Escatel2015.pdf

Journal : JHERED Article Doi

: 10.1093/jhered/esv030

Article Title

: Population Genetic Structure of the Bonnethead Shark, Sphyrna tiburo From the Western North Atlantic Ocean Based on mtDNA Sequences

First Author

: Elena Escatel-Luna

Corr. Author

: Píndaro Díaz-Jaimes

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AUTHOR QUERY FORM Journal : JHERED Article Doi

: 10.1093/jhered/esv030

Article Title : Population Genetic Structure of the Bonnethead Shark, Sphyrna tiburo From the Western North Atlantic Ocean Based on mtDNA Sequences

First Author : Elena Escatel-Luna Corr. Author : Píndaro Díaz-Jaimes AUTHOR QUERIES - TO BE ANSWERED BY THE CORRESPONDING AUTHOR The following queries have arisen during the typesetting of your manuscript. Please answer these queries by marking the required corrections at the appropriate point in the text. AQ1

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Journal of Heredity, 2015, 1–12 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

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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: Dr Jose Lopez

Abstract The population genetic structure of 251 bonnetheads, 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 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 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]

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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 (McCandless et al. 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 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 (nonGulf 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 NWA, 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. 2012). 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. 00, No. 00

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 TB (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 140 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 the sequence of S. tiburo from the Genbank as reference (accession

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Figure 1.  Sampling locations where genetic tissue samples of bonnetheads were collected.

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 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 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

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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 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

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

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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. b T is the time since population expansion.

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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. Black dots along the branches represent a “missing haplotype” that was not included in the sample.

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).

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

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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).

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

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).

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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

CAMP

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 and the southwestern Gulf of Mexico.

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 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

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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 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)

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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. 2012) 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. 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

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continental margins, was concluded as evidence of philopatry (DalyEngel et al. 2012). Evidence for philopatry in small scale has been reported also 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 (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 in 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. 2003; 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 to 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 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. Likewise, sampling efforts should be directed to collect young-of-the-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

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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. 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

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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. Thanks to the 3 anonymous reviewers for their comments which notably improved the manuscript.

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Journal of Heredity, 2015, Vol. 00, No. 00