Bull Mar Sci. 90(1):493–512. 2014
http://dx.doi.org/10.5343/bms.2013.1032
research paper
Phylogeography of the manybar goatfish, Parupeneus
multifasciatus, reveals isolation of the Hawaiian Archipelago
and a cryptic species in the Marquesas Islands
1
Hawai‘i Institute of Marine
Biology, University of Hawai‘i,
Kaneohe, Hawaii 96744.
2
Department of Biology,
University of Hawai‘i, Honolulu,
Hawaii 96822.
Department of Marine Science
and Environmental Studies,
University of San Diego, San
Diego, California 92110.
Zoltán Szabó 1 *
Brent Snelgrove 2
Matthew T Craig 3
Luiz A Rocha 4
Brian W Bowen 1
3
4
Section of Ichthyology,
California Academy of Sciences,
55 Music Concourse Dr, San
Francisco, California 94118.
Corresponding author email:
<[email protected]>.
*
Date Submitted: 4 April, 2013.
Date Accepted: 5 December, 2013.
Available Online: 10 January, 2014.
Abstract.—To assess genetic connectivity in a common
and abundant goatfish (family Mullidae), we surveyed
637 specimens of Parupeneus multifasciatus (Quoy and
Gaimard, 1825) from 15 locations in the Hawaiian Islands
plus Johnston Atoll, two locations in the Line Islands, two
locations in French Polynesia, and two locations in the
northwestern Pacific. Based on mitochondrial cytochrome
b sequences, we found no evidence of population structure
across Hawaii and the North Pacific; however, we observed
genetic structuring between northern and southern Pacific
locations with the equator-straddling Line Islands affiliated
with the southern population. The Marquesas Islands
sample in the South Pacific was highly divergent (d = 4.12%
average sequence divergence from individuals from all
other locations) indicating a cryptic species. These findings
demonstrate that this goatfish is capable of extensive
dispersal consistent with early life history traits in Mullidae,
and provide further evidence for the biogeographic isolation
of the Marquesas Islands.
With more than 60 species in six genera, goatfishes (family Mullidae) represent a
major component of reef ecosystem assemblages (Uiblein 2007). Their benthic foraging behavior is facilitated by chemosensory barbels that invoke their common name.
This excavation of soft sediments can shape benthic community structure and attract other fishes to the feeding foray, and thus goatfishes are regarded as community builders and keystone species in benthic feeding assemblages (Johnson and Gill
1998, Uiblein 2007). In addition to the chemosensory barbels, goatfishes have other
unusual adaptations, including the ability to change coloration rapidly, mimic the
coloration of other species in mixed-species schools (Randall and Guézé 1980), and
survive in a pelagic environment long after transforming from larval to juvenile stage
(Lo-Yat et al. 2006). Goatfishes are also economically important species, caught in
artisanal fisheries throughout the tropical and subtropical oceans.
The manybar goatfish, Parupeneus multifasciatus (Quoy and Gaimard, 1825), is
probably the most common Indo-Pacific member of the family Mullidae (Friedlander
Bulletin of Marine Science
© 2014 Rosenstiel School of Marine & Atmospheric Science of
the University of Miami
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et al. 2007, ZS pers obs). It occurs inshore around coral reefs and adjacent habitats of
the Pacific and can be found to at least 161 m depth (Randall 2007). While specific
life history data on the manybar goatfish indicate a pelagic larval duration of 24–28
d in captivity and a short generation time (Pavlov et al. 2011, 2012, 2013), other members of this family have a relatively long larval stage of about 50 d (Robertson et al.
2004) followed by a pelagic juvenile stage that eventually settles on reefs at lengths of
5–10 cm (Lo-Yat et al. 2006). These pelagic juveniles have been recovered over 1000
km from the nearest shallow water habitat (Clarke 1995), and this trait is likely to
translate into high connectivity in population genetic assays (Craig et al. 2007, Horne
et al. 2008, Reece et al. 2011), an expectation we hold for P. multifasciatus.
Manybar goatfish are distributed throughout the Pacific Ocean, from the
Northwestern Hawaiian Islands to the Marquesas in the central Pacific, east of
Pitcairn Islands through the islands of Oceania to northwestern Australia and
Christmas and Cocos-Keeling Islands in the Indian Ocean, north to Southern Japan,
and south to New South Wales, Lord Howe, Norfolk, and Rapa Islands (Randall 2005,
and http://www.iucnredlist.org). A similar distribution is common among many
demersal fish species (Woodland 1983, Briggs 1999) and encompasses three recognized biogeographic provinces. Based on high levels of endemism, the Hawaiian
Archipelago in the North Pacific (25% endemism, Randall 2007) and the Marquesas
Archipelago in the South Pacific (12% endemism, Randall and Earle 2000) represent independent provinces. The remainder of the range encompasses the vast IndoPolynesian province (Briggs and Bowen 2012) from the eastern Indian Ocean to the
central Pacific. This area spans about half the planet, and biogeographic cohesiveness
is likely maintained by the relatively small distances among island and coastal habitats. As noted by Schultz et al. (2008), dispersive propagules never have to travel >800
km to reach adjacent habitat across this region. To the east of this region, the range
of the manybar goatfish is presumably constrained by the East Pacific Barrier (EPB),
the 5000 km gap in shallow habitat between the central Pacific and the Americas.
In recent phylogeographic appraisals of Pacific reef fishes, genetic partitions tend
to be concordant with the biogeographic provinces noted above (Gaither et al. 2010,
2011, Leray et al. 2010, DiBattista et al. 2011, Eble et al. 2011a). Hence our initial
expectations are genetic breaks distinguishing the Marquesas and Hawaii from the
rest of the Pacific range.
The present study is also part of a multi-species initiative to explore genetic connectivity of reef organisms within the Hawaiian Archipelago (reviewed in Toonen
et al. 2011). In particular, the 1600 km expanse of the uninhabited Northwestern
Hawaiian Islands (NWHI) was designated as the Papahānaumokuākea Marine
National Monument (PMNM, Fig. 1) in 2006, and intensive research efforts were
initiated to examine its efficacy in preserving biodiversity and replenishing exploited
fish stocks in the densely populated Main Hawaiian Islands (MHI). While very limited artesian bottom fishing existed before the PMNM, public access and fishing was
further reduced at the formation of the PMNM. In contrast, the MHI have a current
population of approximately 1.4 million people and are heavily fished by local anglers
and spearfishers, impacted by sports and tour operators, beach use, land erosion, and
development.
Here, we focus on the manybar goatfish to address the following questions: (1) Is
there genetic partitioning within the range of the species? (2) Is there population
genetic structuring within the Hawaiian Archipelago (e.g., NWHI vs MHI)? (3) If so,
Szabó et al.: Phylogeography of the manybar goatfish
495
Figure 1. Map of manybar goatfish, Parupeneus multifasciatus, collection sites with number of
samples at each site. Species distribution range is indicated in blue shading. On the large-scale
map, the Hawaiian Archipelago is represented only by its northernmost and southernmost islands, Kure and Hawaii, respectively. Inset details collections within the Hawaiian Archipelago.
Photo credit: J Williams.
what is the present rate and direction of gene flow among populations? and (4) What
are the management implications?
Materials and Methods
Sample Collections
Between 2005 and 2010, 637 specimens of P. multifasciatus were collected with
pole spears while scuba diving or snorkeling at 22 locations across the Pacific Ocean:
15 sites in the Hawaiian Archipelago (MHI: The islands of Hawaii, Oahu, Kauai and
Niihau; Kaula Rock; NWHI: Nihoa Island, Necker Island, French Frigate Shoals,
Gardner Pinnacles, Maro Reef, Laysan Island, Lisianski Island, Pearl and Hermes
Atoll, Midway Atoll, Kure Atoll), Johnston Atoll, Palmyra and Kiritimati in the Line
Islands, Palau and Okinawa in the northwest Pacific, and Moorea and Nuku Hiva
(Marquesas Islands) in French Polynesia (Fig. 1, first column of Table 1). The uninhabited Ka‘ula Rock was grouped with the NWHI for the purpose of our study. Tissue
samples were stored in a saturated salt-DMSO buffer (Amos and Hoelzel 1991) or in
70% ethanol at room temperature until DNA extraction. Specimens collected from
the NWHI were obtained on the NOAA Ship Hi’ialakai as part of an initiative to
document and monitor resources in the PMNM.
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Table 1. Collection sites, sample sizes (n), number of haplotypes (HN) and unique haplotypes (HU) observed in a single
individual, molecular diversity indices, and estimated age of the analyzed Parupeneus multifasciatus populations.
Time since most recent population collapse was calculated from mismatch distributions assuming 1% nucleotide
sequence divergence / MY within lineages. Significant (P < 0.02) Fu’s FS values are in bold.
Haplotype
Allelic
Percent nucleotide
diversity, h (SD) richness [r(9)] diversity, π (SD) Fu’s FS Age (yrs)
0.808 (0.046)
3.806
0.22 (0.16)
−2.87 116,343
0.868 (0.032)
4.856
0.28 (0.18)
−10.75 146,197
Location
Kure Atoll
n HN
29
8
Midway
45
16
5
Pearl and Hermes
37
8
1
0.764 (0.047)
3.352
0.21 (0.15)
Lisianski
28
12
3
0.884 (0.036)
4.996
0.28 (0.19)
Laysan
52
14
4
0.812 (0.035)
4.062
0.23 (0.16)
Maro Reef
30
13
2
0.899 (0.031)
5.281
0.30 (0.20)
Gardner Pinnacles
12
6
1
0.682 (0.148)
3.750
0.21 (0.16)
French Frigate Shoals
31
13
5
0.785 (0.071)
4.327
0.26 (0.18)
Necker
25
10
1
0.837 (0.056)
4.467
0.25 (0.17)
Nihoa
29
11
5
0.823 (0.050)
4.220
0.28 (0.18)
Kaula Rock
19
9
3
0.813 (0.081)
4.455
0.25 (0.18)
Niihau
30
8
0
0.777 (0.063)
3.773
0.23 (0.16)
Kauai
30
9
2
0.770 (0.063)
3.706
0.26 (0.17)
Oahu
28
12
3
0.823 (0.062)
4.545
0.29 (0.19)
Island of Hawaii
28
10
2
0.788 (0.067)
4.060
0.25 (0.17)
Johnston Atoll
20
6
1
0.816 (0.051)
3.702
0.21 (0.15)
9
3
0
0.556 (0.165)
2.000
0.10 (0.10)
Palmyra
28
9
4
0.587 (0.107)
2.954
0.15 (0.12)
Kiritimati
58
17
9
0.712 (0.061)
3.649
0.17 (0.13)
Moorea
38
13
5
0.753 (0.066)
3.874
0.20 (0.14)
Okinawa
13
8
2
0.885 (0.070)
5.138
0.25 (0.18)
18
2
2
0.366 (0.112)
0.959
0.06 (0.07)
−4.74
0.80
131,149
Nuku Hiva (Marquesas)
637
99
59
0.842 (0.009)
0.53 (0.30)
−24.53
133,819
Palau
Total
HU
3
−2.54
117,880
−6.93
147,249
−7.68
161,974
−8.51
160,356
−8.48
−2.67
−5.18
−5.45
118,851
88,188
129,126
139,887
−4.70
138,269
−3.26
136,570
−4.87
123,058
−2.67
−6.63
−1.59
−0.53
113,269
95,793
113,107
63,673
−6.15
80,421
−9.70
100,485
−16.40
91,990
40,615
DNA Extraction, PCR, and Sequencing
Total genomic DNA was extracted from 2 to 6 mm2 of pectoral fin clips in 50
μl volume using the HotSHOT protocol (Meeker et al. 2007) with the modification
of using a pH 7.5 TRIS-HCl buffer (1M) for the neutralization step. A segment of
the mitochondrial cytochrome b gene (mt-cyb) was amplified with primers Cyb9/
L14725 (5΄–GTGACTTGAAAAACCACCGTTG–3΄) and Cyb7/H15573 (5΄–
AATAGGAAGTATCATTCGGGTTTGATG–3΄) (Meyer 1993). Polymerase chain
reaction (PCR) mixes were prepared following the manufacturer’s instructions using
MangoMix (Bioline USA, Inc., Taunton, MA), containing 0.2 μM of each primer, 1 µl
of 1:50 dilution of template DNA in 15 μl total volume. In a few cases, lower dilution
(1:10 or undiluted) DNA stocks were used to achieve successful amplification. PCRs
were performed in an ABI 2720 thermocycler (Applied Biosystems, Inc., Foster City
CA, USA) as follows: initial denaturation at 95 °C for 3 min followed by 35 cycles of
denaturing at 95 °C for 30 s, annealing at 50 °C for 45 s, and extension at 72 °C for 45
s, followed by a final extension at 72˚C for 5 min. PCR products were visualized on
1% agarose gels stained with GelStar (Lonza AG, Basel, Switzerland ) under UV light.
PCR products were cleaned of excess oligonucleotides and unincorporated primers
by incubating with exonuclease I and FastAP alkaline phosphatase (Fermentas, Glen
Burnie, MD, USA) at 37˚C for 60 min, followed by deactivation at 85˚C for 15 min.
Szabó et al.: Phylogeography of the manybar goatfish
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All DNA fragments were sequenced in the forward direction (and reverse direction
for rare or questionable haplotypes, those with ambiguous base reads) with fluorescently labeled dye terminators following manufacturer’s protocols (BigDye, Applied
Biosystems, Inc., Foster City, CA) and analyzed on an ABI 3130XL Genetic Analyzer
(Applied Biosystems) at the Hawai‘i Institute of Marine Biology EPSCoR Sequencing
Facility. The sequences were aligned, edited, and trimmed to a common length of
618 bp using Sequencher 4.9 DNA analysis software (GeneCodes Corporation, Ann
Arbor, MI). Variable sites were visually checked to ensure accuracy, and unique mtcyb haplotypes were deposited in GenBank (Pmu 1–Pmu 99, accession numbers
JN006869–JN006963 and KF425538–KF425539). The full data set is also available
from GenBank as a popset file (KF439062–KF439698).
Data Analysis
mtDNA Haplotype Network.—Evolutionary connections were estimated with
an unrooted parsimony-based network of mtDNA haplotypes using Network 4.6
(http://www.fluxus-engineering.com). The data were first processed through the MJ
(median-joining) algorithm (Bandelt et al. 1999) followed by the maximum parsimony
(MP) option (Polzin and Daneschmand 2003). The default calculation weights for
variable nucleotide positions were changed to 15, which allowed for lowering the
weights for two highly variable nucleotide positions of #46 and #247 (5΄ à 3΄, refer
to submitted GeneBank haplotype for numbering of nucleotide positions) to 10
and 5, respectively, to further reduce “superfluous” links, as suggested by the user
manual. The initial network was drawn with Network Publisher 1.3.0.0 (http://www.
fluxus-engineering.com/), and was further simplified by hand to eliminate multiple
connections. Connections were deemed superfluous only if they were between low
frequency haplotypes and there was an alternate connection to another haplotype of
10-fold higher frequency. Also, loops via internal nodes (where haplotypes were not
present) were eliminated if there was an alternative direct connection.
Molecular Diversity.—Arlequin 3.5 (Excoffier et al. 2005) was used to calculate
summary statistics including haplotype diversity (h, equation 8.5 in Nei 1987) and
nucleotide diversity (π, equation 10.19 in Nei 1987) for each collection site, as well
as to test for genetic structure on several geographic scales: (1) within the Hawaiian
archipelago, (2) between Hawaii and all other Pacific islands without Marquesas,
and (3) between Marquesas and all other collections sites. Haplotype diversities were
rarefied to nine individuals using the program Contrib 1.2 (Petit et al. 1998) to account for increasing haplotype diversity with larger sample sizes. To assess whether
haplotype diversities differed significantly between groups, we ran Mann-Whitney
(Hawaiian archipelago vs all other Pacific locations) and Kruskal-Wallis (MHI vs
NWHI vs all other locations) tests on the rarefactioned allele richness values from
Table 1 using VassarStats (available from http://www.vassarstats.net/index.html, accessed 14 July, 2013).
Population Structure.—We tested for population structure and phylogeographic
patterns with three independent analyses in a hierarchical manner. First, population pairwise ΦST statistics were generated in Arlequin to identify genetic partitioning with the mutational model of Tamura and Nei (1993), the closest match to the
TrN+I+G model that was chosen by jModelTest 0.1.1 (Guindon and Gascuel 2003,
Posada 2008) using the Akaike information criteria. jModelTest also indicated that
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the best-fit model of DNA sequence evolution had a γ = 0.324 that was used throughout all analyses in Arlequin. Significance was tested by permutation and P values
adjusted (corrected α = 0.008) according to the modified false discovery rate method
(Benjamini and Yekutieli 2001, Narum 2006).
Second, an analysis of molecular variance (AMOVA, Excoffier et al. 1992) was performed to assess population structure between regions, among populations within
regions, and between all populations in several scenarios or groupings. These groupings were primarily guided by the significant ΦST values (Table 2), but also included
scenarios where geographical distance was a consideration. Nonparametric permutation procedures (n = 20,000 iterations) were used to construct null distributions
and test the significance of variance components for each hierarchical comparison.
Third, a spatial analysis of molecular variance (SAMOVA 1.0, Dupanloup et al.
2002) was conducted to evaluate patterns emerging from pairwise ΦST values and
AMOVA. SAMOVA utilizes a simulated annealing procedure (n = 100 permutations)
within an AMOVA framework and removes a priori group identity bias by randomly
partitioning mtDNA sequences into “K” groups. We tested K = 2 to K = 14, and
the configuration with the largest among group differentiation (ΦCT) was retained.
Specimens from Marquesas were excluded from the SAMOVA analyses because the
haplotype network indicated an ancient divergence of the Marquesan population
from the rest of the range.
Mantel tests were carried out with 10,000 iterations in Arlequin to assess whether
significant correlations existed between population differentiation (calculated ΦST
values) and geographical distance (isolation by distance, IBD). Negative ΦST values
were converted to zeros after it was confirmed in pilot runs that doing so did not
change outcomes.
Test of Neutrality and Selection.—Deviations from neutrality and possible signatures of population expansion were assessed with Fu’s FS (Fu 1997) and by comparing
observed and expected pairwise mismatch distributions using Arlequin; significance
was tested using 99,999 permutations. As neutrality tests are sensitive to deviations
from panmixia, we estimated these statistics both on the full data set, and independently within each region identified as genetically distinct by SAMOVA (i.e., all
Hawaiian Islands including Johnston Atoll vs all other Pacific islands). Specimens
collected from Johnston Atoll were geographically grouped with the Hawaiian samples given the proximity (1400 km) and assignment to the same biogeographic province (Hourigan and Reese 1987, Briggs and Bowen 2012). FS values were regarded
as significant at P < 0.02 per Arlequin user manual. Significant negative FS values
indicate an abundance of rare haplotypes in non-recombining sequences such as
mtDNA, a signature of either population expansion or selection.
Population Coalescent Time Estimates.—Mismatch distributions were fitted with
the population parameter τ to estimate coalescent time (time to most recent population expansion). We estimated population age using the equation τ = 2ut (Rogers
and Harpending 1992, Harpending 1994), where t is age in generations and u is the
mutation rate per generation for the 618 bp fragment. We used a chronological mutation rate of u = 1% per My within lineages (as calibrated for other reef fishes; Bowen
et al. 2001, Reece et al. 2010) to estimate coalescent times. A first order estimate
of generation time, 2.2 yrs, is based on life history data (Pavlov et al. 2013) and the
von Bertalanffy growth function (von Bertalanffy 1938) using the life-history tool
Szabó et al.: Phylogeography of the manybar goatfish
499
at http://www.fishbase.us/summary/Parupeneus-multifasciatus.html (accessed 29
October, 2012. Linf = 22.1 and K = 0.47, kindly provided by D Pavlov, Moscow State
University).
Migration.—Bayesian coalescent-based calculations of time-averaged migration
rates (Nem: where Ne is effective population size and m is migration rate) and direction
among groups were assessed with Migrate 3.3.2 (Beerli 2009) on a multilevel scale: (A)
between the MHI and the NWHI in the Hawaiian Archipelago (Online Supplement
S1-A), (B) between the populations of [Hawaii + Palau] vs [PKM + Okinawa] that
were identified by a SAMOVA (Online Supplement S1-B), and (C) a purely geographical model, where the western Pacific locations of Okinawa and Palau were separately tested (or the two grouped into a WEST population) vs MHI vs NWHI vs PKM
(Online Supplement S1-C). Specimens from Marquesas were excluded from the
Migrate analyses, because of the ancient divergence of the Marquesan population.
Settings were as follows: population subsampling option was set to match the sample
number of the smallest sample in any comparison. After several exploratory runs,
we chose Metropolis sampling for the proposal distributions of Θ and M and the
exponential window setting for the prior distributions. Slice sampling of priors was
used for the migration analysis of the two populations identified by SAMOVA (see
B above). Values for Θ prior were: Minimum = 0.00, Mean = 0.01, Maximum = 0.10,
Delta = 0.01, and Bins = 1500. Values for M prior were: Minimum = 0, Mean = 1000,
Maximum = 10000, Delta = 1000, Bins = 1500. We ran a total of 1,000,000 genealogies sampled at every 100 generations with a 20% burn-in; Metropolis-Hastings sampling of both Θ and M priors was used in A and C (above), slice sampling was used in
B. Static heating was turned on and four Markov chains were run with temperatures
1.0, 1.5, 3.0, and 1,000,000. Program defaults were used for all other settings. The
transition-to-transversion ratio was calculated using jModelTest 0.1.1 and was set
to 1.43:1. Each successful run was repeated a second time to ensure that posterior
distributions remained the same and were independent from the starting point of the
prior distributions. Peak values (i.e., mode) of the Θ and M posterior distributions
were used to calculate the number of migrants per generation (Nem = Θj × Mji, where
direction of migration is j à i). For Bayes factor calculations and model comparisons
(i.e., likelihood of reduced number of parameters), the log-probability of the data
given the model numbers [Prob(D|Model)], were used as instructed by the Migrate
tutorial (https://molevol.mbl.edu/wiki/index.php/Migrate_tutorial, and Beerli and
Palczewski 2010). Using NWHI and MHI as an example, the migration models were:
(1) two populations sizes and two migration rates, (2) two population sizes and one
migration rate to population 1 (MHI), (3) two population sizes and one migration
rate to population 2 (NWHI), and (4) the two population (NWHI and MHI) are panmictic. The log-probability number used for this calculation was obtained by using a
Bezier-curve and thermodynamic integration (Beerli and Palczewski 2010, provided
in the Migrate outfile).
Results
We resolved 618 bp of the mtDNA (mt-cyb) of 637 individuals sampled at 22 locations across the Pacific Ocean (Fig. 1, Table 1). Ninety-nine haplotypes were
resolved, among which 65 were detected in single individuals, and there were no
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Figure 2. Maximum parsimony network of 637 mt-cyb haplotypes from Parupeneus multifasciatus. Pie charts represent individual haplotypes and colors designate geographical locations.
The size of the pie charts is proportional to haplotype frequencies. Sticks indicate mutational
distance. Mutational differences larger than one nucleotide are indicated by cross bars on branches. Numbers within haplotypes indicate the number of individuals (with the given haplotype).
Empty circles with a cross represent predicted haplotypes that were not observed. The lack of
magenta colors in the first and fourth most common haplotypes labeled 172 and 37 is a strong
indication of haplotype frequency shifts between the Hawaiian Islands and Palmyra, Kiritimati,
and Moorea.
shared haplotypes between Marquesas and the remaining Pacific island populations
indicating complete genetic partitioning. We observed two haplotypes in 18 specimens at Marquesas, representing significantly lower allelic richness and nucleotide
diversity (one sample Wilcoxon signed-rank test: reff = 0.959, π = 0.006, P < 0.0001)
at this site. Allelic richness in Hawaii was significantly higher than other locations
in the Pacific (one-tailed Mann-Whitney: Ua = 21, Ub = 69, n1 = 15, n2 = 6, P < 0.05).
Haplotype Network
The most striking feature of the mt-cyb haplotype network (Fig. 2) is that Marquesas
specimens are 25 mutations away from their nearest relative. This translates to d =
4.12% corrected pairwise genetic difference (Tamura and Nei 1993) from the rest of
the population, well within the domain of species-level divergences in other fishes
(Johns and Avise 1998, DiBattista et al. 2011). The remaining 619 specimens could be
sorted into 97 closely related haplotypes. The star shape phylogeny of the rest of the
Szabó et al.: Phylogeography of the manybar goatfish
501
network indicates a shallow maternal genetic history, a common feature of marine
fishes (Grant and Bowen 1998). The abundance of low frequency haplotypes differing
by only one nucleotide from the four most frequent haplotypes (numbered 37, 98,
154, and 172) is consistent with recent population expansion. The central haplotype
(154) is ubiquitously present at all sampled locations (except the Marquesas).
Population Structure
Pairwise ΦST.—Significant and large pairwise ΦST values (Table 2) indicated three
distinct populations: Marquesas stood out from all other locations with ΦST > 0.96
(group 1); the Hawaiian Islands grouped together (group 2) and were separated from
the Line Islands and Society Islands (Palmyra, Kiritimati, and Moorea = PKM), although P values were non-significant in six out of 17 comparisons with group 2.
Okinawa also seemed to group with PKM (group 3). Palau (n = 9) was only significantly different from Marquesas, but had the smallest sample size.
Analysis of Molecular Variance.—Seven AMOVAs were run (Table 3) to test population groupings indicated by the pairwise ΦST table and geographical distance:
Hawaii, PKM (central-south Pacific), Okinawa, and Palau. The Marquesan population was dropped from the AMOVA comparisons, because the 4.1% divergence is
more appropriate for a phylogenetic analysis. The highest among groups (AG) variations were in the range of ΦCT = 0.132–0.136, and the strongest partitioning were
identical to that detected with the pairwise ΦST table: [Hawaii + Palau] vs [PKM +
Okinawa] or Hawaii vs [PKM + Okinawa + Palau] (ΦCT = 0.136, P < 0.001). Since the
Palau population did not differ significantly from any other population in this analysis, grouping with either Hawaii or [PKM + Okinawa] did not change the ΦCT values.
Breaking up the Hawaiian population into a NWHI and a MHI group resulted in a
37.5% drop of the among groups variation (ΦCT = 0.085 vs 0.136), thus such partitioning is not supported by genetic data.
This geographic partitioning was also consistent with the SAMOVA (Online
Supplement S2). Excluding Marquesas, K = 2 indicated the highest genetic partitioning, with the two maximally differentiated groups consisted of [PKM + Okinawa]
and [Hawaii + Palau] (ΦCT = 0.138, P < 0.0001). The second highest SAMOVA score
(ΦCT = 0.136), K = 3, consisted of PKM, Okinawa, and [Hawaii + Palau]. Comparisons
of Marquesas vs all other islands yielded ΦCT = 0.948 (P < 0.04). Tests for IBD (correlation between genetic and geographical distance) were run parallel with AMOVA
and were non-significant among populations (P = 0.09).
Historical Demography
The overwhelming majority of the haplotypes were present at low frequencies and
only one to two mutational steps away from the four major haplotypes in the haplotype network (Fig. 2), indicating recent population expansions. As expected, the
mismatch analysis of pairwise nucleotide differences for the total data set indicated
a unimodal distribution plus a small spike to indicate the two Marquesan haplotypes (Online Supplement S3; Harpending’s raggedness index: r = 0.078, P < 0.001).
Mismatch distributions were unimodal for all sample groups, and a non-significant
raggedness index (r) was detected only in the MHI (Table 4: MHI: r = 0.050, P =
0.453; NWHI: r = 0.072, P = 0.003; Hawaii + Palau: r = 0.067, P = 0.002; PKM +
Okinawa: r = 0.086, P = 0.027; Marquesas: r = 0.206, P = 0.417; all other: r = 0.087, P
< 0.001). When mismatch distribution was analyzed at the level of individual sample
−
−0.015
−0.022 −0.015
−0.028 −0.019 −0.021
−0.003
2. Midway
3. Pearl and Hermes
4. Lisianski
5. Laysan
3
4
−
0.942
0.964
0.989
0.044
7. Gardner Pinnacles
−
−0.020 −0.018 −0.019 −0.022
−0.024 −0.013 −0.018 −0.020 −0.002
−0.023 −0.012 −0.019 −0.020
−0.021 −0.016 −0.019 −0.020
0.960
−0.005
−0.033 −0.017 −0.022 −0.028 −0.021 −0.017
0.086
−0.002
0.028
0.147
0.149
0.140
0.125
12. Niihau
13. Kauai
14. Oahu
15. Island of Hawaii
16. Johnston Atoll
17. Palau
18. Palmyra
19. Kiritimati
20. Moorea
21. Okinawa
22. Nuku Hiva (Marquesas) 0.970
0.105
0.117
0.106
0.017
0.016
0.016
0.970
0.120
0.134
0.140
0.139
0.028
0.001
0.012
0.037
0.964
0.097
0.120
0.131
0.121
0.964
0.108
0.102
0.108
0.100
0.057
0.013
0.001
−
0.746
0.568
0.059
0.173
0.431
0.493
0.249
0.006
10
−
0.347
0.187
0.082
0.596
0.341
0.955
0.897
0.962
0.818
0.961
0.054
0.078
0.087
0.078
0.020 −0.018
−
0.577
0.928
0.843
0.485
0.244
0.413
0.771
0.696
0.640
12
−
0.714
0.147
0.411
0.933
0.376
0.070
0.147
0.328
0.212
0.147
0.406
13
−
0.425
0.943
0.789
0.759
0.722
0.238
0.288
0.329
0.895
0.877
0.712
0.936
14
15
−
0.978
0.297
0.310
0.342
0.357
0.192
0.965
0.201
0.221
0.238
0.230
0.079
0.968
0.174
0.187
0.206
0.203
0.053
0.964
0.081
0.117
0.124
0.118
0.026
0.970
0.150
0.168
0.191
0.187
0.040
0.969
0.210
0.219
0.234
0.230
0.073
0.966
0.132
0.157
0.171
0.166
0.045
0.962 0.968
0.112 0.183
0.145 0.219
0.160 0.233
0.151 0.229
0.038 0.083
0.059 −0.002 −0.004 −0.020 −0.022 −0.011 −0.021 −0.022 0.006
−
0.471
0.997 0.620
0.511 0.387
0.844 0.700
0.873 0.279
0.463 0.730
0.563 0.720
0.180 0.436
0.445 0.034
0.351 0.039
0.919 0.319
0.867 0.330
0.862 0.149
0.873 0.435
0.006 −0.018 −0.001 −0.012 −0.006
0.025 −0.009 −0.006 −0.019 −0.023 −0.007 −0.027
0.050 −0.007 −0.014 −0.015
0.008
11
0.829
0.017 −0.014 −0.016 −0.017 −0.028 −0.005
0.035 −0.002 −0.022 −0.002
0.001 −0.004
0.002
0.015
−
0.681
0.046
0.074
0.335
0.239
0.139
9
0.520
0.010 −0.010 −0.022 −0.027 −0.013
0.002 −0.010
0.013 −0.012
0.003
0.003
−
0.020
0.039
0.123
0.082
0.073
8
0.449
0.038 −0.015 −0.015
11. Kaʻula Rock
0.013
7
0.112
0.041 −0.022
0.099
10. Nihoa
0.007 −0.007 −0.004
0.025
0.070
−0.009
0.002
0.040
0.398
0.533
0.355
0.652
9. Necker
0.008
0.056
0.001 −0.007 −0.001
−
0.509
0.459
0.373
6
0.361
−0.004
0.016
5
0.459
8. French Frigate Shoals
0.053
0.001 −0.009
6. Maro Reef
0.000 −0.003 −0.005
−
0.921
0.937
1. Kure Atoll
2
0.837
1
−
Location
17
0.039
0.974
0.113
0.978
0.010
0.118 −0.002
0.127 −0.010
0.127
−
0.334
−
0.003
0.065
0.152
0.141
0.088
0.181
0.208
0.110
0.054
0.030
0.320
0.505
0.266
0.206
0.250
0.205
0.292
0.794
0.757
0.550
0.694
0.748
0.411
0.415
0.100
0.724
0.902
0.935
0.793
0.778
0.947
16
0.972
0.010
0.002
0.037
−
0.093
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.001
0.0*
0.0*
0.0*
0.0*
0.0*
18
0.971
0.009
0.030
−
0.091
0.860
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
19
21
22
0.009 0.0*
0.001 0.0*
0.007 0.0*
0.005 0.0*
0.0* 0.0*
0.004 0.0*
0.021 0.0*
0.001 0.0*
0.0* 0.0*
0.0* 0.0*
0.044 0.0*
0.003 0.0*
0.011 0.0*
0.007 0.0*
0.013 0.0*
0.008 0.0*
−
−
0.0*
0.037 0.0*
0.986 0.974
0.076
−
0.143 0.254 0.0*
0.283 0.236 0.0*
0.470 0.248 0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
0.0*
20
Table 2. Matrix of pairwise ΦST (below diagonal) and associated P values (above diagonal) based on 618 bp of cyt B sequence data from Parupeneus multifasciatus sampled at sites across the Pacific (n =
637). Significant (P < 0.0083) values are in gray background. For 0.0*, P is <0.001.
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503
Table 3. Analysis of molecular variance (AMOVA) for different population groupings. NWHI
= Northwestern Hawaiian Islands; MHI = Main Hawaiian Islands; PKM = Palmyra, Kiritimati,
Moorea. Significant F statistics are in bold (P < 0.05 unless otherwise noted, * P < 0.001). AG =
among groups, AP(G) = among populations within groups, WP = within populations.
Population groupings
Source of variation
NWHI, MHI, [Palau+PKM+Okinawa]
AG
AP(G)
WP
Hawaii, [Palau+PKM+Okinawa]
AG
AP(G)
WP
[Hawaii+Palau], [PKM+Okinawa]
AG
AP(G)
WP
[Hawaii+Palau+Okinawa], PKM.
AG
AP(G)
WP
[Hawaii+Palau], Okinawa, PKM
AG
AP(G)
WP
Hawaii, Palau, [PKM+Okinawa]
AG
AP(G)
WP
Hawaii, Palau, PKM, Okinawa
AG
AP(G)
WP
Variation (%)
8.48
−0.07
91.64
13.55
−0.05
86.50
13.55
−0.05
86.50
12.67
0.61
86.72
13.31
−0.07
86.76
13.42
−0.08
86.66
13.18
−0.09
86.91
Φ statistics
ΦCT = 0.085*
ΦSC = −0.001
ΦCT = 0.136*
ΦSC = −0.001
ΦCT = 0.136*
ΦSC = −0.001
ΦCT = 0.127*
ΦSC = 0.007
ΦCT = 0.133*
ΦSC = −0.001
ΦCT = 0.134*
ΦSC = −0.001
ΦCT = 0.132*
ΦSC = −0.001
locations, raggedness values were all non-significant (data not shown). Fu’s FS indicated an abundance of rare haplotypes (Tables 1, 4), which could be evidence for recent
demographic expansion of all populations identified by SAMOVA. Fu’s FS was significantly negative for 11 out of 16 locations in Hawaii (Fu’s FS = −10.17 to −1.59) and 4
out of 6 in the remaining Pacific samples (Table 1). For all the combined intraspecific
sample groups (NWHI, MHI, Hawaii, PKM + Okinawa, All combined; Table 4), Fu’s
FS was negative and ranged from −24.07 (n = 135) to −181.70 (n = 619). Coalescence
time estimates for individual sampling sites were in the range 80–162 ky (Table 1).
Older populations were indicated in the NWHI and MHI vs PKM, which was confirmed when samples were analyzed as metapopulations defined by SAMOVA (Table
4). Estimated ages are NWHI: 140,500, MHI: 137,000 and PKM + Okinawa: 95,800
yrs. The age difference between the NWHI and PKM + Okinawa was particularly notable, since sample sizes were almost identical: 135 and 137, respectively. The single
nucleotide difference between the two haplotypes recovered at Nuku Hiva does not
allow for a reliable estimation of a historical bottleneck in the Marquesan population
(0 < τ < 1.2; 0–100 ky). Using a divergence rate of 0.02/My between lineages and an
average corrected sequence divergence of d = 4.12%, we estimate the divergence of
the Marquesan population at about 2 My.
Contemporary Gene Flow
Although occasionally we were able to get converging values for a full geographical
migration model in which MHI, NWHI, WEST, and PKM were treated as separate
Population
Main Hawaiian Is.
95% CI
NW Hawaiian Is.
95% CI
“Hawaii”
95% CI
PKM+Okinawa
95% CI
Marquesas
95% CI
All other
95% CI
Overall
95% CI
637
619
18
137
482
318
n
135
τ
1.736
(0.69–2.70)
1.693
(1.44–2.09)
1.654
(1.41–2.05)
1.184
(0.82–1.65)
0.502
(0.00–1.20)
1.633
(1.42–2.02)
1.654
(1.44–2.05)
133,819
132,120
40,615
95,793
133,819
136,974
Age (1%)
140,453
66,909
66,060
20,307
47,896
66,909
68,487
Age (2%)
70,227
Theta0
0
(0.000–0.782)
0
(0.000–0.095)
0
(0.000–0.077)
0.002
(0.000–0.142)
0
(0.000–0.686)
0
(0.000–0.067)
0
(0.000–0.067)
Theta1
20.611
(2.81–99999)
∞
(12.91–99999)
∞
(16.80–99999)
∞
(4.25–99999)
∞
(9.25–99999)
∞
(21.15–99999)
∞
(21.89–99999)
0.078
0.087
0.206
0.086
0.067
0.072
0.000
0.000
0.417
0.027
0.002
0.003
Harpending raggedness
r
P
0.050
0.453
0.007
0.008
0.005
0.005
0.006
0.008
0.002
0.000
0.382
0.102
0.004
0.003
Model (SSD)
SSD
P
0.007
0.153
−181.70*
0.80+
−44.84*
−109.16*
−74.09*
FS
−24.07*
Table 4. Estimates (95% CI) of manybar goatfish historical demography for SAMOVA populations. τ: population age parameter, age: coalescent time (population
age) estimate for within lineage mutation rate of 1% and 2% per million years. Theta0 and Theta1 are population size parameter estimates at time of coalescence
and present, respectively. Harpending’s raggedness (r) and Fu’s F­S tests for population expansion or selective neutrality, SSD tests for deviations from the sudden
expansion model of mt-cyb mismatches. CI = confidence interval; PKM = Palmyra, Kiritimati, Moorea; “Hawaii” = MHI + NWHI + Palau. * P < 0.001, + P <
0.391.
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505
populations (Online Supplement S1-C), they were not reliably reproducible, thus
we were not able to conclusively test hypotheses about dispersal. We had the same
outcome for migration models where Okinawa and Palau were treated separately
from Hawaii and PKM. A four-parameter migration analysis between the NWHI
and MHI indicated a migration predominantly in the MHI direction. Based on five
replicate runs, the mean number of migrants per generation was 85 to the MHI and
1.3 to the NWHI. With static heating turned on, we were able to evaluate four possible migration models: (1) two populations sizes and two migration rates, (2) two
populations sizes, one migration rate to MHI, (3) two population sizes one migration
rate to NWHI, (4) panmixia within Hawaii. Bayes factor calculations indicated a
statistically significant (98.9%) probability for the single migration rate model toward
the NWHI (Online Supplement S1-A). Between the SAMOVA-defined two populations, Hawaii vs [PKM + Okinawa + Palau], a full four-parameter model indicated
migration from the central and South Pacific toward the Hawaiian Islands: 8.1 migrants/generation (Nem) into Hawaii vs 0.016 from Hawaii. Bayes factor calculations
(Online Supplement S1-B), however, were only slightly in favor of a single migration rate model toward Hawaii with a 60% probability vs single rate migration out of
Hawaii at 30% probability vs full migration model of 10% probability. We consider
this latter result as not robust enough to exclude a two-directional four-parameter
migration model between Hawaii vs [PKM + Okinawa + Palau].
Discussion
In our phylogeographic analysis of P. multifasciatus, we identified a monophyletic
lineage in the Marquesas Islands (Fig. 2) and detected a significant genetic partition
between the Hawaiian Archipelago and our sample locations in the southern and
western Pacific (Tables 2, 3). Our migration analysis, while yielding contradictory results, indicates a rate of about eight migrants per generation into Hawaii, low but possibly sufficient to prevent evolutionary separations. AMOVA results (Table 3) show
no significant barriers to gene flow within the Hawaiian Archipelago. Coalescence
analysis of expanding populations indicates a genetic bottleneck ca 140 ka in the
main Hawaiian Islands and Okinawa and a very recent one in the Marquesas. The
timing of the Hawaiian and Okinawan bottleneck coincides approximately with a
Pleistocene (Illinoian era) sea level minimum of 120 m below current sea level (http://
www.ncdc.noaa.gov/paleo/ctl/clisci100k.html#sea, Voris 2000).
Prior to dissecting these results, we address two caveats. First, we note that this is
a single locus study with the inherent limitations that entails, especially in regards
to estimating migration with Bayesian coalescent-based calculations (Beerli 2009).
Selective sweeps or sex-biased dispersal could alter our conclusions; however, the
former is very rare (Karl et al. 2012) and the latter is unknown in fishes with larval
dispersal. Nonetheless, discrepancies between mtDNA and nuclear DNA data sets
are documented in marine fishes for reasons that have yet to be adequately explained
(DiBattista et al. 2012). Second, the finding of a divergent evolutionary lineage in the
Marquesas is not an artifact of species misidentification. Our research team collected and identified these specimens, which were readily distinguishable from the five
other goatfish species in the Marquesas. Vouchered specimens from the Marquesas
clearly fit the key for P. multifasciatus. Finally, our (unpublished) morphological
comparisons between P. multifasciatus from the Marquesas and elsewhere in the
range indicate very high similarity.
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Bulletin of Marine Science. Vol 90, No 1. 2014
Endemism in the Marquesas and Routes of Colonization
Our survey of P. multifasciatus indicates an ancient separation of the Marquesas
population and a cryptic species. The observed cytochrome b divergence of d = 4.12%
is comparable to other congeneric species pairs of fish species (Johns and Avise 1998,
Rocha et al. 2008, DiBattista et al. 2011), but nuclear DNA data and morphological
examinations would be desirable to evaluate this taxonomic issue. We compared external morphology in a limited number of specimens in the collection of the Bishop
Museum and no obvious differences were detected between the Marquesan individuals and specimens from elsewhere in the range of P. multifasciatus.
The Marquesas is one of the most isolated archipelagos in the Indo-Pacific region
with 11.6% endemism in fish species (Randall and Earle 2000), the third highest behind Hawaii (25%; Randall 2007) and Easter Island (21.7%; Randall and Cea 2012).
Recent surveys have revealed that this isolation extends to phylogeographic studies
as well (Planes and Fauvelot 2002, Gaither et al. 2010, Leray et al. 2010). This high
level of endemism in both species and genetic lineages is attributed to a combination
of physical and ecological factors (Randall and Earle 2000), including geographical
isolation (distance from larval sources), hydrographical isolation (cold upwelling,
prevailing currents), young geological age (few marine habitats), and temperature
fluctuations. The Marquesas Archipelago is isolated from the Americas by the
Eastern Pacific Barrier spanning 4700 km of open ocean. The nearest atoll is 500
km to the southwest in the Tuamotus. Because of the prevailing east–west direction
of the South Equatorial Current (Wyrtki and Kilonsky 1983, Bonjean and Lagerloef
2002); however, the Marquesas normally does not receive larvae from the west. The
only exception may be during El Niño conditions, when warm water flows toward the
east. This increase of water temperature and the reversal of current flow might be an
opportunity for larvae to disperse toward the east. Higher surface water temperature
during ENSO events also lowers the thermocline, which allows for a larger body of
warmer water to come in near shores of these mostly volcanic islands (Randall and
Earl 2000). Once the oscillation reverses, the cold upwelling returns creating intolerable conditions for tropical Indo-Pacific shore fish species that are not adapted to
colder temperatures. Parupeneus multifasciatus is a demersal species that has been
reported at 161 m depth (Chave and Mundy 1994) and therefore can tolerate cold
water.
Until recently, pelagic larval duration (PLD) was believed to have a primary role in
the dispersal of marine species. Intuitively, the longer the PLD, the farther larvae can
disperse. However, more recent analyses indicate that the relationship between PLD
and dispersal is not a simple one, and is likely confounded by navigation, swimming
ability, and oceanic conditions (Selkoe et al. 2010, Leis et al. 2011, Selkoe and Toonen
2011). Mora et al. (2012) suggested that larvae can travel long distances on oceanic
currents, concluding that PLD is not a determining factor in successful colonization.
While stepping-stone atolls greatly facilitate dispersal, rare long-distance dispersal
events can also contribute to colonization (Crandall et al. 2012). These long-range
dispersal events, however, have much less chance to succeed because the larvae become diluted and there is a greater chance for habitat differences between remote
locations. For a species to become established in a new geographical location, the
larvae must reach their destination in sufficiently high numbers and find suitable
habitat. Often the new location has different environmental parameters than the
origin, e.g., greater temperature fluctuations or limited food resources. Multiple
Szabó et al.: Phylogeography of the manybar goatfish
507
introductions are probably necessary for a successful establishment of a breeding
population. Certain life history traits, such as a non-specialized carnivorous diet consisting mainly of benthic invertebrates (>72%), fishes, and fish eggs (Randall 2004),
indeterminate fecundity, and year around spawning (Pavlov et al. 2011, Emel‘yanova
et al. 2013) make P. multifasciatus an excellent candidate for long-range dispersal.
Parupeneus multifasciatus appears to be one of the most successful colonizers
among goatfish species. In the Marquesas there are six Parupeneus species, but only
one reached Rapa Nui (Easter Island) to the east (Randall and Cea 2012). This Easter
Island species was initially identified as Pseudupeneus multifasciatus (Quoy and
Gaimard, 1824) by Kendall and Radcliffe (1912), which was the historical name for
Parupeneus multifasciatus at the time. Later, morphological differences were noted
(e.g., shorter barbel length in the Easter Island), and the Easter Island endemic form
was renamed Parupeneus orientalis (Fowler, 1933). It is possible that the Marquesan
P. multifasciatus is on an evolutionary trajectory similar to P. orientalis, and it would
be informative to conduct a molecular phylogenetic comparison of P. orientalis and
P. multifasciatus. Easter Island is farther south of the Equator, and temperature fluctuations are even greater than in the Marquesas (Randall and Cea 2012). The ability
of P. multifasciatus to tolerate colder temperatures and greater temperature fluctuations could have contributed to the colonization of these remote locations.
Low Genetic Diversity at the Marquesas
The Marquesas are geologically very young (1.3–4.7 My), rises steeply from the
ocean and therefore do not have a fringe reef or abundant live coral (Randall and
Earl 2000, ZS pers obs). Allelic richness at Nuku Hiva is very low compared to other
collection sites in our data set (Table 1), consistent with the assumption that smaller
habitat generally translates into smaller effective population sizes. It is not surprising,
therefore, that our analysis of historical demography indicates a much smaller population and a more recent genetic bottleneck in the Marquesas than in the Hawaiian
Islands. This kind of pruning of the genetic diversity could have been repeated many
times during the 2-My history of the Marquesan lineage.
Population Structure Within the Hawaiian Archipelago
Our mtDNA analyses of P. multifasciatus did not reveal significant population
structure within the Hawaiian Archipelago, a common outcome for marine fishes
(Eble et al. 2009, Craig et al. 2010, DiBattista et al. 2011, Gaither et al. 2011, but see
Ramon et al. 2008, Eble et al. 2011b, Rivera et al. 2011, Toonen et al. 2011). One of
the main goals of our study was to examine whether larval exchange can occur between the NWHI and the populated MHI. We found no evidence of barriers to gene
flow and our results indicate that larval dispersal is sufficient to homogenize haplotype distributions from one end of the archipelago to the other, a distance of about
2600 km. While migration results were contradictory, the predominant direction of
larval flow seems to be from the Main Hawaiian Islands toward the Northwestern
Hawaiian Islands, consistent with the dominant surface currents and with previous
genetic surveys (Gaither et al. 2011, DiBattista et al. 2011, Toonen et al. 2011). The
management implications of this finding are that the heavily-fished MHI cannot be
quickly replenished by the protected NWHI and draws attention to the importance
of effective management of local fish stocks in the Main Hawaiian Islands.
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Bulletin of Marine Science. Vol 90, No 1. 2014
Population Structure Between Hawaii and the Wider Pacific
We observed significant mtDNA haplotype frequency shifts between the Hawaiian
Archipelago and the central and South Pacific (Palmyra, Kiritimati, Moorea =
PKM). The highest level of differentiation centered on the Gardner Pinnacle/French
Frigate shoals area in the middle of the archipelago (0.200 < ΦST < 0.357, Table 2).
Geographically, this area may be shielded from larval showers that arrive through
the Kuroshio-North Pacific currents (Eble et al. 2011a). Palau (n = 9) did not show
significant difference from either the Hawaiian Archipelago or PKM, indicating that
dispersal routes are capable of maintaining genetic connectivity across the Pacific
Ocean. On the other hand, Okinawa (n = 13) lies 19° north of Palau in the path of
the Kuroshio Current and still maintains genetic differentiation from the Hawaiian
Archipelago, but not from PKM. It is likely that this genetic connectivity across thousands of kilometers is augmented by the extended pelagic phase known for members
of the goatfish family.
In conclusion, the range of the manybar goatfish encompasses three biogeographic
provinces defined by endemism: Marquesas, Hawaii, and the vast Indo-Polynesian
Province (Briggs and Bowen 2012). We discovered significant genetic structure between Hawaii and the South and western Pacific indicating historic population partitioning, and an isolated population in the Marquesas Islands that is mostly likely
a cryptic endemic species based on mtDNA genetic distance. The genetic partitions
overall are concordant with the marine biogeographic provinces of the Pacific Ocean.
Since the inception of phylogeography as a discipline (Avise et al. 1987), practitioners
have asked if the microevolutionary separations observed within species (defined by
DNA sequence data) eventually translate into the macroevolutionary separations between species (defined by taxonomy). In this case the barriers apparent in mtDNA
sequence analyses agree with the biogeographic boundaries based on species distributions. It seems that at least in some cases, phylogeographic breaks are the starting
point for speciation (Rocha and Bowen 2008).
Acknowledgments
This research was supported by the National Science Foundation Grants OCE-0929031 to
BW Bowen, as well as NOAA National Marine Sanctuaries Program MOA 2005-008/6682
to RJ Toonen. For specimen collections, the authors thank K Szabó, M Kinjyou, T Arakaki,
J Reimer, anonymous fishermen in Okinawa, R Kosaki, C Meyer, Y Papastamatiou, J Eble, J
DiBattista, T Daly-Engel, M Gaither, S Jones, C Wilcox, G Concepcion, D Pence, P Colin,
L Colin, D Smith, K Tenggardjaja, J Zamzow, M Iacchei, D Wagner, J Schultz, R Coleman,
J Copus, I Fernandez-Silva, The Nature Conservancy, Coral Reef Research Foundation, the
supporting staff of Palmyra Atoll Research Consortium, and the crew of the RV Hi‘ialakai.
The authors also thank S Rowley, A Suzomoto, and L O’Hara for assistance with morphological analysis; M Donovan and DA Pavlov for help with life history data analysis, P Beerli,
J DiBattista, M Gaither, Y Chan, C Wilcox, and J Eble for consulting on genetic analysis; R
Toonen, Hawai’i Department of Land and Natural Resources, and the Papahānaumokuākea
Marine National Monument, US Fish and Wildlife Service, and members of the ToBo lab
for logistic support; J Williams and J Randall for providing photographs and consultation;
A Eggers, L Valentino, and M Mizobe of the HIMB EPSCoR core facility for their assistance
with DNA sequencing. We thank editor C Riginos and three anonymous reviewers whose
comments improved the manuscript. This is contribution no. 1576 from the Hawai‘i Institute
of Marine Biology and no. 9057 from the School of Ocean and Earth Science and Technology.
Szabó et al.: Phylogeography of the manybar goatfish
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