt-b and d-loop). These two partitions seem to conflict with one another at nodes II and III, as one partition is negative and the other positive for PBS at these nodes. DISCUSSION Phylogenetic Considerations There has been significant debate concerning the systematics of the lemurid family (Tattersall and Schwartz, 1974, 1991; Eaglen, 1983; Groves and Eaglen, 1988; Simons and Rumpler, 1988). Older classifications (Hill, 1953; Napier and Napier, 1967; Simpson, 1945; Szalay and Delson, 1979) placed four currently recognized genera (Lemur, Varecia, Hapalemur, and Lepilemur) in the family Lemuridae. The genus Lepilemur has since been recognized as separate from the family Lemuridae. It has alternately been placed in its own family, Lepilemuridae, or in the family Megalapidae along with some lemur subfossils (Schwartz and Tattersall, 1985). Simons and Rumpler (1988) named a new genus, Eulemur, to classify all the species, except for L. catta, that were formerly in the genus Lemur (E. mongoz, E. fulvus, E. macaco, E. coronatus, and E. rubriventer), since L. catta, the type species for the lemur genus, shares more affinities with Hapalemur than it does with the other species previously classified

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in the genus Lemur. Subsequent chromosomal, behavioral, and molecular analyses have provided further support for the phylogenetic affinities of the species in the genus Eulemur to each other and of the sister relationship of Hapalemur to Lemur (Crovella and Rumpler, 1992; Del Pero et al., 1995; Crovella et al., 1993; Macedonia and Stanger, 1994; Yoder et al., 1996). Morphological studies of these primates as well as other Lemuriformes by Tattersall and Schwartz (1974, 1991), Schwartz and Tattersall (1985), Groves and Eaglen (1988), Macedonia and Stanger (1994), and Yoder (1994) prompted Stanger-Hall (1997) to reexamine the morphological information for these taxa. We have followed Stanger-Hall’s (1997) report and used the morphological data matrix that she generated for the morphological information in the present study. Stanger-Hall (1997) reduced the character data present for these primates to 25 reliably scoreable morphological characters. In the current study we expanded the taxonomic sampling to include E. coronatus and at least two representatives of each species in the family. We constructed two matrices to examine phylogeny in this family and in general the results of analyzing these two matrices agree well with each other. As with some recent molecular studies on lemurs, certain nodes in our analyses are either unresolved or weakly supported. The various molecular studies that have emerged in the past 3 years (Stanger-Hall and Cunningham, 1997; Yoder et al., 1996b; Yoder and Irwin, 1999) agree on several things: (1) Hapalemur and L. catta are strongly supported as sister taxa; (2) Varecia is the most basal genus in the family; (3) E. fulvus subspecies form a monophyletic group; (4) E. macaco subspecies form a monophyletic group; and (5) nodes defining relationships of E. macaco, E. mongoz, E. fulvus, and E. rubriventer are problematic. In the present study using the expanded taxon data matrix, we also show affinity for E. coronatus and E. macaco as a sister pair in all analyses, except for transversion parsimony. There is a topological discrepancy between the morphological inferences and our analysis. However, our analysis of the congruence of morphology and molecules suggests that there is no significant incongruence among molecules and morphology using the Stanger-Hall (1997) character matrix to contrast with molecular characters. This lack of significant incongruence may be the result of the reduction of the number of morphological characters that are relevant to the relationships of the primates in the present study. Given our simultaneous analysis, we suggest that more morphological characters need to be collected to bear upon the phylogenetic questions that are relevant to this family. In particular, some of the old characters that were originally studied by Tattersall and Schwartz (1974, 1991) and used for defining relationships among

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species in the genus Eulemur might be reconsidered. New morphological characters should focus on differences relevant to these species. Character Behavior in Simultaneous Analysis To understand the agreement of phylogenetic signal from different sources of information, data can be used to test levels of congruence between partitions. Several authors have presented a number of approaches for understanding incongruence between data partitions. Some authors support analyzing different data partitions separately to maximize the phylogenetic signal apparent from each data set and then uniting all trees into one consensus tree (Miyamoto and Fitch, 1995). Others support devising models to minimize apparent incongruence between data sets, while maximizing phylogenetic signal (Cunningham, 1997; Cunningham et al., 1998). Still other approaches suggest that congruence of data partitions should be a criterion for their combination in simultaneous analysis (Bull et al., 1993; deQuiroz et al., 1995). Finally, others support combining all data partitions into one analysis, but determining at exactly which nodes incongruence is greatest using measures such as partitioned Bremer support (Nixon and Carpenter, 1995; Brower et al., 1996; Baker and DeSalle, 1997). This debate is far from over, but in order to make inferences about groups of organisms, a framework for analysis must be adopted. In the present study we have adopted the simultaneous analysis framework that allows us to examine character support in reference to a simultaneous analysis tree for each data partition. We have also attempted to examine a range of character weighting approaches to examine the effect of assumptions of DNA sequence evolution (removal of third positions in codons and transversion parsimony) on phylogenetic inference and the behavior of characters. Previous studies of Lemuriformes systematics have found a high degree of incongruence between codon positions of two mitochondrial genes, cyt-b and COII (Yoder et al., 1996a; Adkins and Honeycutt, 1994). More recently, molecular characters have been used to approach questions of phylogeny in the Lemuridae. Stanger-Hall and Cunningham (1997), Yoder et al. (1996b), and Yoder and Irwin (1999) have reported on molecular data sets relevant to the phylogeny of the Lemuridae. Most of the discussion around these molecular studies concerns the incongruence of characters used to infer phylogeny and the related subject of character weighting. Stanger-Hall and Cunningham (1997) were interested in the relationships of the various genera in the family Lemuridae, while Yoder and Irwin (1999) focused on the species-level relationships within Eulemur, as well as the generic relationships within the family. Both studies demonstrated problems with resolution at particular nodes in the phylogeny.

It has been suggested that resolution of problematic nodes in molecular studies of the Lemuridae (StangerHall and Cunningham, 1997; Yoder and Irwin, 1999) comes down to a question of character weighting and data treatment. In particular, different character weighting schemes recover different topologies for these problematic nodes. Other forms of data analysis such as maximum likelihood recover topologies that are relevant to the same problems of resolution. Yoder and Irwin (1999) used ML to examine the reduced taxon data set and found that inferences around the nodes that define relationships among E. mongoz, E. macaco, E. rubriventer, and E. fulvus are weak. In the present study, ML gives a fully resolved and reasonable inference about these problematic taxa and one with which the parsimony analysis is consistent. However, when we consider the ML inference in the context of character support in a simultaneous analysis, we see that ML resolves a node with no support (total or partitioned) in the parsimony analysis. The taxa in question probably diverged very rapidly, leaving behind a series of divergence events that are extremely difficult to determine. The real question here is whether ML can be used to resolve polytomies at which the parsimony information is neutral or weak. We suggest that a more reasonable solution to the systematic questions in this group is to collect more character data rather than relying on a model of sequence change to resolve this problematic node. We further suggest that equal weighting may be an important consideration for this systematic problem, as this form of weighting recovered high support for E. mongoz as the most basal Eulemur taxon, where all other weighting schemes showed low levels of support for any other hypothesis. CONCLUSIONS The present study strongly supports previous molecular hypotheses of relationships for species in this family of primates. In particular, Varecia is strongly supported as basal in the family. Hapalemur and L. catta are strongly supported as sister taxa and together are the sister group to the genus Eulemur. E. fulvus subspecies form a monophyletic group with three distinct lineages (see also Wyner et al., 1999). E. coronatus is strongly supported in all equal weighting analyses as the sister taxon to E. macaco. Support for the placement of E. rubriventer and E. mongoz is weak, but the current analysis suggests that E. mongoz is the most basal member of the genus Eulemur. Our analysis combined molecular and morphological data but demonstrates the lack of influence that morphology has on simultaneous analysis when these two kinds of data are given equal weight. Another issue that can be addressed with the present analysis is what new character partitions should be appended to the present analysis to further test hypoth-

PHYLOGENY OF LEMURIDAE

eses of relationships in this group? More specifically, what character partitions might be added to resolve the problematic nodes that are present in the current analysis? It appears that adding noncoding regions of nuclear genes such as IRBP and casein kinase II do not improve the resolution at these problematic nodes. It is clear that the d-loop partition contributes a great amount of information to the current analysis. Nuclear gene regions that approximate the same dynamics of sequence change as d-loop, such as intron regions that are more rapidly evolving than the ones that have already been sequenced, might be useful. In addition, reconsideration of morphological characters, as well as further examination of morphology, will be essential in unraveling the relationships among the taxa in the genus Eulemur. ACKNOWLEDGMENTS We thank Rebecca Stumpf for E. f. albocollaris and Hapalemur simus samples. Yael Wyner is supported by an NSF Predoctoral Fellowship. This is Duke University Primate Center Publication number 713.

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