Phylogeography of the reef fish Cephalopholis
argus (Epinephelidae) indicates Pleistocene
isolation across the indo-pacific barrier with
contemporary overlap in the coral triangle
Gaither et al.
Gaither et al. BMC Evolutionary Biology 2011, 11:189
http://www.biomedcentral.com/1471-2148/11/189 (1 July 2011)
Gaither et al. BMC Evolutionary Biology 2011, 11:189
http://www.biomedcentral.com/1471-2148/11/189
RESEARCH ARTICLE
Open Access
Phylogeography of the reef fish Cephalopholis
argus (Epinephelidae) indicates Pleistocene
isolation across the indo-pacific barrier with
contemporary overlap in the coral triangle
Michelle R Gaither1*, Brian W Bowen1, Tiana-Rae Bordenave1, Luiz A Rocha2, Stephen J Newman3, Juan A Gomez4,
Lynne van Herwerden4 and Matthew T Craig5
Abstract
Background: The Coral Triangle (CT), bounded by the Philippines, the Malay Peninsula, and New Guinea, is the
epicenter of marine biodiversity. Hypotheses that explain the source of this rich biodiversity include 1) the center
of origin, 2) the center of accumulation, and 3) the region of overlap. Here we contribute to the debate with a
phylogeographic survey of a widely distributed reef fish, the Peacock Grouper (Cephalopholis argus; Epinephelidae)
at 21 locations (N = 550) using DNA sequence data from mtDNA cytochrome b and two nuclear introns
(gonadotropin-releasing hormone and S7 ribosomal protein).
Results: Population structure was significant (FST = 0.297, P < 0.001; FST = 0.078, P < 0.001; FST = 0.099, P < 0.001
for the three loci, respectively) among five regions: French Polynesia, the central-west Pacific (Line Islands to
northeastern Australia), Indo-Pacific boundary (Bali and Rowley Shoals), eastern Indian Ocean (Cocos/Keeling and
Christmas Island), and western Indian Ocean (Diego Garcia, Oman, and Seychelles). A strong signal of isolation by
distance was detected in both mtDNA (r = 0.749, P = 0.001) and the combined nuclear loci (r = 0.715, P < 0.001).
We detected evidence of population expansion with migration toward the CT. Two clusters of haplotypes were
detected in the mtDNA data (d = 0.008), corresponding to the Pacific and Indian Oceans, with a low level of
introgression observed outside a mixing zone at the Pacific-Indian boundary.
Conclusions: We conclude that the Indo-Pacific Barrier, operating during low sea level associated with glaciation,
defines the primary phylogeographic pattern in this species. These data support a scenario of isolation on the scale
of 105 year glacial cycles, followed by population expansion toward the CT, and overlap of divergent lineages at
the Pacific-Indian boundary. This pattern of isolation, divergence, and subsequent overlap likely contributes to
species richness at the adjacent CT and is consistent with the region of overlap hypothesis.
Background
Current efforts to identify and preserve biodiversity are
dependent upon our ability to locate hotspots and to
understand how that diversity is generated. Conservation
efforts must preserve not just standing biodiversity
but also the mechanisms that produce it [1]. The Coral
Triangle (CT), bounded by the Philippines, the Malay
Peninsula, and New Guinea, is the epicenter of marine
* Correspondence: gaither@hawaii.edu
1
Hawaii Institute of Marine Biology University of Hawaii PO Box 1346,
Kaneohe, HI 96744, USA
Full list of author information is available at the end of the article
biodiversity. Species diversity declines with distance from
this region, both latitudinally and longitudinally, a pattern that applies to a broad array of taxa [2-8]. The generality of this pattern has led many to conclude that a
common mechanism may be responsible for generating
diversity in the CT. A number of hypotheses have been
proposed to explain the source of the incredible number
of species found in this region and these can be grouped
into three categories: 1) center of origin, 2) center of
accumulation, and 3) region of overlap.
The center of origin hypothesis was proposed by
Ekman [9], who suggested that the CT is the primary
© 2011 Gaither et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons
Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in
any medium, provided the original work is properly cited.
Gaither et al. BMC Evolutionary Biology 2011, 11:189
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source of biodiversity in the Indo-Pacific due to an unusually high rate of speciation in the region. He suggested
that the decline in species richness with distance from
the CT is an artifact of prevailing currents that impede
outward dispersal [9]. The most common mechanism
invoked to explain the proposed elevated speciation rate
is the fracturing of populations as a result of the geological complexity of the region and eustatic sea level
changes [10]. Others have suggested that increased rates
of sympatric or parapatric speciation driven by different
selection pressures in a heterogeneous environment
could be contributing to the species richness of the CT
[11,12]. Evidence for this argument includes the finding
of fine scale population subdivisions within the CT
[13-18].
In contrast, the center of accumulation hypothesis [19]
proposes speciation in isolated peripheral locations with
subsequent dispersal of novel taxa into the CT. The long
history of the Pacific archipelagos, some of which date to
the Cretaceous, and ocean current and wind patterns that
favor dispersal toward the CT have been offered as a
mechanism [19,20]. Finally, the region of overlap hypothesis [21] maintains that the high species diversity in the
CT is due to the overlap of faunas from two biogeographic
provinces: Indo-Polynesian and Western Indian Ocean
[22]. The region roughly dividing these two provinces is
west of the shallow Sunda and Sahul shelves of the East
Indies. During the Pleistocene, sea level was as much as
130 m below present levels and produced a near continuous land bridge between Asia and Australia [23], greatly
restricting dispersal between ocean basins in the region
known as the Indo-Pacific Barrier (IPB). Isolation of conspecific populations across the IPB may have led to allopatric speciation and contributed to the distinction of the
Pacific and Indian Ocean faunas. According to the region
of overlap hypothesis, relaxation of the IPB following each
Pleistocene glacial maximum has resulted in dispersal
pathways between the Pacific and Indian Oceans with the
CT representing the area of overlap between the two distinct biotas. The differences between the center of accumulation and region of overlap hypotheses are subtle. In
both cases speciation occurs outside the CT with subsequent dispersal toward the CT. However, the region of
overlap hypothesis is based on the premise that the isolating mechanism is the IPB with the faunas of the Pacific
and Indian Oceans diverging during periods of restricted
dispersal. In contrast, the center of accumulation hypothesis does not specify a mechanism of divergence nor is it
associated with any biogeographic barrier. This hypothesis
invokes speciation in peripheral locations, followed by dispersal to the CT on prevailing oceanic currents.
Contemporary species distributions are the most common line of evidence offered to examine these hypotheses yet no consensus has evolved. Mora et al. [7]
Page 2 of 15
examined the ranges of nearly 2,000 Indo-Pacific fishes
and found that the midpoint of their ranges centered on
the CT, a result they interpret as evidence for the center
of origin hypothesis. Connolly et al. [24], using a midpoint domain model, found evidence for the accumulation of taxa in the CT due to species dispersing on
oceanic gyres. Halas and Winterbottom [25] employed a
novel phylogenetic approach to address the issue but
found no conclusive evidence for any of the hypotheses.
Evidence for a combined influence of all these processes
in generating the high biodiversity in the CT has led
many to conclude that the processes are not mutually
exclusive and act simultaneously [3,26-28].
Patterns of genetic variation in widely distributed species, while not often employed to address the source of
biodiversity hotspots, provide a historical perspective that
cannot be resolved with contemporary species distributions. Each hypothesis results in specific predictions about
geographic positioning of new species and lineages within
species [29]. The center of origin hypothesis predicts that
the oldest populations (within new species) will be in the
CT, possibly with decreasing haplotype diversity emanating from the center similar to the observed decline in species richness (sensu [30]). In contrast, the center of
accumulation hypothesis predicts that the oldest populations (within new species) will be found peripheral to the
CT accompanied with unidirectional dispersal toward the
CT. Similar to the center of origin, the region of overlap
hypothesis predicts that the most diverse (but not oldest)
populations will be centered in the CT, however in this
case the high diversity is the result of the overlap of divergent lineages from peripheral regions. While there have
been a handful of intraspecific genetic studies that address
the origin of diversity in the CT, the results are conflicting.
Evidence for the center of accumulation hypothesis has
been found in the Lemon Damselfish (Pomacentrus
moluccensis) [29] and the Yellow Tang (Zebrasoma flavescens) [31]. On the other hand, sea urchins [32] and wrasses
[33] invoke a combination of the center of origin and the
center of accumulation hypotheses. Of course all of these
conclusions, including our own, are premised on the
assumption that intraspecific genetic divergences translate
into macroevolutionary (interspecific) partitions [34].
Here we contribute a range-wide phylogeographic
study of a widely distributed grouper to test competing
hypotheses concerning the origins of biodiversity in the
CT. The Peacock Grouper, Cephalopholis argus (Bloch
and Schneider 1801), is a demersal (bottom dwelling)
reef fish of the family Epinephelidae. This species is
found in reef habitat (2-40 m depth) from the Pitcairn
group in the Pacific to east Africa and the Red Sea [[35],
Figure 1]. Many members of the genus Cephalopholis
display complex social behaviors such as territoriality,
sequential hermaphroditism, and a haremic social system
Gaither et al. BMC Evolutionary Biology 2011, 11:189
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Page 3 of 15
Figure 1 Map of study area. Pie charts represent the ratio of individuals at each location with either the Pacific or Indian Ocean lineage as
defined in Figure 2 (Photo credit: Luiz Rocha).
[36]. Long-range dispersal in this species, as in most coral
reef organisms, is limited to the pelagic larval stage [37].
The pelagic larval duration for C. argus has not been
determined but a 40-day average is proposed for Epinephelids [38]. We analyzed DNA sequence data to assess
phylogeographic patterns across the range of this species
to test three alternative hypotheses concerning the origin
of the biodiversity in the CT. Explicitly we address the
following questions: 1) does genetic diversity in the CT
indicate an ancestral population with dispersal away from
the CT as would be expected under the center of origin
hypothesis, 2) is the ancestral diversity peripheral to the
CT and accompanied with evidence of migration toward
the CT as would be expected under the center of accumulation hypothesis, or 3) is the genetic diversity in the
CT the result of mixing of divergent lineages across the
IPB as would be expected under the region of overlap
hypothesis?
Methods
A total of 550 Cephalopholis argus were collected from 21
locations across the species range in the Pacific and Indian
Oceans including two locations at opposite ends of the CT
(Philippines and Bali; Table 1). Most samples were collected by SCUBA divers using polespears or by fishers
using lines. In some cases, samples were obtained from fish
markets but only when we were confident they had been
caught locally (within 100 km). Tissues samples (fin clips
or gill filaments) were preserved in salt-saturated DMSO
[39] and stored at room temperature. DNA was isolated
using the modified HotSHOT method [40,41]. Approximately 870 bp of mitochondrial cytochrome b (Cytb) were
amplified using the primers CB6F (5’-CTCCCTGCACC
TTCAAACAT-3’) and CB6R (5’-GGAAGG TTAAAG
CCC GTTGT-3’) which we designed for this species. Additionally, approximately 375 bp of the third intron in the
gonadotropin-releasing hormone (GnRH) gene were
amplified using the primers GnRH3F and GnRH3R [42]
and approximately 730 bp of the first intron of the S7 ribosomal protein (S7) gene were amplified using the primers
S7RPEX1F and S7RPEX2R [43].
Polymerase chain reactions (PCRs) for all three markers were carried out in a 10 μl volume containing 2-15
ng of template DNA, 0.2-0.3 μM of each primer, 5 μl of
the premixed PCR solution BioMix Red™(Bioline Inc.,
Springfield, NJ, USA), and deionized water to volume.
PCR reactions utilized the following cycling parameters:
initial denaturation at 95°C and final extension at 72°C
(10 min each), with an intervening 35 cycles of 30 s at
94°C, 30 s at the annealing temperature (54°C for Cytb;
58°C for GnRH and S7), and 45 s at 72°C. Amplification
products were purified using 0.75 units of Exonuclease
I/0.5 units of Shrimp Alkaline Phosphatase (ExoSAP;
USB, Cleveland, OH, USA) per 7.5 μl PCR products at
Gaither et al. BMC Evolutionary Biology 2011, 11:189
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Page 4 of 15
Table 1 Molecular diversity indices for 21 populations of Cephalopholis argus
Cytb
GnRH
S7
Sample Location
N
Nh
h
π
N
Na
HO
HE
P-value
N
Na
HO
HE
P-value
Marquesas (MQ)
50
8
0.65 ± 0.06
0.002 ± 0.001
34
3
0.21
0.44
0.002
48
9
0.52
0.60
0.596
Moorea (MR)
36
5
0.38 ± 0.10
0.001 ± 0.001
33
2
0.24
0.26
0.549
34
7
0.59
0.60
0.298
Kiritimati (KI)
32
8
0.74 ± 0.05
0.003 ± 0.002
33
3
0.55
0.49
0.335
28
7
0.36
0.40
0.388
Palmyra (PY)
29
6
0.65 ± 0.07
0.002 ± 0.002
30
3
0.30
0.33
0.217
27
6
0.33
0.33
0.337
Samoa/Tokelau (ST)
27
6
0.64 ± 0.07
0.001 ± 0.001
21
4
0.29
0.33
0.044
24
6
0.25
0.34
0.076
Baker/Howland (BH)
27
6
0.68 ± 0.06
0.002 ± 0.001
27
4
0.52
0.55
0.767
27
7
0.37
0.39
0.365
Kwajalein (KW)
Pohnpei (PN)
22
15
10
6
0.86 ± 0.05
0.74 ± 0.09
0.005 ± 0.003
0.004 ± 0.002
23
15
5
3
0.48
0.20
0.52
0.38
0.846
0.055
23
15
7
8
0.26
0.67
0.48
0.67
< 0.001
0.709
Saipan (SP)
19
6
0.77 ± 0.07
0.003 ± 0.002
19
3
0.37
0.56
0.570
18
6
0.56
0.50
0.271
Palau (PA)
22
8
0.77 ± 0.07
0.004 ± 0.002
23
5
0.57
0.47
0.897
23
6
0.52
0.60
0.128
Lizard Island (LI)
12
5
0.67 ± 0.14
0.001 ± 0.001
10
3
0.40
0.35
1.000
7
3
0.29
0.28
1.000
Philippines (PI)
6
4
0.87 ± 0.13
0.009 ± 0.006
5
3
0.60
0.71
1.000
5
4
0.60
0.64
0.644
Bali (BA)
23
7
0.81 ± 0.05
0.005 ± 0.003
19
4
0.47
0.60
0.054
16
7
0.69
0.76
0.322
Scott Reef (SR)
42
8
0.73 ± 0.05
0.004 ± 0.002
41
7
0.56
0.58
0.262
39
8
0.72
0.64
0.897
Rowley Shoals (RS)
Christmas Island (CM)
40
49
9
10
0.81 ± 0.04
0.83 ± 0.02
0.005 ± 0.003
0.006 ± 0.004
33
47
7
7
0.67
0.55
0.65
0.57
0.073
0.262
30
49
10
11
0.80
0.71
0.77
0.70
0.780
0.717
Cocos/Keeling (CK)
40
9
0.87 ± 0.02
0.006 ± 0.004
30
10
0.83
0.78
0.161
29
7
0.72
0.71
0.599
Sumatra (SU)
4
3
0.83 ± 0.22
0.007 ± 0.005
6
5
0.83
0.82
0.703
5
4
0.60
0.71
1.000
Diego Garcia (DG)
33
10
0.87 ± 0.03
0.003 ± 0.002
33
8
0.82
0.80
0.295
33
9
0.76
0.66
0.047
Oman (OM)
9
5
0.81 ± 0.12
0.006 ± 0.003
4
4
0.75
0.64
1.000
7
6
0.71
0.79
0.869
Seychelles (SE)
13
10
0.96 ± 0.04
0.003 ± 0.002
13
5
0.62
0.80
0.054
13
5
0.77
0.70
0.739
All samples
550
55
0.80 ± 0.01
0.005 ± 0.003
499
11
500
20
0.58
0.67
Sample locations and number of individuals (N) are shown. Number of haplotypes (Nh), haplotype diversity (h), and nucleotide diversity (π) are listed for the
cytochrome b dataset. Number of alleles (Na), observed heterozygosity (HO), and expected heterozygosity (HE) are listed for the gonadotropin releasing hormone
(GnRH), and S7 ribosomal protein gene (S7) nuclear introns. P-values are the result of exact tests for Hardy-Weinberg equilibrium using a Markov chain with
100,000 steps in ARLEQUIN 3.5 [42].
37°C for 60 min, followed by deactivation at 80°C for 10
min. DNA sequencing was performed with fluorescently-labeled dideoxy terminators on an ABI 3730XL
Genetic Analyzer (Applied Biosystems, Foster City, CA,
USA) at the University of Hawaii’s Advanced Studies of
Genomics, Proteomics, and Bioinformatics sequencing
facility.
Sequences for each locus were aligned, edited, and
trimmed to a common length using the DNA sequence
assembly and analysis software GENEIOUS PRO 5.0
(Biomatters, LTD, Auckland, NZ). In all cases, alignment
was unambiguous with no indels or frameshift mutations.
Allelic states of nuclear sequences with more than one
heterozygous site (GnRH = 43.1% and S7 = 48.4% of individuals) were estimated using the Bayesian program
PHASE 2.1 [44,45] as implemented in the software
DnaSP 5.0 [46]. We conducted six runs in PHASE for
each dataset. Each run had a unique random-number
seed. Five runs were conducted for 1000 iterations with
1000 burn-in iterations. To ensure proper allele assignment, a sixth run of 10000 iterations was conducted. All
runs returned consistent allele identities. GnRH and S7
genotyptes resulted in no more than 4 and 6 ambiguous
sites per individual, respectively. PHASE was able to
differentiate all alleles with > 95% probability at both loci
except at single nucleotide positions in 4 individuals at
GnRH and 10 individuals at S7 or 0.8% and 2.0% of samples, respectively. Unique haplotypes and alleles were
identified with the merge taxa option in MacClade 4.05
[47] and deposited in GenBank [ascension numbers:
JN157683-JN157739 (Cytb), JN157740-JN157750 (GnRH
intron), JN157663-JN157682 (S7 intron)].
Data analyses
Mitochondrial DNA
Summary statistics for C. argus, including haplotype
diversity (h) and nucleotide diversity (π), were estimated
with algorithms from Nei [48] as implemented in the statistical software package ARLEQUIN 3.5 [49]. To test
whether haplotype and nucleotide diversities differed
between ocean basins (Pacific Ocean = Marquesas,
Moorea, Kiritimati, Palmyra, Samoa/Tokelau, Baker/
Howland, Kwajalein, Pohnpei, Saipan, Palau, Lizard
Island, and Philippines; Indian Ocean = Sumatra, Bali,
Scott Reef, Rowley Shoals, Christmas Island, Cocos/Keeling, Diego Garcia, Oman, and Seychelles) we calculated
unpaired t-tests using the online calculator GraphPad
(http://www.graphpad.com/quickcalcs/ttest1.cfm). The
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AIC implemented in jMODELTEST 0.1.1 indicated the
TPM1uf+G as the best-fit model of DNA sequence evolution with a gamma value of 0.065. Median-joining networks were constructed using the program NETWORK
4.5 with default settings [50]. An intra-specific phylogeny
was produced using maximum likelihood (ML) methods
and default settings in the program RAXML 7.2.7 [51].
Trees were rooted using Cytb sequences of two congenerics (C. urodeta and C. taeniops) obtained from GenBank
(ascension numbers AY786426 and EF455990, respectively). Bootstrap support values were calculated using
default settings with 1000 replicates. The ML tree topology was confirmed by neighbor-joining (NJ) and Bayesian
Markov Chain Monte Carlo (MCMC) analysis using
MEGA 4.0 [52] and MRBAYES 3.1.1 [53], respectively.
The NJ tree was generated using the Tamura-Nei model
of evolution [54] and a gamma parameter of 0.065. Bootstrap support values were calculated using 1000 replicates. The Bayesian analysis was run using the default
four heated, one million step chains with an initial burnin of 100,000 steps. We calculated the corrected average
number of pairwise differences between mitochondrial
lineages (d) in ARLEQUIN.
To determine whether the number of pairwise differences among all DNA sequences reflected expanding or
stable populations [55], we calculated the frequency distribution of the number of mutational differences
between haplotypes (mismatch analyses), as implemented
in ARLEQUIN. To determine confidence intervals
around this value we calculated Harpending’s raggedness
index, r [55], which tests the null hypothesis of an
expanding population. This statistic quantifies the
smoothness of the observed pairwise difference distribution and a non-significant result indicates an expanding
population. Fu’s F S [56], which is highly sensitive to
population expansions was calculated using 10,000 permutations. Significant negative values of FS indicate an
excess of low-frequency haplotypes, a signature characteristic of either selection or a recent demographic
expansion [56].
To test for hierarchical population genetic structure in
C. argus, an analysis of molecular variance (AMOVA)
was performed in ARLEQUIN using 20,000 permutations. Because the TPM1uf+G model of sequence evolution is not implemented in ARLEQUIN, we used the
most similar model available [54] with a gamma value
of 0.065. An analogue of Wright’s F ST (F ST ), which
incorporates the model of sequence evolution, was calculated for the entire dataset and for pairwise comparisons among all locations. We maintained a = 0.05
among all pairwise tests by controlling for the false discovery rate as recommended by Benjamini and Yekutieli
[57] and reviewed by Narum [58]. A Mantel test was
Page 5 of 15
performed to determine whether significant isolation-bydistance exists among populations by testing for correlation between pairwise F ST values and geographic
distance using the Isolation-by-Distance Web Service
3.16 [59]. Mantel tests were performed with 10,000
iterations on the dataset that included negative F ST
values and again with negative FST values converted to
zeros.
To estimate the time to coalescence we used the Bayesian MCMC approach implemented in BEAST 1.5.4
[60]. We conducted our analysis with a relaxed lognormal clock and under a model of uncorrelated substitution rates among branches. We used default priors
under the HKY + G model of mutation (jMODELTEST)
[61,62] and ran simulations for 10 million generations
with sampling every 1000 generations. Five independent
runs were computed to ensure convergence and log files
were combined using the program TRACER 1.5 [63].
Nuclear introns
Observed heterozygosity (HO) and expected heterozygosity (HE) were calculated for each locus and an exact
test of Hardy-Weinberg equilibrium (HWE) using
100,000 steps in a Markov chain was performed using
ARLEQUIN. To test whether HE differed between ocean
basins we calculated unpaired t-tests as described above.
Linkage disequilibrium between the two nuclear loci
was assessed using the likelihood ratio test with 20,000
permutations in ARLEQUIN. We tested for population
expansions by calculating Fu’s FS [56], using 10,000 permutations in ARLEQUIN. Genotypes for each individual
at the GnRH and S7 introns were compiled and used to
calculate FST for the multi-locus dataset and for pairwise
comparisons between locations in ARLEQUIN. The false
discovery rate among multiple comparisons was controlled as described above. Median-joining networks for
alleles at each locus were constructed using the program
NETWORK. We tested for correlation between pairwise
F ST values and geographic distance (isolation-bydistance) among all populations using the Isolation-byDistance Web Service [60] as described above.
Migration
Migration rates between groups (Nm: where N is effective
population size and m is migration rate) were calculated
with the software MIGRATE 3.1.6 [64,65]. To minimize
the parameters run, we pooled locations that showed no
pairwise structure (i.e. those locations with a pairwise FST
that did not significantly differ from zero) into demes
defined by region (see Results). This program uses a Bayesian MCMC search strategy of a single, replicated, two
million step chain. The default settings for priors were
used with an unrestricted migration model. Estimates of
the number of immigrants per generation (Nm) were calculated by multiplying final estimates of θ and M [66].
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Results
Mitochondrial DNA
We resolved a 729 bp segment of cytochrome b in 550
individuals yielding 57 haplotypes with 34 of these haplotypes observed in single individuals (Table 1). Due to
geographic proximity and a lack of genetic differentiation (as measured by pairwise FST) we grouped the specimens from the central Pacific locations of Samoa and
Tokelau, and Baker and Howland Island. The number of
individuals (N), number of haplotypes (Nh), haplotype
diversity (h), and nucleotide diversity (π) for each location are provided in Table 1. Overall nucleotide diversity
in C. argus was low (π = 0.005) while the corresponding
haplotype diversity was high (h = 0.80). Across all samples, π = 0.001 - 0.009 and h = 0.38 - 0.96 with higher
genetic diversity detected in the Pacific compared to the
Indian Ocean (unpaired t-test, π: t = 2.22, df = 19, P =
0.039; h: t = 2.88, df = 19, P = 0.010). Using the program BEAST and implementing a molecular clock of 2%
per million years [67-69] we estimated a coalescence
time of approximately 930,000 years with bounds of the
95% highest posterior density intervals (HPD) of 0.5 and
1.5 million yrs, dates that correspond to the middle of
the Pleistocene. The median-joining network revealed
two clusters of haplotypes that are distinguished by
three substitutions (d = 0.008, Figure 2a). The two
lineages, which we refer to as the Pacific and Indian
Ocean lineages, were confirmed by the phylogenetic
analyses (Figure 3). Coalescence times for the two
lineages were 580,000 (95% HPD = 0.25 - 1.0 million)
and 520,000 (95% HPD = 0.22 - 0.88 million) yrs,
respectively. No haplotypes from the Pacific Ocean lineage were detected at the western Indian Ocean locations
of Diego Garcia, Oman, and Seychelles while 10 of 291
samples from the Pacific Ocean fell into the Indian
Ocean lineage (Figure 1). A region of extensive overlap
was found at the Indian Ocean locations of Bali, Scott
Reef, Rowley Shoals, Christmas Island, and Cocos/Keeling Islands (Figure 1).
Overall FST was 0.297 (P < 0.001). When we grouped
samples by ocean basin (as described in Methods) we
found significant structure between the Pacific and
Indian Oceans (FCT = 0.242, P < 0.001). Within oceans
we found low but significant structure in the Pacific
Ocean (FST = 0.036, P < 0.001) and higher structure in
the Indian Ocean (FST = 0.249, P < 0.001). Pairwise comparisons indicate low levels of structure at the eastern
edge of the range distinguishing Marquesas and Moorea
(Table 2) but no structure across the entire central Pacific from Kiritimati to Lizard Island (Table 2). While there
was no structure among locations in the western Indian
Ocean (Diego Garcia, Oman, and Seychelles) and Sumatra, high levels of structure were observed between these
Page 6 of 15
locations and the eastern Indian Ocean (Christmas
Island, Cocos/Keeling, Bali, Scott Reef, and Rowley
Shoals).
Population expansion parameters for the overall dataset
gave conflicting results. As expected with the presence of
two divergent mitochondrial lineages, the mismatch distribution for the overall dataset was bimodal (Figure 4) and
resulted in a significant raggedness index (r = 0.24, P <
0.001), a result that indicates a stable population. In contrast, Fu’s FS resulted in FS = -12.8 (P < 0.001) signifying
an excess of low-frequency haplotypes and an expanding
population. Grouping locations that demonstrated no significant population structure (see Table 2) resulted in five
groups: French Polynesia (FP) = Marquesas and Moorea;
central-west Pacific (CW) = Kiritimati, Palmyra, Samoa/
Tokelau, Baker/Howland, Kwajalein, Pohnpei, Saipan,
Palau, Lizard Island, Philippines, and Scott Reef; IndoPacific boundary (IB) = Bali and Rowley Shoals; eastern
Indian Ocean (EI) = Cocos/Keeling and Christmas Islands;
western Indian Ocean (WI) = Sumatra, Diego Garcia,
Oman, and Seychelles. Despite their close geographic
proximity and lack of genetic structure with many populations in the CW, Bali and Rowley Shoals were grouped
separately because they demonstrate significant genetic
structure when compared to Samoa/Tokelau and Baker/
Howland. When analyzed separately, mismatch analyses
resulted in non-significant raggedness indices for each
group (data not presented). Fu’s FS indicated expanding
populations for FP (FS = -4.8, P = 0.014), CW (FS = -20.9,
P < 0.001) and WI (FS = -8.9, P < 0.001) but no evidence
for population expansion was found for either IB (FS =
-0.43, P = 0.48) or EI (FS = -0.48, P = 0.63).
Nuclear introns
We resolved 245 bp of the GnRH intron in 488 specimens and 393 bp of the S7 intron in 490 specimens
(Table 1). Seven polymorphic sites yielded 11 alleles at
the GnRH locus and 15 polymorphic sites yielded 20
alleles at the S7 locus. Median-joining networks for the
GnRH and S7 introns revealed two prominent alleles at
each locus that were found throughout the species’ range
(Figure 2b, c). The number of individuals (N), number of
alleles (Na), observed heterozygosity (HO), expected heterozygosity (HE), and the corresponding P-value for the
exact tests for HWE are listed in Table 1. The samples
from the Marquesas and Samoa/Tokelau were found to
be inconsistent with HWE expectations with an excess of
homozygotes at the GnRH locus (P = 0.002 and 0.044,
respectively) while the sample from Diego Garcia was
found to have an excess of heterozygotes at the S7 locus
(P = 0.047) (Table 1). Across all samples HE = 0.26 - 0.80
for the GnRH intron and H E = 0.28 - 0.79 for the S7
intron with higher values of HE detected in the Pacific
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Figure 2 Median-joining networks for Cephalopholis argus. Networks were constructed using the program NETWORK 4.5 [43] for (a) 550
cytochrome b sequences (b) alleles at GnRH intron from 488 individuals, and (c) alleles at S7 intron for 490 individuals. Each circle represents
one mitochondrial haplotype or nuclear allele with the area of each circle proportional to the number of that particular haplotype or allele in
the dataset; dashes represent hypothetical haplotypes or alleles; colors represent collection location (see key).
compared to the Indian Ocean (unpaired t-test, GnRH: t
= 3.17, df = 19, P = 0.005; S7: t = 3.99, df = 19, P <
0.001). There was no indication of linkage disequilibrium
between the two loci (P > 0.05).
Overall FST values for GnRH, S7, and the multi-locus
dataset were FST = 0.078 (P < 0.001), FST = 0.099 (P <
0.001), and FST = 0.127 (P < 0.001), respectively. Analyses of these data reveal patterns of population structure that are concordant with the mitochondrial dataset.
Grouping samples by ocean basin (as above) revealed
significant structure between the Pacific and Indian
Oceans (GnRH, FCT = 0.056, P = 0.002; S7, FCT = 0.103,
P < 0.001, multi-locus FCT = 0.154, P < 0.001) and significant structure within ocean basins (Pacific Ocean:
GnRH, F ST = 0.020, P = 0.025; S7, F ST = 0.041, P <
0.001; multi-locus, F ST = 0.013, P = 0.039; Indian
Ocean: GnRH, FST = 0.074, P < 0.001; S7, FST = 0.049,
P < 0.001; multi-locus, FST = 0.072, P < 0.001). Pairwise
FST for the multi-locus dataset are reported in Table 2.
Overall the nuclear dataset measured lower levels of
population structure compared to mtDNA. Using the
multi-locus dataset we found little population subdivision across the central Pacific and no structure in the
western Indian Ocean. This dataset did not detect the
low levels of population structure at the Marquesas and
Moorea as revealed in the mtDNA dataset, nor were the
Indian Ocean populations as divergent using these markers (Table 2).
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89/100/100
Indian Ocean Lineage
WI) contribute to genetic diversity across the central portion of the range (Nm per generation = 2.2 - 87.3 and 1.5
- 6.6, respectively), they rarely receive migrants (Nm per
generation = 0.0 - 0.4 and 0.0, respectively; Figure 5).
There is evidence of considerable migration between the
other groups (Nm per generation = 1.8 - 39.0; Figure 5).
Isolation by distance (IBD)
70/68/88
Pacific Ocean Lineage
Fixed differences
between lineages at
5' positions 11, 14 & 53
Mantel tests showed a strong correlation between genetic
distance (F ST or F ST ) and geographic distance in the
mtDNA (r = 0.749, P = 0.001) and the multi-locus
nuclear (r = 0.715, P < 0.001) datasets. Replacing negative
values of FST and FST with zeros did not affect the pattern or statistical significance. To test if genetic structure
between ocean basins was driving IBD we conducted
Mantel tests within oceans and found weaker but still significant correlations between genetic distance and geographic distance with the Cytb dataset (Pacific Ocean: r =
0.301, P = 0.033; Indian Ocean: r = 0.778, P = 0.004) but
not the multi-locus nuclear dataset (Pacific Ocean: r =
-0.056, P = 0.629; Indian Ocean: r = 0.315, P = 0.085).
79/57/94
76/84/100
C. urodeta
C. taeniops
Figure 3 Phylogenetic tree of Cephalopholis argus cytochrome
b haplotypes. The best maximum likelihood tree generated using
program default settings in RAxML [44] and rooted using two
congenerics (C. urodeta and C. taeniops). Bootstrap support values
were calculated using default settings with 1000 replicates. For
comparison neighbor-joining bootstrap values (1000 bootstrap
replicates) and Bayesian posterior probabilities are presented.
Colored bars delineate the Pacific and Indian Ocean lineages
separated by three fixed differences (see figure 1).
As might be expected from loci with low numbers of
closely related alleles, the mismatch distributions for the
overall nuclear dataset and for the five geographic
groups (FP, CW, IB, EI, and WI) were unimodal and
resulted in non-significant raggedness indices (overall
dataset: GnRH, r = 0.32, P = 0.082; S7, r = 0.12, P =
0.235; data for geographic groups not shown). Fu’s FS
calculations offered no evidence for expanding populations for either the overall dataset (GnRH, FS = -0.34,
P = 0.521; S7, F S = -3.93, P = 0.162) or for the geographic groups (data not shown).
Migration
Migration analyses for the nuclear dataset proved to be
uninformative. Posterior probabilities did not narrow on
a single mode for several comparisons and confidence
intervals were unreasonably large. We present only the
mtDNA data here. Migration rates indicate that while the
populations of C. argus at the ends of the range (FP and
Discussion
The origin of the remarkable species richness of the Coral
Triangle (CT) has fostered numerous and seemingly conflicting hypotheses. The center of origin hypothesis postulates that elevated rates of speciation in the CT have
resulted in high species diversity [9]. In contrast, the center of accumulation hypothesis contends that taxa have
evolved peripherally and subsequently accumulate in the
CT due to prevailing currents [19]. Finally, the region of
overlap hypothesis states that the observed pattern is the
result of admixture of the distinct biotas of the Pacific and
Indian Oceans [21]. Despite considerable effort to determine the mechanism driving species diversity in the IndoPacific, no consensus has emerged [7,24,25]. Our genetic
survey of C. argus across 18,000 km of the Indo-Pacific
lends some insight into this debate.
Cephalopholis argus demonstrates significant levels of
genetic structure that indicate a historical partition
between the Pacific and Indian Oceans (Table 2). Two
mitochondrial lineages are distinguished by fixed differences (d = 0.008) indicating isolation for approximately
one million years (95% HPD intervals are 0.5 - 1.5 million yrs), a time interval that corresponds to Pleistocene
sea level fluctuations linked to Milankovitch climate
cycles on the scale of 105 years [70]. Our analyses indicate expanding populations with migration toward the
center of the range. The high genetic diversity of this
species within and adjacent to the CT is a result of mixing Pacific and Indian Ocean lineages (Figures 1, 5).
Hence these data support isolation of Pacific and Indian
Ocean populations during prolonged and repeated sea
level fluctuations of the Pleistocene, followed by
Location
1. Marquesas
2. Moorea
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
0.042
0.010
-
0.020
-0.021
0.031
0.004
0.077
0.035
0.048
0.023
0.015
0.003
0.038
0.026
0.024
0.004
-0.001
0.007
-0.077
-0.117
-0.018
0.117
0.093
0.095
0.021
0.022
0.059
0.064
0.089
0.093
0.197
0.200
0.298
0.399
0.335
0.340
0.193
0.188
0.255
0.261
3. Kiritimati
0.039
0.059
-
0.002
0.017
-0.020
-0.029
0.036
-0.007
0.004
-0.044
0.041
0.222
0.026
0.111
0.122
0.269
0.380
0.424
0.312
0.374
4. Palmyra
0.036
0.021
0.006
-
-0.002
-0.027
-0.019
0.088
0.017
0.024
-0.077
0.161
0.275
0.067
0.164
0.164
0.322
0.496
0.471
0.381
0.431
5. Samoa/Tokelau
0.022
0.044
-0.002
0.002
-
0.004
0.012
0.108
0.039
0.057
-0.115
0.162
0.277
0.098
0.190
0.183
0.329
0.483
0.476
0.372
0.426
6. Baker/Howland
0.063
0.104
-0.023
0.032
-0.006
-
-0.004
0.089
0.027
0.041
-0.125
0.025
0.241
0.077
0.164
0.169
0.309
0.361
0.457
0.341
0.399
7. Kwajalein
0.114
0.135
0.015
0.030
0.059
0.036
-
0.032
-0.001
-0.001
-0.133
0.022
0.151
0.026
0.097
0.104
0.229
0.328
0.381
0.242
0.304
8. Pohnpei
0.019
0.015
-0.025
-0.014
-0.034
-0.019
0.029
-
0.050
0.002
-0.063
0.073
0.009
0.004
0.021
0.007
0.079
0.280
0.225
0.067
0.135
9. Saipan
10. Palau
0.109
0.097
0.107
0.103
-0.011
0.013
0.040
0.002
0.055
0.056
0.015
0.050
0.009
-0.020
0.054
0.050
0.006
0.015
-
-0.089
0.033
0.048
0.035
0.169
0.060
0.017
0.004
0.077
0.041
0.118
0.045
0.233
0.145
0.355
0.286
0.372
0.292
0.244
0.138
0.300
0.202
11. Lizard Is
0.008
-0.011
0.009
-0.015
-0.009
0.036
0.052
-0.020
0.040
-0.111
-
0.128
0.174
-0.045
0.040
0.033
0.187
0.432
0.348
0.222
0.290
12. Philippines
0.140
0.205
-0.039
-0.003
0.087
0.020
-0.095
0.072
-0.088
-0.093
0.070
-
0.043
0.003
-0.010
0.047
0.046
0.160
0.147
0.107
0.082
13. Bali
0.169
0.179
0.072
0.063
0.126
0.112
-0.015
0.096
0.039
-0.014
0.092
-0.077
-
0.055
0.006
-0.024
0.001
0.151
0.093
-0.028
0.022
14. Scott Reef
0.103
0.085
0.007
0.030
0.057
0.035
-0.001
0.050
-0.027
-0.012
0.042
-0.095
0.017
-
0.012
0.046
0.124
0.224
0.257
0.115
0.177
15. Rowley Shoals
0.165
0.156
0.062
0.067
0.119
0.099
0.003
0.100
0.022
-0.010
0.094
-0.084
-0.016
0.017
-
0.024
0.059
0.137
0.155
0.035
0.084
16. Christmas Is
0.271
0.263
0.169
0.167
0.224
0.206
0.067
0.196
0.116
0.064
0.190
-0.004
0.014
0.095
0.014
-
0.020
0.168
0.134
0.010
0.057
17. Cocos/Keeling
18. Sumatra
19. Diego Garcia
0.391
0.830
0.765
0.387
0.906
0.798
0.287
0.731
0.694
0.276
0.751
0.703
0.345
0.849
0.759
0.327
0.805
0.737
0.150
0.535
0.565
0.303
0.835
0.738
0.226
0.676
0.659
0.158
0.595
0.604
0.294
0.836
0.734
0.105
0.570
0.644
0.081
0.461
0.511
0.201
0.615
0.611
0.092
0.459
0.498
0.009
0.277
0.351
0.147
0.030
-
0.041
-0.019
-0.027
-0.045
-0.007
-0.008
0.228
0.039
-
0.014
-0.009
20. Oman
0.790
0.861
0.695
0.718
0.801
0.760
0.521
0.620
0.648
0.580
0.775
0.379
0.472
0.592
0.453
0.299
0.174
-0.034
-0.013
-
-0.028
21. Seychelles
0.778
0.831
0.688
0.706
0.775
0.742
0.521
0.741
0.640
0.582
0.738
0.595
0.475
0.596
0.476
0.337
0.216
0.109
-0.005
0.055
-
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Table 2 Pairwise F statistics for 21 populations of Cephalopholis argus
Pairwise FST values for cytochrome b data are below diagonal and pairwise FST values for multi-locus nuclear dataset are above diagonal. Significant comparisons are in bold. We maintained a = 0.05 among all
pairwise tests by controlling for the false discovery [51,52]. The corrected a = 0.008.
Page 9 of 15
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population expansion and colonization of the CT from
both the Pacific and Indian Oceans: a pattern that is
consistent with predictions of the region of overlap
hypothesis.
While incomplete lineage sorting is a serious problem
for species level reconstructions, our pattern of divergence across the IPB is corroborated by three independent markers. Additionally, the finding of isolation by
distance across the species range is strong evidence that
the patterns we present here are not driven by stochastic events.
Indo-Pacific Barrier-the mechanism of isolation
Figure 4 Mismatch distribution for Cephalopholis argus.
Mismatch distribution based on 550 cytochrome b sequences from
twenty-one populations. The dark colored line represents the
observed and light colored line is the simulated pairwise differences
as reported by DnaSP 5.0 [39]. The Harpending’s raggedness index
as calculated in ARLEQUIN 3.5 [42] and corresponding P-value are
shown.
The Sunda shelf, surrounding the Malay Peninsula and
western islands of Indonesia, and the Sahul shelf off northern Australia and New Guinea, separate the Pacific and
Indian Oceans and together are known as the Indo-Pacific
Barrier (IPB) [71]. Over the last 700,000 yrs there have
been at least three to six glacial cycles that lowered sea
level as much as 130 m below present levels (Figure 6,
[23,72-74]). Species on the continental shelves were
Figure 5 Migration rates for Cephalopholis argus. Migration rates (Nm: where N is effective female population size and m is migration rate)
based on cytochrome b sequences calculated using MIGRATE 3.1.6 [54,55]. Locations with non-significant pairwise FST values were grouped (see
Table 2). French Polynesia (FP) = Marquesas and Moorea; central-west Pacific (CW) = Kiritimati, Palmyra, Samoa/Tokelau, Baker/Howland,
Kwajalein, Pohnpei, Saipan, Palau, Lizard Island, Philippines, and Scott Reef; Indo-Pacific boundary (IB) = Bali and Rowley Shoals; eastern Indian
Ocean (EI) = Christmas Island and Cocos/Keeling; western Indian Ocean (WI) = Sumatra, Diego Garcia, Oman, and Seychelles. The direction of
migration is indicated. Numbers of migrants per generation between geographic regions are reported with 95% confidence intervals in
parentheses.
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Figure 6 Map of Indo-Malaysia region during glacial maxima. Map shows the effect of lowered sea level on habitat in the region during
Pleisotocene glacial maxima (Figure credit: Eric Franklin).
repeatedly subjected to widespread extirpations and presumably interruption of gene flow between Pacific and
Indian Ocean populations. However, at glacial maxima the
isolation of the two ocean basins was not complete. Associated with the change in sea level were concomitant
changes in oceanographic current patterns, altered discharge of local rivers, with corresponding changes in temperature and salinity [75,76]. The narrow seaways that
remained were likely under the influence of cooler upwelling, further limiting the availability of suitable habitat for
tropical marine organisms [10,23,71,73,77]. In sum, the
isolating mechanism between ocean basins may have been
due to both ecological and geological factors.
The evidence for the impact of the IPB on shallow tropical marine organisms is extensive and compelling. Historical and contemporary restrictions to dispersal between the
Pacific and Indian Oceans are indicated by the confinement of many demersal species primarily to one ocean or
the other [3,21,78,79]. More recently, genetic data have
been used to assess the IPB. Studies of demersal organisms
that lack vagile adults have found intraspecific genetic differentiation across the IPB in many fishes [80-88] and
invertebrates [89-96] with few exceptions [67,69,95,97,98].
Genetic analyses reveal signatures of isolation that correspond to Pleistocene sea level fluctuations across a diversity of taxa [82,85,93,97,99] including C. argus. This
species demonstrates strong population structure between
Pacific and Indian Ocean locations in both the mitochondrial and nuclear datasets. The mismatch distribution for
C. argus is distinctly bimodal (Figure 4) which is characteristic of species under the influence of a strong biogeographic barrier [100,101]. The mid-Pleistocene age of the
two mitochondrial lineages of C. argus coupled with
assortment by ocean basins is compelling evidence that
the divergence is a result of isolation on either side of the
IPB.
Eastern Indian Ocean and the Coral Triangle: A region of
overlap
Since the last glacial maximum about 18,000 yrs ago, the
land bridge that impeded dispersal between the Pacific
and Indian oceans submerged and the rising sea level not
only opened dispersal pathways but was also accompanied by an approximately 10 fold increase in suitable
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shallow reef habitat [4]. Woodland [21] was the first to
propose that range expansions of species formed in isolation during Pleistocene glacial cycles contributed to the
incredible species richness of the CT. His work on species distributions of rabbitfishes (Family Siganidae) and
later the work of Donaldson [102] on hawkfishes (Family
Cirrhitidae) offer supporting evidence. Range expansions
are also indicated by the presence of a hybrid zone in the
eastern Indian Ocean [103]. Cocos/Keeling and Christmas Islands lie 500 and 1,400 km, respectively, from the
southern coast of the Indonesian Island of Java, and are a
known region of overlap for Pacific and Indian Ocean
fish faunas. Here, sister species that are otherwise
restricted to different oceans inhabit the same reefs and
in many cases hybridize [103-105]. Notably, we found
nearly equal proportions of Pacific and Indian Ocean C.
argus haplotypes in this hybrid zone (Figure 1). These
findings demonstrate that, at least in terms of intraspecific genetic diversity, the introgression is not restricted to
Cocos/Keeling and Christmas Islands but instead extends
well into Indonesia, the western Pacific, and to a lesser
extent, the central Pacific.
If we provisionally assume that genetic divergences are
the result of isolation across the IPB, we can estimate the
degree of introgression since the last ice age. In some taxa,
effective migration between ocean basins is absent as evidenced by a lack of shared haplotypes between oceans
(Chlorurus sordidus [82]; Penaeus monodon [93]). Other
taxa reveal signatures of historical isolation but lack contemporary spatial structure (Naso brevirostris [97]). Pacific
and Indian Ocean populations of C. argus share haplotypes but mixing is incomplete as evidenced by significant
population structure between oceans, a pattern observed
in several other species (Myripristis berndti [84]; Naso vlamingii [99]; Nerita albieilla [106]). C. argus is unique in
that it demonstrates unidirectional dispersal out of the
western Indian Ocean (WI) and French Polynesia (FP)
toward the center of the range (Figure 5) while populations in the CT and western Australia, the area near the
Indo-Pacific boundary, demonstrate high levels of bidirectional dispersal, high genetic diversity, and extensive lineage overlap (Figures 1, 5).
There is compelling evidence for the influence of the
IPB on coral reef organisms from intraspecific lineage
sorting to species level distributions. The degree of
range expansion or lineage mixing after the last glacial
maximum varies among taxa and may reflect species
level differences in dispersal ability, reproductive strategy, competitive ability, or habitat requirements.
Phylogeographic inferences: emerging patterns in IndoPacific reef fishes
Our dataset allows for several phylogeographic inferences. Molecular diversity indices and the topology of
Page 12 of 15
the medium joining networks indicate that Indian
Ocean populations harbor more genetic diversity. The
position of the Indian Ocean lineage in the phylogenetic
tree indicates that this lineage may be older but coalescence dates do not support this. Taken together these
data may indicate that during low sea level stands,
populations in the western Indian Ocean were less
severely impacted than those in the Pacific. C. argus
demonstrates no population structure across the nearly
8,000 km central Pacific range, from Kiritimati to Palau.
However, pairwise F ST and F ST values and migration
rates indicate that populations at the eastern end of the
range at Moorea and the Marquesas are isolated. This
pattern of extensive population connectivity across the
central Pacific with isolation at the ends of the Pacific
range is emerging in reef fishes (reviewed in [86]; see
also [107]).
Biogeographic inferences: the Western Indian Ocean
Province
The isolation of the western Indian Ocean (WIO) is supported by both species distributions [22] and intraspecific
genetic data [84,87,97], evidence that the microevolutionary divergences documented with DNA sequence data
can lead to macroevolutionary partitions between species.
Genetic analyses seperate Indian Ocean populations of
C. argus along an east-west gradient and indicate unidirectional dispersal out of the WIO. Despite being geographically located in the Indian Ocean, the eastern Indian
Ocean faunas at Cocos/Keeling and Christmas Islands,
and Western Australia are closely affiliated with the Pacific ichthyofauna with only 5% of reef fishes at Cocos/
Keeling of exclusively Indian Ocean origin [108]. Instead,
these islands are considered to be a part of the IndoPolynesian Province that stretches from the eastern
Indian Ocean to French Polynesia [3,22]. Diego Garcia in
the Chagos Archipelago lies in the middle of the Indian
Ocean 1,900 km east of the Seychelles and 2,400 km west
of Cocos/Keeling. Fish surveys in the Chagos Islands delineated the archipelago into two distinct assemblages,
with the northern portion sharing affinities with the eastern Indian Ocean and the southern portion (including
Diego Garcia) more closely aligned with faunal assemblages further west [109]. The distinction of the ichthyofauna assemblage of the southern Chagos Archipelago
coupled with a lack of intraspecific genetic structure in
two species of reef fishes from Diego Garcia and sites
further west (Lutjanus kasmira [98] and C. argus, this
study) indicate that Diego Garcia is a part of the Western
Indian Ocean Province as described by Briggs [22]. Faunal surveys indicate that the fishes of India and Sri Lanka
have a strong affiliation with the Malay Peninsula [22].
Taken together, these data indicate that the western
boundary of the Indo-Polynesian Province lies east of
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Oman and includes India, Sri Lanka, and the northern
Chagos Archipelago [110]. While we use species distributions and genetic data to define biogeographic provinces,
the mechanisms that separate the eastern and western
Indian Ocean are unknown and require more detailed
genetic and oceanographic work.
Proteomics, and Bioinformatics sequencing facility for their assistance with
DNA sequencing and all the staff at the Hawaii Institute of Marine Biology
for their support throughout this project. We thank Dr. Gert Wrheide and
four anonymous reviewers whose comments substantially improved the
manuscript. This is contribution #1451 from the Hawaii Institute of Marine
Biology, #8197 from the School of Ocean and Earth Science and
Technology, and UNIHI-SEAGRANT-JC-09-37 from the University of Hawaii
Sea Grant Program.
Conclusions
Our genetic survey of the grouper Cephalopholis argus
indicates that this species was strongly impacted by Pleistocene sea level fluctuations which resulted in the partitioning of this species into Pacific and Indian Ocean
mitochondrial lineages that are distinguished by fixed differences (d = 0.008). Following the end of the last glacial
maximum, connectivity between the Pacific and Indian
Oceans resumed and C. argus populations expanded.
Representatives of each mitochondrial lineage are now
found in both oceans with the center of diversity occurring in the Coral Triangle: a pattern that we offer as support for the region of overlap hypothesis. In a recent
review 15 out of 18 species demonstrated significant
structure across the IPB, such that subsequent contact
would constitute support of the region of overlap hypothesis [98]. However, the studies cited above, on a diverse
array of marine taxa, offer equally compelling evidence
for the other two competing hypotheses: the center of
origin and center of accumulation. None of these hypotheses are mutually exclusive, and acting in concert, they
are likely to explain the patterns of biodiversity in the
Indo-Pacific.
Author details
1
Hawaii Institute of Marine Biology University of Hawaii PO Box 1346,
Kaneohe, HI 96744, USA. 2Department of Ichthyology California Academy of
Sciences 55 Music Concourse Drive San Francisco, CA 94118, USA. 3Western
Australian Fisheries and Marine Research Laboratories Department of
Fisheries Government of Western Australia P.O. Box 20, North Beach, WA
6920, Australia. 4School of Marine & Tropical Biology James Cook University
Townsville, QLD 4811, Australia. 5Department of Marine Sciences University
of Puerto Rico Mayagüez P.O. Box 9000, Mayagüez PR 00681, USA.
Acknowledgements
This study was supported by the National Science Foundation (NSF) under
grants No. OIA0554657, OCE-0453167 (BWB), and OCE-0929031 (BWB).
Additional support for this work came from NOAA National Marine
Sanctuaries Program MOA grant No. 2005-008/66882 (BWB) and the National
Oceanic and Atmospheric Administration, Project R/HE-1, which is sponsored
by the University of Hawaii Sea Grant College Program, SOEST, under
Institutional Grant No. NA09OAR4170060 (BWB) from NOAA Office of Sea
Grant, Department of Commerce. Field work at Cocos/Keeling and Christmas
Island was supported by National Geographic Grant 8208-07 (MTC). Sample
collection at the Rowley Shoals was facilitated by a research permit from the
Department of Environment and Conservation (Western Australia). The views
expressed herein are those of the authors and do not necessarily reflect the
views of NSF, NOAA, or any of their sub-agencies. Thanks to Kimberly
Andrews, Christopher Bird, Kimberly Conklin, Zac Forsman, Jennifer Schultz,
Derek Skillings, and especially Robert Toonen and Steve Karl for their
intellectual input. Paul Barber, J. Howard Choat, Pat Collins, Laura Colin,
Joseph DiBattista, John Earle, Jeff Eble, Brian Greene, Matthew “quick like a
cat” Iacchei, Shelley Jones, Jim Maragos, Gabby Mitsopoulos, Craig
Musburger, David Pence, Jon Puritz, D. Ross Robertson, Ben Rome, Charles
Sheppard, Craig Skepper, John Starmer, Robert Thorn, Daniel “Danimal”
Wagner, and Zoltan Szabo helped collect specimens. Trina Leberer at The
Nature Conservancy Micronesia, Sue Taei at Conservation International,
Graham Wragg of the RV Bounty Bay, the Coral Reef Research Foundation,
and the British Indian Ocean Territory. We thank the entire staff at the
research station on Palmyra including Kydd Pollock and Zachary Caldwell,
and especially Erik Conklin at TNC and Amanda Meyer at the US Fish and
Wildlife Service Palmyra for making collections there possible. We thank the
staff of the University of Hawaii’s Advanced Studies of Genomics,
Authors’ contributions
MRG obtained samples from the central Pacific and the Philippines,
participated in DNA sequencing, data analysis, data interpretation, and
prepared the manuscript. BWB participated in study design, funding, and
sampling from the Pacific and Indian Oceans, and helped prepare the
manuscript. TRB participated in DNA sequencing. LAR obtained samples
from across the Pacific and Indian Oceans, and helped prepare the
manuscript. SJN obtained samples from Western Australia and the eastern
Indian Ocean. LAG and LVH participated in sequencing individuals from
Western Australia and the east Indian Ocean. MTC obtained samples from
throughout the Pacific and Indian Oceans, participated in the design and
coordination of the study, and helped prepare the manuscript. All authors
approved the final manuscript.
Received: 5 December 2010 Accepted: 1 July 2011
Published: 1 July 2011
References
1. Bowen BW, Roman J: Gaia’s handmaidens: the Orlog model for
conservation biology. Con Biol 2005, 19:1037-1043.
2. Veron JEM: Corals in space and time: The biogeography and evolution of the
Scleratinia Sydney: University of New South Wales Press; 1995.
3. Randall JE: Zoogeography of shorefishes of the Indo-Pacific region. Zool
Studies 1998, 37:227-268.
4. Bellwood DR, Wainwright PC: The history and biogeography of fishes on
coral reefs. In Coral reef fishes: dynamics and diversity in a complex
ecosystem. Edited by: Sale PF. San Diego: Academic Press; 2002:5-32.
5. Roberts CM, McClean CJ, Veron JEN, Hawkins JP, Allen GR, McAllister DE,
Mittermeier CG, Schueler FW, Spalding M, Wells F, Vynne C, Werner TB:
Marine biodiversity hotspots and conservation priorities for tropical
reefs. Science 2002, 295:1280-1284.
6. Briggs JC: Marine centers of origin as evolutionary engines. J Biogeogr
2003, 30:1-18.
7. Mora C, Sale PF, Kritzer JP, Ludsin SA: Patterns and processes in reef fish
diversity. Nature 2003, 421:933-936.
8. Allen GR: Conservation hotspots of biodiversity and endemism for IndoPacific coral reef fishes. Aquatic Conservation: Marine and Freshwater
Ecosystems; 2007:18:541-556.
9. Ekman S: Zoogeography of the sea London: Sidgwick and Jackson; 1986.
10. McManus JW: Marine speciation, tectonics, and sea-level changes in
southeast Asia. In Proceedings of the Fifth International Coral Reef Congress.
Edited by: Gabrie C, Vivien MH. Moorea: Antenne Museum-Ephe;
1985:133-138, 27 May-1 June 1985; Tahiti.
11. Briggs JC: The marine East Indies: diversity and speciation. J Biogeogr
2005, 32:1517-1522.
12. Rocha LA, Bowen BW: Speciation in coral reef fishes. J Fish Biol 2008,
72:1101-1121.
13. Barber PH, Erdmann MV, Palumbi SR: Comparative phylogeography of
three codistributed stomatopods: origins and timing of regional lineage
diversification in the Coral Triangle. Evolution 2006, 60:1825-1839.
14. DeBoer TS, Subia MD, Erdmann MV, Kovitvongsa K, Barber PH:
Phylogeography and limited genetic connectivity in the endangered
Gaither et al. BMC Evolutionary Biology 2011, 11:189
http://www.biomedcentral.com/1471-2148/11/189
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
giant boring clam across the Coral Triangle. Conserv Biol 2008,
22:1255-1266.
Knittweis L, Kräemer WE, Timm J, Kochzius M: Genetic structure of
Heliofungia actiniformis (Scleractinia: Fungiidae) populations in the IndoMalay Archipelago: implications for the live coral trade management
efforts. Conserv Biol 2009, 10:241-249.
Kochzius M, Seidel C, Hauschild J, Kirchhoff S, Mester P, MeyerWachsmuth I, Nuryanto A, Timm J: Genetic population structure of the
blue starfish Linckia laevigata and its gastropod ectoparasite Thyca
crystallina. Mar Eco Prog Ser 2009, 396:211-219.
Nuryanto A, Kochzius M: Highly restricted gene flow and deep
evolutionary lineages in the giant clam Tridacna maxima. Coral Reefs
2009, 28:607-619.
Timm J, Kochzius M: Geological history and oceanography of the IndoMalay Archipelago shape the genetic population structure in the false
clown anemonefish (Amphiprion ocellaris). Mol Ecol 2008, 17:3999-4014.
Ladd HS: Origin of the Pacific Island molluscan fauna. Am J Sci 1960,
258A:137-150.
Jokiel P, Martinelli FJ: The vortex model of coral reef biogeography. J of
Biogeogr 1992, 19:449-458.
Woodland DJ: Zoogeography of the Siganidae (Pisces): an interpretation
of distribution and richness patterns. Bull Mar Sci 1983, 33:713-717.
Briggs JC: Marine zoogeography New York: McGraw-Hill; 1974.
Voris HK: Maps of Pleistocene sea levels in Southeast Asia: Shorelines,
river systems and time durations. J Biogeogr 2000, 27:1153-1167.
Connolly SR, Bellwood DR, Hughes TP: Indo-Pacific biodiversity of coral
reefs: deviations from a mid-domain model. Ecology 2003, 84:2178-2190.
Halas D, Winterbottom R: A phylogenetic test of multiple proposals for
the origins of the East Indies coral reef biota. J Biogeogr 2009,
36:1847-1860.
Wallace CC: The Indo-Pacific center of coral diversity re-examined at
species level. In Proceedings of the 8th international Coral Reef Symposium.
Edited by: Lessios HA, Macintyre IG. Balboa: Smithsonian Tropical Research
Institute; 1997:365-370, 24-29 June 1997; Panama.
Allen GR, Adrim M: Coral reef fishes of Indonesia. Zool Studies 2003,
42:1-72.
Barber PH, Bellwood DR: Biodiversity hotspots: evolutionary origins of
biodiversity in wrasses (Halichoeres: Labridae) in the Indo-Pacific and
new world tropics. Phylogenet Evol 2005, 35:235-253.
Drew J, Barber PH: Sequential cladogenesis of the reef fish Pomacentrus
moluccensis (Pomacentridae) supports the peripheral origin of marine
biodiversity in the Indo-Australian archipelago. Mol Phylogenet Evol 2009,
53:335-339.
Bowen BW, Clark AM, Abreu-Grobois FA, Chavez A, Reichart H, Ferl RJ:
Global phylogeography of the ridley sea turtles (Lepidochelys spp.)
inferred from mitochondrial DNA sequences. Genetica 1998, 101:179-189.
Eble JA, Toonen RJ, Sorenson L, Basch LV, Papastamatiou YP, Bowen BW:
Escaping paradise: larval export from Hawaii in an Indo-Pacific reef fish,
the Yellow Tang (Zebrasoma flavescens). Mar Ecol Prog Ser 2011,
428:245-258.
Palumbi SR: Molecular biogeography of the Pacific. Coral Reefs 1997, 16:
S47-S52.
Bernardi G, Bucciarelli G, Costagliola D, Robertson DR, Heiser JB: Evolution
of coral reef fish Thalassoma spp. (Labridae): 1. Molecular phylogeny
and biogeography. Mar Biol 2004, 144:369-375.
Avise JC: Molecular markers, natural history, and evolution Sunderland:
Sinauer Associates, Inc.; 2004.
Randall JE: Reef and Shore Fishes of the South Pacific Honolulu: Sea Grant
College Program University of Hawaii; 2005.
Shpigel M, Fishelson L: Territoriality and associated behvaiour in three
species of the genus Cephalopholis (Pisces: Serranidae) in the Gulf of
Aquba, Red Sea. J Fish Biol 1999, 38:887-896.
Leis JM: The pelagic phase of coral reef fishes: larval biology of coral
reef fishes. In The Ecology of Fishes on Coral Reefs. Edited by: Sale PF. San
Diego: Academic Press; 1991:183-230.
Linderman KC, Lee TM, Wilson WD, Claro R, Ault JS: Transport of larvae
originating in southwest Cuba and the Dry Tortugas: evidence for partial
retention in grunts and snappers. Proc Gulf Carib Fish Inst 2000,
52:253-278.
Seutin G, White BN, Boag PT: Preservation of avian and blood tissue
samples for DNA analyses. Can J Zool 1991, 69:82-92.
Page 14 of 15
40. Meeker ND, Hutchinson SA, Ho L, Trede NS: Method for isolation of PCRready genomic DNA from zebrafish tissues. BioTechniques 2007,
43:610-614.
41. Truett GE, Mynatt RL, Truett AA, Walker JA, Warman ML: Preparation of
PCR-quality mouse genomic DNA with hot sodium hydroxide and Tris
(HotSHOT). BioTechniques 2000, 29:52-54.
42. Hassan M, Lemaire C, Fauvelot C, Bonhomme F: Seventeen new exonprimed intron-crossing polymerase chain reaction amplifiable introns in
fish. Mol Ecol Notes 2002, 2:334-340.
43. Chow S, Hazama K: Universal PCR primers for S7 ribosomal protein gene
introns in fish. Mol Ecol 1998, 7:1247-1263.
44. Stephens M, Smith NJ, Donnelly P: A new statistical method for haplotype
reconstruction from population data. Am J Hum Genet 2001, 68:978-989.
45. Stephens M, Donnelly P: A comparison of Bayesian methods for
haplotype reconstruction from population genotype data. Am J Hum
Genet 2003, 73:1162-1169.
46. Librado P, Rozas J, DnaSP v5: As software for comprehensive analysis of
DNA polymorphism data. Bioinformatics 2009, 25:1451-1452.
47. Maddison DR, Maddison WP: MacClade 4: analysis of phylogeny and
character evolution Sunderland: Sinauer Associates; 2002.
48. Nei M: Molecular evolutionary genetics New York: Columbia University Press;
1987.
49. Excoffier L, Lischer HEL: Arlequin suite ver 3.5: a new series of programs
to perform population genetics analyses under Linux and Windows. Mol
Ecol Res 2010, 10:564-567.
50. Bandelt HJ, Forster P, Röhl A: Median-joining networks for inferring
intraspecific phylogenies. Mol Biol Evol 1999, 16:37-48.
51. Stamatakis A: RAxML-VI-HPC: Maximum likelihood-based phylogenetic
analyses with thousands of taxa and mixed models. Bioinformatics 2006,
22:2688-2690.
52. Tamura K, Dudley J, Nei M, Kamar S: MEGA4: molecular evolutionary
genetics analysis (MEGA) software version 4.0. Mol Biol Evol 2007,
24:1596-1599.
53. Huelsenbeck JP, Ronquist F: MRBAYES: Bayesian inference of phylogeny.
Bioinformatics 2001, 17:754-755.
54. Tamura K, Nei M: Estimation of the number of nucleotide substitutions in
the control region of mitochondrial DNA in humans and chimpanzees.
Mol Biol Evol 1993, 10:512-526.
55. Harpending HC: Signature of ancient population growth in a low-resolution
mitochondrial DNA mismatch distribution. Human Biol 1994, 66:591-600.
56. Fu YX: Statistical tests of neutrality of mutations against population
growth, hitchhiking, and background selection. Genetics 1997,
147:915-925.
57. Benjamini Y, Yekutieli D: The control of the false discovery rate in
multiple testing under dependency. Annals of Statistics 2001,
29:1165-1188.
58. Narum SR: Beyond Bonferroni: Less conservative analyses for
conservation genetics. Conservation Genetics 2006, 7:783-787.
59. Jensen JL, Bohonak AJ, Kelley ST: Isolation by distance, web service. BMC
Genetics 2005, 6:13.
60. Drummond AJ, Rambaut A: BEAST: Bayesian evolutionary analysis by
sampling trees. BMC Evol Biol 2007, 7:214-221.
61. Guindon S, Gascuel O: A simple, fast, and accurate algorithm to estimate
large phylogenies by maximum likelihood. Syst Biol 2003, 14:685-695.
62. Posada D: jModelTest: Phylogenetic model averaging. Mol Biol Evol 2008,
25:1253-1256.
63. Molecular Evolution, Phylogenetics, and Epidemiology Website. [http://
tree.bio.ed.ac.uk/software/tracer/].
64. Beerli P, Felsenstein J: Maximum-likelihood estimation of migration rates
and effective population numbers in two populations using a coalescent
approach. Genetics 1999, 152:763-773.
65. Beerli P, Felsenstein J: Maximum likelihood estimation of a migration
matrix and effective population sizes in n subpopulations by using a
coalescent approach. Proc Nat Acad Sci 2001, 98:4563-4568.
66. Beerli P: How to use Migrate or why are Markov chain Monte Carlo
programs difficult to use? In Population Genetics for Animal Conservation.
Edited by: Bertorelle G, Bruford MW, Hauffe HC, Rizzoli A, Vernesi C.
Cambridge: Cambridge University Press; 2009:42-79.
67. Bowen BW, Bass AL, Rocha LA, Grant WS, Robertson DR: Phylogeography
of the trumpetfish (Aulostomus spp.): ring species complex on a global
scale. Evolution 2001, 55:1029-1039.
Gaither et al. BMC Evolutionary Biology 2011, 11:189
http://www.biomedcentral.com/1471-2148/11/189
68. Lessios HA: The great American schism: divergence of marine organisms
after the rise of the Central American Isthmus. Ann Rev Evo Evol Sys 2008,
39:63-91.
69. Reece JS, Bowen BW, Joshi K, Goz V, Larson AF: Phylogeography of two
moray eels indicates high dispersal throughout the Indo-Pacific. J Hered
2010, 101:391-402.
70. Hays JD, Imbrie J, Shackleton NJ: Variations in the Earth’s Orbit:
Pacemaker of the Ice Ages. Science 1976, 194:1121-1132.
71. Fleminger A: The Pleistocene equatorial barrier between the Indian and
Pacific Oceans and a likely cause for Wallace’s line. UNESCO Technical
Papers in Marine Science 1986, 49:84-97.
72. Chappell J: Relative and average sea level changes, and endo-, epi-, and
exogenic processes on the earth. Sea level, ice, and climatic change Int Ass
Hydrol Sci Publ 1981, 131:411-430.
73. Potts DC: Evolutionary disequilibrium among Indo-Pacific corals. Bull Mar
Sci 1983, 33:619-632.
74. Naish T, et al: Obliquity-paced Pliocene West Atlantic ice sheet
oscillations. Nature 2009, 458:322-328.
75. Tjia HD: Java Sea. In The Encyclopedia of Oceanography. Edited by:
Fairbridge RW. New York: Reinhold; 1966:424-429.
76. Van Andel TH, Heath GR, Moore TC, McGeary DFR: Late Quaternary history,
climate, and oceanography of the Timor Sea, northwestern Australia. Am
J Sci 1967, 265:737-758.
77. Galloway RW, Kemp EM: Late Cenozoic environments in Australia. In
Ecological Biogeography of Australia. Edited by: Keast A. Junk: The Hague;
1981:51-80.
78. McMillan WO, Palumbi SR: Concordant evolutionary patterns among
Indo-West Pacific butterflyfishes. Proc Roy Soc B 1995, 260:229-236.
79. Briggs JC: Extinction and replacement in the Indo-West Pacific Ocean. J
Biogeogr 1999, 26:777-783.
80. Lacson JM, Clark S: Genetic divergence of Maldivian and Micronesian
demes of the damselfishes Stegastes nigricans, Chrysiptera biocellata, C.
glauca and C. leucopoma (Pomacentridae). Mar Biol 1995, 121:585-590.
81. Planes S, Fauvelot C: Isolation by distance and vicariance drive genetic
structure of a coral reef fish in the Pacific Ocean. Evolution 2002,
56:378-399.
82. Bay LK, Choat JH, van Herwerden L, Robertson DR: High genetic diversities
and complex genetic structure in an Indo-Pacific tropical reef fish
(Chlorurus sordidus): evidence of an unstable evolutionary past? Mar Biol
2004, 144:757-767.
83. Menezes MR, Ikeda M, Taniguchi N: Genetic variation in skipjack tuna
Katsuwonus pelamis (L.) using PCR-RFLP analysis of the mitochondrial
DNA D-loop region. J Fish Biol 2006, 68:156-161.
84. Craig MT, Eble JA, Robertson DR, Bowen BW: High genetic connectivity
across the Indian and Pacific Oceans in the reef fish Myripristis berndti
(Holocentridae). Mar Ecol Prog Ser 2007, 334:245-254.
85. Leray M, Beldade R, Holbrook SJ, Schmitt RJ, Planes S, Bernardi G: Allopatric
divergence and speciation in coral reef fish: the three-spot Dascyllus,
Dascyllus Trimaculatus, species complex. Evolution 2010, 64-5:1218-1230.
86. Eble JA, Rocha LA, Craig MT, Bowen BW: Not all larvae stay close to
home: Long-distance dispersal in Indo-Pacific reef fishes, with a focus
on the Brown Surgeonfish (Acanthurus nigrofuscus). J Mar Bio 2011.
87. Winters KL, van Herwerden L, Choat HJ, Robertson DR: Phylogeography of
the Indo-Pacific parrotfish Scarus psittacus: isolation generates distinctive
peripheral populations in two oceans. Mar Biol 2010, 157:1679-1691.
88. Fitzpatrick JM, Carlon DB, Lippe C, Robertson DR: The west Pacific hotspot
as a source or sink for new species? Population genetic insights from
the Indo-Pacific parrotfish Scarus rubroviolaceus. Mol Ecol 2011,
20:219-234.
89. Lavery S, Moritz C, Fielder DR: Changing patterns of population structure
and gene flow at different spatial scales in Birgus latro (the coconut
crab). Heredity 1995, 74:531-541.
90. Lavery S, Mortiz C, Fielder DR: Indo-Pacific population structure and
evolutionary history of the coconut crab Birgus latro. Mol Ecol 1996,
5:557-570.
91. Williams ST, Benzie JAH: Evidence of a biogeographic break between
populations of a high dispersal starfish: congruent regions within the
Indo-West Pacific defined by color morphs, mtDNA, and allozyme data.
Evolution 1998, 52:87-99.
Page 15 of 15
92. Benzie JAH: Major genetic differences between crown-of-thorns starfish
(Acanthaster planci) populations in the Indian and Pacific Oceans.
Evolution 1999, 53:1782-1795.
93. Duda TF, Palumbi SR: Population structure of the black tiger prawn,
Penaeus monodon, among western Indian Ocean and western Pacific
populations. Mar Biol 1999, 134:705-710.
94. Barber PH, Palumbi SR, Erdmann MV, Moosa MK: A marine Wallace’s line?
Nature 2000, 406:692-693.
95. Lessios HA, Kessing BD, Pearse JS: Population structure and speciation in
tropical seas: global phylogeography of the sea urchin Diadema.
Evolution 2001, 55:955-975.
96. Lessios HA, Kane J, Robertson DR: Phylogeography of the pantropical sea
urchin Tripneustes: Contrasting patterns of population structure between
oceans. Evolution 2003, 57:2026-2036.
97. Horne JB, van Herwerden L, Choat HJ, Robertson DR: High population
connectivity across the Indo-Pacific: congruent lack of phylogeographic
structure in three reef fish congeners. Mol Phylogenet Evol 2008,
49:629-638.
98. Gaither MR, Toonen RJ, Robertson DR, Planes S, Bowen BW: Genetic
evaluation of marine biogeographic barriers: perspectives from two
widespread Indo-Pacific snappers (Lutjanus spp.). J Biogeogr 2010,
37:133-147.
99. Klanten OS, Choat JH, Van Herwerden L: Extreme genetic diversity and
temporal rather than spatial partitioning in a widely distributed coral
reef fish. Mar Biol 2007, 150:659-670.
100. Miller MP, Bellinger RM, Forsman ED, Haig SM: Effects of historical climate
change, habitat connectivity and vicariance on the genetic structure
and diversity across the range of the red tree vole (Phenacomys
longicaudus). Mol Ecol 2006, 15:145-159.
101. Mora MS, Lessa EP, Cutrera AP, Kitttlein MJ, Vasallo AI: Phylogeographical
structure in the subterranean tuco-tuco Ctenomys talarum (Rodentia:
Ctenomyidea): constrasting the demographic consequences of regional
and habitat specific histories. Mol Ecol 2007, 16:3453-3465.
102. Donaldson TJ: Distribution and species richness patterns of Indo-West
Pacific Cirrhitidae: support for Woodland’s hypothesis. In Proceedings of
the Second International Conference on Indo-Pacific fishes. Edited by: Uyeno
T, Arai R, Taniuchi T, Matsuura K. Tokyo: Ichthyological Society of Japan;
1986:623-628, 1986; Tokyo.
103. Hobbs JPA, Frisch AJ, Allen GR, van Herwerden L: Marine hybrid hotspot
at Indo-Pacific biogeographic border. Biology Letters 2009, 5:258-261.
104. Marie AD, van Herwerden L, Choat JH: Hybridization of reef fishes at the
Indo-Pacific biogeographic barrier: a case study. Coral Reefs 2007,
26:841-850.
105. Craig MT: The goldrim surgeonfish (Acanthurus nigricans; Acanthuridae)
from Diego Garcia, Chagos Archipelago: first record for the central
Indian Ocean. Zootaxa 2008, 1850:65-68.
106. Crandall ED, Frey MA, Grosberg RK, Barber PH: Contrasting demographic
history and phylogeographical patterns in two Indo-Pacific gastropods.
Mol Ecol 2008, 17:611-626.
107. Schultz JK, Feldheim KA, Gruber SH, Ashley MV, McGovern TM, Bowen BW:
Global phylogeography and seascape genetics of the lemon sharks
(genus Negaprion). Mol Ecol 2008, 17:5336-5348.
108. Allen GR, Smith-Vaniz WF: Fishes of the Cocos (Keeling) Islands. Atoll Res
Bull 1994, 412:1-21.
109. Winterbottom R, Anderson RC: A revised checklist of the epipelagic and
shore fishes of the Chagos Archipelago, Central Indian Ocean. JLB Smith
Institute of Ichthyology Ichthyological Bulletin; 1997:66:1-28.
110. Briggs JC, Bowen BW: A realignment of marine biogeographic provinces
with particular reference to fish distributions. J Biogeogr 2011.
doi:10.1186/1471-2148-11-189
Cite this article as: Gaither et al.: Phylogeography of the reef fish
Cephalopholis argus (Epinephelidae) indicates Pleistocene isolation
across the indo-pacific barrier with contemporary overlap in the coral
triangle. BMC Evolutionary Biology 2011 11:189.