Phylogeographical structure within Boa constrictor imperator across the lowlands and mountains of...

ORIGINALARTICLE

Phylogeographical structure withinBoa constrictor imperator across thelowlands and mountains of CentralAmerica and MexicoMarco Su�arez-Atilano1,4, Frank Burbrink2,3 and Ella V�azquez-Domı́nguez1*

1Departamento de Ecolog�ıa de la

Biodiversidad, Instituto de Ecolog�ıa,

Universidad Nacional Aut�onoma de M�exico,

Ciudad Universitaria, M�exico, DF 04510,

M�exico, 2Department of Biology, The

Graduate School, City University of New

York, New York, NY 10016, USA,3Department of Biology, College of Staten

Island, Staten Island, NY 10314, USA,4Posgrado en Ciencias Biol�ogicas, Universidad

Nacional Aut�onoma de M�exico, Coyoac�an,

M�exico, DF 04510, M�exico

*Correspondence: Ella V�azquez-Dom�ınguez,

Departamento de Ecolog�ıa de la Biodiversidad,

Instituto de Ecolog�ıa, Universidad Nacional

Aut�onoma de M�exico, Ap. Postal 70-275,

Ciudad Universitaria, M�exico, DF 04510,

M�exico.

E-mail: [email protected]

ABSTRACT

Aim To evaluate the genetic diversity and phylogeographical structure of Boa

constrictor imperator, in order to identify the key historical events responsible

for its current distribution and diversity.

Location The Neotropical region of Mexico and mainland Central America.

Methods We used data from the mitochondrial cytochrome b gene, nuclear

ornithine decarboxylase intron and microsatellites to perform spatial genetic

analyses, and coalescence methods to infer phylogeographical structure, diver-

gence times and historical demography.

Results Cytochrome b results revealed two main reciprocally monophyletic

lineages, one along the Mexican Pacific coast and another along the Gulf of

Mexico, Yucat�an Peninsula and Central America, diverging c. 5.2 Ma. Both lin-

eages are subdivided into haplogroups and show steady historical growth and a

more recent population expansion. High genetic diversity was observed for

both cytochrome b (h = 0.944) and microsatellites (HNei = 0.810–0.900).

Main conclusions We demonstrate deep phylogeographical structure with

two reciprocally monophyletic lineages and five genetic clusters in Mexico and

Central America. Our results suggest that several geographical barriers (includ-

ing the Trans-Mexican Volcanic Belt and the Motagua–Polochic–Jocot�anfaults) and ecological features generated this structure. We report genetic diver-

sity values for the boa at a regional scale and suggest that the two lineages may

be considered distinct species.

Keywords

Boidae, Central America, conservation biogeography, Mexico, microsatellites,

mitochondrial DNA, Neotropics, nuclear DNA, phylogeography, snakes.

INTRODUCTION

Phylogeographical research has generally focused on the

northern temperate regions of the world, including Europe

and the USA, with fewer studies occurring at the boundaries

of temperate and tropical regions (Beheregaray, 2008), even

though the Neotropical region of Mexico and Central Amer-

ica is considered one of the most biologically diverse areas on

Earth (Myers, 2003). Multiple biotic assemblages are likely to

have been shaped in this region, particularly along the frontier

between the Neotropics and Nearctic – the Mexican Transi-

tion Zone (MTZ), located in central Mexico – and associated

major geographical features, such as the Sierra Madre

Occidental, Trans-Mexican Volcanic Belt and Sierra Madre

Oriental (Savage, 1982). Accordingly, the geological and bio-

geographical history of Central America has been critical in

shaping the distribution of Neotropical biota in this region.

Central America served as a bridge connecting North America

and South America, allowing organisms to disperse between

them, in what is known as the Great American Biotic Inter-

change (Woodburne, 2010). Three major biogeographical

events in this region have been highlighted as key factors in

forming present-day patterns of biological distribution: (1)

the emergence of the Isthmus of Panama; (2) orogenic

processes across Central America during the Miocene; and

(3) global Pleistocene glacial cycles, which triggered cli-

matic, vegetation and sea-level changes (Guti�errez-Garc�ıa &

V�azquez-Dom�ınguez, 2013).

ª 2014 John Wiley & Sons Ltd http://wileyonlinelibrary.com/journal/jbi 1doi:10.1111/jbi.12372

Journal of Biogeography (J. Biogeogr.) (2014)

Several studies have demonstrated that reptiles can be useful

taxa for understanding the impacts of biogeographical barriers

on population structure throughout this region (Fig. 1,

Table 1). Sister lineages are found to have diverged by trans-

continental dispersals and remain distributed on opposite ver-

sants of Central America (Pacific vs. Caribbean/Gulf of

Mexico) (Hasb�un et al., 2005). Nevertheless, previous studies

have shown that these focal taxa are all of Nearctic origin, in

contrast to other species originating in the Neotropics, such as

boids (Noonan & Chippindale, 2006). Boid snakes (Serpentes:

Boidae) have been used as model organisms to understand the

impacts of dispersal and vicariance events on diversification

processes throughout the Neotropics at different taxonomic

levels (Burbrink, 2005; Noonan & Chippindale, 2006; Colston

et al., 2013; Reynolds et al., 2013a).

Within Boidae, the Boa constrictor complex has the widest

distribution, being naturally present throughout most of the

Neotropics, with a latitudinal range from Mexico (30° N) to

Argentina (35° S), and inhabiting a variety of environments

below 1500 m (Bertona & Chiaraviglio, 2003). Some geo-

graphically delimited populations have been recognized as

subspecies (Langhammer, 1983; Price & Russo, 1991), which

exhibit extensive variation in morphological and ecological

traits. Despite their popularity, no comprehensively detailed

phylogeographical studies exist for this species. The only

published work, based mostly on boas from captive breeders,

describes two clades (cytochrome b): one from Mexico and

Central America (CA), and the other encompassing localities

from South America (SA) (Hynkov�a et al., 2009). The CA

clade coincides with the recognized subspecies Boa constrictor

imperator Daudin, 1803.

We sampled throughout the range of B. c. imperator in

Neotropical Mexico and continental Central America and

used nuclear and mitochondrial molecular markers to infer

the biogeographical processes that determine population

structure in a coalescent framework, an approach that allows

patterns at different spatial and temporal scales to be exam-

ined. Specifically, we characterize the boa’s genetic diversity

and phylogeographical structure to test: (1) whether it dem-

onstrates key spatial patterns observed in other vertebrates in

this region, such as a Pacific–Atlantic divergence; (2) whether

times of divergence of lineages were related to historical and

dispersal events occurring in Mexico and CA; and (3)

whether biogeographical boundaries in the region, like the

MTZ, delimit the current genetic groups.

MATERIALS AND METHODS

Sample collection and molecular protocols

A total of 149 individuals were obtained directly from the

field, from museum specimens and from captive exemplars

of known origin. DNA was extracted from blood, scales

and shed skin from live animals (obtained by non-invasive

techniques) and various tissues and bone fragments

from museum collections (see Appendix S1 in Supporting

Information). We extracted DNA following the manufac-

turer’s instructions using different commercial kits depend-

ing on the nature of samples: Quick Gene DNA Tissue Kit

and Quick Gene DNA Whole Blood Kit (Fujifilm, Tokyo,

Japan) for fresh tissue and blood; DNeasy Blood and Tissue

Kit (Qiagen, Valencia, CA, USA) for shed skin and bone;

and QIAamp DNA FFPE Tissue Kit (Qiagen) for formalin-

fixed tissues. We assessed the quantity and quality of the

DNA on 1% agarose gels stained with 0.5 lg mL�1 ethidium

bromide and visualized under ultraviolet light.

We amplified the mitochondrial cytochrome b gene (cyt b)

with the primers L14910 (50-GACCTGTGATMTGAAAACC-

AYCGTTGT-30) and H16064 (50-CTTTGGTTTACAAGAA-CAATGCTTTA-30) (Burbrink et al., 2000). We also designed

five pairs of primers to amplify 200-bp fragments of cyt b from

formalin-fixed samples (Table S1 in Appendix S2). We ampli-

fied the nuclear intron of the ornithine decarboxylase gene

(ODC) using the primers OD-F (50-GACTCCAAAGCA-GTTTGTCGTCTCAGTGT-30) and OD-R (50-TCTTCAGAG-CCAGGGAAGCCACCACCAAT-30) (Noonan & Chippindale,

2006) for 50 samples selected from the main lineages recovered

within the mitochondrial dataset (see Results). See Appendix

S3 for details of the amplification protocols.

We tested 10 fluorescently labelled microsatellite primers

(Booth et al., 2011; V�azquez-Dom�ınguez et al., 2012) using

the PCR conditions given by those authors; only seven were

polymorphic (Table S2 in Appendix S2). Allele size was

determined with Genemarker 1.95 (SoftGenetics, State

College, PA, USA). Multiple samples were sized at least twice

to ensure correct readings.

Phylogenetic analysis

To determine the genealogical relationships between haplo-

types, structure and diversification, we performed phyloge-

netic analyses for each dataset (cyt b and ODC). We used the

Akaike information criterion scores as implemented in the

program jModelTest 0.1.1 (Posada, 2008) to select the best-

fitting models of sequence evolution for our datasets, which

were used for phylogenetic analyses with maximum- likeli-

hood (ML) and Bayesian inference (BI) methods (see Appen-

dix S3 for details of phylogenetic analyses). Five sequences of

the Argentinean subspecies B. constrictor occidentalis Philippi,

1873 (EU273651.1, GQ300911.3, GQ300912.2, GQ300914.1

and GQ300916.1) were included in the cyt b analyses; no

ODC sequence was available for this subspecies. We chose

four sister species of Boa (Table S3 in Appendix S2) as

outgroups for phylogenetic analyses.

To further investigate the relationships among unique haplo-

types, we constructed unrooted networks using two methods:

the Neighbor-Net algorithm with SplitsTree 4.6 (Huson &

Bryant, 2006), based on the patristic distance corrected by the

GTR+I+G model of evolution; and the median-joining

method in Network 4.6.1.1 (available at: http://www.fluxus-

engineering.com/), considering the two main lineages sepa-

rately (see Results) and assuming a transition/transversion

Journal of Biogeographyª 2014 John Wiley & Sons Ltd

2

M. Su�arez-Atilano et al.

Figure 1 The main physiographical features and/or biogeographical boundaries for snakes within the regions of Neotropical Mexico and

Central America, evaluated using phylogeographical approaches: (1) Mexican Transition Zone (MTZ); (2) Trans-Mexican Volcanic Belt(TMVB); (3) Balsas Depression (BD); (4) Isthmus of Tehuantepec, TI (north–south barrier); (5) Isthmus of Tehuantepec (east–westbarrier); (6) Central American highlands; and (7) Andes mountain chain. Details of phylogeographical patterns are listed in Table 1. MPJF,Motagua–Polochic–Jocot�an fault system; NA, Nearctic biogeographical region; NT, Neotropical biogeographical region; SCh, Sierra Madre

de Chiapas; SMOcc, Sierra Madre Occidental; SMS, Sierra Madre del Sur; SNO, Sierra Norte de Oaxaca; TC, Cordillera de Talamanca.


3

Phylogeography of Boa constrictor imperator

Table

1Themainphysiographical

featuresandbiogeographical

boundarieswithin

theNeotropical

MexicoandCentral

American

region,evaluated

phylogeographically

indifferentsnake

species.Numbers(1)–(7)arerelatedfeaturesorboundariesshownin

Fig.1.

Physiographical

feature

orbiogeographical

boundary

Phylogeographical

pattern

Species

References

Mexican

Transition

Zone(M

TZ)

(1)Genetic

differentiationassociated

withthepresence

oftheTMBV,

affectingtaxa

intheMexican

Pacificcoast.

Hypsiglenatorquata;

Trimorphodon

biscutatus;

Crotalusspp.

Devitt(2006);Mulcahy(2008);

Reyes-V

elasco

etal.(2013)

Trans-Mexican

Volcanic

Belt(TMVB)

(2)North–south

structure

associated

withthepresence

oftheTMBV,

affectingtaxa

intheMexican

Pacificcoast.

Lam

propeltistriangulum;

Trimorphodon

biscutatus

Devitt(2006);Ruaneet

al.(2014)

BalsasDepression(BD)

(3)Changesin

theBalsasRiver

levelandtectonic

activity

associated

withtheTMVBupliftfacilitatingthedifferentiationof‘inner

BD’

lineagesfrom

‘Pacificcoast’populations.

Lam

propeltissplendida;

Pituophisdeppei;

Pituophislineaticollis;

Crotalusspp.

Dazaet

al.(2009);Brysonet

al.(2011);

Reyes-V

elasco

etal.(2013)

IsthmusofTehuantepec

(north–south

barrier)

(4)Form

ationofmountain

chainsonboth

sides

oftheisthmus

(SMOcc

andSM

S)andexpansion–contractioncycles

ofpine–oak

forest,limitingdispersalforhighlandspecies.

Atropoides

olmec;

Cerrophidionspp.;

Crotalusdurissus

W€ uster

etal.(2005);Castoeet

al.(2009)

IsthmusofTehuantepec

(east–westbarrier)

(5)Sea-levelchanges,continentalupliftandvegetationtransitions

(tropical

dry

forest

inthePacificvs.rainforestin

coastalGulfof

Mexico)werefactors

associated

withthedifferentiationoflowlandtaxa.

Agkistrodon

bilineatus;

Leptodeira

annulata;

Leptodeira

maculata;

Leptodeira

septentrionalis

Parkinsonet

al.(2000);Dazaet

al.

(2009,

2010)

Central

American

Highlandsbarrier

(6)Mountain

system

s(Talam

anca,SM

Ch,Motagua–Polochic–Jocot�an

faults)

permitted,in

abroad

sense,thestructuringoflowlandand

highlandtaxa

alongtheAtlanticandPacific.

Atropoides

occidus ;

Atropoides

mexicanus;

Bothriechisspp.;

Crotalusdurissus;

Trimorphodon

biscutatus

W€uster

etal.(2005);Castoeet

al.(2009);

Devitt(2006);Dazaet

al.(2010)

AndeanCordillera

(7)NorthernAndes

uplift(above

4000

m)associated

withdivergence

oftranscontinentaltaxa.

Boa

constrictor;

Corallusspp.;Lachesis

muta

Zam

udio

&Greene(1997);

Hynko

v� aet

al.(2009);

Colstonet

al.(2013)

SMCh,Sierra

Madre

deChiapas;SM

Occ,Sierra

Madre

Occidental;SM

S,Sierra

Madre

delSu

r.


4


ratio of 1:3. The ODC haplotypes inferred by Phase 2.1.1 (Ste-

phens & Donnelly, 2003) were used in both network

constructions.

Genetic diversity and historical demography

We performed Tajima’s D (Tajima, 1989), Fu and Li’s F

(Fu & Li, 1993) and Fu’s FS (Fu, 1997) tests to evaluate if

sequences conformed to a neutral model of evolution; statis-

tical significance was determined using the coalescent simula-

tor in DnaSP 5.10 (Librado & Rozas, 2009). We calculated

three genetic diversity estimates with DnaSP for each dataset:

the nucleotide diversity (p), haplotype diversity (h) and

average number of differences among sequences (k). For the

ODC data, the phases of heterozygous genotypes were

resolved using Phase, where the most probable pair of alleles

was used for each heterozygous individual.

We used beast 1.7.4 (Drummond & Rambaut, 2007) to

estimate diversification times for the mitochondrial lineages

obtained, an approach that uses a relaxed phylogenetic

method that does not rely on a molecular clock. The time to

the most recent common ancestor for the main lineages was

obtained using Bayesian Markov chain Monte Carlo (MCMC)

searches. We used a GTR+I+G model of evolution across all

gene and codon positions and implemented an uncorrelated

lognormal relaxed molecular clock method. The time of diver-

gence was estimated with an uncorrelated lognormal tree

prior, with a constant population size prior and lognormal cal-

ibration dates. These analyses estimated tree shape and diver-

gence dates for all nodes and were sampled every thousandth

iteration for 50,000,000 generations with 10% of the initial

samples discarded as burn-in. For the relaxed method, we

provided calibration points and error estimates derived from a

lognormal distribution. We used three calibration points: the

oldest Patagonian boa fossil (Albino & Carlini, 2008), the

unique Baja California fossil (Miller, 1980) and the oldest boa

fossil from Panama (Head et al., 2012; Table S4 in Appendix

S2). We tested these in beast using the fossil records sepa-

rately and the three points together to ensure consistency.

We examined evidence of historical demographic changes

by constructing Bayesian skyline plots for each main mito-

chondrial lineage with beast, to infer population fluctua-

tions over time by estimating the posterior distribution of

the effective population size at specified intervals along a

phylogeny (Drummond & Rambaut, 2007). Genealogies and

model parameters were sampled every thousandth iteration

along 107 generations under a relaxed lognormal molecular

clock, with uniformly distributed priors and a burn-in of

100 iterations, using coalescent intervals (m) of 10. Demo-

graphic plots for each analysis were visualized using Tracer.

Genetic clustering, diversity and differentiation

using microsatellite data

To examine spatial structure using microsatellites, we used

Geneland 3.1.4 (Guillot et al., 2005), which applies an MCMC

method that considers genetic data and geographical coordi-

nates to identify genetic discontinuities between populations in

space from individual multilocus genotypes. In addition, we

tested the consistency of the individual assignment (Gene-

land) using a spatially independent analysis with structure

2.3.3 (Pritchard et al., 2000) (see Appendix S3 for details).

To estimate genetic diversity and assess structure of the

genetic clusters defined by Geneland, we examined possible

departures from Hardy–Weinberg equilibrium (HWE) with

an exact test and calculated the unbiased P-value with a

Markov-chain algorithm (Guo & Thompson, 1992) with

10,000 dememorizations, 1000 batches and 10,000 iterations

per batch. Linkage disequilibrium was evaluated by a log-like-

lihood-ratio statistic (G-test) and heterozygote deficit or

excess and allele frequencies were estimated using FIS statistics

in GenePop 4.0 (Raymond & Rousset, 1995). We applied a

sequential Bonferroni correction (Rice, 1989) where necessary.

We estimated genetic variability based on the observed (no)

and effective number of alleles (ne) and the observed (HO)

and expected heterozygosity (HE) and Nei’s unbiased expected

heterozygosity (HNei) values for each cluster with GenAlEx

6.2 (Peakall & Smouse, 2006). We evaluated the presence of

null alleles and genotyping errors with Micro-Checker 2.2.3

(van Oosterhout et al., 2004), using a 95% confidence inter-

val, 1000 repetitions and the Brookfield 1 estimator. To assess

the degree of genetic structure among clusters, we calculated

FST using Arlequin 3.5 (Excoffier & Lischer, 2010). We also

used Arlequin to perform an analysis of molecular variance

(AMOVA) based on FST to analyse the distribution of the

genetic variation between and within populations. Signifi-

cance was calculated using a nonparametric test with 30,000

permutations of genotypes among populations.

We explored the robustness of the genetic structure

obtained and determined differentiation between clusters

with the genetic distance measure DA (Nei & Chesser, 1983).

This measure is based on the infinite-allele model and makes

no assumptions about mutational rates or of constant popu-

lation size, and therefore has a higher probability of converg-

ing and depicting the correct tree topology (Destro-Bisol

et al., 2000). We also estimated genetic distance under a

stepwise mutation model in order to generate branch lengths

proportional to evolutionary change, using dl2 (Goldstein

et al., 1995). Based on these genetic distances, we con-

structed neighbour-joining dendrograms, with 1000 replicates

for bootstrap values, using Populations 1.2.30 (available at:

http://bioinformatics.org/~tryphon/populations/).

Gene flow based on microsatellites and cytochrome b

To assess the presence and direction of migration events

between the observed lineages, we performed two analyses

using nuclear and mitochondrial information simultaneously.

We used the mitochondrial lineages as the defined popula-

tions and microsatellites as the molecular markers, consider-

ing a full asymmetrical matrix of migration rates among

lineages, using Migrate-n (Beerli, 2007). In order to infer


5


the approximate times of migration events between mito-

chondrial lineages, we also performed coalescent simulations

under an isolation-with-migration model (Hey & Nielsen,

2004) with IMa2 (Linux v.10.13.10; see Appendix S3).

RESULTS

Molecular sequence diversity

and phylogenetic lineages

We amplified a 1063-bp fragment of cyt b from 122 individ-

uals, which included 174 polymorphic sites, 133 parsimony-

informative sites and 108 unique haplotypes, yielding high

haplotype diversity (h = 0.994) and low nucleotide diversity

(p = 0.033) and an average number of nucleotide differences

between haplotypes (k) of 35.2. Tajima’s D (D = �0.751;

P > 0.1), Fu and Li’s F (F = 0.172; P > 0.1) and Fu’s FS tests

(FS = �33.697; P > 0.1) indicated no departures from neu-

trality in molecular variation. The estimated Tr/Tv ratio was

3.5, with mean nucleotide frequencies of 32.7% A, 28.3% C,

13.8% G and 25.2% T. The TIM2+I+G (pinv = 0.73; a =0.95) model was chosen (the closest equivalent, GTR+I+G,was used in subsequent analyses).

Both phylogenetic inference methods (ML and BI) showed

the same topology, in which two distinct main lineages were

recovered with high levels of support (Fig. 2a): (1) Mexican

Pacific coast (PAC; 38 individuals); and (2) the Gulf of Mex-

ico, Yucat�an Peninsula and Central America (GYCA; 84 indi-

viduals). Net nucleotide divergence (DA) between the two

lineages was 4.2%. The samples from B. c. occidentalis (Argen-

tina) and Brazil were sister to the B. c. imperator clade. The

network analysis based on all haplotypes showed the same pat-

tern, with two well-defined lineages (PAC and GYCA;

Fig. 2b). Minimum-distance networks for each lineage are

consistent with the phylogenetic results, with a few widespread

and/or abundant haplotypes and numerous unique ones.

From the nuclear ODC intron, we amplified a 610-bp

fragment from 50 samples, which yielded 35 polymorphic

sites, comprising 10 parsimony-informative sites and 25 sites

that represented singleton mutations. These defined 39 hapl-

otypes, with h = 0.78, p = 0.069 and k = 4.6. Tajima’s, Fu

and Li’s and Fu’s statistics showed no deviation from neu-

trality (D = �1.02; F = 0.058; FS = �39.843; P > 0.1 in each

case). The selected model of evolution was GTR+I(pinv = 0.939), the estimated transition/transversion ratio was

1.3 and the mean nucleotide frequencies were 29.3% A,

16.9% C, 18.4% G and 35.4% T. Both phylogenetic inference

methods (ML, BI) recovered the same main topology, in

which the GYCA linage is well resolved, although the haplo-

types in PAC are less well resolved (Fig. S1 in Appendix S3).

Divergence time, demographic reconstruction

and gene flow

The simultaneous use of three calibration points was selected

as the best-fitting model of divergence-time estimation, based

on the median mutation rate of 0.0124 mutations per site per

million years. This value is similar to estimates for cyt b in

other snake species (Jiang et al., 2007). The oldest estimated

divergence event corresponds to the main split between South

American and Central American samples, dated around 7.41

million years ago (Ma) (node 1 in Fig. 3a; and see Table S5

in Appendix S2). The split of the two main B. c. imperator

lineages – PAC and GYCA (node 2) – occurred 5.20 Ma, and

was followed by the divergence between B. c. occidentalis

(Argentina) and the Brazilian sample (node 3; 4.55 Ma).

Within the PAC lineage, the next diversification event

occurred in the southernmost sampled region in Oaxaca

(node 4; 3.0 Ma); diversification continued from 2.02 Ma

(node 5) until 0.83 Ma (node 10) at different locations along

the Mexican Pacific coast. Similarly, within the GYCA line-

age, one divergence separated haplotypes exclusive to the

Guatemalan Pacific coast and the Isthmus of Tehuantepec

from the rest of Central America, the Gulf of Mexico and the

Yucat�an Peninsula (node 11; 1.79 Ma). The most recent

event (node 15; 780,000 years ago) separated individuals

from the Gulf of Mexico and the Yucat�an Peninsula.

The Bayesian skyline demographic reconstructions showed

a pattern of population growth through time, in which the

plots for PAC and GYCA indicated constant growth from

2.0 until 0.2 Ma and from 3.0 until 0.2 Ma, respectively

(Fig. 3b,c). Both lineages also showed evidence of a recent

population expansion, starting at 0.5 Ma. Skyline reconstruc-

tions showed that GYCA has a population size at least four

times that of PAC (350.3 and 89.9, respectively; Fig. 3b,c).

None of the plots showed evidence of genetic bottlenecks or

historical population contractions. Values of h were similar

under both methods (Migrate-n and BSL), indicating

higher values for GYCA (h = 4.91; 95% confidence interval,

CI: 4.9–5.0) than PAC (h = 2.81; 95% CI: 2.5–3.0).

Results for gene flow (Migrate-n) revealed a greater con-

tribution of GYCA into PAC, with a value of 31.3 migrants

per generation (95% CI: 9.3–33.0) in the direction GYCA to

PAC, compared to 7.78 (95% CI: 0–11.9) in the other direc-

tion. IMa2 analysis estimated that the gene flow from GYCA

to PAC began c. 294,000 generations ago (95% CI: 180,000–

462,000), which is c. 1.03 Ma, assuming a generation time of

3.5 years. The gene flow from PAC to GYCA occurred later,

c. 190,000 generations ago (95% CI: 68,000–336,000), or c.

619,000 years ago.

Genetic diversity and structure

with microsatellite data

The spatial clustering analysis with Geneland was based on

multilocus genotypes from 148 individuals from Mexico and

Central America, discarding a single sample from Brazil. This

analysis defined five genetic clusters (K = 5), based on con-

sistent results from 22 runs [ln Pr(K = 5) = �4263.426],

where all individuals were systematically distributed in the

same group among runs. We named these clusters based on

their geographical distributions: North Pacific (NP), South


6


Pacific (SP), Gulf of Mexico (GM), North Central America

(NCA) and South Central America (SCA) (Fig. S2 in Appen-

dix S3). Cluster sample size varied from 48 individuals in

NCA to 6 in SCA. The assignment performed with struc-

ture showed similar results, yielding five main groups; both

methods infer the same spatial boundaries between clusters

when comparing the Gulf of Mexico cluster (GM) with the

cluster obtained with structure (G1) (see Results in

Appendix S3) and when comparing the South Pacific clusters

(SP vs. P2), although genetic discontinuities for the Central

America clusters differ between Geneland and structure

(NCA, SCA and G1, G2, G3; see Results in Appendix S3).

We found a total of 157 alleles across the seven loci, with

a range of 11 to 35 (average 25) alleles per locus for the

entire sample; Bci-14 was the most variable locus. Expected

and observed heterozygosity values across clusters were mod-

erately high (Ho = 0.48–0.70; He = 0.74–0.88; HNei = 0.81–

0.90) (Table S6 in Appendix S3), although the values for

SCA should be viewed with caution given its low sample size.

After Bonferroni correction, exact tests found departures

from HWE in three clusters regarding heterozygote defi-

ciency and only two loci showed consistent departures across

all five (Bci-18 and lsat20). All loci were in linkage equilib-

rium and most loci showed exclusive alleles in all clusters

(from three in SP to 26 in NCA). No consistent presence of

null alleles was detected in comparisons across clusters.

Genetic differentiation showed significant FST values

(0.027–0.100; P < 0.01), whereas the AMOVA results

(P < 0.01) revealed that most of the genetic variation was

found within individuals (67%), followed by that among

individuals within clusters (27%); the lowest proportion was

between clusters (6%). Genetic structuring was confirmed by

the NJ dendrograms, where each cluster can be distinguished

(Fig. 4): western (PC) clusters are clearly differentiated from

eastern ones (GM and NCA), with SCA being the most

genetically differentiated of all. The same topology was

achieved with all distance measures considered, irrespective

of what mutation model was assumed.

(a) (b) (c)

Figure 2 Phylogenetic analyses of Boa constrictor imperator distributed in Mexico and Central America based on cytochrome b. (a)

Phylogeny using Bayesian inference showing two major clades (PAC and GYCA). The 10 haplogroups recovered within each main linageare shown with coloured lines and capital letters A–J (see also Fig. 3): groups A–D (within PAC) and groups E–J (within GYCA). The

dashed line (node) represents the placement for the outgroup species (branch lengths not to scale). Haplotype networks obtained with(b) the Neighbor-Net algorithm and (c) the median-joining method. PAC and GYCA lineages are shown in red (at the bottom) and

green (at the top), respectively.


7


Geographical distribution of lineages

and genetic clusters

The results for the haplotype lineages (cytochrome b) and

the genetic clusters (microsatellites) showed concordant

phylogeographical patterns in the phylogenetic, assignment

and neighbour-joining (NJ) analyses: two main lineages

(PAC and GYCA), 10 haplogroups and five genetic clusters

(Fig. 4). These results show that PAC encompasses four dif-

ferent haplogroups (A–D; Fig. 3a). Group A includes haplo-

types from the northernmost distribution of the lineage –

Sonora, Sinaloa and Jalisco; Group B is distributed in Jalisco

and Colima; Group C is the most geographically restricted

group within this lineage, present only in Morelos; Group D,

with the southernmost distribution within PAC, has haplo-

types from Michoac�an, Guerrero and Oaxaca. The GYCA

lineage was subdivided into six groups (E–J; Fig. 4a). The

two groups with the widest distributions are group E, present

from Oaxaca and Guatemala along the Pacific coast, and

group F, found in Panama, Costa Rica and El Salvador. Two

more have restricted distributions: group G found exclusively

in El Salvador, and group H, only found in Honduras.

Distributed exclusively in Mexico, group I includes haplo-

types from the Yucat�an Peninsula and Chiapas, and group J

is restricted to the Gulf of Mexico.

The genetic clusters and NJ phenogram are congruent with

the cyt b phylogeny: the SP and NP clusters have similar

geographical distributions with the PAC lineage, whereas

GM, NCA and SCA are present within the spatial distribu-

tion of GYCA (Fig. 4b,c); this agreement is further shown

where the clusters SNP and NPC include haplotypes from

groups A–B and groups C–E, respectively, whereas the GM

cluster encompasses haplotypes from group J and NCA

includes haplotypes from groups F–I (Fig. 4a,b). The SCA

cluster includes exclusively haplotypes from Panama. The

Geneland results also showed high posterior probabilities of

assignment of individuals to each corresponding genetic

cluster (see pie charts in Fig. 4c).

DISCUSSION

Boa constrictor imperator is highly structured genetically and

geographically in Mexico and Central America. There are

two main reciprocally monophyletic mitochondrial lineages,

(a) (b)

(c)

Figure 3 (a) Divergence-time estimation (time-scale in millions of years ago), and Bayesian skyline plots of Boa constrictor imperatordistributed in Mexico and Central America for (b) GYCA and (c) PAC lineages, obtained with beast.


8


(a)

(d)

(b) (c)

Figure 4 Summary of phylogeographical patterns within Boa constrictor imperator in Mexico and Central America. (a) beast

phylogenetic results showing 10 haplogroups recovered within each main linage: Pacific coast, PAC (groups A–D, represented withwarm colours); and Gulf of Mexico–Yucat�an Peninsula–Central America, GYCA (groups E–J; with cold colours). A time scale is shown

on the bottom (Ma). (b) Spatial delimitation of the five genetic clusters, represented by coloured squares, named in relation togeographical location: GM, Gulf of Mexico; NCA, North Central America; SCA, South Central America; SP, South Pacific; NP, North

Pacific. (c) Neighbour-joining phenogram with bootstrap support values based on the microsatellite dataset and Nei standard geneticdistances between genetic clusters; pie charts represent average assignment (posterior probability) of each individual belonging to the

corresponding inferred cluster. (d) Map depicting the geographical location of cytochrome b lineages as the different groups recovered(Pacific Coast, PAC; Gulf of Mexico–Yucat�an Peninsula–Central America, GYCA) and the five genetic clusters (microsatellites) defined

by Geneland; PAC and GYCA individuals are shown as triangles and circles, respectively (those in white represent individuals that haveno association to any group). Black solid lines represent major geographical barriers: 1, Trans-Mexican Volcanic Belt; 2, Sierra Madre

del Sur; 3, Isthmus of Tehuantepec; 4, Sierra Norte de Oaxaca; 5, Motagua–Polochic–Jocot�an fault system; 6, Chagres River system and

Panama Channel. The white dashed polygon represents the Oaxaca region.


9


with c. 4% genetic divergence: one along the Pacific coast

(PAC) and the other encompassing the Gulf of Mexico,

Yucat�an Peninsula and Central America (GYCA). Further-

more, five genetic clusters are geographically differentiated at

a regional level. Based on our results, we describe the role

that diverse geographical features and barriers played in the

dispersal and diversification of this species.

Our results indicate that separation between the South

American and Central American/Mexican boa lineages

occurred prior to the closing of the Isthmus of Panama, c.

7.4 Ma, followed by genetic differentiation of PAC and

GYCA, with further independent dispersal events within each

lineage, distinct in time and geographical distribution. These

two major lineages coincide with examples of other verte-

brates with Neotropical origin that show a similar pattern

along the Pacific and Gulf of Mexico/Central America: the

nine-banded armadillo, Dasypus novencintus (Arteaga et al.,

2012), and the little yellow-shouldered bat, Sturnira lilium

(Hern�andez-Canchola, 2013). In contrast to other snakes

(Fig. 1, Table 1), the divergence and phylogeographical

structure of the boa reveals a much more complex pattern

associated with major geographical features structuring

lineages along this region.

Pacific Coast linage (PAC)

The PAC lineage is structured into four haplogroups

(A–D; Fig. 4), which can be associated with some biogeo-

graphical provinces and ecoregions (Olson et al., 2001)

that have distributions delimited by geological and ecologi-

cal features. The PAC lineage is distributed entirely within

the Mexican Pacific Coast province (MPC), which ranges

along the coastal southern and central regions of Pacific

coastal Mexico, and is characterized by the presence of dry

deciduous and semi-deciduous tropical forest (Morrone,

2006). Groups A–D coincide with three ecoregions with

predominantly dry forest vegetation: Southern Pacific Dry

Forests, Jalisco Dry Forests and Balsas Dry Forest, respec-

tively (Olson et al., 2001). These ecoregions are bounded

by some of the main mountain systems that are likely to

have acted as barriers to dispersal: the Sierra Madre del

Sur (SMS) in Oaxaca and Guerrero, limiting the distribu-

tion of Group D, and the convergence of the Sierra Madre

Occidental (SMOcc) and the Trans-Mexican Volcanic Belt

(TMVB) that border group B. Group C, in the Balsas

River valley, is also limited by the SMS, while the TMVB

separates groups A and B to the north from groups C

and D to the south. This complex orography and diversity

of dry forests have been recognized as factors that isolate

areas currently identified as areas of high endemism for

herpetofauna (Garc�ıa, 2006). Indeed, genetic intraspecific

structure along the MPC has been observed for lowland

reptile species like the black iguana, Ctenosaura pectinata

(Zarza et al., 2008), and the Middle American gopher-

snakes Pituophis deppei and P. lineaticollis (Bryson et al.,

2011).

Microsatellite results revealed two genetic clusters within

PAC: the North Pacific (NP) and South Pacific (SP). Group

B is structured along the limit between the two (Fig. 4d), on

an area known as the Jalisco block (Johnson & Harrison,

1989) that has experienced intense volcanic activity over the

last 2 million years. The eastern limit of the TMVB is a

physiographical feature delimiting the genetic discontinuity

between NP and SP. Vertebrates like the western lyre-snake

(Trimorphodon biscutatus) have shown diverse phylogeo-

graphical patterns directly related to the TMVB barrier

(Devitt, 2006).

Gulf of Mexico, Yucat�an Peninsula and Central

America lineage (GYCA)

Our results showed that the GYCA lineage is structured into

six haplogroups (E–J) and three genetic clusters (Fig. 4),

with a north–south substructure. The Motagua–Polochic–Jo-

cot�an fault system (MPJF) is likely to have acted as a barrier

influencing this structure, as suggested by the distribution of

groups F–H to the south and groups E, I and J on the north-

ern side. The MPJF has been shown to function as a barrier

in northern CA, with similar geographical patterns seen in

other vertebrate species, like the Mesoamerican spiny-tailed

lizards of the Ctenosaura quinquecarinata complex (Hasb�un

et al., 2005) and the big-eared climbing rat Ototylomys phyll-

otis (Guti�errez-Garc�ıa & V�azquez-Dom�ınguez, 2012).

The split between groups I (Yucat�an Peninsula) and J

(Gulf of Mexico) represents a recent diversification event

(< 800,000 years ago), supported by the short branches

within each group, little differentiation between haplotypes

within networks and low levels of divergence (DA = 0.003).

This agrees with the evidence that the present-day verte-

brate faunas of the northern portion of the Yucat�an Penin-

sula are of recent origin, having mostly originated by the

dispersal of species from the south after the Great Ameri-

can Biotic Interchange (GABI; V�azquez-Dom�ınguez & Arita,

2010). As in other taxa, like the lowland toad, Incilius

valliceps (Mulcahy et al., 2006), the Gulf and Yucat�an pop-

ulations are poorly differentiated. The spatial division

between groups I and J coincides with the boundary

between two distinct herpetological provinces (Veracruz and

Pet�en; Casas-Andreu & Trujillo, 1990), suggesting that eco-

logical factors may have driven the divergence in this

region. Indeed, the Gulf of Mexico (GM) cluster is highly

concordant with the Veracruz herpetological province,

whereas the boundary between GM and North Central

America (NCA) clusters is concordant with the division

between groups I and J (Fig. 4d). The boundary between

the NCA and South Central America (SCA) clusters is con-

sistent with the Chagres River system and the Panama

Canal, both of which waterways are recognized as recent

barriers at regional scales (D�ıaz-Mu~noz, 2011); considering

the differences shown by the assignment analyses for these

clusters, however, a wider sampling for this area is needed

to corroborate these hypotheses.


10


Oaxaca, a secondary contact zone

The state of Oaxaca in Mexico (Fig. 4d) is a key region for

understanding the evolutionary history of both boa lineages.

The oldest diversification event for PAC occurred here

3.0 Ma and it is the only region of sympatry observed in our

results, where haplotypes from GYCA (group D) are found

within the geographical distribution of PAC (specifically in

the SP cluster), which is likely to be a result of secondary

contact between PAC and GYCA. Our isolation–migration

results support the latter, showing that the contribution of

GYCA into PAC occurred nearly 1 Ma. Clustering analyses

also revealed individuals assigned to the SP cluster to have

GYCA haplotypes, suggesting a more contemporary contri-

bution from PAC into GYCA (c. 600,000 years ago).

The Great American Biotic Interchange and

diversification of Boa

The Miocene fossil (Head et al., 2012) indicates that a Boa

species was present in CA around 19.3 Ma, suggesting a

transcontinental pre-GABI dispersal similar to those observed

in Neotropical colubroid and viperid snakes. Considering the

accelerated rate of mitochondrial DNA evolution in snakes

(Kumazawa & Nishida, 1999), we would expect a higher level

of sequence divergence between lineages if PAC or GYCA

had originated from older dispersal events. Our lineages

reveal a more recent spread and diversification of Boa into

Mexico and CA, in accordance with the interruption of gene

flow between Central and South America proposed by Head

et al. (2012). Moreover, the split between PAC and GYCA

around 5.2 Ma and the oldest diversification events within

each lineage (3 and 2 Ma, respectively) support the hypothe-

sis of the role of the GABI on their diversification (Green,

2011). The closure of the Isthmus of Panama (7–3.5 Ma),

the final uplift of the Colombian Andes (4–3.5 Ma) and the

maximum GABI large-scale dispersion (3.1–2.5 Ma; Coates

& Obando, 1996; Woodburne, 2010) are in agreement with

our estimated divergence and dispersal of PAC and GYCA.

Taxonomic and conservation implications

The present work provides invaluable and novel information

about this charismatic species. Our results show high levels

of nuclear and mitochondrial diversity within B. c. imperator,

which is of crucial conservation value. Few studies have per-

formed analyses with these genetic markers and none within

the geographical range we evaluated. Boas have been geneti-

cally studied with microsatellites in natural (Green, 2011)

and introduced (V�azquez-Dom�ınguez et al., 2012; Reynolds

et al., 2013b) island populations, revealing similar heterozy-

gosity values but lower allelic diversity than in the present

study.

The presence of two reciprocally monophyletic lineages

based on mtDNA, together with similar structure between

microsatellites clusters, are in agreement with the genetic

criteria established for the recognition of evolutionarily signif-

icant units (ESUs; Moritz, 1994); we therefore consider PAC

and GYCA as ESUs. Although B. c. imperator has been recog-

nized throughout Mexico and Central America as a subspe-

cies, also recently proposed as B. imperator (Reynolds et al.,

2014), our findings of two major lineages and a region of

potential secondary contact provide evidence that they can be

considered to be two distinct species under a lineage species

concept (de Queiroz, 2007), which should be confirmed using

coalescent species-delimitation methods. Moreover, our infor-

mation highlights the need for the taxonomic status and spe-

cies delimitation to be reviewed within the entire Boa

constrictor complex. The latter has important conservation

consequences considering the vulnerable and legally protected

status of the species in many countries, including Mexico.

ACKNOWLEDGEMENTS

Our immense gratitude goes to the following curators and

collections that provided tissue loans: Rafe M. Brown

(NHM, University of Kansas), Oscar Flores-Villela (MZFC,

Facultad de Ciencias, UNAM), Eduardo Gonz�alez-Correa

(RVSBR, Veracruz), David Lazcano-Villarreal (Facultad de

Ciencias Biol�ogicas, UANL), Jimmy A. McGuire (MVZ, Uni-

versity of California-Berkeley), Gregory J. Watkins-Colwell

(PMNH, Yale University), Kevin de Queiroz (USNM, Smith-

sonian Institution) and Stephen P. Rogers (CMNH, Carnegie

Museum of Natural History). We thank Omar Becerra, Itzu�e

Caviedes, Alfredo Cuar�on, Denisse Garc�ıa, Cristopher

Gonz�alez, Gualberto Pacheco, Gabriela Parra, Sergio P�erez,

Francisco Reyes, Eunice Romero, Armando Soto, David

Valenzuela and Bibiana Trivi~no for sharing samples and/or

fieldwork support. Alejandro Gonz�alez and Daniel Valle pro-

vided technical and computational support and Susette Cas-

te~neda provided molecular advice. Special thanks go to

Alexander McKelvy, Edward Myers, Sara Ruane and Xin

Chen for help with numerous analyses. We thank the editor

and three anonymous referees for helpful comments on ear-

lier versions of this manuscript. This paper constitutes a

partial fulfilment of the Graduate Program in Biological

Sciences of the National Autonomous University of Mexico

(UNAM). E.V.D. received financial support from CONACyT

(Grant 101861) and Papiit (IN217910). M.S.A. acknowledges

the scholarship and financial support provided by the

National Council of Science (CONACyT 346511), Scholar-

ship Program for Postgraduate Studies (PAEP) and UNAM.

Scientific collector permit to E.V.D.: Semarnat-FAUT-0168.

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SUPPORTING INFORMATION

Additional Supporting Information may be found in the

online version of this article:

Appendix S1 List of samples with locality and genetic

information and GenBank numbers.

Appendix S2 Tables associated with molecular protocols,

phylogenetic methods and results.

Appendix S3 Supplementary methods, results and figures.

BIOSKETCHES

Marco Su�arez-Atilano is a PhD candidate at Ecology

Institute, UNAM. His current research interests include pop-

ulation and landscape genetics, phylogeography and phyloge-

netics of native and invasive reptile species, particularly

snakes.

Frank T. Burbrink examines processes of diversification,

historical ecology, phylogenetics and phylogeography of

reptiles and amphibians across the world.

Ella V�azquez-Dom�ınguez is interested in aspects of

molecular ecology at both local and regional scales, working

with population, conservation and landscape genetics and

phylogeography, in vertebrates, insects and parasites, from

Mexico and Central America.

Editor: Brett Riddle


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