Molecular Phylogenetics and Evolution 84 (2015) 254–265

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Molecular Phylogenetics and Evolution

journal homepage: www.elsevier .com/locate /ympev

Molecular phylogenetics and species delimitation of leaf-toed geckos(Phyllodactylidae: Phyllodactylus) throughout the Mexican tropical dryforest

http://dx.doi.org/10.1016/j.ympev.2015.01.0031055-7903/� 2015 Elsevier Inc. All rights reserved.

⇑ Corresponding author. Present Address: Department of Biological Sciences, NewYork City College of Technology, The City University of New York, 300 Jay Street,Brooklyn, NY 11201, USA.

E-mail addresses: CBlair@citytech.cuny.edu, blair.chr@gmail.com (C. Blair).

Christopher Blair a,b,⇑, Fausto R. Méndez de la Cruz c, Christopher Law d, Robert W. Murphy a,b

a Department of Ecology and Evolutionary Biology, University of Toronto, 25 Willcocks Street, Toronto, Ontario M5S 3B2, Canadab Department of Natural History, Royal Ontario Museum, 100 Queen’s Park, Toronto, Ontario M5S 2C6, Canadac Laboratorio de Herpetología, Instituto de Biología, Universidad Nacional Autónoma de México, A.P. 70-153, C.P. 04510, Mexicod Department of Integrative Biology, Science Complex, University of Guelph, Guelph, Ontario N1G 2W1, Canada

a r t i c l e i n f o a b s t r a c t

Article history:Received 29 June 2014Revised 7 January 2015Accepted 9 January 2015Available online 22 January 2015

Keywords:BayesianBiogeographyLizardMexicoPhylogenySpeciation

Methods and approaches for accurate species delimitation continue to be a highly controversial subject inthe systematics community. Inaccurate assessment of species’ limits precludes accurate inference of his-torical evolutionary processes. Recent evidence suggests that multilocus coalescent methods show prom-ise in delimiting species in cryptic clades. We combine multilocus sequence data with coalescence-basedphylogenetics in a hypothesis-testing framework to assess species limits and elucidate the timing ofdiversification in leaf-toed geckos (Phyllodactylus) of Mexico’s dry forests. Tropical deciduous forests(TDF) of the Neotropics are among the planet’s most diverse ecosystems. However, in comparison tomoist tropical forests, little is known about the mode and tempo of biotic evolution throughout thisthreatened biome. We find increased speciation and substantial, cryptic molecular diversity originatingfollowing the formation of Mexican TDF 30–20 million years ago due to orogenesis of the Sierra MadreOccidental and Mexican Volcanic Belt. Phylogenetic results suggest that the Mexican Volcanic Belt, theRio Fuerte, and Isthmus of Tehuantepec may be important biogeographic barriers. Single- and multilocuscoalescent analyses suggest that nearly every sampling locality may be a distinct species. These resultssuggest unprecedented levels of diversity, a complex evolutionary history, and that the formation andexpansion of TDF vegetation in the Miocene may have influenced subsequent cladogenesis of leaf-toedgeckos throughout western Mexico.

� 2015 Elsevier Inc. All rights reserved.

1. Introduction

Accurate species delimitation continues to pose a major chal-lenge for systematics and evolutionary research (Bauer et al.,2011; Carstens et al., 2013; Fujita and Leaché, 2011). This difficultyis exacerbated by the fact that many ‘‘good’’ species possess highlyconserved morphological features leading to the commonly usedterm ‘cryptic species’ (Leaché and Fujita, 2010). Timely and accu-rate species delimitation is becoming increasingly important asanthropogenic and climatic forces threaten the evolutionary trajec-tories of taxa (Sinervo et al., 2010), particularly in megadiverse bio-mes (Myers et al., 2000). Our current challenge is thus to identifyevolutionary processes and patterns of biodiversity before

extinctions eliminate species before we can discover and describethem. Molecular data have become an important staple in thisregard, with the continual ease in which these data can be gath-ered. For example, diagnostic molecular barcodes can often be usedas a rapid means to discover diversity (Hebert et al., 2003). How-ever, sole reliance on a short fragment of a single mitochondrialgene with taxa-specific cut-off divergence values can be fraughtwith issues for species delimitation, particularly when goals andhypotheses are not explicitly stated (Collins and Cruickshank,2013).

The emergence of multilocus DNA sequence data sets, genome-enabled marker development, and novel statistical methods arerevolutionizing biological systematics (Blair and Murphy, 2011;Lemmon et al., 2012). New methods of phylogenetic inferenceaccount for discordance between gene trees and species trees(Heled and Drummond, 2008; Kubatko et al., 2009; Liu, 2008)and use more realistic models to estimate the timing of lineagedivergence (Drummond et al., 2006). Multilocus algorithms can

C. Blair et al. / Molecular Phylogenetics and Evolution 84 (2015) 254–265 255

also estimate demographic history (Heled and Drummond, 2008),estimate effective population sizes and asymmetric migrationrates (Beerli, 2006; Beerli and Felsenstein, 2001), and delimit spe-cies (Yang and Rannala, 2010,2014). These new statistical methodsformulate and test hypotheses pertaining to the historical forcesthat shaped the evolutionary histories of species and populations(Knowles, 2009; Knowles and Carstens, 2007).

Historically, mitochondrial DNA (mtDNA) was the marker ofchoice for examining spatial patterns of lineage divergence in clo-sely related groups. However, sole reliance on mtDNA for extrapo-lating population history is problematic (Barrowclough and Zink,2009; Edwards and Bensch, 2009). Whereas analyses based onmtDNA resolve matrilineal histories only, nuclear DNA (nDNA)data provide evidence of paternal contributions to gene flow andevolutionary history. However, nDNA genes have larger effectivepopulation sizes than mtDNA resulting in longer coalescence timesand concomitantly higher levels of incomplete sorting of ancestralpolymorphisms in recently diverged groups (Degnan andRosenberg, 2006, 2009). As support for relationships in individualnuclear gene trees tends to be low, a larger number of nDNA locimay be required to obtain the same level of signal found withmtDNA (Lee and Edwards, 2008). This realization is responsiblefor the rapid growth of theory and computational methods thatestimate species or population trees versus gene trees (Edwardsand Beerli, 2000; Edwards, 2009; Knowles, 2009). However, rela-tively few studies have utilized these techniques in Neotropicallowland taxa (e.g. Brumfield et al., 2008; Brunes et al., 2010).

The tropical deciduous forests (TDF), or dry forests, of the Neo-tropics are home to an extraordinary diversity of species (Ceballosand Garcia, 1995; García, 2006; Gillespie et al., 2000). Unlike trop-ical rainforests, TDF has a distinct seasonality with up to 8 monthsof dry, arid-like conditions separated by 4 months of deluge(Murphy and Lugo, 1986). This seasonality causes many plants tolose their leaves in a similar fashion to the vegetation of temperatedeciduous forests. It is hypothesized that the TDF of Mexico origi-nated sometime between 30 and 20 million years ago (Ma) due tothe further orogenesis of two of Mexico’s major montane systems,the Sierra Madre Occidental and the Mexican Volcanic Belt (MVB;Becerra, 2005). These mountain chains effectively block the flow ofcolder northern air masses allowing the TDF to expand throughoutmuch of western Mexico and Middle America. Further, diversifica-tion analyses of the tree genus Bursera, a conspicuous member ofTDF, indicate an increased diversification rate between 20 and7.5 Ma (Becerra, 2005) suggesting that this window may be partic-ularly important for shaping populations and communities withinMexican TDF.

Although Neotropical dry forests are a diversity hotspot (Myerset al., 2000), the drivers of diversification throughout this biomeremain largely unknown (Werneck et al., 2011). Recent empiricalanalyses conflict as to the role played by Pleistocene climatic shiftsin shaping diversification patterns in lowland Neotropical species(Klicka and Zink, 1997; Weir, 2006; Weir and Schluter, 2004;Zarza et al., 2008; Zink et al., 2004). Some alternative perspectivesmay be due to the employment of different statistical methods.These results also suggest that additional studies are required totest for the influence of Quaternary climatic shifts on rates and pat-terns of cladogenesis.

How TDF responded to climatic fluctuations of the Pleistoceneremains uncertain. Early studies suggested that during the Pleisto-cene TDF encompassed a much broader distribution that subse-quently fragmented as temperature and precipitation levelsincreased during the Pleistocene–Holocene transition(Pennington et al., 2000). This hypothesis partly explains the frag-mented distributions of several plants and animals restricted tothese forests. Conversely, recent evidence from paleodistributionalmodeling suggests that the distribution of TDF was much more

disjunct during the Last Glacial Maximum than today (Wernecket al., 2011). Fortunately, it is likely that genetic signatures datingto this time period are present in species largely restricted to thisecosystem.

Recent molecular phylogenetic and phylogeographic studies inMexico focus predominantly on patterns and processes of speciesinhabiting highland pine and pine-oak habitats and suggest a dualeffect of Neogene vicariance and Pleistocene climatic change (e.g.Bryson et al., 2011a,b; Bryson et al., 2012a,b). The few empiricalstudies that focus on genetic patterns of species throughout thelowlands of western Mexico report cryptic lineages (e.g. Devitt,2006; Hasbun et al., 2005; Zarza et al., 2008), many of which cor-respond to major biogeographic provinces within Mexico. Forexample, many studies report deep genetic breaks that coincidewith northern and southern units at the MVB (e.g. Devitt, 2006;Zarza et al., 2008). Further, studies show evidence for a deepmtDNA break between the states of Sonora and Sinaloa, whichmay be attributed to the large Rio Fuerte that bisects the area(Devitt, 2006). The Isthmus of Tehuantepec in Oaxaca may alsoplay a role in shaping biogeographic patterns in Mexican lowlandbiotas (Mulcahy et al., 2006). Although these few studies providevaluable information regarding evolutionary patterns and pro-cesses, additional studies are required to assess regional patternsof biodiversity, especially because anthropogenic and climatic fac-tors severely threaten TDF habitat (Burgos and Maass, 2004; Trejoand Dirzo, 2000). Analyses of spatial distribution of cryptic diver-sity and hypothesis-testing can illuminate palaeoclimatic, geologic,and biogeographic histories within Mexico’s TDF and inform con-servation and management for a diversity of taxa (Becerra andVenable, 2008).

Geckos may harbor substantial cryptic molecular diversity andmay be useful models for testing historical ecological and evolu-tionary hypotheses (Fujita et al., 2010; Gübitz et al., 2000;Kasapidis et al., 2005; Rato et al., 2011). High levels of geneticstructure among populations suggest that many species of geckorarely disperse. However, some species (e.g. Hemidactylus spp.)are invasive on a global scale and may be having negative demo-graphic consequences for native species (Blair et al., 2014). Leaf-toed geckos (Phyllodactylidae: Phyllodactylus) range from southernCalifornia, the peninsula of Baja California, and the Sea of Cortesthrough the western lowlands of Mexico and Central America tothe coasts of northern South America and several islands in theWest Indies (Dixon, 1964). They occur in arid and semi-aridregions and commonly occur in tropical thornscrub and TDF; theyavoid rainforests. These habitat associations make the genus idealfor testing hypotheses pertaining to historical diversificationwithin the Mexican TDF. Like many other geckos, Phyllodactylusappear to be microhabitat specialists and are commonly foundon rocky outcroppings adjacent to drainages (Bauer, 1999; Carillode Espinoza et al., 1990). However, the paucity of genetic assess-ments (Blair et al., 2009, 2013) and highly conserved morphology(Dixon, 1964) precludes assessments of ecological and evolution-ary processes within these geckos.

Herein we employ multilocus DNA sequence data from leaf-toed geckos to examine phylogeographic structure and delimitspecies. We specifically address the following questions: (1) Howis molecular diversity spatially structured? (2) How does the tim-ing of lineage divergence correlate with the formation of TDF andPleistocene climate change? (3) How do genetic patternscorrespond to the MVB, Rio Fuerte, and the Isthmus of Tehuante-pec? (4) Is there evidence for cryptic species based on coales-cent-based species delimitation? We address these questionsthrough recently developed multilocus coalescent methods to helpunderstand species limits and the processes governing historicaldiversification throughout this biodiverse and threatenedecosystem.

256 C. Blair et al. / Molecular Phylogenetics and Evolution 84 (2015) 254–265

2. Materials and methods

2.1. Study area and sampling

From 2008 to 2010 we sampled approximately 150 individualsof the P. tuberculosus group (P. t. saxatilis [20], P. t. magnus [45], P.lanei lanei [47], P. l. rupinus [19], P. muralis isthmus [13], an unde-scribed form P. spp. [6], and P. xanti [1]) from distant sites coveringmost of the Mexican ranges of each species (Fig. 1; Table A.1), anarea that has continued to experience elevated rates of fragmenta-tion (Trejo and Dirzo, 2000); some sites occurred in heavily

SMO

RF

P. lanei laneiP. lanei rupinusP. muralis isthmusP. tuberculosus magnusP. tubercuosus saxatlisP. spp.P. xanti

Fig. 1. Map of collecting localities for all species and subspecies used in this study. Shadrepresents a sampled population. SMO = Sierra Madre Occidental; RF = Rio Fuerte; MVMaterial for locality abbreviations.

disturbed areas with little forest cover. All known species (four)and five of six subspecies for the group within the sampled geo-graphic range were included (Dixon, 1964). No samples of P. mural-is muralis were available due to the elusive nature of thissubspecies (Dixon, 1964). Taxonomic identifications were per-formed utilizing both locality and morphological information pre-sented in Dixon (1964). When possible, we obtained sample sizeslarge enough to capture intrapopulation diversity and sampledtype localities for each taxon. Tissue samples (tail tips) were col-lected in the field and directly preserved in 95% ethanol. Betweentwo–four voucher specimens were taken per population and

MVB

IT

ed landscape represents the present distribution of Mexican dry forest. Each pointB = Mexican Volcanic Belt; IT = Isthmus of Tehuantepec. Refer to Supplementary

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deposited in the Laboratorio de Herpetología, Instituto de Biología,Universidad Nacional Autónoma de México.

2.2. Laboratory methods

Total genomic DNA was extracted using standard phenol–chlo-roform procedures. We amplified two mitochondrial genes (NADHdehydrogenase subunit 4 (ND4) and cytochrome b (cyt b) usingestablished protocols (Blair et al., 2009). We also amplified andsequenced two rapidly evolving nDNA introns (alpha-enolase andlamin-A). Primer sequences and annealing temperatures used foreach of the four loci are summarized in Table A.2. Following ampli-fication, each PCR product was separated on a 1% agarose gel.Bands were excised, purified, and directly sequenced in both direc-tions using the BigDye Terminator Cycle Sequencing Kit (AppliedBiosystems) following previous studies (Blair et al., 2009).Sequences were read on an ABI 3730 automated sequencer(Applied Biosystems) and protocols followed the manufacturer’srecommendations.

2.3. Sequence alignment, haplotype estimation, and recombination

Sequence editing and assembly used BioEdit v7.05 (Hall, 1999).Locus identity was confirmed using BLASTn searches. Mitochon-drial genes were translated into their corresponding amino acidsto check for premature stop codons that would have suggestednDNA pseudogenes. Alleles from heterozygous individuals in theintron data were identified using Phase v2.1 (Stephens andDonnelly, 2003; Stephens et al., 2001) with the default parametersand a threshold value of 0.90. Input files for Phase were generatedusing SeqPhase (Flot, 2010). All sequences were deposited in Gen-Bank (KP664173-KP664964; Table A.1). Multiple sequence align-ments were performed using mafft v6.814b (Katoh et al., 2002).We used rdp 3 (Martin et al., 2010) to test for recombinationwithin the intron loci using the rdp (Martin and Rybicki, 2000),geneconv (Padidam et al., 1999) and maxchi (Smith, 1992) meth-ods. In brief, each method sampled a subset of two or threesequences in a multiple sequence alignment, discarded monomor-phic sites, and searched for regions of high levels of similaritybetween pairs or triplets (rdp method), which was assumed toindicate recombination. All analyses implemented default parame-ters and strictly followed recommendations of the program’sauthor(s) (comprehensive explanations given in originaldescriptions).

2.4. Gene tree reconstruction and sequence diversity

We used RAxML v8.1.3 (Stamatakis, 2014) to estimate genea-logical and phylogenetic relationships under a maximum likeli-hood (ML) framework. We analyzed three data sets—mtDNA,alpha-enolase (ENO1), lamin-A (LMNA)—specifying theGTRGAMMA model for each. We only included unique haplotypesfrom the phased intron data. Each analysis started from a maxi-mum parsimony tree and implemented a full ML search usingthe rapid bootstrap algorithm (Stamatakis et al., 2008) with thenumber of bootstrap replicates determined by the autoMRE option.Tarentola mauritanica (GenBank JQ425060.1) was used as the out-group taxon to root the mtDNA tree whereas the ENO1 and LMNAgenealogies were rooted using midpoint rooting. BS values >70were assumed to indicate strong nodal support (Hillis and Bull,1993).

DnaSP v5 (Librado and Rozas, 2009) was used to calculate thefollowing nucleotide diversity statistics for each locus in eachmajor lineage: number of haplotypes (h); haplotype diversity (H);average number of nucleotide differences assuming no recombina-tion (k); number of segregating sites (S); and nucleotide diversity

(p). Sequence divergence between maternal lineages (uncorrectedp-distances and Tamura-Nei corrected distances) was calculated inMega 5 (Tamura et al., 2011).

2.5. Species delimitation—discovery-based

Species delimitation methods can be broadly classified into dis-covery-based and validation-based approaches (Carstens et al.,2013) Discovery-based approaches have the benefit of not requir-ing a priori assignment of individuals to putative species. However,discovery-based methods tend to not be as parameter rich as val-idation-based methods and will many times make many over-sim-plifying assumptions and be prone to over-delimitation (Carstenset al., 2013; Satler et al., 2013). A caveat to many validation-basedmethods is their reliance on a multilocus species tree to serve as aguide to delimit species (Yang and Rannala, 2010; but see Yang andRannala, 2014). Because the most comprehensive species delimita-tion studies harness the power of multiple methods, we used bothdiscovery and validation approaches to delimit species of leaf-toedgeckos throughout Mexican TDF. First, we implemented a likeli-hood method to delimit species by explicitly modeling the transi-tion in branching rates between and within species for single-locusdata (Pons et al., 2006). Under the assumption of a single panmicticpopulation, branching rates should be modeled under a coalescentprocess. Alternatively, a general mixed Yule-coalescent model(GMYC; Pons et al., 2006) would better approximate shifts inbranching rates within versus between species, as those shiftswere indicative of coalescence and speciation, respectively. Thismethod has recently been shown to be robust using simulations(Fujisawa and Barraclough, 2013). The R package splits was usedto test the fit of a GMYC model versus a null model of coalescence.We first used Beast v1.7.5 (Drummond et al., 2012), to generate anultrametric mtDNA gene tree for input into splits. We specified theGTR + I + G model for the mtDNA data as estimated by jModeltestv0.1 (Posada, 2008). We used a strict clock, constant-size coales-cent tree prior, and a random starting tree. These parameter set-tings are commonly used to generate a gene tree for single-locusspecies delimitation (e.g. Monaghan et al., 2009). The chain wasrun for 50 million generations, sampling every 5000 generations.Following a burnin of 10%, trees were annotated in TreeAnnotatorand a maximum clade credibility tree was generated. Adequatesampling for all parameters was assessed with ESS values of atleast 200.

2.6. Species tree reconstruction and divergence times

Divergence dating for geckos has been difficult due to the poorfossil record and taxonomic uncertainty surrounding fossils (seeFujita and Papenfuss, 2011; Gamble et al., 2011 for discussion).Thus, we pursued a broad understanding of the tempo of lineagedivergence by employing previously estimated mtDNA substitu-tion rates for geckos (see below). Phylogenies calibrated usingindependently derived substitution rates have provided robustresults, particularly when a parametric prior distribution wasapplied to the rate (Ho and Phillips, 2009). Because incompletelineage sorting can be common at our level of study, we performeda species tree analysis using the coalescent model implemented in⁄Beast (Heled and Drummond, 2010), one of the few algorithmsthat simultaneously estimates individual gene trees, species trees,effective population sizes, and divergence times under a Bayesianframework. All ⁄Beast analyses were performed using Beast v1.8(Drummond et al., 2012). We defined ‘species’ based on resultsfrom the GMYC analyses (see Gamble et al., 2012 for a similar pro-cedure). For computational efficiency, we used three individualsper species only (Heled and Drummond, 2010; McCormack et al.,2011). We specified the GTR + I + G model for ND4 and an HKY

258 C. Blair et al. / Molecular Phylogenetics and Evolution 84 (2015) 254–265

model for both nDNA loci as estimated by jModeltest v2.1.6.(Darriba et al., 2012). Due to potential differences in substitutionrate for different concatenated mitochondrial genes, cyt b wasexcluded from the species tree analysis. Excluding cyt b also sub-stantially improved mixing, convergence and parameter estima-tion. We used an uncorrelated lognormal relaxed clock, Yule treeprior, and a random starting tree. A substitution rate of 0.0057 sub-stitutions per site per million years was specified for the mtDNAdata as estimated from previous studies on geckos (Fujita andPapenfuss, 2011; Macey et al., 1999). To incorporate uncertaintyin this value (Ho and Phillips, 2009), we selected a normal priorfor the rate with a mean and initial value of 0.0057 and a standarddeviation of 0.0015. We implemented two separate runs of100 million generations each, sampling every 10,000 generationsfor a total of 10,000 states per run. Following a burnin of 10%, runswere combined in LogCombiner and trees were annotated in Tre-eAnnotator. Adequate sampling for all parameters was assessedwith Tracer v1.6.1 (Rambaut and Drummond, 2007) with targetESS values >200.

2.7. Species delimitation—validation-based

We used the multilocus coalescent model implemented in theprogram Bayesian Phylogenetics and Phylogeography (bpp v3.0;Rannala and Yang, 2003; Yang and Rannala, 2010, 2014) as a vali-dation-based method to estimate the number of undocumentedspecies in the P. tuberculosus group. Unlike earlier methods of spe-cies delimitation, bpp does not rely on reciprocal monophyly inmultiple gene trees, can account for coalescent stochasticity, andincorporates phylogenetic uncertainty into parameter estimation.bpp follows the biological species concept and assumes no admix-ture following a speciation event (Yang and Rannala, 2010). Theprogram uses reversible-jump MCMC (rjMCMC) to estimate twoparameters from the data, h and s, with the former representedas 4Nel and the latter as divergence times in the expected numberof mutations per site. Although early versions of the software werereliant on a fixed guide tree to delimit species, recent modificationsuse nearest-neighbor interchange for branch swapping to alter theguide tree topology to explicitly incorporate phylogenetic uncer-tainty when delimiting species (Yang and Rannala, 2014). We per-formed analyses separately for the lineages P. tuberculosus/muralis/spp. and P. lanei to increase computational efficiency. We usedmean estimates obtained from migrate-n analyses as prior esti-mates for h (G(2, 140) for P. tuberculosus/muralis/spp. and G(2,397) for P. lanei; see Supplementary Material for details).migrate-n was also used to estimate migration rates between lin-eages, which could impact the efficacy of the model, particularlyif Nm > �10 (Yang and Rannala, 2010; Zhang et al., 2011). A diffuseprior of G(2, 1000) was used for s0 in all analyses. Both prior distri-butions were shown to be reasonable estimates for many species ofanimals (Zhang et al., 2011). We specified the multilocus speciestree estimated from ⁄beast as the guide tree for all analyses. Thesame individuals and alleles were used for bpp as for ⁄beast. Eachrun consisted of a burnin of 50,000, sample frequency 5, and num-ber of samples 100,000. We performed analyses both with andwithout the mtDNA data to ascertain the impact of mtDNA poly-morphism on species delimitation. For computational efficiencyand because all mtDNA genes are linked, only ND4 was used forthe combined analyses. We introduced inheritance scalars G(4, 4)to account for the combined mtDNA and nDNA data and estimatedthe mutation rate for each locus by specifying a Dirichlet distribu-tion D(2.0) for the combined mtDNA and nDNA data and D(10.0)for the nDNA data only. Each analysis was run at least twice usinga different search algorithm (algorithm 0, e = 2; algorithm 1, a = 2,m = 1; [(Yang and Rannala, 2010)]) and different starting trees tosearch for congruence.

3. Results

3.1. Sequence characteristics

General sequence characteristics are presented in the onlineSupplementary Material (Tables A.3–A.5). The total mtDNA andnDNA data set contained 2334 characters. The combined mtDNAdata contained 1301 characters, 776 of which were variable and670 potentially parsimony-informative. Alignment of ENO1 con-tained 441 characters, 134 of which were variable and 116 poten-tially parsimony-informative. The LMNA alignment contained 592characters, 113 of which were variable and 105 potentially parsi-mony-informative. No premature stop codons were found in themtDNA genes and no recombinant breakpoints were detected forthe nDNA loci. No indels were present in ENO1. The data set forLMNA contained a total of nine indels ranging from 1 to 20 bp inlength; these were coded as missing data for subsequent analyses.Sequence divergence between major matrilines was exceptionallyhigh, with uncorrected mtDNA p-distances and Tamura-Nei dis-tances approaching 32% (Table A.6). Genetic diversity within pop-ulations was higher based on mtDNA versus both nDNA loci(Tables A.3–A.5). However, diversity within some populationsand lineages (e.g. lineages A3, A8, A10, and B1) was exceptionallylow.

3.2. Gene tree analysis

The topology of the ML matrilineal genealogy revealed twodeep divergences that generally corresponded to a divisionbetween P. lanei and P. tuberculosus + P. muralis (Fig. A.1). Multiplehighly divergent lineages were present within each species. Boot-strap support was moderate to high for most of the major lineages,whereas support for deeper relationships was low. For example,Lineage A1 (P. spp.) was placed as sister to a clade containing allP. lanei samples and P. xanti with low support (bootstrap = 0.46).Lineage B1 was not reciprocally monophyletic due to an extremelyshort branch separating samples CB577 and CB573 from theremaining samples within the population (bootstrap = 0.45). Twohighly divergent and sympatric matrilines (A1 and B1) occurredat El Charco, Jalisco (Fig. A.1). Genetic structure was much less pro-nounced in both intron data sets compared to the mtDNA datawith extensive shared polymorphism among species and subspe-cies (Figs. A.2 and A.3). Phyllodactylus tuberculosus saxatilis formeda well-supported lineage in the ENO1 gene tree (bootstrap = 94)and there was moderate support for a P. lanei lineage (boot-strap = 64). Phyllodactylus muralis haplotypes were nested withinP. t. magnus. More extensive shared polymorphisms were presentin the LMNA data set with low support for the majority of nodes(Fig. A.3).

3.3. Species delimitation—discovery-based

Adequate ESS values (>200) were obtained from the BeastmtDNA analysis. Support for relationships was generally higherin the Beast mtDNA gene tree versus the RAxML mtDNA gene tree.There were also several instances of conflicting relationships(Fig. 2). For example, Lineage B1 formed a well-supported cladein the Beast analysis. Other differences included the relationshipswithin the P. t. saxatilis clade, membership within Lineages A6,A9, and A10, and the phylogenetic placement of Lineage B3. Weimported the ultrametric MCC mtDNA gene tree into Splits for sin-gle-locus species delimitation. Results suggested that a GMYCmodel was a better fit to the data (likelihood ratio = 79.21,p < 0.001). A total of 22 ML clusters were identified (95% confi-

P. tuberculosus magnus

P. tuberculosus saxatlis

P. lanei lanei

P. lanei rupinus

P. muralis isthmus

P. spp.

P. xanti

Fig. 2. Results from GMYC analysis based on an ultrametric maximum clade credibility mtDNA gene tree calculated in Beast. Clades highlighted in red represent putative species suggested by GMYC modeling in Splits. Colorsrepresent currently defined species and subspecies within the P. tuberculosus species group. Values at nodes represent Bayesian posterior probability values.

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01 02 03 04 05 06 07 08 0

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P. lanei rupinus spp. 2

P. lanei rupinus spp. 1

P. lanei lanei spp. 1

P. lanei lanei spp. 2

P. lanei lanei spp. 3

P. spp.

P. tuberculosus saxatilis spp. 1

P. tuberculosus saxatilis spp. 2

P. muralis isthmus spp. 1

P. muralis isthmus spp. 2

P. tuberculosus magnus spp. 1

P. tuberculosus magnus spp. 2

P. tuberculosus magnus spp. 3

P. tuberculosus magnus spp. 4

P. tuberculosus magnus spp. 5

P. tuberculosus magnus spp. 6

Fig. 3. Maximum clade credibility tree from the ⁄beast analysis of the combined ND4 and nDNA data. Horizontal lines at nodes represent the 95% highest posterior density forinferred nodal ages. Values at nodes represent Bayesian posterior probabilities. Putative ‘species’ were designated based on the results of GMYC analyses.

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dence interval 22–23), while the number of estimated ML entitieswas 26 (95% confidence interval 25–27) (Fig. 2).

3.4. Species tree and divergence times

We used the results from the GMYC analysis to a priori definespecies for species tree analyses. Although GMYC results suggestedup to 26 species, many of these were represented by one or fewindividuals (particularly within lineage A11); a sampling which isgenerally not suitable for multilocus coalescent species tree esti-mation and may complicate mixing and parameter estimation(Heled and Drummond, 2010). Thus, we adopted a conservativeapproach to species tree estimation and used the GMYC resultsto define species represented primarily by a minimum of threeindividuals in separate clades. The combined independent runs of⁄beast obtained adequate sampling of the posterior distribution(ESS values > 200). The 95% highest posterior density (HPD) forucld.stdev and coefficient of variation did not include zero. The mul-tilocus species tree was divided into two main lineages, one con-sisting of P. lanei spp. and the other consisting of P. tuberculosusspp., P. muralis spp., P. xanti and P. spp. (Fig. 3). Phyllodactylus laneilanei was not monophyletic due to the position of Lineage B3within the P. lanei clade. Both P. t. saxatilis and P. m isthmus weremonophyletic. Support for many nodes in the species tree wasmoderate to high. The common ancestor of sampled leaf-toedgeckos dated to �50 Ma. Divergence times suggested gradual clad-ogenesis of leaf-toed geckos since the Eocene with some evidencefor Pleistocene speciation (Fig. 3). Sampling from the prior only (i.e.no data) gave different mean and 95% HPD estimates for mostparameters, illustrating the information content in our data.

3.5. Species delimitation—validation-based

Historical migration rates were minimal, with most lineagesexchanging fewer than one migrant per generation (Tables A.7,A.8; Fig. A.4). Multiple runs of bpp gave consistent results betweensearch algorithms and starting trees, indicating that the MCMCchains were mixing well. Therefore, we presented results fromalgorithm 0 only. Analyses for P. tuberculosus/muralis/spp. usingthe nDNA data only suggested a delimitation consisting of all spe-cies in the species tree (Fig. 3) except that species A6 and A10 weremerged into a single unit (probability = 0.67443). The model withthe next highest posterior probability was a delimitation consistingof all terminals in the species tree (probability = 0.20678). All otherspecies delimitations had low posterior probabilities. Across allalternative delimitations, the probability for a model containing10 or 11 species was 0.90834. Results of the combined nuclearand mitochondrial data were similar in that there was supportfor a model consisting of all species (probability = 0.51599) and amodel in which A6 and A10 were merged into a single species(probability = 0.45912). All other delimitations had weak support.Across all alternative delimitations, the probability for a modelcontaining 10 or 11 species was 0.98978. Posterior probabilitiesfor different species both with and without the mitochondrial dataare summarized in Fig. 4A.

Results for P. lanei using the nDNA data only suggested a delim-itation consisting of all species in the species tree (Fig. 3) exceptthat species B1 and B2 were merged into a single unit (probabil-ity = 0.66935). The model with the next highest posterior probabil-ity was a delimitation consisting of all terminals in the species tree(probability = 0.29793). All other delimitation models had rela-

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Fig. 4. (A) Bayesian species delimitation results (algorithm 0) from bpp for the P. tuberculosus/muralis/spp. lineage. Posterior probabilities represent the probabilities thatdifferent terminals in the species tree represent distinct species. Results are presented both without (black bars) and with the mtDNA data (gray). (B) Bayesian speciesdelimitation results (algorithm 0) from bpp for the P. lanei lineage. Posterior probabilities represent the probabilities that different terminals in the species tree representdistinct species. Results are presented both without (black bars) and with the mtDNA data (gray).

C. Blair et al. / Molecular Phylogenetics and Evolution 84 (2015) 254–265 261

tively low support. Across all alternative delimitations, the proba-bility for a model containing 4 or 5 species was 0.97832. Results ofthe combined nuclear and mitochondrial data favored a modelwhere each terminal was a distinct species (probability = 0.87143).The model in which B1 and B2 were merged into a single speciesreceived less support (probability = 0.12708), as did all remainingmodels. Across all alternative delimitations, the probability for amodel containing 4 or 5 species was 0.99972. Posterior probabili-ties for different species both with and without the mitochondrialdata are summarized in Fig. 4B.

4. Discussion

Delimiting species in lineages with highly conserved anatomicalcharacters remains a challenge for systematics, although multilo-cus molecular methods show promise (Fujita et al., 2012). Tropicaldry forests are one of Earth’s most diverse ecosystems (Myers et al.,2000). However, these forests occur primarily in developing coun-tries where the threat of extirpation is drastically increasing due toa suite of anthropogenic factors (Trejo and Dirzo, 2000). Recentconservation efforts in Mexico seek to determine both specificareas of high species diversity and endemism as well as source-sink areas for future diversification (e.g. Becerra and Venable,2008; García, 2006). Attainment of this goal requires comprehen-sive analyses from diverse disciplines. Here, we use multilocus coa-lescent methods to delimit species and elucidate the timing oflineage diversification throughout the TDF of western Mexico.The high number of new lineages detected suggests that these for-ests may house much greater biodiversity than previously realized.

Our species tree results suggest limited evidence for Pleistocenecladogenesis. In contrast, the majority of diversification began fol-lowing the origin of TDF in the Oligo-Miocene.

4.1. Historical diversification

All phylogenetic analyses reveal extraordinary diversity of leaf-toed geckos (>16 different lineages). Analyses of the nDNA allelesreveals genetic structure, albeit less pronounced than that formtDNA. Conflicts between independent gene trees at the specieslevel often suggest either gene flow or incomplete lineage sorting(ILS). Shared polymorphisms in the data occur both over broadand fine scales, indicating that both ILS and introgression are likelyresponsible for the observed patterns. Indeed, the widespread P.tuberculosus is known to be sympatric with many congenersthroughout its range with some degree of introgression likely(Dixon, 1964), and our results suggest two sympatric species atthe El Charco House population. Species tree methods can addresspatterns of ILS by incorporating the stochasticity of the coalescentprocess into phylogenetic inference (Liu et al., 2009). Althoughgene tree analyses do not resolve a single matriline for some taxa(e.g. P. muralis isthmus), the species tree analysis resolves thesetaxa as monophyletic (Fig. 3).

Our species tree dates the most recent common ancestor of allsampled Phyllodactylus to approximately 50 Ma, corroboratingother recent molecular evidence for an ancient origin of geckos(Gamble et al., 2008). These results suggest that ecological and cli-matic shifts during the Eocene may have initiated speciation inleaf-toed geckos in Mexico. However, the majority of diversifica-tion in these geckos occurred in the Miocene (�23–5 Ma). As these

262 C. Blair et al. / Molecular Phylogenetics and Evolution 84 (2015) 254–265

lizards are common inhabitants of TDF habitat, this timing maycorrespond to the formation of the Mexican TDF �25 Ma(Becerra, 2005). For example, the origin of Bursera (a common con-stituent of TDF) dates to 70–80 Ma, and the genus experiencedrapid diversification at around 20–7.5 Ma when extensive tectonicactivity was altering the Sierra Madre Occidental and MVB(Becerra, 2005). Thus, the formation of the Mexican TDF may beresponsible for driving subsequent speciation in these geckosthrough the creation of a novel environment. Additional studiesinvolving other similarly distributed groups are needed to assessconcordance between diversification and the origin of MexicanTDF.

A second interesting result is the apparently older divergencetimes inferred in this study versus previous molecular phylogeneticstudies including leaf-toed geckos. For example, Gamble et al.(2011) infer a divergence time of �25 Ma for P. tuberculosus andP. xanti whereas our species tree analysis suggests �40 Ma(although 95% HPDs include 25 Ma). These discrepancies could bedue to a number of factors including taxon and gene sampling, pri-ors, methods of calibration, and analytical methods used. Further,Gamble et al. (2011) use only one sample of what is currently P.tuberculosus while our results suggest that this taxon in fact repre-sents multiple undescribed species. Further, the phylogeneticplacement of P. xanti was ambiguous in our species tree (posteriorprobability 0.67) and was placed in alternative positions in the MLand Bayesian mtDNA gene trees. Thus, although it appears that thetwo studies conflict, we suggest that this further highlights theneed for additional phylogenetic and taxonomic work on the group.

The importance of Pleistocene climatic shifts in shaping Neo-tropical diversification is controversial (Hewitt, 2000; Klicka andZink, 1997). Our phylogenetic results suggest weak evidence thatPleistocene climate change profoundly influenced diversificationand speciation in these geckos and are concordant with previousstudies that suggest an older timeframe of speciation in Neotropi-cal lowland taxa (Weir, 2006; Weir and Schluter, 2004) as diver-gence between many species occurred well before theQuaternary. Only five lineages in our species tree diverged duringthe Pleistocene (B1 + B2 and A10 + A6 + A7). However, our speciesdelimitation results suggest that many of these lineages do notrepresent distinct species (see below). Thus, it appears that olderprocesses were the predominant evolutionary force acting uponclades inhabiting diverse ecological conditions throughout thelowlands of the Neotropics.

The MVB has been suggested as a major biogeographic barrierbetween highly differentiated lowland Nearctic and Neotropicalbiotas (e.g. Devitt, 2006; Morrone, 2006; Mulcahy andMendelson III, 2000; Zarza et al., 2008) and also appears to drivecladogenesis within montane species (e.g. Bryson and Riddle,2012; Bryson et al., 2011a,b; Bryson et al., 2012a,b). The MVBformed in a west-to-east progression beginning at around 23 Maand ending approximately 2.5 Ma (Moran-Zenteno, 1994). Themost extensive ridges of this belt occur in western regions of Jali-sco, and the number and prominence of volcanoes dissipates east-wardly toward Veracruz. However, even smaller eastern ridgesappear to serve as major biogeographic barriers to lowland taxa(Mulcahy and Mendelson III, 2000; Mulcahy et al., 2006). In ouranalysis P. t. saxatilis occurs north of the MVB whereas a deeplydivergent P. t. magnus occurs south of the MVB, consistent withthe hypothesis of vicariance. These taxa also diverged �25 Ma con-sistent with vicariance due to the MVB. However, due to the highdegree of cryptic lineages recovered in this study along with thepresumably low vagility in these geckos it is also possible thatthese patterns are simply a result of limited dispersal over geologictime with no influence of geographic barriers (Irwin, 2002).

Within P. t. saxatilis, we recover three deeply divergent lineages.Devitt (2006) suggests that the Rio Fuerte, a large river that

roughly divides the states of Sonora and Sinaloa, may be an impor-tant biogeographic barrier for tropical lowland taxa. Our RAxMLresults show divergent lineages between Sonora and Sinaloa con-sistent with vicariance due to the Rio Fuerte (Fig. A.1). Conversely,genealogical relationships recovered in the Bayesian analysis donot lend support to this hypothesis as individuals from Cosala, Sin-aloa are more closely related to individuals from Alamos, Sonorathan to geckos from Villa Union, Sinaloa (posterior probabil-ity = 0.9; Fig. 2).

Our analyses of P. tuberculosus magnus corroborate previouslyhypothesized vicariant events near the Isthmus of Tehuantepec(Rico et al., 2008; Sullivan et al., 1997). Unlike the MVB, the occur-rence of this historical barrier in southern/eastern Oaxaca has beencontroversial for both lowland (e.g. Mulcahy et al., 2006) andupland taxa (e.g. Barber and Klicka, 2010; Marshall and Liebherr,2000; Sullivan et al., 2000), with some authors suggesting that aPliocene seaway may have isolated populations across the isthmus(Sullivan et al., 2000). Our results cannot reject this hypothesis aswe recover two clades across this region within Lineage A11. Asleaf-toed geckos primarily inhabit the lowlands of western/south-ern Mexico, a putative Plio-Pleistocene seaway serving as a biogeo-graphic barrier is certainly a tenable hypothesis.

Phylogenetic analyses for P. lanei suggest a splitting of popula-tions in Guerrero from those in Jalisco and Michoacan. This divisionroughly corresponds to the current taxonomy of P. lanei (Dixon,1964); P. l. lanei is restricted to Guerrero and P. l. rupinus occursin Jalisco and Michoacan on opposite sides of the Balsas Basin, ahighly speciose region that contains many endemic taxa (Becerraand Venable, 2008; Rzedowski et al., 1993; Zaldı́var-Riverónet al., 2004). Phyllodactylus lanei lanei is not monophyletic in thespecies tree analysis due to the poorly supported position of Line-age B3, although monophyly was observed in the ML mtDNA genetree. Vicariance in this group may be due to the Río Balsas, a largeriver that flows southwestwards through the states of Mexico, Pue-bla, Morelos, and Guerrero. However, the Sierra de Taxco dividesthe Balsas Basin into eastern and western units and it too maybe responsible for the split (Becerra and Venable, 1999). Thus,the relative importance of orogenesis versus river drainageremains unknown.

4.2. Species delimitation

Although promising, the use of multilocus coalescent methodsfor species delimitation remains in its infancy (Camargo et al.,2012). Regardless, the algorithms provided in bpp appear to behighly accurate and robust against slight-to-moderate deviationsfrom the assumptions of the model (Zhang et al., 2011). The addi-tion of coalescent methods as part of an integrative taxonomy isimperative if we are to discover and conserve biological diversitybefore it disappears (Fujita et al., 2012).

A majority of gecko phylogeographic studies published to datefocus on evolutionary patterns and processes throughout NorthAfrica, Europe, and Australia (e.g. Fujita et al., 2010; Gübitz et al.,2000; Kasapidis et al., 2005; Rato et al., 2011), with relatively lessattention focused on Neotropical processes (but see Werneck et al.,2012). In many cases, geckos harbor substantial cryptic diversityand their dispersal distances are presumably quite small. Our sin-gle- and multilocus species delimitation results suggest that thetaxonomy of leaf-toed geckos requires substantial revision. Indeed,both bpp and GMYC results suggest that almost every populationthroughout western Mexico may be a distinct species, a findingwhich has significant conservation implications for Mexican TDF.

Although previous work suggests that priors on h and s0 in bppmay influence results (Leaché and Fujita, 2010), we use a relativelylarge prior for h and small prior for s0, both of which would favor amodel with fewer species (Yang and Rannala, 2010; Zhang et al.,

C. Blair et al. / Molecular Phylogenetics and Evolution 84 (2015) 254–265 263

2011). Uncertainty in the guide tree can also impact results, partic-ularly if highly divergent lineages are placed sister to the exclusionof other closely related lineages (Leaché and Fujita, 2010; Yang andRannala, 2010). However, recent additions to the software usenearest-neighbor interchange to swap branches on the guide treeto explicitly incorporate phylogenetic uncertainty into coales-cent-based species delimitation (Yang and Rannala, 2014). Finally,high migration rates can impact results and lead to collapsing ofnodes in the species tree (Zhang et al., 2011). Although ourmigrate-n analysis suggested Nm > 1 between some populations(albeit with large confidence intervals and over unrealistic geo-graphic scales), we still recovered high posterior probabilities formultiple undocumented species. Thus, our results provide compel-ling evidence that a multitude of cryptic species (some in sympa-try) await formal description. These results further highlight theutility of Bayesian coalescent approaches for species delimitationin morphologically cryptic clades (Camargo et al., 2012; Leachéand Fujita, 2010). Moreover, our GMYC results were highly congru-ent with bpp, suggesting that single-locus methods that simulta-neously incorporate Yule and coalescent processes may bepowerful in delimiting species (Esselstyn et al., 2012; Pons et al.,2006). The fact that our species delimitation results are congruentwith previous subspecific taxonomic designations (Dixon, 1964)further highlights the utility of these approaches for defining spe-cies boundaries.

4.3. Taxonomic implications

Due to the presumably low vagility in leaf-toed geckos (Blairet al., 2013,2014) and the fact that almost every sampled popula-tion may be a distinct species, it is unlikely that many taxonomi-cally informative ecological or behavioral characters can beisolated. Although beyond the scope of the present study, a com-prehensive examination of internal anatomical features may beuseful in this system. However, previous morphological studiesshow a high degree of overlap in character states between thesespecies (Dixon, 1964). Therefore, we tentatively recognize a totalof 15 species (17 total for the species group), 9 of which are newto science—a conservative estimate given our results. As coales-cent-based species delimitation should be used as part of an inte-grative taxonomy (Fujita et al., 2012), formal descriptions of thesetaxa are forthcoming. Regardless, these results suggest that thedegree of species diversity in these geckos and potentially in othergroups throughout the TDF of western Mexico may be substan-tially underestimated.

4.4. Conclusions

Our results provide limited support for the hypothesis of rapidlineage diversification during Quaternary glaciation and suggestthat the formation and expansion of Mexican TDF in the Miocenemay have initiated increased rates of speciation in leaf-toedgeckos. Dry forests are one of the most diverse yet threatened eco-systems (Myers et al., 2000). Compared to moist tropical forests,we know relatively little about the tempo and mechanisms of bio-logical diversification in this system (Werneck et al., 2011). Forestfragmentation continues to increase (Trejo and Dirzo, 2000), andwill no doubt have detrimental impacts on the local flora andfauna. By employing sophisticated multilocus coalescent analyses,our results point to diversification processes operating prior toQuaternary climatic change and resulting in an extraordinary num-ber of undocumented species. For conservation, similar multi-tiered approaches are required to identify diversity hotspots andelucidate the diverse processes that drive the evolution of richbiota. Delimiting species using objective and highly reproducible

coalescent approaches is an exciting avenue of research thatshould be explored further.

Funding

This work was funded by Discovery Grant 3148 from the Natu-ral Sciences and Engineering Research Council of Canada (RWM)and the Theodore Roosevelt Memorial Fund (CB).

Acknowledgments

We thank Victor H. Jiménez Arcos, Roberto Lhemish MartínezBernal, and Anibal Diaz De-la Vega for helping in the field. KristenChoffe, Oliver Haddrath, and Amy Lathrop assisted with lab work.Christina Davy, Jean-François Flot, and Santiago Sánchez Ramirezhelped with data analysis. Alexei Drummond, Joseph Heled, andmembers of the Beast discussion forum provided invaluable assis-tance with all ⁄Beast analyses. Jason Brown, Ryan Campbell, AmyHeilman, Erin McKenney, Peter Larsen, and Anne Yoder providedvaluable comments to improve the manuscript. All research wasconducted using approved Animal Use Protocols. All necessary per-mits (SGPA/DGVS/1995/08, SGPA/DGVS/01493/09, SGPA/DGVS/3220/10) were obtained from SEMARNAT through the UniversidadNacional Autónoma de México (UNAM).

Appendix A. Supplementary material

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.ympev.2015.01.003.

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