Abstract

Phylogenetic relationships within marsupials were investigated based on a 20.1-kilobase molecular supermatrix comprising 7 nuclear and 15 mitochondrial genes analyzed using both maximum likelihood and Bayesian approaches and 3 different partitioning strategies. The study revealed that base composition bias in the 3rd codon positions of mitochondrial genes misled even the partitioned maximum-likelihood analyses, whereas Bayesian analyses were less affected. After correcting for base composition bias, monophyly of the currently recognized marsupial orders, of Australidelphia, and of a clade comprising Dasyuromorphia, Notoryctes, and Peramelemorphia, were supported strongly by both Bayesian posterior probabilities and maximum-likelihood bootstrap values. Monophyly of the Australasian marsupials, of Notoryctes + Dasyuromorphia, and of Caenolestes + Australidelphia were less well supported. Within Diprotodontia, Burramyidae + Phalangeridae received relatively strong support. Divergence dates calculated using a Bayesian relaxed molecular clock and multiple age constraints suggested at least 3 independent dispersals of marsupials from North to South America during the Late Cretaceous or early Paleocene. Within the Australasian clade, the macropodine radiation, the divergence of phascogaline and dasyurine dasyurids, and the divergence of perameline and peroryctine peramelemorphians all coincided with periods of significant environmental change during the Miocene. An analysis of “unrepresented basal branch lengths” suggests that the fossil record is particularly poor for didelphids and most groups within the Australasian radiation.

Molecular analyses of the higher-level phylogeny of marsupials have a long history (Nuttall 1904; Weymss 1953) and have been more common than equivalent morphological studies. Several of these molecular analyses have added considerably to our current understanding of marsupial phylogeny and classification (e.g., Kirsch 1968, 1977; Sarich et al. 1982). However, even with recent advances in sequencing and phylogenetic methods, different molecular data sets continue to support incon-gruent topologies (e.g., Amrine-Madsen et al. 2003; Asher et al. 2004; Baker et al. 2004; Nilsson et al. 2004); hence, the higher-level phylogeny of marsupials remains uncertain.

The affinities of several marsupial groups have proven particularly difficult to resolve. It is unclear whether the South American didelphid opossums (Didelphimorphia) and caenolestid shrew opossums (Paucituberculata) comprise a monophyletic group (Ameridelphia) or are a paraphyletic assemblage at the base of modern marsupials. Current evidence supports the monophyly of Australidelphia (Amrine-Madsen et al. 2003; Cardillo et al. 2004; Horovitz and Sanchez-Villagra 2003; Szalay 1982, 1994), a clade comprising the modern Australasian marsupial orders Peramelemorphia, Notoryctemorphia, Dasyuromorphia, and Diprotodontia and the South American monito del monte Dromiciops (Microbiotheria). The position of Dromiciops within Australidelphia remains unresolved and yet is crucial to our understanding of marsupial biogeography: if Dromiciops is the sister group to all Australasian marsupials (Amrine-Madsen et al. 2003; Phillips et al. 2006), then only a single dispersal of marsupials from South America to Australasia is implied; if Dromiciops is nested within the Australasian radiation (Asher et al. 2004; Cardillo et al. 2004; Nilsson et al. 2004), there must have been multiple dispersals of marsupials to Australasia or back-migration of microbiotheres from Australasia to South America. Within Australasian marsupials, the affinities of the highly autapomorphic, fossorial marsupial mole Notoryctes (Notoryctemorphia) are uncertain, as are those of the bandicoots (Peramelemorphia), with some studies (e.g., Kirsch et al. 1997) suggesting that the latter may not be members of Australidelphia.

Together with a robust phylogeny, divergence dates are essential for understanding the patterns, processes, and tempo of marsupial evolution and biogeography. For example, they enable assessment of whether divergences coincided with periods of environmental change, such as climatic variations (e.g., Delsuc et al. 2004; Douady and Douzery 2003) and fluctuations in sea level (Johnson et al. 2006; Mercer and Roth 2003). However, robust dates for divergences within Marsupialia have been unavailable because of incompleteness of the fossil record, notably a lack of sites from the Late Cretaceous and early Tertiary when most of the deep divergences are thought to have occurred.

Late Cretaceous marsupials from North America were relatively diverse and include taxa that have been tentatively assigned to extant lineages by some authors (Case et al. 2005; Kielan-Jaworowska et al. 2004), but they are known only from fragmentary material (largely isolated teeth) and their relationships to the marsupial crown-group remain controversial. In South America, there are no Late Cretaceous fossil sites containing marsupials; the oldest known South American marsupial is a single tooth from the earliest Paleocene (Goin et al. 2006). The Tiupampa fauna in Bolivia (Marshall and Muizon 1988; Muizon 1991) contains exceptionally well-preserved, articulated skeletons of several plesiomorphic marsupials, as well as more fragmentary remains of several other marsupial taxa. However, the Tiupampa fauna may be somewhat younger than usually assumed (Benton and Donoghue 2007; Gradstein et al. 2004), being middle (59.2–60.4 million years ago [mya]) rather than early (63–64.5 mya) Paleocene. In Australia, there is only a single mammalian fauna from the early Tertiary (the early Eocene [54.6 mya] Tingamarra fauna—Godthelp et al. 1992), and marsupial fossils from this site are highly fragmentary. The next oldest Australian sites contain diverse and often well-preserved marsupial fossils, but are some 30 million years younger (late Oligocene—Archer et al. 1999; Long et al. 2002). Attempts to determine divergence dates from fossil evidence also may be confounded by the existence of “phylogenetic fuses” (Cooper and Fortey 1998): morphological apomorphies that distinguish 2 lineages may not have evolved until a considerable time after those lineages diverged.

These factors suggest that molecular methods, which are not strictly tied to the known fossil record (although they do usually require fossils to act as calibration points), seem more likely to provide accurate divergence dates. However, previous molecular dates for marsupials have been based on dubious assumptions, such as rate homogeneity or the use of a single (often questionable) fossil calibration. Indeed, in a number of instances, molecular dates for particular marsupial clades have been considerably younger than their oldest fossil members (e.g., Nilsson et al. 2004; Sarich et al. 1982), assuming, of course, that these fossils have been correctly identified.

In an attempt to resolve these problems, I have combined molecular data from 3 recent phylogenetic analyses of marsupials (Amrine-Madsen et al. 2003; Asher et al. 2004; Nilsson et al. 2004) to produce a supermatrix of 7 nuclear and 15 mitochondrial genes. This is, to my knowledge, the largest molecular data set used so far to investigate higher-level marsupial relationships, and it is the 1st to use a Bayesian relaxed molecular clock approach to calculate divergence dates between the major groups of marsupials.

Materials and Methods

Initial data set.—Sequence data were taken from the following studies: Amrine-Madsen et al. (2003; matrix supplied by M. Springer), who sampled the nuclear genes apolipoprotein B (APOB), breast cancer 1 (BRCA1), interphotoreceptor retinoid binding-protein (IRBP), recombination activating gene 1 (RAG1), and Von Willebrand factor (VWF); Asher et al. (2004; matrix downloaded from doi:10.1016/j.ympev.2004. 05.004), who sampled the nuclear genes IRBP, phosphoglycerate kinase 1 (PGK1), and protamine 1 (P1) and the mitochondrial genes cytochrome b (CYTB), 12S rRNA, 16S rRNA, tRNA valine, and reduced nicotinamide adenine dinucleotide dehydrogenase 2 (NADH2); and Nilsson et al. (2004; matrix supplied by M. Nilsson), who sampled the 12 mitochondrial H-strand protein-coding genes. The original alignments of all 3 matrices were maintained; for the data set of Asher et al. (2004), the original authors’ static alignment produced by the program CLUSTAL was preferred over any of their direct-optimization alignments produced by the program POY (De Laet and Wheeler 2003). Portions of the matrix of Asher et al. (2004) that overlapped with those of the other 2 studies (i.e., IRBP, CYTB, and NADH2) were deleted, because taxon sampling was sparser in the former study. In total, sequences from 7 nuclear genes (APOB, BRCA1, IRBP, PGK1, P1, RAG1, and VWF) and 15 mitochondrial loci (12S rRNA, 16S rRNA, tRNA valine, and the 12 H-strand protein-coding genes) were included in this study (Appendix I). The “Macropodinae” terminal of Amrine-Madsen et al. (2003) was decomposed into separate Macropus and Dendrolagus sequences and combined with sequences for these 2 genera from the other 2 studies. Sequences of 3 genes, P1, CYTB, and 12S rRNA, for the thylacine Thylacinus were downloaded from GenBank and added manually to the alignment. In total, 22 marsupial ingroup taxa were included, with 2 monotreme (Ornithorhynchus and Tachyglossus) and 2 placental (Eulipotyphla and Xenarthra) outgroups. Five of the marsupial taxa comprised sequences from more than 1 genus: Didelphini (Didelphis and Lutreolina), Peramelinae (Perameles and Isoodon), Petauridae (Petaurus and Dactylopsila), Phascogalinae (Phascogale and Antechinus), and Pseudocheiridae (Pseudocheirus and Pseudochirops).

Choice of taxa for this study essentially replicates that of Asher et al. (2004). Some taxa suffer from relatively large amounts of missing data (notably Dasyuroides and Thylacinus, which are represented by only 2 and 3 genes, respectively), but all share at least 1 nuclear (P1) and 1 mitochondrial (12S rRNA) gene in common, thus avoiding the problem of non-overlapping sequences identified by Springer et al. (2004). The supermatrix also can be easily combined with the morphological data set of Horovitz and Sanchez-Villagra (2003) for total evidence analyses. Because recent work by Phillips et al. (2006) suggests that base composition bias might not be accounted for by current likelihood models, 2 versions of the supermatrix were analyzed, 1 including 3rd codon positions of mitochondrial protein-coding genes (“full”; 20,121 base pairs [bp]) and 1 that excludes them (“no mt3”; 16,662 bp).

Data partitioning.—Three different partitioning strategies were applied to both the full and no mt3 data sets: a single partition for the entire supermatrix (“unpartitioned”); each gene assigned its own partition (“gene-partitioned”); and each codon position within each protein-coding gene and stems and loops within each ribosomal gene assigned their own partitions (“genes, codons, stems, loops [GCSL]-partitioned”). In the GCSL-partitioned analyses, the 250-bp noncoding region of P1 identified by Queralt et al. (1995; see also Asher et al. 2004) also was assigned its own partition, and stem and loop regions of the ribosomal genes were defined using secondary structure masks from the Organellar Genome Retrieval (OGRe) database (Jameson et al. 2003). The 12 mitochondrial protein-coding genes were treated as a single supergene (which was further partitioned by codon position in the GCSL-partitioned analyses), rather than individual genes to avoid a very large number of partitions. Too many partitions risk overparameterization and greatly increase computation time and difficulty in reaching convergence in Bayesian analyses. Furthermore, base composition does not vary significantly among the 12 mitochondrial protein-coding genes (Nilsson 2006), so it seems reasonable to treat them as a single supergene.

Phylogenetic analysis.—Maximum-likelihood analyses were carried out using RAxML VI (Stamatakis 2006), which can implement partitioned analysis by applying 1 of 2 models to each partition: GTRGAMMA (general time reversible model with rate heterogeneity accommodated by a gamma distribution) or GTRCAT (as for GTRGAMMA, but rate heterogeneity is accommodated by a number of discrete rate categories). To maximize computational efficiency, the GTRMIX option of RAxML was used; this assumes the GTRCAT model (which is faster and less memory intensive than GTRGAMMA) when searching for tree topologies, but assumes the GTRGAMMA model when calculating the likelihood score of each topology. The RAxML analyses each comprised 100 tree search replicates (assuming default parameters) and were implemented using the perl script batchRAxML.

Bayesian analyses used MrBayes 3.1.2 (Ronquist and Huelsenbeck 2003), which, unlike RAxML, allows specification of 1 of a wide range of models for each partition. Models for the Bayesian analyses were identified using the model selection program MrModeltest 2.2 (Nylander 2004), and models preferred by the Akaike information criterion were implemented (following Posada and Buckley [2004]; a list of models used for each partition is available from the author). For the MrBayes analyses, all parameters except topology were unlinked across partitions, and 2 independent runs (each comprising 1 “cold” and 3 “heated” chains) were run simultaneously, with trees sampled every 100th generation. The MrBayes analyses were run for either 1 × 106 (unpartitioned), 2.5 × 106 (gene-partitioned), or 12 × 106 (GCSL-partitioned) generations for both the full and no mt3 data sets. In all cases, stationarity had been reached by the end of the analysis (average standard deviation of split frequencies <0.01). Majority-rule consensus trees were constructed, with a burn-in period of either 1 × 105 (unpartitioned), 2.5 × 105 (gene-partitioned), or 10 × 106 (GCSL-partitioned) generations excluded. Bayes factors (Nylander et al. 2004), calculated as 2 times the difference in the harmonic means of the log likelihoods of the post–burn-in trees (obtained using the “sump” command in MrBayes), were examined to investigate whether particular partitioning schemes show a better fit to the data than do others.

Support values.—Support for different clades was calculated by 1,000 bootstrap replicates for the maximum-likelihood analyses (again using RAxML and batchRAxML together with the perl script bootStrip), and by posterior probabilities for the Bayesian analyses. Studies indicate that posterior probabilities may be misleadingly high, whereas bootstrap values are more conservative (Suzuki et al. 2002; Taylor and Piel 2004). However, Hall and Salipante (2007) have argued recently that neither measure reflects the probability of a particular clade. Statistical tests of alternative topologies may therefore be more informative than either of these support measures (Shimodaira and Hasegawa 1999).

Testing alternative topologies.—The different topologies found in the various analyses, as well as a number of others taken from other studies, were tested using the approximately unbiased (AU—Shimodaira 2002) and Kishino–Hasegawa (KH—Kishino and Hasegawa 1989) tests as implemented in CONSEL (Shimodaira and Hasegawa 2001). Both the full and no mt3 data sets were used for these tests. PAUP* version 4.0b10 (Swofford 2002) was used to calculate the site likelihoods for each of the test topologies, with the GCSL-partitioning scheme assumed and the appropriate model for each partition specified using the output from MrModeltest 2.2. The CONSEL analyses employed 10 batches of 1 × 105 bootstrap replicates and 1 of 1 × 106 bootstrap replicates.

Molecular dating analysis.—A Bayesian relaxed molecular clock method was used, as implemented by the program Multidivtime (Kishino et al. 2001; Thorne et al. 1998). General methodology follows Rutschmann (2005; see also Inoue et al. 2005), with a single F84 + gamma model applied to the entire supermatrix (incomplete overlap of sequences prevented a separate model being applied to each partition) and maximum-likelihood parameters estimated under PAML version 3.15 (Yang 1997). Because a partitioned approach could not be implemented in Multidivtime, only the no mt3 data set (which excludes a partition with a known base composition bias) was used for the calculation of dates. Following Benton and Donoghue (2007), a high number of constraints was specified (23 minima and 3 maxima) and a conservative approach was used when assigning dates: if based on absolute (radiometric) dating, dates were assumed to be the lower end of the 95% confidence interval (95% CI), where given; if based on relative (biostratigraphic) dating, dates were assumed to represent the lower bound, for example, late Oligocene was assumed to be the Oligocene–Miocene boundary. Ages of boundaries were taken from Gradstein et al. (2004). The root prior rttm (the mean of the prior distribution for the time from the ingroup root to the tips) was set at 162.5 mya (the age of the monotreme–therian split) following the arguments of Benton and Donoghue (2007). A full list of calibrations is given in Table 1. Other Multidivtime parameters were calculated as follows (following Rutschmann 2005): rtrate (mean of prior distribution for the rate at the root node) = X/rttm, where X is the median amount of evolution from the root to tips; rtratesd (standard deviation of rtrtate) = 0.5 × rtrate; brownmean (mean of the prior distribution for the autocorrelation parameter, v) = 1/rttm; and brownsd (standard deviation of brownmean) = 1/rttm. Three independent Multidivtime analyses were run for 1 × 106 cycles with samples taken every 100 cycles after a burn-in period of 1 × 105 cycles. The estimated dates for each node varied <1% across the 3 runs in all analyses indicating that stationarity had been reached; the dates presented here are mean values for the 3 runs.

Table 1

Minimum and maximum time constraints used in the Multidivtime dating analysis. Node numbers correspond to nodes in Figs. 3 and 4.

Node number Age (mya) Justification 
162.5 (root prior) Amphilestes broderipii and Phascolotherium bucklandi—oldest known theriiomorphs (Benton and Donoghue 2007
124.6 (minimum) Sinodelphys szalayi and Eomaia scansoria—oldest known metatherian (Luo et al. 2003) and eutherian (Ji et al. 2002), respectively 
124.6 (maximum) All splits within placental crown-group assumed to be younger than oldest known eutherian, Eomaia 
58.5 (minimum) Riostegotherium yanei—oldest known xenarthran (Rose et al. 2005
124.6 (maximum) All splits within marsupial crown-group assumed to be younger than oldest metatherian, Sinodelphys 
4a, 6a, 7a 59 (minimum) Khasia cordillerensis—oldest known microbiothere (Marshall and Muizon 1988
4b, 6b 58.5 (minimum) Oldest known tarsals with the apomorphic didelphimorphian proximal calcaneocuboid facet (Szalay 1994) and the oldest known paucituberculate (Oliveira et al. 1996
11.8 (minimum) Micoureus laventicus (Goin 1997)—Micoureus is more closely related to Monodelphis than Didelphis (Jansa and Voss 2005; Steiner et al. 2005
8c 71.2 (maximum) Apparent absence of marsupials from South America, and no evidence of australidelphians in North America 
7, 8, 9 23.03 (minimum) Oldest known Australasian marsupials referable to modern orders (Archer et al. 1999; Long et al. 2002
10 3.53 (minimum) Cf. Peroryctes sp.—oldest known peroryctids (Turnbull et al. 2003
11, 12 23.03 (minimum) Badjcinus turnbulli—oldest known thylacinid (Muirhead and Wroe 1998
13 4.45 (minimum) Antechinus sp.—oldest known phascogaline (Archer 1982; Turnbull et al. 2003
14 4.45 (minimum) Cf. Dasyurus sp.—oldest known Dasyurus (Turnbull et al. 2003
15 23.03 (minimum) Oldest known vombatiforms and phalangeridans (Archer et al. 1999; Long et al. 2002
16 23.03 (minimum) Oldest known koalas and vombatoids (Long et al. 2002
17 23.03 (minimum) Oldest known petauroids, burramyids, phalangerids, and macropodoids (Archer et al. 1999; Long et al. 2002
18 23.03 (minimum) Oldest known petaurids and pseudocheirids (Archer et al. 1999; Long et al. 2002
19 23.03 (minimum) Oldest known burramyids, phalangerids, and macropodoids (Archer et al. 1999; Long et al. 2002
20 4.45 (minimum) Dorcopsis wintercookorum—oldest known Dorcopsis (Flannery et al. 1992
21 4.45 (minimum) Thylogale ignis—oldest known Thylogale (Flannery et al. 1992
22 4.45 (minimum) Thylogale ignis—oldest known Thylogale (Flannery et al. 1992
23 23.03 (minimum) Oldest known burramyids and phalangerids (Archer et al. 1999; Long et al. 2002
24 23.03 (minimum) Oldest known trichosurin (Crosby 2004
Node number Age (mya) Justification 
162.5 (root prior) Amphilestes broderipii and Phascolotherium bucklandi—oldest known theriiomorphs (Benton and Donoghue 2007
124.6 (minimum) Sinodelphys szalayi and Eomaia scansoria—oldest known metatherian (Luo et al. 2003) and eutherian (Ji et al. 2002), respectively 
124.6 (maximum) All splits within placental crown-group assumed to be younger than oldest known eutherian, Eomaia 
58.5 (minimum) Riostegotherium yanei—oldest known xenarthran (Rose et al. 2005
124.6 (maximum) All splits within marsupial crown-group assumed to be younger than oldest metatherian, Sinodelphys 
4a, 6a, 7a 59 (minimum) Khasia cordillerensis—oldest known microbiothere (Marshall and Muizon 1988
4b, 6b 58.5 (minimum) Oldest known tarsals with the apomorphic didelphimorphian proximal calcaneocuboid facet (Szalay 1994) and the oldest known paucituberculate (Oliveira et al. 1996
11.8 (minimum) Micoureus laventicus (Goin 1997)—Micoureus is more closely related to Monodelphis than Didelphis (Jansa and Voss 2005; Steiner et al. 2005
8c 71.2 (maximum) Apparent absence of marsupials from South America, and no evidence of australidelphians in North America 
7, 8, 9 23.03 (minimum) Oldest known Australasian marsupials referable to modern orders (Archer et al. 1999; Long et al. 2002
10 3.53 (minimum) Cf. Peroryctes sp.—oldest known peroryctids (Turnbull et al. 2003
11, 12 23.03 (minimum) Badjcinus turnbulli—oldest known thylacinid (Muirhead and Wroe 1998
13 4.45 (minimum) Antechinus sp.—oldest known phascogaline (Archer 1982; Turnbull et al. 2003
14 4.45 (minimum) Cf. Dasyurus sp.—oldest known Dasyurus (Turnbull et al. 2003
15 23.03 (minimum) Oldest known vombatiforms and phalangeridans (Archer et al. 1999; Long et al. 2002
16 23.03 (minimum) Oldest known koalas and vombatoids (Long et al. 2002
17 23.03 (minimum) Oldest known petauroids, burramyids, phalangerids, and macropodoids (Archer et al. 1999; Long et al. 2002
18 23.03 (minimum) Oldest known petaurids and pseudocheirids (Archer et al. 1999; Long et al. 2002
19 23.03 (minimum) Oldest known burramyids, phalangerids, and macropodoids (Archer et al. 1999; Long et al. 2002
20 4.45 (minimum) Dorcopsis wintercookorum—oldest known Dorcopsis (Flannery et al. 1992
21 4.45 (minimum) Thylogale ignis—oldest known Thylogale (Flannery et al. 1992
22 4.45 (minimum) Thylogale ignis—oldest known Thylogale (Flannery et al. 1992
23 23.03 (minimum) Oldest known burramyids and phalangerids (Archer et al. 1999; Long et al. 2002
24 23.03 (minimum) Oldest known trichosurin (Crosby 2004
a

Used in the “all constraints,” but not in the “no Khasia constraint” MultiDivTime analyses.

b

Used in the “no Khasia constraint,” but not in the “all constraints” MultiDivTime analyses.

c

Not used in the “no 71.2 mya constraint” MultiDivTime analyses.

An additional analysis was carried out with the lower constraint based on Khasia cordillerensis (Table 1) excluded, as doubts have been raised (e.g., Szalay 1994) as to whether Khasia is indeed a microbiothere. When Khasia was excluded, the lower constraint on the Didelphimoiphia–(Caenolesto + Australidelphia) and the Caenolestes–Australidelphia splits was 58.5 mya, based on the presence of didelphimorphian-type tarsals (Szalay 1994) and an undescribed paucituberculate (Oliveira et al. 1996) at Itaborai. Likewise, in this analysis the lower constraint on the Microbiotheria–Australasian radiation split was 23.03 mya, based on the oldest known members of the Australasian crown-group (Table 1). A further analysis was carried out with the 71.2 upper constraint on divergences within the Australasian radiation excluded, because the apparent absence of marsupials from South America before this date may be an artifact of the incomplete fossil record.

All 3 analyses (i.e., all constraints, no Khasia constraint, and no 71.2 mya constraint) were repeated using a reduced data set excluding Burramyidae, Dasyuroides, Dorcopsis, Thylacinus, and Thylogale; these taxa were represented by fewer than 6 of the 22 genes (Appendix I), which may lead to inappropriate branch lengths if these genes are evolving particularly slowly or rapidly relative to the average rate across all 22 genes.

Analysis of unrepresented basal branch lengths (UBBLs).—Following Teeling et al. (2005), I calculated unrepresented basal branch lengths (UBBLs) for several lineages to quantify the incompleteness of the fossil record implied by the molecular divergence dates (Appendix II). UBBL was calculated as 1 – (age of oldest fossil assignable to a particular branch divided by age of divergence of that branch) and converted into a percentage by multiplying by 100. Unlike the dating analysis, in which it is preferable to specify conservative minimum divergence dates (Benton and Donoghue 2007), the point estimate age (rather than the lower bound of the 95% CI) of fossils from radiometrically dated sites was used in the UBBL analysis, and the ages of sites estimated by biocorrelation were assumed to be the midpoint of the assigned age range (following the dates given by Gradstein et al. [2004]), for example, late Oligocene = 25.715 mya ( of 23.03–28.4 mya).

Results

The unpartitioned Bayesian analysis (Fig. 1A) and all maximum-likelihood analyses (Fig. 1B) of the full data set recover a broadly similar topology in which Peramelemorphia is sister to all other australidelphians (= Eometatheria) and Dromiciops forms a clade with either Dasyuromorphia (unpartitioned Bayesian and unpartitioned maximum-likelihood analyses; Fig. 1A) or Dasyuromorphia + Notoryctes (gene- and GCSL-partitioned maximum-likelihood analyses; Fig. 1B). By contrast, gene-partitioned and GCSL-partitioned Bayesian analyses of the full data set (Fig. 2A) and all Bayesian and maximum-likelihood analyses of the no mt3 data set (Figs. 2B and 3) support Peramelemorphia as the sister to Dasyuromorphia + Notoryctes and place Dromiciops as the sister to all other australidelphians. The only differences between the topologies presented in Fig. 2A (no mt3 data set, GCSL-partitioning, Bayesian), Fig. 2B (full data set, GCSL-partitioning, maximum-likelihood), and Fig. 3 (no mt3 data set, GCSL-partitioning, Bayesian) concern the position of Caenolestes (sister to Didelphimorphia in Fig. 2B, but sister to Australidelphia in Figs. 2A and 3) and relationships within macropodines (Thylogale is sister to Dendrolagus in Figs. 2B and 3, but sister to Macropus in Fig. 2A). These alternatives are statistically indistinguishable (Table 2), and I focus my discussion on the tree in Fig. 3 (no mt3 data set, GCSL-partitioning, Bayesian), because this represents the topology and data set used in the molecular dating analysis.

Fig. 1

Topologies that result from A) Bayesian analysis of the full data set without partitioning, and B) maximum-likelihood analysis of the full data set using the GCSL-partitioning scheme. The Bayesian tree is a 50% majority rule consensus tree. Numbers in A are Bayesian posterior probabilities, and in B are maximum-likelihood bootstrap values.

Fig. 1

Topologies that result from A) Bayesian analysis of the full data set without partitioning, and B) maximum-likelihood analysis of the full data set using the GCSL-partitioning scheme. The Bayesian tree is a 50% majority rule consensus tree. Numbers in A are Bayesian posterior probabilities, and in B are maximum-likelihood bootstrap values.

Fig. 2

Topologies that result from A) Bayesian analysis of the full data set using the GCSL-partitioning scheme, and B) maximum-likelihood analysis of the no mt3 data set using the GCSL-partitioning scheme. Other details are as in Fig. 1.

Fig. 2

Topologies that result from A) Bayesian analysis of the full data set using the GCSL-partitioning scheme, and B) maximum-likelihood analysis of the no mt3 data set using the GCSL-partitioning scheme. Other details are as in Fig. 1.

Fig. 3

Topology that results from Bayesian analysis of the no mt3 data set using the GCSL-partitioning scheme. Numbers to the left of the nodes correspond to constraints used in the Multidivtime analyses (Table 1). All Bayesian posterior probability values are ≥0.98, unless otherwise indicated. Other details are as in Fig. 1.

Fig. 3

Topology that results from Bayesian analysis of the no mt3 data set using the GCSL-partitioning scheme. Numbers to the left of the nodes correspond to constraints used in the Multidivtime analyses (Table 1). All Bayesian posterior probability values are ≥0.98, unless otherwise indicated. Other details are as in Fig. 1.

Table 2

Results of approximately unbiased (AU—Shimodaira 2002) and Kishino–Hasegawa (KH—Kishino and Hasegawa 1989) tests of alternative topologies as calculated by CONSEL (Shimodaira and Hasegawa 2001) assuming both the full and no mt3 (excluding 3rd codon positions of mitochondrial protein-coding genes) data sets. P-values less than 0.05 (indicating that the topology is statistically rejected by the data set) are indicated with asterisks. The first 5 topologies are from Figs. 1–3, with the remainder from the studies cited.

  Full data set No mt3 data set 
Topology Reference AU KH AU KH 
Full, unpartitioned, Bayesian Fig. 1A 0.084 0.076 0.031* 0.026* 
Full, GCSL-partitioned, ML Fig. IB 0.118 0.071 0.047* 0.036* 
No mt3, GCSL-partitioned, ML Fig. 2A 0.48 0.299 0.529 0.371 
Full, GCSL-partitioned, Bayesian Fig. 2B 0.577 0.38 0.608 0.405 
No mt3, Bayesian, GCSL-partitioned Fig. 3 0.708 0.414 0.774 
Didelphimorphia + Caenolestes (= Ameridelphia) — 0.473 0.298 0.526 0.372 
Caenolestes sister to rest of Marsupialia Baker et al. 2004; Kirsch et al. 1997; Szalay and Sargis 2001, 2006 0.732 0.586 0.654 0.481 
Peramelemorphia sister to rest of Australidelphia (= Eometatheria) Asher et al. 2004: figure 1; Kirsch et al. 1997 0.408 0.267 0.261 0.154 
Diprotodontia + Peramelemorphia (= Syndactyla excluding NotoryctesSzalay 1994; Szalay and Sargis 2001, 2006 0.012* 0.024* 0.016* 0.011* 
Diprotodontia + (Peramelemorphia + Notoryctes) (= Syndactyla including NotoryctesSzalay 1994; Szalay and Sargis 2001, 2006 0.038* 0.036* 0.037* 0.023* 
Peramelemorphia + Notoryctes Horovitz and Sanchez-Villagra 2003; Warburton 2003 0.3 0.186 0.3 0.143 
Dromiciops + Diprotodontia Horovitz and Sanchez-Villagra 2003, Cardillo et al. 2004 0.339 0.236 0.27 0.159 
Dromiciops + Dasyuromorphia (= Gondwanadelphia) Szalay 1994; Szalay and Sargis 2001 0.022* 0.021* 0.009* 0.008* 
Dromiciops + (Dasyuromorphia + Notoryctes) — 0.004* 0.014* 0.029* 0.004* 
Dromiciops + Peramelemorphia Asher et al. 2004: figure 2—right 0.075 0.063 0.074 0.048* 
Dromiciops + (Peramelemorphia + (Dasyuromorphia + Notoryctes)) Nilsson et al. 2004 0.025* 0.04* 0.023* 0.017* 
Macropodoidea + Petauroidea Amrine-Madsen et al. 2003 0.208 0.175 0.227 0.159 
Petauroidea + (Burramyidae + Phalangeridae) (= possum monophyly) — 0.498 0.36 0.515 0.376 
Burramyidae sister to rest of Diprotodontia Asher et al. 2004: figure 1 0.036* 0.063 0.041* 0.02* 
  Full data set No mt3 data set 
Topology Reference AU KH AU KH 
Full, unpartitioned, Bayesian Fig. 1A 0.084 0.076 0.031* 0.026* 
Full, GCSL-partitioned, ML Fig. IB 0.118 0.071 0.047* 0.036* 
No mt3, GCSL-partitioned, ML Fig. 2A 0.48 0.299 0.529 0.371 
Full, GCSL-partitioned, Bayesian Fig. 2B 0.577 0.38 0.608 0.405 
No mt3, Bayesian, GCSL-partitioned Fig. 3 0.708 0.414 0.774 
Didelphimorphia + Caenolestes (= Ameridelphia) — 0.473 0.298 0.526 0.372 
Caenolestes sister to rest of Marsupialia Baker et al. 2004; Kirsch et al. 1997; Szalay and Sargis 2001, 2006 0.732 0.586 0.654 0.481 
Peramelemorphia sister to rest of Australidelphia (= Eometatheria) Asher et al. 2004: figure 1; Kirsch et al. 1997 0.408 0.267 0.261 0.154 
Diprotodontia + Peramelemorphia (= Syndactyla excluding NotoryctesSzalay 1994; Szalay and Sargis 2001, 2006 0.012* 0.024* 0.016* 0.011* 
Diprotodontia + (Peramelemorphia + Notoryctes) (= Syndactyla including NotoryctesSzalay 1994; Szalay and Sargis 2001, 2006 0.038* 0.036* 0.037* 0.023* 
Peramelemorphia + Notoryctes Horovitz and Sanchez-Villagra 2003; Warburton 2003 0.3 0.186 0.3 0.143 
Dromiciops + Diprotodontia Horovitz and Sanchez-Villagra 2003, Cardillo et al. 2004 0.339 0.236 0.27 0.159 
Dromiciops + Dasyuromorphia (= Gondwanadelphia) Szalay 1994; Szalay and Sargis 2001 0.022* 0.021* 0.009* 0.008* 
Dromiciops + (Dasyuromorphia + Notoryctes) — 0.004* 0.014* 0.029* 0.004* 
Dromiciops + Peramelemorphia Asher et al. 2004: figure 2—right 0.075 0.063 0.074 0.048* 
Dromiciops + (Peramelemorphia + (Dasyuromorphia + Notoryctes)) Nilsson et al. 2004 0.025* 0.04* 0.023* 0.017* 
Macropodoidea + Petauroidea Amrine-Madsen et al. 2003 0.208 0.175 0.227 0.159 
Petauroidea + (Burramyidae + Phalangeridae) (= possum monophyly) — 0.498 0.36 0.515 0.376 
Burramyidae sister to rest of Diprotodontia Asher et al. 2004: figure 1 0.036* 0.063 0.041* 0.02* 

When the probable microbiothere Khasia is not used as a fossil constraint, molecular dates become 1–6% younger, whereas removal of the 71.2 mya upper constraint on the diversification of Australasian marsupials results in an 8–12% increase in age (Table 3). Exclusion of the 5 taxa with the most missing data (Burramyidae, Dasyuroides, Dorcopsis, Thylacinus, and Thylogale) generally results in somewhat (∼2–8%) younger dates, although some nodes instead show a slight increase in age (Table 3). In the absence of compelling evidence that Khasia is not a microbiothere or that marsupials were present in South America before 71.2 mya, I will assume for the purposes of discussion the divergence dates that result when all constraints (Table 1; Fig. 4) are enforced.

Table 3

Divergence dates estimated using Multidivtime (node numbers are given in Figs. 3 and 4). Two different data sets were used, 1 including all sequences and the other excluding the 5 taxa with most incomplete data (Burramyidae, Dasyuroides, Dorcopsis, Thylacinus, and Thylogale). Multidivtime analyses were carried out using all constraints listed in Table 1 (“All constraints”), excluding Khasia as the oldest known microbiothere (“No Khasia constraint”), or excluding the 71.2 mya upper constraint on divergences within the Australasian radiation (“No 71.2 mya constraint”). Divergence dates from the analysis using all sequences and all constraints are illustrated in Fig. 4.

 No mt3 data set, all sequences No mt3 data set, 5 most incomplete taxa deleted 
Node All constraints No Khasia constraint No 71.2 mya constraint All constraints No Khasia constraint No 71.2 mya constraint 
197.2 ± 23.5 (154.9–246.9) 193.8 ± 24.5 (150.1–245.5) 215.4 ± 33.1 (159.2–285.5) 198.9 ± 22.6 (159.6–247.2) 190.6 ± 23.6 (151.5–242.6) 216.2 ± 32.8 (163.4–287.8) 
78.2 ± 11.5 (60.3–104.0) 77.0 ±11.5 (59.8–103.4) 85.1 ± 14.7 (61.3–116.7) 77.9 ± 11.3 (60.3–103.3) 75.0 ± 11.1 (59.5–101.1) 84.2 ± 14.7 (61.1–116.5) 
80.6 ± 5.2 (70.7–90.0) 79.0 ± 6.3 (65.8–89.7) 90.3 ± 12.7 (71.5–118.8) 79.3 ± 5.5 (70.2–90.1) 75.0 ± 7.5 (62.6–89.1) 88.4 ± 13.0(70.9–118.0) 
44.4 ± 4.5 (35.9–53.4) 43.4 ± 4.9 (34.1–53.1) 50.4 ± 8.7 (37.1–70.3) 42.4 ± 4.4 (34.4–51.5) 39.8 ± 5.3 (30.6–50.5) 47.9 ± 8.5 (35.4–67.5) 
76.5 ± 4.7 (67.5–84.7) 74.9 ± 5.8 (62.7–84.4) 85.9 ± 12.1 (68.1–113.0) 75.1 ± 5.0 (67.0–84.5) 70.9 ± 7.0 (59.4–83.8) 83.9 ± 12.4(67.6–112.3) 
67.4 ± 3.9 (59.8–73.6) 66.0 ± 4.9 (55.5–73.5) 75.9 ± 10.8 (60.3–100.2) 65.8 ± 4.2 (59.3–73.3) 62.0 ± 6.2 (51.7–73.0) 73.6 ± 11.0(59.5–99.1) 
65.2 ± 3.7 (57.9–70.9) 63.8 ± 4.7 (53.7–70.8) 73.3 ± 10.4 (58.3–96.8) 63.5 ± 4.0(57.1–70.7) 59.9 ± 6.0 (49.9–70.5) 71.2 ± 10.7 (57.5–95.8) 
63.4 ± 3.7 (56.3–69.2) 62.1 ± 4.6 (52.3–69.1) 71.4 ± 10.2 (56.8–94.3) 61.6 ± 4.0 (55.2–68.8) 58.1 ± 5.8 (48.3–68.5) 69.1 ± 10.4 (55.7–93.1) 
10 11.7 ± 1.5 (9.1–15.1) 11.5 ± 1.6(8.7–14.9) 13.2 ± 2.5 (9.4–19.0) 11.3 ± 1.5 (8.8–14.5) 10.6 ± 1.6 (7.9–14.0) 12.8 ± 2.5 (9.1–18.7) 
11 60.1 ± 3.6 (53.2–66.1) 58.9 ± 4.4 (49.6–65.9) 67.6 ± 9.7 (53.8–89.8) 58.3 ± 3.9 (51.8–65.5) 54.9 ± 5.6 (45.4–65.1) 65.4 ± 10.0 (52.3–88.3) 
12 26.0 ± 2.2 (23.2–31.4) 25.7 ± 2.2 (23.1–31.1) 28.6 ± 4.5 (23.2–39.7) — — — 
13 11.6 ± 1.6(8.8–15.2) 11.4 ± 1.6(8.7–15.1) 12.8 ± 2.5 (9.1–18.9) 10.6 ± 1.3 (8.3–13.5) 10.0 ± 1.5 (7.5–13.2) 12.0 ± 2.3 (8.6–17.5) 
14 7.8 ± 1.5 (5.3–11.1) 7.7 ± 1.5 (5.2–11.0) 8.6 ± 2.1 (5.5–13.5) — — — 
15 57.1 ± 3.4 (50.5–62.9) 55.9 ± 4.3 (47.1–62.8) 64.3 ± 9.3 (50.9–85.2) 55.4 ± 3.7 (49.2–62.3) 52.2 ± 5.3 (43.3–61.8) 62.1 ± 9.5 (49.7–84.0) 
16 40.7 ± 3.3 (34.4–47.0) 39.8 ± 3.7 (32.5–46.9) 45.8 ± 7.1 (35.0–62.1) 39.2 ± 3.4 (33.0–45.8) 36.9 ± 4.2 (29.5–45.2) 44.0 ± 7.2 (33.7–60.6) 
17 51.1 ± 3.2 (44.9–57.0) 50.0 ± 4.0 (41.8–56.8) 57.4 ± 8.4 (45.2–76.4) 49.0 ± 3.5 (43.0–55.8) 46.2 ± 4.8 (38.2–55.2) 55.0 ± 8.5 (43.4–74.7) 
18 32.4 ± 3.1 (26.6–38.7) 31.7 ± 3.4 (25.3–38.5) 36.4 ± 6.0 (27.0–50.1) 30.8 ± 3.1 (25.3–37.2) 29.1 ± 3.5 (23.6–36.4) 34.6 ± 6.0 (25.7–48.5) 
19 47.1 ± 3.2 (41.1–53.0) 46.0 ± 3.8 (38.3–52.8) 52.9 ± 7.9 (41.3–70.7) 45.0 ± 3.4 (39.1–51.6) 42.4 ± 4.5 (34.8–51.0) 50.5 ± 8.0 (39.5–68.9) 
20 16.7 ± 2.3 (12.6–21.7) 16.3 ± 2.4 (12.0–21.4) 18.7 ± 3.7 (12.9–27.2) — — — 
21 14.7 ± 2.1 (10.9–19.2) 14.3 ± 2.2(10.3–19.0) 16.4 ± 3.3 (11.1–24.0) 17.1 ± 2.5 (12.6–22.4) 16.1 ± 2.6(11.5–21.8) 19.2 ± 3.9 (13.1–28.2) 
22 13.1 ± 2.0 (9.4–17.4) 12.7 ± 2.1 (9.0–17.2) 14.6 ± 3.1 (9.7–21.6) — — — 
23 40.0 ± 3.7 (33.0–47.4) 38.8 ± 4.2 (30.6–46.9) 44.5 ± 7.4 (33.0–61.3) — — — 
24 28.1 ± 3.2 (23.3–35.3) 26.5 ± 4.1 (18.7–34.9) 30.4 ± 6.2 (20.2–44.4) 27.1 ± 4.1 (19.5–35.4) 25.5 ± 4.3 (17.8–34.5) 30.4 ± 6.2 (20.4–44.7) 
 No mt3 data set, all sequences No mt3 data set, 5 most incomplete taxa deleted 
Node All constraints No Khasia constraint No 71.2 mya constraint All constraints No Khasia constraint No 71.2 mya constraint 
197.2 ± 23.5 (154.9–246.9) 193.8 ± 24.5 (150.1–245.5) 215.4 ± 33.1 (159.2–285.5) 198.9 ± 22.6 (159.6–247.2) 190.6 ± 23.6 (151.5–242.6) 216.2 ± 32.8 (163.4–287.8) 
78.2 ± 11.5 (60.3–104.0) 77.0 ±11.5 (59.8–103.4) 85.1 ± 14.7 (61.3–116.7) 77.9 ± 11.3 (60.3–103.3) 75.0 ± 11.1 (59.5–101.1) 84.2 ± 14.7 (61.1–116.5) 
80.6 ± 5.2 (70.7–90.0) 79.0 ± 6.3 (65.8–89.7) 90.3 ± 12.7 (71.5–118.8) 79.3 ± 5.5 (70.2–90.1) 75.0 ± 7.5 (62.6–89.1) 88.4 ± 13.0(70.9–118.0) 
44.4 ± 4.5 (35.9–53.4) 43.4 ± 4.9 (34.1–53.1) 50.4 ± 8.7 (37.1–70.3) 42.4 ± 4.4 (34.4–51.5) 39.8 ± 5.3 (30.6–50.5) 47.9 ± 8.5 (35.4–67.5) 
76.5 ± 4.7 (67.5–84.7) 74.9 ± 5.8 (62.7–84.4) 85.9 ± 12.1 (68.1–113.0) 75.1 ± 5.0 (67.0–84.5) 70.9 ± 7.0 (59.4–83.8) 83.9 ± 12.4(67.6–112.3) 
67.4 ± 3.9 (59.8–73.6) 66.0 ± 4.9 (55.5–73.5) 75.9 ± 10.8 (60.3–100.2) 65.8 ± 4.2 (59.3–73.3) 62.0 ± 6.2 (51.7–73.0) 73.6 ± 11.0(59.5–99.1) 
65.2 ± 3.7 (57.9–70.9) 63.8 ± 4.7 (53.7–70.8) 73.3 ± 10.4 (58.3–96.8) 63.5 ± 4.0(57.1–70.7) 59.9 ± 6.0 (49.9–70.5) 71.2 ± 10.7 (57.5–95.8) 
63.4 ± 3.7 (56.3–69.2) 62.1 ± 4.6 (52.3–69.1) 71.4 ± 10.2 (56.8–94.3) 61.6 ± 4.0 (55.2–68.8) 58.1 ± 5.8 (48.3–68.5) 69.1 ± 10.4 (55.7–93.1) 
10 11.7 ± 1.5 (9.1–15.1) 11.5 ± 1.6(8.7–14.9) 13.2 ± 2.5 (9.4–19.0) 11.3 ± 1.5 (8.8–14.5) 10.6 ± 1.6 (7.9–14.0) 12.8 ± 2.5 (9.1–18.7) 
11 60.1 ± 3.6 (53.2–66.1) 58.9 ± 4.4 (49.6–65.9) 67.6 ± 9.7 (53.8–89.8) 58.3 ± 3.9 (51.8–65.5) 54.9 ± 5.6 (45.4–65.1) 65.4 ± 10.0 (52.3–88.3) 
12 26.0 ± 2.2 (23.2–31.4) 25.7 ± 2.2 (23.1–31.1) 28.6 ± 4.5 (23.2–39.7) — — — 
13 11.6 ± 1.6(8.8–15.2) 11.4 ± 1.6(8.7–15.1) 12.8 ± 2.5 (9.1–18.9) 10.6 ± 1.3 (8.3–13.5) 10.0 ± 1.5 (7.5–13.2) 12.0 ± 2.3 (8.6–17.5) 
14 7.8 ± 1.5 (5.3–11.1) 7.7 ± 1.5 (5.2–11.0) 8.6 ± 2.1 (5.5–13.5) — — — 
15 57.1 ± 3.4 (50.5–62.9) 55.9 ± 4.3 (47.1–62.8) 64.3 ± 9.3 (50.9–85.2) 55.4 ± 3.7 (49.2–62.3) 52.2 ± 5.3 (43.3–61.8) 62.1 ± 9.5 (49.7–84.0) 
16 40.7 ± 3.3 (34.4–47.0) 39.8 ± 3.7 (32.5–46.9) 45.8 ± 7.1 (35.0–62.1) 39.2 ± 3.4 (33.0–45.8) 36.9 ± 4.2 (29.5–45.2) 44.0 ± 7.2 (33.7–60.6) 
17 51.1 ± 3.2 (44.9–57.0) 50.0 ± 4.0 (41.8–56.8) 57.4 ± 8.4 (45.2–76.4) 49.0 ± 3.5 (43.0–55.8) 46.2 ± 4.8 (38.2–55.2) 55.0 ± 8.5 (43.4–74.7) 
18 32.4 ± 3.1 (26.6–38.7) 31.7 ± 3.4 (25.3–38.5) 36.4 ± 6.0 (27.0–50.1) 30.8 ± 3.1 (25.3–37.2) 29.1 ± 3.5 (23.6–36.4) 34.6 ± 6.0 (25.7–48.5) 
19 47.1 ± 3.2 (41.1–53.0) 46.0 ± 3.8 (38.3–52.8) 52.9 ± 7.9 (41.3–70.7) 45.0 ± 3.4 (39.1–51.6) 42.4 ± 4.5 (34.8–51.0) 50.5 ± 8.0 (39.5–68.9) 
20 16.7 ± 2.3 (12.6–21.7) 16.3 ± 2.4 (12.0–21.4) 18.7 ± 3.7 (12.9–27.2) — — — 
21 14.7 ± 2.1 (10.9–19.2) 14.3 ± 2.2(10.3–19.0) 16.4 ± 3.3 (11.1–24.0) 17.1 ± 2.5 (12.6–22.4) 16.1 ± 2.6(11.5–21.8) 19.2 ± 3.9 (13.1–28.2) 
22 13.1 ± 2.0 (9.4–17.4) 12.7 ± 2.1 (9.0–17.2) 14.6 ± 3.1 (9.7–21.6) — — — 
23 40.0 ± 3.7 (33.0–47.4) 38.8 ± 4.2 (30.6–46.9) 44.5 ± 7.4 (33.0–61.3) — — — 
24 28.1 ± 3.2 (23.3–35.3) 26.5 ± 4.1 (18.7–34.9) 30.4 ± 6.2 (20.2–44.4) 27.1 ± 4.1 (19.5–35.4) 25.5 ± 4.3 (17.8–34.5) 30.4 ± 6.2 (20.4–44.7) 
Fig. 4

Modified version of Fig. 3 with dates calculated by Multidivtime assuming full constraints and including all taxa (estimated dates from all the Multidivtime analyses are given in Table 3). Monotreme and placental outgroups have been pruned. Dark gray bars represent 1 SD either side of the point estimate, and light gray bars represent the 95% CI. Circles on branches and their associated letters represent the earliest known fossils assignable to that lineage and used to calculate unrepresented basal branch lengths (UBBLs; Appendix II). Black circle = fossil confidently assigned to that lineage and used to calibrate the Multidivtime analysis (Table 1); gray circle = fossil confidently assigned to that lineage but not used to calibrate the Multidivtime analysis; white circle = fossil only tentatively assigned to that lineage.

Fig. 4

Modified version of Fig. 3 with dates calculated by Multidivtime assuming full constraints and including all taxa (estimated dates from all the Multidivtime analyses are given in Table 3). Monotreme and placental outgroups have been pruned. Dark gray bars represent 1 SD either side of the point estimate, and light gray bars represent the 95% CI. Circles on branches and their associated letters represent the earliest known fossils assignable to that lineage and used to calculate unrepresented basal branch lengths (UBBLs; Appendix II). Black circle = fossil confidently assigned to that lineage and used to calibrate the Multidivtime analysis (Table 1); gray circle = fossil confidently assigned to that lineage but not used to calibrate the Multidivtime analysis; white circle = fossil only tentatively assigned to that lineage.

Discussion

Although relatively strongly supported by both bootstrapping and posterior probabilities, the positions of Peramelemorphia and Dromiciops in Figs. 1A and 1B are most likely anomalous and result from misleading signals in the 3rd codon positions of the mitochondrial protein-coding genes. Increased partitioning of the full data set, which is strongly supported by Bayes factors ≫ 10 (Nylander et al. 2004), results in a different topology (Fig. 2A) that is largely identical to that from the no mt3 data set, albeit only when Bayesian analysis is used. The topologies in Fig. 1 also are rejected by both the AU and KH tests when the no mt3 data set is assumed (Table 2). Finally, Phillips et al. (2006) found clear support for a close relationship between Peramelemorphia and Dasyuromorphia (and for Dromiciops as the sister to the Australasian radiation) when the analysis was corrected for base composition bias. The inability of maximum-likelihood analysis (as implemented by RAxML) to recover the inferred correct topology, even under the GCSL-partitioning scheme (Fig. 1B), was unexpected and may relate to the fact that maximum-likelihood model parameters must be specified before the analysis, whereas they are estimated during the analysis in the Bayesian approach. Also, RAxML only allows use of the GTR + gamma model for each partition, rather than other models that may be more appropriate.

Figure 3 is fully resolved, and all but 1 of the interordinal divergences are strongly supported by Bayesian posterior probabilities (BPP ≥ 0.98), although equivalent bootstrap values from the maximum-likelihood analysis using the same data set and partitioning scheme (Fig. 2A) are low for some nodes. The deepest split within marsupials (BPP = 1.00) is between Didelphimorphia and a clade comprising Caenolestes and Australidelphia. This arrangement is congruent with recent molecular phylogenies (Amrine-Madsen et al. 2003; Nilsson et al. 2004), the morphological analysis of Horovitz and Sanchez-Villagra (2003), and the combined analysis of Asher et al. (2004). However, the Caenolestes + Australidelphia clade is relatively weakly supported (BPP = 0.72), and neither the AU nor KH test rejects a monophyletic Ameridelphia (recovered in the equivalent maximum-likelihood analysis with 60% bootstrap support; Fig. 2A) or Didelphimorphia + Australidelphia. The latter clade was favored by Szalay and Sargis (2001, 2006) on morphological grounds and has been found in some molecular studies, for example, Baker et al. (2004) and Kirsch et al. (1997). Thus, the relationships of caenolestids remain uncertain, and inclusion of sequence data from 1 or both of the other extant caenolestid genera (Lestoros and Rhyncholestes) may help increase resolution by breaking up the long branch leading to Caenolestes. At least part of this uncertainty also may be due to rooting difficulties, because studies suggest that the position of the root is often the most difficult region of a molecular phylogeny to resolve robustly (Sanderson and Shaffer 2002). Additional sources of molecular data, such as retrotransposon insertions, insertions–deletions, or other rare genomic changes (Rokas and Holland 2000), may be required to root the marsupial tree with confidence.

Within Australidelphia, the South American Dromiciops is sister to a monophyletic Australasian clade (BPP = 1.00; bootstrap = 100). The alternative positions for Dromiciops recovered by Asher et al. (2004—sister to all Australasian marsupials except Peramelemorphia) and Nilsson et al. (2004—sister to Notoryctes + Dasyuromorphia + Peramelemorphia) are most likely erroneous, because both studies used mitochondrial genes without correcting for the biases identified by Phillips et al. (2006). The topology of Nilsson et al. (2004) is rejected by both the AU and KH tests, whereas the topology of Asher et al. (2004) is not (Table 2).

Within the Australasian radiation, the 1st divergence is between the diverse order Diprotodontia and a clade comprising the 3 Australasian “polyprotodont” orders, Peramelemorphia, Notoryctemorphia, and Dasyuromorphia (BPP = 1.00; bootstrap = 40). This topology agrees with that of Amrine-Madsen et al. (2003) and Phillips et al. (2006), and it indicates that syndactyly (fusion of digits II and III and their integration into a single functional digit—Weisbecker and Nilsson 2006) evolved independently in these 2 orders (contra Szalay 1994). Although syndactyly is a derived feature present in all diprotodontians and peramelemorphians, a monophyletic Syndactyla (Szalay 1982, 1994), whether including or excluding Notoryctes (which may or may not be syndactylous), is rejected by both the KH and AU tests (Table 2). Notoryctes is the sister-group of Dasyuromorphia (BPP = 0.98; bootstrap = 70). Recent morphological studies (Horovitz and Sanchez-Villagra 2003; Warburton 2003) have linked Notoryctes with Peramelemorphia, and a Notoryctes + Peramelemorphia clade is not rejected by KH and AU tests (Table 2). Tarsal material of a fossil notoryctid from early Miocene Faunal Zone B (previously “System B”—Arena 2004; Travouillon et al. 2006) sites at Riversleigh also shares distinctive apomorphies (not present in the more derived Notoryctes) with peramele-morphians (R. M. D. Beck, in litt.). Notoryctes is the sole extant representative of the order Notoryctemorphia and is extremely autapomorphic; it thus represents both a molecular and morphological long branch that may be difficult to place robustly with either morphological or sequence data. Other kinds of molecular data may be required to resolve the affinities of Notoryctes conclusively. Within Dasyuromorphia, Dasyuridae is monophyletic relative to the thylacine Thylacinus (BPP = 1.00; bootstrap = 100).

In agreement with morphological data (e.g., Aplin and Archer 1987), Diprotodontia comprises 2 major clades: Vombatiformes (the koala and wombats; BPP = 1.00; bootstrap = 100) and Phalangerida (the various families of extant “possums” and kangaroos; BPP = 1.00; bootstrap = 90). An alternative topology, with Burramyidae sister to other diprotodontians (Asher et al. 2004), is rejected by both the AU and KH tests with the no mt3 data set, but only by the AU test for the full data set (Table 2). Petauroidea, a clade comprising pseudocheirids and petaurids, is monophyletic (BPP = 1.00; bootstrap = 100) and also is well supported by morphology (Aplin and Archer 1987). A 2nd possum clade consisting of Burramyidae and Phalangeridae (BPP = 0.98; bootstrap = 70) also was seen in the DNA-hybridization trees of Springer and Kirsch (1991) and Kirsch et al. (1997), a maximum-likelihood analysis of RAG1 sequences by Baker et al. (2004), and morphological analyses of phalangeridans by Crosby (2004). “Possums,” as a whole, appear to be a paraphyletic assemblage (although possum monophyly cannot be rejected; Table 2) because kangaroos are the sister-group of the Burramyidae + Phalangeridae clade (BPP = 0.98; bootstrap = 50). Plesio-morphic macropodoids, burramyids, and phalangerids all possess a hypertrophied 3rd premolar that may represent a morphological synapomorphy of this clade.

Divergence dates.—On initial examination, the divergence dates in Fig. 4 and Table 3 seem congruent with the known fossil record; the dates are not implausibly ancient (i.e., older than the Late Cretaceous), nor are any lineages younger than the oldest known fossils referred to them. In contrast, at least some of the molecular dates of Nilsson et al (2004), who used a penalized log-likelihood method and a relatively young estimate of 135 mya for the divergence between marsupials and placentals (compared to 186–193 mya calculated by van Rheede et al. [2006]), appear incongruent with the fossil record. For example, their estimated age for the divergence of Microbiotheria is 46 mya, but the oldest known fossil microbiothere, Khasia cordillerensis from Tiupampa (Marshall and Muizon 1988), is approximately 60 million years old (however, there are some doubts as to whether Khasia is indeed a microbiothere—Szalay 1994). Below, I undertake a more detailed examination of the divergence dates to identify the degree of congruence with the fossil record and to determine whether particular divergences coincided with major environmental changes.

The 2 deepest splits within marsupials are here estimated as occurring 80.6 mya (Didelphimorphia–other marsupials) and 76.5 mya (Caenolestes–Australidelphia), that is, in the Campanian of the Late Cretaceous. If the apparent absence of marsupials from the Alamitian (∼71.2 mya) faunas of South America is accurate, then these 2 divergences must have occurred in Laurasia (probably North America, given that marsupials appear to have been rare in Eurasia during the Late Cretaceous), and members of 3 separate marsupial lineages (didelphimorphians, paucituberculates, and australidelphians) dispersed from North America to South America during the latest Cretaceous–earliest Paleocene. This total does not include fossil groups, such as borhyaenoids and polydolopi-morphians, that may lie outside the marsupial crown-group. Fossil evidence indicates that as many as 4 separate placental lineages also dispersed from North to South America during the latest Cretaceous–earliest Paleocene (Muizon 1991; Muizon and Cifelli 2000), as did other terrestrial vertebrates such as hadrosaurs and snakes (Case et al. 2000, 2005), suggesting the existence of a relatively robust connection between the 2 continents during this period.

Evidence of crown marsupials in the Late Cretaceous of North America is equivocal given the limited fossil material currently known, but the dates presented here are congruent with the assignment of Glasbius to Paucituberculata (Kielan-Jaworowska et al. 2004) and Nortedelphys to Didelphimorphia (Case et al. 2005), in which case UBBL is 17.4% and 13% for Didelphimorphia and Paucituberculata, respectively (Appendix II). Unequivocal didelphimorphians (identified by the presence of the distinctive proximal calcaneocuboid facet of the tarsus seen in all extant didelphids—Szalay 1994) and paucituberculatans (Oliveira et al. 1996) are 1st known from the late Paleocene (58.7–59.2 mya) Itaborai fauna in Brazil, but have not been identified in the slightly older (59.2–60.4 mya) Tiupampa fauna. If the Itaboraian fossils are preferred as the earliest known members of these orders, then UBBL increases to 26.9% and 22.9% for Didelphimorphia and Paucituberculata, respectively (Appendix II). Efforts to discover earlier records of these orders are hampered by a lack of South American marsupials older than those from Tiupampa, with the exception of the highly fragmentary Punta Peligro fauna (possibly early Paleocene) and a single tooth from the early Paleocene Lefipan Formation (Goin et al. 2006). UBBLs for the crown didelphimorphians Monodelphis (68.4%) and Didelphini (87.8%) are high, probably because didelphids are poorly defined on dental grounds (the family is characterized by a highly plesiomorphic dentition), making referral of isolated teeth to the family or to specific genera difficult.

The split between microbiotheres and the Australasian marsupials is estimated as 67.4 mya. There is no evidence of microbiotheres or any member of the Australasian radiation in the Late Cretaceous North American deposits, which may be indirect evidence that this split occurred in Gohdwana. However, stem australidelphians most likely had a relatively plesiomorphic tribosphenic dentition (perhaps similar to that of the early Eocene Australian marsupial Djarthia murgonensis—R. M. D. Beck, in litt.), and unequivocal australidelphian synapomorphies are restricted to the tarsus, suggesting that it may be impossible to identify them from isolated teeth alone. The oldest known australidelphian is the probable micro-biothere Khasia cordillerensis from Tiupampa; hence, UBBL for Microbiotheria is only 11.3% (Appendix II).

Although the estimated age of the 1st split within the Australasian marsupials (65.2 mya) is almost immediately after the Cretaceous–Tertiary boundary, this is not necessarily evidence of a causal link between these 2 events. Whether this split occurred in South America, Australia, or Antarctica is uncertain. However, given that the modern Australasian radiation appears to be monophyletic, and that there is no fossil evidence of members of any Australasian order in South America or the middle Eocene of Seymour Island in western Antarctica, an Australasian or eastern Gondwanan center of origin seems likely. If so, the date of this split represents the minimum age for the arrival of marsupials in Australasia–eastern Gondwana, which therefore must have occurred between 65.2 (± 3.7; 95% CI = 57.9–70.9) and 71.2 mya. All 4 extant Australasian orders—Peramelemorphia, Dasyuromorphia, Notoryctemorphia, and Diprotodontia—are estimated to have diverged by the age of the early Eocene Tingamarra fauna (54.6 mya). However, no undoubted members of any of these orders have been identified among the marsupial specimens recovered from this site; hence UBBL for these 4 orders is 59.4%, 57.2%, 67.5%, and 60.6%, respectively (Appendix II). A single upper molar from Tingamarra was tentatively identified as a possible bandicoot (Archer et al. 1999), but it lacks unequivocal peramelemorphian dental synapomorphies. A 2nd upper molar from Tingamarra reported as an undoubted peramelemorphian (Beck et al. 2006) is in fact a misattributed specimen from a younger site. Woodburne and Case (1996) suggested that the bunodont Tingamarran marsupial Thylacotinga is a peramelemorphian, but it also lacks unequivocal apomorphies that would distinguish it from other bunodont forms such as polydolopimorphians. Given that the most distinctive feature of peramelemorphian molars—a highly invasive, incomplete centrocrista that breaches the ectoloph—is not present in the late Oligocene Yarala burchfieldi (Muirhead and Filan 1995), identifiable dental synapomorphies of Peramelemorphia may not have evolved until long after the early Eocene. If so, fossil peramelemorphians may be present at Tingamarra but cannot be recognized as such. This explanation also may apply to Notoryctemorphia; although notoryctemorphians are estimated as originating at 60.0 mya, the only known fossil notoryctid (from the middle Miocene of Riversleigh—Long et al. 2002) is considerably more plesiomorphic than Notoryctes, suggesting that many characteristic notoryctid specializations may have evolved much later than the early Eocene. The absence of notoryctids from the late Oligocene Faunal Zone A of Riversleigh is more surprising, given that a relatively derived notoryctid is present in the middle Miocene Faunal Zone B. However, Faunal Zone A sites appear biased (whether taphonomically or ecologically) toward large-bodied taxa such as thylacinids and larger diprotodontians (H. Godthelp, University of New South Wales, pers. comm.).

A detailed analysis of marsupial dental characters by Godthelp et al. (1999) failed to identify dental apomorphies that distinguish dasyuromorphians from other marsupials with relatively unspecialized tribosphenic dentitions. Thus, dasyuromorphians may be represented by some of the hundreds of isolated teeth now recovered from Tingamarra but cannot be distinguished unequivocally from other dentally plesiomorphic groups. Within Dasyuromorphia, the dasyurid–thylacinid divergence date of 26.0 mya is congruent with presence of the plesiomorphic thylacinids Nimbacinus and Badjcinus in late Oligocene Riversleigh Faunal Zone A deposits and the dasyurid Barinya (which shows relatively derived dasyurid apomorphies of the petrosal—Wroe 1999) in middle Miocene Faunal Zone B deposits. UBBL for Thylacinidae is only 1.1%, yet Muirhead and Wroe (1998) identified 6 thylacinid apomorphies in Badjcinus. This suggests either that morphological evolution in the earliest thylacinids was quite rapid, that Riversleigh Faunal Zone A sites may be somewhat younger than the 25.7 mya assumed here, or that the molecular divergence date calculated here is an underestimate resulting from the high proportion of missing data for Thylacinus.

The estimated divergence dates for the split between phascogaline and dasyurine dasyurids (11.6 mya) and between peramelid and peroryctid bandicoots (11.7 mya) are almost identical and coincide with the middle–late Miocene boundary, which saw a major drop in sea level (Haq et al. 1987). These dates explain the absence of these groups from Faunal Zones A–C (late Oligocene–middle Miocene) sites at Riversleigh; they are 1st seen in the fossil record only in the Pliocene, probably because of a lack of Australian sites from the late Miocene.

Within Diprotodontia, the point estimate for the Vombati-formes–Phalangerida split is 57.1 mya, implying that these lineages had diverged by the estimated age of the Tingamarra fauna. Both vombatiforms and phalangeridans possess apomorphically enlarged “diprotodont” 1st lower incisors that were presumably present in their last common ancestor, but no such teeth (or any other specimens that can be referred unequivocally to Diprotodontia) have been found at Tingamarra. However, the standard deviation for the Vombati-formes-Phalangerida split is 3.4 million years and the 95% CI is 50.5–62.9 mya, and so it may in fact postdate Tingamarra. Drummond et al. (2006) used a different relaxed molecular clock method that (unlike Multidivtime) does not employ rate autocorrelation and estimated a slightly younger age for this split, at about 48 mya.

Both koalas and vombatoids (but not vombatids), estimated here as having diverged 40.5 mya, are known from the late Oligocene deposits of Riversleigh, as are petaurids and pseudocheirids (divergence date = 32.2 mya), and burramyids and phalangerids (divergence date = 39.4 mya). Crosby (2004) identified trichosurins among the late Oligocene Riversleigh phalangerids, congruent with the 26.9 mya divergence date estimated for the trichosurin–phalangerin split presented here, hence UBBL for trichosurins is only 8.5%. However, undoubted phalangerins have not been found at Riversleigh or indeed any fossil site older than the Pleistocene, resulting in a very large UBBL of 96.6%. Phalangerins may have evolved in New Guinea or Sulawesi and invaded Australia during the Pleistocene (Raterman et al. 2006). The earliest undoubted macropodoids are from the late Oligocene (Archer et al. 1999; Long et al. 2002), and an undescribed macropodine is known from a middle Miocene Faunal Zone C site at Riversleigh (B. N. Cooke, Queensland University of Technology, pers. comm.). The radiation of the macropodines, which appears to have started in the middle Miocene (16.7 mya), coincided with the mid-Miocene climatic optimum (Gradstein et al. 2004; Zachos et al. 2001) and the 1st appearance of grasslands in Australia (Martin 2006). Late Miocene macropodines have yet to be found, but, as already mentioned, few Australian sites of this age are known.

Acknowledgments

I thank M. Springer and M. Nilsson for kindly providing me with molecular matrices. My particular gratitude goes to O. Bininda-Emonds, who carried out all of the RAxML analyses on my behalf. The perl scripts batchRAxML and bootStrip for automating RAxML analyses can be downloaded from his Web site (http://www2.uni-jena.de/∼b6biol2/). H. Godthelp, M. Archer, B. Cooke, and R. Voss provided extremely helpful information and advice, and Y. Gurovich assisted me in the preparation of the figures. V. Weisbecker, R. Tomlins, M. Hafner, and 2 anonymous reviewers gave insightful comments that have greatly improved this manuscript. Funding for this work is provided by the Leverhulme Trust through Study Abroad Studentship SAS/30110.

Literature Cited

Amrine-Madsen
H.
Scally
M.
Westerman
M.
Stanhope
M. J.
Krajewski
C. W.
Springer
M. S.
.
2003
.
Nuclear gene sequences provide evidence for the monophyly of australidelphian marsupials
.
Molecular Phylogenetics and Evolution
 
28
:
186
196
.
Aplin
K.
Archer
M.
.
1987
.
Recent advances in marsupial systematics with a new syncretic classification
. Pp.
xv
lxxii
in
Possums and opossums: studies in evolution
  (
Archer
M.
, ed.).
Surrey Beatty and Sons and the Royal Zoological Society of New South Wales
,
Sydney, New South Wales, Australia
.
Archer
M.
1982
.
Review of the dasyurid (Marsupialia) fossil record, integration of data bearing on phylogenetic interpretation, and suprageneric classification
. Pp.
397
443
in
Carnivorous marsupials
  (
Archer
M.
, ed.).
Royal Zoological Society of New South Wales
,
Mosman, New South Wales, Australia
.
Archer
M.
Wade
M.
.
1976
.
Results of the Ray E. Lemley expeditions, part I
.
The Allingham Formation and a new Pliocene vertebrate fauna from northern Australia. Memoirs of the Queensland Museum
 
17
:
379
398
.
Archer
M.
et al
.
1999
.
The evolutionary history and diversity of Australian mammals
.
Australian Mammalogy
 
21
:
1
45
.
Arena
D. A.
2004
.
The geological history and development of the terrain at the Riversleigh World Heritage Area during the middle Tertiary
.
Ph.D. dissertation
 ,
University of New South Wales
,
Sydney, New South Wales, Australia
.
Asher
R. J.
Horovitz
I.
Sanchez-Villagra
M. R.
.
2004
.
First combined cladistic analysis of marsupial mammal interrelationships
.
Molecular Phylogenetics and Evolution
 
33
:
240
250
.
Baker
M. L.
Wares
J. P.
Harrison
G. A.
Miller
R. D.
.
2004
.
Relationships among the families and orders of marsupials and the major mammalian lineages based on recombination activating gene-1
.
Journal of Mammalian Evolution
 
11
:
1
16
.
Bartholomai
A.
1978
.
Results of the Ray E. Lemley expeditions, part 2. The Macropodidae (Marsupialia) from the Allingham Formation, northern Queensland
.
Memoirs of the Queensland Museum
 
18
:
127
143
.
Beck
R. M. D.
Godthelp
H.
Archer
M.
Hand
S. J.
.
2006
.
“Ameridelphian” and crown australidelphian marsupials from the early Eocene of Australia
.
Symposium of Vertebrate Palaeontology and Comparative Anatomy
 ,
Paris, France
.
Benton
M. J.
Donoghue
P. C. J.
.
2007
.
Paleontological evidence to date the tree of life
.
Molecular Biology and Evolution
 
24
:
26
53
.
Brammall
J. R.
Archer
M.
.
1997
.
A new Oligo–Miocene species of Burramys (Marsupialia, Burramyidae) from Riversleigh, northwestern Queensland
.
Memoirs of the Queensland Museum
 
41
:
247
268
.
Cardillo
M.
Bininda-Emonds
O. R. P.
Boakes
E.
Purvis
A.
.
2004
.
A species-level phylogenetic supertree of marsupials
.
Journal of Zoology (London)
 
264
:
11
31
.
Case
J. A.
et al
.
2000
.
The first duck-billed dinosaur (family Hadrosauridae) from Antarctica
.
Journal of Vertebrate Paleontology
 
20
:
612
614
.
Case
J. A.
Goin
F. J.
Woodburne
M. O.
.
2005
.
“South American” marsupials from the Late Cretaceous of North America and the origin of marsupial cohorts
.
Journal of Mammalian Evolution
 
12
:
461
494
.
Cooper
A.
Fortey
R.
.
1998
.
Evolutionary explosions and the phylogenetic fuse
.
Trends in Ecology and Evolution
 
13
:
151
156
.
Crosby
K. M. L.
2004
.
Studies in the diversity and evolution of phalangeroid possums (Marsupialia; Phalangerida; Phalangeroidea)
.
Ph.D. dissertation
 ,
University of New South Wales
,
Sydney, New South Wales, Australia
.
Crosby
K. M. L.
Bassarova
M.
Archer
M.
Carbery
K.
.
2004
.
Fossil possums in Australasia: discovery, diversity and evolution
. Pp.
161
176
in
The biology of Australian possums and gliders
  (
Goldingray
R. L.
Jackson
S. M.
, eds.).
Surrey Beatty and Sons
,
Chipping Norton, New South Wales, Australia
.
De Laet
J.
Wheeler
W.
.
2003
.
POY version 3.0.11 (Wheeler, Gladstein, and De Laet, May 6, 2003). Command line documentation
 .
American Museum of Natural History
,
New York
.
Delsuc
F.
Vizcaíno
S. F.
Douzery
E. J. P.
.
2004
.
Influence of Tertiary paleoenvironmental changes on the diversification of South American mammals: a relaxed molecular clock study within xenarthrans
.
BMC Evolutionary Biology
 
4
:
11
.
Douady
C. J.
Douzery
E. J. P.
.
2003
.
Molecular estimation of eulipotyphlan divergence times and the evolution of “Insectivora.”
Molecular Phylogenetics and Evolution
 
28
:
285
296
.
Drummond
A. J.
Ho
S. Y. W.
Phillips
M. J.
Rambaut
A.
.
2006
.
Relaxed phylogenetics and dating with confidence
.
PLoS Biology
 
4
:
e88
.
Flannery
T. F.
Rich
T. H.
Turnbull
W. D.
Lundelius
E. L.
Jr.
1992
.
The Macropodoidea (Marsupialia) of the early Pliocene Hamilton local fauna, Victoria, Australia
.
Fieldiana: Geology
 
25
:
1
37
.
Godthelp
H.
Archer
M.
Cifelli
R. L.
Hand
S. J.
Gilkeson
C. F.
.
1992
.
Earliest known Australian Tertiary mammal fauna
.
Nature
 
356
:
514
516
.
Godthelp
H.
Wroe
S.
Archer
M.
.
1999
.
A new marsupial from the early Eocene Tingamarra Local Fauna of Murgon, southeastern Queensland: a prototypical Australian marsupial?
Journal of Mammalian Evolution
 
6
:
289
313
.
Goin
F. J.
1997
.
New clues for understanding Neogene marsupial radiations
. Pp.
187
206
in
Vertebrate paleontology in the Neotropics: the Miocene fauna of La Venta, Colombia
  (
Kay
R. F.
Madden
R. H.
Cifelli
R. L.
Flynn
J. J.
, eds.).
Smithsonian Institution Press
,
Washington, D.C
.
Goin
F. J.
et al
.
2006
.
The earliest Tertiary therian mammal from South America
.
Journal of Vertebrate Paleontology
 
26
:
505
510
.
Gradstein
F.
Ogg
J.
Smith
A.
.
2004
.
A geologic time scale 2004
 .
Cambridge University Press
,
Cambridge, United Kingdom
.
Hall
B. G.
Salipante
S. J.
.
2007
.
Measures of clade confidence do not correlate with accuracy of phylogenetic trees
.
PLOS Computational Biology
 
3
:
e51
.
Haq
B.
Hardenbol
J.
Vail
P.
.
1987
.
Chronology of fluctuating sea levels since the Triassic
.
Science
 
235
:
1156
1167
.
Horovitz
I.
Sanchez-Villagra
M. R.
.
2003
.
A morphological analysis of marsupial mammal higher-level phylogenetic relationships
.
Cladistics
 
19
:
181
212
.
Inoue
J. G.
Miya
M.
Venkatesh
B.
Nishida
M.
.
2005
.
The mitochondrial genome of Indonesian coelacanth Latimeria menadoensis (Sarcopterygii: Coelacanthiformes) and divergence time estimation between the two coelacanths
.
Gene
 
349
:
227
235
.
Jameson
D.
Gibson
A. P.
Hudelot
C.
Higgs
P. G.
.
2003
.
OGRe: a relational database for comparative analysis of mitochondrial genomes
.
Nucleic Acids Research
 
31
:
202
206
.
Jansa
S. A.
Voss
R. S.
.
2005
.
Phylogenetic relationships of the marsupial genus Hyladelphys based on nuclear gene sequences and morphology
.
Journal of Mammalogy
 
86
:
853
865
.
Ji
Q.
Luo
Z.-X.
Yuan
C.-X.
Wible
J. R.
Zhang
J.-P.
Georgi
J. A.
.
2002
.
The earliest known eutherian mammal
.
Nature
 
416
:
816
822
.
Johnson
W. E.
et al
.
2006
.
The late Miocene radiation of modern Felidae: a genetic assessment
.
Science
 
311
:
73
77
.
Kielan-Jaworowska
Z.
Cifelli
R. L.
Luo
Z.-X.
.
2004
.
Mammals from the age of dinosaurs: origins, evolution, and structure
 .
Columbia University Press
,
New York
.
Kirsch
J. A. W.
1968
.
Prodromus of the comparative serology of Marsupialia
.
Nature
 
217
:
418
420
.
Kirsch
J. A. W.
1977
.
The comparative serology of Marsupialia, and a classification of marsupials
.
Australian Journal of Zoology, Supplementary Series
 
52
:
1
152
.
Kirsch
J. A. W.
Lapointe
F.-J.
Springer
M. S.
.
1997
.
DNA-hybridization studies of marsupials and their implications for metatherian classification
.
Australian Journal of Zoology
 
45
:
211
280
.
Kishino
H.
Hasegawa
M.
.
1989
.
Evaluation of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data and the branching order Hominidae
.
Journal of Molecular Evolution
 
29
:
170
179
.
Kishino
H.
Thorne
J. L.
Bruno
W. J.
.
2001
.
Performance of a divergence time estimation method under a probabilistic model of rate evolution
.
Molecular Biology and Evolution
 
18
:
352
361
.
Long
J. A.
Archer
M.
Flannery
T. F.
Hand
S. J.
.
2002
.
Prehistoric mammals of Australia and New Guinea: one hundred million years of evolution
 .
UNSW Press
,
Sydney, New South Wales, Australia
.
Luo
Z.-X.
Ji
Q.
Wible
J. R.
Yuan
C.-X.
.
2003
.
An Early Cretaceous tribosphenic mammal and metatherian evolution
.
Science
 
302
:
1934
1940
.
Marshall
L. G.
1976
.
New didelphine marsupials from the La Venta fauna (Miocene) of Colombia, South America
.
Journal of Paleontology
 
50
:
402
418
.
Marshall
L. G.
de Muizon
C.
.
1988
.
The dawn of the age of mammals in South America
.
National Geographic Research
 
4
:
23
55
.
Martin
H. A.
2006
.
Cenozoic climatic change and the development of the arid vegetation in Australia
.
Journal of Arid Environments
 
66
:
533
563
.
Mercer
J. M.
Roth
V. L.
.
2003
.
The effects of Cenozoic global change on squirrel phylogeny
.
Science
 
299
:
1568
1572
.
Muirhead
J.
Filan
S.
.
1995
.
Yarala burchfieldi (Peramelemorphia) from Oligo–Miocene deposits of Riversleigh, northwestern Queensland
.
Journal of Paleontology
 
69
:
127
134
.
Muirhead
J.
Wroe
S.
.
1998
.
A new genus and species, Badjcinus turnbulli (Thylacinidae: Marsupialia), from the late Oligocene of Riversleigh, northern Australia, and an investigation of thylacinid phylogeny
.
Journal of Vertebrate Paleontology
 
18
:
612
626
.
de Muizon
C.
.
1991
.
La fauna de mamiferos de Tiupampa (Paleoceno Inferior, Formacion Santa Lucia), Bolivia
. Pp.
575
624
in
Fossils y facies de Bolivia. Vol. 1. Vertebrados
  (
Suarez-Soruco
R.
, ed.).
Revista Technica de Yacimientos Petroliferos Fiscales Bolivianos
,
Santa Cruz, Bolivia
.
de Muizon
C.
Cifelli
R. L.
.
2000
.
The “condylarths” (archaic Ungulata, Mammalia) from the early Palaeocene of Tiupampa (Bolivia): implications on the origin of the South American ungulates
.
Geodiversitas
 
22
:
47
150
.
Nilsson
M. A.
2006
.
Marsupial mitogenomics
.
Ph.D. dissertation
 ,
Lund University
,
Lund, Sweden
.
Nilsson
M. A.
Arnason
U.
Spencer
P. B. S.
Janke
A.
.
2004
.
Marsupial relationships and a timeline for marsupial radiation in South Gondwana
.
Gene
 
340
:
189
196
.
Nuttall
G. H. F.
1904
.
Blood immunity and blood relationship
 .
Cambridge University Press
,
Cambridge, United Kingdom
.
Nylander
J. A. A.
2004
.
MrModeltest v2. Program distributed by the author
 ,
Evolutionary Biology Centre, Uppsala University
,
Uppsala, Sweden
.
Nylander
J. A. A.
Ronquist
F.
Huelsenbeck
J. P.
Nieves-aldrey
J. L.
.
2004
.
Bayesian phylogenetic analysis of combined data
.
Systematic Biology
 
53
:
47
67
.
Oliveira
E. V.
Goin
F. J.
Candela
A. M.
.
1996
.
Un nuevo marsupial “pseudodiprotodonte” del Paleoceno Medio de Itaborai (Brasil)
.
Consideraciones sobre el origen, radiation y heterocronía en los Paucituberculata. Ameghiniana
 
33
:
468
.
Phillips
M. J.
McLenachan
P. A.
Down
C.
Gibb
G. C.
Penny
D.
.
2006
.
Combined mitochondrial and nuclear DNA sequences resolve the interrelations of the major Australasian marsupial radiations
.
Systematic Biology
 
55
:
122
137
.
Posada
D.
Buckley
T. R.
.
2004
.
Model selection and model averaging in phylogenetics: advantages of the AIC and Bayesian approaches over likelihood ratio tests
.
Systematic Biology
 
53
:
793
808
.
Queralt
R.
Adroer
R.
Oliva
R.
Winkfein
R. J.
Retief
J. D.
Dixon
G. H.
.
1995
.
Evolution of protamine P1 genes in mammals
.
Journal of Molecular Evolution
 
40
:
601
607
.
Raterman
D.
Meredith
R. W.
Ruedas
L. A.
Springer
M. S.
.
2006
.
Phylogenetic relationships of the cuscuses and brushtail possums (Marsupialia: Phalangeridae) using the nuclear gene BRCA1
.
Australian Journal of Zoology
 
54
:
353
361
.
Rokas
A.
Holland
P.
.
2000
.
Rare genomic changes as a tool for phylogenetics
.
Trends in Ecology and Evolution
 
15
:
454
459
.
Ronquist
F.
Huelsenbeck
J. P.
.
2003
.
MrBayes3: Bayesian phylogenetic inference under mixed models
.
Bioinformatics
 
19
:
1572
1574
.
Rose
K. D.
Emry
R. J.
Gaudin
T. J.
Storch
G.
.
2005
.
Xenarthra and Pholidota
. Pp.
106
126
in
The rise of placental mammals: origins and relationships of the major extant clades
  (
Rose
K. D.
Archibald
J. D.
, eds.).
Johns Hopkins University Press
,
Baltimore, Maryland
.
Rutschmann
F.
2005
.
Bayesian molecular dating using PAML/multidivtime: a step-by-step manual
 .
University of Zurich
,
Zurich, Switzerland
.
Sanderson
M. J.
Shaffer
H. B.
.
2002
.
Troubleshooting molecular phylogenetic analyses
.
Annual Review of Ecology and Systematics
 
33
:
49
72
.
Sarich
V.
Lowenstein
J. M.
Richardson
B. J.
.
1982
.
Phylogenetic relationships of Thylacinus cynocephalus (Marsupialia) as reflected in comparative serology
. Pp.
445
476
in
Carnivorous marsupials
  (
Archer
M.
, ed.).
Royal Zoological Society of New South Wales
,
Sydney, New South Wales, Australia
.
Shimodaira
H.
2002
.
An approximately unbiased test of phylogenetic tree selection
.
Systematic Biology
 
51
:
492
508
.
Shimodaira
H.
Hasegawa
M.
.
1999
.
Multiple comparisons of log likelihoods with applications to phylogenetic inference
.
Molecular Biology and Evolution
 
16
:
1114
1116
.
Shimodaira
H.
Hasegawa
M.
.
2001
.
CONSEL: for assessing the confidence of phylogenetic tree selection
.
Bioinformatics
 
17
:
1246
1247
.
Simpson
G. G.
1974
.
Notes on Didelphidae (Mammalia, Marsupialia) from the Huayquerian (Pliocene) of Argentina
.
American Museum Novitates
 
2559
:
1
15
.
Springer
M. S.
Kirsch
J. A. W.
.
1991
.
DNA hybridization, the compression effect, and the radiation of diprotodontian marsupials
.
Systematic Zoology
 
40
:
131
151
.
Springer
M. S.
Scally
M.
Madsen
O.
de Jong
W. W.
Douady
C. J.
Stanhope
M. J.
.
2004
.
The use of composite taxa in supermatrices
.
Molecular Phylogenetics and Evolution
 
30
:
883
884
.
Stamatakis
A.
2006
.
RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models
.
Bioinformatics
 
22
:
2688
2690
.
Steiner
C.
Tilak
M.-K.
Douzery
E. J. P.
Catzeflis
F. M.
.
2005
.
New DNA data from a transthyretin nuclear intron suggest an Oligocene to Miocene diversification of living South America opossums (Marsupialia: Didelphidae)
.
Molecular Phylogenetics and Evolution
 
35
:
363
379
.
Suzuki
Y.
Glazko
G. V.
Nei
M.
.
2002
.
Overcredibility of molecular phylogenies obtained by Bayesian phylogenetics
.
Proceedings of the National Academy of Sciences
 
99
:
16138
16143
.
Swofford
D. L.
2002
.
PAUP*: phylogenetic analysis using parsimony (* and other methods)
 ,
version 4.0b10
.
Sinauer Associates, Inc., Publishers
,
Sunderland, Massachusetts
.
Szalay
F. S.
1982
.
A new appraisal of marsupial phylogeny and classification
. Pp.
621
640
in
Carnivorous marsupials
  (
Archer
M.
, ed.).
Royal Zoological Society of New South Wales
,
Mosman, New South Wales, Australia
.
Szalay
F. S.
1994
.
Evolutionary history of the marsupials and an analysis of osteological characters
 .
Cambridge University Press
,
Cambridge, United Kingdom
.
Szalay
F. S.
Sargis
E. J.
.
2001
.
Model-based analysis of postcranial osteology of marsupials from the Palaeocene of Itaboraí (Brazil) and the phylogenetics and biogeography of Metatheria
.
Geodiversitas
 
23
:
139
302
.
Szalay
F. S.
Sargis
E. J.
.
2006
.
Cretaceous therian tarsals and the metatherian–eutherian dichotomy
.
Journal of Mammalian Evolution
 
13
:
171
210
.
Taylor
D. J.
Piel
W. H.
.
2004
.
An assessment of accuracy, error, and conflict with support values from genome-scale phylogenetic data
.
Molecular Biology and Evolution
 
21
:
1534
1537
.
Teeling
E. C.
Springer
M. S.
Madsen
O.
Bates
P.
O'Brien
S. J.
Murphy
W. J.
.
2005
.
A molecular phylogeny for bats illuminates biogeography and the fossil record
.
Science
 
307
:
580
584
.
Thorne
J. L.
Kishino
H.
Painter
I. S.
.
1998
.
Estimating the rate of evolution of the rate of molecular evolution
.
Molecular Biology and Evolution
 
15
:
1647
1657
.
Travouillon
K. J.
Archer
M.
Hand
S. J.
Godthelp
H.
.
2006
.
Multivariate analyses of Cenozoic mammalian faunas from Riversleigh, northwestern Queensland
.
Alcheringa Special Issue
 
1
:
323
349
.
Turnbull
W. D.
Lundelius
E. L.
Jr.
Archer
M.
.
2003
.
Dasyurids, perameloids, phalangeroids, and vombatoids from the early Pliocene Hamilton Fauna, Victoria, Australia
.
Bulletin of the American Museum of Natural History
 
279
:
513
540
.
van Rheede
T.
Bastiaans
T.
Boone
D. N.
Hedges
S. B.
de Jong
W. W.
Madsen
O.
.
2006
.
The platypus is in its place: nuclear genes and indels confirm the sister group relation of monotremes and therians
.
Molecular Biology and Evolution
 
23
:
587
597
.
Warburton
N. M.
2003
.
Functional morphology and evolution of marsupial moles (Marsupialia; Notoryctemorphia)
.
Ph.D. dissertation
 ,
University of Western Australia
,
Perth, Western Australia, Australia
.
Weisbecker
V.
Nilsson
M. A.
.
2006
.
Evolution of syndactyly in the marsupial foot: a morphometric and developmental reassessment
.
Journal of Vertebrate Paleontology
 
26
:
137A
.
Weymss
C. T.
1953
.
A preliminary study of marsupial relationships as indicated by the precipitin test
.
Zoologica (New York)
 
38
:
173
181
.
Woodburne
M. O.
Case
J. A.
.
1996
.
Dispersal, vicariance, and the Late Cretaceous to early Tertiary land mammal biogeography from South America to Australia
.
Journal of Mammalian Evolution
 
3
:
121
161
.
Wroe
S.
1999
.
The geologically oldest dasyurid (Marsupialia), from the Miocene Riversleigh, northwestern Queensland
.
Palaeontology
 
42
:
1
27
.
Yang
Z.
1997
.
PAML: a program package for phylogenetic analysis by maximum likelihood
.
Computer Applications in Biosciences
 
13
:
555
556
.
Zachos
J.
Pagani
M.
Sloan
L.
Thomas
E.
Billups
K.
.
2001
.
Trends, rhythms, and aberrations in global climate 65 Ma to present
.
Science
 
292
:
686
693
.

Appendix I

GenBank accession numbers for all gene sequences used in this analysis. All sequences and alignments except those for Thylacinus(which were added manually) are taken from Amrine-Madsen et al. (2003), Asher et al. (2004), and Nilsson et al. (2004). Abbreviations for gene names are given in text.

 APOB BRCA1 IRBP P1 PGK1 RAG1 VWF 12S rRNA 16S rRNA tRNA valine 12 mt protein-coding genes 
Ornithorhynchus    Z26849    X83427 X83427 X83427 X83427 
Tachyglossus    Z26848    AJ303116 AJ303116  AJ303116 
Eulipotyphla            
Erinaceus        X88898 X88898 X88898  
Talpa AY243373 AY121756    AF447515 AY121762     
Uropsilus   AY057831         
Xenarthra            
Bradypus AF548427 AF284002 U48708   AY243401 U31603     
Dasypus        Y11832 Y11832 Y11832 Y11832 
Burramyidae            
Cercatetus     AF011242       
Burramys        AF108223 AF108223 AF108223  
Caenolestes AY243418 AF355794 AF025381 L35332 AF011240 AY243384 AY243403 U61072 AF102808 U61072 AJ508400 
Dasyuroides    AJ508400    AF009888    
Dasyurus AY243430 AY243452 AY243439 L35341 AF011239 AY243398 AY243414 AF009890 AF166349 AF166349  
Dendrolagus AY243422  AY243435 AF187537 AF011237 AY243388  AF027990 AF027990 AF027990  
Didelphini            
Didelphis AF548432 AF497261 Z11814 L17007 AF011232  AF226848 Z29573 Z29573 Z29573 Z29573 
Lutreolina      AY243390      
Dorcopsis    AF187540    AF027995 AF027995 AF027995  
Dromiciops AY243423 AY243446 AF025384 L35449 AF011238 AY243389 AY243407 U61073 U97341 U61073 AJ508402 
Echymipera AY243420 AF355796 AF025383  AF011230 AY243386 AY243405 U97342 U97342 U97342  
Macropus  AF284033  L35447 AF011261  AJ224670 Y10524 Y10524 Y10524 Y10524 
Monodelphis AY243431 AY243453 AF257694 L35448 AF011260 U51897 AY243415 AF166346 AF166346 AF166346 AJ508398 
Notoryctes AY243424 AY243447 AF025385 L35446 AF011254 AY243391 AY243408 U61075 AF102810 U61075 AJ639874 
Peramelinae            
Isoodon     AF011227       
Perameles AY243426 AY243450 AY243437 L35305  AY243394 AY243411 AF166347 AF166347 AF166347 AJ639872 
Petauridae            
Dactylopsila     AF011235       
Petaurus AY243433 AY243455 AY243441   AY243400 AY243417 U21181    
Phalanger AF548431 AY243449 AY243436  AF011250 AY243393 AY243410 AF108222 AF108222 AF108222  
Phascogalinae            
Antechinus     AF011245       
Phascogale AY243427 AF355795 AF025382 L35327  AY243395 AY243412 U33497 AF102809 AF102809 AJ639869 
Phascolarctos AY243421 AY243445 AY243434 U87789  AY243387 AY243406 U61076 AF166344 U61076  
Pseudocheiridae            
Pseudocheirus  AY243448         AJ639870 
Pseudochirops AY243425  AF025387 L35334 AF011252 AY243392 AY243409 AF102812 AF102812 AF102812  
Thylacinus    U87140    U87405   M99452 (CYTBonly) 
Thylogale    AF187534 AF011266   AF027991 AF027991 AF027991  
Trichosurus    L32744    AF357238 AF357238 AF357238 AF357238 
Vombatus AY243429 AF284031 AF284031   AY243397 AF497260 NC_003322 NC_003322 NC_003322 AJ304828 
 APOB BRCA1 IRBP P1 PGK1 RAG1 VWF 12S rRNA 16S rRNA tRNA valine 12 mt protein-coding genes 
Ornithorhynchus    Z26849    X83427 X83427 X83427 X83427 
Tachyglossus    Z26848    AJ303116 AJ303116  AJ303116 
Eulipotyphla            
Erinaceus        X88898 X88898 X88898  
Talpa AY243373 AY121756    AF447515 AY121762     
Uropsilus   AY057831         
Xenarthra            
Bradypus AF548427 AF284002 U48708   AY243401 U31603     
Dasypus        Y11832 Y11832 Y11832 Y11832 
Burramyidae            
Cercatetus     AF011242       
Burramys        AF108223 AF108223 AF108223  
Caenolestes AY243418 AF355794 AF025381 L35332 AF011240 AY243384 AY243403 U61072 AF102808 U61072 AJ508400 
Dasyuroides    AJ508400    AF009888    
Dasyurus AY243430 AY243452 AY243439 L35341 AF011239 AY243398 AY243414 AF009890 AF166349 AF166349  
Dendrolagus AY243422  AY243435 AF187537 AF011237 AY243388  AF027990 AF027990 AF027990  
Didelphini            
Didelphis AF548432 AF497261 Z11814 L17007 AF011232  AF226848 Z29573 Z29573 Z29573 Z29573 
Lutreolina      AY243390      
Dorcopsis    AF187540    AF027995 AF027995 AF027995  
Dromiciops AY243423 AY243446 AF025384 L35449 AF011238 AY243389 AY243407 U61073 U97341 U61073 AJ508402 
Echymipera AY243420 AF355796 AF025383  AF011230 AY243386 AY243405 U97342 U97342 U97342  
Macropus  AF284033  L35447 AF011261  AJ224670 Y10524 Y10524 Y10524 Y10524 
Monodelphis AY243431 AY243453 AF257694 L35448 AF011260 U51897 AY243415 AF166346 AF166346 AF166346 AJ508398 
Notoryctes AY243424 AY243447 AF025385 L35446 AF011254 AY243391 AY243408 U61075 AF102810 U61075 AJ639874 
Peramelinae            
Isoodon     AF011227       
Perameles AY243426 AY243450 AY243437 L35305  AY243394 AY243411 AF166347 AF166347 AF166347 AJ639872 
Petauridae            
Dactylopsila     AF011235       
Petaurus AY243433 AY243455 AY243441   AY243400 AY243417 U21181    
Phalanger AF548431 AY243449 AY243436  AF011250 AY243393 AY243410 AF108222 AF108222 AF108222  
Phascogalinae            
Antechinus     AF011245       
Phascogale AY243427 AF355795 AF025382 L35327  AY243395 AY243412 U33497 AF102809 AF102809 AJ639869 
Phascolarctos AY243421 AY243445 AY243434 U87789  AY243387 AY243406 U61076 AF166344 U61076  
Pseudocheiridae            
Pseudocheirus  AY243448         AJ639870 
Pseudochirops AY243425  AF025387 L35334 AF011252 AY243392 AY243409 AF102812 AF102812 AF102812  
Thylacinus    U87140    U87405   M99452 (CYTBonly) 
Thylogale    AF187534 AF011266   AF027991 AF027991 AF027991  
Trichosurus    L32744    AF357238 AF357238 AF357238 AF357238 
Vombatus AY243429 AF284031 AF284031   AY243397 AF497260 NC_003322 NC_003322 NC_003322 AJ304828 

Appendix II

Unrepresented basal branch lengths (UBBLs—Teeling et al. 2005) of selected lineages, with fossils used to calculate UBBLs indicated. The UBBL value for a particular lineage is the proportion of the age of that lineage for which fossils are unknown. Age ranges are taken from Gradstein et al. (2004). Fossils are indicated on Fig. 4 by the letters in parentheses after the fossil names.

Lineage Earliest fossil Age (mya) Reference UBBL (%) 
Didelphimorphia Nortedelphysspp. (A) 66.55 (late Maastrichtian = 65.5–67.6) Case et al. 2005 17.4 
 IMG V and IMG XII (B) 58.95 (Itaboraian = 58.7–59.2) Szalay 1994 26.9 
Monodelphis Micoureus laventicus(C) 14.05 (Laventan–Friasian = 11.8–16.3) Marshall 1976; Goin 1997 68.4 
Didelphis Didelphis pattersoni(D) 5.4 (Montehermosan = 4–6.8) Simpson 1974 87.8 
Paucituberculata Glasbiusspp. (E) 66.55 (Late Maastrichtian = 65.5–67.6) Kielan-Jaworowska et al. 2004 13.0 
 Unnamed paucituberculate (F) 58.95 (Itaboraian = 58.7–59.2) Oliveira et al. 1996 22.9 
Microbiotheria Khasia cordillerensis(G) 59.8 (Tiupampan = 59.2–60.4) Marshall and Muizon 1988 11.3 
Peramelemorphia Yarala burchfieldi(H) 25.715 (late Oligocene = 23.03–28.4) Muirhead and Filan 1995 59.4 
Peramelidae Perameles allinghamensis(I) 3.615 (Allingham Formation = 3.6–3.63) Archer and Wade 1976 69.1 
Peroryctidae Cf. Peroryctesspp. (J) 4.46 (Hamilton Fauna = 4.46) Turnbull et al. 2003 61.9 
Notoryctemorphia Unnamed notoryctid (K) 19.5 (early Miocene = 15.97–23.03) Archer et al. 1999; Long et al. 2002 67.6 
Thylacinidae Badjcinus turnbulli(L) 25.715 (late Oligocene = 23.03–28.4) Muirhead and Wroe 1998 1.1 
Dasyuridae Barinya wangala(M) 19.5 (early Miocene = 15.97–23.03) Wroe 1999 25 
Phascogalinae Antechinussp. (N) 4.46 (Hamilton Fauna = 4.46) Archer 1982; Turnbull et al. 2003 61.6 
Dasyurus Cf. Dasyurussp. (O) 4.46 (Hamilton Fauna = 4.46) Turnbull et al. 2003 42.8 
Dasyuroides Dasyuroides achilpatna(P) 1.81 (late Pliocene–early Pleistocene = 1.81) Archer 1982 76.9 
Vombatidae Vombatoid spp. (Q) 25.715 (late Oligocene = 23.03–28.4) Archer et al. 1999; Long et al. 2002 36.8 
Phascolarctidae Phascolarctid spp. (R) 25.715 (late Oligocene = 23.03–28.4) Archer et al. 1999; Long et al. 2002 36.8 
Pseudocheiridae Pseudocheirid spp. (S) 25.715 (late Oligocene = 23.03–28.4) Archer et al. 1999; Long et al. 2002 20.6 
Petauridae Petaurid spp. (T) 25.715 (late Oligocene = 23.03–28.4) Archer et al. 1999; Long et al. 2002 20.6 
Macropodidae Macropodoid spp. (U) 25.715 (late Oligocene = 23.03–28.4) Archer et al. 1999; Long et al. 2002 45.4 
Dorcopsis Dorcopsis wintercookorum(V) 4.46 (Hamilton Fauna = 4.46) Flannery et al. 1992 73.3 
Macropus Macropus(Osphranter) pavana(W) 3.615 (Allingham Formation = 3.6–3.63) Bartholomai 1978 75.4 
Thylogale Thylogale ignis(X) 4.46 (Hamilton Fauna = 4.46) Flannery et al. 1992 66.0 
Dendrolagus Cf. Dendrolagussp. (Y) 4.46 (Hamilton Fauna = 4.46) Flannery et al. 1992 66.0 
Burramyidae Burramys brutyi(Z) 25.715 (late Oligocene = 23.03–28.4) Brammall and Archer 1997 35.7 
Trichosurini Unnamed trichosurins (AA) 25.715 (late Oligocene = 23.03–28.4) Crosby 2004 8.5 
Phalangerini Pleistocene phalangerins (AB) 0.955 (Pleistocene = 0.01–1.81) Crosby et al. 2004 96.6 
Lineage Earliest fossil Age (mya) Reference UBBL (%) 
Didelphimorphia Nortedelphysspp. (A) 66.55 (late Maastrichtian = 65.5–67.6) Case et al. 2005 17.4 
 IMG V and IMG XII (B) 58.95 (Itaboraian = 58.7–59.2) Szalay 1994 26.9 
Monodelphis Micoureus laventicus(C) 14.05 (Laventan–Friasian = 11.8–16.3) Marshall 1976; Goin 1997 68.4 
Didelphis Didelphis pattersoni(D) 5.4 (Montehermosan = 4–6.8) Simpson 1974 87.8 
Paucituberculata Glasbiusspp. (E) 66.55 (Late Maastrichtian = 65.5–67.6) Kielan-Jaworowska et al. 2004 13.0 
 Unnamed paucituberculate (F) 58.95 (Itaboraian = 58.7–59.2) Oliveira et al. 1996 22.9 
Microbiotheria Khasia cordillerensis(G) 59.8 (Tiupampan = 59.2–60.4) Marshall and Muizon 1988 11.3 
Peramelemorphia Yarala burchfieldi(H) 25.715 (late Oligocene = 23.03–28.4) Muirhead and Filan 1995 59.4 
Peramelidae Perameles allinghamensis(I) 3.615 (Allingham Formation = 3.6–3.63) Archer and Wade 1976 69.1 
Peroryctidae Cf. Peroryctesspp. (J) 4.46 (Hamilton Fauna = 4.46) Turnbull et al. 2003 61.9 
Notoryctemorphia Unnamed notoryctid (K) 19.5 (early Miocene = 15.97–23.03) Archer et al. 1999; Long et al. 2002 67.6 
Thylacinidae Badjcinus turnbulli(L) 25.715 (late Oligocene = 23.03–28.4) Muirhead and Wroe 1998 1.1 
Dasyuridae Barinya wangala(M) 19.5 (early Miocene = 15.97–23.03) Wroe 1999 25 
Phascogalinae Antechinussp. (N) 4.46 (Hamilton Fauna = 4.46) Archer 1982; Turnbull et al. 2003 61.6 
Dasyurus Cf. Dasyurussp. (O) 4.46 (Hamilton Fauna = 4.46) Turnbull et al. 2003 42.8 
Dasyuroides Dasyuroides achilpatna(P) 1.81 (late Pliocene–early Pleistocene = 1.81) Archer 1982 76.9 
Vombatidae Vombatoid spp. (Q) 25.715 (late Oligocene = 23.03–28.4) Archer et al. 1999; Long et al. 2002 36.8 
Phascolarctidae Phascolarctid spp. (R) 25.715 (late Oligocene = 23.03–28.4) Archer et al. 1999; Long et al. 2002 36.8 
Pseudocheiridae Pseudocheirid spp. (S) 25.715 (late Oligocene = 23.03–28.4) Archer et al. 1999; Long et al. 2002 20.6 
Petauridae Petaurid spp. (T) 25.715 (late Oligocene = 23.03–28.4) Archer et al. 1999; Long et al. 2002 20.6 
Macropodidae Macropodoid spp. (U) 25.715 (late Oligocene = 23.03–28.4) Archer et al. 1999; Long et al. 2002 45.4 
Dorcopsis Dorcopsis wintercookorum(V) 4.46 (Hamilton Fauna = 4.46) Flannery et al. 1992 73.3 
Macropus Macropus(Osphranter) pavana(W) 3.615 (Allingham Formation = 3.6–3.63) Bartholomai 1978 75.4 
Thylogale Thylogale ignis(X) 4.46 (Hamilton Fauna = 4.46) Flannery et al. 1992 66.0 
Dendrolagus Cf. Dendrolagussp. (Y) 4.46 (Hamilton Fauna = 4.46) Flannery et al. 1992 66.0 
Burramyidae Burramys brutyi(Z) 25.715 (late Oligocene = 23.03–28.4) Brammall and Archer 1997 35.7 
Trichosurini Unnamed trichosurins (AA) 25.715 (late Oligocene = 23.03–28.4) Crosby 2004 8.5 
Phalangerini Pleistocene phalangerins (AB) 0.955 (Pleistocene = 0.01–1.81) Crosby et al. 2004 96.6