Content uploaded by Robert John Toonen
Author content
All content in this area was uploaded by Robert John Toonen
Content may be subject to copyright.
MARINE ECOLOGY PROGRESS SERIES
Mar Ecol Prog Ser
Vol. 428: 245–258, 2011
doi: 10.3354/meps09083 Published May 3
INTRODUCTION
The marine fauna of Hawaii is considerably less
diverse than that of the tropical West and South
Pacific but includes many of the same species (Ran-
dall 1998, Mundy 2005). Community similarities indi-
cate the possibility of ongoing connections between
the geographically remote Hawaiian Archipelago and
the broader Indo-Pacific, but the rate of connectivity is
difficult to assess. The broad distribution of many spe-
cies similarly limits the identification of dispersal cor-
ridors and the directionality of colonization (Hourigan
& Reese 1987, Jokiel 1987, Craig et al. 2010). Never-
theless, Hawaii’s marine fauna is widely regarded as a
biogeographic ‘dead end’, with diversity flowing into
but not out of the islands (Hourigan & Reese 1987,
Jokiel 1987, Kay & Palumbi 1987, Randall 1998,
Briggs 1999).
© Inter-Research 2011 · www.int-res.com*Email: eble@email.arizona.edu
Escaping paradise: larval export from Hawaii in
an Indo-Pacific reef fish, the yellow tang
Zebrasoma flavescens
Jeff A. Eble1,2,5,*, Robert J. Toonen1, Laurie Sorenson3, Larry V. Basch4,
Yannis P. Papastamatiou1,6, Brian W. Bowen1
1Hawaii Institute of Marine Biology, School of Oceanography and Earth Science and Technology, University of Hawai’i,
Kaneohe, Hawai’i 96744 USA
2Department of Zoology, University of Hawai’i, Honolulu, Hawai’i 96822 USA
3Virginia Institute of Marine Science, Gloucester Point, Virginia 23062 USA
4Ecology, Evolution, and Conservation Biology Program, University of Hawai’i, Honolulu, Hawai’i 96822 USA
5Present address: Department of Entomology, University of Arizona, Tucson, Arizona 85721 USA
6Present address: Florida Museum of Natural History, University of Florida, Gainesville, Florida 32611 USA
ABSTRACT: The depauperate marine ecosystems of the Hawaiian Archipelago share a high propor-
tion of species with the southern and western Pacific, indicating historical and/or ongoing connec-
tions across the large oceanic expanse separating Hawaii from its nearest neighbors. The rate and
direction of these interactions are, however, unknown. While previous biogeographic studies have
consistently described Hawaii as a diversity sink, prevailing currents likely offer opportunities for
larval export. To assess interactions between the remote reefs of the Hawaiian Archipelago and the
species-rich communities of the Central and West Pacific, we surveyed 14 nuclear microsatellite loci
(nDNA, n = 857) and a 614 bp segment of mitochondrial cytochrome b(mtDNA, n = 654) in the yel-
low tang Zebrasoma flavescens. Concordant frequency shifts in both nDNA and mtDNA reveal sig-
nificant population differentiation among 3 West Pacific sites and Hawaii (nDNA F’CT = 0.116;
mtDNA φCT = 0.098, p < 0.001). SAMOVA analyses of microsatellite data additionally indicate fine
scale differentiation within the 2600 km Hawaiian Archipelago (F’SC = 0.026, p < 0.001), which has
implications for management of this heavily-exploited aquarium fish. Mismatch analyses indicate the
oldest contemporary populations are in the Hawaiian Archipelago (ca. 318 000 yr) with younger pop-
ulations in the West Pacific (91000 to 175 000 yr). Estimates of yellow tang historical demography
contradict expectations of Hawaii as a population sink and instead indicate asymmetrical gene flow,
with Hawaii exporting rather than importing yellow tang larvae.
KEY WORDS: Acanthuridae · Larval dispersal · Larval retention · Marine connectivity ·
Phylogeography · Stock assessment
Resale or republication not permitted without written consent of the publisher
Mar Ecol Prog Ser 428: 245–258, 2011
Dispersal corridors
Affinities between reef fish communities in Hawaii
and southern Japan have prompted the suggestion of
larval exchange via the Kuroshio Current (KRC) and
the North Pacific Current (NPC; Randall 1998), which
encounters Kure and Midway Atoll in the recently
established Papahânaumokuâkea Marine National
Monu ment (PMNM; Fig. 1). Sister taxa for 2 of Ha -
waii’s 3 endemic butterflyfishes (family Chaetodonti-
dae) occur only in the West Pacific (including southern
Japan), indicating likely colonization via the NPC
(Craig et al. 2010). Drogues released off Japan have
made their way to the PMNM (McNally et al. 1983),
though the drogues required more than a year to make
the journey, which is far longer than most species’
pelagic larval duration (PLD). Formation of a land
bridge between Taiwan and the southern Ryukyu
Islands of Japan during recent glacial maxima de -
flected the Kuroshio Current eastward (Ujiie et al.
2003), potentially reducing travel time to Hawaii.
Alternatively, dispersal may be aided by juvenile raft-
ing with flotsam (Jokiel 1987, Randall 2007).
Dispersal to Hawaii may also occur along the east-
ward flowing Hawaiian Lee Countercurrent (HLCC),
which attains speeds of up to 8 cm s–1 (Kobashi &
Kawa mura 2002) as it flows past Wake Atoll and north-
ern portions of the Marshall Islands before terminating
near Johnston Atoll 800 km southwest of the Hawaiian
archipelago (Fig. 1). Johnston Atoll has been proposed
as a link between Hawaii and other Central Pacific
communities (Kobayashi 2006), though faunal affini-
ties and recent genetic studies indicate that Johnston is
more likely an outpost of Hawaii rather than a link to
the broader Pacific (Hourigan & Reese 1987, Skillings
et al. 2011, Timmers et al. 2011). Johnston Atoll’s ap -
parent inability to facilitate dispersal to Hawaii may be
because dispersal to the atoll via the HLCC is prohibi-
246
Fig. 1. Zebrasoma flavescens. Yellow tang collection sites (s). Hawaiian sampling sites are detailed in the inset. Collections were
made from June 2004 to July 2005. Major currents (arrows): KRC = Kuroshio Current; NPC = North Pacific Current; HLC = Hawaiian
Lee Current; HLCC = Hawaiian Lee Counter Current; NEC = North Equatorial Current
Eble et al.: Larval export from Hawaii
tively long and, like contemporary dispersal via the
NPC, would require a minimum journey of nearly a
year (Kobashi & Kawamura 2002).
The Line Islands, 1800 km south of Hawaii (Fig. 1),
have also been proposed as a source for larvae dispers-
ing to the archipelago (Myers 1989) and occasional
strays and migrants have been observed (Randall 2007).
Nonetheless, opportunities for exchange be tween the
Line Islands and Hawaii are likely rare be cause of the
need to cross the broad, fast and westward flowing North
Equatorial Current (NEC), which regularly attains
speeds greater than 25 cm s–1 and sometimes exceeds
60 cm s–1 (Kashino et al. 2009). These velocities are well
beyond maximum sustainable swimming speeds for reef
fishes (Fisher et al. 2005). Moreover, unlike the Southern
Equatorial Current (SEC) that can experience dramatic
inter-annual changes in current velocity and direction in
response to El Niño/ La Niña conditions (Johnston &
Merrifield 2000), the NEC is considerably more stable,
slowing only slightly during La Niña (Qiu & Joyce 1992,
Kashino et al. 2009).
While the consistency and velocity of the NEC would
appear to limit opportunities for larval exchange with
the Line Islands, these same features may facilitate
downstream export of Hawaiian born larvae (Jokiel &
Martinelli 1992, Connolly et al. 2003). Anti-cyclonic
eddies forming off the leeward shore of Hawaii Island
have been recorded travelling as far west as the Mar-
shall Islands under the influence of the NEC (Calil et
al. 2008), and larvae from a diverse set of nearshore
taxa have been found entrained within the eddies (Lo-
bel & Robinson 1988). The minimum estimated travel
time along the NEC is 70 d, which is considerably
shorter than dispersal estimates for other proposed cor-
ridors, and is within estimated larval durations for
many fishes, particularly when considering the poten-
tial for many taxa to extend their pelagic period in the
absence of suitable substrate (e.g. Toonen & Pawlik
2001) and that larval behavior may further reduce
travel time (Fisher 2005, Cowen & Sponaugle 2009).
Genetic insights into larval dispersal
Recent phylogeographic assessments of Pacific reef
fishes have revealed that larvae at least occasionally
bridge Hawaii’s isolation (Craig et al. 2007, Reece et al.
2010, Eble et al. 2011). Connectivity rates and direc-
tionality have not explicitly been assessed, with the
exception of a recently published survey of range-wide
patterns of gene flow in the widely distributed ruby -
lipped parrotfish Scarus rubrioviolaceus, which re -
vealed intriguing evidence of larval dispersal from
Hawaii to reefs in the Central Pacific (Fitzpatrick et al.
2011). Additional support for larval export from Hawaii
can be found in the bullethead parrotfish Chlorurus
sor didus, which revealed Hawaiian-derived mitochon-
drial lineages in West Pacific populations (Bay et al.
2004). Here we employ a multi-locus, range-wide ge -
netic survey of the Indo-Pacific reef fish, the yellow
tang Zebrasoma flavescens, to assess connectivity pat-
terns across the northern tropical and subtropical
Pacific. A previous survey of yellow tang mitochondrial
DNA (mtDNA) variation within the Hawaiian Archi-
pelago revealed no population subdivisions (φCT =
0.001, p = 0.38; Eble et al. 2009), indicating the poten-
tial for high rates of population connectivity across
long distances. We build on the previous mtDNA sur-
vey with range-wide coverage, larger sample sizes,
and the inclusion of 14 microsatellite loci developed for
yellow tang (Christie & Eble 2009).
Yellow tang are abundant reef herbivores in Hawaii
(Walsh 1987, Tissot et al. 2004) but also occur in lower
numbers throughout the tropical and subtropical North
Pacific (Randall 1998). Juveniles and adults are rela-
tively sessile (Claisse et al. 2009, Williams et al. 2009),
restricting inter-population connectivity to the esti-
mated 55-d planktonic larval phase (determined by
otolith microdissection; Basch et al. 2003). In Hawaii,
yellow tang comprise ~85% of the ornamental fish har-
vest with an estimated 300 000 juveniles collected
annually (Tissot & Hallacher 2003). Accordingly, one of
the rationales for the recent establishment of the
360 000 km2PMNM is that the region’s uninhabited
islands and atolls may be an important source of larvae
for the depleted reefs of the main Hawaiian Islands
(MHI; McClanahan & Mangi 2000).
MATERIALS AND METHODS
Sample collection. To identify patterns of genetic
structure and connectivity at multiple spatial scales,
we sampled juvenile and adult yellow tang throughout
its range, resulting in 857 individuals from 19 locations
(Fig. 1, Table 1). Previous collections from Hawaii and
Johnston Atoll (Eble et al. 2009; n = 560) were supple-
mented with 297 additional specimens from the same
locations as well as collections at 3 locations in the
West Pacific (Chichi-jima, Saipan, and Pohnpei). Ha -
waiian collections spanned the full 2600 km of the
archipelago and included 6 sites within the newly
established PMNM and 9 sites within the MHI, includ-
ing 4 sites on the largest island in the archipelago,
Hawaii Island. Collections were made with pole-spears
while using SCUBA or snorkeling. Tissue specimens
(fin clips) were stored in a saturated salt-dimethylsul-
foxide (DMSO) buffer (Seutin et al. 1991), and total
genomic DNA was extracted using a standard salting
out protocol (Sunnucks & Hales 1996).
247
Mar Ecol Prog Ser 428: 245–258, 2011
Mitochondrial DNA (mtDNA). Fish isolates were
sequenced to produce a 614 bp fragment of the mito-
chondrial cyto chrome bgene with heavy strand primer
(5’-GTG ACT TGA AAA ACC ACC GTT G-3’) and
light strand primer (5’-AAT AGG AAG TAT CAT TCG
GGT TTG ATG-3’) designed by Song et al. (1998) and
Taberlet et al. (1992), respectively. Polymerase chain
reaction (PCR) and sequencing protocols are described
in Eble et al. (2009). All specimens were sequenced in
the forward direction, and rare or questionable haplo-
types were sequenced in the reverse direction to con-
firm identity with an ABI 3130xl automated sequencer
(Applied Biosystems).
Sequences were aligned in MAFFT 6.62 (Katoh et al.
2002) and edited with SEQUENCHER 4.6 (Gene Codes).
Haplotype (h) and nucleotide (π) diversities were cal-
culated in ARLEQUIN 3.11 (Excoffier et al. 2005), which
implements diversity index algorithms described in
Nei (1987), and a statistical parsimony network was
constructed using the software TCS 1.21 (Clement et
al. 2000) with default settings.
Range-wide patterns of population structure were
assessed with a spatial analysis of molecular variance
(SAMOVA 1.0; Dupanloup et al. 2002). SAMOVA re moves
bias in group designation by implementing a simulated
annealing procedure to identify maximally differenti-
ated groupings without a priori assumptions about
group identity. To ensure validity of the final Kgroup-
ings, the simulated annealing process was repeated
100 times with a different random partition of samples
into Kgroups. The configuration with the largest
among-group differentiation (φCT) is retained as the
best sample grouping. SAMOVA was run with values of
K= 2 to 14 to identify the most likely number of sample
groups. Deviations from random expectations were
tested with 20 000 permutations. In ARLEQUIN, patterns
of genetic differentiation among individual sampling
sites were estimated with pairwise φST values. A Man-
tel test implemented in ARLEQUIN with 10 000 simula-
tions was used to test for an isolation-by-distance (IBD)
signature (a positive correlation be tween genetic and
geographic distance measured as shortest route over
water; Slatkin 1993). To provide insight into how the
spatial scale of gene flow may differ across closely
associated islands and large stretches of open ocean,
IBD tests were conducted on the full data set and sep-
arately on Hawaii and Johnston Atoll samples because
limited sampling within the West Pacific precluded
testing for IBD.
Estimates of migration between populations were
calculated with MIGRATE 2.1.3 (Beerli & Felsenstein
2001) on the University of Hawaii’s 96 node dual Xeon
3.2 GHz ‘Dell Cluster’. MIGRATE offers a robust frame-
work for testing migration between more than 2 popu-
248
Site N hπAH
OHE
mtDNA nDNA
Chichi 32 36 0.85 (0.06) 0.003 (0.002) 9.95 0.79 (0.02) 0.84 (0.02)
Sai. 33 35 0.85 (0.05) 0.003 (0.002) 10.40 0.75 (0.02) 0.86 (0.02)
Poh. 29 29 0.70 (0.10) 0.002 (0.002) 11.01 0.85 (0.02) 0.87 (0.02)
Joh. 32 47 0.79 (0.03) 0.003 (0.002) 9.02 0.79 (0.01) 0.80 (0.04)
Kure 35 55 0.80 (0.04) 0.004 (0.002) 8.73 0.76 (0.01) 0.80 (0.04)
Mid. 33 53 0.74 (0.04) 0.004 (0.002) 8.99 0.79 (0.01) 0.81 (0.04)
PH 29 55 0.77 (0.04) 0.004 (0.002) 8.70 0.78 (0.01) 0.80 (0.04)
Maro 26 29 0.70 (0.04) 0.003 (0.002) 8.37 0.74 (0.02) 0.79 (0.04)
FFS 40 50 0.73 (0.03) 0.003 (0.002) 8.72 0.76 (0.01) 0.80 (0.05)
Nihoa 20 32 0.81 (0.05) 0.004 (0.002) 8.64 0.77 (0.01) 0.80 (0.04)
Kauai 42 55 0.71 (0.04) 0.003 (0.002) 8.62 0.76 (0.01) 0.79 (0.04)
Oahu 35 50 0.70 (0.04) 0.003 (0.002) 8.56 0.78 (0.01) 0.79 (0.04)
Mol. 48 48 0.70 (0.04) 0.004 (0.002) 8.53 0.77 (0.01) 0.79 (0.04)
Maui 39 52 0.76 (0.03) 0.003 (0.002) 8.55 0.78 (0.01) 0.80 (0.04)
Lanai 35 33 0.69 (0.06) 0.003 (0.002) 8.53 0.73 (0.02) 0.79 (0.04)
Waw. 31 53 0.74 (0.05) 0.003 (0.002) 8.24 0.75 (0.02) 0.78 (0.04)
Kea. 36 45 0.78 (0.05) 0.004 (0.003) 8.79 0.77 (0.01) 0.81 (0.04)
SP 37 50 0.70 (0.04) 0.003 (0.002) 8.78 0.76 (0.01) 0.79 (0.04)
Hilo 42 50 0.69 (0.04) 0.003 (0.002) 8.78 0.78 (0.01) 0.81 (0.04)
Total / Mean 654 857 0.75 (0.05) 0.003 (0.002) 8.94 0.77 (0.01) 0.81 (0.04)
Table 1. Zebrasoma flavescens. Yellow tang collection sites with sample size (N) for mtDNA sequencing (mtDNA) and mi-
crosatellite genotyping (nDNA). Haplotype diversity (h), nucleotide diversity (π), allelic richness (A) standardized for sample
size, and observed (HO) and expected heterozygosity (HE) with SD in parentheses. Chichi: Chichi-jima, Japan; Sai.: Saipan,
Northern Marianas Islands; Poh.: Pohnpei, Federated States of Micronesia; Joh.: Johnston Atoll; Kure: Kure Atoll; Mid.: Midway
Atoll; PH: Pearl and Hermes Atoll; Maro: Maro Reef; FFS: French Frigate Atoll; Mol.: Molokai; Waw.: Wawaloli; Kea.:
Kealakekua; SP: South Point
Eble et al.: Larval export from Hawaii 249
lations, whereas similar analyses are constrained by
the assumption that a single population has split into 2
daughter populations (Hey & Nielsen 2007). Roy-
Choudhury & Stephens (2007) found MIGRATE-based
estimates of gene flow were significantly different from
expected for a simulated data set, but their analysis
employed an earlier version of MIGRATE (1.7.3) with
default settings. Subsequent tests of the same data set
in MIGRATE 2.1 found bias and error was low and simi-
lar to that observed in other widely accepted programs
(e.g. AMOVA; Beerli 2007). We employed the recom-
mended Bayesian Markov chain Monte Carlo (MCMC)
search strategy of a single, replicated, one million step
chain (Beerli 2009). Chain convergence was assessed
by ensuring (1) prior and posterior parameter estimates
differed and (2) concordance in posterior parameter
estimates over 10 replicate runs with different random
number seeds (Beerli 2004). Starting population para-
meters for diversity (Θ) and migration (M) were esti-
mated from Wright’s fixation index (FST). Initial runs
were conducted with default exponential priors and an
unrestricted migration model. Resulting posterior dis-
tributions for Θand Mwere used to inform priors for
the final set of replicated runs. Estimates of the number
of immigrants per generation (Nm) were calculated by
multiplying final estimates (mode, 2.5%, and 97.5%
quantile) of Θand M.
To test for deviations from selective neutrality we
generated F* and D* (Fu & Li 1993) in DnaSP 4.10.9
(Rozas et al. 2003). Female effective population sizes
(Nef) were estimated from the equation θ= Nef2μtwith
θestimated in ARLEQUIN from the mean number of seg-
regating sites (θS), μis the estimated annual fragment
mutation rate and tis the estimated generation time.
Population ages in years were estimated from the pop-
ulation age parameter (τ), τ= 2μT, where Tis the time
since the most recent bottleneck. We provisionally
applied a generation time of 5 years for yellow tang
(Claisse et al. 2009). Divergence estimates for cyto-
chrome bhave been obtained for a number of reef
fishes though never specifically for an Acanthurid. We
therefore employed within-lineage mutation rates that
en compass the range of cytochrome bevolutionary
rates reported for reef fishes: 1% per million years
(Bowen et al. 2001) and 2.5% per million years (Lessios
2008).
We tested for a signature of population expansion
with Fs (Fu 1997) and by comparing observed and
expected mismatch distributions (Rogers & Harpend-
ing 1992) in ARLEQUIN with 90 000 simulated samples.
Fu (1997) noted that Fs is particularly sensitive to devi-
ations from a constant population size with population
expansion resulting in a significant negative Fs.
Nuclear DNA (nDNA). Fish were genotyped at 14
micro satellite loci (Table 2) using the procedures
described in Christie & Eble (2009). Unlabeled reverse
primers were obtained from Integrated DNA Tech-
nologies. Forward primers were labeled with 6-FAM,
VIC, NED, and PET proprietary dyes (Applied Biosys-
tems). PCR products were scored relative to a known
size standard on an ABI 3100 automated sequencer
and visualized using ABI PRISM GENEMAPPER 3.0
(Applied Biosystems).
Quality control followed Selkoe & Toonen (2006) and
included tests for null alleles, loci scorability, linkage
disequilibrium, and Mendelian inheritance. Depar-
tures from Hardy-Weinberg proportions (Guo &
Thompson 1992) and linkage disequilibrium were
tested using GENEPOP 3.2 (Raymond & Rousset 1995)
with a Bonferroni correction for multiple pairwise com-
parisons (Bonferroni 1936). Tests of significance were
combined over all loci using Fisher’s combined proba-
bility test (Sokal & Rohlf 1981). We employed MICRO-
CHECKER 2.2.3 (van Oosterhout et al. 2004) to infer
scoring errors resulting from null alleles, large allele
drop-out, and stutter peaks. In addition, a random sub-
set of 10% of the samples were re-amplified, re-scored
and compared to initial scores, which indicated a scor-
ing error of <2% overall. Per locus estimates of allelic
richness were standardized for sample size by rarefac-
tion in FSTAT 2.9.3 (Goudet 2001).
Estimates of genotypic population structure were
conducted according to the methods described for
sequence data. Estimates of population subdivision
based on FST are impacted by the amount of genetic
variation within populations with high levels of within
population genetic variation leading to lower estimates
of population differentiation without a corresponding
effect on estimates of significance (Neigel 2002,
Locus N bp h or A hor HO
mtDNA 654 614 45 0.74 (0.07)
Zefl01 810 129–243 33 0.83 (0.06)
Zefl02 808 175–253 21 0.83 (0.05)
Zefl08 814 133–195 12 0.75 (0.07)
Zefl09 815 146–250 32 0.89 (0.05)
Zefl10 818 198–246 14 0.67 (0.08)
Zefl12 820 259–297 13 0.31 (0.10)
Zefl14 811 170–300 50 0.89 (0.05)
Zefl15 810 307–356 16 0.84 (0.05)
Zefl17 814 275–396 21 0.80 (0.07)
Zefl19 811 234–284 26 0.84 (0.05)
Zefl20 814 131–189 20 0.77 (0.05)
Zefl21 818 182–235 14 0.84 (0.04)
Zefl22 814 182–250 29 0.87 (0.06)
Zefl23 813 162–186 13 0.69 (0.05)
Table 2. Zebrasoma flavescens. Loci details with sample size
(N), fragment size (bp), number of mtDNA haplotypes (h),
number of nDNA alleles (A), observed haplotype diversity
(h; ±SD), and observed allelic heterozygosity (HO; ±SD)
Mar Ecol Prog Ser 428: 245–258, 2011
Hedrick 2005). Therefore, microsatellite-based esti-
mates of population differentiation were standardized
relative to the maximum attainable value given ob -
served within-population genetic variance using the
standardization method of Hedrick (2005) as imple-
mented in RecodeData 0.1 (Meirmans 2006; F’ST:
among paired sites; F’CT: among groups; F’SC: within
groups). A Mantel test implemented in ARLEQUIN was
used to test for a relationship between pairwise F’ST
and φST (mtDNA).
Population groupings were re-estimated in STRUC-
TURE 2.3.2 (Hubisz et al. 2009), which assigns individu-
als to one or more populations by minimizing devia-
tions from Hardy-Weinberg and linkage equilibria.
Be cause of an expectation of weak genetic structure
(Eble et al. 2009), sample locations were used as infor-
mative priors (Hubisz et al. 2009). For each run we con-
ducted a 100 000 step burn-in followed by 100 000
MCMC iterations with the admixture model and corre-
lated allele frequencies, as this configuration was
determined to be the best one in cases of subtle popu-
lation structure (Falush et al. 2003). We performed 10
runs for each estimated number of groups (K), from K=
1 to K = 10, and calculated the mean probability for
each Kover all replicate runs (Pritchard et al. 2007).
Evanno et al. (2005) proposed calculating the change
in mean probability for each K(ΔK) to identify the most
likely number of groups. Because ΔKcannot be calcu-
lated for K = 1, we instead calculated the posterior
probabilities of each Kto identify the most appropriate
number of groups (Pritchard et al. 2007). Where subdi-
vision was indicated, we tested for further structure by
running each of the subdivided groups independently
as recommended by Pritchard et al. (2007).
Recent population contractions or founder events will
confound estimates of population differentiation and
migration. We therefore tested for bottlenecked popu-
lations by assessing a number of characteristic traits in-
cluding reduced allelic richness, excess hetero zygosity
(Maruyama & Fuerst 1985, Cornuet & Luikart 1996),
and a reduced value for the mean ratio of the number of
alleles to the range of allele size (Garza & Williamson
2001). Allelic richness (A) was compared among groups
in FSTAT 2.9.3. Heterozygosity excess relative to expec-
tations under mutation-drift equilibrium was tested
with the Wilcoxon’s signed-rank test of BOTTLENECK
1.2.02 (Cornuet & Luikart 1996) using the recom-
mended 2-phase mutational model (95% frequency of
step-wise mutations; Piry et al. 1999). The mean ratio of
the number of alleles to the range in allele size was cal-
culated according to Garza & Wil li am son (2001). Signif-
icance was assessed by a comparison of the mean allele
size/range ratio across all loci for each sample grouping
with values less than 0.68 indicating a recent bottle-
neck (Garza & Williamson 2001).
Estimates of migration rates were calculated in
MIGRATE 2.1.3 with allele frequency data (in units of
number of repeats). Runs were conducted with
MIGRATE’s Brownian motion approximation of step-
wise microsatellite evolution. Initial runs consisted of
the recommended Bayesian MCMC search strategy of
a single, replicated, 1 million step chain with 5 repli-
cates (Beerli 2009). For allelic data, initial test runs
indicated a lack of convergence after 1 million steps,
but convergence was observed after 2 million steps
with a 20 000 step burn-in and this setting was used on
all subsequent runs. As with mtDNA sequence based
runs, priors included an unrestricted migration model,
and initial estimates of Θand Mwere used to inform
priors for the final set of replicated runs.
RESULTS
Cytochrome bdiversity
Sequences from 654 yellow tang revealed 39 haplo-
types (Table 2; GenBank accession numbers FJ376767 –
FJ376787 and GU320254–GU320271) with the number
of haplotypes per site ranging from 20 to 28. Haplotype
and nucleotide diversity ranged from h= 0.69–0.85 and
π= 0.002–0.004, respectively (Table 1). The statistical
250
Fig. 2. Zebrasoma flavescens. Statistical parsimony network
for yellow tang. Area of circle is proportional to the frequency
of the respective haplotype, with the smallest circles for
haplotypes found in only 1 fish and exact frequencies pro-
vided for the 4 most common haplotypes. Shades represent
haplotype location. TCS analysis was used to identify the
putative ancestral haplotype (q)
Eble et al.: Larval export from Hawaii
parsimony network indicated a cluster of closely related
haplotypes (Fig. 2), a common outcome for ma rine
fishes (Grant & Bowen 1998). Two of the 3 most com-
mon haplotypes were observed at every site and in-
cluded the putative ancestral haplotype (Fig. 2).
Microsatellite diversity
A sample of 857 yellow tang genotyped at 14 loci re -
vealed 14–50 alleles per locus, and allelic richness per
site ranging from A= 8.24–11.01 (Table 1). Mean ex-
pected heterozygosity ranged from HE= 0.79–0.87, and
mean observed heterozygosity ranged from HO=
0.73–0.85. There were no significant deviations from
Hardy-Weinberg proportions after applying a Bonferroni
correction for multiple tests. Significant linkage disequi-
librium was detected in only 27 of 2548 comparisons
among the 14 loci after Bonferroni correction within pop-
ulations. There was no consistent tendency towards link-
age disequilibrium between any loci or within any pop-
ulation with the exception of Midway Atoll, where 7 out
of 91 loci comparisons exhibited Bonferroni adjusted sig-
nificance. While evidence of linkage disequilibrium
within the Midway Atoll sample may be indicative of
population natural history or selection, the pattern is
more likely the result of scoring errors. Although null al-
leles were detected in only 4 of 266 within-sample com-
parisons with no consistent pattern observed within loci
or samples, locus Zefl 14 was found to contain null alle-
les in the Midway Atoll sample and, notably, was also
present in 4 of the 7 significant tests for linkage. Because
the presence of null alleles can confound estimates of
population differentiation and historical demography, we
compared pairwise FST estimates for Midway with and
without locus Zefl 14. A paired t-test revealed no signif-
icant change in FST due to the presence of null alleles (t =
2.11, p = 0.38, df = 340), we therefore retained Zefl 14 in
all subsequent analyses.
Population structure
Population genetic comparisons reveal shared micro -
satellite (nDNA) alleles and mtDNA haplotypes across
the species range, though we observed significant pair-
wise differences in mtDNA haplotype distributions (φST)
in 49 of 171 comparisons (Table 3) and in nDNA allele
frequencies (F’ST) in 70 of 171 comparisons (Table 3). Sig-
nificant estimates of pairwise population structure were
φST = 0.037– 0.291 and F’ST = 0.013– 0.169. Pairwise differ-
entiation was consistently greatest between Hawaii and
West Pacific collection sites, though neither nDNA nor
mtDNA exhibited a significant IBD correlation at this
scale. A Mantel test comparing pairwise F’ST and φST val-
251
Joh. Kure Mid. PH Maro FFS Nihoa Kauai Oahu Mol. Maui Lanai Waw. Kea. SP Hilo Chichi Sai. Poh.
Joh. –0.012 –0.015 –0.023 –0.005 –0.017 –0.035 –0.005 –0.002 0.010 –0.019 0.040 0.037 0.018 0.008 0.001 0.070* 0.048* 0.147**
Kure 0.002 –0.019 –0.016 –0.006 –0.017 –0.014 –0.002 –0.019 –0.019 –0.017 –0.006 0.007* –0.014 –0.005 –0.005 0.121** 0.092** 0.119**
Mid. –0.010 –0.004 –0.002 0.021 –0.007 –0.006 0.023 0.005 0.001 –0.003 0.003 0.140* 0.011 0.027 0.023 0.109** 0.096* 0.230**
PH 0.001 –0.007 –0.005 –0.017 –0.017 –0.039 –0.029 –0.018 –0.008 –0.024 0.030 0.027 –0.006 –0.012 –0.020 0.098** 0.061* 0.132*
Maro –0.004 0.008 –0.006 0.002 –0.022 –0.022 –0.025 –0.025 –0.001 –0.024 0.050 0.010 0.001 –0.030 –0.025 0.086* 0.034 0.100*
FFS 0.000 0.008 –0.005 –0.003 0.002 –0.021 –0.010 –0.018 –0.003 –0.022 0.027 0.041 0.002 –0.012 –0.009 0.083* 0.045* 0.144*
Nihoa 0.018 0.018 0.008 0.008 0.017 –0.010 –0.027 –0.014 0.001 –0.029 0.047 0.002 0.006 –0.012 –0.020 0.067* 0.034 0.106*
Kauai 0.006 0.024** 0.006 0.013* 0.014 –0.010 0.002 –0.017 0.001 –0.018 0.051 0.013 0.002 –0.020 –0.022 0.103** 0.053* 0.101*
Oahu 0.006 0.014 0.008 –0.001 0.012 –0.009 –0.001 0.002 –0.018 –0.020 0.012 0.051 –0.017 –0.024 –0.021 0.118** 0.072* 0.153*
Mol. 0.002 0.022* 0.000 0.003 0.003 –0.001 –0.003 –0.008 0.006 –0.006 –0.006 0.087* –0.019 –0.006 –0.005 0.147 0.108** 0.189**
Maui 0.000 0.007 –0.010 0.000 0.003 –0.005 –0.003 –0.002 –0.003 –0.005 0.030 0.029 0.000 –0.016 –0.017 0.090** 0.052* 0.129*
Lanai 0.002 0.008 –0.005 –0.005 –0.002 –0.007 0.012 0.015* 0.010 –0.010 0.000 0.170 –0.005 0.040 0.040 0.191***0.166** 0.291**
Waw. 0.015* 0.026** 0.012 0.001 0.010 0.001 0.004 –0.001 –0.002 0.000 0.017 0.012 0.087* 0.030 0.025 0.076** 0.021 0.008
Kea. 0.019* 0.016 0.000 0.007 0.034** 0.006 0.018 0.019* 0.019* 0.004 –0.001 –0.001 0.024** –0.005 –0.005 0.151***0.109** 0.182**
SP 0.035***0.042***0.032***0.023** 0.024* 0.014 0.021* 0.017* 0.008 0.007 0.012 0.015* 0.017* 0.037*** –0.023 0.117** 0.063* 0.118*
Hilo 0.009 0.012 –0.006 0.001 0.008 0.003 0.007 0.011 –0.003 0.002 –0.007 0.006 0.007 0.001 0.029** 0.114** 0.063* 0.112*
Chichi 0.108***0.088***0.072***0.101***0.108***0.090***0.081***0.100***0.102***0.099***0.088***0.103***0.090***0.092***0.117***0.080*** –0.010 0.121**
Sai. 0.123***0.101***0.108***0.127***0.138***0.133***0.118***0.134***0.140***0.151***0.137***0.142***0.146***0.125***0.169***0.139***0.018 0.054*
Poh. 0.147***0.128***0.135***0.143***0.145***0.116***0.093***0.155***0.129***0.145***0.154***0.128***0.132***0.136***0.160***0.139***0.037 0.020
Table 3. Zebrasoma flavescens. Results of pairwise tests for yellow tang population structure with mtDNA (φCT) above diagonal, and standardized microsatellites (F’ST) below
diagonal. Site abbreviations as in Table 1. *p < 0.05, **p < 0.01, ***p < 0.001
Mar Ecol Prog Ser 428: 245–258, 2011
ues indicated strong agreement in estimates of range-
wide nDNA and mtDNA population structure (r2= 0.749,
p < 0.001).
Tests for IBD in Hawaii were non-significant for both
marker sets. However, exclusion of the Hawaii Island
collections yielded a significant IBD signature in pair-
wise F’ST estimates across the remainder of the Hawai-
ian archipelago (r2= 0.12, m = 4 ×10–6, p = 0.008). This
re sult is likely because collections around Hawaii Is -
land, which were separated by as little as 50 km, ex -
hibited genetic subdivision equivalent to comparisons
between Hawaii Island and Midway Atoll, a distance
of more than 2000 km (Table 3). Notably, exclusion of
all the main Hawaiian Island samples increased the
strength of the nDNA IBD correlation (r2= 0.43, slope =
1 ×10–5, p = 0.009). Although the rate of change in ge -
netic distance with increasing geographic distance
was small, genetic differentiation increased consis-
tently and did not plateau, likely indicating drift-
migration equilibrium and stable populations through-
out the majority of the archipelago. Hierarchical
SAMOVA for both nDNA and mtDNA indicated K= 4
maximally differentiated groupings: Chichi-jima, Sai -
pan, Pohnpei, and Hawaii, which included Johnston
Atoll, Table 4). Among these groupings, estimates of
differentiation were highly significant (p < 0.001) and
remarkably similar between data sets (φCT = 0.098,
F’CT = 0.116). Within-group differentiation (φSC), how-
ever, differed markedly between nDNA and mtDNA.
Where the mtDNA data set returned a non-significant
estimate of within-group differentiation at K= 4 (φSC =
0.002, p = 0.38), nDNA data indicated further popula-
tion subdivision in Hawaii (F’SC = 0.026, p < 0.001).
Tests for mtDNA cytochrome bselective neutrality (F*
and D*) within the 4 SAMOVA populations were uni-
formly non-significant, indicating observed patterns of
population structure are not the result of differential
selection among collection sites (Table 5).
While SAMOVA clearly identified 4 maximally differ-
entiated groupings for both data sets, within Hawaii
non-random allele frequency shifts provided further
evidence of fine-scale genetic subdivision, with K= 13
being the smallest number of sample groups returning
a non-significant estimate of within-group differentia-
tion (F ’SC = –0.01, p = 0.13; Table 4). These groupings
demonstrate subtle genetic divisions between all col-
lection sites with the exception of 3 undifferentiated
sample groupings: (1) Kure, Midway, and Pearl and
Hermes Atoll, (2) French Frigate Shoals, Nihoa, Kauai,
and Oahu, and (3) Maui and Molokai. In contrast,
STRUCTURE indicated only 2 populations (West Pacific
and Hawaii) with posterior and mean probabilities
highest for the full data set at K= 2, and for each region
at K= 1. The discrepancy between STRUCTURE and
SAMOVA is likely due to the inherent difficulty of re -
solving fine-scale population structure with individual
clustering algorithms (Pritchard et al. 2007). Evanno et
al. (2005) found the Bayesian clustering method of
STRUCTURE was generally able to detect only the
uppermost hierarchical levels of population structure
252
(a)
KGrouping Among groups Among samples within groups
df VC % variation φCT df VC % variation φSC
1All 18 0.03 2.43 0.024**
2 Poh. / Sai., Chichi, Hawaii 1 0.13 10.99 0.110 17 0.02 1.67 0.019*
3 Poh. / Sai. / Chichi, Hawaii 2 0.09 7.83 0.078* 16 0.01 1.26 0.014
4 Poh. / Sai. / Chichi / Hawaii 3 0.11 9.80 0.098*** 15 0 0.18 0.002
(b)
KGrouping Among groups Among samples within groups
df VC % variation F’
CT (FCT) df VC % variation F’
SC (FSC)
1All 18 0.03 0.45 0.026*** (0.005)
2 Poh., Sai. / Chichi, Hawaii 1 0.11 1.99 0.095** (0.019) 17 0.01 0.24 0.010*** (0.002)
3 Poh. / Sai. / Chichi, Hawaii 2 0.11 2.01 0.103** (0.020) 16 0.01 0.24 0.011*** (0.002)
4 Poh. / Sai. / Chichi / Hawaii 3 0.11 1.93 0.116*** (0.022) 15 0.01 0.13 0.005*** (0.001)
13 Poh. / Sai. / Chichi / Joh. / 12 0.03 0.61 0.032*** (0.006) 6 0 –0.12 –0.011 (–0.002)
Kure, Mid., PH / Maro / FFS,
Nihoa, Kauai, Oahu / Lanai /
Maui, Mol. / Waw. / Kea. / SP / Hilo
Table 4. Zebrasoma flavescens. Structural analysis of molecular variance (SAMOVA) with maximally differentiated groupings
(K) for (a) mtDNA (K= 1 to 4) and (b) microsatellites (K= 1 to 4, 13). Site abbreviations as described in Table 1. df: degrees of
freedom; VC: variance components; fixation indices for mtDNA among-groups (φCT) and within groups (φSC), standardized
nDNA among-groups (F’
CT) and within groups (F’
SC), and non-standardized nDNA among-groups (FCT) and within groups (FSC).
*p < 0.05, **p < 0.01, ***p < 0.001
Eble et al.: Larval export from Hawaii
and did not detect more subtle (but significant) genetic
subdivision. In contrast, SAMOVA permutes samples
among groups within the AMOVA framework, essen-
tially testing every reasonable combination of sample
sites (Dupanloup et al. 2002). The permutation-based
strategy offers an enhanced ability to resolve fine-scale
structure because when predetermined sample sites
correspond closely with actual populations, tests for
allele frequency shifts are more powerful than individ-
ual clustering based on linkage disequilibrium and de -
viations from Hardy-Weinberg equilibrium (Pritchard
et al. 2007).
Historical demography
Microsatellite tests for recent population bottlenecks
were uniformly non-significant (data not shown), but all
sites demonstrated a high frequency of closely related
mtDNA haplotypes (Fig. 2) consistent with the sudden
expansion model of mismatch analysis (Table 5). Mis-
match analyses indicated time since ex pansion to be on
the order of 90 000 to 175 000 yr in the West Pacific and
320 000 yr in the Hawaiian group (assuming a within-
lineage mutation rate of 1% per million years; Table 5),
which may explain our observation of non-significant
Fs values in the Hawaii collections and significant neg-
ative values for Fs in the 3 West Pacific ones (Table 5).
Simulations have shown Fs to be more sensitive to re-
cent population expansion than other tests of demo-
graphic history (Fu 1997), so we place greater emphasis
on Fs when interpreting each population’s most recent
demographic trajectory. Coalescence estimates for indi-
vidual sites in Hawaii (300 000 to 375000 yr) were simi-
lar to the average for the archipelago (320 000 yr), indi-
cating that differences in the estimated age of extant
West Pacific and Hawaiian populations were not arti-
facts of Hawaii biased sampling. Female effective pop-
ulation sizes derived from θSvalues were similar for all
sites with 95% confidence intervals (CI) ranging be-
tween approximately 20 000 and 70 000 ind. region–1
(for μ= 1%; Table 5). θSvalues for individual collection
sites from Hawaii Island (1.19–2.17) were not signifi-
cantly different from those from other sites in the archi-
pelago (1.16–2.00; t= 2.78, p = 0.65), indicating that the
recent decline of yellow tang due to aquarium collect-
ing (Tissot & Hallacher 2003) has not led to a corre-
sponding loss of genetic diversity. Coalescence based
migration estimates for both mtDNA and nDNA reveal
strongly asymmetrical gene flow with larval export
from Hawaii at least 16 times greater than the recipro-
cal (Table 6). Migration rates, which are not scaled for
population size, were likewise asymmetrical in favor of
dispersal from Hawaii for both nDNA and mtDNA data
sets. Assuming a within-lineage mutation rate of 10–8
253
Population θSNef (1%) Nef (2.5%) Mismatch analyses Fs Selective neutrality
SSD τage (1%) age (2.5%) F*D*
Chichi-jima 2.85 46 416 18 567 0.002 2.15 175 081 70 033 –6.17*** 0.47 0.01
(1.64–4.06) (26 710– 66 123) (10 684– 26 450) (p = 0.73) (0.68–3.72) (55 375–302 932) (22 150–121 173)
Saipan 3.14 51 140 20 456 0.004 1.94 157 980 63 192 –6.67*** –1.67 –1.85
(1.83–4.45) (29 804–72 475) (11 922–28 990) (p = 0.57) (0.48–3.13) (39 088–254 886) (15 635–101 954)
Pohnpei 1.26 20 521 8 208 0.015 1.12 91 205 36 482 –2.01** –1.36 –1.59
(0.51–2.01) (8 306–31 596) (3 322–13 094) (p = 0.62) (0.54–2.12) (43 974–172 638) (17 590–69 055)
Hawaii 2.74 44 625 17 850 0.044 3.90 317 590 127 036 0.51 0.19 0.44
(1.94–3.54) (31 596–57 654) (12 638–23 061) (p = 0.16) (2.09–7.75) (170 196–631 107) (68 078–252 443)
Table 5. Zebrasoma flavescens. Estimates (±95% CI) of yellow tang historical demography for the 4 SAMOVA populations. θS: theta estimates; Nef: female effective popula-
tion size for within lineage mutation rates of 1% and 2.5% per million years; SSD: test for deviations from the sudden expansion model of mismatch analysis with associated
significance; τ: population age parameter, age: population age (yr) for within lineage mutation rates of 1% and 2.5% per million years; Fs: tests for population expansion;
F* and D*: selective neutrality for mtDNA haplotypes. *p < 0.05, **p < 0.01, *** p < 0.001
Mar Ecol Prog Ser 428: 245–258, 2011
for mtDNA (1% per million years, Bowen et al. 2001)
and an average per repeat mutation rate of 10–5 (Jarne
& Lagoda 1996) for microsatellite loci, the migration
rate from Hawaii was 4.2 ×10–4 to 5.8 ×10–4 (nDNA) and
2.1 ×10–5 to 1.4 ×10–5 (mtDNA), while the migration
rate to Hawaii was 7.5 ×10–5 to 1.2 ×10–4 (nDNA) and
2.5 ×10–6 to 4.9 ×10–6 (mtDNA). Posterior distributions
of parameter estimates consistently departed from pri-
ors, and results were consistent over multiple runs, indi-
cating chain convergence (Beerli 2009). The ex ceptions
to this pattern of convergence were migration estimates
among West Pacific sites. Replicate migration estimates
among these 3 sites varied from run to run but were
consistently high, indicating that gene flow within this
region is greater than can be resolved accurately (Beerli
2004).
To test whether more extensive sampling of the Ha -
waiian Archipelago confounded migration estimates,
MIGRATE was re-run 10 times with 50 randomly drawn
individuals from Hawaii. Migration estimates derived
from the randomly drawn Hawaiian samples con-
curred with estimates from the full data set, demon-
strating that the observed pattern of westward disper-
sal was not an artifact of intensive sampling in Hawaii.
DISCUSSION
Counter to expectations of Hawaii as exclusively a re-
cipient of external biodiversity (Briggs 1999, Hourigan &
Reese 1987, Randall 2007), nDNA and mtDNA migration
estimates reveal a strong pattern of asymmetric gene
flow between Hawaii and the West Pacific, with Hawaii
exporting yellow tang alleles and haplotypes, presum-
ably as larvae (Table 6). However, the frequency of larval
export is insufficient to homogenize populations across
the range. SAMOVA tests for population structure re-
vealed significant genetic differentiation between
Hawaii and the West Pacific (φST = 0.008–0.230, F’ST =
0.072–0.169) as well as significant subdivision within the
West Pacific (φST = 0.010–0.121, F’ST = 0.018–0.037), and
fine-scale partitions within the Hawai-
ian Archipelago were detected with
microsatellites but not mtDNA (φSC =
0.002, p = 0.38; F’SC = 0.026, p < 0.001;
Table 4). While nDNA and mtDNA
markers differ in their resolution of pop-
ulation subdivisions within Hawaii, a
Mantel test comparing pairwise F’ST and
φST values indicated strong agreement in
estimates of range-wide population
structure (r2= 0.749, p < 0.001). Yellow
tang are known to occasionally hybri -
dize with congeners (J.E. Randall pers.
comm.), and the presence of hybrids
within the sample might confound interpretation of the
data. However, the limited genetic distance between
mtDNA haplotypes (Fig. 2) and the ubiquity of admixed
individuals (nDNA STRUCTURE plot, data not shown)
indicates that hybrids were not likely sampled.
Population structure within Hawaii
We observed microsatellite allele frequency shifts
that provide clear evidence of an IBD signature across
the majority of the Hawaiian Archipelago, indicating a
general pattern of reduced larval exchange with in -
creased distance. No IBD pattern, however, was ob -
served in the mtDNA sequence data, likely because
Hawaiian collections were dominated by the 3 most
common haplotypes. The significance of the micro -
satellite- based IBD relationship was confounded by
inclusion of Hawaii Island samples that were signifi-
cantly differentiated across ≤50 km, indicating that
factors other than IBD may be driving patterns of larval
exchange at smaller spatial scales (e.g. near-shore
currents; Selkoe et al. 2010, White et al. 2010).
The population structure of yellow tang in Hawaii
has ramifications on at least 2 conservation fronts. First,
the genetic resolution of populations indicates isolated
stocks with structure primarily corresponding to (1) the
northern-most islands of the Hawaiian Archipelago
(Kure, Midway, and Pearl and Hermes), (2) the broad
region of the central archipelago from French Frigate
Shoals to Oahu, (3) adjacent Maui and Molo kai, and (4)
multiple management units on Hawaii Island [though
this latter designation deserves further research given
recent indications of yellow tang larval exchange
among Hawaii Island reefs (Christie et al. 2010)]. Pop-
ulation designations are consistent with the linear
geography of the archipelago (Fig. 1) and are generally
concordant with population discontinuities in other
Hawaiian fishes, invertebrates, and marine mammals
(Bird et al. 2007, Andrews et al. 2010, Polato et al. 2010,
Toonen et al. 2011).
254
West Pacific nDNA mtDNA
populations From Hawaii To Hawaii From Hawaii To Hawaii
Chichi-jima 6.05 0.26 1.97 0.00
(3.16–8.42) (0.00–0.61) (0.00–29.25) (0.00–0.03)
Saipan 4.60 0.15 2.49 0.01
(1.63–6.50) (0.00–0.51) (0.00–64.84) (0.00–0.08)
Pohnpei 4.18 0.25 6.43 0.00
(0.98–6.39) (0.00–0.62) (0.53–22.31) (0.00–0.04)
Table 6. Zebrasoma flavescens. Estimates (±95% CI) of yellow tang larval dis-
persal (migrants per generation) derived from MIGRATE for 14 microsatellites
(nDNA) and mtDNA cytochrome bsequence data
Eble et al.: Larval export from Hawaii
Second, since one of the yellow tang populations
defined above (French Frigate Shoals to Oahu) spans
portions of both the PMNM and the impacted reefs of
the MHI, evidence of genetic connectivity between
these regions indicates the potential for some larval
spillover. Prevailing northwest surface currents (HLC;
Fig.1) may, however, limit opportunities for larval dis-
persal from the PMNM to the MHI (Calil et al. 2008,
Rivera et al. 2011, DiBattista et al. 2011). Rather, the
impacted reefs of the MHI may serve as a larval source
for the PMNM (Bird et al. 2007). A recent assessment
of parentage within Hawaii Island yellow tang identi-
fied 4 parent-offspring pairs, with larval dispersal from
natal reefs consistently to the north (Christie et al.
2010). While the extrapolation of patterns from within a
single island to the broader archipelago is question-
able, observed northward dispersal matched predic-
tions from the authors’ oceanographic model and indi-
cates the potential for dispersal downstream from the
MHI to the PMNM.
Larval export from Hawaii
The geographic distribution of yellow tang nDNA
and mtDNA diversity reveal a pattern of westward
biased gene flow, with dispersal from Hawaii roughly
16 times greater than the reciprocal (Table 6). Because
of the high likelihood of larval exchange with unsam-
pled yellow tang populations in the Central and West
Pacific, migration rates cannot be interpreted as direct
estimates of larval exchange between Hawaii and
West Pacific collection sites (Beerli 2004). Rather, mi -
gration estimates offer a qualitative assessment of the
direction and tempo of gene flow across the large ex -
panse of open ocean separating Hawaii from its near-
est neighbors. Furthermore, coalescent based migra-
tion estimates represent a historic average over the
time scale of genetic drift (e.g. 4Nefor diploid markers;
Beerli 2004) and therefore may not reflect current con-
ditions. Migration estimates derived from 10 random-
ized subsamples of Hawaiian collections matched
results from the full data set, demonstrating that evi-
dence of westward dispersal was not an artifact of our
extensive sampling in Hawaii.
Yellow tang are particularly abundant among the
southernmost islands of Maui Nui (Maui, Molokai, and
Lanai) and Hawaii Island where they are the dominant
herbivore (Walsh 1987). Yellow tang are less common
outside of Hawaii (J.E. Randall pers. comm.), raising
the possibility that the observed pattern of asymmetri-
cal larval export may in part result from differences in
population size and corresponding reproductive output
(Cowen & Sponaugle 2009). This, however, does not
appear to be the case since migration rates (which are
not scaled for population size) were likewise asymmet-
rical in favor of dispersal from Hawaii for both nDNA
and mtDNA data sets.
Larval export from Hawaii does not appear to be re -
stricted to yellow tang. Ember parrotfish Scarus rubro -
violaceus are common throughout the Indo-Pacific and
East Pacific (Randall 2007), and estimates of the
number of migrants per generation (m) derived from
15 micro satellite markers revealed a similar pattern of
asym metric larval export, with migration from Hawaii
to the Central West Pacific (1.70, 0.98–2.21; mean, 95%
CI), approximately an order of magnitude greater than
the reciprocal (0.14, 0.03–0.49; Fitzpatrick et al. 2011).
A similar, though substantially more balanced, pattern
of larval export was revealed in an assessment of
mtDNA (CO1) diversity in the Indo- Pacific sea cucum-
ber Holothuria atra (Skillings et al. 2011). Overall,
H. atra larval export from Hawaii (0.02– 1.02) was mar-
ginally greater than larval import (0.01– 0.84) and indi-
cates a pattern of bi directional larval exchange. Evi-
dence of larval export from Hawaii can also be found in
a phylo genetic re construction of mtDNA control region
se quences from the bullethead parrotfish Chlorurus
sordidus (Bay et al. 2004). Three highly differentiated,
monophyletic lineages were re solved, with lineages
corresponding to the Indian Ocean, the West Pacific,
and Hawaii. However, several fish collected in the
West Pacific contained haplotypes derived from the
Hawaiian lineage, with the depth of the partitions
between lineages indicating a period of extended
isolation followed by more recent larval export (Bay et
al. 2004).
Trans-Pacific biodiversity feedback
While much of Hawaii’s marine biodiversity clearly
derives from the West Pacific (Hourigan & Reese 1987,
Jokiel 1987, Kay & Palumbi 1987, Randall 1998, Briggs
1999, Craig et al. 2010), evidence of larval export in
yellow tang and other reef species reveal Hawaii to be
more than a simple diversity sink. Broader taxonomic
sampling is required before we can determine the true
balance between larval export and import; nonethe-
less, the consistency of larval export in initial migration
assessments begs the question of whether Hawaii may
be exporting more than just genes.
Our phylogeographic assessment of the yellow tang
reveals 3 lines of evidence that indicate yellow tang
may have been a Hawaiian endemic that subsequently
‘escaped’ to the west. (1) Mismatch analyses indicate
more recent population coalescence in the West Pacific
(91 000 to 175 000 yr compared to 317000 yr in Hawaii;
Table 5), an unexpected finding under a scenario of
West Pacific origin especially considering the likeli-
255
Mar Ecol Prog Ser 428: 245–258, 2011
hood of a population bottleneck upon colonization of
Hawaii and the higher rates of population turnover in
peripheral populations (Frankham 1996, Pardo et al.
2005). (2) Fs values (Fu 1997; Table 5) indicate recent
population expansion in the 3 West Pacific collection
sites and stable populations in Hawaii. (3) The asym-
metrical gene flow described above runs counter to
expectations of a West Pacific origin. While we cannot
rule out colonization of Hawaii from the West Pacific
followed by the establishment of a prevailing pattern
of westward dispersal, estimates of historical demo -
graphy and migration indicate a possible Hawaiian
origin for yellow tang.
However, regardless of yellow tang’s origins, evi-
dence of larval export from Hawaii provides insights
into evolutionary interactions between the remote
reefs of the Hawaiian Archipelago and the species-rich
communities of the West Pacific. Rather than being a
biogeographic ‘dead end’, biological and genetic
diversity arising in Hawaii may be able to escape its
remote origins, ultimately contributing to community
diversity across the Indo-Pacific in a process of biodi-
versity feedback (sensu Rocha et al. 2008). Taken
together with evidence of recent dispersal from Hawaii
in other reef organisms, these findings indicate that the
remote archipelagos of the central Pacific may function
as both a source and recipient of Indo-Pacific marine
diversity.
Acknowledgements. We thank the Papahânaumokuâkea
Marine National Monument, US Fish and Wildlife Service,
and Hawai’i Department of Land and Natural Resources for
coordinating research activities and permitting procedures,
and the crew of the NOAA Ship ‘Hi’ialakai’, M. Christie, J.
Starmer, T. Donaldson, N. Yasuda, A. Alexander, B. Walsh, B.
Carmen, I. Williams, S. Cotton, T. Daly-Engel, J. Claisse, M.
Craig, L. Rocha, R. Kosaki, C. Musberger, S. Karl, D. White, C.
Meyer, M. Gaither, M. Iacchei, G. Conception, M. Crepeau, Z.
Szabo, D. Pence, K. Flanagan, and the UH Dive Safety Pro-
gram for field collections, laboratory assistance, and valuable
advice, and the University of Kansas Natural History Museum
for providing specimens. This work was funded by US
National Science Foundation grants to B.W.B. and R.J.T.
(OCE- 0454873, OCE-0453167, OCE-0623678, and OCE-
0929031) and to the UH EECB program (OCE-0232016), in
conjunction with the HIMB-NWHI Coral Reef Research Part-
nership (NMSP MOA 2005-008/6682), and the National
Oceanic and Atmospheric Administration, Center for Spon-
sored Coastal Ocean Science, under awards no. NA05NOS
4261157 to the University of Hawai’i for the Hawai’i Coral
Reef Initiative. We thank the staff of the HIMB Core Facility
for sequencing and fragment analysis (EPS-0554657) and the
UH Dell Computer Cluster for computing resources (grant
number 5 P20 RR16467 and NSF-EPS02-37065). This is HIMB
Contribution No. 1433 and SOEST Contribution No. 8087.
This study complied with current laws in the United States
and was conducted in accordance with the regulations of the
University of Hawai’i Institutional Animal Care and Use Com-
mittee (IACUC).
LITERATURE CITED
Andrews KR, Karczmarski L, Au WL, Bowen BW, Rickards S,
Toonen RJ (2010) Rolling stones and stable homes: social
structure, habitat, diversity and population genetics of the
spinner dolphin (Stenella longirostris). Mol Ecol 19:
732–748
Basch L, Shafer DJ, Walsh W, Eble J (2003) Recruitment
dynamics and early life history strategies of key herbi-
vorous coral reef fishes in a Hawaiian MPA network. 84th
Meeting of Western Society of Naturalists, Western Soci-
ety of Naturalists, Long Beach, CA
Bay LK, Choat JH, van Herwerden L, Robertson DR (2004)
High genetic diversities and complex genetic structure in
an Indo-Pacific tropical reef fish (Chlorurus sordidus): evi-
dence of an unstable evolutionary past? Mar Biol 144:
757–767
Beerli P (2004) MIGRATE: documentation and program, part of
LAMARC. Version 2.0. Revised 23 December 2004. Distrib-
uted over the Internet
http:// evolution.genetics. washington.
edu/ lamarc/index.html
Beerli P (2007) Estimation of the population scaled mutation
rate from microsatellite data. Genetics 177:1967–1968
Beerli P (2009) How to use Migrate or why are Markov chain
Monte Carlo programs difficult to use? In: Bertorelle G,
Bruford MW, Hauffe HC, Rizzoli A, Vernesi C (eds) Popu-
lation Genetics for Animal Conservation. Cambridge Uni-
versity Press, Cambridge, p 42–74
Beerli P, Felsenstein J (2001) Maximum likelihood estimation
of a migration matrix and effective population sizes in n
subpopulations by using a coalescent approach. Proc Natl
Acad Sci USA 98:4563–4568
Bird CE, Holland BS, Bowen BW, Toonen RJ (2007) Contrast-
ing phylogeography in three endemic Hawaiian limpets
(Cellana spp.) with similar life histories. Mol Ecol 16:
3173–3186
Bonferroni CE (1936) Teoria statistica delle classi e calcolo
delle probabilità. Pubblicazioni del R Instituto Superiore di
Scienze Economiche e Commerciali di Firenze 8:3–62
Bowen BW, Bass AL, Rocha LA, Grant WS, Robertson DR
(2001) Phylogeography of the trumpetfishes (Aulostomus):
ring species complex on a global scale. Evolution 55:
1029–1039
Briggs JC (1999) Coincident biogeographic patterns: Indo-
West Pacific Ocean. Evolution 53:326–335
Calil PHR, Richards KJ, Jia YL, Bidigare RR (2008) Eddy activ-
ity in the lee of the Hawaiian Islands. Deep-Sea Res II 55:
1179–1194
Christie MR, Eble JA (2009) Isolation and characterization of
23 microsatellite loci in the yellow tang, Zebrasoma
flavescens (Pisces: Acanthuridae). Mol Ecol Res 9:544–546
Christie MR, Tissot BN, Albins MA, Beets JP, Yanli J, Thomp-
son SE, Hixon MA (2010) Larval connectivity in an effective
network of marine protected areas. PLoS ONE 5: e15715
Claisse JT, Kienzle M, Bushnell ME, Shafer DJ, Parrish JD
(2009) Habitat- and sex-specific life history patterns of yel-
low tang Zebrasoma flavescens in Hawaii, USA.Mar Ecol
Prog Ser 389:245–255
Clement M, Posada D, Crandall KA (2000) TCS: a computer
program to estimate gene genealogies. Mol Ecol 9:
1657–1660
Connolly SR, Bellwood DR, Hughes TP (2003) Indo-Pacific
biodiversity of coral reefs: deviations from a mid-domain
model. Ecology 84:2178–2190
Cornuet JM, Luikart G (1996) Description and power analysis
of two tests for detecting recent population bottlenecks
from allele frequency data. Genetics 144:2001–2004
256
➤
➤➤
➤➤
➤➤
➤➤
➤
➤
➤
➤➤
➤
➤➤
➤
➤
Eble et al.: Larval export from Hawaii
Cowen RK, Sponaugle S (2009) Larval dispersal and marine
population connectivity. Annu Rev Mar Sci 1:443–466
Craig MT, Eble JA, Bowen BW, Robertson DR (2007) High
genetic connectivity across the Indian and Pacific Oceans
in the reef fish Myripristis berndti (Holocentridae). Mar
Ecol Prog Ser 334:245–254
Craig MT, Eble JA, Bowen BW (2010) Origins, ages and pop-
ulation histories: comparative phylogeography of endemic
Hawaiian butterflyfishes (genus Chaetodon). J Biogeogr
37: 2125–2136
DiBattista JD, Wilcox C, Craig MT, Rocha LA, Bowen BW
(2011) Phylogeography of the Pacific blueline surgeonfish,
Acanthurus nigroris, reveals high genetic connectivity and
a cryptic endemic species in the Hawaiian Archipelago.
J Mar Biol 2011:1–17 2011/839134
Dupanloup I, Schneider S, Excoffier L (2002) A simulated
annealing approach to define the genetic structure of pop-
ulations. Mol Ecol 11:2571–2581
Eble JA, Toonen RJ, Bowen BW (2009) Endemism and disper-
sal: comparative phylogeography of three surgeonfishes
across the Hawaiian Archipelago. Mar Biol 156:689–698
Eble JA, Rocha LA, Craig MT, Bowen BW (2011) Not all lar-
vae stay close to home: Insights into marine population
connectivity with a focus on the brown surgeonfish (Acan-
thurus nigrofuscus). J Mar Biol 2011:1–12 doi: 10. 1155/
2011/ 518516
Evanno G, Regnaut S, Goudet J (2005) Detecting the number
of clusters of individuals using the software STRUCTURE:
a simulation study. Mol Ecol 14:2611–2620
Excoffier L, Laval LG, Schneider S (2005) Arlequin (version
3.0): an integrated software package for population genet-
ics data analysis. Evol Bioinform Online 1:47–50
Falush D, Stephens M, Pritchard JK (2003) Inference of popula-
tion structure using multilocus genotype data: linked loci
and correlated allele frequencies. Genetics 164: 1567–1587
Fisher R (2005) Swimming speeds of larval coral reef fishes:
impacts on self-recruitment and dispersal. Mar Ecol Prog
Ser 285:223–232
Fisher R, Leis JM, Clark DL, Wilson SK (2005) Critical swim-
ming speeds of late-stage coral reef fish larvae: variation
within species, among species and between locations. Mar
Biol 147:1201–1212
Fitzpatrick JM, Carlon DB, Lippe C, Robertson DR (2011) The
West Pacific diversity hotspot as a source or sink for new
species? Population genetic insights from the Indo-Pacific
parrotfish Scarus rubroviolaceus. Mol Ecol 20:219–234
Frankham R (1996) Relationship of genetic variation to popu-
lation size in wildlife. Conserv Biol 10:1500–1508
Fu YX (1997) Statistical tests of neutrality of mutations against
population growth, hitchhiking and background selection.
Genetics 147:915–925
Fu YX, Li WH (1993) Statistical tests of neutrality of muta-
tions. Genetics 133:693–709
Garza JC, Williamson EG (2001) Detection of reduction in
population size using data from microsatellite loci. Mol
Ecol 10:305–318
Goudet J (2001) FSTAT a program to estimate and test gene
diversities and fixation indices (version 2.9.3). Available at
http:// www2. unil.ch/popgen/softwares/fstat.htm, accessed
on 15 Aug 2010
Grant WAS, Bowen BW (1998) Shallow population histories in
deep evolutionary lineages of marine fishes: insights from
sardines and anchovies and lessons for conservation.
J Hered 89:415–426
Guo SW, Thompson EA (1992) A Monte Carlo method for
combined segregation and linkage analysis. Am J Hum
Genet 51:1111–1126
Hedrick PW (2005) A standardized genetic differentiation
measure. Evolution 59:1633–1638
Hey J, Nielsen R (2007) Integration within the Felsenstein
equation for improved Markov chain Monte Carlo meth-
ods in population genetics. Proc Natl Acad Sci USA 104:
2785–2790
Hourigan TF, Reese ES (1987) Mid-ocean isolation and the
evolution of Hawaiian reef fishes. Trends Ecol Evol 2:
187–191
Hubisz MJ, Falush D, Stephens M, Pritchard JK (2009) Infer-
ring weak population structure with the assistance of sam-
ple group information. Mol Ecol Resour 9:1322–1332
Jarne P, Lagoda PJL (1996) Microsatellites, from molecules to
populations and back. Trends Ecol Evol 11:424–429
Johnston TMS, Merrifield MA (2000) Interannual geostrophic
current anomalies in the near-equatorial western Pacific.
J Phys Oceanogr 30:3–14
Jokiel P (1987) Ecology, biogeography and evolution of corals
in Hawaii. Trends Ecol Evol 2:179–182
Jokiel P, Martinelli FJ (1992) The vortex model of coral reef
biogeography. J Biogeogr 19:449–458
Kashino Y, Espana N, Syamsudin F, Richards KJ, Jensen T,
Dutrieux P, Ishida A (2009) Observations of the North
Equatorial Current, Mindanao Current, and Kuroshio cur-
rent system during the 2006/07 El Niño and 2007/08 La
Niña. J Oceanogr 65:325–333
Katoh K, Misawa K, Kuma K, Miyata T (2002) MAFFT: a
novel method for rapid multiple sequence alignment
based on fast Fourier transform. Nucleic Acids Res 30:
3059–3066
Kay EA, Palumbi SR (1987) Endemism and evolution in
Hawaiian marine invertebrates. Trends Ecol Evol 2:
183–187
Kobashi F, Kawamura H (2002) Seasonal variation and insta-
bility nature of the North Pacific Subtropical Countercur-
rent and the Hawaiian Lee Countercurrent. J Geophys Res
107:6.1–6.18
Kobayashi DR (2006) Colonization of the Hawaiian Archipel-
ago via Johnston Atoll: a characterization of oceano-
graphic transport corridors for pelagic larvae using com-
puter simulation. Coral Reefs 25:407–417
Lessios HA (2008) The great American schism: Divergence of
marine organisms after the rise of the Central American
Isthmus. Annu Rev Ecol Evol Syst 39:63–91
Lobel PS, Robinson AR (1988) Larval fishes and zooplankton
in a cyclonic eddy in Hawaiian waters. J Plankton Res 10:
1209–1223
Maruyama T, Fuerst PA (1985) Population bottlenecks and
nonequilibrium models in population genetics. II. Number
of alleles in a small population that was formed by a recent
bottleneck. Genetics 111:675–689
McClanahan TR, Mangi S (2000) Spillover of exploitable
fishes from a marine park and its effect on the adjacent
fishery. Ecol Appl 10:1792–1805
McNally GJ, Patzert WC, Kirwan AD, Vastano AC (1983) The
near-surface circulation of the North Pacific using satellite
tracked drifting buoys. J Geophys Res 88:7507–7518
Meirmans PG (2006) Using the AMOVA framework to esti-
mate a standardized genetic differentiation measure. Evo-
lution 60:2399–2402
Mundy BC (2005) Checklist of fishes of the Hawaiian Archi-
pelago. Bishop Museum Bulletin in Zoology 6. Bishop
Museum, Honolulu
Myers RF (1989) Micronesian reef fishes. Coral Graphics, Bar-
rigada Guam
Nei M (1987) Molecular evolutionary genetics, Columbia Uni-
versity Press, New York
257
➤
➤
➤
➤
➤➤
➤
➤➤
➤
➤
➤
➤➤
➤
➤
➤
➤
➤
➤
➤➤
➤➤
➤
➤➤
➤
➤➤
➤
➤
➤➤
➤➤
➤
➤
➤
➤
➤
➤
➤
Mar Ecol Prog Ser 428: 245–258, 2011
Neigel JE (2002) Is FST obsolete? Conserv Genet 3:167–173
Pardo LM, MacKay I, Oostra B, van Duijn CM, Aulchenko YS
(2005) The effect of genetic drift in a young genetically
isolated population. Ann Hum Genet 69:288–295
Piry S, Luikart G, Cornuet JM (1999) BOTTLENECK: A com-
puter program for detecting recent reductions in the effec-
tive population size using allele frequency data. J Hered
90:502–503
Polato NR, Concepcion GT, Toonen RJ, Baums IB (2010) Iso-
lation by distance across the Hawaiian Archipelago in
the reef-building coral Porites lobata. Mol Ecol 19:
4661–4677
Pritchard JK, Wen, X, Falush D (2007) Documentation for struc-
ture software: Version 2.2. Available at http:// pritch. bsd.
uchicago.edu/software/structure22/readme.pdf, accessed on
05 May 2010
Qiu B, Joyce TM (1992) Interannual variability in the mid-
and low-latitude western North Pacific. J Phys Oceanogr
22: 1062–1079
Randall JE (1998) Zoogeography of shore fishes of the Indo-
Pacific region. Zool Stud 37:227–268
Randall JE (2007) Reef and shore fishes of the Hawaiian
Islands. University of Hawaii Press, Honolulu
Raymond M, Rousset F (1995) An exact test for population dif-
ferentiation. Evolution 49:1280–1283
Reece JS, Bowen BW, Joshi K, Goz V, Larson L (2010) Phylo-
geography of two moray eels indicates high dispersal
throughout the Indo-Pacific. J Hered 101:391–402
Rivera MJ, Andrews KR, Kobayashi DR, Wren JLK, Kelley C,
Roderick GK, Toonen RJ (2011) Genetic analyses and sim-
ulations of larval dispersal reveal distinct populations and
directional connectivity across the range of the Hawaiian
grouper (Epinephelus quernus). J Mar Biol 2011:1–11
Rocha LA, Rocha CR, Robertson DR, Bowen BW (2008) Com-
parative phylogeography of Atlantic reef fishes indicates
both origin and accumulation of diversity in the
Caribbean. BMC Evol Biol 8:157.1–157.16
Rogers AR, Harpending H (1992) Population growth makes
waves in the distribution of pairwise genetic differences.
Mol Biol Evol 9:552–569
RoyChoudhury A, Stephens M (2007) Fast and accurate esti-
mation of the population-scaled mutation rate, θ, from
microsatellite genotype data. Genetics 176:1363–1366
Rozas J, Sanchez-DelBarrio JC, Messeguer X, Rozas R (2003)
DnaSP, DNA polymorphism analyses by the coalescent
and other methods. Bioinformatics 19:2496–2497
Selkoe KA, Toonen RJ (2006) Microsatellites for ecologists: a
practical guide to using and evaluating microsatellite
markers. Ecol Lett 9:615–629
Selkoe KA, Watson JR, White C, Ben Horin T and others
(2010) Taking the chaos out of genetic patchiness:
seascape genetics reveals ecological and oceanographic
drivers of genetic patterns in three temperate reef species.
Mol Ecol 19:3708–3726
Seutin G, White BN, Boag PT (1991) Preservation of avian
blood and tissue samples for DNA analyses. Can J Zool 69:
82–90
Skillings DJ, Bird CE, Toonen RJ (2011) Gateways to Hawai’i:
genetic population structure of the tropical sea cucumber
Holothuria atra. J Mar Biol 2011:1–16.
Slatkin M (1993) Isolation by distance in equilibrium and non-
equilibrium populations. Evolution 47:264–279
Sokal RR, Rohlf FJ (1981) Taxonomic congruence in the Lepto -
podomorpha re-examined. Syst Zool 30:309–325
Song CB, Near TJ, Page JM (1998) Phylogenetic relations
among percid fishes as inferred from mitochondrial cyto-
chrome bDNA sequence data. Mol Phylogenet Evol 10:
343–353
Sunnucks P, Hales DF (1996) Numerous transposed se -
quences of mitochondrial cytochrome oxidase I-II in
aphids of the genus Sitobion (Hemiptera: Aphididae). Mol
Biol Evol 13:510–524
Taberlet P, Meyer A, Bouvet J (1992) Unusual mitochondrial
DNA polymorphism in two local populations of blue tit
Parus caeruleus. Mol Ecol 1:27–36
Timmers MA, Andrews KR, Bird CE, deMaintenon MJ,
Brainard RE, Toonen RJ (2011) Widespread dispersal of
the crown-of-thorns sea star, Acanthaster planci, across
the Hawaiian Archipelago and Johnston Atoll. J Mar Biol
2011: 1–10.
Tissot BN, Hallacher LE (2003) Effects of aquarium collectors
on coral reef fishes in Kona, Hawaii. Conserv Biol 17:
1759–1768
Tissot BN, Williams JW, Hallacher LE (2004) Evaluating effec-
tiveness of a marine protected area network in west
Hawai’i to increase productivity of an aquarium fishery.
Pac Sci 58:175–188
Toonen RJ, Pawlik JR (2001) Settlement of the gregarious
tube worm Hydroides dianthus (Polychaeta: Serpulidae). I.
Gregarious and nongregarious settlement. Mar Ecol Prog
Ser 224:103–114
Toonen RJ, Andrews KR, Baums I, Bird CE and others (2011)
Defining boundaries for ecosystem-based management: A
multispecies case study of marine connectivity across the
Hawaiian Archipelago. J Mar Biol 2011:1–13
Ujiie Y, Ujiie H, Taira A, Nakamura T, Oguri K (2003) Spatial
and temporal variability of surface water in the Kuroshio
source region, Pacific Ocean, over the past 21,000 years:
evidence from planktonic foraminifera. Mar Micropaleon-
tol 49:335–364
van Oosterhout CV, Hutchinson W, Wills D, Shipley P (2004)
MICRO-CHECKER: software for identifying and correcting
genotyping errors in microsatellite data. Mol Ecol Notes
4:535–538
Walsh WJ (1987) Patterns of recruitment and spawning in
Hawaiian reef fishes. Environ Biol Fishes 18:257–276
White C, Selkoe KA, Watson J, Siegel DA, Zacherl DC, Too-
nen RJ (2010) Ocean currents help explain population
genetic structure. Proc R Soc B 277:1685–1694
Williams ID, Walsh WJ, Claisse JT, Tissot BN, Stamoulis KA
(2009) Impacts of a Hawaiian marine protected area net-
work on the abundance and fishery sustainability of the
yellow tang, Zebrasoma flavescens. Biol Conserv 142:
1066–1073
258
Editorial responsibility: John Choat,
Townsville, Australia
Submitted: September 16, 2010; Accepted: February 11, 2011
Proofs received from author(s): April 22, 2011
➤
➤➤
➤
➤
➤
➤➤
➤
➤➤
➤
➤➤
➤➤
➤➤
➤➤
➤
➤
➤
➤➤
➤
➤➤
➤
➤
➤
➤
➤
➤
➤
➤
➤➤
