Living Together but Remaining Apart:
Atlantic and Mediterranean Loggerhead
Sea Turtles (Caretta caretta) in Shared
Feeding Grounds
C ARLOS C ARRERAS, MARTA PASCUAL, LUIS C ARDONA, ADOLFO MARCO, JUAN JESÚ S BELLIDO, JUAN
JOSÉ C ASTILLO, JESÚ S TOMÁ S, JUAN ANTONIO RAGA, MANUEL SANFÉ LIX, GLORIA FERNÁ NDEZ, AND
ALEX AGUILAR
From the Department of Animal Biology, Faculty of Biology, University of Barcelona, Avda Diagonal 645, E-08028 Barcelona, Spain
(Carreras, Cardona, and Aguilar); the Biological Station of Doñana-CSIC-Apdo, 1056-E-41013 Sevilla, Spain (Carreras and Marco); the
Department of Genetics, Faculty of Biology, University of Barcelona, Avda Diagonal 645, E-08028 Barcelona, Spain (Pascual); the Centro
de Recuperación de Especies Marinas de Andalucı́a—Avda, Manuel Agustı́n Heredia n° 35, E-29001 Málaga, Spain (Bellido and Castillo);
the Marine Zoology Unit, Cavanilles Institute of Biodiversity and Evolutionary Biology, University of Valencia, Aptdo 22085, E-46071
Valencia, Spain (Tomás and Raga); the Marine Biology Laboratory, Department of Zoology, Faculty of Biology, University of Valencia,
C/Dr Moliner 50, E-46100 Burjasot, Valencia, Spain (Sanfélix); and the Aspro-Ocio Foundation, C/Garcilaso de la Vega, 9 E-07181
Costa d’en Blanes, Calvià, Spain (Fernández)
Address correspondence to Luis Cardona at the address above, or e-mail: luis.cardona@ub.edu.
Abstract
Juvenile loggerhead sea turtles (Caretta caretta) from Atlantic nesting populations migrate into the western Mediterranean,
where they share feeding grounds with turtles originating in the Mediterranean. In this scenario, male-mediated gene flow
may lead to the homogenization of these distant populations. To test this hypothesis, we genotyped 7 microsatellites from
56 Atlantic individuals sampled from feeding grounds in the western Mediterranean and then compared the observed allele
frequencies with published data of 112 individuals from Mediterranean nesting beaches. Mediterranean populations were
found to be genetically differentiated from the Atlantic stock reaching the western Mediterranean (Fst 5 0.029, P , 0.001);
therefore, the possible mating events between Atlantic and Mediterranean individuals are not sufficient to homogenize these
2 areas. The differentiation observed between these 2 areas demonstrates that microsatellites are sufficiently powerful for
mixed stock analysis and that individual assignment (IA) tests can be performed in combination with mitochondrial DNA
(mtDNA) analysis. In a set of 197 individuals sampled in western Mediterranean feeding grounds, 87% were robustly
assigned to Atlantic or Mediterranean groups with the combined marker, as compared with only 52% with mtDNA alone.
These findings provide a new approach for tracking the movements of these oceanic migrants and have strong implications
for the conservation of the species.
Key words: gene flow, isolation, microsatellite DNA, mitochondrial DNA
Loggerhead sea turtles (Caretta caretta) carry out vast
migrations across oceans throughout their lives (Bolten
2003). These fascinating migrations have been studied using
a large variety of techniques, including capture-taggingrecapture methods (Revelles et al. 2008), genetics (Bowen
and Karl 2007; Lee 2008), and satellite telemetry (Cardona
et al. 2005; Hawkes et al. 2007), but many important
questions remain unanswered. One of the most challenging
of these migrations is that undertaken by hatchlings from
nesting beaches in the northwestern Atlantic to foraging
grounds in the western Mediterranean (Bolten et al. 1998),
where they mix with juveniles born in Mediterranean nesting
areas (Carreras et al. 2006). Previous studies of Atlantic
nesting areas revealed that populations of sea turtles sharing
common feeding grounds are usually homogeneous at
nuclear DNA (nDNA) loci due to male-mediated gene flow,
although they may differ in mitochondrial DNA (mtDNA)
haplotype frequencies (Bowen et al. 2005). However, the
possibility of male-mediated gene flow from the Atlantic
into the Mediterranean remains to be tested.
Analyses using mtDNA markers have demonstrated that
Atlantic females do not nest in the eastern Mediterranean, as
some haplotypes that are frequent (i.e., CC-A1) in Atlantic
beach populations (Encalada et al. 1998; Monzon-Argü ello
et al. 2010) are not detected in the Mediterranean (Carreras
et al. 2007; Garofalo et al. 2009). However, the actual degree
of genetic isolation of the Mediterranean populations from
the Atlantic ones could not be properly assessed in these
analyses because only maternally inherited markers were
used (Bowen et al. 1993; Laurent et al. 1993, 1998; Encalada
et al. 1998). Male-mediated gene flow is common in
loggerhead sea turtles (Bowen et al. 2005; Carreras et al.
2007), and the coexistence of Atlantic and Mediterranean
loggerhead sea turtles in feeding grounds in the western
Mediterranean presents the possibility of a genetic connection between these very distant groups of populations.
Hormone levels, which were determined to sex Atlantic
loggerhead sea turtles from the western Mediterranean
feeding grounds, indicate an unusually high frequency of
males in this population, thus suggesting the possibility that
this migration into the western Mediterranean is male biased
(Casale et al. 2002). Hormone sex determination in marine
turtles can be imprecise and should be validated by
laparoscopy (Diez and van Dam 2003; Braun-McNeill
et al. 2007; Blanvillain et al. 2008) or histology (Mrosovsky
and Benabib 1990). However, direct gonadal examination of
stranded turtles from the western Mediterranean supported
the hypothesis of male-biased migration to the Mediterranean, as sex ratio was not significantly different from 1:1 in
that region (Casale et al. 2006), whereas the primary sex ratio
of these turtles is highly female biased in Mediterranean
nesting areas (Casale et al. 2006), Atlantic nesting areas, and
eastern Atlantic feeding grounds (Delgado et al. 2010).
Male-mediated gene flow would be possible only if adult
males were present in the western Mediterranean. Most of
the turtles in the western Mediterranean are immature
individuals and leave the region before reaching adulthood
(Revelles et al. 2007), but some individuals large enough to
be sexually mature have been recorded (Laurent et al. 1998;
Carreras et al. 2006; Casale, Freggi, Gratton, et al. 2008).
Thus, male-mediated gene flow from the Atlantic into the
Mediterranean could be possible if Atlantic males mate with
Mediterranean females. If not, this would mean that males
are philopatric to the nesting basin, similar to females.
Understanding the degree of isolation of these populations is important for the management of this species
because the conservation status of the Mediterranean and
Atlantic populations is very different. The Mediterranean
populations are smaller and genetically less diverse at the
mtDNA level than those in the Atlantic (Ehrhart et al. 2003;
Margaritoulis et al. 2003; Carreras et al. 2007). Moreover,
most of the Mediterranean populations have been dramatically reduced due to centuries of exploitation, degradation
of nesting, and internesting habitats and incidental catch,
whereas the impact of other threats, such as pollution and
boat collisions, remain poorly understood (Margaritoulis
et al. 2003; Casale and Margaritoulis 2010). Conversely, the
northwestern Atlantic supports the largest population of
loggerhead sea turtles in the Atlantic (Ehrhart et al. 2003),
despite recent declines (Witherington et al. 2009).
A second issue related to the simultaneous occurrence of
loggerhead sea turtles from Atlantic and Mediterranean
populations in feeding grounds of the western Mediterranean is methodological. Assessing the precise origin of each
individual turtle is relevant not only to understanding
migratory patterns and genetic structuring but also to
understand the actual significance of human impacts far
away from nesting beaches. In the Mediterranean, juvenile
and immature loggerhead sea turtles of all origins are
exposed to a much higher mortality rate (Casale, Freggi, and
Rocco 2008) than in the Atlantic (Bjorndal et al. 2003), but
this is relevant for Atlantic loggerhead sea turtles only if
large numbers of this population enter the Mediterranean.
The assignment of the origin of marine turtles in these
feeding grounds has been previously achieved using
mtDNA markers and ‘‘mixed stock analysis’’ (MSA)
(Laurent et al. 1998; Carreras et al. 2006; Maffucci et al.
2006). This technique estimates the percentage of the
individuals that come from each putative nesting area.
Given that female philopatry in marine turtles generates
strong genetic structure of mtDNA markers at different
nesting beaches, these markers are useful for MSA and have
been used to assess the contribution of turtles from diverse
areas to feeding grounds (Bowen and Karl 2007; Lee 2008).
However, MSA is unable to assess the origin of each
individual turtle in a feeding ground, and hence, clustering
methods are needed for ‘‘individual assignments’’ (IA)
(Pritchard et al. 2000). Because mtDNA differentiation
between loggerhead sea turtle populations rely mostly on
shifts in haplotype frequencies, IA is not possible in turtles
bearing common haplotypes. Furthermore, some putative
populations of origin mainly include individuals with
common haplotypes (e.g., Mediterranean nesting areas;
Carreras et al. 2007), whereas others have a much higher
proportion of individuals with exclusive haplotypes (e.g.,
Atlantic nesting areas; Encalada et al. 1998), and hence, the
utility of mtDNA markers for IA is population biased.
Despite this shortcoming, some studies have combined IA
based on mtDNA with hormonal sex determination (Casale
et al. 2002) or satellite telemetry (Polovina et al. 2000),
although a high percentage of the investigated specimens
could not be assigned for the reason explained above.
However, microsatellites have been used for IA studies in
many different species (Ciampolini et al. 2006; Sheehan et al.
2010) because the combination of several markers increases
the power of assignment; therefore, these microsatellites
could represent promising markers for the improvement of
either MSA or IA in marine turtles.
Thus, the aim of the present study was to use 7
microsatellite loci to test 1) if the presence of Atlantic
individuals in Mediterranean feeding grounds allows
connectivity between the Atlantic and the Mediterranean
nesting populations, 2) if the historic reductions in the
number of nesting females from Mediterranean populations
667
have produced a decrease in genetic variability compared
with the Atlantic nesting populations, and 3) assess the
usefulness of microsatellite loci to infer the origin of the
individuals found in western Mediterranean feeding grounds
using both MSA and IA.
Materials and Methods
Sampling and Molecular Methods
A total of 197 specimens were collected from loggerhead sea
turtle juveniles at 4 feeding sites in the western Mediterranean and the adjoining Atlantic (Figure 1, Table 1),
including southwestern Spain (SWS: west of the Strait of
Gibraltar), southeastern Spain (SES: east of the Strait of
Gibraltar to Palos Cape), the Pitiü ses islands (PIT: south
Balearic Islands), and the Gimnesies Islands (GIM: north
Balearic Islands). These feeding grounds showed a high
proportion of Atlantic individuals in previous studies
(Carreras et al. 2006) and for this reason were sampled.
Additionally, we sampled individuals from mideastern Spain
(MES: Palos Cape to Ebro Delta), a feeding ground not
previously analyzed. Specimens were collected from live and
dead individuals from 1998 to 2004. Live animals were
caught accidentally by fishermen, or samples were collected
from basking turtles by scuba divers (Ehrhart and Ogren
1999). To avoid pseudoreplication, all living turtles were
tagged with external flipper tags or subcutaneous PIT tags.
These procedures are expected to ensure the independency
of the collected specimens. Muscle or skin samples were
collected from each individual and stored in 95% ethanol.
DNA was extracted using the QIAamp extraction kit
(QIAGEN) following the manufacturer’s instructions.
We amplified a fragment of 391 bp of the mtDNA
control region in all the samples using the methodology
described in Carreras et al. (2006). According to Casale et al.
(2002), samples exhibiting the haplotype CC-A1 are
considered to be a group of Atlantic individuals entering
the Mediterranean (coded as ATL, Table 1) because
haplotype CC-A1 had previously been reported only from
north Atlantic nesting beaches (Encalada et al. 1998). The
fragment analyzed was long enough to detect the recently
described longer CC-A1 variants from Cape Verde (CCA1.3, CC-A1.4, and CC-A1.5; (Monzon-Argü ello et al. 2010)
and, hence, ensure that the individuals presenting these
variants were not included in the ATL group as previous
studies (Monzon-Argü ello et al. 2010) showed that Cape
Verde is an independent unit and that its contribution to the
Mediterranean is low. All the samples were genotyped for 7
microsatellites previously studied in this species: Cm84,
Cc117, Cm72, and Ei8 (Fitzsimmons et al. 1995); Cc141 and
Cc7 (Fitzsimmons et al. 1996); and Ccar176 (Moore and Ball
2002), as described in Carreras et al. (2007). A few samples
from Carreras et al. (2007) were genotyped again to ensure
that allele designations corresponded to the old data set. The
ATL group, selected using mtDNA as described above, was
used as representative of the microsatellite signature of
Atlantic individuals entering the Mediterranean, as although
Figure 1. Sampling locations. Circles mark sampled feeding grounds in the western Mediterranean: MES, mideastern Spain;
GIM, Gimesies; PIT, Pitiuses; SES, southeastern Spain; SWS, southwestern Spain. Nesting populations in the eastern
Mediterranean are from Carreras et al. (2007): GRE, Greece; CRE, Crete; WTU, western Turkey; CYP, Cyprus; LEB, Lebanon;
and ISR, Israel.
Carreras et al. • Genetic Structuring in Loggerhead Sea Tur tle Feeding Grounds
Table 1 Sampling locations
Location
Feeding grounds
Southwestern Spain
Southeastern Spain
Mideastern Spain
Pitiuses
Gimnesies
Global Atlantic visitors
Mediterranean nesting populations
Greece
Crete
Western Turkey
Cyprus
Lebanon
Israel
Global eastern Mediterranean
Code
na
Ho
He
NA
SWS
SES
MES
PIT
GIM
ATL
40 (13)
47 (15)
35 (7)
43 (9)
32 (12)
(56)
0.65
0.62
0.83
0.62
0.76
0.68 ± 0.17
0.73
0.72
0.73
0.73
0.75
0.72 ± 0.21
6.57
6.57
5.28
5.14
4.87
11.86 ± 3.53
GRE
CRE
WTU
CYP
LEB
ISR
MED
39
18
16
10
9
20
112
0.56
0.62
0.68
0.70
0.63
0.67
0.63 ± 0.23
0.63
0.66
0.66
0.72
0.72
0.70
0.67 ± 0.25
7.00
6.43
5.71
5.86
6.43
7.00
10.29 ± 3.25
Including their abbreviation code, number of individuals (n), observed heterozygosity (Ho), gene diversity (He), and allele diversity (NA) using
microsatellites.
a
Number in parenthesis indicates the total number of individuals that have the CC-A1 haplotype and were selected as Atlantic visitors into the
Mediterranean (coded as ATL: see Materials and Methods). The diversity values in feeding grounds correspond only to ATL individuals. Mediterranean data
from nesting populations are from Carreras et al. (2007).
the CC-A1 frequencies may change across the Atlantic A sequential Bonferroni correction was not applied for
nesting beaches, the microsatellite frequencies do not multiple pairwise comparisons, as Bonferroni procedures
dramatically increase the probability for type II error
(Bowen et al. 2005).
(b: assume no differentiation when it does exist), and this
effect becomes worse as many P values are discarded
Genetic Variability and Differentiation between Basins
(Perneger 1998; Cabin and Mitchell 2000; Moran 2003). In
The microsatellite data from the individuals of the ATL substitution, we applied the false discovered rate (FDR)
group were compared with the 112 individuals genotyped by correction that calculates the most appropriate threshold for
Carreras et al. (2007) sampled from 7 nesting areas in the P value significance considering the multiple comparisons
eastern Mediterranean (Table 1, Figure 1) during the 2003 involved in the analysis under an expected original threshold
and 2004 nesting seasons. This previous study comprised of P , 0.05 (Narum 2006).
the following populations: Greece (GRE: samples from
The genetic structure between the Atlantic migrants and
Zakynthos Island and Lakonikos Bay); Crete (CRE: the Mediterranean nesting populations was also analyzed
Rethymno); western Turkey (WTU: Fethiye, in the using a principal components analysis (PCA) with the
southwest); northern Cyprus (CYP); Lebanon (LEB: El package GENALEX version 6.2 (Peakall and Smouse 2006).
Mansouri); and nesting sites scattered along the coastline of The existence of barriers to the gene flow between
Israel (ISR). Different measures of variability, such as gene populations was explored using the software BARRIER
diversity (He), observed heterozygosity (Ho), and number of version 2.2 (Manni et al. 2004) and considering a barrier as
alleles (NA), were calculated using GENECLASS version an abrupt rate of change in the genetic profile of the
2.0 (Piry et al. 2004) for all these groups of samples. The populations. This software implements a maximum differdifferences in these parameters among all sampling sites ence algorithm (Monmonier 1973) within a computational
were assessed using the nonparametric Kruskal–Wallis test geographic scale to detect barriers and establish the relative
implemented in STATISTICA version 6.0. Linkage disequi- importance of these barriers for genetic dispersion.
librium between pairs of loci and departures from Hardy–
Population structure was also assessed using the program
Weinberg expectation were tested for each locus and STRUCTURE version 2.1 (Pritchard et al. 2000), which
population. We also conducted tests for pairwise population implements a Bayesian clustering method to identify the
differentiation (Fst), and significance was calculated using most likely number of populations (K) without using a priori
a Markov chain randomization (Guo and Thompson 1992) information on sampling locations. This program groups
with an unbiased estimate of the P value of a log-likelihood individuals into K populations to achieve Hardy–Weinberg
ratio (G)–based exact test (Goudet et al. 1996). All these and linkage equilibrium. Following the search strategy
statistical analyses were conducted using GENEPOP described in Evanno et al. (2005), 20 runs were carried
version 4.0 (Raymond and Rousset 1995). We also out for each value of K (from 1 to 10). Most of the
calculated the recently proposed Dst parameter (Jost parameters in the analysis were set to their default values,
2008), which was implemented in SMOGD (Crawford but we used the correlated allele frequencies option, as
2010), as an alternative measurement of genetic distance. recommended in cases of low population structure (Falush
et al. 2003), and we allowed the program to infer alpha
(degree of admixture) from the data. We set the length of
the burn-in and Markov chain Monte Carlo to 100 000, as
preliminary tests showed that the results did not change
substantially with a longer burn-in. We used the ad hoc
statistic DK (Evanno et al. 2005) to detect the number of
clusters in our sample, and we also calculated the statistic Pr
(X/K) as described in the manual of the program. Once the
number of populations was assessed, prior information was
used to test whether the individuals were correctly
reassigned to each population.
Origin of Juveniles in Feeding Grounds
An MSA was conducted using microsatellite data from the
5 feeding sites employing the same methodology as
described by Carreras et al. (2006) with the program
Bayes (Pella and Masuda 2001) and implementing the
Bayesian model BM2 because it has been proposed to be
the most accurate model for marine turtles MSA (Bass
et al. 2004; Carreras et al. 2006). As a baseline, we used the
data set including the known Atlantic visitors (ATL) from
the present study and all samples from Mediterranean
nesting populations (Carreras et al. 2007). To compare
both microsatellites and mtDNA, we also performed an
MSA for the mtDNA data employing the same methodology as described above and using the baseline from
Carreras et al. (2006).
IA were made for all 197 individuals found in the feeding
grounds using a combination of microsatellites and
mtDNA. When an exclusive mtDNA haplotype from
a nesting area was present in an individual, this individual
was directly assigned to this nesting area without any further
analysis. All individuals presenting common mtDNA
haplotypes or haplotypes not assigned to any particular
nesting area were genotyped for the 7 microsatellites and
individually assigned using the program STRUCTURE
version 2.1 (Pritchard et al. 2000) considering the same
baseline as used for MSA. Hence, a probability of being
either Atlantic or Mediterranean will be ascribed to each
individual. Additionally, some individuals bearing haplotypes other than CC-A1, but also exclusive of known
nesting areas, were genotyped for the 7 microsatellites and
used as controls to validate the IA test.
Results
Genetic Variability and Differentiation between Basins
No linkage disequilibrium was found between any loci pair in
our sampling set (chi square, P . 0.05 in all cases), and hence,
independence of loci was assumed. A total of 56 out of the
197 analyzed juveniles from the western Mediterranean
feeding grounds exhibited the Atlantic haplotype CC-A1, so
the microsatellite data of these samples were considered as
representative of the Atlantic stock entering the Mediterranean and coded as ATL throughout the manuscript (Table 1).
No statistical differences were found when comparing ATL
individuals from different feeding grounds using the 7
microsatellite loci (overall Fst 5 —0.034, P . 0.05); thus, they
were grouped for posterior analysis.
No departure from Hardy–Weinberg equilibrium (chi
square, P . 0.05 in all cases) was detected for the ATL
group. However, when all the samples from Mediterranean
nesting populations are grouped, the resulting group departs
from Hardy–Weinberg equilibrium (chi square, P , 0.05),
thus reflecting the heterogeneity among Mediterranean
nesting populations, as previously reported (Carreras et al.
2007). The results did not change when using the P value
threshold suggested by the FDR correction in any multiple
comparisons. No significant differences were found in terms
of genetic variability (He, Ho, and NA) between the Atlantic
individuals found in feeding grounds (ATL) and any of the
single Mediterranean nesting areas (Kruskall–Wallis, P .
0.05 in all cases, Table 1).
Significant genetic structure was observed among
populations (overall Fst 5 0.029, P , 0.05, Table 2).
Comparisons involving the Atlantic individuals and Mediterranean populations yielded the highest and most
significant Fst and Dst values, which were usually one order
of magnitude higher than those involving any 2 Mediterranean nesting sites (Table 2). The only exception was the
comparison between ATL and CYP, although the P value
was very close to the FDR threshold (P 5 0.0159).
The PCA based on microsatellite Fst values clearly
separated the ATL group from all sampled Mediterranean
nesting areas, with the first 2 principal components
explaining 81.24% of the observed genetic variability (Figure
2). Similar results were found when using the Dst genetic
Table 2 Genetic differentiation of nesting areas using microsatellites
ATL
GRE
CRE
WTU
CYP
LEB
ISR
ATL
GRE
CRE
WTU
CYP
LEB
ISR
—
0.0356
0.0385
0.0409
0.0141
0.0263
0.0133
0.0816
—
—0.0046
0.0072
0.0013
0.0041
0.0160
0.0597
—0.0002
—
0.0110
0.0044
—0.0045
0.0078
0.0376
0.0031
0.0047
—
0.0046
0.0071
0.0153
0.0334
—0.0005
0.0000
0.0005
—
—0.0036
0.0129
0.0244
0.0003
—0.0004
0.0145
—0.0003
—
0.0096
0.0113
0.0186
—0.0002
0.0031
0.0025
0.0060
—
Below the diagonal, Fst values between each population pairs; above the diagonal, Dst values. Significant values given by the G exact test are in bold below the
diagonal considering the FDR threshold P , 0.0137. ATL, Atlantic visitors (see Materials and Methods); GRE, Greece; CRE, Crete; WTU, western Turkey;
CYP, Cyprus; LEB, Lebanon; ISR, Israel. Mediterranean data from nesting populations are from Carreras et al. (2007).
Mediterranean hatchlings (one from Cyprus and one from
Israel; Carreras et al. 2007) were assigned to the Atlantic
(cluster 1) with a probability higher than 80% (Figure 4).
Principal Coordinates (F st)
Coord. 2 (16.87%)
ISR
CRE
Origin of Juveniles in Feeding Grounds
GRE
LEB
ATL
CYP
TUR
Coord. 1 (64.38%)
Principal Coordinates (D st)
Coord. 2 (10.29%)
TUR
GRE
ATL
LEB
CYP
CRE
ISR
Coord. 1 (87.32%)
Figure 2. PCA using Fst and Dst genetic distances. The
analysis includes the Atlantic individuals entering the
Mediterranean (ATL: see Materials and Methods) and the
Mediterranean nesting populations (GRE, Greece; CRE, Crete;
WTU, western Turkey; CYP, Cyprus; LEB, Lebanon; ISR,
Israel). The percentage of variation explained for each
coordinate is indicated in brackets.
distance, but with the first 2 principal components explaining 97.61% of the observed genetic variability (Figure 2). As
revealed by the program BARRIER, the most important
barrier to gene flow separated the Atlantic individuals from
all the Mediterranean nesting populations (Figure 3). Three
additional barriers were encountered between the Mediterranean nesting populations, which divided them along an
east–west axis (Figure 3).
Analyses using the software STRUCTURE without
including any prior information on the origin of samples
resulted in the post hoc statistic DK decreasing from K 5 1,
with a secondary peak at K 5 5, suggesting the existence of
a contact zone (Evanno et al. 2005) formed by 5 groups.
This result agreed with the existence of the major break
between the ATL and Mediterranean populations detected
by PCA and BARRIER software and the existence of 4
groups at a lower level in the Mediterranean, as detected in
previous studies (Carreras et al. 2007).
Considering all this evidence, prior information was used
to check for reassignment taking into account the 2 groups
that reflect the major discontinuity, the Atlantic and
Mediterranean groups. All Atlantic (ATL) individuals were
assigned to cluster 1 with a probability greater than 80%, and
all but 13 Mediterranean individuals (88.4%) were assigned to
cluster 2 with a probability higher than 80%. Two
The MSA yielded similar results for both microsatellites and
mtDNA, indicating that SE Spain, SW Spain, Gimnesies,
and Pitiü ses were inhabited almost exclusively by Atlantic
turtles, whereas MES had a mixture of individuals coming
from Atlantic or Mediterranean nesting areas (Figure 5). The
confidence intervals were smaller for microsatellites.
A total of 102 individuals (51.78%), including those 56
used as a baseline from ATL, were directly assigned (IA)
using only mtDNA data because they bore haplotypes
exclusive to either the Mediterranean or the Atlantic nesting
areas (Table 3). From these samples, microsatellites were
analyzed for 15 individuals and used as controls to validate
the IA tests using microsatellites (Table 4). A total of 13 of
these control individuals were assigned to the corresponding
expected area with a high probability, including those
individuals with CC-A1 variants from Cape Verde (.0.8,
Table 4). One control sample bearing CC-A7 was incorrectly
assigned (sample V25, Table 4). The remaining 95 turtles were
individually assigned using microsatellites. A total of 73.68%
of these individuals were included in either cluster 1 (Atlantic)
or cluster 2 (Mediterranean) with a high probability (.0.8),
including some specimens where mtDNA amplification failed
as a result of their degraded status (Table 3). As a result,
almost all specimens from feeding grounds (87.31%) could be
individually assigned using exclusive mtDNA haplotypes and
significant microsatellite assignments (Table 3).
Discussion
Juvenile loggerhead sea turtles from western Atlantic nesting
beaches are thought to reach the Mediterranean through the
Gulf Stream by following magnetic cues (Lohmann KJ and
Lohmann CMF 2003). Once in the Mediterranean, they may
remain trapped for approximately 8 years due to the barrier
imposed by currents around the Strait of Gibraltar (Revelles
et al. 2007; Eckert et al. 2008). Determining whether these
individuals contribute to the gene pool of the Mediterranean
populations is a major challenge that remained to be tested prior
to this study. The present study represents a unique opportunity
for comparing the genetic profile of the migrant turtles as
opposed to members of the possible recipient populations.
Genetic Variability and Differentiation between Basins
The microsatellite frequency distribution in the Atlantic
visitors and the Mediterranean nesting populations revealed
significant genetic differentiation between the 2 stocks. Such
a level of differentiation also agrees with that revealed by
mtDNA (Bowen et al. 1993; Encalada et al. 1998; Laurent
et al. 1998), and the overall evidence suggests that this level
of differentiation is one step higher than that found between
the different Mediterranean nesting populations. Previous
studies of Atlantic nesting areas revealed that populations of
Figure 3. Geographic representation of the 4 strongest barriers to the gene dispersion in the Mediterranean. Barriers are
represented by the arrows, and each number represents its relative importance using BARRIER version 2.2 (ATL, Atlantic
individuals, see Materials and Methods; GRE, Greece; CRE, Crete; WTU, western Turkey; CYP, Cyprus; LEB, Lebanon; ISR,
Israel).
sea turtles sharing common feeding grounds are usually
homogeneous at the nDNA level due to male-mediated
gene flow, although they may differ at the mtDNA level
(Bowen et al. 2005). Based on our results, this is clearly not
the case in the western Mediterranean feeding grounds
because the Atlantic individuals and Mediterranean nesting
populations sharing the same feeding grounds remain
genetically isolated despite being no evidence of physical
barriers to the gene flow. This is not unprecedented, as it
was previously reported for other marine turtle species and
interpreted as male philopatry (FitzSimmons et al. 1997). At
least 2 non-exclusive reasons may explain such a paradox.
The first explanation is that the encounter probability
between 2 individuals coming from different nesting areas is
low. The relative abundance of Atlantic and Mediterranean
turtles is, indeed, highly variable among their western
Mediterranean feeding grounds, and although turtles from
both origins co-occur everywhere, both populations are
present at a high frequency only in MES (Carreras et al.
2006; present study). Hence, the probability that 2 individuals
of different origin will meet is lower than previously suggested
(Laurent et al. 1993, 1998; Casale et al. 2002). The second
reason is that most of the individuals found at shared feeding
grounds are juveniles. Although individuals as large as 100 cm
straight carapace length (SCL) can be found, the mean values
from the feeding grounds are around 50 cm SCL (Carreras
et al. 2006; Tomas, Gozalbes, et al. 2008), whereas turtles
rarely mature at sizes below 60 cm SCL (Margaritoulis et al.
2003). Hence, most of these individuals should be considered
as immature (Margaritoulis et al. 2003; Casale and Margaritoulis 2010). Furthermore, Atlantic loggerhead sea turtles are
known to leave the Mediterranean at an average length of 54.5
cm SCL (Revelles et al. 2007). Previous mtDNA studies
showed that large juveniles and adults caught by bottom
trawlers (presumably adults and subadults in a neritic stage)
mostly originated from Mediterranean nesting areas, although
a few mature Atlantic individuals have been found (Laurent
et al. 1998; Casale, Freggi, Gratton, et al. 2008). Thus, the
overall evidence indicates that almost all Atlantic individuals
leave the western Mediterranean before they reach maturity
and that the probability that 2 mature individuals of different
origins will meet and mate in the western Mediterranean
feeding grounds is very low. However, the presence of eastern
Mediterranean hatchlings (sampled in Carreras et al. 2007)
with high assignment values to the Atlantic population
suggests the presence of some minor gene flow between the
Atlantic and the Mediterranean nesting areas (present study).
This possible gene flow could increase the genetic variability in
the Mediterranean, but it is evident that this effect is not large
enough to prevent isolation between the 2 basins. A recent
paper (Wallace et al. 2010) extended the definition of
population units for marine turtles and suggested the inclusion
of the regional management units (RMUs) as conservation
units above the level of nesting populations to complement
the classical definitions of management units (MUs) or
evolutionary significant units (ESUs) (Moritz 1994). The new
data of the present study fit with this hypothesis and indicate
that the Atlantic and Mediterranean should be considered
different RMUs although they geographically overlap in the
western Mediterranean. Furthermore, the classification of the
Atlantic and Mediterranean loggerhead populations as separate
RMUs, on the basis of our data, does neither negate nor
contradict the fact that each of these units is made up of
several MUs (Encalada et al. 1998; Carreras et al. 2007).
Origin Assessment of Juveniles in Feeding Grounds
The ability to assess the origin of marine turtles at
a particular feeding ground represents a milestone for
developing conservation strategies because it allows managers to link threats at sea with the nesting populations
ultimately impacted by them. The results presented here
demonstrate that microsatellite loci provide an alternative to
mtDNA for MSA when assessing the relative contribution
of Atlantic and Mediterranean populations at a particular
feeding ground. Moreover, these hypervariable nuclear
markers generate the same results as mtDNA markers but
with narrower confidence intervals. However, loggerhead
sea turtle males are much less philopatric than females either
in the Atlantic (Bowen et al. 2005) or in the Mediterranean
(Carreras et al. 2007), hence resulting in intense malemediated gene flow among the nesting beaches within each
basin that dilutes the genetic signature of each specific
nesting beach. Hence, this nDNA basin philopatry
Figure 4. Summary of the reassignation results using the 2 clusters defined by the program STRUCTURE. Each vertical bar
shows the estimated probability of one individual to belong to one of the 2 clusters using Mediterranean samples (dark gray cluster)
and Atlantic samples (light gray cluster). X axis indicates the real origin of the sample reassigned: Mediterranean (MED) or Atlantic
(ATL: see Materials and Methods).
represents a difficulty when the primary goal of a study is to
identify the specific nesting beach of origin of the turtles
using a particular feeding ground. As a result, due to female
philopatry, mtDNA markers could be better than microsatellites when doing MSA to specific nesting areas, that is,
to assess contribution of MUs (Moritz 1994), although the
confidence intervals will always be wide. On the other hand,
microsatellites could be more useful when doing MSA at
a basin level, that is, to assess contribution of different
RMUs (Wallace et al. 2010).
Independently of the markers used, MSA resolves the
relative contribution of several populations to a particular
feeding ground but cannot identify the origin of individual
turtles in the sample. IA is difficult to perform based
exclusively on mtDNA data in this case due to the high
frequency of shared haplotypes. The Mediterranean was
colonized by individuals from the Atlantic approximately
12 000 years ago (Bowen et al. 1993), and hence, most
individuals exhibit haplotypes that are common to both
areas (such as CC-A2 or CC-A3). Furthermore, exclusive
haplotypes are very rare in the Mediterranean (Carreras et al.
2007), whereas much more common in the Atlantic
(Encalada et al. 1998). As a consequence, the results of IA
based on mtDNA data are highly biased, as almost no turtle
from the Mediterranean nesting beaches can be identified by
this method. In this study, we demonstrated that microsatellites combined with mtDNA dramatically improve IA
in shared feeding grounds, assigning 87% of the individuals
in the sample in contraposition of only a 52% of the
samples being assigned using only mtDNA.
Nevertheless, the method has limitations, as demonstrated by a control individual that was assigned to a nesting
beach in the Atlantic on the basis of mtDNA haplotype
(CC-A7) but which was assigned to a Mediterranean nesting
beach according to microsatellites. One of the possible
explanations for this result is that haplotypes at low
frequencies are usually hard to find, and CC-A7 could be
present in Mediterranean populations at low frequency. This
is not unprecedented, as haplotype CC-A20, which was
thought to be exclusive to Atlantic nesting areas, was found
recently in the Mediterranean (Garofalo et al. 2009).
Furthermore, small sample sizes and small numbers of loci
being used are common shortcomings in defining populations in endangered species (Waples and Gaggiotti 2006),
including loggerhead sea turtles.
The fact that all the CC-A1 individuals and almost all the
control individuals were correctly reassigned demonstrates
that this methodology is powerful for performing IA for
western Mediterranean loggerhead turtles, indicating that
these positive assignments are robust. The application of IA
with microsatellites in combination with mtDNA is an
alternative approach to MSA. For instance, MSA usually
A
1
0,8
0,6
ATL
MED
0,4
0,2
0
SW S
SES
MES
PIT
GIM
B
1
0,8
0,6
ATL
MED
0,4
0,2
0
SW S
SES
MES
PIT
GIM
Figure 5. Proportion of individuals in the feeding grounds
born in the Atlantic (ATL: see Materials and Methods) or the
Mediterranean (MED) nesting areas. The proportion was
obtained using an MSA under BM2 model showing the 0.5
confidence intervals. (A) Using mtDNA; (B) Using
microsatellites (MES, mideastern Spain; GIM, Gimesies; PIT,
Pitiuses; SES, southeastern Spain; SWS, southwestern Spain).
673
Table 3 Summary of IA combining both mtDNA and
microsatellites
Haplotype
CC-A1
CC-A2
CC-A3
CC-A5
CC-A6
CC-A7
CC-A9
CC-A11
CC-A12
CC-A13
CC-A14
CC-A17
CC-A20
CC-A21
CC-A26
CC-A27
No mtDNA
Total
Origin
Atlantic
Shared
Shared
Atlantic
Mediterranean
Atlantic
Atlantic
Atlantic
Unknown
Unknown
Atlantic
Atlantic
Shared
Unknown
Unknown
Unknown
Unknown
n
ATL
a
87
72
5
2
1
1
4
2
1
1
4
1
2
2
2
1
9
197
87
48
1
2
MED
10
1
Unknown
14
3
1
1
4
2
1
1
4
1
1
2
4
159
1
13
2
1
5
25
a
Includes 9 samples with CC-A1.1 variant from Cape Verde and the 56
samples used from the group ATL (see Materials and Methods).
fails to distinguish between low contribution and no
contribution, as it assumes that all nesting areas are
contributing, which is an assumption that might produce
spurious results (Engstrom et al. 2002). IA is a powerful
method that can detect even weak contributions of some
nesting areas because each individual is treated separately.
This methodology has been successfully used to demonstrate that individuals born in the Mediterranean basin move
to the nearby Atlantic (Revelles et al. 2007).
Implications for Conservation
It was proposed that nesting populations of loggerhead sea
turtles in the Mediterranean should be catalogued as critically
endangered at the end of the 20th century based on
contemporary threats, reduced population sizes, and apparent
declines in the last decades (Groombridge 1990). However,
no genetic studies were included in this recommendation to
assess whether Mediterranean populations were isolated or if
the recent reductions of population sizes have affected the
genetic diversity of these turtles. The present study fills that
gap, as it demonstrates that Mediterranean populations are
genetically unique and isolated from Atlantic populations.
This finding implies that the fate of the Mediterranean
populations is genetically and demographically independent
from that of populations in the Atlantic. As a consequence,
Mediterranean populations emerge as an independent MU.
Furthermore, the genetic uniqueness detected by neutral
markers might be reflected in morphological and adaptive
traits because loggerhead sea turtles that nest in the different
Mediterranean MUs are significantly smaller at maturity than
turtles from other Atlantic populations (Margaritoulis et al.
2003). Whether this trait is adaptive or just a result of
phenotypic plasticity remains unsolved, but if it is adaptive,
an increase of gene flow between Mediterranean and
674
Table 4 IA of samples bearing mtDNA haplotypes exclusive
from either the Atlantic (ATL: see Materials and Methods) or the
Mediterranean (MED)
Sample
name
Mev-11
P7
V36
V25
FOR1
F40
F42
FOR11
A19
A59
A21
A61
A22
A35
A54
A60
A22
A39
F43
Location
GIM
GIM
MES
MES
PIT
PIT
PIT
PIT
SES
SES
SWS
SWS
SWS
SWS
SWS
SWS
SWS
SES
PIT
mtDNA
haplotype
CC-A1a
CC-A1a
CC-A6
CC-A7
CC-A14
CC-A14
CC-A5
CC-A9
CC-A1a
CC-A1a
CC-A1a
CC-A1a
CC-A17
CC-A9
CC-A9
CC-A12
CC-A21
CC-A21
CC-A13
Origin of
haplotype
ATL
ATL
MED
ATL
ATL
ATL
ATL
ATL
ATL
ATL
ATL
ATL
ATL
ATL
ATL
UNKNOWN
UNKNOWN
UNKNOWN
UNKNOWN
Prob
MED
0.017
0.044
0.975
0.883
0.006
0.019
0.001
0.073
0.085
0.002
0.002
0.159
0.018
0.012
0.301
0.000
0.133
0.149
0.012
Prob
ATL
0.980
0.905
0.025
0.117
0.994
0.979
0.999
0.927
0.912
0.998
0.998
0.841
0.982
0.988
0.699
1.000
0.867
0.851
0.988
Assignations are shown as probabilities to belong to the Mediterranean
(Prob MED) or the Atlantic (Prob ATL) areas. Bold indicates probabilities
higher than 0.8. Additionally, samples of individuals with mtDNA
haplotypes not yet found in any nesting area (UNKNOWN) with high
assignation probability (.0.8) are shown.
a
Indicates Cape Verde CC-A1 variants described in Monzón-Argüello et al.
2010.
Atlantic nesting areas could compromise the genetic
integrity of each area and cause outbreeding depression
due to dilution of local adaptations (Frankham et al. 2002).
Conversely, inbreeding depression is not a threat for the
Mediterranean populations, as the levels of nuclear genetic
variability in the Mediterranean nesting populations are
similar to those found in the individuals coming from the
Atlantic nesting area, despite the smaller population sizes of
the Mediterranean nesting populations and the lower level
of mtDNA variability in the Mediterranean (Bowen et al.
1993; Encalada et al. 1998; Laurent et al. 1998; Carreras et al.
2007). Several factors can explain these observations. First,
the effective population size represented by mtDNA is 4fold lower than that of diploid nDNA loci (Birky et al.
1983). Thus, the former marker would have been more
affected by the loss of diversity as a result of founder events
during the colonization of Mediterranean nesting areas by
Atlantic individuals. Second, differences in male and female
philopatry are known to produce situations where populations are isolated in terms of mtDNA, but not in terms of
nDNA (Bowen et al. 2005; Carreras et al. 2007).
Consequently, an ancestral scenario of colonization characterized by continuous male-mediated gene flow in the initial
stages, with a resulting smaller bottleneck for autosomal loci,
is possible. Third, the higher diversity observed in nDNA
could also be a consequence of the higher mutation rate of
microsatellites (2 x 10—3 My—1, Ellegren 2000) compared
with the mtDNA control region (2 x 10—8 My—1, Encalada
et al. 1998). Fourth, it is possible that the effects of the
recent decline of Mediterranean nesting populations are not
yet reflected in the genetic diversity of these populations,
considering the long generation time of these marine turtles
compared with the relative proximity of population reduction. Finally, the low levels of gene flow detected in the
present study could increase the genetic variability in the
Mediterranean, despite the fact that these levels are not
enough to prevent population-level isolation.
Unfortunately, we have no evidence of what the normal
levels of genetic variability in the Mediterranean would be (i.e.,
prior to human influence) because no samples to test this
hypothesis are available from these turtles before their first
decline. One of the main pitfalls affecting endangered
populations of marine turtles is that all their natural
populations have been affected by human threats, and hence,
there are no reference values of healthy genetic variability
available. However, the magnitudes of the threats affecting
population size are not equal, and for this reason, the results
of comparing the genetic variability of populations with very
different conservation statuses provide valuable insight about
the relative loss of genetic diversity.
The existence of similar levels of variability in Atlantic
and Mediterranean individuals indicates a similar conservation status from the genetic point of view, although this
does not necessarily imply the existence of acceptable levels
of genetic variability in these populations. However, their
different population census sizes should be considered,
especially if there is a delay in detecting population declines
using molecular markers. Thus, a continuation of the
reduction of Mediterranean nesting populations may be
disastrous. Neutral markers, such as those used here, are
most appropriate for detecting demographic processes such
as reductions in genetic variability, isolation, or gene flow
between populations. However, integrated studies of
adaptive divergence (life-history and morphological traits)
and genetic differentiation should be carried out to correctly
assign conservation resources and describe ESUs (Crandall
et al. 2000; Fraser and Bernatchez 2001). These issues
should certainly be addressed in future studies to complete
our understanding of the scenario described here.
One of the major conservation challenges of highly
migratory marine species is to link threats at sea with the
reproductive populations (Hamann et al. 2010). For instance,
high numbers of loggerhead sea turtles are caught accidentally
every year by fishing operations in the western Mediterranean
(Casale and Margaritoulis 2010) that could affect 2 very distant
nesting areas (Carreras et al. 2006). The present study provides
a means to link those fishery-induced mortalities to source
populations but also is a case study to develop alternative tools
that could be applied to other regions and species.
gı́a
of the Spanish Government (CGL2009-10017,
CGL2006-13423); the Banco Bilbao Vizcaya Argentaria
Foundation (BIOCON08-187); the Regional Activity Centre
for Specially Protected Areas of the Mediterranean Action
Plan (United Nations Environment Programme) in Tunis.
Funding
Cardona L, Revelles M, Carreras C, San Felix M, Gazo M, Aguilar A. 2005.
Western Mediterranean immature loggerhead turtles: habitat use in spring
and summer assessed through satellite tracking and aerial surveys. Mar Biol.
147:583–591.
Life program of the European Union (LIFE00NAT/E/
7303); the Comisión Interministerial de Ciencia y Tecnolo-
Acknowledgments
The ‘‘Fundació pel Desenvolupament Sostenible’’ provided logistic support
for the fieldwork. The samples from turtles on the Balearic archipelago
were provided by the tissue bank of the University of Barcelona, with the
support of the Pew Fellows Program in Marine Conservation and
Earthtrust. We thank Alnitak and the Volunteer Stranding Network of
the Andalusian Coast for their help in sampling in the South Spain. We also
thank the Biodiversity Department of the Conselleria de Medio Ambiente,
Agua, Urbanismo y Vivienda of the Valencia Government for its support in
the sampling of turtles from the MES area. Some of the authors are part of
the research groups 2009SGR-636 and 2009SGR-842 of the Generalitat de
Catalunya.
References
Bass AL, Epperly SP, Braun-McNeill J. 2004. Multi-year analysis of stock
composition of a loggerhead turtle (Caretta caretta) foraging habitat using
maximum likelihood and Bayesian methods. Conserv Genet. 5:783–796.
Birky CW, Maruyama T, Fuerst P. 1983. An approach to population and
evolutionary genetic theory for genes in mitochondria and chloroplasts, and
some results. Genetics. 103:513–527.
Bjorndal KA, Bolten AB, Martins HR. 2003. Estimates of survival
probabilities for oceanic-stage loggerhead sea turtles (Caretta caretta) in the
North Atlantic. Fish B-NOAA. 101:732–736.
Blanvillain G, Wood LD, Meylan A, Meylan PB. 2008. Sex ratio prediction
of juvenile Hawksbill sea turtles (Eretmochelys imbricata) from South Florida.
Herpetol Conserv Biol. 3:21–27.
Bolten AB. 2003. Variation in sea turtle life history patterns: neritic vs. oceanic
developmental stages. In: Lutz P, Musick JA, Wyneken J, editors. Biology of
sea turtles: volume II. Boca Raton (FL): USA CRC Press. p. 243–257.
Bolten AB, Bjorndal KA, Martins HR, Dellinger T, Biscoito MJ, Encalada
SE, Bowen BW. 1998. Transatlantic developmental migrations of loggerhead
sea turtles demonstrated by mtDNA sequence analysis. Ecol Appl. 8:1–7.
Bowen BW, Avise JC, Richardson JI, Meylan A, Margaritoulis D, HopkinsMurphy SR. 1993. Population structure of loggerhead turtles (Caretta caretta)
in the Northwestern Atlantic Ocean and Mediterranean Sea. Conserv Biol.
7:834–844.
Bowen BW, Bass AL, Soares L, Toonen RJ. 2005. Conservation
implications of complex population structure: lessons from the loggerhead
turtle (Caretta caretta). Mol Ecol. 14:2389–2402.
Bowen BW, Karl SA. 2007. Population genetics and phylogeography of sea
turtles. Mol Ecol. 16:4886–4907.
Braun-McNeill J, Epperly S, Owens DW, Avens L, Williams E, Harms CA.
2007. Seasonal reliability of testosterone radioimmunoassay (RIA) for
predicting sex ratios of juvenile loggerhead (Caretta caretta) turtles.
Herpetologica. 63:275–284.
Cabin RJ, Mitchell RJ. 2000. To Bonferroni or not to Bonferroni: when and
how are the questions. Bull Ecol Soc Am. 81:246–248.
Carreras C, Pascual M, Cardona L, Aguilar A, Margaritoulis D, Rees A,
Turkozan O, Levy Y, Gasith A, Aureggi M, et al. 2007. The genetic
structure of the loggerhead sea turtle (Caretta caretta) in the Mediterranean as
revealed by nuclear and mitochondrial DNA and its conservation
implications. Conserv Genet. 8:761–775.
Carreras C, Pont S, Maffucci F, Pascual M, Barcelo A, Bentivegna F, Cardona
L, Alegre F, SanFelix M, Fernandez G, et al. 2006. Genetic structuring of
immature loggerhead sea turtles (Caretta caretta) in the Mediterranean Sea
reflects water circulation patterns. Mar Biol. 149:1269–1279.
Casale P, Freggi D, Gratton P, Argano R, Oliverio M. 2008. Mitochondrial
DNA reveals regional and interregional importance of the central
Mediterranean African shelf for loggerhead sea turtles (Caretta caretta). Sci
Mar. 72:541–548.
Casale P, Freggi D, Rocco M. 2008. Mortality induced by drifting longline
hooks and branchlines in loggerhead sea turtles, estimated through
observation in captivity. Aquat Conserv. 18:945–954.
Casale P, Laurent L, Gerosa G, Argano R. 2002. Molecular evidence of
male-biased dispersal in loggerhead turtle juveniles. J Exp Mar Biol Ecol.
267:139–145.
Casale P, Lazar B, Pont S, Tomas J, Zizzo N, Alegre F, Badillo J, Di Summa
A, Freggi D, Lackovic G, et al. 2006. Sex ratios of juvenile loggerhead sea
turtles Caretta caretta in the Mediterranean Sea. Mar Ecol Prog Ser.
324:281–285.
Casale P, Margaritoulis D. 2010. Sea turtles in the Mediterranean:
distribution, threats and conservation priorities. Gland (Switzerland):
IUCN/SSC Marine Turtle Specialist Group.
Ciampolini R, Cetica V, Ciani E, Mazzanti E, Fosella X, Marroni F, Biagetti
M, Sebastiani C, Papa P, Filippini G, et al. 2006. Statistical analysis of
individual assignment tests among four cattle breeds using fifteen STR loci.
J Anim Sci. 84:11–19.
Evanno G, Regnaut S, Goudet J. 2005. Detecting the number of clusters of
individuals using the software STRUCTURE: a simulation study. Mol Ecol.
14:2611–2620.
Falush D, Stephens M, Pritchard JK. 2003. Inference of population
structure using multilocus genotype data: linked loci and correlated allele
frequencies. Genetics. 164:1567–1587.
Fitzsimmons NN, Moritz C, Limpus CJ, Miller JD, Parmenter CJ, Prince
RI. 1996. Comparative genetic structure of green, loggerhead, and flatback
population in Australia based on variable mtDNA and nDNA regions. In:
Bowen BW, Witzell WN, editors. Proceedings of the International
Symposium on Sea Turtle Conservation Genetics. Springfield (VA):
National Technical Information Service. NOAA Technical Memorandum
NMFS-SEFSC-396. p. 25–32.
FitzSimmons NN, Moritz C, Limpus CJ, Pope L, Prince R. 1997.
Geographic structure of mitochondrial and nuclear gene polymorphisms in
Australian green turtle populations and male-biased gene flow. Genetics.
147:1843–1854.
Fitzsimmons NN, Moritz C, Moore SS. 1995. Conservation and dynamics
of microsatellite loci over 300 million years of marine turtle evolution. Mol
Biol Evol. 12:432–440.
Frankham R, Ballou JD, Briscoe DA. 2002. Introduction to conservation
genetics. Cambridge (UK): Cambridge University Press.
Fraser DJ, Bernatchez L. 2001. Adaptive evolutionary conservation:
towards a unified concept for defining conservation units. Mol Ecol.
10:2741–2752.
Garofalo L, Mingozzi T, Mico A, Novelletto A. 2009. Loggerhead turtle
(Caretta caretta) matrilines in the Mediterranean: further evidence of genetic
diversity and connectivity. Mar Biol. 156:2085–2095.
Goudet J, Raymond M, de Meeüs T. 1996. Testing differentiation in diploid
populations. Genetics. 144:1931–1938.
Crandall KA, Bininda-Emonds ORP, Mace GM, Wayne RK. 2000.
Considering evolutionary processes in conservation biology. Trends Ecol
Evol. 15:290–295.
Groombridge B. 1990. Marine turtles in the Mediterranean: distribution,
population status, conservation. Nat Environ Ser (Council Europe).
48:1–98.
Crawford NG. 2010. SMOGD: software for the measurement of genetic
diversity. Mol Ecol Resour. 10:556–557.
Guo SW, Thompson EA. 1992. Performing the exact test of HardyWeinberg proportions for multiple alleles. Biometrics. 48:361–372.
Delgado C, Canario AVM, Dellinger T. 2010. Sex ratios of loggerhead sea
turtles Caretta caretta during the juvenile pelagic stage. Mar Biol. 157:979–990.
Diez CE, van Dam RP. 2003. Sex ratio of an immature Hawksbill sea turtle
aggregation at Mona Island, Puerto Rico. J Herpetol. 37:533–537.
Hamann M, Godfrey MH, Seminoff JA, Arthur K, Barata PCR, Bjorndal
KA, Bolten A, Broderick AC, Campbell LM, Carreras C, et al. 2010. Global
research priorities for sea turtles: informing management and conservation
in the 21st century. Endanger Species Res. 11:245–269.
Eckert SA, Moore JE, Dunn DC, van Buiten RS, Eckert KL, Halpin PN.
2008. Modelling loggerhead turtle movement in the Mediterranean:
importance of body size and oceanography. Ecol Appl. 18:290–308.
Hawkes LA, Broderick AC, Coyne MS, Godfrey MH, Godley BJ. 2007.
Only some like it hot—quantifying the environmental niche of the
loggerhead sea turtle. Divers Distrib. 13:447–457.
Ehrhart LM, Bagley DA, Redfoot W. 2003. Loggerhead turtles in the
Atlantic ocean: geographic distribution, abundance, and population status.
In: Bolten A, Witherington BE, editors. Loggerhead sea turtles. Washington
(DC): Smithsonian Books. p. 167–174.
Jost L. 2008. G(ST) and its relatives do not measure differentiation. Mol
Ecol. 17:4015–4026.
Ehrhart LM, Ogren H. 1999. Studies in foraging habitats: capturing and
handling turtles. In: Eckert KL, Bjorndal A, Abreu-Grobois A, Donnelly M,
editors. Research and management techniques for the conservation of sea
turtles. Washington (DC): IUCN/SSC Marine Turtle Specialist Group.
p. 70–74.
Ellegren H. 2000. Microsatellite mutations in the germline: implications for
evolutionary inference. Trends Genet. 16:551–558.
Encalada SE, Bjorndal KA, Bolten AB, Zurita JC, Schroeder B, Possardt E,
Sears CJ, Bowen BW. 1998. Population structure of loggerhead turtle (Caretta
caretta) nesting colonies in the Atlantic and Mediterranean as inferred from
mitochondrial DNA control region sequences. Mar Biol. 130:567–575.
Engstrom TN, Meylan PA, Meylan AB. 2002. Origin of juvenile loggerhead
turtles (Caretta caretta) in a tropical developmental habitat in Caribbean
Panama. Anim Conserv. 5:125–133.
Laurent L, Casale P, Bradai MN, Godley BJ, Gerosa G, Broderick AC,
Schroth W, Schierwater B, Levy AM, Freggi D, et al. 1998. Molecular
resolution of marine turtle stock composition in fishery bycatch: a case
study in the Mediterranean. Mol Ecol. 7:1529–1542.
Laurent L, Lescure J, Excoffier L, Bowen BW, Domingo M, Hadjichristophorou
M, Kornaraky L, Trabucht G. 1993. Genetic studies of relationships between
Mediterranean and Atlantic populations of loggerhead turtle Caretta caretta with
a mitochondrial marker. CR Acad Sci Ser III Paris. 316:1233–1239.
Lee PLM. 2008. Molecular ecology of marine turtles: new approaches and
future directions. J Exp Mar Biol Ecol. 356:25–42.
Lohmann KJ, Lohmann CMF. 2003. Orientation mechanisms of hatchling
loggerheads. In: Bolten A, Witherington BE, editors. Loggerhead sea
turtles. Washington (DC): Smithsonian Books. p. 44–62.
Maffucci F, Kooistra W, Bentiveyna F. 2006. Natal origin of loggerhead
turtles, Caretta caretta, in the neritic habitat off the Italian coasts, Central
Mediterranean. Biol Conserv. 127:183–189.
Manni F, Guerard E, Heyer E. 2004. Geographic patterns of (genetic,
morphologic, linguistic) variation: how barriers can be detected by using
Monmonier’s algorithm. Hum Biol. 76:173–190.
Margaritoulis D, Argano R, Baran I, Bentivegna F, Bradai MN, Caminas JA,
Casale P, De Metrio G, Demetropoulos A, Gerosa G, et al. 2003.
Loggerhead turtles in the Mediterranean Sea: present knowledge and
conservation perspectives. In: Bolten A, Witherington BE, editors.
Loggerhead sea turtles. Washington (DC): Smithsonian Books. p. 175–198.
Monmonier M. 1973. Maximum-difference barriers: an alternative
numerical regionalization method. Geogr Anal. 3:245–261.
Monzon-Argüello C, Rico C, Naro-Maciel E, Varo-Cruz N, López P,
Marco A, López-Jurado LF. 2010. Population structure and conservation
implications for the loggerhead sea turtle of the Cape Verde Islands.
Conserv Genet. 11:1871–1884.
Moore MK, Ball RM. 2002. Multiple paternity in loggerhead turtle (Caretta
caretta) nests on Melbourne Beach, Florida: a microsatellite analysis. Mol
Ecol. 11:281–288.
Moran MD. 2003. Arguments for rejecting the sequential Bonferroni in
ecological studies. Oikos. 100:403–405.
Moritz C. 1994. Defining ‘evolutionary significant units’ for conservation.
Trends Ecol Evol. 9:373–375.
Mrosovsky N, Benabib M. 1990. An assessment of two methods of sexing
hatchling sea turtles. Copeia. 1990:589–591.
Narum SR. 2006. Beyond Bonferroni: less conservative analyses for
conservation genetics. Conserv Genet. 7:783–787.
Peakall R, Smouse PE. 2006. GENALEX 6: genetic analysis in Excel.
Population genetic software for teaching and research. Mol Ecol Notes.
6:288–295.
Pella J, Masuda M. 2001. Bayesian methods for analysis of stock mixtures
from genetic characters. Fish B-NOAA. 99:151–167.
Perneger TV. 1998. What’s wrong with Bonferroni adjustments. Br Med J.
316:1236–1238.
fronts, spanning longline fishing grounds in the central North Pacific, 19971998. Fish Oceanogr. 9:71–82.
Pritchard JK, Stephens M, Donnelly P. 2000. Inference of population
structure using multilocus genotype data. Genetics. 155:945–959.
Raymond M, Rousset F. 1995. GENEPOP (version 1.2): population
genetics software for exact tests and ecumenicism. J Hered. 86:248–249.
Revelles M, Caminas JA, Cardona L, Parga M, Tomas J, Aguilar A, Alegre
F, Raga A, Bertolero A, Oliver G. 2008. Tagging reveals limited exchange of
immature loggerhead sea turtles (Caretta caretta) between regions in the
western Mediterranean. Sci Mar. 72:511–518.
Revelles M, Carreras C, Cardona L, Marco A, Bentivegna F, Castillo JJ,
De Martino G, Mons JL, Smith MB, Rico C, et al. 2007. Evidence for an
asymmetrical size exchange of loggerhead sea turtles between the
Mediterranean and the Atlantic through the Straits of Gibraltar. J Exp
Mar Biol Ecol. 349:261–271.
Sheehan TF, Legault CM, King TL, Spidle AP. 2010. Probabilistic-based
genetic assignment model: assignments to subcontinent of origin of the
West Greenland Atlantic salmon harvest. ICES J Mar Sci. 67:537–550.
Tomas J, Gozalbes P, Antonio Raga J, Godley BJ. 2008. Bycatch of
loggerhead sea turtles: insights from 14 years of stranding data. Endanger
Species Res. 5:161–169.
Wallace BP, DiMatteo AD, Hurley BJ, Finkbeiner EM, Bolten AB,
Chaloupka MY, Hutchinson BJ, Abreu-Grobois FA, Amorocho D,
Bjorndal KA, et al. 2010. Regional management units for marine turtles:
a novel framework for prioritizing conservation and research across
multiple
scales.
PLoS One.
5(12):e15465doi:10.1371/journal.pone.0015465
Waples RS, Gaggiotti O. 2006. What is a population? An empirical
evaluation of some genetic methods for identifying the number of gene
pools and their degree of connectivity. Mol Ecol. 15:1419–1439.
Witherington BE, Kubilis P, Brost B, Meylan A. 2009. Decreasing annual
nest counts in a globally important loggerhead sea turtle population. Ecol
Appl. 19:30–54.
Piry S, Alapetite A, Cornuet JM, Paetkau D, Baudouin L, Estoup A. 2004.
GENECLASS2: a software for genetic assignment and first-generation
migrant detection. J Hered. 95:536–539.
Polovina JJ, Kobayashi DR, Parker DM, Seki MP, Balazs GH. 2000. Turtles
on the edge: movement of loggerhead turtles (Caretta caretta) along oceanic
677