Journal of Heredity, 2015, 355–365
doi:10.1093/jhered/esv030
Original Article
Original Article
Population Genetic Structure of the Bonnethead
Shark, Sphyrna tiburo, from the Western North
Atlantic Ocean Based on mtDNA Sequences
Elena Escatel-Luna, Douglas H. Adams, Manuel Uribe-Alcocer,
Valentina Islas-Villanueva, and Píndaro Díaz-Jaimes
From the Posgrado en Ciencias del Mar y Limnología, Universidad Nacional Autónoma de México, Apdo. Postal 70–305
Ciudad Universitaria, México D.F. 04510, Mexico (Escatel-Luna); Florida Fish and Wildlife Conservation Commission,
Fish and Wildlife Research Institute, 1220 Prospect Avenue, Suite 285, Melbourne, FL 32901 (Adams); and Laboratorio
de Genética de Organismos Acuáticos, Instituto de Ciencias del Mar y Limnología, Universidad Nacional Autónoma de
México, Apdo. Postal 70–305, México D.F. 04510, México (Uribe-Alcocer, Islas-Villanueva, and Díaz-Jaimes).
Address correspondence to Píndaro Díaz-Jaimes at the address above, or e-mail: [email protected].
Received September 5, 2014; First decision October 30, 2015; Accepted April 23, 2015.
Corresponding editor: Jose Lopez
Abstract
The population genetic structure of 251 bonnethead sharks, Sphyrna tiburo, from estuarine and
nearshore ocean waters of the Western North Atlantic Ocean (WNA), was assessed using sequences
of the mitochondrial DNA-control region. Highly significant genetic differences were observed
among bonnetheads from 3 WNA regions; Atlantic coast of Florida, Gulf coast of Florida, and
southwestern Gulf of Mexico (analysis of molecular variance, ΦCT = 0.137; P=0.001). Within the Gulf
coast of Florida region, small but significant genetic differences were observed between bonnetheads
from neighboring estuaries. These overall patterns were consistent with known latitudinal and
inshore-offshore movements that occur seasonally for this species within US waters, and with the
residency patterns and high site fidelity to feeding/nursery grounds reported in estuaries along the
Atlantic coast of Florida and South Carolina. Historical demography also supported the occurrence
of past population expansions occurring during Pleistocene glacial-interglacial cycles that caused
drastic reductions in bonnethead population size, as a consequence of the eustatic processes that
affected the Florida peninsula. This is the first population genetics study for bonnetheads to report
genetic divergence among core abundance areas in US and Mexican waters of the WNA. These
results, coupled with recent advances in knowledge regarding regional differences in life-history
parameters of this species, are critical for defining management units to guide future management
strategies for bonnetheads within US waters and across international boundaries into Mexico.
Subject areas: Population structure and phylogeography; Conservation genetics and biodiversity
Key words: bonnethead shark, nursery areas, philopatry, population structure
Conservation of genetic resources of elasmobranchs is especially
important as many shark species have exhibited significant population declines or range contraction as a consequence of increased fishing pressure, habitat loss, or other co-occurring factors (Shepherd
and Myers 2005; Cortes et al. 2007; Baum and Blanchard 2010).
Elasmobranchs are typically characterized by slow growth, long life
span, late maturity, and low fecundity compared with teleost fishes,
which result in low intrinsic rates of increase and low resilience to
© The American Genetic Association 2015. All rights reserved. For permissions, please e-mail: [email protected]
355
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fishing mortality (Hoenig and Gruber 1990; Stevens et al. 2000;
Reynolds et al. 2001). Recent conservation and management focus
has been placed on delineation of nursery areas for early life stages of
sharks (Heithaus 2007) as they may contain evolutionary significant
units, and since early stages can be particularly vulnerable to fisheries. Coastal and estuarine systems are used by many shark species as
primary and secondary nursery areas, which potentially affects species survival because these waters frequently suffer from significant
anthropogenic alteration and habitat loss or degradation. Critical
nursery areas have been identified on both the Gulf of Mexico and
Atlantic coasts of Florida for multiple shark species (Castro 1993;
Heupel et al. 2007; Reyier et al. 2008; Curtis et al. 2011).
Bonnetheads, Sphyrna tiburo, are commonly distributed in the
western Atlantic Ocean from North Carolina, United States to southern Brazil, including the Gulf of Mexico and the Caribbean, and
are seasonally found within estuarine, coastal, and continental shelf
waters (Compagno 1984). They are also found in the Eastern Pacific
Ocean, ranging from southern California to Ecuador (Compagno
1984). Although the continuous distribution of individuals across the
species range in Atlantic US waters may suggest the existence of a single panmictic population, regional differences in life-history parameters of bonnetheads have been observed which suggest there may be
multiple populations within the Western North Atlantic (WNA). For
example, latitudinal differences in maximum adult size, size at parturition, and size and age at maturity were found among 3 different areas
of the Gulf coast of Florida (northwest Florida, [Tampa Bay], Florida
Bay) (Parsons 1993; Lombardi-Carlson et al. 2003). Additionally,
significant differences in age and growth parameters were detected
between bonnetheads from the southeastern US Atlantic coast and
the Gulf of Mexico (Frazier et al. 2014). Significant differences have
also been noted in the concentration of thyroidal hormone from
maternal serum and embryo yolk tissue between Florida Bay and
Tampa Bay (TB) estuaries (McComb et al. 2005). These regional/
latitudinal differences may be environmentally controlled or physiologically influenced, but similar to other fish species (Conover and
Present 1990), genetic factors may also play a role. There have been
also no observations of bonnetheads mixing or moving between US
waters of the Gulf of Mexico and the south Atlantic Ocean (non-Gulf
waters) (Kohler and Turner 2007; Driggers et al. 2013) and preliminary genetic data for this species suggests the existence of multiple
genetically distinct populations (Diaz-Jaimes et al. 2013).
In addition, some studies based on acoustic tagging in estuarine
waters of the Gulf of Mexico coast of Florida have suggested that bonnetheads are long-term residents within a specific estuary, with low dispersal among different estuaries, and do not appear to make long coastal
migrations (Heupel et al. 2006; Bethea and Grace 2013). However,
evidence of repeated use and seasonal site fidelity, with associated significant coastal migrations on a seasonal basis, has been provided for
South Carolina estuaries in the WNA, where extensive conventional
tagging data also revealed significant group cohesion of bonnetheads
over yearly scales (Driggers et al. 2014). The proclivity of individuals
to remain or return for extended periods to areas where they were born
is one of the main criteria for philopatry (Feldheim et al. 2014). These
areas are critical for protection of neonates and young juveniles and for
subsequent recruitment into the adult population.
Bonnetheads in US waters are currently managed as one population and expanded genetic information is critical to effectively assess
the number of management units for conservation (Moritz 1994) of
bonnetheads within its range in the WNA and also to assess potential genetic differences or similarities among nursery grounds of both
Atlantic Ocean and Gulf of Mexico waters. The use of molecular
Journal of Heredity, 2015, Vol. 106, No. 4
markers is valuable to address these issues (Portnoy and Heist 2012).
The present study aims to use mitochondrial DNA-control region
(mtDNA-CR) sequences, to evaluate the genetic population structure
of bonnetheads from 3 major regions: 1) the Gulf of Mexico coast
of Florida (hereafter referred as Gulf coast of Florida); 2) Atlantic
coast of Florida; and 3) Mexican waters of the Gulf of Mexico (hereafter the southwestern Gulf of Mexico), and generate information to
address important questions regarding the population genetic structure and the philopatric behavior of this coastal shark species.
Materials and Methods
Sample Collection and DNA Isolation
Bonnetheads were collected from 1992 to 2013 by the Florida Fish
and Wildlife Conservation Commission-Fish and Wildlife Research
Institute’s Fisheries-Independent Monitoring Program and cooperative
research cruises operating in estuarine systems and adjacent coastal
waters. Otherwise, samples were obtained from recreational and commercial fisheries in the nearshore and offshore waters of Florida in the
Atlantic and Gulf regions, and from commercial landings in the southwestern Gulf of Mexico (Figure 1). Dorsal muscle and fin clips from
each specimen were collected and preserved in nondenatured ethanol.
Atlantic region study areas ranged from waters near the GeorgiaFlorida border south to the Florida Keys (FK) area. Specific estuarine
study areas within the Atlantic region included the St. Marys River
system, the Nassau Sound - Nassau River system, the lower St. Johns
River system, all of which were combined into a north Atlantic Florida
group (NAFL). The Indian River Lagoon and adjacent coastal waters
representing the central portion of the Atlantic coast of Florida were
combined into the central Atlantic Florida group (CAFL).
Within Florida Gulf of Mexico waters, bonnetheads were collected from the northwestern Florida coast near Cedar Key (CK), the
southwestern Florida coast including Charlotte Harbor (CH) and
Tampa Bay (collectively referred to as CH-TB). Additional samples
were collected from adjacent nearshore and offshore waters within
the West Florida Shelf (WFS) and FK. The samples collected in the
southwestern Gulf of Mexico were directly from commercial fisheries operating within inshore (estuarine) waters from Champoton
Campeche Mexico (CAM) and Frontera Tabasco (TAB) during 2012
and 2013, respectively.
PCR Amplification and Sequencing
Total genomic DNA was isolated using Wizard Genomic®
Promega kit and resuspended in 50–100 μL of TE buffer. A fragment of 940 base pairs (bp) of the mtDNA-CR of bonnetheads was
amplified in 251 samples by using the primers ElasmoCR15642F
(5′-TTGGCTCCCAAAGCC-3′)
and
ElasmoCR16638R
(5′-CCCTCGTTTTWGGGGTTTTTCGAG-3′; Stoner et al. 2003).
Reactions for sequencing were done in a total volume of 50 μL
containing 50–100 ng DNA in buffer 10 mM TRIS-HCl (pH 8.4),
50 mM KCl, 1.5 mM MgCl2, 0.2 mM of each dNTP, 0.1 mM of each
primer, and 2.5 units of platinum Taq DNA polymerase. PCR amplifications consisted of an initial step of 5 min at 94 °C for denaturation, 35 cycles of 1 min at 95 °C for denaturation, 1 min at 59 °C
for annealing, and 1 min at 65 °C for extension, and a final extension step at 65 °C for 3 min. PCR products were sequenced in the
forward direction on an ABI 3730xl automated sequencer applying
the dye-termination method (Applied Biosystems). Only high quality
sequences were used for the analyses and quality control consisted
on the review of every polymorphic site in the chromatogram using
Journal of Heredity, 2015, Vol. 106, No. 4
357
Figure 1. Sampling locations where genetic tissue samples of bonnetheads were collected. North Atlantic Florida group (NAFL); central Atlantic Florida group
(CAFL); Florida Keys (FK); Cedar Key (CK); Tampa Bay (TB); Charlotte Harbor (CH); West Florida Shelf (WFS); Champoton Campeche, Mexico (CAM); Frontera
Tabasco, Mexico (TAB).
the sequence of S. tiburo from the Genbank as reference (accession
number GU385313.1) and also the sequence for the most common
haplotype. Every chromatogram was checked by 2 independent people and disagreements between reviewers, if any, were verified thoroughly or sequence repeated in order to determine if substitutions
were potential sources of sequencing errors.
Data Analyses
Multiple alignment was performed with Clustal X ver. 1.8 (Thompson
et al. 1997) as well as by optimizing the gap penalties in order to
minimize artificial homologies between haplotypes (homoplasy) during the alignment. The hierarchical likelihood ratio method implemented in jModelTest 2.0 (Darriba et al. 2012) was applied to define
the most appropriate substitution model of sequence evolution for
the segment of the mtDNA-CR analyzed. Additionally, a minimum
spanning tree (MST) was constructed using pairwise number of
sequence differences with Arlequin.
Haplotype (h) and nucleotide (π) diversities were estimated using
Arlequin 3.5 (Excoffier and Lischer 2010). Pairwise ΦST between
sample locations were obtained to identify genetically differentiated
localities. Similarly, the molecular analogue of the unbiased Wright’s
F-statistics (Φ-statistics) was computed with the application of the
TPM3uf + I + G substitution model (with a gamma of 0.124) in a
hierarchical analyses of molecular variance (AMOVA).
Sex-biased dispersal may result in differences of mtDNA haplotype frequencies between nurseries after several generations (Hueter
et al. 2004). For this reason a measure of genetic differences based
on the proportion of allele frequencies rather than that based on
genetic distances between alleles is more appropriate (Daly-Engel
et al. 2012). The conventional pairwise FST estimates using haplotype frequencies were obtained in order to assess genetic differences due to philopatry between potential nursery grounds. Both
approaches, based on distances between haplotypes (ΦST) and haplotype frequencies (FST), were used to assess the AMOVA with samples grouped into Atlantic coast of Florida (NAFL and CAFL), Gulf
coast of Florida (CK, CH-TB, and WFS), the transition zone between
Gulf and Atlantic coasts of Florida (FK) and southwestern Gulf of
Mexico (CAM and TAB).
To confirm the existence of boundaries to gene flow among
the main sample groups assessed in the hierarchical AMOVA, the
BARRIER v.2.2 program was used. This software implements a
Monmonier’s algorithm that finds the edges associated with genetic
differences and the geographical localization of samples to identify
genetic boundaries (Manni et al. 2004) and delivers graphical representations of discontinuities in gene flow that can be visualized in
a geographical context. As no specific criteria to select the optimal
number of boundaries is described in Barrier and because the program defines the potential barriers in a sequential fashion according
to its importance, 4 boundaries were selected corresponding to the
number of groups tested in the AMOVA.
The demographic parameters τ, θ0, and θ1 were obtained from
nucleotide mismatch distributions with the Arlequin software to
examine the impact of demographic fluctuations related to past glaciations on the molecular architecture of bonnetheads. The parameters included Tau (τ) and the θ-estimates θ0 = 2N0μ and θ1 = 2N1μ,
where μ is the mutation rate, and N0 and N1 are the female effective
population sizes before time 0 and after time 1; expansions were
translated into parameter estimations using as range, the calibrated
mutation rates of 0.67–1.2% of Keeney and Heist (2006) and Nance
et al. (2011) for blacktip shark Carcharhinus limbatus and scalloped hammerhead S. lewini, respectively. Fu’s Fs, as implemented
in Arlequin was used to test for departures from neutrality due to
recent population expansions or to selection (Fu 1997).
Bayesian sampling coalescence-based and Markov chain Monte
Carlo (MCMC) methods implemented in IMa2 (Hey and Nielsen
2004) were used to estimate the “isolation with migration” parameters for the most divergent populations (CK, CH-TB, NAFL, CAFL,
TAB, and CAM). IMa2 uses a multipopulation approach to obtain
simultaneously estimates of population size, θ or 4Nu (where N is
the effective population size), as well as a mutational scaled migration to each population with which it coexists in time m = M/u (M
is the migration rate per generation per gene copy). In addition to
Journal of Heredity, 2015, Vol. 106, No. 4
358
these parameters and on the basis of a predefined population tree
topology, it is possible to obtain the splitting time, t = T/u where T
is the time in generations. We assess convergence by running IMa
in M-mode and by sampling autocorrelation and estimated sample
sizes (ESS) values each 6.0 h monitoring the trend line plots and
verifying that ESS reached values over 50. Runs were repeated 3
times in order to get an exhaustive sampling of the posterior distribution. All runs consisted of at least 100 000 000 generations and
1 000 000 generations discarded as burn-in. After M-mode runs we
ran IMa2 in L-mode to obtain likelihood ratio tests to compare the
fit of the models implemented in IMa2 to the full model (i.e., m1 ≠
m2; θ1≠θ2≠θA).
In fulfillment of data archiving guidelines, we have deposited
the primary data underlying these analyses in Genbank (accessions
KM987020 through 987112).
Results
mtDNA-CR Variability and Phylogeny
We sequenced a fragment of 940 bp of the mtDNA-CR for a total
of 251 bonnetheads that resulted in 98 haplotypes. Sixty-three segregating sites were observed, featuring 44 transitions and 15 transversions. Mean haplotype diversity was high (h = 0.932), yet within
the range for the reported values for other shark species, with values ranging from 0.826 for CH-TB samples to 1.0 for bonnetheads
from the FK and samples collected from the WFS. The average number of nucleotide differences between haplotypes was 2.0 and the
mean nucleotide diversity π was 0.32% which means that differences between haplotypes were based on variation at 3 variable sites.
Estimates of nucleotide diversity per sample ranged from 0.16% for
CH-TB to 0.43% for TAB (Table 1).
The MST resulted in 2 main haplotypes separated by one mutation; the haplotype St-1 was most abundant (20.3%) and contained
mostly sequences from the Gulf coast of Florida (CK, CH-TB, and
WFS) and Florida Atlantic coast (NAFL, CAFL) plus one from the
southwestern Gulf of Mexico (TAB). Although the second most
abundant haplotype St-9 (12.9%), contained individuals from all
areas, they were mainly from the Gulf coast of Florida (CK, CH-TB,
FK, and WFS) and the southwestern Gulf of Mexico (TAB and
CAM). Both haplotypes showed a star-like phylogeny surrounded
by haplotypes from different locations; however, most haplotypes
from the southwestern Gulf of Mexico were separated from the most
abundant haplotypes by longer branches (2 or more mutational
steps) and clustered with haplotypes almost exclusively from the
Gulf coast Florida (CK, CH-TB, and WFS) (Figure 2).
Population Genetic Divergence
Estimates of pairwise sample ΦST and FST are shown in Table 2.
In general, ΦST showed higher values as compared with FST estimates; however, both estimators displayed consistent patterns of
genetic differences among locations from the main sampled regions.
Highly significant genetic differences of bonnetheads were observed
when we compared estuaries from both Florida coasts; Gulf (CK
and CH-TB) versus Atlantic (NAFL and CAFL). Significant differences were observed for comparisons between CK and NAFL
(ΦST = 0.059; P < 0.001, FST = 0.027; P = 0.025), and CH-TB versus
NAFL (ΦST = 0.068; P = 0.001, FST = 0.039; P = 0.012). Similar levels
of significance were observed for CK when compared with CAFL
(ΦST = 0.079; P < 0.001, FST = 0.038; P = 0.021) and CAFL with
CH-TB (ΦST = 0.093; P = 0.001, FST = 0.047; P = 0.019). In addition,
highly significant genetic differences were observed for both ΦST and
FST estimates (P < 0.001) among all the US waters locations and the
southwestern Gulf of Mexico samples (TAB, CAM), except for FK.
Small, yet statistically significant genetic differences were observed
between close estuaries of the Gulf coast of Florida (i.e., CK vs.
CH-TB) based on the FST estimate (FST = 0.025; P = 0.049) and ΦST
(ΦST = 0.021; P = 0.048). Contrastingly, no differences were observed
for estuaries from the Atlantic coast of Florida (CAFL vs. NAFL).
Further genetic differences based on estimates of ΦST were observed
for comparisons between CAFL and NAFL with FK (ΦST = 0.2;
P = 0.004, ΦST = 0.17; P = 0.012) and WFS (ΦST = 0.077; P = 0.008,
ΦST = 0.064; P = 0.012).
AMOVA using both ΦST and FST estimates, was consistent with
the differences observed from pairwise sample comparisons. A significant estimate for the variance component among groups (ΦCT = 0.129;
P < 0.001, FCT = 0.037; P = 0.001) was obtained by grouping samples into the Atlantic Florida coast (NAFL, CAFL), the Gulf coast
of Florida (CK, CH-TB, WFS), the transition zone (FK), and the
Table 1. CR-mtDNA sequence variability and historical demography parameters for bonnetheads from the Atlantic and Gulf of Mexico
coasts of Florida
Location
n
nh
Gulf coast of Florida
CK
42
17
CH-TB
42
13
WFS
14
14
FK
5
5
Atlantic coast of Florida
CAFL
25
13
NAFL
48
18
Southwestern Gulf of Mexico
CAM
38
28
TAB
37
31
Total
251
98
h
π
S
K
τa
Tb
Hri
SSD
F
0.854
0.826
1.000
1.000
0.0024
0.0016
0.0036
0.0027
19
11
15
6
1.88
1.02
2.37
2
2.46
1.63
3.48
2.22
109 000–195 000
72 000–130 000
154 000–276 000
98 000–176 000
0.024
0.075
0.057
0.12
0.0014
0.0046
0.0123
0.0237
−9.957*
−7.503*
−13.60*
−2.517*
0.877
0.846
0.002
0.0019
14
20
1.24
1.15
1.87
1.87
83 000–149 000
83 000–149 000
0.059
0.048
0.0020
0.0016
−8.311*
−12.80*
0.963
0.991
0.932
0.0039
0.0043
0.0032
27
28
63
2.73
3.27
2.06
3.89
4.13
2.07
172 000–308 000
183 000–327 000
91 700–164 000
0.019
0.023
0.019
0.0007
0.0014
0.0004
−25.33*
−25.84*
−26.12*
Sample size (n), number of haplotypes (nh), haplotype diversity (h), nucleotide diversity (π), number of segregating sites (S), mean pairwise differences between
individuals (K), Harpending’s raggedness index (Hri), and sum of squared differences from mismatch analyses (SSD).
a
τ = 2μT, where μ is the mutation rate within a range of 0.67–1.2% (Keeney and Heist 2006; Nance et al. 2011) for blacktip shark and scalloped hammerhead shark, respectively. *P < 0.05.
b
T is the time since population expansion.
Journal of Heredity, 2015, Vol. 106, No. 4
359
St-89
Gulf coast of Florida
St-59
Atlantic coast of Florida
St-48
St-95
St-63
St-77
St-75
St-72
St-22
St-98
St-18
St-68
St-69
St-85
St-6
50
30
10
2
St-90
St-86
St-87
Southwestern Gulf of Mexico
StSt-15
St-35
St-44
St-11
St-51
St-32
St-58
St-60
St-76
St-62
St-91
St-81
St-14
St-30
St-80
St-26
St-47
St-70
St-
St-2
St-96
St-73
St-79
St-8
St-34
St-23
St-27
St-24
St-37
St-74
St-50
St-53
St-25
St-57
St-64
St-16
St-82
St-67
St-7
St-5
St-4
St-65
St-83
St-71
St-61
St-3
St-36
St-92
St-54
St-46
St-20
St-49
St-21
St-10
St-56
Figure 2. mtDNA-CR minimum spanning tree showing the 2 most abundant haplotypes St-1 and St-9, displaying a star-like topology. Small black dots along the
branches represent a “missing haplotype” that was not included in the sample.
southwestern Gulf of Mexico (TAB and CAM). The variance component among populations within groups was nonsignificant suggesting genetic homogeneity within regions (Table 3). These groups were
supported with Barrier analysis that identified 3 main boundaries, the
first corresponding to FK area (a transition zone between the Gulf and
Atlantic coasts of Florida), the second within the Gulf area between
CK and CH-TB and WFS, and the third among all Florida samples
and the southwestern Gulf of Mexico in Mexican waters (Figure 3).
Journal of Heredity, 2015, Vol. 106, No. 4
360
Table 2. Pairwise sample comparisons of ΦST estimates (below diagonal) and conventional pairwise FST estimates (above diagonal)
CK
CH-TB
WFS
FK
CAFL
NAFL
CAM
TAB
CK
CH-TB
WFS
FK
CAFL
NAFL
CAM
TAB
—
0.021
0.059*
0.057
0.079**
0.059**
0.151***
0.140***
0.026*
—
0.046
0.043
0.093**
0.068**
0.129***
0.119***
0.051*
0.062*
—
−0.015
0.077*
0.064*
0.037*
0.026
0.057
0.009
−0.029
—
0.200*
0.170*
−0.048
−0.045
0.038*
0.047*
0.025
0.017
—
−0.022
0.209***
0.190***
0.027*
0.039*
0.044*
0.041
−0.013
—
0.217***
0.201***
0.064***
<0.049**
0.010*
−0.033
0.076***
0.087***
—
−0.009
0.059**
<0.067***
−0.009
−0.022
0.054***
0.070***
0.002
—
Significant P values at *<0.05, **<0.001, and ***<0.0001.
Table 3. AMOVA analysis using pairwise genetic distances and conventional FST estimates
ΦST
Variance
% Total
FST
P
Among groups (Gulf coast of Florida; Atlantic coast of Florida; FK; Southwestern Gulf of Mexico)
Among populations within groups
Within populations
FST
Among groups (Gulf coast of Florida; Atlantic coast of Florida; FK; Southwestern Gulf of Mexico)
Among populations within groups
Within populations
0.202
0.011
1.33
13.0
0.72
86.3
0.129
0.008
0.137
0.0004
0.097
<0.001
0.018
0.006
0.448
3.73
1.39
94.8
0.037
0.014
0.051
0.031
0.02
<0.001
Locations were grouped into Gulf coast of Florida (CK, CH-TB, and WFS), Atlantic coast of Florida (CAFL, NAFL), transition zone between Gulf and Atlantic
Florida coasts (FK) and southwestern Gulf of Mexico (TAB and CAM).
Figure 3. mtDNA-CR differences between locations from the Atlantic and Gulf coast of Florida and the southwestern Gulf of Mexico, assessed with Barrier 2.2.
Sampling locations are in red dots and its corresponding Voronoi tessellation (connecting green lines). Delaunay triangulations are represented with blue and
red lines (genetic barriers).
Historical Demography and Coalescence Analysis
Fu’s neutrality tests supported historical demographic expansions for
all sample locations (P < 0.001). In addition, the distribution of mismatches was unimodal for all locations (Figure 4) which was supported by nonsignificant estimates of the raggedness index and the
sum of squared deviation (Table 1). Populations from both Florida
coasts showed a more recent expansion (83 000–195 000 years) as
compared with populations from the southwestern Gulf of Mexico
(172 000–327 000 years). For all the locations, long-term effective
female population size before the expansion (θ0) was zero with a small
Journal of Heredity, 2015, Vol. 106, No. 4
361
CK
CH-TB
250
100
200
80
150
60
100
40
50
20
0
0
1
2
3
4
5
6
7
8
9
1
10
2
3
4
Frequency
NAFL
5
6
7
8
9
CAFL
400
350
300
250
200
150
100
50
0
50
40
30
20
10
0
1
2
3
4
5
6
7
8
1
2
3
TAB
4
5
6
7
CAM
160
160
140
140
120
120
100
100
80
80
60
60
40
40
20
20
0
0
1
2
3
4
5
6
7
8
9
10 11
1
2
3
4
5
6
7
8
9
10
11
Number of differences
Figure 4. Pairwise distribution of mismatches for the mtDNA-CR of bonnetheads, populations from Florida coasts (CK, CH-TB, NAFL, CAFL) and the southwestern
Gulf of Mexico (TAB, CAM).
increase in size after expansion (θ1) for US locations suggesting slow
increase in population size after a bottleneck (range 3.51 for CAFL to
14.9 for WFS; data not shown). Differences between θ0 and θ1 were
larger for the southwestern Gulf of Mexico locations suggesting a
rapid population increment during expansion (Carlsson et al. 2004).
The coalescence-based and MCMC methods implemented in
IMa2 (Hey and Nielsen 2004) were used to estimate the “isolation
with migration” parameters from population comparisons. The
“isolation with migration” model makes it possible to distinguish
between complete isolation from divergence with gene flow (Nielsen
and Wakeley 2001) and is appropriate for recently divergent populations that share haplotypes or alleles due to either gene flow or
ancestral polymorphism (Nance et al. 2011). Likelihood ratio tests
(LLR) for testing nested models in relation with the full model
(where θA≠θ1≠θ2≠m1≠m2) supported models with migration and
unequal effective population sizes as compared with the ancestral
population (that from which the 2 populations coalesce) which was
significantly smaller than estimates for actual populations. Similarly,
LLR tests supported high estimates of effective population size for
CAM and TAB populations and allowed for the identification of a
consistent pattern of asymmetric gene flow between populations
from the main US estuaries examined (see Supplementary Table
S1 online). In general, gene flow was higher for populations within
the Atlantic (mNAFL>CAFL = 14.21) or the Gulf coasts of Florida (mCH = 21.23) than for comparisons among areas (mCK>NAFL = 2.18;
TB>CK
mCK>CAFL = 1.53; mCH-TB>NAFL = 0.95; mCH-TB>CAFL = 0.13). Gene flow
362
in the coalescence (back in time) was also asymmetric among areas,
mainly for populations from the Gulf of Florida to the Atlantic
areas, and zero in the opposite direction. Similarly, gene flow estimates in terms of coalescence for comparisons among locations of
both Florida regions and the southwestern Gulf of Mexico (TAB
and CAM), were low and also asymmetric, predominately from TAB
(mTAB>CH-TB = 0.52; mTAB>CK = 0.26) and/or CAM to locations from the
Gulf coasts of Florida (mCAM>CH-TB = 1.55; mCAM>CK = 0.37) and zero
(or close to zero) in the opposite direction, whereas for locations
from the Atlantic Florida coasts, were symmetric (mTAB>CAFL = 0.07;
mTAB>NAFL = 0.06; mCAM>CAFL = 0.1; mNAFL>CAM = 0.05).
Estimates of time for population divergence were different from
zero for comparisons among Florida and Mexican areas (which
ranged from 0.98 to 1.16) corresponding to a divergence estimated
to occur some 87 000–103 000 years ago. In contrast, time for population divergence for comparisons between locations from the Gulf
and Atlantic coasts of Florida, was nearly zero (range: 0.17–0.38),
which corresponds to a divergence that occurred between 15 000
and 34 000 years ago.
Discussion
Genetic Diversity
Bonnethead populations in the Gulf of Mexico and US Atlantic coast
waters displayed high levels of haplotype diversity similar to other
coastal shark species such as the blacktip shark, C. limbatus (Keeney
and Heist 2006) and the sandbar shark, C. plumbeus (Portnoy et al.
2010), but also similar to some pelagic shark species, such as the
shortfin mako, Isurus oxyrhinchus (Taguchi et al. 2011). Haplotype
diversity of bonnetheads contrasts with estimates for the congeneric
scalloped hammerhead for a similar area in US Atlantic and the Gulf
of Mexico, where a notably low number of haplotypes (n = 3) were
observed (Duncan et al. 2006). The high gene diversity we observed
is compatible with some biological parameters reported for bonnetheads such as fast growth, short generation time (2.5 years), and
short gestation period (~6 months) (Cortés and Parsons 1996).
The MST did not reveal a clear arrangement of haplotypes in the
core study regions (e.g., the Atlantic vs. the Gulf coasts of Florida)
or spatially separated regions (e.g., Florida-US waters vs. Mexico)
denoting the existence of some extent of gene flow among regions
mediated by dispersal through adult migration. The lack of a clear
phylogeographic signal may be a result of several factors in addition to gene flow, including incomplete lineage sorting (due to recent
divergence or divergence with gene flow) or expansion reduction
cycles (Avise 2000). The 2 most abundant haplotypes in the MST
displayed a star-like topology typical of populations that experienced demographic expansions after a bottleneck, which could have
eliminated any previous phylogeographic signals.
Population Divergence and Philopatry
Highly significant genetic differences were observed among 3 major
regions; the Gulf coast of Florida (CK, CH-TB), the Atlantic coast
of Florida (NAFL, CAFL), and Mexican waters of the southwestern Gulf of Mexico (TAB and CAM). Contrastingly, variance within
regions of the Atlantic coasts of Florida and the southwestern Gulf of
Mexico was not significantly different but small genetic differences
were observed between locations from the Gulf coast of Florida (e.g.,
CK vs. CH-TB).
These results emphasize that, although bonnetheads exhibit
dispersal capability, movements probably occur between nearby or
adjacent estuaries but are limited among regions separated by the
Journal of Heredity, 2015, Vol. 106, No. 4
scale of thousands of km. Bonnetheads are distributed widely in the
Western Atlantic; however, their primary abundance areas are estuarine and nearshore ocean waters. The high residency, and site fidelity
to estuaries, determined by both acoustic and conventional tagging
data, suggest that this species does not typically make significantly
long coastal migrations throughout its range. It was estimated that
bonnetheads within CH remain a mean of 49 days (range 1–89 days)
and traveled a mean distance of approximately 9.9 km within estuarine waters over an entire time at liberty of 187 days (Heupel et al.
2006). In contrast, on the US Atlantic, seasonal latitudinal movements along the coast have been documented. Although tagged bonnetheads were most often recaptured within the same estuary where
they were originally tagged, a number of individuals were recaptured during migratory periods (late fall, winter, and spring), within
nearshore ocean waters of North Carolina, South Carolina, Georgia,
and Florida (Driggers et al. 2014), suggesting dispersal capability of
bonnetheads that may help explain the lack of genetic differences
among nearby or adjacent estuaries.
All tag-recapture data to date indicate low or no movements of
bonnetheads from US Atlantic waters into the Gulf of Mexico, or
vice versa (Bethea and Grace 2013; Tyminski et al. 2013; Driggers
et al. 2014), including movements to the southwestern Gulf of Mexico
(Kohler et al. 2013). Although there was one bonnethead recorded
moving from US waters to the Mexican-managed portion of the
Gulf of Mexico near the Texas border, the full extent of movements
between US and Mexican waters is unknown due mainly to the underreporting of recaptured sharks in Mexican waters (Kohler et al. 2013).
Thus, whereas the lack of evidence for movement among the
3 major regions studied (Gulf and Atlantic coasts of Florida and
southwestern Gulf of Mexico) supports the genetic differences we
observed for bonnetheads, their seasonal latitudinal and/or offshore
movements may also help to explain the lack of genetic differences
between locations along the Atlantic coast of Florida.
There were small genetic differences observed between CK and
CH-TB (2 potential nursery areas) which may have resulted from
philopatric behavior of this species. Philopatry is the tendency of
an individual to remain in or return to certain areas during its life
cycle (Feldheim et al. 2014) and it is considered to include natal or
reproductive philopatry (when individuals return to natal nurseries
to mate or give birth) and sex-specific philopatry, where one sex is
more philopatric than the other (Hueter et al. 2002). In sex-specific
philopatry, due to the maternal inheritance and lack of recombination of mtDNA, the repeated use of estuaries and/or coastal waters
by individuals for mating or parturition may result in differences in
haplotype frequencies among populations from different nurseries as
compared with the nuclear DNA which is bi-parentally inherited. As
a result, the existence of genetic differences in the mtDNA, and its
absence in nuclear DNA should be indicative of philopatry (Portnoy
and Heist 2012). Based on the increasing evidence of philopatry for
several shark species it is important to consider that the genetic differences observed between bonnethead populations in the uniparentally inherited mtDNA could result from sex-biased dispersal.
This was determined for the scalloped hammerhead, a larger and
circumglobally distributed congeneric species, in the western Atlantic
where Chapman et al. (2009) found 3 distinct “mtDNA stocks”
across the Western Atlantic (WNA, Central America, and Brazil)
based on the single use of sequences of the mtDNA-CR. No differences between locations of the Gulf and Atlantic coasts of Florida
were detected for this hammerhead species. Although the differences
between these 3 major regions were attributed to philopatry, it was
not fully supported by the lack of nuclear DNA data.
Journal of Heredity, 2015, Vol. 106, No. 4
However, evidence of philopatry for the scalloped hammerhead
shark was later supported by Daly-Engel et al. (2012) based on the
strong discrepancies in the genetic signal of differentiation between
uniparental (mtDNA) and bi-parental (nDNA) markers. Moreover,
whereas locations from the same marginal coastline showed highly
significant genetic differences with mtDNA, the low or nonexistent
genetic differentiation observed between locations from different
continental margins, was concluded as evidence of philopatry (DalyEngel et al. 2012).
Evidence for philopatry over small spatial scales has also been
reported for other shark species within the WNA, such as the lemon
shark (Feldheim et al. 2014), blacktip shark (Keeney et al. 2005),
and bull shark (Karl et al. 2011). Both, mtDNA and nuclear data
were examined in each of these previous studies, and the genetic
differences occurred between adjacent or nearby estuarine systems.
Considering that potential shark nursery grounds for both Gulf
and Atlantic coasts of Florida have been reported (Carlson 2002;
McCandless et al. 2007), that include CK and CH, and due to the
small scale differences explaining philopatry for other co-occurring
shark species, one could expect similar differences for bonnetheads.
This was not the case for bonnetheads for 2 possible nursery grounds
on the Gulf coast of Florida (CK and CH-TB), which showed weakly
significant differences, while no differences were detected between
estuaries from the Atlantic coast of Florida. Moreover, it is not possible to fully distinguish between population structure and philopatry with the single use of maternally inherited mtDNA and we are
limited on fully addressing the existence of natal philopatry.
However, a general conclusion about philopatry can be drawn
based on evidence provided by tagging data. Although high residency of bonnetheads to estuaries has been reported (Heupel et al.
2006), seasonal migrations southward from South Carolina waters
to coastal Florida waters have been also observed (Driggers et al.
2014). Furthermore, observations of postpartum females and neonates in estuaries from the US Atlantic coast are limited (Ulrich et al.
2007; Driggers et al. 2014), suggesting that mating and parturition
of bonnetheads may occur outside of estuaries in this part of their
range. With these points in mind, there is currently not enough data
to support or refute the existence of natal or reproductive philopatry
for bonnetheads.
The high residence in estuaries might be related to the use of these
estuarine areas as feeding grounds or serve as a combination of both
nursery and feeding functions for bonnetheads on the southeastern
US Atlantic coast (Driggers et al. 2014). The latitudinal migrations
of bonnetheads during late fall, winter, and spring, has been hypothesized as evidence of bonnetheads using South Carolina estuaries as
feeding grounds concurrent with high abundance peaks of preferred
prey (mature female blue crabs Callinectes sapidus) during spring
and summer months, a behavior that may be socially transmitted to
young sharks from experienced older adults. In this case, limited or
no genetic differences between closely adjacent estuaries would be
expected.
The highly significant differences among bonnetheads from the
3 major regions we examined and the lack of consistent differences
within areas points for now, to the limited dispersal of bonnetheads
between spatially separated regions as the most plausible explanation of the differences observed. Estuarine or nearshore nursery
areas are critical for protection of neonates and young juveniles
and for subsequent recruitment into the adult population. Although
there is a lack of clear evidence of philopatry for bonnetheads, it
should be explored in more detail in future studies by using a wider
set of molecular markers, especially those based on nuclear DNA.
363
Likewise, sampling efforts should be directed to collect young-ofthe-year individuals, juveniles, and/or postpartum females from
nursery areas.
Historical Demography and Bonnethead Shark
Population History
In Florida, climate change during Pleistocene glacial-interglacial
cycles has played a pivotal role in defining the species’ genetic architecture as consequence of fluctuations in population size originating
from habitat loss by sea-level changes at key distribution areas (Avise
2000). This is likely the main cause of the unimodal distribution of
mismatches observed in bonnethead populations, which is consistent
with a relatively recent population expansion that was estimated to
have occurred approximately 100 000–160 000 years ago during the
Illinois-Wisconsin interglacial period (136 000–115 000 years; Muhs
et al. 2002). During glacial events some 150 000 years ago, sea level
dropped as much as 120 m, significantly increasing the land area coverage (Lambeck and Chappell 2001; Muhs et al. 2002). During these
sea-level changes, many estuaries might have disappeared, reducing
habitable areas for bonnetheads. Food sources for bonnetheads may
have been limited or depleted as habitat loss progressed during glacial maxima, reducing their populations drastically. Once the glaciers retracted and sea level increased again, estuaries were reflooded
providing optimal conditions for population expansion, including a main prey of bonnetheads, the blue crab, C. sapidus (Cortés
et al. 1996), and other prey species. Sudden population expansion
has been detected also for the blue crab from similar locations at
both the Gulf and Atlantic coasts of Florida which has been associated also to population reductions during Pleistocene glaciations
followed by expansion at interglacial periods (McMillen-Jackson
and Bert 2004). Moreover, the phylogeographic pattern reported in
the blue crab and that for bonnetheads was similar in supporting
the existence of gene flow between adjacent estuaries related to seasonal northward migrations reported for both species (Steele, 1991;
Bethea and Grace 2013; Kohler et al. 2013; Driggers et al. 2014). It
is important to note that this similarity is consistent with the findings
of Driggers et al. (2014) with regard to site fidelity of bonnetheads
populations to feeding grounds. Phylogeographic patterns associated
with population reductions and expansions have been identified for
other invertebrate and/or fish species along coastlines of Florida
from the Atlantic and Gulf of Mexico by Avise (2000), especially
for coastal species which were pushed southward during cooling sea
temperatures, toward warmer and more suitable conditions.
Analyses from IMa appeared to support this expansion scenario,
because all comparisons between samples from the main estuaries
coincided with small ancestral population sizes, suggesting that current populations originated after a genetic bottleneck. The reduction
of the ancestral populations may have stemmed from the eustatic
events that occurred during glacial periods. The estimated time
for population divergence between the Gulf and Atlantic coasts of
Florida, was relatively recent (between 23 000 and 50 000 years
ago) suggesting that populations from both sides of Florida mixed
in the past during glacial periods when populations were pushed
southward. The past opportunities of contact between populations
from the Gulf and Atlantic coast of Florida have occurred also for
other coastal marine species (Avise 2000). Contrastingly, the time
for population divergence between all Florida locations (especially
those from the Gulf coast of Florida) and the southwestern Gulf of
Mexico region was earlier (146 000–140 000 years ago) and seems
to coincide with the interglacial Illinois-Wisconsin supporting the
expansion of populations.
364
This is the first population genetic study of bonnetheads to report
genetic divergence between core abundance areas from US waters
on Florida’s coasts and Mexican waters of the southwestern Gulf of
Mexico. These results are critical for defining future management strategies for bonnetheads populations. Bonnetheads in US waters have
been managed as one population. Our results, coupled with recent
advances in knowledge regarding differences in life-history parameters
of this species are important considerations for effective species management within US waters and across international boundaries into
Mexico. However, it is also clear that the divergence pattern observed
for bonnetheads needs to be further investigated using nuclear markers
in order to better define the roles of specific habitat use and dispersal
capability, and this research is currently in progress.
Supplementary Material
Supplementary material can be found at http://www.jhered.oxfordjournals.org/.
Funding
Programa de Apoyo a Proyectos de Investigación e Inovación
Tecnológica PAPIIT at DGAPA-UNAM (IN208112). This project was supported in part by proceeds from State of Florida saltwater recreational fishing licenses, and by funding from the U.S.
Department of the Interior, U.S. Fish and Wildlife Service, Federal
Aid for Sportfish Restoration (Project Number F14AF00328).
Acknowledgments
We thank N. S. Laurrabaquio and G. Martínez for sample processing,
and N. Bayona for data analysis. The efforts of the FWC-FWRI FisheriesIndependent Monitoring program in collecting sharks for this study are
greatly appreciated. We also appreciate additional sharks provided by Eric
Reyier of NASA’s Kennedy Space Center Ecological Program, as well as Cape
Canaveral Scientific, Inc. Thanks to the 3 anonymous reviewers for their comments which notably improved the manuscript.
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