Widespread co-occurrence of divergent Central … ARTICLE Widespread co-occurrence of divergent...

ORIGINALARTICLE

Widespread co-occurrence of divergentmitochondrial haplotype lineages in aCentral American species of poison frog(Oophaga pumilio)

J. Susanne Hauswaldt1*, Ann-Kathrin Ludewig1, Miguel Vences1

and Heike Prohl2

INTRODUCTION

Since the advent of phylogeography, amphibians have served as

an exemplar group of organisms, showing strong geographical

structuring of genealogical divergence (Avise, 2000). The

diversity of phylogeographic patterns observed across organ-

isms was categorized by Avise (2000), who combined the

genetic distance between major lineages [deep (> 3% mito-

chondrial sequence divergence) versus shallow] and the

geographic distribution (allopatric versus sympatric) of these

lineages. Historical biogeographical factors as well as ecology

and behaviour jointly affect population genetic patterns.

1Unit of Evolutionary Biology, Institute of

Zoology, TU Braunschweig, Spielmannstrasse

8, 38106 Braunschweig, Germany, 2Institute of

Zoology, University of Veterinary Medicine,

Bunteweg 17, 30559 Hannover, Germany

*Correspondence: Susanne Hauswaldt, Unit of

Evolutionary Biology, Institute of Zoology, TU

Braunschweig, Spielmannstrasse 8, 38106

Braunschweig, Germany.

E-mail: [email protected]

ABSTRACT

Aim To analyse the phylogeographic structure of the strawberry poison frog,

Oophaga pumilio (Dendrobatidae), across a large part of its range using a

combination of mitochondrial and nuclear markers.

Location Costa Rica and Panama.

Methods Sequence analyses of a mitochondrial (cytochrome b) and a nuclear

(RAG-1) gene fragment as well as analyses of seven microsatellite loci were carried

out on 269 individuals of O. pumilio sampled from 24 localities and on two

individuals of O. vicentei.

Results Two main mitochondrial haplotype lineages, corresponding to a

northern (north Costa Rica) and a southern (south Costa Rica and eastern

Panama) lineage, were identified. They differed by up to 7% uncorrected distance.

We observed co-occurrence of both lineages in seven populations in Costa Rica

and Panama, indicating a pattern of extensive admixture. The two main

mitochondrial lineages of O. pumilio roughly corresponded to a previously

described phylogeographic pattern. Microsatellites indicate admixture spanning

over a wide geographic area, but significant variation between the northern and

southern groups was also found with microsatellite data. While microsatellite

data reconstructed a separation south of an assumed Caribbean valley barrier,

mitochondrial haplotypes of the ‘southern lineage’ shifted this barrier towards the

north.

Main conclusions Despite admixture, all three markers showed significant

variation between the northern and southern groups. Phylogeographical breaks

known from other anuran species in the study region could not be verified for

O. pumilio. The unexpected clustering of the population from Escudo de

Veraguas and the individuals of O. vincentei with the northern O. pumilio lineage

indicates the need for a fundamental and careful taxonomic revision, including an

interspecific phylogeography of the entire genus.

Keywords

Amphibia, Anura, Costa Rica, cytochrome b, Dendrobatidae, microsatellites,

Oophaga vicentei, Panama, phylogeography, RAG-1.

Journal of Biogeography (J. Biogeogr.) (2011) 38, 711–726

ª 2010 Blackwell Publishing Ltd http://wileyonlinelibrary.com/journal/jbi 711doi:10.1111/j.1365-2699.2010.02438.x

Amphibians are generally considered to be highly philopatric

and poor dispersers, which facilitates the isolation and

subsequent genetic divergence of populations (Vences &

Wake, 2007; Zeisset & Beebee, 2008). This simplistic view is

contradicted by evidence of overseas dispersal by amphibians

(Hedges et al., 1992; Vences et al., 2003; Measey et al., 2007)

and by fast post-glacial colonization of northern areas of the

Palaearctic and Nearctic (e.g. Babik et al., 2004; Kuchta & Tan,

2005; Makowsky et al., 2009). However, the fact that most

amphibian species and genera are endemic to major biogeo-

graphical regions (Vences & Kohler, 2008) is a clear indication

of their generally poor performance as dispersers. An exception

to this pattern has been found in the widely distributed

Bufonidae, a family in which specific traits favouring dispersal

capacity have been identified (Van Bocxlaer et al., 2010).

The phylogeographic structure of amphibian gene trees is

usually of category I of Avise (2000), characterized by deep

gene trees with an allopatric distribution of major lineages, and

often with private haplotypes in most populations (Vences &

Wake, 2007; Zeisset & Beebee, 2008). In at least one case of a

tropical amphibian, a pattern of star-like phylogeographic

structure, with a wide-ranging main cytochrome b haplotype

and weakly differentiated locally restricted haplotypes, has

been found (Rabemananjara et al., 2007). This pattern corre-

sponds to category IV of Avise (2000), characterized by a shallow

gene tree and sympatric lineages, and suggests that widespread

species of tropical amphibians do indeed exist (Fouquet et al.,

2007). In a number of amphibian species the co-occurrence of

strongly divergent haplotypes within one population has been

observed (e.g. Babik et al., 2003; Zamudio & Savage, 2003;

Vences et al., 2004; Zhang et al., 2008). In most cases, this was

interpreted as evidence for local hybridization with introgres-

sion. In several other cases, similar haplotype distribution

patterns in amphibians have been used as an indication of

species-level mitochondrial paraphyly (e.g. Shimada et al.,

2008; Brown & Twomey, 2009), confirming that mitochondrial

paraphyly cannot always be explained by poor taxonomic

resolution or erroneous identifications (Funk & Omland,

2003). A pattern not recognized from amphibians is a wide

geographic co-occurrence of deep haplotype lineages across

populations belonging to the same species; that is, category II

of Avise (2000). Recently, however, Robertson et al. (2009)

found such a pattern in several populations of the red-eyed

tree frog (Agalychnis callidryas) from Costa Rica and Panama,

whereas populations of a co-distributed species, the hourglass

tree frog (Dendropsophus ebraccatus), had reciprocally mono-

phyletic haplotype lineages.

The strawberry poison frog, Oophaga pumilio (Schmidt,

1857), is a small diurnal amphibian of remarkable colour

polymorphism inhabiting the lowlands of eastern Panama,

Costa Rica and Nicaragua. The species is part of a monophy-

letic genus containing nine closely related species [Oophaga

arborea (Myers et al., 1984), O. granulifera (Taylor, 1958),

O. histrionica (Berthold, 1845), O. lehmanni (Myers and Daly,

1976), O. occultator (Myers and Daly, 1976), O. pumilio,

O. speciosa (Schmidt, 1857), O. sylvatica (Funkhouser, 1956)

and O. vicentei (Jungfer et al., 1996)] (Grant et al., 2006)

distributed in Central America and north-western South

America. As many of these species are phenotypically poly-

morphic and no conclusive phylogenetic analysis covering

populations from all (putative) species is available, species

delimitations are not completely resolved.

The ecology and behaviour of O. pumilio have been the

subject of many studies focusing mainly on territorial behav-

iour (Donnelly, 1989; Prohl, 1997), acoustic communication

and sexual selection (e.g. Prohl & Hodl, 1999; Summers et al.,

1999; Maan & Cummings, 2008, 2009). Strawberry poison

frogs have become a model species for evolutionary biologists

regarding the importance of natural and sexual selection for

phenotypic variation (i.e. morphology, behaviour), and phy-

logeographic studies may help to disentangle the interplay

between behaviour, ecology and population structure. Special

attention has also been paid to their skin toxins (reviewed in

Saporito et al., 2007a); in fact, O. pumilio is the first species of

dendrobatid frog for which an aposematic function of its

bright coloration has been demonstrated experimentally (Sa-

porito et al., 2007b). Previous molecular studies have focused

on populations of O. pumilio from a small area in Panama, the

Bocas del Toro archipelago (e.g. Rudh et al., 2007; Brown

et al., 2010), where they show a particularly remarkable

variability in colour and pattern (Daly & Myers, 1967). Other

studies covered larger ranges but included only a small number

of individuals per population and were based only on

mitochondrial sequence information (Hagemann & Prohl,

2007; Wang & Shaffer, 2008) or only on microsatellite markers

(Wang & Summers, 2010).

Two main genetic mitochondrial lineages of O. pumilio have

been identified in previous studies (Hagemann & Prohl, 2007;

Wang & Shaffer, 2008): one lineage that includes frogs from

north-eastern Costa Rica with red body coloration and blue or

black legs (monomorphic northern lineage) and a second

lineage that includes red frogs with red or black legs from

south-eastern Costa Rica as well as populations of various

colour morphs from Panama (polymorphic southern lineage).

The polymorphic frogs from the islands of the Bocas del Toro

(excluding Escudo de Veraguas) as well as three populations

from mainland Panama form a monophyletic group within the

second lineage (Wang & Shaffer, 2008). Several populations do

not follow this general pattern: although they are geograph-

ically located within the distribution of the southern lineage,

they belong genetically to the northern lineage. One particu-

larly striking example is the population from Escudo de

Veraguas, the southernmost island of the Bocas del Toro,

which was found to be genetically closely related to the

populations from north Costa Rica and also shows the typical

northern colour pattern (red body with blue legs) (Hagemann

& Prohl, 2007). Moreover, individuals from other Panamanian

species of Oophaga included in the analysis were either

grouped with the northern (O. speciosa) or with the southern

(O. arborea) lineage.

Focusing on the phenotypic divergence in O. pumilio, Wang

& Summers (2010) demonstrated that the genetic distance

J. S. Hauswaldt et al.

712 Journal of Biogeography 38, 711–726ª 2010 Blackwell Publishing Ltd

based on microsatellite markers is correlated with dorsal

coloration rather than with geographic isolation, and Brown

et al. (2010) provided quantitative support that strong diver-

sifying selection has caused extreme colour polymorphism.

Using increased sample sizes and mitochondrial DNA

(mtDNA) D-loop sequences, Brown et al. (2010) also found

a substantial lack of reciprocal monophyly among Panamanian

O. pumilio populations. These authors associated this pattern

with a lack of lineage sorting, given the relatively young age of

the islands and reduced gene flow among island populations

(Wang & Summers, 2010).

Thus, previous works suggested a complex phylogeography

of these frogs at the interspecific as well as at the intraspecific

level and, in particular, mitochondrial polyphyly for O. pumilio.

Here we analyse over 250 samples from 24 localities covering

most of the Costa Rican and Panamanian part of the

distribution range of the species, and compare genetic

differentiation using mtDNA sequences of cytochrome b,

nuclear DNA sequences of RAG-1, and seven microsatellite

markers. Our aim was to determine the level of mitochondrial

polyphyly across a major part of the range of the species, and

to compare the phylogeographic pattern (e.g. barriers to gene

flow) of O. pumilio with that of other Neotropical frogs

covering the same distribution range. By combining nuclear

and mitochondrial markers in the phylogeographic analyses of

this species we follow a methodological approach considered

superior for revealing population histories compared with

using only mtDNA (Hare, 2001). Our results contradict some

of the phylogeographic hypotheses drawn from previous

studies, as we found co-occurrence of divergent haplotypes

in many populations, and we also found only weak indications

for geographic structure in nuclear gene divergence, thus

indicating a complex phylogeographic structure that probably

originated from recurrent waves of differentiation with

subsequent admixture.

MATERIALS AND METHODS

Samples and DNA extraction and sequencing

Between 2004 and 2005, 269 adults of O. pumilio were sampled

from 11 sites in Costa Rica (CR) and from 13 sites in Panama

(PA) by taking toe clips and releasing specimens at the site of

capture (Table 1 and Fig. 1). Total genomic DNA was

extracted using the Qiagen DNeasy Tissue Kit (Qiagen,

Hilden, Germany).

We amplified a 559-bp fragment of the mitochondrial

cytochrome b (cyt b) gene using primers MTAL (5¢-CTCCCAGGCCCATCCAACATCTCAGCATGATGAAACTTC

G-3¢) (K. C. Wollenberg, TU Braunschweig, pers. comm.) and

Cytb-c (Bossuyt & Milinkovitch, 2000). To obtain a 572-bp-

long fragment of RAG-1 we used newly designed primers

Rag1_Oop-F1 (5¢-CCATGAAATCCAGCGAGCTC-3¢) and Ra-

g1_Oop-R1 (5¢-CACGTTCAATGATCTCTGGGAC-3¢). Poly-

merase chain reactions (PCRs) were performed in a total

volume of 12.5 lL, each containing 1 · PCR buffer, 0.24 lm

of each primer, 200 lm dNTPs, and 0.4 units GoTaq

(Promega, Mannheim, Germany). Sequences were obtained

for nearly all individuals sampled (Table 1). The thermocy-

cling profile for cyt b comprised an initial denaturation at

94 �C for 90 s, followed by 35 cycles of denaturation (30 s at

94 �C), annealing (45 s at 55 �C) and elongation (90 s at

72 �C), and a final elongation step at 72 �C for 10 min. The

profile for RAG-1 was identical, except that the annealing

temperature was 62 �C. A volume of 5 lL of PCR product was

cleaned with 0.225 lL of Shrimp Alkaline Phosphatase (SAP)

(Promega) (1 unit lL)1), 0.06 lL of Exonuclease I

(20 units lL)1) (New England Biolabs, Frankfurt am Main,

Germany) and 1.215 lL of H2O, incubated first at 37 �C and

then at 80 �C for 15 min each. Sequencing reactions (10 lL)

contained between 2 and 3 lL of cleaned PCR product, 0.5 lL

BigDye 3.1 (Applied Biosystems, Darmstadt, Germany) and

0.3 lm primer. Sequences were run on a 3130XL sequencer

(Applied Biosystems). Cytochrome b was sequenced in one

direction and RAG-1 in both directions.

Sequences were aligned and edited using CodonCode

Aligner (CodonCode Corporation, Dedham, MA, USA). To

reconstruct haplotypes for the RAG-1 sequences we used

Phase 2.1 (Stephens et al., 2001; Stephens & Donelly, 2003), a

coalescent-based Bayesian method to infer haplotypes, as

implemented in DnaSP 5 (Rozas et al., 2003). Sequences were

deposited in GenBank (accession numbers GQ980333–

980855).

For a preliminary assessment of the divergences of popu-

lations of O. pumilio from the Nicaraguan part of its range that

were not included in our study, but for which a few sequences

had been obtained previously by other authors, we conducted

a neighbour-joining analysis of 505 bp of all available 16S

sequences of O. pumilio and O. vicentei from the literature

(Grant et al., 2006; Hagemann & Prohl, 2007; Santos et al.,

2009) with mega (Tamura et al., 2007).

Genetic diversity and population structure from

sequence data

We used tcs 1.21 (Clement et al., 2000) to generate haplotype

networks of the sequences. We calculated the number of

segregating sites (S), haplotype diversity (h), nucleotide

diversity (p), uncorrected pairwise distances (p-distance) and

sequence diversity (j) using DnaSP.

To determine whether populations had undergone recent

changes in demography, we tested the null hypothesis of

population stability by calculating the R2 raggedness index

(Ramos-Onsins & Rozas, 2002) and Fu’s FS (Fu, 1997) for the

cyt b sequences using DnaSP. While R2 has greater statistical

power than FS with small samples, FS is more reliable for larger

samples (Ramos-Onsins & Rozas, 2002). We also tested the

null hypothesis of recent demographic expansion under a

stepwise expansion model by comparing the distribution of

observed differences between pairs of haplotypes (i.e. mis-

match distributions) with the expected distributions calculated

as a sum of squared deviations (SSD) (Schneider & Excoffier,

Phylogeography in a Central American poison frog

Journal of Biogeography 38, 711–726 713ª 2010 Blackwell Publishing Ltd

1999). If a population has experienced a recent demographic

expansion, the mismatch distribution will be unimodal and

represent a Poisson distribution (null model), whereas a

significant deviation resulting in a ‘ragged’ distribution

indicates demographic stability. Mismatch distribution and

the raggedness index (rHarp) of the observed distribution

(Harpending, 1994) were calculated with Arlequin, and the

significance of both of these statistics was assessed by PHARP

and PSSD, which when < 0.05 are consistent with population

stability (in contrast to FS and R2).

Microsatellite genotyping and analyses

Individuals were initially genotyped for 10 microsatellite loci

(Oop_C3, Oop_B8, Oop_B9, Oop_F1, Oop_E3, Oop_G5,

Oop_01, Oop_H5, Oop_D4 and Oop_C11) (Hauswaldt et al.,

2009). However, after checking the data for microsatellite null

alleles and scoring errors with micro-checker (Oosterhout

et al., 2004), we excluded the last three loci owing to high

levels of null alleles. Electrophoresis was performed on a

3130XL sequencer (Applied Biosystems) using the Genescan

LIZ 600-bp ladder, and fragments were scored using

GeneMarker 4.0 software (SoftGenetics, StateCollege, PA,

USA).

We used GenAlEx 6.1 (Peakall & Smouse, 2006) to calculate

observed and expected heterozygosities (Ho and He) and the

number of private alleles (AP). Allelic richness (AR), averaged

over all loci and estimated for a minimum of seven individuals

per population, was calculated with fstat (Goudet, 1995).

Linkage disequilibrium and departures from Hardy–Weinberg

equilibrium at each locus and population were computed with

Genepop on the Web (Raymond & Rousset, 1995b; Rousset,

2008) using the Markov chain Monte Carlo (MCMC) method

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

per batch) to obtain unbiased estimates of Fisher’s exact tests

(Raymond & Rousset, 1995a). Evidence of a recent population

bottleneck was assessed for each population by comparing the

observed gene diversity with the gene diversity expected under

mutation-drift equilibrium using bottleneck (Cornuet &

Luikart, 1996). We performed the calculations choosing the

two-phase model (TPM) as the mutational model with 95%

single-step mutations and 5% multi-step mutations, with the

Table 1 Summary statistics of sample origin, the abbreviation used throughout the paper, coordinates (in decimal degrees), and number of

individuals genotyped for cytochrome b, RAG-1 and seven microsatellite markers (Msat.) for Oophaga pumilio and O. vicentei from Costa

Rica (1–11) and Panama (12–24).

Population Abb. Region Coordinates [lat. (�N), long. (�W)] Cyt b RAG-1 Msat.

1 Upala CRU North-western CR 10.91356, 85.04706 7 7 7

2 Cano Negro CRC North-western CR 10.86508, 84.77947 11 11 11

3 Tortuguero CRTZ North-eastern CR 10.61288, 83.53113 9 10 10

4 La Selva CRL North-eastern CR 10.43111, 84.00333 11 11 11

5 Guapiles CRG North-eastern CR 10.19158, 83.82428 11 10 10

6 Rio Reventazon CRRR Rio Reventazon 10.09011, 83.56202 9 10 10

7 Pueblo Nuevo CRP Rio Reventazon 10.32117, 83.58761 11 10 11

8 Siquirres CRS Rio Reventazon 10.0985, 83.52003 12 13 13

9 Hitoy Cerere CRHC South-eastern CR 9.66667, 83.08669 14 15 15

10 Bribri CRB South-eastern CR 9.64547, 82.88258 9 12 10

11 Puerto Viejo de Talamanca CRTB South-eastern CR 9.64756, 82.75619 12 11 12

RCR = 116 120 120

12 Almirante PAA Bocas del Toro* 9.28610, 82.39065 9 10 10

13 Tierra Oscura PAT Bocas del Toro* 9.17893, 82.25878 8 9 9

14 Cauchero PAK Bocas del Toro* 9.15642, 82.25432 12 13 13

15 Colon PAC Bocas del Toro 9.38652, 82.23623 12 13 12

16 Bastimentos PAB Bocas del Toro 9.30361, 82.14028 10 10 16

17 Solarte PAS Bocas del Toro 9.33263, 82.21855 12 10 11

18 San Cristobal PASC Bocas del Toro 9.27152, 82.29005 10 9 10

19 Pastores PAPA Bocas del Toro 9.23992, 82.35055 10 9 9

20 Popa PAP Bocas del Toro 9.21500, 82.12978 19 18 19

21 Loma Partida PAL Bocas del Toro 9.13645, 82.16513 10 10 10

22 Cayo de Agua PACA Bocas del Toro 9.15740, 82.04888 12 12 12

23 Punta Alegre PA Bocas del Toroa 9.16333, 81.90921 8 8 8

24 Escudo de Veraguas PAE Escudo de Veraguas 9.10177, 81.54932 11 9 10

RPAN = 143 140 149

R R = 259 260 269

Oophaga vicentei O.v.1 Provincia Veraguas 8.50944; 81.07683 2 2 2

O.v.2 Provincia Cocle 8.62684; 80.58374

*Indicates sites on the mainland.



variance for mutation size set to 12 (as suggested by Piry et al.,

1999), and used the Wilcoxon signed-rank test running 10,000

simulations.

Population differentiation

Based on the microsatellite data, we used a Bayesian assignment

test (Pritchard et al., 2000) to estimate the number of genetic

clusters using the program structure 2.3.3, available through

the Computational Biology Applications Suite for High Perfor-

mance Computing (BioHPC Suite at Cornell University; http://

cbsuapps.tc.cornell.edu/structure.aspx). Runs were performed

with a burn-in length of 106 and an MCMC of 3 · 106 using an

admixture model (ainitial = 1.0; amax = 10.0). The range of

possible groups (K) tested was from 1 to 15, and 5 runs were

conducted for each K. To identify the uppermost hierarchical

level of population structure, we determined the greatest rate of

change in estimated likelihood between successive K-values

according to Evanno et al. (2005). Population differentiation

was assessed by calculating pairwise multi-locus estimates of FST

(= h, Weir & Cockerham, 1984) using Arlequin 3.11 (Excoffier

et al., 2005). For the sequence data, we used the Kimura two-

parameter model (Kimura, 1980). The same software was used

to conduct an analysis of molecular variance (AMOVA;

Excoffier et al., 1992) to assess the genetic differentiation within

and among regions and populations using all three markers.

Significance was tested with 10,000 permutations of each

dataset.

To determine whether genetic distance was correlated with

geographic distances (isolation by distance, IBD), we con-

ducted partial Mantel tests between the matrices and tested the

significance of the correlation with a Z-test using 10,000

randomizations with ibdws 3.16 (Jensen et al., 2005). To

assess the most significant barriers to gene flow, we computed

biogeographical boundaries using Monmonier’s algorithm as

implemented in Barrier 2.2 (Manni et al., 2004). For the

microsatellite data we tested the robustness of the barriers by

generating 100 FST matrices via a bootstrapping procedure

using a function from R (kindly provided by E. Petit, UMR

CNRS, Paimpont via M. Sala-Bozano, UC Dublin).

RESULTS

Mitochondrial DNA sequences

Amplification of a 559-bp-long segment of cytochrome b from

259 individuals of O. pumilio and two of O. vicentei resulted in

89 unique haplotypes (Fig. 2). The sequences contained 151

variable sites. Mean haplotype diversity was high

(0.686 ± 0.168) (Table 2). On average, populations from

Costa Rica had higher diversity indices than those from

Panama [even when excluding Escudo de Veraguas (popula-

tion PAE)], although the mean number of haplotypes per

population was similar (Costa Rica 4.09 ± 1.37; Panama

4.67 ± 2.06). For example, mean sequence diversity (j) was

11.67 (± 6.89) in Costa Rica but only 4.59 (± 6.11) in Panama

(excluding population PAE), and nucleotide diversity (p) per

population was 2.5 times larger in Costa Rica [0.02 (± 0.01) vs.

0.008 (± 0.01)]. Among the populations from Panama, two of

the four mainland populations (Cauchero and Almirante), as

well as the one from the island closest to the mainland (San

Cristobal) had the highest diversity parameters (h, j, p). In

Costa Rica, the biogeographical region around Rio Reventazon

showed the highest genetic diversity, with the population Rio

Reventazon having the highest sequence and nucleotide

diversity, as well as the highest number of segregating sites

(S = 55) of all populations. Of the 89 haplotypes, 77 were

private. Eight of the twelve shared haplotypes occurred in two

populations, two haplotypes occurred in three populations,

one was shared by four, and another by five populations. Seven

haplotypes were exclusively shared among Panamanian popu-

lations, three among Costa Rican populations, and two

haplotypes co-occurred in Costa Rica and Panama.

The haplotype network is divided into two main clusters

separated by 16 inferred mutational steps (Fig. 2). The cluster

shown on the left side of Fig. 2 contains 52 haplotypes found

Figure 1 Sampling sites of Oophaga pumilio from Costa Rica and Panama and of O. vicentei from Panama. Populations are coded as in

Table 1.



in the Bocas del Toro Archipelago as well as 10 haplotypes

from south-eastern Costa Rica and the Region of Rio

Reventazon. One haplotype is shared with a population from

north-eastern Costa Rica. Altogether, eight haplotypes in this

cluster are shared between populations.

The cluster shown on the right side of Fig. 2 shows a very

different pattern: genetic diversity is higher and only four

haplotypes are shared. Seven of the 37 haplotypes in this cluster

were restricted to Panamanian populations (five from Escudo

and two others from mainland Panama), two were shared

among countries, and two haplotypes were found in O. vicentei.

All other haplotypes were exclusively found in Costa Rica, and

one of them was found in all but the north-western regions.

While most of the haplotypes in the first cluster were separated

by single steps, the second cluster contained much more

diversity. Uncorrected pairwise distances (p-distances) between

cytochrome b haplotypes belonging to the two main clusters

reached 7.7%, corresponding to 43 substitutions. In seven

populations we observed a syntopic occurrence of haplotypes

belonging to the two main clusters, namely in Bribri (CRB),

Siquirres (CRS), Rio Reventazon (CRRR), Guapiles (CRG), San

Cristobal (PASC), Cauchero (PAK) and Almirante (PAA). In

three of these, PASC, PAK, PAA, the haplotypes had high

divergences of 38–39 substitutions (6.8–7.0% p-distance). In the

16S rRNA gene, using sequences available from GenBank

originally obtained by Hagemann & Prohl (2007), the uncor-

rected divergence between haplotypes belonging to the two

clusters was 1.2–2.6% (6–13 substitutions).

Genetic differentiation among populations based on the

mitochondrial data was substantial, and FST values ranged from

0 to 0.97 (mean 0.588 ± 0.240) (Table 3). Of the 276 pairwise

population comparisons, 266 significantly deviated from zero.

Among the Costa Rican (CR) populations, mean FST values

were lower than those among Panamanian (PA) populations

[FST (CR) = 0.46 ± 0.239 vs. FST (PA) = 0.53 ± 0.273]; how-

ever, they were similar when excluding Escudo: FST =

0.46 ± 0.240. The mean FST between Costa Rican and

Panamanian populations (without population PAE) was

0.68 ± 0.164.

RAG-1 sequences

For RAG-1, 262 individuals were sequenced and a 572-bp

fragment was aligned. Seventy-three individuals contained at

Figure 2 Haplotype network of 89 unique haplotypes of cytochrome b of Oophaga pumilio and O. vicentei (559 bp) from Costa Rica (CR)

and Panama (PA). Populations are numbered as in Table 1. Haplotypes are indicated by circles, with the area being proportional to the

number of individuals sharing that haplotype. Inferred intermediate haplotypes between observed haplotypes are indicated by dashes. For

illustrative purposes, the number of inferred haplotypes has been written out in two cases. Colours in the network refer to geographical

regions. In the map, numbers of localities with co-occurrence of haplotypes belonging to the two main lineages are italicized and underlined.



least one heterozygous position, and, after phasing the

sequences, the subsequent analyses were conducted with 524

sequences. These contained 21 different haplotypes differing by

one mutational step; no geographic structure could be

recognized in the pattern of the network (Fig. 3). Compared

with the mitochondrial marker (Table 2), genetic diversity was

much lower: h = 0.491 ± 0.24, with the Panamanian popula-

tions showing somewhat higher diversity in regard to h and j(hPAN = 0.57 ± 0.2, hCR = 0.357 ± 0.26 and jPAN = 0.815 ±

0.31, jCR = 0.521 ± 0.43). Nucleotide diversities were also

extremely low (pPAN = 0.00021 ± 0.0015 and pCR = 0.00091 ±

0.0007). Comparing haplotype diversities between regions as

defined in Table 1, these were lowest in north-western and

north-eastern Costa Rica, and Rio Reventazon (0–0.497), and

higher in south-eastern Costa Rica, Bocas del Toro and

Escudo de Veraguas (0.709–0.810), with the highest diversity at

Escudo de Veraguas. Nucleotide diversity values followed a

similar distribution, with values of 0–0.00096 vs. 0.00180–

0.00229.

Microsatellite data

All microsatellite loci were polymorphic across all 24 sites and

no deviation in linkage disequilibrium was found. Across all

populations and sites we found 172 alleles, ranging from 14 to

36 (mean 24.5 ± 7.21) for the seven loci. In 18 of the 24

O. pumilio populations, one or more (maximum 5) loci were

out of Hardy–Weinberg equilibrium (HWE) after Bonferroni

correction (Table 4). In two populations, Hitoy Cerere and

Popa, five loci were out of HWE. While among the Costa

Rican populations the most frequent locus out of HWE was

H5, in Panama it was locus B9. Within-population diversity

was similar between Costa Rica and Panama (Table 4).

We detected significance in 260 out of 276 pairwise FST

comparisons, indicating reduced gene flow (Table 3). Mean

FST was 0.079 (± 0.036) and ranged from 0.009 to 0.18. Among

Costa Rican populations, mean FST values were slightly higher

than those among Panama, whether including Escudo de

Veraguas or not: among Costa Rica = 0.079 ± 0.036; among

Table 2 Summary of regional and within-population diversity for cytochrome b gene sequences and population demographic statistics for

Oophaga pumilio from Costa Rica (CR) and Panama (PA).

n S H h j p R2 FS MMSSD rHarp

North-western CR 18 45 6 0.85 17.680 0.032 0.1926 9.497 0.10203*** 0.193***

CRU 7 6 2 0.57 3.429 0.006 0.2857 4.834* 0.37279*** 0.837*

CRC 11 35 4 0.75 16.364 0.029 0.2258* 8.758 0.14536*** 0.172

North-eastern CR 31 61 13 0.90 19.366 0.035 0.1482 6.211 0.03251*** 0.028*

CRTZ 9 35 3 0.72 18.722 0.033 0.2463* 10.568** 0.21954*** 0.342

CRL 11 39 7 0.91 16.400 0.029 0.1893 2.78 0.06300 0.084

CRG 11 37 3 0.47 8.945 0.016 0.1965 8.091 0.18057 0.492

Rio Reventazon CR 32 61 13 0.86 20.204 0.036 0.1506 5.662 0.08003*** 0.072**

CRRR 9 55 5 0.81 23.056 0.041 0.1733 5.892 0.14703*** 0.258

CRP 11 35 4 0.60 14.073 0.025 0.1791* 7.923 0.18767 0.335

CRS 12 32 5 0.74 5.833 0.010 0.2502* 2.683** 0.02230 0.075

South-eastern CR 35 59 12 0.92 17.901 0.032 0.1350 6.788 0.07245*** 0.058**

CRHC 14 40 5 0.76 13.187 0.024 0.1476 7.262 0.15991*** 0.325***

CRB 9 30 4 0.81 7.556 0.014 0.284* 3.902 0.24257** 0.771**

CRTB 12 2 3 0.68 0.833 0.001 0.2083 0.325 0.02927 0.211

Bocas del Toro PA 132 70 46 0.96 6.945 0.013 0.0434 )19.29 0.00580 0.017

PAA 9 36 4 0.81 9.667 0.017 0.2831* 4.78 0.06787 0.15

PAT 8 3 3 0.61 1.107 0.002 0.1804 0.39 0.04022 0.164

PAK 12 45 6 0.85 20.742 0.037 0.2081 6.184 0.11021 0.162

PAC 12 14 5 0.58 2.333 0.004 0.1953 0.149** 0.02029 0.079

PAB 10 11 4 0.71 2.533 0.005 0.2451 1.135 0.03362 0.125

PAS 12 8 2 0.17 1.333 0.002 0.2764* 3.113** 0.04037 0.75

PASC 10 38 4 0.78 10.711 0.019 0.2311 5.863 0.12125 0.319

PAPA 10 4 5 0.82 1.422 0.003 0.1623 )1.393 0.00717 0.098

PAP 19 10 10 0.84 1.965 0.004 0.0781 )4.926 0.01435 0.061

PAL 10 2 3 0.38 0.400 0.001 0.2000 )1.164 0.00580 0.183

PACA 12 7 6 0.68 1.167 0.002 0.1231 )2.857* 0.33000 0.128

PA 8 4 4 0.79 1.750 0.003 0.2049 )0.114 0.12375 0.431

Escudo de Veraguas PAE 11 6 5 0.62 1.236 0.002 0.0434 )1.535 0.00305 0.017

n, number of individuals sequenced per population; S, number of segregating sites; H, number of haplotypes; h, haplotype diversity; j, sequence

diversity; p, nucleotide diversity; R2, Ramos-Onsins & Rozas (2002); FS, Fu’s FS (Fu, 1997); MMSSD, sum of squared deviations between the observed

mismatch distribution and the distribution expected under a sudden demographic expansion model; rHarp, raggedness index of the mismatch

distribution as defined by Harpending (1994). *P < 0.05; **P < 0.001; ***P < 0.0001.



Tab

le3

Dif

fere

nti

atio

nb

etw

een

po

pu

lati

on

so

fO

oph

aga

pum

ilio

fro

mC

ost

aR

ica

and

Pan

ama

by

pai

rwis

eF

ST

valu

esfo

rm

icro

sate

llit

es(l

ow

erd

iago

nal

)an

dcy

toch

rom

eb

seq

uen

ces

(up

per

dia

gon

al).

Po

pu

lati

on

sar

eco

ded

asin

Tab

le1.

Val

ues

that

are

no

n-s

ign

ifica

nt

afte

rse

qu

enti

alB

on

ferr

on

iad

just

men

tar

eit

alic

ized

.

CR

UC

RC

CR

TZ

CR

LC

RG

CR

RR

CR

PC

RS

CR

HC

CR

BC

RT

BP

AA

PA

TP

AK

PA

CP

AB

PA

SP

ASC

PA

PA

PA

PP

AL

PA

CA

PA

PA

E

CR

U–

0.51

60.

440

0.56

50.

526

0.48

20.

475

0.85

20.

644

0.83

10.

949

0.82

50.

946

0.62

00.

932

0.92

70.

947

0.79

90.

946

0.94

10.

960

0.95

10.

936

0.90

8

CR

C0.

086

–0.

144

0.20

10.

259

0.17

80.

083

0.60

10.

197

0.55

80.

713

0.60

80.

728

0.34

40.

739

0.71

40.

746

0.57

10.

740

0.78

50.

754

0.75

60.

706

0.40

8

CR

TZ

0.15

90.

129

–)

0.05

40.

403

0.14

70.

243

0.61

80.

220

0.56

00.

728

0.60

90.

734

0.36

50.

749

0.72

30.

757

0.57

90.

749

0.79

70.

763

0.76

50.

712

0.39

9

CR

L0.

108

0.07

90.

058

–0.

496

0.20

00.

330

0.64

00.

231

0.58

60.

741

0.63

40.

749

0.39

20.

761

0.73

80.

767

0.60

40.

762

0.80

50.

774

0.77

50.

730

0.40

7

CR

G0.

132

0.13

80.

110

0.08

4–

0.32

20.

077

0.70

70.

554

0.68

10.

818

0.71

30.

828

0.50

90.

827

0.81

10.

838

0.67

60.

834

0.85

40.

848

0.84

60.

811

0.74

9

CR

RR

0.10

50.

086

0.04

10.

037

0.06

5–

0.24

00.

222

0.27

30.

217

0.43

90.

381

0.52

30.

151

0.55

10.

505

0.54

30.

315

0.55

70.

631

0.56

40.

566

0.49

40.

420

CR

P0.

055

0.04

00.

066

0.03

00.

072

0.04

3–

0.65

00.

382

0.61

50.

754

0.65

30.

764

0.42

90.

773

0.75

10.

781

0.61

60.

774

0.81

10.

788

0.78

90.

745

0.57

7

CR

S0.

147

0.09

40.

035

0.05

90.

115

0.06

00.

077

–0.

651

0.26

00.

500

0.52

30.

713

0.32

40.

698

0.65

90.

686

0.39

90.

736

0.75

40.

749

0.72

00.

684

0.84

6

CR

HC

0.11

90.

098

0.06

00.

055

0.07

90.

039

0.06

40.

051

–0.

621

0.75

20.

653

0.76

60.

354

0.77

30.

754

0.77

90.

624

0.77

60.

811

0.78

70.

787

0.75

10.

370

CR

B0.

095

0.06

10.

061

0.02

80.

094

0.04

60.

040

0.02

70.

034

–0.

129

0.48

80.

706

0.29

80.

683

0.64

00.

675

0.37

30.

720

0.74

70.

736

0.70

80.

662

0.82

8

CR

TB

0.18

00.

128

0.07

00.

069

0.14

00.

100

0.09

80.

040

0.08

10.

070

–0.

680

0.92

60.

457

0.86

90.

856

0.89

10.

563

0.90

90.

883

0.94

60.

909

0.89

80.

959

PA

A0.

132

0.08

70.

087

0.06

80.

105

0.05

70.

080

0.09

50.

058

0.05

70.

101

–0.

316

0.14

50.

156

0.16

40.

191

0.01

00.

224

0.38

10.

318

0.20

90.

173

0.83

1

PA

T0.

087

0.09

00.

145

0.06

70.

122

0.07

70.

061

0.13

10.

088

0.09

10.

136

0.08

2–

0.27

50.

634

0.64

60.

557

0.33

90.

750

0.62

50.

450

0.57

90.

560

0.96

3

PA

K0.

081

0.08

60.

099

0.06

90.

095

0.05

20.

065

0.09

80.

069

0.06

50.

119

0.05

10.

020

–0.

344

0.31

00.

308

0.13

70.

356

0.41

70.

313

0.32

70.

266

0.52

3

PA

C0.

125

0.11

80.

095

0.09

20.

106

0.06

90.

096

0.11

60.

062

0.07

70.

120

0.03

50.

105

0.05

8–

0.03

40.

459

0.22

20.

507

0.59

60.

644

0.48

60.

475

0.94

2

PA

B0.

086

0.07

90.

098

0.05

90.

116

0.06

70.

048

0.09

30.

074

0.06

10.

098

0.05

20.

040

0.04

00.

057

–0.

480

0.20

30.

510

0.61

10.

667

0.52

00.

498

0.93

9

PA

S0.

105

0.12

20.

112

0.08

60.

121

0.08

90.

080

0.12

50.

093

0.09

30.

162

0.09

50.

063

0.04

70.

092

0.06

0–

0.22

10.

620

0.45

30.

521

)0.

011

0.14

80.

957

PA

SC0.

141

0.13

80.

182

0.12

40.

160

0.13

70.

132

0.17

30.

132

0.13

60.

185

0.13

60.

056

0.05

80.

151

0.07

90.

095

–0.

295

0.41

30.

346

0.26

30.

225

0.79

3

PA

PA

0.13

20.

094

0.13

90.

091

0.16

40.

111

0.10

40.

129

0.10

40.

087

0.11

50.

082

0.04

10.

034

0.08

30.

055

0.10

00.

045

–0.

676

0.78

30.

641

0.61

90.

958

PA

P0.

081

0.09

40.

052

0.05

30.

073

0.03

60.

063

0.05

20.

020

0.03

10.

088

0.04

80.

078

0.04

30.

039

0.05

50.

059

0.11

30.

083

–0.

614

0.46

20.

469

0.94

6

PA

L0.

116

0.11

80.

091

0.07

30.

090

0.05

80.

070

0.10

60.

063

0.07

20.

123

0.04

20.

086

0.05

80.

033

0.07

80.

102

0.14

70.

093

0.03

7–

0.54

70.

561

0.97

4

PA

CA

0.08

70.

119

0.12

20.

074

0.12

20.

080

0.08

60.

125

0.06

90.

090

0.14

30.

078

0.03

80.

027

0.07

80.

032

0.03

80.

062

0.06

10.

047

0.08

0–

0.15

90.

961

PA

0.06

70.

074

0.06

20.

040

0.06

10.

040

0.03

40.

066

0.03

10.

037

0.08

60.

043

0.03

80.

017

0.04

50.

025

0.04

00.

073

0.06

00.

009

0.05

00.

024

–0.

953

PA

E0.

137

0.14

80.

145

0.06

10.

139

0.10

40.

097

0.14

80.

114

0.10

50.

182

0.11

60.

057

0.06

50.

132

0.08

30.

063

0.11

40.

112

0.09

10.

100

0.05

70.

062

–



Figure 3 Haplotype network of 21 unique haplotypes of RAG-1 of Oophaga pumilio and O. vicentei (572 bp) from Costa Rica and Panama.

Colours as in Fig. 2.

Table 4 Summary of analyses of seven microsatellite loci of Oophaga pumilio from Costa Rica and Panama. Populations are abbreviated as

in Table 1.

n AR Ho He HWE AP

CRU 7 6.71 ± 2.43 0.71 ± 0.40 0.73 ± 0.22 –

CRC 11 7.39 ± 3.02 0.66 ± 0.26 0.78 ± 0.18 E3 –

CRTZ 10 6.23 ± 1.96 0.70 ± 0.25 0.75 ± 0.19 E3 –

CRL 11 7.12 ± 1.41 0.78 ± 0.19 0.82 ± 0.06 –

CRG 10 5.99 ± 1.95 0.64 ± 0.28 0.76 ± 0.10 B8, B9, DP01 1

CRRR 10 7.50 ± 1.39 0.77 ± 0.14 0.83 ± 0.05 B8, E3 –

CRP 11 7.31 ± 2.24 0.71 ± 0.28 0.81 ± 0.12 F1, E3 –

CRS 13 7.17 ± 1.73 0.62 ± 0.21 0.77 ± 0.18 E3, G5 2

CRHC 15 7.63 ± 2.03 0.55 ± 0.25 0.84 ± 0.09 B8, B9, E3, G5, DP01 4

CRB 10 7.53 ± 1.53 0.71 ± 0.25 0.83 ± 0.07 B9 1

CRTB 12 6.65 ± 2.17 0.80 ± 0.18 0.74 ± 0.20 1

PAA 10 8.08 ± 1.33 0.59 ± 0.20 0.84 ± 0.07 B8, B9, E3, G5 3

PAT 9 7.76 ± 2.39 0.77 ± 0.21 0.79 ± 0.16 B9 3

PAK 13 8.02 ± 1.77 0.65 ± 0.17 0.84 ± 0.10 B9, G5 –

PAC 12 7.33 ± 1.90 0.70 ± 0.23 0.81 ± 0.13 C3, B9 –

PAB 16 7.55 ± 1.37 0.69 ± 0.25 0.85 ± 0.05 C3, G5, DP01 3

PAS 11 6.53 ± 1.50 0.57 ± 0.27 0.77 ± 0.13 C3, B9 –

PASC 10 6.84 ± 3.20 0.57 ± 0.36 0.74 ± 0.26 C3 6

PAPA 9 6.49 ± 1.79 0.59 ± 0.14 0.78 ± 0.11 G5 –

PAP 19 8.20 ± 0.78 0.61 ± 0.16 0.88 ± 0.02 C3, B8, B9, G5, DP01 1

PAL 10 7.49 ± 1.47 0.76 ± 0.14 0.82 ± 0.10 1

PACA 12 7.31 ± 2.05 0.68 ± 0.23 0.81 ± 0.16 B9, G5 –

PA 8 8.25 ± 1.19 0.58 ± 0.30 0.85 ± 0.03 B9, E3 1

PAE 10 6.68 ± 1.98 0.56 ± 0.20 0.74 ± 0.16 C3, B8 1

n, number of individuals analysed; AR, mean allelic richness (± SD); Ho, observed heterozygosity (± SD); He, expected heterozygosity (± SD); HWE,

loci out of Hardy–Weinberg equilibrium (HWE) after Bonferroni corrections; AP, number of private alleles.



Panama without population PAE = 0.062 ± 0.030; among

Panama including PAE = 0.066 ± 0.031. Between Costa Rican

and Panamanian populations, the mean FST was 0.093 ± 0.033.

Bayesian assignment analyses identified six clusters with

high admixture among the geographic regions. At K = 2,

Costa Rican and Panamanian populations are mostly sepa-

rated into two clusters, with the first cluster composed

mainly of Costa Rican populations (Fig. 4). However,

admixture values were high for the populations from

north-western CR; the proportion of membership of CRU

to the first cluster was only 35% and of CRC it was 42%.

Among the Panamanian populations, low assignment to the

second cluster was found in PAS (49%) as well as in PA

(55%). Escudo de Veraguas clearly grouped with Costa Rican

populations. At K = 6, Costa Rican frogs were predominately

assigned to three clusters, while Panamanian frogs were

assigned into the three other clusters (Fig. 4). Frogs from

Guapiles had the highest assignment score (70%) of all Costa

Rican populations to any cluster. Among Panamanian

populations, the clearest patterns found were: (1) assignment

of most frogs (75%) from Almirante to cluster 5, which

otherwise contained the majority of frogs from Colon (51%);

(2) a high proportion of membership of San Cristobal (86%)

and Pastores (66%) to one cluster; and (3) a high proportion

of membership of Escudo (59%) to cluster 3.

Demographics

Evidence for population expansion was found in the cyto-

chrome b sequences of two populations in Costa Rica, namely

Tortuguero and Siquirres, as well as for Solarte in Panama, in

which both R2 and FS were significant (Table 2). For

Tortuguero, however, this evidence is in conflict with a highly

significant mismatch distribution. Support for population

stability (as opposed to expansion) was found in three

populations from Costa Rica, namely Upala, Hitoy Cerere

and Bribri; here, both the mismatch distribution and ragged-

ness index (rHarp) were highly significant. Based on the

microsatellite data, we found an indication of a recent

bottleneck for one Costa Rican and one Panamanian popu-

lation, Hitoy Cerere and Popa (in both, one-tailed P = 0.039);

however, in both cases heterozygosity excess was found in only

five loci.

AMOVA results differed greatly between the three markers.

Whereas for cytochrome b the majority of the variation

(39.8%) was distributed among the two groups (Costa Rica

and Panama) (Table 5), for nuclear markers the highest

variation was found within populations (91% for microsatellite

1.00

0.80

0.60

0.40

0.20

0.001.00

0.80

0.60

0.40

0.20

0.00

Figure 4 Assignment probabilities of individuals of Oophaga pumilio from Costa Rica and Panama to putative population clusters at K = 2

and K = 6 using the program structure. Sampling locations are indicated below the graph, and populations are coded as in Table 1.

Table 5 Analysis of molecular variance (AMOVA) examining the

partitioning of genetic variation for each marker among and

within populations of Oophaga pumilio from Costa Rica and

Panama (including Escudo de Veraguas).

Comparison

cyt b

%

Microsatellites

%

RAG-1

%

Among groups 39.8*** 2.5** 10.1*

Among populations

but within groups

32.6*** 6.8*** 22.1***

*P < 0.005; **P < 0.001; *** P £ 0.0001.



data and 68% for RAG-1). When considering Escudo, part of

the Costa Rican group, the among-group variation found in

the mitochondrial dataset increased by almost 10% (48.6%).

For the RAG-1 and microsatellite datasets, the placement of

Escudo did not change the distribution of variation.

Mantel tests revealed significant isolation by distance for all

genetic markers. The highest association between geographic

and genetic distances was found with cytochrome b-derived

distances (Z = 25037.7, r = 0.443, R2 = 0.19, one-sided

P < 0.001), followed by microsatellite data (Z = 3142.9,

r = 0.364, R2 = 0.13, one-sided P < 0.001) and RAG-1

(Z = 10363.3, r = 0.20, R2 = 0.04, one-sided P < 0.05). The

associations remained significant for each marker if repeating

the analysis for the 15 mainland populations only. When

considering only the Costa Rican populations, the correlations

of genetic and geographic distances were significant for all

markers except RAG-1.

The only genetic break that was indicated by all three

markers with the Barrier analysis was the one separating the

Costa Rican from the Panamanian populations. For the

microsatellite data, bootstrap support for this barrier was 88%.

DISCUSSION

Phylogeography of Oophaga pumilio from Costa Rica

and Panama

We found evidence of the syntopic occurrence of deep

haplotype lineages (cytochrome b divergence up to 7.0%; 16S

rDNA divergence up to 2.6%) in several populations of

strawberry poison frogs from Costa Rica and Panama. A

previous molecular study of O. pumilio based on mitochon-

drial sequences of only a single specimen per population found

distinct geographic structure in the genetic variation, with a

northern and a southern haplotype group separated geograph-

ically by the River Rio Reventazon (Hagemann & Prohl, 2007).

According to that study, haplotypes assigned to O. pumilio

were paraphyletic with respect to two other species, O. arborea

and O. speciosa. Although these previous results represent a

general trend, the more exhaustive data herein demonstrate a

much more complex situation. We demonstrated the co-

occurrence of haplotypes belonging to the two main lineages

identified by Hagemann & Prohl (2007) in seven populations

across Panama and Costa Rica (north and south of Rio

Reventazon). Therefore, these lineages cannot be regarded as

strictly allopatric northern and southern lineages, a result that

is consistent with those of other recent studies (Wang &

Shaffer, 2008; Brown et al., 2010).

Explanations for the co-occurrence of deep haplotype

lineages may lie in factors of population genetic history of

the species or in taxonomy. Possible hypotheses include: (1)

incomplete lineage sorting, (2) historical allopatric divergence

with subsequent admixture owing to natural processes or

human translocation, or (3) the possible existence of cryptic

species. The paraphyly of O. pumilio haplotype lineages with

respect to O. arborea, O. speciosa and O. vicentei (Hagemann &

Prohl, 2007 and data herein) would be in agreement with the

third hypothesis. However, multiple lines of evidence reject

this hypothesis of cryptic species and support instead the idea

of the widespread coexistence of divergent haplotype lineages

within a single species. First, the degree of divergence is below

the threshold of 3% (in the 16S gene) that empirically appears

to be useful to identify candidate species in amphibians

(Fouquet et al., 2007; Vieites et al., 2009). In fact, there are

many examples of haplotypes of this degree of divergence

found within biological species of amphibians, although this is

usually in the case of allopatric populations (Vences et al.,

2005). Second, an analysis of advertisement calls of O. pumilio

(Prohl et al., 2007) from largely the same populations as

studied herein found no evidence for the occurrence of

strongly divergent calls co-occurring at any of the sites, which

would be expected in the case of syntopic cryptic species.

Third, and most importantly, there was no evidence for the

existence of different species from the nuclear DNA data.

In particular, there was no strong indication of linkage

disequilibrium in the microsatellite data, not even in those

populations in which haplotypes of the two main lineages were

found.

Poison frogs are brightly coloured animals that have been

the subject of extensive collecting and research, and the co-

occurrence of distinct haplotype lineages could be caused by

the human translocation of individuals belonging to geo-

graphically separated groups, as in the case of introduced

lizards, Anolis sagrei, in Florida (Kolbe et al., 2008). Regarding

O. granulifera, Savage (2002) notes that during the early 1980s

the Costa Rican authorities often released confiscated dend-

robatid collections near to the assumed site of collection (also

see Lotters et al., 2007, p. 575). This could have led not only to

the introduction of O. granulifera (which is phenotypically

similar to O. pumilio) outside its natural range (Savage, 2002;

see also Myers et al., 1995) but also to the release of genetically

divergent O. pumilio specimens into Costa Rican populations.

However, given (1) the widespread occurrence of haplotype

co-occurrence in O. pumilio, (2) the fact that it is not an

invasive species of which introduced specimens are likely to

undergo fast population and range expansions, (3) the

co-occurrence of haplotype lineages in both Costa Rican and

Panamanian populations, and (4) a similar pattern with

similar levels of sequence divergence in south-western Costa

Rican populations of another Neotropical frog, Agalychnis

callidryas (see Robertson et al., 2009), we consider a human-

mediated widespread translocation of haplotype lineages of

Costa Rican and Panamanian O. pumilio to be unlikely.

Although anthropogenic factors may be responsible for some

aspects of its phylogeographic structure, we are convinced that

populations currently assigned to O. pumilio represent a single

species of complex phylogeographic structure as a result of its

natural evolutionary and biogeographical history.

In our study, O. pumilio populations from northern Costa

Rica had, except for a single individual, haplotypes belonging

to the ‘northern’ lineage of Hagemann & Prohl (2007),

whereas the majority of Panamanian populations in the Bocas



del Toro area had haplotypes belonging to the southern

lineage. Two mainland populations and one from the island of

San Cristobal also included individuals with northern haplo-

types. In populations from south-eastern Costa Rica and the

Rio Reventazon area, both haplotype lineages occurred in

approximately similar proportions. This suggests that

O. pumilio was subjected to an early vicariant event whereby

populations may have diverged in a northern and a southern

refugium, with subsequent secondary contact and genetic

admixture among these main lineages. The microsatellite data,

if analysed by structure with K = 2, support a general north–

south separation of lineages (Fig. 4), with Costa Rican

populations assigned to the northern lineage. The initial

north–south split, however, has been extensively blurred by

admixture and probably also by subsequent events of local

differentiation of populations, with a signal of isolation by

distance as supported by our IBD analysis of microsatellite and

RAG-1 data.

In a previous study using microsatellite markers, Wang &

Summers (2010) did not find genetic distance increasing with

geographic distance, but rather a strong association between

genetic distance and differences in dorsal coloration. Using

amplified fragment length polymorphism (AFLP) markers,

Rudh et al. (2007) also found isolation by distance among the

Bocas del Toro populations. Of the seven cytochrome b

haplotypes shared among Panamanian populations, three are

shared among mainland populations and the others are shared

among island populations that are in relative proximity. The

high admixture shown in the microsatellite data blurs the

genetic structure among the islands, and a larger number of

markers should give a better resolution; therefore, we are wary

of over-interpreting the results of the structure analysis.

Of the possible barriers to gene flow identified by Crawford

et al. (2007) and Robertson et al. (2009) for isthmic Central

America, only two slice the current distribution of O. pumilio:

the Caribbean valley complex and the Bocas del Toro break.

The Caribbean valley complex is a series of floodplain valleys

that appears to limit the ranges of various frog species

(Robertson et al., 2009). It separates three groups of Costa

Rican populations (north-eastern and north-western Costa

Rica and Rio Reventazon) from the remaining populations and

thus very roughly coincides with the separation of the

‘northern’ and ‘southern’ haplotype lineages. While Hagemann

& Prohl (2007) suggested Rio Reventazon as a possible barrier,

we have now found ‘southern’ haplotypes occurring com-

monly in the Rio Reventazon populations and one haplotype

even as far north as Guapiles. We have also found south-

eastern Costa Rican populations south of the barrier with

‘northern’ mitochondrial haplotypes; thus, at least in the past,

admixture proceeded widely in both directions across this

putative Caribbean valley complex barrier. On the basis of

microsatellite data (Fig. 4) and RAG-1, the break is shifted

southwards and coincides more or less with the border

between Costa Rica and Panama. This region contains two

large rivers (Rio Sixaola and Changuinola) that could be

barriers to (recent) gene flow. This break between countries

separates monomorphic (mainly red) Costa Rican populations

from the polymorphic Panamanian populations. The Bocas del

Toro break constitutes a biogeographical separation between

the Bocas del Toro region and eastern Panama on the basis of

the geological history of this region (Crawford et al., 2007).

This barrier coincides with genetic barriers in three lowland

frog species of the genus Craugastor and was also found in

D. ebraccatus, but not in A. callidryas (Robertson et al., 2009).

It also coincides with the eastern range limit of O. pumilio and

may represent the contact zone between O. pumilio and

O. vicentei.

Male advertisement calls, which certainly constitute the

most important sexual signal in frogs and usually are species-

specific, show some geographic variation in O. pumilio that is

roughly in accordance with the subdivision into a northern

and a southern group. According to Prohl et al. (2007),

O. pumilio from northern and central Costa Rica, including the

Rio Reventazon area, have on average a slower call rate, longer

call duration and lower pulse rate compared with frogs from

Panama. Frogs from south-eastern Costa Rica, however, have

an intermediate call rate and call duration but their pulse rate

coincides with the animals from northern Costa Rica. This,

again, is consistent with a wide admixture zone centred in

south-eastern Costa Rica.

Our sampling lacks samples from Nicaragua, where the

species is widely distributed in the southern half of the Atlantic

versant. In fact, Nicaraguan samples have so far not been

included in any assessment of O. pumilio phylogeography

(Summers et al., 1997; Hagemann & Prohl, 2007; Rudh et al.,

2007; Wang & Shaffer, 2008; Brown et al., 2010; Wang &

Summers, 2010). Sequences from a Nicaraguan population

(near Isla Diamante, close to the border with Costa Rica) are

available from the work of Grant et al. (2006). A comparison

of the 16S sequences of these authors with the ones of

Hagemann & Prohl (2007) and Santos et al. (2009) indicates a

considerable differentiation of the Nicaraguan specimens, but

this pattern requires confirmation. In particular, O. pumilio

populations from the central and northern parts of its vast

range in Nicaragua need to be studied, to obtain a full

understanding of the genetic variability within this species.

A particular case is Escudo de Veraguas in Panama, which

separated from the mainland prior to the islands of the Bocas

del Toro archipelago, but only 8900 years ago (Anderson &

Handley, 2002; Wang & Shaffer, 2008). It is populated by

poison frogs with mitochondrial haplotypes not shared with

any other of the populations studied by us. These haplotypes

are at least eight mutational steps away from the next Costa

Rican haplotype, almost equidistant to the haplotypes of

O. vicentei, but clearly belong to the northern lineage,

although geographically Escudo is the southernmost site in

our study. The association with the northern lineage is also

supported by the microsatellite data shown by the Bayesian

assignment tests with K = 2 (Fig. 4), whereas at K = 6 the

population turns out to be genetically distinct. Furthermore,

it is the population with the highest RAG-1 diversity values.

It is relevant to note that mainland populations in the



Veraguas region are assumed to belong to O. vicentei (Grant

et al., 2006; also see http://www.dendrobase.de), which

according to our data are also attributed to the northern

lineage (Fig. 2). It could therefore be hypothesized that the

Escudo de Veraguas population also belongs to O. vicentei,

but this is contradicted by characters of the advertisement call

of this population, with call duration much shorter than that

reported for O. vicentei (Jungfer et al., 1996; Prohl et al.,

2007). We therefore conclude that the Escudo population

should be considered an evolutionary significant unit that

should receive special conservation status, and recommend a

more detailed study of identity of the adjacent mainland

populations in the Veraguas area.

Our results emphasize the evolutionary complexity under-

lying the evolution of coloration in the strawberry poison frog

(Hagemann & Prohl, 2007; Rudh et al., 2007; Wang & Shaffer,

2008). Most of the colour variability of this species occurs in

the Bocas del Toro archipelago (Daly & Myers, 1967; Myers &

Daly, 1983; Summers et al., 1997, 2003; Hagemann & Prohl,

2007; Lotters et al., 2007; Rudh et al., 2007; Batista & Kohler,

2008): crosses among different colour morphs from localities

in the Bocas del Toro archipelago are known to interbreed,

with such hybridization producing intermediate colour pat-

terns (Summers et al., 2004). In this archipelago, mitochon-

drial variability is relatively low, especially regarding nucleotide

diversity (Table 2), and nuclear admixture is high (Fig. 4).

This pattern is in agreement with the very recent (Late

Pleistocene) isolation of the various islands in this archipelago

(Anderson & Handley, 2002; Wang & Shaffer, 2008) and

supports the hypothesis that selective forces rather than neutral

selection alone have contributed to shaping this extraordinary

colour and pattern diversity over a very short time frame

(Brown et al., 2010). While sexual selection on colour may be a

relevant factor (Summers et al., 1999; Reynolds & Fitzpatrick,

2007; Maan & Cummings, 2008; Brown et al., 2010), different

predation pressures in different parts of the range are also

likely to play a role (our own, unpublished data). However,

indicators of genetic diversity from microsatellite data (our

study and that of Wang & Summers, 2010) do not flag the

Bocas del Toro populations as being genetically less variable

than other populations, and for RAG-1 a higher number of

haplotypes, higher haplotype diversity and higher nucleotide

diversity was found here (and on Escudo de Veraguas) than

elsewhere. Although the various populations in the Bocas del

Toro archipelago have not experienced long periods of genetic

isolation from each other, they certainly are not genetically

depauperate compared with other populations of O. pumilio.

Savage (2002) characterized O. pumilio as a charming

species that is among the most photographed and studied of

Neotropical amphibians. The past years have seen a large

number of studies using O. pumilio as an excellent model

species with which to study the evolution of colour patterns

and behavioural signals (e.g. Summers et al., 1997, 1999, 2003,

2004; Prohl, 2003; Siddiqi et al., 2004; Hagemann & Prohl,

2007; Prohl et al., 2007; Reynolds & Fitzpatrick, 2007; Rudh

et al., 2007; Maan & Cummings, 2008, 2009; Wang & Shaffer,

2008; Brown et al., 2010; Wang & Summers, 2010). Our results

suggest that for a complete understanding of the evolutionary

history of this species, including the origin of the extraordinary

polychromatism among and within some populations, it will

be necessary to include a full taxon sampling of Oophaga

alongside ecological and behavioural studies. Clearly, consid-

ering our genetic data, the status of O. vicentei is in need of

confirmation, and doubts have also been cast on the validity of

several other congeneric species (Hagemann & Prohl, 2007),

such as O. arborea and O. speciosa, described by Myers et al.

(1984) and Jungfer (1985), respectively. Future endeavours

should involve an integrative taxonomic study including

closely related polychromatic South American species, such

as O. histrionica and O. sylvatica, which may be more closely

related to some of the Central American haplotype lineages

than to other lineages from Central America (Santos et al.,

2009; A. Amezquita, Universidad de los Andes, Bogota, pers.

comm.). The status of O. vicentei and of other currently

accepted species of Oophaga in Central America requires a

fundamental and careful taxonomic revision, including an

interspecific phylogeography with extensive population-level

sampling.

ACKNOWLEDGEMENTS

We would like to thank Sabine Hagemann, Jan Karsch and

Julia Gunther for collecting the samples, and Gaby Keunecke,

Meike Kondermann and Eva Saxinger for their help in the lab.

Sabine Hagemann developed one of the microsatellite markers

used and carried out preliminary analyses of the same samples.

Some of the data were obtained by Stefanie Janssen, Malte

Kuhnemund, Julia Lemanski and Stefanie Schweinhuber. We

would like to thank Sonke von den Berg for drawing the map

of the sampling sites. We are grateful to the Panamanian and

Costa Rican authorities for collection and export permits of

samples (permit nos SE/A-87-04; N088-204-OFAU, SEX/

A15504, CR-018-2004, CR-033-2004).

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BIOSKETCH

J. Susanne Hauswaldt is an assistant professor at the TU

Braunschweig. Her current research interests include phylo-

geography and conservation genetics of European and tropical

herpetofauna.

Author contributions: J.S.H. conducted laboratory, microsat-

ellite and some sequence data analyses; A.-K.L. conducted

laboratory and some sequence data analyses; H.P. and M.V.

conceived the study and participated in the interpretation of

data; and M.V. and J.S.H. led the writing.

Editor: John Lambshead



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