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Phylogeny, biogeography and evolution of clutch size in South American lizards of the genus Kentropyx (Squamata: Teiidae)

February 2009
Molecular Ecology 18(2):262-78

February 2009
18(2):262-78

DOI:10.1111/j.1365-294X.2008.03999.x

Source
PubMed

Authors:

Fernanda P Werneck

Instituto Nacional de Pesquisas da Amazônia

Rosane Garcia Collevatti

Universidade Federal de Goiás

Guarino R Colli

University of Brasília

The lizard genus Kentropyx (Squamata: Teiidae) comprises nine species, which have been placed in three species groups (calcarata group, associated to forests ecosystems; paulensis and striata groups, associated to open ecosystems). We reconstructed phylogenetic relationships of Kentropyx based on morphology (pholidosis and coloration) and mitochondrial DNA data (12S and 16S), using maximum parsimony and Bayesian methods, and evaluated biogeographic scenarios based on ancestral areas analyses and molecular dating by Bayesian methods. Additionally, we tested the life-history hypothesis that species of Kentropyx inhabiting open ecosystems (under seasonal environments) produce larger clutches with smaller eggs and that species inhabiting forest ecosystems (under aseasonal conditions) produce clutches with fewer and larger eggs, using Stearns' phylogenetic-subtraction method and canonical phylogenetic ordination to take in to account the effects of phylogeny. Our results showed that Kentropyx comprises three monophyletic groups, with K. striata occupying a basal position in opposition to previous suggestions of relationships. Additionally, Bayesian analysis of divergence time showed that Kentropyx may have originated at the Tertiary (Eocene/Oligocene) and the 'Pleistocene Refuge Hypothesis' may not explain the species diversification. Based on ancestral reconstruction and molecular dating, we argued that a savanna ancestor is more likely and that historical events during the Tertiary of South America promoted the differentiation of the genus, coupled with recent Quaternary events that were important as dispersion routes and for the diversification at populational levels. Clutch size and egg volume were not significantly different between major clades and ecosystems of occurrence, even accounting for the phylogenetic effects. Finally, we argue that phylogenetic constraints and phylogenetic inertia might be playing essential roles in life history evolution of Kentropyx.

Geographic areas used in the DIVA analysis. A: Guianan Shield, B: Amazon Basin, C: Atlantic Forest, D: Brazilian Shield, E: Chaco-Paraná Basin.

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Geographic areas used in the DIVA analysis. A: Guianan Shield, B: Amazon Basin, C: Atlantic Forest, D: Brazilian Shield, E: Chaco-Paran? Basin. Fig. 2 Kentropyx phylogeny inferred from morphological data. (A) Most parsimonious tree, with bootstrap and Bremer support values, respectively. Bremer support values are not absolute numbers because they were divided by 999 in order to compensate the character weighting. (B) Tree inferred by Bayesian analysis, with posterior probability values.

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Species, locality, collection, collection number and GenBank Accession number

…

Distribution of females of nine species of Kentropyx, according to the reproductive condition

…

Effect of monophyletic groups and ecosystems on the reproductive features of Kentropyx. Clade labels according to Fig. 4

…

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262 Phylogeny, biogeography and evolution of clutch size

in South American lizards of the genus Kentropyx

(Squamata: Teiidae)

F. De P. Werneck, L. G. Giugliano, R. G. Collevatti &

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332 Cospeciation of termite gut flagellates and their

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VOLUME 18, NUMBER 2, JANUARY 2009

MOLECULAR ECOLOGY

VOLUME 18, NUMBER 2, JANUARY 2009, pp. 169–374

INVITED REVIEW

169 The interaction of sexually and naturally selected traits

in the adaptive radiations of cichlid fishes

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D. Fournier, J.-C. De Biseau & S. Aron

200 Genetic diversity and gene flow in collapsed and

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212 High genetic diversity and connectivity in the

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227 Molecular genetic data provide support for a model of

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235 Population structure of spotted salamanders

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MOLECULAR

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JANUARY

2009

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Molecular Ecology (2009) 18, 262–278 doi: 10.1111/j.1365-294X.2008.03999.x

Blackwell Publishing Ltd

Phylogeny, biogeography and evolution of clutch

size in South American lizards of the genus Kentropyx

(Squamata: Teiidae)

FERNANDA DE P. WERNECK,* LILIAN G. GIUGLIANO,† ROSANE G. COLLEVATTI‡

and GUARINO R. COLLI*

*Departamento de Zoologia, Universidade de Brasília, 70910-900, Brasília, DF, Brazil, †Programa de Pós-Graduação em

Biologia Animal, Universidade de Brasília, 70910-900, Brasília, DF, Brazil, ‡Programa de Pós-Graduação em Ciências

Genômicas e Biotecnologia, Universidade Católica de Brasília, 70790-160, Brasília, DF, Brazil

Abstract

The lizard genus Kentropyx (Squamata: Teiidae) comprises nine species, which have been

placed in three species groups (calcarata group, associated to forests ecosystems; paulensis

and striata groups, associated to open ecosystems). We reconstructed phylogenetic relationships

of Kentropyx based on morphology (pholidosis and coloration) and mitochondrial DNA

data (12S and 16S), using maximum parsimony and Bayesian methods, and evaluated

biogeographic scenarios based on ancestral areas analyses and molecular dating by Bayesian

methods. Additionally, we tested the life-history hypothesis that species of Kentropyx

inhabiting open ecosystems (under seasonal environments) produce larger clutches with

smaller eggs and that species inhabiting forest ecosystems (under aseasonal conditions)

produce clutches with fewer and larger eggs, using Stearns’ phylogenetic-subtraction

method and canonical phylogenetic ordination to take in to account the effects of phylogeny.

Our results showed that Kentropyx comprises three monophyletic groups, with K. striata

occupying a basal position in opposition to previous suggestions of relationships. Addi-

tionally, Bayesian analysis of divergence time showed that Kentropyx may have originated

at the Tertiary (Eocene/Oligocene) and the ‘Pleistocene Refuge Hypothesis’ may not explain

the species diversification. Based on ancestral reconstruction and molecular dating, we

argued that a savanna ancestor is more likely and that historical events during the Tertiary

of South America promoted the differentiation of the genus, coupled with recent Quaternary

events that were important as dispersion routes and for the diversification at populational

levels. Clutch size and egg volume were not significantly different between major clades

and ecosystems of occurrence, even accounting for the phylogenetic effects. Finally, we argue

that phylogenetic constraints and phylogenetic inertia might be playing essential roles in

life history evolution of Kentropyx.

Keywords: biogeography, Kentropyx, life-history evolution, phylogenetic ordination, phylogenetic

subtraction, phylogeny

Received 10 June 2008; revision received 3 October 2008; accepted 5 October 2008

Introduction

A great deal of biotic and abiotic factors may influence lizards’

reproductive cycles (Fitch 1970). Food and water availability

are often considered the main constraints on reproduction

(Magnusson 1987; De Marco 1989). Due to this influence,

local populations tend to adapt their reproductive cycles to the

environment, being under continuous selective pressure

(Roff 1992). As a result, populations and species from

different localities, under distinct environmental conditions,

may exhibit variation in life-history traits, such as repro-

ductive frequency, and number and size of offspring (Fitch

1982, 1985; Brown & Shine 2006).

Correspondence: Fernanda de P. Werneck, Department of Biology,

WIDB, Brigham Young University, Provo, UT84602, USA.

Fax: 801-422-0090; Email: fewerneck@gmail.com

PHYLOGENY, BIOGEOGRAPHY AND CLUTCH SIZE OF KENTROPYX 263

Quantitative characteristics, such as clutch size and egg

volume, are essential to the study of life history because

they can elucidate how energy is allocated to reproduction.

The amount of energy available for reproduction and

limiting factors, such as body size and shape, foraging

mode and habitat specificity, may determine the number

and size of offspring (Vitt 1981; Zug et al. 2001). Thus, based

on hypotheses of trade-offs in life-history evolution, an

offspring should represent an optimal compromise between

number and size of eggs that results in maximum survival

of juveniles and gravid females (Stearns 1989; Shine &

Schwarzkopf 1992; Pough et al. 1998). As an adjustment to

different selective pressures, species of nonseasonal and

seasonal environments usually have distinct reproductive

strategies. Fitch (1982) hypothesized that species in tropical

forest (often aseasonal) ecosystems should temporally spread

out their reproductive investments, thus producing more

clutches with fewer and larger eggs. Conversely, species in

open (often seasonal) ecosystems should concentrate repro-

ductive investment during the favourable (rainy) period,

and thus produce larger clutches with smaller eggs (Fitch

1982). This hypothesis has never been adequately tested

within monophyletic groups that have species in both

seasonal and aseasonal environments.

A problem of most comparative studies is that they do

not consider the phylogeny of species under study. In such

a case, it is difficult to determine whether the option for one

reproductive strategy was determined by ecological relations

of the population or by the inheritance of ancestral adap-

tations. Species belong to hierarchical phylogenies, and

thus cannot be treated as independent observations for

the study of covariation among life-history traits (Felsen-

stein 1985b; Harvey & Pagel 1991). Dunham & Miles (1985)

suggested that phylogenetic constraints have a central

importance in reproductive patterns of lizards and snakes

and cannot be ignored in analyses of the life-history

evolution.

The lizard genus Kentropyx (Squamata: Teiidae) is dis-

tributed in South America, east of the Andes (Gallagher &

Dixon 1992). The genus was described by Spix in 1825 and

is distinguished from all other teiid genera by the presence

of keeled ventral scales (Gallagher 1979). The systematics

of Kentropyx had been problematic, with 19 nominal taxa

already proposed, most of which were later considered as

junior synonyms. Gallagher & Dixon (1992) recognized eight

species in three species groups, based on qualitative char-

acteristics of dorsal scales: (i) the calcarata group (K. calcarata,

K. pelviceps and K. altamazonica), with small granular dorsal

and lateral scales, and a clear distinction between the

dorsals and the keeled plate-like supracaudals; (ii) the

paulensis group (K. paulensis, K. viridistriga and K. vanzoi),

with granular dorsals and lateral scales gradually enlarging

towards the tail, where dorsals and supracaudals are almost

indistinct; and (iii) the striata group (K. striata and K. borckiana)

with rows of enlarged plate-like dorsals and granular

lateral scales. This arrangement, however, was based solely

on total similarity without assessing phylogenetic rela-

tionships among species or the monophyly of the groups

proposed. It should be noted that K. borckiana is parthe-

nogenetic and its hybrid origin between K. calcarata and

K. striata has been supported (Cole et al. 1995; Reeder et al.

2002). Through a similarity analysis of mitochondrial

DNA, Reeder et al. (2002) observed that the maternal

ancestor of K. borckiana was K. striata. More recently, we

collected an undescribed species from the Jalapão region

in central Brazil, one of the largest remaining tracts of

undisturbed Cerrado, the largest Neotropical savanna

biome (Oliveira & Marquis 2002). This species seemingly

belongs to the paulensis group and is hereafter referred to

as Kentropyx sp.

Species of the calcarata group occur mostly in forests of

the Amazon Basin, including forest edges, clearings caused

by fallen trees, secondary growth, river margins and

plantation sites; however, some isolated populations of K.

calcarata exist in the Atlantic forest of Brazil (Gallagher &

Dixon 1992; Ávila-Pires 1995). On the other hand, species of

the paulensis group inhabit open ecosystems of the Brazilian

Shield, with K. vanzoi being endemic to the Cerrado, partic-

ularly in areas with sandy soils (Nogueira 2006; Vitt &

Caldwell 1993), and K. viridistriga being endemic to the

flooded savannas of the Chaco-Paraná Basin, in the Pantanal

and Guaporé depressions. Finally, species of the striata group

occur in open ecosystems of the Guiana Shield, northern

Amazon Basin, and in some Caribbean islands. Gallagher

& Dixon (1992) identified some isolated populations of K.

striata in northeastern Brazil (Gallagher & Dixon 1992).

Within Teiidae, Kentropyx forms a monophyletic group

with Ameiva, Cnemidophorus and Aspidoscelis (‘cnemido-

phorines’; Vanzolini & Valencia 1965; Gorman 1970; Presch

1974; Reeder et al. 2002; Teixeira 2003; Giugliano et al. 2007).

Gallagher & Dixon (1992) proposed that dorsal scales

increased in size and femoral pores decreased in number

during the evolution of Kentropyx, with the calcarata, pau-

lensis, and striata groups, in this order, being arranged in a

linear progression of increasing size of dorsal scales (and

consequent decreasing number) and decreasing number of

femoral pores. This progression was interpreted as being

related to thermoregulation, such that large numbers of

femoral pores and dorsal scales (smaller in size) are associ-

ated with shade-tolerance in forest species, whereas small

numbers of femoral pores and dorsals (larger) are related

to heat-tolerance in open vegetation species (Gallagher et al.

1986). However, without phylogenetic analyses, the division

of Kentropyx into groups and the interpretation of the

evolution of morphological and ecological traits are merely

speculative.

Gallagher & Dixon (1992) interpreted the current distribu-

tional patterns of Kentropyx as consistent with the ‘Pleistocene

264 F. P. W ER NE CK E T A L .

Refuge Hypothesis’: successive climatic and vegetational

cycles during the Pleistocene promoted the expansion and

retraction of species ranges, with speciation occurring

in forest refuges during dry/cold periods, and in savanna

refuges, during wet/hot periods (Haffer 1969, 1982;

Gallagher 1979; Gallagher & Dixon 1992). The presence of

K. striata in open ecosystem enclaves within Amazon and

Atlantic forests and the widely geographically separated

populations of K. calcarata in Amazon and Atlantic forests

apparently support this hypothesis. However, other events

able to explain current distributional patterns, such as

secondary dispersal, were not considered. Moreover, the

importance of the ‘Pleistocene Refuge Hypothesis’ on the

distributional patterns of the South American herpetofauna

has been clearly overestimated (Colli 2005). Ancient historical

events of the Tertiary, like marine transgressions, the arrival

of immigrants from Central and North America, and the

uplift of the Central Brazil Plateau, may have had more

profound influences (Colli 2005).

Herein, we reconstruct phylogenetic relationships of

Kentropyx based on morphology and mitochondrial DNA

data (12S and 16S), using maximum parsimony and Bayesian

methods, and evaluate biogeographic scenarios based on

ancestral areas analyses and molecular dating by Bayesian

methods. We also test the life-history hypothesis that open

ecosystem species of Kentropyx produce larger clutches

with smaller eggs and that forest ecosystems species pro-

duce clutches with fewer and larger eggs, using Stearns’

phylogenetic-subtraction method and canonical phylogenetic

ordination.

Materials and methods

Phylogeny and biogeography

Morphological data. We obtained reproductive and morph-

ological data of Ameiva ameiva and Cnemidophorus grami-

vagus (used as outgroups in phylogenetic analyses), and

Kentropyx from museum specimens (Appendix I; total of

1143 specimens of Kentropyx; Table 1). Morphological data

included pholidosis and coloration patterns (for a detailed

description of morphological characters and states see

Appendix II).

We coded quantitative characters as continuous variables

using step matrix gap-weighting for parsimony analysis

(Wiens 2001). This method attributes different weights to

intervals with different ranges, through a step matrix that

shows costs of transitions between each character state.

For each species sampled, we coded qualitative characters

with intraspecific variation (polymorphism) using the

frequency of derived states (Wiens 1995). We weighed

qualitative characters with no polymorphism by 999 and

polymorphic qualitative characters by 999 divided by the

largest number of steps between two character states, and

thus, the cost of a transformation in quantitative characters is

equivalent to the weight of a polymorphic or no-polymorphic

character (Wiens 2001). Consequently, all analyses using

this weighting scheme produced cladograms with lengths

(and Bremer branch support) multiplied by 999. Thus, we

divided the length and Bremer branch support of those

cladograms by 999, allowing comparisons with other studies.

For Bayesian analyses, we gap-coded quantitative characters

(Thiele 1993), using 0.5 standard deviation as cut-point and

regarded them as ordered. We conducted Bayesian analyses

using MrBayes-ordered standard model (Huelsenbeck &

Ronquist 2001).

Molecular data. We used 12S and 16S mitochondrial

DNA sequences previously published (GenBank–NCBI;

www.ncbi.nlm.nih.gov/) or obtained by us (Table 2). We

extracted whole genomic DNA from liver using DNeasy

tissue kits (QIAGEN) and amplified fragments of nearly

350 bp of the 12S ribosomal gene and of nearly 500 bp of

the 16S gene with 12Sa, 12Sb, 16SaR, and 16Sd primers,

using the same polymerase chain reaction (PCR) conditions

described in Reeder (1995). We sequenced PCR products

on an ABI PRISM 377 automated DNA sequencer (Applied

Biosystems) using DYEnamic ET terminator cycle sequencing

kit (Amersham Pharmacia Biotech), according to manu-

facturer’s instructions, and analysed and edited sequences

using BioEdit 5.09 (Hall 1999). We obtained a multiple

alignment based on parsimony with MALIGN 2.7 (Wheeler

& Gladstein 1994). We assigned gap costs for internal gaps

(2) and leading and trailing gaps (1), but equal weight for

transitions and transversions. All alignments were submitted

to TreeBase (study Accession no. SN3720). For both 12S and

16S mitochondrial DNA sequences, we chose the model of

sequence evolution by hierarchical likelihood ratio tests

(HLRTs) using ModelTest 3.7 (Posada & Crandall 1998).

For the Bayesian combined molecular data (12S +16S), each

sequence had its own independent model of evolution and

model parameters.

Phylogenetic analysis. We conducted phylogenetic analyses

with maximum parsimony (MP) and Bayesian methods,

using the species A. ameiva and C. gramivagus as outgroups.

We excluded Kentropyx borckiana from analyses because of

its hybrid origin (Cole et al. 1995; Reeder et al. 2002), which

precludes a dichotomous tree to correctly represent its

relations with other species of Kentropyx (Frost & Wright

1988). We analysed each character partition (morphology,

12S, 16S) separately and in combination, using paup*

version 4.0b10 (Swofford 1999) and MrBayes version 3.0b4

(Huelsenbeck & Ronquist 2001). For MP analysis, we used

branch-and-bound searches, coding gaps as a fifth state

(Giribet & Wheeler 1999) and assessed the reliability of

results with 1000 bootstrap samples (Felsenstein 1985a)

and Bremer support (Bremer 1994), with MacClade 4.0

PHYLOGENY, BIOGEOGRAPHY AND CLUTCH SIZE OF KENTROPYX 265

(Maddison & Maddison 1999) and paup*. Bayesian analyses

started with randomly generated trees and ran for 5.0 ×106

generations, implementing the Metropolis-coupled Markov

chain Monte Carlo method (MC3) (Altekar et al. 2004). We

sampled trees at intervals of 100 generations, producing

50 000 trees. We plotted the log-likelihood scores of the

50 000 trees against generation time to detect stationarity

using Tracer 1.4 (Rambaut & Drummond 2007). We regarded

all sample points before stationarity as burn-in samples

(until 6500th generation) that contained no useful information

about parameters. For each analysis, we conducted four

independent runs to avoid trapping in local optima. The

frequency of any particular clade in the majority-rule

consensus tree of the stationarity stage, from the four

independent runs, represented the posterior probability of

that node (Huelsenbeck & Ronquist 2001).

Molecular dating. We estimated divergence times based on

a Bayesian relaxed molecular clock approach implemented

in MULTIDISTRIBUTE (Thorne et al. 1998; Kishino et al.

2001; Thorne & Kishino 2002). This approach allows the

incorporation of multiple time constraints, and takes into

account both molecular and palaeontological uncertainties

to estimate the variance of divergence times. For this

analysis, we used the most parsimonious tree topology

of the combined analysis (morphological + 12S and 16S

mitochondrial DNA sequences). We calibrated the origin

of the genus based on Giugliano et al. (2007) estimate [29.8

Table 1 Meristic characters of nine species of Kentropyx. Values indicate x± SD, with range in parentheses

Variables

K. altamazonica

(n= 233)

K. borckiana

(n= 4)

K. calcarata

(n= 231)

K. paulensis

(n= 96)

K. pelviceps

(n= 157)

K. striata

(n= 150)

K. vanzoi

(n= 160)

K. viridistriga

(n= 21)

Kentropyx sp.

(n= 21)

Supralabials 12.2 ± 0.6 12.0 ± 0.0 12.1 ± 0.5 12.2 ± 0.6 12.3 ± 0.6 12.0 ± 0.2 12.0 ± 0.3 12.3 ± 0.6 12.1 ± 0.7

(10–14) (12–12) (10–15) (11–15) (10–15) (12–13) (11–14) (12–14) (10–14)

Infralabials 10.2 ± 1.5 8.2 ± 0.5 9.9 ± 1.3 8.7 ± 1.4 10.3 ± 1.7 9.9 ± 1.4 8.7 ± 1.2 7.8 ± 0.7 8.0 ± 0.0

(8–15) (8–9) (8–12) (6–14) (8–14) (6–13) (7–13) (6–9) (8–8)

Collar scales 16.6 ± 1.5 17.5 ± 0.6 16.4 ± 1.6 16.2 ± 1.6 16.9 ± 1.6 13.9 ± 1.1 14.3 ± 1.2 16.1 ± 1.8 15.8 ± 1.5

(13–22) (17–18) (13–22) (12–21) (11–22) (11–17) (12–17) (12–19) (13–18)

Supraoculars 3.1 ± 0.3 3.2 ± 0.5 3.0 ± 0.1 3.1 ± 0.2 3.1 ± 0.3 3.1 ± 0.3 3.1 ± 0.3 3.2 ± 0.4 3.0 ± 0.0

(3–4) (3–4) (3–4) (3–4) (3–5) (3–4) (3–4) (3–4) (3–3)

Parietals 3.0 ± 0.0 3.0 ± 0.0 3.0 ± 0.1 3.0 ± 0.2 3.0 ± 0.1 3.0 ± 0.0 3.0 ± 0.0 3.0 ± 0.0 3.0 ± 0.0

(3–3) (3–3) (3–5) (3–4) (3–4) (3–3) (3–3) (3–3) (3–3)

Postparietals 2.5 ± 0.8 2.7 ± 0.5 2.2 ± 0.4 2.5 ± 0.7 2.3 ± 0.5 2.1 ± 0.4 2.3 ± 0.5 2.6 ± 0.7 2.5 ± 0.7

(2–6) (2–3) (2–5) (2–5) (2–4) (2–5) (2–4) (2–5) (2–4)

Scales around

midbody

107.7 ± 7.8 74.7 ± 2.1 113.8 ± 9.7 78.4 ± 7.9 111.9 ± 7.5 47.8 ± 4.3 83.8 ± 6.6 75.0 ± 5.1 71.8 ± 7.2

(89–135) (72–77) (93–140) (61–100) (94–132) (38–64) (71–106) (66–83) (61–90)

Transverse rows

of ventrals

33.3 ± 1.1 30.3 ± 0.5 32.5 ± 1.2 32.2 ± 1.1 31.2 ± 1.1 31.7 ± 0.9 31.6 ± 1.1 33.9 ± 1.2 32.7 ± 0.8

(30–36) (30–31) (29–35) (30–35) (29–34) (29–34) (29–35) (32–36) (31–34)

Ventrals in

transverse row

15.6 ± 0.8 16.0 ± 0.0 14.3 ± 0.7 13.9 ± 0.7 14.7 ± 0.9 14.6 ± 0.9 12.7 ± 0.9 14.5 ± 0.8 14.0 ± 0.0

(13–17) (16–16) (13–16) (12–16) (14–16) (13–16) (12–14) (14–16) (14–14)

Femoral pores 33.1 ± 2.8 25.5 ± 2.4 37.8 ± 3.4 18.7 ± 2.5 40.3 ± 3.3 13.1 ± 1.2 10.3 ± 1.9 23.1 ± 2.5 21.1 ± 1.3

(20–40) (23–28) (28–46) (12–24) (32–49) (10–16) (6–16) (18–28) (19–24)

Prefemorals 12.7 ± 1.8 10.0 ± 0.0 12.4 ± 1.7 8.6 ± 1.1 11.9 ± 1.4 7.3 ± 0.6 7.6 ± 0.9 8.9 ± 0.9 8.8 ± 0.6

(9–19) (10–10) (7–17) (6–11) (8–16) (6–9) (6–10) (7–11) (8–10)

Prefemorals rows 15.4 ± 1.2 14.3 ± 0.5 16.2 ± 1.2 12.9 ± 1.0 16.1 ± 1.0 13.9 ± 0.8 12.2 ± 0.9 15.0 ± 1.5 13.0 ± 0.7

(12–20) (14–15) (12–19) (11–15) (14–18) (12–16) (10–14) (12–18) (11–14)

Infratibiais rows 11.6 ± 0.9 11.5 ± 1.0 11.0 ± 0.9 9.3 ± 0.9 11.5 ± 1.2 9.0 ± 0.8 8.4 ± 0.7 9.6 ± 0.8 7.9 ± 0.6

(9–14) (10–12) (9–15) (8–11) (9–15) (7–11) (7–11) (8–11) (7–9)

Preanals 4.7 ± 0.6 4.5 ± 0.6 4.6 ± 0.6 4.0 ± 0.5 4.6 ± 0.5 4.3 ± 0.5 3.8 ± 0.5 4.3 ± 0.5 4.5 ± 0.6

(4–6) (4–5) (4–6) (3–5) (3–6) (3–5) (3–5) (4–5) (4–6)

Fourth finger

lamellae

18.8 ± 1.4 18.0 ± 0.8 17.1 ± 1.1 15.1 ± 1.2 17.4 ± 1.2 16.1 ± 1.0 15.8 ± 1.0 16.2 ± 1.3 15.4 ± 0.7

(15–22) (17–19) (15–23) (12–18) (14–20) (13–19) (13–18) (14–20) (14–17)

Fourth toe

lamellae

27.3 ± 1.7 28.0 ± 0.8 26.5 ± 1.5 22.9 ± 1.9 25.8 ± 1.7 24.5 ± 1.3 23.4 ± 1.4 25.1 ± 1.5 21.7 ± 1.2

(20–33) (27–29) (22–32) (18–28) (21–31) (22–28) (20–28) (23–29) (20–24)

Dorsals 164.0 ± 17.4 118.0 ± 3.5 157.6 ± 10.0 129.5 ± 10.6 143.9 ± 9.4 84.1 ± 3.9 143.7 ± 9.2 134.0 ± 11.4 118.3 ± 5.7

(130–207) (115–121) (132–186) (106–155) (119–182) (75–93) (123–164) (116–156) (108–129)

Scales around

tail (15)

19. ± 1.6 16.5 ± 0.6 17.2 ± 1.6 15.5 ± 1.6 19.6 ± 1.5 18.2 ± 1.0 14.7 ± 1.2 17.6 ± 1.4 16.8 ± 1.1

(16–22) (16–17) (14–22) (13–19) (16–23) (15–28) (12–19) (15–20) (14–18)

266 F. P. W ER NE CK E T A L .

million years ago (Ma)] and confidence intervals (lower

bound 15.7 Ma and upper bound 48.4 Ma).

Dispersal-vicariance analysis. We inferred ancestral areas

based on parsimony, using DIVA 1.1 (Ronquist 1997), which

searches for optimal distribution of ancestral nodes that

minimize dispersal and extinction events (higher costs

events) (Ronquist 1997). We used five areas in the analysis,

corresponding to four large geological areas of the South

American Platform mostly formed during the Tertiary

(Almeida et al. 2000) and important for the diversification

of the South American herpetofauna (Colli 2005). We also

included the Atlantic Forest, corresponding to peripheral

records of Kentropyx calcarata. Thus, the areas were: (A)

Guianan Shield, (B) Amazon Basin, (C) Atlantic Forest, (D)

Brazilian Shield, and (E) Chaco-Paraná Basin (Fig. 1).

Life-history parameters

We considered females containing oviductal eggs, vitellogenic

follicles or corpora lutea as reproductive, and estimated

clutch size based on the number of eggs or vitellogenic

follicles. For reproductive analyses, we removed, counted,

and measured length and width (with digital calipers to

0.01 mm) of oviductal eggs. We calculated egg volume

with the formula for a spheroid:

where w is egg width and l is egg length. For each

individual lizard, we also measured the snout-vent length

(SVL) to 1 mm, with digital calipers.

We assessed interspecific differences in clutch size and

mean egg volume of Kentropyx, using the analysis of cov-

ariance, with SVL as the covariate, and the Tukey HSD test,

for a posteriori multiple comparisons of species means. To

assess differences in clutch size and mean egg volume of

Kentropyx between forest and open vegetation ecosystems

(calcarata group in forests; paulensis and striata groups in

open vegetations) and among all species of Kentropyx, we

built linear mixed-effects models, with species as a nested

random effect and SVL as a covariate. We chose this

approach (i) because of significant correlations between

SVL vs. clutch size (r= 0.62, t207 = 11.32, P< 0.001) and SVL

vs. mean egg volume (r= 0.45, t50 = 3.54, P< 0.001), (ii)

because the design was unbalanced, and (iii) to avoid

inflation of type I Error by pseudoreplication (degrees of

freedom should be based on species, not on individual

lizards). We performed these statistical analyses using r

version 2.7.0 (R DCT 2008).

Stearns phylogenetic-subtraction method and canonical

phylogenetic ordination

We used Stearns’ phylogenetic subtraction method (SPSM,

Stearns 1983; Harvey & Pagel 1991) and canonical phylo-

genetic ordination (CPO; Giannini 2003) to examine the

influence of habitat (major vegetation type of occurrence) on

Table 2 Species, locality, collection, collection number and GenBank Accession number

Species Locality Collection Tag GenBank Accession no.

meiva ameiva 1 Peru: Cuzco Amazônico SBH 267103 12S – AY359473, 16S – AY359493

Cnemidophorus gramivagus Venezuela: Portuguesa ALM 8199 12S – AY046432, 16S – AY046474

Kentropyx altamazonica Peru: Loreto KU 205015 12S – AY046456, 16S – AY046498

Kentropyx altamazonica Venezuela: Tapirapeco AMNH R-134175 12S – AY046455, 16S – AY046497

Kentropyx calcarata 1 Guyana: Warniabo Creek AMNH R-140967 12S – AY046458, 16S – AY046500

Kentropyx calcarata 2 Brazil: Vila Rica-MT MTR 978224 12S – AF420707, 16S – AF420760

Kentropyx pelviceps Ecuador: Sucumbios OMNH 36502 12S – AY046459, 16 s – AY046501

Kentropyx striata Guyana: Southern Rupununi Savanna AMNH R-139881 12S – AY046460, 16S – AY046502

Kentropyx paulensis 1* Brazil: Paracatu -MG CHUNB 26031 12S – EU345185, 16S – EU345179

Kentropyx paulensis 2* Brazil: Paracatu -MG CHUNB 26032 12S – EU345187, 16S – EU345181

Kentropyx vanzoi 1* Brazil: Vilhena – RO CHUNB 11631 12S – EU345191, 16S – EU345177

Kentropyx vanzoi 2* Brazil: Vilhena – RO CHUNB 11644 12S – EU345188, 16S – EU345178

Kentropyx sp. 1* Brazil: Mateiros-TO CHUNB 41296 12S – EU345192, 16S – EU345184

Kentropyx sp. 2* Brazil: Mateiros-TO CHUNB 41299 12S – EU345190, 16S – EU345180

K. viridistriga 1* Brazil: Mato Grosso UFMT 1270 12S – EU345189, 16S – EU345182

K. viridistriga 2* Brazil: Mato Grosso UFMT 2375 12S – EU345186, 16S – EU345183

ALM, field series of Allan L. Markezich, Black Hawk College, Moline, IL; AMNH, American Museum of Natural History; CHUNB, Coleção

Herpetológica da Universidade de Brasília; KU, Natural History Museum, University of Kansas; MTRs, from Miguel Trefaut Rodrigues

(IBUSP and MZUSP, São Paulo, Brazil), OMNH, Oklahoma Museum of Natural History, University of Oklahoma; SBH, Tissue collection

of S. Blair Hedges, Pennsylvania State University; UFMT, Universidade Federal do Mato Grosso, Mato Grosso, Brazil. Asterisks correspond

to sequences provided by our study.

Vw l

=⎛

⎝

⎜⎞

⎠

⎟⎛

⎝

⎜⎞

⎠

⎟

3 2 2

π,

PHYLOGENY, BIOGEOGRAPHY AND CLUTCH SIZE OF KENTROPYX 267

clutch size and egg volume, independently of phylogenetic

relationships. We performed SPSM through multiple linear

regressions between clutch size and egg volume (dependent

variables) and the phylogenetic information (independent

variables), which consisted of binary variables representing

all monophyletic groups of Kentropyx, based on a given

topology (defined in Fig. 4A). Next, we used regression

residuals, representing the variation not attributed to

phylogenetic effects, to evaluate the influence of vegetation

type upon clutch size and egg volume, using the analysis of

covariance (ancova) with SVL as covariate. We conducted

these analyses using r version 2.7.0 (R DCT 2008).

CPO is a modification of canonical correspondence

analysis (CCA, Ter Braak 1986), a constrained multivariate

ordination technique that relates the variation in a matrix

of dependent variables with another matrix of independent

variables, maximizing their correlations (Ter Braak 1986;

Giannini 2003). The significance of the association between

each monophyletic group and variables of interest is tested

by randomization of one or both of the data sets. In our

CPO, one of the matrices (Y) contained reproductive data

(clutch size and egg volume) measured over the species of

Kentropyx, whereas the other matrix (X) consisted of a tree

matrix that contained all monophyletic groups of a given

topology, each coded separately as a binary variable

(Fig. 4A) and major vegetation type of occurrence of each

species of Kentropyx. We used SVL as a covariate in CPO. The

analysis thus consisted of finding the subset of groups (columns

of X) that best explained the variation in Y, independently

of SVL, using CCA coupled with Monte Carlo permutations.

We performed CPO in Canoco 4.5 for Windows (Ter Braak &

Smilauer 2002), using the following parameters: symmetric

scaling, biplot scaling, downweighting of rare species, manual

selection of environmental variables (monophyletic groups),

9999 permutations, and unrestricted permutations.

Results

Phylogenetic analysis and biogeographic scenarios

Morphological phylogeny. The maximum-parsimony analysis

recovered a single most-parsimonious tree (Fig. 2A)

with 77 steps (CI = 0.634, RI = 0.570). Despite low branch

support values, the topology indicated the monophyly of

two groups: a forest clade consisting of K. altamazonica,

K. calcarata, and K. pelviceps and an open vegetation clade

consisting of K. striata, K. vanzoi, K. paulensis, K. viridistriga,

and Kentropyx sp. (Fig. 2A). Within the open vegetation

clade, K. striata is sister to a clade comprising K. vanzoi, K.

Fig. 1 Geographic areas used in the DIVA analysis. A: Guianan

Shield, B: Amazon Basin, C: Atlantic Forest, D: Brazilian Shield,

E: Chaco-Paraná Basin. Fig. 2 Kentropyx phylogeny inferred from morphological data. (A)

Most parsimonious tree, with bootstrap and Bremer support

values, respectively. Bremer support values are not absolute

numbers because they were divided by 999 in order to compensate

the character weighting. (B) Tree inferred by Bayesian analysis,

with posterior probability values.

268 F. P. W ER NE CK E T A L .

paulensis, K. viridistriga, and Kentropyx sp., occupying a

basal position among these species. The Bayesian analysis

produced a similar topology with a polytomy uniting

species of the forest clade (Fig. 2B).

Molecular data. We obtained five equally parsimonious

alignments for 12S sequences, with slight differences

among them, but only one most parsimonious alignment

was found for 16S sequences. We carried out phylogenetic

analyses on each of the five 12S alignments and obtained a

single topology, with small differences in bootstrap indices

and Bremer support (results not shown). Thus, we arbitrarily

chose one of the alignments to be used in the following

analyses (TreeBase Accession no. SN3720). The likelihood-

ratio test implemented in ModelTest favoured the TrN + G

model of sequence evolution [Tamura–Nei model with

a gamma distribution parameter; (Tamura & Nei 1993)]

for both 12S and 16S. Table 3 depicts the inferred base

frequencies, the ratio of invariable sites, and the gamma

distribution parameter.

The multiple alignments of 12S sequences generated a

fragment of 333 base-pair characters, with 67 informative

characters. An unweighted branch-and-bound search

produced a single most parsimonious tree with 185 steps

(CI= 0.762, RI = 0.777), placing K. striata at the base of the tree,

followed by a clade containing K. viridistriga, K. paulensis,

and Kentropyx sp., and another formed by K. vanzoi, K.

altamazonica, K. pelviceps, and K. calcarata. Except for the

placement of K. vanzoi, the other groupings had high

branch support values. The consensus tree obtained by

Bayesian analysis under the TrN + G model of evolution

had some incongruences with the MP tree, with a single

well-supported group formed by K. viridistriga, K. vanzoi,

K. paulensis, and Kentropyx sp. (paulensis group).

For the 16S gene, we obtained a fragment with 446

positions and 84 informative characters. We found two

equally most parsimonious trees with 224 steps (CI = 0.665,

RI = 0.706), with three well-supported groups: a clade

formed by K. viridistriga, K. paulensis, and Kentropyx sp.,

another formed by K. paulensis and Kentropyx sp. and a

third consisting of K. striata in basal position (striata group).

These monophyletic groups were also recovered by MP

and Bayesian analyses based on the 12S sequences. The

consensus tree obtained by Bayesian analysis under the

TrN + G model of evolution was consistent with the MP

tree, containing the same three groups.

The MP analysis of the combined molecular data (12S

+ 16S) resulted in one most parsimonious tree (Fig. 3A)

with 413 steps (CI = 0.702, RI = 0.728). The MP tree strongly

supported K. striata as the basal species (striata group),

followed by a clade consisting of K. altamazonica, K. calcarata

and K. pelviceps (the forest-dwelling calcarata group) and

another formed by K. vanzoi, K. viridistriga, K. paulensis, and

Kentropyx sp. (paulensis group). The Bayesian analysis

resulted in a different topology (Fig. 3B) but also strongly

supported the monophyly of the paulensis group.

Combined data: DNA and morphology. The combined data

included 779 molecular and 49 morphological characters,

with 156 informative characters. The MP analysis produced

a single most parsimonious tree with 454 steps (CI = 0.714,

Table 3 Parameters of molecular substitution model selected

y ModelTest for 12S and 16S regions

DNA

region

Base

frequencies

Substitution

frequency

Gamma

distribution (G

)

12S A = 0.3323 A-C = 1.0000 0.2503

C = 0.2428 A-G = 3.8806

G = 0. 1721 A-T = 1.0000

T = 0.2288 C-G = 1.0000

C-T = 12.9889

G-T = 1.0000

16S A = 0.3499 A-C = 1.0000 0.1266

C = 0.2571 A-G = 6.1200

G = 0.1642 A-T = 1.0000

T = 0.2288 C-G = 1.0000

C-T = 8.3267

G-T = 1.0000

Fig. 3 Kentropyx combined mtDNA phylogeny inferred fro

combined 12S and 16S sequences. (A) Most parsimonious tree,

with bootstrap and Bremer support values, respectively. (B) Tree

inferred by Bayesian analysis using the TrN + G model, with

posterior probability values.

PHYLOGENY, BIOGEOGRAPHY AND CLUTCH SIZE OF KENTROPYX 269

RI = 0.573, Fig. 4A). The MP tree presented three major

well-supported clades, corresponding to: (i) striata group

(at the base of the tree); (ii) calcarata group, and (iii)

paulensis group. The Bayesian analysis resulted in a similar

topology, except for the position of K. striata, which is a

sister species of the paulensis group forming a clade that

includes all open vegetations species (Fig. 4B). To investigate

if different coding strategies adopted for MP and Bayesian

analysis could be influencing the incongruent results, we

repeated MP using gap-coding for quantitative characters

(Thiele 1993), but we found exactly the same topology, with

small differences in branch support (results not shown).

In summary, relationships within and between calcarata

and paulensis groups are well established in both MP and

Bayesian analysis (Fig. 4). Conversely, the two approaches

disagree only in the placement of K. striata, either placed in

a basal position related to all other species (MP) or in a

more derived position as sister taxon of the paulensis group

(Bayesian). Based on the larger number of informative

characters supporting the relationships of K. striata (6

morphological and 13 molecular in the MP topology; 5/0

in the Bayesian topology), on higher nodal support values

for the placement of K. striata (even if nodal support and

posterior probabilities are not directly comparable), and

on the smaller number of assumptions, we favoured the

topology recovered by MP for performing the analyses

that follow.

Molecular dating. The molecular dating analysis indicated

an early diversification of Kentropyx species mostly during

the Miocene (Fig. 5). According to our analysis, K. striata

was the first species to diverge during the Late Oligocene–

Early Miocene, and the last divergence was between K.

paulensis and Kentropyx sp. during the Late Miocene–Early

Pliocene. The calcarata and paulensis groups probably

diverged in the Early–Middle Miocene and the only

diversification that took place during the Quaternary was

among populations within species (Fig. 5).

Fig. 4 Kentropyx phylogeny inferred from

combined molecular (12S + 16S) and

morphological data. (A) Most parsimonious

tree, with bootstrap and Bremer support

values, respectively. Bremer support values

are not absolute numbers because they

were divided by 999 in order to compensate

the character weighting. (B) Tree inferred

by Bayesian analysis using the TrN + G

model, with posterior probability values.

Letters above clades correspond to mono-

phyletic groups of Kentropyx used as

individual groups in canonical phylogenetic

ordination.

270 F. P. W ER NE CK E T A L .

Dispersal–vicariance analysis. The DIVA analysis found two

equally most parsimonious reconstructions, with four

dispersal events each during the evolution of Kentropyx

(Fig. 6). In both reconstructions, the divergence of K. striata

was due to a vicariance event that isolated this group in the

Guianan Shield. In addition, both reconstructions indicate

that the divergence of the calcarata (in the Amazon Basin)

and paulensis (in the Brazilian Shield) groups was due to

vicariance. The two reconstructions differ in whether the

common ancestor of all living species of Kentropyx was

restricted to the Guianan and Brazilian Shields (Fig. 6A) or

if it also inhabited the Amazon Basin (Fig. 6B). The first

reconstruction implies that, after the divergence of K.

striata by vicariance and isolation in the Guianan Shield,

the common ancestor of the calcarata and paulensis groups

occupied the Amazon Basin via dispersal (Fig. 6A). According

to the second reconstruction, the common ancestor of all

living species of Kentropyx was widespread, occupying

the Amazon Basin and the Brazilian and Guianan Shields

due to an earlier dispersal event (Fig.6B). Both reconstructions

require one dispersal event of K. calcarata into the Atlantic

Forest and another involving the common ancestor of

K. viridistriga, K. paulensis, and Kentropyx sp. into the

Chaco-Paraná Basin.

Reproduction life-history evolution

Female reproduction. We obtained reproductive data from

all nine species of Kentropyx, but had no reproductive

female of Kentropyx sp. (Table 4). For data analysis, we

considered only reproductive females containing oviductal

eggs or vitellogenic follicles. Mean clutch size ranged from

3.31 (K. vanzoi) to 7.33 (K. viridistriga) (Table 5). For some

species, our results indicated clutch sizes largely different

from previous literature reports. For instance, previous

studies indicate clutches of K. viridistriga of 6–7 eggs,

whereas we recorded a maximum clutch size of 12 eggs

(Table 5). Clutch size differed significantly among species

(irrespective of habitat), independently of SVL (ancova

F7,200 = 12.97, P< 0.001). Based on post hoc Tukey HSD tests,

we found that clutch size of Kentropyx pelviceps (adjusted

mean ± SE: 3.84 ± 0.23) was significantly smaller than

Fig. 5 Chronogram of Kentropyx evolution based on the combined

morphological and molecular data, with divergence times estimated

from a Bayesian relaxed molecular clock approach. Boxes indicate

mean divergence time ± one standard deviation.

Fig. 6 Reconstructed ancestral distributions for each node on the

most parsimonious solutions obtained that consider (A) Guianan

and Brazilian Shield as ancestral areas or (B) Amazon Basin as an

ancestral area as well.

Table 4 Distribution of females of nine species of Kentropyx,

according to the reproductive condition

Species

Non reproductive

females

Reproductive

females

Total of

females

K. altamazonica† 70 38 108

K. borckiana§ 1 1 1

K. calcarata† 34 56 90

K. paulensis‡ 8 19 27

K. pelviceps† 33 31 64

K. striata§ 68 45 113

K. vanzoi‡ 26 13 39

K. viridistriga‡ 1 7 8

Kentropyx sp.‡ 9 0 9

†calcarata group; ‡paulensis group; §striata group.

PHYLOGENY, BIOGEOGRAPHY AND CLUTCH SIZE OF KENTROPYX 271

K. altamazonica (5.70 ± 0.16), K. calcarata (5.02 ± 0.14), and

K. striata (5.89 ± 0.15), whereas K. striata had significantly

larger clutches than K. calcarata (Tukey HSD, P< 0.05).

In addition, clutches of K. viridistriga (7.67 ± 0.41) were

significantly larger than all other species of Kentropyx.

Species differ significantly in mean egg volume, indepen-

dently of SVL (ancova F6,44 = 6.60, P< 0.001). Based on

post hoc Tukey HSD tests, mean egg volume of K. striata

(adjusted mean ± SE: 671.40 ± 53.03 mm3) was significantly

smaller than K. calcarata (928.45 ± 39.20 mm3) and K. pelviceps

(1112.59 ± 71.29 mm3), whereas mean egg volume of K.

pelviceps was larger than K. altamazonica (709.28 ± 40.61mm3).

However, there was no difference between forest and

open-vegetation species in clutch size (forest: 5.5 ± 1.1;

open-vegetation: 4.9 ±1.6; F1,6 =5.22; P= 0.06), or egg volume

(forest: 4= 868.42 ± 201.46 mm3, n= 36; open-vegetation:

4= 650.20 ± 164.17 mm3, n= 16; F1,5 = 4.12; P= 0.10),

independently of SVL.

CPO and stearns phylogenetic-subtraction method. Multiple

linear regressions from the Stearns’ phylogenetic subtraction

method revealed no significant phylogenetic effects on

clutch size (F4,2 = 0.645, P= 0.683) or egg volume (F4,2 = 2.003,

P= 0.359) of Kentropyx. An ancova on the regression

residuals revealed no significant influence of major habitat

type on clutch size (F1,4 = 0.313, P= 0.605) or egg volume

(F1,4 = 0.603, P= 0.481), independently of phylogenetic

structure. Moreover, SVL was significantly correlated with

both clutch size (r= 0.768, t= 2.683, P= 0.044) and egg

volume (r= 0.936, t= 5.927, P< 0.001). Monte Carlo

permutations from CPO revealed no significant effects of

phylogenetic structure or habitat type on reproductive

parameters of Kentropyx (Table 6).

Discussion

Phylogenetic relationships and historical biogeography of

Kentropyx

The total evidence reconstructions, based on morphological

and molecular data, supported the monophyly of the

three phenetic groups of Kentropyx previously recognized

(Gallagher 1979), both using MP and Bayesian methods.

However, our results differ fundamentally from previous

proposals in the placement of K. striata (which represents

the striata group). According to our MP combined analysis,

K. striata is the most basal, and not the most derived species

of Kentropyx. Gallagher & Dixon (1992) advocated the

Table 5 Clutch size and egg volume (in mm3) of eight species of Kentropyx observed in this study and obtained from the literature. Values

indicate x± SD, sample size (in parentheses), and range (only for clutch size)

Species

Clutch size

(this study)

Egg volume

(this study)

Clutch size

(literature) Source†

K. altamazonica 5.45 ± 1.11 (38) 713.45 ± 127.94 (14) 2,4 1

3–9

K. borckiana 6 (1) — 5,9 2

K. calcarata 5.63 ± 1.23 (56) 921.16 ± 149.13 (16) 3,7 1,2,3,4

3–9

K. paulensis 3.90 ± 0.78 (19) 528.94 ± 189.10 (4) 3–5 5

3–6

K. pelviceps 5.52 ± 0.85 (31) 1089.39 ± 200.25 (6) 5–8 6

4–7

K. striata 5.84 ± 1.72 (45) 670.65 ± 135.69 (8) 3–10 1,7,8

3–12

K. vanzoi 3.31 ± 1.18 (13) 510.11 (1) — —

(1–6)

K. viridistriga 7.33 ± 2.34 (6) 804.06 ± 87.42 (3) 6–7 2

(6–12)

†1- Ávila-Pires (1995); 2- Gallagher & Dixon (1992); 3- Vitt (1991); 4- Magnusson & Lima (1984); 5- Anjos et al. (2002); 6- Vitt et al. (1995);

7- Dixon et al. (1975); 8- Vitt & Carvalho (1992).

Table 6 Effect of monophyletic groups and ecosystems on the

reproductive features of Kentropyx. Clade labels according to Fig. 4

Groups Variation F P

A < 0.01 0.190 0.7692

B < 0.01 0.122 0.7143

D < 0.01 0.411 0.5225

E < 0.01 0.050 0.8132

Ecosystems < 0.01 0.122 0.7063

272 F. P. W ER NE CK E T A L .

lower number of dorsals (because of their larger sizes) and

femoral pores of K. striata as an adaptation for dry, open

ecosystems and as a derived condition relative to the

paulensis and calcarata groups, since other teiid genera do

not share these character states (Gallagher & Dixon 1992).

However, even if the phenetic grouping proposed previously

(Gallagher & Dixon 1992) matches the phylogenetic

relationships (this study), the relations among groups

should not necessarily follow the evolution of a single

character. The same sort of gene tree vs. species tree incon-

gruence problems deriving from single gene phylogenies

(Doyle 1997; Maddison 1997) can also occur for a single

morphological character phylogeny. Furthermore, correla-

tions between scale counts and surface area available for

thermoregulation or environmental properties are not

clear and straight. Controversial results indicate both

positive (Soulé & Kerfoot 1972; Malhotra & Thorpe 1997;

Sanders et al. 2004) and negative (Horton 1972; Lister 1976)

correlations between number of scales (inversely propor-

tional to their sizes) and drier environments. In addition,

Gallagher & Dixon (1992) used this character evolution

scenario and the current species distribution to conclude

that the ancestral Kentropyx ‘proceeded from a forest proto-

Kentropyx stock, derived from an Ameiva-Cnemidophorus-like

ancestor’ and that Quaternary refuge events promoted the

diversification of the genus, with secondary colonization

of drier, open environments. In summary, previous studies

addressing Kentropyx evolution proposed phylogenetic

relationships and biogeographic scenarios for the genus

without implementing rigorous phylogenetic analyses,

using alternative data sets, or including any biogeographic

reconstruction.

Our evolutionary scenario implies that Kentropyx striata

was the first species to diverge in the genus, at Late Oli-

gocene–Early Miocene, and that enlargement of dorsal

scales occurred early in the evolution the genus, with a

possible reversal occurring later in the calcarata group. The

basal divergence between K. striata (a Guianan Shield species)

and other species of Kentropyx is paralleled by other vertebrate

groups and concordant with a basal Brazilian/Guianan

Shield split, frequently attributed to Miocene marine intro-

gressions (Rasanen et al. 1995; Webb 1995; Ribas et al. 2005;

Noonan & Wray 2006; Garda & Cannatella 2007). Most of

Kentropyx diversification occurred at the Oligocene/Miocene,

a period fundamentally relevant for the diversification of

South America’s fauna (Gamble et al. 2008).

The period of origin of Kentropyx (Eocene/Oligocene)

was marked by savanna expansion in South America

(Giugliano et al. 2007) and is much more ancient than the

previously suggested origin and diversification during the

Quaternary (Gallagher & Dixon 1992). Thus, the ‘Pleistocene

Refuge Hypothesis’ has only limited importance for the

diversification of Kentropyx species, being able to explain

only the recent diversification of populations. This and the

DIVA results suggest that the ancestor of Kentropyx was not

a forest-dweller as previously proposed (might be both

present in the Amazon Basin or totally non-forest). Given

that the close relatives of Kentropyx are primarily open

vegetation taxa even when occurring in the Amazon Basin,

an open vegetation ancestor is more plausible (Fig. 6A).

Therefore, savannas were likely the centre of origin of the

genus, instead of Amazonian forest, and successive Tertiary

events played a significant role in the differentiation of

living species. Accordingly, the distribution of species of the

calcarata group in the Amazon Basin is better explained as

a more recent dispersal, after the beginning of the marine

retraction.

Both most parsimonious DIVA reconstructions required

a dispersal event of K. calcarata into the Atlantic Forest.

Faunal and floral affinities between Amazon and Atlantic

forests are extensively documented (Andrade-Lima 1982;

Oliveira-Filho & Ratter 1995; Silva 1995; Bates et al. 1998;

Costa 2003). Older vicariance connections might be respon-

sible for some of these affinities, but most might be attributed

to one of the several more recent (Quaternary) forest corridors

proposed, acting as dispersal routes linking these forests

(Andrade-Lima 1982; Rizzini 1963, 1979; Bigarella et al.

1975; Oliveira-Filho & Ratter 1995). As a result, considering

the recent divergence between the two forest populations

of K. calcarata included here (3.4 Ma), the main distribution

of this species in eastern Amazonia and the occurrence of

Quaternary forest corridors previously connecting Amazon

and Atlantic Forests, the dispersal scenario proposed by

DIVA is supported.

Independent of the character partition analyzed and

optimality criteria adopted, some relationships were

typically recovered with high bootstrap and Bremer nodal

support and posterior probabilities values, such as the sister

relationship between K. paulensis and Kentropyx sp. and

between these two species and K. viridistriga. Further, the

monophyly of the paulensis group was well-supported, in

contrast to the calcarata group. Genetic population studies

might be useful to reveal higher levels of genetic similarity

and possible gene flow among species of the calcarata

group. The monophyly of the paulensis group corroborates

the hypotheses that the three emergent large land blocks

(Guianan Shield, Brazilian Shield, and Eastern base of the

Andes) during marine introgressions in the Tertiary (Miocene)

of South America would bear monophyletic taxa when

compared to lowlands (Aleixo 2004; Rasanen et al. 1995;

Webb 1995). This scenario was already corroborated from

the point of view of different groups of vertebrates (Aleixo

2004; Ribas et al. 2005; Noonan & Wray 2006; Garda &

Cannatella 2007).

In contrast to previous suggestions that K. vanzoi and K.

paulensis are sister species, primarily distributed in Cerrado

of Brazilian Shield (Colli 2005), our results indicate that K.

paulensis is the sister species of Kentropyx sp. and is more

PHYLOGENY, BIOGEOGRAPHY AND CLUTCH SIZE OF KENTROPYX 273

closely related to K. viridistriga, which inhabits the Chaco-

Paraná depressions, than to K. vanzoi. The early divergence

between K. vanzoi and the other species of the paulensis

group might be attributed to isolation in the Parecis

Plateau, an extensive sedimentary basin (Hasui & Almeida

1985; Bahia et al. 2006) which experienced a regional uplift

during the Miocene (Costa et al. 1996; Westaway 2006).

Further, our DIVA results indicate that the common ancestor

of K. viridistriga, K. paulensis, and Kentropyx sp. was widely

distributed in the Brazilian Shield and the Chaco-Paraná

Basin, and that a later vicariance event, probably the final

epeirogenic uplift of the Brazilian Shield during Middle–

Late Tertiary (Colli 2005), promoted the divergence between

K. viridistriga and the sister group, in the Pantanal and

Guaporé depressions. More recently, a parapatric speciation

event associated with sandy soils of the Tocantins depression

might have promoted the divergence between K. paulensis

and Kentropyx sp.

Reproduction life history evolution

Considering the direct comparisons between species, we

found that clutch size and eggs volume can significantly

differ between species of the same group (for instance for

clutch size: K. pelviceps vs. other calcarata group species), as

well as species of different groups (as Kentropyx striata vs.

K. calcarata; K. viridistriga vs. all other species). Within the

paulensis group the significantly lower clutch size of Kentropyx

paulensis and K. vanzoi, relative to K. viridistriga, suggests a

derived condition. This implies that low clutch size should

have evolved twice within the paulensis group or this

characteristic was secondarily lost in K. viridistriga, which

has the greatest clutch size among all species of Kentropyx

(Table 5).

Our results did not corroborate the hypothesis of Fitch

(1982) that postulates larger clutch sizes and smaller eggs

in open vegetation species and smaller clutch sizes with

larger eggs in forest species, irrespective of phylogenetic

structure. Thus, although forest and open vegetation species

of Kentropyx form monophyletic groups, easily distinguished

by meristic characters, such as femoral pores (Table 1), they

show conservatism in life history traits. A possible expla-

nation is that variation in reproductive parameters we

studied is not affected by major habitat type where species

occur. Consequently, species of Kentropyx did not diverge

in a significant way with respect to their ancestral life

history characters. Therefore, nonadaptive phylogenetic

constraints and inertia seem to determine clutch size and

egg volume in Kentropyx, instead of limitations on resource

availability associated with different habitat types.

Phylogenetic constraints might be recognized when a

given trait was in the environment where it has originally

evolved, but is under limits on the production of new

phenotypic variants (Harvey & Pagel 1991; Blomberg &

Garland Jr 2002). Phylogenetic constraints (instead of envi-

ronmental and climatic variables) that might limit variation

in reproductive parameters of Kentropyx include: female

body size, availability of nest sites, foraging mode, ther-

moregulation requirements, pelvic constraints (characterized

by the inability of large eggs to pass through a small pelvic

aperture), life habits (some species have semi-arboreal and

semi-aquatic habits), and locomotion performance, among

others (Aubret et al. 2005; Vitt & Congdon 1978; Vitt 1981;

Vitt & Price 1982; Shine & Schwarzkopf 1992; Oufiero et al.

2007; Pizzato et al. 2007). On the other hand, phylogenetic

inertia is often invoked as an alternative hypothesis to

adaptation by means of natural selection, to explain lack of

interspecific variation in phenotypic traits (Blomberg &

Garland Jr 2002). Hence, even after the ending of selective

forces that have produced/maintained them, some traits

might persist within a lineage (Blomberg & Garland 2002).

Accordingly, even accounting for phylogenetic influences,

the major clades of Kentropyx present negligible variation

in their reproductive strategies. It is essential to emphasize

the importance of including species historical relationships

in comparative analyses of life history traits. The current

features of species and populations may reflect only past

adaptations of their ancestors, phylogenetic inertia, and

constraints, instead of current adaptations to environmental

variation. Thus, ignoring the phylogenetic context may

imply ignoring the determinant aspect, as shown for

Kentropyx.

Conclusions

In summary, our results show that living species of Kentropyx

form three monophyletic groups, which correspond to the

phenetic grouping proposed earlier: calcarata, paulensis and

striata. However, relationships among the groups differ

from previous suggestions, with K. striata being the most

basal species. The origin of the genus date back to the

Tertiary (Eocene/Oligocene) and the ‘Pleistocene Refuge

Hypothesis’ cannot account for the diversification of

Kentropyx, and can only be associated with more recent

divergence among populations. Ancestors of the genus

were not restricted to forests as previously suggested and

could be either present or absent from the Amazon Basin.

We argue that a savanna ancestor is more likely and that

the historical events which promoted the diversification of

the genus include: (i) isolation of Brazilian/Guianan Shields

attributed to Miocene marine introgressions, corresponding

to the basal divergent between K. striata (a Guiana Shield

species) and other Kentropyx species, specially the monophyletic

paulensis group in the Brazilian Shield; (ii) distribution of

calcarata species group in Amazon Basin possibly due to

dispersion after the marine retraction; (iii) distribution of K.

calcarata in Atlantic forest due to more recent (Quaternary)

forest corridors acting as dispersion routes linking this

274 F. P. W ER NE CK E T A L .

forests with the Amazon; (iv) differentiation of K. vanzoi

from other species of the paulensis group occurring during

the Miocene, coinciding with the isolation of the Parecis

Plateau; (v) final epeirogenic uplift of the Brazilian Shield

during the Late Tertiary, driving the differentiation of K.

viridistriga in the Pantanal and Guaporé depressions and

(vi) divergence between K. paulensis and Kentropyx sp. due

to parapatric speciation in the Tocantins depression. SPSM

and CPO showed that variation in reproductive parameters

was not determined by the major habitat type where species

occur, but may reflect past adaptations and phylogenetic

inertia, essential aspects of life history evolution for Kentropyx.

Acknowledgements

We thank to L.J. Vitt for making available his data on the reproduction

of some species of Kentropyx. We also thank G.H.C. Vieira for

comments on a previous version of the manuscript; R. Teixeira

and D.O. Mesquita for sharing their experience on meristic data

collecting and analyses; C. Nogueira for providing material for the

study and helpful comments on the work; A. A. Garda for help

with the biogeographic reconstruction figures. We also thank Eric

Taylor, Tiffany Doan and an anonymous reviewer for helpful

comments on the manuscript. We also acknowledge the curators

and collection managers of the following museums for the support

and specimen loans: Coleção Herpetológica da Universidade de

Brasília; Field Museum of Natural History; Instituto Nacional de

Pesquisas da Amazônia; Natural History Museum, University of

Kansas; Museum of Vertebrate Zoology; Museu de Zoologia da

Universidade de São Paulo; and Sam Noble Oklahoma Museum

of Natural History. This work was supported by Conselho

Nacional de Desenvolvimento Científico e Tecnológico-CNPq,

through student fellowships to F.P.W and L.G.G. and research

fellowships to G.R.C. and R.G.C. and by Fundação de

Empreendimentos Científicos e Tecnológicos-Finatec.

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Fernanda P. Werneck is a Brazilian PhD student at Brigham Young

University currently working on the phylogeography, niche

modelling, and conservation genetics of lizards from Seasonally

Dry Tropical Forests of South America. Her main research

interests are biodiversity, phylogeography and biogeography

of Neotropical herpetofauna. Lilian G. Giugliano is a PhD student

at Universidade de Brasília focusing cnemidophorines phylogenetic

relationships and evolution based on molecular and morphological

data. Dr Rosane Garcia Collevatti is a geneticist who is interested

in understanding population genetics and phylogeny of tropical

species. Dr Guarino R. Colli is a professor in the Department of

Zoology at the University of Brasília, with major research interests

on the ecology, biogeography, and systematics of the Cerrado

herpetofauna.

PHYLOGENY, BIOGEOGRAPHY AND CLUTCH SIZE OF KENTROPYX 277

Appendix I

Specimens examined

The specimens are referred by their individual catalogue

numbers, and initials for their respective collections are as

follows: CHUNB (Coleção Herpetológica da Universidade

de Brasília); FMNH (Field Museum of Natural History),

INPA (Instituto Nacional de Pesquisas da Amazônia), KU

(Natural History Museum, University of Kansas); MVZ

(Museum of Vertebrate Zoology); MZUSP (Museu de

Zoologia da Universidade de São Paulo).

Kentropyx altamazonica (235): CHUNB: 7505, 7507, 7508,

9816, 9821–9823, 9829, 9836, 11410–11431, 12775, 12776,

12778, 13327–13331, 13620, 18163–18210, 18212–18217, 22258,

22287, 22327. FMNH: 168016–168021, 168023, 168025,

168064–168066, 168069, 168071, 168075, 168131, 168175,

168177, 168225, 168230, 168232, 168235–168238, 168244,

168247, 168248, 168259, 168275, 168286, 168287, 168290,

168331, 168333–168336, 168338, 168343, 168345–168347,

168356, 168358, 168385–168388, 168390, 168393, 168395,

168397–168399, 168401, 168402, 168414, 168421, 168447,

168451, 168453, 168455, 168458, 208464, 218566, 229382,

229384. INPA: 491, 1466–1470, 1476–1479, 1490, 1494–1497,

1506–1509, 9480, 9481, 9483, 9492, 9493, 9496, 9498, 9499,

9676. KU: 205009, 205015, 209211–209214. MVZ: 163086–

163088, 163090–163101, 163103–163113, 174856–174863.

MZUSP: 52414, 60800, 70280.

Kentropyx borckiana (4): MZUSP: 51627–51630.

Kentropyx calcarata (231): CHUNB: 1653, 1654, 1656, 5215,

5225–5236, 7360–7362, 7500–7504, 7506, 7509, 9819, 9838,

11295, 11296, 12360, 12504, 12505, 13623, 13624, 13876–13878,

14095, 14096, 15131, 15137, 16145, 16959, 16960, 22239–22250,

22252–22257, 22259, 22260, 22281–22317, 22319–22326,

23822, 24653, 28972, 28994, 29046–29048, 29275. FMNH:

128956, 128958, 128961, 128965–128970, 134728. INPA: 62,

65, 68, 71, 74, 77, 78, 82, 131, 179, 194, 195, 225, 226, 814, 858,

859, 912, 919–923, 1083, 1128, 1274, 1275, 1309, 1310, 1480,

9023, 9591–9593, 9742, 10513, 11500, 11534, 11541, 11551.

KU: 69806–69808, 97864, 124630, 127241–127244, 167544–

167548. MZUSP: 885, 56785, 60795–60799, 60801, 67728,

68980–68982, 72655, 72658, 72840–72843, 72937–72949,

73280–73298.

Kentropyx paulensis (96): CHUNB: 1657, 5216, 8216, 9431,

9534, 11562–11566, 11568, 13628, 21755, 21756, 21758, 24529,

24541, 24549, 25672–25689, 26030–26033, 26512, 28010–28026,

30887. MZUSP: 10, 402, 629, 970, 986, 999, 1027, 2550, 2622,

4789–4792, 4794, 4795–4797, 4800–4804, 4850, 9944, 21464,

28427, 30716, 78162, 78163, 79655, 83204–83207, 87666,

93411.

Kentropyx pelviceps (156): INPA: 2183, 2184, 9413, 9482,

9484–9490, 9494, 9497, 9594, 9674, 9675, 9677, 9678, 10388,

10440, 11542. KU: 98948, 98949, 105376, 105377, 105379,

109713–109746, 122181–122188, 126793–126800, 144379,

147186, 148194–148204, 175341, 205007, 205008, 205010,

205012, 205013. MVZ: 163114–163138, 173758, 174869–174876,

174878, 174879, 174881, 174883, 174886, 174887, 174889,

174890, 175782, 199526. MZUSP: 12995, 32343, 32346,

32347, 32484, 41524, 41525, 41777, 42114, 42115, 42394–42396,

42399, 72652, 72653, 72656.

Kentropyx striata (219): CHUNB: 1197–1199, 1280–1292,

1300–1317, 1607–1652, 5217–5222, 5237–5243, 14093, 14094,

30825–30833. INPA: 1283, 1284, 10448–10464. MVZ: 84048–

84050. MZUSP: 2158, 2977, 3000, 7145, 7214, 7215, 7217–7243,

7246–7248, 7730, 7735, 13525, 15074, 15368–15372, 16593,

16594, 18586, 18587, 23610, 35403, 66702–66704, 66849–66858,

66860–66878, 66985, 66997, 69085–69091, 72659.

Kentropyx vanzoi (160): CHUNB: 9824, 11591–11650, 12274–

12280, 14057, 25289, 25290. MZUSP: 783, 801, 806–811, 834–838,

881, 898, 921–923, 941, 942, 64556–64570, 64572–64578,

64581–64605, 74988, 74989, 81614–81828, 88197, 88408–

88410, 93410.

Kentropyx viridistriga (21): CHUNB: 29198, 29279. MVZ:

127394–127407. MZUSP: 45906, 45927, 57855, 57856, 74987.

Kentropx sp. (21): CHUNB 9996 10008 10009 10042 10043

10053 10070 10109 10160 10221 10225 10232–10235 10299

10407 10408 10448 10462 10497.

Ameiva ameiva (42): CHUNB: 00868–00877, 00920–00930,

00941–00950, 01553–01559, 01603–01606.

Cnemidophorus gramivagus (64): CHUNB: 3501–3508, 3511,

3513–3515, 3517, 3519, 3520–3522, 3525–3527, 3529–3533,

3535–3545, 3547–3553, 3555–3564, 3509, 3510, 3512, 3516,

3518, 3523, 3524, 3528, 3534, 3554, 7944.

Appendix II

Morphologial data description

From each specimen, we recorded the following quantitative

meristic characters: supralabials (number of enlarged

scales along the upper jaw, total on both sides), infralabials

(number of enlarged scales along the lower jaw, total on

both sides), gular folds (number of folds in the gular

region), collar scales (number of enlarged scales present in

the gular fold), supraoculars (number of supraocular scales

on left side), parietals (number of parietal scales, including

the interparietal scale), postparietals (number of postparietals

scales contacting the interparietal scale, granular scales

278 F. P. W ER NE CK E T A L .

were included when present), dorsals (counted along the

midline, from occiput to first transverse row of scales

around tail), scales around mid-body (counted midway

between fore- and hindlimbs, excluding ventrals), transverse

rows of ventrals (counted along the midline, from gular

fold to anterior margin of hindlimbs), ventrals in one trans-

verse row (counted midway between fore- and hindlimbs),

femoral pores (total number on both sides), prefemorals

(number of enlarged scales on anterior aspect of thigh,

counted midway between the hip and the knee, on a row

from femoral pores to granules on dorsal aspect of thigh),

prefemoral rows (counted from hip to knee), infratibial

rows (number of enlarged scales on longitudinal row from

knee to base of first metatarsal), preanals (number of enlarged

scales on preanal plate, from level of medialmost femoral

pores to vent), fourth finger lamellae (counted under the

finger), fourth toe lamellae (counted under the toe), scales

around tail (counted on 15th transverse row).

We recorded the following qualitative characters, with

no intraspecific variation (polymorphism): granular scales

between chinshields and infralabials (absent or present),

contact between supraciliaries and supraoculars (absent or

present), precloacal spur in males (absent or present), keeled

ventrals (absent or present), and dorsal scales of tail (smooth

or keeled). Finally, we also scored the following qualitative

characters, with intraspecific variation (polymorphism):

shape of frontonasal (hexagonal or pentagonal); degree

of contact between first pair of chinshields (no contact;

contact smaller than half of their lengths or contact greater

than half of their lengths); degree of contact between

supraoculars and medial head scales (supraoculars

contacting prefrontal, frontal, frontoparietals and parietals;

supraoculars contacting prefrontal, frontal and frontopari-

etals; supraoculars contacting prefrontal and frontoparietal;

no contact between supraoculars and medial head scales);

shape of posterior margin of interparietal (flat, angular or

rounded); condition of dorsals (granular dorsal and lateral

scales, with a clear distinction between dorsals and keeled

plate-like supracaudals; granular dorsal and lateral scales,

gradually enlarging to the tail, where dorsal and supracau-

dals are almost indistinct; rows of enlarged plate-like

dorsal and granular lateral scales); hindlimb spots (absent

or present), lateral spots (absent or present) and pattern of

stripes and fields. Fields are delimitated by stripes, and

we considered the following states: absent (when stripes

that delimit field are absent), dark, spotted, or light. The

fields we scored were: vertebral fields (middorsal between

paravertebral and vertebral stripes); dorsolateral fields

(between paravertebral and dorsolateral stripes); upper

lateral fields (between dorsolateral and upper lateral stripes);

and lower lateral fields (between lateral stripes and ventral

scales).

Kentropyx sp. CHUNB 41296 16S ribosomal RNA gene, partial sequence; mitochondrial

Nucleotide Sequence

December 2007

L.G. Giugliano · Fernanda P Werneck · Rosane Garcia Collevatti · Guarino R Colli

Kentropyx paulensis voucher CHUNB 26032 16S ribosomal RNA gene, partial sequence; mitochondrial

Nucleotide Sequence

December 2007

L.G. Giugliano · Fernanda P Werneck · Rosane Garcia Collevatti · Guarino R Colli

Kentropyx vanzoi voucher CHUNB 11631 12S ribosomal RNA gene, partial sequence; mitochondrial

Nucleotide Sequence

December 2007

L.G. Giugliano · Fernanda P Werneck · Rosane Garcia Collevatti · Guarino R Colli

Kentropyx paulensis voucher CHUNB 26031 12S ribosomal RNA gene, partial sequence; mitochondrial

Nucleotide Sequence

December 2007

L.G. Giugliano · Fernanda P Werneck · Rosane Garcia Collevatti · Guarino R Colli

Kentropyx paulensis voucher CHUNB 26032 12S ribosomal RNA gene, partial sequence; mitochondrial

Nucleotide Sequence

December 2007

L.G. Giugliano · Fernanda P Werneck · Rosane Garcia Collevatti · Guarino R Colli

Kentropyx sp. CHUNB 41299 16S ribosomal RNA gene, partial sequence; mitochondrial

Nucleotide Sequence

December 2007

L.G. Giugliano · Fernanda P Werneck · Rosane Garcia Collevatti · Guarino R Colli

Kentropyx vanzoi voucher CHUNB 11644 12S ribosomal RNA gene, partial sequence; mitochondrial

Nucleotide Sequence

December 2007

L.G. Giugliano · Fernanda P Werneck · Rosane Garcia Collevatti · Guarino R Colli

Kentropyx sp. CHUNB 41299 12S ribosomal RNA gene, partial sequence; mitochondrial

Nucleotide Sequence

December 2007

L.G. Giugliano · Fernanda P Werneck · Rosane Garcia Collevatti · Guarino R Colli

Kentropyx viridistriga voucher UFMT 2375 16S ribosomal RNA gene, partial sequence; mitochondrial

Nucleotide Sequence

December 2007

L.G. Giugliano · Fernanda P Werneck · Rosane Garcia Collevatti · Guarino R Colli

Kentropyx paulensis voucher CHUNB 26031 16S ribosomal RNA gene, partial sequence; mitochondrial

Nucleotide Sequence

December 2007

L.G. Giugliano · Fernanda P Werneck · Rosane Garcia Collevatti · Guarino R Colli

Kentropyx sp. CHUNB 41296 12S ribosomal RNA gene, partial sequence; mitochondrial

Nucleotide Sequence

December 2007

L.G. Giugliano · Fernanda P Werneck · Rosane Garcia Collevatti · Guarino R Colli

Kentropyx viridistriga voucher UFMT 2375 12S ribosomal RNA gene, partial sequence; mitochondrial

Nucleotide Sequence

December 2007

L.G. Giugliano · Fernanda P Werneck · Rosane Garcia Collevatti · Guarino R Colli

Kentropyx vanzoi voucher CHUNB 11631 16S ribosomal RNA gene, partial sequence; mitochondrial

Nucleotide Sequence

December 2007

L.G. Giugliano · Fernanda P Werneck · Rosane Garcia Collevatti · Guarino R Colli

Kentropyx viridistriga voucher UFMT 1270 12S ribosomal RNA gene, partial sequence; mitochondrial

Nucleotide Sequence

December 2007

L.G. Giugliano · Fernanda P Werneck · Rosane Garcia Collevatti · Guarino R Colli

Kentropyx vanzoi voucher CHUNB 11644 16S ribosomal RNA gene, partial sequence; mitochondrial

Nucleotide Sequence

December 2007

L.G. Giugliano · Fernanda P Werneck · Rosane Garcia Collevatti · Guarino R Colli

Kentropyx viridistriga voucher UFMT 1270 16S ribosomal RNA gene, partial sequence; mitochondrial

Nucleotide Sequence

December 2007

L.G. Giugliano · Fernanda P Werneck · Rosane Garcia Collevatti · Guarino R Colli

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