Point of View

Syst. Biol. 00(0):1–13, 2015© The Author(s) 2015. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved.For Permissions, please email: journals.permissions@oup.comDOI:10.1093/sysbio/syv005

Ancestral State Reconstruction, Rate Heterogeneity, and the Evolution of Reptile Viviparity

BENEDICT KING1 AND MICHAEL S. Y. LEE2,3,∗1School of Biological Sciences, Flinders University, PO Box 2100, Adelaide, South Australia 5001; 2School of Biological Sciences, University of Adelaide,

Adelaide, South Australia 5005; and 3Earth Sciences Section, South Australian Museum, North Terrace, Adelaide 5000, Australia∗Correspondence to be sent to: School of Biological Sciences, University of Adelaide, Adelaide, South Australia 5005;

E-mail: Mike.Lee@samuseum.sa.gov.au.

Received 29 October 2014; reviews returned 22 December 2014; accepted 14 January 2015Associate Editor: Richard Glor

Abstract.—Virtually all models for reconstructing ancestral states for discrete characters make the crucial assumption thatthe trait of interest evolves at a uniform rate across the entire tree. However, this assumption is unlikely to hold in manysituations, particularly as ancestral state reconstructions are being performed on increasingly large phylogenies. Here, weshow how failure to account for such variable evolutionary rates can cause highly anomalous (and likely incorrect) results,while three methods that accommodate rate variability yield the opposite, more plausible, and more robust reconstructions.The random local clock method, implemented in BEAST, estimates the position and magnitude of rate changes on the tree;split BiSSE estimates separate rate parameters for pre-specified clades; and the hidden rates model partitions each characterstate into a number of rate categories. Simulations show the inadequacy of traditional models when characters evolve withboth asymmetry (different rates of change between states within a character) and heterotachy (different rates of characterevolution across different clades). The importance of accounting for rate heterogeneity in ancestral state reconstruction ishighlighted empirically with a new analysis of the evolution of viviparity in squamate reptiles, which reveal a predominanceof forward (oviparous–viviparous) transitions and very few reversals. [Ancestral state reconstruction; BEAST; BiSSE; discretecharacters; lizards; oviparity; rate heterogeneity; squamates; snakes; viviparity.]

The evolution of viviparity (live-birth, including“ovoviviparity”) from oviparity (egg-laying) has longbeen a topic of great scientific interest, particularly insquamate reptiles (lizards, snakes, and amphisbaenians),which show much greater lability in reproductive modethan do other amniotes. Studies have focused ona range of aspects including physiology, ecology,and evolutionary history (Blackburn 2000; Siteset al. 2011; Shine 2014). Viviparity is present at avariety of phylogenetic levels within squamates,including some reproductively bimodal species suchas Lerista bougainvillii (Qualls and Shine 1998) andSaiphos equalis (Smith et al. 2001). In most taxa,viviparity involves retention of shell-less eggs, withembryos sustained mainly by a large yolk. However,some skinks, including the South American genusMabuya, and the African genera Trachylepis and Eumecia,have chorioallantoic placentae convergent with thoseof eutherian mammals, allowing the embryos to besustained by direct transfer of nutrients across theplacenta rather than by the yolk (Blackburn et al. 1984;Blackburn and Flemming 2009).

One important aspect of the evolution of viviparityis the question of whether oviparity can evolvefrom viviparity. Oviparity has been assumed to beusually or invariably ancestral to viviparity, given thewide distribution of oviparity in amniotes and theidea that reversals to oviparity are unlikely due tothe need to re-evolve complex structures and enzymesinvolved in the deposition of egg-shell. There have

been numerous attempts to reconstruct parity modeevolution in a phylogenetic context. Blackburn (1982,1985) identified a minimum of 92 oviparity ⇒ viviparity(O ⇒ V) transitions, and noted that approximately 20%of squamate species are viviparous. Also noted was theheterogenous distribution of viviparous groups acrossthe phylogeny, with Scincidae, Iguanidae, Viperidae,and Anguidae containing a large proportion of theinferred origins of viviparity. These studies implicitlyused parsimony to identify the minimum numberof origins required by then-current taxonomy andphylogeny; they also did not seriously consider thepossibility of viviparity ⇒ oviparity (V ⇒ O) “reversals.”Fraipont et al. (1996) suggested that reversals werepossible and frequent, and indeed that egg guardingoften evolves from viviparity. However, this study wascriticized due to methodological problems (Blackburn1999; Shine and Lee 1999). A more explicitly phylogeneticstudy using parsimony to optimize reproductive modeonto a composite phylogeny (Lee and Shine 1998)identified five possible reversals, but noted that nonewere well supported, requiring only a small number ofextra steps to overturn. Until recently, the best evidenceof a V ⇒ O reversal was provided by the oviparouserycine snake Eryx jayakari, which is deeply nestedwithin viviparous species and further lacks the egg toothtypical of oviparous squamates (Lynch and Wagner2010).

The recent publication of the most comprehensivephylogenetic analysis of squamates to date (>4000

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species: Pyron et al. 2013) allowed a large-scale analysisof squamate parity mode evolution (Pyron and Burbrink2014). That analysis employed Binary State Speciationand Extinction (BiSSE) (Maddison et al. 2007). Thismodel has up to six parameters: independent speciationand extinction rates for taxa possessing each of thetwo character states, and independent forward andreverse rates between the two character states (i.e.,asymmetry). This allows ancestral state reconstructionwhile accounting for state-dependant diversification andextinction (e.g., viviparity might increase speciationrate). Surprisingly, the optimal model showed strongsupport for viviparity across many basal squamatenodes, and strong asymmetry, with huge numbers ofV ⇒ O “reversals” which outnumbered forward O ⇒V transitions. This was a particularly surprising andnovel conclusion, as it strongly contradicts entrenchedideas (Pyron and Burbrink 2014). It was acknowledged,however, that parsimony reconstructions yielded a verydifferent and more conventional pattern: later originsand few reversals.

Importantly, the BiSSE analyses—like most model-based comparative studies of discrete characters—assumed that rates of evolution of viviparity werehomogenous across squamates. However, analyses ofdiscrete characters are being performed on increasinglylarge phylogenies, where it is likely that evolutionaryrates will vary greatly between different clades (Beaulieuand O’Meara 2014). Although methods for identifyingevolutionary rate shifts in continuous characters haveattracted recent attention (e.g., Eastman et al. 2011;Stack et al. 2011; Rabosky 2014), analogous methodsfor discrete characters have only very recently beendeveloped (Beaulieu et al. 2013, Beaulieu and O’Meara2014) and have yet to be widely used. Similarly, therehave been few attempts to incorporate among-lineagerate heterogeneity (heterotachy) into ancestral statereconstructions of discrete characters (Skinner 2010;Beaulieu et al. 2013). The former applied a modelthat assumed rates were completely uncorrelated evenacross adjacent branches; our tests with the uncorrelatedlognormal clock in BEAST showed that such modelsessentially mimic parsimony, and cannot identify (forinstance) clades with accelerated rates of parity modeevolution. Yet, it is widely recognized that reproductivemode is more labile in some squamate clades than others(Blackburn 1982, 1985; Shine 1985). Here, we show thataccounting for this strong heterotachy in parity modeevolution across squamates gives a very different resultto standard BiSSE. Random local clock (RLC) modelsimplemented in BEAST, split BiSSE, and the hidden ratesmodel strongly reinstate oviparity as the ancestral statein basal squamate nodes, and oviparity ⇒ viviparityas the predominant transformation (∼115 origins ofviviparity). However, the analyses also robustly supportthe existence of a small number of reversals (inagreement with Pyron and Burbrink 2014), the bestsupported of which are Lachesis, E. jayakari, and Liolaemuscalchaqui.

MATERIALS AND METHODS

Bayesian Reconstructions Using RLC ModelsAncestral state reconstruction was first performed

in BEAST (Drummond et al. 2012). These analysesused the time-calibrated tree of 3951 species withreproductive mode data as in the previous study(Pyron and Burbrink 2014). In the BEAST xmlscript (Supplementary File S1, available on Dryadhttp://dx.doi.org/10.5061/dryad.cj2fg), topology andbranch lengths were fixed by setting this tree as thestarting tree and removing relevant operators, andparity mode was analyzed as an “alignment” of onecharacter. The analyses used a stochastic Mk model(Lewis 2001), with forward and reverse rates eitherassumed to be equal/symmetrical (Mk1) or allowed tobe unequal/asymmetrical and estimated (Mk2). Paritymode could then be analyzed with clock modelsnormally used in molecular phylogenetics (see below).Four independent runs of each analysis were performed,each of 100 or 200 million generations, with 1000 samplessaved. The prior on (mean) rate of evolution was set as anexponential distribution with mean of 0.00126 (the valueobtained by dividing the number of changes inferredby parsimony—116—by total branch length). This isdeliberately a rather uninformative (flat) prior, whichpermits very fast rates at relatively high probability; the95% upper bound entails three times as many changes(rate = 0.00378, ∼348 changes). To further ensureadequate exploration of “faster” rates, the starting valueof this parameter in each analysis was 0.1 (i.e., ∼79× themean prior). Further, increasing the rate prior 10-foldbarely changed the retrieved rates. Results were viewedin Tracer (Rambaut et al. 2014) and convergence of thefour runs confirmed by superimposition of likelihoodand posterior probability traces, and effective samplesize (ESS) of >100 for all parameters. We recordedthe total number of forward and reverse transitions,the branch on which each transition occurred in eachMCMC sample, as well as the ratio of forward:reverseevolutionary rates, ancestral state for each node, andlocal clock rate for each branch (see below). The postburn-in samples from the four runs were combined toproduce the consensus tree, and associated distributionsof the above parameters. Bayes factors (sensu Kass andRaftery 1995) for alternative models were calculatedby comparing marginal likelihood estimated using thestepping stone method (Xie et al. 2011) as implementedin BEAST 1.8.

(1) First, a strict clock was used, thereby enforcing ahomogenous rate of trait evolution across all branches;an asymmetric model—permitting different relativerates for forward (O ⇒ V) and reverse (V ⇒ O)transitions—was favored.

(2) The RLC was then used (Drummond and Suchard2010) to accommodate heterotachy, thus relaxing theassumption of a homogenous rate across all branches;the number, phylogenetic position, and magnitude ofrate changes are estimated using MCMC. All RLC

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analyses were supported over the strict clock by Bayesfactors. The focal analysis had an exponential priorof mean 1 on the number of rate changes (thusfavoring few rate changes), and a gamma prior on thedistribution of relative rates (shape 0.5 and scale 2;thus favoring smaller rate changes, which were equallylikely to be either accelerations or decelerations). Thisprior (which places most weight on fewer, smaller ratechanges) will favor results more similar to a strictclock, and is thus conservative in this context (i.e.,testing for the effects of relaxing the strict clock). Threeadditional analyses with different priors on the numberand magnitude of rate changes were also performed,details of which are given as Supplementary File S2on Dryad. The priors in analysis 2 were deliberatelypermissive of large numbers of rate changes. Onefurther analysis, with another set of priors, was runfor 500 million generations as it appeared to be cyclingslowly between two very different likelihood peaks (seeDiscussion).

The xml file for the focal analysis, includingthe stepping-stone calculations, is included asSupplementary File S1 (Dryad); the other analysesrequire simple changes to relevant parameters inthis file.

Likelihood and Bayesian Reconstructions Using Split BiSSETo make our results directly comparable with Pyron

and Burbrink (2014), reproductive mode evolution wasinferred using the Binary State Speciation and Extinctionmodel (Maddison et al. 2007), a six-parameter modelthat estimates state-dependent speciation, extinction,and character transition rates. The data have previouslybeen analyzed using standard BiSSE (Pyron andBurbrink 2014); we repeated this analysis, confirming thesurprising conclusions: an early origin of viviparity andmultiple reversals to oviparity (see Results).

We then used split BiSSE (FitzJohn 2012), whichpermits particular clades, selected a priori, to havedifferent rates of trait evolution compared with their“background.” Appropriate clades were identified bythe position of large rate shifts in the consensus treefrom the focal BEAST analysis (see Results), and tested invarious combinations. These analyses were performedusing the R package Diversitree (FitzJohn 2012). Thesplit BiSSE models were constrained such that only traittransition rates (O ⇒ V and V ⇒ O) varied across theclades, while state-dependent speciation and extinctionrates were homogenous across the whole phylogeny.Alternative root states were weighted according to therelative probabilities of generating the observed datafrom that root state, given the model parameters andtree (FitzJohn et al. 2009). The best-fit model was alsotested with equal weighting of both root states, but thishad no effect on parameter estimation (SupplementaryTable S3).

In addition to the standard maximum-likelihoodanalyses, the best-fit model was also run in aBayesian framework using the MCMC function in

Diversitree, with an exponential prior of rate=(1/(2 ∗ state-independent diversification rate)) on allparameters. Four independent runs of 1500 generationswere performed, with convergence confirmed bysuperimposition of likelihood and posterior probabilitytraces, and ESS of >1000 for all parameters. The postburn-in samples for the four runs were combined forsummary statistics.

The Hidden Rates ModelThe hidden rates model (Beaulieu et al. 2013) is another

method that accommodates heterotachy in ancestralstate reconstruction. This model divides each characterinto a number of rate classes (known as “hidden states”).In contrast to the previous two methods, it does notspecifically identify clades with different rates, althoughthis is implicit in rate category assignment. We analyzedthe same tree and data using this model in the R packagecorHMM (Beaulieu et al. 2013). Models with between twoand five rate categories for each state were analyzed andcompared using AIC.

SimulationsThe BEAST RLC has been tested on molecular data

and found to yield highly consistent results (Drummondand Suchard 2010). However, as this method representsa novel approach to inferring ancestral states for discretebinary characters, simulations were carried out toassess its performance. Trait evolution incorporatingasymmetry and/or heterotachy was carried out in Rusing the phytools, geiger, and ape packages (Paradiset al. 2004; Harmon et al. 2008; Revell 2012; see DryadSupplementary File S4). Four sets of five replicatesimulations were analyzed, each with simulated treesof 500–600 taxa (tips) and a height of five time units,and an increase in trait evolution rate occurring at arandom node that had between 200 and 300 descendenttaxa (“fast clade”). The four sets were as follows: (1)As a control, simulations with only asymmetry intransition rates: forward rate 0.2, backward rate 0.01; (2)heterotachy only: 0.005 forward and backward rate, withan increase in the “fast clade” to 0.2; (3) heterotachyand asymmetry: 0.005 forward and 0.00025 backwardrate, with an increase in the “fast clade” to 0.2 forwardrate and 0.01 backward rate; (4) heterotachy and variableasymmetry, that is, the degree of asymmetry differingin the fast clade compared with the background: 0.005forward and 0.001 backward rate, with a rate increaseto 0.2 forward rate and 0.01 backward rate. The lastmodel is more complex than any available BEAST model,and was done to assess performance when the real dataare more complex than the RLC model allows. Thesimulated character states were exported and analyzedin BEAST using: (1) a strict clock with no asymmetry(Mk1: simplest model); (2) strict clock with asymmetryestimated (Mk2: the “correct” model for simulation set1); (3) RLC with no asymmetry (RLC+Mk1, “correct”

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model for simulation set 2); and (4) RLC with asymmetryconstant but estimated (RLC+Mk2, “correct” model forsimulation set 3, and nearest model for set 4). Meanevolutionary rate had a deliberately flat, uninformativeprior (exponential with mean 0.01). Convergence of runswas assessed as before, with two runs of each analysisbeing performed due to computational demands. Tocompare BEAST with traditional likelihood methods,ancestral state reconstructions were also performed onthe simulated character states using the ace function inAPE (Paradis et al. 2004), with both equal rates (Mk1) andunequal rates (Mk2) models. Note that some simulationreplicates gave results that were trivial to reconstruct(e.g., a shift to viviparity near the base of the tree typicallyresulted in a single large clade of viviparous taxa and avery straightforward optimization under all methods);we thus analyzed five non-trivial replicates for each ofthe four simulation scenarios. Models were comparedusing Bayes factors for the BEAST models (with marginallikelihoods calculated using the stepping stone method,Xie et al. 2011), and likelihood ratio tests for the acemodels.

The performance of each ancestral state reconstructionwas assessed qualitatively. After viewing the results, itwas found that each analysis could be clearly placed inone of three categories: (1) those in which there wasstrong support for the incorrect root state; (2) correctroot state but reconstruction inaccurate, in general thisinvolved strong support for the derived state at basalnodes within the fast clade, and incorrect estimates ofdirection of asymmetry (Supplementary Table S4); (3)reconstruction accurate, with the correct state at basalnodes in the fast clade, and the correct estimates ofdirection of asymmetry. In Table 3, those reconstructionsin the last category are highlighted by shading.

RESULTS

Bayesian Reconstructions Using RLC ModelsAssuming a strict clock on parity mode evolution—

that is, a homogenous rate across the tree resulted ina reconstruction consistent with Pyron and Burbrink(2014). An asymmetrical model with separate forward(O ⇒ V) and reverse (V ⇒ O) rates was favored overa symmetrical model with equal forward and reverserates (Bayes factor 32.8 sensu Kass and Raftery 1995). Inthe favored model, V ⇒ O “reversals” evolve at 6.9×the rate of O ⇒ V forward transitions (SupplementaryFig. S1 on Dryad). Accordingly, across the sampled trees,approximately 89.7 V ⇒ O reversals were reconstructed,compared with only approximately 56.7 O ⇒ Vtransitions. There is an early evolution of viviparity insquamates (above dibamids and gekkotans); however,support for either ancestral state was equivocal inall basal squamate nodes (Supplementary Fig. S2). Apossible explanation is that high rates of trait evolutionin particular clades elevated the estimated “tree-wide”rate, resulting in uncertainty in reconstructions in deepernodes (see Discussion).

Implementing a RLC—and thus accommodatingheterotachy—further improved model fit (Bayes factor80.24 over the asymmetrical rate model) and alsochanged the inferred pattern drastically (Fig. 1). Thefocal RLC analysis robustly restores oviparity as theancestral state in the common ancestor of squamates (pp= 0.9997) and in all basal squamate nodes (pp >0.99).The evolutionary rate of forward (O ⇒ V) transitionsgreatly exceeds the reverse rate (ratio = 5.56:1), inaccordance with conventional views. Accordingly, theabsolute numbers of these transitions exhibit a similarratio. There are an average of 118.73 forward transitionsin the sampled trees, with origins of viviparityreconstructed on 115 branches in the consensus tree forthe focal analysis (2 in Gekkota, 39 in Scincoidea, 3 inLacertoidea, 8 in Anguimorpha, 26 in Iguania, and 37in Serpentes). Note that this does not include originswithin reproductively bimodal species, which had tobe treated as unknown due to constraints in BEAST.The majority of these 115 branches have an origin with>0.5 posterior probability; however, origins with pp <0.5can still feature in the consensus reconstruction whenuncertainty in reconstruction causes a change in paritymode to be sampled across a large number of successivebranches (see Supplementary Table S1 caption forfurther discussion). Supplementary Table S1 on Dryadsummarizes each of these 115 origins. In contrast, thereis an average of 11.65 reversals, and only 6 branches areconsistently (pp >0.5; see Table 1) reconstructed withreversals: all are in liolaemids and snakes (Booidea andviperids): Liolaemus calchaqui, L. chiliensis, Anomochilusleonardi, Eryx Jayakari, Calabaria reinhardtii and Lachesis.Other reversals with lower support (pp <0.5) are alsomostly in these clades (Liolaemus platei, L. reichei, andTrimeresurus borneensis) except for one in Trachylepis(Scincidae). All six well-supported reversals potentiallyoccur within a relatively narrow time “window” afterthe preceding origin of viviparity (see Discussion).

The focal RLC analysis converged on a mean of12.87 shifts in evolutionary rate (95% HPD = 7–17).The consensus tree reveals certain clades have greatlyelevated rates of trait evolution (Fig. 2). The fastest ratesare within Sceloporus (∼0.0145, i.e., 1.45% probabilityof change per lineage per million years) and Liolaemus(∼0.0109) and are an order of magnitude faster thanthe mean rate across the tree (∼0.00125). Both generahave previously been suggested as being highly labilefor reproductive mode (Benabib et al. 1997; Schulteet al. 2000; Lambert and Wiens 2013; Pincheira-Donosoet al. 2013). Other groups with fast rates are: Scincoidea,Anguimorpha, Alethinophidia (excluding Colubridaesensu lato), and Viperidae.

The other three BEAST analyses were implementedwith different priors on the number and magnitude ofrate shifts. Priors that were more permissive regardingthe number of rate changes essentially allowed extrasmaller-scale changes, which did not change the overallpattern. The fastest rates were always identified inthe same six clades, there was a preponderance offorward transitions over reversals, and all basal nodes

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0 50 Ma100 Ma150 Ma200 Ma

Squamata

Gekkota

Scincoidea

Lacertoidea

Anguimorpha

Iguania

Serpentes

Oviparous

Viviparous

FIGURE 1. Reproductive mode in squamate reptiles, as reconstructed by Bayesian methods accommodating heterogeneity in evolutionaryrates across different clades (heterotachy). Consensus tree from BEAST random local clock analysis. Branch color represents the most probable(pp >0.5) reproductive mode in the descendant node; the tree reveals a preponderance of forward (oviparity ⇒ viviparity) and few reverse(viparity ⇒ oviparity) changes. A higher-resolution electronic version of this figure, with names and reproductive states for terminal taxa, isavailable on Dryad (Fig. 1 expanded).

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TABLE 1. List of candidate viviparity ⇒ oviparity reversals, based on the consensus tree of the BEAST analyses with the following statistics:number of sampled species, mean posterior probability of the reversal over the four main BEAST analyses, and minimum and maximum inferredduration that each lineage was viviparous before the reversal in the focal analysis (see main text)

Number of mean PP over four Min time viviparous (Ma): Max time viviparous (Ma):species BEAST analyses focal analysis focal analysis

Liolaemus chiliensis 1 0.5961 2.5 15Liolaemus calchaqui 1 0.8665 1.2 7.9Calabaria reinhardtii 1 0.4789 1.9 78.1Eryx jayakari 1 0.9414 22.1 78.1Anomochilus leonardi 1 0.5487 10.8 72.94Lachesis 2 0.9890 8.7 26.1

Notes: Strongly supported reversals (PP >0.5 in all four analyses) are in bold. The exact parameters of the four BEAST analyses are in SupplementaryFile S2.

in squamates were robustly reconstructed as oviparous.In addition, the individual reversals identified aboveappeared in each analysis, although only Lachesis,E. jayakari, and L. calchaqui have posterior probability ofa reversal >0.5 across all four analyses.

One further BEAST RLC analysis (DryadSupplementary File S2, analysis 5) suggested theexistence of two optimality peaks (SupplementaryFig. S3): each of the four runs spent some time samplingone optimum with fewer (∼4) rate changes and a biastoward V ⇒ O reversals, but three of the four runseventually favored a slightly higher optimum withmore (∼9) rate changes and a bias toward forwardO ⇒ V transitions. Because of slow cycling betweenthese optima, this analysis cannot be considered tohave converged. However, it is consistent with theresults of the other BEAST analyses using strict clockand the random local clock: assuming less (or no)rate heterogeneity in parity mode evolution favorsreconstructions with a preponderance of V ⇒ Oreversals.

Likelihood and Bayesian Reconstructions Using Split BiSSEStandard BiSSE reconstructed an early origin of

viviparity in squamates and preponderance of V ⇒O “reversals”, exactly as previously proposed (Pyronand Burbrink 2014). However, split BiSSE models,which accommodate heterotachy by permitting different(prespecified) clades to have different evolutionary ratesfor parity mode, gave very different reconstructions.

The tested model with the best AIC supportallowed all the following clades to have separaterates of parity mode evolution (compared with theirbackground rate): Scincidae, Anguimorpha, Sceloporus(subclade bracketed by Sceloporus grammicus andS. adleri), Liolaemidae (Phymaturus–Liolaemus subclade),Alethinophidia, “Henophidia” (Booidea of Pyron et al.[2013] plus Bolyeriidae), and Viperidae. Clade-specificevolutionary rates retrieved in this analysis were highlycongruent with results from the BEAST RLC analysis. Inall partitions the rate of O ⇒ V transitions was higherthan the rate of V ⇒ O reversals (Table 2). The rate ofV ⇒ O reversals is extremely low (<0.00001 changes

per million years, effectively zero) in all clades exceptliolaemids, “henophidian,” and viperid snakes. Theseclades were the only clades in the BEAST analysis toshow V ⇒ O reversals with any degree of support.Setting these parameters, as well as the extinctionparameters, to 0 (Table 2) in a likelihood run has noeffect on model fit or estimation of the remaining freeparameters. In addition, a Bayesian analysis of thesame split BiSSE model shows that estimates for theseparameters abut against zero (Supplementary Fig. S4).

Repeating the split BiSSE analyses with alternativecombinations of clades revealed two alternative patterns(Fig. 3): models with a greater number of split clades,a bias toward O ⇒ V transitions, and strong support,versus models with fewer split clades, a bias toward V⇒ O reversals and weaker support. The results in Figure3 therefore fall into two clusters, with AIC values thatdo not overlap. These seem to reflect two optimality“peaks” similar to those suggested by one of the BEASTanalyses: a higher peak (with a greater number of rateshifts, and a preponderance of O ⇒ V transitions),and a slightly lower peak (with fewer or no rate shiftsand a preponderance of V ⇒ O reversals). Table 2summarizes the results from four key models. Detailsof the other models used are shown in SupplementaryTable S2.

As in Pyron and Burbrink (2014) there is support forhigher speciation rate in viviparous lineages, althoughthere is no evidence for higher extinction rates. Trait-dependent speciation rate parameters are thereforenot very sensitive to different ancestral reconstructionsand different estimated rates and symmetries of traitevolution. However, we hesitate to draw conclusionsfrom this result due to the problems associated withassuming homogenous diversification dynamics acrosstrees with incomplete taxon sampling (Rabosky 2010;Quental and Marshall 2010; Stadler and Bokma 2013)and diversification asymmetries driven by factors otherthan the trait under analysis (Rabosky and Goldberg2015). BiSSE furthermore has problems estimatingextinction rates and can retrieve unrealistically low rates(Maddison et al. 2007; Davis et al. 2013) with speciationestimates thus representing a greatly time-averagedapproximation of net diversification.

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0.0145 (Sceloporus)0.0001(Gekkota)

0.001 0.01

Viperidae

Liolaemidae

Sceloporus

subclade

Anguimorpha

Alethinophidia

Scincoidea

Mean rate across posterior sample

“Henophidia”

200 Ma 150 Ma 100 Ma 50 Ma 0

FIGURE 2. Among-lineage variability in rates of evolution (heterotachy) of reproductive mode in squamates. Consensus tree from BEASTrandom local clock analysis colored according to rate; seven major clades/grades with rates different to their “background” are identified. Fastestrates are in a Sceloporus subclade and Liolaemus, and are an order of magnitude faster than the overall rate in squamates. A higher-resolutionelectronic version of this figure, with names and reproductive states for terminal taxa, is available on Dryad (Fig. 2 expanded). Exact rates for allbranches are presented in Dryad file S3, viewable in Figtree (Rambaut 2014).

Ancestral State Reconstruction Using theHidden Rates Model

Use of four or five rate categories in the hidden ratesmodel produced a reconstruction broadly similar to theresults from the BEAST RLC analysis, with oviparity as

the ancestral state for squamates and a preponderanceof forward transitions. In contrast, use of only two orthree categories led to a reconstruction with a viviparousancestor and numerous reversals to oviparity. AICsupported the use of extra rate classes, and therefore anoviparous ancestor (AIC = 1149.03, 1009.845, 991.28, and

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TABLE 2. Comparison of model parameters and likelihood for the best-fit split BiSSE model (seven split clades, 20 parameters), anothersplit BiSSE model (5 split clades, 16 parameters), and the standard BiSSE (0 split clades, 6 parameters) used by Pyron and Burbrink (2014)

Model Best-fit split BiSSE Five clade split BiSSE Standard BiSSE Best-fit split BiSSE with(background and (background and (background only, certain parametersseven split clades) five split clades) 0 split clades) set to 0

dF 20 16 6 13−LnL 16488.23 16497.15 16573.26 −16,488.27�AIC 0 9.84 142.06 −13.92Speciation rate O 6.22e−2 6.21e−2 6.26e−2 6.23e−2Speciation rate V 7.33e−2 7.37e−2 8.56e−2 7.32e−2Extinction rate O 2.40e−7 2.48e−7 3.05e−7 0Extinction rate V 1.80e−6 2.36e−5 2.84e−2 0Background squamates: O ⇒ V 2.45e−4 2.37e−4 7.07e−4 2.46e−4Background squamates: V ⇒ O 1.66e−7 8.44e−8 5.84e−3* 0Scinciodea: O ⇒ V 5.24e−3 5.21e−3 5.20e−3Scinciodea: V ⇒ O 4.26e−6 4.61e−9 0Anguimorpha: O ⇒ V 4.31e−3 4.33e−3 4.33e−3Anguimorpha: V ⇒ O 5.73e−6 4.98e−6 0Sceloporus: O ⇒ V 3.96e−2 3.94e−2 4.05e−2Sceloporus: V ⇒ O 2.84e−3 3.54e−3 0Liolaemidae: O ⇒ V 1.80e−2 1.80e−2 1.80e−2Liolaemidae: V ⇒ O 1.05e−2 1.06e−2 1.05e−2Alethinophidia: O ⇒ V 1.50e−3 1.28e−3 1.51e−3Alethinophidia: V ⇒ O 4.19e−7 5.89e−3* 0“Henophidia”: O ⇒ V 3.42e−3 3.43e−3“Henophidia”: V ⇒ O 2.44e−3 2.45e−3Viperidae: O ⇒ V 1.55e−2 1.56e−2Viperidae: V ⇒ O 1.12e−3 1.12e−3

Notes: The predominant direction of change is in bold. *V ⇒ O reversals predominate: it can be seen that a bias toward reversals in Alethinophidiain the model with five split clades can be overturned by further isolating two clades of snakes that exhibit high rates of parity mode evolution(model with seven split clades). The fourth column shows that setting extinction rates and all V ⇒ O rates except Liolaemidae, “Henophidia”and Viperidae to 0 reduces the number of parameters with no effect on model fit.

1000.697 for 2, 3, 4, and 5 rate categories, respectively).Supplementary Figure S5 shows the result for fourrate categories. This further supports the conclusionthat incorporating heterotachy improves the accuracy ofancestral state reconstructions of squamate parity mode.

Simulation StudiesSummaries of the performance of each method in

the simulations are shown in Table 3 for BEAST andSupplementary Table S5 for ace. Figure 4 shows thesimulated character states and BEAST ancestral statereconstructions for one example where the simulationhad both asymmetry and heterotachy. Full results for allthe simulations are in the Supplementary Information(File S5).

In the case where simulations were performedwith only asymmetry in forward/backward rate andno heterotachy, Mk2 models which incorporate thisparameter (in ace, BEAST strict clock, BEAST randomlocal clock) outperformed Mk1 models, as expected.However, in one simulation both the BEAST strictclock Mk2 and the BEAST RLC Mk2 models producedincorrect reconstructions, although ace mk2 performedwell. All three Mk1 models always assigned the incorrectroot state, likely because the high rates of evolution in thesimulations led to most tips having the derived state.

Simulations involving only heterotachy and noasymmetry were found to cause significant problems

to those models (incorrectly) utilizing the Mk2model (which estimates asymmetry): ace-Mk2 alwaysreconstructed the incorrect root state, whereas theBEAST strict clock Mk2 model did so in three out offive cases. The presence of heterotachy in the data,but asymmetry in the reconstructing model, meansthe model tries to explain the rate heterogeneity byincorrectly applying extreme asymmetry. For example,the variability in parity mode in the fast clade—generated by rapid changes in both directions in thesimulations—is instead explained by (1) a high rateof reversals relative to forward transitions and (2)reconstructing the derived state at the base of thefast clade, with multiple reversals in this clade. Thisidea is supported by the estimated asymmetry forthe BEAST strict clock Mk2 model in the three caseswhere reconstructions are inaccurate (0.07, 0.04, 0.08—i.e., strong bias toward reversals) compared with thetwo cases where they are better (0.44, 1.38—i.e., closerto equality). The ace Mk2 models also estimate veryhigh asymmetry in all five cases (between 0.024 and0.089). Further evidence is provided in SupplementaryFigure S6 and the accompanying discussion. In addition,the branches between the root and the fast clade areoften also reconstructed with the derived state in amanner completely at odds with parsimony, but closelyresembling the parity mode reconstruction in Pyron andBurbrink (2014). Despite the inaccurate reconstructionsfor these Mk2 models, the extra parameter was strongly

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-1 0 1 2 3 4 5

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0BiSSE model support vs. transition rate biasshows support for models with more O V transitions

forward/reverse bias in squamates (background partition)

supp

ort -

dA

IC

six parameter standard BiSSE model (no split clades)

model

forward transitions (O->V) favouredreversals (V->O)

favoured

FIGURE 3. The results for 14 split BiSSE models (different numbersand combinations of clades chosen) as well as standard BiSSE. Here,model support (�AIC) is plotted against the bias in transition rateparameters. Transition rate bias is calculated as log(rate of O ⇒ Vtransition/rate of V ⇒ O reversals) for the “background” partition.The best-supported model has �AIC of 0, a greater �AIC meanslower support. The results fall into two groups: (1) lower right-shadedquadrant—models with a bias toward O ⇒ V forward transitions andhigher support and (2) upper left-shaded quadrant—those modelswhich have a bias toward V ⇒ O reversals and lower support. Thearrows point to the best-supported model in our analysis (with sevenclade-specific rates: Table 2), and to the standard BiSSE model, whichassumes a uniform rate across all squamates (Pyron and Burbrink 2014).Since there is no overlap in �AIC of the two quadrants, this providesstrong support for oviparity as the ancestral state and O ⇒ V as thepredominant transition.

supported statistically in these cases (likelihood ratiotests for ace and Bayes factors for BEAST strict clock).Only the BEAST-RLC-Mk1 model (which most closelymatched the simulation model) produced accuratereconstructions for all five simulations. The BEAST-RLC-Mk2 model produced good reconstructions for three outof five simulations, but in one case was subject to thesame problem found for the other Mk2 models: highestimated asymmetry and incorrect assignment of thederived state to basal nodes.

For simulations involving both asymmetry andheterotachy, the BEAST RLC Mk2 model producedaccurate reconstructions in four out of five cases. Forthese four, the BEAST RLC Mk2 model is stronglyfavored over the other BEAST models (Bayes factors).In the case where it performed badly, it appears thatthe simulation resulted in almost all the tips in the fastclade being in the derived state, causing all the modelsto be equally inaccurate. In three out of the four casesin which the BEAST RLC Mk2 model is accurate, allthe other models perform badly. In one case however,those using the Mk2 model perform equally well,suggesting the simulated heterotachy has had little effect

in this instance. Figure 4 shows the reconstructionsfor one example under these simulation conditions.Figure 4e shows that correct reconstructions are onlyachieved when both asymmetry and heterotachy areparameterized.

The results for the most complex simulations (set 4)—in which the degree of asymmetry differs between thebackground and the fast clade—resemble those in whichthe degree of asymmetry is the same (set 3). This suggeststhat, at least under certain conditions, the random localclock model can perform well even in cases where thecharacter has evolved in a manner more complex thanthe model allows. In all five cases, the BEAST RLC Mk2model produces accurate reconstructions. Bayes factorssupport the RLC Mk2 model over the other BEASTmodels in all five cases. The other models are alwaysinaccurate, apart from one case (out of five replicates) inwhich the BEAST strict clock Mk2 model performs well.

Finally, we note that in all simulations showingheterotachy, the random local clock was able toaccurately identify the fast clade. However, thedegree of heterotachy was always underestimated,with rates overestimated in the background clade andunderestimated in the fast clade (by approximately afactor of 2).

Results from this series of simulations suggest twomain conclusions:

1. When rates of character evolution differ across thetree (i.e., heterotachy), incorrect use of a modelallowing only unequal rates of forward and reversetransitions (i.e., asymmetry) can cause seriousproblems. Heterotachy will be accommodated bya combination of asymmetrical rates (i.e., highrates of reversals) and incorrect placement of lotsof “fast” transitions (i.e., reversals) in the fastclade. Despite these highly inaccurate ancestralstate reconstructions, models with asymmetricalrates will be strongly supported statistically overmodels with symmetrical rates.

2. When the data show both asymmetry andheterotachy, only a model that incorporates both ofthese factors is able to produce accurate ancestralreconstructions. In 7 out of 10 cases, all modelsperformed poorly apart from the BEAST RLC Mk2model.

DISCUSSION

Reversibility of Viviparity: Rare But PresentThe well-supported and highly congruent results from

three rather different methods provide strong evidencethat oviparity characterized all basal nodes withinsquamates, and that reversals are infrequent. Thesemethods all allow rates of trait evolution to vary acrossclades (heterotachy), an assumption that makes intuitivesense and is supported statistically in this particularinstance. However, when a homogenous rate is insteadassumed across the tree, models that allow asymmetry

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TABLE 3. Performance of four different ancestral state reconstruction models on simulated data with different conditions of asymmetry(forward–reverse bias) and among-lineage rate heterogeneity (heterotachy), showing model support (numbers) and quality of ancestral statereconstruction (shading)

Notes: Numbers are negative log marginal likelihoods. Shaded cells are those models that produced an accurate ancestral state reconstruction, asshown by comparison with the simulation. Unshaded cells represent inaccurate reconstructions. Bold denotes the optimal model(s) under Bayesfactors: the best-fit model and any model within two log-likelihood units of this. The black boxes surround the models in which the parametersmatch those of the simulation, or in the case of Simulations 16–20, are the closest match. It is clear that when both asymmetry and heterotachyare present in the data, an accurate ancestral state reconstruction requires both of these effects to be parameterized (i.e., random local clock Mk2).

reconstruct a preponderance of “reversals” (Pyron andBurbrink 2014). Simulations generate results consistentwith the view that the latter conclusions are artifacts ofan inappropriate model.

These analyses support the conventional view thatviviparity evolves from oviparity and reversals arerare, but also support a small number of reversals(in agreement with Pyron and Burbrink 2014). Suchreversals suggest that the loss of structures during theevolution of viviparity may initially involve switching offrelevant genetic pathways while still preserving them.Reversals may be possible for a finite time window afterthe evolution of viviparity, before these pathways havebeen irreversibly degraded by mutation. As a minimumestimate, the six candidate V ⇒ O reversals occur withina 25 Ma time window after the origin of viviparity,although longer intervals are possible. However even25 Ma is longer than most estimates for the length oftime required to silence a gene through neutral evolution(Marshall et al. 1994; Lynch and Conery 2000), althoughthese estimates do not factor in the likely existence ofpleiotropy for many genes (Collin and Miglietta 2008).

It should be noted that these reversals are onlystrongly supported under the assumed tree topology.Uncertainty in the topology of trees assembled from

supermatrices with extensive missing data is well-documented (Sanderson et al. 2011; Simmons andGoloboff 2014). However the highly nested positions ofLachesis and E. jayakari within oviparous groups are alsosupported by finer scale analyses (Lynch and Wagner2010; Fenwick et al. 2012). This is not the case forL. calchaqui, which was not found to represent a reversalin a recent analysis due to differences in topology(Pincheira-Donoso et al. 2013).

An intriguing observation is the low species diversityin the oviparous clades resulting from each putativereversal, suggesting reversals are not a pathway todiversification. A possible explanation is that reversalsare “incomplete” in that not all of the advantages ofoviparity can be immediately regained. Such initialconstraints may limit the success of lineages that resultfrom a reversion to oviparity, even in the habitats inwhich oviparity is selectively beneficial. Eryx jayakari, forexample, has been proposed to have evolved oviparityas an adaptation to extremely arid deserts (Lynch andWagner 2010). Eryx jayakari has not regained the eggtooth (Lynch and Wagner 2010) and this may constrainother aspects of reproductive biology such as egg-shellthickness, which is very thin in E. jayakari. It is thereforepossible that the small number of reversals, and the small

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A) Simulated

ancestral states

B) BEAST strict clock Mk1 reconstruction C) BEAST strict clock Mk2 reconstruction

D) BEAST random local clock Mk1 reconstruction E) BEAST random local clock Mk2 reconstruction

rate

increase

0 . 9 40 . 9 8

0 . 9 5

0 . 9 9

0 . 9 9

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10 . 7 30 . 7 4

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0 . 9 6

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FIGURE 4. Simulated data and reconstructions under different models, for simulation 11. a) Simulated data with both asymmetry andheterotachy: a bias toward forward (blue/oviparous to red/viviparous) transitions, and an increase in transition rates occurring at the yellow star.b–e) Ancestral state reconstructions under four different BEAST models, which permit (b) neither asymmetry or heterotachy, (c) only asymmetry,(d) only heterotachy, and (e) both asymmetry and heterotachy. Only the last model (e) accurately reconstructs ancestral states. Notably, model (c)reconstructs incorrect states for all basal nodes in the “fast clade” and infers the wrong direction of asymmetry (preponderance of viviparous–oviparous “reversals”). The branch labels refer to the posterior probability of the reconstructed parity mode at a few key nodes. Each numberrefers to the node at the younger (right-hand) end of the branch.

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clades resulting from them, is due to the interactionof both ecological factors as well as developmentalconstraints.

Fast Rates of Reproductive Mode Evolution: EcologicalCorrelates and Importance for Comparative Methods

Comparative analyses of trait evolution derive greaterstatistical power from larger phylogenies, permittingmore independent contrasts. However, traits are unlikelyto evolve at a homogenous rate across large swathesof the tree of life, yet the majority of comparativeanalyses of discrete traits make this assumption. If acharacter is evolving rapidly in one part of the tree,but very slowly in other parts, a model assuming aconstant rate of evolution is likely to reconstruct anintermediate rate which does not match either true rate,leading to uncertain and/or erroneous reconstructionsof ancestral states and forward–reverse ratios. Wehere demonstrate the importance of incorporatingheterotachy into ancestral state reconstruction. Certainsquamate clades are highly labile in reproductive mode(e.g., Sceloporus and Liolaemus are an order of magnitudefaster than typical squamates), and including thisvariable dramatically changes inferences of the evolutionof reproductive mode. Notably, parsimony analyseseffectively permit infinite heterotachy (Tuffley and Steel1997): accordingly parsimony reconstructions of thisdata set also retrieve a pattern of late origins of viviparityand a preponderance of forward changes (Pyron andBurbrink 2014).

The rate homogeneity assumption may be problematicin the case of parity mode, as discrete states arebeing applied to what is arguably a continuum.For example, Zootoca vivipara, which is reproductivelybimodal, shows thicker eggshells and longer incubationtimes in Italian and Slovenian oviparous populationscompared with French oviparous populations (Heulinet al. 2002). Clades nearer the boundary of oviparity andviviparity are likely to show higher rates of transitions.Few squamates lay eggs at a developmental stageintermediate between the eggs of typical oviparousspecies (about stage 30) and the neonates of viviparousspecies (stage 40) (Blackburn 1995). However exceptionsare found in Sceloporus, oviparous members of which canexhibit facultative egg retention (Mathies and Andrews1996; Calderón-Espinosa et al. 2006), consistent withSceloporus showing the highest rates of parity modeevolution in our analysis. The threshold model (Revell2014) is therefore an appealing fit for the evolution ofviviparity. However, it was found to be computationallyunfeasible on this data set.

Clades that inhabit regions conducive to the evolutionof viviparity (e.g., temperate or mountainous regions[Shine 1985]) would also be expected to have elevatedrates of parity mode evolution. In particular, groupsthat can readily disperse between adjacent high and lowaltitude regions could be expected to have elevated ratesof parity mode evolution. Indeed, this appears to be the

case in Liolaemus in the Andes (Schulte et al. 2000) andSceloporus in North America (e.g., Mathies and Andrews1995).

It is here shown that heterotachy poses majorchallenges for ancestral state reconstruction. This isan important and underexplored area, at least fordiscrete characters. Researchers performing ancestralstate reconstructions on large-scale phylogenies shouldbe vigilant for the warning signs that their analyseshave been affected by the artifacts discussed in thisarticle, including radical departures from parsimonyand biological orthodoxy, reconstruction of a rootstate that is scored for the minority of tips, andobservable patterns in tip states which indicate strongheterotachy. Particular caution should be exercised whenapplying models that ignore heterotachy and onlyallow asymmetry: such models may attempt to explainpatterns caused by heterotachy with the only parameteravailable, asymmetry.

SUPPLEMENTARY MATERIAL

Supplementary material, including data files, can befound in the Dryad data repository (http://dx.doi.org/10.5061/dryad.cj2fg).

FUNDING

This work was supported by the Australian ResearchCouncil (to M.S.Y.L.).

ACKNOWLEDGMENTS

The authors thank e-Research SA for grid computingfacilities, A. Pyron and F. Burbrink for providing us witha timely copy of their study, R. Fitzjohn and L. Revell forhelp with R, F. Anderson, R. Glor, S. Lambert, and twoanonymous reviewers for comments and suggestions onthe manuscript.

REFERENCES

Beaulieu J.M., O’Meara B.C., Donoghue M.J. 2013. Identifying hiddenrate changes in the evolution of a binary morphological character:the evolution of plant habit in campanulid angiosperms. Syst. Biol.62:725–737.

Beaulieu J.M., O’Meara B.C. 2014. Hidden Markov models for studyingthe evolution of binary morphological characters. In: GaramszegiL.Z., editor. Modern phylogenetic comparative methods and theirapplication in evolutionary biology. Berlin: Springer. p. 395–408.

Benabib M., Kjer K.M., Sites J.W. 1997. Mitochondrial DNA sequence-based phylogeny and the evolution of viviparity in the Sceloporusscalaris group (Reptilia, Squamata). Evolution 51:1262–1275.

Blackburn D.G. 1982. Evolutionary origins of viviparity in the reptilia.I. Sauria. Amphib. Reptil. 3:185–205.

Blackburn, D.G. 1985. Evolutionary origins of viviparity in the Reptilia.II. Serpentes, Amphisbaenia, and Ichthyosauria. Amphib. Reptil.6:259–291.

Blackburn D.G. 1995. Saltationist and punctuated equilibrium modelsfor the evolution of viviparity and placentation. J. Theor. Biol.174:199–216.

Blackburn D.G. 1999. Are viviparity and egg-guarding evolutionarilylabile in squamates? Herpetologica 55:556–573.

at Flinders University of South A

ustralia Library on A

pril 6, 2015http://sysbio.oxfordjournals.org/

Dow

nloaded from

2015 POINT OF VIEW 13

Blackburn D.G. 2000. Reptilian viviparity: past research, futuredirections, and appropriate models. Comp. Biochem. Physiol. AMol. Integr. Physiol. 127:391–409.

Blackburn D.G., Flemming A.F. 2009. Morphology, development, andevolution of fetal membranes and placentation in squamate reptiles.J. Exp. Zool. B Mol. Dev. Evol. 312:579–589.

Blackburn D.G., Vitt L.J., Beuchat C.A. 1984. Eutherian-likereproductive specializations in a viviparous reptile. Proc. Natl.Acad. Sci. USA. 81:4860–4863.

Calderón-Espinosa M.L., Andrews R.M., Cruz F.R.M. de la2006. Evolution of egg retention in the Sceloporus spinosusgroup: exploring the role of physiological, environmental, andphylogenetic factors. Herpetol. Monogr. 20:147–158.

Collin R., Miglietta M.P. 2008. Reversing opinions on Dollo’s Law.Trends Ecol. Evol. 23:602–609.

Davis M.P., Midford P.E., Maddison W. 2013. Exploring power andparameter estimation of the BiSSE method for analyzing speciesdiversification. BMC Evol. Biol. 13:38.

Drummond A.J., Suchard M.A. 2010. Bayesian random local clocks, orone rate to rule them all. BMC Biol. 8:114.

Drummond A.J., Suchard M.A., Xie D., Rambaut A. 2012. Bayesianphylogenetics with BEAUti and the BEAST 1.7. Mol. Biol. Evol.29:1969–1973.

Eastman J.M., Alfaro M.E., Joyce P., Hipp A.L., Harmon L.J. 2011.A novel comparative method for identifying shifts in the rate ofcharacter evolution on trees. Evolution 65:3578–3589.

Fenwick A.M., Greene H.W., Parkinson C.L. 2012. The serpent andthe egg: unidirectional evolution of reproductive mode in vipers?J. Zool. Syst. Evol. Res. 50:59–66.

FitzJohn R.G. 2012. Diversitree: comparative phylogenetic analyses ofdiversification in R. Methods Ecol. Evol. 3:1084–1092.

FitzJohn R.G., Maddison W.P., Otto S.P. 2009. Estimating trait-dependent speciation and extinction rates from incompletelyresolved phylogenies. Syst. Biol. 58:595–611.

Fraipont M. de, Clobert J., Barbault R. 1996. The evolution ofoviparity with egg guarding and viviparity in lizards and snakes: aphylogenetic analysis. Evolution 50:391–400.

Harmon L.J., Weir J.T., Brock C.D., Glor R.E., Challenger W. 2008.GEIGER: investigating evolutionary radiations. Bioinformatics24:129–131.

Heulin B., Ghielmi S., Vogrin N., Surget-Groba Y., Guillaume C.P. 2002.Variation in eggshell characteristics and in intrauterine egg retentionbetween two oviparous clades of the lizard lacerta vivipara: insightinto the oviparity–viviparity continuum in squamates. J. Morphol.252:255–262.

Kass R.E., Raftery A.E. 1995. Bayes factors. J. Am. Stat. Assoc.90:773–795.

Lambert S.M., Wiens J.J. 2013. Evolution of viviparity: a phylogenetictest of the cold-climate hypothesis in phrynosomatid lizards.Evolution 67:2614–2630.

Lee M.S.Y., Shine R. 1998. Reptilian viviparity and Dollo’s law.Evolution 52:1441–1450.

Lewis P.O. 2001. A likelihood approach to estimating phylogeny fromdiscrete morphological character data. Syst. Biol. 50:913–925.

Lynch M., Conery J.S. 2000. The evolutionary fate and consequencesof duplicate genes. Science 290:1151–1155.

Lynch V.J., Wagner G.P. 2010. Did egg-laying boas break Dollo’s law?Phylogenetic evidence for reversal to oviparity in sand boas (Eryx:Boidae). Evolution 64:207–216.

Maddison W.P., Midford P.E., Otto S.P. 2007. Estimating a binarycharacter’s effect on speciation and extinction. Syst. Biol. 56:701–710.

Marshall C.R., Raff E.C., Raff R.A. 1994. Dollo’s law and the death andresurrection of genes. Proc. Natl. Acad. Sci. USA 91:12283–12287.

Mathies T., Andrews R.M. 1995. Thermal and reproductive biology ofhigh and low elevation populations of the lizard Sceloporus scalaris:implications for the evolution of viviparity. Oecologia 104:101–111.

Mathies T., Andrews R.M. 1996. Extended egg retention and itsinfluence on embryonic development and egg water balance:implications for the evolution of viviparity. Physiol. Zool.69:1021–1035.

Paradis E., Claude J., Strimmer K. 2004. APE: analyses of phylogeneticsand evolution in R language. Bioinformatics 20:289–290.

Pincheira-Donoso D., Tregenza T., Witt M.J., Hodgson D.J. 2013. Theevolution of viviparity opens opportunities for lizard radiationbut drives it into a climatic cul-de-sac. Glob. Ecol. Biogeogr. 22:857–867.

Pyron R.A., Burbrink F.T. 2014. Early origin of viviparity andmultiple reversions to oviparity in squamate reptiles. Ecol. Lett.17:13–21.

Pyron R.A., Burbrink F.T., Wiens J.J. 2013. A phylogeny and revisedclassification of Squamata, including 4161 species of lizards andsnakes. BMC Evol. Biol. 13:93.

Qualls C.P., Shine R. 1998. Lerista bougainvillii, a case study for theevolution of viviparity in reptiles. J. Evol. Biol. 11:63–78.

Quental T.B., Marshall C.R. 2010. Diversity dynamics: molecularphylogenies need the fossil record. Trends Ecol. Evol. 25:434–441.

Rabosky D.L. 2010. Extinction rates should not be estimated frommolecular phylogenies. Evolution 64:1816–1824.

Rabosky D.L. 2014. Automatic detection of key innovations, rateshifts, and diversity-dependence on phylogenetic trees. PLoS One9:e89543.

Rabosky D.L., Goldberg E.E. 2015. Model inadequacy and mistakeninferences of trait-dependent speciation. Syst. Biol. 64:340–355.

Rambaut A. 2014. Figtree v.1.4.2. Available from: URL http://tree.bio.ed.ac.uk/software/figtree/.

Rambaut A., Suchard M.A., Xie D., Drummond A.J. 2014. Tracer v1.6,Available from http://beast.bio.ed.ac.uk/Tracer.

Revell L.J. 2012. phytools: an R package for phylogenetic comparativebiology (and other things). Methods Ecol. Evol. 3:217–223.

Revell L.J. 2014. Ancestral character estimation under the thresholdmodel from quantitative genetics. Evolution 68:743–759.

Sanderson M.J., McMahon M.M., Steel M. 2011. Terraces inphylogenetic tree space. Science 333:448–450.

Schulte J.A.S. II, Macey J.R., Espinoza R.E., Larson A. 2000.Phylogenetic relationships in the iguanid lizard genus Liolaemus:multiple origins of viviparous reproduction and evidence forrecurring Andean vicariance and dispersal. Biol. J. Linn. Soc.69:75–102.

Shine R. 1985. The evolution of viviparity in reptiles: an ecologicalanalysis. Biol. Reptil. 15:605–694.

Shine R. 2014. Evolution of an evolutionary hypothesis: a history ofchanging ideas about the adaptive significance of viviparity inreptiles. J. Herpetol. 48:147–161.

Shine R., Lee M.S.Y. 1999. A reanalysis of the evolution ofviviparity and egg-guarding in squamate reptiles. Herpetologica55:538–549.

Simmons M.P., Goloboff P.A. 2014. Dubious resolution and supportfrom published sparse supermatrices: the importance of thoroughtree searches. Mol. Phylogenet. Evol. 78:334–348.

Sites J.W., Reeder T.W., Wiens J.J. 2011. Phylogenetic insights onevolutionary novelties in lizards and snakes: sex, birth, bodies,niches, and venom. Annu. Rev. Ecol. Evol. Syst. 42:227–244.

Skinner A. 2010. Rate heterogeneity, ancestral character statereconstruction, and the evolution of limb morphology in Lerista(Scincidae, Squamata). Syst. Biol. 59:723–740.

Smith S.A., Austin C.C., Shine R. 2001. A phylogenetic analysis ofvariation in reproductive mode within an Australian lizard (Saiphosequalis, Scincidae). Biol. J. Linn. Soc. 74:131–139.

Stack J.C., Harmon L.J., O’Meara B. 2011. RBrownie: an R packagefor testing hypotheses about rates of evolutionary change. MethodsEcol. Evol. 2:660–662.

Stadler T., Bokma F. 2013. Estimating speciation and extinction ratesfor phylogenies of higher taxa. Syst. Biol. 62:220–230.

Tuffley C., Steel M. 1997. Links between maximum likelihood andmaximum parsimony under a simple model of site substitution.Bull. Math. Biol. 59:581–607.

Xie W., Lewis P.O., Fan Y., Kuo L., Chen M.-H. 2011. Improving marginallikelihood estimation for Bayesian phylogenetic model selection.Syst. Biol. 60:150–160.

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pril 6, 2015http://sysbio.oxfordjournals.org/

Dow

nloaded from