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Genetic structure among spawning aggregations of the gulf coney Hyporthodus acanthistius

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Many large groupers form spawning aggregations, returning to the same spawning sites in consecutive spawning seasons. Connectivity between spawning aggregations is thus assured by larval dispersal. This study looks into the genetic structure and gene flow among spawning aggregations of a large grouper, the gulf coney Hyporthodus acanthistius, in the northern Gulf of California. First, using the mitochondrial control region and 11 microsatellites, we calculated FST metrics and conducted a Bayesian clustering analysis to determine structure among 5 spawning aggregations. Shallow genetic structure was found, separating the southernmost spawning aggregate from the remainder. Second, we used the results from the structure analysis and local water circulation patterns to delineate 3 distinct models of gene flow. The best-supported model, in which the southernmost spawning aggregate formed one group and all other spawning aggregates were nested into a second group, was the one that was consistent with water circulation during the species’ spawning season. Larval retention within a seasonal anticyclonic gyre that formed during the gulf coney’s spawning season may be responsible for the patterns found. This study highlights the importance of local oceanographic conditions in dictating the structure among spawning aggregations even at small geographic scales and contributes to informed management plans for this overexploited grouper.
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MARINE ECOLOGY PROGRESS SERIES
Mar Ecol Prog Ser
Vol. 499: 193–201, 2014
doi: 10.3354/meps10637 Published March 3
INTRODUCTION
Knowledge of how genetic variation is partitioned
in the ocean is fundamental for understanding the
ecology, conservation and management of marine
resources (Mora & Sale 2002, Gell & Roberts 2003,
Cowen et al. 2007, Francis et al. 2007, Planes et
al. 2009). One of the strongest drivers of genetic struc-
ture is connectivity, i.e. the demographic linking of lo-
cal populations via the dispersal of larvae, juveniles
or adults (Sale et al. 2005), which influences almost
all ecological and evolutionary processes in meta -
populations (Hanski & Gaggiotti 2004). Genetic
connectivity has been shown across a range of geo-
graphical scales among different marine taxa, ranging
from virtually panmictic throughout considerably
large geographic ranges (Bowen et al. 2001, Lessios et
al. 2003, Klanten et al. 2007, Beldade et al. 2009, Leray
© Inter-Research 2014 · www.int-res.com*Corresponding author: rbeldade@gmail.com
Genetic structure among spawning aggregations of
the gulf coney Hyporthodus acanthistius
Ricardo Beldade1, 2, 3, 4,*, Alexis M. Jackson1, Richard Cudney-Bueno5, 6,
Peter T. Raimondi1, Giacomo Bernardi1
1Department of Ecology and Evolutionary Biology, University of California Santa Cruz, 100 Shaffer Road, Santa Cruz,
California 95060, USA
2USR 3278 CRIOBE, CNRS EPHE, CBETM de l’Université de Perpignan, 66860 Perpignan Cedex, France
3Laboratoire d’excellence ‘Corail’, USR 3278 CRIOBE CNRS-EPHE, 66860 Perpignan Cedex, France
4Universidade de Lisboa, Faculdade de Ciências, Centro de Oceanografia, Campo Grande, 1749-016 Lisboa, Portugal
5School of Natural Resources and the Environment, University of Arizona, Biological Sciences East, Room 325, Tucson,
Arizona 85721, USA
6Institute of Marine Sciences, University of California Santa Cruz, 100 Shaffer Road, Santa Cruz, California 95060, USA
ABSTRACT: Many large groupers form spawning aggregations, returning to the same spawning
sites in consecutive spawning seasons. Connectivity between spawning aggregations is thus
assured by larval dispersal. This study looks into the genetic structure and gene flow among
spawning aggregations of a large grouper, the gulf coney Hyporthodus acanthistius, in the north-
ern Gulf of California. First, using the mitochondrial control region and 11 microsatellites, we cal-
culated FST metrics and conducted a Bayesian clustering analysis to determine structure among
5 spawning aggregations. Shallow genetic structure was found, separating the southernmost
spawning aggregate from the remainder. Second, we used the results from the structure analysis
and local water circulation patterns to delineate 3 distinct models of gene flow. The best-sup-
ported model, in which the southernmost spawning aggregate formed one group and all other
spawning aggregates were nested into a second group, was the one that was consistent with
water circulation during the species’ spawning season. Larval retention within a seasonal anti -
cyclonic gyre that formed during the gulf coney’s spawning season may be responsible for the pat-
terns found. This study highlights the importance of local oceanographic conditions in dictating
the structure among spawning aggregations even at small geographic scales and contributes to
informed management plans for this overexploited grouper.
KEY WORDS: Grouper · Dispersal · Connectivity · Sea of Cortez · Oceanography · Eddies ·
Retention · Migration models · Rooster hind · Epinephelus
Resale or republication not permitted without written consent of the publisher
Mar Ecol Prog Ser 499: 193–201, 2014
et al. 2010) to clearly structured populations at very
small scales (Sotka et al. 2004, Bernardi 2005, Barber
et al. 2006, Gerlach et al. 2007, Beldade et al. 2012).
Many fish form spawning aggregations (i.e. groups
of conspecific fish that gather for the purpose of
spawning, with densities or numbers significantly
higher than those found in the area of aggregation
during non-reproductive periods; Domeier & Colin
1997), including groupers, snappers, jacks, surgeon-
fishes, damselfishes and parrotfishes (Sala et al.
2003, Erisman et al. 2007, Gladstone 2007, Sadovy
de Mitcheson et al. 2008, Gerhardinger et al. 2009).
Some groupers return to the same spawning sites in
consecutive spawning seasons (Sala et al. 2001, Starr
et al. 2007), in some cases covering large distances
to do so (Bolden 2000). If adult spawning aggrega-
tion site fidelity is indeed ubiquitous among large
groupers, then the dispersal of the pelagic larval
stages that are subjected to transport by ocean cur-
rents should be the main driver of genetic connec -
tivity. Two elements underline the importance of
oceanographic characteristics to the dispersal of
spawning aggregation offspring. First, the specific
location of spawning aggregations appears to maxi-
mize the rapid advection of eggs and larvae away
from the reef environment (e.g. Choat 2012, Colin
2012a). Second, knowledge of the onset of sensorial
and swimming abilities of pelagic larvae, which in
the case of groupers is still largely unknown, is
essential to understand how larval abilities might
steer the dispersal process (e.g. Colin 2012b, Hamner
& Largier 2012). Larval abundance and even the
magnitude of recruitment events appear to be corre-
lated with oceanographic and climatic parameters,
such as temperature, salinity and depth (but see e.g.
Aburto-Oropeza et al. 2010, Marancik et al. 2012).
The northern Gulf of California (NGC) is home to
several fishes that aggregate to spawn and is part of
one of the most productive marine ecosystems in
the world, contributing most of Mexico’s fishery re -
sources (Arvizu-Martínez 1987, Lluch-Cota et al.
2007, Erisman et al. 2012). The NGC covers a rela-
tively small area extending from the Colorado delta
in the north to Bahia de Los Angeles and Isla Tiburon
in the south (Fig. 1). In this region, in-depth know -
ledge of water circulation patterns and other geomor-
phological characteristics (Fig. 1) provide a unique
opportunity to describe genetic structure and test
models of gene flow in locally occurring species. In
the NGC, the main oceanographic features comprise
intense tidal mixing (Argote et al. 1995) and a sea-
sonally reversing gyre, anticyclonic in summer (June
to September) (Fig. 1B) and cyclonic in winter
(Fig. 1C) (Lavín et al. 1997, Marinone et al. 2008);
strong coastal currents along the eastern Sonora
coastline (Peguero-Icaza et al. 2011); and small resid-
ual currents and small eddies in the upper gulf (Mari-
none et al. 2011). These characteristics are likely to
influence the transport of larvae in the NGC (Mari-
none et al. 2004, Cudney-Bueno et al. 2009). Both
local water circulation and bottom geomorphologic
characteristics may have important implications for
the formation of spawning aggregations as well as for
the fate of eggs or larvae released there (Cherubin et
al. 2011, Karnauskas et al. 2011). In the NGC, there
are 2 deep basins, the Delfin Basin (800 m) and the
Wagner Basin (200 m), and several sills (Lavín et al.
1997) whose putative part in limiting dispersal of lar-
vae or concentrating prey for early larval stages
remains unclear (e.g. Karnauskas et al. 2011).
The gulf coney Hyporthodus acanthistius (formerly
Epinephelus acanthistius; Craig & Hastings 2007) is a
194
Fig. 1. Northern Gulf of California (NGC) including (A) bathymetry (depth in meters) and named sampled spawning aggrega-
tions of the gulf coney Hyporthodus acanthistius (PLI, Puerto Libertad; PLO, Puerto Lobos; STO, Santo Tomas; PPE, Puerto
Peñasco; and SLG, San Luiz Gonzaga); (B) ocean circulation in the summer (only the month of July is represented); and (C) in
the winter (only the month of January is represented). Ocean circulation reproduced from Marinone (2003) by permission of the
American Geophysical Union
Beldade et al.: Genetic structure among grouper spawning aggregations
tropical and subtropical large grouper that occurs
from southern California to Peru (Heemstra & Ran-
dall 1993), including the Gulf of California (or Sea of
Cortez) (Cudney-Bueno & Turk-Boyer 1998, Aburto-
Oropeza et al. 2008). It is found at depths greater
than ~45 m usually in silty areas adjacent to rocky
reefs (Thomson et al. 2000), and spawns in aggre -
gations on muddy bottoms during the spring and
summer months (Cudney-Bueno & Turk-Boyer 1998).
During the spawning period, artisanal fishermen
heavily target this species (Aburto-Oropeza et al.
2008). Indeed, the high commercial value and tempo-
ral and spatial predictability of their mass gatherings
make groupers a prime target for fisheries. Despite
its present ‘Least Concern’ conservation status (IUCN
2012), the abundance of the gulf coney in the NGC
has been rapidly declining over the past 2 decades
(Aburto-Oropeza et al. 2008). Elsewhere, there are
many examples of collapsed grouper spawning
aggregations because of overfishing such as the Nas-
sau grouper E. striatus (e.g. Sala et al. 2001, Aguilar-
Perera 2006) and the gulf grouper Mycteroperca jor-
dani (Sáenz-Arroyo et al. 2005). Given the threat of
overfishing to fish that form spawning aggregations
(Sadovy de Mitcheson et al. 2013), it is imperative to
provide connectivity data to devise informed man-
agement plans.
In this study, we integrate molecular evidence from
highly variable molecular markers (control region
and 11 microsatellites) to assess genetic structure
and connectivity among spawning aggregations of
the gulf coney in the NGC. Oceanographic and geo-
morphological regional characteristics are used to
delineate particular models of gene flow across the
spawning aggregation network. This study provides
essential information for the management and re -
covery of this threatened fishery in the NGC.
MATERIALS AND METHODS
Sampling and DNA extraction
Fin clips of Hyporthodus acanthistius were collected
in 2003 aboard fishing boats that operated at 5 spawn-
ing locations in the NGC: Puerto Libertad, Puerto
Lobos, Santo Tomás, Puerto Peñasco, and San Luiz
Gonzaga (Fig. 1). Immediately after collection, fin
clips were placed in 95% ethanol and stored at ambi-
ent temperature in the field and then at 4°C in the lab.
Total genomic DNA was extracted from 20 mg of fin
tissue by Proteinase K digestion in lysis buffer (10 mM
Tris, 400 mM NaCl, 2 mM EDTA, 1% sodium dodecyl
sulfate) overnight at 55°C. This was followed by
purification using phenol/chloroform ex tractions and
alcohol precipitation (Sambrook et al. 1989).
mtDNA and microsatellites
We amplified the 5’ end of the hyper-variable por-
tion of the mitochondrial control region using the
universal primers CR-A and CR-E (Lee et al. 1995).
Each 100 µl reaction contained 10 to 100 ng of DNA,
10 mM Tris HCl (pH 8.3), 50 mM KCl, 1.5 mM MgCl2,
2.5 units of Taq DNA polymerase (Perkin-Elmer),
150 mM of each dNTP, and 0.3 mM of each primer
and was amplified with a cycling profile of 45 s at
94°C, 1 min at 52°C and 1 min at 72°C for 35 cycles.
After purification of amplified DNA genes following
the manufacturer’s protocol (ABI, Perkin-Elmer), we
sequenced on an ABI 3100 automated sequencer
(Applied Biosystems).
All individuals were genotyped for 13 microsatel-
lites following protocols described in Molecular Eco -
logy Resources Primer Development Consortium et
al. (2009). Each individual was genotyped using
GENE MAPPER 3.7 (Applied Biosystems). To estimate
potential genotyping errors, we re-amplified and re-
scored 21 randomly picked samples and evaluated
concordance between the first and second score.
Overall, the genotyping error rate was less than 2%,
which is reasonable for population differentiation
studies based on allele frequencies (Bonin et al. 2004),
and less than 2% of data were missing for any given
locus. Data were scanned for null alleles and stutter-
ing using MICROCHECKER 2.2.3 (van Oosterhout et
al. 2004) and for deviations from Hardy-Weinberg
equilibrium (HWE) and linkage disequilibrium after
10 000 permutations using ARLEQUIN 3.5 (Excoffier
& Lischer 2010). Two micro satellites, EAC_ A08 and
EAC_B08, were dropped from the ana lysis because of
the putative presence of null alleles.
Genetic diversity and genetic structure among
spawning aggregations
Genetic diversity measures for each population
including number of haplotypes, haplotype diver-
sity and nucleotide diversity were calculated with
DNAsp 5 (Librado & Rozas 2009). To assess popula-
tion structure, we used 2 separate approaches. In the
first, more classical approach, fixation indices (FST)
relying on allele frequencies were calculated using
ARLEQUIN 3.5 (Excoffier & Lischer 2010). We calcu-
195
Mar Ecol Prog Ser 499: 193–201, 2014
lated 95% confidence intervals around the FST esti-
mates using GDA 1.1 (Lewis & Zaykin 2001), rather
than just p-values, as these may not be good indica-
tors of differentiation between populations and are
dependent on sample size and variability (Jost 2008).
In the second approach, we used a Bayesian model-
based clustering method using microsatellite data im -
plemented in STRUCTURE 2.3.2 (Falush et al. 2007).
STRUCTURE assumes that there are knumber of
groups within which samples have compatible multi-
locus genotypes. Convergence of parameters (α, Fand
likelihood) in preliminary runs was used to deter-
mine the burn-in (500 000) and length (1 000 000) of
each run. For our analysis, we used an admixture
model, which allows individuals to have mixed
ancestry, and added sampling location as a weak
prior (Falush et al. 2007). Then we performed 10
replicate runs for each cluster kvarying between 1
and 6. To determine the correct number of clusters
in the sample, we followed Evanno et al. (2005), who
proposed the use of an ad hoc statistic Δkbased on
the rate of change in the log probability of data
between successive kvalues. STRUCTURE HAR-
VESTER was used to calculate Evanno’s Δkand illus-
trate the differences in likelihood and Δkfor each k
(Earl & VonHoldt 2012). A Q plot was chosen to illus-
trate differences between populations, where each
single vertical line (representing 1 individual) is par-
titioned into k-colored segments that represent that
indi vidual’s estimated membership fraction in each
of the k-inferred clusters (Pritchard et al. 2000).
Direction and magnitude of gene flow among
spawning aggregations
To determine the pervasive migration pattern in
the study area, we used MIGRATE-N 3.2.16 (Beerli
& Palczewski 2010) to contrast 3 migration models.
In all 3 models, spawning aggregates were nested
according to the genetic structure suggested by the
FST and structure analysis. Based on well-described
local oceanographic circulation, we defined the di -
rection of gene flow for each model as follows: (1) an
unrestricted full migration model, (2) a model consid-
ering 2 population sizes and unidirectional north-
ward gene flow and (3) a model considering 2 pop -
ulation sizes and unidirectional southward gene
flow. Model 2 was delineated taking into account
that Hyporthodus acanthistius spawns in the spring-
summer, during which time anticyclonic circulation
forces the water to flow northward on the eastern
side of the NGC (see Fig. 1B) (Marinone 2012). Model
3 depicts the autumn-winter cyclonic water circula-
tion pattern, which forces the water to flow south-
ward (see Fig. 1C) (Marinone 2012).
MIGRATE-N provides the ratio of the marginal
likelihoods (Bayes factors) of each model, which can
subsequently be compared to select the most sup-
ported model (Beerli & Palczewski 2010). The best-
supported model will have the highest log Bayes fac-
tors. This approach is particularly suited to our data
because local hydrodynamics allow for a clear expec-
tation of unidirectional gene flow in the study area
and the nesting of aggregates reduces the number
of parameters to be estimated from the data, thus
increasing the power of the approach. A random sub-
set of 30 samples from each of the 2 populations
identified previously was used to compare the mod-
els. The mitochondrial locus was not used to test the
models of gene flow because of its limited capability,
as it is a single locus, for distinguishing the models.
A series of preliminary runs using Model 1, the
unrestricted model, were used to determine con -
vergence of posterior probabilities for each of the
parameters. Running conditions chosen included
1 000 000 recorded steps, 10 long chains and 15
heated chains, a static heating scheme with the
inverse of the temperature regularly spaced between
0 and 1 and a tree swapping interval of one; finally,
the upper prior boundary for northward migration
was set to vary between 0 and 10 000. The natural
logarithm of Bayes factors with a Bezier approxima-
tion was calculated following Beerli & Palczewski
(2010) as well as each model’s probability by dividing
each marginal likelihood by the sum of the marginal
likelihoods of both models used. The best-supported
model will be the one with the highest probability
(Beerli & Palczewski 2010).
RESULTS
Genetic diversity
We obtained 232 sequences for a 361 bp frag -
ment of the mitochondrial control region (Genbank
KF425014 to KF425245). The sequences analyzed
here had 133 polymorphic sites, 54 of which were
informative. Genetic diversity was high for almost all
spawning aggregations (Table 1). Genetic diversity
was also calculated for the microsatellites from 246
individuals and included number of alleles, ratio of
homozygotes to heterozygotes per locus, as well as
HWE tests (Table S1 in the Supplement, available at
www.int-res.com/articles/suppl/m499p193_supp.pdf).
196
Beldade et al.: Genetic structure among grouper spawning aggregations
Genetic structure of spawning aggregations
Low pairwise FST values were found across both
genetic markers (Table 2). In spite of the significant
differences found between pairs of FST estimates
derived from microsatellites, 95% confidence inter-
vals precluded any conclusion regarding the struc-
ture between Puerto Libertad and either Santo
Tomás or Puerto Peñasco population pairs (Table 2).
Differentiation between the southernmost aggrega-
tion of Puerto Libertad and the remaining aggrega-
tions was identified through the Bayesian clustering
method (Fig. 2). Evanno’s Δkbased on the mean and
standard deviation of likelihoods, L(k), for each kwas
highest for k= 2 (Fig. 3), confirming that k= 2 is the
best representation of the genetic partitioning in the
data. Assessment of convergence examples of skyline
plots of log(α) are given in the Supplement (Fig. S1).
Gene flow between spawning aggregations
Model 2 was the most supported migration model,
as demonstrated by the highest value for the natural
logarithm of the Bayes’ factors (Table 3). Estimates
of population size and number of migrants between
the defined populations as well as parameter conver-
gence are given in the Supplement (Table S2). Our
analysis aligns well with the summer anticyclonic
gyre used to delineate Model 2, which is consistent
with both magnitude and direction of the gulf coney’s
gene flow in the NGC. This
period coincides with the
pelagic phase of the Hypor -
tho dus acan thistius larvae.
The full migration model
comes second to Model 2
because of the unrestricted
mi gra tion between the pop-
ulations to the north of
Puerto Libertad. Finally,
Model 3, in which gene flow
follows the winter cyclonic
water movement patterns
described for the area,
scored the lowest in ex -
plaining larval mi gration in
the area.
197
Sampling site n nhhdπ
Puerto Libertad 53 18 0.839 0.0061
Puerto Lobos 62 27 0.911 0.0072
Santo Tomás 21 10 0.914 0.0068
Puerto Peñasco 55 17 0.902 0.0061
San Luiz Gonzaga 41 16 0.871 0.0065
Total 232 47 0.886 0.0066
Table 1. Collection sites, number of mitochondrial control
region sequences used (n) and molecular diversity indices
(number of haplotypes, nh; haplotype diversity, hd; and
nucleotide diversity, π) for Hyporthodus acanthistius
PLI PLO STO PPE SLG
PLI 0.003 0.003 0.002 0.005
[0.000 to 0.007] [−0.005 to 0.009] [0.000 to 0.018] [0.002 to 0.020]
PLO 0.04254 0 0.001 0.003
[−0.001 to 0.009] [−0.003 to 0.003] [−0.001 to 0.005]
STO 0.03838 0.00049 −0.003 −0.005
[−0.005 to 0.001] [−0.008 to −0.002]
PPE 0.07154 0.00045 0.0052 −0.001
[−0.003 to 0.002]
SLG 0.00561 0.01327 0.01133 0.02289
Table 2. Population structure estimated by FST between Hyporthodus acanthistius popu-
lations calculated from the mitochondrial control region (below left) and from 11 mi-
crosatellites (above right) with 95% confidence intervals between brackets. Significant
pairwise FST (at p < 0.05) after 10 000 permutations shown in bold. PLI, Puerto Libertad;
PLO, Puerto Lobos; STO, Santo Tomás; PPE, Puerto Peñasco; SLG, San Luiz Gonzaga
Fig. 2. Q-plot of the Bayesian population assignment test based on 11 microsatellite loci. Each vertical line represents a single
Hyporthodus acanthistius individual; black/gray in each vertical line represent the likelihood of belonging to each of the
clusters. Black vertical lines separate the spawning aggregations; population acronyms are defined in Fig. 1
Mar Ecol Prog Ser 499: 193–201, 2014
DISCUSSION
Genetic structure, hydrodynamics and site fidelity
In groupers, genetic differentiation of spawning
aggregations has been observed but usually at large
geographic scales (e.g. Rhodes et al. 2003, Rivera et
al. 2004, Zatcoff et al. 2004). In this study, FST statistics
based on mtDNA and microsatellites as well as
Bayesian analysis were consistent in showing weak
structure at a much smaller scale. In scenarios of weak
genetic partitioning, FST metrics and Bayesian analysis
have limited power in asserting structure (e.g. Waples
& Gaggiotti 2006). In the present study, the inclusion
of zero within the calculated FST 95% confidence in-
tervals for 2 of the pairwise comparisons between
Puerto Libertad and the other populations, and the
limited capacity for Evanno’s Δkto distinguish be-
tween a panmictic population (k= 1) and the genetic
structure suggested (k= 2) as well as similar posterior
probabilities for the same kvalues, have to be ac-
knowledged. Nonetheless, the concordance between
markers and analysis in showing that within the NGC,
the southernmost spawning aggregation sampled,
Puerto Libertad, was slightly distinct from all others
lends support to this conclusion. Hence, we present
evidence for structure between spawning aggrega-
tions at a small geographic scale. Furthermore, while
unimportant over evolutionary time scales, weak ge-
netic structure can have important implications in
ecology and conservation biology (Jones & Wang 2012).
Given that the NGC covers such a small geo-
graphic area, it was unexpected to observe even
weak population structure among spawning aggrega-
tions that are so close geographically. The spawning
aggregation at Puerto Libertad was only 40 km from
the closest spawning aggregation at Puerto Lobos.
Hydrodynamic features of the study area during the
dispersive stage of the gulf coney’s larvae are also
consistent with our results, as the southernmost
spawning aggregation is the only one that sits just
outside of the summer anticyclonic gyre. This sea-
sonal gyre may trap the larvae originating from all
other spawning aggregations, preventing them from
travelling south. Eddies may entrap fish eggs and
larvae both in the open ocean (e.g. Holliday et al.
2011) and in enclosed seas (e.g. Contreras-Catala et
al. 2012). Simultaneously, the northward currents
described for the Puerto Libertad spawning aggrega-
tion site will transport larvae northward. The genetic
differentiation of Puerto Libertad may also be recon-
ciled with some level of site fidelity. While there are
no published accounts of site fidelity or home range
for Hyporthodus acanthistius, several grouper spe-
cies such as Epinephelus tauvina (Kaunda-Arara &
Rose 2004) have some degree of site fidelity. Other
examples have come from tagging studies of E. stria-
tus, in which distances traveled to spawning sites
ranged from 30 km (Sala et al. 2001) to upwards of
100 km (Carter et al. 1994, Bolden 2000). Movement
at even the smallest of these scales could be very rel-
evant within the NGC. The potential homogenizing
effects of dispersing larvae are best explained by the
study of gene flow.
Gulf coney’s gene flow in the NGC
The most supported model for the genetic ex -
change among spawning aggregations of gulf coney
198
Model No. Bezier Harmonic Choice Model
lmL lML (Bezier) probability
1 −4482.37 −4297.46 2 0.000
2 −4353.63 −4134.17 1 1.000
3 −5018.29 −4871.79 3 0.000
Table 3. Natural log Bayes factors (lmL) and log marginal
likelihoods (lML) for each gene flow model estimated by
thermodynamic integration using 11 microsatellite markers.
Model details are explained in ‘Materials and methods’
Fig. 3. Mean and standard deviation of log likelihoods, L(k)
(d); and Evanno’s Δk(j) for each kvalue estimated in 10 in-
dependent runs in STRUCTURE. The highest Δkindicates
the choice of k= 2 as the one that best describes the genetic
partitioning in the data
Beldade et al.: Genetic structure among grouper spawning aggregations
depicts the anticyclonic summer gyre, which coin-
cides with the pelagic stage of this species’ larvae. In
the NGC, using a 3-dimensional baroclinic numerical
model, Marinone et al. (2008) followed particles re -
leased in this gyre and found the same south-north
direction of dispersal. Calderon-Aguillera et al. (2003)
showed how hydrodynamics in the NGC influenced
the dispersal of blue shrimp Litopenaeus stylirostris
larvae and more recently Cudney-Bueno et al. (2009)
reported similar circulation patterns and enhanced
recruitment of rock scallop Spondyllus calcifer larvae
and black murex Hexaplex nigritus larvae coming
from the south of the NGC and settling into marine
reserves located to the north. The currents along the
eastern shore of the NGC may reach speeds of up to
0.06 m s–1 during the summer (Cudney-Bueno et al.
2009), which, considering a planktonic larval dura-
tion of approximately 30 d for the gulf coney in the
NGC (K. Rowell, Biology Department, University of
Washington, pers. comm.), would easily allow them
to disperse between adjoining spawning aggre gates
and even beyond. Within 4 wk, larvae may travel the
148 km distance that separates Puerto Libertad and
Puerto Peñasco, the southernmost and northernmost
spawning aggregations.
Management of spawning aggregations
Our study highlights the importance of detailing
the genetic structure and gene flow between spawn-
ing aggregations even at small geographic scales
where panmixia is expected. The weak genetic
structure found here can have important implications
in ecology and conservation biology of this species.
Management programs for the gulf coney in the
NGC should reinforce protection of the southernmost
spawning aggregation near Puerto Libertad. Both
shallow genetic structure and an anticyclonic direc-
tion of gene flow suggest that Puerto Libertad is a
source population, primarily exporting larvae north
into the NGC. Oceanographic data suggest that
Puerto Libertad may also play an important role as a
gateway for larvae and gene flow originating from
the middle gulf (e.g. Danell-Jiménez et al. 2009). If
this pattern proves to be true, overfishing in the mid-
dle gulf region may have dire consequences for the
populations in the NGC.
Acknowledgements. We thank the Intercultural Center for
the Study of Deserts and Oceans (CEDO), especially R.
Loiaza, I. Martinez and A. Sanchez; as well as Community
and Biodiversity, AC (COBI) especially N. Encinas, C.
Moreno and M. Rojo. We also thank 2 anonymous reviewers
who provided helpful comments on an earlier version of
the manuscript. Funding for this study was provided by the
David and Lucile Packard Foundation, grant award #2008-
32210. R.B. was also funded by the Fundação para a Ciência
e a Tecnologia (SFRH/BPD/26901/2006). Collecting permits
for this study were issued by SAGARPA under the National
Commission for Aquaculture and Fisheries, permit #2885.
This is a scientific contribution to the PANGAS project (www.
pangas.arizona.edu).
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Editorial responsibility: Per Palsbøll,
Groningen, The Netherlands
Submitted: January 24, 2013; Accepted: November 3, 2013
Proofs received from author(s): February 15, 2014
... The use of molecular techniques to investigate genetic diversity, population structure and connec- tivity in marine ecosystems has increased substan- tially over the last 2 decades (Shulman & Bermingham 1995, Palumbi 2004, Cowen et al. 2006, Craig & Hastings 2007, Harrison et al. 2012, Beldade et al. 2014, Jackson et al. 2015). Molecular methods are now being applied in the assessments of population structure and genetic diversity (Silva-Oliveira et al. 2008), investigating evolutionary processes and local adaptation to natural or anthropogenic stressors ( Paris et al. 2015), exploring genes controlling or reg- ulating diseases ( Teng et al. 2008), understanding sexual development ( Luo et al. 2010), informing con- servation management plans ( Reiss et al. 2009) and in predicting the impacts of climate change (Nielsen et al. 2009, Davey et al. 2011, Horreo et al. 2011, Narum et al. 2013, Hemmer-Hansen et al. 2014). ...
... Although evidence of population structuring has been documented in coral reef fish (e.g. Shulman & Bermingham 1995, Bay et al. 2008, only a few studies have assessed population structure in Epi- nephelinae groupers ( Rivera et al. 2004, Zatcoff et al. 2004, Maggio et al. 2006, Silva-Oliveira et al. 2008, Beldade et al. 2014, Jackson et al. 2014, 2015 and there is a paucity of information regarding genotypic variation within and among spawning aggregations generally. ...
... Although evidence of population structuring has been documented in coral reef fish (e.g. Shulman & Bermingham 1995, Bay et al. 2008, only a few studies have assessed population structure in Epi- nephelinae groupers ( Rivera et al. 2004, Zatcoff et al. 2004, Maggio et al. 2006, Silva-Oliveira et al. 2008, Beldade et al. 2014, Jackson et al. 2014, 2015 and there is a paucity of information regarding genotypic variation within and among spawning aggregations generally. ...
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... Besides the gaps in habitat, other studies have found that at scales <1,000 km the larval dispersal and recruitment were the main processes affecting genetic structure (Berkström et al., 2020;Dalongeville et al., 2018;Pascual et al., 2017;Schunter et al., 2019).The general lack of genetic structure in the GC could be related to seasonally-reversing surface currents and mesoscale eddies (Lavín and Marinone, 2003). that transport fish larvae, creating different patterns of metapopulation structure that tend to homogenize allele frequencies (Beldade et al., 2014;Cisneros-Mata et al., 2018;Lodeiros et al., 2016;Munguia-Vega et al., 2014, 2018aReguera-Rouzaud et al., 2020;Soria et al., 2012). However, swimming behaviour, different settlement success and topography, like the narrow continental shelf or very steep slopes, could also contribute to genetic differences (Sefc et al., 2020). ...
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The tropical Eastern Pacific (TEP) is a highly dynamic region and a model system to study how habitat discontinuities affect the distribution of shorefishes, particularly for species that display ontogenetic habitat shifts, including snappers (Lutjanidae). To evaluate the genetic structure of the Pacific red snapper (Lutjanus peru) and the yellow snapper (Lutjanus argentiventris) throughout their distribution range along the TEP, 13 and 11 microsatellite loci were analyzed, respectively. The genetic diversity of L. peru (N = 446) and L. argentiventris (N = 170) was evaluated in 10 and five localities, respectively, showing slightly higher but non‐significant values in the Gulf of California for both species. The genetic structure analysis identified the presence of significant genetic structure in both species, but the locations of the identified barriers for the gene flow differed between species. The principal driver for the genetic structure at large scales >2500 km was isolation by distance. At smaller scales (<250 km) the habitat discontinuity for juveniles and adults and the environmental differences throughout the distribution range represented potential barriers to gene flow between populations for both species. This article is protected by copyright. All rights reserved.
... Spawning in the Gulf of California occurs in the spring and summer months with a peak in July when fish form spawning aggregations on muddy bottoms (Cudney-Bueno and Turk-Boyer 1998, Aburto-Oropeza et al. 2008, Beldade et al. 2014. Spawning peaks occur in Colombia in July and February (Acevedo 1996). ...
... Advances in molecular biology and population genetics have proven to be extremely valuable in generating information on population status, genetic diversity and connectivity of a variety of fish species (Carvalho and Hauser, 1998;Silva-Oliveira et al., 2008;Davey et al., 2011;Adams et al., 2016;Garcia-Mayoral et al., 2016); in turn, these data have been applied to support population management and conservation efforts Beldade et al., 2014;Selkoe et al., 2016). In particular, the application of genetics for stock identification (Carvalho and Hauser, 1994) and estimates of effective population size, N e (Wright, 1931), combined with traditional fisheries stock assessment models (Hilborn and Walters, 1992) are emerging approaches for advancing conservation management of at-risk species (Luikart et al., 2010;Hare et al., 2011;Ovenden et al., 2016). ...
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Severe declines of endangered Nassau grouper (Epinephelus striatus) across The Bahamas and Caribbean have spurred efforts to improve their fisheries management and population conservation. The Bahamas is reported to hold the majority of fish spawning aggregations for Nassau grouper, however, the status and genetic population structure of fish within the country is largely unknown, presenting a major knowledge gap for their sustainable management. Between August 2014–February 2017, 464 individual Nassau grouper sampled from The Bahamas were genotyped using 15 polymorphic microsatellite loci to establish measures of population structure, genetic diversity and effective population size (Ne). Nassau grouper were characterized by mostly high levels of genetic diversity, but we found no evidence for geographic population structure. Microsatellite analyses revealed weak, but significant genetic differentiation of Nassau grouper throughout the Bahamian archipelago (Global FST 0.00236, p = 0.0001). Temporal analyses of changes in Ne over the last 1,000 generations provide evidence in support of a pronounced historic decline in Bahamian Nassau grouper that appears to pre-date anthropogenic fishing activities. M-ratio results corroborate significant reductions in Ne throughout The Bahamas, with evidence for population bottlenecks in three islands and an active fish spawning aggregation along with apparent signs of inbreeding at two islands. Current estimates of Ne for Nassau grouper are considerably lower compared with historic levels. These findings represent important new contributions to our understanding of the evolutionary history, demographics and genetic connectivity of this endangered species, which are of critical importance for advancing their sustainable management.
... In the GC, multiple seasonal oceanic gyres present within each of the main deep (1-3 km) basins shift direction at the beginning of the spring (March) and fall (October) seasons (Marinone et al. 2011;Marinone 2012). These gyres create a unique model system, where strongly asymmetric oceanic currents define a metapopulation structure, where upstream larval sources export larvae towards specific downstream locations, according to the spawning time and the direction of the predominant flow (Soria et al. 2012;Beldade et al. 2014;Munguia-Vega et al. 2015;Lodeiros et al. 2016). ...
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The dispersal during the planktonic larval period is a key feature to understand the metapopulation structure of marine fishes, and is commonly described by four general models: 1) lack of population structure due to extensive larval dispersal, 2) isolation by geographic distance where larval connectivity decreases with increasing distance between sites in all directions (isotropy), 3) population structure without any clear geographic trend (chaotic), 4) population structure explained by seascape approaches that explicitly incorporate the spatial and temporal variation in the direction and strength of oceanic currents via oceanographic modeling. We tested the four models in the Pacific red snapper Lutjanus peru, a key commercial species in the Gulf of California (GC), Mexico. We genotyped 15 microsatellite loci in 225 samples collected during 2015-2016 from 8 sites, and contrasted the observed empirical genetic patterns against predictions from each model. We found low but significant levels of population structure among sites. Only the seascape approach was able to significantly explain levels of genetic structure and diversity, but exclusively within spring and summer, suggesting this period represents the spawning season for L. peru. We showed that in the GC the strong asymmetry in the oceanic currents cause larval connectivity to show different values when measured in distinct directions (anisotropy). Management tools, including marine reserves, could be more effective if placed upstream of the predominant flow. Managers should consider that oceanographic distances describing the direction and intensity of currents during the spawning period are significant predictors of larval connectivity between sites, as opposed to geographic distances. The manuscript is available free to view here: http://rdcu.be/y7yr
... Though the sites included in our study are small and isolated, these eddies may serve to enhance self-recruitment, especially for species with short PLDs, and therefore increase genetic structure among sites. Oceanographic features such as seasonal eddies have been shown to drive genetic connectivity of reef fishes elsewhere (e.g., Beldade et al. 2014). The eddies in the narrowest part of the Mozambique Channel near Juan de Nova may increase retention rates of larvae with short durations, such as A. akallopisos. ...
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The Western Indian Ocean harbors one of the world’s most diverse marine biota yet is threatened by exploitation with few conservation measures in place. Primary candidates for conservation in the region are the Scattered Islands (Îles Éparses), a group of relatively pristine and uninhabited islands in the Mozambique Channel. However, while optimal conservation strategies depend on the degree of population connectivity among spatially isolated habitats, very few studies have been conducted in the area. Here, we use highly variable microsatellite markers from two damselfishes (Amphiprion akallopisos and Dascyllus trimaculatus) with differing life history traits [pelagic larval duration (PLD), adult habitat] to compare genetic structure and connectivity among these islands using classic population structure indices as well as Bayesian clustering methods. All classical fixation indexes FST, RST, G′ST, and Jost’s D show stronger genetic differentiation among islands for A. akallopisos compared to D. trimaculatus, consistent with the former species’ shorter PLD and stronger adult site attachment, which may restrict larval dispersal potential. In agreement with these results, the Bayesian analysis revealed clear genetic differentiation among the islands in A. akallopisos, separating the southern group (Bassas da India and Europa) from the center (Juan de Nova) and northern (Îles Glorieuses) islands, but not for D. trimaculatus. Local oceanographic patterns such as eddies that occur along the Mozambique Channel appear to parallel the results reported for A. akallopisos, but such features seem to have little effect on the genetic differentiation of D. trimaculatus. The contrasting patterns of genetic differentiation between species within the same family highlight the importance of accounting for diverse life history traits when assessing community-wide connectivity, an increasingly common consideration in conservation planning.
... Pearse and Crandall 2004;Hedgecock et al. 2007), or the degree to which gene flow affects evolutionary processes within populations (Lowe and Allendorf 2010), as well as historical and contemporary mechanisms driving divergence when connectivity is limited (Cowen and Sponaugle 2009). The extent of connectivity among established reserves, and the extent of genetic differentiation among organisms within them, may be influenced by a number of mechanisms including vicariance events (Bernardi et al. 2003;Riginos 2005), environmental differences (Riginos and Nachman 2001), oceanography (Soria et al. 2012;Beldade et al. 2014), and limited dispersal ability (Hurtado et al. 2010). ...
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Most reef fishes have bipartite life histories, separate pelagic-oceanic (egg/larvae) and benthic (juvenile/adult) periods. The several-week pelagic period has early planktonic (egg, yolk sac and preflexion larva) and later nektonic components (post-flexion larva to settlement); the plankton-nekton transition timing is variable. For aggregating species, larvae are weak swimmers early in life, but late stages are often strong swimmers able to perhaps influence their settlement locations. No obvious differences were found between larval stages of aggregating and non-aggregating species and both types of spawning are found within single families, and even within a species. There are no egg types, morphologies, feeding strategies or special structures exclusive to aggregating species. Initial dispersal is determined by location and time of spawning. Pelagic eggs are buoyant, keeping them in near-surface waters and away from benthic predators. The larvae go through a series of stages (egg, yolk sac larvae, pre- and post-flexion larvae, pelagic juvenile), becoming larger and more capable over time. Critical periods occur and can cause major mortality of a cohort. Ocean conditions during the early egg and yolk sac stage are critical to survival followed by initiation of feeding as a second critical event. During pelagic life larvae must survive in open water, find appropriate food as larvae and avoid predators. Cohorts from aggregations can recruit as a large pulse, but other fishes may also have such pulses. The mass spawnings of reef invertebrates, such as stony corals, are generally not comparable to those of fishes, while crustaceans (spiny lobsters, marine crabs, terrestrial crabs) have some similarities. There is a need for fisheries oceanography research on aggregation spawning, as well as more work on laboratory culture. The question of potential maternal benefits to larvae needs careful attention.
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Transects of CTD (to 1000 m) and zooplankton stations (to 200 m in 50 m strata) were made across an anticyclonic eddy in the southern Gulf of California during October 2007 to determine its influence upon the three-dimensional distribution of larval fish assemblages. The eddy was ∼90 km in diameter and ∼70 m deep. A larval fish assemblage, representing a mix of oceanic and coastal species, was defined mainly in the eddy from 200 m depth to the surface. Mesopelagic species, such as Vinciguerria lucetia, were dominant. Coastal reef (Diplectrum sp.) and pelagic (Auxis spp.) species were found mainly in the surface layer. This suggests that, because of the Gulf's relative narrowness, the eddy trapped coastal fish larvae during its formation and trajectory southward, retaining larvae of different adult habits. Another larval fish assemblage was defined off the eastern coast; its high larval abundance and specific richness was probably associated with coastal upwelling. Mesopelagic species (e.g. Triphoturus mexicanus) dominated this assemblage, and coastal demersal species that were absent from the eddy (e.g. Symphurus williamsi) were recorded in the surface layer, suggesting that the thermocline was a vertical boundary in this assemblage. The 3D differentiation of planktonic habitats was the result of the mesoscale hydrodynamics in the area sampled, in particular that associated to the eddy life history and characteristics (radius, depth and velocity), and to coastal upwelling, promoting larval retention of a mix of species of different adult habits.